50 Clinical Neurogenetics Brent L

50 Clinical Neurogenetics Brent L. Fogel, Daniel H. Geschwind

CHAPTER OUTLINE research has permitted dissection of the cellular machinery supporting the function of the brain and its connections while establishing causal relationships between such dysfunction, GENETICS IN CLINICAL NEUROLOGY human genetic variation, and various neurological diseases. In GENE EXPRESSION, DIVERSITY, AND REGULATION the modern practice of neurology, the use of genetics has DNA to RNA to Protein become widespread, and neurologists are confronted daily with data from an ever-increasing catalog of genetic studies TYPES OF GENETIC VARIATION AND MUTATIONS relating to conditions such as developmental disorders, Rare versus Common Variation dementia, ataxia, neuropathy, and epilepsy, to name but a few. Polymorphisms and Point Mutations The use of genetic information in the clinical evaluation of Structural Chromosomal Abnormalities and Copy neurological disease has expanded dramatically over the past Number Variation (CNV) decade. More efficient techniques for discovering disease genes Repeat Expansion Disorders have led to a greater availability of genetic testing in the clinic. CHROMOSOMAL ANALYSIS AND ABNORMALITIES Approximately one-third of pediatric neurology hospital admissions are related to a genetic diagnosis, and there are DISORDERS OF MENDELIAN INHERITANCE now hundreds of individual genetic tests available to the prac- Autosomal Dominant Disorders ticing neurologist, including several related to common dis- Autosomal Recessive Disorders eases. This number continues to increase rapidly (Fig. 50.1), Sex-Linked (X-Linked) Disorders but is rapidly being supplanted by the clinical availability of exome and genome sequencing, allowing neurologists to MENDELIAN DISEASE GENE IDENTIFICATION BY rapidly survey every gene in human genome for disease- LINKAGE ANALYSIS AND CHROMOSOME MAPPING causing mutations. NON-MENDELIAN PATTERNS OF INHERITANCE As neuroscience and genetic research have progressed, we Mitochondrial Disorders have been led to a deeper understanding of the sources and Imprinting nature of human genetic variation and its relationship to clini- Uniparental Disomy cal phenotypes. In the past there has been a tendency to consider genetic traits as either present or absent, and corre- COMMON NEUROLOGICAL DISORDERS AND COMPLEX spondingly, patients were either healthy or diseased; this is the DISEASE GENETICS traditional view of Mendelian, or single gene, conditions. Common Variants and Genome-Wide Association Although certain relatively rare neurological diseases— Studies Friedreich ataxia or Huntington disease (HD), for example— Rare Variants and Candidate Gene Resequencing can be traced to a single causal gene, the common forms of Copy Number Variation and Comparative Genomic other diseases such as Alzheimer dementia, stroke, epilepsy, Hybridization or autism usually arise from an interplay of multiple genes, each of which increases disease susceptibility and likely inter- GENOME/EXOME SEQUENCING IN CLINICAL PRACTICE acts with environmental factors. Subsequently, the realm of AND DISEASE GENE DISCOVERY the “sporadic” and the “idiopathic” has been challenged by FUTURE ROLE OF SYSTEMS BIOLOGY IN NEUROGENETIC the identification of genetic susceptibility factors, which has DISEASE sparked a flurry of investigation into a variety of genes and genetic markers that confer a risk of illness yet are not wholly ENVIRONMENTAL CONTRIBUTIONS TO NEUROGENETIC causative. Disease status may lie on the end of a continuum DISEASE of individual variation and thus can be considered a quantita- GENETICS AND THE PARADOX OF DISEASE DEFINITION tive rather than purely qualitative trait (Plomin et al., 2009). So, rather than using what might be considered an arbitrary CLINICAL APPROACH TO THE PATIENT WITH cutoff point, such as a specific number of senile plaques or SUSPECTED NEUROGENETIC DISEASE neuritic tangles that define affected or unaffected patients, one Evaluation and Diagnosis might instead think in terms of a continuum of pathology that Genetic Counseling relates to different levels of burden or susceptibility. Prognosis and Treatment As we continue to discover more genes involved either directly or indirectly in neurological disease pathogenesis, the amount of information available to the clinician grows, as do the challenges in interpreting this in a meaningful way for an individual patient. Much of this information, particularly with respect to genetic risk, is not a matter of a positive or negative GENETICS IN CLINICAL NEUROLOGY result, but instead is a feature to be incorporated into the Since the discovery of the structure of deoxyribonucleic acid clinical framework supporting an overall diagnosis. While (DNA) and the elucidation of the genetic mechanisms of modern neurologists need not also be geneticists, it is essential heredity, clinical neurology has benefited from advances in that they possess a firm understanding of the basics of human genetics and neuroscience. This clinically relevant basic genetics in order to be fully prepared to confront the litany of 648

2500 50 2250 2000 1750 1500 1250 1000 750 500 250 0 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 Fig. 50.1 Rapid growth of clinical testing for genetic disease. This graph plots the number of genetic diseases for which clinical testing was available over the period of 1993–2013, illustrating an approximate 20-fold increase in the number of testable disorders. (Data from GeneTests. Available at http://www.genetests.org/.)

diagnostic information available today. This is becoming more contains one or more promoters, DNA sequences that allow for true as the use of clinical exome and genome sequencing the binding of a cellular protein complex that includes RNA becomes increasingly widespread. In this chapter we will polymerase and other factors that faithfully copy the DNA in discuss these essential basics and present examples of how the 5′ to 3′ direction in a process known as transcription. The genetic information has informed our understanding of resulting single-stranded molecule contains a ribose sugar unit disease definition and etiology, show how it is utilized in the in its backbone and thus the resulting molecule is termed practice of neurology today, and how it will be used even more ribonucleic acid, or RNA. RNA also differs from the template extensively in the future. Given the massive acceleration in DNA by the incorporation of uracil (U) in place of thymine technology, from microarrays to the methods enabling com- (T), as it also pairs efficiently with adenine, and thymine serves plete and efficient human genome sequencing, this future is a secondary role in DNA repair that is not necessary in RNA. closer than most realize and the era of genomic medicine is The sequence of the RNA matches the sense DNA strand and fast approaching. is therefore complementary to (and hence derived from) the antisense strand. GENE EXPRESSION, DIVERSITY, Transcribed coding RNA must be processed to become AND REGULATION protein-encoding messenger RNA (mRNA), a term used to differentiate these RNAs from all other types of RNA in the cell. The basic principles of molecular genetics are outlined in Fig. To become mature, RNA is stabilized by modification at the 50.2 and Table 50.1, and more detailed descriptions can be ends with a 7-methylguanosine 5′ cap and a long poly-A 3′ found elsewhere (Alberts et al., 2008; Griffiths et al., 2002; tail. A further critical stage in the maturation of the RNA mol- Lodish et al., 2008; Strachan and Read, 2003). To briefly sum- ecule involves a rearrangement process termed RNA splicing marize, deoxyribonucleic acid (DNA), found in the nucleus of (Fig. 50.3). This is necessary because the expressed coding all cells, comprises the raw material from which heritable sequences in DNA, called exons, of virtually every gene are information is transferred among individuals, with the sim- discontinuous and interspersed with long stretches of gener- plest heritable unit being the gene. DNA is composed of a ally nonconserved intervening sequences referred to as introns. series of individual nucleotides, all of which contain an identi- This, along with other mechanisms, likely plays an evolution- cal pentose (2′-deoxyribose)-phosphate backbone but differ ary role in the development of new genes by allowing for the at an attached base that can be adenine (A), guanine (G), shuffling of functional sequences (Babushok et al., 2007). thymine (T), or cytosine (C). A and G are purine bases and Nascent RNA molecules are recognized by the spliceosome, a pair with the pyrimidine bases T and C, respectively, to form protein complex that removes the introns and rejoins the a double-stranded helical structure which allows for semicon- exons. Not every exon is utilized at all times in every RNA servative bidirectional replication, the means by which DNA derived from a single gene. Exons may be skipped or included is copied in a precise and efficient manner. In total, there are in a regulated manner through alternative splicing, which approximately 3.2 billion base pairs in human DNA. By con- occurs in nearly 95% of all genes to create different isoforms vention, a DNA sequence is described by listing the bases as of that mRNA. The dynamic nature of this observation is criti- they are expressed from the 5′ to 3′ direction along the pentose cal to a complete understanding of cellular gene expression. backbone (e.g., 5′-ATGCAT-3′), as this is the order in which it DNA is essentially a storage molecule, and with few exceptions is typically used by the cellular machinery, also called the sense in the absence of mutagens, its sequence remains static and, strand (compare to RNA, later). The opposite paired, or anti- aside from epigenetic events, is therefore limited to a genetic sense, strand is arranged antiparallel (3′ to 5′) and can also be regulatory role as a transcriptional rheostat. Current estimates referred to when discussing sequence; however, by convention place the number of individual human genes at just over this is generally not done unless that strand is also transcribed 22,000 (Pertea and Salzberg, 2010), so it is difficult to recon- into RNA. cile biological and clinical diversity with simple variations in The expression of a gene is tightly and coordinately regu- expression. Alternative splicing provides a means of dramati- lated (Fig. 50.2), an important consideration for understand- cally elevating this diversity by enabling a single gene to ing the molecular mechanisms of disease. The typical gene encode multiple proteins with a wide array of functions.

Cytoplasm 9 3’ 5’ Protein modification Nucleus X Epigenetic Protein transport modification AUG Met and protein-protein 2 X interactions

X 4 10 TAC RNA processing X 1 and alternative X AUG splicing Translation Chromosome Transcription AAAAAAA 8 Function condensation X 3 AUG X AAAAAAA X RNA 5 transport

AUG AAAAAAA 3’ 5’ 7 ER 6 AAAAAAA

RNA stability AAAAAAA miRNA regulation

Fig. 50.2 Neuronal gene expression and regulation. A generic human neuron is depicted. (1) DNA bound to histones forms transcriptionally inactive chromatin, which can be relieved through the action of various proteins and enzymes. (2) Epigenetic modifications (yellow) are heritable changes to the DNA or its associated histones that alter gene expression without changing the DNA sequence and can result from various environmental stimuli or perturbations. (3) Active DNA is bound by RNA polymerase in a process regulated by protein factors, and the genetic information contained within the DNA is converted to RNA via the process of transcription. An example of a three-nucleotide codon (red) is shown on the antisense DNA strand being converted to its complement on the sense strand of the RNA. (4) Nascent RNA undergoes processing to become messenger RNA (mRNA) with the addition of a 5′ cap structure (green) and a poly-A tail, as well as undergoing RNA splicing which removes noncoding sequences and can generate transcript diversity through the use of alternative exons (see text). (5) Mature mRNA is exported from the nucleus to the cytoplasm and/or to a specific subcellular location. (6) Over time, mRNA is subject to degradation within the cell, and its inherent stability can be dynamic, changing in relation to the state of the cell. (7) Short noncoding RNAs, called micro-RNAs (miRNAs) (pink), can target cellular protein complexes (white) to specific mRNAs and regulate their activity by promoting degradation or blocking translation (see text). (8) The mRNA is bound by ribosomes (either free or associated with the endoplasmic reticulum) and undergoes translation into protein. The three-nucleotide codon (red) directs the incorporation of a single amino acid into the newly synthesized protein (in this example methionine, met). (9) The protein undergoes post-translational chemical modifications (pink) to generate a functional protein for use by the cell. (10) Mature protein interacts with other proteins and/or is transported to its site of activity within the cell. All direct steps in this pathway are potential sites for disease-modifying therapies (red X’s), depending on the gene in question.

Supporting this, recent analysis of RNA complexity in human tissues suggests that there are at least seven alternative splicing DNA to RNA to Protein events per multi-exon gene, generating over 100,000 alterna- The central dogma of genetics has been that DNA is tran- tive splicing events (Pan et al., 2008). Because alternative scribed into RNA that is then translated into protein—the splicing and other forms of RNA processing can be subject to “business” end of the process. So, following its transcription complex layers of temporal and spatial regulation, particularly from DNA in the nucleus, mRNA is transported out of the in the human brain (Licatalosi and Darnell, 2010; Ward and nucleus to the cytoplasm, and possibly to a specific subcellular Cooper, 2010), it is a robust source for both biological diver- location depending on the mRNA, where it can be deciphered sity and disease-causing mutations (see Polymorphisms and by the cell. This takes place via interaction with a complex Point Mutations). known as the ribosome, which binds the mRNA and converts

TABLE 50.1 Glossary of Genetic Terminology 50 Allele Alternate forms of a locus (gene) Lyonization The process of random inactivation of one of the pair of X chromosomes in females Anticipation Earlier onset and/or worsening severity of disease in successive generations Marker Sequence of DNA used to identify a gene or a locus Antisense Nucleic acid sequence complementary to mRNA Megabase 1,000,000 bases or base-pairs Chromosome Organizational unit of the genome consisting of a linear arrangement of genes Meiosis Process of cellular division that produces gametes containing a haploid amount of DNA Cis-acting A regulatory nucleotide sequence present on the molecule being regulated Mendelian Obeying standard single-gene patterns of inheritance (e.g., recessive or dominant) Codon A three-nucleotide sequence representing a single amino acid Microarray A glass or plastic support (e.g., slide or chip) to which large numbers of DNA molecules can be Complex disease Disease exhibiting non-Mendelian inheritance attached for use in high-throughput genetic involving the interaction of multiple genes and analysis the environment Missense DNA mutation that changes a given codon to De novo A mutation newly arising in an individual and not represent a different amino acid present in either parent Mitosis Process of cellular division during which DNA is Diploid A genome having paired genetic information; replicated half-normal number is haploid Nonsense DNA mutation that changes a given codon into a DNA Deoxyribonucleic acid; used for storage, translation termination signal replication, and inheritance of genetic information Penetrance The likelihood of a disease-associated genotype to express a specific disease phenotype Dominant Allele that determines phenotype when a single copy is present in an individual Phenotype The clinical manifestations of a given genotype Endophenotype Subset of phenotypic characteristics used to Polymorphism Sequence variation among individuals, typically not group patients manifesting a given trait considered to be pathogenic Epigenetic Relating to heritable changes in gene expression Probe DNA sequence used for identifying a specific gene resulting from DNA, histone, or other or allele modifications that do not involve changes in Promoter DNA sequences that regulate transcription of a DNA sequence given gene Exome Portion of the genome representing only the Protein Functional cellular macromolecules encoded by a coding regions of genes gene Exon Segment of DNA that is expressed in at least one Recessive Allele that determines phenotype only when two mature mRNA copies are present in an individual Expressivity The range of phenotypes observed with a specific Relative risk The ratio of the chance of disease in individuals disease-associated genotype with a specific genetic susceptibility factor over Frameshift DNA mutation that adds or removes nucleotides, the chance of disease in those without it affecting which are grouped as codons Resequencing A method of identifying clinically relevant genetic Gene Contiguous DNA sequence that codes for a given variation in a candidate gene of interest by messenger RNA and its splice variants comparing the sequence in individuals with disease to a reference sequence Genome A complete set of DNA from a given individual RNA Ribonucleic acid; expressed form of a gene, called Genotype The DNA sequence of a gene messenger or mRNA if protein coding Haplotype A group of alleles on the same chromosome close Sense Nucleic acid sequence corresponding to mRNA enough to be inherited together Silent DNA mutation that changes a given codon but Hemizygous Genes having only a single allele in an individual, does not alter the corresponding amino acid such as the X chromosome in males SNP Single nucleotide polymorphism Heteroplasmy A mixture of multiple mitochondrial genomes in a given individual Splicing RNA processing mechanism where introns are removed and exons joined to create mRNA; in Heterozygous Genes having two distinct alleles in an individual at alternative splicing, exons are utilized in a a given locus regulated manner within a cell or tissue Homozygous Genes having two identical alleles in an individual Trans-acting A regulatory protein that acts on a molecule other at a given locus than that which expressed it Intron Segment of DNA between exons that is Transcription Cellular process where DNA sequence is used as transcribed into RNA but removed by splicing template for RNA synthesis Kilobase 1000 bases or base-pairs Transcriptome The complete set of RNA transcripts produced by Linkage The co-occurrence of two alleles more frequently a cell, tissue, or individual disequilibrium than expected by random chance, suggesting Translation Cellular process where mRNA sequence is they are in close proximity to one another converted to protein Locus Location of a DNA sequence (or a gene) on a chromosome or within the genome

CONSTITUTIVE AND ALTERNATIVE SPLICING

Exonic splicing 5' splice site enhancers and 3' splice site silencers Intron Exon Exon

Intronic splicing Branch site enhancers A and silencers

3' splice site Branch site Spliced product

5' splice site Intron lariat B

Intron retention

Alternative 5' splice sites Cassette exon Alternative promoters

AAAAAAAAAAAAAA

C Alternative 3' splice sites Mutually exclusive exons Alternative polyadenylation sites Fig. 50.3 RNA splicing. A, A generic precursor RNA is shown, consisting of three exons (blue) with intervening introns (dark lines). Representa- tive sequences recognized by the protein complexes that mediate splicing are shown (5′ and 3′ splice sites and the branch site). Binding of these complexes may be influenced either positively or negatively by regulatory sequences and their associated proteins (circles) located in either the introns or exons. Splicing pattern is shown by angled lines spanning introns. B, Splicing occurs via the complex-mediated association of the 5′ splice site and the branch site, with subsequent attack of the 3′ splice site by the upstream exon (arrow), which joins it to the downstream exon and releases the intron. C, Possible alternative splicing patterns for various mRNAs are shown. Constitutive exons are in blue. Alternatively utilized exons are shown in orange or purple. A retained intron is shown by an orange line. its genetic information into protein via the process of transla- gene regulation and neurological disease (Weinberg and tion. The ribosome initiates translation at a pre-encoded start Wood, 2009). Nascent miRNA molecules are processed to site and converts the mRNA sequence into protein until a form short (approximately 22-nucleotide) RNA duplexes that designated termination site is reached. Sequence information target endogenous cellular machinery to specific coding RNAs is read in three-nucleotide groups called codons, each of which and induce post-transcriptional gene silencing through a specifies an individual amino acid. With the four distinct diverse repertoire including RNA cleavage, translational block- bases, there are mathematically 64 possible codons, but these ing, transport to inactive cell sites, or promotion of RNA decay have an element of redundancy and code for only 20 different (Filipowicz et al., 2008; Weinberg and Wood, 2009). Depend- amino acids and 3 termination signals (UAG, UGA, and UAA), ing on the cell and the context, miRNA activity can result in also called stop codons. The start codon is ATG and codes for specific gene inactivation, functional repression, or more methionine. These amino acids are joined by the ribosome to subtle regulatory effects and may involve multiple RNAs in a synthesize a protein. This protein, which may undergo further given biological pathway (Flynt and Lai, 2008). Estimates modification, will ultimately carry out a programmed biologi- suggest that miRNAs may regulate 30% of protein-coding cal function in the cell. Regulation of this process is highly genes, implicating these molecules as important targets for coordinated and important in learning, for example, where future research into the biology of neurological disease (Filip- activity-dependent translation at the synapse underlies some owicz et al., 2008; Weinberg and Wood, 2009). aspects of synaptic plasticity, which may go awry in certain For a specific disease-related gene, the DNA sequence disorders such as fragile X syndrome and autism (Morrow present within an individual is referred to as their genotype, et al., 2008). and the expression of that code often results in a feature (or Over the past decade, the discovery of several classes of features) that can be observed or measured, known as the functional non-protein coding RNAs has added additional phenotype. Genes are further organized into higher-order struc- complexity to our understanding of how the genetic code is tures termed chromosomes, which together compose the entire manifest at the level of cellular function. Of these, microRNAs set of DNA, or genome, of the individual. The human genome (miRNAs) are increasingly being recognized as vital players in is diploid, meaning we possess 23 pairs of chromosomes, 22

Descargado de ClinicalKey.es desde Univ Antioquia septiembre 06, 2016. Para uso personal exclusivamente. No se permiten otros usos sin autorización. Copyright ©2016. Elsevier Inc. Todos los derechos reservados. Clinical Neurogenetics 653 autosomes and 1 sex chromosome. Consequently, normal downstream effects. Mutation of the methyl-CpG-binding individuals possess two copies (or alleles) of every autosomal protein 2 (MECP2), which regulates chromatin structure, 50 gene, one from the mother and one from the father. Because causes the neurodevelopmental disorder Rett syndrome, but there are two distinct sex chromosomes, X and Y, genes on other mutations in this gene can cause intellectual disability these chromosomes are expressed in a slightly different or autism (Gonzales and LaSalle, 2010). Similarly, the RBFOX1 manner, discussed in more detail later for the sex-linked protein (also called ataxin 2 binding protein 1, or A2BP1), a disorders. neuron-specific RNA splicing factor (Underwood et al., 2005) It is important to emphasize that most genes are not simply predicted to regulate a large network of genes important “on” or “off.” In reality, cells maintain strict regulatory control to neurodevelopment (Fogel et al., 2012; Yeo et al., 2009; over their genes. Some genes, such as those required for cell Zhang et al., 2008), causes autistic spectrum disorder when structure or maintenance, must be expressed constitutively, disrupted (Martin et al., 2007) but has also been implicated but genes with specific precise functions may only be needed as a susceptibility gene associated with both primary biliary in certain cells at certain times under certain conditions. cirrhosis (Joshita et al., 2010) and hand osteoarthritis (Zhai Potential levels of regulation are depicted in Fig. 50.2 and et al., 2009), presumably due to downstream effects or specific include virtually every stage of gene expression. Initially, genes effects in non-neural tissues. This concept of genes acting on can be regulated at the level of transcription, ranging from the other genes will be explored further later (see Common Neu- regulated binding of histone proteins, which leads to chromo- rological Disorders and Complex Disease Genetics). some condensation, inactivating genes, to the coordinated In addition to the complexity of regulatory mutations that activity of protein factors that activate or repress gene tran- affect gene expression by altering RNA or protein levels or by scription in response to cell state, environmental conditions, disrupting RNA splicing, there are certain mutations that do or other factors. Once expressed, the RNA is subject to process- not cause protein dysfunction, but instead have effects ing regulation, particularly through alternative splicing as restricted to the RNA itself. For example, RNA inclusions are already discussed. Transport of the mRNA and its translation found in several forms of triplet repeat disorders (see Repeat provide additional steps for cellular regulation. Lastly, the final Expansion Disorders) including myotonic dystrophy type 1 protein can be subject to control via post-translational modi- and the fragile X-associated tremor/ataxia syndrome (FXTAS) fications or interactions with other proteins. To operate, all (Garcia-Arocena and Hagerman, 2010; Orr and Zoghbi, 2007). these levels of regulation require trans-acting factors, such as The latter is particularly interesting from a genetic standpoint, proteins, which stimulate or repress a particular step, as well because a disorder of late-onset progressive ataxia, tremor, as cis-acting elements, sequences recognized and bound by the and cognitive impairment occurs in carriers of FMR1 alleles regulatory factors. of intermediate sizes, which are not full fragile X-causing Epigenetics, or the study of heritable changes in gene expres- mutations (Garcia-Arocena and Hagerman, 2010). FXTAS is sion that do not involve changes in the DNA sequence itself, a dominant gain-of-function disease that occurs via an entirely is emerging as an important aspect of both gene regulation different mechanism than the recessive loss-of-function dis and neurological disease (Qureshi and Mehler, 2013). These ease, fragile X syndrome (Garcia-Arocena and Hagerman, 2010; changes can involve several mechanisms including methyla- Penagarikano et al., 2007). FXTAS pathogenicity appears related tion of the DNA, modification of histone proteins, chromatin to repeat-associated non-AUG-initiated translation of a cryptic remodeling, expression of noncoding RNAs, and RNA editing, polyglycine protein (Todd et al., 2013), an example of a all of which may occur in response to a variety of intracellular rapidly emerging mechanism in several RNA-mediated neuro- or environmental signals (Qureshi and Mehler, 2013). Disrup- degenerative disorders, including DM1 myotonic dystrophy tion of epigenetic mechanisms can cause Mendelian neuro- and C9orf72-mediated amyotrophic lateral sclerosis and fron- logical disease (see Imprinting) as can impairment of the totemporal dementia (Cleary and Ranum, 2013; Mohan et al., function of factors which mediate these epigenetic mecha- 2014). Primary disorders of RNA still represent relatively nisms (Qureshi and Mehler, 2013). Epigenetics may also play uncharted territory, and it is likely that more RNA-specific a role in sporadic disease as a recent study reported the H1 diseases will be identified. This is particularly exciting for haplotype of the MAPT gene to be differentially methylated in many reasons, not the least of which is that certain classes of a dose-dependent manner in patients with progressive supra- these disorders may be amendable to therapy (Nakamori and nuclear palsy (Li et al., 2014), suggesting an epigenetic mecha- Thornton, 2010; Wheeler et al., 2009). nism for the disease risk associated with the presence of that haplotype. Further studies investigating the role of these pathways genome-wide in clinical populations will likely uncover TYPES OF GENETIC VARIATION more associations with disease and disease risk (Qureshi and AND MUTATIONS Mehler, 2013). Rare versus Common Variation These detailed levels of regulation provide a dynamic and expansive capability to precisely control cellular function, As dictated by the principles of natural selection, most genetic essential for growth, development, and survival in an unpre- variation is not deleterious, and the induced phenotypic vari- dictable environment. However, this also provides many ability can be beneficial as a source on which evolution may potential points at which disease can arise from disrupted act. From a clinical standpoint, it is helpful to dichotomize regulation. Consequently, a defective gene could cause disease genetic variation into common and rare variation, while directly through its own action or indirectly by disrupting accepting that genetic variation is likely a continuum, and the regulation of other cellular pathways. For example, the fork- choice of cutoff could be considered arbitrary. Rare genetic head box P2 (FOXP2) transcription factor regulates the expres- variants are of low frequency in the population (<1% fre- sion of genes thought to be important for the development of quency), either because they are deleterious and selected spoken language (Konopka et al., 2009). Mutations in this against or because they are new and most often benign. gene cause an autosomal dominant disorder characterized by Common genetic variation (>1% to 5% population fre- impairment of speech articulation and language processing quency), on the other hand, is adaptive, neutral, or not delete- ( Lai et al., 2001). However, other mutations in this gene are rious enough to be subject to strong negative selection; such responsible for approximately 1% to 2% of sporadic develop- variants are referred to as polymorphisms. The preeminent mental verbal dyspraxia (MacDermot et al., 2005), likely via genetic model has been that common disease susceptibility is

Normal Protein S e r - V a l - I l e - A s p - A r g - S e r - P r o - C y s - L e u - G l n - A l a RNA AGC - GUA - AUC - GAU - CGC - UCU - CCG - UGC - UUG - CAG - GCU DNA TCG - CAT - TAG - CTA - GCG - AGA - GGC - ACG - AAC - GTC - CGA Insertion Point mutation - missense Protein S e r - V a l - I l e - A s p - G l y - S e r - P r o - C y s - L e u - G l n - A l a RNA AGC - GUA - AUC - GAU - GGC - UCU - CCG - UGC - UUG - CAG - GCU Inversion DNA TCG - CAT - TAG - CTA - CCG - AGA - GGC - ACG - AAC - GTC - CGA

Point mutation - nonsense Protein S e r - V a l - I l e - A s p - A r g - S e r - P r o - STOP RNA AGC - GUA - AUc - GAU - CGC - UCU - CCG - UGA - UUG - CAG - GCU Deletion DNA TCG - CAT - TAG - CTA - GCG - AGA - GGC - ACT - AAC - GTC - CGA

Point mutation - silent Protein S e r - V a l - I l e - A s p - A r g - S e r - P r o - C y s - L e u - G l n - A l a Translocation A RNA AGC - GUA - AUC - GAU - CGC - UCG - CCG - UGC - UUG - CAG - GCU DNA TCG - CAT - TAG - CTA - GCG - AGC - GGC - ACG - AAC - GTC - CGA

Frameshift - insertion CAG(N) Protein S e r - V a l - I l e - A s p - A r g - S e r - S e r - V a l - L e u - A l a - G l y RNA AGC - GUA - AUC - GAU - CGC - UCC - UCC - GUG - CUU - GCA - CCC - U DNA TCG - CAT - TAG - CTA - GCG - AGG - AGG - CAC - GAA - CGT - CCG - A

CAG(N + X) Frameshift - deletion Protein S e r - V a l - I l e - A s p - A r g - S e r - A r g - A l a - C y s - A r g - — RNA AGC - GUA - AUC - GAU - CGC - UC-C - CGU - GCU - UGC - AGG - CU C B DNA TCG - CAT - TAG - CTA - GCG - AG-G - GCA - CGA - ACG - TCC - GA Fig. 50.4 Genetic mutations. A, Categories of chromosomal aberrations. Paired homologous chromosomes are shown, with various anomalies indicated. An insertional translocation is depicted; other common types include reciprocal translocations and centric fusions (Robertsonian translocations). B, Types of point mutations. A generic DNA sequence is shown (boxed) along with its corresponding mRNA sequence. Codons are indicated, as are their translation into protein (designed by the standard three-letter code). Mutations are in purple, as are the corresponding alterations in the mRNA and protein if present. Note that silent point mutations do not alter the protein sequence. C, Repeat expansion disorders. An example mRNA is shown with a CAG-codon (polyglutamine) repeat region indicated. In the expanded form, an additional number of repeats are present which may perturb the function of the protein produced and/or lead to cell damage via the expanded polyglutamine region (see text for details).

Descargado de ClinicalKey.es desde Univ Antioquia septiembre 06, 2016. Para uso personal exclusivamente. No se permiten otros usos sin autorización. Copyright ©2016. Elsevier Inc. Todos los derechos reservados. Clinical Neurogenetics 655 of rare variants is not immediately discernable, and without CNVs will be discussed in greater detail when we consider strong statistical or functional evidence, labeling such genetic common and complex disease genetics (see Copy Number 50 variation a mutation is premature and may be misleading. It Variation and Comparative Genomic Hybridization). is likely that most of these, including some variants thought previously to cause rare Mendelian diseases, may simply be Repeat Expansion Disorders benign genetic variation. This is because even a complete knockout of one allele caused by a premature stop codon Most mutations thus far discussed pass from parent to off- (haploinsufficiency) may have no discernable effect on gene spring unaltered, and in large affected families, the identical function for a majority of genes in the human genome (Lupski mutation can potentially be traced back generations. In con- et al., 2010; Ng et al., 2009; Shen et al., 2013; Yngvadottir trast, there is a specific class of mutation, the repeat expansion et al., 2009). In some cases, Mendelian diseases may even (Orr and Zoghbi, 2007) (Table 50.2), which is unstable and require combined mutations in more than one gene (Margo- can present with earlier onset and increasing severity in succes- lin et al., 2013) before a phenotype is observed, further illus- sive generations, a process known as anticipation. There are trating the challenge of predicting pathogenicity. several examples of diseases caused by expanded repeats in Occasionally, silent coding mutations or point mutations coding sequence (e.g., most spinocerebellar ataxias, HD), as in noncoding regions may be significant for disease if they well as examples in noncoding sequence (e.g., fragile X syn- damage sequences important for gene expression (e.g., tran- drome, myotonic dystrophy) and within an intron (e.g., Fried- scriptional and/or RNA processing regulatory elements). It has reich ataxia). Interestingly, virtually all these disorders show been estimated that up to half of all disease-causing mutations neurological symptoms that can include such features as ataxia, impact RNA splicing, which can have dire consequences given intellectual disability, dementia, myotonia, or epilepsy, depend- the importance of splicing to regulated gene expression. Such ing on the disease. The most common repeated sequence seen is the case for frontotemporal dementia with parkinsonism in these diseases is the CAG triplet, which codes for glutamine linked to chromosome 17 (FTDP-17), where in some popula- and expansion of which is seen in a variety of the spinocerebel- tions, the most common mutations disrupt splicing, causing lar ataxias (SCAs) including SCA types 1, 2, 3, 6, 7, 17, and a pathogenic imbalance in tau isoforms (D’Souza and Schel- dentatorubropallidoluysian atrophy (DRPLA). In addition to lenberg, 2005). As for noncoding mutations, given the large protein-specific effects, these disorders likely share a common volume of such sequences in the human genome—perhaps up pathogenesis due to the presence of the polyglutamine repeat to 96%—and our still imprecise ability to predict sequences regions. In some disorders, the phenotype can be quite differ- required for regulation or to interpret identified sequence ent depending on the number of repeats, such as in the FMR1 changes without direct experimentation (Thusberg et al., gene, where more than 200 CCG repeats cause fragile X 2011), the majority of these mutations likely go unrecognized. syndrome, but repeats in the premutation range of 60 to 200, Advances in the next generation of sequencing and bioinfor- from which fully expanded alleles arise, can result in FXTAS matic technologies are beginning to examine larger popula- or premature ovarian failure (Oostra and Willemsen, 2009). tions of patients for both coding and noncoding variants and Although, in general, the underlying mutation is similar, each are expected to expand our understanding of the role of these specific repeat expansion has distinct effects on its correspond- types of mutation in human disease. ing gene, and thus in addition to varying phenotypes, they may also show very different inheritance patterns, as illustrated later Structural Chromosomal Abnormalities and Copy (see Disorders of Mendelian Inheritance). Number Variation (CNV) CHROMOSOMAL ANALYSIS Small deletions and insertions can occur through slippage and AND ABNORMALITIES strand mispairing at regions of short, tandem DNA repeats during replication. If the deletion or insertion is not a multiple The DNA coding for an individual gene is generally too small of three, a frameshift will result, which leads to the translation to be visualized microscopically, but it is possible to observe of an altered protein sequence from the site of the mutation. the chromosomes as they condense during mitosis as part of On a larger scale, errors of chromosomal replication or recom- cell division (Griffiths et al., 2002; Strachan and Read, 2003). bination can result in inversions, translocations, deletions, Traditionally, various staining techniques (e.g., Giemsa) are duplications, or insertions (Stankiewicz and Lupski, 2010). applied, producing a detailed pattern of banding along the When the region of deletion or duplication is greater than 1 kb, chromosomes that are then photographed and aligned for this is referred to as a copy number variation (CNV). Copy comparative analysis. This arrangement and analysis of the number variation is far more common than previously sus- chromosomes is known as a karyotype (Fig. 50.5). Through pected, and it is estimated that at least 4% of the human these methods, it is possible to visually identify large chro genome varies in copy number (Conrad et al., 2010; Redon mosomal deletions, duplications, or rearrangements. If high- et al., 2006), much of which is commonly observed in the resolution banding techniques are employed, structural population and benign (Conrad et al., 2010). However, some alterations on the order of as small as 3 Mb (3 million base rare CNVs such as the recurrent chromosome 17p12 duplica- pairs) can be detected. More sophisticated techniques can also tion underlying most cases of Charcot–Marie–Tooth type 1A be employed, such as fluorescent in situ hybridization (FISH). (Shchelochkov et al., 2010) or the alpha-synuclein triplication In this method, a short DNA sequence, or probe, that corre- that can cause Parkinson disease (PD)(Singleton et al., 2003) sponds to a chromosomal region of interest is hybridized with are pathogenic and act in a Mendelian fashion. Even though the patient’s DNA and detected visually via excitation of a such changes may be extensive, they may not be pathogenic if fluorescent label. FISH can improve on visual resolution by they do not disrupt expression of any key genes. This is particu- 10- to 100-fold and is in common use for detection of a large larly true for balanced translocations where genetic material is number of well-defined genetic syndromes (Speicher and rearranged between chromosomes, yet no significant portion Carter, 2005) such as 15q duplication syndrome, DiGeorge is actually lost. Although an individual with such a condition syndrome (22q11 deletion), and Smith-Magenis syndrome may be normal, if the germline is affected their offspring may (17p11 deletion). receive unbalanced chromosomal material and consequently More recent technological developments involving micro- develop a clinical phenotype (Kovaleva and Shaffer, 2003). array technology (Geschwind, 2003) permit screening of the

TABLE 50.2 Selected Repeat Expansion Disorders Gene Normal Repeat Expanded Disease Locus Symbol Protein name Protein function repeat* location† repeat‡ ALS 9p21.2 C9orf72 C9orf72 protein Unknown ≤23 GGGGCC Promoter ≥700 FTD 5′ UTR DM1 19q13.2-q13.3 DMPK Dystrophia myotonica Ser/Thr protein ≤34 CTG 3′ UTR ≥50 protein kinase kinase DM2 3q13.3-q24 ZNF9 Zinc finger protein 9 Translational ≤26 CCTG Intronic ≥75 regulation DRPLA 12p13.31 ATN1 Atrophin-1 Transcription ≤35 CAG Coding ≥48 FRAXA Xq27.3 FMR1 Fragile-X mental Translational ≤40 CGG 5′ UTR >200 FXTAS§ retardation protein regulation 60–200§ FRDA 9q13 FXN Frataxin Mitochondrial ≤33 GAA Intronic ≥66 metabolism HD 4p16.3 HTT Huntington Unknown ≤26 CAG Coding ≥36 SBMA Xq11-q12 AR Androgen receptor Transcription ≤34 CAG Coding ≥38 SCA1 6p23 ATXN1 Ataxin-1 Transcription ≤38 CAG Coding ≥39 SCA2 12q24 ATXN2 Ataxin-2 RNA processing ≤31 CAG Coding ≥32 SCA3 14q24.3-q31 ATXN3 Ataxin-3 Protein quality ≤44 CAG Coding ≥52 control

SCA6 19p13 CACNA1A CaV2.1 Calcium channel ≤18 CAG Coding ≥20 SCA7 3p21.1-p12 ATXN7 Ataxin-7 Transcription ≤19 CAG Coding ≥36 SCA8¶ 13q21 ATXN8 Ataxin-8 Unknown ≤50 CAG Coding ≥80 ATXN8OS None Unknown ≤50 CTG Noncoding ≥80 SCA10 22q13 ATXN10 Ataxin-10 Unknown ≤29 ATTCT Intronic ≥800 SCA12 5q31-q33 PPP2R2B Protein phosphatase Mitochondrial ≤32 CAG 5′ UTR ≥51 2 regulatory subunit morphogenesis B, beta SCA17 6q27 TBP TATA box-binding Transcription ≤42 CAG Coding ≥49 protein ALS, Amyotrophic lateral sclerosis; DM, myotonic dystrophy; DRPLA, dentatorubral-pallidoluysian atrophy; FRAXA, fragile X syndrome; FRDA, Friedreich ataxia; FTD, Frontotemporal dementia; FXTAS, fragile X-associated tremor/ataxia syndrome; HD, Huntington disease; SBMA, spinal and bulbar muscular atrophy; SCA, spinocerebellar ataxia; UTR, untranslated region. *In some instances, normal/abnormal repeat length is an estimate due to adjacent polymorphic sequences. †Location of repeat region within the expressed mRNA. ‡Does not include alleles with known incomplete penetrance. §Premutation alleles for FRAXA result in the FXTAS phenotype. ¶SCA8 involves bi-directional expression from two overlapping reading frames. entire genome at high resolution (from kilobase to single nevi, and hand and elbow variations, with a very specific cog- nucleotide level) and are rapidly replacing techniques based nitive profile in patients with the full deletion (Strachan and on microscopic analysis. This technology is responsible for the Read, 2003). Individuals with additional copies of the X chro- emerging appreciation for the structural chromosomal varia- mosome are also seen. While both females (47,XXX) and tion in humans mentioned earlier, most of which is submi- males (47,XXY) may have varying degrees of learning disabili- croscopic. For this section, we will focus on chromosomal ties, especially involving language and attention (Geschwind alterations that can be detected microscopically, since the et al., 2000), the males are referred to as having Klinefelter clinical implications of many small or rare structural variants syndrome (KS) due to a phenotype also involving gynecomas- identified are not yet clear (see Copy Number Variation and tia and infertility. XYY males have cognitive profiles similar to Comparative Genomic Hybridization). XXY males but several studies have suggested more severe The most common chromosomal abnormalities encoun- social and behavioral problems in some individuals, espe- tered clinically involve sporadic aneuploidy, either a deletion cially increased aggression, which is rare in KS. Trisomy 21 (47, leaving one chromosome, or a monosomy, or a duplication +21), or Down syndrome, includes profound intellectual leaving three chromosomes, or a trisomy (Strachan and Read, impairment, flat faces with prominent epicanthal folds, and a 2003). This occurs most frequently via nondisjunction, predisposition to cardiac disease. At 1 in approximately 700 whereby chromosomes fail to separate during meiosis in the births, this is the most common genetic cause of intellectual production of the gametes. The majority of aneuploidies are disability and is associated with advanced maternal age at the lethal, although there are a few that are viable and will be time of conception. The other aneuploidies which can survive briefly discussed. Monosomy X (45,XO), also called Turner to term (trisomy 13 [47, +13], Edwards syndrome; trisomy syndrome, is seen in approximately 1 of every 5000 births and 18 [47, +18], Patau syndrome) have much more severe results in sterile females of small stature with a variety of mild phenotypes with drastically decreased viability, and death gen- physical deformities including webbing of the neck, multiple erally occurs within weeks to months after birth.

Fig. 50.5 Abnormal male karyogram. Patient is a male child with a clinical diagnosis of autism. Metaphase chromosomes were isolated from peripheral blood leukocytes and high-resolution GPG banding was performed to visualize structural features. A deletion of the telomeric region of the long arm of chromosome 3 was detected (arrow), consistent with a diagnosis of 3q29 microdeletion syndrome. A normal chromosome 3 pair is shown for comparison (insert). Analysis of the parents showed this to be a de novo deletion. (Photo courtesy F. Quintero-Rivera, UCLA Clinical Cytogenetics Laboratory.)

DISORDERS OF MENDELIAN INHERITANCE Autosomal Dominant Disorders In this section we will consider genetic disorders caused by Diseases involving autosomal genes that require mutation of mutation of a single gene. Associating a clinical disease phe- only one allele are defined as dominant. In most cases, the notype to the mutation of a specific gene has long been the affected individual has two distinct alleles of a gene (in this goal of clinically based, or translational, neuroscience. It is case, one normal and one pathogenic) and is described as expected that gene identification will eventually lead to an being heterozygous. Often these pathogenic mutations impart understanding of the disease etiology as well as more accurate new functionality, referred to as a toxic gain of function, meaning diagnosis and better treatments. The ability to determine the that the phenotype is produced as a result of the expression genetic nature of most single-gene disease is ultimately based of the mutated protein. Other disease mechanisms in domi- upon the laws of inheritance devised by Mendel in the late nantly inherited conditions include: (1) haploinsufficiency, 1800s (Griffiths et al., 2002). To summarize these findings in where inactivation of a single allele is sufficient to produce a clinical context, the assumption is made that a phenotypic disease despite the presence of another normal copy, and trait (or in this example, a disease) is caused by the alteration (2) dominant negative effects, where a mutated protein disrupts of a single gene. It is important to emphasize that this assump- function of the normal protein transcribed from the other tion does not always hold true, particularly for the more nonmutant allele. complex genetic diseases, as we will discuss later, but it is still Autosomal dominant inheritance is characterized by direct true for many diseases seen by neurologists, and more than transmission of the disorder from parent to child (Fig. 50.6). 4000 Mendelian conditions have been identified to date Affected individuals are seen in all generations, and a vertical (OMIM, 2014). Now, if we accept the premise that a given line can be drawn on the pedigree to illustrate the passage of disease is caused by a single gene, we know that for any indi- the disorder. Since only one deleterious copy of the disease vidual, the gene exists as a pair of alleles with one copy from gene is necessary, risk of transmission from an affected parent each parent. However, the alleles may not be equal, and one is 50%. Since the disorder is autosomal, there is no sex prefer- member of the pair may control the phenotype despite the ence, and both males and females can present with the disease. presence of the other copy. In this case, we say that allele is One caveat involves the concept of penetrance, or the percent dominant over the other, the latter of which is labeled as reces- likelihood that a trait will manifest in a person with a specific sive. Depending on the gene and the mutation, as discussed genotype. A dominant gene is considered to have complete later, a disease allele may be either dominant or recessive. penetrance if all individuals with a given mutation develop Next, during the development of the gametes, these alleles disease. In practice, however, many autosomal dominant segregate randomly in a process independent from all other genes show varying degrees of penetrance or expressivity, most genes. Therefore, the chance of a child receiving a particular likely due to the influence of other genes and environmental allele is entirely random. If these laws all hold true, the factors. observed inheritance of the clinical disease in families will There are nearly 500 examples of diseases with neurologi- follow a specific pattern that can be used to identify the nature cal phenotypes that show autosomal dominant inheritance of the causative gene. Although diseases showing Mendelian (OMIM, 2014). These conditions include hyperkalemic peri- inheritance are either rare conditions or rare forms of common odic paralysis (voltage-gated sodium channel NaV1.4 on chro- conditions (e.g., early-onset Alzheimer dementia or PD), iden- mosome 17, often caused by missense mutations), HD tification of such genes is a seminal biological advance that (Huntington on chromosome 4, caused by CAG repeat expan- can have enormous impact on our understanding of these sion), SCA type 3 (ataxin-3 on chromosome 14, caused neurological conditions. by CAG repeat expansion), Charcot–Marie–Tooth type 1B

produced because of the absence of the mutated protein. This I is referred to as a loss of function. 1 2 Autosomal recessive inheritance is characterized by lack of intergenerational transmission, in contrast to dominantly inherited disorders (Fig. 50.7). Affected individuals are seen in single generations, often separated by one or more unaf- II fected generations. Because two deleterious copies of the 1 2 3 4 5 disease gene are necessary, transmission requires both parents to be either affected or carriers. In the most common scenario III when both parents are carriers, the risk of an affected child is 1 2 3 4 5 25% (50% from each parent). As with all autosomal disorders, there is no sex preference, and both males and females can present with the disease. In families showing this mode of IV inheritance, it is important to ask about consanguinity. In rare 1 2 3 4 5 6 7 cases of families with considerable inbreeding, recessive alleles may be so common as to cause disease in successive generations, creating a pseudodominant pattern of inheritance. 3 V As mentioned for the autosomal dominant disorders, dis- 3421 5 6 7–9 eases that share this mode of inheritance may have very distinct types of underlying mutations. Upward of 700 disorders with Fig. 50.6 Autosomal dominant inheritance. A pedigree diagram is autosomal recessive inheritance show neurological symptoms shown, using standard nomenclature. Generations are numbered con- (OMIM, 2014). Examples include Friedreich ataxia (frataxin on secutively on the left, and individuals are numbered within each gen- chromosome 9, caused by intronic GAA repeat expansion), eration. Males are depicted as squares and females as circles. Affected spinal muscular atrophy type 1 (survival of motor neuron 1 on persons are indicated by filled icons. Death is indicated by a diagonal chromosome 5, caused by deletion of exon 7), Wilson disease line. A union producing offspring is indicated by horizontal lines. A (ATPase, Cu++ transporting, beta-polypeptide on chromosome diamond represents individuals (n) of unknown sex. A triangle repre- 13, often caused by missense mutations), Tay-Sachs disease sents a spontaneous abortion. Individuals V-2 and V-3 illustrate the (hexosaminidase A on chromosome 15, commonly caused by diagramming of dizygotic twins. The proband of the pedigree is indi- frameshift, splicing, or nonsense mutations), glycogen storage cated by an arrow. An autosomal dominant pedigree demonstrates type II or Pompe disease (acid alpha-glucosidase gene on chro- vertical transmission of disease without a sex preference. On average, mosome 17, often caused by point mutations, splicing muta- 50% of offspring are affected. Individual III-4 represents a case of tions, and exon deletions), phenylketonuria (phenylalanine incomplete penetrance (dark circle) where the individual carries hydroxylase on chromosome 12, often caused by missense the mutation but does not manifest disease. Anticipation (see text) mutations), and ataxia-telangiectasia (ataxia-telangiectasia would be illustrated by increasing severity/onset in patients III-1, IV-2, mutated on chromosome 11, often caused by point mutations and V-4. and splicing mutations). More detailed lists can be found using the recommended online resources (see Table 50.3). It is important to note that there are examples of genes (myelin protein zero on chromosome 1, often caused by mis- which can exhibit both dominant and recessive phenotypes, sense mutations), early-onset familial Alzheimer disease depending on the type/location of the mutation in question. (AD)(presenilin-1, often caused by missense mutations), For example, heterozygous inframe deletions and missense frontotemporal dementia with parkinsonism (microtubule- mutations in the SPTBN2 gene cause an adult-onset pure cer- associated protein tau on chromosome 17, often caused by ebellar ataxia termed spinocerebellar ataxia type 5 (SCA5), missense or splicing mutations), tuberous sclerosis type 1 while homozygous truncating mutations cause a more severe (hamartin on chromosome 9, often caused by nonsense muta- infantile-onset disorder of ataxia and cognition (Cho and tions and frameshifts), neurofibromatosis type 1 (neurofibro- Fogel, 2013; Elsayed et al., 2014; Lise et al., 2012). This adds min on chromosome 17, caused by point mutations, frameshifts, another layer of complexity to the study of phenotypic expres- and splicing mutations), and familial amyotrophic lateral scle- sivity caused by mutations within specific genes, and likely rosis (ALS) (superoxide dismutase-1 on chromosome 21, caused more examples will be detected as clinical exome and genome by missense mutations), to name a few. Even rare Mendelian sequencing are used more broadly in varying clinical forms of more common syndromes such as epilepsy or sleep populations. disorders (e.g., familial advanced sleep-phase syndrome) have been identified. More detailed lists can be found using the Sex-Linked (X-Linked) Disorders recommended online resources (Table 50.3). The sex chromosomes in humans are referred to as the X and Autosomal Recessive Disorders Y chromosomes, the latter of which programs the individual to be male. There are as yet no known Y-linked diseases, so Disease involving autosomal genes that require mutation of we will focus on the X chromosome. As males only possess a both alleles is defined as recessive. An unaffected individual single X chromosome, they are hemizygous for all its genes, and who harbors one disease-causing allele is referred to as a consequently any pathogenic mutation is expressed by default. carrier of that allele. For some disorders, a mild phenotype can Because of this, dominance of X-linked genes applies with be seen in these individuals, who are then described as symp- respect to whether female carriers express disease. This is com- tomatic carriers. An individual with two identical alleles (in plicated by the observation that although females possess two this case both pathogenic) is described as being homozygous. X chromosomes, no single cell expresses genes from both; Alternatively, if they possess two different pathogenic alleles, instead, one chromosome is randomly and permanently inac- this is described as being compound heterozygous. In general, tivated during development via a process known as lyonization. autosomal recessive mutations modify the function of the Therefore, all women inherently possess cells of two different protein in a negative way, meaning that the phenotype is genotypes, or are mosaic, for the X chromosome. This can be

TABLE 50.3 Selected Online Clinical Neurogenetics Resources 50 Disease-specific and GeneCards: The Human Gene Compendium Genomic variation Catalog of Published Genome-Wide Association gene-specific Crown Human Genome Center, Department of and other genome Studies resources Molecular Genetics, The Weizmann Institute resources US National Human Genome Research Institute of Science, Rehovot, Israel http://www.genome.gov/gwastudies/ http://www.genecards.org ClinVar Database GeneReviews US National Center for Biotechnology University of Washington, Seattle, WA, USA Information US National Center for Biotechnology https://www.ncbi.nlm.nih.gov/clinvar/ Information http://www.ncbi.nlm.nih.gov/books/NBK1116/ Database of Genomic Variants The Centre for Applied Genomics, Canada GeneTests http://dgv.tcag.ca/dgv/app/home Bio-Reference Laboratories, Inc., Elmwood Park, NJ, USA Ensembl Databases http://www.genetests.org/ European Molecular Biology Laboratory— European Bioinformatics Institute The Genetic Testing Registry Wellcome Trust Sanger Institute, UK US National Center for Biotechnology http://www.ensembl.org/ Information http://www.ncbi.nlm.nih.gov/gtr/ Exome Variant Server National Heart Lung and Blood Institute Grand Locus Specific Mutation Databases Opportunity Exome Sequencing Project Human Genome Variation Society, Australia http://evs.gs.washington.edu/EVS/ http://www.hgvs.org/dblist/glsdb.html International HapMap Project Neuromuscular Disease Center http://hapmap.ncbi.nlm.nih.gov/index.html Washington University, St. Louis, MO, USA http://neuromuscular.wustl.edu/ National Center for Biotechnology Information Databases Online Mendelian Inheritance in Man US National Center for Biotechnology Johns Hopkins University, Baltimore, MD, USA Information http://omim.org/ http://www.ncbi.nlm.nih.gov/ Clinical genetic ClinicalTrials.gov Single Nucleotide Polymorphism Database testing and clinical US National Institutes of Health US National Center for Biotechnology trials http://clinicaltrials.gov/ Information GeneTests http://www.ncbi.nlm.nih.gov/projects/SNP/ Bio-Reference Laboratories, Inc., Elmwood 1000 Genomes Project Park, NJ, USA http://www.1000genomes.org/ http://www.genetests.org/ University of California, Santa Cruz (UCSC) The Genetic Testing Registry Genome Bioinformatics US National Center for Biotechnology University of California, Santa Cruz, Santa Cruz, Information CA, USA http://www.ncbi.nlm.nih.gov/gtr/ http://genome.ucsc.edu/

clinically relevant insofar as disproportionate activation of an dystrophy (dystrophin, commonly caused by deletions), abnormal X chromosome could potentially lead to clinical Emery–Dreifuss muscular dystrophy-1 (emerin, often caused phenotypes in female carriers of recessive X-linked disorders. by nonsense mutations), Menkes disease (ATPase, Cu++-trans- Usually though, skewing occurs, so that the pathogenic allele porting, alpha-polypeptide, commonly caused by frameshifts, is less expressed than the other normal allele. nonsense mutations, and splicing mutations), Fabry disease Recessive X-linked transmission is characterized by the (alpha-galactosidase A, commonly caused by point mutations, presence of disease in males only (Fig. 50.8). Affected males gene rearrangements, and splicing mutations), and Pelizaeus- cannot pass the disease on to their sons, but all their daughters Merzbacher disease (proteolipid protein-1, often caused by must inherent the abnormal X chromosome and are, there- duplications and missense mutations). X-linked dominant dis- fore, obligate carriers. A carrier female has a 50% chance of orders include Rett syndrome (methyl-CpG-binding protein-2, passing the disease allele to a child, but all males receiving it often due to missense and nonsense mutations), inconti will be affected. Dominant X-linked transmission (see Fig. nentia pigmenti (inhibitor of kappa light polypeptide gene 50.8) is similar, except carrier females are affected and trans- enhancer in B cells, kinase gamma [IKBKG], often due to dele- mit the disease to 50% of their children irrespective of their tions), and Aicardi syndrome (gene unknown). More detailed sex. Affected males usually show a more severe phenotype, or lists can be found using the recommended online resources may even exhibit lethality, and transmit the disease to all of (see Table 50.3). their daughters and none of their sons. Over 100 X-linked disorders with neurological phenotypes are known (OMIM, 2014). The majority of these X-linked MENDELIAN DISEASE GENE disorders are recessive, and as seen for the autosomal diseases, IDENTIFICATION BY LINKAGE ANALYSIS mutation type varies widely among the different disorders. AND CHROMOSOME MAPPING Some examples include X-linked adrenoleukodystrophy (ATP- binding cassette subfamily D member 1, commonly caused by As mentioned previously, patterns of inheritance can be uti- missense and frameshift mutations), Duchenne muscular lized to locate genes responsible for disease. Traditionally,

X-LINKED RECESSIVE X-LINKED DOMINANT

I I 1 2 1 2

II II 1 2 3 4 1 2 3 4

III III 1 2 3 4 1 2

IV IV 1 2 3 1 2 3

V V A 1 2 3 4 5 B 1 2 3 4 5

Fig. 50.8 X-linked inheritance. A, X-linked recessive disease. A pedigree diagram is shown using standard nomenclature as described in Fig. 50.6. Carriers of disease are indicated by half-filled icons. Disease manifests only in hemizygous males. Fathers cannot pass the disease to their sons, but all daughters of an affected male are obligate carriers of disease. Carrier females have a 50% chance to pass on the disease gene and can have affected sons. In some cases, a female carrier can be mildly symptomatic, usually due to nonrandom lyonization. B, X-linked dominant disease. A pedigree diagram is shown using standard nomenclature as described in Fig. 50.6. Disease manifests in heterozygous females (although severity may be affected by lyonization). The mutant gene is either lethal in males (as shown here) or has a much more severe phenotype. Affected females pass on the disease 50% of the time.

1 1 50 2 2 I 3 3 4 4 1 2 5 5 1 6 X 6 7 7 2 8 8 3 9 9 II 10 10 4 1 2 3 4 5 6 1 III 7 2 8 3 1 2 3 4 5 9 4 I 10 5 6 IV 1 2 7 1 2 3 4 5 8 9 10 V 1 2 3 4 5 II Fig. 50.10 Mitochondrial (maternal) inheritance. A pedigree 1 2 3 diagram is shown using standard nomenclature as described in Fig. 50.6. As the mutant gene is carried in the mitochondrial genome, 1 disease is passed on to all the offspring of affected females (see text). 2 Males can be affected but cannot pass on disease. Severity and onset 3 of the disease may be affected by heteroplasmy, the proportion of 4 III abnormal mitochondria per cell, as illustrated by a severe phenotype 5 seen in patient IV-1. 1 1 2 6 2 7 3 8 4 9 is not all inclusive. Other examples exist, such as developmen- 5 10 tal events that can potentially lead to disease or syndromic 6 conditions through formation of a mosaic, an individual with 7 cells of different genotypes derived from a common cell, or a IV 8 chimera, an individual who contains cells of different distinct 9 genotypes (e.g., from separate fertilizations). Such rare events 10 1 2 will not be discussed further. Additionally, the non-Mendelian heritability of diseases that are polygenic, or involve multiple genes, and other forms of complex disorders will be discussed Fig. 50.9 Linkage analysis. A pedigree is depicted as in Fig. 50.6, in later sections. showing autosomal dominant inheritance of disease (filled icons). Transmission of the chromosome containing the mutant gene (purple line) is illustrated for all affected individuals. Numbers represent the Mitochondrial Disorders location of specific chromosomal markers (e.g., single nucleotide poly- Mitochondria are double-membraned organelles responsible morphisms or other sequences). Purple numbers represent markers for energy production within the cell via the process of oxida- originally from the mutant chromosome in individual I-1. With each tive phosphorylation, which relies on the transfer of electrons mating, there is potential crossing over between regions of homolo- through a chain of protein complexes within the inner mito- gous chromosomes (inset), likely resulting in the separation of markers chondrial membrane. Disruption of mitochondrial function spaced far apart along the chromosome. In this example, examination can lead to a variety of diseases with multisystem involve- of all affected individuals shows the disease segregates with marker ment, including prominent neurological symptoms (DiMauro 3, and the two are therefore in linkage disequilibrium, suggesting they and Hirano, 2009; Zeviani and Carelli, 2007). Mitochondria are near one another. Once identified, the marker location can be used possess their own genome with 37 genes. Because mitochon- to select candidate genes for sequencing to identify the causative gene dria are cytoplasmic and the majority of cytoplasm within the and mutation in the family. zygote is derived from the egg and not the sperm, disorders involving mitochondrial DNA are inherited through the NON-MENDELIAN PATTERNS OF INHERITANCE maternal line (Fig. 50.10). A single cell contains many mitochondria which all replicate independently of the nuclear In rare instances, pedigree analysis of affected families has DNA, so it is possible that a mutation in the mitochondrial revealed patterns of inheritance that do not conform to the genome may be present in some of the mitochondria but not classic Mendelian patterns thus far described and, therefore, others, a condition termed heteroplasmy. This proportion can must result from other mechanisms. In this section, we will affect whether a disease is expressed and, if so, what tissues discuss the more common and clinically relevant ways in are affected if a minimum threshold of abnormal mitochon- which single-gene disorders can be transmitted in a non- dria is reached. Heteroplasmy may also change over time as Mendelian fashion: mitochondrial inheritance, imprinting, cells divide and the mitochondria are redistributed. Some and uniparental disomy. It is important to recognize that this examples of such disorders include MELAS (mitochondrial

Descargado de ClinicalKey.es desde Univ Antioquia septiembre 06, 2016. Para uso personal exclusivamente. No se permiten otros usos sin autorización. Copyright ©2016. Elsevier Inc. Todos los derechos reservados. 662 PART II Neurological Investigations and Related Clinical Neurosciences encephalomyopathy, lactic acidosis, and stroke-like episodes, IMPRINTING caused by point mutations within the gene encoding mitochondrial tRNALEU), MERRF (myoclonic epilepsy with ragged Maternal chromosome 15q11-q13 red fibers, caused by point mutations within the gene- Me X encoding mitochondrial tRNALYS), and LHON (Leber heredi- Prader-Willi locus Angelman locus tary optic neuropathy, most often caused by point mutations -- in either of two mitochondrial genes encoding complex I subunits, ND4 or ND6). A Paternal chromosome 15q11-q13 Because the mitochondria themselves contain only a few genes, the majority of mitochondrial proteins, including the machinery responsible for the replication and repair of the UNIPARENTAL DISOMY mitochondrial genome, are all encoded by nuclear genes. Paternal Maternal Since these genes are located within the nuclear genome, despite the fact that their mutation gives rise to dysfunctional NORMAL mitochondria, the disease will show a Mendelian pattern of inheritance. Some examples include infantile-onset SCA (twinkle on chromosome 10, autosomal recessive, caused by Me missense mutations), progressive external ophthalmoplegia Chromosome A2 (adenine nucleotide translocator 1 on chromosome 4, 15q11-q13 autosomal dominant, caused by missense mutations), and Charcot–Marie–Tooth type 2A2 (mitofusin-2 on chromosome 1, autosomal dominant, often caused by missense mutations). Interestingly, various mutations, commonly missense, of the Paternal Maternal nuclear gene DNA polymerase gamma (POLG) on chromo- only only some 15, which encodes the polymerase responsible for both replication and repair of the mitochondrial genome, cause a Angelman Prader-Willi wide variety of diverse phenotypes with different modes of syndrome syndrome inheritance (Hudson and Chinnery, 2006). These include the autosomal recessive Alpers syndrome of encephalopathy, sei- Me zures, and liver failure, an autosomal dominant form of Chromosome Chromosome Me chronic progressive external ophthalmoplegia, and autosomal 15q11-q13 15q11-q13 recessive phenotypes of cerebellar ataxia and peripheral neuropathy, among others. B Fig. 50.11 Epigenetics in human disease. A, Imprinting. Gene Imprinting expression on human chromosome 15q11-q13 is subject to epige- For most genes, expression is controlled by distinct cellular netic regulation via imprinting. The region contains the loci for two processes that operate irrespective of the gene’s parental origin. neurological diseases, Prader–Willi syndrome and Angelman syn- However, for some genes, expression in the offspring differs, drome (see text). When inherited from the father, gene expression depending on whether the allele was maternally or paternally occurs from the Prader–Willi locus (blue arrow), and this also inacti- inherited, and such genes are described as being imprinted vates genes at the Angelman locus via a presumed antisense-RNA (Spencer, 2009). Imprinting arises from epigenetic modifica- mechanism (dashed arrow). In contrast, when inherited from the tions such as DNA or histone methylation, which are parent- mother, a specific site on the chromosome called the imprinting center specific alterations that do not change the actual DNA sequence (circle) becomes methylated (Me). This methylation causes transcrip- (Fig. 50.11). One example of this is sex-specific DNA methyla- tional inactivation of the genes within the Prader–Willi locus (X), which tion that occurs for some genes during the formation of correspondingly allows transcription from genes at the Angelman locus gametes. In the offspring, the methylated gene is bound by (purple arrow). If imprinting does not properly occur, either Angelman histone proteins forming transcriptionally inactive hetero- or Prader–Willi syndrome will arise depending on whether the maternal chromatin. This allows all gene expression to be driven by the or paternal expression pattern is absent. B, Uniparental disomy. During allele derived from the other parent. This can be dynamic gamete/zygote formation, errors in chromosomal segregation or chro- depending on the gene, and the magnitude of differential mosomal rearrangement can result in retention of all or part of a expression between the alleles can vary based on stage of chromosome inherited from the same parent. Although there is no loss development, tissue type, and possibly other factors. Deletion of genetic information, the epigenetic imprinting pattern is lost, and of an imprinted region or defective imprinting in gametogen- therefore correct gene expression patterns are not retained. For chro- esis can lead to disease as illustrated by observations involving mosome 15q11-q13, for example, this can give rise to Angelman or chromosome 15q (Lalande and Calciano, 2007). In this Prader–Willi syndrome depending on whether the duplicated chromo- example, differential methylation affects the expression of some is that of the father or the mother, respectively. multiple genes, and loss of maternal patterning can lead to Angelman syndrome, characterized by intellectual impairment, epilepsy, ataxia, and inappropriate laughter, while loss small deletions involving sequences important for regulating of the paternal pattern causes Prader–Willi syndrome, associ- parent-specific methylation. ated with intellectual impairment, obesity, and behavioral problems. The most common mechanism involves de novo Uniparental Disomy deletion of the imprinted region from one parent, although in some cases, defective imprinting can also occur during Uniparental disomy arises when pairs of chromosomes are gametogenesis. In the majority of cases, defective imprinting inherited from the same parent, either in their entirety or in occurs spontaneously and is therefore unlikely to recur in large segments due to segregation errors or chromosomal rear- families; however, imprinting defects can rarely be due to rangement (Kotzot, 2008) (see Fig. 50.11). The uniparentally

Descargado de ClinicalKey.es desde Univ Antioquia septiembre 06, 2016. Para uso personal exclusivamente. No se permiten otros usos sin autorización. Copyright ©2016. Elsevier Inc. Todos los derechos reservados. Clinical Neurogenetics 663 inherited chromosomes can be identical (isodisomic) or dif- involving interplay between multiple genes, each with small ferent (heterodisomic). In families where the parents lack effect size, and environmental factors, none of which are suf- 50 underlying chromosomal abnormalities, these events usually ficient to be causal, but each of which increases susceptibility occur spontaneously and are unlikely to recur. Disease can to the disorder. This is the basis of the “common disease– result from effects related to loss of chromosomal imprinting, common variant” (CDCV) model, which has driven most pairing of an autosomal recessive mutation, pairing of an research into common genetic diseases (Schork et al., 2009). X-linked recessive mutation in a female child, or from the The alternative model is that rather than common SNPs, mul- generation of a mosaic trisomy. The disorders most commonly tiple inherited rare variants of small to intermediate effect size associated with this mechanism are the Prader–Willi and or de novo mutations with large effect size underlie genetic Angelman syndromes, discussed previously for imprinting dis- risk for common disorders. The difficulty with assessing this orders, which can arise from maternal and paternal uniparen- latter proposition is that until the very recent advent of effi- tal disomy, respectively, due to a loss of the imprinting pattern cient genome or exome sequencing, genome-wide identifica- from the missing parental allele. Down syndrome can also tion of such rare variants was not feasible. In contrast, efficient rarely result from a mosaic trisomy. There are several examples genome-wide assessment of common variation has been pos- in the literature of single cases where an autosomal recessive sible for several years and has been applied to numerous disease arose in a child from uniparental disomy pairing an neurological disorders (for examples see eTable 50.5, available abnormal allele from a carrier parent, including disorders such online). Still, the true nature of the type of genetic variation as abetalipoproteinemia, Bloom syndrome, autosomal reces- underlying most complex disease is not known, but major sive deafness-1A, spinal muscular atrophy, cystic fibrosis, and advances are being made. Here we discuss the strategies cur- others (Zlotogora, 2004). rently being used, starting with genome-wide screening for common variation. COMMON NEUROLOGICAL DISORDERS AND COMPLEX DISEASE GENETICS Common Variants and Genome-Wide Association Studies To this point, we have focused on Mendelian neurological disease, in which mutations of a single gene are sufficient to As already discussed, genetic linkage provides a means of cause disease. Neurological diseases with Mendelian inherit- localizing a disease gene to a specific region of a chromosome ance are rare in most populations, and account for less than by using a DNA marker that tracks with affected individuals 5% of those with common conditions such as Alzheimer within families. Linkage analysis, while not without value in dementia. Yet, many of the common neurological diseases genetically complex disease, is less powered than genetic asso- seen worldwide have significant genetic contributions (Table ciation studies for identification of common variation in 50.4). For example, twin studies have shown high heritability complex genetic disease. Genetic association studies assess (≥60%) for Alzheimer dementia (Gatz et al., 2006) and autism whether one or more of a defined set of genetic variants are (Abrahams and Geschwind, 2008; Freitag, 2007), increased increased or decreased in a disease versus a control popula- relative risk is seen in first-degree relatives of probands with tion. If a genetic variant is observed in individuals with disease ALS (approximately 10-fold) (Fang et al., 2009) and epilepsy significantly more often or less than expected by chance, that (about 2.5-fold) (Helbig et al., 2008), and a variety of studies variant is said to be associated with the disease. When one or support a degree of heritability in PD (Belin and Westerlund, a few genes are studied, this is a candidate gene association 2008) and cerebrovascular disease (Matarin et al., 2010). But study. When common variants from across the entire genome even when family history is present, the mode of inheritance are studied in this manner, the result is a genome-wide asso- is not clear, and no major disease-causing Mendelian muta- ciation study, or GWAS (Mullen et al., 2009; Simon-Sanchez tions are usually identified in the majority of cases. So in and Singleton, 2008) (Fig. 50.12). Original genetic associa- contrast to the single-gene Mendelian disorders previously tion studies were conducted with a small number of candi- discussed, these common complex genetic conditions appear date genes, but advances in technology have permitted GWAS to be genetically heterogeneous and multifactorial, likely in thousands of subjects in a wide variety of human diseases,

TABLE 50.4 Estimated Heritability of Selected Neurological Diseases Disease Heritability* Method Reference Alzheimer dementia 60%–80% Twin studies (Gatz et al., 2006) Amyotrophic lateral sclerosis 9.7 RR† Familial aggregation data (Fang et al., 2009) Autism 70%–90% Twin studies (Abrahams and Geschwind, 2008) Epilepsy 80%‡ Twin study (Kjeldsen et al., 2003) Frontotemporal dementia 42%§ Family history data (Rohrer et al., 2009) Ischemic stroke 1.75 RR Family history data (Flossmann et al., 2004) Multiple sclerosis 25%–76% Twin studies (Hawkes and Macgregor, 2009) Parkinson disease 6 RR (onset ≤ 50 years) Twin study (Vaughan et al., 2001) Restless legs syndrome 40%–90% Twin studies (Caylak, 2009) RR, Relative risk among family members. *Unless otherwise indicated, percent heritability refers to the proportion of variation attributable to genetic causes. †Among first degree relatives. ‡Varies per syndrome. §Estimation based on likelihood of having an affected family member.

Descargado de ClinicalKey.es desde Univ Antioquia septiembre 06, 2016. Para uso personal exclusivamente. No se permiten otros usos sin autorización. Copyright ©2016. Elsevier Inc. Todos los derechos reservados. Clinical Neurogenetics 663.e1 ¶ 95% CI [2.41–2.66] [2.37–2.71] [0.79–0.89] [0.80–0.90] [1.14–1.29] [0.81–0.90] [NR] [NR] [NR] [NR] [0.77–0.89] [0.53–0.71] [1.27–1.57] [NR] [NR] [2.46–3.07] [0.72–0.85] [1.10–1.31] [0.68–0.88] [0.72–0.89] [1.07–1.30] [1.84–2.15] ¶ 2.53 2.53 0.84 0.85 1.21 0.86 1.25 1.22 0.55 1.19 0.83 0.61 1.4 2.78 0.81 2.75 0.78 1.20 0.77 0.80 1.18 1.99 Odds ratio § Continued on following page 0.14 0.15 0.40 0.37 0.19 0.38 0.34 0.23 0.04 0.38 0.37 0.44 0.83 0.16 0.33 0.22 0.41 0.45 0.12 0.19 0.25 0.23 Minor allele frequency ‡ Closest gene(s) APOE APOE TOMM40 CLU PICALM CR1 CLU UNC13A MOBKL2B SEMA5A CDH10 CDH9 AL132875.2 TMEM106B CBLB HLA-DRB1 METTL1 CYP27B1 HLA-DRB1 HLA-B TNFRSF1A CD58 IRF8 CD6 HLA-DRA − 10 − 9 − 9 − 9 − 14 − 9 − 7 # − 10 − 7 # − 11 − 10 − 11 − 17 − 11 − 10 − 9 − 9 − 81 − 295 − 157 − 184 − 225 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

× × × × × × × × × × × × × × × × × × × × × ×

P value 1.00 1.80 8.50 1.30 3.50 7.50 2.50 7.45 2.10 2.10 3.34 1.08 1.60 7.00 5.40 3.80 1.00 1.59 3.10 3.73 3.79 8.94 † Associated SNP rs2075650 rs6656401 rs12608932 rs4307059 rs1990622 rs3135388 rs2075650 rs10513025 rs346291 rs9657904 rs3135388 rs9271366 rs11136000 rs3851179 rs11136000 rs2814707 rs703842 rs2523393 rs1800693 rs2300747 rs17445836 rs17824933 Locus 19q13.32 1q32.2 19p13.11 5p14.1 7p21.3 6p21.32 19q13.32 5p15.2 6q14.1 3q13.11 6p21.32 6p21.32 8p21.1 11q14.2 8p21.1 9p21.2 12q14.1 6p22.1 12p13.31 1p13.1 16q24.1 11q12.2 million million million

Total SNPs * 529,000 537,000 293,000 474,000 500,000 335,000 2.5 365,000 529,000 6.6 2.6 302,000

and Illumina and Illumina Genotyping platform Illumina Illumina Illumina Illumina Illumina Affymetrix Affymetrix Affymetrix Affymetrix Illumina Affymetrix Illumina Disease

trios

447 trios,

# members of families, Neurological

Replication cohort cases/ controls 6505/13,532 2023/2340 3978/3297 2532/5940 1755 1390 108/540 NR 89/553 1775/2005 2215/2116 609 2322/2987 2256/2310 of

2431

Studies

affected members

1031 780 trios,

of families of families, controls Discovery cohort cases/ controls 1553 3101 1204/6491 931 3006/14,642 3941/7848 2032/5328 2323/9013 3445/6935 515/2509 882/872 2624/7220 1618/3413 Association

PubMed ID 20460622 19734902 19734903 19734901 19812673 19404256 20522523 19812673 20453840 19525953 17660530 19525955 CLEROSIS Genome-Wide

al. al. EMENTIA

al.

al. al. et al. ) D et

al.

al. al.

ATERAL et et et

et et

Selected

al. al. EMENTIA Deerlin Es

Jager

CLEROSIS

et et D PARTIAL S ( Study Seshadri Harold Lambert van Weiss Wang Kasperaviciute Van Sanna De Hafler ANZgene ULTIPLE LZHEIMER MYOTROPHIC UTISM PILEPSY RONTOTEMPORAL eTABLE 50.5 Year A 2010 2009 2009 2010 2010 2010 2009 2009 A A 2009 E F M 2009 2009 2007

¶ recent

cohorts

95% CI [1.52–1.88] [1.27–1.48] [1.21–1.39] [1.16–1.34] [NR] [NR] [1.31–1.59] [1.50–2.10] [1.57–1.92] [1.49–1.89] [1.36–1.66] [1.19–1.41] more

¶ of

1.69 1.37 1.30 1.24 1.23 0.77 1.44 1.8 1.74 1.67 1.5 1.29 Odds ratio replication

authors

§ without

some

0.14 0.42 0.48 0.36 0.51 0.18 0.12 0.66 0.24 0.24 0.33 0.19 that

Minor allele frequency Studies

Note

author. ‡

first

commas.

TRA-alpha TRAJ10 SNCA PARK16 Closest gene(s) BST1 SNCA MAPT PTPRD BTBD9 MEIS1 BTBD9 MAP2K5 NINJ2 and by

− 13 − 17 − 12 − 9 − 16 − 16 − 10 − 12 − 28 − 18 − 15 − 09 association.

10 10 10 10 10 10 10 10 10 10 10 10

of × × × × × × × × × × × ×

separated

publication

of lack

are

P value 1.90 7.35 1.52 3.94 2.24 1.95 5.91 2.00 3.41 3.99 1.06 1.10

any year

cohorts

confirm †

listed

are Associated SNP rs1154155 rs11931074 rs2736990 rs4626664 rs3923809 rs2300478 rs12425791 rs947211 rs4538475 rs393152 rs9296249 rs12593813

replication

and

Studies

publications

Locus 14q11.2 4q22 4q22.1 9p23 6p21.2 2p14 12p13.33 1q32 4p15 17q21.31 6p21.2 15q23 listed.

discovery

is original listed.

publications. shown. the

million is

Multiple

Total SNPs * 550,000 435,000 463,000 209,000 307,000 237,000 2.2 groups

population primary

referred the

strongest

excluded. of

control

are

filtering.

the

(Continued)

replication

were and Illumina

only review

− 8 and

largest Genotyping platform Affymetrix Illumina Illumina Affymetrix Illumina Affymetrix Affymetrix

control a readers

Disease for

× as so

disease, 1.0 quality

well

loci,

discovery

as with

frequency

Neurological

Replication cohort cases/ controls 1057/1104 612/14139 3361/4573 1835/3111 311/1895 1158/1178 215/2430 652/3613 321/1614 following

of 2010 ),

allele

combined threshold

fields.

al.,

associated the

et well-established minor

analysis

Studies

for

arbitrary the

with

respective an ratio

( Hindorff

significantly Discovery cohort cases/ controls 807/1074 988/2521 1713/3978 628/1644 306/15,664 401/1644 1544/19,602 the

their association

Association below reported,

authors.

for were

not associations within

database

were

reported. reported, study

used

locus

were

by not PubMed ID 19412176 19915576 19915575 18660810 17634447 17637780 19369658

public ,

interest were

a SNPs

single significant Genome-Wide

values a of al.

high

frequencies

P ratios from

et of al.

YNDROME report al. suggested from

et S

odd allele interval; Selected et

number

not

al. al. al. al. ISEASE

whose

EGS D et et et et SNPs obtained

did because L

gene Study Hallmayer Satake Simon-Sanchez Schormair Stefansson Winkelmann Ikram

multiple multiple SNPs

were

Confidence

multiple and studies ,

ARCOLEPSY ESTLESS ARKINSON TROKE When If Closest When Included eTABLE 50.5 Year N 2009 2009 2008 2009 *Approximate † ‡ § ¶ # Data P 2009 R 2007 2007 S CI

(Harold et al., 2009; Lambert et al., 2009; Naj et al., 2011; Seshadri et al., 2010). In Parkinson disease, recent GWASs in large cohorts of European and Japanese patients identified alpha-synuclein (SNCA) and LRRK2 as susceptibility loci (Edwards et al., 2010; Lill et al., 2012; Satake et al., 2009; Sharma et al., 2012; Simon-Sanchez et al., 2009), which is notable because both genes also give rise to autosomal dominant forms of parkinsonism. The tau protein (MAPT), another gene responsible for autosomal dominant forms of parkinsonism, was also found to be associated with disease in European #1 Select population (cases and controls) for study populations (Edwards et al., 2010; Lill et al., 2012; Sharma et al., 2012; Simon-Sanchez et al., 2009). Together these results suggest a commonality between Mendelian and sporadic #2 Genotyping forms of this disorder. Single Nucleotide Polymorphism (SNP) It is important that physicians have a clear understanding …ACGTCAGTGGCATA…Major allele of the meaning of GWAS results so as to be able to differentiate …ACGTCAGTCGCATA…Minor allele common variants associated with disease from disease-causing mutations. A potential error to be avoided in the clinical interpretation of GWAS data is directly equating the findings to the #3 Analysis – Is either SNP associated with disease phenotype? future development of the disease. It must be reiterated that the finding of an association with a common variant does not equal the finding of a disease gene. By definition, these common variants must have low penetrance; otherwise, they would not be so common in normal individuals, and they would likely act in a more Mendelian way. Furthermore, such variants might be associated with disease modifiers—for example, genes acting either upstream or downstream in pathways where disruption or dysregulation can lead to the disease, or perhaps genes involved in the production or regulation of factors involved in such pathways. Instead of directly causing disease, such modifier genes confer a risk of disease, the mag- Controls Cases nitude of which is sometimes not directly quantifiable because it involves interaction with other genes and the environment. Patients with major allele are more likely to have disease Therefore, for most conditions, reported GWAS information odds ratio > 1.0 cannot be directly translated into a clinical setting, because the presence of the variant does not necessarily lead to the disease Fig. 50.12 Genome-wide association study (GWAS). A GWAS for in most cases, particularly for the more rare disorders. As an disease is performed by genotyping a selected population of cases example, one of the strongest and best-known identified asso- and controls using microarray or other technology for single nucleotide ciations, the apolipoprotein E ε4 allele detected in sporadic polymorphisms (SNPs) across the genome. In this example, a sample AD, with an odds ratio of 4 (Coon et al., 2007), has such an SNP is depicted, with major and minor alleles illustrated as green or inconsistent predictive value that it is not recommended for red, respectively. Detailed computational analysis is performed to routine use in disease prediction nor as a typical part of most determine whether any individual SNPs are associated with the disease clinical dementia evaluations (Knopman et al., 2001). Despite state greater than by chance. In this example, the major allele (green) this, some commercial organizations have begun to market is associated with the disease and more likely to be present in cases direct-to-consumer tests for genetic variation associated with than controls, reflected in an odds ratio above 1.0. Note that while the disease. As the public has become more aware of the impact SNP in question may be involved in the disease, it may also be a of genetics on health and disease, there has been a growing marker near an involved gene. desire for pre-emptive screening, particularly for individuals with family members afflicted with common disease (Sweeny including dozens of neurological conditions (for examples et al., 2014). In response to this need, genetic variation screen- see eTable 50.5, available online). Although the SNPs them- ing tests are often marketed as a means of assessing the poten- selves may directly influence the disease under study, most tial for future development of disease. Given the caveats often this is not the case, and SNPs are best thought of as discussed, there is no definitive means at present to accurately markers for the location of a gene(s) or region relevant to the define an individual’s risk of disease based on the presence of disease. In fact, most alleles of the second major type of one or more associated common variants, and attempting to common genetic variation, CNVs, are mostly captured by do may place patients at unnecessary risk (Bellcross et al., SNPs (Conrad et al., 2010) and can be identified by the 2012; Brownstein et al., 2014). It is important for the physi- common SNP genotyping platforms, allowing GWASs to eval- cian to be aware of this insofar as patients may contact them uate the contribution of common inherited CNVs as well as regarding such testing, and it should be emphasized that any SNPs. Further discussion of the use of this technology (includ- positive results would have unclear predictive value. ing Box 50.1) is available at http://expertconsult.inkling.com. There are examples of clinically important allelic variants For the most common neurodegenerative dementia, Alzhe- identified by other methods, so such expectations for GWAS imer dementia, recent GWASs have benefited from large in neurological disease are not unfounded. One such illustra- numbers of available cases and expanded the loci known to tion is the variation seen in the cytochrome P450 isoenzyme be associated with disease beyond the apolipoprotein E locus CYP2C9, which is responsible for the metabolism of a number to include other neuronal molecules such as BIN1 and of clinically relevant pharmaceutical agents, in particular the PICALM, which are involved in clathrin-mediated endocytosis anticoagulant, warfarin (Sanderson et al., 2005). The major and intracellular trafficking, and the apolipoprotein CLU allele CYP2C9*1 is seen in more than 95% of Asian and

The model that underlies the value of GWAS is based on Genetic Data Repositories and Data Sharing the concept that common disease is predicted to arise from BOX 50.1 50 the interplay of effects caused by common polymorphisms in Sharing genetic data is very important, and this is emphasized multiple genes, as well as environmental and other factors. clearly in relation to genome-wide association study (GWAS) data The aim of a GWAS is to identify these common variants that which, because they are produced on common platforms typing correlate to risk for the disease in question but do not alone essentially the same genetic variation in multiple populations, cause the disease. Because the effect size, or increase in odds have great value beyond their original intended purpose. for a disease, is expected to be small (negative selection would have removed strongly deleterious variants from the popula- • By sharing these data, other researchers have the opportunity tion), and many independent genetic markers are tested, large to virtually perform GWAS analysis on populations they would sample sizes are needed to have power to detect genome-wide not necessarily be able to evaluate. association. This is further compounded by two of the many • Large sample sizes increase the power of GWAS, and few major factors challenging GWASs of common neurological single groups can recruit enough patients for a well-powered diseases, phenotypic and genetic heterogeneity. Phenotypic het- GWAS, so this permits pooling and reanalysis of data collected erogeneity describes the wide and variable clinical spectrum of in many laboratories on a single neuropsychiatric disease such patients with a particular neurological disorder or syndrome as schizophrenia (e.g., Purcell et al., 2009; The International (e.g., frontotemporal dementia, epilepsy, multiple sclerosis, Schizophrenia Consortium at http://pngu.mgh.harvard.edu/ autism) manifest. Genetic heterogeneity refers to the notion that isc/). even in those with a relatively homogeneous phenotype, many • Sharing data permits study across diseases that may share different genetic factors may be contributing in different indi- common etiologies, such as amyotrophic lateral sclerosis and viduals to lead to the same phenotype. Both of these forms of frontotemporal dementia (van Es et al., 2009) or autism and heterogeneity require large samples to have adequate power schizophrenia (e.g., Cantor and Geschwind, 2008; Psychiatric to detect genetic risk factors of even moderate size. The smaller Genomics Consortium at http://www.med.unc.edu/pgc/). the effect of any given genetic variant, the larger the sample • Populations could be resorted based on other known size needed to detect that variant. One strategy that may variables, SNPs could be excluded or grouped during analysis, increase power is to study intermediate phenotypes, or endo- different methods of analysis could be applied to the raw data, phenotypes, that may be more related to individual genetic risk or data from individual members could be extracted for use in factors than the broad clinical diagnosis of a disorder, such as other studies (Purcell et al., 2009). specific measures of language or social behavior in autism Because of the benefits of this versatility, many funding (Abrahams and Geschwind, 2008; Alarcon et al., 2008; Vernes organizations, including the National Institutes of Health, and et al., 2008). Alternatively, such phenotypes can be used to major scientific journals, such as Nature and Science, have identify more homogeneous subgroups of patients, such as policies in place for investigators to make GWAS and other those with specific forms of pathology, as in TAR DNA-binding genomic data available to other researchers. In some cases, protein (TARDBP) inclusion-positive frontotemporal demen- disease-specific repositories have been established for the tia (FTD), which may have improved power in a recent FTD purpose of sharing both the biomaterials and genetic information, GWAS by reducing heterogeneity (Van Deerlin et al., 2010). such as the Autism Genetic Resource Exchange (AGRE at http:// Efficiently generating the extensive genotype data - neces www.agre.org/) and the NIMH Human Genetics Initiative sary for a GWAS has been made possible using microarray repository (https://www.nimhgenetics.org/nimh_human_genetics_ technology (Coppola and Geschwind, 2006; Geschwind, initiative/). Other examples of such repositories can be found at 2003). In this type of experiment, specific fragments of DNA the National Institutes of Health Genomic Data Sharing website corresponding to the sequences of the target SNPs are immo- (http://gds.nih.gov/) bilized in a grid pattern across a glass slide, termed the array. Genomic DNA from individual cases and controls is fluorescently labeled, hybridized to the slide, and the signals from laser-induced dye excitation are collected. The readout will be significant genome-wide association for total stroke implicat- a map of the SNP pattern for each patient. Data cleaning, ing the NINJ2 gene, which encodes a cell-adhesion molecule quality control, and statistical analysis are performed to deter- found in radial glia (Ikram et al., 2009). Replication in an mine whether any SNPs are associated with patients more independent cohort confirmed the association of one SNP than controls. Given the large number of independent tests with a combined hazard ratio of 1.29 for ischemic stroke in performed in a GWAS, statistical significance is commonly white persons (Ikram et al., 2009). The mechanism of how set at 5 × 10−8 (McCarthy et al., 2008; Wellcome Trust Case NINJ2 increases risk for ischemic stroke is unclear at this time, Control Consortium, 2007) to correct for multiple compari- but the results of this GWAS open up a new avenue of research sons. It is now also considered standard to demonstrate that by highlighting it as a candidate for future molecular and cel- any statistically significant association identified is present in lular studies into stroke etiology. more than one study population, providing an independent GWASs can also contribute to the discovery of biological replication of the initial finding. Study power and replication pathways relevant to disease, as seen in a recent study of FTD may also both be aided by the availability of shared GWAS patients grouped pathologically by the presence of TARDBP data (Box 50.1). inclusions. The study identified a susceptibility locus on chro- Examples of recently published genome-wide association mosome 7p21.3 that contained a previously uncharacterized studies of interest involving neurological disease are shown in transmembrane protein, TMEM106B (Van Deerlin et al., Table 50.5. One example illustrating the use of a GWAS in 2010). TMEM106B, thought to be involved in lysosomal func- complex disease is from a 2009 study by Ikram and colleagues, tion (Brady et al., 2013), was subsequently shown to be a who performed a GWAS using a population of 19,602 white genetic modifier for FTD resulting from mutations in two dif- persons, of whom 1544 had strokes (Ikram et al., 2009). They ferent genes, GRN (Finch et al., 2011) and C9orf72 (Gallagher identified two intergenic SNPs on chromosome 12p13 with et al., 2014; van Blitterswijk et al., 2014).

African populations, but multiple variants commonly exist in Rare Variants and Candidate Gene Resequencing European and Caucasian populations, including CYP2C9*2 50 and CYP2C9*3, both of which reduce warfarin metabolism So far, common variation is only able to explain a small per- (Sanderson et al., 2005). In one study, 20% of patients carried centage of genetic risk for common neurological disease. The either CYP2C9*2 or CYP2C9*3 and required a mean reduc- other major model that attempts to explain what is currently tion of their warfarin dosage by 27% to maintain an optimal referred to as the missing heritability (Manolio et al., 2009) therapeutic range, reflected by an increased relative risk of in complex genetic disease implicates rare variants with bleeding of about 2.3 (Sanderson et al., 2005). Although the medium to high penetrance instead of more common ones relative risk in this example is still greater than typically seen with low penetrance (Schork et al., 2009) (Fig. 50.13). Rare in most GWASs (ranging from 1.1 to 1.3), it demonstrates how variants are defined as DNA alterations that are found in less common variant risk information can potentially affect the than 1% of most populations or, in some cases, are “private” care of an individual patient. As we discover more regarding and only seen in specific affected families. In this model, one the nature of complex genetic disease, new ways of utilizing or more rare variants, alone or in combination with common this information clinically will likely be determined. In the variants, produce the disease in question. A GWAS is not well meantime, the value of GWAS data, especially from a pharma- suited to detect these variants, because they are rare and most cogenomic research perspective, is significant; it can help iden- likely to be relatively recent mutations that do not segregate tify new genes, pathways, and biological networks related to on common haplotypes measured in these studies. Even when disease that may have therapeutic benefit (Box 50.2). they do, they do not occur in high enough frequency in the general population to provide statistical power for their detection using current sample sizes. Detection generally requires resequencing of potentially involved candidate genes in a BOX 50.2 Pharmacogenetics and Personalized Medicine defined population of patients and controls. One major difficulty of such investigations is that the baseline level of In addition to contributing to disease susceptibility, genetic rare variation among normal humans is not clearly estab- variation can have other medically applicable roles. One of the lished. Studies such as the 1000 Genomes Project (http:// most highly anticipated benefits for genetic research is the www.1000genomes.org/) are attempting to catalog normal capability of tailoring medical or pharmacological therapies to human variation within the 0.1% to 1% range, so researchers target a patient’s disease based on their individual genotype, the will be able to better define this class of rare variants and so-called concept of personalized medicine. The initial application develop more effective strategies for their detection. of this concept is in the optimization of drug effects and minimization of toxic side effects based on genotype, termed pharmacogenetics (Chan et al., 2011; Holmes et al., 2009). Although this field has not yet advanced to the point of routine clinic use, there are several examples of the potential utility and the benefit to patients we may hope to see in the near future (Chan et al., 2011). • In stroke, genetic variation has been found to impact patient response to antiplatelet agents and anticoagulants (Meschia, 2009; see main text) and influence statin-associated myopathy (Link et al., 2008; Meschia, 2009). In a recent GWAS analysis, an association was demonstrated between a SNP in the SLCO1B1 gene, which encodes a membrane protein that mediates liver uptake of various drugs including statins, and Common disease, common variant myopathy (odds ratio [OR] 4.3 when heterozygous and 17.4 (variant identifiable by GWAS) when homozygous) (Link et al., 2008), clearly reflecting a need to modify statin treatment in such patients. • In epilepsy, GWAS analysis has identified the HLA-A*3101 allele as associated with carbamazepine-induced hypersensitivity reactions in patients of Northern European (OR = 12.4, 95% confidence interval 1.27–121.03) (McCormack et al., 2011) and Japanese (OR = 10.8, 95% confidence interval 5.9–19.6) (Ozeki et al., 2011) descent, suggesting a need to consider individual genotype when selecting antiepileptic medications. • In Parkinson disease, patients with the COMTHH genotype, reflecting a homozygous SNP that modulates catechol-O- Common disease, rare variant methyltransferase activity, show a more clinically effective (variant too rare to be identifiable by GWAS) response to entacapone during a levodopa challenge (Corvol Fig. 50.13 Models of causal variants in complex disease. In the et al., 2011), suggesting genotyping may play a useful role in common disease–common variant model, risk of disease is imparted the management of an individual patient’s drug therapies. by the presence of one or more gene variants present in 5% or more A number of practical issues will have to be solved before of the population (red). Such variants are amenable to detection by such testing can achieve widespread use in the clinic, particularly genome-wide association studies (GWAS). Conversely, in the common determinations of the clinical benefit relative to cost-effectiveness disease–rare variant model, disease is caused by rare genetic variants in specific diseases and populations (Chan et al., 2011; Holmes present in less than 1% of the population or only in specific families et al., 2009; Meschia, 2009; Swen et al., 2007); however, recent (various colors). Such variants would not be amenable to detection by rapid advancements in technology, such as next-generation DNA GWAS, since they would not be represented in large enough numbers sequencing, may prove beneficial in this arena (Chan et al., 2011). to generate statistical significance. Note that both models are not mutually exclusive, and both may contribute to common disease.

An example of this approach involves the developmental Fig. 50.14, A). The average ratio of fluorescence is normalized disorder, autism, where sequencing of the gene, contactin- across the array and then evaluated for each probe. If both associated protein-like 2 (CNTNAP2), in 635 patients with samples hybridize to a given probe equally, the corresponding autism spectrum disorder (ASD) and 942 controls found 13 DNA region is present equally in both samples. However, if rare variants unique to patients, including one which was seen the DNA sample being studied hybridizes more or less in 4 patients from 3 unrelated families (Bakkaloglu et al., intensely than the reference sample, it must contain either 2008). Recessively inherited mutations in CNTNAP2 in an more or less of the chromosomal region in question, thus Amish family with a syndromic form of autism with epilepsy indicating a copy number variation at that location. The provided the most convincing evidence for the causal role of minimum size of a CNV that can be detected by this method mutations in this gene (Strauss et al., 2006). Interestingly, this is limited to the genomic distance between the minimum same gene illustrates that the common disease–rare variant number of probes needed to observe a statistically significant and common disease–common variant hypotheses are not signal change, but is usually on the order of kilobases for the mutually exclusive, since common variants in this gene modu- highest resolution arrays. The same microarrays used to geno- late language function in ASD and other conditions (Alarcon type SNPs in GWASs may also be used to detect CNVs, incor- et al., 2008; Vernes et al., 2008). Integrating genetic and porating both intensity and inheritance data. Array CGH clinical data from human studies with other investigative essentially produces a molecular karyotype capable of detect- approaches to understanding gene function (i.e., animal ing genomic structural changes with much finer detail than disease models) can better define mechanisms of disease routine microscopic methods. In most major diagnostic labs, pathogenesis and may suggest novel treatment strategies this method has replaced microscopic karyotyping and FISH, (Penagarikano et al., 2011; Penagarikano and Geschwind, the latter of which is now used for confirmation. 2012). Exciting advances in DNA sequencing (see Genome/ Some examples of clinically relevant copy number varia- Exome Sequencing in Clinical Practice and Disease Gene Dis- tions are seen in Mendelian disorders including adult-onset covery) will allow us to finally analyze many whole genomes autosomal dominant leukodystrophy (autosomal dominant, and understand to what extent common and/or rare variants caused by duplication of the lamin B1 gene on chromosome contribute to many common neurological diseases. 5), Charcot–Marie–Tooth type 1A (autosomal dominant, most frequently caused by duplication of the peripheral Copy Number Variation and Comparative myelin protein 22 on chromosome 17), hereditary liability to Genomic Hybridization pressure palsies (autosomal dominant, most commonly due to deletion of the peripheral myelin protein 22 on chromo- The majority of variation and disease-causing mutations dis- some 17), spastic paraplegia type 4 (autosomal dominant, cussed to this point have centered around single base pair occasionally caused by deletion of the spastin gene on chro- changes in DNA sequence. However, as previously described mosome 2), juvenile PD 2 (autosomal recessive, occasionally in Structural Chromosomal Abnormalities and Copy Number caused by deletions or duplications in parkin on chromo- Variation, the CNV (Beckmann et al., 2007; Stankiewicz and some 6), and Williams syndrome (autosomal dominant, Lupski, 2010; Wain et al., 2009; Zhang et al., 2009) (Fig. caused by deletion of several contiguous genes on chromo- 50.14) actually represents more total real estate in our genome. some 7). Advances in methods such as the advent of the microarray CNVs are also particularly important for neurodevelop- indicate that such changes occur quite commonly (at 10−4 to mental disorders, with de novo CNVs present in more than 10−6 per locus per generation) compared to single nucleotide 5% of patients with intellectual disability (ID) (Koolen et al., changes (10−8 per base pair per generation on average) (Lupski, 2009) or ASD (Bucan et al., 2009; Marshall et al., 2008; Pinto 2007). Overall, CNVs are estimated to represent at least 4% et al., 2010; Sebat et al., 2007). Based on these findings, array (Conrad et al., 2010) and potentially up to 13% of the total CGH is now clinically indicated in children with a wide range human genome (Redon et al., 2006; Stankiewicz and Lupski, of neurodevelopmental disabilities including ID and ASD 2010). The high frequency of these events may reflect an evo- (Miller, D.T., et al., 2010). These studies also revealed several lutionary advantage of CNVs as a mechanism for producing potential new autism candidate genes as well as novel biologi- genetic diversity (Zhang et al., 2009) but also implies that cal pathways for future study of disease pathogenesis (Bucan clinically relevant CNVs are quite likely to occur de novo more et al., 2009; Pinto et al., 2010). Remarkably, de novo CNVs are frequently than point mutations (Table 50.6). CNVs can also associated with schizophrenia (Stefansson et al., 2008; potentially cause disease in numerous ways, including disrup- Walsh et al., 2008), especially childhood-onset forms, and tion of a gene’s coding region (which could cause a dominant some of the same CNVs observed in ASD are also observed in effect or release a recessive effect on the homologous allele) schizophrenia (Cantor and Geschwind, 2008), suggesting or by altering regulated gene expression via positive or nega- some shared liability between what were previously consid- tive dosage effects. If the CNV itself results in the disease ered clinically distinct conditions. phenotype, it could be transmitted as a Mendelian disorder, as is the case for Charcot–Marie–Tooth type 1A. Such CNVs GENOME/EXOME SEQUENCING IN CLINICAL may be examples of rare variants in the common disease PRACTICE AND DISEASE GENE DISCOVERY model. Alternatively, their contribution may be more subtle and insidious, with low penetrance and variable expressivity The identification of disease genes and their mutations hinges contributing to the risk of a complex genetic disease, such as on the capability to sequence DNA to assess for detrimental in autism (Bucan et al., 2009). alterations. The standard method of DNA sequencing tech- CNVs can be detected via essentially the same microarray nology most commonly in use today is called Sanger sequenc- technology used to detect SNPs, with only a few minor adjust- ing. Although effective and accurate, the high throughput of ments. In this case, DNA probes corresponding to specific this method is severely limited by reaction time and length chromosomal regions are placed on an array and hybridized of read, which is less than 1 kilobase. Recently, another with differentially fluorescent-labeled genomic DNA from the new technology has been developed, termed next-generation individual being studied and from a reference genomic DNA sequencing (NextGen) (McGinn and Gut, 2013; Mardis, 2013; sample, a technique termed array comparative genomic hybridi- Metzker, 2010), that can rapidly generate large amounts zation (CGH) (also called chromosomal microarray analysis) (see of high-quality DNA sequence information in a relatively

Patient DNA Control DNA Fig. 50.14 Copy number variation (CNV). A, Copy number variation can be detected via comparative genomic hybridization or chromo- 50 somal microarray analysis, shown here. In this example, patient genomic DNA and an equal amount of control DNA is hybridized to a microarray platform containing representative probes spanning the genome at a specified resolution, usually at the kilobase level. In the illustration, patient DNA is fluorescently labeled green, and control DNA Chr7 Chr7 is labeled red. Following hybridization, regions present in equal amounts are yellow, whereas regions duplicated in the patient are green, and deletions are red. In this example, the patient possesses two CNVs, a duplication on chromosome 7 (illustrated by the increased green signal at that locus on the array) and a deletion on chromosome 16 (with corresponding increased red signal at the locus). The patient Chr 16 Chr 16 also has Turner syndrome (monosomy X) reflected by the increased Chr 7 red signal across the entire chromosome. Chromosome 10 is shown Chr 10 as an example of a chromosome that does not differ between the samples (yellow). B, Introduction of CNVs by the nonallelic homolo- Chr 16 gous recombination (NAHR) mechanism. NAHR occurs when genomic instability is introduced by the presence of low copy repeat (LCR) Chr X Chr X Chr X regions greater than 1 kilobase in size with more than 90% homology. Pairing of nearby regions during DNA replication can lead to deletions, A duplications, or inversions as illustrated. C, Introduction of CNVs by the fork stalling and template switching (FoSTeS) mechanism. FoSTeS occurs when replication on the lagging strand stalls during DNA rep- LCR LCR lication and resumes at an adjacent replication fork. The structural variation introduced depends on whether the reinitiation occurs upstream or downstream of the original fork and whether it occurs on the lagging or leading strand. Examples of how deletions, duplications, Duplication or inversions might result are shown (orange arrows). Furthermore, if LCR LCR more than one FoSTeS event occurs (purple arrow), a complex struc- Inversion L LC CR R tural rearrangement could result. Deletion B LCR LCR

Deletion be applied to mRNA to study gene expression and/or alternative splicing on a genome-wide basis. This technology has Inversion dramatically reduced the cost of sequencing an entire genome to less than 1% of the cost of Sanger technology (McGinn and Gut, 2013; Mardis, 2013; Metzker, 2010), and this is expected to reach a level comparable to current clinical testing, such as Sanger sequencing-based genetic panels, in the near future. Although this technology brings new questions regarding data storage, analysis, and quality control, the translation to Duplication use in a clinical setting has already begun, adding new powerful technology to the clinician’s repertoire capable of assess- Inversion ing genetic variation on a genome-wide scale (Coppola and Geschwind, 2012). The first example of the clinical utility of Complex rearrangement this approach was demonstrated by Lupski and colleagues, who sequenced the genome of the proband in a family with a previously undiagnosed form of Charcot–Marie–Tooth C (CMT) disease type 1 (Lupski et al., 2010). By comparing the proband’s genome sequence to the human genome reference sequence, over 3.4 million SNPs and 234 CNVs were detected and subsequently paired down using a more detailed analysis until compound heterozygous mutations were identified in inexpensive and efficient manner (Table 50.7). The sequence the SH3TC2 gene on chromosome 5, a gene previously shown of the human genome was derived using Sanger sequencing to cause a different form of CMT, CMT type 4C (Lupski et al., over a 13-year period, and subsequent Sanger sequencing of 2010). The new mutations identified within this single family human genomes took roughly a year, but next-generation revealed an unexpected level of complexity and highlight sequencing can now accomplish the same feat in days. There- an observation that has become more common as more fore, it is now possible to rapidly interrogate an individual clinical exome sequencing has been performed, namely that patient’s DNA on a genome-wide level for unknown disease- genomic sequencing methods may be clinically necessary to causing mutations. Several different technologies exist under identify many disease-causing mutations, even in known the next-generation sequencing umbrella and cannot be disease genes, as they lead to unexpected phenotypic varia- fully described here (for details, see McGinn and Gut, 2013; tion distinct from the classically reported presentations of the Mardis, 2013; Metzker, 2010). The same technology can also disease.

TABLE 50.6 Selected Neurologic Diseases Caused by Copy Number Variation Disease Locus Variation Gene* Inheritance† Alzheimer dementia 21q21 Duplication APP Complex Amyotrophic lateral sclerosis 5q12.2-q13.3 Deletion SMN1 Complex Angelman syndrome 15q11-q12 Maternal deletion UBE3A Sporadic Aniridia 11p13 Deletion AN Sporadic Ataxia with oculomotor apraxia type 2 9q34.13 Deletion SETX Mendelian Autism spectrum disorder 2p16.3 Deletion NRXN1 Complex 15q11-q13 Deletion or duplication Many Complex, sporadic 16p11.2 Deletion or duplication Many Complex, sporadic 22q13.3 Deletion SHANK3 Complex Xp22.33 Deletion NLGN4 Complex Autosomal dominant leukodystrophy 5q23.2 Duplication LMNB1 Mendelian Charcot–Marie–Tooth type 1A 17p12 Duplication PMP22 Mendelian Charcot–Marie–Tooth type 4B2 11p15.4 Deletion SBF2 Mendelian CHARGE syndrome 8q12.1 Deletion CHD7 Sporadic Cri du chat syndrome 5p15.2-p15.3 Deletion Many Sporadic DiGeorge and velocardiofacial syndrome 22q11.2 Deletion Many Sporadic Duchenne/Becker muscular dystrophy Xp21.2 Deletion or duplication DMD Mendelian Epilepsy 15q13.3 Deletion CHRNA7 Complex Hereditary neuropathy with liability to pressure palsies 17p12 Deletion PMP22 Mendelian Miller-Dieker syndrome 17p13.3 Deletion LIS1 Sporadic Neurofibromatosis type 1 17q11.2 Deletion or duplication NF1 Sporadic Parkinson disease 4q21 Duplication or triplication SNCA Mendelian Pelizaeus–Merzbacher disease Xq22.2 Deletion or duplication PLP1 Mendelian Potocki–Lupski syndrome 17p11.2 Duplication RAI1 Sporadic Prader–Willi syndrome 15q11-q12 Paternal deletion Many Sporadic Rett syndrome and variants Xq28 Deletion or duplication MECP2 Sporadic Rubinstein–Taybi syndrome 16p13.3 Deletion or duplication CREBBP Sporadic Schizophrenia 2q31.2 Deletion RAPGEF4 Complex 2q34 Deletion ERBB4 Complex 5p13.3 Deletion SLC1A3 Complex 12q24 Deletion CIT Complex Silver–Russell syndrome 11p15 Duplication Many Complex Smith–Magenis syndrome 17p11.2 Deletion RAI1 Sporadic Sotos syndrome 5q35 Deletion NSD1 Sporadic Spinal muscular atrophy 5q13 Deletion SMN1 Mendelian Tuberous sclerosis 16p13.3 Deletion or duplication TSC2 Sporadic WAGR syndrome 11p13 Deletion Many Sporadic Williams–Beuren syndrome 7q11.23 Deletion ELN Sporadic Other microdeletion/duplication syndromes with 1q41-q42 Deletion Many Sporadic developmental delay and/or mental retardation 2q37 Deletion Many Sporadic 3q29 Deletion or duplication Many Sporadic 7q11.23 Duplication Many Sporadic 17q21.3 Deletion or duplication Many Sporadic 22q11.2 Duplication Many Complex Table adapted from Fanciulli et al., 2010; Lee and Scherer, 2010; Stankiewicz and Lupski, 2010; Wain et al., 2009. Additional data accessed July 2010 from the Database of Genomic Variants available at http://dgv.tcag.ca/dgv/app/home; GeneTests available at http://www.genetests.org/; and OMIM: Online Mendelian Inheritance in Man available at http://omim.org/. *If a single causative or strong candidate gene is known. If multiple genes are suspected to be involved, this is indicated. †Inheritance is described as sporadic if the variation typically arises de novo in patients, complex if it most commonly increases disease susceptibility (rare familial mutations may also occur), and Mendelian if it is typically inherited.

TABLE 50.7 Comparison of DNA-Sequencing Technologies for test for evaluating heterogeneous diseases such as xeroderma Genome Sequencing pigmentosum (Ortega-Recalde et al., 2013), Charcot–Marie– 50 Tooth disease (Choi et al., 2012), or spinocerebellar ataxia Sanger Next-Generation (Sailer et al., 2012; Sawyer et al., 2014; Fogel et al., 2014). Technology Dye-terminator Massively parallel* Next-generation methods also make possible the concomi- Approximate read 500–800 50–100† tant examination of the mitochondrial genome as well as the length (bases) exome or genome (Dinwiddie et al., 2013; Picardi and Pesole, 2012), clinically useful as mitochondrial dysfunction can Current clinical use Gene mutation Exome, genome, analysis and targeted gene arise from mutations in both the mitochondrial and nuclear mutation analysis genomes. Furthermore, in addition to identification of Men- delian mutations, this technology also allows for a more § Number of individual 1 Many detailed exploration of complex genetic variation. In studies genomes sequenced of common disease, it may prove a more effective means of and published assessing the contributions of rare variants than other methods Estimated clinical cost $Hundreds to $0.50 or less (US) such as a GWAS (Cirulli and Goldstein, 2010). Additionally, it per gene sequenced thousands may also identify novel types of variation such as double- and (US) triple-nucleotide polymorphisms, which generate amino acid Estimated cost per $Millions (US) ~$3,000 (US) changes more than 90% and 99% of the time, respectively, genome‡ and occur at 1% the density of SNPs (Rosenfeld et al., 2010). Estimated time per Years Days Future studies will have to further assess the contribution of genome‡ such novel DNA changes to human disease, but the current findings confirm that next-generation sequencing technology *A number of commercial platforms exist which utilize variations in will be able to uncover new types of functional genomic this technology. †Most common, varies per specific platform used. variation. ‡Not including bioinformatic analysis. Lastly, genome sequencing may also provide new infor §Not including the Human Genome Project reference genome. mation regarding environmental contributions to disease. Recently, genome sequencing was reported from a pair of monozygotic twins who were discordant for multiple sclerosis (Baranzini et al., 2010). No significant genomic, transcrip- Although extremely powerful, the challenges of data inter- tional, or epigenetic changes were found to explain disease pretation and analysis present a formidable challenge to the disconcordance among these twins (Baranzini et al., 2010), routine use of genome sequencing in the clinic. As an initial suggesting there may be other critical genetic or epigenetic step in the transition of this technology to the clinical arena, factors not examined by this study, or that key differences may a significant reduction in cost, data volume, and degree of lie in other cell types, or that as-yet-undetermined environ- analysis can be achieved by selecting only genomic regions mental factors are contributing to disease—conclusions which containing protein-coding information for sequencing, a would not be possible to establish without next- generation process called exome sequencing (Choi et al., 2009; Hedges sequencing technology. et al., 2009; Ng et al., 2009). These coding sequences are initially enriched from a pool of total genomic DNA and FUTURE ROLE OF SYSTEMS BIOLOGY IN then subjected to next-generation sequencing. Although this NEUROGENETIC DISEASE method is unable to detect relevant noncoding or structural events such as copy number variation, it still proves useful as The complex relationship between genetic risk variants, even a means of evaluating Mendelian disorders caused by coding when they are inherited in a Mendelian fashion, and clinical mutations, which are thought to represent up to 85% of features, or the relationship of these mutations to disease disease-causing mutations (Cooper et al., 1995). This was pathophysiology, presents significant challenges to the use of illustrated by early reports using this technology to detect genetics for diagnosis and therapeutics. Furthermore, the novel mutations causing distal arthrogryposis type 2A majority of studies investigating genetic disorders have focused (Freeman-Sheldon syndrome) (Ng et al., 2009), to confirm an on the discovery and molecular analysis of the disease genes unanticipated diagnosis of congenital chloride diarrhea (Choi themselves, as these would intuitively appear to be the most et al., 2009), and to elucidate the gene underlying postaxial immediately useful in diagnosis and potential treatment. acrofacial dysostosis (Miller syndrome) (Ng et al., 2010). In There are some examples, such as metabolic disease and the past few years, the use of exome sequencing has dramati- enzyme replacement therapy (Beck, 2010), which support this cally increased for the identification of disease genes both in practice. However, for many more diseases, including virtually individual families and in populations of patients with disease. all neurodegenerative disorders, knowledge of the specific Some recent examples of the effectiveness of this method causative gene has not immediately yielded new curative ther- include the discovery of MATR3 (Johnson et al., 2014), PFN1 apies but has instead raised many new questions regarding the ( Wu et al., 2012), and VCP (Johnson et al., 2010) in familial underlying molecular etiology of the disease. The hope is that ALS, ADA2 in early-onset stroke (Zhou et al., 2014), GNAO1 research into these underlying mechanisms will uncover new in epileptic encephalopathy (Nakamura et al., 2013), KCND3 therapeutic targets; toward that goal, the technologies dis- in SCA22 (Lee et al., 2012), TGM6 in SCA35 (Wang et al., cussed have made greater amounts of information available 2010), KCNT1 in nocturnal frontal lobe epilepsy (Heron et al., for scientific analysis than ever before. For example, microar- 2012), ATP1A3 in alternating hemiplegia of childhood rays can be used to study not only genome-wide genetic vari- (Heinzen et al., 2012), and numerous studies identifying ation via SNPs as described earlier but also variations in gene novel or published mutations in known disease genes associ- expression (Fig. 50.15). For this method, the array platform ated with classic or variant presentations. Additionally, the contains probes that are complementary to genome-wide comprehensive nature and relative low-cost of exome sequenc- mRNA sequences, and the study is performed by hybridizing ing (see Clinical Approach to the Patient with Suspected Neu- the array with fluorescently labeled mRNA collected from rogenetic Disease) has suggested it to be an effective diagnostic either patients or controls. The intensity of the fluorescent

Unidimensional approach

Phenotypic data

Gene expression data

Epigenetic data

Copy number data

Sequence data

A Systems biology approach

BA44 BA40 BA46 BA22 BA47 BA21 BA37

B Fig. 50.15 A systems biology approach to human disease allows integration of multiple layers of data. A, Typical experimental approaches to neurological diseases are one dimensional, and most commonly, efforts focus on a single layer of information such as genetic data (e.g., sequence variants), genomic data (e.g., gene expression changes), or clinical data (e.g., phenotypes). The systems biology approach considers all these aspects simultaneously using comprehensive databases to explore the relationships between the individual data sets by identifying higher-level structure. This multidimensional use of the data sets (e.g., via network analysis) links the different types of information. B, An example using a systems-based approach to study regional gene expression in the brain, using network-based analysis and imaging data to provide insights into brain connectivity. This is a stylized visualization of the combination of diffusion tensor imaging of language areas, with gene expression and weighted gene coexpression network analysis (WGCNA) to reveal integration of gene coexpression across brain areas (BA, Brodmann area), as well as novel brain region wiring. The green lines and dashed red lines indicate information flow in both directions and can be extrapo- lated to suggest excitatory and inhibitory interconnections. Each gene is depicted as a node (green or purple), with hub genes (those with the most connections to other genes) represented by purple nodes. Blue lines indicate positive correlations, and red lines indicate negative correlations. Lines between Brodmann areas indicate real and potential interactions through white matter tracts. This integration of network analysis, gene expression data, and imaging demonstrates relationships among key genetic factors in distinct regions and their role in regional brain connectivity in both normal individuals and those with disease. (With permission from Geschwind, D.H., Konopka, G., 2009. Neuroscience in the era of functional genomics and systems biology. Nature 461, 908–915.)

Descargado de ClinicalKey.es desde Univ Antioquia septiembre 06, 2016. Para uso personal exclusivamente. No se permiten otros usos sin autorización. Copyright ©2016. Elsevier Inc. Todos los derechos reservados. Clinical Neurogenetics 671 signal can be used to determine and compare the relative neurological disorders for environmental influence. Several levels of expression for each gene across the samples. Similar environmental factors have been postulated to play a role in 50 techniques can also be used to evaluate RNA splicing with the development of multiple sclerosis. These include vitamin probes that correspond to all the exons in a given gene and D levels, which may explain epidemiological findings that MS then assessing samples for their alternative usage in cases and risk is associated with geographical location in childhood and controls. With the availability of this genome-wide data, month of birth; exposure to Epstein–Barr virus, which is asso- encompassing both genetic variation and gene expression ciated with increased MS risk if it occurs after the age of 15 in clinically evaluated patients and controls, it becomes years; and smoking, which appears to increase MS risk and can possible to incorporate and synthesize the totality of this worsen established disease course (Banwell et al., 2011; Handel information together in ways which assess phenotype, genetic et al., 2010). If such environmental influences could be linked variation, and gene expression simultaneously in a more com- to specific molecular and/or cellular events that may trigger prehensive way. This field of study, known as systems biology, disease in genetically susceptible individuals, it would have a strives to use these sets of information to develop detailed dramatic impact on our understanding of disease pathogen- genetic pathways to identify related genes and genetic pro- esis, our treatment of established patients, and our recom- grams relevant to disease (Geschwind and Konopka, 2009) mended preventive strategies to reduce disease. The influx of (see Fig. 50.15). Such integrative analysis has begun to acceler- new genetic information identifying risk factors for complex ate our understanding of disease pathogenesis and generate disease is expected to stimulate research into the impact of the new insights into more effective treatment strategies, which environment on these variants (Traynor, 2009), ideally trans- will only improve as we learn more and the techniques lating into improvements in our understanding of the envi- improve. ronmental effects on neurogenetic disease. One example of this type of systems biology approach involves using gene expression data, such as from microarray GENETICS AND THE PARADOX studies, to group individual genes according to their degree of OF DISEASE DEFINITION coexpression, forming functionally related gene expression modules. These modules are then graphed according to the Research into the genetics of neurological disease has estab- interconnectivity of their members, which produces a network lished an alternative standard to the clinical or pathological of correlations centered around one or more key genes, termed definition of a disease, the genetic diagnosis. However, these hubs, which functionally drive the association either directly standards are not equivalent, and to fully understand the dif- or indirectly. Further assessment of these hub genes and their ference, we must consider the meaning of a genetic diagnosis. connections can identify potentially important genes and bio- Currently, pathology is thought of as a gold standard for diag- logical pathways affected in disease. Such techniques have nosis, but it is not available antemortem in many cases. A already been applied to the study of Alzheimer disease (Miller, clinical diagnosis is limited by the homogeneity of the disease J.A., et al., 2008, 2010), epilepsy (Winden et al., 2011), HIV- in question and the sensitivity and specificity of its clinical associated dementia (Levine et al., 2013), amyotrophic lateral features. Although genetic testing can often provide a defini- sclerosis (Saris et al., 2009), chronic fatigue syndrome (Presson tive answer to diagnosis, one of the potential paradoxes that et al., 2008), hereditary cerebellar ataxia (Fogel et al., 2014), has emerged from our identification of disease genes, and and schizophrenia (Torkamani et al., 2010). These various subsequent clinical and pathological correlations, is that the systems biology studies illustrate the versatility of such an relationship between genetic susceptibility and clinical diag- approach and the potential impact these studies can have on nosis is far from simple. This is true for virtually all Mendelian research into complex disease pathogenesis. diseases and becomes even more complicated when complex diseases are considered. ENVIRONMENTAL CONTRIBUTIONS TO In Mendelian disorders, X-linked adrenoleukodystrophy is NEUROGENETIC DISEASE a prime example of this paradox. In a single family, all with the same mutation, neurological phenotypes may range from Although this chapter has principally dealt with the molecular an inflammatory cerebral demyelination to a noninflamma- aspect of neurogenetic disease, the contributions of the envi- tory distal axonopathy to a behavioral phenotype similar to ronment cannot be overlooked, particularly for complex attention-deficit hyperactive disorder or autism spectrum dis- genetic disease. Aside from perhaps the few Mendelian disor- order (Moser et al., 2005), despite all family members carry- ders with complete penetrance, all genetic disorders are likely ing the identical genetic diagnosis. With regard to complex influenced either directly by environmental factors or- indi disease, frontotemporal dementia spectrum disorders provide rectly by the influence of the environment on other aspects of another salient example, as families with the same mutations the patient’s genetic background. Despite this, we still know can have vastly different clinical features ranging from purely very little regarding the precise role of the environment in the psychiatric to motor neuron disease, parkinsonism, cortical development of neurogenetic disease, and this is therefore an basal degeneration, progressive supranuclear palsy, or demen- important area requiring further study (Reis and Roman, tia, either singly or in combination (van Swieten and Heutink, 2007). Monozygotic twin studies and animal studies have 2008). A similar scenario can be observed in epilepsy, where both indicated that environmental influences can affect the broad seizure phenotypes are seen in some familial forms of development/severity of Mendelian genetic disease, as well as epilepsy (Helbig et al., 2008). Conversely, identification of more complex disorders, but precisely how this occurs in a Mendelian mutations can lead to a broadening of disease genetically susceptible individual remains a mystery. Many definition, as has been the case in Friedreich ataxia, where suggestions have been postulated for various disorders, includ- adults with a distinct late-onset phenotype are now frequently ing exposures to diverse physical, chemical, or biological identified (Bhidayasiri et al., 2005), or in adult polyglucosan insults, but an overall comprehensive picture has yet to body disease, a progressive myeloneuropathy discovered to be develop. For example, multiple sclerosis (MS) is a complex the adult form of glycogen storage disease type IV, which can neurological disease that likely results from a combination of lead to fatal liver complications in children (Lossos et al., genetic susceptibility and environmental contributions, all of 2009). What is further remarkable is that genetic findings in which may act independently of one another (Banwell et al., certain Mendelian forms of PD question the notion of pathol- 2011; Handel et al., 2010), and is one of the most well-studied ogy as the gold standard. Here, certain families with mutations

TABLE 50.8 The Neurogenetic Evaluation and the Clinical Utilization of Genetic Testing Establish the phenotype All patients in whom a genetic diagnosis is suspected require a thorough physical examination and clinical history including a detailed family history. Differential diagnosis is established based on phenotype. Genetic etiologies should be considered in all cases where there is a positive family history of disease. Rule out nongenetic With the exception of suspected genetic diseases with known disease-modifying treatments, patients should be fully etiologies evaluated for nongenetic causes of disease prior to the initiation of genetic testing, as these are generally more amenable to curative or disease-modifying treatment. Order genetic testing Genetic testing should not be used as a screening tool. Physicians suspecting a hereditary disorder but unable to based on phenotype arrive at a diagnostically useful clinical phenotype should refer these patients for further evaluation at a tertiary center specializing in such cases. Use disease biomarkers Cost management should be maintained through the use of biomarker testing whenever possible, with genetic testing when available as the confirmatory step in diagnosis to obtain the genotype for clinical trials, research studies, and genotype– phenotype clinical correlations. Avoid genetic panels Disease- or inheritance-based multigene panels should be discouraged in routine clinical practice, as these are not a cost-effective use of patient resources. There may, however, be a role for small focused panels (or panels based on less expensive next-generation sequencing technology) in specific disorders with heterogeneous phenotypes. Provide genetic counseling Genetic counseling (by a physician, geneticist, or genetic counselor) should be provided to all patients for whom genetic testing is recommended. Follow-up counseling should be provided to all patients with a positive gene test and offered to family members who may be at risk or disease carriers. Any and all ethical concerns should be fully addressed. Utilize new technology in Genome and/or exome sequencing, if clinically available, could potentially be an appropriate consideration for patients challenging cases with suspected genetic disease and complete negative genetic and nongenetic evaluations.

in the LRRK2 gene lack Lewy body pathology, yet have clear Mendelian disease genes, and in some settings, genetic testing dopamine-responsive PD (Zimprich et al., 2004). This raises has become as routine as other common blood tests. However, the question as to what is the gold standard, as the absence of because genetic testing carries additional implications for a Lewy bodies would not be consistent with a pathological PD patient and their family, particularly with regard to heritability diagnosis. Seen from this perspective, it is clear that pathology, of disease, it is important that it be used appropriately and genetic findings, or clinical phenotypes cannot be interpreted that patients be fully educated prior to such testing. Important in isolation, and it is the combination of these characteristics points to consider for genetic testing are summarized in Table that defines a disease. As we gather more genetic information 50.8. Although how the testing is incorporated into a clinical about neurological disorders in the coming years, our defini- evaluation strategy will vary by disease, a general principle is tions of these diseases will certainly expand and change. Iden- that most genetic disease is diagnosed clinically via a thorough tifying disease-causing mutations and/or establishing a genetic history (including family history) and physical examination. risk profile will provide further knowledge regarding disease A complete evaluation for nongenetic causes should be per- etiology, with implications for counseling, further diagnostic formed as appropriate prior to any genetic testing so that workup, and eventually for treatment—described in greater possible treatments can be initiated in a timely manner. detail next. Genetic testing should only be used to confirm a clinical sus- picion, not for screening purposes, because currently this is CLINICAL APPROACH TO THE PATIENT WITH low yield and not cost-effective in the majority of cases (Fogel et al., 2013). Specialist referral to a tertiary center is appropri- SUSPECTED NEUROGENETIC DISEASE ate for all cases where a diagnostically useful clinical pheno- In this chapter we have outlined the current state of clinical type cannot be established. Genetic counseling (see later) neurogenetics and the techniques available to neuroscientists should be provided, by either a physician or a licensed genetic to better understand and study genetic disease for the benefit counselor, prior to testing to ensure that patients understand of patients. A consistent theme has been that, in the near the nature of the test and the possible results. When testing is future, most neurological diseases will be described on a ordered, it should be based on phenotype and supported by genomic level, and large amounts of detailed genetic informa- mode of inheritance if this can be determined. Testing of an tion will become available to the clinician, particularly with asymptomatic minor is never indicated for a genetic disease the availability of exome and genome sequencing. This raises where there is no treatment or cure. Knowledge of the disease the important question of how the clinical neurologist is to status without chance for treatment may have many negative synthesize all this newly available genetic information regard- consequences. ing Mendelian disorders and common disease and apply that Many companies now offer broad genetic panels based on to patients in the clinic on a daily basis. We hope this overview general phenotypes or modes of inheritance for a particular will provide some basic tools to utilize and interpret such symptom, which have appeal because they are simple to order information in a meaningful way. In this section, we will deal and often advertised as a molecular means of differentiating with the four major clinical areas impacted most by this new between overlapping phenotypes. Unfortunately this does a genetic knowledge: (1) evaluation and diagnosis, (2) genetic disservice to the patient, since these panels can be quite costly counseling, (3) prognosis, and (4) treatment. (up to $15,000 or more for 20 genes or fewer) and despite being billed as complete, often test disorders with such diverse Evaluation and Diagnosis phenotypes as to make it impossible to consider both in the same individual, or test genes so rare that only a few families Evaluation and diagnosis benefit from the arsenal of genetic are even known to possess them. Over time, the clinical avail- testing available for single gene disorders and for genomic ability of exome and genome sequencing will likely signifi- variation. Many commercial laboratories offer testing for cantly reduce the usage of most multigene panels, given these

Descargado de ClinicalKey.es desde Univ Antioquia septiembre 06, 2016. Para uso personal exclusivamente. No se permiten otros usos sin autorización. Copyright ©2016. Elsevier Inc. Todos los derechos reservados. Clinical Neurogenetics 673 tests are vastly more comprehensive and cost-effective TABLE 50.9 Types of Genetic Testing (Coppola and Geschwind, 2012; Fogel et al., 2014), on the 50 order of approximately $5,000 for over 21,000 genes. In the Sequence variant(s) missed short term, the use of broader gene panels that take advantage Sequence variant(s) or not accurately of the less expensive next-generation sequencing technology Type of test identified determined (approximately $2,000 for ~200 genes) will likely form a tran- ‡ sition step between current methodologies and sequencing of Gene Point mutations* Noncoding variants the complete exome or genome (Nemeth et al., 2013). Regard- sequencing Frameshifts Copy number Splicing mutations† variations§ less, the clinical examination should be used to precisely Polymorphisms Repeat expansions define the patient’s phenotype, which will in turn suggest the most high-yield conditions for genetic testing. This systematic Select exon Known predefined Variants outside sequencing variants target region** approach is of immense benefit in resource management and #,** the education of current and future physicians should include (Targeted Target region only Point mutations* mutation Point mutations* Frameshifts discussion on the implementation and utilization of such analysis) Frameshifts Splicing mutations† strategies in clinical practice (Fogel et al., 2013). Splicing mutations† Polymorphisms The types of single-gene testing available vary per labora- Polymorphisms Noncoding variants‡ tory and gene (Table 50.9). The most comprehensive (and Copy number expensive) testing type commonly available is full individual variations§ gene sequencing, where all coding regions, as well as approxi- Repeat expansions mately 50 bases in each intron/exon junction, are sequenced Repeat Repeat expansion in Point mutations* for the presence of mutation. This will detect all coding point expansion the specific gene Frameshifts mutations and splice-site mutations as well as small insertions testing¶ tested Splicing mutations† and deletions but will miss more detailed structural variation. (Targeted Polymorphisms Importantly, novel coding mutations can be detected in this mutation Noncoding variants‡ analysis) Copy number way. Targeted sequence analysis (also called select exon testing) § consists of specific sequencing reactions designed to only variations detect one or a few previously identified mutations. This will Gene copy Copy number variation§ Point mutations* not detect any sequence variations outside of the limited number of gene tested Frameshifts region of the gene being searched. For repeat disorders, there variation Splicing mutations† (Deletion/ Polymorphisms are specific tests to identify the relevant expansions using ‡ either polymerase chain reaction (PCR) or Southern blotting, duplication Noncoding variants testing) Repeat expansions a hybridization-based DNA sizing technique. Larger deletions or duplications (e.g., copy number variations) can be detected Chromosomal Genome-wide copy Point mutations* by quantitative PCR methods or by comparative genomic microarray number variations‡‡ Frameshifts †† † hybridization. It is important to be aware of the type of testing analysis Splicing mutations being ordered; in some cases, such as select exon testing, a (Comparative Polymorphisms genomic Noncoding variants‡ negative result does not exclude mutations elsewhere in the hybridization) Repeat expansions gene being tested. Interpretation of these genetic results may Clinical exome Point mutations* Noncoding variants‡ be straightforward, for example, if no variants are present †† or if known pathogenic changes are found. In contrast, inter- sequencing Frameshifts Copy number Splicing mutations† variations§ pretation may be complicated if novel sequence variants of Polymorphisms Repeat expansions# unknown pathological significance are identified. Inconclu- sive results may require interpretation by a specialist and/or Clinical genome Point mutations* Repeat expansions# sequencing†† Frameshifts further testing to determine the likelihood of pathogenicity. † Common diseases must be approached in a different Splicing mutations Polymorphisms manner, because detailed phenotype alone cannot always Noncoding variants‡ predict the mutation to test for, particularly when assessing Copy number genomic variation. Still, the goal remains to develop strategies variations§ incorporating known genetic information into a systematic protocol designed to maximize diagnostic capability while *Includes missense, nonsense, and silent mutations. †Includes only those involving splice sites and exonic splicing minimizing cost and unnecessary testing (Lintas and Persico, regulatory sequences. 2009). Tests such as chromosomal microarray analysis are ‡Includes promoter mutations and noncoding splicing regulatory clinically available to search genome-wide for disease-causing elements. CNVs and are recommended for sporadic causes in disorders §Arbitrarily defined here as any deletion/duplication/insertion larger such as intellectual disability or autism where CNVs have been than detectable by Sanger sequencing. found responsible for a reasonable percentage of disease ¶Targeted mutation analysis using either polymerase chain reaction (Geschwind and Spence, 2008; Miller D.T., et al., 2010). Use (PCR) and/or Southern blot is preferred, as sequencing may be inaccurate due to the large size of many repeat regions. of such testing in sporadic adult-onset disease is less clear, so # the physician is advised to refer to current published guide- Potentially detectable by genomic sequencing methods with appropriate read lengths. lines for the disease in question before ordering. For more **Size and number of region(s) targeted varies per individual test. specific phenotypes, other available tests include those assess- ††Genome-wide testing method. ing for CNVs (often called simply deletions/duplications) involv- ‡‡Minimum size of CNVs detected and density of genomic coverage ing individual genes or specific chromosomal regions. Overall, varies per test. interpretation of CNV results can be challenging, particularly if the CNV was previously unreported. Here, the parents will often need to be evaluated to determine whether the CNV in question is inherited or de novo. As already discussed for DNA sequence changes, such findings may require interpretation by

Descargado de ClinicalKey.es desde Univ Antioquia septiembre 06, 2016. Para uso personal exclusivamente. No se permiten otros usos sin autorización. Copyright ©2016. Elsevier Inc. Todos los derechos reservados. 674 PART II Neurological Investigations and Related Clinical Neurosciences a specialist and/or further testing to determine the likelihood from published case studies to be utilized in the care of an of pathogenicity. individual patient. This can aid in the identification of specific Clinical genome and/or exome sequencing are becoming clinical features to focus on for surveillance in the develop- more routinely available in the clinic but have not yet achieved ment of a particular genetic disorder, such as cognitive decline widespread use (Coppola and Geschwind, 2012). Like CNV in a patient with isolated chorea found to have HD or cardiac analysis, clinical exome sequencing appears to be appropriate testing in an autistic patient with chromosome 15q duplica- in the principal evaluation of sporadic neurodevelopmental tion. A genetic diagnosis may also alert the clinician to poten- cases, such as severe intellectual disability (de Ligt et al., 2012), tial life-threatening comorbidities such as adrenal insufficiency and in the evaluation of patients with early-onset and/or in X-linked adrenoleukodystrophy or cardiomyopathy in Frie- familial disorders (Coppola and Geschwind, 2012); however, dreich ataxia. Review of case studies in a particular disorder use in sporadic adult-onset disease will likely be disease- may help answer questions regarding life expectancy or future specific (Fogel et al., 2014) and should await the publication disability, such as years of disease prior to loss of ambulation of specific guidelines. Genome sequencing is the more compre- in the various SCAs. Lastly, there are important positive psy- hensive of the two methods and capable of detecting more chological aspects to establishing a definitive diagnosis, par- types of mutation, as well as structural variation, but its use will ticularly for patients who have undergone many fruitless hinge on the development of accurate and efficient bioinfor- clinical evaluations. matic techniques for translating the expected massive genomic Although the majority of genetic diseases are not curable, variation per patient (millions of SNPs and hundreds of CNVs therapies do exist for many of them. Defining the genetic across the whole genome) into clinically meaningful results. etiology of a patient’s disease allows for utilization of the How such a pipeline would operate has not yet been estab- published literature on symptomatic treatments and pharma- lished, but we expect that the cost should be equivalent to that cotherapy that may benefit a specific condition. Phenylke- of an MRI study within 5 years. Incorporation of such testing tonuria is an excellent example of this, since dietary restriction into a clinical evaluation will also depend on other elements of phenylalanine initiated soon after birth will prevent cogni- such as cost of testing and time of analysis, but these factors tive impairment and enable virtually normal development are not expected to vary much from clinical exome sequencing (Burgard et al., 1999). More importantly, new clinical trials or other methods of genetic testing currently in use. are being developed frequently and can be offered to patients with an established diagnosis. Many disease-based patient reg- Genetic Counseling istries exist to facilitate this. The ultimate goal of translational neuroscience is to utilize Establishing a precise genetic diagnosis will definitively estab- advances in our understanding of disease at the molecular lish the means of inheritance of a disorder and is extremely level to aid in the treatment of patients in the clinic. Recent useful in genetic counseling and family planning, particularly new treatments, which take advantage of the molecular for disorders that show incomplete penetrance. However, aspects of these disorders, show promise in the clinic and the unlike other tests typically ordered by physicians, a positive laboratory. Such treatments include enzyme replacement diagnosis carries implications not only for individual patients therapy for metabolic disorders such as the severe fatal glyco- but for the entire family. Genetic counseling, therefore, should gen storage disorder Pompe disease, where use of recom- be provided in all cases where genetic testing is recommended, binant acid α-glucosidase in 18 infants prior to 6 months of by an experienced neurologist, a geneticist, or a licensed age enabled all to live to the age of 18 months, a 99% reduc- genetic counselor. Follow-up counseling should also be pro- tion in death, as well as reduced their risk of death or invasive vided to all patients with a positive test result and, in many ventilation by 92% compared to historical controls (Kishnani cases, offered to other family members who may be at risk for et al., 2007). Work in animal models has suggested potential disease or as carriers. Physicians must be aware of the various new pharmacological treatments, such as a recent research ethical implications involved in such testing (Ensenauer study which demonstrated that the use of histone-deacetylase et al., 2005). One area of particular importance in this regard inhibitors can unsilence expanded frataxin alleles in a involves considerations of genetic testing in asymptomatic Friedreich ataxia mouse model, restoring wild-type gene individuals, especially minors. This stems in part from con- expression levels and reversing cellular transcription changes cerns that have been raised regarding risks of depression and associated with frataxin deficiency (Rai et al., 2008), leading suicide in asymptomatic individuals diagnosed with fatal to the use of such compounds in clinical trials (Gottesfeld genetic disease, although this is not well established, and et al., 2013). Targeted molecules have been designed to further study will be important for determining best practices. correct specific disease-causing biological defects, as shown For minors, standard practice dictates that unless there is by recent work where antisense oligonucleotides were used to disease-modifying therapy available for them, they should not block mutations that promote splicing defects in the ataxia- be tested if asymptomatic until they reach an age to consent telangiectasia mutated (ATM) gene in cell lines from patients to such testing and are properly counseled as to the implica- with ataxia-telangiectasia, leading to restoration of functional tions. Counseling regarding prenatal testing and assisted protein (Du et al., 2007), and such molecules are poised for reproduction are other topics of relevance to patients of repro- clinical study (Du et al., 2011). Such newer techniques may ductive age. Current reproductive medicine techniques such as markedly exceed the therapeutic benefit of current options, in vitro fertilization and preimplantation genetic testing, by such as in Duchenne muscular dystrophy where patients can assuring that offspring will not harbor the mutation in ques- expect only moderate short-term benefit (up to 2 years) from tion, can aid couples concerned about the risk for passing on the gold standard, glucocorticosteroid treatment (Manzur inherited conditions. Other ethical considerations may also et al., 2008; Wood et al., 2010). Newer molecular strategies apply, depending on the disease and specific family/patient such as dystrophin splice-modulation, which promotes exon circumstances. skipping via antisense oligonucleotides to bypass point mutations or frameshifts, may potentially resolve the primary Prognosis and Treatment defect and has shown promising results in early clinical trials (Kinali et al., 2009; Wood et al., 2010). Novel treatments A confirmed genetic diagnosis can contribute clinically useful aimed at genetic modification of disease are also in develop- data concerning patient prognosis, as it allows information ment, as was seen in a recent study where investigators used

RNA interference techniques to specifically degrade and thus of functional oligodendrocytes in patients with Pelizaeus- silence the disease allele in a rat model of SCA type 3, result- Merzbacher disease (Gupta et al., 2012), whose cells are inca- 50 ing in a reduction in neuropathological changes in the brain pable of myelinating axons. The incorporation of new (Alves et al., 2008), and further molecular analysis suggests technologies such as next-generation sequencing and the use such strategies are viable for further preclinical studies of systems biology approaches to disease are expected to lead (Rodriguez-Lebron et al., 2013). More recently, targeted to additional new innovations. With these advances, the viral-mediated gene therapy strategies designed to restore future of clinical neurogenetics is full of promise and stands dopamine expression (Palfi et al., 2014) or modulate the pro- poised to answer the challenge stated most eloquently by duction of GABA (LeWitt et al., 2011) in Parkinson disease, or Bernard Baruch (1870–1965): “There are no such things as introduce nerve growth factor into the brains of patients with incurables; there are only things for which [medicine] has not Alzheimer disease (Rafii et al., 2014), have shown some found a cure.” success in early clinical trials and support the further testing of such strategies for these and other disorders. Stem cell REFERENCES therapies, although in their infancy, have also shown early promise in the restoration of gene function in X-linked adre- The complete reference list is available online at https://expertconsult noleukodystrophy (Cartier et al., 2009) and in the generation .inkling.com.

Choi, M., Scholl, U.I., Ji, W., et al., 2009. Genetic diagnosis by whole REFERENCES exome capture and massively parallel DNA sequencing. Proc. Natl. 50 Abrahams, B.S., Geschwind, D.H., 2008. Advances in autism genetics: Acad. Sci. U.S.A. 106 (45), 19096–19101. on the threshold of a new neurobiology. Nat. Rev. Genet. 9 (5), Cirulli, E.T., Goldstein, D.B., 2010. Uncovering the roles of rare vari- 341–355. ants in common disease through whole-genome sequencing. Nat. Alarcon, M., Abrahams, B.S., Stone, J.L., et al., 2008. Linkage, associa- Rev. Genet. 11 (6), 415–425. tion, and gene-expression analyses identify CNTNAP2 as an autism- Cleary, J.D., Ranum, L.P., 2013. Repeat-associated non-ATG (RAN) susceptibility gene. Am. J. Hum. Genet. 82 (1), 150–159. translation in neurological disease. Hum. Mol. Genet. 22 (R1), Alberts, B., Johnson, A., Lewis, J., et al., 2008. Molecular Biology of R45–R51. the Cell, fifth ed. Garland Science, New York. Conrad, D.F., Pinto, D., Redon, R., et al., 2010. Origins and functional Altshuler, D., Daly, M.J., Lander, E.S., 2008. Genetic mapping in impact of copy number variation in the human genome. Nature human disease. Science 322 (5903), 881–888. 464 (7289), 704–712. Alves, S., Nascimento-Ferreira, I., Auregan, G., et al., 2008. Allele- Coon, K.D., Myers, A.J., Craig, D.W., et al., 2007. A high-density specific RNA silencing of mutant ataxin-3 mediates neuroprotection whole-genome association study reveals that APOE is the major in a rat model of Machado-Joseph disease. PLoS ONE 3 (10), e3341. susceptibility gene for sporadic late-onset Alzheimer’s disease. J. Australia and New Zealand Multiple Sclerosis Genetics Consortium Clin. Psychiatry 68 (4), 613–618. (ANZgene), 2009. Genome-wide association study identifies new Cooper, D., Krawczak, M., Antonorakis, S., 1995. The nature and multiple sclerosis susceptibility loci on chromosomes 12 and 20. mechanisms of human gene mutation. In: Scriver, C., Beaudet, A., Nat. Genet. 41 (7), 824–828. Sly, W., et al. (Eds.), The Metabolic and Molecular Bases of Inherited Babushok, D.V., Ostertag, E.M., Kazazian, H.H. Jr., 2007. Current Disease, seventh ed. McGraw-Hill, New York, pp. 259–291. topics in genome evolution: molecular mechanisms of new gene Coppola, G., Geschwind, D.H., 2006. Technology insight: querying formation. Cell. Mol. Life Sci. 64 (5), 542–554. the genome with microarrays—progress and hope for neurological Bakkaloglu, B., O’Roak, B.J., Louvi, A., et al., 2008. Molecular cytoge- disease. Nat. Clin. Pract. Neurol. 2 (3), 147–158. netic analysis and resequencing of contactin associated protein-like Coppola, G., Geschwind, D.H., 2012. Genomic medicine enters the 2 in autism spectrum disorders. Am. J. Hum. Genet. 82 (1), neurology clinic. Neurology 79 (2), 112–114. 165–173. Corvol, J.C., Bonnet, C., Charbonnier-Beaupel, F., et al., 2011. The Banwell, B., Bar-Or, A., Arnold, D.L., et al., 2011. Clinical, environ- COMT Val158Met polymorphism affects the response to entaca- mental, and genetic determinants of multiple sclerosis in children pone in Parkinson’s disease: a randomized crossover clinical trial. with acute demyelination: a prospective national cohort study. Ann. Neurol. 69 (1), 111–118. Lancet Neurol. 10 (5), 436–445. D’Souza, I., Schellenberg, G.D., 2005. Regulation of tau isoform Baranzini, S.E., Mudge, J., van Velkinburgh, J.C., et al., 2010. Genome, expression and dementia. Biochim. Biophys. Acta 1739 (2–3), epigenome and RNA sequences of monozygotic twins discordant 104–115. for multiple sclerosis. Nature 464 (7293), 1351–1356. De Jager, P.L., Jia, X., Wang, J., et al., 2009. Meta-analysis of genome Beck, M., 2010. Therapy for lysosomal storage disorders. IUBMB Life scans and replication identify CD6, IRF8 and TNFRSF1A as new 62 (1), 33–40. multiple sclerosis susceptibility loci. Nat. Genet. 41 (7), 776–782. Beckmann, J.S., Estivill, X., Antonarakis, S.E., 2007. Copy number de Ligt, J., Willemsen, M.H., van Bon, B.W., et al., 2012. Diagnostic variants and genetic traits: closer to the resolution of phenotypic to exome sequencing in persons with severe intellectual disability. N. genotypic variability. Nat. Rev. Genet. 8 (8), 639–646. Engl. J. Med. 367 (20), 1921–1929. Belin, A.C., Westerlund, M., 2008. Parkinson’s disease: a genetic per- DiMauro, S., Hirano, M., 2009. Pathogenesis and treatment of mito- spective. FEBS J. 275 (7), 1377–1383. chondrial disorders. Adv. Exp. Med. Biol. 652, 139–170. Bellcross, C.A., Page, P.Z., Meaney-Delman, D., 2012. Direct-to-con- Dinwiddie, D.L., Smith, L.D., Miller, N.A., et al., 2013. Diagnosis of sumer personal genome testing and cancer risk prediction. Cancer mitochondrial disorders by concomitant next-generation sequenc- J. 18 (4), 293–302. ing of the exome and mitochondrial genome. Genomics 102 (3), Bhidayasiri, R., Perlman, S.L., Pulst, S.M., et al., 2005. Late-onset Frie- 148–156. dreich ataxia: phenotypic analysis, magnetic resonance imaging Du, L., Kayali, R., Bertoni, C., et al., 2011. Arginine-rich cell-penetrating findings, and review of the literature. Arch. Neurol. 62 (12), peptide dramatically enhances AMO-mediated ATM aberrant splic- 1865–1869. ing correction and enables delivery to brain and cerebellum. Hum. Brady, O.A., Zheng, Y., Murphy, K., et al., 2013. The frontotemporal Mol. Genet. 20 (16), 3151–3160. lobar degeneration risk factor, TMEM106B, regulates lysosomal Du, L., Pollard, J.M., Gatti, R.A., 2007. Correction of prototypic ATM morphology and function. Hum. Mol. Genet. 22 (4), 685–695. splicing mutations and aberrant ATM function with antisense mor- Brownstein, C.A., Margulies, D.M., Manzi, S.F., 2014. Misinterpreta- pholino oligonucleotides. Proc. Natl. Acad. Sci. U.S.A. 104 (14), tion of TPMT by a DTC genetic testing company. Clin. Pharmacol. 6007–6012. Ther. 95 (6), 598–600. Edwards, T.L., Scott, W.K., Almonte, C., et al., 2010. Genome-wide Bucan, M., Abrahams, B.S., Wang, K., et al., 2009. Genome-wide anal- association study confirms SNPs in SNCA and the MAPT region as yses of exonic copy number variants in a family-based study point common risk factors for Parkinson disease. Ann. Hum. Genet. 74 to novel autism susceptibility genes. PLoS Genet. 5 (6), e1000536. (2), 97–109. Burgard, P., Bremer, H.J., Buhrdel, P., et al., 1999. Rationale for the Elsayed, S.M., Heller, R., Thoenes, M., et al., 2014. Autosomal domi- German recommendations for phenylalanine level control in phe- nant SCA5 and autosomal recessive infantile SCA are allelic condi- nylketonuria, 1997. Eur. J. Pediatr. 158 (1), 46–54. tions resulting from SPTBN2 mutations. Eur. J. Hum. Genet. 22 (2), Cantor, R.M., Geschwind, D.H., 2008. Schizophrenia: genome, inter- 286–288. rupted. Neuron 58 (2), 165–167. Ensenauer, R.E., Michels, V.V., Reinke, S.S., 2005. Genetic testing: prac- Cartier, N., Hacein-Bey-Abina, S., Bartholomae, C.C., et al., 2009. tical, ethical, and counseling considerations. Mayo Clin. Proc. 80 Hematopoietic stem cell gene therapy with a lentiviral vector in (1), 63–73. X-linked adrenoleukodystrophy. Science 326 (5954), 818–823. Fanciulli, M., Petretto, E., Aitman, T.J., 2010. Gene copy number vari- Caylak, E., 2009. The genetics of sleep disorders in humans: nar- ation and common human disease. Clin. Genet. 77 (3), 201–213. colepsy, restless legs syndrome, and obstructive sleep apnea syn- Fang, F., Kamel, F., Lichtenstein, P., et al., 2009. Familial aggregation drome. Am. J. Med. Genet. A 149A (11), 2612–2626. of amyotrophic lateral sclerosis. Ann. Neurol. 66 (1), 94–99. Chan, A., Pirmohamed, M., Comabella, M., 2011. Pharmacogenomics Filipowicz, W., Bhattacharyya, S.N., Sonenberg, N., 2008. Mechanisms in neurology: current state and future steps. Ann. Neurol. 70 (5), of post-transcriptional regulation by microRNAs: are the answers in 684–697. sight? Nat. Rev. Genet. 9 (2), 102–114. Cho, E., Fogel, B.L., 2013. A family with spinocerebellar ataxia type 5 Finch, N., Carrasquillo, M.M., Baker, M., et al., 2011. TMEM106B regu- found to have a novel missense mutation within a SPTBN2 spectrin lates progranulin levels and the penetrance of FTLD in GRN muta- repeat. Cerebellum 12 (2), 162–164. tion carriers. Neurology 76 (5), 467–474. Choi, B.O., Koo, S.K., Park, M.H., et al., 2012. Exome sequencing is Flossmann, E., Schulz, U.G., Rothwell, P.M., 2004. Systematic review an efficient tool for genetic screening of Charcot-Marie-Tooth of methods and results of studies of the genetic epidemiology of disease. Hum. Mutat. 33 (11), 1610–1615. ischemic stroke. Stroke 35 (1), 212–227.

Flynt, A.S., Lai, E.C., 2008. Biological principles of microRNA- Heron, S.E., Smith, K.R., Bahlo, M., et al., 2012. Missense mutations mediated regulation: shared themes amid diversity. Nat. Rev. Genet. in the sodium-gated potassium channel gene KCNT1 cause severe 9 (11), 831–842. autosomal dominant nocturnal frontal lobe epilepsy. Nat. Genet. Fogel, B.L., Cho, E., Wahnich, A., et al., 2014. Mutation of senataxin 44 (11), 1188–1190. alters disease-specific transcriptional networks in patients with Hindorff, L., MacArthur, J., Morales, J., et al., 2010. A Catalog of ataxia with oculomotor apraxia type 2. Hum. Mol. Genet. 23 (18), Published Genome-Wide Association Studies. Available at: (Accessed July 2010). Fogel, B.L., Lee, H., Deignan, J.L., et al., 2014. Exome sequencing in Holmes, M.V., Shah, T., Vickery, C., et al., 2009. Fulfilling the promise the clinical diagnosis of sporadic or familial cerebellar ataxia. JAMA of personalized medicine? Systematic review and field synopsis of Neurol. 71 (10), 1237–1246. pharmacogenetic studies. PLoS ONE 4 (12), e7960. Fogel, B.L., Vickrey, B.G., Walton-Wetzel, J., et al., 2013. Utilization of Hudson, G., Chinnery, P.F., 2006. Mitochondrial DNA polymerase- genetic testing prior to subspecialist referral for cerebellar ataxia. gamma and human disease. Hum. Mol. Genet. 15 (Spec2), Genet. Test Mol. Biomarkers 17 (8), 588–594. R244–R252. Fogel, B.L., Wexler, E., Wahnich, A., et al., 2012. RBFOX1 regulates Ikram, M.A., Seshadri, S., Bis, J.C., et al., 2009. Genomewide both splicing and transcriptional networks in human neuronal association studies of stroke. N. Engl. J. Med. 360 (17), development. Hum. Mol. Genet. 21 (19), 4171–4186. 1718–1728. Freitag, C.M., 2007. The genetics of autistic disorders and its Johnson, J.O., Mandrioli, J., Benatar, M., et al., 2010. Exome sequenc- clinical relevance: a review of the literature. Mol. Psychiatry 12 (1), ing reveals VCP mutations as a cause of familial ALS. Neuron 68 2–22. (5), 857–864. Gallagher, M.D., Suh, E., Grossman, M., et al., 2014. TMEM106B is a Johnson, J.O., Pioro, E.P., Boehringer, A., et al., 2014. Mutations in genetic modifier of frontotemporal lobar degeneration with the Matrin 3 gene cause familial amyotrophic lateral sclerosis. Nat. C9orf72 hexanucleotide repeat expansions. Acta Neuropathol. 127 Neurosci. 17 (5), 664–666. (3), 407–418. Joshita, S., Umemura, T., Yoshizawa, K., et al., 2010. A2BP1 as a novel Garcia-Arocena, D., Hagerman, P.J., 2010. Advances in understanding susceptible gene for primary biliary cirrhosis in Japanese patients. the molecular basis of FXTAS. Hum. Mol. Genet. 19 (R1), Hum. Immunol. 71 (5), 520–524. R83–R89. Kasperaviciute, D., Catarino, C.B., Heinzen, E.L., et al., 2010. Common Gatz, M., Reynolds, C.A., Fratiglioni, L., et al., 2006. Role of genes and genetic variation and susceptibility to partial epilepsies: a genome- environments for explaining Alzheimer disease. Arch. Gen. Psychia- wide association study. Brain 133 (Pt 7), 2136–2147. try 63 (2), 168–174. Kinali, M., Arechavala-Gomeza, V., Feng, L., et al., 2009. Local restora- Geschwind, D., Spence, S., 2008. Genetics of autism. Continuum tion of dystrophin expression with the morpholino oligomer (N Y) 14 (2), 49–64. AVI-4658 in Duchenne muscular dystrophy: a single-blind, placebo- Geschwind, D.H., 2003. DNA microarrays: translation of the genome controlled, dose-escalation, proof-of-concept study. Lancet Neurol. from laboratory to clinic. Lancet Neurol. 2 (5), 275–282. 8 (10), 918–928. Geschwind, D.H., Boone, K.B., Miller, B.L., et al., 2000. Neurobehav- Kishnani, P.S., Corzo, D., Nicolino, M., et al., 2007. Recombinant ioral phenotype of Klinefelter syndrome. Ment. Retard. Dev. Disabil. human acid [alpha]-glucosidase: major clinical benefits in infantile- Res. Rev. 6 (2), 107–116. onset Pompe disease. Neurology 68 (2), 99–109. Geschwind, D.H., Konopka, G., 2009. Neuroscience in the era of Kjeldsen, M.J., Corey, L.A., Christensen, K., et al., 2003. Epileptic sei- functional genomics and systems biology. Nature 461 (7266), zures and syndromes in twins: the importance of genetic factors. 908–915. Epilepsy Res. 55 (1–2), 137–146. Gonzales, M.L., LaSalle, J.M., 2010. The role of MeCP2 in brain devel- Knopman, D.S., DeKosky, S.T., Cummings, J.L., et al., 2001. Practice opment and neurodevelopmental disorders. Curr. Psychiatry Rep. parameter: diagnosis of dementia (an evidence-based review). 12 (2), 127–134. Report of the Quality Standards Subcommittee of the American Gottesfeld, J.M., Rusche, J.R., Pandolfo, M., 2013. Increasing frataxin Academy of Neurology. Neurology 56 (9), 1143–1153. gene expression with histone deacetylase inhibitors as a therapeutic Konopka, G., Bomar, J.M., Winden, K., et al., 2009. Human-specific approach for Friedreich’s ataxia. J. Neurochem. 126 (Suppl. 1), transcriptional regulation of CNS development genes by FOXP2. 147–154. Nature 462 (7270), 213–217. Griffiths, A.J.F., Gelbart, W.M., Lewontin, R.C., et al., 2002. Modern Koolen, D.A., Pfundt, R., de Leeuw, N., et al., 2009. Genomic microar- Genetic Analysis: Integrating Genes and Genomes, second ed. W. rays in mental retardation: a practical workflow for diagnostic appli- H. Freeman & Co., New York. cations. Hum. Mutat. 30 (3), 283–292. Gupta, N., Henry, R.G., Strober, J., et al., 2012. Neural stem cell Kotzot, D., 2008. Complex and segmental uniparental disomy engraftment and myelination in the human brain. Sci. Transl. Med. updated. J. Med. Genet. 45 (9), 545–556. 4 (155), 155ra137. Kovaleva, N.V., Shaffer, L.G., 2003. Under-ascertainment of mosaic Hafler, D.A., Compston, A., Sawcer, S., et al., 2007. Risk alleles for carriers of balanced homologous acrocentric translocations and iso- multiple sclerosis identified by a genomewide study. N. Engl. J. chromosomes. Am. J. Med. Genet. A 121A (2), 180–187. Med. 357 (9), 851–862. Lai, C.S., Fisher, S.E., Hurst, J.A., et al., 2001. A forkhead-domain gene Hallmayer, J., Faraco, J., Lin, L., et al., 2009. Narcolepsy is strongly is mutated in a severe speech and language disorder. Nature 413 associated with the T-cell receptor alpha locus. Nat. Genet. 41 (6), (6855), 519–523. 708–711. Lalande, M., Calciano, M.A., 2007. Molecular epigenetics of Angelman Handel, A.E., Giovannoni, G., Ebers, G.C., et al., 2010. Environmental syndrome. Cell. Mol. Life Sci. 64 (7–8), 947–960. factors and their timing in adult-onset multiple sclerosis. Nat. Rev. Lambert, J.C., Heath, S., Even, G., et al., 2009. Genome-wide associa- Neurol. 6 (3), 156–166. tion study identifies variants at CLU and CR1 associated with Alzhe- Harold, D., Abraham, R., Hollingworth, P., et al., 2009. Genome-wide imer’s disease. Nat. Genet. 41 (10), 1094–1099. association study identifies variants at CLU and PICALM associated Lee, Y.C., Durr, A., Majczenko, K., et al., 2012. Mutations in KCND3 with Alzheimer’s disease. Nat. Genet. 41 (10), 1088–1093. cause spinocerebellar ataxia type 22. Ann. Neurol. 72 (6), Hawkes, C.H., Macgregor, A.J., 2009. Twin studies and the heritability 859–869. of MS., a conclusion. Mult. Scler. 15 (6), 661–667. Lee, C., Scherer, S.W., 2010. The clinical context of copy number vari- Hedges, D.J., Burges, D., Powell, E., et al., 2009. Exome sequencing ation in the human genome. Expert Rev. Mol. Med. 12, e8. of a multigenerational human pedigree. PLoS ONE 4 (12), Levine, A.J., Miller, J.A., Shapshak, P., et al., 2013. Systems analysis of e8232. human brain gene expression: mechanisms for HIV-associated neu- Heinzen, E.L., Swoboda, K.J., Hitomi, Y., et al., 2012. De novo muta- rocognitive impairment and common pathways with Alzheimer’s tions in ATP1A3 cause alternating hemiplegia of childhood. Nat. disease. BMC Med. Genomics 6, 4. Genet. 44 (9), 1030–1034. LeWitt, P.A., Rezai, A.R., Leehey, M.A., et al., 2011. AAV2-GAD gene Helbig, I., Scheffer, I.E., Mulley, J.C., et al., 2008. Navigating the chan- therapy for advanced Parkinson’s disease: a double-blind, sham- nels and beyond: unravelling the genetics of the epilepsies. Lancet surgery controlled, randomised trial. Lancet Neurol. 10 (4), Neurol. 7 (3), 231–245. 309–319.

Li, Y., Chen, J.A., Sears, R.L., et al., 2014. An epigenetic signature in Mohan, A., Goodwin, M., Swanson, M.S., 2014. RNA-protein peripheral blood associated with the haplotype on 17q21.31, a risk interactions in unstable microsatellite diseases. Brain Res. 1584, 50 factor for neurodegenerative tauopathy. PLoS Genet. 10 (3), 3–14. e1004211. Morrow, E.M., Yoo, S.Y., Flavell, S.W., et al., 2008. Identifying autism Licatalosi, D.D., Darnell, R.B., 2010. RNA processing and its regula- loci and genes by tracing recent shared ancestry. Science 321 (5886), tion: global insights into biological networks. Nat. Rev. Genet. 11 218–223. (1), 75–87. Moser, H.W., Raymond, G.V., Dubey, P., 2005. Adrenoleukodystrophy: Lill, C.M., Roehr, J.T., McQueen, M.B., et al., 2012. Comprehensive new approaches to a neurodegenerative disease. JAMA 294 (24), research synopsis and systematic meta-analyses in Parkinson’s 3131–3134. disease genetics: The PDGene database. PLoS Genet. 8 (3), Mullen, S.A., Crompton, D.E., Carney, P.W., et al., 2009. A neurolo- e1002548. gist’s guide to genome-wide association studies. Neurology 72 (6), Link, E., Parish, S., Armitage, J., et al., 2008. SLCO1B1 variants and 558–565. statin-induced myopathy—a genomewide study. N. Engl. J. Med. Naj, A.C., Jun, G., Beecham, G.W., et al., 2011. Common variants at 359 (8), 789–799. MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with Lintas, C., Persico, A.M., 2009. Autistic phenotypes and genetic testing: late-onset Alzheimer’s disease. Nat. Genet. 43 (5), 436–441. state-of-the-art for the clinical geneticist. J. Med. Genet. 46 (1), Nakamori, M., Thornton, C., 2010. Epigenetic changes and non- 1–8. coding expanded repeats. Neurobiol. Dis. 39 (1), 21–27. Lise, S., Clarkson, Y., Perkins, E., et al., 2012. Recessive mutations in Nakamura, K., Kodera, H., Akita, T., et al., 2013. De Novo mutations SPTBN2 implicate beta-III spectrin in both cognitive and motor in GNAO1, encoding a Galphao subunit of heterotrimeric G pro- development. PLoS Genet. 8 (12), e1003074. teins, cause epileptic encephalopathy. Am. J. Hum. Genet. 93 (3), Lodish, H., Berk, A., Kaiser, C.A., et al., 2008. Molecular Cell Biology, 496–505. sixth ed. W. H. Freeman, New York. Nemeth, A.H., Kwasniewska, A.C., Lise, S., et al., 2013. Next genera- Lossos, A., Klein, C.J., McEvoy, K.M., et al., 2009. A 63-year-old tion sequencing for molecular diagnosis of neurological disorders woman with urinary incontinence and progressive gait disorder. using ataxias as a model. Brain 136 (Pt 10), 3106–3118. Neurology 72 (18), 1607–1613. Ng, S.B., Buckingham, K.J., Lee, C., et al., 2010. Exome sequencing Lupski, J.R., 2007. Genomic rearrangements and sporadic disease. Nat. identifies the cause of a mendelian disorder. Nat. Genet. 42 (1), Genet. 39 (Suppl. 7), S43–S47. 30–35. Lupski, J.R., Reid, J.G., Gonzaga-Jauregui, C., et al., 2010. Whole- Ng, S.B., Turner, E.H., Robertson, P.D., et al., 2009. Targeted capture genome sequencing in a patient with Charcot-Marie-Tooth neu- and massively parallel sequencing of 12 human exomes. Nature 461 ropathy. N. Engl. J. Med. 362 (13), 1181–1191. (7261), 272–276. McCarthy, M.I., Abecasis, G.R., Cardon, L.R., et al., 2008. Genome- Online Mendelian Inheritance in Man (OMIM), 2014. McKusick- wide association studies for complex traits: consensus, uncertainty Nathans Institute of Genetic Medicine, Johns Hopkins University and challenges. Nat. Rev. Genet. 9 (5), 356–369. (Baltimore, MD). Available at: (Accessed April McCormack, M., Alfirevic, A., Bourgeois, S., et al., 2011. HLA-A*3101 2014). and carbamazepine-induced hypersensitivity reactions in Europe- Oostra, B.A., Willemsen, R., 2009. FMR1: a gene with three faces. ans. N. Engl. J. Med. 364 (12), 1134–1143. Biochim. Biophys. Acta 1790 (6), 467–477. MacDermot, K.D., Bonora, E., Sykes, N., et al., 2005. Identification of Orr, H.T., Zoghbi, H.Y., 2007. Trinucleotide repeat disorders. Annu. FOXP2 truncation as a novel cause of developmental speech and Rev. Neurosci. 30, 575–621. language deficits. Am. J. Hum. Genet. 76 (6), 1074–1080. Ortega-Recalde, O., Vergara, J.I., Fonseca, D.J., et al., 2013. Whole- McGinn, S., Gut, I.G., 2013. DNA sequencing—spanning the genera- exome sequencing enables rapid determination of xeroderma pig- tions. N. Biotechnol. 30 (4), 366–372. mentosum molecular etiology. PLoS ONE 8 (6), e64692. Manolio, T.A., Collins, F.S., Cox, N.J., et al., 2009. Finding the Ozeki, T., Mushiroda, T., Yowang, A., et al., 2011. Genome-wide asso- missing heritability of complex diseases. Nature 461 (7265), ciation study identifies HLA-A*3101 allele as a genetic risk factor for 747–753. carbamazepine-induced cutaneous adverse drug reactions in Japa- Manzur, A.Y., Kuntzer, T., Pike, M., et al., 2008. Glucocorticoid corti- nese population. Hum. Mol. Genet. 20 (5), 1034–1041. costeroids for Duchenne muscular dystrophy. Cochrane Database Palfi, S., Gurruchaga, J.M., Ralph, G.S., et al., 2014. Long-term safety Syst. Rev. (1), CD003725. and tolerability of ProSavin, a lentiviral vector-based gene therapy Mardis, E.R., 2013. Next-generation sequencing platforms. Annu. Rev. for Parkinson’s disease: a dose escalation, open-label, phase 1/2 Anal. Chem. (Palo Alto Calif) 6, 287–303. trial. Lancet 383 (9923), 1138–1146. Margolin, D.H., Kousi, M., Chan, Y.M., et al., 2013. Ataxia, dementia, Pan, Q., Shai, O., Lee, L.J., et al., 2008. Deep surveying of alternative and hypogonadotropism caused by disordered ubiquitination. N. splicing complexity in the human transcriptome by high-throughput Engl. J. Med. 368 (21), 1992–2003. sequencing. Nat. Genet. 40 (12), 1413–1415. Marshall, C.R., Noor, A., Vincent, J.B., et al., 2008. Structural variation Penagarikano, O., Abrahams, B.S., Herman, E.I., et al., 2011. Absence of chromosomes in autism spectrum disorder. Am. J. Hum. Genet. of CNTNAP2 leads to epilepsy, neuronal migration abnormalities, 82 (2), 477–488. and core autism-related deficits. Cell 147 (1), 235–246. Martin, C.L., Duvall, J.A., Ilkin, Y., et al., 2007. Cytogenetic and molec- Penagarikano, O., Geschwind, D.H., 2012. What does CNTNAP2 ular characterization of A2BP1/FOX1 as a candidate gene for reveal about autism spectrum disorder? Trends Mol. Med. 18 (3), autism. Am. J. Med. Genet. B Neuropsychiatr. Genet. 144 (7), 156–163. 869–876. Penagarikano, O., Mulle, J.G., Warren, S.T., 2007. The pathophysiol- Matarin, M., Singleton, A., Hardy, J., et al., 2010. The genetics of ogy of fragile x syndrome. Annu. Rev. Genomics Hum. Genet. 8, ischaemic stroke. J. Intern. Med. 267 (2), 139–155. 109–129. Meschia, J.F., 2009. Pharmacogenetics and stroke. Stroke 40 (11), Pertea, M., Salzberg, S.L., 2010. Between a chicken and a grape: esti- 3641–3645. mating the number of human genes. Genome Biol. 11 (5), 206. Metzker, M.L., 2010. Sequencing technologies—the next generation. Picardi, E., Pesole, G., 2012. Mitochondrial genomes gleaned from Nat. Rev. Genet. 11 (1), 31–46. human whole-exome sequencing. Nat. Methods 9 (6), 523–524. Miller, D.T., Adam, M.P., Aradhya, S., et al., 2010. Consensus state- Pinto, D., Pagnamenta, A.T., Klei, L., et al., 2010. Functional impact ment: chromosomal microarray is a first-tier clinical diagnostic test of global rare copy number variation in autism spectrum disorders. for individuals with developmental disabilities or congenital anom- Nature 466 (7304), 368–372. alies. Am. J. Hum. Genet. 86 (5), 749–764. Plomin, R., Haworth, C.M., Davis, O.S., 2009. Common disorders are Miller, J.A., Horvath, S., Geschwind, D.H., 2010. Divergence of human quantitative traits. Nat. Rev. Genet. 10 (12), 872–878. and mouse brain transcriptome highlights Alzheimer disease path- Presson, A.P., Sobel, E.M., Papp, J.C., et al., 2008. Integrated weighted ways. Proc. Natl. Acad. Sci. U.S.A. 107 (28), 12698–12703. gene co-expression network analysis with an application to chronic Miller, J.A., Oldham, M.C., Geschwind, D.H., 2008. A systems level fatigue syndrome. BMC Syst Biol 2, 95. analysis of transcriptional changes in Alzheimer’s disease and Pulst, S.M., 2003. Neurogenetics: single gene disorders. J. Neurol. normal aging. J. Neurosci. 28 (6), 1410–1420. Neurosurg. Psychiatry 74 (12), 1608–1614.

Purcell, S.M., Wray, N.R., Stone, J.L., et al., 2009. Common polygenic Speicher, M.R., Carter, N.P., 2005. The new cytogenetics: blurring the variation contributes to risk of schizophrenia and bipolar disorder. boundaries with molecular biology. Nat. Rev. Genet. 6 (10), Nature 460 (7256), 748–752. 782–792. Qureshi, I.A., Mehler, M.F., 2013. Understanding neurological disease Spencer, H.G., 2009. Effects of genomic imprinting on quantitative mechanisms in the era of epigenetics. JAMA Neurol. 70 (6), traits. Genetica 136 (2), 285–293. 703–710. Stankiewicz, P., Lupski, J.R., 2010. Structural variation in the human Rafii, M.S., Baumann, T.L., Bakay, R.A., et al., 2014. A phase1 study of genome and its role in disease. Annu. Rev. Med. 61, 437–455. stereotactic gene delivery of AAV2-NGF for Alzheimer’s disease. Stefansson, H., Rujescu, D., Cichon, S., et al., 2008. Large recurrent Alzheimers Dement. 10 (5), 571–581. microdeletions associated with schizophrenia. Nature 455 (7210), Rai, M., Soragni, E., Jenssen, K., et al., 2008. HDAC inhibitors correct 232–236. frataxin deficiency in a Friedreich ataxia mouse model. PLoS ONE Stefansson, H., Rye, D.B., Hicks, A., et al., 2007. A genetic risk factor 3 (4), e1958. for periodic limb movements in sleep. N. Engl. J. Med. 357 (7), Redon, R., Ishikawa, S., Fitch, K.R., et al., 2006. Global variation in 639–647. copy number in the human genome. Nature 444 (7118), Strachan, T., Read, A.P., 2003. Human Molecular Genetics, third ed. 444–454. Garland Science, London. Reis, J., Roman, G.C., 2007. Environmental neurology: a promising Strauss, K.A., Puffenberger, E.G., Huentelman, M.J., et al., 2006. Reces- new field of practice and research. J. Neurol. Sci. 262 (1–2), 3–6. sive symptomatic focal epilepsy and mutant contactin-associated Rodriguez-Lebron, E., Costa, M., Luna-Cancalon, K., et al., 2013. protein-like 2. N. Engl. J. Med. 354 (13), 1370–1377. Silencing mutant ATXN3 expression resolves molecular phenotypes Sweeny, K., Ghane, A., Legg, A.M., et al., 2014. Predictors of genetic in SCA3 transgenic mice. Mol. Ther. 21 (10), 1909–1918. testing decisions: a systematic review and critique of the literature. Rohrer, J.D., Guerreiro, R., Vandrovcova, J., et al., 2009. The heritabil- J. Genet. Couns. 23 (3), 263–288. ity and genetics of frontotemporal lobar degeneration. Neurology Swen, J.J., Huizinga, T.W., Gelderblom, H., et al., 2007. Translating 73 (18), 1451–1456. pharmacogenomics: challenges on the road to the clinic. PLoS Med. Rosenfeld, J.A., Malhotra, A.K., Lencz, T., 2010. Novel multi-nucleotide 4 (8), e209. polymorphisms in the human genome characterized by whole Thusberg, J., Olatubosun, A., Vihinen, M., 2011. Performance of muta- genome and exome sequencing. Nucleic. Acids. Res. tion pathogenicity prediction methods on missense variants. Hum. Sailer, A., Scholz, S.W., Gibbs, J.R., et al., 2012. Exome sequencing in Mutat. 32 (4), 358–368. an SCA14 family demonstrates its utility in diagnosing heterogene- Todd, P.K., Oh, S.Y., Krans, A., et al., 2013. CGG repeat-associated ous diseases. Neurology 79 (2), 127–131. translation mediates neurodegeneration in fragile X tremor ataxia Sanderson, S., Emery, J., Higgins, J., 2005. CYP2C9 gene variants, drug syndrome. Neuron 78 (3), 440–455. dose, and bleeding risk in warfarin-treated patients: a HuGEnet Torkamani, A., Dean, B., Schork, N.J., et al., 2010. Coexpression systematic review and meta-analysis. Genet. Med. 7 (2), 97–104. network analysis of neural tissue reveals perturbations in develop- Sanna, S., Pitzalis, M., Zoledziewska, M., et al., 2010. Variants within mental processes in schizophrenia. Genome Res. 20 (4), 403–412. the immunoregulatory CBLB gene are associated with multiple scle- Traynor, B.J., 2009. The era of genomic epidemiology. Neuroepidemi- rosis. Nat. Genet. 42 (6), 495–497. ology 33 (3), 276–279. Saris, C.G., Horvath, S., van Vught, P.W., et al., 2009. Weighted gene Underwood, J.G., Boutz, P.L., Dougherty, J.D., et al., 2005. Homo- co-expression network analysis of the peripheral blood from amyo- logues of the Caenorhabditis elegans Fox-1 protein are neuronal splic- trophic lateral sclerosis patients. BMC Genomics 10, 405. ing regulators in mammals. Mol. Cell. Biol. 25 (22), Satake, W., Nakabayashi, Y., Mizuta, I., et al., 2009. Genome-wide 10005–10016. association study identifies common variants at four loci as genetic van Blitterswijk, M., Mullen, B., Nicholson, A.M., et al., 2014. risk factors for Parkinson’s disease. Nat. Genet. 41 (12), TMEM106B protects C9ORF72 expansion carriers against fronto- 1303–1307. temporal dementia. Acta Neuropathol. 127 (3), 397–406. Sawyer, S.L., Schwartzentruber, J., Beaulieu, C.L., et al., 2014. Exome Van Deerlin, V.M., Sleiman, P.M., Martinez-Lage, M., et al., 2010. sequencing as a diagnostic tool for pediatric-onset ataxia. Hum. Common variants at 7p21 are associated with frontotemporal lobar Mutat. 35 (1), 45–49. degeneration with TDP-43 inclusions. Nat. Genet. 42 (3), Schork, N.J., Murray, S.S., Frazer, K.A., et al., 2009. Common vs. rare 234–239. allele hypotheses for complex diseases. Curr. Opin. Genet. Dev. 19 van Es, M.A., Veldink, J.H., Saris, C.G., et al., 2009. Genome-wide (3), 212–219. association study identifies 19p13.3 (UNC13A) and 9p21.2 as sus- Schormair, B., Kemlink, D., Roeske, D., et al., 2008. PTPRD (protein ceptibility loci for sporadic amyotrophic lateral sclerosis. Nat. tyrosine phosphatase receptor type delta) is associated with restless Genet. 41 (10), 1083–1087. legs syndrome. Nat. Genet. 40 (8), 946–948. van Swieten, J.C., Heutink, P., 2008. Mutations in progranulin (GRN) Sebat, J., Lakshmi, B., Malhotra, D., et al., 2007. Strong association of within the spectrum of clinical and pathological phenotypes of de novo copy number mutations with autism. Science 316 (5823), frontotemporal dementia. Lancet Neurol. 7 (10), 965–974. 445–449. Vaughan, J.R., Davis, M.B., Wood, N.W., 2001. Genetics of parkinson- Seshadri, S., Fitzpatrick, A.L., Ikram, M.A., et al., 2010. Genome-wide ism: a review. Ann. Hum. Genet. 65 (Pt 2), 111–126. analysis of genetic loci associated with Alzheimer disease. JAMA 303 Vernes, S.C., Newbury, D.F., Abrahams, B.S., et al., 2008. A functional (18), 1832–1840. genetic link between distinct developmental language disorders. N. Sharma, M., Ioannidis, J.P., Aasly, J.O., et al., 2012. Large-scale replica- Engl. J. Med. 359 (22), 2337–2345. tion and heterogeneity in Parkinson disease genetic loci. Neurology Wain, L.V., Armour, J.A., Tobin, M.D., 2009. Genomic copy number 79 (7), 659–667. variation, human health, and disease. Lancet 374 (9686), Shchelochkov, O.A., Cheung, S.W., Lupski, J.R., 2010. Genomic and 340–350. clinical characteristics of microduplications in chromosome 17. Walsh, T., McClellan, J.M., McCarthy, S.E., et al., 2008. Rare structural Am. J. Med. Genet. A 152A (5), 1101–1110. variants disrupt multiple genes in neurodevelopmental pathways in Shen, H., Li, J., Zhang, J., et al., 2013. Comprehensive characterization schizophrenia. Science 320 (5875), 539–543. of human genome variation by high coverage whole-genome Wang, J.L., Yang, X., Xia, K., et al., 2010. TGM6 identified as a novel sequencing of forty four Caucasians. PLoS ONE 8 (4), e59494. causative gene of spinocerebellar ataxias using exome sequencing. Simon-Sanchez, J., Schulte, C., Bras, J.M., et al., 2009. Genome-wide Brain 133 (Pt 12), 3510–3518. association study reveals genetic risk underlying Parkinson’s disease. Wang, K., Zhang, H., Ma, D., et al., 2009. Common genetic variants Nat. Genet. 41 (12), 1308–1312. on 5p14.1 associate with autism spectrum disorders. Nature 459 Simon-Sanchez, J., Singleton, A., 2008. Genome-wide association (7246), 528–533. studies in neurological disorders. Lancet Neurol. 7 (11), Ward, A.J., Cooper, T.A., 2010. The pathobiology of splicing. J. Pathol. 1067–1072. 220 (2), 152–163. Singleton, A.B., Farrer, M., Johnson, J., et al., 2003. alpha-Synuclein Weinberg, M.S., Wood, M.J., 2009. Short non-coding RNA biology and locus triplication causes Parkinson’s disease. Science 302 (5646), neurodegenerative disorders: novel disease targets and therapeutics. 841. Hum. Mol. Genet. 18 (R1), R27–R39.

Weiss, L.A., Arking, D.E., Daly, M.J., et al., 2009. A genome-wide Yngvadottir, B., Xue, Y., Searle, S., et al., 2009. A genome-wide survey linkage and association scan reveals novel loci for autism. Nature of the prevalence and evolutionary forces acting on human non- 50 461 (7265), 802–808. sense SNPs. Am. J. Hum. Genet. 84 (2), 224–234. Wellcome Trust Case Control Consortium, 2007. Genome-wide asso- Zeviani, M., Carelli, V., 2007. Mitochondrial disorders. Curr. Opin. ciation study of 14,000 cases of seven common diseases and 3,000 Neurol. 20 (5), 564–571. shared controls. Nature 447 (7145), 661–678. Zhai, G., van Meurs, J.B., Livshits, G., et al., 2009. A genome-wide Wheeler, T.M., Sobczak, K., Lueck, J.D., et al., 2009. Reversal of RNA association study suggests that a locus within the ataxin 2 binding dominance by displacement of protein sequestered on triplet repeat protein 1 gene is associated with hand osteoarthritis: the Treat-OA RNA. Science 325 (5938), 336–339. consortium. J. Med. Genet. 46 (9), 614–616. Winden, K.D., Karsten, S.L., Bragin, A., et al., 2011. A systems level, Zhang, C., Zhang, Z., Castle, J., et al., 2008. Defining the regulatory functional genomics analysis of chronic epilepsy. PLoS ONE 6 (6), network of the tissue-specific splicing factors Fox-1 and Fox-2. e20763. Genes Dev. 22 (18), 2550–2563. Winkelmann, J., Schormair, B., Lichtner, P., et al., 2007. Genome- Zhang, F., Gu, W., Hurles, M.E., et al., 2009. Copy number variation wide association study of restless legs syndrome identifies in human health, disease, and evolution. Annu. Rev. Genomics common variants in three genomic regions. Nat. Genet. 39 (8), Hum. Genet. 10, 451–481. 1000–1006. Zhou, Q., Yang, D., Ombrello, A.K., et al., 2014. Early-onset stroke Wood, M.J., Gait, M.J., Yin, H., 2010. RNA-targeted splice-correction and vasculopathy associated with mutations in ADA2. N. Engl. J. therapy for neuromuscular disease. Brain 133 (Pt 4), 957–972. Med. 370 (10), 911–920. Wu, C.H., Fallini, C., Ticozzi, N., et al., 2012. Mutations in the profilin Zimprich, A., Biskup, S., Leitner, P., et al., 2004. Mutations in LRRK2 1 gene cause familial amyotrophic lateral sclerosis. Nature 488 cause autosomal-dominant parkinsonism with pleomorphic (7412), 499–503. pathology. Neuron 44 (4), 601–607. Yeo, G.W., Coufal, N.G., Liang, T.Y., et al., 2009. An RNA code for the Zlotogora, J., 2004. Parents of children with autosomal recessive dis- FOX2 splicing regulator revealed by mapping RNA-protein interac- eases are not always carriers of the respective mutant alleles. Hum. tions in stem cells. Nat. Struct. Mol. Biol. 16 (2), 130–137. Genet. 114 (6), 521–526.