Downloaded from http://cshperspectives.cshlp.org/ on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press Molecular Genetics of Neurodegenerative Dementias Flora I. Hinz1 and Daniel H. Geschwind1,2 1Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90095 2Center for Autism Research and Treatment and Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California 90024 Correspondence: [email protected] Neurodegenerative dementias are clinically heterogeneous, progressive diseases with fre- quently overlapping symptoms, such as cognitive impairments and behavior and movement deficits. Although a majority of cases appear to be sporadic, there is a large genetic compo- nent that has yet to be fully explained. Here, we review the recent genetic and genomic findings pertaining to Alzheimer’s disease, frontotemporal dementia, Lewy body dementia, and prion dementia. In this review, we describe causal and susceptibility genes identified for these dementias and discuss recent research pertaining to the molecular function of these genes. Of particular interest, there is a large overlap in clinical phenotypes, genes, and/or aggregating protein products involved in these diseases, as well as frequent comorbid pre- sentation, indicating that these dementias may represent a continuum of syndromes rather than individual diseases. eurodegenerative dementias are clinically double roughly every 20 years. Of these demen- Nheterogeneous, progressive diseases with tias, AD is by far the most frequent, comprising frequently overlapping symptoms, such as cog- 50%–75% of all cases (Fig. 1) (Prince et al. nitive impairments and behavior and move- 2014). ment deficits. This spectrum of disease includes Over the last few decades, substantial pro- vascular dementia (VaD), Lewy body dementia gress has been made in understanding the (LBD), Alzheimer’s disease (AD), frontotem- molecular genetics of neurodegenerative de- poral dementia (FTD), and prion dementias mentias and identifying the pathologically (Fig. 1). Recent estimates indicate that 5.9%– aggregating proteins involved. In large part, 9.4% of people .65 years of age suffer from this can be attributed to advances in sequenc- dementia, with approximately 44 million affect- ing techniques and bioinformatic analysis ap- ed worldwide (Prince et al. 2014). Moreover, as proaches. Beginning in the early 1990s with the a result of our aging population, the number of identification of microsatellites (also known as people affected with dementia is expected to short tandem repeats) and single nucleotide Editor: Stanley B. Prusiner Additional Perspectives on Prion Biology available at www.cshperspectives.org Copyright # 2017 Cold Spring Harbor Laboratory Press; all rights reserved; doi: 10.1101/cshperspect.a023705 Cite this article as Cold Spring Harb Perspect Biol 2017;9:a023705 1 Downloaded from http://cshperspectives.cshlp.org/ on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press F.I. Hinz and D.H. Geschwind GRN [3%–25%] 0%–50% C9ORF72 [~25%] MAPT Sporadic Familial ~15% 25%–50% 50%–75% APP VaD ~80% 20%–30% FTD Familial PSEN1 5%–15% <5% PSEN2 [~5%] LBD Sporadic 4.2%–7.5% AD SNCA [<1%] 50%–75% Sporadic >95% Figure 1. Frequency of specific neurodegenerative dementias. The inner circle shows the frequency of specific neurodegenerative dementias (indicated by different colors) as an approximate percentage of all cases of disease. The middle circle shows the percentage of patients that show familial or sporadic patterns of inheritance for each disease. The outer circle depicts the approximate percent of patients with familial inheritance patterns that harbor mutations in specific known causal genes. polymorphisms (SNPs), researchers began to analysis, the majority of disease genes involved apply an approach termed linkage analysis. in these familial, often early-onset cases were This technique makes use of these genomic discovered. More recently, genome-wide associ- markers to identify chromosomal regions ation studies (GWAS) have been applied to shared by affected family members in large identify a multitude of risk variants (mutations families with apparent dominant transmission. with low penetrance) in idiopathic dementia. The assumption is that the pathogenic muta- This new approach was enabled by the develop- tion lies within this shared chromosomal re- ment of comprehensive genome-wide arrays, gion, which carries disease risk, as it segregates allowing for the simultaneous evaluation of with the disease in the family. Linkage analysis millions of SNPs in thousands of samples in a led to the rapid identification of a number of cost-effective manner. GWAS, by comparing highly penetrant disease-causing mutations the SNPs of millions of patients to SNPs from (Kerem et al. 1989; MacDonald et al. 1993; millions of unaffected controls, are used to Ha¨stbacka et al. 1994; Feder et al. 1996; Poorkaj identify genetic variants that are common in et al. 1998; Amir et al. 1999). the population but modulate the risk of disease. However, only a small subset (5%) of Recently, GWAS and, subsequently, meta-anal- neurodegenerative dementia cases show a pat- yses of GWAS,which pool samples from multi- tern of autosomal dominant inheritance, ple studies to increase statistical power, have led whereas most cases appear to be sporadic. Early to the identification of hundreds of mutations on, using genetic approaches such as linkage in so-called susceptibility genes, most with very 2 Cite this article as Cold Spring Harb Perspect Biol 2017;9:a023705 Downloaded from http://cshperspectives.cshlp.org/ on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press Molecular Genetics of Neurodegenerative Dementias small effect sizes (odds ratios usually ,2; for ALZHEIMER’S DISEASE review, see Visscher et al. 2012). Although the By far the most common form of age-related effect size of these variants is not large enough dementia, AD is clinically heterogeneous and to inform disease prediction, these loci may slowly progressive, characterized by a gradual shed light on novel genes and molecular path- decline in memory and other cognitive func- ways dysregulated in disease. However, it is im- tions (such as anomia, agnosia, and apraxia), portant to keep in mind that GWASuse SNPs as depression, and apathy (www.alz.org/research/ proxies for tagging chromosomal regions. Thus, diagnostic_criteria). The brain regions most this type of analysis can determine that a spe- affected by neurodegeneration are the cortex, cific SNP or genomic locus is associated with hippocampus, amygdala, basal forebrain, and disease risk, but does not necessarily mean brainstem (Rademakers and Rovelet-Lecrux that a particular SNP functionally contributes 2009). Progressive atrophy in these regions is to disease risk or which gene in a genomic locus preceded by the accumulation of extracellular may be associated with the pathology. b-amyloid plaques formed by cleavage products In the past few years, with the cost of se- of amyloid precursor protein (APP) and intra- quencing dropping and bioinformatics tech- cellular neurofibrillary tangles (NFTs) com- nology advancing, next-generation sequencing posed of hyperphosphorylated microtubule (NGS) approaches are becoming more com- binding protein tau (MAPT). Plaques and tan- monly used. Rather than limiting sequencing gles have been shown to interfere with calcium to a gene or a small region of the chromosome, signaling and synaptic transmission, to induce a it is now possible to sequence the entire genome persistent inflammatory response, and to lead (whole-genome sequencing, WGS) or only the to synapse loss and ultimately neuronal degen- gene-coding regions, the exons (whole-exome eration. The presence of NFTs is strongly corre- sequencing, WES) (Ng et al. 2009). WES, as a lated with neuronal dysfunction and disease result of focusing on only 2% of the genome, progression (for reviews of AD pathology, see is still considerably cheaper, and the analytical Braak and Braak 1997, 1998; Serrano-Pozo et al. processing power, as well as the storage space 2011). required to handle the data produced, is more AD is classified as early onset (before 65 feasible to acquire for individual laboratories years of age) versus late onset (after 65). Less (Singleton 2011; Wang et al. 2013). Important- than 10% of cases are early onset, and these ly, these NGS approaches allow for the direct usually follow an autosomal dominant inheri- identification of rare variants in disease, with- tance pattern in which mutations in a single out prior linkage or GWAS. As compared to gene can cause the disease. Late-onset AD is WES, WGS has the advantage of better coverage much more common and far more genetically of the exome, owing in part to longer reads and complex, possibly involving concurrent muta- more consistent read depth. Furthermore, WGS tions in multiple genes and interactions among can be used to investigate regulatory variants, these susceptibility genes with each other, as which are increasingly thought to play a signifi- well as unknown environmental factors. Al- cant role in the cause of and risk for neurode- though late-onset AD is largely idiopathic, there generative disease (Wang et al. 2013). is still a significant genetic contribution to sus- Despite these advances, much of the genetic ceptibility, with twin