Exploration of Functional Genetic Variants in Candidate Genes for Psychiatric Disorders
DISSERTATION
Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University
By
Robert A. Moyer
Graduate Program in Integrated Biomedical Science Program
The Ohio State University
2010
Dissertation Committee:
Professor Wolfgang Sadée, Advisor
Professor Rene Anand
Professor R. Thomas Boyd
Professor Howard Gu
Copyright by
Robert A. Moyer
2010 Abstract
Drug addiction is a chronic disorder characterized by compulsive drug seeking and drug taking despite serious negative consequences. While twin studies indicate a significant contribution of genetic factors to an individual’s susceptibility to addiction, identifying and replicating significant genetic associations for addiction has proven difficult.
Association studies have identified a number of candidate genes harboring variants associated with susceptibility to addiction, but the causative variants frequently remain unknown. Instead, the association is found between the disease and a polymorphism that is linked to the causal variant. As allele frequencies and linkage patterns may vary between populations, associations found are frequently not replicated in follow-up studies, in part due to a lack of consideration of the molecular mechanisms underlying the effects of the polymorphisms.
A solution to this problem is the thorough characterization of functional genetic polymorphisms and their effects on regulation of candidate genes for addiction and other psychiatric disorders. Historically, many genetic studies have focused on nonsynonymous single nucleotide polymorphisms (SNPs) that alter amino acid sequence, even though regulatory polymorphisms in non-protein coding regions are likely to be more prevalent. Regulatory polymorphisms can result in altered transcription, alternative splicing, and mRNA folding and stability, to name but a few mechanisms. The first step
ii in our approach is to measure allelic mRNA expression and/or differential expression of functionally distinct splice variants for candidate genes in relevant brain regions from human autopsies. We use these measurements as phenotypic traits to identify causative genetic variants affecting the amount and/or nature of the mRNA. Finally, we test the putative functional variant for association with human phenotype to establish its clinical relevance.
I focused on a number of candidate genes for drug addiction, and made some novel and significant findings: 1) The effects of two intronic SNPs in the human dopamine receptor D2 (DRD2) gene, previously shown to alter DRD2 alternative splicing, were confirmed in human brain autopsy tissues (putamen and prefrontal cortex) obtained from a population of cocaine abusers and controls. The same SNPs were significantly associated with cocaine abuse with an odds ratio of ~2. Furthermore, I detected a significant interaction between these SNPs and a functional variant in the dopamine transporter (DAT) gene in the same population. 2) A synonymous SNP in the human arrestin2 (ARRB2) gene was associated with a small but significant increase in
ARRB2 mRNA expression in prefrontal cortex obtained from Alzheimer’s patients.
However, there was no genotype effect on arrestin2 protein levels in the same samples.
3) I identified a number of samples with significant allelic expression imbalance (AEI) of
DRD3 mRNA in nucleus accumbens obtained from a cohort of normal controls and patients diagnosed with schizophrenia, bipolar disorder, or depression, indicating the presence of a cis-acting regulatory variant affecting mRNA expression. However, none
iii of the 11 SNPs genotyped across the DRD3 gene locus could account for the observed
AEI.
Identification of functional genetic variants and characterization of the underlying molecular genetic mechanisms are critical for interpretation of clinical association studies and selection of valid biomarkers affecting disease susceptibility and treatment response.
The striking association of the DRD2 SNPs with cocaine abuse supports the notion that the modulation of DRD2 alternative splicing is an important regulator of dopaminergic activity with phenotypic consequences, although the data do not prove a causative link between alternative splicing and cocaine abuse. The results of this study contribute to our understanding of the functional genetic variation in three important candidate genes and have the potential to improve the prevention and treatment of drug addiction and other psychiatric disorders.
iv Acknowledgments
I thank my adviser, Dr. Wolfgang Sadée, for teaching me to think and ask questions like a scientist, and for teaching me a great deal about the many other facets to becoming a successful scientist in a relatively short amount of time. I also thank our lab manager, Audrey Papp, for countless helpful discussions about biology, problem solving, and life in general. I thank them both for providing an excellent work environment that allowed me ask and pursue my own questions while keeping me on track. I am also grateful to my committee members, Drs. Rene Anand, R. Thomas Boyd, Howard Gu, and
Lane Wallace, for their time and for their guidance along the way.
I am thankful to the rest of the Sadée laboratory members, both past and present, for their advice, challenging questions, and friendly and often entertaining dicussions:
Ryan Smith, Dr. Danxin Wang, Dr. Julia Pinsonneault, Mandy Zaret, Gloria Smith, Dr.
Ying Zhang, Dave Straka, Diane Delobel, Beth Barrie, Jonathon Sanford, Kumiko
Aizawa, Danielle Sullivan, and Sarah Fritz.
I thank Dr. Laura Bohn, my advisor before she moved to another institution, for getting me started in biomedical research and involving me in collaboration with the
Sadée laboratory before she left. I am also grateful to her for her support and understanding before, during, and after my deployment to Iraq. I also thank the members of her laboratory for all the coaching, collaborating, and some pretty good times both in v and out of the lab: Dr. Kirsten Raehal, Chad Groer, Lori Hudson, Cullen Schmid, and
Alex Jaeger.
I am thankful for the support of IBGP program staff, without whom there would be no Integrated Biomedical Science Graduate Program and who were always there to help me navigate the system successfully: Christine Kerr, Dr. Allan Yates, Dr. Virginia
Sanders, Dr. R. Thomas Boyd, Angie Thomas, Darlene Johns, Amy Lahmers, and Kelly
Dillon. I am also grateful to the Pharmacology Department staff (Sherry Ring, Gina
Pace) for all their patience and help with important paperwork and procedures.
I thank my collaborators outside the laboratory whose work is also presented here:
Dr. Deborah Mash, Linda Duque, Dr. Alessandro Bertolino, and Dr. Maree Webster.
I thank the anonymous tissue donors and their families without whom this work would not have been possible.
I am forever grateful to my parents, Tom and Rose Moyer, who brought me up curious and were always supportive. I would not be the person I am today were it not for their example and the values they instilled in me from very early on.
I thank my wife, Katie, who has been a wonderful mother to our daughter in addition to supporting me every step of the way during this dissertation research. Her patience, kindness, and love throughout all the ups and downs of graduate school
(including my deployment to Iraq right in the middle of it) have been invaluable for me to reach this point.
Finally, I thank my baby daughter Emmalyn, for really opening my eyes and changing my perspective on just about everything.
vi Vita
1992...... Chanel High School
1997...... B.S. in Education, Kent State University
2004 to present ...... Ph.D. in Integrated Biomedical Science, The
Ohio State University
Publications
1. McLennan GP, Kiss A, Miyatake M, Belcheva MM, Chambers KT, Pozek JJ, Mohabbat Y, Moyer RA, Bohn LM, Coscia CJ. Kappa opioids promote the proliferation of astrocytes via G and -arrestin 2-dependent MAPK-mediated pathways. J Neurochem. 2008 Dec;107(6):1753-65.
2. Groer CE, Tidgewell K, Moyer RA, Harding WW, Rothman RB, Prisinzano TE, Bohn LM. An opioid agonist that does not induce -opioid receptor--arrestin interactions or receptor internalization. Mol Pharmacol. 2007 Feb;71(2):549-57.
Fields of Study
Major Field: Integrated Biomedical Science Program
vii Table of Contents
Abstract...... ii
Acknowledgments...... v
Vita...... vii
List of Tables ...... x
List of Figures...... xi
Chapter 1: Introduction...... 1
1.1 Drug addiction and genetics...... 1
1.2 The role of cis-acting regulatory polymorphisms in human genetic variation ...... 3
1.3 Epigenetic Factors...... 5
1.4 Cis-Acting Genetic Regulation of Alternative Splicing...... 7
1.5 Review of DRD2 Genotype-Phenotype Associations...... 7
1.6 Review of ARRB2 Genotype-Phenotype Associations ...... 9
1.7 Review of DRD3 Genotype-Phenotype Associations...... 9
1.8 Summary of the Main Studies...... 10
Chapter 2: Intronic Polymorphisms Affecting Alternative Splicing of Human D2
Receptor are Associated with Cocaine Abuse ...... 13
viii 2.1 Introduction ...... 13
2.2 Materials and Methods...... 17
2.3 Results ...... 20
2.4 Discussion ...... 36
Chapter 3: A Synonymous SNP in ARRB2 is Associated with Increased mRNA
Expression...... 48
3.1 Introduction ...... 48
3.2 Materials and Methods...... 52
3.3 Results ...... 57
3.4 Discussion ...... 67
Chapter 4: Allelic Imbalance in DRD3 mRNA Expression ...... 74
4.1 Introduction ...... 74
4.2 Materials and Methods...... 77
4.3 Results ...... 80
4.4 Discussion ...... 84
Bilbliography ...... 87
ix List of Tables
Table 2.1. Results of sequencing DNA from five samples that displayed different
D2L/D2S allelic ratios…………………………………………………………………...22
Table 2.2. Demographic Characteristics………………………………………………...31
Table 2.3. Pairwise Linkage Disequilibrium Values……………………………………32
Table 2.4. Minor allele frequencies in cocaine abusers and controls, plus results of statistical group comparisons…………………………………………………………….33
Table 2.5. Haplotype Analysis in Cocaine Abusers and Controls………………………35
Table 2.6. DRD2-DAT Gene Interaction………………………………………………..36
Table 2.7. Clinical Associations of SNPs in LD (R2>0.6) with rs2283265…………….45
Table 2.8. Sequences of Oligonucleotides (Primers) Used………………………….46-47
Table 3.1. Demographic Characteristics………………………………………………...71
Table 3.2. Sequences of Oligonucleotides (Primers) Used……………………………...73
Table 4.1. Sequences of Oligonucleotides (Primers) Used……………………………...86
x List of Figures
Figure 1.1. Quantitative allele-specific expression analysis……………………………..5
Figure 2.1. DRD2 gene map, with blown up view of the region that was sequenced…..21
Figure 2.2. Alternative splicing from DRD2 minigenes in HEK 293 cells……………..24
Figure 2.3. DRD2 mRNA expression…………………………………………………...25
Figure 2.4. DRD2 mRNA expression grouped by race and cocaine abuse status……....26
Figure 2.5. Expression of D2S relative to D2L…………………………………………28
Figure 2.6. Expression of D2S relative to D2L grouped by race.………………………29
Figure 2.7. LD plot of surrogate markers for the intron 5 SNP rs2283265 (SNP1) as the seed………………………………………………………………………………………43
Figure 3.1. ARRB2 gene map……………………………………………………………52
Figure 3.2. ARRB2 mRNA expression………………………………………..……..59-60
Figure 3.3. Allelic ARRB2 mRNA expression ratios………………………...………62-63
Figure 3.4. Western Blot………………………………………………………………...65
Figure 3.5. Quantitative detection of ARRB2 mRNA splice variants…………………...67
Figure 3.6. LD plot of the ARRB2 genomic locus………………………………………72
Figure 4.1. DRD3 gene map…………………………………………………………….77
Figure 4.2. Allelic DRD3 mRNA expression ratios…………………………………….81
Figure 4.3. Quantitative detection of DRD3 mRNA splice variants…………………….83
xi Chapter 1: Introduction
1.1 Drug addiction and genetics
Drug addiction is a chronic disorder that is defined by compulsive drug seeking and drug use, even in the face of dire consequences including the loss of job, reputation, home, and family. In addition to their serious negative effects on individuals and families, including failure in work and school, domestic abuse, and other crimes, drug abuse and addiction are a major economic burden to society: Recent estimates for the annual overall costs of substance abuse including lost productivity as well as health- and crime-related costs were $181 billion for illicit drugs (Office of National Drug Control Policy, 2004), $168 billion for tobacco (Centers for Disease Control and Prevention, 2005), and $185 billion for alcohol (Harwood, 2000). By comparison, cancer and diabetes were estimated to carry a cost of $172 billion (American Cancer Society, 2003) and $132 billion (Petersen,
2003), respectively, underscoring the magnitude of the economic impact of drug addiction on society.
It is well documented that the influence on behavior of both addictive drugs and natural rewards is due to their effect of causing an increase in synaptic dopamine levels in the nucleus accumbens (NAc) in the ventral striatum (Wise and Bozarth, 1987; Koob and
1 Bloom, 1988; Di Chiara, 1998; Wise, 1998). The NAc is a part of the mesolimbic dopamine pathway, which originates in the ventral tegmental area (VTA) with projections to the amygdala, hippocampus, and prefrontal cortex (PFC) as well as NAc.
Although the mechanisms differ between drug classes (Johnson and North, 1992; Jones et al., 1998; Tapper et al., 2004; Waldhoer et al. 2004; Justinova et al., 2005), all addictive drugs activate this pathway, which has long been postulated to be critical for their reinforcing properties. Dopamine signaling in the mesolimbic pathway has been intensely studied for its role in addiction, as have many of the genes encoding receptors, enzymes, and other proteins thought to be important for dopaminergic signaling and regulation. Despite these efforts, the genetic mechanisms underlying susceptibility have remained elusive.
Genetic factors contribute to the susceptibility to drug addiction, with multiple candidate genes (Hiroi and Agatsuma, 2005; Howard et al., 2002; Kreek et al., 2004;
Tyndale, 2003). Epidemiological and twin studies have established that 40-60% of an individual’s risk for addiction, whether it is to alcohol, opiates or cocaine, is genetic
(Kendler et al., 1994; Kender et al., 2000; Prescott and Kendler, 1999; Tsuang et al.,
1998). Genetic association studies have identified a number of plausible candidate genes harboring variants associated with susceptibility for addiction, although such associations are often not replicated in follow-up studies (Kreek et al., 2004; Kreek et al., 2005; Le
Foll et al., 2009). A limitation of many phenotype-genotype association studies is a lack of consideration of the mechanisms underlying the effects of polymorphisms,
2 underscoring the importance of identifying functional polymorphisms in candidate genes
and characterizing their molecular genetic effects.
1.2 The role of cis-acting regulatory polymorphisms in human genetic variation
Many association studies have focused on polymorphisms in protein coding regions that
alter the amino acid sequence, though recent studies indicate that regulatory
polymorphisms in non-coding regions occur more frequently and have yet to be
discovered (Bray et al., 2003; Johnson et al., 2005; Rockman and Wray, 2002; Wray,
2007; Yan et al., 2002). Since functional variants altering gene function and directly
contributing to susceptibility are generally not known, the reported associations between
phenotypes and a polymorphism typically rely on a marker SNP in linkage disequilibrium
(LD) with the causal variant. As allele frequencies and LD patterns may vary widely
between populations, results may vary between association studies, underscoring the
importance of identifying functional genetic variants in candidate genes.
Regulatory polymorphisms that do not affect amino acid sequence may influence
gene function through altered genetic regulatory regions and stability and processing of
mRNA. The existence of regulatory variants affecting transcription (especially in the
promoter region) has long been recognized (Callahan and Balbinde, 1970; Roberts,
1969). As numerous proteins interact with heteronuclear RNA and mRNA at multiple
sites, cis-regulatory polymorphisms can enhance or inhibit transcription through the modification of regulatory sites or structure of regulatory elements. Furthermore, the folding of single stranded mRNA is readily altered by SNP substitutions, with subsequent
3 effects on mRNA stability and processing (Johnson et al., 2008b, Johnson et al., 2005).
Alternative splicing represents another important source of protein diversity and regulation that can be affected by genetic polymorphisms and is discussed in more detail below. Transcription and mRNA processing are also affected by noncoding RNAs, the mRNA docking sites for which may be altered by genetic polymorphisms (Saunders et al., 2007). Although largely undiscovered, regulatory polymorphisms are relatively common and estimated to be present in nearly all genes (Rockman and Wray, 2002).
Regardless of the mechanism, cis-acting regulatory variants share the common feature of affecting the amount and nature of mRNA generated from one allele versus the other. One powerful approach to identifying cis-acting polymorphisms relies on allelic expression imbalance (AEI) as the phenotypic measure (Johnson et al., 2008b, Johnson et al., 2005): Using a heterozygous marker SNP in the transcribed region of the gene of interest, the mRNA specifically generated from each allele is measured (Fig. 1.1). Since both alleles are subject to the same trans-acting factors, any imbalance in allelic expression must be due to cis-acting factors. Upon identifying a gene that displays significant AEI, the gene locus is scanned for candidate SNPs associated with AEI. This powerful approach has already been successful in identifying regulatory cis-acting variants in a number of genes (Johnson et al., 2009; Lim et al., 2007; Wang et al., 2008a;
Wang et al., 2005; Zhang et al., 2007; Zhang et al., 2005), including some with clinical associations (Johnson et al., 2009; Wang et al., 2008a; Zhang et al., 2007).
4 Figure 1.1. Quantitative allele-specific expression analysis. A segment of DNA or
RNA (cDNA) surrounding a heterozygous marker SNP is amplified by PCR. The PCR products are subjected to a single base extension reaction (SNaPshot), which adds a single fluorophore-labeled (blue or green, in this case) nucleotide complementary to the marker SNP. Each peak represents a distinct allele, and the peak heights are proportional to the amount of PCR product specifically generated for each allele.
1.3 Epigenetic Factors
Changes in gene function that are not caused by variation in DNA sequence are referred to as epigenetic. Well characterized examples of epigenetic mechanisms include methylation of DNA in regions with high CG content (CpG islands) and chromatin remodeling. CpG methylation attracts binding proteins which in turn recruit additional
5 specialized proteins that can alter chromatin structure through methylation, acetylation, and phosphorylation (Chen et al., 2003; Laird, 2005). Chromatin structure plays an important role in the regulation of gene expression by restricting or permitting access of various enzymes to the DNA, either obstructing or enabling transcription, respectively
(Wolffe and Matzke, 1999; Workman and Kingston, 1998). Genetic and epigenetic factors are not independent of each other and their effects on gene regulation must be considered together. For example, promoter polymorphisms may affect CpG methylation and lead to allele-specific changes in methylation, as in the case of a G/A promoter SNP in SLC12A6, which introduces an additional methylation site on the opposite strand when the rare G allele is present (Moser et al., 2009). Furthermore, the authors showed the G allele is associated with decreased gene expression (Moser et al., 2009). Another example is MAOA, which has a variable number tandem repeat (VNTR) repeat polymorphism in the promoter region that has been associated with a number of psychiatric disorders (Herman et al., 2005; Huang et al., 2004; Manuck et al., 2000). In this case the two different alleles are 3- and 4-repeats, with large allelic differences in
CpG methylation that correlate with AEI ratios in female samples, independent of X- inactivation (Pinsonneault et al., 2006). Moreover, CpG methylation can affect the rate of transcription which could in turn affect mRNA processing (including splicing) since the proteins involved may be present in limiting supply.
6 1.4 Cis-Acting Genetic Regulation of Alternative Splicing
Alternative mRNA splicing is thought to be a major source of proteomic diversity in eukaryotes (Nilsen and Graveley, 2010). In humans, over 90% of genes are alternatively spliced and ~85% have a minor isoform frequency of 15% or more (Wang et al., 2008b).
Furthermore, mRNA splicing is an especially important source of diversity and regulation for neuronal genes (Lee et al., 2003). There are abundant examples of cis-acting genetic variants affecting splicing with subsequent effects on human phenotypes: A novel acceptor splice site mutation in the PAX3 gene has been shown to cause aberrant splicing resulting in Waardenburg syndrome, an autosomal dominant disorder characterized by developmental defects including hearing loss (Attaie et al., 1997). In DRD2, two intronic
SNPs that shift the balance of two functionally distinct isoforms modulate memory processing and dopamine pathway activity in healthy humans (Zhang et al., 2007) and are associated with cocaine abuse in Caucasians (Moyer, manuscript in preparation).
Another gene where a SNP is shown to exert a robust and clinically relevant effect on alternative splicing is MUC1, the protein product of which is ligand for Helicobacter pylori, where it plays a role in gastric carcinogenesis. An exonic SNP in MUC1 controls alternative splicing of the same gene (Ng et al., 2008) and has been associated with an increased risk of stomach cancer (Jia et al., 2010). Taken together, these results indicate an important regulatory role for genetic polymorphisms in alternative mRNA splicing.
1.5 Review of DRD2 Genotype-Phenotype Associations
DRD2 is an intensely studied gene for its potential role in drug addiction and other psychiatric disorders thought to involve dopamine dysregulation. The most intensely 7 studied variant is Taq1A (rs1800497), a SNP located ~ 10 kb upstream of DRD2 that was
recently shown to be in the coding region of another gene, namely ANKK1 (Neville et al.,
2004). Approximately 100 association studies have assessed the linkage of Taq1A to
clinical phenotypes including schizophrenia, addiction, and antipsychotic treatment
response, with results that are not always replicable (for reviews see Le Foll et al., 2009;
Munafo et al., 2004; Munafo et al., 2007; Thelma et al., 2008; Zhang et al., 2010). Of
special interest are studies reporting associations of Taq1A with addiction to various
drugs, including cocaine (Noble et al., 1993), alcohol (Smith et al., 2008), heroin
(Lawford et al., 2000), and nicotine (Huang et al., 2009). Another frequently studied
DRD2 SNP is the -141C Ins/Del promoter polymorphism (rs1799732), which has been associated with schizophrenia (Arinami et al., 1997) and alcoholism (Ishiguro et al.,
1998). Another promoter SNP, rs12364283, was shown to be predictive of avoidance learning in healthy humans (Frank and Hutchison, 2009). The synonymous SNP C957T
(rs6277), located in exon 7, was reported to be associated with schizophrenia (Lawford et al., 2005). In addition to the often more intensely studied promoter and exonic SNPs, a number of intronic SNPs in DRD2 have recently been associated with clinical
phenotypes, most notably rs2283265 (intron 5) and rs1076560 (intron 6), associated with
cocaine abuse (Moyer et al., manuscript in preparation), altered emotional control (Blasi
et al., 2009), schizophrenia (Glatt et al., 2009) and schizophrenia-related phenotypes,
(Bertolino et al., 2009b), alcoholism (Sasabe et al., 2007), opiate addiction (Doehring et
al., 2009), and relative avoidance to reward-seeking behavior (Frank and Hutchison,
2009). Both SNPs have been shown to modulate DRD2 alternative splicing (Zhang et al.,
8 2007; Moyer et al., manuscript in preparation) and are part of a large haplotype block that
includes a number of other SNPs with clinical associations (Table 2.7).
1.6 Review of ARRB2 Genotype-Phenotype Associations
Genetic variants in ARRB2 have been associated with psychiatric disorders, including
drug addiction (Ikeda et al., 2007; Sun et al., 2008), attention deficit hyperactivity
disorder (Brookes et al., 2006) and tardive dyskinesia (Liou et al., 2007). Furthermore,
ARRB2 has also been implicated in altered response to drug therapy: Cancer patients
who did not respond to morphine for pain management and/or who experienced
intolerable adverse effects were found to be less likely to carry the minor allele of the
synonymous ARRB2 SNP rs1045280 than patients who responded to morphine (Ross et al., 2005).
1.7 Review of DRD3 Genotype-Phenotype Associations
Like DRD2, DRD3 has been intensely studied for its potential role in disorders thought to
involve dopamine dysregulation. One DRD3 SNP in particular, the nonsynonymous SNP
rs6280 (also called Ser9Gly or BalI), has received the most attention. The rs6280 variant
has been associated with nicotine dependence (Huang et al., 2008), tardive dyskinesia
(Lerer et al., 2002; Steen et al., 1997), schizophrenia (Jonsson et al., 2003), familial
essential tremor (Jeanneteau et al., 2006), and antipsychotic treatment response (Lane et
al., 2005; Scharfetter et al., 1999; Szekeres et al., 2004). The Gly-9 variant of rs6280 has
an increased affinity for dopamine in vitro (Jeanneteau et al., 2006), evidence that the
amino acid substitution causes a functional change to the protein that could account for
9 some of the clinical associations, although other genetic factors could contribute as well.
Clinical associations for other DRD3 SNPs have been reported, including rs167771 associated with autism spectrum disorder (de Krom et al., 2009) and risperidone-induced extrapyramidal symptoms (Gasso et al., 2009). A study that assessed the contribution of a number of SNPs across the DRD3 gene locus in two independent populations identified a common haplotype spanning most of the gene that was associated with schizophrenia
(Talkowski et al., 2006).
1.8 Summary of the Main Studies
The dopamine receptor D2 (encoded by DRD2) is implicated in susceptibility to mental disorders and cocaine abuse, but mechanisms responsible for this relationship remain uncertain. DRD2 mRNA exists in two main splice isoforms with distinct functions: D2 long (D2L) and D2 short (D2S, lacking exon 6), expressed mainly post-synaptically and pre-synaptically, respectively. Two intronic single nucleotide polymorphisms (SNPs rs2283265 (intron 5) and rs1076560 (intron 6)) in high linkage disequilibrium with each other have been reported to alter D2S/D2L splicing and several behavioral traits in human subjects, such as memory processing. To assess the role of DRD2 variants in cocaine abuse, I measured levels of D2S and D2L mRNA in human brain autopsy tissues
(prefrontal cortex and putamen) obtained from cocaine abusers (n=119) and controls
(n=95), and genotyped a panel of DRD2 SNPs in these tissues. Robust effects of rs2283265 and rs1076560 on D2S/L splicing were confirmed, with additive effects for each minor allele in reducing D2S. The minor alleles of rs2283265/rs1076560 were considerably more frequent in Caucasians (18%) compared to African Americans (7%). 10 Also, in Caucasians, rs2283265/rs1076560 minor alleles were significantly
overrepresented in cocaine abusers compared to controls (rs2283265: 25% to 9%,
respectively; p=0.001; OR=3.4 (1.7-7.1)), with possible additive effects for the minor
allele (minor allele homozygous: p=0.052; OR=8.3 (0.98-70)). My results confirm the
role of rs2283265/rs1076560 in D2 alternative splicing and support a strong role in
susceptibility to cocaine abuse.
Arrestin2 (encoded by ARRB2) is an important regulator of most G-protein
coupled receptors that also initiates its own distinct signaling pathways. Genetic variants
of ARRB2 have been implicated in psychiatric disorders, but the underlying mechanisms
remain unknown. One particular synonymous SNP located in exon 11, rs1045280, has a
number of clinical associations and is an ideal candidate marker SNP for analysis of
allelic expression. To assess the effects of rs1045280 on ARRB2 expression and splicing,
I measured allelic and total mRNA expression and the levels of the two major ARRB2
splice isoforms in human brain autopsy PFC from Alzheimer’s patients (n=26) and
normal controls (n=20) as well as in cultured human lymphocytes. In the Alzheimer’s
samples, I also assessed arrestin2 protein levels by Western blotting. The presence of significant AEI in a number of Alzheimer’s and lymphocyte samples suggest that rs1045280 is in LD with a regulatory variant or variants causing increased transcription, and rs1045280 was associated with increased expression of overall ARRB2 mRNA in the
Alzheimer’s cohort (p<0.01), although there was no correlation between rs1045280
genotype and arrestin2 protein levels in the Alzheimer’s samples. Alternative splicing
did not differ across tissues or between samples, with the major full-length transcript
11 representing the overwhelming majority of ARRB2 mRNA in all three cohorts. My
results indicate that rs1045280 is in LD with a regulatory variant exerting a small but
significant effect on ARRB2 mRNA expression that is not maintained at the protein level.
The dopamine receptor D3 (encoded by DRD3) is implicated in susceptibility to
mental disorders including schizophrenia and addiction, but the mechanisms responsible
for remain uncertain. DRD3 mRNA exists in two main splice isoforms: D3 long (D3L), encoding the functional receptor, and the truncated D3nf, which may have a dominant negative effect. DRD3 has high homology with other dopamine receptor genes and is expressed at lower levels, presenting challenges for the study of its RNA species and necessitating that assessment of DRD3 mRNA expression and alternative splicing be performed in tissues where it is most highly expressed. Using AEI as the phenotypic measure, I searched for regulatory variants in DRD3 affecting mRNA expression in human brain autopsy nucleus accumbens (NAc) from a cohort of normal controls and patients diagnosed with schizophrenia, bipolar disorder, or depression (n=15 in each group). Additionally, I assessed alternative splicing of DRD3 in the same samples. The
presence of significant AEI in 4 out of 29 samples tested suggests the presence of a cis-
acting regulatory variant or variants with a modest effect on mRNA expression.
However, none of the 11 SNPs genotyped were associated with the observed AEI.
Furthermore, D3nf mRNA was not detectable in any of the samples. My results indicate
that there is at least one cis-acing regulatory variant with a small but significant effect on
DRD3 mRNA expression that is yet to be identified. The absence of measureable D3nf
mRNA suggests that it is not expressed in the NAc samples tested.
12 Chapter 2: Intronic Polymorphisms Affecting Alternative
Splicing of Human D2 Receptor are Associated with Cocaine
Abuse
2.1 Introduction
The dopamine receptor D2 (encoded by DRD2) is a member of the D2-like family of dopamine receptor subtypes, which are coupled to Gi inhibitory G-proteins and generally reduce formation of intracellular cAMP when activated (Civelli et al., 1993; Strange,
1993). D2 receptors are robustly expressed in the striatum and prefrontal cortex (PFC), areas involved in the primary reinforcing effects of drugs of abuse (Hyman et al., 2006) and cognitive processes (Seamans and Yang, 2004), respectively. The involvement of
D2 receptors with addiction and cognition is well documented. In rodent models, response to drugs of abuse, including cocaine, ethanol, nicotine, and morphine, is disrupted by administration of D2 agonists or antagonists, and in transgenic mice lacking
D2 (reviewed by Le Foll et al., 2009). In human cocaine abusers, D2 receptor availability and activity in frontal brain regions is reduced, even after months of detoxification (Volkow et al., 1993).
13 DRD2 has been linked to drug addiction, although associations with specific genetic variants are not always replicable (for recent review see Le Foll et al., 2009).
Association studies have typically focused on markers in protein coding regions used, in part, for historical reasons, whereas recent studies indicate that regulatory polymorphisms in non-coding regions – most as yet undiscovered – occur more frequently (Johnson et al., 2005; Rockman and Wray, 2002; Wray, 2007). Since functional variants contributing to disease are generally unknown for multigenic non-Mendelian disorders, such as drug addiction, reported associations between the disease and a polymorphism typically rely on marker SNPs in linkage disequilibrium (LD) with the causal variant. As allele frequencies and LD patterns between surrogate marker SNPs and the responsible functional variants may differ across ethnic populations, results obtained using surrogate markers may vary between association studies, underscoring the importance of identifying functional genetic variants in candidate genes.
One important mechanism for modulating D2 signaling is alternative splicing of
exon 6, resulting in long (D2L) and short (D2S) isoforms expressed mainly
postsynaptically and presynaptically, respectively (Khan et al., 1998). Studies in mice
lacking D2L but not D2S have shown that D2S functions primarily as an autoreceptor
inhibiting D1 dopamine receptor-mediated functions, whereas post-synaptic D2L
receptors can act synergistically with D1 receptors (Usiello et al., 2000). Further studies
in mice lacking D2L have identified altered dopamine-dependent modulation of GABA
and glutamate transmission in the striatum (Centonze et al., 2003; Centonze et al., 2004)
and altered behavioral responses to morphine (Smith et al., 2002) and psychotic and
14 antipsychotic agents (Xu et al., 2002). In postmortem human striatum and PFC, we have
previously characterized two DRD2 intronic single nucleotide polymorphisms (SNPs rs1076560 and rs2283265, referred to hereafter as SNP1 and SNP2, existing in high LD with each other (D’=1.0)), which were associated with decreased relative expression of
D2S mRNA, and a promoter SNP (rs12364283) associated with enhanced DRD2 mRNA expression (Zhang et al., 2007). In the same study, SNP1/SNP2 also reduced cognitive performance in healthy humans on working memory and attentional control tasks (Zhang et al., 2007). Both SNPs modulate putative splice factor binding sites, and both were found to independently affect splicing in vitro using a minigene construct (Zhang et al.,
2007). Interestingly, the extensively studied rs1800497 (also known as Taq1A) did not appear to contribute directly to DRD2 mRNA expression or splicing, but the Taq1A1
allele is in LD with the minor alleles of SNP1/SNP2 (D’=0.855, Zhang et al., 2007),
providing a potential mechanistic basis for the clinical associations observed with Taq1A.
Other recent studies have linked SNP1 and SNP2 to additional human phenotypes.
Individually, SNP1 genotype has been shown to interact with dopamine transporter
(DAT) 3’-variable number tandem repeat (VNTR) genotype to modulate response of the working memory network, including the striatum and PFC (Bertolino et al., 2009a).
SNP1 has also been associated with altered emotional control (Blasi et al., 2009), schizophrenia-related phenotypes, (Bertolino et al., 2009b), and reduced binding of DAT and D2 receptor radiotracers in human striatum (Bertolino et al., 2010). Furthermore,
SNP1 has been associated with alcoholism (Sasabe et al., 2007), opiate addiction
(Doehring et al., 2009), and apomorphine-induced growth hormone response in alcohol
15 dependent patients (Lucht et al., 2010), and SNP2 has been associated with schizophrenia
(Glatt et al., 2009). Both SNPs have been linked to relative avoidance to reward-seeking behavior (Frank and Hutchison, 2009). Taken together, these results support the notion that SNP1/SNP2 modulate the D2S/L ratio in striatum and PFC, which in turn affects dopamine signaling and related phenotypes in humans. The functional effect of
SNP1/SNP2 could account for the phenotypic associations of other DRD2 SNPs in high
LD with SNP1/SNP2.
Epistatic interaction between genetic loci is thought to be an important factor in assessing the genetic contribution to disease risk, and is likely to be especially important in complex multigenic disorders like drug addiction. The risk associated with a given genetic locus may be influenced by the genotype at another locus, confounding attempts to detect phenotypic associations in a single locus analysis (Carlson et al., 2004).
However, the sheer number of possible interactions between genetic variants presents a challenge to identifying real epistatic interactions with biological consequences. One approach to this problem is to limit the analysis to putative functional variants in genes in related pathways (the dopamine pathway in this case). Encoding the molecular target of cocaine, the DAT gene represents another important candidate gene for addiction.
Importantly, DAT physically interacts with D2 receptors in vivo and a statistical interaction between SNP1 genotype and DAT 3’ variable number tandem repeat (VNTR) genotype was detected and shown to modulate the response of the working memory network in humans (Bertolino et al., 2009a). In light of the evidence for interactions between DRD2 and DAT, we asked whether there is a significant interaction of
16 SNP1/SNP2 with the DAT 3’-VNTR or other DAT variants with evidence for being functional, including the intron 8 VNTR (Guindalini et al., 2006) and rs6347 and rs27072
(Pinsonneault, manuscript in preparation).
Because of the importance of D2 alternative splicing, one goal of the current study was to replicate the relationship between SNP1/SNP2 and D2 splicing in a different set of brain tissues. Moreover, we searched for additional genetic variants that could affect D2 splicing, because most, but not all of the observed splicing variability for D2 could be accounted for by SNP1/SNP2 (see Zhang et al. 2007, Fig. 3a). In addition, we assessed the relationship between D2S/L splicing, SNP1/SNP2 genotype, and cocaine abuse status in human brain autopsy PFC and putamen tissues from chronic cocaine abusers who died from cocaine overdose and age-matched drug-free controls. We also tested for interaction of SNP2 with four putative functional DAT SNPs and identified a significant interaction with the DAT intron 8 VNTR. While we did not identify any additional polymorphisms between exon 5 and exon 7 affecting D2S/L splicing, we did confirm the role of SNP1/SNP2 in D2S/L splicing and identified both SNPs as potential risk factors for cocaine abuse.
2.2 Materials and Methods
Postmortem Human Brain Tissues.
Miami Brain Bank. PFC (Brodmann’s area 46) and putamen tissue samples from 119 cocaine abusers who died from cocaine intoxication and 95 age-matched drug-free controls were provided by the Miami Brain Endowment Bank (University of Miami,
Miami, FL). Supplemental brain and blood toxicology and neuropathologic evaluations 17 were done in every case, and most of the drug-exposure cases obtained at autopsy came from individuals who had evidence of a number of surrogate measures of chronic cocaine abuse (drug-related pathology, arrest records, and hospital and treatment admissions).
Drug-free age-matched control subjects were selected from accidental or cardiac sudden deaths with negative urine screens for all common drugs and there was no history of psychiatric disorders or licit or illicit drug use prior to death.
Stanley Array Collection. DNA and RNA extracted from postmortem brain tissues were donated by The Stanley Medical Research Institute's (Chevy Chase, MD) brain collection. We obtained genomic DNA and total RNA extracted from 105 individuals previously diagnosed with schizophrenia or bipolar disorder (35 of each) and 35 controls.
DNA and RNA Extraction. DNA and RNA were extracted as described in Zhang et al.
2005. cDNA was synthesized with SuperScript™ III (Life Technologies, Foster City,
CA) using both gene-specific primers and oligo(dT), except for the minigene experiment
(see below).
DNA Sequencing. DNA sequencing of PCR product amplified from genomic DNA was performed with a 3730 DNA analyzer using the BigDye® Terminator Cycle Sequencing kit (Life Technologies, Foster City, CA).
Cell Culture and Minigene Splicing. Human embryonic kidney (HEK) 293 cells were cultured in DMEM/F12 media containing 10% FBS and 1% penicillin-streptomycin under 5% CO2. We used the Stratagene QuikChange Lightning site-directed mutagenesis kit (Agilent Technologies, Santa Clara, CA) to introduce rs35608204 into a DRD2 minigene consisting of exons 5-7 and introns 5 and 6 in pcDNA3 (Zhang et al. 2007).
18 The constructs were sequenced to confirm the intended genotypes and transfected into
HEK 293 cells using Lipofectamine 2000 (Life Technologies, Foster City, CA). RNA was extracted 24 hr later and cDNA synthesized using only a plasmid-specific primer,
SP6, to avoid synthesis of endogenous DRD2 cDNA. Splice variants were assayed as described below.
Quantitative mRNA Analysis by Real-Time PCR. Real-time PCR was performed on cDNA samples on an ABI 7000 sequence detection system with Power SYBR® Green
PCR Master Mix (Life Technologies, Foster City, CA). DRD2 expression levels, in arbitrary units, were calculated by subtracting the β-actin cycle threshold (Ct) from the
DRD2 Ct to get a Ct as described previously (Pinsonneault et al., 2006). Arbitrary units for each sample = 100(2-ΔCt).
Quantitative Detection of Splice Isoforms. D2S and D2L were measured following
PCR amplification of cDNA with a fluorescent Fam-labeled exon 5 primer and an exon 7 reverse primer as described in Wang et al., 2006. Standard curves were prepared with varying mixtures of cloned D2S and D2L cDNA (Zhang et al., 2007).
Genotyping Methods. SNPs were genotyped by at least one of four methods: SNPlex
(Life Technologies, Foster City, CA), SNaPshot (Life Technologies, Foster City, CA)
(Zhang et al. 2005), and allele-specific primers as described in Papp et al., 2003. The fourth method was a modified PCR-restriction fragment length polymorphism (RFLP) method (Haliassos et al., 1989a; Haliassos et al., 1989b). For this method, one of the
PCR primers was Fam-labeled, allowing for resolution of the restriction fragments by
19 capillary electrophoresis with an Applied Biosystems 3730 DNA analyzer (Life
Technologies, Foster City, CA).
Statistical Analysis. HelixTree 6.4.3 (Golden Helix, Bozeman, MT) was used to test for
Hardy-Weinberg equilibrium, calculate LD and R2 values, haplotype estimation, and a
basic allele chi-squared test for association with cocaine status. One-way ANOVA and
student’s t tests were performed with GraphPad Prism software (GraphPad Software, La
Jolla, CA). The associations between genotypes or haplotypes and disease risk as well as
the contribution of each minor allele to disease risk were analyzed using logistic
regression model performed using SAS 9.1 software (SAS Institute Inc., Cary, NC). The
suitability of model fitting was judged by deviance goodness of fit statistics p value and
score test p value, both of which should be equal to or below 0.05.
2.3 Results
Search for Additional Polymorphisms Associated with Alternative Splicing. Based on results of earlier experiments measuring allelic mRNA ratios of D2S and D2L in human postmortem tissues (Zhang et al., 2007), we selected five samples homozygous for the major alleles of SNP1/SNP2 for further analysis. Three of the samples had displayed substantial variation in the allelic mRNA ratio of D2S to D2L, indicative of other variants potentially affecting splicing, while two samples lacking allelic differences served as controls. An approximately 3 kb region around exon 6 was sequenced (Fig.
2.1), and the results analyzed for additional polymorphisms associated with differential alternative splicing. One control sample was heterozygous for rs12363125, which was excluded as potentially affecting splicing. One sample with an allelic D2L/D2S ratio >1 20 was a heterozygous carrier for the minor allele of rs35608204 (C/T genotype), located in intron 5 (Table 2.1), suggesting a possible effect of rs35608204 on D2 splicing. We did not identify any other sequence differences in the samples.
65.5 kb
rs35608204 rs1125394 rs4648308 rs11214608 rs12364283
E8 E1
Region for Direct Sequencing (3 kb)
E7 E6 E5 rs1076560 (SNP1) rs2283265 (SNP2)
Figure 2.1. DRD2 gene map, with blown up view of the region that was sequenced.
The exon that is included in D2L but absent in D2S (exon 6) is in gray. The locations of
SNPs genotyped in this study are marked.
21 Table 2.1. Results of sequencing DNA from five samples that displayed different
D2L/D2S allelic ratios
Sample ID (with AEI (L) / AEI (S) ratio) Low 1 Low 2 Control 1 Control 2 SNP (0.74) (0.74) High (1.67) (0.99) (0.86) 3' rs1110977 AA AA AA AA AA rs71653614 AA AA AA AA AA rs6277 CT CT CT CT CT rs6275 CT CT CT CT CT rs1801028 CC CC CC CC CC rs1800496 CC CC CC CC CC rs4986921 CC CC CC CC CC rs1076561 AA AA AA AA AA rs1076560 GG GG GG GG GG rs4986920 CC CC CC CC CC rs34684460 no deletion no deletion no deletion no deletion no deletion rs1079721 GG GG GG GG GG rs1110976 AA AA AA AA AA rs1110975 CC CC CC CC CC rs2362873 CC CC CC CC CC rs55900980 no deletion no deletion no deletion no deletion no deletion rs35319840 no insertion no insertion no insertion no insertion no insertion rs72153544 no insertion no insertion no insertion no insertion no insertion rs34525623 no insertion no insertion no insertion no insertion no insertion rs2511521 TT TT TT TT TT rs2283265 GG GG GG GG GG rs57837178 CC CC CC CC CC rs56014166 CC CC CC CC CC rs35608204 TT TT CT TT TT rs35579712 no deletion no deletion no deletion no deletion no deletion rs12363125 AG AG AG AA AG rs34674946 no insertion no insertion no insertion no insertion no insertion 5' rs71653613 CC CC CC CC CC
All SNPs (according to the dbSNP database) within the region sequenced are listed along with the observed genotype in each sample. The only two positions where the samples differed from each other are indicated by the shaded boxes. The rs6277 and rs6275 SNPs were used as marker SNPs for the allelic expression assay and therefore are heterozygous in these samples because only heterozygous samples were selected.
22 Alternative Splicing of a DRD2 Minigene Carrying rs35608204. We introduced the minor ‘C’ allele SNP for rs35608204 into a partial gene construct containing exon 5 to exon 7 and carrying the major alleles of SNP1 and SNP2 in an expression vector (Zhang et al. 2007). This construct along with two others, one carrying the minor alleles of both
SNP1 and SNP2 with the major allele of rs35608204 and a reference construct carrying the major alleles of all three SNPs, were transfected separately into HEK 293 cells. We extracted RNA from the cells, made cDNA using a plasmid-specific primer, and measured relative expression of D2S and D2L mRNA (cDNA), using PCR with fluorescently labeled primers. As shown previously by Zhang et al. 2007, the minor alleles of SNP1/SNP2 generated significantly less D2S relative to D2L (Fig. 2.2).
However, rs35608204 did not affect D2S/L splicing (Fig. 2.2). These results confirm that the minor T alleles of SNP1/SNP2 reduce the formation of D2S relative to D2L but do not support a role for rs35608204 in D2S/L splicing regulation.
23 Figure 2.2. Alternative splicing from DRD2 minigenes in HEK 293 cells. Minigenes carrying the indicated genotypes were transfected into HEK 293 cells and D2S relative to
D2L expression levels measured. Minor alleles are indicated by bold type. Data are mean ± SEM (n = 3 separate transfections). *, P<0.05, one-way ANOVA with
Bonferroni post-test, compared to GGT and GGC.
DRD2 mRNA Expression in Human PFC and Putamen from Cocaine Abusers and
Controls. We measured overall DRD2 mRNA expression with real time PCR in postmortem human PFC and putamen from cocaine abusers and age-matched controls.
We did not observe a statistically significant difference in overall DRD2 mRNA 24 expression between cocaine abusers and controls in either brain region in the complete
cohort (Fig. 2.3) or in Caucasians or African Americans when analyzed separately (Fig.
2.4). No SNP tested correlated with overall DRD2 mRNA levels (data not shown); any
potential small effects likely masked by large interindividual variability in total mRNA
levels in autopsy brain tissues.
a b
Figure 2.3. DRD2 mRNA expression. Real-time PCR was applied to quantify mRNA, with -actin as an internal control. DRD2 mRNA levels are presented in arbitrary units
(see Materials and Methods). Data are mean ± SEM, single measurements in PFC and
duplicate measurements in putamen.
25 Caucasians African Americans
Figure 2.4. DRD2 mRNA expression grouped by race and cocaine abuse status.
Real-time PCR was applied to quantify mRNA, with -actin as an internal control.
DRD2 mRNA levels are presented in arbitrary units (see Materials and Methods). Data are mean ± SEM, single measurements in PFC and duplicate measurements in putamen.
Alternative Splicing of DRD2 mRNA in Human PFC and Putamen from Cocaine
Abusers and Controls. To assess D2S/L splicing in the context of cocaine abuse, we measured relative expression of D2S and D2L mRNA in postmortem human PFC and putamen from cocaine abusers and age-matched controls. Consistent with previous reports (Khan et al., 1998; Zhang et al., 2007), relative D2S expression was higher in
PFC (27 ± 5%, n = 73) than in putamen (17 ± 4%, n = 70) (p<0.0001, Student’s t test).
Importantly, subjects carrying the minor allele T of SNP1/SNP2 had significantly reduced relative expression of D2S mRNA in both brain regions (Fig. 2.5a). This result is consistent with an earlier report (Zhang et al., 2007) and confirms a strong effect of
SNP1/SNP2 on D2S/L splicing in both tissues, in a different cohort. The D2S/L ratio 26 was reduced to a greater extent in individuals homozygous for the minor allele than in
heterozygotes, indicating that the effects of SNP1/SNP2 on D2S/L splicing are additive
(Fig. 2.5a). Consistent with the results of the in vitro minigene experiments, rs35608204 was not associated with the D2S/L ratio (data not shown). No difference was observed in relative expression of D2S between cocaine abusers and controls in either brain region tested (Fig. 2.5b). Since allele frequencies and linkage patterns may differ between populations, we analyzed the relationship of SNP1/SNP2 with D2S/L splicing separately in Caucasians and African Americans and obtained similar results across ethnicity (Fig.
2.6), mirroring the combined analysis shown in fig. 2.5a, and further supporting the role of SNP1/SNP2 as functional variants affecting splicing.
27 a
b
Figure 2.5. Expression of D2S relative to D2L. (a) Relative D2S mRNA expression grouped by SNP1/SNP2 genotype (T is minor allele). (b) Relative D2S mRNA expression grouped by cocaine abuse status. Data are mean ± SEM, at least three measurements per sample, *, P<0.05, ***, P<0.001, one-way ANOVA with Bonferroni post-test.
28 Caucasians African Americans
Figure 2.6. Expression of D2S relative to D2L grouped by race. Relative D2S
mRNA expression grouped by race and SNP1/SNP2 genotype (T is minor allele). Data
are mean ± SEM, at least three measurements per sample, *, P<0.05, ***, P<0.001, one-
way ANOVA with Bonferroni post-test.
Cocaine Status and DRD2 Genotype. Given the well-established role of dopamine signaling in drug addiction and the mounting evidence that SNP1/SNP2 affect the
D2S/D2L balance in relevant brain regions, we tested both SNPs for association with cocaine abuse in a population of cocaine abusers (n=119) and age-matched controls
(n=95) obtained from an archived biorepository housed in the Miami Brain Endowment
Bank (population characteristics are provided in Table 2.2). We also genotyped the SNP we initially suspected might have an effect on D2S/L splicing, rs35608204, as well as the promoter SNP rs12364283, previously shown to alter allelic DRD2 mRNA expression
(Zhang et al., 2007) and predictive of avoidance learning in healthy humans (Frank and
Hutchison, 2009). In addition, we selected three other DRD2 SNPs for genotyping based 29 on their associations with clinical phenotypes and/or utility as haplotype tagging SNPs: rs1125394 (intron 1, Hwang et al., 2005; Hwang et al., 2006), rs4648318 (intron 1,
Huang et al., 2009), and rs11214608 (5’ upstream). All SNPs tested were in Hardy-
Weinberg equilibrium (p>0.05) except SNP1, SNP2, and a third SNP, rs1125394, in high
LD with SNP1/SNP2, (D’=1.0, Table 2.3). This violation of Hardy-Weinberg equilibrium appears to be driven by the cocaine abuse cohort, as all three SNPs were in
Hardy-Weinberg equilibrium in the controls. Genotyping errors are unlikely to be the cause, as SNP1 and SNP2 genotypes were verified with two independent methods.
We found that SNP1, SNP2, and rs1125394 were associated with cocaine abuse, with minor allele frequencies approximately twice as high in cocaine abusers as in controls (SNP2: p=0.01, OR=2.3, 95% CI 1.2 - 4.2, Table 2.4). When the data were analyzed separately in Caucasians and African Americans, association of SNP1/SNP2 with cocaine abuse was even stronger in Caucasians (SNP2: p=0.001, OR=3.4, 95% CI
1.7 – 7.1), whereas there was no significant association in African Americans, who have a considerably lower minor allele frequency (7% versus 18% in Caucasians; Table 2.4).
As the splicing data suggest an additive effect of each minor allele of SNP1/SNP2, we further analyzed the number of minor alleles of SNP2 (i.e. GG=0. GT=1, TT=2) vs. cocaine status using a logistic regression model. The odds ratio (OR) of each minor allele in the complete cohort was 2.0 (95% CI 1.1 - 3.7, p=0.02; in Caucasians OR=3.0,
95% CI 1.5 - 6.0, p=0.003), suggesting the OR for minor allele homozygotes would be at least four. When we analyzed the genotype effect (i.e. SNP2 GG, GT and TT) vs. cocaine status, the association did not reach statistical significance in the complete cohort
30 (TT vs. GG, p=0.06, OR=7.3, 95% CI 0.90 - 60) or in the Caucasian subgroup (TT vs.
GG, p=0.052, OR=8.3, 95% CI 0.98 – 70) despite the large odds ratios, possibly due to the relatively small sample size.
To assess the effect of cocaine abuse on D2S/L splicing independent of the effects of SNP1/SNP2, we analyzed the splicing data from both brain regions broken down by
SNP1/SNP2 genotype and further analyzed across controls and cocaine abusers within each group. No significant differences in D2S/L splicing were detectable between controls and cocaine abusers (data not shown).
Table 2.2. Demographic Characteristics
Cocaine Controls Abusers n= 93 118 Age (mean ± SD) 35 ± 11 37 ± 10 % Male 87% 85% Caucasian 63 74 African American 30 44
Three individuals were excluded from all analyses and are not included in this table. One was the only subject of Asian ancestry, and we did not obtain quality DNA/reliable genotyping results from the other two.
31 Table 2.3. Pairwise Linkage Disequilibrium Values
2 All R rs1076560 rs2283265 rs35608204 rs1125394 rs4648318 rs11214608 rs12364283 rs1076560 0.94 0 0.75 0.05 0.12 0.01 rs2283265 0.98 0 0.81 0.05 0.13 0.01 rs35608204 0.97 0.96 0.01 0.01 0.03 0.12 rs1125394 0.95 1 0.99 0.05 0.18 0.01 rs4648318 0.89 0.89 1 0.77 0.32 0 rs11214608 0.92 1 0.99 1 1 0 rs12364283 0.12 0.13 0.56 0.18 0.40 0.20 D' 2 Caucasians R rs1076560 rs2283265 rs35608204 rs1125394 rs4648318 rs11214608 rs12364283 rs1076560 0.93 0.01 0.90 0.06 0.29 0 rs2283265 0.97 0.01 0.97 0.06 0.31 0 rs35608204 0.98 0.99 0.01 0.01 0.02 0.14 rs1125394 0.96 1 0.99 0.06 0.31 0.02 rs4648318 1 1 0.99 1 0.39 0.01 rs11214608 0.94 1 1 1 1 0.01 rs12364283 0.09 0.09 0.61 0.22 0.62 0.26 D' 2 African Americans R rs1076560 rs2283265 rs35608204 rs1125394 rs4648318 rs11214608 rs12364283 rs1076560 1 0 0.43 0.02 0 0 rs2283265 1 0 0.43 0.02 0 0 rs35608204 1 1 0 0.01 0.04 0 rs1125394 1 1 1 0.03 0.04 0 rs4648318 0.57 0.57 1 0.46 0.14 0.02 rs11214608 0.05 0.05 1 0.99 1 0 rs12364283 1 1 1 0.96 0.99 0.96 D'
32 Table 2.4. Minor allele frequencies in cocaine abusers and controls, plus results of statistical group comparisons
All (n=211) Minor Allele Frequencies Controls Cocaine c2, Odds Ratio SNP All (n=93) (n=118) P Value (95% C.I.) rs1076560 (SNP1) 0.14 0.10 0.17 0.03 1.94 (1.07 - 3.50) rs2283265 (SNP2) 0.14 0.09 0.18 0.01 2.27 (1.23 - 4.19) rs35608204 0.02 0.03 0.02 0.30 0.52 (0.14 - 1.86) rs1125394* 0.17 0.12 0.22 0.03 2.05 (1.07 - 3.94) rs4648318* 0.28 0.27 0.29 0.64 1.13 (0.67 - 1.89) rs11214608* 0.45 0.51 0.41 0.09 0.67 (0.42 - 1.06) rs12364283 0.06 0.05 0.07 0.53 1.31 (0.56 - 3.07) Caucasians (n=137) Minor Allele Frequencies Controls Cocaine c2, Odds Ratio SNP All (n=63) (n=74) P Value (95% C.I.) rs1076560 (SNP1) 0.18 0.10 0.24 0.003 2.74 (1.38 - 5.45) rs2283265 (SNP2) 0.18 0.09 0.25 0.001 3.42 (1.66 - 7.05) rs35608204 0.03 0.05 0.02 0.21 0.42 (0.10 - 1.71) rs1125394* 0.17 0.09 0.25 0.004 3.33 (1.42 - 7.80) rs4648318* 0.21 0.23 0.19 0.46 0.78 (0.39 - 1.53) rs11214608* 0.41 0.36 0.45 0.19 1.46 (0.83 - 2.59) rs12364283 0.08 0.07 0.09 0.63 1.25 (0.51 - 3.02) African Americans (n=74) Minor Allele Frequencies Controls Cocaine c2, Odds Ratio SNP All (n=30) (n=44) P Value (95% C.I.) rs1076560 (SNP1) 0.07 0.08 0.06 0.53 0.66 (0.18 - 2.40) rs2283265 (SNP2) 0.07 0.08 0.06 0.53 0.66 (0.18 - 2.40) rs35608204 0.01 0.00 0.01 0.42 N.D. rs1125394* 0.18 0.19 0.17 0.73 0.83 (0.28 - 2.41) rs4648318* 0.43 0.35 0.47 0.28 1.61 (0.68 - 3.82) rs11214608* 0.15 0.17 0.15 0.78 0.85 (0.28 - 2.62) rs12364283 0.01 0.00 0.02 0.25 N.D.
Minor allele frequencies were determined for all samples (n=211), controls (n=93), and cocaine abusers (n=118) separately within each group. Approximately 70% of samples were successfully genotyped with SNPlex for SNPs annotated with a *. The rest of the SNPs were successfully genotyped in >95% of samples with a number of techniques (see Materials and Methods).
33 Haplotype Analysis. We conducted a haplotype analysis for all seven SNPs and identified four major haplotypes that occurred at >2% frequency in the complete cohort
(Table 2.5). Of the two haplotypes containing the minor alleles of SNP1/SNP2, the more frequent haplotype H3 was present at almost twice the frequency in cocaine abusers vs. controls (14% vs. 8%), although the association with cocaine abuse did not reach statistical significance (p=0.2). One relatively rare haplotype (H6) was also more prevalent in cocaine abusers, (4% vs. <1% in controls, Table 2.5). Interestingly, the only difference between this haplotype and the second most frequent haplotype (H2) is rs12364283, the promoter SNP previously associated with increased DRD2 mRNA expression (Zhang et al., 2007). However, none of the haplotypes was significantly associated with cocaine abuse in the complete cohort (data not shown), requiring a larger sample size.
The haplotype distribution (Table 2.5) and LD pattern (Table 2.3) differed between Caucasians and African Americans in our cohort. The frequent haplotype carrying the minor alleles of SNP1/SNP2, H3, was significantly associated with cocaine abuse in Caucasians (p=0.049, OR=3.0, 95% CI 1.0 – 9.1). However, in African
Americans it was much less frequent and tends to be overrepresented in controls (Table
2.5), although this did not approach statistical significance (p=0.6). No other haplotypes were associated with cocaine abuse in the complete cohort or in the Caucasian or African
American subgroups, although the rare haplotype carrying the functional promoter SNP rs12364283 (H6) tends to be more prevalent in cocaine abusers in both Caucasians and
African Americans (Table 2.5).
34 Table 2.5. Haplotype Analysis in Cocaine Abusers and Controls
Haplotype frequencies were determined by EM algorithm in all samples (n=211), controls (n=93), and cocaine abusers (n=118) separately. Minor alleles are indicated by shaded boxes. The only haplotype significantly associated with cocaine abuse in any of the three groups (H3 in Caucasians) is annotated by a *. Haplotypes occurring at frequencies of at least 2% in at least two groups were included in the table.
Interaction of SNP2 with a Functional Variant in the Dopamine Transporter Gene
(DAT). To test for a statistical interaction between SNP2 and each of the four DAT variants, logistic regression was performed in SNP2 major allele homozygotes and minor 35 allele carriers separately (allele frequencies separated by cocaine status and SNP2 genotype are shown in Table 2.6). We found a significant interaction of SNP2 with the intron 8 VNTR (OR for association with cocaine abuse in SNP2 minor allele carriers =
0.28, 95% CI 0.072 - 1.03, p=0.055). In SNP2 major allele homozygotes, OR = 2.1, 95%
CI 1.1 ~ 3.9, p=0.028, indicating that the intron 8 VNTR minor allele five repeat is protective in individuals carrying the SNP2 minor allele, while increasing risk in individuals homozygous for the major allele of SNP2. No other significant interactions were identified, and none of the DAT variants were associated with cocaine abuse when tested separately.
Table 2.6. DRD2-DAT Gene Interaction
Minor allele frequencies were determined for controls (n=93), and cocaine abusers (n=118) separately within each group.
2.4 Discussion
The present study confirms a robust effect of SNP1/SNP2 on D2S/L splicing in human
PFC and putamen autopsy tissues in a cohort of cocaine abusers with a documented history of heavy abuse, and age-matched controls. Sequencing the region of DRD2
36 between exon 5 and exon 7 suggested an additional candidate SNP, rs35608204, but a
role in splicing was not corroborated by analysis of D2S/D2L mRNA in human PFC and
putamen, or by DRD2 minigene experiments in vitro. A genetic association analysis revealed that SNP1, SNP2, and a third SNP also in high LD, rs1125394, but lacking evidence for any biological function, are associated with cocaine abuse in Caucasians but not African Americans.
The association of SNP1/SNP2 with decreased expression of D2S relative to D2L in human PFC and putamen was consistent with our earlier report (Zhang et al., 2007), replicating the finding in a separate population with a different pathophysiology. While this study failed to reveal any additional polymorphisms affecting splicing, the validation of SNP1/SNP2 as DRD2 variants affecting D2S/D2L splicing is important because only a
firm understanding of the molecular genetic effect can guide the interpretation of clinical
association studies. A number of SNPs are in high LD with SNP1/SNP2. Fig. 2.7
demonstrates the large LD block and the many SNPs that could have served as surrogate
markers for SNP1/SNP2 (http://www.broadinstitute.org/mpg/snap/ldplot.php; Johnson et
al., 2008a). All of these can thus be considered markers for a true genetic effect with
demonstrable impact on human behavioral phenotypes (Table 2.7). It is further noted
that the LD block extends in to the adjacent gene ANNK1 (Fig. 2.7), including the Taq1A
variant used as a marker in numerous clinical association studies (Table 2.7). While
ANNK1 could well represent a risk gene on its own, the strong LD to SNP1/SNP2 in the
DRD2 locus must be considered. Lastly, the haplotype block is significantly shorter in
37 subjects of African descent when measured using the Yoruban HapMap population (not shown), indicating that strong ethnic differences in association studies can be expected.
As the importance of dopamine in the pathophysiology of addiction is well established, perturbations in dopamine signaling could impact an individual’s response to drugs of abuse and/or risk for addiction. Alternative splicing of DRD2 to form D2S and
D2L represents a regulatory event that could affect dopamine signaling: There is ample evidence that D2S and D2L are functionally distinct (Smith et al., 2002; Usiello et al.,
2000; Wang et al., 2000; Xu et al., 2002), and D2S levels could influence dopamine transport as well as release. DAT is regulated by D2S receptors through a protein-protein interaction which promotes localization of intracellular DAT to the cell membrane, resulting in enhanced clearance of extracellular dopamine (Bolan et al., 2007; Lee et al.,
2007).. In light of the compelling evidence for the effects of SNP1 and SNP2 on D2S/L splicing, we tested for and found a positive association of SNP1 and SNP2 with cocaine abuse in our cohort (Table 2.4). When analyzing the Caucasian and African American subgroups separately, an even stronger association emerged with cocaine abuse in
Caucasians, but no association in African Americans (Table 2.4). Allele frequencies were substantially higher in the Caucasian cocaine group (SNP1 24% and SNP2 25%), compared to the controls (SNP1 10% and SNP2 9% (p=0.003 and 0.001, respectively,
Table 2.4). The positive association in one racial group but not another could be interpreted as evidence against SNP1/SNP2 being the functional variants driving the association. However, the African American subgroup of our cohort is smaller (n=74 vs.
137 Caucasians) and both SNPs are less frequent in African Americans (MAF=7% vs.
38 18% in Caucasians) (Table 2.4), resulting in a loss of power to detect statistically significant associations in the African American subgroup. In fact, there were only nine minor allele carriers of SNP1/SNP2 in the African American subgroup, including only one individual homozygous for the minor allele, who was a cocaine abuser. Furthermore,
SNP1/SNP2 exist in a different genomic context in Caucasians vs. African Americans, given the different LD pattern (Table 2.3) and haplotype distribution (Table 2.5) in the two groups, differential contribution of other genetic factors in each group must be considered. However, the biological effect of SNP1/SNP2 on D2S/L splicing was recapitulated in both groups (Fig. 2.6).
Another SNP tested, rs1125394, was also associated with cocaine abuse in the complete cohort and in Caucasians (p=0.03 and p=0.004, respectively, Table 2.4). This third SNP is in tight LD with SNP1/SNP2 (D’=1.0, Table 2.3) and has also been shown to be predictive of clozapine response in schizophrenic patients (Hwang et al., 2005;
Hwang et al., 2006). In light of the data presented here and by Zhang et al. 2007 supporting SNP1 and SNP2 being functional variants modulating D2S/L splicing, it is likely that the clinical associations of rs1125394 are due to its LD with SNP1/SNP2.
The apparent additive effect of the minor alleles of SNP1/SNP2 on D2S/L splicing (Fig. 2.5a) led us to ask whether they had an additive effect on susceptibility to cocaine abuse. An analysis of SNP2 revealed the OR of each minor allele to be 2.0 (95%
CI 1.1 - 3.7, p=0.02), suggesting that the OR for homozygotes would be ~4. However, when we analyzed the genotype effect vs. cocaine status, comparison of minor allele homozygotes vs. major allele homozygotes only displayed a trend towards statistical
39 significance (p=0.052 in Caucasians, with a large odds ratio), indicating that
susceptibility of carriers homozygous for the SNP1/SNP2 minor alleles to cocaine abuse
must be studied in a larger cohort.
The D2S/L ratio was not measurably affected by cocaine abuse, nor was it
correlated with cocaine abuse in our cohort, even though SNP1 and SNP2 were
associated with reduced relative expression of D2S and with cocaine abuse. The
contribution of external trans-acting factors to variability in transcription and alternative
splicing must be considered, introducing sufficient noise so that any correlations between
splicing and cocaine abuse are no longer apparent. Previous evidence supports varied
trans effects on splicing. Cocaine abuse has been shown to act as a trans-factor modulating overall gene expression in humans and animals (reviewed in Lull et al., 2008) and altering differential expression of specific isoforms of brain-derived neurotrophic factor in human brain (Jiang et al., 2009). Furthermore, D2S and D2L expression in mouse striatum and ventral tegmental area is differentially affected following treatment with amphetamine, another psychostimulant (Giordano et al., 2006). A host of other
trans-acting factors, including postmortem decay, and the variability in extracting RNA
from postmortem human tissues could have contributed to increased variability in the
measurements of D2S/L splicing, confounding the three-way relationship between
genotype, splicing, and cocaine abuse. Another possibility is that D2S/L splicing in the
brain regions tested is not important in the etiology of cocaine abuse and the association
of SNP1/SNP2 with cocaine abuse is due to altered D2S/L splicing in other brain regions
(nucleus accumbens, for instance) or to another mechanism yet to be identified. Further
40 studies are needed to better characterize the interaction between SNP1/SNP2 genotype,
cocaine abuse, and D2S/L splicing in specific brain regions.
A haplotype analysis was conducted to test for an interaction between
SNP1/SNP2 and the functional promoter SNP rs12364283 and to assess the DRD2
haplotype distribution in Caucasians and African Americans separately. The haplotype
distribution differed considerably between the two groups (Table 2.5), requiring
haplotype associations with cocaine abuse to be performed for each group separately. A
haplotype carrying the minor alleles of SNP1/SNP2 (H3) was significantly associated
with cocaine abuse in Caucasians, while no other haplotype showed significant
associations in the complete cohort or in the Caucasian or African American subgroups
(Table 2.5). The only two haplotypes carrying the minor allele of rs12364283 (H6 and
H7) tended to be overrepresented in cocaine abusers, but they are too rare (<3%) to
permit a meaningful statistical analysis in our cohort (Table 2.5).
Given the evidence for interactions between DRD2 and DAT (Bertolino et al.,
2009a), we assessed the interaction of SNP2 with four DAT variants thought to be
functional, and identified a significant interaction between SNP2 and the DAT intron 8
VNTR, previously associated with altered DAT expression in vitro (Guindalini et al.,
2006). The data indicate that the minor allele five repeat is protective in SNP2 minor allele carriers, while increasing susceptibility to cocaine abuse in individuals homozygous for the major allele of SNP2. It is interesting to speculate about the
potential mechanism for this relationship: The D2S receptor interacts with DAT and
“holds” it in the plasma membrane (Bolan et al., 2007; Lee et al., 2007), so D2S levels
41 influence the level of functional DAT that is localized to the cell membrane. In vitro, the
intron 8 VNTR five repeat mediates higher DAT expression than the six repeat, and the
effect of genotype on DAT expression is influenced by the cellular environment: the five
repeat mediates even higher expression when the cells are treated with cocaine
(Guindalini et al., 2006). However, the 5 repeat allele is associated with lower DAT
mRNA expression in human substantia nigra autopsy samples (Pinsonneault et al.,
manuscript in preparation). Further study is needed to determine the functional effects of
the DAT intron 8 VNTR in relevant brain regions, particularly in the context of cocaine
abuse and other environmental factors. In light of the evidence for the effects of
SNP1/SNP2 on D2S/L splicing and for the effects of the intron 8 VNTR on DAT
expression, the interaction between the two variants in the context of cocaine abuse
reported here is striking. As drug addiction is thought to be a complex, multigenic
disorder involving a large number of genes with low penetrance, the finding of a
significant interaction between two genetic variants in plausible candidate genes is an
important finding requiring replication in a larger cohort.
In the present study we examined the relationship between DRD2 genotype,
D2S/L splicing, and cocaine abuse. We replicated our earlier finding that SNP1 and
SNP2 decrease the relative expression of D2S in human brain in a different population and found both SNPs to be associated with cocaine abuse. The latter finding is supported by numerous earlier clinical association results in various disorders with these same
SNPs, or SNPs in high LD with them. Furthermore, we identified a significant interaction between SNP2 and the DAT intron 8 VNTR. Taking all previous studies and
42 the present results together, SNP1/SNP2 are regulatory variants that modulate the ratio of
D2S to D2L in human brain, affecting cognitive processes and psychiatric disorders including drug addiction. The large odds ratios observed for SNP1/SNP2 in the present study for risk of cocaine abuse supports a large effect size in this population of subjects with documented heavy abuse, leading eventually to cocaine overdose and death.
Figure 2.7. LD plot of surrogate markers for the intron 5 SNP rs2283265 (SNP1) as the seed. (http://www.broadinstitute.org/mpg/snap/ldplot.php) (Johnson et al., 2008a).
The sequence window spans 25 kb on either side of the seed SNP, overlapping with both the DRD2 and ANNK1 genes (green arrows, reflecting gene orientation), and the threshold was set at r2=0.8. The plot also shows the recombination rate, which is low
43 throughout this entire region but increases strongly at the borders (not shown). The LD results are from the CEU population (Utah residents with ancestry from northern and western Europe; HapMap release 22, Frazer et al., 2007). In Yoruban subjects in Ibadan,
Nigeria (YRI), a significantly shortened LD block was observed, not extending beyond the DRD2 locus (not shown). SNPs with clinical associations (Table 2.7) are labeled.
44 Table 2.7. Clinical Associations of SNPs in LD (R2>0.6) with rs2283265
45 Table 2.8. Sequences of Oligonucleotides (Primers) Used
Experiment Oligos Comments Real Time PCR to Assess DRD2 Forward: 5'CCAGCTGACTCTCCCCGAC mRNA Expression Reverse: 5'GCATGCCCATTCTTCTCTGG Splice Variant Forward: 5'ACATTGTCCTCCGCAGACG Detection Reverse: 5'GCATGCCCATTCTTCTCTGG Forward primer was Fam labeled Forward: 5'GCTCCCTCTGACTCCTCCACCCTCTTTCC TTTACCTTCCG Reverse: Minigene 5'CGGAAGGTAAAGGAAAGAGGGTGGAGGAGT For introduction of rs35608204 Mutagenesis CAGAGGGAGC into minigene Minigene cDNA Used for cDNA synthesis from Synthesis SP6: 5'CATTTAGGTGACACTATAG RNA derived from plasmid SNP Forward: 5'GCCCGGCGCGCGCCCTGTCCTCAGTT rs12364283 GC WT Forward: 5'CTGTCCTCAGTTTGCCGGA Clamp Genotyping Reverse: 5'CAGCACCTGTTTAAGCCTCAGT rs12364283 Forward: 5'GCAGCAATTAGTTACCAACTGTCC SNaPshot Reverse: 5'CAGCACCTGTTTAAGCCTCAGT Genotyping PEP: 5'GTGACTTCTGAATCTGACACAGAA Forward: 5'TCTTGTTCCTTCTGTGCCCA WT Reverse: 5'TAGCTCCCTCTGACTCCTGCAT SNP Reverse: rs35608204 GC 5'GCCGCCGCCGCCGCGCCTAGCTCCCTCT Clamp Genotyping GACTCCTCGAC rs35608204 RFLP Forward: 5'TCTTGTTCCTTCTGTGCCCA Forward primer was Fam Genotyping Reverse: 5'TTAGCTCCCTCTGACTCCTCGA labeled, restriction enzyme was Forward: rs35608204 Reverse:5'CTCTTTTCTGGTTTCTCTGTCTCACT SNaPshot 5'TTTGATTCCCATTTAACAGATGAGG Genotyping PEP: 5'GGAAACAGGCTCATAGAAGGTAAG Forward: 5'TTTTGCTGAGTGACCTTAGGCAA WT Reverse: 5'GGAAACAGGCTCATAGAAGGTATGC SNP Reverse: rs2283265 GC 5'CCGGCGCGGCCGCCGGAAACAGGCTCAT Clamp Genotyping AGAAGGTACGA
Continued
46 Table 2.8 Continued Clamp Genotyping AGAAGGTACGA Forward: Reverse:5'CTCTTTTCTGGTTTCTCTGTCTCACT rs2283265 5'TTTGATTCCCATTTAACAGATGAGG SNaPshot PEP: Genotyping 5'TTGAGGAAACAGGCTCATAGAAGGTAAG Forward: 5'CTGCACCAGAGGCAGAGG WT Reverse: 5'TTGCAGGAGTCTTCAGAGTGG SNP Reverse: rs1076560 GC 5'CGGGCCGGCCGCCCGGTTGCAGGAGTCT Clamp Genotyping TCAGAGCGT Forward: 5'CACCCATCTCACTGGCCC rs1076560 SNaPshot Reverse: 5'GTGGTGTTTGCAGGAGTCTTCAG Genotyping PEP: 5'GTTTGCAGGAGTCTTCAGAGGG
47 Chapter 3: A Synonymous SNP in ARRB2 is Associated with
Increased mRNA Expression
3.1 Introduction
Arrestin2 is an important mediator in the desensitization and internalization of G-
protein coupled receptors (GPCRs) (Ferguson, 2001; Ferguson et al., 1996; Luttrell and
Lefkowitz, 2002; Perry and Lefkowitz, 2002). More recently, it has also been shown to
activate signaling cascades independent of G-protein activation (DeWire et al., 2007; Lin
et al., 1998; Luttrell et al., 2001). It is ubiquitously expressed and interacts with most
GPCRs, including dopamine receptors (Beaulieu et al., 2005; Klewe et al., 2008; Lan et
al., 2009). Mice lacking arrestin2 display a number of altered phenotypes relevant to psychiatric disorders, including enhanced morphine antinociception (Bohn et al., 1999) and reward (Bohn et al., 2003) as well as decreased locomotor activity and disrupted dopaminergic signaling and dopamine-related behaviors (Beaulieu et al., 2005).
Furthermore, it has been suggested that identification of “biased ligands” that selectively activate G-protein or arrestin2-mediated signaling could represent a novel approach to
drug discovery (Violin and Lefkowitz, 2007). In fact, it has been recently shown that
lithium, which is used to treat psychiatric disorders including schizophrenia, bipolar
48 disorder, and depression, disrupts a signaling complex that includes arrestin2 and mice
lacking arrestin2 are resistant to the behavioral changes induced by lithium (Beaulieu et
al., 2008), underscoring the potential impact of arrestin2 on drug therapy.
Variants of the gene encoding arrestin2 (ARRB2) have been associated with
psychiatric disorders and with altered response to drug therapy in human populations.
One single nucleotide polymorphism (SNP) located in exon 11 of the ARRB2 gene, rs1045280, comes up repeatedly in the literature: It has been linked to tardive dyskinesia in Chinese patients with schizophrenia (Liou et al., 2008) and was part of a haplotype associated with nicotine dependence in a European American population (Sun et al.,
2008). In a Japanese population, rs1045280 was associated with methamphetamine use disorder but not schizophrenia (Ikeda et al., 2007). Another recent study showed that cancer patients who did not respond to morphine for pain management and/or who experienced intolerable adverse effects were less likely to carry the minor allele of rs1045280 than patients who responded to morphine (Ross et al., 2005).
Association studies have historically focused on SNPs in protein coding regions, since variants that change the amino acid sequence or introduce a premature stop codon are the most obvious candidates for genetic variants affecting the amount or function of the gene product. However, recent studies indicate that regulatory polymorphisms in non-coding regions – most as yet undiscovered – occur more frequently (Johnson et al.,
2005; Rockman and Wray, 2002; Wray, 2007). As rs1045280 is a synonymous SNP that does not change the amino acid sequence, its functional consequences (if any) must be due to its regulatory effects at the RNA level (e.g. transcription, mRNA processing,
49 mRNA stability, and translation) rather than structural alterations in the protein. One
limitation of most association studies is a lack of consideration of the molecular genetic
mechanisms underlying the effects of polymorphisms, resulting in the association of
phenotype with genetic variants that may be functional or, more likely, are simply in
linkage disequilibrium (LD) with a variant that is functional. Since allele frequencies and
linkage patterns may differ vary between populations, results may vary between
association studies, underscoring the importance of identifying functional genetic variants
in candidate genes.
The ARRB2 gene occupies ~11 kb on chromosome 17. It consists of 15 exons
(Fig. 3.1) and undergoes alternative splicing to form at least 22 distinct splice variants
(http://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/; Thierry-Mieg and Thierry-Mieg,
2006). At least 90% of human genes undergo alternative splicing (Wang et al., 2008b), a
process that has emerged as an especially important source of diversity and regulation for
genes expressed in the brain (Lee et al., 2003). NCBI’s RefSeq database (Pruitt et al.,
2007) annotates two major ARRB2 transcripts, the full-length isoform and a short isoform lacking exon 4 (Fig. 3.1), although little is known about the functional significance of the different ARRB2 splice variants. Located in exon 11, the synonymous SNP rs1045280 is
one of five SNPs in the coding region of ARRB2 and the only one of the five with >5%
minor allele frequency. ARRB2 is highly expressed in the central nervous system as well
as in other tissues all over the body. In summary, ARRB2 is biologically important,
implicated in psychiatric disorders and drug response, highly expressed, and contains a
frequent marker SNP in the coding region (rs1045280) amenable to analysis of allelic
50 expression. Given all of these factors, I asked whether rs1045280, previously associated
with a number of human phenotypes, affects transcription and/or alternative splicing in
human brain.
I assessed overall and allelic expression of ARRB2 mRNA in postmortem human
prefrontal cortex tissue samples from Alzheimer’s patients (n=26) and normal controls
(n=20) as well as in cultured human lymphocytes. In addition, I evaluated the levels of
the two major ARRB2 mRNA transcripts in all three cohorts and the arrestin2 protein levels in the Alzheimer’s cohort. The major full-length transcript represented the overwhelming majority of ARRB2 mRNA in all three cohorts. In the Alzheimer’s and
lymphocyte samples, allelic expression imbalance (AEI), in a number of samples suggest
that rs1045280 is in LD with a regulatory variant or variants causing increased
transcription, and rs1045280 was associated with increased expression of overall ARRB2
mRNA in the Alzheimer’s cohort. However, I tested for and did not identify any
relationship between rs1045280 genotype and arrestin2 protein levels in the
Alzheimer’s cohort.
51 Figure 3.1. ARRB2 gene map. The exon that is included in the full length isoform of
ARRB2 mRNA but absent in the short isoform tested for in this study (exon 4), is in gray.
The location of the synonymous SNP rs1045280 in exon 11 is indicated.
3.2 Materials and Methods
Human Tissue Selection and Sources
Post-mortem prefrontal cortex (PFC) tissue samples were obtained from different sources as follows: 26 from patients with histologically confirmed Alzheimer’s disease from the
Ohio State University Neurodegenerative Disease Brain Tissue Repository (Buckeye
Brain Bank), courtesy of Dr. Maria Kataki and 20 from normal controls from the Miami
Brain Endowment Bank (University of Miami, Miami, FL), courtesy of Dr. Deborah
Mash. Ninety Epstein-Barr virus-transformed B-lymphoblast cell lines, consisting of 30
Caucasian family trios, were obtained from the Coriell Cell Repository (Coriell Institute,
Camden, NJ).
DNA and RNA Preparation
Genomic DNA and total RNA were prepared from frozen brain samples or cultured lymphocytes. Samples were treated with sucrose-Triton (with SDS for brain tissues only)
52 and digested overnight with proteinase K, followed by sodium chloride precipitation to
separate proteins and ethanol precipitation of DNA. Total RNA was extracted with
TRIzol reagent (Life Technologies, Foster City, CA) and purified using RNeasy
(QIAGEN, Germantown, MD) columns according to the manufacturer’s instructions,
including an on-column DNase treatment to remove genomic DNA. Complementary
DNA (cDNA) was generated from 500 ng of total RNA with Superscript III reverse
transcriptase (Life Technologies, Foster City, CA) using oligo(dT) and, for the
Alzheimer’s and Coriell cultured lymphocyte samples, ARRB2-specific primers.
Quantitative mRNA Analysis by Real-Time PCR
Real-time PCR was performed on cDNA samples on an ABI 7000 sequence detection
system with Power SYBR® Green PCR Master Mix (Life Technologies, Foster City,
CA). PCR reactions were performed in 20 L reaction volumes in standard 96-well
plates. Cycle thresholds (Ct), the point at which a reaction reaches a fluorescent intensity
above background, were determined with ABI 7000 SDS software. Replicate cycle
thresholds were averaged and ARRB2 expression levels in arbitrary units were calculated
by subtracting the β-actin Ct from the ARRB2 Ct to get a Ct as described previously
(Pinsonneault et al., 2006). Arbitrary units for each sample = 100(2-ΔCt).
Allelic Expression Imbalance
Allele-specific mRNA expression in samples heterozygous for selected marker SNPs was
measured with SNaPshot (Life Technologies, Foster City, CA). The SNaPshot assay is a
single base extension method that allows quantitative comparison of two alleles. The
first step was PCR amplification of the target region of DNA containing the SNP of
53 interest. PCR conditions were as follows: Initial denaturation of 5 min at 95°C, followed by 30 cycles of 15 sec denaturation at 95°C, 45 sec primer annealing at 60°C, 1 min of extension at 72°C, and one final extension step at 72°C for 10 min. Following amplification, the reaction mixture was treated with exonuclease I (New England
Biolabs, Ipswich, MA) to degrade unused primers and bacterial Antarctic alkaline phosphatase (New England Biolabs, Ipswich, MA) to remove the 5’ phosphate groups from unused deoxynucleotides. The single base extension reaction followed, where a single primer with its 3’ end one base from the target SNP was extended by one base complementary to the SNP. I used the SNaPshot kit (Life Technologies, Foster City,
CA) that includes fluorescently labeled dideoxynucleotides that allow for extension by a single base and detection of the individual nucleotides in the product. SNaPshot reaction conditions were as follows: 25 cycles of 95°C denaturation for 10 sec, 55°C for 5 sec, and 60°C for 30 sec. Each reaction mixture was then treated with calf intestinal phosphatase (New England Biolabs, Ipswich, MA) to remove the 5’ phosphate groups from unused dideoxynucleotides before being analyzed on an Applied Biosystems 3730
DNA Analyzer and the results compiled and quantitated with GeneMapper software (Life
Technologies, Foster City, CA). Each of the four possible dideoxynucleotides was labeled with a different color fluorophore, allowing for quantitative detection of individual alleles in the amplified product. In heterozygous genomic DNA samples, the amounts of each allele are assumed to be equal. However, since different fluorophores may influence nucleotide incorporation rates and migration of the product through the capillaries in the ABI 3730, peak height ratios for DNA as well as cDNA were
54 normalized to the mean of the DNA ratios. As an additional control for variation
introduced by different fluorophores, two primers (one upstream and one downstream)
were utilized independently for the SNaPshot reaction, allowing for the comparison of
the results utilizing one pair of fluorescently labeled dideoxynucleotides to the other pair.
Genotyping Methods
Genotyping of rs1045280 was accomplished by at least one of two methods: SNaPshot,
as described above, or GC clamp. The GC clamp genotyping assay is described in detail
in (Papp et al., 2003). Briefly, I designed two different allele specific primers along with
one common primer in the opposite direction. A GC clamp of 10-15 bases was
introduced to the 5’ end of one of the allele specific primers, allowing the two different
allelic PCR products to be differentiated by their melting temperatures by an ABI 7000
Sequence Detection System real time PCR instrument.
Western Blotting
Frozen tissues from human autopsy samples were homogenized in RIPA buffer (20 mM
Tris-HCl, pH 7.5, 150 mM NaCl, 2 mM EDTA, 0.1% SDS, 1% NP-40, 0.25%
deoxycholate, 1 mM PMSF, 1 mM NaF, with Complete Mini, EDTA-free protease
inhibitor cocktail tablet (Roche Diagnostics, IN). As a positive control and to enable
identification of arrestin2 vs. arrestin1, each blot included cell lysates from
untransfected HEK 293 cells as well as cells transiently transfected with human ARRB2
(3 g or 6 g cDNA). Protein levels were determined with the use of the detergent- compatible protein assay system (Bio-Rad, Hercules, CA), and equal amounts of protein per sample (50 g from cells or 75 g from tissue) were resolved by 1-D gel
55 electrophoresis on 10% NUPAGE Bis-Tris gels (Life Technologies, Foster City, CA).
Proteins were transferred to polyvinylidene fluoride (PVDF) membranes (Immobilon P;
Millipore, Billerica, MA) and immunoblotted for arrestin2 (arrestin2 (H-9) sc-13140);
Santa Cruz Biotechnology, Inc., Santa Cruz, CA). Blots were stripped and blotted for actin levels (MAB1501 antibody; Millipore, Billerica MA), which were used to normalize the overall arrestin2 levels between samples. Chemiluminescence was detected and quantified using the Kodak 2000R imaging system (Eastman Kodak
Company, NY). Data are mean ± SEM, n=3 measurements per sample.
Cell Culture and Transient Transfection
HEK 293 cells were cultured in minimum essential medium (MEM; Life Technologies,
Foster City, CA) containing 10% heat inactivated fetal bovine serum (FBS; Life
Technologies, Foster City, CA) and 1% penicillin-streptomycin (Life Technologies,
Foster City, CA) at 37°C under 5% CO2. Transient transfections were performed by electroporation using the Gene Pulser II system (Bio-Rad, Hercules, CA). Cells were resuspended in MEM + 10% FBS + 5 mM BES at a concentration of approximately 106 cells in 0.5 ml per 0.4-cm cuvette with 3 g or 6 g of human arrestin2 cDNA in a pcDNA 3.1 (-) vector. A single pulse at 260 V, 1000 F, was used. Additional complete media without BES was added immediately to the cells, which were then returned to the incubator. The media was changed 4-6 hours later and the cells harvested 24-48 hours later in cold RIPA buffer as described above.
56 Quantitative Detection of Splice Isoforms. The ARRB2 splice variants were measured following PCR amplification of cDNA with a fluorescent Fam-labeled exon 3 primer and an exon 5 reverse primer as described in Wang et al., 2006.
Statistical Analysis
Genomic DNA and cDNA peak height ratios were normalized as described above in
“Allelic Expression Imbalance”. The presence of AEI was determined with normalized
cDNA ratios compared to the normalized genomic DNA ratio. The standard deviation
(S.D.) of the normalized genomic DNA ratio was determined and samples that had
significant allelic ratio differences between cDNA and DNA (> 2 S.D.) were considered
to show significant AEI. One-way ANOVA was performed with Prism software
(GraphPad Software, La Jolla, CA). Haplotype estimation and generation of the LD plot
were performed with Haploview 4.2 (www.broadinstitute.org/haploview/haploview;
Barrett et al., 2005)
3.3 Results
Total ARRB2 mRNA Expression
PFC from Alzheimer’s Patients and Normal Controls
I measured overall ARRB2 mRNA expression with real time PCR in postmortem human
PFC from Alzheimer’s patients (n=26) and normal controls (n=20). The ARRB2 mRNA levels measured were approximately 10-fold higher in the Alzheimer’s group than in the controls, possibly due to the lack of ARRB2-specific primers in the cDNA synthesis for
the latter. In the Alzheimer’s group, the minor allele C of rs1045280 was significantly
associated with increased ARRB2 mRNA expression (TT vs. CC, P<0.01, Fig. 3.2a). In 57 the control group, there was no correlation between rs1045280 genotype and ARRB2 mRNA expression (Fig. 3.2b).
Coriell Cultured Lymphocytes
Since ARRB2 is ubiquitously expressed, I was able to measure overall ARRB2 mRNA expression with real time PCR in cultured lymphocytes as well (n=82). ARRB2 mRNA levels in the lymphocytes were lower than in the Alzheimer’s samples but comparable to the levels observed in the control PFC samples, not surprising considering that ARRB2 is more highly expressed in brain than in lymphocytes (Unigene EST profile; Wheeler et al., 2003) but the cDNA synthesis for the RNA from the control brains was the only one that did not utilize ARRB2-specific primers. There was no significant correlation between rs1045280 genotype and ARRB2 mRNA expression in the lymphocytes (Fig.
3.2c).
58 Figure 3.2. ARRB2 mRNA expression. Real-time PCR was applied to quantify mRNA, with -actin as an internal control. ARRB2 mRNA levels are presented in arbitrary units (see Materials and Methods). Data are mean ± SEM, two cDNA syntheses and triplicate measurements for each cDNA synthesis per sample for the Alzheimer’s brains (a), and one cDNA synthesis with duplicate measurements in the control brains
(b), and lymphocytes (c). **, P<0.01, one-way ANOVA with Bonferroni post-test.
59 Figure 3.2. ARRB2 mRNA expression 60 Allelic ARRB2 mRNA Expression
PFC from Alzheimer’s Patients and Normal Controls
Measurement of the mRNA generated from each allele requires the use of frequent marker SNPs located in the transcribed region. The ARRB2 transcript contains only one
SNP with >5% heterozygosity, rs1045280, which was used as the marker SNP for all of the AEI measurements. To control for fluorescent dye bias in the SNaPshot reaction, extension primers were included for both orientations in separate reactions and analyzed separately. The two different extension primers yielded similar results, which are averaged together for each sample (Fig. 3.3). I measured allelic mRNA expression in samples heterozygous for rs1045280 from the Alzheimer’s patients (n=12) and normal controls (n=8). In the Alzheimer’s cohort, I found significant AEI in three samples (Fig.
3.3a), all below unity, indicating that the minor allele C yielded more mRNA than the major allele T in these samples. The fact that the AEI ratios were all in the same direction suggest that the marker SNP is in LD with a regulatory variant causing the AEI.
None of the control samples displayed significant AEI (Fig. 3.3b).
Coriell Cultured Lymphocytes
I measured allelic mRNA expression in 34 samples heterozygous for rs1045280 and found significant AEI in four of them (Fig. 3.3c), all below unity to a similar extent as in the Alzheimer’s samples (Fig. 3.3a). Similar to the results obtained from the Alzheimer’s cohort, these results indicate that the minor allele C yielded more mRNA than the major allele T and that the functional SNP is linked to the marker SNP rs1045280.
61 Figure 3.3. Allelic ARRB2 mRNA expression ratios. Ratios were normalized to genomic DNA and are mean ± SEM , two cDNA syntheses and at least triplicate measurements for each cDNA synthesis per sample in the Alzheimer’s brains (a), one cDNA synthesis with triplicate measurements in the control brains (b), and one cDNA synthesis with either one or triplicate measurements (samples with error bars representing the latter) in lymphocytes (c). Samples with significant AEI are denoted with a * and were determined as described in Materials and Methods.
62 Figure 3.3. Allelic ARRB2 mRNA expression ratios.
63 arrestin2 Protein Expression in Human PFC from Alzheimer’s Patients Assessed
by Western Blotting
In light of the observation that the minor allele of rs1045280 was associated with
increased ARRB2 mRNA expression in the Alzheimer’s cohort (Fig. 3.2a), I assessed
arrestin2 protein in the same samples (n=26) by Western blotting to determine whether
rs1045280 was associated with increased protein levels as well. Either 50 or 75 g of
total protein was loaded per lane and resolved by 1-D gel electrophoresis on 10% bis-tris
gels. Since the arrestin2 antibody also reacts to arrestin1, which has a slightly higher
but similar molecular weight, cell lysates from HEK 293 cells transiently transfected with
human ARRB2 cDNA were included on each gel as a positive control and to enable identification of the arrestin2 band (see representative blot; Fig. 3.4a). rrestin1 has
been shown to be the predominant arrestin in several human brain regions (Bychkov et
al., 2008), and it predominates in our human PFC samples as well (Fig. 3.4a). Both
arrestins are expressed in HEK 293 cells. However, arrestin1 is expressed at lower
levels in HEK 293 cells than arrestin2 (BioGPS database; Wu et al., 2009), which
accounts for the lack of a visible band corresponding to arrestin1 in the HEK 293 cell
lysates (Fig. 3.4a). The inclusion of the transfected HEK 293 cell lysates allowed for
unambiguous identification of the arrestin2 band on each blot. I detected no correlation
between rs1045280 genotype and arrestin2 protein levels (Fig. 3.4b).
64 Figure 3.4. Western Blot. (a) Representative Western blot and (b) densitometric analysis of relative arrestin2 protein levels in extract prepared from human PFC from
Alzheimer’s patients (75 g total protein per lane) or HEK 293 cells (50 g total protein per lane) transfected with the indicated amounts of human ARRB2 cDNA. Arrestin2 levels were normalized to actin. Data are mean ± SEM; n=3 measurements per sample.
65 Alternative Splicing of ARRB2 mRNA
To test for genetic effects on splicing, I assessed the levels of the two major splice
variants of ARRB2, the full-length long isoform and a short isoform lacking exon 4. The
experiments revealed that the full-length isoform represented the overwhelming majority
of ARRB2 mRNA in the Alzheimer’s (n=26) and normal brains (n=20) as well as the
cultured lymphocytes (n=14, Fig. 3.5). Interestingly, I did not detect the expected short
isoform but did detect additional fluorescent peaks representing PCR products that did
not correspond in size with any reported ARRB2 splice variant, representing either novel
mRNA splice variants or PCR artifacts. The peaks in question appeared consistently in
nearly all samples from the lymphocytes and both brain regions at approximately the
same intensity (Fig. 3.5), suggesting that even if they do represent real ARRB2 mRNA
splice variants, there is very little variability in alternative splicing in this region between
samples or even between tissues. Given the lack of evidence that the ARRB2 splice variants are functionally distinct and the lack of variability of the splice variants measured in our samples, I did not pursue the characterization of ARRB2 splice variants any further.
66 Alzheimer’s
Control
Lymphocyte
Short Isoform Long Isoform
(expected) (expected) Figure 3.5. Quantitative detection of ARRB2 mRNA splice variants. The peaks
correspond to PCR products of the size indicated on the X axis that have incorporated the
fam-labeled primer. Peak heights are proportional to the amount of PCR product.
Representative results from one sample from each of the three cohorts are shown.
3.4 Discussion
The present study indicates that the synonymous SNP rs1045280 is associated with
enhanced ARRB2 mRNA expression in human PFC autopsy tissues in a cohort of
Alzheimer’s patients but not in PFC from normal controls or in cultured human lymphocytes. An assessment of allelic ARRB2 mRNA expression in the same samples
suggested that rs1045280 is in LD with a functional variant or variants with a small but
significant effect (increase) on expression, an effect detected in the lymphocytes and the
Alzheimer’s cohort but not in the controls. In the Alzheimer’s cohort, measurement of
67 arrestin2 protein by Western blotting did not reveal any association between rs1045280
genotype and arrestin2 protein levels.
Since genetic regulatory mechanisms may differ between tissues, it is necessary to
assess the genetic regulation of a candidate gene in tissues where it is functionally
expressed. ARRB2 is ubiquitously expressed but I focused on brain since rs1045280 has
been linked to psychiatric disorders including tardive dyskinesia (Liou et al., 2008) and
drug addiction (Ikeda et al., 2007; Sun et al., 2008). Furthermore, I evaluated the genetic
regulation of ARRB2 in lymphocytes in order to determine whether ARRB2 is
differentially regulated in the two different tissues. It is well documented that gene
expression is altered in neurodegenerative disorders including Alzheimer’s (Liang et al.,
2008; Loring et al., 2001). Moreover, ARRB2 mRNA expression is elevated in striatum in patients with Parkinson’s disease with dementia (Bychkov et al., 2008). In the current study, ARRB2 mRNA levels were approximately 10-fold higher in the Alzheimer’s patients than in the normal controls (Fig. 3.2a,b). This difference could be due to the lack of ARRB2-specific primers in the cDNA synthesis for the normal controls and/or the
effect of Alzheimer’s disease on gene expression. Other differences between the two
cohorts are also potentially contributing factors: The average age of the controls was
much lower than that of the Alzheimer’s patients, and the controls were all female (Table
3.1).
The association of rs1045280 with increased overall ARRB2 mRNA expression in
the Alzheimer’s cohort is consistent with the only significant AEI ratios being <1 in the
same samples, since the AEI ratio is calculated as major allele expression/minor (SNP)
68 allele expression. The observation that not every sample heterozygous for rs1045280
displayed significant AEI (Fig. 3.3) is an indication that it is not a functional SNP
affecting transcription. However, all of the significant ratios observed were in the same
direction (Fig. 3.3), suggesting that rs1045280 is in LD with a functional variant. Given
the haplotype structure of ARRB2, this is not a surprising finding: ARRB2 is a relatively
small gene (~11 kb) that sits in a large haplotype block (Fig. 3.6), so any cis-acting
regulatory SNP in the gene locus is likely to be in LD with rs1045280. Given the
association of rs1045280 with enhanced ARRB2 mRNA expression in the Alzheimer’s
cohort, I assessed the relationship between rs1045280 genotype and arrestin2 protein
levels in the same tissues and found no correlation (Fig. 3.4b), most likely due to a
compensatory translational mechanism or experimental variability inherent in extracting
RNA and protein from autopsy samples.
Alternative mRNA splicing is an important source of diversity and regulation for
genes expressed in the brain (Lee et al., 2003) and is thought to be a major source of
proteomic diversity in all eukaryotes (Nilsen and Graveley, 2010). At least 22 distinct
ARRB2 splice variants have been identified,
(http://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/; Thierry-Mieg and Thierry-Mieg,
2006), with two major isoforms (http://www.ncbi.nlm.nih.gov/refseq/; Pruitt et al., 2007).
We have previously characterized two SNPs that modulate alternative splicing of dopamine D2 receptor mRNA, resulting in a shift in the balance of two functionally distinct isoforms with effects on human phenotypes including cognitive performance
(Zhang et al., 2007) and risk for cocaine addiction (Moyer et al., 2010 (manuscript in
69 preparation)). Given the importance of alternative splicing, the evidence that ARRB2
mRNA is alternatively spliced, and our previous findings that SNPs can modulate
alternative splicing with consequences for human phenotypes, I assessed the levels of the
two major ARRB2 splice variants in each cohort. The striking similarity between cohorts and tissue types (Fig. 3.5) and between samples within each cohort (data not shown) is an indication that there is little variability in alternative splicing in the region tested (exon 3-
5) in our samples, evidence that alternative splicing of exon 4 is not important for
arrestin2 regulation in human PFC or lymphocytes.
In the present study I examined the relationship between rs1045280, previously
associated with human phenotypes, and ARRB2 mRNA and expression and assessed
alternative splicing of ARRB2 mRNA in human PFC autopsy tissues and in cultured human lymphocytes. Alternative splicing did not differ between tissue types or between samples. The minor allele of rs1045280 was associated with increased overall ARRB2
mRNA expression in PFC from Alzheimer’s patients but not in PFC from normal
controls or in cultured lymphocytes. Analysis of allelic mRNA expression in the same
samples indicated that rs1045280 likely does not directly influence transcription but is in
LD with a functional variant that does, and examination of the haplotype structure of the
gene locus revealed that ARRB2 lies in a large haplotype block, so there are likely
numerous SNPs in LD with the functional variant(s) that could serve as surrogate
markers. There was no correlation between rs1045280 genotype and arrestin2 protein
levels, indicating that the must be a compensatory translational mechanism or the
difference in protein level is too small to be seen by Western blotting. Taken together,
70 the results suggest that rs1045280 is in LD with a regulatory variant exerting a small but significant effect on ARRB2 mRNA expression that is not maintained at the protein level.
Table 3.1. Demographic Characteristics
Alzheimer's Controls Patients n= 20 26 Age (mean ± SD) 59 ± 7 80 ± 9 % Female 100% 73% Caucasian 19 26 African American 1 0
71 Figure 3.6. LD plot of the ARRB2 genomic locus. (www.broadinstitute.org/haploview/haploview; Barrett et al., 2005). The sequence window spans 5 kb on either side of ARRB2 and linkage disequilibrium values (D’) are indicated as percent in each box, with darker boxes indicating higher linkage between alleles (D’=1 for the darkest boxes). The results are from the CEU population (Utah residents with ancestry from northern and western Europe; Frazer et al., 2007). 72 Table 3.2. Sequences of Oligonucleotides (Primers) Used
Experiment Oligos Comments Forward: 5'CCAGGTATCTCCCAGCTCCA Reverse: 5'CAAAGGGTAGGTCCCGC SNaPshot (AEI PEF: 5'ACCATAACCCCACTGCTCAG Also used for rs1045280 measurement) PER: 5'CGCTTCTCCCGGTTGTC genotyping Splice Variant Forward: 5'GCGGGACTTCGTAGATCACC Forward primer was Fam Detection Reverse: 5'CCAGCACATCCAGGTCTTCA labeled
Real Time PCR to Forward:5'CCAGGTATCTCCCAGCTCCA Assess ARRB2 mRNA Expression Reverse:5'CAAAGGGTAGGTCCCGC
73 Chapter 4: Allelic Imbalance in DRD3 mRNA Expression
4.1 Introduction
The dopamine receptor D3 (encoded by DRD3) is a member of the D2-like family of
dopamine receptor subtypes, which are coupled to Gi inhibitory G-proteins and generally
reduce formation of intracellular cAMP when activated (Civelli et al., 1993; Strange,
1993). DRD3 is expressed predominantly in the brain’s limbic system and nucleus
accumbens (NAc), brain regions thought to be involved in the pathophysiology of drug
addiction and schizophrenia (Suzuki et al., 1998). The involvement of D3 receptors with
addiction is well documented in preclinical studies: Pharmacological blockade of D3
receptors or genetic ablation of DRD3 in rodents both result in reduced cue-induced reinstatement of drug-seeking behavior for a number of drugs of abuse including ethanol, nicotine, opiates, and cocaine (reviewed by Le Foll et al., 2009). In humans, increased levels of DRD3 mRNA have been reported in the NAc of cocaine fatalities (Segal et al.,
1997; Staley and Mash, 1996), and decreased DRD3 mRNA expression was observed in
cortical brain regions in patients with schizophrenia (Schmauss et al., 1993). Changes in
D3 receptor density and/or function could be clinically relevant, since the D3 receptor is
thought to mediate the actions of antipsychotic drugs (Schwartz et al., 2000; Sokoloff et
74 al., 1992) and it is a potential drug target for the treatment of addiction (Pilla et al., 1999;
Xi and Gardner, 2007).
Genetic variants of DRD3 have been scrutinized in a number of association studies, often with inconsistent results (for recent review see Le Foll et al., 2009).
Association studies are often biased toward polymorphisms in the protein coding in the gene(s) of interest, and association studies of DRD3 are no exception; most have evaluated the nonsynonymous SNP rs6280, also called Ser9Gly or BalI. The Gly-9 variant has an increased affinity for dopamine in vitro (Jeanneteau et al., 2006), evidence for a gain of function. A number of clinical associations with rs6280 have been found, although they are often not replicable (Le Foll et al., 2009). It is also noted that the Ser allele frequency varies widely across ethnic populations (Crocq et al., 1996; HapMap release 22, Frazer et al., 2007; Lerer et al., 2002). Taken together, the inconsistent results of clinical association studies and varied allelic distribution of rs6280 suggest that there may be other functional variants that contribute to the phenotypes tested. Given their potential impact and predicted prevalence, regulatory polymorphisms in non-coding regions must be considered (Johnson et al., 2005; Rockman and Wray, 2002; Wray,
2007).
The DRD3 gene occupies ~50 kb on chromosome 3. The full-length isoform
(D3L) consists of 7 exons (Fig. 4.1) and DRD3 mRNA is alternatively spliced to form at least 5 distinct splice variants (http://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/;
Thierry-Mieg and Thierry-Mieg, 2006). Alternative splicing is an important source of proteomic diversity and regulation (Nilsen and Graveley, 2010) that occurs in nearly all
75 human genes (Wang et al., 2008b) and is thought to be an especially important source of diversity and regulation for neuronal genes (Lee et al., 2003). NCBI’s RefSeq database
(Pruitt et al., 2007) annotates two major DRD3 transcripts, the full-length isoform (D3L) and a truncated isoform (D3nf) with a frame shift mutation and a premature stop codon, resulting in a shortened transcript with an altered sequence beginning in exon 6 (Fig. 4.1).
D3nf mRNA is translated into a protein lacking D3-typical transmembrane-spanning domains 6 and 7 that has been detected in human brain (Liu et al., 1994). In vitro co- immunoprecipitation studies have shown that D3nf protein physically interacts with the functional D3 receptor and causes it to accumulate in an intracellular compartment rather than inserting into the plasma membrane, indicating a dominant negative effect for D3nf
(Elmhurst et al., 2000; Karpa et al., 2000).
DRD3 is expressed at low levels in the brain compared to other dopamine receptor genes, so it is critical to examine a physiologically relevant brain region where
DRD3 is functionally expressed at levels high enough to measure reliably. To this end, I measured allelic mRNA expression and alternative splicing in human brain autopsy NAc obtained from a cohort of normal controls as well as patients diagnosed with schizophrenia, bipolar disorder, or depression (n=15 in each group) and searched for
SNPs associated with altered transcript levels. Using rs6280 as the marker SNP, I detected significant AEI in 4 out of 29 samples tested, although none of the 11 SNPs genotyped were associated with the observed AEI. Additionally, I assessed D3L and
D3nf mRNA levels in the same samples and found only D3L.
76 Figure 4.1. DRD3 gene map. The altered 3’ region of D3nf is in gray. The locations of the SNPs genotyped in this study are indicated.
4.2 Materials and Methods
Human Tissue Selection and Sources
Postmortem brain tissues were donated by The Stanley Medical Research Institute's
(Chevy Chase, MD) Neuropathology Consortium Brain Collection, courtesy of Dr.
Maree Webster. We obtained frozen sections from 60 individuals previously diagnosed with schizophrenia, bipolar disorder, or depression (15 of each) and 15 controls.
DNA and RNA Preparation
Genomic DNA and total RNA were prepared from frozen brain samples. Samples were treated with sucrose-Triton with SDS and digested overnight with proteinase K, followed by sodium chloride precipitation to separate proteins and ethanol precipitation of DNA.
Total RNA was extracted with TRIzol reagent (Life Technologies, Foster City, CA) and
77 purified using RNeasy (QIAGEN, Germantown, MD) columns according to the manufacturer’s instructions, including an on-column DNase treatment to remove genomic
DNA. Complementary DNA (cDNA) was generated from 500 ng of total RNA with
Superscript III reverse transcriptase (Life Technologies, Foster City, CA) using oligo(dT) and DRD3-specific primers.
Allelic Expression Imbalance
Allele-specific mRNA expression in samples heterozygous for selected marker SNPs was measured with SNaPshot (Life Technologies, Foster City, CA). The SNaPshot assay is a single base extension method that allows quantitative comparison of two alleles. The first step was PCR amplification of the target region of DNA containing the SNP of interest. PCR conditions were as follows: Initial denaturation of 5 min at 95°C, followed by 30 cycles of 15 sec denaturation at 95°C, 45 sec primer annealing at 60°C, 1 min of extension at 72°C, and one final extension step at 72°C for 10 min. Following amplification, the reaction mixture was treated with exonuclease I (New England
Biolabs, Ipswich, MA) to degrade unused primers and bacterial Antarctic alkaline phosphatase (New England Biolabs, Ipswich, MA) to remove the 5’ phosphate groups from unused deoxynucleotides. The single base extension reaction followed, where a single primer with its 3’ end one base from the target SNP was extended by one base complementary to the SNP. I used the SNaPshot kit (Life Technologies, Foster City,
CA) that includes fluorescently labeled dideoxynucleotides that allow for extension by a single base and detection of the individual nucleotides in the product. SNaPshot reaction conditions were as follows: 25 cycles of 95°C denaturation for 10 sec, 55°C for 5 sec,
78 and 60°C for 30 sec. Each reaction mixture was then treated with calf intestinal phosphatase (New England Biolabs, Ipswich, MA) to remove the 5’ phosphate groups from unused dideoxynucleotides before being analyzed on an Applied Biosystems 3730
DNA Analyzer (Life Technologies, Foster City, CA) and the results compiled and quantitated with GeneMapper software (Life Technologies, Foster City, CA). Each of the four possible dideoxynucleotides was labeled with a different color fluorophore, allowing for quantitative detection of individual alleles in the amplified product. In heterozygous genomic DNA samples, the amounts of each allele are assumed to be equal.
However, since different fluorophores may influence nucleotide incorporation rates and migration of the product through the capillaries in the ABI 3730, peak height ratios for
DNA as well as cDNA were normalized to the mean of the DNA ratios. As an additional control for variation introduced by different fluorophores, two primers (one upstream and one downstream) were utilized independently for the SNaPshot reaction, allowing for the comparison of the results utilizing one pair of fluorescently labeled dideoxynucleotides to the other pair.
Genotyping Methods
Genotyping was accomplished by at least one of three methods: SNPlex (Life
Technologies, Foster City, CA), SNaPshot, as described above, or GC clamp. The GC clamp genotyping assay is described in detail in (Papp et al., 2003). Briefly, I designed two different allele specific primers along with one common primer in the opposite direction. A GC clamp of 10-15 bases was introduced to the 5’ end of one of the allele specific primers, allowing the two different allelic PCR products to be differentiated by
79 their melting temperatures by an ABI 7000 Sequence Detection System real time PCR
instrument.
Quantitative Detection of Splice Isoforms. The DRD3 splice variants were measured following PCR amplification of cDNA with a fluorescent Fam-labeled exon 6 primer and an exon 8 reverse primer as described in Wang et al., 2006.
Statistical Analysis
Genomic DNA and cDNA peak height ratios were normalized as described above in
“Allelic Expression Imbalance”. The presence of AEI was determined with normalized
cDNA ratios compared to the normalized genomic DNA ratio. The standard deviation
(S.D.) of the normalized genomic DNA ratio was determined and samples that had
significant allelic ratio differences between cDNA and DNA (> 2 S.D.) were considered
to show significant AEI. Haplotype tagging SNPs were selected with Haploview 4.2
(www.broadinstitute.org/haploview/haploview; Barrett et al., 2005).
4.3 Results
Allelic DRD3 mRNA Expression
Measurement of the mRNA generated from each allele requires the use of frequent
marker SNPs located in the transcribed region. The DRD3 transcript contains only one
SNP with >10% heterozygosity, rs6280, which was used as the marker SNP for all of the
AEI measurements. I measured allelic mRNA expression in samples heterozygous for
rs6280 (n=29), and identified four samples that displayed significant AEI (Fig. 4.2). The
fact that the AEI ratios go in both directions (i.e. <1 and >1) suggest that the marker SNP
80 is not in LD with a regulatory variant causing the AEI or that there may be more than one variant influencing mRNA expression.
Figure 4.2. Allelic DRD3 mRNA expression ratios. Ratios were normalized to genomic DNA and are mean ± SEM, one cDNA syntheses and at least triplicate measurements per sample. Samples with significant AEI are denoted with a * and were determined as described in Materials and Methods.
SNP Scanning
To scan for regulatory polymorphisms affecting mRNA expression, I genotyped a series of 11 SNPs in the DRD3 gene locus (Fig. 4.1) in all samples. Except for rs6280 (the marker SNP), SNPs were chosen based on their utility as haplotype tagging SNPs in the genomic region from 20 kb upstream to 20 kb downstream of DRD3: The 11 SNPs captured 30 of 44 (68%) alleles at r2 > 0.8, as assessed with Haploview 4.2 81 (www.broadinstitute.org/haploview/haploview; Barrett et al., 2005). No SNP tested was significantly associated with the observed AEI.
Alternative Splicing of DRD3 mRNA
To test for genetic effects on splicing, I assessed the levels of the two major splice variants of DRD3; D3L and D3nf and detected only D3L (Fig. 4.3) in all samples. The absence of PCR product corresponding to D3nf was not due to complete failure of the
PCR reaction, since virtually all samples displayed robust amplification of a single product corresponding to D3L (Fig. 4.3).
82 Figure 4.3. Quantitative detection of DRD3 mRNA splice variants. The peaks correspond to PCR products of the size indicated on the X axis that have incorporated the fam-labeled primer. Peak heights are proportional to the amount of PCR product.
Representative results from three NAc samples are shown.
83 4.4 Discussion
The present study indicates that there is at least one regulatory cis-acting variant with a modest effect on DRD3 mRNA expression, although none of the 11 SNPs tested could account for the observed AEI. Measurements of DRD3 mRNA splice variants indicate that D3nf is not expressed at detectable levels in the samples tested.
Since gene regulation is tissue specific, it is critical to examine the regulation of a candidate gene in tissues where it is functionally expressed. This is an especially important consideration for DRD3, due to its relatively low expression and high homology with other dopamine receptor genes. NAc was an ideal brain region for this study, since DRD3 is most highly expressed in NAc and other limbic areas of the brain
(Sokoloff et al., 1990; Bouthenet et al., 1991).
Significant AEI was observed in only 4 out of 29 samples tested, an indication that the marker SNP (rs6280) does not influence mRNA expression. That there was AEI in some samples suggests the existence of at least one cis-acting regulatory variant affecting DRD3 mRNA expression. Moreover, the allelic ratios of the samples with significant AEI were not all in the same direction, indicating that rs6280 is not in LD with the causal variant and/or that there may be more than one causal variant.
Given the potential dominant negative effect of D3nf (Elmhurst et al., 2000;
Karpa et al., 2000), alternative splicing of DRD3 to form D3L or D3nf represents an important regulatory event that could have important biological consequences.
Furthermore, it is well-documented that cis-acting genetic polymorphisms can modulate alternative splicing (Attaie et al., 1997; Ng et al., 2008; Zhang et al., 2007; Moyer,
84 manuscript in preparation). Given the functional significance of DRD3 mRNA splicing
and the evidence that cis-regulatory variants can affect alternative mRNA splicing, I
assessed D3L and D3nf mRNA (cDNA) levels in postmortem human NAc samples that I
had already genotyped a number of SNPs across the DRD3 gene locus. I did not detect
D3nf, a surprising finding since it has previously been detected at levels comparable to
D3L in 12 different regions in postmortem human brain, including NAc (Schmauss et al.,
1993). These disparate results could be due to a number of factors, including different
experimental conditions (primers, PCR conditions) or differences in the populations
tested including age, sex, race, or postmortem interval and condition of the samples.
In the present study I assessed allelic mRNA expression and alternative splicing
in human brain autopsy NAc obtained from a cohort of normal controls as well as
patients diagnosed with schizophrenia, bipolar disorder, or depression (n=15 in each
group). Significant AEI was detected in 4 out of 29 samples tested, indicating the
existence of at least one cis-acting regulatory variant affecting mRNA expression.
However, none of the 11 SNPs tested could account for the observed AEI. Evaluation of
D3L and D3nf mRNA levels revealed detectable levels of D3L only, an indication that
D3nf is not expressed in the samples tested. These results suggest the existence of a cis- acting regulatory variant affecting DRD3 mRNA expression that is not in LD with any
SNP tested and call into question whether D3nf mRNA is universally expressed in human
NAc.
85 Table 4.1. Sequences of Oligonucleotides (Primers) Used
Experiment Oligos Comments Forward: 5'GAAGCCCCTTGGCATCAC SNaPshot (AEI Reverse: 5'GCCCCACAGGTGTAGTTCAG Also used for rs6280 measurement) PEP: 5'TCTCTGAGCCAGCTGAGT genotyping Splice Variant Forward: 5'AAAGAGAGGAGAAGACTCGGAATTC Forward primer was Fam Detection Reverse: 5'TGGGTATTGAGAACATGGGTCA labeled Forward: 5'ACTCCTTGACCCCCGTGG WT Reverse: 5'GAAGTCCAGAGAGAAAGGATCGCT SNP Reverse: rs9825563 GC 5'CGCGCCGGCGGCCGGAAGTCCAGAGAGAA Clamp Genotyping AGGATGACC WT Forward: 5'TAGAGCTCAGGCACATGCTCA SNP Forward: 5'GGCCGGCCCGGGCGTAGAGCTCAGGCACA TGGACC rs9824856 GC Reverse: Clamp Genotyping 5'ACCACTACTAGAGGAGTTCTGAAGTCTC rs324036 Forward: 5'TGCTAGGATTATAGGTGTGAGGCA SNaPshot Reverse: 5'AATACCTGGAATGAGGCCTGG Genotyping PEP: 5'GGCACTGTGCTCAGCCTT rs167771 Forward: 5'TCATCTCTTCCCAGGTTGCC SNaPshot Reverse: 5'GAATCAGACTGTGGGAATGTGAA Genotyping PEP: 5'CATGCTCCAAAGTCTATCACAAT rs12491239 Forward: 5'TGATATGAGCAATTGATGGAAATGA SNaPshot Reverse: 5'CCAAGCATTAGTTGTTCCTCTTCA Genotyping PEP: 5'GCAGTATTTTCTGAAATAACAAAGC rs3732783 Forward: 5'GCATCTCTGAGCCAGCTGAG SNaPshot Reverse: 5'GGCTGGCACCTGTGGAGT Genotyping PEP: 5'CTGAACTACACCTGTGGGGC rs2630351 Forward: 5'GGGCGGTGCCAGGATTAG SNaPshot Reverse: 5'AGAAGGCAGGGATGTAGTTGGA Genotyping PEP: 5'CTATTTGACTCCAAGTTAGTAATCTTAA
86 Bilbliography
American Cancer Society. Cancer Facts & Figures 2003. Atlanta: American Cancer Society; 2003.
Arinami T, Gao M, Hamaguchi H, Toru M (1997). A functional polymorphism in the promoter region of the dopamine D2 receptor gene is associated with schizophrenia. Human Molecular Genetics 6(4): 577-582.
Attaie A, Kim E, Wilcox ER, Lalwani AK (1997). A splice-site mutation affecting the paired box of PAX3 in a three generation family with Waardenburg syndrome type I (WS1). Molecular and Cellular Probes 11(3): 233-236.
Ballon N, Leroy S, Roy C, Bourdel MC, Olie JP, Charles-Nicolas A, et al (2007). Polymorphisms TaqI A of the DRD2, BalI of the DRD3, Exon III repeat of the DRD4, and 3 ' UTR VNTR of the DAT: Association with childhood ADHD in male African-Caribbean cocaine dependents? American Journal of Medical Genetics Part B-Neuropsychiatric Genetics 144B(8): 1034-1041.
Barrett JC, Fry B, Maller J, Daly MJ (2005). Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21(2): 263-265.
Beaulieu JM, Marion S, Rodriguiz RM, Medvedev IO, Sotnikova TD, Ghisi V, et al (2008). A beta-arrestin 2 signaling complex mediates lithium action on Behavior. Cell 132(1): 125-136.
Beaulieu JM, Sotnikova TD, Marion S, Lefkowitz RJ, Gainetdinov RR, Caron MG (2005). An Akt/beta-arrestin 2/PP2A signaling complex mediates dopaminergic neurotransmission and behavior. Cell 122(2): 261-273.
Bertolino A, Fazio L, Di Giorgio A, Blasi G, Romano R, Taurisano P, et al (2009a). Genetically Determined Interaction between the Dopamine Transporter and the D-2
87 Receptor on Prefronto-Striatal Activity and Volume in Humans. Journal of Neuroscience 29(4): 1224-1234.
Bertolino A, Fazio L, Caforio G, Blasi G, Rampino A, Romano R, et al (2009b). Functional variants of the dopamine receptor D2 gene modulate prefronto-striatal phenotypes in schizophrenia. Brain 132: 417-425.
Bertolino A, Taurisano P, Pisciotta NM, Blasi G, Fazio L, Romano R, et al (2010). Genetically Determined Measures of Striatal D2 Signaling Predict Prefrontal Activity during Working Memory Performance. Plos One 5(2).
Blasi G, Lo Bianco L, Taurisano P, Gelao B, Romano R, Fazio L, et al (2009). Functional Variation of the Dopamine D-2 Receptor Gene Is Associated with Emotional Control as well as Brain Activity and Connectivity during Emotion Processing in Humans. Journal of Neuroscience 29(47): 14812-14819.
Bohn LM, Gainetdinov RR, Sotnikova TD, Medvedev IO, Lefkowitz RJ, Dykstra LA, et al (2003). Enhanced rewarding properties of morphine, but not cocaine, in beta arrestin-2 knock-out mice. Journal of Neuroscience 23(32): 10265-10273.
Bohn LM, Lefkowitz RJ, Gainetdinov RR, Peppel K, Caron MG, Lin FT (1999). Enhanced morphine analgesia in mice lacking beta-arrestin 2. Science 286(5449): 2495-2498.
Bolan EA, Kivell B, Jaligam V, Oz M, Jayanthi LD, Han Y, Sen N, Urizar E, Gomes I, Devi LA, Ramamoorthy S, Javitch JA, Zapata A, Shippenberg TS (2007) D2 receptors regulate dopamine transporter function via an extracellular signal- regulated kinases 1 and 2-dependent and phosphoinositide 3 kinase-independent mechanism. Mol Pharmacol 71:1222–1232.
Bouthenet ML, Souil E, Martres MP, Sokoloff P, Giros B, Schwartz JC (1991). Localization of dopamine-D3 receptor messenger –RNA in the rat-brain using in situ hybridization histochemistry – comparison with dopamine D2-receptor messenger –RNA. Brain Research 564(2): 203-219.
Bray NJ, Buckland PR, Owen MJ, O'Donovan MC (2003). Cis-acting variation in the expression of a high proportion of genes in human brain. Human Genetics 113(2): 149-153.
Brookes K, Xu X, Chen W, Zhou K, Neale B, Lowe N, et al (2006). The analysis of 51 genes in DSM-IV combined type attention deficit hyperactivity disorder: association signals in DRD4, DAT1 and 16 other genes. Molecular Psychiatry 11(10): 934-953.
88 Bychkov ER, Gurevich VV, Joyce JN, Benovic JL, Gurevich EV (2008). Arrestins and two receptor kinases are upregulated in Parkinson's disease with dementia. Neurobiology of Aging 29(3): 379-396.
Callahan R, Balbinde.E (1970). Tryptophan operon-structural gene mutation creating a promoter and leading to 5-methyl tryptophan dependence. Science 168(3939): 1586-&.
Carlson CS, Eberle MA, Kruglyak L, Nickerson DA (2004). Mapping complex disease loci in whole-genome association studies. Nature 429(6990): 446-452.
Centers for Disease Control and Prevention. Annual Smoking–Attributable Mortality, Years of Potential Life Lost, and Productivity Losses — United States, 1997–2001. Morbidity and Mortality Weekly Report 54(25):625–628, July 1, 2005.
Centonze D, Grande C, Usiello A, Gubellini P, Erbs E, Martin AB, et al (2003). Receptor subtypes involved in the presynaptic and postsynaptic actions of dopamine on striatal interneurons. Journal of Neuroscience 23(15): 6245-6254.
Centonze D, Gubellini P, Usiello A, Rossi S, Tscherter A, Bracci E, et al (2004a). Differential contribution of dopamine D2S and D2L receptors in the modulation of glutamate and GABA transmission in the striatum. Neuroscience 129(1): 157-166.
Chen WG, Chang Q, Lin YX, Meissner A, West AE, Griffith EC, et al (2003). Derepression of BDNF transcription involves calcium-dependent phosphorylation of MeCP2. Science 302(5646): 885-889.
Civelli O, Bunzow JR, Grandy DK (1993). Molecular Diversity of the dopamine receptors. Annual Review of Pharmacology and Toxicology 33: 281-307.
Crocq MA, Buguet A, Bisser S, Burgert E, Stanghellini A, Uyanik G, et al (1996). BalI and MspI polymorphisms of the dopamine D3 receptor gene in African blacks and Caucasians. Human Heredity 46(1): 58-60. de Krom M, Staal WG, Ophoff RA, Hendriks J, Buitelaar J, Franke B, et al (2009). A Common Variant in DRD3 Receptor Is Associated with Autism Spectrum Disorder. Biological Psychiatry 65(7): 625-+.
DeWire SM, Ahn S, Lefkowitz RJ, Shenoy SK (2007). beta-arrestins and cell signaling. Annual Review of Physiology 69: 483-510.
Di Chiara G (1998). A motivational learning hypothesis of the role of mesolimbic dopamine in compulsive drug use. Journal of Psychopharmacology 12(1): 54-67.
89 Doehring A, von Hentig N, Graff J, Salamat S, Schmidt M, Geisslinger G, et al (2009). Genetic variants altering dopamine D2 receptor expression or function modulate the risk of opiate addiction and the dosage requirements of methadone substitution. Pharmacogenetics and Genomics 19(6): 407-414.
Dubertret C, Gorwood P, Ades J, Feingold J, Schwartz JC, Sokoloff P (1998). Meta- analysis of DRD3 gene and schizophrenia: Ethnic heterogeneity and significant association in Caucasians. American Journal of Medical Genetics 81(4): 318-322.
Elmhurst JL, Xie ZD, O'Dowd BF, George SR (2000). The splice variant D3nf reduces ligand binding to the D3 dopamine receptor: evidence for heterooligomerization. Molecular Brain Research 80(1): 63-74.
Ferguson SSG (2001). Evolving concepts in G protein-coupled receptor endocytosis: The role in receptor desensitization and signaling. Pharmacological Reviews 53(1): 1-24.
Ferguson SSG, Downey WE, Colapietro AM, Barak LS, Menard L, Caron MG (1996). Role of beta-arrestin in mediating agonist-promoted G protein-coupled receptor internalization. Science 271(5247): 363-366.
Frank MJ, Hutchison K (2009). Genetic contributions to avoidance-based decisions:striatal D2 receptor polymorphisms. Neuroscience 164(1): 131-140.
Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, Gibbs RA, et al (2007). A second generation human haplotype map of over 3.1 million SNPs. Nature 449(7164): 851-U853.
Gasso P, Mas S, Bernardo M, Alvarez S, Parellada E, Lafuente A (2009). A common variant in DRD3 gene is associated with risperidone-induced extrapyramidal symptoms. Pharmacogenomics Journal 9(6): 404-410.
Giordano TP, Satpute SS, Striessnig J, Kosofsky BE, Rajadhyaksha AM (2006). Up- regulation of dopamine D2L mRNA levels in the ventral tegmental area and dorsal striatum of amphetamine-sensitized C57BL/6 mice: role of Ca(v)1.3 L-type Ca2+ channels. Journal of Neurochemistry 99(4): 1197-1206.
Glatt SJ, Faraone SV, Lasky-Su JA, Kanazawa T, Hwu HG, Tsuang MT (2009). Family-based association testing strongly implicates DRD2 as a risk gene for schizophrenia in Han Chinese from Taiwan. Molecular Psychiatry 14(9): 885-893.
Gosso MF, de Geus EJC, Polderman TJC, Boomsma DI, Heutink P, Posthuma D (2008). Catechol O-methyl transferase and dopamine D2 receptor gene polymorphisms: evidence of positive heterosis and gene-gene interaction on 90 working memory functioning. European Journal of Human Genetics 16(9): 1075- 1082.
Guindalini C, Howard M, Haddley K, Laranjeira R, Collier D, Ammar N, et al (2006). A dopamine transporter gene functional variant associated with cocaine abuse in a Brazilian sample. Proceedings of the National Academy of Sciences of the United States of America 103(12): 4552-4557.
Haliassos A, Chomel JC, Grandjouan S, Kruh J, Kaplan JC, Kitzis A (1989a). Detection of minority point mutations by modified PCR trechniques – a new approach for a sensitive diagnosis of tumor-progression. Nucleic Acids Research 17(20): 8093-8099.
Haliassos A, Chomel JC, Tesson L, Baudis M, Kruh J, Kaplan JC, et al (1989b). Modification of enzymatically amplified DNA for the detection of point mutations. Nucleic Acids Research 17(9): 3606-3606.
Harwood, H. Updating Estimates of the Economic Costs of Alcohol Abuse in the United States: Estimates, Update Methods, and Data Report. Prepared by the Lewin Group for the National Institute on Alcohol Abuse and Alcoholism, 2000.
Herman AI, Kaiss KM, Ma R, Philbeck JW, Hasan A, Dasti H, et al (2005). Serotonin transporter promoter polymorphism and monoamine oxidase type a VNTR allelic variants together influence alcohol binge drinking risk in young women. American Journal of Medical Genetics Part B-Neuropsychiatric Genetics 133B(1): 74-78.
Hiroi N, Agatsuma S (2005). Genetic susceptibility to substance dependence. Molecular Psychiatry 10(4): 336-344.
Howard LA, Sellers EM, Tyndale RF (2002). The role of pharmacogenetically- variable cytochrome P450 enzymes in drug abuse and dependence. Pharmacogenomics 3(2): 185-199.
Huang WH, Payne TJ, Ma JZ, Beuten J, Dupont RT, Inohara N, et al (2009). Significant Association of ANKK1 and Detection of a Functional Polymorphism with Nicotine Dependence in an African-American Sample. Neuropsychopharmacology 34(2): 319-330.
Huang WH, Payne TJ, Ma JZ, Li MD (2008). A Functional Polymorphism, rs6280, in DRD3 Is Significantly Associated With Nicotine Dependence in European- American Smokers. American Journal of Medical Genetics Part B-Neuropsychiatric Genetics 147B(7): 1109-1115.
91 Huang YY, Cate SP, Battistuzzi C, Oquendo MA, Brent D, Mann JJ (2004). An association between a functional polymorphism in the monoamine oxidase A gene promoter, impulsive traits and early abuse experiences. Neuropsychopharmacology 29(8): 1498-1505.
Hwang R, Shinkai T, De Luca V, Muller DJ, Ni XQ, Macciardi F, et al (2005). Association study of 12 polymorphisms spanning the dopamine D-2 receptor gene and clozapine treatment response in two treatment refractory/intolerant populations. Psychopharmacology 181(1): 179-187.
Hwang R, Shinkai T, Deluca V, Macciardi F, Potkin S, Meltzer HY, et al (2006). Dopamine D2 receptor gene variants and quantitative measures of positive and negative symptom response following clozapine treatment. European Neuropsychopharmacology 16(4): 248-259.
Hyman SE, Malenka RC, Nestler EJ (2006). Neural mechanisms of addiction: The role of reward-related learning and memory. Annual Review of Neuroscience 29: 565-598.
Ikeda M, Ozaki N, Suzuki T, Kitajima T, Yamanouchi Y, Kinoshita Y, et al (2007). Possible association of beta-arrestin 2 gene with methamphetamine use disorder, but not schizophrenia. Genes Brain and Behavior 6(1): 107-112.
Ishiguro H, Arinami T, Saito T, Akazawa S, Enomoto M, Mitushio H, et al (1998). Association study between the -141C Ins/Del and TaqI A polymorphisms of the dopamine D2 receptor gene and alcoholism. Alcoholism-Clinical and Experimental Research 22(4): 845-848.
Jeanneteau F, Funalot B, Jankovic J, Deng H, Lagarde JP, Lucotte G, et al (2006). A functional variant of the dopamine D-3 receptor is associated with risk and age-at- onset of essential tremor. Proceedings of the National Academy of Sciences of the United States of America 103(28): 10753-10758.
Jia YB, Persson C, Hou LF, Zheng ZL, Yeager M, Lissowska J, et al (2010). A comprehensive analysis of common genetic variation in MUC1, MUC5AC, MUC6 genes and risk of stomach cancer. Cancer Causes & Control 21(2): 313-321.
Jiang XY, Zhou J, Mash DC, Marini AM, Lipsky RH (2009). Human BDNF Isoforms are Differentially Expressed in Cocaine Addicts and are Sorted to the Regulated Secretory Pathway Independent of the Met66 Substitution. Neuromolecular Medicine 11(1): 1-12.
Johnson AD, Gong Y, Wang D, Langaee TY, Shin J, Cooper-DeHoff RM, et al (2009). Promoter Polymorphisms in ACE (Angiotensin I-Converting Enzyme) 92 Associated With Clinical Outcomes in Hypertension. Clinical Pharmacology & Therapeutics 85(1): 36-44.
Johnson AD, Handsaker RE, Pulit SL, Nizzari MM, O'Donnell CJ, de Bakker PIW (2008a). SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics 24(24): 2938-2939.
Johnson AD, Wang DX, Sadee W (2005). Polymorphisms affecting gene regulation and mRNA processing: Broad implications for pharmacogenetics. Pharmacology & Therapeutics 106(1): 19-38.
Johnson AD, Zhang Y, Papp AC, Pinsonneault JK, Lim JE, Saffen D, et al (2008b). Polymorphisms affecting gene transcription and mRNA processing in pharmacogenetic candidate genes: detection through allelic expression imbalance in human target tissues. Pharmacogenetics and Genomics 18(9): 781-791.
Jonsson EG, Flyckt L, Burgert E, Crocq MA, Forslund K, Mattila-Evenden M, et al (2003). Dopamine D3 receptor gene Ser9Gly variant and schizophrenia: association study and meta-analysis. Psychiatric Genetics 13(1): 1-12.
Karpa KD, Lin RW, Kabbani N, Levenson R (2000). The dopamine D3 receptor interacts with itself and the truncated D3 splice variant D3nf: D3-D3nf interaction causes mislocalization of D3 receptors. Molecular Pharmacology 58(4): 677-683.
Kendler KS, Neale MC, Heath AC, Kessler RC, Eaves LJ (1994). A twin-family study of alcoholism in women. American Journal of Psychiatry 151(5): 707-715.
Khan ZU, Mrzljak L, Gutierrez A, de la Calle A, Goldman-Rakic PS (1998). Prominence of the dopamine D2 short isoform in dopaminergic pathways. Proceedings of the National Academy of Sciences of the United States of America 95(13): 7731-7736.
Klewe IV, Nielsen SM, Tarpo L, Urizar E, Dipace C, Javitch JA, et al (2008). Recruitment of beta-arrestin2 to the dopamine D2 receptor: Insights into anti- psychotic and anti-parkinsonian drug receptor signaling. Neuropharmacology 54(8): 1215-1222.
Kollins SH, Anastopoulos AD, Lachiewicz AM, FitzGerald D, Morrissey-Kane E, Garrett ME, et al (2008). SNPs in Dopamine D2 Receptor Gene (DRD2) and Norepinephrine Transporter Gene (NET) are Associated With Continuous Performance Task (CPT) Phenotypes in ADHD Children and Their Families. American Journal of Medical Genetics Part B-Neuropsychiatric Genetics 147B(8): 1580-1588.
93 Koob GF, Bloom FE (1988). Cellular and molecular mechanisms of drug- dependence. Science 242(4879): 715-723.
Kreek MJ, Bart G, Lilly C, Laforge KS, Nielsen DA (2005). Pharmacogenetics and human molecular genetics of opiate and cocaine addictions and their treatments. Pharmacological Reviews 57(1): 1-26.
Kreek MJ, Nielsen DA, LaForge KS (2004). Genes associated with addiction - Alcoholism, opiate, and cocaine addiction. Neuromolecular Medicine 5(1): 85-108.
Laird PW (2005). Cancer epigenetics. Human Molecular Genetics 14: R65-R76.
Lan HX, Teeter MM, Gurevich VV, Neve KA (2009). An Intracellular Loop 2 Amino Acid Residue Determines Differential Binding of Arrestin to the Dopamine D-2 and D-3 Receptors. Molecular Pharmacology 75(1): 19-26.
Lane HY, Hsu SK, Liu YC, Chang YC, Huang CH, Chang WH (2005). Doparnine D-3 receptor Ser9GIy polymorphism and risperidone response. Journal of Clinical Psychopharmacology 25(1): 6-11.
Lawford BR, Young RM, Noble EP, Sargent J, Rowell J, Shadforth S, et al (2000). The D-2 dopamine receptor al allele and opioid dependence: Association with heroin use and response to methadone treatment. American Journal of Medical Genetics 96(5): 592-598.
Lawford BR, Young RM, Swagell CD, Barnes M, Burton SC, Ward WK, et al (2005). The C/C genotype of the C957T polymorphism of the dopamine D2 receptor is associated with schizophrenia. Schizophrenia Research 73(1): 31-37.
Le Foll B, Gallo A, Le Strat Y, Lu L, Gorwood P (2009). Genetics of dopamine receptors and drug addiction: a comprehensive review. Behavioural Pharmacology 20(1): 1-17.
Lee CJ, Irizarry K (2003). Alternative splicing in the nervous system: An emerging source of diversity and regulation. Biological Psychiatry 54(8): 771-776.
Lee FJ, Pei L, Moszczynska A, Vukusic B, Fletcher PJ, Liu F (2007) Dopamine transporter cell surface localization facilitated by a direct interaction with the dopamine D2 receptor. EMBO J 26:2127–2136.
Lerer B, Segman RH, Fangerau H, Daly AK, Basile VS, Cavallaro R, et al (2002). Pharmacogenetics of tardive dyskinesia: Combined analysis of 780 patients supports 94 association with dopamine D3 receptor gene Ser9Gly polymorphism. Neuropsychopharmacology 27(1): 105-119.
Liang WS, Dunckley T, Beach TG, Grover A, Mastroeni D, Ramsey K, et al (2008). Altered neuronal gene expression in brain regions differentially affected by Alzheimer's disease: a reference data set. Physiological Genomics 33(2): 240-256.
Lim JE, Pinsonneault J, Sadee W, Saffen D (2007). Tryptophan hydroxylase 2 (TPH2) haplotypes predict levels of TPH2 mRNA expression in human pons. Molecular Psychiatry 12(5): 491-501.
Lin FT, Daaka Y, Lefkowitz RJ (1998). beta-arrestins regulate mitogenic signaling and clathrin-mediated endocytosis of the insulin-like growth factor I receptor. Journal of Biological Chemistry 273(48): 31640-31643.
Liou YJ, Wang YC, Chen JY, Chen ML, Chen TT, Bai YM, et al (2008). The coding-synonymous polymorphism rs1045280 (Ser280Ser) in beta-arrestin 2 (ARRB2) gene is associated with tardive dyskinesia in Chinese patients with schizophrenia. European Journal of Neurology 15(12): 1406-1408.
Liu K, Bergson C, Levenson R, Schmauss C (1994). On the origin of messenger- RNA encoding the truncated dopamine D3-type receptor D3nf and detection of D3nf-like immunoreactivity in human brain. Journal of Biological Chemistry 269(46): 29220-29226.
Loring JF, Wen X, Lee JM, Seilhamer J, Somogyi R (2001). A gene expression profile of Alzheimer's disease. DNA and Cell Biology 20(11): 683-695.
Lucht M, Samochowiec A, Samochowiec J, Jasiewicz A, Grabe HJ, Geissler I, et al (2010). Influence of DRD2 and ANKK1 genotypes on apomorphine-induced growth hormone (GH) response in alcohol-dependent patients. Progress in Neuro- Psychopharmacology & Biological Psychiatry 34(1): 45-49.
Lull ME, Freeman WM, Vrana KE, Mash DC (2008). Correlating Human and Animal Studies of Cocaine Abuse and Gene Expression. Addiction Reviews 2008. Vol 1141, pp 58-75.
Luttrell LM, Lefkowitz RJ (2002). The role of beta-arrestins in the termination and transduction of G-protein-coupled receptor signals. Journal of Cell Science 115(3): 455-465.
Luttrell LM, Roudabush FL, Choy EW, Miller WE, Field ME, Pierce KL, et al (2001). Activation and targeting of extracellular signal-regulated kinases by beta-
95 arrestin scaffolds. Proceedings of the National Academy of Sciences of the United States of America 98(5): 2449-2454.
Manuck SB, Flory JD, Ferrell RE, Mann JJ, Muldoon MF (2000). A regulatory polymorphism of the monoamine oxidase-A gene may be associated with variability in aggression, impulsivity, and central nervous system serotonergic responsivity. Psychiatry Research 95(1): 9-23.
Moser D, Ekawardhani S, Kumsta R, Palmason H, Bock C, Athanassiadou Z, et al (2009). Functional Analysis of a Potassium-Chloride Co-Transporter 3 (SLC12A6) Promoter Polymorphism Leading to an Additional DNA Methylation Site. Neuropsychopharmacology 34(2): 458-467.
Munafo MR, Clark TG, Johnstone EC, Murphy MFG, Walton RT (2004). The genetic basis for smoking behavior: A systematic review and meta-analysis. Nicotine & Tobacco Research 6(4): 583-597.
Munafo MR, Matheson IJ, Flint J (2007). Association of the DRD2 gene Taq1A polymorphism and alcoholism: a meta-analysis of case-control studies and evidence of publication bias. Molecular Psychiatry 12(5): 454-461.
Neville MJ, Johnstone EC, Walton RT (2004). Identification and characterization of ANKK1: A novel kinase gene closely linked to DRD2 on chromosome band 11q23.1. Human Mutation 23(6): 540-545.
Ng W, Loh AXW, Teixeira AS, Pereira SP, Swallow DM (2008). Genetic regulation of MUC1 alternative splicing in human tissues. British Journal of Cancer 99(6): 978-985.
Nilsen TW, Graveley BR (2010). Expansion of the eukaryotic proteome by alternative splicing. Nature 463(7280): 457-463.
Noble EP, Blum K, Khalsa ME, Ritchie T, Montgomery A, Wood RC, et al (1993). Allelic association of the D(2) dopamine-receptor gene with cocaine dependence. Drug and Alcohol Dependence 33(3): 271-285.
Office of National Drug Control Policy. The Economic Costs of Drug Abuse in the United States: 1992-2002. Washington, DC: Executive Office of the President (Publication No. 207303), 2004.
Papp AC, Pinsonneault JK, Cooke G, Sadee W (2003). Single nucleotide polymorphism genotyping using allele-specific PCR and fluorescence melting curves. Biotechniques 34(5): 1068-1072.
96 Perry SJ, Lefkowitz RJ (2002). Arresting developments in heptahelical receptor signaling and regulation. Trends in Cell Biology 12(3): 130-138.
Petersen M, Amer Diabet A (2003). Economic costs of diabetes in the US in 2002. Diabetes Care 26(3): 917-932.
Pilla M, Perachon S, Sautel F, Garrido F, Mann A, Wermuth CG, et al (1999). Selective inhibition of cocaine-seeking behaviour by a partial dopamine D-3 receptor agonist. Nature 400(6742): 371-375.
Pinsonneault JK, Papp AC, Sadee W (2006). Allelic mRNA expression of X-linked monoamine oxidase a (MAOA) in human brain: dissection of epigenetic and genetic factors. Human Molecular Genetics 15(17): 2636-2649.
Prescott CA, Kendler KS (1999). Genetic and environmental contributions to alcohol abuse and dependence in a population-based sample of male twins. American Journal of Psychiatry 156(1): 34-40.
Preuss UW, Zill P, Koller G, Bondy B, Soyka M (2007). D2 dopamine receptor gene haplotypes and their influence on alcohol and tobacco consumption magnitude in alcohol-dependent individuals. Alcohol and Alcoholism 42(3): 258-266.
Pruitt KD, Tatusova T, Maglott DR (2007). NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Research 35: D61-D65.
Roberts JW (1969). Promotor mutation in vitro. Nature 223(5205): 480-&.
Rockman MV, Wray GA (2002). Abundant raw material for cis-regulatory evolution in humans. Molecular Biology and Evolution 19(11): 1991-2004.
Ross JR, Rutter D, Welsh K, Joel SP, Goller K, Wells AU, et al (2005). Clinical response to morphine in cancer patients and genetic variation in candidate genes. Pharmacogenomics Journal 5(5): 324-336.
Sasabe T, Furukawa A, Matsusita S, Higuchi S, Ishiura S (2007). Association analysis of the dopamine receptor D2 (DRD2) SNP rs1076560 in alcoholic patients. Neuroscience Letters 412(2): 139-142.
Scharfetter J, Chaudhry HR, Hornik K, Fuchs K, Sieghart W, Kasper S, et al (1999). Dopamine D3 receptor gene polymorphism and response to clozapine in schizophrenic Pakistani patients. European Neuropsychopharmacology 10(1): 17- 20.
97 Schmauss C, Haroutunian V, Davis KL, Davidson M (1993). Selective loss of dopamine-D3-type receptor messenger-RNA expression in parietal and motor cortices of patients with chronic-schizophrenia. Proceedings of the National Academy of Sciences of the United States of America 90(19): 8942-8946.
Schwartz JC, Diaz J, Pilon C, Sokoloff P (2000). Possible implications of the dopamine D-3 receptor in schizophrenia and in antipsychotic drug actions. Brain Research Reviews 31(2-3): 277-287.
Seamans JK, Yang CR (2004). The principal features and mechanisms of dopamine modulation in the prefrontal cortex. Progress in Neurobiology 74(1): 1-57.
Segal DM, Moraes CT, Mash DC (1997). Up-regulation of D3 dopamine receptor mRNA in the nucleus accumbens of human cocaine fatalities. Molecular Brain Research 45(2): 335-339.
Smith JW, Fetsko LA, Xu R, Wang Y (2002). Dopamine D2L receptor knockout mice display deficits in positive and negative reinforcing properties of morphine and in avoidance learning. Neuroscience 113(4): 755-765.
Smith L, Watson M, Gates S, Ball D, Foxcroft D (2008). Meta-analysis of the association of the Taq1A polymorphism with the risk of alcohol dependency: A HuGE gene-disease association review. American Journal of Epidemiology 167(2): 125-138.
Sokoloff P, Andrieux M, Besancon R, Pilon C, Martres MP, Giros B, et al (1992). Pharmacology of human dopamine D3 receptor expressed in a mammalian cell line comparison with D2 receptor. European Journal of Pharmacology-Molecular Pharmacology Section 225(4): 331-337.
Sokoloff P, Giros B, Martres MP, Bouthenet ML, Schwartz JC (1990). Molecular cloning and characterization of a novel dopamine receptor (D3) as a target for neuroleptics. Nature 347(6289): 146-151.
Staley JK, Mash DC (1996). Adaptive increase in D-3 dopamine receptors in the brain reward circuits of human cocaine fatalities. Journal of Neuroscience 16(19): 6100-6106.
Steen VM, Lovlie R, MacEwan T, McCreadie RG (1997). Dopamine D3-receptor gene variant and susceptibility to tardive dyskinesia in schizophrenic patients. Molecular Psychiatry 2(2): 139-145.
Strange PG (1993). New insights into dopamine receptors in the central nervous system. Neurochemistry International 22(3): 223-236. 98 Sun D, Ma JZ, Payne TJ, Li MD (2008). beta-Arrestins 1 and 2 are associated with nicotine dependence in European American smokers. Molecular Psychiatry 13(4): 398-406.
Suzuki M, Hurd YL, Sokoloff P, Schwartz JC, Sedvall G (1998). D-3 dopamine receptor mRNA is widely expressed in the human brain. Brain Research 779(1-2): 58-74.
Szekeres G, Keri S, Juhasz A, Rimanoczy A, Szendi I, Czimmer C, et al (2004). Role of dopamine D3 receptor (DRD3) and dopamine transporter (DAT) polymorphism in cognitive dysfunctions and therapeutic response to atypical antipsychotics in patients with schizophrenia. American Journal of Medical Genetics Part B-Neuropsychiatric Genetics 124B(1): 1-5.
Talkowski ME, Mansour H, Chowdari KV, Wood J, Butler A, Varma PG, et al (2006). Novel, replicated associations between dopamine D3 receptor gene polymorphisms and schizophrenia in two independent samples. Biological Psychiatry 60(6): 570-577.
Thelma BK, Srivastava V, Tiwari AK (2008). Genetic underpinnings of tardive dyskinesia: passing the baton to pharmacogenetics. Pharmacogenomics 9(9): 1285- 1306.
Thierry-Mieg D, Thierry-Mieg J (2006). AceView: a comprehensive cDNA- supported gene and transcripts annotation. Genome Biology 7.
Tsuang MT, Lyons MJ, Meyer JM, Doyle T, Eisen SA, Goldberg J, et al (1998). Co- occurrence of abuse of different drugs in men - The role of drug-specific and shared vulnerabilities. Archives of General Psychiatry 55(11): 967-972.
Tyndale RF (2003). Genetics of alcohol and tobacco use in humans. Annals of Medicine 35(2): 94-121.
Usiello A, Baik JH, Rouge-Pont F, Picetti R, Dierich A, LeMeur M, et al (2000). Distinct functions of the two isoforms of dopamine D-2 receptors. Nature 408(6809): 199-203.
Violin JD, Lefkowitz RJ (2007). beta-arrestin-biased ligands at seven- transmembrane receptors. Trends in Pharmacological Sciences 28(8): 416-422.
Volkow ND, Fowler JS, Wang GJ, Hitzemann R, Logan J, Schlyer DJ, et al (1993). Decreased dopamine D2 receptor availability is associated with reduced frontal metabolism in cocaine abusers. Synapse 14(2): 169-177.
99 Wang D, Papp AC, Binkley PF, Johnson JA, Sadee W (2006). Highly variable mRNA expression and splicing of L-type voltage-dependent calcium channel alpha subunit 1C in human heart tissues. Pharmacogenetics and Genomics 16(10): 735- 745.
Wang DX, Chen HZ, Momary KM, Cavallari LH, Johnson JA, Sadee W (2008a). Regulatory polymorphism in vitamin K epoxide reductase complex subunit 1 (VKORC1) affects gene expression and warfarin dose requirement. Blood 112(4): 1013-1021.
Wang ET, Sandberg R, Luo SJ, Khrebtukova I, Zhang L, Mayr C, et al (2008b). Alternative isoform regulation in human tissue transcriptomes. Nature 456(7221): 470-476.
Wang YY, Xu R, Sasaoka T, Tonegawa S, Kung MP, Sankoorikal EB (2000). Dopamine D2 long receptor-deficient mice display alterations in striatum-dependent functions. Journal of Neuroscience 20(22): 8305-8314.
Wheeler DL, Church DM, Federhen S, Lash AE, Madden TL, Pontius JU, et al (2003). Database resources of the National Center for Biotechnology. Nucleic Acids Research 31(1): 28-33.
Wise RA (1998). Drug-activation of brain reward pathways. Drug and Alcohol Dependence 51(1-2): 13-22.
Wise RA, Bozarth MA (1987). A psychomotor stimulant theory of addiction. Psychological Review 94(4): 469-492.
Wolffe AP, Matzke MA (1999). Epigenetics: Regulation through repression. Science 286(5439): 481-486.
Workman JL, Kingston RE (1998). Alteration of nucleosome structure as a mechanism of transcriptional regulation. Annual Review of Biochemistry 67: 545- 579.
Wray GA (2007). The evolutionary significance of cis-regulatory mutations. Nature Reviews Genetics 8(3): 206-216.
Wu C, Orozco C, Boyer J, Leglise M, Goodale J, Batalov S, et al (2009). BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources. Genome Biology 10(11): 8.
100 Xu R, Hranilovic D, Fetsko LA, Bucan M, Wang Y (2002). Dopamine D2S and D2L receptors may differentially contribute to the actions of antipsychotic and psychotic agents in mice. Molecular Psychiatry 7(10): 1075-1082.
Yan H, Yuan WS, Velculescu VE, Vogelstein B, Kinzler KW (2002). Allelic variation in human gene expression. Science 297(5584): 1143-1143.
Zhang JP, Lencz T, Malhotra AK (2010). D-2 Receptor Genetic Variation and Clinical Response to Antipsychotic Drug Treatment: A Meta-Analysis. American Journal of Psychiatry 167(7): 763-772.
Zhang Y, Bertolino A, Fazio L, Blasi G, Rampino A, Romano R, et al (2007). Polymorphisms in human dopamine D2 receptor gene affect gene expression, splicing, and neuronal activity during working memory. Proceedings of the National Academy of Sciences of the United States of America 104(51): 20552-20557.
Zhang Y, Wang DX, Johnson AD, Papp AC, Sadee W (2005). Allelic expression imbalance of human mu opioid receptor (OPRM1) caused by variant A118G. Journal of Biological Chemistry 280(38): 32618-32624.
101