Catherine Johnson

Molecular genetics of nicotine dependence and abstinence: whole genome association using 520,000 SNPs

BackgroundClassical genetic studies indicate that nicotine dependence is a substantially heritable complex disorder. Genetic vulnerabilities to nicotine dependence largely overlap with genetic vulnerabilities to dependence on other addictive substances. Successful abstinence from nicotine displays substantial heritable components as well. Some of the heritability for the ability to quit smoking appears to overlap with the genetics of nicotine dependence and some does not. We now report genome wide association studies of nicotine dependent individuals who were successful in abstaining from cigarette smoking, nicotine dependent individuals who were not successful in abstaining and ethnically-matched control subjects free from substantial lifetime use of any addictive substance.ResultsThese data, and their comparison with data that we have previously obtained from comparisons of four other substance dependent vs control samples support two main ideas: 1) Single nucleotide polymorphisms (SNPs) whose allele frequencies distinguish nicotine-dependent from control individuals identify a set of genes that overlaps significantly with the set of genes that contain markers whose allelic frequencies distinguish the four other substance dependent vs control groups (p < 0.018). 2) SNPs whose allelic frequencies distinguish successful vs unsuccessful abstainers cluster in small genomic regions in ways that are highly unlikely to be due to chance (Monte Carlo p < 0.00001).ConclusionThese clustered SNPs nominate candidate genes for successful abstinence from smoking that are implicated in interesting functions: cell adhesion, enzymes, transcriptional regulators, neurotransmitters and receptors and regulation of DNA, RNA and proteins. As these observations are replicated, they will provide an increasingly-strong basis for understanding mechanisms of successful abstinence, for identifying individuals more or less likely to succeed in smoking cessation efforts and for tailoring therapies so that genotypes can help match smokers with the treatments that are most likely to benefit them.

Addiction molecular genetics: 639,401 SNP whole genome association identifies many “cell adhesion” genes†‡

Addictions are substantially heritable complex disorders. We now report whole genome association studies that identify 89 genes likely to contain variants that contribute to addiction vulnerability, using previously‐ and newly‐validated microarray based pooling assays. Each gene contains clustered single nucleotide polymorphisms (SNPs) that display significant allele frequency differences between abusers and controls in each of the two samples studied with 639,401 SNP arrays and confirmatory SNPs from each of two other abuser/control samples. These genes are implicated in interesting functions, including “cell adhesion” processes that help to establish and maintain neuronal connections of special relevance to addictions memory‐like features.

Molecular Genetics of Addiction and Related Heritable Phenotypes

Genome‐wide association (GWA) can elucidate molecular genetic bases for human individual differences in complex phenotypes that include vulnerability to addiction. Here, we review (a) evidence that supports polygenic models with (at least) modest heterogeneity for the genetic architectures of addiction and several related phenotypes; (b) technical and ethical aspects of importance for understanding GWA data, including genotyping in individual samples versus DNA pools, analytic approaches, power estimation, and ethical issues in genotyping individuals with illegal behaviors; (c) the samples and the data that shape our current understanding of the molecular genetics of individual differences in vulnerability to substance dependence and related phenotypes; (d) overlaps between GWA data sets for dependence on different substances; and (e) overlaps between GWA data for addictions versus other heritable, brain‐based phenotypes that include bipolar disorder, cognitive ability, frontal lobe brain volume, the ability to successfully quit smoking, neuroticism, and Alzheimers disease. These convergent results identify potential targets for drugs that might modify addictions and play roles in these other phenotypes. They add to evidence that individual differences in the quality and quantity of brain connections make pleiotropic contributions to individual differences in vulnerability to addictions and to related brain disorders and phenotypes. A “connectivity constellation” of brain phenotypes and disorders appears to receive substantial pathogenic contributions from individual differences in a constellation of genes whose variants provide individual differences in the specification of brain connectivities during development and in adulthood. Heritable brain differences that underlie addiction vulnerability thus lie squarely in the midst of the repertoire of heritable brain differences that underlie vulnerability to other common brain disorders and phenotypes.

Personalized smoking cessation: interactions between nicotine dose, dependence and quit-success genotype score.

Improving and targeting nicotine replacement therapy (NRT) are cost-effective strategies for reducing adverse health consequences for smokers. Treatment studies document the efficacy of precessation NRT and support important roles for level of nicotine dependence and precessation smoking reduction in successful quitting. However, prior work has not identified the optimal precessation dose or means for personalizing NRT. Genome-wide association has identified groups of genomic markers associated with successful quitting, allowing us to develop a v1.0 “quit-success” genotype score. We now report influences of v1.0 quit-success genotype score, level of dependence and precessation smoking reduction in a smoking cessation trial that examined effects of 21 versus 42 mg/24 h precessation NRT. Four hundred seventy-nine smokers were randomized to 21 or 42 mg NRT, initiated 2 wks prior to target quit dates. We monitored self-reported abstinence and end-expired air carbon monoxide (CO). Genotyping used Affymetrix arrays (Santa Clara, CA, USA). The primary outcome was 10-wk continuous smoking abstinence. NRT dose, level of nicotine dependence and genotype scores displayed significant interactive effects on successful quitting. Successful abstinence also was predicted by CO reductions during precessation NRT. These results document ways in which smoking cessation strategies can be personalized based on levels of nicotine dependence, genotype scores and CO monitoring. These assessments, taken together, can help match most smokers with optimal NRT doses and help rapidly identify some who may be better treated using other methods.

Genome Wide Association for Addiction: Replicated Results and Comparisons of Two Analytic Approaches

Background Vulnerabilities to dependence on addictive substances are substantially heritable complex disorders whose underlying genetic architecture is likely to be polygenic, with modest contributions from variants in many individual genes. “Nontemplate” genome wide association (GWA) approaches can identity groups of chromosomal regions and genes that, taken together, are much more likely to contain allelic variants that alter vulnerability to substance dependence than expected by chance. Methodology/Principal Findings We report pooled “nontemplate” genome-wide association studies of two independent samples of substance dependent vs control research volunteers (n = 1620), one European-American and the other African-American using 1 million SNP (single nucleotide polymorphism) Affymetrix genotyping arrays. We assess convergence between results from these two samples using two related methods that seek clustering of nominally-positive results and assess significance levels with Monte Carlo and permutation approaches. Both “converge then cluster” and “cluster then converge” analyses document convergence between the results obtained from these two independent datasets in ways that are virtually never found by chance. The genes identified in this fashion are also identified by individually-genotyped dbGAP data that compare allele frequencies in cocaine dependent vs control individuals. Conclusions/Significance These overlapping results identify small chromosomal regions that are also identified by genome wide data from studies of other relevant samples to extents much greater than chance. These chromosomal regions contain more genes related to “cell adhesion” processes than expected by chance. They also contain a number of genes that encode potential targets for anti-addiction pharmacotherapeutics. “Nontemplate” GWA approaches that seek chromosomal regions in which nominally-positive associations are found in multiple independent samples are likely to complement classical, “template” GWA approaches in which “genome wide” levels of significance are sought for SNP data from single case vs control comparisons.

Convergent genome wide association results for bipolar disorder and substance dependence

Twin studies document substantial heritability for substance dependence and bipolar disorder [Shih et al. ( 2004 ); Uhl et al. ( 2008a )]. Individuals with bipolar disorder display substance use disorders at rates that are much higher than those in the general population [Krishnan ( 2005 )]. We would thus predict: 1) substantial overlap between different genome wide association (GWA) studies of bipolar disorder 2) significant overlap between results from bipolar disorder and substance dependence. Recent GWA studies [Baum et al. ( 2007 ); Sklar et al. ( 2008 ); Uhl et al. ( 2008a ); Wellcome Trust Consortium (2007)] allow us to test these ideas, although 1) these datasets display difficult features that include use of differing sets of SNPs, likely polygenic genetics, likely differences in linkage disequilibrium between samples, heterogeneity both between and within loci and 2) several, though not all, reports have failed to identify any allele of any single nucleotide polymorphism (SNP) (“same SNP same allele”) that is reproducibly associated with bipolar disorder with “genome wide” significance. We now report analyses that identify clustered, P < 0.05 SNPs within genes that overlap between the bipolar samples (Monte Carlo P < 0.00001). Overlapping data from at least three of these studies identify 69 genes. 23 of these genes also contain overlapping clusters of nominally‐positive SNPs for substance dependence. Variants in these “addiction/bipolar” genes are candidates to influence the brain in ways that manifest as enhanced vulnerabilites to both substance dependence and bipolar disorder.

Genome wide association for substance dependence: convergent results from epidemiologic and research volunteer samples

BackgroundDependences on addictive substances are substantially-heritable complex disorders whose molecular genetic bases have been partially elucidated by studies that have largely focused on research volunteers, including those recruited in Baltimore. Maryland. Subjects recruited from the Baltimore site of the Epidemiological Catchment Area (ECA) study provide a potentially-useful comparison group for possible confounding features that might arise from selecting research volunteer samples of substance dependent and control individuals. We now report novel SNP (single nucleotide polymorphism) genome wide association (GWA) results for vulnerability to substance dependence in ECA participants, who were initially ascertained as members of a probability sample from Baltimore, and compare the results to those from ethnically-matched Baltimore research volunteers.ResultsWe identify substantial overlap between the home address zip codes reported by members of these two samples. We find overlapping clusters of SNPs whose allele frequencies differ with nominal significance between substance dependent vs control individuals in both samples. These overlapping clusters of nominally-positive SNPs identify 172 genes in ways that are never found by chance in Monte Carlo simulation studies. Comparison with data from human expressed sequence tags suggests that these genes are expressed in brain, especially in hippocampus and amygdala, to extents that are greater than chance.ConclusionThe convergent results from these probability sample and research volunteer sample datasets support prior genome wide association results. They fail to support the idea that large portions of the molecular genetic results for vulnerability to substance dependence derive from factors that are limited to research volunteers.

Replicated genome wide association for dependence on illegal substances: genomic regions identified by overlapping clusters of nominally positive SNPs

Declaring “replication” from results of genome wide association (GWA) studies is straightforward when major gene effects provide genome‐wide significance for association of the same allele of the same SNP in each of multiple independent samples. However, such unambiguous replication may be unlikely when phenotypes display polygenic genetic architecture, allelic heterogeneity, locus heterogeneity, and when different samples display linkage disequilibria with different fine structures. We seek chromosomal regions that are tagged by clustered SNPs that display nominally significant association in each of several independent samples. This approach provides one “nontemplate” approach to identifying overall replication of groups of GWA results in the face of difficult genetic architectures. We apply this strategy to 1 million (1M) SNP Affymetrix and Illumina GWA results for dependence on illegal substances. This approach provides high confidence in rejecting the null hypothesis that chance alone accounts for the extent to which clustered, nominally significant SNPs from samples of the same racial/ethnic background identify the same chromosomal regions. There is more modest confidence in: (a) identification of individual chromosomal regions and genes and (b) overlap between results from samples of different racial/ethnic backgrounds. The strong overlap identified among the samples with similar racial/ethnic backgrounds, together with prior work that identified overlapping results in samples of different racial/ethnic backgrounds, support contributions to individual differences in vulnerability to addictions that come from both relatively older allelic variants that are common in many current human populations and newer allelic variants that are common in fewer current human populations.

Meta-analysis and genome-wide interpretation of genetic susceptibility to drug addiction

BackgroundClassical genetic studies provide strong evidence for heritable contributions to susceptibility to developing dependence on addictive substances. Candidate gene and genome-wide association studies (GWAS) have sought genes, chromosomal regions and allelic variants likely to contribute to susceptibility to drug addiction.ResultsHere, we performed a meta-analysis of addiction candidate gene association studies and GWAS to investigate possible functional mechanisms associated with addiction susceptibility. From meta-data retrieved from 212 publications on candidate gene association studies and 5 GWAS reports, we linked a total of 843 haplotypes to addiction susceptibility. We mapped the SNPs in these haplotypes to functional and regulatory elements in the genome and estimated the magnitude of the contributions of different molecular mechanisms to their effects on addiction susceptibility. In addition to SNPs in coding regions, these data suggest that haplotypes in gene regulatory regions may also contribute to addiction susceptibility. When we compared the lists of genes identified by association studies and those identified by molecular biological studies of drug-regulated genes, we observed significantly higher participation in the same gene interaction networks than expected by chance, despite little overlap between the two gene lists.ConclusionsThese results appear to offer new insights into the genetic factors underlying drug addiction.

Addiction Genetics and Pleiotropic Effects of Common Haplotypes that Make Polygenic Contributions to Vulnerability to Substance Dependence

Abundant evidence from family, adoption, and twin studies point to large genetic contributions to individual differences in vulnerability to develop dependence on one or more addictive substances. Twin data suggest that most of this genetic vulnerability is shared by individuals who are dependent on a variety of addictive substances. Molecular genetic studies, especially genomewide and candidate gene association studies, have elucidated common haplotypes in dozens of genes that appear to make polygenic contributions to vulnerability to developing dependence. Most genes that harbor currently identified addiction-associated haplotypes are expressed in the brain. Haplotypes in many of the same genes are identified in genomewide association studies that compare allele frequencies in substance dependent vs. control individuals from European, African, and Asian racial/ethnic backgrounds. Many of these addiction-associated haplotypes display pleiotropic influences on a variety of related brain-based phenotypes that display 1) substantial heritability and 2) clinical cooccurence with substance dependence.