Real-Time PCR Method for Detection of Salmonella spp. in Environmental Samples.

The methods currently used for detecting Salmonella in environmental samples require 2 days to produce results and have limited sensitivity. Here, we describe the development and validation of a real-time PCR Salmonella screening method that produces results in 18 to 24 h. Primers and probes specific to the gene invA, group D, and Salmonella enterica serovar Enteritidis organisms were designed and evaluated for inclusivity and exclusivity using a panel of 329 Salmonella isolates representing 126 serovars and 22 non-Salmonella organisms. The invA- and group D-specific sets identified all the isolates accurately. The PCR method had 100% inclusivity and detected 1 to 2 copies of Salmonella DNA per reaction. Primers specific for Salmonella-differentiating fragment 1 (Sdf-1) in conjunction with the group D set had 100% inclusivity for 32 S Enteritidis isolates and 100% exclusivity for the 297 non-Enteritidis Salmonella isolates. Single-laboratory validation performed on 1,741 environmental samples demonstrated that the PCR method detected 55% more positives than the Vitek immunodiagnostic assay system (VIDAS) method. The PCR results correlated well with the culture results, and the method did not report any false-negative results. The receiver operating characteristic (ROC) analysis documented excellent agreement between the results from the culture and PCR methods (area under the curve, 0.90; 95% confidence interval of 0.76 to 1.0) confirming the validity of the PCR method.IMPORTANCE This validated PCR method detects 55% more positives for Salmonella in half the time required for the reference method, VIDAS. The validated PCR method will help to strengthen public health efforts through rapid screening of Salmonella spp. in environmental samples.

Functional consequences of 17q21.31/WNT3-WNT9B amplification in hPSCs with respect to neural differentiation.

Human pluripotent stem cell (hPSC) lines exhibit repeated patterns of genetic variation, which can alter in vitro properties as well as suitability for clinical use. We examined associations between copy-number variations (CNVs) on chromosome 17 and hPSC mesodiencephalic dopaminergic (mDA) differentiation. Among 24 hPSC lines, two karyotypically normal lines, BG03 and CT3, and BG01V2, with trisomy 17, exhibited amplification of the WNT3/WNT9B region and rapid mDA differentiation. In hPSC lines with amplified WNT3/WNT9B, basic fibroblast growth factor (bFGF) signaling through mitogen-activated protein kinase (MAPK)/ERK amplifies canonical WNT signaling by phosphorylating LRP6, resulting in enhanced undifferentiated proliferation. When bFGF is absent, noncanonical WNT signaling becomes dominant due to upregulation of SIAH2, enhancing JNK signaling and promoting loss of pluripotency. When bFGF is present during mDA differentiation, stabilization of canonical WNT signaling causes upregulation of LMX1A and mDA induction. Therefore, CNVs in 17q21.31, a "hot spot" for genetic variation, have multiple and complex effects on hPSC cellular phenotype.

Genomic regions identified by overlapping clusters of nominally-positive SNPs from genome-wide studies of alcohol and illegal substance dependence.

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 is 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 M SNP GWA results for dependence on: a) alcohol (including many individuals with dependence on other addictive substances) and b) at least one illegal substance (including many individuals dependent on alcohol). 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 sets of chromosomal regions. It identifies several genes that are also reported in other independent alcohol-dependence GWA datasets. There is more modest confidence in: a) identification of individual chromosomal regions and genes that are not also identified by data from other independent samples, b) the more modest overlap between results from samples of different racial/ethnic backgrounds and c) the extent to which any gene not identified herein is excluded, since the power of each of these individual samples is modest. Nevertheless, the strong overlap identified among the samples with similar racial/ethnic backgrounds supports contributions to individual differences in vulnerability to addictions that come from newer allelic variants that are common in subsets of current humans.

"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.

Genome-wide association for smoking cessation success in a trial of precessation nicotine replacement.

Abilities to successfully quit smoking display substantial evidence for heritability in classic and molecular genetic studies. Genome-wide association (GWA) studies have demonstrated single-nucleotide polymorphisms (SNPs) and haplotypes that distinguish successful quitters from individuals who were unable to quit smoking in clinical trial participants and in community samples. Many of the subjects in these clinical trial samples were aided by nicotine replacement therapy (NRT). We now report novel GWA results from participants in a clinical trial that sought dose/response relationships for "precessation" NRT. In this trial, 369 European-American smokers were randomized to 21 or 42 mg NRT, initiated 2 wks before target quit dates. Ten-week continuous smoking abstinence was assessed on the basis of self-reports and carbon monoxide levels. SNP genotyping used Affymetrix 6.0 arrays. GWA results for smoking cessation success provided no P value that reached "genome-wide" significance. Compared with chance, these results do identify (a) more clustering of nominally positive results within small genomic regions, (b) more overlap between these genomic regions and those identified in six prior successful smoking cessation GWA studies and (c) sets of genes that fall into gene ontology categories that appear to be biologically relevant. The 1,000 SNPs with the strongest associations form a plausible Bayesian network; no such network is formed by randomly selected sets of SNPs. The data provide independent support, based on individual genotyping, for many loci previously nominated on the basis of data from genotyping in pooled DNA samples. These results provide further support for the idea that aid for smoking cessation may be personalized on the basis of genetic predictors of outcome.

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 smoking cessation success: participants in the Patch in Practice trial of nicotine replacement.

AIMS: To confirm and extend to primary care settings prior genome-wide association results that distinguish smokers who successfully quit from individuals who were not able to quit smoking in clinical trials. MATERIALS & METHODS: Affymetrix 6.0 Arrays were used to study DNA from successful quitters and matched individuals who did not quit from the Patch in Practice study of 925 smokers in 26 UK general practices who were provided with 15 mg/16 h nicotine-replacement therapy and varying degrees of behavioral support. RESULTS: Only a few SNPs provided results near 'genome-wide' levels of significance. Nominally significant (p < 0.01) SNP results identify the same chromosomal regions identified by prior genome-wide association studies to a much greater extent than expected by chance. CONCLUSION: Ability to change smoking behavior in a general practice setting appears to share substantial underlying genetics with the ability to change this behavior in clinical trials, though the modest sample sizes available for these studies provides some caution to these conclusions.

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.

Genome-wide association for smoking cessation success: participants in a trial with adjunctive denicotinized cigarettes.

The ability to quit smoking successfully displays substantial heritability in classical and molecular genetic studies. Twin studies suggest that some of the genetics for the ability to quit overlap with genetic components of nicotine dependence, but many do not. Genome-wide association (GWA) studies have demonstrated haplotypes that distinguish successful quitters from individuals who were not able to quit smoking in: i) clinical trials that employed nicotine replacement; ii) clinical trials that employed bupropion; and iii) community quitter samples. We now report novel GWA results from participants in a clinical trial that document the efficacy of adjunctive use of denicotinized cigarettes. These results buttress data from our prior GWA studies of smoking cessation. They suggest that ability to change smoking behavior using denicotinized cigarettes shares substantial underlying genetics with the ability to change this behavior in community settings or in response to treatments with nicotine replacement or bupropion.

Smoking and smoking cessation in disadvantaged women: assessing genetic contributions.

Abundant evidence from family, adoption and twin studies points to large genetic contributions to individual differences in vulnerability to develop dependence on one or more addictive substances, including tobacco. Twin data suggests that much of this genetic vulnerability is shared by individuals who are dependent on a variety of addictive substances. Interestingly, some twin data also supports substantial differences in the apparent heritability of nicotine dependence in women as environmental conditions become more permissive for their smoking. In addition, twin studies also support the idea that ability to quit smoking displays substantial heritability, and that this heritable influence overlaps partially with genetic influences on nicotine dependence. Candidate gene molecular genetic studies and genome wide association studies of substance dependence and ability to quit smoking each document apparent polygenic influences that identify lists of genes that display partial overlap, as expected from classical genetic studies. More of these genes are expressed in the brain than would be anticipated by chance. These lists of genes overlap significantly with those identified in molecular genetic studies of individual differences in cognitive abilities, frontal lobe brain volumes as well as personality and psychiatric phenotypes. Though most available genome wide association data do not separate results by gender, it may be notable that few of these genes lie on sex chromosomes. These data provide a substrate to improve understanding of nicotine dependence, the ability to quit smoking, the potential for less permissive environments to restrict the expression of genetic influences on smoking and the possibility that brain features that underlie phenotypes such as individual differences in cognitive abilities might interact with environmental features that are especially prominent for disadvantaged women to provide special circumstances that should be considered in prevention and treatment efforts to reduce smoking.

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.

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.

Genome-wide association for nicotine dependence and smoking cessation success in NIH research volunteers.

Phenotypes related to both nicotine dependence and ability to successfully quit smoking display substantial heritabilities in classical and molecular genetic studies. Twin studies suggest that some genetic components for dependence overlap with genetic components of ability to quit, but that many components do not overlap. Initial genome-wide association (GWA) studies have demonstrated haplotypes that distinguish nicotine-dependent from nondependent smokers. These haplotypes overlap partially with those that distinguish individuals who successfully quit smoking from those who were not able to quit smoking in clinical trials for smoking cessation. We now report novel genome-wide association results from National Institutes of Health research volunteers who reported smoking histories, symptoms of nicotine dependence, and ability to successfully quit smoking outside the context of a clinical trial. These results buttress data from several prior GWA studies. The data from these volunteers support the idea that previously reported studies of genes associated with smoking cessation success in clinical trial participants may also apply to smokers who are more or less able to initiate and sustain abstinence outside of clinical trial settings.

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

BACKGROUND: Dependences 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. RESULTS: We 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. CONCLUSION: The 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.

Molecular genetics of addiction and related heritable phenotypes: genome-wide association approaches identify "connectivity constellation" and drug target genes with pleiotropic effects.

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 Alzheimer's 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.

Molecular genetics of successful smoking cessation: convergent genome-wide association study results.

CONTEXT: Smoking remains a major public health problem. Twin studies indicate that the ability to quit smoking is substantially heritable, with genetics that overlap modestly with the genetics of vulnerability to dependence on addictive substances. OBJECTIVES: To identify replicated genes that facilitate smokers' abilities to achieve and sustain abstinence from smoking (herein after referred to as quit-success genes) found in more than 2 genome-wide association (GWA) studies of successful vs unsuccessful abstainers, and, secondarily, to nominate genes for selective involvement in smoking cessation success with bupropion hydrochloride vs nicotine replacement therapy (NRT). DESIGN: The GWA results in subjects from 3 centers, with secondary analyses of NRT vs bupropion responders. SETTING: Outpatient smoking cessation trial participants from 3 centers. PARTICIPANTS: European American smokers who successfully vs unsuccessfully abstain from smoking with biochemical confirmation in a smoking cessation trial using NRT, bupropion, or placebo (N = 550). MAIN OUTCOME MEASURES: Quit-success genes, reproducibly identified by clustered nominally positive single-nucleotide polymorphisms (SNPs) in more than 2 independent samples with significant P values based on Monte Carlo simulation trials. The NRT-selective genes were nominated by clustered SNPs that display much larger t values for NRT vs placebo comparisons. The bupropion-selective genes were nominated by bupropion-selective results. RESULTS: Variants in quit-success genes are likely to alter cell adhesion, enzymatic, transcriptional, structural, and DNA, RNA, and/or protein-handling functions. Quit-success genes are identified by clustered nominally positive SNPs from more than 2 samples and are unlikely to represent chance observations (Monte Carlo P< .0003). These genes display modest overlap with genes identified in GWA studies of dependence on addictive substances and memory. CONCLUSIONS: These results support polygenic genetics for success in abstaining from smoking, overlap with genetics of substance dependence and memory, and nominate gene variants for selective influences on therapeutic responses to bupropion vs NRT. Molecular genetics should help match the types and/or intensity of antismoking treatments with the smokers most likely to benefit from them.

Hyperpolarized growth of Saccharomyces cerevisiae cak1P212S and cla4 mutants weakens cell walls and renders cells dependent on chitin synthase 3.

In a screen for cell wall defects in Saccharomyces cerevisiae, we isolated a strain carrying a mutation in the Cdc28-activating kinase CAK1. The cak1P212S mutant cells exhibit multiple, elongated and branched buds, beta(1,3)glucan-poor regions of the cell periphery and lysed upon osmotic shock after treatment with the chitin synthase III inhibitor Nikkomycin Z. Ultrastructural examination of cak1P212S mutants revealed a thin, uneven cell wall and marked abnormalities in septum formation. In all of the above aspects, the cak1P212S mutants are similar to previously described cla4 mutants, suggesting that the cell wall defects are common to mutants with hyperpolarized growth. In cak1P212S mutants, chitin accumulates all over the surface of the cells and glucan synthase activity is located preferentially to the tips of elongated buds. We conclude that the cell wall weakness in cak1P212S mutants is caused by hyperpolarized secretion of glucan synthase and lack of reinforcement of the lateral cell walls. Showing that the defect depends at least in part on Cdc28, the cak1P212S hyperpolarized growth phenotype can be suppressed by a Cak1-independent Cdc28-allele. The results underline the importance of a minor cell wall component, the chitin of lateral walls, for the integrity of the cell in a stress situation.

Genome-wide association for methamphetamine dependence: convergent results from 2 samples.

CONTEXT: We can improve understanding of human methamphetamine dependence, and possibly our abilities to prevent and treat this devastating disorder, by identifying genes whose allelic variants predispose to methamphetamine dependence. OBJECTIVE: To find "methamphetamine dependence" genes identified by each of 2 genome-wide association (GWA) studies of independent samples of methamphetamine-dependent individuals and matched controls. DESIGN: Replicated GWA results in each of 2 case-control studies. SETTING: Japan and Taiwan. PARTICIPANTS: Individuals with methamphetamine dependence and matched control subjects free from psychiatric, substance abuse, or substance dependence diagnoses (N = 580). MAIN OUTCOME MEASURES: "Methamphetamine dependence" genes that were reproducibly identified by clusters of nominally positive single-nucleotide polymorphisms (SNPs) in both samples in ways that were unlikely to represent chance observations, based on Monte Carlo simulations that corrected for multiple comparisons, and subsets of "methamphetamine dependence" genes that were also identified by GWA studies of dependence on other addictive substances, success in quitting smoking, and memory. RESULTS: Genes identified by clustered nominally positive SNPs from both samples were unlikely to represent chance observations (Monte Carlo P < .00001). Variants in these "methamphetamine dependence" genes are likely to alter cell adhesion, enzymatic functions, transcription, cell structure, and DNA, RNA, and/or protein handling or modification. Cell adhesion genes CSMD1 and CDH13 displayed the largest numbers of clustered nominally positive SNPs. "Methamphetamine dependence" genes overlapped, to extents much greater than chance, with genes identified in GWA studies of dependence on other addictive substances, success in quitting smoking, and memory (Monte Carlo P range < .04 to < .00001). CONCLUSION: These data support polygenic contributions to methamphetamine dependence from genes that include those whose variants contribute to dependence on several addictive substances, success in quitting smoking, and mnemonic processes.

"Higher order" addiction molecular genetics: convergent data from genome-wide association in humans and mice.

Family, adoption and twin data each support substantial heritability for addictions. Most of this heritable influence is not substance-specific. The overlapping genetic vulnerability for developing dependence on a variety of addictive substances suggests large roles for "higher order" pharamacogenomics in addiction molecular genetics. We and others have now completed genome-wide association (GWA) studies of DNAs from individuals with dependence on a variety of addictive substances versus appropriate controls. Recently reported replicated GWA observations identify a number of genes based on comparisons between controls and European-American and African-American polysubstance abusers. Here we review the convergence between these results and data that compares control samples and (a) alcohol-dependent European-Americans, (b) methamphetamine-dependent Asians and (c) nicotine dependent samples from European backgrounds. We also compare these human data to quantitative trait locus (QTL) results from studies of addiction-related phenotypes in mice that focus on alcohol, methamphetamine and barbiturates. These comparisons support a genetic architecture built from largely polygenic contributions of common allelic variants to dependence on a variety of legal and illegal substances. Many of the gene variants identified in this way are likely to alter specification and maintenance of neuronal connections.