We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage ...disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.
Nicotine dependence is one of the world's leading causes of preventable death. To discover genetic variants that influence risk for nicotine dependence, we targeted over 300 candidate genes and ...analyzed 3713 single nucleotide polymorphisms (SNPs) in 1050 cases and 879 controls. The Fagerström test for nicotine dependence (FTND) was used to assess dependence, in which cases were required to have an FTND of 4 or more. The control criterion was strict: control subjects must have smoked at least 100 cigarettes in their lifetimes and had an FTND of 0 during the heaviest period of smoking. After correcting for multiple testing by controlling the false discovery rate, several cholinergic nicotinic receptor genes dominated the top signals. The strongest association was from an SNP representing CHRNB3, the β3 nicotinic receptor subunit gene (P = 9.4 × 10−5). Biologically, the most compelling evidence for a risk variant came from a non-synonymous SNP in the α5 nicotinic receptor subunit gene CHRNA5 (P = 6.4 × 10−4). This SNP exhibited evidence of a recessive mode of inheritance, resulting in individuals having a 2-fold increase in risk of developing nicotine dependence once exposed to cigarette smoking. Other genes among the top signals were KCNJ6 and GABRA4. This study represents one of the most powerful and extensive studies of nicotine dependence to date and has found novel risk loci that require confirmation by replication studies.
Tobacco use is a leading contributor to disability and death worldwide, and genetic factors contribute in part to the development of nicotine dependence. To identify novel genes for which natural ...variation contributes to the development of nicotine dependence, we performed a comprehensive genome wide association study using nicotine dependent smokers as cases and non-dependent smokers as controls. To allow the efficient, rapid, and cost effective screen of the genome, the study was carried out using a two-stage design. In the first stage, genotyping of over 2.4 million single nucleotide polymorphisms (SNPs) was completed in case and control pools. In the second stage, we selected SNPs for individual genotyping based on the most significant allele frequency differences between cases and controls from the pooled results. Individual genotyping was performed in 1050 cases and 879 controls using 31 960 selected SNPs. The primary analysis, a logistic regression model with covariates of age, gender, genotype and gender by genotype interaction, identified 35 SNPs with P-values less than 10−4 (minimum P-value 1.53 × 10−6). Although none of the individual findings is statistically significant after correcting for multiple tests, additional statistical analyses support the existence of true findings in this group. Our study nominates several novel genes, such as Neurexin 1 (NRXN1), in the development of nicotine dependence while also identifying a known candidate gene, the β3 nicotinic cholinergic receptor. This work anticipates the future directions of large-scale genome wide association studies with state-of-the-art methodological approaches and sharing of data with the scientific community.
Alcohol dependence (AD) is a complex disorder with environmental and genetic origins. The role of two genetic variants in ALDH2 and ADH1B in AD risk has been extensively investigated. This study ...tested for associations between nine polymorphisms in ALDH2 and 41 in the seven ADH genes, and alcohol-related flushing, alcohol use and dependence symptom scores in 4597 Australian twins. The vast majority (4296) had consumed alcohol in the previous year, with 547 meeting DSM-IIIR criteria for AD. There were study-wide significant associations (P < 2.3 × 10−4) between ADH1B-Arg48His (rs1229984) and flushing and consumption, but only nominally significant associations (P < 0.01) with dependence. Individuals carrying the rs1229984 G-allele (48Arg) reported a lower prevalence of flushing after alcohol (P = 8.2 × 10−7), consumed alcohol on more occasions (P = 2.7 × 10−6), had a higher maximum number of alcoholic drinks in a single day (P = 2.7 × 10−6) and a higher overall alcohol consumption (P = 8.9 × 10−8) in the previous year than those with the less common A-allele (48His). After controlling for rs1229984, an independent association was observed between rs1042026 (ADH1B) and alcohol intake (P = 4.7 × 10−5) and suggestive associations (P < 0.001) between alcohol consumption phenotypes and rs1693482 (ADH1C), rs1230165 (ADH5) and rs3762894 (ADH4). ALDH2 variation was not associated with flushing or alcohol consumption, but was weakly associated with AD measures. These results bridge the gap between DNA sequence variation and alcohol-related behavior, confirming that the ADH1B-Arg48His polymorphism affects both alcohol-related flushing in Europeans and alcohol intake. The absence of study-wide significant effects on AD results from the low P-value required when testing multiple single nucleotide polymorphisms and phenotypes.
Reward-related disturbances after withdrawal from nicotine are hypothesized to contribute to relapse to tobacco smoking but mechanisms underlying and linking such processes remain largely unknown.
To ...determine whether withdrawal from nicotine affects reward responsiveness (ie, the propensity to modulate behavior as a function of prior reinforcement experience) across species using translational behavioral assessments in humans and rats.
Experimental studies used analogous reward responsiveness tasks in both humans and rats to examine whether reward responsiveness varied in (1) an ad libitum smoking condition compared with a 24-hour acute nicotine abstinence condition in 31 human smokers with (n = 17) or without (n = 14) a history of depression; (2) rats 24 hours after withdrawal from chronic nicotine (n = 19) or saline (n = 20); and (3) rats following acute nicotine exposure after withdrawal from either chronic nicotine or saline administration.
Performance on a reward responsiveness task under nicotine and nonnicotine conditions.
In both human smokers and nicotine-treated rats, reward responsiveness was significantly reduced after 24-hour withdrawal from nicotine (P < .05). In humans, withdrawal-induced deficits in reward responsiveness were greater in those with a history of depression. In rats previously exposed to chronic nicotine, acute nicotine reexposure long after withdrawal potentiated reward responsiveness (P < .05).
These findings across species converge in suggesting that organisms have diminished ability to modulate behavior as a function of reward during withdrawal of nicotine. This blunting may contribute to relapse to tobacco smoking, particularly in depression-vulnerable individuals, to reinstate responsiveness to natural rewards and to experience potentiated nicotine-induced reward responsiveness. Moreover, demonstration of behavioral homology across humans and rodents provides a strong translational framework for the investigation and development of clinical treatments targeting reward responsiveness deficits during early withdrawal of nicotine.
Family studies have identified a heritable component to self-harm that is partially independent from comorbid psychiatric disorders. However, the genetic aetiology of broad sense (non-suicidal and ...suicidal) self-harm has not been characterised on the molecular level. In addition, controversy exists about the degree to which suicidal and non-suicidal self-harm share a common genetic aetiology. In the present study, we conduct genome-wide association studies (GWAS) on lifetime self-harm ideation and self-harm behaviour (i.e. any lifetime self-harm act regardless of suicidal intent) using data from the UK Biobank (n > 156,000). We also perform genome wide gene-based tests and characterize the SNP heritability and genetic correlations between these traits. Finally, we test whether polygenic risk scores (PRS) for self-harm ideation and self-harm behaviour predict suicide attempt, suicide thoughts and non-suicidal self-harm (NSSH) in an independent target sample of 8,703 Australian adults. Our GWAS results identified one genome-wide significant locus associated with each of the two phenotypes. SNP heritability (h
) estimates were ~10%, and both traits were highly genetically correlated (LDSC r
> 0.8). Gene-based tests identified seven genes associated with self-harm ideation and four with self-harm behaviour. Furthermore, in the target sample, PRS for self-harm ideation were significantly associated with suicide thoughts and NSSH, and PRS for self-harm behaviour predicted suicide thoughts and suicide attempt. Follow up regressions identified a shared genetic aetiology between NSSH and suicide thoughts, and between suicide thoughts and suicide attempt. Evidence for shared genetic aetiology between NSSH and suicide attempt was not statistically significant.
SNPs discovered by genome-wide association studies (GWASs) account for only a small fraction of the genetic variation of complex traits in human populations. Where is the remaining heritability? We ...estimated the proportion of variance for human height explained by 294,831 SNPs genotyped on 3,925 unrelated individuals using a linear model analysis, and validated the estimation method with simulations based on the observed genotype data. We show that 45% of variance can be explained by considering all SNPs simultaneously. Thus, most of the heritability is not missing but has not previously been detected because the individual effects are too small to pass stringent significance tests. We provide evidence that the remaining heritability is due to incomplete linkage disequilibrium between causal variants and genotyped SNPs, exacerbated by causal variants having lower minor allele frequency than the SNPs explored to date.
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