Genome‐wide association study identifies loci associated with liability to alcohol and drug dependence that is associated with variability in reward‐related ventral striatum activity in African‐ and European‐Americans

Genetic influences on alcohol and drug dependence partially overlap, however, specific loci underlying this overlap remain unclear. We conducted a genome‐wide association study (GWAS) of a phenotype representing alcohol or illicit drug dependence (ANYDEP) among 7291 European‐Americans (EA; 2927 cases) and 3132 African‐Americans (AA: 1315 cases) participating in the family‐based Collaborative Study on the Genetics of Alcoholism. ANYDEP was heritable (h ² in EA = 0.60, AA = 0.37). The AA GWAS identified three regions with genome‐wide significant (GWS; P < 5E‐08) single nucleotide polymorphisms (SNPs) on chromosomes 3 (rs34066662, rs58801820) and 13 (rs75168521, rs78886294), and an insertion‐deletion on chromosome 5 (chr5:141988181). No polymorphisms reached GWS in the EA. One GWS region (chromosome 1: rs1890881) emerged from a trans‐ancestral meta‐analysis (EA + AA) of ANYDEP, and was attributable to alcohol dependence in both samples. Four genes (AA: CRKL, DZIP3, SBK3; EA: P2RX6) and four sets of genes were significantly enriched within biological pathways for hemostasis and signal transduction. GWS signals did not replicate in two independent samples but there was weak evidence for association between rs1890881 and alcohol intake in the UK Biobank. Among 118 AA and 481 EA individuals from the Duke Neurogenetics Study, rs75168521 and rs1890881 genotypes were associated with variability in reward‐related ventral striatum activation. This study identified novel loci for substance dependence and provides preliminary evidence that these variants are also associated with individual differences in neural reward reactivity. Gene discovery efforts in non‐European samples with distinct patterns of substance use may lead to the identification of novel ancestry‐specific genetic markers of risk.     

Pleiotropy informed adaptive association test of multiple traits using genome‐wide association study summary data

Genetic variants associated with disease outcomes can be used to develop personalized treatment. To reach this precision medicine goal, hundreds of large‐scale genome‐wide association studies (GWAS) have been conducted in the past decade to search for promising genetic variants associated with various traits. They have successfully identified tens of thousands of disease‐related variants. However, in total these identified variants explain only part of the variation for most complex traits. There remain many genetic variants with small effect sizes to be discovered, which calls for the development of (a) GWAS with more samples and more comprehensively genotyped variants, for example, the NHLBI Trans‐Omics for Precision Medicine (TOPMed) Program is planning to conduct whole genome sequencing on over 100 000 individuals; and (b) novel and more powerful statistical analysis methods. The current dominating GWAS analysis approach is the “single trait” association test, despite the fact that many GWAS are conducted in deeply phenotyped cohorts including many correlated and well‐characterized outcomes, which can help improve the power to detect novel variants if properly analyzed, as suggested by increasing evidence that pleiotropy, where a genetic variant affects multiple traits, is the norm in genome‐phenome associations. We aim to develop pleiotropy informed powerful association test methods across multiple traits for GWAS. Since it is generally very hard to access individual‐level GWAS phenotype and genotype data for those existing GWAS, due to privacy concerns and various logistical considerations, we develop rigorous statistical methods for pleiotropy informed adaptive multitrait association test methods that need only summary association statistics publicly available from most GWAS. We first develop a pleiotropy test, which has powerful performance for truly pleiotropic variants but is sensitive to the pleiotropy assumption. We then develop a pleiotropy informed adaptive test that has robust and powerful performance under various genetic models. We develop accurate and efficient numerical algorithms to compute the analytical P‐value for the proposed adaptive test without the need of resampling or permutation. We illustrate the performance of proposed methods through application to joint association test of GWAS meta‐analysis summary data for several glycemic traits. Our proposed adaptive test identified several novel loci missed by individual trait based GWAS meta‐analysis. All the proposed methods are implemented in a publicly available R package.     

A genome‐wide association study of coping behaviors suggests FBXO45 is associated with emotional expression

Individuals use coping behaviors to deal with unpleasant daily events. Such behaviors can moderate or mediate the pathway between psychosocial stress and health‐related outcomes. However, few studies have examined the associations between coping behaviors and genetic variants. We conducted a genome‐wide association study (GWAS) on coping behaviors in 14088 participants aged 35 to 69 years as part of the Japan Multi‐Institutional Collaborative Cohort Study. Five coping behaviors (emotional expression, emotional support seeking, positive reappraisal, problem solving and disengagement) were measured and analyzed. A GWAS analysis was performed using a mixed linear model adjusted for study area, age and sex. Variants with suggestive significance in the discovery phase (N = 6403) were further examined in the replication phase (N = 7685). We then combined variant‐level association evidence into gene‐level evidence using a gene‐based analysis. The results showed a significant genetic contribution to emotional expression and disengagement, with an estimation that the 19.5% and 6.6% variance in the liability‐scale was explained by common variants. In the discovery phase, 12 variants met suggestive significance (P < 1 × 10^?6) for association with the coping behaviors and perceived stress. However, none of these associations were confirmed in the replication stage. In gene‐based analysis, FBXO45, a gene with regulatory roles in synapse maturation, was significantly associated with emotional expression after multiple corrections (P < 3.1 × 10^?6). In conclusion, our results showed the existence of up to 20% genetic contribution to coping behaviors. Moreover, our gene‐based analysis using GWAS data suggests that genetic variations in FBXO45 are associated with emotional expression.     

Extreme‐phenotype genome‐wide association study (XP‐GWAS): a method for identifying trait‐associated variants by sequencing pools of individuals selected from a diversity panel

Although approaches for performing genome‐wide association studies (GWAS) are well developed, conventional GWAS requires high‐density genotyping of large numbers of individuals from a diversity panel. Here we report a method for performing GWAS that does not require genotyping of large numbers of individuals. Instead XP‐GWAS (extreme‐phenotype GWAS) relies on genotyping pools of individuals from a diversity panel that have extreme phenotypes. This analysis measures allele frequencies in the extreme pools, enabling discovery of associations between genetic variants and traits of interest. This method was evaluated in maize (Zea mays) using the well‐characterized kernel row number trait, which was selected to enable comparisons between the results of XP‐GWAS and conventional GWAS. An exome‐sequencing strategy was used to focus sequencing resources on genes and their flanking regions. A total of 0.94 million variants were identified and served as evaluation markers; comparisons among pools showed that 145 of these variants were statistically associated with the kernel row number phenotype. These trait‐associated variants were significantly enriched in regions identified by conventional GWAS. XP‐GWAS was able to resolve several linked QTL and detect trait‐associated variants within a single gene under a QTL peak. XP‐GWAS is expected to be particularly valuable for detecting genes or alleles responsible for quantitative variation in species for which extensive genotyping resources are not available, such as wild progenitors of crops, orphan crops, and other poorly characterized species such as those of ecological interest.     

Profile of common prostate cancer risk variants in an unscreened Romanian population

To find sequence variants affecting prostate cancer (PCA) susceptibility in an unscreened Romanian population we use a genome‐wide association study (GWAS). The study population included 990 unrelated pathologically confirmed PCA cases and 1034 male controls. DNA was genotyped using Illumina SNP arrays, and 24.295.558 variants were imputed using the 1000 Genomes data set. An association test was performed between the imputed markers and PCA. A systematic literature review for variants associated with PCA risk identified 115 unique variants that were tested in the Romanian sample set. Thirty of the previously reported SNPs replicated (P‐value < 0.05), with the strongest associations observed at: 8q24.21, 11q13.3, 6q25.3, 5p15.33, 22q13.2, 17q12 and 3q13.2. The replicated variants showing the most significant association in Romania are rs1016343 at 8q24.21 (P = 2.2 × 10^?4), rs7929962 at 11q13.3 (P = 2.7 × 10^?4) and rs9364554 at 6q25.2 (P = 4.7 × 10^?4). None of the variants tested in the Romanian GWAS reached genome‐wide significance (P‐value <5 × 10^?8) but 807 markers had P‐values <1 × 10^?4. Here, we report the results of the first GWAS of PCA performed in a Romanian population. Our study provides evidence that a substantial fraction of previously validated PCA variants associate with risk in this unscreened Romanian population.     

Common biological networks underlie genetic risk for alcoholism in African‐ and European‐American populations

Alcohol dependence (AD) is a heritable substance addiction with adverse physical and psychological consequences, representing a major health and economic burden on societies worldwide. Genes thus far implicated via linkage, candidate gene and genome‐wide association studies (GWAS) account for only a small fraction of its overall risk, with effects varying across ethnic groups. Here we investigate the genetic architecture of alcoholism and report on the extent to which common, genome‐wide SNPs collectively account for risk of AD in two US populations, African‐Americans (AAs) and European‐Americans (EAs). Analyzing GWAS data for two independent case–control sample sets, we compute polymarker scores that are significantly associated with alcoholism (P = 1.64 × 10^–3 and 2.08 × 10^–4 for EAs and AAs, respectively), reflecting the small individual effects of thousands of variants derived from patterns of allelic architecture that are population specific. Simulations show that disease models based on rare and uncommon causal variants (MAF < 0.05) best fit the observed distribution of polymarker signals. When scoring bins were annotated for gene location and examined for constituent biological networks, gene enrichment is observed for several cellular processes and functions in both EA and AA populations, transcending their underlying allelic differences. Our results reveal key insights into the complex etiology of AD, raising the possibility of an important role for rare and uncommon variants, and identify polygenic mechanisms that encompass a spectrum of disease liability, with some, such as chloride transporters and glycine metabolism genes, displaying subtle, modifying effects that are likely to escape detection in most GWAS designs.     

Searching new signals for production traits through gene‐based association analysis in three Italian cattle breeds

Genome‐wide association studies (GWAS) have been widely applied to disentangle the genetic basis of complex traits. In cattle breeds, classical GWAS approaches with medium‐density marker panels are far from conclusive, especially for complex traits. This is due to the intrinsic limitations of GWAS and the assumptions that are made to step from the association signals to the functional variations. Here, we applied a gene‐based strategy to prioritize genotype–phenotype associations found for milk production and quality traits with classical approaches in three Italian dairy cattle breeds with different sample sizes (Italian Brown n = 745; Italian Holstein n = 2058; Italian Simmental n = 477). Although classical regression on single markers revealed only a single genome‐wide significant genotype–phenotype association, for Italian Holstein, the gene‐based approach identified specific genes in each breed that are associated with milk physiology and mammary gland development. As no standard method has yet been established to step from variation to functional units (i.e., genes), the strategy proposed here may contribute to revealing new genes that play significant roles in complex traits, such as those investigated here, amplifying low association signals using a gene‐centric approach.     

Association between putative functional variants in the PSMB9 gene and risk of melanoma – re‐analysis of published melanoma genome‐wide association studies

To mine possibly hidden causal single‐nucleotide polymorphisms (SNPs) of melanoma, we investigated the association of SNPs in 76 M/G1 transition genes with melanoma risk using our published genome‐wide association study (GWAS) data set with 1804 melanoma cases and 1026 cancer‐free controls. We found multiple SNPs with P < 0.01 and performed validation studies for 18 putative functional SNPs in PSMB9 in two other GWAS data sets. Two SNPs (rs1351383 and rs2127675) were associated with melanoma risk in the GenoMEL data set (P = 0.013 and 0.004, respectively), but failed in validation using the Australian data set. Genotype–phenotype analysis revealed these two SNPs were significantly correlated with mRNA expression level of PSMB9. Further experiments revealed that SNP rs2071480, which is in high LD with rs1351383 and rs2127675, may have a weak effect on the promoter activity of PSMB9. Taken together, our data suggested that functional variants in PSMB9 may contribute to melanoma susceptibility.     

Replication of Association Between a Common Variant Near Melanocortin‐4 Receptor Gene and Obesity‐related Traits in Asian Sikhs

Recent genome‐wide association studies (GWAS) in Asian Indians reported strong associations of variants near melanocortin‐4 receptor (MC4R) and MLX interacting protein‐like (MLXIPL) genes with insulin resistance and several obesity‐related quantitative traits (QTs). Here, we evaluated the association of two variants (rs12970134 and rs4450508) near MC4R and a nonsynonymous (Gln241His) variant (rs3812316) in MLXIPL gene with type 2 diabetes (T2D) and obesity‐related QTs in our case–control cohort (n = 1,528; 745 T2D cases and 783 controls) from a Sikh population from North India. We have successfully replicated the association of MC4R (rs12970134) with BMI (P = 0.0005), total weight (WT) (P = 0.001), and waist circumference (WC) (P = 0.001). These associations remained significant after controlling for multiple testing by applying Bonferroni's correction. However, our data did not confirm the association of rs3812316 in the MLXIPL gene with triglyceride (TG) levels. These observations demonstrate that the genetic variation in MC4R locus can have a moderate contribution in the regional fat deposition and development of central obesity in Asian Indians.     

Further confirmation of the association between anxiety and CTNND2: replication in humans

The rat genome sequencing and mapping consortium found evidence for an association between the catenin‐δ2 gene (CTNND2) and anxious behaviour. We replicated these results in humans by carrying out a genetic association test in patients with panic disorder, social phobia, generalized anxiety disorder and/or agoraphobia (N = 1714) and controls (N = 4125). We further explored the association between CTNND2 and other psychiatric disorders based on publicly available genome‐wide association results. A gene‐based test showed that single nucleotide polymorphisms (SNPs) in CTNND2 have a significantly increased signal (P < 1e^?5) and decreased P‐values. Single nucleotide polymorphism rs1012176 showed the strongest association with any anxiety disorder (odds ratio: 0.8128, SE = 0.063, P = 0.00099), but this effect was not significant after correction for multiple testing. In available genome‐wide association results from the Psychiatric Genomics Consortium we found that SNPs in CTNND2 collectively showed an increased signal for schizophrenia (P < 1e^?5) and major depressive disorder (P < 1e^?5), but not for bipolar disorder. These signals remained significant after correction for potential confounders. The association between CTNND2 and anxiety was not strong enough to be picked up in the current generation of human genome‐wide analyses, indicating the usefulness of and need for animal genetic studies to identify candidate genes for further study in human samples .     

Resequencing Three Candidate Genes for Major Depressive Disorder in a Dutch Cohort

Major depressive disorder (MDD) is a psychiatric disorder, characterized by periods of low mood of more than two weeks, loss of interest in normally enjoyable activities and behavioral changes. MDD is a complex disorder and does not have a single genetic cause. In 2009 a genome wide association study (GWAS) was performed on the Dutch GAIN-MDD cohort. Many of the top signals of this GWAS mapped to a region spanning the gene PCLO, and the non-synonymous coding single nucleotide polymorphism (SNP) rs2522833 in the PCLO gene became genome wide significant after post-hoc analysis. We performed resequencing of PCLO, GRM7, and SLC6A4 in 50 control samples from the GAIN-MDD cohort, to detect new genomic variants. Subsequently, we genotyped these variants in the entire GAIN-MDD cohort and performed association analysis to investigate if rs2522833 is the causal variant or simply in linkage disequilibrium with a more associated variant. GRM7 and SLC6A4 are both candidate genes for MDD from literature. We aimed to gather more evidence that rs2522833 is indeed the causal variant in the GAIN-MDD cohort or to find a previously undetected common variant in either PCLO, GRM7, or SLC6A4 with a higher association in this cohort. After next generation sequencing and association analysis we excluded the possibility of an undetected common variant to be more associated. For neither PCLO nor GRM7 we found a more associated variant. For SLC6A4, we found a new SNP that showed a lower P-value (P = 0.07) than in the GAIN-MDD GWAS (P = 0.09). However, no evidence for genome-wide significance was found. Although we did not take into account rare variants, we conclude that our results provide further support for the hypothesis that the non-synonymous coding SNP rs2522833 in the PCLO gene is indeed likely to be the causal variant in the GAIN-MDD cohort.     

Haplotype‐based genotyping‐by‐sequencing in oat genome research

In a de novo genotyping‐by‐sequencing (GBS) analysis of short, 64‐base tag‐level haplotypes in 4657 accessions of cultivated oat, we discovered 164741 tag‐level (TL) genetic variants containing 241224 SNPs. From this, the marker density of an oat consensus map was increased by the addition of more than 70000 loci. The mapped TL genotypes of a 635‐line diversity panel were used to infer chromosome‐level (CL) haplotype maps. These maps revealed differences in the number and size of haplotype blocks, as well as differences in haplotype diversity between chromosomes and subsets of the diversity panel. We then explored potential benefits of SNP vs. TL vs. CL GBS variants for mapping, high‐resolution genome analysis and genomic selection in oats. A combined genome‐wide association study (GWAS) of heading date from multiple locations using both TL haplotypes and individual SNP markers identified 184 significant associations. A comparative GWAS using TL haplotypes, CL haplotype blocks and their combinations demonstrated the superiority of using TL haplotype markers. Using a principal component‐based genome‐wide scan, genomic regions containing signatures of selection were identified. These regions may contain genes that are responsible for the local adaptation of oats to Northern American conditions. Genomic selection for heading date using TL haplotypes or SNP markers gave comparable and promising prediction accuracies of up to r = 0.74. Genomic selection carried out in an independent calibration and test population for heading date gave promising prediction accuracies that ranged between r = 0.42 and 0.67. In conclusion, TL haplotype GBS‐derived markers facilitate genome analysis and genomic selection in oat.     

Mapping the four‐horned locus and testing the polled locus in three Chinese sheep breeds

Four‐horned sheep are an ideal animal model for illuminating the genetic basis of horn development. The objective of this study was to locate the genetic region responsible for the four‐horned phenotype and to verify a previously reported polled locus in three Chinese breeds. A genome‐wide association study (GWAS) was performed using 34 two‐horned and 32 four‐horned sheep from three Chinese indigenous breeds: Altay, Mongolian and Sishui Fur sheep. The top two significant single nucleotide polymorphisms (SNPs) associated with the four‐horned phenotype were both located in a region spanning positions 132.6 to 132.7 Mb on sheep chromosome 2. Similar locations for the four‐horned trait were previously identified in Jacob, Navajo‐Churro, Damara and Sishui Fur sheep, suggesting a common genetic component underlying the four‐horned phenotype. The two identified SNPs were both downstream of the metaxin 2 (MTX2) gene and the HOXD gene cluster. For the top SNP—OAR2:g.132619300G>A—the strong associations of the AA and AG genotypes with the four‐horned phenotype and the GG genotype with the two‐horned phenotype indicated the dominant inheritance of the four‐horned trait. No significant SNPs for the polled phenotype were identified in the GWAS analysis, and a PCR analysis for the detection of the 1.8‐kb insertion associated with polled sheep in other breeds failed to verify the association with polledness in the three Chinese breeds. This study supports the hypothesis that two different loci are responsible for horn existence and number. This study contributes to the understanding of the molecular regulation of horn development and enriches the knowledge of qualitative traits in domestic animals.     

Association of DVL2 and AXIN2 gene polymorphisms with cleft lip with or without cleft palate in a polish population

BACKGROUND: Nonsyndromic cleft lip with or without cleft palate (NSCL/P) is one of the most common congenital anomalies, with a complex and still not fully understood etiology. Given the important role of the Wnt/β‐catenin pathway during craniofacial development, we decided to test the hypothesis that common polymorphic variants of the genes encoding crucial components of this signaling pathway might contribute to the risk of NSCL/P in the Polish population. METHODS: A set of 19 single nucleotide polymorphisms (SNPs) in the APC, AXIN1, AXIN2, CTNNB1, DVL2, and GSK‐3β genes were analyzed using restriction fragment length polymorphism and high‐resolution melting curve methods in a group of 280 patients with NSCL/P and a properly matched control group (n = 330). RESULTS: Both single‐marker and haplotype analyses showed an association between SNPs in the DVL2 gene and the risk for NSCL/P. The strongest association was found under an overdominant model for the rs35594616 variant located in the exonic sequence of DVL2 (odds ratio [OR], 1.90; 95% confidence interval [CI], 1.37–2.62; p < 0.0001). Moreover, the gene‐gene interaction analysis revealed a significant epistatic interaction between DVL2 gene SNPs in the susceptibility to orofacial clefts. Borderline association with a decreased risk of NSCL/P was also observed for the AXIN2 rs3923087 variant (dominant model OR, 0.69; 95% CI, 0.50–0.95; p = 0.03). CONCLUSION: This study suggests that polymorphic variants of the Wnt/β‐catenin pathway genes have a role in the susceptibility to orofacial clefts. The DVL2 and AXIN2 genes might be candidate genes for this craniofacial anomaly in the Polish population. Birth Defects Research (Part A), 2012. © 2012 Wiley Periodicals, Inc.     

A Mutation in the SUV39H2 Gene in Labrador Retrievers with Hereditary Nasal Parakeratosis (HNPK) Provides Insights into the Epigenetics of Keratinocyte Differentiation

Hereditary nasal parakeratosis (HNPK), an inherited monogenic autosomal recessive skin disorder, leads to crusts and fissures on the nasal planum of Labrador Retrievers. We performed a genome-wide association study (GWAS) using 13 HNPK cases and 23 controls. We obtained a single strong association signal on chromosome 2 (p_raw = 4.4×10⁻¹⁴). The analysis of shared haplotypes among the 13 cases defined a critical interval of 1.6 Mb with 25 predicted genes. We re-sequenced the genome of one case at 38× coverage and detected 3 non-synonymous variants in the critical interval with respect to the reference genome assembly. We genotyped these variants in larger cohorts of dogs and only one was perfectly associated with the HNPK phenotype in a cohort of more than 500 dogs. This candidate causative variant is a missense variant in the SUV39H2 gene encoding a histone 3 lysine 9 (H3K9) methyltransferase, which mediates chromatin silencing. The variant c.972T>G is predicted to change an evolutionary conserved asparagine into a lysine in the catalytically active domain of the enzyme (p.N324K). We further studied the histopathological alterations in the epidermis in vivo. Our data suggest that the HNPK phenotype is not caused by hyperproliferation, but rather delayed terminal differentiation of keratinocytes. Thus, our data provide evidence that SUV39H2 is involved in the epigenetic regulation of keratinocyte differentiation ensuring proper stratification and tight sealing of the mammalian epidermis.     

Signal localization: a new approach in signal discovery

A new approach for statistical association signal identification is developed in this paper. We consider a strategy for nonprecise signal identification by extending the well‐known signal detection and signal identification methods applicable to the multiple testing problem. Collection of statistical instruments under the presented approach is much broader than under the traditional signal identification methods, allowing more efficient signal discovery. Further assessments of maximal value and average statistics in signal discovery are improved. While our method does not attempt to detect individual predictors, it instead detects sets of predictors that are jointly associated with the outcome. Therefore, an important application would be in genome wide association study (GWAS), where it can be used to detect genes which influence the phenotype but do not contain any individually significant single nucleotide polymorphism (SNP). We compare power of the signal identification method based on extremes of single p‐values with the signal localization method based on average statistics for logarithms of p‐values. A simulation analysis informs the application of signal localization using the average statistics for wide signals discovery in Gaussian white noise process. We apply average statistics and the localization method to GWAS to discover better gene influences of regulating loci in a Chinese cohort developed for risk of nasopharyngeal carcinoma (NPC).     

Associations of Variants in FTO and Near MC4R With Obesity Traits in South Asian Indians

Recent genome‐wide association studies show that loci in FTO and melanocortin 4 receptor (MC4R) associate with obesity‐related traits. Outside Western populations the associations between these variants have not always been consistent and in Indians it has been suggested that FTO relates to diabetes without an obvious intermediary obesity phenotype. We investigated the association between genetic variants in FTO (rs9939609) and near MC4R (rs17782313) with obesity‐ and type 2 diabetes (T2DM)‐related traits in a longitudinal birth cohort of 2,151 healthy individuals from the Vellore birth cohort in South India. The FTO locus displayed significant associations with several conventional obesity‐related anthropometric traits. The per allele increase is about 1% for BMI, waist circumference (WC), hip circumference (HC), and waist—hip ratio. Consistent associations were observed for adipose tissue‐specific measurements such as skinfold thickness reinforcing the association with obesity‐related traits. Obesity associations for the MC4R locus were weak or nonsignificant but a signal for height (P < 0.001) was observed. The effect on obesity‐related traits for FTO was seen in adulthood, but not at younger ages. The loci also showed nominal associations with increased blood glucose but these associations were lost on BMI adjustment. The effect of FTO on obesity‐related traits was driven by an urban environmental influence. We conclude that rs9939609 variant in the FTO locus is associated with measures of adiposity and metabolic consequences in South Indians with an enhanced effect associated with urban living. The detection of these associations in Indians is challenging because conventional anthropometric obesity measures work poorly in the Indian “thin‐fat” phenotype.     

Genetic effects on information processing speed are moderated by age – converging results from three samples

Information processing is a cognitive trait forming the basis of complex abilities like executive function. The Trail Making Test (TMT) is a well‐established test of information processing with moderate to high heritability. Age of the individual also plays an important role. A number of genetic association studies with the TMT have been performed, which, however, did not consider age as a moderating factor. We report the results of genome‐wide association studies (GWASs) on age‐independent and age‐dependent TMT performance in two population‐representative community samples (Munich Antidepressant Response Signature, MARS: N₁ = 540; Ludwig Maximilians University, LMU: N₂ = 350). Age‐dependent genome‐wide findings were then evaluated in a third sample of healthy elderly subjects (Sydney Memory and Ageing Study, Sydney MAS: N₃ = 448). While a meta‐analysis on the GWAS findings did not reveal age‐independent TMT associations withstanding correction for multiple testing, we found a genome‐wide significant age‐moderated effect between variants in the DSG1 gene region and TMT‐A performance predominantly reflecting visual processing speed (rs2199301, P_{meta‐analysis} = 1.3 × 10^?7). The direction of the interaction suggests for the minor allele a beneficial effect in younger adults turning into a detrimental effect in older adults. The detrimental effect of the missense single nucleotide polymorphism rs1426310 within the same DSG1 gene region could be replicated in Sydney MAS participants aged 70–79, but not in those aged 80 years and older, presumably a result of survivor bias. Our findings demonstrate opposing effects of DSG1 variants on information processing speed depending on age, which might be related to the complex processes that DSG1 is involved with, including cell adhesion and apoptosis.