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.     

Genome‐wide screening for DNA variants associated with reading and language traits

Reading and language abilities are heritable traits that are likely to share some genetic influences with each other. To identify pleiotropic genetic variants affecting these traits, we first performed a genome‐wide association scan (GWAS) meta‐analysis using three richly characterized datasets comprising individuals with histories of reading or language problems, and their siblings. GWAS was performed in a total of 1862 participants using the first principal component computed from several quantitative measures of reading‐ and language‐related abilities, both before and after adjustment for performance IQ. We identified novel suggestive associations at the SNPs rs59197085 and rs5995177 (uncorrected P ≈ 10^–7 for each SNP), located respectively at the CCDC136/FLNC and RBFOX2 genes. Each of these SNPs then showed evidence for effects across multiple reading and language traits in univariate association testing against the individual traits. FLNC encodes a structural protein involved in cytoskeleton remodelling, while RBFOX2 is an important regulator of alternative splicing in neurons. The CCDC136/FLNC locus showed association with a comparable reading/language measure in an independent sample of 6434 participants from the general population, although involving distinct alleles of the associated SNP. Our datasets will form an important part of on‐going international efforts to identify genes contributing to reading and language skills.     

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.     

Genome‐wide association study of genetic factors related to confectionery intake: Potential roles of the ADIPOQ gene

Objective: The excessive consumption of confectionery might have adverse effects on human health. To screen genetic factors associated with confectionery‐intake frequency, a genome‐wide association study (GWAS) in Japan was conducted. Design and Methods: For the discovery phase (stage 1), we conducted a GWAS of 939 noncancer patients in a cancer hospital. Additive models were used to test associations between genotypes of approximately 500,000 single‐nucleotide polymorphisms (SNPs) and the confectionery‐intake score (based on intake frequency). We followed‐up association signals with P < 1 × 10^?5 and minor allele frequency >0.01 in stage 1 by genotyping the SNPs of 4,491 participants in a cross‐sectional study within a cohort (replication phase [stage 2]). Results: We identified 12 SNPs in stage 1 that were potentially related to confectionery intake. In stage 2, this association was replicated for one SNP (rs822396; P = 0.049 for stage 2 and 4.2 × 10^?5 for stage 1+2) in intron 1 of the ADIPOQ gene, which encodes the adipokine adiponectin. Conclusions: Given the biological plausibility and previous relevant findings, the association of an SNP in the ADIPOQ gene with a preference for confectionery is worthy of follow‐up and provides a good working hypothesis for experimental testing.     

A genome‐wide search for quantitative trait loci affecting the cortical surface area and thickness of Heschl's gyrus

Heschl's gyrus (HG) is a core region of the auditory cortex whose morphology is highly variable across individuals. This variability has been linked to sound perception ability in both speech and music domains. Previous studies show that variations in morphological features of HG, such as cortical surface area and thickness, are heritable. To identify genetic variants that affect HG morphology, we conducted a genome‐wide association scan (GWAS) meta‐analysis in 3054 healthy individuals using HG surface area and thickness as quantitative traits. None of the single nucleotide polymorphisms (SNPs) showed association P values that would survive correction for multiple testing over the genome. The most significant association was found between right HG area and SNP rs72932726 close to gene DCBLD2 (3q12.1; P = 2.77 × 10^?7). This SNP was also associated with other regions involved in speech processing. The SNP rs333332 within gene KALRN (3q21.2; P = 2.27 × 10^?6) and rs143000161 near gene COBLL1 (2q24.3; P = 2.40 × 10^?6) were associated with the area and thickness of left HG, respectively. Both genes are involved in the development of the nervous system. The SNP rs7062395 close to the X‐linked deafness gene POU3F4 was associated with right HG thickness (Xq21.1; P = 2.38 × 10^?6). This is the first molecular genetic analysis of variability in HG morphology.     

A genome‐wide association study in Caucasian women suggests the involvement of HLA genes in the severity of facial solar lentigines

Solar lentigines are a common feature of sun‐induced skin ageing. Little is known, however, about the genetic factors contributing to their development. In this genome‐wide association study, we aimed to identify genetic loci associated with solar lentigines on the face in 502 middle‐aged French women. Nine SNPs, gathered in two independent blocks on chromosome 6, exhibited a false discovery rate below 25% when looking for associations with the facial lentigine score. The first block, in the 6p22 region, corresponded to intergenic SNPs and also exhibited a significant association with forehead lentigines (P = 1.37 × 10^?8). The second block, within the 6p21 HLA region, was associated with decreased HLA‐C expression according to several eQTL databases. Interestingly, these SNPs were also in high linkage disequilibrium with the HLA‐C*0701 allele (r² = 0.95). We replicated an association recently found by GWAS in the IRF4 gene. Finally, a complementary study on 44 selected candidate SNPs revealed novel associations in the MITF gene. Overall, our results point to several mechanisms involved in the severity of facial lentigines, including HLA/immunity and the melanogenesis pathway.     

Genetic variants and underlying mechanisms influencing variance heterogeneity in maize

Traditional genetic studies focus on identifying genetic variants associated with the mean difference in a quantitative trait. Because genetic variants also influence phenotypic variation via heterogeneity, we conducted a variance‐heterogeneity genome‐wide association study to examine the contribution of variance heterogeneity to oil‐related quantitative traits. We identified 79 unique variance‐controlling single nucleotide polymorphisms (vSNPs) from the sequences of 77 candidate variance‐heterogeneity genes for 21 oil‐related traits using the Levene test (P < 1.0 × 10^?5). About 30% of the candidate genes encode enzymes that work in lipid metabolic pathways, most of which define clear expression variance quantitative trait loci. Of the vSNPs specifically associated with the genetic variance heterogeneity of oil concentration, 89% can be explained by additional linked mean‐effects genetic variants. Furthermore, we demonstrated that gene × gene interactions play important roles in the formation of variance heterogeneity for fatty acid compositional traits. The interaction pattern was validated for one gene pair (GRMZM2G035341 and GRMZM2G152328) using yeast two‐hybrid and bimolecular fluorescent complementation analyses. Our findings have implications for uncovering the genetic basis of hidden additive genetic effects and epistatic interaction effects, and we indicate opportunities to stabilize efficient breeding and selection of high‐oil maize (Zea mays L.).     

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.     

Genome‐wide linkage analysis for human longevity: Genetics of Healthy Aging Study

Clear evidence exists for heritability of human longevity, and much interest is focused on identifying genes associated with longer lives. To identify such longevity alleles, we performed the largest genome‐wide linkage scan thus far reported. Linkage analyses included 2118 nonagenarian Caucasian sibling pairs that have been enrolled in 15 study centers of 11 European countries as part of the Genetics of Healthy Aging (GEHA) project. In the joint linkage analyses, we observed four regions that show linkage with longevity; chromosome 14q11.2 (LOD = 3.47), chromosome 17q12‐q22 (LOD = 2.95), chromosome 19p13.3‐p13.11 (LOD = 3.76), and chromosome 19q13.11‐q13.32 (LOD = 3.57). To fine map these regions linked to longevity, we performed association analysis using GWAS data in a subgroup of 1228 unrelated nonagenarian and 1907 geographically matched controls. Using a fixed‐effect meta‐analysis approach, rs4420638 at the TOMM40/APOE/APOC1 gene locus showed significant association with longevity (P‐value = 9.6 × 10^?8). By combined modeling of linkage and association, we showed that association of longevity with APOEε4 and APOEε2 alleles explain the linkage at 19q13.11‐q13.32 with P‐value = 0.02 and P‐value = 1.0 × 10^?5, respectively. In the largest linkage scan thus far performed for human familial longevity, we confirm that the APOE locus is a longevity gene and that additional longevity loci may be identified at 14q11.2, 17q12‐q22, and 19p13.3‐p13.11. As the latter linkage results are not explained by common variants, we suggest that rare variants play an important role in human familial longevity.     

A genome‐wide association study of bipolar disorder and comorbid migraine

Both migraine and bipolar affective disorder (BPAD) are complex phenotypes with significant genetic and nongenetic components. Epidemiological and clinical studies have showed a high degree of comorbidity between migraine and BPAD, and overlapping regions of linkage have been shown in numerous genome‐wide linkage studies. To identify susceptibility factors for the BPAD/migraine phenotype, we conducted a genome‐wide association study (GWAS) in 1001 cases with bipolar disorder collected through the NIMH Genetics Initiative for Bipolar Disorder and genotyped at 1 m single‐nucleotide polymorphisms (SNPs) as part of the Genetic Association Information Network (GAIN). We compared BPAD patients without any headache (n = 699) with BPAD patients with doctor diagnosed migraine (n = 56). The strongest evidence for association was found for several SNPs in a 317‐kb region encompassing the uncharacterized geneKIAA0564 {e.g. rs9566845 [OR = 4.98 (95% CI: 2.6–9.48), P = 7.7 × 10^?8] and rs9566867 (P = 8.2 × 10^?8)}. Although the level of signficance was significantly reduced when using the Fisher's exact test (as a result of the low count of cases with migraine), rs9566845 P = 1.4 × 10^?5 and rs9566867 P = 1.5 × 10^?5, this region remained the most prominent finding. Furthermore, marker rs9566845 was genotyped and found associated with migraine in an independent Norwegian sample of adult attention deficit hyperactivity disorder (ADHD) patients with and without comorbid migraine (n = 131 and n = 324, respectively), OR = 2.42 (1.18–4.97), P = 0.013. This is the first GWAS examining patients with bipolar disorder and comorbid migraine. These data suggest that genetic variants in the KIAA0564 gene region may predispose to migraine headaches in subgroups of patients with both BPAD and ADHD.     

Single nucleotide polymorphisms in the REG‐CTNNA2 region of chromosome 2 and NEIL3 associated with impulsivity in a Native American sample

Impulsivity is a multi‐faceted construct that, while characterized by a set of correlated dimensions, is centered around a core definition that involves acting suddenly in an unplanned manner without consideration for the consequences of such behavior. Several psychiatric disorders include impulsivity as a criterion, and thus it has been suggested that it may link a number of different behavioral disorders, including substance abuse. Native Americans (NA) experience some of the highest rates of substance abuse of all the US ethnic groups. The described analyses used data from a low‐coverage whole genome sequence scan to conduct a genome‐wide association study (GWAS) of an impulsivity phenotype in an American Indian community sample (n = 658). Demographic and clinical information were obtained using a semi‐structured interview. Impulsivity was assessed using a scale derived from the Maudsley personality inventory that combines both novelty seeking and lack of planning items. The impulsivity score was tested for association with each variant adjusted for demographic variables, and corrected for ancestry and kinship, using emmax . Simulations were conducted to calculate empirical P‐values. Genome‐wide significant findings were observed for a variant 50‐kb upstream from catenin cadherin‐associated protein, alpha 2 (CTNNA2), a neuronal‐specific catenin, in the REG gene cluster. A meta‐analysis of GWAS had previously identified common variants in CTNNA2 as being associated with excitement seeking. A second locus upstream of nei endonuclease VIII‐like 3 (NEIL3) on chromosome 4 also achieved genome‐wide significance. The association between sequence variants in these regions suggests their potential roles in the genetic regulation of this phenotype in this population.     

A Genome-wide Expression Association Analysis Identifies Genes and Pathways Associated with Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with strong genetic components. To identity novel risk variants for ALS, utilizing the latest genome-wide association studies (GWAS) and eQTL study data, we conducted a genome-wide expression association analysis by summary data-based Mendelian randomization (SMR) method. Summary data were derived from a large-scale GWAS of ALS, involving 12577 cases and 23475 controls. The eQTL annotation dataset included 923,021 cis-eQTL for 14,329 genes and 4732 trans-eQTL for 2612 genes. Genome-wide single gene expression association analysis was conducted by SMR software. To identify ALS-associated biological pathways, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). SMR single gene analysis identified one significant and four suggestive genes associated with ALS, including C9ORF72 (P value = 7.08 × 10^?6), NT5C3L (P value = 1.33 × 10^?5), GGNBP2 (P value = 1.81 × 10^?5), ZNHIT3(P value = 2.94 × 10^?5), and KIAA1600(P value = 9.97 × 10^?5). GSEA identified 7 significant biological pathways, such as PEROXISOME (empirical P value = 0.006), GLYCOLYSIS_GLUCONEOGENESIS (empirical P value = 0.043), and ARACHIDONIC_ACID_ METABOLISM (empirical P value = 0.040). Our study provides novel clues for the genetic mechanism studies of ALS.     

Genetic contributions to precocity traits in racing Thoroughbreds

Adaptation to early training and racing (i.e. precocity), which is highly variable in racing Thoroughbreds, has implications for the selection and training of horses. We hypothesised that precocity in Thoroughbred racehorses is heritable. Age at first sprint training session (work day), age at first race and age at best race were used as phenotypes to quantify precocity. Using high‐density SNP array data, additive SNP heritability () was estimated to be 0.17, 0.14 and 0.17 for the three traits respectively. In genome‐wide association studies (GWAS) for age at first race and age at best race, a 1.98‐Mb region on equine chromosome 18 (ECA18) was identified. The most significant association was with the myostatin (MSTN) g.66493737C>T SNP (P = 5.46 × 10^?12 and P = 1.89 × 10^?14 respectively). In addition, two SNPs on ECA1 (g.37770220G>A and g.37770305T>C) within the first intron of the serotonin receptor gene HTR7 were significantly associated with age at first race and age at best race. Although no significant associations were identified for age at first work day, the MSTN:g.66493737C>T SNP was among the top 20 SNPs in the GWAS (P = 3.98 × 10^?5). Here we have identified variants with potential roles in early adaptation to training. Although there was an overlap in genes associated with precocity and distance aptitude (i.e. MSTN), the HTR7 variants were more strongly associated with precocity than with distance. Because HTR7 is closely related to the HTR1A gene, previously implicated in tractability in young Thoroughbreds, this suggests that behavioural traits may influence precocity.     

A large‐scale genomic association analysis identifies the candidate causal genes conferring stripe rust resistance under multiple field environments

The incorporation of resistance genes into wheat commercial varieties is the ideal strategy to combat stripe or yellow rust (YR). In a search for novel resistance genes, we performed a large‐scale genomic association analysis with high‐density 660K single nucleotide polymorphism (SNP) arrays to determine the genetic components of YR resistance in 411 spring wheat lines. Following quality control, 371 972 SNPs were screened, covering over 50% of the high‐confidence annotated gene space. Nineteen stable genomic regions harbouring 292 significant SNPs were associated with adult‐plant YR resistance across nine environments. Of these, 14 SNPs were localized in the proximity of known loci widely used in breeding. Obvious candidate SNP variants were identified in certain confidence intervals, such as the cloned gene Yr18 and the major locus on chromosome 2BL, despite a large extent of linkage disequilibrium. The number of causal SNP variants was refined using an independent validation panel and consideration of the estimated functional importance of each nucleotide polymorphism. Interestingly, four natural polymorphisms causing amino acid changes in the gene TraesCS2B01G513100 that encodes a serine/threonine protein kinase (STPK) were significantly involved in YR responses. Gene expression and mutation analysis confirmed that STPK played an important role in YR resistance. PCR markers were developed to identify the favourable TraesCS2B01G513100 haplotype for marker‐assisted breeding. These results demonstrate that high‐resolution SNP‐based GWAS enables the rapid identification of putative resistance genes and can be used to improve the efficiency of marker‐assisted selection in wheat disease resistance breeding.     

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.     

Lung eQTLs to Help Reveal the Molecular Underpinnings of Asthma

Genome-wide association studies (GWAS) have identified loci reproducibly associated with pulmonary diseases; however, the molecular mechanism underlying these associations are largely unknown. The objectives of this study were to discover genetic variants affecting gene expression in human lung tissue, to refine susceptibility loci for asthma identified in GWAS studies, and to use the genetics of gene expression and network analyses to find key molecular drivers of asthma. We performed a genome-wide search for expression quantitative trait loci (eQTL) in 1,111 human lung samples. The lung eQTL dataset was then used to inform asthma genetic studies reported in the literature. The top ranked lung eQTLs were integrated with the GWAS on asthma reported by the GABRIEL consortium to generate a Bayesian gene expression network for discovery of novel molecular pathways underpinning asthma. We detected 17,178 cis- and 593 trans- lung eQTLs, which can be used to explore the functional consequences of loci associated with lung diseases and traits. Some strong eQTLs are also asthma susceptibility loci. For example, rs3859192 on chr17q21 is robustly associated with the mRNA levels of GSDMA (P = 3.55×10⁻¹⁵¹). The genetic-gene expression network identified the SOCS3 pathway as one of the key drivers of asthma. The eQTLs and gene networks identified in this study are powerful tools for elucidating the causal mechanisms underlying pulmonary disease. This data resource offers much-needed support to pinpoint the causal genes and characterize the molecular function of gene variants associated with lung diseases.