Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network

Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype–phenotype associations, 26 represented phenotypes closely related to previously known genotype–phenotype associations, and 33 represented potentially novel genotype–phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits.     

A Multi-Trait,Meta-analysis for Detecting Pleiotropic Polymorphisms for Stature,Fatness and Reproduction in Beef Cattle

Polymorphisms that affect complex traits or quantitative trait loci (QTL) often affect multiple traits. We describe two novel methods (1) for finding single nucleotide polymorphisms (SNPs) significantly associated with one or more traits using a multi-trait, meta-analysis, and (2) for distinguishing between a single pleiotropic QTL and multiple linked QTL. The meta-analysis uses the effect of each SNP on each of n traits, estimated in single trait genome wide association studies (GWAS). These effects are expressed as a vector of signed t-values (t) and the error covariance matrix of these t values is approximated by the correlation matrix of t-values among the traits calculated across the SNP (V). Consequently, t''V⁻¹t is approximately distributed as a chi-squared with n degrees of freedom. An attractive feature of the meta-analysis is that it uses estimated effects of SNPs from single trait GWAS, so it can be applied to published data where individual records are not available. We demonstrate that the multi-trait method can be used to increase the power (numbers of SNPs validated in an independent population) of GWAS in a beef cattle data set including 10,191 animals genotyped for 729,068 SNPs with 32 traits recorded, including growth and reproduction traits. We can distinguish between a single pleiotropic QTL and multiple linked QTL because multiple SNPs tagging the same QTL show the same pattern of effects across traits. We confirm this finding by demonstrating that when one SNP is included in the statistical model the other SNPs have a non-significant effect. In the beef cattle data set, cluster analysis yielded four groups of QTL with similar patterns of effects across traits within a group. A linear index was used to validate SNPs having effects on multiple traits and to identify additional SNPs belonging to these four groups.     

Genetic determinants of mortality. Can findings from genome-wide association studies explain variation in human mortality?

Twin studies have estimated the heritability of longevity to be approximately 20–30 %. Genome-wide association studies (GWAS) have revealed a large number of determinants of morbidity, but so far, no new polymorphisms have been discovered to be associated with longevity per se in GWAS. We aim to determine whether the genetic architecture of mortality can be explained by single nucleotide polymorphisms (SNPs) associated with common traits and diseases related to mortality. By extensive quality control of published GWAS we created a genetic score from 707 common SNPs associated with 125 diseases or risk factors related with overall mortality. We prospectively studied the association of the genetic score with: (1) time-to-death; (2) incidence of the first of nine major diseases (coronary heart disease, stroke, heart failure, diabetes, dementia, lung, breast, colon and prostate cancers) in two population-based cohorts of Dutch and Swedish individuals (N = 15,039; age range 47–99 years). During a median follow-up of 6.3 years (max 22.2 years), we observed 4,318 deaths and 2,132 incident disease events. The genetic score was significantly associated with time-to-death [hazard ratio (HR) per added risk allele = 1.003, P value = 0.006; HR 4th vs. 1st quartile = 1.103]. The association between the genetic score and incidence of major diseases was stronger (HR per added risk allele = 1.004, P value = 0.002; HR 4th vs. 1st quartile = 1.160). Associations were stronger for individuals dying at older ages. Our findings are compatible with the view of mortality as a complex and highly polygenetic trait, not easily explainable by common genetic variants related to diseases and physiological traits.     

A meta-analysis and genome-wide association study of platelet count and mean platelet volume in african americans

Several genetic variants associated with platelet count and mean platelet volume (MPV) were recently reported in people of European ancestry. In this meta-analysis of 7 genome-wide association studies (GWAS) enrolling African Americans, our aim was to identify novel genetic variants associated with platelet count and MPV. For all cohorts, GWAS analysis was performed using additive models after adjusting for age, sex, and population stratification. For both platelet phenotypes, meta-analyses were conducted using inverse-variance weighted fixed-effect models. Platelet aggregation assays in whole blood were performed in the participants of the GeneSTAR cohort. Genetic variants in ten independent regions were associated with platelet count (N?=?16,388) with p<5×10(-8) of which 5 have not been associated with platelet count in previous GWAS. The novel genetic variants associated with platelet count were in the following regions (the most significant SNP, closest gene, and p-value): 6p22 (rs12526480, LRRC16A, p?=?9.1×10(-9)), 7q11 (rs13236689, CD36, p?=?2.8×10(-9)), 10q21 (rs7896518, JMJD1C, p?=?2.3×10(-12)), 11q13 (rs477895, BAD, p?=?4.9×10(-8)), and 20q13 (rs151361, SLMO2, p?=?9.4×10(-9)). Three of these loci (10q21, 11q13, and 20q13) were replicated in European Americans (N?=?14,909) and one (11q13) in Hispanic Americans (N?=?3,462). For MPV (N?=?4,531), genetic variants in 3 regions were significant at p<5×10(-8), two of which were also associated with platelet count. Previously reported regions that were also significant in this study were 6p21, 6q23, 7q22, 12q24, and 19p13 for platelet count and 7q22, 17q11, and 19p13 for MPV. The most significant SNP in 1 region was also associated with ADP-induced maximal platelet aggregation in whole blood (12q24). Thus through a meta-analysis of GWAS enrolling African Americans, we have identified 5 novel regions associated with platelet count of which 3 were replicated in other ethnic groups. In addition, we also found one region associated with platelet aggregation that may play a potential role in atherothrombosis.     

A genome-wide association study of prostate cancer in West African men

Age-adjusted mortality rates for prostate cancer are higher for African-American men compared with those of European ancestry. Recent data suggest that West African men also have elevated risk for prostate cancer relative to European men. Genetic susceptibility to prostate cancer could account for part of this difference. We conducted a genome-wide association study (GWAS) of prostate cancer in West African men in the Ghana Prostate Study. Association testing was performed using multivariable logistic regression adjusted for age and genetic ancestry for 474 prostate cancer cases and 458 population-based controls on the Illumina HumanOmni-5 Quad BeadChip. The most promising association was at 10p14 within an intron of a long non-coding RNA (lncRNA RP11-543F8.2) 360 kb centromeric of GATA3 (p = 1.29E?7). In sub-analyses, SNPs at 5q31.3 were associated with high Gleason score (≥7) cancers, the strongest of which was a missense SNP in PCDHA1 (rs34575154, p = 3.66E?8), and SNPs at Xq28 (rs985081, p = 8.66E?9) and 6q21 (rs2185710, p = 5.95E?8) were associated with low Gleason score (<7) cancers. We sought to validate our findings in silico in the African Ancestry Prostate Cancer GWAS Consortium, but only one SNP, at 10p14, replicated at p < 0.05. Of the 90 prostate cancer loci reported from studies of men of European, Asian or African-American ancestry, we were able to test 81 in the Ghana Prostate Study, and 10 of these replicated at p < 0.05. Further genetic studies of prostate cancer in West African men are needed to confirm our promising susceptibility loci.     

Genome-wide association study identified novel genetic variant on SLC45A3 gene associated with serum levels prostate-specific antigen (PSA) in a Chinese population

Prostate-specific antigen (PSA) is a commonly used cancer biomarker for prostate cancer, and is often included as part of routine physical examinations in China. Serum levels of PSA may be influenced by genetic factors as well as other factors. A genome-wide association study (GWAS) conducted in a European population successfully identified six genetic loci that were significantly associated with PSA level. In this study, we aimed to identify common genetic variants that are associated with serum level of PSA in a Chinese population. We also evaluated the effects of those variants by creating personalized PSA cutoff values. A two-stage GWAS of PSA level was performed among men age 20–69 years and self-reported cancer-free participants that underwent routine physical examinations at several hospitals in Guangxi Province, China. Single nucleotide polymorphisms (SNPs) significantly associated with PSA levels in the first stage of sample (N = 1,999) were confirmed in the second stage of sample (N = 1,496). Multivariate linear regression was used to assess the independent contribution of confirmed SNPs and known covariates, such as age, to the level of PSA. SNPs in three regions were significantly associated with levels of PSA in this two-stage GWAS, and had combined P values between 4.62 × 10^?17 and 6.45 × 10^?37. The three regions are located on 1q32.1 at SLC45A3, 10q11.23 at MSMB, and 19q13.33 at KLK3. The region 1q32.1 at SLC45A3 was identified as a novel locus. Genetic variants contributed significantly more to the variance of PSA level than known covariates such as age. Personalized cutoff values of serum PSA, calculated based on the inheritance of these associated SNPs, differ considerably among individuals. Identification of these genetic markers provides new insight into the molecular mechanisms of PSA. Taking individual variation into account, these genetic variants may improve the performance of PSA to predict prostate cancer.     

Genome-wide pathway analysis of genome-wide association studies on systemic lupus erythematosus and rheumatoid arthritis

The aim of this study was to explore candidate single nucleotide polymorphisms (SNPs) and candidate mechanisms of systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). Two SLE genome-wide association studies (GWASs) datasets were included in this study. Meta-analysis was conducted using 737,984 SNPs in 1,527 SLE cases and 3,421 controls of European ancestry, and 4,429 SNPs that met a threshold of p?<?0.01 in a Korean RA GWAS dataset was used. ICSNPathway (identify candidate causal SNPs and pathways) analysis was applied to the meta-analysis results of the SLE GWAS datasets, and a RA GWAS dataset. The most significant result of SLE GWAS meta-analysis concerned rs2051549 in the human leukocyte antigen (HLA) region (p?=?3.36E?22). In the non-HLA region, meta-analysis identified 6 SNPs associated with SLE with genome-wide significance (STAT4, TNPO3, BLK, FAM167A, and IRF5). ICSNPathway identified five candidate causal SNPs and 13 candidate causal pathways. This pathway-based analysis provides three hypotheses of the biological mechanism involved. First, rs8084 and rs7192?→?HLA-DRA?→?bystander B cell activation. Second, rs1800629?→?TNF?→?cytokine network. Third, rs1150752 and rs185819?→?TNXB?→?collagen metabolic process. ICSNPathway analysis identified three candidate causal non-HLA SNPs and four candidate causal pathways involving the PADI4, MTR, PADI2, and TPH2 genes of RA. We identified five candidate SNPs and thirteen pathways, involving bystander B cell activation, cytokine network, and collagen metabolic processing, which may contribute to SLE susceptibility, and we revealed candidate causal non-HLA SNPs, genes, and pathways of RA.     

Exploration into natural variation for genes associated with fruit shape and size among Capsicum chinense collections

Phenotype diversity within cultivated Capsicum chinense is particularly evident for fruit shape and size. We used this diversity in C. chinense to further unravel the genetic mechanisms underlying fruit shape variation in pepper and related Solanaceous species. We identified candidate genes for C. chinense fruit shape, explored their contribution to population structure, and characterized their potential function in pepper fruit shape. Using genotyping by sequencing, we identified 43,081 single nucleotide polymorphisms (SNPs) from diverse collections of C. chinense. Principal component, neighbor-joining tree, and population structure analyses resolved 3 phylogenetically robust clusters associated with fruit shapes. Genome-wide association study (GWAS) was used to identify associated genomic regions with various fruit shape traits obtained from image analysis with Tomato Analyzer software. In our GWAS, we selected 12 SNPs associated with locule number trait and 8 SNP markers associated with other fruit shape traits such as perimeter, area, obovoid, ellipsoid and morphometrics (5y, 6y and 7y). The SNPs in CLAVATA1, WD-40, Auxin receptor, AAA type ATPase family protein, and RNA polymerase III genes were the major markers identified for fruit locule number from our GWAS results. Furthermore, we found SNPs in tetratricopeptide-repeat thioredoxin-like 3, enhancer of ABA co-receptor 1, subunit of exocyst complex 8 and pleiotropic drug resistance proteins associated with various fruit shape traits. CLAVATA1, WD-40 and Auxin receptor genes are known genes that affect tomato fruit shape. In this study, we used Arabidopsis thaliana T-DNA insertion knockout mutants and expression profiles for functional characterization of newly identified genes and to understand their role in fruit shape.     

Multivariate eQTL mapping uncovers functional variation on the X-chromosome associated with complex disease traits

Very few studies have investigated the associations between genetic polymorphisms and gene expression on the X-chromosome. This is a major bottleneck when conducting functional follow-up studies of trait-associated variants, as those identified in genome-wide association studies (GWAS). We used a multivariate approach to test the association between individual single nucleotide polymorphisms (SNPs) and exon expression levels measured in 356 Epstein–Barr virus-transformed lymphoblastoid cell lines (LCLs) from the Geuvadis RNA sequencing project to identify SNPs associated with variation in gene expression on the X-chromosome, which we refer to as eSNPs. At an FDR of 5 %, we discovered 548 independent [linkage disequilibrium (LD) r ² < 0.1] eSNPs on the X-chromosome. Of these, 35 were in LD (r ² > 0.8) with previously published disease- or trait-associated variants identified through GWAS. One of the strongest eSNPs identified was rs35975601, which was associated with F8A1 expression (p value = 3 × 10^?20) and was in LD with a type 1 diabetes risk variant. Additionally, we identified a number of genes for which eSNPs were in LD with multiple diseases or traits, including DNASE1L1 which was mapped to bilirubin levels, type 1 diabetes and schizophrenia. Our results also indicate that multivariate exon-level analysis provides a more powerful approach than univariate gene-level analysis, particularly when SNPs influence the expression of different exons with different magnitude and/or direction of effect. The associations identified in our study may provide new insights into the molecular process by which gene expression may contribute to trait variation or disease risk in humans.     

Detection of Pleiotropy through a Phenome-Wide Association Study (PheWAS) of Epidemiologic Data as Part of the Environmental Architecture for Genes Linked to Environment (EAGLE) Study

We performed a Phenome-wide association study (PheWAS) utilizing diverse genotypic and phenotypic data existing across multiple populations in the National Health and Nutrition Examination Surveys (NHANES), conducted by the Centers for Disease Control and Prevention (CDC), and accessed by the Epidemiological Architecture for Genes Linked to Environment (EAGLE) study. We calculated comprehensive tests of association in Genetic NHANES using 80 SNPs and 1,008 phenotypes (grouped into 184 phenotype classes), stratified by race-ethnicity. Genetic NHANES includes three surveys (NHANES III, 1999–2000, and 2001–2002) and three race-ethnicities: non-Hispanic whites (n = 6,634), non-Hispanic blacks (n = 3,458), and Mexican Americans (n = 3,950). We identified 69 PheWAS associations replicating across surveys for the same SNP, phenotype-class, direction of effect, and race-ethnicity at p<0.01, allele frequency >0.01, and sample size >200. Of these 69 PheWAS associations, 39 replicated previously reported SNP-phenotype associations, 9 were related to previously reported associations, and 21 were novel associations. Fourteen results had the same direction of effect across more than one race-ethnicity: one result was novel, 11 replicated previously reported associations, and two were related to previously reported results. Thirteen SNPs showed evidence of pleiotropy. We further explored results with gene-based biological networks, contrasting the direction of effect for pleiotropic associations across phenotypes. One PheWAS result was ABCG2 missense SNP rs2231142, associated with uric acid levels in both non-Hispanic whites and Mexican Americans, protoporphyrin levels in non-Hispanic whites and Mexican Americans, and blood pressure levels in Mexican Americans. Another example was SNP rs1800588 near LIPC, significantly associated with the novel phenotypes of folate levels (Mexican Americans), vitamin E levels (non-Hispanic whites) and triglyceride levels (non-Hispanic whites), and replication for cholesterol levels. The results of this PheWAS show the utility of this approach for exposing more of the complex genetic architecture underlying multiple traits, through generating novel hypotheses for future research.     

NOD2 and CCDC122-LACC1 genes are associated with leprosy susceptibility in Brazilians

Leprosy is a complex disease with phenotypes strongly influenced by genetic variation. A Chinese genome-wide association study (GWAS) depicted novel genes and pathways associated with leprosy susceptibility, only partially replicated by independent studies in different ethnicities. Here, we describe the results of a validation and replication study of the Chinese GWAS in Brazilians, using a stepwise strategy that involved two family-based and three independent case–control samples, resulting in 3,614 individuals enrolled. First, we genotyped a family-based sample for 36 tag single-nucleotide polymorphisms (SNPs) of five genes located in four different candidate loci: CCDC122-LACC1, NOD2, TNFSF15 and RIPK2. Association between leprosy and tag SNPs at NOD2 (rs8057431) and CCDC122-LACC1 (rs4942254) was then replicated in three additional, independent samples (combined OR_AA = 0.49, P = 1.39e?06; OR_CC = 0.72, P = 0.003, respectively). These results clearly implicate the NOD2 pathway in the regulation of leprosy susceptibility across diverse populations.     

Serum vitamins A and E as modifiers of lipid trait genetics in the National Health and Nutrition Examination Surveys as part of the Population Architecture using Genomics and Epidemiology (PAGE) study

Both environmental and genetic factors impact lipid traits. Environmental modifiers of known genotype–phenotype associations may account for some of the “missing heritability” of these traits. To identify such modifiers, we genotyped 23 lipid-associated variants identified previously through genome-wide association studies (GWAS) in 2,435 non-Hispanic white, 1,407 non-Hispanic black, and 1,734 Mexican-American samples collected for the National Health and Nutrition Examination Surveys (NHANES). Along with lipid levels, NHANES collected environmental variables, including fat-soluble macronutrient serum levels of vitamin A and E levels. As part of the Population Architecture using Genomics and Epidemiology (PAGE) study, we modeled gene–environment interactions between vitamin A or vitamin E and 23 variants previously associated with high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. We identified three SNP?×?vitamin A and six SNP?×?vitamin E interactions at a significance threshold of p?<?2.2?×?10^?3. The most significant interaction was APOB rs693?×?vitamin E (p?=?8.9?×?10^?7) for LDL-C levels among Mexican-Americans. The nine significant interaction models individually explained 0.35–1.61?% of the variation in any one of the lipid traits. Our results suggest that vitamins A and E may modify known genotype–phenotype associations; however, these interactions account for only a fraction of the overall variability observed for HDL-C, LDL-C, and TG levels in the general population.     

Targeted next-generation sequencing for identifying genes related to horse temperament

It is a fundamental challenge to discover the association of genetic traits with phenotypic traits. In this study, we aimed to identify possible genetic traits related to horse temperament. Based on previous findings, we selected 71 candidate genes related to temperamental trait and examined them in the human and horse reference genomes (hg38 and equCab2, respectively). We found 16 orthologous genes and, by comparing with the human reference genome, 17 homologous genes in the horse reference genome. We designed probes specific for the 33 horse genes. Using the probes, we built sequencing libraries of the genomic DNA samples from eight aggressive and eight docile horses, and sequenced the constructed libraries using the Illumina Hiseq2500 platform. Through the analysis of the targeted exome sequences, we identified single nucleotide polymorphisms (SNPs) in the genes. SNPs could be served as genetic markers to evaluate aggressive or docile levels of horses. To examine whether any genetic variants are associated with horse temperament, we performed genome-wide association study (GWAS) using the SNP data. GWAS analysis identified ten variants (p-value?<0.05) which could be related to horse temperament. We validated the variants using Sanger sequencing. The most significant variants were found in MAOA (c.1164+41T>C) and AR (c.1047+27G>T) genes with 8.09?×?10^?4 p-value. We suggest that the variants might be used to assess horse temperament and to determine superior horses for riding or racing.     

Genome-wide association study of aspirin-exacerbated respiratory disease in a Korean population

Aspirin-exacerbated respiratory disease (AERD) is a nonallergic clinical syndrome characterized by a severe decline in forced expiratory volume in one second (FEV1) following the ingestion of non-steroidal anti-inflammatory drugs (NSAIDs) such as aspirin. The effects of genetic variants have not fully explained all of the observed individual differences to an aspirin challenge despite previous attempts to identify AERD-related genes. In the present study, we performed genome-wide association study (GWAS) and targeted association study in Korean asthmatics to identify new genetic factors associated with AERD. A total of 685 asthmatic patients without AERD and 117 subjects with AERD were used for the GWAS of the first stage, and 996 asthmatics without AERD and 142 subjects with AERD were used for a follow-up study. A total of 702 SNPs were genotyped using the GoldenGate assay with the VeraCode microbead. GWAS revealed the top-ranked variants in 3′ regions of the HLA-DPB1 gene. To investigate the detailed genetic effects of an associated region with the risk of AERD, a follow-up targeted association study with the 702 single nucleotide polymorphisms (SNPs) of 14 genes was performed on 802 Korean subjects. In a case–control analysis, HLA-DPB1 rs1042151 (Met105Val) shows the most significant association with the susceptibility of AERD (p = 5.11 × 10^?7; OR = 2.40). Moreover, rs1042151 also shows a gene dose for the percent decline of FEV1 after an aspirin challenge (p = 2.82 × 10^?7). Our findings show that the HLA-DPB1 gene polymorphism may be the most susceptible genetic factor for the risk of AERD in Korean asthmatics and confirm the importance of HLA-DPB1 in the genetic etiology of AERD.     

Marker-trait associations in Virginia Tech winter barley identified using genome-wide mapping

Genome-wide association studies (GWAS) provide an opportunity to examine the genetic architecture of quantitatively inherited traits in breeding populations. The objectives of this study were to use GWAS to identify chromosome regions governing traits of importance in six-rowed winter barley (Hordeum vulgare L.) germplasm and to identify single-nucleotide polymorphisms (SNPs) markers that can be implemented in a marker-assisted breeding program. Advanced hulled and hulless lines (329 total) were screened using 3,072 SNPs as a part of the US. Barley Coordinated Agricultural Project (CAP). Phenotypic data collected over 4 years for agronomic and food quality traits and resistance to leaf rust (caused by Puccinia hordei G. Otth), powdery mildew [caused by Blumeria graminis (DC.) E.O. Speer f. sp. hordei Em. Marchal], net blotch (caused by Pyrenophora teres), and spot blotch [caused by Cochliobolus sativus (Ito and Kuribayashi) Drechsler ex Dastur] were analyzed with SNP genotypic data in a GWAS to determine marker-trait associations. Significant SNPs associated with previously described quantitative trait loci (QTL) or genes were identified for heading date on chromosome 3H, test weight on 2H, yield on 7H, grain protein on 5H, polyphenol oxidase activity on 2H and resistance to leaf rust on 2H and 3H, powdery mildew on 1H, 2H and 4H, net blotch on 5H, and spot blotch on 7H. Novel QTL also were identified for agronomic, quality, and disease resistance traits. These SNP-trait associations provide the opportunity to directly select for QTL contributing to multiple traits in breeding programs.     

Genome-wide scan revealed that polymorphisms in the PNPLA3, SAMM50, and PARVB genes are associated with development and progression of nonalcoholic fatty liver disease in Japan

We examined the genetic background of nonalcoholic fatty liver disease (NAFLD) in the Japanese population, by performing a genome-wide association study (GWAS). For GWAS, 392 Japanese NAFLD subjects and 934 control individuals were analyzed. For replication studies, 172 NAFLD and 1,012 control subjects were monitored. After quality control, 261,540 single-nucleotide polymorphisms (SNPs) in autosomal chromosomes were analyzed using a trend test. Association analysis was also performed using multiple logistic regression analysis using genotypes, age, gender and body mass index (BMI) as independent variables. Multiple linear regression analyses were performed to evaluate allelic effect of significant SNPs on biochemical traits and histological parameters adjusted by age, gender, and BMI. Rs738409 in the PNPLA3 gene was most strongly associated with NAFLD after adjustment (P = 6.8 × 10^?14, OR = 2.05). Rs2896019, and rs381062 in the PNPLA3 gene, rs738491, rs3761472, and rs2143571 in the SAMM50 gene, rs6006473, rs5764455, and rs6006611 in the PARVB gene had also significant P values (<2.0 × 10^?10) and high odds ratios (1.84–2.02). These SNPs were found to be in the same linkage disequilibrium block and were associated with decreased serum triglycerides and increased aspartate aminotransferase (AST) and alanine aminotransferase (ALT) in NAFLD patients. These SNPs were associated with steatosis grade and NAFLD activity score (NAS). Rs738409, rs2896019, rs738491, rs6006473, rs5764455, and rs6006611 were associated with fibrosis. Polymorphisms in the SAMM50 and PARVB genes in addition to those in the PNPLA3 gene were observed to be associated with the development and progression of NAFLD.     

A fast algorithm for Bayesian multi-locus model in genome-wide association studies

Genome-wide association studies (GWAS) have identified a large amount of single-nucleotide polymorphisms (SNPs) associated with complex traits. A recently developed linear mixed model for estimating heritability by simultaneously fitting all SNPs suggests that common variants can explain a substantial fraction of heritability, which hints at the low power of single variant analysis typically used in GWAS. Consequently, many multi-locus shrinkage models have been proposed under a Bayesian framework. However, most use Markov Chain Monte Carlo (MCMC) algorithm, which are time-consuming and challenging to apply to GWAS data. Here, we propose a fast algorithm of Bayesian adaptive lasso using variational inference (BAL-VI). Extensive simulations and real data analysis indicate that our model outperforms the well-known Bayesian lasso and Bayesian adaptive lasso models in accuracy and speed. BAL-VI can complete a simultaneous analysis of a lung cancer GWAS data with ~3400 subjects and ~570,000 SNPs in about half a day.     

Evaluation of European Schizophrenia GWAS Loci in Asian Populations via Comprehensive Meta-Analyses

Schizophrenia is a severe and highly heritable neuropsychiatric disorder. Recent genetic analyses including genome-wide association studies (GWAS) have implicated multiple genome-wide significant variants for schizophrenia among European populations. However, many of these risk variants were not largely validated in other populations of different ancestry such as Asians. To validate whether these European GWAS significant loci are associated with schizophrenia in Asian populations, we conducted a systematic literature search and meta-analyses on 19 single nucleotide polymorphisms (SNPs) in Asian populations by combining all available case-control and family-based samples, including up to 30,000 individuals. We employed classical fixed (or random) effects inverse variance weighted methods to calculate summary odds ratios (ORs) and 95 % confidence intervals (CIs). Among the 19 GWAS loci, we replicated the risk associations of nine markers (e.g., SNPs at VRK2, ITIH3/4, NDST3, NOTCH4) surpassing significance level (two-tailed P?<?0.05), and three additional SNPs in MIR137 and ZNF804A also showed trend associations (one-tailed P?<?0.05). These risk associations are in the same directions of allelic effects between Asian replication samples and initial European GWAS findings, and the successful replications of these GWAS loci in a different ethnic group provide stronger evidence for their clinical associations with schizophrenia. Further studies, focusing on the molecular mechanisms of these GWAS significant loci, will become increasingly important for understanding of the pathogenesis to schizophrenia.