Deep resequencing identifies candidate functional genes in leprosy GWAS loci

Leprosy is the second most prevalent mycobacterial disease globally. Despite the existence of an effective therapy, leprosy incidence has consistently remained above 200,000 cases per year since 2010. Numerous host genetic factors have been identified for leprosy that contribute to the persistently high case numbers. In the past decade, genetic epidemiology approaches, including genome-wide association studies (GWAS), identified more than 30 loci contributing to leprosy susceptibility. However, GWAS loci commonly encompass multiple genes, which poses a challenge to define causal candidates for each locus. To address this problem, we hypothesized that genes contributing to leprosy susceptibility differ in their frequencies of rare protein-altering variants between cases and controls. Using deep resequencing we assessed protein-coding variants for 34 genes located in GWAS or linkage loci in 555 Vietnamese leprosy cases and 500 healthy controls. We observed 234 nonsynonymous mutations in the targeted genes. A significant depletion of protein-altering variants was detected for the IL18R1 and BCL10 genes in leprosy cases. The IL18R1 gene is clustered with IL18RAP and IL1RL1 in the leprosy GWAS locus on chromosome 2q12.1. Moreover, in a recent GWAS we identified an HLA-independent signal of association with leprosy on chromosome 6p21. Here, we report amino acid changes in the CDSN and PSORS1C2 genes depleted in leprosy cases, indicating them as candidate genes in the chromosome 6p21 locus. Our results show that deep resequencing can identify leprosy candidate susceptibility genes that had been missed by classic linkage and association approaches.     

Unifying candidate gene and GWAS Approaches in Asthma

The first genome wide association study (GWAS) for childhood asthma identified a novel major susceptibility locus on chromosome 17q21 harboring the ORMDL3 gene, but the role of previous asthma candidate genes was not specifically analyzed in this GWAS. We systematically identified 89 SNPs in 14 candidate genes previously associated with asthma in >3 independent study populations. We re-genotyped 39 SNPs in these genes not covered by GWAS performed in 703 asthmatics and 658 reference children. Genotyping data were compared to imputation data derived from Illumina HumanHap300 chip genotyping. Results were combined to analyze 566 SNPs covering all 14 candidate gene loci. Genotyped polymorphisms in ADAM33, GSTP1 and VDR showed effects with p-values <0.0035 (corrected for multiple testing). Combining genotyping and imputation, polymorphisms in DPP10, EDN1, IL12B, IL13, IL4, IL4R and TNF showed associations at a significance level between p = 0.05 and p = 0.0035. These data indicate that (a) GWAS coverage is insufficient for many asthma candidate genes, (b) imputation based on these data is reliable but incomplete, and (c) SNPs in three previously identified asthma candidate genes replicate in our GWAS population with significance after correction for multiple testing in 14 genes.     

A comprehensive analysis of shared loci between systemic lupus erythematosus (SLE) and sixteen autoimmune diseases reveals limited genetic overlap

In spite of the well-known clustering of multiple autoimmune disorders in families, analyses of specific shared genes and polymorphisms between systemic lupus erythematosus (SLE) and other autoimmune diseases (ADs) have been limited. Therefore, we comprehensively tested autoimmune variants for association with SLE, aiming to identify pleiotropic genetic associations between these diseases. We compiled a list of 446 non–Major Histocompatibility Complex (MHC) variants identified in genome-wide association studies (GWAS) of populations of European ancestry across 17 ADs. We then tested these variants in our combined Caucasian SLE cohorts of 1,500 cases and 5,706 controls. We tested a subset of these polymorphisms in an independent Caucasian replication cohort of 2,085 SLE cases and 2,854 controls, allowing the computation of a meta-analysis between all cohorts. We have uncovered novel shared SLE loci that passed multiple comparisons adjustment, including the VTCN1 (rs12046117, P = 2.02×10⁻⁰⁶) region. We observed that the loci shared among the most ADs include IL23R, OLIG3/TNFAIP3, and IL2RA. Given the lack of a universal autoimmune risk locus outside of the MHC and variable specificities for different diseases, our data suggests partial pleiotropy among ADs. Hierarchical clustering of ADs suggested that the most genetically related ADs appear to be type 1 diabetes with rheumatoid arthritis and Crohn''s disease with ulcerative colitis. These findings support a relatively distinct genetic susceptibility for SLE. For many of the shared GWAS autoimmune loci, we found no evidence for association with SLE, including IL23R. Also, several established SLE loci are apparently not associated with other ADs, including the ITGAM-ITGAX and TNFSF4 regions. This study represents the most comprehensive evaluation of shared autoimmune loci to date, supports a relatively distinct non–MHC genetic susceptibility for SLE, provides further evidence for previously and newly identified shared genes in SLE, and highlights the value of studies of potentially pleiotropic genes in autoimmune diseases.     

Large-Scale Genome-Wide Association Studies and Meta-Analyses of Longitudinal Change in Adult Lung Function

Background

Genome-wide association studies (GWAS) have identified numerous loci influencing cross-sectional lung function, but less is known about genes influencing longitudinal change in lung function.

Methods

We performed GWAS of the rate of change in forced expiratory volume in the first second (FEV₁) in 14 longitudinal, population-based cohort studies comprising 27,249 adults of European ancestry using linear mixed effects model and combined cohort-specific results using fixed effect meta-analysis to identify novel genetic loci associated with longitudinal change in lung function. Gene expression analyses were subsequently performed for identified genetic loci. As a secondary aim, we estimated the mean rate of decline in FEV₁ by smoking pattern, irrespective of genotypes, across these 14 studies using meta-analysis.

Results

The overall meta-analysis produced suggestive evidence for association at the novel IL16/STARD5/TMC3 locus on chromosome 15 (P  =  5.71 × 10^-7). In addition, meta-analysis using the five cohorts with ≥3 FEV₁ measurements per participant identified the novel ME3 locus on chromosome 11 (P  =  2.18 × 10^-8) at genome-wide significance. Neither locus was associated with FEV₁ decline in two additional cohort studies. We confirmed gene expression of IL16, STARD5, and ME3 in multiple lung tissues. Publicly available microarray data confirmed differential expression of all three genes in lung samples from COPD patients compared with controls. Irrespective of genotypes, the combined estimate for FEV₁ decline was 26.9, 29.2 and 35.7 mL/year in never, former, and persistent smokers, respectively.

Conclusions

In this large-scale GWAS, we identified two novel genetic loci in association with the rate of change in FEV₁ that harbor candidate genes with biologically plausible functional links to lung function.     

SNP-SNP Interactions Discovered by Logic Regression Explain Crohn's Disease Genetics

In genome-wide association studies (GWAS), the association between each single nucleotide polymorphism (SNP) and a phenotype is assessed statistically. To further explore genetic associations in GWAS, we considered two specific forms of biologically plausible SNP-SNP interactions, ‘SNP intersection’ and ‘SNP union,’ and analyzed the Crohn''s Disease (CD) GWAS data of the Wellcome Trust Case Control Consortium for these interactions using a limited form of logic regression. We found strong evidence of CD-association for 195 genes, identifying novel susceptibility genes (e.g., ISX, SLCO6A1, TMEM183A) as well as confirming many previously identified susceptibility genes in CD GWAS (e.g., IL23R, NOD2, CYLD, NKX2-3, IL12RB2, ATG16L1). Notably, 37 of the 59 chromosomal locations indicated for CD-association by a meta-analysis of CD GWAS, involving over 22,000 cases and 29,000 controls, were represented in the 195 genes, as well as some chromosomal locations previously indicated only in linkage studies, but not in GWAS. We repeated the analysis with two smaller GWASs from the Database of Genotype and Phenotype (dbGaP): in spite of differences of populations and study power across the three datasets, we observed some consistencies across the three datasets. Notable examples included TMEM183A and SLCO6A1 which exhibited strong evidence consistently in our WTCCC and both of the dbGaP SNP-SNP interaction analyses. Examining these specific forms of SNP interactions could identify additional genetic associations from GWAS. R codes, data examples, and a ReadMe file are available for download from our website: http://www.ualberta.ca/~yyasui/homepage.html.     

A meta-analysis of genome-wide association scans identifies IL18RAP, PTPN2, TAGAP, and PUS10 as shared risk loci for Crohn's disease and celiac disease

Crohn''s disease (CD) and celiac disease (CelD) are chronic intestinal inflammatory diseases, involving genetic and environmental factors in their pathogenesis. The two diseases can co-occur within families, and studies suggest that CelD patients have a higher risk to develop CD than the general population. These observations suggest that CD and CelD may share common genetic risk loci. Two such shared loci, IL18RAP and PTPN2, have already been identified independently in these two diseases. The aim of our study was to explicitly identify shared risk loci for these diseases by combining results from genome-wide association study (GWAS) datasets of CD and CelD. Specifically, GWAS results from CelD (768 cases, 1,422 controls) and CD (3,230 cases, 4,829 controls) were combined in a meta-analysis. Nine independent regions had nominal association p-value <1.0×10⁻⁵ in this meta-analysis and showed evidence of association to the individual diseases in the original scans (p-value <1×10⁻² in CelD and <1×10⁻³ in CD). These include the two previously reported shared loci, IL18RAP and PTPN2, with p-values of 3.37×10⁻⁸ and 6.39×10⁻⁹, respectively, in the meta-analysis. The other seven had not been reported as shared loci and thus were tested in additional CelD (3,149 cases and 4,714 controls) and CD (1,835 cases and 1,669 controls) cohorts. Two of these loci, TAGAP and PUS10, showed significant evidence of replication (Bonferroni corrected p-values <0.0071) in the combined CelD and CD replication cohorts and were firmly established as shared risk loci of genome-wide significance, with overall combined p-values of 1.55×10⁻¹⁰ and 1.38×10⁻¹¹ respectively. Through a meta-analysis of GWAS data from CD and CelD, we have identified four shared risk loci: PTPN2, IL18RAP, TAGAP, and PUS10. The combined analysis of the two datasets provided the power, lacking in the individual GWAS for single diseases, to detect shared loci with a relatively small effect.     

Are C-Reactive Protein Associated Genetic Variants Associated with Serum Levels and Retinal Markers of Microvascular Pathology in Asian Populations from Singapore?

Introduction

C-reactive protein (CRP) levels are associated with cardiovascular disease and systemic inflammation. We assessed whether CRP-associated loci were associated with serum CRP and retinal markers of microvascular disease, in Asian populations.

Methods

Genome-wide association analysis (GWAS) for serum CRP was performed in East-Asian Chinese (N = 2,434) and Malays (N = 2,542) and South-Asian Indians (N = 2,538) from Singapore. Leveraging on GWAS data, we assessed, in silico, association levels among the Singaporean datasets for 22 recently identified CRP-associated loci. At loci where directional inconsistencies were observed, quantification of inter-ethnic linkage disequilibrium (LD) difference was determined. Next, we assessed association for a variant at CRP and retinal vessel traits [central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE)] in a total of 24,132 subjects of East-Asian, South-Asian and European ancestry.

Results

Serum CRP was associated with SNPs in/near APOE, CRP, HNF1A and LEPR (p-values ≤4.7×10⁻⁸) after meta-analysis of Singaporean populations. Using a candidate-SNP approach, we further replicated SNPs at 4 additional loci that had been recently identified to be associated with serum CRP (IL6R, GCKR, IL6 and IL1F10) (p-values ≤0.009), in the Singaporean datasets. SNPs from these 8 loci explained 4.05% of variance in serum CRP. Two SNPs (rs2847281 and rs6901250) were detected to be significant (p-value ≤0.036) but with opposite effect directions in the Singaporean populations as compared to original European studies. At these loci we did not detect significant inter-population LD differences. We further did not observe a significant association between CRP variant and CRVE or CRAE levels after meta-analysis of all Singaporean and European datasets (p-value >0.058).

Conclusions

Common variants associated with serum CRP, first detected in primarily European studies, are also associated with CRP levels in East-Asian and South-Asian populations. We did not find a causal link between CRP and retinal measures of microvascular disease.     

Replication Study in a Japanese Population of Six Susceptibility Loci for Type 2 Diabetes Originally Identified by a Transethnic Meta-Analysis of Genome-Wide Association Studies

AimWe performed a replication study in a Japanese population to evaluate the association between type 2 diabetes and six susceptibility loci (TMEM154, SSR1, FAF1, POU5F1, ARL15, and MPHOSPH9) originally identified by a transethnic meta-analysis of genome-wide association studies (GWAS) in 2014.MethodsWe genotyped 7,620 Japanese participants (5,817 type 2 diabetes patients and 1,803 controls) for each of the single nucleotide polymorphisms (SNPs) using a multiplex polymerase chain reaction invader assay. The association of each SNP locus with the disease was evaluated using logistic regression analysis.ResultsOf the six SNPs examined in this study, four (rs6813195 near TMEM154, rs17106184 in FAF1, rs3130501 in POU5F1 and rs4275659 near MPHOSPH9) had the same direction of effect as in the original reports, but two (rs9505118 in SSR1 and rs702634 in ARL15) had the opposite direction of effect. Among these loci, rs3130501 and rs4275659 were nominally associated with type 2 diabetes (rs3130501; p = 0.017, odds ratio [OR] = 1.113, 95% confidence interval [CI] 1.019–1.215, rs4275659; p = 0.012, OR = 1.127, 95% CI 1.026–1.238, adjusted for sex, age and body mass index), but we did not observe a significant association with type 2 diabetes for any of the six evaluated SNP loci in our Japanese population.ConclusionsOur results indicate that effects of the six SNP loci identified in the transethnic GWAS meta-analysis are not major among the Japanese, although SNPs in POU5F1 and MPHOSPH9 loci may have some effect on susceptibility to type 2 diabetes in this population.     

Refining Susceptibility Loci of Chronic Obstructive Pulmonary Disease with Lung eqtls

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of mortality worldwide. Recent genome-wide association studies (GWAS) have identified robust susceptibility loci associated with COPD. However, the mechanisms mediating the risk conferred by these loci remain to be found. The goal of this study was to identify causal genes/variants within susceptibility loci associated with COPD. In the discovery cohort, genome-wide gene expression profiles of 500 non-tumor lung specimens were obtained from patients undergoing lung surgery. Blood-DNA from the same patients were genotyped for 1,2 million SNPs. Following genotyping and gene expression quality control filters, 409 samples were analyzed. Lung expression quantitative trait loci (eQTLs) were identified and overlaid onto three COPD susceptibility loci derived from GWAS; 4q31 (HHIP), 4q22 (FAM13A), and 19q13 (RAB4B, EGLN2, MIA, CYP2A6). Significant eQTLs were replicated in two independent datasets (n = 363 and 339). SNPs previously associated with COPD and lung function on 4q31 (rs1828591, rs13118928) were associated with the mRNA expression of HHIP. An association between mRNA expression level of FAM13A and SNP rs2045517 was detected at 4q22, but did not reach statistical significance. At 19q13, significant eQTLs were detected with EGLN2. In summary, this study supports HHIP, FAM13A, and EGLN2 as the most likely causal COPD genes on 4q31, 4q22, and 19q13, respectively. Strong lung eQTL SNPs identified in this study will need to be tested for association with COPD in case-control studies. Further functional studies will also be needed to understand the role of genes regulated by disease-related variants in COPD.     

Replication Study in a Japanese Population to Evaluate the Association between 10 SNP Loci,Identified in European Genome-Wide Association Studies,and Type 2 Diabetes

AimWe performed a replication study in a Japanese population to evaluate the association between type 2 diabetes and 7 susceptibility loci originally identified by European genome-wide association study (GWAS) in 2012: ZMIZ1, KLHDC5, TLE1, ANKRD55, CILP2, MC4R, and BCAR1. We also examined the association of 3 additional loci: CCND2 and GIPR, identified in sex-differentiated analyses, and LAMA1, which was shown to be associated with non-obese European type 2 diabetes.MethodsWe genotyped 6,972 Japanese participants (4,280 type 2 diabetes patients and 2,692 controls) for each of the 10 single nucleotide polymorphisms (SNPs): rs12571751 in ZMIZ1, rs10842994 near KLHDC5, rs2796441 near TLE1, rs459193 near ANKRD55, rs10401969 in CILP2, rs12970134 near MC4R, rs7202877 near BCAR1, rs11063069 near CCND2, rs8108269 near GIPR, and rs8090011 in LAMA1 using a multiplex polymerase chain reaction invader assay. The association of each SNP locus with the disease was evaluated using a logistic regression analysis.ResultsAll SNPs examined in this study had the same direction of effect (odds ratio > 1.0, p = 9.77 × 10^-4, binomial test), as in the original reports. Among them, rs12571751 in ZMIZ1 was significantly associated with type 2 diabetes [p = 0.0041, odds ratio = 1.123, 95% confidence interval 1.037–1.215, adjusted for sex, age and body mass index (BMI)], but we did not observe significant association of the remaining 9 SNP loci with type 2 diabetes in the present Japanese population (p ≥ 0.005). A genetic risk score, constructed from the sum of risk alleles for the 7 SNP loci identified by un-stratified analyses in the European GWAS meta-analysis were associated with type 2 diabetes in the present Japanese population (p = 2.3 × 10^-4, adjusted for sex, age and BMI).ConclusionsZMIZ1 locus has a significant effect on conferring susceptibility to type 2 diabetes also in the Japanese population.     

A systems genetics approach provides a bridge from discovered genetic variants to biological pathways in rheumatoid arthritis

Genome-wide association studies (GWAS) have yielded novel genetic loci underlying common diseases. We propose a systems genetics approach to utilize these discoveries for better understanding of the genetic architecture of rheumatoid arthritis (RA). Current evidence of genetic associations with RA was sought through PubMed and the NHGRI GWAS catalog. The associations of 15 single nucleotide polymorphisms and HLA-DRB1 alleles were confirmed in 1,287 cases and 1,500 controls of Japanese subjects. Among these, HLA-DRB1 alleles and eight SNPs showed significant associations and all but one of the variants had the same direction of effect as identified in the previous studies, indicating that the genetic risk factors underlying RA are shared across populations. By receiver operating characteristic curve analysis, the area under the curve (AUC) for the genetic risk score based on the selected variants was 68.4%. For seropositive RA patients only, the AUC improved to 70.9%, indicating good but suboptimal predictive ability. A simulation study shows that more than 200 additional loci with similar effect size as recent GWAS findings or 20 rare variants with intermediate effects are needed to achieve AUC = 80.0%. We performed the random walk with restart (RWR) algorithm to prioritize genes for future mapping studies. The performance of the algorithm was confirmed by leave-one-out cross-validation. The RWR algorithm pointed to ZAP70 in the first rank, in which mutation causes RA-like autoimmune arthritis in mice. By applying the hierarchical clustering method to a subnetwork comprising RA-associated genes and top-ranked genes by the RWR, we found three functional modules relevant to RA etiology: “leukocyte activation and differentiation”, “pattern-recognition receptor signaling pathway”, and “chemokines and their receptors”.These results suggest that the systems genetics approach is useful to find directions of future mapping strategies to illuminate biological pathways.     

Alzheimer’s Disease Risk Polymorphisms Regulate Gene Expression in the ZCWPW1 and the CELF1 Loci

Late onset Alzheimer’s disease (LOAD) is a genetically complex and clinically heterogeneous disease. Recent large-scale genome wide association studies (GWAS) have identified more than twenty loci that modify risk for AD. Despite the identification of these loci, little progress has been made in identifying the functional variants that explain the association with AD risk. Thus, we sought to determine whether the novel LOAD GWAS single nucleotide polymorphisms (SNPs) alter expression of LOAD GWAS genes and whether expression of these genes is altered in AD brains. The majority of LOAD GWAS SNPs occur in gene dense regions under large linkage disequilibrium (LD) blocks, making it unclear which gene(s) are modified by the SNP. Thus, we tested for brain expression quantitative trait loci (eQTLs) between LOAD GWAS SNPs and SNPs in high LD with the LOAD GWAS SNPs in all of the genes within the GWAS loci. We found a significant eQTL between rs1476679 and PILRB and GATS, which occurs within the ZCWPW1 locus. PILRB and GATS expression levels, within the ZCWPW1 locus, were also associated with AD status. Rs7120548 was associated with MTCH2 expression, which occurs within the CELF1 locus. Additionally, expression of several genes within the CELF1 locus, including MTCH2, were highly correlated with one another and were associated with AD status. We further demonstrate that PILRB, as well as other genes within the GWAS loci, are most highly expressed in microglia. These findings together with the function of PILRB as a DAP12 receptor supports the critical role of microglia and neuroinflammation in AD risk.     

Genome-wide association mapping of salinity tolerance in rice (Oryza sativa)

Salinity tolerance in rice is highly desirable to sustain production in areas rendered saline due to various reasons. It is a complex quantitative trait having different components, which can be dissected effectively by genome-wide association study (GWAS). Here, we implemented GWAS to identify loci controlling salinity tolerance in rice. A custom-designed array based on 6,000 single nucleotide polymorphisms (SNPs) in as many stress-responsive genes, distributed at an average physical interval of <100 kb on 12 rice chromosomes, was used to genotype 220 rice accessions using Infinium high-throughput assay. Genetic association was analysed with 12 different traits recorded on these accessions under field conditions at reproductive stage. We identified 20 SNPs (loci) significantly associated with Na⁺/K⁺ ratio, and 44 SNPs with other traits observed under stress condition. The loci identified for various salinity indices through GWAS explained 5–18% of the phenotypic variance. The region harbouring Saltol, a major quantitative trait loci (QTLs) on chromosome 1 in rice, which is known to control salinity tolerance at seedling stage, was detected as a major association with Na⁺/K⁺ ratio measured at reproductive stage in our study. In addition to Saltol, we also found GWAS peaks representing new QTLs on chromosomes 4, 6 and 7. The current association mapping panel contained mostly indica accessions that can serve as source of novel salt tolerance genes and alleles. The gene-based SNP array used in this study was found cost-effective and efficient in unveiling genomic regions/candidate genes regulating salinity stress tolerance in rice.     

Genetics of venous thrombosis: insights from a new genome wide association study

Background

Venous Thrombosis (VT) is a common multifactorial disease associated with a major public health burden. Genetics factors are known to contribute to the susceptibility of the disease but how many genes are involved and their contribution to VT risk still remain obscure. We aimed to identify genetic variants associated with VT risk.

Methodology/Principal Findings

We conducted a genome-wide association study (GWAS) based on 551,141 SNPs genotyped in 1,542 cases and 1,110 controls. Twelve SNPs reached the genome-wide significance level of 2.0×10⁻⁸ and encompassed four known VT-associated loci, ABO, F5, F11 and FGG. By means of haplotype analyses, we also provided novel arguments in favor of a role of HIVEP1, PROCR and STAB2, three loci recently hypothesized to participate in the susceptibility to VT. However, no novel VT-associated loci came out of our GWAS. Using a recently proposed statistical methodology, we also showed that common variants could explain about 35% of the genetic variance underlying VT susceptibility among which 3% could be attributable to the main identified VT loci. This analysis additionally suggested that the common variants left to be identified are not uniformly distributed across the genome and that chromosome 20, itself, could contribute to ∼7% of the total genetic variance.

Conclusions/Significance

This study might also provide a valuable source of information to expand our understanding of biological mechanisms regulating quantitative biomarkers for VT.     

A genome-wide association study identifies genomic loci associated with backfat thickness,carcass weight,and body weight in two commercial pig populations

Growth and fatness traits are economically important in the pig industry. To dissect the genetic architecture of these traits in commercial pigs, we conducted a genome-wide association study (GWAS) for carcass weight, backfat thickness, and body weight in two commercial populations: Duroc × (Landrace × Yorkshire) (DLY) and Duroc populations. To enhance the detection power, three GWAS approaches including single-trait GWAS, multi-trait GWAS and meta-analysis were used in this study. A total of 13 suggestive loci were identified on nine chromosomes. The most significant locus was detected at 272.05 Mb on SSC1, and it was associated with backfat thickness at the first rib in the DLY population. Three genes at the identified loci (TBC1D1, BAAT and PHLPP1) were highlighted as functionally plausible candidate genes for pig growth and fatness traits. Genome-wide significant locus was not evidenced in this study, indicating that large populations are required to identify QTL with minor effects on growth and fatness traits in commercial pig populations, in which intensively artificial selections have been imposed on these traits and small genetical variances usually retain in these traits.     

Genome-wide association study of heading and flowering dates and construction of its prediction equation in Chinese common wheat

Heading date is one of the most important traits in wheat breeding as it affects adaptation and yield potential. A genome-wide association study (GWAS) using the 90 K iSelect SNP genotyping assay indicated that a total of 306 loci were significantly associated with heading and flowering dates in 13 environments in Chinese common wheat from the Yellow and Huai wheat region. Of these, 105 loci were significantly correlated with both heading and flowering dates and were found in clusters on chromosomes 2, 5, 6, and 7. Based on differences in distribution of the vernalization and photoperiod genes among chromosomes, arms, or block regions, 13 novel, environmentally stable genetic loci were associated with heading and flowering dates, including RAC875_c41145_189 on 1DS, RAC875_c50422_299 on 2BL, and RAC875_c48703_148 on 2DS, that accounted for more than 20% phenotypic variance explained (PVE) of the heading/flowering date in at least four environments. GWAS and t test of a combination of SNPs and vernalization and photoperiod alleles indicated that the Vrn-B1, Vrn-D1, and Ppd-D1 genes significantly affect heading and flowering dates in Chinese common wheat. Based on the association of heading and flowering dates with the vernalization and photoperiod alleles at seven loci and three significant SNPs, optimal linear regression equations were established, which show that of the seven loci, the Ppd-D1 gene plays the most important role in modulating heading and flowering dates in Chinese wheat, followed by Vrn-B1 and Vrn-D1. Additionally, three novel genetic loci (RAC875_c41145_189, Excalibur_c60164_137, and RAC875_c50422_299) also show important effect on heading and flowering dates. Therefore, Ppd-D1, Vrn-B1, Vrn-D1, and the novel genetic loci should be further investigated in terms of improving heading and flowering dates in Chinese wheat. Further quantitative analysis of an F₁₀ recombinant inbred lines population identified a major QTL that controls heading and flowering dates within the Ppd-D1 locus with PVEs of 28.4% and 34.0%, respectively; this QTL was also significantly associated with spike length, peduncle length, fertile spikelets number, cold resistance, and tiller number.     

Mendelian randomization analysis identified genes potentially pleiotropically associated with periodontitis

ObjectiveTo prioritize genes that were pleiotropically or potentially causally associated with periodontitis.MethodsWe applied the summary data-based Mendelian randomization (SMR) method integrating genome-wide association study (GWAS) for periodontitis and expression quantitative trait loci (eQTL) data to identify genes that were pleiotropically associated with periodontitis. We performed separate SMR analysis using CAGE eQTL data and GTEx eQTL data. SMR analysis were done for participants of European and East Asian ancestries, separately.ResultsWe identified multiple genes showing pleiotropic association with periodontitis in participants of European ancestry and participants of East Asian ancestry. PDCD2 (corresponding probe: ILMN_1758915) was the top hit showing pleotropic association with periodontitis in the participants of European ancestry using CAGE eQTL data, and BX093763 (corresponding probe: ILMN_1899903) and AC104135.3 (corresponding probe: ENSG00000204792.2) were the top hits in the participants of East Asian ancestry using CAGE eQTL data and GTEx eQTL data, respectively.ConclusionWe identified multiple genes that may be involved in the pathogenesis of periodontitis in participants of European ancestry and participants of East Asian ancestry. Our findings provided important leads to a better understanding of the mechanisms underlying periodontitis and revealed potential therapeutic targets for the effective treatment of periodontitis.     

Network-based Analysis of Genome Wide Association Data Provides Novel Candidate Genes for Lipid and Lipoprotein Traits

Genome wide association studies (GWAS) identify susceptibility loci for complex traits, but do not identify particular genes of interest. Integration of functional and network information may help in overcoming this limitation and identifying new susceptibility loci. Using GWAS and comorbidity data, we present a network-based approach to predict candidate genes for lipid and lipoprotein traits. We apply a prediction pipeline incorporating interactome, co-expression, and comorbidity data to Global Lipids Genetics Consortium (GLGC) GWAS for four traits of interest, identifying phenotypically coherent modules. These modules provide insights regarding gene involvement in complex phenotypes with multiple susceptibility alleles and low effect sizes. To experimentally test our predictions, we selected four candidate genes and genotyped representative SNPs in the Malmö Diet and Cancer Cardiovascular Cohort. We found significant associations with LDL-C and total-cholesterol levels for a synonymous SNP (rs234706) in the cystathionine beta-synthase (CBS) gene (p = 1 × 10⁻⁵ and adjusted-p = 0.013, respectively). Further, liver samples taken from 206 patients revealed that patients with the minor allele of rs234706 had significant dysregulation of CBS (p = 0.04). Despite the known biological role of CBS in lipid metabolism, SNPs within the locus have not yet been identified in GWAS of lipoprotein traits. Thus, the GWAS-based Comorbidity Module (GCM) approach identifies candidate genes missed by GWAS studies, serving as a broadly applicable tool for the investigation of other complex disease phenotypes.Genome wide association studies (GWAS)¹ meta-analyses have pinpointed a number of new gene regions contributing to multifactorial diseases. GWAS typically find limited numbers of loci that contribute modestly to complex phenotypes (1), and GLGC meta-analysis of GWAS data has reached the limit of what can be expected (2) without the use of alternative strategies. Given that susceptibility loci for complex traits are unlikely to be randomly distributed in the genome (3), we might expect that the genes associated with a disease will be more likely to be present within the same pathways or functional groupings. In published cases, pathway based GWAS analysis provides an alternative approach to the dissection of complex disease traits (4, 5). In addition, nominal GWAS p values superimposed upon the human molecular network have been used to identify genes associated with multiple sclerosis (6), and the disease association protein–protein link evaluator (DAPPLE) has been used to find significant interactions among proteins encoded by genes in loci associated with other particular diseases (7). Other approaches incorporate heterogeneous molecular data such as linkage studies, cross species conservation measures, gene expression data and protein–protein interactions to better understand GWAS results (8, 9). Integrating molecular network information, pathway analyses, and GWAS data thus holds promise for identifying new susceptibility loci and improving the identification of relevant candidate genes.If a gene is involved in a specific functional process or disease, its molecular network neighbors might also be suspected to have some role (3). In line with this “local” hypothesis, proteins involved in the same disease show a high propensity to interact (10) or cluster together (11) with each other. Interactions between variations in multiple genes, each with strong or modest effects, perturbing the same pathways or modules, may govern complex traits (3, 6). The molecular triangulation (MT) algorithm can be applied to rank seed genes according to their common disease associated neighbors, assigning closer and more connected neighbors higher values (12). Interactions between modestly associated MT genes may be indicative of coherent disease pathways or of genes conferring susceptibility to disease in a coordinated manner. The jActiveModule method (13) combines seed gene scores with biologically relevant interactions to identify network modules where perturbations causative of disease are more likely to reside. Lastly, although not yet implemented at the module level, phenotypic coherence between interacting pairs of genes has been quantified using the combination of molecular level gene to disease relationships and Medicare comorbidity data (14, 15).We believe that GWAS significant SNPs and variants representing potential candidate genes can use the above strategies to reveal more about the missing heritability of complex phenotypes. The most important risk factors for coronary artery disease (CAD) include serum concentrations of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG). We present a GWAS-based meta-analysis Comorbid Module (GCM) approach that uses significant (p < 5 × 10⁻⁸) GWAS signals for these four traits in the context of molecular networks to prioritize modules of disease-associated candidate genes. We evaluate our approach experimentally through allelic association and genotyping within the Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC) for SNPs representing top candidate genes.     

Inferred expression regulator activities suggest genes mediating cardiometabolic genetic signals

Expression QTL (eQTL) analyses have suggested many genes mediating genome-wide association study (GWAS) signals but most GWAS signals still lack compelling explanatory genes. We have leveraged an adipose-specific gene regulatory network to infer expression regulator activities and phenotypic master regulators (MRs), which were used to detect activity QTLs (aQTLs) at cardiometabolic trait GWAS loci. Regulator activities were inferred with the VIPER algorithm that integrates enrichment of expected expression changes among a regulator’s target genes with confidence in their regulator-target network interactions and target overlap between different regulators (i.e., pleiotropy). Phenotypic MRs were identified as those regulators whose activities were most important in predicting their respective phenotypes using random forest modeling. While eQTLs were typically more significant than aQTLs in cis, the opposite was true among candidate MRs in trans. Several GWAS loci colocalized with MR trans-eQTLs/aQTLs in the absence of colocalized cis-QTLs. Intriguingly, at the 1p36.1 BMI GWAS locus the EPHB2 cis-aQTL was stronger than its cis-eQTL and colocalized with the GWAS signal and 35 BMI MR trans-aQTLs, suggesting the GWAS signal may be mediated by effects on EPHB2 activity and its downstream effects on a network of BMI MRs. These MR and aQTL analyses represent systems genetic methods that may be broadly applied to supplement standard eQTL analyses for suggesting molecular effects mediating GWAS signals.