Dataset Information

Gene-based genome-wide association studies and meta-analyses of conotruncal heart defects.

ABSTRACT: Conotruncal heart defects (CTDs) are among the most common and severe groups of congenital heart defects. Despite evidence of an inherited genetic contribution to CTDs, little is known about the specific genes that contribute to the development of CTDs. We performed gene-based genome-wide analyses using microarray-genotyped and imputed common and rare variants data from two large studies of CTDs in the United States. We performed two case-parent trio analyses (N = 640 and 317 trios), using an extension of the family-based multi-marker association test, and two case-control analyses (N = 482 and 406 patients and comparable numbers of controls), using a sequence kernel association test. We also undertook two meta-analyses to combine the results from the analyses that used the same approach (i.e. family-based or case-control). To our knowledge, these analyses are the first reported gene-based, genome-wide association studies of CTDs. Based on our findings, we propose eight CTD candidate genes (ARF5, EIF4E, KPNA1, MAP4K3, MBNL1, NCAPG, NDFUS1 and PSMG3). Four of these genes (ARF5, KPNA1, NDUFS1 and PSMG3) have not been previously associated with normal or abnormal heart development. In addition, our analyses provide additional evidence that genes involved in chromatin-modification and in ribonucleic acid splicing are associated with congenital heart defects.

SUBMITTER: Sewda A

PROVIDER: S-EPMC6636758 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Gene-based genome-wide association studies and meta-analyses of conotruncal heart defects.

Sewda Anshuman A Agopian A J AJ Goldmuntz Elizabeth E Hakonarson Hakon H Morrow Bernice E BE Taylor Deanne D Mitchell Laura E LE

PloS one 20190717 7

Conotruncal heart defects (CTDs) are among the most common and severe groups of congenital heart defects. Despite evidence of an inherited genetic contribution to CTDs, little is known about the specific genes that contribute to the development of CTDs. We performed gene-based genome-wide analyses using microarray-genotyped and imputed common and rare variants data from two large studies of CTDs in the United States. We performed two case-parent trio analyses (N = 640 and 317 trios), using an ex ...[more]

PMID: 31314787

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Project description:IntroductionGene-set analysis (GSA) methods are used as complementary approaches to genome-wide association studies (GWASs). The single marker association estimates of a predefined set of genes are either contrasted with those of all remaining genes or with a null non-associated background. To pool the p-values from several GSAs, it is important to take into account the concordance of the observed patterns resulting from single marker association point estimates across any given gene set. Here we propose an enhanced version of Fisher's inverse ?2-method META-GSA, however weighting each study to account for imperfect correlation between association patterns.Simulation and powerWe investigated the performance of META-GSA by simulating GWASs with 500 cases and 500 controls at 100 diallelic markers in 20 different scenarios, simulating different relative risks between 1 and 1.5 in gene sets of 10 genes. Wilcoxon's rank sum test was applied as GSA for each study. We found that META-GSA has greater power to discover truly associated gene sets than simple pooling of the p-values, by e.g. 59% versus 37%, when the true relative risk for 5 of 10 genes was assume to be 1.5. Under the null hypothesis of no difference in the true association pattern between the gene set of interest and the set of remaining genes, the results of both approaches are almost uncorrelated. We recommend not relying on p-values alone when combining the results of independent GSAs.ApplicationWe applied META-GSA to pool the results of four case-control GWASs of lung cancer risk (Central European Study and Toronto/Lunenfeld-Tanenbaum Research Institute Study; German Lung Cancer Study and MD Anderson Cancer Center Study), which had already been analyzed separately with four different GSA methods (EASE; SLAT, mSUMSTAT and GenGen). This application revealed the pathway GO0015291 "transmembrane transporter activity" as significantly enriched with associated genes (GSA-method: EASE, p = 0.0315 corrected for multiple testing). Similar results were found for GO0015464 "acetylcholine receptor activity" but only when not corrected for multiple testing (all GSA-methods applied; p ? 0.02).

Project description:BackgroundCongenital heart defects (CHD) are structural defects of the heart affecting approximately 1% of newborns. They exhibit low penetrance and non-Mendelian patterns of inheritance as varied and complex traits. While genetic factors are known to play an important role in the development of CHD, the specific genetics remain unknown for the majority of patients. To elucidate the underlying genetic risk, we performed a genome wide association study (GWAS) of CHDs in general and specific CHD subgroups using the FinnGen Release 10 (R10) (N > 393,000), followed by functional fine-mapping through eQTL and co-localization analyses using the GTEx database.ResultsWe discovered three genome-wide significant loci associated with general CHD. Two of them were located in chromosome 17: 17q21.32 (rs2316327, intronic: LRRC37A2, Odds ratio (OR) [95% Confidence Interval (CI)] = 1.17[1.12-1.23], p = 1.5 × 10-9) and 17q25.3 (rs1293973611, nearest: BAHCC1, OR[95%CI] = 4.48[2.80-7.17], p = 7.0 × 10-10), respectively, and in addition to general CHD, the rs1293973611 locus was associated with the septal defect subtype. The third locus was in band 1p21.2 (rs35046143, nearest: PALMD, OR[95%CI] = 1.15[1.09-1.21], p = 7.1 × 10-9), and it was associated with general CHD and left-sided lesions. In the subgroup analysis, two additional loci were associated with septal defects (rs75230966 and rs6824295), and one with left-sided lesions (rs1305393195). In the eQTL analysis the variants rs2316327 (general CHD), and rs75230966 (septal defects) both located in 17q21.32 (with a LD r2 of 0.41) were both predicted to significantly associate with the expression of WNT9B in the atrial appendage tissue category. This effect was further confirmed by co-localization analysis, which also implicated WNT3 expression in the atrial appendage. A meta-analysis of general CHD together with the UK Biobank (combined N = 881,678) provided a different genome-wide significant locus in LRRC37A2; rs16941382 (OR[95%CI] = 1.15[1.11-1.20], p = 1.5 × 10-9) which is in significant LD with rs2316327.ConclusionsOur results of general CHD and different CHD subcategories identified a complex risk locus on chromosome 17 near BAHCC1 and LRRC37A2, interacting with the genes WNT9B, WNT3 and MYL4, may constitute potential novel CHD risk associated loci, warranting future experimental tests to determine their role.

Project description:Recent genome-wide association studies (GWAS) of chronic periodontitis (CP) offer rich data sources for the investigation of candidate genes, functional elements, and pathways. We used GWAS data of CP (n = 4,504) and periodontal pathogen colonization (n = 1,020) from a cohort of adult Americans of European descent participating in the Atherosclerosis Risk in Communities study and employed a MAGENTA approach (i.e., meta-analysis gene set enrichment of variant associations) to obtain gene-centric and gene set association results corrected for gene size, number of single-nucleotide polymorphisms, and local linkage disequilibrium characteristics based on the human genome build 18 (National Center for Biotechnology Information build 36). We used the Gene Ontology, Ingenuity, KEGG, Panther, Reactome, and Biocarta databases for gene set enrichment analyses. Six genes showed evidence of statistically significant association: 4 with severe CP (NIN, p = 1.6 × 10(-7); ABHD12B, p = 3.6 × 10(-7); WHAMM, p = 1.7 × 10(-6); AP3B2, p = 2.2 × 10(-6)) and 2 with high periodontal pathogen colonization (red complex-KCNK1, p = 3.4 × 10(-7); Porphyromonas gingivalis-DAB2IP, p = 1.0 × 10(-6)). Top-ranked genes for moderate CP were HGD (p = 1.4 × 10(-5)), ZNF675 (p = 1.5 × 10(-5)), TNFRSF10C (p = 2.0 × 10(-5)), and EMR1 (p = 2.0 × 10(-5)). Loci containing NIN, EMR1, KCNK1, and DAB2IP had showed suggestive evidence of association in the earlier single-nucleotide polymorphism-based analyses, whereas WHAMM and AP2B2 emerged as novel candidates. The top gene sets included severe CP ("endoplasmic reticulum membrane," "cytochrome P450," "microsome," and "oxidation reduction") and moderate CP ("regulation of gene expression," "zinc ion binding," "BMP signaling pathway," and "ruffle"). Gene-centric analyses offer a promising avenue for efficient interrogation of large-scale GWAS data. These results highlight genes in previously identified loci and new candidate genes and pathways possibly associated with CP, which will need to be validated via replication and mechanistic studies.

Dataset Information

Gene-based genome-wide association studies and meta-analyses of conotruncal heart defects.

Publications

Gene-based genome-wide association studies and meta-analyses of conotruncal heart defects.

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