Congenital heart disease risk loci identified by genome-wide association study in European patients.
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ABSTRACT:
SUBMITTER: Lahm H
PROVIDER: S-EPMC7810487 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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.
| S-EPMC10918883 | biostudies-literature
Project description:We conducted a meta-analysis of three endometrial cancer genome-wide association studies (GWAS) and two follow-up phases totaling 7,737 endometrial cancer cases and 37,144 controls of European ancestry. Genome-wide imputation and meta-analysis identified five new risk loci of genome-wide significance at likely regulatory regions on chromosomes 13q22.1 (rs11841589, near KLF5), 6q22.31 (rs13328298, in LOC643623 and near HEY2 and NCOA7), 8q24.21 (rs4733613, telomeric to MYC), 15q15.1 (rs937213, in EIF2AK4, near BMF) and 14q32.33 (rs2498796, in AKT1, near SIVA1). We also found a second independent 8q24.21 signal (rs17232730). Functional studies of the 13q22.1 locus showed that rs9600103 (pairwise r(2) = 0.98 with rs11841589) is located in a region of active chromatin that interacts with the KLF5 promoter region. The rs9600103[T] allele that is protective in endometrial cancer suppressed gene expression in vitro, suggesting that regulation of the expression of KLF5, a gene linked to uterine development, is implicated in tumorigenesis. These findings provide enhanced insight into the genetic and biological basis of endometrial cancer.
| S-EPMC4907351 | biostudies-literature
Project description:The majority of established prostate cancer (PCa) risk-associated single nucleotide polymorphisms (SNPs) identified from genome-wide association studies do not fall into protein coding regions. Therefore, the mechanisms by which these SNPs affect PCa risk remain unclear. Here, we used a series of bioinformatic tools and databases to provide possible molecular insights into the actions of risk SNPs.We performed a comprehensive assessment of the potential functional impact of 33 SNPs that were identified and confirmed as associated with PCa risk in previous studies. For these 33 SNPs and additional SNPs in linkage disequilibrium (LD) (r(2) ???0.5), we first mapped them to genomic functional annotation databases, including the encyclopedia of DNA elements (ENCODE), 11 genomic regulatory elements databases defined by the University of California Santa Cruz (UCSC) table browser, and androgen receptor (AR)-binding sites defined by a ChIP-chip technique. Enrichment analysis was then carried out to assess whether the risk SNP blocks were enriched in the various annotation sets. Risk SNP blocks were significantly enriched over that expected by chance in two annotation sets, including AR-binding sites (P?=?0.003), and FoxA1-binding sites (P?=?0.05). About one-third of the 33 risk SNP blocks are located within AR-binding regions.The significant enrichment of risk SNPs in AR-binding sites may suggest a potential molecular mechanism for these SNPs in PCa initiation, and provide guidance for future functional studies.
| S-EPMC3070182 | biostudies-literature
Project description:BackgroundDepression is a debilitating mental disorder that often coexists with anxiety. The genetic mechanisms of depression and anxiety have considerable overlap, and studying depression in non-anxiety samples could help to discover novel gene. We assess the genetic variation of depression in non-anxiety samples, using genome-wide association studies (GWAS) and linkage disequilibrium score regression (LDSC).MethodsThe GWAS of depression score and self-reported depression were conducted using the UK Biobank samples, comprising 99,178 non-anxiety participants with anxiety score <5 and 86,503 non-anxiety participants without self-reported anxiety, respectively. Replication analysis was then performed using two large-scale GWAS summary data of depression from Psychiatric Genomics Consortium (PGC). LDSC was finally used to evaluate genetic correlations with 855 health-related traits based on the primary GWAS.ResultsTwo genome-wide significant loci for non-anxiety depression were identified: rs139702470 (p = 1.54 × 10-8, OR = 0.29) locate in PIEZO2, and rs6046722 (p = 2.52 × 10-8, OR = 1.09) locate in CFAP61. These associated genes were replicated in two GWAS of depression from PGC, such as rs1040582 (preplication GWAS1 = 0.02, preplication GWAS2 = 2.71 × 10-3) in CFAP61, and rs11661122 (preplication GWAS1 = 8.16 × 10-3, preplication GWAS2 = 8.08 × 10-3) in PIEZO2. LDSC identified 19 traits genetically associated with non-anxiety depression (p < 0.001), such as marital separation/divorce (rg = 0.45, SE = 0.15).ConclusionsOur findings provide novel clues for understanding of the complex genetic architecture of depression.
| S-EPMC9353885 | biostudies-literature
Project description:ObjectiveTo detect rare coding variants underlying loci detected by genome-wide association studies (GWAS) of late onset Alzheimer disease (LOAD).MethodsWe conducted targeted sequencing of ABCA7, BIN1, CD2AP, CLU, CR1, EPHA1, MS4A4A/MS4A6A, and PICALM in 3 independent LOAD cohorts: 176 patients from 124 Caribbean Hispanics families, 120 patients and 33 unaffected individuals from the 129 National Institute on Aging LOAD Family Study; and 263 unrelated Canadian individuals of European ancestry (210 sporadic patients and 53 controls). Rare coding variants found in at least 2 data sets were genotyped in independent groups of ancestry-matched controls. Additionally, the Exome Aggregation Consortium was used as a reference data set for population-based allele frequencies.ResultsOverall we detected a statistically significant 3.1-fold enrichment of the nonsynonymous mutations in the Caucasian LOAD cases compared with controls (p = 0.002) and no difference in synonymous variants. A stop-gain mutation in ABCA7 (E1679X) and missense mutation in CD2AP (K633R) were highly significant in Caucasian LOAD cases, and mutations in EPHA1 (P460L) and BIN1 (K358R) were significant in Caribbean Hispanic families with LOAD. The EPHA1 variant segregated completely in an extended Caribbean Hispanic family and was also nominally significant in the Caucasians. Additionally, BIN1 (K358R) segregated in 2 of the 6 Caribbean Hispanic families where the mutations were discovered.InterpretationTargeted sequencing of confirmed GWAS loci revealed an excess burden of deleterious coding mutations in LOAD, with the greatest burden observed in ABCA7 and BIN1. Identifying coding variants in LOAD will facilitate the creation of tractable models for investigation of disease-related mechanisms and potential therapies.
| S-EPMC4546546 | biostudies-literature
Project description:BACKGROUND: Several novel susceptibility loci for type 2 diabetes have been identified through genome-wide association studies (GWAS) for type 2 diabetes or quantitative traits related to glucose metabolism in European populations. To investigate the association of the 13 new European GWAS-derived susceptibility loci with type 2 diabetes in the Japanese population, we conducted a replication study using 3 independent Japanese case-control studies. METHODOLOGY/PRINCIPAL FINDINGS: We examined the association of single nucleotide polymorphisms (SNPs) within 13 loci (MTNR1B, GCK, IRS1, PROX1, BCL11A, ZBED3, KLF14, TP53INP1, KCNQ1, CENTD2, HMGA2, ZFAND6 and PRC1) with type 2 diabetes using 4,964 participants (2,839 cases and 2,125 controls) from 3 independent Japanese samples. The association of each SNP with type 2 diabetes was analyzed by logistic regression analysis. Further, we performed combined meta-analyses for the 3 studies and previously performed Japanese GWAS data (4,470 cases vs. 3,071 controls). The meta-analysis revealed that rs2943641 in the IRS1 locus was significantly associated with type 2 diabetes, (P = 0.0034, OR = 1.15 95% confidence interval; 1.05-1.26) and 3 SNPs, rs10930963 in the MTNR1B locus, rs972283 in the KLF14 locus, and rs231362 in the KCNQ1 locus, had nominal association with type 2 diabetes in the present Japanese samples (P<0.05). CONCLUSIONS: These results indicate that IRS1 locus may be common locus for type 2 diabetes across different ethnicities.
| S-EPMC3202571 | biostudies-literature
Project description:ObjectiveTo explore the relationship between sleep habits (sleep duration, sleep efficiency, sleep onset timing) and ischemic stroke, and whether there is an interaction between sleep habits and ischemic stroke susceptibility gene loci.MethodsA questionnaire survey, physical examination, blood biochemical testing and genotyping were conducted among rural residents in Beijing, and the gene loci of ischemic stroke suggested by previous genome-wide association studies (GWAS) were screened. Multivariable generalized linear model was used to analyze the correlation between sleep habits, sleep-gene interaction and ischemic stroke.ResultsA total of 4 648 subjects with an average age of (58.5±8.7) years were enrolled, including 1 316 patients with ischemic stroke. Compared with non-stroke patients, stroke patients with sleep duration ≥9 hours, sleep efficiency < 80%, and sleep onset timing earlier than 22:00 accounted for a higher proportion (P < 0.05). There was no significant association between sleep duration and risk of ischemic stroke (OR=1.04, 95%CI: 0.99-1.10, P=0.085). Sleep efficiency was inversely associated with the risk of ischemic stroke (OR=0.18, 95%CI: 0.06-0.53, P=0.002). The risk of ischemic stroke in the subjects with sleep efficiency < 80% was 1.47-fold (95%CI: 1.03-2.10, P=0.033) of that in the subjects with sleep efficiency ≥80%. Falling asleep earlier than 22:00 was associated with 1.26 times greater risk of stroke than falling asleep between 22:00 and 22:59 (95%CI: 1.04-1.52, P=0.017). Multifactorial adjustment model showed that rs579459 on ABO gene had an interaction with sleep time (P for interaction =0.040). When there were two T alleles for rs579459 on the ABO gene, those who fell asleep before 22:00 had 1.56 times (95%CI: 1.20-2.04, P=0.001) the risk of stroke compared with those who fell asleep between 22:00 and 22:59, and there was no significant difference when the number of pathogenic alleles was 0 or 1. In the model adjusted only for gender, age and family structure, sleep duration and the number of T allele rs2634074 on PITX2 gene had an interaction with ischemic stroke (P for interaction=0.033).ConclusionDecreased sleep efficiency is associated with increased risk of ischemic stroke, and falling asleep earlier than 22:00 is associated with higher risk of ischemic stroke. Sleep onset timing interacted with rs579459 in ABO gene and the risk of ischemic stroke. Sleep duration and PITX2 rs2634074 may have a potential interaction with ischemic stroke risk.
| S-EPMC9197694 | biostudies-literature
Project description:ObjectiveWe examined whether a panel of SNPs, systematically selected from genome-wide association studies (GWAS), could improve risk prediction of coronary heart disease (CHD), over-and-above conventional risk factors. These SNPs have already demonstrated reproducible associations with CHD; here we examined their use in long-term risk prediction.Study design and settingSNPs identified from meta-analyses of GWAS of CHD were tested in 840 men and women aged 55-75 from the Edinburgh Artery Study, a prospective, population-based study with 15 years of follow-up. Cox proportional hazards models were used to evaluate the addition of SNPs to conventional risk factors in prediction of CHD risk. CHD was classified as myocardial infarction (MI), coronary intervention (angioplasty, or coronary artery bypass surgery), angina and/or unspecified ischaemic heart disease as a cause of death; additional analyses were limited to MI or coronary intervention. Model performance was assessed by changes in discrimination and net reclassification improvement (NRI).ResultsThere were significant improvements with addition of 27 SNPs to conventional risk factors for prediction of CHD (NRI of 54%, P<0.001; C-index 0.671 to 0.740, P?=?0.001), as well as MI or coronary intervention, (NRI of 44%, P<0.001; C-index 0.717 to 0.750, P?=?0.256). ROC curves showed that addition of SNPs better improved discrimination when the sensitivity of conventional risk factors was low for prediction of MI or coronary intervention.ConclusionThere was significant improvement in risk prediction of CHD over 15 years when SNPs identified from GWAS were added to conventional risk factors. This effect may be particularly useful for identifying individuals with a low prognostic index who are in fact at increased risk of disease than indicated by conventional risk factors alone.
| S-EPMC3584137 | biostudies-literature
Project description:In 2007, the Wellcome Trust Case Control Consortium (WTCCC) performed a genome-wide association study in 2,000 British coronary heart disease (CHD) cases and 3,000 controls after genotyping 469,557 single nucleotide polymorphisms (SNPs). Seven variants associated with CHD were initially identified, and 5 SNPs were later found in replication studies. In the current study, the authors aimed to determine whether the 12 SNPs reported by the WTCCC predicted incident CHD through 2004 in a biracial, prospective cohort study (Atherosclerosis Risk in Communities) comprising 15,792 persons aged 45-64 years who had been selected by probability sampling from 4 different US communities in 1987-1989. Cox proportional hazards models with adjustment for age and gender were used to estimate CHD hazard rate ratios (HRRs) over a 17-year period (1,362 cases in whites and 397 cases in African Americans) under an additive genetic model. The results showed that 3 SNPs in whites (rs599839, rs1333049, and rs501120; HRRs were 1.10 (P = 0.044), 1.14 (P < 0.001), and 1.14 (P = 0.030), respectively) and 1 SNP in African Americans (rs7250581; HRR = 1.60, P = 0.05) were significantly associated with incident CHD. This study demonstrates that genetic variants revealed in a case-control genome-wide association study enriched for early disease onset may play a role in the genetic etiology of CHD in the general population.
| S-EPMC2800304 | biostudies-literature
Project description:BackgroundAlzheimer's disease is a debilitating and highly heritable neurological condition. As such, genetic studies have sought to understand the genetic architecture of Alzheimer's disease since the 1990s, with successively larger genome-wide association studies (GWAS) and meta-analyses. These studies started with a small sample size of 1086 individuals in 2007, which was able to identify only the APOE locus. In 2013, the International Genomics of Alzheimer's Project (IGAP) did a meta-analysis of all existing GWAS using data from 74 046 individuals, which stood as the largest Alzheimer's disease GWAS until 2018. This meta-analysis discovered 19 susceptibility loci for Alzheimer's disease in populations of European ancestry.Recent developmentsThree new Alzheimer's disease GWAS published in 2018 and 2019, which used larger sample sizes and proxy phenotypes from biobanks, have substantially increased the number of known susceptibility loci in Alzheimer's disease to 40. The first, an updated GWAS from IGAP, included 94 437 individuals and discovered 24 susceptibility loci. Although IGAP sought to increase sample size by recruiting additional clinical cases and controls, the two other studies used parental family history of Alzheimer's disease to define proxy cases and controls in the UK Biobank for a genome-wide association by proxy, which was meta-analysed with data from GWAS of clinical Alzheimer's disease to attain sample sizes of 388 324 and 534 403 individuals. These two studies identified 27 and 29 susceptibility loci, respectively. However, the three studies were not independent because of the large overlap in their participants, and interpretation can be challenging because different variants and genes were highlighted by each study, even in the same locus. Furthermore, neither the variant with the strongest Alzheimer's disease association nor the nearest gene are necessarily causal. This situation presents difficulties for experimental studies, drug development, and other future research. WHERE NEXT?: The ultimate goal of understanding the genetic architecture of Alzheimer's disease is to characterise novel biological pathways that underly Alzheimer's disease pathogenesis and to identify novel drug targets. GWAS have successfully contributed to the characterisation of the genetic architecture of Alzheimer's disease, with the identification of 40 susceptibility loci; however, this does not equate to the discovery of 40 Alzheimer's disease genes. To identify Alzheimer's disease genes, these loci need to be mapped to variants and genes through functional genomics studies that combine annotation of variants, gene expression, and gene-based or pathway-based analyses. Such studies are ongoing and have validated several genes at Alzheimer's disease loci, but greater sample sizes and cell-type specific data are needed to map all GWAS loci.
| S-EPMC8176461 | biostudies-literature