rs113819537 - SSPN
Magnitude 2.2 · 5 studies on file
Reported associations
-
A cross-population atlas of genetic associations for 220 human phenotypes. - Nature genetics (2021) · Sakaue S, Kanai M, Tanigawa Y, Karjalainen J, Kurki M, Koshiba S, Narita A, Konuma T, Yamamoto K, Akiyama M, Ishigaki K, Suzuki A, Suzuki K, Obara W, Yamaji K, Takahashi K, Asai S, Takahashi Y, Suzuki T, Shinozaki N, Yamaguchi H, Minami S, Murayama S, Yoshimori K, Nagayama S, Obata D, Higashiyama M, Masumoto A, Koretsune Y, Ito K, Terao C, Yamauchi T, Komuro I, Kadowaki T, Tamiya G, Yamamoto M, Nakamura Y, Kubo M, Murakami Y, Yamamoto K, Kamatani Y, Palotie A, Rivas MA, Daly MJ, Matsuda K, Okada Y · PubMed 34594039
Current genome-wide association studies do not yet capture sufficient diversity in populations and scope of phenotypes. To expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype genome-wide association studies (diseases, biomarkers and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining of electronic medical records. Meta-analyses with the UK Biobank and FinnGen (n = 628,000) identified ~5,000 new loci, which improved the resolution of the genomic map of human traits. This atlas elucidated the landscape of pleiotropy as represented by the major histocompatibility complex locus, where we conducted HLA fine-mapping. Finally, we performed statistical decomposition of matrices of phenome-wid
-
Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure - Unknown journal (n.d.) · Unknown authors · PubMed 36376295
ABSTRACT: Heart failure is a leading cause of cardiovascular morbidity and mortality. However, the contribution of common genetic variation to heart failure risk has not been fully elucidated, particularly in comparison to other common cardiometabolic traits. We report a multi-ancestry genome-wide association study meta-analysis of all-cause heart failure including up to 115,150 cases and 1,550,331 controls of diverse genetic ancestry, identifying 47 risk loci. We also perform multivariate genome-wide association studies that integrate heart failure with related cardiac magnetic resonance imaging endophenotypes, identifying 61 risk loci. Gene-prioritization analyses including colocalization and transcriptome-wide association studies identify known and previously unreported candidate cardio
-
Cross-ancestry genome-wide analysis of atrial fibrillation unveils disease biology and enables cardioembolic risk prediction - Unknown journal (n.d.) · Unknown authors · PubMed 36653681
ABSTRACT: Atrial fibrillation (AF) is a common cardiac arrhythmia resulting in increased risk of stroke. Despite highly heritable etiology, our understanding of the genetic architecture of AF remains incomplete. Here we performed a genome-wide association study in the Japanese population comprising 9,826 cases among 150,272 individuals and identified East Asian-specific rare variants associated with AF. A cross-ancestry meta-analysis of >1 million individuals, including 77,690 cases, identified 35 new susceptibility loci. Transcriptome-wide association analysis identified IL6R as a putative causal gene, suggesting the involvement of immune responses. Integrative analysis with ChIP-seq data and functional assessment using human induced pluripotent stem cell-derived cardiomyocytes demonstrat
-
Large-scale genome-wide association analyses identify novel genetic loci and mechanisms in hypertrophic cardiomyopathy - Unknown journal (n.d.) · Unknown authors · PubMed 39966646
ABSTRACT: Hypertrophic cardiomyopathy (HCM) is an important cause of morbidity and mortality with both monogenic and polygenic components. Here, we report results from a large genome-wide association study and multitrait analysis including 5,900 HCM cases, 68,359 controls and 36,083 UK Biobank participants with cardiac magnetic resonance imaging. We identified 70 loci (50 novel) associated with HCM and 62 loci (20 novel) associated with relevant left ventricular traits. Among the prioritized genes in the HCM loci, we identify a novel HCM disease gene, SVIL, which encodes the actin-binding protein supervillin, showing that rare truncating SVIL variants confer a roughly tenfold increased risk of HCM. Mendelian randomization analyses support a causal role of increased left ventricular contrac
-
Multi-Ethnic Genome-wide Association Study for Atrial Fibrillation - Unknown journal (n.d.) · Unknown authors · PubMed 29892015
ABSTRACT: Atrial fibrillation (AF) affects over 33 million individuals worldwide and has a complex heritability. We conducted the largest meta-analysis of genome-wide association studies for AF to date, consisting of over half a million individuals including 65,446 with AF. In total, we identified 97 loci significantly associated with AF including 67 of which were novel in a combined-ancestry analysis, and 3 in a European specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait loci (eQTL) analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate
Auto-generated from study metadata. AI-synthesised commentary is added when this entry is regenerated through content-service's LLM mode.
Lifestyle context
Concrete actions anchored to the cited research. We do not prescribe, we describe.
Lifestyle
-
atrial fibrillation modifiable risk factors Moderate
Standard AF prevention (blood pressure, weight, exercise, alcohol, sleep) becomes priority with genetic predisposition to atrial fibrillation
Target BP <130/80 mmHg, BMI 18.5-25, 150+ min exercise weekly, alcohol <2 drinks/day, screen for sleep apnea
Screening
-
atrial fibrillation screening baseline Moderate
rs113819537-C allele increases atrial fibrillation risk by 5% (p=7.00e-9, n=588,190) through effects on SSPN gene expression across cardiac tissues
Review ECG baseline and discuss periodic rhythm monitoring or screening strategy with cardiologist