rs1112718 - Y_RNA - EXOC6

Magnitude 2.2 · 7 studies on file

Reported associations

• Genome-wide association study of medication-use and associated disease in the UK Biobank - Unknown journal (n.d.) · Unknown authors · PubMed 31015401

  ABSTRACT: Genome-wide association studies (GWASs) of medication use may contribute to understanding of disease etiology, could generate new leads relevant for drug discovery and can be used to quantify future risk of medication taking. Here, we conduct GWASs of self-reported medication use from 23 medication categories in approximately 320,000 individuals from the UK Biobank. A total of 505 independent genetic loci that meet stringent criteria (P < 10−8/23) for statistical significance are identified. We investigate the implications of these GWAS findings in relation to biological mechanism, potential drug target identification and genetic risk stratification of disease. Amongst the medication-associated genes are 16 known therapeutic-effect target genes for medications from 9 cat

• Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation - Unknown journal (n.d.) · Unknown authors · PubMed 35551307

  ABSTRACT: We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 cases and 1,159,055 controls (48.9% non-European descent) through the DIAMANTE (DIAbetes Meta-ANalysis of Trans-Ethnic association studies) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 x 10−9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular me

• Multiple Sclerosis Genomic Map implicates peripheral immune cells & microglia in susceptibility - Unknown journal (n.d.) · Unknown authors · PubMed 31604244

  ABSTRACT: We analyzed genetic data of 47,429 multiple sclerosis (MS) and 68,374 control subjects and establish a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 within the extended MHC. We used an ensemble of methods to prioritize 551 putative susceptibility genes, that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we observe enrichment for MS genes in these brain-resident immune cells, suggesting that these may have a role in targeting an autoimmune process to the central nervous system, although MS is most likely initially triggere

• Fine-mapping of an expanded set of type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps - Unknown journal (n.d.) · Unknown authors · PubMed 30297969

  ABSTRACT: We aggregated genome-wide genotyping data from 32 European-descent GWAS (74,124 T2D cases, 824,006 controls) imputed to high-density reference panels of >30,000 sequenced haplotypes. Analysis of ˜27M variants (˜21M with minor allele frequency [MAF]<5%), identified 243 genome-wide significant loci (p<5x10-8; MAF 0.02%-50%; odds ratio [OR] 1.04-8.05), 135 not previously-implicated in T2D-predisposition. Conditional analyses revealed 160 additional distinct association signals (p<10-5) within the identified loci. The combined set of 403 T2D-risk signals includes 56 low-frequency (0.5%≤MAF<5%) and 24 rare (MAF<0.5%) index SNPs at 60 loci, including 14 with estimated allelic OR>2. Forty-one of the signals displayed effect-size heterogeneity between BMI-unadjusted and adjusted anal

• Identification of genetic effects underlying type 2 diabetes in South Asian and European populations - Unknown journal (n.d.) · Unknown authors · PubMed 35393509

  ABSTRACT: South Asians are at high risk of developing type 2 diabetes (T2D). We carried out a genome-wide association meta-analysis with South Asian T2D cases (n = 16,677) and controls (n = 33,856), followed by combined analyses with Europeans (neff = 231,420). We identify 21 novel genetic loci for significant association with T2D (P = 4.7 × 10−8 to 5.2 × 10−12), to the best of our knowledge at the point of analysis. The loci are enriched for regulatory features, including DNA methylation and gene expression in relevant tissues, and highlight CHMP4B, PDHB, LRIG1 and other genes linked to adiposity and glucose metabolism. A polygenic risk score based on South Asian-derived summary statistics shows ~4-fold higher risk for T2D between the top and bottom quartile.

• The phenotypic and genetic association between endometriosis and immunological diseases - Unknown journal (n.d.) · Unknown authors · PubMed 40262193

  ABSTRACT: Abstract STUDY QUESTION Is there an increased risk of immunological diseases among endometriosis patients, and does a shared genetic basis contribute to this risk? SUMMARY ANSWER Endometriosis patients show a significantly increased risk of autoimmune, autoinflammatory, and mixed-pattern diseases, including rheumatoid arthritis, multiple sclerosis, coeliac disease, osteoarthritis, and psoriasis, with genetic correlations between endometriosis and osteoarthritis, rheumatoid arthritis, and multiple sclerosis, and a potential causal link to rheumatoid arthritis. WHAT IS KNOWN ALREADY The epidemiological evidence for an increased risk of immunological diseases among women with endometriosis is limited in scope and has varied in robustness due to the opportunity for biases. The presen

• Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors - Unknown journal (n.d.) · Unknown authors · PubMed 31043758

  ABSTRACT: Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n=321,223) and offspring birth weight (n=230,069 mothers), we identified 190 independent association signals (129 novel). We used structural equation modelling to decompose the contributions of direct fetal and indirect maternal genetic effects, and then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth we

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