rs11979110 - KLF14 - LINC-PINT
Magnitude 2.2 · 3 studies on file
Reported associations
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Dyslipidaemia-Genotype Interactions with Nutrient Intake and Cerebro-Cardiovascular Disease - Unknown journal (n.d.) · Unknown authors · PubMed 35884923
ABSTRACT: A comprehensive understanding of gene-diet interactions is necessary to establish proper dietary guidelines to prevent and manage cardio-cerebrovascular disease (CCD). We investigated the role of genetic variants associated with dyslipidaemia (DL) and their interactions with macro-nutrients for cardiovascular disease using a large-scale genome-wide association study of Korean adults. A total of 58,701 participants from a Korean genome and epidemiology study were included. Their dietary intake was assessed using a food frequency questionnaire. Dyslipidaemia was defined as total cholesterol (TCHL) ≥ 240 mg/dL, high-density lipoprotein (HDL) < 40 mg/dL, low-density lipoprotein (LDL) ≥ 160 mg/dL, triglycerides (TG) ≥ 200 mg/dL, or dyslipidaemia history. Their nutrient intake wa
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High Blood Pressure and Intraocular Pressure: A Mendelian Randomization Study - Unknown journal (n.d.) · Unknown authors · PubMed 35762941
ABSTRACT: Purpose To test for causality with regard to the association between blood pressure (BP) and intraocular pressure (IOP) and glaucoma. Methods Single nucleotide polymorphisms (SNPs) associated with BP were identified in a genome-wide association study (GWAS) meta-analysis of 526,001 participants of European ancestry. These SNPs were used to assess the BP versus IOP relationship in a distinct sample (n = 70,832) whose corneal-compensated IOP (IOPcc) was measured. To evaluate the BP versus primary open-angle glaucoma (POAG) relationship, additional Mendelian randomization (MR) analyses were conducted using published GWAS summary statistics. Results Observational analysis revealed a linear relationship between BP traits and IOPcc, with a +0.28 mm Hg increase in IOPcc per 10-mm Hg inc
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Genome-wide characterization of circulating metabolic biomarkers - Unknown journal (n.d.) · Unknown authors · PubMed 38448586
ABSTRACT: Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases. Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associa
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