Expressive

rs10412048 - SMARCA4 - LDLR

Magnitude 2.2 · 8 studies on file

Reported associations

  • Metabolomic investigation of major depressive disorder identifies a potentially causal association with polyunsaturated fatty acids - Unknown journal (n.d.) · Unknown authors · PubMed 36764567

    ABSTRACT: Background: Metabolic differences have been reported between individuals with and without Major Depressive Disorder (MDD), but their consistency and causal relevance has been unclear. Methods: We conducted a metabolome-wide association study of MDD with 249 metabolomic measures available in UK Biobank (N = 29, 757). We then applied 2-sample bidirectional Mendelian Randomisation (MR) and colocalization analysis to identify potentially causal relationships between each metabolite and MDD. Results: One hundred and ninety-one metabolites tested were significantly associated with MDD (PFDR < 0.05), which reduced to 129 after adjustment for likely confounders. Lower abundance of Omega-3 fatty acid measures and a higher Omega-6: Omega-3 ratio showed potentially causal effects on liabili

  • Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation - Unknown journal (n.d.) · Unknown authors · PubMed 35213538

    ABSTRACT: Large-scale molecular profiling and genotyping provide a unique opportunity to systematically compare the genetically predicted effects of therapeutic targets on the human metabolome. We firstly constructed genetic risk scores for 8 drug targets on the basis that they primarily modify low-density lipoprotein (LDL) cholesterol (HMGCR, PCKS9, and NPC1L1), high-density lipoprotein (HDL) cholesterol (CETP), or triglycerides (APOC3, ANGPTL3, ANGPTL4, and LPL). Conducting mendelian randomisation (MR) provided strong evidence of an effect of drug-based genetic scores on coronary artery disease (CAD) risk with the exception of ANGPTL3. We then systematically estimated the effects of each score on 249 metabolic traits derived using blood samples from an unprecedented sample size of up to

  • Exploration of haplotype research consortium imputation for genome-wide association studies in 20,032 Generation Scotland participants - Unknown journal (n.d.) · Unknown authors · PubMed 28270201

    ABSTRACT: Background The Generation Scotland: Scottish Family Health Study (GS:SFHS) is a family-based population cohort with DNA, biological samples, socio-demographic, psychological and clinical data from approximately 24,000 adult volunteers across Scotland. Although data collection was cross-sectional, GS:SFHS became a prospective cohort due to of the ability to link to routine Electronic Health Record (EHR) data. Over 20,000 participants were selected for genotyping using a large genome-wide array. Methods GS:SFHS was analysed using genome-wide association studies (GWAS) to test the effects of a large spectrum of variants, imputed using the Haplotype Research Consortium (HRC) dataset, on medically relevant traits measured directly or obtained from EHRs. The HRC dataset is the largest

  • Multitrait genome association analysis identifies new susceptibility genes for human anthropometric variation in the GCAT cohort - Unknown journal (n.d.) · Unknown authors · PubMed 30166351

    ABSTRACT: Background Heritability estimates have revealed an important contribution of SNP variants for most common traits; however, SNP analysis by single-trait genome-wide association studies (GWAS) has failed to uncover their impact. In this study, we applied a multitrait GWAS approach to discover additional factor of the missing heritability of human anthropometric variation. Methods We analysed 205 traits, including diseases identified at baseline in the GCAT cohort (Genomes For Life- Cohort study of the Genomes of Catalonia) (n=4988), a Mediterranean adult population-based cohort study from the south of Europe. We estimated SNP heritability contribution and single-trait GWAS for all traits from 15 million SNP variants. Then, we applied a multitrait-related approach to study genome-

  • Blood metabolic biomarkers and colorectal cancer risk: results from large prospective cohort and Mendelian randomisation analyses - Unknown journal (n.d.) · Unknown authors · PubMed 40307439

    ABSTRACT: Background Emerging evidence suggests metabolic dysregulation may contribute to colorectal cancer (CRC) aetiology. We aimed to identify pre-diagnostic metabolic biomarkers for CRC risk in 230,420 UK Biobank participants. Methods Nuclear magnetic resonance spectroscopy was used to quantify 249 metabolic biomarkers in plasma samples collected at baseline. Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals (CIs) for associations of metabolic biomarkers with CRC risk after adjusting for potential confounders. To infer the potential causality of biomarkers that were associated with CRC independent of the others, we performed genome-wide association analyses among 199,732 UK Biobank participants of European ancestry to identify biomarker-as

  • Pleiotropic genetic architecture and novel loci for C-reactive protein levels - Unknown journal (n.d.) · Unknown authors · PubMed 36376304

    ABSTRACT: C-reactive protein is involved in a plethora of pathophysiological conditions. Many genetic loci associated with C-reactive protein are annotated to lipid and glucose metabolism genes supporting common biological pathways between inflammation and metabolic traits. To identify novel pleiotropic loci, we perform multi-trait analysis of genome-wide association studies on C-reactive protein levels along with cardiometabolic traits, followed by a series of in silico analyses including colocalization, phenome-wide association studies and Mendelian randomization. We find 41 novel loci and 19 gene sets associated with C-reactive protein with various pleiotropic effects. Additionally, 41 variants colocalize between C-reactive protein and cardiometabolic risk factors and 12 of them display

  • The genetics of a "femaleness/maleness" score in cardiometabolic traits in the UK biobank - Unknown journal (n.d.) · Unknown authors · PubMed 37277458

    ABSTRACT: We recently devised continuous "sex-scores" that sum up multiple quantitative traits, weighted by their respective sex-difference effect sizes, as an approach to estimating polyphenotypic "maleness/femaleness" within each binary sex. To identify the genetic architecture underlying these sex-scores, we conducted sex-specific genome-wide association studies (GWASs) in the UK Biobank cohort (females: n = 161,906; males: n = 141,980). As a control, we also conducted GWASs of sex-specific "sum-scores", simply aggregating the same traits, without weighting by sex differences. Among GWAS-identified genes, while sum-score genes were enriched for genes differentially expressed in the liver in both sexes, sex-score genes were enriched for genes differentially expressed

  • 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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