352 research outputs found

    Genome-wide associations for birth weight and correlations with adult disease

    Get PDF
    Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P\textit{P}  < 5 × 108^{-8}). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (R\textit{R}g_{g} = -0.22, P\textit{P}  = 5.5 × 1013^{-13}), T2D (R\textit{R}g_{g} = -0.27, P\textit{P}  = 1.1 × 106^{-6}) and coronary artery disease (R\textit{R}g_{g} = -0.30, P\textit{P}  = 6.5 × 109^{-9}). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P\textit{P} = 1.9 × 104^{-4}). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.For a full list of the funders pelase visit the publisher's website and look at the supplemetary material provided. Some of the funders are: British Heart Foundation, Cancer Research UK, Medical Research Council, National Institutes of Health, Royal Society and Wellcome Trust

    Genome-wide associations for birth weight and correlations with adult disease

    Get PDF
    Birth weight (BW) is influenced by both foetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease1. These lifecourse associations have often been attributed to the impact of an adverse early life environment. We performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where foetal genotype was associated with BW (P <5x10-8). Overall, ˜15% of variance in BW could be captured by assays of foetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (rg-0.22, P =5.5x10-13), T2D (rg-0.27, P =1.1x10-6) and coronary artery disease (rg-0.30, P =6.5x10-9) and, in large cohort data sets, demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P =1.9x10-4). We have demonstrated that lifecourse associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and have highlighted some of the pathways through which these causal genetic effects are mediated

    The trans-ancestral genomic architecture of glycemic traits

    Get PDF
    Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

    The trans-ancestral genomic architecture of glycemic traits

    Get PDF
    Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets

    Latin American Trans-ancestry INitiative for OCD genomics (LATINO): Study protocol

    Get PDF
    Obsessive-compulsive disorder (OCD) is a debilitating psychiatric disorder. Worldwide, its prevalence is ~2% and its etiology is mostly unknown. Identifying biological factors contributing to OCD will elucidate underlying mechanisms and might contribute to improved treatment outcomes. Genomic studies of OCD are beginning to reveal long-sought risk loci, but \u3e95% of the cases currently in analysis are of homogenous European ancestry. If not addressed, this Eurocentric bias will result in OCD genomic findings being more accurate for individuals of European ancestry than other ancestries, thereby contributing to health disparities in potential future applications of genomics. In this study protocol paper, we describe the Latin American Trans-ancestry INitiative for OCD genomics (LATINO, https://www.latinostudy.org). LATINO is a new network of investigators from across Latin America, the United States, and Canada who have begun to collect DNA and clinical data from 5000 richly phenotyped OCD cases of Latin American ancestry in a culturally sensitive and ethical manner. In this project, we will utilize trans-ancestry genomic analyses to accelerate the identification of OCD risk loci, fine-map putative causal variants, and improve the performance of polygenic risk scores in diverse populations. We will also capitalize on rich clinical data to examine the genetics of treatment response, biologically plausible OCD subtypes, and symptom dimensions. Additionally, LATINO will help elucidate the diversity of the clinical presentations of OCD across cultures through various trainings developed and offered in collaboration with Latin American investigators. We believe this study will advance the important goal of global mental health discovery and equity

    Variable outcomes of human heart attack recapitulated in genetically diverse mice.

    Get PDF
    Clinical variation in patient responses to myocardial infarction (MI) has been difficult to model in laboratory animals. To assess the genetic basis of variation in outcomes after heart attack, we characterized responses to acute MI in the Collaborative Cross (CC), a multi-parental panel of genetically diverse mouse strains. Striking differences in post-MI functional, morphological, and myocardial scar features were detected across 32 CC founder and recombinant inbred strains. Transcriptomic analyses revealed a plausible link between increased intrinsic cardiac oxidative phosphorylation levels and MI-induced heart failure. The emergence of significant quantitative trait loci for several post-MI traits indicates that utilizing CC strains is a valid approach for gene network discovery in cardiovascular disease, enabling more accurate clinical risk assessment and prediction

    Variable outcomes of human heart attack recapitulated in genetically diverse mice

    Get PDF
    Clinical variation in patient responses to myocardial infarction (MI) has been difficult to model in laboratory animals. To assess the genetic basis of variation in outcomes after heart attack, we characterized responses to acute MI in the Collaborative Cross (CC), a multi-parental panel of genetically diverse mouse strains. Striking differences in post-MI functional, morphological, and myocardial scar features were detected across 32 CC founder and recombinant inbred strains. Transcriptomic analyses revealed a plausible link between increased intrinsic cardiac oxidative phosphorylation levels and MI-induced heart failure. The emergence of significant quantitative trait loci for several post-MI traits indicates that utilizing CC strains is a valid approach for gene network discovery in cardiovascular disease, enabling more accurate clinical risk assessment and prediction

    Profiling of DNA Methylation and Single Nucleotide Polymorphism for Diagnosis, Prognosis and Targeting DNA Methyltransferases for Therapeutic Intervention of Breast Cancer

    Get PDF
    Breast cancer being multifaceted disease constitutes a wide spectrum of histological and molecular variability in tumors. Now, in the wake-up of the Human Genome Project (HGP) several evidences recommend a marked plasticity adopted by tumor cells in modulating the tissue invasion and progression during multiple stages of metastasis. However, the task for the identification of these casualties in a cancer genome is complicated by the interplay of inherited genetic and epigenetic aberrations. These aberrations are like two sides of the same coin. Therefore, in this thesis we provide an extrapolate outlook to the sinister partnership between genetic and epigenetic aberrations in relevance to breast cancer. DNA methylation is a prototypical epigenetic parameter that lay ground in understanding the gene regulation and their intricate interactions in the normal and diseased state. However, when it is comprehended by the extensive study of the genomicand transcriptomic parameter, it leads to better understanding of complex traitarchitecture of disease aetiology. The key to our analysis holds in identification of effective model that enables in predicting the phenotypic traits and outcomes, elucidating the presence of diagnostic and prognostic biomarkers and generate an insight into genetic underpinnings of heritable complex traits. In view of this, we explored the emerging approaches based upon data integration and meta-dimensional analysis to deepen our understanding to the relationship between the genomic variations and human phenotypes. This integrated study comprised of Illumina 450 DNA methylation, Affymetrix SNP array and RNAseq dataset retrieved from the Cancer genome atlas (TCGA) portal which elaborated the biological and complex outlay in the diagnosis, prognosis and therapeutic implications of breast cancer
    corecore