21 research outputs found
DNA methylation signatures associated with cardiometabolic risk factors in children from India and The Gambia: results from the EMPHASIS study.
BACKGROUND: The prevalence of cardiometabolic disease (CMD) is rising globally, with environmentally induced epigenetic changes suggested to play a role. Few studies have investigated epigenetic associations with CMD risk factors in children from low- and middle-income countries. We sought to identify associations between DNA methylation (DNAm) and CMD risk factors in children from India and The Gambia. RESULTS: Using the Illumina Infinium HumanMethylation 850 K Beadchip array, we interrogated DNAm in 293 Gambian (7-9 years) and 698 Indian (5-7 years) children. We identified differentially methylated CpGs (dmCpGs) associated with systolic blood pressure, fasting insulin, triglycerides and LDL-Cholesterol in the Gambian children; and with insulin sensitivity, insulinogenic index and HDL-Cholesterol in the Indian children. There was no overlap of the dmCpGs between the cohorts. Meta-analysis identified dmCpGs associated with insulin secretion and pulse pressure that were different from cohort-specific dmCpGs. Several differentially methylated regions were associated with diastolic blood pressure, insulin sensitivity and fasting glucose, but these did not overlap with the dmCpGs. We identified significant cis-methQTLs at three LDL-Cholesterol-associated dmCpGs in Gambians; however, methylation did not mediate genotype effects on the CMD outcomes. CONCLUSION: This study identified cardiometabolic biomarkers associated with differential DNAm in Indian and Gambian children. Most associations were cohort specific, potentially reflecting environmental and ethnic differences
Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care
Genetic drivers of heterogeneity in type 2 diabetes pathophysiology
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p
SWI/SNF Infobase-An exclusive information portal for SWI/SNF remodeling complex subunits.
Chromatin remodeling complexes facilitate the access of condensed genomic DNA during transcription, replication, and repair, by altering the histone-DNA contacts in the nucleosome structures. SWI/SNF (SWItch/Sucrose Non-Fermentable) family of ATP dependent chromatin remodeling complexes have been documented for their tumour suppressor function. Recent studies have reported the high frequency of cancer causing mutations in this protein family. There exist multiple subunits for this complex and can form context-dependent sub-complexes. The cataloguing of individual subunits of this complex is essential for understanding their specific functions and their mechanism of action during chromatin remodeling. This would also facilitate further studies to characterize cancer causing mutations in SWI/SNF subunits. In the current study, a database containing information on the subunits of SWI/SNF-α (BRG1/BRM-Associated Factors (BAF)) and SWI/SNF-β (Polybromo-Associated BAF (PBAF)) sub classes of SWI/SNF family has been curated and catalogued. The database hosts information on 27 distinct SWI/SNF subunits from 20 organisms spanning a wide evolutionary range of eukaryotes. A non-redundant set of 522 genes coding for SWI/SNF subunits have been documented in the database. A detailed annotation on each subunit, including basic protein/gene information, protein sequence, functional domains, homologs and missense mutations of human proteins have been provided with a user-friendly graphical interface. The SWI/SNF Infobase presented here, would be a first of its kind exclusive information portal on SWI/SNF complex subunits and would be a valuable resource for the research community working on chromatin remodeling. The database is available at http://scbt.sastra.edu/swisnfdb/index.php
Summary statistics of Pfam domains and missense mutations in SWI/SNF subunits.
<p>(A) The frequency of Pfam domains found in the human BAF and PBAF complex assembly. (B) % of cancer associated missense mutation sites in human SWI/SNF subunits according to COSMIC database. (C) % distribution of the SWI/SNF subunit missense mutations in different primary tissue types.</p
SWI/SNF subunit details from organisms, human, mouse, fruit fly, round worm, and yeast.
<p>SWI/SNF subunit details from organisms, human, mouse, fruit fly, round worm, and yeast.</p
Snapshot of the SWI/SNF Infobase features.
<p>(A) The graphical interface of SWI/SNF Infobase (selection option for organism is highlighted). (B) The search page of SWI/SNF Infobase (C) Detailed subunit information provided upon the selection of the ATPase, BRG1 from <i>Homo sapiens</i> (option to list missense mutation information based on primary tissue has been highlighted).</p
In silico screening of cancer-associated mutations in the HSA domain of BRG1 and its role in affecting the Arp-HSA sub-complex of SWI/SNF
DNA methylation at the suppressor of cytokine signaling 3 (SOCS3) gene influences height in childhood
Recommended from our members
DNA methylation at the suppressor of cytokine signaling 3 ( SOCS3 ) gene influences height in childhood
Human height is strongly influenced by genetics but the contribution of modifiable epigenetic factors is under-explored, particularly in low and middle-income countries (LMIC). We investigate links between blood DNA methylation and child height in four LMIC cohorts (n = 1927) and identify a robust association at three CpGs in the suppressor of cytokine signaling 3 (SOCS3) gene which replicates in a high-income country cohort (n = 879). SOCS3 methylation (SOCS3m)—height associations are independent of genetic effects. Mendelian randomization analysis confirms a causal effect of SOCS3m on height. In longitudinal analysis, SOCS3m explains a maximum 9.5% of height variance in mid-childhood while the variance explained by height polygenic risk score increases from birth to 21 years. Children’s SOCS3m is associated with prenatal maternal folate and socio-economic status. In-vitro characterization confirms a regulatory effect of SOCS3m on gene expression. Our findings suggest epigenetic modifications may play an important role in driving child height in LMIC