Association of Body Mass Index with DNA Methylation and Gene Expression in Blood Cells and Relations to Cardiometabolic Disease: A Mendelian Randomization Approach

Background The link between DNA methylation, obesity, and adiposity-related diseases in the general population remains uncertain. Methods and Findings We conducted an association study of body mass index (BMI) and differential methylation for over 400,000 CpGs assayed by microarray in whole-blood-derived DNA from 3,743 participants in the Framingham Heart Study and the Lothian Birth Cohorts, with independent replication in three external cohorts of 4,055 participants. We examined variations in whole blood gene expression and conducted Mendelian randomization analyses to investigate the functional and clinical relevance of the findings. We identified novel and previously reported BMI-related differential methylation at 83 CpGs that replicated across cohorts; BMI-related differential methylation was associated with concurrent changes in the expression of genes in lipid metabolism pathways. Genetic instrumental variable analysis of alterations in methylation at one of the 83 replicated CpGs, cg11024682 (intronic to sterol regulatory element binding transcription factor 1 [SREBF1]), demonstrated links to BMI, adiposity-related traits, and coronary artery disease. Independent genetic instruments for expression of SREBF1 supported the findings linking methylation to adiposity and cardiometabolic disease. Methylation at a substantial proportion (16 of 83) of the identified loci was found to be secondary to differences in BMI. However, the cross-sectional nature of the data limits definitive causal determination. Conclusions We present robust associations of BMI with differential DNA methylation at numerous loci in blood cells. BMI-related DNA methylation and gene expression provide mechanistic insights into the relationship between DNA methylation, obesity, and adiposity-related diseases

Integrated genome-wide association, coexpression network, and expression single nucleotide polymorphism analysis identifies novel pathway in allergic rhinitis

Background: Allergic rhinitis is a common disease whose genetic basis is incompletely explained. We report an integrated genomic analysis of allergic rhinitis. Methods: We performed genome wide association studies (GWAS) of allergic rhinitis in 5633 ethnically diverse North American subjects. Next, we profiled gene expression in disease-relevant tissue (peripheral blood CD4+ lymphocytes) collected from subjects who had been genotyped. We then integrated the GWAS and gene expression data using expression single nucleotide (eSNP), coexpression network, and pathway approaches to identify the biologic relevance of our GWAS. Results: GWAS revealed ethnicity-specific findings, with 4 genome-wide significant loci among Latinos and 1 genome-wide significant locus in the GWAS meta-analysis across ethnic groups. To identify biologic context for these results, we constructed a coexpression network to define modules of genes with similar patterns of CD4+ gene expression (coexpression modules) that could serve as constructs of broader gene expression. 6 of the 22 GWAS loci with P-value ≤ 1x10−6 tagged one particular coexpression module (4.0-fold enrichment, P-value 0.0029), and this module also had the greatest enrichment (3.4-fold enrichment, P-value 2.6 × 10−24) for allergic rhinitis-associated eSNPs (genetic variants associated with both gene expression and allergic rhinitis). The integrated GWAS, coexpression network, and eSNP results therefore supported this coexpression module as an allergic rhinitis module. Pathway analysis revealed that the module was enriched for mitochondrial pathways (8.6-fold enrichment, P-value 4.5 × 10−72). Conclusions: Our results highlight mitochondrial pathways as a target for further investigation of allergic rhinitis mechanism and treatment. Our integrated approach can be applied to provide biologic context for GWAS of other diseases

Association of body mass index with DNA methylation and gene expression in blood cells and relations to cardiometabolic disease: A Mendelian randomization approach

Background The link between DNA methylation, obesity, and adiposity-related diseases in the general population remains uncertain. Methods and Findings We conducted an association study of body mass index (BMI) and differential methylation for over 400,000 CpGs assayed by microarray in whole-blood-derived DNA from 3,743 participants in the Framingham Heart Study and the Lothian Birth Cohorts, with independent replication in three external cohorts of 4,055 participants. We examined variations in whole blood gene expression and conducted Mendelian randomization analyses to investigate the functional and clinical relevance of the findings. We identified novel and previously reported BMI-related differential methylation at 83 CpGs that replicated across cohorts; BMI-related differential methylation was associated with concurrent changes in the expression of genes in lipid metabolism pathways. Genetic instrumental variable analysis of alterations in methylation at one of the 83 replicated CpGs, cg11024682 (intronic to sterol regulatory element binding transcription factor 1 [SREBF1]), demonstrated links to BMI, adiposity-related traits, and coronary artery disease. Independent genetic instruments for expression of SREBF1 supported the findings linking methylation to adiposity and cardiometabolic disease. Methylation at a substantial proportion (16 of 83) of the identified loci was found to be secondary to differences in BMI. However, the cross-sectional nature of the data limits definitive causal determination. Conclusions We present robust associations of BMI with differential DNA methylation at numerous loci in blood cells. BMI-related DNA methylation and gene expression provide mechanistic insights into the relationship between DNA methylation, obesity, and adiposity-related diseases

Multi-Omics Approaches to Uncover Novel Regulators of Complex Disease

The dramatic decrease in sequencing and super-computing costs has enabled the generation of very large-scale datasets and the use of advanced algorithmic solutions applied to those datasets to achieve a better understanding of complex diseases. In this thesis, I integrate multiple modalities of data and apply rigorous statistical and mathematical modeling approaches to analyze these data and create data-driven hypotheses. I start with the exploration of the reproducibility of a commonly used modeling approach, probabilistic causal Bayesian networks, and then application of this modeling method to two complex diseases: Coronary Artery Disease (CAD) and food allergy. Using integrative approaches and a large CAD cohort, I detected downstream effects of GWAS genes via cis- and trans- eQTLs and identified a liver-specific regulatory sub-network that inversely affects plasma cholesterol and blood-glucose levels. Applying a similar framework to longitudinal measurements in peanut allergy patients with and without being challenged with peanut exposure, I found specific transcriptomic changes and highlighted novel regulators of the allergy response. This work emphasizes the importance of using integrative approaches to uncover novel regulators of complex human disease

Endothelial to mesenchymal transition is common in atherosclerotic lesions and is associated with plaque instability

Endothelial to mesenchymal transition (EndMT) plays a major role during development, and also contributes to several adult cardiovascular diseases. Importantly, mesenchymal cells including fibroblasts are prominent in atherosclerosis, with key functions including regulation of: inflammation, matrix and collagen production, and plaque structural integrity. However, little is known about the origins of atherosclerosis-associated fibroblasts. Here we show using endothelial-specific lineage-tracking that EndMT-derived fibroblast-like cells are common in atherosclerotic lesions, with EndMT-derived cells expressing a range of fibroblast-specific markers. In vitro modelling confirms that EndMT is driven by TGF-beta signalling, oxidative stress and hypoxia; all hallmarks of atherosclerosis. `Transitioning' cells are readily detected in human plaques co-expressing endothelial and fibroblast/mesenchymal proteins, indicative of EndMT. The extent of EndMT correlates with an unstable plaque phenotype, which appears driven by altered collagen-MMP production in EndMT-derived cells. We conclude that EndMT contributes to atherosclerotic patho-biology and is associated with complex plaques that may be related to clinical events.J.C.K. and this project were directly supported by National Institutes of Health (NIH) Grant K08HL111330. J.C.K. also acknowledges support from NIH R01HL130423, Fondation Leducq (Transatlantic Network of Excellence Award) and receives research support from AstraZeneca. K.C.M. and V.d'E. are supported by NIH T32HL007824. L.H. is supported by NIH K01HL103176. G.P. is supported by NIH R01GM114434, P30ES023515, U01HL107388, U2CES026561, U2CES026555 and an IBM faculty award. R.H. is supported by NIH R01HL117505, HL119046, HL129814, 128072, P50HL112324 and the Fondation Leducq (Transatlantic Network of Excellence Award). We acknowledge the assistance and technical expertise of the Microscopy, Genomics and Multiscale Biology, and Flow Cytometry Core Facilities and the Center for Comparative Medicine and Surgery of the Icahn School of Medicine at Mount Sinai.S

Integrative functional genomics identifies regulatory mechanisms at coronary artery disease loci

Coronary artery disease (CAD) is the leading cause of mortality and morbidity, driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies have identified 4150 loci associated with CAD and myocardial infarction susceptibility in humans. A majority of these variants reside in non-coding regions and are co-inherited with hundreds of candidate regulatory variants, presenting a challenge to elucidate their functions. Herein, we use integrative genomic, epigenomic and transcriptomic profiling of perturbed human coronary artery smooth muscle cells and tissues to begin to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps, we prioritize 64 candidate variants and perform allele-specific binding and expression analyses at seven top candidate loci: 9p21.3, SMAD3, PDGFD, IL6R, BMP1, CCDC97/TGFB1 and LMOD1. We validate our findings in expression quantitative trait loci cohorts, which together reveal new links between CAD associations and regulatory function in the appropriate disease context

Deciphering the transcriptional network of the dendritic cell lineage.

Although much progress has been made in the understanding of the ontogeny and function of dendritic cells (DCs), the transcriptional regulation of the lineage commitment and functional specialization of DCs in vivo remains poorly understood. We made a comprehensive comparative analysis of CD8(+), CD103(+), CD11b(+) and plasmacytoid DC subsets, as well as macrophage DC precursors and common DC precursors, across the entire immune system. Here we characterized candidate transcriptional activators involved in the commitment of myeloid progenitor cells to the DC lineage and predicted regulators of DC functional diversity in tissues. We identified a molecular signature that distinguished tissue DCs from macrophages. We also identified a transcriptional program expressed specifically during the steady-state migration of tissue DCs to the draining lymph nodes that may control tolerance to self tissue antigens