Search

Brandon Tejada,1,2 Roby Joehanes,1,2 Shih-Jen Hwang,1,2 Tianxiao Huan,1– 3 Chen Yao,1,2 Jennifer E Ho,4 Daniel Levy1,2,5 1Framingham Heart Study, Framingham, MA, USA; 2Population Sciences Branch, National Heart, Lung, and Blood Institute, Bethesda, MD, USA; 3Ophthalmology and Visual Sciences, University of Massachusetts Medical School, Worcester, MA, USA; 4CardioVascular Institute and Division of Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, Unites States; 5Boston University School of Medicine, Boston, MA, USACorrespondence: Daniel Levy, Framingham Heart Study, 73 Mt. Wayte Avenue, Suite 2, Framingham, MA, 01702, USA, Email Levyd@nih.govPurpose: Assessing an individual’s systemic inflammatory state is vital to understand inflammation’s role in cardiometabolic diseases and identify those at the greatest risk of disease. We generated global inflammation scores and investigated their associations with cardiometabolic risk factors and adverse outcomes.Patients and Methods: Aggregate Inflammation Scores (AIS) and Principal Component Analysis (PCA) scores were generated for 7287 Framingham Heart Study participants using up to 26 inflammation-related proteins, with higher scores reflecting a pro-inflammatory milieu. Multivariable regression and proportional hazards analyses were conducted to investigate the associations of inflammation with cardiometabolic risk factors and outcomes. The primary outcomes for cross-sectional analyses included age, cigarette smoking, fasting lipid and glucose levels, blood pressure, body mass index (BMI), and hypertension, diabetes, and obesity. For prospective analyses, new-onset hypertension, diabetes, obesity, cardiovascular disease and all-cause mortality were investigated.Results: Higher inflammation scores were associated with smoking and older age, higher BMI, systolic blood pressure, lipids, and glucose levels, and with greater odds of hypertension and diabetes after adjusting for age, sex, cohort, and BMI (all p < 0.001). Higher baseline scores were associated with greater odds of new-onset hypertension after adjusting for traditional risk factors (OR [95% CI] per one standard deviation [1-SD] increase, AIS: 1.33 [1.21– 1.47], PCA score: 1.26 [1.12– 1.42], p < 0.001). The AIS also was associated with new-onset diabetes (1.32 [1.14– 1.52], p < 0.001). Proportional hazards analyses revealed greater risk of new-onset cardiovascular disease events and all-cause mortality (HR [95% CI] per 1-SD, AIS: 1.25 [1.14– 1.37] and 1.32 [1.23– 1.42], PCA score: 1.22 [1.13– 1.33] and 1.40 [1.31– 1.49], p < 0.001).Conclusion: Global inflammation scores encompassing an array of pro- and anti-inflammatory proteins and pathways may enhance risk assessment for cardiometabolic diseases. The AIS and PCA scores provide further opportunities to investigate the mechanisms of inflammation-related risk of disease.Keywords: inflammation scores, cardiovascular disease, heart failure, pathways

BackgroundExpression quantitative trait methylation (eQTM) analysis identifies DNA CpG sites at which methylation is associated with gene expression and may reveal molecular mechanisms of disease. The present study describes an eQTM resource of CpG-transcript pairs.MethodsDNA methylation was measured in blood samples from 1,045 Framingham Heart Study (FHS) participants using the Illumina 450K BeadChip and in 1,070 FHS participants using the Illumina EPIC array. Blood gene expression data were collected from all 2,115 participants using RNA sequencing (RNA-seq). The association between DNA methylation and gene expression was quantified for all cis (i.e., within 1Mb) and trans (>1Mb) CpG-transcript pairs. Significant results (pcis and trans) were subsequently tested for enrichment of biological pathways and of clinical traits.ResultsWe identified 70,047 significant cis CpG-transcript pairs where the top most significant eGenes (i.e., gene transcripts associated with a CpG) were enriched in biological pathways related to cell signaling, and for 1,208 clinical traits (enrichment false discovery rate [FDR] ≤ 0.05). We also identified 246,667 significant trans CpG-transcript pairs where the top most significant eGenes were enriched in biological pathways related to activation of the immune response, and for 1,191 clinical traits (enrichment FDR ≤ 0.05). Using significant cis CpG-transcript pairs, we identified significant mediation of the association between CpG sites and cardiometabolic traits through gene expression and identified shared genetic regulation between CpGs and transcripts associated with these cardiometabolic traits.ConclusionsWe developed a robust and powerful resource of eQTM CpG-transcript pairs that can help inform future functional studies that seek to understand the molecular basis of disease.