Multigene interactions and the prediction of depression in the Wisconsin Longitudinal Study

Objectives: Single genetic loci offer little predictive power for the identification of depression. This study examined whether an analysis of gene-gene (G x G) interactions of 78 single nucleotide polymorphisms (SNPs) in genes associated with depression and agerelated diseases would identify significant interactions with increased predictive power for depression. Design: A retrospective cohort study. Setting: A survey of participants in the Wisconsin Longitudinal Study. Participants: A total of 4811 persons (2464 women and 2347 men) who provided saliva for genotyping; the group comes from a randomly selected sample of Wisconsin high school graduates from the class of 1957 as well as a randomly selected sibling, almost all of whom are non-Hispanic white. Primary outcome measure: Depression as determine by the Composite International Diagnostic Interview-Short-Form. Results: Using a classification tree approach (recursive partitioning (RP)), the authors identified a number of candidate G 3 G interactions associated with depression. The primary SNP splits revealed by RP (ANKK1 rs1800497 (also known as DRD2 Taq1A) in men and DRD2 rs224592 in women) were found to be significant as single factors by logistic regression (LR) after controlling for multiple testing (p=0.001 for both). Without considering interaction effects, only one of the five subsequent RP splits reached nominal significance in LR (FTO rs1421085 in women, p=0.008). However, after controlling for G x G interactions by running LR on RP-specific subsets, every split became significant and grew larger in magnitude (OR (before) → (after): men: GNRH1 novel SNP: (1.43 → 1.57); women: APOC3 rs2854116: (1.28 → 1.55), ACVR2B rs3749386: (1.11 → 2.17), FTO rs1421085: (1.32 → 1.65), IL6 rs1800795: (1.12 → 1.85)). Conclusions: The results suggest that examining G x G interactions improves the identification of genetic associations predictive of depression. 4 of the SNPs identified in these interactions were located in two pathways well known to impact depression: neurotransmitter (ANKK1 and DRD2) and neuroendocrine (GNRH1 and ACVR2B) signalling. This study demonstrates the utility of RP analysis as an efficient and powerful exploratory analysis technique for uncovering genetic and molecular pathway interactions associated with disease aetiology

Serum 25-hydroxyvitamin D and risk of venous thromboembolism: the Atherosclerosis Risk in Communities (ARIC) Study

Some evidence suggests that an inadequate vitamin D level may increase the risk atherosclerotic cardiovascular disease. Whether low vitamin D has a role in venous thromboembolism (VTE), i.e., venous thrombosis and pulmonary embolism, is largely unexplored

Prospective study of sickle cell trait and venous thromboembolism incidence

Sickle cell trait may increase risk of venous thromboembolism, but this is not fully established

Carotid Intima-Media Thickness and Arterial Stiffness and the Risk of Atrial Fibrillation: The Atherosclerosis Risk in Communities (ARIC) Study, Multi-Ethnic Study of Atherosclerosis (MESA), and the Rotterdam Study

BACKGROUND: We evaluated the association of carotid intima‐media thickness (cIMT), carotid plaque, carotid distensibility coefficient (DC), and aortic pulse wave velocity (PWV) with incident atrial fibrillation (AF) and their role in improving AF risk prediction beyond the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)‐AF risk score. METHODS AND RESULTS: We analyzed data from 3 population‐based cohort studies: Atherosclerosis Risk in Communities (ARIC) Study (n=13 907); Multi‐Ethnic Study of Atherosclerosis (MESA; n=6640), and the Rotterdam Study (RS; n=5220). We evaluated the association of arterial indices with incident AF and computed the C‐statistic, category‐based net reclassification improvement (NRI), and relative integrated discrimination improvement (IDI) of incorporating arterial indices into the CHARGE‐AF risk score (age, race, height weight, systolic and diastolic blood pressure, antihypertensive medication use, smoking, diabetes, previous myocardial infarction, and previous heart failure). Higher cIMT (meta‐analyzed hazard ratio [95% CI] per 1‐SD increment, 1.12 [1.08–1.16]) and presence of carotid plaque (1.30 [1.19–1.42]) were associated with higher AF incidence after adjustment for CHARGE‐AF risk‐score variables. Lower DC and higher PWV were associated with higher AF incidence only after adjustment for the CHARGE‐AF risk‐score variables excepting height, weight, and systolic and diastolic blood pressure. Addition of cIMT or carotid plaque marginally improved CHARGE‐AF score prediction as assessed by the relative IDI (estimates, 0.025–0.051), but not when assessed with the C‐statistic and NRI. CONCLUSIONS: Higher cIMT, presence of carotid plaque, and greater arterial stiffness are associated with higher AF incidence, indicating that atherosclerosis and arterial stiffness play a role in AF etiopathogenesis. However, arterial indices only modestly improve AF risk prediction

Blood lipids and the incidence of atrial fibrillation: The multi-ethnic study of atherosclerosis and the framingham heart study

© 2014 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell. Background-Dyslipidemia is a major contributor to the development of atherosclerosis and coronary disease. Its role in the etiology of atrial fibrillation (AF) is uncertain. Methods and Results-We studied 7142 men and women from the Multi-Ethnic Study of Atherosclerosis (MESA) and the Framingham Heart Study who did not have prevalent AF at baseline and were not on lipid-lowering medications. Total cholesterol, high-density lipoprotein and low-density lipoprotein cholesterol, and triglycerides were measured using standard procedures. Incident AF during follow-up was identified from hospital discharge codes; review of medical charts; study electrocardiograms; and, in MESA only, Medicare claims. Multivariable Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals of AF by clinical categories of blood lipids in each cohort. Study-specific results were meta-analyzed using inverse of variance weighting. During 9.6 years of mean follow-up, 480 AF cases were identified. In a combined analysis of multivariable-adjusted results from both cohorts, high levels of high-density lipoprotein cholesterol were associated with lower AF risk (hazard ratio 0.64, 95% CI 0.48 to 0.87 in those with levels =60 mg/dL versus <40 mg/dL), whereas high triglycerides were associated with higher risk of AF (hazard ratio 1.60, 95% CI 1.25 to 2.05 in those with levels =200 mg/dL versus <150 mg/dL). Total cholesterol and low-density lipoprotein cholesterol were not associated with the risk of AF. Conclusion-In these 2 community-based cohorts, high-density lipoprotein cholesterol and triglycerides but not low-density lipoprotein cholesterol or total cholesterol were associated with the risk of AF, accounting for other cardiometabolic risk factors

Genetic Contributions of Inflammation to Depression

This paper describes the effects of immune genes genetic variants and mRNA expression on depression's risk, severity, and response to antidepressant treatment, through a systematic review on all papers published between 2000 and 2016. Our results, based largely on case–control studies, suggest that common genetic variants and gene-expression pathways are involved in both immune activation and depression. The most replicated and relevant genetic variants include polymorphisms in the genes for interleukin (IL)-1β, IL-6, IL-10, monocyte chemoattractant protein-1, tumor necrosis factor-alpha, C-reactive protein, and phospholipase A2. Moreover, increased blood cytokines mRNA expression (especially of IL-1β) identifies patients that are less likely to respond to conventional antidepressants. However, even for the most replicated findings there are inconsistent results, not only between studies, but also between the immune effects of the genetic variants and the resulting effects on depression. We find evidence that these discrepant findings may be explained, at least in part, by the heterogeneity of the depression immunophenotype, by environmental influences and gene × environment interactions, and by the complex interfacing of genetic variants with gene expression. Indeed, some of the most robust findings have been obtained in patients developing depression in the context of treatment with interferon-alpha, a widely used model to mimic depression in the context of inflammation. Further ‘omics' approaches, through GWAS and transcriptomics, will finally shed light on the interaction between immune genes, their expression, and the influence of the environment, in the pathogenesis of depression