Characteristics of the Rotterdam Study (RS).

<p>Characteristics of the Rotterdam Study (RS).</p

Association between survival and individual ROH regions.

<p>Cox proportional hazard regression adjusted for sex and age at baseline; *p<0.05; Freq-frequency; HR-hazard ratio; CI-confidence interval.</p

Genome-wide association studies of cardiometabolic phenotypes and inflammation.

<p>Abbreviations: BMI, body mass index; CAD, coronary artery disease; CARDIoGRAMplusC4D, Coronary Artery Disease Genome-wide Replication and Meta-Analysis plus Coronary Artery Disease Genetics Consortium; CHARGE, Cohorts for Heart and Aging Research in Genomic Epidemiology; CRP, c-reactive protein; DBP, diastolic blood pressure; DIAGRAM, DIAbetes Genetics Replication And Meta-analysis; FG, fasting glucose; FI, fasting insulin; GIANT, Genetic Investigation of ANthropometric Traits; GLGC, Global Lipids Genetic Consortium; HDLC, HDL-cholesterol; ICBP, International Consortium for Blood Pressure; LDLC, LDL-cholesterol; MAGIC, Meta-Analyses of Glucose and Insulin-related traits Consortium; SBP, systolic blood pressure; T2D, type 2 diabetes; TC, total cholesterol; TG, triglycerides.</p><p>Genome-wide association studies of cardiometabolic phenotypes and inflammation.</p

Biological and mediated pleiotropy of overlapping loci among inflammation and cardiometabolic phenotypes.

<p>Overlapping loci among inflammation and cardiometabolic phenotypes and type of pleiotropy according to the additional analyses. We identified six overlapping loci with mediated pleiotropic effects on CRP (left) and seven with a biological pleiotropic effect (right).</p

Quantile-quantile plots of CRP SNPs in cardiometabolic GWAS.

<p>QQ-plots were used to evaluate whether SNPs that are genome-wide significant associated with CRP, were in the cardiometabolic GWAS distributed differently from what is expected under the null-hypothesis. The observed p-values (dotted line) for the phenotypes HDL-cholesterol, fasting glucose, type 2 diabetes and coronary artery disease deviated significantly leftwards indicating that these p-values are smaller than expected under null hypothesis.</p

The association of known loci for cardiometabolic traits with serum CRP.

<p>^a Effect represents 1-unit change in the natural log-transformed CRP (mg/L) per copy increase in the risk allele. SE, standard error.</p><p>^b A1 and A2 represent respectively the risk allele and non-risk allele.</p><p>^c Top-SNP represents the SNP with the lowest p-value in the genomic region in the CRP meta-analysis. If the top-SNP is “The same”, the top SNP for the cardiometabolic traits is the same as the SNP with the lowest p-value in the CRP meta-analysis.</p><p><i>Note</i>: p-value ≤ 1.1×10^-4 is considered as study-wide significant (0.05/463)</p><p>Abbreviations: BMI, body mass index; CAD, coronary artery disease; FG, fasting glucose; FI, fasting insulin; HDLC, high-density lipoprotein cholesterol; LDL, low-density lipoprotein cholesterol; T2D, type 2 diabetes; TC, total cholesterol; TG, triglycerides.</p><p>The association of known loci for cardiometabolic traits with serum CRP.</p

Quantile-quantile plot of cardiometabolic SNPs in CRP GWAS.

<p>QQ-plot was used to evaluate whether SNPs that are genome-wide significant associated with the cardiometabolic phenotypes, were in the CRP GWAS distributed differently from what is expected under the null-hypothesis. The observed p-values (dotted line) for the phenotypes deviated significantly leftwards indicating that these p-values are smaller than expected under null hypothesis.</p

Pleiotropic SNPs and their association with CRP.

<p>^a Model 1: adjusted for age</p><p>^b Model 2: additionally adjusted for BMI, HDL-cholesterol, LDL-cholesterol, triglycerides, total cholesterol and HbA1C</p><p>^c B: biological pleiotropy; M: mediated pleiotropy.</p><p>Pleiotropic SNPs and their association with CRP.</p

P-values for the associations of the 18 CRP SNPs with different cardiometabolic phenotypes.

<p>P-values for the associations between the 18 CRP SNPs and BMI, lipids, glycemic phenotypes, SBP and coronary artery disease. The genes on the x-axis represent the genes in which the CRP SNPs are located or closest by. The numbers on the y-axis indicate the p-values of the association between the SNPs and the cardiometabolic phenotypes. Significant associations are colored as depicted in the figure legend. For BMI and SBP, no significant associations were observed. CAD, coronary artery disease; FG, fasting glucose; FI, fasting insulin; HDLC, HDL-cholesterol; LDLC, LDL-cholesterol; T2D, type 2 diabetes; TC, total cholesterol; TG, Triglycerides.</p

Methylation of Migraine-Related Genes in Different Tissues of the Rat

<div><p>17ß-Estradiol, an epigenetic modulator, is involved in the increased prevalence of migraine in women. Together with the prophylactic efficacy of valproate, which influences DNA methylation and histone modification, this points to the involvement of epigenetic mechanisms. Epigenetic studies are often performed on leukocytes, but it is unclear to what extent methylation is similar in other tissues. Therefore, we investigated methylation of migraine-related genes that might be epigenetically regulated (CGRP-ergic pathway, estrogen receptors, endothelial NOS, as well as MTHFR) in different migraine-related tissues and compared this to methylation in rat as well as human leukocytes. Further, we studied whether 17ß-estradiol has a prominent role in methylation of these genes. Female rats (n = 35) were ovariectomized or sham-operated and treated with 17β-estradiol or placebo. DNA was isolated and methylation was assessed through bisulphite treatment and mass spectrometry. Human methylation data were obtained using the Illumina 450k genome-wide methylation array in 395 female subjects from a population-based cohort study. We showed that methylation of the <i>Crcp</i>, <i>Calcrl</i>, <i>Esr1</i> and <i>Nos3</i> genes is tissue-specific and that methylation in leukocytes was not correlated to that in other tissues. Interestingly, the interindividual variation in methylation differed considerably between genes and tissues. Furthermore we showed that methylation in human leukocytes was similar to that in rat leukocytes in our genes of interest, suggesting that rat may be a good model to study human DNA methylation in tissues that are difficult to obtain. In none of the genes a significant effect of estradiol treatment was observed.</p></div