68 research outputs found

    Improving Phenotypic Prediction by Combining Genetic and Epigenetic Associations

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    We tested whether DNA-methylation profiles account for inter-individual variation in body mass index (BMI) and height and whether they predict these phenotypes over and above genetic factors. Genetic predictors were derived from published summary results from the largest genome-wide association studies on BMI (n ∼ 350,000) and height (n ∼ 250,000) to date. We derived methylation predictors by estimating probe-trait effects in discovery samples and tested them in external samples. Methylation profiles associated with BMI in older individuals from the Lothian Birth Cohorts (LBCs, n = 1,366) explained 4.9% of the variation in BMI in Dutch adults from the LifeLines DEEP study (n = 750) but did not account for any BMI variation in adolescents from the Brisbane Systems Genetic Study (BSGS, n = 403). Methylation profiles based on the Dutch sample explained 4.9% and 3.6% of the variation in BMI in the LBCs and BSGS, respectively. Methylation profiles predicted BMI independently of genetic profiles in an additive manner: 7%, 8%, and 14% of variance of BMI in the LBCs were explained by the methylation predictor, the genetic predictor, and a model containing both, respectively. The corresponding percentages for LifeLines DEEP were 5%, 9%, and 13%, respectively, suggesting that the methylation profiles represent environmental effects. The differential effects of the BMI methylation profiles by age support previous observations of age modulation of genetic contributions. In contrast, methylation profiles accounted for almost no variation in height, consistent with a mainly genetic contribution to inter-individual variation. The BMI results suggest that combining genetic and epigenetic information might have greater utility for complex-trait prediction

    Classical Pathway of Complement Activation: Longitudinal Associations of C1q and C1-INH With Cardiovascular Outcomes: The CODAM Study (Cohort on Diabetes and Atherosclerosis Maastricht).

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    Objective—The classical complement pathway has been assigned both protective and pathological effects in cardiovascular disease (CVD), but human data are lacking. We determined the associations of the pattern recognition factor C1q and the regulator C1-INH with incident CVD, carotid intima–media thickness, endothelial dysfunction, and low-grade inflammation.Approach and Results—Baseline concentrations of C1q and C1-INH were measured in the CODAM study (Cohort on Diabetes and Atherosclerosis Maastricht; n=574; 61% men; age, 60±7 years). The 7-year incidence of CVD in participants free of CVD at baseline was evaluated using logistic regression analyses (n=342; 73 cases). The lowest incidence of CVD was observed in the middle tertile of C1q (Tlow compared with Tmiddle: odds ratio, 2.38 [95% confidence interval, 1.14–4.95]; Thigh compared with Tmiddle: odds ratio, 1.96 [95% confidence interval, 0.94–4.07]). C1-INH was not associated with CVD. During the 7-year follow-up period, C1q and C1-INH were not, or inconsistently, associated with carotid intima–media thickness or with biomarker scores reflecting endothelial dysfunction and low-grade inflammation.Conclusions—Our results suggest a nonlinear association between C1q and incident CVD. This supports the concept that early steps in classical pathway activation may have both protective and pathological effects on human CVD

    Classical Pathway of Complement Activation: Longitudinal Associations of C1q and C1-INH With Cardiovascular Outcomes: The CODAM Study (Cohort on Diabetes and Atherosclerosis Maastricht).

    No full text
    Objective—The classical complement pathway has been assigned both protective and pathological effects in cardiovascular disease (CVD), but human data are lacking. We determined the associations of the pattern recognition factor C1q and the regulator C1-INH with incident CVD, carotid intima–media thickness, endothelial dysfunction, and low-grade inflammation.Approach and Results—Baseline concentrations of C1q and C1-INH were measured in the CODAM study (Cohort on Diabetes and Atherosclerosis Maastricht; n=574; 61% men; age, 60±7 years). The 7-year incidence of CVD in participants free of CVD at baseline was evaluated using logistic regression analyses (n=342; 73 cases). The lowest incidence of CVD was observed in the middle tertile of C1q (Tlow compared with Tmiddle: odds ratio, 2.38 [95% confidence interval, 1.14–4.95]; Thigh compared with Tmiddle: odds ratio, 1.96 [95% confidence interval, 0.94–4.07]). C1-INH was not associated with CVD. During the 7-year follow-up period, C1q and C1-INH were not, or inconsistently, associated with carotid intima–media thickness or with biomarker scores reflecting endothelial dysfunction and low-grade inflammation.Conclusions—Our results suggest a nonlinear association between C1q and incident CVD. This supports the concept that early steps in classical pathway activation may have both protective and pathological effects on human CVD.<br/

    Assessing the Contribution of Relative Macrophage Frequencies to Subcutaneous Adipose Tissue

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    Background: Macrophages play an important role in regulating adipose tissue function, while their frequencies in adipose tissue vary between individuals. Adipose tissue infiltration by high frequencies of macrophages has been linked to changes in adipokine levels and low-grade inflammation, frequently associated with the progression of obesity. The objective of this project was to assess the contribution of relative macrophage frequencies to the overall subcutaneous adipose tissue gene expression using publicly available datasets. Methods: Seven publicly available microarray gene expression datasets from human subcutaneous adipose tissue biopsies (n = 519) were used together with TissueDecoder to determine the adipose tissue cell-type composition of each sample. We divided the subjects in four groups based on their relative macrophage frequencies. Differential gene expression analysis between the high and low relative macrophage frequencies groups was performed, adjusting for sex and study. Finally, biological processes were identified using pathway enrichment and network analysis. Results: We observed lower frequencies of adipocytes and higher frequencies of adipose stem cells in individuals characterized by high macrophage frequencies. We additionally studied whether, within subcutaneous adipose tissue, interindividual differences in the relative frequencies of macrophages were reflected in transcriptional differences in metabolic and inflammatory pathways. Adipose tissue of individuals with high macrophage frequencies had a higher expression of genes involved in complement activation, chemotaxis, focal adhesion, and oxidative stress. Similarly, we observed a lower expression of genes involved in lipid metabolism, fatty acid synthesis, and oxidation and mitochondrial respiration. Conclusion: We present an approach that combines publicly available subcutaneous adipose tissue gene expression datasets with a deconvolution algorithm to calculate subcutaneous adipose tissue cell-type composition. The results showed the expected increased inflammation gene expression profile accompanied by decreased gene expression in pathways related to lipid metabolism and mitochondrial respiration in subcutaneous adipose tissue in individuals characterized by high macrophage frequencies. This approach demonstrates the hidden strength of reusing publicly available data to gain cell-type-specific insights into adipose tissue function

    Traditional lifestyle factors partly mediate the association of socioeconomic position with intrahepatic lipid content:The Maastricht study

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    Background &amp; Aims: Recent studies have unveiled an association between socioeconomic position (SEP) and intrahepatic lipid (IHL) content. The aim of this study was to examine to what extent traditional lifestyle factors mediate the relationship between SEP and IHL content, independent of aetiology, and non-alcoholic fatty liver disease (NAFLD). Methods: We used cross-sectional data derived from The Maastricht Study (N = 4,001; mean age: 60 years, 49% women, 32% low education level, 21% diabetes, 21% NAFLD). Education, income, and occupation were used as indicators of SEP. Physical activity (accelerometer), intake of total energy, alcohol, saturated fat, protein, vitamin E, dietary fibre, and fructose from sugar-sweetened beverages (SSBs) and fruit juice (food frequency questionnaires) were potential mediators. IHL content was quantified by magnetic resonance imaging. Age, sex, and type 2 diabetes were covariates. Multiple parallel mediation analyses (bootstraps = 10,000) were performed. Results: Individuals with a low education level had a 1.056-fold higher IHL content (95% CI: 1.03–1.08) and a 44% greater NAFLD risk (OR:1.44; 95% CI:1.18–1.77) compared with those with higher education levels. Approximately 8.9% of educational disparity in risk of IHL content was attributable to moderate-to-vigorous physical activity; 6.3% to fructose intake from SSBs; 5.5% to dietary fibre; and -23% to alcohol. Approximately 8.7% of educational disparity in risk of NAFLD was attributable to moderate-to-vigorous physical activity; and 7.7% to fructose intake from SSBs. However, the indirect effect of these mediators was small (0.998 for IHL content and 1.045 for NAFLD) in comparison to the total effect. Similar results were found when income and occupation were used as SEP indicators. Conclusions: Societal measures may alleviate the burden of NAFLD and further studies that identify mediators other than traditional lifestyle factors are warranted to define the relationship underlying SEP and IHL content. Impact and implications: Individuals with a low or medium level of education, income, or occupational status had more fat accumulation in their livers than individuals with a higher education, income, or occupational status. This difference may be attributed to the influence of unhealthy lifestyle factors, such as reduced physical activity and a higher intake of sugar-sweetened beverages among individuals with lower socioeconomic position. Nevertheless, other yet unknown factors may also play a role
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