T cells are the most common immune cells in atherosclerotic plaques, and the function of T cells can be altered by fatty acids. Here, we show that pre-exposure of CD4+ T cells to oleic acid, an... Show moreT cells are the most common immune cells in atherosclerotic plaques, and the function of T cells can be altered by fatty acids. Here, we show that pre-exposure of CD4+ T cells to oleic acid, an abundant fatty acid linked to cardiovascular events, upregulates core metabolic pathways and promotes differentiation into interleukin-9 (IL-9)-producing cells upon activation. RNA sequencing of non-activated T cells reveals that oleic acid upregulates genes encoding key enzymes responsible for cholesterol and fatty acid biosynthesis. Transcription footprint analysis links these expression changes to the differentiation toward TH9 cells, a pro-atherogenic subset. Spectral flow cytometry shows that pre-exposure to oleic acid results in a skew toward IL-9+-producing T cells upon activation. Importantly, pharmacological inhibition of either cholesterol or fatty acid biosynthesis abolishes this effect, suggesting a beneficial role for statins beyond cholesterol lowering. Taken together, oleic acid may affect inflammatory diseases like atherosclerosis by rewiring T cell metabolism. Show less
Background Dietary intake of n-3 polyunsaturated fatty acids (PUFA) may have a protective effect on the development of cardiovascular diseases, diabetes, depression and cancer, while a high intake... Show moreBackground Dietary intake of n-3 polyunsaturated fatty acids (PUFA) may have a protective effect on the development of cardiovascular diseases, diabetes, depression and cancer, while a high intake of n-6 PUFA was often reported to be associated with inflammation-related traits. The effect of PUFAs on health outcomes might be mediated by DNA methylation (DNAm). The aim of our study is to identify the impact of PUFA intake on DNAm in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 cohort and the Leiden Longevity Study (LLS). Results DNA methylation levels were measured in whole blood from the population-based KORA FF4 study (N = 1354) and LLS (N = 448), using the Illumina MethylationEPIC BeadChip and Illumina HumanMethylation450 array, respectively. We assessed associations between DNAm and intake of eight and four PUFAs in KORA and LLS, respectively. Where possible, results were meta-analyzed.Below the Bonferroni correction threshold (p < 7.17 x 10(-8)), we identified two differentially methylated positions (DMPs) associated with PUFA intake in the KORA study. The DMP cg19937480, annotated to gene PRDX1, was positively associated with docosahexaenoic acid (DHA) in model 1 (beta: 2.00 x 10(-5), 95%CI: 1.28 x 10(-5)-2.73 x 10(-5), P value: 6.98 x 10(-8)), while cg05041783, annotated to gene MARK2, was positively associated with docosapentaenoic acid (DPA) in our fully adjusted model (beta: 9.80 x 10(-5), 95%CI: 6.25 x 10(-5)-1.33 x 10(-4), P value: 6.75 x 10(-8)). In the meta-analysis, we identified the CpG site (cg15951061), annotated to gene CDCA7L below Bonferroni correction (1.23 x 10(-7)) associated with eicosapentaenoic acid (EPA) intake in model 1 (beta: 2.00 x 10(-5), 95% CI: 1.27 x 10(-5)-2.73 x 10(-5), P value = 5.99 x 10(-8)) and we confirmed the association of cg19937480 with DHA in both models 1 and 2 (beta: 2.07 x 10(-5), 95% CI: 1.31 x 10(-5)-2.83 x 10(-5), P value = 1.00 x 10(-7) and beta: 2.19 x 10(-5), 95% CI: 1.41 x 10(-5)-2.97 x 10(-5), P value = 5.91 x 10(-8) respectively).Conclusions Our study identified three CpG sites associated with PUFA intake. The mechanisms of these sites remain largely unexplored, highlighting the novelty of our findings. Further research is essential to understand the links between CpG site methylation and PUFA outcomes. Show less
BackgroundB vitamins such as folate (B9), B6, and B12 are key in one carbon metabolism, which generates methyl donors for DNA methylation. Several studies have linked differential methylation to... Show moreBackgroundB vitamins such as folate (B9), B6, and B12 are key in one carbon metabolism, which generates methyl donors for DNA methylation. Several studies have linked differential methylation to self-reported intakes of folate and B12, but these estimates can be imprecise, while metabolomic biomarkers can offer an objective assessment of dietary intakes. We explored blood metabolomic biomarkers of folate and vitamins B6 and B12, to carry out epigenome-wide analyses across up to three European cohorts. Associations between self-reported habitual daily B vitamin intakes and 756 metabolites (Metabolon Inc.) were assessed in serum samples from 1064 UK participants from the TwinsUK cohort. The identified B vitamin metabolomic biomarkers were then used in epigenome-wide association tests with fasting blood DNA methylation levels at 430,768 sites from the Infinium HumanMethylation450 BeadChip in blood samples from 2182 European participants from the TwinsUK and KORA cohorts. Candidate signals were explored for metabolite associations with gene expression levels in a subset of the TwinsUK sample (n = 297). Metabolomic biomarker epigenetic associations were also compared with epigenetic associations of self-reported habitual B vitamin intakes in samples from 2294 European participants.ResultsEighteen metabolites were associated with B vitamin intakes after correction for multiple testing (Bonferroni-adj. p < 0.05), of which 7 metabolites were available in both cohorts and tested for epigenome-wide association. Three metabolites — pipecolate (metabolomic biomarker of B6 and folate intakes), pyridoxate (marker of B6 and folate) and docosahexaenoate (DHA, marker of B6) — were associated with 10, 3 and 1 differentially methylated positions (DMPs), respectively. The strongest association was observed between DHA and DMP cg03440556 in the SCD gene (effect = 0.093 ± 0.016, p = 4.07E−09). Pyridoxate, a catabolic product of vitamin B6, was inversely associated with CpG methylation near the SLC1A5 gene promoter region (cg02711608 and cg22304262) and with SLC7A11 (cg06690548), but not with corresponding changes in gene expression levels. The self-reported intake of folate and vitamin B6 had consistent but non-significant associations with the epigenetic signals.ConclusionMetabolomic biomarkers are a valuable approach to investigate the effects of dietary B vitamin intake on the human epigenome. Show less
BackgroundLoss of epigenetic control is a hallmark of aging. Among the most prominent roles of epigenetic mechanisms is the inactivation of one of two copies of the X chromosome in females through... Show moreBackgroundLoss of epigenetic control is a hallmark of aging. Among the most prominent roles of epigenetic mechanisms is the inactivation of one of two copies of the X chromosome in females through DNA methylation. Hence, age-related disruption of X-chromosome inactivation (XCI) may contribute to the aging process in women.MethodsWe analyzed 9,777 CpGs on the X chromosome in whole blood samples from 2343 females and 1688 males (Illumina 450k methylation array) and replicated findings in duplicate using one whole blood and one purified monocyte data set (in total, 991/924 females/males). We used double generalized linear models to detect age-related differentially methylated CpGs (aDMCs), whose mean methylation level differs with age, and age-related variably methylated CpGs (aVMCs), whose methylation level becomes more variable with age.ResultsIn females, aDMCs were relatively uncommon (n = 33) and preferentially occurred in regions known to escape XCI. In contrast, many CpGs (n = 987) were found to display an increased variance with age (aVMCs). Of note, the replication rate of aVMCs was also high in purified monocytes (94%), indicating an independence of cell composition. aVMCs accumulated in CpG islands and regions subject to XCI suggesting that they stemmed from the inactive X. In males, carrying an active copy of the X chromosome only, aDMCs (n = 316) were primarily driven by cell composition, while aVMCs replicated well (95%) but were infrequent (n = 37).ConclusionsOur results imply that age-related DNA methylation differences at the inactive X chromosome are dominated by the accumulation of variability. Show less
Hellbach, F.; Sinke, L.; Costeira, R.; Baumeister, S.E.; Beekman, M.; Louca, P.; ... ; Linseisen, J. 2022
Purpose Examining epigenetic patterns is a crucial step in identifying molecular changes of disease pathophysiology, with DNA methylation as the most accessible epigenetic measure. Diet is... Show morePurpose Examining epigenetic patterns is a crucial step in identifying molecular changes of disease pathophysiology, with DNA methylation as the most accessible epigenetic measure. Diet is suggested to affect metabolism and health via epigenetic modifications. Thus, our aim was to explore the association between food consumption and DNA methylation. Methods Epigenome-wide association studies were conducted in three cohorts: KORA FF4, TwinsUK, and Leiden Longevity Study, and 37 dietary exposures were evaluated. Food group definition was harmonized across the three cohorts. DNA methylation was measured using Infinium MethylationEPIC BeadChip in KORA and Infinium HumanMethylation450 BeadChip in the Leiden study and the TwinsUK study. Overall, data from 2293 middle-aged men and women were included. A fixed-effects meta-analysis pooled study-specific estimates. The significance threshold was set at 0.05 for false-discovery rate-adjusted p values per food group. Results We identified significant associations between the methylation level of CpG sites and the consumption of onions and garlic (2), nuts and seeds (18), milk (1), cream (11), plant oils (4), butter (13), and alcoholic beverages (27). The signals targeted genes of metabolic health relevance, for example, GLI1, RPTOR, and DIO1, among others. Conclusion This EWAS is unique with its focus on food groups that are part of a Western diet. Significant findings were mostly related to food groups with a high-fat content. Show less
Motivation: Batch effects heavily impact results in omics studies, causing bias and false positive results, but software to control them preemptively is lacking. Sample randomization prior to... Show moreMotivation: Batch effects heavily impact results in omics studies, causing bias and false positive results, but software to control them preemptively is lacking. Sample randomization prior to measurement is vital for minimizing these effects, but current approaches are often ad hoc, poorly documented and ill-equipped to handle multiple batches and outcomes.Results: We developed Omixer-a Bioconductor package implementing multivariate and reproducible sample randomization for omics studies. It proactively counters correlations between technical factors and biological variables of interest by optimizing sample distribution across batches. Show less
