Search

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 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 × 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 × 10–5, 95%CI: 1.28 × 10–5-2.73 × 10–5, P value: 6.98 × 10–8), while cg05041783, annotated to gene MARK2, was positively associated with docosapentaenoic acid (DPA) in our fully adjusted model (beta: 9.80 × 10–5, 95%CI: 6.25 × 10–5-1.33 × 10–4, P value: 6.75 × 10–8). In the meta-analysis, we identified the CpG site (cg15951061), annotated to gene CDCA7L below Bonferroni correction (1.23 × 10–7) associated with eicosapentaenoic acid (EPA) intake in model 1 (beta: 2.00 × 10–5, 95% CI: 1.27 × 10–5–2.73 × 10–5, P value = 5.99 × 10–8) and we confirmed the association of cg19937480 with DHA in both models 1 and 2 (beta: 2.07 × 10–5, 95% CI: 1.31 × 10–5–2.83 × 10–5, P value = 1.00 × 10–7 and beta: 2.19 × 10–5, 95% CI: 1.41 × 10–5–2.97 × 10–5, P value = 5.91 × 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. [ABSTRACT FROM AUTHOR]

With an estimated prevalence of 463 million affected, type 2 diabetes represents a major challenge to health care systems worldwide. Analyzing the plasma proteomes of individuals with type 2 diabetes may illuminate hitherto unknown functional mechanisms underlying disease pathology. We assessed the associations between type 2 diabetes and >1,000 plasma proteins in the Cooperative Health Research in the Region of Augsburg (KORA) F4 cohort (n = 993, 110 cases), with subsequent replication in the third wave of the Nord-Trøndelag Health Study (HUNT3) cohort (n = 940, 149 cases). We computed logistic regression models adjusted for age, sex, BMI, smoking status, and hypertension. Additionally, we investigated associations with incident type 2 diabetes and performed two-sample bidirectional Mendelian randomization (MR) analysis to prioritize our results. Association analysis of prevalent type 2 diabetes revealed 24 replicated proteins, of which 8 are novel. Proteins showing association with incident type 2 diabetes were aminoacylase-1, growth hormone receptor, and insulin-like growth factor–binding protein 2. Aminoacylase-1 was associated with both prevalent and incident type 2 diabetes. MR analysis yielded nominally significant causal effects of type 2 diabetes on cathepsin Z and rennin, both known to have roles in the pathophysiological pathways of cardiovascular disease, and of sex hormone–binding globulin on type 2 diabetes. In conclusion, our high-throughput proteomics study replicated previously reported type 2 diabetes–protein associations and identified new candidate proteins possibly involved in the pathogenesis of type 2 diabetes. [ABSTRACT FROM AUTHOR]

• First study on the effects of air temperature on epigenetic age acceleration. • Medium-term exposures to high temperatures are associated with increased HorvathAA, HannumAA, GrimAA, and SkinBloodAA. • Long-term exposures to high temperatures are associated with increased HorvathAA, HannumAA, PhenoAA, GrimAA, and SkinBloodAA. • More pronounced associations between air temperature and epigenetic age acceleration are observed among women and people with obesity or diabetes. Climate change poses a serious threat to human health worldwide, while aging populations increase. However, no study has ever investigated the effects of air temperature on epigenetic age acceleration. This study involved 1,725 and 1,877 participants from the population-based KORA F4 (2006–2008) and follow-up FF4 (2013–2014) studies, respectively, conducted in Augsburg, Germany. The difference between epigenetic age and chronological age was referred to as epigenetic age acceleration and reflected by Horvath's epigenetic age acceleration (HorvathAA), Hannum's epigenetic age acceleration (HannumAA), PhenoAge acceleration (PhenoAA), GrimAge acceleration (GrimAA), and Epigenetic Skin and Blood Age acceleration (SkinBloodAA). Daily air temperature was estimated using hybrid spatiotemporal regression-based models. To explore the medium- and long-term effects of air temperature modeled in time and space on epigenetic age acceleration, we applied generalized estimating equations (GEE) with distributed lag non-linear models, and GEE, respectively. We found that high temperature exposure based on the 8-week moving average air temperature (97.5th percentile of temperature compared to median temperature) was associated with increased HorvathAA, HannumAA, GrimAA, and SkinBloodAA: 1.83 (95% CI: 0.29–3.37), 11.71 (95% CI: 8.91–14.50), 2.26 (95% CI: 1.03–3.50), and 5.02 (95% CI: 3.42–6.63) years, respectively. Additionally, we found consistent results with high temperature exposure based on the 4-week moving average air temperature was associated with increased HannumAA, GrimAA, and SkinBloodAA: 9.18 (95% CI: 6.60–11.76), 1.78 (95% CI: 0.66–2.90), and 4.07 (95% CI: 2.56–5.57) years, respectively. For the spatial variation in annual average temperature, a 1 °C increase was associated with an increase in all five measures of epigenetic age acceleration (HorvathAA: 0.41 [95% CI: 0.24–0.57], HannumAA: 2.24 [95% CI: 1.95–2.53], PhenoAA: 0.32 [95% CI: 0.05–0.60], GrimAA: 0.24 [95%: 0.11–0.37], and SkinBloodAA: 1.17 [95% CI: 1.00–1.35] years). In conclusion, our results provide first evidence that medium- and long-term exposures to high air temperature affect increases in epigenetic age acceleration. [ABSTRACT FROM AUTHOR]