Fine-grained investigation of the relationship between human nutrition and global DNA methylation patterns.

PURPOSE: Nutrition is an important, modifiable, environmental factor affecting human health by modulating epigenetic processes, including DNA methylation (5mC). Numerous studies investigated the association of nutrition with global and gene-specific DNA methylation and evidences on animal models highlighted a role in DNA hydroxymethylation (5hmC) regulation. However, a more comprehensive analysis of different layers of nutrition in association with global levels of 5mC and 5hmC is lacking. We investigated the association between global levels of 5mC and 5hmC and human nutrition, through the stratification and analysis of dietary patterns into different nutritional layers: adherence to Mediterranean diet (MD), main food groups, macronutrients and micronutrients intake. METHODS: ELISA technique was used to measure global 5mC and 5hmC levels in 1080 subjects from the Moli-sani cohort. Food intake during the 12 months before enrolment was assessed using the semi-quantitative EPIC food frequency questionnaire. Complementary approaches involving both classical statistics and supervised machine learning analyses were used to investigate the associations between global 5mC and 5hmC levels and adherence to Mediterranean diet, main food groups, macronutrients and micronutrients intake. RESULTS: We found that global DNA methylation, but not hydroxymethylation, was associated with daily intake of zinc and vitamin B3. Random Forests algorithms predicting 5mC and 5hmC through intakes of food groups, macronutrients and micronutrients revealed a significant contribution of zinc, while vitamin B3 was reported among the most influential features. CONCLUSION: We found that nutrition may affect global DNA methylation, suggesting a contribution of micronutrients previously implicated as cofactors in methylation pathways.

Association of nutritional glycaemic indices with global DNA methylation patterns: results from the Moli-sani cohort.

BACKGROUND: High dietary glycaemic index (GI) and load (GL) have been associated with increased risk of various cardiometabolic conditions. Among the molecular potential mechanisms underlying this relationship, DNA methylation has been studied, but a direct link between high GI and/or GL of diet and global DNA methylation levels has not been proved yet. We analyzed the associations between GI and GL and global DNA methylation patterns within an Italian population. RESULTS: Genomic DNA methylation (5mC) and hydroxymethylation (5hmC) levels were measured in 1080 buffy coat samples from participants of the Moli-sani study (mean(SD) = 54.9(11.5) years; 52% women) via ELISA. A 188-item Food Frequency Questionnaire was used to assess food intake and dietary GI and GL for each participant were calculated. Multiple linear regressions were used to investigate the associations between dietary GI and GL and global 5mC and 5hmC levels, as well as the proportion of effect explained by metabolic and inflammatory markers. We found negative associations of GI with both 5mC (ß (SE) = - 0.073 (0.027), p = 0.007) and 5hmC (- 0.084 (0.030), p = 0.006), and of GL with 5mC (- 0.14 (0.060), p = 0.014). Circulating biomarkers did not explain the above-mentioned associations. Gender interaction analyses revealed a significant association of the gender-x-GL interaction with 5mC levels, with men showing an inverse association three times as negative as in women (interaction ß (SE) = - 0.16 (0.06), p = 0.005). CONCLUSIONS: Our findings suggest that global DNA methylation and hydroxymethylation patterns represent a biomarker of carbohydrate intake. Based on the differential association of GL with 5mC between men and women, further gender-based separate approaches are warranted.

NMU DNA methylation in blood is associated with metabolic and inflammatory indices: results from the Moli-sani study.

Neuromedin U (NMU) is a neuropeptide involved in gut-brain axis, energy balance and immune response. We aimed at analysing the association between NMU epigenetic variability and metabolic indices and the potential mediating role of low-grade inflammation in a general population of Italian adults.NMU Blood DNA methylation levels at two CpG islands (NMU76 and NMU32) were analysed using pyrosequencing in a randomly selected sub-cohort of 1,160 subjects from the Moli-sani study (≥35years; 49.20% men). Multivariable regressions adjusted for age, sex, smoking, alcohol and vegetable consumption were performed to estimate the associations between methylation and metabolic phenotypes (BMI, waist-to-hip ratio, blood pressure, glucose, HOMA-IR, lipids, lipoprotein(a) and apolipoproteins). Mediation analysis was performed to identify the influence of low-grade inflammation in the association using a composite index based on C reactive protein, granulocyte-to-lymphocyte ratio (GLR), platelet and white blood cell counts (INFLA-score).Using principal component analysis four methylation factors were identified: NMU76-F1, NMU76-F2, NMU32-F1 and NMU32-F2. NMU76-F1 was FDR significantly associated with total cholesterol (for 1 SD increase: ß = 4.5 ± 1.4 mg/dL of, R2 = 10.8%, p = 0.001), ApoB (0.03 ± 0.01 g/L, 12.2%, p = 0.0004), with INFLA-score (1.05 ± 0.22, p = 2.7E-6) and GLR (-0.27 ± 0.03, 30.4%, p = 1.3E-20). GLR and lymphocyte numbers mediate the association of NMU76-F1 with cholesterol (24.0% of total effect, Sobel p = 0.013) and ApoB (42.6%, p = 9E-7), respectively.These findings suggest that NMU promoter methylation patterns could mark a pathway linking lipids with haematopoiesis and systemic inflammation.

Assessing Genetic Overlap Between Platelet Parameters and Neurodegenerative Disorders.

Neurodegenerative disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD) suffer from the lack of risk-predictive circulating biomarkers, and clinical diagnosis occurs only when symptoms are evident. Among potential biomarkers, platelet parameters have been associated with both disorders. However, these associations have been scarcely investigated at the genetic level. Here, we tested genome-wide coheritability based on common genetic variants between platelet parameters and PD/AD risk, through Linkage Disequilibrium Score Regression. This revealed a significant genetic correlation between platelet distribution width (PDW), an index of platelet size variability, and PD risk (rg [SE] = 0.080 [0.034]; p = 0.019), which was confirmed by a summary-summary polygenic score analysis, where PDW explained a small but significant proportion PD risk (<1%). AD risk showed no significant correlations, although a negative trend was observed with PDW (rg [SE] =-0.088 [0.053]; p=0.096), in line with previous epidemiological reports. These findings suggest the existence of limited shared genetic bases between PDW and PD and warrant further investigations to clarify the genes involved in this relation. Additionally, they suggest that the association between platelet parameters and AD risk is more environmental in nature, prompting an investigation into which factors may influence these traits.