Genes with epigenetic alterations in human pancreatic islets impact mitochondrial function, insulin secretion, and type 2 diabetes.

Epigenetic dysregulation may influence disease progression. Here we explore whether epigenetic alterations in human pancreatic islets impact insulin secretion and type 2 diabetes (T2D). In islets, 5,584 DNA methylation sites exhibit alterations in T2D cases versus controls and are associated with HbA1c in individuals not diagnosed with T2D. T2D-associated methylation changes are found in enhancers and regions bound by ß-cell-specific transcription factors and associated with reduced expression of e.g. CABLES1, FOXP1, GABRA2, GLR1A, RHOT1, and TBC1D4. We find RHOT1 (MIRO1) to be a key regulator of insulin secretion in human islets. Rhot1-deficiency in ß-cells leads to reduced insulin secretion, ATP/ADP ratio, mitochondrial mass, Ca2+, and respiration. Regulators of mitochondrial dynamics and metabolites, including L-proline, glycine, GABA, and carnitines, are altered in Rhot1-deficient ß-cells. Islets from diabetic GK rats present Rhot1-deficiency. Finally, RHOT1methylation in blood is associated with future T2D. Together, individuals with T2D exhibit epigenetic alterations linked to mitochondrial dysfunction in pancreatic islets.

Eating out intensity, ultra-processed foods and BMI among Albanian youth.

OBJECTIVE: Ultra-processed foods (UPF) and eating out of home (OH) are changing nutrition, particularly among youth in constrained settings. We aimed to assess the role of eating OH intensity on the associations of UPF and unprocessed or minimally processed foods (UMPF) with BMI among Albanian youth. DESIGN: Cross-sectional. SETTING: Albania, a south-eastern European country. PARTICIPANTS: 281 youth, predominantly females. METHODS: UPF and UMPF were defined based on NOVA, while eating OH intensity based on energy percentage from OH foods. Multivariable models tested associations of UPF and UMPF with BMI stratified by eating OH intensity, controlled for relevant covariates including diet quality, portion size and costs. RESULTS: The respondents age ranged between 18 and 23 years with a female predominance (87·5 %). Mean energy from UPF and UMPF was 846 (sd: 573·0) and 802·9 (422·5) kcals, respectively. Among substantial at home eaters UPF intake was not associated (ß = −0·07, 95 % CI (−0·13, 0·267)) with BMI; however, UMPF negatively associated with BMI (ß = −0·24, 95 % CI (−0·43, −0·06)). Among those defined as substantial OH eaters, UPF (ß = 0·24, 95 % CI (0·08, 0·40)) and UMPF (ß = 0·18, 95 % CI (0·04, 0·33)) were positively associated with BMI. CONCLUSIONS: Our findings provide evidence for the hypothesis that eating OH plays an important role in the association of UPF and UMPF with BMI in youth. While causality cannot be established due to cross-sectional design, to the best of our knowledge, we provide the first assessment of UPF and UMPF intake in a south-eastern European setting, while highlighting the need for establishing and integrating youth nutrition into national nutritional surveillance systems for key dietary risk factors in Albania.

Plasma lipidic fingerprint associated with type 2 diabetes in patients with coronary heart disease: CORDIOPREV study.

OBJECTIVE: We aimed to identify a lipidic profile associated with type 2 diabetes mellitus (T2DM) development in coronary heart disease (CHD) patients, to provide a new, highly sensitive model which could be used in clinical practice to identify patients at T2DM risk. METHODS: This study considered the 462 patients of the CORDIOPREV study (CHD patients) who were not diabetic at the beginning of the intervention. In total, 107 of them developed T2DM after a median follow-up of 60 months. They were diagnosed using the American Diabetes Association criteria. A novel lipidomic methodology employing liquid chromatography (LC) separation followed by HESI, and detection by mass spectrometry (MS) was used to annotate the lipids at the isomer level. The patients were then classified into a Training and a Validation Set (60-40). Next, a Random Survival Forest (RSF) was carried out to detect the lipidic isomers with the lowest prediction error, these lipids were then used to build a Lipidomic Risk (LR) score which was evaluated through a Cox. Finally, a production model combining the clinical variables of interest, and the lipidic species was carried out. RESULTS: LC-tandem MS annotated 440 lipid species. From those, the RSF identified 15 lipid species with the lowest prediction error. These lipids were combined in an LR score which showed association with the development of T2DM. The LR hazard ratio per unit standard deviation was 2.87 and 1.43, in the Training and Validation Set respectively. Likewise, patients with higher LR Score values had lower insulin sensitivity (P = 0.006) and higher liver insulin resistance (P = 0.005). The receiver operating characteristic (ROC) curve obtained by combining clinical variables and the selected lipidic isomers using a generalised lineal model had an area under the curve (AUC) of 81.3%. CONCLUSION: Our study showed the potential of comprehensive lipidomic analysis in identifying patients at risk of developing T2DM. In addition, the lipid species combined with clinical variables provided a new, highly sensitive model which can be used in clinical practice to identify patients at T2DM risk. Moreover, these results also indicate that we need to look closely at isomers to understand the role of this specific compound in T2DM development. Trials registration NCT00924937.

Association of the human gut microbiota with vascular stiffness.

Gut microbiota metabolites have been mechanistically linked to inflammatory pathway activation and atherosclerosis, which are major causes of vascular stiffness (VS). Aiming to investigate if the gut microbiome might be involved in VS development, we performed a cross-sectional study (n = 3,087), nested within the population-based European Prospective Investigations into Cancer and Nutrition (EPIC) Potsdam. We investigated the correlation of the gut microbiota (alpha diversity and taxa abundance) with 3 vascular stiffness measures: carotid-femoral (PWV), aortic augmentation index (AIX) and ankle-brachial index (ABI). Shannon index was not significantly associated with VS but the number of observed Amplicon Sequence Variants (ASV) was positively associated with PWV and AIX. We found a total of 19 ASVs significantly associated with at least one VS measure in multivariable-adjusted models. One ASV (classified as Sutterella wadsworthensis) was associated with 2 VS measures, AIX (- 0.11 ± 0.04) and PWV (-0.14 ± 0.03). Other examples of ASVs associated with VS were Collinsella aerofaciens, previously reported to be affected by diet and Bacteroides uniformis, commercially available as probiotics. In conclusion, our study suggests a potential role of individual components of the gut microbiota in the aetiology of VS.

Differences in DNA methylation of HAMP in blood cells predicts the development of type 2 diabetes.

OBJECTIVES: Better disease management can be achieved with earlier detection through robust, sensitive, and easily accessible biomarkers. The aim of the current study was to identify novel epigenetic biomarkers determining the risk of type 2 diabetes (T2D). METHODS: Livers of 10-week-old female New Zealand Obese (NZO) mice, slightly differing in their degree of hyperglycemia and liver fat content and thereby in their diabetes susceptibility were used for expression and methylation profiling. We screened for differences in hepatic expression and DNA methylation in diabetes-prone and -resistant mice, and verified a candidate (HAMP) in human livers and blood cells. Hamp expression was manipulated in primary hepatocytes and insulin-stimulated pAKT was detected. Luciferase reporter assays were conducted in a murine liver cell line to test the impact of DNA methylation on promoter activity. RESULTS: In livers of NZO mice, the overlap of methylome and transcriptome analyses revealed a potential transcriptional dysregulation of 12 hepatokines. The strongest effect with a 52% decreased expression in livers of diabetes-prone mice was detected for the Hamp gene, mediated by elevated DNA methylation of two CpG sites located in the promoter. Hamp encodes the iron-regulatory hormone hepcidin, which had a lower abundance in the livers of mice prone to developing diabetes. Suppression of Hamp reduces the levels of pAKT in insulin-treated hepatocytes. In liver biopsies of obese insulin-resistant women, HAMP expression was significantly downregulated along with increased DNA methylation of a homologous CpG site. In blood cells of incident T2D cases from the prospective EPIC-Potsdam cohort, higher DNA methylation of two CpG sites was related to increased risk of incident diabetes. CONCLUSIONS: We identified epigenetic changes in the HAMP gene which may be used as an early marker preceding T2D.

Replacement of dietary saturated with unsaturated fatty acids is associated with beneficial effects on lipidome metabolites: a secondary analysis of a randomized trial.

BACKGROUND: The effects of replacing dietary saturated fatty acids (SFAs) with monounsaturated fatty acids (MUFAs) and/or polyunsaturated fatty acids (PUFAs) on the plasma lipidome in relation to the cardiometabolic disease (CMD) risk is poorly understood. OBJECTIVES: We aimed to assess the impact of substituting dietary SFAs with unsaturated fatty acids (UFAs) on the plasma lipidome and examine the relationship between lipid metabolites modulated by diet and CMD risk. METHODS: Plasma fatty acid (FA) concentrations among 16 lipid classes (within-class FAs) were measured in a subgroup from the Dietary Intervention and VAScular function (DIVAS) parallel randomized controlled trial (n = 113/195), which consisted of three 16-wk diets enriched in SFAs (target SFA:MUFA:n-6PUFA ratio = 17:11:4% total energy [TE]), MUFAs (9:19:4% TE), or a MUFA/PUFA mixture (9:13:10% TE). Similar lipidomics analyses were conducted in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study (specific case/cohorts: n = 775/1886 for type 2 diabetes [T2D], n = 551/1671 for cardiovascular disease [CVD]). Multiple linear regression and multivariable Cox models identified within-class FAs sensitive to replacement of dietary SFA with UFA in DIVAS and their association with CMD risk in EPIC-Potsdam. Elastic-net regression models identified within-class FAs associated with changes in CMD risk markers post-DIVAS interventions. RESULTS: DIVAS high-UFA interventions reduced plasma within-class FAs associated with a higher CVD risk in EPIC-Potsdam, especially SFA-containing glycerolipids and sphingolipids (e.g., diacylglycerol (20:0) z-score = -1.08; SE = 0.17; P value < 10-8), whereas they increased those inversely associated with CVD risk. The results on T2D were less clear. Specific sphingolipids and phospholipids were associated with changes in markers of endothelial function and ambulatory blood pressure, whereas higher low-density lipoprotein cholesterol concentrations were characterized by higher plasma glycerolipids containing lauric and stearic acids. CONCLUSIONS: These results suggest a mediating role of plasma lipid metabolites in the association between dietary fat and CMD risk. Future research combining interventional and observational findings will further our understanding of the role of dietary fat in CMD etiology. This trial was registered in ClinicalTrials.gov as NCT01478958.

Circulating amino acid levels and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition and UK Biobank cohorts.

BACKGROUND: Amino acid metabolism is dysregulated in colorectal cancer patients; however, it is not clear whether pre-diagnostic levels of amino acids are associated with subsequent risk of colorectal cancer. We investigated circulating levels of amino acids in relation to colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank cohorts. METHODS: Concentrations of 13-21 amino acids were determined in baseline fasting plasma or serum samples in 654 incident colorectal cancer cases and 654 matched controls in EPIC. Amino acids associated with colorectal cancer risk following adjustment for the false discovery rate (FDR) were then tested for associations in the UK Biobank, for which measurements of 9 amino acids were available in 111,323 participants, of which 1221 were incident colorectal cancer cases. RESULTS: Histidine levels were inversely associated with colorectal cancer risk in EPIC (odds ratio [OR] 0.80 per standard deviation [SD], 95% confidence interval [CI] 0.69-0.92, FDR P-value=0.03) and in UK Biobank (HR 0.93 per SD, 95% CI 0.87-0.99, P-value=0.03). Glutamine levels were borderline inversely associated with colorectal cancer risk in EPIC (OR 0.85 per SD, 95% CI 0.75-0.97, FDR P-value=0.08) and similarly in UK Biobank (HR 0.95, 95% CI 0.89-1.01, P=0.09) In both cohorts, associations changed only minimally when cases diagnosed within 2 or 5 years of follow-up were excluded. CONCLUSIONS: Higher circulating levels of histidine were associated with a lower risk of colorectal cancer in two large prospective cohorts. Further research to ascertain the role of histidine metabolism and potentially that of glutamine in colorectal cancer development is warranted.

Plasma Lipidomic n-6 Polyunsaturated Fatty Acids and Type 2 Diabetes Risk in the EPIC-Potsdam Prospective Cohort Study.

OBJECTIVE: Evidence on plasma n-6 polyunsaturated fatty acids (PUFAs) and type 2 diabetes risk is inconsistent. We examined the associations of lipid class-specific PUFA concentrations with type 2 diabetes risk. RESEARCH DESIGN AND METHODS: In the prospective European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (nested case-cohort study: subcohort 1,084 participants, 536 participants with type 2 diabetes, median follow-up 6.5 years), we measured plasma 18:2, 20:3, and 20:4 concentrations in 12 lipid (sub)classes, likely reflecting the plasma concentrations of linoleic acid (18:2n-6), dihomo-γ-linolenic acid (20:3n-6), and arachidonic acid (20:4n-6). The Δ-5 desaturase (D5D) activity was estimated as the 20:4/20:3 ratio. Associations with diabetes were estimated with Cox proportional hazards models. RESULTS: Higher concentrations of 18:2 were inversely associated with type 2 diabetes risk, particularly in lysophosphatidylcholines (hazard ratio [HR] per 1 SD 0.53; 95% CI 0.23-1.26) and monoacylglycerols (HR 0.59; 0.38-0.92). Higher concentrations of 20:3 in phospholipid classes phosphatidylcholines (HR 1.63; 1.23-2.14), phosphatidylethanolamines (HR 1.87; 1.32-2.65), and phosphatidylinositol (HR 1.40; 1.05-1.87); free fatty acids (HR 1.44; 1.10-1.90); and cholesteryl esters (HR 1.47; 1.09-1.98) were linked to higher type 2 diabetes incidence, and these associations remained statistically significant after correction for multiple testing. Higher 20:4 concentrations were not associated with risk. The estimated D5D activity in phospholipids and cholesteryl esters was associated with lower type 2 diabetes risk. Single nucleotide polymorphisms in the D5D-encoding FADS genes explained relatively high proportions of variation of estimated D5D activity in those lipid classes. CONCLUSIONS: Plasma n-6 PUFAs were associated differently with type 2 diabetes, depending on fatty acid and the lipid class.

Blood cell DNA methylation biomarkers in preclinical malignant pleural mesothelioma: The EPIC prospective cohort.

Malignant pleural mesothelioma (MPM) is a rare and aggressive cancer mainly caused by asbestos exposure. Specific and sensitive noninvasive biomarkers may facilitate and enhance screening programs for the early detection of cancer. We investigated DNA methylation (DNAm) profiles in MPM prediagnostic blood samples in a case-control study nested in the European Prospective Investigation into Cancer and nutrition (EPIC) cohort, aiming to characterise DNAm biomarkers associated with MPM. From the EPIC cohort, we included samples from 135 participants who developed MPM during 20 years of follow-up and from 135 matched, cancer-free, controls. For the discovery phase we selected EPIC participants who developed MPM within 5 years from enrolment (n = 36) with matched controls. We identified nine differentially methylated CpGs, selected by 10-fold cross-validation and correlation analyses: cg25755428 (MRI1), cg20389709 (KLF11), cg23870316, cg13862711 (LHX6), cg06417478 (HOOK2), cg00667948, cg01879420 (AMD1), cg25317025 (RPL17) and cg06205333 (RAP1A). Receiver operating characteristic (ROC) analysis showed that the model including baseline characteristics (age, sex and PC1wbc) along with the nine MPM-related CpGs has a better predictive value for MPM occurrence than the baseline model alone, maintaining some performance also at more than 5 years before diagnosis (area under the curve [AUC] < 5 years = 0.89; AUC 5-10 years = 0.80; AUC >10 years = 0.75; baseline AUC range = 0.63-0.67). DNAm changes as noninvasive biomarkers in prediagnostic blood samples of MPM cases were investigated for the first time. Their application can improve the identification of asbestos-exposed individuals at higher MPM risk to possibly adopt more intensive monitoring for early disease identification.

Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the European Prospective Investigation into Cancer and Nutrition.

BACKGROUND: Epidemiological studies of associations between metabolites and cancer risk have typically focused on specific cancer types separately. Here, we designed a multivariate pan-cancer analysis to identify metabolites potentially associated with multiple cancer types, while also allowing the investigation of cancer type-specific associations. METHODS: We analysed targeted metabolomics data available for 5828 matched case-control pairs from cancer-specific case-control studies on breast, colorectal, endometrial, gallbladder, kidney, localized and advanced prostate cancer, and hepatocellular carcinoma nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. From pre-diagnostic blood levels of an initial set of 117 metabolites, 33 cluster representatives of strongly correlated metabolites and 17 single metabolites were derived by hierarchical clustering. The mutually adjusted associations of the resulting 50 metabolites with cancer risk were examined in penalized conditional logistic regression models adjusted for body mass index, using the data-shared lasso penalty. RESULTS: Out of the 50 studied metabolites, (i) six were inversely associated with the risk of most cancer types: glutamine, butyrylcarnitine, lysophosphatidylcholine a C18:2, and three clusters of phosphatidylcholines (PCs); (ii) three were positively associated with most cancer types: proline, decanoylcarnitine, and one cluster of PCs; and (iii) 10 were specifically associated with particular cancer types, including histidine that was inversely associated with colorectal cancer risk and one cluster of sphingomyelins that was inversely associated with risk of hepatocellular carcinoma and positively with endometrial cancer risk. CONCLUSIONS: These results could provide novel insights for the identification of pathways for cancer development, in particular those shared across different cancer types.

Immunoglobulin G N-Glycosylation Signatures in Incident Type 2 Diabetes and Cardiovascular Disease.

OBJECTIVE: N-glycosylation is a functional posttranslational modification of immunoglobulins (Igs). We hypothesized that specific IgG N-glycans are associated with incident type 2 diabetes and cardiovascular disease (CVD). RESEARCH DESIGN AND METHODS: We performed case-cohort studies within the population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (2,127 in the type 2 diabetes subcohort [741 incident cases]; 2,175 in the CVD subcohort [417 myocardial infarction and stroke cases]). Relative abundances of 24 IgG N-glycan peaks (IgG-GPs) were measured by ultraperformance liquid chromatography, and eight glycosylation traits were derived based on structural similarity. End point-associated IgG-GPs were preselected with fractional polynomials, and prospective associations were estimated in confounder-adjusted Cox models. Diabetes risk associations were validated in three independent studies. RESULTS: After adjustment for confounders and multiple testing correction, IgG-GP7, IgG-GP8, IgG-GP9, IgG-GP11, and IgG-GP19 were associated with type 2 diabetes risk. A score based on these IgG-GPs was associated with a higher diabetes risk in EPIC-Potsdam and independent validation studies (843 total cases, 3,149 total non-cases, pooled estimate per SD increase 1.50 [95% CI 1.37-1.64]). Associations of IgG-GPs with CVD risk differed between men and women. In women, IgG-GP9 was inversely associated with CVD risk (hazard ratio [HR] per SD 0.80 [95% CI 0.65-0.98]). In men, a weighted score based on IgG-GP19 and IgG-GP23 was associated with higher CVD risk (HR per SD 1.47 [95% CI 1.20-1.80]). In addition, several derived traits were associated with cardiometabolic disease incidence. CONCLUSIONS: Selected IgG N-glycans are associated with cardiometabolic risk beyond classic risk factors, including clinical biomarkers.

Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate Cancer.

Three metabolite patterns have previously shown prospective inverse associations with the risk of aggressive prostate cancer within the European Prospective Investigation into Cancer and Nutrition (EPIC). Here, we investigated dietary and lifestyle correlates of these three prostate cancer-related metabolite patterns, which included: 64 phosphatidylcholines and three hydroxysphingomyelins (Pattern 1), acylcarnitines C18:1 and C18:2, glutamate, ornithine, and taurine (Pattern 2), and 8 lysophosphatidylcholines (Pattern 3). In a two-stage cross-sectional discovery (n = 2524) and validation (n = 518) design containing 3042 men free of cancer in EPIC, we estimated the associations of 24 dietary and lifestyle variables with each pattern and the contributing individual metabolites. Associations statistically significant after both correction for multiple testing (False Discovery Rate = 0.05) in the discovery set and at p < 0.05 in the validation set were considered robust. Intakes of alcohol, total fish products, and its subsets total fish and lean fish were positively associated with Pattern 1. Body mass index (BMI) was positively associated with Pattern 2, which appeared to be driven by a strong positive BMI-glutamate association. Finally, both BMI and fatty fish were inversely associated with Pattern 3. In conclusion, these results indicate associations of fish and its subtypes, alcohol, and BMI with metabolite patterns that are inversely associated with risk of aggressive prostate cancer.

Deep Lipidomics in Human Plasma: Cardiometabolic Disease Risk and Effect of Dietary Fat Modulation.

BACKGROUND: In blood and tissues, dietary and endogenously generated fatty acids (FAs) occur in free form or as part of complex lipid molecules that collectively represent the lipidome of the respective tissue. We assessed associations of plasma lipids derived from high-resolution lipidomics with incident cardiometabolic diseases and subsequently tested if the identified risk-associated lipids were sensitive to dietary fat modification. METHODS: The EPIC Potsdam cohort study (European Prospective Investigation into Cancer and Nutrition) comprises 27 548 participants recruited within an age range of 35 to 65 years from the general population around Potsdam, Germany. We generated 2 disease-specific case cohorts on the basis of a fixed random subsample (n=1262) and all respective cohort-wide identified incident primary cardiovascular disease (composite of fatal and nonfatal myocardial infarction and stroke; n=551) and type 2 diabetes (n=775) cases. We estimated the associations of baseline plasma concentrations of 282 class-specific FA abundances (calculated from 940 distinct molecular species across 15 lipid classes) with the outcomes in multivariable-adjusted Cox models. We tested the effect of an isoenergetic dietary fat modification on risk-associated lipids in the DIVAS randomized controlled trial (Dietary Intervention and Vascular Function; n=113). Participants consumed either a diet rich in saturated FAs (control), monounsaturated FAs, or a mixture of monounsaturated and n-6 polyunsaturated FAs for 16 weeks. RESULTS: Sixty-nine lipids associated (false discovery rate<0.05) with at least 1 outcome (both, 8; only cardiovascular disease, 49; only type 2 diabetes, 12). In brief, several monoacylglycerols and FA16:0 and FA18:0 in diacylglycerols were associated with both outcomes; cholesteryl esters, free fatty acids, and sphingolipids were largely cardiovascular disease specific; and several (glycero)phospholipids were type 2 diabetes specific. In addition, 19 risk-associated lipids were affected (false discovery rate<0.05) by the diets rich in unsaturated dietary FAs compared with the saturated fat diet (17 in a direction consistent with a potential beneficial effect on long-term cardiometabolic risk). For example, the monounsaturated FA-rich diet decreased diacylglycerol(FA16:0) by 0.4 (95% CI, 0.5-0.3) SD units and increased triacylglycerol(FA22:1) by 0.5 (95% CI, 0.4-0.7) SD units. CONCLUSIONS: We identified several lipids associated with cardiometabolic disease risk. A subset was beneficially altered by a dietary fat intervention that supports the substitution of dietary saturated FAs with unsaturated FAs as a potential tool for primary disease prevention.

Anti-cancer therapy is associated with long-term epigenomic changes in childhood cancer survivors.

BACKGROUND: Childhood cancer survivors (CCS) exhibit significantly increased chronic diseases and premature death. Abnormalities in DNA methylation are associated with development of chronic diseases and reduced life expectancy. We investigated the hypothesis that anti-cancer treatments are associated with long-term DNA methylation changes that could be key drivers of adverse late health effects. METHODS: Genome-wide DNA methylation was assessed using MethylationEPIC arrays in paired samples (before/after therapy) from 32 childhood cancer patients. Separately, methylation was determined in 32 samples from different adult CCS (mean 22-years post-diagnosis) and compared with cancer-free controls (n = 284). RESULTS: Widespread DNA methylation changes were identified post-treatment in childhood cancer patients, including 146 differentially methylated regions (DMRs), which were consistently altered in the 32 post-treatment samples. Analysis of adult CCS identified matching methylation changes at 107/146 of the DMRs, suggesting potential long-term retention of post-therapy changes. Adult survivors also exhibited epigenetic age acceleration, independent of DMR methylation. Furthermore, altered methylation at the DUSP6 DMR was significantly associated with early mortality, suggesting altered methylation may be prognostic for some late adverse health effects in CCS. CONCLUSIONS: These novel methylation changes could serve as biomarkers for assessing normal cell toxicity in ongoing treatments and predicting long-term health outcomes in CCS.

Plasma Industrial and Ruminant Trans Fatty Acids and Incident Type 2 Diabetes in the EPIC-Potsdam Cohort.

OBJECTIVE: Although dietary intake of trans fatty acid (TFA) is a major public health concern because of the associated increase in the risk of cardiovascular events, it remains unclear whether TFAs also influence risk of type 2 diabetes (T2D) and whether industrial TFAs (iTFAs) and ruminant TFAs (rTFAs) exert the same effect on health. RESEARCH DESIGN AND METHODS: To investigate the relationship of 7 rTFAs and iTFAs, including 2 conjugated linoleic acids (CLAs), plasma phospholipid TFAs were measured in a case-cohort study nested within the European Prospective Investigation Into Cancer and Nutrition-Potsdam cohort. The analytical sample was a random subsample (n = 1,248) and incident cases of T2D (n = 801) over a median follow-up of 6.5 years. Using multivariable Cox regression models, we examined associations of TFAs with incident T2D. RESULTS: The TFA subtypes were intercorrelated with each other, with other fatty acids, and with different food sources. After controlling for other TFAs, the iTFAs (18:1n-6t, 18:1n-9t, 18:2n-6,9t) were not associated with diabetes risk. Some rTFA subtypes were inversely associated with diabetes risk: vaccenic acid (18:1n-7t; hazard ratio [HR] per SD 0.72; 95% CI 0.58-0.89) and t10c12-CLA (HR per SD 0.81; 95% CI 0.70-0.94), whereas c9t11-CLA was positively associated (HR per SD 1.39; 95% CI 1.19-1.62). Trans-palmitoleic acid (16:1n-7t) was not associated with diabetes risk when adjusting for the other TFAs (HR per SD 1.08; 95% CI 0.88-1.31). CONCLUSIONS: The TFAs' conformation plays an essential role in their relationship to diabetes risk. rTFA subtypes may have opposing relationships to diabetes risk. Previous observations for reduced diabetes risk with higher levels of circulating trans-palmitoleic acid are likely due to confounding.

Association of the odd-chain fatty acid content in lipid groups with type 2 diabetes risk: A targeted analysis of lipidomics data in the EPIC-Potsdam cohort.

BACKGROUND: Plasma odd-chain saturated fatty acids (OCFA) are inversely associated with type 2 diabetes (T2D) risk and may serve as biomarkers for dairy fat intake. Their distribution across different lipid classes and consequences for diabetes risk remain unknown. AIM: To investigate the prospective associations of OCFA-containing lipid species with T2D risk and their dietary determinants. METHODS: Within the European Prospective Investigation into Cancer and Nutrition-Potsdam study (n = 27,548), we applied a nested case-cohort design (subcohort: n = 1,248; T2D cases: n = 820; median follow-up 6.5 years). OCFA-containing lipids included triacylglycerols, free fatty acids (FFA), cholesteryl esters (CE), phosphatidylcholines, phosphatidylethanolamines, lysophosphatidylcholines, lysophosphatidylethanolamines, monoacylglycerols, and diacylglycerols. We estimated lipid class-specific associations between OCFA-containing lipids and T2D in sex-stratified Cox proportional-hazards models. We investigated correlations between lipids and dietary intakes derived from food-frequency questionnaires. RESULTS: We observed heterogeneous integration of OCFA in different lipid classes: triacylglycerols, FFA, CE, and phosphatidylcholines contributed most to the total OCFA-plasma abundance. The relative concentration of OCFA was particularly high in monoacylglycerols, and the contribution of C15:0 versus C17:0 to the total OCFA-abundance differed across lipid classes. In women, several OCFA-containing phospholipids were inversely associated with T2D risk [phosphatidylcholine(C15:0), HR Q5 vs Q1: 0.56, 95% CI 0.32-0.97; phosphatidylcholine(C17:0), HR per SD: 0.59, 95% CI 0.48-0.71; lysophosphatidylcholine(C17:0), HR Q5 vs Q1: 0.42, 95% CI 0.23-0.76]. In men, we did not detect statistically significant inverse associations in phospholipids, and lysophosphatidylcholine(C15:0) was associated with higher T2D risk (HR Q5 vs. Q1: 1.96, 95% CI 1.06-3.63). Besides, CE(C17:0), monoacylglycerols(C15:0), and diacylglycerols(C15:0) were inversely associated with T2D risk; FFA(C17:0) was positively associated with T2D risk in women. Consumption of fat-rich dairy and fiber-rich foods were positively and red meat inversely correlated to OCFA-containing lipid plasma levels. CONCLUSIONS: OCFA-containing lipids are linked to T2D risk in a lipid class and sex-specific manner, and they are correlated with several foods.

Advanced glycation end-products, measured as skin autofluorescence, associate with vascular stiffness in diabetic, pre-diabetic and normoglycemic individuals: a cross-sectional study.

BACKGROUND: Advanced glycation end-products are proteins that become glycated after contact with sugars and are implicated in endothelial dysfunction and arterial stiffening. We aimed to investigate the relationships between advanced glycation end-products, measured as skin autofluorescence, and vascular stiffness in various glycemic strata. METHODS: We performed a cross-sectional analysis within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort, comprising n = 3535 participants (median age 67 years, 60% women). Advanced glycation end-products were measured as skin autofluorescence with AGE-Reader™, vascular stiffness was measured as pulse wave velocity, augmentation index and ankle-brachial index with Vascular Explorer™. A subset of 1348 participants underwent an oral glucose tolerance test. Participants were sub-phenotyped into normoglycemic, prediabetes and diabetes groups. Associations between skin autofluorescence and various indices of vascular stiffness were assessed by multivariable regression analyses and were adjusted for age, sex, measures of adiposity and lifestyle, blood pressure, prevalent conditions, medication use and blood biomarkers. RESULTS: Skin autofluorescence associated with pulse wave velocity, augmentation index and ankle-brachial index, adjusted beta coefficients (95% CI) per unit skin autofluorescence increase: 0.38 (0.21; 0.55) for carotid-femoral pulse wave velocity, 0.25 (0.14; 0.37) for aortic pulse wave velocity, 1.00 (0.29; 1.70) for aortic augmentation index, 4.12 (2.24; 6.00) for brachial augmentation index and - 0.04 (- 0.05; - 0.02) for ankle-brachial index. The associations were strongest in men, younger individuals and were consistent across all glycemic strata: for carotid-femoral pulse wave velocity 0.36 (0.12; 0.60) in normoglycemic, 0.33 (- 0.01; 0.67) in prediabetes and 0.45 (0.09; 0.80) in diabetes groups; with similar estimates for aortic pulse wave velocity. Augmentation index was associated with skin autofluorescence only in normoglycemic and diabetes groups. Ankle-brachial index inversely associated with skin autofluorescence across all sex, age and glycemic strata. CONCLUSIONS: Our findings indicate that advanced glycation end-products measured as skin autofluorescence might be involved in vascular stiffening independent of age and other cardiometabolic risk factors not only in individuals with diabetes but also in normoglycemic and prediabetic conditions. Skin autofluorescence might prove as a rapid and non-invasive method for assessment of macrovascular disease progression across all glycemic strata.

Trace element profile and incidence of type 2 diabetes, cardiovascular disease and colorectal cancer: results from the EPIC-Potsdam cohort study.

PURPOSE: We aimed to examine the prospective association between manganese, iron, copper, zinc, iodine, selenium, selenoprotein P, free zinc, and their interplay, with incident type 2 diabetes (T2D), cardiovascular disease (CVD) and colorectal cancer (CRC). METHODS: Serum trace element (TE) concentrations were measured in a case-cohort study embedded within the EPIC-Potsdam cohort, consisting of a random sub-cohort (n = 2500) and incident cases of T2D (n = 705), CVD (n = 414), and CRC (n = 219). TE patterns were investigated using principal component analysis. Cox proportional hazard models were fitted to examine the association between TEs with T2D, CVD and CRC incidence. RESULTS: Higher manganese, zinc, iodine and selenium were associated with an increased risk of developing T2D (HR Q5 vs Q1: 1.56, 1.09-2.22; HR per SD, 95% CI 1.18, 1.05-1.33; 1.09, 1.01-1.17; 1.19, 1.06-1.34, respectively). Regarding CVD, manganese, copper and copper-to-zinc ratio were associated with an increased risk (HR per SD, 95% CI 1.13, 1.00-1.29; 1.22, 1.02-1.44; 1.18, 1.02-1.37, respectively). The opposite was observed for higher selenium-to-copper ratio (HR Q5 vs Q1, 95% CI 0.60, 0.39-0.93). Higher copper and zinc were associated with increasing risk of developing CRC (HR per SD, 95% CI 1.29, 1.05-1.59 and 1.14, 1.00-1.30, respectively). Selenium, selenoprotein P and selenium-to-copper-ratio were associated to decreased risk (HR per SD, 95% CI 0.82, 0.69-0.98; 0.81, 0.72-0.93; 0.77, 0.65-0.92, respectively). Two TE patterns were identified: manganese-iron-zinc and copper-iodine-selenium. CONCLUSION: Different TEs were associated with the risk of developing T2D, CVD and CRC. The contrasting associations found for selenium with T2D and CRC point towards differential disease-related pathways.

Lipid Profiles and Heart Failure Risk: Results From Two Prospective Studies.

RATIONALE: Altered lipid metabolism has been implicated in heart failure (HF) development, but no prospective studies have examined comprehensive lipidomics data and subsequent risk of HF. OBJECTIVE: We aimed to link single lipid metabolites and lipidomics networks to the risk of developing HF. METHODS AND RESULTS: Discovery analyses were based on 216 targeted lipids in a case-control study (331 incident HF cases and 507 controls, matched by age, sex, and study center), nested within the PREDIMED (Prevención con Dieta Mediterránea) study. Associations of single lipids were examined in conditional logistic regression models. Furthermore, lipidomics networks were linked to HF risk in a multistep workflow, including machine learning-based identification of the HF-related network clusters, and regression-based discovery of the HF-related lipid patterns within these clusters. If available, significant findings were externally validated in a subsample of the EPIC-Potsdam cohort (2414 at-risk participants, including 87 incident HF cases). After confounder-adjustments, 2 lipids were significantly associated with HF risk in both cohorts: CER (ceramide) 16:0 (relative risk [RR] per SD in PREDIMED, 1.28 [95% CI, 1.13-1.47]) and phosphatidylcholine 32_0 (RR per SD in PREDIMED, 1.23 [95% CI, 1.08-1.41]). Additionally, lipid patterns in several network clusters were associated with HF risk in PREDIMED. Adjusted for standard risk factors, an internally cross-validated score based on the significant HF-related lipids that were identified in the network analysis in PREDIMED was associated with a higher HF risk (20 lipids, RR per SD, 2.33 [95% CI, 1.93%-2.81%). Moreover, a lipid score restricted to the externally available lipids was significantly associated with HF incidence in both cohorts (6 lipids, RRs per SD, 1.30 [95% CI, 1.14-1.47] in PREDIMED, and 1.46 [95% CI, 1.17-1.82] in EPIC-Potsdam). CONCLUSIONS: Our study identified and validated 2 lipid metabolites and several lipidomics patterns as potential novel biomarkers of HF risk. Lipid profiling may capture preclinical molecular alterations that predispose for incident HF. Registration: URL: https://www.isrctn.com/ISRCTN35739639; Unique identifier: ISRCTN35739639.