The identification of MHC class II restricted peptide epitopes is an important goal in immunological research. A number of computational tools have been developed for this purpose, but there is a lack of large-scale systematic evaluation of their performance. Herein, we used a comprehensive dataset consisting of more than 10,000 previously unpublished MHC-peptide binding affinities, 29 peptide/MHC crystal structures, and 664 peptides experimentally tested for CD4+ T cell responses to systematically evaluate the performances of publicly available MHC class II binding prediction tools. While in selected instances the best tools were associated with AUC values up to 0.86, in general, class II predictions did not perform as well as historically noted for class I predictions. It appears that the ability of MHC class II molecules to bind variable length peptides, which requires the correct assignment of peptide binding cores, is a critical factor limiting the performance of existing prediction tools. To improve performance, we implemented a consensus prediction approach that combines methods with top performances. We show that this consensus approach achieved best overall performance. Finally, we make the large datasets used publicly available as a benchmark to facilitate further development of MHC class II binding peptide prediction methods.

BackgroundWhether and how n-3 and n-6 polyunsaturated fatty acids (PUFAs) are related to type 2 diabetes (T2D) is debated. Objectively measured plasma PUFAs can help to clarify these associations.Methods and FindingsPlasma phospholipid PUFAs were measured by gas chromatography among 12,132 incident T2D cases and 15,919 subcohort participants in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct study across eight European countries. Country-specific hazard ratios (HRs) were estimated using Prentice-weighted Cox regression and pooled by random-effects meta-analysis. We also systematically reviewed published prospective studies on circulating PUFAs and T2D risk and pooled the quantitative evidence for comparison with results from EPIC-InterAct. In EPIC-InterAct, among long-chain n-3 PUFAs, α-linolenic acid (ALA) was inversely associated with T2D (HR per standard deviation [SD] 0.93; 95% CI 0.88–0.98), but eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) were not significantly associated. Among n-6 PUFAs, linoleic acid (LA) (0.80; 95% CI 0.77–0.83) and eicosadienoic acid (EDA) (0.89; 95% CI 0.85–0.94) were inversely related, and arachidonic acid (AA) was not significantly associated, while significant positive associations were observed with γ-linolenic acid (GLA), dihomo-GLA, docosatetraenoic acid (DTA), and docosapentaenoic acid (n6-DPA), with HRs between 1.13 to 1.46 per SD. These findings from EPIC-InterAct were broadly similar to comparative findings from summary estimates from up to nine studies including between 71 to 2,499 T2D cases. Limitations included potential residual confounding and the inability to distinguish between dietary and metabolic influences on plasma phospholipid PUFAs.ConclusionsThese large-scale findings suggest an important inverse association of circulating plant-origin n-3 PUFA (ALA) but no convincing association of marine-derived n3 PUFAs (EPA and DHA) with T2D. Moreover, they highlight that the most abundant n6-PUFA (LA) is inversely associated with T2D. The detection of associations with previously less well-investigated PUFAs points to the importance of considering individual fatty acids rather than focusing on fatty acid class.

Aims/hypothesis Recent evidence suggests that oxidative stress may contribute to the pathogenesis of type 2 diabetes. The diet, and especially fruit and vegetables, contains a variety of compounds with antioxidant activity, which may have cumulative/synergistic antioxidant effects. The total antioxidant capacity, an index derived from dietary intake, is a single estimate of antioxidant capacity from all dietary antioxidants. The main aim of this study was to investigate the relationship between total antioxidant capacity and risk of type 2 diabetes. Methods Among 64,223 women (mean age 52 ± 7 years) from the French E3N-European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, 1751 women had validated type 2 diabetes during 15 years of follow-up. The total antioxidant capacity was estimated with the ferric ionreducing antioxidant power (FRAP) method. Adjusted Cox proportional hazards regression models were used to calculate HRs and 95% CIs for the associations between total antioxidant capacity and type 2 diabetes risk, adjusted for potential confounders.Results In multivariable models, higher levels of total antioxidant capacity were associated with a lower risk of type 2 diabetes. Compared with women in the lowest quintile, women in the third, fourth and fifth quintiles for total antioxidant capacity had HRs of 0.74 (95% CI 0.63, 0.86), 0.70 (95% CI 0.59, 0.83) and 0.73 (95% CI 0.60, 0.89), respectively. The inverse association between total antioxidant capacity and risk of type 2 diabetes was linear up to values of 15 mmol/day, after which the effect reached a plateau. Conclusions/interpretation Our findings suggest that the total antioxidant capacity may play an important role in reducing the risk of type 2 diabetes in middle-aged women. More studies are warranted to better understand the biological mechanisms underlying this inverse association.

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Diabetic retinopathy is a microvascular complication of diabetes that threatens all individuals with diabetes, leading to vision loss or blindness if left untreated. It is frequently associated with diabetic macular edema, which can occur at any point during the development of diabetic retinopathy. The key factors known to lead to its development include hyperglycemia, hypertension, and the duration of diabetes. Though the diet is important in the development of diabetes, its role in diabetic retinopathy has not been clearly identified. In this systematic review, we aimed to identify, summarize and interpret the literature on the association between the diet and dietary intakes of specific foods, nutrients, and food groups, and the risk of diabetic retinopathy. We searched PubMed and Web of Science for English-language studies evaluating the association between the dietary intake of individual foods, macro or micronutrients, dietary supplements, and dietary patterns and their association with retinopathy or macular edema. After reviewing potentially relevant abstracts and, when necessary, full texts, we identified 27 relevant studies. Identified studies investigated intakes of fruit, vegetables, fish, milk, carbohydrates, fibre, fat, protein, salt, potassium, vitamins C, D, and E, carotenoids, dietary supplements, green tea and alcohol. Studies suggest that adherence to the Mediterranean diet and high fruit, vegetable and fish intake may protect against the development of diabetic retinopathy, although the evidence is limited. Studies concerning other aspects of the diet are not in agreement. The role of the diet in the development of diabetic retinopathy is an area that warrants more attention.

Activation of CD4؉ epitopes, four of them also stimulate CD8 ؉ T cells in a statistically significant manner. Furthermore, we assessed these CD4 ؉ T-cell responses during the memory phase of LCMV Armstrong infection and after infection with a chronic strain of LCMV and determined that a subset of the responses could be detected under these different conditions. This is the first example of a broad repertoire of shared epitopes between CD4 ؉ and CD8 ؉ T cells in the context of viral infection. These findings demonstrate that immunodominance is a complex phenomenon in the context of helper responses.

Background: Gene-diet interactions have been reported to contribute to the development of type 2 diabetes (T2D). However, to our knowledge, few examples have been consistently replicated to date.Objective: We aimed to identify existing evidence for gene-macronutrient interactions and T2D and to examine the reported interactions in a large-scale study.Design: We systematically reviewed studies reporting gene-macronutrient interactions and T2D. We searched the MEDLINE, Human Genome Epidemiology Network, and WHO International Clinical Trials Registry Platform electronic databases to identify studies published up to October 2015. Eligibility criteria included assessment of macronutrient quantity (e.g., total carbohydrate) or indicators of quality (e.g., dietary fiber) by use of self-report or objective biomarkers of intake. Interactions identified in the review were subsequently examined in the EPIC (European Prospective Investigation into Cancer)-InterAct case-cohort study (n = 21,148, with 9403 T2D cases; 8 European countries). Prentice-weighted Cox regression was used to estimate country-specific HRs, 95% CIs, and P-interaction values, which were then pooled by random-effects meta-analysis. A primary model was fitted by using the same covariates as reported in the published studies, and a second model adjusted for additional covariates and estimated the effects of isocaloric macronutrient substitution.Results: Thirteen observational studies met the eligibility criteria (n < 1700 cases). Eight unique interactions were reported to be significant between macronutrients [carbohydrate, fat, saturated fat, dietary fiber, and glycemic load derived from self-report of dietary intake and circulating n–3 (ω-3) polyunsaturated fatty acids] and genetic variants in or near transcription factor 7–like 2 (TCF7L2), gastric inhibitory polypeptide receptor (GIPR), caveolin 2 (CAV2), and peptidase D (PEPD) (P-interaction < 0.05). We found no evidence of interaction when we tried to replicate previously reported interactions. In addition, no interactions were detected in models with additional covariates.Conclusions: Eight gene-macronutrient interactions were identified for the risk of T2D from the literature. These interactions were not replicated in the EPIC-InterAct study, which mirrored the analyses undertaken in the original reports. Our findings highlight the importance of independent replication of reported interactions.

BackgroundCombinations of multiple fatty acids may influence cardiometabolic risk more than single fatty acids. The association of a combination of fatty acids with incident type 2 diabetes (T2D) has not been evaluated.Methods and findingsWe measured plasma phospholipid fatty acids by gas chromatography in 27,296 adults, including 12,132 incident cases of T2D, over the follow-up period between baseline (1991–1998) and 31 December 2007 in 8 European countries in EPIC-InterAct, a nested case-cohort study. The first principal component derived by principal component analysis of 27 individual fatty acids (mole percentage) was the main exposure (subsequently called the fatty acid pattern score [FA-pattern score]). The FA-pattern score was partly characterised by high concentrations of linoleic acid, stearic acid, odd-chain fatty acids, and very-long-chain saturated fatty acids and low concentrations of γ-linolenic acid, palmitic acid, and long-chain monounsaturated fatty acids, and it explained 16.1% of the overall variability of the 27 fatty acids. Based on country-specific Prentice-weighted Cox regression and random-effects meta-analysis, the FA-pattern score was associated with lower incident T2D. Comparing the top to the bottom fifth of the score, the hazard ratio of incident T2D was 0.23 (95% CI 0.19–0.29) adjusted for potential confounders and 0.37 (95% CI 0.27–0.50) further adjusted for metabolic risk factors. The association changed little after adjustment for individual fatty acids or fatty acid subclasses. In cross-sectional analyses relating the FA-pattern score to metabolic, genetic, and dietary factors, the FA-pattern score was inversely associated with adiposity, triglycerides, liver enzymes, C-reactive protein, a genetic score representing insulin resistance, and dietary intakes of soft drinks and alcohol and was positively associated with high-density-lipoprotein cholesterol and intakes of polyunsaturated fat, dietary fibre, and coffee (p < 0.05 each). Limitations include potential measurement error in the fatty acids and other model covariates and possible residual confounding.ConclusionsA combination of individual fatty acids, characterised by high concentrations of linoleic acid, odd-chain fatty acids, and very long-chain fatty acids, was associated with lower incidence of T2D. The specific fatty acid pattern may be influenced by metabolic, genetic, and dietary factors.