We aggregated genome-wide genotyping data from 32 European-descent GWAS (74,124 T2D cases, 824,006 controls) imputed to high-density reference panels of >30,000 sequenced haplotypes. Analysis of ˜27M variants (˜21M with minor allele frequency [MAF]<5%), identified 243 genome-wide significant loci (p<5x10-8; MAF 0.02%-50%; odds ratio [OR] 1.04-8.05), 135 not previously-implicated in T2D-predisposition. Conditional analyses revealed 160 additional distinct association signals (p<10-5) within the identified loci. The combined set of 403 T2D-risk signals includes 56 low-frequency (0.5%≤MAF<5%) and 24 rare (MAF<0.5%) index SNPs at 60 loci, including 14 with estimated allelic OR>2. Forty-one of the signals displayed effect-size heterogeneity between BMI-unadjusted and adjusted analyses. Increased sample size and improved imputation led to substantially more precise localisation of causal variants than previously attained: at 51 signals, the lead variant after fine-mapping accounted for >80% posterior probability of association (PPA) and at 18 of these, PPA exceeded 99%. Integration with islet regulatory annotations enriched for T2D association further reduced median credible set size (from 42 variants to 32) and extended the number of index variants with PPA>80% to 73. Although most signals mapped to regulatory sequence, we identified 18 genes as human validated therapeutic targets through coding variants that are causal for disease. Genome wide chip heritability accounted for 18% of T2D-risk, and individuals in the 2.5% extremes of a polygenic risk score generated from the GWAS data differed >9-fold in risk. Our observations highlight how increases in sample size and variant diversity deliver enhanced discovery and single-variant resolution of causal T2D-risk alleles, and the consequent impact on mechanistic insights and clinical translation.

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Vegan or vegetarian diets have been suggested to reduce type 2 diabetes (T2D) risk. However, not much is known on whether variation in the degree of having a plant-based versus animal-based diet may be beneficial for prevention of T2D. We aimed to investigate whether level of adherence to a diet high in plant-based foods and low in animal-based foods is associated with insulin resistance, prediabetes, and T2D. Our analysis included 6798 participants (62.7 ± 7.8 years) from the Rotterdam Study (RS), a prospective population-based cohort in the Netherlands. Dietary intake data were collected with food-frequency questionnaires at baseline of three sub-cohorts of RS (RS-I-1: 1989–1993, RS-II-1: 2000–2001, RS-III-1: 2006–2008). We constructed a continuous plant-based dietary index (range 0–92) assessing adherence to a plant-based versus animal-based diet. Insulin resistance at baseline and follow-up was assessed using homeostasis model assessment of insulin resistance (HOMA-IR). Prediabetes and T2D were collected from general practitioners’ records, pharmacies’ databases, and follow-up examinations in our research center until 2012. We used multivariable linear mixed models to examine association of the index with longitudinal HOMA-IR, and multivariable Cox proportional-hazards regression models to examine associations of the index with risk of prediabetes and T2D. During median 5.7, and 7.3 years of follow-up, we documented 928 prediabetes cases and 642 T2D cases. After adjusting for sociodemographic and lifestyle factors, a higher score on the plant-based dietary index was associated with lower insulin resistance (per 10 units higher score: β = −0.09; 95% CI: − 0.10; − 0.08), lower prediabetes risk (HR = 0.89; 95% CI: 0.81; 0.98), and lower T2D risk [HR = 0.82 (0.73; 0.92)]. After additional adjustment for BMI, associations attenuated and remained statistically significant for longitudinal insulin resistance [β = −0.05 (− 0.06; − 0.04)] and T2D risk [HR = 0.87 (0.79; 0.99)], but no longer for prediabetes risk [HR = 0.93 (0.85; 1.03)]. In conclusion, a more plant-based and less animal-based diet may lower risk of insulin resistance, prediabetes and T2D. These findings strengthen recent dietary recommendations to adopt a more plant-based diet.Clinical Trial Registry number and website NTR6831, http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=6831.Electronic supplementary materialThe online version of this article (10.1007/s10654-018-0414-8) contains supplementary material, which is available to authorized users.

Aims To select a core list of standard outcomes for diabetes to be routinely applied internationally, including patientreported outcomes. Methods We conducted a structured systematic review of outcome measures, focusing on adults with either type 1 or type 2 diabetes. This process was followed by a consensus-driven modified Delphi panel, including a multidisciplinary group of academics, health professionals and people with diabetes. External feedback to validate the set of outcome measures was sought from people with diabetes and health professionals. Results The panel identified an essential set of clinical outcomes related to diabetes control, acute events, chronic complications, health service utilisation, and survival that can be measured using routine administrative data and/or clinical records. Three instruments were recommended for annual measurement of patient-reported outcome measures: the WHO Well-Being Index for psychological well-being; the depression module of the Patient Health Questionnaire for depression; and the Problem Areas in Diabetes scale for diabetes distress. A range of factors related to demographic, diagnostic profile, lifestyle, social support and treatment of diabetes were also identified for case-mix adjustment. Conclusions We recommend the standard set identified in this study for use in routine practice to monitor, benchmark and improve diabetes care. The inclusion of patient-reported outcomes enables people living with diabetes to report directly on their condition in a structured way.

It remains unclear whether endogenous sex hormones (ESH) are associated with risk of type 2 diabetes (T2D) in women. Data of 3,117 postmenopausal women participants of the Rotterdam Study were analyzed to examine whether ESH and sex hormone-binding globulin (SHBG) were associated with the risk of incident T2D. Additionally, we performed a systematic review and meta-analysis of studies assessing the prospective association of ESH and SHBG with T2D in women. During a median follow-up of 11.1 years, we identified 384 incident cases of T2D in the Rotterdam Study. No association was observed between total testosterone (TT) or bioavailable testosterone (BT) with T2D. SHBG was inversely associated with the risk of T2D, whereas total estradiol (TE) was associated with increased risk of T2D. Similarly, in the meta-analysis of 13 population-based prospective studies involving more than 1,912 incident T2D cases, low levels of SHBG and high levels of TE were associated with increased risk of T2D, whereas no associations were found for other hormones. The association of SHBG with T2D did not change by menopause status, whereas the associations of ESH and T2D were based only in postmenopausal women. SHBG and TE are independent risk factors for the development of T2D in women.

ImportanceEpigenetic modifications of the genome, such as DNA methylation and histone modifications, have been reported to play a role in neurodegenerative diseases (ND) such as Alzheimer’s disease (AD) and Parkinson’s disease (PD).ObjectiveTo systematically review studies investigating epigenetic marks in AD or PD.MethodsEleven bibliographic databases (Embase.com, Medline (Ovid), Web-of-Science, Scopus, PubMed, Cinahl (EBSCOhost), Cochrane Central, ProQuest, Lilacs, Scielo and Google Scholar) were searched until July 11th 2016 to identify relevant articles. We included all randomized controlled trials, cohort, case-control and cross-sectional studies in humans that examined associations between epigenetic marks and ND. Two independent reviewers, with a third reviewer available for disagreements, performed the abstract and full text selection. Data was extracted using a pre-designed data collection form.ResultsOf 6,927 searched references, 73 unique case-control studies met our inclusion criteria. Overall, 11,453 individuals were included in this systematic review (2,640 AD and 2,368 PD outcomes). There was no consistent association between global DNA methylation pattern and any ND. Studies reported epigenetic regulation of 31 genes (including cell communication, apoptosis, and neurogenesis genes in blood and brain tissue) in relation to AD and PD. Methylation at the BDNF, SORBS3 and APP genes in AD were the most consistently reported associations. Methylation of α-synuclein gene (SNCA) was also found to be associated with PD. Seven studies reported histone protein alterations in AD and PD.ConclusionMany studies have investigated epigenetics and ND. Further research should include larger cohort or longitudinal studies, in order to identify clinically significant epigenetic changes. Identifying relevant epigenetic changes could lead to interventional strategies in ND.

We conducted an epigenome-wide association study on obesity-related traits. We used data from two prospective, population-based cohort studies: the Rotterdam Study (RS) (2006-2013) and the Atherosclerosis Risk in Communities (ARIC) Study (1990-1992). We used RS (n = 1,454) as the discovery panel and ARIC (n = 2,097) as replication panel. Linear mixed-effect models were used to assess the cross-sectional association between genome-wide DNA methylation in leukocytes with body mass index (BMI) and waist circumference (WC) adjusting for sex, age, smoking, leukocyte proportions, array number and position on array. The two latter were modelled as random effects. Fourteen CpGs were associated with BMI and 26 CpGs with WC in RS after Bonferroni-correction (P < 1.07 × 10-7), of which 12 and 13 CpGs replicated in ARIC Study, respectively. The most significant novel CpGs were located at MSI2 (cg21139312) and LARS2 (cg18030453) and were associated both with BMI and WC. CpGs at BRDT, PSMD1, IFI44L, MAP1A, and MAP3K5 were associated with BMI. CpGs at LGALS3BP, MAP2K3, DHCR24, CPSF4L, and TMEM49 were associated with WC. We report novel associations of methylation at MSI2 and LARS2 with obesity-related traits. These results provide further insight in mechanisms underlying obesity-related traits, which can enable identification of new biomarkers in obesity-related chronic diseases.

We aggregated genome-wide genotyping data from 32 European-descent GWAS (74,124 T2D cases, 824,006 controls) imputed to high-density reference panels of >30,000 sequenced haplotypes. Analysis of ˜27M variants (˜21M with minor allele frequency [MAF]<5%), identified 243 genome-wide significant loci (p<5×10−8; MAF 0.02%-50%; odds ratio [OR] 1.04-8.05), 135 not previously-implicated in T2D-predisposition. Conditional analyses revealed 160 additional distinct association signals (p<10−5) within the identified loci. The combined set of 403 T2D-risk signals includes 56 low-frequency (0.5%≤MAF<5%) and 24 rare (MAF<0.5%) index SNPs at 60 loci, including 14 with estimated allelic OR>2. Forty-one of the signals displayed effect-size heterogeneity between BMI-unadjusted and adjusted analyses. Increased sample size and improved imputation led to substantially more precise localisation of causal variants than previously attained: at 51 signals, the lead variant after fine-mapping accounted for >80% posterior probability of association (PPA) and at 18 of these, PPA exceeded 99%. Integration with islet regulatory annotations enriched for T2D association further reduced median credible set size (from 42 variants to 32) and extended the number of index variants with PPA>80% to 73. Although most signals mapped to regulatory sequence, we identified 18 genes as human validated therapeutic targets through coding variants that are causal for disease. Genome wide chip heritability accounted for 18% of T2D-risk, and individuals in the 2.5% extremes of a polygenic risk score generated from the GWAS data differed >9-fold in risk. Our observations highlight how increases in sample size and variant diversity deliver enhanced discovery and single-variant resolution of causal T2D-risk alleles, and the consequent impact on mechanistic insights and clinical translation.