Jana Nano

Abstract Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes 1,2 and molecular mechanisms that are often specific to cell type 3,4 . Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance ( P < 5 × 10 −8 ) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores 5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

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 .

AIMS: To select a core list of standard outcomes for diabetes to be routinely applied internationally, including patient-reported 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.