Aim/hypothesis Five subgroups were described in European diabetes patients using a data driven machine learning approach on commonly measured variables. We aimed to test the applicability of this phenotyping in Indian individuals with young-onset type 2 diabetes. Methods We applied the European-derived centroids to Indian individuals with type 2 diabetes diagnosed before 45 years of age from the WellGen cohort (n = 1612). We also applied de novo k-means clustering to the WellGen cohort to validate the subgroups. We then compared clinical and metabolic-endocrine characteristics and the complication rates between the subgroups. We also compared characteristics of the WellGen subgroups with those of two young European cohorts, ANDIS (n = 962) and DIREVA (n = 420). Subgroups were also assessed in two other Indian cohorts, Ahmedabad (n = 187) and PHENOEINDY-2 (n = 205). Results Both Indian and European young-onset type 2 diabetes patients were predominantly classified into severe insulin-deficient (SIDD) and mild obesity-related (MOD) subgroups, while the severe insulin-resistant (SIRD) and mild age-related (MARD) subgroups were rare. In WellGen, SIDD (53%) was more common than MOD (38%), contrary to findings in Europeans (Swedish 26% vs 68%, Finnish 24% vs 71%, respectively). A higher proportion of SIDD compared with MOD was also seen in Ahmedabad (57% vs 33%) and in PHENOEINDY-2 (67% vs 23%). Both in Indians and Europeans, the SIDD subgroup was characterised by insulin deficiency and hyperglycaemia, MOD by obesity, SIRD by severe insulin resistance and MARD by mild metabolic-endocrine disturbances. In WellGen, nephropathy and retinopathy were more prevalent in SIDD compared with MOD while the latter had higher prevalence of neuropathy. Conclusions /interpretation Our data identified insulin deficiency as the major driver of type 2 diabetes in young Indians, unlike in young European individuals in whom obesity and insulin resistance predominate. Our results provide useful clues to pathophysiological mechanisms and susceptibility to complications in type 2 diabetes in the young Indian population and suggest a need to review management strategies. Graphical abstract

Background: Epigenetics research is progressing in basic, pre-clinical and clinical studies using various model systems. Hence, updating the knowledge and integration of biological data emerging from in silico, in vitro and in vivo studies for different epigenetic factors is essential. Moreover, new drugs are being discovered which target various epigenetic proteins, tested in pre-clinical studies, clinical trials and approved by the FDA. It brings distinct challenges as well as opportunities to update the existing HIstome database for implementing and applying enormous data for biomedical research. Results: HISTome2 focuses on the sub-classification of histone proteins as variants and isoforms, post-translational modifications (PTMs) and modifying enzymes for humans (Homo sapiens), rat (Rattus norvegicus) and mouse (Mus musculus) on one interface for integrative analysis. It contains 232, 267 and 350 entries for histone proteins (noncanonical/variants and canonical/isoforms), PTMs and modifying enzymes respectively for human, rat, and mouse. Around 200 EpiDrugs for various classes of epigenetic modifiers, their clinical trial status, and pharmacological relevance have been provided in HISTome2. The additional features like 'Clustal omega' for multiple sequence alignment, link to 'FireBrowse' to visualize TCGA expression data and 'TargetScanHuman' for miRNA targets have been included in the database. Conclusion: The information for multiple organisms and EpiDrugs on a common platform will accelerate the understanding and future development of drugs. Overall, HISTome2 has significantly increased the extent and diversity of its content which will serve as a 'knowledge Infobase' for biologists, pharmacologists, and clinicians. HISTome2: The HISTone Infobase is freely available on http://www.actre c.gov.in/histo me2/.

Objective: To explore the perceptions of adolescents and their caregivers on drivers of diet and physical activity in rural India in the context of ongoing economic, social and nutrition transition. Design: A qualitative study comprising eight focus group discussions (FGD) on factors affecting eating and physical activity patterns, perceptions of health and decision-making on food preparation. Setting: Villages approximately 40–60 km from the city of Pune in the state of Maharashtra, India. Participants: Two FGD with adolescents aged 10–12 years (n 20), two with 15- to 17- year-olds (n 18) and four with their mothers (n 38). Results: Dietary behaviour and physical activity of adolescents were perceived to be influenced by individual and interpersonal factors including adolescent autonomy, parental influence and negotiations between adolescents and caregivers. The home food environment, street food availability, household food security and exposure to television and digital media were described as influencing behaviour. The lack of facilities and infrastructure was regarded as barriers to physical activity as were insufficient resources for public transport, safe routes for walking and need for cycles, particularly for girls. It was suggested that schools take a lead role in providing healthy foods and that governments invest in facilities for physical activity. Conclusions: In this transitioning environment, that is representative of many parts of India and other Lower Middle Income Countries (LMIC), people perceive a need for interventions to improve adolescent diet and physical activity. Caregivers clearly felt that they had a stake in adolescent health, and so we would recommend the involvement of both adolescents and caregivers in intervention design.