Swedish Research Council, European Research Council, Vinnova, Academy of Finland, Novo Nordisk Foundation, Scania University Hospital, Sigrid Juselius Foundation, Innovative Medicines Initiative 2 Joint Undertaking, Vasa Hospital district, Jakobstadsnejden Heart Foundation, Folkhälsan Research Foundation, Ollqvist Foundation, and Swedish Foundation for Strategic Research.

Betatrophin has recently been described as a key hormone to stimulate beta-cell mass expansion in response to insulin resistance and obesity in mice. The finding has generated an interest in the development of antidiabetic drugs with betatrophin as the active component. However, the circulating levels of betatrophin in patients with type 2 diabetes are not well known. Betatrophin concentrations in plasma of 27 type 2 diabetes patients and 18 gender-, age-, and BMI-matched controls were measured. Study participants were characterized with regard to BMI, waist and hip circumference, blood pressure, and fasting plasma blood lipids, creatinine, glucose, HbA1c, and C-peptide. HOMA2 indices were calculated. Betatrophin was 40% higher in patients with type 2 diabetes (893 ± 80 versus 639 ± 66 pg/mL). Betatrophin positively correlated with age in the controls and with HbA1c in the type 2 diabetes patients. All study participants were insulin resistant with mean HOMA2B IR in both groups exceeding 2 and HOMA2%S < 50%. Control individuals had impaired fasting glucose concentrations. In this report on betatrophin concentrations in type 2 diabetes and insulin resistance, elevated betatrophin levels were measured in the patients with type 2 diabetes. Future studies are clearly needed to delineate the exact role, if any, of betatrophin in regulating human beta-cell mass.

Aims/hypothesis Excessive weight is a risk factor for type 2 diabetes, but its role in the promotion of autoimmune diabetes is not clear. We investigated the risk of latent autoimmune diabetes in adults (LADA) in relation to overweight/obesity in two large population-based studies. Methods Analyses were based on incident cases of LADA (n = 425) and type 2 diabetes (n = 1420), and 1704 randomly selected control participants from a Swedish case-control study and prospective data from the Norwegian HUNT Study including 147 people with LADA and 1,012,957 person-years of follow-up (1984-2008). We present adjusted ORs and HRs with 95% CI. Results In the Swedish data, obesity was associated with an increased risk of LADA (OR 2.93, 95% CI 2.17, 3.97), which was even stronger for type 2 diabetes (OR 18.88, 95% CI 14.29, 24.94). The association was stronger in LADA with low GAD antibody (GADA;

Swedish type 2 diabetic patients in this large sample from Uppsala county required steady annual amounts of outpatient care and increasing amounts of inpatient care during 2000-2004. The associated costs in 2004 were substantial, with inpatient care identified as the most important component.

Research in context Evidence before this studyThe current diabetes classification into T1D and T2D relies primarily on presence (T1D) or absence (T2D) of autoantibodies against pancreatic islet beta cell autoantigens and age at diagnosis (earlier for T1D). With this approach 75-85% of patients are classified as T2D. A third subgroup, Latent Autoimmune Diabetes in Adults (LADA,<10%), is defined by presence of autoantibodies against glutamate decarboxylase (GADA) with onset in adult age. In addition, several rare monogenic forms of diabetes have been described, including Maturity Onset Diabetes of the Young (MODY) and neonatal diabetes. This information is provided by national guidelines (ADA,WHO, IDF , Diabetes UK etc) but has not been much updated during the past 20 years and very few attempts have been made to explore heterogeneity of T2D. A topological analysis of potential T2D subgroups using electronic health records was published in 2015 but this information has not been implemented in the clinic. Added value of this studyHere we applied a data-driven cluster analysis of 5 simple variables measured at diagnosis in 4 independent cohorts of newly-diagnosed diabetic patients (N=14755) and identified 5 replicable clusters of diabetes patients, with significantly different patient characteristics and risk of diabetic complications. Particularly, individuals in the most insulin-resistant cluster 3 had significantly higher risk of diabetic kidney disease. Implications of the available evidenceThis new sub-stratification may help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/186387 doi: bioRxiv preprint first posted online Sep. 8, 2017; Abstract Background