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Aims/hypothesis: A precision medicine approach in type 2 diabetes could enhance targeting specific glucose-lowering therapies to individual patients most likely to benefit. We aimed to use the recently developed Bayesian causal forest (BCF) method to develop and validate an individualised treatment selection algorithm for two major type 2 diabetes drug classes, sodium-glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1-RA)., Methods: We designed a predictive algorithm using BCF to estimate individual-level conditional average treatment effects for 12-month glycaemic outcome (HbA 1c ) between SGLT2i and GLP1-RA, based on routine clinical features of 46,394 people with type 2 diabetes in primary care in England (Clinical Practice Research Datalink; 27,319 for model development, 19,075 for hold-out validation), with additional external validation in 2252 people with type 2 diabetes from Scotland (SCI-Diabetes [Tayside & Fife]). Differences in glycaemic outcome with GLP1-RA by sex seen in clinical data were replicated in clinical trial data (HARMONY programme: liraglutide [n=389] and albiglutide [n=1682]). As secondary outcomes, we evaluated the impacts of targeting therapy based on glycaemic response on weight change, tolerability and longer-term risk of new-onset microvascular complications, macrovascular complications and adverse kidney events., Results: Model development identified marked heterogeneity in glycaemic response, with 4787 (17.5%) of the development cohort having a predicted HbA 1c benefit >3 mmol/mol (>0.3%) with SGLT2i over GLP1-RA and 5551 (20.3%) having a predicted HbA 1c benefit >3 mmol/mol with GLP1-RA over SGLT2i. Calibration was good in hold-back validation, and external validation in an independent Scottish dataset identified clear differences in glycaemic outcomes between those predicted to benefit from each therapy. Sex, with women markedly more responsive to GLP1-RA, was identified as a major treatment effect modifier in both the UK observational datasets and in clinical trial data: HARMONY-7 liraglutide (GLP1-RA): 4.4 mmol/mol (95% credible interval [95% CrI] 2.2, 6.3) (0.4% [95% CrI 0.2, 0.6]) greater response in women than men. Targeting the two therapies based on predicted glycaemic response was also associated with improvements in short-term tolerability and long-term risk of new-onset microvascular complications., Conclusions/interpretation: Precision medicine approaches can facilitate effective individualised treatment choice between SGLT2i and GLP1-RA therapies, and the use of routinely collected clinical features for treatment selection could support low-cost deployment in many countries., (© 2024. The Author(s).)

Background: Heterogeneity in type 2 diabetes can be represented by a tree-like graph structure by use of reversed graph-embedded dimensionality reduction. We aimed to examine whether this approach can be used to stratify key pathophysiological components and diabetes-related complications during longitudinal follow-up of individuals with recent-onset type 2 diabetes., Methods: For this cohort analysis, 927 participants aged 18-69 years from the German Diabetes Study (GDS) with recent-onset type 2 diabetes were mapped onto a previously developed two-dimensional tree based on nine simple clinical and laboratory variables, residualised for age and sex. Insulin sensitivity was assessed by a hyperinsulinaemic-euglycaemic clamp, insulin secretion was assessed by intravenous glucose tolerance test, hepatic lipid content was assessed by 1 H magnetic resonance spectroscopy, serum interleukin (IL)-6 and IL-18 were assessed by ELISA, and peripheral and autonomic neuropathy were assessed by functional and clinical measures. Participants were followed up for up to 16 years. We also investigated heart failure and all-cause mortality in 794 individuals with type 2 diabetes undergoing invasive coronary diagnostics from the Ludwigshafen Risk and Cardiovascular Health (LURIC) cohort., Findings: There were gradients of clamp-measured insulin sensitivity (both dimensions: p<0·0001) and insulin secretion (p dim1 <0·0001, p dim2 =0·00097) across the tree. Individuals in the region with the lowest insulin sensitivity had the highest hepatic lipid content (n=205, p dim1 <0·0001, p dim2 =0·037), pro-inflammatory biomarkers (IL-6: n=348, p dim1 <0·0001, p dim2 =0·013; IL-18: n=350, p dim1 <0·0001, p dim2 =0·38), and elevated cardiovascular risk (n events =143, p dim1 =0·14, p dim2 <0·00081), whereas individuals positioned in the branch with the lowest insulin secretion were more prone to require insulin therapy (n events =85, p dim1 =0·032, p dim2 =0·12) and had the highest risk of diabetic sensorimotor polyneuropathy (n events =184, p dim1 =0·012, p dim2 =0·044) and cardiac autonomic neuropathy (n events =118, p dim1 =0·0094, p dim2 =0·06). In the LURIC cohort, all-cause mortality was highest in the tree branch showing insulin resistance (n events =488, p dim1 =0·12, p dim2 =0·0032). Significant gradients differentiated individuals having heart failure with preserved ejection fraction from those who had heart failure with reduced ejection fraction., Interpretation: These data define the pathophysiological underpinnings of the tree structure, which has the potential to stratify diabetes-related complications on the basis of routinely available variables and thereby expand the toolbox of precision diabetes diagnosis., Funding: German Diabetes Center, German Federal Ministry of Health, Ministry of Culture and Science of the state of North Rhine-Westphalia, German Federal Ministry of Education and Research, German Diabetes Association, German Center for Diabetes Research, European Community, German Research Foundation, and Schmutzler Stiftung., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Diabetic retinopathy (DR) is a major sight-threatening microvascular complication in individuals with diabetes. Systemic inflammation combined with oxidative stress is thought to capture most of the complexities involved in the pathology of diabetic retinopathy. A high level of neutrophil-lymphocyte ratio (NLR) is an indicator of abnormal immune system activity. Current estimates of the association of NLR with diabetes and its complications are almost entirely derived from cross-sectional studies, suggesting that the nature of the reported association may be more diagnostic than prognostic. Therefore, in the present study, we examined the utility of NLR as a biomarker to predict the incidence of DR in the Scottish population., Methods: The incidence of DR was defined as the time to the first diagnosis of R1 or above grade in the Scottish retinopathy grading scheme from type 2 diabetes diagnosis. The effect of NLR and its interactions were explored using a competing risks survival model adjusting for other risk factors and accounting for deaths. The Fine and Gray subdistribution hazard model (FGR) was used to predict the effect of NLR on the incidence of DR., Results: We analysed data from 23,531 individuals with complete covariate information. At 10 years, 8416 (35.8%) had developed DR and 2989 (12.7%) were lost to competing events (death) without developing DR and 12,126 individuals did not have DR. The median (interquartile range) level of NLR was 2.04 (1.5 to 2.7). The optimal NLR cut-off value to predict retinopathy incidence was 3.04. After accounting for competing risks at 10 years, the cumulative incidence of DR and deaths without DR were 50.7% and 21.9%, respectively. NLR was associated with incident DR in both Cause-specific hazard (CSH = 1.63; 95% CI: 1.28-2.07) and FGR models the subdistribution hazard (sHR = 2.24; 95% CI: 1.70-2.94). Both age and HbA 1c were found to modulate the association between NLR and the risk of DR., Conclusions: The current study suggests that NLR has a promising potential to predict DR incidence in the Scottish population, especially in individuals less than 65 years and in those with well-controlled glycaemic status., (© 2023. The Author(s).)

Type 2 diabetes (T2D) is a complex chronic disease characterized by considerable phenotypic heterogeneity. In this study, we applied a reverse graph embedding method to routinely collected data from 23,137 Scottish patients with newly diagnosed diabetes to visualize this heterogeneity and used partitioned diabetes polygenic risk scores to gain insight into the underlying biological processes. Overlaying risk of progression to outcomes of insulin requirement, chronic kidney disease, referable diabetic retinopathy and major adverse cardiovascular events, we show how these risks differ by patient phenotype. For example, patients at risk of retinopathy are phenotypically different from those at risk of cardiovascular events. We replicated our findings in the UK Biobank and the ADOPT clinical trial, also showing that the pattern of diabetes drug monotherapy response differs for different drugs. Overall, our analysis highlights how, in a European population, underlying phenotypic variation drives T2D onset and affects subsequent diabetes outcomes and drug response, demonstrating the need to incorporate these factors into personalized treatment approaches for the management of T2D., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: India was one of the countries to institute strict measures for Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) control in the early phase. Since, then, the epidemic growth trajectory was slow before registering an explosion of cases due to local cluster transmissions., Methods: We estimated the growth rate and doubling time of SARS-CoV-2 for India and high burden states using crowdsourced time series data. Further, we also estimated the Basic Reproductive Number (R0) and Time-dependent Reproductive number (Rt) using serial intervals from the data. We compared the R0 estimated from five different methods and R0 from SB was further used in the analysis. We modified standard Susceptible-Infectious-Recovered (SIR) models to SIR/Death (SIRD) model to accommodate deaths using R0 with the sequential Bayesian method for simulation in SIRD models., Results: On average, 2.8 individuals were infected by an index case. The mean serial interval was 3.9 days. The R0 estimated from different methods ranged from 1.43 to 1.85. The mean time to recovery was 14 ± 5.3 days. The daily epidemic growth rate of India was 0.16 [95% CI; 0.14, 0.17] with a doubling time of 4.30 days [95% CI; 3.96, 4.70]. From the SIRD model, it can be deduced that the peak of SARS-CoV-2 in India will be around mid-July to early August 2020 with around 12.5% of the population likely to be infected at the peak time., Conclusion: The pattern of spread of SARS-CoV-2 in India is suggestive of community transmission. There is a need to increase funds for infectious disease research and epidemiologic studies. All the current gains may be reversed if air travel and social mixing resume rapidly. For the time being, these must be resumed only in a phased manner and should be back to normal levels only after we are prepared to deal with the disease with efficient tools like vaccines or medicine., Key Points: ., Question: What are the estimates of infectious disease parameters of early phase of novel SARS-CoV-2 epidemic in India?, Findings: Incidence pattern SARS-CoV-2 shows possible evidence of community transmission. However, the estimated Basic Reproductive Number (R0) is relatively lower than those observed in high burden regions (range 1.43-1.85). Our simulation using susceptible-infectious-recovered/death model shows that peak of SARS-CoV-2 in India is farther than currently projected and is likely to affect around 12.5% of population., Meaning: The lower estimated R0 is indicative of the effectiveness of early social distancing measures and lockdown. Premature relaxation of the current control measures may result in large numbers of cases in India., Competing Interests: The authors declare they have no conflicts of interest., (© 2020 The Authors. Published by Atlantis Press International B.V.)

Introduction: Type 2 diabetes is characterized by considerable heterogeneity in its etiopathogenesis and clinical presentation. We aimed to identify clusters of type 2 diabetes in Asian Indians and to look at the clinical implications and outcomes of this clustering., Research Design and Methods: From a network of 50 diabetes centers across nine states of India, we selected 19 084 individuals with type 2 diabetes (aged 10-97 years) with diabetes duration of less than 5 years at the time of first clinic visit and performed k-means clustering using the following variables: age at diagnosis, body mass index, waist circumference, glycated hemoglobin, serum triglycerides, serum high-density lipoprotein cholesterol and C peptide (fasting and stimulated). This was then validated in a national epidemiological data set of representative individuals from 15 states across India., Results: We identified four clusters of patients, differing in phenotypic characteristics as well as disease outcomes: cluster 1 (Severe Insulin Deficient Diabetes, SIDD), cluster 2 (Insulin Resistant Obese Diabetes, IROD), cluster 3 (Combined Insulin Resistant and Deficient Diabetes, CIRDD) and cluster 4 (Mild Age-Related Diabetes, MARD). While SIDD and MARD are similar to clusters reported in other populations, IROD and CIRDD are novel clusters. Cox proportional hazards showed that SIDD had the highest hazards for developing retinopathy, followed by CIRDD, while CIRDD had the highest hazards for kidney disease., Conclusions: Compared with previously reported clustering, we show two novel subgroups of type 2 diabetes in the Asian Indian population with important implications for prognosis and management. The coexistence of insulin deficiency and insulin resistance seems to be peculiar to the Asian Indian population and is associated with an increased risk of microvascular complications., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

Background: The pathophysiology of type 2 diabetes differs markedly by ethnicity., Purpose: A systematic review and meta-analysis was conducted to assess the impact of ethnicity on the glucose-lowering efficacy of the newer oral agents, sodium-glucose cotransporter 2 inhibitors (SGLT-2i), glucagon-like peptide 1 receptor agonists (GLP-1RA), and dipeptidyl peptidase 4 inhibitors (DPP-4i), using evidence from randomized clinical trials (RCTs)., Data Sources: A literature search was conducted in PubMed of all randomized, placebo-controlled trials of DPP-4i, SGLT-2i, and GLP-1RA. The search strategy was developed based on Medical Subject Headings (MeSH) terms and keywords., Study Selection: A total of 64 studies that qualified for meta-analysis after full-text review based on predefined inclusion and exclusion criteria-RCTs with at least 50 patients in each arm, >70% of population from Asian or white group, duration ≥24 weeks, and publication up to March 2019-were selected for systematic review and meta-analysis., Data Extraction: Data extraction was done for aggregated study-level data by two independent researchers. Absolute changes in HbA 1c (%) from baseline to 24 weeks between the drug and placebo were considered as the primary end point of the study., Data Synthesis: Change in HbA 1c was evaluated by computing mean differences and 95% CIs between treatment and placebo arms., Limitations: The study is based on summarized data and could not be separated based on East Asians and South Asians., Conclusions: The glucose-lowering efficacy of SGLT-2i, and to a lesser extent DPP-4i, was greater in studies of predominantly Asian ethnicity compared with studies of predominantly white ethnicity. There was no difference seen by ethnicity for GLP-1RA., (© 2020 by the American Diabetes Association.)