IntroductionType 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 methodsFrom 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.ResultsWe 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.ConclusionsCompared 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.

The most common side effect of angiotensin converting enzyme inhibitor drugs (ACEi) is a cough. We conducted a genome wide association study (GWAS) of ACEi-induced cough among 7,080 subjects of diverse ancestries in the eMERGE network. Cases were subjects diagnosed with ACEi-induced cough. Controls were subjects with at least 6 months of ACEi use and no cough. A GWAS (1,595 cases and 5,485 controls) identified associations on chromosome 4 in an intron of KCNIP4. The strongest association was at rs145489027 (MAF=0.33, OR=1.3 [95%CI: 1.2–1.4], p=1.0×10−8). Replication for six SNPs in KCNIP4 was tested in a second eMERGE population (n=926) and in the GoDARTS cohort (n=4,309). Replication was observed at rs7675300 (OR=1.32 [1.01–1.70], p=0.04) in eMERGE and rs16870989 and rs1495509 (OR=1.15 [1.01–1.30], p=0.03 for both) in GoDARTS. The combined association at rs1495509 was significant (OR=1.23 [1.15–1.32], p=1.9×10−9). These results indicate that SNPs in KCNIP4 may modulate ACEi-induced cough risk.

BackgroundThere are few observational studies evaluating the risk of AKI in people with type 2 diabetes, and even fewer simultaneously investigating AKI and CKD in this population. This limits understanding of the interplay between AKI and CKD in people with type 2 diabetes compared with the nondiabetic population.MethodsIn this retrospective, cohort study of participants with or without type 2 diabetes, we used electronic healthcare records to evaluate rates of AKI and various statistical methods to determine their relationship to CKD status and further renal function decline.ResultsWe followed the cohort of 16,700 participants (9417 with type 2 diabetes and 7283 controls without diabetes) for a median of 8.2 years. Those with diabetes were more likely than controls to develop AKI (48.6% versus 17.2%, respectively) and have preexisting CKD or CKD that developed during follow-up (46.3% versus 17.2%, respectively). In the absence of CKD, the AKI rate among people with diabetes was nearly five times that of controls (121.5 versus 24.6 per 1000 person-years). Among participants with CKD, AKI rate in people with diabetes was more than twice that of controls (384.8 versus 180.0 per 1000 person-years after CKD diagnostic date, and 109.3 versus 47.4 per 1000 person-years before CKD onset in those developing CKD after recruitment). Decline in eGFR slope before AKI episodes was steeper in people with diabetes versus controls. After AKI episodes, decline in eGFR slope became steeper in people without diabetes, but not among those with diabetes and preexisting CKD.ConclusionsPatients with diabetes have significantly higher rates of AKI compared with patients without diabetes, and this remains true for individuals with preexisting CKD.

increased expression of APP and BACE1 and the production of Aβ peptides, whereas exogenous NO reduces APP, BACE1, and Aβ levels in cerebral microvessels (23). Thus, there appears to be an interesting reciprocal connection between BACE1, APP processing, Aβ levels, and NO bioavailability. Hyperglycemia and hyperlipidemia increase BACE1 activity and Aβ peptide levels in tissues and plasma (24, 25), linking key metabolic disease markers with increased amyloid processing. Consequently, we hypothesized that the development of type 2 diabetes (T2D) and/or obesity elevates circulating Aβ levels, which in turn drives vascular dysfunction. We tested this hypothesis in 3 ways: firstly, by reducing BACE1 activity genetically and pharmacologically in mice and ascertaining how this modified diet-induced endothelial dysfunction; secondly, by increasing plasma Aβ levels, indirectly through overexpression of mutant human APP genes and directly by Aβ peptide infusion, to promote vascular dysfunction in mice; and thirdly, by cross-sectionally examining the association between plasma Aβ levels and endothelial function in patients with T2D.

AimsA genetic variant in LILRB5 (leukocyte immunoglobulin-like receptor subfamily-B) (rs12975366: T > C: Asp247Gly) has been reported to be associated with lower creatine phosphokinase (CK) and lactate dehydrogenase (LDH) levels. Both biomarkers are released from injured muscle tissue, making this variant a potential candidate for susceptibility to muscle-related symptoms. We examined the association of this variant with statin intolerance ascertained from electronic medical records in the GoDARTS study.Methods and resultsIn the GoDARTS cohort, the LILRB5 Asp247 variant was associated with statin intolerance (SI) phenotypes; one defined as having raised CK and being non-adherent to therapy [odds ratio (OR) 1.81; 95% confidence interval (CI): 1.34–2.45] and the other as being intolerant to the lowest approved dose of a statin before being switched to two or more other statins (OR 1.36; 95% CI: 1.07–1.73). Those homozygous for Asp247 had increased odds of developing both definitions of intolerance. Importantly the second definition did not rely on CK elevations. These results were replicated in adjudicated cases of statin-induced myopathy in the PREDICTION-ADR consortium (OR1.48; 95% CI: 1.05–2.10) and for the development of myalgia in the JUPITER randomized clinical trial of rosuvastatin (OR1.35, 95% CI: 1.10–1.68). A meta-analysis across the studies showed a consistent association between Asp247Gly and outcomes associated with SI (OR1.34; 95% CI: 1.16–1.54).ConclusionThis study presents a novel immunogenetic factor associated with statin intolerance, an important risk factor for cardiovascular outcomes. The results suggest that true statin-induced myalgia and non-specific myalgia are distinct, with a potential role for the immune system in their development. We identify a genetic group that is more likely to be intolerant to their statins.

Objectives To identify and assess the quality and accuracy of prognostic models for nephropathy and to validate these models in external cohorts of people with type 2 diabetes. Design Systematic review and external validation. Data sources PubMed and Embase. Eligibility criteria Studies describing the development of a model to predict the risk of nephropathy, applicable to people with type 2 diabetes. Methods Screening, data extraction, and risk of bias assessment were done in duplicate. Eligible models were externally validated in the Hoorn Diabetes Care System (DCS) cohort (n=11 450) for the same outcomes for which they were developed. Risks of nephropathy were calculated and compared with observed risk over 2, 5, and 10 years of follow-up. Model performance was assessed based on intercept adjusted calibration and discrimination (Harrell’s C statistic). Results 41 studies included in the systematic review reported 64 models, 46 of which were developed in a population with diabetes and 18 in the general population including diabetes as a predictor. The predicted outcomes included albuminuria, diabetic kidney disease, chronic kidney disease (general population), and end stage renal disease. The reported apparent discrimination of the 46 models varied considerably across the different predicted outcomes, from 0.60 (95% confidence interval 0.56 to 0.64) to 0.99 (not available) for the models developed in a diabetes population and from 0.59 (not available) to 0.96 (0.95 to 0.97) for the models developed in the general population. Calibration was reported in 31 of the 41 studies, and the models were generally well calibrated. 21 of the 64 retrieved models were externally validated in the Hoorn DCS cohort for predicting risk of albuminuria, diabetic kidney disease, and chronic kidney disease, with considerable variation in performance across prediction horizons and models. For all three outcomes, however, at least two models had C statistics >0.8, indicating excellent discrimination. In a secondary external validation in GoDARTS (Genetics of Diabetes Audit and Research in Tayside Scotland), models developed for diabetic kidney disease outperformed those for chronic kidney disease. Models were generally well calibrated across all three prediction horizons. Conclusions This study identified multiple prediction models to predict albuminuria, diabetic kidney disease, chronic kidney disease, and end stage renal disease. In the external validation, discrimination and calibration for albuminuria, diabetic kidney disease, and chronic kidney disease varied considerably across prediction horizons and models. For each outcome, however, specific models showed good discrimination and calibration across the three prediction horizons, with clinically accessible predictors, making them applicable in a clinical setting. Systematic review registration PROSPERO CRD42020192831.

Angioedema in the mouth or upper airways is a feared adverse reaction to angiotensin-converting enzyme inhibitor (ACEi) and angiotensin receptor blocker (ARB) treatment, which is used for hypertension, heart failure and diabetes complications. This candidate gene and genome-wide association study aimed to identify genetic variants predisposing to angioedema induced by these drugs. The discovery cohort consisted of 173 cases and 4890 controls recruited in Sweden. In the candidate gene analysis, ETV6, BDKRB2, MME, and PRKCQ were nominally associated with angioedema (p < 0.05), but did not pass Bonferroni correction for multiple testing (p < 2.89 × 10 −5). In the genome-wide analysis, intronic variants in the calcium-activated potassium channel subunit alpha-1 (KCNMA1) gene on chromosome 10 were significantly associated with angioedema (p < 5 × 10 −8). Whilst the top KCNMA1 hit was not significant in the replication cohort (413 cases and 599 ACEi-exposed controls from the US and Northern Europe), a meta-analysis of the replication and discovery cohorts (in total 586 cases and 1944 ACEi-exposed controls) revealed that each variant allele increased the odds of experiencing angioedema 1.62 times (95% confidence interval 1.05-2.50, p = 0.030). Associated KCNMA1 variants are not known to be functional, but are in linkage disequilibrium with variants in transcription factor binding sites active in relevant tissues. In summary, our data suggest that common variation in KCNMA1 is associated with risk of angioedema induced by ACEi or ARB treatment. Future whole exome or genome sequencing studies will show whether rare variants in KCNMA1 or other genes contribute to the risk of ACEi-and ARBinduced angioedema.

Aims/hypothesis The aim of the study was to examine the association between lipoprotein-associated phospholipase A 2 (Lp-PLA 2 ) activity levels and incident diabetic retinopathy and change in retinopathy grade. Methods This was a cohort study of diabetic participants with serum collected at baseline and routinely collected diabetic retinal screening data. Participants with type 2 diabetes from the GoDARTS (Genetics of Diabetes Audit and Research in Tayside Scotland) cohort were used. This cohort is composed of individuals of white Scottish ancestry from the Tayside region of Scotland. Survival analysis accounting for informative censoring by modelling death as a competing risk was performed for the development of incident diabetic retinopathy from a disease-free state in a 3 year follow-up period (n = 1364) by stratified Lp-PLA 2 activity levels (in quartiles). The same analysis was performed for transitions to more severe grades. Results The hazard of developing incident diabetic retinopathy was 2.08 times higher (95% CI 1.64, 2.63) for the highest quartile of Lp-PLA 2 activity compared with the lowest. Higher Lp-PLA 2 activity levels were associated with a significantly increased risk for transitions to all grades. The hazards of developing observable (or more severe) and referable (or more severe) retinopathy were 2.82 (95% CI 1.71, 4.65) and 1.87 (95% CI 1.26, 2.77) times higher for the highest quartile of Lp-PLA 2 activity compared with the lowest, respectively. Conclusions/interpretation Higher Lp-PLA 2 levels are associated with increased risk of death and the development of incident diabetic retinopathy, as well as transitions to more severe grades of diabetic retinopathy. These associations are independent of calculated LDL-cholesterol and other traditional risk factors. Further, this biomarker study shows that the association is temporally sensitive to the proximity of the event to measurement of Lp-PLA 2.