Addressing Ancestry and Sex Bias in Pharmacogenomics.

The association of an individual's genetic makeup with their response to drugs is referred to as pharmacogenomics. By understanding the relationship between genetic variants and drug efficacy or toxicity, we are able to optimize pharmacological therapy according to an individual's genotype. Pharmacogenomics research has historically suffered from bias and underrepresentation of people from certain ancestry groups and of the female sex. These biases can arise from factors such as drugs and indications studied, selection of study participants, and methods used to collect and analyze data. To examine the representation of biogeographical populations in pharmacogenomic data sets, we describe individuals involved in gene-drug response studies from PharmGKB, a leading repository of drug-gene annotations, and showcaseCYP2D6, a gene that metabolizes approximately 25% of all prescribed drugs. We also show how the historical underrepresentation of females in clinical trials has led to significantly more adverse drug reactions in females than in males.

Competing risks analysis for neutrophil to lymphocyte ratio as a predictor of diabetic retinopathy incidence in the Scottish population.

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 HbA1c 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.

Common and Distinct Genetic Architecture of Age at Diagnosis of Diabetes in South Indian and European Populations.

OBJECTIVE: South Asians are diagnosed with type 2 diabetes (T2D) more than a decade earlier in life than seen in European populations. We hypothesized that studying the genomics of age of diagnosis in these populations may give insight into the earlier age diagnosis of T2D among individuals of South Asian descent. RESEARCH DESIGN AND METHODS: We conducted a meta-analysis of genome-wide association studies (GWAS) of age at diagnosis of T2D in 34,001 individuals from four independent cohorts of European and South Asian Indians. RESULTS: We identified two signals near the TCF7L2 and CDKAL1 genes associated with age at the onset of T2D. The strongest genome-wide significant variants at chromosome 10q25.3 in TCF7L2 (rs7903146; P = 2.4 × 10-12, ß = -0.436; SE 0.02) and chromosome 6p22.3 in CDKAL1 (rs9368219; P = 2.29 × 10-8; ß = -0.053; SE 0.01) were directionally consistent across ethnic groups and present at similar frequencies; however, both loci harbored additional independent signals that were only present in the South Indian cohorts. A genome-wide signal was also obtained at chromosome 10q26.12 in WDR11 (rs3011366; P = 3.255 × 10-8; ß = 1.44; SE 0.25), specifically in the South Indian cohorts. Heritability estimates for the age at diagnosis were much stronger in South Indians than Europeans, and a polygenic risk score constructed based on South Indian GWAS explained ∼2% trait variance. CONCLUSIONS: Our findings provide a better understanding of ethnic differences in the age at diagnosis and indicate the potential importance of ethnic differences in the genetic architecture underpinning T2D.

A gene risk score using missense variants in SLCO1B1 is associated with earlier onset statin intolerance.

BACKGROUND AND AIMS: The efficacy of statin therapy is hindered by intolerance to the therapy, leading to discontinuation. Variants in SLCO1B1, which encodes the hepatic transporter OATB1B1, influence statin pharmacokinetics, resulting in altered plasma concentrations of the drug and its metabolites. Current pharmacogenetic guidelines require sequencing of the SLCO1B1 gene, which is more expensive and less accessible than genotyping. In this study, we aimed to develop an easy, clinically implementable functional gene risk score (GRS) of common variants in SLCO1B1 to identify patients at risk of statin intolerance. METHODS AND RESULTS: A GRS was developed from four common variants in SLCO1B1. In statin users from Tayside, Scotland, UK, those with a high-risk GRS had increased odds across three phenotypes of statin intolerance [general statin intolerance (GSI): ORGSI 2.42; 95% confidence interval (CI): 1.29-4.31, P = 0.003; statin-related myopathy: ORSRM 2.51; 95% CI: 1.28-4.53, P = 0.004; statin-related suspected rhabdomyolysis: ORSRSR 2.85; 95% CI: 1.03-6.65, P = 0.02]. In contrast, using the Val174Ala genotype alone or the recommended OATP1B1 functional phenotypes produced weaker and less reliable results. A meta-analysis with results from adjudicated cases of statin-induced myopathy in the PREDICTION-ADR Consortium confirmed these findings (ORVal174Ala 1.99; 95% CI: 1.01-3.95, P = 0.048; ORGRS 1.76; 95% CI: 1.16-2.69, P = 0.008). For those requiring high-dose statin therapy, the high-risk GRS was more consistently associated with the time to onset of statin intolerance amongst the three phenotypes compared with Val174Ala (GSI: HRVal174Ala 2.49; 95% CI: 1.09-5.68, P = 0.03; HRGRS 2.44; 95% CI: 1.46-4.08, P < 0.001). Finally, sequence kernel association testing confirmed that rare variants in SLCO1B1 are associated with the risk of intolerance (P = 0.02). CONCLUSION: We provide evidence that a GRS based on four common SLCO1B1 variants provides an easily implemented genetic tool that is more reliable than the current recommended practice in estimating the risk and predicting early-onset statin intolerance.

The cholesterol-lowering effect of statins is modified by LILRB5 intolerance genotype: Results from a recruit-by-genotype clinical trial.

Background/Aims: Statin intolerance leads to poor adherence to statin therapy, resulting in a failure to achieve desired cholesterol reduction and adverse outcomes. The LILRB5 Asp247Gly genotype has been identified as being associated with statin intolerance and statin-induced myalgia. We conducted a randomized clinical trial to examine its role in immune response through T regulatory cell aggregation and in achieving cholesterol reduction targets. Methods: A double-blind, cross-over, recruit-by-genotype trial was undertaken. A total of 18 participants who had either the Asp247Asp (T/T) genotype or the Gly247Gly (C/C) genotype were recruited to the study. Participants were randomised to receive placebo or atorvastatin 80 mg daily for 28 days. Following a washout period of 3 weeks, they were then switched to the opposite treatment. Biochemical and immunological measurements as well as interviews were performed prior to and after both treatment periods. Within genotype group comparisons were performed using repeated measures Wilcoxon tests. Two-way repeated measures ANOVA with genotype and treatment as factors were used to compare changes in biochemical parameters between groups during placebo and atorvastatin periods. Results: Individuals with the Asp247Asp genotype had a greater increase in creatine kinase (CK) compared to those with Gly247Gly genotype in response to atorvastatin (p = 0.03). Those with Gly247Gly genotype had a mean non-HDL cholesterol reduction of 2.44 (95% CI:1.59 - 3.29) mmol/L while in Asp247Asp genotype group the mean reduction was 1.28 (95%CI: 0.48 - 2.07) mmol/L. The interaction between the genotype and atorvastatin treatment for total cholesterol (p = 0.007) and non-HDL cholesterol response was significant (p = 0.025). Immunological assessment showed no significant changes in aggregation of T regulatory cells by genotype. Conclusion: The Asp247Gly variant in LILRB5, previously associated with statin intolerance, was associated with differential increases in creatine kinase and total cholesterol and non-HDL cholesterol-lowering response to atorvastatin. Taken together, these results suggest that this variant could have utility in precision cardiovascular therapy.

Weight variability and cardiovascular outcomes: a systematic review and meta-analysis.

The association between body weight variability and the risk of cardiovascular disease (CVD) has been investigated previously with mixed findings. However, there has been no extensive study which systematically evaluates the current evidence. Furthermore, the impact of ethnicity and type 2 diabetes on this phenomena has not yet been investigated. Therefore, the aim of this study was to comprehensively evaluate the effect of weight variability on risk of CVD (any cardiovascular (CV) event, composite CV outcome, CV death, Stroke, Myocardial Infarction) and the influence of ethnicity and type 2 diabetes status on the observed association. A systematic review and meta-analysis was performed according to the meta-analyses of observational studies in epidemiology (MOOSE) guidelines. The electronic databases PubMed, Web of Science, and the Cochrane Library were searched for studies that investigated the relationship between body weight or BMI variability and CV diseases using Medical Subject Headings (MeSH) terms and keywords. The relative risks (RRs) for the outcomes were collected from studies, pooled, and analysed using a random-effects model to estimate the overall relative risk. Of 5645 articles screened, 23 studies with a total population of 15,382,537 fulfilled the prespecified criteria and were included. Individuals in the highest strata of body weight variability were found to have significantly increased risk of any CV event (RR = 1.27; 95% Confidence Interval (CI) 1.17-1.38; P < 0.0001; I2 = 97.28%), cardiovascular death (RR = 1.29; 95% CI 1.03-1.60; P < 0.0001; I2 = 55.16%), myocardial infarction (RR = 1.32; 95% CI 1.09-1.59; P = 0.0037; I2 = 97.14%), stroke (RR = 1.21; 95% CI 1.19-1.24; P < 0.0001; I2 = 0.06%), and compound CVD outcomes (RR = 1.36; 95% CI 1.08-1.73; P = 0.01; I2 = 92.41%). Similar RRs were observed regarding BMI variability and per unit standard deviation (SD) increase in body weight variability. Comparable effects were seen in people with and without diabetes, in White Europeans and Asians. In conclusion, body weight variability is associated with increased risk of CV diseases regardless of ethnicity or diabetes status. Future research is needed to prove a causative link between weight variability and CVD risk, as appropriate interventions to maintain stable weight could positively influence CVD.

Major cardiovascular events and subsequent risk of kidney failure with replacement therapy: a CKD Prognosis Consortium study.

AIMS: Chronic kidney disease (CKD) increases risk of cardiovascular disease (CVD). Less is known about how CVD associates with future risk of kidney failure with replacement therapy (KFRT). METHODS AND RESULTS: The study included 25 903 761 individuals from the CKD Prognosis Consortium with known baseline estimated glomerular filtration rate (eGFR) and evaluated the impact of prevalent and incident coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF) events as time-varying exposures on KFRT outcomes. Mean age was 53 (standard deviation 17) years and mean eGFR was 89 mL/min/1.73 m2, 15% had diabetes and 8.4% had urinary albumin-to-creatinine ratio (ACR) available (median 13 mg/g); 9.5% had prevalent CHD, 3.2% prior stroke, 3.3% HF, and 4.4% prior AF. During follow-up, there were 269 142 CHD, 311 021 stroke, 712 556 HF, and 605 596 AF incident events and 101 044 (0.4%) patients experienced KFRT. Both prevalent and incident CVD were associated with subsequent KFRT with adjusted hazard ratios (HRs) of 3.1 [95% confidence interval (CI): 2.9-3.3], 2.0 (1.9-2.1), 4.5 (4.2-4.9), 2.8 (2.7-3.1) after incident CHD, stroke, HF and AF, respectively. HRs were highest in first 3 months post-CVD incidence declining to baseline after 3 years. Incident HF hospitalizations showed the strongest association with KFRT [HR 46 (95% CI: 43-50) within 3 months] after adjustment for other CVD subtype incidence. CONCLUSION: Incident CVD events strongly and independently associate with future KFRT risk, most notably after HF, then CHD, stroke, and AF. Optimal strategies for addressing the dramatic risk of KFRT following CVD events are needed.

Incidence and Outcomes of Patients Receiving Chronic Kidney Replacement Therapy Admitted to Scottish ICUs Between 2009 and 2019-A National Observational Cohort Study.

OBJECTIVES: To determine the incidence and characteristics of ICU admissions in the Scottish population of patients treated with chronic kidney replacement therapy (KRT) over an 11-year period and determine factors associated with post-ICU admission mortality. DESIGN: Retrospective observational cohort study. SETTING: We analyzed admissions to Scottish intensive care environments between January 1, 2009, and December 31, 2019. PATIENTS: All patients receiving chronic KRT-including maintenance dialysis and kidney transplant-in Scotland. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: Descriptive statistics and factors associated with mortality using logistic regression and Cox proportional hazard models. From 10,657 unique individuals registered in the Scottish Renal Registry over the 11-year study period and alive as of January 1, 2009, 1,402 adult patients were identified as being admitted to a Scottish critical care setting. Between 2009 and 2019, admissions to ICU increased in a nonlinear manner driven by increases in admissions for renal causes and elective cardiac surgery. The ICU admission rate was higher among patients on chronic dialysis than in kidney transplant recipients (59.1 vs 19.9 per 1,000 person-years), but post-ICU mortality was similar (about 24% at 30 d and 40% at 1 year). Admissions for renal reasons were most common (20.9%) in patients undergoing chronic dialysis, whereas kidney transplant recipients were most frequently admitted for pneumonia (19.3%) or sepsis (12.8%). Adjusted Cox PH models showed that receiving invasive ventilation and vasoactive drugs was associated with an increased risk of death at 30 days post-ICU admission (HR, 1.75; 95% CI, 1.28-2.39 and 1.72; 95% CI, 1.28-2.31, respectively). CONCLUSIONS: With a growing population of kidney transplant recipients and the improved survival of patients on chronic dialysis, the number of ICU admissions is rising in the chronic KRT population. Mortality post-ICU admission is high for these patients.

Using Data to Improve the Management of Diabetes: The Tayside Experience.

Tayside is a region in the East of Scotland and forms one of nine local government regions in the country. It is home to approximately 416,000 individuals who fall under the National Health Service (NHS) Tayside health board, which provides health care services to the population. In Tayside, Scotland, a comprehensive informatics network for diabetes care and research has been established for over 25 years. This has expanded more recently to a comprehensive Scotland-wide clinical care system, Scottish Care Information - Diabetes (SCI-Diabetes). This has enabled improved diabetes screening and integrated management of diabetic retinopathy, neuropathy, nephropathy, cardiovascular health, and other comorbidities. The regional health informatics network links all of these specialized services with comprehensive laboratory testing, prescribing records, general practitioner records, and hospitalization records. Not only do patients benefit from the seamless interconnectedness of these data, but also the Tayside bioresource has enabled considerable research opportunities and the creation of biobanks. In this article we describe how health informatics has been used to improve care of people with diabetes in Tayside and Scotland and, through anonymized data linkage, our understanding of the phenotypic and genotypic etiology of diabetes and associated complications and comorbidities.

Identification of 4 New Loci Associated With Primary Hyperparathyroidism (PHPT) and a Polygenic Risk Score for PHPT.

CONTEXT: A hypothesis-free genetic association analysis has not been reported for patients with primary hyperparathyroidism (PHPT). OBJECTIVE: We aimed to investigate genetic associations with PHPT using both genome-wide association study (GWAS) and candidate gene approaches. METHODS: A cross-sectional study was conducted among patients of European White ethnicity recruited in Tayside (Scotland, UK). Electronic medical records were used to identify PHPT cases and controls, and linked to genetic biobank data. Genetic associations were performed by logistic regression models and odds ratios (ORs). The combined effect of the genotypes was researched by genetic risk score (GRS) analysis. RESULTS: We identified 15 622 individuals for the GWAS that yielded 34 top single-nucleotide variations (formerly single-nucleotide polymorphisms), and LPAR3-rs147672681 reached genome-wide statistical significance (P = 1.2e-08). Using a more restricted PHPT definition, 8722 individuals with data on the GWAS-identified loci were found. Age- and sex-adjusted ORs for the effect alleles of SOX9-rs11656269, SLITRK5-rs185436526, and BCDIN3D-AS1-rs2045094 showed statistically significant increased risks (P < 1.5e-03). GRS analysis of 5482 individuals showed an OR of 2.51 (P = 1.6e-04), 3.78 (P = 4.0e-08), and 7.71 (P = 5.3e-17) for the second, third, and fourth quartiles, respectively, compared to the first, and there was a statistically significant linear trend across quartiles (P < 1.0e-04). Results were similar when stratifying by sex. CONCLUSION: Using genetic loci discovered in a GWAS of PHPT carried out in a Scottish population, this study suggests new evidence for the involvement of genetic variants at SOX9, SLITRK5, LPAR3, and BCDIN3D-AS1. It also suggests that male and female carriers of greater numbers of PHPT-risk alleles both have a statistically significant increased risk of PHPT.

Cardiovascular outcomes in patients with chronic kidney disease and COVID-19: a multi-regional data-linkage study.

BACKGROUND: Data describing cardiovascular outcomes in patients with coronavirus disease 2019 (COVID-19) and chronic kidney disease (CKD) are lacking. We compared cardiovascular outcomes of patients with and without COVID-19, stratified by CKD status. METHODS: This retrospective, multi-regional data-linkage study utilised individual patient-level data from two Scottish cohorts. All patients tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Cohort 1 between 1 February 2020 and 31 March 2021 and in Cohort 2 between 28 February 2020 and 8 February 2021 were included. RESULTS: Overall, 86 964 patients were tested for SARS-CoV-2. There were 36 904 patients (mean±sd age 61±21 years; 58.1% women; 15.9% CKD; 10.1% COVID-19 positive) in Cohort 1 and 50 060 patients (mean±sd age 63±20 years; 62.0% women; 16.4% CKD; 9.1% COVID-19 positive) in Cohort 2. In CKD patients, COVID-19 increased the risk of cardiovascular death by more than two-fold within 30 days (cause-specific hazard ratio (csHR) meta-estimate 2.34, 95% CI 1.83-2.99) and by 57% at the end of study follow-up (csHR meta-estimate 1.57, 95% CI 1.31-1.89). Similarly, the risk of all-cause death in COVID-19 positive versus negative CKD patients was greatest within 30 days (HR 4.53, 95% CI 3.97-5.16). Compared with patients without CKD, those with CKD had a higher risk of testing positive (11.5% versus 9.3%). Following a positive test, CKD patients had higher rates of cardiovascular death (11.1% versus 2.7%), cardiovascular complications and cardiovascular hospitalisations (7.1% versus 3.3%) than those without CKD. CONCLUSIONS: COVID-19 increases the risk of cardiovascular and all-cause death in CKD patients, especially in the short-term. CKD patients with COVID-19 are also at a disproportionate risk of cardiovascular complications than those without CKD.

Young-onset diabetes in Asian Indians is associated with lower measured and genetically determined beta cell function.

AIMS/HYPOTHESIS: South Asians in general, and Asian Indians in particular, have higher risk of type 2 diabetes compared with white Europeans, and a younger age of onset. The reasons for the younger age of onset in relation to obesity, beta cell function and insulin sensitivity are under-explored. METHODS: Two cohorts of Asian Indians, the ICMR-INDIAB cohort (Indian Council of Medical Research-India Diabetes Study) and the DMDSC cohort (Dr Mohan's Diabetes Specialties Centre), and one of white Europeans, the ESDC (East Scotland Diabetes Cohort), were used. Using a cross-sectional design, we examined the comparative prevalence of healthy, overweight and obese participants with young-onset diabetes, classified according to their BMI. We explored the role of clinically measured beta cell function in diabetes onset in Asian Indians. Finally, the comparative distribution of a partitioned polygenic score (pPS) for risk of diabetes due to poor beta cell function was examined. Replication of the genetic findings was sought using data from the UK Biobank. RESULTS: The prevalence of young-onset diabetes with normal BMI was 9.3% amongst white Europeans and 24-39% amongst Asian Indians. In Asian Indians with young-onset diabetes, after adjustment for family history of type 2 diabetes, sex, insulin sensitivity and HDL-cholesterol, stimulated C-peptide was 492 pmol/ml (IQR 353-616, p<0.0001) lower in lean compared with obese individuals. Asian Indians in our study, and South Asians from the UK Biobank, had a higher number of risk alleles than white Europeans. After weighting the pPS for beta cell function, Asian Indians have lower genetically determined beta cell function than white Europeans (p<0.0001). The pPS was associated with age of diagnosis in Asian Indians but not in white Europeans. The pPS explained 2% of the variation in clinically measured beta cell function, and 1.2%, 0.97%, and 0.36% of variance in age of diabetes amongst Asian Indians with normal BMI, or classified as overweight and obese BMI, respectively. CONCLUSIONS/INTERPRETATION: The prevalence of lean BMI in young-onset diabetes is over two times higher in Asian Indians compared with white Europeans. This phenotype of lean, young-onset diabetes appears driven in part by lower beta cell function. We demonstrate that Asian Indians with diabetes also have lower genetically determined beta cell function.

Metabolic dysfunction-related liver disease as a risk factor for cancer.

OBJECTIVE: The aim of this study was to investigate the association between obesity, diabetes and metabolic related liver dysfunction and the incidence of cancer. DESIGN: This study was conducted with health record data available from the National Health Service in Tayside and Fife. Genetics of Diabetes Audit and Research Tayside, Scotland (GoDARTS), Scottish Health Research Register (SHARE) and Tayside and Fife diabetics, three Scottish cohorts of 13 695, 62 438 and 16 312 patients, respectively, were analysed in this study. Participants in GoDARTS were a volunteer sample, with half having type 2 diabetes mellitus(T2DM). SHARE was a volunteer sample. Tayside and Fife diabetics was a population-level cohort. Metabolic dysfunction-related liver disease (MDLD) was defined using alanine transaminase measurements, and individuals with alternative causes of liver disease (alcohol abuse, viruses, etc) were excluded from the analysis. RESULTS: MDLD associated with increased cancer incidence with a HR of 1.31 in a Cox proportional hazards model adjusted for sex, type 2 diabetes, body mass index(BMI), and smoking status (95% CI 1.27 to 1.35, p<0.0001). This was replicated in two further cohorts, and similar associations with cancer incidence were found for Fatty Liver Index (FLI), Fibrosis-4 Index (FIB-4) and non-alcoholic steatohepatitis (NASH). Homozygous carriers of the common non-alcoholic fatty liver disease (NAFLD) risk-variant PNPLA3 rs738409 had increased risk of cancer. (HR=1.27 (1.02 to 1.58), p=3.1×10 -2). BMI was not independently associated with cancer incidence when MDLD was included as a covariate. CONCLUSION: MDLD, FLI, FIB-4 and NASH associated with increased risk of cancer incidence and death. NAFLD may be a major component of the relationship between obesity and cancer incidence.

Prescribing Patterns and Response to Antihyperglycemic Agents Among Novel Clusters of Type 2 Diabetes in Asian Indians.

Aim: To assess the prescribing patterns and response to different classes of antihyperglycemic agents in novel clusters of type 2 diabetes (T2D) described in India. Materials and Methods: We attempted to replicate the earlier described clusters of T2D, in 32,867 individuals with new-onset T2D (within 2 years of diagnosis) registered between October 2013 and December 2020 at 15 diabetes clinics located across India, by means of k-means clustering utilizing 6 clinically relevant variables. Individuals who had follow-up glycated hemoglobin (HbA1c) up to 2 years were included for the drug response analysis (n = 13,247). Results: Among the 32,867 participants included in the study, 20,779 (63.2%) were males. The average age at diagnosis was 45 years and mean HbA1c at baseline was 8.9%. The same four clusters described in India earlier were replicated. Forty percent of the study participants belonged to the mild age-related diabetes cluster, followed by insulin-resistant obese diabetes (27%), severe insulin-deficient diabetes (21%), and combined insulin-resistant and insulin-deficient diabetes (12%) clusters. The most frequently used antihyperglycemic agents were sulfonylureas, metformin, and dipeptidyl peptidase-4 inhibitors apart from insulin. While there were significant differences in HbA1c reduction between drugs across clusters, these were largely driven by differences in the baseline (pretreatment) HbA1c. Conclusions: In this new cohort, we were able to reliably replicate the four subtypes of T2D earlier described in Asian Indians. Prescribing patterns show limited usage of newer antihyperglycemic agents across all clusters. Randomized clinical trials are required to establish differential drug responses between clusters.

Diabetes status modifies the long-term effect of lipoprotein-associated phospholipase A2 on major coronary events.

AIMS/HYPOTHESIS: Lipoprotein-associated phospholipase A2 (Lp-PLA2) activity has an independent prognostic association with major coronary events (MCE). However, no study has investigated whether type 2 diabetes status modifies the effect of Lp-PLA2 activity or inhibition on the risk of MCE. We investigate the interaction between diabetes status and Lp-PLA2 activity with risk of MCE. Subsequently, we test the resulting hypothesis that diabetes status will play a role in modifying the efficacy of an Lp-PLA2 inhibitor. METHODS: A retrospective cohort study design was utilised in two study populations. Discovery analyses were performed in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) cohort based in Scotland, UK. Participants were categorised by type 2 diabetes control status: poorly controlled (HbA1c ≥ 48 mmol/mol or ≥6.5%) and well-controlled (HbA1c < 48 mmol/mol or <6.5%) diabetes (n = 7420). In a secondary analysis of the Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy (STABILITY) trial of Lp-PLA2 inhibitor (darapladib) efficacy, 15,828 participants were stratified post hoc by type 2 diabetes diagnosis status (diabetes or no diabetes) at time of recruitment. Lp-PLA2 activity was then divided into population-specific quartiles. MCE were determined from linked medical records in GoDARTS and trial records in STABILITY. First, the interaction between diabetes control status and Lp-PLA2 activity on the outcome of MCE was explored in GoDARTS. The effect was replicated in the placebo arm of STABILITY. The effect of Lp-PLA2 on MCE was then examined in models stratified by diabetes status. This helped determine participants at higher risk. Finally, the effect of Lp-PLA2 inhibition was assessed in STABILITY in the higher risk group. Cox proportional hazards models adjusted for confounders were used to assess associations. RESULTS: In GoDARTS, a significant interaction between increased Lp-PLA2 activity (continuous and quartile divided) and diabetes control status was observed in the prediction of MCE (p < 0.0001). These effects were replicated in the placebo arm of STABILITY (p < 0.0001). In GoDARTS, stratified analyses showed that, among individuals with poorly controlled diabetes, the hazards of MCE for those with high (Q4) Lp-PLA2 activity was 1.19 compared with individuals with lower (Q1-3) Lp-PLA2 activity (95% CI 1.11, 1.38; p < 0.0001) and 1.35 (95% CI 1.16, 1.57; p < 0.0001) when compared with those with the lowest activity (Q1). Those in the higher risk group were identified as individuals with the highest Lp-PLA2 activity (Q4) and poorly controlled diabetes or diabetes. Based on these observations in untreated populations, we hypothesised that the Lp-PLA2 inhibitor would have more benefit in this higher risk group. In this risk group, Lp-PLA2 inhibitor use was associated with a 33% reduction in MCE compared with placebo (HR 0.67 [95% CI 0.50, 0.90]; p = 0.008). In contrast, Lp-PLA2 inhibitor showed no efficacy in individuals with low activity, regardless of diabetes status, or among those with no baseline diabetes and high Lp-PLA2 activity. CONCLUSIONS/INTERPRETATION: These results support the hypothesis that diabetes status modifies the association between Lp-PLA2 activity and MCE. These results suggest that cardiovascular morbidity and mortality associated with Lp-PLA2 activity is especially important in patients with type 2 diabetes, particularly those with worse glycaemic control. Further investigation of the effects of Lp-PLA2 inhibition in diabetes appears warranted. DATA AVAILABILITY: STABILITY trial data are available from clinicaltrials.gov repository through the GlaxoSmithKline clinical study register https://clinicaltrials.gov/ct2/show/NCT00799903 . GoDARTS datasets generated during and/or analysed during the current study are available following request to the GoDARTS Access Managements Group https://godarts.org/scientific-community/ .