ORCID Profile
0000-0001-6504-0036
Current Organisation
University of Oxford
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Publisher: Springer Science and Business Media LLC
Date: 06-07-2021
DOI: 10.1007/S00125-021-05491-7
Abstract: Type 2 diabetes increases the risk of cardiovascular and renal complications, but early risk prediction could lead to timely intervention and better outcomes. Genetic information can be used to enable early detection of risk. We developed a multi-polygenic risk score (multiPRS) that combines ten weighted PRSs (10 wPRS) composed of 598 SNPs associated with main risk factors and outcomes of type 2 diabetes, derived from summary statistics data of genome-wide association studies. The 10 wPRS, first principal component of ethnicity, sex, age at onset and diabetes duration were included into one logistic regression model to predict micro- and macrovascular outcomes in 4098 participants in the ADVANCE study and 17,604 in iduals with type 2 diabetes in the UK Biobank study. The model showed a similar predictive performance for cardiovascular and renal complications in different cohorts. It identified the top 30% of ADVANCE participants with a mean of 3.1-fold increased risk of major micro- and macrovascular events ( p = 6.3 × 10 −21 and p = 9.6 × 10 −31 , respectively) and a 4.4-fold ( p = 6.8 × 10 −33 ) higher risk of cardiovascular death. While in ADVANCE overall, combined intensive blood pressure and glucose control decreased cardiovascular death by 24%, the model identified a high-risk group in whom it decreased the mortality rate by 47%, and a low-risk group in whom it had no discernible effect. High-risk in iduals had the greatest absolute risk reduction with a number needed to treat of 12 to prevent one cardiovascular death over 5 years. This novel multiPRS model stratified in iduals with type 2 diabetes according to risk of complications and helped to target earlier those who would receive greater benefit from intensive therapy.
Publisher: Wiley
Date: 03-01-2020
DOI: 10.1111/DOM.13920
Publisher: Cold Spring Harbor Laboratory
Date: 02-11-2019
DOI: 10.1101/19010785
Abstract: Type 2 diabetes increases the risk of cardiovascular and renal complications, but early risk prediction can lead to timely intervention and better outcomes. Through summary statistics of meta-analyses of published genome-wide association studies performed in over 1.2 million of in iduals, we combined 9 PRS gathering genomic variants associated to cardiovascular and renal diseases and their key risk factors into one logistic regression model, to predict micro- and macrovascular endpoints of diabetes. Its clinical utility in predicting complications of diabetes was tested in 4098 participants with diabetes of the ADVANCE trial followed during a period of 10 years and replicated it in three independent non-trial cohorts. The prediction model adjusted for ethnicity, sex, age at onset and diabetes duration, identified the top 30% of ADVANCE participants at 3.1-fold increased risk of major micro- and macrovascular events (p=6.3×10 −21 and p=9.6×10 −31 , respectively) and at 4.4-fold (p=6.8×10 −33 ) increased risk of cardiovascular death compared to the remainder of T2D subjects. While in ADVANCE overall, combined intensive therapy of blood pressure and glycaemia decreased cardiovascular mortality by 24%, the prediction model identified a high-risk group in whom this therapy decreased mortality by 47%, and a low risk group in whom the therapy had no discernable effect. Patients with high PRS had the greatest absolute risk reduction with a number needed to treat of 12 to prevent one cardiovascular death over 5 years. This novel polygenic prediction model identified people with diabetes at low and high risk of complications and improved targeting those at greater benefit from intensive therapy while avoiding unnecessary intensification in low-risk subjects.
Publisher: Springer Science and Business Media LLC
Date: 27-08-2021
Publisher: Oxford University Press (OUP)
Date: 07-04-2021
DOI: 10.1093/CVR/CVAB128
Abstract: Given the benefits of sodium glucose co-transporter 2 inhibition (SGLT2i) in protecting against heart failure in diabetic patients, we sought to explore the potential impact of SGLT2i on the clinical features of patients presenting with myocardial infarction (MI) through a post hoc analysis of CANVAS Programme and CREDENCE trial. In iduals with type 2 diabetes and history or high risk of cardiovascular disease (CANVAS Programme) or type 2 diabetes and chronic kidney disease (CREDENCE) were included. The intervention was canagliflozin 100 or 300 mg (combined in the analysis) or placebo. MI events were adjudicated as ST-elevation myocardial infarction (STEMI), non-STEMI, and type 1 MI or type 2 MI. A total of 421 first MI events in the CANVAS Programme and 178 first MI events in the CREDENCE trial were recorded (83 fatal, 128 STEMI, 431 non-STEMI, and 40 unknown). No benefit of canagliflozin compared with placebo on time to first MI event was observed [hazard ratio (HR) 0.89 95% confidence interval (CI) 0.75, 1.05]. Canagliflozin was associated with lower risk for non-STEMI (HR 0.78 95% CI 0.65, 0.95) but suggested a possible increase in STEMI (HR 1.55 95% CI 1.06, 2.27), with no difference in risk of type 1 or type 2 MI. There was no change in fatal MI (HR 1.22, 95% CI 0.78, 1.93). Canagliflozin was not associated with a reduction in overall MI in the pooled CANVAS Programme and CREDENCE trial population. The possible differential effect on STEMI and Non-STEMI observed in the CANVAS cohort warrants further investigation. ClinicalTrials.gov identifiers: NCT01032629, NCT01989754, and NCT02065791.
Publisher: Wiley
Date: 24-08-2020
DOI: 10.1111/DOM.14143
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for David Matthews.