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Polygenic risk scores predict diabetes complications and their response to intensive blood pressure and glucose control
J. Tremblay, M. Haloui, R. Attaoua, R. Tahir, C. Hishmih, F. Harvey, FC. Marois-Blanchet, C. Long, P. Simon, L. Santucci, C. Hizel, J. Chalmers, M. Marre, S. Harrap, R. Cífková, A. Krajčoviechová, DR. Matthews, B. Williams, N. Poulter, S....
Jazyk angličtina Země Německo
Typ dokumentu časopisecké články, práce podpořená grantem
Grantová podpora
CH/1996001/9454
British Heart Foundation - United Kingdom
MC_PC_17228
Medical Research Council - United Kingdom
MC_QA137853
Medical Research Council - United Kingdom
CIHR - Canada
NLK
ProQuest Central
od 1999-01-01 do Před 1 rokem
Medline Complete (EBSCOhost)
od 2000-01-01 do Před 1 rokem
Health & Medicine (ProQuest)
od 1999-01-01 do Před 1 rokem
Public Health Database (ProQuest)
od 1999-01-01 do Před 1 rokem
- MeSH
- celogenomová asociační studie MeSH
- diabetes mellitus 2. typu * komplikace genetika MeSH
- komplikace diabetu * komplikace MeSH
- krevní glukóza MeSH
- krevní tlak genetika MeSH
- lidé MeSH
- multifaktoriální dědičnost * MeSH
- rizikové faktory MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
AIMS/HYPOTHESIS: 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. METHODS: 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 individuals with type 2 diabetes in the UK Biobank study. RESULTS: 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 individuals had the greatest absolute risk reduction with a number needed to treat of 12 to prevent one cardiovascular death over 5 years. CONCLUSIONS/INTERPRETATION: This novel multiPRS model stratified individuals with type 2 diabetes according to risk of complications and helped to target earlier those who would receive greater benefit from intensive therapy.
Beijing Hypertension League Institute Beijing China
Boden Institute University of Sydney Sydney NSW Australia
Clinique Ambroise Paré Neuilly sur Seine and Centre de Recherches des Cordeliers Paris France
Department of Medicine Faculty of Medicine Université de Montréal Montréal Québec Canada
Department of Medicine University of Montréal CRCHUM Québec Canada
Department of Physiology University of Melbourne Melbourne VIC Australia
Istituto Auxologico Italiano University of Milano Bicocca Italy
Montreal Heart Institute Research Center Montréal Québec Canada
Ontario Institute for Cancer Research Toronto ON Canada
Oxford Centre for Diabetes Endocrinology and Metabolism University of Oxford Oxford UK
School of Public Health and Preventive Medicine Monash University Melbourne VIC Australia
School of Public Health Faculty of Medicine Imperial College London London UK
The George Institute for Global Health School of Public Health Imperial College London London UK
The George Institute for Global Health University of New South Wales Sydney NSW Australia
University College London Institute of Cardiovascular Science London UK
Citace poskytuje Crossref.org
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