D Gill1, V Karhunen2, R Malik3, M Dichgans4, N Sofat5. 1. Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom; Institute for Infection and Immunity, St George's University of London, London, United Kingdom; St George's University Hospitals NHS Foundation Trust, London, United Kingdom. Electronic address: dgill@sgul.ac.uk. 2. Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom. Electronic address: v.karhunen@imperial.ac.uk. 3. Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-University (LMU), Munich, Germany. Electronic address: rainer.malik@med.uni-muenchen.de. 4. Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-University (LMU), Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; German Centre for Neurodegenerative Diseases (DZNE), Munich, Germany. Electronic address: martin.dichgans@med.uni-muenchen.de. 5. Institute for Infection and Immunity, St George's University of London, London, United Kingdom; St George's University Hospitals NHS Foundation Trust, London, United Kingdom. Electronic address: nsofat@sgul.ac.uk.
Abstract
OBJECTIVE: To investigate which cardiometabolic factors underlie clustering of osteoarthritis (OA) with cardiovascular disease, and the extent to which these mediate an effect of education. DESIGN: Genome-wide association study (GWAS) of OA was performed in UK Biobank (60,800 cases and 328,251 controls) to obtain genetic association estimates for OA risk. Genetic instruments and association estimates for body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP), smoking and education were obtained from existing GWAS summary data (sample sizes 188,577-866,834 individuals). Two-sample Mendelian randomization (MR) analyses were performed to investigate the effects of exposure traits on OA risk. MR mediation analyses were undertaken to investigate whether the cardiometabolic traits mediate any effect of education on OA risk. RESULTS: MR analyses identified protective effects of higher genetically predicted education (main MR analysis odds ratio (OR) per standard deviation increase 0.59, 95% confidence interval (CI) 0.54-0.64) and LDL-C levels (OR 0.94, 95%CI 0.91-0.98) on OA risk, and unfavourable effects of higher genetically predicted BMI (OR 1.82, 95%CI 1.73-1.92) and smoking (OR 2.23, 95%CI 1.85-2.68). There was no strong evidence of an effect of genetically predicted SBP on OA risk (OR 0.98, 95% CI 0.90-1.06). The proportion of the effect of genetically predicted education mediated through genetically predicted BMI and smoking was 35% (95%CI 13-57%). CONCLUSIONS: These findings highlight education, obesity and smoking as common mechanisms underlying OA and cardiovascular disease. These risk factors represent clinical and public health targets for reducing multi-morbidity related to the burden these common conditions.
OBJECTIVE: To investigate which cardiometabolic factors underlie clustering of osteoarthritis (OA) with cardiovascular disease, and the extent to which these mediate an effect of education. DESIGN: Genome-wide association study (GWAS) of OA was performed in UK Biobank (60,800 cases and 328,251 controls) to obtain genetic association estimates for OA risk. Genetic instruments and association estimates for body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP), smoking and education were obtained from existing GWAS summary data (sample sizes 188,577-866,834 individuals). Two-sample Mendelian randomization (MR) analyses were performed to investigate the effects of exposure traits on OA risk. MR mediation analyses were undertaken to investigate whether the cardiometabolic traits mediate any effect of education on OA risk. RESULTS: MR analyses identified protective effects of higher genetically predicted education (main MR analysis odds ratio (OR) per standard deviation increase 0.59, 95% confidence interval (CI) 0.54-0.64) and LDL-C levels (OR 0.94, 95%CI 0.91-0.98) on OA risk, and unfavourable effects of higher genetically predicted BMI (OR 1.82, 95%CI 1.73-1.92) and smoking (OR 2.23, 95%CI 1.85-2.68). There was no strong evidence of an effect of genetically predicted SBP on OA risk (OR 0.98, 95% CI 0.90-1.06). The proportion of the effect of genetically predicted education mediated through genetically predicted BMI and smoking was 35% (95%CI 13-57%). CONCLUSIONS: These findings highlight education, obesity and smoking as common mechanisms underlying OA and cardiovascular disease. These risk factors represent clinical and public health targets for reducing multi-morbidity related to the burden these common conditions.
Authors: Petri Böckerman; Jutta Viinikainen; Laura Pulkki-Råback; Christian Hakulinen; Niina Pitkänen; Terho Lehtimäki; Jaakko Pehkonen; Olli T Raitakari Journal: Prev Med Date: 2017-06-21 Impact factor: 4.018
Authors: Simon Haworth; Ruth Mitchell; Laura Corbin; Kaitlin H Wade; Tom Dudding; Ashley Budu-Aggrey; David Carslake; Gibran Hemani; Lavinia Paternoster; George Davey Smith; Neil Davies; Daniel J Lawson; Nicholas J Timpson Journal: Nat Commun Date: 2019-01-18 Impact factor: 14.919