Relationship Between Metabolic Risk Factors and Genetic Predisposition in Coronary Heart Disease Risk
Investigating whether metabolic risk factors mediate the genetic risk for coronary heart disease, this study explores data from the Malm Diet and Cancer Study. Analysis includes the impact of genetic scores, family history, and metabolic risk factors like blood pressure and diabetes mellitus on CHD events in middle-aged participants. The study sheds light on the interplay between genetics and lifestyle factors in cardiovascular health.
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Do metabolic risk factors mediate the genetic risk for coronary heart disease? Josef Fritz1, Dov Shiffman2, Olle Melander3,4, Hayato Tada5, Hanno Ulmer1 1Department of Medical Statistics, Informatics and Health Economics, Medical University of Innsbruck, Austria 2Quest Diagnostics, San Juan Capistrano, CA, USA 3Department of Clinical Sciences, Lund University, Malm , Sweden 4Department of Internal Medicine, Sk ne University Hospital, Malm , Sweden 5Department of Cardiovascular and Internal Medicine, Kanazawa University Graduate School of Medicine, Kanazawa, Japan josef.fritz@i-med.ac.at 1
Declaration of interest Dov Shiffman is an employee of Quest Diagnostics. Otherwise, we have nothing to declare. 2
2016 ESC Guidelines on CVD prevention (1) A positive family history of premature CV death is associated with an increased risk of early and lifetime CVD. conventional CV risk factors can partly explain the impact of family history. Questions not answered: How much is explained? By which risk factors exactly? 3
2016 ESC Guidelines on CVD prevention (2) genetic scores to summarize the genetic component of CVD risk Studies found a significant association of genetic scores with incident CVD, adjusting for the main CV risk factors. 4
Measuring CHD genetics Family history of CHD self-reported Genetic risk scores (GRS) directly assessed based on multiple SNPs 2010: GRS13 2013: GRS46 2016: GRS50 (EHJ 2016;37:561-7) 5
Data used the Malm Diet and Cancer (MDC) study Community-based, prospective observational study 23,595 participants with complete data for our investigation Middle-aged men and women (aged 45-73) Enrolled between 1991 and 1996 2,213 first CHD events during a median follow-up of 14.4 years defined as coronary revascularization, fatal or nonfatal myocardial infarction, or death due to ischemic heart disease Measured metabolic risk factors: blood pressure, antihypertensive medication, apolipoproteins (A-I and B), diabetes mellitus Measured genetic risk factors: family history, GRS50 6
Metabolic risk factors are intermediate variables on the causal pathway between exposure (family history or GRS50) and outcome (CHD incidence) Age Sex Smoking Blood pressure including hypertension treatment Apolipoprotein B Apolipoprotein A-I Prevalent diabetes mellitus Family history of CHD or GRS50 CHD event Red: confounders; blue: mediators : direct effect; Total effect: direct and indirect effects together : indirect effects 7
Two examples for a strong direct effect: metabolically healthy person without risk factors and genetic risk for a strong indirect effect: metabolically unhealthy person with risk factors and genetic risk conventional CV risk factors explain the impact of genetic risk 8
Aim To decompose the total effect of family history of CHD or GRS50 into a direct effect and indirect effects mediated by metabolic risk factors in a statistical mediation analysis To quantitatively assess the fraction of family history and of GRS50 mediated through established cardio-metabolic risk pathways 9
Methods Natural effect models proposed by Lange et al. Am. J. Epidemiol. 2012;176:190-5 Am. J. Epidemiol. 2014;179:513-8 Novel method to perform statistical mediation analysis Embedded in the framework of causal inference and counterfactuals Cox proportional hazards and additive hazards models as final outcome models 10
Results: family history Metabolic mediators of CHD incidence Family history of CHD (yes vs. no) Effects Proportion explained (%) (95% CI) Additional incident CHD cases per 100,000 person-years at risk Hazard Ratio (95% CI) Total effect 1.52 (1.39 to 1.65) 100.0% 269.7 Direct effect 1.40 (1.28 to 1.52) 80.0% (73.6% to 85.2%) 220.2 Indirect effect, combined 1.09 (1.07 to 1.11) 20.0% (14.8% to 26.4%) 52.5 Indirect effect, through systolic BP 1.04 (1.03 to 1.05) 8.5% (5.9% to 12.0%) 23.5 Indirect effect, through apoA-I Indirect effect, through apoB Indirect effect, through diabetes mellitus Effects adjusted for age, sex, and smoking status 1.01 (1.00 to 1.01) 1.04 (1.03 to 1.05) 1.01 (1.00 to 1.02) 1.7% (0.2% to 3.4%) 8.3% (5.8% to 11.7%) 1.5% (-0.8% to 3.8%) 5.1 19.8 4.1 11
Results: family history Metabolic mediators of CHD incidence 4.1 19.8 Family history of CHD (yes vs. no) 5.1 Effects Proportion explained (%) (95% CI) Additional incident CHD cases per 100,000 person-years at risk Hazard Ratio (95% CI) Direct effect 23.5 Total effect 1.52 (1.39 to 1.65) 100.0% 269.7 Indirect effect through Direct effect 1.40 (1.28 to 1.52) 80.0% (73.6% to 85.2%) systolic BP 220.2 Indirect effect, combined 1.09 (1.07 to 1.11) 20.0% (14.8% to 26.4%) Indirect effect through apoA-I 52.5 Indirect effect, through systolic BP 1.04 (1.03 to 1.05) 8.5% (5.9% to 12.0%) Indirect effect through apoB 23.5 Indirect effect, through apoA-I Indirect effect, through apoB Indirect effect, through diabetes mellitus Effects adjusted for age, sex, and smoking status 1.01 (1.00 to 1.01) 1.04 (1.03 to 1.05) 1.01 (1.00 to 1.02) 1.7% (0.2% to 3.4%) 8.3% (5.8% to 11.7%) 1.5% (-0.8% to 3.8%) 5.1 19.8 4.1 Indirect effect through diabetes mellitus 220.2 Additional incident CHD cases per 100,000 person-years 12
Results: GRS50 Metabolic mediators of CHD incidence Highest vs. lowest quintile of GRS50 GRS50 (high vs. low) Hazard Ratio (95% CI)Proportion explained(%) Effects Additional incident CHD cases per 100,000 person-years at risk (95% CI) Total effect 2.01 (1.76 to 2.30) 100.0% 469.3 Direct effect 1.87 (1.64 to 2.14) 89.3% (84.0% to 94.2%) 424.7 Indirect effect, combined 1.08 (1.04 to 1.11) 10.7% (5.8% to 16.0%) 44.6 Indirect effect, through systolic BP 1.02 (1.01 to 1.04) 3.5% (1.0% to 5.9%) 16.2 Indirect effect, through apoA-I Indirect effect, through apoB Indirect effect, through diabetes mellitus Effects adjusted for age, sex, and smoking status 1.01 (1.00 to 1.02) 1.04 (1.03 to 1.06) 1.00 (0.99 to 1.02) 1.1% (-0.2% to 2.6%) 6.0% (3.7% to 8.6%) 0.2% (-1.6% to 2.7%) 5.3 22.3 0.7 13
Results: GRS50 Metabolic mediators of CHD incidence Highest vs. lowest quintiles of GRS50 16.25.322.3 0.7 GRS50 (high vs. low) Hazard Ratio (95% CI)Proportion explained(%) Effects Additional incident CHD cases per 100,000 person-years at risk Direct effect (95% CI) Indirect effect through systolic BP Total effect 2.01 (1.76 to 2.30) 100.0% 469.3 Indirect effect through apoA-I Direct effect 1.87 (1.64 to 2.14) 89.3% (84.0% to 94.2%) 424.7 Indirect effect, combined 1.08 (1.04 to 1.11) 10.7% (5.8% to 16.0%) 44.6 Indirect effect through apoB Indirect effect, through systolic BP 1.02 (1.01 to 1.04) 3.5% (1.0% to 5.9%) 16.2 Indirect effect through diabetes mellitus Indirect effect, through apoA-I Indirect effect, through apoB Indirect effect, through diabetes mellitus Effects adjusted for age, sex, and smoking status 1.01 (1.00 to 1.02) 1.04 (1.03 to 1.06) 1.00 (0.99 to 1.02) 1.1% (-0.2% to 2.6%) 6.0% (3.7% to 8.6%) 0.2% (-1.6% to 2.7%) 5.3 22.3 0.7 424.7 Additional incident CHD cases per 100,000 person-years 14
Conclusions Our data indicates that a fraction of the CHD risk associated with family history or with GRS50 is mediated through dyslipidaemia and hypertension, but not through diabetes. However, it seems that the major part ( 80%) of the genetic effect operates independently from the established metabolic risk factors. Metabolically healthy individuals with genetic predisposition form an important group of individuals at risk for CHD providing a major challenge for primary prevention. Therefore, intensified preventive measures in addition to risk factor surveillance and treatment may be of benefit in genetically predisposed individuals. 15
References Piepoli, M. F. et al. 2016 European Guidelines on cardiovascular disease prevention in clinical practice: The Sixth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice. Eur. Heart J. 37, 2315 81 (2016). Tada, H. et al. Risk prediction by genetic risk scores for coronary heart disease is independent of self- reported family history. Eur. Heart J. 37, 561 7 (2016). Schunkert, H. Family or SNPs: what counts for hereditary risk of coronary artery disease? Eur. Heart J. 37, 568 71 (2016). Lange, T., Vansteelandt, S. & Bekaert, M. A simple unified approach for estimating natural direct and indirect effects. Am. J. Epidemiol. 176, 190 5 (2012). Lange, T., Rasmussen, M. & Thygesen, L. C. Assessing natural direct and indirect effects through multiple pathways. Am. J. Epidemiol. 179, 513 8 (2014). 16
