Abstract: FR-OR93
Polygenic Scores for Incident Myocardial Infarction in CKD
Session Information
- Novel Clinical Impacts on Cardiorenal Disease
November 03, 2023 | Location: Room 103, Pennsylvania Convention Center
Abstract Time: 04:48 PM - 04:57 PM
Category: Hypertension and CVD
- 1602 Hypertension and CVD: Clinical
Authors
- Marthi, Amarnath, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
- He, Jiang, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States
- Rao, Panduranga S., University of Michigan Health System, Ann Arbor, Michigan, United States
- Rahman, Mahboob, University Hospitals, Cleveland, Ohio, United States
- Go, Alan S., Kaiser Permanente Division of Research, Oakland, California, United States
- Ricardo, Ana C., University of Illinois Chicago College of Medicine, Chicago, Illinois, United States
- Li, Yun, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
- Franceschini, Nora, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
Background
Improving prediction of cardiovascular events in CKD has focussed on integrating kidney biomarkers to existing models. In the general population, genetic data may provide orthogonal information to clinical variables, identifying individuals at high risk of coronary artery disease (CAD) even in the absence of classical risk factors. In CKD, where cardiovascular risk is elevated and underlying aetiology may differ, the utility of CAD polygenic scores (PGS) has not been assessed.
Methods
Individuals with genetic data at risk of incident myocardial infarction (MI) in the Chronic Renal Insufficiency Cohort (CRIC) were included. Following relevant quality control and imputation of array-derived genotypes, variants with an imputation quality RSQ ≥ 0.3 or RSQ ≥ 0.8 with minor allele frequency <0.01 were retained. Individuals were stratified as European [EUR] or African [AFR] ancestry (based on self-report and genotype). We applied PGS derived in European and multi-ancestry populations (pgscatalog.org), for CAD and for estimated glomerular filtration rate (eGFR), to Cox-proportional hazard models sequentially adjusted for: first 10 PCs, age, sex, baseline eGFR and statin use. The primary outcome was incident MI; over the follow-up period and after censoring at dialysis initiation.
Results
1175 AFR and 1607 EUR individuals in CRIC included, had 142 (12.1%) and 156 (9.7%) MI events, respectively, including 79 (6.7%) and 113 (7.0%) events occurring before dialysis initiation. Variant availability limited application of some PGS (Tcheandjieu 2022). Among EUR individuals, one standard deviation increase in European-derived CAD PGS was associated with 31% increased hazard of MI (95% confidence interval [CI] 1.1 – 1.56). This result was similar when events were censored at dialysis (1.35, 95% CI 1.1 – 1.66). However, the CAD-PGS association was not significant in CRIC AFR individuals or when using PGS for eGFR in both AFR or EUR individuals.
Conclusion
Current PGS for CAD predicts incident MI in European ancestry individuals with CKD but no significant effect was revealed in African ancestry individuals. As PGS is being considered as a potential tool for prediction in clinical practice, there is a pressing need to understand the genetic architecture of CAD in the milieu of CKD and how PGS perform in the context of diverse ancestry.
Funding
- Other NIH Support