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331 A Machine Learning-based Pharmacogenomic Association Study of Major Adverse Cardiovascular Events (MACEs) in Caribbean Hispanic Patients on Clopidogrel

Published online by Cambridge University Press:  19 April 2022

Luis A. Rosario Arroyo
Affiliation:
Universidad Ana G. Mendez
Luis Rosario-Arroyo
Affiliation:
Health Sciences School, Ana G. Mendez University, Puerto Rico, USA
Krystal S Roman-Rodriguez
Affiliation:
College of Natural Sciences, Department of Biology, University of Puerto Rico at RÃo Piedras Campus, Puerto Rico, USA
Carola F Gonzalez-Lebron
Affiliation:
College of Natural Sciences, University of Puerto Rico at Humacao Campus, Puerto Rico, USA
Ednalise Santiago
Affiliation:
Research Centers in Minority Institutions (RCMI) Program, Center for Collaborative Research in Health Disparities (CCRHD), Academic Affairs Deanship, University of Puerto Rico, Medical Sciences Campus, Puerto Rico, USA
Mariangeli Monera-Paredes
Affiliation:
Biomedical Sciences Graduate Program, Pharmacology department, School of Medicine, University of Puerto Rico, Medical Sciences Campus, Puerto Rico, USA
Roberto A. Feliu-Maldonado
Affiliation:
Research Centers in Minority Institutions (RCMI) Program, Center for Collaborative Research in Health Disparities (CCRHD), Academic Affairs Deanship, University of Puerto Rico, Medical Sciences Campus, Puerto Rico, USA Integrated Informatics Services core IIS-RCMI, University of Puerto Rico, Medical Science Campus, Puerto Rico, USA
Abiel Roche-Lima
Affiliation:
Research Centers in Minority Institutions (RCMI) Program, Center for Collaborative Research in Health Disparities (CCRHD), Academic Affairs Deanship, University of Puerto Rico, Medical Sciences Campus, Puerto Rico, USA Integrated Informatics Services core IIS-RCMI, University of Puerto Rico, Medical Science Campus, Puerto Rico, USA
Jorge Duconge
Affiliation:
Research Centers in Minority Institutions (RCMI) Program, Center for Collaborative Research in Health Disparities (CCRHD), Academic Affairs Deanship, University of Puerto Rico, Medical Sciences Campus, Puerto Rico, USA Pharmaceutical Sciences department, School of Pharmacy, University of Puerto Rico, Medical Sciences Campus, Puerto Rico, USA
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Abstract

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OBJECTIVES/GOALS: To summarize baseline characteristics and risk factors for major adverse cardiovascular events (MACEs) and develop a prediction model by testing the association between genetic variants and MACEs in Caribbean Hispanic patients on clopidogrel using machine-learning (ML) techniques. METHODS/STUDY POPULATION: This is a secondary analysis of available clinical and genomic data from an existing database of 600 Caribbean Hispanic cardiovascular (CV) patients on clopidogrel. MACEs is defined as the composite of all-cause death, myocardial infarction, stroke and stent thrombosis over 6 months. Dataset is divided into training (60%) and testing (40%) sets, respectively. Two different supervised ML approaches (i.e. multiclass classification and regression algorithms) are applied to the study dataset using Python v3.5 and WEKA, and tested by receiver operating curve (ROC) analysis. A case-control association analysis between MACEs at 6 months and genotypes is performed by using chi-squared test. RESULTS/ANTICIPATED RESULTS: Average age of participants was 68 years-old, 55% males, with high prevalence of risk factors (i.e., overweight: 28.4 kg/m2; hypertension: 83.8%; hypercholesterolemia: 71.9% and diabetes: 54.8%). MACEs rate is 13.8%, with 33.5% resistant to clopidogrel. Logistic regression, KNN and gradient boosting showed the best performance, as suggested by ROC analysis and AUC CV scores of 0.6-0.7. A significant association between MACE occurrence and ≥3 risk alleles was found (OR=8.17; p=0.041). We anticipate that these genetic variants (CYP2C19*2, rs12777823, PON1-rs662, ABCB1-rs2032582, PEAR1-rs12041331) will uniquely contribute to clopidogrel resistance and MACEs in Caribbean Hispanics. DISCUSSION/SIGNIFICANCE: Our findings help address in part the long-standing problem of excluding minorities from research, which entails a gap of knowledge about clopidogrel pharmacogenomics in Puerto Ricans. This study provides a possible ML model that integrates clinical and pharmacogenomics for MACE risk estimation.

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Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2022. The Association for Clinical and Translational Science