Multi-site Investigation of Genetic Determinants of Warfarin Dose Variability in Latinos.

We conducted a multi-site investigation of genetic determinants of warfarin dose variability in Latinos from the U.S. and Brazil. Patients from four institutions in the United States (n = 411) and Brazil (n = 663) were genotyped for VKORC1 c.-1639G> A, common CYP2C9 variants, CYP4F2*3, and NQO1*2. Multiple regression analysis was used in the U.S. cohort to test the association between warfarin dose and genotype, adjusting for clinical factors, with further testing in an independent cohort of Brazilians. In the U.S. cohort, VKORC1 and CYP2C9 variants were associated with lower warfarin dose (ß = -0.29, P < 2.0 × 10-16 ; ß = -0.21, P = 4.7 × 10-7 , respectively) whereas CYP4F2 and NQO1 variants were associated with higher dose (ß = 0.10, P = 2 × 10-4 ; ß = 0.10, P = 0.01, respectively). Associations with VKORC1 (ß = -0.14, P = 2.0 × 10-16 ), CYP2C9 (ß = -0.07, P = 5.6 × 10-10 ), and CYP4F2 (ß = 0.03, P = 3 × 10-3 ), but not NQO1*2 (ß = 0.01, P = 0.30), were replicated in the Brazilians, explaining 43-46% of warfarin dose variability among the cohorts from the U.S. and Brazil, respectively. We identified genetic associations with warfarin dose requirements in the largest cohort of ancestrally diverse, warfarin-treated Latinos from the United States and Brazil to date. We confirmed the association of variants in VKORC1, CYP2C9, and CYP4F2 with warfarin dose in Latinos from the United States and Brazil.

Machine Learning for Prediction of Stable Warfarin Dose in US Latinos and Latin Americans.

Populations used to create warfarin dose prediction algorithms largely lacked participants reporting Hispanic or Latino ethnicity. While previous research suggests nonlinear modeling improves warfarin dose prediction, this research has mainly focused on populations with primarily European ancestry. We compare the accuracy of stable warfarin dose prediction using linear and nonlinear machine learning models in a large cohort enriched for US Latinos and Latin Americans (ULLA). Each model was tested using the same variables as published by the International Warfarin Pharmacogenetics Consortium (IWPC) and using an expanded set of variables including ethnicity and warfarin indication. We utilized a multiple linear regression model and three nonlinear regression models: Bayesian Additive Regression Trees, Multivariate Adaptive Regression Splines, and Support Vector Regression. We compared each model's ability to predict stable warfarin dose within 20% of actual stable dose, confirming trained models in a 30% testing dataset with 100 rounds of resampling. In all patients (n = 7,030), inclusion of additional predictor variables led to a small but significant improvement in prediction of dose relative to the IWPC algorithm (47.8 versus 46.7% in IWPC, p = 1.43 × 10-15). Nonlinear models using IWPC variables did not significantly improve prediction of dose over the linear IWPC algorithm. In ULLA patients alone (n = 1,734), IWPC performed similarly to all other linear and nonlinear pharmacogenetic algorithms. Our results reinforce the validity of IWPC in a large, ethnically diverse population and suggest that additional variables that capture warfarin dose variability may improve warfarin dose prediction algorithms.

Ethnogeographic prevalence and implications of the 677C>T and 1298A>C MTHFR polymorphisms in US primary care populations.

Aim: Variants of the MTHFR gene have been associated with a wide range of diseases. Materials & methods: The present study analyzed data from clinical genotyping of MTHFR 677C>T and 1298A>C in 1405 patients in urban primary care settings. Results: Striking differences in ethnogeographic frequencies of MTHFR polymorphisms were observed. African-Americans appear to be protected from MTHFR deficiency. Hispanics and Caucasians may be at elevated risk due to increased frequencies of 677C>T and 1298A>C, respectively. Conclusion: Individuals carrying mutations for both genes were rare and doubly homozygous mutants were absent, suggesting the TTcc is extremely rare in the greater population. The results suggest multilocus MTHFR genotyping may yield deeper insight into the ethnogeographic association between MTHFR variants and disease.