Jesús Alegre-Díaz

This study conducts GWAS on blood pressure traits in 140,559 admixed Mexican adults, identifying novel genetic signals and highlighting ancestry-specific heterogeneity.

The paper improves metabolomic biomarker discovery in admixed American cohorts by training models on diverse data, achieving better predictive performance and more significant associations with cardiometabolic diseases.

The paper investigates the effect of the PKHD1L1 splice donor variant rs17368310 on female fertility, showing reduced child count in homozygous carriers across Finnish and Mexican populations.

The paper introduces Tractor-Mix, a mixed model method for GWAS in admixed cohorts with high relatedness, improving ancestry-specific association detection and controlling false positives.

This study identifies 86 T2D GWAS associations in 125,000 admixed Mexican adults, including 21 novel signals, and highlights the role of common regulatory variation in the endocrine pancreas.

This study identifies 207 height-associated genes using rare protein-altering variants from over 1.4 million individuals, showing large effect sizes and overlap with Mendelian height syndromes.

The paper estimates direct effects of genetic ancestry on complex traits in a Mexican population using family-based analyses and finds significant associations for height and type 2 diabetes but not for educational attainment.

This study compares clonal haematopoiesis (CH) between admixed Americans and Europeans, finding ancestry-specific genetic factors and lower CH prevalence in admixed populations.

The paper identifies protein-truncating variants in BSN associated with severe adult-onset obesity, type 2 diabetes, and fatty liver disease, with no effect on childhood adiposity.

This paper improves genetic scores for adiposity traits in East Asian populations by using trans-ancestry meta-analysis, increasing variance explained compared to European-derived scores.

The paper genotypes and sequences 140,000 adults from the Mexico City Prospective Study, revealing ancestry diversity and developing imputation resources for genetic studies.