José María Ordovás

The paper identifies DNA methylation and gene expression changes in human blood after a meal, linking them to cardiometabolic health and obesity-related genes.

The paper identifies four genetic loci associated with risk across seven cardiometabolic traits using GWAS in the UK Biobank and replication in independent meta-analyses.

The paper identifies mQTL effects of MS susceptibility loci on DNA methylation in CD4+ T cells, revealing both cis and trans regulatory impacts.

PhyteByte predicts bioactivity of food compounds using machine learning, identifying potential agonists of PPARG and other targets.

The paper develops a DNA methylation-based risk score for cardiovascular disease and shows it predicts risk independently of traditional factors.

The paper develops a gene-diet interaction score to predict dietary fat response for cardiometabolic risk factors using the Women's Health Initiative cohort.

The paper investigates the genetic relationship between low LDL-C and type-2 diabetes, identifying 31 loci and suggesting a causal link through Mendelian randomization.

The paper identifies DNA methylation modules and regions associated with incident cardiovascular disease and cumulative risk factor exposure using data from the Women's Health Initiative and Framingham Heart Study Offspring Cohort.

Inter-Tools aggregates protein interaction data from PSI-MITAB sources, creates species-specific interactomes, and provides basic analysis tools for interactome networks.