Hub members Have many expertise, covering most of the fields in bioinformatics and biostatistics. You'll find below a non-exhaustive list of these expertise
Searched keyword : Association studies
Related people (1)
Initially trained in evolutionary and environmental sciences, I studied population genetics and micro-evolutionary processes in a number of postdoctoral research projects. I recently joined the C3BI-Hub at the Institut Pasteur, where I work on various aspects involving Biostatistics and the analysis of genetic data.
Association studiesGenomicsGenotypingBiostatisticsGeneticsEvolutionPopulation genetics
BacteriaParasiteHumanInsect or arthropodOther animal
Related project (1)
Complex chronic diseases are caused by the accumulation of genetic, microbial and lifestyle factors. The number and complexity of such factors makes prediction of pathogenesis and therapy particularly difficult. Although a single factor is rarely sufficient to trigger pathology, genetic and environmental factors have so far been studied in isolation. Nevertheless, a substantial number of genetic variants have been associated with disease risk and the concomitant lifestyle shift and excessive hygiene are thought to contribute to the increased incidence in inflammatory diseases in industrialized countries. Moreover, clinical and experimental observations suggest a strong impact of gut microbiota on susceptibility to inflammatory diseases. The aim of 3D PATH is to explore the multiplicity and complexity of genetic, microbial and lifestyle factors associated with vulnerability to inflammatory pathology, using mice of the Collaborative Cross (CC), that model human genetic variability. Quantitative trait loci analyses, as well as integrative data analyses on metabolic and inflammatory outcomes will reveal new genetic variants and combinations of variants associated with disease susceptibility, and whether alterations of the gut microbiota in genetically susceptible mouse strains can trigger the phenotype. Moreover, the longitudinal design of experiments will allow us to identify early biomarkers that predict the pathology later in life. In a second step, validation of the identified risk factor combinations and exploration of the underlying molecular mechanisms will be performed taking advantage of the mouse model.