Integrated epidemiological, pharmacologic, omic and genetic profiles in Mexicans

BACKGROUND

Genetic, metabolomic and proteomic profiles are associated with the risk of many diseases, but are also altered by medication use, lifestyle or disease itself. European studies have reported that metabolic factors and medications alter the human metabolome independent of genetic predisposition to disease.

The aim of this project is to assess the metabolic and physiologic impact of pharmacological regimens in a Mexican population, and to map-out unexplored drug-metabolite associations, enhance understanding of on- and off-target effects of common medications and, ultimately, provide a Latino-American resource for experimental pharmaceutical research and clinical trials to inform drug usage and repurposing.

The Mexico City Prospective Study (MCPS) is a prospective cohort study of 150,000 participants with socio-demographic and lifestyle characteristics, medication and disease history, biological characteristics (including genetics and NMR-metabolomics) and 20 years of follow-up for cause-specific mortality.

The specific aims will be tailored to the applicant’s interests but could include:

1. characterising overall drug-metabolomic and disease-metabolomic associations among those taking individual or combined pharamacological regimens (eg, statins, anti-diabetic, cardio-protective, reno-protective, chemo, anti-depressant, anti-inflammatory, hormonal therapies).
2. assessing if drug-metabolite profiles (above) are independent of disease-metabolite associations. Using disease-specific polygenic risk scores (PRSs) for vascular, renal, diabetic, respiratory, and neoplastic causes, Mendelian Randomisation analyses can further assess if genetic-predisposition to specific diseases influences specific drug-omic-profiles.
3. assessing the potential confounding effect of BMI, smoking or physical exercise on the drug-metabolite associations above.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

The student will work in a multi-disciplinary team and will gain experience in genetic epidemiology and analysis of large prospective data. They will develop skills in study design for causal inference in a general population context, statistical programming and data analysis. The student will be supported to publish their results and present at conferences.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING

The project will be based within the MCPS group at the Big Data Institute, a world-class community for population health research. In-house training in statistical and epidemiological methods, programming, and scientific writing will be provided. Participation to departmental workshops and lectures is expected. 

PROSPECTIVE  STUDENT

The ideal candidate will have a good first degree and MSc in pharmacology, statistics, epidemiology, genetics, biomedical sciences or a related subject, and proficiency with programing analyses using different software.