An integrated atlas of adiposity traits in Mexican adults

BACKGROUND

In recent decades, the prevalence of obesity and diabetes has increased substantially in Latin-America, and the worldwide risks of death due to overweight and obesity have doubled. Obesity and various adipose traits are of clinical interest due to their causal link to cardiometabolic diseases and premature deaths. However, abdominal and gluteofemoral fat have opposing associations with cardiometabolic disease risk, as do fat and lean mass. Whether these inverse associations of different adiposity traits with favourable cardio-metabolic risk factors and cause-specific mortality share common genetically-determined pathways is unclear. Furthermore, populations with dominant Indigenous ancestry may have a more hazardous metabolic risk profile compared with European populations. However, there is limited evidence on the genetic architecture of various adiposity traits and pathways related to disease-specific risk in such populations. 

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. It provides a unique platform for genetic discovery studies of adipose traits in a contemporary admixed Hispanic population with a high degree of relatedness. 

The specific aims of the project may include:

1. characterising the genetic architecture of adiposity traits (e.g. BMI, fat and lean mass, WHR, hip and waist circumferences) in an admixed Mexican cohort through genome-wide association analyses. This would include resolving conditionally-independent associations, identifying novel variants that may be segregating at higher frequencies in Indigenous American populations, and genetic fine-mapping.
2. leveraging local ancestry analysis to detect population-specific genetic associations and systemically evaluate heterogeneity in genetic effects across ancestries for various adiposity traits (for example, using the TRACTOR method).
3. incorporating tissue- and cell-specific epigenomic annotations to resolve the molecular basis of genetic associations with adiposity through genome-wide enrichment analyses and molecular QTL colocalization analyses at trait-associated loci.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

The student will gain experience and skills in genetic epidemiology research in a general population context, analysis of large-scale prospective data using specific software, statistical programming, bioinformatics data analysis, and presentation skills. The student will be supported to publish peer-reviewed papers emerging from their DPhil.

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.

PROSPECTIVE  STUDENT

The ideal candidate will have a good first degree and MSc in statistics, epidemiology, genetics, biomedical sciences or related subject, and proficiency with programing analyses in R, Python, SUGEN, DEPICT packages.