Principal Investigator: Dr Robert Hoehndorf
King Abdullah University of Science and Technology
Computational Bioscience Research Center, 4700 KAUST, Thuwal, Mekkah 23955-6900, Saudi ArabiaTags: 31224, co-morbidity, complex disease, epidemiology, PheWAS
Lead Collaborators: 1) Professor Georgios Gkoutos
Collaborating Institutions and Addresses: 1) University of Birmingham
Institute of Cancer and Genomic Sciences
College of Medical and Dental Sciences
Lead Collaborators: 2) Dr Paul Schofield
Collaborating Institutions and Addresses: 2) University of Cambridge
Physiology Development and Neuroscience
Cambridge CB2 3EG
1a: There is evidence that genes implicated in similar diseases reflect underlying physiological networks, such that mutations in genes that normally interact with each other result in similar diseases. Common diseases, such as depression or diabetes result from having multiple genes affected in the same individual; the challenge is to identify which genes and variants are important and how the combination affects risk. We will develop a computational modelling approach examining diseases which occur together in the same individual (co-morbidity), and will identify common or overlapping disease mechanisms across the genome through correlating allele frequencies with observed relative risk.
1b: If successful, our research will identify molecular mechanisms for a large number of genetically-based complex diseases. Understanding them will aid in improving diagnosis, treatment, and prevention, and will have significant public health benefits.
1c: Our work consists of two steps, data preparation and pre-processing, and model construction. In the first step, we will extract relevant features from the genomic and phenotypic information in the cohort, and perform standard statistical analyses for genetic associations with disease, relative risk between diseases, and frequency of genetic variants within the cohort. In the second step, we will build a computational model (an algorithm) that explains the observed co-morbidities through the observed genetic variant frequencies.
1d: We will utilize all available genotype and phenotype data, i.e., the full cohort. This is to ensure the generality of our approach and to obtain sufficient statistical power for our statistical model.