EHR and phenotype analysis of rare and common variants and disease genes leading to complex diseases, and expansion of models of regional constraint in the human genome
Principal Investigator: Professor Kai Wang
Approved Research ID: 54327
Approval date: November 20th 2019
Finding regions of constraint in the human genome is critical to uncovering new disease genes and determining which variants are more likely to cause severe autosomal dominant developmental phenotypes. Areas of the genome that are constrained, by definition do not tolerate genetic changes (variants) in the general healthy population. If mutated, these areas are highly likely to lead to disease, and delineating the boundaries of these regions is critical to our advancement of disease literature and human health. Additionally, many human diseases are associated with genetic variants in genetic association studies, and some of them are highly penetrant variants that are believed to be clinically actionable or have therapeutic value. However, such variants may potentially contribute to other diseases/phenotypes which are undiscovered yet given the large amount of individuals required to be genotyped. Moreover, although some genetic variants can contribute to protecting human body from dangerous pathogens but they may also be deleterious to human survival. As a great example, in a recent study using the UK Biobank data, it has been shown that although a specific mutation in the gene CCR5 can prevent HIV, at the same time it increases the overall death rates among individuals who carry such a mutation. Therefore, it is critical to delineate different aspects of such mutations. In this project, we aim to identify all of the genetic mutations which are significantly associated with one disease, but also affects additional under-explored diseases/phenotypes (including EHR-derived phenotypes that are not originally diagnosed by icd9/icd10 or disease names) that they may not be known in literature.