Skip to navigation Skip to main content Skip to footer

Approved Research

Polygenic risk score and causality analysis of comorbidities for psychosis diseases

Principal Investigator: Dr Alpha Tom Kodamullil
Approved Research ID: 101861
Approval date: January 24th 2024

Lay summary

We want to learn more about why people with psychiatric disorders also exhibit physical health disorders such as type 2 diabetes and cardiovascular diseases, which can further exacerbate the person's overall health. To do this, we aim to study the genetic data from UKBioBank and existing studies on psychiatric disorders and the physical health disorders that occur alongside psychiatric diseases. First, we will perform a polygenic risk score (PRS) analysis to assess the risk of psychiatric patients developing conditions such as type 2 diabetes and cardiovascular diseases. PRS are scores that quantify an individual's risk of developing a disease based on the cumulative effect of single nucleotide polymorphisms (SNPs). This analysis also considers the probability of each SNP occurring in a patient without the condition being evaluated (healthy patient). We will use artificial neural networks (ANNs) and other machine learning models to study the genes of people with psychiatric diseases and other diseases like type 2 diabetes and heart disease. We will train these machine learning models to find patterns and relationships in the genetic data to help us predict who is at risk of developing these physical health problems. Finally, we will analyze the strength of linkage disequilibrium (LD) between each SNP and the disease to identify causal SNPs and genetic variants that directly influence a trait or disease. LD is a statistical concept that refers to the non-random association of genetic variants (single nucleotide polymorphisms or SNPs) at different locations on a chromosome. When two or more SNPs are found to be in LD, they tend to be inherited together more often than expected by chance alone. This is because they are located close to each other on the same chromosome and have not undergone much recombination during evolution. The project will take approximately six months, and the outcome of this study could provide insights into the genetic links between multiple diseases and causal mechanisms of SNPs on comorbidity development.