Understanding and exploiting sterol metabolism in chronic kidney disease and cancer

Code: BC-DTP_2026_11

Title: Understanding and exploiting sterol metabolism in chronic kidney disease and cancer

Primary Supervisor: Ben Jacobs

Email: b.jacobs@qmul.ac.uk

Institute: Wolfson Institute of Population Health

Secondary Supervisor: Moneeza Siddiqui

Email: moneeza.siddiqui@qmul.ac.uk  

Institute: Wolfson Institute of Population Health

Lay Summary:

The Major Histocompatibility Complex (MHC) is a region of the human genome that controls how the immune system recognises pathogens. Because of this, the MHC plays a critical role in determining an individual’s—or even a species’—ability to effectively fight infection. Variations in the MHC also influence an individual’s risk of developing autoimmune disease. In fact, common variants in this region account for up to 50% of the genetic contribution to several major autoimmune conditions, including Rheumatoid Arthritis, Type 1 Diabetes Mellitus, and Multiple Sclerosis.

Understanding how genetic differences at the MHC affect susceptibility to autoimmune disease is essential for improving disease prediction and developing targeted treatments. However, most existing research has focused on White populations of European ancestry. MHC gene variants differ widely in frequency across ancestral groups, and failing to include people of diverse backgrounds means important risk‑related variants may be overlooked.

This PhD project aims to address this gap by investigating how MHC variation influences autoimmune disease risk in a cohort of over 60,000 British South Asians.

The student will gain skills in statistical genetics, data science, and working with electronic healthcare records. Their findings will help ensure that genetic risk prediction tools for autoimmune disease are accurate and applicable to British South Asian communities—particularly the local British Bangladeshi population. The project will generate code, data, and specialist expertise that will support other researchers and ultimately benefit the local community by enabling these scientific advances to be applied to a broad range of future research questions.

Aims:

1. Infer classical HLA alleles and phased long-range haplotypes in British South Asians using exome sequencing data from >60,000 participants.
2. Validate the HLA allele calls developed in aim 1 using both internal validation (via SNP-based imputation) and external validation (with UK Biobank sequencing data and reference data).
3. Test the association of classical HLA alleles with selected autoimmune diseases, and derive independent signals through fine-mapping and stepwise conditioning.
4. Develop genetic risk scores for selected autoimmune diseases by incorporating the HLA associations derived above with previously-described genome-wide associations for each of these traits.
5. Test whether these ancestry-specific genetic risk scores enhance the prediction of prevalent autoimmune disease in UK Biobank, with a specific focus on the performance gains for people of South Asian ancestry, and extend these findings to a local cohort of Multiple Sclerosis cases of diverse ancestry.