Project ID CM-HD2024_14


Co Supervisor 1A Faculty of Life Sciences & Medicine, School of Basic & Medical Biosciences, Department of Medical & Molecular GeneticsWebsite

Co Supervisor 1B Institute of Psychiatry, Psychology and Neuroscience, Mental Health and Psychological Sciences, Social, Genetic and Developmental Psychiatry CentreWebsite

Additional Supervisor Prof. Timothy Vyse

Dissecting Pleiotropy in Systemic Lupus Erythematosus: Unravelling Shared Genetic Pathways across Diseases

Systemic Lupus Erythematosus (SLE) is a complex autoimmune disease. It has been observed that the genetic architecture of SLE often overlaps with other diseases, a phenomenon known as pleiotropy. This project aims to delve deeper into this aspect of SLE and ascertain how these shared genetic components influence the onset, progression, and treatment outcomes of SLE and its comorbidities.

Our primary objective is to analyze large Genome-Wide Association Studies (GWAS) data sets of SLE to identify shared genetic variants among multiple diseases. The data will help us better understand the underlying genetic basis of SLE and its association with other health conditions.

Throughout the course of the PhD project, the student will be trained in various bioinformatics and statistical techniques to analyze and interpret GWAS data. The skills acquired would include genetic data analysis, advanced statistical modeling, data visualization, and interpretation of complex biological data.

Year 1: The focus will be on acquiring essential skills and gaining an in-depth understanding of SLE genetics, pleiotropy, and GWAS analysis.

Year 2: The student will commence with a detailed analysis of the GWAS data, identifying overlapping genetic variants between SLE and other diseases.

Year 3: The findings from the analysis will be consolidated, followed by interpretation and synthesis of results to delineate the role of shared genetic components in disease manifestation and progression.

Year 4: The final year will involve drafting the PhD thesis, potential publication of results, and exploring translational aspects of our findings to determine how these insights could potentially shape future clinical approaches to SLE and associated conditions.

Representative Publications

1. Morris DL, Sheng Y, Zhang Y, Wang Y-F, Zhu Z, Tombleson P, Chen L, Graham D S-C, Bentham J, Chen R, Zuo X, Wang T, Wen L, Yang C, Liu L, Yang L, Li F, Huang Y, Yin X, Yang S, Rönnblom L, Fürnrohr BG, Voll RE, Schett G, Costedoat–Chalumeau N, Gaffney PM, Lau YL, Zhang X, Yang W, Cui Y, Vyse TJ. (2016). Genome-wide association meta-analysis in Chinese and European individuals identifies ten new loci associated with systemic lupus erythematosus. Nature Genetics. doi: 10.1038/ng.3603. Aug; 48(8): 940-946 2. Wang Y, Guga S, Wu K, Khaw Z, Tzoumkas K, Tombleson P, Comeau ME, Langefeld CD, Cunninghame Graham DS, Morris DL*, Vyse TJ*. COVID-19 and systemic lupus erythematosus genetics: A balance between autoimmune disease risk and protection against infection. PLOS Genetics. 3;18(11). 3. Morris DL. et al., (2012) Unraveling Multiple MHC Gene Associations with Systemic Lupus Erythematosus: Model Choice Indicates a Role for HLA Alleles and Non-HLA Genes in Europeans. The American Journal of Human Genetics. 91(5): p. 778-793.

Coleman JRI. et al. (2020). The genetics of the mood disorder spectrum: Genome-wide association analyses of more than 185,000 cases and 439,000 controls Biological psychiatry 88.2 (2020): 169-184.
Mundy J, Hübel C, Gelernter J, Levey D, Murray RM, Skelton M, Stein MB, Vassos E, Breen G, Coleman JRI. (2022). Psychological trauma and the genetic overlap between posttraumatic stress disorder and major depressive disorder. Psychological medicine, 52(16), 3975-3984.
Coleman JRI, Euesden J, Patel H, Folarin AA, Newhouse S, Breen G. (2016). Quality control, imputation and analysis of genome-wide genotyping data from the Illumina HumanCoreExome microarray. Briefings in functional genomics 15.4: 298-304.