Genetic Architecture of Multiple Sclerosis Across South Asian and African Ancestries
The article “Genetic determinants of Multiple Sclerosis susceptibility in diverse ancestral backgrounds” addresses a central limitation in contemporary neurogenetics: the disproportionate reliance on European-ancestry cohorts in genome-wide association studies of multiple sclerosis (MS). Although MS susceptibility is known to be highly polygenic, with major contributions from the Major Histocompatibility Complex (MHC), the authors emphasize that genetic risk prediction, causal fine-mapping, and therapeutic target discovery require broader ancestral representation. The study is presented as a medRxiv preprint and has not yet been peer reviewed, so its conclusions should be interpreted as preliminary rather than clinically directive.
Study Design and Cohort Construction
The investigators developed the ADAMS project, a UK-based genotype–phenotype study focused on people with MS from diverse ancestral backgrounds. Participants were recruited through clinical sites, an online platform, primary care, and the UK MS Register. Phenotypic data included demographic variables, MS history, treatment exposure, disability measures, and established risk factors such as family history, adolescent body mass index, smoking, and glandular fever. DNA was obtained from saliva samples, genotyped using the Illumina Global Screening Array, imputed, and combined with UK Biobank data to provide ancestrally matched controls.
Defining Ancestry for Genetic Analysis
A key methodological feature of the study was the use of genetic ancestry inference rather than reliance only on self-reported ethnicity. The authors used reference panels from the Human Genome Diversity Project and 1,000 Genomes to classify individuals and then focused on two broad inferred ancestry groups: South Asian and African. After quality control and exclusion of ambiguous ancestry outliers, the final genome-wide association analyses included 175 MS cases and 6,744 controls of South Asian ancestry, and 113 MS cases and 5,177 controls of African ancestry. This design strengthened the validity of within-ancestry comparisons, although the case numbers remained modest for a complex-trait GWAS.
Genome-Wide Association Findings
The principal genome-wide signal in both ancestry groups mapped to the MHC region on chromosome 6, consistent with the established immunogenetic basis of MS. In the South Asian ancestry cohort, the lead variant was near HLA-DRB1 with an odds ratio of 1.84, while in the African ancestry cohort the lead variant was near HLA-A with an odds ratio of 2.24. Outside the MHC, the authors observed several nominal associations, but none reached genome-wide significance, and the authors caution that these signals may reflect statistical noise or residual population structure rather than true susceptibility loci.
HLA Signals and Shared Immunogenetic Architecture
The HLA analysis provided a more detailed view of the MHC signal. In South Asian ancestry participants, several alleles showed suggestive associations, including risk-increasing effects for HLA-DPB1*10:01, HLA-B*37:01, HLA-A*26:01, and HLA-DRB1*15:01, as well as protective effects for HLA-DRB1*13:01 and HLA-DQB1*06:03. In African ancestry participants, HLA-A*66:01 was the strongest signal. Importantly, the canonical MS risk allele HLA-DRB1*15:01 showed concordant effects across ancestries, although its population-level contribution was lower in South Asian and African groups because of lower allele frequency.
European-Derived Polygenic Risk Scores in Non-European Cohorts
The authors also tested whether polygenic risk scores derived from European-ancestry MS GWAS data could predict MS susceptibility in South Asian and African ancestry participants. These scores performed better than chance, supporting a shared genetic architecture across populations, but their performance was substantially weaker than in European-ancestry cohorts. The best-performing score explained 1.6% of liability in the South Asian ancestry cohort and 0.5% in the African ancestry cohort, compared with a previously reported European-ancestry estimate of 4.3%. This result illustrates both the portability and the limitations of European-derived genetic prediction models.
Interpretation, Limitations, and Future Directions
Overall, the study supports the conclusion that MS susceptibility has a broadly shared genetic architecture across ancestral groups, particularly at immune-related loci within the MHC. However, the authors appropriately frame the work as an early step rather than a definitive map of ancestry-specific MS genetics. Major limitations include small case numbers, reliance on imputed rather than directly sequenced HLA alleles, use of cases and controls from partly distinct cohorts, and the absence of genome-wide significant non-MHC discoveries. The study’s broader importance lies in demonstrating the feasibility and necessity of larger multi-ancestry MS genetic studies, which could improve equitable risk prediction, refine causal variant discovery, and identify new therapeutic targets.
Disclaimer: This blog post is based on the provided research article and is intended for informational purposes only. It is not intended to provide medical advice. Please consult with a healthcare professional for any health concerns.
References:
Jacobs, B. M., Schalk, L., Tregaskis-Daniels, E., Scalfari, A., Nandoskar, A., Dunne, A., ... & Dobson, R. (2026). Genetic determinants of multiple sclerosis susceptibility in people from diverse ancestral backgrounds. Neurology, 106(7), e214708.
