Temporal Dynamics of Multiple Sclerosis Risk: Integrating Genetic Susceptibility and Early-Life Exposures
Multiple Sclerosis (MS) is a chronic autoimmune disorder characterized by demyelination within the central nervous system, with a well-established genetic component underlying disease susceptibility. Over the past two decades, genome-wide association studies (GWAS) have identified hundreds of loci associated with MS risk, predominantly in populations of European ancestry. However, this Eurocentric bias has limited the generalizability of genetic findings and constrained the development of equitable predictive models. The present study addresses this critical gap by investigating MS susceptibility in individuals of South Asian and African ancestry within a United Kingdom cohort, thereby contributing to a more globally representative understanding of disease genetics.
Study Design and Multi-Ancestry Cohort Construction
The study utilized the ADAMS (A Genetic Association study in Diverse Ancestries of Multiple Sclerosis) cohort, integrating genotyped MS cases with ancestrally matched controls from the UK Biobank. Genetic data were obtained through saliva-based DNA extraction and high-density genotyping arrays, followed by imputation using reference panels such as the Haplotype Reference Consortium and 1000 Genomes Project. Importantly, ancestry inference was conducted using principal component analysis and machine learning classification, enabling the identification of two major groups: South Asian (SAS) and African (AFR) ancestry cohorts. This design allowed for robust within-ancestry GWAS while minimizing confounding due to population stratification.
Genome-Wide Association Findings and the Central Role of the MHC
The GWAS analyses revealed that the strongest genetic associations with MS susceptibility in both ancestral groups were localized within the Major Histocompatibility Complex (MHC) region on chromosome 6. In the South Asian cohort, the lead signal was near the HLA-DRB1 gene, whereas in the African cohort, the strongest association was near HLA-A. These findings reinforce the central immunogenetic role of the MHC in MS pathogenesis across populations. Notably, no loci outside the MHC reached genome-wide significance, which the authors attribute to limited statistical power rather than absence of effect, highlighting the necessity for larger multi-ancestry cohorts.
Cross-Ancestry Concordance of Genetic Risk
A key objective of the study was to assess whether MS-associated variants identified in European populations exhibit similar effects in non-European ancestries. The analysis demonstrated a significant enrichment of European-derived risk alleles among MS cases in both SAS and AFR cohorts, with stronger concordance observed in South Asians. While the direction of effect was largely consistent, the magnitude of correlation was moderate, suggesting that shared biological mechanisms exist but are modulated by ancestry-specific factors such as linkage disequilibrium structure and allele frequency differences. These findings underscore both the universality and complexity of MS genetic architecture.
HLA Allelic Diversity and Ancestry-Specific Signals
Fine-mapping of the MHC region through HLA imputation revealed both shared and potentially ancestry-specific allelic associations. The well-established risk allele HLA-DRB115:01 demonstrated consistent effects across populations but exhibited markedly lower frequency in South Asian and African groups, resulting in reduced population-attributable risk. Additionally, novel associations such as HLA-DPB110:01 in South Asians and HLA-A*66:01 in Africans were identified, although their validity requires replication in larger cohorts. These observations highlight the importance of studying diverse populations to uncover genetic variants that may be rare or absent in European populations.
Polygenic Risk Scores and Predictive Limitations
The study further evaluated the performance of polygenic risk scores (PRS) derived from European GWAS when applied to non-European populations. Although PRS demonstrated statistically significant predictive ability in both SAS and AFR cohorts, their explanatory power was substantially reduced compared to European populations. Specifically, PRS accounted for approximately 1.6% of disease liability in South Asians and 0.5% in Africans, compared to over 4% in Europeans. This decline reflects differences in genetic architecture and emphasizes the limitations of transferring predictive models across ancestries without recalibration.
Implications and Future Directions in Multi-Ancestry Genomics
This study provides compelling evidence that while the genetic basis of MS is broadly shared across populations, significant ancestry-specific variation exists that impacts both biological understanding and clinical translation. The consistent involvement of the MHC region across ancestries supports common immunopathogenic pathways, whereas differences in allele frequency and effect size highlight the need for inclusive research frameworks. Crucially, the study underscores the importance of expanding multi-ancestry GWAS efforts to improve fine-mapping resolution, identify novel therapeutic targets, and develop equitable genetic risk prediction tools. As genomic medicine advances, incorporating diverse populations will be essential for ensuring that its benefits are universally accessible.
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.
