Multiple Sclerosis (MS) is a complex autoimmune disorder influenced by both genetic and environmental factors. According to the Atlas of MS (www.atlasofms.org), the prevalence of MS worldwide is 2.9 million individuals, with Europe bearing the highest MS disease burden. While genome-wide association studies (GWAS) have identified numerous risk loci, the evolutionary forces shaping the genetic architecture of MS remain poorly understood. Investigating whether MS-associated alleles bear signatures of natural selection can provide important insights into the evolutionary trade-offs that may underlie susceptibility to this disease.
We used large-scale population genomic resources—the 1000 Genomes Project and the Human Genome Diversity Project (HGDP) to explore signatures of recent and historical natural selection at loci implicated in MS. By applying integrated haplotype score(iHS), we have identified extended haplotype structures within populations, while cross-population extended haplotype homozygosity (XP-EHH) was used to detect differential selection across populations. To further refine these findings, we employed coalescent-based methods to reconstruct local genealogical histories using advanced tools such as Relate(3) and tsinfer(2). This enabled us to distinguish adaptive signals from those driven by neutral demographic processes.
To further validate my findings, we compared our results with GWAS summary statistics from the International Multiple Sclerosis Genetics Consortium (IMSGC)(1), which identified more than 200 loci associated with a higher risk of MS. Our analyses revealed evidence of selection in regions overlapping or proximal to known MS risk loci, particularly within immune-related pathways. Moreover, the integration of ARG-based genealogical reconstructions provided deeper insights into the timing, duration, and population-specific nature of selection processes shaping MS susceptibility. Overall, our findings highlight the evolutionary processes influencing MS-related genetic variation and emphasise the importance of studying complex diseases from an evolutionary perspective.