Unraveling the Genetic Complexity of Familial Multiple Sclerosis: Beyond Known Polymorphisms

Multiple sclerosis (MS) is a complex autoimmune disease that affects the central nervous system (CNS), leading to a range of neurological symptoms. It predominantly affects young adults and is characterized by chronic inflammation and demyelination. The genetic underpinnings of MS have been extensively studied through genome-wide association studies (GWAS), which have identified numerous risk loci. However, the role of these genetic factors in familial MS, particularly beyond known polymorphisms, remains an area of active research.

Genetic Contributions to MS
MS has a significant genetic component, with early studies showing higher concordance rates among monozygotic twins compared to dizygotic twins. Recent GWAS have identified over 100 risk loci associated with MS, highlighting the polygenic nature of the disease. Despite these advances, each identified locus contributes only marginally to the overall disease risk, and the functional relevance of many of these loci remains unclear.

Weighted Genetic Risk Score (wGRS)
A weighted genetic risk score (wGRS) has been developed to aggregate the effects of multiple MS-associated risk loci. This score is calculated by summing the risk alleles, each weighted by its odds ratio (OR), to estimate an individual's genetic predisposition to MS. While wGRS has shown promise in correlating with clinical and paraclinical features of MS, its utility in predicting MS in familial cases has been less clear.

Case Study: A Family with Multiple Affected Siblings
This study focuses on a family with several MS-affected members, including monozygotic triplets. The family was genotyped for 57 non-MHC risk loci and the HLA-DRB1*1501 tagging SNP rs3135388. The aim was to determine if the genetic load, as indicated by the wGRS, could predict MS manifestation in this familial context.

Clinical Characteristics and Genetic Findings
The oldest male child in the family was diagnosed with relapsing-remitting MS (RRMS) at age 25. His three younger sisters, who are monozygotic triplets, were diagnosed with RRMS at age 21. The genetic analysis confirmed their monozygosity and identified that the father, who is unaffected by MS, had the highest wGRS. This finding was contrary to the hypothesis that higher genetic load would be associated with disease manifestation.

Microarray Analysis
To further investigate the genetic basis of MS in this family, SNP microarray genotyping was performed. This analysis aimed to identify structural variations such as deletions, duplications, and regions of loss of heterozygosity (LOH) that could contribute to the MS phenotype. Several regions of interest were identified, including a significant LOH region on chromosome 15 harboring genes like MYEF2 and SLC27A2, which have potential roles in myelin regulation and lipid metabolism, respectively.

Discussion
The study's results suggest that while wGRS can be an indicator of MS risk in general, it may not be a reliable predictor in all familial cases. The highest wGRS in the unaffected father highlights the complexity of genetic contributions to MS. Additionally, the identified structural variations in the affected siblings point to potential genetic mechanisms beyond known polymorphisms that could influence MS susceptibility and progression.

The findings underscore the heterogeneous genetic background of MS and the need for further research integrating next-generation sequencing, epigenomics, proteomics, and transcriptomics. Such comprehensive analyses could uncover new pathways and targets for therapeutic strategies.

Conclusion
This study contributes to the understanding of genetic factors in familial MS, emphasizing the limitations of wGRS as a predictive tool in certain cases. The identification of novel structural variations provides new insights into the genetic architecture of MS, paving the way for future research to elucidate the complex interplay of genetic and environmental factors in this multifactorial disease.

References
Akkad, D. A., Lee, D. H., Bruch, K., Haghikia, A., Epplen, J. T., Hoffjan, S., & Linker, R. A. (2016). Multiple sclerosis in families: risk factors beyond known genetic polymorphisms. neurogenetics, 17, 131-135.