Leveraging Family History for Enhanced Polygenic Risk Score Calculation in Multiple Sclerosis

Polygenic risk scores (PRS) have revolutionized our understanding of genetic susceptibility to complex diseases, including multiple sclerosis (MS). In the article "Polygenic risk score association with multiple sclerosis susceptibility and phenotype in Europeans," Hengameh Shams et al. highlight the significant role of PRS in predicting MS risk and severity, emphasizing the utility of incorporating family history to refine these predictions further​​.

Understanding Polygenic Risk Scores
PRS aggregates the effects of numerous genetic variants to estimate an individual's genetic predisposition to a particular disease. For MS, a chronic inflammatory disease of the central nervous system, PRS has demonstrated considerable potential in identifying individuals at high risk. The study by Shams et al. leverages data from large genome-wide association studies (GWAS) to develop PRS that show robust associations with MS susceptibility and phenotypic outcomes​​.

The Role of Family History in PRS Calculation
Family history has long been recognized as a crucial factor in disease risk assessment. For MS, which exhibits familial aggregation, incorporating family history into PRS models can enhance their predictive power. The study shows that individuals within the top decile of PRS are at a significantly higher risk of developing MS compared to those with median PRS values​​.

The researchers utilized a comprehensive dataset from the International Multiple Sclerosis Genetics Consortium (IMSGC), which includes genetic data from over 47,000 MS cases and 68,000 controls. By applying advanced algorithms like LDPred2, they derived PRS that account for the polygenic nature of MS. The validation of these scores in independent cohorts, such as the UK Biobank and Kaiser Permanente in Northern California (KPNC), underscores their robustness​​.

Enhancing PRS with Familial Data
To assess the impact of familial genetic load, the study included DNA samples from 135 individuals across 35 multi-case families. These families comprised both affected and unaffected members, allowing for the examination of PRS distributions within a familial context. The findings indicate that affected siblings typically have higher PRS compared to their unaffected counterparts, particularly in families where one or both parents have high genetic risk scores​​.

Implications for Risk Prediction
Including family history in PRS calculations provides a more nuanced risk assessment. For instance, in families with discordant parental MS status, affected siblings exhibited higher PRS than their unaffected siblings, suggesting a potential for using PRS to identify at-risk individuals within families. This approach can aid in early diagnosis and intervention, potentially mitigating the disease's progression through tailored monitoring and preventive strategies​​.

The integration of PRS and family history into clinical practice could transform MS management. By identifying individuals with high genetic risk, healthcare providers can implement targeted surveillance and preventive measures, such as lifestyle modifications and early therapeutic interventions. This proactive approach could significantly reduce the disease burden and improve patient outcomes​​.

The study highlights the need for further research to optimize PRS models and validate them in diverse populations. Given the genetic heterogeneity of MS, expanding PRS research to include non-European cohorts is crucial for developing universally applicable risk prediction tools. Additionally, combining PRS with other biomarkers and environmental factors could enhance the accuracy of MS risk assessments​​.

Conclusion
The study by Shams et al. underscores the potential of PRS in predicting MS susceptibility and emphasizes the added value of incorporating family history into these models. By refining genetic risk assessments, we can move towards more personalized and effective strategies for managing MS, ultimately improving the quality of life for those affected by this debilitating disease.

Reference:
Shams, H., Shao, X., Santaniello, A., Kirkish, G., Harroud, A., Ma, Q., ... & Oksenberg, J. R. (2023). Polygenic risk score association with multiple sclerosis susceptibility and phenotype in Europeans. Brain, 146(2), 645-656.