A Risk Score for Predicting Multiple Sclerosis.

Area of Science:

• Neuroimmunology
• Genetic Epidemiology

Background:

• Multiple sclerosis (MS) arises from a complex interplay of genetic predisposition and environmental triggers.
• First-degree relatives, particularly siblings of MS patients, exhibit a significantly elevated risk for developing the disease or asymptomatic neurological changes.

Purpose of the Study:

• To develop and validate a novel risk score for multiple sclerosis (MS) by integrating established genetic and environmental risk factors.
• To utilize this score to identify siblings of MS patients at the highest risk, facilitating targeted pre-symptomatic research.

Main Methods:

• A cohort comprising 78 MS probands, 121 unaffected siblings, and 103 healthy controls was analyzed.
• Genetic data (Illumina Immunochip) and personal history were collected; MS risk factors' odds ratios were synthesized into an additive risk score.
• Risk scores were calculated using HLA-DRB1*1501 allele and subsequently all MS-associated SNPs from the 2011 GWAS; extreme-risk individuals underwent MRI validation.

Main Results:

• Significant differences in risk scores were observed across MS patients, their siblings, and controls (p<0.0005).
• Unaffected siblings presented intermediate risk scores compared to MS patients and controls (p<0.0005).
• The optimal risk score achieved an Area Under the Curve (AUC) of 0.82 (95% CI 0.75-0.88), indicating strong discriminative power.

Conclusions:

• The developed MS risk score demonstrates performance on the threshold for clinical applicability.
• This tool effectively identifies high-risk sibling cohorts, crucial for informing and advancing pre-symptomatic longitudinal studies in multiple sclerosis research.