Genetic Burden in Familial Versus Sporadic Multiple Sclerosis: Quantifying Polygenic Risk and the Central Role of HLA-DRB1*15

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disorder of the central nervous system with a multifactorial aetiology in which both genetic susceptibility and environmental exposures contribute to disease risk. Familial clustering is well recognised: roughly one-fifth of patients report an affected family member, and recurrence risk is higher among siblings than in the general population. Against this background, Mescheriakova and colleagues addressed a longstanding question in MS epidemiology—whether “multiplex” families (families with more than one affected relative) carry a measurably greater burden of known common risk alleles than patients with apparently sporadic MS, and whether such burden meaningfully relates to clinical phenotype or prediction.

Study design and participant ascertainment
The investigators assembled Dutch MS cases evaluated at the Erasmus Medical Centre (2004–2009) and classified individuals as familial (multiplex) or sporadic based on structured assessment of family history; multiplex families met the criterion of at least one first- or second-degree relative with clinically definite MS. After genotyping quality control and restriction to participants of European descent, the analytic sample comprised 569 MS patients and 2028 population controls from the Rotterdam Study III; for the principal familial–sporadic comparisons, 169 probands from multiplex families were used alongside 283 sporadic cases. Importantly, Table 1 indicates no statistically significant differences between multiplex probands and sporadic cases in core clinical descriptors—sex ratio, age at onset, disease course categories, EDSS, or MSSS—supporting the interpretation that any observed genetic differences are not trivially confounded by major phenotype imbalance.

Construction of the weighted genetic risk score
To operationalise “genetic burden,” the authors calculated a weighted genetic risk score (wGRS) using 102 non-HLA loci derived from established MS GWAS signals (with proxy/tagging SNPs used when needed), and they evaluated models with and without the major HLA class II risk allele HLA-DRB1*1501 (approximated by a high-LD tagging SNP, rs9271366). Each variant’s contribution was weighted by published effect sizes, thereby producing aggregate scores (wGRS102 and wGRS102+HLA) intended to capture cumulative susceptibility attributable to common variants rather than rare, family-specific mutations. This framework is particularly relevant for MS, where the HLA region has a disproportionately large effect and non-HLA loci individually exert modest odds ratios.

Principal finding: higher genetic burden in familial MS, driven by HLA
Across analyses, both sporadic and familial MS groups showed higher wGRS than controls, as expected for a polygenic disease; however, the key observation was that familial MS probands carried a significantly higher wGRS than sporadic cases when HLA-DRB11501 was included (Figure 1; Table 2). Numerically, wGRS102 differed modestly (11.60 in familial probands vs 11.48 in sporadic; trend-level P≈0.08), whereas wGRS102+HLA separated groups clearly (12.39 vs 12.04; P < 0.0001). Concordantly, the HLA-DRB11501 risk allele frequency was higher in familial probands (0.35) than in sporadic cases (0.25) and controls (0.13), indicating that enrichment of this major locus largely accounts for the familial–sporadic burden differential in this cohort.

Genetic burden and clinical phenotype: modest links, limited within families
The authors next evaluated whether higher polygenic burden translated into clinically relevant differences. In the combined MS sample, higher genetic burden (especially when including HLA) correlated with a lower age at disease onset, consistent with the concept that greater inherited susceptibility may lower the threshold for clinical manifestation (Figure 2). After stratification, the association with age at onset was significant in sporadic MS but not in multiplex probands, which the authors interpret cautiously in light of power constraints for the familial subgroup. Notably, the wGRS showed no meaningful relationship with disability severity (MSSS) or disease course, and no sex differences in genetic burden were observed within case strata—results that collectively suggest that currently known common variants explain susceptibility more readily than they explain heterogeneity in progression or clinical trajectory.

Prediction performance: statistically significant, clinically inadequate discrimination
A central translational question is whether aggregate genetic information can discriminate cases from controls (or familial from sporadic MS) with sufficient performance to inform clinical decision-making. Receiver operating characteristic analyses showed that models based on HLA alone or non-HLA loci alone were weak (AUC ~0.63 and ~0.66, respectively, for all MS vs controls), improving to ~0.72 when HLA and 102 non-HLA loci were combined (Figure 3; Table 3). The combined model performed better for familial MS vs controls (AUC ~0.77) than for sporadic MS vs controls (AUC ~0.69), consistent with greater genetic loading in multiplex families; nevertheless, discrimination between familial and sporadic MS was poor (AUC values near 0.61 at best), underscoring that the presently catalogued common-variant architecture is insufficient for clinically useful classification, particularly given MS’s relatively low population prevalence and the need for high specificity in risk prediction.

Interpretation, limitations, and future directions
This study provides empirical support—within a well-characterised Dutch cohort—that multiplex MS families are enriched for common risk alleles relative to sporadic cases, with the dominant contribution arising from HLA-DRB1*1501. The work also clarifies that, despite statistically detectable effects, polygenic scores built from known loci have limited clinical utility for diagnosis or prediction, and they do not robustly explain severity or course. The authors appropriately note limitations that constrain inference: simplified modelling of the HLA region using a single tagging SNP; moderate sample size (particularly for familial analyses of phenotype correlations); reliance on effect sizes estimated in general MS GWAS rather than multiplex-specific estimates; and potential attenuation introduced by proxy SNPs—though sensitivity checks reportedly preserved directionality. The logical next step is integrative modelling that incorporates additional HLA alleles, rare variants, and quantified environmental exposures, particularly within multiplex families where genetic enrichment can increase power to detect contributions beyond common GWAS loci.

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:
Mescheriakova, J. Y., Broer, L., Wahedi, S., Uitterlinden, A. G., van Duijn, C. M., & Hintzen, R. Q. (2016). Burden of genetic risk variants in multiple sclerosis families in the Netherlands. Multiple Sclerosis Journal–Experimental, Translational and Clinical, 2, 2055217316648721.