NINJ2 Regulatory Variation and Gene Expression as Predictors of Interferon-β Response in Relapsing–Remitting Multiple Sclerosis

Clinical Problem and Rationale.
Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system with substantial heterogeneity in clinical course and treatment response, particularly in relapsing–remitting MS (RRMS). Interferon-β (IFN-β) remains a widely used first-line disease-modifying therapy, yet a sizeable fraction of patients exhibit suboptimal response, and confirming non-response can require prolonged follow-up. This creates a clear need for pharmacogenomic biomarkers that could predict, early in the treatment course, which patients are unlikely to benefit from IFN-β. Khorrami and colleagues address this problem by examining whether a regulatory polymorphism in NINJ2 (rs7298096) and NINJ2 mRNA expression are interdependent determinants of IFN-β responsiveness in an Iranian RRMS cohort.

Study Cohort and Phenotyping Strategy.
The investigators enrolled 205 RRMS patients receiving IFN-β for at least 12 months and stratified them into 99 responders and 106 non-responders, collecting demographic and clinical variables including relapse metrics, first symptoms, and disability as assessed by EDSS, alongside MRI findings. While age and sex distribution did not differ materially between groups, several disease activity indicators did: annualized relapse rate, relapse measures, first symptoms, and baseline EDSS showed statistically significant differences between responders and non-responders (Table 1), reinforcing that the two groups represent clinically meaningful response strata rather than arbitrary partitions.

Genetic Association of rs7298096 With IFN-β Response.
Genotyping focused on rs7298096 (G>A), a single nucleotide polymorphism positioned approximately 3.5 kb upstream of the NINJ2 transcription start site in a predicted regulatory region. Using high-resolution melting (HRM) with confirmatory Sanger sequencing in a subset, the authors report that both genotype and allele distributions differed strongly between responders and non-responders (Table 2; both p< 0.001). Notably, responders were enriched for GG (52.5%) and had a higher G allele frequency (69.2%), whereas non-responders were enriched for AA (42.5%) with a higher A allele frequency (61.8%); the reported odds ratio for the allele contrast was 3.632 (95% CI 2.411–5.471), consistent with a substantial association between rs7298096 and non-response to IFN-β in this cohort.

Differential NINJ2 Expression in Responders vs Non-Responders.
To test whether the putatively regulatory variant corresponded to transcriptional differences, the study quantified NINJ2 mRNA in whole blood via SYBR-green qPCR, normalized to GAPDH and analyzed using the ΔΔCt framework. At the cohort level, NINJ2 expression was significantly increased in non-responders compared with responders (p=0.024; Figure 1), suggesting that elevated NINJ2 transcription may be a molecular correlate of inadequate IFN-β clinical response. Importantly, the authors report no significant relationships between NINJ2 expression and certain covariates (e.g., age, disease onset, EDSS) within their analyses, implying that the observed expression shift is not trivially explained by those factors alone.

Genotype–Expression Interdependency Signals a Regulatory Mechanism.
Beyond the main effects of genotype and expression, the central contribution of the paper is the combined pattern: NINJ2 expression differed significantly across rs7298096 genotypes when stratified by responder status (p=0.032; Figure 2). The AA genotype in the non-responder group exhibited the highest NINJ2 mRNA levels, whereas the AA genotype in the responder group showed the lowest relative expression; intermediate patterns were observed for GA and GG across groups. This genotype–expression interaction is consistent with the authors’ interpretation that rs7298096 may influence transcriptional regulation (directly or via linkage with nearby functional elements), and that the resulting expression state is clinically relevant to IFN-β responsiveness.

Biological Plausibility in the Context of Immune Trafficking and IFN-β Activity.
NINJ2 encodes ninjurin-2, described here as a cell-surface adhesion molecule implicated in processes such as inflammation and endothelial activation, with high expression in the nervous system. The authors situate their findings in a mechanistic frame aligned with established IFN-β biology: IFN-β can modulate adhesion and migration of immune cells from peripheral blood into the CNS via effects on adhesion molecules expressed by endothelial and immune cells. Within this conceptual model, higher NINJ2 expression—particularly in AA carriers among non-responders—could reflect (or contribute to) a pro-migratory/adhesive immune milieu associated with higher disease activity, whereas effective IFN-β response may involve down-regulation of such pathways, including NINJ2 transcription. This mechanistic interpretation remains inferential in the present work (association plus expression correlation), but it provides a coherent hypothesis for downstream functional validation.

Translational Implications, Limitations, and Next Steps.
If replicated, the combined use of rs7298096 genotyping and NINJ2 expression profiling could contribute to a clinically actionable stratification strategy: identifying patients at higher risk of IFN-β non-response earlier, thereby reducing exposure to ineffective therapy and accelerating transition to alternative disease-modifying treatments. However, the authors appropriately emphasize the need for larger cohorts and multi-ethnic replication, as well as deeper functional experiments to establish causality and to map how rs7298096 (or linked variants) modulates NINJ2 regulatory activity within relevant immune cell subsets. Future prospective studies that integrate genetic variation, longitudinal expression dynamics under therapy, neutralizing antibody status, and standardized response definitions would be especially valuable for determining whether NINJ2 can mature from a promising biomarker signal into a robust component of precision therapeutics for RRMS.

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:
Khorrami, M., Saneipour, M., Moridnia, A., Shaygannejad, V., Sadeghi, E., Kassani, A., ... & Mirmosayyeb, O. (2024). Interdependency of NINJ2 gene expression and polymorphism with susceptibility and response to interferon beta in patients with multiple sclerosis. International Journal of Neuroscience, 134(4), 347-352.