MS: How the LTBR–LTA Axis Reframes Causality
Multiple sclerosis (MS) is classically framed as a T cell–driven demyelinating disease, but pinning down which immune signals are upstream drivers versus downstream noise has been hard. A large proteogenomic study in Nature Immunology gives us a cleaner causal map by pairing plasma proteomics with human genetics—then cross-walking the signals into immune-mediated diseases, including MS. The headline for MS: a trans-acting genetic effect that ties lymphotoxin biology to MS risk, with a tidy mechanistic story that’s hard to ignore.
What the study did—fast but rigorous
Researchers measured 91 inflammation-related proteins in plasma (Olink platform) across 14,824 Europeans and mapped 180 protein quantitative trait loci (pQTLs), two-thirds of which were trans associations (121 trans, 59 cis). Replication across independent cohorts and platforms showed broad robustness (e.g., Pearson r≈0.97 between discovery and replication effect sizes). This gives a high-confidence atlas linking common variants to circulating immune proteins.
They then integrated these pQTLs with eQTLs, GWAS data, and Mendelian randomization (MR). The integration mattered: many cis-pQTLs did not colocalize with whole-blood eQTLs, underscoring that plasma proteins often reflect non-blood sources and post-transcriptional regulation—one reason proteogenomics can surface drivers that transcript-only screens miss.
The MS signal: fewer LTBR transcripts, more circulating LTA, higher MS risk
A multiple-sclerosis–associated variant on chromosome 12 (rs2364485) emerged as a trans-pQTL for lymphotoxin-α (LTA, TNF-β). The MS risk allele (A) was associated with higher plasma LTA. Crucially, that same allele is a cis-eQTL that reduces expression of LTBR (lymphotoxin-β receptor) in blood and other tissues. Conditional colocalization supported a shared causal variant for LTBR expression and the MS association (posterior probability ≈0.86 for MS and 0.79 for LTBR eQTL), while pointing away from nearby TNFRSF1A as the mediator of this particular signal.
The simplest (and biologically neat) model is: risk allele → fewer LTBR receptors → less ligand binding → more LTA left circulating. Because the eQTL is cis to LTBR and the pQTL is trans to LTA, the directionality likely runs from the receptor to the ligand pool, not vice versa. Functionally, that implicates the LTBR–LTA axis in MS etiology rather than just inflammation “weather.”
Why this matters for human biology
LTA (a TNF-superfamily member) can signal via TNFR1 or, when complexed with LTB, through LTBR. The study’s genetics says the LTBR side of lymphotoxin biology is the relevant human causal lever at this locus in MS. That sharpened view is valuable because the neighborhood also houses TNFRSF1A, which harbors an independent, well-known MS signal; without the proteomic layer you might mis-assign causality. Proteogenomics here disentangles two close-by risk signals and anchors one to a receptor–ligand pair with a tractable mechanism.
A cautionary rhyme with anti-TNF history
Therapeutic context matters. Anti-TNF is a success in rheumatoid arthritis and IBD but can worsen MS or trigger demyelination—a stark reminder that “anti-inflammatory” is not a universal good in the CNS. The authors explicitly draw this parallel when discussing pathway pleiotropy and the need to anticipate disease-specific oppositions. It’s a sober note for anyone eyeing lymphotoxin or downstream nodes as drug targets in the brain.
CD40: protection in MS, risk in RA—same pathway, opposite directions
Their MR scan across immune-mediated diseases is a second lens on causal direction. For CD40, higher genetically proxied plasma levels increased rheumatoid arthritis risk but reduced risk for MS and IBD (MS OR≈0.75 per 1 s.d. increase). That is a clean illustration of pathway pleiotropy in humans: the same axis can push one disease while pulling another, and “turning the dial down” pharmacologically may help joints but harm brain or gut.
Why proteogenomics adds “humanized” insight for MS
It orders molecules along a causal chain. A cis eQTL on LTBR plus a trans pQTL on LTA argues the receptor change is upstream and the ligand elevation is a consequence. That’s more mechanistic than “protein X is up in patients.”
It disambiguates crowded loci. The LTBR versus TNFRSF1A question at 12p13 is answered with colocalization rather than proximity assumptions.
It quantifies therapeutic directionality. The CD40 example shows why “block the inflammator” can backfire by disease context; MR gives direction and magnitude in humans before a trial.
Limitations worth keeping in view
These proteins are measured in plasma, not CNS compartments; some genetic effects on soluble proteins won’t mirror tissue-local biology 1:1. Many cis pQTLs did not align with blood eQTLs (tissue specificity and post-transcriptional control are real), and the panel covered 91 proteins—a curated slice, not the proteome. Still, the replication and cross-modality convergence make the MS inference compelling.
Take-home for MS researchers and clinicians
The LTBR–LTA axis is causally implicated in MS risk: decreased LTBR expression associates with higher circulating LTA and higher MS risk. That nominates LTBR pathway biology—not just TNFR signaling in general—as a human-prioritized space for mechanistic and therapeutic exploration.
Pathway direction matters: approaches that broadly dampen TNF-superfamily signaling can diverge across diseases (cf. anti-TNF). Any LTBR/LTA-targeted strategy should be engineered with MS-specific safety signals in mind.
Use genomics to pre-sort targets: The same framework that validated IL-12B for IBD and flagged CXCL5 in ulcerative colitis also clarifies CD40’s opposite effects in RA versus MS—an argument for routine proteogenomic triage of immune targets before big trials.
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:
Zhao, J.H., Stacey, D., Eriksson, N. et al. Genetics of circulating inflammatory proteins identifies drivers of immune-mediated disease risk and therapeutic targets. Nat Immunol 24, 1540–1551 (2023). https://doi.org/10.1038/s41590-023-01588-w
