Genes in the Blood: How MS Risk Variants Reshape the Human Proteome

Multiple sclerosis (MS) is a complex immune-mediated disease in which the immune system mistakenly attacks the protective myelin sheath surrounding nerve fibers in the brain and spinal cord. This leads to inflammation, neurodegeneration, and a wide range of symptoms, from vision problems to muscle weakness and cognitive decline.

Over the past decade, genome-wide association studies (GWAS) have identified more than 200 genetic loci associated with MS susceptibility. However, most of these risk variants do not lie within protein-coding regions of the genome. Instead, they are found in regulatory regions that influence how genes are expressed. This suggests that these variants may contribute to disease by altering gene activity and protein abundance, rather than changing the structure of the proteins themselves.

Understanding how these genetic differences influence the plasma proteome—the complete set of proteins circulating in the blood—can help uncover the biological pathways through which MS risk alleles act. Such insights may reveal new therapeutic targets and improve our ability to design drugs that directly address the molecular causes of the disease.

A Proteogenomic Approach Using the UK Biobank
To investigate the biological impact of MS risk alleles, researchers from Queen Mary University of London, led by Dr. Benjamin Jacobs, analyzed genetic and plasma proteomic data from the UK Biobank, one of the largest biomedical resources in the world. This dataset includes proteomic measurements from around 54,000 participants.

The team performed a protein quantitative trait locus (pQTL) analysis, a method that identifies genetic variants influencing protein levels. They examined nearly 1,900 plasma proteins and linked this information with data from the largest MS GWAS conducted by the International Multiple Sclerosis Genetics Consortium, which included almost 15,000 individuals with MS and over 26,000 controls.

By integrating these two datasets, the researchers aimed to determine whether specific genetic variants associated with MS also influence plasma protein levels, and whether these proteins could mediate disease risk. Mendelian Randomization: Testing Causality Through Genetics
To explore whether changes in protein levels might cause MS rather than simply correlate with it, the researchers used a method called Mendelian randomization (MR). This approach takes advantage of the random assortment of genetic variants at conception, which mimics the conditions of a natural randomized trial.

If a genetic variant both alters the level of a protein and affects MS risk, and if these two effects are proportional, it suggests a causal relationship between the protein and the disease. This is particularly valuable in human studies, where direct experimental manipulation is often impossible.

Using MR, the researchers identified four proteins whose genetically predicted plasma levels were strongly linked to MS risk. These were CD58, CD40, TNFRSF1A, and FCRL3.

How Genetic Variants Influence Protein Expression
Each of these four proteins plays an important role in immune system regulation. The study found that higher levels of CD58 were associated with an increased risk of MS, while lower levels of CD40, TNFRSF1A, and FCRL3 were also linked to greater disease risk.

To better understand the mechanism behind these associations, the team conducted co-localization analyses, a statistical method that tests whether the same genetic variant drives both protein expression and disease risk. This approach confirmed that several known MS risk variants are also responsible for changes in protein levels.

For example, at the TNFRSF1A locus, the variant known as rs1800693C was identified as a shared causal variant influencing both MS risk and protein expression. This variant is known to affect how the TNFRSF1A gene is spliced, leading to increased production of a soluble form of the TNF receptor, rather than the standard membrane-bound form. The soluble version may interfere with normal immune signaling, contributing to inflammation and MS risk.

Similarly, at the CD40 locus, the risk allele rs4810485T was associated with decreased expression of full-length CD40 and increased production of decoy receptor forms. This variant is thought to disrupt immune regulation by weakening signaling between immune cells.

At the CD58 locus, the variant rs10801908C was linked to increased protein expression and higher MS risk. Although this variant is not known to influence splicing directly, it may regulate gene expression in a tissue-specific manner. The findings at this locus appear novel and suggest complex effects on how CD58 is expressed in different immune cell types.

Implications for Understanding and Treating MS
These findings provide compelling genetic evidence that MS risk alleles influence disease by altering the abundance or form of key immune-related proteins in the blood. Importantly, some of these proteins are already being explored as therapeutic targets.

For instance, TNFRSF1A is the target of drugs designed to block the inflammatory TNF signaling pathway, such as the selective TNFR1 antagonist atrosab. Similarly, CD40 is a co-stimulatory molecule critical for activating immune responses, and antibodies that inhibit this pathway, such as toralizumab and frexalimab, are already under development for autoimmune diseases, including MS.

By identifying these genetic links, the study strengthens the rationale for developing or repurposing drugs that target these specific pathways. It also highlights the power of combining large-scale genetic and proteomic data to uncover mechanisms of complex diseases.

Limitations and Future Directions
While the results are promising, there are some important limitations. The proteomic assays used in the UK Biobank measure overall protein concentrations in plasma but do not distinguish between different isoforms of the same protein. This means that the observed associations could reflect shifts in isoform balance rather than total protein abundance.

For example, in the case of TNFRSF1A, the risk allele may increase the soluble form of the protein while decreasing the membrane-bound form, and only one of these may be relevant to MS risk. More detailed proteomic and transcriptomic studies will be needed to clarify which protein forms are biologically active in disease development.

Additionally, because MS primarily affects the central nervous system, plasma proteins may only capture part of the story. Future studies examining protein changes in cerebrospinal fluid or brain tissue could provide a more complete view of how genetic risk translates into neuroinflammation and demyelination.

Towards Precision Neurology
This research represents an important step forward in understanding how genetic variation contributes to multiple sclerosis at the molecular level. By linking DNA changes to measurable shifts in plasma proteins, the study bridges the gap between genetic risk and biological mechanism.

In the long term, these insights could pave the way for more targeted and effective treatments. Rather than broadly suppressing the immune system, future therapies could focus on correcting the specific molecular pathways altered by MS risk variants. This approach aligns with the broader vision of precision neurology, where treatments are tailored to an individual’s genetic and molecular profile.

Summary
In summary, this study demonstrates that genetic variants associated with multiple sclerosis influence plasma levels of key immune-related proteins, including CD58, CD40, TNFRSF1A, and FCRL3. By combining data from the UK Biobank with the largest MS GWAS to date, the researchers identified causal links between genetic risk and protein abundance.

These findings provide strong genetic support for pharmacological targeting of these proteins and offer new insights into how MS develops at the molecular level. More broadly, this work illustrates the power of integrating genomics and proteomics to unravel complex diseases and guide the next generation of precision therapies.

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:
Healey S.A.B., Giovannoni G., Noyce A., Dobson R., & Jacobs B.M. (2024). Impact of Multiple Sclerosis Risk Alleles on the Plasma Proteome. Brain, 147(2), e17–e21. DOI: 10.1093/brain/awad363