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What Fluid Biomarkers Tell Us at Different Stages of Multiple Sclerosis

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Published Online: Dec 18th 2023 touchREVIEWS in Neurology. 2024;20(1):Online ahead of journal publication
Authors: Georgina Arrambide
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Abstract
Article
Article Information
Abstract:
Overview

Multiple sclerosis presents various challenges, leading to an exploration of fluid biomarkers that could provide insights into disease diagnosis, prognosis and treatment response. This editorial focuses on a few biomarkers that may be useful at different stages of multiple sclerosis, reviewing the evidence, potential uses and challenges to overcome for their clinical application. Fluid biomarkers, ranging from kappa free light chains for diagnosing multiple sclerosis to neurofilament light and glial fibrillary acidic protein for monitoring disease evolution or treatment response, could offer a more nuanced understanding of the disease and potential for targeted treatments.

Keywords

Diagnosisfluid biomarkersglial fibrillary acidic proteinkappa free light chainsmultiple sclerosisneurofilament lightprognosistreatment response

Article:

Multiple sclerosis (MS) is a complex disease that can pose significant challenges in diagnosis, monitoring and treatment. Over the years, the quest for more precise and accessible diagnostic tools has led to the exploration of different fluid biomarkers in cerebrospinal fluid (CSF) or serum. Fluid biomarkers can offer insights into the diagnosis, prognosis and treatment response of MS, from the initial diagnostic stages to long-term follow-up. This editorial reviews the use of several fluid biomarkers in MS, examining their utility and potential to transform the current paradigm.

Early diagnosis of multiple sclerosis

Diagnosing MS requires a combination of clinical assessment with magnetic resonance imaging (MRI) and laboratory investigations.1 The demonstration of CSF-restricted immunoglobulin G oligoclonal bands (OBs) has long been part of the diagnostic process.2 Although their role has been modified across different iterations of the McDonald criteria,1,3 their main contribution to MS diagnosis is the demonstration of the inflammatory nature of the symptoms and lesions observed on MRI.4 A limitation of OBs involves comparing the number of CSF and serum bands using immunoblotting, a process that is rater-dependent. Conversely, kappa free light chains (KFLCs) have emerged as rater-independent biomarkers due to their automated quantification.5 Of the different methods used to assess their intrathecal production, the KFLC index has the strongest evidence for differentiating MS from other diseases.6 It has also shown predictive value for a second attack or the fulfilment of the McDonald criteria in typical clinically isolated syndromes (CIS), yielding similar results to those obtained with OBs.7,8 No specific KFLC index cut-off has been established to date; however, recent studies have suggested that values above 6 could point towards an MS diagnosis if applied in the right clinical setting, demonstrating similar diagnostic properties to OB.5–8 Does this mean that the KFLC index could replace OBs in the diagnosis of MS? Both methods have strengths and limitations, and neither is specific to MS. One potential approach could involve using the KFLC index as a screening test.9 OB detection could be reserved for cases falling in a grey zone between clear negatives and positives or in negative cases, where the suspicion index of MS is high.

Neurofilament light chain (NfL) levels have also been studied in early MS. In radiologically isolated syndromes, increased CSF or serum NfL (sNfL) indicates a higher risk of future clinical activity.10,11 In typical CIS, sNfL z-scores with values above 1.5 were found to increase the risk of future clinical activity and the fulfilment of the 2017 McDonald criteria.12,13 Perhaps the use of NfL as a biomarker of MS diagnosis has not been fully explored due to its lack of specificity. However, it could be argued that OBs and KFLCs are useful in the right context, even though they are not specific to MS. Moreover, if increased NfL levels are associated with contrast-enhancing lesions, could they be used as a surrogate for dissemination in time? These are topics that our research group considers worth exploring, bearing in mind that the diagnosis of MS is a construct in which combinations of different findings may help increase diagnostic specificity, sensitivity or accuracy.

Monitoring disease activity, progression and treatment response

It has long been established that sNfL levels correlate with concentrations in CSF and are associated with clinical and MRI inflammatory activity in MS.14 Thus, they could be used regularly in clinical practice to monitor disease activity. Baseline sNfL levels, along with clinical and MRI findings, could aid in tailoring the selection of disease-modifying treatments (DMTs) for patients with differing degrees of inflammatory activity. Furthermore, sNfL levels decrease after starting DMT, particularly with highly effective treatments.14,15 These findings suggest that incorporating sNfL measurements into routine clinical assessments will help monitor treatment response; however, the methodology for doing so is yet to be clearly defined.

MRI is a very useful tool to assess treatment response, and it is currently difficult to envision a therapeutic landscape without it. What sNfL measurements could bring to the table is more frequent, real-time disease monitoring, enabling more timely interventions when necessary. However, sNfL levels are less clearly associated with disability progression. They are probably associated with inflammatory activity-related disability accrual, but they do not seem to predict progression independent of relapse activity or MRI inflammatory activity.13,16 Another emerging biomarker, glial fibrillary acidic protein (GFAP), appears to be associated with the severity of MS worsening, especially in progressive forms.17 Indeed, recent data suggest serum GFAP (sGFAP) to be a prognostic biomarker for future progression independent of relapse activity.16 That this biomarker can also be reliably measured in serum makes it complementary to sNfL. Using both sGFAP and sNfL as biomarkers would, therefore, assist clinicians in obtaining a more comprehensive view of neuroinflammation and neurodegeneration in individual patients; this, in turn, would improve decision-making processes. One common clinical scenario in which measuring both biomarkers could prove useful is when it is difficult to determine, from a purely clinical perspective, whether a patient is experiencing a relapse, a pseudo-relapse or a more severe disability accrual. In this setting, blood biomarker measurements could be conducted faster than an MRI in some institutions, again expediting the decision-making process.

However, the utility of sGFAP measurements for monitoring treatment response is a subject of consideration. While we still need to fine-tune the integration of sNfL with MRI findings and clinical biomarkers such as relapses, questions on the use of sGFAP for this purpose remain: Could increasing sGFAP levels indicate that certain DMTs are no longer useful in a given patient? Can highly efficacious DMTs decrease or at least stabilize sGFAP levels? Finally, could the value of other fluid biomarkers be enhanced if they were used in combination with sNfL and sGFAP? For instance, the KFLC index returns a metric result. In this sense, indexes above 100 increase the risk of a second attack in the following year after a CIS, particularly in subjects who also have sNfL z-scores of >1.5 and especially >3.0.7,12 However, evidence regarding the predictive value of the KFLC index for disability accrual remains limited.7

Challenges and opportunities

While the potential of fluid biomarkers in MS management is undeniable, several challenges must be addressed to ensure their successful integration into clinical practice. Standardization of measurement techniques, establishment of reference ranges and validation across different patient populations are crucial steps towards reliable biomarker adoption. Guaranteeing accessible and affordable testing is key, especially since some biomarker determinations may remain centralized in the foreseeable future. Efficient logistics, including the management of sample storage and shipping, must be carefully planned, particularly in regions with limited access to biomarker evaluation. Furthermore, the clinical implementation of fluid biomarkers and their interplay with imaging and clinical findings during disease evolution must be better defined, especially in progressive MS. Although no fluid biomarker is specific for MS, as our understanding of its disease mechanisms deepens, it seems clear that using fluid biomarker panels may be required to capture the multifaceted nature of MS. In turn, such detailed phenotyping could lead to targeted drug developments and a better design of clinical trials in specific patient subgroups.

Conclusions

Remarkable progress in our understanding of the trajectory of MS, from diagnosis to follow-up, and the assessment tools at our disposal. Fluid biomarkers, though not specific to MS, are proving valuable for its management. They contribute to the early diagnosis of MS and can be useful for optimizing treatment and monitoring disease evolution. Alongside existing clinical tools, such as MRI, these biomarkers have the potential to refine how we manage MS, ultimately improving outcomes and quality of life for those affected by this disease.

Article Information:
Disclosure

Georgina Arrambide has received compensation for consulting services, speaking honoraria, or participation in advisory boards from Merck, Roche, and Horizon Therapeutics and travel support for scientific meetings from Novartis, Roche, ECTRIMS, and EAN. She serves as editor for Europe of the Multiple Sclerosis Journal – Experimental, Translational and Clinical journal and as a member of the editorial and scientific committee of Acta Neurológica Colombiana. She is a member of the International Women in Multiple Sclerosis (iWiMS) network executive committee, the European Biomarkers in Multiple Sclerosis (BioMS-eu) steering committee and the MOGAD Eugene Devic European Network (MEDEN) steering group. She has received funding for projects on fluid and/or imaging biomarkers in multiple sclerosis from Instituto de Salud Carlos III, Spain (projects PI19/01590 and PI22/01570).

Compliance With Ethics

This article is an opinion piece and does not report on new clinical data, or any studies with human or animal subjects performed by the author.

Review Process

Double-blind peer review.

Authorship

The named author meets the International Committee of Medical Journal Editors (ICMJE) criteria for authorship of this manuscript, takes responsibility for the integrity of the work as a whole, and has given final approval for the version to be published.

Correspondence

Georgina ArrambideEdifici Cemcat, Hospital Universitario Vall d´HebronPasseig Vall d´Hebron 119-129, 08035 BarcelonaSpaingarrambide@cem-cat.org

Support

No funding was received in the publication of this article.

Access

This article is freely accessible at touchNEUROLOGY.com © Touch Medical Media 2023.

Data Availability

Data sharing is not applicable to this article as no datasets were generated or analysed during the writing of this article.

Received

2023-08-23

References

1. Thompson AJBanwell BLBarkhof Fet alDiagnosis of multiple sclerosis: 2017 revisions of the McDonald criteriaLancet Neurol2018;17:16273DOI10.1016/S1474-4422(17)30470-2.

2. Poser CMPaty DWScheinberg Let alNew diagnostic criteria for multiple sclerosis: Guidelines for research protocolsAnn Neurol1983;13:22731DOI10.1002/ana.410130302.

3. Polman CHReingold SCBanwell Bet alDiagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteriaAnn Neurol2011;69:292302DOI10.1002/ana.22366.

4. Arrambide GTintore MEspejo Cet alThe value of oligoclonal bands in the multiple sclerosis diagnostic criteriaBrain2018;141:107584DOI10.1093/brain/awy006.

5. Hegen HArrambide GGnanapavan Set alCerebrospinal fluid kappa free light chains for the diagnosis of multiple sclerosis: A systematic review and meta-analysisMult Scler2023;29:18295DOI10.1177/13524585221134217.

6. Leurs CETwaalfhoven HLissenberg-Witte BIet alKappa free light chains is a valid tool in the diagnostics of MS: A large multicenter studyMult Scler2020;26:91223DOI10.1177/1352458519845844.

7. Berek KBsteh GAuer Met alKappa-free light chains in CSF predict early multiple sclerosis disease activityNeurol Neuroimmunol Neuroinflamm2021;8:e1005DOI10.1212/NXI.0000000000001005.

8. Arrambide GEspejo CCarbonell-Mirabent Pet alThe kappa free light chain index and oligoclonal bands have a similar role in the McDonald criteriaBrain2022;145:393142DOI10.1093/brain/awac220.

9. Hegen HArrambide GGnanapavan Set alCerebrospinal fluid kappa free light chains for the diagnosis of multiple sclerosis: A consensus statementMult Scler2023;29:18295DOI10.1177/13524585221134217.

10. Matute-Blanch CVillar LMÁlvarez-Cermeño JCet alNeurofilament light chain and oligoclonal bands are prognostic biomarkers in radiologically isolated syndromeBrain2018;141:108593DOI10.1093/brain/awy021.

11. Bjornevik KMunger KLCortese Met alSerum neurofilament light chain levels in patients with presymptomatic multiple sclerosisJAMA Neurol2020;77:5864DOI10.1001/jamaneurol.2019.3238.

12. Hegen HBerek KBsteh Get alKappa free light chain and neurofilament light independently predict early multiple sclerosis disease activity—A cohort studyEBioMedicine2023;91:104573DOI10.1016/j.ebiom.2023.104573.

13. Arrambide GCarbonell-Mirabent PFissolo Net alPredictive sNfL Z score cut-offs in MS vary depending on the outcome and may help increase diagnostic specificity at the expense of sensitivity in CIS patients not fulfilling McDonald MS at baselinePresented at38th Congress of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS)Amsterdam, the Netherlands, 28 October 2022Abstr O177.

14. Benkert PMeier SSchaedelin Set alSerum neurofilament light chain for individual prognostication of disease activity in people with multiple sclerosis: A retrospective modelling and validation studyLancet Neurol2022;21:24657DOI10.1016/S1474-4422(22)00009-6.

15. Novakova LZetterberg HSundström Pet alMonitoring disease activity in multiple sclerosis using serum neurofilament light proteinNeurology2017;89:22307DOI10.1212/WNL.0000000000004683.

16. Meier SWillemse EAJSchaedelin Set alSerum glial fibrillary acidic protein compared with neurofilament light chain as a biomarker for disease progression in multiple sclerosisJAMA Neurol2023;80:28797. DOI10.1001/jamaneurol.2022.5250.

17. Abdelhak AFoschi MAbu-Rumeileh Set alBlood GFAP as an emerging biomarker in brain and spinal cord disordersNat Rev Neurol2022;18:15872DOI10.1038/s41582-021-00616-3.

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