Serum neurofilament light chain levels predict long-term disability progression in patients with progressive multiple sclerosis

Serum biomarker levels predict disability progression in patients with primary progressive multiple sclerosis

BACKGROUND

We aimed to investigate the potential of serum biomarker levels to predict disability progression in a multicentric real-world cohort of patients with primary progressive multiple sclerosis (PPMS).

METHODS

A total of 141 patients with PPMS from 18 European MS centres were included. Disability progression was investigated using change in Expanded Disability Status Scale (EDSS) score over three time intervals: baseline to 2 years, 6 years and to the last follow-up. Serum levels of neurofilament light chain (sNfL), glial fibrillar acidic protein (sGFAP) and chitinase 3-like 1 (sCHI3L1) were measured using single-molecule array assays at baseline. Correlations between biomarker levels, and between biomarkers and age were quantified using Spearman's r. Univariable and multivariable linear models were performed to assess associations between biomarker levels and EDSS change over the different time periods.

RESULTS

Median (IQR) age of patients was 52.9 (46.4-58.5) years, and 58 (41.1%) were men. Median follow-up time was 9.1 (7.0-12.6) years. Only 8 (5.7%) patients received treatment during follow-up. sNfL and sGFAP levels were moderately correlated (r=0.43) and both weakly correlated with sCHI3L1 levels (r=0.19 and r=0.17, respectively). In multivariable analyses, levels of the three biomarkers were associated with EDSS changes across all time periods. However, when analysis was restricted to non-inflammatory patients according to clinical and radiological parameters (n=64), only sCHI3L1 levels remained associated with future EDSS change.

CONCLUSIONS

Levels of sNfL, sGFAP and sCHI3L1 are prognostic biomarkers associated with disability progression in patients with PPMS, being CHI3L1 findings less dependent on the inflammatory component associated with disease progression.

Guidance for use of neurofilament light chain as a cerebrospinal fluid and blood biomarker in multiple sclerosis management

Neurofilament light chain (NfL) is a long-awaited blood biomarker that can provide clinically useful information about prognosis and therapeutic efficacy in multiple sclerosis (MS). There is now substantial evidence for this biomarker to be used alongside magnetic resonance imaging (MRI) and clinical measures of disease progression as a decision-making tool for the management of patients with MS. Serum NfL (sNfL) has certain advantages over traditional measures of MS disease progression such as MRI because it is relatively noninvasive, inexpensive, and can be repeated frequently to monitor activity and treatment efficacy. sNfL levels can be monitored regularly in patients with MS to determine change from baseline and predict subclinical disease activity, relapse risk, and the development of gadolinium-enhancing (Gd+) lesions. sNfL does not replace MRI, which provides information related to spatial localisation and lesion stage. Laboratory platforms are starting to be made available for clinical application of sNfL in several countries. Further work is needed to resolve issues around comparisons across testing platforms (absolute values) and normalisation (reference ranges) in order to guide interpretation of the results.

Association between serum multi-protein biomarker profile and real-world disability in multiple sclerosis

Few studies examined blood biomarkers informative of patient-reported outcome (PRO) of disability in people with multiple sclerosis (MS). We examined the associations between serum multi-protein biomarker profiles and patient-reported MS disability. In this cross-sectional study (2017-2020), adults with diagnosis of MS (or precursors) from two independent clinic-based cohorts were divided into a training and test set. For predictors, we examined seven clinical factors (age at sample collection, sex, race/ethnicity, disease subtype, disease duration, disease-modifying therapy [DMT], and time interval between sample collection and closest PRO assessment) and 19 serum protein biomarkers potentially associated with MS disease activity endpoints identified from prior studies. We trained machine learning (ML) models (Least Absolute Shrinkage and Selection Operator regression [LASSO], Random Forest, Extreme Gradient Boosting, Support Vector Machines, stacking ensemble learning, and stacking classification) for predicting Patient Determined Disease Steps (PDDS) score as the primary endpoint and reported model performance using the held-out test set. The study included 431 participants (mean age 49 years, 81% women, 94% non-Hispanic White). For binary PDDS score, combined feature input of routine clinical factors and the 19 proteins consistently outperformed base models (comprising clinical features alone or clinical features plus one single protein at a time) in predicting severe (PDDS ≥ 4) versus mild/moderate (PDDS < 4) disability across multiple machine learning approaches, with LASSO achieving the best area under the curve (AUCPDDS = 0.91) and other metrics. For ordinal PDDS score, LASSO model comprising combined clinical factors and 19 proteins as feature input (R2PDDS = 0.31) again outperformed base models. The two best-performing LASSO models (i.e., binary and ordinal PDDS score) shared six clinical features (age, sex, race/ethnicity, disease subtype, disease duration, DMT efficacy) and nine proteins (cluster of differentiation 6, CUB-domain-containing protein 1, contactin-2, interleukin-12 subunit-beta, neurofilament light chain [NfL], protogenin, serpin family A member 9, tumor necrosis factor superfamily member 13B, versican). By comparison, LASSO models with clinical features plus one single protein at a time as feature input did not select either NfL or glial fibrillary acidic protein (GFAP) as a final feature. Forcing either NfL or GFAP as a single protein feature into models did not improve performance beyond clinical features alone. Stacking classification model using five functional pathways to represent multiple proteins as meta-features implicated those involved in neuroaxonal integrity as significant contributors to predictive performance. Thus, serum multi-protein biomarker profiles improve the prediction of real-world MS disability status beyond clinical profile alone or clinical profile plus single protein biomarker, reaching clinically actionable performance.

Validity of serum neurofilament light chain as a prognostic biomarker of disease activity in multiple sclerosis

Multiple sclerosis (MS) is a chronic demyelinating and neuroinflammatory disease of the human central nervous system with complex pathoetiology, heterogeneous presentations and an unpredictable course of disease progression. There remains an urgent need to identify and validate a biomarker that can reliably predict the initiation and progression of MS as well as identify patient responses to disease-modifying treatments/therapies (DMTs). Studies exploring biomarkers in MS and other neurodegenerative diseases currently focus mainly on cerebrospinal fluid (CSF) analyses, which are invasive and impractical to perform on a repeated basis. Recent studies, replacing CSF with peripheral blood samples, have revealed that the elevation of serum neurofilament light chain (sNfL) in the clinical stages of MS is, potentially, an ideal prognostic biomarker for predicting disease progression and for possibly guiding treatment decisions. However, there are unresolved factors (the definition of abnormal values of sNfL concentration, the standardisation of measurement and the amount of change in sNfL concentration that is significant) that are preventing its use as a biomarker in routine clinical practice for MS. This updated review critiques these recent findings and highlights areas for focussed work to facilitate the use of sNfL as a prognostic biomarker in MS management.

Association of Serum Neurofilament Light Chain Levels at Disease Onset With Disability Worsening in Patients With a First Demyelinating Multiple Sclerosis Event Not Treated With High-Efficacy Drugs

Importance

The value of serum neurofilament light chain (sNfL) levels for predicting long-term disability in patients with multiple sclerosis (MS) remains controversial.

Objective

To assess whether high sNfL values are associated with disability worsening in patients who underwent their first demyelinating MS event.

Design, Setting, and Participants

This multicenter cohort study included patients who underwent their first demyelinating event suggestive of MS at Hospital Universitario Ramón y Cajal (development cohort; June 1, 1994, to September 31, 2021, with follow-up until August 31, 2022) and 8 Spanish hospitals (validation cohort; October 1, 1995, to August 4, 2020, with follow-up until August 16, 2022).

Exposures

Clinical evaluations at least every 6 months.

Main Outcomes and Measures

The main outcomes were 6-month confirmed disability worsening (CDW) and an Expanded Disability Status Scale (EDSS) score of 3. Levels of sNfL were measured in blood samples obtained within 12 months after disease onset using a single molecule array kit. The cutoffs used were sNfL level of 10 pg/mL and a standardized score (z score) of 1.5. Multivariable Cox proportional hazards regression models were used to evaluate outcomes.

Results

Of the 578 patients included in the study, 327 were in the development cohort (median age at sNfL analysis, 34.1 years [IQR, 27.2-42.7 years]; 226 female [69.1%]) and 251 patients were in the validation cohort (median age at sNfL analysis, 33.3 years [IQR, 27.4-41.5 years]; 184 female [73.3%]). The median follow-up was 7.10 years (IQR, 4.18-10.0 years). Levels of sNfL greater than 10 pg/mL were independently associated with higher risk of 6-month CDW and an EDSS of 3 in the development cohort (6-month CDW: hazard ratio [HR], 2.39; 95% CI, 1.39-4.12; P = .002; EDSS of 3: HR, 4.12; 95% CI, 2.18-7.77; P < .001) and the validation cohort (6-month CDW: HR, 1.61; 95% CI, 1.07-2.42; P = .02; EDSS of 3: HR, 2.03; 95% CI, 1.23-3.33; P = .005). Highly effective disease-modifying treatments were associated with lower risks of 6-month CDW and an EDSS of 3 in patients with high baseline sNfL values.

Conclusions and Relevance

This cohort study found that high sNfL values obtained within the first year of disease were associated with long-term disability worsening in MS, suggesting that sNfL level measurement may help identify optimal candidates for highly effective disease-modifying treatments.

Long-term prognosis communication preferences in early-stage relapsing-remitting multiple sclerosis

BACKGROUND

Multiple sclerosis is one of the most common causes of neurological disability in young adults with major consequences for their future lives. Improving communication strategies on prognosis may help patients deal with the disease and adjust their long-term life goals. However, there is limited information on patients' preferences of long-term prognosis (LTP) communication and associated factors.

OBJECTIVE

The aim of this study was to describe patients' preferences and assess the factors associated with LTP communication preferences in early-stage relapsing-remitting multiple sclerosis (RRMS) patients.

METHODS

A multicenter, non-interventional study was conducted. Adult patients with a diagnosis of RRMS, a disease duration from first attack ≤ 3 years, and an Expanded Disability Status Scale (EDSS) score of 0-5.5 were included. The Prognosis in MS questionnaire was used to assess how much patients want to know about their LTP. Different patient-reported measures were administered to gather information on symptom severity, pain, fatigue, mood/anxiety, quality of life, stigma, illness perception, feeling of hopelessness, self-efficacy, information avoidance and coping strategies. Cognition was assessed using the Symbol Digit Modalities Test (SDMT). A multivariate logistic regression analysis was performed to assess the association between LTP information preference and demographic and clinical characteristics, as well as patients' perspectives.

RESULTS

A total of 189 patients were included (mean age: 36.1  ±  9.4 years, 71.4% female, mean disease duration: 1.2  ±  0.8 years). Median EDSS score was 1.0 (IQR = 0.0-2.0). A proportion of 68.5% (n  =  126) of patients had never discussed LTP with their neurologists, whereas 69.2% (n = 126) reported interest in knowing it (73.5% at diagnosis). Bivariate analyses suggested that patients were significantly more likely to have higher LTP information preferences if they were male and had a lower SDMT score. Male gender and a lower SDMT score were predictors of LTP information preferences.

CONCLUSIONS

Patients with early-stage RRMS want to discuss their LTP shortly after diagnosis. Understanding the factors involved may be useful to design individualized communication strategies.