Enhancing the clinical value of serum neurofilament light chain measurement

Association between serum neurofilament light chains and Life's Essential 8: A cross-sectional analysis

BACKGROUND AND AIM

Serum neurofilament light chain (sNfL), a protein released into the bloodstream post-neuronal axonal damage, has been validated as a robust biomarker for a range of neurological and systemic diseases. Concurrently, Life's Essential 8 (LE8) comprises a holistic suite of health behaviors and metabolic markers that are essential for assessing and enhancing cardiovascular health. Nevertheless, the interrelation between LE8 and sNfL is not yet fully elucidated. This investigation seeks to evaluate the association between LE8 and sNfL within the framework of the National Health and Nutrition Examination Survey (NHANES).

METHODS

According to data from the 2013-2014 NHANES, the study enrolled a total of 5262 participants aged between 20 and 75 years. We excluded 3035 individuals lacking sNfL measurements, included 2071 subjects for analysis, and further excluded cases from LE8 due to missing data. Ultimately, 1691 valid datasets were obtained. Hierarchical and multiple regression analyses were conducted, supplemented by smooth curve fitting and saturation effect analysis to investigate the relationship between LE8 and sNfL.

RESULTS

An inverse correlation was observed between LE8 scores and sNfL levels. For each SD change increase in LE8, log-transformed sNfL levels decreased by 0.14 (-0.17, -0.11 in the non-adjusted model), 0.08 (-0.10, -0.05 in the minimally adjusted model), and 0.08 (-0.12, -0.05 in the fully adjusted model). The multi-factor adjusted β coefficients and 95% confidence intervals (CIs) for LE8 categories (<50, 50 ~ 80, and ≥80) were as follows: reference, -0.20 (-0.34, -0.06), and -0.26 (-0.42, -0.10). The inflection point was determined to be 58.12, identified using a two-piece linear regression model.

CONCLUSION

The analysis indicated a non-linear relationship between LE8 scores and sNfL levels. Associations were noted a positive association between LE8 and sNfL. These results suggest that lifestyle modifications and optimization of metabolic markers could potentially correlate with reduced sNfL levels; further investigation is necessary to confirm a causal relationship.

Impact of amyloid and cardiometabolic risk factors on prognostic capacity of plasma neurofilament light chain for neurodegeneration

BACKGROUND

Plasma neurofilament light chain (NfL) is a blood biomarker of neurodegeneration, including Alzheimer's disease. However, its usefulness may be influenced by common conditions in older adults, including amyloid-β (Aβ) deposition and cardiometabolic risk factors like hypertension, diabetes mellitus (DM), impaired kidney function, and obesity. This longitudinal observational study using the Alzheimer's Disease Neuroimaging Initiative cohort investigated how these conditions influence the prognostic capacity of plasma NfL.

METHODS

Non-demented participants (cognitively unimpaired or mild cognitive impairment) underwent repeated assessments including the Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) scores, hippocampal volumes, and white matter hyperintensity (WMH) volumes at 6- or 12-month intervals. Linear mixed-effect models were employed to examine the interaction between plasma NfL and various variables of interest, such as Aβ (evaluated using Florbetapir positron emission tomography), hypertension, DM, impaired kidney function, or obesity.

RESULTS

Over a mean follow-up period of 62.5 months, participants with a mean age of 72.1 years (n = 720, 48.8% female) at baseline were observed. Higher plasma NfL levels at baseline were associated with steeper increases in ADAS-Cog scores and WMH volumes, and steeper decreases in hippocampal volumes over time (all p-values < 0.001). Notably, Aβ at baseline significantly enhanced the association between plasma NfL and longitudinal changes in ADAS-Cog scores (p-value 0.005) and hippocampal volumes (p-value 0.004). Regarding ADAS-Cog score and WMH volume, the impact of Aβ was more prominent in cognitively unimpaired than in mild cognitive impairment. Hypertension significantly heightened the association between plasma NfL and longitudinal changes in ADAS-Cog scores, hippocampal volumes, and WMH volumes (all p-values < 0.001). DM influenced the association between plasma NfL and changes in ADAS-Cog scores (p-value < 0.001) without affecting hippocampal and WMH volumes. Impaired kidney function did not significantly alter the association between plasma NfL and longitudinal changes in any outcome variables. Obesity heightened the association between plasma NfL and changes in hippocampal volumes only (p-value 0.026).

CONCLUSION

This study suggests that the prognostic capacity of plasma NfL may be amplified in individuals with Aβ or hypertension. This finding emphasizes the importance of considering these factors in the NfL-based prognostic model for neurodegeneration in non-demented older adults.

Data-driven risk/benefit estimator for multiple sclerosis therapies

Background

Multiple sclerosis (MS) disease-modifying treatments (DMTs) are tested in patients preselected for favorable risk/benefits ratios but prescribed broadly in clinical practice. We aimed to establish data-driven computations of individualized risk/benefit ratios to optimize MS care.

Methods

We derived determinants of DMTs efficacy on disability progression from re-analysis and integration of 61 randomized, blinded Phase 2b/3 clinical trials that studied 46,611 patients for 91,787 patient-years. From each arm we extracted 80 and computed 30 features to identify and adjust for biases, and to use in multiple regression models. DMTs mortality risks were estimated from age mortality tables modified by published hazard ratios.

Findings

Baseline characteristics of the recruited patients determine disability progression rates and DMTs efficacies with high effect sizes. DMTs efficacies increase with MS lesional activity (LA) measured by relapses or contrast-enhancing lesions and decrease with increasing age, disease duration and disability. Unexpectedly, as placebo arms' relapse rate rapidly declines with trial duration, efficacy of MS DMTs likewise decreases quickly with treatment duration. Conversely, DMTs morbidity/mortality risks increase with age, advanced disability, and comorbidities. We integrated these results into an interactive personalized web based DMTs risk/benefit estimator.

Interpretation

Results predict that prescribing DMTs to patients traditionally excluded from MS clinical trials causes more harm than benefit. Treatment with high efficacy drugs at MS onset followed by de-escalation to DMTs that do not increase infectious risks would optimize risk/benefit. DMTs targeting mechanisms of progression independent of LA are greatly needed as current DMTs inhibit disability caused by LA only.

Global research trends on the links between NfL and neurological disorders: A bibliometric analysis and review

Background

The global incidence of neurological diseases has been on the rise, creating an urgent need for a validated marker. Neurofilament Light Chain (NfL) holds promise as such a marker and has garnered significant attention in the field of neurological diseases over the past decades.

Methods

Corresponding articles from 2013 to 2023 were collected from the Web of Science database, and data were analyzed by CiteSpace and VOSviewer software.

Results

A total of 1350 articles were collected from 296 countries/regions, involving 7246 research organizations. Since 2013, among the top ten institutions and authors with the highest number of published papers, the most are from the US and the UK. The United States leads in the number of published papers, but England holds a more momentous position, because it has higher IF. Henrik Zetterberg is the most influential scholar in the field.

Conclusions

The output of papers mainly relies on researchers from developed countries, and scholars from the United States and England have contributed the largest number of papers. Until now, the importance of NfL in neurological diseases has attracted global attention. In addition, NfL contributes to the potential diagnosis of various neurological disorders and can be used to improve the accuracy of differential diagnosis and prognostic assessment as well as predict the response to treatments. More and more in-depth studies are highly needed in the future.

Neurofilaments as biomarkers in neurological disorders - towards clinical application

Neurofilament proteins have been validated as specific body fluid biomarkers of neuro-axonal injury. The advent of highly sensitive analytical platforms that enable reliable quantification of neurofilaments in blood samples and simplify longitudinal follow-up has paved the way for the development of neurofilaments as a biomarker in clinical practice. Potential applications include assessment of disease activity, monitoring of treatment responses, and determining prognosis in many acute and chronic neurological disorders as well as their use as an outcome measure in trials of novel therapies. Progress has now moved the measurement of neurofilaments to the doorstep of routine clinical practice for the evaluation of individuals. In this Review, we first outline current knowledge on the structure and function of neurofilaments. We then discuss analytical and statistical approaches and challenges in determining neurofilament levels in different clinical contexts and assess the implications of neurofilament light chain (NfL) levels in normal ageing and the confounding factors that need to be considered when interpreting NfL measures. In addition, we summarize the current value and potential clinical applications of neurofilaments as a biomarker of neuro-axonal damage in a range of neurological disorders, including multiple sclerosis, Alzheimer disease, frontotemporal dementia, amyotrophic lateral sclerosis, stroke and cerebrovascular disease, traumatic brain injury, and Parkinson disease. We also consider the steps needed to complete the translation of neurofilaments from the laboratory to the management of neurological diseases in clinical practice.

Predictive value of individual serum neurofilament light chain levels in short-term disease activity in relapsing multiple sclerosis

Background

The assessment of serum neurofilament light chain (sNFL) has emerged as a diagnostic and prognostic tool in monitoring multiple sclerosis (MS). However, the application of periodic measurement in daily practice remains unclear.

Objective

To evaluate the predictive value of individual sNFL levels in determining disease activity in patients with relapsing MS (RMS).

Methods

In this two-year prospective study, 129 RMS patients underwent quarterly sNFL assessments and annual MRI scans. The study analyzed the correlation between individual NFL levels and past, current, and future disease activity. Group-level Z-scores were employed as a comparative measure.

Results

Among the 37 participants, a total of 61 episodes of disease activity were observed. sNFL levels proved valuable in distinct ways; they were confirmatory of previous and current clinical and/or radiological activity and demonstrated a high negative predictive value for future 90 days activity. Interestingly, Z-scores marginally outperformed sNFL levels in terms of predictive accuracy, indicating the potential for alternative approaches in disease activity assessment. In our cohort, sNFL cut-offs of 10.8 pg./mL (sensitivity 27%, specificity 90%) and 14.3 pg./mL (sensitivity 15%, specificity 95%) correctly identified 7 and 4 out of 26 cases of radiological activity within 90 days, respectively, with 14 and 15% false negatives. When using lower cut-off values, individuals with sNFL levels below 5 pg/mL (with a sensitivity of 92%, specificity of 25%, and negative predictive value of 94%) were less likely to experience radiological activity within the next 3 months.

Conclusion

Individual sNFL levels may potentially confirm prior or current disease activity and predict short-term future radiological activity in RMS. These findings underscore its periodic measurement as a valuable tool in RMS management and decision-making, enhancing the precision of clinical evaluation in routine practice.

Cerebrospinal fluid neurofilament light chains predicts early disease-activity in Multiple Sclerosis

BACKGROUND

Among biomarkers of axonal damage, neurofilament light chains (NFL) seem to play a major role, representing a promising and interesting tool in Multiple Sclerosis (MS). Our aim was to explore the predictive role of cerebrospinal fluid (CSF) NFL in patients with a recent diagnosis of MS, naïve to any MS therapy.

METHODS

We retrospectively collected data of patients diagnosed with MS, referred to the Neurology Clinic of the University-Hospital G. Rodolico of Catania between January 1st 2005 and December 31st 2015. All patients underwent CSF collection at the time of MS diagnosis and were followed-up for at least three years afterwards. NFL levels were measured in CSF samples with Simoa NFLight advantage kit at the CRESM (University Hospital San Luigi Gonzaga, Orbassano, Torino). NFL levels were expressed as LogNFL. Symbol Digit Modalities test (SDMT) was performed at baseline, at 1-year and at 3-year follow-up. Multivariate logistic regression analysis was performed to investigate LogNFL as a potential risk factor of different clinical outcomes.

RESULTS

244 MS patients (230 relapsing-remitting, RRMS; 94.3 %), with a mean age at diagnosis of 37.0 ± 11.1 years, were recruited. LogNFL did not correlate neither with EDSS score at diagnosis and at subsequent follow-up up to 12 years, nor with SDMT performed at diagnosis, at 1 year and at 3 years. LogNFL were an independent factor for the occurrence of at least one relapse during the first two years after MS diagnosis (OR = 2.75; 95 % CI 1.19-6.31; p = 0.02) and for the occurrence of gadolinium-enhanced (Gd+) lesions during the first 2 years from diagnosis at brain and spine MRI scans (OR = 3.45, 95 % CI 1.81-6.57; p < 0.001).

CONCLUSION

The detection of CSF NFL at the time of MS diagnosis can be a useful support to predict the two-year risk of clinical and radiological relapses, thus affecting therapeutic choices in the very early phases of the disease.

Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis

Sensitive and reliable protein biomarkers are needed to predict disease trajectory and personalize treatment strategies for multiple sclerosis (MS). Here, we use the highly sensitive proximity-extension assay combined with next-generation sequencing (Olink Explore) to quantify 1463 proteins in cerebrospinal fluid (CSF) and plasma from 143 people with early-stage MS and 43 healthy controls. With longitudinally followed discovery and replication cohorts, we identify CSF proteins that consistently predicted both short- and long-term disease progression. Lower levels of neurofilament light chain (NfL) in CSF is superior in predicting the absence of disease activity two years after sampling (replication AUC = 0.77) compared to all other tested proteins. Importantly, we also identify a combination of 11 CSF proteins (CXCL13, LTA, FCN2, ICAM3, LY9, SLAMF7, TYMP, CHI3L1, FYB1, TNFRSF1B and NfL) that predict the severity of disability worsening according to the normalized age-related MS severity score (replication AUC = 0.90). The identification of these proteins may help elucidate pathogenetic processes and might aid decisions on treatment strategies for persons with MS.

Association between Cerebrospinal Fluid and Serum Biomarker Levels and Diagnosis, Injury Severity, and Short-Term Outcomes in Patients with Acute Traumatic Spinal Cord Injury

Acute traumatic spinal cord injury (SCI) is recognized as a global problem that can lead to a range of acute and secondary complications impacting morbidity and mortality. There is still a lack of reliable diagnostic and prognostic biomarkers in patients with SCI that could help guide clinical care and identify novel therapeutic targets for future drug discovery. The aim of this prospective controlled study was to determine the cerebral spinal fluid (CSF) and serum profiles of 10 biomarkers as indicators of SCI diagnosis, severity, and prognosis to aid in assessing appropriate treatment modalities. CSF and serum samples of 15 SCI and ten healthy participants were included in the study. The neurological assessments were scored on admission and at discharge from the hospital using the American Spinal Injury Association Impairment Score (AIS) grades. The CSF and serum concentrations of SBDP150, S100B, GFAP, NF-L, UCHL-1, Tau, and IL-6 were significantly higher in SCI patients when compared with the control group. The CSF GBDP 38/44K, UCHL-L1, S100B, GFAP, and Tau levels were significantly higher in the AIS A patients. This study demonstrated a strong correlation between biomarker levels in the diagnosis and injury severity of SCI but no association with short-term outcomes. Future prospective controlled studies need to be done to support the results of this study.

Demographic and disease-related factors impact on cerebrospinal fluid neurofilament light chain levels in multiple sclerosis

BACKGROUND

Neurofilament light (NfL) levels reflect inflammatory disease activity in multiple sclerosis (MS), but it is less clear if NfL also can serve as a biomarker for MS progression in treated patients without relapses and focal lesion accrual. In addition, it has not been well established if clinically effective treatment re-establishes an age and sex pattern for cerebrospinal fluid NfL (cNfL) as seen in controls, and to what degree levels are affected by disability level and magnetic resonance imaging (MRI) atrophy metrics.

METHODS

We included subjects for whom cNfL levels had been determined as per clinical routine or in clinical research, classified as healthy controls (HCs, n = 89), MS-free disease controls (DCs, n = 251), untreated MS patients (uMS; n = 296), relapse-free treated MS patients (tMS; n = 78), and ProTEct-MS clinical trial participants (pMS; n = 41).

RESULTS

Using linear regression, we found a positive association between cNfL and age, as well as lower concentrations among women, in all groups, except for uMS patients. In contrast, disability level in the entire MS cohort, or T1 and T2 lesion volumes, brain parenchymal fraction, thalamic fraction, and cortical thickness in the pMS trial cohort, did not correlate with cNfL concentrations. Furthermore, the cNfL levels in tMS and pMS groups did not differ.

CONCLUSIONS

In participants with MS lacking signs of inflammatory disease activity, disease modulatory therapy reinstates an age and sex cNfL pattern similar to that of control subjects. No significant association was found between cNfL levels and clinical worsening, disability level, or MRI metrics.

Molecular models of multiple sclerosis severity identify heterogeneity of pathogenic mechanisms

While autopsy studies identify many abnormalities in the central nervous system (CNS) of subjects dying with neurological diseases, without their quantification in living subjects across the lifespan, pathogenic processes cannot be differentiated from epiphenomena. Using machine learning (ML), we searched for likely pathogenic mechanisms of multiple sclerosis (MS). We aggregated cerebrospinal fluid (CSF) biomarkers from 1305 proteins, measured blindly in the training dataset of untreated MS patients (N = 129), into models that predict past and future speed of disability accumulation across all MS phenotypes. Healthy volunteers (N = 24) data differentiated natural aging and sex effects from MS-related mechanisms. Resulting models, validated (Rho 0.40-0.51, p < 0.0001) in an independent longitudinal cohort (N = 98), uncovered intra-individual molecular heterogeneity. While candidate pathogenic processes must be validated in successful clinical trials, measuring them in living people will enable screening drugs for desired pharmacodynamic effects. This will facilitate drug development making, it hopefully more efficient and successful.