Limited value of serum neurofilament light chain in diagnosing amyotrophic lateral sclerosis

Diagnostic value of neurofilaments in differentiating motor neuron disease from multifocal motor neuropathy

OBJECTIVE

To evaluate the performance of serum neurofilament light chain (NfL) and cerebrospinal fluid (CSF) phosphorylated neurofilament heavy chain (pNfH) as diagnostic biomarkers for the differentiation between motor neuron disease (MND) and multifocal motor neuropathy (MMN).

METHODS

This retrospective, monocentric study included 16 patients with MMN and 34 incident patients with MND. A subgroup of lower motor neuron (MN) dominant MND patients (n = 24) was analyzed separately. Serum NfL was measured using Ella automated immunoassay, and CSF pNfH was measured using enzyme-linked immunosorbent assay. Area under the curve (AUC), optimal cutoff values (Youden's index), and correlations with demographic characteristics were calculated.

RESULTS

Neurofilament concentrations were significantly higher in MND compared to MMN (p < 0.001), and serum NfL and CSF pNfH correlated strongly with each other (Spearman's rho 0.68, p < 0.001). Serum NfL (AUC 0.946, sensitivity and specificity 94%) and CSF pNfH (AUC 0.937, sensitivity 90.0%, specificity 100%) performed excellent in differentiating MND from MMN. Optimal cutoff values were ≥ 44.15 pg/mL (serum NfL) and ≥ 715.5 pg/mL (CSF pNfH), respectively. Similar results were found when restricting the MND cohort to lower MN dominant patients. Only one MMN patient had serum NfL above the cutoff. Two MND patients presented with neurofilament concentrations below the cutoffs, both featuring a slowly progressive disease.

CONCLUSION

Neurofilaments are valuable supportive biomarkers for the differentiation between MND and MMN. Serum NfL and CSF pNfH perform similarly well and elevated neurofilaments in case of diagnostic uncertainty underpin MND diagnosis.

Plasma proteomic profiles of UK Biobank participants with multiple sclerosis

OBJECTIVE

We aimed to describe plasma protein biomarkers of multiple sclerosis risk and to explore protein biomarkers of disease severity using radiological outcome measures.

METHODS

Multiple sclerosis cases and controls were identified in UK Biobank, a longitudinal cohort study of ~500,000 British adults. Plasma proteins were assayed in ~50,000 UK Biobank participants using the Olink proximity extension assay. We performed case-control association testing to examine the association between 2911 proteins and multiple sclerosis, using linear models adjusted for confounding covariates. Associations with radiological lesion burden and brain volume were determined in a subset of the cohort with available magnetic resonance imaging, using normalized T2-hyperintensity volume or whole brain volume as the outcome measure.

RESULTS

In total, 407 prevalent multiple sclerosis cases and 39,979 healthy controls were included. We discovered 72 proteins associated with multiple sclerosis at a Bonferroni-adjusted p value of 0.05, including established markers such as neurofilament light chain and glial fibrillary acidic protein. We observed a decrease in plasma Granzyme A, a marker of T cell and NK cell degranulation, which was specific to multiple sclerosis. Higher levels of plasma proteins involved in coagulation were associated with lower T2 lesion burden and preserved brain volume.

INTERPRETATION

We report the largest plasma proteomic screen of multiple sclerosis, replicating important known associations and suggesting novel markers, such as the reduction in granzyme A. While these findings require external validation, they demonstrate the power of biobank-scale datasets for discovering new biomarkers for multiple sclerosis.

Data-independent acquisition proteomics of cerebrospinal fluid implicates endoplasmic reticulum and inflammatory mechanisms in amyotrophic lateral sclerosis

While unbiased proteomics of human cerebrospinal fluid (CSF) has been used successfully to identify biomarkers of amyotrophic lateral sclerosis (ALS), high-abundance proteins mask the presence of lower abundance proteins that may have diagnostic and prognostic value. However, developments in mass spectrometry (MS) proteomic data acquisition methods offer improved protein depth. In this study, MS with library-free data-independent acquisition (DIA) was used to compare the CSF proteome of people with ALS (n = 40), healthy (n = 15) and disease (n = 8) controls. Quantified protein groups were subsequently correlated with clinical variables. Univariate analysis identified 7 proteins, all significantly upregulated in ALS versus healthy controls, and 9 with altered abundance in ALS versus disease controls (FDR < 0.1). Elevated chitotriosidase-1 (CHIT1) was common to both comparisons and was proportional to ALS disability progression rate (Pearson r = 0.41, FDR-adjusted p = 0.035) but not overall survival. Ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1; upregulated in ALS versus healthy controls) was proportional to disability progression rate (Pearson r = 0.53, FDR-adjusted p = 0.003) and survival (Kaplan Meier log-rank p = 0.013) but not independently in multivariate proportional hazards models. Weighted correlation network analysis was used to identify functionally relevant modules of proteins. One module, enriched for inflammatory functions, was associated with age at symptom onset (Pearson r = 0.58, FDR-adjusted p = 0.005) and survival (Hazard Ratio = 1.78, FDR = 0.065), and a second module, enriched for endoplasmic reticulum proteins, was negatively correlated with disability progression rate (r = -0.42, FDR-adjusted p = 0.109). DIA acquisition methodology therefore strengthened the biomarker candidacy of CHIT1 and UCHL1 in ALS, while additionally highlighted inflammatory and endoplasmic reticulum proteins as novel sources of prognostic biomarkers.