Cerebrospinal fluid proteomics: A new window for understanding human demyelinating disorders?

Diagnostic Potential of Two Novel Biomarkers for Neuromyelitis Optica Spectrum Disorder and Multiple Sclerosis

BACKGROUND

Currently, no tests can definitively diagnose and distinguish neuromyelitis optica spectrum disorder (NMOSD) from multiple sclerosis (MS).

METHODS

Initially, cerebrospinal fluid (CSF) proteomics were employed to uncover the novel biomarkers that differentiate NMOSD from MS into cohorts of 10 MS and 10 NMOSD patients. Subsequently, screening biomarkers were validated using an enzyme-linked immunosorbent assay method and CSF and serum samples from 20 MS patients, 20 NMOSD patients, 20 non-inflammatory neurological controls, and 20 healthy controls.

RESULTS

In study cohort, insulin-like growth factor-binding protein 7 (IGFBP7) and lysosome-associated membrane glycoprotein 2 (LAMP2) were screened. In validation cohort, serum and CSF IGFBP7 not only exhibited higher levels in MS and NMOSD patients than controls, but also had greatest area under the curve (AUC, above or equal to 0.8) in MS and NMOSD diagnoses. Serum IGFBP7 (0.945) and CSF IGFBP7 (0.890) also had the greatest AUCs for predicting MS progression, while serum LAMP2 had a moderate curve (0.720).

CONCLUSIONS

IGFBP7 was superior in diagnosing MS and NMOSD, and IGFBP7 and serum LAMP2 performed exceptionally well in predicting the MS progression. These results offered reasons for further investigations into the functions of IGFBP7 and LAMP2 in MS and NMOSD.

Serum proteomics in multiple sclerosis disease progression

Multiple sclerosis (MS) is associated with chronic degeneration of the central nervous system and may cause permanent neurological problems and considerable disability. While its causes remain unclear, its extensive phenotypic variability makes its prognosis and treatment difficult. The identification of serum proteomic biomarkers of MS progression could further our understanding of the molecular mechanisms related to MS disease processes. In the current study, we used isobaric tagging for relative and absolute protein quantification (iTRAQ) methodology and advanced multivariate statistical analysis to quantify and identify potential serum biomarker proteins of MS progression. We identified a panel of 11 proteins and combined them into a classifier that best classified samples into the two disease groups. The estimated area under the receiver operating curve of this classifier was 0.88 (p-value=0.017), with 86% sensitivity and specificity. The identified proteins encompassed processes related to inflammation, opsonization, and complement activation. Results from this study are in particular valuable to design a targeted Multiple Reaction Monitoring mass spectrometry based (MRM-MS) assay to conduct an external validation in an independent and larger cohort of patients. Validated biomarkers may result in the development of a minimally-invasive tool to monitor MS progression and complement current clinical practices.

BIOLOGICAL SIGNIFICANCE

A hallmark of multiple sclerosis is the unpredictable disease course (progression). There are currently no clinically useful biomarkers of MS disease progression; most work has focused on the analysis of CSF, which requires an invasive procedure. Here, we explore the potential of proteomics to identify panels of serum biomarkers of disease progression in MS. By comparing the protein signatures of two challenging to obtain, but well-defined, MS phenotypic groups at the extremes of progression (benign and aggressive cases of MS), we identified proteins that encompass processes related to inflammation, opsonization, and complement activation. Findings require validation, but are an important step on the pathway to clinically useful biomarker discovery. This article is part of a Special Issue entitled: Protein dynamics in health and disease. Guest Editors: Pierre Thibault and Anne-Claude Gingras.

The antibody genetics of multiple sclerosis: comparing next-generation sequencing to sanger sequencing

We previously identified a distinct mutation pattern in the antibody genes of B cells isolated from cerebrospinal fluid (CSF) that can identify patients who have relapsing-remitting multiple sclerosis (RRMS) and patients with clinically isolated syndromes who will convert to RRMS. This antibody gene signature (AGS) was developed using Sanger sequencing of single B cells. While potentially helpful to patients, Sanger sequencing is not an assay that can be practically deployed in clinical settings. In order to provide AGS evaluations to patients as part of their diagnostic workup, we developed protocols to generate AGS scores using next-generation DNA sequencing (NGS) on CSF-derived cell pellets without the need to isolate single cells. This approach has the potential to increase the coverage of the B-cell population being analyzed, reduce the time needed to generate AGS scores, and may improve the overall performance of the AGS approach as a diagnostic test in the future. However, no investigations have focused on whether NGS-based repertoires will properly reflect antibody gene frequencies and somatic hypermutation patterns defined by Sanger sequencing. To address this issue, we isolated paired CSF samples from eight patients who either had MS or were at risk to develop MS. Here, we present data that antibody gene frequencies and somatic hypermutation patterns are similar in Sanger and NGS-based antibody repertoires from these paired CSF samples. In addition, AGS scores derived from the NGS database correctly identified the patients who initially had or subsequently converted to RRMS, with precision similar to that of the Sanger sequencing approach. Further investigation of the utility of the AGS in predicting conversion to MS using NGS-derived antibody repertoires in a larger cohort of patients is warranted.

Pediatric multiple sclerosis: current concepts and consensus definitions

Multiple sclerosis (MS), a chronic inflammatory autoimmune disease of the central nervous system (CNS) commonly diagnosed in adults, is being recognized increasingly in children. An estimated 1.7%-5.6% of all patients with MS have clinical symptoms before reaching the age of 18 years. In comparison with adults, the diagnosis of MS in children can be more difficult, being dismissed or misdiagnosed as other clinical disorders. Although adults and children share basic aspects of the disorder, children have distinctive clinical features, neuroimaging, laboratory, and courses of the disease. The 2010 McDonald criteria have simplified the requirements for establishing the diagnosis of MS and have been proposed to be applicable for the diagnosis of pediatric MS, mainly in children 12 years and older. This paper describes the distinctive features of common pediatric demyelinating disorders, including MS, and summarizes the most recent advances based on the available literature.