Plasma Peptide Biomarker Discovery for Amyotrophic Lateral Sclerosis by MALDI –TOF Mass Spectrometry Profiling

<div><p>The diagnostic of Amyotrophic lateral sclerosis (ALS) remains based on clinical and neurophysiological observations. The actual delay between the onset of the symptoms and diagnosis is about 1 year, preventing early inclusion of patients into clinical trials and early care of the disease. Therefore, finding biomarkers with high sensitivity and specificity remains urgent. In our study, we looked for peptide biomarkers in plasma samples using reverse phase magnetic beads (C18 and C8) and MALDI-TOF mass spectrometry analysis. From a set of ALS patients (n=30) and healthy age-matched controls (n=30), C18- or C8-SVM-based models for ALS diagnostic were constructed on the base of the minimum of the most discriminant peaks. These two SVM-based models end up in excellent separations between the 2 groups of patients (recognition capability overall classes > 97%) and classify blinded samples (10 ALS and 10 healthy age-matched controls) with very high sensitivities and specificities (>90%). Some of these discriminant peaks have been identified by Mass Spectrometry (MS) analyses and correspond to (or are fragments of) major plasma proteins, partly linked to the blood coagulation.</p> </div

PLS results.

<p>Analysis of C18 data from ALS patients A/ spinal-onset (red) and bulbar-onset (turquoise); B/ female (red) and male (turquoise) - Each dot correspond to one patient (average of 9 spectra per patient).</p

Peak variance and ROC curves.

<p>A/ Representation of the expression level for some of the most discriminating C8- or C18-peaks (x-axis, peak intensity), B/ corresponding receiver operating characteristic curve (ROC) with ALS group define as positive class.</p

MALDI-TOF profiles representation.

<p>2D C8 (A) and C18 (B) MALDI-TOF profiles representation (Log₁₀ Intensity with results expressed in arbitrary units) of ALS (bottom) and healthy (top) patients; Mass range (x-axis): 1-10kDa, underlined spectra correspond to excluded data (miss-calibrated spectrum).</p

Principal component analysis.

<p>The first 3 principal components which account for most of the variance in the original data set are shown A) from MS-data of C8-beads sample preparation and B) from MS-data of C18-beads sample preparation; ALS patients (red) and healthy controls (green) ; 1 dot per patient (average of 9 spectra per patient); Eigenvalues screen plots are at the right of each PCA.</p

Workflow of the SVM model generation.

<p>Data were randomly separated into two data sets, a training set (30 ALS patients and 30 healthy controls) used for the biomarker discovery step and a validation set used for classification of blinded samples (10 ALS patients and 10 healthy controls). This process of data randomization, discovery and validation was repeated ten times.</p

Population demographics and clinical features in SMA patients.

<p>Population demographics and clinical features in SMA patients.</p

3D atrophy profile along the cervical spinal cord in SMA patients.

<p>The color-coding indicates regions with significant atrophy (color scale = p-values of the between groups comparison). A, anterior; I, inferior; L, left, P, posterior, R, right, S, superior.</p

Spinal cord segmentation, cord straightening and radial distance illustration.

<p>(A) Preprocessed T2-weighted mid-sagittal section in an SMA patient. The yellow dashed lines delimit the cervical spinal cord region. (B) Resulted segmentation mask (orange). (C) Cervical spinal cord straightening. (D) Mask straightening (orange). (E) Radial distance measurements. A, anterior; I, inferior; L, left, P, posterior, R, right, S, superior.</p