Serum Peptide Profiles of Duchenne Muscular Dystrophy (DMD) Patients Evaluated by Data Handling Strategies for High Resolution Content

Abstract

The accuracy of Mass Spectrometry (MS)-based analysis of peptides in complex biological mixtures improves upon using high resolution instrumentation. However, high resolution content poses challenges to data processing and statistical analysis. Here, three different data handling strategies were evaluated with respect to classification performance using a well-defined cohort of serum samples from Duchenne Muscular Dystrophy (DMD) patients and controls. For this purpose, serum samples were purified using a solid-phase extraction (SPE) protocol based on Reversed-Phase (RP) C18 magnetic beads. Isotopically-resolved peptide profiles were acquired on a Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) mass spectrometer and examined by either using the full mass spectrum or after selecting peaks between 1000<m/z<4000 followed by data filtering or data integration. To identify discriminative peptides, linear Logistic Regression Analysis (LRA) with doublecross validation was applied for each method. The data integration strategy resulted in the lowest classification error rate while use of the filtered or full profile data gave higher error rates. From this it was concluded that peak selection methods may increase the discriminative power, however with the potential downside of loss of potentially interesting peptides. Seven peptides were found by all three methods when considering the top 15 discriminating peptides. Correlation analysis of discriminative peptides showed strong associations between peptides of different m/z-values, suggesting that the list of discriminative peptides reflected a smaller group of proteins. Validation studies using larger patient cohorts are required for further statistical evaluation of these results.

Circulating Biomarkers for Duchenne Muscular Dystrophy

“…Notably, GPX3 and LIFr normalized after treatment with a histone deacetylase inhibitor, suggesting these biomarkers might be used to monitor therapy. Fibrinogen was also found in two other studies [ 97, 98 ] and it has been linked to the formation of fibrotic tissue in mice [ 99 ]. Nadarajah et al.…”

Mass Spectrometry-Based Identification of Muscle-Associated and Muscle-Derived Proteomic Biomarkers of Dystrophinopathies

“…This has included established animal models of muscular dystrophy [113][114][115][116][117] and patient specimens. Global changes in muscle-associated proteins were determined using serum samples from the mdx mouse [118,119] and Duchenne patients [120][121][122], the secretome of mdx myotubes [123], Duchenne muscle biopsies [124], the cytosolic mdx muscle fraction [125,126], microsomes from mdx leg muscle [127], crude mdx hind limb muscle extracts [128], individual mdx leg muscles including gastrocnemius, tibialis anterior, extensor digitorum longus, soleus, flexor digitorum brevis and interosseus muscles [129][130][131][132], mildly affected mdx extraocular muscles [133,134], the severely dystrophic mdx diaphragm [134][135][136][137][138][139], the mdx heart [140][141][142] and skeletal muscle extracts from the grmd dog [143].…”

“…Since the identification and establishment of biofluid-based biomarkers is essential for improved diagnosis, enhanced approaches of risk stratification and the optimum management of pathological devel-opments, recently international efforts have intensified and initiated the systematic screening of suitable body fluids for muscle-derived proteins. However, in contrast to the large number of proteomic studies described in above sections that have analysed muscle tissue extracts or subcellular fractions [63], relatively few mass spectrometric investigations that focus on leaked or secreted proteins from dystrophic muscle tissues have been published [118][119][120][121][122][123]. Serum and plasma, examples of distal biofluids, are composed of components originating from cells throughout the entire body, including various hormones, enzymes, glycoproteins, and growth factors.…”

Detection of pancreatic cancer using serum protein profiling

“…In the calibration set, 12 (24%) patients had stage I, 24 (48%) had stage II, 5 (10%) had stage III and 9 (18%) had stage IV. In the validation set, 4 (10.3%) patients were classified as stage I, 24 (61.5%) as stage II, 2 (5.1%) as stage III and 9 (23.1%) as stage IV. In 29 patients (32.6%) the tumour appeared irresectable during surgery.…”

“…19,20 In the last decade, multiple studies have been carried out using a magnetic bead-based method for offline serum peptide/protein capture and MALDI-TOF-MS readout. 14,[21][22][23][24][25] For PC, several proteomic studies have been performed since the introduction of protein profiling in 2002 by Petricoin et al, 26 all with different fractionation platforms and type of MS. [27][28][29][30][31][32][33] For example, Koopman et al 34 used a surface enhanced laser desorption/ionization (SELDI)-TOF approach combined with WCX and metal affinity protein chips as the solid-phase extraction (SPE) method to discriminate between patient groups with a sensitivity of 78% and a specificity of 97%. No study has been published using a combination of WCX MB and MALDI-TOF.…”