A critical assessment of feature selection methods for biomarker discovery in clinical proteomics.

In this paper, we compare the performance of six different feature selection methods for LC-MS-based proteomics and metabolomics biomarker discovery-t test, the Mann-Whitney-Wilcoxon test (mww test), nearest shrunken centroid (NSC), linear support vector machine-recursive features elimination (SVM-RFE), principal component discriminant analysis (PCDA), and partial least squares discriminant analysis (PLSDA)-using human urine and porcine cerebrospinal fluid samples that were spiked with a range of peptides at different concentration levels. The ideal feature selection method should select the complete list of discriminating features that are related to the spiked peptides without selecting unrelated features. Whereas many studies have to rely on classification error to judge the reliability of the selected biomarker candidates, we assessed the accuracy of selection directly from the list of spiked peptides.

Mutations in the phospholipid remodeling gene SERAC1 impair mitochondrial function and intracellular cholesterol trafficking and cause dystonia and deafness.

Using exome sequencing, we identify SERAC1 mutations as the cause of MEGDEL syndrome, a recessive disorder of dystonia and deafness with Leigh-like syndrome, impaired oxidative phosphorylation and 3-methylglutaconic aciduria. We localized SERAC1 at the interface between the mitochondria and the endoplasmic reticulum in the mitochondria-associated membrane fraction that is essential for phospholipid exchange. A phospholipid analysis in patient fibroblasts showed elevated concentrations of phosphatidylglycerol-34:1 (where the species nomenclature denotes the number of carbon atoms in the two acyl chains:number of double bonds in the two acyl groups) and decreased concentrations of phosphatidylglycerol-36:1 species, resulting in an altered cardiolipin subspecies composition.

Profiling and identification of cerebrospinal fluid proteins in a rat EAE model of multiple sclerosis.

The experimental autoimmune encephalomyelitis (EAE) model resembles certain aspects of multiple sclerosis (MScl), with common features such as motor dysfunction, axonal degradation, and infiltration of T-cells. We studied the cerebrospinal fluid (CSF) proteome in the EAE rat model to identify proteomic changes relevant for MScl disease pathology. EAE was induced in male Lewis rats by injection of myelin basic protein (MBP) together with complete Freund's adjuvant (CFA).

The impact of delayed storage on the measured proteome and metabolome of human cerebrospinal fluid.

Background: Because cerebrospinal fluid (CSF) is in close contact with diseased areas in neurological disorders, it is an important source of material in the search for molecular biomarkers. However, sample handling for CSF collected from patients in a clinical setting might not always be adequate for use in proteomics and metabolomics studies.

Methods: We left CSF for 0, 30, and 120 min at room temperature immediately after sample collection and centrifugation/removal of cells.

Data processing pipelines for comprehensive profiling of proteomics samples by label-free LC-MS for biomarker discovery.

Label-free quantitative LC-MS profiling of complex body fluids has become an important analytical tool for biomarker and biological knowledge discovery in the past decade. Accurate processing, statistical analysis and validation of acquired data diversified by the different types of mass spectrometers, mass spectrometer parameter settings and applied sample preparation steps are essential to answer complex life science research questions and understand the molecular mechanism of disease onset and developments. This review provides insight into the main modules of label-free data processing pipelines with statistical analysis and validation and discusses recent developments.

Time alignment algorithms based on selected mass traces for complex LC-MS data.

Time alignment of complex LC-MS data remains a challenge in proteomics and metabolomics studies. This work describes modifications of the Dynamic Time Warping (DTW) and the Parametric Time Warping (PTW) algorithms that improve the alignment quality for complex, highly variable LC-MS data sets. Regular DTW or PTW use one-dimensional profiles such as the Total Ion Chromatogram (TIC) or Base Peak Chromatogram (BPC) resulting in correct alignment if the signals have a relatively simple structure.

The effect of preanalytical factors on stability of the proteome and selected metabolites in cerebrospinal fluid (CSF).

To standardize the use of cerebrospinal fluid (CSF) for biomarker research, a set of stability studies have been performed on porcine samples to investigate the influence of common sample handling procedures on proteins, peptides, metabolites and free amino acids. This study focuses at the effect on proteins and peptides, analyzed by applying label-free quantitation using microfluidics nanoscale liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (chipLC-MS) as well as matrix-assisted laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FT-ICR-MS) and Orbitrap LC-MS/MS to trypsin-digested CSF samples. The factors assessed were a 30 or 120 min time delay at room temperature before storage at -80 degrees C after the collection of CSF in order to mimic potential delays in the clinic (delayed storage), storage at 4 degrees C after trypsin digestion to mimic the time that samples remain in the cooled autosampler of the analyzer, and repeated freeze-thaw cycles to mimic storage and handling procedures in the laboratory.

Optimized time alignment algorithm for LC-MS data: correlation optimized warping using component detection algorithm-selected mass chromatograms.

Correlation optimized warping (COW) based on the total ion current (TIC) is a widely used time alignment algorithm (COW-TIC). This approach works successfully on chromatograms containing few compounds and having a well-defined TIC. In this paper, we have combined COW with a component detection algorithm (CODA) to align LC-MS chromatograms containing thousands of biological compounds with overlapping chromatographic peaks, a situation where COW-TIC often fails.