Longitudinal evaluation of myofiber microstructural changes in a preclinical ALS model using the transverse relaxivity at tracer equilibrium (TRATE): A preliminary study.

T2⁎ relaxivity contrast imaging may serve as a potential imaging biomarker for amyotrophic lateral sclerosis (ALS) by noninvasively quantifying the tissue microstructure. In this preliminary longitudinal study, we investigated the Transverse Relaxivity at Tracer Equilibrium (TRATE) in three muscle groups between SOD1-G93A (ALS model) rat and a control population at two different timepoints. The control group was time matched to the ALS group such that the second timepoint was the onset of disease. We observed a statistically significant decrease in TRATE over time in the gastrocnemius, tibialis, and digital flexor muscles in the SOD1-G93A model (p-value = 0.003, 0.008, 0.005; respectively), whereas TRATE did not change over time in the control group (p-value = 0.4777, 0.6837, 0.9682; respectively). Immunofluorescent staining revealed a decrease in minimum fiber area and cell density in the SOD1-G93A model when compared to the control group (p-value = 6.043E-10 and 2.265E-10, respectively). These microstructural changes observed from histology align with the theorized biophysical properties of TRATE. We demonstrate that TRATE can longitudinally differentiate disease associated atrophy from healthy muscle and has potential to serve as a biomarker for disease progression and ultimately therapy response in patients with ALS.

Tocilizumab is safe and tolerable and reduces C-reactive protein concentrations in the plasma and cerebrospinal fluid of ALS patients.

INTRODUCTION/AIMS: We tested safety, tolerability, and target engagement of tocilizumab in amyotrophic lateral sclerosis (ALS) patients. METHODS: Twenty-two participants, whose peripheral blood mononuclear cell (PBMC) gene expression profile reflected high messenger ribonucleic acid (mRNA) expression of inflammatory markers, were randomized 2:1 to three tocilizumab or placebo treatments (weeks 0, 4, and 8; 8 mg/kg intravenous). Participants were followed every 4 wk in a double-blind fashion for 16 wk and assessed for safety, tolerability, plasma inflammatory markers, and clinical measures. Cerebrospinal fluid (CSF) was collected at baseline and after the third treatment. Participants were genotyped for Asp358 Ala polymorphism of the interleukin 6 receptor (IL-6R) gene. RESULTS: Baseline characteristics, safety, and tolerability were similar between treatment groups. One serious adverse event was reported in the placebo group; no deaths occurred. Mean plasma C-reactive protein (CRP) level decreased by 88% in the tocilizumab group and increased by 4% in the placebo group (-3.0-fold relative change, P < .001). CSF CRP reduction (-1.8-fold relative change, P = .01) was associated with IL-6R C allele count. No differences in PBMC gene expression or clinical measures were observed between groups. DISCUSSION: Tocilizumab treatment was safe and well tolerated. PBMC gene expression profile was inadequate as a predictive or pharmacodynamic biomarker. Treatment reduced CRP levels in plasma and CSF, with CSF effects potentially dependent on IL-6R Asp358 Ala genotype. IL-6 trans-signaling may mediate a distinct central nervous system response in individuals inheriting the IL-6R C allele. These results warrant further study in ALS patients where IL-6R genotype and CRP levels may be useful enrichment biomarkers.

Optical barcoding of PLGA for multispectral analysis of nanoparticle fate in vivo.

Understanding of the mechanisms by which systemically administered nanoparticles achieve delivery across biological barriers remains incomplete, due in part to the challenge of tracking nanoparticle fate in the body. Here, we develop a new approach for "barcoding" nanoparticles composed of poly(lactic-co-glycolic acid) (PLGA) with bright, spectrally defined quantum dots (QDs) to enable direct, fluorescent detection of nanoparticle fate with subcellular resolution. We show that QD labeling does not affect major biophysical properties of nanoparticles or their interaction with cells and tissues. Live cell imaging enabled simultaneous visualization of the interaction of control and targeted nanoparticles with bEnd.3 cells in a flow chamber, providing direct evidence that surface modification of nanoparticles with the cell-penetrating peptide TAT increases their biophysical association with cell surfaces over very short time periods under convective current. We next developed this technique for quantitative biodistribution analysis in vivo. These studies demonstrate that nanoparticle surface modification with the cell penetrating peptide TAT facilitates brain-specific delivery that is restricted to brain vasculature. Although nanoparticle entry into the healthy brain parenchyma is minimal, with no evidence for movement of nanoparticles across the blood-brain barrier (BBB), we observed that nanoparticles are able to enter to the central nervous system (CNS) through regions of altered BBB permeability - for example, into circumventricular organs in the brain or leaky vasculature of late-stage intracranial tumors. In sum, these data demonstrate a new, multispectral approach for barcoding PLGA, which enables simultaneous, quantitative analysis of the fate of multiple nanoparticle formulations in vivo.

Label-Free LC-MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis.

Analysis of the cerebrospinal fluid (CSF) proteome has proven valuable to the study of neurodegenerative disorders. To identify new protein/pathway alterations and candidate biomarkers for amyotrophic lateral sclerosis (ALS), we performed comparative proteomic profiling of CSF from sporadic ALS (sALS), healthy control (HC), and other neurological disease (OND) subjects using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 1712 CSF proteins were detected and relatively quantified by spectral counting. Levels of several proteins with diverse biological functions were significantly altered in sALS samples. Enrichment analysis was used to link these alterations to biological pathways, which were predominantly related to inflammation, neuronal activity, and extracellular matrix regulation. We then used our CSF proteomic profiles to create a support vector machines classifier capable of discriminating training set ALS from non-ALS (HC and OND) samples. Four classifier proteins, WD repeat-containing protein 63, amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule 3, were identified by feature selection and externally validated. The resultant classifier distinguished ALS from non-ALS samples with 83% sensitivity and 100% specificity in an independent test set. Collectively, our results illustrate the utility of CSF proteomic profiling for identifying ALS protein/pathway alterations and candidate disease biomarkers.

Identification of a novel fibronectin-aggrecan complex in the synovial fluid of knees with painful meniscal injury.

BACKGROUND: Molecular biomarkers associated with knee pain may be useful as diagnostic modalities, prognostic indicators, and surrogate end points for therapeutic trials. The present study describes a novel complex of fibronectin and aggrecan that is present in the affected knee of patients with pain and meniscal abnormality. METHODS: The present prospective study included thirty patients with knee pain, mechanical symptoms, and magnetic resonance imaging findings that were positive for a meniscal tear who chose arthroscopic partial meniscectomy after unsuccessful nonoperative management. Synovial fluid was aspirated at the time of surgery and was assayed for the fibronectin-aggrecan complex with use of a heterogeneous enzyme-linked immunosorbent assay (ELISA). The results were compared with knee aspirates from ten asymptomatic volunteers with no pain who underwent magnetic resonance imaging of the knee. RESULTS: The mean optical density (and standard deviation) of the fibronectin-aggrecan complex was significantly greater in synovial fluid from knees undergoing arthroscopic surgery as compared with fluid from asymptomatic controls (13.29 ± 8.48 compared with 0.03 ± 0.09; p < 0.001). The mean age in the study group was significantly greater than in control group (46.0 ± 12.6 compared with 38.5 ± 6.0 years; p = 0.02), but controlling for age did not affect the results. Post hoc, an optical density cutoff value of 0.3 distinguished the study group from the control group with 100% accuracy. CONCLUSIONS: A novel fibronectin-aggrecan complex is present in the synovial fluid of painful knees with meniscal abnormality. The fibronectin-aggrecan complex may prove to be useful as a clinical biomarker or therapeutic target. Further research is warranted to correlate functional outcome after surgery with the fibronectin-aggrecan complex and other cartilage biomarkers.

Outcome of lumbar epidural steroid injection is predicted by assay of a complex of fibronectin and aggrecan from epidural lavage.

STUDY DESIGN: A single-center, prospective, consecutive case series of patients undergoing epidural lavage before the treatment of radiculopathy due to lumbar disc herniation. OBJECTIVE: To determine whether a novel complex of fibronectin and aggrecan predicts clinical response to epidural steroid injection (ESI) for the indication of radiculopathy from lumbar herniated nucleus pulposus (HNP). SUMMARY OF BACKGROUND DATA: ESI for lumbar radiculopathy due to HNP is widely used despite variable effectiveness for this indication. With increased attention aimed at cost containment, it would be beneficial to identify those in whom ESI may be helpful. There are currently no accurate diagnostic tests to predict response to ESI in back pain and sciatica syndromes. We have previously investigated biomarkers of disc degeneration associated with radiculopathy. METHODS: We embarked to determine whether a molecular complex of fibronectin and aggrecan predicts clinical response to ESI for the indication of radiculopathy from HNP. This prospective study was conducted at a single center and included 26 patients with radiculopathic pain and magnetic resonance imaging positive for HNP, who elected ESI. Epidural lavage with physiologic saline was performed immediately before ESI. The lavage fluid was assayed for the fibronectin-aggrecan complex (FAC) by using a heterogeneous sandwich enzyme-linked immunosorbent assay. The results were compared with the interval improvement in the physical component summary (PCS) score of the Medical Outcomes Study Short Form-36 instrument (SF-36) after injection compared with baseline. RESULTS: The mean improvement from baseline PCS in patients with the FAC was 22.9 (SD, 12.4) and without the complex was 0.64 (SD, 3.97; P < 0.001). Differences in total SF-36 improvement were also highly significant (P < 0.001). The presence of the FAC predicts a clinically significant increase in PCS after lumbar ESI by receiver-operating-characteristic analysis (area under the curve = 0.97; P < 0.001). There was no significant difference in age (P = 0.25), sex (P = 0.84), laterality (P = 0.06), lumbar spinal level (P = 0.75), or payer type (worker's compensation vs. private insurance; P = 0.90) between groups with and without the marker. CONCLUSION: A molecular complex of fibronectin and aggrecan predicts response to lumbar ESI for radiculopathy with HNP. The biomarker is accurate, objective, and not affected by demographic or psychosocial variables in this series.

Knowledge-based variable selection for learning rules from proteomic data.

BACKGROUND: The incorporation of biological knowledge can enhance the analysis of biomedical data. We present a novel method that uses a proteomic knowledge base to enhance the performance of a rule-learning algorithm in identifying putative biomarkers of disease from high-dimensional proteomic mass spectral data. In particular, we use the Empirical Proteomics Ontology Knowledge Base (EPO-KB) that contains previously identified and validated proteomic biomarkers to select m/zs in a proteomic dataset prior to analysis to increase performance. RESULTS: We show that using EPO-KB as a pre-processing method, specifically selecting all biomarkers found only in the biofluid of the proteomic dataset, reduces the dimensionality by 95% and provides a statistically significantly greater increase in performance over no variable selection and random variable selection. CONCLUSION: Knowledge-based variable selection even with a sparsely-populated resource such as the EPO-KB increases overall performance of rule-learning for disease classification from high-dimensional proteomic mass spectra.

Using a novel resource to decrease proteomic biomarker identification time.

The Empirical Proteomic Ontology Knowledge Base (EPO-KB) is an online database that represents current knowledge of biomarkers and contains associations between mass-to-charge (m/z) ratios of mass-spectrometry peaks to proteins. Such a database is a useful tool for identifying putative proteins associated with a m/z ratio. At present, EPO-KB contains data that have been extracted from 120 published research papers. It has been used in successful identification of a protein associated with a biomarker.