SMA-MAP: A Plasma Protein Panel for Spinal Muscular Atrophy

Objectives: Spinal Muscular Atrophy (SMA) presents challenges in (i) monitoring disease activity and predicting progression, (ii) designing trials that allow rapid assessment of candidate therapies, and (iii) understanding molecular causes and consequences of the disease. Validated biomarkers of SMA motor and non-motor function would offer utility in addressing these challenges. Our objectives were (i) to discover additional markers from the Biomarkers for SMA (BforSMA) study using an immunoassay platform, and (ii) to validate the putative biomarkers in an independent cohort of SMA patients collected from a multi-site natural history study (NHS). Methods: BforSMA study plasma samples (N = 129) were analyzed by immunoassay to identify new analytes correlating to SMA motor function. These immunoassays included the strongest candidate biomarkers identified previously by chromatography. We selected 35 biomarkers to validate in an independent cohort SMA type 1, 2, and 3 samples (N = 158) from an SMA NHS. The putative biomarkers were tested for association to multiple motor scales and to pulmonary function, neurophysiology, strength, and quality of life measures. We implemented a Tobit model to predict SMA motor function scores. Results: 12 of the 35 putative SMA biomarkers were significantly associated (p\u3c0.05) with motor function, with a 13th analyte being nearly significant. Several other analytes associated with non-motor SMA outcome measures. From these 35 biomarkers, 27 analytes were selected for inclusion in a commercial panel (SMA-MAP) for association with motor and other functional measures. Conclusions: Discovery and validation using independent cohorts yielded a set of SMA biomarkers significantly associated with motor function and other measures of SMA disease activity. A commercial SMA-MAP biomarker panel was generated for further testing in other SMA collections and interventional trials. Future work includes evaluating the panel in other neuromuscular diseases, for pharmacodynamic responsiveness to experimental SMA therapies, and for predicting functional changes over time in SMA patients. © 2013 Kobayashi et al

Comprehensive Serum Profiling for the Discovery of Epithelial Ovarian Cancer Biomarkers

FDA-cleared ovarian cancer biomarkers are limited to CA-125 and HE4 for monitoring and recurrence and OVA1, a multivariate panel consisting of CA-125 and four additional biomarkers, for referring patients to a specialist. Due to relatively poor performance of these tests, more accurate and broadly applicable biomarkers are needed. We evaluated the dysregulation of 259 candidate cancer markers in serum samples from 499 patients. Sera were collected prospectively at 11 monitored sites under a single well-defined protocol. All stages of ovarian cancer and common benign gynecological conditions were represented. To ensure consistency and comparability of biomarker comparisons, all measurements were performed on a single platform, at a single site, using a panel of rigorously calibrated, qualified, high-throughput, multiplexed immunoassays and all analyses were conducted using the same software. Each marker was evaluated independently for its ability to differentiate ovarian cancer from benign conditions. A total of 175 markers were dysregulated in the cancer samples. HE4 (AUC = 0.933) and CA-125 (AUC = 0.907) were the most informative biomarkers, followed by IL-2 receptor α, α1-antitrypsin, C-reactive protein, YKL-40, cellular fibronectin, CA-72-4 and prostasin (AUC>0.800). To improve the discrimination between cancer and benign conditions, a simple multivariate combination of markers was explored using logistic regression. When combined into a single panel, the nine most informative individual biomarkers yielded an AUC value of 0.950, significantly higher than obtained when combining the markers in the OVA1 panel (AUC 0.912). Additionally, at a threshold sensitivity of 90%, the combination of the top 9 markers gave 88.9% specificity compared to 63.4% specificity for the OVA1 markers. Although a blinded validation study has not yet been performed, these results indicate that alternative biomarker combinations might lead to significant improvements in the detection of ovarian cancer

Particle on membrane assay system

Described herein is an analyte detection device and method related to a portable instrument suitable for point-of-care analyses. In some embodiments, a portable instrument may include a disposable cartridge, an optical detector, a sample collection device and/or sample reservoir, reagent delivery systems, fluid delivery systems, one or more channels, and/or waste reservoirs. Use of a portable instrument may reduce the hazard to an operator by reducing an operator's contact with a sample for analysis. The device is capable of obtaining diagnostic information using cellular- and/or particle-based analyses and may be used in conjunction with membrane- and/or particle-based analysis cartridges. Analytes, including proteins and cells and/or microbes may be detected using the membrane and/or particle based analysis system.Board of Regents, University of Texas Syste

Integration of fluids and reagents into self-contained cartridges containing sensor elements and reagent delivery systems

Described herein is an analyte detection device and method related to a portable instrument suitable for point-of-care analyses. In some embodiments, a portable instrument may include a disposable cartridge, an optical detector, a sample collection device and/or sample reservoir, reagent delivery systems, fluid delivery systems, one or more channels, and/or waste reservoirs. Use of a portable instrument may reduce the hazard to an operator by reducing an operator's contact with a sample for analysis. The device is capable of obtaining diagnostic information using cellular- and/or particle-based analyses and may be used in conjunction with membrane- and/or particle-based analysis cartridges. Analytes, including proteins and cells and/or microbes may be detected using the membrane and/or particle based analysis system.Board of Regents, University of Texas Syste

Integration of fluids and reagents into self-contained cartridges containing sensor elements

Described herein is an analyte detection device and method related to a portable instrument suitable for point-of-care analyses. In some embodiments, a portable instrument may include a disposable cartridge, an optical detector, a sample collection device and/or sample reservoir, reagent delivery systems, fluid delivery systems, one or more channels, and/or waste reservoirs. Use of a portable instrument may reduce the hazard to an operator by reducing an operator's contact with a sample for analysis. The device is capable of obtaining diagnostic information using cellular- and/or particle-based analyses and may be used in conjunction with membrane- and/or particle-based analysis cartridges. Analytes, including proteins and cells and/or microbes may be detected using the membrane and/or particle based analysis system.Board of Regents, University of Texas Syste

SMA-MAP: A Plasma Protein Panel for Spinal Muscular Atrophy

<div><p>Objectives</p><p>Spinal Muscular Atrophy (SMA) presents challenges in (i) monitoring disease activity and predicting progression, (ii) designing trials that allow rapid assessment of candidate therapies, and (iii) understanding molecular causes and consequences of the disease. Validated biomarkers of SMA motor and non-motor function would offer utility in addressing these challenges. Our objectives were (i) to discover additional markers from the Biomarkers for SMA (BforSMA) study using an immunoassay platform, and (ii) to validate the putative biomarkers in an independent cohort of SMA patients collected from a multi-site natural history study (NHS).</p> <p>Methods</p><p>BforSMA study plasma samples (N = 129) were analyzed by immunoassay to identify new analytes correlating to SMA motor function. These immunoassays included the strongest candidate biomarkers identified previously by chromatography. We selected 35 biomarkers to validate in an independent cohort SMA type 1, 2, and 3 samples (N = 158) from an SMA NHS. The putative biomarkers were tested for association to multiple motor scales and to pulmonary function, neurophysiology, strength, and quality of life measures. We implemented a Tobit model to predict SMA motor function scores.</p> <p>Results</p><p>12 of the 35 putative SMA biomarkers were significantly associated (p<0.05) with motor function, with a 13^th analyte being nearly significant. Several other analytes associated with non-motor SMA outcome measures. From these 35 biomarkers, 27 analytes were selected for inclusion in a commercial panel (SMA-MAP) for association with motor and other functional measures.</p> <p>Conclusions</p><p>Discovery and validation using independent cohorts yielded a set of SMA biomarkers significantly associated with motor function and other measures of SMA disease activity. A commercial SMA-MAP biomarker panel was generated for further testing in other SMA collections and interventional trials. Future work includes evaluating the panel in other neuromuscular diseases, for pharmacodynamic responsiveness to experimental SMA therapies, and for predicting functional changes over time in SMA patients.</p> </div

Top 13 SMA motor function regressors are markers in two SMA populations.

<p>The top 13 list was compiled based on significant regression to HFMS and other SMA motor outcome measures in the PNCRN natural history study sampleset. The pilot panel of markers tested included 35 top motor analytes identified via the BforSMA study and these 13 analytes represent robust repeat markers in a distinct SMA population.</p

SMA non-motor outcome regressors.

<p>Several markers were identified in the PNCR NHS as regressing to the Children’s Hospital of Philadelphia Test of Strength (CHOP-TOSS), pulmonary function (best FVC), electrophysiology (CMAP and MUNE), strength as measured by knee and elbow flexion and extension(log average MyoEF, MyoKE, MyoKF), parent-reported and child-reported quality of life (PQP and PQC).</p

SMA-MAP motor function score prediction model.

<p>Using Tobit linear regression models SMA motor scores were predicted from SMA-MAP analytes values with age of onset as a covariable. Pearson correlations between actual and predicted motor scores for the top 6 combinations from BforSMA were plotted. <b>A</b>: Graph of actual and predicted motor scores of a 6 analyte model uncensored model. Type 1 SMA patients and ambulatory Type 3 subjects can be represented in the analysis and given a score below 0 or over 40 respectively. <b>B</b>: Graph of 6 analyte motor scores using values censored between 0 and 40. Note that the Type 1 datapoints have been moved arbitrarily to the right to allow visualization, and these points still represent values of 0.</p