Dataset Information

Multi-Study Proteomic and Bioinformatic Identification of Molecular Overlap between Amyotrophic Lateral Sclerosis (ALS) and Spinal Muscular Atrophy (SMA).

ABSTRACT: Unravelling the complex molecular pathways responsible for motor neuron degeneration in amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA) remains a persistent challenge. Interest is growing in the potential molecular similarities between these two diseases, with the hope of better understanding disease pathology for the guidance of therapeutic development. The aim of this study was to conduct a comparative analysis of published proteomic studies of ALS and SMA, seeking commonly dysregulated molecules to be prioritized as future therapeutic targets. Fifteen proteins were found to be differentially expressed in two or more proteomic studies of both ALS and SMA, and bioinformatics analysis identified over-representation of proteins known to associate in vesicles and molecular pathways, including metabolism of proteins and vesicle-mediated transport-both of which converge on endoplasmic reticulum (ER)-Golgi trafficking processes. Calreticulin, a calcium-binding chaperone found in the ER, was associated with both pathways and we independently confirm that its expression was decreased in spinal cords from SMA and increased in spinal cords from ALS mice. Together, these findings offer significant insights into potential common targets that may help to guide the development of new therapies for both diseases.

SUBMITTER: Soltic D

PROVIDER: S-EPMC6315439 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Multi-Study Proteomic and Bioinformatic Identification of Molecular Overlap between Amyotrophic Lateral Sclerosis (ALS) and Spinal Muscular Atrophy (SMA).

Šoltić Darija D Bowerman Melissa M Stock Joanne J Shorrock Hannah K HK Gillingwater Thomas H TH Fuller Heidi R HR

Brain sciences 20181204 12

Unravelling the complex molecular pathways responsible for motor neuron degeneration in amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA) remains a persistent challenge. Interest is growing in the potential molecular similarities between these two diseases, with the hope of better understanding disease pathology for the guidance of therapeutic development. The aim of this study was to conduct a comparative analysis of published proteomic studies of ALS and SMA, seeking common ...[more]

PMID: 30518112

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Project description:ObjectivesSpinal 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).MethodsBforSMA 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.Results12 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.ConclusionsDiscovery 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.

Project description:BackgroundSpinal muscular atrophy (SMA) is a rare, progressive neuromuscular disease that affects individuals with a broad age range. SMA is typically characterised by symmetrical muscle weakness but is also associated with cardiac defects, life-limiting impairments in respiratory function and bulbar function defects that affect swallowing and speech. Despite the advent of three innovative disease-modifying therapies (DMTs) for SMA, the cost of DMTs in addition to the costs of standard of care can be a barrier to treatment access for patients. Health Technology Assessment (HTA) decision makers evaluate the cost effectiveness of a new treatment before making a reimbursement decision.ObjectiveThe primary objective was to conduct a systematic literature review (SLR) to identify the modelling approaches used in economic evaluations that assess current approved treatments in SMA, with a secondary objective to widen the scope and identify economic evaluations assessing other (non-SMA) neuromuscular disorders.MethodsAn SLR was performed to identify available economic evaluations associated with any type of SMA (Type 1, 2, 3 and/or 4). Economic evaluations associated with other (non-SMA) neuromuscular disorders were identified but not further analysed. Electronic searches were conducted in Embase, MEDLINE, Evidence-Based Medicine Reviews and EconLit via the Ovid platform in August 2019, and were supplemented by searches of the grey literature (reference lists, conference proceedings, global HTA body websites and other relevant sources). Eligibility criteria were based on the population, interventions, comparators and outcomes (PICO) framework. Quality assessment of full publications was conducted with reference to a published checklist.ResultsNine publications covering eight unique studies met all eligibility criteria for inclusion in the SLR, including four conference abstracts, two peer-reviewed original research articles and three HTA submissions (conducted in Canada, the US and the UK). Evaluations considered patients with early infantile-onset (most likely to develop Type 1 or Type 2 SMA), later-onset SMA and both infantile- and later-onset SMA. Data for the identified economic models were collected from literature reviews and relatively short-term clinical trials. Several intent-to-treat clinical trial populations were used in the studies, which resulted in variation in cycle length and different outcome measures to determine clinical efficacy. The results of the quality assessment on the five full-text, peer-reviewed publications found that they generally provided clear descriptions of objectives, modelling methods and results. However, key decisions, such as choice of economic evaluation, model type and choice of variables for sensitivity analysis, were often not adequately justified.ConclusionsThis SLR highlights the need for economic evaluations in SMA to better align in modelling approaches with respect to (i) consistency in model structure and use of motor function milestones as health states; (ii) consensus on measuring quality of life to estimate utilities; (iii) consistency in data collection by registries; and (iv) consensus on SMA-type classification and endpoints that determine intervention efficacy. Future economic evaluations should also incorporate the review group critiques of previous HTA submissions relating to data inputs and approaches to modelling and should include patient data reflective of the SMA population being modelled. Economic evaluations would also be improved with inclusion of long-term efficacy and safety data from clinical trials and valid patient and caregiver utility data.

Dataset Information

Multi-Study Proteomic and Bioinformatic Identification of Molecular Overlap between Amyotrophic Lateral Sclerosis (ALS) and Spinal Muscular Atrophy (SMA).

Publications

Multi-Study Proteomic and Bioinformatic Identification of Molecular Overlap between Amyotrophic Lateral Sclerosis (ALS) and Spinal Muscular Atrophy (SMA).

Similar Datasets

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