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Deep learning methods to predict amyotrophic lateral sclerosis disease progression.

ABSTRACT: Amyotrophic lateral sclerosis (ALS) is a highly complex and heterogeneous neurodegenerative disease that affects motor neurons. Since life expectancy is relatively low, it is essential to promptly understand the course of the disease to better target the patient's treatment. Predictive models for disease progression are thus of great interest. One of the most extensive and well-studied open-access data resources for ALS is the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) repository. In 2015, the DREAM-Phil Bowen ALS Prediction Prize4Life Challenge was held on PRO-ACT data, where competitors were asked to develop machine learning algorithms to predict disease progression measured through the slope of the ALSFRS score between 3 and 12 months. However, although it has already been successfully applied in several studies on ALS patients, to the best of our knowledge deep learning approaches still remain unexplored on the ALSFRS slope prediction in PRO-ACT cohort. Here, we investigate how deep learning models perform in predicting ALS progression using the PRO-ACT data. We developed three models based on different architectures that showed comparable or better performance with respect to the state-of-the-art models, thus representing a valid alternative to predict ALS disease progression.

SUBMITTER: Pancotti C

PROVIDER: S-EPMC9374680 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Deep learning methods to predict amyotrophic lateral sclerosis disease progression.

Pancotti Corrado C Birolo Giovanni G Rollo Cesare C Sanavia Tiziana T Di Camillo Barbara B Manera Umberto U Chiò Adriano A Fariselli Piero P

Scientific reports 20220812 1

Amyotrophic lateral sclerosis (ALS) is a highly complex and heterogeneous neurodegenerative disease that affects motor neurons. Since life expectancy is relatively low, it is essential to promptly understand the course of the disease to better target the patient's treatment. Predictive models for disease progression are thus of great interest. One of the most extensive and well-studied open-access data resources for ALS is the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) repository. ...[more]

PMID: 35962027

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Project description:Amyotrophic lateral sclerosis is a relentless and devastating adult-onset neurodegenerative disease with no known cure. In mice with amyotrophic lateral sclerosis, CD4+ T lymphocytes and wild-type microglia potentiate protective inflammatory responses and play a principal role in disease pathoprogression. Using this model, we demonstrate that endogenous T lymphocytes, and more specifically regulatory T lymphocytes, are increased at early slowly progressing stages, augmenting interleukin-4 expression and protective M2 microglia, and are decreased when the disease rapidly accelerates, possibly through the loss of FoxP3 expression in the regulatory T lymphocytes. Without ex vivo activation, the passive transfer of wild-type CD4+ T lymphocytes into amyotrophic lateral sclerosis mice lacking functional T lymphocytes lengthened disease duration and prolonged survival. The passive transfer of endogenous regulatory T lymphocytes from early disease stage mutant Cu2+/Zn2+ superoxide dismutase mice into these amyotrophic lateral sclerosis mice, again without ex vivo activation, were substantially more immunotherapeutic sustaining interleukin-4 levels and M2 microglia, and resulting in lengthened disease duration and prolonged survival; the stable disease phase was extended by 88% using mutant Cu2+/Zn2+ superoxide dismutase regulatory T lymphocytes. A potential mechanism for this enhanced life expectancy may be mediated by the augmented secretion of interleukin-4 from mutant Cu2+/Zn2+ superoxide dismutase regulatory T lymphocytes that directly suppressed the toxic properties of microglia; flow cytometric analyses determined that CD4+/CD25+/FoxP3+ T lymphocytes co-expressed interleukin-4 in the same cell. These observations were extended into the amyotrophic lateral sclerosis patient population where patients with more rapidly progressing disease had decreased numbers of regulatory T lymphocytes; the numbers of regulatory T lymphocytes were inversely correlated with disease progression rates. These data suggest a cellular mechanism whereby endogenous regulatory T lymphocytes are immunocompetent and actively contribute to neuroprotection through their interactions with microglia. Furthermore, these data suggest that immunotherapeutic interventions must begin early in the pathogenic process since immune dysfunction occurs at later stages. Thus, the cumulative mouse and human amyotrophic lateral sclerosis data suggest that increasing the levels of regulatory T lymphocytes in patients with amyotrophic lateral sclerosis at early stages in the disease process may be of therapeutic value, and slow the rate of disease progression and stabilize patients for longer periods of time.

Project description:Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disease with progressive motor neuron death, where patients usually die within 5 years of diagnosis. Previously, we showed that the C-boutons, which are large cholinergic synapses to motor neurons that modulate motor neuron activity, are necessary for behavioral compensation in mSOD1G93A mice, a mouse model for ALS. We reasoned that, since the C-boutons likely increase the excitability of surviving motor neurons to compensate for motor neuron loss during ALS disease progression, then amplitude modulation through the C-boutons likely increases motor neuron stress and worsens disease progression. By comparing male and female mSOD1G93A mice to mSOD1G93A mice with genetically silenced C-boutons [mSOD1G93A ; Dbx1::cre; ChATfl/fl (mSOD1G93A/Coff )], we show that the C-boutons do not influence the humane end point of mSOD1G93A mice; however, our histologic analysis shows that C-bouton silencing significantly improves fast-twitch muscle innervation over time. Using immunohistology, we also show that the C-boutons are active in a task-dependent manner, and that symptomatic mSOD1G93A mice show significantly higher C-bouton activity than wild-type mice during low-intensity walking. Last, by using behavioral analysis, we provide evidence that C-bouton silencing in combination with swimming is beneficial for the behavioral capabilities of mSOD1G93A mice. Our observations suggest that manipulating the C-boutons in combination with a modulatory-targeted training program may therefore be beneficial for ALS patients and could result in improved mobility and quality of life.SIGNIFICANCE STATEMENT Despite decades of research on amyotrophic lateral sclerosis (ALS), there have been little improvements in treatments and therapies. We sought to better understand how the activation of C-boutons, which are large cholinergic modulatory synapses on motor neurons, change and affect the disease as it progresses. When these C-boutons are genetically silenced and exercises designed to otherwise activate the C-boutons are frequently performed in ALS model mice, the mice perform better than their untreated counterparts over time. C-bouton-targeted therapies could therefore be beneficial for ALS patients and could result in improved mobility and quality of life.

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Deep learning methods to predict amyotrophic lateral sclerosis disease progression.

Publications

Deep learning methods to predict amyotrophic lateral sclerosis disease progression.

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