ArticleAnnals of human genetics2020
Genetic model of MS severity predicts future accumulation of disability.
Article in Annals of human genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 40 citations in OpenAlex.
- The role of machine learning in developing non-magnetic resonance imaging based biomarkers for multiple sclerosis: a systematic review.BMC medical informatics and decision making · 2022Pooled it
- Current Status and Future Opportunities in Modeling Clinical Characteristics of Multiple Sclerosis.Frontiers in neurology · 2022Pooled it
- Analysis of CNS autoimmunity in genetically diverse mice reveals unique phenotypes and mechanisms.JCI insight · 2024Article
- Artificial Intelligence and Multiple Sclerosis.Current neurology and neuroscience reports · 2024Review
- Big data and artificial intelligence applied to blood and CSF fluid biomarkers in multiple sclerosis.Frontiers in immunology · 2024Review
- Methyl-CpG-Binding Protein 2 Emerges as a Central Player in Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders.Cellular and molecular neurobiology · 2023Review
- Prognostic models for predicting clinical disease progression, worsening and activity in people with multiple sclerosis.The Cochrane database of systematic reviews · 2023Review
- The association between disability progression, relapses, and treatment in early relapse onset MS: an observational, multi-centre, longitudinal cohort study.Scientific reports · 2023Observational
- Genetic influences on disease course and severity, 30 years after a clinically isolated syndrome.Brain communications · 2023Article
- Molecular models of multiple sclerosis severity identify heterogeneity of pathogenic mechanisms.Nature communications · 2022Article
- Ensemble machine learning identifies genetic loci associated with future worsening of disability in people with multiple sclerosis.Scientific reports · 2022Article
- Multiple sclerosis diagnosis and phenotype identification by multivariate classification of in vivo frontal cortex metabolite profiles.Scientific reports · 2022Article
- Role of Multiple Vitamin D-Related Polymorphisms in Multiple Sclerosis Severity: Preliminary Findings.Genes · 2022Observational
- Classification of multiple sclerosis clinical profiles using machine learning and grey matter connectome.Frontiers in robotics and AI · 2022Article
- Machine learning-optimized Combinatorial MRI scale (COMRISv2) correlates highly with cognitive and physical disability scales in Multiple Sclerosis patients.Frontiers in radiology · 2022Article
- Machine Learning Use for Prognostic Purposes in Multiple Sclerosis.Life (Basel, Switzerland) · 2021Review
- Developing a clinical-environmental-genotypic prognostic index for relapsing-onset multiple sclerosis and clinically isolated syndrome.Brain communications · 2021Article
- Genetic factors for susceptibility to and manifestations of neuromyelitis optica.Annals of clinical and translational neurology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
No genetic modifiers of multiple sclerosis (MS) severity have been independently validated, leading to a lack of insight into genetic determinants of the rate of disability progression. We investigated genetic modifiers of MS severity in prospectively acquired training (N = 205) and validation (N = 94) cohorts, using the following advances: (1) We focused on 113 genetic variants previously identified as related to MS severity; (2) We used a novel, sensitive outcome: MS Disease Severity Scale (MS-DSS); (3) Instead of validating individual alleles, we used a machine learning technique (random forest) that captures linear and complex nonlinear effects between alleles to derive a single Genetic Model of MS Severity (GeM-MSS). The GeM-MSS consists of 19 variants located in vicinity of 12 genes implicated in regulating cytotoxicity of immune cells, complement activation, neuronal functions, and fibrosis. GeM-MSS correlates with MS-DSS (r = 0.214; p = 0.043) in a validation cohort that was not used in the modeling steps. The recognized biology identifies novel therapeutic targets for inhibiting MS disability progression.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.