ALS molecular subtypes are a combination of cellular and pathological features learned by deep multiomics classifiers

O'Neill, Kathryn, Shaw, Regina, Bolger, Isobel, NYGC ALS Consortium, Tam, Oliver H, Phatnani, Hemali, Gale Hammell, Molly (March 2025) ALS molecular subtypes are a combination of cellular and pathological features learned by deep multiomics classifiers. Cell Reports, 44 (3). p. 115402. ISSN 2211-1247 (Public Dataset)

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Abstract

Amyotrophic lateral sclerosis (ALS) is a complex syndrome with multiple genetic causes and wide variation in disease presentation. Despite this heterogeneity, large-scale genomics studies revealed that ALS postmortem samples can be grouped into a small number of subtypes, defined by transcriptomic signatures of mitochondrial dysfunction and oxidative stress (ALS-Ox), microglial activation and neuroinflammation (ALS-Glia), or TDP-43 pathology and associated transposable elements (ALS-TE). In this study, we present a deep ALS neural net classifier (DANCer) for ALS molecular subtypes. Applying DANCer to an expanded cohort from the NYGC ALS Consortium highlights two subtypes that strongly correlate with disease duration: ALS-TE in cortex and ALS-Glia in spinal cord. Finally, single-nucleus transcriptomes demonstrate that ALS subtypes are recapitulated in neurons and glia, with both ALS-wide and subtype-specific alterations in all cell types. In summary, ALS molecular subtypes represent a combination of cellular and pathological features that correlate with clinical features of ALS.

Item Type: Paper
Subjects: diseases & disorders
diseases & disorders > neurodegenerative diseases > ALS
diseases & disorders > neurodegenerative diseases
CSHL Authors:
Communities: CSHL Cancer Center Program > Cancer Genetics and Genomics Program
CSHL labs > Hammell M. lab
CSHL Cancer Center Program
SWORD Depositor: CSHL Elements
Depositing User: CSHL Elements
Date: 25 March 2025
Date Deposited: 28 Apr 2025 12:40
Last Modified: 28 Apr 2025 12:40
PMCID: PMC12011103
Related URLs:
Dataset ID:
URI: https://repository.cshl.edu/id/eprint/41860

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