Amyotrophic lateral sclerosis (ALS) is a terminal neurodegenerative disease, marked by considerable clinical and molecular heterogeneity. While several genetic drivers have been linked to familial ALS (fALS), the biology of sporadic ALS (sALS)—which accounts for the majority of ALS cases—remains poorly defined. To address this gap, we analyzed 247 bulk mRNA-sequenced post-mortem tissue samples from the lumbar spinal cord and motor cortex and compared expression profiles between fALS, sALS, and controls. Variance-stabilized DEGs from DESeq2 analysis were used as inputs for weighted gene co-expression network analysis (WGCNA). Finally, gene ontology was used to identify transcriptomic signatures and biological pathways unique to sALS and fALS. In the spinal cord, sALS samples exhibited specific downregulation of mitochondrial complex I subunits (e.g., NDUFS8 and NDUFB7) and regulatory genes (e.g., AURKAIP1 and ATP5F1D), suggesting compromised metabolic resilience. In the motor cortex, a co-expression module associated with adaptive immune function and leukocyte infiltration was downregulated in sALS yet upregulated in fALS, indicating distinct inflammatory pathways between these two forms of ALS. Together, our findings highlight that while sALS and fALS are largely the same disease, they exhibit distinct transcriptomic signatures. By accounting for mode of inheritance in study designs—particularly sALS, which represents ~90% of ALS cases—researchers may reveal deeper insights into ALS pathology. This perspective could enable more targeted therapeutic strategies, ultimately improving outcomes for all ALS patients.
Stratifying ALS Patients by Mode of Inheritance Reveals Transcriptomic Signatures Specific to sALS and fALS
Alexandria Awai,Erica L. Johnson,Tiandong Leng,John Patrickson,Michael C. Zody,J. Lillard
Published 2025 in International Journal of Molecular Sciences
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- Publication year
2025
- Venue
International Journal of Molecular Sciences
- Publication date
2025-09-01
- Fields of study
Biology, Medicine
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- Source metadata
Semantic Scholar, PubMed
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