Meta-analysis of gene expression differences in post-mortem cortex samples from ALS patients and control subjects

Gene expression profiling has been used to understand transcriptional alterations that distinguish tissues from ALS patients and normal control individuals [1, 2], as well as to identify molecular subtypes and substages contributing to the heterogeneity observed among ALS patients [3]. This work will use a random effect inverse variance meta-analysis model to identify genes with robustly altered expression in post-mortem ALS tissues [2]. The model will generate differential expression summary statistics for all protein-coding genes having detectable expression within the CNS, identifying those transcriptional alterations that are most repeatable across a broad range of expression profiling platforms and technologies (i.e., microarray, bulk RNA-seq, snRNA-seq). These genes will then be further investigated to identify over-represented annotations, based upon multiple databases, such as Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathways. A comparison will be made to genes located near previously identified ALS genetic risk loci, with the goal of identifying functional genomics changes that correspond to genetic alterations predisposing patients to disease. A mixed-effects meta-regression model will be used to identify moderating variables associated with between-study variation in effect size. Data will only be accessed by Dr. William Swindell in accordance with NIAGADS. appropriate use policies, without further access by any other investigators.

[1] Swindell WR. 2025. Meta-analysis of gene expression in bulk-processed post-mortem spinal cord from ALS patients and normal controls. NeuroSci 6(3): 65.

[2] Swindell WR. 2024. Meta-analysis of differential gene expression in lower motor neurons isolated by laser capture microdissection from post-mortem ALS spinal cords. Frontiers in Genetics 15:1385114.

[3] Swindell WR, Kruse CPS, List EO, Berryman DE, Kopchick JJ. 2019. ALS blood expression profiling identifies new biomarkers, patient subgroups, and evidence for neutrophilia and hypoxia. Journal of Translational Medicine 17(1):170.

ALS is a debilitating neurodegenerative disease with genetic and sporadic forms. Prognosis is poor although there is substantial heterogeneity among patients and new treatments have been developed and approved for those with certain types of familial disease (e.g., SOD1 mutations). This study will use gene expression profiling to identify mRNA transcripts having expression that is consistently altered in post-mortem cortex samples from ALS patients. The approach will involve large-scale integration between multiple datasets that have been generated in over decades and deposited within the public domain. The goal of this work is to highlight highly reproducible findings in post-mortem tissue samples from ALS patients, which can help focus investigational effort on genes and pathways most robustly altered in end-stage disease.