ArticlebioRxiv : the preprint server for biology2026
RNA-seq variants reveal distinct patterns in the aging epitranscriptome: an in-depth analysis of age-matched Alzheimer's Disease patients and a cognitively normal cohort.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Background: Post-transcriptional modifications are those made to the RNA transcript, which can modulate RNA stability and function. Despite robust investigation of the genome, transcriptome, and proteome, little is known about post-transcriptional modifications during normal aging or Alzheimer's disease (AD) pathogenesis. Several studies have shown epitranscriptomic changes in AD brains for certain modification types, establishing epitranscriptomic links to the disease; however, the complete set of post-transcriptional modifications have not been assessed in the context of AD. Furthermore, it is not understood which genes or pathways are under epitranscriptomic regulation, how conserved and sporadic modifications are distributed, or which conserved sites are differentially modified in diseased brains. Therefore, there is a need for a more complete analysis to describe the full landscape of the epitranscriptome in AD, helping to bridge the knowledge gap between post-transcriptional modifications and the molecular etiology of AD. Methods: We designed and implemented a novel bioinformatics pipeline for complex epitranscriptome-wide analysis of potential RNA modification sites in sample-matched, whole-genome sequencing-filtered variant calls from RNA sequencing data. Using parametric and non-parametric tests, we tested differences in patterns for all detectable variant calls between postmortem brains of AD and cognitively normal, aged individuals. Results: We identified 544 genes with hyper-modified transcripts in AD samples compared with cognitively normal controls, a notable observation being high enrichment of genes in the "Kaposi's sarcoma-associated herpesvirus" pathway. We also identified patterns of recurring and sporadic modification sites that differed complementarily between disease and non-disease conditions. We found 17 genes (33 total sites) that were differentially modified between conditions including several sites found exclusively in the AD epitranscriptome. Conclusions: These findings provide a more complete profile of the potential molecular underpinnings which differentiate AD brains from their non-diseased, aged counterparts and reveal patterns and modification sites which can be further investigated for how they contribute to the network of molecular interactions underlying AD. These elements are likely to be valuable candidates for investigations that aim to further the search for biomarkers and therapeutic targets.
Indexed as
Identifiers
What OpenQuestion holds
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.