Evidence map›Paper›PMID 40100818›Full record

ArticlePloS one2025

Potential multiple disease progression pathways in female patients with Alzheimer's disease inferred from transcriptome and epigenome data of the dorsolateral prefrontal cortex.

Kousei Honda, Akinori Awazu

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Kousei HondaGraduate School of Integrated Sciences for Life, Hiroshima University, Higashihiroshima, Hiroshima, Japan.
Akinori AwazuGraduate School of Integrated Sciences for Life, Hiroshima University, Higashihiroshima, Hiroshima, Japan.ORCID https://orcid.org/0000-0002-0778-021X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Late-onset Alzheimer's disease (AD) is a typical type of dementia for which therapeutic strategies have not yet been established. The database of the Rush Alzheimer's Disease study by the ENCODE consortium contains transcriptome and various epigenome data. Although the Rush AD database may contain a satisfactory amount of data for women, the amount of data for men remains insufficient. Here, based on an analysis of publicly available data from female patients, this study found that AD pathology appears to be nonuniform; AD patients were divided into several groups with differential gene expression patterns, including those related to cognitive function. First, cluster analysis was performed on individuals diagnosed with "No Cognitive Impairment (NCI)," "Mild Cognitive Impairment (MCI)," and "Alzheimer's Disease (AD)" stages in clinical trials using gene expression, and multiple substages were identified across AD progression. The epigenome data, in particular genome-wide H3k4me3 distribution data, also supported the existence of multiple AD substages. However, APOE gene polymorphisms of individuals seemed to not correlate with disease stage. An inference of adjacency networks among substages, evaluated via partition-based graph abstraction using the gene expression profiles of individuals, suggested the possibility of multiple typical disease progression pathways from NCI to different AD substages through various MCI substages. These findings could refine biomarker discovery or inform personalized therapeutic approaches.

Indexed as

Alzheimer DiseaseEpigenomePrefrontal CortexTranscriptomeAgedAged, 80 and overApolipoproteins ECognitive DysfunctionDisease ProgressionEpigenesis, GeneticFemaleGene Expression ProfilingHumansApolipoproteins E

Identifiers

PMID40100818
PMCPMC11918443

What Socratic holds

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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 Socratic graph.