OSCR

A meta-refined human Alzheimer's disease-associated gene subset shows partial mouse-model pathway correspondence and limited cross-cohort machine-learning transportability.

Overview

Authors: Linsong Chai1, Yunshi Huang1, Jinglei Ni1, Shuang Zuo1, Jia Huang1,2,3, Bingbing Lin1,2,3
ORCID iDs: Linsong Chai
  1. College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
  2. National‐Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China
  3. Fujian Key Laboratory of Rehabilitation Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, China
Institutions: Fujian University of Traditional Chinese Medicine (China)
Journal: Alzheimer's & dementia : the journal of the Alzheimer's Association, volume 22, issue 9, article e71804
Dates: received 12 June 2026; accepted 4 August 2026; published online 7 September 2026; in print September 2026
Type: Research article · Language: English
License: CC BY-NC
Identifiers: DOI 10.1002/alz.71804 · PMID 42706501 · PMCID PMC13550512 · OpenAlex W7211942319
Open access: hybrid, a free copy (OpenAlex)
Status: data only
Categories: genetics / omics (modality), human (organism), mouse (organism), Alzheimer's / dementia (population), cellular / molecular (subfield)
Methods: Connectivity, Statistics, Smoothing, state filtering, decompositions, Machine learning
Keywords: Alzheimer's disease, cross‐cohort transportability, cross‐species transcriptomics, mouse models, pathway correspondence
MeSH: Alzheimer Disease*, Disease Models, Animal*, Machine Learning*, Animals, Brain, Cohort Studies, Humans, Mice (* major topic)
Topic: Alzheimer's disease research and treatments (Physiology, Medicine), according to OpenAlex
Funding: Natural Science Foundation of Fujian Province (2023J01876); Joint Funds for the Innovation of Science and Technology (2025Y9599)
Citations: not cited yet (Europe PMC); 50 references in the paper

Abstract

INTRODUCTION: Common Alzheimer's disease (AD) mouse models are widely used, but their molecular correspondence with human AD remains uncertain.

METHODS: We analyzed 15 post mortem human brain datasets, four human non‐brain or in vitro sensitivity datasets, and nine AD‐related mouse‐model molecular‐profiling datasets; GSE222494 was analyzed separately for single‐nucleus localization. Refined107, a meta‐refined 107‐gene human AD‐associated gene subset, was evaluated using recurrence‐matched control sampling, independent pathway‐level comparison, within cohort out‐of‐fold (OOF) classification, and ordered cross‐cohort transportability.

RESULTS: Refined107 comprised 37 Tier 1 and 70 Tier 2 genes and showed greater statistical consistency than recurrence‐matched controls. Functional annotation implicated inflammatory, blood–brain barrier, metabolic, neuronal, and developmental programs. Among 636 recurrent human pathways, 226 showed same‐direction support in at least one evaluated mouse‐model family, indicating partial and model‐dependent human–mouse correspondence. Post‐selection within‐cohort OOF areas under the curve (AUCs) were 0.833 to 0.980, whereas ordered cross‐cohort AUCs were 0.288 to 0.720.

DISCUSSION: Refined107 represents a statistically consistent, meta‐refined human AD‐associated gene subset rather than a comprehensive disease signature. Human–mouse pathway correspondence was partial and model‐dependent, and within‐cohort classification did not translate into robust cross‐cohort transportability.

Reproduced under the paper's license (CC BY-NC), from the paper cited above.

Code

The paper links to its data, not to its authors' code: see the Data section.

Tracing map

A tracing map links a paper to the code its authors published: this paper has none, so it has no map.

Data

Datasets cited

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 5 keywords, 8 MeSH terms, 2 funders, 50 references.

Cite

This paper

Chai, L., Huang, Y., Ni, J., Zuo, S., Huang, J., & Lin, B. (2026). A meta-refined human Alzheimer's disease-associated gene subset shows partial mouse-model pathway correspondence and limited cross-cohort machine-learning transportability. Alzheimer's & dementia : the journal of the Alzheimer's Association, 22(9), e71804. https://doi.org/10.1002/alz.71804

BibTeX

@article{chai2026meta,
author = {Chai, Linsong and Huang, Yunshi and Ni, Jinglei and Zuo, Shuang and Huang, Jia and Lin, Bingbing},
title = {{A meta-refined human Alzheimer's disease-associated gene subset shows partial mouse-model pathway correspondence and limited cross-cohort machine-learning transportability}},
journal = {Alzheimer's \& dementia : the journal of the Alzheimer's Association},
year = {2026},
month = sep,
volume = {22},
number = {9},
pages = {e71804},
publisher = {Wiley},
issn = {1552-5260},
doi = {10.1002/alz.71804},
url = {https://doi.org/10.1002/alz.71804},
pmid = {42706501},
pmcid = {PMC13550512}
}

RIS

TY - JOUR
AU - Chai, Linsong
AU - Huang, Yunshi
AU - Ni, Jinglei
AU - Zuo, Shuang
AU - Huang, Jia
AU - Lin, Bingbing
TI - A meta-refined human Alzheimer's disease-associated gene subset shows partial mouse-model pathway correspondence and limited cross-cohort machine-learning transportability
T2 - Alzheimer's & dementia : the journal of the Alzheimer's Association
J2 - Alzheimers Dement
PY - 2026
DA - 2026/09/01
VL - 22
IS - 9
SP - e71804
SN - 1552-5260
PB - Wiley
DO - 10.1002/alz.71804
UR - https://doi.org/10.1002/alz.71804
LA - en
ER -

CSL-JSON

{
"id": "10.1002/alz.71804",
"type": "article-journal",
"title": "A meta-refined human Alzheimer's disease-associated gene subset shows partial mouse-model pathway correspondence and limited cross-cohort machine-learning transportability",
"container-title": "Alzheimer's & dementia : the journal of the Alzheimer's Association",
"author": [
{
"family": "Chai",
"given": "Linsong"
},
{
"family": "Huang",
"given": "Yunshi"
},
{
"family": "Ni",
"given": "Jinglei"
},
{
"family": "Zuo",
"given": "Shuang"
},
{
"family": "Huang",
"given": "Jia"
},
{
"family": "Lin",
"given": "Bingbing"
}
],
"container-title-short": "Alzheimers Dement",
"volume": "22",
"issue": "9",
"page": "e71804",
"DOI": "10.1002/alz.71804",
"PMID": "42706501",
"PMCID": "PMC13550512",
"ISSN": "1552-5260",
"publisher": "Wiley",
"URL": "https://doi.org/10.1002/alz.71804",
"language": "en",
"issued": {
"date-parts": [
[
2026,
9,
1
]
]
}
}

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.34133/csbj.0134 [code]
Integrated Multi-Tissue Transcriptomics Reveals Antagonistic Pleiotropy in Aging and Alzheimer's Disease.
Journal: Computational and structural biotechnology journal
In common: Alzheimer's / dementia, genetics / omics, cellular / molecular, 10 references
[2] doi:10.1038/s41586-026-10793-0
Cell-type signatures of Alzheimer's disease shared across population groups.
Journal: Nature
In common: Alzheimer's / dementia, genetics / omics, cellular / molecular, 8 references
[3] doi:10.1093/braincomms/fcag326 [code]
Brain multiomic profiling identifies tau-related transcriptomic dysregulation in Alzheimer's disease.
Journal: Brain communications
In common: Alzheimer's / dementia, genetics / omics, cellular / molecular, 7 references
[4] doi:10.3390/biomedicines14050998 [code]
Integrative Multi-Omics and Machine Learning Analysis Identifies Therapeutic Targets and Drug Repurposing Candidates for Alzheimer's Disease.
Journal: Biomedicines
In common: Alzheimer's / dementia, genetics / omics, cellular / molecular, 8 references
[5] doi:10.1038/s41467-026-73007-1 [code]
Single-nucleus epigenomic dysregulation unmasks genetic risk-associated neurodegenerative glia states.
Journal: Nature communications
In common: Alzheimer's / dementia, genetics / omics, cellular / molecular, 7 references
[6] doi:10.34133/csbj.0108 [code]
Latent Factor Modeling Reveals Unexpected Spatial Heterogeneity in Human Alzheimer's Disease Brain Transcriptomes.
Journal: Computational and structural biotechnology journal
In common: Alzheimer's / dementia, genetics / omics, cellular / molecular, 7 references
[7] doi:10.1126/sciadv.aed6825
SORLA up-regulation suppresses pathological effects in aged tauopathy mouse brain.
Journal: Science advances
In common: Alzheimer's / dementia, genetics / omics, mouse, 1 other category, 6 references
[8] doi:10.1038/s43587-026-01204-0
Fibronectin mediates APOE4-driven blood-brain barrier dysfunction in Alzheimer's disease.
Journal: Nature aging
In common: Alzheimer's / dementia, genetics / omics, mouse, 1 other category, 5 references
[9] doi:10.1128/mbio.01294-26
Single-cell analysis of Powassan virus-infected brains reveals age-dependent neuroinflammatory crosstalk and progressive Alzheimer's-like APP/Aβ accumulation.
Journal: mBio
In common: Alzheimer's / dementia, genetics / omics, mouse, 1 other category, 6 references
[10] doi:10.1007/s12031-026-02598-7
A Lipoylation-PDH-TCA Transcriptional Deficit in the Alzheimer's Disease Cortex - Donor-level Multi-cohort Evidence with Neuronal-composition, Disease-specificity and Matched-null Controls.
Journal: Journal of molecular neuroscience : MN
In common: Alzheimer's / dementia, genetics / omics, 7 references

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.