Evidence map›Paper›PMID 40869991›Full record

ReviewGenes2025

MicroRNAs as Potential Biomarkers for Alzheimer's Disease in Women.

Shiwei Huang, Lily Zhong, Lilly Zheng, Jian Shi

Abstract readReview
In one paragraph

Review in Genes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Shiwei HuangDepartment of Neurosurgery, University of Minnesota, Minneapolis, MN 55455, USA.
Lily ZhongDepartment of Neurology, Department of Veterans Affairs Health Care System, San Francisco and University of California, San Francisco, CA 94121, USA.
Lilly ZhengDepartment of Neurology, Department of Veterans Affairs Health Care System, San Francisco and University of California, San Francisco, CA 94121, USA.
Jian ShiDepartment of Neurology, Department of Veterans Affairs Health Care System, San Francisco and University of California, San Francisco, CA 94121, USA.ORCID 0000-0002-7961-8545

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD) affects approximately 50 million people worldwide, with women comprising two-thirds of those affected. Despite this disproportionate impact, the sex-specific pathological mechanisms underlying AD in women remain poorly understood, and female-specific biomarkers have been significantly understudied. This critical knowledge gap requires focused research to improve diagnostic and therapeutic approaches for women with AD. In this review, we systematically examine the pathological mechanisms underlying AD in women, including sex-related differences in inflammation, autophagy, and metabolic dysfunction. We further explore microRNA (miRNA) expression patterns and evaluate miRNA candidates as potential biomarkers for AD in women based on current literature. Through this analysis, we identified approximately 20 miRNA candidates derived from diverse human samples, including brain tissue, blood, and cerebrospinal fluid, in multiple independent studies. These candidates demonstrate the potential for developing accessible, non-invasive biomarkers, particularly those identified in blood and cerebrospinal fluid. However, the limited overlap between studies highlights that female-specific miRNA biomarker research for AD remains in its early discovery phase, emphasizing the urgent need for large-scale validation studies and standardized methodological approaches to advance this promising field for clinical application.

Indexed as

Alzheimer DiseaseMicroRNAsBiomarkersFemaleHumansBiomarkersMicroRNAsAlzheimer’s diseasebiomarkersfemale specific mechanisminflammationmiRNAssex differences

Identifiers

PMID40869991
PMCPMC12386123

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.