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Leveraging artificial intelligence for analysis of the gut microbiome for dementia diagnosis: a scoping review and discussion
Laya Krishnan, Gaurie Gunasekaran, Tamanna Dhore, Alexa Lauinger, Vijaya Kolachalama, Suguna Pappu. Frontiers in Dementia, 2026-06-17
Topic: Risk, prevention and care in population studies
Background Dementia, a multifactorial disease with progressive cognitive decline, has been linked to imbalances in the gut-brain axis. Emerging artificial intelligence tools have augmented the identification of several gastrointestinal biomarkers for differential dementia detection and severity, but current literature lacks a comprehensive review. Aims This study aims to better quantify the applications of AI in the exploration of the gut microbiome for diagnosis of specific subtypes of dementia. Methods Primary articles ( n = 896) from any point in time through July 2025 were identified from PubMed, Web of Science, Scopus, and ScienceDirect. Title and abstract screenings filtered articles from 896 to 28 for critical appraisal and review for key bacteria, fungi, and metabolites. Methods adhered to the PRISMA extension for Scoping Reviews (PRISMA-ScR) guidelines. Results Several studies utilized predictive models including random forests and neural networks to demonstrate alterations in the gut microbiota of Alzheimer’s disease, an increasingly prevalent dementia subtype. These individuals have notably reduced levels of butyrate-producing bacteria, such as Butyrivibrio , Eubacterium , and Faecalibacterium , which contribute to anti-inflammation and gut-barrier maintenance. Increased levels of Odoribacter splanchnicus and Klebsiella pneumoniae, as well as bacteria from generas Bacteroides and Prevotella, which help generate short-chain fatty acids, have been implicated in neuroinflammation; Roseburia inulinivorans negatively correlates with functional ability. Interestingly, superagers also display unique microbiome profiles that seemingly have protective effects linked to superior cognitive resilience. Conclusion Distinct gut microbial compositions are associated with dementia. Furthermore, elucidating gut-brain interactions and their neurodegenerative implications can identify targets for earlier, synergistic diagnostics. Systematic review registration https://osf.io/yw2dc/overview .
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Krishnan, L., Gunasekaran, G., Dhore, T., Lauinger, A., Kolachalama, V., & Pappu, S. (2026). Leveraging artificial intelligence for analysis of the gut microbiome for dementia diagnosis: a scoping review and discussion. Frontiers in Dementia. https://doi.org/10.3389/frdem.2026.1865441
Vancouver
Krishnan L, Gunasekaran G, Dhore T, Lauinger A, Kolachalama V, Pappu S. Leveraging artificial intelligence for analysis of the gut microbiome for dementia diagnosis: a scoping review and discussion. Frontiers in Dementia. 2026. doi:10.3389/frdem.2026.1865441. PMID: 42389671.
BibTeX
@article{krishnan2026-42389671,
author = {Krishnan, Laya and Gunasekaran, Gaurie and Dhore, Tamanna and Lauinger, Alexa and Kolachalama, Vijaya and Pappu, Suguna},
title = {{Leveraging artificial intelligence for analysis of the gut microbiome for dementia diagnosis: a scoping review and discussion}},
journal = {Frontiers in Dementia},
year = {2026},
doi = {10.3389/frdem.2026.1865441},
pmid = {42389671},
url = {https://doi.org/10.3389/frdem.2026.1865441}
}
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
Key findings
- Results Several studies utilized predictive models including random forests and neural networks to demonstrate alterations in the gut microbiota of Alzheimer’s disease, an increasingly prevalent dementia subtype.
- Conclusion Distinct gut microbial compositions are associated with dementia.
Why it matters
This scoping review found that distinct gut microbial compositions are associated with dementia, with studies using models such as random forests and neural networks and noting reduced butyrate-producing bacteria in Alzheimer's disease. It is about diagnosis and association, not about treating, curing or preventing Alzheimer's disease.
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Study details
- Study designsystematic review
- Participants896
- Evidence strengthHigh
How this study scored 55/100
Published in a peer-reviewed journal, and it is a systematic review of all the studies on the question. Scored zero for effect reported because the record does not state it. We have no data on senior author's track record, so that was left out: it earned 53 of the 96 points we could judge it on, which is 55 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Frontiers in Dementia) |
| Journal's citation record | 0 / 4 | Frontiers in Dementia: journal h-index 13 (OpenAlex, 2026-10-29) |
| Study design | 12 / 12 | A systematic review of all the studies on the question |
| Strength of evidence | 5 / 5 | Rated “high” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 2 / 4 | 896 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | A review of other studies — randomisation is not credited here |
| Times cited | 1 / 7 | Cited 1 times (OpenAlex, 2026-10-10) |
| Citations per year | 0 / 5 | 0.5 citations a year over 2 year(s) since 2026 |
| Impact for its field and year | 2 / 6 | Cited 1.9× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 0 / 4 | Cited 1 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | — / 4 | OpenAlex's profile for last-listed author Suguna Pappu holds only 1 work(s), too few to judge a track record — left out of this score |
| Institution's track record | 1 / 3 | Boston University: institution h-index 1,456 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 3 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 42389671) |
| Free to read | 2 / 2 | Free to read |
| Points | 53 / 96 | Scored on 19 of 20 parts. We have no data for the rest, so they are left out: 53 of the 96 points we could judge it on is 55 out of 100. |
| Total | 55 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.3389/frdem.2026.1865441
- PubMed: 42389671
- Original source →
- Free full text: Frontiers in Dementia →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
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