Home › Research › Digital health tools
Multi-omics analysis reveals the key factors involved in the severity of the Alzheimer's disease
Meng L, Jin H, Yulug B, Altay O, Li X, Hanoglu L, Cankaya S, Coskun E et al.. Alzheimer's research & therapy, 2024-10-02
Topic: Amyloid, tau and blood-test diagnosis
Alzheimer's disease (AD) is a debilitating neurodegenerative disorder with a global impact, yet its pathogenesis remains poorly understood. While age, metabolic abnormalities, and accumulation of neurotoxic substances are potential risk factors for AD, their effects are confounded by other factors. To address this challenge, we first utilized multi-omics data from 87 well phenotyped AD patients and generated plasma proteomics and metabolomics data, as well as gut and saliva metagenomics data to investigate the molecular-level alterations accounting the host-microbiome interactions. Second, we analyzed individual omics data and identified the key parameters involved in the severity of the dementia in AD patients. Next, we employed Artificial Intelligence (AI) based models to predict AD severity based on the significantly altered features identified in each omics analysis. Based on our integrative analysis, we found the clinical relevance of plasma proteins, including SKAP1 and NEFL, plasma metabolites including homovanillate and glutamate, and Paraprevotella clara in gut microbiome in predicting the AD severity. Finally, we validated the predictive power of our AI based models by generating additional multi-omics data from the same group of AD patients by following up for 3 months. Hence, we observed that these results may have important implications for the development of potential diagnostic and therapeutic approaches for AD patients.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Meng, L., Jin, H., Yulug, B., Altay, O., Li, X., Hanoglu, L., et al. (2024). Multi-omics analysis reveals the key factors involved in the severity of the Alzheimer's disease. Alzheimer's research & therapy. https://doi.org/10.1186/s13195-024-01578-6
Vancouver
Meng L, Jin H, Yulug B, Altay O, Li X, Hanoglu L, et al. Multi-omics analysis reveals the key factors involved in the severity of the Alzheimer's disease. Alzheimer's research & therapy. 2024. doi:10.1186/s13195-024-01578-6. PMID: 39358810.
BibTeX
@article{meng2024-39358810,
author = {Meng, L. and Jin, H. and Yulug, B. and Altay, O. and Li, X. and Hanoglu, L. and Cankaya, S. and Coskun, E. and others},
title = {{Multi-omics analysis reveals the key factors involved in the severity of the Alzheimer's disease}},
journal = {Alzheimer's research \& therapy},
year = {2024},
doi = {10.1186/s13195-024-01578-6},
pmid = {39358810},
url = {https://doi.org/10.1186/s13195-024-01578-6}
}
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
Key findings
- Next, we employed Artificial Intelligence (AI) based models to predict AD severity based on the significantly altered features identified in each omics analysis.
- Based on our integrative analysis, we found the clinical relevance of plasma proteins, including SKAP1 and NEFL, plasma metabolites including homovanillate and glutamate, and Paraprevotella clara in gut microbiome in predicting the AD severity.
- Hence, we observed that these results may have important implications for the development of potential diagnostic and therapeutic approaches for AD patients.
Why it matters
Using multi-omics data from 87 patients, this study identified plasma proteins, metabolites, and a gut microbe linked to Alzheimer's severity and built AI models to predict it. It concerns prediction and possible drug targets, not a proven treatment or cure.
New to this subject? Start with our plain-English guide: Digital health →
Study details
- Evidence strengthLow
How this study scored 47/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Alzheimer's research & therapy) |
| Journal's citation record | 1 / 4 | Alzheimer s Research & Therapy: journal h-index 146 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2024 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 4 / 7 | Cited 47 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 11.8 citations a year over 4 year(s) since 2024 |
| Impact for its field and year | 4 / 6 | Cited 12.8× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 2 other studies in this library |
| Still being cited | 2 / 4 | Cited 47 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Adil Mardinoğlu: h-index 66 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | King's College London: institution h-index 1,348 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 9 institution(s) in 3 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 39358810) |
| Free to read | 2 / 2 | Free to read |
| Total | 47 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1186/s13195-024-01578-6
- PubMed: 39358810
- Original source →
- Free full text: Alzheimer s Research & Therapy →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Studies this one cites
Referenced by this study and also in the alzhub library, so you can read them here.
Later studies that cite this one
2 studies in the alzhub library list this one in their references.
Related studies in Digital health tools
Also in Digital health tools
178 studies in the library are filed under Digital health tools with no topic tag they share with another; these are this study's neighbours in a fixed tour of them. The Digital health tools hub.