Home › Research › Disparities
Improving genetic risk modeling of dementia from real-world data in underrepresented populations
Mingzhou Fu, Leopoldo Valiente-Banuet, Satpal S Wadhwa, Bogdan Pasaniuc, Keith Vossel, Timothy S Chang. Communications biology, 2024-08-25
Topic: Genetics and APOE
Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited. We employ an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compare this model with APOE and polygenic risk score models across genetic ancestry groups (Hispanic Latino American sample: 610 patients with 126 cases; African American sample: 440 patients with 84 cases; East Asian American sample: 673 patients with 75 cases), using electronic health records from UCLA Health for discovery and the All of Us cohort for validation. Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 31-84% (Wilcoxon signed-rank test p-value <0.05) and the area-under-the-receiver-operating characteristic by 11-17% (DeLong test p-value <0.05) compared to the APOE and the polygenic risk score models. We identify shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge. Our study highlights the benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Fu, M., Valiente-Banuet, L., Wadhwa, S. S., Pasaniuc, B., Vossel, K., & Chang, T. S. (2024). Improving genetic risk modeling of dementia from real-world data in underrepresented populations. Communications biology. https://doi.org/10.1038/s42003-024-06742-0
Vancouver
Fu M, Valiente-Banuet L, Wadhwa SS, Pasaniuc B, Vossel K, Chang TS. Improving genetic risk modeling of dementia from real-world data in underrepresented populations. Communications biology. 2024. doi:10.1038/s42003-024-06742-0. PMID: 39183196.
BibTeX
@article{fu2024-39183196,
author = {Fu, Mingzhou and Valiente-Banuet, Leopoldo and Wadhwa, Satpal S and Pasaniuc, Bogdan and Vossel, Keith and Chang, Timothy S},
title = {{Improving genetic risk modeling of dementia from real-world data in underrepresented populations}},
journal = {Communications biology},
year = {2024},
doi = {10.1038/s42003-024-06742-0},
pmid = {39183196},
url = {https://doi.org/10.1038/s42003-024-06742-0}
}
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
- Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited.
- Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 31-84% (Wilcoxon signed-rank test p-value <0.05) and the area-under-the-receiver-operating characteristic by 11-17% (DeLong test p-value <0.05) compared to the APOE and the polygenic risk score models.
- Our findings hold potential for refining precision medicine strategies in dementia diagnosis.
New to this subject? Start with our plain-English guide: Disparities →
Study details
- Participants610
- Evidence strengthModerate
How this study scored 55/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record, multi-centre collaboration and free to read, so those were left out: it earned 31 of the 56 points we could judge it on, which is 55 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Communications biology) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 3 / 5 | Rated “moderate” 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 | 2 / 4 | 610 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 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 39183196) |
| Free to read | — / 2 | Access not recorded — left out of this score |
| Points | 31 / 56 | Scored on 10 of 20 parts. We have no data for the rest, so they are left out: 31 of the 56 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
Free copy unknown: no free-copy check has an answer for this record yet. That does not mean it is paywalled.
Related studies in Disparities
Also tagged “genetics”
346 studies in the library carry the topic tag “genetics”; these are this study's neighbours in a fixed, alphabetical-by-hash tour of them, not the closest in content. All 346 tagged studies.