Topic: Genetics and APOE
Alzheimer disease (AD) is a complex and progressive neurodegenerative disorder that accounts for the majority of individuals with dementia. Here, we aim to identify causal plasma proteins for AD, shedding light on the etiology of AD. We utilized the latest large-scale plasma proteomic data from the UK Biobank Pharma Proteomics Project (UKB-PPP) and AD genome-wide association study (GWAS) summary data from the International Genomics of Alzheimer's Project (IGAP). Via a robust univariate instrumental variable (IV) regression method, we identified causal proteins through cis-protein quantitative trait loci (pQTLs) and (both cis- and trans-)pQTLs. To further reduce potential false positives due to high linkage disequilibrium (LD) of some pQTLs and high correlations among some proteins, we developed a robust multivariate IV regression method, called two-stage constrained maximum likelihood (MV-2ScML), to distinguish direct and confounding/mediating effects of proteins; some key features of the method include its robustness to invalid IVs and applicability to GWAS summary data. Our work highlights some differences between using cis-pQTLs and trans-pQTLs and critical values of multivariate analysis for fine-mapping causal proteins, providing insights into plasma protein pathways to AD.
Key findings
- Here, we aim to identify causal plasma proteins for AD, shedding light on the etiology of AD.
- We utilized the latest large-scale plasma proteomic data from the UK Biobank Pharma Proteomics Project (UKB-PPP) and AD genome-wide association study (GWAS) summary data from the International Genomics of Alzheimer's Project (IGAP).
- Via a robust univariate instrumental variable (IV) regression method, we identified causal proteins through cis-protein quantitative trait loci (pQTLs) and (both cis- and trans-)pQTLs.
- To further reduce potential false positives due to high linkage disequilibrium (LD) of some pQTLs and high correlations among some proteins, we developed a robust multivariate IV regression method, called two-stage constrained maximum likelihood (MV-2ScML), to distinguish direct and confounding/mediating effects of proteins; some key features of the method include its robustness to invalid IVs and applicability to GWAS summary data.
- Our work highlights some differences between using cis-pQTLs and trans-pQTLs and critical values of multivariate analysis for fine-mapping causal proteins, providing insights into plasma protein pathways to AD.
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Study details
- Evidence strengthLow
How this study scored 43/100
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. 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 24 of the 56 points we could judge it on, which is 43 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (American journal of human genetics) |
| 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 | 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 | 2025 — 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 | — / 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 39793580) |
| Free to read | — / 2 | Access not recorded — left out of this score |
| Points | 24 / 56 | Scored on 10 of 20 parts. We have no data for the rest, so they are left out: 24 of the 56 points we could judge it on is 43 out of 100. |
| Total | 43 / 100 | — |
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APA 7th
Fang, L., Xue, H., Lin, Z., & Pan, W. (2025). Multivariate proteome-wide association study to identify causal proteins for Alzheimer disease. American journal of human genetics. https://doi.org/10.1016/j.ajhg.2024.12.010
Vancouver
Fang L, Xue H, Lin Z, Pan W. Multivariate proteome-wide association study to identify causal proteins for Alzheimer disease. American journal of human genetics. 2025. doi:10.1016/j.ajhg.2024.12.010. PMID: 39793580.
BibTeX
@article{fang2025-39793580,
author = {Fang, Lei and Xue, Haoran and Lin, Zhaotong and Pan, Wei},
title = {{Multivariate proteome-wide association study to identify causal proteins for Alzheimer disease}},
journal = {American journal of human genetics},
year = {2025},
doi = {10.1016/j.ajhg.2024.12.010},
pmid = {39793580},
url = {https://doi.org/10.1016/j.ajhg.2024.12.010}
}