Topic: Brain proteins, microglia and lab models
Transcriptome-wide association studies (TWASs) have been widely used to integrate gene expression and genetic data for studying complex traits. Due to the computational burden, existing TWAS methods do not assess distant trans-expression quantitative trait loci (eQTL) that are known to explain important expression variation for most genes. We propose a Bayesian genome-wide TWAS (BGW-TWAS) method that leverages both cis- and trans-eQTL information for a TWAS. Our BGW-TWAS method is based on Bayesian variable selection regression, which not only accounts for cis- and trans-eQTL of the target gene but also enables efficient computation by using summary statistics from standard eQTL analyses. Our simulation studies illustrated that BGW-TWASs achieved higher power compared to existing TWAS methods that do not assess trans-eQTL information. We further applied BWG-TWAS to individual-level GWAS data (N = ∼3.3K), which identified significant associations between the genetically regulated gene expression (GReX) of ZC3H12B and Alzheimer dementia (AD) (p value = 5.42 × 10 -13 ), neurofibrillary tangle density (p value = 1.89 × 10 -6 ), and global measure of AD pathology (p value = 9.59 × 10 -7 ). These associations for ZC3H12B were completely driven by trans-eQTL. Additionally, the GReX of KCTD12 was found to be significantly associated with β-amyloid (p value = 3.44 × 10 -8 ) which was driven by both cis- and trans-eQTL. Four of the top driven trans-eQTL of ZC3H12B are located within APOC1, a known major risk gene of AD and blood lipids. Additionally, by applying BGW-TWAS with summary-level GWAS data of AD (N = ∼54K), we identified 13 significant genes including known GWAS risk genes HLA-DRB1 and APOC1, as well as ZC3H12B.
Key findings
- Our simulation studies illustrated that BGW-TWASs achieved higher power compared to existing TWAS methods that do not assess trans-eQTL information.
- We further applied BWG-TWAS to individual-level GWAS data (N = ∼3.3K), which identified significant associations between the genetically regulated gene expression (GReX) of ZC3H12B and Alzheimer dementia (AD) (p value = 5.42 × 10 -13 ), neurofibrillary tangle density (p value = 1.89 × 10 -6 ), and global measure of AD pathology (p value = 9.59 × 10 -7 ).
- Additionally, the GReX of KCTD12 was found to be significantly associated with β-amyloid (p value = 3.44 × 10 -8 ) which was driven by both cis- and trans-eQTL.
- Additionally, by applying BGW-TWAS with summary-level GWAS data of AD (N = ∼54K), we identified 13 significant genes including known GWAS risk genes HLA-DRB1 and APOC1, as well as ZC3H12B.
Why it matters
This paper describes a new statistical method for finding genes linked to traits and applies it to identify associations between expression of ZC3H12B and KCTD12 and Alzheimer-related measures. It is a methods and genetics study and does not test any treatment or prevention.
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Study details
- Evidence strengthLow
How this study scored 44/100
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 (American journal of human genetics) |
| Journal's citation record | 3 / 4 | The American Journal of Human Genetics: journal h-index 385 (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 | 2 / 5 | 2020 — within 10 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 90 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 11.2 citations a year over 8 year(s) since 2020 |
| Impact for its field and year | 3 / 6 | Cited 5.4× 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 49 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Jingjing Yang: h-index 32 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | Columbia University: institution h-index 1,824 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 5 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 32961112) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 44 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
Full text: free to read — PubMed Central lists this copy as free to read: the link above (checked 10 Oct 2026).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
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 names 7 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Luningham, J. M., Chen, J., Tang, S., De Jager, P. L., Bennett, D. A., Buchman, A. S., et al. (2020). Bayesian Genome-wide TWAS Method to Leverage both cis- and trans-eQTL Information through Summary Statistics. American journal of human genetics. https://doi.org/10.1016/j.ajhg.2020.08.022
Vancouver
Luningham JM, Chen J, Tang S, De Jager PL, Bennett DA, Buchman AS, et al. Bayesian Genome-wide TWAS Method to Leverage both cis- and trans-eQTL Information through Summary Statistics. American journal of human genetics. 2020. doi:10.1016/j.ajhg.2020.08.022. PMID: 32961112.
BibTeX
@article{luningham2020-32961112,
author = {Luningham, J. M. and Chen, J. and Tang, S. and De Jager, P. L. and Bennett, D. A. and Buchman, A. S. and Yang, J.},
title = {{Bayesian Genome-wide TWAS Method to Leverage both cis- and trans-eQTL Information through Summary Statistics}},
journal = {American journal of human genetics},
year = {2020},
doi = {10.1016/j.ajhg.2020.08.022},
pmid = {32961112},
url = {https://doi.org/10.1016/j.ajhg.2020.08.022}
}
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