Multi-ancestry eQTL meta-analysis of human brain identifies candidate causal variants for brain-related traits
Zeng B, Bendl J, Kosoy R, Fullard JF, Hoffman GE, Roussos P.. Nature genetics, 2022-01-20
Topic: Brain proteins, microglia and lab models
While large-scale, genome-wide association studies (GWAS) have identified hundreds of loci associated with brain-related traits, identification of the variants, genes and molecular mechanisms underlying these traits remains challenging. Integration of GWAS with expression quantitative trait loci (eQTLs) and identification of shared genetic architecture have been widely adopted to nominate genes and candidate causal variants. However, this approach is limited by sample size, statistical power and linkage disequilibrium. We developed the multivariate multiple QTL approach and performed a large-scale, multi-ancestry eQTL meta-analysis to increase power and fine-mapping resolution. Analysis of 3,983 RNA-sequenced samples from 2,119 donors, including 474 non-European individuals, yielded an effective sample size of 3,154. Joint statistical fine-mapping of eQTL and GWAS identified 329 variant-trait pairs for 24 brain-related traits driven by 204 unique candidate causal variants for 189 unique genes. This integrative analysis identifies candidate causal variants and elucidates potential regulatory mechanisms for genes underlying schizophrenia, bipolar disorder and Alzheimer's disease.
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APA 7th
Zeng, B., Bendl, J., Kosoy, R., Fullard, J. F., Hoffman, G. E., & Roussos, P. (2022). Multi-ancestry eQTL meta-analysis of human brain identifies candidate causal variants for brain-related traits. Nature genetics. https://doi.org/10.1038/s41588-021-00987-9
Vancouver
Zeng B, Bendl J, Kosoy R, Fullard JF, Hoffman GE, Roussos P. Multi-ancestry eQTL meta-analysis of human brain identifies candidate causal variants for brain-related traits. Nature genetics. 2022. doi:10.1038/s41588-021-00987-9. PMID: 35058635.
BibTeX
@article{zeng2022-35058635,
author = {Zeng, B. and Bendl, J. and Kosoy, R. and Fullard, J. F. and Hoffman, G. E. and Roussos, P.},
title = {{Multi-ancestry eQTL meta-analysis of human brain identifies candidate causal variants for brain-related traits}},
journal = {Nature genetics},
year = {2022},
doi = {10.1038/s41588-021-00987-9},
pmid = {35058635},
url = {https://doi.org/10.1038/s41588-021-00987-9}
}
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Key findings
- While large-scale, genome-wide association studies (GWAS) have identified hundreds of loci associated with brain-related traits, identification of the variants, genes and molecular mechanisms underlying these traits remains challenging.
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Study details
- Study designmeta-analysis
- Evidence strengthHigh
How this study scored 71/100
Published in a leading specialty journal, and it is a meta-analysis pooling many studies. Scored zero for sample size, effect reported and studied in people 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 and multi-centre collaboration, so those were left out: it earned 41 of the 58 points we could judge it on, which is 71 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 9 / 10 | Tier 2 — leading specialty journal (Nature genetics) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 12 / 12 | A meta-analysis pooling many studies |
| 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 | 3 / 5 | 2022 — within 6 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 | A review of other studies — randomisation is not credited here |
| 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 35058635) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 41 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 41 of the 58 points we could judge it on is 71 out of 100. |
| Total | 71 / 100 | — |
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