Brain expression quantitative trait locus and network analyses reveal downstream effects and putative drivers for brain-related diseases
Niek de Klein, Ellen A. Tsai, Martijn Vochteloo, Denis A. Baird, Yunfeng Huang, Chia‐Yen Chen, Sipko van Dam, Roy Oelen et al.. Nature Genetics, 2023-02-23
Topic: Genetics and APOE
Gaining insight into the downstream consequences of non-coding variants is an essential step towards the identification of therapeutic targets from genome-wide association study (GWAS) findings. Here we have harmonized and integrated 8,727 RNA-seq samples with accompanying genotype data from multiple brain-regions from 14 datasets. This sample size enabled us to perform both cis - and trans -expression quantitative locus (eQTL) mapping. Upon comparing the brain cortex cis -eQTLs (for 12,307 unique genes at FDR<0.05) with a large blood cis- eQTL analysis (n=31,684 samples), we observed that brain eQTLs are more tissue specific than previously assumed. We inferred the brain cell type for 1,515 cis -eQTLs by using cell type proportion information. We conducted Mendelian Randomization on 31 brain-related traits using cis -eQTLs as instruments and found 159 significant findings that also passed colocalization. Furthermore, two multiple sclerosis (MS) findings had cell type specific signals, a neuron-specific cis- eQTL for CYP24A1 and a macrophage specific cis -eQTL for CLECL1 . To further interpret GWAS hits, we performed trans -eQTL analysis. We identified 2,589 trans -eQTLs (at FDR<0.05) for 373 unique SNPs, affecting 1,263 unique genes, and 21 replicated significantly using single-nucleus RNA-seq data from excitatory neurons. We also generated a brain-specific gene-coregulation network that we used to predict which genes have brain-specific functions, and to perform a novel network analysis of Alzheimer’s disease (AD), amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS) and Parkinson’s disease (PD) GWAS data. This resulted in the identification of distinct sets of genes that show significantly enriched co-regulation with genes inside the associated GWAS loci, and which might reflect drivers of these diseases.
Key findings
- Upon comparing the brain cortex cis -eQTLs (for 12,307 unique genes at FDR<0.05) with a large blood cis- eQTL analysis (n=31,684 samples), we observed that brain eQTLs are more tissue specific than previously assumed.
- We conducted Mendelian Randomization on 31 brain-related traits using cis -eQTLs as instruments and found 159 significant findings that also passed colocalization.
- We identified 2,589 trans -eQTLs (at FDR<0.05) for 373 unique SNPs, affecting 1,263 unique genes, and 21 replicated significantly using single-nucleus RNA-seq data from excitatory neurons.
- This resulted in the identification of distinct sets of genes that show significantly enriched co-regulation with genes inside the associated GWAS loci, and which might reflect drivers of these diseases.
New to this subject? Start with our plain-English guide: Genetics →
Study details
- Participants31,684
- Evidence strengthLow
How this study scored 59/100
Published in a leading specialty 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 and multi-centre collaboration, so those were left out: it earned 34 of the 58 points we could judge it on, which is 59 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 | 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 | 3 / 5 | 2023 — within 6 year(s) of the newest study here |
| Sample size | 4 / 4 | 31,684 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 36823318) |
| Free to read | 2 / 2 | Free to read |
| Points | 34 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 34 of the 58 points we could judge it on is 59 out of 100. |
| Total | 59 / 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.
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's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
de Klein, N., Tsai, E. A., Vochteloo, M., Baird, D. A., Huang, Y., Chen, C., et al. (2023). Brain expression quantitative trait locus and network analyses reveal downstream effects and putative drivers for brain-related diseases. Nature Genetics. https://doi.org/10.1038/s41588-023-01300-6
Vancouver
de Klein N, Tsai EA, Vochteloo M, Baird DA, Huang Y, Chen C, et al. Brain expression quantitative trait locus and network analyses reveal downstream effects and putative drivers for brain-related diseases. Nature Genetics. 2023. doi:10.1038/s41588-023-01300-6. PMID: 36823318.
BibTeX
@article{deklein2023-36823318,
author = {de Klein, Niek and Tsai, Ellen A. and Vochteloo, Martijn and Baird, Denis A. and Huang, Yunfeng and Chen, Chia‐Yen and van Dam, Sipko and Oelen, Roy and others},
title = {{Brain expression quantitative trait locus and network analyses reveal downstream effects and putative drivers for brain-related diseases}},
journal = {Nature Genetics},
year = {2023},
doi = {10.1038/s41588-023-01300-6},
pmid = {36823318},
url = {https://doi.org/10.1038/s41588-023-01300-6}
}