Genetic control of the human brain proteome
Open accessAbstract
Alteration of protein abundance and conformation are widely believed to be the hallmark of neurodegenerative diseases. Yet relatively little is known about the genetic variation that controls protein abundance in the healthy human brain. The genetic control of protein abundance is generally thought to parallel that of RNA expression, but there is little direct evidence to support this view. Here, we performed a large-scale protein quantitative trait locus (pQTL) analysis using single nucleotide variants (SNVs) from whole-genome sequencing and tandem mass spectrometry-based proteomic quantification of 12,691 unique proteins (7,901 after quality control) from the dorsolateral prefrontal cortex (dPFC) in 144 cognitively normal individuals. We identified 28,211 pQTLs that were significantly associated with the abundance of 864 proteins. These pQTLs were compared to dPFC expression quantitative trait loci (eQTL) in cognitive normal individuals (n=169; 81 had protein data) and a meta-analysis of dPFC eQTLs (n=1,433). We found that strong pQTLs are generally only weak eQTLs, and that the majority of strong eQTLs are not detectable pQTLs. These results suggest that the genetic control of mRNA and protein abundance may be substantially distinct and suggests inference concerning protein abundance made from mRNA in human brain should be treated with caution.
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Most pQTL studies have been conducted using serum or plasma measurements from blood samples, and only a limited number of studies has involved examination of liver and brain tissue-specific pQTLs.
“Second, most pQTL studies have been conducted using serum or plasma measurements from blood samples4,6,8,51 and only a limited number of studies has involved the examination of liver and brain tissue–specific pQTLs88,89.”
From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [89]
Individuals carrying the APOE ε4 allele display distinct proteo-metabolomic signatures in lipid transport and immune pathways.
“For example, individuals carrying the APOE ε4 allele display distinct proteo-metabolomic signatures in lipid transport and immune pathways206,207.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [207]
The Abstract (p. 1) describes a brain protein-QTL analysis, and the Statistical Analyses (p. 16) describe testing genetic variants against protein abundance. Searches for APOE ε4, lipid transport, immune pathways, and metabolomic signatures found no passage in our copy reporting the claimed carrier-specific signatures. (LLM, conf=0.76)
Experimental — accuracy not yet measuredCSF Siglec-9, plasma sICAM-1, and brain PPAC have been replicated in other studies using a different proteomic approach, indicating these findings may not be driven by platform.
“CSF Siglec-9, plasma sICAM-1, and brain PPAC have been replicated in other studies16,29,31,32 using a different proteomic approach, which indicates that these findings may not be driven by platform.”
From Genomic atlas of the proteome from brain, CSF and plasma prioritizes proteins implicated in neurological disorders (2021) · cites this paper as [16]
No statistical methods were used to predetermine sample sizes within each tissue type, but the sample sizes are much larger or comparable to those in previous publications.
“No statistical methods were used to predetermine sample sizes within each tissue type, but our sample sizes are much larger or comparable to those in previous publications13,14,16.”
From Genomic atlas of the proteome from brain, CSF and plasma prioritizes proteins implicated in neurological disorders (2021) · cites this paper as [16]
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Yang, C., Farias, F. H. G., Ibanez, L., Suhy, A., Sadler, B., Fernandez, M. V., Wang, F., Bradley, J. L., Eiffert, B., Bahena, J. A., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00886-6 · Cited by 290 · see citing works
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Genetic determinants of plasma protein levels in the Estonian population
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- Authors
- Robins, C., Wingo, A. P., Fan, W., Duong, D. M., Meigs, J., Gerasimov, E. S., Dammer, E. B., Cutler, D. J., Jager, P. L. D., Bennett, D. A., Lah, J. J., Levey, A. I., Seyfried, N. T., & Wingo, T. S.
- Affiliations
- Emory University (US)
- Columbia University Irving Medical Center (US)
- Rush University Medical Center (US)
- Corresponding author
- Seyfried, Nicholas T.
- Wingo, Thomas S.
- ORCID
- Venue
- The American Journal of Human Genetics
- Publisher
- openRxiv
- Published
- 2019-10-24
- Volume
- 108
- Issue
- 3
- Pages
- 400-410
- ISSN
- 0002-9297 (ISSN-L)
- PMC
- PMC8008492
- OpenAlex
- W3128936277
- Cited by
- 104
- References
- 89
- Citations by year
- 2026: 14 · 2025: 19 · 2024: 29 · 2023: 14 · 2022: 18 · 2021: 7 · 2020: 3
- FWCI
- 10.03
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The American Journal of Human Genetics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- U.S. Department of Veterans Affairs (BX003853, I01BX003853)
- Michael J. Fox Foundation for Parkinson's Research
- Illinois Department of Public Health (R01AG017917, P30AG10161, R01AG15819, R01AG17917, R01AG30146, R01AG015819)
- Arizona Department of Health Services
- Translational Genomics Research Institute
- Arizona Biomedical Research Commission
- National Institutes of Health (T32 NS00748018, NS007480, AG057195, AG025688)
- National Institute on Aging (R01AG017917, P30-AG 10161, R01AG056533, U01 AG32984, R01AG030146, AG057195, R01 AG30146, R01‐AG17917, R01 AG15819, R01-AG36836, AG 025688, U01AG057195, U01‐AG61356, R01AG036836, U01AG046152, R01AG036042, R01AG015819, R56AG060757, P30AG010161, U01AG032984, U01AG061357, U01AG061356, P30AG019610, R56AG062256, RF1AG051633, AG056533, R56AG062633, P50AG025688, U01‐AG46152, AG051633, P30AG072980, P30AG066511)
- National Institute of Mental Health (U01MH115484)
- National Institute of Neurological Disorders and Stroke (T32NS007480, U24NS072026)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Keywords
- protein quantitative trait loci, brain proteome, dorsolateral prefrontal cortex, postmortem brain, expression quantitative trait loci, non-synonymous variants, protein abundance, evolutionary constraints, protein-protein interaction
- MeSH terms
- Autopsy, Brain, Female, Gene Expression Regulation, Genotype, Humans, Male, RNA, Messenger, Genetic Variation, Proteome, Quantitative Trait Loci, Proteomics, Genome-Wide Association Study, Transcriptome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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