Decoupling of mRNA and Protein Expression in Aging Brains Reveals the Age-Dependent Adaptation of Specific Gene Subsets
Open accessPublished version of a preprint
Abstract
During aging, changes in gene expression are associated with a decline in physical and cognitive abilities. Here, we investigate the connection between changes in mRNA and protein expression in the brain by comparing the transcriptome and proteome of the mouse cortex during aging. Our transcriptomic analysis revealed that aging mainly triggers gene activation in the cortex. We showed that an increase in mRNA expression correlates with protein expression, specifically in the anterior cingulate cortex, where we also observed an increase in cortical thickness during aging. Genes exhibiting an aging-dependent increase of mRNA and protein levels are involved in sensory perception and immune functions. Our proteomic analysis also identified changes in protein abundance in the aging cortex and highlighted a subset of proteins that were differentially enriched but exhibited stable mRNA levels during aging, implying the contribution of aging-related post- transcriptional and post-translational mechanisms. These specific genes were associated with general biological processes such as translation, ribosome assembly and protein degradation, and also important brain functions related to neuroplasticity. By decoupling mRNA and protein expression, we have thus characterized distinct subsets of genes that differentially adjust to cellular aging in the cerebral cortex.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Global quantification of mammalian gene expression control
Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W., & Selbach, M. (2011) · Nature · doi:10.1038/nature10098 · Cited by 6,566 · cited 1× · see citing works
“Aging studies typically used 3-month and 18-month-old mice to respectively represent these two populations, however important morphological modifications occur up to 4 months of age such as the myelination (Hammelrath et al. 2016; Semple et al. 2013).”
MethodThe translational landscape of mTOR signalling steers cancer initiation and metastasis
Hsieh, A. C., Liu, Y., Edlind, M. P., Ingolia, N. T., Janes, M. R., Sher, A., Shi, E. Y., Stumpf, C. R., Christensen, C., Bonham, M. J., et al. (2012) · Nature · doi:10.1038/nature10912 · Cited by 1,313 · see citing works
Epigenetics and aging: the targets and the marks
Fraga, M. F., & Esteller, M. (2007) · Trends in Genetics · doi:10.1016/j.tig.2007.05.008 · Cited by 690 · see citing works
Aging as an event of proteostasis collapse
Taylor, R. C., & Dillin, A. (2011) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a004440 · Cited by 538 · see citing works
Dynamic profiling of the protein life cycle in response to pathogens
Jovanovic, M., Rooney, M. S., Mertins, P., Przybylski, D., Chevrier, N., Satija, R., Rodriguez, E. H., Fields, A. P., Schwartz, S., Raychowdhury, R., et al. (2015) · Science · doi:10.1126/science.1259038 · Cited by 460 · see citing works
A Quantitative Proteome Map of the Human Body
Jiang, L., Wang, M., Lin, S., Jian, R., Li, X., Chan, J., Dong, G., Fang, H., Robinson, A. E., Aguet, F., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.036 · Cited by 458 · see citing works
The role of DNA damage and repair in aging through the prism of Koch-like criteria
Moskalev, A. A., Shaposhnikov, M. V., Plyusnina, E. N., Zhavoronkov, A., Budovsky, A., Yanai, H., & Fraifeld, V. E. (2013) · Ageing Research Reviews · doi:10.1016/j.arr.2012.02.001 · Cited by 387 · see citing works
Keller, J. (2002) · Ageing Research Reviews · doi:10.1016/s1568-1637(01)00006-x · Cited by 247 · see citing works
Molecular aging in human prefrontal cortex is selective and continuous throughout adult life
Erraji-Benchekroun, L., Underwood, M. D., Arango, V., Galfalvy, H., Pavlidis, P., Smyrniotopoulos, P., Mann, J. J., & Sibille, E. (2005) · Biological Psychiatry · doi:10.1016/j.biopsych.2004.10.034 · Cited by 236 · see citing works
The DLGAP family: neuronal expression, function and role in brain disorders
Rasmussen, A. H., Rasmussen, H. B., & Silahtaroglu, A. (2017) · Molecular Brain · doi:10.1186/s13041-017-0324-9 · Cited by 234 · see citing works
Svennerholm, L., Boström, K., & Jungbjer, B. (1997) · Acta Neuropathologica · doi:10.1007/s004010050717 · Cited by 232 · see citing works
Histone methylation makes its mark on longevity
Han, S., & Brunet, A. (2012) · Trends in Cell Biology · doi:10.1016/j.tcb.2011.11.001 · Cited by 204 · see citing works
Wei, Y.-N., Hu, H.-Y., Xie, G.-C., Fu, N., Ning, Z.-B., Zeng, R., & Khaitovich, P. (2015) · Genome Biology · doi:10.1186/s13059-015-0608-2 · Cited by 117 · see citing works
Flagged first, then by citations
- Authors
- Khatir, I., Brunet, M. A., Meller, A., Amiot, F., Patel, T., Lapointe, X., Avila Lopez, J., Guilloy, N., Castonguay, A., Husain, M. A., Germain, J. S., Boisvert, F.-M., Plourde, M., Roucou, X., & Laurent, B.
- Affiliations
- Université de Sherbrooke (CA)
- Research Center on Aging, Centre Intégré Universitaire de Santé et Services Sociaux de l’Estrie-Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC J1H 4C4, Canada
- ORCID
- Venue
- Cells
- Publisher
- MDPI AG
- Published
- 2023-02-14
- Volume
- 12
- Issue
- 4
- Pages
- 615
- ISSN
- 2073-4409 (ISSN-L)
- PMC
- PMC9954025
- OpenAlex
- W4320919322
- Cited by
- 22
- References
- 13
- Citations by year
- 2026: 9 · 2025: 5 · 2024: 5 · 2023: 3
- FWCI
- 1.49
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Cells (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- HAL (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Canadian Institutes of Health Research (PJT-166109)
- Faculty of Medicine and Health Sciences at the Université de Sherbrooke (PJT-166109)
- Fonds de Recherche du Québec-Santé (FRQS) (PJT-166109)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Keywords
- brain aging, cerebral cortex, transcriptome, proteome, anterior cingulate cortex, cortical thickness, post-transcriptional regulation, post-translational regulation, immune function genes, neuroplasticity, translation (biology), ribosome assembly, protein degradation, mice
- MeSH terms
- Aging, Animals, Brain, RNA, Messenger, Proteome, Proteomics, Mice
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
