Six drivers of aging identified among genes differentially expressed with age.

Autor:	Coler-Reilly A; Division of Bone and Mineral Diseases, Musculoskeletal Research Center.; Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA.; Department of Medical Scientist Training Program, Washington University School of Medicine, St. Louis, MO, USA., Pincus Z; Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA.; Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA., Scheller EL; Division of Bone and Mineral Diseases, Musculoskeletal Research Center.; Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA.; Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA.; Department of Cell Biology and Physiology; Washington University School of Medicine, St. Louis, MO, USA., Civitelli R; Division of Bone and Mineral Diseases, Musculoskeletal Research Center.; Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA.; Department of Cell Biology and Physiology; Washington University School of Medicine, St. Louis, MO, USA.
Jazyk:	angličtina
Zdroj:	BioRxiv : the preprint server for biology [bioRxiv] 2024 Aug 06. Date of Electronic Publication: 2024 Aug 06.
DOI:	10.1101/2024.08.02.606402
Abstrakt:	Many studies have compared gene expression in young and old samples to gain insights on aging, the primary risk factor for most major chronic diseases. However, these studies only describe associations, failing to distinguish drivers of aging from compensatory geroprotective responses and incidental downstream effects. Here, we introduce a workflow to characterize the causal effects of differentially expressed genes on lifespan. First, we performed a meta-analysis of 25 gene expression datasets comprising samples of various tissues from healthy, untreated adult mammals (humans, dogs, and rodents) at two distinct ages. We ranked each gene according to the number of distinct datasets in which the gene was differentially expressed with age in a consistent direction. The top age-upregulated genes were TMEM176A, EFEMP1, CP, and HLA-A; the top age-downregulated genes were CA4, SIAH, SPARC, and UQCR10. Second, the effects of the top ranked genes on lifespan were measured by applying post-developmental RNA interference of the corresponding ortholog in the nematode C. elegans (two trials, with roughly 100 animals per genotype per trial). Out of 10 age-upregulated and 9 age-downregulated genes that were tested, two age-upregulated genes ( csp-3 /CASP1 and spch-2 /RSRC1) and four age-downregulated genes ( C42C1.8 /DIRC2, ost-1 /SPARC, fzy-1 /CDC20, and cah-3 /CA4) produced significant and reproducible lifespan extension. Notably, the data do not suggest that the direction of differential expression with age is predictive of the effect on lifespan. Our study provides novel insight into the relationship between differential gene expression and aging phenotypes, pilots an unbiased workflow that can be easily repeated and expanded, and pinpoints six genes with evolutionarily conserved, causal roles in the aging process for further study. Competing Interests: Conflict of Interest Statement: The authors have declared that no conflicts of interest exist.
Databáze:	MEDLINE
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