bioRxivGeneticsPreprint
Circadian Dysregulation in Aging Alters Senescence and Inflammatory Pathways in a Sex- and Time-of-Day Dependent Manner
Gretchen T. ClarkiD, Yue Zhao, Robyn E. ReeveiD, Colleen M. Farley, Courtney WilleyiD, Susan SheehaniD, Samantha SpellacyiD, Alicia WarreniD, Abigail Brackett, Nadia A RosenthaliD, Ron KorstanjeiD
Abstract
The circadian rhythm orchestrates gene expression and critical physiological processes but becomes disrupted with aging, contributing to disease. How this disruption interacts with cellular senescence--a key driver of aging pathology--remains poorly defined. We studied renal gene expression at four timepoints over 24hrs in 6- and 24-month-old genetically diverse UM-HET3 mice of both sexes and performed complementary analyses in synchronized fibroblasts sampled at seven timepoints. Aging dysregulated core clock relationships, including loss of the canonical anti-phase expression between Bmal1 and Per2. Senescence-associated genes were not static but exhibited pronounced oscillations, with senescence phenotypes varying by sex and time of day. Differential expression analysis revealed immune activation, metabolic rewiring, and epigenetic changes that were sex- and time-dependent. Variance analysis uncovered increased transcriptional noise in aging, particularly in circadian-regulated pathways such as RNA splicing, ribosome biogenesis, and TOR signaling. Single-nucleus RNA-Seq identified two cell populations lacking the normal Bmal1-Cdkn1a expression relationship: one senescent-like and another profibrotic, revealing distinct cell states linked to circadian dysregulation. Fibroblasts recapitulated key age-related circadian changes seen in the kidneys, including phase shifts in mTOR and oxidative phosphorylation. Together, this work demonstrates that senescence phenotypes are dynamic, sex-specific, and time-of-day dependent, and introduces a new framework for detecting senescent cells based on circadian gene relationships. These findings underscore the need to integrate temporal context into aging research and therapeutic strategies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=185 HEIGHT=200 SRC="FIGDIR/small/709919v1_ufig1.gif" ALT="Figure 1"> View larger version (86K): org.highwire.dtl.DTLVardef@247e70org.highwire.dtl.DTLVardef@1e8f66borg.highwire.dtl.DTLVardef@18a0673org.highwire.dtl.DTLVardef@ad91d7_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: mouse
- assay: bulk RNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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