Academic Journal
Προβολή σε EDS
Συνδεδεμένο Πλήρες Κείμενο

Network Model to Predict Age-Related Transcriptional Reprogramming.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Network Model to Predict Age-Related Transcriptional Reprogramming.
Συγγραφείς: McNeill TJ; Discovery Center for Musculoskeletal Recovery, Schoen Adams Research Institute at Spaulding, Charlestown, Massachusetts, USA.; Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Charlestown, Massachusetts, USA.; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA., Ambrosio F; Discovery Center for Musculoskeletal Recovery, Schoen Adams Research Institute at Spaulding, Charlestown, Massachusetts, USA.; Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Charlestown, Massachusetts, USA.; Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts, USA., Iijima H; Discovery Center for Musculoskeletal Recovery, Schoen Adams Research Institute at Spaulding, Charlestown, Massachusetts, USA.; Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Charlestown, Massachusetts, USA.; Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts, USA.
Πηγή: Aging cell [Aging Cell] 2026 Sep; Vol. 25 (9), pp. e70683.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Wiley-Blackwell Country of Publication: England NLM ID: 101130839 Publication Model: Print Cited Medium: Internet ISSN: 1474-9726 (Electronic) Linking ISSN: 14749718 NLM ISO Abbreviation: Aging Cell Subsets: MEDLINE
Imprint Name(s): Publication: Oxford, UK : Wiley-Blackwell
Original Publication: Oxford, UK : Blackwell Pub., c2002-
Ιατρικοί όροι (MeSH): Aging*/genetics , Cellular Reprogramming*/genetics, Chondrocytes/metabolism ; Animals ; Humans
Περίληψη: Understanding how secreted factors from aged tissue, often referred to as the senescence-associated secretome, reshape cellular phenotypes remains a major challenge due to the complexity of downstream molecular cascades. Here, we present a computational framework for in silico perturbation modeling designed to predict distinct transcriptional responses to age-specific extracellular environmental cues. We exemplify applications of this framework using articular chondrocytes exposed to secretomes derived from infrapatellar fat pads-an integral component of the cartilage microenvironment-excised from the knee joints of young and aged animals. First, we accessed public transcriptomic data of cartilage from healthy and osteoarthritic knee joints and constructed a cartilage-specific co-expression network using topological overlap matrices, which measure network interconnectedness. We then implemented a Random Walk with Restart to simulate the downstream signal propagation of differentially expressed ligands secreted from young and aged infrapatellar fat pads. We benchmarked predicted perturbation signatures against RNA-seq data from aged chondrocytes treated in vitro with either young or aged infrapatellar fat pad-conditioned medium. Our evaluation pipeline included functional enrichment comparison and receiver operating characteristic analysis. These analyses confirmed that simulated perturbations recapitulated chondrocyte signaling pathways modulated by young and aged infrapatellar fat pad secretomes, including primary effects on mitochondrial respiration, a central hallmark of aging. The network paradigm introduced here provides a data-driven strategy to disentangle how complex, age-dependent extracellular environments influence cellular fate. Ultimately, we anticipate that this pipeline can be extended to diverse tissues and age-related diseases to guide the development of interventions that restore youthful cellular phenotypes.
(© 2026 The Author(s). Aging Cell published by Anatomical Society and John Wiley & Sons Ltd.)
References: PLoS One. 2012;7(9):e45517. (PMID: 23029067)
Nat Commun. 2015 Jul 22;6:7866. (PMID: 26198319)
Aging Cell. 2024 Feb;23(2):e14043. (PMID: 38111237)
Nat Commun. 2023 Jan 10;14(1):18. (PMID: 36627269)
Bioinformatics. 2010 Apr 1;26(7):976-8. (PMID: 20179076)
Cold Spring Harb Perspect Biol. 2021 Sep 1;13(9):. (PMID: 34187808)
Cartilage. 2021 Dec;13(2_suppl):1102S-1121S. (PMID: 34894777)
Brief Bioinform. 2022 Jul 18;23(4):. (PMID: 35704883)
Osteoarthritis Cartilage. 2022 Jun;30(6):862-874. (PMID: 35176481)
Trends Genet. 2025 Mar;41(3):218-235. (PMID: 39424502)
Innovation (Camb). 2021 Jul 01;2(3):100141. (PMID: 34557778)
Nat Rev Genet. 2013 Jan;14(1):35-48. (PMID: 23207911)
Signal Transduct Target Ther. 2025 Jun 11;10(1):190. (PMID: 40500258)
J Cell Sci. 2005 Nov 1;118(Pt 21):4947-57. (PMID: 16254242)
Nat Methods. 2020 Feb;17(2):159-162. (PMID: 31819264)
Sci Adv. 2021 Apr 14;7(16):. (PMID: 33853780)
Nat Rev Dis Primers. 2025 Feb 13;11(1):10. (PMID: 39948092)
Genes Dev. 2002 Nov 1;16(21):2813-28. (PMID: 12414734)
J Bacteriol. 2022 Jan 18;204(1):e0035321. (PMID: 34748388)
Cell Metab. 2015 Aug 4;22(2):207-18. (PMID: 26166745)
Essays Biochem. 2018 Jul 20;62(3):255-270. (PMID: 30030361)
Science. 2012 Aug 31;337(6098):1062-5. (PMID: 22936770)
NPJ Aging. 2024 Jul 15;10(1):34. (PMID: 39009582)
Bioinformatics. 2019 Feb 1;35(3):497-505. (PMID: 30020411)
Database (Oxford). 2024 Feb 12;2024:. (PMID: 38345567)
PLoS Biol. 2020 Jan 16;18(1):e3000599. (PMID: 31945054)
J Biol Chem. 2021 Oct;297(4):101224. (PMID: 34560099)
Signal Transduct Target Ther. 2022 Dec 16;7(1):391. (PMID: 36522308)
Cell. 2016 Dec 1;167(6):1598-1609.e10. (PMID: 27912063)
Nat Commun. 2024 Oct 2;15(1):8520. (PMID: 39353907)
J Cell Biol. 2025 Apr 07;224(4):. (PMID: 40047641)
BMC Syst Biol. 2014;8 Suppl 1:S6. (PMID: 24565229)
J Clin Invest. 1996 Feb 1;97(3):761-8. (PMID: 8609233)
Nat Protoc. 2008;3(8):1253-60. (PMID: 18714293)
Osteoarthritis Cartilage. 2018 Nov;26(11):1531-1538. (PMID: 30081074)
Osteoarthritis Cartilage. 2024 Apr;32(4):365-371. (PMID: 38049031)
Nat Rev Rheumatol. 2016 Jul;12(7):412-20. (PMID: 27192932)
BMC Bioinformatics. 2008 Dec 29;9:559. (PMID: 19114008)
Curr Mol Med. 2012 Dec;12(10):1220-43. (PMID: 22834826)
BMC Bioinformatics. 2018 Jun 13;19(Suppl 8):208. (PMID: 29897326)
Bioinformatics. 2010 May 1;26(9):1219-24. (PMID: 20215462)
Arthritis Res Ther. 2025 May 3;27(1):100. (PMID: 40319309)
PLoS Comput Biol. 2012;8(8):e1002640. (PMID: 22916002)
Bioinformatics. 2014 Nov 15;30(22):3215-22. (PMID: 25078397)
J Gerontol A Biol Sci Med Sci. 2025 Jun 10;80(7):. (PMID: 40375383)
Grant Information: R01 AG089455 United States AG NIA NIH HHS; R01 AG090356 United States AG NIA NIH HHS; R01AG089455 United States NH NIH HHS; R01AG090356 United States NH NIH HHS
Contributed Indexing: Keywords: cell communication; extracellular signaling; gene expression profiling; in silico simulation; osteoarthritis
Entry Date(s): Date Created: 20260822 Date Completed: 20260822 Latest Revision: 20260825
Update Code: 20260825
PubMed Central ID: PMC13499505
DOI: 10.1111/acel.70683
PMID: 42631664
Βάση Δεδομένων: MEDLINE
Περιγραφή
ISSN:1474-9726
DOI:10.1111/acel.70683