Literature DB >> 21751870

Crosstissue coexpression network of aging.

Tao Huang1, Jian Zhang, Lu Xie, Xiao Dong, Lei Zhang, Yu-Dong Cai, Yi-Xue Li.   

Abstract

Aging is characterized by the interlocking decay of biological functions over time. Microarrays have been successful in elucidating some of the genome-wide changes that occur with age. Using the AGEMAP dataset that catalogs changes in gene expression as a function of age in 16 tissues in mice, we identified tissue-specific aging genes. Coordinated aging processes across different tissues then were clarified in crosstissue coexpression networks on both the gene and pathway levels. Our findings provide more concrete information about coordinated aging across different tissues. By bridging gene-level and tissue-level research, this study could help identify targets for attenuation of critical aging-related genes, pathways, or networks for antiaging intervention.

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Year:  2011        PMID: 21751870     DOI: 10.1089/omi.2011.0034

Source DB:  PubMed          Journal:  OMICS        ISSN: 1536-2310


  9 in total

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Journal:  Int J Clin Exp Pathol       Date:  2021-05-15

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Journal:  Cell       Date:  2017-09-21       Impact factor: 66.850

Review 4.  Defining the interorgan communication network: systemic coordination of organismal cellular processes under homeostasis and localized stress.

Authors:  Ilia A Droujinine; Norbert Perrimon
Journal:  Front Cell Infect Microbiol       Date:  2013-11-19       Impact factor: 5.293

5.  Integrative analysis of methylation and transcriptional profiles to predict aging and construct aging specific cross-tissue networks.

Authors:  Yin Wang; Tao Huang; Lu Xie; Lei Liu
Journal:  BMC Syst Biol       Date:  2016-12-23

6.  Dysfunctions associated with methylation, microRNA expression and gene expression in lung cancer.

Authors:  Tao Huang; Min Jiang; Xiangyin Kong; Yu-Dong Cai
Journal:  PLoS One       Date:  2012-08-17       Impact factor: 3.240

7.  Signal propagation in protein interaction network during colorectal cancer progression.

Authors:  Yang Jiang; Tao Huang; Lei Chen; Yu-Fei Gao; Yudong Cai; Kuo-Chen Chou
Journal:  Biomed Res Int       Date:  2013-03-20       Impact factor: 3.411

8.  Aging on a different scale--chronological versus pathology-related aging.

Authors:  Joost P M Melis; Martijs J Jonker; Jan Vijg; Jan H J Hoeijmakers; Timo M Breit; Harry van Steeg
Journal:  Aging (Albany NY)       Date:  2013-10       Impact factor: 5.682

9.  Omics for prediction of environmental health effects: Blood leukocyte-based cross-omic profiling reliably predicts diseases associated with tobacco smoking.

Authors:  Panagiotis Georgiadis; Dennie G Hebels; Ioannis Valavanis; Irene Liampa; Ingvar A Bergdahl; Anders Johansson; Domenico Palli; Marc Chadeau-Hyam; Aristotelis Chatziioannou; Danyel G J Jennen; Julian Krauskopf; Marlon J Jetten; Jos C S Kleinjans; Paolo Vineis; Soterios A Kyrtopoulos
Journal:  Sci Rep       Date:  2016-02-03       Impact factor: 4.379

  9 in total

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