AgeAnnoMO: a knowledgebase of multi-omics annotation for animal aging.

Journal: Nucleic acids research
Published Date: Jan 5, 2024

Abstract

Aging entails gradual functional decline influenced by interconnected factors. Multiple hallmarks proposed as common and conserved underlying denominators of aging on the molecular, cellular and systemic levels across multiple species. Thus, understanding the function of aging hallmarks and their relationships across species can facilitate the translation of anti-aging drug development from model organisms to humans. Here, we built AgeAnnoMO (https://relab.xidian.edu.cn/AgeAnnoMO/#/), a knowledgebase of multi-omics annotation for animal aging. AgeAnnoMO encompasses an extensive collection of 136 datasets from eight modalities, encompassing 8596 samples from 50 representative species, making it a comprehensive resource for aging and longevity research. AgeAnnoMO characterizes multiple aging regulators across species via multi-omics data, comprehensively annotating aging-related genes, proteins, metabolites, mitochondrial genes, microbiotas and age-specific TCR and BCR sequences tied to aging hallmarks for these species and tissues. AgeAnnoMO not only facilitates a deeper and more generalizable understanding of aging mechanisms, but also provides potential insights of the specificity across tissues and species in aging process, which is important to develop the effective anti-aging interventions for diverse populations. We anticipate that AgeAnnoMO will provide a valuable resource for comprehending and integrating the conserved driving hallmarks in aging biology and identifying the targetable biomarkers for aging research.

Authors

  • Kexin Huang
    School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China.
  • Xi Liu
    Collaborative Innovation Center of Radiological Medicine of Jiangsu Higher Education Institutions, Suzhou Medical College, Soochow University, Suzhou, Jiangsu 215123, China.
  • Zhaocan Zhang
    School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China.
  • Tiangang Wang
    School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China.
  • Haixia Xu
    The Center of Gerontology and Geriatrics and West China Biomedical Big Data Centre, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, PR China.
  • Qingxuan Li
    State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P.R. China.
  • Yuhao Jia
    School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China.
  • Liyu Huang
    School of Life Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, People's Republic of China. huangly@mail.xidian.edu.cn.
  • Pora Kim
    Center for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
  • Xiaobo Zhou
    Department of Diagnostic Radiology, Wake Forest Medical School, Winston-Salem, NC 27103, USA. Electronic address: xizhou@wakehealth.edu.

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