Decipher reliable biomarkers of brain aging by integrating literature-based evidence with interactome data

Exp Mol Med. 2018 Apr 13;50(4):1-15. doi: 10.1038/s12276-018-0057-6.

Abstract

Aging is an inevitable progressive decline in every physiological function and serves as a primary risk factor for cognitive decline and Alzheimer's disease. Thus, age-dependent impairments in cognitive function must be understood in association with general aging processes with an integrative approach in a systemic manner. An integrative aging gene network was constructed based on mutual molecular interactions using literature-curated interactome data and separated into functionally distinct modules. To investigate key surrogate biomarkers of the aging brain in the context of the general aging process, co-expression networks were built on post-mortem and Alzheimer's brain transcriptome data. In both the normal aging brain and the brain affected by Alzheimer's disease, the immune-related co-expression module was positively correlated with advancing age, whereas the synaptic transmission-related co-expression module was decreased with age. Importantly, the network topology-based analysis indicated that complement system genes were prioritized as a surrogate biomarker in evaluating the process of brain aging. Our public data-centered analysis coupled with experimental validation revealed that the complement system is likely to be a master regulator in initiating and regulating the immune system in the aging brain and could serve as reliable and surrogate biomarkers for the diagnosis of cognitive dysfunction.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aging / genetics*
  • Animals
  • Biomarkers*
  • Brain / metabolism*
  • Brain / physiopathology*
  • Computational Biology / methods
  • Connectome*
  • Databases, Genetic
  • Female
  • Gene Expression Profiling
  • Gene Regulatory Networks*
  • Humans
  • Metabolic Networks and Pathways
  • Mice
  • Molecular Sequence Annotation
  • Reproducibility of Results
  • Transcriptome*

Substances

  • Biomarkers