Integrative analysis of methylation and transcriptional profiles to predict aging and construct aging specific cross-tissue networks.
BACKGROUND
Aging is a complex process relating multi-scale omics data. Finding key age markers in normal tissues could help to provide reliable aging predictions in human. However, predicting age based on multi-omics data with both accuracy and informative biological function has not been performed systematically, thus relative cross-tissue analysis has not been investigated entirely, either.


RESULTS
Here we have developed an improved prediction pipeline, the Integrating and Stepwise Age-Prediction (ISAP) method, to regress age and find key aging markers effectively. Furthermore, we have performed a serious of network analyses, such as the PPI network, cross-tissue networks and pathway interaction networks.


CONCLUSIONS
Our results find important coordinated aging patterns between different tissues. Both co-profiling and cross-pathway analyses identify more thorough functions of aging, and could help to find aging markers, pathways and relative aging disease researches.
Shanghai Public Health Clinical Center and Institutes of Biomedical Sciences, Fudan University, Shanghai, China.
Yin
Y
Wang
Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, People's Republic of China.
Tao
T
Huang
Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, Shanghai, 201203, China.
Lu
L
Xie
Shanghai Public Health Clinical Center and Institutes of Biomedical Sciences, Fudan University, Shanghai, China. liulei@fudan.edu.cn.|Shanghai Center for Bioinformation Technology, Shanghai Academy of Science and Technology, Shanghai, 201203, China. liulei@fudan.edu.cn.
Lei
L
Liu
D000375:Aging / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D019175:DNA Methylation; D020869:Gene Expression Profiling; D005819:Genetic Markers / Q000235:genetics; D006801:Humans; D025941:Protein Interaction Mapping; D014158:Transcription, Genetic
D005819:Genetic Markers