A computational framework for detecting inter-tissue gene-expression coordination changes with aging
Abstract Aging is a complex and systematic biological process that involves multiple genes and biological pathways across different tissues. While existing studies focus on tissue-specific aging factors, the inter-tissue interplay between molecular pathways during aging remains insufficiently explor...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-03-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-94043-9 |
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| Summary: | Abstract Aging is a complex and systematic biological process that involves multiple genes and biological pathways across different tissues. While existing studies focus on tissue-specific aging factors, the inter-tissue interplay between molecular pathways during aging remains insufficiently explored. To bridge this gap, we propose a novel computational framework to identify the effect of aging on the coordinated patterns of gene-expression across multiple tissues. Our framework includes (1) an adjusted multi-tissue weighted gene co-expression network analysis, (2) differential network connectivity analysis between age groups and (3) machine learning models, XGBoost and Random Forest (RF) fed by gene expression levels and lower-dimensional pathway score space, to identify unique key inter-tissue genes and biological pathways for classifying aging. We applied our approach to three representative tissues: Adipose-Subcutaneous, Muscle-Skeletal and Brain-Cortex. The RF model demonstrated the best performance in predicting age group (AUC < 88%) highlighting key genes involved in inter-tissue coordination processes in aging. We also identified the inter-tissue involvement of lipid metabolism, immune system, and cell communication pathways during aging and detected distinct aging pathways manifested between tissues. The proposed framework highlights the importance of inter-tissue coordination processes underlying aging and provides valuable insights into aging mechanisms which can further assist in the development of therapeutic strategies promoting healthy aging. |
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| ISSN: | 2045-2322 |