Chapter Twelve - Aging and Age-Associated Diseases: Translational Bioinformatics and Systems Biology Methods

Abstract

Aging has complex consequences especially in age-associated diseases such as Alzheimer’s disease, cancer, cardiovascular diseases, and type 2 diabetes. Translational bioinformatics may enhance the understanding in the systems biology of aging with the simulation of the dynamics of biological systems in the aging processes. The systems-based approaches may link various aging stages at different structural, temporal, and spatial levels. Translational bioinformatics strategies may also contribute to drug repurposing for age-associated diseases. The immune system has the essential role in aging and age-associated diseases. The combination of translational bioinformatics and experimental approaches may lead to systems-based models with predictive capabilities to describe the interactions among immune molecules, cells, and tissues in aging. The data integration and data mining methods may help identify the dynamical biomarkers such as altered cellular networks to represent the disease onset and development for the preventive and treatment strategies during early phases. The establishment of the accurate associations between biomarkers and disease stages and severity can make it possible to predict the cognitive decline and disease development. Comprehensive biomarkers can also be helpful for the elucidation of the heterogeneities in populations for personalized medicine.