Researchers developed DISCO (Distance of Covariance), an entropy-based aging metric that consistently outperformed existing dysregulation measures and matched top epigenetic clocks in predicting mortality across five major cohorts including UK Biobank. The metric quantifies biological entropy across clinical biomarkers, proteomics, metabolomics, and microbiomes, revealing that aging involves interconnected entropy increases rather than isolated organ decline. Notably, brain entropy emerged as the strongest predictor across multiple mortality causes, while organ-specific DISCO scores showed broad rather than targeted predictive power for diseases. This challenges the conventional view of organ-specific aging signatures. The entropy-spillover concept suggests that maintaining health during aging requires coordinated homeostatic control across multiple systems rather than targeting individual organs. Network analysis revealed that more centrally connected organ systems had stronger predictive power for health outcomes. While promising for understanding aging dynamics, this preprint awaits peer review and validation may change results. The findings could reshape aging research from studying isolated biomarkers toward systemic entropy management, though practical interventions targeting cross-system entropy remain to be developed.