In medical and epidemiological research, the term "Health" is often used without clear criteria, posing challenges in control group selection with general standard. To address this, we propose "Quantum Healthomics," aiming to define a standardized health index using various parameters. Our algorithms, Personalized Lifetime Disease Severity (PLDS) and Phenotypical Health Ideality (PHI), utilize 237 disease histories and 50 clinical features from the Korean Genome Project (KGP) to quantify health. While PLDS exhibited limited ability to distinguish between the disease and non-disease groups (p = 0.0541), PHI demonstrated robust discriminatory power (p = 6.76e-05). This initiative aims to enhance study reproducibility and further analyze precise health using multi-omic parameters, thereby contributing to healthy aging in the future.
Publisher
Ulsan National Institute of Science and Technology