Individual health-disease phase diagrams for disease prevention based on machine learning.

Early disease detection and prevention methods based on effective interventions are gaining attention worldwide. Progress in precision medicine has revealed that substantial heterogeneity exists in health data at the individual level and that complex health factors are involved in chronic disease development. Machine-learning techniques have enabled precise personal-level disease prediction by capturing individual differences in multivariate data. However, it is challenging to identify what aspects should be improved for disease prevention based on future disease-onset prediction because of the complex relationships among multiple biomarkers. Here, we present a health-disease phase diagram (HDPD) that represents an individual's health state by visualizing the future-onset boundary values of multiple biomarkers that fluctuate early in the disease progression process. In HDPDs, future-onset predictions are represented by perturbing multiple biomarker values while accounting for dependencies among variables. We constructed HDPDs for 11 diseases using longitudinal health checkup cohort data of 3,238 individuals, comprising 3,215 measurement items and genetic data. The improvement of biomarker values to the non-onset region in HDPD remarkably prevented future disease onset in 7 out of 11 diseases. HDPDs can represent individual physiological states in the onset process and be used as intervention goals for disease prevention.

Three-dimensional Culture of Human Proximal Tubular Epithelial Cells for an in vitro Evaluation of Drug-induced Kidney Injury.

Drug-induced kidney injury (DIKI) is the major cause of acute kidney injury (AKI). Renal proximal tubular epithelial cells (RPTECs) are the primary target sites of DIKI and express transporters involved in renal drug disposition. In the present study, we focused on three-dimensionally cultured human RPTECs (3D-RPTECs) with elevated expression of drug transporters to investigate their utility in DIKI evaluation. Intracellular ATP levels in 3D-RPTECs are reduced by tenofovir and cisplatin that are substrates of an organic anion transporter 1 and an organic cation transporter 2, respectively. In addition, 3D-RPTECs were exposed to 17 and 15 drugs that are positive and negative to RPTEC toxicity, respectively, for up to 28 d. The 20 % decreasing concentration of drugs for ATP amount (EC20) was obtained, and the ratio of EC20 values and clinical maximum concentration (Cmax) ≤100 were used as cut-off value to evaluate potential of DIKI. The sensitivities of 3D-RPTECs were 82.4 % and 88.2 % after 7 d and 28 d of drug exposure, respectively, and the specificities were 100 % and 93.3 %, respectively. The predictive performance of 3D-RPTECs was higher than that of two-dimensional cultured RPTECs and the kidney cell line HK-2. In conclusion, 3D-RPTECs are useful for in vitro evaluation of RPTEC injury by measuring intracellular ATP levels.