Prediabetes, Healthy individuals
Conditions
Interventions
AI feedback from Taohealth App
Sponsors
University of Yamanashi
Eligibility
Sex/Gender
All
Inclusion criteria
Inclusion criteria: Individuals who underwent a comprehensive health check-up or periodic health examination between fiscal years 2024 and 2026 and meet the following criteria will be eligible for inclusion. 1. The age at the time of examination is between 25 and 70 years, inclusive. 2. The fasting plasma glucose level at the time of examination is 100 mg/dL or higher and 125 mg/dL or lower. 3. The HbA1c level at the time of examination is less than 6.5%. 4. Based on the questionnaire at the time of examination, the individual reports not taking any medication for type 2 diabetes. 5. Written informed consent for participation in this study has been obtained.
Exclusion criteria
Exclusion criteria: Individuals who meet any of the following criteria will be excluded from the study. 1. Individuals who are considered unable to adequately understand the study explanation due to cognitive impairment, severe psychiatric disorders, serious physical illness, or other similar conditions, or who are judged to have difficulty participating in the study or undergoing the required examinations. 2. Individuals who do not possess a smartphone. 3. Individuals who are unable to communicate smoothly in Japanese. 4. Individuals who are judged by the principal investigator to have other conditions that make them inappropriate for participation in this study.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Identification of proteome (protein) networks associated with changes in insulin resistance (HOMA-R). | — |
Secondary
| Measure | Time frame |
|---|---|
| Identification of activity monitor data and health behavior indicators associated with changes in the identified proteome networks. Identification of SNPs, DNA methylation, RNA, metabolome, microbiome, miRNA, cfDNA, and exosomes associated with changes in insulin resistance (HOMA-R). Identification of physical activity and behavioral change indicators associated with the identified SNPs, DNA methylation, RNA, metabolome, microbiome, miRNA, cfDNA, and exosomes. Examination of correlations among each omics modality (SNPs, DNA methylation, RNA, proteome, metabolome, microbiome, miRNA, cfDNA, and exosomes). Examination of the correlation between dietary records collected through the health record application (Taohealth) and the food frequency questionnaire (FFQ). | — |
Countries
Japan
Contacts
Public ContactTadao Ooka
University of Yamanashi Department of Health Sciences
Outcome results
None listed