ArticleClinical hypertension2025
Nutriomics and artificial intelligence nutrition obesity cohort (NAINOC): a design paper for a prospective cohort for nutrition and obesity research.
Article in Clinical hypertension, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: The increase in obesity is becoming a world-wide health issue. However, no prospective cohorts in East Asia have thoroughly explored comprehensive nutritional and multiomic data in individuals with obesity. This study is designed to establish an obesity cohort that constitutes clinical characteristics, nutritional status, laboratory profiles, metabolic complication studies, and multiomic profiles with the goal of artificial intelligence platform-based nutriomic analysis. Methods: This study aims to enroll at least 400 obese adults (aged ≥ 19 years; body mass index ≥ 25 kg/m Conclusions: The strength of this cohort will be as follows. First, the cohort will enable the integration of nutritional intake data with other multiomics data for a comprehensive analysis. Second, inclusion of both obese individuals with various metabolic traits and non-obese individuals as controls is advantageous for studying a wide range of obesity phenotypes in comparison with non-obese conditions. Third, diverse modalities to assess metabolic and complication status will facilitate multifaceted analysis. Lastly, beyond the typical blood and stool samples in multiomic studies, the inclusion of urine, saliva, and skin samples will further refine obesity characterization.
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