[논문]정밀영양: 개인 간 대사 다양성을 이해하기 위한 접근

김양하

doi:10.4163/jnh.2022.55.1.1

정밀영양: 개인 간 대사 다양성을 이해하기 위한 접근
Precision nutrition: approach for understanding intra-individual biological variation 원문보기

Journal of nutrition and health, v.55 no.1, 2022년, pp.1 - 9

Abstract ▼ AI-Helper

In the past few decades, great progress has been made on understanding the interaction between nutrition and health status. But despite this wealth of knowledge, health problems related to nutrition continue to increase. This leads us to postulate that the continuing trend may result from a lack of consideration for intra-individual biological variation on dietary responses. Precision nutrition utilizes personal information such as age, gender, lifestyle, diet intake, environmental exposure, genetic variants, microbiome, and epigenetics to provide better dietary advices and interventions. Recent technological advances in the artificial intelligence, big data analytics, cloud computing, and machine learning, have made it possible to process data on a scale and in ways that were previously impossible. A big data platform is built by collecting numerous parameters such as meal features, medical metadata, lifestyle variation, genome diversity and microbiome composition. Sophisticated techniques based on machine learning algorithm can be used to integrate and interpret multiple factors and provide dietary guidance at a personalized or stratified level. The development of a suitable machine learning algorithm would make it possible to suggest a personalized diet or functional food based on analysis of intra-individual metabolic variation. This novel precision nutrition might become one of the most exciting and promising approaches of improving health conditions, especially in the context of non-communicable disease prevention.

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그림 Fig. 1. Precision nutrition. A big data platform is built by collecting numerous parameters such as meal features, medical metadata, lifestyle variation, genome diversity, and microbiome composition. A machine learning algorithm can be used to integrate and interpret multiple factors to deliver health solutions (e.g.. dietary advice or functional foods) [9].
그림 Fig. 2. Difference in effects of hypocaloric diet intervention according to the presence of ADIPOQ SNP (rs1501299) [17]. SNP, single nucleotide polymorphism; TC, total cholesterol; LDL, low-density lipoprotein; TG, triglyceride; HOMAIR, homeostasis model assessment for insulin resistance.

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정밀영양: 개인 간 대사 다양성을 이해하기 위한 접근
Precision nutrition: approach for understanding intra-individual biological variation 원문보기

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정밀영양: 개인 간 대사 다양성을 이해하기 위한 접근 Precision nutrition: approach for understanding intra-individual biological variation 원문보기

Abstract ▼ AI-Helper

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정밀영양: 개인 간 대사 다양성을 이해하기 위한 접근
Precision nutrition: approach for understanding intra-individual biological variation 원문보기