by Liu Jia, Chinese Academy of Sciences

Flow chart of the area between response curves (ABRC) method. Credit: National Science Review (2024). DOI: 10.1093/nsr/nwae425

Chinese scientists have developed a novel two-dimensional (2D) framework, the "Health State Map (HSM)," to define metabolic health and nutritional capacity. The study, which was conducted by Prof. Lin Xu's team from the Shanghai Institute of Nutrition and Health of the Chinese Academy of Sciences (CAS), collaborating with Prof. Chen Luonan and Prof. Zeng Rong from the Center for Excellent in Molecular Cell Science of CAS, and scientists from BYHEALTH Institute of Nutrition & Health, was published online in National Science Review on Nov. 26.

Defining metabolic health remains a global challenge due to a lack of specific quantification criteria or methods. Current disease-based diagnosis under fasting conditions does not adequately detect early signs of dysmetabolism and impaired organ function. As a result, it may miss the best window for disease prevention and reversal through effective intervention.

Homeostatic resilience, which reflects an individual's ability to adapt to external interruptions like meal intake, has been proposed as an important health criterion and a new approach to holistically defining metabolic health. However, a sophisticated methodology for assessing postprandial homeostatic resilience is still lacking.

In this study, a total of 111 sex-matched Chinese individuals, aged 20–70 years with different body weights, were recruited. Blood samples were collected at fasting and five time-points after a mixed macronutrient tolerance test (MMTT). All collected samples were assessed using metabolomics and clinical organ/tissue functional biomarkers.

HSM was constructed by integrating a fasting feature-based dimension "Health Phenotype Score" (HPS) and a postprandial feature-based dimension "Homeostatic Resilience Score" (HRS). To test whether the 2D HSM is more informative than a one-dimensional (1D) model, a mixed score was built by combing fasting and post-MMTT data using the same set as HSM.

The results showed that the mixed score was highly correlated with HPS, while HRS was significantly associated with metabolic syndrome prevalence, independent of both HPS and the mixed score. Even with similar HPSs or mixed scores, participants with higher HRSs exhibited better liver function and insulin sensitivity than those with lower HRSs, indicating that HRS provided additional information.

Moreover, large interpersonal variations in postprandial homeostatic resilience for glucose, lipids, and amino acids were observed, even among participants with similar overall HRS values. High levels of physical activity and specific gut microbiome compositions were found to be positively associated with HRS, suggesting the potential influence of these factors on metabolic homeostatic resilience.

"By separately analyzing pre- and post-MMTT features, we found that this 2D framework is clearly superior to the 1D mixed-score framework using the same dataset. This will inform future intervention trials to improve early detection of organ/tissue dysfunction and facilitate the development of more targeted prevention and treatment strategy," said Prof. Chen Zhengming from the University of Oxford.

Overall, the HSM assessment framework can comprehensively and precisely reflect individuals' metabolic health and nutritional adaptability. This framework, after having been validated and improved by intervention trials, may facilitate shifting to "well-being-centered" metabolic health assessments from the "disease-centered" assessments currently used.

"This work provides a new perspective and promising means for re-defining metabolic health. It will lead to the development of novel precision nutrition approaches that are urgently needed in the fields of precision nutrition and preventive medicine," said Prof. Gu Zhenglong from the Greater Bay Area Institute of Precision Medicine (Guangzhou).

More information: Yanpu Wu et al, Two-dimensional health state map to define metabolic health using separated static and dynamic homeostasis features: a proof-of-concept study, National Science Review (2024). DOI: 10.1093/nsr/nwae425

Provided by Chinese Academy of Sciences