Two-dimensional health state map to define metabolic health using separated static and dynamic homeostasis features: a proof-of-concept study

Abstract

Defining metabolic health is critical for earlier reversing metabolic dysfunction and disease, and fasting-based diagnosis may not adequately assess individual's metabolic adaptivity under stress. We constructed a novel Health State Map (HSM) comprising Health Phenotype Score (HPS) with fasting features alone and Homeostatic Resilience Score (HRS) with a 5-time point features only (t = 30, 60, 90, 180, 240 min) following a standardized mixed macronutrient tolerance test (MMTT). Among 111 adult Chinese, the mixed-score, using the same set of fasting and post-MMTT data as HSM, was highly correlated with HPS. HRS was significantly associated with metabolic syndrome prevalence, independent of HPS (OR [95% CI]: 0.41 [0.18, 0.92]) and the mixed-score (0.34 [0.15, 0.69]). Moreover, HRS could discriminate metabolic characteristics unseparated by HPS and the mixed-score. Participants with higher HRS had better metabolic traits than those with lower HRS. Large interpersonal variations were also evidenced by evaluating postprandial homeostatic resiliencies for glucose, lipids, and amino acids, when participants had similar overall HRS. Additionally, HRS was positively associated with physical activity level and specific gut microbiome structure. Collectively, our HSM model might offer a novel approach to precisely define an individual's metabolic health and nutritional capacity.