People, who simultaneously suffer from metabolic dysfunction and multiple diseases, tend to die at a younger age. In scientific publications many time highlight how aging is “the biggest risk factor for a majority of chronic diseases driving both morbidity and mortality”, аt the same time, it is noted that biological age is a more accurate indicator of premature aging. The mass, organs function and biological clocks (biological age) are closely related and conceptually “engineered” to meet the highest metabolic and mechanical functional requirements. Authors formulated a hypothesis: metabolic disorders, i.e. dysmetabolism, is formed in the form of general or systemic (within the whole organism, example – metabolic syndrome) dysmetabolism, and in the form of local dysmetabolism (individual organs, example – metabolic dysfunction-associated fatty liver disease (MAFLD)).

Methodological features:

Tetrapolar dual-frequency bioimpedansometry with vector analysis and registration of 40 parameters, with software that determines metabolic (biological) age (Met-age), was used. In total, 30 volunteers were included and all selected parameters (bioimpedance, hematological and biochemical) were measured three times. Biological (metabolic) clock was calculated by the difference between chronological age (CHR-age) minus biological (metabolic) age (MET-age), as more than 1year difference. Additionally, the degree of L-lysine-induced ketosis was determined in 15 volunteers. Ketosis was determined by the content (ppm) of ketones in the exhaled air (KETONIX® device) before and at equal time intervals after the use (per os) of 2.0 grams of L-lysine (KETO-Lysine) and the area under curve (AUC) concentration-time was calculated, as a metabolic plasticity indicator, from rankings to slow, medium and fast, as described previously.

Results:

A group (16 cases) with a younger MET-age v.s. CHR-age: its values show a significant (p less than 0.05) correlation (Spearman Rank) of 0,3 or more with the following parameters: CHR-age, body weight, indicators of water and electrolyte balance, fat (FM), lean(LM) parts of body mass, content blood cholesterol, glucose, ALT activity, level of lymphocytes and platelets in the blood. At the same time, in the older MET-age v.s. CHR-age group (10 cases), a significant relationship (r equal to or greater than 0,3) was found only with blood cholesterol levels and CHR-age. Moreover, it shows: younger MET-age /FM:   r = -0,36; p = 0,04( y = 18,1 – 0,08*x) and MET-age/ICF:   r = -0,5 p = 0,002( y = 1796,2 – 8,9*x) and older MET-age / ICF:   r = -0,32; p = 0,074 (y = 24,38 – 0,08*x)  (not significant or loss of reliability), older MET-age/FM:   r = -0,36; p = 0,04 (y = 18,1 – 0,08*x). At the same time, highly sensitive CRP above 5 mg/l was found much more often in this group (26% v.s.2%, Chi-square (df=1) – 6,50, p= 0,01), as well as cholesterol over 6.5 mmol/l. These data clearly indicate the presence metabolic dysfunction (systemic dysmetabolism) in the group with premature metabolic age. KETO-Lysine test revealed a significantly more frequent increase in blood ALT activity (more than 30 IU) in the older MET-age group (41% vs. 5%), otherwise more frequent metabolic dysfunction of the liver (local dysmetabolism).

Conclusion:

It is possible to propose a new non-invasive test for differentiating dysmetabolism variants as systemic, local, and a combination of systemic with local, which allows more differentiated pathology features verification, including metabolic dysfunction-associated fatty liver disease (MAFLD).