Clinical phenotyping of patients with type 2 diabetes mellitus: constitutional, anthropometric, metabolic markers of different phenotypes

3 липня 2020
940
Therapy, General practice
Endocrinology
Prybyla O.V.
Zinych O.V.
Korpachev V.V.
Kushnareva N.N.
Kovalchuk A.V.
Gurina N.M.
Shuprovich A.A.
Ключові слова :
diabetes mellitus type 2,
obesity,
phenotype,
visceral fat
Спеціальності :
Therapy, General practice
Endocrinology
Резюме

The aim was to describe the types of the body composition and metabolic characteristics of patients with type 2 diabetes mellitus (DM2), depending on obesity levels. Object and methods of research. Anthropometric parameters, body composition, glucose, lipid and urate metabolism of 51 patients with DM2, aged 30–81 years, with a duration of DM2 1–20 years, were determined. All patients were divided into 2 body mass index (BMI) groups: 1) metabolically unhealthy without obesity (n=17; BMI <30 kg/m2); 2) metabolically unhealthy with obesity (n=34; BMI ≥30 kg/m2) who practically did not differ in age, glycated hemoglobin level, fasting glycemia, uricemia, uricosuria, muscle mass on the body and extremities, total bone mass, total cholesterol, triglycerides, high-density lipoprotein, central adiposity index, visceral adiposity index (p>0.05). Results. Patients without obesity have significantly higher percentages of water into the body, estimated metabolic age (p<0.05). As a result of comparative analysis, it was found that patients with obesity had higher values of waist and thing level, thickness of fat folds, percentage of total body fat, visceral fat, increase of fat levels in the body and both extremities, atherogenic index (p<0.001). Conclusions. Identification of clinical phenotypes based on the identification of constitutional and metabolic characteristics will allow a more differentiated assessment of possible cardiometabolic risks in patients with DM2. The data obtained are the basis for further selection of markers of hormonal and metabolic changes in persons with appropriate phenotypic characteristics and development of personalized recommendations for their correction.

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