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

July 3, 2020
801
Resume

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.

References:

  • Bershteyn L.M., Kovalenko I.G. (2010) «Metabolicheski zdorovyie» litsa s ozhireniem i metabolicheskie priznaki ozhireniya u lits s normalnoy massoy tela: chto za etim stoit? Probl. endokrinol., 3: 47–51.
  • Korpachev V.V., Pribila O.V., Korpacheva-Zinyich O.V. i dr. (2016) Antropometricheskie, gormonalnyie i biohimicheskie markeryi metabolicheskih fenotipov u bolnyih saharnyim diabetom 2-go tipa. Universum: Meditsina i farmakologiya, 1: 17.
  • Kushnarova N.M., Korpachev V.V., Korpacheva-Zinych O.V. ta in. (2016) Vidnoshennia kortyzol/DHEA ta pokaznyky lipidnoho profiliu syrovatky krovi khvorykh na tsukrovyi diabet 2 typu z riznym indeksom vistseralnoho ozhyrinnia. ScienceRise, 3(18): 19–25.
  • Alberti K.G., Eckel R.H., Grundy S.M. et al. (2009) Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation, 120:1640–1645.
  • Amato M.C., Giordano C., Galia M., Criscimanna A. (2010) Visceral Adiposity Index. A reliable indicator of visceral fat function associated with cardiometabolic risk. Diab. Care, 33(4): 920–922.
  • Andersen G.B., Tost J. (2018) A Summary of the biological processes, disease-associated changes, and clinical applications of DNA methylation. Methods Mol. Biol., 1708: 3–30.
  • Appleton S.L., Seaborn C.J., Visvanathan R. et al. (2013) Diabetes and cardiovascular disease outcomes in the metabolically healthy obese phenotype: a cohort study. Diabetes Care, 36(8): 2388–2394.
  • Arnett D.K., Blumenthal R.S., Albert M.A. et al. (2019) 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease. J. Am. Coll. Cardiol., 74(10): e177–e232.
  • Calori G., Lattuada G., Piemonti L. et al. (2011) Prevalence, metabolic features, and prognosis of metabolically healthy obese Italian individuals: The cremona study. Diabetes Care, 34: 210–215.
  • Camhi S.M., Katzmarzyk P.T. (2014) Differences in body composition between metabolically healthy obese and metabolically abnormal obese adults. Int. J. Obes. (Lond.), 38(8): 1142–1145.
  • Canning K.L., Brown R.E., Wharton S. et al. (2015) Edmonton Obesity Staging System Prevalence and Association with Weight Loss in a Publicly Funded Referral-Based Obesity Clinic. J. Obes., 2015: 619734.
  • Christensen D.H., Nicolaisen S.K., Berencsi K. et al. (2018) Danish Centre for Strategic Research in Type 2 Diabetes (DD2) project cohort of newly diagnosed patients with type 2 diabetes: a cohort profile. BMJ Open, 8: e017273.
  • Cӑtoi A.F., Pârvu A.E., Andreicuț A.D. et al. (2018) Metabolically Healthy versus Unhealthy Morbidly Obese: Chronic Inflammation, Nitro-Oxidative Stress, and Insulin Resistance. Nutrients, 10(9): 1199.
  • De Lorenzo A., Del Gobbo V., Premrov M.G.et al. (2007) Normal-weight obese syndrome: early inflammation? Am. J. Clin. Nutr., 85: 40–45.
  • De Lorenzo A., Soldati L., Sarlo F. et al. (2016) New obesity classification criteria as a tool for bariatric surgery indication. World J. Gastroenterol., 22(2): 681–703.
  • DeBoer M.D. (2013) Obesity, systemic inflammation, and increased risk for cardiovascular disease and diabetes among adolescents: A need for screening tools to target interventions. Nutrition, 29: 379–386.
  • Dhana K., Koolhaas C.M., van Rossum E. et al. (2016) Metabolically Healthy Obesity and the Risk of Cardiovascular Disease in the Elderly Population. PLoS ONE, 11(4): e0154273.
  • Ding C., Chan Z., Magkos F. (2016) Lean, but not healthy: the ‘metabolically obese, normal-weight’ phenotype. Curr. Opin. Clin. Nutr. Metab. Care, 19(6): 408–417.
  • Eckel N., Meidtner K., Kalle-Uhlmann T. et al. (2016) Metabolically healthy obesity and cardiovascular events: a systematic review and meta-analysis. Eur. J. Prev. Cardiol., 23(9): 956–966.
  • Eckel N., Mühlenbruch K., Meidtner K. et al. (2015) Characterization of metabolically unhealthy normal-weight individuals: Risk factors and their associations with type 2 diabetes. Metabolism, 64(8): 862–871.
  • Ferro Y., Gazzaruso C., Coppola A. et al. (2013) Fat utilization and arterial hypertension in overweight/obese subjects. J. Transl. Med., 11: 2.
  • Gomez-Huelgas R., Ruiz-Nava J., Santamaria-Fernandez S. et al. (2019) Impact of Intensive Lifestyle Modification on Levels of Adipokines and Inflammatory Biomarkers in Metabolically Healthy Obese Women. Mediators Inflamm., 2019: 4165260.
  • Goossens G.H. (2017) The Metabolic Phenotype in Obesity: Fat Mass, Body Fat Distribution, and Adipose Tissue Function. Obes. Facts, 10(3): 207–215.
  • Hyun Y.J., Koh S.J., Chae J.S. et al. (2008) Atherogenecity of LDL and unfavorable adipokine profile in metabolically obese, normal-weight woman. Obesity (Silver Spring), 16: 784–789.
  • Johannsen W. (1911) The genotype conception of heredity. Am. Nat., 45: 129–159.
  • Karelis A.D., Brochu M., Rabasa-Lhoret R. (2004) Can we identify metabolically healthy but obese individuals (MHO)? Diabetes Metab., 30: 569–572.
  • Koves T.R., Ussher J.R., Noland R.C. et al. (2008) Mitochondrial overload and incomplete fatty acid oxidation contribute to skeletal muscle insulin resistance. Cell Metab., 7: 45–56.
  • Kuk J.L., Ardern C.I., Church T.S. et al. (2011) Edmonton obesity staging system: association with weight history and mortality risk. App. Physiol. Nutr. Metab., 36(4): 570–576.
  • Lear S.A., Humphries K.H., Kohli S., Birmingham C.L. (2007) The use of BMI and waist circumference as surrogates of body fat differs by ethnicity. Obesity (Silver Spring), 15: 2817–2824.
  • Lin H., Zhang L., Zheng R., Zheng Y. (2017) The prevalence, metabolic risk and effects of lifestyle intervention for metabolically healthy obesity: a systematic review and meta-analysis: a PRISMA-compliant article. Medicine (Baltimore), 96(47): e8838.
  • Mathew H., Farr O.M., Mantzoros C.S. (2015) Metabolic health and weight: Understanding metabolically unhealthy normal weight or metabolically healthy obese patients. Metabolism, 65(1): 73–80.
  • Meigs J.B., Wilson P.W., Fox C.S. et al. (2006) Body mass index, metabolic syndrome, and risk of type 2 diabetes or cardiovascular disease. J. Clin. Endocrinol. Metab., 91: 2906–2912.
  • Mohammadreza B., Farzad H. (2012) Prognostic significance of the Complex «Visceral Adiposity Index» vs. simple anthropometric measures: Tehran lipid and glucose study. Cardiovasc. Diabetol., 11: 20.
  • Montalcini T., Lamprinoudi T., Morrone A. et al. (2014) Nutrients utilization in obese individuals with and without hypertriglyceridemia. Nutrients, 21: 790–798.
  • Nusrianto R., Tahapary D.L., Soewondo P. (2019) Visceral adiposity index as a predictor for type 2 diabetes mellitus in Asian population: A systematic review. Diab. Metab. Syndr. Clin. Res. Rev.,13(2): 1231–1235.
  • Padwal R.S., Pajewski N.M., Allison D.B., Sharma A.M. (2011) Using the Edmonton obesity staging system to predict mortality in a population-representative cohort of people with overweight and obesity. Canad. Med. Assoc. J., 183(14): E1059–E1066.
  • Petrushenko V., Stoliarchuk O.V. (2016) Oxidative Stress in Patients with Acute Pancreatitis: Associations with Systemic Inflammatory Response Syndrome and Organ Dysfunction. Emergency Мed., 128(10): 22141–2224.
  • Petta S., Amato M., Cabibi D. et al. (2010) Visceral adiposity index is associated with histological findings and high viral load in patients with chronic hepatitis C due to genotype 1. Hepatology, 52(5): 1543–1552.
  • Pujia A., Gazzaruso C., Ferro Y. et al. (2016) Individuals with Metabolically Healthy Overweight/Obesity Have Higher Fat Utilization than Metabolically Unhealthy Individuals. Nutrients, 8(1): 2.
  • Pujia A., Mazza E., Ferro Y. et al. (2018) Lipid Oxidation Assessed by Indirect Calorimetry Predicts Metabolic Syndrome and Type 2 Diabetes. Front. Endocrinol. (Lausanne), 9: 806.
  • Sharma A.M, Kushner R.F. (2009) A proposed clinical staging system for obesity. Int. J. Obes. (Lond.), 33(3): 289–295.
  • Somi M.H., Nikniaz Z., Ostadrahimi A. et al. (2019) Is normal body mass index a good indicator of metabolic health in Azar cohort population? J. Cardiovasc. Thorac. Res., 11(1): 53–60.
  • Stefan N., Fritsche A., Schick F., Häring H. (2016) Phenotypes of prediabetes and stratification of cardiometabolic risk. The Lancet, 4(9): 789–798.
  • Stefan N., Haring H.U., Hu F.B., Schulze M.B. (2013) Metabolically healthy obesity: Epidemiology, mechanisms, and clinical implications. Lancet Diabetes Endocrinol., 1: 152–162.
  • Stidsen J.V., Henriksen J.E., Olsen M.H. (2018) Pathophysiology-based phenotyping in type 2 diabetes: a clinical classification tool. Diabetes Metab. Res. Rev., 34(5): e3005.
  • Tang A., Coster A.C., Tonks K.T. (2019) Longitudinal Changes in Insulin Resistance in Normal Weight, Overweight and Obese Individuals. J. Clin. Med., 8(5): E623.
  • Thomas E.L., Frost G., Taylor-Robinson S.D. Bell J.D. (2012) Excess body fat in obese and normal-weight subjects. Nutr. Res. Rev., 25: 150–161.
  • van Wijk D.F., Boekholdt S.M., Arsenault B.J. et al. (2016) C-reactive protein identifies low-risk metabolically healthy obese persons: the European Prospective Investigation of Cancer — Norfolk Prospective Population Study. J. Am. Heart Assoc., 5(6): e002823.
  • Wildman R.P., Muntner P., Reynolds K. et al. (2008) The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering: prevalence and correlates of 2 phenotypes among the US population (NHANES 1999–2004). Arch. Intern. Med., 168: 1617–1624.
  • Worm D., Madsbad S., Hansen D.L. (2019) Metabolic Health in Severely Obese Subjects: A Descriptive Study. Metab. Syndr. Relat. Disord., 17(2): 115–119.
  • Zarzour A., Kim H.W., Weintraub N.L. (2019) Epigenetic Regulation of Vascular Diseases. Arteriosc. Thromb. Vasc. Biol., 39: 984–990.