Ectopic adipose tissue: association of obesity phenotypes with integral metabolic indices of obesity

Aim. To study the relationship and predictive value of integral metabolic indices of obesity in the identification of ectopic obesity.

Material and methods. The study included 326 patients (146 men and 180 women, mean age 61±9 years). Anthropometric data, degree of obesity, body mass index (BMI), waist circumference (WC), sagittal abdominal diameter (SAD), body obesity index (BAI), visceral obesity index (VAI), lipid accumulation index (LAP), triglycerides-glucose index (TyG) was assessed. Perivascular adipose tissue (PVAT) volume, pericardial adipose tissue (PAT) volume and thickness of perirenal fat tissue (PRF) were assessed with CT.

Results. Patients were divided into groups: with isolated ectopic obesity (iEO) (n=17); with isolated abdominal obesity (iAO) (n=74); with EO variants: pericardial (PCO) (n=31), perivascular (PVO) (n=22) or perirenal (PRO) (n=33) with AO; with mixed ectopic obesity and AO (mEO+AO) (n=117), and patients without obesity (n=32). Significantly higher BMI, WC, SAD, and BAI indices were found in individuals with PCO+AO, PRO+AO and mEO+AO. The highest values of LAP were found in groups: PCO+AO, PVO+AO, PRO+AO. There was a correlation between ectopic fat depots and WC (r=0,62 for PAT, r=0,55 for PVAT and r=0,39 for PRF, p=0,01) and SAD (0,429, 0,329 and 0,435, respectively, p=0,01). Correlation was established between PAT, PRF and LAP (0,425 and 0,319, respectively, p=0,01). The highest AUC values>0,8 had models of WC and SAD in identification of PCO (0,801 and 0,801, respectively) and PRO (0,826 and 0,826, respectively). For PCO, the cut-off point of WC was 100,5 cm (specificity 72,9%, sensitivity 70,2%, p=0,000), SAD — 25 cm (specificity 73%, sensitivity 70,2%, p=0,000). For PRO, the cut-off of WC was 101 cm (specificity 71,4%, sensitivity 72,7%, p=0,000), SAD — 25 cm (specificity 71,4%, sensitivity 72,7%, p=0,000).

Conclusion. Еctopic fat depots are related to the risk of metabolic disorders. Potential informative value of simple and accessible integral metabolic indices was established. WC>100,5 cm, SAD>25 cm may indicate to the presence of PCO; WC>101 cm, SAD>25 cm — to the presence of PRO.

1. Neeland IJ, Ross R, Després JP, et al.; International Atherosclerosis Society; International Chair on Cardiometabolic Risk Working Group on Visceral Obesity. Visceral and ectopic fat, atherosclerosis, and cardiometabolic disease: a position statement. Lancet Diabetes Endocrinol. 2019;7(9):715-25. DOI:10.1016/S2213-8587(19)30084-1.

2. Thanassoulis G, Massaro JM, Hoffmann U, et al. Prevalence, distribution, and risk factor correlates of high pericardial and intrathoracic fat depots in the Framingham heart study. Circ Cardiovasc Imaging. 2010;3(5):559-66. DOI:10.1161/CIRCIMAGING.110.956706.

3. Podzolkov VI, Bragina AE, Osadchiy KK, et al. Ectopic obesity in patients without manifested cardiovascular disease: regulations, frequency and clinical characteristics. Ter Arkh. 2022;94(9):1072-7. (In Russ.) DOI:10.26442/00403660.2022.09.201847.

4. Al-Makhamreh HK, Toubasi AA, Al-Harasis LM, et al. Pericardial fat and cardiovascular diseases: A systematic review and meta-analysis. J Evid Based Med. 2023;16(2):178-85. DOI:10.1111/jebm.12542.

5. Antoniades C, Tousoulis D, Vavlukis M, et al. Perivascular adipose tissue as a source of therapeutic targets and clinical biomarkers. Eur Heart J. 2023;44(38):3827-44. DOI:10.1093/eurheartj/ehad484.

6. Amato MC, Pizzolanti G, Torregrossa V, et al. Visceral adiposity index (VAI) is predictive of an altered adipokine profile in patients with type 2 diabetes. PLoS One. 2014;9(3):e91969. DOI:10.1371/JOURNAL.PONE.0091969.

7. Bergman RN, Stefanovski D, Buchanan TA, et al. A better index of body adiposity. Obesity (Silver Spring). 2011;19(5):1083-9. DOI:10.1038/OBY.2011.38.

8. Li Y, Zheng R, Li S, et al. Association Between Four Anthropometric Indexes and Metabolic Syndrome in US Adults. Front Endocrinol (Lausanne). 2022;13:889785. DOI:10.3389/FENDO.2022.889785.

9. Li S, Guo B, Chen H, et al. The role of the triglyceride (triacylglycerol) glucose index in the development of cardiovascular events: a retrospective cohort analysis. Sci Rep. 2019;9(1):7320. DOI:10.1038/S41598-019-43776-5.

10. Shlyakhto EV, Nedogoda SV, Konradi AO, et al. The concept of novel national clinical guidelines on obesity. Russian Journal of Cardiology. 2016;(4):7-13. (In Russ.) DOI:10.15829/1560-4071-2016-4-7-13.

11. Nam GE, Park HS. Perspective on Diagnostic Criteria for Obesity and Abdo­­minal Obesity in Korean Adults. J Obes Metab Syndr. 2018;27(3):134-42. DOI:10.7570/JOMES.2018.27.3.134.

12. Williams B, Mancia G, Spiering W, et al; ESC Scientific Document Group. 2018 ESC/ESH Guidelines for the management of arterial hypertension: The Task Force for the management of arterial hypertension of the European Society of Cardiology (ESC) and the European Society of Hypertension (ESH). Eur Heart J. 2018;39(33):3021-104. DOI:10.1093/EURHEARTJ/EHY339.

13. Dedov II, Shestakova MV, Mayorov AY, et al. Diabetes mellitus type 2 in adults. Diabetes mellitus. 2020;23(2S):4-102. DOI:10.14341/DM12507-9653 (In Russ) DOI:10.14341/DM12507-9653.

14. Mach F, Baigent C, Catapano AL, et al.; ESC Scientific Document Group. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk: The Task Force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS). Eur Heart J. 2020;41(1):111-88. DOI:10.1093/EURHEARTJ/EHZ455.

15. Kahn HS. The lipid accumulation product is better than BMI for identifying diabetes: a population-based comparison. Diabetes Care. 2006;29(1):151-3. DOI:10.2337/DIACARE.29.1.151.

16. Simental-Mendía LE, Rodríguez-Morán M, Guerrero-Romero F. The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects. Metab Syndr Relat Disord. 2008;6(4):299-304. DOI:10.1089/MET.2008.0034.

17. Goldenberg L, Saliba W, Hayeq H, et al. The impact of abdominal fat on abdominal aorta calcification measured on non-enhanced CT. Medicine (Baltimore). 2018;97(49):e13233. DOI:10.1097/MD.0000000000013233.

18. Podzolkov VI, Bragina AE, Osadchiy KK, et al. Pararenal Fat Tissue: Rate of Pararenal Obesity and Relation with Anthropometric Indices of Obesity. Rational Pharmacotherapy in Cardiology. 2022;18(5):516-21 (In Russ.) DOI:10.20996/1819-6446-2022-09-04.

19. Chen X, Shi F, Xiao J, et al. Associations Between Abdominal Obesity Indices and Nonalcoholic Fatty Liver Disease: Chinese Visceral Adiposity Index. Front Endocrinol (Lausanne). 2022;13:831960. DOI:10.3389/FENDO.2022.831960.

20. Gui J, Li Y, Liu H, et al. Obesity- and lipid-related indices as a predictor of obesity metabolic syndrome in a national cohort study. Front Public Health. 2023;11:1073824. DOI:10.3389/FPUBH.2023.1073824.

21. Ding X, Wang X, Wu J, et al. Triglyceride-glucose index and the incidence of atherosclerotic cardiovascular diseases: a meta-analysis of cohort stu­dies. Cardiovasc Diabetol. 2021;20(1):76. DOI:10.1186/S12933-021-01268-9.

22. Saad MAN, Jorge AJL, de Ávila DX, et al. Sagittal abdominal diameter as a marker of visceral obesity in older primary care patients. J Geriatr Cardiol. 2020;17(5):279-83. DOI:10.11909/J.ISSN.1671-5411.2020.05.007.

23. Logacheva IV, Ryazanova TA, Makarova VR, et al. Heart remodeling in overweight and obesity with cardiac comorbidities. Russian Journal of Cardiology. 2017;144(4):40-6 (In Russ.) DOI:10.15829/1560-4071-2017-4-40-46.