Advertisement

Clinical impact of abdominal fat distribution measured by 3-D computed tomography volumetry on post-transplant renal function in recipients after living kidney transplantation: a retrospective study

  • Yosuke Mitsui
  • Takuya Sadahira
  • Motoo Araki
  • Yuki Maruyama
  • Koichiro Wada
  • Ryuta Tanimoto
  • Yasuyuki Kobayashi
  • Masami Watanabe
  • Toyohiko Watanabe
  • Yasutomo Nasu
Original Article
  • 30 Downloads

Abstract

Background

Excessive visceral fat may decrease renal function because of metabolic derangements. The aim of this study was to evaluate the impact of abdominal fat distribution on renal function of recipients after kidney transplantation using the visceral adipose tissue (VAT)/subcutaneous adipose tissue (SAT) ratio.

Methods

Seventy-nine patients underwent living kidney transplantation from 2009 to 2017. Patients without a correct measurement of VAT and SAT, follow-up of < 6 months, or with kidney transplant rejection or a virus infection were excluded. VAT and SAT were calculated automatically by 3-D volume analyzer software in recipients prior to living kidney transplantation. Our primary aim was to identify abdominal fat distribution measured by CT associated with renal dysfunction (estimate glomerular filtration rate; eGFR < 45) at 6 month post renal transplantation in recipient.

Results

Fifty-eight living kidney recipients were included in this retrospective study: 30 for the high VAT/SAT ratio group; 28 for the VAT/SAT low group. Multiple logistic regression analysis showed the VAT/SAT ratio and pre-donor eGFR were associated with eGFR < 45 ml/min/1.73 m2. An increase in VAT/SAT ratio was associated independently with the incidence of decreased renal function.

Conclusion

This finding indicates that adipose tissue distribution is an important predictor of the outcome of living kidney transplantation in recipients.

Keywords

Kidney transplantation Renal dysfunction Abdominal fat Computed tomography VAT/SAT ratio 

Notes

Acknowledgements

The authors thank the clinical laboratory technicians of Okayama University Hospital for their technical support.

Compliance with ethical standards

Conflict of interest

The authors have declared that no conflict of interest exists.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Ethical approval

This clinical study was approved by the Okayama University Institutional Review Board prior to study initiation (Registration No. 951).

References

  1. 1.
    Suthanthiran M, Strom TB. Renal transplantation. N Engl J Med. 1994;331:365–76.CrossRefPubMedGoogle Scholar
  2. 2.
    Port FK, Wolfe RA, Mauger EA, Berling DP, Jiang K. Comparison of survival probabilities for dialysis patients vs. cadaveric renal transplant recipients. JAMA. 1993;270:1339–43.CrossRefPubMedGoogle Scholar
  3. 3.
    Hart A, Smith JM, Skeans MA, Gustafson SK, Stewart DE, Cherikh WS, et al. 2014 annual report of the U.S. Organ Procurement and Transplantation Network and the Scientific Registry of Transplant Recipients: kidney. Am J Transplant. 2016;16:11–46.CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Wang JH, Skeans MA, Israni AK. Current status of kidney transplant outcomes: dying to survive. Adv Chronic Kidney Dis. 2016;23:281–6.CrossRefPubMedGoogle Scholar
  5. 5.
    Gabriel MD. Handbook of kidney transplantation. 6th ed. Alphen aan den Rijn: Wolters Kluwer; 2017. pp. 306–8.Google Scholar
  6. 6.
    Hricik DE. Metabolic syndrome in kidney transplantation: management of risk factors. Clin J Am Soc Nephrol. 2011;6:1781–5.CrossRefPubMedGoogle Scholar
  7. 7.
    LaGuardia H, Zhang R. Obesity and metabolic syndrome in kidney transplantation. Curr Hypertens Rep. 2013;15:215–23.CrossRefPubMedGoogle Scholar
  8. 8.
    Alman AC, Smith SR, Eckel RH, Hokanson JE, Burkhardt BR, Sudini PR, et al. The ratio of pericardial to subcutaneous adipose tissues is associated with insulin resistance. Obesity. 2017;25:1284–91.CrossRefPubMedGoogle Scholar
  9. 9.
    Shulman GI. Ectopic fat in insulin resistance, dyslipidemia, and cardiometabolic disease. N Engl J Med. 2014;371:1131–41.CrossRefPubMedGoogle Scholar
  10. 10.
    Rosenquist KJ, Pedley A, Massaro JM, Therkelsen KE, Murabito JM, Hoffmann U, et al. Visceral and subcutaneous fat quality and cardiometabolic risk. J Am Coll Cardiol Imaging. 2013;6:762–71.CrossRefGoogle Scholar
  11. 11.
    Abraham TM, Pedley A, Massaro JM, Hoffmann U, Fox CS. Association between visceral and subcutaneous adipose depots and incident cardiovascular disease risk factors. Circulation. 2015;132:1639–47.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    von Düring ME, Jenssen T, Bollerslev J, Asberg A, Godang K, Hartmann A. Visceral fat is strongly associated with post-transplant diabetes mellitus and glucose metabolism 1 year after kidney transplantation. Clin Transplant. 2017;31:e12869.CrossRefGoogle Scholar
  13. 13.
    Ladeiras-Lopes R, Sampaio F, Bettencourt N, Fontes-Carvalho R, Ferreira N, Leite-Moreira A, Gama V. The ratio between visceral and subcutaneous abdominal fat assessed by computed tomography is an independent predictor of mortality and cardiac events. Rev Esp Cardiol. 2017;70:331–7.CrossRefPubMedGoogle Scholar
  14. 14.
    Lee HH, Kang SK, Yoon YE, Huh KH, Kim MS, Kim SI. Impact of the ratio of visceral to subcutaneous adipose tissue in donor nephrectomy patients. Transplant Proc. 2017;49:940–3.CrossRefPubMedGoogle Scholar
  15. 15.
    Amato MC, Giordano C, Pitrone M, Galluzzo A. Cut-off points of the Visceral Adiposity Index (VAI) identifying a visceral adipose dysfunction associated with cardiometabolic risk in a Caucasian Sicilian population. Lipids Health Dis. 2011;10:183.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Hiuge-Shimizu A, Kishida K, Funahashi T, Ishizaka Y, Oka R, Okada M, et al. Absolute value of visceral fat area measured on computed tomography scans and obesity-related cardiovascular risk factors in large-scale Japanese general population (The VACATION-J study). Ann Med. 2012;44:82–92.CrossRefPubMedGoogle Scholar
  17. 17.
    Kanda Y. Investigation of the freely available easy-to-use software‘EZR’ for medical statistics. Bone Marrow Transplant. 2013;48:452–8.CrossRefPubMedGoogle Scholar
  18. 18.
    Miyazaki Y, DeFronzo RA. Visceral fat dominant distribution in male type 2 diabetic patients is closely related to hepatic insulin resistance, irrespective of body type. Cardiovasc Diabetol. 2009;8:44.CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    He H, Ni Y, Chen J, Zhao Z, Zhong J, Liu D, et al. Sex difference in cardiometabolic risk profile and adiponectin expression in subjects with visceral fat obesity. Transl Res. 2010;155:71–7.CrossRefPubMedGoogle Scholar
  20. 20.
    Kaess BM, Pedley A, Massaro JM, Murabito J, Hoffmann U, Fox CS. The ratio of visceral to subcutaneous fat, a metric of body fat distribution, is a unique correlate of cardiometabolic risk. Diabetologia. 2012;55:2622–30.CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Mitsui Y, Sadahira T, Araki M, Wada K, Tanimoto R, Ariyoshi Y, et al. The assessment of renal cortex and parenchymal volume using automated CT volumetry for predicting renal function after donor nephrectomy. Clin Exp Nephrol. 2018;22:453–8.CrossRefPubMedGoogle Scholar
  22. 22.
    Lentine KL, Delos Santos R, Axelrod D, Schnitzler MA, Brennan DC, Tuttle-Newhall JE. Obesity and kidney transplant candidates: how big is too big for transplantation? Am J Nephrol. 2012;36:575–86.CrossRefPubMedGoogle Scholar
  23. 23.
    Minh-Ha T, Clarence EF, Kamyar KZ, Hirohito I. Kidney transplantation in obese patients. World J Transplant. 2016;6:135.CrossRefGoogle Scholar
  24. 24.
    Bertram LK, Charles BC, Sundaram H, Hricik DE, Kerman RH, Roth D, et al. The evaluation of renal transplant candidates: clinical practice guidelines. Am J Transplant. 2001;2:3–95.Google Scholar
  25. 25.
    Montano-Loza AJ, Mazurak VC, Ebadi M, Meza-Junco J, Sawyer MB, Baracos VE, et al. Visceral adiposity increases risk for hepatocellular carcinoma in male patients with cirrhosis and recurrence after liver transplant. Hepatology. 2018;67:914–23.CrossRefPubMedGoogle Scholar
  26. 26.
    Jabłonowska-Lietz B, Wrzosek M, Włodarczyk M, Nowicka G. New indexes of body fat distribution, Visceral Adiposity Index, Body Adiposity Index, waist-to-height ratio, and metabolic disturbances in the obese. Kardiol Pol. 2017;75:1185–91.CrossRefPubMedGoogle Scholar
  27. 27.
    Raz I, Eldor R, Cernea S, Shafrir E. Diabetes: insulin resistance and derangements in lipid metabolism. Cure through intervention in fat transport and storage. Diabetes Metab Res Rev. 2005;21:3–14.CrossRefPubMedGoogle Scholar
  28. 28.
    Bayer ND, Cochetti PT, Anil Kumar MS, Teal V, Huan Y, Doria C, et al. Association of metabolic syndrome with development of new-onset diabetes after transplantation. Transplantation. 2010;90:861–6.CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    O’Hare AM, Choi AI, Bertenthal D, Bacchetti P, Garg AX, Kaufman JS, et al. Age affects outcomes in chronic kidney disease. J Am Soc Nephrol. 2007;18:2758–65.CrossRefPubMedGoogle Scholar
  30. 30.
    Chen KW, Wu MW, Chen Z, Tai BC, Goh YS, Lata R, et al. Compensatory hypertrophy after living donor nephrectomy. Transplant Proc. 2016;48:716–9.CrossRefPubMedGoogle Scholar
  31. 31.
    Pantik C, Cho YE, Hathaway D, Tolley E, Cashion A. Characterization of body composition and fat mass distribution 1 year after kidney transplantation. Prog Transplant. 2017;27:10–5.CrossRefPubMedGoogle Scholar
  32. 32.
    Kidney Disease. Improving Global Outcomes (KDIGO) Transplant Work Group. KDIGO clinical practice guideline for the care of kidney transplant recipients. Am J Transplant. 2009;9(Suppl 3):S1.Google Scholar

Copyright information

© Japanese Society of Nephrology 2018

Authors and Affiliations

  • Yosuke Mitsui
    • 1
  • Takuya Sadahira
    • 1
  • Motoo Araki
    • 1
  • Yuki Maruyama
    • 1
  • Koichiro Wada
    • 1
  • Ryuta Tanimoto
    • 1
  • Yasuyuki Kobayashi
    • 1
  • Masami Watanabe
    • 1
  • Toyohiko Watanabe
    • 1
  • Yasutomo Nasu
    • 1
  1. 1.Department of UrologyOkayama University Graduate School of Medicine, Dentistry and Pharmaceutical SciencesOkayamaJapan

Personalised recommendations