, Volume 62, Issue 1, pp 169–177 | Cite as

Prospective associations of circulating adipocyte fatty acid-binding protein levels with risks of renal outcomes and mortality in type 2 diabetes

  • Chi Ho Lee
  • Chloe Y. Y. Cheung
  • Yu Cho Woo
  • David T. W. Lui
  • Michele M. A. Yuen
  • Carol H. Y. Fong
  • Wing Sun Chow
  • Amin Xu
  • Karen S. L. LamEmail author



Elevated circulating adipocyte fatty acid-binding protein (AFABP) levels have been found to correlate with diabetic nephropathy staging in cross-sectional studies. However, it remains unclear whether these higher serum levels reflect a role of AFABP in the development of diabetic kidney disease (DKD), or simply result from its impaired renal clearance in DKD. Here we investigated prospectively the prognostic importance of serum AFABP level in the development of adverse renal outcomes in a large clinic-based cohort of participants with type 2 diabetes.


Baseline serum AFABP levels were measured in 5454 Chinese participants from the Hong Kong West Diabetes Registry. The association between circulating AFABP levels and incident adverse renal outcomes—defined as a composite endpoint of a sustained 40% decline in eGFR, end-stage renal disease requiring renal replacement therapy or kidney transplantation, or renal deaths—was evaluated using multivariable Cox regression analysis.


Over a median follow-up of 5 years, 754 of the 5454 participants developed incident adverse renal outcomes. Elevated circulating AFABP levels were independently associated with incident adverse renal outcomes (HR 1.43, 95% CI 1.31, 1.57, p < 0.001) after adjustments for conventional risk factors for DKD progression. Importantly, the prognostic role of serum AFABP was independent of the baseline albuminuria status or eGFR levels of the study participants.


Circulating AFABP levels were predictive of incident adverse renal outcomes, even in participants with relatively well-preserved kidney function at baseline, suggesting its potential to be a useful marker for early risk stratification in DKD.


Adipocyte fatty acid-binding protein Microvascular complications Nephropathy Prediction model Type 2 diabetes mellitus 



ACE inhibitor


Adipocyte fatty acid-binding protein


Angiotensin II receptor blocker


Diabetic kidney disease


Endoplasmic reticulum


End-stage renal disease




High-sensitivity C-reactive protein


Integrated discrimination improvement


c-Jun NH2-terminal kinase


Kidney injury molecule-1




Net reclassification index


Tumour necrosis factor receptor


Waist circumference



We thank RLC Wong (Department of Medicine, University of Hong Kong, Hong Kong) for her technical assistance in the measurements of serum AFABP and hsCRP levels. Some of the data were presented as an abstract at the International Diabetes Federation Western Pacific Region Congress (IDF-WPR) in 2014.

Contribution statement

CHL contributed to analysis of the data and writing of the manuscript. CYYC, YCW, DTWL, MMAY, WSC and AX contributed to the interpretation of data and revising the manuscript. CHYF contributed to analysis of the data and writing of the manuscript. KSLL initiated and supervised the study, critically revised for important intellectual content and is the guarantor of this work, and as such has had full access to all study data and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors have approved the final version.


This work was supported by the Health and Medical Research Fund (reference 14150781).

Duality of interest

The authors declare that there is no duality of interest associated with this manuscript.

Supplementary material

125_2018_4742_MOESM1_ESM.pdf (184 kb)
ESM (PDF 184 kb)


  1. 1.
    Afkarian M, Zelnick LR, Hall YN et al (2016) Clinical manifestations of kidney disease among US adults with diabetes, 1988-2014. JAMA 316:602–610. CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Zhang L, Long J, Jiang W et al (2016) Trends in chronic kidney disease in China. N Engl J Med 375:905–906. CrossRefPubMedGoogle Scholar
  3. 3.
    Ninomiya T, Perkovic V, de Galan BE et al (2009) Albuminuria and kidney function independently predict cardiovascular and renal outcomes in diabetes. J Am Soc Nephrol 20:1813–1821. CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Afkarian M, Sachs MC, Kestenbaum B et al (2013) Kidney disease and increased mortality risk in type 2 diabetes. J Am Soc Nephrol 24:302–308. CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Mogensen CE (1984) Microalbuminuria predicts clinical proteinuria and early mortality in maturity-onset diabetes. N Engl J Med 310:356–360. CrossRefPubMedGoogle Scholar
  6. 6.
    Berrut G, Bouhanick B, Fabbri P et al (1997) Microalbuminuria as a predictor of a drop in glomerular filtration rate in subjects with non-insulin-dependent diabetes mellitus and hypertension. Clin Nephrol 48:92–97PubMedGoogle Scholar
  7. 7.
    Retnakaran R, Cull CA, Thorne KI, Adler AI, Holman RR, UKPDS Study Group (2006) Risk factors for renal dysfunction in type 2 diabetes: U.K. Prospective Diabetes Study 74. Diabetes 55:1832–1839. CrossRefPubMedGoogle Scholar
  8. 8.
    Coca SG, Nadkarni GN, Huang Y et al (2017) Plasma biomarkers and kidney function decline in early and established diabetic kidney disease. J Am Soc Nephrol 28:2786–2793. CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Boord JB, Fazio S, Linton MF (2002) Cytoplasmic fatty acid-binding proteins: emerging roles in metabolism and atherosclerosis. Curr Opin Lipidol 13:141–147. CrossRefPubMedGoogle Scholar
  10. 10.
    Makowski L, Boord JB, Maeda K et al (2001) Lack of macrophage fatty-acid-binding protein aP2 protects mice deficient in apolipoprotein E against atherosclerosis. Nat Med 7:699–705. CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Hui X, Li H, Zhou Z et al (2010) Adipocyte fatty acid-binding protein modulates inflammatory responses in macrophages through a positive feedback loop involving c-Jun NH2-terminal kinases and activator protein-1. J Biol Chem 285:10273–10280. CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Xu A, Wang Y, Xu JY et al (2006) Adipocyte fatty acid-binding protein is a plasma biomarker closely associated with obesity and metabolic syndrome. Clin Chem 52:405–413. CrossRefPubMedGoogle Scholar
  13. 13.
    Xu A, Tso AW, Cheung BM et al (2007) Circulating adipocyte-fatty acid binding protein levels predict the development of the metabolic syndrome: a 5-year prospective study. Circulation 115:1537–1543. CrossRefPubMedGoogle Scholar
  14. 14.
    Tso AW, Xu A, Sham PC et al (2007) Serum adipocyte fatty acid binding protein as a new biomarker predicting the development of type 2 diabetes: a 10-year prospective study in a Chinese cohort. Diabetes Care 30:2667–2672. CrossRefPubMedGoogle Scholar
  15. 15.
    Nowak C, Sundstrom J, Gustafsson S et al (2016) Protein biomarkers for insulin resistance and type 2 diabetes risk in two large community cohorts. Diabetes 65:276–284. CrossRefPubMedGoogle Scholar
  16. 16.
    Chow WS, Tso AW, Xu A et al (2013) Elevated circulating adipocyte-fatty acid binding protein levels predict incident cardiovascular events in a community-based cohort: a 12-year prospective study. J Am Heart Assoc 2:e004176CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Djousse L, Bartz TM, Ix JH et al (2013) Fatty acid-binding protein 4 and incident heart failure: the Cardiovascular Health Study. Eur J Heart Fail 15:394–399. CrossRefPubMedGoogle Scholar
  18. 18.
    Lee CH, Cheung CYY, Woo YC et al (2018) Circulating adipocyte fatty acid-binding protein concentrations predict multiple mortality outcomes among men and women with diabetes. Clin Chem.
  19. 19.
    Cabre A, Lazaro I, Girona J et al (2008) Plasma fatty acid-binding protein 4 increases with renal dysfunction in type 2 diabetic patients without microalbuminuria. Clin Chem 54:181–187. CrossRefPubMedGoogle Scholar
  20. 20.
    Yeung DC, Xu A, Tso AW et al (2009) Circulating levels of adipocyte and epidermal fatty acid-binding proteins in relation to nephropathy staging and macrovascular complications in type 2 diabetic patients. Diabetes Care 32:132–134. CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Toruner F, Altinova AE, Akturk M et al (2011) The relationship between adipocyte fatty acid binding protein-4, retinol binding protein-4 levels and early diabetic nephropathy in patients with type 2 diabetes. Diabetes Res Clin Pract 91:203–207. CrossRefPubMedGoogle Scholar
  22. 22.
    Sommer G, Ziegelmeier M, Bachmann A et al (2008) Serum levels of adipocyte fatty acid-binding protein (AFABP) are increased in chronic haemodialysis (CD). Clin Endocrinol 69:901–905. CrossRefGoogle Scholar
  23. 23.
    Levey AS, Stevens LA, Schmid CH et al (2009) A new equation to estimate glomerular filtration rate. Ann Intern Med 150:604–612. CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    (2013) Chapter 2: definition, identification, and prediction of CKD progression. Kidney Int Suppl 3: 63–72Google Scholar
  25. 25.
    Ong KL, Rye KA, O’Connell R et al (2012) Long-term fenofibrate therapy increases fibroblast growth factor 21 and retinol-binding protein 4 in subjects with type 2 diabetes. J Clin Endocrinol Metab 97:4701–4708. CrossRefPubMedGoogle Scholar
  26. 26.
    Hao Y, Ma X, Luo Y et al (2014) Serum adipocyte fatty acid binding protein levels are positively associated with subclinical atherosclerosis in Chinese pre- and postmenopausal women with normal glucose tolerance. J Clin Endocrinol Metab 99:4321–4327. CrossRefPubMedGoogle Scholar
  27. 27.
    Neal B, Perkovic V, Mahaffey KW et al (2017) Canagliflozin and cardiovascular and renal events in type 2 diabetes. N Engl J Med 377:644–657. CrossRefPubMedGoogle Scholar
  28. 28.
    Niewczas MA, Gohda T, Skupien J et al (2012) Circulating TNF receptors 1 and 2 predict ESRD in type 2 diabetes. J Am Soc Nephrol 23:507–515. CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Berhane AM, Weil EJ, Knowler WC, Nelson RG, Hanson RL (2011) Albuminuria and estimated glomerular filtration rate as predictors of diabetic end-stage renal disease and death. Clin J Am Soc Nephrol 6:2444–2451. CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Ebert T, Hopf LM, Wurst U et al (2014) Circulating adipocyte fatty acid binding protein is increased in chronic and acute renal dysfunction. Nutr Metab Cardiovasc Dis 24:1027–1034. CrossRefPubMedGoogle Scholar
  31. 31.
    Van JA, Scholey JW, Konvalinka A (2017) Insights into diabetic kidney disease using urinary proteomics and bioinformatics. J Am Soc Nephrol 28:1050–1061. CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Nguyen D, Ping F, Mu W, Hill P, Atkins RC, Chadban SJ (2006) Macrophage accumulation in human progressive diabetic nephropathy. Nephrology (Carlton) 11:226–231. CrossRefGoogle Scholar
  33. 33.
    Navarro JF, Milena FJ, Mora C, Leon C, Garcia J (2006) Renal pro-inflammatory cytokine gene expression in diabetic nephropathy: effect of angiotensin-converting enzyme inhibition and pentoxifylline administration. Am J Nephrol 26:562–570. CrossRefPubMedGoogle Scholar
  34. 34.
    Wada T, Furuichi K, Sakai N et al (2000) Up-regulation of monocyte chemoattractant protein-1 in tubulointerstitial lesions of human diabetic nephropathy. Kidney Int 58:1492–1499. CrossRefPubMedGoogle Scholar
  35. 35.
    Kwok KH, Cheng KK, Hoo RL, Ye D, Xu A, Lam KS (2016) Adipose-specific inactivation of JNK alleviates atherosclerosis in apoE-deficient mice. Clin Sci (Lond) 130:2087–2100. CrossRefGoogle Scholar
  36. 36.
    Eklund CM (2009) Proinflammatory cytokines in CRP baseline regulation. Adv Clin Chem 48:111–136CrossRefPubMedGoogle Scholar
  37. 37.
    Tanaka M, Furuhashi M, Okazaki Y et al (2014) Ectopic expression of fatty acid-binding protein 4 in the glomerulus is associated with proteinuria and renal dysfunction. Nephron Clin Pract 128:345–351. CrossRefPubMedGoogle Scholar
  38. 38.
    Yao F, Li Z, Ehara T et al (2015) Fatty acid-binding protein 4 mediates apoptosis via endoplasmic reticulum stress in mesangial cells of diabetic nephropathy. Mol Cell Endocrinol 411:232–242. CrossRefPubMedGoogle Scholar
  39. 39.
    Perkovic V, Zeeuw D, Mahaffey KW et al (2018) Canagliflozin and renal outcomes in type 2 diabetes: results from the CANVAS Program randomised clinical trials. Lancet Diabetes Endocrinol 6:691–704. CrossRefPubMedGoogle Scholar
  40. 40.
    Gregg EW, Cheng YJ, Srinivasan M et al (2018) Trends in cause-specific mortality among adults with and without diagnosed diabetes in the USA: an epidemiological analysis of linked national survey and vital statistics data. Lancet 391:2430–2440. CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Chi Ho Lee
    • 1
    • 2
  • Chloe Y. Y. Cheung
    • 1
  • Yu Cho Woo
    • 1
  • David T. W. Lui
    • 1
  • Michele M. A. Yuen
    • 1
  • Carol H. Y. Fong
    • 1
  • Wing Sun Chow
    • 1
  • Amin Xu
    • 1
    • 2
    • 3
  • Karen S. L. Lam
    • 1
    • 2
    • 3
    Email author
  1. 1.Department of MedicineThe University of Hong Kong, Queen Mary HospitalHong KongPeople’s Republic of China
  2. 2.Research Center of Heart, Brain, Hormone and Healthy AgingThe University of Hong KongHong KongPeople’s Republic of China
  3. 3.State Key Laboratory of Pharmaceutical BiotechnologyThe University of Hong KongHong KongPeople’s Republic of China

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