Advertisement

Pediatric Nephrology

, Volume 33, Issue 2, pp 315–323 | Cite as

Accumulation of uraemic toxins is reflected only partially by estimated GFR in paediatric patients with chronic kidney disease

  • Evelien Snauwaert
  • Wim Van Biesen
  • Ann Raes
  • Els Holvoet
  • Griet Glorieux
  • Koen Van Hoeck
  • Maria Van Dyck
  • Nathalie Godefroid
  • Raymond Vanholder
  • Sanne Roels
  • Johan Vande Walle
  • Sunny Eloot
Original Article

Abstract

Background

Chronic kidney disease (CKD) in childhood is characterised by the accumulation of uraemic toxins resulting in a multisystem disorder that has a negative impact on quality of life. Childhood CKD is predominantly defined by a decrease in glomerular filtration rate, estimated (eGFR) by a single serum measurement of endogenous biomarkers, e.g. creatinine. The objective of this study was to evaluate how accurately eGFR predicts the concentration of uraemic toxins in a paediatric CKD cohort.

Methods

In 65 children (10.8 [5.1; 14.7] years) with CKD (eGFR 44 [20; 64] mL/min/1.73 m2), serum concentrations were determined of small solutes (uric acid [UA], urea, symmetric dimethylarginine [SDMA], asymmetric dimethylarginine [ADMA]), middle molecules (β2-microglobulin [β2M], complement factor D [CfD]) and protein-bound solutes (p-cresylglucuronide [pCG], hippuric acid, indole acetic acid, indoxyl sulphate [IxS], p-cresylsulfate [pCS] and 3-carboxy-4-methyl-5-propyl-furanpropionic acid [CMPF]). Spearman’s correlation coefficients (r) were calculated to correlate uraemic toxin concentrations with three different eGFR equations, based on either serum creatinine or β2M.

Results

Updated Schwartz eGFR was correlated reasonably well with concentrations of creatinine (r = −0.98), urea (rs = −0.84), SDMA (r = −0.82) and middle molecules CfD and β2M (both rs = −0.90). In contrast, poor correlation coefficients were found for CMPF (rs = −0.32), UA (rs = −0.45), ADMA (rs = −0.47) and pCG (rs = −0.48). The other toxins, all protein-bound, had rs between −0.75 and −0.57. Comparable correlations were found between the three evaluated eGFR equations and uraemic toxin concentrations.

Conclusions

This study demonstrates that eGFR poorly predicts concentrations of protein-bound uraemic toxins, UA and ADMA in childhood CKD. Therefore, eGFR only partially reflects the complexity of the accumulation pattern of uraemic toxins in childhood CKD.

Keywords

Chronic kidney disease Child Uremic toxins Glomerular filtration rate 

Notes

Acknowledgements

This study was funded by the Agency for Innovation by Science and Technology (IWT), from the “Applied Biomedical Research with a Primary Societal Goal” (TBM) program in Flanders (Belgium): UToPaed project, grant number IWT-TBM 150195. The authors are indebted to our laboratory staff Sophie Lobbestael, Tom Mertens and Maria Van Landschoot, and to Sofie Vermeiren, Sofie Eerens, Kimi Lambregts, Imelda Hamels, Ariadne Van Hulle and Julia Versavau for their support.

Compliance with ethical standards

The study protocol was approved by the Ethics Committee and written informed consent was obtained from all individual participants included in the study.

Conflicts of interest

Evelien Snauwaert, Maria Van Dyck, Koen Van Hoeck, Nathalie Godefroid, Raymond Vanholder and Sanne Roels: no conflicts of interest.

Wim Van Biesen: lecture fees, travel and grant support from Fresenius Medical Care, Baxter Gambro, Leo Pharma and Astellas.

Ann Raes: lecture fees and travel support from Ferring Pharmaceuticals.

Griet Glorieux: lecture fees from Fresenius Medical Care and Baxter. Travel support from Baxter.

Johan Vande Walle: paid advisory boards of Alexion, Astellas and Ferring Pharmaceuticals for the last 2 years; lecture fees from Alexion, Astellas and Ferring Pharmaceuticals.

Sunny Eloot: lecture fees and travel support from Fresenius Medical Care.

References

  1. 1.
    McDonald SP, Craig JC, Australian, Australian and New Zealand Paediatric Nephrology Association (2004) Long-term survival of children with end-stage renal disease. N Engl J Med 350:2654–2662Google Scholar
  2. 2.
    Kaspar CD, Bholah R, Bunchman TE (2016) A review of pediatric chronic kidney disease. Blood Purif 41:211–217CrossRefPubMedGoogle Scholar
  3. 3.
    Shroff R, Ledermann S (2009) Long-term outcome of chronic dialysis in children. Pediatr Nephrol 24:463–474CrossRefPubMedGoogle Scholar
  4. 4.
    Pasala S, Carmody JB (2017) How to use...serum creatinine, cystatin C and GFR. Arch Dis Child Educ Pract Ed 102:37–43CrossRefPubMedGoogle Scholar
  5. 5.
    Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group (2013) KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl 3:1–150CrossRefGoogle Scholar
  6. 6.
    Schwartz GJ, Munoz A, Schneider MF, Mak RH, Kaskel F, Warady BA, Furth SL (2009) New equations to estimate GFR in children with CKD. J Am Soc Nephrol 20:629–637CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Hoste L, Dubourg L, Selistre L, De Souza VC, Ranchin B, Hadj-Aissa A, Cochat P, Martens F, Pottel H (2014) A new equation to estimate the glomerular filtration rate in children, adolescents and young adults. Nephrol Dial Transplant 29:1082–1091CrossRefPubMedGoogle Scholar
  8. 8.
    Eloot S, Schepers E, Barreto DV, Barreto FC, Liabeuf S, Van Biesen W, Verbeke F, Glorieux G, Choukroun G, Massy Z, Vanholder R (2011) Estimated glomerular filtration rate is a poor predictor of concentration for a broad range of uremic toxins. Clin J Am Soc Nephrol 6:1266–1273CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Neirynck N, Eloot S, Glorieux G, Barreto DV, Barreto FC, Liabeuf S, Lenglet A, Lemke HD, Massy ZA, Vanholder R (2012) Estimated glomerular filtration rate is a poor predictor of the concentration of middle molecular weight uremic solutes in chronic kidney disease. PLoS One 7:e44201CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Liabeuf S, Barreto DV, Barreto FC, Meert N, Glorieux G, Schepers E, Temmar M, Choukroun G, Vanholder R, Massy ZA, European Uraemic Toxin Work Group (EUTox) (2010) Free p-cresylsulphate is a predictor of mortality in patients at different stages of chronic kidney disease. Nephrol Dial Transplant 25:1183–1191CrossRefPubMedGoogle Scholar
  11. 11.
    Wu IW, Hsu KH, Lee CC, Sun CY, Hsu HJ, Tsai CJ, Tzen CY, Wang YC, Lin CY, Wu MS (2011) P-Cresyl sulphate and indoxyl sulphate predict progression of chronic kidney disease. Nephrol Dial Transplant 26:938–947CrossRefPubMedGoogle Scholar
  12. 12.
    Zoccali C, Benedetto FA, Maas R, Mallamaci F, Tripepi G, Malatino LS, Boger R (2002) Asymmetric dimethylarginine, C-reactive protein, and carotid intima-media thickness in end-stage renal disease. J Am Soc Nephrol 13:490–496CrossRefPubMedGoogle Scholar
  13. 13.
    Schepers E, Glorieux G, Dhondt A, Leybaert L, Vanholder R (2009) Role of symmetric dimethylarginine in vascular damage by increasing ROS via store-operated calcium influx in monocytes. Nephrol Dial Transplant 24:1429–1435CrossRefPubMedGoogle Scholar
  14. 14.
    Schepers E, Barreto DV, Liabeuf S, Glorieux G, Eloot S, Barreto FC, Massy Z, Vanholder R (2011) Symmetric dimethylarginine as a proinflammatory agent in chronic kidney disease. Clin J Am Soc Nephrol 6:2374–2383CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Meijers BK, Bammens B, De Moor B, Verbeke K, Vanrenterghem Y, Evenepoel P (2008) Free p-cresol is associated with cardiovascular disease in hemodialysis patients. Kidney Int 73:1174–1180CrossRefPubMedGoogle Scholar
  16. 16.
    Meijers BK, Claes K, Bammens B, de Loor H, Viaene L, Verbeke K, Kuypers D, Vanrenterghem Y, Evenepoel P (2010) P-cresol and cardiovascular risk in mild-to-moderate kidney disease. Clin J Am Soc Nephrol 5:1182–1189CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Barreto FC, Barreto DV, Liabeuf S, Meert N, Glorieux G, Temmar M, Choukroun G, Vanholder R, Massy ZA, European Uremic Toxin Work G (2009) Serum indoxyl sulfate is associated with vascular disease and mortality in chronic kidney disease patients. Clin J Am Soc Nephrol 4:1551–1558CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Vanholder R, Eloot S, Schepers E, Neirynck N, Glorieux G, Massy Z (2012) An obituary for GFR as the main marker for kidney function? Semin Dial 25:9–14CrossRefPubMedGoogle Scholar
  19. 19.
    Pottel H, Hoste L, Martens F (2012) A simple height-independent equation for estimating glomerular filtration rate in children. Pediatr Nephrol 27:973–979CrossRefPubMedGoogle Scholar
  20. 20.
    Pottel H, Mottaghy FM, Zaman Z, Martens F (2010) On the relationship between glomerular filtration rate and serum creatinine in children. Pediatr Nephrol 25:927–934CrossRefPubMedGoogle Scholar
  21. 21.
    Ikezumi Y, Uemura O, Nagai T, Ishikura K, Ito S, Hataya H, Fujita N, Akioka Y, Kaneko T, Iijima K, Honda M (2015) Beta-2 microglobulin-based equation for estimating glomerular filtration rates in Japanese children and adolescents. Clin Exp Nephrol 19:450–457CrossRefPubMedGoogle Scholar
  22. 22.
    Snauwaert E, Van Biesen W, Raes A, Glorieux G, Van Bogaert V, Van Hoeck K, Coppens M, Roels S, Vande Walle J, Eloot S (2017) Concentrations of representative uremic toxins in a healthy versus non-dialysis chronic kidney disease paediatric population. Nephrol Dial Transplant.  https://doi.org/10.1093/ndt/gfx224
  23. 23.
    Cleveland WS, Devlin SJ (1988) Locally weighted regression—an approach to regression-analysis by local fitting. J Am Stat Assoc 83:596–610CrossRefGoogle Scholar
  24. 24.
    R Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/ Google Scholar
  25. 25.
    Fliser D (2005) Asymmetric dimethylarginine (ADMA): the silent transition from an 'uraemic toxin' to a global cardiovascular risk molecule. Eur J Clin Investig 35:71–79CrossRefGoogle Scholar
  26. 26.
    Fliser D, Kielstein JT, Haller H, Bode-Boger SM (2003) Asymmetric dimethylarginine: a cardiovascular risk factor in renal disease? Kidney Int Suppl (84):S37–S40Google Scholar
  27. 27.
    Kielstein JT, Boger RH, Bode-Boger SM, Frolich JC, Haller H, Ritz E, Fliser D (2002) Marked increase of asymmetric dimethylarginine in patients with incipient primary chronic renal disease. J Am Soc Nephrol 13:170–176PubMedGoogle Scholar
  28. 28.
    Schepers E, Speer T, Bode-Boger SM, Fliser D, Kielstein JT (2014) Dimethylarginines ADMA and SDMA: the real water-soluble small toxins? Semin Nephrol 34:97–105CrossRefPubMedGoogle Scholar
  29. 29.
    Furth SL, Abraham AG, Jerry-Fluker J, Schwartz GJ, Benfield M, Kaskel F, Wong C, Mak RH, Moxey-Mims M, Warady BA (2011) Metabolic abnormalities, cardiovascular disease risk factors, and GFR decline in children with chronic kidney disease. Clin J Am Soc Nephrol 6:2132–2140CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Schaefer F, Doyon A, Azukaitis K, Bayazit A, Canpolat N, Duzova A, Niemirska A, Sozeri B, Thurn D, Anarat A, Ranchin B, Litwin M, Caliskan S, Candan C, Baskin E, Yilmaz E, Mir S, Kirchner M, Sander A, Haffner D, Melk A, Wuhl E, Shroff R, Querfeld U (2017) Cardiovascular phenotypes in children with CKD: the 4C study. Clin J Am Soc Nephrol 12:19–28CrossRefPubMedGoogle Scholar
  31. 31.
    Bonthuis M, van Stralen KJ, Verrina E, Edefonti A, Molchanova EA, Hokken-Koelega AC, Schaefer F, Jager KJ (2012) Use of national and international growth charts for studying height in European children: development of up-to-date European height-for-age charts. PLoS One 7:e42506CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Vanholder RC, Eloot S, Glorieux GL (2016) Future avenues to decrease uremic toxin concentration. Am J Kidney Dis 67:664–676CrossRefPubMedGoogle Scholar
  33. 33.
    Miyamoto Y, Watanabe H, Noguchi T, Kotani S, Nakajima M, Kadowaki D, Otagiri M, Maruyama T (2011) Organic anion transporters play an important role in the uptake of p-cresyl sulfate, a uremic toxin, in the kidney. Nephrol Dial Transplant 26:2498–2502CrossRefPubMedGoogle Scholar
  34. 34.
    Enomoto A, Takeda M, Tojo A, Sekine T, Cha SH, Khamdang S, Takayama F, Aoyama I, Nakamura S, Endou H, Niwa T (2002) Role of organic anion transporters in the tubular transport of indoxyl sulfate and the induction of its nephrotoxicity. J Am Soc Nephrol 13:1711–1720CrossRefPubMedGoogle Scholar
  35. 35.
    Deguchi T, Kusuhara H, Takadate A, Endou H, Otagiri M, Sugiyama Y (2004) Characterization of uremic toxin transport by organic anion transporters in the kidney. Kidney Int 65:162–174CrossRefPubMedGoogle Scholar
  36. 36.
    Deguchi T, Ohtsuki S, Otagiri M, Takanaga H, Asaba H, Mori S, Terasaki T (2002) Major role of organic anion transporter 3 in the transport of indoxyl sulfate in the kidney. Kidney Int 61:1760–1768CrossRefPubMedGoogle Scholar
  37. 37.
    Lowenstein J, Grantham JJ (2016) The rebirth of interest in renal tubular function. Am J Physiol Renal Physiol 310:F1351–F1355CrossRefPubMedGoogle Scholar
  38. 38.
    Termorshuizen F, Dekker FW, van Manen JG, Korevaar JC, Boeschoten EW, Krediet RT, Group NS (2004) Relative contribution of residual renal function and different measures of adequacy to survival in hemodialysis patients: an analysis of the Netherlands cooperative study on the adequacy of dialysis (NECOSAD)-2. J Am Soc Nephrol 15:1061–1070CrossRefPubMedGoogle Scholar
  39. 39.
    Bargman JM, Thorpe KE, Churchill DN, Group CPDS (2001) Relative contribution of residual renal function and peritoneal clearance to adequacy of dialysis: a reanalysis of the CANUSA study. J Am Soc Nephrol 12:2158–2162PubMedGoogle Scholar
  40. 40.
    Rubin MI, Bruck E, Rapoport M, Snively M, McKay H, Baumler A (1949) Maturation of renal function in childhood: clearance studies. J Clin Invest 28:1144–1162CrossRefPubMedCentralGoogle Scholar
  41. 41.
    Calcagno PL, Rubin MI (1963) Renal extraction of para-aminohippurate in infants and children. J Clin Invest 42:1632–1639CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Evenepoel P, Poesen R, Meijers B (2016) The gut-kidney axis. Pediatr Nephrol.  https://doi.org/10.1007/s00467-016-3527-x Google Scholar
  43. 43.
    Cummings JH, Hill MJ, Jivraj T, Houston H, Branch WJ, Jenkins DJ (1979) The effect of meat protein and dietary fiber on colonic function and metabolism. I. Changes in bowel habit, bile acid excretion, and calcium absorption. Am J Clin Nutr 32:2086–2093CrossRefPubMedGoogle Scholar
  44. 44.
    Cummings JH, Hill MJ, Bone ES, Branch WJ, Jenkins DJ (1979) The effect of meat protein and dietary fiber on colonic function and metabolism. II. Bacterial metabolites in feces and urine. Am J Clin Nutr 32:2094–2101CrossRefPubMedGoogle Scholar
  45. 45.
    Gabriele S, Sacco R, Altieri L, Neri C, Urbani A, Bravaccio C, Riccio MP, Iovene MR, Bombace F, De Magistris L, Persico AM (2016) Slow intestinal transit contributes to elevate urinary p-cresol level in Italian autistic children. Autism Res 9:752–759CrossRefPubMedGoogle Scholar

Copyright information

© IPNA 2017

Authors and Affiliations

  • Evelien Snauwaert
    • 1
  • Wim Van Biesen
    • 2
  • Ann Raes
    • 3
  • Els Holvoet
    • 2
  • Griet Glorieux
    • 2
  • Koen Van Hoeck
    • 4
  • Maria Van Dyck
    • 5
  • Nathalie Godefroid
    • 6
  • Raymond Vanholder
    • 2
  • Sanne Roels
    • 7
  • Johan Vande Walle
    • 3
  • Sunny Eloot
    • 2
  1. 1.Department of Paediatrics and Medical Genetics, Faculty of Medicine and Health SciencesGhent UniversityGhentBelgium
  2. 2.Department of NephrologyGhent University HospitalGhentBelgium
  3. 3.Department of Paediatric NephrologyGhent University HospitalGhentBelgium
  4. 4.Department of Paediatric NephrologyAntwerp University HospitalAntwerpBelgium
  5. 5.Department of Paediatric NephrologyUniversity Hospital LeuvenLeuvenBelgium
  6. 6.Department of Paediatric NephrologyUniversity Hospital Saint-LucBrusselsBelgium
  7. 7.Department of Data Analysis, Faculty of Psychology and PedagogyGhent UniversityGhentBelgium

Personalised recommendations