Potential Biomarkers of the Turnover, Mineralization, and Volume Classification: Results Using NMR Metabolomics in Hemodialysis Patients

Imagem de Miniatura
Arquivos
art_BAPTISTA_Potential_Biomarkers_of_the_Turnover_Mineralization_and_Volume_2020.PDF (779.32 KB)
Citações na Scopus
4
Tipo de produção
article
Data de publicação
2020
DOI
Scopus
Web of Science
Título da Revista
ISSN da Revista
Título do Volume
Editora
BLACKWELL PUBLISHING LTD
Autores
ZERI, A.C.M.
MARTINS, J.S.
Citação
JBMR PLUS, v.4, n.7, article ID e10372, p, 2020
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Bone biopsy is still the gold standard to assess bone turnover (T), mineralization (M), and volume (V) in CKD patients, and serum biomarkers are not able to replace histomorphometry. Recently, metabolomics has emerged as a new technique that could allow for the identification of new biomarkers useful for disease diagnosis or for the understanding of pathophysiologic mechanisms, but it has never been assessed in the chronic kidney disease–mineral and bone disorder (CKD–MBD) scenario. In this study, we investigated the association between serum metabolites and the bone TMV classification in patients with end-stage renal disease by using serum NMR spectroscopy and bone biopsy of 49 hemodialysis patients from a single center in Brazil. High T was identified in 21 patients and was associated with higher levels of dimethylsulfone, glycine, citrate, and N-acetylornithine. The receiver-operating characteristic curve for the combination of PTH and these metabolites provided an area under the receiver-operating characteristic curve (AUC) of 0.86 (0.76 to 0.97). Abnormal M was identified in 30 patients and was associated with lower ethanol. The AUC for age, diabetes mellitus, and ethanol was 0.83 (0.71 to 0.96). Low V was identified in 17 patients and was associated with lower carnitine. The association of age, phosphate, and carnitine provided an AUC of 0.83 (0.70 to 0.96). Although differences among the curves by adding selected metabolites to traditional models were not statistically significant, the accuracy of the diagnosis according to the TMV classification seemed to be improved. This is the first study to evaluate the TMV classification system in relation to the serum metabolome assessed by NMR spectroscopy, showing that selected metabolites may help in the evaluation of bone phenotypes in CKD–MBD. © 2020 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research. © 2020 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.
Palavras-chave
ANALYSIS/QUANTITATION OF BONE, BIOCHEMICAL MARKERS OF BONE TURNOVER, BONE HISTOMORPHOMETRY, BONE MODELING AND REMODELING, DISEASES AND DISORDERS OF/RELATED TO BONE, NMR SPECTROSCOPY
URI
https://observatorio.fm.usp.br/handle/OPI/40225
Referências
  1. Graciolli, F.G., Neves, K.R., Barreto, F., The complexity of chronic kidney disease-mineral and bone disorder across stages of chronic kidney disease (2017) Kidney Int., 91 (6), pp. 1436-1446
  2. Inker, L.A., Grams, M.E., Levey, A.S., Relationship of estimated GFR and albuminuria to concurrent laboratory abnormalities: an individual participant data meta-analysis in a global consortium (2019) Am J Kidney Dis., 73 (2), pp. 206-217
  3. Malluche, H.H., Blomquist, G., Monier-Faugere, M.C., Cantor, T.L., Davenport, D.L., High parathyroid hormone level and osteoporosis predict progression of coronary artery calcification in patients on dialysis (2015) J Am Soc Nephrol., 26 (10), pp. 2534-2544
  4. Nigwekar, S.U., Kroshinsky, D., Nazarian, R.M., Calciphylaxis: risk factors, diagnosis, and treatment (2015) Am J Kidney Dis., 66 (1), pp. 133-146
  5. Wang, M., Obi, Y., Streja, E., Association of Parameters of mineral bone disorder with mortality in patients on hemodialysis according to level of residual kidney function (2017) Clin J Am Soc Nephrol., 12 (7), pp. 1118-1127
  6. KDIGO clinical practice guideline for the diagnosis, evaluation, prevention, and treatment of Chronic Kidney Disease-Mineral and Bone Disorder (CKD-MBD) (2009) Kidney Int Suppl., (113), pp. S1-130
  7. Sprague, S.M., Bellorin-Font, E., Jorgetti, V., Diagnostic accuracy of bone turnover markers and bone histology in patients with CKD treated by dialysis (2016) Am J Kidney Dis., 67 (4), pp. 559-566
  8. Moe, S., Drueke, T., Cunningham, J., Definition, evaluation, and classification of renal osteodystrophy: a position statement from kidney disease: improving global outcomes (KDIGO) (2006) Kidney Int., 69 (11), pp. 1945-1953
  9. Steller Wagner Martins, C., Jorgetti, V., Moyses, R.M.A., Time to rethink the use of bone biopsy to prevent fractures in patients with chronic kidney disease (2018) Curr Opin Nephrol Hypertens., 27 (4), pp. 243-250
  10. You, Y.S., Lin, C.Y., Liang, H.J., Association between the metabolome and low bone mineral density in Taiwanese women determined by (1)H NMR spectroscopy (2014) J Bone Miner Res., 29 (1), pp. 212-222
  11. Miyamoto, T., Hirayama, A., Sato, Y., A serum metabolomics-based profile in low bone mineral density postmenopausal women (2017) Bone., 95, pp. 1-4
  12. Da Silva, M.J., Castro, J.H., Sainz Rueda, N.A., Renal osteodystrophy in the obesity era: is metabolic syndrome relevant? (2017) PLoS One., 12 (7)
  13. Hernandez, J.D., Wesseling, K., Pereira, R., Gales, B., Harrison, R., Salusky, I.B., Technical approach to iliac crest biopsy (2008) Clin J Am Soc Nephrol., 3, pp. S164-S169
  14. Melsen, F., Mosekilde, L., Tetracycline double-labeling of iliac trabecular bone in 41 normal adults (1978) Calcif Tissue Res., 26 (2), pp. 99-102
  15. Dos Reis, L.M., Batalha, J.R., Munoz, D.R., Brazilian normal static bone histomorphometry: effects of age, sex, and race (2007) J Bone Miner Metab., 25 (6), pp. 400-406
  16. Beckonert, O., Keun, H.C., Ebbels, T.M., Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts (2007) Nat Protoc., 2 (11), pp. 2692-2703
  17. Malagrino, P.A., Venturini, G., Yogi, P.S., Metabolomic characterization of renal ischemia and reperfusion in a swine model (2016) Life Sci., 156, pp. 57-67
  18. Salam, S., Gallagher, O., Gossiel, F., Paggiosi, M., Khwaja, A., Eastell, R., Diagnostic accuracy of biomarkers and imaging for bone turnover in renal Osteodystrophy (2018) J Am Soc Nephrol., 29 (5), pp. 1557-1565
  19. Drueke, T.B., Massy, Z.A., Changing bone patterns with progression of chronic kidney disease (2016) Kidney Int., 89 (2), pp. 289-302
  20. Hoppel, C., The role of carnitine in normal and altered fatty acid metabolism (2003) Am J Kidney Dis., 41 (4), pp. S4-12
  21. Hothi, D.K., Geary, D.F., Fisher, L., Chan, C.T., Short-term effects of nocturnal haemodialysis on carnitine metabolism (2006) Nephrol Dial Transplant., 21 (9), pp. 2637-2641
  22. Kalim, S., Wald, R., Yan, A.T., Extended duration nocturnal hemodialysis and changes in plasma metabolite profiles (2018) Clin J Am Soc Nephrol., 13 (3), pp. 436-444
  23. Silverio, R., Laviano, A., Rossi Fanelli, F., Seelaender, M., L-carnitine and cancer cachexia: clinical and experimental aspects (2011) J Cachexia Sarcopenia Muscle., 2 (1), pp. 37-44
  24. Patano, N., Mancini, L., Settanni, M.P., L: -carnitine fumarate and isovaleryl-L: -carnitine fumarate accelerate the recovery of bone volume/total volume ratio after experimetally induced osteoporosis in pregnant mice (2008) Calcif Tissue Int., 82 (3), pp. 221-228
  25. Colucci, S., Mori, G., Vaira, S., L-carnitine and isovaleryl L-carnitine fumarate positively affect human osteoblast proliferation and differentiation in vitro (2005) Calcif Tissue Int., 76 (6), pp. 458-465
  26. Elshaghabee, F.M., Bockelmann, W., Meske, D., Ethanol production by selected intestinal microorganisms and lactic acid bacteria growing under different nutritional conditions (2016) Front Microbiol., 7, p. 47
  27. Gaddini, G.W., Turner, R.T., Grant, K.A., Iwaniec, U.T., Alcohol: a simple nutrient with complex actions on bone in the adult skeleton (2016) Alcohol Clin Exp Res., 40 (4), pp. 657-671
  28. Aljohani, H., Senbanjo, L.T., Chellaiah, M.A., Methylsulfonylmethane increases osteogenesis and regulates the mineralization of the matrix by transglutaminase 2 in SHED cells (2019) PloS One., 14 (12)
  29. Joung, Y.H., Lim, E.J., Darvin, P., MSM enhances GH signaling via the Jak2/STAT5b pathway in osteoblast-like cells and osteoblast differentiation through the activation of STAT5b in MSCs (2012) PLoS One., 7 (10)
  30. Granchi, D., Baldini, N., Ulivieri, F.M., Caudarella, R., Role of citrate in pathophysiology and medical management of bone diseases (2019) Nutrients., 25 (11), p. 11
  31. Chen, H., Wang, Y., Dai, H., Bone and plasma citrate is reduced in osteoporosis (2018) Bone., 114, pp. 189-197
  32. Wu, Q., Lai, X., Zhu, Z., Evidence for chronic kidney disease-mineral and bone disorder associated with metabolic pathway changes (2015) Medicine (Baltimore)., 94 (32)
  33. Kim, J.A., Choi, H.J., Kwon, Y.K., Ryu, D.H., Kwon, T.H., Hwang, G.S., 1H NMR-based metabolite profiling of plasma in a rat model of chronic kidney disease (2014) PLoS One., 9 (1)
  34. Li, L., Wang, C., Yang, H., Metabolomics reveal mitochondrial and fatty acid metabolism disorders that contribute to the development of DKD in T2DM patients (2017) Mol Biosyst., 13 (11), pp. 2392-2400
  35. McMahon, G.M., Hwang, S.J., Clish, C.B., Urinary metabolites along with common and rare genetic variations are associated with incident chronic kidney disease (2017) Kidney Int., 91 (6), pp. 1426-1435
  36. Mutsaers, H.A., Engelke, U.F., Wilmer, M.J., Optimized metabolomic approach to identify uremic solutes in plasma of stage 3-4 chronic kidney disease patients (2013) PLoS One., 8 (8)

Coleções
Artigos e Materiais de Revistas Científicas - HC/ICHC
Artigos e Materiais de Revistas Científicas - HC/InCor
Artigos e Materiais de Revistas Científicas - LIM/09
Artigos e Materiais de Revistas Científicas - LIM/13
Artigos e Materiais de Revistas Científicas - LIM/16
Artigos e Materiais de Revistas Científicas - ODS/03