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Estimating the concentration of urea and creatinine in the human serum of normal and dialysis patients through Raman spectroscopy

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Abstract

Urea and creatinine are commonly used as biomarkers of renal function. Abnormal concentrations of these biomarkers are indicative of pathological processes such as renal failure. This study aimed to develop a model based on Raman spectroscopy to estimate the concentration values of urea and creatinine in human serum. Blood sera from 55 clinically normal subjects and 47 patients with chronic kidney disease undergoing dialysis were collected, and concentrations of urea and creatinine were determined by spectrophotometric methods. A Raman spectrum was obtained with a high-resolution dispersive Raman spectrometer (830 nm). A spectral model was developed based on partial least squares (PLS), where the concentrations of urea and creatinine were correlated with the Raman features. Principal components analysis (PCA) was used to discriminate dialysis patients from normal subjects. The PLS model showed r = 0.97 and r = 0.93 for urea and creatinine, respectively. The root mean square errors of cross-validation (RMSECV) for the model were 17.6 and 1.94 mg/dL, respectively. PCA showed high discrimination between dialysis and normality (95 % accuracy). The Raman technique was able to determine the concentrations with low error and to discriminate dialysis from normal subjects, consistent with a rapid and low-cost test.

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References

  1. Alpern RJ, Caplan MJ, Moe OW (2013) Seldin and Giebisch’s the kidney—physiology and pathophysiology, vol 1. Academic Press, Waltham

    Google Scholar 

  2. About chronic kidney disease: a guide for patients and their families (2010) National Kidney Foundation. http://www.kidney.org/atoz/atozcopy.cfm?pdflink=11-50-0160_jai_patbro_aboutckdv2lr.pdf. Accessed 10 Mar 2014.

  3. Bastos MG, Bregman R, Kirsztajn GM (2010) Chronic kidney diseases: common and harmful, but also preventable and treatable. Rev Assoc Med Bras 56:248–53

    Article  PubMed  Google Scholar 

  4. Von Schacky C (2009) Cardiovascular disease prevention and treatment. Prostaglandins Leukot Essent Fatty Acids 81(2-3):193–8

    Article  Google Scholar 

  5. Centers for Disease Control (CDC) (1992) Incidence of treatment for end-stage renal disease attributed to diabetes mellitus, by race/ethnicity-Colorado, 1982-1989. Morb Mortal Wkly Rep 41(44):845–8

    Google Scholar 

  6. Haase-Fielitz A, Bellomo R, Devarajan P et al (2009) Novel and conventional serum biomarkers predicting acute kidney injury in adult cardiac surgery—a prospective cohort study. Crit Care Med 37(2):553–60

    Article  CAS  PubMed  Google Scholar 

  7. Gabriel IC, Nishidal SK, Kirsztajn GM (2011) Serum cystatin C: a practical alternative for renal function evaluation? J Bras Nefrol 33:261–7

    Article  PubMed  Google Scholar 

  8. Perez-Guaita D, Ventura-Gayete P-RC, Sancho-Andreu M, Garrigues S, de la Guardia M (2013) Evaluation of infrared spectroscopy as a screening tool for serum analysis: impact of the nature of samples included in the calibration set. Microchem J 106:202–11

    Article  CAS  Google Scholar 

  9. Prat R, Galeano I, Lucas A et al (2010) Relative value of magnetic resonance spectroscopy, magnetic resonance perfusion, and 2-(18F) fluoro-2-deoxy-D-glucose positron emission tomography for detection of recurrence or grade increase in gliomas. J Clin Neurosci 17(1):50–3

    Article  CAS  PubMed  Google Scholar 

  10. Pilotto S, Pacheco MTT, Silveira L, Villaverde AB, Zângaro RA (2001) Analysis of near-infrared Raman spectroscopy as a new technique for a transcutaneous non-invasive diagnosis of blood components. Lasers Med Sci 16(1):2–9

    Article  CAS  PubMed  Google Scholar 

  11. Rohleder D, Kocherscheidt G, Gerber K et al (2005) Comparison of mid-infrared and Raman spectroscopy in the quantitative analysis of serum. J Biomed Opt 10(3):031108

    Article  CAS  PubMed  Google Scholar 

  12. Chaiken J, Finney WF, Knudson PE et al (2001) Noninvasive in-vivo tissue-modulated Raman spectroscopy of human blood: microcirculation and viscosity effects. Proc. SPIE 4254, Biomedical Diagnostic, Guidance, and Surgical-Assist Systems III, 106. doi: 10.1117/12.427952.

  13. Berger AJ, Koo TW, Itzkan I, Horowitz G, Feld MS (1999) Multicomponent blood analysis by near-infrared Raman spectroscopy. Appl Opt 38(13):2916–26

    Article  CAS  PubMed  Google Scholar 

  14. Rohleder D, Kiefer W, Petrich W (2004) Quantitative analysis of serum and serum ultrafiltrate by means of Raman spectroscopy. Analyst 129(10):906–11

    Article  CAS  PubMed  Google Scholar 

  15. Qi D, Berger AJ (2007) Chemical concentration measurement in blood serum and urine samples using liquid-core optical fiber Raman spectroscopy. Appl Opt 46(10):1726–34

    Article  CAS  PubMed  Google Scholar 

  16. Hanlon EB, Manoharan R, Koo TW et al (2000) Prospects for in vivo Raman spectroscopy. Phys Med Biol 45(2):R1–59

    Article  CAS  PubMed  Google Scholar 

  17. González-Solís JL, Martínez-Espinosa JC, Torres-González LA, Aguilar-Lemarroy A, Jave-Suárez LF, Palomares-Anda P (2014) Cervical cancer detection based on serum sample Raman spectroscopy. Lasers Med Sci 29(3):979–85

    Article  PubMed  Google Scholar 

  18. Premasiri WR, Clarke RH, Womble ME (2001) Urine analysis by laser Raman spectroscopy. Laser Surg Med 28:330–4

    Article  CAS  Google Scholar 

  19. Smith E, Dent G (2005) Modern Raman spectroscopy: a practical approach. John Wiley & Sons, Chiclester

    Google Scholar 

  20. Guimarães AE, Pacheco MTT, Silveira L et al (2006) Near infrared Raman spectroscopy (NIRS): a technique for doping control. Spectrosc Int J 20:185–94

    Article  Google Scholar 

  21. Silveira L, Sathaiah S, Zângaro RA, Pacheco MT, Chavantes MC, Pasqualucci CA (2002) Correlation between near-infrared Raman spectroscopy and the histopathological analysis of atherosclerosis in human coronary arteries. Laser Surg Med 30:290–7

    Article  Google Scholar 

  22. Bispo JAM, de Sousa Vieira EE, Silveira L, Fernandes AB (2013) Correlating the amount of urea, creatinine, and glucose in urine from patients with diabetes mellitus and hypertension with the risk of developing renal lesions by means of Raman spectroscopy and principal component analysis. J Biomed Opt 18(8):87004. doi:10.1117/1.JBO.18.8.087004

    Article  PubMed  Google Scholar 

  23. Enejder AM, Koo TW, Oh J et al (2002) Blood analysis by Raman spectroscopy. Opt Lett 27:2004–6

    Article  CAS  PubMed  Google Scholar 

  24. Saade J, Pacheco MTT, Rodrigues MR, Silveira L (2008) Identification of hepatitis C in human blood serum by near-infrared Raman spectroscopy. Spectroscopy Int J 22:387–95. doi:10.3233/SPE-2008-0344

    Article  CAS  Google Scholar 

  25. Ito H, Inoue H, Hasegawa K et al (2014) Use of surface-enhanced Raman scattering for detection of cancer-related serum-constituents in gastrointestinal cancer patients. Nanomedicine 10(3):599–608

    CAS  PubMed  Google Scholar 

  26. Chatfield C, Collins AJ (1980) Introduction to multivariate statistics. Chapman & Hall, London

    Book  Google Scholar 

  27. Bueno Filho AC, Silveira L, Yanai ALS, Fernandes AB (2015) Raman spectroscopy for a rapid diagnosis of sickle cell disease in human blood samples: a preliminary study. Lasers Med Sci 30(1):247–53

    Article  Google Scholar 

  28. Bodanese B, Silveira FL, Zângaro RA, Pacheco MTT, Pasqualucci CA, Silveira L (2012) Discrimination of basal cell carcinoma and melanoma from normal skin biopsies in vitro through Raman spectroscopy and principal component analysis. Photomed Laser Surg 30(7):381–7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Lui H, Zhao J, McLean D, Zeng H (2012) Real-time Raman spectroscopy for in vivo skin cancer diagnosis. Cancer Res 72(10):2491–500

    Article  CAS  PubMed  Google Scholar 

  30. Silveira FL, Pacheco MTT, Bodanese B, Pasqualucci CA, Zângaro RA, Silveira L (2015) Discrimination of non-melanoma skin lesions from non-tumor human skin tissues in vivo using Raman spectroscopy and multivariate statistics. Lasers Surg Med 47(1):6–16

    Article  PubMed  Google Scholar 

  31. Chowdary MV, Kumar KK, Kurien J, Mathew S, Krishna CM (2006) Discrimination of normal, benign, and malignant breast tissues by Raman spectroscopy. Biopolymers 83(5):556–69

    Article  CAS  PubMed  Google Scholar 

  32. Biosystems S/A (2011) UREA/BUN - UV (Urease/Glutamato Deshidrogenase). http://www.imunotech.com.br/bulas/ureia.pdf. Accessed 12 Mar 2014.

  33. Eurotech Prod. Laboratoriais e Serviços (2012) Creatinina “Mod. Jaffe”. Reagente diagnóstico para determinação quantitativa in vitro da creatinina em soro humano, plasma ou urina em sistemas fotométricos. http://www.imunotech.com.br/bulas/rea_5073240e63694.pdf. Accessed 12 Mar 2014.

  34. Silveira L, Silveira FL, Bodanese B, Zângaro RA, Pacheco MT (2012) Discriminating model for diagnosis of basal cell carcinoma and melanoma in vitro based on the Raman spectra of selected biochemicals. J Biomed Opt 17:077003

    Article  PubMed  Google Scholar 

  35. Martins JPA, Ferreira M (2013) QSAR modeling: a new open source computational package to generate and validate QSAR model. Quim Nov. 36(4):554–60. doi:10.1590/S0100-40422013000400013

  36. Geladi P, Kowalski BR (1986) Partial least-squares regression: a tutorial. Anal Chim Acta 185:1–17

    Article  CAS  Google Scholar 

  37. Brereton RG (2000) Introduction to multivariate calibration in analytical chemistry. Analyst 125(11):2125–54

    Article  CAS  Google Scholar 

  38. Nurunnabi AAM, Hadi AS, Imon AHMR (2014) Procedures for the identification of multiple influential observations in linear regression. J Appl Stat 41(6):1315–31

    Article  Google Scholar 

  39. Black PE (2004) Euclidean Distance. U.S. National Institute of Standards and Technology. http://www.nist.gov/dads/HTML/euclidndstnc.html. Accessed 07 May 2014.

  40. Ivanov AI, Zhbankov RG, Korolenko EA et al (1994) Infrared and Raman spectroscopic studies of the structure of human serum albumin under various ligand loads. J Appl Spectrosc 60(5-6):305–9

    Google Scholar 

  41. Saha A, Yakovlev VV (2010) Structural changes of human serum albumin in response to a low concentration of heavy ions. J Biophotonics 3(10-11):670–7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Movasaghi Z, Rehman S, Rehman IU (2007) Raman spectroscopy of biological tissues. Appl Spectrosc Rev 42(5):493–541

    Article  CAS  Google Scholar 

  43. Bayrak C, Bayari SH (2010) Vibrational and DFT studies of creatinine and its metal complexes. Hacett J Biol Chem 38(2):107–18

    Google Scholar 

  44. Keuleers R, Desseyn HO, Rousseau B, Van Alsenoy C (1999) Vibrational analysis of urea. J Phys Chem 103(24):4621–30

    Article  CAS  Google Scholar 

  45. Pichardo-Molina JL, Frausto-Reyes C, Barbosa-García O et al (2007) Raman spectroscopy and multivariate analysis of serum samples from breast cancer patients. Lasers Med Sci 22(4):229–36

    Article  CAS  PubMed  Google Scholar 

  46. Stosch R, Henrion A, Schiel D, Güttler B (2005) Surface-enhanced Raman scattering based approach for quantitative determination of creatinine in human serum. Anal Chem 77:7386–92

    Article  CAS  PubMed  Google Scholar 

  47. Peake M, Whiting M (2006) Measurement of serum creatinine—current status and future goals. Clin Biochem Rev 27(4):173–84

    PubMed  PubMed Central  Google Scholar 

  48. Weykamp C, Kuypers A, Bakkeren D, Franck P, van Loon D, Klein Gunnewiek J, de Jonge R, Steigstra H, Cobbaert C (2015) Creatinine, Jaffe, and glucose: another inconvenient truth. Clin Chem Lab Med 53(12):e347–9

    Article  CAS  PubMed  Google Scholar 

  49. Panteghini M (2008) Enzymatic assays for creatinine: time for action. Clin Chem Lab Med 46(4):567–72

    CAS  PubMed  Google Scholar 

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Acknowledgments

L. Silveira Jr. thanks São Paulo Research Foundation (FAPESP) for supporting the acquisition of the Raman spectrometer (Process no. 2009/01788-5). C. J. Saatkamp and M. L. Almeida thank Fundação Esperança, sponsor of the Instituto Esperança de Educação Superior (IESPES) for partly funding this research (Process no. 05/2012). The authors acknowledge the support of the Laboratório Celso Matos in this survey.

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Authors and Affiliations

  1. Instituto Esperança de Ensino Superior - IESPES, Rua Coaracy Nunes, 3315, Caranazal, 68040-100, Santarém, PA, Brazil

    Maurício Liberal de Almeida & Cassiano Junior Saatkamp

  2. Biomedical Engineering Institute, Universidade Camilo Castelo Branco - UNICASTELO, Parque Tecnológico de São José dos Campos, Estr. Dr. Altino Bondesan, 500, Eugênio de Melo, São José dos Campos, 12247-016, SP, Brazil

    Adriana Barrinha Fernandes, Antonio Luiz Barbosa Pinheiro & Landulfo Silveira Jr

  3. Center for Innovaton, Technology and Education - CITÉ, Parque Tecnológico de São José dos Campos, Estr. Dr. Altino Bondesan, 500, Eugênio de Melo, São José dos Campos, 12247-016, SP, Brazil

    Adriana Barrinha Fernandes & Landulfo Silveira Jr

  4. Center of Biophotonics, School of Dentistry, Federal University of Bahia - UFBA, Av. Araújo Pinho, 62, Canela, Salvador, 40110-150, BA, Brazil

    Antonio Luiz Barbosa Pinheiro

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  1. Maurício Liberal de Almeida
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  2. Cassiano Junior Saatkamp
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  5. Landulfo Silveira Jr
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Correspondence to Landulfo Silveira Jr.

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de Almeida, M.L., Saatkamp, C.J., Fernandes, A.B. et al. Estimating the concentration of urea and creatinine in the human serum of normal and dialysis patients through Raman spectroscopy. Lasers Med Sci 31, 1415–1423 (2016). https://doi.org/10.1007/s10103-016-2003-y

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  • DOI: https://doi.org/10.1007/s10103-016-2003-y

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