Profiling renal dysfunction using Raman chemometric urinalysis, with special reference to COVID19, lupus nephritis, and diabetic nephropathy
Main Article Content
Abstract
Background: Many systemic and urinary tract diseases alter renal structure and function, including changing the composition of urine. While routine urinalysis (physical properties, sediment evaluation, urine chemistry analytes) is useful in screening, it has limitations on separating disease processes, structural changes, and functional abnormalities. Likewise, while many individual ‘biomarkers’ have been used to screen for disease, they have not met with widespread clinical adoption. The recent COVID19 Pandemic and the recognition of post-acute sequelae SARS-CoV-2 infection (PASC) have highlighted the need for rapid, scalable, economical, and accurate screening tools for managing disease.
Aims: Validate a Raman spectroscopy-based screening technology for urine analysis that could be used for recognition and quantification of systemic and renal effects of acute and PASC COVID19 disease.
Methods: One hundred ten (110) urine specimens were obtained from consented adults diagnosed with COVID19 disease by RT-PCR and/or proximate (household) contact With RT-PCR-confirmed COVID19 disease. Samples were analyzed using Raman chemometric urinalysis, a technology that detects hundreds of discrete chemicals in urine and applies computational comparison-machine learning to detect COVID19-associated molecular patterns (‘fingerprints’).
Results: When compared with the urine multimolecular ‘fingerprints’ of healthy individuals and patients with known systemic diseases (diabetes mellitus, lupus) that alter renal structure and function, patients with acute and PASC COVID19 had unique ‘fingerprints’ indicative of alterations in renal function (i.e. – infection altered urine composition). Differences in disease severity (mild to severe) were reflected by different ‘fingerprints’ in urine. Roughly 20% of hospitalized patients developed a degree of renal dysfunction (decrements in eGFR) that were correlated with distinct changes in urine fingerprints.
Conclusion: Raman chemometric urinalysis may be a useful tool in management of patients with COVID19 disease, particularly in detecting patients with evolving renal dysfunction for whom there should be attention to medication use and renal health restoration/preservation.
Keywords:
enal dysfunction, Raman chemometric urinalysis, COVID19, lupus nephritis, diabetic nephropathy
Article Details
How to Cite
ROBERTSON, John et al.
Profiling renal dysfunction using Raman chemometric urinalysis, with special reference to COVID19, lupus nephritis, and diabetic nephropathy.
Medical Research Archives, [S.l.], v. 11, n. 9, sep. 2023.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/4384>. Date accessed: 21 nov. 2024.
doi: https://doi.org/10.18103/mra.v11i9.4384.
Section
Research Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
References
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29. Senger R, Sayed Issa A, Agnor B, Talty J, Hollis A, Robertson JL. Disease-associated multimolecular signature in the urine of patients with Lyme disease, detected using Raman spectroscopy and chemometrics (Rametrix®)” Appl Spectrosc. 2022; 76 (3): 284-299 doi: 10.1177/00037028211061769
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31. Perumal R, Shunmugam L, Naidoo K, et al. Long COVID: A review and proposed visualization of the complexity of Long COVID. Front. Immunol. 2023; 14:1117464. doi: 10.3389/fimmu.2023.1117464
32. Xiang HX, Fei J, Xiang Y, Xu Z, Zheng L, Li XY, Fu L, Zhao H. Renal dysfunction and prognosis of COVID19 patients: a hospital-based retrospective cohort study. BMC Infect Dis. 2021 Feb 8; 21(1):158. doi: 10.1186/s12879-021-05861-x. PMID: 33557785; PMCID: PMC7868870.
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34. Mohamed MM, Lukitsch I, Torres-Ortiz AE, Walker JB, Varghese V, Hernandez-Arroyo CF. Acute kidney injury associated with coronavirus disease 2019 in urban New Orleans. Kidney360. 2020; 1: 614–622 https://doi.org/10.34067/KID.0002652020 PMID: 35372932
35. Ng JH, Bijol V, Sparks MA, Sise ME, Izzedine H, Jhaveri KD. Pathophysiology and pathology of acute kidney injury in patients with COVID19. Adv Chronic Kidney Dis. 2020 Sep; 27(5):365-376. doi: 10.1053/j.ackd.2020.09.003. Epub 2020 Oct 20. PMID: 33308501; PMCID: PMC7574722
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40. Hassler L, Reyes F, Sparks MA, Welling P, Battle D. Evidence for and against direct kidney Infection by SARS-CoV-2 in patients with COVID19. Clin J Am Soc Nephrol. 2021; 16: https://doi.org/10.2215/CJN.04560421 PMID: 34127485
41. Robertson JL, Senger RS, Talty J, Du P, Sayed-Issa A, Avellar ML, et al. Alterations in the molecular composition of COVID19 patient urine, detected using Raman spectroscopic/computational analysis. PLOS ONE. 2022; 17: e0270914. doi:10.1371/journal.pone.0270914
42. Gomez dela Espriella M, Fazili T, Jackson-Akers J, Sayed Issa A, Ngo L, Talty, J, Du P, Senger R, Robertson, J. Effects of COVID-19 on urine composition and kidney function in a cohort of hospitalized patients, determined using Raman chemometric urinalysis (Rametrix®) In preparation
43. Palazzo L, Lindblom J, Mohan C, Parodis I. Current Insights on biomarkers in lupus nephritis: A systematic review of the literature. J Clin Med. 2022 Sep 28; 11(19):5759. doi: 10.3390/jcm11195759. PMID: 36233628; PMCID: PMC9570701
44. Howe HS, Kong KO, Thong BY, et al. Urine sVCAM-1 and sICAM-1 levels are elevated in lupus nephritis. Int J Rheum. Dis. 2012; 15, 13–16
45. Parodis I, Gokaraju S, Zickert A, et al. ALCAM and VCAM-1 as urine biomarkers of activity and long-term renal outcome in systemic lupus erythematosus. Rheumatology 2019; 59, 2237–2249
46. Mejia-Vilet JM, Zhang XL, Cruz C, et al. Urinary soluble CD163: A novel noninvasive biomarker of activity for lupus nephritis. J Amer Soc Nephrol. 2020; 31, 1335–1347
47. Zhang T, Li H, Vanarsa K, et al. Association of urine sCD163 with proliferative lupus nephritis, fibrinoid necrosis, cellular crescents and intrarenal M2 macrophages. Front Immunol. 2020; 11, 671
48. Senger R, Sullivan K, Maurer K, Sayed Issa A, Ngo L, Robertson J. Identification of unique molecular ‘fingerprints’ of Systemic Lupus Erythematosus (SLE) and evaluation of kidney function using urine Raman spectroscopy and chemometrics. In preparation
49. Poggio ED, McClelland RL, Blank KN, et al. Kidney Precision Medicine Project. Systematic review and meta-analysis of native kidney biopsy complications. Clin J Am Soc Nephrol 2020 Nov 6; 15(11):1595-1602. doi: 10.2215/CJN.04710420. Epub 2020 Oct 15. Erratum in: Clin J Am Soc Nephrol. 2021 Feb 8; 16(2):293. PMID: 33060160; PMCID: PMC7646247.
50. Kavuru V, Senger RS, Robertson JL, Choudhury D. Analysis of urine Raman spectra differences from patients with diabetes mellitus and renal pathologies. PeerJ. 2023; 11:e14879 DOI 10.7717/peerj.14879
2. Delanghe J, Speeckaert M. Preanalytical requirements of urinalysis. Biochem Med (Zagreb). 2014 Feb 15; 24(1):89-104. doi: 10.11613/BM.2014.011. PMID: 24627718; PMCID: PMC3936984.)
3. Kavuru V, Vu T, Karageorge L, et al. Dipstick analysis of urine chemistry: benefits and limitations of dry chemistry-based assays. Postgrad Med Published on-line Oct 19 2019 https://doi.org/10.1080/00325481.2019.1679540
4. Magalhães P, Mischak H, Zürbig P. Urinary proteomics using capillary electrophoresis coupled to mass spectrometry for diagnosis and prognosis in kidney diseases. Curr Opin Nephrol Hypertens. 2016 Nov; 25(6):494-501. doi:10.1097/MNH.0000000000000278. PMID: 27584928; PMCID: PMC6813039
5. Darshi M, Van Espen B, Sharma K. Metabolomics in diabetic kidney disease: Unraveling the biochemistry of a silent killer. Am J Nephrol 2016; 44, 92–103
6. American Urological Association (AUA) / American Society of Clinical Oncology (ASCO) / American Society for Radiation Oncology (ASTRO) / Society of Urologic Oncology (SUO). Treatment of non-metastatic muscle-invasive Bladder cancer: AUA/ASCO/ASTRO/SUO Guideline (amended 2020). (Contributors: Chang SS, et. al., 2020)
7. American Urological Association (AUA)/ Society of Urologic Oncology (SUO) Guideline. Diagnosis and treatment of Non-Muscle Invasive Bladder Cancer: AUA/SUO GUIDELINE. 2016, Amended 2020) (Contributors: Chang SS, et. al.)
8. Petrella G, Ciufolini G, Vago R, Cicero DO. Urinary metabolic markers of bladder cancer: A reflection of the tumor or the response of the body? Metabolites. 2021, Oct 31; 11(11):756. doi: 10.3390/metabo11110756. PMID: 34822414; PMCID: PMC8621503
9. Senger R, DelaTorre-Campos D, et al. Assessment of urine specimen storage conditions using Raman Chemometric UrinalysisTM (Rametrix®), in preparation, 2023
10. Butler HJ, Ashton L, Bird B, et al. Using Raman spectroscopy to characterize biological materials. Nat Protoc. 2016; 11: 664–687. doi:10.1038/nprot.2016.036
11. Cialla-May D, Schmitt M, Popp J. Theoretical principles of Raman spectroscopy. Physical Sciences Reviews. 2019; 4. doi:10.1515/psr-2017-0040
12. Czamara K, Szafraniec E, Wiercigroch E, et al. Small and large Molecules investigated by Raman spectroscopy. In: Koleżyński A, Król M, editors. Molecular Spectroscopy—Experiment and Theory: From Molecules to Functional Materials. Cham: Springer International Publishing; 2019. pp. 161–198. doi: 10.1007/978-3-030-01355-4_6
13. Krafft C, Popp J. The many facets of Raman spectroscopy for biomedical analysis. Anal Bioanal Chem. 2015; 407: 699–717. doi: 10.1007/s00216-014-8311-9
14. Shen Y, Hu F, Min W. Raman imaging of small biomolecules. Ann Rev Biophysics. 2019; 48: 347–369. doi: 10.1146/annurev-biophys-052118-115500
15. Movasaghi Z, Rehman S, Rehman DIU. Raman spectroscopy of biological tissues. Appl Spectrosc Rev. 2007; 42: 493–541. doi: 10.1080/05704920701551530
16. Talari ACS, Movasaghi Z, Rehman S, Rehman I. Raman spectroscopy of biological tissues. Appl Spectrosc Rev. 2015; 50: 46–111. doi:10.1080/05704928.2014.92390
17. Senger RS, Kavuru V, Sullivan M, Gouldin A, Lundgren S, Merrifield K, et al. Spectral characteristics of urine specimens from healthy human volunteers analyzed using Raman chemometric urinalysis (Rametrix). PLOS ONE. 2019; 14: e0222115. doi:10.1371/journal.pone.0222115
18. Senger RS, Sullivan M, Gouldin A, Lundgren S, Merrifield K, Steen C, et al. Spectral characteristics of urine from patients with end-stage kidney disease analyzed using Raman Chemometric Urinalysis (Rametrix). PLOS ONE. 2020; 15: e0227281. doi:10.1371/journal.pone.0227281
19. Senger RS, Robertson JL. The RametrixTM PRO Toolbox v1.0 for MATLAB®. PeerJ. 2020; 8. doi:10.7717/peerj.8179
20. Liland KH, Kohler A, Afseth NK. Model-based pre-processing in Raman spectroscopy of biological samples. J Raman Spectrosc. 2016; 47: 643–650. doi:10.1002/jrs.4886
21. Guo S, Bocklitz T, Popp J. Optimization of Raman-spectrum baseline correction in biological application. Analyst. 2016; 141: 2396–2404. doi: 10.1039/C6AN00041J
22. Zimmermann B, Kohler A. Optimizing Savitzky–Golay parameters for improving Spectral resolution and quantification in infrared spectroscopy. Appl Spectrosc. 2013; 67: 892–902. doi: 10.1366/12-06723
23. Liu J, Sun J, Huang X, Li G, Liu B. Goldindec: A novel algorithm for Raman spectrum baseline correction. Appl Spectrosc. 2015; 69: 834–842. doi: 10.1366/14-07798
24. Xu Y, Du P, Senger R, Robertson J, Pirkle JL. ISREA: An efficient peak-preserving baseline correction algorithm for Raman spectra. Appl Spectrosc. 2021; 75: 34–45. doi: 10.1177/0003702820955245
25. Fisher AK, Carswell WF, Athamneh AIM, et al. The RametrixTM LITE Toolbox v1.0 for MATLAB®. J Raman Spectrosc. 2018; 49: 885–896. doi:https://doi.org/10.1002/jrs.5348
26. Trevethan R. Sensitivity, specificity, and predictive values: Foundations, pliabilities, and pitfalls in research and practice. Front Public Health. 2017; 5. doi:10.3389/fpubh.2017.00307
27. Huttanus HM, Vu T, Guruli G, et al. Raman chemometric urinalysis (Rametrix®) as a screen for bladder cancer. PLOS ONE. 2020; 15: e0237070.
28. Pegalajar-Jurado A, Fitzgerald BL, Islam MN, Belisle JT, Wormser GP, Waller KS, et al. Identification of urine metabolites as biomarkers of early Lyme disease. Sci Rep. 2018; 8: 12204. doi: 10.1038/s41598-018-29713-y
29. Senger R, Sayed Issa A, Agnor B, Talty J, Hollis A, Robertson JL. Disease-associated multimolecular signature in the urine of patients with Lyme disease, detected using Raman spectroscopy and chemometrics (Rametrix®)” Appl Spectrosc. 2022; 76 (3): 284-299 doi: 10.1177/00037028211061769
30. Patel JM. Multisystem inflammatory syndrome in children (MIS-C). Curr Allergy Asthma Rep. 2022 May; 22(5):53-60. doi: 10.1007/s11882-022-01031-4. Epub 2022 Mar 22. PMID: 35314921; PMCID: PMC8938222.
31. Perumal R, Shunmugam L, Naidoo K, et al. Long COVID: A review and proposed visualization of the complexity of Long COVID. Front. Immunol. 2023; 14:1117464. doi: 10.3389/fimmu.2023.1117464
32. Xiang HX, Fei J, Xiang Y, Xu Z, Zheng L, Li XY, Fu L, Zhao H. Renal dysfunction and prognosis of COVID19 patients: a hospital-based retrospective cohort study. BMC Infect Dis. 2021 Feb 8; 21(1):158. doi: 10.1186/s12879-021-05861-x. PMID: 33557785; PMCID: PMC7868870.
33. Hirsch JS, Ng JH, Ross DW, Sharma P, Shah HH, Barnett RL, et al. Acute kidney injury in patients hospitalized with COVID19. Kidney Int. 2020; 98: 209–218, 2020 https://doi.org/10.1016/j.kint.2020.05.006 PMID: 32416116
34. Mohamed MM, Lukitsch I, Torres-Ortiz AE, Walker JB, Varghese V, Hernandez-Arroyo CF. Acute kidney injury associated with coronavirus disease 2019 in urban New Orleans. Kidney360. 2020; 1: 614–622 https://doi.org/10.34067/KID.0002652020 PMID: 35372932
35. Ng JH, Bijol V, Sparks MA, Sise ME, Izzedine H, Jhaveri KD. Pathophysiology and pathology of acute kidney injury in patients with COVID19. Adv Chronic Kidney Dis. 2020 Sep; 27(5):365-376. doi: 10.1053/j.ackd.2020.09.003. Epub 2020 Oct 20. PMID: 33308501; PMCID: PMC7574722
36. Laudanski K, Okeke T, Hajj J, Siddiq K, Rader DJ, Wu J, Susztak K. Longitudinal urinary biomarkers of immunological activation in COVID19 patients without clinically apparent kidney disease versus acute and chronic failure. Sci Rep. 2021; Oct 4; 11(1):19675. doi: 10.1038/s41598-021-99102-5. Erratum in: Sci Rep. 2021 Nov 11; 11(1):22456. PMID: 34608231; PMCID: PMC8490434.
37. Fisher M, Neugarten J, Bellin E, et al. AKI in hospitalized patients with and without COVID19: A comparison study. J Am Soc Nephrol. 2020; 31: 2145–2157 https://doi.org/10.1681/ASN.2020040509 PMID: 32669322
38. Moledina DG, Simonov M, Yamamoto Y, et al. The association of COVID19 with acute kidney injury independent of severity of illness: A multicenter cohort study. Am J Kidney Dis. 2021; 77: 490–499.e1 https://doi.org/10.1053/j.ajkd.2020.12.007 PMID: 33422598
39. Carlson N, Nelveg-Kristensen KE, Freese Ballegaard E, et al. Increased vulnerability to COVID19 in chronic kidney disease. J Intern Med. 2021 Jul; 290(1):166-178. doi: 10.1111/joim.13239. Epub 2021 Feb 10. PMID: 33452733; PMCID: PMC8014284
40. Hassler L, Reyes F, Sparks MA, Welling P, Battle D. Evidence for and against direct kidney Infection by SARS-CoV-2 in patients with COVID19. Clin J Am Soc Nephrol. 2021; 16: https://doi.org/10.2215/CJN.04560421 PMID: 34127485
41. Robertson JL, Senger RS, Talty J, Du P, Sayed-Issa A, Avellar ML, et al. Alterations in the molecular composition of COVID19 patient urine, detected using Raman spectroscopic/computational analysis. PLOS ONE. 2022; 17: e0270914. doi:10.1371/journal.pone.0270914
42. Gomez dela Espriella M, Fazili T, Jackson-Akers J, Sayed Issa A, Ngo L, Talty, J, Du P, Senger R, Robertson, J. Effects of COVID-19 on urine composition and kidney function in a cohort of hospitalized patients, determined using Raman chemometric urinalysis (Rametrix®) In preparation
43. Palazzo L, Lindblom J, Mohan C, Parodis I. Current Insights on biomarkers in lupus nephritis: A systematic review of the literature. J Clin Med. 2022 Sep 28; 11(19):5759. doi: 10.3390/jcm11195759. PMID: 36233628; PMCID: PMC9570701
44. Howe HS, Kong KO, Thong BY, et al. Urine sVCAM-1 and sICAM-1 levels are elevated in lupus nephritis. Int J Rheum. Dis. 2012; 15, 13–16
45. Parodis I, Gokaraju S, Zickert A, et al. ALCAM and VCAM-1 as urine biomarkers of activity and long-term renal outcome in systemic lupus erythematosus. Rheumatology 2019; 59, 2237–2249
46. Mejia-Vilet JM, Zhang XL, Cruz C, et al. Urinary soluble CD163: A novel noninvasive biomarker of activity for lupus nephritis. J Amer Soc Nephrol. 2020; 31, 1335–1347
47. Zhang T, Li H, Vanarsa K, et al. Association of urine sCD163 with proliferative lupus nephritis, fibrinoid necrosis, cellular crescents and intrarenal M2 macrophages. Front Immunol. 2020; 11, 671
48. Senger R, Sullivan K, Maurer K, Sayed Issa A, Ngo L, Robertson J. Identification of unique molecular ‘fingerprints’ of Systemic Lupus Erythematosus (SLE) and evaluation of kidney function using urine Raman spectroscopy and chemometrics. In preparation
49. Poggio ED, McClelland RL, Blank KN, et al. Kidney Precision Medicine Project. Systematic review and meta-analysis of native kidney biopsy complications. Clin J Am Soc Nephrol 2020 Nov 6; 15(11):1595-1602. doi: 10.2215/CJN.04710420. Epub 2020 Oct 15. Erratum in: Clin J Am Soc Nephrol. 2021 Feb 8; 16(2):293. PMID: 33060160; PMCID: PMC7646247.
50. Kavuru V, Senger RS, Robertson JL, Choudhury D. Analysis of urine Raman spectra differences from patients with diabetes mellitus and renal pathologies. PeerJ. 2023; 11:e14879 DOI 10.7717/peerj.14879