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Kalantari, Shiva, Chashmniam, Saeed, Nafar, Mohsen, Zakeri, Zahra, Parvin, Mahmoud. (1398). Metabolomics approach reveals urine biomarkers and pathways associated with the pathogenesis of lupus nephritis. , 22(11), 1288-1295. doi: 10.22038/ijbms.2019.38713.9178
Shiva Kalantari; Saeed Chashmniam; Mohsen Nafar; Zahra Zakeri; Mahmoud Parvin. "Metabolomics approach reveals urine biomarkers and pathways associated with the pathogenesis of lupus nephritis". , 22, 11, 1398, 1288-1295. doi: 10.22038/ijbms.2019.38713.9178
Kalantari, Shiva, Chashmniam, Saeed, Nafar, Mohsen, Zakeri, Zahra, Parvin, Mahmoud. (1398). 'Metabolomics approach reveals urine biomarkers and pathways associated with the pathogenesis of lupus nephritis', , 22(11), pp. 1288-1295. doi: 10.22038/ijbms.2019.38713.9178
Kalantari, Shiva, Chashmniam, Saeed, Nafar, Mohsen, Zakeri, Zahra, Parvin, Mahmoud. Metabolomics approach reveals urine biomarkers and pathways associated with the pathogenesis of lupus nephritis. , 1398; 22(11): 1288-1295. doi: 10.22038/ijbms.2019.38713.9178

Metabolomics approach reveals urine biomarkers and pathways associated with the pathogenesis of lupus nephritis

Iranian Journal of Basic Medical Sciences
مقاله 7، دوره 22، شماره 11، بهمن 2019، صفحه 1288-1295    اصل مقاله (775.26 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22038/ijbms.2019.38713.9178
نویسندگان
Shiva Kalantari1؛ Saeed Chashmniam2؛ Mohsen Nafar* 3؛ Zahra Zakeri4؛ Mahmoud Parvin5
1Chronic Kidney Disease Research Center, Shahid Beheshti University of Medical Sciences, Tehran-Iran
2Department of Chemistry, Sharif University of Technology, Tehran, Iran
3Urology-Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
4Department of Rheumatology, Shahid Labbafinejad Medical Center, Shahid Beheshti University of Medical Sciences Tehran, Iran
5Department of Pathology, Shahid Labbafinejad Medical Center, Shahid Beheshti University of Medical Sciences Tehran, Iran
چکیده
Objective(s): lupus nephritis (LN) is a severe form of systemic lupus erythematosus (SLE) with renal complications. Current diagnosis is based on invasive renal biopsy and serum antibodies and complement levels that are not specific enough. The current study aims to identify new biomarker candidates for non-invasive diagnosis of LN and explore the pathogenic mechanisms that contribute to renal injury.
Materials and Methods: A metabolomics approach using 1H-nuclear magnetic resonance (1H-NMR), was developed for comparison of urine metabolic profile of 14 LN patients, 10 SLE patients, and 11 healthy controls (HCs). Differential biomarker candidates were identified by using multivariate modeling, and their diagnostic accuracy was evaluated by receiver operating characteristic analysis (ROC).  
Results: Three metabolites were common in differentiating all three groups including beta-alanine, 2,2-dimethylsucssinic acid, and 3,4-Dihydroxyphenylacetaldehyde and suggested as a diagnostic panel for LN with AUC of 0.89, sensitivity of 81 %, and specificity of 100 %. Complementary analyses on pathways indicated that nicotinate and nicotinamide metabolism is the most important perturbed pathway in LN.
Conclusion: Metabolomics is a useful tool for identification of biomarkers with the ability to diagnose LN patients and predict perturbed pathways responsible for renal injury.
کلیدواژه‌ها
Biomarker؛ Lupus nephritis؛ Metabolomics؛ Non-invasive diagnosis؛ Nuclear Magnetic Resonance؛ Urinary metabolites
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مراجع
1. Chen Y, Sun J, Zou K, Yang Y, Liu G. Treatment for lupus nephritis: an overview of systematic reviews and meta-analyses. Rheumatol Int 2017; 37:1089-1099.
2. Chambers SA, Allen E, Rahman A, Isenberg D. Damage and mortality in a group of British patients with systemic lupus erythematosus followed up for over 10 years. Rheumatology 2009; 48:673-675.
3. Borchers AT, Leibushor N, Naguwa SM, Cheema GS, Shoenfeld Y, Gershwin ME. Lupus nephritis: a critical review. Autoimmun Rev 2012; 12:174-194.
4. Mok CC. Biomarkers for lupus nephritis: a critical appraisal. J Biomed Biotechnol 2010; 2010:638413-638424.
5. Lech M, Anders H-J. The pathogenesis of lupus nephritis. J Am Soc Nephrol 2013; 24:1357-1366.
6. Musa R, Qurie A. Lupus Nephritis.  StatPearls [Internet]: StatPearls Publishing; 2018.
7. Rahman A, Isenberg DA. Systemic lupus erythematosus. N Engl J Med 2008; 358:929-939.
8. Bengtsson AA, Trygg J, Wuttge DM, Sturfelt G, Theander E, Donten M, et al. Metabolic profiling of systemic lupus erythematosus and comparison with primary Sjögren’s syndrome and systemic sclerosis. PLoS One 2016; 11:159384-159399.
9. Weening JJ, D’agati VD, Schwartz MM, Seshan SV, Alpers CE, Appel GB, et al. The classification of glomerulonephritis in systemic lupus erythematosus revisited. Kidney Int 2004; 65:521-530.
10. Romick-Rosendale LE, Brunner HI, Bennett MR, Mina R, Nelson S, Petri M, et al. Identification of urinary metabolites that distinguish membranous lupus nephritis from proliferative lupus nephritis and focal segmental glomerulosclerosis. Arthritis Res Ther 2011; 13:199-209.
11. Qi S, Chen Q, Xu D, Xie N, Dai Y. Clinical application of protein biomarkers in lupus erythematosus and lupus nephritis. Lupus 2018; 27:1582-1590.
12. Guleria A, Pratap A, Dubey D, Rawat A, Chaurasia S, Sukesh E, et al. NMR based serum metabolomics reveals a distinctive signature in patients with lupus nephritis. Sci Rep 2016; 6:35309-35320.
13. Nicholson JK, Lindon JC. Systems biology: metabonomics. Nature 2008; 455:1054-1056.
14. Beckonert O, Keun HC, Ebbels TM, Bundy J, Holmes E, Lindon JC, et al. Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nat Protoc 2007; 2:2692-2703.
15. Li J, Xie X, Zhou H, Wang B, Zhang M, Tang F. Metabolic profiling reveals new serum biomarkers of lupus nephritis. Lupus 2017; 26:1166-1173.
16. Kalantari S, Nafar M, Samavat S, Parvin M. 1 H NMR‐based metabolomics study for identifying urinary biomarkers and perturbed metabolic pathways associated with severity of IgA nephropathy: a pilot study. Magn Reson Chem 2017; 55:693-699.
17. Kalantari S, Nafar M, Samavat S, Parvin M, Nobakht M. GH BF, Barzi F. 1H NMR‐based metabolomics exploring urinary biomarkers correlated with proteinuria in focal segmental glomerulosclerosis: a pilot study. Magn Reson Chem 2016; 54:821-826.
18. Karnovsky A, Weymouth T, Hull T, Tarcea VG, Scardoni G, Laudanna C, et al. Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data. Bioinformatics 2011; 28:373-380.
19. Artioli GG, Gualano B, Smith A, Stout J, Lancha Jr AH. Role of beta-alanine supplementation on muscle carnosine and exercise performance. Med Sci Sports Exerc 2010; 42:1162-1173.
20. Hipkiss AR, Brownson C, Carrier MJ. Carnosine, the anti-ageing, anti-oxidant dipeptide, may react with protein carbonyl groups. Mech Ageing Dev 2001; 122:1431-1445.
21. Peters V, Klessens CQ, Baelde HJ, Singler B, Veraar KA, Zutinic A, et al. Intrinsic carnosine metabolism in the human kidney. Amino acids 2015; 47:2541-2550.
22. Burckhardt BC, Lorenz J, Kobbe C, Burckhardt G. Substrate specificity of the human renal sodium dicarboxylate cotransporter, hNaDC-3, under voltage-clamp conditions. Am J Physiol Renal Physiol 2005; 288:792-799.
23. Pajor AM, Sun NN. Molecular cloning, chromosomal organization, and functional characterization of a sodium-dicarboxylate cotransporter from mouse kidney. Am J Physiol Renal Physiol 2000; 279:482-490.
24. Mandel LJ. Metabolic substrates, cellular energy production, and the regulation of proximal tubular transport. Annu Rev Physiol 1985; 47:85-101.
25. Hao X, Liu X, Wang W, Ren H, Xie J, Shen P, et al. Distinct metabolic profile of primary focal segmental glomerulosclerosis revealed by NMR-based metabolomics. PLoS One 2013; 8:78531-78541.
26. Burke WJ, Li SW, Williams EA, Nonneman R, Zahm DS. 3,4-Dihydroxyphenylacetaldehyde is the toxic dopamine metabolite in vivo: implications for Parkinson’s disease pathogenesis. Brain Res 2003; 989:205-213.
27. Burke WJ. 3,4-dihydroxyphenylacetaldehyde: a potential target for neuroprotective therapy in Parkinson’s disease. Curr Drug Targets CNS Neurol Disord 2003; 2:143-148.
28. Rees JN, Florang VR, Eckert LL, Doorn JA. Protein reactivity of 3,4-dihydroxyphenylacetaldehyde, a toxic dopamine metabolite, is dependent on both the aldehyde and the catechol. Chem Res Toxicol 2009; 22:1256-1263.
29. Anderson DG, Mariappan SV, Buettner GR, Doorn JA. Oxidation of 3,4-dihydroxyphenylacetaldehyde, a toxic dopaminergic metabolite, to a semiquinone radical and an ortho-quinone. J Biol Chem 2011; 286:26978-26986.
30. Rees JN. Protein reactivity of 3,4-dihydroxyphenylacetaldehyde,
an endogenous, potential neurotoxin relevant to Parkinson’s disease. Medicinal and Natural Products Chemistry The University of Iowa; 2009.
31. Moroni G, Novembrino C, Quaglini S, De Giuseppe R, Gallelli B, Uva V, et al. Oxidative stress and homocysteine metabolism in patients with lupus nephritis. Lupus 2010; 19:65-72.
32. Souliotis VL, Vougas K, Gorgoulis VG, Sfikakis PP. Defective DNA repair and chromatin organization in patients with quiescent systemic lupus erythematosus. Arthritis Res Ther 2016; 18:182-194.
33. Wang XD, Huang XF, Yan QR, Bao CD. Aberrant activation of the WNT/beta-catenin signaling pathway in lupus nephritis. PLoS One 2014; 9:84852-84859.

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