NMR based serum metabolomics reveals

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NMR based serum metabolomics reveals reprogramming of lipid dysregulation following Cyclophosphamide based induction therapy in lupus nephritis . Anupam Guleria, Sanat Phatak, Durgesh Dubey, Sandeep Kumar, abhishek zanwar, Smriti Chaurasia, Umesh Kumar, Ranjan Gupta, Amita Aggarwal, Dinesh Kumar, and Ramnath Misra J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.8b00192 • Publication Date (Web): 07 Jun 2018 Downloaded from http://pubs.acs.org on June 8, 2018

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Journal of Proteome Research

NMR based serum metabolomics reveals reprogramming of lipid dysregulation following Cyclophosphamide based induction therapy in lupus nephritis Anupam Guleria1*, Sanat Phatak2, Durgesh Dubey1, Sandeep Kumar2, Abhishek Zanwar2, Smriti Chaurasia2, Umesh Kumar1, Ranjan Gupta2, Amita Aggarwal2, Dinesh Kumar1* and Ramnath Misra2* 1

Centre of Biomedical Research, SGPGIMS Campus, Lucknow-226014, India

2

Department of Immunology, SGPGIMS, Lucknow-226014, India

Correspondence to: Dr Ramnath Misra M.D.,F.R.C.P (London) Professor and Head Department of Clinical Immunology and Rheumatology S.G.P.G.I.M.S Lucknow 226 014 Email: [email protected] Cell No : +91 8004904387 Orcid ID - 0000-0001-7921-4199

Dr. Anupam Guleria Centre of Biomedical Research (CBMR), SGPGIMS Campus, Lucknow-226014 Uttar Pradesh, India Email: [email protected] Mobile: +91-9918004592 ORCID iD: 0000-0002-4158-2241 Dr Dinesh Kumar Centre of Biomedical Research, SGPGIMS Campus, Lucknow-226014, India Email: [email protected]

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Abstract: Lupus nephritis (LN) is a major cause of morbidity and mortality in lupus. Renal biopsy is the gold standard for classification of nephritis but due to its impracticality, new approaches for improving patient prognostication and monitoring treatment efficacy are needed. In the present study, we aimed to evaluate the potential of metabolic profiling in identifying biomarkers to distinguish disease and monitor treatment efficacy in patients with LN. Serum samples from patients with LN (n=18) were profiled on NMR based metabolomics platforms at diagnosis and after six months of treatment. LN patients had a different metabolomic fingerprint as compared to healthy controls with increased lipoproteins, lipids and reduced acetate and amino acids. Using multivariate statistical analysis, we found that the metabolic changes observed in naïve LN patients at diagnosis displayed a variation in the opposite direction upon responding to treatment. Increased levels of lipid metabolites including low and very-low density lipoproteins (LDL/VLDL) in LN patients significantly decreased after six months of treatment, while the serum levels of acetate increased. These levels correlated significantly with SLE Disease Activity Index (SLEDAI 2K), renal SLEDAI, serum C3 and C4 levels. The result presented in this pilot longitudinal study revealed the reprogramming of metabolome in LN patients on immunosuppressive therapy using NMR based metabolomics and thus this approach may be used to monitor response to treatment.

KEYWORDS: NMR based metabolomics; Systemic lupus erythematosus, Lupus Nephritis; Serum metabolites.


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Introduction: Systemic lupus erythematosus (SLE) is multisystem autoimmune disroder. Renal involvement in the form of glomerulonephritis remains to be a significant cause of significant morbidity and mortality in patietns with SLE.

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A major challenge in the management of LN is assessment of disease activity

and monitoring of treatment response; currently used biomarkers like 24 hours proteinuria, anti dsDNA antibody, complement levels are far from perfect to differntiate disease activity from damage.2,3 Treatment of lupus nephritis is guided by histological classification of disease activity and damage on kideny biopsy.4 The severe LN conditions are generally treated with induction therapy comprising

corticosteroids

and

immunosuppressive

agents

such

as

cyclophosphamide,

mycophenolate mofetil and azathioprine, with the aim to normalize renal function or, at least, to prevent progressive loss of renal function.5 Renal biopsy is impractical in monitoring treatment efficacy as it is unduly invasive. Therefore, there is an unmet need for biomarkers that will reflect accurately the efficacy of treatment protocol; thus could avoid the need for serial renal biopsies, and provide a basis of alternative treatment protocol. Metabolomics is the analysis of global changes in complete set of metabolites present in biological ﬂuids and has increasingly been exploited for the discovery of disease biomarkers in recent times in various diseases.6,7 In our previous nuclear magnetic resonance (NMR) based serum metabolomics study,8 we have shown that the LN patients –compared to lupus patients- exhibit distinctive metabolic profiles characterised by raised serum levels of lipid metabolites including low and very low density lipoproteins (LDL/VLDL), triglycerides and fatty acids and decreased levels of acetate in LN patients, and these metabolites discriminated LN from non-renal SLE patients with high sensitivity and specificity.8 In this study, we sought to investigate whether the deranged metabolic profile reprogrammed after induction therapy to provide a potential biomarker for monitoring treatment Materials & Methods Patients and clinical characteristics: Institutional ethics committee approval was obatined. Both patients and healthy volnteers were enrolled in study after obtaining written informed consent.. Patients with SLE who fulfilled the SLICC criteria9 were included if they had nephritis as defined daily proteinuria >0.5 g and /or hematuria (RBC /WBC > 5 /hpf) or increase in serum creatinine > 0.3 mg%.10 Those who were having infections or critically ill, pregnant or were unable to give consent were excluded. Renal 3 ACS Paragon Plus Environment


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histology after kidney biopsy was carried out to characterise the histological class. Patients were followed up for 6 months after induction therapy with either high (NIH) or low (ELNT) dose cyclophosphamide along with prednisolone. Systemic and renal disease activity at base line and 6 months were measured using SLEDAI11 and renal SLEDAI (rSLEDAI), respectively.12,13 At the end of 6 months, patients were defined to be in complete response (24 hour protein excretion 1.0 and their relative changes (i.e. if elevated or depleted) were identified from the loading plots (for PLS-DA). The discriminatory metabolites were further tested for statistical significane through performing the independent samples T-test (univariate analysis) using SPSS software (v11.2, IBM). A p-value < 0.05 was used as the criterion for statistical significance. The non-overlapping resonances of marker metabolites in the 1D 1H NMR spectra (scaled with respect to TSP resonance) were used to calculate their quantitative levels in the serum. The variations in the levels of marker metabolites were visualized using the boxplot representation with the error bars representinbg standard error of the mean. The correlation analysis between the serum marker metabolites and clinical parameters were performed using Pearson correlation (ρ) method.


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Results: Patient characteristics: There were 18 patients with LN (16 females, 2 males, mean age 28.4 ± 6.6 years) seen at base line before treatment (labelled here as LN) and after receiving six months induction treatment as mentioned above (labelled here as LNT). Additionally, sera from 30 healthy control (HC) subjects (27 females, 3 males, mean age 23.7 ± 3.3 years, Mean body mass index (Kg/m2) 23±3.8) were obtained. The body mass index was lower in patients compared to healthy individuals. The clinical characteristics including extrarenal manifestations of patients are presented in Table S1. All patients had proliferative nephritis and received treatment with steroid and cyclophosphamide. Nine patients received monthly high dose cyclophosphamide as per NIH protocol while 9 received low dose cyclophosphamide as per Eurolupus protocol. Patients also received hydroxychloroquine (HCQ, n= 17) and antihypertensives. At the end of 6 months, 8, 7 and 3 patients had complete response, partial response and no response. There was a significant reduction in disease activity parameters such as SLEDAI, renal SLEDAI and raised anti dsDNA antibodies levels following treatment (Table 1).

Table 1: Disease Activity parameters before and after induction treatment in patients with 18 patients with lupus nephritis.

Lupus Nephritis before Lupus Nephritis after treatment (LN) treatment (LNT)

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SLEDAI Renal SLEDAI Anti-dsDNA antibodies n (%) C3 (mg/dl)

19 ± 4.89 8.88 ± 3.23 260.2±84.2 43.7 ± 26.8

4.82 ± 5.28 3.05 ± 3.88 96.3±103.3 101.7 ± 36.8

C4 (mg/dl)

9.55±5.95

17.4±12.3

H NMR spectroscopy and metabolic fingerprinting of Lupus Nephritis

The typical 1H NMR spectra of serum of a LN patient before and after treatment are shown in Figure 1 with the assignment of spectral peaks to various metabolites. Visual inspection of the spectra revealed higher levels of lipids and lipoproteins in LN patient which decreases significantly after six months of treatment. For metabolic profiling of LN patients, the NMR spectra recorded on 18 LN and 30 HC serum samples were first subjected to multivariate data analysis. A clear separation 7 ACS Paragon Plus Environment


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between the healthy controls and LN patients was observed in the PLS-DA score plot as shown in Figure S2(A) with good model parameters R2X(cum) = 0.948, R2Y(cum) = 0.965, Q2(cum) = 0.927 and high statistically significant p value by CV-ANOVA (p= 5.29× 10-19). Metabolites responsible for discriminating LN group from HC in the PLS-DA 2D score plot were identified based on their VIP score value >1 and statistical significance at the level of p-value 1 and were then tested for statistical significance using independent samples t-test. The discriminatory metabolites (VIP score >1) with p value