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Objectives Differentiating smoldering disease activity from weakness due to fatty replacement of atrophied muscle can often be a challenge in the idiopathic inflammatory myositis (IIM). We aimed to identify the metabolic disturbances associated with IIM and if these changes can aid in the assessment of disease activity. Methods Metabolic profiles of sera (N = 99) and muscle (N = 21) from patients with IIM (ACR‐EULAR criteria) were compared with healthy control (HC) samples (N = 75 for serum and N = 12 for muscle tissues) employing 800 MHz NMR (Nuclear Magnetic Resonance) spectroscopy. Metabolic disparity between IIM and HC was established based on Partial Least Squares Discriminant Analysis (PLS‐DA) and the discriminatory metabolites were identified based on variable importance in projection (VIP) statistics (P‐value < .05, corrected for false discovery rate (FDR)). Results Serum metabolomics profiles were distinctive in IIM as compared to HC, with a visible shift to anaerobic metabolism (increased lactate, low glucose), oxidative defect (high Phenylalanine/tyrosine), decreased muscle mass (low serum creatinine), increased muscle catabolism (increased branched‐chain amino acids), and dyslipidemia (higher lipids, higher very low‐density lipoprotein [VLDL]/low‐density lipoprotein [LDL] ratio, lower polyunsaturated fatty acid [PUFA]). The sera of active IIM patients were characterized by anaerobic metabolism (low glucose), loss of muscle mass (low creatinine, amino acids), and oxidative defect (high Phenylalanine/tyrosine). Three metabolites (isopropanol, succinate, and glycine) were distinctive in muscle tissue metabolomics. NMR‐based serum metabolic disparity was lacking between different clinical subsets of IIM. Conclusion Serum and muscle tissue metabolomics have the potential to distinguish (a) IIM from HC and (b) active IIM from inactive IIM irrespective of disease subtype.

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IntroductionThe mechanisms leading to chronic kidney disease (CKD) in patients with idiopathic inflammatory myopathies (IIMs) are poorly understood. We assessed the prevalence of subclinical renal injury in patients with IIMs, through elevation in biomarker levels of tubular injury and fibrosis (NGAL, KIM1, Activin A, CD163, and Cys-c), and assessed differences between subtypes of IIMs, and the effect of disease activity and duration.Materials and methodsClinical data, core set measures, sera and urine were prospectively collected from all patients enrolled in the MyoCite cohort from 2017 to 2021. Twenty healthy subjects (HC) and 16 patients with acute kidney injury (AKI) were included as controls. Baseline and follow up data for IIMs were included. Enzyme-linked immunosorbent assay (ELISA) was used to measure urine NGAL (Human Lipocalin-2/NGAL Duoset ELISA, Cat no: DY1757), KIM1 (Human TIM-1/KIM 1/HAVCR Duoset ELISA, Cat.no: DY1750B), Activin A (Human Activin A Duoset ELISA, Cat no: DY338), CD163 (Human CD163 Duoset ELISA,Cat no: DY1607-05), and Cys-c (Human Cystatin C Duoset ELISA, Cat. no.: DY1196) levels, while eGFR (unit mL/min/1.73 m2) was calculated by the Cockcroft-Gault formula and CKD-EPI formula.ResultsAnalysis of 201 visits of 110 adult patients with IIMs indicated higher normalized biomarker levels compared to HCs, and comparable to patients with AKI, with the exception of NGAL, which was higher in the AKI group. Notably 72 (49%) patients with IIMs had eGFR&lt;90; the levels of the 5 biomarkers were comparable between active and inactive IIMs, and different subtypes of IIMs. Similarly, a poor correlation between urine biomarker levels and core set measures of activity and damage was found. Changes in biomarker levels on follow-up did not correlate with eGFR changes.DiscussionThis exploratory analysis of urinary biomarkers identified low eGFR and elevated biomarkers of CKD in nearly half of the patients with IIMs, comparable to patients with AKI and higher than HCs, indicative of potential renal damage in IIMs that may have a lead to complications in other systems.