Chinese Journal of Dermatology ›› 2025, Vol. 58 ›› Issue (8): 736-743.doi: 10.35541/cjd.20240588

• Original Articles • Previous Articles     Next Articles

Serum lipidomic profiling in patients with dermatomyositis based on ultra-performance liquid chromatography-mass spectrometry

Ma Tongchuan1, Cai Xinying1, Wang Rui1, Dong Liping1, Chen Lele1, Xiao Fengli1,2   

  1. 1Department of Dermatology and Venereology, the First Affiliated Hospital, Institute of Dermatology, Anhui Medical University, Key Laboratory of Dermatology, Anhui Medical University, Ministry of Education, Hefei 230032, China; 2Collaborative Innovation Center of Complex and Severe Skin Disease, Anhui Medical University, Hefei 230032, China
  • Received:2024-10-30 Revised:2025-06-18 Online:2025-08-15 Published:2025-08-05
  • Contact: Xiao Fengli E-mail:xiaofengli@126.com
  • Supported by:
    National Natural Science Foundation of China (82373481, 82203920); Natural Science Research in Colleges and Universities in Anhui Province (2023AH053302)

Abstract: 【Abstract】 Objective To investigate differences in serum lipid profiles between patients with dermatomyositis (DM) and healthy controls. Methods A retrospective analysis was conducted on the clinical data and serum samples collected from 51 patients with DM who visited the First Affiliated Hospital, Anhui Medical University from September 2020 to January 2022. Serum samples were also collected from 66 healthy controls during the same period. Serum lipid profiles were analyzed using ultra-performance liquid chromatography-mass spectrometry in both groups. Differential lipids were screened using principal component analysis and orthogonal partial least squares-discriminant analysis. The predictive value of these differential lipids for DM was evaluated by receiver operating characteristic (ROC) curve analysis, and their correlations with clinical indicators were also evaluated. Results A total of 51 patients with DM were enrolled, including 27 males and 24 females, with ages (M [Q1, Q3]) of 55.00 (47.00, 66.00) years and body mass index (BMI) values of 22.64 (19.79, 24.75). The control group included 66 healthy individuals (33 males and 33 females), with ages of 51.00 (43.75, 56.00) years and BMI values of 23.60 (21.18, 25.19). No significant differences were observed between the two groups in terms of sex, age, or BMI (all P > 0.05). A total of 341 lipid metabolites were identified, and 16 lipid metabolites such as ceramides (Cer), sphingomyelins, phosphatidylcholines (PC), phosphatidylethanolamines, lysophosphatidylcholines (LPC), and triglycerides (TG) significantly differed between the DM group and the control group, of which 8 were upregulated and 8 were downregulated in the DM group. ROC curve analysis identified 7 differential lipids with area under the curve (AUC) values of > 0.9, of which 2 were Cer, 3 were TG, 1 was phosphatidylethanolamine, and 1 was LPC. In the DM patients, serum LPC (22∶1) levels were negatively correlated with creatine kinase isoenzyme MB levels (r = -0.276, P < 0.05), serum PC (15∶1/16∶0) levels were negatively correlated with aspartate aminotransferase levels (r = -0.305, P < 0.05), and serum Cer (d18∶1/18∶0) levels were positively correlated with C-reactive protein levels (r = 0.283, P < 0.05). Significant differences in serum lipid levels were observed between some DM subgroups (all P < 0.05): sphingomyelin (d24∶0) levels significantly differed between anti-Sj?gren syndrome type A/Ro52 antibody-positive and -negative DM patients; LPC (17∶1) levels significantly differed between anti-PM-SCL75 antibody-positive and -negative DM patients; LPC (20∶0) and PC (32∶1p) levels significantly differed between anti-Mi-2 antibody-positive and -negative DM patients; LPC (22∶1) and TG (9∶0/9∶0/9∶0) levels significantly differed between anti-TIF1-γ antibody-positive and -negative DM patients; Cer (d18∶1/18∶0) levels significantly differed between DM patients with and without Heliotrope's sign. Conclusion Lipid profiles were significantly altered in DM patients compared with healthy controls, and some lipids showed potential diagnostic value for DM.

Key words: Dermatomyositis, Lipidomics, Biomarkers, Ceramide, Principal component analysis