DNA Methylation Markers in Peripheral Blood as Effective Diagnostic Biomarkers for Adult-onset Still’s Disease

Shijia Rao¹, Bo Zhang², Yuwei Li³, Tian Zhou¹, Xiaoli Shi¹, Wei Shi⁴, Yongfang Jiang¹, Wenlong Wang¹, Yun Xu¹, Yi Tian¹, Min Zhang¹, Jing Ma¹, Hongyu Luo¹, Hui Luo⁴, Hongjun Zhao⁴, Fen Li¹, Guanghui Ling¹, Jing Tian¹, Xiaojing Kang⁵, Junqin Liang⁵, Aijun Chen⁶, Shuang Chen⁶, Jianjun Qiao⁷, Gang Wang⁸, Lei wang⁸, Bing Li⁸, Youkun Lin⁹, Sijian Wen⁹, Zhiqiang Song¹⁰, Min Zhang¹⁰, Jun Liu⁴, Yixin Tan¹, Haijing Wu¹, Hai Long¹, Ming Zhao¹¹ and Qianjin Lu¹², ¹The Second Xiangya Hospital, Central South University, Changsha, China, ²Chinese Academy of Medical Sciences & Peking Union Medical College, Nanjing, China, ³University of Science and Technology of China, Hefei, China, ⁴Xiangya Hospital, Central South University, Changsha, China, ⁵People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, China, ⁶The First Affiliated Hospital of Chongqing Medical University, Chongqing, China, ⁷The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China, ⁸Xijing Hospital, Fourth Military Medical University, Xi'an, China, ⁹The First Affiliated Hospital of Guangxi Medical University, Nanning, China, ¹⁰Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China, ¹¹Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China, ¹²Hospital for Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Changsha, China

Meeting: ACR Convergence 2023

Keywords: immunology

Session Information

Date: Sunday, November 12, 2023

Title: (0252–0282) Miscellaneous Rheumatic & Inflammatory Diseases Poster I

Session Type: Poster Session A

Session Time: 9:00AM-11:00AM

Background/Purpose: Adult-onset still’s disease (AOSD) is an auto-inflammatory disease affecting multiple systems. The diagnostic procedures of AOSD are still a challenge. We aimed to find an effective DNA methylation biomarker for AOSD diagnosis in this study

Methods: Differential methylation CpG sites (DMSs) were selected from DNA methylation array comprised of a discovery cohort including 50 AOSD patients, 49 healthy controls (HCs), 24 T cell lymphoma (TL) patients, 24 sepsis (SP) patients and 24 drug eruption (DE) patients. A cohort of 96 AOSD patients, 92 HCs, 50 rheumatoid arthritis (RA) patients, 28 SP patients, 21 DE patients and 62 TL patients was used for validation via pyrosequencing. Subsequently, four logistic regression prediction models were performed.

Results: Nine DMSs were selected from the discovery cohort via the DNA methylation array incorporating Least Absolute Shrinkage and Selector Operation (LASSO). We analyzed the methylation levels of these CpG sites by pyrosequencing in the validation cohort, and calculated four logistic regression prediction models in order to differentiate AOSD from the HCs (AUC: 0.964, sensitivity: 98.5%, specificity: 98.9%), the RA group (AUC: 0.988, sensitivity: 97.8%, specificity: 94%), the SP group (AUC: 0.885, sensitivity: 77.1%, specificity: 92.9%) and the DE group (AUC: 0.842, sensitivity: 72%, specificity: 90.5%) respectively. In addition, the methylation level of cg14887853 could be used to distinguish AOSD (AUC: 0.693, sensitivity: 79.6%, specificity: 59.5%) and active AOSD (AUC: 0.761, sensitivity: 81.5%, specificity: 67.8%) from TL respectively.

Conclusion: The DNA methylation levels of CpG sites can be used as biomarker for diagnosis of AOSD.

Volcano plots, location information, KEGG pathway analysis and GO analysis of differentially methylated CpG sites (DMSs) in AOSD. A Volcano plot of the distribution of DMSs between AOSD and HC group. B Volcano plot of the distribution of DMSs between AOSD and DC groups. C Location information of DMSs on genome E Top 20 statistic of pathway enrichment of DMSs between AOSD and HC group. F GO analysis DMSs between AOSD and HC group.

DNA methylation level of the identified six differential methylated sites (DMSs) between AOSD and healthy controls (HCs)/ disease controls (DCs) in validation cohort. A It shows that methylation level of Site1 is significantly lower in the blood of AOSD patients than that in HCs, patients with rheumatoid arthritis (RA), patients with sepsis (SP) and patients with drug eruption (DE). B It shows that methylation level of Site2 is significantly lower in the blood of AOSD patients than that in patients with RA and patients with SP, and is significantly higher in the blood of AOSD patients than that in HCs. C It shows that methylation level of Site3 is significantly lower in the blood of AOSD patients than that in HCs. D It shows that methylation level of Site4 is significantly lower in the blood of AOSD patients than that in HCs and patients with RA. E It shows that methylation level of Site5 is significantly higher in the blood of AOSD patients than that in HCs, patients with SP and patients with drug eruption (DE). F It shows that methylation level of Site6 is significantly lower in the blood of AOSD patients than that in HCs and patients with T cell lymphoma (TL).

Receiver operating characteristic (ROC) curves analysis of logistic regression prediction model. A show the ROC curve of the logistic regression prediction model based on Site1, Site3, Site4 and Site5 in patients with AOSD compared with HCs. B show the ROC curve of the logistic regression prediction model based on Site1, Site2, Site3 and Site4 in patients with AOSD compared with patients with RA. C show the ROC curve of the logistic regression prediction model based on Site1, Site2, and Site3 in patients with AOSD compared with patients with SP. D show the ROC curve of the logistic regression prediction model based on Site1, Site3, Site4 and Site5 in patients with AOSD compared with patients with DE. E show the ROC curve of Site 6 in patients with AOSD compared with patients with TL. F show the ROC curve of Site 6 in AOSD patients in active phase compared with patients with TL.

Disclosures: S. Rao: None; B. Zhang: None; Y. Li: None; T. Zhou: None; X. Shi: None; W. Shi: None; Y. Jiang: None; W. Wang: None; Y. Xu: None; Y. Tian: None; M. Zhang: None; J. Ma: None; H. Luo: None; H. Luo: None; H. Zhao: None; F. Li: None; G. Ling: None; J. Tian: None; X. Kang: None; J. Liang: None; A. Chen: None; S. Chen: None; J. Qiao: None; G. Wang: None; L. wang: None; B. Li: None; Y. Lin: None; S. Wen: None; Z. Song: None; M. Zhang: None; J. Liu: None; Y. Tan: None; H. Wu: None; H. Long: None; M. Zhao: None; Q. Lu: None.

To cite this abstract in AMA style:

Rao S, Zhang B, Li Y, Zhou T, Shi X, Shi W, Jiang Y, Wang W, Xu Y, Tian Y, Zhang M, Ma J, Luo H, Luo H, Zhao H, Li F, Ling G, Tian J, Kang X, Liang J, Chen A, Chen S, Qiao J, Wang G, wang L, Li B, Lin Y, Wen S, Song Z, Zhang M, Liu J, Tan Y, Wu H, Long H, Zhao M, Lu Q. DNA Methylation Markers in Peripheral Blood as Effective Diagnostic Biomarkers for Adult-onset Still’s Disease [abstract]. Arthritis Rheumatol. 2023; 75 (suppl 9). https://acrabstracts.org/abstract/dna-methylation-markers-in-peripheral-blood-as-effective-diagnostic-biomarkers-for-adult-onset-stills-disease/. Accessed .

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