Serum metabolomic and lipidomic profiling identifies diagnostic biomarkers for seropositive and seronegative rheumatoid arthritis patients

Luan, Hemi1; Gu, Wanjian2; Li, Hua3; Wang, Zi1; Lu, Lu2; Ke, Mengying4; Lu, Jiawei5; Chen, Wenjun2; Lan, Zhangzhang1; Xiao, Yanlin1; Xu, Jinyue1; Zhang, Yi1; Cai, Zongwei6; Liu, Shijia2; Zhang, Wenyong1

2021-12-07

10.1186/s12967-021-03169-7

JOURNAL OF TRANSLATIONAL MEDICINE   影响因子和分区

1479-5876

Background Diagnosing seronegative rheumatoid arthritis (RA) can be challenging due to complex diagnostic criteria. We sought to discover diagnostic biomarkers for seronegative RA cases by studying metabolomic and lipidomic changes in RA patient serum. Methods We performed comprehensive metabolomic and lipidomic profiling in serum of 225 RA patients and 100 normal controls. These samples were divided into a discovery set (n = 243) and a validation set (n = 82). A machine-learning-based multivariate classification model was constructed using distinctive metabolites and lipids signals. Results Twenty-six metabolites and lipids were identified from the discovery cohort to construct a RA diagnosis model. The model was subsequently tested on a validation set and achieved accuracy of 90.2%, with sensitivity of 89.7% and specificity of 90.6%. Both seropositive and seronegative patients were identified using this model. A co-occurrence network using serum omics profiles was built and parsed into six modules, showing significant association between the inflammation and immune activity markers and aberrant metabolism of energy metabolism, lipids metabolism and amino acid metabolism. Acyl carnitines (20:3), aspartyl-phenylalanine, pipecolic acid, phosphatidylethanolamine PE (18:1) and lysophosphatidylethanolamine LPE (20:3) were positively correlated with the RA disease activity, while histidine and phosphatidic acid PA (28:0) were negatively correlated with the RA disease activity. Conclusions A panel of 26 serum markers were selected from omics profiles to build a machine-learning-based prediction model that could aid in diagnosing seronegative RA patients. Potential markers were also identified in stratifying RA cases based on disease activity.

Rheumatoid arthritis Seronegative Metabolomic Lipidomic

SCI

英语

第一 ; 通讯

National Natural Science Foundation of China[21904058,21904057,81774096] ; Open Projects of the Discipline of Chinese Medicine of Nanjing University of Chinese Medicine - Subject of Academic Priority Discipline of Jiangsu Higher Education Institutions[ZYX03KF031] ; Young Elite Scientists Sponsorship Program by CAST[QNRC2-B04]

Research & Experimental Medicine

Medicine, Research & Experimental

WOS:000728333100005

BMC

Web of Science

1.Southern Univ Sci & Technol, Acad Adv Interdisciplinary Studies, Sch Med, 1088 Xueyuan Rd, Shenzhen, Peoples R China
2.Nanjing Univ Chinese Med, Affiliated Hosp, Nanjing 210029, Jiangsu, Peoples R China
3.Southern Univ Sci & Technol, Sustech Core Res Facil, Shenzhen, Peoples R China
4.Nanjing Univ Chinese Med, Jiangsu Collaborat Innovat Ctr Chinese Med Resour, Coll Pharm, Nanjing 210046, Peoples R China
5.China Pharmaceut Univ, Sch Tradit Chinese Pharm, State Key Lab Nat Med, Nanjing 210009, Peoples R China
6.Hong Kong Baptist Univ, Dept Chem, State Key Lab Environm & Biol Anal SKLEBA, Kowloon Tong, Hong Kong, Peoples R China

Luan, Hemi,Gu, Wanjian,Li, Hua,et al. Serum metabolomic and lipidomic profiling identifies diagnostic biomarkers for seropositive and seronegative rheumatoid arthritis patients[J]. JOURNAL OF TRANSLATIONAL MEDICINE,2021,19(1).

Luan, Hemi.,Gu, Wanjian.,Li, Hua.,Wang, Zi.,Lu, Lu.,...&Zhang, Wenyong.(2021).Serum metabolomic and lipidomic profiling identifies diagnostic biomarkers for seropositive and seronegative rheumatoid arthritis patients.JOURNAL OF TRANSLATIONAL MEDICINE,19(1).

Luan, Hemi,et al."Serum metabolomic and lipidomic profiling identifies diagnostic biomarkers for seropositive and seronegative rheumatoid arthritis patients".JOURNAL OF TRANSLATIONAL MEDICINE 19.1(2021).