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Cheng L, Li Y, Wu Z, et al. Comprehensive analysis of immunoglobulin and clinical variables identifies functional linkages and diagnostic indicators associated with Behcet's disease patients receiving immunomodulatory treatment. BMC Immunol. 2021;22(1):16doi: 10.1186/s12865-021-00403-1.
Cheng, L., Li, Y., Wu, Z., Li, L., Liu, C., Liu, J., Dai, J., Zheng, W., Zhang, F., Tang, L., Yu, X., & Li, Y. (2021). Comprehensive analysis of immunoglobulin and clinical variables identifies functional linkages and diagnostic indicators associated with Behcet's disease patients receiving immunomodulatory treatment. BMC immunology, 22(1), 16. https://doi.org/10.1186/s12865-021-00403-1
Cheng, Linlin, et al. "Comprehensive analysis of immunoglobulin and clinical variables identifies functional linkages and diagnostic indicators associated with Behcet's disease patients receiving immunomodulatory treatment." BMC immunology vol. 22,1 (2021): 16. doi: https://doi.org/10.1186/s12865-021-00403-1
Cheng L, Li Y, Wu Z, Li L, Liu C, Liu J, Dai J, Zheng W, Zhang F, Tang L, Yu X, Li Y. Comprehensive analysis of immunoglobulin and clinical variables identifies functional linkages and diagnostic indicators associated with Behcet's disease patients receiving immunomodulatory treatment. BMC Immunol. 2021 Feb 22;22(1):16. doi: 10.1186/s12865-021-00403-1. PMID: 33618671; PMCID: PMC7901184.
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BMC Immunol. 2021 Feb 22;22(1):16. doi: 10.1186/s12865-021-00403-1.

Comprehensive analysis of immunoglobulin and clinical variables identifies functional linkages and diagnostic indicators associated with Behcet's disease patients receiving immunomodulatory treatment.

BMC immunology

Linlin Cheng, Yang Li, Ziyan Wu, Liubing Li, Chenxi Liu, Jianhua Liu, Jiayu Dai, Wenjie Zheng, Fengchun Zhang, Liujun Tang, Xiaobo Yu, Yongzhe Li

Affiliations

  1. Department of Clinical Laboratory, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
  2. State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, No. 38, Life Science Park Road Changping District, Beijing, 102206, China.
  3. Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Key Laboratory of Rheumatology and Clinical Immunology, Ministry of Education, Beijing, 100730, China.
  4. Department of Laboratory Medicine, Shengjing Hospital of China Medical University, Shenyang, 110004, China.
  5. State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, No. 38, Life Science Park Road Changping District, Beijing, 102206, China. [email protected].
  6. State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, No. 38, Life Science Park Road Changping District, Beijing, 102206, China. [email protected].
  7. Department of Clinical Laboratory, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China. [email protected].

PMID: 33618671 PMCID: PMC7901184 DOI: 10.1186/s12865-021-00403-1

Abstract

BACKGROUND: Behcet's disease (BD) is a relapsing systemic vascular autoimmune/inflammatory disease. Despite much effort to investigate BD, there are virtually no unique laboratory markers identified to help in the diagnosis of BD, and the pathogenesis is largely unknown. The aim of this work is to explore interactions between different clinical variables by correlation analysis to determine associations between the functional linkages of different paired variables and potential diagnostic biomarkers of BD.

METHODS: We measured the immunoglobulin proteome (IgG, IgG1-4, IgA, IgA1-2) and 29 clinical variables in 66 healthy controls and 63 patients with BD. We performed a comprehensive clinical variable linkage analysis and defined the physiological, pathological and pharmacological linkages based on the correlations of all variables in healthy controls and BD patients without and with immunomodulatory therapy. We further calculated relative changes between variables derived from comprehensive linkage analysis for better indications in the clinic. The potential indicators were validated in a validation set with 76 patients with BD, 30 healthy controls, 18 patients with Takayasu arteritis and 18 patients with ANCA-associated vasculitis.

RESULTS: In this study, the variables identified were found to act in synergy rather than alone in BD patients under physiological, pathological and pharmacological conditions. Immunity and inflammation can be suppressed by corticosteroids and immunosuppressants, and integrative analysis of granulocytes, platelets and related variables is likely to provide a more comprehensive understanding of disease activity, thrombotic potential and ultimately potential tissue damage. We determined that total protein/mean corpuscular hemoglobin and total protein/mean corpuscular hemoglobin levels, total protein/mean corpuscular volume, and plateletcrit/monocyte counts were significantly increased in BD compared with controls (P < 0.05, in both the discovery and validation sets), which helped in distinguishing BD patients from healthy and vasculitis controls. Chronic anemia in BD combined with increased total protein contributed to higher levels of these biomarkers, and the interactions between platelets and monocytes may be linked to vascular involvement.

CONCLUSIONS: All these results demonstrate the utility of our approach in elucidating the pathogenesis and in identifying novel biomarkers for autoimmune diseases in the future.

Keywords: Clinical variable; Corticosteroids; Immunoglobulin; Immunosuppressants; Plasma microarray

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