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Sema4D as a biomarker for Predicting rheumatoid arthritis disease activity

  • ORIGINAL ARTICLE
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Clinical Rheumatology Aims and scope Submit manuscript

Abstract

Objective

The semaphorins are membrane or secreted proteins first identified in neural development. Semaphorin 4D (Sema4D) is the first family member found to have immune properties. We evaluated the potential of Sema4D as a marker for rheumatoid arthritis (RA) disease activity, singly and in combination with other known biomarkers including rheumatoid factor (RF) and C-reactive protein (CRP).

Methods

Three hundred and eleven RA patients were enrolled. The patients were divided into three groups based on their disease activity in 28 joints (DAS28): mild, moderate, and severe. The healthy group included 40 healthy individuals. SerumSema4D was measured by quantitative ELISA and the specificity and sensitivity of biomarkers were evaluated by generating a receiver operating characteristic (ROC) curve to analyze their diagnostic accuracy.

Results

Serum Sema4D levels in the moderate and severe RA groups were elevated significantly above those of the controls (P < 0.01), while levels in the mild RA and control groups did not differ significantly (P > 0.05). The Sema4D cutoff threshold was 15.7 ng/ml when the DAS28 was applied as a reference. Compared to the erythrocyte sedimentation rate (ESR and CRP, Sema4D had the highest specificity (96.8%) and area under the curve (0.80) for diagnosing RA activity. The highest specificity (100%) for the biomarker combinations was obtained when Sema4D was combined with CRP and anti-CCP, the combination of the Sema4D combined with ESR and anti-CCP had the highest sensitivity (99.35%). According to this result, a new model for jointly calculating RA activity of Sema4D,anti-CCP and CRP was constructed. Meanwhile another model is established by using the method of multivariate analysis.Model comparison results showed the the multiple regression algorithm method fitted the patients' disease activity better.

Conclusion

The serum Sema 4D level effectively reflects moderate to severe RA activity. Sema4D levels can be used together with conventional RA biomarkers to increase the diagnostic power of RA activity. The multiple regression algorithm method is promising in disease activity calculation.

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Data availability

The datasets used and or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

RA :

Rheumatoid arthritis

Sema4D :

Semaphorin 4D

DAS28 :

Disease Activity Score in 28 joints

SDAI :

Simplified Disease Activity Index

CDAI :

Clinical Disease Activity Index

anti-CCP :

Anti-cyclic citrullinated peptide antibody

RF :

Rheumatoid factor

CRP :

C-reactive protein

ESR :

Erythrocyte sedimentation rate

NE :

Neutrophil

MONO :

Monocytes

PLT :

Platelecount

LY :

Lymphocyte

PCT :

Plateletcrit

PDW :

Platelet distribution width

RBC :

Red blood cell

HGB :

Hemoglobin

TC :

Total cholesterol

TG :

Triglycerides

GLU :

Glucose

C3 :

Complement 3

C4 :

Complement 4

LDL :

Low-density lipoprotein

HDL :

High-density lipoprotein

a :

The data are presented as the mean ± standard deviation.

b :

The data are presented as the median and interquartile range

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Acknowledgements

We thank all participating subjects who provided blood samples and clinical information necessary for this study.

Funding

This work was supported by National Natural Science Foundation of China (Grant No. 82173604), The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Department of Clinical Epidemiology and Evidence-Based Medicine, the First Affiliated Hospital, China Medical University, Shenyang, China

    Huiyuan Liu, Yuelin Zhang, Jiaming Cao, Jiahui Li, Ruobing Liao & Lingyu Fu

  2. Department of Medical Record Management Center, the First Affiliated Hospital, China Medical University, Shenyang, China

    Lingyu Fu

  3. Department of Rheumatology, the First Affiliated Hospital, China Medical University, Shenyang, China

    Haina Liu

  4. Department of Rheumatology, Dalian Municipal Central Hospital Affiliated of Dalian Medical University, Dalian, China

    Bingbing Dai

  5. Department of Rheumatology, ShengJing Hospital Affiliated of China Medical University, Shenyang, China

    Lei Jin

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  1. Huiyuan Liu
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Corresponding author

Correspondence to Lingyu Fu.

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Ethics approval and consent to participate

The study protocol was approved by Institutional Medical Ethics Review Board of the First Affiliated Hospital of China Medical University (AF-SOP-07–1.0–01). Informed written consent was obtained from all study participants according to the principlesof the Declaration of Helsinki.

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All of the subjects provided written informed consent for publication.

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Liu, H., Zhang, Y., Cao, J. et al. Sema4D as a biomarker for Predicting rheumatoid arthritis disease activity. Clin Rheumatol 43, 645–655 (2024). https://doi.org/10.1007/s10067-023-06840-0

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  • DOI: https://doi.org/10.1007/s10067-023-06840-0

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