Chemokines in Type 1 Diabetes Mellitus

Xiongfeng Pan; Atipatsa C Kaminga; Sanjay Kinra; Shi Wu Wen; Hongying Liu; Xinrui Tan; Aizhong Liu

doi:10.3389/fimmu.2021.690082

Chemokines in Type 1 Diabetes Mellitus

Front Immunol. 2022 Feb 15:12:690082. doi: 10.3389/fimmu.2021.690082. eCollection 2021.

Authors

Xiongfeng Pan¹, Atipatsa C Kaminga^{1

2}, Sanjay Kinra³, Shi Wu Wen^{4

5

6}, Hongying Liu¹, Xinrui Tan⁷, Aizhong Liu¹

Affiliations

¹ Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China.
² Department of Mathematics and Statistics, Mzuzu University, Mzuzu, Malawi.
³ Departmentof Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
⁴ Ottawa Hospital Research Institute (OMNI) Research Group, Ottawa Hospital Research Institute, Ottawa, ON, Canada.
⁵ Department of Obstetrics and Gynaecology, University of Ottawa Faculty of Medicine, Ottawa, ON, Canada.
⁶ School of Epidemiology and Public Health, University of Ottawa Faculty of Medicine, Ottawa, ON, Canada.
⁷ Department of Pediatrics, the Second Xiangya Hospital, Central South University, Changsha, China.

Abstract

Background: Previous studies suggested that chemokines may play an important role in the formation and mediation of immune microenvironments of patients affected by Type 1 Diabetes Mellitus (T1DM). The aim of this study was to summarise available evidence on the associations of different chemokines with T1DM.

Methods: Following PRISMA guidelines, we systematically searched in PubMed, Web of Science, Embase and Cochrane Library databases for studies on the associations of different chemokines with T1DM. The effect size of the associations were the standardized mean differences (SMDs) with corresponding 95% confidence intervals (CIs) of the chemokines concentrations, calculated as group differences between the T1DM patients and the controls. These were summarized using network meta-analysis, which was also used to rank the chemokines by surface under cumulative ranking curve (SUCRA) probabilities.

Results: A total of 32 original studies on the association of different chemokines with T1DM were identified. Fifteen different chemokine nodes were compared between 15,683 T1DM patients and 15,128 controls, and 6 different chemokine receptor nodes were compared between 463 T1DM patients and 460 controls. Circulating samples (blood, serum, and plasma) showed that concentrations of CCL5 and CXCL1 were significantly higher in the T1DM patients than in the controls (SMD of 3.13 and 1.50, respectively). On the other hand, no significant difference in chemokine receptors between T1DM and controls was observed. SUCRA probabilities showed that circulating CCL5 had the highest rank in T1DM among all the chemokines investigated.

Conclusion: The results suggest that circulating CCL5 and CXCL1 may be promising novel biomarkers of T1DM. Future research should attempt to replicate these findings in longitudinal studies and explore potential mechanisms underlying this association.

Keywords: chemokines; diabetes mellitus; inflammatory; network meta-analysis; type 1 diabetes mellitus.

Publication types

Meta-Analysis
Research Support, Non-U.S. Gov't

MeSH terms

Biomarkers
Chemokines
Diabetes Mellitus, Type 1* / complications
Humans
Network Meta-Analysis

Substances

Biomarkers
Chemokines