Association of beta-2-microglobulin, cystatin C and lipocalin-2 with stroke risk in the general Chinese population

Juanying Zhen; Shuyun Liu; Ryan Yan Lam Kam; Guoru Zhao; Hao Peng; Jianguo Liang; Aimin Xu; Chao Li; Lijie Ren; Jun Wu; Bernard Man Yung Cheung

doi:10.1080/07853890.2023.2203516

Association of beta-2-microglobulin, cystatin C and lipocalin-2 with stroke risk in the general Chinese population

Ann Med. 2023 Dec;55(1):2203516. doi: 10.1080/07853890.2023.2203516.

Authors

Juanying Zhen^{1

2}, Shuyun Liu³, Ryan Yan Lam Kam², Guoru Zhao⁴, Hao Peng⁵, Jianguo Liang⁶, Aimin Xu^{2

7}, Chao Li^{1

2

7}, Lijie Ren⁸, Jun Wu¹, Bernard Man Yung Cheung^{2

7

9}

Affiliations

¹ Department of Neurology, Peking University Shenzhen Hospital, Shenzhen, China.
² Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Queen Mary Hospital, Pokfulam, Hong Kong, China.
³ Department of Neurology, Shenzhen Longhua District Central Hospital, Shenzhen, China.
⁴ CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Research Center for Neural Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
⁵ Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, China.
⁶ Precision Health Research Center Company Limited, Kowloon, Hong Kong, China.
⁷ State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Pokfulam, Hong Kong, China.
⁸ Department of Neurology, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, China.
⁹ Institute of Cardiovascular Science and Medicine, The University of Hong Kong, Hong Kong, China.

Abstract

Introduction: Beta-2-microglobulin (B2M), cystatin C and lipocalin-2 (LCN-2) are established renal biomarkers, yet their roles in stroke have not been fully evaluated. We aimed to investigate the relationship of B2M, cystatin C, and LCN-2 with stroke risk in a general Chinese population.

Methods: We used ordinal regression to study the relationship between serum B2M, cystatin C, and LCN-2 with stroke risk in 1060 participants (mean age 45.4 ± 10.8 years, 46% male) from the Shenzhen-Hong Kong United Network on Cardiovascular Disease (SHUN-CVD) study. Stroke risk was classified into low-risk, middle-risk and high-risk groups according to the China National Stroke Screening Survey criteria. Serum biomarker levels were measured using immunoturbidimetric assays. Participants with valid data on serum biomarker levels and stroke risk were included in the analysis.

Results: The number of participants in the low-risk, middle-risk and high-risk stroke risk groups were 663, 143 and 254 respectively. Elevated serum B2M, cystatin C, and LCN-2 levels were associated with being male, overweight/obesity, hypertension, alcohol consumption and smoking. Serum B2M, cystatin C and LCN-2 levels were significantly associated with stroke risk in the overall population (B2M: β = 0.595, p < .001; cystatin C: β = 3.718, p < .001; LCN-2: β = 0.564, p < .001) after adjustment for age.

Conclusion: Elevated serum B2M, cystatin C and LCN-2 levels are associated with stroke risk. They may be novel biomarkers for clinicians to assess stroke risk.Key messagesSerum beta-2-microglobulin, cystatin C and lipocalin-2 levels are significantly associated with stroke risk.Beta-2-microglobulin, cystatin C and lipocalin-2 may serve as useful biomarkers for stroke risk stratification in the general population.

Keywords: Beta-2-microglobulin; cystatin C; lipocalin-2; stroke risk.

Publication types

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

MeSH terms

Adult
Biomarkers
Creatinine
Cystatin C*
East Asian People
Female
Humans
Lipocalin-2
Male
Middle Aged
Stroke* / epidemiology
Stroke* / etiology

Substances

Cystatin C
Lipocalin-2
Biomarkers
Creatinine

Grants and funding

This work was financially supported by Hong Kong Innovation and Technology Fund, Guangdong-Hong Kong Technology Cooperation Funding Scheme (TCFS) from Hong Kong Innovation and Technology Commission (GHP/138/18SZ) and Grant of Shenzhen-Hong Kong Innovation Circle from Shenzhen Science and Technology Innovation Committee (SGLH20180629094602262).