Multiple biomarkers covering several pathways for the prediction of depression after ischemic stroke

Bizhong Che; Zhengbao Zhu; Xiaoqing Bu; Jieyun Yin; Liyuan Han; Tan Xu; Zhong Ju; Jiale Liu; Jintao Zhang; Jing Chen; Jiang He; Yonghong Zhang; Chongke Zhong

doi:10.1016/j.jad.2020.10.075

Multiple biomarkers covering several pathways for the prediction of depression after ischemic stroke

J Affect Disord. 2021 Feb 1;280(Pt A):442-449. doi: 10.1016/j.jad.2020.10.075. Epub 2020 Nov 11.

Authors

Bizhong Che¹, Zhengbao Zhu², Xiaoqing Bu³, Jieyun Yin¹, Liyuan Han⁴, Tan Xu¹, Zhong Ju⁵, Jiale Liu⁶, Jintao Zhang⁷, Jing Chen⁸, Jiang He⁸, Yonghong Zhang⁹, Chongke Zhong¹⁰

Affiliations

¹ Department of Epidemiology, School of Public Health and Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, 199 Renai Road, Industrial Park District, Suzhou, Jiangsu Province, 215123, China.
² Department of Epidemiology, School of Public Health and Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, 199 Renai Road, Industrial Park District, Suzhou, Jiangsu Province, 215123, China; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA.
³ Department of Epidemiology, School of Public Health and Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, 199 Renai Road, Industrial Park District, Suzhou, Jiangsu Province, 215123, China; Department of Epidemiology, School of Public Health, Chongqing Medical University, Chongqing, China.
⁴ Department of Global Health, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, Zhejiang, PR China.
⁵ Department of Neurology, Kerqin District First People's Hospital of Tongliao City, Inner Mongolia, China.
⁶ Department of Neurology, Jilin Central Hospital, Jilin, China.
⁷ Department of Neurology, the 88th Hospital of PLA, Taian, Shandong, China.
⁸ Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA; Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA.
⁹ Department of Epidemiology, School of Public Health and Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, 199 Renai Road, Industrial Park District, Suzhou, Jiangsu Province, 215123, China. Electronic address: yhzhang@suda.edu.cn.
¹⁰ Department of Epidemiology, School of Public Health and Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, 199 Renai Road, Industrial Park District, Suzhou, Jiangsu Province, 215123, China. Electronic address: ckzhong@suda.edu.cn.

PMID: 33242715
DOI: 10.1016/j.jad.2020.10.075

Abstract

Background: To assess the potential incremental utility of multiple biomarkers reflecting several pathological pathways for the risk prediction of depression after stroke.

Methods: We used data from the China Antihypertensive Trial in Acute Ischemic Stroke, and a panel of 13 circulating biomarkers were measured. The study outcome was depression (24-item Hamilton Depression Rating Scale score≥8) at 3 months after ischemic stroke. Logistic regression models were performed to evaluate the risk of depression associated with multiple biomarkers. Discrimination and risk reclassification for depression were analyzed.

Results: Among 631 included ischemic stroke patients, elevated growth differentiation factor-15, anticardiolipin antibodies, antiphosphatidylserine antibodies and matrix metalloproteinase-9 were individually associated with increased risks of depression after stroke. The multiple biomarker analysis showed a clear gradient in the risk of depression with increasing numbers of elevated biomarkers, and multivariate adjusted odds ratio (95% confidence interval) of patients with 4 elevated biomarkers was 6.52 (2.24-18.95) compared with those without elevation in any of 4 biomarkers. The simultaneous inclusion of all 4 biomarkers to the conventional model significantly improved discrimination (C statistic increased from 0.702 to 0.748, P=0.004) and risk reclassification (net reclassification improvement 45.0%; integrated discrimination improvement 6.2%; both P<0.001) for depression after stroke.

Limitations: We selected biomarkers that had previously been reported to be promising predictors of depression after stroke, while other novel biomarkers not tested might have additional predictive value.

Conclusions: Simultaneously adding multiple biomarkers from several pathophysiological pathways to traditional risk factors provided substantial incremental utility of the risk stratification for depression after stroke.

Keywords: Acute ischemic stroke; Depression; Multiple biomarkers; Risk prediction.

Publication types

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

MeSH terms

Biomarkers
Brain Ischemia* / complications
China
Depression / diagnosis
Depression / etiology
Humans
Ischemic Stroke*
Prognosis
Risk Factors
Stroke* / complications

Substances

Biomarkers