Association between ultra-short heart rate variability and risk of Parkinson's disease: a prospective cohort study

超短时程心率变异性与帕金森病风险之间的关联:一项前瞻性队列研究

阅读:1

Abstract

BACKGROUND: Cross-sectional studies have suggested that patients with Parkinson's disease (PD) have significantly lower heart rate variability (HRV) than healthy controls. However, the role of ultra-short HRV (usHRV) as an early biomarker for PD remains unclear. The objective of this study was to investigate the association between usHRV and PD risk and its underlying mechanisms. METHODS: In a prospective cohort study based on the UK Biobank, participants without PD and dementia at baseline who had available 15-second resting electrocardiogram data (n = 48 202) were included. The participants were followed up for an average of 12.24 years, and some were diagnosed with PD (n = 307). Cox proportional hazards models were used to examine the association between usHRV parameters and PD risk. A nested case-control study was conducted within the cohort to further investigate temporal trends in HRV. Mediation analysis was used to explore the underlying mechanisms driven by brain structure, peripheral inflammation, and proteomic biomarkers. RESULTS: We found that lower usHRV parameters were significantly associated with an increased PD risk. Notably, an L-shaped association was observed between the corrected root mean square of successive differences and PD risk. Temporal trend analysis suggested usHRV levels of patients with PD started to decline approximately 10 years before diagnosis. Mediation analysis revealed that thalamus-related fiber tracts, plasma inflammatory, and neuroendocrine markers mediated the association between usHRV and PD risk. CONCLUSIONS: Our findings provide evidence supporting that usHRV may serve as an early, convenient, and noninvasive biomarker of PD risk up to a decade before diagnosis.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。