Lifespan cardiometabolic exposures are associated with midlife white matter microstructure: The Bogalusa Heart Study

IF 4.7 2区 医学 Q1 NEUROIMAGING
Reagan Dugan , Sreekrishna Ramakrishnapillai , Julia St Amant , Kori Murray , Kevin McKlveen , Maryam Naseri , Kaitlyn Madden , Lydia Bazzano , Owen Carmichael
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引用次数: 0

Abstract

Introduction

Compartment model analysis of diffusion MRI data provides unique information on the microstructural properties of white matter. However, studies relating compartment model microstructural measures to longitudinal cardiometabolic health data are rare.

Methods

130 cognitively healthy participants in the Bogalusa Heart Study completed diffusion MRI scans. Compartment model analysis was performed, and summary metrics were measured in organized and diffuse white matter. Multiple linear regression models were used to relate the white matter microstructure metrics to demographics and cardiometabolic risk factors.

Results

In both organized and diffuse white matter, age was associated with worse diffusion metrics, women had better diffusion metrics than men, and African American participants had worse diffusion metrics compared to White participants. Greater blood pressure in pre-adulthood was associated with worse diffusion metrics in midlife.

Discussion

Summary metrics from compartment model analyses of diffusion MRI data were associated cardiometabolic risk factors from youth to midlife as well as demographic factors.
寿命心脏代谢暴露与中年白质微观结构有关:Bogalusa心脏研究。
扩散MRI数据的室室模型分析提供了白质微观结构特性的独特信息。然而,将室室模型微观结构测量与纵向心脏代谢健康数据联系起来的研究很少。方法:Bogalusa心脏研究中130名认知健康的参与者完成了弥散MRI扫描。进行隔室模型分析,并在组织和弥漫性白质中测量总结指标。使用多元线性回归模型将白质微观结构指标与人口统计学和心脏代谢危险因素联系起来。结果:在组织白质和弥漫性白质中,年龄与较差的弥散指标相关,女性的弥散指标优于男性,非裔美国参与者的弥散指标优于白人参与者。成年前较高的血压与中年时较差的弥散指标相关。讨论:弥散MRI数据的室室模型分析的总结指标与从青年到中年的心脏代谢危险因素以及人口统计学因素相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
NeuroImage
NeuroImage 医学-核医学
CiteScore
11.30
自引率
10.50%
发文量
809
审稿时长
63 days
期刊介绍: NeuroImage, a Journal of Brain Function provides a vehicle for communicating important advances in acquiring, analyzing, and modelling neuroimaging data and in applying these techniques to the study of structure-function and brain-behavior relationships. Though the emphasis is on the macroscopic level of human brain organization, meso-and microscopic neuroimaging across all species will be considered if informative for understanding the aforementioned relationships.
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