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英国生物银行中脑健康指数的标准值。

Normative values of the brain health index in UK biobank.

作者信息

Watt Jodi K, Dickie David Alexander, Lyall Donald M, Ward Joey, Ho Frederick K, Dawson Jesse, Quinn Terence J

机构信息

School of Cardiovascular and Metabolic Health, University of Glasgow, UK.

School of Health and Wellbeing, University of Glasgow, UK.

出版信息

Neuroimage Rep. 2023 Jun 20;3(3):100176. doi: 10.1016/j.ynirp.2023.100176. eCollection 2023 Sep.

Abstract

BACKGROUND

The Brain Health Index (BHI) is an automated approach to quantifying brain integrity, combining different types of structural magnetic resonance imaging (MRI). Normative values derived from generally healthy individuals provide a vital baseline for understanding neurodegenerative change. Although commonplace in other areas of medicine, these are not always established when proposing new analytical approaches using MRI. The scale and quality of the UK Biobank imaging cohort (approximately N = 50k, as of 2022) allows for derivation of such values, and the wealth of additional lifestyle, physiological and demographic data enables validation of BHI through comparison with more established variables which may affect brain health.

AIM

This study aimed to: 1) establish normative BHI values in a cohort of 'healthy' participants, and 2) explore associations between BHI and risk factors for brain health.

METHODS

The BHI was computed using voxel-based Gaussian mixture model cluster analysis of T1 and T2 FLAIR MRI in a sub-cohort of UK Biobank participants. From these data, normative score curves - with bounds described as 1, 2 and 3 standard deviations from the mean - were produced for males and females, using regression analyses to measure the scale of the BHI values as a function of age. Additional Pearson's correlation testing was used to examine known risk factors to brain health and their relationship to BHI scores, with t-tests and ANOVAs used to determine between-group differences in BHI scoring.

RESULTS

Data from 2,990 participants (50.07% male, 97.05% Caucasian, 43.6% with degree-level education) were used to derive normative BHI curves from 48 to 77 years old. BHI scores were higher in female than male participants (95% CI: 0.0103 to 0.0162, <0.001, Cohen's d = 0.0416), males with a degree (95% CI: 0.000 to 0.009;  < 0.05; Cohen's d = 0.044), and lower in people with type 2 diabetes mellitus (95% CI: 0.018 to 0.033; p <0.001; Cohen's d = 0.0417), hypertension (95% CI: 0.008 to 0.018; p <0.001; Cohen's d = 0.0419), and regular smokers (95% CI: 0.009 to 0.017, p <0.001, Cohen's d = 0.041). BHI scores were higher in those with lower waist-to-hip ratios (WHR; males: R = 0.02121, F(1, 1466) = 31.77, p <0.001; females: R = 0.02201, F(1, 1454) = 32.72, p <0.001), and lower pulse pressure (males: R = 0.06261, F(1, 1215) = 81.16, p <0.001; females: R = 0.07616, F(1, 1205) = 99.34, p <0.001).

CONCLUSIONS

BHI score curves may provide useful reference values for future clinical research. More work is required to determine normative values in more diverse populations.

摘要

背景

脑健康指数(BHI)是一种通过结合不同类型的结构磁共振成像(MRI)来量化脑完整性的自动化方法。从一般健康个体得出的标准值为理解神经退行性变化提供了至关重要的基线。尽管在医学的其他领域很常见,但在提出使用MRI的新分析方法时,这些标准值并不总是确定的。英国生物银行成像队列的规模和质量(截至2022年约N = 50k)允许得出此类值,并且丰富的其他生活方式、生理和人口统计学数据能够通过与可能影响脑健康的更成熟变量进行比较来验证BHI。

目的

本研究旨在:1)在一组“健康”参与者中建立BHI标准值,以及2)探索BHI与脑健康风险因素之间的关联。

方法

使用基于体素的高斯混合模型聚类分析对英国生物银行参与者子队列中的T1和T2 FLAIR MRI计算BHI。从这些数据中,使用回归分析来测量BHI值随年龄变化的尺度,为男性和女性生成标准评分曲线,其界限描述为距平均值1、2和3个标准差。额外的皮尔逊相关性检验用于检查已知的脑健康风险因素及其与BHI评分的关系,使用t检验和方差分析来确定BHI评分的组间差异。

结果

来自2990名参与者(50.07%为男性,97.05%为白种人,43.6%具有学位水平教育)的数据用于得出48至77岁的BHI标准曲线。女性参与者的BHI评分高于男性(95%置信区间:0.0103至0.0162,p<0.001,科恩d = 0.0416),有学位的男性(95%置信区间:0.000至0.009;p<0.05;科恩d = 0.044),而2型糖尿病患者(95%置信区间:0.018至0.033;p<0.001;科恩d = 0.0417)、高血压患者(95%置信区间:0.008至0.018;p<0.001;科恩d = 0.0419)和经常吸烟者(95%置信区间:0.009至0.017,p<0.001,科恩d = 0.041)的BHI评分较低。腰臀比(WHR)较低者的BHI评分较高(男性:R = 0.02121,F(1, 1466) = 31.77,p<0.001;女性:R =

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a7e/12172921/cbe92c50a12b/gr1.jpg

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