Normative values of the brain health index in UK biobank

Q4 Neuroscience
Jodi K. Watt , David Alexander Dickie , Donald M. Lyall , Joey Ward , Frederick K. Ho , Jesse Dawson , Terence J. Quinn
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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, p <0.001, Cohen’s d = 0.0416), males with a degree (95% CI: 0.000 to 0.009; p < 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: R2 = 0.02121, F(1, 1466) = 31.77, p <0.001; females: R2 = 0.02201, F(1, 1454) = 32.72, p <0.001), and lower pulse pressure (males: R2 = 0.06261, F(1, 1215) = 81.16, p <0.001; females: R2 = 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.

英国生物库脑健康指数的正常值
背景大脑健康指数(BHI)是一种结合不同类型的结构磁共振成像(MRI)来量化大脑完整性的自动化方法。来自一般健康个体的正常值为理解神经退行性变化提供了重要的基线。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,这些并不总是成立的。英国生物银行成像队列的规模和质量(截至2022年,约N=5万)允许推导这些值,而丰富的额外生活方式、生理和人口统计数据使BHI能够通过与可能影响大脑健康的更多既定变量进行比较来验证。目的本研究旨在:1)在一组“健康”参与者中建立规范的BHI值,2)探索BHI与大脑健康风险因素之间的关系。方法在英国生物银行参与者的子队列中,使用基于体素的T1和T2 FLAIR MRI高斯混合模型聚类分析来计算BHI。根据这些数据,使用回归分析来测量BHI值作为年龄函数的规模,为男性和女性生成了标准得分曲线,其边界描述为与平均值的1、2和3个标准差。使用额外的Pearson相关检验来检查已知的大脑健康风险因素及其与BHI评分的关系,并使用t检验和方差分析来确定BHI评分中的组间差异。结果2990名参与者(50.07%为男性,97.05%为白人,43.6%为学历)的数据用于推导48至77岁的标准BHI曲线。女性参与者的BHI得分高于男性参与者(95%可信区间:0.0103至0.0162,p<0.001,Cohen’s d=0.0416)、有学位的男性参与者(95%可信区间:0.000至0.009;p<0.05;Cohen’sd=0.044),而2型糖尿病患者的BHI分较低(95%置信区间:0.018至0.033;p<0.001;Cohen‘s d=0.04 17)、,和经常吸烟的人(95%可信区间:0.009至0.017,p<0.001,Cohen’s d=0.041)。腰臀比较低的人的BHI得分较高(WHR;男性:R2=0.02121,F(11466)=31.77,p<0.01);0.001;雌性:R2=0.02201,F(11454)=32.72,p<;0.001)和较低的脉压(男性:R2=0.06261,F(1215)=81.16,p<;0.001;雌性:R2=0.07616,F(11205)=99.34,p<;结论sHI评分曲线可为今后的临床研究提供有用的参考价值。需要做更多的工作来确定更多样化人群的规范价值。
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. Reports
Neuroimage. Reports Neuroscience (General)
CiteScore
1.90
自引率
0.00%
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审稿时长
87 days
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