Alterations of brain gray matter volume in children with obstructive sleep apnea

Yu, Chenyi; Fu, Yuchuan; Lee, Yi; Huang, Yufan; Chen, Fang‐Fang; Wei, Jiayun; Li, Lingling; Ampadu, Janet Akoto; Yu, Wenbin; Wang, Zheng; Jiang, Changcan; Li, Weiyuan; Lui, Su; X, Cai

doi:10.3389/fneur.2023.1107086

Cited by 7 publications

(1 citation statement)

References 39 publications

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“…These effects were further associated with individual differences in CSF levels of Aβ42 and p-tau proteins and global cognitive function, with SDB status influencing the associations of Aβ burden, rFDG, and GMV with CSF biomarkers and cognitive function. Of note, the independent impact of SDB on brain atrophy has been reported previously, even in children and middle-aged adults [50][51][52][53] . SDB may thus represent a critical factor triggering greater cognitive vulnerability to AD pathophysiology.…”

Section: Discussionsupporting

confidence: 68%

How is sleep-disordered breathing linked with biomarkers of Alzheimer’s disease?

Akradi,

Farzane-Daghigh,

Ebneabbasi

et al. 2023

Preprint

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Sleep-disordered breathing (SDB) is prevalent in Alzheimer disease (AD). We assessed whether and how SDB affects neuroimaging biomarkers of AD, including amyloid-beta plaque burden (Ab), regional uptake of fluorodeoxyglucose using positron emission tomography (rFDG-PET), grey matter volume (GMV), as well as cognitive scores and cerebrospinal fluid (CSF) biomarkers. We selected 757 subjects from the Alzheimer Disease Neuroimaging Initiative (ADNI) database based on cognitive status (AD, mild cognitive impairment (MCI), cognitively unimpaired (CU)), and SDB condition (with/without SDB). To ensure the reliability of our findings and considering imbalanced sample size across groups, we used a stratified subsampling approach generating 10,000 subsamples (n=10/group). We then selected 512 subsamples with matched covariates. The effect size of the cognitive status-SDB interaction was computed for each biomarker and cognitive score. For reference, we computed 1000 null models by shuffling group labels randomly. The average value of effect sizes for each biomarker in each region was estimated through bootstrapping with 10,000 iterations for both the main and null models and compared with the null model distribution. Linear regression models were next implemented to identify associations between the effect size on Ab, rFDG, and GMV with the effect size on cognitive scores and CSF biomarkers across all subsamples. The cognitive status-SDB interaction had a medium-sized effect on Ab, rFDG and GMV biomarkers in several brain areas. The effect sizes of the mentioned interactions on Ab plaque burden in the right precuneus, left middle temporal gyrus, and left occipital fusiform gyrus were associated with the effect sizes of the interactions on cognitive scores. Further, the interaction effect sizes on CSF Ab were related to the interaction effect sizes on Ab in the right precuneus and posterior cingulate cortex, as well as rFDG in the left precuneus cortex and GMV in bilateral angular gyrus and right occipital fusiform gyrus. Effect sizes on CSF p-tau were also correlated with the effect sizes on Ab in the left lateral occipital cortex and GMV in the left middle temporal gyrus. We observed that SDB interacts with neuroimaging and CSF biomarkers of AD. Specifically, SDB has a robust association with markers of Ab pathology in PET and CSF relative to rFDG and GMV in the AD group. The cognitive status-SDB interaction on Ab is associated with cognitive decline. This study further supports the hypothesis that SDB may precipitate AD pathology.

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Section: Discussionsupporting

confidence: 68%