In a recent study posted to the medRxiv* preprint server, researchers evaluated the impact of sleep-disordered breathing (SDB) on neuroimaging biomarkers of Alzheimer's disease (AD).

Study: How is sleep-disordered breathing linked with biomarkers of Alzheimer’s disease? Image Credit: fizkes/Shutterstock.com

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Background

SDB and insomnia are modifiable risk factors for AD, affecting cognitive functions like attention, language, and reasoning.

Lifestyle factors like exercise and cardiovascular health management can decrease dementia risk. Modifiable risk factors include obesity, hypertension, diabetes, and vascular disease.

Sleep disturbances, such as SDB, may interact with AD pathophysiology, increasing the risk of developing AD and exacerbating cognitive impairments.

About the study

The present study explored interactions between sleep-disordered breathing, cognitive status, and Alzheimer's disease (AD) biomarkers.

The team selected 757 individuals from the AD Neuroimaging Initiative database (ADNI) after evaluating their cognitive status [cognitively unimpaired (CU), mild cognitive impairment (MCI), and AD] and sleep-disordered breathing condition (with or without SDB).

Stratified subsampling was performed to increase the robustness and reliability of the results and consider imbalanced sample sizes across groups.

The sampling procedure generated 10,000 sub-samples [10 per group matched in terms of covariates such as age, sex, body mass index (BMI), and apolipoprotein E (APOE ε4)]. Subsequently, 512 covariate-matched subsamples were selected.

The neuroimaging biomarkers investigated included amyloid-beta (Aβ) positron emission tomography (PET) imaging, gray matter volume (GMV) of cortical and subcortical brain areas, regional uptake of fluorodeoxyglucose using PET (rFDG-PET), cerebrospinal fluid (CSF), and cognitive scores.

Intra-subject structural magnetic resonance imaging (sMRI) and PET information were matched for each individual, and voxel-based morphometry (VBM) was performed.

Aβ PET assessments were performed as a proxy for Aβ plaque burden in the brain; rFDG indicated glucose metabolism as a surrogate of neural activity in the brain; and GMV values indicated brain structure.

Mini-Mental State Examination (MMSE) scores were evaluated to evaluate the cognitive performance of the individuals. CSF Aβ42, p-tau, and MMSE data were obtained from the subject's medical history.

The cognitive score-sleep-disordered breathing association effect size was determined for all biomarkers and cognitive scores. For reference, 1,000 null models were computed by random shuffling of group labels.

The mean effect size for every biomarker was estimated by bootstrapping for 10,000.0 iterations using the null and main models and comparing them with the distribution of the null model.

Linear regression modeling was performed to determine the effect sizes for the interactions between the cognitive scores, GMV, Aβ, rFDG biomarkers, and cerebrospinal fluid biomarkers across the subsamples.

Individuals with a history of Parkinson's disease, brain malignancies, or stroke were excluded from the analysis. In addition, SDB+ individuals who had received bi-level positive airway pressure (BiPAP) or continuous positive airway pressure (CPAP) were excluded.

Results and discussion

The interaction between cognitive status and sleep-disordered breathing had medium-sized effects on GMB, rFDG, and Aβ biomarkers in multiple brain regions.

The effect size for Aβ burden interaction in the fusiform gyrus of the left occipital lobe, the right precuneus, and the middle gyrus of the temporal lobe were related to those for cognitive score interactions.

Furthermore, the association effect sizes for cerebrospinal fluid Aβ42 were associated with those for amyloid-beta in the posterior cingulate cortex (PCC) and right precuneus, GMV in the right and left angular gyri, the fusiform gyrus in the right occipital region, and the regional FDG uptake in the precuneus cortex of the left brain.

In addition, effect sizes for cerebrospinal fluid p-tau protein were correlated with those for GMV in the middle gyrus of the left temporal lobe and Aβ protein in the lateral portion of the left occipital cortex.

There was a strong association between SDB and various AD biomarkers across disease stages, with higher structural atrophy and functional hyperactivity and lower amyloid burden in the preclinical and prodromal stages in SDB-positive individuals than in SDB-negative ones.

Particularly, Aβ burden was increased among SDB-positive individuals in AD, indicating that SDB degenerates AD-vulnerable brain networks independently of AD pathophysiology, increasing cognitive vulnerability to AD pathophysiology and resulting in earlier clinical conversion at lower levels of pathology.

Intermittent hypoxia, sleep fragmentation, age-related cellular and molecular impairments, and synaptic integrity alter synaptic integrity, enhancing brain vulnerability earlier than Aβ accumulation.

In later stages, when subjects have higher levels of Aβ accumulation, SDB and AD have synergic maladaptive effects exacerbated by genetic, environmental, and lifestyle factors.

The changes, combined with genetic, environmental, and lifestyle factors, increase the accumulation of Aβ in the brain and the aggregation and distribution of insoluble tau protein, leading to brain metabolic, functional, and structural alterations and increasing brain vulnerability to AD pathophysiology and cognitive decline.

Conclusion

Overall, the study findings showed that SDB is linked to cognitive decline in Alzheimer's patients, as it is strongly related to Aβ pathology in positron emission tomography and cerebrospinal fluid.

The findings indicated that SDB may increase brain vulnerability to AD pathophysiology.

The interaction between SDB and Aβ protein in CU and MCI may lead to neuronal hyperactivity, independent of AD pathologies, contributing to cognitive impairment and decline.

*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Written by

Pooja Toshniwal Paharia

Dr. based clinical-radiological diagnosis and management of oral lesions and conditions and associated maxillofacial disorders.