SBAV: A Sex-Stratified Precision Framework for Predicting Sleep Apnea–Driven Neurodegeneration in Aging Women

TL;DR

This paper introduces SBAV, a new framework to better detect sleep apnea-related cognitive risks in aging women, using a combination of genomics, hormones, and brain activity data.

Contribution

SBAV is a sex-stratified precision model that integrates multi-modal data to improve early detection of OSA-associated cognitive decline in women.

Findings

Women with OSA show distinct EEG patterns linked to elevated tau and memory decline.

Hormonal depletion and APOE ε4 increase neurodegenerative vulnerability in women with OSA.

SBAV outperforms traditional AHI-based methods by 35–42% in identifying female OSA cases.

Abstract

Background Obstructive sleep apnea (OSA) is a known risk factor for cognitive impairment, yet remains underrecognized in aging women. Traditional tools such as STOP-BANG and apnea–hypopnea index (AHI) thresholds were validated in male cohorts, failing to account for hormonal decline, altered sleep architecture, and sex-specific neuroinflammation post-menopause. Objective To develop and present the SBAV (Sleep–Brain–Aging Vulnerability) framework—a multi-modal, sex-stratified precision model integrating genomics, electrophysiology, hormonal markers, and AI-supported analytics to improve early detection of OSA-associated cognitive risk in women. Methods A structured scoping review (2018–2024) was conducted using PubMed, Scopus, and Web of Science. Key domains included: - Genomics (APOE ε4, CRY1, CLOCK) - Proteomics (tau, amyloid-β, IL-6, BDNF) - Endocrine markers (estrogen, cortisol) - EEG sleep microarchitecture (spindle loss, REM/NREM fragmentation) - Neuroimaging features (hippocampal atrophy) Findings were synthesized into a sex-stratified dashboard linking EEG and biomarker data with cognitive profiles. Results Women with OSA demonstrate a distinct EEG phenotype: reduced spindle density, altered slow-wave activity, and delayed cortical arousal, correlated with elevated tau and memory decline. Hormonal depletion and APOE ε4 synergistically amplify neurodegenerative vulnerability under intermittent hypoxia. Standard diagnostics miss over 40% of female cases. SBAV integrates omics, EEG, and hormonal data to outperform AHI-based stratification by 35–42%, enabling earlier, sex-specific risk identification. Conclusion SBAV redefines OSA in women as a sex-dependent neurodegenerative amplifier, proposing a paradigm shift in sleep and dementia screening. By leveraging AI-assisted, multi-omic stratification, this model lays the groundwork for tailored women’s cognitive prevention in midlife.