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. 2019 Jun 11;42(6):zsz048.
doi: 10.1093/sleep/zsz048.

Obstructive sleep apnea and longitudinal Alzheimer's disease biomarker changes

Omonigho M Bubu  1   2   3   4 , Elizabeth Pirraglia  2 , Andreia G Andrade  2 , Ram A Sharma  2 , Sandra Gimenez-Badia  5 , Ogie Q Umasabor-Bubu  6 , Megan M Hogan  3 , Amanda M Shim  3 , Fahad Mukhtar  1 , Nidhi Sharma  7 , Alfred K Mbah  1 , Azizi A Seixas  4 , Korey Kam  8 , Ferdinand Zizi  4 , Amy R Borenstein  9 , James A Mortimer  1 , Kevin E Kip  1 , David Morgan  10   11 , Ivana Rosenzweig  12   13 , Indu Ayappa  8 , David M Rapoport  8 , Girardin Jean-Louis  4 , Andrew W Varga  8 , Ricardo S Osorio  2   14 ; Alzheimer’s Disease Neuroimaging Initiative
Affiliations

Obstructive sleep apnea and longitudinal Alzheimer's disease biomarker changes

Omonigho M Bubu et al. Sleep. .

Abstract

Study objectives: To determine the effect of self-reported clinical diagnosis of obstructive sleep apnea (OSA) on longitudinal changes in brain amyloid PET and CSF biomarkers (Aβ42, T-tau, and P-tau) in cognitively normal (NL), mild cognitive impairment (MCI), and Alzheimer's disease (AD) elderly.

Methods: Longitudinal study with mean follow-up time of 2.52 ± 0.51 years. Data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Participants included 516 NL, 798 MCI, and 325 AD elderly. Main outcomes were annual rate of change in brain amyloid burden (i.e. longitudinal increases in florbetapir PET uptake or decreases in CSF Aβ42 levels); and tau protein aggregation (i.e. longitudinal increases in CSF total tau [T-tau] and phosphorylated tau [P-tau]). Adjusted multilevel mixed effects linear regression models with randomly varying intercepts and slopes was used to test whether the rate of biomarker change differed between participants with and without OSA.

Results: In NL and MCI groups, OSA+ subjects experienced faster annual increase in florbetapir uptake (B = .06, 95% CI = .02, .11 and B = .08, 95% CI = .05, .12, respectively) and decrease in CSF Aβ42 levels (B = -2.71, 95% CI = -3.11, -2.35 and B = -2.62, 95% CI = -3.23, -2.03, respectively); as well as increases in CSF T-tau (B = 3.68, 95% CI = 3.31, 4.07 and B = 2.21, 95% CI = 1.58, 2.86, respectively) and P-tau (B = 1.221, 95% CI = 1.02, 1.42 and B = 1.74, 95% CI = 1.22, 2.27, respectively); compared with OSA- participants. No significant variations in the biomarker changes over time were seen in the AD group.

Conclusions: In both NL and MCI, elderly, clinical interventions aimed to treat OSA are needed to test if OSA treatment may affect the progression of cognitive impairment due to AD.

Keywords: Alzheimer’s disease; Aβ42; CSF biomarkers; P-tau; T-tau; brain amyloid PET; longitudinal study; obstructive sleep apnea.

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Figures

Figure 1.
Figure 1.
Stepwise exclusion process for NL, MCI, and AD participants used in the study.
Figure 2.
Figure 2.
Mean change variations and trajectory plots in AD biomarker values over time in NL, MCI, and AD subjects by OSA status (cognitive normal—NL).
Figure 3.
Figure 3.
Mean change variations and trajectory plots in AD biomarker values over time in NL, MCI, and AD subjects by OSA status (mild cognitive impairment—MCI).
Figure 4.
Figure 4.
Mean change variations and trajectory plots in AD biomarker values over time in NL, MCI, and AD subjects by OSA status (Alzheimer’s disease—AD).
Figure 5.
Figure 5.
Proposed mechanisms linking OSA with amyloid deposition in late-life.
See this image and copyright information in PMC

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