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. 2023 Jul 11;101(2):e125-e136.
doi: 10.1212/WNL.0000000000207392. Epub 2023 May 10.

Association of Polysomnographic Sleep Parameters With Neuroimaging Biomarkers of Cerebrovascular Disease in Older Adults With Sleep Apnea

Diego Z Carvalho  1 , Stuart J McCarter  2 , Erik K St Louis  2 , Scott A Przybelski  2 , Kohl L Johnson Sparrman  2 , Virend K Somers  2 , Bradley F Boeve  2 , Ronald C Petersen  2 , Clifford R Jack Jr  2 , Jonathan Graff-Radford  2 , Prashanthi Vemuri  2
Affiliations

Association of Polysomnographic Sleep Parameters With Neuroimaging Biomarkers of Cerebrovascular Disease in Older Adults With Sleep Apnea

Diego Z Carvalho et al. Neurology. .

Abstract

Background and objectives: Our objective was to determine whether polysomnographic (PSG) sleep parameters are associated with neuroimaging biomarkers of cerebrovascular disease (CVD) related to white matter (WM) integrity in older adults with obstructive sleep apnea (OSA).

Methods: From the population-based Mayo Clinic Study of Aging, we identified participants without dementia who underwent at least 1 brain MRI and PSG. We quantified 2 CVD biomarkers: WM hyperintensities (WMHs) from fluid-attenuated inversion recovery (FLAIR)-MRI, and fractional anisotropy of the genu of the corpus callosum (genu FA) from diffusion MRI. For this cross-sectional analysis, we fit linear models to assess associations between PSG parameters (NREM stage 1 percentage, NREM stage 3 percentage [slow-wave sleep], mean oxyhemoglobin saturation, and log of apnea-hypopnea index [AHI]) and CVD biomarkers (log of WMH and log of genu FA), respectively, while adjusting for age (at MRI), sex, APOE ε4 status, composite cardiovascular and metabolic conditions (CMC) score, REM stage percentage, sleep duration, and interval between MRI and PSG.

Results: We included 140 participants with FLAIR-MRI (of which 103 had additional diffusion MRI). The mean ± SD age was 72.7 ± 9.6 years at MRI with nearly 60% being men. The absolute median (interquartile range [IQR]) interval between MRI and PSG was 1.74 (0.9-3.2) years. 90.7% were cognitively unimpaired (CU) during both assessments. For every 10-point decrease in N3%, there was a 0.058 (95% CI 0.006-0.111, p = 0.030) increase in the log of WMH and 0.006 decrease (95% CI -0.012 to -0.0002, p = 0.042) in the log of genu FA. After matching for age, sex, and N3%, participants with severe OSA had higher WMH (median [IQR] 0.007 [0.005-0.015] vs 0.006 [0.003-0.009], p = 0.042) and lower genu FA (median [IQR] 0.57 [0.55-0.63] vs 0.63 [0.58-0.65], p = 0.007), when compared with those with mild/moderate OSA.

Discussion: We found that reduced slow-wave sleep and severe OSA were associated with higher burden of WM abnormalities in predominantly CU older adults, which may contribute to greater risk of cognitive impairment, dementia, and stroke. Our study supports the association between sleep depth/fragmentation and intermittent hypoxia and CVD biomarkers. Longitudinal studies are required to assess causation.

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Conflict of interest statement

D.Z. Carvalho and S.J. McCarter report no relevant disclosures. E.K. St. Louis has received research support from Mayo Clinic CCaTS, NIH, the Michael J. Fox Foundation, and Sunovion, Inc. S.A. Przybelski and K.L. Johnson Sparrman report no relevant disclosures. V.K. Somers has served as a consultant for ResMed, Zoll, Bayer, Lilly, Huxley, Apnimed, Jazz Pharmaceuticals, and Wesper and is on the Scientific Advisory Board for Sleep Number Corporation. B.F. Boeve has served as an investigator for clinical trials sponsored by Alector, Biogen, and Transposon and serves on the Scientific Advisory Board of the Tau Consortium. R.C. Petersen consults for Roche, Inc., Merck, Inc., Genentech, Inc., Biogen, Inc., and GE Healthcare and receives royalties from Oxford University Press for the publication of Mild Cognitive Impairment. C.R. Jack Jr. serves on an independent data monitoring board for Roche, but he receives no personal compensation from any commercial entity. J. Graff-Radford receives research funding from NIH and serves on the editorial board of Neurology®. P. Vemuri receives research funding from NIH (NIA and National Institute of Neurological Disorders and Stroke). Go to Neurology.org/N for full disclosures.

Figures

Figure 1
Figure 1. Scatterplot Shows Unadjusted Associations Between N3% and Log of WMH (A) and Log of Genu FA (B) in Samples With Best Model Performance
(A) Participants older than 60 years and (B) participants with representation of N3, as referenced. Best fit line is displayed. Genu FA = genu FA = FA in the genu of the corpus callosum; N3% = NREM stage 3 percentage; TIV = total intracranial volume; WMH = white matter hyperintensity.
Figure 2
Figure 2. Axial FLAIR-MRI Sequences Display White Matter Hyperintensities in 3 Participants According to Their N3%
(A) 76-year-old man, AHI 15 per hour, N3 22%. (B) 78-year-old man, AHI 6 per hour, N3 13%. (C) 76-year-old man, AHI 11 per hour, N3 5%. AHI = apnea-hypopnea index; FLAIR = fluid-attenuated inversion recovery; N3 = NREM stage 3.
Figure 3
Figure 3. Axial (Top) and Coronal (Bottom) Diffusion MRI Sequences Display Fractional Anisotropy of White Matter Tracks (With Center of the Genu of the Corpus Callosum Marked With Yellow Circle) in 3 Participants According to Their N3%
(A) 76-year-old man, AHI 15 per hour, N3 22%. (B) 78-year-old man, AHI 6 per hour, N3 13%. (C) 76-year-old man, AHI 11 per hour, N3 5%. AHI = apnea-hypopnea index; N3 = NREM stage 3.
Figure 4
Figure 4. Distribution of WMH (A) and Genu FA (B) According to OSA Severity
*p = 0.042; **p = 0.007. Genu FA = FA in the genu of the corpus callosum; TIV = total intracranial volume; WMH = white matter hyperintensity.
Figure 5
Figure 5. Axial FLAIR-MRI Sequences Display 2 Comparisons of White Matter Hyperintensities (A vs B and C vs D)
(A) 70-year-old woman, AHI 7 per hour, N3 28%. (B) 70-year-old woman, AHI 50 per hour, N3 25%. (C) 73-year-old man, AHI 12 per hour, N3 11%. (D) 72-year-old man, AHI 61 per hour, N3 29%. AHI = apnea-hypopnea index; FLAIR = fluid-attenuated inversion recovery; N3 = NREM stage 3.
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