TY - JOUR
T1 - Proteomic Biomarkers of the Apnea Hypopnea Index and Obstructive Sleep Apnea
T2 - Insights into the Pathophysiology of Presence, Severity, and Treatment Response
AU - Cederberg, Katie L.J.
AU - Hanif, Umaer
AU - Peris Sempere, Vicente
AU - Hédou, Julien
AU - Leary, Eileen B.
AU - Schneider, Logan D.
AU - Lin, Ling
AU - Zhang, Jing
AU - Morse, Anne M.
AU - Blackman, Adam
AU - Schweitzer, Paula K.
AU - Kotagal, Suresh
AU - Bogan, Richard
AU - Kushida, Clete A.
AU - Ju, Yo El S.
AU - Petousi, Nayia
AU - Turnbull, Chris D.
AU - Mignot, Emmanuel
AU - The STAGES Cohort Investigator Group
N1 - Publisher Copyright:
© 2022 by the authors.
PY - 2022
Y1 - 2022
N2 - Obstructive sleep apnea (OSA), a disease associated with excessive sleepiness and increased cardiovascular risk, affects an estimated 1 billion people worldwide. The present study examined proteomic biomarkers indicative of presence, severity, and treatment response in OSA. Participants (n = 1391) of the Stanford Technology Analytics and Genomics in Sleep study had blood collected and completed an overnight polysomnography for scoring the apnea–hypopnea index (AHI). A highly multiplexed aptamer-based array (SomaScan) was used to quantify 5000 proteins in all plasma samples. Two separate intervention-based cohorts with sleep apnea (n = 41) provided samples pre- and post-continuous/positive airway pressure (CPAP/PAP). Multivariate analyses identified 84 proteins (47 positively, 37 negatively) associated with AHI after correction for multiple testing. Of the top 15 features from a machine learning classifier for AHI ≥ 15 vs. AHI < 15 (Area Under the Curve (AUC) = 0.74), 8 were significant markers of both AHI and OSA from multivariate analyses. Exploration of pre- and post-intervention analysis identified 5 of the 84 proteins to be significantly decreased following CPAP/PAP treatment, with pathways involving endothelial function, blood coagulation, and inflammatory response. The present study identified PAI-1, tPA, and sE-Selectin as key biomarkers and suggests that endothelial dysfunction and increased coagulopathy are important consequences of OSA, which may explain the association with cardiovascular disease and stroke.
AB - Obstructive sleep apnea (OSA), a disease associated with excessive sleepiness and increased cardiovascular risk, affects an estimated 1 billion people worldwide. The present study examined proteomic biomarkers indicative of presence, severity, and treatment response in OSA. Participants (n = 1391) of the Stanford Technology Analytics and Genomics in Sleep study had blood collected and completed an overnight polysomnography for scoring the apnea–hypopnea index (AHI). A highly multiplexed aptamer-based array (SomaScan) was used to quantify 5000 proteins in all plasma samples. Two separate intervention-based cohorts with sleep apnea (n = 41) provided samples pre- and post-continuous/positive airway pressure (CPAP/PAP). Multivariate analyses identified 84 proteins (47 positively, 37 negatively) associated with AHI after correction for multiple testing. Of the top 15 features from a machine learning classifier for AHI ≥ 15 vs. AHI < 15 (Area Under the Curve (AUC) = 0.74), 8 were significant markers of both AHI and OSA from multivariate analyses. Exploration of pre- and post-intervention analysis identified 5 of the 84 proteins to be significantly decreased following CPAP/PAP treatment, with pathways involving endothelial function, blood coagulation, and inflammatory response. The present study identified PAI-1, tPA, and sE-Selectin as key biomarkers and suggests that endothelial dysfunction and increased coagulopathy are important consequences of OSA, which may explain the association with cardiovascular disease and stroke.
KW - Apnea–hypopnea index
KW - Biomarkers
KW - Machine learning
KW - Obstructive sleep apnea
KW - Proteomics
KW - Treatment
U2 - 10.3390/ijms23147983
DO - 10.3390/ijms23147983
M3 - Journal article
C2 - 35887329
AN - SCOPUS:85137368129
SN - 1661-6596
VL - 23
JO - International Journal of Molecular Sciences
JF - International Journal of Molecular Sciences
IS - 14
M1 - 7983
ER -