Identifying Sleep Biomarkers to Evaluate Cognition in HIV

Hilda Azimi; Kristin M. Gunnarsdottir; Sridevi V. Sarma; Alyssa A. Gamaldo; Rachel M.E. Salas; Charlene E. Gamaldo

doi:10.1109/EMBC44109.2020.9176592

Identifying Sleep Biomarkers to Evaluate Cognition in HIV

Hilda Azimi
, Kristin M. Gunnarsdottir
, Sridevi V. Sarma
, Alyssa A. Gamaldo
, Rachel M.E. Salas
, Charlene E. Gamaldo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

Sleep disturbance and cognitive impairment represent two of the most common and debilitating conditions facing seropositive (HIV+) individuals who are otherwise well controlled with antiretroviral therapy. Sleep-assessment-based biomarkers represent an important step towards improving our understanding of the unique mechanistic features that may link sleep disruption and cognition in HIV+ individuals, ultimately leading to advancements in treatment and management options. In this study, a risk score was computed via a generalized linear model (GLM), which optimally combines polysomnography (PSG) features extracted from EEG, EMG, and EOG signals, to distinguish 18 HIV+ Black male individuals with and without cognitive impairment. The optimal set of features was identified via the least absolute shrinkage and selection operator (LASSO) approach, and the risk separation between the two groups, i.e., cognitively normal and cognitive impaired, was significant (and has a P-value <.001). The optimal set of predictive features were all EEG derived and sleep stage-specific. These preliminary findings suggest that sleep-based EEG features may be used as both diagnostic and prognostic biomarkers for cognition in HIV+ subjects.

Original language	English (US)
Title of host publication	42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publication	Enabling Innovative Technologies for Global Healthcare, EMBC 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2332-2336
Number of pages	5
ISBN (Electronic)	9781728119908
DOIs	https://doi.org/10.1109/EMBC44109.2020.9176592
State	Published - Jul 2020
Event	42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada Duration: Jul 20 2020 → Jul 24 2020

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume	2020-July
ISSN (Print)	1557-170X

Conference

Conference	42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
Country/Territory	Canada
City	Montreal
Period	7/20/20 → 7/24/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Access to Document

10.1109/EMBC44109.2020.9176592

Cite this

Azimi, H., Gunnarsdottir, K. M., Sarma, S. V., Gamaldo, A. A., Salas, R. M. E., & Gamaldo, C. E. (2020). Identifying Sleep Biomarkers to Evaluate Cognition in HIV. In 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020 (pp. 2332-2336). Article 9176592 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2020-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC44109.2020.9176592

Azimi, Hilda ; Gunnarsdottir, Kristin M. ; Sarma, Sridevi V. et al. / Identifying Sleep Biomarkers to Evaluate Cognition in HIV. 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 2332-2336 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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title = "Identifying Sleep Biomarkers to Evaluate Cognition in HIV",

abstract = "Sleep disturbance and cognitive impairment represent two of the most common and debilitating conditions facing seropositive (HIV+) individuals who are otherwise well controlled with antiretroviral therapy. Sleep-assessment-based biomarkers represent an important step towards improving our understanding of the unique mechanistic features that may link sleep disruption and cognition in HIV+ individuals, ultimately leading to advancements in treatment and management options. In this study, a risk score was computed via a generalized linear model (GLM), which optimally combines polysomnography (PSG) features extracted from EEG, EMG, and EOG signals, to distinguish 18 HIV+ Black male individuals with and without cognitive impairment. The optimal set of features was identified via the least absolute shrinkage and selection operator (LASSO) approach, and the risk separation between the two groups, i.e., cognitively normal and cognitive impaired, was significant (and has a P-value <.001). The optimal set of predictive features were all EEG derived and sleep stage-specific. These preliminary findings suggest that sleep-based EEG features may be used as both diagnostic and prognostic biomarkers for cognition in HIV+ subjects.",

author = "Hilda Azimi and Gunnarsdottir, \{Kristin M.\} and Sarma, \{Sridevi V.\} and Gamaldo, \{Alyssa A.\} and Salas, \{Rachel M.E.\} and Gamaldo, \{Charlene E.\}",

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Azimi, H, Gunnarsdottir, KM, Sarma, SV, Gamaldo, AA, Salas, RME & Gamaldo, CE 2020, Identifying Sleep Biomarkers to Evaluate Cognition in HIV. in 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020., 9176592, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2020-July, Institute of Electrical and Electronics Engineers Inc., pp. 2332-2336, 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020, Montreal, Canada, 7/20/20. https://doi.org/10.1109/EMBC44109.2020.9176592

Identifying Sleep Biomarkers to Evaluate Cognition in HIV. / Azimi, Hilda; Gunnarsdottir, Kristin M.; Sarma, Sridevi V. et al.
42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 2332-2336 9176592 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2020-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Identifying Sleep Biomarkers to Evaluate Cognition in HIV

AU - Azimi, Hilda

AU - Gunnarsdottir, Kristin M.

AU - Sarma, Sridevi V.

AU - Gamaldo, Alyssa A.

AU - Salas, Rachel M.E.

AU - Gamaldo, Charlene E.

PY - 2020/7

Y1 - 2020/7

N2 - Sleep disturbance and cognitive impairment represent two of the most common and debilitating conditions facing seropositive (HIV+) individuals who are otherwise well controlled with antiretroviral therapy. Sleep-assessment-based biomarkers represent an important step towards improving our understanding of the unique mechanistic features that may link sleep disruption and cognition in HIV+ individuals, ultimately leading to advancements in treatment and management options. In this study, a risk score was computed via a generalized linear model (GLM), which optimally combines polysomnography (PSG) features extracted from EEG, EMG, and EOG signals, to distinguish 18 HIV+ Black male individuals with and without cognitive impairment. The optimal set of features was identified via the least absolute shrinkage and selection operator (LASSO) approach, and the risk separation between the two groups, i.e., cognitively normal and cognitive impaired, was significant (and has a P-value <.001). The optimal set of predictive features were all EEG derived and sleep stage-specific. These preliminary findings suggest that sleep-based EEG features may be used as both diagnostic and prognostic biomarkers for cognition in HIV+ subjects.

AB - Sleep disturbance and cognitive impairment represent two of the most common and debilitating conditions facing seropositive (HIV+) individuals who are otherwise well controlled with antiretroviral therapy. Sleep-assessment-based biomarkers represent an important step towards improving our understanding of the unique mechanistic features that may link sleep disruption and cognition in HIV+ individuals, ultimately leading to advancements in treatment and management options. In this study, a risk score was computed via a generalized linear model (GLM), which optimally combines polysomnography (PSG) features extracted from EEG, EMG, and EOG signals, to distinguish 18 HIV+ Black male individuals with and without cognitive impairment. The optimal set of features was identified via the least absolute shrinkage and selection operator (LASSO) approach, and the risk separation between the two groups, i.e., cognitively normal and cognitive impaired, was significant (and has a P-value <.001). The optimal set of predictive features were all EEG derived and sleep stage-specific. These preliminary findings suggest that sleep-based EEG features may be used as both diagnostic and prognostic biomarkers for cognition in HIV+ subjects.

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T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

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Azimi H, Gunnarsdottir KM, Sarma SV, Gamaldo AA, Salas RME, Gamaldo CE. Identifying Sleep Biomarkers to Evaluate Cognition in HIV. In 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 2332-2336. 9176592. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC44109.2020.9176592

Identifying Sleep Biomarkers to Evaluate Cognition in HIV

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

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