Macro and micro sleep architecture and cognitive performance in older adults

Ina Djonlagic, Sara Mariani, Annette L. Fitzpatrick, Veerle M. G. T. H. Klei, Dayna A. Johnson, Alexis C. Wood, Teresa Seeman, Ha T. Nguyen, Michael J. Prerau, José A. Luchsinger, Joseph M. Dzierzewski, Stephen R. Rapp, Gregory J. Tranah, Kristine Yaffe, Katherine E. Burdick, Katie L. Stone, Susan Redline and Shaun M. Purcell ()
Additional contact information
Ina Djonlagic: Beth Israel Deaconess Medical Center
Sara Mariani: Harvard Medical School
Annette L. Fitzpatrick: University of Washington
Veerle M. G. T. H. Klei: Brigham and Women’s Hospital
Dayna A. Johnson: Emory University
Alexis C. Wood: Baylor College of Medicine
Teresa Seeman: University of California, Los Angeles
Ha T. Nguyen: Wake Forest School of Medicine
Michael J. Prerau: Harvard Medical School
José A. Luchsinger: Columbia University Medical Center
Joseph M. Dzierzewski: Virginia Commonwealth University
Stephen R. Rapp: Wake Forest Baptist Medical Center
Gregory J. Tranah: California Pacific Medical Center Research Institute
Kristine Yaffe: University of California, San Francisco
Katherine E. Burdick: Harvard Medical School
Katie L. Stone: California Pacific Medical Center Research Institute
Susan Redline: Beth Israel Deaconess Medical Center
Shaun M. Purcell: Harvard Medical School

Nature Human Behaviour, 2021, vol. 5, issue 1, 123-145

Abstract: Abstract We sought to determine which facets of sleep neurophysiology were most strongly linked to cognitive performance in 3,819 older adults from two independent cohorts, using whole-night electroencephalography. From over 150 objective sleep metrics, we identified 23 that predicted cognitive performance, and processing speed in particular, with effects that were broadly independent of gross changes in sleep quality and quantity. These metrics included rapid eye movement duration, features of the electroencephalography power spectra derived from multivariate analysis, and spindle and slow oscillation morphology and coupling. These metrics were further embedded within broader associative networks linking sleep with aging and cardiometabolic disease: individuals who, compared with similarly aged peers, had better cognitive performance tended to have profiles of sleep metrics more often seen in younger, healthier individuals. Taken together, our results point to multiple facets of sleep neurophysiology that track coherently with underlying, age-dependent determinants of cognitive and physical health trajectories in older adults.

Date: 2021
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DOI: 10.1038/s41562-020-00964-y

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