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Bigalke JA, Cleveland EL, Barkstrom E, Gonzalez JE, Carter JR. Core body temperature changes before sleep are associated with nocturnal heart rate variability. J Appl Physiol (1985) 2023; 135:136-145. [PMID: 37262106 PMCID: PMC10292981 DOI: 10.1152/japplphysiol.00020.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/08/2023] [Accepted: 05/25/2023] [Indexed: 06/03/2023] Open
Abstract
Core body temperature (CBT) reductions occur before and during the sleep period, with the extent of presleep reductions corresponding to sleep onset and quality. Presleep reductions in CBT coincide with increased cardiac parasympathetic activity measured via heart rate variability (HRV), and while this appears to persist into the sleep period, individual differences in presleep CBT decline and nocturnal HRV remain unexplored. The purpose of the current study was to assess the relationship between individual differences in presleep CBT reductions and nocturnal heart rate (HR) and HRV in a population of 15 objectively poor sleeping adults [10 males, 5 females; age, 33 ± 4 yr; body mass index (BMI) 27 ± 1 kg/m2] with the hypothesis that blunted CBT rate of decline would be associated with elevated HR and reduced nocturnal HRV. Following an adaptation night, all participants underwent an overnight, in-laboratory sleep study with simultaneous recording of polysomnographic sleep including electrocardiography (ECG) and CBT recording. Correlations between CBT rate of change before sleep and nocturnal HRV were assessed. Blunted rate of CBT decline was significantly associated with increased heart rate (HR) in stage 2 (N2; R = 0.754, P = 0.001), stage 3 (N3; R = 0.748, P = 0.001), and rapid-eye movement (REM; R = 0.735, P = 0.002). Similarly, blunted rate of CBT decline before sleep was associated with reduced HRV across sleep stages. These findings indicate a relationship between individual differences in presleep thermoregulatory processes and nocturnal cardiac autonomic function in poor sleeping adults.NEW & NOTEWORTHY Core body temperature (CBT) reductions before sleep onset coincide with increases in heart rate variability (HRV) that persist throughout the sleep period. However, the relationship between individual differences in the efficiency of presleep core temperature regulation and nocturnal heart rate variability remains equivocal. The present study reports an association between the magnitude of presleep core body temperature changes and nocturnal parasympathetic activity, highlighting overlap between thermoregulatory processes before sleep and nocturnal cardiac autonomic function.
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Affiliation(s)
- Jeremy A Bigalke
- Department of Health and Human Development, Montana State University, Bozeman, Montana, United States
- Department of Psychology, Montana State University, Bozeman, Montana, United States
- Department of Kinesiology and Integrative Physiology, Michigan Technological University, Houghton, Michigan, United States
| | - Emily L Cleveland
- Microbiology and Cell Biology, Montana State University, Bozeman, Montana, United States
| | - Elyse Barkstrom
- Department of Health and Human Development, Montana State University, Bozeman, Montana, United States
| | - Joshua E Gonzalez
- Department of Kinesiology and Integrative Physiology, Michigan Technological University, Houghton, Michigan, United States
- Oregon Institute of Occupational Health Sciences, Oregon Health and Science University, Portland, Oregon, United States
| | - Jason R Carter
- Department of Kinesiology and Integrative Physiology, Michigan Technological University, Houghton, Michigan, United States
- Robbins College of Health and Human Sciences, Department of Health, Human Performance, and Recreation, Baylor University, Waco, Texas, United States
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Grant AD, Upton TJ, Terry JR, Smarr BL, Zavala E. Analysis of wearable time series data in endocrine and metabolic research. CURRENT OPINION IN ENDOCRINE AND METABOLIC RESEARCH 2022; 25:100380. [PMID: 36632470 PMCID: PMC9823090 DOI: 10.1016/j.coemr.2022.100380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Many hormones in the body oscillate with different frequencies and amplitudes, creating a dynamic environment that is essential to maintain health. In humans, disruptions to these rhythms are strongly associated with increased morbidity and mortality. While mathematical models can help us understand rhythm misalignment, translating this insight into personalised healthcare technologies requires solving additional challenges. Here, we discuss how combining minimally invasive, high-frequency biosampling technologies with wearable devices can assist the development of hormonal surrogates. We review bespoke algorithms that can help analyse multidimensional, noisy, time series data and identify wearable signals that could constitute clinical proxies of endocrine rhythms. These techniques can support the development of computational biomarkers to support the diagnosis and management of endocrine and metabolic conditions.
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Affiliation(s)
- Azure D. Grant
- Helen Wills Neuroscience Institute, University of California, Berkeley, 94720, United States of America
| | - Thomas J. Upton
- Laboratories for Integrative Neuroscience and Endocrinology, University of Bristol, Bristol, BS1 3NY, United Kingdom
| | - John R. Terry
- Centre for Systems Modelling & Quantitative Biomedicine, University of Birmingham, Edgbaston, B15 2TT, United Kingdom
| | - Benjamin L. Smarr
- Department of Bioengineering, University of California, San Diego, 92093, United States of America,Halıcıoğlu Data Science Institute, University of California, San Diego, 92093, United States of America,Corresponding author. Smarr, Benjamin L.
| | - Eder Zavala
- Centre for Systems Modelling & Quantitative Biomedicine, University of Birmingham, Edgbaston, B15 2TT, United Kingdom,Corresponding author. Zavala, Eder twitter icon
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