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Brooks TG, Lahens NF, Grant GR, Sheline YI, FitzGerald GA, Skarke C. Diurnal rhythms of wrist temperature are associated with future disease risk in the UK Biobank. Nat Commun 2023; 14:5172. [PMID: 37620332 PMCID: PMC10449859 DOI: 10.1038/s41467-023-40977-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 08/15/2023] [Indexed: 08/26/2023] Open
Abstract
Many chronic disease symptomatologies involve desynchronized sleep-wake cycles, indicative of disrupted biorhythms. This can be interrogated using body temperature rhythms, which have circadian as well as sleep-wake behavior/environmental evoked components. Here, we investigated the association of wrist temperature amplitudes with a future onset of disease in the UK Biobank one year after actigraphy. Among 425 disease conditions (range n = 200-6728) compared to controls (range n = 62,107-91,134), a total of 73 (17%) disease phenotypes were significantly associated with decreased amplitudes of wrist temperature (Benjamini-Hochberg FDR q < 0.05) and 26 (6.1%) PheCODEs passed a more stringent significance level (Bonferroni-correction α < 0.05). A two-standard deviation (1.8° Celsius) lower wrist temperature amplitude corresponded to hazard ratios of 1.91 (1.58-2.31 95% CI) for NAFLD, 1.69 (1.53-1.88) for type 2 diabetes, 1.25 (1.14-1.37) for renal failure, 1.23 (1.17-1.3) for hypertension, and 1.22 (1.11-1.33) for pneumonia (phenome-wide atlas available at http://bioinf.itmat.upenn.edu/biorhythm_atlas/ ). This work suggests peripheral thermoregulation as a digital biomarker.
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Affiliation(s)
- Thomas G Brooks
- Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | - Nicholas F Lahens
- Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Gregory R Grant
- Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yvette I Sheline
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Garret A FitzGerald
- Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Carsten Skarke
- Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
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Skarke C, Brooks T, Lahens N, Grant G, Sheline Y, FitzGerald G. Diurnal rhythmicity of wearable device-measured wrist temperature predicts future disease incidence in the UK Biobank. RESEARCH SQUARE 2023:rs.3.rs-2535978. [PMID: 36824952 PMCID: PMC9949244 DOI: 10.21203/rs.3.rs-2535978/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
Many chronic disease symptomatologies involve desynchronized sleep-wake cycles, indicative of disrupted biorhythms. This can be interrogated using body temperature rhythms, which are well-established biomarkers for circadian clock function. Here, we investigated the association of wrist temperature amplitudes with a future onset of disease in the UK Biobank one year after actigraphy. Among 425 disease conditions (range n = 200-6,728) compared to controls (range n = 62,107 - 91,134), a total of 73 (36.5%) disease phenotypes were significantly associated with decreased amplitudes of wrist temperature (Benjamini-Hochberg FDR q < 0.05) and 26 (13%) PheCODEs passed a more stringent significance level (Bonferroni-correction α < 0.05). Here, for example, a two-standard deviation (1.8° Celsius) lower wrist temperature amplitude corresponded to hazard ratios of 1.91 (1.58-2.31 95% CI) for NAFLD, 1.69 (1.53-1.88) for type 2 diabetes, 1.25 (1.14-1.37) for renal failure, 1.23 (1.17-1.3) for hypertension, and 1.22 (1.11-1.33) for pneumonia. A comprehensive phenome-wide atlas of the identified mappings has been made available at http://bioinf.itmat.upenn.edu/biorhythm_atlas/. These findings strongly suggest peripheral thermoregulation as a digital biomarker.
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Affiliation(s)
| | | | | | - Gregory Grant
- Institute of Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania; Department of Genetics, University of Pennsylvania Perelman School of Medicine
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Hondula DM, Kuras ER, Betzel S, Drake L, Eneboe J, Kaml M, Munoz M, Sevig M, Singh M, Ruddell BL, Harlan SL. Novel metrics for relating personal heat exposure to social risk factors and outdoor ambient temperature. ENVIRONMENT INTERNATIONAL 2021; 146:106271. [PMID: 33395929 DOI: 10.1016/j.envint.2020.106271] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 10/04/2020] [Accepted: 11/05/2020] [Indexed: 06/12/2023]
Abstract
A more precise understanding of individual-level heat exposure may be helpful to advance knowledge about heat-health impacts and effective intervention strategies, especially in light of projected increases in the severity and frequency of extreme heat events. We developed and interrogated different metrics for quantifying personal heat exposure and explored their association with social risk factors. To do so, we collected simultaneous personal heat exposure data from 64 residents of metropolitan Phoenix, Arizona. From these data, we derived five exposure metrics: Mean Individually Experienced Temperature (IET), Maximum IET, Longest Exposure Period (LEP), Percentage Minutes Above Threshold (PMAT), and Degree Minutes Above Threshold (DMAT), and calculated each for Day Hours, Night Hours, and All Hours of the study period. We then calculated effect sizes for the associations between those metrics and four social risk factors: neighborhood vulnerability, income, home cooling type, and time spent outside. We also investigated exposure misclassification by constructing linear regression models of observations from a regional weather station and hourly IET for each participant. Our analysis revealed that metric choice and timeframe added depth and nuance to our understanding of differences in exposure within and between populations. We found that time spent outside and income were the two risk factors most strongly associated with personal heat exposure. We also found evidence that Mean IET is a good, but perhaps not optimal, measure for assessing group differences in exposure. Most participants' IETs were poorly correlated with regional weather station observations and the slope and correlation coefficient for linear regression models between regional weather station data and IETs varied widely among participants. We recommend continued efforts to investigate personal heat exposure, especially in combination with physiological indicators, to improve our understanding of links between ambient temperatures, social risk factors, and health outcomes.
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Affiliation(s)
- David M Hondula
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA.
| | - Evan R Kuras
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA; Department of Environmental Conservation, University of Massachusetts Amherst, Amherst, MA 01003, USA
| | - Summer Betzel
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Lauren Drake
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Jason Eneboe
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Miranda Kaml
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Mary Munoz
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Mara Sevig
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Marianna Singh
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Benjamin L Ruddell
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86011, USA
| | - Sharon L Harlan
- Department of Health Sciences and Department of Sociology and Anthropology, Northeastern University, Boston, MA 02115, USA
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