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Hawks ZW, Beck ED, Jung L, Fonseca LM, Sliwinski MJ, Weinstock RS, Grinspoon E, Xu I, Strong RW, Singh S, Van Dongen HPA, Frumkin MR, Bulger J, Cleveland MJ, Janess K, Kudva YC, Pratley R, Rickels MR, Rizvi SR, Chaytor NS, Germine LT. Dynamic associations between glucose and ecological momentary cognition in Type 1 Diabetes. NPJ Digit Med 2024; 7:59. [PMID: 38499605 PMCID: PMC10948782 DOI: 10.1038/s41746-024-01036-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 02/14/2024] [Indexed: 03/20/2024] Open
Abstract
Type 1 diabetes (T1D) is a chronic condition characterized by glucose fluctuations. Laboratory studies suggest that cognition is reduced when glucose is very low (hypoglycemia) and very high (hyperglycemia). Until recently, technological limitations prevented researchers from understanding how naturally-occurring glucose fluctuations impact cognitive fluctuations. This study leveraged advances in continuous glucose monitoring (CGM) and cognitive ecological momentary assessment (EMA) to characterize dynamic, within-person associations between glucose and cognition in naturalistic environments. Using CGM and EMA, we obtained intensive longitudinal measurements of glucose and cognition (processing speed, sustained attention) in 200 adults with T1D. First, we used hierarchical Bayesian modeling to estimate dynamic, within-person associations between glucose and cognition. Consistent with laboratory studies, we hypothesized that cognitive performance would be reduced at low and high glucose, reflecting cognitive vulnerability to glucose fluctuations. Second, we used data-driven lasso regression to identify clinical characteristics that predicted individual differences in cognitive vulnerability to glucose fluctuations. Large glucose fluctuations were associated with slower and less accurate processing speed, although slight glucose elevations (relative to person-level means) were associated with faster processing speed. Glucose fluctuations were not related to sustained attention. Seven clinical characteristics predicted individual differences in cognitive vulnerability to glucose fluctuations: age, time in hypoglycemia, lifetime severe hypoglycemic events, microvascular complications, glucose variability, fatigue, and neck circumference. Results establish the impact of glucose on processing speed in naturalistic environments, suggest that minimizing glucose fluctuations is important for optimizing processing speed, and identify several clinical characteristics that may exacerbate cognitive vulnerability to glucose fluctuations.
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Affiliation(s)
- Z W Hawks
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - E D Beck
- Department of Psychology, University of California Davis, Davis, CA, USA
| | - L Jung
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, USA
| | - L M Fonseca
- Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, USA
- Programa Terceira Idade (PROTER, Old Age Research Group), Department and Institute of Psychiatry, University of São Paulo School of Medicine, São Paulo, Brazil
| | - M J Sliwinski
- Department of Human Development and Family Studies, Center for Healthy Aging, Pennsylvania State University, State College, PA, USA
| | | | - E Grinspoon
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, USA
| | - I Xu
- Department of Psychology, University of Notre Dame, Notre Dame, IN, USA
| | - R W Strong
- The Many Brains Project, Belmont, MA, USA
| | - S Singh
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - H P A Van Dongen
- Sleep and Performance Research Center & Department of Translational Medicine and Physiology, Washington State University, Spokane, WA, USA
| | - M R Frumkin
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - J Bulger
- SUNY Upstate Medical University, Syracuse, NY, USA
| | - M J Cleveland
- Department of Human Development, Washington State University, Pullman, WA, USA
| | - K Janess
- Jaeb Center for Health Research, Tampa, FL, USA
| | - Y C Kudva
- Division of Endocrinology, Diabetes and Nutrition, Mayo Clinic, Rochester, MN, USA
| | - R Pratley
- AdventHealth Translational Research Institute, Orlando, FL, USA
| | - M R Rickels
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - S R Rizvi
- Division of Endocrinology, Diabetes and Nutrition, Mayo Clinic, Rochester, MN, USA
| | - N S Chaytor
- Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, USA
| | - L T Germine
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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