Dynamic associations between glucose and ecological momentary cognition in Type 1 Diabetes

Z W Hawks; E D Beck; L Jung; L M Fonseca; M J Sliwinski; R S Weinstock; E Grinspoon; I Xu; R W Strong; S Singh; H P A Van Dongen; M R Frumkin; J Bulger; M J Cleveland; K Janess; Y C Kudva; R Pratley; M R Rickels; S R Rizvi; N S Chaytor; L T Germine

doi:10.1038/s41746-024-01036-5

Dynamic associations between glucose and ecological momentary cognition in Type 1 Diabetes

NPJ Digit Med. 2024 Mar 18;7(1):59. doi: 10.1038/s41746-024-01036-5.

Authors

Z W Hawks^{1

2}, E D Beck³, L Jung⁴, L M Fonseca^{5

6}, M J Sliwinski⁷, R S Weinstock⁸, E Grinspoon⁴, I Xu⁹, R W Strong¹⁰, S Singh^{4

11}, H P A Van Dongen¹², M R Frumkin^{11

13

14}, J Bulger⁸, M J Cleveland¹⁵, K Janess¹⁶, Y C Kudva¹⁷, R Pratley¹⁸, M R Rickels¹⁹, S R Rizvi¹⁷, N S Chaytor⁵, L T Germine^{4

11}

Affiliations

¹ Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, USA. [email protected].
² Department of Psychiatry, Harvard Medical School, Boston, MA, USA. [email protected].
³ Department of Psychology, University of California Davis, Davis, CA, USA.
⁴ Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, USA.
⁵ Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, USA.
⁶ Programa Terceira Idade (PROTER, Old Age Research Group), Department and Institute of Psychiatry, University of São Paulo School of Medicine, São Paulo, Brazil.
⁷ Department of Human Development and Family Studies, Center for Healthy Aging, Pennsylvania State University, State College, PA, USA.
⁸ SUNY Upstate Medical University, Syracuse, NY, USA.
⁹ Department of Psychology, University of Notre Dame, Notre Dame, IN, USA.
¹⁰ The Many Brains Project, Belmont, MA, USA.
¹¹ Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
¹² Sleep and Performance Research Center & Department of Translational Medicine and Physiology, Washington State University, Spokane, WA, USA.
¹³ Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA.
¹⁴ Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
¹⁵ Department of Human Development, Washington State University, Pullman, WA, USA.
¹⁶ Jaeb Center for Health Research, Tampa, FL, USA.
¹⁷ Division of Endocrinology, Diabetes and Nutrition, Mayo Clinic, Rochester, MN, USA.
¹⁸ AdventHealth Translational Research Institute, Orlando, FL, USA.
¹⁹ University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.

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.

Abstract

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