Pre-diabetes and type 2 diabetes (i.e., hyperglycemia) are characterized by insulin resistance (IR). These problems with energy metabolism may exacerbate emotional reactivity to negatively valenced stimuli and related phenomena like predisposition toward negative affect, as well as cognitive deficits. Higher emotional reactivity is seen with hyperglycemia and IR. Yet, it is largely unknown how metabolic dysfunction correlates with related neural, hormonal, and cognitive outcomes.
Among 331 adults from the Midlife in the United States (MIDUS), we cross-sectionally examined eye- blink response (EBR) to gauge reactivity to negative, positive, or neutrally-valenced pictures from international affect picture system (IAPS) stimuli proximal to an acoustic startle probe. Increased EBR to negative stimuli was considered an index of stress reactivity. Frontal alpha asymmetry, a biomarker of negative affect predisposition, was determined using resting electroencephalography (EEG).
Baseline urinary cortisol output was collected. Cognitive performance was gauged using the Brief Test of Adult Cognition by telephone (BTACT). Fasting glucose and insulin characterized hyperglycemia or the homeostatic model assessment of IR (HOMA-IR).
Higher HOMA-IR corresponded to an increased startle response, measured by EBR magnitude, for negative versus positive stimuli [R2=0.218, F(1,457)=5.48, p=.020, euglycemia: Mean±SD=.092±.776, hyperglycemia: Mean±SD=.120±.881]. Participants with hyperglycemia vs. euglycemia showed greater right frontal alpha asymmetry [F(1,307)=6.62, p=.011, euglycemia: Mean±SD=.018±.167, hyperglycemia: Mean±SD=-.029±.160] and worse BTACT arithmetic performance [F(1,284)=4.25, p=.040, euglycemia: Mean±SD=2.390±1.526), hyperglycemia: Mean±SD=1.920±1.462]. Baseline urinary cortisol (log10 μg/12 hr) was also dysregulated in individuals with hyperglycemia [[F(1,324)=5.09, p=.025, euglycemia: Mean±SD=1.052±.332, hyperglycemia: Mean±SD=.961±.362].
These results suggest that dysmetabolism is associated with increased emotional reactivity, predisposition toward negative affect, and specific cognitive deficits.
1Department of Food Science and Human Nutrition, Iowa State University, Ames, IA, United States.
2Institute on Aging, University of Wisconsin-Madison, Madison, WI, United States.
3Department of Psychology, University of Wisconsin-Madison, Madison, WI, United States.
4Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, United States.
5Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI, United States.
6Department of Psychology, Iowa State University, Ames, IA, United States.
7Department of Biomedical Sciences, Iowa State University, Ames, IA, United States.
8Department of Neurology, University of Iowa, Iowa City, IA, United States.
Conflicts of Interest and Source of Funding: No potential conflicts of interests relevant to this article to report.
This work was funded in part by the College of Human Sciences at Iowa State University, a Big Data Brain Initiative grant through the Iowa State University Office of Vice President for Research, NIH grant AG047282, and the Alzheimer's Association Research Grant to Promote Diversity grant AARGD-17-529552. Neither funding source had any involvement in the report. MIDUS is funded by the National Institute on Aging (PO1-AG020166; Carol D. Ryff, Principal Investigator). John D. Catherine and Catherine T. MacArthur of the Foundation Research Network on Successful Midlife Development were the supporters of the original project.
Send Correspondence To: Auriel A. Willette, 224A MacKay Hall Ames, IA 50011, E-mail: firstname.lastname@example.org
Received for publication December 21, 2016; revision received January 23, 2018.