Association of Glycemic Variability With Imaging Markers of Vascular Burden, β-Amyloid, Brain Atrophy, and Cognitive Impairment

Abstract

Background and objective: We aimed to investigate the association between glycemic variability (GV) and neuroimaging markers of white matter hyperintensities (WMH), beta-amyloid (Aβ), brain atrophy, and cognitive impairment.

Methods: This was a retrospective cohort study that included participants without dementia from a memory clinic. They all had Aβ PET, brain MRI, and standardized neuropsychological tests and had fasting glucose (FG) levels tested more than twice during the study period. We defined GV as the intraindividual visit-to-visit variability in FG levels. Multivariable linear regression and logistic regression were used to identify whether GV was associated with the presence of severe WMH and Aβ uptake with DM, mean FG levels, age, sex, hypertension, and presence of APOE4 allele as covariates. Mediation analyses were used to investigate the mediating effect of WMH and Aβ uptake on the relationship between GV and brain atrophy and cognition.

Results: Among the 688 participants, the mean age was 72.2 years, and the proportion of female participants was 51.9%. Increase in GV was predictive of the presence of severe WMH (coefficient [95% CI] 1.032 [1.012-1.054]; p = 0.002) and increased Aβ uptake (1.005 [1.001-1.008]; p = 0.007). Both WMH and increased Aβ uptake partially mediated the relationship between GV and frontal-executive dysfunction (GV → WMH → frontal-executive; direct effect, -0.319 [-0.557 to -0.080]; indirect effect, -0.050 [-0.091 to -0.008]) and memory dysfunction (GV → Aβ → memory; direct effect, -0.182 [-0.338 to -0.026]; indirect effect, -0.067 [-0.119 to -0.015]), respectively. In addition, increased Aβ uptake completely mediated the relationship between GV and hippocampal volume (indirect effect, -1.091 [-2.078 to -0.103]) and partially mediated the relationship between GV and parietal thickness (direct effect, -0.00101 [-0.00185 to -0.00016]; indirect effect, -0.00016 [-0.00032 to -0.000002]).

Discussion: Our findings suggest that increased GV is related to vascular and Alzheimer risk factors and neurodegenerative markers, which in turn leads to subsequent cognitive impairment. Furthermore, GV can be considered a potentially modifiable risk factor for dementia prevention.

Figure 1. Diagram of Mediation Analyses Indicating the Relationship of GV With Brain Atrophy

Results for mediation analyses of the association between (A) GV, severe WMH, and frontal thickness; (B) GV, Aβ uptakes, and hippocampal volume; and (C) GV, Aβ uptakes, and parietal thickness. Aβ = beta-amyloid; GV = glycemic variability; WMH = white matter hyperintensities. Direct and indirect effects are represented as coefficients (95% confidence interval) with p values.

Figure 2. Diagram of Mediation Analyses Depicting the Relationship of GV With Cognition

Results for mediation analyses of the association between (A) GV, severe WMH, and frontal-executive function; (B) GV, severe WMH, and MMSE ; (C) GV, Aβ uptakes, and memory function and (D) GV, Aβ uptakes, and MMSE. Aβ = beta-amyloid; MMSE = Mini-Mental State Examination; WMH = white matter hyperintensities. Direct and indirect effects are represented as coefficients (95% confidence interval) with p values.