Association of Glycemic Variability With Imaging Markers of Vascular Burden, β-Amyloid, Brain Atrophy, and Cognitive Impairment
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VIEW CORRECTIONAbstract
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.
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© 2023 American Academy of Neurology.
Publication History
Received: May 22, 2023
Accepted: September 27, 2023
Published online: December 15, 2023
Published in issue: January 9, 2024
Disclosure
The authors report no relevant disclosures. Go to Neurology.org/N for full disclosures.
Study Funding
This research was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) funded by the Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea (grant number: HU20C0111), and funded by the Ministry of HealthWelfare, Republic of Korea (grant number: HR21C0885). This research was supported by the “National Institute of Health” Research Project (2021-ER1006-021) and a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2020R1A2C1009778). This study was also supported by the Future Medicine 2030 Project of Samsung Medical Center [#SMX1210771]. This research was supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) and Korea Dementia Research Center (KDRC), funded by the Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea (HU20C0414).
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- Machine learning reveals distinct neuroanatomical signatures of cardiovascular and metabolic diseases in cognitively unimpaired individuals, Nature Communications, 16, 1, (2025).https://doi.org/10.1038/s41467-025-57867-7
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- Association of Glycemic Variability With Imaging Markers of Vascular Burden, β-Amyloid, Brain Atrophy, and Cognitive Impairment, Neurology, 102, 7, (2024)./doi/10.1212/WNL.0000000000209274
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