Brain Structure as a Correlate of Odor Identification and Cognition in Type 2 Diabetes

Abstract

Background: It has been reported that type 2 diabetes (T2DM) is associated with olfactory identification (OI) impairments and cognitive decline. However, the relationship between OI impairments and cognitive decline is largely unknown in T2DM patients.Methods: Sixty-eight T2DM patients and 68 healthy controls underwent 3D-T1 MRI scans, olfactory and cognitive assessments. The cortical thickness of olfaction-related brain regions, olfactory and cognitive scores were compared between groups. Correlation analyses were carried out among cognition, olfaction, and cortical thickness of olfaction-related brain regions.Results: First, the cognitive and olfactory test scores of T2DM patients were lower than healthy subjects. Second, higher olfactory scores were associated with increased cortical thickness in the left parahippocampal gyrus and bilateral insula in T2DM. Third, higher olfactory scores were associated with higher cognitive performance in T2DM. Fourth, some cognitive performances were related to cortical thickness in the left parahippocampal gyrus and left insula in T2DM.Conclusion: These findings indicated that olfactory dysfunction may be useful for future applications that attempt to predict cognitive decline or develop tailored therapies in T2DM patients.

A systematic review of the impact of type 2 diabetes on brain cortical thickness

“…Average age among study cohorts was distributed between 45.8 ± 7.6 years to 83.3 ± 2.6 years (Cherie M Falvey et al, 2013 ) for the control groups, and 47.7 ± 7.8 years (Shi et al, 2019 ; Chen et al, 2022 ) to 83.3 ± 3.1 years (C. M. Falvey et al, 2013 ) for T2D cohorts. The percentage of women ranged from 25% to 80% (Peng et al, 2014 ).…”

“…We have already noted that Freesurfer was used in the majority of studies, a software that has been shown to have high accuracy and reliability in measuring cortical thickness (Gronenschild et al, 2012 ). Other toolkits included SPM8 (Garcia-Casares et al, 2014 ; Gao et al, 2023 ) and SPM12 (Roy et al, 2020 ; Palix et al, 2022 ; Zhang et al, 2022 ), MRIcroN (Roy et al, 2020 ), REST (Roy et al, 2020 ), VSRAD (Hayashi et al, 2011 ), MarsBaR (Ferreira et al, 2017 ), MEDx (Korf et al, 2006 ), PM12 (Crisóstomo et al, 2021 ) and CAT12 (Crisóstomo et al, 2021 ), Computational Anatomy Toolbox 12 (CAT12: http://www.neuro.uni-jena.de/cat/ ) (Chen et al, 2022 ; Zhang et al, 2023 ). We observed that almost all discrepant studies (6 out of 10) predominantly utilized newer versions of Freesurfer, specifically versions 5.3 and 6.0.…”