Laura W Vergoossen1,2,3, Miranda T Schram3,4,5, Joost J de Jong1,2, Coen D Stehouwer3,4, Nicolaas C Schaper3,4,6, Ronald M Henry3,4,5, Carla J van der Kallen3,4, Pieter C Dagnelie3,4, Martin P van Boxtel2, Simone J Eussen3,7, Walter H Backes1,2, Jacobus F Jansen8,2,9. 1. Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+ (MUMC+), Maastricht, the Netherlands. 2. School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, the Netherlands. 3. School for Cardiovascular Disease (CARIM), Maastricht University, Maastricht, the Netherlands. 4. Department of Internal Medicine, Maastricht University Medical Center+, Maastricht, the Netherlands. 5. Heart and Vascular Centre, Maastricht University Medical Center+, Maastricht, the Netherlands. 6. School for Public Health and Primary Care (CAPHRI), Maastricht University, Maastricht, the Netherlands. 7. Department of Epidemiology, Maastricht University, Maastricht, the Netherlands. 8. Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+ (MUMC+), Maastricht, the Netherlands jacobus.jansen@mumc.nl. 9. Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.
Abstract
OBJECTIVE: Prediabetes and type 2 diabetes are associated with structural brain abnormalities, often observed in cognitive disorders. Besides visible lesions, (pre)diabetes might also be associated with alterations of the intrinsic organization of the white matter. In this population-based cohort study, the association of prediabetes and type 2 diabetes with white matter network organization was assessed. RESEARCH DESIGN AND METHODS: In the Maastricht Study, a type 2 diabetes-enriched population-based cohort study (1,361 subjects with normal glucose metabolism, 348 with prediabetes, and 510 with type 2 diabetes assessed by oral glucose tolerance test; 52% men; aged 59 ± 8 years), 3 Tesla structural and diffusion MRI was performed. Whole-brain white matter tractography was used to assess the number of connections (node degree) between 94 brain regions and the topology (graph measures). Multivariable linear regression analyses were used to investigate the associations of glucose metabolism status with network measures. Associations were adjusted for age, sex, education, and cardiovascular risk factors. RESULTS: Prediabetes and type 2 diabetes were associated with lower node degree after full adjustment (standardized [st]βPrediabetes = -0.055 [95% CI -0.172, 0.062], stβType2diabetes = -0.256 [-0.379, -0.133], P trend < 0.001). Prediabetes was associated with lower local efficiency (stβ = -0.084 [95% CI -0.159, -0.008], P = 0.033) and lower clustering coefficient (stβ = -0.097 [95% CI -0.189, -0.005], P = 0.049), whereas type 2 diabetes was not. Type 2 diabetes was associated with higher communicability (stβ = 0.148 [95% CI 0.042, 0.253], P = 0.008). CONCLUSIONS: These findings indicate that prediabetes and type 2 diabetes are associated with fewer white matter connections and weaker organization of white matter networks. Type 2 diabetes was associated with higher communicability, which was not yet observed in prediabetes and may reflect the use of alternative white matter connections.
OBJECTIVE: Prediabetes and type 2 diabetes are associated with structural brain abnormalities, often observed in cognitive disorders. Besides visible lesions, (pre)diabetes might also be associated with alterations of the intrinsic organization of the white matter. In this population-based cohort study, the association of prediabetes and type 2 diabetes with white matter network organization was assessed. RESEARCH DESIGN AND METHODS: In the Maastricht Study, a type 2 diabetes-enriched population-based cohort study (1,361 subjects with normal glucose metabolism, 348 with prediabetes, and 510 with type 2 diabetes assessed by oral glucose tolerance test; 52% men; aged 59 ± 8 years), 3 Tesla structural and diffusion MRI was performed. Whole-brain white matter tractography was used to assess the number of connections (node degree) between 94 brain regions and the topology (graph measures). Multivariable linear regression analyses were used to investigate the associations of glucose metabolism status with network measures. Associations were adjusted for age, sex, education, and cardiovascular risk factors. RESULTS: Prediabetes and type 2 diabetes were associated with lower node degree after full adjustment (standardized [st]βPrediabetes = -0.055 [95% CI -0.172, 0.062], stβType2diabetes = -0.256 [-0.379, -0.133], P trend < 0.001). Prediabetes was associated with lower local efficiency (stβ = -0.084 [95% CI -0.159, -0.008], P = 0.033) and lower clustering coefficient (stβ = -0.097 [95% CI -0.189, -0.005], P = 0.049), whereas type 2 diabetes was not. Type 2 diabetes was associated with higher communicability (stβ = 0.148 [95% CI 0.042, 0.253], P = 0.008). CONCLUSIONS: These findings indicate that prediabetes and type 2 diabetes are associated with fewer white matter connections and weaker organization of white matter networks. Type 2 diabetes was associated with higher communicability, which was not yet observed in prediabetes and may reflect the use of alternative white matter connections.
Authors: Frank C T van der Heide; Yuri D Foreman; Iris W M Franken; Ronald M A Henry; Abraham A Kroon; Pieter C Dagnelie; Simone J P M Eussen; Tos T J M Berendschot; Jan S A G Schouten; Carroll A B Webers; Miranda T Schram; Carla J H van der Kallen; Marleen M J van Greevenbroek; Anke Wesselius; Casper G Schalkwijk; Nicolaas C Schaper; Martijn C G J Brouwers; Coen D A Stehouwer Journal: Sci Rep Date: 2022-10-22 Impact factor: 4.996
Authors: Farzaneh Rahmani; Qing Wang; Nicole S McKay; Sarah Keefe; Nancy Hantler; Russ Hornbeck; Yong Wang; Jason Hassenstab; Suzanne Schindler; Chengjie Xiong; John C Morris; Tammie L S Benzinger; Cyrus A Raji Journal: J Alzheimers Dis Date: 2022 Impact factor: 4.160