Correlations between white matter microintegrity and risk level of allostatic load in cognitive complaint subjects
Abstract Background Chronic exposition to stressor factors has been postulated as a cause of structural changes in the brain in the context of dementia. One of these changes can be the fiber integrity loss, that can be measured by diffusion tensor imaging (DTI). We obtained DTI whole brain metrics to relate them with allostatic load in subjects of a chilean cohort of cognitive complaint subjects. Method We selected 135 subjects of a chilean cohort of cognitive complaint subjects and classified based in MoCA test in subjects with (58) (MCI) and without (77) (SCC) cognitive decline groups. To measure AL, we selected 15 metabolic, cardiovascular and immunitary biomarkers and the subjects were categorized in low, medium, and high‐risk categories of AL. DTI was calculated using a deterministic tractography algorithm and the relationships were established using a correlational tractoghraphy tool, based in DSIstudio, calculating the FDR (≤ 0,05) of whole brain fasciculus. Age and education was regressed out. After that, fasciculus with significance were segmented based on HCP 1065 atlas. Result we obtained significative correlations in many fibers, depending on the parameter studied. Is interesting to note that bilateral cingulum bundles, and corpus callosum integrity are within the fibers that have relationship with allostatic load in both cognitive groups. Additionally, MCI group presents more compromised tracts than SCC group. Conclusion In this study, a relationship between allostatic load and DTI integrity measurements in MCI and SCC groups was found. An interesting correlation exists in fornix and bilateral cingulum bundles, that can be supported by findings in previous studies based in human and animal models where the stress effects in white matter were studied. These results open an interesting research area to explore the role of stress response and mediators in early steps of dementia, who until today, has been poorly studied.
Authors
- Michele Demanet
- Daniela Thumala (ORCID: https://orcid.org/0000-0003-0392-7031)
- Paola Contreras (ORCID: https://orcid.org/0000-0001-9415-5393)
- Fernando Henríquez (ORCID: https://orcid.org/0000-0001-9854-9680)
- Andrea Slachevsky (ORCID: https://orcid.org/0000-0001-6285-3189)
- Patricia Lillo (ORCID: https://orcid.org/0000-0001-7398-7203)
- Cristina Godoy (ORCID: https://orcid.org/0000-0001-5037-1916)
- Graciela Muñiz‐Terrera (ORCID: https://orcid.org/0000-0002-4516-0337)
- Ingrid Buller‐Peralta (ORCID: https://orcid.org/0000-0002-4427-9897)
- Cecilia González Campo
- Cecilia Okuma (ORCID: https://orcid.org/0009-0001-6910-3732)
- Pamela Guevara Alvez
- El‐Deredy Wael
- María Francisca Damm
Institutions
- Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
- Pontificia Universidad Católica de Chile (CL)
- University of Concepción (CL)
- University of San Andrés (AR)
- Hospital del Salvador (CL)
- Ohio University (US)
- Clínica MEDS (Chile) (CL)
- Instituto de Neurociencia Biomédica (CL)
- Center for Climate and Resilience Research (CL)
- University of Chile (CL)
- University of Valparaíso (CL)
- University of Edinburgh (GB)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1002/alz.085867
- Primary Topic
- Advanced Neuroimaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00