Schulz, MA;
Hetzer, S;
Eitel, F;
Asseyer, S;
Meyer-Arndt, L;
Schmitz-Hübsch, T;
Bellmann-Strobl, J;
... Weygandt, M; + view all
(2023)
Similar neural pathways link psychological stress and brain-age in health and multiple sclerosis.
iScience
, 26
(9)
, Article 107679. 10.1016/j.isci.2023.107679.
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Abstract
Clinical and neuroscientific studies suggest a link between psychological stress and reduced brain health in health and neurological disease but it is unclear whether mediating pathways are similar. Consequently, we applied an arterial-spin-labeling MRI stress task in 42 healthy persons and 56 with multiple sclerosis, and investigated regional neural stress responses, associations between functional connectivity of stress-responsive regions and the brain-age prediction error, a highly sensitive machine learning brain health biomarker, and regional brain-age constituents in both groups. Stress responsivity did not differ between groups. Although elevated brain-age prediction errors indicated worse brain health in patients, anterior insula–occipital cortex (healthy persons: occipital pole; patients: fusiform gyrus) functional connectivity correlated with brain-age prediction errors in both groups. Finally, also gray matter contributed similarly to regional brain-age across groups. These findings might suggest a common stress–brain health pathway whose impact is amplified in multiple sclerosis by disease-specific vulnerability factors.
| Type: | Article |
|---|---|
| Title: | Similar neural pathways link psychological stress and brain-age in health and multiple sclerosis |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.isci.2023.107679 |
| Publisher version: | https://doi.org/10.1016/j.isci.2023.107679 |
| Language: | English |
| Additional information: | © 2023 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
| Keywords: | Age, Machine learning, Neural networks, Neuroscience |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10176473 |
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