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Patients with subclinical GAD-states (sub-GAD) do not fulfill the diagnostic criteria of GAD, but they often show a disease burden similar to GAD, and the subclinical state may turn into a full syndrome. Neuroinflammation may contribute to changes in brain structures in sub-GAD, but direct evidence remains lacking. We investigated 73 newly recruited sub-GAD patients who had never received pharmacological or psychological treatment and 64 matched non-clinical individuals. We utilized magnetic resonance imaging (MRI) to assess putative neuroinflammatory markers (DBSI-RF, diffusion-based spectral imaging-based restricted fraction) in the hippocampus, amygdala, and neocortex. The patients completed the Hamilton Anxiety Rating Scale (HAM-A), the Generalized Anxiety Disorder 7-item scale (GAD-7), and the Beck Depression Inventory-II (BDI-II). Compared to controls, sub-GAD individuals had significantly elevated inflammatory MRI markers in the amygdala but not in the hippocampus and neocortex. The DBSI-RF values correlated with the severity of anxiety (HAM-A and GAD-7 scores), but not with BDI-II. These findings suggest that neuroinflammation in the amygdala may play a critical role in the development of anxiety in sub-GAD.<\/jats:p>","DOI":"10.1007\/s00702-025-03014-x","type":"journal-article","created":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T01:53:20Z","timestamp":1757555600000},"page":"539-546","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["MRI markers of neuroinflammation in untreated patients with subclinical generalized anxiety disorder"],"prefix":"10.1007","volume":"133","author":[{"given":"Bal\u00e1zs","family":"Bark\u00f3","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oguz","family":"Kelemen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7638-1741","authenticated-orcid":false,"given":"Szabolcs","family":"K\u00e9ri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,9,11]]},"reference":[{"key":"3014_CR1","doi-asserted-by":"publisher","first-page":"400","DOI":"10.1016\/j.neuroimage.2017.10.034","volume":"166","author":"F Alfaro-Almagro","year":"2018","unstructured":"Alfaro-Almagro F, Jenkinson M, Bangerter NK, Andersson JLR, Griffanti L, Douaud G, Sotiropoulos SN, Jbabdi S, Hernandez-Fernandez M, Vallee E, Vidaurre D, Webster M, McCarthy P, Rorden C, Daducci A, Alexander DC, Zhang H, Dragonu I, Matthews PM, Miller KL, Smith SM (2018) Image processing and quality control for the first 10 000 brain imaging datasets from UK biobank. 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