# paper.pdf ## Metadata - PDFFormatVersion=1.4 - Language=EN - IsLinearized=false - IsAcroFormPresent=false - IsXFAPresent=false - IsCollectionPresent=false - IsSignaturesPresent=false - Author=Joel Tuomaala - CreationDate=D:20260429235825+05'30' - Creator=Springer - Custom.CrossMarkDomains[1]=springer.com - Custom.CrossMarkDomains[2]=springerlink.com - Custom.CrossmarkDomainExclusive=true - Custom.CrossmarkMajorVersionDate=2010-04-23 - Custom.doi=10.1007/s00415-026-13842-w - Custom.robots=noindex - Keywords=[11C]PK11195; Glial activation; Limbic system; Long COVID; Neuropsychiatric symptoms; TSPO PET - ModDate=D:20260430131449+02'00' - Producer=Acrobat Distiller 10.1.8 (Windows); modified using iText® 5.5.13.4 ©2000-2024 iText Group NV (SPRINGER SBM; licensed version) - Subject=Journal of Neurology, https://doi.org/10.1007/s00415-026-13842-w - Title=Association between post-COVID-19 neuropsychiatric symptoms and persistent glial activation in the limbic system: a TSPO PET study - Trapped=False - dc:publisher=Springer Berlin Heidelberg - dc:description=Journal of Neurology, https://doi.org/10.1007/s00415-026-13842-w - dc:subject=[11C]PK11195,Glial activation,Limbic system,Long COVID,Neuropsychiatric symptoms,TSPO PET - dc:title=Association between post-COVID-19 neuropsychiatric symptoms and persistent glial activation in the limbic system: a TSPO PET study - dc:creator=Joel Tuomaala,Maija Saraste,Emma Smith,Matilda Kuusi,Elisabet Westerberg,Eveliina Honkonen,Rahim Kargar,Sini Laaksonen,Jussi Lehto,Amelie Luoma,Markus Matilainen,Olavi Misin,Janne Atosuo,Mari Kanerva,Helena Liira,Sini Laakso,Tatiana Posharina,Virva Saunavaara,Saara Wahlroos,Johan Rajander,Laura Airas - crossmark:crossmarkdomains=springer.comspringerlink.com - pdfx:crossmarkdomains=springer.comspringerlink.com ## Contents ### Page 1 Vol.:(0123456789)Journal of Neurology (2026) 273:298 https://doi.org/10.1007/s00415-026-13842-wORIGINAL COMMUNICATIONAssociation between post‑COVID‑19 neuropsychiatric symptoms and persistent glial activation in the limbic system: a TSPO PET studyJoel Tuomaala1,2,3,4 · Maija Saraste1,2,3,4 · Emma Smith3 · Matilda Kuusi1 · Elisabet Westerberg 5 · Eveliina Honkonen 1,2,3,4 · Rahim Kargar2 · Sini Laaksonen1,2,3 · Jussi Lehto 1,2,4 · Amelie Luoma1,3 · Markus Matilainen 1,2,3,4 · Olavi Misin1,2,3 · Janne Atosuo6 · Mari Kanerva 7 · Helena Liira8 · Sini Laakso8 · Tatiana Posharina8 · Virva Saunavaara 1 · Saara Wahlroos9 · Johan Rajander10 · Laura Airas1,2,3,4Received: 18 February 2026 / Revised: 8 April 2026 / Accepted: 17 April 2026 © The Author(s) 2026AbstractBackground A subset of individuals experience prolonged neurological and psychiatric symptoms following SARS-CoV-2 infection, a condition referred to as long COVID (LC). Limited evidence implicates ongoing neuroinflammatory processes as a driver of LC. This study investigates neuroinflammation in LC using translocator protein positron emission tomography (TSPO PET).Methods 14 LC, 11 healthy control (HC) and 13 multiple sclerosis (MS) participants were included in the study. They underwent [ 11 C]PK11195 TSPO PET and 3T magnetic resonance imaging (MRI) to evaluate glial activation, white matter (WM) pathology and brain volumetrics. Serum neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) were measured as markers of neuronal and glial damage. LC participants completed neurological examinations and mental health assessments.Results TSPO availability, measured as distribution volume ratio (DVR), was not elevated in LC compared to HCs but was significantly lower in LC compared to MS (WM DVR 1.03 vs. 1.06; p = 0.007). Individuals imaged within 16 months of SARS-CoV-2 infection showed higher WM DVR compared to those with a longer disease duration (1.05 vs. 1.02;p = 0.04). Moreover, lower quality of life was associated with higher DVRs in the hippocampus, amygdala and thala- mus (ρ = − 0.83- − 0.70), and depression and anxiety correlated positively with DVRs in the hippocampus and amygdala (ρ = 0.75–0.97).Conclusions LC TSPO availability did not differ from HCs in any studied brain area. However, lower WM TSPO availability in individuals with longer LC duration suggests COVID-19-associated neuroinflammation may subside with time, while the association between limbic TSPO availability and LC severity may imply a role for limbic activity in LC symptomology.Keywords [11C]PK11195 · Glial activation · Limbic system · Long COVID · Neuropsychiatric symptoms · TSPO PET Joel Tuomaala, Maija Saraste and Emma Smith have contributed equally to this work.* Laura Airaslaura.airas@utu.fi 1 Turku PET Centre, Turku University Hospital, University of Turku, and Åbo Akademi University, Turku, Finland 2 Turku University Hospital, Neurocenter, Turku, Finland 3 Clinical Neurosciences, University of Turku, Turku, Finland 4 InFLAMES Research Flagship, University of Turku, Turku, Finland 5 Åland Central Hospital, Mariehamn, Åland, Finland 6 Department of Biotechnology, University of Turku, Turku, Finland 7 Department of Hospital Hygiene and Infection Control, TYKS Turku University Hospital, Turku, Finland 8 Outpatient Clinic for Long-Term Effects of COVID-19, Helsinki University Central Hospital, and University of Helsinki, Helsinki, Finland 9 Radiopharmaceutical Chemistry Laboratory, Turku PET Centre, University of Turku, Turku, Finland 10 Accelerator Laboratory, Åbo Akademi University, Turku PET Centre, Turku, Finland ### Page 2 Journal of Neurology (2026) 273:298298 Page 2 of 13IntroductionIn the aftermath of the COVID-19 pandemic, a substantial proportion of individuals report a variety of persistent or new- onset symptoms, collectively referred to as long COVID (LC). The World Health Organisation (WHO) defines LC as the con- tinuation or development of new symptoms 3 months after the initial SARS-CoV-2 infection, with these symptoms lasting for at least 2 months with no other explanation [1]. The commonly reported symptoms, such as fatigue, post-exertional malaise, difficulties in concentrating, headaches, depression and anxiety [2, 3], suggest possible post-infectious cerebral involvement. Emerging evidence implicates neuroinflammation as a key contributor [4, 5], but also other mechanisms such as damage to blood vessels, neuronal injury and autoimmune response against the nervous system have been suggested [6, 7]. Positron emission tomography (PET) imaging using 18-kDa translocator protein (TSPO)-specific radioligands can detect glial activation, a hallmark of neuroinflammation [8]. This technique is widely used in the study of neuroinflamma- tory conditions such as multiple sclerosis (MS). In the context of LC, increased TSPO availability has been found in multiple brain regions along with diverse symptom profiles [9]. Further, elevated TSPO total distribution volume (Vt) was also reported in people who had developed depression following a COVID- 19 infection [10]. Serum glial fibrillary acidic protein (GFAP) and neurofila- ment light chain (NfL) are biomarkers which reflect astrocytic and axonal damage, respectively [11]. During acute COVID- 19, both GFAP and NfL can be elevated [12], particularly in patients exhibiting neurological symptoms [13]. At approxi- mately 3 months post-infection, increased GFAP (but not NfL) levels have been reported in those with neurological LC symptoms; however, by 6 months post-infection, levels of both markers typically return to baseline, irrespective of symptom persistence [14–17]. This study investigates whether neuroinflammation is ele- vated in the context of prolonged neurological and psychiatric LC symptoms by quantifying glial activation via TSPO PET imaging using the [ 11 C]PK11195 radioligand. Additionally, we assess serum levels of GFAP and NfL and examine their correlation with PET-derived measures of neuroinflammation. Finally, as an exploratory analysis, we evaluate associations between TSPO binding and participant-reported disability, wellbeing, and neuropsychiatric and cognitive symptoms.Materials and methodsParticipants and study designPeople with LC symptoms were prospectively recruited from the Neurocenter Outpatient Clinic of Turku Univer- sity Hospital, Turku, Finland and from the Long COVID Outpatient Clinic at Helsinki University Hospital, Hel- sinki, Finland in 2021–2023. Inclusion criteria were age ≥ 18 years, neurological symptoms like fatigue or cog- nitive symptoms that interfered with work or study capac- ity, symptoms that had lasted for at least 2 months and were present at 3 months after the SARS-CoV-2 infection, and a confirmation of COVID-19 condition by a positive polymerase chain reaction (PCR) or antigen test during the acute infection phase. The exclusion criteria for LC participants were another condition causing symptoms associated with LC, pregnancy or breastfeeding, corti- costeroid treatment within the past 4 weeks before PET/ MRI, claustrophobia or history of severe anxiety or panic attacks, exposure to experimental radiation within the past 12 months, and intolerance to PET or MRI scans. Age- and sex-matched HCs with no known neurologi- cal symptoms or diseases and patients with MS were used as control groups for imaging parameters and biomarker assays. HCs were prospectively recruited for this study from Turku University Hospital staff and members of the local community through staff networks (2021–2022). MS participants were originally recruited for other studies at the MS Neurocenter Outpatient Clinic of Turku University Hospital based on a confirmed MS diagnosis using current diagnostic criteria and willingness to participate in PET studies (2019–2022) and were retrospectively included in this study. The MS PET data presented in this study have not been used in other publications. All study participants underwent PET and MRI scans and blood sampling. Clinical neurological examina- tion was performed for individuals with LC for assess- ment of neurological symptoms and for patients with MS to assess the Expanded Disability Status Scale (EDSS) scores. The LC participants freely self-reported unstruc- tured descriptions of their medical history, LC symptoms and hospitalisation details related to COVID-19 during a medical consultation and answered several mental health questionnaires. Imaging parameters and biomarker assays were com- pared between the LC, MS, and HC groups to determine whether LC is associated with overall elevated neuroin- flammation relative to a healthy reference group and a neuroinflammatory disease control. Mental health ques- tionnaires were completed by LC participants only, while the HC and MS groups served exclusively as imaging and ### Page 3 Journal of Neurology (2026) 273:298 Page 3 of 13 298biomarker reference groups. Within the LC group, associa- tions between questionnaire scores and imaging param- eters were examined in an exploratory manner to evaluate the relationship between subjective symptom severity and neuroinflammation.QuestionnairesLC participants filled in Finnish versions of two quality of life questionnaires (European Health Interview Survey— Quality of Life [EuroHIS-8], RAND Corporation 36-item Short Form Health Survey [RAND SF-36]) [18, 19], two fatigue questionnaires (Fatigue Severity Scale [FSS], Modi- fied Fatigue Impact Scale [MFIS]) [20, 21], anxiety (Gen- eral Anxiety Disorder-7 [GAD-7]) [22] and depression questionnaires (Patient Health Questionnaire 9 [PHQ-9]) [23], insomnia (Insomnia Severity Index [ISI]) [24] and finally, health and disability questionnaires (WHO Disabil- ity Assessment Schedule 2.0 [WHODAS 2.0]) [25]. Ques- tionnaire scores were calculated according to instructions as either the average of the total scores (EuroHIS-8, FSS), the sum of the total scores (MFIS, GAD-7, PHQ-9, ISI, and WHODAS 2.0) or the average of subsegments (RAND SF-36). For HC and MS participants, questionnaires were not obtained.Biomarker analysisSerum NfL and GFAP concentrations were measured with a single molecule array assay (Neurology 2 plex B, Simoa® Technology, Quanterix, Billerica, MA, U.S.) from serum samples collected as previously described [26].PET/MR image acquisition and processingThe PET/MR imaging was performed at the Turku PET Cen- tre (Turku, Finland) with GE SIGNA™ PET/MR scanner (GE HealthCare, Chicago, IL, U.S.). Beginning at radio- ligand injection, a 30-min 3.0 T brain MRI and a dynamic 60-min whole brain [ 11 C]-PK11195 PET were performed simultaneously. MRI included axial T2, 3D fluid-attenuated inversion recovery (FLAIR) and 3D T1 sequences. The[ 11 C]PK11195 radioligand radiochemical synthesis was performed as previously described [27]. The mean (SD) injected radioligand was 443.5 (63.4) for HC, 445.4 (47.15) for MS, and 429.6 (56.3) for LC participants, with no sig- nificant differences between groups. T1 MR images were used for auto segmentation of regions of interest (ROIs) with the FreeSurfer image analysis suite v7.2.0. (http://surfer.nmr.mgh.harvard.edu/). ROIs used in this study were the whole brain, white matter (WM), cor- tical gray matter (GM), amygdala, hippocampus, thalamus, putamen, pallidum, cingulate cortex, corpus callosum and brain stem. In the MS participants, the WM ROI was con- verted to a normal-appearing white matter (NAWM) ROI by subtracting manually curated MS lesion masks from it. For the LC and HC participants, the WM and NAWM ROIs were identical. ROI volumes were calculated from MR images based on segments created in FreeSurfer as described pre- viously [27]. Intracranial volumes (ICVs) were calculated using SPM12. ROI volumes are reported as parenchymal fractions (PF), defined as the ratio of brain region parenchy- mal volume to total intracranial volume. MR and PET image co-registration was performed using SPM12 (Wellcome Trust Center for Neuroimaging) running on Matlab 2017a (The MathWorks, Natick, MA, U.S.). PET images were reconstructed using Bayesian penalised likeli- hood algorithm Q.Clear that incorporates a time-of-flight model and point spread function correction. A penaliza- tion factor β = 350, 17 time frames, and voxel dimensions 1.172 × 1.172 × 2.78 mm (radial, tangential, axial) were used for reconstruction. Mutual information realignment in SPM12 was used to correct possible displacements between frames. PET had an approximate spatial resolution of 4.4 × 4.1 × 5.5 mm as determined by NEMA 2012 1 cm sphere standard test with 18 F isotope. All images were res- liced to the MRI voxel size of 1 × 1 × 1 mm. Specific bind- ing of [11 C]PK11195 radioligand was quantified as distribu- tion volume ratio (DVR) in different ROIs using the Logan method within a time interval of 20–60 min. A supervised clustering algorithm with four predefined kinetic tissue classes was used with the Matlab SuperPK software package to acquire the time activity curve corresponding to a refer- ence region devoid of specific radioligand binding [28, 29]. The kinetic classes describing binding in normal GM (GM cortex), normal WM (centrum semiovale), and the blood activity (95% threshold mask from the sum from the first five PET frames) were defined using data from the HCs. The kinetic class for the high-binding GM was extracted from the core of the thalamus of the participants with secondary progressive MS.Statistical analysesStatistical analyses were conducted in R programming environment (R v4.3.2). Non-normality of data was deter- mined using Shapiro–Wilk test (stats v4.3.2, shapiro.test), histograms and quantile–quantile plots (ggplot2 v3.5.1, geom_qq). For parameters non-normally distributed within any group, the median with first and third quantile limits (Q1–Q3) and Wilcoxon test (stats v4.3.2, wilcox. test) for group-wise comparisons is reported. Otherwise mean with standard deviation and two-sample Welch’st-test (stats v4.3.2, t.test) is reported. In group-wise com- parisons of sex proportions Fisher’s exact test (stats v4.3.2, fisher.test) is reported. Corrected p-values were adjusted ### Page 4 Journal of Neurology (2026) 273:298298 Page 4 of 13for within-parameter multiple comparisons using Benja- mini–Hochberg method (stats v4.3.2, p.adjust). For corre- lation analyses, Spearman correlation coefficient (ρ), 95% confidence interval and raw p-value are reported (psych v2.4.6.26, corr.test). Trendlines shown in correlation scat- terplots are based on linear regression and are not derived from the associated Spearman correlation coefficients. Enrichment of significant correlations in limbic regions was assessed using an exact permutation test, enumerating all 165 possible combinations of 3 ROIs from the 11 examined. Analysis was restricted to non-dependent symptom scores WHODAS total, MFIS total, RAND-36 subscales, FSS total, GAD-7 total, PHQ-9 total, ISI total, and EUROHIS-QOL total to ensure independence of symptom measures. Fold enrichment was calculated relative to the null expectation of random proportional distribution across all 11 ROIs. Cron- bach’s alpha test (psych v2.4.6.26, alpha) for covariance and Spearman–Brown corrected mean even–odd split-half reli- ability (psych v2.4.6.26, splitHalf) of all possible splits for internal reliability consistency among questionnaire replies were calculated for final and subsection scores across the corresponding individual questions. All tests were two-tailed and p-values under 0.05 were considered statistically signifi- cant for all analyses.ResultsDemographic data14 participants with LC symptoms, 11 HC participants and 13 MS participants were included in the study. Six of the 14 LC participants had been hospitalised during the acute SARS-CoV-2 infection but did not require intensive care. In the HC group, five participants had been diagnosed with and had fully recovered from COVID-19 and were free of any LC-like symptoms prior to study participa- tion. The recovered controls did not differ from other con- trols in demographic, serum biomarker or PET parameters (Table S1). The MS group contained six relapsing–remitting MS (RRMS) and seven secondary progressive MS (SPMS) patients with a median disease duration of 20 years and a median EDSS of 3.5. Age and weight did not differ signifi- cantly between the LC, MS and HC groups. The mean BMI of the LC participants was higher compared to HCs, but the difference was not significant after multiple comparison correction (Table 1).Self‑reported neurological symptoms correspond poorly with clinical examination findings in long COVID participantsLC duration from SARS-CoV-2 diagnosis ranged from 7 to 33 (median 15) months at the time of imaging. The most commonly reported symptom was post-exertional malaise, defined as the worsening of symptoms after physical or men- tal exertion, reported by 11 (79%) LC participants. Fatigue and “brain fog” were also common, reported by nine (64%) participants (Fig. 1). All 14 LC participants underwent a clinical neurologi- cal examination. Seven participants (50%) showed a fully normal examination, while the remaining seven exhibited some neurological abnormalities. Four (29%) participants had impaired olfaction—two (14%) of whom also experi- enced loss of taste. Four (29%) had decreased sensation in the lower extremities (mainly impaired sense of vibration),Table 1 Demographic and soluble biomarker data of the study cohort Number of male and female participants, percentage of females, and Fisher’s exact test for group-wise comparisons are reported for sex. For other, normally distributed parameters, mean (SD) and t-test p-values are reported; for non-normally distributed parameters, median (Q1–Q3) and Wilcoxon test p-values are reported. P-values in brackets are corrected for within-parameter multiple comparisons using the Benjamini– Hochberg method. Significant p-values are bolded. BMI body mass index, EDSS Expanded disability status scale, GFAP glial fibrillary acidic protein, HC healthy control, LC long COVID, MS multiple sclerosis, NfL neurofilament light chain MS HC LC HC vs MS LC vs MS HC vs LCn 13 11 14 – – –n male/n female (% female) 3/10 (78) 7/4 (36) 8/6 (43) 0.095 (0.180) 0.120 (0.180) 1.000 (1.000) Age (years) 46.79 (6.62) 45.55 (12.16) 45.00 (7.75) 0.766 (0.899) 0.524 (0.899) 0.899 (0.899) Weight (kg) 85.00 (66.60–96.00) 78.90 (77.20–85.15) 102.10 (81.23–121.75) 0.728 (0.728) 0.152 (0.228) 0.095 (0.228) BMI (kg/m 2 ) 30.25 (8.37) 26.91 (3.89) 32.68 (7.23) 0.215 (0.322) 0.431 (0.431) 0.019 (0.056) NfL (pg/ml) 8.27 (5.28–14.12) 7.86 (4.31–9.59) 5.87 (4.97–10.29) 0.418 (0.704) 0.470 (0.704) 0.976 (0.976) GFAP (pg/ml) 75.84 (64.49–124.65) 53.71 (44.41–63.17) 67.67 (55.07–89.61) 0.043 (0.128) 0.347 (0.347) 0.343 (0.347) Long COVID duration (months) – – 15.00 (10.00–23.50) – – – MS duration (years) 20.01 (18.30–24.44) – – – – – EDSS 3.50 (2.50–5.00) – – – – – ### Page 5 Journal of Neurology (2026) 273:298 Page 5 of 13 298and one (7%) had difficulties in toe-and-heel walking, jump- ing on one leg and squat sitting. Additionally, one partici- pant had dysmetria (7%), and another presented a bilateral Babinski’s sign (7%). The symptoms reported by the LC participants, apart from anosmia, were rarely accompanied by corresponding clinical examination abnormalities. For example, of the five participants reporting weakness or numbness of the limbs, three exhibited clinical symptoms upon the neurological examination: one reported impaired sensation, one had dysmetria, and one reported impaired olfaction. The remain- ing two had a fully normal neurological examination.Mental health questionnaire scores indicate elevated depression and anxiety in long COVID participantsEuroHIS-8, FSS, GAD-7, MFIS, ISI, PHQ-9, and WHODAS 2.0 questionnaire final scores are shown in Table 2. RAND- 36 questionnaire scores by subsection, and subsectionFig. 1 Symptoms reported by long COVID participants. The number of affected patients and symptom frequency is shown above the barTable 2 Mental health questionnaire scores among participants with long COVID 10 LC participants completed all questionnaires, one completed all but GAD-7 and ISI, and three did not complete any questionnaires. Means (SD) and medians (Q1–Q3) are calculated on questionnaire sum scores and Cronbach’s α across the corresponding individual questions. FSS Fatigue Severity Scale, GAD-7General Anxiety Disorder-7, ISI Insomnia Severity Index, MFIS Modified Fatigue Impact Scale, PHQ-9Patient Health Questionnaire 9, WHODAS 2.0 WHO Disability Assessment Schedule 2.0 Mean (SD) Median (Q1–Q3) Min–Max Cronbach’s α Split-half reli- ability mean rQuality of life (EuroHIS-8) 24.3 (6.4) 21.0 (20.0–29.2) 17–34 0.90 0.89 Fatigue (FSS) 5.8 (1.4) 6.2 (5.8–6.6) 2–7 0.97 0.97 Fatigue (MFIS) 48.9 (20.2) 49.0 (40.5–61.5) 3–75 0.97 0.97 Sleep (ISI) 11.8 (5.3) 12.0 (7.5–13.8) 6–23 0.82 0.80 Anxiety (GAD-7) 12.5 (4.4) 12.5 (9.2–14.8) 7–20 0.90 0.89 Depression (PHQ-9) 8.4 (5.6) 6.5 (5.0–12.5) 2–17 0.88 0.87 Disability (WHODAS 2.0) 46.1 (23.5) 42.5 (38.8–60.0) 12–91 0.70 0.96 ### Page 6 Journal of Neurology (2026) 273:298298 Page 6 of 13scores for the other questionnaires, are shown in Table S2. All questionnaire final scores were internally consistent at Cronbach’s α ≥ 0.70 and mean split-half reliability r ≥ 0.80. The LC participant PHQ-9 and GAD-7 mean scores were 8.4 and 12.5, indicating mild depression and moderate anxi- ety, respectively. Two participants demonstrated moderately severe depression with a PHQ-9 score of 17. Three partici- pants had a GAD-7 score of 15 or higher, indicating severe anxiety. Questionnaire scores did not correlate with duration of LC, weight, BMI or age, except for correlations between older age and higher fatigue questionnaire scores (FSS ρ = 0.68, p = 0.022 and MFIS ρ = 0.78, p = 0.005).TSPO binding does not differ between long COVID and healthy control participantsThere were no significant differences in [ 11 C]PK11195 DVRs between LC and HC participants in any examined brain region (Table 3; Fig. 2A–F). Compared to MS patients, LC participants had lower DVRs across most brain regions with significant differences in the putamen, thalamus, amyg- dala and pallidum. Compared to HC participants, the MS group had higher DVRs in the thalamus (1.26 vs. 1.20, p < 0.001), and SPMS patients (Table S5) additionally in the NAWM (1.08 vs. 1.05, p = 0.023) (Fig. 2G–H, Table S6). LC participants imaged within 16 months of SARS- CoV-2 diagnosis (median LC duration 10 months, n = 8) had consistently higher DVRs in most regions compared to participants with longer time between diagnosis and imaging (median LC duration 26 months, n = 6) (Tables S7 and S8). The difference was significant for NAWM (1.05 vs. 1.02,p = 0.042) and trending to significance for the whole brain (1.08 vs. 1.06, p = 0.059) (Fig. 2I–J).MRI volumetric measurements do not differ between long COVID and healthy control participantsThere were no significant differences between HC and LC participants in the volume parenchymal fractions of the examined brain regions (Table 4; Fig. S1A–F). The frac- tions were consistently higher in LC participants compared to MS patients, and the difference was significant in all brain areas except for the hippocampus and amygdala. MS paren- chymal fractions of NAWM, thalamus, putamen, pallidum and brain stem were significantly lower than those in both LC and HC groups.Serum biomarkers of neuronal and astrocytic damage do not differ between long COVID participants and healthy controlsNfL serum concentrations showed no significant differences between any of the study groups (Table 1; Fig. 2K–L). No significant differences were found in GFAP concentration between LC participants and HCs. The MS patients had higher GFAP concentration compared to HCs (median 76 vs. 68 pg/ml, p = 0.043), but the difference did not remain significant after multiple comparison correction (p= 0.13).TSPO binding correlates with mental health questionnaire scores in the long COVID cohortThere were several significant correlations between LC par- ticipant questionnaire scores and DVRs in deep gray matter structures thalamus, hippocampus and amygdala (Table 5, Figs. 3A–P and 4). Lower EuroHIS-8 scores indicating decreased quality of life correlated strongly with higherTable 3 Regional [11 C]PK11195 distribution volume ratios in healthy control, long COVID and multiple sclerosis participants For normally distributed parameters, mean (SD) and t-test p-values are reported; for non-normally distributed parameters, median (Q1–Q3) and Wilcoxon test p-values are reported. P-values in brackets are corrected for within-parameter multiple comparisons using the Benjamini– Hochberg method. Significant p-values are bolded. DVR distribution volume ratio, HC healthy control, LC long COVID, MS multiple sclerosis,NAWM normal-appearing white matter MS HC LC HC vs MS LC vs MS HC vs LC Whole brain DVR 1.10 (0.02) 1.08 (0.02) 1.08 (0.02) 0.126 (0.190) 0.046 (0.139) 0.587 (0.587) NAWM DVR 1.06 (1.05–1.10) 1.04 (1.02–1.07) 1.03 (1.01–1.06) 0.072 (0.108) 0.007 (0.020) 0.467 (0.467) Cortex gray matter DVR 1.11 (0.02) 1.10 (0.02) 1.10 (0.02) 0.307 (0.627) 0.627 (0.627) 0.563 (0.627) Amygdala DVR 1.07 (0.04) 1.05 (0.05) 1.03 (0.05) 0.309 (0.309) 0.014 (0.041) 0.220 (0.309) Hippocampus DVR 1.04 (0.03) 1.03 (0.04) 1.02 (0.06) 0.547 (0.547) 0.219 (0.547) 0.480 (0.547) Thalamus DVR 1.26 (0.06) 1.20 (0.06) 1.18 (0.05) 0.015 (0.022) < 0.001 (0.002) 0.404 (0.404) Putamen DVR 1.18 (0.06) 1.14 (0.04) 1.12 (0.04) 0.057 (0.085) 0.006 (0.019) 0.298 (0.298) Pallidum DVR 1.18 (1.15–1.21) 1.16 (1.11–1.19) 1.11 (1.09–1.16) 0.258 (0.258) 0.006 (0.017) 0.149 (0.224) Cingulate cortex DVR 1.09 (0.04) 1.09 (0.03) 1.09 (0.03) 0.548 (0.782) 0.782 (0.782) 0.700 (0.782) Corpus callosum DVR 0.86 (0.85–0.92) 0.91 (0.88–0.91) 0.87 (0.84–0.89) 0.531 (0.796) 0.981 (0.981) 0.202 (0.607) Brain stem DVR 1.23 (0.05) 1.20 (0.05) 1.18 (0.05) 0.076 (0.115) 0.006 (0.018) 0.326 (0.326) ### Page 7 Journal of Neurology (2026) 273:298 Page 7 of 13 298DVRs in all three regions (ρ = − 0.70, p = 0.03; ρ = −0.83, p < 0.01; ρ = −0.76, p = 0.01). Higher GAD-7 and PHQ-9 scores evaluating anxiety and depression correlated strongly with increased hippocampus and amygdala DVRs (ρ = 0.88,p< 0.01; ρ = 0.75, p = 0.01). Of the fatigue questionnaires, an increased MFIS score, which includes questions about mental fatigue, correlated with higher DVRs in the hippocampus and thalamus. In con- trast, the FSS questionnaire, in which mental and physical fatigue are not evaluated separately, did not correlate with any DVRs. Overall health and disability questionnaire WHODAS 2.0 showed no correlation with DVRs in any region, but the cognitive section subscore correlated with increased hippocampal (ρ = 0.71, p= 0.02) and amygdala (ρ = 0.64, p= 0.04) DVRs (Tables S3, S4, Fig. 3C, G). Similarly, worse RAND-36 energy/fatigue-, pain- and emotional wellbeing subsection scores, but not general health subsection scores,Fig. 2 Regional [11 C]PK11195 distribution volume ratios and serum biomarker levels in healthy controls, long COVID and multiple scle- rosis participants. DVRs and within-parameter multiple-comparison- corrected (Benjamini–Hochberg method) t-test A, C–H, J or Wil- coxon test B, I p-values for group-wise comparisons are reported.A–F Whole brain, NAWM, cortical gray matter, amygdala, hip- pocampus and thalamus DVRs for all multiple sclerosis, LC and healthy control participants. G–H NAWM and thalamus DVRs for relapsing–remitting MS (RRMS), secondary progressive MS (SPMS) and healthy control participants. I–J Whole brain and NAWM DVRs in LC participants with SARS-CoV-2 diagnosis within 16 months of imaging versus over 16 months from imaging. K–L Serum concentra- tion of GFAP and NfL biomarkers of astrocytic and axonal damage. GFAP and NfL were available in 13 LC participants, 10 healthy con- trols and 12 MS patients. DVR distribution volume ratio, GFAP glial fibrillary acidic protein, HC healthy control, LC long COVID, MSmultiple sclerosis, NAWM normal-appearing white matter, NfL neuro- filament light chain ### Page 8 Journal of Neurology (2026) 273:298298 Page 8 of 13correlated with higher DVRs in the hippocampus (Table S3, Fig. 3). The sleep evaluation questionnaire ISI showed no signifi- cant correlation with DVRs in any studied region. Across all comparisons, 16 of the 17 identified significant correlations were in the limbic system. A permutation enrich- ment analysis was used to assess whether this concentration exceeds the number expected by chance. The analysis was restricted to the questionnaire scores that were independent of each other by excluding questionnaire subsection scores. Of the 13 remaining correlations, 12 concentrated in the ana- tomically predefined limbic system, representing a more than threefold enrichment (permutation p = 0.006), inconsistent with a multiple-testing artefact. The one significant correlationTable 4 Regional brain volume parenchymal fractions in healthy control, long COVID and multiple sclerosis participants For normally distributed parameters, mean (SD) and t-test p-values are reported; for non-normally distributed parameters, median (Q1–Q3) and Wilcoxon test p-values are reported. P-values in brackets are corrected for within-parameter multiple comparisons using the Benjamini–Hoch- berg method. Significant p-values are bolded. HC healthy control, LC long COVID, MS multiple sclerosis, NAWM normal-appearing white mat- ter, PF parenchymal fraction MS HC LC HC vs MS LC vs MS HC vs LC Whole-brain volume PF 82.26 (3.85) 84.68 (3.11) 85.84 (2.25) 0.102 (0.153) 0.009 (0.026) 0.312 (0.312) NAWM volume PF 32.39 (31.22–32.77) 35.00 (32.96–35.21) 34.75 (33.94–37.15) 0.013 (0.019) < 0.001 (0.001) 0.291 (0.291) Cortex gray matter volume PF 31.07 (2.06) 32.35 (2.23) 32.75 (1.54) 0.159 (0.239) 0.025 (0.076) 0.618 (0.618) Amygdala volume PF 0.24 (0.03) 0.24 (0.02) 0.24 (0.03) 0.736 (0.837) 0.648 (0.837) 0.837 (0.837) Hippocampus volume PF 0.60 (0.07) 0.65 (0.04) 0.64 (0.06) 0.022 (0.065) 0.068 (0.102) 0.731 (0.731) Thalamus volume PF 0.93 (0.11) 1.09 (0.07) 1.10 (0.09) < 0.001 (0.001) < 0.001 (< 0.001) 0.949 (0.949) Putamen volume PF 0.59 (0.07) 0.67 (0.07) 0.66 (0.06) 0.007 (0.010) 0.007 (0.010) 0.757 (0.757) Pallidum volume PF 0.26 (0.24–0.27) 0.30 (0.27–0.30) 0.28 (0.27–0.30) 0.005 (0.014) 0.043 (0.064) 0.501 (0.501) Cingulate cortex volume PF 1.30 (0.12) 1.32 (0.19) 1.34 (0.13) 0.767 (0.767) 0.409 (0.767) 0.764 (0.767) Corpus callosum vol- ume PF 0.27 (0.04) 0.27 (0.03) 0.28 (0.02) 0.810 (0.810) 0.571 (0.810) 0.371 (0.810) Brain stem volume PF 1.43 (0.18) 1.57 (0.06) 1.57 (0.12) 0.020 (0.046) 0.030 (0.046) 0.996 (0.996)Table 5 Spearman correlations between mental health questionnaire scores and regional [ 11 C]PK11195 distribution volume ratios in long COVID participants Spearman correlation coefficients, 5% to 95% confidence intervals [0.05–0.95 CI] and naive t-test p-values (p) are shown. Significant p-values are bolded. FSS Fatigue Severity Scale, GAD-7 General Anxiety Disorder-7, ISI Insomnia Severity Index, MFIS Modified Fatigue Impact Scale,NAWM normal-appearing white matter, PHQ-9 Patient Health Questionnaire-9, WHODAS 2.0 WHO Disability Assessment Schedule 2.0 Questionnaire Whole brain DVR NAWM DVR Cortex gray matter DVR Amygdala DVR Hippocampus DVR Thalamus DVR Quality of life (EuroHIS-8) 0.17 [-0.51–0.72] (0.64) -0.09 [-0.68–0.57] (0.81) 0.43 [-0.27–0.84] (0.21) -0.76 [-0.94–-0.25](0.01)-0.83 [-0.96–- 0.42] (< 0.01)-0.70 [-0.92–-0.12](0.03)Disability (WHO- DAS 2.0) 0.33 [-0.37–0.80] (0.35) 0.41 [-0.30–0.82] (0.24) 0.05 [-0.60–0.66] (0.88) 0.54 [-0.14–0.87] (0.11) 0.49 [-0.20–0.86] (0.15) 0.31 [-0.40–0.79] (0.38) Fatigue (FSS) 0.21 [-0.44–0.72] (0.53) 0.17 [-0.48–0.70] (0.61) 0.13 [-0.51–0.68] (0.70) 0.11 [-0.52–0.67] (0.74) 0.35 [-0.31–0.79] (0.29) 0.32 [-0.35–0.77] (0.35) Fatigue (MFIS) 0.30 [-0.37–0.76] (0.37) 0.37 [-0.29–0.79] (0.26) -0.03 [-0.62–0.58] (0.94) 0.50 [-0.14–0.85] (0.12) 0.75 [0.26–0.93](0.01)0.68 [0.14–0.91](0.02)Anxiety (GAD-7) 0.05 [-0.60–0.66] (0.89) 0.36 [-0.35–0.81] (0.31) -0.26 [-0.76–0.45] (0.48) 0.83 [0.41–0.96](< 0.01)0.88 [0.55–0.97](< 0.01)0.57 [-0.10–0.88] (0.09) Depression (PHQ- 9) 0.07 [-0.59–0.67] (0.85) 0.22 [-0.48–0.74] (0.55) -0.29 [-0.78–0.42] (0.42) 0.75 [0.22–0.94](0.01)0.87 [0.53–0.97](< 0.01)0.59 [-0.06–0.89] (0.07) Sleep (ISI) 0.01 [-0.63–0.63] (0.99) 0.23 [-0.47–0.75] (0.52) -0.26 [-0.77–0.44] (0.46) 0.49 [-0.20–0.85] (0.15) 0.59 [-0.07–0.89] (0.08) 0.27 [-0.43–0.77] (0.44) ### Page 9 Journal of Neurology (2026) 273:298 Page 9 of 13 298outside the limbic system was between putamen DVR and RAND social functioning (ρ = − 0.70, p = 0.02) (Table S4).Fig. 3 Significant Spearman correlations between mental health questionnaire scores and regional [ 11 C]PK11195 distribution volume ratios in long COVID participants. A–P Correlations in amygdala, hippocampus and thalamus. Spearman correlation coefficients and associated raw p-values are shown along with linear regression-based trend lines. Questionnaire names in brackets. FSS Fatigue Severity Scale, GAD-7 General Anxiety Disorder-7, ISI Insomnia Severity Index, MFIS Modified Fatigue Impact Scale, NAWM normal-appear- ing white matter, PHQ-9 Patient Health Questionnaire-9, RAND-36RAND 36-Item Short Form Health Survey, WHODAS 2.0 WHO Dis- ability Assessment Schedule 2.0 ### Page 10 Journal of Neurology (2026) 273:298298 Page 10 of 13DiscussionTo our knowledge, this is the first study to employ both posi- tive and negative control groups to investigate neuroinflam- mation in a LC cohort with neurological and psychiatric symptoms. We found no significant differences in [ 11 C] PK11195 DVR, a measure of TSPO availability associated with glial cell activation, in any brain region between LC and HC participants. LC participants consistently demon- strated lower DVRs, indicative of lower TSPO availability, than the positive neuroinflammation control group of MS patients. Compared to HCs, MS patients showed higher TSPO availability in the thalamus [30], while SPMS patients additionally showed higher expression in the NAWM [31], validating the imaging methodology. While we did not observe altered regional TSPO avail- ability in LC participants compared to the HCs, we found strong positive associations between LC mental health symptom severity and [ 11 C]PK11195 DVRs in limbic regions—including the hippocampus, amygdala, and thala- mus. This regionally selective association in the absence of elevated global glial activation suggests that the increased TSPO availability in the limbic areas may reflect the func- tional central nervous system (CNS) alterations associated with the neurological and psychiatric LC symptoms rather than residual elevated inflammation from the acute SARS- Cov-2 infection. It is important to note that TSPO avail- ability is relatively unspecific, and aside from inflammation, also reflects other cellular functions such as mitochondrial metabolic activity and the density of TSPO-expressing glial cells actively performing functions not related to inflamma- tion (reviewed in [32]). Thus, TSPO availability may reflect CNS activation in LC without necessarily indicating ongo- ing proinflammatory processes [33, 34]. Glial cells contrib- ute to several essential brain functions—including debris clearance, synaptic pruning, and neuromodulation (reviewed in [35])—which may be particularly active in the limbic sys- tem in chronic neuropsychiatric conditions. Indeed, similarities in clinical presentation and neu- roimaging findings have been reported across LC, myal- gic encephalomyelitis/chronic fatigue syndrome (ME/ CFS), and depression [36, 37]. Nakatomi et al. (2014), for example, reported increased TSPO expression in the hip- pocampus, amygdala, and thalamus in ME/CFS patients with neuropsychiatric symptoms [38]. Meta-analyses of TSPO PET imaging in depression have likewise shown increased expression in limbic structures, including the anterior cingulate cortex (ACC) and hippocampus [39, 40]. Our findings align with these reports, suggesting that increased TSPO availability in limbic regions may associ- ate with a shared neurobiological mechanism underlying the chronic psychiatric and neurological symptoms. Simi- lar “sickness behaviour” symptoms—such as fatigue, sleep disturbances, anhedonia, and cognitive impairment— across LC, ME/CFS, and depression further support this interpretation.Fig. 4 Fatigue, depression and anxiety correlate with limbic TSPO availability in LC participants. The figure shows glial activation in the limbic system of a female LC participant with high limbic TSPO availability (left) and a female LC participant with low limbic TSPO availability (right). Volumetric T1 MRI (grayscale) and limbic TSPO PET (colour gradient) images are overlaid and rendered with trans- parency to visualise TSPO availability throughout the limbic volume. ### Page 11 Journal of Neurology (2026) 273:298 Page 11 of 13 298In line with the lack of LC-associated elevated neu- roinflammation in our study cohort, Visser et al. (2025) reported no difference in TSPO availability between 33 individuals with persistent post-COVID-19 symptoms and 14 individuals without post-infection symptoms using [ 18 F]DPA-714 radioligand [41]. However, earlier studies have reported increased TSPO expression in LC. VanElzakker et al. (2024) reported elevated [ 11 C]PBR28 radioligand standardised uptake value (SUVR) in the lim- bic system, anterior cingulate cortex, thalamus, and basal ganglia in LC patients compared to pre-pandemic con- trols [9]. Braga et al. (2023) found increased [ 18 F]FEPPA radioligand binding in the ventral striatum and dorsal puta- men in moderately depressed LC patients, though without correlation to symptom severity or cognitive function [10]. One potential explanation for these discrepancies is the use of different radioligands. While our study used the first- generation tracer [ 11 C]PK11195, others have employed second-generation tracers [ 11 C]PBR28 and [ 18 F]FEPPA. Although [ 11 C]PK11195 is widely used and has well- established analysis methods, it has a lower signal-to-noise ratio due to high nonspecific binding, which may reduce its sensitivity to subtle inflammatory changes [42, 43]. This limitation could explain why our study did not detect elevated TSPO availability in LC, while still capturing the pronounced increases observed in MS patients. Notably, however, the earlier PET studies reporting elevated neuroinflammation have focussed on participants imaged within 6 months of infection [10], or selected those with severe ME/CFS-like symptom profiles [9], which may account for the higher observed inflammation [14]. In con- trast, our inclusion criterion resulted in a cohort with mean disease duration of 17 months and, similar to the Visser et al. 2025 cohort with 25-month mean disease duration, reflected the effects of established chronic disease rather than acute post-infection changes. Consistently, we observed higher NAWM DVRs in participants with more recent infections, suggesting that neuroinflammation may be more prominent early on, potentially resolving over time while symptoms persist. This may suggest a shift from neuroinflammatory to other mechanisms, such as increased neuronal activity and the concomitant alteration of glial metabolism in the limbic areas, as contributors to LC symptomatology [36]. Regarding peripheral biomarkers, we found no differ- ences in GFAP or NfL levels between the LC and HC groups. Although both markers are elevated during the acute phase of COVID-19 [12], our finding is consistent with previous studies reporting lack of post-infection NfL elevation [15, 17]. Furthermore, elevated GFAP levels measured at an early post-infection stage return to normal levels by the 6-month post-infection timepoint [14–17].LimitationsThis study included a relatively small sample of 14 LC patients, 11 HCs, and 13 MS patients. Future research should recruit larger LC cohorts, either targeting partici- pants with well-defined symptom subtypes, duration and severity, or defining the population more broadly while incorporating precise clinical stratifications that cap- ture greater phenotypic diversity of LC symptoms and durations. Furthermore, while group differences in age and sex were not significant, LC participants had a nearly significantly higher BMI compared to HCs, which may represent a poten- tial confounder. However, correcting TSPO availability for BMI differences did not diminish the association of neu- ropsychiatric symptoms with limbic TSPO availability. Five HC participants had prior COVID-19 diagnoses. It would have been more attractive to have an entirely COVID-naive HC cohort, but the high population-level exposure to SARS- CoV-2 prior to and during the study period means that truly COVID-naive controls were not practically attainable. More- over, the absence of a documented diagnosis does not pre- clude prior undetected infection. Nonetheless, the HCs with and without prior COVID diagnosis were devoid of any LC symptoms, and did not differ in the measured inflammatory parameters. Therefore, the risk that a previous exposure to SARS-CoV-2 among the healthy controls would have con- founded the findings can be considered negligible.ConclusionWe found no evidence of increased TSPO availability or elevated serum biomarkers indicative of CNS damage in LC patients experiencing psychiatric and cognitive symptoms on average 17 months post-infection. Moreover, NAWM TSPO availability was lower in participants with a prolonged LC duration compared to those with more recent SARS- CoV-2 infection. These findings suggest that persistent LC symptoms are unlikely to be driven by ongoing elevated neuroinflammation. However, LC symptom severity corre- lated positively with TSPO availability in the limbic regions. This may imply that residual COVID-19-associated elevated neuroinflammation observed in early LC subsides with time and does not explain the persistent LC symptoms which may instead reflect cellular metabolic changes in mood- and cog- nition-related brain areas.Supplementary Information The online version contains supplemen- tary material available at https://doi.org/10.1007/s00415-026-13842-w. ### Page 12 Journal of Neurology (2026) 273:298298 Page 12 of 13Acknowledgements All the study participants and the expert staff at Turku PET Centre, especially Ms Marjo Nylund, are gratefully acknowledged for making this study possible.Author Contributions Concept and design: LA, MM, MSa, EH and TP. Acquisition of data: AL, EH, JA, JL, JR, MKa, OM, SL, SLn, LH, TP, SV and SW. Data analysis or interpretation: LA, MM, MSa and JT. Drafting or critical revision of the manuscript for important intel- lectual content: ES, EW, JT, LA, MKa, MM, MSa and SLn. Statistical analysis: MM, JT, RK. Guarantor: LA.Funding Open Access funding provided by University of Turku (including Turku University Central Hospital). This work was funded by the Research Council of Finland grant for a clinical researcher (decision number: 330902), Sigrid Juselius Foundation (decision num- ber N/A), Finnish MS Foundation (decision number N/A), Suomen lääketieteen Säätiö (decision number N/A), the InFLAMES Flagship Programme of the Academy of Finland (decision numbers: 374291, 337530, 357910 and 358823), and the European Union’s Horizon Europe research and innovation programme (grant agreement No 101057553).Data Availability Data are available on reasonable request. Anonymised data not published within the article will be shared on a request from a qualified investigator.DeclarationsCompeting Interests The authors declare no competing interests.Ethics Approval This study involves human participants and was approved by the Ethics Committee of the Hospital District of South- west Finland (reference numbers 56/1801/2021, 89/1800/2019 and 67/1801/2018). All study participants have provided written informed consent that covers the use of their data in this study. All procedures performed were in line with the principles of the 1964 Declaration of Helsinki and its later amendments.Open Access This article is licensed under a Creative Commons Attri- bution 4.0 International License, which permits use, sharing, adapta- tion, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 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