Blood-brain barrier disruption in Long COVIDassociated cognitive impairment Chris Greene Trinity College Dublin https://orcid.org/0000-0003-4192-9433 Ruairi Connolly Trinity College Dublin Declan Brennan Trinity College Dublin Aoife Laffan St James' Hospital Eoin O'Keeffe Trinity College Dublin Lilia Zaporojan Trinity College Dublin Emma Connolly Trinity College Dublin Cliona Ni Cheallaigh Trinity College Dublin Niall Conlon St James' Hospital Colin Doherty St James's Hospital Matthew Campbell Trinity College Dublin https://orcid.org/0000-0003-3325-240X Article Keywords: SARS-CoV-2, long COVID, blood-brain barrier, brain fog Posted Date: January 23rd, 2023 DOI: https://doi.org/10.21203/rs.3.rs-2069710/v2 Page 1/25 License:   This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Additional Declarations: There is NO Competing Interest. Version of Record: A version of this preprint was published at Nature Neuroscience on February 22nd, 2024. See the published version at https://doi.org/10.1038/s41593-024-01576-9. Page 2/25 Abstract Vascular disruption has been heavily implicated in COVID-19 pathogenesis and may predispose the neurological sequelae associated with the condition now known as long COVID. To date, no studies have objectively assessed blood-brain barrier (BBB) function in individuals with neurological complications stemming from prior SARS-CoV-2 infection. Here, we explored the neurobiological effects of SARS-CoV-2 infection in humans with acute infection (n = 76) and those with persistent long COVID with and without neurological impairment. Following acute infection, patients with neurological impairment had increased serum S100β, indicative of BBB disruption. Furthermore, using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in long COVID patients (n = 32), we observed elevated BBB permeability in distinct neuroanatomical regions including the frontal cortex, occipital lobe and temporal lobes which correlated with global brain volume and white matter volume de cits in patients with neurological impairment. Patients with neurological impairment had increased levels of blood-based biomarkers including GFAP, TGFβ and IL8 with levels of TGFβ that correlated with BBB permeability and structural brain changes. Peripheral blood mononuclear cells isolated from unaffected and long COVID patients had persistent upregulation of in ammatory markers including IFNA/G and showed increased adhesion to human brain endothelial cells in vitro. Finally, exposure of endothelial cells to serum from long COVID patients induced increases in ICAM-1, VCAM-1 and TNF irrespective of neurological sequelae. Together, these data suggest that sustained systemic in ammation and persistent localised BBB dysfunction is a feature of long COVID-associated neurological impairment. Importantly, this may also be therapeutically relevant in the treatment and clinical management of this patient group. Introduction Coronavirus disease 2019 (COVID-19) is a clinical syndrome caused by a novel coronavirus, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). COVID-19 primarily affects the respiratory tract and can progress to respiratory compromise, severe acute respiratory distress syndrome and death1,2. Neurological sequelae of COVID-19, colloquially known as “brain fog” are increasingly being reported and include headache, fatigue, malaise and altered levels of consciousness. Acute respiratory distress syndrome (ARDS) due to COVID-19 has been associated with encephalopathy, agitation, confusion, and corticospinal tract dysfunction. Such symptoms however, including anosmia (although not to the extent seen in the rst wave of COVID-19), may be expected in anyone recovering from a severe viral illness due to cytokine release, critical illness encephalopathy, or medication3. Clinical observations of neurological complications in 236,379 patients in the 6 months following a COVID-19 diagnosis have found that 33.62% of patients were estimated to have demonstrated clinically signi cant neurological or psychiatric dysfunction4. Neurological problems have been reported in other respiratory viral infections including in uenza, coronavirus and metapneumovirus with febrile or afebrile seizures, status epilepticus, encephalopathies and encephalitis being the most frequently reported5. However, there is still little understanding of the pathogenesis and long-term outcome of neurological problems following SARSCoV-2 infection. SARS-CoV-2 gains cellular entry via its receptors ACE2 and TMPRSS2, but it may enter Page 3/25 via other receptors including neuropilin and vimentin, all of which are enriched in vascular cells6–10. There are, however, con icting reports regarding the neuro-invasiveness of SARS-CoV-2 and indeed the cellular expression of the receptors11–15, suggesting that other mechanisms are responsible for the neurological problems reported. A recent preprint suggests persistence of viral RNA in multiple anatomic sites including the brain for up to 230 days following symptom onset, though, these data are from postmortem donor tissues which represent the sickest of individuals16. One hypothesis suggests that breakdown to the integrity of the blood-brain barrier (BBB) and subsequent brain penetration of serum components is responsible for the neurological manifestations following SARS-CoV-2 infection. The BBB is formed by endothelial cells lining cerebral blood vessels and supported by surrounding cells including astrocytes, pericytes, microglia, neurons and the acellular basement membrane17. The barrier is characterised by an enrichment of interendothelial tight junction proteins, a variety of luminal and abluminal transporters and luminal e ux transporters which together maintain separation of the blood and brain and tightly regulate molecular tra cking between the blood and brain and vice versa18. There is clear evidence of microvascular injury in the brains of deceased COVID-19 patients, including brinogen leakage, and thinning of the endothelial cell basal laminae in the olfactory bulb13,19. A more comprehensive evaluation of the same cohort using spatial transcriptomics revealed more detailed vascular and immunological features of microvessels in the brain including serum protein extravasation, platelet accumulation and coagulation system activation20. Numerous studies have also examined BBBrelated changes and responses to SARS-CoV-2 infection or spike protein treatment in post-mortem tissue and animal models13,14,19,21−35. Indeed, it has been shown that the spike protein can cross the BBB in rodents which may cause neuroin ammation and cognitive changes32. However, the cerebrovascular pathology in patients and the underlying mechanisms are still unclear, especially in individuals with long COVID. The lack of a speci c neurological signature of the disease is interesting as other zoonotic betacoronaviruses often produce robust and predictable neurological injury36. In humans, data from SARS and MERS also shows that neurological injury in humans is rare, strongly suggesting that, normally, the BBB provides robust neuroprotection from viral CNS invasion in the majority of patients37. The clinical manifestation of SARS-CoV2 induced BBB alterations in patients have not yet been reported. Here, we hypothesised that the neurological response to COVID may be due to BBB breakdown and subsequent extravasation of serum components. We show that BBB disruption is evident in acute neurological COVID patients and that a cohort of patients with persistent “brain fog” have BBB disruption on neuroimaging which was associated with circulating biomarkers of neuroin ammation and BBB breakdown. We suggest that measurement of BBB integrity may be a clinically useful biomarker of the neurological sequelae that is associated with COVID-19 in some patients. Added to this, targeted Page 4/25 regulation of BBB integrity may also represent a novel method of clinically managing patients with long COVID. Results Acute COVID-induced brain fog is associated with BBB dysfunction We obtained serum samples from 76 in-patients with acute COVID-19 recruited as part of the St James Hospital STTAR Bioresources collection during the initial wave of COVID-19 in March/April 2020 (Fig. 1a)38. 25 unaffected control samples were collected prior to the COVID-19 pandemic. The mean age of control and COVID samples was 44 and 44.7 respectively. The most frequent presenting symptoms included dyspnoea (47), loss of smell and taste (46), cough (45), fatigue (40) and fever (36). As previously reported, more males than females had severe COVID (***p < 0.001) and more males required supplemental oxygen (**p = 0.002) (Table 1). Serum samples were screened on a Luminex 10-plex kit for in ammatory and BBB dysfunction markers. Severity of COVID-19 was determined according to the WHO Severity Guidelines with 25 unaffected, 43 mild, 10 moderate and 23 severe. We found a signi cant increase of IL8 (**p = 0.01 vs unaffected) in moderate cases. There was a signi cant increase in TNF (**p = 0.004 vs unaffected; **p < 0.002 vs mild), IL6 (**p = 0.002 vs unaffected; ***p < 0.001 vs mild) and IL8 (***p < 0.001 vs unaffected; *p = 0.03 vs mild) cytokines in severe COVID-19 patients (Fig. 1a). Strati cation of patients according to presence or absence of brain fog revealed a signi cant increase in serum concentrations of TNF (**p = 0.003), IL6 (***p < 0.001), IL8 (**p = 0.008) and S100β (*p = 0.010) in brain fog patients after controlling for age, sex and severity of infection (Fig. 1c). There was a signi cant increase in serum concentrations of TNF (***p < 0.001), IL6 (***p < 0.001) and IL8 (*p = 0.038) in patients requiring supplemental oxygen (Figure S1a) while there was a signi cant increase in TNF (**p = 0.005), IL6 (***p < 0.001) and IL8 (*p = 0.046) in patients requiring hospitalisation (Figure S1b). Spearman’s partial correlation analysis revealed a signi cant correlation between WHO Severity of COVID-19 and serum concentrations of TNF, IL6 and IL8 (r = 0.367, ***p = 0.002; r = 0.425, ***p < 0.001; and r = 0.231, *p = 0.047 respectively after adjusting for age and sex) (Figure S2a-c). Of the 76 patients, 36 had a second blood sample drawn owing to deterioration of clinical symptoms so serum concentrations of all analytes were assessed between timepoint 1 and 2 (T1 and T2) to monitor disease progression. There was a signi cant increase in serum concentrations of IL8 (***p < 0.001 Wilcoxon signed-rank test) between T1 and T2 (Figure S3). Bbb Dysfunction Is Associated With Long COVID-induced Cognitive Impairment Given the signi cantly increased serum concentrations of S100β our data indicated that active/acute SARS-CoV-2 infection is associated with BBB dysfunction in individuals with neurological impairment. To directly visualise BBB function, we recruited 10 recovered and 22 Long COVID patients who were Page 5/25 diagnosed with COVID-19 during the rst outbreak of disease in Ireland in April 2020 (Fig. 2a and Table 2). All participants were recruited from St James Hospital Dublin and were PCR con rmed cases of COVID-19. None of the patients in this cohort had received a vaccine. We used a quick smell identi cation test (Q-SIT) based method to determine objective anosmia status in participants and determined a strong correlation of reported anosmia status and Q-SIT score, providing an excellent readout of the utility of objective anosmia measurement in prolonged anosmia after COVID-19. Participants were grouped according to the presence or absence of brain fog (brain fog (-) or brain fog (+)). We hypothesised that COVID-19 associated cognitive impairment may be a strong predictor of BBB disruption in COVID-19 patients. Brain fog patients reported a mean symptom duration of 222.75 days while non-brain fog participants had a mean symptom duration of 170.55 days. Participants were scanned an average of 146 days following SARS-CoV-2 infection (Table 2). 16 (50%) participants reported anosmia which was con rmed by Q-SIT testing (average score 1/3; 159 +/- 88 days duration) at the time of scanning. 6 participants (all brain fog) showed mild-moderate cognitive impairment on the MOCA test (score 18–25) along with de cits in recall, executive function and word nding (Table 2). While standard diagnostic MRI scans showed no pathological ndings in any participant, DCE-MRI imaging revealed signi cantly increased whole brain leakage in COVID-19 patients with brain fog (Fig. 2bd) with increased percentage of brain volume with leaky blood vessels in the brain fog cohort compared to the cohort without brain fog (***p < 0.001). Stratifying the cohort into recovered, long COVID without brain fog and long COVID with brain fog revealed signi cantly increased BBB permeability in the brain fog cohort compared to recovered (*p = 0.014) and long COVID without brain fog (***p < 0.001). Region of interest analysis identi ed signi cantly increased leakage in the right and left temporal lobes (p***<0.001 and p = 0.005 respectively) and right and left frontal cortex (**p = 0.005 and **p = 0.004 respectively) (Fig. 2e-i). Stratifying the groups according to recovered, long COVID or brain fog revealed signi cantly increased BBB permeability in the brain fog group only in the right (**p = 0.007 vs recovered; **p = 0.008 vs long COVID) and left (*p = 0.035 vs recovered; p = 0.051 vs long COVID) temporal lobe and right (*p = 0.015 vs long COVID) and left (*p = 0.05 vs recovered; *p = 0.025 vs long COVID) frontal cortex (Figure S4a-e). There was no association between BBB permeability and anosmia status, duration of anosmia, QSIT or MOCA scores (Figure S5), however regional BBB permeability in the right (r = 0.546, **p = 0.002) and left (r = 0.532, **p = 0.002) temporal lobes correlated with the duration of anosmia. Long COVID Associated Brain Fog Induces Structural Changes In The Brain To explore if there were structural brain changes accompanying increased BBB permeability in our cohorts, we conducted volume and thickness measurements on recovered, long COVID and 60 agematched healthy controls from the publicly available IXI dataset (Table 2) and examined global brain volume, cerebrospinal uid (CSF) volume and right and left volumes of cerebral and cerebellar white and grey matter and brainstem, hippocampus, and amygdala. Comparing individuals with prior COVID infection to unaffected revealed volumetric de cits predominantly in the frontal and temporal lobes and Page 6/25 increases in the lateral ventricles and occipital lobes (Fig. 3a) while groupwise comparisons of macrostructures revealed decreased global brain volume in brain fog patients (**p = 0.001) along with signi cantly reduced cerebral white matter volume in both hemispheres in the recovered (***p < 0.001) and brain fog (***p < 0.001) cohorts along with reduced cerebellar white matter volume in recovered (***p < 0.001, right; **p = 0.006, left), long COVID (**p = 0.01, right; *p = 0.049, left) and brain fog (***p < 0.001, right and left) cohorts (Fig. 3b-e and Table 3). There was signi cantly increased CSF volume in the brain fog cohort only (**p = 0.005) (Fig. 3f and Table 3). Cortical thinning was also evident predominantly in the temporal and frontal lobes when looking at all patients with prior SARS-CoV-2 infection compared to unaffected controls (Fig. 3g). When comparing groups, there was reduced thickness in the fontal pole in recovered (**p = 003), long COVID (**p = 0.002) and brain fog (***p < 0.001); superior frontal gyrus in long COVID (**p = 0.003) and brain fog (**p = 0.002); middle temporal gyrus in brain fog only (*p = 0.016); and superior temporal gyrus (***p < 0.001) in brain fog only. Spearman partial correlations revealed signi cant negative associations between the number of BBB disrupted voxels with global brain volume (r=-0.528, **p = 0.002), right (r=-0.424, *p = 0.022) and left (r=-0.466, *p = 0.011) white matter volume, and right (r=-0.503, **p = 0.005) and left (r=-0.493, **p = 0.007) cerebral volume and was positively associated with CSF volume (r = 0.532, **p = 0.002) (Fig. 4a-g). Immunovascular Dysregulation In Long COVID Blood Samples Finally, we analysed blood-based biomarkers of neuroin ammation and BBB dysfunction in the long COVID cohort. We selected markers previously associated with BBB dysfunction, neuroin ammation and chronic fatigue syndrome including S100β, GFAP, TGFβ, IL6, IL8 and CCL2. Individuals with brain fog had signi cantly increased GFAP (*p = 0.022), TGFβ (**p = 0.004) and IL8 (*p = 0.0427) compared to unaffected, recovered, and long COVID without brain fog. Levels of phosphorylated TAU, sICAM1 and S100β were comparable between groups (Fig. 5a-e). This differs from the blood analysis of the patients with acute COVID and suggests a temporal change in the utility of these markers for prognosis and clinical management. Next, we performed Spearman partial correlation analysis adjusting for age and sex to identify any associations between neuroin ammatory/BBB dysfunction markers with BBB permeability assessed by DCE-MRI. Levels of TGFβ were signi cantly associated with the percentage of brain volume displaying leaky blood vessels (r = 0.501, **p = 0.008) as well as with global brain volume (r=-0.394, *p = 0.042), CSF volume (r = 0.438, *p = 0.020), brainstem volume (r=-0.656, p < 0.001) and amygdala volume (r=-0.402, *p = 0.038) (Fig. 5f-j and Figure S6). White Blood Cells From COVID Patients Activate Brain Endothelial Cells Given the prevalence of circulating markers indicative of BBB dysfunction and immune cell activation, we examined gene expression changes in PBMCs isolated from long COVID patients which revealed increased expression of interferon signalling components and in ammatory markers independent of neurological impairment indicating sustained in ammatory responses in all groups including recovered Page 7/25 individuals (Fig. 6a-f). We next examined immunovascular interactions in PBMCs isolated from patients with COVID and found increased adhesion of PBMCs to human brain endothelial cells in the long COVID group compared to unaffected (***p < 0.001) which was heightened in the presence of TNF (**p = 0.0031 vs control) (Fig. 6g, h). Furthermore, exposure of human brain endothelial cells to 10% serum from recovered, and long COVID groups resulted in the upregulation of ICAM1 (**p = 0.0081), VCAM1 (*p = 0.0127) and TNF (**p = 0.004) transcripts compared to unaffected sera (Fig. 6i-l). Exposure of human brain endothelial cells to S1 spike protein had similar effects with dose-dependent increases in TNF (*p = 0.045), TGFβ (*p = 0.017), ICAM1 (p = 0.057) and VCAM1 (***p < 0.001) (Figure S7) following 72 hours treatment with 0-400 nM S1 spike protein. Discussion Overall, our results suggest that long COVID “brain fog” is associated with impairment of BBB function and increased expression of systemic in ammatory and BBB dysfunction markers including GFAP, TGFβ and IL8. BBB dysfunction was unique to the brain fog cohort in our study with sustained dysfunction up to one year following recovery from active infection with dysfunction evident in multiple neuroanatomical regions including the temporal lobes and frontal cortex. We found no evidence of BBB dysfunction in patients with anosmia without accompanying brain fog suggesting that cerebrovascular dysfunction in the olfactory bulb does not clearly drive this condition. It has been shown instead that accumulation of in ltrating T-cells expressing interferon-gamma results in reduction of olfactory sensory neurons relative to support cells in patients with long COVID associated anosmia39. It is possible that this sustained in ammatory response in the olfactory epithelium results in cerebrovascular damage in the olfactory bulbs and higher resolution MRI could help to tease out these changes. We did observe a signi cant correlation between BBB disruption in the temporal lobes with the duration of anosmia. The temporal lobe contains important regions that form part of the primary olfactory cortex including the piriform cortex, amygdala and entorhinal cortex with direct connections from and to the olfactory bulb encompassing regions of the piriform cortex, parahippocampal gyrus and entorhinal cortex along with orbitofrontal areas40–42. The hippocampus is also important for odour recognition memory and it is possible that BBB dysfunction in these regions contributes to anosmia or hyposmia41. In the brain fog cohort, we found evidence of reduced global brain volume along with reductions in white matter in cortical and cerebellar tissue that was also apparent in individuals who had recovered from infection suggesting that these changes do not drive the fatigue and cognitive slowing associated with brain fog in this condition. Other groups have also found changes on neuroimaging following mild infection. Initial systemic neuropathological changes in patients with COVID-19 appeared to be mild, with marked brainstem neuroin ammation the most common nding43. In a three-month follow up MRI study of COVID-19 patients, higher grey matter volumes were found in several cerebral territories, including the olfactory cortices, hippocampi, and cingulate gyri which may be a marker of acute or sub-acute in ammation43. A recent large cohort study revealed longitudinal changes in brain volume and cortical thinning following mild SARS-CoV-2 infection42. Neuroimaging has also been used to detect other Page 8/25 cerebrovascular changes in the brain following SARS-CoV-2 infection. Abnormalities detected include cerebral microbleeds, hypometabolism and cerebral hypoperfusion in several brain regions29,44−47. BBB dysfunction was evident in individuals suffering acute neurological impairment during the active phase of SARS-CoV-2 infection with increased serum levels of the astrocytic protein S100β together with increased expression of TNF and IL6 after adjusting for age, sex, and severity of infection. This suggests that a heightened in ammatory response in this neurological cohort may drive BBB dysfunction. Serum levels of S100β have previously been found elevated in several neurological disorders including epilepsy, traumatic brain injury and schizophrenia48–50. However, longitudinal studies will be required to determine if BBB disrupted acute COVID patients are more likely to develop long COVID-associated brain fog. We also found increased expression of IL8 in individuals with deteriorating clinical symptoms. In the long COVID cohort, levels of IL8, GFAP and TGFβ were elevated in the brain fog group only. GFAP is a marker of cerebrovascular damage and has previously been shown to be elevated following repetitive head trauma, re ecting BBB disruption, as seen in contact sport athletes24,51. Interestingly, TGFβ was strongly associated with the number of BBB disrupted blood vessels along with global brain volume and white matter volume changes. TGFβ has been implicated in the pathogenesis of chronic fatigue syndrome, a condition noted for its overlap of brain fog with COVID 52–54. Several studies have examined BBB function in animal models of SARS-CoV-2 infection and in postmortem tissue to understand the impact of acute infection on BBB integrity. The spike protein of SARSCoV-2 was shown to cross the BBB while direct intrahippocampal injection induced cognitive de cits and anxiety-like behaviour in mice32,55. In samples from patients who died during the initial wave of COVID in 2020, Lee et al. showed brinogen extravasation and evidence of overactivation of the coagulation system19,20 while Wenzel et al. found string vessels, pathological blood vessels without endothelial cells25. A few studies have also examined changes in systemic markers in convalescent COVID patients and pinpoint to strong upregulation of biomarkers of in ammation and innate immunity and downregulation of platelet-related pathways56. Persistent immune activation has also been reported in individuals with long COVID up to 8 months post infection57. Long COVID is a signi cant burden in many patients post recovery from COVID-19. Patients describe fatigue, memory loss, dyspnoea as some of the key symptoms of long COVID, while another subset of patients describe “brain fog” like that commonly reported in post-concussive syndrome and chronic fatigue syndrome58,59. In this study, we assessed BBB integrity in a series of patients who had recovered from infection but had symptoms persisting up to 1 year following infection. Our data suggest that BBB disruption is strongly associated with long COVID-associated cognitive impairment with regional differences in BBB integrity in long COVID patients displaying brain fog. Our biomarker analysis in acute COVID patients suggests that a subset of infected individuals with acute cognitive impairment have a disrupted BBB as determined by serum presence of the astrocytic protein S100β. This study is the rst to focus on long COVID patients with or without neurological impairment and compare them to individuals Page 9/25 who recovered from a previous SARS-CoV-2 infection. Individuals with brain fog have persistent BBB dysfunction which could be detected by DCE-MRI and plasma assessment of circulating biomarkers. This provides the rst objective evidence for a link between BBB disruption and cognitive impairment within a cohort of patients with long COVID. Further longitudinal studies will be required to examine changes in BBB permeability over time, however, targeted regulation of BBB integrity could now potentially be considered for the treatment of patients with brain fog associated with long COVID. Methods Study participants Participants included recovered COVID-19 patients, male or female aged 18 and above with and without neurological symptoms. Participants with long COVID, with symptom persistence over 12 weeks from infection were also recruited. Candidates were excluded if they had a history of a neurological disorder that may better explain the results of the study such as epilepsy, brain trauma, neuropsychiatric disorder, or mild cognitive impairment. Suitable candidates proceeded to assessment with DCE-MRI imaging, Q-SIT olfactory testing and a review of pulmonary imaging and haematological parameters at the time of COVID-19 diagnosis. The Joint Research Ethics Committee (JREC) of St James’s and Tallaght Hospital’s approved the study and informed consent was obtained from all participants. Research was performed according to the principles of the Declaration of Helsinki. The legal basis for the Study was consent according to GDPR principles. Olfactory Testing Participants olfactory function was assessed using the quick smell identi cation test (Q-SIT). The Q-SIT is a standardised and validated three item odour identi cation screen60. A score of 2 or more is a normal test and cut-off score of 1 or less is an abnormal test for anosmia. Q-SIT has displayed high positive and negative predictive value in detecting olfactory dysfunction in COVID-19 patients. In addition, the Q-SIT is a tear-off card test is disposable so there is no concern about contamination and transmission of disease form COVID-19 patients61. Dynamic Contrast-enhanced Magnetic Resonance Imaging BBB permeability maps were created using the slope of contrast agent concentration in each voxel over time, calculated by a linear t model as previously described62,63. Thresholds of high permeability was de ned by the 95th percentile of all slopes in a previously examined control group. Imaging was performed with a 3T Philips Achieva scanner. Sequences included a T1- weighted anatomical scan (3D gradient echo, TE/TR = 3/6.7 ms, acquisition matrix 268x266, voxel size: 0.83x0.83x.9mm), T2-weighted imaging (TE/TR = 80/3000 ms, voxel size: 0.45x0.45x.4mm), FLAIR (TE/TR = 125/11000 ms, voxel size:0.45x0.45x4mm). For the calculation of pre-contrast longitudinal relaxation time (T10), the variable Page 10/25 ip angle (VFA) method was used (3D T1w-FFE, TE/TR = 2.78/5.67 ms, acquisition matrix: 240x184, voxel size: 0.68x0.68x5 mm, ip angles: 2, 10, 16 and 24°). Dynamic contrast enhanced (DCE) sequence was then acquired (Axial, 3D T1w-FFE, TE/TR = 2.78/5.6 ms, acquisition matrix: 240x184, voxel size: 0.68x0.68x5 mm, ip angle: 6°, Tt = 6.5 Sec, temporal repetitions: 61, total scan length: 22.6 minutes). An intravenous bolus injection of the contrast agent gadobenate dimeglumine (Gd-BOPTA, Bracco Diagnostics Inc., Milan, Italy) was administered using an automatic injector after the rst three DCE repetitions. To control for interindividual variabilities due to heart rate, blood ow or rate of contrast injection, each voxel’s leakage rate was normalised to that of the superior sagittal sinus. The percent of suprathreshold voxels was used as a measure re ecting global BBB leakage. Volumetric And Thickness Measurements T1-weighted anatomical images were uploaded to the VolBrain online brain volumetry software (https://volbrain.upv.es)64, and analysed with vol2brain 1.0 which is an online pipeline that registers images to the Montreal Neurological Institute (MNI) space, and reports the volumes of expert-labelled anatomical structures as percentage of total intracranial volume. We analysed the volume of the right/left cerebral and cerebellar grey/white matter, frontal, temporal, parietal and occipital and CSF along with thickness of the frontal, parietal, occipital and temporal lobes. All volume data was normalised to total intracranial volume (TIV) which is the sum of grey matter, white matter and CSF. Volumes were expressed as a percentage of TIV. 60 age and sex matched healthy control scans were randomly selected from the IXI dataset (https://brain-development.org/ixi-dataset/) which represents 10% of the entire dataset. All scans were performed on the same Philips 3T system at Hammersmith Hospital. Volumetric maps for comparisons between COVID positive and negative groups were generated in xjview following automatic brain segmentation in the CAT12 toolbox with default parameters and subsequent smoothing with an 8 mm kernel. Thickness maps for comparisons between COVID positive and negative groups were generated in CAT12 toolbox run in SPM12 in MATLAB R2021a following brain segmentation as above and smoothing with a 15 mm kernel. Two-sample t-test was used for statistical analysis with age, sex and TIV as covariates. Sample Collection Blood samples were collected into serum separator tubes and EDTA-coated tubes for serum and PBMC isolation respectively. Serum was separated by centrifugation at 2000 rpm for 10 min at room temperature. PBMCs were separated via layering of blood samples diluted twofold in PBS (ThermoFisher, #14190) over Lymphoprep™ density gradient medium (Stemcell Technologies, #07851) followed by centrifugation at 400 rcf for 25 min at room temperature at 0 break and 0 acceleration. Plasma was collected and PBMC layer was collected into a new 50 ml falcon tube, resuspended to 50 ml with PBS and centrifuged at 2000 rpm for 5 min at room temperature. PBMCs were resuspended in 50 ml PBS and centrifuged at 1000 rpm for 10 min at room temperature. PBMCs were resuspended to 2 x 106 cells/ml in Page 11/25 RPMI 1640 media with L-glutamine (Lonza, #LZBE12-702F) supplemented with 50% fetal bovine serum (Merck, #F7524) and 10% DMSO (Merck, #D5879) and frozen at -800C overnight before being moved to liquid nitrogen. Luminex Assay A 10-plex Luminex assay (R&D Systems, #LXSAHM-10) was used for cytokine pro ling. Serum samples were diluted twofold in sample dilution buffer. Then, 50 µl of sample or standard were pipetted in duplicate into each wall of an assay 96 well plate. 50 µl of diluted Microparticle Cocktail were added to each well, the plate was covered and incubated for 2 hours at room temperature on a shaker at 300 rpm. Wells were washed 3 times with Wash Buffer before addition of 50 µl of diluted Biotin-Antibody Cocktail. The plate was covered and incubated for 1 hour at room temperature on a shaker at 300 rpm. Wells were washed as above before addition of 50 µl of diluted Streptavidin-PE to each well. The plate was covered and incubated for 30 min at room temperature on a shaker at 300 rpm. Wells were washed as above before microparticles were resuspended in 100 µl of Wash Buffer. The plate was incubated for 2 min at room temperature on a shaker at 300 rpm and was read on a MAGPIX plate reader (Luminex). Dot Blot Plasma samples were spotted (2 µl) onto 0.2 µm nitrocellulose membrane (Whatman, #10401391) and allowed to dry for 30 minutes. Membranes were blocked in 5% bovine serum albumin (BSA, Merck, #A7906) in phosphate buffered saline supplemented with 0.1% Triton X-100 (PBST) for 1 hour at room temperature. Membranes were incubated overnight in primary antibody in blocking buffer. Membranes were washed three times for ve minutes each in PBST, followed by incubation in secondary HRPconjugated antibodies. Membranes were washed three times for ve minutes each in PBST and incubated with strong ECL substrate (Advansta, #K-12045-D50) for 2 min before being developed on a CDigit (LiCor). Protein bands were quanti ed in ImageJ (National Institutes of Health, Rockville, MD, USA). Primary antibodies used were mouse anti-GFAP (1/500, Merck, #G3893), rabbit anti-TGFβ (1/500, Abcam, #ab92486) and mouse anti-Phospho-Tau (1/500, Fisher Scienti c, #10599853). Secondary antibodies used were anti-mouse HRP (1/5000, Merck, #A4416) and anti-rabbit HRP (1/5000, Merck, #A6154). RT-qPCR RNA was isolated from PBMCs and the human brain endothelial cell line hCMEC/d3 (Millipore, #SCC066) with the Omega RNA isolation kit (Omega, #R6834-02) according to manufacturer’s instructions. cDNA was reverse transcribed from 500 ng RNA with the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, # 4368814). Transcript levels were quanti ed on a StepOne Plus instrument (Applied Biosystems) with FastStart Universal SYBR Green Master (ROX) master mix (Roche, #04913914001). RTPCR was performed with the following conditions: 950C x 2 min, (950C x 5s, 600C x 30s) x40, 950C x 15s, Page 12/25 600C x 1 min, 950C x 15s, 600C x 15s. Primer sequences for RT-PCR experiments are supplied in Supplementary Table 4. Relative gene expression levels were quanti ed using the comparative CT method (ΔΔCT). Expression levels of target genes were normalised to β-actin. Adhesion Assay hCMEC/d3 cells were cultured in EGM2-MV growth medium (Lonza, #CC-3202) and were stimulated with 10 ng/ml recombinant human TNF-a (Peprotech, #300-01A) for 4 hours and incubated with 1x105 MitoTracker Orange (ThermoFisher, # M7510) labelled PBMCs for 1 hour at 37oC. Cells were washed three times in PBS to remove unbound PBMCs and xed in 4% formaldehyde (Merck, #F1635) for 10 min at room temperature. The number of adhered PBMCs was counted with the ImageJ cell counter plugin. Images were imported and converted to 8-bit and thresholded. Noise was removed with the despeckle function, and the images were converted to binary. The cell counter plugin was then used for counting adhered PBMCs. Counts were averaged from 5 images per treatment. Serum And Spike Protein Treatment hCMEC/d3 cells were seeded in 12-well plates at 2x105 cells/well and grown to con uence. Media was replaced with media containing 10% serum from COVID and unaffected controls and incubated for up to 72 hours followed by RNA isolation. hCMEC/d3 cells were cultured in12-well plates as described above and stimulated with 4, 40 and 400 nM Recombinant SARS-CoV-2 Spike S1 subunit protein (R&D Systems, #BT10569) for up to 72 hours and RNA was isolated as described above. Ethical Approval Informed consent was obtained from each participant. All ethical approvals were in place prior to the initiation of studies on human subjects. All experiments conformed to the principles set out in the WMA Declaration of Helsinki and the Department of Health and Human Services Belmont Report. The St James’ Hospital ethics committee approved these studies. Statistical analysis IBM SPSS Statistics V.28 (IBM Corporation, Armonk, New York, USA) and GraphPad Prism V.9.00 (GraphPad Software, La Jolla California, USA) were used for statistical analysis. Prism 9 was used to generate charts. Categorical variables were compared between groups with x2 tests. Normal and nonnormal data were analysed with Mann-Whitney tests or ANOVA followed by Tukey or Kruskal-Wallis test respectively with age and sex adjusted p-values reported. A multivariate general linear model with age, sex and TIV as covariates was used for volumetric MRI analysis. Correlations were assessed with Pearson or Spearman rho correlation tests using partial correlations to control for age, sex and TIV. For repeated blood samples, matched samples were compared with Wilcoxon signed-rank test. To control for multiple comparisons in brain region MRI analysis and correlation analysis, false discovery rate was Page 13/25 applied using the Benjamini-Hochberg correction. A p-value <0.05 was considered statistically signi cant. All quantitative PCR, ELISA and adhesion assays were performed in duplicate. Declarations Acknowledgements This work was supported by grants from Science Foundation Ireland (SFI), (12/YI/B2614 and 11/PI/1080), The Irish Research Council (IRC) and by a research grant from SFI under grant number 16/RC/3948 and co‐funded under the European Regional Development fund by FutureNeuro industry partners. The Campbell lab is also supported by a European Research Council (ERC) grant, “Retina‐ Rhythm” (864522). We thank Nollaig Bourke and Matt McElheron for assistance with the Luminex assays. Author contributions CG: Designed research, performed experiments, collected, and analysed data, and wrote the manuscript. RC: Patient recruitment, assessment and data collection. EOK: Sample preparation. DB, AL, LZ: Patient recruitment and assessment. EC: Data maintenance and statistical analysis. CNC: Sample collection/recruitment. NC: Sample collection/recruitment. CPD: Conceived project, designed experiments and edited manuscript. MC: Conceived project, designed experiments and edited manuscript. Competing interests The authors declare no competing interests. References 1. Zhu, N. et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. N Engl J Med 382, 727-733 (2020). https://doi.org:10.1056/NEJMoa2001017 2. Wu, Z. & McGoogan, J. M. 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Eur Arch Otorhinolaryngol 277, 2251-2261 (2020). https://doi.org:10.1007/s00405-020-05965-1 2. O'Keeffe, E. et al. Dynamic Blood-Brain Barrier Regulation in Mild Traumatic Brain Injury. Journal of neurotrauma 37, 347-356 (2020). https://doi.org:10.1089/neu.2019.6483 3. Weissberg, I. et al. Imaging Blood-Brain Barrier Dysfunction in Football Players. JAMA Neurology 71, 1453-1455 (2014). https://doi.org:10.1001/jamaneurol.2014.2682 Page 18/25 4. Manjón, J. V. & Coupé, P. volBrain: An Online MRI Brain Volumetry System. Frontiers in Neuroinformatics 10 (2016). https://doi.org:10.3389/fninf.2016.00030 Tables Tables 1 to 4 are available in the Supplementary Files section. Figures Page 19/25 Figure 1 In ammation and blood-brain barrier (BBB) permeability in acute COVID-19 infected cases. a) TNF, IL6, IL8, S100β and CCL2 serum concentrations in unaffected, mild, moderate, and severe SARS-CoV-2 infected patients. b) TNF, IL6, IL8, S100β and CCL2 serum concentrations in neurological SARS-CoV-2 infected patients. Data represent means with 95% con dence intervals; each datapoint represents one Page 20/25 patient. Data analysed by MANCOVA with age, sex and WHO severity as covariates. *p<0.05; **p<0.01; ***p<0.001. Figure 2 BBB disruption in Long COVID-associated cognitive impairment. a) Patient cohort for dynamic contrastenhanced magnetic resonance imaging (DCE-MRI). b) Averaged BBB permeability maps in non-brain fog and brain fog cases. c) There were signi cantly increased percentage of brain volume with leaky blood vessels in the brain fog cohort compared to recovered and non-brain fog cases. d) Frequency distribution of the percentage of BBB disrupted voxels in the non-brain fog and brain fog cases. e) Representative BBB permeability maps at the level of the temporal lobe, frontal lobe and occipital lobe showing enhanced BBB permeability in brain fog cases. f-i) Quanti cation of regional BBB permeability in the right and left temporal lobe and right and left frontal cortex. Data represent means ± s.e.m.; each datapoint represents one patient. Data analysed by ANCOVA with age and sex as covariates. *p<0.05; **p<0.01; ***p<0.001. Page 21/25 Figure 3 COVID-associated brain changes. a) Voxel-based morphometry map indicating brain regions with reduced volume in patients with prior SARS-CoV-2 infection. b-e) Group-wise comparison of brain volume in unaffected, recovered, long COVID and brain fog groups. f) Surface-based morphometry map indicating brain regions with reduced cortical thickness in patients with prior SARS-CoV-2 infection. g-j) Group-wise comparison of cortical thinning in unaffected, recovered, long COVID and brain fog groups. Maps generated with CAT12 toolbox in SPM12 running on MATLAB 2021a. Groups compared with unpaired t-test with family-wise error <0.05, adjusted for age, sex and TIV. Volumetric and thickness region of interest measurements were obtained from VolBrain. Groups were compared with ANCOVA adjusted for age and sex. Data represents means ± s.e.m.; each datapoint represents one patient. *p<0.05, **p<0.01, ***p<0.001. Page 22/25 Figure 4 BBB permeability is associated with structural brain changes. a-f) Spearman partial correlation between the percentage of BBB disrupted voxels and white matter volume and global brain volume. g) Heat-map of Spearman correlations between BBB permeability and global brain volume. Each datapoint represents one patient. Spearman partial correlation analysis for all panels adjusted for age, sex and TIV. *p<0.05; **p<0.01. Page 23/25 Figure 5 Plasma TGFβ is associated with increased BBB permeability. a-e) Serum and plasma analysis of GFAP, TGFβ, P-TAU, IL8 and CCL2 in recovered, non-brain fog and brain fog cohort. f) Spearman partial correlations between analyte levels and BBB permeability and global brain volume measurements. g-i) Spearman correlation between levels of TGFβ and percentage BBB disruption, percentage CSF volume, brainstem volume and amygdala volume. Data represent means ± s.e.m.; each datapoint represents one patient. Kruskal Wallis test for a-e, Spearman partial correlation analysis controlling for age, sex and TIV for f-j. *p<0.05; **p<0.01. Page 24/25 Figure 6 Immunovascular dysfunction in long COVID blood samples. a-f) Gene expression changes in unaffected and long COVID PBMCs. g-h) PBMC adhesion assay on human brain endothelial cells (hCMEC/d3) in the presence or absence of 10 ng/ml TNF. i-l) Gene expression changes in hCMEC/d3 cells exposed to control or long COVID serum. Data represent means ± s.e.m.; each datapoint represents one patient. Unpaired ttest for gene expression data, two-way ANOVA for adhesion assay. *p<0.05; **p<0.01; ***p<0.001. Supplementary Files This is a list of supplementary les associated with this preprint. Click to download. Tables.pdf SupplementaryFigures.pdf Page 25/25