SARS-CoV-2 is associated with changes in brain structure in UK Biobank

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

There is strong evidence of brain-related abnormalities in COVID-19 ^{1–
13}. However, it remains unknown whether the impact of SARS-CoV-2 infection can be detected in milder cases, and whether this can reveal possible mechanisms contributing to brain pathology. Here we investigated brain changes in 785 participants of UK Biobank (aged 51–81 years) who were imaged twice using magnetic resonance imaging, including 401 cases who tested positive for infection with SARS-CoV-2 between their two scans—with 141 days on average separating their diagnosis and the second scan—as well as 384 controls. The availability of pre-infection imaging data reduces the likelihood of pre-existing risk factors being misinterpreted as disease effects. We identified significant longitudinal effects when comparing the two groups, including (1) a greater reduction in grey matter thickness and tissue contrast in the orbitofrontal cortex and parahippocampal gyrus; (2) greater changes in markers of tissue damage in regions that are functionally connected to the primary olfactory cortex; and (3) a greater reduction in global brain size in the SARS-CoV-2 cases. The participants who were infected with SARS-CoV-2 also showed on average a greater cognitive decline between the two time points. Importantly, these imaging and cognitive longitudinal effects were still observed after excluding the 15 patients who had been hospitalised. These mainly limbic brain imaging results may be the in vivo hallmarks of a degenerative spread of the disease through olfactory pathways, of neuroinflammatory events, or of the loss of sensory input due to anosmia. Whether this deleterious effect can be partially reversed, or whether these effects will persist in the long term, remains to be investigated with additional follow-up.

Abstract

After infection with SARS-CoV-2, individuals show a greater reduction in grey matter thickness and tissue contrast in the orbitofrontal cortex and parahippocampal gyrus; greater changes in markers of tissue damage in regions that are functionally connected to the primary olfactory cortex; and a greater reduction in global brain size.

Related collections

Most cited references 79

Record: found
Abstract: found
Article: not found

Neurologic Features in Severe SARS-CoV-2 Infection

Julie Helms, Stéphane Kremer, Hamid Merdji … (2020)

To the Editor: We report the neurologic features in an observational series of 58 of 64 consecutive patients admitted to the hospital because of acute respiratory distress syndrome (ARDS) due to Covid-19. The patients received similar evaluations by intensivists in two intensive care units (ICUs) in Strasbourg, France, between March 3 and April 3, 2020. Six patients were excluded because of paralytic neuromuscular blockade when neurologic data were collected or because they had died without a neurologic examination having been performed. In all 58 patients, reverse-transcriptase–polymerase-chain-reaction (RT-PCR) assays of nasopharyngeal samples were positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The median age of the patients was 63 years, and the median Simplified Acute Physiology Score II at the time of neurologic examination was 52 (interquartile range, 37 to 65, on a scale ranging from 0 to 163, with higher scores indicating greater severity of illness). Seven patients had had previous neurologic disorders, including transient ischemic attack, partial epilepsy, and mild cognitive impairment. The neurologic findings were recorded in 8 of the 58 patients (14%) on admission to the ICU (before treatment) and in 39 patients (67%) when sedation and a neuromuscular blocker were withheld. Agitation was present in 40 patients (69%) when neuromuscular blockade was discontinued (Table 1). A total of 26 of 40 patients were noted to have confusion according to the Confusion Assessment Method for the ICU; those patients could be evaluated when they were responsive (i.e., they had a score of −1 to 1 on the Richmond Agitation and Sedation Scale, on a scale of −5 [unresponsive] to +4 [combative]). Diffuse corticospinal tract signs with enhanced tendon reflexes, ankle clonus, and bilateral extensor plantar reflexes were present in 39 patients (67%). Of the patients who had been discharged at the time of this writing, 15 of 45 (33%) had had a dysexecutive syndrome consisting of inattention, disorientation, or poorly organized movements in response to command. Magnetic resonance imaging (MRI) of the brain was performed in 13 patients (Figs. S1 through S3 in the Supplementary Appendix, available with the full text of this letter at NEJM.org). Although these patients did not have focal signs that suggested stroke, they underwent MRI because of unexplained encephalopathic features. Enhancement in leptomeningeal spaces was noted in 8 patients, and bilateral frontotemporal hypoperfusion was noted in all 11 patients who underwent perfusion imaging. Two asymptomatic patients each had a small acute ischemic stroke with focal hyperintensity on diffusion-weighted imaging and an overlapping decreased apparent diffusion coefficient, and 1 patient had a subacute ischemic stroke with superimposed increased diffusion-weighted imaging and apparent diffusion coefficient signals. In the 8 patients who underwent electroencephalography, only nonspecific changes were detected; 1 of the 8 patients had diffuse bifrontal slowing consistent with encephalopathy. Examination of cerebrospinal fluid (CSF) samples obtained from 7 patients showed no cells; in 2 patients, oligoclonal bands were present with an identical electrophoretic pattern in serum, and protein and IgG levels were elevated in 1 patient. RT-PCR assays of the CSF samples were negative for SARS-CoV-2 in all 7 patients. In this consecutive series of patients, ARDS due to SARS-CoV-2 infection was associated with encephalopathy, prominent agitation and confusion, and corticospinal tract signs. Two of 13 patients who underwent brain MRI had single acute ischemic strokes. Data are lacking to determine which of these features were due to critical illness–related encephalopathy, cytokines, or the effect or withdrawal of medication, and which features were specific to SARS-CoV-2 infection.

0 comments Cited 1277 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Multiorgan and Renal Tropism of SARS-CoV-2

Victor G. Puelles, Marc Lütgehetmann, Maja T Lindenmeyer … (2020)

To the Editor: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) preferentially infects cells in the respiratory tract, 1,2 but its direct affinity for organs other than the lungs remains poorly defined. Here, we present data from an autopsy series of 27 patients (see the clinical data in Table S1 in the Supplementary Appendix, available with the full text of this letter at NEJM.org) that show that SARS-CoV-2 can be detected in multiple organs, including the lungs, pharynx, heart, liver, brain, and kidneys. We first quantified the SARS-CoV-2 viral load in autopsy tissue samples obtained from 22 patients who had died from Covid-19. Seventeen patients (77%) had more than two coexisting conditions (Figure 1A), and a greater number of coexisting conditions was associated with SARS-CoV-2 tropism for the kidneys (Table S2), even in patients without a history of chronic kidney disease (Table S3). The highest levels of SARS-CoV-2 copies per cell were detected in the respiratory tract, and lower levels were detected the kidneys, liver, heart, brain, and blood (Figure 1B). These findings indicate a broad organotropism of SARS-CoV-2. Since the kidneys are among the most common targets of SARS-CoV-2, we performed in silico analysis of publicly available data sets of single-cell RNA sequencing. This analysis revealed that RNA for angiotensin-converting enzyme 2 (ACE2), transmembrane serine protease 2 (TMPRSS2), and cathepsin L (CTSL) — RNA of genes that are considered to facilitate SARS-CoV-2 infection 3 — is enriched in multiple kidney-cell types from fetal development through adulthood (Fig. S1). This enrichment may facilitate SARS-CoV-2–associated kidney injury, as previously suggested. 4 We also quantified the SARS-CoV-2 viral load in precisely defined kidney compartments obtained with the use of tissue microdissection from 6 patients who underwent autopsy (1 patient who was included in the previously mentioned 22 patients as an internal negative control, plus 5 additional patients). Three of these 6 patients had a detectable SARS-CoV-2 viral load in all kidney compartments examined, with preferential targeting of glomerular cells (Fig. S2). We also detected viral RNA and protein with high spatial resolution using in situ hybridization and indirect immunofluorescence with confocal microscopy (Figure 1C). Data on additional controls are provided in Figures S3 and S4. On the basis of these findings, renal tropism is a potential explanation of commonly reported new clinical signs of kidney injury in patients with Covid-19, 5 even in patients with SARS-CoV-2 infection who are not critically ill. Our results indicate that SARS-CoV-2 has an organotropism beyond the respiratory tract, including the kidneys, liver, heart, and brain, and we speculate that organotropism influences the course of Covid-19 disease and, possibly, aggravates preexisting conditions.

0 comments Cited 964 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: a retrospective cohort study using electronic health records

Maxime Taquet, John R Geddes, Masud Husain … (2021)

Background Neurological and psychiatric sequelae of COVID-19 have been reported, but more data are needed to adequately assess the effects of COVID-19 on brain health. We aimed to provide robust estimates of incidence rates and relative risks of neurological and psychiatric diagnoses in patients in the 6 months following a COVID-19 diagnosis. Methods For this retrospective cohort study and time-to-event analysis, we used data obtained from the TriNetX electronic health records network (with over 81 million patients). Our primary cohort comprised patients who had a COVID-19 diagnosis; one matched control cohort included patients diagnosed with influenza, and the other matched control cohort included patients diagnosed with any respiratory tract infection including influenza in the same period. Patients with a diagnosis of COVID-19 or a positive test for SARS-CoV-2 were excluded from the control cohorts. All cohorts included patients older than 10 years who had an index event on or after Jan 20, 2020, and who were still alive on Dec 13, 2020. We estimated the incidence of 14 neurological and psychiatric outcomes in the 6 months after a confirmed diagnosis of COVID-19: intracranial haemorrhage; ischaemic stroke; parkinsonism; Guillain-Barré syndrome; nerve, nerve root, and plexus disorders; myoneural junction and muscle disease; encephalitis; dementia; psychotic, mood, and anxiety disorders (grouped and separately); substance use disorder; and insomnia. Using a Cox model, we compared incidences with those in propensity score-matched cohorts of patients with influenza or other respiratory tract infections. We investigated how these estimates were affected by COVID-19 severity, as proxied by hospitalisation, intensive therapy unit (ITU) admission, and encephalopathy (delirium and related disorders). We assessed the robustness of the differences in outcomes between cohorts by repeating the analysis in different scenarios. To provide benchmarking for the incidence and risk of neurological and psychiatric sequelae, we compared our primary cohort with four cohorts of patients diagnosed in the same period with additional index events: skin infection, urolithiasis, fracture of a large bone, and pulmonary embolism. Findings Among 236 379 patients diagnosed with COVID-19, the estimated incidence of a neurological or psychiatric diagnosis in the following 6 months was 33·62% (95% CI 33·17–34·07), with 12·84% (12·36–13·33) receiving their first such diagnosis. For patients who had been admitted to an ITU, the estimated incidence of a diagnosis was 46·42% (44·78–48·09) and for a first diagnosis was 25·79% (23·50–28·25). Regarding individual diagnoses of the study outcomes, the whole COVID-19 cohort had estimated incidences of 0·56% (0·50–0·63) for intracranial haemorrhage, 2·10% (1·97–2·23) for ischaemic stroke, 0·11% (0·08–0·14) for parkinsonism, 0·67% (0·59–0·75) for dementia, 17·39% (17·04–17·74) for anxiety disorder, and 1·40% (1·30–1·51) for psychotic disorder, among others. In the group with ITU admission, estimated incidences were 2·66% (2·24–3·16) for intracranial haemorrhage, 6·92% (6·17–7·76) for ischaemic stroke, 0·26% (0·15–0·45) for parkinsonism, 1·74% (1·31–2·30) for dementia, 19·15% (17·90–20·48) for anxiety disorder, and 2·77% (2·31–3·33) for psychotic disorder. Most diagnostic categories were more common in patients who had COVID-19 than in those who had influenza (hazard ratio [HR] 1·44, 95% CI 1·40–1·47, for any diagnosis; 1·78, 1·68–1·89, for any first diagnosis) and those who had other respiratory tract infections (1·16, 1·14–1·17, for any diagnosis; 1·32, 1·27–1·36, for any first diagnosis). As with incidences, HRs were higher in patients who had more severe COVID-19 (eg, those admitted to ITU compared with those who were not: 1·58, 1·50–1·67, for any diagnosis; 2·87, 2·45–3·35, for any first diagnosis). Results were robust to various sensitivity analyses and benchmarking against the four additional index health events. Interpretation Our study provides evidence for substantial neurological and psychiatric morbidity in the 6 months after COVID-19 infection. Risks were greatest in, but not limited to, patients who had severe COVID-19. This information could help in service planning and identification of research priorities. Complementary study designs, including prospective cohorts, are needed to corroborate and explain these findings. Funding National Institute for Health Research (NIHR) Oxford Health Biomedical Research Centre.

0 comments Cited 856 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Gwenaëlle Douaud:

ORCID: http://orcid.org/0000-0003-1981-391X

gwenaelle.douaud@ndcn.ox.ac.uk

Journal

Journal ID (nlm-ta): Nature

Journal ID (iso-abbrev): Nature

Title: Nature

Publisher: Nature Publishing Group UK (London )

ISSN (Print): 0028-0836

ISSN (Electronic): 1476-4687

Publication date (Electronic): 7 March 2022

Publication date PMC-release: 7 March 2022

Publication date (Print): 2022

Volume: 604

Issue: 7907

Pages: 697-707

Affiliations

[1 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, , University of Oxford, ; Oxford, UK

[2 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, OHBA, Wellcome Centre for Integrative Neuroimaging (WIN), Department of Psychiatry, , University of Oxford, ; Oxford, UK

[3 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Department of Paediatrics, , University of Oxford, ; Oxford, UK

[4 ]GRID grid.83440.3b, ISNI 0000000121901201, Ear Institute, , University College London, ; London, UK

[5 ]GRID grid.94365.3d, ISNI 0000 0001 2297 5165, National Institute of Mental Health, , National Institutes of Health, ; Bethesda, MD USA

[6 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Nuffield Department of Population Health, , University of Oxford, ; Oxford, UK

[7 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, UK Dementia Research Institute and Department of Brain Sciences, , Imperial College, ; London, UK

[8 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Big Data Institute, , University of Oxford, ; Oxford, UK

Author information

Gwenaëlle Douaud http://orcid.org/0000-0003-1981-391X

Christoph Arthofer http://orcid.org/0000-0003-1474-9963

Chaoyue Wang http://orcid.org/0000-0001-9402-1563

Frederik Lange http://orcid.org/0000-0002-1736-7162

Bernd Taschler http://orcid.org/0000-0001-6574-4789

Paul M. Matthews http://orcid.org/0000-0002-1619-8328

Thomas E. Nichols http://orcid.org/0000-0002-4516-5103

Stephen M. Smith http://orcid.org/0000-0001-8166-069X

Article

Publisher ID: 4569

DOI: 10.1038/s41586-022-04569-5

PMC ID: 9046077

PubMed ID: 35255491

SO-VID: 45574503-6cda-4a11-a6b7-7612565f98af

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 19 August 2021

Date accepted : 21 February 2022

Custom metadata

ScienceOpen disciplines: Uncategorized

Keywords: encephalopathy,olfactory cortex

Data availability:

ScienceOpen disciplines: Uncategorized

Keywords: encephalopathy, olfactory cortex

Comments

Comment on this article

scite_

Cited by 518

See all cited by

Most referenced authors 1,387

See all reference authors

SARS-CoV-2 is associated with changes in brain structure in UK Biobank

Read this article at

Abstract

Abstract

Related collections

UCL: Covid-19 Research

Most cited references 79

Neurologic Features in Severe SARS-CoV-2 Infection

Multiorgan and Renal Tropism of SARS-CoV-2

6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: a retrospective cohort study using electronic health records

Author and article information

Contributors

Journal

Affiliations

Author information

Article

History

Categories

Custom metadata

Comments

Comment on this article

Similar content 239

Cited by 518

Most referenced authors 1,387