Home > Publications Database > Neuropathology of patients with COVID-19 in Germany: a post-mortem case series > print

001     154197
005     20240618100829.0
024 7 _ |a pmc:PMC7535629
|2 pmc
024 7 _ |a 10.1016/S1474-4422(20)30308-2
|2 doi
024 7 _ |a 1474-4422
|2 ISSN
024 7 _ |a 1474-4465
|2 ISSN
024 7 _ |a altmetric:91826120
|2 altmetric
024 7 _ |a pmid:33031735
|2 pmid
037 _ _ |a DZNE-2021-00059
082 _ _ |a 610
100 1 _ |a Matschke, Jakob
|b 0
245 _ _ |a Neuropathology of patients with COVID-19 in Germany: a post-mortem case series
260 _ _ |a London
|c 2020
|b Lancet Publ. Group
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1718698038_13421
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Background: Prominent clinical symptoms of COVID-19 include CNS manifestations. However, it is unclear whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, gains access to the CNS and whether it causes neuropathological changes. We investigated the brain tissue of patients who died from COVID-19 for glial responses, inflammatory changes, and the presence of SARS-CoV-2 in the CNS.Methods: In this post-mortem case series, we investigated the neuropathological features in the brains of patients who died between March 13 and April 24, 2020, in Hamburg, Germany. Inclusion criteria comprised a positive test for SARS-CoV-2 by quantitative RT-PCR (qRT-PCR) and availability of adequate samples. We did a neuropathological workup including histological staining and immunohistochemical staining for activated astrocytes, activated microglia, and cytotoxic T lymphocytes in the olfactory bulb, basal ganglia, brainstem, and cerebellum. Additionally, we investigated the presence and localisation of SARS-CoV-2 by qRT-PCR and by immunohistochemistry in selected patients and brain regions.Findings: 43 patients were included in our study. Patients died in hospitals, nursing homes, or at home, and were aged between 51 years and 94 years (median 76 years [IQR 70-86]). We detected fresh territorial ischaemic lesions in six (14%) patients. 37 (86%) patients had astrogliosis in all assessed regions. Activation of microglia and infiltration by cytotoxic T lymphocytes was most pronounced in the brainstem and cerebellum, and meningeal cytotoxic T lymphocyte infiltration was seen in 34 (79%) patients. SARS-CoV-2 could be detected in the brains of 21 (53%) of 40 examined patients, with SARS-CoV-2 viral proteins found in cranial nerves originating from the lower brainstem and in isolated cells of the brainstem. The presence of SARS-CoV-2 in the CNS was not associated with the severity of neuropathological changes.Interpretation: In general, neuropathological changes in patients with COVID-19 seem to be mild, with pronounced neuroinflammatory changes in the brainstem being the most common finding. There was no evidence for CNS damage directly caused by SARS-CoV-2. The generalisability of these findings needs to be validated in future studies as the number of cases and availability of clinical data were low and no age-matched and sex-matched controls were included.Funding: German Research Foundation, Federal State of Hamburg, EU (eRARE), German Center for Infection Research (DZIF).
536 _ _ |a 342 - Disease Mechanisms and Model Systems (POF3-342)
|0 G:(DE-HGF)POF3-342
|c POF3-342
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef
650 _ 2 |a Aged
|2 MeSH
650 _ 2 |a Aged, 80 and over
|2 MeSH
650 _ 2 |a Autopsy: methods
|2 MeSH
650 _ 2 |a Betacoronavirus: isolation & purification
|2 MeSH
650 _ 2 |a Brain: pathology
|2 MeSH
650 _ 2 |a Brain: virology
|2 MeSH
650 _ 2 |a COVID-19
|2 MeSH
650 _ 2 |a Coronavirus Infections: epidemiology
|2 MeSH
650 _ 2 |a Coronavirus Infections: genetics
|2 MeSH
650 _ 2 |a Coronavirus Infections: pathology
|2 MeSH
650 _ 2 |a Female
|2 MeSH
650 _ 2 |a Germany: epidemiology
|2 MeSH
650 _ 2 |a Humans
|2 MeSH
650 _ 2 |a Male
|2 MeSH
650 _ 2 |a Middle Aged
|2 MeSH
650 _ 2 |a Neuropathology
|2 MeSH
650 _ 2 |a Pandemics
|2 MeSH
650 _ 2 |a Pneumonia, Viral: epidemiology
|2 MeSH
650 _ 2 |a Pneumonia, Viral: genetics
|2 MeSH
650 _ 2 |a Pneumonia, Viral: pathology
|2 MeSH
650 _ 2 |a SARS-CoV-2
|2 MeSH
650 _ 2 |a Transcriptome: genetics
|2 MeSH
700 1 _ |a Lütgehetmann, Marc
|b 1
700 1 _ |a Hagel, Christian
|b 2
700 1 _ |a Sperhake, Jan P
|b 3
700 1 _ |a Schröder, Ann Sophie
|0 P:(DE-HGF)0
|b 4
700 1 _ |a Edler, Carolin
|b 5
700 1 _ |a Mushumba, Herbert
|b 6
700 1 _ |a Fitzek, Antonia
|b 7
700 1 _ |a Allweiss, Lena
|b 8
700 1 _ |a Dandri, Maura
|b 9
700 1 _ |a Dottermusch, Matthias
|b 10
700 1 _ |a Heinemann, Axel
|b 11
700 1 _ |a Pfefferle, Susanne
|b 12
700 1 _ |a Schwabenland, Marius
|b 13
700 1 _ |a Sumner Magruder, Daniel
|b 14
700 1 _ |a Bonn, Stefan
|0 P:(DE-2719)2810547
|b 15
|u dzne
700 1 _ |a Prinz, Marco
|b 16
700 1 _ |a Gerloff, Christian
|b 17
700 1 _ |a Püschel, Klaus
|b 18
700 1 _ |a Krasemann, Susanne
|b 19
700 1 _ |a Aepfelbacher, Martin
|b 20
700 1 _ |a Glatzel, Markus
|b 21
773 _ _ |a 10.1016/S1474-4422(20)30308-2
|g Vol. 19, no. 11, p. 919 - 929
|0 PERI:(DE-600)2079704-7
|n 11
|p 919 - 929
|t The lancet / Neurology
|v 19
|y 2020
|x 1474-4422
856 4 _ |u https://pub.dzne.de/record/154197/files/DZNE-2021-00059_Restricted.pdf
856 4 _ |u https://pub.dzne.de/record/154197/files/DZNE-2021-00059_Restricted.pdf?subformat=pdfa
|x pdfa
909 C O |p VDB
|o oai:pub.dzne.de:154197
910 1 _ |a Deutsches Zentrum für Neurodegenerative Erkrankungen
|0 I:(DE-588)1065079516
|k DZNE
|b 15
|6 P:(DE-2719)2810547
913 1 _ |a DE-HGF
|b Gesundheit
|l Erkrankungen des Nervensystems
|1 G:(DE-HGF)POF3-340
|0 G:(DE-HGF)POF3-342
|3 G:(DE-HGF)POF3
|2 G:(DE-HGF)POF3-300
|4 G:(DE-HGF)POF
|v Disease Mechanisms and Model Systems
|x 0
913 2 _ |a DE-HGF
|b Programmungebundene Forschung
|l ohne Programm
|1 G:(DE-HGF)POF4-890
|0 G:(DE-HGF)POF4-899
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-800
|4 G:(DE-HGF)POF
|v ohne Topic
|x 0
914 1 _ |y 2020
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2021-02-04
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2021-02-04
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2022-11-09
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2022-11-09
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2022-11-09
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
|d 2022-11-09
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b LANCET NEUROL : 2021
|d 2022-11-09
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2022-11-09
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2022-11-09
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2022-11-09
915 _ _ |a IF >= 50
|0 StatID:(DE-HGF)9950
|2 StatID
|b LANCET NEUROL : 2021
|d 2022-11-09
920 1 _ |0 I:(DE-2719)1410003
|k AG Bonn 1
|l Computational analysis of biological networks
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-2719)1410003
980 _ _ |a UNRESTRICTED

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21