Alterations of frontal-temporal gray matter volume associate with clinical measures of older adults with COVID-19.

COVID-19 Computed tomography Frontal-temporal network Gray matter volume Source-based morphometry

Journal

Neurobiology of stress
ISSN: 2352-2895
Titre abrégé: Neurobiol Stress
Pays: United States
ID NLM: 101643409

Informations de publication

Date de publication:
May 2021
Historique:
received: 04 02 2021
revised: 03 04 2021
accepted: 05 04 2021
pubmed: 20 4 2021
medline: 20 4 2021
entrez: 19 4 2021
Statut: ppublish

Résumé

COVID-19, the infectious disease caused by the most recently discovered severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has become a global pandemic. It dramatically affects people's health and daily life. Neurological complications are increasingly documented for patients with COVID-19. However, the effect of COVID-19 on the brain is less studied, and existing quantitative neuroimaging analyses of COVID-19 were mainly based on the univariate voxel-based morphometry analysis (VBM) that requires corrections for a large number of tests for statistical significance, multivariate approaches that can reduce the number of tests to be corrected have not been applied to study COVID-19 effect on the brain yet. In this study, we leveraged source-based morphometry (SBM) analysis, a multivariate extension of VBM, to identify changes derived from computed tomography scans in covarying gray matter volume patterns underlying COVID-19 in 120 neurological patients (including 58 cases with COVID-19 and 62 patients without COVID-19 matched for age, gender and diseases). SBM identified that lower gray matter volume (GMV) in superior/medial/middle frontal gyri was significantly associated with a higher level of disability (modified Rankin Scale) at both discharge and six months follow-up phases even when controlling for cerebrovascular diseases. GMV in superior/medial/middle frontal gyri was also significantly reduced in patients receiving oxygen therapy compared to patients not receiving oxygen therapy. Patients with fever presented significant GMV reduction in inferior/middle temporal gyri and fusiform gyrus compared to patients without fever. Patients with agitation showed GMV reduction in superior/medial/middle frontal gyri compared to patients without agitation. Patients with COVID-19 showed no significant GMV differences from patients without COVID-19 in any brain region. Results suggest that COVID-19 may affect the frontal-temporal network in a secondary manner through fever or lack of oxygen.

Identifiants

pubmed: 33869679
doi: 10.1016/j.ynstr.2021.100326
pii: S2352-2895(21)00034-5
pmc: PMC8041745
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100326

Subventions

Organisme : NIA NIH HHS
ID : RF1 AG063153
Pays : United States

Informations de copyright

© 2021 The Author(s).

Déclaration de conflit d'intérêts

Andrea Pilotto is consultant and served on the scientific advisory board of Z-cube (Technology Division of Zambon Pharma), received speaker honoraria from Abbvie, Biomarin and Zambon Pharmaceuticals. Alessandro Padovani received grant support from Ministry of Health (MINSAL) and 10.13039/501100003407Ministry of Education, Research and University (MIUR), from 10.13039/501100002803CARIPLO Foundation; personal compensation as a consultant/scientific advisory board member for Avanir, Lundbeck, Eli-Lilly, Neuraxpharma, Biogen, GE Health. The other authors report no conflict of interest.

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Auteurs

Kuaikuai Duan (K)

Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA.
Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, USA.

Enrico Premi (E)

Stroke Unit, Azienda Socio Sanitaria Territoriale Spedali Civili, Spedali Civili Hospital, Brescia, Italy.
Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Italy.

Andrea Pilotto (A)

Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Italy.

Viviana Cristillo (V)

Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Italy.

Alberto Benussi (A)

Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Italy.

Ilenia Libri (I)

Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Italy.

Marcello Giunta (M)

Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Italy.

H Jeremy Bockholt (HJ)

Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, USA.

Jingyu Liu (J)

Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, USA.
Department of Computer Science, Georgia State University, Atlanta, USA.

Riccardo Campora (R)

Neuroradiology Unit, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia and ASST Spedali Civili Hospital, Brescia, Italy.

Alessandro Pezzini (A)

Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Italy.

Roberto Gasparotti (R)

Neuroradiology Unit, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia and ASST Spedali Civili Hospital, Brescia, Italy.

Mauro Magoni (M)

Stroke Unit, Azienda Socio Sanitaria Territoriale Spedali Civili, Spedali Civili Hospital, Brescia, Italy.

Alessandro Padovani (A)

Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Italy.

Vince D Calhoun (VD)

Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA.
Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, USA.
Department of Computer Science, Georgia State University, Atlanta, USA.
Department of Psychology, Computer Science, Neurosciences, Mathematics & Statistics, Georgia State University, Atlanta, USA.

Classifications MeSH