Long COVID: phenotyping and characterization of the functional and structural connectivity in patients with cognitive sequelae from COVID-19

• Grant number: 22/11786-4
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• Effective date (Start): December 01, 2022
• Effective date (End): May 31, 2026
• Field of knowledge: Health Sciences - Medicine - Medical Clinics
• Principal Investigator: Clarissa Lin Yasuda
• Grantee: Ítalo Karmann Aventurato
• Host Institution: Faculdade de Ciências Médicas (FCM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 13/07559-3 - BRAINN - The Brazilian Institute of Neuroscience and Neurotechnology, AP.CEPID
• Associated scholarship(s): 23/11469-1 - Identifying post-COVID-19 syndrome neuropsychiatric subgroups through resting-state fMRI and graph-based machine learning, BE.EP.DD

Abstract

Neurological symptoms are well established sequelae of the COVID-19 even in mild and moderate cases. The syndrome named long COVID is characterized by affective and cognitive symptoms that significantly impair the life of those affected. Neither the neuropsychological subtypes of this syndrome nor their brain connectivity characteristics have been well defined until now. The goal of the present study is to identify neuropsychological subtypes of the post-COVID cognitive syndrome using data from UNICAMP's NeuroCovid cohort. Subjects with documented previous SARS-Cov-2 infection undergo brief neuropsychological battery and multimodal magnetic resonance imaging. This data will feed a nonsupervised machine learning algorithm in order to characterize subgroups. The groups identified this way will be further compared to find differences in structural and functional connectivity. These comparisons will be performed using well known statistical techniques as well as graph kernel machine learning methods. Preliminary results from the study cohort have shown that subjects with previous mild-to-moderate COVID-19 present significant differences in grey matter structure and functional connectivity as measured by graph and voxel-wise metrics. (AU)