Acute TNFα levels predict cognitive impairment 6-9 months after COVID-19 infection

Abstract

Background: A neurocognitive phenotype of post-COVID-19 infection has recently been described that is characterized by a lack of awareness of memory impairment (i.e., anosognosia), altered functional connectivity in the brain's default mode and limbic networks, and an elevated monocyte count. However, the relationship between these cognitive and brain functional connectivity alterations in the chronic phase with the level of cytokines during the acute phase has yet to be identified.

Aim: Determine whether acute cytokine type and levels is associated with anosognosia and functional patterns of brain connectivity 6-9 months after infection.

Methods: We analyzed the predictive value of the concentration of acute cytokines (IL-1RA, IL-1β, IL-6, IL-8, IFNγ, G-CSF, GM-CSF) (cytokine panel by multiplex immunoassay) in the plasma of 39 patients (mean age 59 yrs, 38-78) in relation to their anosognosia scores for memory deficits via stepwise linear regression. Then, associations between the different cytokines and brain functional connectivity patterns were analyzed by MRI and multivariate partial least squares correlations for the whole group.

Results: Stepwise regression modeling allowed us to show that acute TNFα levels predicted (R² = 0.145; β = -0.38; p = .017) and were associated (r = -0.587; p < .001) with scores of anosognosia for memory deficits observed 6-9 months post-infection. Finally, high TNFα levels were associated with hippocampal, temporal pole, accumbens nucleus, amygdala, and cerebellum connectivity.

Conclusion: Increased plasma TNFα levels in the acute phase of COVID-19 predict the presence of long-term anosognosia scores and changes in limbic system functional connectivity.

Keywords: Anosognosia; Cognition; Cytokine; Immunology; Post-COVID-19 condition; SARS-CoV-2; TNFα.

Fig. 1

Study flowchart. Note. Of the 121 patients initially included in the COVID-COG cohort (Voruz et al., 2022d), we retained only those hospitalized patients who presented blood sample data. Thus, 61 hospitalized patients presented venous blood data (Nuber-Champier, 2022), including 39 patients' samples suitable for cytokine analysis. Regarding the MRI data a total of 41 hospitalized patients presented data (Voruz et al., 2022c). However, of these 41 patients only 15 patients had both analyzable blood samples for cytokine quantification and MRI data. Abbreviation: ICU, intensive care unit.

Fig. 2

Association between TNFα rates and scores of anosognosia for memory deficits. Note. Scores ranging from − 3 (not represented) to < 0 reflect anosognosia for memory disorders, while scores ranging from 0 to + 3 reflects an absence of anosognosia (see also, Voruz et al., 2022 and supplementary information F-J).

Fig. 3

Multivariate latent component of PLSC analysis. Note. A) Loadings of behavioral data. PLSC loadings were defined as correlation coefficients between a given feature and its weight in the latent component. Dots represent samples from the bootstrap procedure, and yellow highlights indicate the reliability of the scores’ contributions to the multivariate correlation component. B) Bootstrap sampling ratios for functional connectivity. This network representation illustrates the neuroimaging pattern, with red links indicating a positive influence of functional connectivity on the latent component and darker colors indicating a higher number of significant connections for each pair of resting-state networks involved in the pattern. C) Twenty brain networks and regions whose connections had the greatest impact (BSR: bootstrap sampling ratio) on the latent component.