COVID-19 related cognitive, structural and functional brain changes among Italian adolescents and young adults: a multimodal longitudinal case-control study

Abstract

Coronavirus disease 2019 (COVID-19) has been associated with brain functional, structural, and cognitive changes that persist months after infection. Most studies of the neurologic outcomes related to COVID-19 focus on severe infection and aging populations. Here, we investigated the neural activities underlying COVID-19 related outcomes in a case-control study of mildly infected youth enrolled in a longitudinal study in Lombardy, Italy, a global hotspot of COVID-19. All participants (13 cases, 27 controls, mean age 24 years) completed resting-state functional (fMRI), structural MRI, cognitive assessments (CANTAB spatial working memory) at baseline (pre-COVID) and follow-up (post-COVID). Using graph theory eigenvector centrality (EC) and data-driven statistical methods, we examined differences in EC_delta (i.e., the difference in EC values pre- and post-COVID-19) and Volumetric_delta (i.e., the difference in cortical volume of cortical and subcortical areas pre- and post-COVID) between COVID-19 cases and controls. We found that EC_delta significantly between COVID-19 and healthy participants in five brain regions; right intracalcarine cortex, right lingual gyrus, left hippocampus, left amygdala, left frontal orbital cortex. The left hippocampus showed a significant decrease in Volumetric_delta between groups (p = 0.041). The reduced EC_delta in the left amygdala associated with COVID-19 status mediated the association between COVID-19 and disrupted spatial working memory. Our results show persistent structural, functional and cognitive brain changes in key brain areas associated with olfaction and cognition. These results may guide treatment efforts to assess the longevity, reversibility and impact of the observed brain and cognitive changes following COVID-19.

Fig. 1. COVID+ group definition.

PHIME COVID-19 participants were included in the COVID+ group based on: (1) a positive RT-PCR for SARS-CoV-2 RNA detection and (2) time of diagnosis within 12 months of data acquisition. The relation between the ratio of anti-SARS-CoV-2-NCP (IgG) detected using an ELISA assay and the time between a positive RT-PCR and data acquisition is reported in the figure for each single positive PHIME COVID-19 participant (blue dot). Three COVID+ participants are not included in the figure since the ELISA test is not available. Black dotted line represents the 12-month cut-off used as threshold for participant inclusion in the COVID+ group.

Fig. 2. Schematic depicting mediation models used.

A Classical mediation and regression models. The objective of the mediation analysis was to determine if the indirect effect (path a*b) was different from zero, suggesting that the mediating variable (i.e., brain metrics) altered the strength of the relationship between X and Y (i.e., COVID-19 status and spatial working memory metrics). Three linear regression equations were used to assess the mediation in the traditional cross-sectional experimental design: Y regressed on X, M regressed on X, and Y regressed on both X and M. The letters a, b, c, and c′ refer to the regression coefficient estimates for each respective model, with e representing the error term. B Given the longitudinal design of our study, we extended the traditional mediation analysis presented in (A) using a pre- and post-test control group design. Diagram includes: the pre-test covariance between mediator (M_pre) and dependent variable (Y_pre), σ_MpreYpre; the effect of the mediator measured pre-COVID (M_pre) on the mediator measured post-COVID (M_post) (stability of mediator s_MpreMpost); effect of the outcome measured pre-COVID (Y_pre) on the outcome measured post-COVID (Y_post) (stability of outcome s_YpreYpost); the effect of M_pre on Y_post (cross-lagged relation, b_MpreYpost); the effect of X on M_post, a_MpostX; the effect of X on Y_post, c′_YpostX; and the effect of M_post on Y_post, b_MpostYpost.

Fig. 3. Functional hubs differ in EC_delta between COVID+ and COVID− participants.

A The identified ROI for which EC_delta (differences in eigenvector centrality (EC) between pre- and post-COVID) differed significantly between PHIME participants with and without COVID-19 (i.e., functional hubs). B The average EC_delta values for each functional hub identified. Blue bars indicate EC values of COVID+ participants, while orange bars indicate COVID− participants.

Fig. 4. Volumetric difference in the hippocampus between COVID+ and COVID− participants.

The left hippocampal Volumetric_delta (difference in volumetric metrics between pre- and post-COVID) statistically differs between PHIME participants with and without COVID-19. The blue box indicates volumetric values of COVID+ participants, while the orange box indicates volumetric values of COVID− participants. Black lines indicate the median value.