Synopsis

Keywords: Brain Connectivity, COVID-19

The neural mechanisms underlying the neuropsychiatric disorders suffered by Long-Covid-19 patients remain unknown. Non-invasive [18F]-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) brain imaging is an effective way to study this issue. In the present study, based on 18F-FDG PET brain imaging and analysis of the brain metabolic network, we found significant reductions in metabolic levels in the frontal, temporal, and parietal lobes in patients with Long-Covid-19. A significant reduction in metabolic connectivity between temporal and frontal networks in patients with Long-Covid-19 may be the underlying neural mechanism underlying cognitive impairment.

Summary of Main Findings

The reduction of metabolic activity in the frontal lobe network may be the brain neural mechanism of the neuropsychiatric disorders suffered by patients with Long-Covid-19.

Introduction

Long-COVID-19 refers to syndromes that develop after the acute phase of COVID-19, with neuropsychiatric disorders being the most frequently reported. But the brain neural mechanisms responsible for the neuropsychiatric disorders suffered by COVID-19 patients are still unclear. Understanding the pathophysiological mechanisms of COVID-19 is essential for predicting, preventing and treating the long-term consequences of COVID-19.

Method

A total of 45 Long-COVID-19 patients (Males: 24, Age: 50.4 ± 1.8) and 48 healthy controls (Males: 25, Age: 49.9 ± 0.8) were enrolled in this study. All participants underwent a routine 18F-FDG PET/CT scanner. 18F-FDG PET image acquisition was performed on patients infected with COVID-19 six months ago. SPM12 (Statistical Parametric Mapping) was used to preprocess the brain images, which included spatial registration, smooth and intensity normalization. A two-sample t-test analysis was used to compare differences in brain metabolic levels between the groups. Pearson's correlation analysis was used to assess the correlation between metabolic levels in brain regions and various clinical scores. Brain metabolic networks and network properties were calculated for different populations.

Result

In patients with Long-COVID-19, there is a significant reduction in brain metabolic activity, which is mainly found in the frontal, temporal, and parietal lobes (***p < 0.001, One-Way ANOVA, Figure 1). These regions of metabolic activity that have shown a significant negative correlation with scores of mental disorders, including depression, anxiety, physical fatigue, and mental fatigue, are also primarily located in the frontal, temporal, and parietal lobes (p < 0.05, Pearson correlation analysis, Figure 2). Brain metabolic network analysis revealed that the strength of metabolic connections within frontal networks (***p < 0.001, Paired t-test), between frontal and parietal networks (***p < 0.001, Paired t-test), and between frontal and temporal networks (**p < 0.01, Paired t-test) were all found to be significantly reduced in COVID-19 patients compared to healthy controls (Figure 3).

Discussion

The Long-COVID-19 syndrome caused by the global pandemic wave of COVID-19 infections will be a substantial burden for patients. Thus, it is extremely important to understand the neural mechanisms in the brain responsible for the neuropsychiatric disorders most frequently reported in Long-COVID-19 syndrome. Previous studies have shown a significant reduction in brain metabolic activity in COVID-19 patients, which is consistent with our findings[1]. In addition, our study gives further evidence of a significant reduction in the strength of connectivity between the frontal and temporal lobes, which are involved in cognition, memory and emotion, in COVID-19 patients. The significantly reduced efficiency of information communication between the frontal and temporal lobes, the two hubs of higher cognitive function, may contribute to the neuropsychiatric impairment observed in Long-COVID-19 patients.

Conclusion

Our findings may provide potential targets for the treatment of neurological symptoms in Long-COVID-19.

Acknowledgements

We acknowledge the support received from the National Natural Science Foundation of China, the National Clinical KeySpecialty of China and the Henan Medical Science and Technology Research Program.

References

[1] Aurélie Kas, Marine Soret, Nadya Pyatigoskaya, et al. The cerebral network of COVID-19-related encephalopathy: a longitudinal voxel-based 18F-FDG-PET study[J]. European Journal of Nuclear Medicine and Molecular Imaging (2021) 48:2543–2557.