Although increasing evidence confirms neuropsychiatric manifestations associated mainly with severe COVID-19 infection, long-term neuropsychiatric dysfunction (recently characterized as part of “long COVID-19” syndrome) has been frequently observed after mild infection. We show the spectrum of cerebral impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, ranging from long-term alterations in mildly infected individuals (orbitofrontal cortical atrophy, neurocognitive impairment, excessive fatigue and anxiety symptoms) to severe acute damage confirmed in brain tissue samples extracted from the orbitofrontal region (via endonasal transethmoidal access) from individuals who died of COVID-19. In an independent cohort of 26 individuals who died of COVID-19, we used histopathological signs of brain damage as a guide for possible SARS-CoV-2 brain infection and found that among the 5 individuals who exhibited those signs, all of them had genetic material of the virus in the brain. Brain tissue samples from these five patients also exhibited foci of SARS-CoV-2 infection and replication, particularly in astrocytes. Supporting the hypothesis of astrocyte infection, neural stem cell–derived human astrocytes in vitro are susceptible to SARS-CoV-2 infection through a noncanonical mechanism that involves spike–NRP1 interaction. SARS-CoV-2–infected astrocytes manifested changes in energy metabolism and in key proteins and metabolites used to fuel neurons, as well as in the biogenesis of neurotransmitters. Moreover, human astrocyte infection elicits a secretory phenotype that reduces neuronal viability. Our data support the model in which SARS-CoV-2 reaches the brain, infects astrocytes, and consequently, leads to neuronal death or dysfunction. These deregulated processes could contribute to the structural and functional alterations seen in the brains of COVID-19 patients.

Major depressive disorder (MDD) is a leading cause of disability worldwide and results tragically in the loss of almost one million lives in Western societies every year. This is due to poor understanding of the disease pathophysiology and lack of empirical medical tests for accurate diagnosis or for guiding antidepressant treatment strategies. Here, we have used shotgun proteomics in the analysis of post-mortem dorsolateral prefrontal cortex brain tissue from 24 MDD patients and 12 matched controls. Brain proteomes were pre-fractionated by gel electrophoresis and further analyzed by shotgun data-independent label-free liquid chromatography-mass spectrometry. This led to identification of distinct proteome fingerprints between MDD and control subjects. Some of these differences were validated by Western blot or selected reaction monitoring mass spectrometry. This included proteins associated with energy metabolism and synaptic function and we also found changes in the histidine triad nucleotide-binding protein 1 (HINT1), which has been implicated recently in regulation of mood and behavior. We also found differential proteome profiles in MDD with (n=11) and without (n=12) psychosis. Interestingly, the psychosis fingerprint showed a marked overlap to changes seen in the brain proteome of schizophrenia patients. These findings suggest that it may be possible to contribute to the disease understanding by distinguishing different subtypes of MDD based on distinct brain proteomic profiles.

Psychiatric disorders represent a great medical and social challenge and people suffering from these conditions face many impairments regarding personal and professional life. In addition, a mental disorder will manifest itself in approximately one quarter of the world’s population at some period of their life. Dysfunction in energy metabolism is one of the most consistent scientific findings associated with these disorders. With this is mind, this review compiled data on disturbances in energy metabolism found by proteomic analyses of postmortem brains collected from patients affected by the most prevalent psychiatric disorders: schizophrenia (SCZ), bipolar disorder (BPD) and major depressive disorder (MDD). We searched in the PubMed database to gather the studies and compiled all the differentially expressed proteins reported in each work. SCZ studies revealed 92 differentially expressed proteins related to energy metabolism, while 95 proteins were discovered in BPD and 41 proteins in MDD. With the compiled data, it was possible to determine which proteins related to energy metabolism were found to be altered in all the disorders as well as which ones were altered exclusively in one of them. In conclusion, the information gathered in this work could contribute to a better understanding of the impaired metabolic mechanisms and hopefully bring insights into the underlying neuropathology of psychiatric disorders.