Reissuing the sigma receptors for SARS-CoV-2

[Structure and dynamics of depressive disorders in patients with a new coronavirus infection]

OBJECTIVE

To analyze the dynamics of depressive disorders in patients who underwent COVID-19.

MATERIAL AND METHODS

The study included female patients (n=30) with mean age 35.4±3.0 years, who received inpatient treatment of depressive spectrum symptoms in accordance with ICD-10 rubrics F31-F34 and who have undergone COVID-19 (U04.9, U07.1, U07.2). Clinical-psychopathological and statistical methods were used.

RESULTS

Among all patients, who underwent inpatient treatment for affective disorders, the most common symptoms were: low mood (96.7%), anxiety (83.3%), decreased interest in daily activities (40%), loss of appetite (36.7%). In patients who have had depressive symptoms before COVID-19, an increase in the number of affective spectrum symptoms (suicidal thoughts - 83.3%), as well as in asthenic manifestations in the form of increased fatigue (60%), sleep disorders (73.3%), feelings of fatigue, weakness (60%), emotional lability (40%).

CONCLUSION

In patients with depressive disorders who underwent COVID-19, hypothymia is most often accompanied by anxiety, suicidal thoughts, as well as asthenic manifestations in the form of fatigue, sleep disturbances, and emotional lability. An increase in the number of asthenic spectrum symptoms in patients with depressive disorders may indicate a possible link between COVID-19 and affective pathology. The impact of coronavirus infection on the structure and dynamics of depressive disorders requires further study, taking into account the severity of affective symptoms, the impact of psychopharmacotherapy, and the severity of the infectious disease.

Accurate prediction of virus-host protein-protein interactions via a Siamese neural network using deep protein sequence embeddings

Prediction and understanding of virus-host protein-protein interactions (PPIs) have relevance for the development of novel therapeutic interventions. In addition, virus-like particles open novel opportunities to deliver therapeutics to targeted cell types and tissues. Given our incomplete knowledge of PPIs on the one hand and the cost and time associated with experimental procedures on the other, we here propose a deep learning approach to predict virus-host PPIs. Our method (Siamese Tailored deep sequence Embedding of Proteins [STEP]) is based on recent deep protein sequence embedding techniques, which we integrate into a Siamese neural network. After showing the state-of-the-art performance of STEP on external datasets, we apply it to two use cases, severe acute respiratory syndrome coronavirus 2 and John Cunningham polyomavirus, to predict virus-host PPIs. Altogether our work highlights the potential of deep sequence embedding techniques originating from the field of NLP as well as explainable artificial intelligence methods for the analysis of biological sequences.

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Deep learning approach (STEP) predicts virus protein to human host protein interactions

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It is based on recent deep protein sequence embeddings and Siamese neural network

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Prediction of PPIs of the JCV VP1 protein and of the SARS-CoV-2 spike protein

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Identify parts of sequences that most likely contribute to the PPI using explainable AI

The development of novel cell and tissue-specific therapies requires a profound knowledge about protein-protein interactions (PPIs). Identifying these PPIs with experimental approaches such as biochemical assays or yeast two-hybrid screens is cumbersome, costly, and at the same time difficult to scale. Computational approaches can help to prioritize huge amounts of possible PPIs by learning from biological sequences plus already known PPIs. In this work, we developed an approach that is based on recent deep protein sequence embedding techniques, which we integrate into a Siamese neural network architecture. We use this approach to train models by using protein sequence information and known PPIs. We apply the models to two use cases to predict virus protein to human host interactions. Altogether our work highlights the potential of deep sequence embedding techniques as well as explainable artificial intelligence methods for the analysis of biological sequence data.

Psychotropics and COVID-19: An analysis of safety and prophylaxis

The use of psychotropics during the COVID-19 pandemic has raised two questions, in order of importance: first, what changes should be made to pharmacological treatments prescribed to mental health patients? Secondly, are there any positive side effects of these substances against SARS-CoV-2? Our aim was to analyze usage safety of psychotropics during COVID-19; therefore, herein, we have studied: (i) the risk of symptomatic complications of COVID-19 associated with the use of these drugs, notably central nervous system activity depression, QTc interval enlargement and infectious and thromboembolic complications; (ii) the risk of mistaking the iatrogenic impact of psychotropics with COVID-19 symptoms, causing diagnostic error. Moreover, we provided a summary of the different information available today for these risks, categorized by mental health disorder, for the following: schizophrenia, bipolar disorder, anxiety disorder, ADHD, sleep disorders and suicidal risk. The matter of psychoactive substance use during the pandemic is also analyzed in this paper, and guideline websites and publications for psychotropic treatments in the context of COVID-19 are referenced during the text, so that changes on those guidelines and eventual interaction between psychotropics and COVID-19 treatment medication can be reported and studied. Finally, we also provide a literature review of the latest known antiviral properties of psychotropics against SARS-CoV-2 as complementary information.

[About the causes and therapy of depressive disorders in COVID-19]

Brief information about the causes of depressive disorders in COVID-19 and general strategies of their treatment is presented. According to the biopsychosocial model of the development of mental diseases, depressive disorders in COVID-19 develop due to the toxic effect of the coronavirus on nervous system and other organism systems, possible side-effects of COVID-19 therapy, the psychogenic effect of excessive and inaccurate information about the coronavirus infection and the consequences of its spread, adverse social changes during the pandemic. If infection with the SARS-CoV-2 did not develop, depressive disorders may arise due to psychogenic information and negative social influences. If coronavirus infection is present, depressive disorders can manifest during the acute period of COVID-19 and after recovery from COVID-19. Depressive disorders may occur for the first time in a patient with COVID-19 or infection can aggravate depression that has been in remission. Care should consistently include psychosocial activities, psychocorrection and psychopharmacotherapy. For the prevention of onset of depressive disorders, it is better to implement social-hygienic and psychological-pedagogical measures. Psychotherapy and psychopharmacotherapy become more important in the development of clinically expressed depressive disorders.

Psychotic Agitation in a Patient with COVID-19: Pathogenesis or Iatrogenesis?

The pathophysiological underpinnings of central nervous system (CNS) involvement in SARS-CoV-2 infection, as well as the profile of adverse neuropsychiatric effects of pharmacological agents employed in the management of COVID-19, are yet to be elucidated. Here, we report a 43-year-old female patient who suffered from COVID-19 and who developed new-onset psychotic agitated behavior which may be related to either the COVID-19 infection itself or to the drugs that were used in the treatment. On her third day of treatment with oseltamivir, hydroxychloroquine, and azithromycin, the patient, who had no previous background of neurological or psychiatric diagnosis, presented with a new-onset psychomotor agitation with auditory hallucinations and insomnia. Her psychiatric symptoms have improved with oral olanzapine 5 mg/d. This report underscores the importance of neuropsychiatric monitoring in patients with COVID-19. Clinicians should be aware of the limited knowledge on the neuropsychiatric safety profile of the medication used for COVID-19 treatment, while they have focused on the neuropsychiatric outcomes of COVID-19 itself.

Fluvoxamine: A Review of Its Mechanism of Action and Its Role in COVID-19

Fluvoxamine is a well-tolerated, widely available, inexpensive selective serotonin reuptake inhibitor that has been shown in a small, double-blind, placebo-controlled, randomized study to prevent clinical deterioration of patients with mild coronavirus disease 2019 (COVID-19). Fluvoxamine is also an agonist for the sigma-1 receptor, through which it controls inflammation. We review here a body of literature that shows important mechanisms of action of fluvoxamine and other SSRIs that could play a role in COVID-19 treatment. These effects include: reduction in platelet aggregation, decreased mast cell degranulation, interference with endolysosomal viral trafficking, regulation of inositol-requiring enzyme 1α-driven inflammation and increased melatonin levels, which collectively have a direct antiviral effect, regulate coagulopathy or mitigate cytokine storm, which are known hallmarks of severe COVID-19.

SARS-CoV-2-associated first episode of acute mania with psychotic features

Despite neuropsychiatric outcomes of SARS-CoV-2 infection are now under close scrutiny, psychoneuroimmunological characteristics of COVID-19 and precise pathophysiology of neuropsychiatric manifestations of the infection are still obscure. Moreover, there still exists a shortfall in demonstrating specific clinical manifestations of the brain involvement of the virus. Here, we presented a 33-year-old female patient with COVID-19, reporting acute-onset paranoid delusions symptoms, insomnia and irritability. Cranial MRI showed an hyperintense signal in the splenium of the corpus callosum with decreased apparent diffusion coefficient, which might possibly indicate the presence of cytotoxic edema related to the brain involvement of the infection. Following the completion of SARS-CoV-2 treatment, both cytotoxic edema and psychiatric symptoms resolved. In light of this report, we suggest that either heightened immune response and direct viral infection that SARS-CoV-2 may lead to such psychiatric manifestations and neuropsychiatric monitoring should be performed in patients with COVID-19. Prompt recognition of psychiatric consequences of COVID-19 may help clinicians provide guidance for differential diagnosis and manage them accordingly.

Repurposing of CNS drugs to treat COVID-19 infection: targeting the sigma-1 receptor

The novel coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The escalating number of SARS-CoV-2-infected individuals has conferred the viral spread with the status of global pandemic. However, there are no prophylactic or therapeutic drugs available on the market to treat COVID-19, although several drugs have been approved. Recently, two articles using the comparative viral-human protein-protein interaction map revealed that the sigma-1 receptor in the endoplasmic reticulum plays an important role in SARS-CoV-2 replication in cells. Knockout and knockdown of SIGMAR1 (sigma-1 receptor, encoded by SIGMAR1) caused robust reductions in SARS-CoV-2 replication, which indicates that the sigma-1 receptor is a key therapeutic target for SARS-CoV-2 replication. Interestingly, a recent clinical trial demonstrated that treatment with the antidepressant fluvoxamine, which has a high affinity at the sigma-1 receptor, could prevent clinical deterioration in adult outpatients infected with SARS-CoV-2. In this review, we discuss the brief history of the sigma-1 receptor and its role in SARS-CoV-2 replication in cells. Here, we propose repurposing of traditional central nervous system (CNS) drugs that have a high affinity at the sigma-1 receptor (i.e., fluvoxamine, donepezil, ifenprodil) for the treatment of SARS-CoV-2-infected patients. Finally, we discussed the potential of other CNS candidates such as cutamesine and arketamine.

Homozygosity for rs17775810 Minor Allele Associated With Reduced Mortality of COVID-19 in the UK Biobank Cohort

BACKGROUND/AIM

Adult outpatients with symptomatic COVID-19 treated with fluvoxamine, compared with placebo, had a lower likelihood of clinical deterioration over 15 days. Fluvoxamine strongly binds to the sigma-1 receptor (S1R) that regulates inflammation by inhibiting the production of cytokines, believed to be responsible for severe COVID-19. We evaluated the S1R locus on chr 9p13.3 in subjects tested positive for SARS-CoV-2. We focused on SNP rs17775810 that has been previously identified by examining loss-of-function mutations in the S1R gene associated with distal hereditary motor neuropathy.

PATIENTS AND METHODS

We utilized UK Biobank (UKB) data. Data processing was performed on Minerva, a Linux mainframe with Centos 7.6, at the Icahn School of Medicine at Mount Sinai.

RESULTS

The effect of rs17775810 genotype on survival was significant (p=0.036, 2 tailed Fisher exact test). The minor allele homozygotes (TT) had the lowest death rate (0%), whereas the non-TT genotypes (i.e. CT and CC) had the highest death rate (16.2%).

CONCLUSION

The rs17775810 analysis corroborates the favorable effect of fluvoxamine on COVID-19 survival.