ABSTRACT
We consider an increasingly popular study design where single-cell RNA-seq data are collected from multiple individuals and the question of interest is to find genes that are differentially expressed between two groups of individuals. Towards this end, we propose a statistical method named IDEAS (individual level differential expression analysis for scRNA-seq). For each gene, IDEAS summarizes its expression in each individual by a distribution and then assesses whether these individual-specific distributions are different between two groups of individuals. We apply IDEAS to assess gene expression differences of autism patients versus controls and COVID-19 patients with mild versus severe symptoms.
Subject(s)
Autistic Disorder/genetics , COVID-19/genetics , Sequence Analysis, RNA/methods , Single-Cell Analysis/methods , Software , Autistic Disorder/metabolism , Autistic Disorder/pathology , COVID-19/metabolism , COVID-19/pathology , COVID-19/virology , Case-Control Studies , Gene Expression Profiling , Gene Expression Regulation , Humans , Microglia/metabolism , Microglia/pathology , Nerve Tissue Proteins/classification , Nerve Tissue Proteins/genetics , Nerve Tissue Proteins/metabolism , SARS-CoV-2/pathogenicity , Severity of Illness Index , Exome SequencingABSTRACT
The recent pandemic outbreak of coronavirus is pathogenic and a highly transmittable viral infection caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2). In this time of ongoing pandemic, many emerging reports suggested that the SARS-CoV-2 has inimical effects on neurological functions, and even causes serious neurological damage. The neurological symptoms associated with COVID-19 include headache, dizziness, depression, anosmia, encephalitis, stroke, epileptic seizures, and Guillain-Barre syndrome along with many others. The involvement of the CNS may be related with poor prognosis and disease worsening. Here, we review the evidence of nervous system involvement and currently known neurological manifestations in COVID-19 infections caused by SARS-CoV-2. We prioritize the 332 human targets of SARS-CoV-2 according to their association with brain-related disease and identified 73 candidate genes. We prioritize these 73 genes according to their spatio-temporal expression in the different regions of brain and also through evolutionary intolerance analysis. The prioritized genes could be considered potential indicators of COVID-19-associated neurological symptoms and thus act as a possible therapeutic target for the prevention and treatment of CNS manifestations associated with COVID-19 patients.