Characterizing cell type specific transcriptional differences between the living and postmortem human brain.

Single-nucleus RNA sequencing (snRNA-seq) is often used to define gene expression patterns characteristic of brain cell types as well as to identify cell type specific gene expression signatures of neurological and mental illnesses in postmortem human brains. As methods to obtain brain tissue from living individuals emerge, it is essential to characterize gene expression differences associated with tissue originating from either living or postmortem subjects using snRNA-seq, and to assess whether and how such differences may impact snRNA-seq studies of brain tissue. To address this, human prefrontal cortex single nuclei gene expression was generated and compared between 31 samples from living individuals and 21 postmortem samples. The same cell types were consistently identified in living and postmortem nuclei, though for each cell type, a large proportion of genes were differentially expressed between samples from postmortem and living individuals. Notably, estimation of cell type proportions by cell type deconvolution of pseudo-bulk data was found to be more accurate in samples from living individuals. To allow for future integration of living and postmortem brain gene expression, a model was developed that quantifies from gene expression data the probability a human brain tissue sample was obtained postmortem. These probabilities are established as a means to statistically account for the gene expression differences between samples from living and postmortem individuals. Together, the results presented here provide a deep characterization of both differences between snRNA-seq derived from samples from living and postmortem individuals, as well as qualify and account for their effect on common analyses performed on this type of data.

Divergent landscapes of A-to-I editing in postmortem and living human brain.

Adenosine-to-inosine (A-to-I) editing is a prevalent post-transcriptional RNA modification within the brain. Yet, most research has relied on postmortem samples, assuming it is an accurate representation of RNA biology in the living brain. We challenge this assumption by comparing A-to-I editing between postmortem and living prefrontal cortical tissues. Major differences were found, with over 70,000 A-to-I sites showing higher editing levels in postmortem tissues. Increased A-to-I editing in postmortem tissues is linked to higher ADAR1 and ADARB1 expression, is more pronounced in non-neuronal cells, and indicative of postmortem activation of inflammation and hypoxia. Higher A-to-I editing in living tissues marks sites that are evolutionarily preserved, synaptic, developmentally timed, and disrupted in neurological conditions. Common genetic variants were also found to differentially affect A-to-I editing levels in living versus postmortem tissues. Collectively, these discoveries illuminate the nuanced functions and intricate regulatory mechanisms of RNA editing within the human brain.

Peripheral Transcriptomics in Acute and Long-Term Kidney Dysfunction in SARS-CoV2 Infection.

Background: Acute kidney injury (AKI) is common in hospitalized patients with SARS-CoV2 infection despite vaccination and leads to long-term kidney dysfunction. However, peripheral blood molecular signatures in AKI from COVID-19 and their association with long-term kidney dysfunction are yet unexplored. Methods: In patients hospitalized with SARS-CoV2, we performed bulk RNA sequencing using peripheral blood mononuclear cells(PBMCs). We applied linear models accounting for technical and biological variability on RNA-Seq data accounting for false discovery rate (FDR) and compared functional enrichment and pathway results to a historical sepsis-AKI cohort. Finally, we evaluated the association of these signatures with long-term trends in kidney function. Results: Of 283 patients, 106 had AKI. After adjustment for sex, age, mechanical ventilation, and chronic kidney disease (CKD), we identified 2635 significant differential gene expressions at FDR<0.05. Top canonical pathways were EIF2 signaling, oxidative phosphorylation, mTOR signaling, and Th17 signaling, indicating mitochondrial dysfunction and endoplasmic reticulum (ER) stress. Comparison with sepsis associated AKI showed considerable overlap of key pathways (48.14%). Using follow-up estimated glomerular filtration rate (eGFR) measurements from 115 patients, we identified 164/2635 (6.2%) of the significantly differentiated genes associated with overall decrease in long-term kidney function. The strongest associations were 'autophagy', 'renal impairment via fibrosis', and 'cardiac structure and function'. Conclusions: We show that AKI in SARS-CoV2 is a multifactorial process with mitochondrial dysfunction driven by ER stress whereas long-term kidney function decline is associated with cardiac structure and function and immune dysregulation. Functional overlap with sepsis-AKI also highlights common signatures, indicating generalizability in therapeutic approaches. SIGNIFICANCE STATEMENT: Peripheral transcriptomic findings in acute and long-term kidney dysfunction after hospitalization for SARS-CoV2 infection are unclear. We evaluated peripheral blood molecular signatures in AKI from COVID-19 (COVID-AKI) and their association with long-term kidney dysfunction using the largest hospitalized cohort with transcriptomic data. Analysis of 283 hospitalized patients of whom 37% had AKI, highlighted the contribution of mitochondrial dysfunction driven by endoplasmic reticulum stress in the acute stages. Subsequently, long-term kidney function decline exhibits significant associations with markers of cardiac structure and function and immune mediated dysregulation. There were similar biomolecular signatures in other inflammatory states, such as sepsis. This enhances the potential for repurposing and generalizability in therapeutic approaches.

A study of gene expression in the living human brain.

A goal of medical research is to determine the molecular basis of human brain health and illness. One way to achieve this goal is through observational studies of gene expression in human brain tissue. Due to the unavailability of brain tissue from living people, most such studies are performed using tissue from postmortem brain donors. An assumption underlying this practice is that gene expression in the postmortem human brain is an accurate representation of gene expression in the living human brain. Here, this assumption - which, until now, had not been adequately tested - is tested by comparing human prefrontal cortex gene expression between 275 living samples and 243 postmortem samples. Expression levels differed significantly for nearly 80% of genes, and a systematic examination of alternative explanations for this observation determined that these differences are not a consequence of cell type composition, RNA quality, postmortem interval, age, medication, morbidity, symptom severity, tissue pathology, sample handling, batch effects, or computational methods utilized. Analyses integrating the data generated for this study with data from earlier landmark studies that used tissue from postmortem brain donors showed that postmortem brain gene expression signatures of neurological and mental illnesses, as well as of normal traits such as aging, may not be accurate representations of these gene expression signatures in the living brain. By using tissue from large cohorts living people, future observational studies of human brain biology have the potential to (1) determine the medical research questions that can be addressed using postmortem tissue as a proxy for living tissue and (2) expand the scope of medical research to include questions about the molecular basis of human brain health and illness that can only be addressed in living people (e.g., "What happens at the molecular level in the brain as a person experiences an emotion?").

Downregulation of exhausted cytotoxic T cells in gene expression networks of multisystem inflammatory syndrome in children.

Multisystem inflammatory syndrome in children (MIS-C) presents with fever, inflammation and pathology of multiple organs in individuals under 21 years of age in the weeks following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Although an autoimmune pathogenesis has been proposed, the genes, pathways and cell types causal to this new disease remain unknown. Here we perform RNA sequencing of blood from patients with MIS-C and controls to find disease-associated genes clustered in a co-expression module annotated to CD56dimCD57+ natural killer (NK) cells and exhausted CD8+ T cells. A similar transcriptome signature is replicated in an independent cohort of Kawasaki disease (KD), the related condition after which MIS-C was initially named. Probing a probabilistic causal network previously constructed from over 1,000 blood transcriptomes both validates the structure of this module and reveals nine key regulators, including TBX21, a central coordinator of exhausted CD8+ T cell differentiation. Together, this unbiased, transcriptome-wide survey implicates downregulation of NK cells and cytotoxic T cell exhaustion in the pathogenesis of MIS-C.

Cytotoxic lymphocytes are dysregulated in multisystem inflammatory syndrome in children.

Multisystem inflammatory syndrome in children (MIS-C) presents with fever, inflammation and multiple organ involvement in individuals under 21 years following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. To identify genes, pathways and cell types driving MIS-C, we sequenced the blood transcriptomes of MIS-C cases, pediatric cases of coronavirus disease 2019, and healthy controls. We define a MIS-C transcriptional signature partially shared with the transcriptional response to SARS-CoV-2 infection and with the signature of Kawasaki disease, a clinically similar condition. By projecting the MIS-C signature onto a co-expression network, we identified disease gene modules and found genes downregulated in MIS-C clustered in a module enriched for the transcriptional signatures of exhausted CD8 + T-cells and CD56 dim CD57 + NK cells. Bayesian network analyses revealed nine key regulators of this module, including TBX21 , a central coordinator of exhausted CD8 + T-cell differentiation. Together, these findings suggest dysregulated cytotoxic lymphocyte response to SARS-Cov-2 infection in MIS-C.

Author Correction: Sampling the host response to SARS-CoV-2 in hospitals under siege.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Validation of the Russian Version of the Positive and Negative Syndrome Scale (PANSS-Ru) and Normative Data.

Objective: The Positive and Negative Syndrome Scale (PANSS) is widely used to assess psychopathology. The Russian version (PANSSRu) has not been validated, and normative data for the Russian-speaking population currently do not exist. The aims of this study were to 1) complete linguistic validation for the PANSSRu, 2) perform psychometric validation of the Russian translation, and 3) present norms for the Russian and Belarusian population. Design: Validation and norms of the PANSS-Ru occurred in three stages-Stage I: linguistic validation; Stage II: psychometric validation of the translated version for 40 inpatients with schizophrenia and other psychoses; and Stage III: norms for 533 census-matched inpatients, outpatients, and healthy control subjects. Results: The rating criteria (PANSS-Ru), interview guide (SCI-PANSSRu), informant questionnaire (IQ-PANSS-Ru), and scoring form (PANSS QuikScore-Ru) were linguistically and psychometrically validated. Convergent validity between the PANSS subscale scores and total score with the Clinical Global Impressions-Severity Scale (CGI-S) were moderate (r=0.41-0.60) to high (r=0.61-0.80). Cronbach's α (0.88) verified internal consistency, and intra-class correlation coefficient (ICC) comparisons had a range of 0.83. Percentile normative data collected from 533 subjects are presented. Conclusion: This is the largest population-based study providing linguistic and psychometric validation of the PANSS-Ru. Normative data can provide clinicians with a benchmark of psychopathology and inform the efficacy of treatment interventions.

Negative Symptom Dimensions of the Positive and Negative Syndrome Scale Across Geographical Regions: Implications for Social, Linguistic, and Cultural Consistency.

Objective: Recognizing the discrete dimensions that underlie negative symptoms in schizophrenia and how these dimensions are understood across localities might result in better understanding and treatment of these symptoms. To this end, the objectives of this study were to 1) identify the Positive and Negative Syndrome Scale negative symptom dimensions of expressive deficits and experiential deficits and 2) analyze performance on these dimensions over 15 geographical regions to determine whether the items defining them manifest similar reliability across these regions. Design: Data were obtained for the baseline Positive and Negative Syndrome Scale visits of 6,889 subjects across 15 geographical regions. Using confirmatory factor analysis, we examined whether a two-factor negative symptom structure that is found in schizophrenia (experiential deficits and expressive deficits) would be replicated in our sample, and using differential item functioning, we tested the degree to which specific items from each negative symptom subfactor performed across geographical regions in comparison with the United States. Results: The two-factor negative symptom solution was replicated in this sample. Most geographical regions showed moderate-to-large differential item functioning for Positive and Negative Syndrome Scale expressive deficit items, especially N3 Poor Rapport, as compared with Positive and Negative Syndrome Scale experiential deficit items, showing that these items might be interpreted or scored differently in different regions. Across countries, except for India, the differential item functioning values did not favor raters in the United States. Conclusion: These results suggest that the Positive and Negative Syndrome Scale negative symptom factor can be better represented by a two-factor model than by a single-factor model. Additionally, the results show significant differences in responses to items representing the Positive and Negative Syndrome Scale expressive factors, but not the experiential factors, across regions. This could be due to a lack of equivalence between the original and translated versions, cultural differences with the interpretation of items, dissimilarities in rater training, or diversity in the understanding of scoring anchors. Knowing which items are challenging for raters across regions can help to guide Positive and Negative Syndrome Scale training and improve the results of international clinical trials aimed at negative symptoms.