Identifying causal role of COVID-19 in immunopsychiatry models.
Ontology highlight
ABSTRACT:
SUBMITTER: Horn SR
PROVIDER: S-EPMC7256562 | biostudies-literature | 2020 Aug
REPOSITORIES: biostudies-literature
Publications
Identifying causal role of COVID-19 in immunopsychiatry models.
Horn Sarah R SR Weston Sara J SJ Fisher Philip A PA
Brain, behavior, and immunity 20200529
Similar Datasets
Project description:The SARS-CoV-2 (COVID-19) pandemic has caused millions of deaths worldwide. Early risk assessment of COVID-19 cases can help direct early treatment measures that have been shown to improve the prognosis of severe cases. Currently, circulating miRNAs have not been evaluated as canonical COVID-19 biomarkers, and identifying biomarkers that have a causal relationship with COVID-19 is imperative. To bridge these gaps, we aim to examine the causal effects of miRNAs on COVID-19 severity in this study using two-sample Mendelian randomization approaches. Multiple studies with available GWAS summary statistics data were retrieved. Using circulating miRNA expression data as exposure, and severe COVID-19 cases as outcomes, we identified ten unique miRNAs that showed causality across three phenotype groups of COVID-19. Using expression data from an independent study, we validated and identified two high-confidence miRNAs, namely, hsa-miR-30a-3p and hsa-miR-139-5p, which have putative causal effects on developing cases of severe COVID-19. Using existing literature and publicly available databases, the potential causative roles of these miRNAs were investigated. This study provides a novel way of utilizing miRNA eQTL data to help us identify potential miRNA biomarkers to make better and early diagnoses and risk assessments of severe COVID-19 cases.
| S-EPMC8700362 | biostudies-literature
Project description:COVID-19 vaccines have been instrumental tools in the fight against SARS-CoV-2 helping to reduce disease severity and mortality. At the same time, just like any other therapeutic, COVID-19 vaccines were associated with adverse events. Women have reported menstrual cycle irregularity after receiving COVID-19 vaccines, and this led to renewed fears concerning COVID-19 vaccines and their effects on fertility. Herein we devised an informatics workflow to explore the causal drivers of menstrual cycle irregularity in response to vaccination with mRNA COVID-19 vaccine BNT162b2. Our methods relied on gene expression analysis in response to vaccination, followed by network biology analysis to derive testable hypotheses regarding the causal links between BNT162b2 and menstrual cycle irregularity. Five high-confidence transcription factors were identified as causal drivers of BNT162b2-induced menstrual irregularity, namely: IRF1, STAT1, RelA (p65 NF-kB subunit), STAT2 and IRF3. Furthermore, some biomarkers of menstrual irregularity, including TNF, IL6R, IL6ST, LIF, BIRC3, FGF2, ARHGDIB, RPS3, RHOU, MIF, were identified as topological genes and predicted as causal drivers of menstrual irregularity. Our network-based mechanism reconstruction results indicated that BNT162b2 exerted biological effects similar to those resulting from prolactin signaling. However, these effects were short-lived and didn't raise concerns about long-term infertility issues. This approach can be applied to interrogate the functional links between drugs/vaccines and other side effects.
| S-EPMC10474200 | biostudies-literature
Project description: Not available
| S-BSST563 | biostudies-other
Project description:Bat sarbecovirus BANAL-236 is highly related to SARS-CoV-2 and infects human cells, albeit lacking the furin cleavage site in its spike protein. BANAL-236 replicates efficiently and pauci-symptomatically in humanized mice and in macaques, where its tropism is enteric, strongly differing from that of SARS-CoV-2. BANAL-236 infection leads to protection against superinfection by a virulent strain. We find no evidence of antibodies recognizing bat sarbecoviruses in populations in close contact with bats in which the virus was identified, indicating that such spillover infections, if they occur, are rare. Six passages in humanized mice or in human intestinal cells, mimicking putative early spillover events, select adaptive mutations without appearance of a furin cleavage site and no change in virulence. Therefore, acquisition of a furin site in the spike protein is likely a pre-spillover event that did not occur upon replication of a SARS-CoV-2-like bat virus in humans or other animals. Other hypotheses regarding the origin of the SARS-CoV-2 should therefore be evaluated, including the presence of sarbecoviruses carrying a spike with a furin cleavage site in bats.
| S-SCDT-10_15252-EMBR_202256055 | biostudies-other
Project description:Evaluating the impacts of clinical or policy interventions on health care utilization requires addressing methodological challenges for causal inference while also analyzing highly skewed data. We examine the impact of registering with a Family Medicine Group, an integrated primary care model in Quebec, on hospitalization and emergency department visits using propensity scores to adjust for baseline characteristics and marginal structural models to account for time-varying exposures. We also evaluate the performance of different marginal structural generalized linear models in the presence of highly skewed data and conduct a simulation study to determine the robustness of alternative generalized linear models to distributional model mis-specification. Although the simulations found that the zero-inflated Poisson likelihood performed the best overall, the negative binomial likelihood gave the best fit for both outcomes in the real dataset. Our results suggest that registration to a Family Medicine Group for all 3?years caused a small reduction in the number of emergency room visits and no significant change in the number of hospitalizations in the final year.
| S-EPMC5340564 | biostudies-literature
Project description:Causal models including genetic factors are important for understanding the presentation mechanisms of complex diseases. Familial aggregation and segregation analyses based on polygenic threshold models have been the primary approach to fitting genetic models to the family data of complex diseases. In the current study, an advanced approach to obtaining appropriate causal models for complex diseases based on the sufficient component cause (SCC) model involving combinations of traditional genetics principles was proposed. The probabilities for the entire population, i.e., normal-normal, normal-disease, and disease-disease, were considered for each model for the appropriate handling of common complex diseases. The causal model in the current study included the genetic effects from single genes involving epistasis, complementary gene interactions, gene-environment interactions, and environmental effects. Bayesian inference using a Markov chain Monte Carlo algorithm (MCMC) was used to assess of the proportions of each component for a given population lifetime incidence. This approach is flexible, allowing both common and rare variants within a gene and across multiple genes. An application to schizophrenia data confirmed the complexity of the causal factors. An analysis of diabetes data demonstrated that environmental factors and gene-environment interactions are the main causal factors for type II diabetes. The proposed method is effective and useful for identifying causal models, which can accelerate the development of efficient strategies for identifying causal factors of complex diseases.
| S-EPMC4391573 | biostudies-literature
Project description:Several humanized ACE2 (hACE2) mouse models have been developed for COVID-19 studies. Insertion of hACE2 at mouse Ace2 locus enables the utilization of endogenous promoter to drive its expression, better reflecting ACE2 abundance in various cell types and tissues. However, the relatively low expression of hACE2 in these mice may limit their fidelity in mimicking COVID-19 manifestations in humans and hinder their application in viral studies. In this study, we generated four hACE2 mouse models using different strategies for hACE2 expression. We found that the position of the β-globin intron within hACE2 cassette could have contrasting effects on hACE2 expression, with its placement downstream of hACE2 significantly increasing its transcription. Western blot analysis demonstrated that optimizing hACE2 codon usage further enhanced translation efficiency from all tested tissue. Consistent with elevated hACE2 expression, opt-hACE2 mice displayed more active immune response and severe COVID-19 phenotypes following SARS-CoV-2 challenging compared to other hACE2 mouse models. Thus, our study has elucidated the dual role of β-globin element in transgene expression, and highlighted that mice with optimized hACE2 codon preference could serve as a better model for SARS-CoV-2 studies.
2025-02-12 | GSE271163 | GEO
Project description:Aging is identified as a significant risk factor for severe coronavirus disease-2019 (COVID-19), often resulting in profound lung damage and mortality. Yet, the biological relationship between aging, aging-related comorbidities, and COVID-19 remains incompletely understood. This study aimed to elucidate the age-related COVID19 pathogenesis using a Hutchinson-Gilford progeria syndrome (HGPS) mouse model with humanized ACE2 receptors. Pathological features were compared between young, aged, and HGPS hACE2 mice following SAR-CoV-2 challenge. We demonstrated that young mice display robust interferon response and antiviral activity, whereas this response is attenuated in aged mice. Viral infection in aged mice results in severe respiratory tract bleeding, likely contributing a higher mortality rate. In contrast, HGPS hACE2 mice exhibit milder disease manifestations characterized by minor immune cell infiltration and dysregulation of multiple metabolic processes. Comprehensive transcriptome analysis revealed both shared and unique gene expression dynamics among different mouse groups. Collectively, our studies evaluated the impact of SARS-CoV-2 infection on progeroid syndromes using a HGPS hACE2 mouse model, which holds promise as a valuable tool for investigating COVID-19 pathogenesis in individuals with premature aging.
2024-08-28 | GSE264189 | GEO
