Browse
Submit Data
Databases
API
Help

Dataset Information

29 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Identifying Putative Causal Links between MicroRNAs and Severe COVID-19 Using Mendelian Randomization.

ABSTRACT: 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.

SUBMITTER: Li C

PROVIDER: S-EPMC8700362 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Proteome-wide Mendelian randomization identifies causal links between blood proteins and severe COVID-19.

Project description:In November 2021, the COVID-19 pandemic death toll surpassed five million individuals. We applied Mendelian randomization including >3,000 blood proteins as exposures to identify potential biomarkers that may indicate risk for hospitalization or need for respiratory support or death due to COVID-19, respectively. After multiple testing correction, using genetic instruments and under the assumptions of Mendelian Randomization, our results were consistent with higher blood levels of five proteins GCNT4, CD207, RAB14, C1GALT1C1, and ABO being causally associated with an increased risk of hospitalization or respiratory support/death due to COVID-19 (ORs = 1.12-1.35). Higher levels of FAAH2 were solely associated with an increased risk of hospitalization (OR = 1.19). On the contrary, higher levels of SELL, SELE, and PECAM-1 decrease risk of hospitalization or need for respiratory support/death (ORs = 0.80-0.91). Higher levels of LCTL, SFTPD, KEL, and ATP2A3 were solely associated with a decreased risk of hospitalization (ORs = 0.86-0.93), whilst higher levels of ICAM-1 were solely associated with a decreased risk of respiratory support/death of COVID-19 (OR = 0.84). Our findings implicate blood group markers and binding proteins in both hospitalization and need for respiratory support/death. They, additionally, suggest that higher levels of endocannabinoid enzymes may increase the risk of hospitalization. Our research replicates findings of blood markers previously associated with COVID-19 and prioritises additional blood markers for risk prediction of severe forms of COVID-19. Furthermore, we pinpoint druggable targets potentially implicated in disease pathology.

| S-EPMC8893330 | biostudies-literature

A Mendelian randomization cytokine screen reveals IL-13 as causal factor in risk of severe COVID-19.

Project description: Not available

| S-EPMC9126023 | biostudies-literature

Causal associations between severe COVID-19 and diseases of seven organs: a proteome-wide mendelian randomization study

Project description: Not available

| S-EPMC11347274 | biostudies-literature

Causal relationship between COVID-19 and chronic pain: A mendelian randomization study.

Project description:ObjectiveCOVID-19 is a highly transmissible disease that can result in long-term symptoms, including chronic pain. However, the mechanisms behind the persistence of long-COVID pain are not yet fully elucidated, highlighting the need for further research to establish causality. Mendelian randomization (MR), a statistical technique for determining a causal relationship between exposure and outcome, has been employed in this study to investigate the association between COVID-19 and chronic pain.Material and methodsThe IVW, MR Egger, and weighted median methods were employed. Heterogeneity was evaluated using Cochran's Q statistic. MR Egger intercept and MR-PRESSO tests were performed to detect pleiotropy. The Bonferroni method was employed for the correction of multiple testing. R software was used for all statistical analyses.ResultBased on the IVW method, hospitalized COVID-19 patients exhibit a higher risk of experiencing lower leg joint pain compared to the normal population. Meanwhile, the associations between COVID-19 hospitalization and back pain, headache, and pain all over the body were suggestive. Additionally, COVID-19 patients requiring hospitalization were found to have a suggestive higher risk of experiencing neck or shoulder pain and pain all over the body compared to those who did not require hospitalization. Patients with severe respiratory-confirmed COVID-19 showed a suggestive increased risk of experiencing pain all over the body compared to the normal population.ConclusionOur study highlights the link between COVID-19 severity and pain in different body regions, with implications for targeted interventions to reduce COVID-19 induced chronic pain burden.

| S-EPMC10798446 | biostudies-literature

Identifying the plasma metabolome responsible for mediating immune cell action in severe COVID-19: a Mendelian randomization investigation.

Project description:IntroductionThe immune response regulates the severity of COVID-19 (sCOVID-19). This study examined the cause-and-effect relationship between immune cell traits (ICTs) and the risk of severe COVID-19. Additionally, we discovered the potential role of plasma metabolome in modulating this risk.MethodsEmploying data from a genome-wide association study (GWAS), we conducted a two-sample Mendelian randomization (MR) assessment of 731 genetic ICTs and sCOVID-19 (5,101 cases, 1,383,241 controls) incidence. The MR analysis was utilized to further quantitate the degree of plasma metabolome-mediated regulation of immune traits in sCOVID-19.ResultsThe inverse variance weighted method recognized 2 plasma metabolites (PMs) responsible for casual associations between immune cells and sCOVID-19 risk. These included Tridecenedioate (C13:1-DC) which regulated the association between CD27 on IgD- CD38br (OR 0.804, 95% CI 0.699-0.925, p = 0.002) and sCOVID-19 risk (mediated proportion: 18.7%); arginine to citrulline ratio which controlled the relationship of CD39 on monocyte (OR 1.053, 95% CI 1.013-1.094, p = 0.009) with sCOVID-19 risk (mediated proportion: -7.11%). No strong evidence that genetically predicted sCOVID-19 influenced the aforementioned immune traits.ConclusionIn this study, we have successfully identified a cause-and-effect relationship between certain ICTs, PMs, and the likelihood of contracting severe COVID-19. Our findings can potentially improve the accuracy of COVID-19 prognostic evaluation and provide valuable insights into the underlying mechanisms of the disease.

| S-EPMC11366714 | biostudies-literature

Causal relationship between particulate matter and COVID-19 risk: A mendelian randomization study

Project description: Not available

| S-EPMC10909784 | biostudies-literature

Mendelian randomization study on the causal effects of COVID-19 on childhood intelligence.

Project description:Although individuals with coronavirus disease 2019 (COVID-19) are known to be at increased risk for other conditions resulting from pathogenic changes (including metaplastic or anaplastic) in the lungs and other organs and organ systems, it is still unknown whether COVID-19 affects childhood intelligence. The present two-sample Mendelian randomization study aims to identify the genetic causal link between COVID-19 and childhood intelligence. Four COVID-19 genetic instrumental variants (IVs) were chosen from the largest genome-wide association studies (GWAS) for COVID-19 (hospitalized vs. population) (6406 cases and 902 088 controls of European ancestry). The largest childhood intelligence GWAS (n = 12 441 individuals of European ancestry) was used to evaluate the effect of the identified COVID-19-associated genetic IVs on childhood intelligence. We found that as the genetic susceptibility to COVID-19 increased, childhood intelligence followed a decreasing trend, according to mr_egger (β = -0.156; p = 0.601; odds ratio [OR] = 0.856; 95% confidence interval [CI]: 0.522-1.405), simple mode (β = -0.126; p = 0.240; OR = 0.882; 95% CI: 0.745-1.044), and weighted mode (β = -0.121; p = 0.226; OR = 0.886; 95% CI: 0.758-1.036) analyses. This trend was further demonstrated by the weighted median (β = -0.134; p = 0.031; OR = 0.875; 95% CI: 0.774-0.988) and the inverse variance weighted (β = -0.152; p = 0.004; OR = 0.859; 95% CI: 0.776-0.952). Our analysis suggests a causal link between genetically increased COVID-19 and decreased childhood intelligence. Thus, COVID-19 may be a risk factor for declines in childhood intelligence.

| S-EPMC9088592 | biostudies-literature

Mendelian randomization analysis reveals causal relationship between obstetric-related diseases and COVID-19.

Project description:BackgroundSeveral observational studies demonstrated that pregnant individuals with COVID-19 had a higher risk of preeclampsia and preterm birth. We aimed to determine whether women with COVID-19 diagnosis had adverse pregnancy outcomes.MethodsA two-sample Mendelian randomization (MR) analysis in this study was used to evaluate the casual relationships between COVID-19 infection and obstetric-related diseases based on genome-wide association studies (GWAS) dataset. Inverse-variance weighted (IVW), MR-Egger and MR-PRESSO were used to infer the connection and estimate the pleiotropy respectively.ResultsThe significant connection was observed between COVID-19 and placental disorders with betaIVW of 1.57 and odds ratio (OR) of 4.81 (95% confidence interval [CI]: 1.05-22.05, p = 0.04). However, there were no associations between COVID-19 infection and gestational diabetes mellitus (GDM) (OR = 1.12; 95% CI: 0.85-1.45, p = 0.41), other disorders of amniotic fluid and membranes (OR = 0.90; 95% CI: 0.61-1.32, p = 0.59), Intrahepatic Cholestasis of Pregnancy (ICP) (OR = 1.42; 95% CI: 0.85-2.36, p = 0.18), birth weight (OR = 1.02; 95% CI: 0.99-1.05, p = 0.19), gestational hypertension (OR = 1.00; 95% CI: 1.00-1.00, p = 0.85), spontaneous miscarriages (OR = 1.00; 95% CI: 0.96-1.04, p = 0.90) and stillbirth (OR = 1.00; 95% CI: 0.98-1.01, p = 0.62).ConclusionThere was no direct causal relationship between COVID-19 infection and maternal and neonatal poor outcomes. Our study could alleviate the anxiety of pregnant women under the COVID-19 pandemic conditions partly.

| S-EPMC10964700 | biostudies-literature

Causal associations between COVID-19 and atrial fibrillation: A bidirectional Mendelian randomization study.

Project description:Background and aimsObservational studies showed that coronavirus disease (2019) (COVID-19) attacks universally and its most menacing progression uniquely endangers the elderly with cardiovascular disease (CVD). The causal association between COVID-19 infection or its severity and susceptibility of atrial fibrillation (AF) remains unknown.Methods and resultsThe bidirectional causal relationship between COVID-19 (including COVID-19, hospitalized COVID-19 compared with not hospitalized COVID-19, hospitalized COVID-19 compared with the general population, and severe COVID-19) and AF are determined by using two-sample Mendelian randomization (MR) analysis. Genetically predicted severe COVID-19 was not significantly associated with the risk of AF [odds ratio (OR), 1.037; 95% confidence interval (CI), 1.005-1.071; P = 0.023, q = 0.115]. In addition, genetically predicted AF was also not causally associated with severe COVID-19 (OR, 0.993; 95% CI, 0.888-1.111; P = 0.905, q = 0.905). There was no evidence to support the association between genetically determined COVID-19 and the risk of AF (OR, 1.111; 95% CI, 0.971-1.272; P = 0.127, q = 0.318), and vice versa (OR, 1.016; 95% CI, 0.976-1.058; P = 0.430, q = 0.851). Besides, no significant association was observed for hospitalized COVID-19 with AF. MR-Egger analysis indicated no evidence of directional pleiotropy.ConclusionOverall, this MR study provides no clear evidence that COVID-19 is causally associated with the risk of AF.

| S-EPMC8605875 | biostudies-literature

Causal associations of COVID-19 on neurosurgical diseases risk: a Mendelian randomization study.

Project description:Many researchers have explored the potential association between one neurosurgical disease and coronavirus disease 2019 (COVID-19), but few systematically analyzed the association and causality between COVID-19 and various neurosurgical diseases. A Mendelian randomization analysis was conducted to evaluate the causal association between COVID-19 (including critically ill COVID-19, hospitalized COVID-19, and respiratory syndrome coronavirus 2 (SARS-CoV-2) infection) and 30 neurosurgical diseases within European populations. The consequences of inverse variance weighted models suggest that genetic susceptibility of critically ill COVID-19 may increase the risk of cerebral infarction (odds ratio [OR] = 1.02; p-value = 0.006), genetic susceptibility of SARS-CoV-2 infection may increase the risk of stroke (OR = 1.02; p-value = 0.047), and conversely, genetic susceptibility of hospitalized COVID-19 may reduce the risk of pituitary adenoma and craniopharyngioma (OR = 0.90; p-value = 0.032). In addition, evidences revealed potential associations between genetic susceptibility of COVID-19 and spinal stenosis (OR = 1.03; p-value = 0.028), diffuse brain injury (OR = 1.21; p-value = 0.040) and focal brain injury (OR = 1.12; p-value = 0.040). By testing for heterogeneity and pleiotropy, the above causal conclusions are robust. In summary, our analysis shows that COVID-19 has an independent and powerful causal influence on multiple neurosurgical disorders.

| S-EPMC10840232 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data