A Mendelian randomization cytokine screen reveals IL-13 as causal factor in risk of severe COVID-19.
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ABSTRACT:
SUBMITTER: Kamali Z
PROVIDER: S-EPMC9126023 | biostudies-literature | 2022 Sep
REPOSITORIES: biostudies-literature
Publications
A Mendelian randomization cytokine screen reveals IL-13 as causal factor in risk of severe COVID-19.
Kamali Zoha Z Vonk Judith M JM Thio Chris H L CHL Vaez Ahmad A Snieder Harold H
The Journal of infection 20220523 3
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Project description:Background & aimsThe coronavirus disease 2019 (COVID-19) pandemic has witnessed more than 4.5 million deaths as of the time of writing. Whether nonalcoholic fatty liver disease (NAFLD) increases the risk for severe COVID-19 remains unclear. We sought to address this question using 2-sample Mendelian randomization (TSMR) analysis approaches in large cohorts.MethodsWe performed large-scale TSMR analyses to examine whether there is a causal relationship between NAFLD, serum alanine aminotransferase, grade of steatosis, NAFLD Activity Score, or fibrosis stage and severe COVID-19. To maximize the power of this analysis, we performed a genome-wide meta-analysis to identify single nucleotide polymorphisms associated with NAFLD. We also examined the impact of 20 major comorbid factors of NAFLD on severe COVID-19.ResultsUnivariate analysis of the UK Biobank data demonstrated a significant association between NAFLD and severe COVID-19 (odds ratio [OR], 3.06; P = 1.07 × 10-6). However, this association disappeared after demographic and comorbid factors were adjusted (OR, 1.57; P = .09). TSMR study indicated that NAFLD (OR, 0.97; P = .61), alanine aminotransferase level (OR, 1.03; P = .47), grade of steatosis (OR, 1.08; P = .41), NAFLD Activity Score (OR, 1.02; P = .39), and fibrosis stage (OR, 1.01; P = .87) were not associated with severe COVID-19. Among all NAFLD-related comorbid factors, body mass index (OR, 1.73; P = 7.65 × 10-9), waist circumference (OR, 1.76; P = 2.58 × 10-5), and hip circumference (OR, 1.33; P = 7.26 × 10-3) were the only ones demonstrated a causal impact on severe COVID-19.ConclusionsThere is no evidence supporting that NAFLD is a causal risk factor for severe COVID-19. Previous observational associations between NAFLD and COVID-19 are likely attributed to the correlation between NAFLD and obesity.
| S-EPMC8812093 | biostudies-literature
Project description:ObjectiveSMI (severe mental illness) has been identified as a risk factor for sepsis in observational studies; however, the causal association between them has yet to be firmly established. We conducted MR (mendelian randomization) to unveil the causal relationship between SMI and sepsis as well as sepsis mortality.MethodsGWAS (Genome-wide association) data for major depression and schizophrenia were selected as exposure. GWAS data for sepsis and sepsis mortality were selected as outcome. Genetic variants significantly associated with the exposure (P value<1x10-6) were selected as instruments. We primarily employed the IVW (inverse-variance weighted) method for analysis. Furthermore, we employed Cochrane's Q test to assess heterogeneity and the MR-Egger intercept test to identify horizontal pleiotropy.ResultsWe selected 108 SNPs (single nucleotide polymorphism) used to predict major depression and 260 SNPs that predicted schizophrenia. Genetically predicted major depression was suggestively linked to a higher sepsis risk (OR=1.13, 95%CI 1.02-1.26, P=0.023). In contrast, MR analysis did not find an association between schizophrenia and sepsis risk (OR=1.00, 95%CI 0.97-1.04, P=0.811). Furthermore, no significant causal evidence was found for genetically predicted SMI in sepsis mortality. Moreover, no heterogeneity and horizontal pleiotropy were detected.ConclusionOur research revealed a suggestive association between genetically predicted major depression and an elevated risk of sepsis in individuals of European ancestry. This finding can serve as a reminder for clinicians to consider the possibility of subsequent infection and sepsis in depressive patients, which may help reduce the incidence of sepsis in individuals with depression.
| S-EPMC10964346 | biostudies-literature
Project description:Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent inflammation in synovial joints and influenced by genetic and environmental factors. The immune system, comprising various cells that either exacerbate or reduce inflammation, plays a central role in RA pathogenesis. Despite extensive research, the causal relationships between immune cell phenotypes and RA remain unclear. We employed a two-sample Mendelian randomization (MR) approach to investigate the causal associations between 731 immune cell phenotypes and RA. Genetic variants, carefully selected based on rigorous criteria, served as instrumental variables to ensure analytical validity. Data on RA were derived from the FinnGen database, whereas immune cell phenotype data were obtained from the genome-wide association studies catalog. We employed 5 MR methods, including inverse variance weighted and MR Egger, to ensure robust causal inference. We assessed for pleiotropy and heterogeneity and adjusted findings using the False Discovery Rate. After False Discovery Rate adjustment (threshold < 0.05), inverse variance weighted analysis revealed potential causal relationships between 4 immune cell types and RA: CD62L- dendritic cells %dendritic cells (P = 3.88E-05; 95% confidence interval [CI] = 1.056), CD19 on IgD+ CD38- naive cells (P = 1.75E-04; 95% CI = 0.969), CD45RA on TD CD8br (P = 5.59E-04; 95% CI = 0.919), and HLA DR on CD33- HLA DR+ (P = 8.13E-05; 95% CI = 1.422). In reverse Mendelian studies, specific immune cell phenotypes were found to be associated with RA risk and progression: the percentage of memory B cells among lymphocytes (P = 2.74E-04; 95% CI = 0.861), IgD+ CD24+ cells among lymphocytes (P = 6.93E-04; 95% CI = 0.867), CD4+ CD8dim cells among lymphocytes (P = 2.92E-04; 95% CI = 0.802), CD4+ CD8dim cells among leukocytes (P = 4.37E-04; 95% CI = 0.814), and CD24 expression on IgD+CD24+ cells (P = 1.05E-04; 95% CI = 0.857). These results identify immune cell phenotypes closely linked to RA susceptibility and progression. The findings suggest that specific immune cell phenotypes are not only influenced by RA but may also contribute to its development and progression. These results offer new insights into the immunological underpinnings of RA and highlight potential targets for therapeutic intervention. Future research should focus on validating these causal relationships in diverse populations and exploring the molecular mechanisms involved.
| S-EPMC11813058 | biostudies-literature
Project description:BackgroundIdentifying causal risk factors for severe coronavirus disease 2019 (COVID-19) is critical for its prevention and treatment. Many associated pre-existing conditions and biomarkers have been reported, but these observational associations suffer from confounding and reverse causation.MethodsHere, we perform a large-scale two-sample Mendelian randomization (MR) analysis to evaluate the causal roles of many traits in severe COVID-19.ResultsOur results highlight multiple body mass index (BMI)-related traits as risk-increasing: BMI (OR: 1.89, 95% CI: 1.51-2.37), hip circumference (OR: 1.46, 1.15-1.85), and waist circumference (OR: 1.82, 1.36-2.43). Our multivariable MR analysis further suggests that the BMI-related effect might be driven by fat mass (OR: 1.63, 1.03-2.58), but not fat-free mass (OR: 1.00, 0.61-1.66). Several white blood cell counts are negatively associated with severe COVID-19, including those of neutrophils (OR: 0.76, 0.61-0.94), granulocytes (OR: 0.75, 0.601-0.93), and myeloid white blood cells (OR: 0.77, 0.62-0.96). Furthermore, some circulating proteins are associated with an increased risk of (e.g., zinc-alpha-2-glycoprotein) or protection from severe COVID-19 (e.g., prostate-associated microseminoprotein).ConclusionsOur study suggests that fat mass and white blood cells might be involved in the development of severe COVID-19. It also prioritizes potential risk and protective factors that might serve as drug targets and guide the effective protection of high-risk individuals.
| S-EPMC9053245 | biostudies-literature
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:The kidney is a vital organ with diverse biological effects and the burden of kidney function impairment is increasing in modern medicine. As the effects from kidney function on diverse biochemical parameters are yet fully understood, additional investigation to reveal the causal effects is warranted. Here we show the causal estimates from kidney function parameter, estimated glomerular filtration rate (eGFR), on 60 biochemical parameters by performing two-sample Mendelian randomization (MR) study in 337,138 white British UK Biobank participants. A higher genetically predicted eGFR was significantly associated with higher lymphocyte percentage, HDL cholesterol, and alanine aminotransferase. The causal estimates indicated that a higher genetically predicted eGFR was associated with lower urea, urate, insulin growth factor-1, and triglycerides levels. The parameters with significant but non-linear causal estimates were hemoglobin concentration, calcium, vitamin D, and urine creatinine values, identified by non-linear MR. Healthcare providers should understand that changes in eGFR may affect the identified biochemical parameters in diverse patterns. Future study is warranted to expand the knowledge of the mechanisms and clinical implications of the causal effects of eGFR on various biochemical parameters.
| S-EPMC9293908 | biostudies-literature
Project description:Causal inference is a critical step in improving our understanding of biological processes, and Mendelian randomization (MR) has emerged as one of the foremost methods to efficiently interrogate diverse hypotheses using large-scale, observational data from biobanks. Although many extensions have been developed to address the three core assumptions of MR-based causal inference (relevance, exclusion restriction, and exchangeability), most approaches implicitly assume that any putative causal effect is linear. Here, we propose PolyMR, an MR-based method that provides a polynomial approximation of an (arbitrary) causal function between an exposure and an outcome. We show that this method provides accurate inference of the shape and magnitude of causal functions with greater accuracy than existing methods. We applied this method to data from the UK Biobank, testing for effects between anthropometric traits and continuous health-related phenotypes, and found most of these (84%) to have causal effects that deviate significantly from linear. These deviations ranged from slight attenuation at the extremes of the exposure distribution, to large changes in the magnitude of the effect across the range of the exposure (e.g., a 1 kg/m2 change in BMI having stronger effects on glucose levels if the initial BMI was higher), to non-monotonic causal relationships (e.g., the effects of BMI on cholesterol forming an inverted U shape). Finally, we show that the linearity assumption of the causal effect may lead to the misinterpretation of health risks at the individual level or heterogeneous effect estimates when using cohorts with differing average exposure levels.
| S-EPMC9272036 | biostudies-literature
Project description:BackgroundThis study aims to investigate the independent causal relation between height, screen time, physical activity, sleep and myopia.MethodsInstrumental variables (IVs) for exposures and outcome were obtained from the largest publicly available genome-wide association studies (GWAS) databases. First, we performed a bidirectional univariate MR analysis using primarily the inverse variance weighted method (IVW) with height, screen time, physical activity and sleep as the exposure and myopia as the outcome to investigate the causal relationship between exposures and myopia. Sensitivity analysis was used to demonstrate its robustness. Then the multivariable MR (MVMR) and MR-based mediation approach was further used to estimate the mediating effect of potential confounders (education and time outdoors) on causality.ResultsThe results of univariate MR analysis showed that taller height (OR = 1.009, 95% CI = 1.005-1.012, p = 3.71 × 10-7), longer time on computer (OR = 1.048, 95% CI = 1.029-1.047, p = 3.87 × 10-7) and less moderate physical activity (OR = 0.976, 95% CI = 0.96-0.991 p = 2.37 × 10-3) had a total effect on the increased risk of developing myopia. Meanwhile our results did not have sufficient evidence to support the causal relationship between chronotype (p = 0.637), sleep duration (p = 0.952) and myopia. After adjusting for education, only taller height remains an independent risk factor for myopia. After adjusting for education, the causal relationship between height, screen and myopia still had statistical significance. A reverse causal relationship was not found in our study. Most of the sensitivity analyses showed consistent results with those of the IVW method.ConclusionOur MR study revealed that genetically predicted taller height, longer time on computer, less moderate physical activity increased the risk of myopia. After full adjustment for confounders, only height remained independently associated with myopia. As a complement to observational studies, the results of our analysis provide strong evidence for the improvement of myopia risk factors and provide a theoretical basis for future measures to prevent and control myopia in adolescents.
| S-EPMC11222599 | biostudies-literature
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
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