Dataset Information

Plasma Insulin-like Growth Factor Binding Protein 7 Contributes Causally to ARDS 28-Day Mortality: Evidence From Multistage Mendelian Randomization.

ABSTRACT:

Background

ARDS is a devastating syndrome with heterogeneous subtypes, but few causal biomarkers have been identified.

Research question

Would multistage Mendelian randomization identify new causal protein biomarkers for ARDS 28-day mortality?

Study design and methods

Three hundred moderate to severe ARDS patients were selected randomly from the Molecular Epidemiology of ARDS cohort for proteomics analysis. Orthogonal projections to latent structures discriminant analysis was applied to detect the association between proteins and ARDS 28-day mortality. Candidate proteins were analyzed using generalized summary data-based Mendelian randomization (GSMR). Protein quantitative trait summary statistics were retrieved from the Efficiency and safety of varying the frequency of whole blood donation (INTERVAL) study (n = 2,504), and a genome-wide association study for ARDS was conducted from the Identification of SNPs Predisposing to Altered Acute Lung Injury Risk (iSPAAR) consortium study (n = 534). Causal mediation analysis detected the role of platelet count in mediating the effect of protein on ARDS prognosis.

Results

Plasma insulin-like growth factor binding protein 7 (IGFBP7) moderately increased ARDS 28-day mortality (OR, 1.11; 95% CI, 1.04-1.19; P = .002) per log2 increase. GSMR analysis coupled with four other Mendelian randomization methods revealed IGFBP7 as a causal biomarker for ARDS 28-day mortality (OR, 2.61; 95% CI, 1.33-5.13; P = .005). Causal mediation analysis indicated that the association between IGFBP7 and ARDS 28-day mortality is mediated by platelet count (OR, 1.03; 95% CI, 1.02-1.04; P = .01).

Interpretation

We identified plasma IGFBP7 as a novel causal protein involved in the pathogenesis of ARDS 28-day mortality and platelet function in ARDS, a topic for further experimental and clinical investigation.

SUBMITTER: Dong X

PROVIDER: S-EPMC8501007 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Plasma Insulin-like Growth Factor Binding Protein 7 Contributes Causally to ARDS 28-Day Mortality: Evidence From Multistage Mendelian Randomization.

Dong Xuesi X Zhu Zhaozhong Z Wei Yongyue Y Ngo Debby D Zhang Ruyang R Du Mulong M Huang Hui H Lin Lijuan L Tejera Paula P Su Li L Chen Feng F Ahasic Amy M AM Thompson B Taylor BT Meyer Nuala J NJ Christiani David C DC

Chest 20201112 3

<h4>Background</h4>ARDS is a devastating syndrome with heterogeneous subtypes, but few causal biomarkers have been identified.<h4>Research question</h4>Would multistage Mendelian randomization identify new causal protein biomarkers for ARDS 28-day mortality?<h4>Study design and methods</h4>Three hundred moderate to severe ARDS patients were selected randomly from the Molecular Epidemiology of ARDS cohort for proteomics analysis. Orthogonal projections to latent structures discriminant analysis w ...[more]

PMID: 33189655

Similar Datasets

Project description:BackgroundAn increasing body of evidence suggests that neuroinflammation is one of the key drivers of late-onset Alzheimer's disease (LOAD) pathology. Due to the increased permeability of the blood-brain barrier (BBB) in older adults, peripheral plasma proteins can infiltrate the central nervous system (CNS) and drive neuroinflammation through interactions with neurons and glial cells. Because these inflammatory factors are heritable, a greater understanding of their genetic relationship with LOAD could identify new biomarkers that contribute to LOAD pathology or offer protection against it.MethodsWe used a genome-wide association study (GWAS) of 90 different plasma proteins (n = 17,747) to create polygenic scores (PGSs) in an independent discovery (cases = 1,852 and controls = 1,990) and replication (cases = 799 and controls = 778) cohort. Multivariate logistic regression was used to associate the plasma protein PGSs with LOAD diagnosis while controlling for age, sex, principal components 1-2, and the number of APOE-e4 alleles as covariates. After meta-analyzing the PGS-LOAD associations between the two cohorts, we then performed a two-sample Mendelian randomization (MR) analysis using the summary statistics of significant plasma protein level PGSs in the meta-analysis as an exposure, and a GWAS of clinically diagnosed LOAD (cases = 21,982, controls = 41,944) as an outcome to explore possible causal relationships between the two.ResultsWe identified four plasma protein level PGSs that were significantly associated (FDR-adjusted p < 0.05) with LOAD in a meta-analysis of the discovery and replication cohorts: CX3CL1, hepatocyte growth factor (HGF), TIE2, and matrix metalloproteinase-3 (MMP-3). When these four plasma proteins were used as exposures in MR with LOAD liability as the outcome, plasma levels of HGF were inferred to have a negative causal relationship with the disease when single-nucleotide polymorphisms (SNPs) used as instrumental variables were not restricted to cis-variants (OR/95%CI = 0.945/0.906-0.984, p = 0.005).ConclusionOur results show that plasma HGF has a negative causal relationship with LOAD liability that is driven by pleiotropic SNPs possibly involved in other pathways. These findings suggest a low transferability between PGS and MR approaches, and future research should explore ways in which LOAD and the plasma proteome may interact.

Project description:Observational studies have indicated an association between cancer and the occurrence of sepsis, with an increased risk of mortality in cancer-related sepsis. However, whether a causal relationship exists between the two remains unknown. Summary statistics of thirteen cancers from the largest available genome-wide association studies (GWAS) of GWAS catalog and FinnGen biobank were extracted for the MR analysis. GWAS data for sepsis and its 28-day mortality were obtained from MRC-IEU. Univariable, multivariable, and reverse MR analyses were employed to explore potential associations between cancers and sepsis and its 28-day mortality. Moreover, a two-step mediation MR analysis was performed to investigate independent positive causal relationships between cancers and sepsis and its 28-day mortality. In univariable Mendelian randomization (MR) analysis, significant causal relationships were found between genetically predicted lung cancer (OR = 1.17, 95% CI = 1.08-1.26, adjusted p = 0.001), squamous cell lung carcinoma (OR = 1.10, 95% CI = 1.02-1.18, adjusted p = 0.042), lung adenocarcinoma (OR = 1.12, 95% CI = 1.03-1.21, adjusted p = 0.032), small cell lung carcinoma (OR = 1.07, 95% CI = 1.02-1.12, adjusted p = 0.031), and sepsis. Subsequent multivariable MR analysis revealed that these three types of lung cancer were independently associated with the risk of sepsis. Additionally, a causal relationship was found between lung cancer and 28-day mortality from sepsis, while no causal link was observed between non-solid tumors and the onset or death of sepsis. Reverse MR analysis did not indicate a potential for sepsis to trigger the onset of cancers. Furthermore, TRAIL was found to have promotive effects on the occurrence and mortality of sepsis. Lung cancer causally correlates with increased sepsis occurrence and 28-day mortality, as evidenced by Mendelian Randomization analysis. Genetic predispositions enhance this risk, underscoring the potential of genetic profiling to guide early, precise sepsis interventions in these patients.

Project description:BackgroundThe effects of heart failure (HF) on cortical brain structure remain unclear. Therefore, the present study aimed to investigate the causal effects of heart failure on cortical structures in the brain using Mendelian randomization (MR) analysis.MethodsWe conducted a two-sample MR analysis utilizing genetically-predicted HF trait, left ventricular ejection fraction (LVEF), and N-terminal prohormone brain natriuretic peptide (NT-proBNP) levels to examine their effects on the cortical surface area (SA) and thickness (TH) across 34 cortical brain regions. Genome-wide association study summary data were extracted from studies by Rasooly (1,266,315 participants) for HF trait, Schmidt (36,548 participants) for LVEF, the SCALLOP consortium (21,758 participants) for NT-proBNP, and the ENIGMA Consortium (51,665 participants) for cortical SA and TH. A series of MR analyses were employed to exclude heterogeneity and pleiotropy, ensuring the stability of the results. Given the exploratory nature of the study, p-values between 1.22E-04 and 0.05 were considered suggestive of association, and p-values below 1.22E-04 were defined as statistically significant.ResultsIn this study, we found no significant association between HF and cortical TH or SA (all p > 1.22E-04). We found that the HF trait and elevated NT-proBNP levels were not associated with cortical SA, but were suggested to decrease cortical TH in the pars orbitalis, lateral orbitofrontal cortex, temporal pole, lingual gyrus, precuneus, and supramarginal gyrus. Reduced LVEF was primarily suggested to decrease cortical SA in the isthmus cingulate gyrus, frontal pole, postcentral gyrus, cuneus, and rostral middle frontal gyrus, as well as TH in the postcentral gyrus. However, it was suggested to causally increase in the SA of the posterior cingulate gyrus and medial orbitofrontal cortex and the TH of the entorhinal cortex and superior temporal gyrus.ConclusionWe found 15 brain regions potentially affected by HF, which may lead to impairments in cognition, emotion, perception, memory, language, sensory processing, vision, and executive control in HF patients.

Project description:PurposeTo reveal the causality between retinal vascular density (VD), fractal dimension (FD), and brain cortex structure using Mendelian randomization (MR).DesignCross-sectional study.ParticipantsGenome-wide association studies of VD and FD involving 54 813 participants from the United Kingdom Biobank were used. The brain cortical features, including the cortical thickness (TH) and surface area (SA), were extracted from 51 665 patients across 60 cohorts. Surface area and TH were measured globally and in 34 functional regions using magnetic resonance imaging.MethodsBidirectional univariable MR (UVMR) was used to detect the causality between FD, VD, and brain cortex structure. Multivariable MR (MVMR) was used to adjust for confounding factors, including body mass index and blood pressure.Main outcome measuresThe global and regional measurements of brain cortical SA and TH.ResultsAt the global level, higher VD is related to decreased TH (β = -0.0140 mm, 95% confidence interval: -0.0269 mm to -0.0011 mm, P = 0.0339). At the functional level, retinal FD is related to the TH of banks of the superior temporal sulcus and transverse temporal region without global weighted, as well as the SA of the posterior cingulate after adjustment. Vascular density is correlated with the SA of subregions of the frontal lobe and temporal lobe, in addition to the TH of the inferior temporal, entorhinal, and pars opercularis regions in both UVMR and MVMR. Bidirectional MR studies showed a causation between the SA of the parahippocampal and cauda middle frontal gyrus and retinal VD. No pleiotropy was detected.ConclusionsFractal dimension and VD causally influence the cortical structure and vice versa, indicating that the retinal microvasculature may serve as a biomarker for cortex structural changes. Our study provides insights into utilizing noninvasive fundus images to predict cortical structural deteriorations and neuropsychiatric disorders.Financial disclosuresThe author(s) have no proprietary or commercial interest in any materials discussed in this article.

Dataset Information

Plasma Insulin-like Growth Factor Binding Protein 7 Contributes Causally to ARDS 28-Day Mortality: Evidence From Multistage Mendelian Randomization.

Background

Research question

Study design and methods

Results

Interpretation

Publications

Plasma Insulin-like Growth Factor Binding Protein 7 Contributes Causally to ARDS 28-Day Mortality: Evidence From Multistage Mendelian Randomization.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets