scholarly journals Metabolome-Wide Mendelian Randomization Analysis of Emotional and Behavioral Responses to Traumatic Stress

2019 ◽  
Author(s):  
Carolina Muniz Carvalho ◽  
Frank R. Wendt ◽  
Dan J. Stein ◽  
Murray B. Stein ◽  
Joel Gelernter ◽  
...  
Keyword(s):  
Traumatic Stress ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Behavioral Responses ◽  
Traumatic Experience ◽  
Blood Metabolites ◽  
Very Low Density Lipoproteins ◽  
Genome Wide ◽  
Stressful Experience ◽  
Trauma Response

AbstractTrauma exposure is an important risk factor for several psychiatric disorders; however, the mechanisms that underlie emotional and behavioral responses to traumatic stress are unclear. To understand these mechanisms, this study investigated the genetic overlap and causal relationship between blood metabolites and traits related to trauma response using genome-wide data. Five traits related to trauma response “in the past month” ascertained in the UK Biobank (52 816<N<117 900 individuals) were considered: i) “Avoided activities or situations because of previous stressful experience” (Avoidance); ii) “Felt distant from other people” (Distant); iii) “Felt irritable or had angry outbursts” (Irritable); iv) “Felt very upset when reminded of stressful experience” (Upset); v) “Repeated disturbing thoughts of stressful experience” (Repeated Thoughts). These were investigated with respect to 52 metabolites assessed using nuclear magnetic resonance metabolomics in a previous genome-wide association study (up to 24,925 individuals of European descent). Applying linkage disequilibrium score regression (LDSC), polygenic risk scoring (PRS), and Mendelian randomization (MR), we observed that 14 metabolites were significantly correlated with trauma response traits (p<0.05); PRS of 4 metabolites (citrate (CIT); glycoprotein acetyls (GP); concentration of large very-low-density lipoproteins (VLDL) particles (LVLDLP); total cholesterol in medium particles of VLDL (MVLDLC)) were associated with traits related to trauma response (false discovery rate Q<10%). These associations were partially due to causal relationships (CIT→Upset β=-0.058, p=9.1×10−4; GP→Avoidance β=0.008, p=0.003; LVLDLP→Distant β=0.008, p=0.022; MVLDLC→Avoidance β=0.019, p=3×10−4). No reverse associations were observed. In conclusion, the genetics of certain blood-metabolites are potentially implicated in the response to traumatic experience.

Investigating Causality Between Blood Metabolites and Emotional and Behavioral Responses to Traumatic Stress: a Mendelian Randomization Study

2019 ◽  
Vol 57 (3) ◽  
pp. 1542-1552
Author(s):  
Carolina Muniz Carvalho ◽  
Frank R. Wendt ◽  
Dan J. Stein ◽  
Murray B. Stein ◽  
Joel Gelernter ◽  
...  
Keyword(s):  
Traumatic Stress ◽  
Mendelian Randomization ◽  
Behavioral Responses ◽  
Blood Metabolites

scholarly journals Using a Two-Sample Mendelian Randomization Method in Assessing the Causal Relationships Between Human Blood Metabolites and Heart Failure

2021 ◽  
Vol 8 ◽  
Author(s):  
Zixian Wang ◽  
Shiyu Chen ◽  
Qian Zhu ◽  
Yonglin Wu ◽  
Guifeng Xu ◽  
...  
Keyword(s):  
Heart Failure ◽  
Human Blood ◽  
Large Scale ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Meta Analysis ◽  
Sensitivity Analyses ◽  
Blood Metabolites ◽  
Causal Relationships

Background: Heart failure (HF) is the main cause of morbidity and mortality worldwide, and metabolic dysfunction is an important factor related to HF pathogenesis and development. However, the causal effect of blood metabolites on HF remains unclear.Objectives: Our chief aim is to investigate the causal relationships between human blood metabolites and HF risk.Methods: We used an unbiased two-sample Mendelian randomization (MR) approach to assess the causal relationships between 486 human blood metabolites and HF risk. Exposure information was obtained from Sample 1, which is the largest metabolome-based genome-wide association study (mGWAS) data containing 7,824 Europeans. Outcome information was obtained from Sample 2, which is based on the results of a large-scale GWAS meta-analysis of HF and contains 47,309 cases and 930,014 controls of Europeans. The inverse variance weighted (IVW) model was used as the primary two-sample MR analysis method and followed the sensitivity analyses, including heterogeneity test, horizontal pleiotropy test, and leave-one-out analysis.Results: We observed that 11 known metabolites were potentially related to the risk of HF after using the IVW method (P &lt; 0.05). After adding another four MR models and performing sensitivity analyses, we found a 1-SD increase in the xenobiotics 4-vinylphenol sulfate was associated with ~22% higher risk of HF (OR [95%CI], 1.22 [1.07–1.38]).Conclusions: We revealed that the 4-vinylphenol sulfate may nominally increase the risk of HF by 22% after using a two-sample MR approach. Our findings may provide novel insights into the pathogenesis underlying HF and novel strategies for HF prevention.

scholarly journals Alcohol consumption and telomere length: observational and Mendelian randomization approaches

2021 ◽  
Author(s):  
Anya Topiwala ◽  
Bernd Taschler ◽  
Klaus P Ebmeier ◽  
Steve Smith ◽  
Hang Zhou ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Telomere Length ◽  
Alcohol Use Disorder ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Prevention Strategies ◽  
Genome Wide ◽  
Non Linear ◽  
Alcoholic Drinks ◽  
Potential Threshold

Alcohols impact on telomere length, a proposed marker of biological age, is unclear. We performed the largest observational study to date and compared findings with Mendelian randomization (MR) estimates. Two-sample MR used data from a recent genome-wide association study (GWAS) of telomere length. Genetic variants were selected on the basis of associations with alcohol consumption and alcohol use disorder (AUD). Non-linear MR employed UK Biobank individual data. MR analyses suggest a causal relationship between alcohol and telomere length: both genetically predicted alcohol traits were inversely associated with telomere length. 1 S.D. higher genetically-predicted log-transformed alcoholic drinks weekly had a -0.07 S.D. effect on telomere length (95% confidence interval [CI]:-0.14 to -0.01); genetically-predicted AUD -0.06 S.D. effect (CI:-0.10 to -0.02). Results were consistent across methods and independent from smoking. Non-linear analyses indicated a potential threshold relationship between alcohol and telomere length. Our findings have implications for potential aging-related disease prevention strategies.

scholarly journals Tuberculosis infection and lung adenocarcinoma: Mendelian randomization and pathway analysis of genome-wide association study data from never-smoking Asian women

Genomics ◽  
2020 ◽  
Vol 112 (2) ◽  
pp. 1223-1232
Author(s):  
Jason Y.Y. Wong ◽  
Han Zhang ◽  
Chao A. Hsiung ◽  
Kouya Shiraishi ◽  
Kai Yu ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Association Study ◽  
Pathway Analysis ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Study Data ◽  
Tuberculosis Infection ◽  
Genome Wide Association ◽  
Asian Women ◽  
Genome Wide

scholarly journals Assessing causality in associations between cannabis use and schizophrenia risk: a two-sample Mendelian randomization study

2016 ◽  
Vol 47 (5) ◽  
pp. 971-980 ◽  
Author(s):  
S. H. Gage ◽  
H. J. Jones ◽  
S. Burgess ◽  
J. Bowden ◽  
G. Davey Smith ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Positive Control ◽  
Negative Control ◽  
Study Data ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Genome Wide Data

BackgroundObservational associations between cannabis and schizophrenia are well documented, but ascertaining causation is more challenging. We used Mendelian randomization (MR), utilizing publicly available data as a method for ascertaining causation from observational data.MethodWe performed bi-directional two-sample MR using summary-level genome-wide data from the International Cannabis Consortium (ICC) and the Psychiatric Genomics Consortium (PGC2). Single nucleotide polymorphisms (SNPs) associated with cannabis initiation (p < 10−5) and schizophrenia (p < 5 × 10−8) were combined using an inverse-variance-weighted fixed-effects approach. We also used height and education genome-wide association study data, representing negative and positive control analyses.ResultsThere was some evidence consistent with a causal effect of cannabis initiation on risk of schizophrenia [odds ratio (OR) 1.04 per doubling odds of cannabis initiation, 95% confidence interval (CI) 1.01–1.07, p = 0.019]. There was strong evidence consistent with a causal effect of schizophrenia risk on likelihood of cannabis initiation (OR 1.10 per doubling of the odds of schizophrenia, 95% CI 1.05–1.14, p = 2.64 × 10−5). Findings were as predicted for the negative control (height: OR 1.00, 95% CI 0.99–1.01, p = 0.90) but weaker than predicted for the positive control (years in education: OR 0.99, 95% CI 0.97–1.00, p = 0.066) analyses.ConclusionsOur results provide some that cannabis initiation increases the risk of schizophrenia, although the size of the causal estimate is small. We find stronger evidence that schizophrenia risk predicts cannabis initiation, possibly as genetic instruments for schizophrenia are stronger than for cannabis initiation.

scholarly journals Inferring Causal Relationships Between Risk Factors and Outcomes from Genome-Wide Association Study Data

2018 ◽  
Vol 19 (1) ◽  
pp. 303-327 ◽  
Author(s):  
Stephen Burgess ◽  
Christopher N. Foley ◽  
Verena Zuber
Keyword(s):  
Risk Factor ◽  
Genetic Variants ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Single Gene ◽  
Study Data ◽  
Causal Inferences ◽  
Genome Wide ◽  
Multiple Regions ◽  
Polygenic Analysis

An observational correlation between a suspected risk factor and an outcome does not necessarily imply that interventions on levels of the risk factor will have a causal impact on the outcome (correlation is not causation). If genetic variants associated with the risk factor are also associated with the outcome, then this increases the plausibility that the risk factor is a causal determinant of the outcome. However, if the genetic variants in the analysis do not have a specific biological link to the risk factor, then causal claims can be spurious. We review the Mendelian randomization paradigm for making causal inferences using genetic variants. We consider monogenic analysis, in which genetic variants are taken from a single gene region, and polygenic analysis, which includes variants from multiple regions. We focus on answering two questions: When can Mendelian randomization be used to make reliable causal inferences, and when can it be used to make relevant causal inferences?

scholarly journals Genetic Architecture of Abdominal Aortic Aneurysm in the Million Veteran Program

Circulation ◽  
2020 ◽  
Vol 142 (17) ◽  
pp. 1633-1646 ◽  
Author(s):  
Derek Klarin ◽  
Shefali Setia Verma ◽  
Renae Judy ◽  
Ozan Dikilitas ◽  
Brooke N. Wolford ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Family History ◽  
Odds Ratio ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Risk Variants ◽  
Genome Wide ◽  
Abdominal Aortic ◽  
A Genome ◽  
Current Screening

Background: Abdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality; however, its genetic determinants remain incompletely defined. In total, 10 previously identified risk loci explain a small fraction of AAA heritability. Methods: We performed a genome-wide association study in the Million Veteran Program testing ≈18 million DNA sequence variants with AAA (7642 cases and 172 172 controls) in veterans of European ancestry with independent replication in up to 4972 cases and 99 858 controls. We then used mendelian randomization to examine the causal effects of blood pressure on AAA. We examined the association of AAA risk variants with aneurysms in the lower extremity, cerebral, and iliac arterial beds, and derived a genome-wide polygenic risk score (PRS) to identify a subset of the population at greater risk for disease. Results: Through a genome-wide association study, we identified 14 novel loci, bringing the total number of known significant AAA loci to 24. In our mendelian randomization analysis, we demonstrate that a genetic increase of 10 mm Hg in diastolic blood pressure (odds ratio, 1.43 [95% CI, 1.24–1.66]; P =1.6×10 −6 ), as opposed to systolic blood pressure (odds ratio, 1.06 [95% CI, 0.97–1.15]; P =0.2), likely has a causal relationship with AAA development. We observed that 19 of 24 AAA risk variants associate with aneurysms in at least 1 other vascular territory. A 29-variant PRS was strongly associated with AAA (odds ratio PRS , 1.26 [95% CI, 1.18–1.36]; P PRS =2.7×10 −11 per SD increase in PRS), independent of family history and smoking risk factors (odds ratio PRS+family history+smoking , 1.24 [95% CI, 1.14–1.35]; P PRS =1.27×10 −6 ). Using this PRS, we identified a subset of the population with AAA prevalence greater than that observed in screening trials informing current guidelines. Conclusions: We identify novel AAA genetic associations with therapeutic implications and identify a subset of the population at significantly increased genetic risk of AAA independent of family history. Our data suggest that extending current screening guidelines to include testing to identify those with high polygenic AAA risk, once the cost of genotyping becomes comparable with that of screening ultrasound, would significantly increase the yield of current screening at reasonable cost.

Genetically determined atrial fibrillation and risk of stroke: a Mendelian randomization study

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
J Fill ◽  
A Fokina ◽  
G Klappacher
Keyword(s):  
Atrial Fibrillation ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Study Data ◽  
Genome Wide Association ◽  
Large Artery ◽  
Validation Sample ◽  
Genome Wide ◽  
Genetically Determined ◽  
Genetic Instruments

Abstract Background Based on observational evidence, atrial fibrillation is a well-established risk factor of stroke to be considered for antithrombotic treatment in presence of additional clinical conditions derived from multivariate risk models. Although biologically plausible, it however still is unknown whether this association is causal and confined to the embolic stroke subtype. Purpose Our objective was to explore whether genetically determined manifestation of atrial fibrillation was associated with stroke and its etiologic subtypes by conducting a 2-sample Mendelian randomization (MR) study on publicly available summary statistics from GWAS consortia. Methods Genetic instruments for atrial fibrillation were obtained from the AFGen Consortium comprising 17,931 cases and 115,142 controls. Their associations with stroke and stroke subtypes were evaluated in the MEGASTROKE genome-wide association study data set (67 162 cases; 454 450 controls) applying inverse variance–weighted meta-analysis, weighted-median analysis, Mendelian randomization–Egger regression, and multivariable Mendelian randomization. The dataset of Nielsen et al. comprising a total of 60,620 cases with atrial fibrillation and 970,216 controls of European ancestry from six contributing studies was used as an independent validation sample. Genetic instruments for atrial fibrillation were further tested for association with etiologically related traits by using publicly available genome-wide association study data. Results Genetic predisposition to atrial fibrillation was associated with higher risk of any stroke (beta coefficient [b] ± standard error [se] = 0.22±0.04; P=0.0001), any ischemic stroke (b ± se = 0.24±0.05; P=0.0003), and cardioembolic stroke (b ± se = 0.76±0.10; P&lt;0.0001), but not with small-vessel stroke or large artery stroke, see figure. Analyses in the validation sample showed similar associations (any stroke: b ± se = 0.19±0.04; P&lt;0.0001; any ischemic stroke: b ± se = 0.21±0.04; P&lt;0.0001; cardioembolic stroke: b ± se = 0.82±0.13; P&lt;0.0001). Genetically determined atrial fibrillation was further weakly associated with chronic kidney disease (b ± se = 0.10±0.04; P=0.0261), but not with coronary artery disease and myocardial infarction or any other available phenotype. Conclusions Genetic predisposition to atrial fibrillation is associated with higher risk of any stroke, mainly driven by the ischemic and cardioembolic subtypes. In contrast, large artery and small-vessel strokes did not exhibit a causal relationship with atrial fibrillation. Funding Acknowledgement Type of funding source: Public hospital(s). Main funding source(s): Medical University of Vienna, Austria

scholarly journals Mendelian randomization analysis identified genes pleiotropically associated with central corneal thickness

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Zhikun Yang ◽  
Jingyun Yang ◽  
Di Liu ◽  
Weihong Yu
Keyword(s):  
Multiple Testing ◽  
Central Corneal Thickness ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Open Angle Glaucoma ◽  
East Asian ◽  
Corneal Thickness ◽  
European Ancestry ◽  
Genome Wide ◽  
Eqtl Data

Abstract Objective To prioritize genes that were pleiotropically or potentially causally associated with central corneal thickness (CCT). Methods We applied the summary data-based Mendelian randomization (SMR) method integrating summarized data of genome-wide association study (GWAS) on CCT and expression quantitative trait loci (eQTL) data to identify genes that were pleiotropically associated with CCT. We performed separate SMR analysis using CAGE eQTL data and GTEx eQTL data. SMR analyses were done for participants of European and East Asian ancestries, separately. Results We identified multiple genes showing pleiotropic association with CCT in the participants of European ancestry. CLIC3 (ILMN_1796423; PSMR = 4.15 × 10− 12), PTGDS (ILMN_1664464; PSMR = 6.88 × 10− 9) and C9orf142 (ILMN_1761138; PSMR = 8.09 × 10− 9) were the top three genes using the CAGE eQTL data, and RP11-458F8.4 (ENSG00000273142.1; PSMR = 5.89 × 10− 9), LCNL1 (ENSG00000214402.6; PSMR = 5.67 × 10− 8), and PTGDS (ENSG00000107317.7; PSMR = 1.92 × 10− 7) were the top three genes using the GTEx eQTL data. No genes showed significantly pleiotropic association with CCT in the participants of East Asian ancestry after correction for multiple testing. Conclusion We identified several genes pleiotropically associated with CCT, some of which represented novel genes influencing CCT. Our findings provided important leads to a better understanding of the genetic factors influencing CCT, and revealed potential therapeutic targets for the treatment of primary open-angle glaucoma and keratoconus.

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