Dataset Information

Assessing causal links between metabolic traits, inflammation and schizophrenia: a univariable and multivariable, bidirectional Mendelian-randomization study.

ABSTRACT: BACKGROUND:Blood immunoreactive biomarkers, such as C-reactive protein (CRP), and metabolic abnormalities have been associated with schizophrenia. Studies comprehensively and bidirectionally probing possible causal links between such blood constituents and liability to schizophrenia are lacking. METHODS:To disentangle putative causal links between CRP blood levels and schizophrenia in both directions, we conducted multiple univariable Mendelian-randomization (MR) analyses, ranging from fixed-effect to inverse variance-weighted (IVW), weighted-median, MR Egger and generalized summary-data-based Mendelian-randomization (GSMR) models. To prioritize metabolic risk factors for schizophrenia, a novel multivariable approach was applied: multivariable Mendelian-randomization-Bayesian model averaging (MR-BMA). RESULTS:All forward univariable MR analyses consistently showed that CRP has a protective effect on schizophrenia, whereas reverse MR analyses consistently suggested absent causal effects of schizophrenia liability on CRP blood levels. Using MR-BMA, as the top protective factors for schizophrenia we prioritized leucine and as the prime risk-factor triglycerides in medium very-low-density lipoprotein (VLDL). The five best-performing MR-BMA models provided one additional risk factor: triglycerides in large VLDL; and two additional protective factors: citrate and lactate. CONCLUSIONS:Our results add to a growing body of literature hinting at metabolic changes-in particular of triglycerides-independently of medication status in schizophrenia. We also highlight the absent effects of genetic liability to schizophrenia on CRP levels.

SUBMITTER: Lin BD

PROVIDER: S-EPMC7070229 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Assessing causal links between metabolic traits, inflammation and schizophrenia: a univariable and multivariable, bidirectional Mendelian-randomization study.

Lin Bochao D BD Alkema Anne A Peters Triinu T Zinkstok Janneke J Libuda Lars L Hebebrand Johannes J Antel Jochen J Hinney Anke A Cahn Wiepke W Adan Roger R Luykx Jurjen J JJ

International journal of epidemiology 20191001 5

<h4>Background</h4>Blood immunoreactive biomarkers, such as C-reactive protein (CRP), and metabolic abnormalities have been associated with schizophrenia. Studies comprehensively and bidirectionally probing possible causal links between such blood constituents and liability to schizophrenia are lacking.<h4>Methods</h4>To disentangle putative causal links between CRP blood levels and schizophrenia in both directions, we conducted multiple univariable Mendelian-randomization (MR) analyses, ranging ...[more]

PMID: 31504541

Similar Datasets

Project description:IntroductionThe correlation between dyslipidemia and periodontitis is revealed through epidemiological studies. However, the results are affected by several confounding factors. This study aims to elucidate the genetic causal association between circulating lipid traits and periodontitis by two-sample Mendelian randomization (MR) analysis.MethodsAfter the different screening processes, two cohorts of circulating lipid traits from the UK Biobank were used as exposure data, including five circulating lipid traits. The Periodontitis cohort was selected from the GeneLifestyle Interactions in Dental Endpoints (GLIDE) consortium as outcome data. In univariable MR, the inverse variance weighted (IVW) was used in conjunction with six additional analytical methods to assess causality. The Cochran Q test, IGX 2 statistic, MR-PRESSO, and MR-Egger intercept were used to quantify heterogeneity and pleiotropy. The multivariable MR-IVW (MVMR-IVW) and MVMR-robust were mainly used as analytical methods in the multiple MR analyses.ResultsThe IVW estimates showed that genetically predicted Apolipoprotein A1 (apo A1) [odds ratio (OR)=1.158, 95% confidence interval (CI)=1.007-1.331, P-value=0.040] was potentially associated with the risk of periodontitis, but the statistical power of the results was low. Multivariable MR analysis did not reveal any significant causal relationship between apo A1 and periodontitis (OR=0.72, 95% CI=0.36-1.41, P-value=0.34). In the validation cohort, there was also no significant causal relationship between apo A1 and periodontitis (OR=1.079, 95% CI=0.903-1.290, P-value=0.401). Meanwhile, genetically predicted Apolipoprotein B (apo B), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) (all P-values>0.05) were not significantly associated with the risk of periodontitis causal inference.ConclusionThis MR analysis was unable to provide genetic evidence for the influence of these five circulating lipid traits on periodontitis. However, a more extensive study with a more comprehensive circulating lipid profile and periodontitis data is needed due to study limitations.

Project description:BackgroundIntervertebral disc degeneration (IVDD) is a prominent contributor to chronic low back pain, impacting millions of individuals annually. Current research on disc degeneration is placing a growing emphasis on the role of the immune system in this process. Nevertheless, the precise relationship between immunity and disc degeneration remains to be fully elucidated.MethodWe obtained GWAS data for immune cells from the latest summary-level GWAS, including 6,620 individuals from Sardinian and 746,667 individuals from five global populations. Summary results for IVDD were sourced from the FinnGen consortium, comprising 20,001 cases and 164,682 controls. We conducted a comprehensive univariable Mendelian randomization (MR) analysis to explore the potential causal relationship between immune cells and IVDD. Primary estimation was carried out using Inverse-Variance Weighting (IVW). To ensure robustness, we employed additional MR methods such as MR-Egger, Weighted Median, Weighted Mode, and Simple Mode. Various tests were employed to assess pleiotropy and heterogeneity, including the Cochran Q test, leave-one-out test, MR-Egger intercept analysis and MR-PRESSO test. To account for potential confounding factors among the immune cells, we conducted a multivariable MR analysis. Finally, we investigated the possibility of a reverse association between immune cells and IVDD through bidirectional MR.ResultIn total, our study identified 15 immune cells significantly associated with IVDD through univariable MR. Among these, 9 immune cell types were indicated as potential contributors to IVDD, while 6 were found to have protective effects. Importantly, we observed no evidence of heterogeneity or pleiotropy, signifying the robustness of our results. To mitigate confounding among immune cells, we utilized multivariable MR, leading to the discovery that only 9 immune cell types exerted independent effects on IVDD. These encompassed 7 as risk factors and 2 as protective factors. Additionally, our analysis revealed a bidirectional causal relationship between CD39+ CD4+ T cell %CD4+ T cell and IVDD.ConclusionOur findings suggest a connection between immune cells and the risk of IVDD, shedding light on potential therapeutic avenues for modulating immune cell function in individuals with IVDD. However, the specific underlying mechanisms warrant further investigation in future experiments.

Project description:Background: Observational studies have identified impaired lung function accessed by forced expiratory volume in one second (FEV1), forced vital capacity (FVC) or the ratio of FEV1 over FVC (FEV1/FVC) as an independent risk factor for atrial fibrillation (AF). However, the result may be affected by confounders or reverse causality. Methods: We performed univariable MR (uvMR), multivariable MR (mvMR) and bidirectional two-sample MR to jointly estimate the causality of lung function with AF. Apart from the inverse variance weighted (IVW) approach as the main MR analysis, three complementary sensitive analyses approaches including MR-Egger regression, weighted median (WM) MR and Pleiotropy Residual Sum and Outlier (MR-PRESSO) in uvMR as well as mvMR-Egger and mvMR-PRESSO in mvMR were applied to control for pleiotropy. Linkage disequilibrium score (LDSC) regression was applied to estimate genetic correlation between lung function and AF. Results: All forward and reverse uvMR analyses consistently suggested absent causal relations between lung function and AF risk [forward IVW: odds ratio (OR)FEV1 = 1.031, 95% CI = 0.909-1.169, P = 0.630; ORFVC = 1.002, 95% CI = 0.834-1.204, P = 0.982; ORFEV1/FVC = 1.076, 95% CI = 0.966-1.199, P = 0.182; reverse IVW: ORFEV1 = 0.986, 95% CI = 0.966-1.007, P = 0.187; ORFVC = 0.985, 95% CI = 0.965-1.006, P = 0.158; ORFEV1/FVC = 0.994, 95% CI = 0.973-1.015, P = 0.545]. The forward MR-Egger showed that each standard deviation (SD) increase in FEV1/FVC was related to a higher AF risk (OR = 1.502, 95% CI = 1.178-1.915, P = 0.006) without heterogeneity (Q_pval = 0.064), but pleiotropy effect exist (intercept = -0.017, P = 0.012). However, this significant effect disappeared after adjustment of FEV1 and FVC (OR = 1.523, 95% CI = 0.445-5.217, P = 0.503) in mvMR. No evidence was found for independent causal effects of FEV1 and FVC on AF in mvMR analysis by using mvIVW method (ORFEV1 = 0.501, 95% CI = 0.056-4.457, P = 0.496; ORFVC = 1.969, 95% CI = 0.288-13.474, P = 0.490). Notably, the association between lung function and AF were replicated using the FinnGen cohort data. Conclusions: Our findings reported no coheritability between lung function and AF, and failed to find substantial causal relation between decreased lung function and risk of AF. However, lung function and AF were both associated with inflammation, which may be potential pathway, warranting further study.

Project description:BackgroundWhether the positive associations of blood lipids with psychiatric disorders are causal is uncertain. We conducted this two-sample Mendelian randomization (MR) analysis to comprehensively investigate associations of blood lipids with psychiatric disorders.MethodsUnivariable and multivariable models were established for MR analyses. Inverse variance-weighted (IVW) MR was employed as the main approach; weighted median and MR-Egger were used as sensitivity analysis methods. The possibility of violating MR assumptions was evaluated utilizing several sensitivity analyses, including heterogeneity statistics, horizontal pleiotropy statistics, single SNP analysis, leave-one-out analysis and MR-PRESSO analysis. As instrumental variables, we screened 362 independent single-nucleotide polymorphisms (SNP) related to blood lipids from a recent genome-wide association study involving 76,627 individuals of European ancestry, with a genome-wide significance level of p < 5 × 10- 8. Summary-level information for the six psychiatric disorders was extracted from Psychiatric Genomics Consortium and Alzheimer Disease Genetics Consortium.ResultsWe observed eight significant associations in univariable MR analysis, four of which were corroborated by multivariable MR (MVMR) analysis modified for the other three lipid traits: high-density lipoprotein cholesterol (HDL-C) level with the risk of PTSD (OR = 0.91, 95% CI = 0.85-0.97, p = 0.002) and AD (OR = 0.79, 95% CI = 0.71-0.88, p < 0.001) and triglycerides (TG) level with the risk of MDD (OR = 1.02, 95% CI = 1.003-1.03, p = 0.01) and panic disorder (OR = 0.83, 95% CI = 0.74-0.92, p < 0.001). In addition, four associations were not significant in MVMR analysis after adjustment for three lipid traits: total cholesterol (TC) level with the risk of PTSD, low-density lipoprotein cholesterol (LDL-C) level with the risk of MDD and AD and TG level with the risk of AD.ConclusionsOur results show that blood lipids and psychiatric disorders may be related in a causal manner. This shows that abnormal blood lipid levels may act as reliable biomarker of psychiatric disorders and as suitable targets for their prevention and treatment.

Project description:BackgroundObservational studies have investigated the effect of serum lipids on kidney function, but these findings are limited by confounding, reverse causation and have reported conflicting results. Mendelian randomization (MR) studies address this confounding problem. However, they have been conducted mostly in European ancestry individuals. We, therefore, set out to investigate the effect of lipid traits on the estimated glomerular filtration rate (eGFR) based on serum creatinine in individuals of African ancestry.MethodsWe used the two-sample and multivariable Mendelian randomization (MVMR) approaches; in which instrument variables (IV's) for the predictor (lipid traits) were derived from summary-level data of a meta-analyzed African lipid GWAS (MALG, n = 24,215) from the African Partnership for Chronic Disease Research (APCDR) (n = 13,612) & the Africa Wits-IN-DEPTH partnership for Genomics studies (AWI-Gen) dataset (n = 10,603). The outcome IV's were computed from the eGFR summary-level data of African-ancestry individuals within the Million Veteran Program (n = 57,336). A random-effects inverse variance method was used in our primary analysis, and pleiotropy was adjusted for using robust and penalized sensitivity testing. The lipid predictors for the MVMR were high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG).FindingsWe found a significant causal association between genetically predicted low-density lipoprotein (LDL) cholesterol and eGFR in African ancestry individuals β = 1.1 (95% CI [0.411-1.788]; p = 0.002). Similarly, total cholesterol (TC) showed a significant causal effect on eGFR β = 1.619 (95% CI [0.412-2.826]; p = 0.009). However, the IVW estimate showed that genetically predicted HDL-C β = -0.164, (95% CI = [-1.329 to 1.00]; p = 0.782), and TG β = -0.934 (CI = [-2.815 to 0.947]; p = 0.33) were not significantly causally associated with the risk of eGFR. In the multivariable analysis inverse-variance weighted (MVIVW) method, there was evidence for a causal association between LDL and eGFR β = 1.228 (CI = [0.477-1.979]; p = 0.001). A significant causal effect of Triglycerides (TG) on eGFR in the MVIVW analysis β = -1.3 ([-2.533 to -0.067]; p = 0.039) was observed as well. All the causal estimates reported reflect a unit change in the outcome per a 1 SD increase in the exposure. HDL showed no evidence of a significant causal association with eGFR in the MVIVW method (β = -0.117 (95% CI [-1.252 to 0.018]; p = 0.840)). We found no evidence of a reverse causal impact of eGFR on serum lipids. All our sensitivity analyses indicated no strong evidence of pleiotropy or heterogeneity between our instrumental variables for both the forward and reverse MR analysis.InterpretationIn this African ancestry population, genetically predicted higher LDL-C and TC are causally associated with higher eGFR levels, which may suggest that the relationship between LDL, TC and kidney function may be U-shaped. And as such, lowering LDL_C does not necessarily improve risk of kidney disease. This may also imply the reason why LDL_C is seen to be a poorer predictor of kidney function compared to HDL. In addition, this further supports that more work is warranted to confirm the potential association between lipid traits and risk of kidney disease in individuals of African Ancestry.FundingWellcome (220740/Z/20/Z).

Project description:BackgroundAccumulating evidence suggests that the gut microbiota and its metabolites may be involved in autoimmune hypothyroidism. However, the causal association between gut microbiota, metabolites and autoimmune hypothyroidism remains to be determined.MethodsInstrumental variables were screened from the GWAS datasets of 211 gut microbiota taxonomic groups, gut microbiota-derived metabolites, and autoimmune hypothyroidism. Univariable Mendelian randomization (MR) and multivariable Mendelian randomization (MVMR) were used to analyse the potential causal relationship between autoimmune hypothyroidism, these metabolites, or these microbiota. During the MR analysis, we alternated multiple MR methods with different model assumptions to assess the consistency and robustness of the findings: inverse variance weighted (IVW), weighted median, MR pleiotropy residual sum and outlier (MRPRESSO) and MR-Egger methods. Reverse MR analysis was performed to assess the possibility of reverse causality. Finally, enrichment analyses were used to investigate potential biofunctions.ResultsThe IVW results of univariable MR showed that the phyla Actinobacteria, genus DefluviitaleaceaeUCG011, genus Eggerthella, family Defluviitaleaceae, genus Subdoligranulum, genus RuminococcaceaeUCG011, and genus Intestinimonas were associated with autoimmune hypothyroidism. After FDR adjustment, the absence of a causal relationship between gut microbiota and autoimmune hypothyroidism (PFDR > 0.05) suggested a possible marginal association. The results on gut metabolites showed that N-(3-furoyl)glycine, pipecolate, phenylalanine, allantoin, indololactate and alanine were associated with autoimmune hypothyroidism. After FDR correction, only indololactate was associated with hypothyroidism (OR=1.592; 95% CI, 1.228-2.065; PFDR= 0.036). Family Defluviitaleaceae and genus DefluviitaleaceaeUCG011 were suggestively significant in the MVMR. The results of reverse MR analysis showed no reverse causality between autoimmune hypothyroidism and the identified gut microbiota. Enrichment analysis revealed that several key regulatory pathways were significantly enriched.ConclusionThis study supported that there were beneficial or detrimental causal effects of gut microbiota and its metabolites on autoimmune hypothyroidism risk, which provides more theoretical support for mechanistic research on the "thyroid-gut" axis.

Dataset Information

Assessing causal links between metabolic traits, inflammation and schizophrenia: a univariable and multivariable, bidirectional Mendelian-randomization study.

Publications

Assessing causal links between metabolic traits, inflammation and schizophrenia: a univariable and multivariable, bidirectional Mendelian-randomization study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets