Oxidative Stress and Psychiatric Disorders: Evidence from the Bidirectional Mendelian Randomization Study.
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ABSTRACT:
SUBMITTER: Lu Z
PROVIDER: S-EPMC9312055 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionAlthough the relationship between psychiatric disorders and Parkinson's disease (PD) has attracted continuous research attention, the causal linkage between them has not reached a definite conclusion.MethodsTo identify the causal relationship between psychiatric disorders and PD, we used public summary-level data from the most recent and largest genome-wide association studies (GWASs) on psychiatric disorders and PD to conduct a bidirectional two-sample Mendelian randomization (MR). We applied stringent control steps in instrumental variable selection using the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) method to rule out pleiotropy. The inverse-variance weighted (IVW) method was used to identify the causal relationship between psychiatric disorders and PD. Multiple MR analysis methods, including MR-Egger, weighted-median, and leave-one-out analyses, were used for sensitivity analysis, followed by heterogeneity tests. Further validation and reverse MR analyses were conducted to strengthen the results of the forward MR analysis.ResultsThe lack of sufficient estimation results could suggest a causal relationship between psychiatric disorders and PD in the forward MR analysis. However, the subsequent reverse MR analysis detected a causal relationship between PD and bipolar disorder (IVW: odds ratios [OR] =1.053, 95% confidence interval [CI] =1.02-1.09, p = 0.001). Further analysis demonstrated a causal relationship between genetically predicted PD and the risk of bipolar disorder subtype. No pleiotropy or heterogeneity was detected in the analyses.DiscussionOur study suggested that while psychiatric disorders and traits might play various roles in the risk of developing PD, PD might also be involved in the risk of developing psychiatric disorders.
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Project description:BackgroundObservational studies have suggested the potential associations between atopic dermatitis (AD) and psychiatric disorders. However, the causal relationship between them remains uncertain. This study aimed to evaluate the potential bidirectional causal relationship between AD and psychiatric disorders, including autism spectrum disorder (ASD), major depressive disorder (MDD), attention deficit hyperactivity disorder (ADHD), bipolar disorder (BD), anorexia nervosa (AN), Tourette syndrome (TS), schizophrenia, and anxiety.MethodsBidirectional two-sample Mendelian randomization (MR) was employed to elucidate the causality between AD and psychiatric disorders, using summary statistics from the most comprehensive genome-wide association studies conducted on AD (Ncases = 60,653, Ncontrols = 804,329). Psychiatric disorders were derived from the Psychiatric Genomics Consortium and were independent of AD data sources. The MR analysis entailed the implementation of multiple methods, including the inverse variance weighted method, MR-Egger regression method, weighted median method, simple mode method, and weighted mode method.ResultsBidirectional two-sample MR analysis uncovered significant causal associations between AD and severe psychiatric disorders. Specifically, liability to AD was associated with increased risk of ADHD (OR = 1.116; 95% CI: [1.009, 1.234]; P = 0.033) and ASD (OR = 1.131; 95% CI: [1.023, 1.251]; P = 0.016). Additionally, evidence suggested that liability to ADHD (OR = 1.112; 95% CI: [1.094, 1.130]; P = 9.20e-40), liability to AN (OR = 1.1; 95% CI: [1.068, 1.134]; P = 4.45e-10) and liability to BD (OR = 1.067; 95% CI: [1.009, 1.128]; P = 0.023) were associated with an increased risk of AD. Only the causal association between AD and ASD was independent of the reverse effect bias. These causal associations were robust and not affected by biases of heterogeneity and horizontal pleiotropy.ConclusionsOur study emphasizes the significant causal association between AD and an increased risk of ASD, and also identifying BD and AN as risk factors for AD.
| S-EPMC10763185 | biostudies-literature
Project description:BackgroundObservational studies have shown associations between psychiatric disorders and osteoarthritis (OA). However, the causal impact of different psychiatric disorder types on specific sites of osteoarthritis remains unclear. This study aimed to comprehensively understand the potential causal associations between psychiatric disorders and osteoarthritis using Mendelian randomization (MR) analysis.MethodsWe collected data from genome-wide association studies of knee osteoarthritis (KOA) (n = 403,124), hip osteoarthritis (HOA) (n = 393,873), osteoarthritis of the knee or hip (KHOA) (n = 417,596), as well as three psychiatric disorders: bipolar disorder (n = 41,917), major depressive disorder (n = 170,756), and schizophrenia (n = 76,755) among European populations. We applied bidirectional univariate and multivariate MR analyses, including inverse variance weighted, Mendelian randomization-Egger, weighted median, simple mode, and weighted mode. We considered p < .05 as a criterion for identifying potential evidence of association. Bonferroni correction was used for multiple tests.ResultsOur univariate MR analysis results demonstrated that bipolar disorder is a protective factor for KOA (OR = 0.90, 95% CI = 0.83 to 0.97, p = 0.0048) and may also be protective for KHOA (p = 0.02). Conversely, major depression has a positive causal effect on both KOA (OR = 1.27; 95% CI = 1.08 to 1.49; p = 0.0036) and KHOA (OR = 1.24; 95% CI = 1.12 to 1.37; p = 3.62×10-05 ). Furthermore, our analysis suggested that KHOA may be a risk factor for major depression (OR = 1.06; 95% CI = 1.00 to 1.12; p = 0.0469) in reverse MR. After adjusting smoking (OR = 1.46; 95% CI = 1.19 to 1.65; p = 0.0032) and body mass index (OR = 1.44; 95% CI = 1.09 to 1.81; p = 8.56×10-04 ), the casual association between major depression and KHOA remained.ConclusionOur study indicates that major depression is a great risk factor for KHOA, increasing the likelihood of their occurrence. However, further in-depth studies will be required to validate these results and elucidate the underlying molecular mechanisms.
| S-EPMC10869882 | biostudies-literature
Project description:Observational studies have investigated the impact of calcium homeostasis on psychiatric disorders; however, the causality of associations is yet to be established. Bidirectional Mendelian randomization (MR) analysis of calcium homeostasis hormones was conducted on nine psychiatric disorders. Calcium, serum 25-hydroxyvitamin D levels (25OHD), parathyroid hormone, and fibroblast growth factor 23 are the major calcium homeostasis hormones. The causality was evaluated by the inverse variance weighted method (IVW) and the MR Steiger test, while Cochran's Q test, the MR-Egger intercept test, funnel plot, and the leave-one-out method were used for sensitivity analyses. Bonferroni correction was used to determine the causative association features (p < 6.94 × 10-4). Schizophrenia (SCZ) was significantly associated with decreased 25OHD concentrations with an estimated effect of -0.0164 (Prandom-effect IVW = 2.39 × 10-7). In the Multivariable MR (MVMR) analysis adjusting for potentially confounding traits including body mass index, obesity, mineral supplements (calcium, fish oil, and vitamin D) and outdoor time (winter and summer), the relationship between SCZ and 25OHD remained. The genetically predicted autism spectrum disorder and bipolar disorder were also nominally associated with decreased 25OHD. This study provided evidence for a causal effect of psychiatric disorders on calcium homeostasis. The clinical monitoring of 25OHD levels in patients with psychiatric disorders is beneficial.
| S-EPMC10535008 | biostudies-literature
Project description:BackgroundPrevious researches have demonstrated a connection between psychiatric disorders and cardiovascular diseases (CVDs), but the cause-and-effect relationship is still unclear. To that goal, the mendelian randomization (MR) method was used to study the causal link between psychiatric disorders and CVDs.MethodsGenome-wide association studies (GWAS) data were collected for four CVDs, including coronary artery disease (n = 547,261), atrial fibrillation (n = 537,409), heart failure (n = 977,323) and ischemic stroke (n = 440,328). Summary data for four psychiatric disorders, including bipolar disorder (n = 51,710), major depressive disorder (n = 480,359), schizophrenia (n = 127,906) and attention deficit hyperactivity disorder (n = 55,374), came from the Psychiatric Genomics Consortium (PGC). All participants were European. The IVW method was mainly used, and the reliability of the results was increased using sensitivity analyses such as MR-Egger, Cochrane's Q test, MR-PRESSO and leave-one-out.ResultsMR revealed that the attention deficit hyperactivity disorder was linked to an increased risk of atrial fibrillation (OR, 1.085; 95% CI, 1.021-1.153; P = 0.008), heart failure (OR, 1.117; 95% CI, 1.044-1.195; P = 0.001), and ischemic stroke (OR, 1.146; 95% CI, 1.052-1.248; P = 0.002). The schizophrenia was linked to an increased risk of heart failure (OR, 1.035; 95% CI, 1.006-1.066; P = 0.017), but was found to be suggestively inverse associated with coronary artery disease (OR, 0.969; 95% CI, 0.941-0.997; P = 0.03). The major depressive disorder was associated with higher odds of coronary artery disease (OR, 1.109; 95% CI, 1.018-1.208; P = 0.018), while the bipolar disorder was linked to a reduced incidence of coronary artery disease (OR, 0.894; 95% CI, 0.831-0.961; P = 0.002) and heart failure (OR, 0.889; 95% CI, 0.829-0.955; P = 0.001). There were no clear relationships between other psychiatric disorders and CVDs.ConclusionThe results provide genetic proof of a possible causal relationship between psychiatric disorders and CVDs. These results imply that psychiatric disorders may be the cause of some CVDs, and that some abnormal mental states may increase or reduce the likelihood of CVDs, providing guidance for the CVDs prevention.
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Project description:AimsSleep disturbance is an important factor in the pathophysiology and progression of psychiatric disorders, but whether it is a cause, or a downstream effect is still not clear.MethodsTo investigate causal relationships between three sleep-associated traits and seven psychiatric diseases, we used genetic variants related to insomnia, chronotype and sleep duration to perform a two-sample bidirectional Mendelian randomisation analysis. Summary-level data on psychiatric disorders were extracted from the Psychiatric Genomics Consortium. Effect estimates were obtained by using the inverse-variance-weighted (IVW), weights modified IVW, weighted-median methods, MR-Egger regression, MR pleiotropy residual sum and outlier (MR-PRESSO) test and Robust Adjusted Profile Score (RAPS).ResultsThe causal odds ratio (OR) estimate of genetically determined insomnia was 1.33 (95% confidence interval (CI) 1.22-1.45; p = 5.03 × 10-11) for attention-deficit/hyperactivity disorder (ADHD), 1.31 (95% CI 1.25-1.37; p = 6.88 × 10-31) for major depressive disorder (MDD) and 1.32 (95% CI 1.23-1.40; p = 1.42 × 10-16) for post-traumatic stress disorder (PTSD). There were suggestive inverse associations of morningness chronotype with risk of MDD and schizophrenia (SCZ). Genetically predicted sleep duration was also nominally associated with the risk of bipolar disorder (BD). Conversely, PTSD and MDD were associated with an increased risk of insomnia (OR = 1.06, 95% CI 1.03-1.10, p = 7.85 × 10-4 for PTSD; OR = 1.37, 95% CI 1.14-1.64; p = 0.001 for MDD). A suggestive inverse association of ADHD and MDD with sleep duration was also observed.ConclusionsOur findings provide evidence of potential causal relationships between sleep disturbance and psychiatric disorders. This suggests that abnormal sleep patterns may serve as markers for psychiatric disorders and offer opportunities for prevention and management in psychiatric disorders.
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Project description:BackgroundPrevious epidemiological investigations and related research efforts consistently have outlined an observable association between anxiety disorders and adhesive capsulitis (AC). However, the intricate nature of the causal connection between these entities has yet to be fully clarified. Therefore, this investigative study aims to thoroughly examine and delineate the causal interrelationship between anxiety disorders and AC using a bidirectional, two-sample Mendelian randomization (MR) approach.MethodsTo pursue this inquiry, datasets related to anxiety disorders and AC were meticulously obtained from a publicly accessible genomewide association study. Instrumental variables, in the form of single nucleotide polymorphisms, were subsequently identified, undergoing a rigorous screening process that included intensity adjustment and the amelioration of linkage disequilibrium. The primary analytical tool for scrutinizing causal ramifications was the inverse variance weighting (IVW) methodology, complemented by supplementary analytical techniques such as weighted median, MR-Egger, simple mode, and weighted mode. Additionally, evaluations of heterogeneity and pleiotropy were meticulously conducted. Heterogeneity was assessed using Cochran's Q-test in conjunction with the IVW and MR-Egger methods, while pleiotropy was appraised through the MR-Egger intercept and MR-PRESSO analysis methods. A leave-one-out analysis was undertaken to enhance the reliability of our findings. Finally, AC was utilized to infer reverse causality concerning the risk of anxiety disorders.ResultsThe random effects IVW analysis results yielded statistical significance (P = 9.362 × 10-6), demonstrating a causal link between anxiety disorders and elevated susceptibility to AC, reflected in an odds ratio of 1.267 (95% confidence interval: 1.141-1.407). Conversely, the inverse MR analysis predominantly produced null findings. Furthermore, sensitivity analyses underscored the robustness of our conclusions.ConclusionIn summary, our meticulously conducted study unequivocally supports the presence of a causal connection between anxiety disorders and an increased propensity for AC. Unfortunately, the reverse MR analysis failed to provide compelling evidence indicative of a reciprocal genetic causative relationship between AC and anxiety disorders.
| S-EPMC10800800 | biostudies-literature
Project description:We conducted a two-sample Mendelian randomization study to determine the association of smoking initiation with seven psychiatric disorders. We used 353 independent single-nucleotide polymorphisms associated with cigarette smoking initiation as instrumental variables at genome-wide significance threshold (p < 5 × 10-8) from a recent genome-wide association study in 1,232,091 European-origin participants. Summary-level data for seven psychiatric disorders, including anxiety, bipolar disorder, insomnia, major depressive disorder, posttraumatic stress disorder, suicide attempts, and schizophrenia, was obtained from large genetic consortia and genome-wide association studies. The odds ratios of genetically predicted smoking initiation were 1.96 for suicide attempts (95% CI 1.70, 2.27; p = 4.5 × 10-20), 1.69 for post-traumatic stress disorder (95% CI 1.32, 2.16; p = 2.5 × 10-5), 1.54 for schizophrenia (95% CI 1.35, 1.75; p = 1.6 × 10-10), 1.41 for bipolar disorder (95% CI 1.25, 1.59; p = 1.8 × 10-8), 1.38 for major depressive disorder (95% CI 1.31, 1.45; p = 2.3 × 10-38), 1.20 for insomnia (95% CI 1.14, 1.25; p = 6.0 × 10-14) and 1.17 for anxiety (95% CI 0.98, 1.40; p = 0.086). Results of sensitivity analyses were consistent and no horizontal pleiotropy was detected in MR-Egger analysis. However, the associations with suicide attempts, schizophrenia, bipolar disorder, and anxiety might be related to possible reverse causality or weak instrument bias. This study found that cigarette smoking was causally associated with increased risks of a number of psychiatric disorders. The causal effects of smoking on suicide attempts, schizophrenia, bipolar disorder and anxiety needs further research.
| S-EPMC7427799 | biostudies-literature
Project description:BackgroundObservational studies have explored the association of psychiatric disorders and the risk of brain cancers. However, the causal effect of specific mental illness on glioma remains elusive due to the lack of solid evidence.MethodsWe performed a two-sample bidirectional Mendelian randomization (MR) analysis to explore the causal relationships between 5 common psychiatric disorders (schizophrenia, major depressive disorder, bipolar disorder, autism spectrum disorder, and panic disorder) and glioma. Summary statistics for psychiatric disorders and glioma were extracted from Psychiatric Genomics Consortium (PGC) and 8 genome-wide association study (GWAS) datasets respectively. We calculated the MR estimates for odds ratio of glioma associated with each psychiatric disorder by using inverse-variance weighting (IVW) method. Sensitivity analyses such as weighted median estimator, MR-Egger and MR-PRESSO were leveraged to assess the strength of causal inference.ResultsA total of 30,657 participants of European ancestry were included in this study. After correction for multiple testing, we found that genetically predicted schizophrenia was associated with a statistically significant increase in odds of non-glioblastoma multiforme (non-GBM) (OR = 1.13, 95% CI: 1.03-1.23, P = 0.0096). There is little evidence for the causal relationships between the other 4 psychiatric disorders with the risk of glioma.ConclusionsIn this MR analysis, we revealed an increased risk of non-GBM glioma in individuals with schizophrenia, which gives an insight into the etiology of glioma.
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Project description:Obesity is a highly prevalent risk factor for cardiometabolic diseases. Observational studies suggest that obesity is associated with psychiatric traits, but causal inference from such studies has several limitations. We used two-sample Mendelian randomization methods (inverse variance weighting, weighted median and MR-Egger regression) to evaluate the association of body mass index (BMI) with three psychiatric traits using data from the Genetic Investigation of Anthropometric Traits and Psychiatric Genomics consortia. Causal odds ratio estimates per 1-standard deviation increment in BMI ranged from 0.88 (95% CI: 0.62; 1.25) to 1.23 (95% CI: 0.65; 2.31) for bipolar disorder; 0.93 (0.78; 1.11) to 1.41 (0.87; 2.27) for schizophrenia; and 1.15 (95% CI: 0.92; 1.44) to 1.40 (95% CI: 1.03; 1.90) for major depressive disorder. Analyses removing potentially influential SNPs suggested that the effect estimates for depression might be underestimated. Our findings do not support the notion that higher BMI increases risk of bipolar disorder and schizophrenia. Although the point estimates for depression were consistent in all sensitivity analyses, the overall statistical evidence was weak. However, the fact that SNP-depression associations were estimated in relatively small samples reduced power to detect causal effects. This should be re-addressed when SNP-depression associations from larger studies become available.
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