Associations between obesity and hyperuricemia combing mendelian randomization with network pharmacology
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ABSTRACT:
SUBMITTER: Panlu K
PROVIDER: S-EPMC10951504 | biostudies-literature | 2024 Mar
REPOSITORIES: biostudies-literature
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Project description:BackgroundObservational studies have suggested a potential non-linear association between sleep duration and hyperuricemia. However, the causal nature and sex-specific differences are poorly understood. We aimed to determine the shape of sex-specific causal associations between sleep duration and hyperuricemia in the UK Biobank.MethodsLogistic regression was used to investigate the observational association between self-reported sleep duration and hyperuricemia among 387,980 white British participants (mean age: 56.9 years and 46.0% males). Linear and non-linear Mendelian Randomization (MR) analyses were performed to assess the causal association between continuous sleep duration and hyperuricemia. The causal effects of genetically predicted short (<7 h) and long (>8 h) sleep durations on hyperuricemia were further estimated, respectively.ResultsTraditional observational analysis suggested U- and J-shaped associations between sleep duration and hyperuricemia in females and males, respectively. Linear MR did not support the causal effect of sleep duration on hyperuricemia. Non-linear MR demonstrated an approximately U-shaped causal association between continuous sleep duration and hyperuricemia in overall participants and females, but not in males. Genetically predicted short sleep duration was significantly associated with hyperuricemia in females (OR [95% CI]: 1.21 [1.08-1.36]; P = 0.001), but not in males (1.08 [0.98-1.18]; P = 0.137). By contrast, genetically predicted long sleep duration was not significantly associated with the risk of hyperuricemia in either females or males.ConclusionGenetically predicted short sleep duration is a potential causal risk factor for hyperuricemia for females but has little effect on males. Long sleep duration does not appear to be causally associated with hyperuricemia.
| S-EPMC9632753 | biostudies-literature
Project description:ObjectiveHyperuricemia is closely associated with insulin resistance syndrome (and its many cardiometabolic sequelae); however, whether they are causally related has long been debated. We undertook this study to investigate the potential causal nature and direction between insulin resistance and hyperuricemia, along with gout, by using bidirectional Mendelian randomization (MR) analyses.MethodsWe used genome-wide association data (n = 288,649 for serum urate [SU] concentration; n = 763,813 for gout risk; n = 153,525 for fasting insulin) to select genetic instruments for 2-sample MR analyses, using multiple MR methods to address potential pleiotropic associations. We then used individual-level, electronic medical record-linked data from the UK Biobank (n = 360,453 persons of European ancestry) to replicate our analyses via single-sample MR analysis.ResultsGenetically determined SU levels, whether inferred from a polygenic score or strong individual loci, were not associated with fasting insulin concentrations. In contrast, genetically determined fasting insulin concentrations were positively associated with SU levels (0.37 mg/dl per log-unit increase in fasting insulin [95% confidence interval (95% CI) 0.15, 0.58]; P = 0.001). This persisted in outlier-corrected (β = 0.56 mg/dl [95% CI 0.45, 0.67]) and multivariable MR analyses adjusted for BMI (β = 0.69 mg/dl [95% CI 0.53, 0.85]) (P < 0.001 for both). Polygenic scores for fasting insulin were also positively associated with SU level among individuals in the UK Biobank (P < 0.001). Findings for gout risk were bidirectionally consistent with those for SU level.ConclusionThese findings provide evidence to clarify core questions about the close association between hyperuricemia and insulin resistance syndrome: hyperinsulinemia leads to hyperuricemia but not the other way around. Reducing insulin resistance could lower the SU level and gout risk, whereas lowering the SU level (e.g., allopurinol treatment) is unlikely to mitigate insulin resistance and its cardiometabolic sequelae.
| S-EPMC8568618 | biostudies-literature
Project description:ObjectiveThe VITAL trial of vitamin D supplementation suggested a possible protective effect for autoimmune diseases but uncertainties remain. We investigated potential causal effects of vitamin D on composite and individual autoimmune diseases using Mendelian randomization.MethodsWe used data from 332,984 participants of the UK Biobank of whom 23,089 had at least one autoimmune disease defined using ICD code and/or self-report. Diseases were further considered in mechanistic subgroups driven by "autoimmunity" (n = 12,774) or "autoinflammation" (n = 11,164), then individually. We selected variants within gene regions implicated in vitamin D biology to generate a weighted genetic score. We performed population-wide analysis using the ratio method, then examined non-linear effects across five quantiles based on 25-hydroxycholecalciferol levels.ResultsGenetically-predicted vitamin D was associated with lower risk of diseases in the autoinflammation group (OR 0.95 per 10 ng/ml increase in 25-hydroxycholecalciferol; 95%CI 0.91-0.99; p = 0.03) but not the autoimmunity group (OR 0.99; 95%CI 0.95-1.03; p = 0.64) or combined. When considering individual diseases, genetically-predicted vitamin D was associated with lower risk of psoriasis (OR 0.91; 95%CI 0.85-0.97; p = 0.005), the most common disease in the autoinflammation group, and suggestively with systemic lupus erythematosus (OR 0.84; 95%CI 0.69-1.02; p = 0.08); results were replicated using data from independent studies. We found no evidence for a plausible non-linear relationship between vitamin D and any outcome.ConclusionsWe found genetic evidence to support a causal link between 25-hydroxycholecalciferol concentrations and psoriasis and systemic lupus erythematosus. These results have implications for potential disease prevention strategies, and the interpretation and design of vitamin D supplementation trials.
| S-EPMC7614794 | biostudies-literature
Project description:ObjectiveThe gut microbiota and its metabolites exert a significant influence on COPD, yet the underlying mechanisms remain elusive. We aim to holistically evaluate the role and mechanisms of the gut microbiota and its metabolites in COPD through network pharmacology and Mendelian randomization approaches.MethodsEmploying network pharmacology, we identified the gut microbiota and its metabolites' impact on COPD-related targets, elucidating the complex network mechanisms involving the gut microbiota, its metabolites, targets, and signaling pathways in relation to COPD. Further, promising gut microbiota metabolites and microbiota were pinpointed, with their causal relationships inferred through Mendelian randomization.ResultsA complex biological network was constructed, comprising 39 gut microbiota, 20 signaling pathways, 19 targets, and 23 metabolites associated with COPD. Phenylacetylglutamine emerged as a potentially promising metabolite for COPD treatment, with Mendelian randomization analysis revealing a causal relationship with COPD.ConclusionThis study illuminates the intricate associations between the gut microbiota, its metabolites, and COPD. Phenylacetylglutamine may represent a novel avenue for COPD treatment. These findings could aid in identifying individuals at high risk for COPD, offering insights into early prevention and treatment strategies.
| S-EPMC11625750 | biostudies-literature
Project description:BackgroundRenshen Yangrong decoction (RSYRD) has been shown therapeutic effects on secondary malaise and fatigue (SMF). However, to date, its bioactive ingredients and potential targets remain unclear.PurposeThe purpose of this study is to assess the potential ingredients and targets of RSYRD on SMF through a comprehensive strategy integrating network pharmacology, Mendelian randomization as well as molecular docking verification.MethodsSearch for potential active ingredients and corresponding protein targets of RSYRD on TCMSP and BATMAN-TCM for network pharmacology analysis. Mendelian randomization (MR) was performed to find therapeutic targets for SMF. The eQTLGen Consortium (sample sizes: 31,684) provided data on cis-expression quantitative trait loci (cis-eQTL, exposure). The summary data on SMF (outcome) from genome-wide association studies (GWAS) were gathered from the MRC-IEU Consortium (sample sizes: 463,010). We built a target interaction network between the probable active ingredient targets of RSYRD and the therapeutic targets of SMF. We next used drug prediction and molecular docking to confirm the therapeutic value of the therapeutic targets.ResultsIn RSYRD, network pharmacology investigations revealed 193 possible active compounds and 234 associated protein targets. The genetically predicted amounts of 176 proteins were related to SMF risk in the MR analysis. Thirty-seven overlapping targets for RSYRD in treating SMF, among which six (NOS3, GAA, IMPA1, P4HTM, RB1, and SLC16A1) were prioritized with the most convincing evidence. Finally, the 14 active ingredients of RSYRD were identified as potential drug molecules. The strong affinity between active components and putative protein targets was established by molecular docking.ConclusionThis study revealed several active components and possible RSYRD protein targets for the therapy of SMF and provided novel insights into the feasibility of using Mendelian randomization for causal inference between Chinese medical formula and disease.
| S-EPMC11222649 | biostudies-literature
Project description:BackgroundAchilles tendinopathy (AT) is associated with severe pain and is the cause of dysfunction and disability that are associated with significant reduction in social and economic benefits. Several potential risk factors have been proposed to be responsible for AT development; however, the results of observational epidemiological studies remain controversial, presumably because the designs of these studies are subject to residual confounding and reverse causality. Mendelian randomization (MR) can infer the causality between exposure and disease outcomes using genetic variants as instrumental variables, and identification of the causal risk factors for AT is beneficial for early intervention. Thus, we employed the MR strategy to evaluate the causal associations between previously reported risk factors (anthropometric parameters, lifestyle factors, blood biomarkers, and systemic diseases) and the risk of AT.MethodsUnivariable MR was performed to screen for potential causal associations between the putative risk factors and AT. Bidirectional MR was used to infer reverse causality. Multivariable MR was conducted to investigate the body mass index (BMI)-independent causal effect of other obesity-related traits, such as the waist-hip ratio, on AT.ResultsUnivariable MR analyses with the inverse-variance weighted method indicated that the genetically predicted BMI was significantly associated with the risk of AT (P=2.0×10-3), and the odds ratios (95% confidence intervals) is 1.44 (1.14-1.81) per 1-SD increase in BMI. For the other tested risk factors, no causality with AT was identified using any of the MR methods. Bidirectional MR suggested that AT was not causally associated with BMI, and multivariable MR indicated that other anthropometric parameters included in this study were not likely to causally associate with the risk of AT after adjusting for BMI.ConclusionsThe causal association between BMI and AT risk suggests that weight control is a promising strategy for preventing AT and alleviating the corresponding disease burden.
| S-EPMC9238354 | biostudies-literature
Project description:To investigate the causal relationship between obesity and meniscal injuries using Mendelian randomization (MR). Genetic loci independently associated with obesity and meniscal injuries in people of European origin were selected as instrumental variables using pooled data from genome-wide association studies. Three MR analyses, MR-Egger, weighted median and inverse variance weighting, were used to investigate the causal relationship between obesity and meniscal injuries. The results were tested for robustness by heterogeneity and multiplicity tests, and sensitivity analyses were performed using the "leave-one-out" method. The inverse variance weighting results showed an OR (95% CI) of 1.13 (1.04-1.22), P = .003, indicating a causal relationship between obesity and the occurrence of meniscal injuries. And no heterogeneity and multiplicity were found by the test and sensitivity analysis also showed robust results. In this study, genetic data were analyzed and explored using 2-sample MR analysis, and the results showed that obesity is a risk factor for meniscal injuries.
| S-EPMC10695575 | biostudies-literature
Project description:BackgroundWhether obesity is a cause or consequence of low physical activity levels and more sedentary time has not yet been fully elucidated. Better instrumental variables and a more thorough consideration of potential confounding variables that may influence the causal inference between physical activity and obesity are needed.MethodsLeveraging results from our recent genome-wide association study for leisure time moderate-to-vigorous intensity (MV) physical activity and screen time, we here disentangle the causal relationships between physical activity, sedentary behavior, education-defined by years of schooling-and body mass index (BMI), using multiple univariable and multivariable Mendelian Randomization (MR) approaches.ResultsUnivariable MR analyses suggest bidirectional causal effects of physical activity and sedentary behavior with BMI. However, multivariable MR analyses that take years of schooling into account suggest that more MV physical activity causes a lower BMI, and a higher BMI causes more screen time, but not vice versa. In addition, more years of schooling causes higher levels of MV physical activity, less screen time, and lower BMI.ConclusionsIn conclusion, our results highlight the beneficial effect of education on improved health and suggest that a more physically active lifestyle leads to lower BMI, while sedentary behavior is a consequence of higher BMI.
| S-EPMC10689836 | biostudies-literature
Project description:BackgroundPrevious observational studies have reported inconsistent findings regarding the incidence of cancer in patients with schizophrenia compared to the general population. The causal relationship between schizophrenia and cancer remains unclear and requires further investigation.ObjectiveTo investigate the causal relationship between schizophrenia and cancer.MethodsIn this study, a two-sample Mendelian randomization (MR) analysis was conducted using publicly available genome-wide association studies to determine the causal relationship. The effect estimates were calculated using the random-effects inverse-variance-weighted method.ResultsWe determined a causal relationship between genetic predisposition to schizophrenia and cancer, with schizophrenia increasing lung cancer (odds ratio (OR) = 1.0007; 95% confidence interval (CI), 1.0001-1.0013; p = 0.0192), thyroid cancer (OR = 1.5482; CI, 1.1112-2.1569; p =0.0098),colorectal cancer (OR = 1.0009; CI, 1.0001-1.0018; p = 0.0344), ovarian cancer (OR = 1.0770; CI, 1.0352-1.1203; p = 0.0002), breast cancer (OR = 1.0011; CI, 1.0001- 1.0022; p =0.0352) and reduced the risk of malignant neoplasm of the stomach (OR = 0.8502; CI, 0.7230-0.9998; p = 0.0496).ConclusionsThis study conducted a two-sample MR analysis and discovered a positive causal relationship between schizophrenia and breast, ovarian, thyroid, lung, and colorectal cancers. On the other hand, an inverse causal relationship was found between schizophrenia and malignant neoplasm of the stomach.
| S-EPMC10693432 | biostudies-literature
Project description:IntroductionPrevious studies have proposed a possible gut-skin axis, and linked gut microbiota to psoriasis risks. However, there is heterogeneity in existing evidence. Observational research is prone to bias, and it is hard to determine causality. Therefore, this study aims to evaluate possible causal associations between gut microbiota (GM) and psoriasis.MethodsWith published large-scale GWAS (genome-wide association study) summary datasets, two-sample Mendelian randomization (MR) was performed to sort out possible causal roles of GM in psoriasis and arthropathic psoriasis (PsA). The inverse variance weighted (IVW) method was taken as the primary evaluation of causal association. As complements to the IVW method, we also applied MR-Egger, weighted median. Sensitivity analyses were conducted using Cochrane's Q test, MR-Egger intercept test, MR-PRESSO (Mendelian Randomization Pleiotropy RESidual Sum and Outlier) global test, and leave-one-out analysis.ResultsBy primary IVW analysis, we identified nominal protective roles of Bacteroidetes (odds ratio, OR 0.81, P = 0.033) and Prevotella9 (OR 0.87, P = 0.045) in psoriasis risks. Bacteroidia (OR 0.65, P = 0.03), Bacteroidales (OR 0.65, P = 0.03), and Ruminococcaceae UCG002 (OR 0.81, P = 0.038) are nominally associated with lower risks for PsA. On the other hand, Pasteurellales (OR 1.22, P = 0.033), Pasteurellaceae (OR 1.22, P = 0.033), Blautia (OR 1.46, P = 0.014), Methanobrevibacter (OR 1.27, P = 0.026), and Eubacterium fissicatena group (OR 1.21, P = 0.028) are nominal risk factors for PsA. Additionally, E. fissicatena group is a possible risk factor for psoriasis (OR 1.22, P = 0.00018). After false discovery rate (FDR) correction, E. fissicatena group remains a risk factor for psoriasis (PFDR = 0.03798).ConclusionWe comprehensively evaluated possible causal associations of GM with psoriasis and arthropathic psoriasis, and identified several nominal associations. E. fissicatena group remains a risk factor for psoriasis after FDR correction. Our results offer promising therapeutic targets for psoriasis clinical management.
| S-EPMC10539234 | biostudies-literature