Significant Causal Relationship Research Articles

Novel insights into causal associations of body mass index or height with pneumothorax: a two-sample Mendelian randomization study

BackgroundObservational studies have reported an association between body mass index (BMI) as well as height and the risk of pneumothorax. However, it has long been unclear whether BMI or height are causally associated with pneumothorax.MethodsGenetic summary data for BMI, height and pneumothorax were retrieved from multiple independent large genome-wide association studies (GWAS). A series of quality control steps were conducted to select instruments. Four independent two-sample Mendelian randomization (MR) analyzes were performed to adequately assess the causal relationship between BMI or height on pneumothorax, and the robustness of the results was assessed by a series of sensitivity analyzes.ResultsHeight increased the risk of pneumothorax with an OR of 1.5181 (95%CI 1.3092–1.7604; p = 3.28e-08); there was no evidence of a causal effect of BMI on the risk of pneumothorax with an OR of 0.8979 (95%CI 0.7417–1.0869; p = 0.269). Height increased the risk of spontaneous pneumothorax with an OR of 1.0010 (95%CI 1.0002–1.0018; p = 0.012); the results showed no significant causal relationship between BMI and spontaneous pneumothorax either with an OR of 0.9992 (95%CI 0.9983–1.0002; p = 0.112).ConclusionOur results supported a genetic association between height and pneumothorax. We found that height increased the risk of pneumothorax. However, no evidence was found to suggest a causal relationship between BMI and pneumothorax risk. The relationship between BMI and pneumothorax requires further in-depth analysis.

Inflammatory bowel disease and risk for hemorrhoids: a Mendelian randomization analysis

Observational studies have reported an association between inflammatory bowel disease (IBD), which includes Crohn’s disease (CD) and ulcerative colitis (UC), and hemorrhoids (HEM). However, the presence of a causal relationship within this observed association remains to be confirmed. Consequently, we utilized the Mendelian randomization (MR) method to assess the causal effects of IBD on hemorrhoids. We validated the association between IBD and hemorrhoids in humans based on genome-wide association studies (GWAS) data. To investigate the causal relationship between IBD and hemorrhoids, we performed a two-sample Mendelian randomization study using training and validation sets. The genetic variation data for IBD, CD, UC, and hemorrhoids were derived from published genome-wide association studies (GWAS) of individuals of European. Two-sample Mendelian randomization and Multivariable Mendelian randomization (MVMR) were employed to determine the causal relationship between IBD (CD or UC) and hemorrhoids. Genetically predicted overall IBD was positively associated with hemorrhoids risk, with ORs of 1.02 (95% CIs 1.01–1.03, P = 4.39 × 10−4) and 1.02 (95% CIs 1.01–1.03, P = 4.99 × 10−5) in the training and validation sets, respectively. Furthermore, we found that CD was positively associated with hemorrhoids risk, with ORs of 1.02 (95% CIs 1.01–1.03, P = 4.12 × 10−6) and 1.02 (95% CIs 1.01–1.02, P = 3.78 × 10−5) for CD in the training and validation sets, respectively. In addition, we found that UC in the training set was positively associated with hemorrhoids risk (ORs 1.02, 95% CIs 1.01–1.03, P = 4.65 × 10−3), while no significant causal relationship between UC and hemorrhoids was shown in the validation set (P > 0.05). However, after MVMR adjustment, UC in the training set was not associated with an increased risk of hemorrhoids. Our study showed that there is a causal relationship between CD and hemorrhoids, which may suggest that clinicians need to prevent the occurrence of hemorrhoids in CD patients.

Causal relationship between type 2 diabetes and glioblastoma: bidirectional Mendelian randomization analysis

As the prevalence of Type 2 Diabetes Mellitus (T2DM) and Glioblastoma (GBM) rises globally, the relationship between T2DM and GBM remains controversial. This study aims to investigate whether genetically predicted T2DM is causally associated with GBM. We performed bidirectional Mendelian randomization (MR) analysis using data from genome-wide studies on T2DM (N = 62,892) and GBM (N = 218,792) in European populations. The results of the inverse-variance weighted (IVW) approach served as the primary outcomes. We applied Cochran’s Q test and MR-Egger regression for heterogeneity assessment. Leave-one-out analysis was used to evaluate whether any single SNP significantly influenced the observed effect. Our findings reveal a significant causal association between T2DM and an increased risk of GBM (OR [95% CI] 1.70 [1.09, 2.65], P = 0.019). Conversely, the reverse association between T2DM and GBM was insignificant (OR [95% CI] 1.00 [0.99, 1.01], P = 0.408) (P > 0.40). Furthermore, the results from Cochran’s Q-test and funnel plots in the MR-Egger method indicated no evidence of pleiotropy between the SNPs and GBM. Additionally, we mapped causal SNPs to genes and identified 10 genes, including MACF1, C1orf185, PTGFRN, NOTCH2, ABCB10, GCKR, THADA, RBMS1, SPHKAP, and PPARG, located on chromosomes 1, 2, and 3. These genes are involved in key biological processes such as the BMP signaling pathway and various metabolic pathways relevant to both conditions. This study provides robust evidence of a significant causal relationship between T2DM and an increased risk of GBM. The identified SNP-mapped genes highlight potential biological mechanisms underlying this association.

The Impact of Climate Change on Life Expectancy in the UK: Empirical Evidence from Fourier Bootstrap ARDL Procedure

This study aims to determine the impact of surface temperature change, considered a proxy for climate change in the United Kingdom, on life expectancy using annual data from 1990–2021. Government expenditure is used as a control variable. The Fourier function-based bootstrap autoregressive distributed lag model is utilized to examine the cointegration among variables. The analysis outcomes reveal a long-term relationship between life expectancy, surface temperature change, and government expenditure. Furthermore, the findings reveal that surface temperature change significantly reduces life expectancy in the long run, while there is no significant relationship between the two variables in the short term. The Toda-Yamamoto causality analysis results show a unidirectional causality relationship between surface temperature change and life expectancy. Additionally, a significant bidirectional causality relationship is found between life expectancy and government expenditure.

Association between blood metabolites and basal cell carcinoma risk: a two-sample Mendelian randomization study.

Circulating metabolites, which play a crucial role in our health, have been reported to be disordered in basal cell carcinoma (BCC). Despite these findings, evidence is still lacking to determine whether these metabolites directly promote or prevent BCC's progression. Therefore, our study aims to examine the potential effects of circulating metabolites on BCC progression. We conducted a two-sample Mendelian randomization (MR) analysis using data from two separate genome-wide association studies (GWAS). The primary study included data for 123 blood metabolites from a GWAS with 25,000 Finnish individuals, while the secondary study had data for 249 blood metabolites from a GWAS with 114,000 UK Biobank participants.GWAS data for BCC were obtained from the UK Biobank for the primary analysis and the FinnGen consortium for the secondary analysis. Sensitivity analyses were performed to assess heterogeneity and pleiotropy. In the primary analysis, significant causal relationships were found between six metabolic traits and BCC with the inverse variance weighted (IVW) method after multiple testing [P < 4 × 10-4 (0.05/123)]. Four metabolic traits were discovered to be significantly linked with BCC in the secondary analysis, with a significance level of P < 2 × 10-4 (0.05/249). We found that all the significant traits are linked to Polyunsaturated Fatty Acids (PUFAs) and their degree of unsaturation. Our research has revealed a direct link between the susceptibility of BCC and Polyunsaturated Fatty Acids and their degree of unsaturation. This discovery implies screening and prevention of BCC.

Association between blood metabolites and basal cell carcinoma risk: a two-sample Mendelian randomization study

BackgroundCirculating metabolites, which play a crucial role in our health, have been reported to be disordered in basal cell carcinoma (BCC). Despite these findings, evidence is still lacking to determine whether these metabolites directly promote or prevent BCC’s progression. Therefore, our study aims to examine the potential effects of circulating metabolites on BCC progression.Material and methodsWe conducted a two−sample Mendelian randomization (MR) analysis using data from two separate genome-wide association studies (GWAS). The primary study included data for 123 blood metabolites from a GWAS with 25,000 Finnish individuals, while the secondary study had data for 249 blood metabolites from a GWAS with 114,000 UK Biobank participants.GWAS data for BCC were obtained from the UK Biobank for the primary analysis and the FinnGen consortium for the secondary analysis. Sensitivity analyses were performed to assess heterogeneity and pleiotropy.ResultsIn the primary analysis, significant causal relationships were found between six metabolic traits and BCC with the inverse variance weighted (IVW) method after multiple testing [P &amp;lt; 4 × 10−4 (0.05/123)]. Four metabolic traits were discovered to be significantly linked with BCC in the secondary analysis, with a significance level of P &amp;lt; 2 × 10−4 (0.05/249). We found that all the significant traits are linked to Polyunsaturated Fatty Acids (PUFAs) and their degree of unsaturation.ConclusionOur research has revealed a direct link between the susceptibility of BCC and Polyunsaturated Fatty Acids and their degree of unsaturation. This discovery implies screening and prevention of BCC.

Daily habits, diseases, drugs and knee osteoarthritis: a two-sample Mendelian randomization analysis.

The causal relationship between daily habits, diseases, drugs, and knee osteoarthritis (KOA) remains unclear. This study utilized a two-sample Mendelian randomization (MR) method to investigate the causal links between these factors and KOA, providing new insights for KOA prevention. SNPs strongly associated with exposure factors (daily habits, diseases, drugs) were extracted from publicly available genome-wide association study (GWAS) as instrumental variables (IVs). We then selected GWAS of KOA as the outcome, conducting a two-sample MR analysis. Our findings revealed significant causal relationships between several factors and KOA. There was a notable association with time spent watching TV (OR = 4.038; 95% CI: 1.859-8.770; P = 4.192E-04), frequency of friend/family visits (OR = 0.415; 95% CI: 0.219-0.788; P = 7.174E-03), smoking history (OR = 0.781; 95% CI: 0.663-0.921; P = 3.235E-03), gastroesophageal reflux disease (GERD) (OR = 1.519; 95% CI: 1.244-1.856; P = 4.183E-05), hypercholesterolemia (OR = 0.498; 95% CI: 0.290-0.855; P = 0.011), hypothyroidism (OR = 1.048; 95% CI: 1.013-1.084; P = 6.645E-03), use of antithrombotic agents (OR = 0.892; 95% CI: 0.816-0.976; P = 0.013), statin medication (OR = 0.956; 95% CI: 0.916-0.998; P = 0.041), and thyroid preparations (OR = 1.042; 95% CI: 1.014-1.071; P = 2.974E-03) with KOA. Specifically, KOA was positively associated with longer time spent watching TV, GERD, hypothyroidism and thyroid preparations, however showed a negative correlation with more frequent visits from friends or family, smoking history, hypercholesterolemia, antithrombotic agents and statin medication. Sensitivity analysis indicated no significant pleiotropy in these studies (P > 0.05). This comprehensive study underscores the significance of modifying certain habits to mitigate the risk of KOA. Additionally, the elevated risk of KOA among individuals with GERD, hypothyroidism, and those using thyroid preparations warrants attention. These results would be beneficial for clinical research and nursing education.

Genetic evidence for causal association between migraine and dementia: a mendelian randomization study

BackgroundThere is an association between migraine and dementia, however, their causal relationship remains unclear. This study employed bidirectional two-sample Mendelian randomization (MR) to investigate the potential causal relationship between migraine and dementia and its subtypes: Alzheimer’s disease (AD), vascular dementia (VaD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB).MethodsSummary-level statistics data were obtained from publicly available genome-wide association studies (GWAS) for both migraine and five types of dementia. Single nucleotide polymorphisms (SNPs) associated with migraine and each dementia subtype were selected. MR analysis was conducted using inverse variance weighting (IVW) and weighted median (WM) methods. Sensitivity analyses included Cochran’s Q test, MR pleiotropy residual sum and outlier (MR-PRESSO) analysis, the intercept of MR-Egger, and leave-one-out analysis.ResultsMigraine showed a significant causal relationship with AD and VaD, whereas no causal relationship was observed with all-cause dementia, FTD, or DLB. Migraine may be a potential risk factor for AD (odds ratio [OR]: 1.09; 95% confidence interval [CI]: 0.02–0.14; P = 0.007), while VaD may be a potential risk factor for migraine (OR: 1.04; 95% CI: 0.02–0.06; P = 7.760E-5). Sensitivity analyses demonstrated the robustness of our findings.ConclusionOur study suggest that migraine may have potential causal relationships with AD and VaD. Migraine may be a risk factor for AD, and VaD may be a risk factor for migraine. Our study contributes to unraveling the comprehensive genetic associations between migraine and various types of dementia, and our findings will enhance the academic understanding of the comorbidity between migraine and dementia.

Exploring the association of physical activity on cognitive function in older adults from observational and genetic insights: a combined NHANES and Mendelian randomization study.

Cognitive function (CF) deterioration is a pressing concern in geriatric research. This study aimed to explore the relationship between physical activity (PA) and CF in older adults. This study adopted a dual approach, employing both observational and genetic approaches through data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014 and Mendelian Randomization (MR) analysis. For the NHANES component, PA levels were evaluated using the Global Physical Activity Questionnaire, and CF was assessed via standardized tests. Multivariate regression, threshold effect analysis, smoothing curve fitting, and subgroup analyses were conducted to examine the association between PA and CF. In parallel, MR methods, using genetic variants as instrumental variables, assessed the causal impact of PA on CF and related conditions such as Alzheimer's disease and dementia. Observational findings from NHANES demonstrated a positive correlation between PA and CF, notably among female participants. The detailed analysis identified specific thresholds of PA that correlate with cognitive enhancements. However, MR results did not support a significant causal relationship between PA and CF or dementia-related outcomes, indicating an absence of a direct genetic basis for the observational associations. Although observational data from NHANES suggest that PA is positively associated with CF in older adults, particularly among women, MR analysis did not confirm these findings as causally related. The discrepancy highlights the complexity of the PA-CF relationship and underscores the need for further research. These results emphasize the potential of PA as a modifiable risk factor for CF, though causal effects remain to be definitively established.

No causal associations of genetically predicted birth weight and life course BMI with thyroid function and diseases.

Observational studies have suggested associations of birth weight, childhood BMI, and adulthood BMI with thyroid function or diseases. However, the causal relationships remain unclear due to residual confounding inherent in conventional epidemiological studies. We performed a two-sample Mendelian randomization (MR) study to investigate causal relationships of genetically predicted birth weight, childhood BMI, and adulthood BMI with a range of clinically relevant thyroid outcomes. Additionally, we conducted a reverse MR analysis on adulthood BMI. Data on exposures and outcomes were obtained from large-scale genome-wide association study meta-analyses predominantly composed of individuals of European ancestry. The MR analysis revealed no evidence of causal associations of birth weight or BMI at different life stages with thyrotropin (TSH) levels, hypothyroidism, hyperthyroidism, autoimmune thyroid disorders, or thyroid cancer. Contrarily, thyroid cancer demonstrated a significant causal relationship with increased adulthood BMI (β = 0.010, 95% CI: 0.006-0.015; p = 5.21 × 10-6). Our comprehensive MR did not find causal links of birth weight, childhood BMI, or adulthood BMI with thyroid diseases but provided evidence that thyroid cancer may play a role in weight gain. Our research findings offer valuable insights into the intricate relationship between body weight and thyroid health throughout an individual's life.

The impact of 25-hydroxyvitamin D and calcium on risk of age-related macular degeneration: a Mendelian randomization study

BackgroundThe relationships between 25-hydroxyvitamin D [25(OH)D] and calcium and age-related macular degeneration (AMD) are unclear. ObjectivesThis study aimed to investigate the causal role of 25(OH)D concentrations, calcium concentrations, and dietary supplements use of vitamin D and calcium on risk of AMD and its subtypes. MethodsIndependent genetic variants associated with 25(OH)D and calcium concentrations were used as instrumental variables in published genome-wide association studies (GWASs) of European ancestry. The bidirectional 2-sample Mendelian randomization (MR) analyses were performed using summary-level data from the UK Biobank and FinnGen datasets. Sensitivity analyses were conducted to ensure the robustness of the MR results. The meta-analyses were conducted using both fixed-effect and random-effect models to provide comprehensive and reliable estimates. ResultsA standard deviation increase in calcium concentrations was linked to a 14%, 17%, and 13% reduction in the likelihood of developing AMD (95% confidence interval [CI]: 0.77, 0.97), wet AMD (95% CI: 0.73, 0.95), and dry AMD (95% CI: 0.75, 1.00), respectively. No significant causal relationships were detected between genetically predicted 25(OH)D concentrations and AMD and its subtypes (all P > 0.05). The combined analyses showed that higher calcium concentrations were associated with a reduced risk of overall AMD, with an odds ratio of 0.89 (95% CI: 0.81, 0.98). ConclusionsThis study provides evidence supporting the causal relationship between calcium concentrations and risk of AMD and its subtypes, which may have important implications for the prevention, monitoring, and treatment of AMD.

A mendelian randomization study investigating the causal relationships between 1400 serum metabolites and autoimmune diseases

ObjectiveThis study aims to explore the causal relationships between 1400 serum metabolites (SMs) and five autoimmune diseases (Myasthenia gravis [MG], Multiple sclerosis [MS], Systemic lupus erythematosus [SLE], Type 1 diabetes mellitus [T1DM], and Ulcerative colitis [UC]) through Mendelian randomization analysis. MethodData on MG, MS, SLE, T1DM, and UC were obtained from the IEU OpenGWAS Project database, while information on 1400 SMs was extracted from GWAS summary statistics provided by Chen et al. Causal relationships were assessed using the inverse variance weighted (IVW), MR-Egger, Weighted Median (WME), and Simple median (SME) methods. The robustness of instrumental variables was verified through computation of the F-statistic. Heterogeneity was evaluated using Cochran's Q test and the leave-one-out (LOO) method. Horizontal pleiotropy was assessed using MR-Egger regression and MR-PRESSO. ResultFollowing correction of the IVW P values using the False Discovery Rate (FDR) method, it was found that increased levels of 5-methyluridine (ribothymidine) (OR = 1.191, 95%CI 1.086–1.307, FDR-P = 0.000) and 2′-deoxyuridine (OR = 1.337, 95%CI 1.127–1.586, FDR-P = 0.001) were found to be correlated with a higher risk of MS. Conversely, the ratio of S-adenosylhomocysteine (SAH) to 5-methyluridine (ribothymidine) (OR = 0.771, 95%CI 0.649–0.916, FDR-P = 0.007) was linked to a decreased risk of MS. Levels of 1,2-dilinoleoyl-GPE (18:2/18:2) (OR = 0.877, 95%CI 0.791–0.974, FDR-P = 0.003) appear to be a protective factor for T1DM. No notable correlations between SMs and MG, SLE, or UC. The study detected no heterogeneity or horizontal pleiotropy. ConclusionLevels of 5-methyluridine (ribothymidine), 2′-deoxyuridine, and the ratio of S-adenosylhomocysteine (SAH) to 5-methyluridine (ribothymidine) can serve as predictors for MS. Similarly, 1,2-dilinoleoyl-GPE (18:2/18:2) levels can be used to predict T1DM. However, no significant causal relationships were found between SMs and MG, SLE, or UC. This observation holds significant clinical implications for crafting tailored preventive and therapeutic approaches for ADs.

Associations between gut microbiota and chronic sinusitis: A bidirectional Mendelian randomization study.

Studies have indicated a close association between dysbiosis of the gut microbiota and chronic sinusitis. However, the causal relationship between the gut microbiota and the risk of chronic sinusitis remains unclear. Using genome-wide association study (GWAS) data for the gut microbiota and chronic sinusitis, we conducted a two-sample Mendelian randomization (MR) study to determine the potential causal relationship between the microbiota and chronic sinusitis. We employed the inverse variance-weighted (IVW) method as the primary analytical approach to estimate the effect. Additionally, sensitivity, heterogeneity, and pleiotropy analyses were conducted to evaluate the robustness of the results. Reverse MR analysis was also applied to investigate potential reverse causality. Through MR analysis, we identified 17 gut microbiota classifications that are closely associated with chronic sinusitis. However, after Bonferroni multiple correction, only class Bacilli (odds ratio: 0.785, 95%confidence interval: 0.677-0.911, p = .001, false discovery rate = 0.023) maintained a significant causal negative relationship with chronic sinusitis. Sensitivity analysis did not reveal any evidence of heterogeneity or horizontal pleiotropy. Reverse MR analysis found five gut microbiota classifications that are significantly associated with chronic sinusitis, but they were no longer significant after Bonferroni multiple correction. There was no evidence to suggest a reverse causal relationship between chronic sinusitis and class Bacilli. Specific gut microbiota predicted by genetics exhibit a potential causal relationship with chronic sinusitis, and class Bacilli may have a protective effect on chronic sinusitis.

The weight of weights: Causal impact of overweight on major depressive disorder and its disparate association with suicide attempts in over 450,000 individuals of European ancestry (AM-SRNMA 003)

AimSome studies and societal discussions have suggested a potential link between overweight and a higher risk of mental disorders and suicidal ideation. However, the causal relationships between these factors remain unclear. This study aims to assess the bidirectional causal associations between overweight and mental disorders, including suicidal attempts. MethodWe conducted a Two-Sample Mendelian Randomization study utilizing data from over 450,000 individuals of European ancestry sourced from a comprehensive Genome-Wide Association Study database. We chose single-nucleotide polymorphisms as instrumental variables. ResultsOur analyses consistently supported a unidirectional causal association of overweight with the increased risk of major depressive disorder (MDD, β = 0.152, se = 0.069, P = 0.027), bipolar affective disorders (BD, β = 0.197, se = 0.092, P = 0.033), and attention-deficit / hyperactivity disorder (ADHD, β = 0.308, se = 0.080, P = 1.366 × 10−4). We observed no significant causal relationships for the exposure of overweight to anxiety disorder (AD), manic episode (MA), panic disorder (PD), schizophrenia (SZ), substance use disorder (SUD), autism spectrum disorder (ASD), ever attempted suicide, recent thoughts of suicide or self-harm, and suicide or other intentional self-harm events. ConclusionThis study has provided evidence for the causal relationship between overweight and MDD, BD, ADHD, with no observed relationship between overweight and AD, MA, PD, SZ, SUD, ASD, ever attempted suicide, recent thoughts of suicide or self-harm, and suicide or other intentional self-harm events.

Asthma and risk of adverse pregnancy outcomes: A Mendelian randomization study

BackgroundMultiple empirical investigations have indicated a connection between asthma and adverse pregnancy outcomes (APOs). Nevertheless, the effects of asthma on APOs remain uncertain. MethodsWe performed bi-directional Univariable Mendelian randomization (UVMR) analyses using combined information obtained from genome-wide association studies (GWAS) data that is publicly accessible. The principal approach used to analyze the causal association between asthma or age when diagnosed and APOs was the inverse variance weighted (IVW) method. The two types of data regarding exposure originate from the IEU Open GWAS project, which includes 56,167 and 47,222 European asthma patients, respectively. The data of four APOs were acquired via the GWAS dataset of the FinnGen collaboration. In addition, we implemented multivariable Mendelian randomization (MVMR), controlling for confounding factors such as smoking status, frequent drinking, body mass index (BMI), and live birth quantity. Furthermore, we executed several meticulous sensitivity studies to ascertain the reliability of our MR results. ResultsFollowing the implementation of the Bonferroni adjustment, the UVMR assessment revealed that in the IVW model, asthma was significantly linked to an elevated risk of spontaneous abortion (SA) (odds ratio [OR]: 1.115; 95 % confidence interval [CI]: 1.031–1.206; P = 0.006) and gestational diabetes mellitus (GDM) (OR: 1.125; 95 % CI: 1.037–1.220; P = 0.005). However, there was no causal correlation between asthma and preterm birth (PTB) (OR: 0.979; 95 % CI: 0.897–1.068; P = 0.629) or preeclampsia (PE) (OR: 1.059; 95 % CI: 0.951–1.179; P = 0.297). After adjusting for confounding factors, including smoking status, frequent drinking, BMI, and live birth quantity, the MVMR analysis shows a statistically significant causal relationship between asthma and SA or GDM. Furthermore, our investigation's findings did not reveal a substantial correlation between the age of asthma onset based on genetics and the likelihood of SA or GDM. The inverse MR outcomes indicate a lack of causal connection linking APOs to the incidence of asthma. The validity of these findings were verified by sensitivity analyses. ConclusionsThe evidence provided by this study proves that genetically determined asthma is linked to a higher likelihood of SA and GDM. Further research is required to examine potential pathways. However, no conclusive evidence has been found to support the increased risk of SA and GDM in early asthma diagnosis or the interaction between asthma and PTB or PE, indicating that confounding factors may affect the results of previous observational studies.

Deciphering the lipid–cancer nexus: comprehensive Mendelian randomization analysis of the associations between lipid profiles and digestive system cancer susceptibility

BackgroundDigestive system cancers represent a significant global health challenge and are attributed to a combination of demographic and lifestyle changes. Lipidomics has emerged as a pivotal area in cancer research, suggesting that alterations in lipid metabolism are closely linked to cancer development. However, the causal relationship between specific lipid profiles and digestive system cancer risk remains unclear.MethodsUsing a two-sample Mendelian randomization (MR) approach, we elucidated the causal relationships between lipidomic profiles and the risk of five types of digestive system cancer: stomach, liver, esophageal, pancreatic, and colorectal cancers. The aim of this study was to investigate the effect impact of developing lipid profiles on the risk of digestive system cancers utilizing data from public databases such as the GWAS Catalog and the UK Biobank. The inverse‒variance weighted (IVW) method and other strict MR methods were used to evaluate the potential causal links. In addition, we performed sensitivity analyses and reverse MR analyses to ensure the robustness of the results.ResultsSignificant causal relationships were identified between certain lipidomic traits and the risk of developing digestive system cancers. Elevated sphingomyelin (d40:1) levels were associated with a reduced risk of developing gastric cancer (odds ratio (OR) = 0.68, P < 0.001), while elevated levels of phosphatidylcholine (16:1_20:4) increased the risk of developing esophageal cancer (OR = 1.31, P = 0.02). Conversely, phosphatidylcholine (18:2_0:0) had a protective effect against colorectal cancer (OR = 0.86, P = 0.036). The bidirectional analysis did not suggest reverse causality between cancer risk and lipid levels. Strict MR methods demonstrated the robustness of the above causal relationships.ConclusionOur findings underscore the significant causal relationships between specific lipidomic traits and the risk of developing various digestive system cancers, highlighting the potential of lipid profiles in informing cancer prevention and treatment strategies. These results reinforce the value of MR in unraveling complex lipid-cancer interactions, offering new avenues for research and clinical application.

Mendelian randomization based on genome-wide association studies and expression quantitative trait loci, predicting gene targets for the complexity of osteoarthritis as well as the clinical prognosis of the condition.

Osteoarthritis (OA) entails a prevalent chronic ailment, marked by the widespread involvement of entire joints. Prolonged low-grade synovial inflammation serves as the key instigator for a cascade of pathological alterations in the joints. The study seeks to explore potential therapeutic targets for OA and investigate the associated mechanistic pathways. Summary-level data for OA were downloaded from the genome-wide association studies (GWAS) database, expression quantitative trait loci (eQTL) data were acquired from the eQTLGen consortium, and synovial chip data for OA were obtained from the GEO database. Following the integration of data and subsequent Mendelian randomization analysis, differential analysis, and weighted gene co-expression network analysis (WGCNA) analysis, core genes that exhibit a significant causal relationship with OA traits were pinpointed. Subsequently, by employing three machine learning algorithms, additional identification of gene targets for the complexity of OA was achieved. Additionally, corresponding ROC curves and nomogram models were established for the assessment of clinical prognosis in patients. Finally, western blotting analysis and ELISA methodology were employed for the initial validation of marker genes and their linked pathways. Twenty-two core genes with a significant causal relationship to OA traits were obtained. Through the application of distinct machine learning algorithms, MAT2A and RBM6 emerged as diagnostic marker genes. ROC curves and nomogram models were utilized for evaluating both the effectiveness of the two identified marker genes associated with OA in diagnosis. MAT2A governs the synthesis of SAM within synovial cells, thereby thwarting synovial fibrosis induced by the TGF-β1-activated Smad3/4 signaling pathway. The first evidence that MAT2A and RBM6 serve as robust diagnostic for OA is presented in this study. MAT2A, through its involvement in regulating the synthesis of SAM, inhibits the activation of the TGF-β1-induced Smad3/4 signaling pathway, thereby effectively averting the possibility of synovial fibrosis. Concurrently, the development of a prognostic risk model facilitates early OA diagnosis, functional recovery evaluation, and offers direction for further therapy.

The circadian syndrome is a better predictor for psoriasis than the metabolic syndrome via an explainable machine learning method - the NHANES survey during 2005-2006 and 2009-2014.

To explore the association between circadian syndrome (CircS) and Metabolic Syndrome (MetS) with psoriasis. Compare the performance of MetS and CircS in predicting psoriasis. An observational study used data from the NHANES surveys conducted in 2005-2006 and 2009-2014. We constructed three multiple logistic regression models to investigate the relationship between MetS, CircS, and their components with psoriasis. The performance of MetS and CircS in predicting psoriasis was compared using five machine-learning algorithms, and the best-performing model was explained via SHAP. Then, bidirectional Mendelian randomization analyses with the inverse variance weighted (IVW) as the primary method were employed to determine the causal effects of each component. A total of 9,531 participants were eligible for the study. Both the MetS (OR = 1.53, 95%CI: 1.07-2.17, P = 0.02) and CircS (OR = 1.40, 95%CI: 1.02-1.91, P = 0.039) positively correlated with psoriasis. Each CircS algorithmic model performs better than MetS, with Categorical Features+Gradient Boosting for CircS (the area under the precision-recall curve = 0.969) having the best prediction effect on psoriasis. Among the components of CircS, elevated blood pressure, depression symptoms, elevated waist circumference (WC), and short sleep contributed more to predicting psoriasis. Under the IVW methods, there were significant causal relationships between WC (OR = 1.52, 95%CI: 1.34-1.73, P = 1.35e-10), hypertension (OR = 1.68, 95%CI: 1.19-2.37, P = 0.003), depression symptoms (OR = 1.39, 95%CI: 1.17-1.65, P = 1.51e-4), and short sleep (OR = 2.03, 95%CI: 1.21-3.39, p = 0.007) with psoriasis risk. CircS demonstrated superior predictive ability for prevalent psoriasis compared to MetS, with elevated blood pressure, depression symptoms, and elevated WC contributing more to the prediction.

Strong evidence supports the use of estradiol therapy for the treatment of vaginal inflammation: a two-way Mendelian randomization study

ObjectiveNowadays, there has been limited Mendelian randomization (MR) research focusing on the causal relationship between estradiol and vaginitis. Therefore, this study conducted a two-way MR study to clarify the causal effect and related influencing factors between them.MethodsAll genetic datasets were obtained using publicly available summary statistics based on individuals of European ancestry from the IEU GWAS database. MR analysis was performed using MR-Egger, weighted median (WM) and inverse variance weighted (IVW) methods to assess the causal relationship between exposure and outcome and to validate the findings by comprehensively evaluating the effects of pleiotropic effects and outliers.ResultsMR analysis revealed no significant causal relationship between estradiol and vaginitis risk. There was a negative correlation between estradiol and age at menarche (IVW, OR: 0.9996, 95% CI: 0.9992–1.0000, P = 0.0295; WM, OR: 0.9995, 95% CI: 0.9993–0.9998, P = 0.0003), and there was a positive correlation between age at menarche and vaginitis (IVW, OR: 1.5108, 95% CI: 1.1474–2.0930, P = 0.0043; MR-Egger, OR: 2.5575, 95% CI: 1.7664–9.6580, P = 0.0013). Estradiol was negatively correlated with age at menopause (IVW, OR: 0.9872, 95% CI: 0.9786–0.9959, P = 0.0041). However, there was no causal relationship between age at menopause and vaginitis (P > 0.05). In addition, HPV E7 Type 16, HPV E7 Type 18, and Lactobacillus had no direct causal effects on estradiol and vaginitis (P > 0.05). Sensitivity analyses revealed no heterogeneity and horizontal pleiotropy.ConclusionWhen estrogen levels drop, it will lead to a later age of menarche, and a later age of menarche may increase the risk of vaginitis, highlighting that the longer the female reproductive tract receives estrogen stimulation, the stronger the defense ability is formed, and the prevalence of vaginitis is reduced. In conclusion, this study indirectly supports an association between reduced level of estrogen or short time of estrogen stimulation and increased risk of vaginitis.

The risk of Alzheimer's disease and cognitive impairment characteristics in eight mental disorders: A UK Biobank observational study and Mendelian randomization analysis.

The cognitive impairment patterns and the association with Alzheimer's disease (AD) in mental disorders remain poorly understood. We analyzed data from 486,297 UK Biobank participants, categorizing them by mental disorder history to identify the risk of AD and the cognitive impairment characteristics. Causation was further assessed using Mendelian randomization (MR). AD risk was higher in individuals with bipolar disorder (BD; hazard ratio [HR]=2.37, P<0.01) and major depressive disorder (MDD; HR=1.63, P<0.001). MR confirmed a causal link between BD and AD (ORIVW=1.098), as well as obsessive-compulsive disorder (OCD) and AD (ORIVW=1.050). Cognitive impairments varied, with BD and schizophrenia showing widespread deficits, and OCD affecting complex task performance. Observational study and MR provide consistent evidence that mental disorders are independent risk factors for AD. Mental disorders exhibit distinct cognitive impairment prior to dementia, indicating the potential different mechanisms in AD pathogenesis. Early detection of these impairments in mental disorders is crucial for AD prevention. This is the most comprehensive study that investigates the risk and causal relationships between a history of mental disorders and the development of Alzheimer's disease (AD), alongside exploring the cognitive impairment characteristics associated with different mental disorders. Individuals with bipolar disorder (BD) exhibited the highest risk of developing AD (hazard ratio [HR]=2.37, P<0.01), followed by those with major depressive disorder (MDD; HR=1.63, P<0.001). Individuals with schizophrenia (SCZ) showed a borderline higher risk of AD (HR=2.36, P=0.056). Two-sample Mendelian randomization (MR) confirmed a causal association between BD and AD (ORIVW=1.098, P<0.05), as well as AD family history (proxy-AD, ORIVW=1.098, P<0.001), and kept significant after false discovery rate correction. MR also identified a nominal significant causal relationship between the obsessive-compulsive disorder (OCD) spectrum and AD (ORIVW=1.050, P<0.05). Individuals with SCZ, BD, and MDD exhibited impairments in multiple cognitive domains with distinct patterns, whereas those with OCD showed only slight declines in complex tasks.