Positive Causal Relationship Research Articles

Association between estrogen and kidney function: population based evidence and mutual bidirectional Mendelian randomization study.

Previous studies have suggested a potential role of estrogen in the pathophysiology of chronic kidney disease (CKD); however, the association and causality between estrogen and kidney function remain unclear. The cross-sectional correlation between serum estradiol concentration and estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (ACR) was analyzed using data from the National Health and Nutrition Examination Survey 2013-2016. Causality was tested using mutual bidirectional Mendelian randomization (MR) approaches based on six large-scale GWAS studies. Weighted generalized multivariate linear regression was employed to estimate the association between estradiol and eGFR and ACR, and a restricted cubic spline analysis was utilized to investigate potential nonlinear relationships. A total of 8932 participants were included. Serum estradiol concentration was positively associated with eGFR after adjusting for potential covariates (β, 0.76; 95% CI 0.24 to 1.27) and with ACR (β, 5.99; 95% CI 1.62 to 10.36). A nonlinear positive association was found between estradiol and eGFR, while an inverse "V"-shaped relationship was seen with ACR. Sensitivity analyses confirmed the stability of the relationship between estradiol and eGFR but indicated a less robust association with ACR. Stratified analysis showed that the association between estradiol and eGFR was particularly significant in populations with CKD and hypertension. All forward MR analyses demonstrated a positive causal relationship between estradiol and eGFR, but no causality was found between estradiol and ACR. No reverse causal association was observed. Serum estradiol concentration was causally associated with eGFR. Further longitudinal research is needed to validate these findings.

Integrating network pharmacology with molecular docking and dynamics to uncover therapeutic targets and signaling mechanisms of vitamin D3 in Parkinson's disease.

Parkinson's disease (PD) is a chronic neurodegenerative disorder marked by dopaminergic neuron degeneration in the substantia nigra. Emerging evidence suggests vitamin D3 (VD) plays a therapeutic role in PD, but its precise molecular mechanisms remain unclear. This study employed network pharmacology and bioinformatics to identify VD's hub targets and related pathways. We identified 24 VD's anti-PD targets, with estrogen receptor 1, estrogen receptor 2 (ESR2), sodium-dependent norepinephrine transporter, and insulin-like growth factor 1 receptor emerging as hub targets. Gene enrichment analysis elucidated that VD's anti-PD mechanism is closely related to the estrogen signaling pathway. Additionally, two-sample Mendelian randomization suggested a positive causal relationship between 25-hydroxyvitamin D and estrogen levels in vivo. To verify the interaction between VD and the hub drug targets, we performed molecular docking and kinetic simulations, finding the strongest interaction between VD and ESR2. Further Mendelian randomization analysis of drug targets confirmed the significant effect of the ESR2 drug target on PD risk. Single-cell nuclear sequencing of dopaminergic neurons, coupled with GSEA analysis, indicated that ESR2 activation upregulates the neuroactive ligand-receptor interaction signaling pathway and downregulates the Parkinson's disease pathway, thereby exerting a neuroprotective effect. In summary, our findings suggest that VD supplementation can not only elevate estradiol levels in humans but also directly activate ESR2, thereby modulating the estrogen signaling pathway in PD patients and providing neuroprotection. These predictive biological targets offer promising avenues for future clinical applications in Parkinson's disease treatment.

Relationship between motivational climate, anxiety and average mark in pre-service physical education teachers: a cross-sectional study based on structural equation modelling approach

BackgroundMotivation is a variable that directly influences task orientation. Within the motivational sphere, the motivational climate determines whether a task is performed with an intrinsic or extrinsic.PurposeIt has been observed that depending on motivational orientations, anxiety levels and task performance can be increased. Likewise, there are differences in interests depending on the gender of individuals.MethodsThis research aims (a) To elaborate and adjust a theoretical model of the causal relationship of motivational climate on anxiety and academic performance and (b) To analyse the causal relationship between the motivational climate on anxiety and the average mark of the participants. Regarding the design, a comparative, cross-sectional and descriptive study was carried out on a sample of 558 trainee physical education teachers. The sample for this study is from southern Spain. Likewise, the branch of study of the sample is related to university degrees in education sciences and physical activity and sport sciences. The Beck Anxiety Inventory (BAI), Perceived Motivational Climate in Sport-2 and an ad hoc socio-demographic questionnaire were used to collect the data.ResultsIt is observed that the male sex presents a greater causal relationship of task climate (β=−0.259; p ≤ 0.05) and ego climate (β = 0.324; p ≤ 0.001) on anxiety. A stronger causal relationship of task climate (β = 0.340; p ≤ 0.001) and ego climate (β = 0.241; p ≤ 0.05) on mean score is also observed for the male population. The sample presents a negative causal relationship of anxiety on the average mark. This is higher for the male population (β=−0.126).ConclusionsMale students show a greater causal effect of motivational climate on anxiety and grade point average. Likewise, the causal relationship of task climate on the development of anxiety is negative for the study sample. In contrast, the ego climate exerts a positive causal relationship on the development of anxiety.

Mendelian randomization study of the relationship between blood and urine biomarkers and lung cancer.

Identifying suitable biomarkers is crucial for exploring the pathogenesis, early screening, and therapeutic monitoring of lung cancer. This study aims to analyze comprehensively the associations between lung cancer and biomarkers in blood and urine. Bidirectional two-sample Mendelian randomization (MR) was used to evaluate the potential causal relationships between blood and urine biomarkers and lung cancer. We obtained Single nucleotide polymorphisms (SNPs) related to lung cancer from the 2021 Finnish database of genome-wide association studies, including small cell lung cancer (SCLC), total non-small cell lung cancer (NSCLC), lung adenocarcinoma (LAC), and lung squamous cell carcinoma (LSCC).Data on blood and urine biomarkers were derived from the UK Biobank cohort, comprising 376,807 participants. We found a potential inverse causal relationship between total bilirubin and SCLC (β=-0.285, P=0.015, FDR=0.12). Urate was inversely associated with NSCLC (β=-0.158, P=0.004, FDR=0.036*). Serum calcium showed a possible inverse relationship with lung squamous cell carcinoma (β=-0.256, P=0.046, FDR=0.138), while urinary creatinine was positively associated (β=1.233, P=0.024, FDR=0.216). Non-albumin proteins (β=-0.272, P=0.020, FDR=0.180) and total protein (β=-0.402, P=0.009, FDR=0.072) were inversely related to lung squamous cell carcinoma. The AST/ALT ratio was positively associated with lung adenocarcinoma (β=0.293, P=0.009, FDR=0.072). Our reverse Mendelian randomization study found a positive causal association between small cell lung cancer and serum creatinine (β=0.022, P=0.002, FDR=0.018*), while it was inversely associated with the estimated glomerular filtration rate(eGFR)(β=-0.022, P=0.003, FDR=0.027*). A positive causal relationship was also observed with cystatin C (β=0.026, P=0.005, FDR=0.045*) and glycated hemoglobin HbA1c (β=0.013, P=0.014, FDR=0.028*). A negative causal relationship was observed with Gamma_glutamyltransferase (β=-0.013, P=0.019, FDR=0.152). For non-small cell lung cancer, a negative causal relationship was found with albumin (β=-0.024, P=0.002, FDR=0.016*), while a potentially positive causal relationship was observed with cystatin C (β=0.022, P=0.006, FDR=0.054). Possible negative causal relationships were also observed with phosphate (β=-0.013, P=0.008, FDR=0.072) and urinary potassium (β=-0.011, P=0.012, FDR=0.108), while a potential positive causal relationship was observed with C-reactive protein (β=0.013, P=0.040, FDR=0.280).Regarding lung squamous cell carcinoma, an inverse causal relationship was found with eGFR (β=-0.022, P=9.58e-06, FDR=8.62×10-5*), while a positive causal relationship was observed with serum creatinine (β=0.021, P=1.16e-4, FDR=1.05×10-3*). Potential positive causal relationships were observed with Urate (β=0.012, P=0.020, FDR=0.180), urea (β=0.010, P=0.046, FDR=0.141), and glycated hemoglobin HbA1c (β=0.020, P=0.049, FDR P=0.098), whereas a potential negative causal relationship was observed with sex hormone-binding globulin(SHBG) (β=-0.020, P=0.036, FDR=0.108).Lastly, adenocarcinoma was found to have a positive causal association with alkaline phosphatase (β=0.015, P=0.006, FDR=0.033*). Our study provides a robust theoretical basis for the early screening and therapeutic monitoring of lung cancer and contributes to understanding the pathogenesis of the disease.

Effects of Mental Disorders on Fibromyalgia Mediated by Insomnia: A Mendelian Randomization Study.

This study employed Mendelian randomization (MR) analysis to confirm the causal effects of mental disorders on fibromyalgia. The summary data for exposures, mediator, and outcome were extracted from the GWAS catalog project, IEU openGWAS project, and Finn biobank database. Significantly associated and independent single-nucleotide polymorphisms (SNPs) meeting the criteria of p < 5×10-8, r2 < 0.001, and kb = 10,000 were selected for MR analysis. We used univariate and multivariate Mendelian randomization (i) to investigate the causal relationship between mental disorders/insomnia and fibromyalgia and (ii) to examine the mediating role of insomnia. The inverse variance weighted (IVW) method along with other MR methods was employed for analysis, while sensitivity analyses were conducted to assess reliability and stability. The results provided strong evidence to confirm the causal and positive associations between depression (OR = 6.749; 95% CI: 2.293-19.868, P = 0.001), irritability (OR: 1.873, 95% CI: 1.023-3.428, P = 0.042), insomnia (OR: 8.395, 95% CI: 1.384-50.931, P = 0.021), and fibromyalgia. Moreover, a positive causal relationship was detected between depression (OR = 1.230; 95% CI: 1.178-1.285; P < 0.001), irritability (OR = 1.084; 95% CI: 1.046-1.122; P < 0.001) and insomnia. Multivariate Mendelian randomization analysis showed that insomnia mediated the effects of depression and irritability on fibromyalgia, and the proportion of insomnia-mediated cases ranged from 25.2% to 26%. This study showed a positive causal relationship between depression, irritability, insomnia, and fibromyalgia. Insomnia partly mediates this overall effect. Understanding the causal relationship between mental disorders and fibromyalgia and the mediating role of insomnia may provide more information for fibromyalgia intervention and prevention strategies.

Genetic Association of Chronic Pains and Analgesics With Telomere Length: A Mendelian Randomization Study

Objective: The aim of this study was to explore the causal relationships between chronic pains (back pain, facial pain, general pain, headaches, knee pain, hip pain, neck/shoulder pain, stomach/abdominal pain) and analgesics (codeine, diclofenac, ibuprofen, morphine, paracetamol, tramadol) with telomere length using Mendelian randomization methods. Methods: In the study, various statistical methods including inverse variance weighted (IVW), Mendelian Randomization-Egger, weighted median, simple mode, and weighted mode were used to investigate the relationships between chronic pains, analgesics, and telomere length. Heterogeneity and pleiotropy tests were conducted to ensure the accuracy of the results. Results: The results of the IVW analysis revealed positive causal relationships between hip pain (odds ratio (OR): 1.145; 95% confidence interval (CI): 1.021–1.285; p = .020), and stomach/abdominal pain (OR: 1.100; 95% CI: 1.008–1.200; p = 0.033) with telomere length. Use of tramadol (OR: 0.074; 95% CI: 0.009–0.605; p = 0.015) had a negative causal relationships with telomere length. Conclusion: This study found positive associations between hip pain and stomach/abdominal pain with telomere length, and a negative association between tramadol and telomere length. However, no significant causal relationships were found with other types of chronic pains and analgesics. This could help develop healthier chronic pain treatments, avoiding the abuse of analgesics.

Bayesian Belief Networks: Redefining wholesale electricity price modelling in high penetration non-firm renewable generation power systems

The transition of electricity generation from firm to non-firm renewable generation is driving changes in wholesale electricity price dynamics that are increasingly challenging to model due to the stochastic nature of wind and solar as the primary energy source. Robust pricing models are essential for optimising financial performance in liberalised electricity markets. The novelty of this paper is the application of Bayesian Belief Networks in the modelling of wholesale electricity price formation, specifically in power systems with a high penetration of non-firm renewable generation. This paper links the mathematical Bayesian representation to established statistical and computational approaches using a functional supply-side wholesale electricity market pricing model. In addition, the paper introduces a novel validation method employing volatility analysis to assess the case study's performance.The case study revealed that when the proportion of stochastic generation was ≥40 % penetration in a trading interval, the Bayesian Belief Network model's accuracy considerably outperformed the benchmark model with a Mean Absolute Scale Error of 1.43 compared to 1.63 in those intervals. Finally, the volatility analysis results challenged the prevailing notion of a positive causal relationship between non-firm renewable penetration and price volatility.

The shared genetic landscape of polycystic ovary syndrome and breast cancer: convergence on ER + breast cancer but not ER- breast cancer

BackgroundThe clinically high comorbidity between polycystic ovary syndrome (PCOS) and breast cancer (BC) has been extensively reported. However, limited knowledge exists regarding their shared genetic basis and underlying mechanisms.MethodLeveraging summary statistics from the largest genome-wide association studies (GWASs) to date, we conducted a comprehensive genome-wide cross-trait analysis of PCOS and BC. A variety of genetic statistical methods were employed to uncover potential shared genetic causes.ResultsOur analysis revealed genetic overlap between the three trait pairs. After partitioning the genome into 2,495 independent regions, we identified two loci, chr8: 75,011,700–76,295,483 and chr17: 6,305,079–7,264,458, with significant localized genetic correlations. Pleiotropic analysis under a composite null hypothesis identified 1,183 significant pleiotropic single nucleotide polymorphisms (SNPs) across three trait pairs. FUMA mapped 26 pleiotropic loci, with regions 16q12.2 and 6q25.1 duplicated across all three trait pairs, while COLOC detected three loci with colocalization evidence. Gene-based analysis identified 23 unique candidate pleiotropic genes, including the FTO shared by all trait pairs, as well as SER1, RALB, and others in two trait pairs. Pathway enrichment analysis further highlighted key biological pathways, primarily involving the significant biological pathways were the metabolism of regulation of autophagy, regulation of cellular catabolic process, and positive regulation of catabolic process. Latent Heritable Confounder Mendelian randomization (LHC-MR) supported a positive causal relationship between PCOS and both BCALL and ERPBC but not with ERNBC.ConclusionIn conclusion, our genome-wide cross-trait analysis identified a shared genetic basis between PCOS and BC, specific identical genetic mechanisms and causality between PCOS and various BC subtypes, which could better explains the genetics of the co-morbidity of PCOS and ERPBC rather than PCOS and ERNBC. These findings provide new insights into the biological mechanisms underlying the co-morbidity of these two complex diseases, which have important implications for clinical disease intervention, treatment, and improved prognosis.

Role of SIRPG gene in type 1 diabetes and lichen planus.

Type 1 diabetes (T1D) is a form of diabetes caused by pancreatic β-cell destruction and absolute insulin deficiency. Lichen planus (LP) is an idiopathic inflammatory skin disease of unclear etiology. The role of SIRPG gene dysregulation in T1D and LP remains unclear. Mendelian randomization (MR) using matched samples was employed to study causal relationship between T1D and increased risk of LP. T1D-related single nucleotide polymorphism identification was conducted. Datasets GSE156035 for T1D and GSE52130 for LP were obtained from gene expression omnibus. Differentially expressed genes were identified, analyses included weighted gene co-expression network analysis, functional enrichment, gene set enrichment analysis, and protein-protein interaction network construction and analysis. Heatmaps of gene expression levels were generated. Comparative toxicogenomics database was used to identify diseases most relevant to core genes. Inverse variance weighted, MR-Egger, weighted median methods estimated genetic predisposition between T1D and LP, showing consistent positive correlations using both weighted median and inverse variance weighted methods. Horizontal pleiotropy analysis with MR-Egger intercept indicated no evidence of significant directional pleiotropy (P = .70645) for LP. There was no evidence of directional pleiotropy effects between T1D and LP. One hundred eighteen differentially expressed genes were identified. In biological processes, they were mainly enriched in apoptosis, inflammatory response, insulin receptor signaling pathway, glucose metabolism. In cellular components, enrichment was observed in mediator complex and replication fork. In molecular function, they were concentrated in leukotriene receptor activity and helicase activity. Kyoto Encyclopedia of Genes and Genomes analysis revealed enrichment in metabolic pathways, PI3K-Akt signaling pathway, cell cycle, p53 signaling pathway, AGE-RAGE signaling pathway in diabetic complications. Weighted gene co-expression network analysis with a soft threshold power of 4. SIRPG showing high expression in both T1D and LP samples. There is a positive causal relationship between T1D and LP. Comparative toxicogenomics database analysis revealed associations of core genes with metabolic syndrome, lipid metabolism disorders, cardiovascular diseases, immune system diseases, peripheral neuropathic pain, and inflammation. SIRPG is highly expressed in both T1D and LP, providing a new insight into the pathogenesis of T1D and LP.

Investigating the correlation of hip circumference to cardiovascular disease and type-2 diabetes using Mendelian randomization.

This study aimed to assess the correlation between hip circumference (HC) and the risk of cardiovascular disease (CVD) and type 2 diabetes mellitus using Mendelian randomization (MR) to overcome observational study limitations. MR analysis utilized genetic variation from the MR Base in a two-sample analysis. Three methods were employed: MR-Egger regression, weighted median estimator, and inverse variance weighting (IVW). Data was acquired from MR Base, a platform summarizing genome-wide association study (GWAS) data for MR research. Publicly available summary statistics datasets from GWAS meta-analyses were used, with HC and HC adjusted for body mass index (BMI) as exposures. Data for CVD and type 2 diabetes mellitus were obtained as outcomes. Results indicated a positive causal relationship between HC and CVD (IVW: P = 1.84e-07, OR: 1.37, 95% CI: 1.22-1.54) as well as type 2 diabetes mellitus (IVW: P = 0.04, OR: 1.62, 95% CI: 1.02-2.56), independent of BMI. However, HC after BMI adjustment showed no significant causal relationship with CVD (IVW: P = 0.05, OR: 1.09, 95% CI: 1.00-1.19) and exhibited a negative association with type 2 diabetes mellitus (IVW: P = 0.00, OR: 0.76, 95% CI: 0.66-0.88), suggesting a protective effect against type 2 diabetes mellitus. After adjusting for BMI, adipose tissue concentrated in the hip region showed a protective effect against type 2 diabetes mellitus but not against CVD. These findings offer insights into diabetes prevention and treatment strategies, and may inform plastic surgery procedures. Further research is needed to validate these findings and explore underlying mechanisms.

Dissecting Causal Links Between Gut Microbiota, Inflammatory Cytokines, and Parkinson's Disease: A Mendelian Randomization Study.

The association between gut microbiota (GM) and Parkinson's disease (PD) has been well established, but whether there is a causal relationship between the two and whether inflammatory cytokines (ICs) act as mediators remain unclear. We utilized the summary databases of large-scale genome-wide association studies (GWAS) conducting Mendelian randomization (MR) analyses to investigate the causal relationships between GM, ICs, and PD. The inverse-variance weighted (IVW) method was primarily used to identify GM and ICs associated with PD and to examine the mediating role of ICs, supplemented by MR Egger and weighted median. Through MR analysis, we identified three positive causal relationships and six negative causal relationships between GM and PD. Additionally, there were three positive associations and five negative associations between ICs and PD. However, after adjusting for FDR, none of these associations were significant. In reverse MR analysis, we also found causal relationships between PD and various GM and ICs. Further, two-step MR analysis indicated that the negative impact of phylum Actinobacteria on PD may be mediated through Fms-related tyrosine kinase 3 ligand levels. This study strengthens the link between GM and the risk of PD, while also revealing the potential mediating role of ICs in the causal relationships between these factors.

Associations between maternal gestational diabetes mellitus and offspring cerebral palsy: a two-sample Mendelian randomization study.

Observational studies on the association between gestational diabetes mellitus (GDM) during pregnancy and pediatric neurological disorders (PNDs) such as cerebral palsy (CP), autism spectrum disorders (ASD), and epilepsy (EP) in offspring have yielded mixed findings, creating ambiguity in causal interpretations. The direct link between GDM and these PNDs remains unclear. Elucidating this connection is vital for developing effective early intervention strategies during pregnancy to mitigate the risk of PNDs in the offspring. This study utilizes a two-sample (2-sample) Mendelian randomization (MR) approach to investigate the causal relationship between GDM and its impact on CP, ASD, and EP in offspring. We employed 2-sample MR using 6 single nucleotide polymorphisms (SNPs) strongly associated with GDM. Summary-level data for CP, ASD, and EP were obtained from the Integrative Epidemiology Unit (IEU) Open Genome-Wide Association Study (GWAS) project, encompassing sample sizes of 217,278, 46,351, and 463,010, respectively. The robustness of our findings was assessed using the inverse variance-weighted (IVW) method along with additional sensitivity analyses. The results demonstrate that GDM is associated with a higher risk of offspring CP as determined by the IVW method [odds ratio (OR): 1.74; 95% confidence interval (CI): 1.27-2.37; P<0.001]. In contrast, no association was observed between GDM and ASD or EP. Additionally, alternative methods for sensitivity analyses showed consistent results, and there was no pleiotropy detected using MR-Egger regression (P=0.48). This study provides strong evidence supporting a positive causal relationship between genetically predicted GDM and the increased risk of offspring CP, with no observed correlation found with ASD or EP.

The causal relationship between trace element status and upper gastrointestinal ulcers: a Mendelian randomization study.

This study aimed to investigate the bidirectional causal relationships between trace elements (such as zinc, magnesium, phosphate, and folate) and upper gastrointestinal ulcers (including gastric and duodenal ulcers). We utilized a two-sample Mendelian randomization (MR) analysis to achieve this. We conducted a two-sample MR analysis using summary-level data from genome-wide association studies (GWAS) obtained from public genomics repositories. We utilized a range of MR methods, including inverse-variance weighted (IVW), MR-Egger, and weighted median methods, and conducted a meta-analysis to synthesize results across different datasets. To ensure the robustness of our findings, we performed extensive sensitivity analyses, including pleiotropy assessment, heterogeneity tests, and leave-one-out analysis. Our findings are significant, indicating a positive causal relationship between increased zinc levels and the risk of gastric ulcers. Moreover, magnesium and folate appear to offer potential protective effects against gastroduodenal ulcers (p < 0.05). The meta-analysis further supports the causal relationship between zinc and gastric ulcers (p < 0.05), confirming zinc's significant causal impact on this condition. The study confirms a positive causal relationship between zinc and gastric ulcers and highlights the complexity of how trace elements regulate the progression of upper gastrointestinal ulcers. These results provide a scientific basis for dietary recommendations regarding trace element intake in clinical and public health practices. They also offer new insights into effective prevention and treatment strategies for gastric and duodenal ulcers.

Causal role of immune cells in muscle atrophy: mendelian randomization study

Immune system and inflammation had a great influence on the progression of muscle atrophy. However, the causal relationship with specific immune cell traits remained uncertain. The aim of this study was to elucidate the genetic influences on these associations, providing insights into the underlying mechanisms of muscle atrophy. A bidirectional two-sample Mendelian randomization (MR) analysis was conducted to investigate the causal relationship between immune cell phenotypes and muscle atrophy. Data on immune cell phenotypes were obtained from a research cohort containing data on 731 immune cell phenotypes and data on muscle atrophy were sourced from a Finnish database. MR analysis was performed using the MR-Egger method, weighted median, inverse variance weighting, heterogeneity testing, sensitivity analysis, and multiplicity analysis, with results subjected to false discovery rate(FDR) correction. Additionally, the UK Biobank cohort was utilized as an external validation. A total of 31 immune phenotypes with causal relationships with muscle atrophy were identified, including various phenotypes of conventional dendritic cells, myeloid cells, T cells/B cells/natural killer cells, regulatory cells, and T cell maturation stages. Among them, 12 immune phenotypes were identified as exhibiting a positive causal relationship with muscle atrophy, while 19 immune phenotypes were demonstrated to have a negative causal association, highlighting the complex interactions between immune cells and muscle health. The results of the reverse MR analysis indicated that a negative correlation between muscle atrophy and CD28 on secreting Treg (OR = 0.9038, 95%CI:0.8308 ~ 0.9832, P = 0.0186). A significant positive correlation was revealed by external datasets between the CD25 on IgD + CD38- immune phenotype and the risk of muscle atrophy, which was consistent with the trend observed in the training group (OR = 1.1041, 95% CI: 1.1005–1.1076, P = 0.0263). No evidence of pleiotropy was observed, and the reliability of these findings was demonstrated by the leave-one-out analysis. The findings highlight significant correlations between certain immune cell features and muscle atrophy, providing potential targets for further investigation of immunological mechanisms and therapeutic interventions for this condition.

Cannabis use disorder increases risk of large-artery atherosclerotic stroke and migraine with aura through mendelian randomization study

Observational studies have shown some association between cannabis use disorder (CUD) and neurological disorders, but their causal relationship is unclear. In this study, we tested the potential causal relationship between CUD and three common neurological disorders using two-sample Mendelian randomization (TSMR) and multivariate MR (MVMR) methods. Thirty-two genetic loci were extracted as exposure factors from the largest genome-wide association study (GWAS) summary statistics for CUD to date. TSMR results showed that genetic prediction of CUD with all stroke, ischemic stroke, large-artery atherosclerotic stroke, migraine with aura, and Alzheimer’s disease (AD) had a positive causal relationship (P < 0.05), which was not found in several other diseases. The association between CUD and stroke, ischemic stroke, and AD in the MVMR study may have been influenced by confounding factors (P > 0.05). Subgroup analyses highlighted a causal relationship between genetically predicted CUD and large-artery atherosclerotic stroke (OR = 1.169; 95%CI 1.030–1.328; P = 0.016) and migraine with aura (OR = 1.142; 95% 1.021–1.278; P = 0.020). Our further functional mapping and annotation enrichment analyses using FUMA suggest that the brain-gut axis may serve as another layer of explanation for the existence of an association between CUD and neurological disorders.

Causal relationship between IgA nephropathy and common neuropsychiatric disorders: A two-sample Mendelian randomization analysis

ObjectiveUtilizing two-sample Mendelian randomization (TSMR), this study seeks to determine the causal relationship between IgA nephropathy and five prevalent neuropsychiatric disorders. By exploring the genetic associations between IgA nephropathy and neuropsychiatric disorders, this research aims to contribute to the prevention of neuropsychiatric disorders in patients with IgA nephropathy. MethodsPublic genome-wide association study databases were searched, with IgA nephropathy as the exposure factor, including 15,587 patients with IgA nephropathy and 462,197 healthy controls. The outcome factors were five common neuropsychiatric disorders (bipolar disorder, depressive disorder, schizophrenia, anorexia nervosa, and Alzheimer's disease), with outcome data drawn from five datasets in the PGC and GWAScatalog databases. Inverse-variance weighting served as the primary method for causal effect estimation, supplemented by MR-Egger, weighted median, weighted mode, and simple mode methods. Heterogeneity was tested using Cochran's Q test, and sensitivity analysis was conducted using MR-Egger and MR-presso. ResultsMR analysis indicated a positive causal relationship between IgA nephropathy and depressive disorder (OR = 1.010, 95%CI: 1.003–1.017, P = 3.27 × 10−3), and a potential positive causal relationship between IgA nephropathy and anorexia nervosa (OR = 1.165, 95%CI: 1.030–1.319, P = 0.015). ConclusionThere is a positive causal relationship between IgA nephropathy and depressive disorder, and a potential positive causal relationship with anorexia nervosa. No causal relationship was found with schizophrenia, bipolar disorder, or Alzheimer's disease.

Using genetic variations to reveal the complex relationships between vegetarianism and well-being, depressive symptoms and neuroticism.

The relationship between vegetarianism and mental well-being remains a debated topic in traditional observational studies. Recent studies have revealed the genetic factors in vegetarianism. We aimed to use genetic variations to explore the potential causal relationships between vegetarianism and mental well-being, offering insights from a new perspective. We conducted the inverse variance weighted approach as the primary analysis to explore the bidirectional genetic associations between vegetarianism (N = 442,589) and depressive symptoms (N = 180,866), neuroticism (N = 170,910), and subjective well-being (N = 298,420). The analysis used the summary data from the largest genome-wide association studies (GWAS). We also performed sensitivity analyses to ensure the robustness of the findings, accounting for potential heterogeneity and pleiotropy. Genetically predicted vegetarianism showed positive causal relationships with depressive symptoms (odds ratio [OR], 3.26; 95% confidence interval [CI], 1.03-10.31; p = 0.044) and neuroticism (OR, 6.72; 95% CI, 2.29-19.74; p = 5.31 × 10-4), as well as a negative causal relationship with subjective well-being (OR, 0.20; 95% CI, 0.05-0.77; p = 0.019). Additionally, depressive symptoms were found to have a causal influence on vegetarianism (OR, 1.01; 95% CI, 1.00-1.02; p = 6.87 × 10-3). No significant heterogeneity or pleiotropy was detected. Vegetarianism is causally correlated with negative mental well-being, reflected in an increased risk of depressive symptoms and neuroticism, as well as lower subjective well-being. Further research should explore the underlying mechanisms in broader populations.

Mitochondrial proteins as therapeutic targets in diabetic ketoacidosis: evidence from Mendelian randomization analysis.

Diabetic ketoacidosis (DKA) is a severe and potentially fatal acute complication in diabetic patients, commonly occurring in type 1 diabetes (T1D) but also seen in type 2 diabetes (T2D). The pathogenesis of DKA involves complex physiological processes that are not fully understood, especially the role of mitochondria. Mitochondria, known as the powerhouse of cells, plays a crucial role in oxidative phosphorylation and ATP production, which is vital in various metabolic diseases, including diabetes. However, the exact causal relationship between mitochondrial dysfunction and DKA remains unclear. This study employed Mendelian randomization (MR) analysis and protein-protein interaction (PPI) networks to systematically explore the causal relationships between mitochondrial DNA copy number (mtDNA-CN) and specific mitochondrial proteins with DKA. We used bidirectional MR analysis and genome-wide association study (GWAS) data from openGWAS database to investigate the causal effects of mtDNA-CN and 64 mitochondrial-related proteins on DKA and its subtypes (T1DKA, T2DKA, unspecified-DKA). The study revealed that increased mtDNA-CN significantly reduces the risk of DKA, whereas the effect of DKA on mtDNA-CN was not significant. Mitochondrial-related proteins such as MRPL32, MRPL33, COX5B, DNAJC19, and NDUFB8 showed a negative causal relationship with DKA, indicating their potential protective roles. Conversely, ATP5F1B and COX4I2 have a positive causal relationship with DKA, indicating that excessive ATP production in diabetic patients may be detrimental to health and increase the risk of severe complications such as DKA. The results emphasize the necessity of protecting mitochondrial function in order to reduce the risk of DKA. The study offers novel perspectives on the molecular pathways involved in DKA, emphasizing the critical functions of mt-DNA and distinct proteins. These evidences not only enhance our comprehension of the implications of mitochondrial dysfunction in diabetes-related complications but also identify potential therapeutic targets for individualized treatment approaches, thereby making a substantial contribution to clinical care and public health initiatives.

Breast cancer and neoplasms of the thyroid gland: a bidirectional two-sample Mendelian randomization study.

With the rising incidence of breast cancer (BC) and neoplasms of the thyroid gland, a potential link between the two has drawn increasing attention. However, the causal relationship remains unclear due to various confounding factors. This study aims to investigate the causality between BC and thyroid tumors using Mendelian Randomization (MR) analysis. We conducted a bidirectional two-sample MR analysis, utilizing breast cancer-associated single nucleotide polymorphisms (SNPs) from the Breast Cancer Association Consortium (BCAC) and thyroid tumor-related SNPs from the FinnGen (https://www.finngen.fi/) database. First, we performed univariable MR (UVMR) to assess the causal relationship between BC and both malignant and benign thyroid tumors, followed by reverse causality analysis. To account for potential confounders, we applied multivariable MR (MVMR). The inverse-variance weighted (IVW) method was primarily used, with secondary analyses performed using the weighted median and MR-Egger regression approaches. UVMR analysis revealed a significant positive causal relationship between BC and malignant thyroid tumors (odds ratio [OR] and 95% confidence interval [CI]: 1.291, 1.143-1.458, P = 3.90×10-5). No causal relationship was found between BC and benign thyroid tumors. The MVMR analysis, adjusting for confounding factors such as smoking, drinking, and body mass index (BMI), confirmed the robustness of the results. This study provides genetic evidence supporting a causal relationship between BC and malignant thyroid tumors. These findings highlight the importance of thyroid cancer screening in BC patients. However, further MR studies or randomized controlled trials (RCTs) are necessary to assess small effects accurately.

Identification of candidate genes for endometrial cancer in multi-omics: a Mendelian randomization analysis

Endometrial cancer is the most common malignant tumor of the uterus, but the underlying genetic mechanisms of EC remain unclear. To identify candidate genes and investigate genetic mechanisms for endometrial cancer, we utilized the summary-data-based Mendelian randomization (SMR) method to investigate causal associations between genetic variants, gene expression, DNA methylation, and endometrial cancer. Three main analyses were conducted utilizing cis-expression and methylation quantitative trait loci (eQTLs and mQTLs) as instrumental variables to examine causal relationships with endometrial cancer, and assessing the causal relationship between DNA methylation and gene expression. Data sources included genetic association data from O'Mara et al. eQTL data from the GTEx database, and mQTL data from McRae et al. Analysis involved the HEIDI test to distinguish pleiotropy, SMR analysis with multiple testing correction, and colocalization analysis to assess associations driven by linkage disequilibrium. Functional enrichment analysis was performed by the Metascape tool. Our study showed that three genes, SNX11, LINC00243, and EVI2A, were identified as causally related to endometrial cancer. SNX11 exhibited a positive causal relationship, while LINC00243 and EVI2A showed negative ones. Furthermore, 24 CpG sites were identified as causally related to endometrial cancer, with cg14424631 (CYP19A1) being the most significant. The study revealed common genes implicated in endometrial cancer, gene expression, and methylation sites, with LINC00243 playing a key role. Colocalization analysis confirmed significant causal relationships between LINC00243, SNX11, and endometrial cancer. Enrichment analysis uncovered pathways like interferon gamma signaling enriched in both endometrial cancer GWAS and e/mQTL. These findings shed light on the molecular mechanisms underlying endometrial cancer development. The study identified candidate genes and DNA methylation loci causally associated with endometrial cancer, which are expected to serve as potential targets for treatment.