Idiopathic Sudden Sensorineural Hearing Loss (ISSHL) is a sudden onset, unexplained sensorineural hearing loss. Depression is a common mental disorder and a leading cause of disability. Here, We used a two-sample Mendelian randomization approach using pooled statistics from genome-wide association studies of ISSHL (1491 cases, 196,592 controls) and depression (23,424 cases, 192,220 controls) in European populations. This study investigated the bidirectional relationship between single nucleotide polymorphisms associated with depression and ISSHL using inverse variance weighting.Additional sensitivity analyses, such as Mendelian randomization-Egger (MR-Egger), weighted median estimates, and leave-one-out analysis, were performed to assess the reliability of the findings. Significant causal association between genetic susceptibility to ISSHL and depression in a random-effects IVW approach (OR = 1.037, 95% CI = 1.004-1.072, P = 0.030). In contrast, genetic depression was not risk factors for ISSHL (OR = 1.134, 95% CI = 0.871-1.475, P = 0.350). After validation by different MR methods and the sensitivity analysis, all of the above results are consistent. The evidence we have gathered suggests a causal relationship between ISSHL and depression. The presence of the former induces or further exacerbates the latter, whereas a similar situation does not exist when the latter is an influencing factor.

Self-reported shorter/longer sleep duration, insomnia, and evening preference are associated with hyperglycaemia in observational analyses, with similar observations in small studies using accelerometer-derived sleep traits. Mendelian randomization (MR) studies support an effect of self-reported insomnia, but not others, on glycated haemoglobin (HbA1c). To explore potential effects, we used MR methods to assess effects of accelerometer-derived sleep traits (duration, mid-point least active 5-h, mid-point most active 10-h, sleep fragmentation, and efficiency) on HbA1c/glucose in European adults from the UK Biobank (UKB) (n = 73,797) and the MAGIC consortium (n = 146,806). Cross-trait linkage disequilibrium score regression was applied to determine genetic correlations across accelerometer-derived, self-reported sleep traits, and HbA1c/glucose. We found no causal effect of any accelerometer-derived sleep trait on HbA1c or glucose. Similar MR results for self-reported sleep traits in the UKB sub-sample with accelerometer-derived measures suggested our results were not explained by selection bias. Phenotypic and genetic correlation analyses suggested complex relationships between self-reported and accelerometer-derived traits indicating that they may reflect different types of exposure. These findings suggested accelerometer-derived sleep traits do not affect HbA1c. Accelerometer-derived measures of sleep duration and quality might not simply be \'objective\' measures of self-reported sleep duration and insomnia, but rather captured different sleep characteristics.

Previous studies have reported an association between physical activity and the occurrence and progression of knee osteoarthritis (KOA). However, the existing evidence remains limited and of low-quality. This study aimed to examine the causal relationship between different levels of physical activity and KOA. Instrumental variables, represented by single nucleotide polymorphisms (SNPs), were utilized to capture sedentary behavior, appropriate physical exercise, and excessive physical activity. Aggregated statistics from the UK Biobank genome-wide association study dataset were used to assess the impact of these SNPs on KOA. Causality was estimated using inverse variance weighting (IVW), MR Egger, simple model, weighted median, and weighted model approaches. The stability of the results was assessed through heterogeneity and sensitivity analyses. Mendelian randomization (MR) analysis revealed a strong association between sedentary behavior and KOA, with an odds ratio (OR) of 2.096 (95% CI: 1.506-2.917) and a P value of 1.14 × 10-5. Appropriate physical exercise behavior exhibited a strong negative association with KOA, with an OR of 0.147 (95% CI: 0.037-0.582) and a P value of 0.006. Conversely, excessive physical activity behavior showed a significant positive association with KOA, with an OR of 2.162 (95% CI: 1.327-3.521) and a P value of .002. Our findings indicate that sedentary behavior and excessive physical activity are identified as risk factors for KOA, whereas engaging in appropriate physical exercise emerges as a protective factor against the development of KOA.

OBJECTIVE: To investigate causal associations between diabetes, insulin treatment and osteoporosis using LDSC analysis with a 2-way Mendelian randomization study.
METHODS: LDSC analysis was used to estimate the likelihood-scale heritability of the genome-wide association study used with genetic correlation between the 2 genome-wide association study used. Then a 2-sample Mendelian randomization study was performed using 3 methods including inverse variance weighted, MR Egger, and weighted median.
RESULTS: The genetic correlation between diabetes, insulin treatment (h2_Z = 3.70, P = 2.16e-4), osteoporosis (h2_Z = 4.93, h2_p = 8.13e-7) and genes was significant. There was a significant genetic correlation (rg = 0.122, P = 0.0211). There was a causal association between diabetes, insulin treatment and osteoporosis [P = 0.003754, OR (95%CI) = 0.998876 (0.998116-0.999636)], while no causal association existed between osteoporosis and insulin use (P = 0.998116-0.999636) causal association existed (P = 0.333244).
CONCLUSIONS: There was a strong genetic correlation between diabetes, insulin treatment and osteoporosis, a causal association between diabetes, insulin treatment and osteoporosis, and no causal association between osteoporosis and diabetes, insulin treatment.

Primary sclerosing cholangitis (PSC), a chronic cholestatic liver condition, is frequently associated with inflammatory bowel disease. Specific immune cells have been implicated in PSC pathogenesis with the emergence of the \"microbiota\" and \"gut lymphocyte homing\" hypotheses, albeit their identities remain controversial. The first genome-wide association analysis leveraged nonoverlapping data from 3757 Europeans to evaluate 731 immunophenotypes. A genome-wide association analysis comprising 2871 cases and 12,019 controls yielded summary statistics for PSC. An inverse-variance weighted (IVW) analysis was performed to identify immunophenotypes causally related to PSC, and the results were validated using weighted mode, MR-Egger, and weighted median methods. Comprehensive sensitivity analyses were performed to verify the robustness, heterogeneity, and horizontal pleiotropy of the results. IVW analysis revealed 26 immune traits exhibiting causal associations with PSC. CD3 on HLA-DR+ CD4+ (IVW odds ratio [OR]: 0.904; 95% confidence interval [CI]: 0.828-0.986, P = .023) and CD3 on secreting Treg (IVW OR: 0.893; 95% CI: 0.823-0.969, P = .007) were negatively associated with PSC susceptibility and demonstrated high consistency across the 3 validation methods. Moreover, 7 other immune traits, including CD39+ resting Treg absolute cell (IVW OR = 1.083, 95% CI: 1.013-1.157, P = .019), CD39+ secreting Treg absolute cell (IVW OR = 1.063, 95% CI: 1.012-1.118, P = .015), CD3 on naive CD8br (IVW OR = 0.907, 95% CI: 0.835-0.986, P = .022), CD3 on CD39+ activated Treg (IVW OR = 0.927, 95% CI: 0.864-0.994, P = .034), CD28 on resting Treg (IVW OR = 0.724, 95% CI: 0.630-0.833, P = 5.95E-06), and CD39 on CD39+ CD4+ (IVW OR = 1.055, 95% CI: 1.001-1.112, P = .044) exhibited consistent results in the Weighted Median and Weighted Mode validation methods. Moreover, no significant heterogeneity or horizontal pleiotropy was observed across the single nucleotide polymorphisms. The leave-one-out results revealed that sequentially eliminating each single nucleotide polymorphism had no significant influence on model effect estimates or qualitative inference. This study evaluated potential causal links between 731 immune traits and PSC susceptibility. Twenty-six immune traits were identified using the IVW method. Verification across multiple methods revealed 9 immune traits with a plausible causal connection to PSC. These findings may uncover mechanistic pathways and novel therapeutic approaches.

Observational studies have reported a relationship between multiple common dermatoses and mental illness. To assess the potential bidirectional causality between 3 skin disorders (psoriasis, eczema, and urticaria) and 4 psychiatric disorders (bipolar disorder, schizophrenia, major depressive disorder, and anxiety) in the European population, we used Mendelian randomization (MR) analysis, which provides definitive evidence for causal inference. Eligible single nucleotide polymorphisms were screened for dermatological and psychiatric disorders using a genome-wide association study database. We conducted bidirectional, 2-sample MR analysis using instrumental variables related to psoriasis, eczema, and urticaria as exposure factors, and bipolar disorder, schizophrenia, major depression, and anxiety as outcomes. Reverse MR analysis with bipolar disorder, schizophrenia, major depression, and anxiety as exposure and psoriasis, eczema, and urticaria as outcomes were also performed, and the causality was analyzed using inverse-variance weighting (IVW), MR-Egger, and weighted median methods. To thoroughly assess causality, sensitivity analyses were conducted using the IVW, MR-PRESSO, and MR-Egger methods. The results showed that bipolar disorder increased the incidence of psoriasis (odds ratio = 1.271, 95% confidence interval = 1.003-1.612, P = .047), heterogeneity test with Cochran Q test in the IVW showed P value > .05, (P = .302), the MR-Pleiotropy and MR-PRESSO (outlier methods) in the multiplicity test showed P value > .05, (P = .694; P = .441), and MR-Pleiotropy evidence showed no apparent intercept (intercept = -0.060; SE = 0.139; P = .694). Major depression increased the risk of eczema (odds ratio = 1.002, 95% confidence interval = 1.000-1.004, P = .024), heterogeneity test showed P value > .05, (P = .328), multiplicity detection showed P value > .05, (P = .572; P = .340), and MR-Pleiotropy evidence showed no apparent intercept (intercept = -0.099; SE = 0.162; P = .572). Sensitivity analyses of the above results were reliable, and no heterogeneity or multiplicity was found. This study demonstrated a statistically significant causality between bipolar disorder and psoriasis, major depression, and eczema in a European population, which could provide important information for physicians in the clinical management of common skin conditions.

Observational studies report inverse associations between educational attainment and depression/anxiety risks, but confounding hinders causal inference. This study aimed to assess potential causal relationships using Mendelian randomization (MR). Two-sample MR analysis was conducted using genetic instruments for education, smoking, body mass index, and physical activity from published genome-wide association studies. Depression and anxiety data came from the UK Biobank ([UKB] 117,782 individuals) and FinnGen (215,644 individuals) cohorts. Inverse variance weighted regression determined associations between exposures and mental health outcomes. Increased educational attainment was causally associated with reduced risks of depression (odds ratio [OR] = 0.99 per year, 95% confidence interval [CI]: 0.990-0.996, P < .001) and anxiety (OR = 0.99, CI: 0.98-0.991, P < .001) in both cohorts. Smoking initiation conferred higher risks of depression (UKB OR = 1.05, CI: 1.03-1.06, P < .001; FinnGen OR = 1.20, CI: 1.10-1.32, P < .001) and anxiety (FinnGen only, OR = 1.10, CI: 1.01-1.21, P < .05). Likewise, maternal smoking history associated with greater depression (UKB OR = 1.15, CI: 1.10-1.35, P = .027) and anxiety susceptibility (FinnGen OR = 3.02, CI: 1.67-5.46, P = .011). Higher body mass index elevated depression risk in both cohorts. Physical activity showed no clear associations. This MR study provides evidence that education may causally reduce mental health disorder risk. Smoking, obesity, and low activity appear detrimentally linked to depression and anxiety. Improving access to education could offer effective strategies for lowering population psychiatric burden.

Gut microbiota, a special group of microbiotas in the human body, contributes to health in a way that can\'t be ignored. In recent years, Mendelian randomization, which is a widely used and successful method of analyzing causality, has been investigated for the relationship between the gut microbiota and related diseases. Unfortunately, there seems to be a shortage of systematic bibliometric analysis in this field. Therefore, this study aims to investigate the research progress of Mendelian randomization for gut microbiota through comprehensive bibliometric analysis. In this study, publications about Mendelian randomization for gut microbiota were gathered from 2013 to 2023, utilizing the Web of Science Core Collection as our literature source database. The search strategies were as follows: TS = (intestinal flora OR gut flora OR intestinal microflora OR gut microflora OR intestinal microbiota OR gut microbiota OR bowel microbiota OR bowel flora OR gut bacteria OR intestinal tract bacteria OR bowel bacteria OR gut metabolites OR gut microbiota) and TS = (Mendelian randomization). VOSviewer (version 1.6.18), CiteSpace (version 6.1.R1), Microsoft Excel 2021, and Scimago Graphica were employed for bibliometric and visualization analysis. According to research, from January 2013 to August 2023, 154 publications on Mendelian randomization for gut microbiota were written by 1053 authors hailing from 332 institutions across 31 countries and published in 86 journals. China had the highest number of publications, with 109. Frontiers in Microbiology is the most prolific journal, and Lei Zhang has published the highest number of significant articles. The most popular keywords were \"Mendelian randomization,\" \"gut microbiota,\" \"instruments,\" \"association,\" \"causality,\" \"gut microbiome,\" \"risk,\" \"bias,\" \"genome-wide association,\" and \"causal relationship.\" Moreover, the current research hotspots in this field focus on utilizing a 2-sample Mendelian randomization to investigate the relationship between gut microbiota and associated disorders. This research systematically reveals a comprehensive overview of the literature that has been published over the last 10 years about Mendelian randomization for gut microbiota. Moreover, the knowledge of key information in the field from a bibliometric perspective may greatly facilitate future research in the field.

Several studies have confirmed the important role of endometrial cancer (EC) in the development and progression of breast cancer (BC), and this study will explore the causal relationship between EC and BC by 2-sample Mendelian randomization analysis. Pooled data from published genome-wide association studies were used to assess the association between EC and BC risk in women using 5 methods, namely, inverse variance weighting (IVW), MR-Egger, weighted median (WME), simple multimaximetry (SM) and weighted multimaximetry (WM) with the EC-associated genetic loci as the instrumental variables (IV) and sensitivity analyses were used to assess the robustness of the results. The statistical results showed a causal association between EC and BC (IVW: OR = 1.07, 95% CI = 1.01-1.32, P = .02; MR-Egger: OR = 1.21, 95% CI = 0.71-1.51, P = .11; weighted median: OR = 1.05, 95% CI = 0.97-1.31, P = .19; simple plurality method: OR = 0.98, 95% CI = 0.81-1.15, P = .78; weighted plurality method: OR = 0.98, 95% CI = 0.81-1.14, P = .75), and the results of the sensitivity analyses showed that there was no significant heterogeneity or multiplicity, and the results were stable. EC is associated with an increased risk of developing BC. The results of this MR analysis can be used as a guideline for screening for BC in women with EC and to help raise awareness of screening for early detection and treatment.

Colorectal cancer (CRC) is a significant public health issue owing to its widespread occurrence and substantial morbidity and mortality rates. Recent studies have highlighted serum uric acid (SUA) level as a probable risk factor for CRC; however, the inconsistency in these findings has created doubt. We performed a Mendelian randomization (MR) study utilizing extensive cohort data from the UK BioBank and the NHGRI-EBI Genome-Wide Association Study (GWAS) Catalog to investigate the causal connection between SUA levels and CRC incidence. Our MR study addresses the constraints of earlier studies, including limited sample sizes and inconsistent results. Considering SUA levels as the exposure and CRC as the outcome, the inverse variance-weighted (IVW) approach in MR showed that the odds ratios (ORs) for CRC for each unit increase in SUA were 0.232 (95% confidence interval [CI] of OR 0.094-0.570; P = .001) and 0.551 (95% CI of OR 0.325-0.934; P = .027). Pleiotropic tests and sensitivity analysis confirmed minimal horizontal pleiotropy and the robustness of causality. Our research deepens the understanding of the association between SUA levels and CRC, offering insights into prevention strategies and patient outcomes prediction.