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Sleep has attracted extensive attention due to its significance in health. However, its association with erectile dysfunction (ED) is insufficiently investigated. To investigate the potential causal links between sleep traits (insomnia, sleep duration, and chronotype) and ED, this study was performed. The single-nucleotide polymorphisms (SNPs) associated with insomnia, sleep duration, and chronotype were retrieved from previous genome-wide association studies (GWAS). A conventional two-sample Mendelian randomization (MR) was used to estimate the causal links between sleep traits and ED. The summary statistics of ED were from individuals of European ancestry (6175 cases vs 217 630 controls). As shown by the random effect inverse-variance-weighting (IVW) estimator, genetically predicted insomnia was causally associated with a 1.15-fold risk of ED (95% confidence interval: 1.07-1.23, P < 0.001). Sleep duration and morningness were not causally associated with ED, as indicated by the IVW (all P > 0.05). These findings were consistent with the results of sensitivity analyses. Based on genetic data, this study provides causal evidence that genetically predicted insomnia increases the risk of ED, whereas sleep duration and chronotype do not.

Objective: Observational studies have shown the association between iron status and osteoarthritis (OA). However, due to difficulties of determining sequential temporality, their causal association is still elusive. Based on the summary data of genome-wide association studies (GWASs) of a large-scale population, this study explored the genetic causal association between iron status and OA. Methods: First, we took a series of quality control steps to select eligible instrumental SNPs which were strongly associated with exposure. The genetic causal association between iron status and OA was analyzed using the two-sample Mendelian randomization (MR). Inverse-variance weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode methods were used for analysis. The results were mainly based on IVW (random effects), followed by sensitivity analysis. IVW and MR-Egger were used for heterogeneity testing. MR-Egger was also used for pleiotropy testing. Leave-one-SNP-out analysis was used to identify single nucleotide polymorphisms (SNPs) with potential impact. Maximum likelihood, penalized weighted median, and IVW (fixed effects) were performed to further validate the reliability of results. Results: IVW results showed that transferrin saturation had a positive causal association with knee osteoarthritis (KOA), hip osteoarthritis (HOA) and KOA or HOA (p < 0.05, OR > 1), and there was a negative causal association between transferrin and HOA and KOA or HOA (p < 0.05, OR < 1). The results of heterogeneity test showed that our IVW analysis results were basically free of heterogeneity (p > 0.05). The results of the pleiotropy test showed that there was no pleiotropy in our IVW analysis (p > 0.05). The analysis results of maximum likelihood, penalized weighted median and IVW (fixed effects) were consistent with our IVW results. No genetic causal association was found between serum iron and ferritin and OA. Conclusions: This study provides evidence of the causal association between iron status and OA, which provides novel insights to the genetic research of OA.

Background Stroke is a major cause of mortality and long-term disability worldwide. Whether the associations between brain imaging-derived phenotypes (IDPs) and stroke are causal is uncertain. Methods We performed two-sample bidirectional Mendelian randomization (MR) analyses to explore the causal associations between IDPs and stroke. Summary data of 587 brain IDPs (up to 33,224 individuals) from the UK Biobank and five stroke types (sample size range from 301,663 to 446,696, case number range from 5,386 to 40,585) from the MEGASTROKE consortium were used. Results Forward MR indicated 14 IDPs belong to projection fibers or association fibers were associated with stroke. For example, higher genetically determined mean diffusivity (MD) in the right external capsule was causally associated with an increased risk of small vessel stroke (IVW OR = 2.76, 95% CI 2.07 to 3.68, P = 5.87 × 10 −12 ). Reverse MR indicated that genetically determined higher risk of any ischemic stroke was associated with increased isotropic or free water volume fraction (ISOVF) in body of corpus callosum (IVW β = 0.23, 95% CI 0.14 to 0.33, P = 3.22 × 10 −7 ). This IDP is a commissural fiber and it is not included in the IDPs identified by forward MR. Conclusions We identified 14 IDPs with statistically significant evidence of causal effects on stroke or stroke subtypes. We also identified potential causal effects of stroke on one IDP of commissural fiber. These findings might guide further work toward identifying preventative strategies at the brain imaging levels.

Skin cancer (SC) is a significant public health issue, with increasing incidence rates globally. Although environmental factors such as ultraviolet (UV) exposure are recognized risk factors, the impact of metabolites on SC development has not been thoroughly examined. This study seeks to explore the causal association between metabolites and SC risks using a Mendelian randomization (MR) approach. Our analysis revealed a total of 76 metabolites associated with SC risk. Of them, leucine to N-palmitoyl-sphingosine ratio, glycerol to palmitoylcarnitine ratio, oleoyl-linoleoyl-glycerol levels, and hypotaurine-to-taurine ratio were strongly associated with SC. Notably, leucine to N-palmitoyl-sphingosine ratio and glycerol to palmitoylcarnitine ratio were linked to increased risk factors for SC. However, oleoyl-linoleoyl-glycerol levels and hypotaurine-to-taurine ratio served as the protective indicators of SC. This study highlights the potential role of metabolites in skin cancer etiology, suggesting that metabolic factors may serve as important targets for prevention and risk assessment strategies.

Numerous observational studies have identified a linkage between the gut microbiota and gastroesophageal reflux disease (GERD). However, a clear causative association between the gut microbiota and GERD has yet to be definitively ascertained, given the presence of confounding variables. The genome-wide association study (GWAS) pertaining to the microbiome, conducted by the MiBioGen consortium and comprising 18,340 samples from 24 population-based cohorts, served as the exposure dataset. Summary-level data for GERD were obtained from a recent publicly available genome-wide association involving 78 707 GERD cases and 288 734 controls of European descent. The inverse variance-weighted (IVW) method was performed as a primary analysis, the other four methods were used as supporting analyses. Furthermore, sensitivity analyses encompassing Cochran's Q statistics, MR-Egger intercept, MR-PRESSO global test, and leave-one-out methodology were carried out to identify potential heterogeneity and horizontal pleiotropy. Ultimately, a reverse MR assessment was conducted to investigate the potential for reverse causation. The IVW method's findings suggested protective roles against GERD for the ( = 0.027), (P = 0.026), ( = 0.026), and (P = 0.019). In contrast, ( = 0.037), (P = 0.049), and ( = 0.024) emerged as potential GERD risk factors. In assessing reverse causation with GERD as the exposure and gut microbiota as the outcome, the findings indicate that GERD leads to dysbiosis in 13 distinct gut microbiota classes. The MR results' reliability was confirmed by thorough assessments of heterogeneity and pleiotropy. For the first time, the MR analysis indicates a genetic link between gut microbiota abundance changes and GERD risk. This not only substantiates the potential of intestinal microecological therapy for GERD, but also establishes a basis for advanced research into the role of intestinal microbiota in the etiology of GERD.

BackgroundWhile targeted systemic inflammatory modulators show promise in preventing chronic kidney disease (CKD) progression, the causal link between specific inflammatory factors and CKD remains uncertain.MethodsUsing a genome-wide association study of 41 serum cytokines from 8,293 Finnish individuals, we conducted a bidirectional two-sample Mendelian randomization (MR) analysis. In addition, we genetically predicted causal associations between inflammatory factors and 5 phenotypes, including CKD, estimated glomerular filtration rate (eGFR), dialysis, rapid progression of CKD, and rapid decline in eGFR. Inverse variance weighting (IVW) served as the primary MR method, while MR-Egger, weighted median, and MR-pleiotropy residual sum and outlier (MR-PRESSO) were utilized for sensitivity analysis. Cochrane’s Q test for heterogeneity. Leave-one-out method ensured stability of MR results, and Bonferroni correction assessed causal relationship strength.ResultsSeventeen cytokines were associated with diverse renal outcomes. Among them, after Bonferroni correction test, higher tumor necrosis factor alpha levels were associated with a rapid decrease in eGFR (OR = 1.064, 95% CI 1.028 – 1.103, P = 0.001), higher interleukin-4 levels were associated with an increase in eGFR (β = 0.003, 95% CI 0.001 – 0.005, P = 0.002), and higher growth regulated oncogene alpha (GROα) levels were associated with an increased risk of CKD (OR=1.035, 95% CI 1.012 - 1.058, P = 0.003). In contrast, genetic susceptibility to CKD was associated with an increase in GROa, and a decrease in eGFR may lead to an increase in stem cell factor. We did not find the presence of horizontal pleiotropy during the analysis.ConclusionWe discovered causally related inflammatory factors that contribute to the initiation and progression of CKD at the genetic prediction level.

BackgroundThe causal association between the gut microbiome and the development of migraine and its subtypes remains unclear.MethodsThe single nucleotide polymorphisms concerning gut microbiome were retrieved from the gene-wide association study (GWAS) of the MiBioGen consortium. The summary statistics datasets of migraine, migraine with aura (MA), and migraine without aura (MO) were obtained from the GWAS meta-analysis of the International Headache Genetics Consortium (IHGC) and FinnGen consortium. Inverse variance weighting (IVW) was used as the primary method, complemented by sensitivity analyses for pleiotropy and increasing robustness.ResultsIn IHGC datasets, ten, five, and nine bacterial taxa were found to have a causal association with migraine, MA, and MO, respectively, (IVW, all P < 0.05). Genus.Coprococcus3 and genus.Anaerotruncus were validated in FinnGen datasets. Nine, twelve, and seven bacterial entities were identified for migraine, MA, and MO, respectively. The causal association still exists in family.Bifidobacteriaceae and order.Bifidobacteriales for migraine and MO after FDR correction. The heterogeneity and pleiotropy analyses confirmed the robustness of IVW results.ConclusionOur study demonstrates that gut microbiomes may exert causal effects on migraine, MA, and MO. We provide novel evidence for the dysfunction of the gut-brain axis on migraine. Future study is required to verify the relationship between gut microbiome and the risk of migraine and its subtypes and illustrate the underlying mechanism between them.

Background The relationship between gout pathogenesis and inflammatory cytokine alterations remains uncertain, with inconsistent findings across studies. This study evaluated the causal links between gout and 41 inflammatory cytokines using Mendelian randomization (MR). Methods Gout-related genetic variants were examined in two large public databases: the Finnish database with 8489 gout patients and 240,862 European ancestry controls and the Genome-Wide Association Studies (GWAS) catalog dataset with 375 gout cases and 455,973 European ancestry controls. Cytokine levels in 8293 healthy participants from the GWAS were analyzed. Moreover, univariate MR analysis, primarily the inverse variance weighting method, was applied to examine the causal association between these factors. The findings were further validated using four additional MR methods based on different modeling assumptions, and their robustness was examined through sensitivity analysis using the MR leave-one-out analysis, Cochran’s Q test, MR-Egger intercept test, and linkage disequilibrium score regression analysis. Results Following Bonferroni correction, this study unveiled a potential connection between macrophage inflammatory protein-1 beta (MIP 1B) and the risk of gout (OR: 1.08, 95%CI: 1.03-1.13, p = 9.61 × 10-4). Additionally, growth-regulated oncogene alpha (GROA) and macrophage migration inhibitory factor (MIF) were implicated in downstream gout development (OR: 1.04, 95%CI: 1.01-1.08, p = 0.02; OR = 1.04, 95%CI: 1.01-1.07, p = 0.0079). Sensitivity analyses confirmed the findings’ reliability and consistency. Conclusion Our study suggests that MIP 1B may be a risk factor for gout, and inflammatory cytokines such as GROA and MIF are involved in the progression of gout. This supports a causal relationship between inflammatory cytokines and gout.

Asthma and lung cancer are both significant public health concerns worldwide. Previous observational studies have indicated a potential link between asthma and an increased risk of lung cancer, whereas the causal relationship remains uncertain. We aimed to investigate the potential causal relationship between asthma and lung cancer risk utilizing Mendelian randomization (MR) design.The present study employed a two-sample MR analysis utilizing summary statistics from genome-wide association studies (GWAS) with European descent of asthma and lung cancer. The MR analysis was performed using inverse variance weighting (IVW), supplemented with MR-Egger regression and weighted median method to investigate the potential causality between asthma and lung cancer. Furthermore, Sensitivity analyses were also conducted to ensure the reliability of the findings. The MR analysis showed that genetically predicted asthma had suggestive causal association with the elevated risk of lung cancer [odds ratio (OR), 1.05 (95%Cl,1.01–1.09), P  = 0.01]. The consistent direction of effects observed in the three methods further supported this finding. In addition, sensitivity analyses demonstrated the reliability of the results. This study provided potential evidence supporting a causal association between asthma and lung cancer. These findings highlighted the importance of early detection and prevention strategies for lung cancer in individuals with asthma. Further research was needed to elucidate the underlying mechanisms linking asthma and lung cancer.