Most non-randomised controlled trials are unable to establish clear causal relationships in chronic obstructive pulmonary disease (COPD) due to the presence of confounding factors. This review summarises the evidence that the Mendelian randomisation method can be a powerful tool for performing causal inferences in COPD.

A non-systematic search of English-language scientific literature was performed on PubMed using the following keywords: 'Mendelian randomisation', 'COPD', 'lung function', and 'GWAS'. No date restrictions were applied. The types of articles selected included randomised controlled trials, cohort studies, observational studies, and reviews.

Mendelian randomisation is becoming an increasingly popular method for identifying the risk factors of COPD. Recent Mendelian randomisation studies have revealed some risk factors for COPD, such as club cell secretory protein-16, impaired kidney function, air pollutants, asthma, and depression. In addition, Mendelian randomisation results suggest that genetically predicted factors such as PM2.5, inflammatory cytokines, growth differentiation factor 15, docosahexaenoic acid, and testosterone may have causal relationships with lung function.

Mendelian randomisation is a robust method for performing causal inferences in COPD research as it reduces the impact of confounding factors.

We explored the causal relationship between certain dietary habits and the risk of developing diabetic kidney disease (DKD) using two-sample Mendelian randomization and multivariate Mendelian randomization.

This study is based on pooled data from a genome-wide association study (GWAS) of 83 dietary habits in a European population. We performed a two-sample Mendelian randomization analysis using GAWS data on diabetic nephropathy in a European population. Validation was then performed against positive results (p < 0.05) in different GAWS data on diabetic nephropathy of European origin. Finally, multivariate Mendelian randomization analyses were performed on dietary habits with positive results (p < 0.05) in both datasets and GWAS data on postprandial glucose in the European population.

This study showed causal relationships between 18 dietary habits and the risk of developing DKD. After validation, causal relationships were found between the risk of DKD and two dietary habits: abstaining from sugar consumption (OR 2.86; 95%CI 1.35, 6.08; p = 0.006) and consuming whole grain/multigrain bread (OR 0.53; 95%CI 0.32, 0.89; p = 0.016). Correcting for the effect of postprandial glucose, the multivariate MR results showed that never eating sugar increased the risk of developing DKD (OR 0.08; 95%CI 0.018, 0.36; p = 0.001), whereas eating whole grain/multigrain bread did not reduce the risk of developing DKD (OR 1.37; 95%CI 0.55, 3.41; p = 0.50).

Our MR results suggest a causal relationship between never eating sugar and an increased risk of developing DKD. Therefore, people with diabetes need a reasonable range of sugar intake.

Thyroid cancer (TC) is the most prevalent endocrine malignancy, with a rising incidence necessitating safer treatment strategies to reduce overtreatment and its side effects. Xiaoyao Powder (XYP), a widely used herbal formula, shows promise in treating TC. This study aims to investigate the mechanisms by which XYP may affect TC.

The components of XYP were identified through database retrieval, and targets related to TC were collected to construct a target network for key screening. GEO dataset samples analyzed immune cells and identified significantly differentially expressed core genes (SDECGs). Based on SDECG expression and clustering, samples were classified for comparison. WGCNA was employed to identify gene modules linked to clinical characteristics. ML models screened characteristic genes and constructed a nomogram validated using another GEO dataset. MR methods explored causal relationships between genes and TC.

The top ten active components of XYP were identified, along with 27 SDECGs that exhibited significant differences in immune cell infiltration between TC patients and normal controls. The nomogram effectively predicted TC risk, validated through ROC curves. Key characteristic genes included SMIM1, PPP1R16A, KIAA1462, DNAJC22, and EFNA5.

XYP may treat TC by regulating SMIM1, PPP1R16A, KIAA1462, DNAJC22, EFNA5, and associated immune pathways; this provides theoretical support for its potential mechanisms.

Though the pathogenesis of myopia remains unclear, emerging evidence suggests a potential link between the onset of myopia and systemic inflammation. This study aims to elucidate the causal relationships between the two via Mendelian randomization (MR).

We utilized genome-wide association study data on circulating inflammatory proteins (n = 14,824), immune cell traits (n = 3757), and myopia (n cases = 4106, n controls = 394,028) for a standard two-sample bidirectional MR analysis, followed by sensitivity analyses employing diverse approaches. The validation of seven inflammatory molecules was conducted through ELISA analysis of 116 plasma samples from a hospital-based cohort, as well as proteomics data from 3310 participants in the UK Biobank cohort.

Our analysis identified three inflammatory proteins (CXCL9, CXCL11, and T cell surface glycoprotein CD5) and six immune phenotypes, primarily related to T cells, as risk factors for myopia, and IL-5 and eight traits as protective factors. Meanwhile, we observed that myopia may elevate the levels of two inflammatory agents (TNFRSF9 and IL-24) and 12 peripheral immunophenotypes, predominantly associated with T cells and monocytes. Validation analysis in two independent cohorts further corroborated the proinflammatory state in highly myopic patients manifested by significantly elevated plasma levels of CXCL9, CXCL11, and TNFRSF9.

Our study identified a potential bidirectional causal relationship between systemic immune dynamics and myopia, underscoring the importance of considering myopia in the context of systemic condition. Research is warranted to further identify underlying mechanisms.

This study aims to examine the possible causal link between periodontal diseases and atrial fibrillation (AF), with a focus on the modifiable risk factors that facilitate this connection.

Firstly, bidirectional and multivariable Mendelian Randomisation (MR) analyses were conducted using genome-wide association studies (GWAS) data on periodontal disease (87,497 cases/259,234 controls) from FinnGen and AF (55,114 cases/482,295 controls) from AFGen. Then, a 2-step MR approach was employed to evaluate the mediating role and proportions of 25 candidate factors among the direct causality between periodontal disease and AF.

Periodontal disease was found to be associated with an increased risk of AF (odds ratio 1.16, 95% CI 1.027-1.314, p = .017), independent of other covariates such as dental caries, pulp, and periapical diseases. Conversely, no causal relationship was detected indicating that AF leads to periodontal disease condition. Furthermore, in the 2-step MR analysis, 5 out of 25 candidate mediators were screened as statistically significant. Ranked by partial mediation proportion, these modifiable mediators included weight (30.3%), IL-17 (17.2%), TNF (14.08%), coronary atherosclerosis (13.4%), and hypertension (11.6%).

Our findings demonstrated the genetic causality between periodontal disease and AF. Maintaining oral hygiene, adopting standardised periodontal therapy, and restricting body weight are critical goals for patients with periodontal disease to mitigate disease progression to AF.

There is growing evidence that tobacco smoking causes depression, but it is unclear which constituents of tobacco smoke (e.g. nicotine, carbon monoxide) may be responsible. We used Mendelian randomisation (MR) to measure the independent effect of nicotine on depression, by adjusting the effect of circulating nicotine exposure [via nicotine metabolite ratio (NMR)] for the overall effect of smoking heaviness [via cigarettes per day (CPD)] to account for the non-nicotine constituents of tobacco smoke.

Univariable MR and multivariable MR (MVMR) were used to measure the total and independent effects of genetic liability to NMR and CPD on major depressive disorder (MDD). Our primary method was inverse variance weighted (IVW) regression, with other methods as sensitivity analyses.

For the exposures, we used genome-wide association study (GWAS) summary statistics among European ancestry individuals for CPD (n = 143 210) and NMR (n = 5185). For the outcome, a GWAS of MDD stratified by smoking status was conducted using individual-level data from UK Biobank (n = 35 871-194 881).

Genetic variants associated with NMR (n = 6) and CPD (n = 53).

Univariable MR-IVW indicated a causal effect of CPD on MDD [odds ratio (OR) = 1.13, 95% confidence interval (CI) = 1.04-1.23, P = 0.003] but no clear evidence for an effect of NMR on MDD (OR = 0.98, 95% CI = 0.97-1.00, P = 0.134). MVMR indicated a causal effect of CPD on MDD when accounting for NMR (IVW: OR = 1.19, 95% CI = 1.03-1.37, P = 0.017; Egger: OR = 1.13, 95% CI = 0.89-1.43, P = 0.300) and weak evidence of a small effect of NMR on MDD when accounting for CPD (IVW: OR = 0.98, 95% CI = 0.96-1.00, P = 0.057; Egger: OR = 0.98, 95% CI = 0.96-1.00, P = 0.038).

The role of nicotine exposure in risk of depression cannot be entirely dismissed. However, the causal effect of tobacco smoking increasing depression risk appears to be largely independent of circulating nicotine exposure, which implies the role of alternative causal pathways.

Previous epidemiological studies have explored the association between obstructive sleep apnea (OSA) and osteoporosis (OP), with inconclusive results due to various biases. Herein, we sought to determine the causal association between OSA and OP through bidirectional two-sample Mendelian randomization analysis.

Summary-level data for OSA were acquired from the FinnGen consortium, while data for fractures and BMDs (FA-BMD, FN-BMD, LS-BMD and eBMD) were derived from the UKBB and GEFOS. The inverse variance weighted (IVW) method was conducted as the main method, and several supplementary methods were further utilized for sensitivity analysis to strengthen the reliability of our findings.

The study findings strongly suggest a causal association between OSA and FA-BMD based on the IVW method (BETA = 0.404; 95 % CI = 0.208, 0.599; p = 5.28 × 10-5). However, OSA showed no significant causal relationship with eBMD (BETA = 0.052; 95 % CI = -0.018, 0.123; p = 0.145), FN-BMD (BETA = 0.095; 95 % CI = -0.009, 0.2; p = 0.073), LS-BMD (BETA = 0.021; 95 % CI = -0.082, 0.124; p = 0.695), and fractures (OR = 0.998; 95 % CI = 0.907, 1.098; p = 0.971). The conclusions from other analytical strategies were generally aligned with those of the IVW. No definitive causal effect of OP on OSA was observed in reverse analysis.

This research provided clear evidence of a causal association between OSA and FA-BMD, shedding light on the potential impact of OSA on bone metabolism.

Circulating lipids and changes in lipid profiles have long been associated with the development of stroke but causal relationships remain unclear.In this study, we aimed to assess the causal relationships between lipid species and multiple stroke phenotypes to inform stroke prevention and treatment strategies. We conducted a two-sample Mendelian randomization analysis using data from genome-wide association studies. The primary method for causal assessment was inverse variance weighting (IVW), complemented by the MR-Egger, weighted median, and weighted mode methods. Sensitivity analyses, based on MR-Egger, MR-PRESSO, and Cochran's Q statistics, were also applied to reinforce the results. In total, potential causality was observed for 133 pairs of lipids with stroke types(P < 0.05). After multiple testing correction (PFDR < 0.05), potential causal associations remained for 10 pairs of lipids, including specific sterol esters and phosphatidylcholines, with various stroke subtypes. The findings demonstrate the significant role that genetically determined lipid profiles may play in the pathogenesis of stroke. Further research is needed to establish whether these biomarkers can be used for stroke prevention or treatment.

Previous studies have established associations between α-Klotho and frailty or sarcopenia; however, the causal nature of these relationships remains unclear. This study investigates the causal effects of α-Klotho on frailty and sarcopenia-related traits using Mendelian randomization (MR). Genetic instruments for circulating α-Klotho concentrations, frailty index (FI), low grip strength (LGS), appendicular lean mass (ALM), and walking pace were developed based on data from large genome-wide association studies. Two-sample MR analyses were performed, supplemented by sensitivity analyses to ensure the robustness of the findings. Reverse MR analyses were also conducted to explore potential reverse causation. The findings demonstrated an inverse causal relationship of circulating α-Klotho levels with FI (β = -0.020, 95% confidence interval [95% CI] = -0.036 to -0.004; p = 0.017) and LGS (β = -0.033, 95% CI = -0.061 to -0.004; p = 0.023). However, no causal relationship was observed between circulating α-Klotho levels and ALM or walking pace. Additionally, no evidence of reverse causation was identified between FI or sarcopenia-related traits and circulating α-Klotho levels. In conclusion, this MR analysis establishes an inverse causal relationship of circulating α-Klotho levels with both FI and LGS.

Observational studies suggest that gut microbiome (GM) may contribute to acute anterior uveitis (AAU) development, but causality remains unclear. This study was conducted to test whether specific GM taxa were causally associated with AAU.

The GM data were obtained from the DMP, which included 7738 individuals' faecal samples and an analysis of host genotype-taxa abundance associations. The AAU data were derived from the FinnGen Consortium (8624 cases and 473,095 controls). We primarily employed the inverse-variance weighted method, complemented by supplementary sensitivity analyses.

Higher abundance of Lachnospiraceae noname (OR = 0.86, 95% CI 0.81-0.91, P = 5.7 × 10-8), Alistipes finegoldii (OR = 0.87, 95% CI 0.78-0.96, P = 0.008), Erysipelotrichaceae (OR = 0.90, 95% CI 0.81-0.99, P = 0.037), Erysipelotrichia (OR = 0.90, 95% CI 0.81-0.99, P = 0.037), Erysipelotrichales (OR = 0.90, 95% CI 0.81-0.99, P = 0.037), and Bacteroides ovatus (OR = 0.93, 95% CI 0.87-1.00, P = 0.039) predicted a lower AAU risk. Conversely, higher abundance of Bifidobacterium catenulatum (OR = 1.06, 95% CI: 1.02-1.10, P = 0.005), Bacteroides coprocola (OR = 1.11, 95% CI: 1.02-1.21, P = 0.014), Parabacteroides unclassified (OR = 1.12, 95% CI 1.03-1.22, P = 0.010), and Prevotella (OR = 1.15, 95% CI: 1.01-1.29, P = 0.029) predicted a higher AAU risk. The results also showed a reverse causation from AAU to Bifidobacterium catenulatum (OR = 1.39, 95% CI: 1.03-1.86, P = 0.005).

This study suggests that specific GM is causally associated with AAU risk, warranting more mechanistic validation and clinical trials.

Epidemiological studies have shown that the association between thyroid dysfunction (TD) and oral lichen planus (OLP) is controversial, and the causal relationship remains ill-defined. This study aims to investigate their probable mutual causality using bidirectional Mendelian randomization (MR) analyses.

We extracted genetic instruments for OLP and 10 phenotypes of TD from the genome-wide association studies database. The inverse variance weighted method was primarily used to evaluate the bidirectional causal relationship between TD and OLP. The results' robustness was verified by sensitivity analysis (Cochran's Q test, MR-Egger intercept, and leave-one-out test). Bonferroni correction threshold (0.05/10) was applied to determine significant differences.

Forward MR analysis indicated that Hashimoto's thyroiditis (HT) was suggestively linked to a higher likelihood of developing OLP (P = .0077), while hypothyroidism significantly increased the risk of OLP occurrence (P = .0002). The reverse MR study found that OLP was suggestively related to the occurrence of hyperthyroidism (P = .0126) and thyroid cancer (P = .0244). Furthermore, OLP was found to significantly increase the risk of HT (P = 3.47 × 10-⁸), Graves' disease (P = 1.03 × 10-⁵), hypothyroidism (P = 1.08 × 10-⁸), and elevated thyroid-stimulating hormone levels (P = 1.99 × 10-⁶). No major pleiotropy or heterogeneity was detected (P > .05).

These findings suggest that hypothyroidism significantly increases the risk of OLP, while OLP may contribute to the development of autoimmune thyroid disorders, particularly HT, Graves' disease, hypothyroidism, and thyroid-stimulating hormone. These findings highlight the complex interaction between endocrine and immune systems, emphasizing the need for further research into shared molecular pathways and potential clinical implications.

This study provides a genetic foundation for understanding the relationship between TD and OLP, which aids early screening and diagnosis and informs therapy development.

The study aimed to explore the association between different sleep traits and all-cause mortality as well as to validate causality in the association through mendelian randomization (MR). We analyzed 451,420 European ancestry participants from the UK Biobank. Multivariable-adjusted Cox proportional hazards model was conducted to evaluate the association between sleep traits and all-cause mortality. In MR analysis, the inverse variance weighting (IVW) method was applied as the primary analysis to investigate the causal association between sleep traits and mortality. During a median follow-up period of 12.68 years, 34,397 individuals died. Observational analyses showed the multivariate-adjusted hazard ratio (HR) and 95% confidence intervals (CIs) for short sleep, long sleep, early chronotype, daytime sleepiness, daytime napping, and insomnia with mortality, 1.246 (1.195, 1.298), 1.735 (1.643, 1.831), 0.931 (0.909, 0.953), 1.276 (1.212, 1.344), 1.299 (1.254, 1.346), and 1.117 (1.091, 1.142) (All p < 0.0001). Based on UK Biobank, MR analysis indicated the association between daytime napping and an increased risk of all-cause mortality (odd ratio [OR]: 1.219, 95% CI: 1.071-1.387, p = 0.003), which may be largely attributable to cancer disease mortality (OR: 1.188, 95% CI: 1.009-1.399, p = 0.039). We found no causal association between sleep duration, short sleep, long sleep, chronotype, daytime sleepiness, insomnia, and mortality risk. The causal associations between sleep traits and all-cause mortality risk were directionally replicated in FinnGen. Our findings suggest a potential causal association between daytime napping and increased risk of all-cause mortality in middle-aged and older persons. The finding could have important implications for evaluating daytime napping habits to decrease the risk of mortality.

This study investigates the causal relationships between gut microbiota (GM), plasma inflammatory proteins (PIPs), and valvular heart disease (VHD) using two-sample Mendelian Randomization (MR) analysis. We also assess whether PIPs mediate the link between GM and VHD. We conducted bidirectional MR analyses to explore causal associations between GM, PIPs, and VHD, and used multivariable MR to test the independence of associations. Genome-wide association study (GWAS) data on 196 GM taxa, 91 PIPs, and VHD were analyzed. MR methods including inverse-variance weighted (IVW), MR-Egger regression, and weighted median approaches were applied. Sensitivity analyses ensured robustness. Actinobacteria and Defluviitaleaceae were associated with lower VHD risk, while Oxalobacteraceae increased risk. At the genus level, Intestinibacter, Lachnospiraceae NC2004 group, Oscillospira, and Ruminococcaceae UCG004 were protective, whereas Oscillibacter increased risk. Among PIPs, Interleukin-10, Interleukin-17C, Leukemia inhibitory factor receptor (LIFR), and monocyte chemoattractant protein 2 were protective, while TNF-beta elevated risk. Multivariable MR confirmed the independent roles of TNF-beta, LIFR, and MCP-2. Actinobacteria's protective effect appeared partially mediated through increased LIFR expression, accounting for 14% of the effect. Our findings suggest that modulating gut microbiota, particularly enhancing Actinobacteria, may serve as a novel strategy for VHD prevention and treatment.

Educational attainment is inversely related to sepsis risk, but the causal nature is still unclear. We therefore conducted the first Mendelian randomization (MR) study of genetically predicted educational attainment on sepsis that also uses a within-family genetic instrument for education. To further explore possible mechanistic pathways that can inform strategies to reduce sepsis risk, we examined the mediating effects of factors that are modifiable or can be prevented.

The association between genetically predicted educational attainment and sepsis was estimated using summary-level data from recent genome-wide association studies. Possible bias due to population stratification, dynastic effects, and assortative mating in the genetic instrument for education was evaluated using summary-level data from a within-sibship genome-wide association study. We used inverse variance weighted MR analysis to estimate the effect of one standard deviation increase in years of education on sepsis risk. The robustness of the findings was assessed in sensitivity analyses, applying weighted median, weighted mode, and MR Egger regression. Finally, we applied multivariable MR analyses to estimate the mediating effects of smoking initiation, alcohol consumption, body mass index, high-density lipoprotein (HDL)-cholesterol, systolic blood pressure and type 2 diabetes.

For each standard deviation increase in genetically predicted educational attainment (3.4 years), the odds ratio (OR) for sepsis was 0.72 (95% confidence interval (CI) 0.66 to 0.78). The results of the analysis using the within-sibship genetic instrument and other sensitivity analyses were in line with this finding: within-sibship OR 0.88 (95% CI 0.64 to 1.18), weighted median OR 0.70 (95% CI 0.62 to 0.80), weighted mode OR 0.70 (95% CI 0.43 to 1.13), and MR Egger OR 0.65 (95% CI 0.50 to 0.85). The mediation analysis showed that 56% of the effect of educational attainment on sepsis risk can be explained by modifiable or preventable factors.

Higher educational attainment is strongly associated with a reduced risk of sepsis, pointing to important socioeconomic differences in this disease. The results also suggest that interventions targeting modifiable or preventable factors could contribute to reducing the socioeconomic differences in sepsis risk.

Recent studies suggest a link between air pollution and lung cancer, but causality remains uncertain due to confounding and reverse causation. Mendelian randomization (MR) reduces such bias and offers a new way to explore this relationship. MR is a method that uses genetic variants as instrumental variables to assess the causal relationship between an exposure and an outcome, effectively controlling for confounding and reverse causation. The inverse-variance weighted method is a commonly used approach in MR analysis, which estimates the overall causal effect by weighting the effect ratios of multiple single nucleotide polymorphisms, assuming all instruments are valid. Based on 2-sample MR, this study incorporated 5 air pollution indices and conducted MR analyses with lung cancer outcome data from 2 different sources. Subsequently, a meta-analysis was performed on the primary inverse-variance weighted results, followed by multiple corrections of the thresholds after the meta-analysis to ensure accuracy. Finally, reverse causality was tested through MR analysis for air pollution indices significantly associated with lung cancer. And the selection criteria for instrumental variables were: P < 5 × 10⁻⁶, F > 10, minor allele frequency > 0.01, clump_kb = 10,000, and clump_r2 = 0.001. Five air pollution indices were analyzed using MR analysis and meta-analysis with lung cancer data from the FinnGen R12 and OpenGWAS databases. Multiple corrections were applied to the significance threshold results after the meta-analysis. The final results showed that only nitrogen dioxide (NO₂) exhibited a significant association, with an OR of 3.426 (95% CI: 1.897-6.186, P = 2.21 × 10⁻⁴). Additionally, the positive air pollution index NO₂ showed no evidence of reverse causality with lung cancer from either data source. This study demonstrates a significant causal association between NO₂ and lung cancer, indicating that NO₂ may be a potential risk factor for lung cancer.

This study aims to investigate the possible causal link between Hashimoto thyroiditis (HT), an autoimmune disorder, and metabolic-associated fatty liver disease (MAFLD), previously referred to as nonalcoholic fatty liver disease (NAFLD), a common metabolic condition. Using genome-wide association study data from large European populations, we performed a bidirectional Mendelian randomization (MR) analysis. We identified single nucleotide polymorphisms strongly associated with HT and MAFLD/NAFLD, which we used as instrumental variables to probe the causal relationship between these 2 conditions. The forward MR analysis, using the inverse variance weighted method, showed that HT may increase the risk of MAFLD/NAFLD (odds ratio = 1.065, 95% confidence intervals: 1.014-1.119, P = .011). However, the reverse MR analysis did not establish a significant causal effect of MAFLD/NAFLD on HT (P > .05). Sensitivity analyses were carried out to assess potential heterogeneity or pleiotropy, and the results supported the robustness of our findings, indicating no significant concerns. These results suggest that HT may be a risk factor for the development of MAFLD/NAFLD. The bidirectional MR study revealed an elevated risk of MAFLD/NAFLD in individuals with HT, but no causal relationship was found from MAFLD/NAFLD to HT in the opposite direction. This understanding could assist healthcare professionals in improving their comprehension and management of both HT and MAFLD/NAFLD, leading to more comprehensive clinical guidance for patients and promoting the development of interdisciplinary treatment strategies.

Prostate cancer remains a major global health burden for men, with its incidence and mortality steadily rising. Thyroid hormones, critical regulators of metabolism and cell growth, have been implicated in tumorigenesis, yet their specific role in prostate cancer risk remains unclear. This study systematically investigates the relationship between thyroid hormones and prostate cancer using multidimensional approaches.

A three-phase study design was employed: (1) A cross-sectional analysis of The National Health and Nutrition Examination Survey (NHANES) data to examine thyroid hormone levels (FT3 and T3) and prostate cancer risk; (2) Mendelian randomization (MR) analysis using genome-wide association studies (GWAS) data to explore causal relationships; (3) Bioinformatics analyses to annotate key Single Nucleotide Polymorphism(SNPs), identify related genes, and assess their biological roles in prostate cancer.

Observational analysis revealed significantly lower FT3 and T3 levels in high-risk prostate cancer patients, with adjusted models confirming an inverse association (p < 0.001). MR analysis supported a causal relationship between thyroid hormone replacement therapy and reduced prostate cancer risk (b < 0, p < 0.05). Four key genes-ADM5, INPP5B, NEURL4, and TYK2-were identified as downregulated in prostate cancer tissues, with prognostic and immune regulatory implications.

Thyroid hormones exhibit a protective role against prostate cancer. ADM5, INPP5B, NEURL4, and TYK2 emerge as potential biomarkers and therapeutic targets, warranting further mechanistic and clinical validation.

Lung cancer remains one of the leading causes of cancer-related mortality, with non-small cell lung cancer (NSCLC) accounting for 85% of cases worldwide. NSCLC pathogenesis and progression are intricately linked to inflammatory stimuli, immune evasion, and metabolic reprogramming. In this study, the impact of inflammation, immunity, and metabolism on NSCLC was investigated by a Mendelian randomization analysis taking 91 inflammatory factors, 731 immune cells, and 1400 metabolites as exposures, and the FinnGen database NSCLC cohort (ncases = 5315, ncontrol = 314,193) was the outcome. A number of metabolites, inflammatory proteins, and immune cells were identified as potentially associated with NSCLC based on mendelian randomization analysis. Validation in the UK Biobank database lung cancer cohort (ncases = 2671, ncontrols = 372,016) further confirmed the inhibitory role of the metabolite N-acetyl-aspartyl-glutamate (NAAG) on lung cancer. Subsequently, single-cell and protein-protein interaction analyses identified inflammatory protein expression patterns in NSCLC, distribution ratios of immune cells in NSCLC. Subsequent multi-omics network analysis showed key interaction nodes between NAAG and inflammatory proteins. These findings enhance the understanding of the roles of inflammation, immunity, and metabolism in NSCLC occurrence and progression, offering potential targets and strategies for further research on its treatment and management.

The genetic risk factors for hypertension are also high-risk factors for preeclampsia-eclampsia. This study examined the association of hypertension in family members with preeclampsia-eclampsia in pregnant women through two-sample Mendelian randomization (MR).

Mendelian randomization.

The data for hypertension in siblings, mother, and father were from the UK Biobank, including 364,661, 426,391, and 402,899 individuals, respectively. The data for preeclampsia-eclampsia were FinnGEN R9 (7217 cases and 194,266 controls). Inverse-variance weighted was used as the main analysis method. Weighted median, MR-Egger, simple mode, and weighted mode were complementary MR methods. Heterogeneity was detected using Cochran's Q-test, horizontal pleiotropy using MR-Egger regression, and driving single-nucleotide polymorphisms (SNPs) using the leave-one-out method.

Mendelian randomization analysis showed that hypertension in family members was positively correlated with preeclampsia-eclampsia risk. The risk of preeclampsia-eclampsia in pregnant women who have siblings with hypertension was the highest (OR = 179.41, 95 % CI: 23.10-1393.65, P = 6.98E-07), followed by hypertension in the mothers (OR = 26.83, 95 % CI: 5.42-132.87, P = 5.56E-05) and the fathers (OR = 18.97, 95 % CI: 1.28-281.29, P = 0.032). The MR-Egger regression test indicated no horizontal pleiotropy (P > 0.05). Cochran's Q-test showed that the effects of the included SNPs exhibited heterogeneity (P < 0.05). The leave-one-out analysis did not reveal SNPs driving the results by themselves.

The risk of preeclampsia-eclampsia in pregnant women who have siblings with hypertension was the highest, followed by pregnant women with a mother or father with hypertension. Having siblings with hypertension should be considered as a high-risk factor for the early prediction of preeclampsia-eclampsia.

Observational studies have increasingly acknowledged the influence of Phosphatidylinositol (PI) on metabolic syndrome (MetS). Nevertheless, the causal association between PI and MetS remains unclear due to the presence of confounding factors and the potential for reverse causation in observational settings. This study seeks to clarify the causal link between PI and MetS while investigating the role of mediating metabolites.

A two-sample Mendelian randomization (MR) analysis was performed to examine the association between PI and MetS, utilizing aggregated data from genome-wide association studies (GWAS). Additionally, a two-step MR approach was applied to quantify the mediation effect of metabolites on the PI-MetS relationship. The inverse variance weighted (IVW) method served as the primary analytical approach, complemented by various sensitivity analyses employing alternative techniques.

A significant positive association was found between genetically predicted PI and a 17% increased risk of MetS. Genetically predicted metabolites, including 4-cholesten-3-one (IVW: OR 1.264, 95% CI 1.076-1.483, p = 0.004), N-acetylalliin (IVW: OR 1.189, 95% CI 1.008-1.402, p = 0.040), and the Adenosine 5'-diphosphate to 5-oxoproline ratio (IVW: OR 1.191, 95% CI 1.045-1.357, p = 0.009), were each significantly associated with an increased risks of MetS, accounting for 14.50, 11.41%, 11.87% and % of the total effect, respectively. Notably, the Retinol to oleoyl-linoleoyl-glycerol ratio (IVW: OR 0.643, 95% CI 0.466-0.887, p = 0.007) mediated 62.6% of the effect, highlighting its pivotal role in the causal pathway linking PI to MetS. Moreover, 1-palmitoyl-2-dihomo-linolenoyl-GPC (IVW: OR 0.865, 95% CI 0.752-0.995, p = 0.042) and the Creatine to carnitine ratio (IVW: OR 0.853, 95% CI 0.740-0.983, p = 0.028) were associated with a reduced risk of MetS, demonstrating inhibitory effects within their respective pathways that accounted to 35.03% and 8.45% reductions in risk, respectively.

Our MR analysis demonstrated a positive association between PI and an increased risk of MetS. Furthermore, the metabolite-mediated PI significantly influenced MetS risk. These findings may offer valuable insights into the pathogenesis of MetS and inform future clinical research.

Glaucoma, characterized by the loss of retinal ganglion cells (RGCs), is a leading cause of blindness for which there are no neuroprotective therapies. To explore observations of elevated homocysteine in glaucoma, we elevate vitreous homocysteine, which increases RGC death by 6% following ocular hypertension. Genetic association with higher homocysteine does not affect glaucoma-associated outcomes from the UK Biobank and serum homocysteine levels have no effect on glaucomatous visual field progression. This supports a hypothesis in which elevated homocysteine is a pathogenic, rather than causative, feature of glaucoma. Further exploration of homocysteine metabolism in glaucoma animal models demonstrates early and sustained dysregulation of genes involved in one-carbon metabolism and the interaction of essential cofactors and precursors (B6, B9, B12, and choline) in whole retina and optic nerve head and RGCs. Supplementing these provides neuroprotection in an acute model and prevents neurodegeneration and protects visual function in a chronic model of glaucoma.

Observational studies have demonstrated a close association between polyunsaturated fatty acids (PUFAs) and acne. However, the findings of clinical trials have been inconsistent, leaving the causal relationship between PUFAs and acne unclear.

To investigate the causal association between genetically proxied PUFAs and acne risk.

Mendelian randomization (MR) was performed using single nucleotide polymorphisms associated with PUFAs as instrumental variables. The causal associations between PUFAs and acne were estimated among 115 006 UK Biobank participants and 363 927 participants of Finnish descent.

Genetically predicted docosahexaenoic acid (DHA) levels [β = -0.303, 95% confidence interval (CI) -0.480 to -0.126; P = 7.74 × 10-4] and its percentage to total fatty acids (β = -0.402, 95% CI -0.651 to -0.258; P = 5.91 × 10-6) showed a significant causal association with a decreased risk of acne. Conversely, genetically predicted percentages of linoleic acid (LA) in total fatty acids (β = 0.768, 95% CI 0.411-0.126; P = 2.87 × 10-4) and omega-6 : omega-3 ratio (β = 0.373, 95% CI 0.142-0.604; P = 4.48 × 10-3) were robustly associated with an increased risk of acne. These effects were attenuated after excluding a genetic variant of rs174528 located upstream of FADS1, highlighting the biologic link between FADS1 and delta-5 desaturase activity. Multivariable MR analysis indicated that PUFAs were causally associated with acne, independent of body mass index.

Our study indicates that high DHA levels and their ratios to total fatty acids have causal protective effects against acne, while high LA levels and omega-6 : omega-3 ratio are associated with increased acne risk. This association was largely attributable to the influence of genetic variants related to FADS1.

Recent research has increasingly suggested an association between changes in specific blood metabolites and prostate cancer (PCa) development. However, it remains unclear whether these observed associations represent a causal relationship. To reveal the potential causal associations between blood metabolites and PCa risk, we conducted a comprehensive two-sample Mendelian randomization (MR) analysis. We used genetic instruments for 514 and 490 metabolites from two independent comprehensive genome-wide association studies. These studies included 14,295 individuals of European ancestry from the INTERVAL/EPIC-Norfolk cohorts and 8299 individuals of European ancestry from the Canadian Longitudinal Study on Aging cohort. Summary statistics of PCa risk involving 122,188 cases and 604,640 controls of European ancestry individuals were analyzed. The associations between metabolites and PCa risk were evaluated using the inverse-variance weighted method, supplemented by sensitivity analyses including MR-Egger and MR-PRESSO tests. Additionally, we conducted a phenome-wide MR analysis to assess the potential side effects of targeting the identified metabolites for PCa intervention. Our analysis revealed 107 unique blood metabolites significantly associated with PCa risk, with 43 of these associations consistently replicated using instruments from two independent data sets. This study provides novel insights into the potential role of specific metabolites in the etiology of PCa, which warrants further investigations.

Previous studies have investigated the potential role of immune factors in chondrosarcoma (CHS). However, the causal relationship is unknown.

A two-sample Mendelian randomization (MR) was used to explore potential correlations between 731 immunocyte phenotypes, 91 inflammatory proteins, and CHS. The data were derived from published summary statistics of genome-wide association studies. Inverse-variance weighted was employed as the primary method. Furthermore, a range of analytical methods, including MR-Egger, weighted mode, and weighted median was used to enhance the robustness of the results. A two-step MR was used to assess the mediating effects of inflammatory proteins. Subsequently, sensitivity and MR Steiger directionality tests were performed.

MR analyses showed that 12 immunocyte phenotypes were positively correlated with CHS (P < 0.05, OR > 1), and 11 immunocyte phenotypes were negatively correlated with CHS (P < 0.05, OR < 1). Five inflammatory proteins were positively associated with CHS (P < 0.05, OR > 1). No heterogeneous or horizontal pleiotropy was found. The MR Steiger analysis found no statistically significant evidence of reverse causation. Mediation analysis did not identify any potential mediating effects.

Our study underscores the pivotal role of immune factors in CHS and offers insights that can inform future research.

The present research aimed to assess the potential causal relationship between systemic antioxidant capacity and male infertility using a two-sample Mendelian randomization approach. The primary MR analysis utilized the inverse variance weighted (IVW)method, supplemented by complementary analyses including MR-Egger, weighted mode, simple mode, and weighted median methods. For male infertility, the available summarized data were gained from the open database (IEU OPEN GWAS PROJECT), which includes a total of 680 male patients with infertility and 72,799 controls of European population.10 biomarkers related to systemic antioxidant capacity were examined to investigate their potential association with male infertility, including glutathione S-transferase (GST), superoxide dismutase(SOD), glutathione peroxidase(GPX), catalase (CAT), total bilirubin, albumin, α-tocopherol, ascorbate, retinol, and uric acid. MR analyses using IVW mode revealed that genetically determined systemic antioxidant capacity biomarkers had no causal effects on male infertility risk, including GST(OR = 1.08, 95%CI: 0.91-1.29, P = 0.35), SOD(OR = 0.83, 95%CI: 0.66-1.04, P = 0.11), GPX(OR = 1.12, 95%CI: 0.92-1.36,P = 0.26), CAT(OR = 1.04, 95%CI: 0.83-1.29, P = 0.75), total bilirubin(OR = 0.98, 95%CI: 0.94-1.01, P = 0.18), albumin(OR = 1.14, 95%CI: 0.73-1.76, P = 0.57), α-tocopherol(OR = 0.56, 95%CI: 0.03-9.38, P = 0.69), ascorbate(OR = 1.06, 95%CI: 0.24-4.60, P = 0.94), retinol(OR = 1.29, 95%CI: 0.34-4.96, P = 0.71), and uric acid (OR = 0.88, 95% CI : 0.67-1.17, P = 0.39). The current study found no significantly causal link between systemic antioxidant capacity and male infertility. Further research with larger sample sizes and data from different ethnicities is needed.

Background: Multiple myeloma (MM) is a hematologic malignancy closely associated with diets and metabolic disorders, showing an increasing incidence trend. Genome-wide association studies (GWAS) contribute to exploring the causal relationships between diets, metabolites, and MM, thereby revealing biological mechanisms underlying cancer progression. Methods: This study included large-scale GWAS data for two diets, four metabolomics, and MM. The two-sample Mendelian randomization (MR) analysis was conducted to assess causalities between these dietary patterns, metabolites, and MM. The MR analysis primarily employed the inverse variance weighted (IVW) method, supported by multiple sensitivity analysis and reverse MR analysis to validate significant associations. Mediation analysis identified specific metabolites mediating the causal relationships between diets and MM. Results: Univariate MR analysis suggested that coffee consumption (ORIVW = 2.72; 95% CI: 1.21-6.10; PIVW = 0.015, P_fdr = 0.022), decaffeinated coffee consumption (ORIVW = 7.10; 95% CI: 1.33-37.87; PIVW = 0.022, P_fdr = 0.022), ground coffee consumption (ORIVW = 4.04; 95% CI: 1.25-13.02; PIVW = 0.019, P_fdr = 0.022), instant coffee consumption (ORIVW = 6.13; 95% CI: 1.95-19.34; PIVW = 0.002, P_fdr = 0.008), and coffee max liking (ORIVW = 2.94; 95% CI: 1.23-7.03; PIVW = 0.015, P_fdr = 0.035) were associated with increased MM risk. Metabolomic MR analysis identified 19 plasma metabolites, 1 blood and urine biomarker, and 4 plasma lipids with significant association with MM. Mediation analysis indicated that hippurate and cinnamoylglycine mediated 35.55% (P < 0.001) and 21.85% (P = 0.002) of the genetically predicted effect of coffee consumption on MM risk, respectively. Cinnamoylglycine contributed 12.63% (P = 0.042) to the total causal effect of ground coffee consumption on MM. Hippurate (21.43%, P < 0.001), 3-hydroxyhippurate (4.39%, P = 0.031), and cinnamoylglycine (8.79%, P = 0.010) mediated the genetically predicted impact of instant coffee consumption on MM risk. Metabolic pathway analysis suggested that glutathione metabolism significantly contributes to MM pathogenesis (P = 0.002, FDR < 0.05). Conclusions: Our findings support the adverse causal effects of various coffee consumption on MM risk, identifying hippurate, 3-hydroxyhippurate, and cinnamoylglycine as key mediators, driving the relationship potentially through the glutathione metabolism pathway.

Ischemic stroke remains a leading cause of mortality and disability globally, emphasizing the urgent need for innovative preventative and therapeutic strategies. Taurine, a critical amino sulfonic acid, has garnered attention for its neuroprotective effects, yet its precise role in ischemic stroke remains elusive. This study utilized a bidirectional Mendelian Randomization (MR) approach to explore the causal relationship between plasma taurine levels and ischemic stroke risk, employing genome-wide association study (GWAS) datasets. In parallel, a novel high-sensitivity liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed to quantify plasma taurine levels in ischemic stroke patients and healthy controls. Our findings reveal a significant inverse association between taurine levels and stroke risk, with IVW analysis showing beta = -0.001 and P = 0.0085. Furthermore, LC-MS/MS analysis demonstrated that plasma taurine levels in patients with ischemic stroke were notably lower at 36.07 ± 5.37 μmol/L compared to controls at 108.66 ± 25.11 μmol/L, confirming taurine's potential as a protective factor. These results suggest taurine as a promising biomarker and therapeutic target for stroke prevention and recovery. This study not only highlights the importance of taurine in cerebrovascular health but also provides a foundation for personalized intervention strategies.

Previous research has indicated that certain personal traits are closely related to cervical cancer; however, owing to the limitations of observational studies, causality remains unclear. This pioneering study employs Mendelian Randomization (MR) analysis to explore the genetic links between personal traits and the risk of cervical cancer. We analyzed 22 personal traits and cervical cancer data from genome-wide association study (GWAS) databases. Utilizing instrumental variables identified from significant single nucleotide polymorphism (SNP) associations, we employed the Inverse Variance Weighted (IVW) method, along with the Weighted Median (WM) method and MR-Egger regression. A sensitivity analysis was conducted to confirm the robustness of the findings. Moreover, risk factor analyses were performed to explore potential mediators. Our results demonstrate positive causal relationships for smoking status (OR = 1.006, 95%CI 1.003-1.009, P < 0.001), smoking initiation (OR = 1.002, 95%CI 1.001-1.003, P = 0.02), past tobacco smoking (OR = 0.998, 95%CI 0.996-0.999, P = 0.023), age at first birth (OR = 0.999, 95%CI 0.998-0.999, P < 0.001), time spent watching television (OR = 1.005, 95%CI 1.002-1.007, P = 0.001), and duration of moderate to vigorous physical activity (OR = 0.997, 95%CI 0.995-0.999, P = 0.003). Smoking status, smoking initiation, and time spent watching television emerged as risk factors for cervical cancer, whereas past tobacco smoking, age at first birth, and duration of moderate to vigorous physical activity were identified as protective factors. No causal relationships were found between the remaining 16 personal traits and cervical cancer. This study establishes significant causal relationships between several personal traits and cervical cancer, providing valuable insights for cervical cancer prevention strategies and guiding future research directions. Moreover, it further explores the potential links between personal traits and cervical cancer.

Background: Adequate control for confounding is key to many observational study designs. Confounders are often identified based on subject matter knowledge from empirical investigations. Negative confounders, which typically generate type 2 error, i.e., false nulls, can be elusive. Such confounders can be identified comprehensively by using Mendelian randomization (MR) to search the wealth of publicly available data systematically. Here, to demonstrate the concept, we examined whether a common positive confounder, body mass index (BMI), is also a negative confounder of any common physiological exposures on health outcomes, overall and specifically by sex. Methods: We used an MR study, based on the largest overall and sex-specific genome-wide association studies of BMI (i.e., from the Genetic Investigation of ANthropometric Traits and the UK Biobank) and of relevant exposures likely affected by BMI, to assess, overall and sex-specifically, whether BMI is a negative confounder potentially obscuring effects of harmful physiological exposures. Inverse variance weighting was the main method. We assessed sex differences using a z-test. Results: BMI was a potential negative confounder for apolipoprotein B and total testosterone in men, and for both sexes regarding low-density lipoprotein cholesterol, choline, linoleic acid, polyunsaturated fatty acids, and cholesterol. Conclusions: Using BMI as an illustrative example, we demonstrate that negative confounding is an easily overlooked bias. Given negative confounding is not always obvious or known, using MR systematically to identify potential negative confounders in relevant studies may be helpful.

Pemphigus, a B-cell-mediated autoimmune disease, has been hypothesized to involve vitamin D due to its immunomodulatory effects on B-cell activity. However, observational studies on this association remain inconclusive due to confounding factors. This study used genome-wide association study (GWAS) data for bidirectional two-sample Mendelian randomization (MR) analysis to clarify causality.

Genetic instruments for serum vitamin D levels (61 SNPs) and pemphigus (3 SNPs) were analyzed via inverse variance weighting (IVW), weighted median, and MR-Egger regression. Forward MR analysis revealed no causal effect of vitamin Don pemphigus risk [IVW OR=0.835 (95% CI:0.318-2.189), P=0.623], consistent across sensitivity analyses. Conversely, reverse MR showed pemphigus did not influence vitamin D levels [IVW OR=1.000 (95% CI:0.993-1.006), P=0.867]. Heterogeneity (Cochran Q test) and pleiotropy (MR-Egger intercept) tests confirmed robustness of results.

Our findings challenge the presumed causal link between vitamin D and pemphigus, suggesting observed associations may arise from confounding factors. This underscores the need for mechanistic studies to explore alternative pathways in pemphigus pathogenesis.

The occurrence of ischemic heart disease (IHD), atrial fibrillation, and flutter demonstrates certain associations with inflammatory bowel disease (IBD), warranting further exploration at the genetic architecture level. This study focused on genome-wide association study (GWAS) data of IHD, atrial fibrillation and flutter, and IBD, analyzing from two dimensions: genetic correlation and shared locus identification. Initially, linkage disequilibrium score regression and genetic covariance analyzer were utilized to assess the overall genetic correlations. Subsequently, the association patterns of local genomic regions were determined using Local Ancestry Variance Association (LAVA) analysis. Mendelian randomization (MR) was employed to assess causal effects. The genetic overlap among different traits was analyzed based on the statistical framework of conditional/conjunctional false discovery rate (cond/conjFDR). Finally, shared loci across these traits were identified by integrating conjFDR analysis with GWAS multi-trait analysis (MTAG). At the genomic level, significant overall correlations were observed among IHD, atrial fibrillation and flutter, and IBD and Crohn's disease (CD), while associations with ulcerative colitis appeared less pronounced. At the local level, IHD and IBD (including subtypes) showed significant associations in multiple regions. However, atrial fibrillation and flutter exhibited local associations only in the context of CD. Through conjFDR analysis, the genetic overlap across these diseases was validated. Additionally, several shared genetic loci were identified by integrating conjFDR and MTAG analyses, with genes confirmed in both IHD and IBD (including subtypes), such as SMAD3, PLCG2, ZNF831, PTPN22, RP11-136O12.2, and RP11-449I17.5. Moreover, six common genes were identified in the analysis between atrial fibrillation and flutter and IBD (including subtypes), such as ZMIZ1, MTHFS, ERAP2, GNA12, and RP1-15D23.2. This study offers empirical evidence of the genetic association between IHD, atrial fibrillation and flutter, and IBD comorbidity, providing new insights for cases where IBD co-occurs with IHD or atrial fibrillation and flutter.

Several observational studies have reported epidemiologic associations between psoriasis and risk of some cancers, but systematic evidence is lacking. Our aim was to comprehensively estimate the association between psoriasis and the risk of 33 common cancers using systematical Mendelian randomization based on genetic data.

Forty-nine independent single-nucleotide polymorphisms (SNPs) significantly associated with psoriasis were extracted as instrumental variables from a large-scale meta-analysis study of genome-wide association study (GWAS) for psoriasis. Outcome GWAS data were obtained from the FinnGen consortium (n = 500,348), UK Biobank (n = 420,531), and other large-scale cancer datasets. The inverse-variance weighted (IVW) was used as the primary method to infer the association between psoriasis and risk of cancer, and finally the results from multiple databases were pooled by meta-analysis.

In the UK Biobank, genetically predicted psoriasis had a suggestive association with colon (OR = 1.055, 95%CI: 1.001-1.113, P = 0.046) and uterine corpus cancer (OR = 0.922, 95%CI: 0.852-0.997, P = 0.042). In the FinnGen consortium, psoriasis had a suggestive association with vulvar cancer (OR = 1.182, 95%CI: 1.023-1.366, P = 0.024), uterine corpus cancer (OR = 0.937, 95%CI: 0.883-0.993, P = 0.028), and prostate cancer (OR = 0.973, 95%CI: 0.948-0.999, P = 0.045). In an additional large-scale cancer dataset, psoriasis also showed a suggestive association with prostate cancer (OR = 0.968, 95%CI:0.942-0.995, P = 0.020). The meta-analysis confirmed the suggestive association of psoriasis with uterine corpus (OR = 0.931, 95% CI: 0.889-0.976, P = 0.003) and prostate cancer (OR = 0.976, 95% CI: 0.955-0.997, P = 0.023). Whereas the effect of psoriasis on colon and vulvar cancer was not in the same direction across different populations. Furthermore, no association between genetically predicted psoriasis and other cancers were observed.

This comprehensive MR study suggests that psoriasis may be a potential protective factor for uterine corpus cancer in women and prostate cancer in men.

Migraine ranks as the second-leading cause of global neurological disability, affecting approximately 1.1 billion individuals worldwide with severe quality-of-life impairments. Although adjustable risk factors-including environmental exposures, sleep disturbances, and dietary patterns-are increasingly implicated in pathogenesis of migraine, their causal roles remain insufficiently characterized, and the integration of multimodal evidence lags behind epidemiological needs.

We developed a three-step analytical framework combining causal inference, predictive modeling, and burden projection to systematically evaluate modifiable factors associated with migraine. First, two-sample mendelian randomization (MR) assessed causality between five domains (metabolic profiles, body composition, cardiovascular markers, behavioral traits, and psychological states) and the risk of migraine. Second, we trained ensemble machine learning (ML) algorithms that incorporated these factors, with Shapley Additive exPlanations (SHAP) value analysis quantifying predictor importance. Finally, spatiotemporal burden mapping synthesized global incidence, prevalence, and disability-adjusted life years (DALYs) data to project region-specific risk and burden trajectories through 2050.

MR analyses identified significant causal associations between multiple adjustable factors (including overweight, obesity class 2, type 2 diabetes [T2DM], hip circumference [HC], body mass index [BMI], myocardial infarction, and feeling miserable) and the risk of migraine (P < 0.05, FDR-q < 0.05). The Random Forest (RF)-based model achieved excellent discrimination (Area under receiver operating characteristic curve [AUROC] = 0.927), identifying gender, age, HC, waist circumference [WC], BMI, and systolic blood pressure [SBP] as the predictors. Burden mapping projected a global decline in migraine incidence by 2050, yet persistently high prevalence and DALYs burdens underscored the urgency of timely interventions to maximize health gains.

Integrating causal inference, predictive modeling, and burden projection, this study establishes hierarchical evidence for adjustable migraine determinants and translates findings into scalable prevention frameworks. These findings bridge the gap between biological mechanisms, clinical practice, and public health policy, providing a tripartite framework that harmonizes causal inference, individualized risk prediction, and global burden mapping for migraine prevention.

High serum uric acid (UA) levels have been linked to cancer development through chronic inflammation and oxidative damage. Traditional epidemiological studies have shown inconsistent results regarding the relationship between uric acid and gynecological cancers. This study uses Mendelian randomization (MR) to explore the potential association between serum UA levels and various gynecological cancers.

In this two-sample MR study, summary statistical data of the genome-wide association studies (GWASs) on serum UA levels were extracted from the UK Biobank (UKB), and those on gynecological cancers were obtained from the FinnGen consortium, the Epidemiology of Endometrial Cancer Consortium (E2C2), and the Ovarian Cancer Association Consortium (OCAC). Inverse variance weighted (IVW), weighted median, MR-Egger, weighted mode, MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and MR-Radial methods were utilized to investigate the bidirectional causal associations of serum UA levels with gynecological cancers. The evaluation indexes were odds ratios (ORs) and confidence intervals (CIs). Tests for horizontal pleiotropism and heterogeneity of instrumental variables (IVs) were performed, respectively using MR-Egger test and Cochran's Q statistics. In addition, leave-one-out and MR scatter plots were employed for sensitivity analyses.

IVW estimates suggested that serum UA levels elevated 1 unit had a potential causal association with higher odds of both cervical cancer (CC) (OR=1.147, 95% CI: 1.020-1.290) and invasive mucinous ovarian cancer (IMOC) (OR=1.199, 95% CI: 1.033-1.393). Also, endometrial carcinoma (EC) had a potential causal association with it (OR=1.012, 95% CI: 1.000-1.024). Additionally, sensitivity analyses showed the potential causal associations between UA and CC/IMOC were relatively robust.

An elevated serum UA level had potential associations with CC and IMOC, whereas patients with EC should pay attention to it in clinical practice, which may reduce the potential risk of gynecological cancers. However, further evidence is needed to clarify the true relationships between UA and gynecological cancers.

BackgroundDNA damage and repair (DDR) and structural atrophies in different brain regions were recognized as critical factors in the onset of Alzheimer's disease (AD).ObjectiveWe utilized Mendelian randomization (MR) to examine the causal effects of the DDR-related molecular traits on AD and the potential mediating roles of different brain region volumes.MethodsIn primary analysis, we utilized public genome-wide association studies of AD and summary data from existing molecular traits datasets, including gene expression, DNA methylation, and protein levels quantitative trait loci (eQTL, mQTL, and pQTL) in both blood and brain to examine their causal associations by summary-data-based MR analysis and additional five two-sample MR methods. Subsequently, mediation analysis explored the potential mediate roles of 13 imaging-derived brain volume phenotypes in the associations between the DDR pathways and AD through a network MR design.ResultsWe found that the volumes of the right thalamus proper and global cerebral white matter mediated the causal pathways from EGFR to AD and relatively weak mediation effects of the right lateral ventricle volume in the causal pathways involving CHRNE, DNTT, and AD.ConclusionsWe identified causal relationships among DDR pathways, specific brain region volumes, and AD. Monitoring the molecular traits of these DDR-related genes and developing targeted drugs may help detect and interrupt the early progression of AD.

Psoriasis has been suggested to be associated with urolithiasis. However, the existing literature is based on observational studies, which provide limited evidence for the causal relationship between these two conditions. This research aims to evaluate the causal association between psoriasis vulgaris and urolithiasis using 2-sample Mendelian Randomization (MR) analysis. Exposures and outcomes were sourced from genome-wide association study data. The psoriasis vulgaris dataset included 5072 patients and 4,78,102 controls. The urolithiasis dataset included 5347 patients and 2,13,445 controls. We used the inverse-variance weighted (IVW) method as our primary analytical strategy, augmented by MR-Egger regression and the weighted median method. Cochran Q test, MR-Egger regression, leave-one-out analysis and Steiger filtering were also conducted to evaluated the stability and credibility of the results. The IVW analysis showed a significant association between psoriasis vulgaris and urolithiasis (odds ratio [OR] = 1.073, 95% confidence interval [CI] = 1.017-1.131, P = .010). The results of weighted median analysis (OR = 1.071, 95% CI = 1.013-1.133, P = .017) and MR-Egger regression (OR = 1.072, 95% CI = 0.992-1.158, P = .12) indicated a consistent directional causality with the IVW analysis. There was no significant horizontal pleiotropy or heterogeneity in the analysis. Steiger filtering further confirmed the accuracy of the directional causality. In conclusion, this MR study supports a causal association between psoriasis vulgaris and urolithiasis.

Alzheimer's disease (AD), an escalating global public health concern, demonstrates complex pathogenesis involving both genetic predisposition and vascular components. Blood pressure variability (BPV) has been implicated in neurodegenerative diseases, but its causal relationship with AD remains unclear. This study aims to explore the causal relationship between BPV and AD by applying Mendelian randomization (MR) to genome-wide association study (GWAS) summary data. Genetic instruments were selected from BPV GWAS based on UK Biobank data, ensuring relevance and significance(p < 5 × 10⁻⁶). Genetic estimates on exposure were obtained from three databases: The The International Genomic of Alzheimer's Project (IGAP); Maternal family history of AD from UK Biobank (MFH-UKBB), and Paternal family history of AD from UK Biobank (PFH-UKBB). Proxy SNPs were manually selected if SNPs were not available in the exposure GWAS. Data harmonization was performed to ensure consistency in effect and reference alleles. Three MR statistical methods were employed to assess causal effects, including inverse variance weighting (IVW) with random or fixed effect, MR-Egger regression, and the Weighted Median Method. Sensitivity analyses to evaluate robustness were also employed. Six SNPs associated with systolic BPV and six SNPs associated with diastolic BPV were included. Significant causal effects of SBPV on AD were found on the PFH-UKBB dataset in all four methods. The odds ratios for AD per 10-unit increment in SBPV were 1.028, 1.015, and 1.015 for MR-Egger, IVW-MR, and weighted median, respectively. In contrast, only IVW methods found significant results for DBPV in the MFH-UKBB dataset. SBPV is a possible causal risk factor for AD, while the evidence for DBPV needs further study. BPV control should be an important treatment target in preventing dementia.

Alopecia areata, a common autoimmune disease, is not fully understood in terms of its cause. However, research suggests that an imbalance in specific blood metabolites may trigger immune system dysfunction, leading to an attack on hair follicles and ultimately resulting in alopecia areata.

Two-sample MR analysis was conducted to investigate the causal relationship between plasma metabolites and alopecia areata using various methods. Heterogeneity and pleiotropy were assessed, robustness of findings evaluated, and reverse MR performed for effect analysis.

The MR analysis found a positive causal relationship between alpha-ketoglutarate, propionylcarnitine (c3) and other metabolites with alopecia areata risk. Conversely, xylose 3-(3-hydroxyphenyl)propionate, glycochenodeoxycholate glucuronide (1) along with other metabolites, showed a protective effect against alopecia areata development. Both BWMR and MR-PRESSO confirmed the accuracy of the above results. Reverse MR revealed no reverse causality between plasma metabolites and AA. The robustness of the results was confirmed using the leave-one-out method, which demonstrated no influential instrumental variables affecting the outcomes while accounting for heterogeneity and eliminating horizontal gene pleiotropy effects on estimating causal effects.

This study establishes a causal relationship between plasma metabolism and alopecia areata, enhancing our understanding of its underlying mechanisms. These findings also provide valuable references for future screening and prevention strategies.

Understanding the impact of depression on brain aging benefits the prognosis of this disease and of the risk that other age-related brain disorders will develop in the same population. The aim of the present study was to explore the genetic effect of depression on longitudinal changes in brain structure throughout the lifespan using a Mendelian randomization approach. Summary data from a genome-wide association study of 195,321 to 377,277 participants in the FinnGen consortium were used to predict depression, anxiety disorders, mood disorders, and antidepressant use genetically. Data from 15,640 participants in the ENIGMA consortium were included to predict changes in 15 brain structures throughout the lifespan. The causal relationship between these depressive traits and the brain structure parameters was assessed by two-sample Mendelian randomization (including inverse-variance weighted). Sensitivity analyses were conducted for quality control. Depression slowed the decrease of cortical gray matter volume significantly throughout the lifespan (p = 0.001). Depression, anxiety, and mood disorders nominally decreased the rates of change of volume in the cerebellum gray matter, lateral ventricles, and cortical gray matter throughout the lifespan (p = 0.048, p = 0.021, p = 0.038, respectively). Antidepressants did not affect these rates of change significantly (p > 0.05). Sensitivity analyses confirmed the reliability of this study. Depression and its main symptoms have a slight effect on longitudinal changes in a few brain structures throughout the lifespan at the genetic level. These findings do not support the notion that depression affects macro-aging in the brain crucially.

The Polycystic ovary syndrome (PCOS), a prevalent endocrine disorder affecting women's reproductive and metabolic health, faces diagnostic challenges due to heterogeneous clinical presentations and the absence of reliable biomarkers. This study investigates the role of Glucosaminyl (N-acetyl) transferase 2 (GCNT2) in modulating sex hormone-binding globulin (SHBG) and its potential as a therapeutic target in PCOS pathophysiology.

A prospective cohort of 103 PCOS patients treated with oral contraceptives (2021-2024) was established. Bidirectional Mendelian randomization (MR) was employed to assess genetic associations and causal relationships between PCOS and SHBG. Molecular docking studies evaluated cryptotanshinone's binding affinity to key proteins (COL1A1, COL4A2, COL6A2) in the PI3K/Akt pathway. GCNT2's regulatory effects on collagen synthesis and extracellular matrix pathways. Pharmacokinetic profiling validated therapeutic viability.

Bidirectional MR revealed significant genetic associations (P < 0.001) and causal links between PCOS and SHBG, implicating GCNT2 as a key modulator. Cryptotanshinone exhibited strong binding affinity to PI3K/Akt signaling pathway proteins and favorable pharmacokinetic properties. Enrichment analyses highlighted GCNT2's role in collagen biosynthesis (FDR < 0.05) and extracellular matrix regulation.

This study identifies GCNT2 as a critical mediator of PCOS pathophysiology through SHBG modulation and collagen remodeling. Cryptotanshinone emerges as a promising therapeutic candidate, targeting PI3K/Akt signaling pathway with high specificity. These findings advance the understanding of PCOS mechanisms and provide a foundation for biomarker-driven diagnostics and precision therapeutics. Further validation in clinical trials is warranted to translate these insights into practice.

Emerging evidence suggests that dysregulated lipid metabolism contributes to Parkinson's disease (PD) risk, with chronic inflammation in the central nervous system (CNS) also playing a pivotal role. Although correlations between inflammatory responses, serum lipid metabolism, and PD risk are established, a causal relationship remains unclear. Building on previous findings linking higher serum triacylglycerol (51:4) levels to reduced PD risk, this study explores the potential causal associations between 38 triacylglycerol isoforms and PD risk using Mendelian randomization (MR). We utilized summary-level data from genome-wide association studies (GWAS) on PD, circulating immune cells, inflammatory proteins, and serum lipidomes-including 38 triacylglycerol isoforms, 15 sterol ester isoforms, and 46 phosphatidylcholine isoforms-to assess the relationship between serum lipid profiles and PD. Our analysis revealed that higher levels of serum triacylglycerol (51:4) and triacylglycerol (53:4) were associated with a reduced PD risk, whereas lower levels of phosphatidylcholine (17:0_18:1) and sterol ester (27:1/20:2) were linked to higher PD risk. Notably, multivariable MR analysis confirmed a robust causal association between increased serum triacylglycerol (53:4) and a 24% reduction in PD risk (1 SD higher triacylglycerol (53:4) leading to a 24% [95% CI, 0.54-0.97] risk reduction, p = 0.005). Mediation analysis suggested that circulating immune cells, rather than inflammatory proteins, may mediate the relationship between triacylglycerol (53:4) levels and PD risk. These findings establish a causal link between triacylglycerol (53:4) and PD risk, highlighting the potential role of immune modulation in PD pathogenesis.