OBJECTIVES: To analyze the potential causal relationship between gut microbiota and food allergy (FA) using two-sample Mendelian randomization (MR) methods. METHODS: Data from genome-wide association studies on gut microbiota and FA were utilized. MR analysis was conducted employing inverse variance weighting, MR-Egger regression, and weighted median methods to assess the causal relationship between gut microbiota and FA. Cochrane's Q test was used to evaluate heterogeneity of instrumental variables, MR-PRESSO analysis was conducted to test for outliers and pleiotropy, and MR-Egger regression was employed to assess horizontal pleiotropy. The "leave-one-out" method was used to evaluate the impact of removing individual single nucleotide polymorphisms on the causal relationship. RESULTS: Inverse variance weighting analysis revealed that the phylum Verrucomicrobia, family Verrucomicrobiaceae, order Verrucomicrobiales, genus Ruminococcaceae UCG013, and genus Akkermansia were negatively associated with FA (P<0.05). Sensitivity analyses confirmed the reliability of the findings, indicating no heterogeneity or pleiotropy present. CONCLUSIONS There is a causal relationship between gut microbiota and FA, with Verrucomicrobia, Verrucomicrobiaceae, Verrucomicrobiales, Ruminococcaceae UCG013, and Akkermansia potentially reducing the risk of developing FA. These findings provide potential targets for the treatment and prevention of FA; however, further research is needed to explore the specific mechanisms by which the microbiota influence FA.
Humans ; Mendelian Randomization Analysis ; Gastrointestinal Microbiome ; Food Hypersensitivity/microbiology* ; Genome-Wide Association Study ; Polymorphism, Single Nucleotide

OBJECTIVES: This study aimed to investigate the association between temporomandibular disorder (TMD) and insomnia using a two-sample Mendelian randomization (MR) approach. METHODS: Bidirectional MR analyses of two samples, TMD (n=377 277) and insomnia (n=375 359), were performed using genome-wide association study statistics published in the FinnGen database. Instrumental variables were first screened, and then inverse variance weighting (IVW) and MR-Egger were used as the main-effect assessment methods. Weighted median, weighted mode, and simple mode served as supplementary methods. We used IVW and MR-Egger to test for heterogeneity, as well as MR-Egger intercepts to assess the single nucleotide polymorphism (SNP) potential level of multiplicity effects. Sensitivity analyses were conducted based on leave-one-out to identify potentially influential SNPs. All analyses were conducted by using the two-sample MR R package and were considered statistically significant when P<0.05. RESULTS: MR analysis showed the presence of TMD on insomnia (OR=1.089, 95%CI: 1.017-1.166, P=0.014). Meanwhile, no effect of insomnia on TMD (OR=0.996, 95%CI: 0.964-1.029, P=0.816) was found. The sensitivity-analysis showed that no heterogeneity existed (P>0.05), and the presence of horizontal pleiotropy was not detected (P>0.05). Leave-one-out sensitivity analysis showed no single SNP, which may affect the causal relation. All findings indicated that the causal relationship between TMD and insomnia was not significantly affected by any individual SNP and that IV did not bias the results. CONCLUSIONS Results of MR analyses showed that TMD is a risk factor for insomnia, whereas insomnia is not a risk factor for TMD.
Humans ; Sleep Initiation and Maintenance Disorders/genetics* ; Mendelian Randomization Analysis ; Polymorphism, Single Nucleotide ; Temporomandibular Joint Disorders/complications* ; Genome-Wide Association Study

OBJECTIVES: To evaluate the causal association between circulating levels of zinc, magnesium, and other minerals and autism spectrum disorder (ASD). METHODS: A two-sample Mendelian randomization (MR) analysis was performed using summary statistics from large-scale genome-wide association studies of European populations, including 18 382 ASD cases and 27 969 controls. Genetic data for iron, calcium, and magnesium were obtained from the UK Biobank, and data for zinc and selenium were sourced from an Australian-British cohort. A total of 351 genetic instrumental variables were selected. Causal inference was performed using inverse-variance weighting as the primary analysis method. Sensitivity analyses were performed by Cochran's Q test and MR-PRESSO global test to assess the robustness of the findings. RESULTS: No statistically significant causal effect was observed for circulating zinc, magnesium, calcium, selenium, or iron levels on ASD risk (all P>0.05). The odds ratios and 95% confidence intervals from the inverse-variance weighting analysis were 0.934 (0.869-1.003) for zinc, 1.315 (0.971-1.850) for magnesium, 1.055 (0.960-1.159) for calcium, 1.015 (0.953-1.080) for selenium, and 0.946 (0.687-1.303) for iron. Sensitivity analysis revealed significant heterogeneity in the causal association between circulating calcium and ASD (P=0.006), while the effect estimate remained stable after MR-PRESSO correction (P=0.487). The causal effect estimates for the remaining minerals demonstrated good robustness. CONCLUSIONS This study did not find significant evidence supporting a causal association between circulating zinc, magnesium, calcium, selenium, or iron levels and ASD risk, providing important clues for the etiology of ASD and precision nutritional interventions.
Humans ; Mendelian Randomization Analysis ; Autism Spectrum Disorder/genetics* ; Magnesium/blood* ; Zinc/blood* ; Minerals/blood* ; Genome-Wide Association Study ; Selenium/blood*

OBJECTIVES: The gut microbiota plays a crucial role in the pathophysiology of various types of diabetes. However, the causal relationship between them has yet to be systematically elucidated. This study aims to explore the potential causal associations between gut microbiota and diabetes using a two-sample Mendelian randomization (MR) analysis, based on multiple taxonomic levels. METHODS: Eligible instrumental variables were extracted from the selected genome-wide association study (GWAS) data on gut microbiota. These were combined with GWAS datasets on type 1 diabetes (T1D), type 2 diabetes (T2D), and gestational diabetes mellitus (GDM) to conduct forward MR analysis, sensitivity analysis, reverse MR analysis, and validation of significant estimates. Microbial taxa with causal effects on T1D, T2D, and GDM were identified based on a comprehensive assessment of all analytical stages. RESULTS: A total of 2 179, 2 176, and 2 166 single nucleotide polymorphisms (SNP) were included in the MR analyses for gut microbiota with T1D, T2D, and GDM, respectively. MR results indicated causal associations between: Six microbial taxa (Eggerthella, Lachnospira, Bacillales, Desulfovibrionales, Parasutterella, and Turicibacter) and T1D; 9 microbial taxa (Verrucomicrobia, Deltaproteobacteria, Actinomycetales, Desulfovibrionale, Actinomycetaceae, Desulfovibrionaceae, Actinomyces, Alcaligenaceae, and Lachnospiraceae NC2004 group) and T2D; 10 microbial taxa (Betaproteobacteria, Coprobacter, Ruminococcus2, Tenericutes, Clostridia, Methanobacteria, Mollicutes, Methanobacteriales, Methanobacteriaceae, and Methanobrevibacter) and GDM. CONCLUSIONS This study identified specific gut microbial taxa that may significantly increase or decrease the risk of developing diabetes. Some findings were fully replicated in independent validation datasets. However, the underlying biological mechanisms of these causal relationships warrant further investigation through mechanistic studies and population-based research.
Gastrointestinal Microbiome/genetics* ; Humans ; Mendelian Randomization Analysis ; Genome-Wide Association Study ; Diabetes Mellitus, Type 2/genetics* ; Diabetes Mellitus, Type 1/genetics* ; Female ; Polymorphism, Single Nucleotide ; Diabetes, Gestational/genetics* ; Pregnancy

OBJECTIVES: Keloids are fibrotic skin disorders characterized by excessive collagen deposition and a high recurrence rate, closely associated with inflammatory mediators. However, existing epidemiological studies are limited by confounding factors and reverse causality, making it difficult to establish causation. This study aims to investigate the causal relationship between circulating cytokines and keloids using Mendelian randomization analysis. METHODS: Significant single nucleotide polymorphisms (SNPs) associated with circulating cytokines (exposures) and keloids (outcomes) were extracted from genome-wide association study (GWAS) summary datasets. Eligible SNPs were selected as instrumental variables (IVs). Exposure data were derived from a cytokine GWAS including 8 293 Finnish participants, and outcome data from a keloid GWAS based on the UK Biobank. The inverse-variance weighted (IVW) method served as the primary analytical approach to estimate causal effects, supplemented by weighted median (WME), MR-Egger regression, and other sensitivity analyses. Horizontal pleiotropy was assessed using MR-Egger regression and the MR pleiotropy residual sum and outlier (MR-PRESSO) test, while Cochran's Q test evaluated heterogeneity. Leave-one-out analysis was used to verify robustness and consistency. A reverse MR analysis was also conducted, with keloid as the exposure and cytokines as outcomes, to rule out reverse causation. RESULTS: IVW analysis identified significant positive causal associations between two cytokines and keloids-macrophage migration inhibitory factor (MIF) [odds ratio (OR)=2.081, 95% confidence interval (CI) 1.219 to 3.552, P=0.007] and monocyte chemoattractant protein-1 (MCP-1) (OR=1.673, 95% CI 1.036 to 2.701, P=0.035). Conversely, stem cell factor (SCF) showed a negative causal relationship with keloids (OR=0.518, 95% CI 0.269 to 0.998, P=0.049). Results from the MR-Egger and weighted median analyses were consistent with IVW findings. No evidence of horizontal pleiotropy was observed (P>0.05). Except for interleukin-6 (P=0.014), no heterogeneity was detected in other cytokines. Leave-one-out analysis further confirmed the robustness of the causal associations. In reverse MR analysis, keloids were causally related only to β-nerve growth factor (beta-NGF) (OR=1.048, 95% CI 1.002 to 1.095, P=0.039), with no heterogeneity or pleiotropy detected in most cytokines (P>0.05). CONCLUSIONS MIF and MCP-1 exhibit positive causal associations with keloid formation, while SCF shows a negative causal relationship. These findings provide new evidence for the causal involvement of inflammatory cytokines in keloid pathogenesis and offer potential molecular targets for developing novel keloid therapies.
Humans ; Keloid/blood* ; Mendelian Randomization Analysis ; Cytokines/genetics* ; Polymorphism, Single Nucleotide ; Genome-Wide Association Study ; Chemokine CCL2/genetics* ; Interleukin-6/genetics* ; Macrophage Migration-Inhibitory Factors/genetics* ; Male ; Stem Cell Factor/blood* ; Female ; Intramolecular Oxidoreductases

OBJECTIVES: To investigate the causal associations between autoimmune diseases and aplastic anemia (AA) using Mendelian randomization analysis. METHODS: Publicly available genome-wide association study (GWAS) data were utilized to obtain single nucleotide polymorphisms (SNPs) associated with autoimmune diseases and AA for analysis. The inverse variance weighted (IVW) method was employed as the primary analytical approach, with MR Egger, Weighted Mode, Weighted Median, and Simple Mode methods serving as complementary analyses. Heterogeneity and pleiotropy analyses were conducted using designated functions, and the robustness of Mendelian randomization results was assessed using leave-one-out analysis. RESULTS: The two-sample Mendelian randomization analysis using the IVW method revealed significant positive causal associations of rheumatoid arthritis (OR=1.094, 95% CI: 1.023-1.170, P=0.009, adjusted P=0.042), systemic lupus erythematosus (OR=1.111, 95% CI: 1.021-1.208, P=0.015, adjusted P=0.036), Hashimoto thyroiditis (OR=1.206, 95% CI: 1.049-1.387, P=0.009, adjusted P=0.029), and Sicca syndrome (OR=1.173, 95% CI: 1.054-1.306, P=0.004, adjusted P=0.035) with AA, which was supported by the results from the Weighted Median method. Sensitivity analyses indicated no evidence of pleiotropy or heterogeneity, and leave-one-out analysis confirmed the robustness of the causal relationships. No direct evidence was found linking Graves' disease, ulcerative colitis, Crohn's disease, autoimmune hepatitis, primary biliary cholangitis, or primary sclerosing cholangitis with AA (P>0.05, adjusted P>0.05), indicating a lack of causal association. Reverse Mendelian randomization results and multiple corrections indicated that AA was not an influencing factor for autoimmune diseases (adjusted P>0.05). CONCLUSIONS Our findings support at the genetic level that rheumatoid arthritis, systemic lupus erythematosus, Hashimoto thyroiditis, and Sicca syndrome are risk factors for AA, and confirm a causal association of the these 4 autoimmune diseases with an increased risk of AA.
Humans ; Mendelian Randomization Analysis ; Anemia, Aplastic/genetics* ; Autoimmune Diseases/complications* ; Polymorphism, Single Nucleotide ; Genome-Wide Association Study ; Arthritis, Rheumatoid/genetics* ; Lupus Erythematosus, Systemic/genetics* ; Genetic Predisposition to Disease

Pelvic organ prolapse (POP), whose etiology is influenced by genetic and clinical risk factors, considerably impacts women's quality of life. However, the genetic underpinnings in non-European populations and comprehensive risk models integrating genetic and clinical factors remain underexplored. This study constructed the first polygenic risk score (PRS) for POP in the Chinese population by utilizing 20 disease-associated variants from the largest existing genome-wide association study. We analyzed a discovery cohort of 576 cases and 623 controls and a validation cohort of 264 cases and 200 controls. Results showed that the case group exhibited a significantly higher PRS than the control group. Moreover, the odds ratio of the top 10% risk group was 2.6 times higher than that of the bottom 10%. A high PRS was significantly correlated with POP occurrence in women older than 50 years old and in those with one or no childbirths. As far as we know, the integrated prediction model, which combined PRS and clinical risk factors, demonstrated better predictive accuracy than other existing PRS models. This combined risk assessment model serves as a robust tool for POP risk prediction and stratification, thereby offering insights into individualized preventive measures and treatment strategies in future clinical practice.
Humans ; Female ; Pelvic Organ Prolapse/epidemiology* ; Middle Aged ; Risk Assessment/methods* ; China/epidemiology* ; Multifactorial Inheritance ; Aged ; Risk Factors ; Genome-Wide Association Study ; Genetic Predisposition to Disease ; Case-Control Studies ; Adult ; Polymorphism, Single Nucleotide ; Genetic Risk Score ; East Asian People

OBJECTIVE: To investigate the potential mechanisms of sepsis pathogenesis in intensive care unit (ICU), with a specific focus on the role of skin microbiota, and to evaluate the causal relationships between skin microbiota and ICU sepsis using Mendelian randomization (MR). METHODS: A two-sample MR analysis was performed using skin microbiota genome-wide association study (GWAS) summary data from German population cohorts as exposures, combined with ICU sepsis susceptibility and 28-day mortality GWAS summary data from the IEU OpenGWAS database as outcomes. The primary causal effect estimates were generated using the inverse variance weighted (IVW) method, supplemented by validation through MR-Egger and weighted median approaches. Heterogeneity and pleiotropy tests, along with sensitivity analyses, were conducted to evaluate the robustness of the results. RESULTS: Regarding risk of ICU sepsis, IVW analysis showed that order Pseudomonadales [odds ratio (OR) = 0.93, 95% confidence interval (95%CI) was 0.88-0.98], family Flavobacteriaceae (OR = 0.93, 95%CI was 0.90-0.96), and genus Acinetobacter (OR = 0.96, 95%CI was 0.93-0.99) were significantly negatively correlated with the risk of ICU sepsis (all P < 0.05). There was a significant positive correlation between the risk of ICU sepsis and the presence of β-Proteobacteria (OR = 1.05, 95%CI was 1.00-1.11) and Actinobacteria (OR = 1.05, 95%CI was 1.00-1.11), both P < 0.05. Regarding 28-day mortality of ICU sepsis, IVW analysis showed that phylum Bacteroidetes (OR = 0.92, 95%CI was 0.86-0.99), family Streptococcaceae (OR = 0.92, 95%CI was 0.85-0.98), family Flavobacteriaceae (OR = 0.90, 95%CI was 0.83-0.97), genus Streptococcus (OR = 0.92, 95%CI was 0.86-0.99), ASV016 [Enhydrobacter] (OR = 0.92, 95%CI was 0.87-0.98), and ASV042 [Acinetobacter] (OR = 0.92, 95%CI was 0.88-0.97) were significantly negatively correlated with the 28-day mortality of ICU sepsis (all P < 0.05); family Moraxellaceae (OR = 1.09, 95%CI was 1.00-1.18) and ASV008 [Staphylococcus] (OR = 1.08, 95%CI was 1.03-1.14) was significantly positively correlated with the 28-day mortality of ICU sepsis (both P < 0.05). Sensitivity analysis and MR-PRESSO showed no heterogeneity, pleiotropy, or horizontal pleiotropy between skin microbiota and ICU sepsis risk and 28-day mortality rate. Analysis of confounding factors showed that single nucleotide polymorphisms (SNPs) associated with relevant skin bacteria could independently and causally affect the risk of ICU sepsis or ICU sepsis related mortality rate, independent of other confounding factors. The Steiger test results indicated that the established causal relationship was not due to reverse causality. CONCLUSIONS Skin microbiota composition may influence both sepsis susceptibility and 28-day mortality in ICU settings. Family Flavobacteriaceae demonstrated protective effects against sepsis onset and mortality. These findings provide new perspectives for early detection and management strategies.
Humans ; Sepsis/mortality* ; Intensive Care Units ; Mendelian Randomization Analysis ; Microbiota ; Skin/microbiology* ; Genome-Wide Association Study ; Risk Factors ; Skin Microbiome

Early-onset colorectal cancer (EOCRC) shows a different epidemiological trend compared to later-onset colorectal cancer, with its incidence rising in most regions and countries worldwide. However, the reasons behind this trend remain unclear. The etiology of EOCRC is complex and could involve both genetic and environmental factors. Apart from Lynch syndrome and Familial Adenomatous Polyposis, sporadic EOCRC exhibits a broad spectrum of pathogenic germline mutations, genetic polymorphisms, methylation changes, and chromosomal instability. Early-life exposures and environmental risk factors, including lifestyle and dietary risk factors, have been found to be associated with EOCRC risk. Meanwhile, specific chronic diseases, such as inflammatory bowel disease, diabetes, and metabolic syndrome, have been associated with EOCRC. Interactions between genetic and environmental risk factors in EOCRC have also been explored. Here we present findings from a narrative review of epidemiological studies on the assessment of early-life exposures, of EOCRC-specific environmental factors, and their interactions with susceptible loci. We also present results from EOCRC-specific genome-wide association studies that could be used to perform Mendelian randomization analyses to ascertain potential causal links between environmental factors and EOCRC.
Humans ; Colorectal Neoplasms/etiology* ; Risk Factors ; Genome-Wide Association Study ; Genetic Predisposition to Disease/genetics*

Intelligence encompasses various abilities, including logical reasoning, comprehension, self-awareness, learning, planning, creativity, and problem-solving. Extensive research and practical experience suggest that there are sex differences in intellectual development, with females typically maturing earlier than males. However, the key genes and molecular network mechanisms underlying these sex differences in intellectual development remain unclear. To date, Genome-Wide Association Studies (GWAS) have identified 507 genes that are significantly associated with intelligence. This study first analyzed RNA sequencing data from different stages of brain development (from BrainSpan), revealing that during the late embryonic stage, the average expression levels of intelligence-related genes are higher in males than in females, while the opposite is observed during puberty. This study further constructed interaction networks of intelligence-related genes with sex-differential expression in the brain, including the prenatal male network (HELP-M: intelligence genes with higher expression levels in prenatal males) and the pubertal female network (HELP-F: intelligence genes with higher expression levels in pubertal females). The findings indicate that the key genes in both networks are Ep300 and Ctnnb1. Specifically, Ep300 regulates the transcription of 53 genes in both HELP-M and HELP-F, while Ctnnb1 regulates the transcription of 45 genes. Ctnnb1 plays a more prominent role in HELP-M, while Ep300 is more crucial in HELP-F. Finally, this study conducted sequencing validation on rats at different developmental stages, and the results indicated that in the prefrontal cortex of female rats during adolescence, the expression levels of the intelligence genes in HELP-F, as well as key genes Ep300 and Ctnnb1, were higher than those in male rats. These genes were also involved in neurodevelopment-related biological processes. The findings reveal a sex-differentiated intelligence gene network and its key genes, which exhibit varying expression levels during the neurodevelopmental process.
Female ; Intelligence/physiology* ; Male ; Sex Characteristics ; Animals ; Brain/growth & development* ; E1A-Associated p300 Protein/physiology* ; beta Catenin/physiology* ; Transcriptome ; Rats ; Gene Expression Profiling ; Genome-Wide Association Study