A cross-population atlas of genetic associations for 220 human phenotypes

Mendelian randomization analysis of blood uric acid and risk of preeclampsia: based on GWAS and eQTL data

BACKGROUND

The causal association between blood uric acid and preeclampsia (Preeclampsia, PE) has not been conclusively established based on the literature reviewed to date. This bi-directional Mendelian randomization study aimed to investigate the bi-directional causal association between blood uric acid concentration and PE at different genetic levels.

METHODS

Pooled data on preeclampsia (sample size = 82,085) and blood uric acid (sample size = 129,405) were conducted based on publicly available genome-wide association analysis (Genome-Wide Association Study, GWAS) on the East Asian populations regarding preeclampsia and blood uric acid, respectively. We assessed blood uric acid and PE associations using two-sample Mendelian randomization (TSMR) analyses based on GWAS pooled statistics using inverse variance weighted (Inverse variance weighted), MR-Egger, and Weighted median (Weighted median) to examine the association between blood uric acid and pre-eclampsia. Causal relationship between blood uric acid and pre-eclampsia.Cochran's Q statistic was used to quantify the heterogeneity of instrumental variables among other methods. Subsequently, we extracted the expression quantitative trait loci (eQCTL, Expression quantitative trait loci) data corresponding to each gene as the instrumental variables using the genes corresponding to the intersecting instrumental variables of the exposure and the outcome in the respective analyses of the forward and backward TSMR respectively, so as to analyze the genetic causality of the genes with the different forward and backward TSMR methods further. Inverse variance weighted (IVW) was used to analyze the genetic causality of genes with different positive and negative outcomes.

RESULTS

Genetically determined blood uric acid level IVW method, ratio (OR) 1.30, 95% confidence interval (CI): [0.6, 2.83], p = 0.51 was not risk associated with PE. In addition according to the inverse MR analysis, we found an OR of 0.99, 95% CI [0.99, 1.0], p = 0.999) for PE on blood uric acid level IVW method and no significant heterogeneity in instrumental variables or level polytropy was found. (ii) Although GWAS data suggested no risk association between PE and uric acid, gene association analysis of eQTL data at blood uric acid levels with PE suggested a risk effect of the TP53INP1 gene for PE (IVW, OR = 11.476, 95% CI 2.511-52.452, p = 1.648 × 10-3) and a protective effect of CTSZ (IVW, OR = 0.011, 95% CI 0.001-0.189, p = 1.804 × 10-3), while a risk effect of ETV7 on hyperuricemia was suggested in a genetic association analysis of PE eQTL data with blood uric acid levels (OR = 1.018, 95% CI 1.007-1.029, p = 1.289 × 10-3).

CONCLUSION

Our MR (Mendelian Randomization) study based on the GWAS database did not support a bidirectional causal effect between blood uric acid levels and PE, whereas MR based on quantitative trait loci suggested that TP53INP1, which affects uric acid levels, has a risk association for PE, whereas CTSZ is protective against preeclampsia. Among the genes affecting PE the ETV7 gene may play a positive role in elevating uric acid levels.

Smoking as a causative factor in chronic kidney disease: a two-sample Mendelian randomization study

Smoking is widely acknowledged for its harmful effects on multiple organs. However, its specific causal relationship with chronic kidney disease (CKD) remains uncertain. This study applied bivariate causal analysis and two-sample Mendelian randomization (MR) methods to examine the association between various smoking behaviors - initiation, cessation, age at initiation, cigarettes smoked per day, and lifetime smoking - and CKD, using genome-wide data. The inverse variance weighted (IVW) method was the primary analytical tool, supported by sensitivity analyses, pleiotropy assessments, and mediation analyses. External validation was conducted using independent datasets. The results revealed positive associations between CKD and smoking initiation (Pivw = 1.8 × 10-2, OR = 1.192), earlier age at initiation (Pivw = 2.3 × 10-3, OR = 1.481), cigarettes smoked per day (Pivw = 8.8 × 10-3, OR = 1.216), and lifetime smoking (Pivw = 2.3 × 10-7, OR = 2.445). In contrast, smoking cessation demonstrated a protective effect against CKD (Pivw = 4.0 × 10-12, OR = 0.791). External validation results aligned with the primary findings, and the absence of significant heterogeneity confirmed the robustness of the MR analysis. Additionally, the effect of smoking on CKD was mediated by factors such as body mass index, cardiovascular disease, hypertension, and type 2 diabetes. These findings identify smoking as a contributing factor to CKD and suggest that reducing smoking prevalence could significantly lower the incidence of CKD in the population.

Dissecting the genetic basis and mechanisms underlying the associations between multiple extrahepatic factors and autoimmune liver diseases

Background

Autoimmune liver diseases (AILDs) encompass autoimmune hepatitis (AIH), primary biliary cholangitis (PBC), and primary sclerosing cholangitis (PSC). The onset of these diseases is fundamentally influenced by genetic susceptibility. Although various extrahepatic factors are potentially linked to AILDs, the genetic underpinnings and mechanisms of these associations remain unclear.

Methods

Utilizing large-scale genome-wide association study (GWAS) data, this study systematically investigated the relationships between extrahepatic autoimmune diseases (EHAIDs), immune cells, and various triggering factors with AILDs. Mendelian randomization (MR) was employed to assess the causal effects of these extrahepatic factors on AILDs, complemented by linkage disequilibrium score (LDSC) regression to uncover shared genetic architecture and causal effects underlying the associations between autoimmune diseases. We employed colocalization, enrichment analysis, and protein-protein interaction (PPI) network to identify the functions of shared loci. Additionally, we proposed that activated immune cells in the circulation may contribute to liver and biliary tract inflammation via migration, mediating the impact of extrahepatic factors on AILDs. This hypothesis was tested using two mediation analysis methods: two-step MR (TSMR) and multivariable MR (MVMR).

Results

Causal associations between multiple extrahepatic factors and AILDs were identified. Notably, CD27+ B cells were found to be a risk factor for PBC, while PSC progression was associated with CD28+ CD8+ T cells exhaustion and increased levels of CD28- CD8+ T cells. Mediation analyses revealed 64 pathways via TSMR and 15 pathways via MVMR, indicating that the effects of extrahepatic factors on AILDs may be mediated by circulating immune cells. The shared genetic architecture also contributed to these associations. Analysis of shared loci and gene functions identified ATXN2 as being shared between PBC and 9 EHAIDs, while SH2B3 and PSMG1 were shared with 6 and 5 EHAIDs, respectively, in PSC.

Conclusions

Our research compared three distinct AILDs, enhancing the understanding of their etiology and providing new evidence on risk factors, diagnostic markers, and potential therapeutic targets.

Helicobacter pylori induces GBA1 demethylation to inhibit ferroptosis in gastric cancer

This research investigates potential therapeutic targets for gastric cancer, focusing on ferroptosis-related genes. Gastric cancer is known for its lower survival rates, necessitating new treatment strategies. This study employed Mendelian randomization to identify ferroptosis-related genes and methylation sites in gastric cancer, examining correlations between Helicobacter pylori infection, GBA1 gene expression, and promoter methylation with single-cell datasets and the TCGA-STAD database. We used Helicobacter pylori-infected gastric cancer cell models and used next-generation sequencing to monitor methylation changes pre- and post-infection. GBA1 expression levels were assessed via qRT-PCR and Western blot both before and after infection. The effect of Helicobacter pylori on GC cell proliferation was analyzed using CCK-8 and EdU assays after knocking down the GBA1 gene. The association between Helicobacter pylori infection and ferroptosis, including its reversibility after GBA1 knockdown, was evaluated using FerrOrange, GSH, MDA, and C11-BODIPY assays. Mass spectrometry measured the impact of Helicobacter pylori and GBA1 knockdown on lipid metabolism. An in vivo subcutaneous tumor-bearing model was also established to confirm these findings. Mendelian randomization analysis revealed that high GBA1 expression and reduced methylation levels of its promoter are risk factors for gastric cancer. Single-cell sequencing and TCGA-STAD datasets indicated a positive correlation between Helicobacter pylori infection and GBA1 expression, with a concurrent negative correlation between GBA1 promoter methylation and GBA1 expression. In gastric cancer cell lines, Helicobacter pylori infection was observed to enhance GBA1 expression and decrease methylation levels at its promoter. Additionally, Helicobacter pylori promoted GC cell proliferation, an effect mitigated by knocking down GBA1. Infection also reduced lipid peroxidation, increased glutathione levels, and impeded ferroptosis in GC cells; however, these effects were reversed following GBA1 knockdown. Changes in sphingolipid metabolism induced by I were detected in GC cell lines. In vivo experiments using a subcutaneous tumor-bearing model demonstrated that Helicobacter pylori infection fosters tumorigenesis in GC cells. Our study demonstrates that Helicobacter pylori infection triggers demethylation and upregulation of GBA1, subsequently inhibiting ferroptosis in gastric cancer cells. These findings suggest that targeting the GBA1 pathway may offer a novel therapeutic approach for managing gastric cancer.

Causal relationship between Hashimoto's thyroiditis and non-ischemic cardiomyopathy and the mediating role of inflammatory cytokines: Evidence from genetic association analysis

BACKGROUND

Previous studies report that Hashimoto's thyroiditis (HT) may be associated with non-ischemic cardiomyopathy (NICM); However, the causal relationship remains to be elucidated. Here, we aimed to investigate the causal relationship between HT and NICM through Mendelian randomization (MR) and explore the potential mediating role of inflammatory cytokines within this association.

METHODS

The bidirectional two-sample MR, multivariable MR and mediation MR analyses were conducted based on genome-wide association study summary datasets, and MR results were further supported by multiple sensitivity analysis methods.

RESULTS

We presented genetic evidence that HT could unidirectionally increase the risk of NICM (odds ratios [OR]: 1.09, 95 % confidence intervals [CI]: 1.03-1.15, P = 0.001). After adjusting for multiple potential cardiovascular risk factors such as body mass index, hypertension, blood glucose levels, several dyslipidemias, alcohol consumption, heart valve problem, thyroid function, heart rate and arrhythmia, the causal effect of HT on NICM remained statistically significant. Further mediation MR analysis results showed that monokine induced by gamma interferon (MIG) could act as a mediator (OR = 1.026, 95 % CI = 1.006-1.052), accounting for about 28.8 % of the increased risk of NICM in patients with HT.

CONCLUSIONS

Our study proposes a causal relationship between HT and NICM, as well as the mediating role of MIG in this process, highlighting the importance of evaluating myocardial damage in patients with HT and providing new insights into the targeted treatment for high-risk patients.

Serum uric acid levels and intracerebral hemorrhage: A two-sample Mendelian randomization study

OBJECTIVE

Previous observational studies have generated controversy regarding the correlation between serum uric acid (UA) levels and intracerebral hemorrhage (ICH), with the causal relationship remaining uncertain. To assess the potential causal relationship between serum UA levels and ICH, two-sample Mendelian randomization analysis was applied.

METHODS

Single-nucleotide polymorphisms (SNPs) closely associated with serum UA were retrieved from the genome-wide association study (GWAS) database, including 580,505 individuals of European descent. A total of 27 and 251 SNPs were chosen as instrumental variables. Summary data for ICH included 1935 cases and 471,578 controls. Two-sample MR analyses, including inverse-variance weighted (IVW), MR-Egger, weighted median, and weighted mode methods, were employed to assess the potential causal relationship between serum UA levels and ICH, with odds ratios (ORs) as effect estimates. Heterogeneity was evaluated using Cochran's Q test, and sensitivity analyses were conducted using the leave-one-out method.

RESULTS

The IVW analysis revealed that a 1 mg/dL increase in serum UA was associated with a 16.5 % higher risk of ICH (OR 1.165, 95 % CI 1.01-1.34, P = 0.034), while a 1 quantile increase in serum UA was associated with a 25.9 % higher risk (OR 1.259, 95 % CI 1.091-1.46, P = 0.002). Cochran's Q test showed no evidence of heterogeneity. No horizontal pleiotropy was detected. The sensitivity analysis using the leave-one-out method supported the robustness and reliability of our results.

CONCLUSION

The study reveals that elevated serum UA levels are causally linked to ICH, suggesting the potential applicability of serum UA as a biomarker for the occurrence of ICH.

Phenotypic Versus Genetic Mismatch of BMI and Type 2 Diabetes: Evidence From Two Prospective Cohort Studies

Little is known about the population-based mismatch between phenotypic and genetic BMI (BMI-PGM) and its association with type 2 diabetes. We therefore used data from the China Kadoorie Biobank and UK Biobank and calculated BMI-PGM for each participant as the difference between the percentile for adjusted BMI at baseline and the percentile for adjusted polygenic risk score for BMI. Participants were categorized into discordantly low (BMI-PGM < the first quartile), concordant (the first quartile ≤ BMI-PGM < the third quartile), and discordantly high (BMI-PGM ≥ the third quartile) groups. We calculated adjusted hazard ratios (HRs) for the association of BMI-PGM and type 2 diabetes using Cox proportional hazard models in each cohort, and combined HRs using random-effects meta-analyses. During a median follow-up of 12 years for both cohorts, BMI-PGM was associated with the risk of type 2 diabetes, with the discordantly low group showing reduced risk and the discordantly high group showing elevated risk compared with the concordant group, independent of BMI and other conventional risk factors. In addition, normal-weight individuals with discordantly high BMI-PGM faced a higher risk of type 2 diabetes than overweight individuals. These findings suggest that BMI-PGM may play a potential role in reassessing the risk of type 2 diabetes, particularly among normal-weight populations.

ARTICLE HIGHLIGHTS

Social developments have fostered an "obesogenic environment" that exacerbated phenotypic versus genetic mismatch of BMI (BMI-PGM) and the risk of type 2 diabetes. The study quantified BMI-PGM and examined its association with type 2 diabetes independent of BMI and other conventional factors. The risk of type 2 diabetes was lower in the discordantly low BMI-PGM group and higher in the discordantly high BMI-PGM group, with concordant BMI-PGM group as reference. These findings indicate the potential to reassess type 2 diabetes risk by quantifying BMI-PGM on individual levels.

Genetic and epigenetic factors shape phenotypes and outcomes in systemic lupus erythematosus - focus on juvenile-onset systemic lupus erythematosus

PURPOSE OF REVIEW

Systemic lupus erythematosus (SLE) is a severe autoimmune/inflammatory disease. Patients with juvenile disease-onset and those of non-European ancestry are most severely affected. While the exact pathophysiology remains unknown, common and rare gene variants in the context of environmental exposure and epigenetic alterations are involved. This manuscript summarizes the current understanding of genetic and epigenetic contributors to SLE risk, manifestations and outcomes.

RECENT FINDINGS

Though SLE is a mechanistically complex disease, we are beginning to understand the impact of rare and common gene variants on disease expression and associated outcomes. Recent trans -ancestral and multigenerational studies suggest that differential genetic and environmental impacts shape phenotypic variability between age-groups and ancestries. High genetic burden associates with young age at disease-onset, organ involvement, and severity. Additional epigenetic impact contributes to disease-onset and severity, including SLE-phenotypes caused by rare single gene variants. Studies aiming to identify predictors of organ involvement and disease outcomes promise future patient stratification towards individualized treatment and care.

SUMMARY

An improved understanding of genetic variation and epigenetic marks explain phenotypic differences between age-groups and ancestries, promising their future exploitation for diagnostic, prognostic and therapeutic considerations.

Reference-Based Standardization Approach Stabilizing Small Batch Risk Prediction via Polygenic Score

The polygenic score (PGS) holds promise for motivating preventive behavioral changes. However, no clinically validated standardization methodology currently exists. Here, we demonstrate the efficacy of a "reference-based" approach for standardization. This method uses the PGS distribution in the general population as a reference for normalization and percentile determination; however, it has not been validated. We investigated three potential influences on PGS computation: (1) the size of the reference population, (2) biases associated with different genotyping platforms, and (3) inclusion of kinship ties within the reference group. Our results indicate that the reference size affects the bootstrap estimate of standard error for PGS percentiles, peaking around the 50th percentile and diminishing at extreme percentiles (1st or 100th). Discrepancies between genotyping platforms, such as different microarrays and whole-genome sequencing, resulted in deviations in PGS (p < 0.05 in Kolmogorov-Smirnov test). However, these deviations were reduced to a nonsignificant level using shared genetic variants in the calculations when the ancestry of the samples and reference were matched. This approach recovered approximately 9.6% of the positive predictive value of PGS by naïve genotype. Our results provide fundamental insights for establishing clinical guidelines for implementing PGS to communicate reliable risks to individuals.

rs762855 single nucleotide polymorphism modulates the risk for diffuse-type gastric cancer in females: a genome-wide association study in the Korean population

BACKGROUND

Intestinal-type gastric cancer (IGC) and diffuse-type gastric cancer (DGC) exhibit different prevalence rates between sexes. While environmental factors like Helicobacter pylori infection and alcohol consumption contribute to these differences, they do not fully account for them, suggesting a role for host genetic factors.

METHODS

We conducted a meta-analysis to explore associations between single nucleotide polymorphisms (SNPs) and the risk of IGC or DGC. The analysis included the SNUBH cohort (998 participants: 159 DGCs, 303 IGCs, 4,962,361 variants) and the GC_HC cohort (6,233 participants: 389 DGCs, 405 IGCs, 4,541,617 variants). Significant variants were validated in the SNUBH2_AA cohort (5,511 participants: 40 DGCs, 49 IGCs, 3,668,632 variants).

RESULTS

The meta-analysis identified that rs762855 (chr4:3,074,795; hg19) is significantly associated with DGC risk in females (OR [95% CI]: 1.758 [1.438-2.150], P = 3.91 × 10-8), a finding replicated in the SNUBH2_AA datasets (OR [95% CI]: 3.356 [1.031-10.92], P = 4.43 × 10-2). Gene-set and transcriptomic analyses revealed that the Myb/SANT DNA Binding Domain Containing 1 (MSANTD1) gene is significantly linked to DGC susceptibility in females. In addition, Mendelian randomization analyses suggested that increased serum total protein and non-albumin protein (NAP) levels elevate DGC risk in females (P < 0.05), but not in males.

CONCLUSION

The rs762855 SNP, MSANTD1, and serum NAP levels are associated with DGC risk in Korean females.

Hypomethylation of the low-density lipoprotein receptor class A domain containing 4 gene in rheumatoid arthritis

BACKGROUND

Rheumatoid arthritis (RA) is a chronic inflammatory disease linked to epigenetic changes, particularly DNA methylation. While LDLRAD4 has been implicated in RA through GWAS, its role in RA via methylation remains unclear.

OBJECTIVES

To investigate LDLRAD4 methylation patterns in RA and evaluate its potential as a diagnostic and inflammatory biomarker.

METHODS

We assessed DNA methylation at specific CpG sites within LDLRAD4 in 150 RA patients and 150 healthy controls. Clinical data, including disease duration and inflammatory markers, were collected.

RESULTS

RA patients showed significant hypomethylation of LDLRAD4, especially in the LDLRAD4-43 and LDLRAD4-44 regions. ROC analysis yielded an AUC of 0.841, indicating strong diagnostic potential. Methylation levels correlated negatively with ESR, CRP and DAS28 in the RF+/CCP- subgroup.

CONCLUSIONS

LDLRAD4 DNA present hypomethylation in rheumatoid arthritis, and methylation levels are correlated with inflammatory indicator, possibly via TGF-β signaling. Further research is needed to explore its therapeutic potential.

Causal relationship between circulating immune cells and the risk of esophageal cancer: a Mendelian randomization study

BACKGROUND

Although relevant research has unveiled the intricate connections between immune cells and the occurrence and prognosis of esophageal cancer (EC), the specific impact of immune cell phenotypes on EC remains unclear.

METHODS

We employed bidirectional two-sample Mendelian Randomization (MR) analysis to explore the causal relationship between immune cell phenotypes and EC. The summary data for immune cell phenotypes and EC are both sourced from the GWAS (Genome-Wide Association Study) database. Sensitivity analysis was conducted on the results, utilizing a combination of MR-Egger and MR-Presso to assess horizontal pleiotropy, employing Cochran's Q test to evaluate heterogeneity.

RESULTS

We identified 24 immunophenotypes with potential causal relationships to EC. Our results are presented based on the panel results from flow cytometry detection, categorized into B-cell panel, TBNK panel, cDC panel, Maturation stages of T-cell panel, Monocyte panel, and Myeloid cell panel. In the reverse MR analysis, we found a potential negative correlation between EC and IgD + CD38dim B cell Absolute Count (OR = 0.94, 95% CI, 0.88-0.99, P = 0.023).

CONCLUSION

This study has unveiled the causal relationship between immune cell phenotypes and EC, providing new insights for the exploration of immunotherapy targets in subsequent EC research and for the assessment of EC prognosis.

Genetic Evidence for Causal Effects of Circulating Remnant Lipid Profile on Cerebral Hemorrhage and Ischemic Stroke: A Mendelian Randomization Study

BACKGROUND

Mendelian randomization was employed to investigate the impact of circulating lipids, specifically residual lipids, on the risk of susceptibility to cerebral hemorrhage and ischemic stroke.

METHODS

According to the previous studies, we chose 19 circulating lipids, comprising 6 regular lipids and 13 residual lipids, to investigate their potential causal relationship with intracranial hemorrhage and ischemic stroke. The effect estimates were computed utilizing the random-effects inverse-variance-weighted methodology.

RESULTS

The findings revealed negative correlations between high-density lipoprotein cholesterol (HDL-C) and cerebral hemorrhage and large artery stroke. HDL-C, apolipoprotein A1 (Apo A1), TG in very small VLDL, and TG in IDL were found to be negatively correlated with any ischemic stroke. apolipoprotein B (Apo B), triglycerides (TG), low-density lipoprotein cholestrol (LDL-C), L.VLDL-TG, TG in medium VLDL, and TG in small VLDL exhibited positive correlations with large artery stroke. TG in very large HDL and TG in IDL were positively correlated with cardioembolic stroke. No significant causal relationship was observed between circulating lipids, with the exception of HDL-C and cerebral hemorrhage. No causal relationship was identified between any circulating lipids and small vessel stroke. Furthermore, the causal relationships were only found between residual lipids and ischemic stroke.

CONCLUSIONS

This study provides evidence for the beneficial impact of Apo A1 and HDL-C in reducing the risk of ischemic stroke, as well as the protective effect of HDL-C against cerebral hemorrhage. It highlights the detrimental effects of Apo B, TG, and LDL-C in increasing the risk of ischemic stroke, particularly in cases of large artery stroke. Furthermore, the study underscores the heterogeneity and 2-sided effects of the causal relationship between triglyceride-rich lipoproteins and ischemic stroke, offering a promising avenue for the treatment of ischemic stroke.

Unsupervised Learning-Derived Complex Metabolic Signatures Refine Cardiometabolic Risk

BACKGROUND

Cardiometabolic diseases have become a leading cause of morbidity and mortality globally. Nuclear magnetic resonance metabolomics represents a precise tool for assessing metabolic individuality.

OBJECTIVES

This study aimed to use unsupervised learning to decode plasma metabolomic profiles, providing new insights into the etiology of cardiometabolic diseases.

METHODS

We applied unsupervised learning to generate robust metabolic signatures from the plasma profiles of 118,001 UK Biobank participants. Phenome-wide and genome-wide association studies were conducted to reveal their phenomic and genetic architectures. Integrated prospective cohort analyses and Mendelian randomization clarified their roles in cardiometabolic risks.

RESULTS

Eleven metabolic clusters were identified, linked to 101 loci and 445 phenotypes, mostly cardiometabolic diseases. These novel signatures partially outperformed traditional lipids in cardiometabolic risk prediction. Triglyceride-rich lipoproteins demonstrated superior predictive power for ischemic heart disease, type 2 diabetes, and hypertension, compared with apolipoprotein B and lipoprotein(a). Non-high-density lipoprotein cholesterol was found to increase the risk of hyperlipidemia and ischemic heart disease while offering a protective effect against type 2 diabetes. Furthermore, different high-density lipoprotein clusters showed heterogeneous associations with cardiometabolic diseases, with high-density lipoprotein subpopulations enriched in free cholesterol or triglyceride increasing risk, and those enriched in cholesterol esters providing protection.

CONCLUSIONS

These metabolic signatures extract comprehensive information from the metabolomic profile while maintaining clarity and interpretability, facilitating clinical translation. The findings emphasize the crucial roles of lipid subpopulations in cardiometabolic risks, encouraging clinicians to take a more nuanced approach to managing blood lipids and balancing different disease risks.

Prioritization of Lipid Metabolism Targets for the Diagnosis and Treatment of Cardiovascular Diseases

Background: Cardiovascular diseases (CVD) are a major global health issue strongly associated with altered lipid metabolism. However, lipid metabolism-related pharmacological targets remain limited, leaving the therapeutic challenge of residual lipid-associated cardiovascular risk. The purpose of this study is to identify potentially novel lipid metabolism-related genes by systematic genomic and phenomics analysis, with an aim to discovering potentially new therapeutic targets and diagnosis biomarkers for CVD. Methods: In this study, we conducted a comprehensive and multidimensional evaluation of 881 lipid metabolism-related genes. Using genome-wide association study (GWAS)-based mendelian randomization (MR) causal inference methods, we screened for genes causally linked to the occurrence and development of CVD. Further validation was performed through colocalization analysis in 2 independent cohorts. Then, we employed reverse screening using phenonome-wide association studies (PheWAS) and a drug target-drug association analysis. Finally, we integrated serum proteomic data to develop a machine learning model comprising 5 proteins for disease prediction. Results: Our initial screening yielded 54 genes causally linked to CVD. Colocalization analysis in validation cohorts prioritized this to 29 genes marked correlated with CVD. Comparison and interaction analysis identified 13 therapeutic targets with potential for treating CVD and its complications. A machine learning model incorporating 5 proteins for CVD prediction achieved a high accuracy of 96.1%, suggesting its potential as a diagnostic tool in clinical practice. Conclusion: This study comprehensively reveals the complex relationship between lipid metabolism regulatory targets and CVD. Our findings provide new insights into the pathogenesis of CVD and identify potential therapeutic targets and drugs for its treatment. Additionally, the machine learning model developed in this study offers a promising tool for the diagnosis and prediction of CVD, paving the way for future research and clinical applications.

Identification of shared genetic loci for asthma, allergic rhinitis, and pollinosis in East Asians

Asthma, allergic rhinitis, and pollinosis are prevalent respiratory conditions that often co-occur, suggesting common genetic and environmental causes. While significant progress has been made in identifying genetic loci in European populations, the genetic architecture in East Asian populations remains poorly understood. Using GWAS summary statistics from BioBank Japan, we performed multi-trait genome-wide association studies (MTAG) to quantify the genetic overlap among asthma, allergic rhinitis, and pollinosis in East Asians. Genetic correlation analysis revealed significant positive correlations among the three conditions, and stratified LDSC (Linkage Disequilibrium Score Regression) analysis identified heritability enrichments in Blood/Immune and Digestive tissues. We discovered novel pleiotropic loci at 9q32 and 10q25.2 specific to East Asians, with candidate gene expression analysis highlighting differential expression of AKNA, ATP6V1G1, and GPAM. These findings provide new insights into the shared genetic architecture and biological mechanisms underlying these conditions, advancing our understanding of their genetic determinants and identifying potential therapeutic targets.

Comprehensive analysis of aging-related gene expression patterns and identification of potential intervention targets

PURPOSE

This study aims to understand the molecular mechanisms underlying the aging process and identify potential interventions to mitigate age-related decline and diseases.

METHODS

This study utilized the GSE168753 dataset to conduct comprehensive differential gene expression analysis and co-expression module analysis. Machine learning and Mendelian randomization analyses were employed to identify core aging-associated genes and potential drug targets. Molecular docking simulations and mediation analysis were also performed to explore potential compounds and mediators involved in the aging process.

RESULTS

The analysis identified 4164 differentially expressed genes, with 1893 upregulated and 2271 downregulated genes. Co-expression analysis revealed 21 modules, including both positively and negatively correlated modules between older age and younger age groups. Further exploration identified 509 aging-related genes with distinct biological functions. Machine learning and Mendelian randomization analyses identified eight core genes associated with aging, including DPP9, GNAZ, and RELL2. Molecular docking simulations suggested resveratrol, folic acid, and ethinyl estradiol as potential compounds capable of attenuating aging through modulation of RELL2 expression. Mediation analysis indicated that eosinophil counts and neutrophil count might act as mediators in the causal relationship between genes and aging-related indicators.

CONCLUSION

This comprehensive study provides valuable insights into the molecular mechanisms of aging and offers important implications for the development of anti-aging therapeutics. Key Messages What is already known on this topic - Prior research outlines aging's complexity, necessitating precise molecular targets for intervention. What this study adds - This study identifies novel aging-related genes, potential drug targets, and therapeutic compounds, advancing our understanding of aging mechanisms. How this study might affect research, practice, or policy - Findings may inform targeted therapies for age-related conditions, influencing future research and clinical practices.

iPSCs and iPSC-derived cells as a model of human genetic and epigenetic variation

Understanding the interaction between genetic and epigenetic variation remains a challenge due to confounding environmental factors. We propose that human induced Pluripotent Stem Cells (iPSCs) are an excellent model to study the relationship between genetic and epigenetic variation while controlling for environmental factors. In this study, we have created a comprehensive resource of high-quality genomic, epigenomic, and transcriptomic data from iPSC lines and three iPSC-derived cell types (neural stem cell (NSC), motor neuron, monocyte) from three healthy donors. We find that epigenetic variation is most strongly associated with genetic variation at the iPSC stage, and that relationship weakens as epigenetic variation increases in differentiated cells. Additionally, cell type is a stronger source of epigenetic variation than genetic variation. Further, we elucidate a utility of studying epigenetic variation in iPSCs and their derivatives for identifying important loci for GWAS studies and the cell types in which they may be acting.

ARIES domains: functional signaling units of type I interferon responses

The innate immune system relies on a network of signaling proteins classified by shared domains, which serve as functional units that orchestrate inflammatory and host defensive activities. Within type I interferon (IFN) responses, the stimulator of interferon genes protein (STING), mitochondrial antiviral-signaling protein (MAVS), Toll-IL-1 receptor-resistance protein domain-containing adapter-inducing interferon-β (TRIF), Toll-like receptor adapter interacting with SLC15A4 on the lysosome (TASL), insulin receptor tyrosine kinase substrate protein of 53 kDa (IRSp53), and GEM interacting protein (GMIP) utilize a conserved pLxIS motif to recruit IRF family transcription factors. Notably, the pLxIS motif functions within a larger signaling unit, which is referred to here as an Activator of Interferon Expression via a pLxIS motif (ARIES) domain. ARIES domains consist of the pLxIS motif and adjacent kinase activation motifs that together drive IFN responses. This review explores how ARIES domains promote immune responses via shared and distinct signaling mechanisms, protein localization, and regulation of metabolic shifts, underscoring their evolutionary conservation and critical role in host defense.

Serum amino acid alterations in hyperuricemia: potential targets for renal disease prevention

Observational studies have linked uric acid (UA) levels and kidney disease to amino acid homeostasis, but the causal relationship is unclear. This study aims to determine if elevated UA affects amino acid levels and whether amino acids mediate this relationship, focusing on the causal links between UA, circulating amino acids, and kidney disease.

METHODS

This study utilized Uox-KO mice as a hyperuricemia model, assessed renal injury through blood biochemistry and pathology, analyzed serum amino acid changes via targeted amino acidomics, and employed Mendelian randomization to investigate the causal links between uric acid, amino acids, and renal disease.

RESULTS

Hyperuricemia Uox-KO mice have significantly higher serum UA and renal impairment markers, with histopathological analysis showing extensive renal tissue damage. Changes in amino acid balance were found in the mice's serum, with key metabolites like alanine, isoleucine, leucine, aspartic acid, cysteine, glutamate, and glycine potentially influencing UA pathophysiology. Genetically predicted UA was positively correlated with chronic renal failure (CRF) and blood urea nitrogen(BUN) levels and negatively with serum cystatin C (eGFRcys) and serum creatinine (eGFRcrea). Alanine (Ala) mediated the effect of UA on elevated CRF and BUN risk, accounting for 4.5% of the UA-CRF relationship and 14.4% of the UA-BUN association.

CONCLUSION

In hyperuricemia mice, serum amino acids undergo metabolic changes. Genetically predicted UA levels are positively linked to CRF and BUN, but negatively linked to eGFRcys and eGFRcrea. Ala mediates UA's effect on CRF and BUN risk, indicating Ala could be a target for preventing renal diseases caused by hyperuricemia.

Examining the relationship between secondhand smoke and non-malignant digestive system diseases: Mendelian randomization evidence

INTRODUCTION

Secondhand smoke (SHS) may exacerbate the global disease burden, particularly in workplace settings. Observational studies have implicated SHS as a risk factor for various non-malignant digestive system diseases (NMDSD), yet establishing a causal relationship remains challenging. Therefore, we conducted a Mendelian randomization (MR) study to explore whether workplace exposure to SHS is associated with NMDSD.

METHODS

This study utilized a secondary dataset analysis based on Genome-Wide association study (GWAS) summary data. Genetic variants associated with exposure to SHS in the workplace were used as instrumental variables. Genome-wide association study (GWAS) summary data for SHS were obtained from the UK Biobank. GWAS summary data for NMDSD were sourced from the FinnGen study, the International Inflammatory Bowel Disease Genetics Consortium (IIBDGC), and a large-scale study conducted in Japan. We employed inverse variance-weighted (IVW), MR-Egger, and weighted median methods for MR analysis. Additionally, sensitivity analyses were conducted to ensure the robustness of our findings.

RESULTS

According to the IVW model, SHS in the workplace was positively associated with ulcerative colitis (UC) (OR=2.03; 95% CI: 1.03-4.05; p=0.04). There was no evidence of horizontal pleiotropy biasing causality (p>0.05), and leave-one-out analysis confirmed the stability and robustness of this association.

CONCLUSIONS

Our study identifies an association between regular exposure to SHS in the workplace and an increased risk of ulcerative colitis. However, the potential influence of active smoking or exposure to SHS from other sources cannot be excluded. Further research is needed to confirm these findings.

TCF7L2 as a target of peripheral artery disease in patients with type 2 diabetes: A 2-sample Mendelian randomization and bioinformatics study

This study examines the causal relationship between type 2 diabetes (T2D) and peripheral artery disease (PAD) and their potential mechanisms based on the analysis of the Gene Expression Omnibus database and 2-sample Mendelian randomization (MR). The first part involved a 2-sample MR study and a comprehensive meta-analysis. Differences in the results were assessed using inverse-variance weighting. Heterogeneity was examined using the Cochrane Q statistical test. The leave-one-out method was applied for sensitivity analysis. The potential horizontal pleiotropic effect was assessed using the MR-Egger intercept technique. The second part involved differential gene analysis and weighted gene coexpression network analysis. Subsequently, we overlapped and consolidated the results from the 2 parts to identify the key genes between them. MR analysis results suggested a statistically significant correlation between the incidence of PAD and T2D (odds ratio: 1.22, 95% confidence interval: 1.13-1.32, P = 3.74e-07). We anticipated a pivotal role for TCF7L2 in PAD and T2D. T2D was significantly associated with PAD risk. Simultaneously, the study deepened our understanding of the underlying mechanisms of both diseases, proposing TCF7L2 as a promising target.

Dietary factors and the risk of gastric and colorectal cancers: A Mendelian randomization study

Dietary factors can significantly affect the development of gastric and colorectal cancers; however, observational findings on the impact of micronutrients and macronutrients on the risk of gastric and colorectal cancers are inconsistent. It is crucial to clarify these relationships to create nutritional recommendations for cancer prevention. A two-sample Mendelian randomization investigation was performed to examine the impact of circulating levels of 15 micronutrients (such as vitamin A, folate, vitamin B6, vitamin B12, vitamin C, vitamin D, vitamin E, β-carotene, calcium, copper, iron, magnesium, phosphorus, selenium, and zinc), along with adjusted relative macronutrient intake (including protein, carbohydrate, sugar, and fat), on the risk of gastric and colorectal cancers. Genetically predicted relative protein intake is significantly associated with the risk of colorectal cancer (odds ratio [OR] 95% confidence interval [CI] = 0.41 [0.24, 0.69]; P = .0007). Evidence suggests that genetically predicted macronutrients, such as carbohydrate (OR 95% CI = 1.88 [1.13, 3.14]; P = .0154), and micronutrients, such as vitamin C (OR 95% CI = 0.81 [0.69-0.94]; P = .008) and vitamin B12 (OR 95% CI = 1.16 [1.04, 1.28]; P = .006), may also influence the risk of colorectal cancer. Evidence suggests that intake of sugar (OR 95% CI = 0.47 [0.24, 0.90]; P = .02), and vitamin C (OR 95% CI = 0.78 [0.62, 0.99]; P = .04) may influence the risk of gastric cancer. However, no significant associations were observed between other nutrients and gastrointestinal malignancy. Taken together, these findings suggest that the intake of protein, carbohydrate, sugar, vitamin C, and vitamin B12 may influence the risk of gastric and colorectal cancers. However, further in-depth studies are needed to confirm this.

Exploring the causal relationship between constipation and ileus: Insights from bidirectional Mendelian randomization and genomic data analysis

Constipation currently affects approximately 15% of the global population, and contemporary lifestyles are increasing its incidence every year. A significant number of individuals with constipation also experience ileus, a common surgical emergency known for its sudden onset and rapid progression. However, the intricate dynamics of the relationship between constipation and ileus are not well understood. This study aimed to elucidate the causal relationship and underlying mechanisms of constipation and ileus, thereby advancing our understanding of their interconnections. A bidirectional 2-sample Mendelian randomization (MR) analysis was performed using the IEU OpenGWAS database. Single nucleotide polymorphisms were used as instrumental variables to determine the causative association between constipation and ileus. Additionally, we utilized eQTL datasets to identify pertinent genes, conducted gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses, and constructed protein-protein interaction (PPI) networks via the GeneMANIA database to identify the possible molecular pathways involved. Bidirectional MR revealed a significantly elevated risk of ileus due to constipation (OR = 1.467, 95% CI = 1.217-1.770, P < .001). Our eQTL investigation revealed 6 genes that were co-expressed in both ailments. Enrichment analysis suggested potential roles of these genes in nucleic acid metabolism and ribosomal biosynthesis, with b-ureidopropionase 1 (UPB1) exhibiting the most pronounced enrichment. Furthermore, PPI network analysis highlighted several pivotal proteins and genes. The findings of this study indicate the existence of a causal nexus between constipation and ileus, underscoring the significant genetic susceptibility shared between these conditions. It has been postulated that constipation can perturb the incidence of ileus via biochemical pathways, including nucleic acid metabolism and ribosomal biosynthesis, with UPB1 possibly serving as a key molecular target. Our results elucidate the novel genetic basis of constipation and ileus and provide a foundation for future experimental studies and the development of customized preventive and therapeutic approaches.

ST3 beta-galactoside alpha-2,3-sialyltransferase 4 (St3gal4) deficiency reveals correlations among alkaline phosphatase activity, metabolic parameters, and fear-related behavior in mice

ST3 beta-galactoside alpha-2,3-sialyltransferase 4 (ST3GAL4) is a sialyltransferase involved in the biosynthesis of alpha2,3-sialic acid on glycoproteins and glycolipids. In mice, St3gal4 gene expression plays a crucial role in modulating epilepsy and anxiety/depression through its expression in thalamic neurons. Genome-wide association studies (GWAS) have identified several peripheral metabolic traits strongly associated with ST3GAL4 in humans. However, whether the symptoms observed in mice are associated with metabolic changes remains unclear. This study investigated the effects of St3gal4 deficiency on the same metabolic parameters in mice as those in humans. The parameters examined included body weight, plasma biochemistry, specifically alkaline phosphatase (ALP), protein, and cholesterol levels, and free amino acids profiles, resulting in elevated ALP and reduced tryptophan and total cholesterol (T-Cho) levels in St3gal4-knockout (KO) mice. Additionally, clearance of blood glucose was delayed in KO male mice. These findings suggest mouse St3gal4 deficiency correlated with modulated ALP, tryptophan, and T-Cho levels in the plasma. Next, brain ALP activity was compared between St3gal4-KO mice and wild-type (WT) mice, focusing on the thalamus. Fear conditioning tests assessed the relationship between behavior and ALP activity in plasma and brain. In KO mice, the enhanced tone freezing positively correlated with plasma ALP levels. Conversely, thalamic ALP activity was greatly reduced in KO mice, negatively correlating with plasma ALP. These findings suggest that mouse St3gal4 deficiency influences ALP activity in both thalamus and plasma, associating with emotional behaviors and metabolic changes.

Potential drug targets for systemic lupus erythematosus identified through Mendelian randomization analysis

So far, there is no clear pathogenesis and no cure for systemic lupus erythematosus (SLE). The therapeutic benefits of existing drug therapies are far from ideal. The proteome is a major source of therapeutic targets. Therefore, new drug targets for SLE need to be discovered. Based on the STROBE-Mendelian randomization (MR) checklist, we performed MR to explore potential drug targets for SLE, using genome-wide association study summary statistics of plasma and cerebrospinal fluid (CSF) and further replicated in the external validation. Bidirectional MR, reverse causality testing by Steiger filtering, Bayesian co-localization were used. In addition, protein-protein interaction networks (PPI) were performed to reveal potential associations between proteins and current SLE drugs. At false discovery rate (FDR) significance (PFDR < .05), MR analysis revealed 8 proteins. Five proteins decreased the SLE risks, whereas the other 3 proteins increased the SLE risks. None of the 8 proteins had reverse causality except sICAM-1. Bayesian co-localization suggested that 5 proteins shared the same variant with SLE. PPI network suggested that intercellular adhesion molecular 1 (ICAM-1), Fc-gamma-RIIb (FCG2B) and N-terminal pro-B-type natriuretic peptide (N-terminal pro-BNP) interacted with targets of current SLE medications. Our integrative analysis revealed that SLE risk is causally associated with ICAM-1, FCG2B, and N-terminal pro-BNP. These 3 proteins have the potential to become drug targets of SLE, especially for ICAM-1 and FCG2B. More further studies are also warranted to support this finding.

Genomic correlation, shared loci, and causal association between obesity, periodontitis and tooth loss

Observational studies have reported an association of obesity with periodontitis and tooth loss, yet findings remain inconsistent. We aim to investigate the genetic link underlying obesity-related traits (BMI [body mass index], WHR [waist-to-hip ratio], WHRadjBMI and childhood BMI), periodontitis and tooth loss. Leveraging summary statistics from large-scale genome-wide association studies, we comprehensively investigated the pair-wise genetic correlation using linkage disequilibrium score regression (LDSC) and SUPERGNOVA, identified shared loci using cross-phenotype association analysis (CPASSOC), and estimated causal association using Mendelian randomization. We identified a significant genetic correlation of obesity with tooth loss, but not with periodontitis. Partitioning the genome into LD-independent regions revealed 10 significantly shared local signals across six regions. Genome-wide cross-trait analysis uncovered 14 shared loci, four of which were colocalized: rs2064044 (PP4 = 0.94), rs6000329 (PP4 = 0.86), rs7134628 (PP4 = 0.86), and rs1286769 (PP4 = 0.90). Notably, rs1286769, identified via CPASSOC and validated through colocalization analysis, is located near RARβ, a gene associated with both BMI and denture use. Mendelian randomization revealed a nominally-significant causal association of obesity with periodontitis (P = 0.045) but a robust causal association with tooth loss represented by number of teeth (BMI: beta = [Formula: see text]0.20, 95%CI = [Formula: see text]0.26 to [Formula: see text]0.14, P = 5.27 × 10-11; WHR: beta = [Formula: see text]0.16, 95%CI = [Formula: see text]0.24 to [Formula: see text]0.08, P = 3.71 × 10-5). Results of CAUSE were consistent with main findings. From a genetic perspective, our work highlights an intrinsic link between obesity, periodontitis and tooth loss, which may add new lines of evidence and provide insights for clinical and public oral health applications.

Causal roles of immune cells and metabolites in chronic pancreatitis: a mendelian randomization study

BACKGROUND

Previous research has established a correlation between immune cells and an increased likelihood of Chronic pancreatitis (CP). However, studies investigating the causal relationship remain limited.

METHODS

This study utilized publicly available genome-wide association study (GWAS) databases and conducted a two-sample Mendelian randomization (MR) analysis to examine the causal relationships (CRs) among 731 immune cells, 1,400 metabolites, and CP. Mediation MR analysis was also performed to assess whether metabolites serve as mediators in the relationship between immune cells and CP.

RESULTS

Our study identified four immune cell types that act as risk factors for CP, with odds ratios (OR) ranging between 1.076 and 1.177. In contrast, three immune cell types were found to serve as protective factors, exhibiting OR values between 0.846 and 0.913. Additionally, four metabolites were implicated as risk factors for CP, with OR values ranging from 1.243 to 1.334. On the other hand, eight metabolites were discovered to have a protective effect, with OR values between 0.580 and 0.871. Mediation analysis revealed that cholesterol levels mediate the causal relationship between immune cell cells and CP, with a mediation effect of 0.00918, accounting for 9.18% of the total effect.

CONCLUSIONS

Our findings provide valuable insights into the genetic underpinnings of CP, highlighting the role of immune cells and plasma metabolites in its pathogenesis. The mediation analysis further suggests that the presence of CD25 on IgD-CD38-B cells may facilitate CP development through the elevation of cholesterol levels. These results not only deepen our understanding of CP but also suggest potential biological targets for therapeutic intervention. Future clinical research should focus on these mediators to develop more effective treatment strategies for CP.

Linking obesity-associated genotype to child language development: the role of early-life neurology-related proteomics and brain myelination

BACKGROUND

The association between childhood obesity and language development may be confounded by socio-environmental factors and attributed to comorbid pathways.

METHODS

In a longitudinal Singaporean mother-offspring cohort, we leveraged trans-ancestry polygenic predictions of body mass index (BMI) to interrogate the causal effects of early-life BMI on child language development and its effects on molecular and neuroimaging measures. Leveraging large genome-wide association studies, we examined whether the link between obesity and language development is causal or due to a shared genetic basis.

FINDINGS

We found an inverse association between polygenic risk for obesity, which is less susceptible to confounding, and language ability assessed at age 9. Our findings suggested a shared genetic basis between obesity and language development rather than a causal effect of obesity on language development. Interrogating early-life mechanisms including neurology-related proteomics and language-related white matter microstructure, we found that EFNA4 and VWC2 expressions were associated with language ability as well as fractional anisotropy of language-related white matter tracts, suggesting a role in brain myelination. Additionally, the expression of the EPH-Ephrin signalling pathway in the hippocampus might contribute to language development. Polygenic risk for obesity was nominally associated with EFNA4 and VWC2 expression. However, we did not find support for mediating mechanisms via these proteins.

INTERPRETATION

This study demonstrates the potential of examining early-life proteomics in conjunction with deep genotyping and phenotyping and provides biological insights into the shared genomic links between obesity and language development.

FUNDING

Singapore National Research Foundation and Agency for Science, Technology and Research.

Causal Effects of Sleep Traits on Angina Pectoris: Mediation by Cardiovascular Risk Factors

Purpose

Angina pectoris (AP) is a major factor in heightened risk of cardiac arrest and has been previously linked to sleep patterns. It remains unclear if sleep traits play a role in the onset of AP. Our study aims to declare the causality of sleep traits on AP by Mendelian randomization (MR) analyses.

Methods

Genome-wide association study (GWAS) data of sleep traits (sleep duration, insomnia, nap during day, chronotype, getting up in morning, narcolepsy, snoring) were obtained from the UK Biobank. The AP datasets came from an analysis containing samples from the UK biobank, FinnGen, and BioBank Japan. The GWAS data of cardiovascular risk factors (hypertension, smoking, hyperlipidemia, type 2 diabetes mellitus (T2DM)) came from the FinnGen. Two-sample MR analyses were carried out to gain a general map of sleep traits, risk factors and AP, then a multivariable MR was performed and the effect of each factor was calculated.

Results

We discovered a positive association between nap, narcolepsy, insomnia and stable angina pectoris (SAP), while getting up in morning associated with SAP negatively. Adequate sleep duration related to a reduced risk of SAP and unstable angina pectoris (UAP). Hypertension and T2DM acted as complete mediators in the relationship of nap and SAP, with an effect value of 1.267 (95% CI = 1.178-1.363, P < 0.01) and 1.059 (95% CI = 1.000-1.120, P < 0.05), and the mediating proportion was 27.7% (P < 0.05) and 7.70% (P = 0.102).

Conclusion

Our study found that nap, narcolepsy, and insomnia increased the risk of SAP, with hypertension and T2DM mediating the causal relationship between nap and SAP. Getting up in the morning reduced the risk of SAP, while longer sleep duration lowered the risk of SAP and UAP. More evidences are required to clarify the roles of sleep traits and risk factors in AP.

Novel susceptibility genes and biomarkers for obstructive sleep apnea: insights from genetic and inflammatory proteins

STUDY OBJECTIVES

Numerous observational studies link obstructive sleep apnea (OSA) to inflammatory proteins, yet the directionality of these associations remains ambiguous. Therefore, we aimed to clarify the potential associations of gene-predicted inflammatory proteins with OSA.

METHODS

Based on genome-wide association study data, we applied Mendelian randomization (MR) to explore potential connections between circulating inflammatory proteins and OSA, primarily using the inverse-variance weighting method for robustness. Cochran's Q test, MR‒Egger intercept test, MR-PRESSO, and leave-one-out method were used to perform sensitivity tests for pleiotropy and heterogeneity. Replication analyses and meta-analyses were performed using other independent data. Steiger tests and multivariate MR assessed the independent effects of exposure factors, and the functional mapping and annotation (FUMA) platform was used to identify key genes to enhance the understanding of genetics.

RESULTS

Our investigation revealed 21 circulating inflammatory proteins significantly associated with OSA-related phenotypes. Notably, IL-10RA, IL-18R1, TNFSF14, CCL23, ADA, and SLAMF1 had significant effects on multiple phenotypes. After FDR correction, IL-18R1, SLAMF1, IL-10RA, and IL-17C were identified as important candidates for OSA, and multivariate MR analysis strengthened the independent heritability of 20 inflammatory factors. The FUMA platform revealed seven overlapping genes: ROBO1, PRIM1, NACA, SHBG, HSD17B6, RBMS2, and WWOX. All reverse MR analyses and sensitivity analyses confirmed the robustness of these associations.

CONCLUSIONS

Our results underscore crucial associations between inflammatory proteins and OSA pathogenesis, revealing new correlates and susceptibility genes. These findings advance biomarker identification for OSA risk and highlight the importance of genetic and inflammatory profiles in OSA management.

Genetic analysis of elevated levels of creatinine and cystatin C biomarkers reveals novel genetic loci associated with kidney function

The rising prevalence of chronic kidney disease (CKD), affecting an estimated 37 million adults in the United States, presents a significant global health challenge. CKD is typically assessed using estimated Glomerular Filtration Rate (eGFR), which incorporates serum levels of biomarkers such as creatinine and cystatin C. However, these biomarkers do not directly measure kidney function; their elevation in CKD results from diminished glomerular filtration. Genome-wide association studies (GWAS) based on eGFR formulas using creatinine (eGFRcre) or cystatin C (eGFRcys) have identified distinct non-overlapping loci, raising questions about whether these loci govern kidney function or biomarker metabolism. In this study, we show that GWAS on creatinine and cystatin C levels in healthy individuals reveal both nonoverlapping genetic loci impacting their metabolism as well as overlapping genetic loci associated with kidney function; whereas GWAS on elevated levels of these biomarkers uncover novel loci primarily associated with kidney function in CKD patients.

Causal association of metformin treatment with diverse immune-mediated inflammatory diseases: A Mendelian randomization analysis

Metformin has been shown to possess immune-modulating and anti-inflammatory effects in various animal and clinical studies. It is believed to be effective in treating some immune-mediated inflammatory diseases (IMIDs). However, there remains ongoing debate regarding the extent to which metformin can reduce the risk of developing IMIDs. We used the data from genome-wide association studies to explore the causal relationship between metformin treatment and some IMIDs through the Mendelian randomization (MR) analysis. Additionally, sensitivity analyses were performed using the Cochran Q-test, MR-PRESSO and "leave-one-out" to confirm the robustness of our conclusions. The MR analysis indicated that metformin treatment could reduce the risk of rheumatoid arthritis (RA) (OR = 0.018, 95% CI: 1.33 × 10-3-0.233, P = .002), multiple sclerosis (MS) (OR = 0.966, 95% CI: 0.936-0.997, P = .030) and primary sclerosing cholangitis (PSC) (OR = 6.82 × 10-4, 95% CI: 7.83 × 10-6-5.93 × 10-2, P = .001). But metformin treatment is not significantly associated with the risk of Crohn disease (OR = 0.994, 95% CI: 0.979-1.009, P = .431), ulcerative colitis (UC) (OR = 0.987, 95% CI: 0.965-1.009, P = .234), systemic lupus erythematosus (SLE) (OR = 164.373, 95% CI: 0.158-1.71 × 105, P = .150), autoimmune hepatitis (AIH) (OR = 2.909, 95% CI: 4.58 × 10-3-1.85 × 103, P = .746) and primary biliary cholangitis (PBC) (OR = 0.055, 95% CI: 1.44 × 10-3-2.112, P = .119). Due to the heterogeneity of the data from UC, SLE, MS, and PBC, we adjusted them. After adjustment, there is no change in the results for UC, SLE, MS, and PBC. The findings of this study support metformin treatment may reduce the risk of RA, MS, and PSC.

Genetic and Plasma Proteomic Approaches to Identify Therapeutic Targets for Graves' Disease and Graves' Ophthalmopathy

Background

The blood proteome is a major source of biomarkers and therapeutic targets. We aimed to identify the causal proteins and potential targets for Graves' disease (GD) and Graves' ophthalmopathy (GO) via systematic genetic analyses.

Methods

Genome-wide association studies (GWASs) on the UK Biobank- Pharma Proteomics Project (UKB-PPP) collected 2923 Olink proteins from 54,219 participants. We conducted a proteome-wide Mendelian randomization (MR) study with cis-pQTLs to identify candidate proteins for GD and GO risk. Colocalization analysis and the Heidi test were used to examine whether the identified proteins and diseases shared the same variant. More proteins with potential causal associations were identified in Summary-data-based MR (SMR) analyses using trans-pQTLs. Then, downstream analyses were performed to detect protein interactions, gene function, cell type-specific expression and druggable information.

Results

This study genetically predicted levels of 62 plasma proteins were associated with GD risk. Four proteins (CD40, TINAGL1, GMPR and CXCL10) were prioritized with the evidence of sharing the same variants with GD. Specifically, some proteins had potential associations with GD with trans-pQTLs mapping in CD40. The four prioritized protein-coding genes were mainly enriched in the regulation of apoptotic and death processes. In addition, GMPR was associated with both GO and GD in a consistent direction. BTN1A1 and FCRL1 were prioritized as the causal proteins for GO onset and were not associated with GD.

Conclusion

By synthesizing proteomic and genetic data, we identified several protein biomarkers for GD, with one linked to both GD and GO and two other protein biomarkers specific to GO onset, which provides valuable insights into the etiology and potential therapeutic targets for the two diseases.

Investigating the causal relationship between rheumatoid arthritis and cardiovascular disease: A Mendelian randomization study

OBJECTIVE

Previous research has revealed a positive correlation between rheumatoid arthritis (RA) and cardiovascular diseases, but the causal relationship is unclear. This study applies Mendelian randomization to examine whether RA causally contributes to the likelihood of various cardiovascular diseases, such as heart failure, coronary artery disease, and atrial fibrillation.

METHODS

Using genome-wide association data, we conducted a univariable MR (UVMR) analysis to evaluate the causal impact of RA on CVD, primarily utilizing the inverse variance weighted method. Additional MR methods were used to test the robustness of the results. Multivariable MR (MVMR) was applied to explore potential confounders.

RESULTS

In the European population, genetically predicted RA had a harmful causal effect on HF, with the IVW analysis indicating an OR of 1.06 (95% CI: 1.02-1.10, P < 0.01) based on 23 SNPs. No causal relationships were found between RA and other CVDs. The MVMR analysis did not identify significant causal impact of rheumatoid arthritis on HF after controlling for traditional risk factors. In the Asian population, RA was associated with an adverse effect on AF, with the IVW method reporting an OR of 1.20 (95% CI: 1.01-1.41, P = 0.03) for 5 SNPs. No other CVD relationships were found.

CONCLUSIONS

Our MR analysis indicates that genetic susceptibility to rheumatoid arthritis increases the likelihood of heart failure in European populations and atrial fibrillation in East Asian populations. However, established CVD risk factors, such as smoking, overweight, and physical inactivity, remain critically important in the management of RA. Key Points • Multiple studies have highlighted a marked increase in the cardiovascular event risk among individuals with RA. However, additional RCTs are needed for confirmation. • We applied Mendelian randomization to explore the potential causal relationship between rheumatoid arthritis and cardiovascular conditions. The findings demonstrated a causal link between RA and heart failure among European populations, as well as an association between RA and atrial fibrillation in East Asian groups. • Further adjustments using multivariable Mendelian randomization to account for the influence of traditional cardiovascular risk factors revealed that the causal association between RA and heart failure disappeared.

Observational and Genetic Analyses of Traumatic Experiences and Endometriosis

Importance

Although psychological traumas have been associated with endometriosis, limited information is available regarding the role of trauma type and genetic predisposition.

Objective

To examine the relationship between traumatic experiences and endometriosis using observational and genetically informed analyses.

Design, Setting, and Participants

For this case-control study, the analyses were performed between May 13, 2023, and September 30, 2024. Genotypic and phenotypic information was combined from UK Biobank individual-level data (up to 8276 patients with endometriosis and 240 117 female controls) with genome-wide information available from a large meta-analysis (European ancestry: 21 779 patients and 449 087 female controls; East Asian ancestry: 1713 patients and 1581 female controls) and the FinnGen cohort (16 588 patients and 111 583 female controls of European descent).

Main Outcomes and Measures

Phenotypic associations via multiple regression; latent-class analysis (LCA) to investigate the co-occurrence patterns of different traumatic experiences in endometriosis cases and controls; genetic correlation and polygenic risk scoring (PRS) analyses to assess pleiotropy linking traumatic events to endometriosis.

Results

Up to 8276 women with endometriosis (mean [SD] age, 53.2 [13.0] years) and 240 117 female controls (mean [SD] age, 56.5 [9.6] years) were investigated in the study. Women with endometriosis were more likely to report childhood and adulthood traumatic experiences and stressful events (eg, contact trauma odds ratio [OR], 1.28; 95% CI, 1.02-1.26). Our LCA highlighted the association of endometriosis with emotional and physical trauma (225 [8%] vs 3948 [5%]; P < 2.2 × 10-16) and sexual trauma (414 [5%] vs 3158 [4%]; P = 2.9 × 10-3). Unaffected women (controls) were more likely assigned to the "no trauma" latent class (563 [20%] vs 18 949 [24%]; P = 7.4 × 10-14). Our genetic correlation (rg) analyses linked endometriosis to multiple trauma-related outcomes, including posttraumatic stress disorder (meta-analysis rg = 0.31, P = 7.1 × 10-16; FinnGen rg = 0.26, P = 4.7 × 10-15) and childhood maltreatment (meta-analysis rg = 0.23, P = 1.3 × 10-6; FinnGen rg = 0.16, P = 1 × 10-4). Endometriosis PRS was associated with increased odds of the disease (β = 0.31, P < 2.2 × 10-16), but no interaction was observed with different types of trauma events.

Conclusions and Relevance

The present study comprehensively investigated the impact of childhood and adulthood traumatic experiences and stressful events on endometriosis. In particular, our findings highlight the potential association between contact traumas and endometriosis, which appears to be independent of the disease genetic predisposition.

Measuring linkage disequilibrium and improvement of pruning and clumping in structured populations

Standard measures of linkage disequilibrium (LD) are affected by admixture and population structure, such that loci that are not in LD within each ancestral population appear linked when considered jointly across the populations. The influence of population structure on LD can cause problems for downstream analysis methods, in particular those that rely on LD pruning or clumping. To address this issue, we propose a measure of LD that accommodates population structure using the top inferred principal components. We estimate LD from the correlation of genotype residuals and prove that this LD measure remains unaffected by population structure when analyzing multiple populations jointly, even with admixed individuals. Based on this adjusted measure of LD, we can perform LD pruning to remove the correlation between markers for downstream analysis. Traditional LD pruning is more likely to remove markers with high differences in allele frequencies between populations, which biases measures for genetic differentiation and removes markers that are not in LD in the ancestral populations. Using data from moderately differentiated human populations and highly differentiated giraffe populations we show that traditional LD pruning biases FST and principal component analysis (PCA), which can be alleviated with the adjusted LD measure. In addition, we show that the adjusted LD leads to better PCA when pruning and that LD clumping retains more sites with the retained sites having stronger associations.

Is type 2 diabetes a link between lung function and metabolic dysfunction-associated steatotic liver disease? Insights from population studies and Mendelian randomization

AIM

This study aimed to investigate the relationship between lung function and metabolic dysfunction-associated steatotic liver disease (MASLD), and the potential mediating role of type 2 diabetes.

METHODS

Data from the 2007 to 2012 National Health and Nutrition Examination Survey were used. Logistic regression analysis was employed to assess the association between lung function parameters [forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), FEV1/FVC] and MASLD prevalence while exploring type 2 diabetes mediation. Further analyses included linkage disequilibrium score regression, Mendelian randomization, and meta-analysis to examine the causal relationship between lung function and MASLD, considering type 2 diabetes mediation.

RESULTS

The results showed that higher FVC and FEV1 levels were associated with decreased MASLD risk, with type 2 diabetes partially mediating this relationship. Genetic analyses supported a causal link between lung function and MASLD, with type 2 diabetes acting as an intermediary. However, no significant association was found between FEV1/FVC and MASLD.

CONCLUSION

The study identified a causal relationship between lung function and MASLD, with type 2 diabetes playing a partial mediating role.

The mediating role of thyroid-related hormones between thyroid dysfunction diseases and osteoporosis: a mediation mendelian randomization study

The links between Thyroid dysfunction diseases (TDFDs) and osteoporosis (OP) has received widespread attention, but the causal relationships and mediating factors have not been systematically studied. We used two-sample Mendelian randomization (MR) analysis to elucidate the causal relationship between TDFDs and OP. Moreover, we performed mediation MR analyses to explore the role of thyroid-related hormones and OP risk factors in the association between TDFDs and OP. Two sample MR analyses showed that hyperthyroidism increased OP (OR = 1.080, 95% CI 1.026 to 1.137; P = 0.0032) risk. Hypothyroidism increases OP (OR = 1.183, 95% CI 1.125 to 1.244; P < 0.0001) risk. Furthermore, mediation analysis revealed that TSH mediated 5.314% of the relationship between hypothyroidism and OP. In contrast, FT4 mediated 9.670% of the relationship between hyperthyroidism and OP. In European populations, TDFDs may increase OP risk. TSH mediates in the causal association between hypothyroidism and OP, and similarly, FT4 mediates in the causal link between hyperthyroidism and OP. Our findings underscore the significance of improving integrative care for individuals with TDFDs to mitigate the risk of OP. It is essential to maintain stable levels of thyroid hormones and closely monitor bone health to effectively mitigate and prevent OP.

Dnajc5b contributes to male fertility by maintaining the mitochondrial functions and autophagic homeostasis during spermiogenesis

DnaJ heat shock protein family member C5 beta (DNAJC5B), also known as cysteine-string protein beta, exhibits a prominent expression in testicular tissue and plays an important role in acrosomal exocytosis in vitro. Nevertheless, the precise role and underlying mechanism of DNAJC5B in spermatogenesis and male fertility remain poorly understood. The meta-analysis of RNA-sequencing datasets from porcine and murine testes reveals that Dnajc5b could be a pivotal factor in spermatogenesis. This study illustrates that male fertility declines with an increased ratio of abnormal spermatozoa in germ-cell knockout Dnajc5b mice. DNAJC5B has been identified as a mitochondrial protein with high expression in spermatids. The absence of DNAJC5B induces a cascade of mitochondrial damages, including oxidative stress, mitochondrial stress in the testes, and lower mitochondrial membrane potential of spermatozoa. In vivo and in vitro evidence demonstrates that DNAJC5B mitigates excessive cellular autophagy and mitophagy via DNAJ domain under environmental stress conditions, such as starvation or exposure to mitochondrial uncouplers FCCP and CCCP. This study highlights the important role of DNAJC5B in safeguarding male fertility by preserving mitochondrial function and regulating autophagy during spermiogenesis.

A Multi-Ancestry Genome Wide Association Study and Evaluation of Polygenic Scores of LDL-C levels

The genetic determinants of low-density lipoprotein cholesterol (LDL-C) levels in blood have been predominantly explored in European populations and remain poorly understood in Middle Eastern populations. We investigated the genetic architecture of LDL-C variation in Qatar by conducting a genome-wide association study (GWAS) on serum LDL-C levels using whole genome sequencing data of 13,701 individuals (discovery; n=5,939, replication; n=7,762) from the population-based Qatar Biobank (QBB) cohort. We replicated 168 previously reported loci from the largest LDL-C GWAS by the Global Lipids Genetics Consortium (GLGC), with high correlation in allele frequencies (R2=0.77) and moderate correlation in effect sizes (Beta; R2=0.53). We also performed a multi-ancestry meta-analysis with the GLGC study using MR-MEGA (Meta-Regression of Multi-Ethnic Genetic Association) and identified one novel LDL-C-associated locus; rs10939663 (SLC2A9; genomic control-corrected P=1.25×10-8). Lastly, we developed Qatari-specific polygenic score (PGS) panels and tested their performance against PGS derived from other ancestries. The multi-ancestry derived PGS (PGS000888) performed best at predicting LDL-C levels, whilst the Qatari-derived PGS showed comparable performance. Overall, we report a novel variant, which may be explored further to decipher its potential role in the etiopathogenesis of cardiovascular diseases. Our findings also highlight the importance of population-based genetics in developing PGS for clinical utilization.

Associations between ABO, FUT2 and chronic pancreatitis: A comprehensive meta-analysis of multiple cohorts and public biobanks

OBJECTIVES

Associations of ABO blood group specifying transferases A/B (ABO) and fucosyltransferase 2 (FUT2) with CP remain inconclusive. We aimed to comprehensively investigate the associations by Chinese sequencing cohorts and external cohorts.

METHODS

First, we analyzed the distributions of ABO blood groups and FUT2 status, along with lead single nucleotide polymorphisms (SNPs) at ABO (rs8176693 C/T) and FUT2 (rs632111 A/G) gene loci in Chinese low-coverage whole-genome sequencing discovery cohort. Subsequently, we investigated the associations of CP with ABO and FUT2 SNPs in Chinese whole-exome sequencing validation cohort and three public biobanks (FinnGen, UK Biobank, and BioBank Japan). Finally, comprehensive meta-analysis was performed by integrating data from two Chinese cohorts, reported cohorts and public biobanks.

RESULTS

Firstly, in Chinese discovery cohort, the distribution of blood types in CP patients showed no significant difference compared to healthy controls, and similar results were observed in subgroup analyses and in meta-analysis with the reported cohorts. Secondly, results indicated no association between rs8176693 or rs632111 and CP in Chinese cohorts and meta-analysis of three biobanks, though ABO SNP was found to be significantly associated with CP in UK Biobank (odds ratio [OR] = 1.27, P = 0.04). Finally, no association was observed between rs8176693 (OR = 1.03, P = 0.29) or rs632111 (OR = 1.04, P = 0.10) and CP in comprehensive meta-analysis.

CONCLUSIONS

No association was found between lead SNPs of ABO or FUT2 and CP in meta-analysis, nor was there an association between ABO blood group or FUT2 secretor status and CP in Chinese cohort. ABO and FUT2 might play limited role in CP development.

Causal Association Between Multidimensional Plasma Lipid Composition and Pediatric Asthma: A Mendelian Randomization Study

BACKGROUND

Asthma is the most common chronic disease among children and poses a major threat to their health. Observational studies have shown lipid disorders in children with asthma. However, it was not possible to determine whether there is a causal link between the two. Therefore, the aim of this study was to assess the causal relationship between serum liposomes and asthma in children.

METHODS

We used large-scale publicly available genome-wide association study summary statistics to elucidate causal associations between plasma liposomes and children using a two-sample Mendelian randomization (MR) approach. The IVW method was used as the primary analysis method, and tests such as the Cochran Q test, MR-Egger intercept, and leave-one-out method were utilized to explore whether there was heterogeneity and pleiotropy in the MR results. In addition, Steiger's test and reverse MR analysis were performed to test the directionality of the MR results.

RESULTS

Our MR results identified a causal link between six plasma liposomes and childhood asthma. Among them, negative association between Diacylglycerol (16:0_18:2) (OR = 0.952, 95%CI = 0.913-0.992, p = 0.018), Triacylglycerol (52:4) (OR = 0.949, 95%CI = 0.905-0.994, p = 0.028), Phosphatidylcholine (18:2_20:3) (OR = 0.915, 95%CI = 0.843-0.993, p = 0.034), sterol ester (27:1/22:6) (OR = 0.929, 95% CI = 0.869-0.994, p = 0.031) and childhood asthma. There is a positive association between Phosphatidylcholine (16:0_22:5) (OR = 1.061, 95%CI = 1.006-1.120, p = 0.030), sterol ester (27:1/20:4) (OR = 1.046, 95% CI = 1.021-1.072, p = 0.0003) and pediatric asthma. A series of sensitivity tests also demonstrate the robustness of the results.

CONCLUSION

This MR study identified a causal link between some plasma liposomes and childhood asthma. This will provide new perspectives on the prevention and treatment of childhood asthma in the future.

Roles of TULA-family proteins in T cells and autoimmune diseases

The T cell Ubiquitin Ligand (TULA) protein family contains two members, UBASH3A and UBASH3B, that display similarities in protein sequence and domain structure. Both TULA proteins act to repress T cell activation via a combination of overlapping and nonredundant functions. UBASH3B acts mainly as a phosphatase that suppresses proximal T cell receptor (TCR) signaling. In contrast, UBASH3A acts primarily as an adaptor protein, interacting with other proteins (including UBASH3B) in T cells upon TCR stimulation and resulting in downregulation of TCR signaling and NF-κB signaling. Human genetic and functional studies have revealed another notable distinction between UBASH3A and UBASH3B: numerous genome-wide association studies have identified statistically significant associations between genetic variants in and around the UBASH3A gene and at least seven different autoimmune diseases, suggesting a key role of UBASH3A in autoimmunity. However, the evidence for an independent role of UBASH3B in autoimmune disease is limited. This review summarizes key findings regarding the roles of TULA proteins in T cell biology and autoimmunity, highlights the commonalities and differences between UBASH3A and UBASH3B, and speculates on the individual and joint effects of TULA proteins on T cell signaling.

IL7 as a Risk Factor for Prostate Cancer: Implications for T Cell Apoptosis and Infiltration in the Tumor Microenvironment

BACKGROUND

Prostate cancer's complex interplay with the immune microenvironment prompted an investigation into immune-related pathogenic mechanisms and potential therapeutic targets.

METHODS

Within the GSE176031 data set, Seurat meticulously dissected single-cell profiles from radical prostatectomy patients. Leveraging CellMarker and SingleR cell identities were precisely annotated. Then, monocle traced pseudotime trajectories, illuminating cellular paths, complemented by CellChat's insights into intricate intercellular communications. Furthermore, mendelian randomization (MR) robustly substantiated causal associations within prostate cancer contexts.

RESULTS

Employing single-cell analysis on intraoperative tumor and normal tissue, we identified 15 distinct cell types, notably observing a significant T cell reduction in tumor samples. Intercellular communication analysis revealed multiple pathways between epithelial cells and T cells, highlighting interleukin (IL)-IL7R-IL2RG interactions. IL7R, crucial in T cell apoptosis, showed differential expression across T cell development stages. Patients with IL7 amplification had poorer outcomes (p < 0.05), supported by MR in two cohorts (ieu-b-4809 cohort: odds ratio [OR] = 1.005, p = 0.002, 95% confidence interval [CI] [1.002-1.008]; ebi-a-GCST90018905: OR = 1.063, p = 0.032, 95% CI [1.005-1.125]), confirming IL7 as a prostate cancer risk factor.

CONCLUSIONS

These findings suggest T cell depletion via IL7-IL7R signaling may drive prostate cancer progression, offering novel therapeutic insights.

Systematic Mendelian Randomization Exploring Druggable Genes for Hemorrhagic Strokes

Patients with hemorrhagic stroke have high rates of morbidity and mortality, and drugs for prevention are very limited. Mendelian randomization (MR) analysis can increase the success rate of drug development by providing genetic evidence. Previous MR analyses only analyzed the role of individual drug target genes in hemorrhagic stroke; therefore, we used MR analysis to systematically explore the druggable genes for hemorrhagic stroke. We sequentially performed summary-data-based MR analysis and two-sample MR analysis to assess the associations of all genes within the database with intracranial aneurysm, intracerebral hemorrhage, and their subtypes. Validated genes were further analyzed by colocalization. Only genes that were positive in all three analyses and were druggable were considered desirable genes. We also explored the mediators of genes affecting hemorrhagic stroke incidence. Finally, the associations of druggable genes with other cardiovascular diseases were analyzed to assess potential side effects. We identified 56 genes that significantly affected hemorrhagic stroke incidence. Moreover, TNFSF12, SLC22A4, SPARC, KL, RELT, and ADORA3 were found to be druggable. The inhibition of TNFSF12, SLC22A4, and SPARC can reduce the risk of intracranial aneurysm, subarachnoid hemorrhage, and intracerebral hemorrhage. Gene-induced hypertension may be a potential mechanism by which these genes cause hemorrhagic stroke. We also found that blocking these genes may cause side effects, such as ischemic stroke and its subtypes. Our study revealed that six druggable genes were associated with hemorrhagic stroke, and the inhibition of TNFSF12, SLC22A4, and SPARC had preventive effects against hemorrhagic strokes.

Diabetes exerts a causal impact on the nervous system within the right hippocampus: substantiated by genetic data

INTRODUCTION

Diabetes and neuronal loss in the hippocampus have been observed to be correlated in several studies; however, the exact causality of this association remains uncertain. This study aims to explore the potential causal relationship between diabetes and the hippocampal nervous system.

METHODS

We utilized the two-sample Mendelian randomization (MR) analysis to investigate the potential causal connection between diabetes and the hippocampal nervous system. The summary statistics of Genome-wide association study (GWAS) for diabetes and hippocampus neuroimaging measurement were acquired from published GWASs, all of which were based on European ancestry. Several two-sample MR analyses were conducted in this study, utilizing inverse-variance weighted (IVW), MR Egger, and Weight-median methods. To ensure the reliability of the results and identify any horizontal pleiotropy, sensitivity analyses were undertaken using Cochran's Q test and the MR-PRESSO global test.

RESULTS

Causal associations were found between diabetes and the nervous system in the hippocampus. Type 1 and type 2 diabetes were both identified as having adverse causal connections with the right hippocampal nervous system. This was supported by specific ranges of IVW-OR values (P < 0.05). The consistency of the sensitivity analyses further reinforced the main findings, revealing no significant heterogeneity or presence of horizontal pleiotropy.

CONCLUSIONS

This study delved into the causal associations between diabetes and the hippocampal nervous system, revealing that both type 1 and type 2 diabetes have detrimental effects on the right hippocampal nervous system. Our findings have significant clinical implications as they indicate that diabetes may play a role in the decline of neurons in the right hippocampus among European populations, often resulting in cognitive decline.

Genetic association between immune-mediated inflammatory diseases and peripheral artery disease: a Mendelian randomization study

Several observational studies have revealed that immune-mediated inflammatory diseases (IMIDs) are associated with an increased risk of peripheral artery disease (PAD). However, the causal association remains to be determined. To corroborate previous research, we conducted Mendelian randomization (MR) analysis with the aim of clarifying the associations of various IMIDs with PAD. two-sample MR analysis was conducted to investigate the potential causal association between eight common IMIDs (including rheumatoid arthritis (RA), Crohn's disease (CD), ulcerative colitis (UC), systemic lupus erythematosus (SLE), ankylosing spondylitis(AS), psoriasis(PSO), multiple sclerosis(MS), and hashimoto thyroiditis(HT)) and PAD. Genome-wide association study (GWAS) was used to identify genetic variants associated with IMIDs and PAD. We employed the inverse variance weighted (IVW) method as the primary method to verify the causal relationship between exposures (IMIDs) and outcomes (PAD). In addition, heterogeneity test, horizontal pleiotropy test, and leave-one-out analysis were performed to evaluate the robustness of the MR results. The IVW model yielded evidence of a positive association between RA and PAD (OR = 1.059, 95% CI: 1.026-1.094, p<0.001), which was consistent with the results obtained from MR-Egger regression and weighted median analyses, indicating that the results of MR analysis were reliable. However, no statistically significant associations were observed between other IMIDs, including UC, CD, SLE, AS, PSO, MS, and HT, and PAD. Our analysis supported the causal association of RA with increased risks of PAD. Strengthening screening and prevention of PAD is of great significance in reducing the risk of PAD in populations with RA.

Multi-ancestry meta-analysis of keloids uncovers novel susceptibility loci in diverse populations

Keloids are raised scars that grow beyond original wound boundaries, resulting in pain and disfigurement. Reasons for keloid development are not well-understood, and current treatment options are limited. Keloids are more likely to occur in darker-skinned individuals of African and Asian descent than in Europeans. We performed a genome-wide association study (GWAS) examining keloid risk across and within continental ancestry groups, incorporating 7,837 cases and 1,593,009 controls. We detected 21 novel independent loci in the multi-ancestry analysis, including several previously associated with fibroproliferative disorders. Heritability estimates were 6%, 21%, and 34% for the European, East Asian, and African ancestry analyses, respectively. Genetically predicted gene expression and colocalization analyses identified 27 gene-tissue pairs, including nine in skin and fibroblasts. Pathway analysis implicated integrin signaling and upstream regulators involved in cancer, fibrosis, and sex hormone signaling. This investigation nearly quintuples the number of keloid-associated risk loci, illuminating biological processes in keloid pathology.

Multi-ancestry genome-wide meta-analysis with 472,819 individuals identifies 32 novel risk loci for psoriasis

BACKGROUND

Psoriasis is a common chronic, recurrent, immune-mediated disease involved in the skin or joints or both. However, deeper insight into the genetic susceptibility of psoriasis is still unclear.

METHODS

Here we performed the largest multi-ancestry meta-analysis of genome-wide association study including 28,869 psoriasis cases and 443,950 healthy controls.

RESULTS

We identified 74 genome-wide significant loci for psoriasis. Of 74 loci, 32 were novel psoriasis risk loci. Across 74 loci, 801 likely causal genes are indicated and 164 causal genes are prioritized. SNP-based heritability analyses demonstrated that common variants explain 15% of genetic risk for psoriasis. Gene-set analyses and the genetic correlation revealed that psoriasis-related genes have the positive correlations with autoimmune diseases such as ulcerative colitis, inflammatory bowel diseases, and Crohn's disease. Gene-drug interaction analysis suggested that psoriasis-associated genes overlapped with targets of current medications for psoriasis. Finally, we used the multi-ancestry meta-analysis to explore drug repurposing and the potential targets for psoriasis.

CONCLUSIONS

We identified 74 genome-wide significant loci for psoriasis. Based on 74 loci, we provided new biological insights to the etiology of psoriasis. Of clinical interest, we gave some hints for 76 potential targets and drug repurposing for psoriasis.