Summary Data-based Mendelian Randomization Research Articles

Mendelian randomization analysis identifies druggable genes and drugs repurposing for chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a prevalent condition that significantly impacts public health. Unfortunately, there are few effective treatment options available. Mendelian randomization (MR) has been utilized to repurpose existing drugs and identify new therapeutic targets. The objective of this study is to identify novel therapeutic targets for COPD. Cis-expression quantitative trait loci (cis-eQTL) were extracted for 4,317 identified druggable genes from genomics and proteomics data of whole blood (eQTLGen) and lung tissue (GTEx Consortium). Genome-wide association studies (GWAS) data for doctor-diagnosed COPD, spirometry-defined COPD (Forced Expiratory Volume in one second [FEV1]/Forced Vital Capacity [FVC] <0.7), and FEV1 were obtained from the cohort of FinnGen, UK Biobank and SpiroMeta consortium. We employed Summary-data-based Mendelian Randomization (SMR), HEIDI test, and colocalization analysis to assess the causal effects of druggable gene expression on COPD and lung function. The reliability of these druggable genes was confirmed by eQTL two-sample MR and protein quantitative trait loci (pQTL) SMR, respectively. The potential effects of druggable genes were assessed through the phenome-wide association study (PheWAS). Information on drug repurposing for COPD was collected from multiple databases. A total of 31 potential druggable genes associated with doctor-diagnosed COPD, spirometry-defined COPD, and FEV1 were identified through SMR, HEIDI test, and colocalization analysis. Among them, 22 genes (e.g., MMP15, PSMA4, ERBB3, and LMCD1) were further confirmed by eQTL two-sample MR and protein SMR analyses. Gene-level PheWAS revealed that ERBB3 expression might reduce inflammation, while GP9 and MRC2 were associated with other traits. The drugs Montelukast (targeting the MMP15 gene) and MARIZOMIB (targeting the PSMA4 gene) may reduce the risk of spirometry-defined COPD. Additionally, an existing small molecule inhibitor of the APH1A gene has the potential to increase FEV1. Our findings identified 22 potential drug targets for COPD and lung function. Prioritizing clinical trials that target these identified druggable genes with existing drugs or novel medications will be beneficial for the development of COPD treatments.

Identification of prospective aging drug targets via Mendelian randomization analysis.

Aging represents a multifaceted process culminating in the deterioration of biological functions. Despite the introduction of numerous anti-aging strategies, their therapeutic outcomes have often been less than optimal. Consequently, discovering new targets to mitigate aging effects is of critical importance. We applied Mendelian randomization (MR) to identify potential pharmacological targets against aging, drawing upon summary statistics from both the Decode and FinnGen cohorts, with further validation in an additional cohort. To address potential reverse causality, bidirectional MR analysis with Steiger filtering was utilized. Additionally, Bayesian co-localization and phenotype scanning were implemented to investigate previous associations between genetic variants and traits. Summary-data-based Mendelian randomization (SMR) analysis was conducted to assess the impact of genetic variants on aging via their effects on protein expression. Additionally, mediation analysis was orchestrated to uncover potential intermediaries in these associations. Finally, we probed the systemic implications of drug-target protein expression across diverse indications by MR-PheWas analysis. Utilizing a Bonferroni-corrected threshold, our MR examination identified 10 protein-aging associations. Within this cohort of proteins, MST1, LCT, GMPR2, PSMB4, ECM1, EFEMP1, and ISLR2 appear to exacerbate aging risks, while MAX, B3GNT8, and USP8 may exert protective influences. None of these proteins displayed reverse causality except EFEMP1. Bayesian co-localization inferred shared variants between aging and proteins such as B3GNT8 (rs11670143), ECM1 (rs61819393), and others listed. Mediator analysis pinpointed 1,5-anhydroglucitol as a partial intermediary in the influence LCT exhibits on telomere length. Circulating proteins play a pivotal role in influencing the aging process, making them promising candidates for therapeutic intervention. The implications of these proteins in aging warrant further investigation in future clinical research.

Causal effect of gut microbiota on pancreatic cancer: A Mendelian randomization and colocalization study.

The causal relationship between gut microbiota (GM) and pancreatic cancer (PC) remains unclear. This study aimed to investigate the potential genes underlying this mechanism. GM Genome-wide association study (GWAS) summary data were from the MiBioGen consortium. PC GWAS data were from the National Human Genome Research Institute-European Bioinformatics Institute (NHGRI-EBI) GWAS Catalogue. To detect the causal relationship between GM and PC, we implemented three complementary Mendelian randomization (MR) methods: Inverse Variance Weighting (IVW), MR-Egger and Weighted Median, followed by sensitivity analyses. Furthermore, we integrated GM GWAS data with blood cis-expression quantitative trait loci (eQTLs) and blood cis-DNA methylation QTL (mQTLs) using Summary data-based Mendelian Randomization (SMR) methods. This integration aimed to prioritize potential GM-affecting genes through SMR analysis of two molecular traits. PC cis-eQTLs and cis-mQTLs were summarized from The Cancer Genome Atlas (TCGA) data. Through colocalization analysis of GM cis-QTLs and PC cis-QTLs data, we identified common genes that influence both GM and PC. Our study found a causal association between GM and PC, including four protective and five risk-associated GM [Inverse Variance Weighted (IVW), p < 0.05]. No significant heterogeneity of instrumental variables (IVs) or horizontal pleiotropy was found. The gene SVBP was identified as a GM-affecting gene using SMR analysis of two molecular traits (FDR<0.05, P_HEIDI>0.05). Additionally, two genes, MCM6 and RPS26, were implicated in the interaction between GM and PC based on colocalization analysis (PPH4>0.5). In summary, this study provides evidence for future research aimed at developing suitable therapeutic interventions and disease prevention.

Statins as a risk factor for diabetic retinopathy: a Mendelian randomization and cross-sectional observational study

BackgroundDiabetic retinopathy (DR) is the foremost cause of vision loss among the global working-age population, and statins are among the most frequently prescribed drugs for lipid management in patients with DR. The exact relationship between statins and DR has not been determined. This study sought to validate the causal association between statins usage and diabetic retinopathy.MethodsThe summary-data-based Mendelian randomization (SMR) method and inverse-variance-weighted Mendelian randomization (IVW-MR) were used to identify the causal relationship between statins and DR via the use of expression quantitative trait loci (eQTL) data for 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) (31,684 blood samples), low density lipoprotein cholesterol-related GWAS data (sample size: 440,546), and DR-related GWAS data (14,584 cases and 176,010 controls). Additionally, a cross-sectional observational study based on the data from the National Health and Nutrition Examination Survey (NHANES) was conducted to supplement the association between DR and statins (sample size: 106,911). The odds ratios (ORs) with corresponding 95% confidence intervals (CIs) was employed to evaluate the results.ResultsBased on the results of the MR analysis, HMGCR inhibitors were causally connected with a noticeably greater incidence of DR (IVW: OR = 0.54, 95% CI [0.42, 0.69], p = 0.000002; SMR: OR = 0.66, 95% CI [0.52, 0.84], p = 0.00073). Subgroup analysis revealed that the results were not affected by the severity of DR. The sensitivity analysis revealed the stability and reliability of the MR analysis results. The results from the cross-sectional study based on NHANES also support the association between not taking statins and a decreased risk of DR (OR = 0.54, 95% CI [0.37, 0.79], p = 0.001).ConclusionsThis study revealed that a significant increase in DR risk was causally related to statins use, providing novel insights into the role of statins in DR. However, further investigations are needed to verify these findings.

Genetic overlap and causality between COVID-19 and multi-site chronic pain: the importance of immunity.

The existence of chronic pain increases susceptibility to virus and is now widely acknowledged as a prominent feature recognized as a major manifestation of long-term coronavirus disease 2019 (COVID-19) infection. Given the ongoing COVID-19 pandemic, it is imperative to explore the genetic associations between chronic pain and predisposition to COVID-19. We conducted genetic analysis at the single nucleotide polymorphism (SNP), gene, and molecular levels using summary statistics of genome-wide association study (GWAS) and analyzed the drug targets by summary data-based Mendelian randomization analysis (SMR) to alleviate the multi-site chronic pain in COVID-19. Additionally, we performed a latent causal variable (LCV) method to investigate the causal relationship between chronic pain and susceptibility to COVID-19. The cross-trait meta-analysis identified 19 significant SNPs shared between COVID-19 and chronic pain. Coloc analysis indicated that the posterior probability of association (PPH4) for three loci was above 70% in both critical COVID-19 and COVID-19, with the corresponding top three SNPs being rs13135092, rs7588831, and rs13135092. A total of 482 significant overlapped genes were detected from MAGMA and CPASSOC results. Additionally, the gene ANAPC4 was identified as a potential drug target for treating chronic pain (P=7.66E-05) in COVID-19 (P=8.23E-03). Tissue enrichment analysis highlighted that the amygdala (P=7.81E-04) and prefrontal cortex (P=8.19E-05) as pivotal in regulating chronic pain of critical COVID-19. KEGG pathway enrichment further revealed the enrichment of pleiotropic genes in both COVID-19 (P=3.20E-03,Padjust=4.77E-02,hsa05171) and neurotrophic pathways (P=9.03E-04,Padjust =2.55E-02,hsa04621). Finally, the latent causal variable (LCV) model was applied to find the genetic component of critical COVID-19 was causal for multi-site chronic pain (P=0.015), with a genetic causality proportion (GCP) of was 0.60. In this study, we identified several functional genes and underscored the pivotal role of the inflammatory system in the correlation between the paired traits. Notably, heat shock proteins emerged as potential objective biomarkers for chronic pain symptoms in individuals with COVID-19. Additionally, the ubiquitin system might play a role in mediating the impact of COVID-19 on chronic pain. These findings contribute to a more comprehensive understanding of the pleiotropy between COVID-19 and chronic pain, offering insights for therapeutic trials.

Proteome-Wide Mendelian Randomization and Colocalization Analysis Identify Therapeutic Targets for Knee and Hip Osteoarthritis.

Osteoarthritis (OA) is a common degenerative disease. Although some biomarkers and drug targets of OA have been discovered and employed, limitations and challenges still exist in the targeted therapy of OA. Mendelian randomization (MR) analysis has been regarded as a reliable analytic method to identify effective therapeutic targets. Thus, we aimed to identify novel therapeutic targets for OA and investigate their potential side effects based on MR analysis. In this study, two-sample MR, colocalization analysis, summary-data-based Mendelian randomization (SMR) and Mendelian randomization phenome-wide association study (MR-PheWAS) were conducted. We firstly analyzed data from 4907 plasma proteins to identify potential therapeutic targets associated with OA. In addition, blood expression quantitative trait loci (eQTLs) data sources were used to perform additional validation. A protein-protein interaction (PPI) network was also constructed to delve into the interactions among identified proteins. Then, MR-PheWASs were utilized to assess the potential side effects of core therapeutic targets. After MR analysis and FDR correction, we identified twelve proteins as potential therapeutic targets for knee OA or hip OA. Colocalization analysis and additional validation supported our findings, and PPI networks revealed the interactions among identified proteins. Finally, we identified MAPK3 (OR = 0.855, 95% CI: 0.791-0.923, p = 6.88 × 10-5) and GZMK (OR = 1.278, 95% CI: 1.131-1.444, p = 8.58 × 10-5) as the core therapeutic targets for knee OA, and ITIH1 (OR = 0.847, 95% CI: 0.784-0.915, p = 2.44 × 10-5) for hip OA. A further MR phenome-wide association study revealed the potential side effects of treatments targeting MAPK3, GZMK, and ITIH1. This comprehensive study indicates twelve plasma proteins with potential roles in knee and hip OA as therapeutic targets. This advancement holds promise for the progression of OA drug development, and paves the way for more efficacious treatments of OA.

Integrated analysis reveals FLI1 regulates the tumor immune microenvironment via its cell-type-specific expression and transcriptional regulation of distinct target genes of immune cells in breast cancer

BackgroundImmunotherapy is a practical therapeutic approach in breast cancer (BRCA), and the role of FLI1 in immune regulation has gradually been unveiled. However, the specific role of FLI1 in BRCA was conflicted; thus, additional convincing evidence is needed.MethodsWe explored the upstream regulation of FLI1 expression via summary data-based Mendelian randomization (SMR) analysis and ncRNA network construction centering on FLI1 using BRCA genome-wide association study (GWAS) summary data with expression quantitative trait loci (eQTLs) and DNA methylation quantitative trait loci (mQTLs) from the blood and a series of in silico analyses, respectively. We illuminated the downstream function of FLI1 in immune regulation by integrating a series of analyses of single-cell RNA sequence data (scRNA-seq).ResultsWe verified a causal pathway from FLI1 methylation to FLI1 gene expression to BRCA onset and demonstrated that FLI1 was downregulated in BRCA. FLI1, a transcription factor, served as myeloid and T cells’ communication regulator by targeting immune-related ligands and receptor transcription in BRCA tissues. We constructed a ceRNA network centering on FLI1 that consisted of three LncRNAs (CKMT2-AS1, PSMA3-AS1, and DIO3OS) and a miRNA (hsa-miR-324-5p), and the expression of FLI1 was positively related to a series of immune-related markers, including immune cell infiltration, biomarkers of immune cells, and immune checkpoints.ConclusionLow-methylation-induced or ncRNA-mediated downregulation of FLI1 is associated with poor prognosis, and FLI1 might regulate the tumor immune microenvironment via a cell-type-specific target genes manner in BRCA.

Revealing genes associated with cervical cancer in distinct immune cells: A comprehensive Mendelian randomization analysis.

Human papillomavirus can be contracted by sexually active women. However, only a small proportion of these infections persist and have the potential to progress into cervical cancers, indicating a significant involvement of the immune system in cervical cancer development. Despite this, our understanding of the precise contributions of genes from different immune cell types in cervical cancers remains limited. Therefore, the primary objective of our study was to investigate the potential causal relationships between specific immune cell genes and the development of cervical cancers. By accessing expression quantitative trait loci datasets of 14 distinct immune cell types and genome wide association study of cervical cancers, we employed the summary data-based Mendelian randomization (SMR) along with multi-single nucleotide polymorphism (SNP)-based SMR to identify significant genes associated with cervical cancers. Colocalization analysis was further conducted to explore the shared genetic causality. A total of 10 genes across 11 immune cell types (26 significant gene-trait associations) were found to be associated with cervical cancers after false discovery rate correction. Notably, the ORMDL3, BRK1 and HMGN1 gene expression levels showed significant association with cervical cancer in specific immune cell types, respectively. These associations were supported by strong evidence of colocalization analyses. Our study has identified several genes in different immune cells that were associated with cervical cancer. However, further research is necessary to confirm these findings and provide more comprehensive insights into the association between these gene expressions and cervical cancer risk.

QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration

DNA methylation provides a crucial epigenetic mark linking genetic variations to environmental influence. We have analyzed array-based DNA methylation profiles of 160 human retinas with co-measured RNA-seq and >8 million genetic variants, uncovering sites of genetic regulation in cis (37,453 methylation quantitative trait loci and 12,505 expression quantitative trait loci) and 13,747 DNA methylation loci affecting gene expression, with over one-third specific to the retina. Methylation and expression quantitative trait loci show non-random distribution and enrichment of biological processes related to synapse, mitochondria, and catabolism. Summary data-based Mendelian randomization and colocalization analyses identify 87 target genes where methylation and gene-expression changes likely mediate the genotype effect on age-related macular degeneration. Integrated pathway analysis reveals epigenetic regulation of immune response and metabolism including the glutathione pathway and glycolysis. Our study thus defines key roles of genetic variations driving methylation changes, prioritizes epigenetic control of gene expression, and suggests frameworks for regulation of macular degeneration pathology by genotype–environment interaction in retina.

Circulating lipids, lipid-lowering drug targets, and breast cancer risk: Comprehensive evidence from Mendelian randomization and summary data-based Mendelian randomization.

Breast cancer (BC) is the most common and fatal cancer among women, yet the causal relationship between circulating lipids, lipid-lowering drugs, and BC remains unclear. Mendelian randomization (MR) and summary data-based MR (SMR) analysis are used to explore the causal relationship between plasma lipids, lipid-lowering drug targets, and BC. The result of MR suggested that per mg/dL higher levels of LDL-C (OR = 1.045, FDR = 0.023), HDL-C (OR = 1.079, FDR = 0.003), TC (OR = 1.043, FDR = 0.026), and APOA-I (OR = 1.085, FDR = 2.64E-04) were associated with increased BC risk, while TG was associated with reduced BC risk (OR = 0.926, FDR = 0.003). Per mg/dL higher levels of HDL-C (OR = 1.080, FDR = 0.011) and APOA-I (OR = 1.083, FDR = 0.002) were associated with increased ER+BC risk, while TG was associated with reduced ER+BC risk (OR = 0.909, FDR = 0.002). For every per 1mg/dL decrease in LDL, HMGCR (OR: 0.839; FDR = 0.016), NPC1L1 (OR: 0.702; FDR = 0.004), and PCSK9 (OR: 0.916; FDR = 0.026) inhibition were associated with reduced BC risk, whereas CETP inhibition (OR: 1.194; FDR = 0.026) was associated with increased BC risk. For every per 1mg/dL decrease in LDL, HMGCR (OR: 0.822; FDR = 0.023), NPC1L1 (OR: 0.633; FDR = 2.37E-03), and APOB inhibition (OR: 0.816; FDR = 1.98E-03) were associated with decreased ER-BC risk, while CETP inhibition (OR: 1.465; FDR = 0.011) was associated with increased ER-BC risk. SMR analysis indicated that HMGCR was associated with increased BC risk (OR: 1.112; p = 0.044). Lipids are associated with the BC risk, and lipid-lowering drugs targets HMGCR, NPC1L1, PCSK9, and APOB may be effective strategies for preventing BC. However, lipid-lowering drugs target CETP may potentially increase BC risk.

Potential association of genetically predicted lipid and lipid-modifying drugs with rheumatoid arthritis: A Mendelian randomization study.

Past studies have demonstrated that patients diagnosed with rheumatoid arthritis (RA) often exhibit abnormal levels of lipids. Furthermore, certain lipid-modifying medications have shown effectiveness in alleviating clinical symptoms associated with RA. However, the current understanding of the causal relationship between lipids, lipid-modifying medications, and the risk of developing RA remains inconclusive. This study employed Mendelian randomization (MR) to investigate the causal connection between lipids, lipid-modifying drugs, and the occurrence of RA. We obtained genetic variation for lipid traits and drug targets related to lipid modification from three sources: the Global Lipids Genetics Consortium (GLGC), UK Biobank, and Nightingale Health 2020. The genetic data for RA were acquired from two comprehensive meta-analyses and the R8 of FINNGEN, respectively. These variants were employed in drug-target MR analyses to establish a causal relationship between genetically predicted lipid-modifying drug targets and the risk of RA. For suggestive lipid-modified drug targets, we conducted Summary-data-based Mendelian Randomization (SMR) analyses and using expression quantitative trait loci (eQTL) data in relevant tissues. In addition, we performed co-localization analyses to assess genetic confounders. Our analysis revealed no significant causal relationship between lipid and RA. We observed that the genetically predicted 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) -mediated low density lipoprotein cholesterol (LDL-C) (OR 0.704; 95% CI 0.56, 0.89; P = 3.43×10-3), Apolipoprotein C-III (APOC3) -mediated triglyceride (TG) (OR 0.844; 95% CI 0.77, 0.92; P = 1.50×10-4) and low density lipoprotein receptor (LDLR) -mediated LDL-C (OR 0.835; 95% CI 0.73, 0.95; P = 8.81×10-3) were significantly associated with a lowered risk of RA. while Apolipoprotein B-100 (APOB) -mediated LDL-C (OR 1.212; 95%CI 1.05,1.40; P = 9.66×10-3) was significantly associated with an increased risk of RA. Our study did not find any supporting evidence to suggest that lipids are a risk factor for RA. However, we observed significant associations between HMGCR, APOC3, LDLR, and APOB with the risk of RA.

Causal relationship between particulate matter and COVID-19 risk: A mendelian randomization study

BackgroundObservational studies have linked exposure to fine (PM2.5) and coarse (PM10) particulate matter air pollution with adverse COVID-19 outcomes, including higher incidence and mortality. However, some studies questioned the effect of air pollution on COVID-19 susceptibility, raising questions about the causal nature of these associations. To address this, a less biased method like Mendelian randomization (MR) is utilized, which employs genetic variants as instrumental variables to infer causal relationships in observational data. MethodWe performed two-sample MR analysis using public genome-wide association studies data. Instrumental variables correlated with PM2.5 concentration, PM2.5 absorbance, PM2.5-10 concentration and PM10 concentration were identified. The inverse variance weighted (IVW), robust adjusted profile score (RAPS) and generalized summary data-based Mendelian randomization (GSMR) methods were used for analysis. ResultsIVW MR analysis showed PM2.5 concentration [odd ratio (OR) = 3.29, 95% confidence interval (CI) 1.48–7.35, P-value = 0.0036], PM2.5 absorbance (OR = 5.62, 95%CI 1.98–15.94, P-value = 0.0012), and PM10 concentration (OR = 3.74, 95%CI 1.52–9.20, P-value = 0.0041) increased the risk of COVID-19 severity after Bonferroni correction. Further validation confirmed PM2.5 absorbance was associated with heightened COVID-19 severity (OR = 6.05, 95%CI 1.99–18.38, P-value = 0.0015 for RAPS method; OR = 4.91, 95%CI 1.65–14.59, P-value = 0.0042 for GSMR method) and hospitalization (OR = 3.15, 95%CI 1.54–6.47, P-value = 0.0018 for RAPS method). No causal links were observed between particulate matter exposure and COVID-19 susceptibility. ConclusionsOur study established a causal relationship between smaller particle pollution, specifically PM2.5, and increased risk of COVID-19 severity and hospitalization. These findings highlight the importance of improving air quality to mitigate respiratory disease progression.

Association of statin use with osteoporosis risk: a drug-targeted Mendelian randomization study.

Hypercholesterolemia and the related inflammatory response promote the development of osteoporosis, but whether targeted interventions are protective against this bone metabolic disease remains unknown. The aim of this study was to investigate the association between the use of statins (one well-recognized cholesterol-lowering drug with anti-inflammatory properties) and the risk of osteoporosis using a drug-targeted Mendelian randomization (MR) approach. Instrumental variables predicting three cholesterol-lowering target genes (including HGMCR) and the cholesterol effectors mediated by these genes (i.e., total cholesterol, LDL cholesterol, and non-HDL cholesterol) were extracted from expression quantitative trait loci and genome-wide association studies. Inverse variance-weighted (IVW), summary data-based MR (SMR), multivariate MR, and colocalization analysis were used to determine the association of the interventions represented by these instrumental variables with heel bone mineral density (one diagnostic indicator of osteoporosis). The IVW reported that increased levels of HGMCR-mediated total cholesterol, LDL cholesterol, and non-HDL cholesterol were associated with the decreased level of heel bone mineral density (P = 4.086e-10, P = 1.487e-09, P = 1.967e-09). The colocalization analysis supported the relationship between HGMCR-mediated non-HDL cholesterol and heel bone mineral density. The SMR reported that higher expression of HGMCR was associated with the decreased level of this osteoporosis indicator (P = 0.036). The multivariate MR further confirmed the role of HGMCR in the correlation between cholesterol traits and heel bone mineral density, and also reported that estrogen played a mediating role in the above correlations. These evidence supported a protective effect of HMGCR-mediated non-HDL cholesterol reduction or statin use against osteoporosis.

Investigating the shared genetic architecture between frailty and insomnia.

The epidemiological association between frailty and insomnia is well established, yet the presence of a common genetic etiology is still uncertain. Further exploration is needed to ascertain the causal relationship between frailty and insomnia. Utilizing data obtained from genome-wide association studies (GWAS) summaries, we utilized the linkage disequilibrium score regression (LDSC) to determine the genetic correlation existing between frailty and insomnia. The determination of causality was achieved through the application of two-sample Mendelian randomization. We investigated the enrichment of single nucleotide polymorphism (SNP) at various tissue types utilizing stratified LD score regression (S-LDSC) and multimarker analysis of genome annotation (MAGMA). Common risk SNPs were identified using Multi-Trait Analysis of GWAS (MTAG) and Cross-Phenotype Association (CPASSOC). We further investigated the expression profiles of risk genes in tissues using Summary-data-based Mendelian randomization(SMR) based on pooled data, to explore potential functional genes. Our findings indicated a significant genetic correlation between frailty and insomnia, highlighting SNPs sharing risk (rs34290943, rs10865954), with a pronounced correlation in the localized genomic region 3p21.31. Partitioned genetic analysis revealed 24 functional elements significantly associated with both frailty and insomnia. Furthermore, mendelian randomization revealed a causal connection between frailty and insomnia. The genetic correlation between frailty and insomnia showed enrichment in 11 brain regions (S-LDSC) and 9 brain regions (MAGMA), where four functional genes (RMB6, MST1R, RF123, and FAM212A) were identified. This study suggests the existence of a genetic correlation and common risk genes between frailty and insomnia, contributing to a deeper comprehension of their pathogenesis and assists in identifying potential therapeutic targets.

Gene associations of lipid traits, lipid-lowering drug-target genes and endometriosis

Research QuestionDoes the observed correlation between dyslipidemia and endometriosis indicate bidirectional causal associations? Furthermore, is the prospect of utilizing lipid-lowering drugs to manage endometriosis a viable strategy? DesignBidirectional Mendelian Randomization (MR) is employed to investigate the causal association between lipid traits and endometriosis. Drug-target MR is utilized to explore potential drug-target genes for managing endometriosis. In cases where lipid-mediated effects via specific drug targets are significant, aggregate analyses, such as Summary-data-based Mendelian Randomization (SMR) and Colocalization methods, are introduced to validate the outcomes. Mediation analyses supplement these evaluations. ResultsBidirectional MR results suggested that genetically predicted triglycerides (TG) (odds ratio [OR] 1.16, 95% confidence interval [CI] 1.08-1.23), high-density lipoprotein cholesterol (HDL-C) (OR 0.87, 95% CI 0.81-0.94), low-density lipoprotein cholesterol (LDL-C) (OR 1.20, 95% CI 1.06-1.34) and apolipoprotein A (APOA) (OR 0.90, 95% CI 0.83-0.96) were causally associated with endometriosis. Reverse MR results revealed that genetically proxied endometriosis was causally associated with TG level (OR 1.02, 95% CI 1.01-1.02). In drug-target MR, genetic mimicry in proprotein convertase subtilisin/kexin type 9 (PCSK9) (OR1.40, 95% CI 1.13-1.72), apolipoprotein B (APOB) (OR 1.49, 95% CI 1.21-1.86) and Angiopoietin-related protein 3 (ANGPTL3) (OR 1.57, 95% CI 1.14-2.16) were significantly associated with the risk of endometriosis stages 1-2. ConclusionOur findings suggest a potential bidirectional causal association between endometriosis and dyslipidemia. Genetic mimicry of PCSK9, APOB, and ANGPTL3 is associated with the risk of early-stage endometriosis. The development of lipid-lowering drugs for treating endometriosis holds potential clinical interest.

Association of Antidiabetic Drug Target Genes with Inflammatory Bowel Disease: A Mendelian Randomization Study.

An unmet medical need for the treatment of inflammatory bowel disease (IBD) exists. A part of antidiabetic drugs had potential effects on IBD in various observational research. To investigate the potential of antidiabetic drugs on IBD. We undertook a summary-data-based Mendelian randomization (SMR) using the expression quantitative trait loci (eQTL) expressed in the blood or colon and a two sample Mendelian randomization (TSMR) utilizing single nucleotide polymorphism (SNP) of antidiabetic drug target genes mediated by blood glucose traits. Participants encompassed patients with IBD (25,042 cases/34,915 controls), UC (12,366 cases/33,609 controls), and CD (12,194 cases/28,072 controls). Data on eQTL in the blood or the colon were from the eQTLGen consortium (31,684 individuals) or GTEx Consortium V8, respectively. SMR was performed by SMR software (20,220,322); the primary method for TSMR was inverse-variance weighted (IVW) or Wald ratio through R studio (2023.06.0+421). Sensitivity analyses were carried out. A 1-SD upper expression of the KCNJ11 gene (target gene of sulfonylureas) in the blood reduced the risk of CD (OR per 1-SD = 0.728, 95% CI = 0.586-0.903, P = 0.004) according to the result of SMR. ABCC8 (target gene of sulfonylureas) expressed in the colon did not affect CD, UC, or IBD. T2D-mediated KCNJ11 has a protective effect on CD (OR = 0.475, 95% CI = 0.297-0.761, P = 0.002). Gene predicted no relationship between T2D and CD. Sulfonylureas (SUs) may have side effects on CD. This work provides some suggestions for the selection of antidiabetic drugs in patients with CD.

Causal relationship between inflammatory factors and cerebral small vessel disease: Univariate, multivariate, and summary-data-based mendelian randomization analysis.

To explore the impact of inflammatory factors on the incidence of cerebral small vessel disease (CSVD), we performed a mendelian randomization (MR) study to analyze the causal relationship between multiple inflammatory factors and CSVD imaging markers and utilized summary-data-based mendelian randomization (SMR) analysis to infer whether the impact of instrumental variables (IVs) on disease is mediated by gene expression or DNA methylation. Using public databases such as UKB and IEU, and original genome-wide association studies, we obtained IVs related to exposure (inflammatory factors) and outcome (CSVD imaging markers). We performed the inverse variance weighted, weighted median, and MR-Egger methods to assess causal effects between exposure and outcome in univariate MR analysis. To evaluate their heterogeneity, a series of sensitivity analyses were conducted, including the Cochrane Q test, MR-Egger intercept test, MR-Presso, and leave-one-out analysis. We also applied mediation and multivariate MR analysis to explore the interactions between positive exposures on the same outcome. Additionally, we conducted the SMR, which utilizes instruments within or near relevant genes in blood or brain tissues, to elucidate the causal associations with CSVD markers. ABO Univariate MR of multiple cohorts revealed that the risk of small vessel stroke (SVS) increases with elevated levels of TNF-related apoptosis-inducing ligand (TRAIL, OR, 1.23, 95% CI, 1.08-1.39) and interleukin-1 receptor-like 2, (IL-1RL2, OR, 1.29, 95% CI, 1.04-1.61). IL-18 was a potential risk factor for extensive basal ganglia perivascular space burden (BGPVS, OR, 1.02, 95% CI, 1.00-1.05). Moreover, the risk of extensive white matter perivascular space burden (WMPVS) decreased with rising levels of E-selectin (OR, .98, 95% CI, .97-1.00), IL-1RL2 (OR, .97, 95% CI, .95-1.00), IL-3 receptor subunit alpha (IL-3Ra, OR, .98, 95% CI, .97-1.00), and IL-5 receptor subunit alpha (IL-5Ra, OR, .98, 95% CI, .97-1.00). Mediation and multivariate MR analysis indicated that E-selectin and IL-3Ra might interact during the pathogenesis of WMPVS. SMR estimates showed that TRAIL-related IVs rs5030044 and rs2304456 increased the risk of SVS by increasing the expression of gene Kininogen-1 (KNG1) in the cerebral cortex, particularly in the frontal cortex (βsmr=.10, Psmr=.003, FDR=.04). Instruments (rs507666 and rs2519093) related to E-selectin and IL-3Ra could increase the risk of WMPVS by enhancing DNA methylation of the gene ABO in blood tissue (βsmr=.01-.02, Psmr=.001, FDR=.01-.03). According to MR and SMR analysis, higher levels of TRAIL increased the risk of SVS by upregulating gene expression of KNG1 in brain cortex tissues. In addition, protective effects of E-selectin and IL-3a levels on WMPVS were regulated by increased DNA methylation of gene ABO in blood tissue.

Circadian clock-related genome-wide mendelian randomization identifies putatively genes for ulcerative colitis and its comorbidity

BackgroundCircadian rhythm is crucial to the function of the immune system. Disorders of the circadian rhythm can contribute to inflammatory diseases such as Ulcerative colitis (UC). This Mendelian Randomization (MR) analysis applies genetic tools to represent the aggregated statistical results of exposure to circadian rhythm disorders and UC and its comorbidities, allowing for causal inferences.MethodsSummary statistics of protein, DNA methylation and gene expression quantitative trait loci in individuals of European ancestry (pQTL, mQTL, and eQTL, respectively) were used. Genetic variants located within or near 152 circadian clock-related genes and closely related to circadian rhythm disorders were selected as instrumental variables. Causal relationships with UC and its comorbidities were then estimated through employed Summary data-based Mendelian Randomization (SMR) and Inverse-Variance-Weighted MR (IVW-MR).ResultsThrough preliminary SMR analysis, we identified a potential causal relationship between circadian clock-related genes and UC along with its comorbidities, which was further confirmed by IVW-MR analysis. Our study identified strong evidence of positive correlation involving seven overlapping genes (CSNK1E, OPRL1, PIWIL2, RORC, MAX, PPP5C, and AANAT) through MWAS and TWAS in UC, four overlapping genes (OPRL1, CHRNB2, FBXL17, and SIRT1) in UC with PSC, and three overlapping genes (ARNTL, USP7, and KRAS) in UC with arthropathy.ConclusionsThis SMR study demonstrates the causal effect of circadian rhythm disorders in UC and its comorbidities. Furthermore, our investigation pinpointed candidate genes that could potentially serve as drug targets.

Interval estimate of causal effect in summary data based Mendelian randomization in the presence of winner's curse.

This research focuses on the interval estimation of the causal effect of an exposure on an outcome using the summary data-based Mendelian randomization (SMR) method while accounting for the winner's curse caused by the selection of single nucleotide polymorphism instruments. This issue is understudied and is important as the point estimate is biased. Since Fieller's theorem and its variations are not suitable for constructing a confidence interval, we use the box method. This box method is known to be conservative and thus provides a lower bound on the coverage level. To assess the performance of the box method, we use simulation studies and compare it with the support interval we proposed earlier and the Wald interval derived from the SMR method. All three methods are applied to a study of causal genes for Alzheimer's disease. Overall, the box method presents an alternative for constructing interval estimates for a causal effect while addressing the winner's curse issue.

Joint analysis of proteome, transcriptome, and multi-trait analysis to identify novel Parkinson's disease risk genes.

Genome-wide association studies (GWAS) have identified multiple risk variants for Parkinson's disease (PD). Nevertheless, how the risk variants confer the risk of PD remains largely unknown. We conducted a proteome-wide association study (PWAS) and summary-data-based mendelian randomization (SMR) analysis by integrating PD GWAS with proteome and protein quantitative trait loci (pQTL) data from human brain, plasma and CSF. We also performed a large transcriptome-wide association study (TWAS) and Fine-mapping of causal gene sets (FOCUS), leveraging joint-tissue imputation (JTI) prediction models of 22 tissues to identify and prioritize putatively causal genes. We further conducted PWAS, SMR, TWAS, and FOCUS using a multi-trait analysis of GWAS (MTAG) to identify additional PD risk genes to boost statistical power. In this large-scale study, we identified 16 genes whose genetically regulated protein abundance levels were associated with Parkinson's disease risk. We undertook a large-scale analysis of PD and correlated traits, through TWAS and FOCUS studies, and discovered 26 casual genes related to PD that had not been reported in previous TWAS. 5 genes (CD38, GPNMB, RAB29, TMEM175, TTC19) showed significant associations with PD at both the proteome-wide and transcriptome-wide levels. Our study provides new insights into the etiology and underlying genetic architecture of PD.