Association of Antihypertensive Drug Target Genes With Psychiatric Disorders: A Mendelian Randomization Study

SLAMF1 as a novel molecule mediating the causal association between rheumatoid arthritis and interstitial lung disease: A Mendelian randomization study combined with transcriptomics and in vivo validation

BACKGROUND

Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) is a common complication of rheumatoid arthritis (RA) that result in significant morbidity and mortality. Understanding the molecular mechanisms underlying RA-ILD is crucial for effective prevention. This study aims to identify the specific molecule that mediate the causal association between RA and ILD, as well as to explore its potential mechanisms in the pathogenesis of RA-ILD.

METHODS

Using two-sample Mendelian randomization (MR) analyses, we investigated the causal relationship among 16,987 blood genes, RA and ILD. Subsequently, a two-step MR technique was employed to identify significant genes that mediate the association between RA and ILD, and to quantify their proportion of mediation effect. To validate the genes as mediators, the replication MR analysis was conducted and the in vivo experiment was performed using an established animal model of RA-ILD. Furthermore, integrated bioinformatic analyses were conducted to elucidate the specific biological functions of the determined mediator in pathogenesis of RA-ILD.

RESULTS

Nine genes, namely MAPK8IP2, TAF11, SLAMF1, DAB2IP, GLUL, SLC4A10, PRSS35, NFX1, and PLK3, were identified as mediators. Among them, SLAMF1 was validated as the most significant mediator, accounting for 4.693% of the mediating effect on the causal relationship between RA and ILD. Upregulated mRNA expression of SLAMF1 was observed in the animal model of RA-ILD compared to controls. Bioinformatic analyses revealed that SLAMF1 was overexpressed in patients with lung fibrosis and correlated with a poor prognosis. Specifically, SLAMF1 was found to be predominantly overexpressed in T cells in lung tissues of patients with lung fibrosis. Additionally, the functional role of SLAMF1 was associated with multiple immune cell infiltrations and the biological process of extracellular matrix synthesis in pulmonary tissues from patients with lung fibrosis.

CONCLUSION

SLAMF1 may play a crucial role as a molecular mediator in the causal association between RA and ILD, and participate in multiple mechanisms underlying the pathogenesis of RA-ILD. This research provides insights into how the development of RA influences the risk of ILD and offers potential interventional targets against RA-ILD.

Genomics-driven integrative analysis highlights immune-related plasma proteins for psychiatric disorders

BACKGROUND

Genome-wide association studies (GWAS) have identified numerous variants associated with psychiatric disorders. However, it remains largely unknown on how GWAS risk variants contribute to psychiatric disorders.

METHODS

Through integrating two largest, publicly available, independent protein quantitative trait loci datasets of plasma protein and nine large-scale GWAS summary statistics of psychiatric disorders, we first performed proteome-wide association study (PWAS) to identify psychiatric disorders-associated plasma proteins, followed by enrichment analysis to reveal the underlying biological processes and pathways. Then, we conducted Mendelian randomization (MR) and Bayesian colocalization (COLOC) analyses, with both discovery and parallel replication datasets, to further identify protein-disorder pairs with putatively causal relationships. We finally prioritized the potential drug targets using Drug Gene Interaction Database.

RESULTS

PWAS totally identified 112 proteins, which were significantly enriched in biological processes relevant to immune regulation and response to stimulus including regulation of immune system process (adjusted P = 1.69 × 10-7) and response to external stimulus (adjusted P = 4.13 × 10-7), and viral infection related pathways, including COVID-19 (adjusted P = 2.94 × 10-2). MR and COLOC analysis further identified 26 potentially causal protein-disorder pairs in both discovery and replication analysis. Notably, eight protein-coding genes were immune-related, such as IRF3, CSK, and ACE, five among 16 druggable genes were reported to interact with drugs, including ACE, CSK, PSMB4, XPNPEP1, and MICB.

CONCLUSIONS

Our findings highlighted the immunological hypothesis and identified potentially causal plasma proteins for psychiatric disorders, providing biological insights into the pathogenesis and benefit the development of preventive or therapeutic drugs for psychiatric disorders.

The future of metronomic chemotherapy: experimental and computational approaches of drug repurposing

Metronomic chemotherapy (MC), long-term continuous administration of anticancer drugs, is gaining attention as an alternative to the traditional maximum tolerated dose (MTD) chemotherapy. By combining MC with other treatments, the therapeutic efficacy is enhanced while minimizing toxicity. MC employs multiple mechanisms, making it a versatile approach against various cancers. However, drug resistance limits the long-term effectiveness of MC, necessitating ongoing development of anticancer drugs. Traditional drug discovery is lengthy and costly due to processes like target protein identification, virtual screening, lead optimization, and safety and efficacy evaluations. Drug repurposing (DR), which screens FDA-approved drugs for new uses, is emerging as a cost-effective alternative. Both experimental and computational methods, such as protein binding assays, in vitro cytotoxicity tests, structure-based screening, and several types of association analyses (Similarity-Based, Network-Based, and Target Gene), along with retrospective clinical analyses, are employed for virtual screening. This review covers the mechanisms of MC, its application in various cancers, DR strategies, examples of repurposed drugs, and the associated challenges and future directions.

Study on the activity and mechanism of herbal formula anti-infection powder (AIP) against influenza-virus-induced pneumonia through genetic susceptibility genes

ETHNOPHARMACOLOGICAL RELEVANCE

Anti-infection powder (AIP), a patented Chinese herbal formulation, is used traditionally in the treatment of upper respiratory tract infections. In this study, an ethanol extract of AIP was demonstrated to inhibit influenza A virus (IAV) infection and IAV-induced pneumonia (IVP), both in vitro and in vivo, highlighting its potential mechanism of action.

AIM OF THE STUDY

To determine the anti-IAV activity of AIP and to explore the possible mechanisms of inhibiting IAV-induced pneumonia.

MATERIALS AND METHODS

An ethanol extract was extracted from AIP and its major ingredients were determined by high-performance liquid chromatography (HPLC). An IAV-infected A549 cell model and an IAV-induced mouse pneumonia model were established to evaluate the therapeutic effects of AIP on IVP in vivo and in vitro. The mice were respectively administered AIP at high- and low-dose in different groups. The anti-IAV activity of AIP was evaluated by detecting viral load, lung lesion, lung index, suvival time, inflammatory cytokines and transcriptomic analysis in the lung tissue. The potential pathways and targets that involved in AIP against IVP were predicted by network pharmacology. Mendelian randomization (MR), colocalization analysis, and molecular docking were employed to identify novel therapeutic targets for IVP. Polymerase chain reaction (PCR) and Western blot (WB) techniques were used to confirm the effect of AIP on the expression of risk target genes in the lungs of IVP mice.

RESULTS

In A549 cell line, AIP effectively inhibited IAV infection with IC50 values of 65.49 μg/mL. The anti-IAV activity of AIP was mainly determined by chlorogenic acid, forsythiarin, puerarin, paeoniflorin and prim-o-glucosylcimigin. Moreover, AIP inhibited the neuraminidase activity and the M gene expression in vitro. In vivo, oral administration of AIP significantly reduced viral load and improved lung tissue lesions. AIP decreased the concentration of pro-inflammatory factors such as IL-1β, TNF-α, and IFN-γ, and significantly increased the concentration of the anti-inflammatory factor IL-4. According to network pharmacology analysis, toll-like receptor signaling pathway, chemokine signaling pathway, and TNF signaling pathway may be the possible mechanisms by which AIP inhibits IVP and regulates excessive inflammatory response.Two new genes, LRG1 and PSMA4, associated with genetic susceptibility to influenza and pneumonia, predicted as potential IVP drug target genes by MR and colocalization analysis. The antiviral mechanism of AIP may be to inhibit the expression levels of LRG1 and PSMA4 in lungs of mouse IVP.

CONCLUSIONS

AIP exhibited anti-IAV activities both in vitro and in vivo. AIP had a protective effect against pneumonia caused by influenza virus and can inhibit the progression of inflammation. This effect may be associated with its ability to inhibit the expression levels of genetic susceptibility genes (LRG1 and PSMA4) in lungs of mouse IVP. The findings of this study enhance our understanding of the role and mechanisms of AIP in the treatment of IVP.

Unveiling new protein biomarkers and therapeutic targets for acne through integrated analysis of human plasma proteomics and genomics

Background

The current landscape of acne therapeutics is notably lacking in targeted treatments, highlighting a critical need for the discovery of new drug targets to improve treatment outcomes.

Objectives

This study aims to investigate the connections between proteomics and genetics in relation to acne across extensive population cohorts, aspiring to identify innovative preventive and therapeutic approaches.

Methods

Employing a longitudinal cohort of 54,306 participants from the UK Biobank Pharmacological Proteomics Project (UKB-PPP), we performed an exhaustive evaluation of the associations between 2,923 serum proteins and acne risk. Initial multivariate Cox regression analyses assessed the relationship between protein expression levels and acne onset, followed by two-sample Mendelian Randomization (TSMR), Summary-data-based Mendelian Randomization (SMR), and colocalization to identify genetic correlations with potential protein targets.

Results

Within the UKB cohort, we identified 19 proteins significantly associated with the risk of acne. Subsequent analysis using Two-Sample Mendelian Randomization (TSMR) refined this to two specific proteins: FSTL1 and ANXA5. Each one-standard deviation increase in the expression levels of FSTL1 and ANXA5 was associated with a 24% and 32% increase in acne incidence, respectively. These results were further validated by additional Summary-data-based Mendelian Randomization (SMR) and differential expression analyses.

Conclusions

Our comprehensive analysis of proteomic and genetic data from a European adult cohort provides compelling causal evidence that several proteins are promising targets for novel acne treatments.

HMGCR as a promising molecular target for therapeutic intervention in aortic aneurisms: a mendelian randomization study

BACKGROUND

Despite the exploration of the connections between serum low-density lipoprotein cholesterol (LDL-C) levels and aneurisms in epidemiological studies, causality remains unclear. Therefore, this study aimed to assess the causal impact of LDL-C-lowering targets (HMGCR, PCSK9, NPC1L1, CETP, APOB, and LDLR) on various forms of aneurisms using Mendelian Randomization (MR) analysis.

METHODS

Two genetic instruments acted as proxies for exposure to LDL-C-lowering drugs: expression quantitative trait loci of drug target genes and genetic variants linked to LDL-C near drug target genes. Summary-data-based MR (SMR), inverse-variance-weighted MR (IVW-MR), and multivariable MR (MVMR) methods were employed to compute the effect estimates.

RESULTS

The SMR analysis revealed substantial associations between increased HMGCR expression and a heightened risk of aortic aneurism (odds ratio [OR] = 1.603, 95% confidence interval [CI] = 1.209-2.124), thoracic aortic aneurism (OR = 1.666, 95% CI = 1.122-2.475), and abdominal aortic aneurism (OR = 1.910, 95% CI = 1.278-2.856). Likewise, IVW-MR analysis demonstrated positive correlations between HMGCR-mediated LDL-C and aortic aneurism (OR = 2.228, 95% CI = 1.702-2.918), thoracic aortic aneurism (OR = 1.751, 95% CI = 1.191-2.575), abdominal aortic aneurism (OR = 4.784, 95% CI = 3.257-7.028), and cerebral aneurism (OR = 1.993, 95% CI = 1.277-3.110). Furthermore, in the MVMR analysis, accounting for body mass index, smoking, and hypertension, a significant positive relationship was established between HMGCR-mediated LDL-C levels and the development of aortic aneurisms, encompassing both thoracic and abdominal subtypes. Similarly, consistent positive associations were observed for PCSK9 and CETP genes, as well as PCSK9-mediated and CETP-mediated LDL-C levels, with the occurrence of aortic aneurism and abdominal aortic aneurism. Nonetheless, the evidence for potential associations between APOB, NPC1L1 and LDLR with specific subtypes of aortic aneurisms lacked consistent support from both SMR and IVW-MR analyses.

CONCLUSIONS

Our MR analysis offered compelling evidence of a plausible causal link between HMGCR and an increased risk of aortic aneurism, encompassing both thoracic and abdominal types. These groundbreaking findings further bolster the case for the deployment of HMGCR inhibitors in the treatment of aortic aneurisms, including both thoracic and abdominal variants.

Validation of TYK2 and exploration of PRSS36 as drug targets for psoriasis using Mendelian randomization

Psoriasis is a chronic inflammatory skin disorder with multiple causes, including genetic and environmental factors. Despite advances in treatment, there remains a need to identify novel therapeutic targets. A Mendelian randomization (MR) analysis was conducted to identify therapeutic targets for psoriasis. Data on cis-expression quantitative trait loci were obtained from the eQTLGen Consortium (n = 31,684). Summary statistics for psoriasis (outcome) were sourced from the GWAS Catalog with a sample size of 484,598, including 5,427 cases and 479,171 controls. Colocalization analysis was used to assess whether psoriasis risk and gene expression were driven by shared single nucleotide polymorphisms. Drug prediction and molecular docking were utilized to validate the pharmacological value of the drug targets. The MR analysis found that 81 drug targets were significantly associated, and two (TYK2 and PRSS36) were supported by colocalization analysis (PP.H4 > 0.80). Phenome-wide association studies did not show any associations with other traits at the gene level. Biologically, these genes were closely related to immune function. Molecular docking revealed strong binding with drugs and proteins, as supported by available structural data. This study validated TYK2 as a drug target for psoriasis, in line with its existing clinical use, including the development of decucravacitinib. PRSS36 is a potential novel target requiring further investigation.

Multiomics identification of ALDH9A1 as a crucial immunoregulatory molecule involved in calcific aortic valve disease

Mitochondrial dysfunction and immune cell infiltration play crucial yet incompletely understood roles in the pathogenesis of calcific aortic valve disease (CAVD). This study aimed to identify immune-related mitochondrial genes critical to the pathological process of CAVD using multiomics approaches. The CIBERSORT algorithm was employed to evaluate immune cell infiltration characteristics in CAVD patients. An integrative analysis combining weighted gene coexpression network analysis (WGCNA), machine learning, and summary data-based Mendelian randomization (SMR) was performed to identify key mitochondrial genes implicated in CAVD. Spearman's rank correlation analysis was also performed to assess the relationships between key mitochondrial genes and infiltrating immune cells. Compared with those in normal aortic valve tissue, an increased proportion of M0 macrophages and resting memory CD4 T cells, along with a decreased proportion of plasma cells and activated dendritic cells, were observed in CAVD patients. Additionally, eight key mitochondrial genes associated with CAVD, including PDK4, LDHB, SLC25A36, ALDH9A1, ECHDC2, AUH, ALDH2, and BNIP3, were identified through the integration of WGCNA and machine learning methods. Subsequent SMR analysis, incorporating multiomics data, such as expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (mQTLs), revealed a significant causal relationship between ALDH9A1 expression and a reduced risk of CAVD. Moreover, ALDH9A1 expression was inversely correlated with M0 macrophages and positively correlated with M2 macrophages. These findings suggest that increased ALDH9A1 expression is significantly associated with a reduced risk of CAVD and that it may exert its protective effects by modulating mitochondrial function and immune cell infiltration. Specifically, ALDH9A1 may contribute to the shift from M0 macrophages to anti-inflammatory M2 macrophages, potentially mitigating the pathological progression of CAVD. In conclusion, ALDH9A1 represents a promising molecular target for the diagnosis and treatment of CAVD. However, further validation through in vivo and n vitro studies is necessary to confirm its role in CAVD pathogenesis and therapeutic potential.

Intestinal flora and inflammatory bowel disease: Causal relationships and predictive models

Background

Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, is significantly influenced by intestinal flora. Understanding the genetic and microbiotic interplay is crucial for IBD prediction and treatment.

Methods

We used Mendelian randomization (MR), transcriptomic analysis, and machine learning techniques, integrating data from the MiBioGen Consortium and various GWAS datasets. SNPs associated with intestinal flora were mapped to genes, with LASSO regression refining gene selection. Differentially expressed genes (DEGs) and immune infiltration patterns were identified through transcriptomic analysis. Six machine learning models were used for predictive modeling.

Findings

MR analysis identified 25 gut microbiota classifications causally related to IBD. SNP mapping and gene expression analysis highlighted 24 significant genes. Drug target MR and colocalization validated these genes' causal relationships with IBD. Key pathways identified included the PI3K-Akt signaling pathway and epithelial-mesenchymal transition. Immune infiltration analysis revealed distinct patterns between high and low LASSO score groups. Machine learning models demonstrated high predictive value, with soft voting enhancing reliability.

Interpretation

By integrating MR, transcriptomic analysis, and sophisticated machine learning approaches, this study elucidates the causal relationships between intestinal flora and IBD. The application of machine learning not only enhanced predictive modeling but also offered new insights into IBD pathogenesis, highlighted potential therapeutic targets, and established a robust framework for predicting IBD onset.

Genome-Wide Mendelian Randomization Identifies Ferroptosis-Related Drug Targets for Alzheimer's Disease

Background

Alzheimer's disease (AD) currently lacks effective disease-modifying treatments. Recent research suggests that ferroptosis could be a potential therapeutic target. Mendelian randomization (MR) is a widely used method for identifying novel therapeutic targets.

Objective

Employ genetic information to evaluate the causal impact of ferroptosis-related genes on the risk of AD.

Methods

564 ferroptosis-related genes were obtained from FerrDb. We derived genetic instrumental variables for these genes using four brain quantitative trait loci (QTL) and two blood QTL datasets. Summary-data-based Mendelian randomization (SMR) and two-sample MR methods were applied to estimate the causal effects of ferroptosis-related genes on AD. Using extern transcriptomic datasets and triple-transgenic mouse model of AD (3xTg-AD) to further validate the gene targets identified by the MR analysis.

Results

We identified 17 potential AD risk gene targets from GTEx, 13 from PsychENCODE, and 22 from BrainMeta (SMR p < 0.05 and HEIDI test p > 0.05). Six overlapping ferroptosis-related genes associated with AD were identified, which could serve as potential therapeutic targets (PEX10, CDC25A, EGFR, DLD, LIG3, and TRIB3). Additionally, we further pinpointed risk genes or proteins at the blood tissue and pQTL levels. Notably, EGFR demonstrated significant dysregulation in the extern transcriptomic datasets and 3xTg-AD models.

Conclusions

This study provides genetic evidence supporting the potential therapeutic benefits of targeting the six druggable genes for AD treatment, especially for EGFR (validated by transcriptome and 3xTg-AD), which could be useful for prioritizing AD drug development in the field of ferroptosis.

Genetic Association of Lipids and Lipid-Lowering Drug Target Genes With Attention Deficit Hyperactivity Disorder

BACKGROUND

Lipid metabolism plays an essential role in nervous system development. Cholesterol deficiency leads to a variety of neurodevelopmental disorders, such as autism spectrum disorder and fragile X syndrome. There have been a lot of efforts to search for biological markers associated with and causal to ADHD, among which lipid is one possible etiological factor that is quite widely studied. We aimed to evaluate the causal relationship between lipids traits, lipid-lowering drugs, and attention deficit hyperactivity disorder (ADHD) outcomes using Mendelian randomization (MR) studies.

METHODS

We used summary data from genome-wide association studies to explore the causal relationships between circulating lipid-related traits and ADHD. Then, quantitative trait loci for the expression of lipid-lowering drug target genes and genetic variants associated with lipid traits were extracted. Summary-data-based MR and inverse-variance-weighted MR (IVW-MR) were used to investigate the correlation between the expression of these drug-target genes and ADHD.

RESULTS

After rigorous screening, 939 instrumental variables were finally included for univariable mendelian randomization analysis. However, there is no correlation between lipid profile and ADHD risk. Drug target analysis by IVW-MR method observed that APOB-mediated low-density lipoprotein cholesterol was associated with lower ADHD risk (odds ratio [OR] = 0.90, 95% confidence interval [CI] [0.84, 0.97]; p = .007), whereas LPL-mediated triglycerides levels were associated with a higher risk of ADHD (OR = 1.13, 95% CI [1.06, 1.21]; p < .001).

CONCLUSION

Our results suggest that APOB gene and LPL gene may be candidate drug target genes for the treatment of ADHD.

Can NPC1L1 inhibitors reduce the risk of biliary tract cancer? Evidence from a mendelian randomization study

BACKGROUND & AIMS

Oxysterols have been implicated in biliary tract cancer (BTC), and Niemann-Pick C1-like 1 (NPC1L1) has been associated with oxysterol uptake in biliary and intestinal cells. Thus, our study aims to investigate the potential causal link between genetically proxied NPC1L1 inhibitors and the risk of BTC.

METHODS

In this study, we employed two genetic instruments as proxies for NPC1L1 inhibitors, which included LDL cholesterol-associated genetic variants located within or in close proximity to the NPC1L1 gene, as well as expression quantitative trait loci (eQTLs) of the NPC1L1 gene. Effect estimates were calculated using the Inverse-variance-weighted MR (IVW-MR) and summary-data-based MR (SMR) methods.

RESULTS

In MR analysis using the IVW method, both proxy instruments from the UK Biobank and the GLGC demonstrated a positive association between NPC1L1-mediated LDL cholesterol and BTC risk, with odds ratios (OR) of 10.30 (95% CI = 1.51-70.09; P = 0.017) and 5.61 (95% CI = 1.43-21.91; P = 0.013), respectively. Moreover, SMR analysis revealed a significant association between elevated NPC1L1 expression and increased BTC risk (OR = 1.19, 95% CI = 1.04-1.37; P = 0.014).

CONCLUSIONS

This MR study suggests a causal link between NPC1L1 inhibition and reduced BTC risk. NPC1L1 inhibitors, like ezetimibe, show potential for chemoprevention in precancerous BTC patients, requiring further clinical investigation.

Association between angiotensin-converting enzyme gene insertion/deletion polymorphism and cognition impairment in patients with schizophrenia

RATIONALE

Several lines of evidence indicate that an insertion/deletion (I/D) polymorphism in the angiotensin-converting enzyme gene (ACE) gene may be involved in the pathogenesis of schizophrenia and cognitive impairment. However, the relationship between ACE I/D polymorphism and cognitive impairment in patients with schizophrenia remains unclear.

OBJECTIVES

The aim of this study was to examine whether ACE gene I/D polymorphism contributed to cognitive impairment in Chinese patients with schizophrenia, and whether the association between clinical symptoms and cognitive impairment depended on different ACE genotypes.

METHODS

The ACE I/D polymorphism was genotyped in 928 schizophrenia patients and 325 healthy controls using a case-control design. The severity of psychopathological symptoms was assessed using the Positive and Negative Syndrome Scale (PANSS). Cognitive functioning was assessed by the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS).

RESULTS

There were significant differences in genotype and allele frequencies of the ACE I/D polymorphism between patients and healthy controls (both P < 0.01). After controlling for demographic characteristics, patients who are homozygous carriers of D and I performed worse on the RBANS attention index than heterozygous carriers (P = 0.009). In addition, attention index score was negatively correlated with PANSS negative symptom score in patients of all genotypes (all P < 0.05), and positively correlated with positive symptom score only in the I/I genotype (P = 0.005).

CONCLUSIONS

These findings suggest that ACE I/D gene variants play a role in susceptibility to schizophrenia, specific cognitive impairment and the association between clinical symptoms and cognitive impairment in schizophrenia patients.

From genetic associations to genes: methods, applications, and challenges

Genome-wide association studies (GWASs) have identified numerous genetic loci associated with human traits and diseases. However, pinpointing the causal genes remains a challenge, which impedes the translation of GWAS findings into biological insights and medical applications. In this review, we provide an in-depth overview of the methods and technologies used for prioritizing genes from GWAS loci, including gene-based association tests, integrative analysis of GWAS and molecular quantitative trait loci (xQTL) data, linking GWAS variants to target genes through enhancer-gene connection maps, and network-based prioritization. We also outline strategies for generating context-dependent xQTL data and their applications in gene prioritization. We further highlight the potential of gene prioritization in drug repurposing. Lastly, we discuss future challenges and opportunities in this field.

Association between psychiatric disorders and intracranial aneurysms: evidence from Mendelian randomization analysis

Objective

Several studies have explored the relationship between intracranial aneurysms and psychiatric disorders; nevertheless, the causal connection remains ambiguous. This study aimed to evaluate the causal link between intracranial aneurysms and specific psychiatric disorders.

Methods

A two-sample Mendelian randomization (MR) analysis was conducted utilizing aggregated genome-wide association study (GWAS) data from the International Stroke Genetics Association for Intracranial Aneurysms (IAs), unruptured Intracranial Aneurysm (uIA), and aneurysmal Subarachnoid Hemorrhage (aSAH). Psychiatric disorder data, encompassing Schizophrenia (SCZ), Bipolar Disorder (BD), and Panic Disorder (PD), were sourced from the Psychiatric Genomics Consortium (PGC), while Cognitive Impairment (CI) data, comprising Cognitive Function (CF) and Cognitive Performance (CP), were obtained from IEU OpenGWAS publications. Causal effects were evaluated using inverse variance weighted (IVW), MR-Egger, and weighted median methods, with the robustness of findings assessed via sensitivity analyses employing diverse methodological approaches.

Results

Our MR analysis indicated no discernible causal link between intracranial aneurysm (IA) and an elevated susceptibility to psychiatric disorders. However, among individuals with genetically predisposed unruptured intracranial aneurysms (uIA), there was a modest reduction in the risk of SCZ (IVW odds ratio [OR] = 0.95, 95% confidence interval [CI] 0.92-0.98, p = 0.0002). Similarly, IAs also exhibited a moderate reduction in SCZ risk (OR = 0.92, 95% CI 0.86-0.99, p = 0.02). Nevertheless, limited evidence was found to support a causal association between intracranial aneurysms and the risk of the other three psychiatric disorders.

Conclusion

Our findings furnish compelling evidence suggesting a causal influence of intracranial aneurysms on psychiatric disorders, specifically, both IAs and uIA exhibit a negative causal association with SCZ.

Integrating Mendelian randomization and single-cell RNA sequencing to identify therapeutic targets of baicalin for type 2 diabetes mellitus

Background

Alternative and complementary therapies play an imperative role in the clinical management of Type 2 diabetes mellitus (T2DM), and exploring and utilizing natural products from a genetic perspective may yield novel insights into the mechanisms and interventions of the disorder.

Methods

To identify the therapeutic target of baicalin for T2DM, we conducted a Mendelian randomization study. Druggable targets of baicalin were obtained by integrating multiple databases, and target-associated cis-expression quantitative trait loci (cis-eQTL) originated from the eQTLGen consortium. Summary statistics for T2DM were derived from two independent genome-wide association studies available through the DIAGRAM Consortium (74,124 cases vs. 824,006 controls) and the FinnGen R9 repository (9,978 cases vs. 12,348 controls). Network construction and enrichment analysis were applied to the therapeutic targets of baicalin. Colocalization analysis was utilized to assess the potential for the therapeutic targets and T2DM to share causative genetic variations. Molecular docking was performed to validate the potency of baicalin. Single-cell RNA sequencing was employed to seek evidence of therapeutic targets' involvement in islet function.

Results

Eight baicalin-related targets proved to be significant in the discovery and validation cohorts. Genetic evidence indicated the expression of ANPEP, BECN1, HNF1A, and ST6GAL1 increased the risk of T2DM, and the expression of PGF, RXRA, SREBF1, and USP7 decreased the risk of T2DM. In particular, SREBF1 has significant interaction properties with other therapeutic targets and is supported by strong colocalization. Baicalin had favorable combination activity with eight therapeutic targets. The expression patterns of the therapeutic targets were characterized in cellular clusters of pancreatic tissues that exhibited a pseudo-temporal dependence on islet cell formation and development.

Conclusion

This study identified eight potential targets of baicalin for treating T2DM from a genetic perspective, contributing an innovative analytical framework for the development of natural products. We have offered fresh insights into the connections between therapeutic targets and islet cells. Further, fundamental experiments and clinical research are warranted to delve deeper into the molecular mechanisms of T2DM.

Effects of genetically proxied statins on diabetic nephropathy and retinopathy: a Mendelian randomization study

There is no reliable causal evidence for the effect of statins on diabetic nephropathy (DN) and diabetic retinopathy (DR), and the results of previous observational studies are contradictory. Genetic variants linked to low-density lipoprotein cholesterol (LDL-C) from a UK biobank genome-wide association study and located within a 100kb window around HMGCR were used to proxy statins, comparing with PCSK9 inhibitors (control). DN and DR genome-wide association study summary statistics were obtained from the FinnGen study. Secondary MR analyses and NHANES cross-sectional data were used for validation. Drug-target Mendelian randomization (MR) was applied to investigate the association between the genetically proxied inhibition of HMGCR and PCSK9 with DN and DR, p < 0.0125 was considered significant after Bonferroni Correction. To triangulate the findings, genetic variants of whole blood-derived targets gene expression (cis-eQTL) and plasma-derived protein (cis-pQTL) levels were used to perform secondary MR analyses and data from the National Health and Nutrition Examination Survey were used for cross-sectional analysis. Genetically proxied inhibition of HMGCR was associated with higher risks of DN and DR (DN: OR = 1.79, p = 0.01; DR: OR = 1.41, p = 0.004), while no such association was found for PCSK9. Secondary MR analyses confirmed these associations. Cross-sectional analysis revealed a positive link between statin use and DR incidence (OR = 1.26, p = 0.03) and a significant negative association with glomerular filtration rate (Beta = - 1.9, p = 0.03). This study provides genetic evidence that genetically proxied inhibition of HMGCR is associated with increased risks of DN/DR, and this effect may not be attributed to their LDL-C-lowering properties. For patients with diabetic dyslipidemia, PCSK9 inhibitors may be a preferable alternative.

Genetic proxy of lipid-lowering drugs and calcific aortic valve stenosis: A Mendelian randomization study

Background

Lipid metabolism plays an important role in the pathogenesis and development of calcific aortic valve stenosis. Our aim was to evaluate the causal effect of lipid-lowering drugs, such as low-density lipoprotein cholesterol (LDL-C) lowering and triglyceride lowering drugs, on the outcome of aortic valve stenosis using a two-sample Mendelian randomization (MR) study.

Methods

We used two genetic tools to represent the exposure of lipid-lowering drugs, including expression quantitative trait loci for the expression of drug target genes, and genetic variants within or near drug target genes that are associated with LDL-C and triglyceride concentrations from Genome-Wide Association Studies (GWAS). Effect estimates were calculated using summary-data-based MR (SMR) and inverse-variance-weighted MR (IVW-MR) analysis.

Results

Based on the results of SMR and IVW-MR analysis, LDL-C-lowering PCSK9 inhibitors have potential in reducing the risk of aortic valve stenosis (for SMR, OR: 1.044; 95%CI: 1.002-1.404; P = 0.047; for IVW-MR, OR: 1.647, 95%CI: 1.316-2.062, P < 0.001). However, no significant association was observed between triglyceride target gene expression, as well as triglyceride-lowering drugs, and aortic valve stenosis.

Conclusion

This two-sample drug-targeted MR study suggests a potential causal relationship between PCSK9 inhibitors and the reduction of calcific aortic valve stenosis risk.

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.

Genetically determined blood pressure, antihypertensive drug classes, and frailty: A Mendelian randomization study

Observational studies have suggested that the use of antihypertensive drugs was associated with the risk of frailty; however, these findings may be biased by confounding and reverse causality. This study aimed to explore the effect of genetically predicted lifelong lowering blood pressure (BP) through different antihypertensive medications on frailty. One-sample Mendelian randomization (MR) and summary data-based MR (SMR) were applied. We utilized two kinds of genetic instruments to proxy the antihypertensive medications, including genetic variants within or nearby drugs target genes associated with systolic/diastolic BP, and expression level of the corresponding gene. Among 298,618 UK Biobank participants, one-sample MR analysis observed that genetically proxied BB use (relative risk ratios, 0.76; 95% CI, 0.65-0.90; p = 0.001) and CCB use (0.83; 0.72-0.95; p = 0.007), equivalent to a 10-mm Hg reduction in systolic BP, was significantly associated with lower risk of pre-frailty. In addition, although not statistically significant, the effect directions of systolic BP through ACEi variants (0.72; 0.39-1.33; p = 0.296) or thiazides variants (0.74; 0.53-1.03; p = 0.072) on pre-frailty were also protective. Similar results were obtained in analyses for diastolic BP. SMR of expression in artery showed that decreased expression level of KCNH2, a target gene of BBs, was associated with lower frailty index (beta -0.02, p = 2.87 × 10-4). This MR analysis found evidence that the use of BBs and CCBs was potentially associated with reduced frailty risk in the general population, and identified KCNH2 as a promising target for further clinical trials to prevent manifestations of frailty.

Renshen Yangrong decoction for secondary malaise and fatigue: network pharmacology and Mendelian randomization study

Background

Renshen Yangrong decoction (RSYRD) has been shown therapeutic effects on secondary malaise and fatigue (SMF). However, to date, its bioactive ingredients and potential targets remain unclear.

Purpose

The purpose of this study is to assess the potential ingredients and targets of RSYRD on SMF through a comprehensive strategy integrating network pharmacology, Mendelian randomization as well as molecular docking verification.

Methods

Search for potential active ingredients and corresponding protein targets of RSYRD on TCMSP and BATMAN-TCM for network pharmacology analysis. Mendelian randomization (MR) was performed to find therapeutic targets for SMF. The eQTLGen Consortium (sample sizes: 31,684) provided data on cis-expression quantitative trait loci (cis-eQTL, exposure). The summary data on SMF (outcome) from genome-wide association studies (GWAS) were gathered from the MRC-IEU Consortium (sample sizes: 463,010). We built a target interaction network between the probable active ingredient targets of RSYRD and the therapeutic targets of SMF. We next used drug prediction and molecular docking to confirm the therapeutic value of the therapeutic targets.

Results

In RSYRD, network pharmacology investigations revealed 193 possible active compounds and 234 associated protein targets. The genetically predicted amounts of 176 proteins were related to SMF risk in the MR analysis. Thirty-seven overlapping targets for RSYRD in treating SMF, among which six (NOS3, GAA, IMPA1, P4HTM, RB1, and SLC16A1) were prioritized with the most convincing evidence. Finally, the 14 active ingredients of RSYRD were identified as potential drug molecules. The strong affinity between active components and putative protein targets was established by molecular docking.

Conclusion

This study revealed several active components and possible RSYRD protein targets for the therapy of SMF and provided novel insights into the feasibility of using Mendelian randomization for causal inference between Chinese medical formula and disease.

Associations of lipids and lipid-modifying drug target genes with atrial fibrillation risk based on genomic data

BACKGROUND

The causal associations of lipids and the drug target genes with atrial fibrillation (AF) risk remain obscure. We aimed to investigate the causal associations using genetic evidence.

METHODS

Mendelian randomization (MR) analyses were conducted using summary-level genome-wide association studies (GWASs) in European and East Asian populations. Lipid profiles (low-density lipoprotein cholesterol, triglyceride, and lipoprotein[a]) and lipid-modifying drug target genes (3-hydroxy-3-methylglutaryl-CoA reductase, proprotein convertase subtilisin/kexin type 9, NPC1-like intracellular cholesterol transporter 1, apolipoprotein C3, angiopoietin-like 3, and lipoprotein[a]) were used as exposures. AF was used as an outcome. The inverse variance weighted method was applied as the primary method. Summary-data-based Mendelian randomization analyses were performed for further validation using expression quantitative trait loci data. Mediation analyses were conducted to explore the indirect effect of coronary heart disease.

RESULTS

In the European population, MR analyses demonstrated that elevated levels of lipoprotein(a) increased AF risk. Moreover, analyses focusing on drug targets revealed that the genetically proxied target gene LPA, which simulates the effects of drug intervention by reducing lipoprotein(a), exhibited an association with AF risk. This association was validated in independent datasets. There were no consistent and significant associations observed for other traits when analyzed in different datasets. This finding was also corroborated by Summary-data-based Mendelian randomization analyses between LPA and AF. Mediation analyses revealed that coronary heart disease plays a mediating role in this association. However, in the East Asian population, no statistically significant evidence was observed to support these associations.

CONCLUSIONS

This study provided genetic evidence that Lp(a) may be a causal factor for AF and that LPA may represent a promising pharmacological target for preventing AF in the European population.

Therapeutic targets for age-related macular degeneration: proteome-wide Mendelian randomization and colocalization analyses

Background

Currently, effective therapeutic drugs for age-related macular degeneration (AMD) are urgently needed, and it is crucial to explore new treatment targets. The proteome is indispensable for exploring disease targets, so we conducted a Mendelian randomization (MR) of the proteome to identify new targets for AMD and its related subtypes.

Methods

The plasma protein level data used in this study were obtained from two large-scale studies of protein quantitative trait loci (pQTL), comprising 35,559 and 54,219 samples, respectively. The expression quantitative trait loci (eQTL) data were sourced from eQTLGen and GTEx Version 8. The discovery set for AMD data and subtypes was derived from the FinnGen study, consisting of 9,721 AMD cases and 381,339 controls, 5,239 wet AMD cases and 273,920 controls, and 6,651 dry AMD cases and 272,504 controls. The replication set for AMD data was obtained from the study by Winkler TW et al., comprising 14,034 cases and 91,234 controls. Summary Mendelian randomization (SMR) analysis was employed to assess the association between QTL data and AMD and its subtypes, while colocalization analysis was performed to determine whether they share causal variants. Additionally, chemical exploration and molecular docking were utilized to validate potential drugs targeting the identified proteins.

Results

SMR and colocalization analysis jointly identified risk-associated proteins for AMD and its subtypes, including 5 proteins (WARS1, BRD2, IL20RB, TGFB1, TNFRSF10A) associated with AMD, 2 proteins (WARS1, IL20RB) associated with Dry-AMD, and 9 proteins (COL10A1, WARS1, VTN, SDF2, LBP, CD226, TGFB1, TNFRSF10A, CSF2) associated with Wet-AMD. The results revealed potential therapeutic chemicals, and molecular docking indicated a good binding between the chemicals and protein structures.

Conclusion

Proteome-wide MR have identified risk-associated proteins for AMD and its subtypes, suggesting that these proteins may serve as potential therapeutic targets worthy of further clinical investigation.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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 1 mg/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 1 mg/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).

CONCLUSION

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.

Genetic associations in ankylosing spondylitis: circulating proteins as drug targets and biomarkers

Background

Ankylosing spondylitis (AS) is a complex condition with a significant genetic component. This study explored circulating proteins as potential genetic drug targets or biomarkers to prevent AS, addressing the need for innovative and safe treatments.

Methods

We analyzed extensive data from protein quantitative trait loci (pQTLs) with up to 1,949 instrumental variables (IVs) and selected the top single-nucleotide polymorphism (SNP) associated with AS risk. Utilizing a two-sample Mendelian randomization (MR) approach, we assessed the causal relationships between identified proteins and AS risk. Colocalization analysis, functional enrichment, and construction of protein-protein interaction networks further supported these findings. We utilized phenome-wide MR (phenMR) analysis for broader validation and repurposing of drugs targeting these proteins. The Drug-Gene Interaction database (DGIdb) was employed to corroborate drug associations with potential therapeutic targets. Additionally, molecular docking (MD) techniques were applied to evaluate the interaction between target protein and four potential AS drugs identified from the DGIdb.

Results

Our analysis identified 1,654 plasma proteins linked to AS, with 868 up-regulated and 786 down-regulated. 18 proteins (AGER, AIF1, ATF6B, C4A, CFB, CLIC1, COL11A2, ERAP1, HLA-DQA2, HSPA1L, IL23R, LILRB3, MAPK14, MICA, MICB, MPIG6B, TNXB, and VARS1) that show promise as therapeutic targets for AS or biomarkers, especially MAPK14, supported by evidence of colocalization. PhenMR analysis linked these proteins to AS and other diseases, while DGIdb analysis identified potential drugs related to MAPK14. MD analysis indicated strong binding affinities between MAPK14 and four potential AS drugs, suggesting effective target-drug interactions.

Conclusion

This study underscores the utility of MR analysis in AS research for identifying biomarkers and therapeutic drug targets. The involvement of Th17 cell differentiation-related proteins in AS pathogenesis is particularly notable. Clinical validation and further investigation are essential for future applications.

Genetic variations in anti-diabetic drug targets and COPD risk: evidence from mendelian randomization

BACKGROUND

Previous research has emphasized the potential benefits of anti-diabetic medications in inhibiting the exacerbation of Chronic Obstructive Pulmonary Disease (COPD), yet the role of anti-diabetic drugs on COPD risk remains uncertain.

METHODS

This study employed a Mendelian randomization (MR) approach to evaluate the causal association of genetic variations related to six classes of anti-diabetic drug targets with COPD. The primary outcome for COPD was obtained from the Global Biobank Meta-analysis Initiative (GBMI) consortium, encompassing a meta-analysis of 12 cohorts with 81,568 cases and 1,310,798 controls. Summary-level data for HbA1c was derived from the UK Biobank, involving 344,182 individuals. Positive control analysis was conducted for Type 2 Diabetes Mellitus (T2DM) to validate the choice of instrumental variables. The study applied Summary-data-based MR (SMR) and two-sample MR for effect estimation and further adopted colocalization analysis to verify evidence of genetic variations.

RESULTS

SMR analysis revealed that elevated KCNJ11 gene expression levels in blood correlated with reduced COPD risk (OR = 0.87, 95% CI = 0.79-0.95; p = 0.002), whereas an increase in DPP4 expression corresponded with an increased COPD incidence (OR = 1.18, 95% CI = 1.03-1.35; p = 0.022). Additionally, the primary method within MR analysis demonstrated a positive correlation between PPARG-mediated HbA1c and both FEV1 (OR = 1.07, 95% CI = 1.02-1.13; P = 0.013) and FEV1/FVC (OR = 1.08, 95% CI = 1.01-1.14; P = 0.007), and a negative association between SLC5A2-mediated HbA1c and FEV1/FVC (OR = 0.86, 95% CI = 0.74-1.00; P = 0.045). No colocalization evidence with outcome phenotypes was detected (all PP.H4 < 0.7).

CONCLUSION

This study provides suggestive evidence for anti-diabetic medications' role in improving COPD and lung function. Further updated MR analyses are warranted in the future, following the acquisition of more extensive and comprehensive data, to validate our results.

Association of intestinal anti-inflammatory drug target genes with psychiatric Disorders: A Mendelian randomization study

INTRODUCTION

Psychiatric disorders present a substantial global public health burden with limited drug options. The gut-brain axis connects inflammatory bowel diseases and psychiatric disorders, which often have comorbidities. While some evidence hints at anti-inflammatory drugs aiding in treating psychiatric conditions, the specific effects of intestinal anti-inflammatory drugs remain unclear.

OBJECTIVES

This study investigates the causal effect of intestinal anti-inflammatory drug targets on psychiatric disorders. We hypothesize that these drug targets may offer new insights into the treatment and prevention of such disorders. Additionally, we explore gut microbiota's mediating role between drug target genes and psychiatric disorders.

METHODS

We performed two-sample Mendelian randomization (MR) using summary data from existing expression quantitative trait loci (eQTL) and protein QTL in the brain, along with public genome-wide association studies of disease. We also explored gut microbiota's mediating effect. The statistics encompassed six psychiatric disorders involving 9,725-500,199 individuals. Colocalization analysis enhanced the MR evidence.

RESULTS

We uncovered a causal link between TPMT (a target of olsalazine) expression in the amygdala and bipolar disorder (BD) risk (odds ratio [OR] = 1.08; P = 4.29 × 10-4). This association was observed even when the sigmoid colon and whole blood eQTL were considered as exposures. Colocalization analysis revealed a shared genetic variant (rs11751561) between TPMT expression and BD, with a posterior probability of 61.6 %. Interestingly, this causal effect was influenced by a decrease in the gut microbiota abundance of the genus Roseburia (effect proportion = 10.05 %). Moreover, elevated ACAT1 expression was associated with higher obsessive-compulsive disorder risk (OR = 1.62; P = 3.64 × 10-4; posterior probability = 3.1 %).

CONCLUSION

These findings provide novel targets for the treatment of psychiatric disorders, underscore the potential of repurposing olsalazine, and emphasize the importance of TPMT and ACAT1 in future drug development.

Gut microbial features may influence antiviral IgG levels after vaccination against viral respiratory infectious diseases: the evidence from two-sample bidirectional mendelian randomization

BACKGROUND

Vaccination is effective in preventing viral respiratory infectious diseases through protective antibodies and the gut microbiome has been proven to regulate human immunity. This study explores the causal correlations between gut microbial features and serum-specific antiviral immunoglobulin G (IgG) levels.

METHODS

We conduct a two-sample bidirectional Mendelian randomization (MR) analysis using genome-wide association study (GWAS) summary data to explore the causal relationships between 412 gut microbial features and four antiviral IgG (for influenza A, measles, rubella, and mumps) levels. To make the results more reliable, we used four robust methods and performed comprehensive sensitivity analyses.

RESULTS

The MR analyses revealed 26, 13, 20, and 18 causal associations of the gut microbial features influencing four IgG levels separately. ​Interestingly, ten microbial features, like genus Collinsella, species Bifidobacterium longum, and the biosynthesis of L-alanine have shown the capacity to regulate multiple IgG levels with consistent direction (rise or fall). The ​reverse MR analysis suggested several potential causal associations of IgG levels affecting microbial features.

CONCLUSIONS

The human immune response against viral respiratory infectious diseases could be modulated by changing the abundance of gut microbes, which provided new approaches for the intervention of viral respiratory infections.

Association between genetically proxied lipid-lowering drug targets, lipid traits, and amyotrophic lateral sclerosis: a mendelian randomization study

BACKGROUND

The use of circulating lipid traits as biomarkers to predict the risk of amyotrophic lateral sclerosis (ALS) is currently controversial, and the evidence-based medical evidence for the use of lipid-lowering agents, especially statins, on ALS risk remains insufficient. Our aim was to apply a Mendelian randomization (MR) approach to assess the causal impact of lipid-lowering agents and circulating lipid traits on ALS risk.

MATERIALS AND METHODS

Our study included primary and secondary analyses, in which the risk associations of lipid-lowering gene inhibitors, lipid traits, and ALS were assessed by the inverse variance weighting method as the primary approach. The robustness of the results was assessed using LDSC assessment, conventional MR sensitivity analysis, and used Mediating MR to explore potential mechanisms of occurrence. In the secondary analysis, the association of lipid-lowering genes with ALS was validated using the Summary data-based Mendelian Randomization (SMR) method.

RESULTS

Our results showed strong evidence between genetic proxies for Apolipoprotein B (ApoB) inhibitor (OR = 0.76, 95% CI = 0.68 - 0.86; P = 5.58 × 10-6) and reduced risk of ALS. Additionally, 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibitor (OR = 1.06, 95% CI = 0. 85-1.33) was not found to increase ALS risk. SMR results suggested that ApoB expression was associated with increased ALS risk, and colocalization analysis did not support a significant common genetic variation between ApoB and ALS. Mediator MR analysis suggested a possible mediating role for interleukin-6 and low-density lipoprotein cholesterol (LDL-C). While elevated LDL-C was significantly associated with increased risk of ALS among lipid traits, total cholesterol (TC) and ApoB were weakly associated with ALS. LDSC results suggested a potential genetic correlation between these lipid traits and ALS.

CONCLUSIONS

Using ApoB inhibitor can lower the risk of ALS, statins do not trigger ALS, and LDL-C, TC, and ApoB levels can predict the risk of ALS.

Association of Antipsychotic Drugs with Venous Thromboembolism: Data Mining of Food and Drug Administration Adverse Event Reporting System and Mendelian Randomization Analysis

AIMS

Past observational studies have reported on the association between antipsychotic drugs and venous thromboembolism (VTE); however, the conclusions remain controversial, and its mechanisms are yet to be fully understood. Thus, in this study, we aim to determine the associations of antipsychotic drugs with VTE, including deep vein thrombosis (DVT) and pulmonary embolism (PE), and their potential mechanisms.

METHODS

We first mined the adverse event signals of VTE, DVT, and PE caused by antipsychotic drugs in Food and Drug Administration Adverse Event Reporting System (FAERS). Next, we used two-sample Mendelian randomization (MR) method to investigate the association of antipsychotic drug target gene expression with VTE, DVT, and PE, using single-nucleotide polymorphisms as genetic instruments. We not only used the expression of all antipsychotic drug target genes as exposure to perform MR analyses but also analyzed the effect of single target gene expression on the outcomes.

RESULTS

In the FAERS, 1694 cases of VTE events were reported by 16 drugs. However, using the MR approach, no significant association was determined between the expression of all antipsychotic target genes and VTE, DVT, or PE, either in blood or brain tissue. Although the analysis of single gene expression data showed that the expression of nine genes was associated with VTE events, these targets lacked significant pharmacological action.

CONCLUSIONS

Adverse event mining results have supported the claim that antipsychotic drugs can increase the risk of VTE. However, we failed to find any genetic evidence for this causal association and potential mechanisms. Thus, vigilance is still needed for antipsychotic drug-related VTE despite the limited supporting evidence.

Drug Target Mendelian Randomization Study of PCSK9 and HMG-CoA Reductase Inhibition and Atrial Fibrillation

INTRODUCTION

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia with significant clinical implications. The potential influence of lipid-lowering therapies, specifically PCSK9 inhibitors (PCSK9i) and HMG-CoA reductase inhibitors (statins), on AF risk remains a topic of interest. This mendelian randomization (MR) study aimed to elucidate the causal relationship between genetically predicted inhibition of PCSK9 and HMG-CoA reductase and the risk of AF.

METHODS

Utilizing publicly available, summary-level genome-wide association study data, we employed single-nucleotide polymorphisms associated with lower LDL-C levels as instruments for gene-simulated inhibition of PCSK9 and HMG-CoA reductase. Multiple MR techniques were applied to estimate the causal effects, and sensitivity analyses were conducted to validate the results.

RESULTS

Genetically predicted inhibition of PCSK9 demonstrated a reduced risk of AF, with an odds ratio (OR) of 0.92 (95% CI: 0.85-0.99, p = 0.01) using the inverse variance-weighted (IVW) method. In contrast, the inhibition of HMG-CoA reductase did not exhibit a statistically significant association with AF risk (IVW: OR = 1.11, 95% CI: 1.00-1.22, p = 0.05).

CONCLUSION

Our MR study suggests that genetically predicted inhibition of PCSK9, but not HMG-CoA reductase, is associated with a lower risk of AF. These findings provide evidence for a causal protective effect of PCSK9i on AF and support the use of PCSK9i for AF prevention in patients with dyslipidemia. Further studies are needed to elucidate the mechanisms underlying the differential effects of PCSK9i and statins on AF and to confirm the clinical implications of our findings.

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

BACKGROUND

Diabetic 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.

METHODS

The 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.

RESULTS

Based 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).

CONCLUSIONS

This 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.

Association of glucose-lowering drug target and risk of gastrointestinal cancer: a mendelian randomization study

BACKGROUND & AIMS

Glucose-lowering drug is associated with various cancers, but the causality with gastrointestinal cancer risk is rarely reported. We aimed to explore the causality between them in this Mendelian randomization (MR) study.

METHODS

Two-sample MR, summary-data-based (SMR), mediation MR, and colocalization analyses was employed. Ten glucose-lowering drug targets (PPARG, DPP4, GLP1R, INSR, SLC5A2, ABCC8, KCNJ11, ETFDH, GPD2, PRKAB1) and seven types of gastrointestinal cancer (anal carcinoma, cardia cancer, gastric cancer, hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), pancreatic cancer, rectum cancer) were included. Patients with gastrointestinal cancers from six different large GWAS databases, including the UK Biobank and Finnish cohorts were incorporated, for discovery and external validation. Meta-analysis was employed to integrate the results from both discovery and validation cohorts, thereby ensuring the reliability of findings.

RESULTS

ABCC8/KCNJ11 were associated with pancreatic cancer risk in both two-sample MR (odds ratio (OR): 15.058, per standard deviation unit (SD) change of glucose-lowering durg target perturbation equivalent to 1 SD unit of HbA1c lowering; 95% confidence interval (95% CI): 3.824-59.295; P-value = 0.0001) and SMR (OR: 1.142; 95% CI: 1.013-1.287; P-value = 0.030) analyses. The mediation effect of body mass index (OR: 0.938; 95% CI: 0.884-0.995; proportion of mediation effect: 3.001%; P-value = 0.033) on ABCC8/KCNJ11 and pancreatic cancer was uncovered. Strong connections of DPP4 with anal carcinoma (OR: 0.123; 95% CI: 0.020-0.745; P-value = 0.023) and ICC (OR: 7.733; 95% CI: 1.743-34.310; P-value = 0.007) were detected. PPARG was associated with anal carcinoma (OR: 12.909; 95% CI: 3.217-51.795; P-value = 0.0003), HCC (OR: 36.507; 95% CI: 8.929-149.259; P-value < 0.0001), and pancreatic cancer (OR: 0.110; 95% CI: 0.071-0.172; P-value < 0.0001). SLC5A2 was connected with pancreatic cancer (OR: 8.096; 95% CI: 3.476-18.857; P-value < 0.0001). Weak evidence indicated the connections of GLP1R, GPD2, and PRKAB1 with anal carcinoma, cardia cancer, ICC, and rectum cancer. In addition, the corresponding results were consistently validated in both the validation cohorts and the integrated outcomes.

CONCLUSIONS

Some glucose-lowering drugs were associated with gastrointestinal cancer risk, which might provide new ideas for gastrointestinal cancer treatment.

Causal effects of various types of physical activities on psychiatric disorders: a Mendelian randomization study

Background

Psychiatric disorders (PD) pose a significant burden, with vast prevalence and mortality, inflicting substantial costs on individuals and society. Despite its widespread prevalence, the complex pathogenesis of PD remains elusive, leading to limited and challenging therapeutic development. An emerging risk factor for chronic diseases, prolonged sedentary behavior, contrasts with the therapeutic potential of exercise, regardless of its intensity, for various ailments, including PD. Yet, the diversity in exercise modalities and intensities may offer varied impacts on health. This study, leveraging Mendelian Randomization (MR), seeks to investigate the causal relationship between exercise and PD, aiming to elucidate the optimal exercise modality and intensity for PD mitigation while addressing potential confounders.

Methods

This study employed a Mendelian randomization analysis using the genome-wide association study (GWAS) database to investigate the causal relationship between types of physical activity and psychiatric disorders. Sensitivity analysis was conducted to demonstrate the reliability and robustness of the results.

Results

In the past 4 weeks, engaging in a substantial amount of DIY physical activity was found to have a causal relationship with psychiatric disorders (IVW: OR = 0.228, 95% CI: 0.113-0.461, P = 0.000038). As for the types of exercises, there may be a potential causal association between aerobic training (including swimming, cycling, fitness, and bowling) and psychiatric disorders (IVW: OR = 0.322, 95% CI = 0.148-0.704, P = 0.004). However, there was no causal relationship found between mild DIY physical activity and psychiatric disorders (IVW: OR = 0.918, 95% CI = 0.417-2.021, P = 0.831). Furthermore, it seems that there is no causal relationship between vigorous exercise and psychiatric disorders (IVW: OR = 2.705, 95% CI = 0.081-3.419, P = 0.578).

Conclusion

Our study confirms that only a certain level of training activity can have a protective effect on psychiatric disorders, while mild physical activity or vigorous training does not have an impact on psychiatric disorders.

Association evaluations of oral anticoagulants with dementia risk based on genomic and real-world data

BACKGROUND

Several observational studies have suggested that oral anticoagulants (OACs) might reduce the risk of dementia in the elderly, but the evidence is inconclusive. And the consistency of this relationship across different OAC classes and dementia subtypes is still uncertain.

METHODS

To comprehensively evaluate this association, we applied Mendelian randomization (MR) combined with pharmacovigilance analysis. MR was used to assess the associations between genetic proxies for three target genes of OACs (VKORC1, F2, and F10) and dementia, including Alzheimer's disease (AD) and vascular dementia (VaD). This genetic analysis was supplemented with real-world pharmacovigilance data, employing disproportionality analysis for more reliable causal inference.

RESULTS

Increased expression of the VKORC1 gene was strongly associated with increased risk of dementia, especially for AD (OR = 1.28, 95% CI = 1.14-1.43; p value < 0.001). Based on pharmacovigilance data, vitamin K antagonists (VKAs, inhibitors targeting VKORC1) exhibited a protective effect against dementia risk (ROR = 0.43, 95% CI = 0.28-0.67). Additional sensitivity analyses, including different MR models and cohorts, supported these results. Conversely, no strong causal associations of genetically proxied F2 and F10 target genes with dementia and its subtypes were found.

CONCLUSIONS

This study reveals that the inhibition of genetically proxied VKORC1 expression or VKAs exposure is associated with a reduced risk of Alzheimer's dementia. However, there is little evidence to support similar associations with direct oral anticoagulants (F2 inhibitors and F10 inhibitors). Further research is warranted to clinically validate our findings.

Genetically proxied therapeutic inhibition of lipid-lowering drug targets and risk of rheumatoid arthritis disease: a Mendelian randomization study

OBJECTIVE

To evaluate the potential impact of consistent use of similar treatments over a long period; it is essential to investigate the potential correlation between genetic variations that influence the expression or function of pharmacological targets for reducing lipid levels and the risk of developing rheumatoid arthritis.

METHODS

We used variants in the following genes to conduct Mendelian randomization analyses: HMGCR (encoding the target for statins), PCSK9 (encoding the target for PCSK9 inhibitors, such as evolocumab and alirocumab), and NPC1L1 (encoding the target for ezetimibe). Data from lipid genetics consortia (173,082 sample size) were used to weight variations according to their correlations with low-density lipoprotein cholesterol (LDL-C). In two large datasets (total n = 19,562 cases, 501,655 controls). We conducted a meta-analysis of Mendelian randomization estimates, weighted by LDL-C levels, on the regional differences in the risk of rheumatoid arthritis using data from two large databases.

RESULTS

We approached SMR and IVW-MR analyses to examine the relationship between target gene expression (including HMGCR, PCSK9, and NPC1L1) and LDL-C levels mediated by these genes with RA. The IVW-MR analysis revealed no significant association between genetically predicted LDL-C concentration and the risk of RA (OR = 0.88, 95% CI = 0.59-1.29; OR = 0.91, 95% CI = 0.67-1.23; OR = 0.81, 95% CI = 0.49-1.36; all p > 0.05). Similarly, our findings from the SMR approach provided no evidence to suggest that gene expression of HMGCR, PCSK9, and NPC1L1 was associated with the risk of RA (OR = 0.91, 95% CI = 0.79-1.05, p = 0.207; OR = 0.96, 95% CI = 0.85-1.09, p = 0.493).

CONCLUSIONS

Our results do not provide evidence to support the hypothesis that reducing LDL-C levels with statins, alirocumab, or ezetimibe effectively prevents the risk of developing RA. However, our study provides valuable insights into the assessment of lipid-lowering agents in RA, which can enhance our understanding of the condition and assist in clinical practice by aiding in the determination and monitoring of RA status to clinical response.

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

Background

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.

Objective

To investigate the potential of antidiabetic drugs on IBD.

Methods

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.

Results

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.

Conclusion

Sulfonylureas (SUs) may have side effects on CD. This work provides some suggestions for the selection of antidiabetic drugs in patients with CD.

Can Lipid-Lowering Drugs Reduce the Risk of Cholelithiasis? A Mendelian Randomization Study

Background and Aims

Cholelithiasis etiology intricately involves lipid metabolism. We sought to investigate the plausible causal link between genetically proxied lipid-lowering medications-specifically HMGCR inhibitors, PCSK9 inhibitors, and NPC1L1 inhibitors-and cholelithiasis risk.

Methods

Our study utilized two genetic instruments for exposure to lipid-lowering drugs. These instruments encompassed genetic variants linked to low-density lipoprotein (LDL) cholesterol within or in proximity to drug target genes, along with loci governing gene expression traits of these targets. Effect estimates were derived through Inverse-variance-weighted MR (IVW-MR) and summary-data-based MR (SMR) methods.

Results

Higher HMGCR-mediated LDL cholesterol levels (IVW-MR, OR = 2.15, 95% CI = 1.58-2.94; P = 0.000) and increased HMGCR expression (SMR, OR = 1.19, 95% CI = 1.04-1.37; P = 0.014) are linked to elevated cholelithiasis risk, suggesting potential benefits of HMGCR inhibition. In contrast, higher PCSK9-mediated LDL cholesterol levels (IVW-MR, OR = 0.72, 95% CI = 0.56-0.94; P = 0.015) and increased PCSK9 expression (SMR, OR = 0.90, 95% CI = 0.82-0.99; P = 0.035) both correlate with lower cholelithiasis risk, indicating that PCSK9 inhibition may elevate this risk. Nevertheless, no substantial link emerged between NPC1L1-mediated LDL cholesterol or NPC1L1 expression and cholelithiasis in both IVW-MR and SMR analyses.

Conclusion

This MR investigation affirms the causal link between the utilization of HMGCR inhibitors and a diminished risk of cholelithiasis. Additionally, it indicates a causal link between PCSK9 inhibitors use and increased cholelithiasis risk. However, no significant correlation was found between NPC1L1 inhibitors use and cholelithiasis risk.

Comparative estimation of the effects of antihypertensive medications on schizophrenia occurrence: a multinational observational cohort study

BACKGROUND

The association between antihypertensive medication and schizophrenia has received increasing attention; however, evidence of the impact of antihypertensive medication on subsequent schizophrenia based on large-scale observational studies is limited. We aimed to compare the schizophrenia risk in large claims-based US and Korea cohort of patients with hypertension using angiotensin-converting enzyme (ACE) inhibitors versus those using angiotensin receptor blockers (ARBs) or thiazide diuretics.

METHODS

Adults aged 18 years who were newly diagnosed with hypertension and received ACE inhibitors, ARBs, or thiazide diuretics as first-line antihypertensive medications were included. The study population was sub-grouped based on age (> 45 years). The comparison groups were matched using a large-scale propensity score (PS)-matching algorithm. The primary endpoint was incidence of schizophrenia.

RESULTS

5,907,522; 2,923,423; and 1,971,549 patients used ACE inhibitors, ARBs, and thiazide diuretics, respectively. After PS matching, the risk of schizophrenia was not significantly different among the groups (ACE inhibitor vs. ARB: summary hazard ratio [HR] 1.15 [95% confidence interval, CI, 0.99-1.33]; ACE inhibitor vs. thiazide diuretics: summary HR 0.91 [95% CI, 0.78-1.07]). In the older subgroup, there was no significant difference between ACE inhibitors and thiazide diuretics (summary HR, 0.91 [95% CI, 0.71-1.16]). The risk for schizophrenia was significantly higher in the ACE inhibitor group than in the ARB group (summary HR, 1.23 [95% CI, 1.05-1.43]).

CONCLUSIONS

The risk of schizophrenia was not significantly different between the ACE inhibitor vs. ARB and ACE inhibitor vs. thiazide diuretic groups. Further investigations are needed to determine the risk of schizophrenia associated with antihypertensive drugs, especially in people aged > 45 years.

Genetic variation in targets of lipid-lowering drugs and amyotrophic lateral sclerosis risk: a Mendelian randomization study

BACKGROUND

The use of lipid-lowering drugs is still highly controversial in patients with amyotrophic lateral sclerosis (ALS). We performed a drug-target Mendelian randomization (MR) analysis to investigate the effect of targeted lipid-lowering drugs on the risk of ALS.

METHODS

First, we evaluated the causal relationship between HMG-CoA (3-hydroxy-3-methylglutaryl coenzyme A) reductase (HMGCR) inhibitors-taking trait and ALS using a bidirectional two-sample MR study. Second, we investigated the causal relationship between lipid-lowering drugs and ALS through a drug-target MR approach. The summary data for HMGCR inhibitors-taking traits were extracted from a genome-wide association study (GWAS) of medication use and associated disease in the UK Biobank. The summary data for low-density lipoprotein cholesterol and apolipoprotein B (apoB) were extracted from a meta-analysis of GWAS in individuals of European ancestry in the UKB. The GWAS summary data of ALS were obtained from the Project MinE.

RESULTS

Our bidirectional two-sample MR showed that genetically determined increased HMGCR inhibitors-taking trait was an independent risk factor for ALS (odds ratio [OR] = 1.090, 95% confidence interval [CI] = 1.035-1.150, p = 0.001). The results of drug-target MR showed that the increased expression of the HMGCR gene in blood with the higher risk of ALS (OR = 1.21, 95% CI = 1.01-1.46; p = 0.042) through SMR method and the apoB level mediated by the APOB gene increased the risk of ALS (OR = 1.15; 95% CI =1.05-1.25; p = 0.001) through inverse-variance weighted MR method.

CONCLUSION

This present study provides genetic support for a positive causal effect of HMGCR inhibitors-taking trait and ALS. The reason for this may be due to the underlying disease condition behind the medication, rather than the medication itself. Our findings also suggested that HMGCR and apoB inhibitors may have potential protective effects on ALS.

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

BACKGROUND

Circadian 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.

METHODS

Summary 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).

RESULTS

Through 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.

CONCLUSIONS

This 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.

Large-Scale Mendelian Randomization Study Reveals Circulating Blood-based Proteomic Biomarkers for Psychopathology and Cognitive Task Performance

Background

Research on peripheral (e.g., blood-based) biomarkers for psychiatric illness has typically been low-throughput in terms of both the number of subjects and the range of assays performed. Moreover, traditional case-control studies examining blood-based biomarkers are subject to potential confounds of treatment and other exposures common to patients with psychiatric illnesses. Our research addresses these challenges by leveraging large-scale, high-throughput proteomics data and Mendelian Randomization (MR) to examine the causal impact of circulating proteins on psychiatric phenotypes and cognitive task performance.

Methods

We utilized plasma proteomics data from the UK Biobank (3,072 proteins assayed in 34,557 European-ancestry individuals) and deCODE Genetics (4,719 proteins measured across 35,559 Icelandic individuals). Significant proteomic quantitative trait loci (both cis-pQTLs and trans-pQTLs) served as MR instruments, with the most recent GWAS for schizophrenia, bipolar disorder, major depressive disorder, and cognitive task performance (all excluding overlapping UK Biobank participants) as phenotypic outcomes.

Results

MR revealed 109 Bonferroni-corrected causal associations (44 novel) involving 88 proteins across the four phenotypes. Several immune-related proteins, including interleukins and complement factors, stood out as pleiotropic across multiple outcome phenotypes. Drug target enrichment analysis identified several novel potential pharmacologic repurposing opportunities, including anti-inflammatory agents for schizophrenia and bipolar disorder and duloxetine for cognitive performance.

Conclusions

Identification of causal effects for these circulating proteins suggests potential biomarkers for these conditions and offers insights for developing innovative therapeutic strategies. The findings also indicate substantial evidence for the pleiotropic effects of many proteins across different phenotypes, shedding light on the shared etiology among psychiatric conditions and cognitive ability.

Lipid-lowering drugs and inflammatory bowel disease's risk: a drug-target Mendelian randomization study

BACKGROUND

Inflammatory bowel disease (IBD) has been associated with lipid-lowering drugs in observational studies. Drug-target Mendelian randomization (MR) was utilized in this study to examine the causal relationship between lipid-lowering drugs and incidence of IBD, aiming to identify new preventive uses for the drugs.

METHODS

We identified instrumental variables for three classes of lipid-lowering drugs: HMGCR inhibitors, PCSK9 inhibitors, and NPC1L1 inhibitors, using data from the Global Lipids Genetics Consortium. Summary statistics of IBD were obtained from UK Inflammatory Bowel Disease Genetics. The summary-data-based MR (SMR) and the inverse-variance weighted (IVW) MR were used for analysis. Sensitivity analyses were performed by conventional MR methods.

RESULTS

The SMR analysis showed no significant genetic association between increased gene expression of HMGCR, PCSK9, and NPC1L1 and IBD, Crohn's disease (CD) and ulcerative colitis (UC). According to IVW-MR analysis, increased HMGCR expression is associated with a reduced risk of IBD (OR = 0.73, 95% confidence interval (CI) 0.59-0.90, P = 0.003) and CD (OR = 0.75, 95% CI 0.57-0.97, P = 0.03), but not with UC. Additionally, increased NPC1L1 gene expression was associated with elevated risk of IBD (OR = 1.60, 95% CI 1.07-2.40, P = 0.023), but not with CD and UC. However, no significant causal relationships were found between PCSK9 gene expression and IBD, CD, and UC. The sensitivity analysis demonstrated no evidence of heterogeneity or pleiotropy among the reported results.

CONCLUSIONS

The heightened expression of genetic variations in HMGCR inhibitor targets could potentially reduce the risk of IBD and CD, while genetic variation in the expression of NPC1L1 targets was positively associated with IBD.

New perspectives on the potential of tetrandrine in the treatment of non-small cell lung cancer: bioinformatics, Mendelian randomization study and experimental investigation

BACKGROUND

Although there are numerous treatment methods for NSCLC, long-term survival remains a challenge for patients. The objective of this study is to investigate the role and causal relationship between the target of tetrandrine and non-small cell lung cancer (NSCLC) through transcriptome and single-cell sequencing data, summary-data-based Mendelian Randomization (SMR) and basic experiments. The aim is to provide a new perspective for the treatment of NSCLC.

METHODS

We obtained the drug target gene of tetrandrine through the drug database, and then used the GSE19188 data set to obtain the NSCLC pathogenic gene, established a drug-disease gene interaction network, screened out the hub drug-disease gene, and performed bioinformatics and tumor cell immune infiltration analysis. Single-cell sequencing data (GSE148071) to determine gene location, SMR to clarify causality and drug experiment verification.

RESULTS

10 drug-disease genes were obtained from 213 drug targets and 529 disease genes. DO/GO/KEGG analysis showed that the above genes were all related to the progression and invasion of NSCLC. Four drug-disease genes were identified from a drug-disease PPI network. These four genes were highly expressed in tumors and positively correlated with plasma cells, T cells, and macrophages. Subsequent single-cell sequencing data confirmed that these four genes were distributed in epithelial cells, and SMR analysis revealed the causal relationship between CCNA2 and CCNB1 and the development of NSCLC. The final molecular docking and drug experiments showed that CCNA2 and CCNB1 are key targets for tetrandrine in the treatment of NSCLC.

Genetic prediction of antihyperglycemic drug targets and risk of epilepsy: a mendelian randomisation study

A connection between diabetes and an increased risk of epilepsy has been suggested by observational studies. Animal studies have also shown that antihyperglycemic drugs can improve seizures. However, it is unclear whether antihyperglycemic drugs have a causal role in epilepsy in humans. To investigate this potential causal relationship, a Mendelian randomisation study was conducted using International League Against Epilepsy data as the discovery set and FinnGen data as the replication set. It was discovered that three antidiabetic drug target genes, ETFDH, CYP21A2 and CYP2D6, were involved in the occurrence of epilepsy. In particular, ETFDH was identified as a target gene in both the discovery set (inverse variance weighting [IVW], odds ratio [OR] = 1.018, 95% confidence interval [CI], 1.004-1.033, p = 0.009) and replication set (IVW, OR = 1.074, 95% CI, 1.034-1.114, p = 0.00016), and CYP21A2 was identified in the discovery set (IVW, OR = 1.029, 95% CI, 1.005-1.053, p = 0.016) and replication set (IVW, OR = 1.057, 95% CI, 1.001-1.116, p = 0.045) as having a causal association with an increased risk of epilepsy. Conversely, the CYP2D6 gene was found to be a protective factor for epilepsy in both the discovery set (IVW, OR = 0.0984, 95% CI, 0.969-0.998, p = 0.025) and replication set (IVW, OR = 0.977, 95% CI, 0.955-1.000, p = 0.046). A search of DrugBank revealed that metformin, an anti-glucose drug, is an inhibitor of the ETFDH gene and may have a potential therapeutic effect on epilepsy.

Genetic proxies for antihypertensive drugs and mental disorders: Mendelian randomization study in European and East Asian populations

BACKGROUND

Mental disorders are among the top causes of disease burden worldwide. Existing evidence regarding the repurposing of antihypertensives for mental disorders treatment is conflicting and cannot establish causation.

METHODS

We used Mendelian randomization to assess the effects of angiotensin-converting-enzyme inhibitors (ACEIs), beta blockers (BBs), and calcium channel blockers (CCBs) on risk of bipolar disorder (BD), major depression disorder (MDD), and schizophrenia (SCZ). We used published genetic variants which are in antihypertensive drugs target genes and correspond to systolic blood pressure (SBP) in Europeans and East Asians, and applied them to summary statistics of BD (cases = 41,917; controls = 371,549 in Europeans), MDD (cases = 170,756; controls = 329,443 in Europeans and cases = 15,771; controls = 178,777 in East Asians), and SCZ (cases = 53,386; controls = 77,258 in Europeans and cases = 22,778; controls = 35,362 in East Asians) from the Psychiatric Genomics Consortium. We used inverse variance weighting with MR-Egger, weighted median, weighted mode, and Mendelian Randomization Pleiotropy RESidual Sum and Outlier. We performed gene-specific analysis and utilized various methods to address potential pleiotropy.

RESULTS

After multiple testing correction, genetically proxied ACEIs were associated with an increased risk of SCZ in Europeans (odds ratio (OR) per 5 mmHg lower in SBP 2.10, 95% CI 1.54 to 2.87) and East Asians (OR per 5 mmHg lower in SBP 2.51, 95% CI 1.38 to 4.58). Genetically proxied BBs were not associated with any mental disorders in both populations. Genetically proxied CCBs showed no benefits on mental disorders.

CONCLUSIONS

Antihypertensive drugs have no protection for mental disorders but potential harm. Their long-term use among hypertensive patients with, or with high susceptibility to, psychiatric illness needs careful evaluation.

Targeting the Renin-Angiotensin System (RAS) for Neuropsychiatric Disorders

BACKGROUND

Neuropsychiatric disorders, such as mood disorders, schizophrenia, and Alzheimer's disease (AD) and related dementias, are associated to significant morbidity and mortality worldwide. The pathophysiological mechanisms of neuropsychiatric disorders remain to be fully elucidated, which has hampered the development of effective therapies. The Renin Angiotensin System (RAS) is classically viewed as a key regulator of cardiovascular and renal homeostasis. The discovery that RAS components are expressed in the brain pointed out a potential role for this system in central nervous system (CNS) pathologies. The understanding of RAS involvement in the pathogenesis of neuropsychiatric disorders may contribute to identifying novel therapeutic targets.

AIMS

We aim to report current experimental and clinical evidence on the role of RAS in physiology and pathophysiology of mood disorders, schizophrenia, AD and related dementias. We also aim to discuss bottlenecks and future perspectives that can foster the development of new related therapeutic strategies.

CONCLUSION

The available evidence supports positive therapeutic effects for neuropsychiatric disorders with the inhibition/antagonism of the ACE/Ang II/AT1 receptor axis or the activation of the ACE2/Ang-(1-7)/Mas receptor axis. Most of this evidence comes from pre-clinical studies and clinical studies lag much behind, hampering a potential translation into clinical practice.

Potential drug targets for myocardial infarction identified through Mendelian randomization analysis and Genetic colocalization

Myocardial infarction (MI) is a major cause of death and disability worldwide, but current treatments are limited by their invasiveness, side effects, and lack of efficacy. Novel drug targets for MI prevention are urgently needed. In this study, we used Mendelian randomization to identify potential therapeutic targets for MI using plasma protein quantitative trait loci as exposure variables and MI as the outcome variable. We further validated our findings using reverse causation analysis, Bayesian co-localization analysis, and external datasets. We also constructed a protein-protein interaction network to explore the relationships between the identified proteins and known MI targets. Our analysis revealed 2 proteins, LPA and APOA5, as potential drug targets for MI, with causal effects on MI risk confirmed by multiple lines of evidence. LPA and APOA5 are involved in lipid metabolism and interact with target proteins of current MI medications. We also found 4 other proteins, IL1RN, FN1, NT5C, and SEMA3C, that may have potential as drug targets but require further confirmation. Our study demonstrates the utility of Mendelian randomization and protein quantitative trait loci in discovering novel drug targets for complex diseases such as MI. It provides insights into the underlying mechanisms of MI pathology and treatment.

Association of HMGCR inhibition with rheumatoid arthritis: a Mendelian randomization and colocalization study

Objective

The objective of this study was to investigate the association between hydroxymethylglutaryl coenzyme A reductase (HMGCR) inhibition and rheumatoid arthritis (RA) using drug-target Mendelian randomization (MR) and genetic colocalization analyses.

Methods

Two sets of genetic instruments were employed to proxy HMGCR inhibitors: expression quantitative trait loci (eQTLs) of target genes from the eQTLGen Consortium and genetic variants associated with low-density lipoprotein cholesterol (LDL-C) levels with HMGCR locus from open genome-wide association studies (GWAS). Positive control analyses were conducted on type 2 diabetes and coronary heart disease, and multiple sensitivity analyses were performed.

Results

Genetically proxied expression of eQTL was associated with a lower risk of RA (OR=0.996, 95% CI =0.992-0.999, p= 0.032). Similarly, hydroxymethylglutaryl coenzyme A reductase (HMGCR)-mediated low-density lipoprotein cholesterol was negatively associated with risk of RA (OR=0.995, 95% CI =0.991-0.998, p= 0.007) in the inverse variance weighted (IVW) method. Colocalization analysis suggested a 74.6% posterior probability of sharing a causal variant within the SNPs locus (PH4 = 74.6%). A causal relationship also existed between HMGCR-mediated LDL and RA risk factors. The results were also confirmed by multiple sensitivity analyses. The results in positive control were consistent with the previous study.

Conclusion

Our study suggested that HMGCR inhibition was associated with an increased risk of RA while also highlighting an increased risk of current smoking and obesity. These findings contribute to a growing body of evidence regarding the adverse effects of HMGCR inhibition on RA risk, calling for further research on alternative approaches using HMGCR inhibitors in RA management.