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

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.

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.

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.

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.

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.

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.

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.

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 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.

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.

Lipid-lowering drugs affect lung cancer risk via sphingolipid metabolism: a drug-target Mendelian randomization study

Background: The causal relationship between lipid-lowering drug (LLD) use and lung cancer risk is controversial, and the role of sphingolipid metabolism in this effect remains unclear. Methods: Genome-wide association study data on low-density lipoprotein (LDL), apolipoprotein B (ApoB), and triglycerides (TG) were used to develop genetic instrumental variables (IVs) for LLDs. Two-step Mendelian randomization analyses were performed to examine the causal relationship between LLDs and lung cancer risk. The effects of ceramide, sphingosine-1-phosphate (S1P), and ceramidases on lung cancer risk were explored, and the proportions of the effects of LLDs on lung cancer risk mediated by sphingolipid metabolism were calculated. Results: APOB inhibition decreased the lung cancer risk in ever-smokers via ApoB (odds ratio [OR] 0.81, 95% confidence interval [CI] 0.70-0.92, p = 0.010), LDL (OR 0.82, 95% CI 0.71-0.96, p = 0.040), and TG (OR 0.63, 95% CI 0.46-0.83, p = 0.015) reduction by 1 standard deviation (SD), decreased small-cell lung cancer (SCLC) risk via LDL reduction by 1 SD (OR 0.71, 95% CI 0.56-0.90, p = 0.016), and decreased the plasma ceramide level and increased the neutral ceramidase level. APOC3 inhibition decreased the lung adenocarcinoma (LUAD) risk (OR 0.60, 95% CI 0.43-0.84, p = 0.039) but increased SCLC risk (OR 2.18, 95% CI 1.17-4.09, p = 0.029) via ApoB reduction by 1 SD. HMGCR inhibition increased SCLC risk via ApoB reduction by 1 SD (OR 3.04, 95% CI 1.38-6.70, p = 0.014). The LPL agonist decreased SCLC risk via ApoB (OR 0.20, 95% CI 0.07-0.58, p = 0.012) and TG reduction (OR 0.58, 95% CI 0.43-0.77, p = 0.003) while increased the plasma S1P level. PCSK9 inhibition decreased the ceramide level. Neutral ceramidase mediated 8.1% and 9.5% of the reduced lung cancer risk in ever-smokers via ApoB and TG reduction by APOB inhibition, respectively, and mediated 8.7% of the reduced LUAD risk via ApoB reduction by APOC3 inhibition. Conclusion: We elucidated the intricate interplay between LLDs, sphingolipid metabolites, and lung cancer risk. Associations of APOB, APOC3, and HMGCR inhibition and LPL agonist with distinct lung cancer risks underscore the multifaceted nature of these relationships. The observed mediation effects highlight the considerable influence of neutral ceramidase on the lung cancer risk reduction achieved by APOB and APOC3 inhibition.

Associations between depressive, anxiety, stress symptoms and elevated blood pressure: Findings from the CHCN-BTH cohort study and a two-sample Mendelian randomization analysis

BACKGROUND

We aimed to determine whether depressive, anxiety, stress symptoms were associated with the risk of elevated blood pressure by performing longitudinal cohort and Mendelian Randomization (MR) analyses.

METHODS

We used data from the Cohort Study on Chronic Disease of Community Natural Population in the Beijing-Tianjin-Hebei region (CHCN-BTH) from 2017 to 2021. The Depression-Anxiety-Stress Scale was used to evaluate the depressive, anxiety, stress symptoms. The longitudinal associations between depressive, anxiety, stress symptoms and elevated blood pressure were estimated using Cox proportional regression models. Two-sample MR analysis was performed using the Inverse-variance weighted (IVW), weighted median, and MR-Egger to explore the causal relationships between depressive, anxiety, stress symptoms and elevated blood pressure.

RESULTS

In total, 5624 participants were included. The risk of SBP ≥ 140 mmHg or DBP ≥ 90 mmHg was significantly higher in participants with baseline anxiety symptoms (HR = 1.48, 95 % CI: 1.03 to 2.12, P = 0.033; HR = 1.56, 95 % CI: 1.05 to 2.32, P = 0.028), especially in men and individuals with higher educational levels, independent of baseline depression and anxiety at the two-year follow-up. The two-sample MR analysis showed positive associations between depressive, anxiety, stress symptoms and elevated blood pressure.

LIMITATION

Self-reported mental health symptoms, relatively shorter follow-up duration and the European-derived genome-wide association study data for MR analysis.

CONCLUSIONS

Anxiety symptoms were positively associated with elevated blood pressures in the longitudinal analysis independent of depression, stress, and other confounders. The results were verified in MR analysis, providing evidence for causal effects of anxiety symptoms on the risk of elevated blood pressure.

Effects of blood pressure and antihypertensive drugs on osteoarthritis: a mendelian randomized study

BACKGROUND

Previous studies have suggested that antihypertensive drugs may play a role in the treatment of osteoarthritis, but these studies may be limited by confounding factors and lead to biased results. Therefore, we conducted a Mendelian randomization study to investigate the effects of blood pressure and antihypertensive drugs on osteoarthritis.

METHODS

We used published large-scale genome-wide association data and applied univariate and multivariate Mendelian randomization methods. The main analysis model was inverse variance weighting, and the reliability of the results was tested using MR-Egger intercept analysis, Cochran's Q test, and leave-one-out analysis. We comprehensively evaluated the relationship between systolic blood pressure, diastolic blood pressure, 12 antihypertensive drugs, and osteoarthritis. We also conducted verification in the independent queue of UK Biobank and built a simple linear regression model to obtain an independent comparison.

RESULTS

We found no evidence that systolic and diastolic blood pressure significantly affected osteoarthritis. However, among antihypertensive drugs, we observed a significant positive correlation between potassium-preserving diuretics and aldosterone antagonists and all osteoarthritis (OR: 0.560, 95% CI 0.406-0.772, P = 0.0004). Sensitivity analysis showed no horizontal pleiotropy or heterogeneity, and the leave-one-out analysis demonstrated the reliability of the results. This result was replicated with nominally statistical significance in the validation cohort and exhibited significant correlation in the linear regression analysis.

CONCLUSIONS

Our study suggested that controlling the protein targets of potassium-sparing diuretics and aldosterone antagonists may have beneficial results for osteoarthritis. These findings provide valuable medication strategies for the control of hypertension in patients with osteoarthritis.

Association between genetically proxied HMGCR inhibition and male reproductive health: A Mendelian randomization study

BACKGROUND

The causal associations between statin use and male sex hormone levels and related disorders have not been fully understood. In this study, we employed Mendelian randomization for the first time to investigate these associations.

METHODS

In two-sample Mendelian randomization framework, genetic proxies for hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibition were identified as variants in the HMGCR gene that were associated with both levels of gene expression and low density lipoprotein cholesterol (LDL-C). We assessed the causal relationship between HMGCR inhibitor and 5 sex hormone levels/2 male-related diseases. Additionally, we investigated the association between 4 circulating lipid traits and outcomes. The "inverse variance weighting" method was used as the primary approach, and we assessed for potential heterogeneity and pleiotropy. In a secondary analysis, we revalidated the impact of HMGCR on 7 major outcomes using the summary-data-based Mendelian randomization method.

RESULTS

Our study found a significant causal association between genetic proxies for HMGCR inhibitor and decreased levels of total testosterone (TT) (LDL-C per standard deviation = 38.7mg/dL, effect = -0.20, 95% confidence interval [CI] = -0.25 to -0.15) and bioavailable testosterone (BT) (effect = -0.15, 95% CI = -0.21 to -0.10). Obesity-related factors were found to mediate this association. Furthermore, the inhibitor were found to mediate a reduced risk of prostate cancer (odds ratio = 0.81, 95%CI = 0.7-0.93) by lowering bioavailable testosterone levels, without increasing the risk of erectile dysfunction (P = .17). On the other hand, there was a causal association between increased levels of LDL-C, total cholesterol, triglycerides (TG) and decreased levels of TT, sex hormone-binding globulin, and estradiol.

CONCLUSIONS

The use of HMGCR inhibitor will reduce testosterone levels and the risk of prostate cancer without the side effect of erectile dysfunction. LDL-C, total cholesterol, and TG levels were protective factors for TT, sex hormone-binding globulin, and estradiol.

Correlations between schizophrenia and lichen planus: a two-sample bidirectional Mendelian randomization study

Background

Several existing studies have shown a correlation between schizophrenia and lichen planus (LP). However, the causality of this relationship remains uncertain. Thus, this study aimed to examine the causal association between schizophrenia and LP.

Methods

A two-sample Mendelian randomization (MR) study was carried out to investigate whether schizophrenia is causally related to LP and vice versa, and genetic variants in this study were taken from previous genome-wide association studies. We used the inverse variance weighted (IVW) method as the main analysis. Furthermore, several sensitivity analyses were performed to assess heterogeneity, horizontal pleiotropy, and stability.

Results

Our results show that schizophrenia has a protective effect on LP (OR = 0.881, 95%CI = 0.795-0.975, p = 0.015). Conversely, we observed no significant relationship between LP and schizophrenia in reverse MR analysis (OR = 0.934, 95%CI = 0.851-1.026, p = 0.156).

Conclusion

Our two-sample Mendelian randomization study supports a significant causal relationship between LP and schizophrenia and finds that schizophrenia can reduce the incidence of LP. This is in contrast to previous findings and provides new insights into the relationship between LP and schizophrenia, but the exact mechanism needs further investigation.

Mendelian Randomization Using the Druggable Genome Reveals Genetically Supported Drug Targets for Psychiatric Disorders

BACKGROUND AND HYPOTHESIS

Psychiatric disorders impose a huge health and economic burden on modern society. However, there is currently no proven completely effective treatment available, partly owing to the inefficiency of drug target identification and validation. We aim to identify therapeutic targets relevant to psychiatric disorders by conducting Mendelian randomization (MR) analysis.

STUDY DESIGN

We performed genome-wide MR analysis by integrating expression quantitative trait loci (eQTL) of 4479 actionable genes that encode druggable proteins and genetic summary statistics from genome-wide association studies of psychiatric disorders. After conducting colocalization analysis on the brain MR findings, we employed protein quantitative trait loci (pQTL) data as genetic proposed instruments for intersecting the colocalized genes to provide further genetic evidence.

STUDY RESULTS

By performing MR and colocalization analysis with eQTL genetic instruments, we obtained 31 promising drug targets for psychiatric disorders, including 21 significant genes for schizophrenia, 7 for bipolar disorder, 2 for depression, 1 for attention deficit and hyperactivity (ADHD) and none for autism spectrum disorder. Combining MR results using pQTL genetic instruments, we finally proposed 8 drug-targeting genes supported by the strongest MR evidence, including gene ACE, BTN3A3, HAPLN4, MAPK3 and NEK4 for schizophrenia, gene NEK4 and HAPLN4 for bipolar disorder, and gene TIE1 for ADHD.

CONCLUSIONS

Our findings with genetic support were more likely to be to succeed in clinical trials. In addition, our study prioritizes approved drug targets for the development of new therapies and provides critical drug reuse opportunities for psychiatric disorders.

Genetically predicted circulating levels of cytokines and the risk of depression: a bidirectional Mendelian-randomization study

Objective: Inflammatory cytokines disturbance is the main result of immune dysregulation, which is widely described in major depressive disorder (MDD). However, the potential causal relationship between these two factors has not been discovered. Therefore, the purpose of this study was to investigate the causal relationship between inflammatory cytokines and MDD risk by using the two-sample Mendelian randomization (MR) analysis. Method: Two genetic instruments obtained from publicly available gene profile data were utilized for the analysis. We obtained the genetic variation data of 41 inflammatory cytokines from genome-wide association studies (GWAS) meta-analysis of 8293 individuals of Finnish descent. The MDD data, including 135,458 MDD cases and 344,901 controls, were obtained from the Psychiatric Genomics Consortium Database. For the Mendelian randomization (MR) estimation, several methods were employed, namely, MR-Egger regression, inverse-variance weighted (IVW), weighted median, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) methods. Result: A causal relationship was identified between the genetically proxied levels of Interleukin (IL) -18, IL-1β, and Regulated upon activation normal T cell expressed and secreted (RANTES) and the risk of MDD (OR = 0.968, 95%CI = 0.938, 0.998, p = 0.036; OR = 0.875, 95%CI = 0.787, 0.971, p = 0.012; OR = 0.947, 95%CI = 0.902, 0.995, p = 0.03; respectively). However, our Mendelian randomization (MR) estimates provided no causality of MDD on inflammatory cytokines. Conclusion: Our study elucidates the connection between inflammatory cytokines and MDD by using MR analysis, thereby enhancing our comprehension of the potential mechanisms. By identifying these associations, our findings hold substantial implications for the development of more effective treatments aimed at improving patient outcomes. However, further investigation is required to fully comprehend the exact biological mechanisms involved.

A Mendelian randomization study for drug repurposing reveals bezafibrate and fenofibric acid as potential osteoporosis treatments

Background: Lipid pathways have been implicated in the pathogenesis of osteoporosis (OP). Lipid-lowering drugs may be used to prevent and treat OP. However, the causal interpretation of results from traditional observational designs is controversial by confounding. We aimed to investigate the causal association between genetically proxied lipid-lowering drugs and OP risk. Methods: We conducted two-step Mendelian randomization (MR) analyses to investigate the causal association of genetically proxied lipid-lowering drugs on the risk of OP. The first step MR was used to estimate the associations of drug target genes expression with low-density lipoprotein cholesterol (LDL-C) levels. The significant SNPs in the first step MR were used as instrumental variables in the second step MR to estimate the associations of LDL-C levels with forearm bone mineral density (FA-BMD), femoral neck BMD (FN-BMD), lumbar spine BMD (LS-BMD) and fracture. The significant lipid-lowering drugs after MR analyses were further evaluated for their effects on bone mineralization using a dexamethasone-induced OP zebrafish model. Results: The first step MR analysis found that the higher expression of four genes (HMGCR, NPC1L1, PCSK9 and PPARG) was significantly associated with a lower LDL-C level. The genetically decreased LDL-C level mediated by the PPARG was significantly associated with increased FN-BMD (BETA = -1.38, p = 0.001) and LS-BMD (BETA = -2.07, p = 3.35 × 10-5) and was marginally significantly associated with FA-BMD (BETA = -2.36, p = 0.008) and reduced fracture risk (OR = 3.47, p = 0.008). Bezafibrate (BZF) and Fenofibric acid (FBA) act as PPARG agonists. Therefore genetically proxied BZF and FBA had significant protective effects on OP. The dexamethasone-induced OP zebrafish treated with BZF and FBA showed increased bone mineralization area and integrated optical density (IOD) with alizarin red staining. Conclusion: The present study provided evidence that BZF and FBA can increase BMD, suggesting their potential effects in preventing and treating OP. These findings potentially pave the way for future studies that may allow personalized selection of lipid-lowering drugs for those at risk of OP.

Investigating the potential anti-depressive mechanisms of statins: a transcriptomic and Mendelian randomization analysis

Observational studies and randomized controlled trials presented inconsistent findings on the effects of cholesterol-lowering statins on depression. It therefore remains unclear whether statins have any beneficial effects on depression, and if so, what the underlying molecular mechanisms are. Here, we aimed to use genomic approaches to investigate this further. Using Connectivity Map (CMap), we first investigated whether statins and antidepressants shared pharmacological effects by interrogating gene expression responses to drug exposure in human cell lines. Second, using Mendelian randomization analysis, we investigated both on-target (through HMGCR inhibition) and potential off-target (through ITGAL and HDAC2 inhibition) causal effects of statins on depression risk and depressive symptoms, and traits related to the shared biological pathways identified from CMap analysis. Compounds inducing highly similar gene expression responses to statins in HA1E cells (indicated by an average connectivity score with statins > 90) were found to be enriched for antidepressants (12 out of 38 antidepressants; p = 9E-08). Genes perturbed in the same direction by both statins and antidepressants were significantly enriched for diverse cellular and metabolic pathways, and various immune activation, development and response processes. MR analysis did not identify any significant associations between statin exposure and depression risk or symptoms after multiple testing correction. However, genetically proxied HMGCR inhibition was strongly associated with alterations in platelets (a prominent serotonin reservoir) and monocyte percentage, which have previously been implicated in depression. Genetically proxied ITGAL inhibition was strongly associated with basophil, monocyte and neutrophil counts. We identified biological pathways that are commonly perturbed by both statins and antidepressants, and haematological biomarkers genetically associated with statin targets. Our findings warrant pre-clinical investigation of the causal role of these shared pathways in depression and potential as therapeutic targets, and investigation of whether blood biomarkers may be important considerations in clinical trials investigating effects of statins on depression.

Non-steroidal anti-inflammatory drug target gene associations with major depressive disorders: a Mendelian randomisation study integrating GWAS, eQTL and mQTL Data

Previous observational studies reported associations between non-steroidal anti-inflammatory drugs (NSAIDs) and major depressive disorder (MDD), however, these associations are often inconsistent and underlying biological mechanisms are still poorly understood. We conducted a two-sample Mendelian randomisation (MR) study to examine relationships between genetic variants and NSAID target gene expression or DNA methylation (DNAm) using publicly available expression, methylation quantitative trait loci (eQTL or mQTL) data and genetic variant-disease associations from genome-wide association studies (GWAS of MDD). We also assessed drug exposure using gene expression and DNAm levels of NSAID targets as proxies. Genetic variants were robustly adjusted for multiple comparisons related to gene expression, DNAm was used as MR instrumental variables and GWAS statistics of MDD as the outcome. A 1-standard deviation (SD) lower expression of NEU1 in blood was related to lower C-reactive protein (CRP) levels of -0.215 mg/L (95% confidence interval (CI): 0.128-0.426) and a decreased risk of MDD (odds ratio [OR] = 0.806; 95% CI: 0.735-0.885; p = 5.36 × 10^-6). A concordant direction of association was also observed for NEU1 DNAm levels in blood and a risk of MDD (OR = 0.886; 95% CI: 0.836-0.939; p = 4.71 × 10^-5). Further, the genetic variants associated with MDD were mediated by NEU1 expression via DNAm (β = -0.519; 95% CI: -0.717 to -0.320256; p = 3.16 × 10^-7). We did not observe causal relationships between inflammatory genetic marker estimations and MDD risk. Yet, we identified a concordant association of NEU1 messenger RNA and an adverse direction of association of higher NEU1 DNAm with MDD risk. These results warrant increased pharmacovigilance and further in vivo or in vitro studies to investigate NEU1 inhibitors or supplements for MDD.

Association of genetically predicted lipid traits and lipid-modifying targets with heart failure

AIMS

To assess the association of genetically predicted lipid traits and lipid-modification via licensed or investigational targets with heart failure (HF).

METHODS AND RESULTS

Two-sample Mendelian randomization (MR) study was conducted using summary-level genome-wide association studies (GWASs) from UK Biobank and HERMES Consortium. Genetic variants obtained from UK Biobank GWAS data were selected as instrumental variables to predict the level of lipid traits [LDL cholesterol (LDL-C), HDL cholesterol (HDL-C), triglyceride (TG), apolipoprotein B (ApoB), and apolipoprotein AI (ApoAI)] and lipid-modifying effect of eight drug targets [HMGCR, PCSK9, NPC1L1, PPARA, lipoprotein lipase (LPL), ANGPTL3, APOC3, and cholesteryl ester transfer protein (CETP)]. In this study, we observed that genetically predicted LDL-C, TG, HDL-C or ApoB were significantly related to HF, which were mainly mediated by coronary heart disease (CHD). Drug target MR analyses identified PCSK9, CETP, and LPL as potential targets to prevent HF. The genetic proxy of LDL-C and ApoB increase modified by PCSK9 showed similar evidence in increasing risk of HF (PLDL-C = 1.27*10-4; PApoB = 1.94*10-4); CETP played a role in HF risk via modifying all investigational lipid traits with the strongest evidence though ApoB (P = 5.87*10-6); LPL exerted effects on HF via modifying most lipid traits with the strongest evidence observed via modifying TG (P = 3.73*10-12).

CONCLUSION

This two-sample MR study provided genetic evidence of the associations between lipid traits and HF risk, which were mostly mediated by CHD. Besides, drug target MR studies indicated that PCSK9 inhibition, CETP inhibition, and LPL activation were effective in HF reduction.

A genomic deep field view of hypertension

Blood pressure is regulated by a complex neurohumoral system including the renin-angiotensin-aldosterone system, natriuretic peptides, endothelial pathways, the sympathetic nervous system, and the immune system. This review charts the evolution of our understanding of the genomic basis of hypertension at increasing resolution over the last 5 decades from monogenic causes to polygenic associations, spanning ∼30 monogenic rare variants and >1500 single nucleotide variants. Unexpected early wins from blood pressure genomics include deepening of our understanding of the complex causation of hypertension; refinement of causal estimates bidirectionally between blood pressure, risk factors, and outcomes through Mendelian randomization; risk stratification using polygenic risk scores; and opportunities for precision medicine and drug repurposing.

CRISPR/Cas-Based Approaches to Study Schizophrenia and Other Neurodevelopmental Disorders

The study of diseases of the central nervous system (CNS) at the molecular level is challenging because of the complexity of neural circuits and the huge number of specialized cell types. Moreover, genomic association studies have revealed the complex genetic architecture of schizophrenia and other genetically determined mental disorders. Investigating such complex genetic architecture to decipher the molecular basis of CNS pathologies requires the use of high-throughput models such as cells and their derivatives. The time is coming for high-throughput genetic technologies based on CRISPR (Clustered Regularly Interspaced Short Palindromic Repeat)/Cas systems to manipulate multiple genomic targets. CRISPR/Cas systems provide the desired complexity, versatility, and flexibility to create novel genetic tools capable of both altering the DNA sequence and affecting its function at higher levels of genetic information flow. CRISPR/Cas tools make it possible to find and investigate the intricate relationship between the genotype and phenotype of neuronal cells. The purpose of this review is to discuss innovative CRISPR-based approaches for studying the molecular mechanisms of CNS pathologies using cellular models.

Identifying novel proteins underlying schizophrenia via integrating pQTLs of the plasma, CSF, and brain with GWAS summary data

BACKGROUND

Schizophrenia (SCZ) is a chronic and severe mental illness with no cure so far. Mendelian randomization (MR) is a genetic method widely used to explore etiologies of complex traits. In the current study, we aimed to identify novel proteins underlying SCZ with a systematic analytical approach.

METHODS

We integrated protein quantitative trait loci (pQTLs) of the brain, cerebrospinal fluid (CSF), and plasma with the latest and largest SCZ genome-wide association study (GWAS) via a systematic analytical framework, including two-sample MR analysis, Steiger filtering analysis, and Bayesian colocalization analysis.

RESULTS

The genetically determined protein level of C4A/C4B (OR = 0.70, p = 1.66E-07) in the brain and ACP5 (OR = 0.42, p = 3.73E-05), CNTN2 (OR = 0.62, p = 2.57E-04), and PLA2G7 (OR = 0.71, p = 1.48E-04) in the CSF was associated with a lower risk of SCZ, while the genetically determined protein level of TIE1 (OR = 3.46, p = 4.76E-05), BCL6 (OR = 3.63, p = 1.59E-07), and MICB (OR = 4.49, p = 2.31E-11) in the CSF were associated with an increased risk for SCZ. Pathway enrichment analysis indicated that genetically determined proteins suggestively associated with SCZ were enriched in the biological process of the immune response.

CONCLUSION

In conclusion, we identified one protein in the brain and six proteins in the CSF that showed supporting evidence of being potentially associated with SCZ, which could provide insights into future mechanistic studies to find new treatments for the disease. Our results also supported the important role of neuroinflammation in the pathogenesis of SCZ.

Mendelian Randomization and GWAS Meta Analysis Revealed the Risk-Increasing Effect of Schizophrenia on Cancers

The causal relationship between cancer and Schizophrenia (SCZ) remains controversial. Some researchers have found that SCZ is a cancer-preventive factor in cohort studies or meta-analyses, whereas others have found the opposite. To understand more about this issue, we used two-sample Mendelian randomization (2SMR) on available GWAS summary results to evaluate potential genetic connections between SCZ and 13 cancers. We discovered that the genetic susceptibility to schizophrenia lead to an increasing risk of breast cancer (odds ratio [OR] per log-odds increase in schizophrenia risk: 1.049, 95% confidence interval [CI]:1.023–1.075; p = 0.00012; FDR = 0.0017), ovarian cancer (OR, 1.326; 95% CI, 1.267–1.387; p = 0.0007; FDR = 0.0045), and thyroid cancer (OR, 1.575; 95% CI, 1.048–2.365; p = 0.0285; FDR = 0.123). Secondly, we performed a meta-analysis based on the GWAS summary statistics of SCZ and the three significant cancers. Next, we associated genetic variants to genes using two gene mapping strategies: (a) positional mapping based on genomic proximity and (b) expression quantitative trait loci (eQTL) mapping based on gene expression linkage across multiple tissues. As a result, we identified 114 shared loci and 437 shared genes in three groups, respectively. Functional enrichment analysis shows that the most enriched biological pathways are related to epigenetic modification. In addition, we noticed that SCZ would affect the level of thyroid-stimulating hormone (OR, 1.095; 95% CI, 1.006–1.191; p = 0.0354; FDR = 0.177), which may further affect the level of estrogen and the risk of the above three cancers. In conclusion, our findings under the 2SMR assumption provide crucial insights into the risk-increasing effect of SCZ on three cancers’ risk. Furthermore, these results may provide insights into understanding the genetic predisposition and underlying biological pathways of comorbid SCZ and cancers.

Locus-level antagonistic selection shaped the polygenic architecture of human complex diseases

BACKGROUND

We aimed to evaluate the potential role of antagonistic selection in polygenic diseases: if one variant increases the risk of one disease and decreases the risk of another disease, the signals of genetic risk elimination by natural selection will be distorted, which leads to a higher frequency of risk alleles.

METHODS

We applied local genetic correlations and transcriptome-wide association studies to identify genomic loci and genes adversely associated with at least two diseases. Then, we used different population genetic metrics to measure the signals of natural selection for these loci and genes.

RESULTS

First, we identified 2120 cases of antagonistic pleiotropy (negative local genetic correlation) among 87 diseases in 716 genomic loci (antagonistic loci). Next, by comparing with non-antagonistic loci, we observed that antagonistic loci explained an excess proportion of disease heritability (median 6%), showed enhanced signals of balancing selection, and reduced signals of directional polygenic adaptation. Then, at the gene expression level, we identified 31,991 cases of antagonistic pleiotropy among 98 diseases at 4368 genes. However, evidence of altered signals of selection pressure and heritability distribution at the gene expression level is limited.

CONCLUSION

We conclude that antagonistic pleiotropy is widespread among human polygenic diseases, and it has distorted the evolutionary signal and genetic architecture of diseases at the locus level.

Antihypertensive drugs and brain function: mechanisms underlying therapeutically beneficial and harmful neuropsychiatric effects

A bidirectional relationship exists between hypertension and psychiatric disorders, including unipolar and bipolar depression, anxiety, post-traumatic stress disorder (PTSD), psychosis, schizophrenia, mania, and dementia/cognitive decline. Repurposing of antihypertensive drugs to treat mental disorders is thus being explored. A systematic knowledge of the mechanisms of action and clinical consequences of the use of antihypertensive agents on neuropsychiatric functions has not been achieved yet. In this article, we review the putative role of antihypertensive agents in psychiatric disorders, discuss the targets and mechanisms of action, and examine how and to what extent specific drug classes/molecules may trigger, worsen, or mitigate psychiatric symptoms. In addition, we review pharmacokinetics (brain penetration of drugs) and pharmacogenetics data that add important information to assess risks and benefits of antihypertensive drugs in neuropsychiatric settings. The scientific literature shows robust evidence of a positive effect of α1 blockers on PTSD symptoms, nightmares and sleep quality, α2 agonists on core symptoms, executive function and quality of life in Attention-Deficit/Hyperactivity Disorder, PTSD, Tourette's syndrome, and β blockers on anxiety, aggression, working memory, and social communication. Renin-angiotensin system modulators exert protective effects on cognition, depression, and anxiety, and the loop diuretic bumetanide reduced the core symptoms of autism in a subset of patients. There is no evidence of clear benefits of calcium channel blockers in mood disorders in the scientific literature. These findings are mainly from preclinical studies; clinical data are still insufficient or of anecdotal nature, and seldom systematic. The information herewith provided can support a better therapeutic approach to hypertension, tailored to patients with, or with high susceptibility to, psychiatric illness. It may prompt clinical studies exploring the potential benefit of antihypertensive drugs in selected patients with neuropsychiatric comorbidities that include outcomes of neuropsychiatric interest and specifically assess undesirable effects or interactions.

Association of lipid-lowering drugs with COVID-19 outcomes from a Mendelian randomization study

Background:

Lipid metabolism plays an important role in viral infections. We aimed to assess the causal effect of lipid-lowering drugs (HMGCR inhibitiors, PCSK9 inhibitiors, and NPC1L1 inhibitior) on COVID-19 outcomes using two-sample Mendelian randomization (MR) study.

Methods:

We used two kinds of genetic instruments to proxy the exposure of lipid-lowering drugs, including expression quantitative trait loci of drugs target genes, and genetic variants within or nearby drugs target genes associated with low-density lipoprotein (LDL cholesterol from genome-wide association study). Summary-data-based MR (SMR) and inverse-variance-weighted MR (IVW-MR) were used to calculate the effect estimates.

Results:

SMR analysis found that a higher expression of HMGCR was associated with a higher risk of COVID-19 hospitalization (odds ratio [OR] = 1.38, 95% confidence interval [CI] = 1.06–1.81). Similarly, IVW-MR analysis observed a positive association between HMGCR-mediated LDL cholesterol and COVID-19 hospitalization (OR = 1.32, 95% CI = 1.00–1.74). No consistent evidence from both analyses was found for other associations.

Conclusions:

This two-sample MR study suggested a potential causal relationship between HMGCR inhibition and the reduced risk of COVID-19 hospitalization.

Funding:

Start-up Fund for high-level talents of Fujian Medical University.

The virus SARS-CoV-2 has caused millions of infections and deaths during the COVID-19 pandemic, but as of December 2021, no new drugs targeted to SARS-CoV-2 specifically exist. Thus, it is important to identify existing drugs that can reduce the infection and mortality of this virus, since repurposing old drugs is faster and cheaper than developing new ones. Fats, such as cholesterol, can play an important role in viral infections, meaning that drugs intended to lower the levels of fats in the blood could have a protective effect against SARS-CoV-2.

To test this hypothesis, Huang, Xiao, et al. carried out a Mendelian randomization study to investigate if there is a link between drugs that lower fats and outcomes of SARS-CoV-2 infection, including susceptibility, hospitalization, and severe disease. This approach consists on grouping people according to their version of a particular gene, which minimizes the effect of variables that can cause spurious associations, something known as confounding bias. Thus, Mendelian randomization studies allow scientists to disentangle cause and effect.

Using this method, Huang, Xiao, et al. found an association between statins (a type of drug that decreases the levels of bad cholesterol) and a reduced risk of being hospitalized after being infected with SARS-CoV-2.

These findings suggest that statins could benefit patients infected with SARS-CoV-2, and indicate that they should be prioritized in future clinical trials for treating COVID-19.