Mendelian randomization: a novel approach for the prediction of adverse drug events and drug repurposing opportunities

Exploring the Relationship Between Atorvastatin and Memory Loss: A Comprehensive Analysis Integrating Real-World Pharmacovigilance and Mendelian Randomization

BACKGROUND AND OBJECTIVE

Atorvastatin is a drug widely used to prevent cardiovascular and cerebrovascular diseases. Current observational studies suggest that atorvastatin may be associated with cognitive dysfunction (especially memory loss). However, some studies have suggested that dyslipidemia may be an important factor in cognitive dysfunction. The purpose of this study was to perform a pharmacovigilance analysis using real-world data from the US Food and Drug Administration's Adverse Event Reporting System (FAERS) to assess whether memory loss is an adverse effect of atorvastatin and to further clarify its causality through Mendelian randomization (MR).

METHODS

We extracted real-world data from the FAERS database (Quarter 1 2004 to Quarter 1 2023). Disproportionality analysis methods and measures of association such as the reporting odds ratio (OR), proportional reporting ratio, Bayesian confidence interval progressive neural network, and polynomial Gamma Poisson distribution reduction were used to assess whether memory loss was an adverse effect of atorvastatin. In addition, we used MR to evaluate causality in depth.

RESULTS

In the pharmacovigilance analysis of atorvastatin, we extracted four datasets of clinical symptoms associated with memory loss from the FAERS database [Amnesia (n = 1196), Memory impairment (n = 840), Transient global amnesia (n = 38), and Retrograde amnesia (n = 9)]. The reporting OR, proportional reporting ratio, Bayesian confidence interval progressive neural network, and Gamma Poisson distribution reduction all showed positive results for amnesia, transient global amnesia, and retrograde amnesia, while the reporting OR and Bayesian confidence interval progressive neural network also showed positive results for memory disorders. Thus, memory loss was a frequent side effect of atorvastatin. The MR analyses were used to further evaluate the association between statins and memory loss. The results of the MR analysis (statins and memory loss) are as follows: Ivw (mre) (β = 0.11 [OR = 1.11], P = 0.01 < 0.05) and the OR and β directions of MR-Egger and weighted mode were the same. The results of the MR analysis (statins and mitochondrial DNA copy number) are as follows: Ivw(mre) (β = -0.03 [OR = 0.96], P < 0.01) and the OR and β direction of MR-Egger and weighted mode are the same. The results of the MR analysis (DNA copy number and memory loss) are as follows: Ivw(β = - 0.06 [OR = 0.94], P = 0.04 < 0.05) and the OR and β direction of MR-Egger and weighted mode were the same. The pleiotropy test did not find horizontal diversity in our results.

CONCLUSIONS

This study suggests that memory loss is a notable adverse event associated with atorvastatin and provides evidence indicating a potential causal relationship between atorvastatin and memory loss. We also found that statins may further affect memory by affecting mitochondrial function. Therefore, in the clinical use of atorvastatin, it is important to carefully monitor the changes in cognitive function of patients. Second, a pharmacovigilance analysis combined with MR was used in this study to provide a new approach for the study of adverse drug reactions. This comprehensive analysis method helps to evaluate the safety of drugs and the risk of adverse reactions more comprehensively and provides doctors with a more accurate clinical decision-making basis.

SCARF2 is a target for chronic obstructive pulmonary disease: Evidence from multi-omics research and cohort validation

Age-related chronic inflammatory lung diseases impose a threat on public health, including idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD). However, their etiology and potential targets have not been clarified. We performed genome-wide meta-analysis for IPF with the largest sample size (2883 cases and 741,929 controls) and leveraged the summary statistics of COPD (17,547 cases and 617,598 controls). Transcriptome-wide and proteome-wide Mendelian randomization (MR) designs, together with genetic colocalization, were implemented to find robust targets. The mediation effect was assessed using leukocyte telomere length (LTL). The single-cell transcriptome analysis was performed to link targets with cell types. Individual-level data from UK Biobank (UKB) were used to validate our findings. Sixteen genetically predicted plasma proteins were causally associated with the risk of IPF and 6 proteins were causally associated with COPD. Therein, genetically-elevated plasma level of SCARF2 protein should reduce the risk of both IPF (odds ratio, OR = 0.9974 [0.9970, 0.9978]) and COPD (OR = 0.7431 [0.6253, 0.8831]) and such effects were not mediated by LTL. Genetic colocalization further corroborated these MR results of SCARF2. The transcriptome-wide MR confirmed that higher expression level of SCARF2 was associated with a reduced risk of both. However, the single-cell RNA analysis indicated that SCARF2 expression level was only relatively lower in epithelial cells of COPD lung tissue compared to normal lung tissue. UKB data implicated an inverse association of serum SCARF2 protein with COPD (hazard ratio, HR = 1.215 [1.106, 1.335]). The SCARF2 gene should be a novel target for COP.

Hypothyroidism's effect on stroke limited to specific subtypes: A Mendelian randomization study

BACKGROUND

The association between hypothyroidism and stroke remains controversial and the association between hypothyroidism and stroke subtypes has not been satisfactorily researched. This study aimed to explore the causal effect of hypothyroidism on the risk of stroke and its subtypes by Mendelian randomization (MR) analysis.

METHODS

Single nucleotide polymorphisms (SNPs) were selected from published genome-wide association studies (GWAS) meta-analysis as instrumental variables (IVs) for hypothyroidism. As outcomes, summary GWAS data for stroke and its subtypes were obtained from two other large GWAS meta-analyses, including any stroke (AS), any ischemic stroke (AIS), large vessel stroke (LAS), cardiogenic embolic stroke (CES), small vessel stroke (SVS), and intracranial hemorrhage (ICH). Univariate Mendelian randomization (UVMR) and multivariate Mendelian randomization (MVMR) were used to assess the causal effect of hypothyroidism on stroke and its subtypes.

RESULTS

In UVMR, genetically predicted hypothyroidism was significantly associated with LAS (OR = 1.14, 95CI = 1.02-1.27) and SVS (OR = 1.14, 95CI = 1.04-1.25), but not with AS, AIS, CES, and ICH. The results of the MVMR showed that after adjusting for smoking, alcohol consumption, hypertension, diabetes, low-density lipoprotein cholesterol (LDL-c), and body mass index (BMI), the causal association between hypothyroidism and SVS remained significant, while the association between hypothyroidism and LAS became nonsignificant.

CONCLUSION

Hypothyroidism is causally associated with risk for LAS and SVS, but not for other stroke subtypes. Hypothyroidism may be an independent risk factor for SVS, and vascular risk factors play an important role in hypothyroidism causing LAS.

The causal relationship between anti-diabetic drugs and gastrointestinal disorders: a drug-targeted mendelian randomization study

BACKGROUND

The incidence of diabetic gastrointestinal diseases is increasing year by year. This study aimed to investigate the causal relationship between antidiabetic medications and gastrointestinal disorders, with the goal of reducing the incidence of diabetes-related gastrointestinal diseases and exploring the potential repurposing of antidiabetic drugs.

METHODS

We employed a two-sample Mendelian randomization (TSMR) design to investigate the causal association between antidiabetic medications and gastrointestinal disorders, including gastroesophageal reflux disease (GERD), gastric ulcer (GU), chronic gastritis, acute gastritis, Helicobacter pylori infection, gastric cancer (GC), functional dyspepsia (FD), irritable bowel syndrome (IBS), ulcerative colitis (UC), Crohn's disease (CD), diverticulosis, and colorectal cancer (CRC). To identify potential inhibitors of antidiabetic drug targets, we collected single-nucleotide polymorphisms (SNPs) associated with metformin, GLP-1 receptor agonists, SGLT2 inhibitors, DPP-4 inhibitors, insulin, and its analogs, thiazolidinediones, sulfonylureas, and alpha-glucosidase inhibitors from published genome-wide association study statistics. We then conducted a drug-target Mendelian randomization (MR) analysis using inverse variance weighting (IVW) as the primary analytical method to assess the impact of these inhibitors on gastrointestinal disorders. Additionally, diabetes was selected as a positive control.

RESULTS

Sulfonylureas were found to significantly reduce the risk of CD (IVW: OR [95% CI] = 0.986 [0.978, 0.995], p = 1.99 × 10- 3), GERD (IVW: OR [95% CI] = 0.649 [0.452, 0.932], p = 1.90 × 10- 2), and chronic gastritis (IVW: OR [95% CI] = 0.991 [0.982, 0.999], p = 4.50 × 10- 2). However, they were associated with an increased risk of GU development (IVW: OR [95%CI] = 2 0.761 [1.259, 6.057], p = 1 0.12 × 10- 2).

CONCLUSIONS

The results indicated that sulfonylureas had a positive effect on the prevention of CD, GERD, and chronic gastritis but a negative effect on the development of gastric ulcers. However, our research found no causal evidence for the impact of metformin, GLP-1 agonists, SGLT2 inhibitors, DPP 4 inhibitors, insulin and its analogs, thiazolidinediones, or alpha-glucosidase inhibitors on gastrointestinal diseases.

Association between smoking and alcohol drinking and benign adrenal tumors: a Mendelian randomization study

BACKGROUND

In recent years, the detection rate of adrenal tumors has increased, but it is unclear whether smoking and alcohol drinking are risk factors for benign adrenal tumors. The objective of this study is to employ Mendelian randomization (MR) analysis to explore the causal relationship between smoking, alcohol drinking and susceptibility to benign adrenal tumors.

METHODS

We acquired large-scale data from publicly accessible databases on genome-wide association studies (GWAS) pertaining to smoking, alcohol drinking and benign adrenal tumors. A total of 11 sets of instrumental variables (IVs) and 281 associated single nucleotide polymorphic (SNP) loci were identified. The Mendelian randomization analyses were conducted using inverse variance weighting (IVW), MR-Egger regression and weighted median estimation (WME) methods, in addition to sensitivity analyses.

RESULTS

There is no causal relationship between smoking status, alcohol drinking status, alcohol intake frequency, alcohol taken with meals, alcohol consumption and benign adrenal tumors, while pack years of smoking and cigarettes per day are risk factors for benign adrenal tumors. The IVW analysis revealed that both the pack years of smoking and cigarettes per day were positively associated with an increased risk of benign adrenal tumors (OR = 2.853, 95%CI = 1.384-5.878, p = 0.004; OR = 1.543, 95%CI = 1.147-2.076, p = 0.004). Two SNPs (rs8042849 in the analysis of pack years of smoking and rs8034191 in the analysis of cigarettes per day) significantly drove the observed causal effects.

CONCLUSION

Two-sample Mendelian randomization analysis showed a causal effect between smoking but not alcohol consumption and benign adrenal tumors.

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.

Antihypertensive drug targets and breast cancer risk: a two-sample Mendelian randomization study

Findings on the correlation between the use of antihypertensive medication and the risk of breast cancer (BC) have been inconsistent. We performed a two-sample Mendelian randomization (MR) using instrumental variables to proxy changes in gene expressions of antihypertensive medication targets to interrogate this. Genetic instruments for expression of antihypertensive drug target genes were identified with expression quantitative trait loci in blood, which should be associated with systolic blood pressure to proxy for the effect of antihypertensive drug. The association between genetic variants and BC risk were obtained from genome-wide association study summary statistics. The summary-based MR was employed to estimate the drug effects on BC risk. We further performed sensitivity analyses to confirm the discovered MR associations such as assessment of horizontal pleiotropy, colocalization, and multiple tissue enrichment analyses. The overall BC risk was only associated with SLC12A2 gene expression at a Bonferroni-corrected threshold. One standard deviation (SD) decrease of SLC12A2 gene expression in blood was associated with a decrease of 1.12 (95%CI, 0.80-1.58) mmHg of systolic blood pressure, but a 16% increased BC risk (odds ratio, 1.16, 95% confidential interval, 1.06-1.28). This signal was further observed for estrogen receptor positive (ER +) BC (1.17, 1.06-1.28). In addition, one SD decrease in expression of PDE1B in blood was associated with 7% decreased risk of ER + BC (0.93, 0.90-0.97). We detected no evidence of horizontal pleiotropy for these associations and the probability of the causal variants being shared between the gene expression and BC risk was 81.5, 40.5 and 66.8%, respectively. No significant association was observed between other target gene expressions and BC risk. Changes in expression of SLC12A2 and PDE1B mediated possibly via antihypertensive drugs may result in increased and decreased BC risk, respectively.

Association between atorvastatin and erectile dysfunction: a comprehensive analysis incorporating real-world pharmacovigilance and Mendelian randomization

Background

Atorvastatin is a commonly prescribed medication for the prevention of cardiovascular diseases. Recent observational studies have suggested a potential association between atorvastatin use and the occurrence of Erectile Dysfunction (ED). In this study, we aimed to explore the relationship between atorvastatin and ED using real-world data from the FAERS database and employed Mendelian randomization to assess causality.

Methods

To evaluate the disproportionality of atorvastatin in relation to ED, we conducted several pharmacovigilance analyses, including odds ratio (ROR), proportional reporting ratio (PRR), Bayesian Confidence propagation neural network (BCPNN), and gamma-Poisson contractile apparatus (GPS). Additionally, we employed Mendelian randomization to investigate the causal relationship between atorvastatin and ED.

Results

Pharmacovigilance disproportionality analysis revealed a significant association between atorvastatin and ED, as indicated by the following results: ROR [3.707078559, 95% CI (3.33250349, 4.123756054)], PRR [3.702969038, χ2 (669.2853829)], IC [1.870490139, IC025 (1.702813857)], and EBGM [3.656567867, EBGM05 (3.28709656)]. Furthermore, the two-sample Mendelian randomization analysis provided evidence supporting a causal relationship between atorvastatin use and ED, with an inverse variance weighted estimate of β = 3.17 (OR = 23.91, p = 0.02 < 0.05).

Conclusion

Based on comprehensive analyses incorporating pharmacovigilance and Mendelian randomization, our findings suggest that atorvastatin use is associated with an increased risk of ED and indicate a causal relationship. These results emphasize the importance of considering potential adverse effects, such as ED, when prescribing atorvastatin for cardiovascular disease prevention. Further research and clinical monitoring are warranted to better understand the underlying mechanisms and develop appropriate strategies to mitigate this side effect.

Causal relationship between dementia and delirium: Insights from a bidirectional two-sample Mendelian randomization analysis

BACKGROUND

Our previous study found dementia as a significant risk factor for delirium development in elderly patients with hip fracture. However, the causal relationship between dementia and delirium remains unclear.

METHODS

To assess the causal relationship between delirium and dementia, we conducted a bidirectional Mendelian randomization (MR) analysis. Inversevariance weighted (IVW), weighted median, MR Egger, weighted mode, and simple mode were employed to conduct the MR analysis. Heterogeneity was assessed using the Cochran Q statistic in MR-Egger and IVW methods. Horizontal pleiotropy was examined via the MR pleiotropy residual sum and outliers (MR-PRESSO) and MR-Egger intercept tests.

RESULTS

The forward MR analysis revealed a significant association between unclassified dementia (1.604 (1.326-1.941), p = 1.12 × 10-6), Alzheimer's disease (1.259 (1.128-1.405), p = 4.10 × 10-5), and dementia with Lewy bodies (1.121 (1.026-1.225), p = 0.011) with an increased risk of delirium. In the reverse MR analysis, delirium was also suggested to increase the risk of unclassified dementia (1.133 (1.066-1.204), p = 6.31 × 10-5) and vascular dementia (1.246 (1.075-1.444), p = 0.003). These significant results were further validated in the multivariable MR analysis. No evidence of heterogeneity or horizontal pleiotropy was observed (p > 0.05).

LIMITATIONS

(1) Limited to European populations. (2) Sample population overlap between delirium and dementia. (3) Not all dementia subtypes were causally associated with delirium.

CONCLUSIONS

This study provides genetic evidence supporting a causal relationship between dementia and delirium, indicating that dementia may influence the risk of delirium while delirium may also increase the risk of dementia.

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.

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

BACKGROUND

Past studies have demonstrated that patients diagnosed with rheumatoid arthritis (RA) often exhibit abnormal levels of lipids. Furthermore, certain lipid-modifying medications have shown effectiveness in alleviating clinical symptoms associated with RA. However, the current understanding of the causal relationship between lipids, lipid-modifying medications, and the risk of developing RA remains inconclusive. This study employed Mendelian randomization (MR) to investigate the causal connection between lipids, lipid-modifying drugs, and the occurrence of RA.

METHODS

We obtained genetic variation for lipid traits and drug targets related to lipid modification from three sources: the Global Lipids Genetics Consortium (GLGC), UK Biobank, and Nightingale Health 2020. The genetic data for RA were acquired from two comprehensive meta-analyses and the R8 of FINNGEN, respectively. These variants were employed in drug-target MR analyses to establish a causal relationship between genetically predicted lipid-modifying drug targets and the risk of RA. For suggestive lipid-modified drug targets, we conducted Summary-data-based Mendelian Randomization (SMR) analyses and using expression quantitative trait loci (eQTL) data in relevant tissues. In addition, we performed co-localization analyses to assess genetic confounders.

RESULTS

Our analysis revealed no significant causal relationship between lipid and RA. We observed that the genetically predicted 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) -mediated low density lipoprotein cholesterol (LDL-C) (OR 0.704; 95% CI 0.56, 0.89; P = 3.43×10-3), Apolipoprotein C-III (APOC3) -mediated triglyceride (TG) (OR 0.844; 95% CI 0.77, 0.92; P = 1.50×10-4) and low density lipoprotein receptor (LDLR) -mediated LDL-C (OR 0.835; 95% CI 0.73, 0.95; P = 8.81×10-3) were significantly associated with a lowered risk of RA. while Apolipoprotein B-100 (APOB) -mediated LDL-C (OR 1.212; 95%CI 1.05,1.40; P = 9.66×10-3) was significantly associated with an increased risk of RA.

CONCLUSIONS

Our study did not find any supporting evidence to suggest that lipids are a risk factor for RA. However, we observed significant associations between HMGCR, APOC3, LDLR, and APOB with the risk of RA.

Novel insights into causal effects of serum lipids and lipid-modifying targets on cholelithiasis

OBJECTIVE

Different serum lipids and lipid-modifying targets should affect the risk of cholelithiasis differently, however, whether such effects are causal is still controversial and we aimed to answer this question.

DESIGN

We prospectively estimated the associations of four serum lipids with cholelithiasis in UK Biobank using the Cox proportional hazard model, including total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglycerides (TG). Furthermore, we estimated the causal associations of the genetically predicted serum lipids with cholelithiasis in Europeans using the Mendelian randomisation (MR) design. Finally, both drug-target MR and colocalisation analyses were performed to estimate the lipid-modifying targets' effects on cholelithiasis, including HMGCR, NPC1L1, PCSK9, APOB, LDLR, ACLY, ANGPTL3, MTTP, PPARA, PPARD and PPARG.

RESULTS

We found that serum levels of LDL-C and HDL-C were inversely associated with cholelithiasis risk and such associations were linear. However, the serum level of TC was non-linearly associated with cholelithiasis risk where lower TC was associated with higher risk of cholelithiasis, and the serum TG should be in an inverted 'U-shaped' relationship with it. The MR analyses supported that lower TC and higher TG levels were two independent causal risk factors. The drug-target MR analysis suggested that HMGCR inhibition should reduce the risk of cholelithiasis, which was corroborated by colocalisation analysis.

CONCLUSION

Lower serum TC can causally increase the risk of cholelithiasis. The cholelithiasis risk would increase with the elevation of serum TG but would decrease when exceeding 2.57 mmol/L. The use of HMGCR inhibitors should prevent its risk.

Investigating the association between genetically proxied circulating levels of immune checkpoint proteins and cancer survival: protocol for a Mendelian randomisation analysis

INTRODUCTION

Compared with the traditional drug development pathway, investigating alternative uses for existing drugs (ie, drug repurposing) requires substantially less time, cost and resources. Immune checkpoint inhibitors are licensed for the treatment of certain breast, colorectal, head and neck, lung and melanoma cancers. These drugs target immune checkpoint proteins to reduce the suppression of T cell activation by cancer cells. As T cell suppression is a hallmark of cancer common across anatomical sites, we hypothesise that immune checkpoint inhibitors could be repurposed for the treatment of additional cancers beyond the ones already indicated.

METHODS AND ANALYSIS

We will use two-sample Mendelian randomisation to investigate the effect of genetically proxied levels of protein targets of two immune checkpoint inhibitors-programmed cell death protein 1 and programmed death ligand 1-on survival of seven cancer types (breast, colorectal, head and neck, lung, melanoma, ovarian and prostate). Summary genetic association data will be obtained from prior genome-wide association studies of circulating protein levels and cancer survival in populations of European ancestry. Various sensitivity analyses will be performed to examine the robustness of findings to potential violations of Mendelian randomisation assumptions, collider bias and the impact of alternative genetic instrument construction strategies. The impact of treatment history and tumour stage on the findings will also be investigated using summary-level and individual-level genetic data where available.

ETHICS AND DISSEMINATION

No separate ethics approval will be required for these analyses as we will be using data from previously published genome-wide association studies which individually gained ethical approval and participant consent. Results from analyses will be submitted as an open-access peer-reviewed publication and statistical code will be made freely available on the completion of the analysis.

The landscape of the methodology in drug repurposing using human genomic data: a systematic review

The process of drug development is expensive and time-consuming. In contrast, drug repurposing can be introduced to clinical practice more quickly and at a reduced cost. Over the last decade, there has been a significant expansion of large biobanks that link genomic data to electronic health record data, public availability of various databases containing biological and clinical information and rapid development of novel methodologies and algorithms in integrating different sources of data. This review aims to provide a thorough summary of different strategies that utilize genomic data to seek drug-repositioning opportunities. We searched MEDLINE and EMBASE databases to identify eligible studies up until 1 May 2023, with a total of 102 studies finally included after two-step parallel screening. We summarized commonly used strategies for drug repurposing, including Mendelian randomization, multi-omic-based and network-based studies and illustrated each strategy with examples, as well as the data sources implemented. By leveraging existing knowledge and infrastructure to expedite the drug discovery process and reduce costs, drug repurposing potentially identifies new therapeutic uses for approved drugs in a more efficient and targeted manner. However, technical challenges when integrating different types of data and biased or incomplete understanding of drug interactions are important hindrances that cannot be disregarded in the pursuit of identifying novel therapeutic applications. This review offers an overview of drug repurposing methodologies, providing valuable insights and guiding future directions for advancing drug repurposing studies.

Causal role of lipid metabolism in pulmonary alveolar proteinosis: an observational and mendelian randomisation study

BACKGROUND

Pulmonary alveolar proteinosis (PAP) is a rare interstitial lung disease characterised by the accumulation of lipoprotein material in the alveoli. Although dyslipidaemia is a prominet feature, the causal effect of lipid traits on PAP remains unclear. This study aimed to explore the role of lipid traits in PAP and evaluate the potential of lipid-lowering drug targets in PAP.

METHODS

Clinical outcomes, lipid profiles and lung function tests were analysed in a clinical cohort of diagnosed PAP patients and propensity score-matched healthy controls. Genome-wide association study data on PAP, lipid metabolism, blood cells and variants of genes encoding potential lipid-lowering drug targets were obtained for Mendelian randomisation (MR) and mediation analyses.

FINDINGS

Observational results showed that higher levels of total cholesterol (TC), triglycerides and low-density lipoprotein (LDL) were associated with increased risks of PAP. Higher levels of TC and LDL were also associated with worse PAP severity. In MR analysis, elevated LDL was associated with an increased risk of PAP (OR: 4.32, 95% CI: 1.63 to 11.61, p=0.018). Elevated monocytes were associated with a lower risk of PAP (OR 0.34, 95% CI: 0.18 to 0.66, p=0.002) and mediated the risk impact of LDL on PAP. Genetic mimicry of PCSK9 inhibition was associated with a reduced risk of PAP (OR 0.03, p=0.007).

INTERPRETATION

Our results support the crucial role of lipid and metabolism-related traits in PAP risk, emphasising the monocyte-mediated, causal effect of elevated LDL in PAP genetics. PCSK9 mediates the development of PAP by raising LDL. These finding provide evidence for lipid-related mechanisms and promising lipid-lowering drug target for PAP.

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.

Parkinson's Disease is Predominantly a Genetic Disease

The discovery of a pathogenic variant in the alpha-synuclein (SNCA) gene in the Contursi kindred in 1997 indisputably confirmed a genetic cause in a subset of Parkinson's disease (PD) patients. Currently, pathogenic variants in one of the seven established PD genes or the strongest known risk factor gene, GBA1, are identified in ∼15% of PD patients unselected for age at onset and family history. In this Debate article, we highlight multiple avenues of research that suggest an important - and in some cases even predominant - role for genetics in PD aetiology, including familial clustering, high rates of monogenic PD in selected populations, and complete penetrance with certain forms. At first sight, the steep increase in PD prevalence exceeding that of other neurodegenerative diseases may argue against a predominant genetic etiology. Notably, the principal genetic contribution in PD is conferred by pathogenic variants in LRRK2 and GBA1 and, in both cases, characterized by an overall late age of onset and age-related penetrance. In addition, polygenic risk plays a considerable role in PD. However, it is likely that, in the majority of PD patients, a complex interplay of aging, genetic, environmental, and epigenetic factors leads to disease development.

Causal effect of beta-blockers on the risk of lung cancer: a Mendelian randomization study

Background

It remains uncertain whether there is a causal association of the use of beta-blockers (BBs) on lung cancer risk. We used a two-sample Mendelian randomization (MR) approach to identify the causal association of BBs and lung cancer risk.

Methods

Twenty-two BB-related single-nucleotide polymorphisms (SNPs) were obtained from the UK Biobank as the instrumental variables (IVs). Genetic summary data information of lung cancer was extracted from the International Lung Cancer Consortium, with a total of 11,348 cases and 15,861 controls. We adopted the inverse-variance weighted (IVW) approach to conduct the MR analyses. Egger-intercept analysis was further performed as sensitivity analysis for pleiotropy evaluation. Additionally, we investigated whether BBs could causally affect the risk of lung cancer through their pharmacological effects.

Results

The current IVW analysis suggested a decreased lung cancer risk in BB users [odds ratio (OR) =0.83; 95% confidence interval (CI): 0.73-0.95; P<0.01]. Results of Egger-intercept analysis demonstrated that no pleiotropy was found (P=0.94), which suggested the robustness of the causality. However, there was little evidence that pharmacological effects mediate the association between BBs and lung cancer.

Conclusions

The current analysis suggested that BBs could decrease the risk of lung cancer but may be not via its pharmacological effects. Further research is in need for elucidating the underlying mechanisms.

Endometriosis and epithelial ovarian cancer: a two-sample Mendelian randomization analysis

Endometriosis, a prevalent condition, has long been recognized as a chronic and debilitating ailment affecting an estimated 1790 million women worldwide. Observational studies have established a correlation between endometriosis and ovarian cancer. Thus, we endeavored to employ Two-Sample Mendelian Randomization, utilizing summary statistics from a Genome-Wide Association Study of endometriosis and epithelial ovarian cancer, with genetic markers serving as proxies for epithelial ovarian cancer. The analysis revealed a significant correlation between these entities, with an odds ratio (OR) of 1.23 (95% CI 1.11-1.36). Upon histotype-specific examination, robust evidence emerged for an association of endometriosis with the risk of endometrioid carcinoma (OR 1.49, 95% CI 1.24-1.81), clear cell carcinoma (OR 2.56, 95% CI 1.75-3.73), and low malignant potential tumors (OR 1.28, 95% CI 1.08-1.53). These findings provide a theoretical framework for prospective investigations aimed at enhancing the potential therapeutic efficacy of managing endometriosis in averting the onset and progression of ovarian cancer.

Conditional inference in cis-Mendelian randomization using weak genetic factors

Mendelian randomization (MR) is a widely used method to estimate the causal effect of an exposure on an outcome by using genetic variants as instrumental variables. MR analyses that use variants from only a single genetic region (cis-MR) encoding the protein target of a drug are able to provide supporting evidence for drug target validation. This paper proposes methods for cis-MR inference that use many correlated variants to make robust inferences even in situations, where those variants have only weak effects on the exposure. In particular, we exploit the highly structured nature of genetic correlations in single gene regions to reduce the dimension of genetic variants using factor analysis. These genetic factors are then used as instrumental variables to construct tests for the causal effect of interest. Since these factors may often be weakly associated with the exposure, size distortions of standard t-tests can be severe. Therefore, we consider two approaches based on conditional testing. First, we extend results of commonly-used identification-robust tests for the setting where estimated factors are used as instruments. Second, we propose a test which appropriately adjusts for first-stage screening of genetic factors based on their relevance. Our empirical results provide genetic evidence to validate cholesterol-lowering drug targets aimed at preventing coronary heart disease.

Genetic variation in solute carrier family 5 member 2 mimicking sodium-glucose co-transporter 2-inhibition and risk of cardiovascular disease and all-cause mortality: reduced risk not explained by lower plasma glucose

AIMS

Treatment with sodium-glucose co-transporter 2 (SGLT2)-inhibitors reduces the risk of cardiovascular disease and mortality, but the mechanism is unclear. We hypothesized that a functional genetic variant in solute carrier family 5 member 2 (SLC5A2), known to be associated with familial renal glucosuria, would mimic pharmacological SGLT2-inhibition, and thus provide an opportunity to examine potential mediators of the effects on lower risk of cardiovascular disease and mortality.

METHODS AND RESULTS

We examined 112 712 individuals from the Copenhagen City Heart Study and Copenhagen General Population Study (CCHS + CGPS), 488 687 from the UK Biobank, and 342 499 from FinnGen, genotyped for SLC5A2 rs61742739, c.1961A > G; p.(Asn654Ser). The 2.0% heterozygotes and 0.01% homozygotes were pooled as carriers and compared with the 98% non-carriers. First, we examined the risk of cardiovascular disease and mortality; second, whether carrying the variant was associated with potential mediators of the effect; and third, whether identified potential mediators could explain the observed reduced risk of cardiovascular disease and mortality. In the CCHS + CGPS, carriers vs. non-carries had a 31% lower risk of heart failure, 21% lower risk of myocardial infarction, 16% lower risk of ischaemic heart disease, and 22% lower risk of all-cause mortality. Corresponding values in meta-analyses of the three studies combined were lower risk by 10%, 6%, 6%, and 10%, respectively. The SLC5A2 rs61742739 variant was not associated with a risk of ischaemic stroke or cardiovascular mortality. Of the lower risks observed in CCHS + CGPS, lower plasma glucose mediated 2.0%(P = 0.004) on heart failure, 3.1%(P = 0.09) on myocardial infarction, 4.1%(P = 0.02) on ischaemic heart disease, and 6.0%(P = 0.39) on all-cause mortality; corresponding values in the UK Biobank were 2.9%(P = 0.70), 1.5%(P = 0.77), 4.1%(P = 0.23), and 3.1%(P = 0.21), respectively.

CONCLUSION

A functional genetic variant in SLC5A2, mimicking SGLT2-inhibition, was associated with a lower risk of heart failure, myocardial infarction, ischaemic heart disease, and all-cause mortality. These effects were at most minimally mediated through lower plasma glucose.

Evaluating the causal association between microRNAs and amyotrophic lateral sclerosis

BACKGROUND

Currently, miRNAs are involved in the development of amyotrophic lateral sclerosis (ALS), and identifying circulating miRNAs that are causally associated with ALS risk as biomarkers is imperative.

METHODS

We performed a two-sample Mendelian randomization study to evaluate the causal relationship between miRNAs and ALS. Our analysis was conducted using summary statistics from miRNA expression quantitative loci (eQTL) data of the Framingham Heart Study and ALS genome-wide association studies data. Another independent miRNA data was used to further validate.

RESULTS

We identified eight unique miRNAs that were causally associated with ALS risk. Using expression data of miRNAs from an independent study, we validated three high-confidence miRNAs, namely hsa-miR-27b-3p, hsa-miR-139-5p, and hsa-miR-152-3p, which might have a potential causal effect on ALS risk.

CONCLUSION

We suggested that higher levels of hsa-miR-27b-3p and hsa-miR-139-5p had protective effects on ALS, whereas higher levels of hsa-miR-152-3p might act as a risk factor for ALS. The analytical framework presented in this study helps to understand the role of miRNAs in the development of ALS and to identify the biomarkers for ALS risk.

Genetically proxied antidiabetic drugs targets and stroke risk

BACKGROUND

Previous studies have assessed the association between antidiabetic drugs and stroke risk, but the results are inconsistent. Mendelian randomization (MR) was used to assess effects of antidiabetic drugs on stroke risk.

METHODS

We selected blood glucose-lowering variants in genes encoding antidiabetic drugs targets from genome-wide association studies (GWAS). A two-sample MR and Colocalization analyses were applied to examine associations between antidiabetic drugs and the risk of stroke. For antidiabetic agents that had effect on stroke risk, an independent blood glucose GWAS summary data was used for further verification.

RESULTS

Genetic proxies for sulfonylureas targets were associated with reduced risk of any stroke (OR=0.062, 95% CI 0.013-0.295, P=4.65×10－4) and any ischemic stroke (OR=0.055, 95% CI 0.010-0.289, P=6.25×10－4), but not with intracranial hemorrhage. Colocalization supported shared casual variants for blood glucose with any stroke and any ischemic stroke within the encoding genes for sulfonylureas targets (KCNJ11 and ABCC8) (posterior probability>0.7). Furthermore, genetic variants in the targets of insulin/insulin analogues, glucagon-like peptide-1 analogues, thiazolidinediones, and metformin were not associated with the risk of any stroke, any ischemic stroke and intracranial hemorrhage. The association was consistent in the analysis of sulfonylureas with stroke risk using an independent blood glucose GWAS summary data.

CONCLUSIONS

Our findings showed that genetic proxies for sulfonylureas targets by lowering blood glucose were associated with a lower risk of any stroke and any ischemic stroke. The study might be of great significance to guide the selection of glucose-lowering drugs in individuals at high risk of stroke.

An atlas of associations between 14 micronutrients and 22 cancer outcomes: Mendelian randomization analyses

BACKGROUND

Micronutrients, namely vitamins and minerals, are associated with cancer outcomes; however, their reported effects have been inconsistent across studies. We aimed to identify the causally estimated effects of micronutrients on cancer by applying the Mendelian randomization (MR) method, using single-nucleotide polymorphisms associated with micronutrient levels as instrumental variables.

METHODS

We obtained instrumental variables of 14 genetically predicted micronutrient levels and applied two-sample MR to estimate their causal effects on 22 cancer outcomes from a meta-analysis of the UK Biobank (UKB) and FinnGen cohorts (overall cancer and 21 site-specific cancers, including breast, colorectal, lung, and prostate cancer), in addition to six major cancer outcomes and 20 cancer subset outcomes from cancer consortia. We used sensitivity MR methods, including weighted median, MR-Egger, and MR-PRESSO, to assess potential horizontal pleiotropy or heterogeneity. Genome-wide association summary statistical data of European descent were used for both exposure and outcome data, including up to 940,633 participants of European descent with 133,384 cancer cases.

RESULTS

In total, 672 MR tests (14 micronutrients × 48 cancer outcomes) were performed. The following two associations met Bonferroni significance by the number of associations (P < 0.00016) in the UKB plus FinnGen cohorts: increased risk of breast cancer with magnesium levels (odds ratio [OR] = 1.281 per 1 standard deviation [SD] higher magnesium level, 95% confidence interval [CI] = 1.151 to 1.426, P < 0.0001) and increased risk of colorectal cancer with vitamin B12 level (OR = 1.22 per 1 SD higher vitamin B12 level, 95% CI = 1.107 to 1.345, P < 0.0001). These two associations remained significant in the analysis of the cancer consortia. No significant heterogeneity or horizontal pleiotropy was observed. Micronutrient levels were not associated with overall cancer risk.

CONCLUSIONS

Our results may aid clinicians in deciding whether to regulate the intake of certain micronutrients, particularly in high-risk groups without nutritional deficiencies, and may help in the design of future clinical trials.

A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records

BACKGROUND

The identification of new uses for existing drug therapies has the potential to identify treatments for comorbid conditions that have the added benefit of glycemic control while also providing a rapid, low-cost approach to drug (re)discovery.

METHODS

We developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically-predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug-gene pairs. These drug-gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR).

FINDINGS

After filtering on sample size, 20 candidate drug-gene pairs were validated and various medications demonstrated evidence of glycemic regulation including two anti-hypertensive classes: angiotensin-converting enzyme inhibitors as well as calcium channel blockers (CCBs). The CCBs demonstrated the strongest evidence of glycemic reduction in both validation approaches (SCCS HbA1c and glucose reduction: -0.11%, p = 0.01 and -0.85 mg/dL, p = 0.02, respectively; MR: OR = 0.84, 95% CI = 0.81, 0.87, p = 5.0 x 10-25).

INTERPRETATION

Our results support CCBs as a strong candidate medication for blood glucose reduction in addition to cardiovascular disease reduction. Further, these results support the adaptation of this approach for use in future drug-repurposing efforts for other conditions.

FUNDING

National Institutes of Health, Medical Research Council Integrative Epidemiology Unit at the University of Bristol, UK Medical Research Council, American Heart Association, and Department of Veterans Affairs (VA) Informatics and Computing Infrastructure and VA Cooperative Studies Program.

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.

The effects of blood pressure and antihypertensive drugs on heart failure: A Mendelian randomization study

BACKGROUND AND AIMS

Heart failure (HF) is often triggered by hypertension and can benefit from antihypertensive treatment. We aimed to investigate whether pulse pressure (PP) could independently raise the risk of HF beyond systolic blood pressure (SBP) and diastolic blood pressure (DBP), as well as explore the potential mechanisms of antihypertensives in HF prevention.

METHODS AND RESULTS

We generated genetic proxies for SBP, DBP, PP, and five drug classes based on a massive genome-wide association study. We applied two-sample Mendelian randomization (MR) using summary statistics derived from European individuals and conducted summary data-based MR (SMR) with gene expression data. In univariate analysis, PP showed an obvious association with HF risk (OR, 1.24 per 10 mm Hg increment; 95% CI, 1.16 to 1.32), which was largely attenuated in multivariable analysis when adjusted for SBP (0.89; 0.77 to 1.04). A significant decrease in HF risk was obtained with genetically proxied β-blockers (equivalent to a 10 mm Hg reduction in SBP, 0.71; 0.62 to 0.82) and calcium channel blockers (0.71; 0.65 to 0.78), but not with genetically proxied angiotensin-converting enzyme inhibitors (0.69; 0.40 to 1.19) and thiazide diuretics (0.80; 0.47 to 1.37). Additionally, the enrichment of expression for the KCNH2 gene, a target gene of β-blockers, in blood vessels and nerves was significantly associated with HF risk.

CONCLUSION

Our findings suggest that PP may not be an independent risk factor for HF. β-blockers and calcium channel blockers have a protective effect against HF, which at least partly depends on their blood pressure-lowering effect.

Genetically proxied impaired GIPR signaling and risk of 6 cancers

Preclinical and genetic studies suggest that impaired glucose-dependent insulinotropic polypeptide receptor (GIPR) signaling worsens glycemic control. The relationship between GIPR signaling and the risk of cancers influenced by impaired glucose homeostasis is unclear. We examined the association of a variant in GIPR, rs1800437 (E354Q), shown to impair long-term GIPR signaling and lower circulating glucose-dependent insulinotropic peptide concentrations, with risk of 6 cancers influenced by impaired glucose homeostasis (breast, colorectal, endometrial, lung, pancreatic, and renal) in up to 235,698 cases and 333,932 controls. Each copy of E354Q was associated with a higher risk of overall and luminal A-like breast cancer and this association was consistent in replication and colocalization analyses. E354Q was also associated with higher postprandial glucose concentrations but diminished insulin secretion and lower testosterone concentrations. Our human genetics analysis suggests an adverse effect of the GIPR E354Q variant on breast cancer risk, supporting further evaluation of GIPR signaling in breast cancer prevention.

Genetically predicted hypertension, antihypertensive drugs, and risk of erectile dysfunction: a Mendelian randomization study

Background

The causal relationship between hypertension, antihypertensive drugs and the risk of erectile dysfunction is still uncertain. We performed a univariable and multivariable Mendelian randomization study to investigate whether they are causally related to erectile dysfunction.

Methods

Genetic variants associated with blood pressure were derived from the genome-wide association study meta-analysis of the UK Biobank and International Consortium of Blood Pressure (N = 757,601). Summary association data for hypertension were obtained from the UK Biobank (N = 463,010) and the FinnGen study (N = 356,077). The summary statistics of erectile dysfunction were obtained from the European ancestry with 223,805 subjects. The SNP instruments used to assess the effect of the protein targets of antihypertensive drugs on erectile dysfunction were obtained from previous studys. Causal effects were estimated using the univariate Mendelian randomization method (inverse variance weighted, MR-Egger, weighted median, MR-PRESSO and Wald ratios) and the multivariate Mendelian randomization method. Sensitivity analyses were implemented with the Cochran's Q-test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis.

Results

Univariate MR found that elevated diastolic blood pressure may increase the occurrence of erectile dysfunction (odds ratio [OR] = 1.012; 95% confidence interval [CI]: 1.000-1.024; P = 0.047). Genetically predicted hypertension is also associated with ED (For the FinnGen, OR = 1.106; 95% CI: 1.027-1.191; P = 0.008. For the UK Biobank, OR = 3.832; 95% CI: 1.410-10.414; P = 0.008). However, after adjusting for systolic blood pressure, diastolic blood pressure and hypertension using multivariate Mendelian randomization, only hypertension was causally associated with ED occurrence (For the FinnGen, OR = 1.103; 95% CI: 1.018-1.195; P = 0.017. For the UK Biobank, OR = 5.037; 95% CI: 1.601-15.846; P = 0.006). We found no evidence that the use of angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and thiazide diuretic increased the risk of erectile dysfunction.

Conclusions

Genetically predicted hypertension increases the risk of erectile dysfunction, but we found no causal relationship between elevated systolic/diastolic blood pressure and erectile dysfunction. We speculate that the relationship between elevated blood pressure and erectile dysfunction risk may be nonlinear. We found little evidence that antihypertensive drugs increase the risk of erectile dysfunction.

Hypertension, antihypertensive drugs, and age at onset of Huntington's disease

BACKGROUND

Associations between blood pressure (BP) with age at onset of Huntington's disease (HD) have reported inconsistent findings. We used Mendelian randomization (MR) to assess effects of BP and lowering systolic BP (SBP) via the genes encoding targets of antihypertensive drugs on age at onset of HD.

METHODS

Genetic variants from genome-wide association studies(GWAS) of BP traits and BP-lowering variants in genes encoding antihypertensive drugs targets were extracted. Summary statistics for age at onset of HD were retrieved from the GWAS meta-analysis of HD residual age at onset from the GEM-HD Consortium included 9064 HD patients of European ancestry (4417 males and 4,647 females). MR estimates were calculated using the inverse variance weighted method, supplemented by MR-Egger, weighted median, and MR-PRESSO methods.

RESULTS

Genetically predicted SBP or diastolic BP increase was associated with a later age at onset of HD. However, after SBP/DBP was present as a covariate using multivariable MR method, no significant causal association was suggested. A 10-mm Hg reduction in SBP through variants in genes encoding targets of calcium channel blockers (CCB) was associated with an earlier age at onset of HD (β=-0.220 years, 95% CI =-0.337 to -0.102, P = 2.42 × 10^- 4). We did not find a causal association between angiotensin converting enzyme inhibitors and β-blockers with the earlier HD onset. No heterogeneity and horizontal pleiotropy were identified.

CONCLUSIONS

This MR analysis provided evidence that genetically determined SBP lowering through antihypertensive drugs might be associated with an earlier age at onset of HD. The results may have a potential impact on management of hypertension in the pre-motor-manifest HD population.

Repurposing antidiabetic drugs for rheumatoid arthritis: results from a two-sample Mendelian randomization study

Despite increasing therapeutic options to treat rheumatoid arthritis (RA), many patients fail to reach treatment targets. The use of antidiabetic drugs like thiazolidinediones has been associated with lower RA risk. We aimed to explore the repurposing potential of antidiabetic drugs in RA prevention by assessing associations between genetic variation in antidiabetic drug target genes and RA using Mendelian randomization (MR). A two-sample MR design was used to estimate the association between the antidiabetic drug and RA risk using summary statistics from genome-wide association studies (GWAS). We selected independent genetic variants from the gene(s) that encode the target protein(s) of the investigated antidiabetic drug as instruments. We extracted the associations of instruments with blood glucose concentration and RA from the UK Biobank and a GWAS meta-analysis of clinically diagnosed RA, respectively. The effect of genetic variation in the drug target(s) on RA risk was estimated by the Wald ratio test or inverse-variance weighted method. Insulin and its analogues, thiazolidinediones, and sulfonylureas had valid genetic instruments (n = 1, 1, and 2, respectively). Genetic variation in thiazolidinedione target (gene: PPARG) was inversely associated with RA risk (odds ratio [OR] 0.38 per 0.1mmol/L glucose lowering, 95% confidence interval [CI] 0.20-0.73). Corresponding ORs (95%CIs) were 0.83 (0.44-1.55) for genetic variation in the targets of insulin and its analogues (gene: INSR), and 1.12 (0.83, 1.49) 1.25 (0.78-2.00) for genetic variation in the sulfonylurea targets (gene: ABCC8 and KCNJ11). In conclusion, genetic variation in the thiazolidinedione target is associated with a lower RA risk. The underlying mechanisms warrant further exploration.

Genetic association of lipids and lipid-lowering drug target genes with non-alcoholic fatty liver disease

BACKGROUND

Some observational studies found that dyslipidaemia is a risk factor for non-alcoholic fatty liver disease (NAFLD), and lipid-lowering drugs may lower NAFLD risk. However, it remains unclear whether dyslipidaemia is causative for NAFLD. This Mendelian randomisation (MR) study aimed to explore the causal role of lipid traits in NAFLD and evaluate the potential effect of lipid-lowering drug targets on NAFLD.

METHODS

Genetic variants associated with lipid traits and variants of genes encoding lipid-lowering drug targets were extracted from the Global Lipids Genetics Consortium genome-wide association study (GWAS). Summary statistics for NAFLD were obtained from two independent GWAS datasets. Lipid-lowering drug targets that reached significance were further tested using expression quantitative trait loci data in relevant tissues. Colocalisation and mediation analyses were performed to validate the robustness of the results and explore potential mediators.

FINDINGS

No significant effect of lipid traits and eight lipid-lowering drug targets on NAFLD risk was found. Genetic mimicry of lipoprotein lipase (LPL) enhancement was associated with lower NAFLD risks in two independent datasets (OR₁ = 0.60 [95% CI 0.50-0.72], p₁ = 2.07 × 10^-8; OR₂ = 0.57 [95% CI 0.39-0.82], p₂ = 3.00 × 10^-3). A significant MR association (OR = 0.71 [95% CI, 0.58-0.87], p = 1.20 × 10^-3) and strong colocalisation association (PP.H₄ = 0.85) with NAFLD were observed for LPL expression in subcutaneous adipose tissue. Fasting insulin and type 2 diabetes mediated 7.40% and 9.15%, respectively, of the total effect of LPL on NAFLD risk.

INTERPRETATION

Our findings do not support dyslipidaemia as a causal factor for NAFLD. Among nine lipid-lowering drug targets, LPL is a promising candidate drug target in NAFLD. The mechanism of action of LPL in NAFLD may be independent of its lipid-lowering effects.

FUNDING

Capital's Funds for Health Improvement and Research (2022-4-4037). CAMS Innovation Fund for Medical Sciences (CIFMS, grant number: 2021-I2M-C&T-A-010).

Association of antihypertensive drugs with fracture and bone mineral density: A comprehensive drug-target Mendelian randomization study

Background

Observational studies have investigated the associations between antihypertensive drugs and fracture risk as well as bone mineral density (BMD), but yielding controversial results.

Methods

In this study, a comprehensive drug-target Mendelian randomization (MR) analysis was conducted to systematically examine the associations between genetic proxies for eight common antihypertensive drugs and three bone health-related traits (fracture, total body BMD [TB-BMD], and estimated heel BMD [eBMD]). The main analysis used the inverse-variance weighted (IVW) method to estimate the causal effect. Multiple MR methods were also employed to test the robustness of the results.

Results

The genetic proxies for angiotensin receptor blockers (ARBs) were associated with a reduced risk of fracture (odds ratio [OR] = 0.67, 95% confidence interval [CI]: 0.54 to 0.84; P = 4.42 × 10-4; P-adjusted = 0.004), higher TB-BMD (β = 0.36, 95% CI: 0.11 to 0.61; P = 0.005; P-adjusted = 0.022), and higher eBMD (β = 0.30, 95% CI: 0.21 to 0.38; P = 3.59 × 10-12; P-adjusted = 6.55 × 10-11). Meanwhile, genetic proxies for calcium channel blockers (CCBs) were associated with an increased risk of fracture (OR = 1.07, 95% CI: 1.03 to 1.12; P = 0.002; P-adjusted = 0.013). Genetic proxies for potassium sparing diuretics (PSDs) showed negative associations with TB-BMD (β = -0.61, 95% CI: -0.88 to -0.33; P = 1.55 × 10-5; P-adjusted = 1.86 × 10-4). Genetic proxies for thiazide diuretics had positive associations with eBMD (β = 0.11, 95% CI: 0.03 to 0.18; P = 0.006; P-adjusted = 0.022). No significant heterogeneity or pleiotropy was identified. The results were consistent across different MR methods.

Conclusions

These findings suggest that genetic proxies for ARBs and thiazide diuretics may have a protective effect on bone health, while genetic proxies for CCBs and PSDs may have a negative effect.

Assessing the association between white matter lesions and Parkinson's disease

BACKGROUND

The association between white matter (WM) lesions and Parkinson's disease (PD) was not fully established. We therefore applied Mendelian randomization (MR) analyses to identify the causal effect between white matter lesions and PD.

METHODS

We performed a bidirectional two-sample Mendelian randomization (MR) study to investigate the association between three WM phenotypes-white matter hyperintensities (WMH, N = 18,381), fractional anisotropy (FA, N = 17,673), and mean diffusivity (MD, N = 17,467)-with PD (N = 482,730) using summary statistics from genome-wide association studies (GWAS). The inverse variance weighted (IVW), weighted median, MR-Egger, and MR-PRESSO methods were used to evaluate the causal estimate.

RESULTS

Significant evidence was suggested that higher MD was associated with a higher PD risk (OR = 1.049, 95% CI = 1.018-1.081, p = 0.022) when the outlier was removed using MR-PRESSO method. Moreover, genetically predicted PD was associated with a lower WMH load (IVW β = - 0.047, 95% CI = - 0.085 to - 0.009, p = 0.016) and a higher FA (β = 0.185, 95% CI = 0.021-0.349, p = 0.027). No evidence of pleiotropy was found using MR-Egger intercept.

CONCLUSION

Our findings provided genetic support that white matter microstructural integrity lesions might increase the risk of PD. However, genetically predicted PD was potentially associated with a lower load of white matter lesions.

Inhibition of tumor necrosis factor receptor 1 and the risk of periodontitis

Aim

To investigate the effect of genetically proxied inhibition of tumor necrosis factor receptor 1 (TNFR1) on the risk of periodontitis.

Materials and methods

Genetic instruments were selected from the vicinity of TNFR superfamily member 1A (TNFRSF1A) gene (chromosome 12; base pairs 6,437,923-6,451,280 as per GRCh37 assembly) based on their association with C-reactive protein (N= 575,531). Summary statistics of these variants were obtained from a genome-wide association study (GWAS) of 17,353 periodontitis cases and 28,210 controls to estimate the effect of TNFR1 inhibition on periodontitis using a fixed-effects inverse method.

Results

Considering rs1800693 as an instrument, we found no effect of TNFR1 inhibition on periodontitis risk (Odds ratio (OR) scaled per standard deviation increment in CRP: 1.57, 95% confidence interval (CI): 0.38;6.46). Similar results were derived from a secondary analysis that used three variants (rs767455, rs4149570, and rs4149577) to index TNFR1 inhibition.

Conclusions

We found no evidence of a potential efficacy of TNFR1 inhibition on periodontitis risk.

Using human genetics to improve safety assessment of therapeutics

Human genetics research has discovered thousands of proteins associated with complex and rare diseases. Genome-wide association studies (GWAS) and studies of Mendelian disease have resulted in an increased understanding of the role of gene function and regulation in human conditions. Although the application of human genetics has been explored primarily as a method to identify potential drug targets and support their relevance to disease in humans, there is increasing interest in using genetic data to identify potential safety liabilities of modulating a given target. Human genetic variants can be used as a model to anticipate the effect of lifelong modulation of therapeutic targets and identify the potential risk for on-target adverse events. This approach is particularly useful for non-clinical safety evaluation of novel therapeutics that lack pharmacologically relevant animal models and can contribute to the intrinsic safety profile of a drug target. This Review illustrates applications of human genetics to safety studies during drug discovery and development, including assessing the potential for on- and off-target associated adverse events, carcinogenicity risk assessment, and guiding translational safety study designs and monitoring strategies. A summary of available human genetic resources and recommended best practices is provided. The challenges and future perspectives of translating human genetic information to identify risks for potential drug effects in preclinical and clinical development are discussed.

Genetically proxied therapeutic prolyl-hydroxylase inhibition and cardiovascular risk

Prolyl hydroxylase (PHD) inhibitors are in clinical development for anaemia in chronic kidney disease. Epidemiological studies have reported conflicting results regarding safety of long-term therapeutic haemoglobin (Hgb) rises through PHD inhibition on risk of cardiovascular disease. Genetic variation in genes encoding PHDs can be used as partial proxies to investigate the potential effects of long-term Hgb rises. We used Mendelian randomization to investigate the effect of long-term Hgb level rises through genetically proxied PHD inhibition on coronary artery disease (CAD: 60 801 cases; 123 504 controls), myocardial infarction (MI: 42 561 cases; 123 504 controls) or stroke (40 585 cases; 406 111 controls). To further characterize long-term effects of Hgb level rises, we performed a phenome-wide association study (PheWAS) in up to 451 099 UK Biobank individuals. Genetically proxied therapeutic PHD inhibition, equivalent to a 1.00 g/dl increase in Hgb levels, was not associated (at P < 0.05) with increased odds of CAD; odd ratio (OR) [95% confidence intervals (CI)] = 1.06 (0.84, 1.35), MI [OR (95% CI) = 1.02 (0.79, 1.33)] or stroke [OR (95% CI) = 0.91 (0.66, 1.24)]. PheWAS revealed associations with blood related phenotypes consistent with EGLN's role, relevant kidney- and liver-related biomarkers like estimated glomerular filtration rate and microalbuminuria, and non-alcoholic fatty liver disease (Bonferroni-adjusted P < 5.42E-05) but these were not clinically meaningful. These findings suggest that long-term alterations in Hgb through PHD inhibition are unlikely to substantially increase cardiovascular disease risk; using large disease genome-wide association study data, we could exclude ORs of 1.35 for cardiovascular risk with a 1.00 g/dl increase in Hgb.

Mendelian randomization study to investigate the causal relationship between plasma homocysteine and chronic obstructive pulmonary disease

BACKGROUND

Several observational studies have shown an association between homocysteine (Hcy) levels and chronic obstructive pulmonary disease (COPD), but causal relationships are not clear. Our study aimed to explore the causal relationship between plasma Hcy and COPD by two-sample Mendelian randomization (MR).

METHODS

A two-sample MR study was performed to infer the causal link. Genetically predicted plasma Hcy was selected as an instrumental variable (IV) from published genome-wide association study (GWAS) meta-analyses. COPD with different etiologies was extracted as outcome variables from other GWAS meta-analyses. The main MR analysis was performed using the inverse-variance weighted (IVW) method. Additional analyses were further performed using Cochran's Q-test and MR-Egger regression to evaluate the heterogeneity or horizontal pleiotropy of our findings.

RESULTS

MR analysis showed no significant association between plasma Hcy and COPD. The results of the groups were consistent with the sensitivity analysis and repeated analysis, without heterogeneity or horizontal pleiotropy. The IVW results showed COPD hospital admissions (odds ratio [OR] 1.06, 95% confidence interval [CI] 0.91-1.24, P=0.42), asthma/COPD (OR 0.97, 95% CI 0.89-1.06, P=0.55), COPD-related chronic infection (OR 1.50, 95% CI 0.57-3.99, P=0.41), COPD/asthma/interstitial lung disease (ILD)-related pneumonia or pneumonia-derived septicemia (OR 0.93, 95% CI 0.86-1.02, P=0.13), and COPD-related respiratory insufficiency (OR 1.00, 95% CI 0.7-1.44, P=0.99).

CONCLUSION

There is no direct causal relationship between plasma Hcy and COPD in our study. As Hcy is known to have deleterious effects on endothelial function and vascular homeostasis, further studies are needed to investigate whether additional factors mediate the association between Hcy and COPD.

Genome-wide association and Mendelian randomization study of fibroblast growth factor 21 reveals causal associations with hyperlipidemia and possibly NASH

BACKGROUND

Fibroblast growth factor 21 (FGF21) is a hepatokine that produces metabolic benefits, such as improvements of lipid profile. We performed a genome-wide association study (GWAS) to identify genetic variants associated with circulating FGF21 and investigated the causal effects of FGF21 on pertinent outcomes using Mendelian randomization (MR).

METHODS

We conducted a GWAS testing ∼7.8 million DNA sequence variants with circulating FGF21 in a discovery cohort of 6259 Swedish adults with replication in 4483 Swedish women. We then performed two-sample MR analyses of genetically predicted circulating FGF21 in relation to alcohol and nutrient intake, cardiovascular and metabolic biomarkers and diseases, and liver function biomarkers using publicly available GWAS summary statistics data.

RESULTS

Our GWAS identified multiple single-nucleotide polymorphisms with genome-wide significant associations (P < 5 × 10^-8) with circulating FGF21 on chromosomes 2 and 19 in or near the GCKR and FGF21 genes, respectively. The strongest signal at the FGF21 locus (rs2548957, β = 0.181, P < 2.18 × 10^-42) displayed in two-sample MR analyses robust associations with lower alcohol intake, lower circulating low-density lipoprotein cholesterol, apolipoprotein B, C-reactive protein, gamma-glutamyl transferase, and galectin-3 concentrations, and higher circulating insulin-like growth factor-I and alkaline phosphatase concentrations after correcting for multiple testing (P < 0.0018) whereas associations with fat mass, type 2 diabetes, and cardiovascular disease were largely null.

CONCLUSIONS

We identified robust associations of certain genetic variants in or near the GCKR and FGF21 genes with circulating FGF21 concentrations. Furthermore, our results support a strong causal effect of FGF21 on improved lipid profile, reduced alcohol consumption and C-reactive protein concentrations, and liver function biomarkers including fibrosis. We found largely null or weak positive associations with fat mass, diabetes, and cardiovascular disease as well as higher insulin-like growth factor-I concentrations, which could indicate a compensatory increase to regulate the above FGF21 resistant states in humans.

Genetic support of a causal relationship between iron status and atrial fibrillation: a Mendelian randomization study

Background

Atrial fibrillation is the most common arrhythmia disease. Animal and observational studies have found a link between iron status and atrial fibrillation. However, the causal relationship between iron status and AF remains unclear. The purpose of this investigation was to use Mendelian randomization (MR) analysis, which has been widely applied to estimate the causal effect, to reveal whether systemic iron status was causally related to atrial fibrillation.

Methods

Single nucleotide polymorphisms (SNPs) strongly associated (P < 5 × 10−8) with four biomarkers of systemic iron status were obtained from a genome-wide association study involving 48,972 subjects conducted by the Genetics of Iron Status consortium. Summary-level data for the genetic associations with atrial fibrillation were acquired from the AFGen (Atrial Fibrillation Genetics) consortium study (including 65,446 atrial fibrillation cases and 522,744 controls). We used a two-sample MR analysis to obtain a causal estimate and further verified credibility through sensitivity analysis.

Results

Genetically instrumented serum iron [OR 1.09; 95% confidence interval (CI) 1.02–1.16; p = 0.01], ferritin [OR 1.16; 95% CI 1.02–1.33; p = 0.02], and transferrin saturation [OR 1.05; 95% CI 1.01–1.11; p = 0.01] had positive effects on atrial fibrillation. Genetically instrumented transferrin levels [OR 0.90; 95% CI 0.86–0.97; p = 0.006] were inversely correlated with atrial fibrillation.

Conclusion

In conclusion, our results strongly elucidated a causal link between genetically determined higher iron status and increased risk of atrial fibrillation. This provided new ideas for the clinical prevention and treatment of atrial fibrillation.

Association between Genetically Proxied Inhibition of HMG-CoA Reductase and Age at Onset of Huntington’s Disease

Background: Previous studies have found that statins may play a potential role in the age at onset (AAO) of Huntington’s disease (HD). We performed this Mendelian randomization (MR) study to assess the association between genetically proxied inhibition of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase and low-density lipoprotein (LDL) cholesterol with age at onset of HD. Methods: Single-nucleotide polymorphisms (SNPs) in HMG-CoA reductase associated with LDL cholesterol in a genome-wide association study (GWAS) analysis were used. The summary data of residual AAO of HD were obtained from a GWAS meta-analysis (n = 9064 HD patients). MR estimates representing lifelong inhibition of drug targets were generated using random-effects inverse-variance weighted analysis. Results: Genetically proxied plasma LDL cholesterol (β = 0.039, 95% CI = −0.454 to 0.531) and HMG-CoA reductase inhibition equivalent to a 1 mmol/L (38.7 mg/dL) reduction in LDL cholesterol (β = −2.228, 95% CI = −4.830 to 0.374) were not associated with age at onset of HD. Conclusion: The plasma LDL cholesterol levels and the reduction of plasma LDL cholesterol levels by the inhibition of HMG-CoA reductase (i.e., statins) were not associated with the age of HD onset.

Evaluating the impact of metformin targets on the risk of osteoarthritis: a mendelian randomization study

OBJECTIVE

To provide some causal evidence concerning the effects of metformin on osteoarthritis (OA) using two metformin targets, namely AMP-activated protein kinase (AMPK) and growth differentiation factor 15 (GDF-15) as metformin proxies.

METHODS

This is a 2-sample Mendelian randomization design. We constructed 44 AMPK-related variants genetically predicted in HbA1c (%) as instruments for AMPK and five variants strongly predicted GDF-15 as instruments for GDF-15. Summary-level data for three OA phenotypes, including OA at any site, knee OA, and hip OA were obtained from the largest genome-wide meta-analysis across the UK Biobank and arcOGEN with 455,211 Europeans. Main analyses were conducted using the inverse-variance weighted method. Weighted median and MR-Egger were conducted as sensitivity analyses to assess the robustness of our results.

RESULTS

Genetically predicted AMPK were negatively associated with OA at any site (OR: 0.60; 95% CI: 0.43-0.83) and hip OA (OR: 0.42; 95% CI: 0.22-0.80), but with not knee OA (OR: 0.85; 95% CI: 0.49-1.50). Higher levels of genetically predicted GDF-15 reduced the risk of hip OA (OR: 0.95; 95% CI: 0.90-0.99), but not OA at any site (OR: 1.00; 95% CI: 0.98-1.02) and knee OA (OR: 1.02; 95% CI: 0.98-1.07).

CONCLUSION

This study indicates that AMPK and GDF-15 can be potential therapeutic targets for OA, especially for hip OA, and metformin would be repurposed for OA therapy which needs to be verified in randomized controlled trials.

Identification and single-base gene-editing functional validation of a cis-EPO variant as a genetic predictor for EPO-increasing therapies

Hypoxia-inducible factor prolyl hydroxylase inhibitors (HIF-PHIs) are currently under clinical development for treating anemia in chronic kidney disease (CKD), but it is important to monitor their cardiovascular safety. Genetic variants can be used as predictors to help inform the potential risk of adverse effects associated with drug treatments. We therefore aimed to use human genetics to help assess the risk of adverse cardiovascular events associated with therapeutically altered EPO levels to help inform clinical trials studying the safety of HIF-PHIs. By performing a genome-wide association meta-analysis of EPO (n = 6,127), we identified a cis-EPO variant (rs1617640) lying in the EPO promoter region. We validated this variant as most likely causal in controlling EPO levels by using genetic and functional approaches, including single-base gene editing. Using this variant as a partial predictor for therapeutic modulation of EPO and large genome-wide association data in Mendelian randomization tests, we found no evidence (at p < 0.05) that genetically predicted long-term rises in endogenous EPO, equivalent to a 2.2-unit increase, increased risk of coronary artery disease (CAD, OR [95% CI] = 1.01 [0.93, 1.07]), myocardial infarction (MI, OR [95% CI] = 0.99 [0.87, 1.15]), or stroke (OR [95% CI] = 0.97 [0.87, 1.07]). We could exclude increased odds of 1.15 for cardiovascular disease for a 2.2-unit EPO increase. A combination of genetic and functional studies provides a powerful approach to investigate the potential therapeutic profile of EPO-increasing therapies for treating anemia in CKD.

The Association of Serum Uric Acid Level, Gout, and Alzheimer's Disease: A Bidirectional Mendelian Randomization Study

BACKGROUND

The relationship between serum uric acid (UA) and Alzheimer's disease (AD) risk still remained ambiguous despite extensive attempts.

OBJECTIVE

Via the two-sample Mendelian randomization (MR) design, we aimed to examine the bidirectional causal relationships of serum UA, gout, and the risk of AD.

METHODS

Genetic variants of UA, gout, and AD were extracted from published genome-wide association summary statistics. The inverse-variance weighted (IVW, the primary method), and several sensitivity methods (MR-Egger, weighted median, and weighted mode) were used to calculate the effect estimates. Egger regression, MR-PRESSO and leave-one-SNP-out analysis were performed to identify potential violations.

RESULTS

Genetic proxies for serum UA concentration [odds ratio (ORIVW) = 1.09, 95% confidence interval (CI) = 1.01-1.19, p = 0.031] were related with an increased risk of AD using 25 single nucleotide polymorphisms (SNPs). This causal effect was confirmed by sensitivity analyses including MR-Egger (1.22, 1.06-1.42, p = 0.014), weighted median (1.18, 1.05-1.33, p = 0.006), and weighted mode (1.20, 1.07-1.35, p = 0.005) methods. No evidence of notable directional pleiotropy and heterogeneity were identified (p >  0.05). Three SNPs (rs2078267, rs2231142, and rs11722228) significantly drove the observed causal effects. Supportive causal effect of genetically determined gout on AD risk was demonstrated using two SNPs (ORIVW = 1.05, 95% CI = 1.00-1.11, p = 0.057). No reverse causal effects of AD on serum UA levels and gout risk were found.

CONCLUSION

The findings revealed a causal relationship between elevated serum UA level and AD risk. However, further research is still warranted to investigate whether serum UA could be a reliable biomarker and therapeutic target for AD.

Phenotypic Causal Inference Using Genome-Wide Association Study Data: Mendelian Randomization and Beyond

statistics for genome-wide association studies (GWAS) are increasingly available for downstream analyses. Meanwhile, the popularity of causal inference methods has grown as we look to gather robust evidence for novel medical and public health interventions. This has led to the development of methods that use GWAS summary statistics for causal inference. Here, we describe these methods in order of their escalating complexity, from genetic associations to extensions of Mendelian randomization that consider thousands of phenotypes simultaneously. We also cover the assumptions and limitations of these approaches before considering the challenges faced by researchers performing causal inference using GWAS data. GWAS summary statistics constitute an important data source for causal inference research that offers a counterpoint to nongenetic methods when triangulating evidence. Continued efforts to address the challenges in using GWAS data for causal inference will allow the full impact of these approaches to be realized.

Association Between C-Reactive Protein and Risk of Amyotrophic Lateral Sclerosis: A Mendelian Randomization Study

Background: Until now, the relationship between C-reactive protein (CRP) levels and amyotrophic lateral sclerosis (ALS) risk has not been fully established. It is necessary to assess whether there is a causal relationship between C-reactive protein levels and ALS risk. Objective and Methods: We aimed to determine whether CRP has causal effects on risk of ALS. In this present study, summary-level data for ALS (20,806 cases and 59,804 controls) was obtained from large analyses of genome-wide association studies. For instrumental variables, 37 single nucleotide polymorphisms that had been previously identified to be related to CRP levels were used, including 4 SNPs of conservative CRP genetic variants and 33 SNPs of liberal CRP genetic variants. MR estimates were calculated using the inverse-variance weighted method, supplemented by MR-Egger, weighted median, and MR-PRESSO methods. Results: There was no significant causal relationship between genetically predicted CRP levels and ALS risk (OR = 1.123, 95% CI = 0.963-1.309, p = 0.139) and results for the conservative CRP instruments were consistent (OR = 0.964, 95% CI = 0.830-1.119, p = 0.628). Pleiotropic bias was not observed in this study. Conclusions: This study suggests that genetically predicted CRP levels may not be a causal risk factor for ALS.

Robust inference of bi-directional causal relationships in presence of correlated pleiotropy with GWAS summary data

To infer a causal relationship between two traits, several correlation-based causal direction (CD) methods have been proposed with the use of SNPs as instrumental variables (IVs) based on GWAS summary data for the two traits; however, none of the existing CD methods can deal with SNPs with correlated pleiotropy. Alternatively, reciprocal Mendelian randomization (MR) can be applied, which however may perform poorly in the presence of (unknown) invalid IVs, especially for bi-directional causal relationships. In this paper, first, we propose a CD method that performs better than existing CD methods regardless of the presence of correlated pleiotropy. Second, along with a simple but yet effective IV screening rule, we propose applying a closely related and state-of-the-art MR method in reciprocal MR, showing its almost identical performance to that of the new CD method when their model assumptions hold; however, if the modeling assumptions are violated, the new CD method is expected to better control type I errors. Notably bi-directional causal relationships impose some unique challenges beyond those for uni-directional ones, and thus requiring special treatments. For example, we point out for the first time several scenarios where a bi-directional relationship, but not a uni-directional one, can unexpectedly cause the violation of some weak modeling assumptions commonly required by many robust MR methods. We also offer some numerical support and a modeling justification for the application of our new methods (and more generally MR) to binary traits. Finally we applied the proposed methods to 12 risk factors and 4 common diseases, confirming mostly well-known uni-directional causal relationships, while identifying some novel and plausible bi-directional ones such as between body mass index and type 2 diabetes (T2D), and between diastolic blood pressure and stroke.

Inferring causal relationships between two traits based on observational data is one of the most important as well as challenging problems in scientific research. The potential impact of such an application on and beyond genetics/genomics is significant, such as in prioritizing molecular, clinical and behavioral targets for therapeutic and behavioral interventions. However, this problem, especially on a possibly bi-directional causal relationship between a pair of traits (in which the causal direction may be from either trait to the other, and both causal directions may be present at the same time), had been largely neglected until very recently. The increasing availability of large-scale GWAS summary data of various traits has popularized the development and application of Mendelian randomization (MR) methods for such a purpose. We point out some severe limitations with the current methods, mainly due to some new and unique challenges facing inference of bi-directional relationships as compared to that of uni-directional relationships that has been more commonly and exclusively considered in MR. By combining two basic ideas of bidirectional (or reciprocal) MR and Steiger’s correlation-based screening methods, we develop two new approaches based on constrained maximum likelihood (cML) and GWAS summary data to infer causal effects (as in typical MR) and SNP-trait correlations (as in Steiger’s method), called MR-cML and CD-cML respectively, demonstrating their similar effectiveness and more importantly their advantages over existing methods through extensive simulations, real data examples and statistical theory. In particular, our proposed two methods are robust to violations of all three valid IV assumptions, including presence of correlated pleiotropy.

Mendelian randomization in pharmacogenomics: The unforeseen potentials

Mendelian randomization (MR) is an epidemiological method that uses genetic variants to proxy an exposure predicting its causal association with an outcome. It occupies a valuable niche between observational studies and randomized trials. MR applications expanded lately, facilitated by the availability of big data, to include disease risk causation prediction, supporting evidence of prior observational data, identifying new drug targets, and drug repurposing. Concurrently, the last decade witnessed the growth of pharmacogenomics (PGx) research as a cornerstone in precision medicine. PGx research, conducted at discovery and implementation levels, resulted in validated PGx biomarkers and tests. Despite many clinically relevant PGx associations that could be translated into clinical applications, worldwide implementation is lagging far behind. The current review examines the intersection zones between MR and PGx research. MR can provide supporting evidence that allows generalizing PGx findings supporting its implementation. Interchangeability, PGx research can fuel MR studies with libraries of genetic variants of validated biological relevance. Furthermore, PGx and MR exhibit a synergistic relationship in drug discovery that can accelerate identifying new targets and repurposing old drugs. Interdisciplinary research applied by PGx researchers, epidemiologists with MR experience, and data scientists' collaborations can unlock unforeseen opportunities in accelerating precision medicine acquisition.

Mendelian Randomization Study of Heart Failure and Stroke Subtypes

Background

Whether heart failure (HF) is an independent risk factor of ischemic stroke (IS) and hemorrhagic stroke remains controversial. We employed a multivariable Mendelian randomization (MR) to further investigate the causal effects of HF on the risk of stroke and stroke subtypes.

Methods

Genetically predicted HF was selected as an instrumental variable (IV) from published genome-wide association studies (GWAS) meta-analyses. Stroke data with different etiologies were extracted as outcome variables from another two GWAS meta-analyses. The random-effects inverse variance-weighted (IVW) model was applied as the main method, along with sensitivity analysis. Atrial fibrillation (AF), coronary heart disease (CHD), and systolic blood pressure (SBP) were controlled for mediating effects in multivariable MR.

Results

Genetically predicted HF was significantly associated with any IS [odds ratio (OR), 1.39; 95% CI, 1.12–1.74; p = 0.03], large artery stroke (LAS; OR, 1.84; 95% CI, 1.27–2.65; p = 0.001), and cardioembolic stroke (CES; OR, 1.73; 95% CI, 1.21–2.47; p = 0.003), but without small vessel stroke (SVS; OR, 1.1; 95% CI, 0.80–1.52; p = 0.56) and intracerebral hemorrhage (ICH; OR, 0.86; 95% CI, 0.41–1.83; p = 0.699) in univariable MR. However, these significant associations were attenuated to the null after adjusting for confounding factor in multivariable MR.

Conclusion

There was no direct causal association between HF and stroke in our study. The association between HF and IS can be driven by AF, CHD, and SBP.