Caution against examining the role of reverse causality in Mendelian Randomization

Investigating the association between blood metabolites and telomere length: A mendelian randomization study

BACKGROUND

Telomere length refers to the protective cap at the end of chromosomes, and it plays a crucial role in many diseases. The objective of this study is to explore the relationship between blood metabolites and telomere length, aiming to identify novel biological factors that influence telomere length.

METHODS

In this study, we extracted genome-wide association study (GWAS) data for blood metabolites from a sample of 7824 Europeans. Additionally, GWAS data for telomere length were obtained from the Open GWAS database (GWAS ID: ieu-b-4879). The primary analysis of this study utilized the random inverse variance weighted (IVW) method. Complementary analyses were also conducted using the MR-Egger and weighted median approaches. Sensitivity analyses were performed to assess the robustness of the findings. These included the Cochran Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis. To investigate the possibility of reverse causation, reverse MR analysis was conducted. Additionally, multivariable MR was utilized to evaluate the direct effect of metabolites on telomere length.

RESULTS

The results suggested a potential association between 15-methylpalmitate, taurocholate, levulinate, and X-12712 and telomere length. MVMR analysis further showed that 15-methylpalmitate, taurocholate, and levulinate can directly influence telomere length, regardless of other metabolites.

CONCLUSIONS

This study suggests that 15-methylpalmitate, taurocholate, and levulinate are likely factors correlated with telomere length. These findings will contribute to the development of strategies for protecting telomeres, preventing related diseases, and establishing a new biological foundation for achieving healthy aging.

Potential drug targets for gastroesophageal reflux disease and Barrett's esophagus identified through Mendelian randomization analysis

Gastroesophageal reflux disease (GERD) is a prevalent chronic ailment, and present therapeutic approaches are not always effective. This study aimed to find new drug targets for GERD and Barrett's esophagus (BE). We obtained genetic instruments for GERD, BE, and 2004 plasma proteins from recently published genome-wide association studies (GWAS), and Mendelian randomization (MR) was employed to explore potential drug targets. We further winnowed down MR-prioritized proteins through replication, reverse causality testing, colocalization analysis, phenotype scanning, and Phenome-wide MR. Furthermore, we constructed a protein-protein interaction network, unveiling potential associations among candidate proteins. Simultaneously, we acquired mRNA expression quantitative trait loci (eQTL) data from another GWAS encompassing four different tissues to identify additional drug targets. Meanwhile, we searched drug databases to evaluate these targets. Under Bonferroni correction (P < 4.8 × 10-5), we identified 11 plasma proteins significantly associated with GERD. Among these, 7 are protective proteins (MSP, GPX1, ERBB3, BT3A3, ANTR2, CCM2, and DECR2), while 4 are detrimental proteins (TMEM106B, DUSP13, C1-INH, and LINGO1). Ultimately, C1-INH and DECR2 successfully passed the screening process and exhibited similar directional causal effects on BE. Further analysis of eQTLs highlighted 4 potential drug targets, including EDEM3, PBX3, MEIS1-AS3, and NME7. The search of drug databases further supported our conclusions. Our study indicated that the plasma proteins C1-INH and DECR2, along with 4 genes (EDEM3, PBX3, MEIS1-AS3, and NME7), may represent potential drug targets for GERD and BE, warranting further investigation.

Investigating the Causal Relationship Between Sleep Behaviors and Primary Open-Angle Glaucoma: A Bidirectional Two-Sample Mendelian Randomization Study

Background

Although previous studies of sleep-related behaviors in relation to primary open-angle glaucoma (POAG) have been noted, the causal relationship remains unclear. The purpose of our present study was to investigate the relationships of genetically predicted sleep traits with POAG using a two-sample bidirectional Mendelian randomization (MR) method.

Methods

Summary-level data collected from publicly available genome-wide association studies (GWAS) of European decent were applied for the bidirectional MR analysis. After quality control steps, independent single-nucleotide polymorphisms for eight sleep behaviors and POAG were selected as the genetic instruments. The inverse-variance weighted (IVW) approach was adopted as the primary method, which was complemented by a series of sensitivity analyses to assess the robustness of the results by estimating heterogeneity and pleiotropy. Multivariable MR (MVMR) was used to assess the direct effect of sleep traits on POAG, after adjusting for several confounding factors.

Results

Our investigation revealed a positive correlation between genetically predicted ease of getting up in the morning and sleep duration and POAG using the IVW method (odds ratio (OR)=1.78, 95% confidence interval (CI):1.29-2.46, P = 4.33× 10-4; OR = 1.66, 95% CI:1.18-2.34, P = 3.38×10-3, respectively). Other supplementary MR methods also confirmed similar results. Moreover, the MVMR results also revealed that the adverse effects of these two sleep traits on POAG persisted after adjusting for body mass index, smoking, drinking, and education (all P < 0.05). Conversely, the relationships between genetic liability of POAG and different sleep behaviors were not statistically significant in the reverse-direction MR estimate (all P > 0.05).

Conclusion

Our study demonstrated that genetic prediction of getting up easily in the morning or sleep duration were associated with a higher risk of POAG, but not vice versa, in a European population. Further validation and clinical interventions are required to offer potential strategies to prevent and manage POAG.

Association of Genetic Polymorphisms in Long Noncoding RNA HOTTIP with Risk of Idiopathic Recurrent Spontaneous Abortion

The clustered homeobox gene family known as the Hox family plays a fundamental role in the morphogenesis of the vertebrate's embryo. A long noncoding RNA (lncRNA), known as HOTTIP (HOXA transcript at the distal tip), has been functionally characterized and contributed to the pathogenesis of various conditions. The current case-control study was undertaken to examine the gene frequencies and shared alleles of the HOTTIP  gene in Iranian participants with or without idiopathic recurrent spontaneous abortion (RSA). Both ARMS-PCR reaction and RFLP-PCR techniques were employed to detect three HOTTIP polymorphisms (rs2023843C/T, rs78248039A/T, and rs1859168C/A) in a DNA sample of 161 women with RSA and 177 healthy women. We found that the TT genotype of the HOTTIP rs2023843 C/T polymorphism was associated with a lower risk for idiopathic RSA. In contrast, the TT genotype of the HOTTIP rs78248039 A/T polymorphism was correlated with an enhanced risk of RSA. The presence of the A-allele for HOTTIP rs1859168 C/A polymorphism was associated with an increased risk for idiopathic RSA. Haplotype analysis showed that the T/T/A, C/T/A, T/T/C, and T/A/A haplotypes of rs2023843/rs78248039/rs1859168 enhanced RSA susceptibility. Computational analysis predicted that this lncRNA might act as a potential sponge for some microRNAs; therefore, affecting the expression of genes being targeted by them. In addition, both rs2023843 and rs1859168 variants could alter the local secondary structure of HOTTIP. Our results showed that HOTTIP rs2023843C/T, rs78248039A/T, and rs1859168C/A polymorphisms may confer genetic susceptibility to idiopathic RSA in an Iranian population.

Identification of potential drug targets for varicose veins: a Mendelian randomization analysis

Introduction

Varicose veins are a common chronic disease that creates a significant economic burden on the healthcare system. Current treatment options, including pharmacological treatments, are not always effective, and there is a need for more targeted therapies. A Mendelian randomization (MR) method uses genetic variants as instrumental variables to estimate the causal effect of an exposure on an outcome, and it has been successful in identifying therapeutic targets in other diseases. However, few studies have used MR to explore potential protein drug targets for varicose veins.

Methods

To identify potential drug targets for varicose veins of lower extremities, we undertook a comprehensive screen of plasma protein with a two-sample MR method. We used recently reported cis-variants as genetic instruments of 2,004 plasma proteins, then applied MR to a recent meta-analysis of genome-wide association study on varicose veins (22,037 cases and 437,665 controls). Furthermore, pleiotropy detection, reverse causality testing, colocalization analysis, and external replication were utilized to strengthen the causal effects of prioritized proteins. Phenome-wide MR (PheW-MR) of the prioritized proteins for the risk of 525 diseases was conducted to screen potential side effects.

Results

We identified eight plasma proteins that are significantly associated with the risk of varicose veins after Bonferroni correction (P < 2.495 × 10^-5), with five being protective (LUM, POSTN, RPN1, RSPO3, and VAT1) and three harmful (COLEC11, IRF3, and SARS2). Most identified proteins showed no pleiotropic effects except for COLLEC11. Bidirectional MR and MR Steiger testing excluded reverse causal relationship between varicose veins and prioritized proteins. The colocalization analysis indicated that COLEC11, IRF3, LUM, POSTN, RSPO3, and SARS2 shared the same causal variant with varicose veins. Finally, seven identified proteins replicated with alternative instruments except for VAT1. Furthermore, PheW-MR revealed that only IRF3 had potential harmful adverse side effects.

Conclusions

We identified eight potential causal proteins for varicose veins with MR. A comprehensive analysis indicated that IRF3, LUM, POSTN, RSPO3, and SARS2 might be potential drug targets for varicose veins.

Can Intelligence Affect Alcohol-, Smoking-, and Physical Activity-Related Behaviors? A Mendelian Randomization Study

People with high levels of intelligence are more aware of risk factors, therefore choosing a healthier lifestyle. This assumption seems reasonable, but is it true? Previous studies appear to agree and disagree. To cope with the uncertainty, we designed a mendelian randomization (MR) study to examine the causal effects of genetically proxied intelligence on alcohol-, smoking-, and physical activity (PA)-related behaviors. We obtained genome-wide association study (GWAS) datasets concerning these variables from separate studies or biobanks and used inverse-variance weighted (IVW) or MR-Egger estimator to evaluate the causal effects according to an MR protocol. The MR-Egger intercept test, MR-PRESSO, and funnel plots were employed for horizontal pleiotropy diagnosis. The Steiger test (with reliability test), Cochran's Q test, MR-PRESSO, and leave-one-out method were employed for sensitivity analysis. We found significant or potential effects of intelligence on alcohol dependence (OR = 0.749, p = 0.003), mental and behavioral disorders due to alcohol (OR = 0.814, p = 0.009), smoking (OR = 0.585, p = 0.005), and smoking cessation (OR = 1.334, p = 0.001). Meanwhile, we found significant or potential effects on walking duration (B = -0.066, p < 0.001), walking frequency (B = -0.055, p = 0.031), moderate PA frequency (B = -0.131, p < 0.001), and vigorous PA frequency (B = -0.070, p = 0.001), but all in a negative direction. In conclusion, our findings reinforce some existing knowledge, indicate the complexity of the health impacts of human intelligence, and underline the value of smoking and alcohol prevention in less intelligent populations. Given the existing limitations in this study, particularly the potential reverse causality in some estimations, re-examinations are warranted in future research.

Genetically predicted higher educational attainment decreases the risk of stroke: a multivariable Mendelian randomization study

Background

The causal association between educational attainment (EA) and stroke remains unclear. Hence, a novel multivariable Mendelian randomization (MVMR) approach was applied to solve this issue.

Methods

The single nucleotide polymorphisms (SNPs) from a recent genome-wide association study (GWAS) on years of schooling served as instruments. Univariable mendelian randomization (MR) and MVMR analyses were performed to detect the relationship between genetically predicted EA and the stroke risk. In the MVMR, cigarette consumption, alcohol consumption, body mass index (BMI), intelligence, and hypertension were adjusted. The summary statistics for stroke from the MEGASTROKE consortium included 446,696 participants (40,585 cases of stroke and 34,217 cases of ischemic stroke), most of whom were of European descent.

Results

In the univariable MR, genetically predicated EA could decrease the risks of total stroke (OR = 0.66, 95% CI 0.61–0.72, P = 2.70 × 10^–23), ischemic stroke (OR = 0.67, 95% CI 0.61–0.73, P = 2.58 × 10^–18), large artery atherosclerosis (OR = 0.51, 95% CI 0.40–0.64, P = 1.80 × 10^–8), small vessel stroke (OR = 0.60, 95% CI 0.49–0.73, P = 5.59 × 10^–7), and cardioembolic stroke (OR = 0.81, 95% CI 0.68–0.96, P = 1.46 × 10^–2) using the inverse-variance weighted (IVW) estimator. Higher EA might be negatively correlated with the odds of total stroke (OR = 0.62, 95% CI 0.50–0.77, P = 1.44 × 10^–5), ischemic stroke (OR = 0.63, 95% CI 0.50–0.80, P = 1.41 × 10^–4), and cardioembolic stroke (OR = 0.59, 95% CI 0.39–0.90, P = 0.01), but was not significant in large artery atherosclerosis (OR = 0.65, 95% CI 0.37–1.15, P = 0.14) and small vessel stroke (OR = 0.68, 95% CI 0.41–1.13, P = 0.14) after controlling other exposures.

Conclusions

We found that genetically predicated higher EA decreased the risks of total stroke, ischemic stroke, and cardioembolic stroke, independent of smoking, alcohol consumption, BMI, intelligence, and hypertension.

Caution against examining the role of reverse causality in Mendelian Randomization

Recently, Mendelian Randomization (MR) has gained in popularity as a concept to assess the causal relationship between phenotypes in genetic association studies. An extension of standard MR methodology, the MR Steiger approach, has recently been developed to infer the causal direction between two phenotypes in prospective studies. Through simulation studies, we examined and quantified the ability of the MR Steiger approach to determine the causal direction between two phenotypes (i.e., effect direction). Through simulation studies, our results show that the MR Steiger approach may fail to correctly identify the direction of causality. This is true, especially in the presence of pleiotropy. We also applied the MR Steiger method to the COPDGene study, a case-control study of chronic obstructive pulmonary disease (COPD) in current and former smokers, to examine the role of smoking on lung function. We have created an R package on Github called reverseDirection which runs simulations for user-specified scenarios to examine when the MR Steiger approach can correctly determine the causal direction between two phenotypes in any user specified scenario. In summary, our results emphasize the importance of caution when the MR Steiger approach is used in to infer the direction of causality.