Usefulness of Mendelian randomization in observational epidemiology

Diet-derived circulating antioxidants and risk of epilepsy: a Mendelian randomization study

Background

Previous studies suggest a link between diet-derived circulating antioxidants and epilepsy, but the causal relationship is unclear. This study aims to investigate the causal effect of these antioxidants on epilepsy.

Methods

To assess the causal link between dietary antioxidants and epilepsy risk, we conducted a two-sample Mendelian randomization (MR) analysis. This involved examining antioxidants such as zinc, selenium, α- and γ-tocopherol, vitamin A (retinol), vitamin C (ascorbate), and vitamin E (α-tocopherol). We utilized instrumental variables (IVs) which were genetic variations highly associated with these commonly used antioxidants. Exposure data were sourced from a comprehensive genome-wide association study (GWAS). We aggregated data from the International League Against Epilepsy (ILAE) Consortium sample, which included various types of epilepsy, as an outcome variable. Finally, we applied the inverse variance weighting method and conducted sensitivity analyses for further validation.

Results

Based on the primary MR estimates and subsequent sensitivity analyses, the inverse variance weighting (IVW) method revealed that a genetically predicted increase in zinc per standard deviation was positively associated with three types of epilepsy. This includes all types of epilepsy (OR = 1.06, 95% CI: 1.02-1.11, p = 0.008), generalized epilepsy (OR = 1.13, 95% CI: 1.01-1.25, p = 0.030), and focal epilepsy (documented hippocampal sclerosis) (OR = 1.01, 95% CI: 1.00-1.02, p = 0.025). However, there is no evidence indicating that other antioxidants obtained from the diet affect the increase of epilepsy either positively or negatively.

Conclusion

Our research indicates that the risk of developing epilepsy may be directly linked to the genetic prediction of zinc, whereas no such association was found for other antioxidants.

Unhealthy lifestyle factors and the risk of colorectal cancer: a Mendelian randomization study

The purpose of this study was to investigate the causal association between unhealthy lifestyle style factors and the risk of colorectal cancer, with the aim of preventing the occurrence of colorectal cancer by modifying unhealthy lifestyles. A two-sample Mendelian randomization (MR) approach was employed in this study, utilizing the inverse-variance weighted method as the primary research method. This MR analysis analyzed data of 3022 colorectal cancer cases and 174,006 controls from the FinnGen database. Single nucleotide polymorphisms (SNPs) associated with unhealthy lifestyle factors were selected as instrumental variables (IVs), including two obesity-related indicators, BMI (body mass index) and WHR (waist-to-hip ratio). Four phenotypes of smoking (smoking initiation, ever smoked, smoking per day, smoking cessation) and one phenotype of alcohol consumption (drinks per week). Four phenotypes of physical activity (accelerometer-based physical activity, moderate-to-vigorous physical activity, vigorous physical activity, strenuous sports or other exercises). All SNPs were obtained from published genome-wide association studies. The study found that the obesity-related indicator, higher WHR (OR = 1.38, 95% CI 1.12-1.70; P = 0.002) were associated with an increased risk of colorectal cancer, and two smoking phenotypes, cigarettes per day(OR = 1.30, 95% CI 1.01-1.68; P = 0.042)and smoking initiation (OR = 3.48, 95% CI 1.15-10.55; P = 0.028), were potentially associated with an increased risk of colorectal cancer. However, there was no evidence to suggest that physical activities and alcohol consumption were associated with colorectal cancer (all p > 0.05). In addition, the study detected no pleiotropy (all p > 0.05). This MR analysis indicates a causal association between a higher waist-to-hip ratio and the risk of colorectal cancer and a suggestive association between smoking and the risk of colorectal cancer among Europeans. These findings contribute to the understanding of the etiology of colorectal cancer and have potential implications for its prevention.

Causal relationship between genetically determined plasma metabolites and skin cancer: a two-sample Mendelian randomization study

We aimed to unveil the underlying pathogenic mechanisms of skin cancer in relation to metabolic factors and pathway mechanisms. This study utilized the TwoSample Mendelian randomization (MR) method to investigate the causal relationship between 1400 plasma metabolites and skin cancer. The primary method employed was the inverse variance weighting (IVW). Through IVW analysis, we found 105 plasma metabolites associated with Basal Cell Carcinoma (BCC), with the highest association observed for Prolylglycine levels (OR [95% CI]: 1.1902 [1.0274, 1.3788]). For Malignant Melanoma of Skin (MSS), 68 plasma metabolites were linked, with the highest causal relationship seen for 3-Hydroxybutyrate levels (OR [95% CI]: 1.0030 [1.0013, 1.0048]). Regarding actinic keratosis (AK), and the highest association observed for Hexadecadienoate (16:2n6) levels (OR [95% CI]: 1.3302 [1.0333, 1.7125]). Glycerol to palmitoylcarnitine (16: n6) levels (OR [95% CI]: 1.3302 [1.0333, 1.125]) were found to be significant for BCC and AK. Palmitoylcarnitine (C16) had the most positive causal effect for BCC (OR [95% CI]: 1.1777 [1.0493, 1.3218]), while 5-hydroxy-2-methylpyridine sulfate levels had the highest effect for AK (OR [95% CI]: 1.1788 [1.0295, 1.3498]). And 4-guanidinobutanoate levels had the largest positive causal effect (OR [95% CI]: 1.0857 [1.0417, 1.1317]) for BCC, and X-11880 levels for MSS (OR [95% CI]: 1.0013 [1.0000, 1.0025]). The study revealed a positive association between hereditary Glycerol to palmitoylcarnitine (C16) and 5-hydroxy-2-methylpyridine sulfate levels with the risk of developing BCC and AK. Additionally, 4-guanidinobutanoate levels and X 11880 levels were found to be positively associated with the risk of BCC and MMS.

Do testosterone and sex hormone-binding globulin affect cancer risk? A Mendelian randomization and bioinformatics study

Using Mendelian Randomization (MR) and large-scale Genome-Wide Association Study (GWAS) data, this study aimed to investigate the potential causative relationship between testosterone and sex hormone-binding globulin (SHBG) levels and the onset of several cancers, including pathway enrichment analyses of single nucleotide polymorphisms (SNPs) associated with cancer allowed for a comprehensive bioinformatics approach, which offered a deeper biological understanding of these relationships. The results indicated that increased testosterone levels in women were associated with a higher risk of breast and cervical cancers but a lower risk of ovarian cancer. Conversely, increased testosterone was linked to lower stomach cancer risk for men, whereas high SHBG levels were related to decreased risks of breast and prostate cancers. The corresponding genes of the identified SNPs, as revealed by pathway enrichment analysis, were involved in significant metabolic and proliferative pathways. These findings emphasize the need for further research into the biological mechanisms behind these associations, paving the way for potential targeted interventions in preventing and treating these cancers.

Mendelian randomization studies of depression: evidence, opportunities, and challenges

BACKGROUND

Major depressive disorder (MDD) poses a significant social and economic burden worldwide. Identifying exposures, risk factors, and biological mechanisms that are causally connected to MDD can help build a scientific basis for disease prevention and development of novel therapeutic approaches.

METHODS

In this systematic review, we assessed the evidence for causal relationships between putative causal risk factors and MDD from Mendelian randomization (MR) studies, following PRISMA. We assessed methodological quality based on key elements of the MR design: use of a full instrumental variable analysis and validation of the three key MR assumptions.

RESULTS

We included methodological details and results from 52 articles. A causal link between lifestyle, metabolic, inflammatory biomarkers, particular pathological states and MDD is supported by MR investigations, although results for each category varied substantially.

CONCLUSIONS

While this review shows how MR can offer useful information for examining prospective treatment targets and better understanding the pathophysiology of MDD, some methodological flaws in the existing literature limit reliability of results and probably underlie their heterogeneity. We highlight perspectives and recommendations for future works on MR in psychiatry.

Allergic Rhinitis and Cancer Risk: A Two-Sample Mendelian Randomization Study

Background: There is increasing evidence that allergic rhinitis (AR) is associated with cancer. However, these results are inconsistent. Because of common risk factors, there may be reverse causality and confounding factors that affect our understanding of the relationship between AR and cancer. We aimed to explore the role of AR in cancer development using Mendelian randomization (MR) analysis. Materials and Methods: We performed a two-sample MR analysis using summary data from genome-wide association studies (GWAS). Single nucleotide polymorphisms (SNPs) strongly associated with AR (or hay fever) were used as instrumental variables, mainly using the inverse variance weighted analysis method, supplemented by MR Egger, maximum likelihood, weighted media, and penalized weighted media for MR analysis. Sensitivity analyses included heterogeneity and horizontal pleiotropy; and leave-one-out analyses were performed to test the robustness of our results. Results: MR analysis revealed no evidence of a causal relationship between AR and any of the examined cancers (all p > 0.05). The results using five different analytical approaches were similar. Sensitivity analyses showed no evidence of heterogeneity nor horizontal pleiotropy. According to the leave-one-out sensitivity analyses, no individual SNP was significantly influencing the causal effect of AR on cancers. Conclusions: These findings do not provide evidence to support that AR has a large impact on the risk of eight common cancers in the European population. However, we cannot rule out a very minor effect of AR on cancer. Further large-scale studies are necessary to validate our findings.

Genetically predicted circulating serum homocysteine levels on osteoporosis: a two-sample mendelian randomization study

To investigate the causal relationship between circulating serum homocysteine (Hcy) levels and osteoporosis (OP). Using public datasets gathered from independently published genome-wide association studies (GWAS), Mendelian randomization (MR) analysis was done to investigate the causal influence of Hcy on OP. SNPs were selected from a meta-analysis of GWAS on Hcy concentrations in 44,147 individuals of European ancestry. Meanwhile, SNPs of individuals of European descent for OP were extracted from the Genetic Factors of Osteoporosis Consortium (GEFOS) UK Biobank. The odds ratio (OR) of inverse variance weighted (IVW) approaches was established as the primary outcome. Moreover, weighted median (WM) and MR-Egger regressions were included in the sensitivity analysis. There were no causal effects of Hcy on forearm bone mineral density and lumbar bone mineral density according to IVW, MR-Egger, and WM analyses (all p > 0.05). In the IVW, we discovered the causality between genetically predicted Hcy and heel bone mineral density (H-BMD) with an OR of 0.96 [95% confidence interval (CI) = 0.927-0.990, p = 0.011]. In the additional sensitivity analysis, WM regression (OR = 0.97, 95% CI = 0.995-1.076, p = 0.084) and MR-Egger regression (OR = 0.98, 95% CI = 0.918-1.049, p = 0.609) yielded values that were comparable in direction but less precise. The MR-Egger intercept, funnel plot, and IVW all indicate the absence of any discernible directional pleiotropy. The leave-one-out analysis revealed that a single SNP did not influence the results of the MR analysis. In conclusion, our MR investigation revealed evidence of a causal relationship between circulating serum Hcy levels and H-BMD, but not OP in the European population. However, larger sample sizes are needed in the future to get more reliable conclusions.

Tools for assessing quality and risk of bias in Mendelian randomization studies: a systematic review

BACKGROUND

The use of Mendelian randomization (MR) in epidemiology has increased considerably in recent years, with a subsequent increase in systematic reviews of MR studies. We conducted a systematic review of tools designed for assessing risk of bias and/or quality of evidence in MR studies and a review of systematic reviews of MR studies.

METHODS

We systematically searched MEDLINE, Embase, the Web of Science, preprints servers and Google Scholar for articles containing tools for assessing, conducting and/or reporting MR studies. We also searched for systematic reviews and protocols of systematic reviews of MR studies. From eligible articles we collected data on tool characteristics and content, as well as details of narrative description of bias assessment.

RESULTS

Our searches retrieved 2464 records to screen, from which 14 tools, 35 systematic reviews and 38 protocols were included in our review. Seven tools were designed for assessing risk of bias/quality of evidence in MR studies and evaluation of their content revealed that all seven tools addressed the three core assumptions of instrumental variable analysis, violation of which can potentially introduce bias in MR analysis estimates.

CONCLUSION

We present an overview of tools and methods to assess risk of bias/quality of evidence in MR analysis. Issues commonly addressed relate to the three standard assumptions of instrumental variables analyses, the choice of genetic instrument(s) and features of the population(s) from which the data are collected (particularly in two-sample MR), in addition to more traditional non-MR-specific epidemiological biases. The identified tools should be tested and validated for general use before recommendations can be made on their widespread use. Our findings should raise awareness about the importance of bias related to MR analysis and provide information that is useful for assessment of MR studies in the context of systematic reviews.

Sepsis as an independent risk factor in atrial fibrillation and cardioembolic stroke

BACKGROUND

Electrolyte balance is an important factor to sustain the homeostasis of human body environment and in sepsis pathogenesis. Many current cohort-based studies have already revealed that electrolyte disorder may intensify sepsis and induce stroke. However, the corresponding randomized controlled trials did not show that electrolyte disorder in sepsis has a harmful effect on stroke.

OBJECTIVES

The aim of this study was to examine the association of genetically sepsis-derived electrolyte disorder with stroke risk using meta-analysis and Mendelian randomization.

RESULTS

In four studies (182,980 patients), electrolyte disorders were compared with stroke incidence in patients with sepsis. The pooled odds ratio (OR) of stroke is 1.79 [95% confidence interval (CI): 1.23-3.06; p < 0.05], which shows a significant association between electrolyte disorder and stroke in sepsis patients. Furthermore, in order to evaluate the causal association between stroke risk and sepsis-derived electrolyte disorder, a two-sample Mendelian randomization (MR) study was conducted. The genetic variants extracted from a genome-wide association study (GWAS) of exposure data that are strongly associated with frequently used sepsis were used as instrumental variables (IVs). Based on the IVs' corresponding effect estimates, we estimated overall stroke risk, cardioembolic stroke risk, and stroke induced by large/small vessels from a GWAS meta-analysis with 10,307 cases and 19,326 controls. As a final step to verify the preliminary MR results, we performed sensitivity analysis using multiple types of Mendelian randomization analysis.

CONCLUSION

Our study revealed the association between electrolyte disorder and stroke in sepsis patients, and the correlation between genetic susceptibility to sepsis and increased risk of cardioembolic stroke, hinting that cardiogenic diseases and accompanying electrolyte disorder interference in due course could help sepsis patients get more benefits in stroke prevention.

Sleep quality traits correlate with inflammatory markers in the breast tissue of women

BACKGROUND

Several mechanisms have been posited to play a role in the sleep and breast cancer association, including alterations in immune function, but evidence remains inconclusive. A closer look at how sleep quality traits affect the breast microenvironment may provide clues for molecular mechanisms underlying the link between sleep and breast cancer. We examined the association between sleep quality traits (sleep duration, sleep aids, and insomnia) and tissue-based protein levels and gene expression of several inflammatory markers associated with breast cancer.

METHODS

Breast tissues (normal n = 165 and adipose n = 74) were surgically obtained from women diagnosed with breast cancer. Protein levels by immunohistochemistry were determined using the quickscore method for 11 inflammatory markers in the normal epithelial breast tissue (interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor-alpha (TNF-α), C-reactive protein (CRP), cyclooxygenase-2 (COX-2), leptin, serum amyloid A1 (SAA1), lactoferrin, transforming growth factor-beta (TGF-β), and signal transducer and activator of transcription 3 markers (STAT3). Relative quantification of 4 genes (COX-2, IL-6, TNF-α and LEP) in the adipose breast tissue was carried out using qPCR. Patient characteristics and sleep traits (average sleep duration per night, taking sleeping aids in the past year, and the average number of insomnia episodes per month) were determined by telephone interview. Associations were tested using Spearman's rank correlation (r_s) coefficients adjusted (ar_s) for age at surgery, menopausal status and PCR batch when applicable. Sleep duration categories (<7, 7-9, >9 h) and root- or log-transformed biomarker levels were examined with adjusted linear mixed models.

RESULTS

TGF-β and CRP levels in normal epithelial breast tissue were positively correlated with sleep aids (ar_s = 0.28, p = 0.013), and insomnia (ar_s = 0.23, p = 0.044) in postmenopausal women, respectively. IL-6 in the adipose breast tissue was inversely correlated with sleep aids (ar_s = -0.26, p = 0.029) in all women. None of the sleep traits significantly correlated with inflammatory markers in premenopausal women. Several markers tended to correlate at 0.05 ≥ p ≤ 0.10. Adjusted mean levels of inflammatory markers were significantly different across sleep duration categories (<7, 7-9, >9 h). Higher mean levels of IL-6, CRP, IL-10, and IL-6 and COX-2 expression were noted in the breast tissues of women sleeping < 7, and particularly, >9 h per night (p < 0.05).

CONCLUSION

Our findings indicate that sleep duration, sleep aids, and insomnia may differently affect women's breast tissues depending on menopausal status. From a public health perspective, these results warrant further validation in larger studies. Since sleep is a modifiable factor, it may be an interesting approach for breast cancer prevention.

Mendelian Randomization: A Review of Methods for the Prevention, Assessment, and Discussion of Pleiotropy in Studies Using the Fat Mass and Obesity-Associated Gene as an Instrument for Adiposity

Pleiotropy assessment is critical for the validity of Mendelian randomization (MR) analyses, and its management remains a challenging task for researchers. This review examines how the authors of MR studies address bias due to pleiotropy in practice. We reviewed Pubmed, Medline, Embase and Web of Science for MR studies published before 21 May 2020 that used at least one single-nucleotide polymorphism (SNP) in the fat mass and obesity-associated (FTO) gene as instrumental variable (IV) for body mass index, irrespective of the outcome. We reviewed: 1) the approaches used to prevent pleiotropy, 2) the methods cited to detect or control the independence or the exclusion restriction assumption highlighting whether pleiotropy assessment was explicitly stated to justify the use of these methods, and 3) the discussion of findings related to pleiotropy. We included 128 studies, of which thirty-three reported one approach to prevent pleiotropy, such as the use of multiple (independent) SNPs combined in a genetic risk score as IVs. One hundred and twenty studies cited at least one method to detect or account for pleiotropy, including robust and other IV estimation methods (n = 70), methods for detection of heterogeneity between estimated causal effects across IVs (n = 72), methods to detect or account associations between IV and outcome outside thought the exposure (n = 85), and other methods (n = 5). Twenty-one studies suspected IV invalidity, of which 16 explicitly referred to pleiotropy, and six incriminating FTO SNPs. Most reviewed MR studies have cited methods to prevent or to detect or control bias due to pleiotropy. These methods are heterogeneous, their triangulation should increase the reliability of causal inference.

Diet-Derived Circulating Antioxidants and Risk of Stroke: A Mendelian Randomization Study

Background

Oxidative stress is crucial in stroke pathogenesis. Many cohort-based studies suggested that the intake of exogenous antioxidants originated from food may prevent stroke. However, the corresponding randomized controlled trials did not show diet-derived antioxidants have a protective effect on stroke.

Objectives

To examine the association of genetically proxied diet-derived antioxidants with stroke risk using Mendelian randomization.

Methods

We performed a two-sample Mendelian randomization (MR) analysis to evaluate the causal effect of diet-derived antioxidants on stroke risk. For exposure data, we extracted genetic variants as instrumental variables (IVs) that are strongly associated with frequently used diet-derived antioxidants, including vitamin C, vitamin E (α-tocopherol, γ-tocopherol), carotene, retinol, zinc, and selenium, from a large-scale genome-wide association study (GWAS). We obtained IVs' corresponding effect estimates on the risk of total stroke and ischemic stroke from a GWAS meta-analysis with 40,585 cases and 406,111 controls. Finally, we applied five types of Mendelian randomization analysis to obtain preliminary MR results and performed four three kinds of sensitivity analysis to verify them.

Results

According to the primary MR estimations and further sensitivity analyses, we established two robust associations after Bonferroni correction: genetically proxied circulating γ-tocopherol was causally associated with total stroke [odds ratio (OR) = 0.68, 95% confidence interval (CI) (0.52-0.88), p = 3.78E − 03] and ischemic stroke [OR = 0.66, 95% CI (0.51-0.86), p = 2.34E − 03]. There was no evidence to support the causal effect of other diet-derived antioxidants on the risk of total stroke and ischemic stroke.

Conclusion

Our study revealed a protective impact of genetic susceptibility to high circulating γ-tocopherol levels on stroke risk, providing new information on the potential therapeutic targets for primary stroke prevention.

Review of Mendelian Randomization Studies on Endometrial Cancer

Endometrial cancer (EC) is a common gynecological cancer. In some parts of the world, the incidence and mortality of EC are on the rise. Understanding the risk factors of EC is necessary to prevent the occurrence of this disease. Observational studies have revealed the association between certain modifiable environmental risk factors and EC risk. However, due to unmeasured confounding, measurement errors, and reverse causality, observational studies sometimes have limited ability to judge robust causal inferences. In recent years, Mendelian randomization (MR) analysis has received extensive attention, providing valuable insights for cancer-related research, and is expected to identify potential therapeutic interventions. In MR analysis, genetic variation (alleles are randomly assigned during meiosis and are usually independent of environmental or lifestyle factors) is used instead of modifiable exposure to study the relationship between risk factors and disease. Therefore, MR analysis can make causal inference about exposure and disease risk. This review briefly describes the key principles and assumptions of MR analysis; summarizes published MR studies on EC; focuses on the correlation between different risk factors and EC risks; and discusses the application of MR methods in EC research. The results of MR studies on EC showed that type 2 diabetes, uterine fibroids, higher body mass index, higher plasminogen activator inhibitor-1 (PAI-1), higher fasting insulin, early insulin secretion, longer telomere length, higher testosterone and higher plasma cortisol levels are associated with increased risk of EC. In contrast, later age of menarche, higher circulatory tumor necrosis factor, higher low-density lipoprotein cholesterol, and higher sex hormone-binding globulin levels are associated with reduced risk of EC. In general, despite some limitations, MR analysis still provides an effective way to explore the causal relationship between different risk factors and EC.

Genetics of Acute Respiratory Distress Syndrome: Pathways to Precision

Clinical risk factors alone fail to fully explain acute respiratory distress syndrome (ARDS) risk or ARDS death, suggesting that individual risk factors contribute. The goals of genomic ARDS studies include better mechanistic understanding, identifying dysregulated pathways that may be amenable to pharmacologic targeting, using genomic causal inference techniques to find measurable traits with meaning, and deconvoluting ARDS heterogeneity by proving reproducible subpopulations that may share a unique biology. This article discusses the latest advances in ARDS genomics, provides historical perspective, and highlights some of the ways that the coronavirus disease 2019 (COVID-19) pandemic is accelerating genomic ARDS research.

Review of Mendelian Randomization Studies on Ovarian Cancer

Ovarian cancer (OC) is one of the deadliest gynecological cancers worldwide. Previous observational epidemiological studies have revealed associations between modifiable environmental risk factors and OC risk. However, these studies are prone to confounding, measurement error, and reverse causation, undermining robust causal inference. Mendelian randomization (MR) analysis has been established as a reliable method to investigate the causal relationship between risk factors and diseases using genetic variants to proxy modifiable exposures. Over recent years, MR analysis in OC research has received extensive attention, providing valuable insights into the etiology of OC as well as holding promise for identifying potential therapeutic interventions. This review provides a comprehensive overview of the key principles and assumptions of MR analysis. Published MR studies focusing on the causality between different risk factors and OC risk are summarized, along with comprehensive analysis of the method and its future applications. The results of MR studies on OC showed that higher BMI and height, earlier age at menarche, endometriosis, schizophrenia, and higher circulating β-carotene and circulating zinc levels are associated with an increased risk of OC. In contrast, polycystic ovary syndrome; vitiligo; higher circulating vitamin D, magnesium, and testosterone levels; and HMG-CoA reductase inhibition are associated with a reduced risk of OC. MR analysis presents a2 valuable approach to understanding the causality between different risk factors and OC after full consideration of its inherent assumptions and limitations.

Does Chronic Intestinal Inflammation Promote Atrial Fibrillation: A Mendelian Randomization Study With Populations of European Ancestry

Background: Inflammatory bowel disease (IBD), comprising ulcerative colitis (UC), and Crohn's disease (CD), has been reported to be associated with an increased risk of atrial fibrillation (AF). However, the causal role of the chronic intestinal inflammation (CII) in the development of AF remains controversial. We use Mendelian randomization (MR) analysis to explore the causal inference of CII on AF. Methods: A two-sample MR analysis was performed to estimate the potential causal effect of CII on AF. Statistical summaries for the associations between single nucleotide polymorphisms (SNPs) and phenotypes of CII were obtained from genome-wide association studies (GWAS) with cohorts of CD (n = 51,874), UC (n = 47,745), and IBD (n = 65,642) of European descent. The GWAS of 1,030,836 people of European ancestry, including 60,620 AF cases and 970,216 controls was collected to identify genetic variants underlying AF. The causal inference was estimated using the multiplicative random effects inverse-variance weighted method (IVW). The methods of MR-Egger, simple median, and weighted median were also employed to avoid the bias of pleiotropy effects. Results: Using three sets of SNPs (75 SNPs of CD, 60 SNPs of UC, and 95 SNPs of IBD), multiplicative random-effect IVW model estimated a universal null effect of CII on AF (CD: OR = 1.0059, 95% CI: 0.9900, 1.0220, p = 0.47; UC: OR = 1.0087, 95% CI: 0.9896, 1.0281, p = 0.38; IBD: OR = 1.0080, 95% CI: 0.9908, 1.0255, p = 0.37). Similar results were observed using the MR-Egger, simple median, weighted median methods. Conclusion: As opposing to the traditional observational studies, our two-sample MR analysis did not find enough evidence to support a causal role of either CD or UC in the development of AF.

Mendelian randomization as an approach to assess causal effects of inflammatory bowel disease on atrial fibrillation

Background: Despite growing evidence indicating that patients with inflammatory bowel disease (IBD) have an increased risk of atrial fibrillation (AF), owing to the potential biases of confounding effects and reverse causation, the specific relationship between IBD and AF remains controversial. The aim of this study is to determine whether there is a causal effect of IBD on AF.

Methods: A two-sample Mendelian randomization (MR) study was performed to evaluate the causal effect of IBD on AF. Statistical summaries for the associations between single nucleotide polymorphisms (SNPs) and traits of interest were obtained from independent consortia with European populations. The dataset of IBD was acquired from genome-wide association studies (GWAS), including more than 75,000 cases and controls. A GWAS with 60,620 AF cases and 970,216 controls was used to identify genetic variation underlying AF. The causal effect was estimated using the multiplicative random effects inverse-variance weighted method (IVW), followed by sensitivity analysis.

Results: Using 81 SNPs, there was no evidence to suggest an association between genetically predicted IBD and risk of AF with multiplicative random-effects IVW MR analysis (odds ratio = 1.0000, 95% confidence interval: 0.9994 1.0005, p = 0.88).

Conclusion: As opposed to current assumptions, no substantial evidence was found to support a causal role of IBD in the development of AF.

Age at first birth and lung cancer: a two-sample Mendelian randomization study

Background

Growing evidence suggests that female reproductive factors, like age at first birth (AFB), may play a potential role in the progression of lung cancer (LC). However, previous studies are susceptible to confounding factors, inadequate attention to variation by histology or reverse causality. Few studies have comprehensively evaluated their association and the causal effect remains unclear.

Methods

We aimed to determine whether AFB is causally correlated with the risk of LC, by means of utilizing aggregated data from the large genome-wide association studies conducted on AFB (251,151 individuals) and data of LC from International Lung and Cancer Consortium (ILCCO, 11,348 cases and 15,861 controls). We used 10 AFB-related single nucleotide polymorphisms as instrument variables and applied several two-sample Mendelian randomization (MR) methods. Secondary results according to different histological subtypes of lung cancer were also implemented.

Results

Conventional inverse-variance weighted method indicated that genetic predisposition towards number unit (1 year) increase of AFB was associated with a 18% lower risk of LC [odds ratio (OR) =0.82, 95% confidence interval (CI): 0.69–0.97; P=0.029]. When results were examined by histotypes, an inverse association was observed between genetically predisposed number unit (1 year) increase of AFB and lung adenocarcinoma (OR =0.75, 95% CI: 0.59–0.97, P=0.017) but not with squamous cell lung cancer (OR =0.77, 95% CI: 0.57–1.05, P=0.103). The results demonstrated no association between number unit decrease of AFB and LC. Pleiotropy was not presented through sensitivity analyses including MR pleiotropy residual sum and outlier test (P=0.412). Genetic predisposition towards older AFB was additionally associated with longer years of schooling (OR =1.12, 95% CI: 1.08–1.16, P<0.001), lower body mass index (OR =0.93, 95% CI: 0.88–0.98, P=0.004) and less alcohol consumption (OR =0.99, 95% CI: 0.99–1.00, P=0.004).

Conclusions

Our study suggested that older AFB was a causal protective factor in the progression of LC. Further studies elucidating the potential mechanisms are needed.

Correlation between total homocysteine and cerebral small vessel disease: A Mendelian randomization study

BACKGROUND AND PURPOSE

Cerebral small vessel disease (CSVD) is a clinical imaging syndrome with diverse etiology. Total homocysteine (HCY) level might increase the risk of myocardial and cerebral infarction by damaging the vascular endothelium. We aimed to explore the correlation between total HCY and CSVD imaging burden, based on Mendelian randomization methods.

METHODS

A total of 1,023 participants of the Shunyi study, a population-based cohort study, were included. Vascular risk factors, total HCY levels and methylenetetrahydrofolate reductase (MTHFR) gene mutations (C677T and A1298C) were examined. CSVD imaging markers, including lacunes, cerebral microbleeds, white matter hyperintensity, enlarged perivascular space and brain parenchymal fraction (BPF) were also assessed.

RESULTS

Mutations of C677T were significantly correlated with increased total HCY levels (CC→TT: β = 0.28, p < 0.0001), while mutations of A1298C were correlated with decreased total HCY levels (AA→AC: β = -0.13, p < 0.0001; AA→CC: β = -0.25, p = 0.004). In the Mendelian randomization study, the C677T genotype was significantly associated with lacunes (CC→CT: odds ratio [OR] 2.76, p = 0.008; CC→TT: OR 2.50, p = 0.018), and the A1298C genotype was significantly correlated with BPF (AA→CC: β = 1.32, p = 0.015). Similarly, in multivariate regression analysis, total HCY levels were significantly correlated with lacunes (OR 2.14, p < 0.0001) and negatively correlated with BPF (β = -0.55, p = 0.004). Age, sex and vascular risk factors were adjusted for.

CONCLUSIONS

Total HCY level was correlated with imaging burden of CSVD, especially with lacunes and brain volume loss. For individuals with risk genetic predisposition, enhanced homocysteine-lowering strategies might be necessary to reduce the risk and progress of CSVD.

Assessment Causality in Associations Between Serum Uric Acid and Risk of Schizophrenia: A Two-Sample Bidirectional Mendelian Randomization Study

Purpose

Although increasing lines of evidence showed associations between serum uric acid (UA) levels and schizophrenia, the causality and the direction of the associations remain uncertain. Thus, we aimed to assess whether the relationships between serum UA levels and schizophrenia are causal and to determine the direction of the association.

Patients and Methods

Two-sample bidirectional Mendelian randomization (MR) analyses and various sensitivity analyses were performed utilizing the summary data from genome-wide association studies within the Global Urate Genetics Consortium and the Psychiatric Genomics Consortium. Secondary MR analyses in both directions were conducted within summary data using genetic risk scores (GRSs) as instrumental variables.

Results

Three MR methods provided no causal relationship between serum UA and schizophrenia. Furthermore, GRS approach showed similar results in the three MR methods after adjustment for heterogeneity. By contrast, inverse variance weighted method, weighted median and GRS approach suggested a causal effect of schizophrenia risk on serum UA after adjustment for heterogeneity (per 10-symmetric percentage increase in schizophrenia risk, beta: -0.039, standard error (SE): 0.013, P = 0.003; beta: -0.036, SE: 0.018, P = 0.043; beta: -0.039, SE: 0.013, P = 0.002; respectively). Moreover, in both directions' analyses, the heterogeneity and sensitivity tests suggested no strong evidence of bias due to pleiotropy.

Conclusion

Schizophrenia may causally affect serum UA levels, whereas the causal role of serum UA concentrations in schizophrenia was not supported by our MR analyses. These findings suggest that UA may be a useful potential biomarker for monitoring treatment or diagnosis of schizophrenia rather than a therapeutic target for schizophrenia.

Plasma sRAGE Acts as a Genetically Regulated Causal Intermediate in Sepsis-associated Acute Respiratory Distress Syndrome

Rationale: Acute respiratory distress syndrome (ARDS) lacks known causal biomarkers. Plasma concentrations of sRAGE (soluble receptor for advanced glycation end products) strongly associate with ARDS risk. However, whether plasma sRAGE contributes causally to ARDS remains unknown.Objectives: Evaluate plasma sRAGE as a causal intermediate in ARDS by Mendelian randomization (MR), a statistical method to infer causality using observational data.Methods: We measured early plasma sRAGE in two critically ill populations with sepsis. The cohorts were whole-genome genotyped and phenotyped for ARDS. To select validated genetic instruments for MR, we regressed plasma sRAGE on genome-wide genotypes in both cohorts. The causal effect of plasma sRAGE on ARDS was inferred using the top variants with significant associations in both populations (P < 0.01, R2 > 0.02). We applied the inverse variance-weighted method to obtain consistent estimates of the causal effect of plasma sRAGE on ARDS risk.Measurements and Main Results: There were 393 European and 266 African ancestry patients in the first cohort and 843 European ancestry patients in the second cohort. Plasma sRAGE was strongly associated with ARDS risk in both populations (odds ratio, 1.86; 95% confidence interval [1.54-2.25]; 2.56 [2.14-3.06] per log increase). Using genetic instruments common to both populations, plasma sRAGE had a consistent causal effect on ARDS risk with a β estimate of 0.50 (95% confidence interval [0.09-0.91] per log increase).Conclusions: Plasma sRAGE is genetically regulated during sepsis, and MR analysis indicates that increased plasma sRAGE leads to increased ARDS risk, suggesting plasma sRAGE acts as a causal intermediate in sepsis-related ARDS.

The causal role of elevated uric acid and waist circumference on the risk of metabolic syndrome components

BACKGROUND/OBJECTIVES

Hyperuricemia has been found to cluster with multiple components of metabolic syndrome (MetS). It is unclear whether hyperuricemia is a downstream result of MetS or may play an upstream role in MetS development. Using the Mendelian randomization (MR) method, we examined the causal relationship between elevated uric acid and the various components of MetS with waist circumference as a positive control.

SUBJECTS/METHODS

Data from 10k participants of Taiwan Biobank was used to carry out MR analysis with uric acid risk score (wGRS) and waist circumference wGRS as instrumental variables and components of MetS as the outcomes.

RESULTS

We found that genetically increased serum uric acid corresponds to a significant increment of triglyceride (β = 0.065, p < 0.0001), systolic blood pressure (β = 1.047, p = 0.0005), diastolic blood pressure (β = 0.857, p < 0.0001), and mean arterial pressure (β = 0.920, p < 0.0001), but a significant reduction of high-density lipoprotein cholesterol (β = -0.020, p = 0.0014). Uric acid wGRS was not associated with fasting serum glucose, HbA1C, waist circumference, or BMI. On the other hand, waist circumference was causally associated with all the components of MetS including uric acid.

CONCLUSIONS

Our MR investigation shows that uric acid increment may augment the risk of MetS through increasing blood pressure and triglyceride levels and lowering HDL-C value but not through accumulating fat or hyperglycemia. High waist circumference may be a causal agent for all the components of MetS including hyperuricemia.

Docosapentaenoic acid and lung cancer risk: A Mendelian randomization study

BACKGROUND

Observational studies have shown that excessive dietary fat may be associated with lung carcinogenesis. However, findings from previous studies are inconsistent and it remains unclear whether docosapentaenoic acid (DPA), a kind of polyunsaturated fatty acid, is linked to the risk of lung cancer. The aim of this study is to investigate the causal effect of DPA on lung cancer with Mendelian randomization (MR) method.

METHODS

With a two-sample MR approach, we analyzed the summary data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE, 8866 individuals of European ancestry) Consortium and International Lung Cancer Consortium (ILCCO, 11 348 lung cancer cases and 15 861 controls; European ancestry) to assess the possible causal relationship of DPA on the risk of lung cancer.

RESULTS

Our results indicated that genetically predicted higher DPA level has a positive association with lung cancer, where 1% higher DPA was associated with a 2.01-fold risk of lung cancer (odds ratio [OR]: 2.01, 95% CI = 1.34-3.01; P = 7.40 × 10^-4 ). Additionally, lung cancer was not a causal factor for DPA. The results of MR-Egger regression analysis showed that there was no evidence for the presence of directional horizontal pleiotropy.

CONCLUSIONS

Genetically elevated DPA is positively associated with risk of lung cancer, and more work is needed to investigate the potential mechanisms.

Use of Mendelian andomization for dentifying isk actors for rain umors

Gliomas are a group of primary brain tumors, the most common and aggressive subtype of which is glioblastoma. Glioblastoma has a median survival of just 15 months after diagnosis. Only previous exposure to ionizing radiation and particular inherited genetic syndromes are accepted risk factors for glioma; the vast majority of cases are thought to occur spontaneously. Previous observational studies have described associations between several risk factors and glioma, but studies are often conflicting and whether these associations reflect true casual relationships is unclear because observational studies may be susceptible to confounding, measurement error and reverse causation. Mendelian randomization (MR) is a form of instrumental variable analysis that can be used to provide supporting evidence for causal relationships between exposures (e.g., risk factors) and outcomes (e.g., disease onset). MR utilizes genetic variants, such as single nucleotide polymorphisms (SNPs), that are robustly associated with an exposure to determine whether there is a causal effect of the exposure on the outcome. MR is less susceptible to confounding, reverse causation and measurement errors as it is based on the random inheritance during conception of genetic variants that can be relatively accurately measured. In previous studies, MR has implicated a genetically predicted increase in telomere length with an increased risk of glioma, and found little evidence that obesity related factors, vitamin D or atopy are causal in glioma risk. In this review, we describe MR and its potential use to discover and validate novel risk factors, mechanistic factors, and therapeutic targets in glioma.

Plasma angiopoietin-2 as a potential causal marker in sepsis-associated ARDS development: evidence from Mendelian randomization and mediation analysis

PURPOSE

A causal biomarker for acute respiratory distress syndrome (ARDS) could fuel precision therapy options. Plasma angiopoietin-2 (ANG2), a vascular permeability marker, is a strong candidate on the basis of experimental and observational evidence. We used genetic causal inference methods-Mendelian randomization and mediation-to infer potential effects of plasma ANG2.

METHODS

We genotyped 703 septic subjects, measured ICU admission plasma ANG2, and performed a quantitative trait loci (QTL) analysis to determine variants in the ANGPT2 gene associated with plasma ANG2 (p < 0.005). We then used linear regression and post-estimation analysis to genetically predict plasma ANG2 and tested genetically predicted ANG2 for ARDS association using logistic regression. We estimated the proportion of the genetic effect explained by plasma ANG2 using mediation analysis.

RESULTS

Plasma ANG2 was strongly associated with ARDS (OR 1.59 (95% CI 1.35, 1.88) per log). Five ANGPT2 variants were associated with ANG2 in European ancestry subjects (n = 404). Rs2442608C, the most extreme cis QTL (coefficient 0.22, 95% CI 0.09-0.36, p = 0.001), was associated with higher ARDS risk: adjusted OR 1.38 (95% CI 1.01, 1.87), p = 0.042. No significant QTL were identified in African ancestry subjects. Genetically predicted plasma ANG2 was associated with ARDS risk: adjusted OR 2.25 (95% CI 1.06-4.78), p = 0.035. Plasma ANG2 mediated 34% of the rs2442608C-related ARDS risk.

CONCLUSIONS

In septic European ancestry subjects, the strongest ANG2-determining ANGPT2 genetic variant is associated with higher ARDS risk. Plasma ANG2 may be a causal factor in ARDS development. Strategies to reduce plasma ANG2 warrant testing to prevent or treat sepsis-associated ARDS.

Alpha-1 antitrypsin deficiency: From the lung to the heart?

BACKGROUND AND AIMS

Alpha-1 antitrypsin (A1AT) is the most abundant serine protease inhibitor in human blood and exerts important anti-inflammatory and immune-modulatory effects. In combination with smoking or other long-term noxious exposures such as occupational dust and fumes, genetic A1AT deficiency can cause chronic obstructive pulmonary disease, a condition with elevated cardiovascular risk. The effects of A1AT deficiency on cardiovascular risk have hardly been studied today.

METHODS

Using data from 2614 adults from the population-based SAPALDIA cohort, we tested associations of serum A1AT and SERPINA1 mutations with carotid intima-media thickness (CIMT, measured by B-mode ultrasonography) or self-reported arterial hypertension or cardiovascular disease in multiple regression models using a Mendelian Randomization like analysis design. Mutations Pi-S and Pi-Z were coded as ordinal genotype score (MM, MS, MZ/SS, SZ and ZZ), according to their progressive biological impact.

RESULTS

Serum A1AT concentration presented a u-shaped association with CIMT. At the lower end of the A1AT distribution, an analogous, linear association between SERPINA1 score and higher CIMT was observed, resulting in an estimated 1.2% (95%-confidence interval -0.1-2.5) increase in CIMT per unit (p = 0.060). Genotype score was significantly associated with arterial hypertension with an odds ratio (OR) of 1.2 (1.0-1.5) per unit (p = 0.028). The association with cardiovascular disease was not significant (OR 1.3 (0.9-1.9)).

CONCLUSIONS

Our results support a possible causal relationship between genetic A1AT deficiency and increased cardiovascular risk, which needs to be better taken into account for the management of affected patients and first-degree relatives.

A Primer in Mendelian Randomization Methodology with a Focus on Utilizing Published Summary Association Data

Mendelian randomization (MR) is becoming a popular approach to estimate the causal effect of an exposure on an outcome overcoming limitations of observational epidemiology. The advent of genome-wide association studies and the increasing accumulation of summarized data from large genetic consortia make MR a powerful technique. In this review, we give a primer in MR methodology, describe efficient MR designs and analytical strategies, and focus on methods and practical guidance for conducting an MR study using summary association data. We show that the analysis is straightforward utilizing either the MR-base platform or available packages in R. However, further research is required for the development of specialized methodology to assess MR assumptions.

Recent Developments in Mendelian Randomization Studies

PURPOSE OF REVIEW

Mendelian randomization (MR) is a strategy for evaluating causality in observational epidemiological studies. MR exploits the fact that genotypes are not generally susceptible to reverse causation and confounding, due to their fixed nature and Mendel's First and Second Laws of Inheritance. MR has the potential to provide information on causality in many situations where randomized controlled trials are not possible, but the results of MR studies must be interpreted carefully to avoid drawing erroneous conclusions.

RECENT FINDINGS

In this review, we outline the principles behind MR, as well as assumptions and limitations of the method. Extensions to the basic approach are discussed, including two-sample MR, bidirectional MR, two-step MR, multivariable MR, and factorial MR. We also consider some new applications and recent developments in the methodology, including its ability to inform drug development, automation of the method using tools such as MR-Base, and phenome-wide and hypothesis-free MR.

SUMMARY

In conjunction with the growing availability of large-scale genomic databases, higher level of automation and increased robustness of the methods, MR promises to be a valuable strategy to examine causality in complex biological/omics networks, inform drug development and prioritize intervention targets for disease prevention in the future.

Circulating interleukin-6 and rheumatoid arthritis: A Mendelian randomization meta-analysis

Interleukin-6 (IL-6), as a pleiotropic cytokine, has been demonstrated to be closely associated with the pathogenisis of rheumatoid arthritis (RA). However, whether this association is causal or not remains unclear, because of the multifactorial role of IL-6 and related confounding factors. We aimed to evaluate the causal relevance between circulating IL-6 levels and the risk of RA through meta-analytical Mendelian randomization approach. IL-6 gene -174G/C variant was selected as an instrument in this Mendelian randomization meta-analysis. Article identification and data collection were conducted in duplicate and independently by 2 authors. The STATA software was used for data analysis. In total, 15 and 5 articles on the association of the -174G/C variant with RA risk and circulating IL-6 level, respectively, were included. The overall analysis showed that C allelic and GC+CC genotype were significantly with 1.59-fold (95% CI: 1.19-2.14) and 1.63-fold (95% CI: 1.17-2.26) increased risk of developing RA, respectively. Asian populations showed stronger association with 4.55-fold (95% CI: 1.62-12.75), 1.84-fold (95% CI: 1.13-2.99), and 4.69-fold (95% CI: 1.68-13.14) increased RA risk in carriers of -174C allelic, CC, and GC+CC genotype, respectively. Carriers of GC+CC genotype showed significant reduction in the circulating IL-6 level compared with GG carriers (WMD = -0.77; 95% CI: -1.16 to -0.38; P = 0.000) in overall populations. Mendelian randomization presented 6% and 22% increased risk of RA with 0.1 pg/mL reduction of circulating IL-6 level in overall and Asian populations, respectively. This Mendelian randomization meta-analysis demonstrated that the long-term genetically reduced circulating IL-6 level might be causally related to a higher risk of RA, especially in Asian populations.

AMD Genetics in India: The Missing Links

Age related macular degeneration is a disease which occurs in aged individuals. There are various changes that occur at the cellular, molecular and physiological level with advancing age (Samiec et al., 1988; Sharma K. et al., 2014). Drusen deposition between retinal pigment epithelium (RPE) and Bruch’s membrane (BM) is one of the key features in AMD patients (Mullins et al., 2000; Hageman et al., 2001) similar to Aβ/tau aggregates in Alzheimer’s disease (AD) patients. The primary goal of this review is to discuss whether the various candidate genes and associated biomarkers, that are known to play an independent role in progression of AMD, exert deleterious effect on phenotype, alone or in combination, in Indian AMD patients from the same ethnic group and the significance of such research. A statistical model for probable interaction between genes could be derived from such analysis. Therefore, one can use multiple modalities to identify and enrol AMD patients based on established clinical criteria and examine the risk factors to determine if these genes are associated with risk factors, biomarkers or disease by Mendelian randomization. Similarly, there are large numbers of single nucleotide polymorphisms (SNPs) identified in human population. Even non-synonymous SNPs (nsSNPs) are believed to induce deleterious effects on the functionality of various proteins. The study of such snSNPs could provide a better genetic insight for diverse phenotypes of AMD patients, predicting significant risk factors for the disease in Indian population. Therefore, the prediction of biological effect of nsSNPs in the candidate genes and the associated grant applications in the subject are highly solicited.Therefore, genotyping and levels of protein expression of various genes would provide wider canvas in genetic complexity of AMD pathology which should be evaluated by valid statistical and bioinformatics’ tools. Longitudinal follow up of Indian AMD patients to evaluate the temporal effect of SNPs and biomarkers on progression of disease would provide a unique strategy in the field.

A significant causal association between C-reactive protein levels and schizophrenia

Many observational studies have shown elevated blood CRP levels in schizophrenia compared with controls, and one population-based prospective study has reported that elevated plasma CRP levels were associated with late- and very-late-onset schizophrenia. Furthermore, several clinical studies have reported the efficacy of anti-inflammatory drugs on the symptoms in patients with schizophrenia. However, whether elevated CRP levels are causally related to schizophrenia is not still established because of confounding factors and reverse causality. In the present study, we demonstrated that serum CRP levels were significantly higher in patients with schizophrenia than in the controls by conducting a case-control study and a meta-analysis of case-control studies between schizophrenia and serum CRP levels. Furthermore, we provided evidence for a causal association between elevated CRP levels and increased schizophrenia risk by conducting a Mendelian randomization analysis. Our findings suggest that elevated CRP itself may be a causal risk factor for schizophrenia.

Genetically lowered concentrations of circulating sRAGE might cause an increased risk of cancer: Meta-analysis using Mendelian randomization

Objectives

To undertake a systematic meta-analysis of all variants in the gene encoding receptor for advanced glycation end products (RAGE) to summarize their associations with cancer risk and changes in the levels of circulating soluble RAGE (sRAGE), with the aim of determining possible causality between circulating sRAGE and cancer risk.

Methods

Articles written in English were retrieved from MEDLINE® and EMBASE® databases. Two researchers independently identified eligible articles and extracted the data (analysed using STATA® software version 12.0).

Results

Fifteen articles qualified for inclusion in the meta-analysis of the RAGE–cancer association and three examined the RAGE–sRAGE relationship. The 82Ser/82Ser genotype was significantly associated with overall cancer risk compared with the 82Gly/Gly genotype (odds ratio 1.75, 95% confidence interval [CI] 1.46, 2.10). Carriers of the 82Ser/82Ser genotype had significantly reduced circulating sRAGE concentrations compared with the 82Gly/82Gly genotype. Mendelian randomization analysis demonstrated that a reduction of 100, 200 and 300 pg/ml in circulating sRAGE concentrations was associated with a 1.11-fold (95% CI 1.06, 1.25), 1.24-fold (95% CI 1.11, 1.57) and 1.38-fold (95% CI 1.18, 1.96) increased risk of developing cancer, respectively.

Conclusions

Genetically lowered concentrations of circulating sRAGE might cause an increased risk of cancer.

Mendelian Randomization versus Path Models: Making Causal Inferences in Genetic Epidemiology

OBJECTIVE

The term Mendelian randomization is popular in the current literature. The first aim of this work is to describe the idea of Mendelian randomization studies and the assumptions required for drawing valid conclusions. The second aim is to contrast Mendelian randomization and path modeling when different 'omics' levels are considered jointly.

METHODS

We define Mendelian randomization as introduced by Katan in 1986, and review its crucial assumptions. We introduce path models as the relevant additional component to the current use of Mendelian randomization studies in 'omics'. Real data examples for the association between lipid levels and coronary artery disease illustrate the use of path models.

RESULTS

Numerous assumptions underlie Mendelian randomization, and they are difficult to be fulfilled in applications. Path models are suitable for investigating causality, and they should not be mixed up with the term Mendelian randomization. In many applications, path modeling would be the appropriate analysis in addition to a simple Mendelian randomization analysis.

CONCLUSIONS

Mendelian randomization and path models use different concepts for causal inference. Path modeling but not simple Mendelian randomization analysis is well suited to study causality with different levels of 'omics' data.

Evaluation of an association between plasma total homocysteine and schizophrenia by a Mendelian randomization analysis

BACKGROUND

The results of meta-analyses conducted by previous association studies between total homocysteine and schizophrenia suggest that an elevated total homocysteine level is a risk factor for schizophrenia. However, observational studies have potential limitations, such as confounding and reverse causation. In the present study, we evaluated a causal relationship between plasma total homocysteine and schizophrenia by conducting a Mendelian randomization analysis.

METHODS

We used the MTHFR C677T polymorphism as an instrumental variable, which affects the plasma total homocysteine levels. To calculate the risk estimate for the association of this single nucleotide polymorphism (SNP) with schizophrenia, we conducted a meta-analysis of case-control studies that comprise a total of 11,042 patients with schizophrenia and 14,557 control subjects. We obtained an estimate for the association of this SNP with the plasma total homocysteine levels from a meta-analysis of genome-wide association studies comprising 44,147 individuals.

RESULTS

By combining these two estimates, we demonstrated a significant effect of the plasma total homocysteine on schizophrenia risk, representing an OR of 2.15 (95 % CI = 1.39-3.32; p = 5.3 x 10(-4)) for schizophrenia per 1-SD increase in the natural log-transformed plasma total homocysteine levels.

CONCLUSIONS

We provided evidence of a causal relationship between the plasma total homocysteine and schizophrenia, and this result will add insight into the pathology and treatment of schizophrenia.

Circulating interleukin-6 and cancer: A meta-analysis using Mendelian randomization

Interleukin-6 (IL-6) plays a contributory role in the progression and severity of many forms of cancer; it however remains unclear whether the relevance between circulating IL-6 and cancer is causal. We therefore meta-analyzed published articles in this regard using IL-6 gene -174G/C variant as an instrument. Seventy-eight and six articles were eligible for the association of -174G/C variant with cancer and circulating IL-6, respectively. Overall analyses failed to identify any significance between -174G/C and cancer risk. In Asians, carriers of the -174CC genotype had an 1.95-fold increased cancer risk compared with the -174GG genotype carriers (P = 0.009). By cancer type, significance was only attained for liver cancer with the -174C allele conferring a reduced risk under allelic (odds ratio or OR = 0.74; P = 0.001), homozygous genotypic (OR = 0.59; P = 0.029) and dominant (OR = 0.67; P = 0.004) models. Carriers of the -174CC genotype (weighted mean difference or WMD = −4.23 pg/mL; P < 0.001) and -174C allele (WMD = −3.43 pg/mL; P < 0.001) had circulating IL-6 reduced significantly compared with the non-carriers. In further Mendelian randomization analysis, a reduction of 1 pg/mL in circulating IL-6 was significantly associated with an 12% reduced risk of liver cancer. Long-term genetically-reduced circulating IL-6 might be causally associated with a lower risk of liver cancer.

Mendelian randomization studies: a review of the approaches used and the quality of reporting

BACKGROUND

Mendelian randomization (MR) studies investigate the effect of genetic variation in levels of an exposure on an outcome, thereby using genetic variation as an instrumental variable (IV). We provide a meta-epidemiological overview of the methodological approaches used in MR studies, and evaluate the discussion of MR assumptions and reporting of statistical methods.

METHODS

We searched PubMed, Medline, Embase and Web of Science for MR studies up to December 2013. We assessed (i) the MR approach used; (ii) whether the plausibility of MR assumptions was discussed; and (iii) whether the statistical methods used were reported adequately.

RESULTS

Of 99 studies using data from one study population, 32 used genetic information as a proxy for the exposure without further estimation, 44 performed a formal IV analysis, 7 compared the observed with the expected genotype-outcome association, and 1 used both the latter two approaches. The 80 studies using data from multiple study populations used many different approaches to combine the data; 52 of these studies used some form of IV analysis; 44% of studies discussed the plausibility of all three MR assumptions in their study. Statistical methods used for IV analysis were insufficiently described in 14% of studies.

CONCLUSIONS

Most MR studies either use the genotype as a proxy for exposure without further estimation or perform an IV analysis. The discussion of underlying assumptions and reporting of statistical methods for IV analysis are frequently insufficient. Studies using data from multiple study populations are further complicated by the combination of data or estimates. We provide a checklist for the reporting of MR studies.

Role of Vitamin D deficiency in extraskeletal complications: predictor of health outcome or marker of health status?

The relationship of vitamin D with extraskeletal complications, such as cardiovascular disease, cancer, and autoimmune disease, is of major interest considering its roles in key biological processes and the worldwide high prevalence of vitamin D deficiency. However, the causal relationships between vitamin D and most extraskeletal complications are weak. Currently, a heated debate over vitamin D is being conducted according to two hypotheses. In this review, we first present the different arguments that suggest a major role of vitamin D in a very broad type of extraskeletal complications (hypothesis #1). We then present results from recent meta-analyses of randomized controlled trials indicating a lack of association of vitamin D with major extraskeletal complications (hypothesis #2). We discuss different issues (e.g., causality, confounding, reverse causation, misclassification, and Mendelian randomization) that contribute to the favoring of one hypothesis over the other. While ultimately only one hypothesis is correct, we anticipate that the results from the ongoing randomized controlled trials will be unlikely to reconcile the divided experts.

Genomics and metabolomics of muscular mass in a community-based sample of UK females

The contribution of specific molecular-genetic factors to muscle mass variation and sarcopenia remains largely unknown. To identify endogenous molecules and specific genetic factors associated with appendicular lean mass (APLM) in the general population, cross-sectional data from the TwinsUK Adult Twin Registry were used. Non-targeted mass spec-based metabolomic profiling was performed on plasma of 3953 females (mostly dizygotic and monozygotic twins). APLM was measured using dual-energy X-ray absorptiometry (DXA) and genotyping was genome-wide (GWAS). Specific metabolites were used as intermediate phenotypes in the identification of single-nucleotide polymorphisms associated with APLM using GWAS. In all, 162 metabolites were found significantly correlated with APLM, and explained 17.4% of its variation. However, the top three of them (unidentified substance X12063, urate, and mannose) explained 11.1% (P ≤ 9.25 × 10(-26)) so each was subjected to GWAS. Each metabolite showed highly significant (P ≤ 9.28 × 10(-46)) associations with genetic variants in the corresponding genomic regions. Mendelian randomization using these SNPs found no evidence for a direct causal effect of these metabolites on APLM. However, using a new software platform for bivariate analysis we showed that shared genetic factors contribute significantly (P ≤ 4.31 × 10(-43)) to variance in both the metabolites and APLM--independent of the effect of the associated SNPs. There are several metabolites, having a clear pattern of genetic inheritance, which are highly significantly associated with APLM and may provide a cheap and readily accessible biomarker of muscle mass. However, the mechanism by which the genetic factor influences muscle mass remains to be discovered.

Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways

BACKGROUND

Mendelian randomization uses genetic variants, assumed to be instrumental variables for a particular exposure, to estimate the causal effect of that exposure on an outcome. If the instrumental variable criteria are satisfied, the resulting estimator is consistent even in the presence of unmeasured confounding and reverse causation.

METHODS

We extend the Mendelian randomization paradigm to investigate more complex networks of relationships between variables, in particular where some of the effect of an exposure on the outcome may operate through an intermediate variable (a mediator). If instrumental variables for the exposure and mediator are available, direct and indirect effects of the exposure on the outcome can be estimated, for example using either a regression-based method or structural equation models. The direction of effect between the exposure and a possible mediator can also be assessed. Methods are illustrated in an applied example considering causal relationships between body mass index, C-reactive protein and uric acid.

RESULTS

These estimators are consistent in the presence of unmeasured confounding if, in addition to the instrumental variable assumptions, the effects of both the exposure on the mediator and the mediator on the outcome are homogeneous across individuals and linear without interactions. Nevertheless, a simulation study demonstrates that even considerable heterogeneity in these effects does not lead to bias in the estimates.

CONCLUSIONS

These methods can be used to estimate direct and indirect causal effects in a mediation setting, and have potential for the investigation of more complex networks between multiple interrelated exposures and disease outcomes.

Mendelian randomization: genetic anchors for causal inference in epidemiological studies

Observational epidemiological studies are prone to confounding, reverse causation and various biases and have generated findings that have proved to be unreliable indicators of the causal effects of modifiable exposures on disease outcomes. Mendelian randomization (MR) is a method that utilizes genetic variants that are robustly associated with such modifiable exposures to generate more reliable evidence regarding which interventions should produce health benefits. The approach is being widely applied, and various ways to strengthen inference given the known potential limitations of MR are now available. Developments of MR, including two-sample MR, bidirectional MR, network MR, two-step MR, factorial MR and multiphenotype MR, are outlined in this review. The integration of genetic information into population-based epidemiological studies presents translational opportunities, which capitalize on the investment in genomic discovery research.

Identifying the odds ratio estimated by a two-stage instrumental variable analysis with a logistic regression model

An adjustment for an uncorrelated covariate in a logistic regression changes the true value of an odds ratio for a unit increase in a risk factor. Even when there is no variation due to covariates, the odds ratio for a unit increase in a risk factor also depends on the distribution of the risk factor. We can use an instrumental variable to consistently estimate a causal effect in the presence of arbitrary confounding. With a logistic outcome model, we show that the simple ratio or two-stage instrumental variable estimate is consistent for the odds ratio of an increase in the population distribution of the risk factor equal to the change due to a unit increase in the instrument divided by the average change in the risk factor due to the increase in the instrument. This odds ratio is conditional within the strata of the instrumental variable, but marginal across all other covariates, and is averaged across the population distribution of the risk factor. Where the proportion of variance in the risk factor explained by the instrument is small, this is similar to the odds ratio from a RCT without adjustment for any covariates, where the intervention corresponds to the effect of a change in the population distribution of the risk factor. This implies that the ratio or two-stage instrumental variable method is not biased, as has been suggested, but estimates a different quantity to the conditional odds ratio from an adjusted multiple regression, a quantity that has arguably more relevance to an epidemiologist or a policy maker, especially in the context of Mendelian randomization.

Model selection approach suggests causal association between 25-hydroxyvitamin D and colorectal cancer

INTRODUCTION

Vitamin D deficiency has been associated with increased risk of colorectal cancer (CRC), but causal relationship has not yet been confirmed. We investigate the direction of causation between vitamin D and CRC by extending the conventional approaches to allow pleiotropic relationships and by explicitly modelling unmeasured confounders.

METHODS

Plasma 25-hydroxyvitamin D (25-OHD), genetic variants associated with 25-OHD and CRC, and other relevant information was available for 2645 individuals (1057 CRC cases and 1588 controls) and included in the model. We investigate whether 25-OHD is likely to be causally associated with CRC, or vice versa, by selecting the best modelling hypothesis according to Bayesian predictive scores. We examine consistency for a range of prior assumptions.

RESULTS

Model comparison showed preference for the causal association between low 25-OHD and CRC over the reverse causal hypothesis. This was confirmed for posterior mean deviances obtained for both models (11.5 natural log units in favour of the causal model), and also for deviance information criteria (DIC) computed for a range of prior distributions. Overall, models ignoring hidden confounding or pleiotropy had significantly poorer DIC scores.

CONCLUSION

Results suggest causal association between 25-OHD and colorectal cancer, and support the need for randomised clinical trials for further confirmations.

The effect of non-differential measurement error on bias, precision and power in Mendelian randomization studies

BACKGROUND

Mendelian randomization (MR) studies assess the causality of associations between exposures and disease outcomes using data on genetic determinants of the exposure. In this work, we explore the effect of exposure and outcome measurement error in MR studies.

METHODS

For continuous traits, we describe measurement error in terms of a theoretical regression of the measured variable on the true variable. We quantify error in terms of the slope (calibration) and the R(2) values (discrimination or classical measurement error). We simulated cohort data sets under realistic parameters and used two-stage least squares regression to assess the effect of measurement error for continuous exposures and outcomes on bias, precision and power. For simulations of binary outcomes, we varied sensitivity and specificity.

RESULTS

Discrimination error in continuous exposures and outcomes did not bias the MR estimate, and only outcome discrimination error substantially reduced power. Calibration error biased the MR estimate when the exposure and the outcome measures were not calibrated in a similar fashion, but power was not affected. For binary outcomes, exposure calibration error introduced substantial bias (with negligible impact on power), but exposure discrimination error did not. Reduced outcome specificity and, to a lesser degree, reduced sensitivity biased MR estimates towards the null.

CONCLUSIONS

Understanding the potential effects of measurement error is an important consideration when interpreting estimates from MR analyses. Based on these results, future MR studies should consider methods for accounting for such error and minimizing its impact on inferences derived from MR analyses.

Vitamin D and mortality: a Mendelian randomization study

BACKGROUND

Decreased circulating 25-hydroxy-vitamin D (25-OH-vitamin D) concentrations have been associated with mortality rates, but it is unclear whether this association is causal. We performed a Mendelian randomization study and analyzed whether 3 common single-nucleotide polymorphisms (SNPs) associated with 25-OH-vitamin D concentrations are causal for mortality rates.

METHODS

Genotypes of SNPs in the group-specific component gene (GC, rs2282679), 7-dehydrocholesterol reductase gene (DHCR7, rs12785878), and cytochrome P450 IIR-1 gene (CYP2R1, rs10741657) were determined in a prospective cohort study of 3316 male and female participants [mean age 62.6 (10.6) years] scheduled for coronary angiography between 1997 and 2000. 25-OH-vitamin D concentrations were determined by RIA. The main outcome measures were all-cause deaths, cardiovascular deaths, and noncardiovascular deaths.

RESULTS

In a linear regression model adjusting for month of blood sampling, age, and sex, vitamin D concentrations were predicted by GC genotype (P < 0.001), CYP2R1 genotype (P = 0.068), and DHCR7 genotype (P < 0.001), with a coefficient of determination (r(2)) of 0.175. During a median follow-up time of 9.9 years, 955 persons (30.0%) died, including 619 deaths from cardiovascular causes. In a multivariate Cox regression adjusted for classical risk factors, GC, CYP2R1, and DHCR7 genotypes were not associated with all-cause mortality, cardiovascular mortality, or noncardiovascular mortality.

CONCLUSIONS

Genetic variants associated with 25-OH-vitamin D concentrations do not predict mortality. This suggests that low 25-OH-vitamin D concentrations are associated with, but unlikely to be causal for, higher mortality rates.

Mendelian randomization suggests non-causal associations of testosterone with cardiometabolic risk factors and mortality

Prospective studies showed that low serum testosterone concentrations are associated with various cardiometabolic risk factors and mortality. However, the causal nature of these associations is controversial. We studied 1 882 men aged 20-79 years with serum testosterone concentrations and genotyping data from the longitudinal population-based Study of Health in Pomerania. Testosterone concentrations were cross-sectionally associated with cardiometabolic risk factors, including anthropometric, lipid, blood pressure and glycaemic parameters; and prospectively with all-cause mortality (277 deaths, 14.7%) during the 10-year follow-up. To overcome problems of residual confounding, reverse causation, or regression dilution bias in the investigated testosterone-outcome associations, we used two-stage least square regression models with previously identified polymorphisms at the SHBG gene (rs12150660) and X chromosome (rs5934505) as multiple genetic instruments in an instrumental variable (IV) approach, also known as Mendelian randomization. In standard regression analyses, testosterone was robustly associated with a wide range of cardiometabolic risk factors. In subsequent IV analyses, no such significant associations were observed. Similarly, prospective analyses showed a consistent association of low testosterone concentrations with increased all-cause mortality risk, which was not apparent in subsequent IV analyses. The present Mendelian randomization analyses did not detect any evidence for causal associations of testosterone concentrations with cardiometabolic risk factors and mortality, suggesting that previously reported associations might largely result from residual confounding or reverse causation. Although testosterone assessment might improve risk prediction, implementation of testosterone replacement therapy requires further evidence of a direct effect on cardiometabolic outcomes from double-blinded randomized controlled trials and large-scale Mendelian randomization meta-analyses.

Serum uric acid and adiposity: deciphering causality using a bidirectional Mendelian randomization approach

Background

Although the relationship between serum uric acid (SUA) and adiposity is well established, the direction of the causality is still unclear in the presence of conflicting evidences. We used a bidirectional Mendelian randomization approach to explore the nature and direction of causality between SUA and adiposity in a population-based study of Caucasians aged 35 to 75 years.

Methods and Findings

We used, as instrumental variables, rs6855911 within the SUA gene SLC2A9 in one direction, and combinations of SNPs within the adiposity genes FTO, MC4R and TMEM18 in the other direction. Adiposity markers included weight, body mass index, waist circumference and fat mass. We applied a two-stage least squares regression: a regression of SUA/adiposity markers on our instruments in the first stage and a regression of the response of interest on the fitted values from the first stage regression in the second stage. SUA explained by the SLC2A9 instrument was not associated to fat mass (regression coefficient [95% confidence interval]: 0.05 [−0.10, 0.19] for fat mass) contrasting with the ordinary least square estimate (0.37 [0.34, 0.40]). By contrast, fat mass explained by genetic variants of the FTO, MC4R and TMEM18 genes was positively and significantly associated to SUA (0.31 [0.01, 0.62]), similar to the ordinary least square estimate (0.27 [0.25, 0.29]). Results were similar for the other adiposity markers.

Conclusions

Using a bidirectional Mendelian randomization approach in adult Caucasians, our findings suggest that elevated SUA is a consequence rather than a cause of adiposity.

Associations between serum uric acid and markers of subclinical atherosclerosis in young adults. The cardiovascular risk in Young Finns study

BACKGROUND AND METHODS

Serum uric acid (SUA) is a suggested biomarker for established coronary artery disease, but the role of SUA in early phases of atherosclerosis is controversial. The relations of SUA with vascular markers of subclinical atherosclerosis, including carotid artery intima-media thickness (cIMT), carotid plaque, carotid distensibility (Cdist) and brachial flow-mediated dilatation (FMD) were examined in 1985 young adults aged 30-45 years. In addition to ordinary regression, we used Mendelian randomization techniques to infer causal associations.

RESULTS

In women, the independent multivariate correlates of SUA included BMI, creatinine, alcohol use, triglycerides, glucose and adiponectin (inverse association) (Model R(2) = 0.30). In men, the correlates were BMI, creatinine, triglycerides, C-reactive protein, alcohol use, total cholesterol and adiponectin (inverse) (Model R(2) = 0.33). BMI alone explained most of the variation of SUA levels both in women and men (Partial R(2) ∼ 0.2). When SUA was modeled as an explanatory variable for vascular markers, it directly associated with cIMT and inversely with Cdist in age- and sex-adjusted analysis. After further adjustments for BMI or glomerular filtration rate, these relations were reduced to non-significance. No associations were found between SUA and FMD or the presence of a carotid plaque. Mendelian randomization analyses using known genetic variants for BMI and SUA confirmed that BMI is causally linked to SUA and that BMI is a significant confounder in the association between SUA and cIMT.

CONCLUSION

SUA is associated with cardiovascular risk markers in young adults, especially BMI, but we found no evidence that SUA would have an independent role in the pathophysiology of early atherosclerosis.