Mendelian randomization: application to cardiovascular disease

The immune factors have complex causal regulation effects on kidney stone disease: a mendelian randomization study

PURPOSE

Previous studies have reported the potential impact of immune cells on kidney stone disease (KSD), but definitive causal relationships have yet to be established. The purpose of this paper is to elucidate the potential causal association between immune cells and KSD by Mendelian randomization (MR) analysis.

METHODS

In our study, a thorough two-sample Mendelian randomization (MR) analysis was performed by us to determine the potential causal relationship between immune cell traits and kidney stone disease. We included a total of four immune traits (median fluorescence intensity (MFI), relative cellular (RC), absolute cellular (AC), and morphological parameters (MP)), which are publicly available data. GWAS summary data related to KSD (9713 cases and 366,693 controls) were obtained from the FinnGen consortium. The primary MR analysis method was Inverse variance weighted. Cochran's Q test, MR Egger, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) were used to assess the stability of the results.

RESULTS

After FDR correction, the CD8 on HLA DR + CD8br (OR = 0.95, 95% CI = 0.93-0.98, p-value = 7.20 × 10- 4, q-value = 0.088) was determined to be distinctly associated with KSD, and we also found other 25 suggestive associations between immune cells and KSD, of which 13 associations were suggested as protective factors and 12 associations were suggested as risk factors. There was no horizontal pleiotropy or significant heterogeneity in our MR analysis, as determined by the p-value results of our Cochrane Q-test, MR Egger's intercept test, and MR-PRESSO, which were all > 0.05.

CONCLUSIONS

Our study has explored the potential causal connection between immune cells and KSD by Mendelian randomization analysis, thus providing some insights for future clinical studies.

Causal relationship between immune cells and aortic aneurysms: a Mendelian randomization study

OBJECTIVES

The causal association between immune cell traits and aortic aneurysm remains unknown.

METHODS

We performed a bidirectional two-sample Mendelian randomization analysis to explore the causality between 731 immune cell characteristics and the risk of abdominal aortic aneurysm and thoracic aortic aneurysms through publicly available genetic data, respectively. To examine heterogeneity and horizontal pleiotropy, Cochran's Q test and MR-Egger intercept were utilized. Additionally, multivariable Mendelian randomization analysis and meta-analysis were performed in further analysis.

RESULTS

We found that 20 immune phenotypes had a suggestive causality on abdominal aortic aneurysm, and 15 immune phenotypes had a suggestive causal effect on thoracic aortic aneurysm. After further false discovery rate adjustment (q value <0.1), CD20 on IgD+ CD38- B cell (q = 0.053) and CD127 on CD28+ CD4+ T cell (q = 0.096) were associated with an increased risk of abdominal aortic aneurysm, respectively, indicating a significant causality between them. After adjusting for smoking, there is still statistical significance between CD127 on CD28+ CD4+ T cell and abdominal aortic aneurysm. However, after adjusting for lipids, no statistical significance can be observed between CD127 on CD28+ CD4+ T cells and abdominal aortic aneurysm. Furthermore, there is still statistical significance between CD20 on IgD+ CD38- B cells and abdominal aortic aneurysm after adjusting for lipids and smoking, which was further identified by meta-analysis.

CONCLUSIONS

We found a causal association between immune cell traits and aortic aneurysm by genetic methods, thus providing new avenues for future mechanism studies.

Causal role of immune cells in hypertension: a bidirectional Mendelian randomization study

Background

Although Hypertension (HTN) is considered to be a cardiovascular disease caused by multiple factors, the cause of it is still unknown. In this study, we aim to find out whether circulating immune cell characteristics have an impact on susceptibility to HTN.

Methods

This study employed a comprehensive two-sample Mendelian randomization (MR) analysis to investigate the causal association between immune cell characteristics and HTN. Utilizing publicly accessible genetic data, we examined the causal relationship between HTN and the susceptibility to 731 immune cell signatures. To ensure the reliability and validity of the findings, a comprehensive sensitivity analysis was conducted to assess heterogeneity, confirm the robustness of the results and evaluate the presence of horizontal pleiotropy.

Results

After FDR correction, immune phenotype had an effect on HTN. In our study, one immunophenotype was identified as being positively associated with HTN risk significance: HLA DR on CD33- HLA DR+. In addition, we examined 8 immune phenotype with no statistically significant effect of HTN, but it is worth mentioning that they had an unadjusted low P-value phenotype.

Conclusions

Our MR study by genetic means demonstrated the close relationship between HTN and immune cells, thus providing guidance for future clinical prediction and subsequent treatment of HTN.

Assessment of the relationship between gut microbiota and bone mineral density: a two-sample Mendelian randomization study

Background

Emerging evidence from observational studies and clinical trials suggests a connection between the gut microbiota and variations in bone mineral density (BMD). Nonetheless, the specific association between gut microbiota and BMD alterations at different skeletal sites has not been comprehensively explored. To address this, we employed Genome-Wide Association Study (GWAS) summary statistics from a publicly accessible database, conducting a two-sample Mendelian Randomization analysis to elucidate the potential causal relationship between gut microbiota composition and BMD.

Methods

This study utilized two distinct thresholds for screening instrumental variables (IVs), followed by an extensive series of quality control procedures to identify IVs that were significantly related to exposure. Gut microbiota were classified into two sets based on hierarchical levels: phylum, class, order, family, and genus. Bone mineral density (BMD) data were systematically collected from four skeletal sites: femoral neck, lumbar spine, forearm, and heel. For Mendelian Randomization (MR) analysis, robust methods including Inverse-Variance Weighting (IVW) and the Wald Ratio Test were employed. Additional analytical tests such as the Outlier Test, Heterogeneity Test, 'Leave-One-Out' Test, and Pleiotropy Test were conducted to assess the impact of horizontal pleiotropy, heterogeneities, and the genetic variation stability of gut microbiota on BMD causal associations. The MR Steiger Directionality Test was applied to exclude studies with potential directional biases.

Results

In this two-sample Mendelian randomization analysis, we utilized five sets of exposure GWAS (Genome-Wide Association Studies) summary statistics and four sets of outcome GWAS summary statistics. The initial analysis, applying a threshold of p < 5 × 10-6, identified 48 significant causal relationships between genetic liability in the gut microbiome and bone mineral density (BMD). A subsequent analysis with a more stringent threshold of p < 5 × 10-8 uncovered 14 additional causal relationships. Upon applying the Bonferroni correction, 9 results from the first analysis and 10 from the second remained statistically significant.

Conclusion

Our MR analysis revealed a causal relationship between gut microbiota and bone mineral density at all sites, which could lead to discoveries in future mechanistic and clinical studies of microbiota-associated osteoporosis.

A Mendelian analysis of the relationships between immune cells and breast cancer

Background

Emerging evidence showed immune cells were associated with the development of breast cancer. Nonetheless, the causal link between them remains uncertain. Consequently, the objective of this study was to investigate the causal connection between immune traits and the likelihood of developing breast cancer.

Methods

A two-sample Mendelian randomization (MR) analysis was conducted to establish the causal relationship between immune cells and breast cancer in this study. Utilizing publicly accessible genetic data, we investigated causal connections between 731 immune cells and the occurrence of breast cancer. The primary approach for exploring this relationship was the application of the inverse-variance-weighted (IVW) method. Furthermore, sensitivity analyses, encompassing the leave-one-out analysis, Cochran Q test, and Egger intercept test were performed to validate the reliability of the Mendelian randomization results. Finally, we used Bayesian Weighted Mendelian Randomization (BWMR) approach to test the results of MR study.

Results

According to the Bonferroni correction, no immune trait was identified with a decreased or increased risk of overall breast cancer risk. As for the ER+ breast cancer, 6 immune trait was identified after the Bonferroni method. the IVW method results showed that CD45RA- CD4+ %CD4+ (p-value:1.37×10-6), CD8dim %T cell (p-value:4.62×10-43), BAFF-R on IgD+ CD38- unsw mem (p-value:6.93×10-5), CD27 on PB/PC (p-value:2.72×10-18) lowered the risk of breast cancer. However, CD19 on IgD- CD38br (p-value:1.64×10-6), CD25 on IgD+ CD38dim (p-value: - ∞) were associated with a higher risk of developing breast cancer. As for the CX3CR1 on CD14+ CD16- monocyte (p-value: 1.15×10-166), the IVW method clearly demonstrated a protective effect against ER- breast cancer. For the above positive results, BAFF-R on IgD+ CD38- unsw mem was the sole association linked to reduced breast cancer risk using the BWMR method. The intercept terms' p-values in MR-Egger regression all exceeded 0.05, indicating the absence of potential horizontal pleiotropy.

Conclusion

Through genetic approaches, our study has illustrated the distinct correlation between immune cells and breast cancer, potentially paving the way for earlier diagnosis and more efficient treatment alternatives.

Causal association of immune cells and polycystic ovarian syndrome: a Mendelian randomization study

Background

Polycystic ovarian syndrome (PCOS) is a common reproductive disorder that affects a considerable number of women worldwide. It is accompanied by irregular menstruation, hyperandrogenism, metabolic abnormalities, reproductive disorders and other clinical symptoms, which seriously endangers women's physical and mental health. The etiology and pathogenesis of PCOS are not completely clear, but it is hypothesized that immune system may play a key role in it. However, previous studies investigating the connection between immune cells and PCOS have produced conflicting results.

Methods

Mendelian randomization (MR) is a powerful study design that uses genetic variants as instrumental variables to enable examination of the causal effect of an exposure on an outcome in observational data. In this study, we utilized a comprehensive two-sample MR analysis to examine the causal link between 731 immune cells and PCOS. We employed complementary MR methods, such as the inverse-variance weighted (IVW) method, and conducted sensitivity analyses to evaluate the reliability of the outcomes.

Results

Four immunophenotypes were identified to be significantly associated with PCOS risk: Memory B cell AC (IVW: OR [95%]: 1.123[1.040 to 1.213], p = 0.003), CD39+ CD4+ %CD4+ (IVW: OR [95%]: 0.869[0.784 to 0.963], p = 0.008), CD20 on CD20- CD38-(IVW: OR [95%]:1.297[1.088 to 1.546], p = 0.004), and HLA DR on CD14- CD16+ monocyte (IVW: OR [95%]:1.225[1.074 to 1.397], p = 0.003). The results of the sensitivity analyses were consistent with the main findings.

Conclusions

Our MR analysis provides strong evidence supporting a causal association between immune cells and the susceptibility of PCOS. This discovery can assist in clinical decision-making regarding disease prognosis and treatment options, and also provides a new direction for drug development.

Causal role of immune cells in schizophrenia: Mendelian randomization (MR) study

BACKGROUND

Complex immune-brain interactions that affect neural development, survival and function might have causal and therapeutic implications for psychiatric illnesses. However, previous studies examining the association between immune inflammation and schizophrenia (SCZ) have yielded inconsistent findings.

METHODS

Comprehensive two-sample Mendelian randomization (MR) analysis was performed to determine the causal association between immune cell signatures and SCZ in this study. Based on publicly available genetic data, we explored causal associations between 731 immune cell signatures and SCZ risk. A total of four types of immune signatures (median fluorescence intensities (MFI), relative cell (RC), absolute cell (AC), and morphological parameters (MP)) were included. Comprehensive sensitivity analyses were used to verify the robustness, heterogeneity, and horizontal pleiotropy of the results.

RESULTS

After FDR correction, SCZ had no statistically significant effect on immunophenotypes. It was worth mentioning some phenotypes with unadjusted low P-values, including FSC-A on NKT (β = 0.119, 95% CI = 0.044 ~ 0.194, P = 0.002), DN (CD4-CD8-) NKT %T cell (β = 0.131, 95% CI = 0.054 ~ 0.208, P = 9.03 × 10- 4), and SSC-A on lymphocytes (β = 0.136, 95% CI = 0.059 ~ 0.213, P = 5.43 × 10- 4). The causal effect of SCZ IgD on transitional was estimated to 0.127 (95% CI = 0.051 ~ 0.203, P = 1.09 × 10- 3). SCZ also had a causal effect on IgD+ %B cell (β = 0.130, 95% CI = 0.054 ~ 0.207, P = 8.69 × 10- 4), and DP (CD4+CD8+) %T cell (β = 0.131, 95% CI = 0.054 ~ 0.207, P = 8.05 × 10- 4). Furthermore, four immunophenotypes were identified to be significantly associated with SCZ risk: naive CD4+ %T cell (OR = 0.986, 95% CI = 0.979 ~ 0.992, P = 1.37 × 10- 5), HLA DR on CD14- CD16- (OR = 0.738 (95% CI = 0.642 ~ 0.849, P = 2.00 × 10- 5), CD33dim HLA DR+ CD11b- AC (OR = 0.631, 95% CI = 0.529 ~ 0.753, P = 3.40 × 10- 7) and activated & resting Treg % CD4 Treg (OR = 0.937, 95% CI = 0.906 ~ 0.970, P = 1.96 × 10- 4).

CONCLUSIONS

Our study has demonstrated the close connection between immune cells and SCZ by genetic means, thus providing guidance for future clinical research.

Cigarette smoking, coffee consumption, alcohol intake, and clozapine metabolism: A Mendelian randomization study

BACKGROUND

Clozapine is an effective antipsychotic medication for patients with treatment-resistant schizophrenia. Previous studies revealed that smoking, alcohol intake, and coffee consumption altered the metabolism of clozapine. However, causal associations between substance use and clozapine levels were not sufficiently established.

METHODS

Several genome-wide association studies provided genetic tools for six measures of substance use, including age of smoking, cigarettes per day, smoking cessation, smoking initiation, coffee consumption, and alcohol consumption (GWASs). Utilizing the CLOZUK consortium's dataset, their associations with clozapine and its metabolite concentrations were evaluated. All GWAS data were collected from the European population. Mendelian randomization (MR) estimations from each genetic test were combined using inverse variance weighted (IVW) meta-analysis in combination with complementing techniques (such as weighted median and MR Egger). We also analyze horizontal pleiotropy and heterogeneity using various sensitivity analyses.

RESULTS

Genetically predicted higher level of smoking initiation was significantly associated with reduced clozapine (β = -0.14, P = 4.53E-04) concentrations and norclozapine concentrations (β = -0.14, P = 3.33E-04), and increased coffee consumption was significantly associated with lower level of clozapine concentrations (β = -0.42, P = 1.70E-14), norclozapine concentrations (β = -0.27, P = 1.51E-07), and the metabolic ratio of clozapine to norclozapine (β = -0.15, P = 5.35E-07), survived after the Bonferroni correction (P = 0.05/6 = 0.008). In sensitivity analyses, the weighted median and MR Egger methods demonstrated directionally consistent effects. In addition, our sensitive test indicated no significant horizontal pleiotropy and heterogeneity (P > 0.05). However, other measures of substance use (age of initiation smoking, cigarettes per day, smoking cessation, and drinks per week) were not associated with clozapine metabolism.

CONCLUSION

Our investigation revealed a correlation between greater smoking initiation and coffee consumption and reduced blood levels of clozapine and norclozapine. Providing clinicians with guidance on how to adjust clozapine levels for clozapine-treated patients.

Circulating ceramides as biomarkers of cardiovascular disease: Evidence from phenotypic and genomic studies

There is a need for new biomarkers of atherosclerotic cardiovascular disease (ACVD), the main cause of death globally. Ceramides, a class of potent bioactive lipid mediators, have signalling roles in apoptosis, cellular stress and inflammation. Recent studies have highlighted circulating ceramides as novel biomarkers of coronary artery disease, type-2 diabetes and insulin resistance. Ceramides are highly regulated by enzymatic reactions throughout the body in terms of their activity and metabolism, including production, degradation and transport. The genetic studies that have been completed to date on the main ceramide species found in circulation are described, highlighting the importance of DNA variants in genes involved in ceramide biosynthesis as key influencers of heritable, circulating ceramide levels. We also review studies of disease associations with ceramides and discuss mechanistic insights deriving from recent genomic studies. The signalling activities of ceramides in vascular inflammation and apoptosis, associations between circulating ceramides and coronary artery disease risk, type-2 diabetes and insulin resistance, and the potential importance of ceramides with regard to ACVD risk factors, such as blood pressure, lipoproteins and lifestyle factors, are also discussed.

Using genetics to decipher the link between type 2 diabetes and cancer: shared aetiology or downstream consequence?

Recent developments in the field of genetics have accelerated our understanding of the aetiology of complex diseases. Type 2 diabetes mellitus and cancer are no exception, with large-scale genome-wide association studies (GWAS) facilitating exploration of the underlying pathology. Here, we discuss how genetics studies can be used to investigate the relationship between these complex diseases. Observational epidemiological studies consistently report that people with type 2 diabetes have a higher risk of several types of cancer. Indeed, type 2 diabetes and cancer share many common risk factors, such as obesity, ageing, poor diet and low levels of physical activity. However, questions remain regarding the biological mechanisms that link these two diseases. Large-scale GWAS of type 2 diabetes and cancer allow us to consider the evidence for shared genetic architecture. Several shared susceptibility genes have been identified, yet tissue specificity and direction of effect must be taken into account when considering common genetic aetiology. We also consider how GWAS, and associated techniques such as Mendelian randomisation, allow us to dissect the link between the two diseases and address questions such as 'Does type 2 diabetes cause cancer or is the increased risk observed driven by higher adiposity or another associated metabolic feature?' Graphical abstract.

Appraising causal relationships of dietary, nutritional and physical-activity exposures with overall and aggressive prostate cancer: two-sample Mendelian-randomization study based on 79 148 prostate-cancer cases and 61 106 controls

BACKGROUND

Prostate cancer is the second most common male cancer worldwide, but there is substantial geographical variation, suggesting a potential role for modifiable risk factors in prostate carcinogenesis.

METHODS

We identified previously reported prostate cancer risk factors from the World Cancer Research Fund (WCRF)'s systematic appraisal of the global evidence (2018). We assessed whether each identified risk factor was causally associated with risk of overall (79 148 cases and 61 106 controls) or aggressive (15 167 cases and 58 308 controls) prostate cancer using Mendelian randomization (MR) based on genome-wide association-study summary statistics from the PRACTICAL and GAME-ON/ELLIPSE consortia. We assessed evidence for replication in UK Biobank (7844 prostate-cancer cases and 204 001 controls).

RESULTS

WCRF identified 57 potential risk factors, of which 22 could be instrumented for MR analyses using single nucleotide polymorphisms. For overall prostate cancer, we identified evidence compatible with causality for the following risk factors (odds ratio [OR] per standard deviation increase; 95% confidence interval): accelerometer-measured physical activity, OR = 0.49 (0.33-0.72; P = 0.0003); serum iron, OR = 0.92 (0.86-0.98; P = 0.007); body mass index (BMI), OR = 0.90 (0.84-0.97; P = 0.003); and monounsaturated fat, OR = 1.11 (1.02-1.20; P = 0.02). Findings in our replication analyses in UK Biobank were compatible with our main analyses (albeit with wide confidence intervals). In MR analysis, height was positively associated with aggressive-prostate-cancer risk: OR = 1.07 (1.01-1.15; P = 0.03).

CONCLUSIONS

The results for physical activity, serum iron, BMI, monounsaturated fat and height are compatible with causality for prostate cancer. The results suggest that interventions aimed at increasing physical activity may reduce prostate-cancer risk, although interventions to change other risk factors may have negative consequences on other diseases.

Causal Inference in Cancer Epidemiology: What Is the Role of Mendelian Randomization?

Observational epidemiologic studies are prone to confounding, measurement error, and reverse causation, undermining robust causal inference. Mendelian randomization (MR) uses genetic variants to proxy modifiable exposures to generate more reliable estimates of the causal effects of these exposures on diseases and their outcomes. MR has seen widespread adoption within cardio-metabolic epidemiology, but also holds much promise for identifying possible interventions for cancer prevention and treatment. However, some methodologic challenges in the implementation of MR are particularly pertinent when applying this method to cancer etiology and prognosis, including reverse causation arising from disease latency and selection bias in studies of cancer progression. These issues must be carefully considered to ensure appropriate design, analysis, and interpretation of such studies. In this review, we provide an overview of the key principles and assumptions of MR, focusing on applications of this method to the study of cancer etiology and prognosis. We summarize recent studies in the cancer literature that have adopted a MR framework to highlight strengths of this approach compared with conventional epidemiological studies. Finally, limitations of MR and recent methodologic developments to address them are discussed, along with the translational opportunities they present to inform public health and clinical interventions in cancer. Cancer Epidemiol Biomarkers Prev; 27(9); 995-1010. ©2018 AACR.

Exploring causality in the association between circulating 25-hydroxyvitamin D and colorectal cancer risk: a large Mendelian randomisation study

BACKGROUND

Whilst observational studies establish that lower plasma 25-hydroxyvitamin D (25-OHD) levels are associated with higher risk of colorectal cancer (CRC), establishing causality has proven challenging. Since vitamin D is modifiable, these observations have substantial clinical and public health implications. Indeed, many health agencies already recommend supplemental vitamin D. Here, we explore causality in a large Mendelian randomisation (MR) study using an improved genetic instrument for circulating 25-OHD.

METHODS

We developed a weighted genetic score for circulating 25-OHD using six genetic variants that we recently reported to be associated with circulating 25-OHD in a large genome-wide association study (GWAS) meta-analysis. Using this score as instrumental variable in MR analyses, we sought to determine whether circulating 25-OHD is causally linked with CRC risk. We conducted MR analysis using individual-level data from 10,725 CRC cases and 30,794 controls (Scotland, UK Biobank and Croatia). We then applied estimates from meta-analysis of 11 GWAS of CRC risk (18,967 cases; 48,168 controls) in a summary statistics MR approach.

RESULTS

The new genetic score for 25-OHD was strongly associated with measured plasma 25-OHD levels in 2821 healthy Scottish controls (P = 1.47 × 10- 11), improving upon previous genetic instruments (F-statistic 46.0 vs. 13.0). However, individual-level MR revealed no association between 25-OHD score and CRC risk (OR 1.03/unit log-transformed circulating 25-OHD, 95% CI 0.51-2.07, P = 0.93). Similarly, we found no evidence for a causal relationship between 25-OHD and CRC risk using summary statistics MR analysis (OR 0.91, 95% CI 0.69-1.19, P = 0.48).

CONCLUSIONS

Despite the scale of this study and employing an improved score capturing more of the genetic contribution to circulating 25-OHD, we found no evidence for a causal relationship between circulating 25-OHD and CRC risk. Although the magnitude of effect for vitamin D suggested by observational studies can confidently be excluded, smaller effects sizes and non-linear relationships remain plausible. Circulating vitamin D may be a CRC biomarker, but a causal effect on CRC risk remains unproven.

MELODI: Mining Enriched Literature Objects to Derive Intermediates

BACKGROUND

The scientific literature contains a wealth of information from different fields on potential disease mechanisms. However, identifying and prioritizing mechanisms for further analytical evaluation presents enormous challenges in terms of the quantity and diversity of published research. The application of data mining approaches to the literature offers the potential to identify and prioritize mechanisms for more focused and detailed analysis.

METHODS

Here we present MELODI, a literature mining platform that can identify mechanistic pathways between any two biomedical concepts.

RESULTS

Two case studies demonstrate the potential uses of MELODI and how it can generate hypotheses for further investigation. First, an analysis of ETS-related gene ERG and prostate cancer derives the intermediate transcription factor SP1, recently confirmed to be physically interacting with ERG. Second, examining the relationship between a new potential risk factor for pancreatic cancer identifies possible mechanistic insights which can be studied in vitro.

CONCLUSIONS

We have demonstrated the possible applications of MELODI, including two case studies. MELODI has been implemented as a Python/Django web application, and is freely available to use at [www.melodi.biocompute.org.uk].

Genetically Driven Hyperglycemia Increases Risk of Coronary Artery Disease Separately From Type 2 Diabetes

OBJECTIVE

This study tested the hypothesis that genetically raised hyperglycemia increases coronary artery disease (CAD) risk separately from the risk conferred by type 2 diabetes as a whole.

RESEARCH DESIGN AND METHODS

We conducted a Mendelian randomization (MR) analysis using summary-level statistics from the largest published meta-analyses of genome-wide association studies (GWAS) for fasting glucose (FG) (n = 133,010 participants free of diabetes) and CAD (n = 63,746 case subjects and 130,681 control subjects) of predominantly European ancestry. FG-increasing variants associated with type 2 diabetes from the largest GWAS for type 2 diabetes were excluded. Variants with pleiotropic effects on other CAD risk factors (blood lipids, blood pressure, and obesity) were excluded using summary-level data from the largest published GWAS. Data from the Framingham Heart Study were used to validate the MR instrument and to build an FG genetic risk score (GRS).

RESULTS

In an instrumental variable analysis comprising 12 FG-raising variants, a 1 mmol/L increase in FG revealed an effect-size estimate of 1.43 CAD odds (95% CI 1.14-1.79). The association was preserved after excluding variants for heterogeneity and pleiotropic effects on other CAD risk factors (odds ratio [OR] 1.33 [95% CI 1.02-1.73]). The 12 FG-increasing variants did not significantly increase type 2 diabetes risk (OR 1.05 [95% CI 0.91-1.23]), and its prevalence was constant across FG GRS quintiles (P = 0.72).

CONCLUSIONS

Our data support that genetic predisposition to hyperglycemia raises the odds of CAD separately from type 2 diabetes and other CAD risk factors. These findings suggest that modulating glycemia may provide cardiovascular benefit.

A Mendelian randomization study of the effect of type-2 diabetes on coronary heart disease

In observational studies, type-2 diabetes (T2D) is associated with an increased risk of coronary heart disease (CHD), yet interventional trials have shown no clear effect of glucose-lowering on CHD. Confounding may have therefore influenced these observational estimates. Here we use Mendelian randomization to obtain unconfounded estimates of the influence of T2D and fasting glucose (FG) on CHD risk. Using multiple genetic variants associated with T2D and FG, we find that risk of T2D increases CHD risk (odds ratio (OR)=1.11 (1.05–1.17), per unit increase in odds of T2D, P=8.8 × 10⁻⁵; using data from 34,840/114,981 T2D cases/controls and 63,746/130,681 CHD cases/controls). FG in non-diabetic individuals tends to increase CHD risk (OR=1.15 (1.00–1.32), per mmol·per l, P=0.05; 133,010 non-diabetic individuals and 63,746/130,681 CHD cases/controls). These findings provide evidence supporting a causal relationship between T2D and CHD and suggest that long-term trials may be required to discern the effects of T2D therapies on CHD risk.

In order to effectively design interventions, it is useful to understand the complex interplay between multiple syndromes. Here, Ahmad et al. use genome-wide association study data and Mendelian randomisation to examine the influence of Type 2 diabetes and fasting glucose levels on coronary heart disease.

Adiposity as a cause of cardiovascular disease: a Mendelian randomization study

BACKGROUND

Adiposity, as indicated by body mass index (BMI), has been associated with risk of cardiovascular diseases in epidemiological studies. We aimed to investigate if these associations are causal, using Mendelian randomization (MR) methods.

METHODS

The associations of BMI with cardiovascular outcomes [coronary heart disease (CHD), heart failure and ischaemic stroke], and associations of a genetic score (32 BMI single nucleotide polymorphisms) with BMI and cardiovascular outcomes were examined in up to 22,193 individuals with 3062 incident cardiovascular events from nine prospective follow-up studies within the ENGAGE consortium. We used random-effects meta-analysis in an MR framework to provide causal estimates of the effect of adiposity on cardiovascular outcomes.

RESULTS

There was a strong association between BMI and incident CHD (HR = 1.20 per SD-increase of BMI, 95% CI, 1.12-1.28, P = 1.9.10(-7)), heart failure (HR = 1.47, 95% CI, 1.35-1.60, P = 9.10(-19)) and ischaemic stroke (HR = 1.15, 95% CI, 1.06-1.24, P = 0.0008) in observational analyses. The genetic score was robustly associated with BMI (β = 0.030 SD-increase of BMI per additional allele, 95% CI, 0.028-0.033, P = 3.10(-107)). Analyses indicated a causal effect of adiposity on development of heart failure (HR = 1.93 per SD-increase of BMI, 95% CI, 1.12-3.30, P = 0.017) and ischaemic stroke (HR = 1.83, 95% CI, 1.05-3.20, P = 0.034). Additional cross-sectional analyses using both ENGAGE and CARDIoGRAMplusC4D data showed a causal effect of adiposity on CHD.

CONCLUSIONS

Using MR methods, we provide support for the hypothesis that adiposity causes CHD, heart failure and, previously not demonstrated, ischaemic stroke.

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.

Lack of association between DRD2 and OPRM1 genotypes and adiposity

BACKGROUND

Dopaminergic and opioid systems are both involved in food intake and appetite control. The dopamine D2 receptor gene (DRD2) and the μ-opioid receptor gene (OPRM1) therefore represent plausible candidates for association with obesity.

OBJECTIVE

Previous studies of these variants have yielded inconsistent findings, which are likely due to insufficient statistical power. The aim of the current study was to determine whether, in a large population-based sample, there are associations between adiposity and (i) the A1 (T) allele of the Taq1A polymorphism (rs1800497) in DRD2 and (ii) the G allele of the A118G polymorphism (rs1799971) in OPRM1.

STUDY POPULATION

Annual clinic-based measures of body mass index (BMI) and waist circumference were taken from children (N=3720) at 5 measurement time points from ages 7 through to 11 years. BMI was also recorded in their mothers (N=2460) at comparable time points and at pre-pregnancy. All participants were genotyped. Our study was powered (at 80%) to detect per-allele effects on BMI of 0.21 kg m(-2).

RESULTS

Our results indicate a lack of association between DRD2 and OPRM1 genotypes and adiposity. Combining the data across mothers and children found per-allele effects on BMI of 0.02 kg m(-2) (95% confidence interval (CI): -0.17, 0.20), P=0.9 for rs1800497 and -0.08 kg m(-2) (95% CI: -0.29, 0.22), P=0.4 for rs1799971. As a positive control, we also examined the effect of FTO genotype over the same time period and confirmed the expected relationship between variability at this locus and higher adiposity.

CONCLUSION

Our findings question existing evidence suggesting associations at DRD2 and OPRM1 loci and adiposity. They also highlight the caution required when employing candidate gene approaches to further our understanding of the neurobiology of eating and obesity.

Genetically elevated bilirubin and risk of ischaemic heart disease: three Mendelian randomization studies and a meta-analysis

BACKGROUND

Elevated plasma levels of bilirubin, an endogenous antioxidant, have been associated with reduced risk of ischaemic heart disease (IHD) and myocardial infarction (MI). Whether this is a causal relationship remains unclear.

OBJECTIVE

We tested the hypothesis that elevated plasma bilirubin is causally related to decreased risk of IHD and MI.

DESIGN

We used a Mendelian randomization approach and three independent studies from Copenhagen, Denmark. We measured bilirubin in 43 708 white individuals from the general population, and genotyped rs6742078 G>T in the uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1) gene in 67 068 individuals, of whom 11 686 had IHD.

RESULTS

Third versus first tertile of baseline bilirubin levels was associated with 134% increased bilirubin levels, with sex- and age-adjusted hazard ratios (HRs) of 0.86 [95% confidence interval (CI), 0.76-0.98; P = 0.02] for IHD and 0.81 (95% CI, 0.66-0.99; P = 0.04) for MI, but with corresponding multifactorially adjusted HRs of 0.93 (95% CI, 0.82-1.06; P = 0.29) and 0.90 (95% CI, 0.73-1.12; P = 0.35). UGT1A1 rs6742078 TT versus GG genotype was associated with 95% increased bilirubin levels (P < 0.001); TT versus GG genotype was associated with odds ratios (ORs) of 1.03 (95% CI, 0.96-1.11; P = 0.73) for IHD and 1.01 (95% CI, 0.92-1.12; P = 0.68) for MI. Finally, in a meta-analysis of the present three studies and eight previous studies including a total of 14 711 cases and 60 324 controls, the random effects OR for ischaemic cardiovascular disease for genotypes with approximately 100% increased bilirubin levels versus reference genotypes was 1.01 (95% CI, 0.88-1.16).

CONCLUSION

These data suggest that plasma bilirubin is not causally associated with risk of IHD.

Two-step epigenetic Mendelian randomization: a strategy for establishing the causal role of epigenetic processes in pathways to disease

The burgeoning interest in the field of epigenetics has precipitated the need to develop approaches to strengthen causal inference when considering the role of epigenetic mediators of environmental exposures on disease risk. Epigenetic markers, like any other molecular biomarker, are vulnerable to confounding and reverse causation. Here, we present a strategy, based on the well-established framework of Mendelian randomization, to interrogate the causal relationships between exposure, DNA methylation and outcome. The two-step approach first uses a genetic proxy for the exposure of interest to assess the causal relationship between exposure and methylation. A second step then utilizes a genetic proxy for DNA methylation to interrogate the causal relationship between DNA methylation and outcome. The rationale, origins, methodology, advantages and limitations of this novel strategy are presented.

The role of longitudinal cohort studies in epigenetic epidemiology: challenges and opportunities

Longitudinal cohort studies are ideal for investigating how epigenetic patterns change over time and relate to changing exposure patterns and the development of disease. We highlight the challenges and opportunities in this approach.

Prenatal nutrition, epigenetics and schizophrenia risk: can we test causal effects?

We posit that maternal prenatal nutrition can influence offspring schizophrenia risk via epigenetic effects. In this article, we consider evidence that prenatal nutrition is linked to epigenetic outcomes in offspring and schizophrenia in offspring, and that schizophrenia is associated with epigenetic changes. We focus upon one-carbon metabolism as a mediator of the pathway between perturbed prenatal nutrition and the subsequent risk of schizophrenia. Although post-mortem human studies demonstrate DNA methylation changes in brains of people with schizophrenia, such studies cannot establish causality. We suggest a testable hypothesis that utilizes a novel two-step Mendelian randomization approach, to test the component parts of the proposed causal pathway leading from prenatal nutritional exposure to schizophrenia. Applied here to a specific example, such an approach is applicable for wider use to strengthen causal inference of the mediating role of epigenetic factors linking exposures to health outcomes in population-based studies.