Network Mendelian Randomization Study Design to Assess Factors Mediating the Causal Link Between Telomere Length and Heart Disease

Lipids, lipid-lowering agents, and inflammatory bowel disease: a Mendelian randomization study

Background

To assess the causal role of lipid traits and lipid-lowering agents in inflammatory bowel disease (IBD).

Methods

Univariable mendelian randomization (MR) and multivariable MR (MVMR) analyses were conducted to evaluate the causal association between low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C) and IBD. Drug-targeted MR analyzed the effects of lipid-lowering drugs on IBD, and network MR was used to analyze potential mediation effects.

Results

The levels of HDL-C had an inverse relationship with the risk of Crohn's disease (CD, OR: 0.85, 95% CI: 0.73-0.98, P = 0.024). In MVMR, the inverse relationships were found in all three outcomes. Drug-targeted MR analyses showed that with one-SD LDL-C decrease predicted by variants at or near proprotein convertase subtilisin/kexin type 9 (PCSK9), the OR values of people diagnosed with IBD, ulcerative colitis (UC) and CD were 1.75 (95%CI: 1.13-2.69, P = 0.011), 2.1 (95%CI: 1.28-3.42, P = 0.003) and 2.24 (95%CI: 1.11-4.5, P = 0.024), respectively. With one-SD LDL-C decrease predicted by variants at or near cholesteryl ester transfer protein (CETP), the OR value of people diagnosed with CD was 0.12 (95%CI: 0.03-0.51, P = 0.004). Network-MR showed that HDL-C mediated the causal pathway from variants at or near CETP to CD.

Conclusion

Our study suggested a causal association between HDL-C and IBD, UC and CD. Genetically proxied inhibition of PCSK9 increased the risk of IBD, UC and CD, while inhibition of CETP decreased the risk of CD. Further studies are needed to clarify the long-term effect of lipid-lowering drugs on the gastrointestinal disorders.

Network Mendelian randomization study: exploring the causal pathway from insomnia to type 2 diabetes

INTRODUCTION

Insomnia is a novel pathogen for type 2 diabetes mellitus (T2DM). However, mechanisms linking insomnia and T2DM are poorly understood. In this study, we apply a network Mendelian randomization (MR) framework to determine the causal association between insomnia and T2DM and identify the potential mediators, including overweight (body mass index (BMI), waist-to-hip ratio, and body fat percentage) and glycometabolism (HbA1c, fasting blood glucose, and fasting blood insulin).

RESEARCH DESIGN AND METHODS

We use the MR framework to detect effect estimates of the insomnia-T2DM, insomnia-mediator, and mediator-T2DM associations. A mediator between insomnia and T2DM is established if MR studies in all 3 steps prove causal associations.

RESULTS

In the Inverse variance weighted method, the results show that insomnia will increase the T2DM risk (OR 1.142; 95% CI 1.072 to 1.216; p=0.000), without heterogeneity nor horizontal pleiotropy, strongly suggesting that genetically predicted insomnia has a causal association with T2DM. Besides, our MR analysis provides strong evidence that insomnia is causally associated with BMI and body fat percentage. There is also suggestive evidence of an association between insomnia and the waist-to-hip ratio. At the same time, our results indicate that insomnia is not causally associated with glycometabolism. Higher BMI, waist-to-hip ratio, and body fat percentage levels are strongly associated with increased risk of T2DM.

CONCLUSIONS

Genetically predicted insomnia has a causal association with T2DM. Being overweight (especially BMI and body fat percentage) mediates the causal pathway from insomnia to T2DM.

Causal effect of education on type 2 diabetes: A network Mendelian randomization study

BACKGROUND

The causality between education and type 2 diabetes (T2DM) remains unclear.

AIM

To identify the causality between education and T2DM and the potential metabolic risk factors [coronary heart disease (CHD), total cholesterol, low-density lipoprotein, triglycerides (TG), body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), fasting insulin, fasting glucose, and glycated hemoglobin] from summarized genome-wide association study (GWAS) data used a network Mendelian randomization (MR).

METHODS

Two-sample MR and network MR were performed to obtain the causality between education-T2DM, education-mediator, and mediator-T2DM. Summary statistics from the Social Science Genetic Association Consortium (discovery data) and Neale Lab consortium (replication data) were used for education and DIAGRAMplusMetabochip for T2DM.

RESULTS

The odds ratio for T2DM was 0.392 (95%CI: 0.263-0.583) per standard deviation increase (3.6 years) in education by the inverse variance weighted method, without heterogeneity or horizontal pleiotropy. Education was genetically associated with CHD, TG, BMI, WC, and WHR in the discovery phase, yet only the results for CHD, BMI, and WC were replicated in the replication data. Moreover, BMI was genetically associated with T2DM.

CONCLUSION

Short education was found to be associated with an increased T2DM risk. BMI might serve as a potential mediator between them.

Exploring the causal pathway from body mass index to coronary heart disease: a network Mendelian randomization study

Background:

We applied a network Mendelian randomization (MR) framework to determine the causal association between body mass index (BMI) and coronary heart disease (CHD) and explored whether glycated hemoglobin (HbA1c) and lipid parameters (total cholesterol, TC; low-density lipoprotein cholesterol, LDL; high-density lipoprotein cholesterol, HDL; triglycerides, TG) serve as causal mediators from BMI to CHD by integrating summary-level genome-wide association study data.

Methods:

Network MR analysis, an approach using genetic variants as the instrumental variables for both the exposure and mediator to infer causality was performed. Summary statistics from the GIANT consortium were used (n = 152,893) for BMI, CARDIoGRAMplusC4D consortium data were used (n = 184,305) for CHD, Global Lipids Genetics Consortium data were used (n = 108,363) for TC, LDL, HDL and TG, and MAGIC consortia data were used (n = 108,363) for HbA1c.

Results:

The inverse-variance-weighted-method estimate indicated that the odds ratio (95% confidence interval) for CHD was 1.562 (1.391–1.753) per 1 standard deviation (kg/m²) increase in BMI. Results were consistent in MR Egger method and weighted-median methods. MR estimate indicated that BMI was positively associated with HbA1c and TG, and negatively associated with HDL, but was not associated with TC or LDL. Moreover, HbA1c, TC, LDL, and TG were positively associated with CHD, yet there was no causal association between HDL and CHD. HbA1c was positively associated with TC, LDL, and HDL, but was not associated with TG.

Conclusions:

Higher BMI conferred an increased risk of CHD, which was partially mediated by HbA1c and lipid parameters. HbA1c and TG might be the main mediators in the link from BMI to CHD.

Exploring the causal pathway from omega-6 levels to coronary heart disease: A network Mendelian randomization study

BACKGROUND AND AIMS

Evidence on the effect of omega-6 fats on coronary heart disease (CHD) risk remains inconclusive. We applied a network MR framework to determine the causal effects between omega-6 levels and CHD and the potential cholesterol metabolic risk factors (Total cholesterol, TC; Low-density lipoprotein cholesterol, LDL-C; High-density lipoprotein cholesterol, HDL-C; Triglycerides, TG) which might act as mediators in the link between omega-6 levels and CHD by integrating summary-level genome wide association study (GWAS) data.

METHODS AND RESULTS

Network MR analysis-an approach using genetic variants as the instrumental variables for both the exposure and mediator to infer causality was performed to examine the causal effects between omega-6 levels and CHD and cholesterol metabolic risk factors. Summary statistics from the Kettunen et al. 's consortium were used (n = 13506) for omega-6, CARDIoGRAMplusC4D consortium data were used (n = 184305) for CHD, and GLGC consortia data were used (n = 108363) for TC, LDL-C, HDL-C, and TG. The IVW method estimate indicated that the odds ratio (OR) (95% confidence interval [CI]) for CHD was 1.210 (1.118-1.310) per standard deviation increase in omega-6. Results were consistent in MR Egger method (OR, 1.418; 95% CI, 1.087-1.851; P = 0.050) and weighted median methods (OR, 1.239; 95% CI, 1.125-1.364; P = 0.000). Omega-6 was positively causal associated with TC, LDL-C, and TG but was not associated with HDL-C. Moreover, TC, LDL-C, and TG were positively associated with CHD.

CONCLUSIONS

Using a network MR framework, we provided evidence supporting a positive causal relationship between omega-6 and CHD, which might be partially mediated by TC, LDL-C, and TG.

Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference

Detailed phenotyping is required to deepen our understanding of the biological mechanisms behind genetic associations. In addition, the impact of potentially modifiable risk factors on disease requires analytical frameworks that allow causal inference. Here, we discuss the characteristics of Recall-by-Genotype (RbG) as a study design aimed at addressing both these needs. We describe two broad scenarios for the application of RbG: studies using single variants and those using multiple variants. We consider the efficacy and practicality of the RbG approach, provide a catalogue of UK-based resources for such studies and present an online RbG study planner.