Separating the direct effects of traits on atherosclerotic cardiovascular disease from those mediated by type 2 diabetes

An Exploration of Shared Risk Factors for Coronary Artery Disease and Cancer from 109 Traits: The Evidence from Two-Sample Mendelian Randomization Studies

Background

Although observational studies have reported several common biomarkers related to coronary artery disease (CAD) and cancer, there is a shortage of traditional epidemiological data to establish causative linkages. Thus, we conducted a comprehensive two-sample Mendelian randomization (MR) analysis to systematically investigate the causal associations of 109 traits with both CAD and cancer to identify their shared risk and protective factors.

Methods

The genetic association datasets pertaining to exposure and outcomes were reviewed using the most recent and public genome-wide association studies (GWAS). Inverse variance weighting (IVW), weighted median (WM), and MR-Egger strategies were implemented for the MR analyses. The heterogeneity and pleiotropy were measured utilizing leave-one-out sensitivity testing, MR-PRESSO outlier detection, and Cochran's Q test.

Results

The IVW analyses revealed that genetic-predicted mean sphered cell volume (MSCV) is a protective factor for CAD, and weight is a risk factor. MSCV and weight also show similar effects on cancer. Furthermore, our study also identified a set of risk and protective factors unique to CAD and cancer, such as telomere length.

Conclusions

Our Mendelian randomization study sheds light on shared and unique risk and protective factors for CAD and cancer, offering valuable insights that could guide future research and the development of personalized strategies for preventing and treating these two significant health issues.

Assessment of potential risk factors associated with gestational diabetes mellitus: evidence from a Mendelian randomization study

Background

Previous research on the association between risk factors and gestational diabetes mellitus (GDM) primarily comprises observational studies with inconclusive results. The objective of this study is to investigate the causal relationship between 108 traits and GDM by employing a two-sample Mendelian randomization (MR) analysis to identify potential risk factors of GDM.

Methods

We conducted MR analyses to explore the relationships between traits and GDM. The genome-wide association studies (GWAS) for traits were primarily based on data from the UK Biobank (UKBB), while the GWAS for GDM utilized data from FinnGen. We employed a false discovery rate (FDR) of 5% to account for multiple comparisons.

Results

The inverse-variance weighted (IVW) method indicated that the genetically predicted 24 risk factors were significantly associated with GDM, such as "Forced expiratory volume in 1-second (FEV1)" (OR=0.76; 95% CI: 0.63, 0.92), "Forced vital capacity (FVC)" (OR=0.74; 95% CI: 0.64, 0.87), "Usual walking pace" (OR=0.19; 95% CI: 0.09, 0.39), "Sex hormone-binding globulin (SHBG)" (OR=0.86; 95% CI: 0.78, 0.94). The sensitivity analyses with MR-Egger and weighted median methods indicated consistent results for most of the trats.

Conclusion

Our study has uncovered a significant causal relationship between 24 risk factors and GDM. These results offer a new theoretical foundation for preventing or mitigating the risks associated with GDM.

Abdominal obesity mediates the causal relationship between depression and the risk of gallstone disease: retrospective cohort study and Mendelian randomization analyses

OBJECTIVE

Our study aimed to explore the causal effect of depression on the risk of gallstone disease, and the mediation effects of metabolic traits.

METHODS

A retrospective cohort study on Chinese elderly from the Dongfeng-Tongji cohort (including 18,141 individuals) was conducted to estimate the adverse effect of probable depression on the risk of gallstone disease. Two-sample Mendelian randomization was performed in European and East-Asian ancestries, to verify the causal relationship between major depression and gallstone disease. We further applied two-step Mendelian randomization to explore the mediation effects of metabolic traits.

RESULTS

In the cohort study, probable depression was associated with an increased risk of gallstone disease within 5 years, with RR (95% CI) of 1.33 (1.12, 1.58) in multivariable regression, and 1.34 (1.11, 1.61) following propensity score weighting. Bidirectional Mendelian randomization in European ancestry revealed a positive causal effect (OR: 1.21; 95% CI: 1.07 to 1.37) of genetically predicted major depression liability on gallstone disease, based on the inverse variance weighted method. Little evidence was presented from other complementary approaches, and the analysis in East-Asian ancestry (IVW estimated OR: 1.03; 95% CI: 0.92 to 1.15). The indirect effect via waist circumference and HDL-C were 1.06 (95% CI: 1.02 to 1.10) and 1.01 (95% CI: 1.00 to 1.01) respectively, which mediated 25.8% and 3.78% of the causal relationship.

CONCLUSIONS

Our study suggested a higher risk of gallstone disease in the population with probable depression, while the two-sample Mendelian randomization provided weak evidence for the causal relationship, which was moderately mediated by abdominal obesity.

Dissecting the mediating and moderating effects of depression on the associations between traits and coronary artery disease: A two-step Mendelian randomization and phenome-wide interaction study

Background

Depression is often present concurrently with coronary artery disease (CAD), a disease with which it shares many risk factors. However, the manner in which depression mediates and moderates the association between traits (including biomarkers, anthropometric indicators, lifestyle behaviors, etc.) and CAD is largely unknown.

Methods

In our causal mediation analyses using two-step Mendelian randomization (MR), univariable MR was first used to investigate the causal effects of 108 traits on liability to depression and CAD. The traits with significant causal effects on both depression and CAD, but not causally modulated by depression, were selected for the second-step analyses. Multivariable MR was used to estimate the direct effects (independent of liability to depression) of these traits on CAD, and the indirect effects (mediated via liability to depression) were calculated. To investigate the moderating effect of depression on the association between 364 traits and CAD, a cross-sectional phenome-wide interaction study (PheWIS) was conducted in a study population from UK Biobank (UKBB) (N=275,257). Additionally, if the relationship between traits and CAD was moderated by both phenotypic and genetically predicted depression at a suggestive level of significance (Pinteraction≤0.05) in the PheWIS, the results were further verified by a cohort study using Cox proportional hazards regression.

Results

Univariable MR indicated that 10 of 108 traits under investigation were significantly associated with both depression and CAD, which showed a similar direct effect compared to the total effect for most traits. However, the traits "drive faster than speed limit" and "past tobacco smoking" were both exceptions, with the proportions mediated by depression at 24.6% and 7.2%, respectively. In the moderation analyses, suggestive evidence of several traits was found for moderating effects of phenotypic depression or susceptibility to depression, as estimated by polygenic risk score, including chest pain when hurrying, reason of smoking quitting and weight change. Consistent results were observed in survival analyses and Cox regression.

Conclusion

The independent role of traits in CAD pathogenesis regardless of depression was highlighted in our mediation analyses, and the moderating effects of depression observed in our study may be helpful for CAD risk stratification and optimized allocation of scarce medical resources.

Assessment of common risk factors of diabetes and chronic kidney disease: a Mendelian randomization study

Background

The increasing prevalence of diabetes and its significant impact on mortality and morbidity rates worldwide has led to a growing interest in understanding its common risk factors, particularly in relation to chronic kidney disease (CKD). This research article aims to investigate the shared risk factors between type 1 diabetes (T1D), type 2 diabetes (T2D), and CKD using a Mendelian randomization (MR) design.

Methods

The study utilized genome-wide association study (GWAS) datasets for T1D, T2D, and CKD from the FinnGen research project. GWAS summary statistics datasets for 118 exposure traits were obtained from the IEU OpenGWAS database. MR analyses were conducted to examine the causal relationships between exposure traits and each of the three outcomes. Multiple methods, including inverse-variance weighted, weighted median, and MR-Egger, were employed for the MR studies.

Results

Phenome-wide MR analyses revealed that eosinophil percentage exhibited a significant and suggestive causal association with T1D and CKD, respectively, suggesting its potential as a shared risk factor for T1D and CKD. For T2D, 34 traits demonstrated significant associations. Among these 34 traits, 14 were also significantly associated with CKD, indicating the presence of common risk factors between T2D and CKD, primarily related to obesity, height, blood lipids and sex hormone binding globulin, blood pressure, and walking pace.

Conclusion

This research has uncovered the eosinophil percentage as a potential common risk factor for both T1D and CKD, while also identifying several traits, such as obesity and blood lipids, as shared risk factors for T2D and CKD. This study contributes to the understanding of the common risk factors between diabetes and CKD, emphasizing the need for targeted interventions to reduce the risk of these diseases.

Insights into Causal Cardiovascular Risk Factors from Mendelian Randomization

PURPOSE OF THE REVIEW

This review summarizes major insights into causal risk factors for cardiovascular disease (CVD) by using Mendelian randomization (MR) to obtain unconfounded estimates, contextualized within its strengths and weaknesses.

RECENT FINDINGS

MR studies have confirmed the role of major CVD risk factors, including alcohol, smoking, adiposity, blood pressure, type 2 diabetes, lipids, and possibly inflammation, but added that the relation with alcohol is likely linear, confirmed the role of diastolic blood pressure, identified apolipoprotein B as the major target lipid, and foreshadowed results of some trials concerning anti-inflammatories. Identifying a healthy diet and the role of early life influences, such as birth weight, has proved more difficult. Use of MR has winnowed empirically driven hypotheses about CVD into a set of genetically validated targets of intervention. Greater inclusion of global diversity in genetic studies and the use of an overarching framework would enable even more informative MR studies.

An examination of causal associations and shared risk factors for diabetes and cardiovascular diseases in the East Asian population: A Mendelian randomization study

BACKGROUND

One of the major contributors to disability and mortality among diabetics is cardiovascular disease (CVD), with coronary artery disease (CAD) as the most prevalent type. However, previous studies have provided controversial evidence linking diabetes to other types of CVDs, such as atrial fibrillation (AF). In addition, the risk factors that predispose people to the risk of diabetes and its complications differ across ethnicities, but the disease risk profiles in the East Asian population have been less investigated.

METHODS

The causal association between type 2 diabetes (T2D) and two types of CVDs (i.e., AF and CAD) in the East Asian population was first studied using Mendelian randomization (MR) analyses. Next, we examined the causal effect of 49 traits on T2D and CAD to identify their separate and shared risk factors in East Asians. A causal mediation analysis was performed to examine the role of T2D in mediating the relationship between the identified shared risk factors and CAD.

RESULTS

T2D was causally associated with CAD, but not AF, in East Asians. A screening of the risk factors indicated that six and 11 traits were causally associated with T2D and CAD, respectively, with suggestive levels of evidence. Alkaline phosphatase (ALP) was the only trait associated with both T2D and CAD, as revealed by the univariable MR analyses. Moreover, the causal association between ALP and CAD no longer existed after adjusting T2D as a covariable in the causal mediation study.

CONCLUSION

Our study highlights the risk profiles in the East Asian population, which is important in formulating targeted therapies for T2D and CVDs in East Asians.

Investigating the causal mediating effect of type 2 diabetes on the relationship between traits and systolic blood pressure: A two-step Mendelian randomization study

Background

Type 2 diabetes mellitus (T2DM) and hypertension commonly coexist, and we presumed that T2DM might mediate the relationship between some shared risk factors and systolic blood pressure (SBP).

Methods

The causal association between T2DM and SBP was first confirmed using Mendelian randomization (MR) analyses, and a two-step MR design was then used to test the causal mediating effect of T2DM on the relationship between 107 traits and SBP using summary statistics from genome-wide association studies.

Results

T2DM was causally associated with SBP. The univariable MR of the two-step causal mediation analyses suggested that 44 and 45 of the 107 traits had causal associations with T2DM and SBP, respectively. Five of the 27 traits that were significantly associated with both T2DM and SBP could not be reversely altered by T2DM and were included in the second step of the causal mediation analyses. The results indicated that most of the investigated traits causally altered SBP independent of T2DM, but the partial causal mediating effect of T2DM on the association between fasting insulin and SBP was successfully identified with a mediation proportion of 33.6%.

Conclusions

Our study provides novel insights into the role of risk factors in the comorbidity of T2DM and high blood pressure, which is important for long-term disease prevention and management.

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

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