Mendelian randomization studies on atherosclerotic cardiovascular disease: evidence and limitations

Causality between allergic diseases and kidney diseases: a two-sample Mendelian randomization study

Background

Evidence from observational studies and clinical trials suggests that the allergic diseases (ADs) are associated with kidney diseases (KDs). However, the causal association between them remains to be determined. We used bidirectional two-sample Mendelian randomization (MR) analysis to evaluate the potential causality between them.

Methods

Mendelian randomization (MR) was performed using publicly available genome-wide association study (GWAS) summary datasets. Inverse variance weighted (IVW), weighted median, MR-Egger regression, simple mode, and weighted mode methods are used to evaluate the causality between ADs and KDs. Sensitivity and heterogeneity analyses were used to ensure the stability of the results.

Results

The MR results indicated that genetic susceptibility to ADs was associated with a higher risk of CKD [odds ratio (OR) = 1.124, 95% CI = 1.020-1.239, p = 0.019] and unspecified kidney failure (OR = 1.170, 95% CI = 1.004-1.363, p = 0.045) but not with kidney stone, ureter stone or bladder stone (OR = 1.001, 95% CI = 1.000-1.002, p = 0.216), other renal or kidney problem (OR = 1.000, 95% CI = 1.000-1.001, p = 0.339), urinary tract or kidney infection (OR = 1.000, 95% CI = 0.999-1.001, p = 0.604), kidney volume (OR = 0.996, 95% CI = 0.960-1.033, p = 0.812) and cyst of kidney (OR = 0.914, 95% CI = 0.756-1.105, p = 0.354). No causal evidence of KDs on ADs was found in present study.

Conclusion

Results from MR analysis indicate a causal association between ADs and CKD and unspecified kidney failure. These findings partly suggest that early monitoring of CKD risk in patients with ADs is intentional.

Genetic evidence for the causal relations between metabolic syndrome and psychiatric disorders: a Mendelian randomization study

Emerging evidence reveals associations between metabolic syndrome (MetS) and psychiatric disorders (PDs), although causality remains uncertain. Consequently, we conducted Mendelian randomization (MR) to systematically evaluate the causality between MetS and PDs. Linkage disequilibrium score regression estimated the heritability of PDs and their genetic correlations with MetS. In primary analyses, the main model employed inverse variance weighting method, with sensitivity analyses using various MR models to ensure robustness. Replication MR analyses, involving cohorts distinct from those in the primary analyses, were performed to validate the generalizability of the findings. Multivariable MR analyses were carried out to account for genetically predicted body mass index (BMI). As a result, genetic correlations of MetS with attention-deficit/hyperactivity disorder(ADHD), anorexia nervosa(ANO), major depressive disorder(MDD), and schizophrenia were identified. Causal effects of MetS on ADHD (OR: 1.59 [95% CI:1.45-1.74]), ANO (OR: 1.42 [95% CI:1.25-1.61]), MDD(OR: 1.23 [95% CI: 1.13-1.33]), and the effects of ADHD (OR: 1.03 [95% CI: 1.02-1.04]) and ANO (OR: 1.01 [95% CI: 1.01-1.02]) on MetS were observed in primary analyses. Results from sensitivity analyses and replication analyses were generally consistent with the primary analyses, confirming the robustness and generalizability of the findings. Associations between MetS and ADHD, as well as ANO persisted after adjusting for BMI, whereas the statistical significance of the association between MetS and MDD was no longer observable. These results contribute to a deeper understanding of the mechanisms underlying PDs, suggesting potential modifiable targets for public prevention and clinical intervention in specific PDs related to metabolic pathways.

Genetically predicted lifestyle factors, socioeconomic status and risk of coronary artery disease in individuals with diabetes: a Mendelian randomization study

Background

This study explores the causal links between genetically predicted lifestyle factors, socioeconomic status, and coronary artery disease (CAD) risk in individuals with diabetes using a bidirectional Mendelian-randomization approach.

Methods

This study explored the potential causal relationships of lifestyle factors and socioeconomic status with the risk of CAD in diabetes patients by a bidirectional, two-sample Mendelian-randomization (MR) analysis.

Results

Genetically predicted smoking initiation (p = 0.005, 95% CI: 1.08-1.55) and insomnia (p = 0.001, 95% CI: 1.06-1.29) were associated with a higher risk of CAD in individuals with diabetes, whereas educational attainment (p = 0.0001, 95% CI: 0.47-0.78) was associated with a lower risk of CAD. The lifetime smoking index (p = 0.016, 95% CI: 1.12-3.03) was suggestively associated with a higher risk of CAD, while household income before taxes (p = 0.048, 95% CI: 0.41-1.00) was suggestively associated with a lower risk of CAD. In addition, we observed a suggestive negative association between the genetically predicted risk of CAD and the lifetime smoking index (p = 0.016, 95% CI: 0.98-0.99) and a significant causal relationship between the risk of CAD and household income before taxes (p = 0.006, 95% CI: 0.97-0.99).

Conclusion

The results of this study provide evidence that smoking initiation, lifetime smoking index and insomnia are associated with an increased risk of CAD in individuals with diabetes, educational attainment and household income before taxes are associated with a reduced risk of CAD in individuals with diabetes, and the possible role of lifetime smoking index and household income before taxes on the risk of CAD in individuals with diabetes. It provides an opportunity for the prevention and management of CAD in individuals with diabetes.

Genetically Predicted Levels of Serum Metabolites and Risk of Sarcopenia: A Mendelian Randomization Study

Metabolites' connection to sarcopenia through inflammation and mitochondrial dysfunction is presumed, but their impact remains unclear due to limitations in conventional observational studies caused by confounding bias and reverse causation. We conducted a Mendelian randomization (MR) analysis to elucidate the association of serum metabolites with sarcopenia and its related traits, i.e., appendicular lean mass and grip strength. Genetic instruments to proxy the serum metabolites were extracted from the most comprehensive genome-wide association study on the topic published so far. The corresponding summary statistics for the associations of genetic instruments with outcomes were calculated from the UK Biobank (n = 324,976 participants). The primary analyses were assessed by an inverse-variance weighted (IVW) method. The weighted median and MR-PRESSO methods were used as sensitive analyses. Fourteen genetically predicted serum metabolites were associated with the risk of sarcopenia (PIVW < 0.05). Two metabolites showed the overlapped association with sarcopenia and its related traits, which were isovalerylcarnitine (sarcopenia: odds ratio [OR] = 4.00, 95% confidence interval [CI] = 1.11~14.52, PIVW = 0.034; appendicular lean mass: β = -0.45 kg, 95% CI = -0.81~-0.09, PIVW = 0.015; grip strength: β = -1.51 kg, 95% CI = -2.31~-0.71, PIVW = 2.19 × 10-4) and docosapentaenoate (sarcopenia: OR = 0.16, 95% CI = 0.03~0.83, PIVW = 0.029; appendicular lean mass: β = -0.45 kg, 95% CI = 0.08~0.81, PIVW = 0.016). Twenty-seven metabolites were suggestive associated with appendicular lean mass or grip strength. This MR study provided evidence for the potential effects of metabolites on sarcopenia.

Review of mendelian randomization studies on age at natural menopause

Menopause marks the end of the reproductive phase of life. Based on epidemiological studies, abnormal age at natural menopause (ANM) is thought to contribute to a number of adverse outcomes, such as osteoporosis, cardiovascular disease, and cancer. However, the causality of these associations remains unclear. A powerful epidemiological method known as Mendelian randomization (MR) can be used to clarify the causality between ANM and other diseases or traits. The present review describes MR studies that included ANM as an exposure, outcome and mediator. The findings of MR analyses on ANM have revealed that higher body mass index, poor educational level, early age at menarche, early age at first live birth, early age at first sexual intercourse, and autoimmune thyroid disease appear to be involved in early ANM etiology. The etiology of late ANM appears to be influenced by higher free thyroxine 4 and methylene tetrahydrofolate reductase gene mutations. Furthermore, early ANM has been found to be causally associated with an increased risk of osteoporosis, fracture, type 2 diabetes mellitus, glycosylated hemoglobin, and the homeostasis model of insulin resistance level. In addition, late ANM has been found to be causally associated with an increased systolic blood pressure, higher risk of breast cancer, endometrial cancer, endometrioid ovarian carcinoma, lung cancer, longevity, airflow obstruction, and lower risk of Parkinson's disease. ANM is also a mediator for breast cancer caused by birth weight and childhood body size. However, due to the different instrumental variables used, some results of studies are inconsistent. Future studies with more valid genetic variants are needed for traits with discrepancies between MRs or between MR and other types of epidemiological studies.

Genetic Variants, Serum 25-Hydroxyvitamin D Levels, and Sarcopenia: A Mendelian Randomization Analysis

Importance

Vitamin D deficiency is commonly associated with sarcopenia; however, the latest International Clinical Practice Guidelines for Sarcopenia do not recommend vitamin D supplementation for sarcopenia owing to a lack of an apparent therapeutic effect on the indices of sarcopenia among participants with replete vitamin D concentration (ie, 25-hydroxyvitamin D [25(OH)D] level >20 ng/mL) from randomized clinical trials. While there is consensus in all vitamin D guidelines that serum levels of 25(OH)D less than 10 ng/mL should be corrected, approximately 30% of the world population's 25(OH)D levels range from 10 to 20 ng/mL, and it remains unclear whether such suboptimal levels can maintain optimal health, including sarcopenia risk.

Objective

To investigate the association of serum 25(OH)D level, especially suboptimal levels, with sarcopenia risk.

Design, Setting, and Participants

This genome-wide genetic association study was performed from August 2022 to February 2023 among the 295 489 unrelated European participants from the UK Biobank (2006-2010). Nonlinear and standard mendelian randomization analyses were used to examine the association of serum 25(OH)D concentration with sarcopenia risk.

Exposures

A weighted genetic risk score using 35 unrelated single-nucleotide variants from the UK Biobank and weights from the SUNLIGHT Consortium was selected as an instrumental variable for serum 25(OH)D concentration.

Main Outcomes and Measures

The primary outcome was sarcopenia, and the secondary outcomes consisted of grip strength, appendicular lean mass index, and gait speed.

Results

The final genetic analyses included 295 489 participants (mean [SD] age, 56.3 [8.1] years; 139 216 female [52.9%]). There was an L-shaped association between genetically predicted serum 25(OH)D concentration and sarcopenia risk. The risk of sarcopenia decreased rapidly as 25(OH)D concentration increased until 20 ng/mL and then leveled off. The odds ratio of sarcopenia for serum 25(OH)D level of 10 vs 20 ng/mL was 1.74 (95% CI, 1.17-2.59). Similar patterns were also observed when the association between serum 25(OH)D concentration and risks of each of the sarcopenia indices were evaluated.

Conclusions and Relevance

In this mendelian randomization genetic association study of adults in the UK Biobank, the findings supported a nonlinear association between suboptimal 25(OH)D levels and sarcopenia risk. Randomized clinical trials among participants with suboptimal 25(OH)D levels are required to verify the potential causality.

Ovarian Cancer and Parkinson's Disease: A Bidirectional Mendelian Randomization Study

(1) Background: Ovarian cancer (OC) and Parkinson's disease (PD) represent a huge public health burden. The relationship of these two diseases is suggested in the literature while not fully understood. To better understand this relationship, we conducted a bidirectional Mendelian ran-domization analysis using genetic markers as a proxy. (2) Methods: Utilizing single nucleotide polymorphisms associated with PD risk, we assessed the association between genetically predicted PD and OC risk, overall and by histotypes, using summary statistics from previously conducted genome-wide association studies of OC within the Ovarian Cancer Association Consortium. Similarly, we assessed the association between genetically predicted OC and PD risk. The inverse variance weighted method was used as the main method to estimate odds ratios (OR) and 95% confidence intervals (CI) for the associations of interest. (3) Results: There was no significant association between genetically predicted PD and OC risk: OR = 0.95 (95% CI: 0.88-1.03), or between genetically predicted OC and PD risk: OR = 0.80 (95% CI: 0.61-1.06). On the other hand, when examined by histotypes, a suggestive inverse association was observed between genetically predicted high grade serous OC and PD risk: OR = 0.91 (95% CI: 0.84-0.99). (4) Conclusions: Overall, our study did not observe a strong genetic association between PD and OC, but the observed potential association between high grade serous OC and reduced PD risk warrants further investigation.

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.

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.

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.

Mendelian Randomization in Cardiovascular Research: Establishing Causality When There Are Unmeasured Confounders

Mendelian randomization is an epidemiological approach to making causal inferences using observational data. It makes use of the natural randomization that occurs in the generation of an individual's genetic makeup in a way that is analogous to the study design of a randomized controlled trial and uses instrumental variable analysis where the genetic variant(s) are the instrument (analogous to random allocation to treatment group in an randomized controlled trial). As with any instrumental variable, there are 3 assumptions that must be made about the genetic instrument: (1) it is associated (not necessarily causally) with the exposure (relevance condition); (2) it is associated with the outcome only through the exposure (exclusion restriction condition); and (3) it does not share a common cause with the outcome (ie, no confounders of the genetic instrument and outcome, independence condition). Using the example of type II diabetes and coronary artery disease, we demonstrate how the method may be used to investigate causality and discuss potential benefits and pitfalls. We conclude that although Mendelian randomization studies can usually not establish causality on their own, they may usefully contribute to the evidence base and increase our certainty about the effectiveness (or otherwise) of interventions to reduce cardiovascular disease.

Associations of egg consumption with incident cardiovascular disease and all-cause mortality

Eggs are nutrient-dense while also loaded with abundant cholesterol, thus making the public hesitant about their consumption. We conducted the study to investigate if egg consumption is associated with incident cardiovascular disease (CVD) and all-cause mortality. Using the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China, we included 102,136 adults free of CVD and assessed their egg consumption with food-frequency questionnaires. CVD endpoints and all-cause mortality were confirmed during follow-ups by interviewing participants or their proxies and checking hospital records/death certificates. The HRs (95% CIs) were calculated using the cohort-stratified Cox regression models. During 777,163 person-years of follow-up, we identified 4,848 incident CVD and 5,511 deaths. U-shaped associations of egg consumption with incident CVD and all-cause mortality were observed. Compared with consumption of 3-<6/week, the multivariable-adjusted HRs (95% CIs) of <1/week and ≥10/week for incident CVD were 1.22 (1.11 to 1.35) and 1.39 (1.28 to 1.52), respectively. The corresponding HRs (95% CIs) for all-cause mortality were 1.29 (1.18 to 1.41) and 1.13 (1.04 to 1.24). Our findings identified that both low and high consumption were associated with increased risk of incident CVD and all-cause mortality, highlighting that moderate egg consumption of 3-<6/week should be recommended for CVD prevention in China.