Obstructive sleep apnea and atrial fibrillation: insights from a bidirectional Mendelian randomization study

The causal relationship between human brain morphometry and knee osteoarthritis: a two-sample Mendelian randomization study

Background

Knee Osteoarthritis (KOA) is a prevalent and debilitating condition affecting millions worldwide, yet its underlying etiology remains poorly understood. Recent advances in neuroimaging and genetic methodologies offer new avenues to explore the potential neuropsychological contributions to KOA. This study aims to investigate the causal relationships between brain-wide morphometric variations and KOA using a genetic epidemiology approach.

Method

Leveraging data from 36,778 UK Biobank participants for human brain morphometry and 487,411 UK Biobank participants for KOA, this research employed a two-sample Mendelian Randomization (TSMR) approach to explore the causal effects of 83 brain-wide volumes on KOA. The primary method of analysis was the Inverse Variance Weighted (IVW) and Wald Ratio (WR) method, complemented by MR Egger and IVW methods for heterogeneity and pleiotropy assessments. A significance threshold of p < 0.05 was set to determine causality. The analysis results were assessed for heterogeneity using the MR Egger and IVW methods. Brain-wide volumes with Q_pval < 0.05 were considered indicative of heterogeneity. The MR Egger method was employed to evaluate the pleiotropy of the analysis results, with brain-wide volumes having a p-value < 0.05 considered suggestive of pleiotropy.

Results

Our findings revealed significant causal associations between KOA and eight brain-wide volumes: Left parahippocampal volume, Right posterior cingulate volume, Left transverse temporal volume, Left caudal anterior cingulate volume, Right paracentral volume, Left paracentral volume, Right lateral orbitofrontal volume, and Left superior temporal volume. These associations remained robust after tests for heterogeneity and pleiotropy, underscoring their potential role in the pathogenesis of KOA.

Conclusion

This study provides novel evidence of the causal relationships between specific brain morphometries and KOA, suggesting that neuroanatomical variations might contribute to the risk and development of KOA. These findings pave the way for further research into the neurobiological mechanisms underlying KOA and may eventually lead to the development of new intervention strategies targeting these neuropsychological pathways.

Evaluate the Relationship Between Obstructive Sleep Apnea and Metabolic Syndrome in Real-World Data

Objective

Obstructive sleep apnea (OSA) is a disorder characterized by disruption in breathing and hypoventilation. In parallel, metabolic syndrome (MetS) mainly co-occur with OSA, however, their association has not been fully elucidated. Therefore, this study aimed to reveal the relationship between OSA and MetS using data from the National Health And Nutrition Examination Survey (NHANES) database and pooled data from Genome-Wide Association Studies (GWAS).

Material and Methods

Data from the National Health and Nutrition Examination Survey and pooled data from genome-wide association analysis (GWAS) were used univariate and multivariate logistic regression analyses were carried out to evaluate the correlation between OSA and MetS, and multivariate logistic regression models were utilized for adjusting for potential confounders. Two-sample Mendelian randomization (MR) was used to assess the causal relationship between OSA and MetS. The variance-weighted inverse method was employed as the main method of analysis.

Results

A positive relationship of OSA with Mets was evidenced by multivariate logistic regression analysis, and OSA was associated with higher incidence rates of all-cause and cardiovascular mortality. OSA is strongly associated with abdominal obesity, hypertension, hyperglycemia, high triglycerides, and low HDL. Furthermore, except for hypertriglyceridemia, MR analysis indicated that genetically driven OSA was causally associated with a higher risk of MetS.

Conclusion

The positive relationship of OSA with Mets was revealed, and higher incidence rates of all-cause mortality and cardiovascular mortality were noted to be correlated with OSA. MR analysis further confirmed the causal relationship of OSA with MetS and cardiovascular disease.

2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

AIM

The "2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation" provides recommendations to guide clinicians in the treatment of patients with atrial fibrillation.

METHODS

A comprehensive literature search was conducted from May 12, 2022, to November 3, 2022, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. Additional relevant studies, published through November 2022, during the guideline writing process, were also considered by the writing committee and added to the evidence tables, where appropriate.

STRUCTURE

Atrial fibrillation is the most sustained common arrhythmia, and its incidence and prevalence are increasing in the United States and globally. Recommendations from the "2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" and the "2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" have been updated with new evidence to guide clinicians. In addition, new recommendations addressing atrial fibrillation and thromboembolic risk assessment, anticoagulation, left atrial appendage occlusion, atrial fibrillation catheter or surgical ablation, and risk factor modification and atrial fibrillation prevention have been developed.

2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines

AIM

The "2023 ACC/AHA/ACCP/HRS Guideline for the Diagnosis and Management of Patients With Atrial Fibrillation" provides recommendations to guide clinicians in the treatment of patients with atrial fibrillation.

METHODS

A comprehensive literature search was conducted from May 12, 2022, to November 3, 2022, encompassing studies, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Library, the Agency for Healthcare Research and Quality, and other selected databases relevant to this guideline. Additional relevant studies, published through November 2022, during the guideline writing process, were also considered by the writing committee and added to the evidence tables, where appropriate.

STRUCTURE

Atrial fibrillation is the most sustained common arrhythmia, and its incidence and prevalence are increasing in the United States and globally. Recommendations from the "2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" and the "2019 AHA/ACC/HRS Focused Update of the 2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation" have been updated with new evidence to guide clinicians. In addition, new recommendations addressing atrial fibrillation and thromboembolic risk assessment, anticoagulation, left atrial appendage occlusion, atrial fibrillation catheter or surgical ablation, and risk factor modification and atrial fibrillation prevention have been developed.

Selection of genetic instruments in Mendelian randomisation studies of sleep traits

This review explores the criteria used for the selection of genetic instruments of sleep traits in the context of Mendelian randomisation studies. This work was motivated by the fact that instrument selection is the most important decision when designing a Mendelian randomisation study. As far as we are aware, no review has sought to address this to date, even though the number of these studies is growing rapidly. The review is divided into the following sections which are essential for genetic instrument selection: 1) Single-gene region vs polygenic analysis; 2) Polygenic analysis: biologically-vs statistically-driven approaches; 3) P-value; 4) Linkage disequilibrium clumping; 5) Sample overlap; 6) Type of exposure; 7) Total (R2) and average strength (F-statistic) metrics; 8) Number of single-nucleotide polymorphisms; 9) Minor allele frequency and palindromic variants; 10) Confounding. Our main aim is to discuss how instrumental choice impacts analysis and compare the strategies that Mendelian randomisation studies of sleep traits have used. We hope that our review will enable more researchers to take a more considered approach when selecting genetic instruments for sleep exposures.

Causal effects of inflammatory bowel diseases on the risk of kidney stone disease: a two-sample bidirectional mendelian randomization

BACKGROUND

Existing epidemiological observational studies have suggested interesting but inconsistent clinical correlations between inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), and kidney stone disease (KSD). Herein, we implemented a two-sample bidirectional Mendelian randomization (MR) to investigate the causal relationship between IBD and KSD.

METHODS

Data on IBD and KSD were obtained from Genome-Wide Association Studies (GWAS) summary statistics and the FinnGen consortium, respectively. Strict selection steps were used to screen for eligible instrumental SNPs. We applied inverse variance weighting (IVW) with the fix-effects model as the major method. Several sensitivity analyses were used to evaluate pleiotropy and heterogeneity. Causal relationships between IBD and KSD were explored in two opposite directions. Furthermore, we carried out multivariable MR (MVMR) to obtain the direct causal effects of IBD on KSD.

RESULTS

Our results demonstrated that CD could increase the risk of KSD (IVW: OR = 1.06, 95% CI = 1.03-1.10, p < 0.001). Similar results were found in the validation group (IVW: OR = 1.05, 95% CI = 1.01-1.08, p = 0.013) and in the MVMR analysis. Meanwhile, no evidence of a causal association between UC and KSD was identified. The reverse MR analysis detected no causal association.

CONCLUSIONS

This MR study verified that CD plays a critical role in developing kidney stones and that the effect of UC on KSD needs to be further explored.

Lifestyle changes in atrial fibrillation management and intervention

Atrial fibrillation (AF) is one of the most common arrhythmias in adults, and its continued rise in the United States is complicated by the increased incidence and prevalence of several AF risk factors, such as obesity, physical inactivity, hypertension, obstructive sleep apnea, diabetes mellitus, coronary artery disease, and alcohol, tobacco, or caffeine use. Lifestyle and risk factor modification has been proposed as an additional pillar of AF therapy, added to rhythm control, rate control, and anticoagulation, to reduce AF burden and risk. Although emerging evidence largely supports the integration of lifestyle and risk factor management in clinical practice, randomized clinical trials investigating the long-term sustainability and reproducibility of these benefits remain sparse. The purpose of this review is to discuss potentially reversible risk factors on AF, share evidence for the impact on AF by modification of these risk factors, and then provide an overview of the effects of reversing or managing these risk factors on the success of various AF management strategies, such as antithrombotic, rate control, and rhythm control therapies.

Association of leisure sedentary behavior and physical activity with the risk of nonalcoholic fatty liver disease: a two-sample Mendelian randomization study

Introduction

Previous observational studies have demonstrated the relationship between leisure sedentary behavior, physical activity, and nonalcoholic liver disease (NAFLD). However, whether these associations are causal or confounding factors remains unclear.

Methods

Pooled genetic data from the UK Biobank and other large genome-wide association studies (GWAS) were used to extract instrumental variables representing sedentary television watching, computer use, driving, vigorous physical activity (VPA), and moderate-to-vigorous physical activity (MVPA). The two-sample Mendelian randomization (MR) method was used to explain the causal relationship between them and NAFLD. The inverse variance of the weighted method was used as the main analysis method, and MR-Egger, weighted median, MR-PRESSO, and other supplementary methods were also used. A sensitivity analysis was also performed. Simultaneously, the common risk factors for NAFLD were further analyzed for potential mediating associations.

Results

We observed that sedentary television viewing (odds ratio (OR): 1.84; 95% confidence interval (CI): 1.09-3.10; p = 0.021) and genetically predicted VPA duration (OR: 0.0033; 95% CI: 0.000015-0.70; p = 0.036) were suggestively associated with the risk of NAFLD. Using a computer (OR: 1.51; 95% CI: 0.47-4.81; p = 0.484), driving (OR: 0.78; 95% CI: 0.05-11.94; p = 0.858), and MVPA time (OR: 0.168; 95% CI: 0.01-2.81; p = 0.214) were not significantly associated with NAFLD. The role of heterogeneity versus pleiotropy was limited in all the analyses.

Discussion

This study supports the association between sedentary television watching and an increased risk of NAFLD, along with vigorous physical activity as a possible protective factor for NAFLD.

Circulating metabolites and depression: a bidirectional Mendelian randomization

Background

Studies have shown an association between depression and circulating metabolites, but the causal relationship between them has not been elucidated. The purpose of this study was to elucidate the causal relationship between circulating metabolites and depression and to explore the role of circulating metabolites in depression.

Methods

In this study, the top single-nucleotide polymorphisms (SNPs) associated with circulating metabolites (n = 24,925) and depression (n = 322,580) were obtained based on the publicly available genome-wide association study using two-sample Mendelian randomization (MR). SNP estimates were summarized through inverse variance weighted, MR Egger, weighted median, MR pleiotropy residual sum and outlier, and "leave-one-out" methods.

Results

Apolipoprotein A-I (OR 0.990, 95% CI 981-0.999) and glutamine (OR 0.985, 95% CI 0.972-0.997) had protective causal effects on depression, whereas acetoacetate (OR 1.021, 95% CI 1.009-1.034), glycoproteins (OR 1.005, 95% CI 1.000-1.009), isoleucine (OR 1.013, 95% CI 1.002-1.024), and urea (OR 1.020, 95% CI 1.000-1.039) had an anti-protective effect on depression. Reversed MR showed no effect of depression on the seven circulating metabolites.

Conclusion

In this study, MR analysis showed that apolipoprotein A-I and glutamine had a protective effect on depression, and acetoacetate, glycoprotein, isoleucine, glucose, and urea may be risk factors for depression. Therefore, further research must be conducted to translate the findings into practice.

Leveraging genetic discoveries for sleep to determine causal relationships with common complex traits

Sleep occurs universally and is a biological necessity for human functioning. The consequences of diminished sleep quality impact physical and physiological systems such as neurological, cardiovascular, and metabolic processes. In fact, people impacted by common complex diseases experience a wide range of sleep disturbances. It is challenging to uncover the underlying molecular mechanisms responsible for decreased sleep quality in many disease systems owing to the lack of suitable sleep biomarkers. However, the discovery of a genetic component to sleep patterns has opened a new opportunity to examine and understand the involvement of sleep in many disease states. It is now possible to use major genomic resources and technologies to uncover genetic contributions to many common diseases. Large scale prospective studies such as the genome wide association studies (GWAS) have successfully revealed many robust genetic signals associated with sleep-related traits. With the discovery of these genetic variants, a major objective of the community has been to investigate whether sleep-related traits are associated with disease pathogenesis and other health complications. Mendelian Randomization (MR) represents an analytical method that leverages genetic loci as proxy indicators to establish causal effect between sleep traits and disease outcomes. Given such variants are randomly inherited at birth, confounding bias is eliminated with MR analysis, thus demonstrating evidence of causal relationships that can be used for drug development and to prioritize clinical trials. In this review, we outline the results of MR analyses performed to date on sleep traits in relation to a multitude of common complex diseases.