Risk factors mediating the effect of body mass index and waist-to-hip ratio on cardiovascular outcomes: Mendelian randomization analysis

The Role of Genetics in Managing Peripheral Arterial Disease

BACKGROUND

Genome wide association studies (GWAS) have allowed for a rapid increase in our understanding of the underlying genetics and biology of many diseases. By capitalizing on common genetic variation between individuals, GWAS can identify DNA variants associated with diseases of interest. A variety of statistical methods can be applied to GWAS results which allows for risk factor identification, stratification, and to identify potential treatments. Peripheral artery disease (PAD) is a common vascular disease that has been shown to have a strong genetic component. This article provides a review of the modern literature and our current understanding of the role of genetics in PAD.

METHODS

All available GWAS studies on PAD were reviewed. A literature search involving these studies was conducted and relevant articles applying the available GWAS data were summarized to provide a comprehensive review of our current understanding of the genetic component in PAD.

RESULTS

The largest available GWAS on PAD has identified 19 genome wide significant loci, with factor V Leiden and genes responsible for circulating lipoproteins being implicated in the development of PAD. Mendelian randomization (MR) studies have identified risk factors and causal associations with smoking, diabetes, and obesity and many other traits; protein-based MR has also identified circulating lipid and clotting factor levels associated with the incidence of PAD. Polygenic risk scores may allow for improved prediction of disease incidence and allow for early identification of at-risk patients but more work needs to be done to validate this approach.

CONCLUSIONS

Genetic epidemiology has allowed for an increased understanding of PAD in the past decade. Genome-wide association studies have led to improved detection of genetic contributions to PAD, and further genetic analyses have validated risk factors and may provide options for improved screening in at-risk populations. Ongoing biobank studies of chronic limb threatening ischemia patients and the increasing ancestral diversity in biobank enrollment will allow for even further exploration into the pathogenesis and progression of PAD.

Causal inference in health and disease: a review of the principles and applications of Mendelian randomization

Mendelian randomization (MR) is a genetic epidemiological technique that uses genetic variation to infer causal relationships between modifiable exposures and outcome variables. Conventional observational epidemiological studies are subject to bias from a range of sources; MR analyses can offer an advantage in that they are less prone to bias as they use genetic variants inherited at conception as "instrumental variables", which are proxies of an exposure. However, as with all research tools, MR studies must be carefully designed to yield valuable insights into causal relationships between exposures and outcomes, and to avoid biased or misleading results that undermine the validity of the causal inferences drawn from the study. In this review, we outline Mendel's laws of inheritance, the assumptions and principles that underlie MR, MR study designs and methods, and how MR analyses can be applied and reported. Using the example of serum phosphate concentrations on liability to kidney stone disease we illustrate how MR estimates may be visualized and, finally, we contextualize MR in bone and mineral research including exemplifying how this technique could be employed to inform clinical studies and future guidelines concerning BMD and fracture risk. This review provides a framework to enhance understanding of how MR may be used to triangulate evidence and progress research in bone and mineral metabolism as we strive to infer causal effects in health and disease.

The role of the gluteofemoral adipose tissue in cerebrovascular disease risk: evidence from a mendelian randomization and mediation analysis

Objective

To explore causal associations between BMI-independent body fat distribution profiles and cerebrovascular disease risk, and to investigate potential mediators underlying these associations.

Methods

Leveraging data from genome wide association studies of BMI-independent gluteofemoral (GFAT), abdominal subcutaneous (ASAT), and visceral (VAT) adipose tissue volumes in UK Biobank, we selected variants associated with each trait, and performed univariable and multivariable mendelian randomization (MR) analyses on ischemic stroke and subtypes (large artery (LAS), cardioembolic (CES), small vessel (SVS)). We used coronary artery disease (CAD), carotid intima media thickness (cIMT), and an MRI-confirmed lacunar stroke as positive controls. For significant associations, we explored the mediatory role of four possible mediator categories in mediation MR analyses.

Results

Higher genetically proxied, BMI-independent GFAT volume was associated with decreased risk of ischemic stroke (FDR-p=0.0084), LAS (FDR-p=0.019), SVS (FDR-p<0.001), CAD (FDR-p<0.001), MRI-confirmed lacunar stroke (FDR-p=0.0053), and lower mean cIMT (FDR-p=0.0023), but not CES (FDR-p=0.749). Associations were largely consistent in pleiotropy- and sample structure-robust analyses. No association was observed between genetically proxied ASAT or VAT volumes and ischemic stroke/subtypes risk. In multivariable MR analyses, GFAT showed the most consistent independent association with ischemic stroke, LAS, and SVS. Common vascular risk factors were the predominant mediators in the GFAT-cerebrovascular disease axis, while adipose-tissue-specific adiponectin and leptin mediated a proportion of ischemic stroke and CAD risk.

Interpretation

Genetically proxied, BMI-independent higher GFAT volume is associated with reduced cerebrovascular disease risk. Although this is largely mediated by common vascular risk factor modification, targeting adipose-tissue specific pathways may provide additional cardiovascular benefit.

Revealing brain cell-stratified causality through dissecting causal variants according to their cell-type-specific effects on gene expression

The human brain has been implicated in the pathogenesis of several complex diseases. Taking advantage of single-cell techniques, genome-wide association studies (GWAS) have taken it a step further and revealed brain cell-type-specific functions for disease loci. However, genetic causal associations inferred by Mendelian randomization (MR) studies usually include all instrumental variables from GWAS, which hampers the understanding of cell-specific causality. Here, we developed an analytical framework, Cell-Stratified MR (csMR), to investigate cell-stratified causality through colocalizing GWAS signals with single-cell eQTL from different brain cells. By applying to obesity-related traits, our results demonstrate the cell-type-specific effects of GWAS variants on gene expression, and indicate the benefits of csMR to identify cell-type-specific causal effect that is often hidden from bulk analyses. We also found csMR valuable to reveal distinct causal pathways between different obesity indicators. These findings suggest the value of our approach to prioritize target cells for extending genetic causation studies.

Robust use of phenotypic heterogeneity at drug target genes for mechanistic insights: Application of cis-multivariable Mendelian randomization to GLP1R gene region

Phenotypic heterogeneity at genomic loci encoding drug targets can be exploited by multivariable Mendelian randomization to provide insight into the pathways by which pharmacological interventions may affect disease risk. However, statistical inference in such investigations may be poor if overdispersion heterogeneity in measured genetic associations is unaccounted for. In this work, we first develop conditional F statistics for dimension-reduced genetic associations that enable more accurate measurement of phenotypic heterogeneity. We then develop a novel extension for two-sample multivariable Mendelian randomization that accounts for overdispersion heterogeneity in dimension-reduced genetic associations. Our empirical focus is to use genetic variants in the GLP1R gene region to understand the mechanism by which GLP1R agonism affects coronary artery disease (CAD) risk. Colocalization analyses indicate that distinct variants in the GLP1R gene region are associated with body mass index and type 2 diabetes (T2D). Multivariable Mendelian randomization analyses that were corrected for overdispersion heterogeneity suggest that bodyweight lowering rather than T2D liability lowering effects of GLP1R agonism are more likely contributing to reduced CAD risk. Tissue-specific analyses prioritized brain tissue as the most likely to be relevant for CAD risk, of the tissues considered. We hope the multivariable Mendelian randomization approach illustrated here is widely applicable to better understand mechanisms linking drug targets to diseases outcomes, and hence to guide drug development efforts.

Assessment of causal associations between obesity and peripheral artery disease: a bidirectional Mendelian randomization study

Background

Several observational studies have documented a potential link between obesity and peripheral artery disease (PAD), although conflicting findings exist. The causal relationship between obesity and PAD continues to be a subject of ongoing debate in the medical community.

Objectives

In this study, we employed a bidirectional Mendelian randomization (MR) analysis to explore the potential causal relationship between obesity and the risk of PAD.

Methods

To investigate these causal relationships, we conducted bidirectional MR analysis using publicly available genome-wide association study (GWAS) data. Effect estimates were calculated using the random-effects inverse variance-weighted (IVW) method.

Results

We identified eight independent single nucleotide polymorphisms (SNPs) associated with obesity in 218,735 samples involving 16,380,465 SNPs, all of which met the genome-wide significance threshold (p < 5 × 10-⁸). The IVW analysis indicates a significant positive association between genetic obesity and multiple datasets with PAD as the outcome: Queue-1 (GWAS ID: finn-b-I9_PAD) (OR = 1.138, 95% CI: 1.027-1.261, p = 0.013), Queue-2 (GWAS ID: bbj-a-144) (OR = 1.190, 95% CI: 1.019-1.390, p = 0.028), Queue-3 (GWAS ID: ebi-a-GCST90018670) (OR = 1.174, 95% CI: 1.014-1.360, p = 0.032), and Queue-4 (GWAS ID: ebi-a-GCST90018890) (OR = 1.194, 95% CI: 1.099-1.296, p < 0.001). However, we did not observe a significant genetic-level association between obesity and PAD for Queue-5 (GWAS ID: ukb-d-I9_PAD) (OR = 1.001, 95% CI: 1.000-1.002, p = 0.071). Furthermore, we conducted a reverse causal MR analysis to explore the potential reverse causal relationship between obesity and PAD. This comprehensive analysis did not provide evidence of a reverse causal association between these two factors.

Conclusions

In summary, our study offers genetic evidence suggesting a possible causal link between obesity and PAD. While we did not find evidence supporting the "obesity paradox", prudent weight management remains crucial, as lower weight does not necessarily guarantee better outcomes. As with any study, caution is required in interpreting the findings. Further research is essential to assess the clinical relevance of weight in preventing PAD, which could inform the development of more precise intervention strategies.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Mendelian randomization studies on coronary artery disease: a systematic review and meta-analysis

BACKGROUND

Coronary artery disease (CAD) remains one of the leading causes of mortality worldwide. We aimed to summarize what is currently known with regard to causal modifiable risk factors associated with CAD in populations of diverse ancestries through conducting a systematic review and meta-analysis of Mendelian randomization (MR) studies on CAD.

METHODS

The databases Embase, Medline, Cochrane Library and Web of Science were searched on the 19th and 20th of December 2022 for MR studies with CAD as a primary outcome; keywords of the search strategy included "coronary artery disease" and "mendelian randomization". Studies were included if they were published in the English language, included only human participants, employed Mendelian randomization as the primary methodology and studied CAD as the outcome of interest. The exclusion criteria resulted in the removal of studies that did not align with the predefined inclusion criteria, as well as studies which were systematic reviews themselves, and used the same exposure and outcome source as another study. An ancestry-specific meta-analysis was subsequently conducted on studies which investigated either body mass index, lipid traits, blood pressure or type 2 diabetes as an exposure variable. Assessment of publication bias and sensitivity analyses was conducted for risk of bias assessment in the included studies.

RESULTS

A total of 1781 studies were identified through the database searches after de-duplication was performed, with 47 studies included in the quantitative synthesis after eligibility screening. Approximately 80% of all included study participants for MR studies on CAD were of European descent irrespective of the exposure of interest, while no study included individuals of African ancestry. We found no evidence of differences in terms of direction of causation between ancestry groups; however, the strength of the respective relationships between each exposure and CAD were different, with this finding most evident when blood pressure was the exposure of interest.

CONCLUSIONS

Findings from this review suggest that patterns regarding the causational relationship between modifiable risk factors and CAD do not differ in terms of direction when compared across diverse ancestry populations. Differences in the observed strengths of the respective relationships however are indicative of the value of increasing representation in non-European populations, as novel genetic pathways or functional SNPs relating to CAD may be uncovered through a more global analysis.

SYSTEMATIC REVIEW REGISTRATION

The protocol for this systematic review was registered to the International Prospective Register of Systematic Reviews (PROSPERO) and is publicly available online (CRD42021272726).

Mendelian randomization for cardiovascular diseases: principles and applications

Large-scale genome-wide association studies conducted over the last decade have uncovered numerous genetic variants associated with cardiometabolic traits and risk factors. These discoveries have enabled the Mendelian randomization (MR) design, which uses genetic variation as a natural experiment to improve causal inferences from observational data. By analogy with the random assignment of treatment in randomized controlled trials, the random segregation of genetic alleles when DNA is transmitted from parents to offspring at gamete formation is expected to reduce confounding in genetic associations. Mendelian randomization analyses make a set of assumptions that must hold for valid results. Provided that the assumptions are well justified for the genetic variants that are employed as instrumental variables, MR studies can inform on whether a putative risk factor likely has a causal effect on the disease or not. Mendelian randomization has been increasingly applied over recent years to predict the efficacy and safety of existing and novel drugs targeting cardiovascular risk factors and to explore the repurposing potential of available drugs. This review article describes the principles of the MR design and some applications in cardiovascular epidemiology.

Emerging Medical Therapies for the Treatment of Obesity in Women with Cardiovascular Diseases

PURPOSE OF REVIEW

In this review, the impact of obesity on cardiovascular disease in women and emerging anti-obesity pharmacologic treatments are discussed.

RECENT FINDINGS

Robust evidence demonstrates the burden of obesity across the lifespan in women and links obesity to a diverse set of cardiovascular diseases. Female-specific risk factors including sex hormones and pregnancy factors intersect with obesity and cardiovascular risk. Sustained weight loss has potential for cardiovascular benefits. Recent trials demonstrate cardiovascular benefits of emerging agents with weight loss effects including GLP-1 RA and SGLT2 inhibitors in women. Treatment and prevention strategies for cardiovascular disease in obese women should include integration of weight management strategies including the targeted use of emerging pharmacologic therapies.

Appraising the Causal Role of Risk Factors in Coronary Artery Disease and Stroke: A Systematic Review of Mendelian Randomization Studies

BACKGROUND Mendelian randomization (MR) offers a powerful approach to study potential causal associations between exposures and health outcomes by using genetic variants associated with an exposure as instrumental variables. In this systematic review, we aimed to summarize previous MR studies and to evaluate the evidence for causality for a broad range of exposures in relation to coronary artery disease and stroke. METHODS AND RESULTS MR studies investigating the association of any genetically predicted exposure with coronary artery disease or stroke were identified. Studies were classified into 4 categories built on the significance of the main MR analysis results and its concordance with sensitivity analyses, namely, robust, probable, suggestive, and insufficient. Studies reporting associations that did not perform any sensitivity analysis were classified as nonevaluable. We identified 2725 associations eligible for evaluation, examining 535 distinct exposures. Of them, 141 were classified as robust, 353 as probable, 110 as suggestive, and 926 had insufficient evidence. The most robust associations were observed for anthropometric traits, lipids, and lipoproteins and type 2 diabetes with coronary artery; disease and clinical measurements with coronary artery disease and stroke; and thrombotic factors with stroke. CONCLUSIONS Despite the large number of studies that have been conducted, only a limited number of associations were supported by robust evidence. Approximately half of the studies reporting associations presented an MR sensitivity analysis along with the main analysis that further supported the causality of associations. Future research should focus on more thorough assessments of sensitivity MR analyses and further assessments of mediation effects or nonlinearity of associations.

Statins and risk of type 2 diabetes: mechanism and clinical implications

Statins are widely used to prevent cardiovascular disease events. Cardiovascular diseases and type 2 diabetes are tightly connected since type 2 diabetes is a major risk factor for cardiovascular diseases. Additionally, cardiovascular diseases often precede the development of type 2 diabetes. These two diseases have common genetic and environmental antecedents. Statins are effective in the lowering of cardiovascular disease events. However, they have also important side effects, including an increased risk of type 2 diabetes. The first study reporting an association of statin treatment with the risk of type 2 diabetes was the WOSCOPS trial (West of Scotland Coronary Prevention Study) in 2001. Other primary and secondary cardiovascular disease prevention studies as well as population-based studies have confirmed original findings. The purpose of our review is to examine and summarize the most important findings of these studies as well as to describe the mechanisms how statins increase the risk of type 2 diabetes.

Sex-specific risks for cardiovascular disease across the glycaemic spectrum: a population-based cohort study using the UK Biobank

Background

We sought to examine sex-specific risks for incident cardiovascular disease (CVD) across the full glycaemic spectrum.

Methods

Using data from UK Biobank, we categorised participants' glycated haemoglobin (HbA1c) at baseline as low-normal (<35 mmol/mol), normal (35-41 mmol/mol), pre-diabetes (42-47 mmol/mol), undiagnosed diabetes (≥48 mmol/mol), or diagnosed diabetes. Our outcomes were coronary artery disease (CAD), atrial fibrillation, deep vein thrombosis (DVT), pulmonary embolism (PE), stroke, heart failure, and a composite outcome of any CVD. Cox regression estimated sex-specific associations between HbA1c and each outcome, sequentially adjusting for socio-demographic, lifestyle, and clinical characteristics.

Findings

Among 427,435 people, CVD rates were 16.9 and 9.1 events/1000 person-years for men and women, respectively. Both men and women with pre-diabetes, undiagnosed diabetes, and, more markedly, diagnosed diabetes were at higher risks of CVD than those with normal HbA1c, with relative increases more pronounced in women than men. Age-adjusted HRs for pre-diabetes and undiagnosed diabetes ranged from 1.30 to 1.47; HRs for diagnosed diabetes were 1.55 (1.49-1.61) in men and 2.00 (1.89-2.12) in women (p-interaction <0.0001). Excess risks attenuated and were more similar between men and women after adjusting for clinical and lifestyle factors particularly obesity and antihypertensive or statin use (fully adjusted HRs for diagnosed diabetes: 1.06 [1.02-1.11] and 1.17 [1.10-1.24], respectively).

Interpretation

Excess risks in men and women were largely explained by modifiable factors, and could be ameliorated by attention to weight reduction strategies and greater use of antihypertensive and statin medications. Addressing these risk factors could reduce sex disparities in risk of CVD among people with and without diabetes.

Funding

Diabetes UK (#15/0005250) and British Heart Foundation (SP/16/6/32726).

Predicting mechanisms of action at genetic loci associated with discordant effects on type 2 diabetes and abdominal fat accumulation

Obesity is a major risk factor for cardiovascular disease, stroke, and type 2 diabetes (T2D). Excessive accumulation of fat in the abdomen further increases T2D risk. Abdominal obesity is measured by calculating the ratio of waist-to-hip circumference adjusted for the body-mass index (WHRadjBMI), a trait with a significant genetic inheritance. Genetic loci associated with WHRadjBMI identified in genome-wide association studies are predicted to act through adipose tissues, but many of the exact molecular mechanisms underlying fat distribution and its consequences for T2D risk are poorly understood. Further, mechanisms that uncouple the genetic inheritance of abdominal obesity from T2D risk have not yet been described. Here we utilize multi-omic data to predict mechanisms of action at loci associated with discordant effects on abdominal obesity and T2D risk. We find six genetic signals in five loci associated with protection from T2D but also with increased abdominal obesity. We predict the tissues of action at these discordant loci and the likely effector Genes (eGenes) at three discordant loci, from which we predict significant involvement of adipose biology. We then evaluate the relationship between adipose gene expression of eGenes with adipogenesis, obesity, and diabetic physiological phenotypes. By integrating these analyses with prior literature, we propose models that resolve the discordant associations at two of the five loci. While experimental validation is required to validate predictions, these hypotheses provide potential mechanisms underlying T2D risk stratification within abdominal obesity.

Bio-psycho-social factors' associations with brain age: a large-scale UK Biobank diffusion study of 35,749 participants

Brain age refers to age predicted by brain features. Brain age has previously been associated with various health and disease outcomes and suggested as a potential biomarker of general health. Few previous studies have systematically assessed brain age variability derived from single and multi-shell diffusion magnetic resonance imaging data. Here, we present multivariate models of brain age derived from various diffusion approaches and how they relate to bio-psycho-social variables within the domains of sociodemographic, cognitive, life-satisfaction, as well as health and lifestyle factors in midlife to old age (N = 35,749, 44.6-82.8 years of age). Bio-psycho-social factors could uniquely explain a small proportion of the brain age variance, in a similar pattern across diffusion approaches: cognitive scores, life satisfaction, health and lifestyle factors adding to the variance explained, but not socio-demographics. Consistent brain age associations across models were found for waist-to-hip ratio, diabetes, hypertension, smoking, matrix puzzles solving, and job and health satisfaction and perception. Furthermore, we found large variability in sex and ethnicity group differences in brain age. Our results show that brain age cannot be sufficiently explained by bio-psycho-social variables alone. However, the observed associations suggest to adjust for sex, ethnicity, cognitive factors, as well as health and lifestyle factors, and to observe bio-psycho-social factor interactions' influence on brain age in future studies.

Establishing plausibility of cardiovascular adverse effects of immunotherapies using Mendelian randomisation

Immune checkpoint inhibitors (ICIs) and Janus kinase inhibitors (JAKis) have raised concerns over serious unexpected cardiovascular adverse events. The widespread pleiotropy in genome-wide association studies offers an opportunity to identify cardiovascular risks from in-development drugs to help inform appropriate trial design and pharmacovigilance strategies. This study uses the Mendelian randomization (MR) approach to study the causal effects of 9 cardiovascular risk factors on ischemic stroke risk both independently and by mediation, followed by an interrogation of the implicated expression quantitative trait loci (eQTLs) to determine if the enriched pathways can explain the adverse stroke events observed with ICI or JAKi treatment. Genetic predisposition to higher systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), waist-to-hip ratio (WHR), low-density lipoprotein cholesterol (LDL), triglycerides (TG), type 2 diabetes (T2DM), and smoking index were associated with higher ischemic stroke risk. The associations of genetically predicted BMI, WHR, and TG on the outcome were attenuated after adjusting for genetically predicted T2DM [BMI: 53.15% mediated, 95% CI 17.21%-89.10%; WHR: 42.92% (4.17%-81.67%); TG: 72.05% (10.63%-133.46%)]. JAKis, programmed cell death protein 1 and programmed death ligand 1 inhibitors were implicated in the pathways enriched by the genes related to the instruments for each of SBP, DBP, WHR, T2DM, and LDL. Overall, MR mediation analyses support the role of T2DM in mediating the effects of BMI, WHR, and TG on ischemic stroke risk and follow-up pathway enrichment analysis highlights the utility of this approach in the early identification of potential harm from drugs.

Exploring the underlying mechanisms linking adiposity and cardiovascular disease: A prospective cohort study of 404,332 UK Biobank participants

BACKGROUND AND AIMS

Obesity is causally associated with multiple cardiovascular outcomes but effective population measure to control obesity is limited. This study aims to decipher to which extent excess atherosclerotic cardiovascular diseases (ASCVD) and heart failure (HF) risk due to obesity can be explained by conventional risk factors.

METHODS

This is a prospective cohort study of 404,332 White UK Biobank participants. Participants with prior CVDs or other chronic diseases at baseline, or body mass index (BMI) <18·5 kg/m2 were excluded. Data were collected at the baseline assessment between 2006 and 2010. Linkage to death registrations and hospital admission records was used to ascertain ASCVD and HF outcomes up to late 2021. Obesity was defined as BMI ≥30 kg/m2. Candidate mediators included lipids, blood pressure, glycated haemoglobin (HbA1c), and liver and kidney function markers, which were chosen based on clinical trials and Mendelian randomisation studies. Cox proportional hazard models were used to estimate hazard ratios (HR) and their 95% confidence intervals (CIs). Mediation analysis based on g-formula was used to separately estimate the relative importance of mediators for ASCVD and HF.

RESULTS

Compared with people without obesity, obese people had an increased risk of ASCVD (HR 1.30, 95% CI 1.26-1.35) and HF (HR 2.04, 95% CI 1.96-2.13) after adjusting for sociodemographic and lifestyle factors and medications for cholesterol, blood pressure and insulin. The strongest mediators for ASCVD were renal function (eGFR: mediation proportion: 44.6%), blood pressure (SBP: 24.4%; DBP: 31.1%), triglycerides (19.6%), and hyperglycaemia (HbA1c 18.9%). These mediators collectively explained more excess risk of ASCVD than that of HF.

CONCLUSIONS

Interventions that help obese individuals to maintain healthy lipid concentrations, blood pressure, glycaemic control and kidney function could potentially alleviate a sizable proportion of the ASCVD burden. However, HF burden could not be meaningfully reduced without weight management.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

The neural correlates of emotional conflict monitoring as an early manifestation of affective and cognitive declines in persons with Type 2 diabetes

Patients with Type 2 diabetes are known to be more susceptible to experience dementia and depression/anxiety. The neural circuits of emotional conflict monitoring, as indicated by a Stroop task, might become altered in terms of cognitive and affective impairments in diabetes. This study investigated alterations in the emotional conflict monitoring and associations of corresponding brain activities with metabolic parameters in persons with Type 2 diabetes. Participants with normal cognitive and affective functioning, including 40 persons with Type 2 diabetes and 30 non-diabetes control subjects, underwent a functional MRI paradigm with the face-word emotional Stroop task and detailed cognitive and affective assessments, including the Montreal Cognitive Assessment and Beck Anxiety Inventory. Compared with the controls, people with diabetes exhibited stronger emotional interference, as indicated by differential reaction times between congruent and incongruent trials (Δcon). Δcon was correlated with Montreal Cognitive Assessment test scores and fasting glucose levels. People with diabetes demonstrated altered brain activation and functional connectivity in the neural network for emotional conflict monitoring. The neural network for emotional conflict monitoring mediated the association of pancreatic function with anxiety scores as well as the relationship between Δcon and Montreal Cognitive Assessment scores. Results suggested that alterations in the neural network underlying emotional conflict monitoring might present before clinically measurable cognitive and affective decrements were apparent, thereby bridging the gap between dementia and anxiety/depression in persons with diabetes.

Using genetic association data to guide drug discovery and development: Review of methods and applications

Evidence on the validity of drug targets from randomized trials is reliable but typically expensive and slow to obtain. In contrast, evidence from conventional observational epidemiological studies is less reliable because of the potential for bias from confounding and reverse causation. Mendelian randomization is a quasi-experimental approach analogous to a randomized trial that exploits naturally occurring randomization in the transmission of genetic variants. In Mendelian randomization, genetic variants that can be regarded as proxies for an intervention on the proposed drug target are leveraged as instrumental variables to investigate potential effects on biomarkers and disease outcomes in large-scale observational datasets. This approach can be implemented rapidly for a range of drug targets to provide evidence on their effects and thus inform on their priority for further investigation. In this review, we present statistical methods and their applications to showcase the diverse opportunities for applying Mendelian randomization in guiding clinical development efforts, thus enabling interventions to target the right mechanism in the right population group at the right time. These methods can inform investigators on the mechanisms underlying drug effects, their related biomarkers, implications for the timing of interventions, and the population subgroups that stand to gain the most benefit. Most methods can be implemented with publicly available data on summarized genetic associations with traits and diseases, meaning that the only major limitations to their usage are the availability of appropriately powered studies for the exposure and outcome and the existence of a suitable genetic proxy for the proposed intervention.

Does educational attainment modify the causal relationship between adiposity and cardiovascular disease? A Mendelian randomization study

A greater risk of cardiovascular disease is associated with low educational attainment and high adiposity. Despite the correlation between low educational attainment and high adiposity, whether educational attainment modifies the risk of CVD caused by high adiposity remains poorly understood. We investigated the effect of adiposity (body mass index [BMI] and waist-to-hip ratio adjusted for BMI [WHRadjBMI]) on incident CVD among individuals with varying education levels, using associational and one-sample Mendelian randomization (MR) survival analyses. Data were collected from 2006 to 2021, and sample sizes were 254,281 (27,511 CVD cases) for BMI and 253,968 (27,458 CVD cases) for WHRadjBMI. In the associational model, a standard deviation (SD) higher BMI was associated with 19.81 (95% CI: 18.55-21.06) additional cases of incident CVD per 10,000 person-years for individuals with a secondary education, versus 32.96 (95% CI: 28.75-37.17) for those without. When university degree served as the education variable, education group differences attenuated, with 18.26 (95% CI: 16.37-20.15) cases from a one SD higher BMI for those with a university degree versus 23.18 [95% CI: 21.56-24.72] for those without. For the MR model, an SD higher BMI resulted in 11.75 (95% CI: -0.84-24.38) and 29.79 (95% CI: 17.20-42.44) additional cases of incident CVD per 10,000 person-years for individuals with versus without a university degree. WHRadjBMI exhibited no effect differences by education. While the associational model showed evidence of educational attainment modifying the relationship between adiposity and incident CVD, it does not modify the association between adiposity and incident CVD in the MR models. This suggests either less education does not cause greater risk of incident CVD from high adiposity, or MR models cannot detect the effect difference. The associational point estimates exist within the MR models' confidence intervals in all BMI analyses, so we cannot rule out the effect sizes in the associational models.

Effects of metabolic traits, lifestyle factors, and pharmacological interventions on liver fat: mendelian randomisation study

Objective

To investigate the effects of metabolic traits, lifestyle factors, and drug interventions on liver fat using the mendelian randomisation paradigm.

Design

Mendelian randomisation study.

Setting

Publicly available summary level data from genome-wide association studies.

Participants

Genome-wide association studies of 32 974 to 1 407 282 individuals who were predominantly of European descent.

Exposures

Genetic variants predicting nine metabolic traits, six lifestyle factors, four lipid lowering drug targets, three antihypertensive drug targets, and genetic association estimates formagnetic resonance imaging measured liver fat.

Main outcome measures

Mendelian randomisation analysis was used to investigate the effects of these exposures on liver fat, incorporating sensitivity analyses that relaxed the requisite modelling assumptions.

Results

Genetically predicted liability to obesity, type 2 diabetes, elevated blood pressure, elevated triglyceride levels, cigarette smoking, and sedentary time watching television were associated with higher levels of liver fat. Genetically predicted lipid lowering drug effects were not associated with liver fat; however, β blocker and calcium channel blocker antihypertensive drug effects were associated with lower levels of liver fat.

Conclusion

These analyses provide evidence of a causal effect of various metabolic traits, lifestyle factors, and drug targets on liver fat. The findings complement existing epidemiological associations, further provide mechanistic insight, and potentially supports a role for drug interventions in reducing the burden of hepatic steatosis and related disease. Further clinical study is now warranted to investigate the relevance of these genetic analyses for patient care.

Salivary uric acid reactivity and baseline associations with physiological stress response

Uric acid, an end product of the purinergic system, plays a role in several physiological systems that are responsive to stress. However, few studies have examined whether (1) uric acid concentrations change in response to acute stress, and (2) there are cross-system associations where uric acid might influence other physiological system responses to acute physical stress. The present study measured indices of the purinergic, hypothalamic-pituitary-adrenal axis, sympathetic, and parasympathetic systems (uric acid, cortisol, pre-ejection period, and root mean square of successive differences, respectively) in response to a standardized acute physical pain stressor, the cold pressor task. A diverse sample of participants (n = 67; mean age = 20.5 years, 52% female; 48% male) from a larger study completed anthropometric measurements and took part in a room temperature water task followed by the cold pressor task and sociodemographic questionnaires. Throughout the study, electrocardiography and impedance cardiography were measured continuously, and five saliva samples were collected that were later assayed for cortisol and uric acid. Descriptively, uric acid increased about 32 min following completion of the cold pressor. Resting uric acid concentrations were not associated with the autonomic nervous system response, but higher resting uric acid concentrations were associated with increased cortisol concentrations. Future research should examine the extent to which the purinergic system influences, and is influenced by, other types of stress and other physiological systems. The current findings highlight the potential role of an understudied biomarker and physiological system in the stress literature and have implications for basic and mechanistic researchers who study psychoneuroendocrinology, stress, and health.

Cardiovascular Disease Risk Reduction and Body Mass Index

PURPOSE OF REVIEW

Anti-hypertensive and lipid lowering therapy addresses only half of the cardiovascular disease risk in patients with body mass index > 30 kg/m², i.e., obesity. We examine newer aspects of obesity pathobiology that underlie the partial effectiveness of anti-hypertensive lipid lowering therapy for the reduction of cardiovascular disease risk in obesity.

RECENT FINDINGS

Obesity-related insulin resistance, vascular endothelium dysfunction, increased sympathetic nervous system/renin-angiotensin-aldosterone system activity, and glomerulopathy lead to type 2 diabetes, coronary atherosclerosis, and chronic disease kidney disease that besides hypertension and dyslipidemia increase cardiovascular disease risk. Obesity increases cardiovascular disease risk through multiple pathways. Optimal reduction of cardiovascular disease risk in patients with obesity is likely to require therapy targeted at both obesity and obesity-associated conditions.

BMI mediates the association of family medical history with self-reported hypertension and diabetes among older adults: Evidence from baseline wave of the longitudinal aging study in India

Background

This study explored the association between family history of hypertension and diabetes with their diagnosis among older Indian adults. The study further examined the role of body mass index (BMI) as a potential mediator in these associations.

Methods

Data from the Longitudinal Ageing Study in India (LASI, 2017-18), wave-1 were used. The sample for the study included 31,464 older adults aged 60 years and above. Descriptive statistics and bivariate analysis has been conducted to assess the prevalence of self-reported hypertension and diabetes. Further, multivariable logistic regression models were used to test the research hypotheses of this study. The Karlson-Holm-Breen (KHB) mediation analysis was conducted to recover the direct and indirect effects of BMI in the association of family medical history and diagnosis of hypertension and diabetes.

Results

A proportion of 32.70% of older adults were diagnosed with hypertension and 14.23% of older adults were diagnosed with diabetes. A proportion of 19.48% and 14.69% of older adults had a family history of hypertension and diabetes, respectively. Also, 16.57% and 5.53% of older adults were overweight and obese, respectively in the current study. Older adults who had family history of hypertension had higher odds of being diagnosed with hypertension [aOR: 2.23, CI: 2.07-2.39] than those who had no such family history. This association was mediated by BMI (percent mediated: 6.31%). Similarly, older adults who had family history of diabetes had higher odds of being diagnosed with diabetes [aOR: 2.63, CI: 2.41-2.88] than those who had no such family history. This association was mediated by BMI (percent effect mediated: 6.66%).

Conclusion

The study highlights the relevance of using family medical history data along with information on BMI as potential source for the control and management of hypertension and diabetes among older population.

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.

Causal Association of Cardiovascular Risk Factors and Lifestyle Behaviors With Peripheral Artery Disease: A Mendelian Randomization Approach

Background

We investigated the causal associations between the genetic liability to cardiovascular and lifestyle risk factors and peripheral artery disease (PAD), using a Mendelian randomization approach.

Methods and Results

We performed a 2‐sample inverse‐variance weighted Mendelian randomization analysis, multiple sensitivity analyses to assess pleiotropy and multivariate Mendelian randomization analyses to assess mediating/confounding factors. European‐ancestry genomic summary data (P<5×10⁻⁸) for type 2 diabetes, lipid‐fractions, smoking, alcohol and coffee consumption, physical activity, sleep, and education level were selected. Genetic associations with PAD were extracted from the Million‐Veteran‐Program genome‐wide association studies (cases=31 307, controls=211 753, 72% European‐ancestry) and the GoLEAD‐SUMMIT genome‐wide association studies (11 independent genome‐wide association studies, European‐ancestry, cases=12 086, controls=449 548). Associations were categorized as robust (Bonferroni‐significant (P<0.00294), consistent over PAD‐cohorts/sensitivity analyses), suggestive (P value: 0.00294–0.05, associations in 1 PAD‐cohort/inconsistent sensitivity analyses) or not present. Robust evidence for genetic liability to type 2 diabetes, smoking, insomnia, and inverse associations for higher education level with PAD were found. Suggestive evidence for the genetic liability to higher low‐density lipoprotein cholesterol, triglyceride‐levels, alcohol consumption, and inverse associations for high‐density lipoprotein cholesterol, and increased sleep duration were found. No associations were found for physical activity and coffee consumption. However, effects fully attenuated for low‐density lipoprotein cholesterol and triglycerides after correcting for apoB, and for insomnia after correcting for body mass index and lipid‐fractions. Nonsignificant attenuation by potential mediators was observed for education level and type 2 diabetes.

Conclusions

Detrimental effects of smoking and type 2 diabetes, but not of low‐density lipoprotein cholesterol and triglycerides, on PAD were confirmed. Lower education level and insomnia were identified as novel risk factors for PAD; however, complete mediation for insomnia and incomplete mediation for education level by downstream risk factors was observed.

Body Mass Index Is Independently Associated with the Presence of Ischemia in Myocardial Perfusion Imaging

Background and Objectives: Obesity has been linked to various cardiovascular risk factors, increased incidence of coronary artery disease, and myocardial perfusion defects. The aim of this study was to investigate if body mass index (BMI) and waist circumference (WC) were associated with myocardial perfusion defects. Materials and Methods: A total of 308 consecutive patients who had myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) and a complete medical record on file were studied retrospectively. Results: The median age was 69 (61−76) years, the BMI was 27.6 (24.4−30.7) kg/m2, and the WC was 110 (102−118) cm. Of the 308 patients, 239 patients (77.6%) had myocardial ischemia. A positive test for ischemia was more frequent in men compared to women (72 vs. 28%, p < 0.001). Within the male group, BMI and WC were not significantly different between the ischemia and non-ischemia groups. In contrast, within the female group, both BMI (30.2 vs. 27.1 kg/m2, p = 0.002) and WC (112 vs. 105.5 cm, p = 0.020) were significantly higher in the ischemia group. Multivariable logistic regression showed that male sex and BMI were the only two independent predictors of ischemia in our patient population. Conclusions: This study showed that BMI was an independent predictor of ischemia in our patient population.

Mendelian randomization highlights the causal association of obesity with periodontal diseases

AIM

The underlying mechanisms connecting obesity and periodontal diseases remain unclear. This study investigates the potential causal association of obesity with periodontal diseases using Mendelian randomization (MR).

MATERIALS AND METHODS

Single-nucleotide polymorphisms of obesity traits including body mass index (BMI), waist circumference (WC), and WC adjusted for BMI (WCadjBMI) from large-scale genome-wide association studies were screened for instrumental variables. The single trait periodontitis and the combined trait comprising periodontitis and loose teeth were adopted as surrogates for periodontal diseases. Inverse-variance weighted (IVW), series of sensitivity analyses and multivariable MR were employed to determine the association of obesity with periodontal diseases.

RESULTS

IVW results showed that per 1-SD increment in BMI (odds ratio, OR = 1.115; 95% confidence interval [CI] = 1.064-1.169; p < .001) and WC (OR = 1.117; 95% CI = 1.052-1.185; p < .001), but not WCadjBMI, were significantly associated with an increased risk of periodontitis/loose teeth. Moreover, the MR estimates were consistent across other MR sensitivity analyses and multivariable MR. However, a causal association of obesity with the single trait periodontitis was not identified.

CONCLUSIONS

The presented evidence supports previous epidemiological findings by showing a potential causal association of genetic liability to obesity with periodontal diseases. The biological mechanisms underlying this association warrant further investigation.

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

AIMS/HYPOTHESIS

Type 2 diabetes and atherosclerotic CVD share many risk factors. This study aimed to systematically assess a broad range of continuous traits to separate their direct effects on coronary and peripheral artery disease from those mediated by type 2 diabetes.

METHODS

Our main analysis was a two-step Mendelian randomisation for mediation to quantify the extent to which the associations observed between continuous traits and liability to atherosclerotic CVD were mediated by liability to type 2 diabetes. To support this analysis, we performed several univariate Mendelian randomisation analyses to examine the associations between our continuous traits, liability to type 2 diabetes and liability to atherosclerotic CVD.

RESULTS

Eight traits were eligible for the two-step Mendelian randomisation with liability to coronary artery disease as the outcome and we found similar direct and total effects in most cases. Exceptions included fasting insulin and hip circumference where the proportion mediated by liability to type 2 diabetes was estimated as 56% and 52%, respectively. Six traits were eligible for the analysis with liability to peripheral artery disease as the outcome. Again, we found limited evidence to support mediation by liability to type 2 diabetes for all traits apart from fasting insulin (proportion mediated: 70%).

CONCLUSIONS/INTERPRETATION

Most traits were found to affect liability to atherosclerotic CVD independently of their relationship with liability to type 2 diabetes. These traits are therefore important for understanding atherosclerotic CVD risk regardless of an individual's liability to type 2 diabetes.

Vascular Health Is Associated With Functional Connectivity Decline in Higher-Order Networks of Older Adults

Background

Poor vascular health may impede brain functioning in older adults, thus possibly increasing the risk of cognitive decline and Alzheimer’s disease (AD). The emerging link between vascular risk factors (VRF) and longitudinal decline in resting-state functional connectivity (RSFC) within functional brain networks needs replication and further research in independent cohorts.

Method

We examined 95 non-demented older adults using the IMAP+ cohort (Caen, France). VRF were assessed at baseline through systolic and diastolic blood pressure, body-mass-index, and glycated hemoglobin (HbA1c) levels. Brain pathological burden was measured using white matter hyperintensity (WMH) volumes, derived from FLAIR images, and cortical β-Amyloid (Aβ) deposition, derived from florbetapir-PET imaging. RSFC was estimated from functional MRI scans within canonical brain networks at baseline and up to 3 years of follow-up. Linear mixed-effects models evaluated the independent predictive value of VRF on longitudinal changes in network-specific and global RSFC as well as a potential association between these RSFC changes and cognitive decline.

Results

We replicate that RSFC increased over time in global RSFC and in the default-mode, salience/ventral-attention and fronto-parietal networks. In contrast, higher diastolic blood pressure levels were independently associated with a decrease of RSFC over time in the default-mode, salience/ventral-attention, and fronto-parietal networks. Moreover, higher HbA1c levels were independently associated with a reduction of the observed RSFC increase over time in the salience/ventral-attention network. Both of these associations were independent of brain pathology related to Aβ load and WMH volumes. The VRF-related changes in RSFC over time were not significantly associated with longitudinal changes in cognitive performance.

Conclusion

Our longitudinal findings corroborate that VRF promote RSFC alterations over time within higher-order brain networks, irrespective of pathological brain burden. Altered RSFC in large-scale cognitive networks may eventually increase the vulnerability to aging and AD.

Noise-augmented directional clustering of genetic association data identifies distinct mechanisms underlying obesity

Clustering genetic variants based on their associations with different traits can provide insight into their underlying biological mechanisms. Existing clustering approaches typically group variants based on the similarity of their association estimates for various traits. We present a new procedure for clustering variants based on their proportional associations with different traits, which is more reflective of the underlying mechanisms to which they relate. The method is based on a mixture model approach for directional clustering and includes a noise cluster that provides robustness to outliers. The procedure performs well across a range of simulation scenarios. In an applied setting, clustering genetic variants associated with body mass index generates groups reflective of distinct biological pathways. Mendelian randomization analyses support that the clusters vary in their effect on coronary heart disease, including one cluster that represents elevated body mass index with a favourable metabolic profile and reduced coronary heart disease risk. Analysis of the biological pathways underlying this cluster identifies inflammation as potentially explaining differences in the effects of increased body mass index on coronary heart disease.

Birth weight, adult weight, and cardiovascular biomarkers: Evidence from the Cardiovascular Young Finns Study

This study quantifies the causal effect of birth weight on cardiovascular biomarkers in adulthood using the Cardiovascular Risk in Young Finns Study (YFS). We apply a multivariable Mendelian randomization (MVMR) method that provides a novel approach to improve inference in causal analysis based on a mediation framework. The results show that birth weight is linked to triglyceride levels (β = -0.294; 95% CI [-0.591, 0.003]) but not to low-density lipoprotein (LDL) cholesterol levels (β = 0.007; 95% CI [-0.168, 0.183]). The total effect of birth weight on triglyceride levels is partly offset by a mediation pathway linking birth weight to adult BMI (β = 0.111; 95% CI [-0.013, 0.234]). The negative total effect is consistent with the fetal programming hypothesis. The positive indirect effect via adult BMI highlights the persistence of body weight throughout a person's life and the adverse effects of high BMI on health. The results are consistent with previous findings that both low birth weight and weight gain increase health risks in adulthood.

Assessment of causal associations between handgrip strength and cardiovascular diseases: A two sample mendelian randomization study

Background

Several observational studies have identified that handgrip strength was inversely associated with cardiovascular diseases (CVDs). Nevertheless, causality remains controversial. We conducted Mendelian randomization (MR) analysis to examine whether handgrip strength and risk of CVDs are causally associated.

Methods

We identified 160 independent single nucleotide polymorphisms (SNPs) for right-hand grip strength and 136 independent SNPs for left-hand grip strength at the genome-wide significant threshold (P < 5 × 10^-8) from UK Biobank participants and evaluated these in relation to risk of CVDs. MR estimates was calculated using the inverse-variance weighted (IVW) method and multiple sensitivity analysis was further conducted.

Results

Genetical liability to handgrip strength was significantly associated with coronary artery disease (CAD) and myocardial infarction (MI), but not stroke, hypertension, or heart failure. Additionally, there was significant association between right-hand grip strength and atrial fibrillation (OR, 0.967; 95% CI, 0.950-0.984; p = 0.000222), however, suggestive significance was found between left-hand grip strength and atrial fibrillation (OR, 0.977; 95% CI, 0.957-0.998; p = 0.033). Results were similar in several sensitivity analysis.

Conclusion

Our study provides support at the genetic level that handgrip strength is negatively associated with the risk of CAD, MI, and atrial fibrillation. Specific handgrip strength interventions on CVDs warrant exploration as potential CVDs prevention measures.

Causal role of high body mass index in multiple chronic diseases: a systematic review and meta-analysis of Mendelian randomization studies

BACKGROUND

Obesity is a worldwide epidemic that has been associated with a plurality of diseases in observational studies. The aim of this study was to summarize the evidence from Mendelian randomization (MR) studies of the association between body mass index (BMI) and chronic diseases.

METHODS

PubMed and Embase were searched for MR studies on adult BMI in relation to major chronic diseases, including diabetes mellitus; diseases of the circulatory, respiratory, digestive, musculoskeletal, and nervous systems; and neoplasms. A meta-analysis was performed for each disease by using results from published MR studies and corresponding de novo analyses based on summary-level genetic data from the FinnGen consortium (n = 218,792 individuals).

RESULTS

In a meta-analysis of results from published MR studies and de novo analyses of the FinnGen consortium, genetically predicted higher BMI was associated with increased risk of type 2 diabetes mellitus, 14 circulatory disease outcomes, asthma, chronic obstructive pulmonary disease, five digestive system diseases, three musculoskeletal system diseases, and multiple sclerosis as well as cancers of the digestive system (six cancer sites), uterus, kidney, and bladder. In contrast, genetically predicted higher adult BMI was associated with a decreased risk of Dupuytren's disease, osteoporosis, and breast, prostate, and non-melanoma cancer, and not associated with Alzheimer's disease, amyotrophic lateral sclerosis, or Parkinson's disease.

CONCLUSIONS

The totality of the evidence from MR studies supports a causal role of excess adiposity in a plurality of chronic diseases. Hence, continued efforts to reduce the prevalence of overweight and obesity are a major public health goal.

Blood Levels of the SMOC1 Hepatokine Are Not Causally Linked with Type 2 Diabetes: A Bidirectional Mendelian Randomization Study

Hepatokines are liver-derived proteins that may influence metabolic pathways such as insulin sensitivity. Recently, Sparc-related modular calcium-binding protein 1 (SMOC1) was identified as glucose-responsive hepatokine that is dysregulated in the setting of non-alcoholic fatty liver disease (NAFLD). While SMOC1 may influence glucose-insulin homeostasis in rodents, it is unknown if SMOC1 is influenced by NAFLD in humans. It is also unknown if SMOC1 is causally associated with metabolic and disease traits in humans. Therefore, we aimed to determine the effect of NAFLD on SMOC1 gene expression in the liver and aimed to explore the potential causal associations of SMOC1 levels with NAFLD, T2D, and glycemic traits in humans. Using an RNA sequencing dataset from a cohort of 216 patients with NAFLD, we assessed SMOC1 expression levels across the NAFLD spectrum. We performed a series of bidirectional inverse-variance weighted Mendelian randomization (MR) analyses on blood SMOC1 levels using two sources of genome-wide association studies (GWAS) (Fenland study, n = 10,708 and INTERVAL study, n = 3301). We utilized GWAS summary statistics for NAFLD in 8434 cases and 770,180 controls, as well as publicly available GWAS for type 2 diabetes (T2D), body mass index (BMI), waist-to-hip ratio (WHR), fasting blood insulin (FBI), fasting blood glucose (FBG), homeostatic Model Assessment of Insulin Resistance (HOMA-B and HOMA-IR), and hemoglobin A1c (HbA1C). We found that SMOC1 expression showed no significant differences across NAFLD stages. We also identified that the top single-nucleotide polymorphism associated with blood SMOC1 levels, was associated with SMOC1 gene expression in the liver, but not in other tissues. Using MR, we did not find any evidence that genetically predicted NAFLD, T2D, and glycemic traits influenced SMOC1 levels. We also did not find evidence that blood SMOC1 levels were causally associated with T2D, NAFLD, and glycemic traits. In conclusion, the hepatokine SMOC1 does not appear to be modulated by the presence of NAFLD and may not regulate glucose-insulin homeostasis in humans. Results of this study suggest that blood factors regulating metabolism in rodents may not always translate to human biology.

Physical Activity and Risks of Cardiovascular Diseases: A Mendelian Randomization Study

Background: Although some observational studies have shown that physical activity may have a positive relationship with cardiovascular diseases, the causal effect remains uncertain. We conducted a Mendelian randomization (MR) study to identify the potential causal effect between physical activity and cardiovascular diseases.

Methods: Summary statistics of genome-wide association studies on four physical activity phenotypes and cardiovascular diseases were utilized. MR analysis was performed using inverse-variance weighted (IVW) and multivariable MR. Multiple sensitivity analysis was further conducted to identify the robustness of our results.

Results: Genetically predicted self-reported vigorous physical activity (VPA) was significantly associated with lower risk of myocardial infarction (IVW OR: 0.24, 95% CI: 0.08–0.68, p-value: 0.007). Additionally, the causal effect of VPA with myocardial infarction was robust after adjusting for several cardiovascular risk factors through using the multivariable MR. There were no apparent causal associations between physical activity with other cardiovascular diseases. Results were consistent with the sensitivity analysis.

Conclusion: The present study supports a protective role of self-reported vigorous physical activity in the initiation of myocardial infarction and highlights the importance of activity levels of physical activity. Further studies are required to elucidate the potential biological pathways of physical activity with cardiovascular diseases.

The "Common Soil Hypothesis" Revisited-Risk Factors for Type 2 Diabetes and Cardiovascular Disease

The prevalence and the incidence of type 2 diabetes (T2D), representing >90% of all cases of diabetes, are increasing rapidly worldwide. Identification of individuals at high risk of developing diabetes is of great importance, as early interventions might delay or even prevent full-blown disease. T2D is a complex disease caused by multiple genetic variants in interaction with lifestyle and environmental factors. Cardiovascular disease (CVD) is the major cause of morbidity and mortality. Detailed understanding of molecular mechanisms underlying in CVD events is still largely missing. Several risk factors are shared between T2D and CVD, including obesity, insulin resistance, dyslipidemia, and hyperglycemia. CVD can precede the development of T2D, and T2D is a major risk factor for CVD, suggesting that both conditions have common genetic and environmental antecedents and that they share “common soil”. We analyzed the relationship between the risk factors for T2D and CVD based on genetics and population-based studies with emphasis on Mendelian randomization studies.