Mendelian randomization in cardiometabolic disease: challenges in evaluating causality

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.

From GWAS to Gene: Transcriptome-Wide Association Studies and Other Methods to Functionally Understand GWAS Discoveries

Since their inception, genome-wide association studies (GWAS) have identified more than a hundred thousand single nucleotide polymorphism (SNP) loci that are associated with various complex human diseases or traits. The majority of GWAS discoveries are located in non-coding regions of the human genome and have unknown functions. The valley between non-coding GWAS discoveries and downstream affected genes hinders the investigation of complex disease mechanism and the utilization of human genetics for the improvement of clinical care. Meanwhile, advances in high-throughput sequencing technologies reveal important genomic regulatory roles that non-coding regions play in the transcriptional activities of genes. In this review, we focus on data integrative bioinformatics methods that combine GWAS with functional genomics knowledge to identify genetically regulated genes. We categorize and describe two types of data integrative methods. First, we describe fine-mapping methods. Fine-mapping is an exploratory approach that calibrates likely causal variants underneath GWAS signals. Fine-mapping methods connect GWAS signals to potentially causal genes through statistical methods and/or functional annotations. Second, we discuss gene-prioritization methods. These are hypothesis generating approaches that evaluate whether genetic variants regulate genes via certain genetic regulatory mechanisms to influence complex traits, including colocalization, mendelian randomization, and the transcriptome-wide association study (TWAS). TWAS is a gene-based association approach that investigates associations between genetically regulated gene expression and complex diseases or traits. TWAS has gained popularity over the years due to its ability to reduce multiple testing burden in comparison to other variant-based analytic approaches. Multiple types of TWAS methods have been developed with varied methodological designs and biological hypotheses over the past 5 years. We dive into discussions of how TWAS methods differ in many aspects and the challenges that different TWAS methods face. Overall, TWAS is a powerful tool for identifying complex trait-associated genes. With the advent of single-cell sequencing, chromosome conformation capture, gene editing technologies, and multiplexing reporter assays, we are expecting a more comprehensive understanding of genomic regulation and genetically regulated genes underlying complex human diseases and traits in the future.

HDL cholesterol concentrations and risk of atherosclerotic cardiovascular disease - Insights from randomized clinical trials and human genetics

Through seven decades the inverse association between HDL cholesterol concentrations and risk of atherosclerotic cardiovascular disease (ASCVD) has been observed in case-control and prospective cohort studies. This robust inverse association fuelled the enthusiasm towards development of HDL cholesterol increasing drugs, exemplified by the cholesteryl ester transfer protein (CETP) inhibitor trials and the extended-release niacin HPS2-THRIVE trial. These HDL cholesterol increasing trials were launched without conclusive evidence from human genetics, and despite discrepant species dependent evidence from animal studies. Evidence from human genetics and from randomized clinical trials over the last 13 years now point in the direction that concentrations of HDL cholesterol, do not appear to be a viable future path to target therapeutically for prevention of ASCVD. A likely explanation for the strong observational association between low HDL cholesterol and high ASCVD risk is the concomitant inverse association between HDL cholesterol and atherogenic triglyceride-rich lipoproteins. The purpose of the present review is to bring HDL cholesterol increasing trials into a human genetics context exemplified by candidate gene studies of key players in HDL biogenesis as well as by HDL cholesterol related genome-wide association studies.

High-density lipoproteins (HDL): Novel function and therapeutic applications

The failure of high-density lipoprotein (HDL)-raising agents to reduce cardiovascular disease (CVD) together with recent findings of increased cardiovascular mortality in subjects with extremely high HDL-cholesterol levels provide new opportunities to revisit our view of HDL. The concept of HDL function developed to explain these contradictory findings has recently been expanded by a role played by HDL in the lipolysis of triglyceride-rich lipoproteins (TGRLs) by lipoprotein lipase. According to the reverse remnant-cholesterol transport (RRT) hypothesis, HDL critically contributes to TGRL lipolysis via acquirement of surface lipids, including free cholesterol, released from TGRL. Ensuing cholesterol transport to the liver with excretion into the bile may reduce cholesterol influx in the arterial wall by accelerating removal from circulation of atherogenic, cholesterol-rich TGRL remnants. Such novel function of HDL opens wide therapeutic applications to reduce CVD in statin-treated patients, which primarily involve activation of cholesterol flux upon lipolysis.

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.

The impact of serum 25-hydroxyvitamin D, calcium, and parathyroid hormone levels on the risk of coronary artery disease in patients with diabetes: a Mendelian randomization study

BACKGROUND

To investigate the causal association between serum 25-hydroxyvitamin D (25OHD), calcium (Ca), and parathyroid hormone (PTH) levels and the risk of coronary artery disease (CAD) in patients with diabetes using a Mendelian randomization approach.

METHODS

Genetic signatures associated with serum 25OHD, Ca, and PTH levels were extracted from recently published genome-wide association study (GWAS), including 79,366, 39,400, 29,155 individuals, respectively. Genetic association estimates for CAD in patients with diabetes were obtained from a GWAS of 15,666 individuals with diabetes (3,968 CAD cases, 11,696 controls). The inverse-variance-weighted method was employed for the primary analysis, and other robust methods were applied for sensitivity analyses.

RESULTS

Six, seven and five single nucleotide polymorphisms were identified as instrumental variables for serum 25OHD, Ca and PTH levels, respectively. There was no significant association between genetically predicted serum 25OHD levels and the risk of CAD in patients with diabetes (odds ratio (OR) = 1.04, 95% confidence interval (CI): 0.58 - 1.87, P = 0.888). Similarly, genetically predicted serum Ca (OR = 1.83, 95% CI: 0.62 - 5.35, P = 0.273) and PTH levels (OR = 1.27, 95% CI: 0.67 - 2.44, P = 0.464) were not significantly associated with the risk of CAD in patients with diabetes. These findings were robust in sensitivity analyses.

CONCLUSIONS/INTERPRETATION

Serum 25OHD, Ca and PTH levels may not be causally associated with the risk of CAD in patients with diabetes.

Mendelian Randomization Analysis as a Tool to Gain Insights into Causes of Diseases: A Primer

Many Mendelian randomization (MR) studies have been published recently, with inferences on the causal relationships between risk factors and diseases that have potential implications for clinical research. In nephrology, MR methods have been applied to investigate potential causal relationships of traditional risk factors, lifestyle factors, and biomarkers from omics technologies with kidney function or CKD. This primer summarizes the basic concepts of MR studies, highlighting methods used in recent applications, and emphasizes key elements in conducting and reporting of MR studies that are important for interpreting the results.

Gene-by-environment modulation of lifespan and weight gain in the murine BXD family

How lifespan and body weight vary as a function of diet and genetic differences is not well understood. Here we quantify the impact of differences in diet on lifespan in a genetically diverse family of female mice, split into matched isogenic cohorts fed a low-fat chow diet (CD, n = 663) or a high-fat diet (HFD, n = 685). We further generate key metabolic data in a parallel cohort euthanized at four time points. HFD feeding shortens lifespan by 12%: equivalent to a decade in humans. Initial body weight and early weight gains account for longevity differences of roughly 4-6 days per gram. At 500 days, animals on a HFD typically gain four times as much weight as control, but variation in weight gain does not correlate with lifespan. Classic serum metabolites, often regarded as health biomarkers, are not necessarily strong predictors of longevity. Our data indicate that responses to a HFD are substantially modulated by gene-by-environment interactions, highlighting the importance of genetic variation in making accurate individualized dietary recommendations.

Germline risk of clonal haematopoiesis

Clonal haematopoiesis (CH) is a common, age-related expansion of blood cells with somatic mutations that is associated with an increased risk of haematological malignancies, cardiovascular disease and all-cause mortality. CH may be caused by point mutations in genes associated with myeloid neoplasms, chromosomal copy number changes and loss of heterozygosity events. How inherited and environmental factors shape the incidence of CH is incompletely understood. Even though the several varieties of CH may have distinct phenotypic consequences, recent research points to an underlying genetic architecture that is highly overlapping. Moreover, there are numerous commonalities between the inherited variation associated with CH and that which has been linked to age-associated biomarkers and diseases. In this Review, we synthesize what is currently known about how inherited variation shapes the risk of CH and how this genetic architecture intersects with the biology of diseases that occur with ageing.

Coffee Consumption and Incident Tachyarrhythmias: Reported Behavior, Mendelian Randomization, and Their Interactions

Importance

The notion that caffeine increases the risk of cardiac arrhythmias is common. However, evidence that the consumption of caffeinated products increases the risk of arrhythmias remains poorly substantiated.

Objective

To assess the association between consumption of common caffeinated products and the risk of arrhythmias.

Design, Setting, and Participants

This prospective cohort study analyzed longitudinal data from the UK Biobank between January 1, 2006, and December 31, 2018. After exclusion criteria were applied, 386 258 individuals were available for analyses.

Exposures

Daily coffee intake and genetic polymorphisms that affect caffeine metabolism.

Main Outcomes and Measures

Any cardiac arrhythmia, including atrial fibrillation or flutter, supraventricular tachycardia, ventricular tachycardia, premature atrial complexes, and premature ventricular complexes.

Results

A total of 386 258 individuals (mean [SD] age, 56 [8] years; 52.3% female) were assessed. During a mean (SD) follow-up of 4.5 (3.1) years, 16 979 participants developed an incident arrhythmia. After adjustment for demographic characteristics, comorbid conditions, and lifestyle habits, each additional cup of habitual coffee consumed was associated with a 3% lower risk of incident arrhythmia (hazard ratio [HR], 0.97; 95% CI, 0.96-0.98; P < .001). In analyses of each arrhythmia alone, statistically significant associations exhibiting a similar magnitude were observed for atrial fibrillation and/or flutter (HR, 0.97; 95% CI, 0.96-0.98; P < .001) and supraventricular tachycardia (HR, 0.96; 95% CI, 0.94-0.99; P = .002). Two distinct interaction analyses, one using a caffeine metabolism-related polygenic score of 7 genetic polymorphisms and another restricted to CYP1A2 rs762551 alone, did not reveal any evidence of effect modification. A mendelian randomization study that used these same genetic variants revealed no significant association between underlying propensities to differing caffeine metabolism and the risk of incident arrhythmia.

Conclusions and Relevance

In this prospective cohort study, greater amounts of habitual coffee consumption were associated with a lower risk of arrhythmia, with no evidence that genetically mediated caffeine metabolism affected that association. Mendelian randomization failed to provide evidence that caffeine consumption was associated with arrhythmias.

Genetic Determinants of Increased Body Mass Index Partially Mediate the Effect of Elevated Birth Weight on the Increased Risk of Atrial Fibrillation

Background: Although several observational studies have shown an association between birth weight (BW) and atrial fibrillation (AF), controversy remains. In this study, we aimed to explore the role of elevated BW on the etiology of AF.

Methods: A two-sample Mendelian randomization (MR) study was designed to infer the causality. The genetic data on the associations of single-nucleotide polymorphisms (SNPs) with BW and AF were separately obtained from two large-scale genome-wide association studies with up to 321,223 and 1,030,836 individuals, respectively. SNPs were identified at a genome-wide significant level (p <5 × 10⁻⁸). The inverse variance-weighted (IVW) method was employed to obtain causal estimates as our primary analysis. Sensitivity analyses with various statistical methods were applied to evaluate the robustness of the results, and multivariable MR analysis was conducted to determine whether this association was mediated by the body mass index (BMI).

Results: In total, 144 SNPs were identified as the genetic instrumental variables. MR analysis revealed a causal effect of elevated BW on AF (OR = 1.27, 95% CI = 1.14–1.40, p = 5.70 × 10⁻⁶). All the results in sensitivity analyses were consistent with the primary result. The effect of BW on AF was attenuated when adjusted for BMI (OR = 1.16, 95% CI = 1.01–1.33, p = 0.04).

Conclusions: This study indicated that elevated BW was significantly associated with increased lifelong risk of AF, which may be partially mediated by BMI.

Mendelian Randomization Studies in Stroke: Exploration of Risk Factors and Drug Targets With Human Genetic Data

Elucidating the causes of stroke is key to developing effective preventive strategies. The Mendelian randomization approach leverages genetic variants related to an exposure of interest to investigate the effects of varying that exposure on disease risk. The random allocation of genetic variants at conception reduces confounding from environmental factors and thus strengthens causal inference, analogous to treatment allocation in a randomized controlled trial. With the recent explosion in the availability of human genetic data, Mendelian randomization has proven a valuable tool for studying risk factors for stroke. In this review, we provide an overview of recent developments in the application of Mendelian randomization to unravel the pathophysiology of stroke subtypes and identify therapeutic targets for clinical translation. The approach has offered novel insight into the differential effects of risk factors and antihypertensive, lipid-lowering, and anticoagulant drug classes on risk of stroke subtypes. Analyses have further facilitated the prioritization of novel drug targets, such as for inflammatory pathways underlying large artery atherosclerotic stroke and for the coagulation cascade that contributes to cardioembolic stroke. With continued methodological advances coupled with the rapidly increasing availability of genetic data related to a broad range of stroke phenotypes, the potential for Mendelian randomization in this context is expanding exponentially.

Impact of sex hormone-binding globulin on the human phenome

Background: Sex hormone-binding globulin (SHBG) is a circulating glycoprotein and a regulator of sex hormone levels, which has been shown to influence various traits and diseases. The molecular nature of SHBG makes it a feasible target for preventative or therapeutic interventions. A systematic study of its effects across the human phenome may uncover novel associations. Methods: We used a Mendelian randomization phenome-wide association study (MR-pheWAS) approach to systematically appraise the potential functions of SHBG while reducing potential biases such as confounding and reverse causation common to the literature. We searched for potential causal effects of SHBG in UK Biobank (N = 334 977) and followed-up our top findings using two-sample MR analyses to evaluate whether estimates may be biased due to horizontal pleiotropy. Results: Results of the MR-pheWAS across over 21 000 outcome phenotypes identified 12 phenotypes associated with genetically elevated SHBG after Bonferroni correction for multiple testing. Follow-up analysis using two-sample MR indicated the associations of increased natural log SHBG with higher impedance of the arms and whole body, lower pulse rate, lower bone density, higher odds of hip replacement, lower odds of high cholesterol or cholesterol medication use and higher odds of gallbladder removal. Conclusions: Our systematic MR-pheWAS of SHBG, which was comprehensive to the range of phenotypes available in UK Biobank, suggested that higher circulating SHBG affects the body impedance, bone density and cholesterol levels, among others. These phenotypes should be prioritized in future studies aiming to investigate the biological effects of SHBG or develop targets for therapeutic intervention.

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.

Genetics of Type 2 Diabetes: Opportunities for Precision Medicine: JACC Focus Seminar

Type 2 diabetes (T2D) is highly prevalent and is a strong contributor for cardiovascular disease. However, there is significant heterogeneity in disease pathogenesis and the risk of complications. Enormous progress has been made in our ability to catalog genetic variation associated with T2D risk and variation in disease-relevant quantitative traits. These discoveries hold the potential to shed light on tractable targets and pathways for safe and effective therapeutic development, but the promise of precision medicine has been slow to be realized. Recent studies have identified subgroups of individuals with differential risk for intermediate phenotypes (eg, lipid levels, fasting insulin, body mass index) that contribute to T2D risk, helping to account for the observed clinical heterogeneity. These "partitioned genetic risk scores" not only have the potential to identify patients at greatest risk of cardiovascular disease and rapid disease progression, but also could aid patient stratification bridging the gap toward precision medicine for T2D.

Educational attainment and drinking behaviors: Mendelian randomization study in UK Biobank

Educational attainment has been associated with drinking behaviors in observation studies. We performed Mendelian randomization analysis to determine whether educational attainment causally affected drinking behaviors, including amount of alcohol intakes (in total and various types), drinking frequency, and drinking with or without meals among 334,507 white British participants from the UK Biobank cohort. We found that genetically instrumented higher education (1 additional year) was significantly related to higher total amount of alcohol intake (inverse-variance weighted method (IVW): beta = 0.44, 95% confidence interval (CI) 0.40-0.49, P = 1.57E-93). The causal relations with total amount and frequency of alcohol drinking were more evident among women. In analyses of different types of alcohol, higher educational attainment showed the strongest causal relation with more consumption of red wine (IVW beta = 0.34, 95% CI 0.32-0.36, P = 2.65E-247), followed by white wine/champagne, in a gender-specific manner. An inverse association was found for beer/cider and spirits. In addition, we found that 1 additional year of educational attainment was causally related to higher drinking frequency (IVW beta = 0.54, 95% CI 0.51-0.57, P = 4.87E-230) and a higher likelihood to take alcohol with meals (IVW: odds ratio (OR) = 3.10, 95% CI 2.93-3.29, P = 0.00E + 00). The results indicate causal relations of higher education with intake of more total alcohol especially red wine, and less beer/cider and spirits, more frequent drinking, and drinking with meals, suggesting the importance of improving drinking behaviors, especially among people with higher education.

Correlation between serum 25-hydroxyvitamin D level and coronary heart disease

OBJECTIVE

To test the relationship between serum 25-hydroxyvitamin D[25(OH)D], interleukin-6 (IL-6), and the severity of coronary heart disease (CHD).

METHODS

A total of 150 patients with suspected myocardial ischemia presenting to our hospital from January 2018 to January 2020 were recruited. All patients underwent percutaneous coronary angiography (CAG). According to CAG results, they were divided into normal group (n=40) and CHD group (n=110). According to the coronary Gensini score, CHD patients were divided into 62 cases in the low-risk group (< 20 points), 31 cases in the moderate-risk group (20-40 points), and 17 cases in the high-risk group (> 40 points). The Gensini scores and serum 25(OH)D and IL-6 levels in each group were recorded, and the correlation between the serum 25(OH)D and IL-6 levels and the severity of the disease was analyzed. The Essen Stroke Risk Scale (ESRS) was evaluated and compared between the two groups.

RESULTS

The serum 25(OH)D, IL-6 level, and ESRS score in the CHD group and the normal group statistically differed (P < 0.05). In the CHD group, Gensini score, serum IL-6 level and ESRS score increased with the increase of coronary artery stenosis, and 25(OH)D level decreased with the increase of coronary artery stenosis, and all the differences were significant (P < 0.05). Pearson correlation analysis demonstrated that serum IL-6 levels in patients with CHD are positively correlated with the severity of the disease (r=0.724, P < 0.001), and 25(OH)D levels are in a negative relation (r=-0.522, P < 0.001).

CONCLUSION

A decrease of serum 25(OH)D level and increase in IL-6 level in patients with CHD are associated with the severity of CHD. This may provide a reference for clinical diagnosis, treatment, and prognosis.

Serum iron status and the risk of breast cancer in the European population: a two-sample Mendelian randomisation study

BACKGROUND

Previous observational studies have provided conflicting results on the association between serum iron status and the risk of breast cancer. Considering the relevance of this relationship to breast cancer prevention, its elucidation is warranted.

OBJECT

We used a two-sample Mendelian randomisation (MR) study to explore the causal relationship between serum iron status and the risk of breast cancer.

METHOD

To select single nucleotide polymorphisms (SNPs) that could be used as instrumental variables for iron status, we used the Genetics of Iron Status consortium, which includes 11 discovery and 8 replication cohorts, encompassing 48,972 individuals of European descent. Moreover, we used the OncoArray network to select SNPs that could be considered instrumental variables for the outcome of interest (breast cancer); this dataset included 122,977 individuals of European descent with breast cancer and 105,974 peers without breast cancer. Both conservative (SNPs associated with overall iron status markers) and liberal (SNPs associated with the levels of at least one iron status marker) approaches were used as part of the MR analysis. For the former, we used an inverse-variance weighted (IVW) method, whereas for the latter, we used the IVW, MR-Egger regression, weighted median and simple mode methods.

RESULTS

When the conservative approach was used, iron status showed no significant association with the risk of breast cancer or any of its subtypes. However, when the liberal approach was used, transferrin levels were found to be positively associated with the risk of ER-negative breast cancer based on the simple mode method (OR for MR, 1.225; 95% CI, 1.064, 1.410; P = 0.030). Nevertheless, the levels of the other iron status markers showed no association with the risk of breast cancer or its subtypes (P > 0.05).

CONCLUSION

In our MR study, the liberal approach suggested that changes in the concentration of transferrin could increase the risk of ER-negative breast cancer, although the levels of other iron status markers had no effect on the risk of breast cancer or its subtypes. This should be verified in future studies.

Using Mendelian Randomization to Improve the Design of Randomized Trials

Randomized controlled trials and Mendelian randomization studies are two study designs that provide randomized evidence in human biological and medical research. Both exploit the power of randomization to provide unconfounded estimates of causal effect. However, randomized trials and Mendelian randomization studies have very different study designs and scientific objectives. As a result, despite sometimes being referred to as "nature's randomized trial," a Mendelian randomization study cannot be used to replace a randomized trial but instead provides complementary information. In this review, we explain the similarities and differences between randomized trials and Mendelian randomization studies, and suggest several ways that Mendelian randomization can be used to directly inform and improve the design of randomized trials illustrated with practical examples. We conclude by describing how Mendelian randomization studies can employ the principles of trial design to be framed as "naturally randomized trials" that can provide a template for the design of future randomized trials evaluating therapies directed against genetically validated targets.

Genetically Determined Higher TSH Is Associated With a Lower Risk of Diabetes Mellitus in Individuals With Low BMI

CONTEXT

Thyroid status is hypothesized to be causally related with the risk of diabetes mellitus (DM), but previous results were conflicting possibly because of a complex interaction between thyrotropin (TSH), body mass index (BMI) and DM.

OBJECTIVE

This work aims to investigate the causal association between thyroid status with DM and glucose homeostasis and to what extent this association is dependent on BMI.

METHODS

A mendelian randomization study was conducted of European-ancestry participants from the UK Biobank population. The present study involved 408 895 individuals (mean age 57.4 years [SD 8.0], 45.9% men), of whom 19 773 had DM. Genetic variants for circulatory TSH, free thyroxine (fT4) concentrations and BMI to calculate weighted genetic risk scores. The main outcome measures included self-reported DM-stratified analyses by BMI. Analyses were repeated for nonfasting glucose and glycated hemoglobin A1c (HbA1c) among individuals without DM.

RESULTS

Genetically determined TSH and fT4 levels were not associated with risk of DM in the total UK Biobank population. However, in analyses stratified on genetically determined BMI, genetically determined higher TSH, and not fT4, was associated with a lower risk for DM only in the low BMI group (odds ratio 0.91; 95% CI, 0.85-0.98 in low BMI; P value for interaction = .06). Similar results were observed for glucose and HbA1c among individuals without DM.

CONCLUSION

TSH, but not fT4, is a potential causal risk factor for DM in individuals with genetically determined low BMI highlighting potential protective effects of TSH only in low-risk populations.

Genetically predicted serum uric acid levels and the risk of coronary artery disease in patients with diabetes: A Mendelian randomization study

BACKGROUND AND AIMS

Serum uric acid (SUA) levels have been reported to be associated with an increased risk of coronary artery disease (CAD) among patients with diabetes in observational study. Whether this relationship is causal remains unclear. The current study aimed to explore the causal association between SUA and the risk of CAD in patients with diabetes.

METHODS AND RESULTS

A two-sample Mendelian randomization (MR) approach was employed to evaluate the causal effect of SUA on the risk of CAD in patients with diabetes. A total of 28 single nucleotide polymorphisms (SNPs) related to SUA were identified as instruments. Genetic association with CAD were obtained from a recently published genome-wide association study (GWAS) of 15,666 patients with diabetes (3968 CAD cases and 11,696 controls). The fixed-effects inverse variance-weighted method was employed to estimate the causal effect for the primary analysis, and other robust methods were employed for sensitivity analyses. In addition, the whole analyses were repeated using 9 non-pleiotropic SNPs. Genetic determined SUA levels were not significantly associated with the risk of CAD in patients with diabetes in the primary analysis (odds ratio = 1.13, 95% confidence interval: 0.98-1.16, P = 0.09). Consistent results were observed in the sensitivity analyses using various robust methods. In addition, this finding was confirmed by the repeated analyses using 9 non-pleiotropic SNPs.

CONCLUSIONS

This two-sample MR study does not support a causal effect of genetically predicted SUA levels on the risk of CAD in patients with diabetes.

Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development

Drug development in cardiovascular disease is stagnating, with lack of efficacy and adverse effects being barriers to innovation. Human genetics can provide compelling evidence of causation through approaches such as Mendelian randomization, with genetic support for causation increasing the probability of a clinical trial succeeding. Mendelian randomization applied to quantitative traits can identify risk factors for disease that are both causal and amenable to therapeutic modification. However, important differences exist between genetic investigations of a biomarker (such as HDL cholesterol) and a drug target aimed at modifying the same biomarker of interest (such as cholesteryl ester transfer protein), with implications for the methodology, interpretation and application of Mendelian randomization to drug development. Differences include the comparative nature of the genetic architecture - that is, biomarkers are typically polygenic, whereas protein drug targets are influenced by either cis-acting or trans-acting genetic variants - and the potential for drug targets to show disease associations that might differ from those of the biomarker that they are intended to modify (target-mediated pleiotropy). In this Review, we compare and contrast the use of Mendelian randomization to evaluate potential drug targets versus quantitative traits. We explain how genetic epidemiological studies can be used to assess the aetiological roles of biomarkers in disease and to prioritize drug targets, including designing their evaluation in clinical trials.

Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments

Over a decade of genome-wide association studies (GWAS) have led to the finding of extreme polygenicity of complex traits. The phenomenon that "all genes affect every complex trait" complicates Mendelian Randomization (MR) studies, where natural genetic variations are used as instruments to infer the causal effect of heritable risk factors. We reexamine the assumptions of existing MR methods and show how they need to be clarified to allow for pervasive horizontal pleiotropy and heterogeneous effect sizes. We propose a comprehensive framework GRAPPLE to analyze the causal effect of target risk factors with heterogeneous genetic instruments and identify possible pleiotropic patterns from data. By using GWAS summary statistics, GRAPPLE can efficiently use both strong and weak genetic instruments, detect the existence of multiple pleiotropic pathways, determine the causal direction and perform multivariable MR to adjust for confounding risk factors. With GRAPPLE, we analyze the effect of blood lipids, body mass index, and systolic blood pressure on 25 disease outcomes, gaining new information on their causal relationships and potential pleiotropic pathways involved.

Metabolic profiling of angiopoietin-like protein 3 and 4 inhibition: a drug-target Mendelian randomization analysis

Aims 

Angiopoietin-like protein 3 (ANGPTL3) and 4 (ANGPTL4) inhibit lipoprotein lipase (LPL) and represent emerging drug targets to lower circulating triglycerides and reduce cardiovascular risk. To investigate the molecular effects of genetic mimicry of ANGPTL3 and ANGPTL4 inhibition and compare them to the effects of genetic mimicry of LPL enhancement.

Methods and results 

Associations of genetic variants in ANGPTL3 (rs11207977-T), ANGPTL4 (rs116843064-A), and LPL (rs115849089-A) with an extensive serum lipid and metabolite profile (208 measures) were characterized in six cohorts of up to 61 240 participants. Genetic associations with anthropometric measures, glucose-insulin metabolism, blood pressure, markers of kidney function, and cardiometabolic endpoints via genome-wide summary data were also explored. ANGPTL4 rs116843064-A and LPL rs115849089-A displayed a strikingly similar pattern of associations across the lipoprotein and lipid measures. However, the corresponding associations with ANGPTL3 rs11207977-T differed, including those for low-density lipoprotein and high-density lipoprotein particle concentrations and compositions. All three genotypes associated with lower concentrations of an inflammatory biomarker glycoprotein acetyls and genetic mimicry of ANGPTL3 inhibition and LPL enhancement were also associated with lower C-reactive protein. Genetic mimicry of ANGPTL4 inhibition and LPL enhancement were associated with a lower waist-to-hip ratio, improved insulin-glucose metabolism, and lower risk of coronary heart disease and type 2 diabetes, whilst genetic mimicry of ANGPTL3 was associated with improved kidney function.

Conclusions 

Genetic mimicry of ANGPTL4 inhibition and LPL enhancement have very similar systemic metabolic effects, whereas genetic mimicry of ANGPTL3 inhibition showed differing metabolic effects, suggesting potential involvement of pathways independent of LPL. Genetic mimicry of ANGPTL4 inhibition and LPL enhancement were associated with a lower risk of coronary heart disease and type 2 diabetes. These findings reinforce evidence that enhancing LPL activity (either directly or via upstream effects) through pharmacological approaches is likely to yield benefits to human health.

SR-B1, a Key Receptor Involved in the Progression of Cardiovascular Disease: A Perspective from Mice and Human Genetic Studies

High plasma level of low-density lipoprotein (LDL) is the main driver of the initiation and progression of cardiovascular disease (CVD). Nevertheless, high-density lipoprotein (HDL) is considered an anti-atherogenic lipoprotein due to its role in reverse cholesterol transport and its ability to receive cholesterol that effluxes from macrophages in the artery wall. The scavenger receptor B class type 1 (SR-B1) was identified as the high-affinity HDL receptor, which facilitates the selective uptake of cholesterol ester (CE) into the liver via HDL and is also implicated in the plasma clearance of LDL, very low-density lipoprotein (VLDL) and lipoprotein(a) (Lp(a)). Thus, SR-B1 is a multifunctional receptor that plays a main role in the metabolism of different lipoproteins. The aim of this review is to highlight the association between SR-B1 and CVD risk through mice and human genetic studies.

Appraising the Causal Association of Plasma Homocysteine Levels With Atrial Fibrillation Risk: A Two-Sample Mendelian Randomization Study

Background

Although several observational studies have suggested an association of elevated plasma homocysteine (Hcy) levels with increased risk of atrial fibrillation (AF), it remains unclear whether this association reflects causality. In this study, we aimed to investigate the causal association of plasma Hcy levels with AF risk.

Methods

A two-sample Mendelian randomization (MR) study was designed to investigate the causal association of Hcy with AF. Summary data on association of single nucleotide polymorphisms (SNPs) with Hcy were extracted from the hitherto largest genome-wide association study (GWAS) with up to 44,147 individuals, and statistics data on association of SNPs with AF were obtained from another recently published GWAS with up to 1,030,836 individuals. SNPs were selected at a genome-wide significance threshold (p < 5 × 10^–8). Fixed-effect inverse variance weighting (IVW) method was used to calculate the causal estimate. Other statistical methods and leave-one-out analysis were applied in the follow-up sensitivity analyses. MR-Egger intercept test was conducted to detect the potential directional pleiotropy.

Results

In total, nine SNPs were identified as valid instrumental variables in our two-sample MR analysis. Fixed-effect IVW analysis indicated no evidence of causal association of genetically predicted Hcy with AF. The odds ratio (OR) and 95% confidence interval (CI) of AF per standard deviation (SD) increase in Hcy were 1.077 (0.993, 1.168), p = 0.075. Similar results were observed in the sensitivity analyses. MR-Egger intercept test suggested no evidence of potential horizonal pleiotropy.

Conclusions

This two-sample MR analysis found no evidence to support causal association of Hcy with AF.

Rheumatoid arthritis and osteoporosis: a bi-directional Mendelian randomization study

Many observation studies have demonstrated a close relationship between rheumatoid arthritis (RA) and osteoporosis (OP). However, the causal genetic correlation between RA and OP remains unclear. In this study, we performed bi-directional Mendelian randomization (MR) analyses to explore causal inference between these two traits. The instrumental variables for RA were selected from a large-scale genome-wide association study (GWAS) (1,523 cases and 461,487 controls). Bone mineral density (BMD) at five different sites (heel (n=265,627), forearm (FA) (n=8,143), femoral neck (FN) (n=32,735), lumbar spine (LS) (n=28,498), and total body (n=28,498)) were used as phenotypes for OP. The inverse variance weighted (IVW) method did not detect any causal effect of BMDs on RA except heel BMD (beta = -7.57 × 10-4, p = 0.02). However, other methods (MR-Egger, weighted median, weighted mode, MR-PRESSO, and MR-RAPS) showed no causal association between heel BMD and RA. Likewise, we did not find a causal effect of RA on BMD at any sites. In conclusion, we found no evidence that RA is causally associated with OP/BMD, or vice versa. We suggested that the associations found in previous observational studies between RA and OP/BMD are possibly related to secondary effects such as antirheumatic treatment and reduced physical activity.

Advances in Genomics Research of Blood Pressure Responses to Dietary Sodium and Potassium Intakes

More than half of US adults have hypertension by 40 years of age and a subsequent increase in atherosclerotic cardiovascular disease risk. Dietary sodium and potassium are intricately linked to the pathophysiology of hypertension. However, blood pressure responses to dietary sodium and potassium, phenomena known as salt and potassium sensitivity of blood pressure, respectively, are heterogenous and normally distributed in the general population. Like blood pressure, salt and potassium sensitivity are complex phenotypes, and previous research has shown that up to 75% of individuals experience a blood pressure change in response to such dietary minerals. Previous research has also implicated both high salt sensitivity and low salt sensitivity (or salt resistance) of blood pressure to an increased risk of hypertension and potentially atherosclerotic cardiovascular disease risk. Given the clinical challenges required to accurately measure the sodium and potassium response phenotypes, genomic characterization of these traits has become of interest for hypertension prevention initiatives on both the individual and population levels. Here, we review advances in human genomics research of blood pressure responses to dietary sodium and potassium by focusing on 3 main areas, including the phenotypic characterization of salt sensitivity and resistance, clinical challenges in diagnosing such phenotypes, and the genomic mechanisms that may help to explain salt and potassium sensitivity and resistance. Through this process, we hope to further underline the value of leveraging genomics and broader multiomics for characterizing the blood pressure response to sodium and potassium to improve precision in lifestyle approaches for primordial and primary atherosclerotic cardiovascular disease prevention.

Plasma HDL cholesterol and risk of dementia - observational and genetic studies

AIMS

The association of plasma high-density lipoprotein (HDL) cholesterol with risk of dementia is unclear. We therefore tested the hypothesis that high levels of plasma HDL cholesterol are associated with increased risk of dementia and whether a potential association is of a causal nature.

METHODS AND RESULTS

In two prospective population-based studies, the Copenhagen General Population Study and the Copenhagen City Heart Study (N = 111,984 individuals), we first tested whether high plasma HDL cholesterol is associated with increased risk of any dementia and its subtypes. These analyses in men and women separately were adjusted multifactorially for other risk factors including apolipoprotein E (APOE) genotype. Second, taking advantage of two-sample Mendelian randomization, we tested whether genetically elevated HDL cholesterol was causally associated with Alzheimer's disease using publicly available consortia data on 643,836 individuals. Observationally, multifactorially adjusted Cox regression restricted cubic spline models showed that both men and women with extreme high HDL cholesterol concentrations had increased risk of any dementia and of Alzheimer's disease. Men in the 96th-99th and 100th versus the 41st-60th percentiles of HDL cholesterol had multifactorially including APOE genotype adjusted hazard ratios of 1.66 (95% confidence interval 1.30-2.11) and 2.00 (1.35-2.98) for any dementia and 1.59 (1.16-2.20) and 1.87 (1.11-3.16) for Alzheimer's disease. Corresponding estimates for women were 0.94 (0.74-1.18) and 1.45 (1.03-2.05) for any dementia and 0.94 (0.70-1.26) and 1.69 (1.13-2.53) for Alzheimer's disease. Genetically, the two-sample Mendelian randomization odds ratio for Alzheimer's disease per 1 standard deviation increase in HDL cholesterol was 0.92 (0.74-1.10) in the IGAP2019 consortium and 0.98 (0.95-1.00) in the ADSP/IGAP/PGC-ALZ/UKB consortium. Similar estimates were observed in sex stratified analyses.

CONCLUSION

High plasma HDL cholesterol was observationally associated with increased risk of any dementia and Alzheimer's disease, suggesting that HDL cholesterol can be used as an easily accessible plasma biomarker for individual risk assessment.

TRANSLATIONAL PERSPECTIVE

The present study identifies very high plasma HDL cholesterol levels as an independent risk factor for any dementia and Alzheimer's disease in both men and women of the general population. Two-sample Mendelian randomization studies do not support that this association is of a causal nature, indicating HDL cholesterol as a non-causal risk factor for Alzheimer's disease. Our findings suggest that very high HDL cholesterol can be used as an easily accessible plasma biomarker to evaluate increased risk of dementia and potential identification of high-risk individuals for early targeted prevention - an area highly recommended to direct attention towards.

Causal effects of gallstone disease on risk of gastrointestinal cancer in Chinese

BACKGROUND

Gallstone disease (GSD) is associated with a higher risk of gastrointestinal (GI) cancer. However, it is unclear whether the associations are causal.

METHODS

The prospective China Kadoorie Biobank (CKB) recorded 17,598 cases of GI cancer among 510,137 participants without cancer at baseline during 10 years of follow-up. Cox regression was used to estimate hazard ratios (HRs) for specific cancer by GSD status and duration. Mendelian randomisation was conducted to assess the genetic associations of GSD with specific cancer.

RESULTS

Overall 6% of participants had symptomatic GSD at baseline. Compared with those without GSD, individuals with symptomatic GSD had adjusted HRs of 1.13 (1.01-1.29) for colorectal, 2.01 (1.78-2.26) for liver, 3.70 (2.88-4.87) for gallbladder, 2.31 (1.78-3.07) for biliary tract, and 1.38 (1.18-1.74) for pancreatic cancer. Compared with participants without GSD, the risks of colorectal, liver, gallbladder, biliary tract, and pancreatic cancer were highest during 0 to <5 years following disease diagnosis. There was evidence of genetic associations of GSD with these cancers, with odds ratios per 1-SD genetic score of 1.08 (1.05-1.11) for colorectal, 1.22 (1.19-1.25) for liver, 1.56 (1.49-1.64) for gallbladder, 1.39 (1.31-1.46) for biliary tract, and 1.16 (1.10-1.22) for pancreatic cancer. When meta-analysing the genetic estimates in CKB and UK Biobank, there was evidence of causal associations of GSD with colon cancer, gallbladder and biliary tract cancer (GBTC), and total GI cancer (RR per 1-SD: 1.05 [0.99-1.11], 2.00 [1.91-2.09], and 1.09 [1.05-1.13]).

CONCLUSIONS

GSD was associated with higher risks of several GI cancers, warranting future studies on the underlying mechanisms.

Repurposing antihypertensive drugs for the prevention of Alzheimer's disease: a Mendelian randomization study

Background

Evidence concerning the potential repurposing of antihypertensives for Alzheimer’s disease prevention is inconclusive. We used Mendelian randomization, which can be more robust to confounding by indication and patient characteristics, to investigate the effects of lowering systolic blood pressure, via the protein targets of different antihypertensive drug classes, on Alzheimer’s disease.

Methods

We used summary statistics from genome-wide association studies of systolic blood pressure and Alzheimer’s disease in a two-sample Mendelian randomization analysis. We identified single-nucleotide polymorphisms (SNPs) that mimic the action of antihypertensive protein targets and estimated the effect of lowering systolic blood pressure on Alzheimer’s disease in three ways: (i) combining the protein targets of antihypertensive drug classes, (ii) combining all protein targets and (iii) without consideration of the protein targets.

Results

There was limited evidence that lowering systolic blood pressure, via the protein targets of antihypertensive drug classes, affected Alzheimer’s disease risk. For example, the protein targets of calcium channel blockers had an odds ratio (OR) per 10 mmHg lower systolic blood pressure of 1.53 [95% confidence interval (CI): 0.94 to 2.49; p = 0.09; SNPs = 17]. We also found limited evidence for an effect when combining all protein targets (OR per 10 mmHg lower systolic blood pressure: 1.14; 95% CI: 0.83 to 1.56; p = 0.41; SNPs = 59) and without consideration of the protein targets (OR per 10 mmHg lower systolic blood pressure: 1.04; 95% CI: 0.95 to 1.13; p = 0.45; SNPs = 153).

Conclusions

Mendelian randomization suggests that lowering systolic blood pressure via the protein targets of antihypertensive drugs is unlikely to affect the risk of developing Alzheimer’s disease. Consequently, if specific antihypertensive drug classes do affect the risk of Alzheimer’s disease, they may not do so via systolic blood pressure.

HDL Cholesterol and Non-Cardiovascular Disease: A Narrative Review

High density lipoprotein (HDL) cholesterol has traditionally been considered the “good cholesterol”, and most of the research regarding HDL cholesterol has for decades revolved around the possible role of HDL in atherosclerosis and its therapeutic potential within atherosclerotic cardiovascular disease. Randomized trials aiming at increasing HDL cholesterol have, however, failed and left questions to what role HDL cholesterol plays in human health and disease. Recent observational studies involving non-cardiovascular diseases have shown that high levels of HDL cholesterol are not necessarily associated with beneficial outcomes as observed for age-related macular degeneration, type II diabetes, dementia, infection, and mortality. In this narrative review, we discuss these interesting associations between HDL cholesterol and non-cardiovascular diseases, covering observational studies, human genetics, and plausible mechanisms.

A Mendelian randomization study of the role of lipoprotein subfractions in coronary artery disease

Recent genetic data can offer important insights into the roles of lipoprotein subfractions and particle sizes in preventing coronary artery disease (CAD), as previous observational studies have often reported conflicting results. We used the LD score regression to estimate the genetic correlation of 77 subfraction traits with traditional lipid profile and identified 27 traits that may represent distinct genetic mechanisms. We then used Mendelian randomization (MR) to estimate the causal effect of these traits on the risk of CAD. In univariable MR, the concentration and content of medium high-density lipoprotein (HDL) particles showed a protective effect against CAD. The effect was not attenuated in multivariable analyses. Multivariable MR analyses also found that small HDL particles and smaller mean HDL particle diameter may have a protective effect. We identified four genetic markers for HDL particle size and CAD. Further investigations are needed to fully understand the role of HDL particle size.

Shared Genetic Background Between Cerebrospinal Fluid Biomarkers and Risk for Alzheimer's Disease: A Two-Sample Mendelian Randomization Study

BACKGROUND

Whether the epidemiological association of amyloid-β (Aβ) and tau pathology in late-onset Alzheimer's disease (LOAD) is causal remains unclear.

OBJECTIVE

We aimed to investigate the shared genetic background between the cerebrospinal fluid (CSF) biomarkers for Aβ and tau pathology and the risk of LOAD.

METHODS

We conducted a two-sample Mendelian randomization (MR) analysis. We used summary statistics of genome-wide association studies for CSF biomarkers (Aβ1-42 [Aβ], phosphorylated tau181 [p-tau], and total tau [t-tau]) in 3,146 individuals and for LOAD in 21,982 cases and 41,944 controls. We tested the association between changes in the genetically predicted CSF biomarkers and LOAD risk.

RESULTS

We found a decrease in LOAD risk per one-standard-deviation (SD) increase in the genetically predicted CSF Aβ (odds ratio [OR], 2.87×10-3 for AD; 95%confidence interval [CI], 1.54×10-4-0.05; p = 8.91×10-5). Conversely, we observed an increase in LOAD risk per one-SD increase in the genetically predicted CSF p-tau (OR, 19.46; 95%CI, 1.50-2.52×102; p = 0.02) and t-tau (OR, 33.80; 95%CI, 1.57-7.29×102; p = 0.02). However, only the association between p-tau and the risk for LOAD remained significant after the exclusion of the APOE variant (rs769449).

CONCLUSION

We found the causal association between CSF biomarkers and the risk for LOAD. Our results suggest that the etiology of LOAD involves multiple biological processes, including the pathways of Aβ and tau proteins. Further MR studies using large-scale data of multiple candidate biomarkers are needed to elucidate the pathophysiology of LOAD.

Rheumatoid arthritis and risk of lung cancer: Meta-analysis and Mendelian randomization study

OBJECTIVE

Observational studies suggest that rheumatoid arthritis (RA) may be associated with lung cancer (LC) risk, while the evidence is inconsistent. We conducted a meta-analysis and a Mendelian randomization study to investigate the association and causality between RA and the LC risk.

METHODS

We conducted a systematic search of cohort studies and performed a meta-analysis (PROSPERO ID CRD42020159082) to calculate the relative risks (RRs) and their 95% confidence intervals (95%CIs). Subgroup analyses based on sex and initiation year of follow-up were carried out. E-values of each study were calculated to evaluate if existing studies were sensitive to unmeasured confounding. Furthermore, we investigated the correlation between genetically predisposed RA and LC risk using summary statistics from the International Lung Cancer Consortium (11,348 cases and 15,861 controls) and 90 RA-related single nucleotide polymorphisms from European and East Asian descent as instrumental variables. A two-sample Mendelian randomization (MR) analysis was performed to detect the findings based on LC and histological subtypes. Sensitivity analyses were performed to test the robustness of our findings.

RESULTS

In the meta-analysis of 11 cohort studies involving 183,888 patients, an increased risk of LC was observed among RA patients (RR = 1.44, 95%CI = 1.31-1.57). Subgroup analyses suggested that male patients have a relatively higher LC risk than female patients, and an increased incidence of LC in RA patients was found from 1950 to 2010. Conversely, in the MR analysis, we found that genetically predisposed RA was associated with a decreased risk of LC overall, while neither causally associated with the risk of lung adenocarcinoma nor squamous cell lung cancer. Nevertheless, genetically predisposed RA was associated with a decreased LC risk among the East Asian population, but not in Europeans. These results were robust against extensive sensitivity analyses.

CONCLUSION

Our meta-analysis suggested that although RA was associated with a relatively higher LC risk, the causal relationship between genetically predisposed RA and LC risk was not supported by the MR study. Further studies are warranted to elucidate the possible association between RA and the risk of LC, as well as its underlying mechanisms.

Polygenic scores for dyslipidemia: the emerging genomic model of plasma lipoprotein trait inheritance

PURPOSE OF REVIEW

Contemporary polygenic scores, which summarize the cumulative contribution of millions of common single-nucleotide variants to a phenotypic trait, can have effects comparable to monogenic mutations. This review focuses on the emerging use of 'genome-wide' polygenic scores for plasma lipoproteins to define the etiology of clinical dyslipidemia, modify the severity of monogenic disease, and inform therapeutic options.

RECENT FINDINGS

Polygenic scores for low-density lipoprotein cholesterol (LDL-C), triglycerides, and high-density lipoprotein cholesterol are associated with severe hypercholesterolemia, hypertriglyceridemia, or hypoalphalipoproteinemia, respectively. These polygenic scores for LDL-C or triglycerides associate with risk of incident coronary artery disease (CAD) independent of polygenic scores designed specifically for CAD and may identify individuals that benefit most from lipid-lowering medication. Additionally, the severity of hypercholesterolemia and CAD associated with familial hypercholesterolemia-a common monogenic disorder-is modified by these polygenic factors. The current focus of polygenic scores for dyslipidemia is to design predictive polygenic scores for diverse populations and determining how these polygenic scores could be implemented and standardized for use in the clinic.

SUMMARY

Polygenic scores have shown early promise for the management of dyslipidemias, but several challenges need to be addressed before widespread clinical implementation to ensure that potential benefits are robust and reproducible, equitable, and cost-effective.

Diabetes Mellitus, Glycemic Traits, and Cerebrovascular Disease: A Mendelian Randomization Study

OBJECTIVE

We employed Mendelian randomization to explore the effects of genetic predisposition to type 2 diabetes (T2D), hyperglycemia, insulin resistance, and pancreatic β-cell dysfunction on risk of stroke subtypes and related cerebrovascular phenotypes.

METHODS

We selected instruments for genetic predisposition to T2D (74,124 cases, 824,006 controls), HbA1c levels (n = 421,923), fasting glucose levels (n = 133,010), insulin resistance (n = 108,557), and β-cell dysfunction (n = 16,378) based on published genome-wide association studies. Applying 2-sample Mendelian randomization, we examined associations with ischemic stroke (60,341 cases, 454,450 controls), intracerebral hemorrhage (1,545 cases, 1,481 controls), and ischemic stroke subtypes (large artery, cardioembolic, small vessel stroke), as well as with related phenotypes (carotid atherosclerosis, imaging markers of cerebral white matter integrity, and brain atrophy).

RESULTS

Genetic predisposition to T2D and higher HbA1c levels were associated with higher risk of any ischemic stroke, large artery stroke, and small vessel stroke. Similar associations were also noted for carotid atherosclerotic plaque, fractional anisotropy, a white matter disease marker, and markers of brain atrophy. We further found associations of genetic predisposition to insulin resistance with large artery and small vessel stroke, whereas predisposition to β-cell dysfunction was associated with small vessel stroke, intracerebral hemorrhage, lower gray matter volume, and total brain volume.

CONCLUSIONS

This study supports causal effects of T2D and hyperglycemia on large artery and small vessel stroke. We show associations of genetically predicted insulin resistance and β-cell dysfunction with large artery and small vessel stroke that might have implications for antidiabetic treatments targeting these mechanisms.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that genetic predisposition to T2D and higher HbA1c levels are associated with a higher risk of large artery and small vessel ischemic stroke.

Phenome-wide investigation of the causal associations between childhood BMI and adult trait outcomes: a two-sample Mendelian randomization study

Background

Childhood obesity is reported to be associated with the risk of many diseases in adulthood. However, observational studies cannot fully account for confounding factors. We aimed to systematically assess the causal associations between childhood body mass index (BMI) and various adult traits/diseases using two-sample Mendelian randomization (MR).

Methods

After data filtering, 263 adult traits genetically correlated with childhood BMI (P < 0.05) were subjected to MR analyses. Inverse-variance weighted, MR-Egger, weighted median, and weighted mode methods were used to estimate the causal effects. Multivariable MR analysis was performed to test whether the effects of childhood BMI on adult traits are independent from adult BMI.

Results

We identified potential causal effects of childhood obesity on 60 adult traits (27 disease-related traits, 27 lifestyle factors, and 6 other traits). Higher childhood BMI was associated with a reduced overall health rating (β = − 0.10, 95% CI − 0.13 to − 0.07, P = 6.26 × 10⁻¹¹). Specifically, higher childhood BMI was associated with increased odds of coronary artery disease (OR = 1.09, 95% CI 1.06 to 1.11, P = 4.28 × 10⁻¹¹), essential hypertension (OR = 1.12, 95% CI 1.08 to 1.16, P = 1.27 × 10⁻¹¹), type 2 diabetes (OR = 1.36, 95% CI 1.30 to 1.43, P = 1.57 × 10⁻³⁴), and arthrosis (OR = 1.09, 95% CI 1.06 to 1.12, P = 8.80 × 10⁻⁹). However, after accounting for adult BMI, the detrimental effects of childhood BMI on disease-related traits were no longer present (P > 0.05). For dietary habits, different from conventional understanding, we found that higher childhood BMI was associated with low calorie density food intake. However, this association might be specific to the UK Biobank population.

Conclusions

In summary, we provided a phenome-wide view of the effects of childhood BMI on adult traits. Multivariable MR analysis suggested that the associations between childhood BMI and increased risks of diseases in adulthood are likely attributed to individuals remaining obese in later life. Therefore, ensuring that childhood obesity does not persist into later life might be useful for reducing the detrimental effects of childhood obesity on adult diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00865-3.

Hypertension and Atrial Fibrillation: A Study on Epidemiology and Mendelian Randomization Causality

Introduction: Hypertension (HT) and atrial fibrillation (AF) often coexist. However, the causality between these two conditions remains to be determined.

Methods: We used individual participant data from the Atherosclerosis Risk in Communities (ARIC) prospective cohort with 9,474 participants. HT was ascertained at visit 1 (1987–1989), and incident AF was identified by ECGs conducted during study examinations at each visit, hospital discharge codes, and death certificates. We used the Kaplan–Meier estimate to compute the cumulative incidence of AF by the HT subgroup. Then we used Cox hazard regression model to assess the association between HT and incident AF. The causality between genetically determined HT and AF was analyzed by the two-sample Mendelian randomization (MR) based on publicly summarized genome-wide association studies (GWASs) data.

Results: A total of 1,414 cases (14.9%) of AF were identified during the follow-up period (median 24.1 years). After adjusting for all covariates, the hazard ratio between the participants with HT and incident AF was 1.50 [95% confidence interval (CI) 1.29–1.73]. In the HT → AF MR analysis, we detected a causal correlation between HT and AF (OR: 1.90, 95% CI 1.18–3.04, P = 0.01) with no evidence of heterogeneity from single-nucleotide polymorphisms. Besides, the genetically determined SBP and DBP (10 mmHg) were consistently associated with a higher risk of AF.

Conclusions: In the ARIC study, the incident AF increased by 50% in patients with HT. In the MR analysis, our results supported causal inference between HT and AF.

Midlife vascular risk factors and risk of incident dementia: Longitudinal cohort and Mendelian randomization analyses in the UK Biobank

INTRODUCTION

Midlife clustering of vascular risk factors has been associated with late-life dementia, but causal effects of individual biological and lifestyle factors remain largely unknown.

METHODS

Among 229,976 individuals (mean follow-up 9 years), we explored whether midlife cardiovascular health measured by Life's Simple 7 (LS7) is associated with incident all-cause dementia and whether the individual components of the score are causally associated with dementia.

RESULTS

Adherence to the biological metrics of LS7 (blood pressure, cholesterol, glycemic status) was associated with lower incident dementia risk (hazard ratio = 0.93 per 1-point increase, 95% confidence interval [CI; 0.89-0.96]). In contrast, there was no association between the composite LS7 score and the lifestyle subscore (smoking, body mass index, diet, physical activity) and incident dementia. In Mendelian randomization analyses, genetically elevated blood pressure was associated with higher risk of dementia (odds ratio = 1.31 per one-standard deviation increase, 95% CI [1.05-1.60]).

DISCUSSION

These findings underscore the importance of blood pressure control in midlife to mitigate dementia risk.

Genetically determined tobacco and alcohol use and risk of atrial fibrillation

BACKGROUND

The causality between the use of alcohol and cigarettes and atrial fibrillation (AF) remains controversial. We conducted a Mendelian randomization (MR) study to evaluate the association of genetic variants related to tobacco and alcohol use with AF.

METHODS

Single nucleotide polymorphisms (SNPs) related to smoking initiation (N = 374), age at initiation of regular smoking (N = 10), cigarettes per day (N = 55), and smoking cessation (N = 24) were derived from a genome-wide association studies (GWAS) of tobacco use (N = 1.2 million individuals). SNPs related to heavy alcohol use (N = 6) were derived from a GWAS of UK biobank (N = 125,249 individuals). The genetically matching instrumented variables were obtained from the GWAS of AF (N = 588,190 individuals). The estimates between tobacco and alcohol use and AF were combined by inverse-variance weighted (IVW), simple median, weighted median, MR-robust adjusted profile score method, MR-PRESSO, and multivariable MR.

RESULTS

A total of 65,446 AF patients and 522,744 referents were included. In the IVW analysis, the odds ratio per one-unit increase of smoking initiation was 1.11 (95% CI, 1.06-1.16; P = 3.35 × 10-6) for AF. Genetically predicted age at initiation of regular smoking, cigarettes per day and smoking cessation were not associated with AF. The IVW estimate showed that heavy alcohol consumption increased AF risk (OR, 1.11; 95% CI, 1.04-1.18; P = 0.001). The results were consistent in complementary analyses and multivariable MR.

CONCLUSION

Our MR study indicated that regular smoking was associated with increased risk of AF, no matter the age at initiation of regular smoking, or the number of cigarettes smoked per day. Genetically predicted heavy alcohol consumption increased the risk of AF.

Associations of Adiposity, Circulating Protein Biomarkers, and Risk of Major Vascular Diseases

Question

Is adiposity associated with differences in circulating protein concentrations, and might these proteins potentially explain the associations of adiposity with risk of cardiovascular disease?

Findings

In a cohort study of 628 individuals in China, there was evidence of genetic associations of body mass index with protein biomarkers consistent with observational associations, particularly for interleukin-6, interleukin-18, monocyte chemoattractant protein–1, monocyte chemotactic protein–3, TNF-related apoptosis-inducing ligand, and hepatocyte growth factor. Several of these proteins were observationally associated with risk of incident cardiovascular disease.

Meaning

In this study of Chinese adults, adiposity was associated both cross-sectionally and through genetic analyses with a range of protein biomarkers, which might partly explain the association between adiposity and cardiovascular disease.

Importance

Obesity is associated with a higher risk of cardiovascular disease (CVD), but little is known about the role that circulating protein biomarkers play in this association.

Objective

To examine the observational and genetic associations of adiposity with circulating protein biomarkers and the observational associations of proteins with incident CVD.

Design, Setting, and Participants

This subcohort study included 628 participants from the prospective China Kadoorie Biobank who did not have a history of cancer at baseline. The Olink platform measured 92 protein markers in baseline plasma samples. Data were collected from June 2004 to January 2016 and analyzed from January 2019 to June 2020.

Exposures

Measured body mass index (BMI) obtained during the baseline survey and genetically instrumented BMI derived using 571 externally weighted single-nucleotide variants.

Main Outcomes and Measures

Cross-sectional associations of adiposity with biomarkers were examined using linear regression. Associations of biomarkers with CVD risk were assessed using Cox regression among those without prior cancer or CVD at baseline. Mendelian randomization was conducted to derive genetically estimated associations of BMI with biomarkers.

Findings

In observational analyses of 628 individuals (mean [SD] age, 52.2 [10.5] years; 385 women [61.3%]), BMI (mean [SD], 23.9 [3.6]) was positively associated with 27 proteins (per 1-SD higher BMI; eg, interleukin-6: 0.21 [95% CI, 0.12-0.29] SD; interleukin-18: 0.13 [95% CI, 0.05-0.21] SD; monocyte chemoattractant protein–1: 0.12 [95% CI, 0.04-0.20] SD; hepatocyte growth factor: 0.31 [95% CI, 0.24-0.39] SD), and inversely with 3 proteins (Fas ligand: −0.11 [95% CI, −0.19 to −0.03] SD; TNF-related weak inducer of apoptosis, −0.14 [95% CI, −0.23 to −0.06] SD; and carbonic anhydrase 9: (−0.14 [95% CI, −0.22 to −0.05] SD), with similar associations identified for other adiposity traits (eg, waist circumference [r = 0.96]). In mendelian randomization, the associations of genetically elevated BMI with specific proteins were directionally consistent with the observational associations. In meta-analyses of genetically elevated BMI with 8 proteins, combining present estimates with previous studies, the most robust associations were shown for interleukin-6 (per 1-SD higher BMI; 0.21 [95% CI, 0.13-0.29] SD), interleukin-18 (0.16 [95% CI, 0.06-0.26] SD), monocyte chemoattractant protein–1 (0.21 [95% CI, 0.11-0.30] SD), monocyte chemotactic protein–3 (0.12 [95% CI, 0.03-0.21] SD), TNF-related apoptosis-inducing ligand (0.23 [95% CI, 0.13-0.32] SD), and hepatocyte growth factor (0.14 [95% CI, 0.06-0.22] SD). Of the 30 BMI-associated biomarkers, 10 (including interleukin-6, interleukin-18, and hepatocyte growth factor) were nominally associated with incident CVD.

Conclusions and Relevance

Mendelian randomization shows adiposity to be associated with a range of protein biomarkers, with some biomarkers also showing association with CVD risk. Future studies are warranted to validate these findings and assess whether proteins may be mediators between adiposity and CVD.

Revealing the role of the human blood plasma proteome in obesity using genetic drivers

Blood circulating proteins are confounded readouts of the biological processes that occur in different tissues and organs. Many proteins have been linked to complex disorders and are also under substantial genetic control. Here, we investigate the associations between over 1000 blood circulating proteins and body mass index (BMI) in three studies including over 4600 participants. We show that BMI is associated with widespread changes in the plasma proteome. We observe 152 replicated protein associations with BMI. 24 proteins also associate with a genome-wide polygenic score (GPS) for BMI. These proteins are involved in lipid metabolism and inflammatory pathways impacting clinically relevant pathways of adiposity. Mendelian randomization suggests a bi-directional causal relationship of BMI with LEPR/LEP, IGFBP1, and WFIKKN2, a protein-to-BMI relationship for AGER, DPT, and CTSA, and a BMI-to-protein relationship for another 21 proteins. Combined with animal model and tissue-specific gene expression data, our findings suggest potential therapeutic targets further elucidating the role of these proteins in obesity associated pathologies.

Mendelian randomization for studying the effects of perturbing drug targets

Drugs whose targets have genetic evidence to support efficacy and safety are more likely to be approved after clinical development. In this paper, we provide an overview of how natural sequence variation in the genes that encode drug targets can be used in Mendelian randomization analyses to offer insight into mechanism-based efficacy and adverse effects. Large databases of summary level genetic association data are increasingly available and can be leveraged to identify and validate variants that serve as proxies for drug target perturbation. As with all empirical research, Mendelian randomization has limitations including genetic confounding, its consideration of lifelong effects, and issues related to heterogeneity across different tissues and populations. When appropriately applied, Mendelian randomization provides a useful empirical framework for using population level data to improve the success rates of the drug development pipeline.

Genetically determined blood pressure, antihypertensive medications, and risk of Alzheimer's disease: a Mendelian randomization study

BACKGROUND

Observational studies suggest that the use of antihypertensive medications (AHMs) is associated with a reduced risk of Alzheimer's disease (AD); however, these findings may be biased by confounding and reverse causality. We aimed to explore the effects of blood pressure (BP) and lowering systolic BP (SBP) via the protein targets of different AHMs on AD through a two-sample Mendelian randomization (MR) approach.

METHODS

Genetic proxies from genome-wide association studies of BP traits and BP-lowering variants in genes encoding AHM targets were extracted. Estimates were calculated by inverse-variance weighted method as the main model. MR Egger regression and leave-one-out analysis were performed to identify potential violations.

RESULTS

There was limited evidence that genetically predicted SBP/diastolic BP level affected AD risk based on 400/398 single nucleotide polymorphisms (SNPs), respectively (all P > 0.05). Suitable genetic variants for β-blockers (1 SNP), angiotensin receptor blockers (1 SNP), calcium channel blockers (CCBs, 45 SNPs), and thiazide diuretics (5 SNPs) were identified. Genetic proxies for CCB [odds ratio (OR) = 0.959, 95% confidence interval (CI) = 0.941-0.977, P = 3.92 × 10-6] and overall use of AHMs (OR = 0.961, 95% CI = 0.944-0.978, P = 5.74 × 10-6, SNPs = 52) were associated with a lower risk of AD. No notable heterogeneity and directional pleiotropy were identified (all P > 0.05). Additional analyses partly support these results. No single SNP was driving the observed effects.

CONCLUSIONS

This MR analysis found evidence that genetically determined lowering BP was associated with a lower risk of AD and CCB was identified as a promising strategy for AD prevention.

Causal relationship between dietary macronutrient composition and anthropometric measures: A bidirectional two-sample Mendelian randomization analysis

BACKGROUND

The question whether the proportion of energy provided by fat and carbohydrates in the diet is associated with body mass index (BMI) and waist circumference (WC) is an important public health issue, but determining causality is difficult in epidemiological studies.

OBJECTIVES

Using a two-sample bidirectional Mendelian randomization (MR) in both a univariable and multivariable setting, we aimed to determine whether the relative proportion of different macronutrients in the diet (in % of total energy intake (E%)) is causally related to BMI and WC and vice versa.

METHODS

All analyses were based on genome-wide association studies including 268,922 Europeans with dietary data (SSGAC Consortium) and at least 232,101 with anthropometric measures (GIANT Consortium). An inverse-variance weighted approach using modified second-order weights within the radial regression framework was performed. Radial MR-Egger, weighted median and mode, Robust Adjusted Profile Score (RAPS), and Pleiotropy RESidual Sum and Outlier (PRESSO) methods were used in sensitivity analyses to verify MR assumptions. Additionally, multivariable MR was conducted to account for inter correlation between macronutrient intakes. All estimates represent the standard deviation (SD) change in each outcome per one SD change in the respective exposure.

RESULTS

We found that genetically predicted relative carbohydrate intake (E%) reduced BMI (β = -0.529; 95% CI: -0.745, -0.312; P-value = 2⋅10^-6) and WC (β = -0.459; 95% CI: -0.656, -0.262; P-value = 5⋅10^-6). Both effects were also supported by the multivariable approach: β = -0.441 (95% CI: -0.772, -0.109; P-value = 0.009) for BMI and β = -0.410 (95% CI: -0.667, -0.154; P-value = 0.002) for WC. Genetically predicted dietary intake of fat (E%) was weaker and positively related to both anthropometric measures. We obtained evidence that a higher BMI and WC increased the relative dietary intake of fat and protein (E%). For example, each SD higher BMI increased protein intake (E%) by 0.114 SD (95% CI: 0.081, 0.147; P-value = 9⋅10^-12) and each SD higher WC increased protein intake (E%) by 0.078 SD (95% CI: 0.035, 0.121; P-value = 4⋅10^-4). Sensitivity analyses confirmed these findings revealing consistent effect estimates.

CONCLUSIONS

Using genetic information to improve causal inference we found evidence, that a low relative carbohydrate proportion (E%) and a high proportion of fat (E%) in the diet is causally related to a higher BMI and a higher WC. Further research considering carbohydrate, fat, and protein quality and possible consequences on micronutrient intake is needed to define the implications for dietary intake recommendations.