Mendelian randomization in cardiometabolic disease: challenges in evaluating causality

Multivariable Mendelian Randomization and Mediation

Mendelian randomization (MR) is the use of genetic variants associated with an exposure to estimate the causal effect of that exposure on an outcome. Mediation analysis is the method of decomposing the effects of an exposure on an outcome, which act directly, and those that act via mediating variables. These effects are decomposed through the use of multivariable analysis to estimate the causal effects between three types of variables: exposures, mediators, and an outcome. Multivariable MR (MVMR) is a recent extension to MR that uses genetic variants associated with multiple, potentially related exposures to estimate the effect of each exposure on a single outcome. MVMR allows for equivalent analysis to mediation within the MR framework and therefore can also be used to estimate mediation effects. This approach retains the benefits of using genetic instruments for causal inference, such as avoiding bias due to confounding, while allowing for estimation of the different effects required for mediation analysis. This review explains MVMR, what is estimated when one exposure is a mediator of another in an MVMR estimation, and how MR and MVMR can therefore be used to estimate mediated effects. This review then goes on to consider the advantages and limitations of using MR and MVMR to conduct mediation analysis.

Impact of metabolic dysfunction on cognition in humans

PURPOSE OF REVIEW

The current review evaluates the recent literature on the impact of metabolic dysfunction in human cognition, focusing on epidemiological studies and meta-analyses of these.

RECENT FINDINGS

Worldwide around 50 million people live with dementia, a number projected to triple by 2050. Recent reports from the Lancet Commission suggest that 40% of dementia cases may be preventable primarily by focusing on well established metabolic dysfunction components and cardiovascular risk factors.

SUMMARY

There is robust evidence that type 2 diabetes and midlife hypertension increase risk of dementia in late life. Obesity and elevated levels of LDL cholesterol in midlife probably increase risk of dementia, but further research is needed in these areas. Physical activity, diet, alcohol, and smoking might also influence the risk of dementia through their effect on metabolic dysfunction. A key recommendation is to be ambitious about prevention, focusing on interventions to promote healthier lifestyles combating metabolic dysfunction. Only comprehensive multidomain and staff-requiring interventions are however efficient to maintain or improve cognition in at-risk individuals and will be unrealistic economic burdens for most societies to implement. Therefore, a risk score that identifies high-risk individuals will enable a targeted early intensive intervention toward those high-risk individuals that will benefit the most from a prevention against cardiovascular risk factors and metabolic dysfunction.

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.

Use of Multivariable Mendelian Randomization to Address Biases Due to Competing Risk Before Recruitment

Background: Mendelian randomization (MR) provides unconfounded estimates. MR is open to selection bias when the underlying sample is selected on surviving to recruitment on the genetically instrumented exposure and competing risk of the outcome. Few methods to address this bias exist. Methods: We show that this selection bias can sometimes be addressed by adjusting for common causes of survival and outcome. We use multivariable MR to obtain a corrected MR estimate for statins on stroke. Statins affect survival, and stroke typically occurs later in life than ischemic heart disease (IHD), making estimates for stroke open to bias from competing risk. Results: In univariable MR in the UK Biobank, genetically instrumented statins did not protect against stroke [odds ratio (OR) 1.33, 95% confidence interval (CI) 0.80-2.20] but did in multivariable MR (OR 0.81, 95% CI 0.68-0.98) adjusted for major causes of survival and stroke [blood pressure, body mass index (BMI), and smoking initiation] with a multivariable Q-statistic indicating absence of selection bias. However, the MR estimate for statins on stroke using MEGASTROKE remained positive and the Q statistic indicated pleiotropy. Conclusion: MR studies of harmful exposures on late-onset diseases with shared etiology need to be conceptualized within a mechanistic understanding so as to identify any potential bias due to survival to recruitment on both genetically instrumented exposure and competing risk of the outcome, which may then be investigated using multivariable MR or estimated analytically and results interpreted accordingly.

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

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

Mendelian randomisation approaches to the study of prenatal exposures: A systematic review

BACKGROUND

Mendelian randomisation (MR) designs apply instrumental variable techniques using genetic variants to study causal effects. MR is increasingly used to evaluate the role of maternal exposures during pregnancy on offspring health.

OBJECTIVES

We review the application of MR to prenatal exposures and describe reporting of methodologic challenges in this area.

DATA SOURCES

We searched PubMed, EMBASE, Medline Ovid, Cochrane Central, Web of Science, and Google Scholar.

STUDY SELECTION AND DATA EXTRACTION

Eligible studies met the following criteria: (a) a maternal pregnancy exposure; (b) an outcome assessed in offspring of the pregnancy; and (c) a genetic variant or score proposed as an instrument or proxy for an exposure.

SYNTHESIS

We quantified the frequency of reporting of MR conditions stated, techniques used to examine assumption plausibility, and reported limitations.

RESULTS

Forty-three eligible studies were identified. When discussing challenges or limitations, the most common issues described were known potential biases in the broader MR literature, including population stratification (n = 29), weak instrument bias (n = 18), and certain types of pleiotropy (n = 30). Of 22 studies presenting point estimates for the effect of exposure, four defined their causal estimand. Twenty-four studies discussed issues unique to prenatal MR, including selection on pregnancy (n = 1) and pleiotropy via postnatal exposure (n = 10) or offspring genotype (n = 20).

CONCLUSIONS

Prenatal MR studies frequently discuss issues that affect all MR studies, but rarely discuss problems specific to the prenatal context, including selection on pregnancy and effects of postnatal exposure. Future prenatal MR studies should report and attempt to falsify their assumptions, with particular attention to issues specific to prenatal MR. Further research is needed to evaluate the impacts of biases unique to prenatal MR in practice.

A Non-Linear Association of High-Density Lipoprotein Cholesterol with All-Cause and Cause-Specific Mortality in Diabetic Patients

BACKGROUND

The association between high-density lipoprotein cholesterol (HDL-C) and the risk of death among people with diabetes remains to be verified.

METHODS

This was a nationwide, population-based cohort study in United States. A total of 6549 diabetes patients were included from the National Health and Nutrition Examination Surveys (NHANES). HDL-C concentration was divided into quintiles, and the lowest risk group (Q4: 1.32 to 1.53 mmol/L) was used as reference. Multivariate Cox proportional hazards models and restrictive cubic curves were performed to estimate hazard ratios (HRs) with 95% confidence interval (CI) for all-cause and cause-specific mortality.

RESULTS

During a median follow-up of 82.36 ± 50.11 months, 1546 (23.61%) cases of all-cause, 389 (5.94%) cardiovascular and 262 (4.00%) cancer mortality have occurred, respectively. After adjusting for potential covariates, a U-shaped association was found between HDL-C and all-cause mortality (minimum mortality risk at 1.37 mmol/L); the risk for all-cause mortality was significantly higher in the groups with HDL-C concentration <0.96 mmol/L (HR: 1.30; 95% CI: 1.09, 1.56; P=0.0046) and with HDL-C concentration ≥1.55 mmol/L (HR: 1.20; 95% CI: 1.00, 1.44; P=0.0481) than participants with HDL-C concentrations ranging from 1.32 to 1.53mmol/L. Nonlinear associations of HDL-C levels with both cardiovascular and cancer mortality were also observed.

CONCLUSION

A non-linear association was observed association of HDL-C with all-cause, cardiovascular and cancer mortality among diabetic patients.

Genetic Liability to Depression and Risk of Coronary Artery Disease, Myocardial Infarction, and Other Cardiovascular Outcomes

Background

Observational studies have indicated that depression is associated with coronary artery disease (CAD) and myocardial infarction. Nevertheless, causal associations between depression and cardiovascular diseases remain controversial. Hence, we conducted a Mendelian randomization and mediation analysis to evaluate the associations of depression‐related genetic variants with CAD and myocardial infarction.

Methods and Results

Summary statistics from genome‐wide association studies of depression (807 553 individuals), and CAD (60 801 cases, including 43 676 with myocardial infarction, and 123 504 controls) were used. We pooled Mendelian randomization estimates using a fixed‐effects inverse‐variance weighted meta‐analysis and multivariable Mendelian randomization. The mediation effects of potential cardiovascular risk factors on depression‐CAD and myocardial infarction risk were investigated by using mediation analysis. We also explored the relationship of genetic liability to depression with heart failure, atrial fibrillation, and ischemic stroke. Genetic liability to depression was associated with higher CAD (odds ratio [OR], 1.14; 95% CI, 1.06–1.24; P=1.0×10⁻³) and myocardial infarction (OR, 1.21; 95% CI, 1.11–1.33; P=4.8×10⁻⁵) risks. Results were consistent in all sensitivity analyses. Type 2 diabetes mellitus and smoking demonstrated significant mediation effects. Furthermore, our Mendelian randomization analyses revealed that the genetic liability to depression was associated with higher risks of heart failure and small vessel stroke.

Conclusions

Genetic liability to depression is associated with higher CAD and myocardial infarction risks, partly mediated by type 2 diabetes mellitus and smoking. The potential preventive value of depression treatment on cardiovascular diseases should be investigated in the future.

Adiposity, metabolites, and colorectal cancer risk: Mendelian randomization study

BACKGROUND

Higher adiposity increases the risk of colorectal cancer (CRC), but whether this relationship varies by anatomical sub-site or by sex is unclear. Further, the metabolic alterations mediating the effects of adiposity on CRC are not fully understood.

METHODS

We examined sex- and site-specific associations of adiposity with CRC risk and whether adiposity-associated metabolites explain the associations of adiposity with CRC. Genetic variants from genome-wide association studies of body mass index (BMI) and waist-to-hip ratio (WHR, unadjusted for BMI; N = 806,810), and 123 metabolites from targeted nuclear magnetic resonance metabolomics (N = 24,925), were used as instruments. Sex-combined and sex-specific Mendelian randomization (MR) was conducted for BMI and WHR with CRC risk (58,221 cases and 67,694 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium, Colorectal Cancer Transdisciplinary Study, and Colon Cancer Family Registry). Sex-combined MR was conducted for BMI and WHR with metabolites, for metabolites with CRC, and for BMI and WHR with CRC adjusted for metabolite classes in multivariable models.

RESULTS

In sex-specific MR analyses, higher BMI (per 4.2 kg/m2) was associated with 1.23 (95% confidence interval (CI) = 1.08, 1.38) times higher CRC odds among men (inverse-variance-weighted (IVW) model); among women, higher BMI (per 5.2 kg/m2) was associated with 1.09 (95% CI = 0.97, 1.22) times higher CRC odds. WHR (per 0.07 higher) was more strongly associated with CRC risk among women (IVW OR = 1.25, 95% CI = 1.08, 1.43) than men (IVW OR = 1.05, 95% CI = 0.81, 1.36). BMI or WHR was associated with 104/123 metabolites at false discovery rate-corrected P ≤ 0.05; several metabolites were associated with CRC, but not in directions that were consistent with the mediation of positive adiposity-CRC relations. In multivariable MR analyses, associations of BMI and WHR with CRC were not attenuated following adjustment for representative metabolite classes, e.g., the univariable IVW OR for BMI with CRC was 1.12 (95% CI = 1.00, 1.26), and this became 1.11 (95% CI = 0.99, 1.26) when adjusting for cholesterol in low-density lipoprotein particles.

CONCLUSIONS

Our results suggest that higher BMI more greatly raises CRC risk among men, whereas higher WHR more greatly raises CRC risk among women. Adiposity was associated with numerous metabolic alterations, but none of these explained associations between adiposity and CRC. More detailed metabolomic measures are likely needed to clarify the mechanistic pathways.

Exploring the Relationship Between Psychiatric Traits and the Risk of Mouth Ulcers Using Bi-Directional Mendelian Randomization

Background

Although the association between mouth ulcers and psychiatric traits has been reported by observational studies, their causal relationship remains unclear. Mendelian randomization (MR), powered by large-scale genome-wide association studies (GWAS), provides an opportunity to clarify the causality between mouth ulcers and psychiatric traits.

Methods

We collected summary statistics of mouth ulcers (sample size n = 461,106) and 10 psychiatric traits from the largest publicly available GWAS on Europeans, including anxiety disorder (n = 83,566), attention deficit/hyperactivity disorder (n = 53,293), autism spectrum disorder (n = 46,350), bipolar disorder (n = 51,710), insomnia (n = 1,331,010), major depressive disorder (n = 480,359), mood instability (n = 363,705), neuroticism (n = 168,105), schizophrenia (n = 105,318), and subjective wellbeing (n = 388,538). We applied three two-sample bi-directional MR analysis methods, namely the Inverse Variance Weighted (IVW) method, the MR pleiotropy residual sum and outlier (MR-PRESSO) method, and the weighted median method, to assess the causal relationship between each psychiatric trait and mouth ulcers.

Results

We found significant effects of autism spectrum disorder, insomnia, major depressive disorder, and subjective wellbeing on mouth ulcers, with the corresponding odds ratio (OR) from the IVW method being 1.160 [95% confidence interval (CI): 1.066–1.261, P = 5.39 × 10^–4], 1.092 (1.062–1.122, P = 3.37 × 10^–10), 1.234 (1.134–1.342, P = 1.03 × 10^–6), and 0.703 (0.571–0.865, P = 8.97 × 10^–4), respectively. We also observed suggestive evidence for mood instability to cause mouth ulcers [IVW, OR = 1.662 (1.059–2.609), P = 0.027]. These results were robust to weak instrument bias and heterogeneity. We found no evidence on causal effects between other psychiatric traits and mouth ulcers, in either direction.

Conclusion

Our findings suggest a protective effect of subjective wellbeing and risk effects of autism spectrum disorder, insomnia, major depressive disorder, and mood instability on mouth ulcers. These results clarify the causal relationship between psychiatric traits and the development of mouth ulcers.

Castanea sativa Mill. bark extract cardiovascular effects in a rat model of high-fat diet

Ellagitannins may have a beneficial impact in cardiovascular diseases. The aim of the study was to evaluate the effect of high-fat diet (HFD) and the efficacy of Castanea sativa Mill. bark extract (ENC) on cardiac and vascular parameters. Rats were fed with regular diet, (RD, n = 15), HFD (n = 15), RD + ENC (20 mg/kg/day by gavage, n = 15), and HFD + ENC (same dose, n = 15) and the effects on body weight, biochemical serum parameters, and inflammatory cytokines determined. Cardiac functional parameters and aorta contractility were also assessed on isolated atria and aorta. Results showed that ENC reduced weight gain and serum lipids induced by HFD. In in vitro assays, HFD decreased the contraction force of left atrium, increased right atrium chronotropy, and decreased aorta K⁺ -induced contraction; ENC induced transient positive inotropic and negative chronotropic effects on isolated atria from RD and HFD rats and a spasmolytic effect on aorta. In ex vivo experiments, ENC reverted inotropic and chronotropic changes induced by HFD and enhanced Nifedipine effect more on aorta than on heart. In conclusion, ENC restores metabolic dysfunction and cardiac cholinergic muscarinic receptor function, and exerts spasmolytic effect on aorta in HFD rats, highlighting its potential as nutraceutical tool in obesity.

Inferring causal direction between two traits in the presence of horizontal pleiotropy with GWAS summary data

Orienting the causal relationship between pairs of traits is a fundamental task in scientific research with significant implications in practice, such as in prioritizing molecular targets and modifiable risk factors for developing therapeutic and interventional strategies for complex diseases. A recent method, called Steiger’s method, using a single SNP as an instrument variable (IV) in the framework of Mendelian randomization (MR), has since been widely applied. We report the following new contributions. First, we propose a single SNP-based alternative, overcoming a severe limitation of Steiger’s method in simply assuming, instead of inferring, the existence of a causal relationship. We also clarify a condition necessary for the validity of the methods in the presence of hidden confounding. Second, to improve statistical power, we propose combining the results from multiple, and possibly correlated, SNPs as multiple instruments. Third, we develop three goodness-of-fit tests to check modeling assumptions, including those required for valid IVs. Fourth, by relaxing one of the three IV assumptions in MR, we propose several methods, including an Egger regression-like approach and its multivariable version (analogous to multivariable MR), to account for horizontal pleiotropy of the SNPs/IVs, which is often unavoidable in practice. All our methods can simultaneously infer both the existence and (if so) the direction of a causal relationship, largely expanding their applicability over that of Steiger’s method. Although we focus on uni-directional causal relationships, we also briefly discuss an extension to bi-directional relationships. Through extensive simulations and an application to infer the causal directions between low density lipoprotein (LDL) cholesterol, or high density lipoprotein (HDL) cholesterol, and coronary artery disease (CAD), we demonstrate the superior performance and advantage of our proposed methods over Steiger’s method and bi-directional MR. In particular, after accounting for horizontal pleiotropy, our method confirmed the well known causal direction from LDL to CAD, while other methods, including bi-directional MR, might fail.

In spite of its importance, due to technical challenges, orienting causal relationships between pairs of traits has been largely under-studied. Mendelian randomization (MR) Steiger’s method has become increasingly used in the last two years. Here we point out several limitations with MR Steiger’s method and propose alternative approaches. First, MR Steiger’s method is based on using only one single SNP as the instrument variable (IV), for which we propose a correlation ratio-based method, called Causal Direction-Ratio, or simply CD-Ratio. An advantage of CD-Ratio is its inference of both the existence and (if so) the direction of a causal relationship, in contrast to MR Steiger’s prior assumption of the existence and its poor performance if the assumption is violated. Furthermore, CD-Ratio can be extended to combine the results from multiple, possibly correlated, SNPs with improved statistical power. Second, we propose two methods, called CD-Egger and CD-GLS, for multiple and possibly correlated SNPs while allowing horizontal pleiotropy. Third, we propose three goodness-of-fit tests to check modeling assumptions for the three proposed methods. Finally, we introduce multivariable CD-Egger, analogous to multivariable MR, as a more robust approach, and an extension of CD-Ratio to cases with possibly bi-directional causal relationships. Our numerical studies demonstrated superior performance of our proposed methods over MR Steiger and bi-directional MR. Our proposed methods, along with freely available software, are expected to be useful in practice for causal inference.

Sleep, major depressive disorder, and Alzheimer disease: A Mendelian randomization study

OBJECTIVE

To explore the causal relationships between sleep, major depressive disorder (MDD), and Alzheimer disease (AD).

METHODS

We conducted bidirectional 2-sample Mendelian randomization analyses. Genetic associations were obtained from the largest genome-wide association studies currently available in UK Biobank (n = 446,118), Psychiatric Genomics Consortium (n = 18,759), and International Genomics of Alzheimer's Project (n = 63,926). We used the inverse variance-weighted Mendelian randomization method to estimate causal effects and weighted median and Mendelian randomization-Egger for sensitivity analyses to test for pleiotropic effects.

RESULTS

We found that higher risk of AD was significantly associated with being a "morning person" (odds ratio [OR] 1.01, p = 0.001), shorter sleep duration (self-reported: β = -0.006, p = 1.9 × 10^-4; accelerometer based: β = -0.015, p = 6.9 × 10^-5), less likely to report long sleep (β = -0.003, p = 7.3 × 10^-7), earlier timing of the least active 5 hours (β = -0.024, p = 1.7 × 10^-13), and a smaller number of sleep episodes (β = -0.025, p = 5.7 × 10^-14) after adjustment for multiple comparisons. We also found that higher risk of AD was associated with lower risk of insomnia (OR 0.99, p = 7 × 10^-13). However, we did not find evidence that these abnormal sleep patterns were causally related to AD or for a significant causal relationship between MDD and risk of AD.

CONCLUSION

We found that AD may causally influence sleep patterns. However, we did not find evidence supporting a causal role of disturbed sleep patterns for AD or evidence for a causal relationship between MDD and AD.

Observational and Genetic Associations of Body Mass Index and Hepatobiliary Diseases in a Relatively Lean Chinese Population

IMPORTANCE

There is some support for the existence of genetic associations between adiposity and certain hepatobiliary diseases in Western populations. However, there is little evidence of such genetic associations in China, where the causes of these diseases may differ from those in Western populations and the mean body mass index (BMI) is much lower.

OBJECTIVES

To compare the observational associations of BMI with hepatobiliary diseases and liver biomarkers with the genetic associations between BMI and these factors and to assess whether the genetic associations of BMI with liver diseases differed by hepatitis B virus infection status.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used data from the prospective China Kadoorie Biobank, including 473 938 adults aged 30 to 79 years without hepatobiliary diseases at baseline from 10 diverse areas in China from June 25, 2004, to July 15, 2008. A random sample of 75 736 participants with genotyping data was included in the Mendelian randomization analysis. Follow-up was completed January 1, 2017 (median [interquartile range] length of follow-up, 10.2 [9.2-11.1] years). Data were analyzed from January to October 2019.

EXPOSURES

Measured BMI obtained during the baseline survey and genetically instrumented BMI derived using 92 single-nucleotide variations.

MAIN OUTCOMES AND MEASURES

Incident cases of hepatobiliary diseases, liver enzymes, fatty liver index, and fibrosis score.

RESULTS

Among 473 938 individuals (276 041 [58.2%] women), the mean (SD) age was 52 (10.9) years and mean (SD) BMI was 23.8 (3.4). Baseline BMI was associated with higher risks of chronic liver disease (adjusted risk ratio per 1-SD increase, 1.14; 95% CI, 1.11 to 1.17) and gallbladder disease (adjusted risk ratio per 1-SD increase, 1.29; 95% CI, 1.27 to 1.31), with heterogeneity by disease subtype (P < .001). Genetically instrumented BMI was associated with higher risks of chronic liver disease (risk ratio per 1-SD increase, 1.55; 95% CI, 1.08 to 2.24) and gallbladder disease (risk ratio per 1-SD increase, 1.40; 95% CI, 1.11 to 1.76), with no heterogeneity between subtypes. A meta-analysis of the genetic associations in China Kadoorie Biobank and those calculated in UK Biobank gave a risk ratio of 1.55 (95% CI, 1.30 to 1.84) for chronic liver disease and 1.42 (95% CI, 1.22 to 1.64) for gallbladder disease. In the China Kadoorie Biobank study, there were positive genetic associations of BMI with liver enzymes, steatosis, and fibrosis scores, consistent with observational associations. The genetic associations of BMI with liver diseases and biomarkers did not differ by hepatitis B virus infection status.

CONCLUSIONS AND RELEVANCE

In this cohort study of a relatively lean Chinese population, there were positive genetic associations of BMI with hepatobiliary diseases. These results suggest that maintaining a healthy weight through diet and physical activity may help prevent hepatobiliary diseases.

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.

Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases

The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma protein levels. Here we estimated the effects of 1,002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium is widespread in naïve phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes ( https://www.epigraphdb.org/pqtl/ ). Evaluation of data from historic drug development programs showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of this approach in identifying and prioritizing potential therapeutic targets.

Association of Type 2 Diabetes With Cancer: A Meta-analysis With Bias Analysis for Unmeasured Confounding in 151 Cohorts Comprising 32 Million People

BACKGROUND AND PURPOSE

Whether the association between type 2 diabetes (T2D) and cancer is causal remains controversial. The goal of this work is to assess the robustness of the observational associations between T2D and cancer to unmeasured confounding.

DATA SOURCES AND STUDY SELECTION

PubMed, Web of Science, and the Cochrane library were systematically searched on 10 January 2019 for observational studies investigating associations between T2D and cancer incidence or mortality.

DATA EXTRACTION AND DATA SYNTHESIS

Cohort-level relative risk (RR) was extracted. RRs were combined in random-effects meta-analyses and pooled estimates used in bias analyses. A total of 151 cohorts (over 32 million people, 1.1 million cancer cases, and 150,000 cancer deaths) were included. In meta-analyses, T2D was associated with incidence of several cancers, from prostate (RR 0.83; 95% CI 0.79, 0.88) to liver (2.23; 1.99, 2.49), and with mortality from pancreatic cancer (1.67; 1.30, 2.14). In bias analyses, assuming an unmeasured confounding associated with both T2D and cancer with a RR of 1.5, the proportion of studies with a true effect size larger than a RR of 1.1 (i.e., 10% increased risk in individuals with T2D) was nearly 100% for liver, pancreatic, and endometrial, 86% for gallbladder, 67% for kidney, 64% for colon, 62% for colorectal, and <50% for other cancer incidences, and 92% for pancreatic cancer mortality.

LIMITATIONS

Biases other than unmeasured confounding were not analytically assessed.

CONCLUSIONS

Our findings strongly suggest a causal association between T2D and liver, pancreatic, and endometrial cancer incidence, and pancreatic cancer mortality. Conversely, associations with other cancers were less robust to unmeasured confounding.

Genetically Predicted Blood Pressure Across the Lifespan: Differential Effects of Mean and Pulse Pressure on Stroke Risk

Hypertension is the leading risk factor for stroke. Yet, it remains unknown whether blood pressure pulsatility (pulse pressure [PP]) causally affects stroke risk independently of the steady pressure component (mean arterial pressure [MAP]). It is further unknown how the effects of MAP and PP on stroke risk vary with age and stroke cause. Using data from UK Biobank (N=408 228; 38-71 years), we selected genetic variants as instruments for MAP and PP at age ≤55 and >55 years and across age deciles. We applied multivariable Mendelian randomization analyses to explore associations with ischemic stroke, intracerebral hemorrhage, and their subtypes. Higher genetically predicted MAP was associated with higher risk of ischemic stroke and intracerebral hemorrhage across the examined age spectrum. Independent of MAP, higher genetically predicted PP only at age >55 years was further associated with higher risk of ischemic stroke (odds ratio per-SD-increment, 1.23 [95% CI, 1.13-1.34]). Among subtypes, the effect of genetically predicted MAP on large artery stroke was attenuated, whereas the effect of genetically predicted PP was augmented with increasing age. Genetically predicted MAP, but not PP, was associated with small vessel stroke and deep intracerebral hemorrhage homogeneously across age deciles. Neither genetically predicted MAP nor PP were associated with lobar intracerebral hemorrhage. Beyond an effect of high MAP at any age on ischemic and hemorrhagic stroke, our results support an independent causal effect of high PP at older ages on large artery stroke. This finding warrants further investigation for the development of stroke preventive strategies targeting pulsatility in later life.

Circulating sphingomyelins on estrogen receptor-positive and estrogen receptor-negative breast cancer-specific survival

Aim: This study aims to determine whether a causal relationship exists between circulating sphingomyelins and breast cancer-specific survival, since, if one does, sphingomyelins could be studied as a therapeutic target in the management of breast cancer. Patients/materials & methods: Mendelian randomization is used here to investigate whether higher levels of circulating sphingomyelins impact breast cancer-specific survival for estrogen receptor-negative (ER–) and estrogen receptor-positive (ER+) patients. Results: The results suggest a null effect of sphingomyelins for ER– breast cancer-specific survival and a protective effect for ER+ breast cancer-specific survival. Sensitivity analyses implicate low-density lipoprotein cholesterol as a potential confounder. Conclusion: Future studies should replicate and triangulate the present findings with other methods and tease out the roles of sphingomyelins and low-density lipoprotein cholesterol on breast cancer-specific survival.

Cardioprotective Properties of HDL: Structural and Functional Considerations

BACKGROUND

As Mendelian Randomization (MR) studies showed no effect of variants altering HDL-cholesterol (HDL-C) levels concerning Cardiovascular Disease (CVD) and novel therapeutic interventions aiming to raise HDL-C resulted to futility, the usefulness of HDL-C is unclear.

OBJECTIVE

As the role of HDL-C is currently doubtful, it is suggested that the atheroprotective functions of HDLs can be attributed to the number of HDL particles, and their characteristics including their lipid and protein components. Scientific interest has focused on HDL function and on the causes of rendering HDL particles dysfunctional, whereas the relevance of HDL subclasses with CVD remains controversial.

METHODS

The present review discusses changes in quality as much as in quantity of HDL in pathological conditions and the connection between HDL particle concentration and cardiovascular disease and mortality. Emphasis is given to the recently available data concerning the cholesterol efflux capacity and the parameters that determine HDL functionality, as well as to recent investigations concerning the associations of HDL subclasses with cardiovascular mortality.

RESULTS

MR studies or pharmacological interventions targeting HDL-C are not in favor of the hypothesis of HDL-C levels and the relationship with CVD. The search of biomarkers that relate with HDL functionality is needed. Similarly, HDL particle size and number exhibit controversial data in the context of CVD and further studies are needed.

CONCLUSION

There is no room for the old concept of HDL as a silver bullet,as HDL-C cannot be considered a robust marker and does not reflect the importance of HDL particle size and number. Elucidation of the complex HDL system, as well as the finding of biomarkers, will allow the development of any HDL-targeted therapy.

Emerging Targets for Cardiovascular Disease Prevention in Diabetes

Type 1 and type 2 diabetes mellitus (T1DM and T2DM) increase the risk of atherosclerotic cardiovascular disease (CVD), resulting in acute cardiovascular events, such as heart attack and stroke. Recent clinical trials point toward new treatment and prevention strategies for cardiovascular complications of T2DM. New antidiabetic agents show unexpected cardioprotective benefits. Moreover, genetic and reverse translational strategies have revealed potential novel targets for CVD prevention in diabetes, including inhibition of apolipoprotein C3 (APOC3). Modeling and pharmacology-based approaches to improve insulin action provide additional potential strategies to combat CVD. The development of new strategies for improved diabetes and lipid control fuels hope for future prevention of CVD associated with diabetes.

Genetically determined blood pressure, antihypertensive drug classes, and risk of stroke subtypes

OBJECTIVE

We employed Mendelian randomization to explore whether the effects of blood pressure (BP) and BP-lowering through different antihypertensive drug classes on stroke risk vary by stroke etiology.

METHODS

We selected genetic variants associated with systolic and diastolic BP and BP-lowering variants in genes encoding antihypertensive drug targets from genome-wide association studies (GWAS) on 757,601 individuals. Applying 2-sample Mendelian randomization, we examined associations with any stroke (67,162 cases; 454,450 controls), ischemic stroke and its subtypes (large artery, cardioembolic, small vessel stroke), intracerebral hemorrhage (ICH, deep and lobar), and the related small vessel disease phenotype of white matter hyperintensities (WMH).

RESULTS

Genetic predisposition to higher systolic and diastolic BP was associated with higher risk of any stroke, ischemic stroke, and ICH. We found associations between genetically determined BP and all ischemic stroke subtypes with a higher risk of large artery and small vessel stroke compared to cardioembolic stroke, as well as associations with deep, but not lobar ICH. Genetic proxies for calcium channel blockers, but not β-blockers, were associated with lower risk of any stroke and ischemic stroke. Proxies for calcium channel blockers showed particularly strong associations with small vessel stroke and the related radiologic phenotype of WMH.

CONCLUSIONS

This study supports a causal role of hypertension in all major stroke subtypes except lobar ICH. We find differences in the effects of BP and BP-lowering through antihypertensive drug classes between stroke subtypes and identify calcium channel blockade as a promising strategy for preventing manifestations of cerebral small vessel disease.

Analytic and Translational Genetics

Understanding the influence of genetics on human disease is among the primary goals for biology and medicine. To this end, the direct study of natural human genetic variation has provided valuable insights into human physiology and disease as well as into the origins and migrations of humans. In this review, we discuss the foundations of population genetics, which provide a crucial context to the study of human genes and traits. In particular, genome-wide association studies and similar methods have revealed thousands of genetic loci associated with diseases and traits, providing invaluable information into the biology of these traits. Simultaneously, as the study of rare genetic variation has expanded, so-called human knockouts have elucidated the function of human genes and the therapeutic potential of targeting them.

Genetic determinants of blood lipids and cerebral small vessel disease: role of high-density lipoprotein cholesterol

Blood lipids are causally involved in the pathogenesis of atherosclerosis, but their role in cerebral small vessel disease remains largely elusive. Here, we explored associations of genetic determinants of blood lipid levels, lipoprotein particle components, and targets for lipid-modifying drugs with small vessel disease phenotypes. We selected genetic instruments for blood levels of high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides, for cholesterol and triglycerides components of size-defined lipoprotein particles, and for lipid-modifying drug targets based on published genome-wide association studies (up to 617 303 individuals). Applying two-sample Mendelian randomization approaches we investigated associations with ischaemic and haemorrhagic manifestations of small vessel disease [small vessel stroke: 11 710 cases, 287 067 controls; white matter hyperintensities (WMH): 10 597 individuals; intracerebral haemorrhage: 1545 cases, 1481 controls]. We applied the inverse-variance weighted method and multivariable Mendelian randomization as our main analytical approaches. Genetic predisposition to higher HDL-C levels was associated with lower risk of small vessel stroke [odds ratio (OR) per standard deviation = 0.85, 95% confidence interval (CI) = 0.78-0.92] and lower WMH volume (β = -0.07, 95% CI = -0.12 to -0.02), which in multivariable Mendelian randomization remained stable after adjustments for LDL-C and triglycerides. In analyses of lipoprotein particle components by size, we found these effects to be specific for cholesterol concentration in medium-sized high-density lipoprotein, and not large or extra-large high-density lipoprotein particles. Association estimates for intracerebral haemorrhage were negatively correlated with those for small vessel stroke and WMH volume across all lipid traits and lipoprotein particle components. HDL-C raising genetic variants in the gene locus of the target of CETP inhibitors were associated with lower risk of small vessel stroke (OR: 0.82, 95% CI = 0.75-0.89) and lower WMH volume (β = -0.08, 95% CI = -0.13 to -0.02), but a higher risk of intracerebral haemorrhage (OR: 1.64, 95% CI = 1.26-2.13). Genetic predisposition to higher HDL-C, specifically to cholesterol in medium-sized high-density lipoprotein particles, is associated with both a lower risk of small vessel stroke and lower WMH volume. These analyses indicate that HDL-C raising strategies could be considered for the prevention of ischaemic small vessel disease but the net benefit of such an approach would need to be tested in a randomized controlled trial.

Advances in lipidomics

The present article examines recently published literature on lipids, mainly focusing on research involving glycero-, glycerophospho- and sphingo-lipids. The primary aim is identification of distinct profiles in biologic lipidomic systems by ultra-high-performance liquid chromatography (UHPLC) coupled with mass spectrometry (MS, tandem MS) with multivariate data analysis. This review specifically targets lipid biomarkers and disease pathway mechanisms in humans and artificial targets. Different specimen matrices such as primary blood derivatives (plasma, serum, erythrocytes, and blood platelets), faecal matter, urine, as well as biologic tissues (liver, lung and kidney) are highlighted.

Early Metabolic Features of Genetic Liability to Type 2 Diabetes: Cohort Study With Repeated Metabolomics Across Early Life

OBJECTIVE

Type 2 diabetes develops for many years before diagnosis. We aimed to reveal early metabolic features characterizing liability to adult disease by examining genetic liability to adult type 2 diabetes in relation to metabolomic traits across early life.

RESEARCH DESIGN AND METHODS

Up to 4,761 offspring from the Avon Longitudinal Study of Parents and Children were studied. Linear models were used to examine effects of a genetic risk score (162 variants) for adult type 2 diabetes on 229 metabolomic traits (lipoprotein subclass-specific cholesterol and triglycerides, amino acids, glycoprotein acetyls, and others) measured at age 8 years, 16 years, 18 years, and 25 years. Two-sample Mendelian randomization (MR) was also conducted using genome-wide association study data on metabolomic traits in an independent sample of 24,925 adults.

RESULTS

At age 8 years, associations were most evident for type 2 diabetes liability (per SD higher) with lower lipids in HDL subtypes (e.g., -0.03 SD [95% CI -0.06, -0.003] for total lipids in very large HDL). At 16 years, associations were stronger with preglycemic traits, including citrate and with glycoprotein acetyls (0.05 SD; 95% CI 0.01, 0.08), and at 18 years, associations were stronger with branched-chain amino acids. At 25 years, associations had strengthened with VLDL lipids and remained consistent with previously altered traits, including HDL lipids. Two-sample MR estimates among adults indicated persistent patterns of effect of disease liability.

CONCLUSIONS

Our results support perturbed HDL lipid metabolism as one of the earliest features of type 2 diabetes liability, alongside higher branched-chain amino acid and inflammatory levels. Several features are apparent in childhood as early as age 8 years, decades before the clinical onset of disease.

Biomarkers for type 2 diabetes

Background

The prevalence and 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 loci in interplay with lifestyle and environmental factors. Recently over 400 distinct association signals were published; these explain 18% of the risk of T2D.

Scope of review

In this review there is a major focus on risk factors and genetic and non-genetic biomarkers for the risk of T2D identified especially in large prospective population-based studies, and studies testing causality of the biomarkers for T2D in Mendelian randomization studies. Another focus is on understanding genome-phenome interplay in the classification of individuals with T2D into subgroups.

Major conclusions

Several recent large population-based studies and their meta-analyses have identified multiple potential genetic and non-genetic biomarkers for the risk of T2D. Combination of genetic variants and physiologically characterized pathways improves the classification of individuals with T2D into subgroups, and is also paving the way to a precision medicine approach, in T2D.

The Nordic Nutrition Recommendations 2022 - principles and methodologies

BACKGROUND

The Nordic Nutrition Recommendations (NNRs) constitute the scientific basis for national dietary reference values (DRVs) and food-based dietary guidelines (FBDGs) in the Nordic and Baltic countries.

OBJECTIVE

To define principles and methodologies for the sixth edition of NNR to be published in 2022 (NNR2022).

DESIGN

The principles and methodologies of the previous edition of NNR were used as a starting point. Recent nutrition recommendations commissioned by other national food and health authorities or international food and health organizations were examined and dissected. Updated principles and methodologies were agreed by the NNR2022 Committee in a consensus-driven process.

RESULTS

An organizational model with 'checks and balances' was developed to minimize the influence of subjective biases of the committee members and experts. Individual chapters on all included nutrients and food groups will be updated as scoping reviews. Systematic reviews (SRs), which are the main basis for evaluating causal effects of nutrients or food groups on health outcomes, will be embedded in each chapter. A NNR SR Centre will be established for performing de novo SRs on prioritized topics. To avoid duplication and optimize the use of resources, qualified SRs commissioned by other national and international organizations and health authorities will also inform DRVs and FBDGs in NNR2022.

DISCUSSION

The evidence-based methods defined in the NNR2022 project are compatible with most contemporary methods used by leading national food and health authorities. Global harmonization of methodological approaches to nutrition recommendations is strongly encouraged.

CONCLUSION

Evidence-informed principles and methodologies underpinned by SRs will ensure that DRVs and FBDGs defined in the NNR2022 project are based on the best available evidence and as far as possible free from overt bias.

Potential causal association of a prolonged PR interval and clinical recurrence of atrial fibrillation after catheter ablation: a Mendelian randomization analysis

A prolonged PR interval predicts atrial fibrillation (AF) recurrence after catheter ablation. We investigated the causal association between the PR interval and AF clinical recurrence by a Mendelian randomization. We prospectively included 1722 patients with AF (73.2% male, 58.6 ± 10.8 years old, 71.3% paroxysmal AF) who underwent catheter ablation into a genome-wide association study (GWAS). We searched for the genetic associations between the PR interval and AF recurrence by analyzing 44 single nucleotide polymorphisms (SNPs) already known to be associated with the PR interval, and investigated the Mendelian randomization. Based on the quartile analysis, the highest quartile of the PR interval was associated with an increased risk of AF recurrence compared with the lowest quartile (Hazard ratio (HR) = 1.91, 95% CI = 1.51-2.42, P = 8.41 × 10^-8) during 35.7 ± 28.5 months of follow-up. Among 44 SNPs known to be associated with the PR interval, two SNPs had significant associations with the PR interval (P < 0.001 for each SNP). CAV1 (HR = 1.15, 95% CI = 1.02-1.31, P = 0.024) was associated with clinical recurrence of AF. A Mendelian randomization analysis demonstrated a significant association with CAV1 (HR = 1.04, 95% CI = 1.01-1.07, P = 0.006). A prolonged PR interval was a risk factor for an AF recurrence, and the PR interval had a potentially causal association with an AF clinical recurrence after catheter ablation at the genetic level.

Use of genetic variation to separate the effects of early and later life adiposity on disease risk: mendelian randomisation study

OBJECTIVE

To evaluate whether body size in early life has an independent effect on risk of disease in later life or whether its influence is mediated by body size in adulthood.

DESIGN

Two sample univariable and multivariable mendelian randomisation.

SETTING

The UK Biobank prospective cohort study and four large scale genome-wide association studies (GWAS) consortiums.

PARTICIPANTS

453 169 participants enrolled in UK Biobank and a combined total of more than 700 000 people from different GWAS consortiums.

EXPOSURES

Measured body mass index during adulthood (mean age 56.5) and self-reported perceived body size at age 10.

MAIN OUTCOME MEASURES

Coronary artery disease, type 2 diabetes, breast cancer, and prostate cancer.

RESULTS

Having a larger genetically predicted body size in early life was associated with an increased odds of coronary artery disease (odds ratio 1.49 for each change in body size category unless stated otherwise, 95% confidence interval 1.33 to 1.68) and type 2 diabetes (2.32, 1.76 to 3.05) based on univariable mendelian randomisation analyses. However, little evidence was found of a direct effect (ie, not through adult body size) based on multivariable mendelian randomisation estimates (coronary artery disease: 1.02, 0.86 to 1.22; type 2 diabetes:1.16, 0.74 to 1.82). In the multivariable mendelian randomisation analysis of breast cancer risk, strong evidence was found of a protective direct effect for larger body size in early life (0.59, 0.50 to 0.71), with less evidence of a direct effect of adult body size on this outcome (1.08, 0.93 to 1.27). Including age at menarche as an additional exposure provided weak evidence of a total causal effect (univariable mendelian randomisation odds ratio 0.98, 95% confidence interval 0.91 to 1.06) but strong evidence of a direct causal effect, independent of early life and adult body size (multivariable mendelian randomisation odds ratio 0.90, 0.85 to 0.95). No strong evidence was found of a causal effect of either early or later life measures on prostate cancer (early life body size odds ratio 1.06, 95% confidence interval 0.81 to 1.40; adult body size 0.87, 0.70 to 1.08).

CONCLUSIONS

The findings suggest that the positive association between body size in childhood and risk of coronary artery disease and type 2 diabetes in adulthood can be attributed to individuals remaining large into later life. However, having a smaller body size during childhood might increase the risk of breast cancer regardless of body size in adulthood, with timing of puberty also putatively playing a role.

Guidelines for performing Mendelian randomization investigations

This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, and at journal editors and reviewers seeking to assess Mendelian randomization manuscripts. The guidelines are divided into nine sections: motivation and scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary and sensitivity analyses (one section on robust statistical methods and one on other approaches), data presentation, and interpretation. These guidelines will be updated based on feedback from the community and advances in the field. Updates will be made periodically as needed, and at least every 18 months.

Powerful three-sample genome-wide design and robust statistical inference in summary-data Mendelian randomization

BACKGROUND

Summary-data Mendelian randomization (MR) has become a popular research design to estimate the causal effect of risk exposures. With the sample size of GWAS continuing to increase, it is now possible to use genetic instruments that are only weakly associated with the exposure.

DEVELOPMENT

We propose a three-sample genome-wide design where typically 1000 independent genetic instruments across the whole genome are used. We develop an empirical partially Bayes statistical analysis approach where instruments are weighted according to their strength; thus weak instruments bring less variation to the estimator. The estimator is highly efficient with many weak genetic instruments and is robust to balanced and/or sparse pleiotropy.

APPLICATION

We apply our method to estimate the causal effect of body mass index (BMI) and major blood lipids on cardiovascular disease outcomes, and obtain substantially shorter confidence intervals (CIs). In particular, the estimated causal odds ratio of BMI on ischaemic stroke is 1.19 (95% CI: 1.07-1.32, P-value <0.001); the estimated causal odds ratio of high-density lipoprotein cholesterol (HDL-C) on coronary artery disease (CAD) is 0.78 (95% CI: 0.73-0.84, P-value <0.001). However, the estimated effect of HDL-C attenuates and become statistically non-significant when we only use strong instruments.

CONCLUSIONS

A genome-wide design can greatly improve the statistical power of MR studies. Robust statistical methods may alleviate but not solve the problem of horizontal pleiotropy. Our empirical results suggest that the relationship between HDL-C and CAD is heterogeneous, and it may be too soon to completely dismiss the HDL hypothesis.

Clinical relationship between anemia and atrial fibrillation recurrence after catheter ablation without genetic background

Background

Anemia is a known adverse prognostic factor among patients with cardiovascular diseases. We investigated whether the hemoglobin level was associated with the rhythm outcome after atrial fibrillation (AF) catheter ablation (AFCA).

Methods

We included 2627 patients who underwent AFCA and a guidelines-based rhythm follow-up (age 58 ± 10.9 years, 73% men, 30.6% with persistent AF), and evaluated the association of pre-AFCA anemia (haemoglobin <13 g/dL in men and <12 g/dL in women) and rhythm outcomes. We studied the mechanistic relationship between anemia and AF recurrence using a Mendelian randomization analysis (1775 subjects with genome-wide association study) after reviewing already proven 12 hemoglobin-associated genetic polymorphisms.

Results

The body mass index, paroxysmal AF, warfarin use, and baseline red cell distribution width were independently associated with anemia in patients with AF. During a 23-month follow-up (interval OR 9–48 months), the clinical AF recurrence rate was significantly higher in patients with than without anemia (log-rank p = 0.001; propensity score-matched log-rank p = 0.004). This pattern was more significant in male patients (Log-rank p < 0.001) or patients with paroxysmal AF (Log-rank p < 0.001). Anemia (hazard ratio [HR] 1.45 [1.17–1.80], p = 0.001), left atrial diameter (HR 1.03 [1.01–1.04], p < 0.001), a female sex (HR 1.17 [1.00–1.36], p = 0.047), and persistent AF (HR 1.58 [1.36–1.84], p < 0.001) were independently associated with post-AFCA clinical recurrence. In the Mendelian randomization, we could not find a significant direct causal relationship between anemia and AF recurrence at the genetic level.

Conclusions

Pre-AFCA anemia is an independent predictor of post-AFCA clinical recurrence, especially in male patients, without a genetically direct causal relationship.

ACE and Type 2 Diabetes Risk: A Mendelian Randomization Study

OBJECTIVE

To determine whether ACE inhibitors reduce the risk of type 2 diabetes using a Mendelian randomization (MR) approach.

RESEARCH DESIGN AND METHODS

A two-sample MR analysis included 17 independent genetic variants associated with ACE serum concentration in 4,147 participants from the Outcome Reduction with Initial Glargine INtervention (ORIGIN) (clinical trial reg. no. NCT00069784) trial, and their effects on type 2 diabetes risk were estimated from 18 studies of the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium. A genetic risk score (GRS) underpinning lower ACE concentration was then tested for association with type 2 diabetes prevalence in 341,872 participants, including 16,320 with type 2 diabetes, from the UK Biobank. MR estimates were compared after standardization for blood pressure change, with the estimate obtained from a randomized controlled trial (RCT) meta-analysis of ACE inhibitors versus placebo (n = 31,200).

RESULTS

Genetically lower ACE concentrations were associated with a lower risk of type 2 diabetes (odds ratio [OR] per SD 0.92 [95% CI 0.89-0.95]; P = 1.79 × 10^-7). This result was replicated in the UK Biobank (OR per SD 0.97 [0.96-0.99]; P = 8.73 × 10^-4). After standardization, the ACE GRS was associated with a larger decrease in type 2 diabetes risk per 2.4-mmHg lower mean arterial pressure (MAP) compared with that obtained from an RCT meta-analysis (OR per 2.4-mmHg lower MAP 0.19 [0.07-0.51] vs. 0.76 [0.60-0.97], respectively; P = 0.007 for difference).

CONCLUSIONS

These results support the causal protective effect of ACE inhibitors on type 2 diabetes risk and may guide therapeutic decision making in clinical practice.

Apolipoprotein A-I concentrations and risk of coronary artery disease: A Mendelian randomization study

BACKGROUND AND AIMS

Apolipoprotein A-I (apoA-I) infusions represent a potential novel therapeutic approach for the prevention of coronary artery disease (CAD). Although circulating apoA-I concentrations inversely associate with risk of CAD, the evidence base of this representing a causal relationship is lacking. The aim was to assess the causal role of apoA-I using human genetics.

METHODS

We identified a variant (rs12225230) in APOA1 locus that associated with circulating apoA-I concentrations (p < 5 × 10-8) in 20,370 Finnish participants, and meta-analyzed our data with a previous GWAS of apoA-I. We obtained genetic estimates of CAD from UK Biobank and CARDIoGRAMplusC4D (totaling 122,733 CAD cases) and conducted a two-sample Mendelian randomization analysis. We compared our genetic findings to observational associations of apoA-I with risk of CAD in 918 incident CAD cases among 11,535 individuals from population-based prospective cohorts.

RESULTS

ApoA-I was associated with a lower risk of CAD in observational analyses (HR 0.81; 95%CI: 0.75, 0.88; per 1-SD higher apoA-I), with the association showing a dose-response relationship. Rs12225230 associated with apoA-I concentrations (per-C allele beta 0.076 SD; SE: 0.013; p = 1.5 × 10-9) but not with confounders. In Mendelian randomization analyses, apoA-I was not related to risk of CAD (OR 1.13; 95%CI: 0.98,1.30 per 1-SD higher apoA-I), which was different from the observational association. Similar findings were observed using an independent ABCA1 variant in sensitivity analysis.

CONCLUSIONS

Genetic evidence fails to support a cardioprotective role for apoA-I. This is in line with the cumulative evidence showing that HDL-related phenotypes are unlikely to have a protective role in CAD.

Effects of eicosapentaenoic acid and docosahexaenoic acid versus α-linolenic acid supplementation on cardiometabolic risk factors: a meta-analysis of randomized controlled trials

Previous randomized controlled trials (RCTs) made direct comparisons between EPA/DHA versus ALA on improving cardiovascular risk factors and have reached inconsistent findings. The aim of this meta-analysis was to compare the effects of EPA/DHA vs. ALA supplementation on cardiometabolic disturbances. Databases including MEDLINE, Embase, PubMed and Cochrane Trials were searched until December 2019. The pooled effects (weighted mean difference, WMD) of outcomes with moderate and high heterogeneity were calculated with a random-effects model, while low heterogeneity was calculated with a fixed-effect model. Fourteen RCTs with 1137 participants who met the eligibility criteria were pooled. Compared with participants supplemented with ALA, those who received EPA/DHA supplementation experienced a greater reduction in triglycerides (TG) (WMD -0.191 mmol l-1; 95% CI -0.249, -0.133) but a greater increase in high-density lipoprotein (HDL) (WMD 0.033 mmol l-1; 95% CI 0.004, 0.062), low-density lipoprotein (LDL) (WMD 0.130 mmol l-1; 95% CI 0.006, 0.253) and total cholesterol (TC) (WMD 0.179 mmol l-1; 95% CI 0.006, 0.352). In subgroup analyses, the WMD for TG was much lower in trials with participants >40 years old (-0.246 mmol l-1; 95% CI -0.325, -0.167). When DHA and EPA were separately administered, modest increases in HDL were observed in trials that used DHA as a supplement (0.161 mmol l-1; 95% CI 0.017, 0.304), but not in trials using EPA (0.040 mmol l-1; 95% CI -0.132, 0.212). In conclusion, dietary EPA/DHA supplementation improved the TG and HDL status but increased LDL levels in comparison with ALA.

Using Mendelian randomization to understand and develop treatments for neurodegenerative disease

Common neurodegenerative diseases are thought to arise from a combination of environmental and genetic exposures. Mendelian randomization is a powerful way to leverage existing genetic data to investigate causal relationships between risk factors and disease. In recent years, Mendelian randomization has gathered considerable traction in neurodegenerative disease research, providing valuable insights into the aetiology of these conditions. This review aims to evaluate the impact of Mendelian randomization studies on translational medicine for neurodegenerative diseases, highlighting the advances made and challenges faced. We will first describe the fundamental principles and limitations of Mendelian randomization and then discuss the lessons from Mendelian randomization studies of environmental risk factors for neurodegeneration. We will illustrate how Mendelian randomization projects have used novel resources to study molecular pathways of neurodegenerative disease and discuss the emerging role of Mendelian randomization in drug development. Finally, we will conclude with our view of the future of Mendelian randomization in these conditions, underscoring unanswered questions in this field.

Association between habitual coffee consumption and multiple disease outcomes: A Mendelian randomisation phenome-wide association study in the UK Biobank

BACKGROUND

Coffee is the most commonly consumed beverage in the world after water, however the debate as to whether coffee consumption is beneficial or detrimental to health continues. Current evidence of the link between coffee and health outcomes is predominately observational, thus subject to methodological issues such a confounding and reverse causation.

METHODS

This Mendelian randomisation phenome-wide association study (MR-PheWAS) used information from up to 333,214 participants of White-British ancestry in the UK Biobank to examine the causal association between genetically instrumented habitual coffee consumption and the full range of disease outcomes. We constructed a genetic risk score for habitual coffee consumption and screened for associations with disease outcomes across 1117 case-control series. All signals under false discovery rate controlled threshold (5.8 × 10^-4) were followed by Mendelian randomisation (MR) analyses, with replication in independent data sources where possible.

RESULTS

The initial phenome-wide association analysis identified signals for 13 outcomes representing five distinct diseases. The strongest signal was seen for gout (P = 2.3 × 10^-12), but there was notable pleiotropy (P_distortion <0.001) and MR analyses did not support an association with habitual coffee consumption (inverse variance weighted MR OR 0.41, 95% CI 0.08 to 2.25, P = 0.31). Support for a possible causal relationship between habitual coffee consumption was only obtained for four distinct disease outcomes, including an increased odds of osteoarthrosis (OR 1.23, 95% CI 1.11 to 1.35), other arthropathies (OR 1.22, 95% CI 1.12 to 1.33) and overweight (OR 1.28, 95% CI 1.05 to 1.56), and a lower odds of postmenopausal bleeding (OR 0.72, 95% CI 0.63 to 0.82). Evidence for an association between habitual coffee consumption and these four diseases was also supported by phenotypic associations with self-reported coffee consumption.

CONCLUSIONS

This large-scale MR-PheWAS provided little evidence for notable harm or benefit with respect to higher habitual coffee consumption. The only evidence for harm was seen with respect to osteoarthrosis, other arthropathies and obesity.

White Blood Cells and Blood Pressure: A Mendelian Randomization Study

BACKGROUND

High blood pressure (BP) is a risk factor for cardiovascular morbidity and mortality. While BP is regulated by the function of kidney, vasculature, and sympathetic nervous system, recent experimental data suggest that immune cells may play a role in hypertension.

METHODS

We studied the relationship between major white blood cell types and blood pressure in the UK Biobank population and used Mendelian randomization (MR) analyses using the ≈750 000 UK-Biobank/International Consortium of Blood Pressure-Genome-Wide Association Studies to examine which leukocyte populations may be causally linked to BP.

RESULTS

A positive association between quintiles of lymphocyte, monocyte, and neutrophil counts, and increased systolic BP, diastolic BP, and pulse pressure was observed (eg, adjusted systolic BP mean±SE for 1st versus 5th quintile respectively: 140.13±0.08 versus 141.62±0.07 mm Hg for lymphocyte, 139.51±0.08 versus 141.84±0.07 mm Hg for monocyte, and 137.96±0.08 versus 142.71±0.07 mm Hg for neutrophil counts; all P<10^-50). Using 121 single nucleotide polymorphisms in MR, implemented through the inverse-variance weighted approach, we identified a potential causal relationship of lymphocyte count with systolic BP and diastolic BP (causal estimates: 0.69 [95% CI, 0.19-1.20] and 0.56 [95% CI, 0.23-0.90] of mm Hg per 1 SD genetically elevated lymphocyte count, respectively), which was directionally concordant to the observational findings. These inverse-variance weighted estimates were consistent with other robust MR methods. The exclusion of rs3184504 SNP in the SH2B3 locus attenuated the magnitude of the signal in some of the MR analyses. MR in the reverse direction found evidence of positive effects of BP indices on counts of monocytes, neutrophils, and eosinophils but not lymphocytes or basophils. Subsequent MR testing of lymphocyte count in the context of genetic correlation with renal function or resting and postexercise heart rate demonstrated a positive association of lymphocyte count with urine albumin-to-creatinine ratio.

CONCLUSIONS

Observational and genetic analyses demonstrate a concordant, positive and potentially causal relationship of lymphocyte count with systolic BP and diastolic BP.

Mendelian Randomization analysis of the causal effect of adiposity on hospital costs

Estimates of the marginal effect of measures of adiposity such as body mass index (BMI) on healthcare costs are important for the formulation and evaluation of policies targeting adverse weight profiles. Most estimates of this association are affected by endogeneity bias. We use a novel identification strategy exploiting Mendelian Randomization - random germline genetic variation modelled using instrumental variables - to identify the causal effect of BMI on inpatient hospital costs. Using data on over 300,000 individuals, the effect size per person per marginal unit of BMI per year varied according to specification, including £21.22 (95% confidence interval (CI): £14.35-£28.07) for conventional inverse variance weighted models to £18.85 (95% CI: £9.05-£28.65) for penalized weighted median models. Effect sizes from Mendelian Randomization models were larger in most cases than non-instrumental variable multivariable adjusted estimates (£13.47, 95% CI: £12.51-£14.43). There was little evidence of non-linearity. Within-family estimates, intended to address dynastic biases, were imprecise.

Night shift work and cardiovascular disease biomarkers in female nurses

BACKGROUND

Night shift work is associated with cardiovascular disease, but its associations with cardiovascular disease biomarkers are unclear. We investigated these associations in a study of female nurses.

METHODS

We used data from the Nurses' Health Study II for total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, C-reactive protein (CRP), and fibrinogen. The sample sizes for our analysis ranged from 458 (fibrinogen) to 3574 (total cholesterol). From questionnaires, we determined the number of night shifts worked in the 2 weeks before blood collection and total years of rotating night shift work. We used quantile regression to estimate differences in biomarker levels by shift work history, adjusting for potential confounders.

RESULTS

Nurses working 1 to 4 recent night shifts had median HDL cholesterol levels 4.4 mg/dL (95% confidence interval [CI]: 0.3, 7.5) lower than nurses without recent night shifts. However, working ≥5 recent night shifts and years of rotating night shift work were not associated with HDL cholesterol. There was no association between recent night shifts and CRP, but median CRP levels were 0.1 (95% CI: 0.0, 0.2), 0.2 (95% CI: 0.1, 0.4), and 0.2 (95% CI: 0.0, 0.4) mg/L higher among nurses working rotating night shifts for 1 to 5, 6 to 9, and ≥10 years compared with nurses never working rotating night shifts. These associations were attenuated when excluding postmenopausal women and women taking statins. We observed no associations between night shift work and other biomarkers.

CONCLUSIONS

We found suggestive evidence of adverse short-term and long-term effects of night shift work on select cardiovascular disease biomarkers.

Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis

BACKGROUND

Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. Using genetic instruments for lipoprotein lipid traits implemented through multivariable Mendelian randomisation (MR), we sought to compare their causal roles in the aetiology of CHD.

METHODS AND FINDINGS

We conducted a genome-wide association study (GWAS) of circulating non-fasted lipoprotein lipid traits in the UK Biobank (UKBB) for low-density lipoprotein (LDL) cholesterol, triglycerides, and apolipoprotein B to identify lipid-associated single nucleotide polymorphisms (SNPs). Using data from CARDIoGRAMplusC4D for CHD (consisting of 60,801 cases and 123,504 controls), we performed univariable and multivariable MR analyses. Similar GWAS and MR analyses were conducted for high-density lipoprotein (HDL) cholesterol and apolipoprotein A-I. The GWAS of lipids and apolipoproteins in the UKBB included between 393,193 and 441,016 individuals in whom the mean age was 56.9 y (range 39-73 y) and of whom 54.2% were women. The mean (standard deviation) lipid concentrations were LDL cholesterol 3.57 (0.87) mmol/L and HDL cholesterol 1.45 (0.38) mmol/L, and the median triglycerides was 1.50 (IQR = 1.11) mmol/L. The mean (standard deviation) values for apolipoproteins B and A-I were 1.03 (0.24) g/L and 1.54 (0.27) g/L, respectively. The GWAS identified multiple independent SNPs associated at P < 5 × 10-8 for LDL cholesterol (220), apolipoprotein B (n = 255), triglycerides (440), HDL cholesterol (534), and apolipoprotein A-I (440). Between 56%-93% of SNPs identified for each lipid trait had not been previously reported in large-scale GWASs. Almost half (46%) of these SNPs were associated at P < 5 × 10-8 with more than one lipid-related trait. Assessed individually using MR, LDL cholesterol (odds ratio [OR] 1.66 per 1-standard-deviation-higher trait; 95% CI: 1.49-1.86; P < 0.001), triglycerides (OR 1.34; 95% CI: 1.25-1.44; P < 0.001) and apolipoprotein B (OR 1.73; 95% CI: 1.56-1.91; P < 0.001) had effect estimates consistent with a higher risk of CHD. In multivariable MR, only apolipoprotein B (OR 1.92; 95% CI: 1.31-2.81; P < 0.001) retained a robust effect, with the estimate for LDL cholesterol (OR 0.85; 95% CI: 0.57-1.27; P = 0.44) reversing and that of triglycerides (OR 1.12; 95% CI: 1.02-1.23; P = 0.01) becoming weaker. Individual MR analyses showed a 1-standard-deviation-higher HDL cholesterol (OR 0.80; 95% CI: 0.75-0.86; P < 0.001) and apolipoprotein A-I (OR 0.83; 95% CI: 0.77-0.89; P < 0.001) to lower the risk of CHD, but these effect estimates attenuated substantially to the null on accounting for apolipoprotein B. A limitation is that, owing to the nature of lipoprotein metabolism, measures related to the composition of lipoprotein particles are highly correlated, creating a challenge in making exclusive interpretations on causation of individual components.

CONCLUSIONS

These findings suggest that apolipoprotein B is the predominant trait that accounts for the aetiological relationship of lipoprotein lipids with risk of CHD.

Exploiting horizontal pleiotropy to search for causal pathways within a Mendelian randomization framework

In Mendelian randomization (MR) analysis, variants that exert horizontal pleiotropy are typically treated as a nuisance. However, they could be valuable in identifying alternative pathways to the traits under investigation. Here, we develop MR-TRYX, a framework that exploits horizontal pleiotropy to discover putative risk factors for disease. We begin by detecting outliers in a single exposure-outcome MR analysis, hypothesising they are due to horizontal pleiotropy. We search across hundreds of complete GWAS summary datasets to systematically identify other (candidate) traits that associate with the outliers. We develop a multi-trait pleiotropy model of the heterogeneity in the exposure-outcome analysis due to pathways through candidate traits. Through detailed investigation of several causal relationships, many pleiotropic pathways are uncovered with already established causal effects, validating the approach, but also alternative putative causal pathways. Adjustment for pleiotropic pathways reduces the heterogeneity across the analyses.

Sarcopenia-related traits and coronary artery disease: a bi-directional Mendelian randomization study

Previous Mendelian randomization (MR) studies have yielded a conflicting causal relationship between sarcopenia and coronary artery disease (CAD), and lack the association of CAD with sarcopenia. We performed a bi-directional MR approach to clarify the causality and causal direction between sarcopenia-related traits and CAD. In stage 1 analysis, estimates of inverse variance weighting (IVW) and several sensitivity analyses were obtained by applying genetic variants that predict sarcopenia-related traits to CAD. Conversely, we also applied genetic variants that predict CAD to sarcopenia-related traits in stage 2 analyses. IVW analysis showed that higher handgrip strength reduces risk for CAD: A 1-kilogram (kg) increase in genetically determined left handgrip strength reduced odds of CAD by 36% [odds ratio (OR) = 0.64, 95% confidence interval (CI) 0.498 - 0.821, p = 4.56E-04], and right handgrip strength reduced odds of CAD by 41.1% (OR = 0.599, 95% CI 0.476 - 0.753, p = 1.10E-05). However, genetically predicted CAD did not show any causal association with handgrip strength, and no significant causal relationship was detected between genetically instrumented body lean mass and CAD. Our results suggest that decreased muscle strength but not decreased muscle mass leads to the increased risk of CAD in sarcopenia.