A Mendelian randomization study of the effect of type-2 diabetes on coronary heart disease

Mendelian randomization analyses clarify the effects of height on cardiovascular diseases

An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested causal association. However, the extent to which the effect estimated by MR can be explained by cardiovascular, anthropometric, lung function, and lifestyle-related risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized a well-powered set of genetic instruments for human stature, comprising >1,800 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 0.02). However, multivariable analyses demonstrated independent effects of height on other cardiovascular traits beyond CAD, consistent with epidemiologic associations and univariable MR experiments. In contrast with published reports, we observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest the impact of height on CAD risk beyond previously established cardiovascular risk factors is minimal and not explained by lung function measures.

Bidirectional relationship between type 2 diabetes mellitus and coronary artery disease: Prospective cohort study and genetic analyses

BACKGROUND

While type 2 diabetes mellitus (T2DM) is considered a putative causal risk factor for coronary artery disease (CAD), the intrinsic link underlying T2DM and CAD is not fully understood. We aimed to highlight the importance of integrated care targeting both diseases by investigating the phenotypic and genetic relationships between T2DM and CAD.

METHODS

We evaluated phenotypic associations using data from the United Kingdom Biobank ( N = 472,050). We investigated genetic relationships by leveraging genomic data conducted in European ancestry for T2DM, with and without adjustment for body mass index (BMI) (T2DM: Ncase / Ncontrol = 74,124/824,006; T2DM adjusted for BMI [T2DM adj BMI]: Ncase / Ncontrol = 50,409/523,897) and for CAD ( Ncase / Ncontrol = 181,522/984,168). We performed additional analyses using genomic data conducted in multiancestry individuals for T2DM ( Ncase / Ncontrol = 180,834/1,159,055).

RESULTS

Observational analysis suggested a bidirectional relationship between T2DM and CAD (T2DM→CAD: hazard ratio [HR] = 2.12, 95% confidence interval [CI]: 2.01-2.24; CAD→T2DM: HR = 1.72, 95% CI: 1.63-1.81). A positive overall genetic correlation between T2DM and CAD was observed ( rg = 0.39, P = 1.43 × 10 -75 ), which was largely independent of BMI (T2DM adj BMI-CAD: rg = 0.31, P = 1.20 × 10 -36 ). This was corroborated by six local signals, among which 9p21.3 showed the strongest genetic correlation. Cross-trait meta-analysis replicated 101 previously reported loci and discovered six novel pleiotropic loci. Mendelian randomization analysis supported a bidirectional causal relationship (T2DM→CAD: odds ratio [OR] = 1.13, 95% CI: 1.11-1.16; CAD→T2DM: OR = 1.12, 95% CI: 1.07-1.18), which was confirmed in multiancestry individuals (T2DM→CAD: OR = 1.13, 95% CI: 1.10-1.16; CAD→T2DM: OR = 1.08, 95% CI: 1.04-1.13). This bidirectional relationship was significantly mediated by systolic blood pressure and intake of 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors, with mediation proportions of 54.1% (95% CI: 24.9-83.4%) and 90.4% (95% CI: 29.3-151.5%), respectively.

CONCLUSION

Our observational and genetic analyses demonstrated an intrinsic bidirectional relationship between T2DM and CAD and clarified the biological mechanisms underlying this relationship.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

SYSTEMATIC REVIEW REGISTRATION

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

Disentangling Dual Threats: Premature Coronary Artery Disease and Early-Onset Type 2 Diabetes Mellitus in South Asians

South Asian individuals (SAs) face heightened risks of premature coronary artery disease (CAD) and early-onset type 2 diabetes mellitus (T2DM), with grave health, societal, and economic implications due to the region's dense population. Both conditions, influenced by cardiometabolic risk factors such as insulin resistance, hypertension, and central adiposity, manifest earlier and with unique thresholds in SAs. Epidemiological, demographic, nutritional, environmental, sociocultural, and economic transitions in SA have exacerbated the twin epidemic. The coupling of premature CAD and T2DM arises from increased obesity due to limited adipose storage, early-life undernutrition, distinct fat thresholds, reduced muscle mass, and a predisposition for hepatic fat accumulation from certain dietary choices cumulatively precipitating a decline in insulin sensitivity. As T2DM ensues, the β-cell adaptive responses are suboptimal, precipitating a transition from compensatory hyperinsulinemia to β-cell decompensation, underscoring a reduced functional β-cell reserve in SAs. This review delves into the interplay of these mechanisms and highlights a prediabetes endotype tied to elevated vascular risk. Deciphering these mechanistic interconnections promises to refine stratification paradigms, surpassing extant risk-prediction strategies.

Molecular bases of comorbidities: present and future perspectives

Co-occurrence of diseases decreases patient quality of life, complicates treatment choices, and increases mortality. Analyses of electronic health records present a complex scenario of comorbidity relationships that vary by age, sex, and cohort under study. The study of similarities between diseases using 'omics data, such as genes altered in diseases, gene expression, proteome, and microbiome, are fundamental to uncovering the origin of, and potential treatment for, comorbidities. Recent studies have produced a first generation of genetic interpretations for as much as 46% of the comorbidities described in large cohorts. Integrating different sources of molecular information and using artificial intelligence (AI) methods are promising approaches for the study of comorbidities. They may help to improve the treatment of comorbidities, including the potential repositioning of drugs.

Causal associations between type 1 diabetes mellitus and cardiovascular diseases: a Mendelian randomization study

BACKGROUND

The presence of type 1 diabetes mellitus (T1DM) has been demonstrated to pose an increased risk for developing cardiovascular diseases (CVDs). However, the causal relationships between T1DM and CVDs remain unclear due to the uncontrolled confounding factors and reverse causation bias of the observational studies.

METHODS

Summary statistics of T1DM and seven CVDs from the largest available genome-wide association studies (GWAS) of European ancestry and FinnGen biobank were extracted for the primary MR analysis, and the analysis was replicated using UK biobank (UKBB) for validation. Three complementary methods: inverse variance weighted (IVW), weighted median, and MR-Egger were used for the MR estimates. The potential pleiotropic effects were assessed by MR-Egger intercept and MR-PRESSO global test. Additionally, multivariable MR (MVMR) analysis was performed to examine whether T1DM has independent effects on CVDs with adjustment of potential confounding factors. Moreover, a two-step MR approach was used to assess the potential mediating effects of these factors on the causal effects between T1DM and CVDs.

RESULTS

Causal effects of T1DM on peripheral atherosclerosis (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 1.02-1.10; p = 0.002)] and coronary atherosclerosis (OR = 1.03, 95% CI: 1.01-1.05; p = 0.001) were found. The results were less likely to be biased by the horizontal pleiotropic effects (both p values of MR-Egger intercept and MR-PRESSO Global test > 0.05). In the following MVMR analysis, we found the causal effects of T1DM on peripheral atherosclerosis and coronary atherosclerosis remain significant after adjusting for a series of potential confounding factors. Moreover, we found that hypertension partly mediated the causal effects of T1DM on peripheral atherosclerosis (proportion of mediation effect in total effect: 11.47%, 95% CI: 3.23-19.71%) and coronary atherosclerosis (16.84%, 95% CI: 5.35-28.33%). We didn't find significant causal relationships between T1DM and other CVDs, including heart failure (HF), coronary artery disease (CAD), atrial fibrillation (AF), myocardial infarction (MI) and stroke. For the reverse MR from CVD to T1DM, no significant causal relationships were identified.

CONCLUSION

This MR study provided evidence supporting the causal effect of T1DM on peripheral atherosclerosis and coronary atherosclerosis, with hypertension partly mediating this effect.

Cardiovascular Implications of Metabolic Dysfunction-Associated Fatty Liver Disease

Both nonalcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated fatty liver disease (MAFLD) have been associated with incident cardiovascular disease (CVD), independent of confounders. Causality has recently been inferred by Mendelian randomization studies. Although these findings have contributed to current guidelines that recommend screening for and treatment of cardiovascular risk factors, it not yet clear how to position NAFLD/MAFLD in cardiovascular risk estimation scores and, consequently, which treatment targets should be used. This review aims to provide practical tools as well as suggestions for further research in order to effectively prevent CVD events in patients with NAFLD/MAFLD.

Qualitative and quantitative analysis of the chemical components in Yuquan capsules by using ultra-performance liquid chromatography-mass spectrometry

The Yuquan capsules is a commonly used traditional Chinese Patent Medicine used for the treatment of diabetes mellitus. In this study, a high-throughput analytical method for identifying the chemical composition of Yuquan capsules was established for the first time by using ultra-performance liquid chromatography-quadrupole time of flight mass spectrometry. The data obtained were subjected to fragment analysis and this was combined with UNIFI processing of natural products. One-hundred sixteen compounds were characterized from Yuquan capsules. Twelve of the bioactive compounds were quantitatively analyzed by ultra-performance liquid chromatography-tandem triple quadrupole mass spectrometry. This study was undertaken to obtain a comprehensive chemical profile analysis as well as to evaluate the overall quality of Yuquan capsules. The results will provide a reference for the quality evaluation of different Yuquan preparations. In addition, the data will enable basic pharmacodynamic research into these extensively used capsules.

Mendelian randomization analyses clarify the effects of height on cardiovascular diseases

An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested causal association. However, the extent to which the effect estimated by MR can be explained by established cardiovascular risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized a well-powered set of genetic instruments for human stature, comprising >1,800 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 0.02). However, multivariable analyses demonstrated independent effects of height on other cardiovascular traits beyond CAD, consistent with epidemiologic associations and univariable MR experiments. In contrast with published reports, we observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest the impact of height on CAD risk beyond previously established cardiovascular risk factors is minimal and not explained by lung function measures.

Examining the causal effect of type 2 diabetes on ischemic heart disease - A longitudinal study with four measurements (1980-2017)

OBJECTIVE

This longitudinal study examines a possible causal effect between type 2 diabetes and ischemic heart disease (IHD) by using measurements on four occasions from the Swedish Statistics on Income and Living Conditions (SILC) together with nationwide healthcare registers.

METHODS

This was a longitudinal study based on a random sample of men and women (n = 2014) from the Swedish population with four measurements in the SILC every eight years. Baseline was 1980/81 and the participants were followed for up to 37 years. The mean age and age range at baseline were 36.5 and 20-59 years, respectively. The study used Marginal Structural Modeling (MSM-Cox) to account for time-varying exposures by implementing inverse probability weighting (IPTW). MSM-Cox with IPTW was compared with Cox proportional hazard modelling.

RESULTS

The hazard ratio (HR) for IHD (369 cases) with 95% confidence interval (CI) in participants with type 2 diabetes (11.1%) compared to participants without type 2 diabetes (88.9%) was significantly higher (1.99; CI = 1.15 - 3.44) when using MSM-Cox with IPTW after adjustments for clinical and sociodemographic risk factors. When applying Cox proportional hazard models adjusted for the same variables, the HR was lower and non-significant at 1.34 (CI = 0.94 - 1.98).

CONCLUSIONS

This longitudinal study with four measurements assessed a possible causal association between type 2 diabetes and IHD by applying MSM-Cox with IPTW. Although causality cannot be determined due to the remaining risk of residual bias, the results may help to elucidate a potential causal relationship between type 2 diabetes and IHD. Further causal studies on possible underlying mechanisms are, however, needed.

Genetic correlation and gene-based pleiotropy analysis for four major neurodegenerative diseases with summary statistics

Recent genome-wide association studies suggested shared genetic components between neurodegenerative diseases. However, pleiotropic association patterns among them remain poorly understood. We here analyzed 4 major neurodegenerative diseases including Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS), and found suggestively positive genetic correlation. We next implemented a gene-centric pleiotropy analysis with a powerful method called PLACO and detected 280 pleiotropic associations (226 unique genes) with these diseases. Functional analyses demonstrated that these genes were enriched in the pancreas, liver, heart, blood, brain, and muscle tissues; and that 42 pleiotropic genes exhibited drug-gene interactions with 341 drugs. Using Mendelian randomization, we discovered that AD and PD can increase the risk of developing ALS, and that AD and ALS can also increase the risk of developing FTD, respectively. Overall, this study provides in-depth insights into shared genetic components and causal relationship among the 4 major neurodegenerative diseases, indicating genetic overlap and causality commonly drive their co-occurrence. It also has important implications on the etiology understanding, drug development and therapeutic targets for neurodegenerative diseases.

A Guide for Selection of Genetic Instruments in Mendelian Randomization Studies of Type 2 Diabetes and HbA1c: Toward an Integrated Approach

In this study we examine the instrument selection strategies currently used throughout the type 2 diabetes and HbA1c Mendelian randomization (MR) literature. We then argue for a more integrated and thorough approach, providing a framework to do this in the context of HbA1c and diabetes. We conducted a literature search for MR studies that have instrumented diabetes and/or HbA1c. We also used data from the UK Biobank (UKB) (N = 349,326) to calculate instrument strength metrics that are key in MR studies (the F statistic for average strength and R2 for total strength) with two different methods ("individual-level data regression" and Cragg-Donald formula). We used a 157-single nucleotide polymorphism (SNP) instrument for diabetes and a 51-SNP instrument (with partition into glycemic and erythrocytic as well) for HbA1c. Our literature search yielded 48 studies for diabetes and 22 for HbA1c. Our UKB empirical examples showed that irrespective of the method used to calculate metrics of strength and whether the instrument was the main one or included partition by function, the HbA1c genetic instrument is strong in terms of both average and total strength. For diabetes, a 157-SNP instrument was shown to have good average strength and total strength, but these were both substantially lesser than those of the HbA1c instrument. We provide a careful set of five recommendations to researchers who wish to genetically instrument type 2 diabetes and/or HbA1c. In MR studies of glycemia, investigators should take a more integrated approach when selecting genetic instruments, and we give specific guidance on how to do this.

Relationship between NAFLD and coronary artery disease: A Mendelian randomization study

BACKGROUND AND AIMS

There is an ongoing debate on whether NAFLD is an active contributor or an innocent bystander in the pathogenesis of coronary artery disease (CAD). The aim of the present study was to assess the causal relationship between NAFLD and CAD.

APPROACH AND RESULTS

We performed two-sample Mendelian randomization (MR) analyses using summary-level data to assess the association between genetically predicted NAFLD (i.e., chronically elevated serum alanine aminotransferase levels [cALT], imaging-based and biopsy-confirmed NAFLD) and risk of CAD. Analyses were repeated after exclusion of NAFLD susceptibility genes that are associated with impaired VLDL secretion.Inverse-variance weighted MR analyses showed a statistically significant association between genetically predicted cALT and risk of CAD (OR: 1.116, 95% CI: 1.039, 1.199), but not for the other NAFLD-related traits (OR: 1.046, 95% CI: 0.764, 1.433 and OR: 1.014, 95% CI: 0.968, 1.062 for imaging-based and biopsy-confirmed NAFLD, respectively). MR-Egger regression revealed a statistically significant intercept, indicative of directional pleiotropy, for all traits. Repeat analyses after exclusion of genes associated with impaired VLDL secretion showed consistent associations between genetically predicted NAFLD and CAD for all traits (i.e., cALT [OR: 1.203, 95% CI: 1.113, 1.300]), imaging-based (OR: 2.149, 95% CI: 1.276, 3.620) and biopsy-confirmed NAFLD (OR: 1.113, 95% CI: 1.041, 1.189), which persisted when more stringent biopsy-confirmed NAFLD criteria were used (OR: 1.154, 95% CI: 1.043, 1.278) or when more stringent MR methods were applied. MR-Egger regression did not show a statistically significant intercept.

CONCLUSION

The two-sample MR analyses showed a robust association between genetically predicted NAFLD and CAD after exclusion of genetic variants that are implicated in impaired VLDL secretion.

Causal effects of genetically predicted type 2 diabetes mellitus on blood lipid profiles and concentration of particle-size-determined lipoprotein subclasses: A two-sample Mendelian randomization study

Background

Observational studies have shown inconsistent results of the associations between type 2 diabetes mellitus (T2DM) and blood lipid profiles, while there is also a lack of evidence from randomized controlled trials (RCTs) for the causal effects of T2DM on blood lipid profiles and lipoprotein subclasses.

Objectives

Our study aimed at investigating the causal effects of T2DM on blood lipid profiles and concentration of particle-size-determined lipoprotein subclasses by using the two-sample Mendelian randomization (MR) method.

Methods

We obtained genetic variants for T2DM and blood lipid profiles including high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglycerides (TG), and total cholesterol (TC) from international genome-wide association studies (GWASs). Two-sample MR method was applied to explore the potential causal effects of genetically predicted T2DM on blood lipid profiles based on different databases, respectively, and results from each MR analysis were further meta-analyzed to obtain the summary results. The causal effects of genetically predicted T2DM on the concentration of different subclasses of lipoproteins that are determined by particle size were also involved in MR analysis.

Results

Genetically predicted 1-unit higher log odds of T2DM had a significant causal effect on a higher level of TG (estimated β coefficient: 0.03, 95% confidence interval [CI]: 0.00 to 0.06) and lower level of HDL-C (estimated β coefficient: −0.09, 95% CI: −0.11 to −0.06). The causality of T2DM on the level of TC or LDL-C was not found (estimated β coefficient: −0.01, 95% CI: −0.02 to 0.01 for TC and estimated β coefficient: 0.01, 95% CI: −0.01 to 0.02 for LDL-C). For different sizes of lipoprotein particles, 1-unit higher log odds of T2DM was causally associated with higher level of small LDL particles, and lower level of medium HDL particles, large HDL particles, and very large HDL particles.

Conclusion

Evidence from our present study showed causal effects of T2DM on the level of TG, HDL-C, and concentration of different particle sizes of lipoprotein subclasses comprehensively, which might be particularly helpful in illustrating dyslipidemia experienced by patients with T2DM, and further indicate new treatment targets for these patients to prevent subsequent excessive cardiovascular events from a genetic point of view.

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

AIMS/HYPOTHESIS

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

METHODS

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

RESULTS

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

CONCLUSIONS/INTERPRETATION

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

Genetic Predisposition to Diabetes and Abdominal Aortic Aneurysm: A Two Stage Mendelian Randomisation Study

OBJECTIVE

Observational studies demonstrate an inverse association between type II diabetes and abdominal aortic aneurysm (AAA) for reasons that are unclear. The aim of this study was to clarify the causal association between type II diabetes predisposition and AAA using Mendelian randomisation.

METHODS

Effect estimates for single nucleotide polymorphisms (SNPs) associated with diabetes were obtained from the DIAbetes Meta-ANalysis of Trans-Ethnic association studies (DIAMANTE) consortium to construct a genetic instrumental variable. Corresponding effect estimates for associations of these SNPs with AAA were obtained from the International Aneurysm Consortium comprising six separate AAA genomewide association studies (4 972 cases and 99 858 controls). Mendelian randomisation estimates were calculated using inverse variance, weighted median, and MR-Egger methods, and compared against recently published observational estimates.

RESULTS

A genetic risk score was constructed from 206 SNPs associated with diabetes. All three Mendelian randomisation models showed no effect of genetic liability to diabetes and risk of AAA (inverse variance: odds ratio 1.04 per unit higher log odds, 95% 0.98 - 1.11, p = .19; MR-Egger slope p = .33; weighted median p = .50). Results were similar after excluding the TCF7L2 locus (inverse variance p = .075). Findings from the Mendelian randomisation analysis differed from previous observational reports of an inverse association (pdif < .001).

CONCLUSION

Lifelong genetic predisposition to diabetes does not appear to protect against AAA. These findings differ from traditional epidemiological studies showing an inverse association between diabetes and AAA, for reasons that remain unclear.

Roles of Cardiometabolic Factors in Mediating the Causal Effect of Type 2 Diabetes on Cardiovascular Diseases: A Two-Step, Two-Sample Multivariable Mendelian Randomization Study

Objective

The objective of this study is to investigate the roles of cardiometabolic factors (including blood pressure, blood lipids, thyroid function, body mass, and insulin sensitivity) in mediating the causal effect of type 2 diabetes (T2DM) on cardiovascular disease (CVD) outcomes.

Design

Two-step, two-sample multivariable Mendelian randomization (MVMR) study.

Setting

International genome-wide association study (GWAS) consortia data.

Exposure

Type 2 diabetes, blood pressure: systolic blood pressure (SBP), diastolic blood pressure (DBP); blood lipids: low-density lipoprotein (LDL), high-density lipoprotein (HDL), total cholesterol (TC), triglycerides (TG); thyroid function: hyperthyroidism, hypothyroidism; body mass index (BMI), waist-hip-ratio (WHR), and insulin sensitivity.

Main Outcomes

Cardiovascular disease includes coronary heart disease (CHD), myocardial infarction (MI), and stroke.

Methods

Summary-level data for exposures and main outcomes were extracted from GWAS consortia. We used two-sample MR to illustrate the causal effect of T2DM on CVD subtypes and regression-based MVMR to quantify the possible mediation effects of cardiometabolic factors on CVD.

Results

Each additional unit of log odds of T2DM increased 16% risk of CHD [odds ratio (OR): 1.16, 95% CI: 1.12–1.21], 15% risk of myocardial infarction (MI) (OR: 1.15, 95% CI: 1.10–1.20), and 10% risk of stroke (OR: 1.10, 95% CI: 1.06–1.13). In mediation analysis, SBP, DBP, and TG were found as main mediators, while the mediation effects of other cardiometabolic factors were not significant. The proportion of total effect of T2DM on CHD mediated by SBP, DBP, and TG was 16% (95% CI: 8–24%), 7% (95% CI: 1–13%) and 10% (95% CI: 2–18%), respectively. Mediation effect of SBP and DBP on MI and stroke, TG on MI was also prominent, while mediation effect of TG on stroke was not significant. The combined mediation effect of all the three mediators accounted for 29%, 26%, and 13% of the total effect of T2DM on CHD, MI, and stroke, respectively.

Conclusion

Systolic blood pressure, DBP, and TG mediate a substantial proportion of the causal effect of T2DM on CVD and thus interventions on these factors might reduce the considerable excess risk of CVD among patients with T2DM.

Robust estimates of heritable coronary disease risk in individuals with type 2 diabetes

Type 2 diabetes (T2D) is an important heritable risk factor for coronary artery disease (CAD), the risk of both diseases being increased by metabolic syndrome (MS). With the availability of large-scale genome-wide association data, we aimed to elucidate the genetic burden of CAD risk in T2D predisposed individuals within the context of MS and their shared genetic architecture. Mendelian randomization (MR) analyses supported a causal relationship between T2D and CAD [odds ratio (OR) = 1.13 per log-odds unit 95% confidence interval (CI): 1.10-1.16; p = 1.59 × 10-17 ]. Simultaneously adjusting MR analyses for the effects of the T2D instrument including blood pressure, dyslipidaemia, and obesity attenuated the association between T2D and CAD (OR = 1.07, 95% CI: 1.04-1.11). Bayesian locus-overlap analysis identified 44 regions with the same causal variant underlying T2D and CAD genetic signals (FDR < 1%) at a posterior probability >0.7; five (MHC, LPL, ABO, RAI1 and MC4R) of these regions contain genome-wide significant (p < 5 × 10-8 ) associations for both traits. Given the small effect sizes observed in genome-wide association studies for complex diseases, even with 44 potential target regions, this has implications for the likely magnitude of CAD risk reduction that might be achievable by pure T2D therapies.

Management of diabetic foot ulcers and the challenging points: An endocrine view

Diabetic foot ulcers (DFU) are one of the most challenging complications of diabetes. Up to one-third of patients with diabetes mellitus (DM) may suffer from DFUs during their life. DFU is one of the leading causes of morbidity in patients with DM. The treatment period is challenging, and the recurrence rate of DFUs is high. Hence, establishing prevention strategies is the most important point to be emphasized. A multidisciplinary approach is necessary in the prevention and treatment of DFUs. Patients at risk should be identified, and prevention measures should be taken based on the risk category. Once a DFU is formed, the appropriate classification and evidence-based treatment interventions should be executed. Glycemic control, diagnosis and treatment of vascular disease, local wound care, diagnosis, and treatment of infection should be addressed along with the proper evaluation and management of general health status.

Systolic blood pressure as the mediator of the effect of early menarche on the risk of coronary artery disease: A Mendelian randomization study

Background

Menarche timing may not be directly associated with the risk of coronary artery disease (CAD). Therefore, we investigated the roles of metabolic factors in explaining the effect of age at menarche on CAD risk.

Methods

We identified women with age at menarche and CAD by using three analytical methods: Mendelian randomization (MR), logistic regression analysis, and Cox proportional hazard regression. The first two analyses were performed in the Taiwan Biobank (N = 71,923) study, and the last analysis was performed in the Chin-Shan Community Cardiovascular Cohort study (N = 1,598). We further investigated the role of metabolic factors in mediating the effect of age at menarche on CAD risk by using three complementary methods with mediation analyses.

Results

One standard deviation of earlier age at menarche was associated with a 2% higher CAD risk [odds ratio = 1.02, 95% confidence interval (CI) = 1.001-1.03] in the MR analysis, an 11% higher risk (odds ratio = 1.11, 95% CI = 1.02-1.21) in the logistic regression analysis, and a 57% higher risk (hazard ratio = 1.57, 95% CI = 1.12-2.19) in the Cox proportional hazard regression. All the analyses consistently supported the role of systolic blood pressure in mediating this effect. The MR results indicated that 29% (95% CI = 26%-32%) of the effect of genetically predicted earlier age at menarche on CAD risk was mediated by genetically predicted systolic blood pressure.

Conclusion

The results obtained using different analytical methods suggest that interventions aimed at lowering systolic blood pressure can reduce the cases of CAD attributable to earlier age at menarche.

Assessing Causal Relationship Between Human Blood Metabolites and Five Neurodegenerative Diseases With GWAS Summary Statistics

Background: Neurodegenerative diseases (NDDs) are the leading cause of disability worldwide while their metabolic pathogenesis is unclear. Genome-wide association studies (GWASs) offer an unprecedented opportunity to untangle the relationship between metabolites and NDDs.

Methods: By leveraging two-sample Mendelian randomization (MR) approaches and relying on GWASs summary statistics, we here explore the causal association between 486 metabolites and five NDDs including Alzheimer’s Disease (AD), amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), Parkinson’s disease (PD), and multiple sclerosis (MS). We validated our MR results with extensive sensitive analyses including MR-PRESSO and MR-Egger regression. We also performed linkage disequilibrium score regression (LDSC) and colocalization analyses to distinguish causal metabolite-NDD associations from genetic correlation and LD confounding of shared causal genetic variants. Finally, a metabolic pathway analysis was further conducted to identify potential metabolite pathways.

Results: We detected 164 metabolites which were suggestively associated with the risk of NDDs. Particularly, 2-methoxyacetaminophen sulfate substantially affected ALS (OR = 0.971, 95%CIs: 0.961 ∼ 0.982, FDR = 1.04E-4) and FTD (OR = 0.924, 95%CIs: 0.885 ∼ 0.964, FDR = 0.048), and X-11529 (OR = 1.604, 95%CIs: 1.250 ∼ 2.059, FDR = 0.048) and X-13429 (OR = 2.284, 95%CIs: 1.457 ∼ 3.581, FDR = 0.048) significantly impacted FTD. These associations were further confirmed by the weighted median and maximum likelihood methods, with MR-PRESSO and the MR-Egger regression removing the possibility of pleiotropy. We also observed that ALS or FTD can alter the metabolite levels, including ALS and FTD on 2-methoxyacetaminophen sulfate. The LDSC and colocalization analyses showed that none of the identified associations could be driven by genetic correlation or confounding by LD with common causal loci. Multiple metabolic pathways were found to be involved in NDDs, such as “urea cycle” (P = 0.036), “arginine biosynthesis” (P = 0.004) on AD and “phenylalanine, tyrosine and tryptophan biosynthesis” (P = 0.046) on ALS.

Conclusion: our study reveals robust bidirectional causal associations between servaral metabolites and neurodegenerative diseases, and provides a novel insight into metabolic mechanism for pathogenesis and therapeutic strategies of these diseases.

A comprehensive gene-centric pleiotropic association analysis for 14 psychiatric disorders with GWAS summary statistics

BACKGROUND

Recent genome-wide association studies (GWASs) have revealed the polygenic nature of psychiatric disorders and discovered a few of single-nucleotide polymorphisms (SNPs) associated with multiple psychiatric disorders. However, the extent and pattern of pleiotropy among distinct psychiatric disorders remain not completely clear.

METHODS

We analyzed 14 psychiatric disorders using summary statistics available from the largest GWASs by far. We first applied the cross-trait linkage disequilibrium score regression (LDSC) to estimate genetic correlation between disorders. Then, we performed a gene-based pleiotropy analysis by first aggregating a set of SNP-level associations into a single gene-level association signal using MAGMA. From a methodological perspective, we viewed the identification of pleiotropic associations across the entire genome as a high-dimensional problem of composite null hypothesis testing and utilized a novel method called PLACO for pleiotropy mapping. We ultimately implemented functional analysis for identified pleiotropic genes and used Mendelian randomization for detecting causal association between these disorders.

RESULTS

We confirmed extensive genetic correlation among psychiatric disorders, based on which these disorders can be grouped into three diverse categories. We detected a large number of pleiotropic genes including 5884 associations and 2424 unique genes and found that differentially expressed pleiotropic genes were significantly enriched in pancreas, liver, heart, and brain, and that the biological process of these genes was remarkably enriched in regulating neurodevelopment, neurogenesis, and neuron differentiation, offering substantial evidence supporting the validity of identified pleiotropic loci. We further demonstrated that among all the identified pleiotropic genes there were 342 unique ones linked with 6353 drugs with drug-gene interaction which can be classified into distinct types including inhibitor, agonist, blocker, antagonist, and modulator. We also revealed causal associations among psychiatric disorders, indicating that genetic overlap and causality commonly drove the observed co-existence of these disorders.

CONCLUSIONS

Our study is among the first large-scale effort to characterize gene-level pleiotropy among a greatly expanded set of psychiatric disorders and provides important insight into shared genetic etiology underlying these disorders. The findings would inform psychiatric nosology, identify potential neurobiological mechanisms predisposing to specific clinical presentations, and pave the way to effective drug targets for clinical treatment.

Genetically Predicted Type 2 Diabetes Mellitus Liability, Glycated Hemoglobin and Cardiovascular Diseases: A Wide-Angled Mendelian Randomization Study

(1) Aim: To investigate the causal effects of T2DM liability and glycated haemoglobin (HbA1c) levels on various cardiovascular disease outcomes, both in the general population and in non-diabetic individuals specifically. (2) Methods: We selected 243 variants as genetic instruments for T2DM liability and 536 variants for HbA1c. Linear Mendelian randomization analyses were performed to estimate the associations of genetically-predicted T2DM liability and HbA1c with 12 cardiovascular disease outcomes in 367,703 unrelated UK Biobank participants of European ancestries. We performed secondary analyses in participants without diabetes (HbA1c < 6.5% with no diagnosed diabetes), and in participants without diabetes or pre-diabetes (HbA1c < 5.7% with no diagnosed diabetes). (3) Results: Genetically-predicted T2DM liability was positively associated (p < 0.004, 0.05/12) with peripheral vascular disease, aortic valve stenosis, coronary artery disease, heart failure, ischaemic stroke, and any stroke. Genetically-predicted HbA1c was positively associated with coronary artery disease and any stroke. Mendelian randomization estimates generally shifted towards the null when excluding diabetic and pre-diabetic participants from analyses. (4) Conclusions: This genetic evidence supports causal effects of T2DM liability and HbA1c on a range of cardiovascular diseases, suggesting that improving glycaemic control could reduce cardiovascular risk in a general population, with greatest benefit in individuals with diabetes.

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.

Current trends in epidemiology of cardiovascular disease and cardiovascular risk management in type 2 diabetes

With the advances in diabetes care, the trend of incident cardiovascular disease (CVD) in patients with type 2 diabetes mellitus (T2DM) has been decreasing over past decades. However, given that CVD is still a major cause of death in patients with diabetes and that the risk of CVD in patients with T2DM is more than twice that in those without DM, there are still considerable challenges to the prevention of CVD in diabetes. Accordingly, there have been several research efforts to decrease cardiovascular (CV) risk in T2DM. Large-scale genome-wide association studies (GWAS) and clinical cohort studies have investigated the effects of factors, such as genetic determinants, hypoglycaemia, and insulin resistance, on CVD and can account for the unexplained CV risk in T2DM. Lifestyle modification is a widely accepted cornerstone method to prevent CVD as the first-line strategy in T2DM. Recent reports from large CV outcome trials have proven the positive CV effects of sodium-glucose cotransporter-2 (SGLT-2) inhibitors and glucagon-like peptide-1 receptor agonists (GLP-1RAs) in patients with high CVD risk. Overall, current practice guidelines for the management of CVD in T2DM are moving from a glucocentric strategy to a more individualised patient-centred approach. This review will discuss the current epidemiologic trends of CVD in T2DM and the risk factors linking T2DM to CVD, including genetic contribution, hypoglycaemia, and insulin resistance, and proper care strategies, including lifestyle and therapeutic approaches.

Interpreting Mendelian-randomization estimates of the effects of categorical exposures such as disease status and educational attainment

Background

Mendelian randomization has been previously used to estimate the effects of binary and ordinal categorical exposures—e.g. Type 2 diabetes or educational attainment defined by qualification—on outcomes. Binary and categorical phenotypes can be modelled in terms of liability—an underlying latent continuous variable with liability thresholds separating individuals into categories. Genetic variants influence an individual’s categorical exposure via their effects on liability, thus Mendelian-randomization analyses with categorical exposures will capture effects of liability that act independently of exposure category.

Methods and results

We discuss how groups in which the categorical exposure is invariant can be used to detect liability effects acting independently of exposure category. For example, associations between an adult educational-attainment polygenic score (PGS) and body mass index measured before the minimum school leaving age (e.g. age 10 years), cannot indicate the effects of years in full-time education on this outcome. Using UK Biobank data, we show that a higher educational-attainment PGS is strongly associated with lower smoking initiation and higher odds of glasses use at age 15 years. These associations were replicated in sibling models. An orthogonal approach using the raising of the school leaving age (ROSLA) policy change found that individuals who chose to remain in education to age 16 years before the reform likely had higher liability to educational attainment than those who were compelled to remain in education to age 16 years after the reform, and had higher income, lower pack-years of smoking, higher odds of glasses use and lower deprivation in adulthood. These results suggest that liability to educational attainment is associated with health and social outcomes independently of years in full-time education.

Conclusions

Mendelian-randomization studies with non-continuous exposures should be interpreted in terms of liability, which may affect the outcome via changes in exposure category and/or independently.

PCSK9 E670G (rs505151) Variant and Coronary Artery Disease Risk Among Diabetics

Background: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is an enzyme in the family of proprotein convertases implicated in lipid metabolism and is a significant genetic risk factor in cardiovascular diseases among various populations. Aim of the Study: This study explored the correlation between the alleles of the rs505151 (E670G) locus of the PCSK9 gene and its expression levels with coronary artery disease (CAD) risk in Egyptian patients with type 2 diabetes mellitus (T2DM). Subjects and Methods: A case-control study was performed on 112 lean subjects compared to 100 T2DM patients without CAD and 84 T2DM patients with CAD to investigate the relationships among PCSK9 expression levels, the E670G (rs505151) gene variant, lipid concentrations, and CAD risk in an Egyptian diabetic population. A restriction fragment length polymorphism-polymerase chain reaction (PCR) assay was used to assess the gene polymorphism, and PCSK9 mRNA expression was determined by quantitative real-time PCR. Results: The prevalence of the E670G (rs505151) AG genotype in diabetics with CAD was significantly greater than the other two groups. The PCSK9 gene expression levels in diabetics with CAD were significantly greater than the other two groups. G allele carriers (AG+GG) had a higher relative PCSK9 expression than A allele carriers. Conclusion: PCSK9 relative expression levels and the E670G (rs505151) AG genotype are CAD risk factors among Egyptian diabetics and are linked positively to the atherogenic index of plasma.

Genetically Predicted Fibroblast Growth Factor 23 and Major Cardiovascular Diseases, Their Risk Factors, Kidney Function, and Longevity: A Two-Sample Mendelian Randomization Study

Introduction

Fibroblast growth factor 23 (FGF23), a potential biomarker for kidney function, is related to cardiovascular disease (CVD) and diabetes, although it is unclear whether the relation is causal. This study evaluated the associations of genetically predicted FGF23 with major CVDs, their risk factors, kidney function, and longevity using Mendelian randomization (MR).

Methods

This is a two-sample MR study using summary statistics from large genome-wide association studies. Primary outcomes included coronary artery disease (CAD), myocardial infarction, heart failure, and atrial fibrillation. Secondary outcomes included cardiovascular risk factors, kidney function, and longevity. We used four single-nucleotide polymorphisms (SNPs) predicting FGF23, excluding rs2769071 in the ABO gene, which likely violates the MR exclusion-restriction assumption. We used inverse-variance weighted (IVW) as the primary statistical method to assess associations of FGF23 with the outcomes. Sensitivity analyses included weighted median (WM) and MR-Egger. We repeated the analyses including all five SNPs. Last, we validated the positive findings from the main analyses in a smaller study, i.e., FinnGen.

Results

Using IVW, genetically predicted higher FGF23 was inversely associated with risk of CAD [odds ratio (OR): 0.69 per logtransformed FGF23 (pg/ml) increase, 95% confidence interval (CI): 0.52–0.91] and type 2 diabetes mellitus (T2DM) (OR: 0.70, 95% CI: 0.52–0.96), but not with the other outcomes. The WM and MR-Egger estimates were directionally consistent.

Conclusion

This study suggests that genetically predicted higher FGF23 may be protective against CAD and T2DM. Future studies should explore the underlying mechanisms related to the potential protective effect of FGF23. FGF23 was unlikely a cause of poorer renal function.

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

BACKGROUND

Higher body mass index (BMI) and waist-to-hip ratio (WHR) increase the risk of cardiovascular disease, but the extent to which this is mediated by blood pressure, diabetes, lipid traits, and smoking is not fully understood.

METHODS

Using consortia and UK Biobank genetic association summary data from 140,595 to 898,130 participants predominantly of European ancestry, Mendelian randomization mediation analysis was performed to investigate the degree to which systolic blood pressure (SBP), diabetes, lipid traits, and smoking mediated an effect of BMI and WHR on the risk of coronary artery disease (CAD), peripheral artery disease (PAD) and stroke.

RESULTS

The odds ratio of CAD per 1-standard deviation increase in genetically predicted BMI was 1.49 (95% CI 1.39 to 1.60). This attenuated to 1.34 (95% CI 1.24 to 1.45) after adjusting for genetically predicted SBP (proportion mediated 27%, 95% CI 3% to 50%), to 1.27 (95% CI 1.17 to 1.37) after adjusting for genetically predicted diabetes (41% mediated, 95% CI 18% to 63%), to 1.47 (95% CI 1.36 to 1.59) after adjusting for genetically predicted lipids (3% mediated, 95% -23% to 29%), and to 1.46 (95% CI 1.34 to 1.58) after adjusting for genetically predicted smoking (6% mediated, 95% CI -20% to 32%). Adjusting for all the mediators together, the estimate attenuated to 1.14 (95% CI 1.04 to 1.26; 66% mediated, 95% CI 42% to 91%). A similar pattern was observed when considering genetically predicted WHR as the exposure, and PAD or stroke as the outcome.

CONCLUSIONS

Measures to reduce obesity will lower the risk of cardiovascular disease primarily by impacting downstream metabolic risk factors, particularly diabetes and hypertension. Reduction of obesity prevalence alongside control and management of its mediators is likely to be most effective for minimizing the burden of obesity.

Impact of lung function on cardiovascular diseases and cardiovascular risk factors: a two sample bidirectional Mendelian randomisation study

INTRODUCTION

Observational studies suggested lung function is inversely associated with cardiovascular disease (CVD) although these studies could be confounded. We conducted a two sample Mendelian randomisation study using summary statistics from genome-wide association studies (GWAS) to clarify the role of lung function in CVD and its risk factors, and conversely the role of CVD in lung function.

METHODS

We obtained genetic instruments for forced expiratory volume in 1 s (FEV₁: 260) and forced vital capacity (FVC: 320) from publicly available UK Biobank summary statistics (n=421 986) and applied to GWAS summary statistics for coronary artery disease (CAD) (n=184 305), stroke (n=446 696), atrial fibrillation (n=1 030 836) and heart failure (n=977 320) and cardiovascular risk factors. Inverse variance weighting was used to assess the impact of lung function on these outcomes, with various sensitivity analyses. Bidirectional Mendelian randomisation was used to assess reverse causation.

RESULTS

FEV₁ and FVC were inversely associated with CAD (OR per SD increase, 0.72 (95% CI 0.63 to 0.82) and 0.70 (95%CI 0.62 to 0.78)), overall stroke (0.87 (95%CI 0.77 to 0.97), 0.90 (95% CI 0.82 to 1.00)) and some stroke subtypes. FEV₁ and FVC were inversely associated with type 2 diabetes and systolic blood pressure. Sensitivity analyses produced similar findings although the association with CAD was attenuated after adjusting for height (eg, OR for 1SD FEV₁0.95 (0.75 to 1.19), but not for stroke or type 2 diabetes. There was no strong evidence for reverse causation.

CONCLUSION

Higher lung function likely protect against CAD and stroke.

Elucidating causal effects of type 2 diabetes on ischemic heart disease from observational data on middle-aged Swedish women: a triangular analytical approach

The association between type 2 diabetes (T2D) and ischemic heart disease (IHD) is well established but the potential causal association needs further studying. In an attempt to elucidate the causal effect of T2D on IHD, we used three different analytical approaches in two different datasets. A well-defined cohort of 6047 women aged 50–59 years were included at baseline (1995 to 2000) and followed until 2015 for IHD. The median follow-up was 16.3 years. We used a Marginal Structural Cox model (MSM Cox) to account for time-varying exposure (time at onset of T2D) and for ten confounders (using inverse probability weighting, IPW). We also compared the MSM-Cox models with traditional Cox regression modelling in the cohort. Finally, we analyzed information on individuals from Swedish population-based registers with national coverage in a comprehensive co-relative design and extrapolated the results to MZ twins. The Hazard Ratio (HR) for IHD in relation to T2D at baseline and T2D occurring during the follow-up in the MSM Cox model weighted by IPW (based on the ten included confounders) was 1.43 (95% confidence interval [CI] 1.07–1.92). The corresponding HR from the traditional Cox regression model was of similar effect size. The average extrapolated MZ twin estimate from our co-relative model was 1.61 (95% CI 1.48–1.86). Our findings, based on a triangular approach, support the existence of a causal association between T2D and IHD and that preventive long-term measures in order to avoid or postpone IHD should include monitoring and treatment of both the T2D itself as well as other cardiovascular risk factors.

Dose-response relationship between genetically proxied average blood glucose levels and incident coronary heart disease in individuals without diabetes mellitus

AIMS/HYPOTHESIS

Our aim was to investigate the relationship between average blood glucose levels and incident CHD in individuals without diabetes mellitus.

METHODS

To investigate average blood glucose levels, we studied HbA_1c as predicted by 40 variants previously shown to be associated with both type 2 diabetes and HbA_1c. Linear and non-linear Mendelian randomisation analyses were performed to investigate associations with incident CHD risk in 324,830 European ancestry individuals from the UK Biobank without diabetes mellitus.

RESULTS

Every one mmol/mol increase in genetically proxied HbA_1c was associated with an 11% higher CHD risk (HR 1.11, 95% CI 1.05, 1.18). The dose-response curve increased at all levels of HbA_1c, and there was no evidence favouring a non-linear relationship over a linear one.

CONCLUSIONS/INTERPRETATIONS

In individuals without diabetes mellitus, lowering average blood glucose levels may reduce CHD risk in a dose-dependent way.

The Diabetes Syndrome - A Collection of Conditions with Common, Interrelated Pathophysiologic Mechanisms

The four basic pathophysiologic mechanisms which damage the β-cell within diabetes (ie, genetic and epigenetic changes, inflammation, an abnormal environment, and insulin resistance [IR]) also contribute to cell and tissue damage and elevate the risk of developing all typical diabetes-related complications. Genetic susceptibility to damage from abnormal external and internal environmental factors has been described including inflammation and IR. All these mechanisms can promote epigenetic changes, and in total, these pathophysiologic mechanisms interact and react with each other to cause damage to cells and tissues ultimately leading to disease. Importantly, these pathophysiologic mechanisms also serve to link other common conditions including cancer, dementia, psoriasis, atherosclerotic cardiovascular disease (ASCVD), nonalcoholic fatty liver disease (NAFLD), and nonalcoholic steatohepatitis (NASH). The “Diabetes Syndrome”, an overarching group of interrelated conditions linked by these overlapping mechanisms, can be viewed as a conceptual framework that can facilitate understanding of the inter-relationships of superficially disparate conditions. Recognizing the association of the conditions within the Diabetes Syndrome due to common pathophysiologies has the potential to provide both benefit to the patient (eg, prevention, early detection, precision medicine) and to the advancement of medicine (eg, driving education, research, and dynamic decision-based medical practice).

Genetically determined lean mass and dietary response

Weight loss attenuates many obesity-related co-morbidities, but is difficult to sustain with dietary change. Dietary adherence, not macronutrient composition, is a better predictor of weight loss. Weight loss-induced endocrine changes promote food intake and increase energy efficiency, contributing to the difficulty with dietary adherence and weight regain. Macronutrient preference is partly genetically determined, suggesting that personalized dietary interventions might be more successful. In this issue, Li et al. report that a genetic risk score comprising the cumulative weighted effects of variants previously associated with increased lean mass is associated with increased satiety and weight loss 6 months after initiating a low- but not a high-fat diet. The effects were attenuated by 2 years. These findings suggest that genetic variants may influence response to specific diet. Further studies are necessary to assess whether genetically determined lean mass is causally associated with dietary response. Significant progress has recently been made in identifying additional genetic determinants of lean mass, which will enable such investigations and potentially inform future nutritional studies.

Sex Differences in the Risk of Coronary Heart Disease Associated With Type 2 Diabetes: A Mendelian Randomization Analysis

OBJECTIVE

Observational studies have demonstrated that type 2 diabetes is a stronger risk factor for coronary heart disease (CHD) in women compared with men. However, it is not clear whether this reflects a sex differential in the causal effect of diabetes on CHD risk or results from sex-specific residual confounding.

RESEARCH DESIGN AND METHODS

Using 270 single nucleotide polymorphisms (SNPs) for type 2 diabetes identified in a type 2 diabetes genome-wide association study, we performed a sex-stratified Mendelian randomization (MR) study of type 2 diabetes and CHD using individual participant data in UK Biobank (251,420 women and 212,049 men). Weighted median, MR-Egger, MR-pleiotropy residual sum and outlier, and radial MR from summary-level analyses were used for pleiotropy assessment.

RESULTS

MR analyses showed that genetic risk of type 2 diabetes increased the odds of CHD for women (odds ratio 1.13 [95% CI 1.08-1.18] per 1-log unit increase in odds of type 2 diabetes) and men (1.21 [1.17-1.26] per 1-log unit increase in odds of type 2 diabetes). Sensitivity analyses showed some evidence of directional pleiotropy; however, results were similar after correction for outlier SNPs.

CONCLUSIONS

This MR analysis supports a causal effect of genetic liability to type 2 diabetes on risk of CHD that is not stronger for women than men. Assuming a lack of bias, these findings suggest that the prevention and management of type 2 diabetes for CHD risk reduction is of equal priority in both sexes.

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.

Vitamin D genes influence MS relapses in children

OBJECTIVE

The aim of this study was to determine whether a vitamin D genetic risk score (vitDGRS) is associated with 25-hydroxyvitamin D (25(OH)D) level and multiple sclerosis (MS) relapses in children.

METHODS

DNA samples were typed for single nucleotide polymorphisms (SNPs) from four genes previously identified to be associated with 25(OH)D levels. SNPs with strong associations with 25(OH)D after multiple comparison correction were used to create a genetic risk score (vitDGRS). Cox regression models tested associations of vitDGRS with relapse hazard.

RESULTS

Two independent SNPs within or near GC and NADSYN1/DHCR7 genes were strongly associated with 25(OH)D levels in the discovery cohort (n = 182) after Bonferroni correction. The vitDGRS of these SNPs explained 4.5% of the variance of 25(OH)D level after adjustment for genetic ancestry. Having the highest versus lowest vitDGRS was associated with 11 ng/mL lower 25(OH)D level (95% confidence interval (CI) = -17.5, -4.5, p = 0.001) in the discovery cohort. Adjusting for ancestry, sex, disease-modifying therapy (DMT), and HLA-DRB1*15 carrier status, the highest versus lowest vitDGRS was associated with 2.6-fold (95% CI = 1.37, 5.03, p = 0.004) and 2.0-fold (95% CI = 0.75, 5.20, p = 0.16) higher relapse hazard in the discovery and replication cohorts, respectively.

CONCLUSION

The vitDGRS identifies children at greater risk of relapse. These findings support a causal role for vitamin D in MS course.

Genetics Insights in the Relationship Between Type 2 Diabetes and Coronary Heart Disease

Diabetes mellitus is a major risk factor for coronary heart disease (CHD). The major form of diabetes mellitus is type 2 diabetes mellitus (T2D), which is thus largely responsible for the CHD association in the general population. Recent years have seen major advances in the genetics of T2D, principally through ever-increasing large-scale genome-wide association studies. This article addresses the question of whether this expanding knowledge of the genomics of T2D provides insight into the etiologic relationship between T2D and CHD. We will investigate this relationship by reviewing the evidence for shared genetic loci between T2D and CHD; by examining the formal testing of this interaction (Mendelian randomization studies assessing whether T2D is causal for CHD); and then turn to the implications of this genetic relationship for therapies for CHD, for therapies for T2D, and for therapies that affect both. In conclusion, the growing knowledge of the genetic relationship between T2D and CHD is beginning to provide the promise for improved prevention and treatment of both disorders.

Metabolic Reprogramming of Macrophages in Atherosclerosis: Is It All about Cholesterol?

Hypercholesterolemia contributes to the chronic inflammatory response during the progression of atherosclerosis, in part by favoring cholesterol loading in macrophages and other immune cells. However, macrophages encounter a substantial amount of other lipids and nutrients after ingesting atherogenic lipoprotein particles or clearing apoptotic cells, increasing their metabolic load and impacting their behavior during atherosclerosis plaque progression. This review examines whether and how fatty acids and glucose shape the cellular metabolic reprogramming of macrophages in atherosclerosis to modulate the onset phase of inflammation and the later resolution stage, in which the balance is tipped toward tissue repair.

Genetics of type 2 diabetes and coronary artery disease and their associations with twelve cardiometabolic traits in the United Arab Emirates population

BACKGROUND

The United Arab Emirates (UAE) population has a high rate of type 2 diabetes mellitus (T2DM) and other metabolic risk factors for coronary artery disease (CAD). Previous studies have indicated strong genetic associations between T2DM and CAD. The objective of this study was to replicate previously reported significant genetic associations for T2DM and CAD which were in a genome-wide significance level in a cohort from the Arab population of the UAE, and to investigate the associations of these loci with twelve cardiometabolic traits that may influence the development of T2DM and CAD.

METHODS

A total of nine hundreds and fourteen Emiratis were recruited to this study to investigate associations of 101 loci for T2DM (422 patients and 455 controls), and 53 loci for CAD (160 patients and 245 controls), using logistic regression models which incorporating possible confounding factors. Results are presented using odds ratios with their corresponding 95% confidence intervals and p-values. Linear regression models, which included possible covariates were applied to determine any associations between the T2DM and CAD reported loci with the twelve cardiometabolic traits and results were presented as effect sizes (beta), standard errors, and p-values. Furthermore, the overall risks for all the loci found to be associated with T2DM and CAD were determined using the cumulative effects of the risk alleles. For those found to be associated with the twelve cardiometabolic traits, risks were determined using calculations of their polygenic risk scores.

RESULTS

The mean age of the T2DM group was 61.5 ± 11.3 and of the CAD group was 66.2 ± 9.3 years. The prevalence of most of the cardiovascular disease risk factors in this cohort were high: mean body mass index (BMI) = 29.4, T2DM (51.9%), hypertension (60.9%), dyslipidemia (68.8%), and smoking (47.9%). All individuals who were tested for CAD (n = 405) also had a diagnosis of T2DM. The highest association variant for T2DM was in SNP rs1977833 in HHEX (p = 0.0016, OR = 0.56 for allele A), which is a multi-ethnic locus for T2DM. The strongest association with CAD was detected with SNP rs264 in LPL, which encodes lipoprotein lipase (p = 0.009, OR = 1.96 for allele A). For the cardiometabolic traits analyses, most notable associations were those of FTO with BMI and waist circumference; ABO with height; KCNK16 with diastolic blood pressure; PROX1-AS1, GCKR, and MIR129-LEP with fasting blood glucose; random blood glucose with ZEB2 and THADA; HbA1c levels with TLE1 and FAM99B loci; HDL-cholesterol levels with BRAF; and triglyceride levels with ZEB2. Furthermore, accumulation of risk alleles and polygenic scores of the associated loci was clearly associated with increased risks for all tested diseases and traits in this cohort.

CONCLUSIONS

The present study highlighted many known genetic loci, which are linked to T2DM and CAD and their associations with major cardiometabolic traits in Arab descendants. We confirmed that some loci are associated with T2DM, CAD, and metabolic traits independently of the ethnic background, with a novel association also detected between height and ABO.

Classification of Type 2 Diabetes Genetic Variants and a Novel Genetic Risk Score Association With Insulin Clearance

CONTEXT

Genome-wide association studies have identified more than 450 single nucleotide polymorphisms (SNPs) for type 2 diabetes (T2D).

OBJECTIVE

To facilitate use of these SNPs in future genetic risk score (GRS)-based analyses, we aimed to classify the SNPs based on physiology. We also sought to validate GRS associations with insulin-related traits in deeply phenotyped Mexican Americans.

DESIGN, SETTING, AND PARTICIPANTS

A total of 457 T2D SNPs from the literature were assigned physiologic function based on association studies and cluster analyses. All SNPs (All-GRS), beta-cell (BC-GRS), insulin resistance (IR-GRS), lipodystrophy (Lipo-GRS), and body mass index plus lipids (B + L-GRS) were evaluated for association with diabetes and indices of insulin secretion (from oral glucose tolerance test), insulin sensitivity and insulin clearance (from euglycemic clamp), and adiposity and lipid markers in 1587 Mexican Americans.

RESULTS

Of the 457 SNPs, 52 were classified as BC, 30 as IR, 12 as Lipo, 12 as B + L, whereas physiologic function of 351 was undefined. All-GRS was strongly associated with T2D. Among nondiabetic Mexican Americans, BC-GRS was associated with reduced insulinogenic index, IR-GRS was associated with reduced insulin sensitivity, and Lipo-GRS was associated with reduced adiposity. B + L-GRS was associated with increased insulin clearance. The latter did not replicate in an independent cohort wherein insulin clearance was assessed by a different method.

CONCLUSIONS

Supporting their utility, BC-GRS, IR-GRS, and Lipo-GRS, based on SNPs discovered largely in Europeans, exhibited expected associations in Mexican Americans. The novel association of B + L-GRS with insulin clearance suggests that impaired ability to reduce insulin clearance in compensation for IR may play a role in the pathogenesis of T2D. Whether this applies to other ethnic groups remains to be determined.

Effects of Adiponectin on T2DM and Glucose Homeostasis: A Mendelian Randomization Study

PURPOSE

The associations of adiponectin with type 2 diabetes mellitus (T2DM), glucose homeostasis (including β-cell function index (HOMA-β), insulin resistance (HOMA-IR), fasting insulin (FI) and fasting glucose (FG)) have reported in epidemiological studies. However, the previous observational studies are prone to biases, such as reverse causation and residual confounding factors. Herein, a Mendelian Randomization (MR) study was conducted to determine whether causal effects exist among them.

MATERIALS AND AND METHODS

Two-sample MR analyses and multiple sensitivity analyses were performed using the summary data from the ADIPOGen consortium, MAGIC Consortium, and a meta-analysis of GWAS with a considerable sample of T2DM (62,892 cases and 596,424 controls of European ancestry). We got eight valid genetic variants to predict the causal effect among adiponectin and T2DM and glucose homeostasis after excluding the probable invalid or pleiotropic variants.

RESULTS

Adiponectin was not associated with T2DM (odds ratio (OR) = 1.004; 95% confidence interval (CI): 0.740, 1.363) when using MR Egger after removing the invalid SNPs, and the results were consistent when using the other four methods. Similar results existed among adiponectin and HOMA-β, HOMA-IR, FI, FG.

CONCLUSION

Our MR study revealed that adiponectin had no causal effect on T2DM and glucose homeostasis and that the associations among them in observational studies may be due to confounding factors.

Mendelian randomization using semiparametric linear transformation models

Mendelian randomization (MR) uses genetic information as an instrumental variable (IV) to estimate the causal effect of an exposure of interest on an outcome in the presence of unknown confounding. We are interested in the causal effect of cigarette smoking on lung cancer survival, which is subject to confounding by underlying pulmonary functions. Despite the well-developed IV analyses for the continuous and binary outcomes, the scarcity of methodology for the survival outcome limits its utility for the time-to-event data collected in many observational studies. We propose an IV analysis method in the survival context, estimating causal effects on a transformed survival time and survival probabilities using semiparametric linear transformation models. We study the conditions under which hazard ratio and the effect on survival probability can be approximated. For statistical inference, we construct estimating equations to circumvent the difficulty in deriving joint likelihood of the exposure and the outcome, due to the unknown confounding. Asymptotic properties of the proposed estimators are established without parametric assumptions about confounders. We study the finite sample performance in extensive simulation studies. The MR analysis of a lung cancer study suggests a harmful prognostic effect of smoking pack-years that would have been missed by the crude association.

A diabetes-associated genetic variant is associated with diastolic dysfunction and cardiovascular disease

Aims

Although the epidemiological association between Type 2 diabetes and congestive heart failure (CHF) as well as cardiovascular disease (CVD) is well established, associations between diabetes‐related single‐nucleotide polymorphisms (SNPs), CHF, and CVD have been surprisingly inconclusive. Our aim is to examine if 43 diabetes‐related SNPs were associated with prevalent diastolic dysfunction assessed by echocardiography and incident CVD and/or CHF.

Methods and results

We genotyped 43 SNPs that previously reported genome‐wide significant associations with Type 2 diabetes, in 1444 subjects from the population‐based Malmö Preventive Project‐Re‐examination Study (MPP‐RES) (mean age 68 years; 29% women, 36% prevalent diabetes) (discovery cohort) and in 996 subjects from the VARA cohort (mean age 51 years, 52% women, 7% prevalent diabetes) (replication cohort). Multivariable logistic regression was assessed. Genetic variants that reached significant association with diastolic dysfunction in both cohorts were then analysed for association with incident CVD/CHF in a larger sample of the MPP‐RES cohort (3,407 cases and 11,776 controls, median follow up >30 years) using Cox regression analysis. A common variant at the HNF1B [major allele (T) coded, also the risk allele for diabetes] was the only SNP associated with increased risk of prevalent diastolic dysfunction in both the discovery [MPP‐RES; odds ratio (OR) 1.21, P = 0.024), and the replication cohort (VARA; OR 1.38, P = 0.042]. Cox regression analysis showed that carriers of the T‐allele of rs757210 had an increased risk of future CVD (HR 1.05, P = 0.042). No significant association was seen for incident CHF.

Conclusions

The diabetes susceptibility locus HNF1B is associated with prevalent diastolic dysfunction in two independent Swedish cohorts as well as incident cardiovascular disease.

Precision Medicine and Cardiovascular Health: Insights from Mendelian Randomization Analyses

Cardiovascular disease (CVD) is considered a primary driver of global mortality and is estimated to be responsible for approximately 17.9 million deaths annually. Consequently, a substantial body of research related to CVD has developed, with an emphasis on identifying strategies for the prevention and effective treatment of CVD. In this review, we critically examine the existing CVD literature, and specifically highlight the contribution of Mendelian randomization analyses in CVD research. Throughout this review, we assess the extent to which research findings agree across a range of studies of differing design within a triangulation framework. If differing study designs are subject to non-overlapping sources of bias, consistent findings limit the extent to which results are merely an artefact of study design. Consequently, broad agreement across differing studies can be viewed as providing more robust causal evidence in contrast to limiting the scope of the review to a single specific study design. Utilising the triangulation approach, we highlight emerging patterns in research findings, and explore the potential of identified risk factors as targets for precision medicine and novel interventions.

Genetic Predisposition to Type 2 Diabetes and Risk of Subclinical Atherosclerosis and Cardiovascular Diseases Among 160,000 Chinese Adults

In observational studies, type 2 diabetes is associated with two- to fourfold higher risk of cardiovascular diseases (CVD). Using data from the China Kadoorie Biobank (CKB), we examined associations of genetically predicted type 2 diabetes with CVD among ∼160,000 participants to assess whether these relationships are causal. A type 2 diabetes genetic risk score (comprising 48 established risk variants) was associated with the presence of carotid plaque (odds ratio 1.17 [95% CI 1.05, 1.29] per 1 unit higher log-odds of type 2 diabetes; n = 6,819) and elevated risk of ischemic stroke (IS) (1.08 [1.02, 1.14]; n = 17,097), nonlacunar IS (1.09 [1.03, 1.16]; n = 13,924), and major coronary event (1.12 [1.02, 1.23]; n = 5,081). There was no significant association with lacunar IS (1.03 [0.91, 1.16], n = 3,173) or intracerebral hemorrhage (ICH) (1.01 [0.94, 1.10], n = 6,973), although effect estimates were imprecise. These associations were consistent with observational associations of type 2 diabetes with CVD in CKB (P for heterogeneity >0.3) and with the associations of type 2 diabetes with IS, ICH, and coronary heart disease in two-sample Mendelian randomization analyses based on summary statistics from European population genome-wide association studies (P for heterogeneity >0.2). In conclusion, among Chinese adults, genetic predisposition to type 2 diabetes was associated with atherosclerotic CVD, consistent with a causal association.

Saxagliptin protects against hypoxia-induced damage in H9c2 cells

Type II diabetes is recognized as a major risk factor for death due to cardiovascular complications such as coronary heart disease (CHD), but the complex interplay between these two diseases remains poorly understood. Suppression of oxidative stress, apoptosis, and inflammation of endothelial cells is a valuable treatment strategy to prevent or halt the progression of CHD. In the present study, we used real-time polymerase chain reaction (PCR), Western blot analysis, and enzyme linked immunosorbent assay (ELISA) to investigate the effects of saxagliptin on hypoxia-inducible factors. Our findings demonstrate that saxagliptin can significantly improve cell viability in H9c2 cells as well as reduce hypoxia-induced oxidative damage and loss of mitochondrial membrane potential. Saxagliptin reduced hypoxia-induced NADPH oxidase 4 (NOX 4). We also show that saxagliptin can reduce the expression of matrix metallopeptidase-2 (MMP-2) and matrix metallopeptidase-9 (MMP-9), two important degradative enzymes. Saxagliptin also suppressed hypoxia-induced expression of high mobility group box-1 protein (HMGB1), a key inflammatory cytokine. Finally, we show that saxagliptin can exert atheroprotective effects by reducing the expression of myeloid differential protein-88 (MyD88) and increasing the expression of nuclear factor erythroid-2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1). Thus, saxagliptin shows promise as a treatment against diabetes-associated CHD.

Genetic predisposition to type 2 diabetes is associated with severity of coronary artery disease in patients with acute coronary syndromes

Background

Accumulating evidence has shown that type 2 diabetes (T2D) and coronary artery disease (CAD) may stem from a ‘common soil’. The aim of our study was to examine the association between genetic predisposition to T2D and the risk of severe CAD among patients with acute coronary syndromes (ACS) undergoing angiography.

Methods

The current case–control study included 1414 ACS patients with at least one major epicardial vessel stenosis > 50% enrolled in the ACS Genetic Study. The severity of CAD was quantified by the number of coronary arteries involved. Genetic risk score (GRS) was calculated using 41 common variants that robustly associated with increased risk of T2D in East Asians. Logistic regression models were used to estimate the association between GRS and the severity of CAD.

Results

In the age-, sex- and BMI-adjusted model, each additional risk allele was associated with a 6% increased risk of multi-vessel disease (OR = 1.06, 95% CI 1.02–1.09). The OR was 1.43 (95% CI 1.08–1.89) for the risk of severe CAD when comparing the extreme tertiles of T2D-GRS. The association was not reduced after further adjustment for conventional cardiovascular risk factors. Additional adjustment for T2D status in our regression model attenuated the association by approximately one quarter. In subgroup analysis, the strengths of the associations between GRS and the severity of CAD were broadly similar in terms of baseline demographic information and disease characteristics.

Conclusions

Our data indicated that genetic predisposition to T2D is associated with elevated risk of severe CAD. This association revealed a possible causal relationship and is partially mediated through diabetic status.