Assessing the linear and non-linear association of HbA1c with cardiovascular disease: a Mendelian randomisation study

A two-sample Mendelian randomization study explores metabolic profiling of different glycemic traits

We assessed the causal relation of four glycemic traits and type 2 diabetes liability with 167 metabolites using Mendelian randomization with various sensitivity analyses and a reverse Mendelian randomization analysis. We extracted instruments for fasting glucose, 2-h glucose, fasting insulin, and glycated hemoglobin from the Meta-Analyses of Glucose and Insulin-related traits Consortium (n = 200,622), and those for type 2 diabetes liability from a meta-analysis of multiple cohorts (148,726 cases, 965,732 controls) in Europeans. Outcome data were from summary statistics of 167 metabolites from the UK Biobank (n = 115,078). Fasting glucose and 2-h glucose were not associated with any metabolite. Higher glycated hemoglobin was associated with higher free cholesterol in small low-density lipoprotein. Type 2 diabetes liability and fasting insulin were inversely associated with apolipoprotein A1, total cholines, lipoprotein subfractions in high-density-lipoprotein and intermediate-density lipoproteins, and positively associated with aromatic amino acids. These findings indicate hyperglycemia-independent patterns and highlight the role of insulin in type 2 diabetes development. Further studies should evaluate these glycemic traits in type 2 diabetes diagnosis and clinical management.

Association between hemoglobin A1c and abdominal aortic calcification: results from the National Health and Nutrition Examination Survey 2013-2014

BACKGROUND

Hemoglobin A1c (HbA1c), a "gold standard" for the assessment of glycemic control, was associated with an increased risk of cardiovascular disease and coronary artery calcification. However, its effects on abdominal aortic calcification (AAC) are uncertain. The present study comprehensively investigated the association between HbA1c and AAC in the 2013-2014 National Health and Nutrition Examinations Surveys.

METHODS

Among 1,799 participants ≥ 40 years, dual-energy X-ray absorptiometry-derived AAC was quantified using the Kauppila score (AAC-24). Severe AAC was defined as a total AAC-24 > 6. Weighted linear regression models and logistic regression models were used to determine the effects of HbA1c on AAC. The restricted cubic spline model was used for the dose-response analysis.

RESULTS

The mean AAC-24 of participants was 1.3, and 6.7% of them suffered from severe AAC. Both AAC-24 and the prevalence of severe AAC increased with the higher tertile of HbA1c (P < 0.001). Elevated HbA1c levels would increase the AAC-24 (β = 0.73, 95% CI: 0.30-1.16) and the risk of severe AAC (OR = 1.63, 95% CI: 1.29-2.06), resulting in nearly linear dose-response relationships in all participants. However, this positive correlation were not statistically significant when participants with diabetes were excluded. Furthermore, subgroup analysis showed significant interactions effect between HbA1c and hypertension on severe AAC with the OR (95% CI) of 2.35 (1.62-3.40) for normotensives and 1.39 (1.09-1.79) for hypertensives (P for interaction = 0.022).

CONCLUSION

Controlling HbA1c could reduce AAC scores and the risk of severe AAC. Glycemic management might be a component of strategies for preventing AAC among all participants, especially normotensives.

Dissecting the mediating and moderating effects of depression on the associations between traits and coronary artery disease: A two-step Mendelian randomization and phenome-wide interaction study

Background

Depression is often present concurrently with coronary artery disease (CAD), a disease with which it shares many risk factors. However, the manner in which depression mediates and moderates the association between traits (including biomarkers, anthropometric indicators, lifestyle behaviors, etc.) and CAD is largely unknown.

Methods

In our causal mediation analyses using two-step Mendelian randomization (MR), univariable MR was first used to investigate the causal effects of 108 traits on liability to depression and CAD. The traits with significant causal effects on both depression and CAD, but not causally modulated by depression, were selected for the second-step analyses. Multivariable MR was used to estimate the direct effects (independent of liability to depression) of these traits on CAD, and the indirect effects (mediated via liability to depression) were calculated. To investigate the moderating effect of depression on the association between 364 traits and CAD, a cross-sectional phenome-wide interaction study (PheWIS) was conducted in a study population from UK Biobank (UKBB) (N=275,257). Additionally, if the relationship between traits and CAD was moderated by both phenotypic and genetically predicted depression at a suggestive level of significance (Pinteraction≤0.05) in the PheWIS, the results were further verified by a cohort study using Cox proportional hazards regression.

Results

Univariable MR indicated that 10 of 108 traits under investigation were significantly associated with both depression and CAD, which showed a similar direct effect compared to the total effect for most traits. However, the traits "drive faster than speed limit" and "past tobacco smoking" were both exceptions, with the proportions mediated by depression at 24.6% and 7.2%, respectively. In the moderation analyses, suggestive evidence of several traits was found for moderating effects of phenotypic depression or susceptibility to depression, as estimated by polygenic risk score, including chest pain when hurrying, reason of smoking quitting and weight change. Consistent results were observed in survival analyses and Cox regression.

Conclusion

The independent role of traits in CAD pathogenesis regardless of depression was highlighted in our mediation analyses, and the moderating effects of depression observed in our study may be helpful for CAD risk stratification and optimized allocation of scarce medical resources.

Violation of the Constant Genetic Effect Assumption Can Result in Biased Estimates for Non-Linear Mendelian Randomization

INTRODUCTION

Non-linear Mendelian randomization is an extension of conventional Mendelian randomization that performs separate instrumental variable analyses in strata of the study population with different average levels of the exposure. The approach estimates a localized average causal effect function, representing the average causal effect of the exposure on the outcome at different levels of the exposure. The commonly used residual method for dividing the population into strata works under the assumption that the effect of the genetic instrument on the exposure is linear and constant in the study population. However, this assumption may not hold in practice.

METHODS

We use the recently developed doubly ranked method to re-analyse various datasets previously analysed using the residual method. In particular, we consider a genetic score for 25-hydroxyvitamin D (25[OH]D) used in a recent non-linear Mendelian randomization analysis to assess the potential effect of vitamin D supplementation on all-cause mortality.

RESULTS

The effect of the genetic score on 25(OH)D concentrations varies strongly, with a five-fold difference in the estimated genetic association with the exposure in the lowest and highest decile groups. Evidence for a protective causal effect of vitamin D supplementation on all-cause mortality in low vitamin D individuals is evident for the residual method but not for the doubly ranked method. We show that the constant genetic effect assumption is more reasonable for some exposures and less reasonable for others. If the doubly ranked method indicates that this assumption is violated, then estimates from both the residual and doubly ranked methods can be biased, although bias was smaller on average in the doubly ranked method.

CONCLUSION

Analysts wanting to perform non-linear Mendelian randomization should compare results from both the residual and doubly ranked methods, as well as consider transforming the exposure for the residual method to reduce heterogeneity in the genetic effect on the exposure.

Evaluating the role of non-alcoholic fatty liver disease in cardiovascular diseases and type 2 diabetes: a Mendelian randomization study in Europeans and East Asians

BACKGROUND

Whether non-alcoholic fatty liver disease (NAFLD) causes cardiovascular disease (CVD) and type 2 diabetes (T2D) is unclear and possible differences between ethnicities have not been thoroughly explored. We used Mendelian randomization (MR) to assess the role of NAFLD in CVD and T2D risk in Europeans and East Asians.

METHODS

We conducted a MR study using genetic predictors of alanine aminotransferase (ALT), liability to NAFLD, aspartate transaminase (AST), liver magnetic resonance imaging corrected T1 and proton density fat fraction and combined them with genome-wide association studies (GWAS) summary statistics of CVD, T2D and glycaemic traits (sample size ranging from 14 400 to 977 320). Inverse-variance weighted analysis was used to assess the effect of NAFLD in these outcomes, with sensitivity analyses and replication in FinnGen. We conducted analyses in East Asians using ethnicity-specific genetic predictors of ALT and AST, and the respective outcome GWAS summary statistics.

RESULTS

In Europeans, higher ALT was associated with higher T2D risk (odds ratio: 1.77 per standard deviation, 95% CI 1.5 to 2.08), with similar results for other exposures, across sensitivity analyses and in FinnGen. Although NAFLD proxies were related to higher coronary artery disease (CAD) and stroke risk, sensitivity analyses suggested possible bias by horizontal pleiotropy. In East Asians, higher ALT was possibly associated with higher T2D risk, and ALT and AST were inversely associated with CAD.

CONCLUSIONS

NAFLD likely increases the risk of T2D in Europeans and East Asians. Potential differential effects on CAD between Europeans and East Asians require further investigation.

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.

Association of hemoglobin A1c with the incidence of hypertension: A large prospective study

Background

Although hemoglobin A1c (HbA1c) is closely related to diabetes, its relationship with the incidence of hypertension is still unknown, so we aimed to evaluate the relationship between HbA1c and the incidence of hypertension in the general population.

Method

In this large prospective cohort study with a median follow-up of 2 years, we included 4,074 participants from the China Health and Nutrition Survey (CHNS). Multivariate COX regression, subgroup analysis, receiver operator characteristic (ROC) curve and restricted cubic spline (RCS) were used to evaluate the relationship between HbA1c and incidental hypertension.

Results

Compared with participants without incident hypertension, participants with incident hypertension had higher levels of HbA1c (P < 0.05). In univariate COX regression analysis, HbA1c was associated with the risk of hypertension (HR: 1.161, 95% CI: 1.105-1.221, P < 0.001). In multivariate COX regression analysis adjusted for confounding variables, HbA1c was still closely related to the risk of hypertension (HR: 1.102, 95% CI: 1.006-1.206, P = 0.037). And subgroup analysis showed that the relationship between HbA1c and hypertension remained significant in female, lower than high school and non-obese subgroups (P < 0.05). ROC curve also showed that HbA1c could predict the risk of hypertension (AUC = 0.583, 95% CI: 0.568-0.598, P < 0.001). Further RCS analysis showed that HbA1c was positively correlated with the risk of hypertension (P for nonlinearity = 0.642).

Conclusion

HbA1c was linearly and positively associated with the incidence of hypertension.

Sex differences in the association of fasting glucose with HbA1c, and their consequences for mortality: A Mendelian randomization study

BACKGROUND

Hemoglobin A1c (HbA1c) is used for diabetes diagnosis and management. HbA1c also represents iron-related erythrocyte properties which differ by sex. We investigated erythrocyte properties on HbA1c and glucose, and whether corresponding consequences for mortality differed by sex.

METHODS

In this two-sample Mendelian randomization study using the largest publicly available European descent summary statistics, we assessed sex-specific associations of iron (n=163,511) and hemoglobin (188,076 women/162,398 men) with HbA1c (185,022 women/159,160 men) and fasting glucose (73,089 women/67,506 men), of fasting glucose with HbA1c and diabetes (cases=6,589 women/10,686 men, controls=187,137 women/155,780 men), and of fasting glucose (n=140,595), HbA1c (n=146,806) and liability to diabetes (74,124 cases/824,006 controls) with parental attained age (412,937 mothers/415,311 fathers).

FINDINGS

Iron and hemoglobin were inversely associated with HbA1c but not fasting glucose. Fasting glucose was more strongly associated with HbA1c and diabetes in women (1.65 standard deviation (SD) per mmol/L [95% confidence interval 1.58, 1.72]; odds ratio (OR) 7.36 per mmol/L [4.12, 10.98]) than men (0.89 [0.81, 0.98]; OR 2.79 [1.96, 4.98]). The inverse associations of HbA1c and liability to diabetes with lifespan were possibly stronger in men (-1.80 years per percentage [-2.77, -0.42]; -0.93 years per logOR [-1.23, -0.59]) than women (-0.80 [-2.69, 0.66]; -0.44 [-0.62, -0.26]).

INTERPRETATION

HbA1c underestimates fasting glucose in men compared with women, possibly due to erythrocyte properties. Whether HbA1c and liability to diabetes reduce lifespan more in men than women because diagnostic and management criteria involving HbA1c mean that glycemia in men is under-treated compared to women needs urgent investigation.

FUNDING

None.

Differentiating Associations of Glycemic Traits With Atherosclerotic and Thrombotic Outcomes: Mendelian Randomization Investigation

We conducted a Mendelian randomization analysis to differentiate associations of four glycemic indicators with a broad range of atherosclerotic and thrombotic diseases. Independent genetic variants associated with fasting glucose (FG), 2 h glucose after an oral glucose challenge (2hGlu), fasting insulin (FI), and glycated hemoglobin (HbA1c) at the genome-wide significance threshold were used as instrumental variables. Summary-level data for 12 atherosclerotic and 4 thrombotic outcomes were obtained from large genetic consortia and the FinnGen and UK Biobank studies. Higher levels of genetically predicted glycemic traits were consistently associated with increased risk of coronary atherosclerosis-related diseases and symptoms. Genetically predicted glycemic traits except HbA1c showed positive associations with peripheral artery disease risk. Genetically predicted FI levels were positively associated with risk of ischemic stroke and chronic kidney disease. Genetically predicted FG and 2hGlu were positively associated with risk of large artery stroke. Genetically predicted 2hGlu levels showed positive associations with risk of small vessel stroke. Higher levels of genetically predicted glycemic traits were not associated with increased risk of thrombotic outcomes. Most associations for genetically predicted levels of 2hGlu and FI remained after adjustment for other glycemic traits. Increase in glycemic status appears to increase risks of coronary and peripheral artery atherosclerosis but not thrombosis.

HemoglobinA1c Is a Risk Factor for Changes of Bone Mineral Density: A Mendelian Randomization Study

BACKGROUND

As a valuable blood glucose measurement, HemoglobinA1c (HbA1c) is of great clinical value for diabetes. However, in previous observational studies, studies on its effect on bone mineral density (BMD) have different results. This study aimed to use Mendelian randomization (MR) to assess the effect of HbA1c on bone mineral density and fracture risk, and try to further explore whether this association was achieved through glycemic or non-glycemic factors.

METHODS

Take HbA1c measurement as exposure, and BMD estimated from quantitative heel ultrasounds (eBMD) and bone fractures as outcomes. Two-Sample MR Analysis was conducted to assess the causal effect of HbA1C on heel BMD and risk fracture. Then, we performed the analysis using two subsets of these variants, one related to glycemic measurement and the other to erythrocyte indices.

RESULTS

Genetically increased HbA1C was associated with the lower heel eBMD [odds ratio (OR) 0.91 (95% CI 0.87, 0.96) per %-unit, P = 3 × 10-4(IVW)]. Higher HbA1C was associated with lower heel eBMD when using only erythrocytic variants [OR 0.87 (0.82, 0.93), P=2× 10-5(IVW)]; However, when using only glycemic variants, this casual association does not hold. In further MR analysis, we test the association of erythrocytic traits with heel eBMD.

CONCLUSION

Our study revealed the significant causal effect of HbA1c on eBMD, and this causal link might achieve through non-glycemic pathways (erythrocytic indices).