Mendelian Randomization Studies in Cardiometabolic Diseases

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: closed (15 July 2022) | Viewed by 21061

Special Issue Editors


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Guest Editor
Department of Clinical and Molecular Biochemistry, Pomeranian Medical University in Szczecin, 70-111 Szczecin, Poland
Interests: genetic polymorphism; association analysis; molecular cardiology; molecular nephrology; pharmacogenetics; monogenic diseases

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Guest Editor
Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, 126 University Place, Glasgow G12 8TA, UK
Interests: high-throughput genomics; metabolomics; cardiovascular traits; drug response

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Guest Editor
Department of Internal Medicine, Jagiellonian University Medical College, 30-688 Kraków, Poland
Interests: molecular mechanism of cancer formation

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Guest Editor
Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London 03/2022, UK
Interests: mendelian randomization; clinical pharmacology; cardiometabolic disease

Special Issue Information

Dear Colleagues,

The burgeoning list of genome-wide association studies, biobanks and deeply phenotyped and genotyped population cohorts has led to advances in methods to infer causality from genomic data. The random allocation of genetic variants at conception means that their associations with clinical traits are relatively devoid of the confounding factors that can hinder causal inference in traditional epidemiological studies. Provided those genetic variants related to an exposure affect an outcome through that exposure and not a pleiotropic pathway, these genetic variants can be leveraged as instruments for exploring causal effects of the exposure on the outcome in an approach termed ‘Mendelian randomization’. This represents an innovative field aimed at obtaining robust evidence from observation data using genetics towards distinguishing causation from correlation. Cardiometabolic disease is a major driver of the global disease burden. The focus of the themed issue is the application of MR in cardiometabolic disease and articles may span MR studies of cardiometabolic phenotypes, methodological papers and reviews.

In this issue, we invite articles that highlight how developments in the field have allowed for genetic association data to be leveraged for identifying causal mechanisms in cardiometabolic disease subtypes, including mediating pathways. We welcome articles that showcase insights on drug target development, including the investigation of efficacy in population subgroups, repurposing potential and adverse effects.

Prof. Dr. Andrzej Ciechanowicz
Prof. Dr. Sandosh Padmanabhan
Prof. Dr. Marek Sanak
Dr. Dipender Gill
Guest Editors

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Keywords

  • Mendelian randomization
  • cardiovascular disease
  • cardiometabolic disease
  • hypertension
  • diabetes
  • obesity
  • liver disease

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Published Papers (5 papers)

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Research

9 pages, 936 KiB  
Article
TwoStepCisMR: A Novel Method and R Package for Attenuating Bias in cis-Mendelian Randomization Analyses
by Benjamin Woolf, Loukas Zagkos and Dipender Gill
Genes 2022, 13(9), 1541; https://doi.org/10.3390/genes13091541 - 26 Aug 2022
Cited by 14 | Viewed by 4437
Abstract
Mendelian randomisation (MR) is an increasingly popular method for strengthening causal inference in epidemiological studies. cis-MR in particular uses genetic variants in the gene region of a drug target protein as an instrumental variable to provide quasi-experimental evidence for on-target drug effects. [...] Read more.
Mendelian randomisation (MR) is an increasingly popular method for strengthening causal inference in epidemiological studies. cis-MR in particular uses genetic variants in the gene region of a drug target protein as an instrumental variable to provide quasi-experimental evidence for on-target drug effects. A limitation of this framework is when the genetic variant is correlated to another variant that also effects the outcome of interest (confounding through linkage disequilibrium). Methods for correcting this bias, such as multivariable MR, struggle in a cis setting because of the high correlation among genetic variants. Here, through simulation experiments and an applied example considering the effect of interleukin 6 receptor signaling on coronary artery disease risk, we present an alternative method for attenuating bias that does not suffer from this problem. As our method uses both MR and the product and difference method for mediation analysis, our proposal inherits all assumptions of these methods. We have additionally developed an R package, TwoStepCisMR, to facilitate the implementation of the method. Full article
(This article belongs to the Special Issue Mendelian Randomization Studies in Cardiometabolic Diseases)
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14 pages, 1854 KiB  
Article
Unravelling the Distinct Effects of Systolic and Diastolic Blood Pressure Using Mendelian Randomisation
by Nhu Ngoc Le, Tran Q. B. Tran, Stefanie Lip, Linsay McCallum, John McClure, Anna F. Dominiczak, Dipender Gill and Sandosh Padmanabhan
Genes 2022, 13(7), 1226; https://doi.org/10.3390/genes13071226 - 9 Jul 2022
Cited by 11 | Viewed by 3656
Abstract
A true discrepancy between the effect of systolic blood pressure (SBP) and diastolic blood pressure (DBP) on cardiovascular (CV) outcomes remains unclear. This study performed two-sample Mendelian randomization (MR) using genetic instruments that exclusively predict SBP, DBP or both to dissect the independent [...] Read more.
A true discrepancy between the effect of systolic blood pressure (SBP) and diastolic blood pressure (DBP) on cardiovascular (CV) outcomes remains unclear. This study performed two-sample Mendelian randomization (MR) using genetic instruments that exclusively predict SBP, DBP or both to dissect the independent effect of SBP and DBP on a range of CV outcomes. Genetic predisposition to higher SBP and DBP was associated with increased risk of coronary artery disease (CAD), myocardial infarction (MI), stroke, heart failure (HF), atrial fibrillation (AF), chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM). Genetically proxied SBP exclusively was associated with CAD (OR 1.18, 95% CI: 1.03–1.36, per 10 mmHg), stroke (1.44[1.28–1.62]), ischemic stroke (1.49[1.30–1.69]), HF (1.41[1.20–1.65]), AF (1.28[1.15–1.43]), and T2DM (1.2[1.13–1.46]). Genetically proxied DBP exclusively was associated with stroke (1.21[1.06–1.37], per 5 mmHg), ischemic stroke (1.24[1.09–1.41]), stroke small-vessel (1.35[1.10–1.65]) and CAD (1.19[1.00–1.41]). Multivariable MR using exclusive SBP and DBP instruments showed the predominant effect of SBP on CAD (1.23[1.05–1.44], per 10 mmHg), stroke (1.39[1.20–1.60]), ischemic stroke (1.44[1.25–1.67]), HF (1.42[1.18–1.71]), AF (1.26[1.10–1.43]) and T2DM (1.31[1.14–1.52]). The discrepancy between effects of SBP and DBP on outcomes warrants further studies on underpinning mechanisms which may be amenable to therapeutic targeting. Full article
(This article belongs to the Special Issue Mendelian Randomization Studies in Cardiometabolic Diseases)
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12 pages, 971 KiB  
Article
Morning Cortisol and Circulating Inflammatory Cytokine Levels: A Mendelian Randomisation Study
by Skanda Rajasundaram, Rezbieara P. Rahman, Benjamin Woolf, Sizheng Steven Zhao and Dipender Gill
Genes 2022, 13(1), 116; https://doi.org/10.3390/genes13010116 - 8 Jan 2022
Cited by 6 | Viewed by 3798
Abstract
Cortisol exerts a broad anti-inflammatory effect on the immune system. Inflammatory cytokines contribute to the molecular signalling pathways implicated in various autoimmune and inflammatory conditions. However, the mechanisms by which cortisol modulates such signalling pathways remain uncertain. Leveraging summary-level data from the CORtisol [...] Read more.
Cortisol exerts a broad anti-inflammatory effect on the immune system. Inflammatory cytokines contribute to the molecular signalling pathways implicated in various autoimmune and inflammatory conditions. However, the mechanisms by which cortisol modulates such signalling pathways remain uncertain. Leveraging summary-level data from the CORtisol NETwork (CORNET, n = 25,314) and FINRISK (n = 8293) genome-wide association studies, we used two-sample Mendelian randomisation to investigate the causal effect of genetically proxied morning cortisol levels on 42 circulating cytokines. We found that increased genetically proxied morning cortisol levels were associated with reduced levels of IL-8 and increased levels of MIF. These results provide mechanistic insight into the immunomodulatory effects of endogenous cortisol and the therapeutic effects of exogenous corticosteroids. Clinically, our findings underline the therapeutic importance of steroids in inflammatory conditions where IL-8 and MIF play a central pathophysiological role in the onset and progression of disease. Full article
(This article belongs to the Special Issue Mendelian Randomization Studies in Cardiometabolic Diseases)
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11 pages, 1211 KiB  
Article
Sleep Disordered Breathing, Obesity and Atrial Fibrillation: A Mendelian Randomisation Study
by Maddalena Ardissino, Rohin K. Reddy, Eric A. W. Slob, Kiran H. K. Patel, David K. Ryan, Dipender Gill and Fu Siong Ng
Genes 2022, 13(1), 104; https://doi.org/10.3390/genes13010104 - 2 Jan 2022
Cited by 9 | Viewed by 4470
Abstract
It remains unclear whether the association between obstructive sleep apnoea (OSA), a form of sleep-disordered breathing (SDB), and atrial fibrillation (AF) is causal or mediated by shared co-morbidities such as obesity. Existing observational studies are conflicting and limited by confounding and reverse causality. [...] Read more.
It remains unclear whether the association between obstructive sleep apnoea (OSA), a form of sleep-disordered breathing (SDB), and atrial fibrillation (AF) is causal or mediated by shared co-morbidities such as obesity. Existing observational studies are conflicting and limited by confounding and reverse causality. We performed Mendelian randomisation (MR) to investigate the causal relationships between SDB, body mass index (BMI) and AF. Single-nucleotide polymorphisms associated with SDB (n = 29) and BMI (n = 453) were selected as instrumental variables to investigate the effects of SDB and BMI on AF, using genetic association data on 55,114 AF cases and 482,295 controls. Primary analysis was conducted using inverse-variance weighted MR. Higher genetically predicted SDB and BMI were associated with increased risk of AF (OR per log OR increase in snoring liability 2.09 (95% CI 1.10–3.98), p = 0.03; OR per 1-SD increase in BMI 1.33 (95% CI 1.24–1.42), p < 0.001). The association between SDB and AF was not observed in sensitivity analyses, whilst associations between BMI and AF remained consistent. Similarly, in multivariable MR, SDB was not associated with AF after adjusting for BMI (OR 0.68 (95% CI 0.42–1.10), p = 0.12). Higher BMI remained associated with increased risk of AF after adjusting for OSA (OR 1.40 (95% CI 1.30–1.51), p < 0.001). Elevated BMI appears causal for AF, independent of SDB. Our data suggest that the association between SDB, in general, and AF is attributable to mediation or confounding from obesity, though we cannot exclude that more severe SDB phenotypes (i.e., OSA) are causal for AF. Full article
(This article belongs to the Special Issue Mendelian Randomization Studies in Cardiometabolic Diseases)
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8 pages, 1228 KiB  
Communication
Genetically Predicted Type 2 Diabetes Mellitus Liability, Glycated Hemoglobin and Cardiovascular Diseases: A Wide-Angled Mendelian Randomization Study
by Bowen Liu, Amy M. Mason, Luanluan Sun, Emanuele Di Angelantonio, Dipender Gill and Stephen Burgess
Genes 2021, 12(10), 1644; https://doi.org/10.3390/genes12101644 - 19 Oct 2021
Cited by 14 | Viewed by 3453
Abstract
(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 [...] Read more.
(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. Full article
(This article belongs to the Special Issue Mendelian Randomization Studies in Cardiometabolic Diseases)
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