Special Issue "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: 15 January 2022.

Special Issue Editors

Prof. Dr. Andrzej Ciechanowicz
E-Mail Website
Guest Editor
Department of Clinical and Molecular Biochemistry, Pomeranian Medical University in Szczecin, Szczecin, Poland
Interests: genetic polymorphism; association analysis; molecular cardiology; molecular nephrology; pharmacogenetics; monogenic diseases
Prof. Dr. Sandosh Padmanabhan
E-Mail Website
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
Prof. Dr. Marek Sanak
E-Mail Website
Guest Editor
Department of Internal Medicine, Jagiellonian University Medical College, Kraków, Poland
Interests: molecular mechanism of cancer formation
Dr. Dipender Gill
E-Mail Website
Guest Editor
Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, 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

Manuscript Submission Information

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

Published Papers (1 paper)

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Genetically Predicted Type 2 Diabetes Mellitus Liability, Glycated Hemoglobin and Cardiovascular Diseases: A Wide-Angled Mendelian Randomization Study
Genes 2021, 12(10), 1644; https://0-doi-org.brum.beds.ac.uk/10.3390/genes12101644 - 19 Oct 2021
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(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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