Mendelian randomization

Nature Reviews Methods Primers, Journal Year: 2022, Volume and Issue: 2(1)

Published: Feb. 10, 2022

Language: Английский

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Mendelian Randomization: Concepts and Scope

Cold Spring Harbor Perspectives in Medicine, Journal Year: 2021, Volume and Issue: 12(1), P. a040501 - a040501

Published: Aug. 23, 2021

Mendelian randomization (MR) is a method of studying the causal effects modifiable exposures (i.e., potential risk factors) on health, social, and economic outcomes using genetic variants associated with specific interest. MR provides more robust understanding influence these because germline are randomly inherited from parents to offspring and, as result, should not be related confounding factors that exposure-outcome associations. The variant can therefore used tool link proposed factor outcome, estimate this effect less bias than conventional epidemiological approaches. We describe scope MR, highlighting range applications being made possible data sets resources become larger freely available. outline approach in detail, covering concepts, assumptions, estimation methods. cover some common misconceptions, provide strategies for overcoming violation discuss future prospects extending clinical applicability, methodological innovations, robustness, generalizability findings.

Language: Английский

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Guidelines for performing Mendelian randomization investigations: update for summer 2023

Wellcome Open Research, Journal Year: 2023, Volume and Issue: 4, P. 186 - 186

Published: Aug. 4, 2023

This paper provides guidelines for performing Mendelian randomization investigations. It is aimed at practitioners seeking to undertake analyses and write up their findings, journal editors reviewers assess manuscripts. The are divided into ten sections: motivation scope, data sources, choice of genetic variants, variant harmonization, primary analysis, supplementary sensitivity (one section on robust statistical methods one other approaches), extensions additional analyses, presentation, interpretation. These will be updated based feedback from the community advances in field. Updates made periodically as needed, least every 24 months.

Language: Английский

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Artificial intelligence in cancer target identification and drug discovery

Signal Transduction and Targeted Therapy, Journal Year: 2022, Volume and Issue: 7(1)

Published: May 10, 2022

Artificial intelligence is an advanced method to identify novel anticancer targets and discover drugs from biology networks because the can effectively preserve quantify interaction between components of cell systems underlying human diseases such as cancer. Here, we review discuss how employ artificial approaches drugs. First, describe scope analysis for target investigations. Second, basic principles theory commonly used network-based machine learning-based algorithms. Finally, showcase applications in cancer identification drug discovery. Taken together, models have provided us with a quantitative framework study relationship network characteristics cancer, thereby leading potential discovery candidates.

Language: Английский

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Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation

PLoS Biology, Journal Year: 2022, Volume and Issue: 20(2), P. e3001547 - e3001547

Published: Feb. 25, 2022

Large-scale molecular profiling and genotyping provide a unique opportunity to systematically compare the genetically predicted effects of therapeutic targets on human metabolome. We firstly constructed genetic risk scores for 8 drug basis that they primarily modify low-density lipoprotein (LDL) cholesterol (HMGCR, PCKS9, NPC1L1), high-density (HDL) (CETP), or triglycerides (APOC3, ANGPTL3, ANGPTL4, LPL). Conducting mendelian randomisation (MR) provided strong evidence an effect drug-based coronary artery disease (CAD) with exception ANGPTL3. then estimated each score 249 metabolic traits derived using blood samples from unprecedented sample size up 115,082 UK Biobank participants. Genetically were generally consistent among targets, which intended same lipid trait. For example, linear fit MR estimates all inhibition LDL lowering HMGCR PCSK9 was r2 = 0.91. In contrast, comparisons between classes designed discrete typically had very different signatures (for instance, versus 4 triglyceride < 0.02). Furthermore, we highlight this discrepancy specific traits, finding therapies weak glycoprotein acetyls, marker inflammation, whereas modifying assessed levels inflammatory biomarker. Our findings indicate perturbations these metabolome can drastically differ, despite largely CAD, potential implications biomarkers in clinical development measuring treatment response.

Language: Английский

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Using Mendelian Randomization to Improve the Design of Randomized Trials

Cold Spring Harbor Perspectives in Medicine, Journal Year: 2021, Volume and Issue: unknown, P. a040980 - a040980

Published: Jan. 11, 2021

Randomized controlled trials and Mendelian randomization studies are two study designs that provide randomized evidence in human biological medical research. Both exploit the power of to unconfounded estimates causal effect. However, have very different scientific objectives. As a result, despite sometimes being referred as "nature's trial," cannot be used replace trial but instead provides complementary information. In this review, we explain similarities differences between studies, suggest several ways can directly inform improve design illustrated with practical examples. We conclude by describing how employ principles framed "naturally trials" template for future evaluating therapies directed against genetically validated targets.

Language: Английский

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Pathogenesis and management of abdominal aortic aneurysm

European Heart Journal, Journal Year: 2023, Volume and Issue: 44(29), P. 2682 - 2697

Published: May 31, 2023

Abdominal aortic aneurysm (AAA) causes ∼170 000 deaths annually worldwide. Most guidelines recommend asymptomatic small AAAs (30 to <50 mm in women; 30 <55 men) are monitored by imaging and large asymptomatic, symptomatic, ruptured considered for surgical repair. Advances AAA repair techniques have occurred, but a remaining priority is therapies limit growth rupture. This review outlines research on pathogenesis growth. Genome-wide association studies identified novel drug targets, e.g. interleukin-6 blockade. Mendelian randomization analyses suggest that treatments reduce low-density lipoprotein cholesterol such as proprotein convertase subtilisin/kexin type 9 inhibitors smoking reduction or cessation also treatment targets. Thirteen placebo-controlled randomized trials tested whether range of antibiotics, blood pressure-lowering drugs, mast cell stabilizer, an anti-platelet drug, fenofibrate slow None these shown convincing evidence efficacy been limited sample sizes, adherence, poor participant retention, over-optimistic Data from some observational cohorts pressure reduction, particularly angiotensin-converting enzyme inhibitors, could rupture, this has not evaluated trials. Some metformin may growth, currently being In conclusion, no therapy convincingly controlled Further prospective other targets needed.

Language: Английский

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Using genetic association data to guide drug discovery and development: Review of methods and applications

The American Journal of Human Genetics, Journal Year: 2023, Volume and Issue: 110(2), P. 195 - 214

Published: Feb. 1, 2023

Language: Английский

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Genetic association of lipids and lipid-lowering drug target genes with non-alcoholic fatty liver disease

EBioMedicine, Journal Year: 2023, Volume and Issue: 90, P. 104543 - 104543

Published: March 30, 2023

Some observational studies found that dyslipidaemia is a risk factor for non-alcoholic fatty liver disease (NAFLD), and lipid-lowering drugs may lower NAFLD risk. However, it remains unclear whether causative NAFLD. This Mendelian randomisation (MR) study aimed to explore the causal role of lipid traits in evaluate potential effect drug targets on NAFLD.Genetic variants associated with genes encoding were extracted from Global Lipids Genetics Consortium genome-wide association (GWAS). Summary statistics obtained two independent GWAS datasets. Lipid-lowering reached significance further tested using expression quantitative trait loci data relevant tissues. Colocalisation mediation analyses performed validate robustness results mediators.No significant eight was found. Genetic mimicry lipoprotein lipase (LPL) enhancement risks datasets (OR1 = 0.60 [95% CI 0.50-0.72], p1 2.07 × 10-8; OR2 0.57 0.39-0.82], p2 3.00 10-3). A MR (OR 0.71 CI, 0.58-0.87], p 1.20 10-3) strong colocalisation (PP.H4 0.85) observed LPL subcutaneous adipose tissue. Fasting insulin type 2 diabetes mediated 7.40% 9.15%, respectively, total risk.Our findings do not support as Among nine targets, promising candidate target The mechanism action be its effects.Capital's Funds Health Improvement Research (2022-4-4037). CAMS Innovation Fund Medical Sciences (CIFMS, grant number: 2021-I2M-C&T-A-010).

Language: Английский

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Mendelian Randomization Study of PCSK9 and HMG-CoA Reductase Inhibition and Cognitive Function

Journal of the American College of Cardiology, Journal Year: 2022, Volume and Issue: 80(7), P. 653 - 662

Published: Aug. 1, 2022

Lipid-lowering therapy with statins and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibition are effective strategies in reducing cardiovascular disease risk; however, concerns remain about potential long-term adverse neurocognitive effects. This genetics-based study aimed to evaluate the relationships of PCSK9 statin use on outcomes. We extracted single-nucleotide polymorphisms 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) from predominantly European ancestry-based genome-wide association studies summary-level statistics low-density lipoprotein cholesterol performed drug-target Mendelian randomization, proxying impact drug-based HMGCR using a range outcomes capture complex facets cognition dementia. Using data combined sample ∼740,000 participants, we observed neutral cognitive profile related genetic inhibition, no significant effects performance, memory or cortical surface area. Conversely, several associations for lowered performance (beta: –0.082; 95% CI: –0.16 –0.0080; P = 0.03), reaction time (beta 0.00064; 0.00030-0.00098; 0.0002), area –0.18; –0.35 –0.014; 0.03). Neither nor impacted biomarkers Alzheimer’s progression Lewy body dementia risk. Consistency findings across randomization methods accommodating different assumptions pleiotropy strengthens causal inference. wide function endpoints, failed find evidence an PCSK9-related impact, suggesting profile. In contrast, which may well be outweighed by benefits use, but nonetheless warrant pharmacovigilance.

Language: Английский

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