Author
Boer Jma.
Bio: Boer Jma. is an academic researcher from University of Cambridge. The author has contributed to research in topics: Allele frequency. The author has an hindex of 1, co-authored 1 publications receiving 733 citations.
Topics: Allele frequency
Papers
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University College London1, University of Cambridge2, University of Cologne3, Leiden University4, Utrecht University5, National Institutes of Health6, University of Pennsylvania7, University of Glasgow8, University of Edinburgh9, Mayo Clinic10, University of London11, University of Bristol12, Cardiff University13, University of Oxford14, University of Ioannina15, University of Hamburg16, Lithuanian University of Health Sciences17, Jagiellonian University18, Russian Academy19, Karolinska Institutet20, Memorial Hospital of South Bend21, University of Groningen22, MedStar Washington Hospital Center23, Swansea University24, Brown University25, University of Iowa26, Harvard University27, University of Exeter28, University of North Carolina at Chapel Hill29, Boston University30, Medical Research Council31, University of California, San Diego32, University of Mississippi33, Fred Hutchinson Cancer Research Center34
TL;DR: IL6R blockade could provide a novel therapeutic approach to prevention of coronary heart disease that warrants testing in suitably powered randomised trials and could help to validate and prioritise novel drug targets or to repurpose existing agents and targets for new therapeutic uses.
891 citations
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Brigham and Women's Hospital1, Novartis2, Baylor College of Medicine3, Federal University of São Paulo4, Technische Universität München5, University of Amsterdam6, St. John's University7, University of Pavol Jozef Šafárik8, McGill University9, First Faculty of Medicine, Charles University in Prague10, University of Szeged11, Iuliu Hațieganu University of Medicine and Pharmacy12, University of East Anglia13, Tohoku University14, Sahlgrenska University Hospital15
TL;DR: Antiinflammatory therapy targeting the interleukin‐1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid‐level lowering.
Abstract: BackgroundExperimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. MethodsWe conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. ResultsAt 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in t...
5,660 citations
TL;DR: It is concluded that Mendelian randomization investigations using summarized data from uncorrelated variants are similarly efficient to those using individual‐level data, although the necessary assumptions cannot be so fully assessed.
Abstract: Genome-wide association studies, which typically report regression coefficients summarizing the associations of many genetic variants with various traits, are potentially a powerful source of data for Mendelian randomization investigations. We demonstrate how such coefficients from multiple variants can be combined in a Mendelian randomization analysis to estimate the causal effect of a risk factor on an outcome. The bias and efficiency of estimates based on summarized data are compared to those based on individual-level data in simulation studies. We investigate the impact of gene–gene interactions, linkage disequilibrium, and ‘weak instruments’ on these estimates. Both an inverse-variance weighted average of variant-specific associations and a likelihood-based approach for summarized data give similar estimates and precision to the two-stage least squares method for individual-level data, even when there are gene–gene interactions. However, these summarized data methods overstate precision when variants are in linkage disequilibrium. If the P-value in a linear regression of the risk factor for each variant is less than , then weak instrument bias will be small. We use these methods to estimate the causal association of low-density lipoprotein cholesterol (LDL-C) on coronary artery disease using published data on five genetic variants. A 30% reduction in LDL-C is estimated to reduce coronary artery disease risk by 67% (95% CI: 54% to 76%). We conclude that Mendelian randomization investigations using summarized data from uncorrelated variants are similarly efficient to those using individual-level data, although the necessary assumptions cannot be so fully assessed.
2,003 citations
TL;DR: Developments of MR, including two-sample MR, bidirectional MR, network MR, two-step MR, factorial MR and multiphenotype MR, are outlined in this review.
Abstract: Observational epidemiological studies are prone to confounding, reverse causation and various biases and have generated findings that have proved to be unreliable indicators of the causal effects of modifiable exposures on disease outcomes. Mendelian randomization (MR) is a method that utilizes genetic variants that are robustly associated with such modifiable exposures to generate more reliable evidence regarding which interventions should produce health benefits. The approach is being widely applied, and various ways to strengthen inference given the known potential limitations of MR are now available. Developments of MR, including two-sample MR, bidirectional MR, network MR, two-step MR, factorial MR and multiphenotype MR, are outlined in this review. The integration of genetic information into population-based epidemiological studies presents translational opportunities, which capitalize on the investment in genomic discovery research.
1,686 citations
TL;DR: Whether therapies to modulate inflammageing can reduce the age-related decline in health is discussed, and the hypothesis that inflammation affects CVD, multimorbidity, and frailty is supported by mechanistic studies but requires confirmation in humans.
Abstract: Most older individuals develop inflammageing, a condition characterized by elevated levels of blood inflammatory markers that carries high susceptibility to chronic morbidity, disability, frailty, and premature death. Potential mechanisms of inflammageing include genetic susceptibility, central obesity, increased gut permeability, changes to microbiota composition, cellular senescence, NLRP3 inflammasome activation, oxidative stress caused by dysfunctional mitochondria, immune cell dysregulation, and chronic infections. Inflammageing is a risk factor for cardiovascular diseases (CVDs), and clinical trials suggest that this association is causal. Inflammageing is also a risk factor for chronic kidney disease, diabetes mellitus, cancer, depression, dementia, and sarcopenia, but whether modulating inflammation beneficially affects the clinical course of non-CVD health problems is controversial. This uncertainty is an important issue to address because older patients with CVD are often affected by multimorbidity and frailty — which affect clinical manifestations, prognosis, and response to treatment — and are associated with inflammation by mechanisms similar to those in CVD. The hypothesis that inflammation affects CVD, multimorbidity, and frailty by inhibiting growth factors, increasing catabolism, and interfering with homeostatic signalling is supported by mechanistic studies but requires confirmation in humans. Whether early modulation of inflammageing prevents or delays the onset of cardiovascular frailty should be tested in clinical trials. Inflammageing is a chronic, pro-inflammatory state that develops with age and is a risk factor for cardiovascular disease, comorbidities, frailty, and death. In this Review, Ferrucci and Fabbri discuss whether therapies to modulate inflammageing can reduce the age-related decline in health.
1,428 citations
01 Jan 2014
TL;DR: Mendelian randomization (MR) is a method that utilizes genetic variants that are robustly associated with such modifiable exposures to generate more reliable evidence regarding which interventions should produce health benefits.
Abstract: Observational epidemiological studies are prone to confounding, reverse causation and various biases and have generated findings that have proved to be unreliable indicators of the causal effects of modifiable exposures on disease outcomes. Mendelian randomization (MR) is a method that utilizes genetic variants that are robustly associated with such modifiable exposures to generate more reliable evidence regarding which interventions should produce health benefits. The approach is being widely applied, and various ways to strengthen inference given the known potential limitations of MR are now available. Developments of MR, including two-sample MR, bidirectional MR, network MR, two-step MR, factorial MR and multiphenotype MR, are outlined in this review. The integration of genetic information into population-based epidemiological studies presents translational opportunities, which capitalize on the investment in genomic discovery research.
1,402 citations