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van Drie E, Taal SEL, Schmidt AF, Verstraelen TE, de Brouwer R, Schoormans D, Mommersteeg PMC, de Boer RA, Wilde AAM, Asselbergs FW, Baas AF, van Tintelen JP, van den Heuvel LM. Influence of stressful life events and personality traits on PLN cardiomyopathy severity: an exploratory study. Europace 2023; 26:euad368. [PMID: 38206619 PMCID: PMC10783237 DOI: 10.1093/europace/euad368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 12/11/2023] [Indexed: 01/12/2024] Open
Affiliation(s)
- E van Drie
- Department of Genetics, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
- Netherlands Heart Institute, Moreelsepark 1, 3511 EP Utrecht, The Netherlands
| | - S E L Taal
- Department of Genetics, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - A F Schmidt
- Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- UCL British Heart Foundation Research Accelerator Centre, London, UK
| | - T E Verstraelen
- Heart Centre, Department of Cardiology, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - R de Brouwer
- Department of Cardiology, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - D Schoormans
- Department of Clinical and Medical Psychology and Center of Research on Psychological Disorders and Somatic Diseases (CoRPS), Tilburg University, PO Box 90153, 5000 LE Tilburg, The Netherlands
| | - P M C Mommersteeg
- Department of Clinical and Medical Psychology and Center of Research on Psychological Disorders and Somatic Diseases (CoRPS), Tilburg University, PO Box 90153, 5000 LE Tilburg, The Netherlands
| | - R A de Boer
- Department of Cardiology, Erasmus Medical Center, Doctor Molewaterplein 40, 3015 GD Rotterdam, The Netherlands
| | - A A M Wilde
- Heart Centre, Department of Cardiology, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
| | - F W Asselbergs
- Heart Centre, Department of Cardiology, Amsterdam UMC Location University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK
| | - A F Baas
- Department of Genetics, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - J P van Tintelen
- Department of Genetics, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - L M van den Heuvel
- Department of Genetics, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
- Netherlands Heart Institute, Moreelsepark 1, 3511 EP Utrecht, The Netherlands
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2
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Jansen M, Schmidt AF, Jans JJM, Christiaans I, van der Crabben SN, Hoedemaekers YM, Dooijes D, Jongbloed JDH, Boven LG, Lekanne Deprez RH, Wilde AAM, van der Velden J, de Boer RA, van Tintelen JP, Asselbergs FW, Baas AF. Circulating Acylcarnitines Associated with Hypertrophic Cardiomyopathy Severity: an Exploratory Cross-Sectional Study in MYBPC3 Founder Variant Carriers. J Cardiovasc Transl Res 2023; 16:1267-1275. [PMID: 37278928 PMCID: PMC10721678 DOI: 10.1007/s12265-023-10398-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 05/10/2023] [Indexed: 06/07/2023]
Abstract
Hypertrophic cardiomyopathy (HCM) is a relatively common genetic heart disease characterised by myocardial hypertrophy. HCM can cause outflow tract obstruction, sudden cardiac death and heart failure, but severity is highly variable. In this exploratory cross-sectional study, circulating acylcarnitines were assessed as potential biomarkers in 124 MYBPC3 founder variant carriers (59 with severe HCM, 26 with mild HCM and 39 phenotype-negative [G + P-]). Elastic net logistic regression identified eight acylcarnitines associated with HCM severity. C3, C4, C6-DC, C8:1, C16, C18 and C18:2 were significantly increased in severe HCM compared to G + P-, and C3, C6-DC, C8:1 and C18 in mild HCM compared to G + P-. In multivariable linear regression, C6-DC and C8:1 correlated to log-transformed maximum wall thickness (coefficient 5.01, p = 0.005 and coefficient 0.803, p = 0.007, respectively), and C6-DC to log-transformed ejection fraction (coefficient -2.50, p = 0.004). Acylcarnitines seem promising biomarkers for HCM severity, however prospective studies are required to determine their prognostic value.
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Affiliation(s)
- Mark Jansen
- Department of Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
- Department of Cardiology, University Medical Center Utrecht, Utrecht University, Internal Mail No HTx Secr. (E03.511), Postbus 85500, 3508 GA, Utrecht, the Netherlands.
- Netherlands Heart Institute, Utrecht, the Netherlands.
- , .
| | - A F Schmidt
- Department of Cardiology, University Medical Center Utrecht, Utrecht University, Internal Mail No HTx Secr. (E03.511), Postbus 85500, 3508 GA, Utrecht, the Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
- Department of Cardiology, Amsterdam UMC Location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Amsterdam, the Netherlands
| | - J J M Jans
- Department of Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - I Christiaans
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - S N van der Crabben
- Department of Human Genetics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Y M Hoedemaekers
- Department of Cardiology, Amsterdam UMC Location University of Amsterdam, Amsterdam, the Netherlands
- Department of Clinical Genetics, Radboud University Medical Center, Nijmegen, the Netherlands
| | - D Dooijes
- Department of Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - J D H Jongbloed
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - L G Boven
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - R H Lekanne Deprez
- Department of Human Genetics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - A A M Wilde
- Department of Cardiology, Amsterdam UMC Location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Amsterdam, the Netherlands
| | - J van der Velden
- Department of Physiology, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - R A de Boer
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Cardiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - J P van Tintelen
- Department of Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Netherlands Heart Institute, Utrecht, the Netherlands
| | - F W Asselbergs
- Department of Cardiology, University Medical Center Utrecht, Utrecht University, Internal Mail No HTx Secr. (E03.511), Postbus 85500, 3508 GA, Utrecht, the Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
- Department of Cardiology, Amsterdam UMC Location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure and Arrhythmias, Amsterdam, the Netherlands
- Health Data Research UK and Institute of Health Informatics, University College London, London, UK
| | - A F Baas
- Department of Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
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3
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Dziopa K, Chaturvedi N, Asselbergs FW, Schmidt AF. Identifying and ranking novel independent features for cardiovascular disease prediction in people with type 2 diabetes. medRxiv 2023:2023.10.23.23297398. [PMID: 37961704 PMCID: PMC10635178 DOI: 10.1101/2023.10.23.23297398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Background CVD prediction models do not perform well in people with diabetes. We therefore aimed to identify novel predictors for six facets of CVD, (including coronary heart disease (CHD), Ischemic stroke, heart failure (HF), and atrial fibrillation (AF)) in people with T2DM. Methods Analyses were conducted using the UK biobank and were stratified on history of CVD and of T2DM: 459,142 participants without diabetes or a history of CVD, 14,610 with diabetes but without CVD, and 4,432 with diabetes and a history of CVD. Replication was performed using a 20% hold-out set, ranking features on their permuted c-statistic. Results Out of the 600+ candidate features, we identified a subset of replicated features, ranging between 32 for CHD in people with diabetes to 184 for CVD+HF+AF in people without diabetes. Classical CVD risk factors (e.g. parental or maternal history of heart disease, or blood pressure) were relatively highly ranked for people without diabetes. The top predictors in the people with diabetes without a CVD history included: cystatin C, self-reported health satisfaction, biochemical measures of ill health (e.g. plasma albumin). For people with diabetes and a history of CVD top features were: self-reported ill health, and blood cell counts measurements (e.g. red cell distribution width). We additionally identified risk factors unique to people with diabetes, consisting of information on dietary patterns, mental health and biochemistry measures. Consideration of these novel features improved risk classification, for example per 1000 people with diabetes 133 CVD and 165 HF cases appropriately received a higher risk. Conclusion Through data-driven feature selection we identified a substantial number of features relevant for prediction of cardiovascular risk in people with diabetes, the majority of which related to non-classical risk factors such as mental health, general illness markers, and kidney disease.
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Affiliation(s)
- K Dziopa
- Institute of Health Informatics, University College London, London, United Kingdom
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
- Department of Cardiology, Amsterdam Cardiovascular Science, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - N Chaturvedi
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, United Kingdom
| | - F W Asselbergs
- Institute of Health Informatics, University College London, London, United Kingdom
- Department of Cardiology, Amsterdam Cardiovascular Science, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- The National Institute for Health Research UCL Hospitals Biomedical Research Centre, University College London, London, United Kingdom
| | - A F Schmidt
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
- Department of Cardiology, Amsterdam Cardiovascular Science, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- UCL BHF Research Accelerator Centre, London, UK
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Hingorani AD, Gratton J, Finan C, Schmidt AF, Patel R, Sofat R, Kuan V, Langenberg C, Hemingway H, Morris JK, Wald NJ. Performance of polygenic risk scores in screening, prediction, and risk stratification: secondary analysis of data in the Polygenic Score Catalog. BMJ Med 2023; 2:e000554. [PMID: 37859783 PMCID: PMC10582890 DOI: 10.1136/bmjmed-2023-000554] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 08/31/2023] [Indexed: 10/21/2023]
Abstract
Objective To clarify the performance of polygenic risk scores in population screening, individual risk prediction, and population risk stratification. Design Secondary analysis of data in the Polygenic Score Catalog. Setting Polygenic Score Catalog, April 2022. Secondary analysis of 3915 performance metric estimates for 926 polygenic risk scores for 310 diseases to generate estimates of performance in population screening, individual risk, and population risk stratification. Participants Individuals contributing to the published studies in the Polygenic Score Catalog. Main outcome measures Detection rate for a 5% false positive rate (DR5) and the population odds of becoming affected given a positive result; individual odds of becoming affected for a person with a particular polygenic score; and odds of becoming affected for groups of individuals in different portions of a polygenic risk score distribution. Coronary artery disease and breast cancer were used as illustrative examples. Results For performance in population screening, median DR5 for all polygenic risk scores and all diseases studied was 11% (interquartile range 8-18%). Median DR5 was 12% (9-19%) for polygenic risk scores for coronary artery disease and 10% (9-12%) for breast cancer. The population odds of becoming affected given a positive results were 1:8 for coronary artery disease and 1:21 for breast cancer, with background 10 year odds of 1:19 and 1:41, respectively, which are typical for these diseases at age 50. For individual risk prediction, the corresponding 10 year odds of becoming affected for individuals aged 50 with a polygenic risk score at the 2.5th, 25th, 75th, and 97.5th centiles were 1:54, 1:29, 1:15, and 1:8 for coronary artery disease and 1:91, 1:56, 1:34, and 1:21 for breast cancer. In terms of population risk stratification, at age 50, the risk of coronary artery disease was divided into five groups, with 10 year odds of 1:41 and 1:11 for the lowest and highest quintile groups, respectively. The 10 year odds was 1:7 for the upper 2.5% of the polygenic risk score distribution for coronary artery disease, a group that contributed 7% of cases. The corresponding estimates for breast cancer were 1:72 and 1:26 for the lowest and highest quintile groups, and 1:19 for the upper 2.5% of the distribution, which contributed 6% of cases. Conclusion Polygenic risk scores performed poorly in population screening, individual risk prediction, and population risk stratification. Strong claims about the effect of polygenic risk scores on healthcare seem to be disproportionate to their performance.
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Affiliation(s)
- Aroon D Hingorani
- Institute of Cardiovascular Science, University College London, London, UK
- British Heart Foundation Research Accelerator, University College London, London, UK
- National Institute of Health Research Biomedical Research Centre, University College London Hospitals, London, UK
- Health Data Research UK, London, UK
| | - Jasmine Gratton
- Institute of Cardiovascular Science, University College London, London, UK
- British Heart Foundation Research Accelerator, University College London, London, UK
| | - Chris Finan
- Institute of Cardiovascular Science, University College London, London, UK
- British Heart Foundation Research Accelerator, University College London, London, UK
- National Institute of Health Research Biomedical Research Centre, University College London Hospitals, London, UK
- Health Data Research UK, London, UK
| | - A Floriaan Schmidt
- Institute of Cardiovascular Science, University College London, London, UK
- National Institute of Health Research Biomedical Research Centre, University College London Hospitals, London, UK
- Health Data Research UK, London, UK
- University Medical Centre Utrecht, Utrecht, Netherlands
| | - Riyaz Patel
- Institute of Cardiovascular Science, University College London, London, UK
- British Heart Foundation Research Accelerator, University College London, London, UK
- National Institute of Health Research Biomedical Research Centre, University College London Hospitals, London, UK
- Health Data Research UK, London, UK
| | - Reecha Sofat
- Health Data Research UK, London, UK
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
| | - Valerie Kuan
- Institute of Cardiovascular Science, University College London, London, UK
- British Heart Foundation Research Accelerator, University College London, London, UK
- National Institute of Health Research Biomedical Research Centre, University College London Hospitals, London, UK
| | - Claudia Langenberg
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK
- Computational Medicine, Berlin Institute of Health at Charite Universitatzmedizin, Berlin, Germany
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Harry Hemingway
- British Heart Foundation Research Accelerator, University College London, London, UK
- National Institute of Health Research Biomedical Research Centre, University College London Hospitals, London, UK
- Health Data Research UK, London, UK
- Institute of Health Informatics, University College London, London, UK
| | - Joan K Morris
- Population Health Research Institute, St George's University of London, London, UK
| | - Nicholas J Wald
- Institute of Health Informatics, University College London, London, UK
- Population Health Research Institute, St George's University of London, London, UK
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Schmidt AF, Leinveber P, Panovsky R, Soukup L, Machac P, van de Leur RR, Sammani A, Lekadir K, Ter Riele A, Asselbergs FW, Boonstra MJ. DCM-PROGRESS: predicting end-stage heart failure in non-ischemic dilated cardiomyopathy patients. medRxiv 2023:2023.09.10.23295251. [PMID: 37745419 PMCID: PMC10516079 DOI: 10.1101/2023.09.10.23295251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Aims Patients with non-ischemic dilated cardiomyopathy (DCM) are at considerable risk for end-stage heart failure (HF), requiring close monitoring to identify early signs of disease. We aimed to develop a model to predict the 5-years risk of end-stage HF, allowing for tailored patient monitoring and management. Methods and results Derivation data were available from a Dutch cohort of 293 DCM patients, with external validation available from a Czech Republic cohort of 235 DCM patients. Candidate predictors spanned patient and family histories, ECG and echocardiogram measurements, and biochemistry. End-stage HF was defined as a composite of death, heart transplantation, or implantation of a ventricular assist device. Lasso and sigmoid kernel support vector machine (SVM) algorithms were trained using cross-validation. During follow-up 65 (22%) of Dutch DCM patients developed end-stage HF, with 27 (11%) cases in the Czech cohort. Out of the two considered models, the lasso model (retaining NYHA class, heart rate, systolic blood pressure, height, R-axis, and TAPSE as predictors) reached the highest discriminative performance (testing c-statistic of 0.85, 95%CI 0.58; 0.94), which was confirmed in the external validation cohort (c-statistic of 0.75, 95%CI 0.61; 0.82), compared to a c-statistic of 0.69 for the MAGGIC score. Both the MAGGIC score and the DCM-PROGRESS model slightly over-estimated the true risk, but were otherwise appropriately calibrated. Conclusion We developed a highly discriminative risk-prediction model for end-stage HF in DCM patients. The model was validated in two countries, suggesting the model can meaningfully improve clinical decision-making.
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Affiliation(s)
- A F Schmidt
- Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, the Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, United Kingdom
- UCL British Heart Foundation Research Accelerator, London, United Kingdom
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - P Leinveber
- International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic
| | - R Panovsky
- Department of Internal Medicine-Cardioangiology, International Clinical Research Center, St. Anne's University Hospital Brno, Czech Republic
- International Clinical Research Center, Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - L Soukup
- International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic
| | - P Machac
- International Clinical Research Center, St. Anne's University Hospital Brno, Brno, Czech Republic
| | - R R van de Leur
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - A Sammani
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - K Lekadir
- Department de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain
| | - A Ter Riele
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - F W Asselbergs
- Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, the Netherlands
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Institute of Health Informatics, Faculty of Population Health, University College London, London, UK
| | - M J Boonstra
- Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, the Netherlands
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
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Schmidt AF, Finan C, Chopade S, Ellmerich S, Rossor MN, Hingorani AD, Pepys MB. Genetic evidence for serum amyloid P component as a drug target for treatment of neurodegenerative disorders. medRxiv 2023:2023.08.15.23293564. [PMID: 37645746 PMCID: PMC10462209 DOI: 10.1101/2023.08.15.23293564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
The direct causes of neurodegeneration underlying Alzheimer's disease (AD) and many other dementias, are not known. Here we identify serum amyloid P component (SAP), a constitutive plasma protein normally excluded from the brain, as a potential drug target. After meta-analysis of three genome-wide association studies, comprising 44,288 participants, cis-Mendelian randomization showed that genes responsible for higher plasma SAP values are significantly associated with AD, Lewy body dementia and plasma tau concentration. These genetic findings are consistent with experimental evidence of SAP neurotoxicity and the strong, independent association of neocortex SAP content with dementia at death. Depletion of SAP from the blood and from the brain, as is provided by the safe, well tolerated, experimental drug, miridesap, may therefore contribute to treatment of neurodegeneration.
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Affiliation(s)
- A Floriaan Schmidt
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, United Kingdom
- UCL British Heart Foundation Research Accelerator, London, United Kingdom
- Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, the Netherlands
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Chris Finan
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, United Kingdom
- UCL British Heart Foundation Research Accelerator, London, United Kingdom
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Sandesh Chopade
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, United Kingdom
- UCL British Heart Foundation Research Accelerator, London, United Kingdom
| | - Stephan Ellmerich
- Wolfson Drug Discovery Unit, Division of Medicine, University College London, London, United Kingdom
| | - Martin N Rossor
- UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, United Kingdom
| | - Aroon D Hingorani
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, United Kingdom
- UCL British Heart Foundation Research Accelerator, London, United Kingdom
| | - Mark B Pepys
- Wolfson Drug Discovery Unit, Division of Medicine, University College London, London, United Kingdom
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de Ruiter SC, Schmidt AF, Grobbee DE, den Ruijter HM, Peters SAE. Sex-specific Mendelian randomisation to assess the causality of sex differences in the effects of risk factors and treatment: spotlight on hypertension. J Hum Hypertens 2023; 37:602-608. [PMID: 37024639 PMCID: PMC10403357 DOI: 10.1038/s41371-023-00821-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 02/24/2023] [Accepted: 03/16/2023] [Indexed: 04/08/2023]
Abstract
Hypertension is a key modifiable risk factor for cardiovascular disease. Several observational studies have found a stronger association of blood pressure and cardiovascular disease risk in women compared to men. Since observational studies can be affected by sex-specific residual confounding and reverse causation, it remains unclear whether these differences reflect actual differential effects. Other study designs are needed to uncover the causality of sex differences in the strength of risk factor and treatment effects. Mendelian randomisation (MR) uses genetic variants as instrumental variables to provide evidence about putative causal relations between risk factors and outcomes. By exploiting the random allocation of genes at gamete forming, MR is unaffected by confounding and results in more reliable causal effect estimates. In this review, we discuss why and how sex-specific MR and cis-MR could be used to study sex differences in risk factor and drug target effects. Sex-specific MR can be helpful to strengthen causal inferences in the field of sex differences, where it is often challenging to distinguish nature from nurture. The challenge of sex-specific (drug target) MR lays in leveraging robust genetic instruments from sex-specific GWAS studies which are not commonly available. Knowledge on sex-specific causal effects of hypertension, or other risk factors, could improve clinical practice and health policies by tailoring interventions based on personalised risk. Drug target MR can help to determine the anticipated on-target effects of a drug compound and to identify targets to pursue in drug development.
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Affiliation(s)
- Sophie C de Ruiter
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - A Floriaan Schmidt
- Department of Cardiology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- UCL British Heart Foundation Research Accelerator Centre, London, UK
| | - Diederick E Grobbee
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Hester M den Ruijter
- Laboratory of Experimental Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Sanne A E Peters
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
- The George Institute for Global Health, School of Public Health, Imperial College London, London, UK.
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Bourfiss M, van Vugt M, Alasiri AI, Ruijsink B, van Setten J, Schmidt AF, Dooijes D, Puyol-Antón E, Velthuis BK, van Tintelen JP, te Riele AS, Baas AF, Asselbergs FW. Prevalence and Disease Expression of Pathogenic and Likely Pathogenic Variants Associated With Inherited Cardiomyopathies in the General Population. Circ Genom Precis Med 2022; 15:e003704. [PMID: 36264615 PMCID: PMC9770140 DOI: 10.1161/circgen.122.003704] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Pathogenic and likely pathogenic variants associated with arrhythmogenic right ventricular cardiomyopathy (ARVC), dilated cardiomyopathy (DCM), and hypertrophic cardiomyopathy (HCM) are recommended to be reported as secondary findings in genome sequencing studies. This provides opportunities for early diagnosis, but also fuels uncertainty in variant carriers (G+), since disease penetrance is incomplete. We assessed the prevalence and disease expression of G+ in the general population. METHODS We identified pathogenic and likely pathogenic variants associated with ARVC, DCM and/or HCM in 200 643 UK Biobank individuals, who underwent whole exome sequencing. We calculated the prevalence of G+ and analyzed the frequency of cardiomyopathy/heart failure diagnosis. In undiagnosed individuals, we analyzed early signs of disease expression using available electrocardiography and cardiac magnetic resonance imaging data. RESULTS We found a prevalence of 1:578, 1:251, and 1:149 for pathogenic and likely pathogenic variants associated with ARVC, DCM and HCM respectively. Compared with controls, cardiovascular mortality was higher in DCM G+ (odds ratio 1.67 [95% CI 1.04; 2.59], P=0.030), but similar in ARVC and HCM G+ (P≥0.100). Cardiomyopathy or heart failure diagnosis were more frequent in DCM G+ (odds ratio 3.66 [95% CI 2.24; 5.81], P=4.9×10-7) and HCM G+ (odds ratio 3.03 [95% CI 1.98; 4.56], P=5.8×10-7), but comparable in ARVC G+ (P=0.172). In contrast, ARVC G+ had more ventricular arrhythmias (P=3.3×10-4). In undiagnosed individuals, left ventricular ejection fraction was reduced in DCM G+ (P=0.009). CONCLUSIONS In the general population, pathogenic and likely pathogenic variants associated with ARVC, DCM, or HCM are not uncommon. Although G+ have increased mortality and morbidity, disease penetrance in these carriers from the general population remains low (1.2-3.1%). Follow-up decisions in case of incidental findings should not be based solely on a variant, but on multiple factors, including family history and disease expression.
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Affiliation(s)
- Mimount Bourfiss
- Dept of Cardiology, Univ Medical Center Utrecht, Utrecht Univ, Utrecht, the Netherlands (M.B., M.v.V., A.I.A., A.S.J.M.t.R., B.R., J.v.S., A.F.S., F.W.A.)
| | - Marion van Vugt
- Dept of Cardiology, Univ Medical Center Utrecht, Utrecht Univ, Utrecht, the Netherlands (M.B., M.v.V., A.I.A., A.S.J.M.t.R., B.R., J.v.S., A.F.S., F.W.A.)
| | - Abdulrahman I. Alasiri
- Dept of Cardiology, Univ Medical Center Utrecht, Utrecht Univ, Utrecht, the Netherlands (M.B., M.v.V., A.I.A., A.S.J.M.t.R., B.R., J.v.S., A.F.S., F.W.A.)
| | - Bram Ruijsink
- Dept of Cardiology, Univ Medical Center Utrecht, Utrecht Univ, Utrecht, the Netherlands (M.B., M.v.V., A.I.A., A.S.J.M.t.R., B.R., J.v.S., A.F.S., F.W.A.)
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom (B.R., E.P.-A.)
| | - Jessica van Setten
- Dept of Cardiology, Univ Medical Center Utrecht, Utrecht Univ, Utrecht, the Netherlands (M.B., M.v.V., A.I.A., A.S.J.M.t.R., B.R., J.v.S., A.F.S., F.W.A.)
| | - A. Floriaan Schmidt
- Dept of Cardiology, Univ Medical Center Utrecht, Utrecht Univ, Utrecht, the Netherlands (M.B., M.v.V., A.I.A., A.S.J.M.t.R., B.R., J.v.S., A.F.S., F.W.A.)
- Faculty of Population Health Sciences Institute of Cardiovascular Science, London, London, United Kingdom (A.F.S., F.W.A.)
| | - Dennis Dooijes
- Dept of Genetics, Univ Medical Center Utrecht, Utrecht Univ, Utrecht, the Netherlands (D.D., J.P.v.T., A.F.B.)
| | - Esther Puyol-Antón
- School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom (B.R., E.P.-A.)
| | - Birgitta K. Velthuis
- Dept of Radiology, Univ Medical Center Utrecht, Utrecht Univ, Utrecht, the Netherlands (B.K.V.)
| | - J. Peter van Tintelen
- Dept of Genetics, Univ Medical Center Utrecht, Utrecht Univ, Utrecht, the Netherlands (D.D., J.P.v.T., A.F.B.)
| | - Anneline S.J.M. te Riele
- Dept of Cardiology, Univ Medical Center Utrecht, Utrecht Univ, Utrecht, the Netherlands (M.B., M.v.V., A.I.A., A.S.J.M.t.R., B.R., J.v.S., A.F.S., F.W.A.)
- Netherlands Heart Institute, Utrecht, the Netherlands (A.S.J.M.t.R)
| | - Annette F. Baas
- Dept of Genetics, Univ Medical Center Utrecht, Utrecht Univ, Utrecht, the Netherlands (D.D., J.P.v.T., A.F.B.)
| | - Folkert W. Asselbergs
- Dept of Cardiology, Univ Medical Center Utrecht, Utrecht Univ, Utrecht, the Netherlands (M.B., M.v.V., A.I.A., A.S.J.M.t.R., B.R., J.v.S., A.F.S., F.W.A.)
- Faculty of Population Health Sciences Institute of Cardiovascular Science, London, London, United Kingdom (A.F.S., F.W.A.)
- Health Data Research UK & Institute of Health Informatics, Univ College London, London, United Kingdom (F.W.A.)
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9
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Borges MC, Haycock P, Zheng J, Hemani G, Howe LJ, Schmidt AF, Staley JR, Lumbers RT, Henry A, Lemaitre RN, Gaunt TR, Holmes MV, Davey Smith G, Hingorani AD, Lawlor DA. The impact of fatty acids biosynthesis on the risk of cardiovascular diseases in Europeans and East Asians: a Mendelian randomization study. Hum Mol Genet 2022; 31:4034-4054. [PMID: 35796550 PMCID: PMC9703943 DOI: 10.1093/hmg/ddac153] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 06/11/2022] [Accepted: 06/24/2022] [Indexed: 11/14/2022] Open
Abstract
Despite early interest, the evidence linking fatty acids to cardiovascular diseases (CVDs) remains controversial. We used Mendelian randomization to explore the involvement of polyunsaturated (PUFA) and monounsaturated (MUFA) fatty acids biosynthesis in the etiology of several CVD endpoints in up to 1 153 768 European (maximum 123 668 cases) and 212 453 East Asian (maximum 29 319 cases) ancestry individuals. As instruments, we selected single nucleotide polymorphisms mapping to genes with well-known roles in PUFA (i.e. FADS1/2 and ELOVL2) and MUFA (i.e. SCD) biosynthesis. Our findings suggest that higher PUFA biosynthesis rate (proxied by rs174576 near FADS1/2) is related to higher odds of multiple CVDs, particularly ischemic stroke, peripheral artery disease and venous thromboembolism, whereas higher MUFA biosynthesis rate (proxied by rs603424 near SCD) is related to lower odds of coronary artery disease among Europeans. Results were unclear for East Asians as most effect estimates were imprecise. By triangulating multiple approaches (i.e. uni-/multi-variable Mendelian randomization, a phenome-wide scan, genetic colocalization and within-sibling analyses), our results are compatible with higher low-density lipoprotein (LDL) cholesterol (and possibly glucose) being a downstream effect of higher PUFA biosynthesis rate. Our findings indicate that PUFA and MUFA biosynthesis are involved in the etiology of CVDs and suggest LDL cholesterol as a potential mediating trait between PUFA biosynthesis and CVDs risk.
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Affiliation(s)
- Maria-Carolina Borges
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PN, UK
| | - Phillip Haycock
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PN, UK
| | - Jie Zheng
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PN, UK
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PN, UK
| | - Laurence J Howe
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PN, UK
| | - A Floriaan Schmidt
- Faculty of Population Health Sciences, Institute of Cardiovascular Science, University College London, London WC1E 6DD, UK
- Department of Cardiology, Division Heart and Lungs, UMC Utrecht, Utrecht 3584 CX, The Netherlands
| | - James R Staley
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PN, UK
| | - R Thomas Lumbers
- Institute of Health Informatics, University College London, London NW1 2DA, UK
- Health Data Research UK London, University College London NW1 2DA, UK
- UCL British Heart Foundation Research Accelerator, London NW1 2DA, UK
| | - Albert Henry
- Faculty of Population Health Sciences, Institute of Cardiovascular Science, University College London, London WC1E 6DD, UK
- Institute of Health Informatics, University College London, London NW1 2DA, UK
- UCL British Heart Foundation Research Accelerator, London NW1 2DA, UK
| | - Rozenn N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA WA 98101, USA
| | - Tom R Gaunt
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PN, UK
| | - Michael V Holmes
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK
- Clinical Trial Service and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PN, UK
| | - Aroon D Hingorani
- Faculty of Population Health Sciences, Institute of Cardiovascular Science, University College London, London WC1E 6DD, UK
- Health Data Research UK London, University College London NW1 2DA, UK
- UCL British Heart Foundation Research Accelerator, London NW1 2DA, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2PN, UK
- NIHR Bristol Biomedical Research Centre, Bristol BS8 2BN, UK
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10
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Abstract
Background Epidemiological studies show that women are generally at lower risk for cardiovascular disease than men. Here, we investigated the sex-specific differential effect of genetically increased low-density lipoprotein cholesterol (LDL-C) on cardiovascular disease (CVD) and other lipid-associated diseases. Methods and Results This is a 2-sample Mendelian randomization study that uses individual participant data from 425 043 participants from the UK Biobank, including 229 279 female participants. An 80-variant LDL-C weighted genetic score was generated. Linear and logistic regression models with interactions were used to identify differences between sex-specific LDL-C effects on lipids, carotid-intima media thickness, and multiple cardiovascular outcomes such as CVD, ischemic heart disease, peripheral artery disease, heart failure, aortic valve disease, type 2 diabetes, atrial fibrillation, and aortic aneurysm and dissection. After correction for multiple testing, we observed that the genetically increased LDL-C effect on CVD events was sex specific: per SD genetically increased LDL-C, female participants had a higher LDL-C increase but an attenuated CVD risk increase compared with male participants (LDL-C: female participants 0.71 mmol/L, 95% CI, 0.70-0.72 and male participants 0.57 mmol/L, 95% CI, 0.56-0.59. P for interaction: 5.03×10-60; CVD: female participants: odds ratio [OR], 1.32; 95% CI 1.24-1.40 and male participants: OR, 1.52; 95% CI, 1.46-1.58. P for interaction: 9.88×10-5). We also observed attenuated risks for ischemic heart disease and (nominally for) heart failure in female participants, and genetically increased LDL-C results in higher risk for aortic valve disease in female participants compared with male participants. Genetically increased LDL-C was also associated with an attenuated carotid-intima media thickness increase in female participants. We did not observe other significant attenuations. Sensitivity analyses with an unweighted genetic score and sex-specific weighted genetic scores showed similar results. Conclusions We found that genetically increased LDL-C has a sex-specific differential effect on the risk for cardiovascular disease, ischemic heart disease, heart failure, and aortic valve stenosis. Our observations provide evidence that LDL-C might be a less important determinant of CVD in women compared with men, suggesting that male patients might benefit more from LDL-C targeted therapies for CVD management than female patients and warranting investigations into the sex-specific relative contribution of risk factors for CVD.
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Affiliation(s)
- Arjen J. Cupido
- Department of Vascular MedicineAmsterdam University Medical Centerslocation AMCUniversity of AmsterdamNetherlands
- Department of CardiologyDivision of Heart & LungsUniversity Medical Center UtrechtUtrecht UniversityUtrechtthe Netherlands
- Division of CardiologyDepartment of MedicineUniversity of California, Los AngelesLos AngelesCA
| | - Folkert W. Asselbergs
- Department of CardiologyDivision of Heart & LungsUniversity Medical Center UtrechtUtrecht UniversityUtrechtthe Netherlands
- Faculty of Population Health SciencesInstitute of Cardiovascular ScienceUniversity College LondonLondonUnited Kingdom
- Health Data Research UK and Institute of Health InformaticsUniversity College LondonLondonUnited Kingdom
| | - A. Floriaan Schmidt
- Department of CardiologyDivision of Heart & LungsUniversity Medical Center UtrechtUtrecht UniversityUtrechtthe Netherlands
- Faculty of Population Health SciencesInstitute of Cardiovascular ScienceUniversity College LondonLondonUnited Kingdom
| | - G. Kees Hovingh
- Department of Vascular MedicineAmsterdam University Medical Centerslocation AMCUniversity of AmsterdamNetherlands
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11
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Cupido AJ, Asselbergs FW, Natarajan P, Ridker PM, Hovingh GK, Schmidt AF. Dissecting the IL-6 pathway in cardiometabolic disease: a Mendelian randomization study on both IL6 and IL6R. Br J Clin Pharmacol 2021; 88:2875-2884. [PMID: 34931349 PMCID: PMC9303316 DOI: 10.1111/bcp.15191] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 10/07/2021] [Accepted: 10/28/2021] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Chronic inflammation is a risk factor for cardiovascular disease. IL-6 signaling perturbation through IL-6 or IL-6R blockade may have potential benefit on cardiovascular risk. It is unknown whether targeting either IL-6 or IL-6 receptor may result in similar effects on CVD and adverse events. We compared the anticipated effects of targeting IL-6 and IL-6 receptor on cardiometabolic risk and potential side effects. METHODS We constructed four instruments: two main instruments with genetic variants in the IL6 and IL6R loci weighted for their association with CRP, and two after firstly filtering variants for their association with IL-6 or IL-6R expression. Analyses were performed for coronary artery disease (CAD), ischemic stroke, atrial fibrillation (AF), heart failure, type 2 diabetes (T2D), rheumatoid arthritis (RA), infection endpoints, and quantitative hematological, metabolic, and anthropometric parameters. RESULTS A 1 mg/L lower CRP by the IL6 instrument was associated with lower CAD (OR 0.86, 95% CI 0.77;0.96), AF, and T2D risk. A 1mg/L lower CRP by the IL6R instrument was associated with lower CAD (OR 0.90, 95% CI 0.86;0.95), any stroke and ischemic stroke, AF, RA risk and higher pneumonia risk. The eQTL filtered results were in concordance with the main results, but with wider confidence intervals. CONCLUSIONS IL-6 signalling perturbation by either IL6 or IL6R genetic instruments is associated with a similar risk reduction for multiple cardiometabolic diseases, suggesting that both IL-6 and IL-6R are potential therapeutic targets to lower CVD. Moreover, IL-6 rather than IL-6R inhibition might have a more favorable pneumonia risk.
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Affiliation(s)
- Arjen J Cupido
- Department of Vascular Medicine, Amsterdam University Medical Centers, location AMC, University of Amsterdam, Amsterdam, Netherlands.,Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.,Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom.,Health Data Research UK and Institute of Health Informatics, University College London, London, United Kingdom
| | - Pradeep Natarajan
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, US.,Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, US
| | | | - Paul M Ridker
- Divisions of Preventive Medicine and Cardiovascular Medicine, Department of Medicine, Center for Cardiovascular Disease Prevention, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - G Kees Hovingh
- Department of Vascular Medicine, Amsterdam University Medical Centers, location AMC, University of Amsterdam, Amsterdam, Netherlands
| | - A Floriaan Schmidt
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.,Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
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12
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Gill D, Georgakis MK, Walker VM, Schmidt AF, Gkatzionis A, Freitag DF, Finan C, Hingorani AD, Howson JM, Burgess S, Swerdlow DI, Davey Smith G, Holmes MV, Dichgans M, Scott RA, Zheng J, Psaty BM, Davies NM. Mendelian randomization for studying the effects of perturbing drug targets. Wellcome Open Res 2021; 6:16. [PMID: 33644404 PMCID: PMC7903200 DOI: 10.12688/wellcomeopenres.16544.2] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/01/2021] [Indexed: 12/11/2022] Open
Abstract
Drugs whose targets have genetic evidence to support efficacy and safety are more likely to be approved after clinical development. In this paper, we provide an overview of how natural sequence variation in the genes that encode drug targets can be used in Mendelian randomization analyses to offer insight into mechanism-based efficacy and adverse effects. Large databases of summary level genetic association data are increasingly available and can be leveraged to identify and validate variants that serve as proxies for drug target perturbation. As with all empirical research, Mendelian randomization has limitations including genetic confounding, its consideration of lifelong effects, and issues related to heterogeneity across different tissues and populations. When appropriately applied, Mendelian randomization provides a useful empirical framework for using population level data to improve the success rates of the drug development pipeline.
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Affiliation(s)
- Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Centre for Pharmacology and Therapeutics, Department of Medicine, Imperial College London, London, UK
- Novo Nordisk Research Centre, Oxford, UK
- Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George’s, University of London, London, UK
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George’s University Hospitals NHS Foundation Trust, London, UK
| | - Marios K. Georgakis
- Institute for Stroke and Dementia Research (ISD), University Hospital of Ludwig-Maximilians-University (LMU), Munich, Germany
| | - Venexia M. Walker
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - A. Floriaan Schmidt
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Apostolos Gkatzionis
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Daniel F. Freitag
- Bayer Pharmaceuticals, Open Innovation & Digital Technologies, Wuppertal, Germany
| | - Chris Finan
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- UCL British Heart Foundation Research Acceleratorversity College London, London, UK
- UCL Hospitals, NIHR Biomedical Research Centre, London, UK
| | - Aroon D. Hingorani
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- UCL British Heart Foundation Research Acceleratorversity College London, London, UK
- UCL Hospitals, NIHR Biomedical Research Centre, London, UK
| | | | - Stephen Burgess
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Daniel I. Swerdlow
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Michael V. Holmes
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital of Ludwig-Maximilians-University (LMU), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- German Centre for Neurodegenerative Diseases (DZNE), Munich, Germany
| | | | - Jie Zheng
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology and Health Services, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Neil M. Davies
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
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13
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Gill D, Georgakis MK, Walker VM, Schmidt AF, Gkatzionis A, Freitag DF, Finan C, Hingorani AD, Howson JM, Burgess S, Swerdlow DI, Davey Smith G, Holmes MV, Dichgans M, Scott RA, Zheng J, Psaty BM, Davies NM. Mendelian randomization for studying the effects of perturbing drug targets. Wellcome Open Res 2021; 6:16. [PMID: 33644404 PMCID: PMC7903200 DOI: 10.12688/wellcomeopenres.16544.1] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/21/2021] [Indexed: 08/17/2023] Open
Abstract
Drugs whose targets have genetic evidence to support efficacy and safety are more likely to be approved after clinical development. In this paper, we provide an overview of how natural sequence variation in the genes that encode drug targets can be used in Mendelian randomization analyses to offer insight into mechanism-based efficacy and adverse effects. Large databases of summary level genetic association data are increasingly available and can be leveraged to identify and validate variants that serve as proxies for drug target perturbation. As with all empirical research, Mendelian randomization has limitations including genetic confounding, its consideration of lifelong effects, and issues related to heterogeneity across different tissues and populations. When appropriately applied, Mendelian randomization provides a useful empirical framework for using population level data to improve the success rates of the drug development pipeline.
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Affiliation(s)
- Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Centre for Pharmacology and Therapeutics, Department of Medicine, Imperial College London, London, UK
- Novo Nordisk Research Centre, Oxford, UK
- Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George’s, University of London, London, UK
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George’s University Hospitals NHS Foundation Trust, London, UK
| | - Marios K. Georgakis
- Institute for Stroke and Dementia Research (ISD), University Hospital of Ludwig-Maximilians-University (LMU), Munich, Germany
| | - Venexia M. Walker
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - A. Floriaan Schmidt
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Apostolos Gkatzionis
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Daniel F. Freitag
- Bayer Pharmaceuticals, Open Innovation & Digital Technologies, Wuppertal, Germany
| | - Chris Finan
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- UCL British Heart Foundation Research Acceleratorversity College London, London, UK
- UCL Hospitals, NIHR Biomedical Research Centre, London, UK
| | - Aroon D. Hingorani
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
- UCL British Heart Foundation Research Acceleratorversity College London, London, UK
- UCL Hospitals, NIHR Biomedical Research Centre, London, UK
| | | | - Stephen Burgess
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Daniel I. Swerdlow
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Michael V. Holmes
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital of Ludwig-Maximilians-University (LMU), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- German Centre for Neurodegenerative Diseases (DZNE), Munich, Germany
| | | | - Jie Zheng
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology and Health Services, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Neil M. Davies
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
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14
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Joshi R, Wannamethee G, Engmann J, Gaunt T, Lawlor DA, Price J, Papacosta O, Shah T, Tillin T, Whincup P, Chaturvedi N, Kivimaki M, Kuh D, Kumari M, Hughes AD, Casas JP, Humphries SE, Hingorani AD, Schmidt AF. Establishing reference intervals for triglyceride-containing lipoprotein subfraction metabolites measured using nuclear magnetic resonance spectroscopy in a UK population. Ann Clin Biochem 2020; 58:47-53. [PMID: 32936666 PMCID: PMC7791273 DOI: 10.1177/0004563220961753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Nuclear magnetic resonance (NMR) spectroscopy allows triglycerides to be subclassified into 14 different classes based on particle size and lipid content. We recently showed that these subfractions have differential associations with cardiovascular disease events. Here we report the distributions and define reference interval ranges for 14 triglyceride-containing lipoprotein subfraction metabolites. METHODS Lipoprotein subfractions using the Nightingale NMR platform were measured in 9073 participants from four cohort studies contributing to the UCL-Edinburgh-Bristol consortium. The distribution of each metabolite was assessed, and reference interval ranges were calculated for a disease-free population, by sex and age group (<55, 55-65, >65 years), and in a subgroup population of participants with cardiovascular disease or type 2 diabetes. We also determined the distribution across body mass index and smoking status. RESULTS The largest reference interval range was observed in the medium very-low density lipoprotein subclass (2.5th 97.5th percentile; 0.08 to 0.68 mmol/L). The reference intervals were comparable among male and female participants, with the exception of triglyceride in high-density lipoprotein. Triglyceride subfraction concentrations in very-low density lipoprotein, intermediate-density lipoprotein, low-density lipoprotein and high-density lipoprotein subclasses increased with increasing age and increasing body mass index. Triglyceride subfraction concentrations were significantly higher in ever smokers compared to never smokers, among those with clinical chemistry measured total triglyceride greater than 1.7 mmol/L, and in those with cardiovascular disease, and type 2 diabetes as compared to disease-free subjects. CONCLUSION This is the first study to establish reference interval ranges for 14 triglyceride-containing lipoprotein subfractions in samples from the general population measured using the nuclear magnetic resonance platform. The utility of nuclear magnetic resonance lipid measures may lead to greater insights for the role of triglyceride in cardiovascular disease, emphasizing the importance of appropriate reference interval ranges for future clinical decision making.
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Affiliation(s)
- Roshni Joshi
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
| | - Goya Wannamethee
- Department of Primary Care & Population Health, Faculty of Population Health, University College London, London, UK
| | - Jorgen Engmann
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
| | - Tom Gaunt
- Department of Primary Care & Population Health, Faculty of Population Health, University College London, London, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,Bristol NIHR Biomedical Research Centre, Bristol, UK.,Population Health Science, Bristol Medical School, Bristol, UK
| | - Jackie Price
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Olia Papacosta
- Department of Primary Care & Population Health, Faculty of Population Health, University College London, London, UK
| | - Tina Shah
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
| | - Therese Tillin
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Peter Whincup
- Population Health Research Institute, St George's, University of London, London, UK
| | - Nishi Chaturvedi
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
| | - Mika Kivimaki
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
| | - Meena Kumari
- Institute for Social and Economic Research, University of Essex, Colchester, UK
| | - Alun D Hughes
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
| | - Juan P Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare, MA, USA.,Division of Aging, Department of Medicine, Brigham and Women's Hospital and Harvard School of Medicine, Boston, MA, USA
| | - Steve E Humphries
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
| | - Aroon D Hingorani
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
| | - A Floriaan Schmidt
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK.,Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands
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15
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Abstract
Abstract
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Affiliation(s)
- Aroon D Hingorani
- UCL Institute of Cardiovascular Science, London, UK.,Health Data Research UK, London, UK.,British Heart Foundation UCL Research Accelerator. London, UK
| | - Chris Finan
- UCL Institute of Cardiovascular Science, London, UK.,Health Data Research UK, London, UK.,British Heart Foundation UCL Research Accelerator. London, UK
| | - A Floriaan Schmidt
- UCL Institute of Cardiovascular Science, London, UK.,British Heart Foundation UCL Research Accelerator. London, UK.,University Medical Centre, Utrecht, The Netherlands
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16
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Joshi R, Wannamethee SG, Engmann J, Gaunt T, Lawlor DA, Price J, Papacosta O, Shah T, Tillin T, Chaturvedi N, Kivimaki M, Kuh D, Kumari M, Hughes AD, Casas JP, Humphries S, Hingorani AD, Schmidt AF. Triglyceride-containing lipoprotein sub-fractions and risk of coronary heart disease and stroke: A prospective analysis in 11,560 adults. Eur J Prev Cardiol 2020; 27:1617-1626. [PMID: 31996015 PMCID: PMC7707881 DOI: 10.1177/2047487319899621] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
AIMS Elevated low-density lipoprotein cholesterol (LDL-C) is a risk factor for cardiovascular disease; however, there is uncertainty about the role of total triglycerides and the individual triglyceride-containing lipoprotein sub-fractions. We measured 14 triglyceride-containing lipoprotein sub-fractions using nuclear magnetic resonance and examined associations with coronary heart disease and stroke. METHODS Triglyceride-containing sub-fraction measures were available in 11,560 participants from the three UK cohorts free of coronary heart disease and stroke at baseline. Multivariable logistic regression was used to estimate the association of each sub-fraction with coronary heart disease and stroke expressed as the odds ratio per standard deviation increment in the corresponding measure. RESULTS The 14 triglyceride-containing sub-fractions were positively correlated with one another and with total triglycerides, and inversely correlated with high-density lipoprotein cholesterol (HDL-C). Thirteen sub-fractions were positively associated with coronary heart disease (odds ratio in the range 1.12 to 1.22), with the effect estimates for coronary heart disease being comparable in subgroup analysis of participants with and without type 2 diabetes, and were attenuated after adjustment for HDL-C and LDL-C. There was no evidence for a clear association of any triglyceride lipoprotein sub-fraction with stroke. CONCLUSIONS Triglyceride sub-fractions are associated with increased risk of coronary heart disease but not stroke, with attenuation of effects on adjustment for HDL-C and LDL-C.
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Affiliation(s)
- Roshni Joshi
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, UK
| | - S Goya Wannamethee
- Department of Primary Care & Population Health, Faculty of Population Health, University College London, UK
| | - Jorgen Engmann
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, UK
| | - Tom Gaunt
- MRC Integrative Epidemiology Unit at the University of Bristol, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, UK.,Bristol NIHR Biomedical Research Centre, UK.,Population Health Science, Bristol Medical School, UK
| | - Jackie Price
- The Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, UK
| | - Olia Papacosta
- Department of Primary Care & Population Health, Faculty of Population Health, University College London, UK
| | - Tina Shah
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, UK
| | - Therese Tillin
- Department of Epidemiology and Public Health, University College London, UK
| | - Nishi Chaturvedi
- Department of Epidemiology and Public Health, University College London, UK
| | - Mika Kivimaki
- Department of Epidemiology and Public Health, University College London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing, UK
| | - Meena Kumari
- Institute for Social and Economic Research, University of Essex, UK
| | - Alun D Hughes
- Department of Epidemiology and Public Health, University College London, UK
| | - Juan P Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare, USA
| | - Steve Humphries
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, UK
| | - Aroon D Hingorani
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, UK
| | - A Floriaan Schmidt
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, UK.,Department of Cardiology, Division Heart and Lungs, University Medical Centre Utrecht, The Netherlands
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17
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Farmer RE, Mathur R, Schmidt AF, Bhaskaran K, Fatemifar G, Eastwood SV, Finan C, Denaxas S, Smeeth L, Chaturvedi N. Associations Between Measures of Sarcopenic Obesity and Risk of Cardiovascular Disease and Mortality: A Cohort Study and Mendelian Randomization Analysis Using the UK Biobank. J Am Heart Assoc 2019; 8:e011638. [PMID: 31221000 PMCID: PMC6662360 DOI: 10.1161/jaha.118.011638] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Accepted: 04/23/2019] [Indexed: 12/22/2022]
Abstract
Background The "healthy obese" hypothesis suggests the risks associated with excess adiposity are reduced in those with higher muscle quality (mass/strength). Alternative possibilities include loss of muscle quality as people become unwell (reverse causality) or unmeasured confounding. Methods and Results We conducted a cohort study using the UK Biobank (n=452 931). Baseline body mass index ( BMI) was used to quantify adiposity and handgrip strength ( HGS ) used for muscle quality. Outcomes were fatal and non-fatal cardiovascular disease, and mortality. As a secondary analysis we used waist-hip-ratio or fat mass percentage instead of BMI , and skeletal muscle mass index instead of HGS . In a subsample, we used gene scores for BMI , waist-hip-ratio and HGS in a Mendelian randomization ( MR ). BMI defined obesity was associated with an increased risk of all outcomes (hazard ratio [ HR ] range 1.10-1.82). Low HGS was associated with increased risks of cardiovascular and all-cause mortality ( HR range 1.39-1.72). HR s for the association between low HGS and cardiovascular disease events were smaller ( HR range 1.05-1.09). There was no suggestion of an interaction between HGS and BMI to support the healthy obese hypothesis. Results using other adiposity metrics were similar. There was no evidence of an association between skeletal muscle mass index and any outcome. Factorial Mendelian randomization confirmed no evidence for an interaction. Low genetically predicted HGS was associated with an increased risk of mortality ( HR range 1.08-1.19). Conclusions Our analyses do not support the healthy obese concept, with no evidence that the adverse effect of obesity on outcomes was reduced by improved muscle quality. Lower HGS was associated with increased risks of mortality in both observational and MR analyses, suggesting reverse causality may not be the sole explanation.
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Affiliation(s)
- Ruth E. Farmer
- Department of Non Communicable Disease EpidemiologyLondon School of Hygiene & Tropical MedicineLondonUnited Kingdom
| | - Rohini Mathur
- Department of Non Communicable Disease EpidemiologyLondon School of Hygiene & Tropical MedicineLondonUnited Kingdom
| | - A. Floriaan Schmidt
- Institute of Cardiovascular ScienceUniversity College LondonUnited Kingdom
- Division Heart and LungsDepartment of CardiologyUniversity Medical Center UtrechtNetherlands
| | - Krishnan Bhaskaran
- Department of Non Communicable Disease EpidemiologyLondon School of Hygiene & Tropical MedicineLondonUnited Kingdom
| | - Ghazaleh Fatemifar
- The Farr Institute of Health InformaticsLondonUnited Kingdom
- The Institute of Health InformaticsUniversity College LondonLondonUnited Kingdom
| | - Sophie V. Eastwood
- Institute of Cardiovascular ScienceUniversity College LondonUnited Kingdom
| | - Chris Finan
- The Institute of Computer ScienceUniversity College LondonUnited Kingdom
- The Farr Institute of Health InformaticsLondonUnited Kingdom
| | - Spiros Denaxas
- The Farr Institute of Health InformaticsLondonUnited Kingdom
- The Institute of Health InformaticsUniversity College LondonLondonUnited Kingdom
| | - Liam Smeeth
- Department of Non Communicable Disease EpidemiologyLondon School of Hygiene & Tropical MedicineLondonUnited Kingdom
| | - Nish Chaturvedi
- Institute of Cardiovascular ScienceUniversity College LondonUnited Kingdom
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18
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Schmidt AF, Dudbridge F. Mendelian randomization with Egger pleiotropy correction and weakly informative Bayesian priors. Int J Epidemiol 2019; 47:1217-1228. [PMID: 29253155 PMCID: PMC6124638 DOI: 10.1093/ije/dyx254] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/14/2017] [Indexed: 12/17/2022] Open
Abstract
Background The MR-Egger (MRE) estimator has been proposed to correct for directional pleiotropic effects of genetic instruments in an instrumental variable (IV) analysis. The power of this method is considerably lower than that of conventional estimators, limiting its applicability. Here we propose a novel Bayesian implementation of the MR-Egger estimator (BMRE) and explore the utility of applying weakly informative priors on the intercept term (the pleiotropy estimate) to increase power of the IV (slope) estimate. Methods This was a simulation study to compare the performance of different IV estimators. Scenarios differed in the presence of a causal effect, the presence of pleiotropy, the proportion of pleiotropic instruments and degree of 'Instrument Strength Independent of Direct Effect' (InSIDE) assumption violation. Based on empirical plasma urate data, we present an approach to elucidate a prior distribution for the amount of pleiotropy. Results A weakly informative prior on the intercept term increased power of the slope estimate while maintaining type 1 error rates close to the nominal value of 0.05. Under the InSIDE assumption, performance was unaffected by the presence or absence of pleiotropy. Violation of the InSIDE assumption biased all estimators, affecting the BMRE more than the MRE method. Conclusions Depending on the prior distribution, the BMRE estimator has more power at the cost of an increased susceptibility to InSIDE assumption violations. As such the BMRE method is a compromise between the MRE and conventional IV estimators, and may be an especially useful approach to account for observed pleiotropy.
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Affiliation(s)
- A F Schmidt
- Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands.,Institute of Cardiovascular Science, University College London, London, UK.,Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - F Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK.,Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
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19
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Joshi R, Wannamethee G, Rhodes D, Engmann J, Dale C, Gaunt T, Jefferis B, Papacosta O, Shah T, Tillin T, Wong A, Chaturvedi N, Kivimaki M, Kuh D, Kumari M, Hughes A, Ben-Shlomo Y, Casas JP, Hingorani AD, Schmidt AF. P15 TRIGLYCERIDE-CONTAINING LIPOPROTEIN SUB-FRACTIONS AND CORONARY HEART DISEASE AND STROKE RISK. Cardiovasc Res 2018. [DOI: 10.1093/cvr/cvy216.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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20
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Schmidt AF, Hingorani AD, Jefferis BJ, White J, Groenwold R, Dudbridge F. Comparison of variance estimators for meta-analysis of instrumental variable estimates. Int J Epidemiol 2018; 45:1975-1986. [PMID: 27591262 PMCID: PMC5654757 DOI: 10.1093/ije/dyw123] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/22/2016] [Indexed: 12/16/2022] Open
Abstract
Background: Mendelian randomization studies perform instrumental variable (IV) analysis using genetic IVs. Results of individual Mendelian randomization studies can be pooled through meta-analysis. We explored how different variance estimators influence the meta-analysed IV estimate. Methods: Two versions of the delta method (IV before or after pooling), four bootstrap estimators, a jack-knife estimator and a heteroscedasticity-consistent (HC) variance estimator were compared using simulation. Two types of meta-analyses were compared, a two-stage meta-analysis pooling results, and a one-stage meta-analysis pooling datasets. Results: Using a two-stage meta-analysis, coverage of the point estimate using bootstrapped estimators deviated from nominal levels at weak instrument settings and/or outcome probabilities ≤ 0.10. The jack-knife estimator was the least biased resampling method, the HC estimator often failed at outcome probabilities ≤ 0.50 and overall the delta method estimators were the least biased. In the presence of between-study heterogeneity, the delta method before meta-analysis performed best. Using a one-stage meta-analysis all methods performed equally well and better than two-stage meta-analysis of greater or equal size. Conclusions: In the presence of between-study heterogeneity, two-stage meta-analyses should preferentially use the delta method before meta-analysis. Weak instrument bias can be reduced by performing a one-stage meta-analysis.
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Affiliation(s)
| | | | - B J Jefferis
- Department of Primary Care and Population Health
| | - J White
- UCL Genetics Institute, University College London, London, UK
| | - Rhh Groenwold
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - F Dudbridge
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
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21
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Abstract
It may not always be possible to blind participants of a randomized controlled trial for treatment allocation. As a result, estimators of the actual treatment effect may be biased. In this paper, we will extend a novel method, originally introduced in genetic research, for instrumental variable meta-analysis, adjusting for bias due to unblinding of trial participants. Using simulation studies, this novel method, "Egger Correction for non-Adherence", is introduced and compared to the performance of the "intention-to-treat," "as-treated," and conventional "instrumental variable" estimators. Scenarios considered (time-varying) non-adherence, confounding, and between-study heterogeneity. The effect of treatment on a binary endpoint was quantified by means of a risk difference. In all scenarios with unblinded treatment allocation, the Egger Correction for non-Adherence method was the least biased estimator. However, unless the variation in adherence was relatively large, precision was lacking, and power did not surpass 0.50. As a comparison, in a meta-analysis of blinded randomized controlled trials, power of the conventional IV estimator was 1.00 versus at most 0.14 for the Egger Correction for non-Adherence estimator. Due to this lack of precision and power, we suggest to use this method mainly as a sensitivity analysis.
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Affiliation(s)
- A F Schmidt
- 1 Institute of Cardiovascular Science, Faculty of Population Health, University College London, London, UK
| | - Rhh Groenwold
- 2 Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
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22
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Schmidt AF, Nielen M, Withrow SJ, Selmic LE, Burton JH, Klungel OH, Groenwold RHH, Kirpensteijn J. Chemotherapy effectiveness and mortality prediction in surgically treated osteosarcoma dogs: A validation study. Prev Vet Med 2016; 125:126-34. [PMID: 26827107 DOI: 10.1016/j.prevetmed.2016.01.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2015] [Revised: 12/17/2015] [Accepted: 01/03/2016] [Indexed: 11/29/2022]
Abstract
Canine osteosarcoma is the most common bone cancer, and an important cause of mortality and morbidity, in large purebred dogs. Previously we constructed two multivariable models to predict a dog's 5-month or 1-year mortality risk after surgical treatment for osteosarcoma. According to the 5-month model, dogs with a relatively low risk of 5-month mortality benefited most from additional chemotherapy treatment. In the present study, we externally validated these results using an independent cohort study of 794 dogs. External performance of our prediction models showed some disagreement between observed and predicted risk, mean difference: -0.11 (95% confidence interval [95% CI]-0.29; 0.08) for 5-month risk and 0.25 (95%CI 0.10; 0.40) for 1-year mortality risk. After updating the intercept, agreement improved: -0.0004 (95%CI-0.16; 0.16) and -0.002 (95%CI-0.15; 0.15). The chemotherapy by predicted mortality risk interaction (P-value=0.01) showed that the chemotherapy compared to no chemotherapy effectiveness was modified by 5-month mortality risk: dogs with a relatively lower risk of mortality benefited most from additional chemotherapy. Chemotherapy effectiveness on 1-year mortality was not significantly modified by predicted risk (P-value=0.28). In conclusion, this external validation study confirmed that our multivariable risk prediction models can predict a patient's mortality risk and that dogs with a relatively lower risk of 5-month mortality seem to benefit most from chemotherapy.
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Affiliation(s)
- A F Schmidt
- Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands; Division of Pharmacoepidemiology and Clinicl Pharmacology, Utrecht Institute for Pharmaceutical Sciences, P.O. Box 80082, 3508 TB Utrecht, The Netherlands; Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 7, 3584 CL Utrecht, The Netherlands; Institute of Cardiovascular Science, Faculty of Population Health, University College London, London WC1E 6BT, UK.
| | - M Nielen
- Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 7, 3584 CL Utrecht, The Netherlands
| | - S J Withrow
- Flint Animal Cancer Center, Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA
| | - L E Selmic
- Flint Animal Cancer Center, Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA
| | - J H Burton
- Flint Animal Cancer Center, Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA; University of California, Davis, Department of Surgical and Radiological Sciences, School of Veterinary Medicine, Davis, CA, USA
| | - O H Klungel
- Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands; Division of Pharmacoepidemiology and Clinicl Pharmacology, Utrecht Institute for Pharmaceutical Sciences, P.O. Box 80082, 3508 TB Utrecht, The Netherlands
| | - R H H Groenwold
- Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands; Division of Pharmacoepidemiology and Clinicl Pharmacology, Utrecht Institute for Pharmaceutical Sciences, P.O. Box 80082, 3508 TB Utrecht, The Netherlands
| | - J Kirpensteijn
- Department of Clinical Sciences of Companion Animals, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 8, Utrecht 3584 CM, The Netherlands
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Sbragia L, Nassr ACC, Gonçalves FLL, Schmidt AF, Zuliani CC, Garcia PV, Gallindo RM, Pereira LAV. VEGF receptor expression decreases during lung development in congenital diaphragmatic hernia induced by nitrofen. Braz J Med Biol Res 2014; 47:171-8. [PMID: 24519134 PMCID: PMC4051183 DOI: 10.1590/1414-431x20133221] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2013] [Accepted: 08/21/2013] [Indexed: 11/22/2022] Open
Abstract
Changes in vascular endothelial growth factor (VEGF) in pulmonary vessels have
been described in congenital diaphragmatic hernia (CDH) and may contribute to
the development of pulmonary hypoplasia and hypertension; however, how the
expression of VEGF receptors changes during fetal lung development in CDH is not
understood. The aim of this study was to compare morphological evolution with
expression of VEGF receptors, VEGFR1 (Flt-1) and VEGFR2 (Flk-1), in
pseudoglandular, canalicular, and saccular stages of lung development in normal
rat fetuses and in fetuses with CDH. Pregnant rats were divided into four groups
(n=20 fetuses each) of four different gestational days (GD) 18.5, 19.5, 20.5,
21.5: external control (EC), exposed to olive oil (OO), exposed to 100 mg
nitrofen, by gavage, without CDH (N-), and exposed to nitrofen with CDH (CDH) on
GD 9.5 (term=22 days). The morphological variables studied were: body weight
(BW), total lung weight (TLW), left lung weight, TLW/BW ratio, total lung
volume, and left lung volume. The histometric variables studied were: left lung
parenchymal area density and left lung parenchymal volume. VEGFR1 and VEGFR2
expression were determined by Western blotting. The data were analyzed using
analysis of variance with the Tukey-Kramer post hoc test. CDH
frequency was 37% (80/216). All the morphological and histometric variables were
reduced in the N- and CDH groups compared with the controls, and reductions were
more pronounced in the CDH group (P<0.05) and more evident on GD 20.5 and GD
21.5. Similar results were observed for VEGFR1 and VEGFR2 expression. We
conclude that N- and CDH fetuses showed primary pulmonary hypoplasia, with a
decrease in VEGFR1 and VEGFR2 expression.
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Affiliation(s)
- L Sbragia
- Divisão de Cirurgia Pediátrica, Departamento de Cirurgia e Anatomia, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão PretoSP, Brasil, Divisão de Cirurgia Pediátrica, Departamento de Cirurgia e Anatomia, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brasil
| | - A C C Nassr
- Departamento de Hidrobiologia do Centro de Ciências Biológicas e da Saúde, Universidade Federal de São Carlos, São CarlosSP, Brasil, Departamento de Hidrobiologia do Centro de Ciências Biológicas e da Saúde, Universidade Federal de São Carlos, São Carlos, SP, Brasil
| | - F L L Gonçalves
- Divisão de Cirurgia Pediátrica, Departamento de Cirurgia e Anatomia, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão PretoSP, Brasil, Divisão de Cirurgia Pediátrica, Departamento de Cirurgia e Anatomia, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brasil
| | - A F Schmidt
- Pediatrics House Office, Cincinnati Children's Hospital Medical Center, CincinnatiOH, USA, Pediatrics House Office, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - C C Zuliani
- Departamento de Clínica Médica, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, CampinasSP, Brasil, Departamento de Clínica Médica, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, SP, Brasil
| | - P V Garcia
- Departamento de Histologia e Embriologia, Instituto de Biologia, Universidade Estadual de Campinas, UNICAMP, CampinasSP, Brasil, Departamento de Histologia e Embriologia, Instituto de Biologia, Universidade Estadual de Campinas, UNICAMP, Campinas, SP, Brasil
| | - R M Gallindo
- Divisão de Cirurgia Pediátrica, Departamento de Cirurgia e Anatomia, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão PretoSP, Brasil, Divisão de Cirurgia Pediátrica, Departamento de Cirurgia e Anatomia, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brasil
| | - L A V Pereira
- Departamento de Histologia e Embriologia, Instituto de Biologia, Universidade Estadual de Campinas, UNICAMP, CampinasSP, Brasil, Departamento de Histologia e Embriologia, Instituto de Biologia, Universidade Estadual de Campinas, UNICAMP, Campinas, SP, Brasil
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Gonçalves FLL, de Souza GFP, Schmidt AF, Regis AC, de Oliveira MG, Sbragia L. Evaluation of nitric oxide (NO) and nitric oxide synthases (NOS) in the amniotic fluid in an experimental gastroschisis rat model. Eur J Pediatr Surg 2011; 21:362-5. [PMID: 21960425 DOI: 10.1055/s-0031-1285872] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
UNLABELLED Intestinal damage due to gastroschisis (G), an anomaly found with increasing incidence by pediatric surgeons, is intimately associated with endogenous nitric oxide (NO) production and NO synthase (NOS) expression. AIM Aim of the study was to evaluate NO production and NOS isoforms in the intestine and amniotic fluid (AF) using a rat model of gastroschisis. METHODS A gastroschisis rat model was surgically created at 18.5 days of gestation (term=22 days). 3 groups of 12 fetuses each were studied: control (C), sham (S) and (G). Morphometric data of body weight (BW), intestinal weight (IW) and the IW/BW ratio were evaluated and compared. Indirect quantification of NO (nitrite and nitrate - NOx) was analyzed by chemiluminescence, and the expression of the 3 isoforms was analyzed by Western blotting. RESULTS Group G showed an increase in IW and IW/BW compared with groups C and S. IW: G=0.27 ± 0.06, C=0.20 ± 0.02, S=0.20 ± 0.02 (p<0.01); IW/BW: G=4.11 ± 0.57, C=5.21 ± 1.04, S=5.18 ± 1.23 (p<0.05). NO in the G group was lower in the intestine and higher in AF, as opposed to C and S, where it had increased in the intestine and decreased in AF. Intestinal NOx: G=0.85 ± 0.28, C=1.86 ± 0.82, S=1.80 ± 0.69 (p<0.05); NOx in AF: G=161.87 ± 52.11, C=6.99 ± 5.45, S=48.73 ± 13.183 (p<0.001). CONCLUSION The intestinal inflammation in gastroschisis promotes the release of nitric oxide to the environment (AF). Perhaps NO in the AF may be an inflammatory marker for G.
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Affiliation(s)
- F L L Gonçalves
- Department of Surgery, School of Medical Sciences, University of Campinas, Campinas, SP, Brazil
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Sbragia L, Schmidt AF, Moraes S, Bittencourt DG, Gonçalves FLL, Pereira LAVD, Velloso LA. Inflammatory response in a rat model of gastroschisis is associated with an increase of NF-kappaB. ACTA ACUST UNITED AC 2010; 43:160-5. [PMID: 20098844 DOI: 10.1590/s0100-879x2010005000005] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2009] [Accepted: 12/17/2009] [Indexed: 11/22/2022]
Abstract
Babies with gastroschisis have high morbidity, which is associated with inflammatory bowel injury caused by exposure to amniotic fluid. The objective of this study was to identify components of the inflammatory response in the intestine and liver in an experimental model of gastroschisis in rats. The model was surgically created at 18.5 days of gestation. The fetuses were exposed through a hysterotomy and an incision at the right of the umbilicus was made, exposing the fetal bowel. Then, the fetus was placed back into the uterus until term. The bowel in this model had macro- and microscopic characteristics similar to those observed in gastroschisis. The study was conducted on three groups of 20 fetuses each: gastroschisis, control, and sham fetuses. Fetal body, intestine and liver weights and intestine length were measured. IL-1beta, IL-6, IL-10, TNF-alpha, IFN-gamma and NF-kappaB levels were assessed by ELISA. Data were analyzed statistically by ANOVA followed by the Tukey post-test. Gastroschisis fetuses had a decreased intestine length (means +/- SD, 125 +/- 25 vs 216 +/- 13.9; P < 0.005) and increased intestine weight (0.29 +/- 0.05 vs 0.24 +/- 0.04; P < 0.005). Intestine length correlated with liver weight only in gastroschisis fetuses (Pearson's correlation coefficient, r = 0.518, P = 0.019). There were no significant differences in the concentrations of IL-1beta, TNF-alpha or IFN-gamma in the intestine, whereas the concentration of NF-kappaB was increased in both the intestine and liver of fetuses with gastroschisis. These results show that the inflammatory response in the liver and intestine of the rat model of gastroschisis is accompanied by an increase in the amount of NF-kappaB in the intestine and liver.
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Affiliation(s)
- L Sbragia
- Disciplina de Cirurgia Pediátrica, Departamento de Cirurgia, Universidade Estadual de Campinas, SP, Brasil.
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Schmidt AF. An insider's tips on purchasing laboratory instruments. MLO Med Lab Obs 1999; 31:26-9. [PMID: 11185284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
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Rodrigues OR, Losso LC, Ghefter MC, Imaeda CJ, Biscegli Jatene F, Brito Filomeno LT, Ribas Milanez De Campos J, Minamoto H, Kawahara N, Pinhata Otoch J, Saad R, Schmidt AF. Thoracoscopic surgery in Brazil. An overview. J Cardiovasc Surg (Torino) 1996; 37:147-53. [PMID: 10064368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
The Video Assisted Thoracic Surgery (VATS) was introduced in Brazil in 1992 by Losso, Ghefter and Imaeda. Since its advent up to November 1994, 488 patients have been submitted to 497 VATS procedures in four Medical Centers of São Paulo city. The indications for the procedures were: lung diseases in 244 patients (50%), pleural disease in 155 patients (31.7%), thoracic traumas in 42 patients (8.6%), mediastinal diseases in 35 patients (7.1%), cardiovascular diseases in 7 patients (1.4%), chest wall diseases in 3 patients (0.6%) and esophageal diseases in 2 patients (0.4%). In the group of lung disease the most commonly used procedures were the lung biopsy in order to diagnose diffuse pulmonary disease and the indeterminate solitary nodule resection. Among the occurrences of pleural diseases, the most commonly used procedures were the pleurodesis with talc (talc poudrage) for the treatment of recurrent pleural effusion, the driven pleura biopsy and debridment or decortication of trapped lung in cases of pleural empyema. Concerning the mediastinal diseases, the pathology which was most frequently treated by VATS was the recurrent pericardic effusion through partial pericardiectomy. Among the patients presenting chest traumatic diseases, the VATS was used to explore thoracoabdominal penetrating injuries, to control bleeding, to remove clotted hemothorax, to suture diaphragm lesions and to remove intrapleural foreign bodies. Out of 497 procedures, there were 28 convertions to thoracotomy (5.7%) and two deaths occurred all over the cases. The complications, limitations and growth related to this method as well as a future overview of the VATS in Brazil will be presented.
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Affiliation(s)
- O R Rodrigues
- Department of Surgery of the Universidade de Mogi das Cruzes, São Paulo, Brazil
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