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Young WJ, van der Most PJ, Bartz TM, Bos MM, Biino G, Duong T, Foco L, Lominchar JT, Müller-Nurasyid M, Nardone GG, Pecori A, Ramirez J, Repetto L, Schramm K, Shen X, van Duijvenboden S, van Heemst D, Weiss S, Yao J, Benjamins JW, Alonso A, Spedicati B, Biggs ML, Brody JA, Dörr M, Fuchsberger C, Gögele M, Guo X, Ikram MA, Jukema JW, Kääb S, Kanters JK, Lin HJ, Linneberg A, Nauck M, Nolte IM, Pianigiani G, Santin A, Soliman EZ, Tesolin P, Vaccargiu S, Waldenberger M, van der Harst P, Verweij N, Arking DE, Concas MP, De Grandi A, Girotto G, Grarup N, Kavousi M, Mook-Kanamori DO, Navarro P, Orini M, Padmanabhan S, Pattaro C, Peters A, Pirastu M, Pramstaller PP, Heckbert SR, Sinner M, Snieder H, Völker U, Wilson JF, Gauderman WJ, Lambiase PD, Sotoodehnia N, Tinker A, Warren HR, Noordam R, Munroe PB. Genome-Wide Interaction Analyses of Serum Calcium on Ventricular Repolarization Time in 125 393 Participants. J Am Heart Assoc 2024; 13:e034760. [PMID: 39206732 DOI: 10.1161/jaha.123.034760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 07/31/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND Ventricular repolarization time (ECG QT and JT intervals) is associated with malignant arrhythmia. Genome-wide association studies have identified 230 independent loci for QT and JT; however, 50% of their heritability remains unexplained. Previous work supports a causal effect of lower serum calcium concentrations on longer ventricular repolarization time. We hypothesized calcium interactions with QT and JT variant associations could explain a proportion of the missing heritability. METHODS AND RESULTS We performed genome-wide calcium interaction analyses for QT and JT intervals. Participants were stratified by their calcium level relative to the study distribution (top or bottom 20%). We performed a 2-stage analysis (genome-wide discovery [N=62 532] and replication [N=59 861] of lead variants) and a single-stage genome-wide meta-analysis (N=122 393, [European ancestry N=117 581, African ancestry N=4812]). We also calculated 2-degrees of freedom joint main and interaction and 1-degree of freedom interaction P values. In 2-stage and single-stage analyses, 50 and 98 independent loci, respectively, were associated with either QT or JT intervals (2-degrees of freedom joint main and interaction P value <5×10-8). No lead variant had a significant interaction result after correcting for multiple testing and sensitivity analyses provided similar findings. Two loci in the single-stage meta-analysis were not reported previously (SPPL2B and RFX6). CONCLUSIONS We have found limited support for an interaction effect of serum calcium on QT and JT variant associations despite sample sizes with suitable power to detect relevant effects. Therefore, such effects are unlikely to explain a meaningful proportion of the heritability of QT and JT, and factors including rare variation and other environmental interactions need to be considered.
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Affiliation(s)
- William J Young
- Clinical Pharmacology and Precision Medicine William Harvey Research Institute, Queen Mary University of London United Kingdom
- Barts Heart Centre St Bartholomew's Hospital, Barts Health NHS Trust London United Kingdom
| | - Peter J van der Most
- Department of Epidemiology University of Groningen, University Medical Center Groningen Groningen The Netherlands
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Biostatistics and Medicine University of Washington Seattle WA USA
| | - Maxime M Bos
- Department of Epidemiology Erasmus MC University Medical Center Rotterdam Netherlands
| | - Ginevra Biino
- Institute of Molecular Genetics, National Research Council of Italy Pavia Italy
| | - ThuyVy Duong
- Department of Genetic Medicine McKusick-Nathans Institute, Johns Hopkins University School of Medicine Baltimore MD USA
| | - Luisa Foco
- Eurac Research Institute for Biomedicine (Affiliated with the University of Lübeck) Bolzano Italy
| | - Jesus T Lominchar
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences University of Copenhagen Denmark
| | - Martina Müller-Nurasyid
- German Research Center for Environmental Health Institute of Genetic Epidemiology, Helmholtz Zentrum München Neuherberg Germany
- IBE, Faculty of Medicine, LMU Munich Munich Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University Mainz Germany
| | | | - Alessandro Pecori
- Institute for Maternal and Child Health-IRCCS "Burlo Garofolo" Trieste Italy
| | - Julia Ramirez
- Clinical Pharmacology and Precision Medicine William Harvey Research Institute, Queen Mary University of London United Kingdom
- Aragon Institute of Engineering Research, University of Zaragoza Spain
- Centro de Investigación Biomédica en Red-Bioingeniería, Biomateriales y Nanomedicina Zaragoza Spain
| | - Linda Repetto
- Centre for Global Health Research Usher Institute, University of Edinburgh Scotland
| | - Katharina Schramm
- German Research Center for Environmental Health Institute of Genetic Epidemiology, Helmholtz Zentrum München Neuherberg Germany
- IBE, Faculty of Medicine, LMU Munich Munich Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University Mainz Germany
| | - Xia Shen
- Centre for Global Health Research Usher Institute, University of Edinburgh Scotland
- Department of Medical Epidemiology and Biostatistics Karolinska Institutet Stockholm Sweden
- Greater Bay Area Institute of Precision Medicine (Guangzhou), Fudan University Guangzhou China
| | - Stefan van Duijvenboden
- Clinical Pharmacology and Precision Medicine William Harvey Research Institute, Queen Mary University of London United Kingdom
- Institute of Cardiovascular Sciences, University of College London London United Kingdom
- Nuffield Department of Population Health University of Oxford United Kingdom
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics Leiden University Medical Center Leiden The Netherlands
| | - Stefan Weiss
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald Greifswald Germany
- Interfaculty Institute for Genetics and Functional Genomics; Department of Functional Genomics University Medicine Greifswald Greifswald Germany
| | - Jie Yao
- Department of Pediatrics The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center Torrance CA USA
| | - Jan-Walter Benjamins
- Department of Cardiology University of Groningen, University Medical Center Groningen Groningen The Netherlands
| | - Alvaro Alonso
- Department of Epidemiology Rollins School of Public Health, Emory University Atlanta GA USA
| | - Beatrice Spedicati
- Department of Medicine, Surgery and Health Sciences University of Trieste Italy
| | - Mary L Biggs
- Cardiovascular Health Research Unit, Department of Medicine University of Washington Seattle WA USA
- Department of Biostatistics University of Washington Seattle WA USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine University of Washington Seattle WA USA
| | - Marcus Dörr
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald Greifswald Germany
- Department of Internal Medicine B-Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine University Medicine Greifswald Greifswald Germany
| | - Christian Fuchsberger
- Eurac Research Institute for Biomedicine (Affiliated with the University of Lübeck) Bolzano Italy
- Department of Biostatistics University of Michigan School of Public Health Ann Arbor MI USA
- Center for Statistical Genetics University of Michigan School of Public Health Ann Arbor MI USA
| | - Martin Gögele
- Eurac Research Institute for Biomedicine (Affiliated with the University of Lübeck) Bolzano Italy
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences/The Lundquist Institute at Harbor-UCLA Medical Center Torrance CA USA
- Department of Pediatrics David Geffen School of Medicine at UCLA Los Angeles CA USA
| | - M Arfan Ikram
- Department of Epidemiology Erasmus MC University Medical Center Rotterdam Netherlands
| | - J Wouter Jukema
- Department of Cardiology Leiden University Medical Center Leiden The Netherlands
- Netherlands Heart Institute Utrecht The Netherlands
| | - Stefan Kääb
- Department of Cardiology University Hospital, LMU Munich Munich Germany
- DZHK (German Centre for Cardiovascular Research), partner site: Munich Heart Alliance Munich Germany
| | - Jørgen K Kanters
- Laboratory of Experimental Cardiology, Department of Biomedical Sciences University of Copenhagen Denmark
| | - Henry J Lin
- Department of Pediatrics The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center Torrance CA USA
- Department of Pediatrics David Geffen School of Medicine at UCLA Los Angeles CA USA
- Department of Pediatrics/Harbor-UCLA Medical Center Torrance CA USA
| | - Allan Linneberg
- Center for Clinical Research and Prevention Bispebjerg and Frederiksberg Hospital, The Capital Region Copenhagen Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences University of Copenhagen Denmark
| | - Matthias Nauck
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald Greifswald Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald Greifswald Germany
| | - Ilja M Nolte
- Department of Epidemiology University of Groningen, University Medical Center Groningen Groningen The Netherlands
| | - Giulia Pianigiani
- Institute for Maternal and Child Health-IRCCS "Burlo Garofolo" Trieste Italy
| | - Aurora Santin
- Department of Medicine, Surgery and Health Sciences University of Trieste Italy
| | - Elsayed Z Soliman
- Epidemiological Cardiology Research Center (EPICARE) Wake Forest School of Medicine Winston Salem USA
| | - Paola Tesolin
- Institute for Maternal and Child Health-IRCCS "Burlo Garofolo" Trieste Italy
| | - Simona Vaccargiu
- Institute for Genetic and Biomedical Research, National Research Council of Italy Cagliari Italy
| | - Melanie Waldenberger
- DZHK (German Centre for Cardiovascular Research), partner site: Munich Heart Alliance Munich Germany
- Research Unit Molecular Epidemiology Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health Neuherberg Germany
| | - Pim van der Harst
- Department of Cardiology University of Groningen, University Medical Center Groningen Groningen The Netherlands
- Department of Cardiology, Heart and Lung Division University Medical Center Utrecht Utrecht The Netherlands
| | - Niek Verweij
- Department of Cardiology University of Groningen, University Medical Center Groningen Groningen The Netherlands
| | - Dan E Arking
- Department of Genetic Medicine McKusick-Nathans Institute, Johns Hopkins University School of Medicine Baltimore MD USA
| | - Maria Pina Concas
- Institute for Maternal and Child Health-IRCCS "Burlo Garofolo" Trieste Italy
| | - Alessandro De Grandi
- Eurac Research Institute for Biomedicine (Affiliated with the University of Lübeck) Bolzano Italy
| | - Giorgia Girotto
- Department of Medicine, Surgery and Health Sciences University of Trieste Italy
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences University of Copenhagen Denmark
| | - Maryam Kavousi
- Department of Epidemiology Erasmus MC University Medical Center Rotterdam Netherlands
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology Leiden University Medical Center Leiden The Netherlands
- Department of Public Health and Primary Care Leiden University Medical Center Leiden The Netherlands
| | - Pau Navarro
- MRC Human Genetics Unit Institute of Genetics and Cancer, University of Edinburgh Scotland
| | - Michele Orini
- Barts Heart Centre St Bartholomew's Hospital, Barts Health NHS Trust London United Kingdom
- Institute of Cardiovascular Sciences, University of College London London United Kingdom
| | | | - Cristian Pattaro
- Eurac Research Institute for Biomedicine (Affiliated with the University of Lübeck) Bolzano Italy
| | - Annette Peters
- German Research Center for Environmental Health Institute of Genetic Epidemiology, Helmholtz Zentrum München Neuherberg Germany
- IBE, Faculty of Medicine, LMU Munich Munich Germany
- DZHK (German Centre for Cardiovascular Research), partner site: Munich Heart Alliance Munich Germany
| | - Mario Pirastu
- Institute for Genetic and Biomedical Research, Sassari Unit, National Research Council of Italy Sassari Italy
| | - Peter P Pramstaller
- Eurac Research Institute for Biomedicine (Affiliated with the University of Lübeck) Bolzano Italy
- Department of Neurology University of Lübeck Germany
| | - Susan R Heckbert
- Cardiovascular Health Research Unit, Department of Medicine University of Washington Seattle WA USA
- Department of Epidemiology University of Washington Seattle WA USA
| | - Mortiz Sinner
- Department of Cardiology University Hospital, LMU Munich Munich Germany
- DZHK (German Centre for Cardiovascular Research), partner site: Munich Heart Alliance Munich Germany
| | - Harold Snieder
- Department of Epidemiology University of Groningen, University Medical Center Groningen Groningen The Netherlands
| | - Uwe Völker
- DZHK (German Centre for Cardiovascular Research), partner site Greifswald Greifswald Germany
- Interfaculty Institute for Genetics and Functional Genomics; Department of Functional Genomics University Medicine Greifswald Greifswald Germany
| | - James F Wilson
- Centre for Global Health Research Usher Institute, University of Edinburgh Scotland
- MRC Human Genetics Unit Institute of Genetics and Cancer, University of Edinburgh Scotland
| | - W James Gauderman
- Department of population and public health sciences University of Southern California Los Angeles CA USA
| | - Pier D Lambiase
- Barts Heart Centre St Bartholomew's Hospital, Barts Health NHS Trust London United Kingdom
- Institute of Cardiovascular Sciences, University of College London London United Kingdom
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, Department of Medicine University of Washington Seattle WA USA
| | - Andrew Tinker
- Clinical Pharmacology and Precision Medicine William Harvey Research Institute, Queen Mary University of London United Kingdom
- NIHR Barts Biomedical Research Centre Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London United Kingdom
| | - Helen R Warren
- Clinical Pharmacology and Precision Medicine William Harvey Research Institute, Queen Mary University of London United Kingdom
- NIHR Barts Biomedical Research Centre Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London United Kingdom
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics Leiden University Medical Center Leiden The Netherlands
| | - Patricia B Munroe
- Clinical Pharmacology and Precision Medicine William Harvey Research Institute, Queen Mary University of London United Kingdom
- NIHR Barts Biomedical Research Centre Barts and The London Faculty of Medicine and Dentistry, Queen Mary University of London United Kingdom
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Isaksen JL, Sivertsen CB, Jensen CZ, Graff C, Linz D, Ellervik C, Jensen MT, Jørgensen PG, Kanters JK. Electrocardiographic markers in patients with type 2 diabetes and the role of diabetes duration. J Electrocardiol 2024; 84:129-136. [PMID: 38663227 DOI: 10.1016/j.jelectrocard.2024.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 04/01/2024] [Accepted: 04/14/2024] [Indexed: 06/16/2024]
Abstract
BACKGROUND The association between type 2 diabetes and electrocardiographic (ECG) markers are incompletely explored and the dependence on diabetes duration is largely unknown. We aimed to investigate the electrocardiographic (ECG) changes associated with type 2 diabetes over time. METHODS In this cross-sectional study, we matched people with type 2 diabetes 1:1 on sex, age, and body mass index with people without diabetes from the general population. We regressed ECG markers with the presence of diabetes and the duration of clinical diabetes, respectively, adjusted for sex, age, body mass index, smoking, heart rate, diabetes medication, renal function, hypertension, and myocardial infarction. RESULTS We matched 988 people with type 2 diabetes (332, 34% females) with as many controls. Heart rate was 8 bpm higher (p < 0.001) in people with vs. without type 2 diabetes, but the difference declined with increasing diabetes duration. For most depolarization markers, the difference between people with and without type 2 diabetes increased progressively with diabetes duration. On average, R-wave amplitude was 6 mm lower in lead V5 (p < 0.001), P-wave duration was 5 ms shorter (p < 0.001) and QRS duration was 3 ms (p = 0.03). Among repolarization markers, T-wave amplitude (measured in V5) was lower in patients with type 2 diabetes (1 mm lower, p < 0.001) and the QRS-T angle was 10 degrees wider (p = 0.002). We observed no association between diabetes duration and repolarization markers. CONCLUSIONS Type 2 diabetes was independently associated with electrocardiographic depolarization and repolarization changes. Differences in depolarization markers, but not repolarization markers, increased with increasing diabetes duration.
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Affiliation(s)
- Jonas L Isaksen
- Laboratory of Experimental Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Christian B Sivertsen
- Laboratory of Experimental Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christian Zinck Jensen
- Laboratory of Experimental Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Claus Graff
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Dominik Linz
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christina Ellervik
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Laboratory Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Department of Data and Data Support, Region Zealand, Sorø, Denmark
| | | | - Peter G Jørgensen
- Department of Cardiology, Herlev and Gentofte University Hospital, Copenhagen, Denmark
| | - Jørgen K Kanters
- Laboratory of Experimental Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark; Center of Physiological Research, University of California San Francisco, San Francisco, USA
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3
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Hoffmann TJ, Lu M, Oni-Orisan A, Lee C, Risch N, Iribarren C. A large genome-wide association study of QT interval length utilizing electronic health records. Genetics 2022; 222:iyac157. [PMID: 36271874 PMCID: PMC9713425 DOI: 10.1093/genetics/iyac157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 09/22/2022] [Indexed: 12/13/2022] Open
Abstract
QT interval length is an important risk factor for adverse cardiovascular outcomes; however, the genetic architecture of QT interval remains incompletely understood. We conducted a genome-wide association study of 76,995 ancestrally diverse Kaiser Permanente Northern California members enrolled in the Genetic Epidemiology Research on Adult Health and Aging cohort using 448,517 longitudinal QT interval measurements, uncovering 9 novel variants, most replicating in 40,537 individuals in the UK Biobank and Population Architecture using Genomics and Epidemiology studies. A meta-analysis of all 3 cohorts (n = 117,532) uncovered an additional 19 novel variants. Conditional analysis identified 15 additional variants, 3 of which were novel. Little, if any, difference was seen when adjusting for putative QT interval lengthening medications genome-wide. Using multiple measurements in Genetic Epidemiology Research on Adult Health and Aging increased variance explained by 163%, and we show that the ≈6 measurements in Genetic Epidemiology Research on Adult Health and Aging was equivalent to a 2.4× increase in sample size of a design with a single measurement. The array heritability was estimated at ≈17%, approximately half of our estimate of 36% from family correlations. Heritability enrichment was estimated highest and most significant in cardiovascular tissue (enrichment 7.2, 95% CI = 5.7-8.7, P = 2.1e-10), and many of the novel variants included expression quantitative trait loci in heart and other relevant tissues. Comparing our results to other cardiac function traits, it appears that QT interval has a multifactorial genetic etiology.
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Affiliation(s)
- Thomas J Hoffmann
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94143, USA
| | - Meng Lu
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Akinyemi Oni-Orisan
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Clinical Pharmacy, University of California San Francisco, San Francisco, CA 94143, USA
| | - Catherine Lee
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Neil Risch
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94143, USA
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Carlos Iribarren
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
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4
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Effect of different antidiabetic medications on atherosclerotic cardiovascular disease (ASCVD) risk score among patients with type-2 diabetes mellitus: A multicenter non-interventional observational study. PLoS One 2022; 17:e0270143. [PMID: 35763504 PMCID: PMC9239438 DOI: 10.1371/journal.pone.0270143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 06/03/2022] [Indexed: 11/19/2022] Open
Abstract
Objective
The aim of this study was to compare the clinical outcomes associated with different combinations of oral diabetic drugs among patients with type 2 diabetes mellitus.
Method
A prospective multicenter longitudinal, noninterventional observation study design was applied. At baseline (0 month), clinical parameters including glucose profile, renal function, lipid profile and risk assessment for cardiovascular risks were calculated. Mean Weighted difference (MWD) with heterogeneity and effect z was calculated to determine the risk reduction at the end of the study.
Results
A total of 1,657 were enrolled to different cohorts with response rate of 75.5%. The distribution of patients was based on prescribed drug. A total of 513 (30.9%) in G1 (metformin alone), 217 (13.09%) in G2 (metformin with Glimepiride), 231 (12.85%) in G3 (Metformin with Gliclazide), 384 (23.17%) in G4 (metformin with Sitagliptin) and 312 (18.89%) in G5 (Metformin with Saxagliptin). There was no significant different in all clinical and social variables at baseline. The Intergroup analysis showed significant differences with all the primary outcome variables except BMI (p = 0.217) and eGFR (p = 0.782) among patients using sulphonylurea (SU) combination (G2 & G3). Findings also showed significant high frequency of emergency visit and hospitalization in G1 (78.16% & 30.8%) as compared to SU (70.1% & 28.3%, p = 0.001) and DPP-4 (56.6% & 20.4%, p = 0.001). The overall reported effect was z = 2.58, p = 0.001 for ASCVD risk reduction assessment.
Conclusion
The study concluded that significant effect of Dipeptidyl peptidase-4 inhibitor on reduction of hospitalization, lipid profile and also ASCVD risk score of type-II diabetes mellitus patients regardless of clinical comorbidities. Also, sulfonylurea combinations have showed significant reduction in LDL and triglycerides values.
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Lopez-Medina AI, Chahal CAA, Luzum JA. The genetics of drug-induced QT prolongation: evaluating the evidence for pharmacodynamic variants. Pharmacogenomics 2022; 23:543-557. [PMID: 35698903 DOI: 10.2217/pgs-2022-0027] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Drug-induced long QT syndrome (diLQTS) is an adverse effect of many commonly prescribed drugs, and it can increase the risk for lethal ventricular arrhythmias. Genetic variants in pharmacodynamic genes have been associated with diLQTS, but the strength of the evidence for each of those variants has not yet been evaluated. Therefore, the purpose of this review was to evaluate the strength of the evidence for pharmacodynamic genetic variants associated with diLQTS using a novel, semiquantitative scoring system modified from the approach used for congenital LQTS. KCNE1-D85N and KCNE2-T8A had definitive and strong evidence for diLQTS, respectively. The high level of evidence for these variants supports current consideration as risk factors for patients that will be prescribed a QT-prolonging drug.
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Affiliation(s)
- Ana I Lopez-Medina
- Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, MI 48109, USA
| | - Choudhary Anwar A Chahal
- Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA.,Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN 55905, USA.,Barts Heart Centre, St. Bartholomew's Hospital, West Smithfield, London, EC1A 7BE, UK.,WellSpan Health, Lancaster, PA 17607, USA
| | - Jasmine A Luzum
- Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, MI 48109, USA
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7
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Optimising Seniors' Metabolism of Medications and Avoiding Adverse Drug Events Using Data on How Metabolism by Their P450 Enzymes Varies with Ancestry and Drug-Drug and Drug-Drug-Gene Interactions. J Pers Med 2020; 10:jpm10030084. [PMID: 32796505 PMCID: PMC7563167 DOI: 10.3390/jpm10030084] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Revised: 08/01/2020] [Accepted: 08/06/2020] [Indexed: 12/16/2022] Open
Abstract
Many individuals ≥65 have multiple illnesses and polypharmacy. Primary care physicians prescribe >70% of their medications and renew specialists’ prescriptions. Seventy-five percent of all medications are metabolised by P450 cytochrome enzymes. This article provides unique detailed tables how to avoid adverse drug events and optimise prescribing based on two key databases. DrugBank is a detailed database of 13,000 medications and both the P450 and other complex pathways that metabolise them. The Flockhart Tables are detailed lists of the P450 enzymes and also include all the medications which inhibit or induce metabolism by P450 cytochrome enzymes, which can result in undertreatment, overtreatment, or potentially toxic levels. Humans have used medications for a few decades and these enzymes have not been subject to evolutionary pressure. Thus, there is enormous variation in enzymatic functioning and by ancestry. Differences for ancestry groups in genetic metabolism based on a worldwide meta-analysis are discussed and this article provides advice how to prescribe for individuals of different ancestry. Prescribing advice from two key organisations, the Dutch Pharmacogenetics Working Group and the Clinical Pharmacogenetics Implementation Consortium is summarised. Currently, detailed pharmacogenomic advice is only available in some specialist clinics in major hospitals. However, this article provides detailed pharmacogenomic advice for primary care and other physicians and also physicians working in rural and remote areas worldwide. Physicians could quickly search the tables for the medications they intend to prescribe.
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8
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Ikram MA, Brusselle G, Ghanbari M, Goedegebure A, Ikram MK, Kavousi M, Kieboom BCT, Klaver CCW, de Knegt RJ, Luik AI, Nijsten TEC, Peeters RP, van Rooij FJA, Stricker BH, Uitterlinden AG, Vernooij MW, Voortman T. Objectives, design and main findings until 2020 from the Rotterdam Study. Eur J Epidemiol 2020; 35:483-517. [PMID: 32367290 PMCID: PMC7250962 DOI: 10.1007/s10654-020-00640-5] [Citation(s) in RCA: 304] [Impact Index Per Article: 76.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 04/23/2020] [Indexed: 12/19/2022]
Abstract
The Rotterdam Study is an ongoing prospective cohort study that started in 1990 in the city of Rotterdam, The Netherlands. The study aims to unravel etiology, preclinical course, natural history and potential targets for intervention for chronic diseases in mid-life and late-life. The study focuses on cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1700 research articles and reports. This article provides an update on the rationale and design of the study. It also presents a summary of the major findings from the preceding 3 years and outlines developments for the coming period.
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Affiliation(s)
- M Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.
| | - Guy Brusselle
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.,Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - André Goedegebure
- Department of Otorhinolaryngology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - M Kamran Ikram
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.,Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Brenda C T Kieboom
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Caroline C W Klaver
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.,Department of Ophthalmology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Robert J de Knegt
- Department of Gastroenterology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Annemarie I Luik
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Tamar E C Nijsten
- Department of Dermatology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Robin P Peeters
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Frank J A van Rooij
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Bruno H Stricker
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Trudy Voortman
- Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
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9
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Mylona M, Liatis S, Anastasiadis G, Kapelios C, Kokkinos A. Severe iatrogenic hypoglycaemia requiring medical assistance is associated with concurrent prolongation of the QTc interval. Diabetes Res Clin Pract 2020; 161:108038. [PMID: 32006648 DOI: 10.1016/j.diabres.2020.108038] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Revised: 01/03/2020] [Accepted: 01/27/2020] [Indexed: 11/28/2022]
Abstract
AIMS Hypoglycaemia has been shown to exert arrhythmogenic effects. Herein, we explore the association between severe hypoglycaemia requiring medical assistance and the length of the QT interval in patients with diabetes. METHODS Data from a prospective study, conducted in eight tertiary hospitals, which recorded cases of hypoglycaemia from patients with diabetes seeking treatment at emergency departments (ED) were analyzed. The patients' electrocardiograms (ECGs), were compared to those of non-hypoglycaemic diabetic individuals, matched for age, gender and duration of diabetes, obtained during their scheduled follow-up visits. The corrected QT intervals (QTc) were calculated blindly by two cardiologists. RESULTS ECGs from 154 patients presenting with hypoglycaemia were analyzed and compared to 95 matched controls. The mean QTc interval was significantly longer in patients with hypoglycaemia than in controls (441.9 ± 48.2 vs. 401.0 ± 29.6 ms, p < 0.001) A significantly higher proportion of hypoglycaemic patients had an abnormally prolonged QTc (≥440 ms) compared to controls (49.4% vs. 11.6%, p < 0.001). Among patients with hypoglycaemia, there was a statistically significant but rather weak negative correlation between QTc interval and plasma glucose at presentation (r: -0.183, p = 0.02). CONCLUSIONS In diabetic patients, hypoglycemia requiring medical assistance is associated with a significant prolongation of the QTc interval. The degree of this prolongation is associated with hypoglycaemia severity.
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Affiliation(s)
- Maria Mylona
- Diabetes Center, First Department of Propaedeutic Internal Medicine, Medical School, National and Kapodistrian University of Athens, Laiko Hospital, Athens, Greece.
| | - Stavros Liatis
- Diabetes Center, First Department of Propaedeutic Internal Medicine, Medical School, National and Kapodistrian University of Athens, Laiko Hospital, Athens, Greece
| | | | | | - Alexander Kokkinos
- Diabetes Center, First Department of Propaedeutic Internal Medicine, Medical School, National and Kapodistrian University of Athens, Laiko Hospital, Athens, Greece
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10
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Genome-wide association study identifies novel risk variants from RPS6KA1, CADPS, VARS, and DHX58 for fasting plasma glucose in Arab population. Sci Rep 2020; 10:152. [PMID: 31932636 PMCID: PMC6957513 DOI: 10.1038/s41598-019-57072-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Accepted: 12/20/2019] [Indexed: 12/14/2022] Open
Abstract
Consanguineous populations of the Arabian Peninsula, which has seen an uncontrolled rise in type 2 diabetes incidence, are underrepresented in global studies on diabetes genetics. We performed a genome-wide association study on the quantitative trait of fasting plasma glucose (FPG) in unrelated Arab individuals from Kuwait (discovery-cohort:n = 1,353; replication-cohort:n = 1,196). Genome-wide genotyping in discovery phase was performed for 632,375 markers from Illumina HumanOmniExpress Beadchip; and top-associating markers were replicated using candidate genotyping. Genetic models based on additive and recessive transmission modes were used in statistical tests for associations in discovery phase, replication phase, and meta-analysis that combines data from both the phases. A genome-wide significant association with high FPG was found at rs1002487 (RPS6KA1) (p-discovery = 1.64E-08, p-replication = 3.71E-04, p-combined = 5.72E-11; β-discovery = 8.315; β-replication = 3.442; β-combined = 6.551). Further, three suggestive associations (p-values < 8.2E-06) with high FPG were observed at rs487321 (CADPS), rs707927 (VARS and 2Kb upstream of VWA7), and rs12600570 (DHX58); the first two markers reached genome-wide significance in the combined analysis (p-combined = 1.83E-12 and 3.07E-09, respectively). Significant interactions of diabetes traits (serum triglycerides, FPG, and glycated hemoglobin) with homeostatic model assessment of insulin resistance were identified for genotypes heterozygous or homozygous for the risk allele. Literature reports support the involvement of these gene loci in type 2 diabetes etiology.
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11
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Abstract
The cytochromes P450 comprise a family of enzymes that are responsible for around three-quarters of all drug metabolism reactions that occur in human populations. Many isoforms of cytochrome P450 exist but most reactions are undertaken by CYP2C9, CYP2C19, CYP2D6 and CYP3A4. This brief review focusses on the first three isozymes which exhibit polymorphism of phenotype.If there is a wide variation in drug metabolising capacity within the population, this may precipitate clinical consequences and influence the drug treatment of patients. Such problems range from a lack of efficacy to unanticipated toxicity. In order to minimise untoward events and "personalise" a patient's treatment, efforts have been made to discover an individual's drug metabolism status. This requires knowledge of the subject's phenotype at the time of clinical treatment. Since such testing is difficult, time-consuming and costly, the simpler approach of genotyping has been advocated.However, the correlation between genotype and phenotype is not good, with values of up to 50% misprediction being reported. Genotype-assisted forecasts cannot therefore be used with confidence to replace actual phenotype measurements. Obfuscating factors discussed include gene splicing, single nucleotide polymorphisms, epigenetics and microRNA, transcription regulation and multiple gene copies.
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12
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Genomic approaches for the elucidation of genes and gene networks underlying cardiovascular traits. Biophys Rev 2018; 10:1053-1060. [PMID: 29934864 PMCID: PMC6082306 DOI: 10.1007/s12551-018-0435-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Accepted: 06/13/2018] [Indexed: 12/31/2022] Open
Abstract
Genome-wide association studies have shed light on the association between natural genetic variation and cardiovascular traits. However, linking a cardiovascular trait associated locus to a candidate gene or set of candidate genes for prioritization for follow-up mechanistic studies is all but straightforward. Genomic technologies based on next-generation sequencing technology nowadays offer multiple opportunities to dissect gene regulatory networks underlying genetic cardiovascular trait associations, thereby aiding in the identification of candidate genes at unprecedented scale. RNA sequencing in particular becomes a powerful tool when combined with genotyping to identify loci that modulate transcript abundance, known as expression quantitative trait loci (eQTL), or loci modulating transcript splicing known as splicing quantitative trait loci (sQTL). Additionally, the allele-specific resolution of RNA-sequencing technology enables estimation of allelic imbalance, a state where the two alleles of a gene are expressed at a ratio differing from the expected 1:1 ratio. When multiple high-throughput approaches are combined with deep phenotyping in a single study, a comprehensive elucidation of the relationship between genotype and phenotype comes into view, an approach known as systems genetics. In this review, we cover key applications of systems genetics in the broad cardiovascular field.
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13
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Ikram MA, Brusselle GGO, Murad SD, van Duijn CM, Franco OH, Goedegebure A, Klaver CCW, Nijsten TEC, Peeters RP, Stricker BH, Tiemeier H, Uitterlinden AG, Vernooij MW, Hofman A. The Rotterdam Study: 2018 update on objectives, design and main results. Eur J Epidemiol 2017; 32:807-850. [PMID: 29064009 PMCID: PMC5662692 DOI: 10.1007/s10654-017-0321-4] [Citation(s) in RCA: 338] [Impact Index Per Article: 48.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 10/06/2017] [Indexed: 02/07/2023]
Abstract
The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1500 research articles and reports (see www.erasmus-epidemiology.nl/rotterdamstudy ). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods.
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Affiliation(s)
- M Arfan Ikram
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands.
| | - Guy G O Brusselle
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Respiratory Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium
| | - Sarwa Darwish Murad
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Gastro-Enterology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Oscar H Franco
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Cardiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - André Goedegebure
- Department of Otolaryngology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Caroline C W Klaver
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Tamar E C Nijsten
- Department of Dermatology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Robin P Peeters
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Bruno H Stricker
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Henning Tiemeier
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
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