articles+ search results

HEART failure patients, PATIENT reported outcome measures, PATIENTS' attitudes, CLINICAL trials, HEART failure, and QUALITY of life

There are many consequences of heart failure (HF), including symptoms, impaired health‐related quality of life (HRQoL), and physical and social limitations (functional status). These have a substantial impact on patients' lives, yet are not routinely captured in clinical trials. Patient‐reported outcomes (PROs) can quantify patients' experiences of their disease and its treatment. Steps can be taken to improve the use of PROs in HF trials, in regulatory and payer decisions, and in patient care. Importantly, PRO measures (PROMs) must be developed with involvement of patients, family members, and caregivers from diverse demographic groups and communities. PRO data collection should become more routine not only in clinical trials but also in clinical practice. This may be facilitated by the use of digital tools and interdisciplinary patient advocacy efforts. There is a need for standardization, not only of the PROM instruments, but also in procedures for analysis, interpretation and reporting PRO data. More work needs to be done to determine the degree of change that is important to patients and that is associated with increased risks of clinical events. This 'minimal clinically important difference' requires further research to determine thresholds for different PROMs, to assess consistency across trial populations, and to define standards for improvement that warrant regulatory and reimbursement approvals. PROs are a vital part of patient care and drug development, and more work should be done to ensure that these measures are both reflective of the patient experience and that they are more widely employed. [ABSTRACT FROM AUTHOR]

SEPTIC shock, INTERLEUKIN-7, LYMPHOCYTE count, LYMPHOPENIA, T cells, and INTRAVENOUS therapy

Background: Profound lymphopenia is an independent predictor of adverse clinical outcomes in sepsis. Interleukin-7 (IL-7) is essential for lymphocyte proliferation and survival. A previous phase II study showed that CYT107, a glycosylated recombinant human IL-7, administered intramuscularly reversed sepsis-induced lymphopenia and improved lymphocyte function. Thepresent study evaluated intravenous administration of CYT107. This prospective, double-blinded, placebo-controlled trial was designed to enroll 40 sepsis patients, randomized 3:1 to CYT107 (10 µg/kg) or placebo, for up to 90 days. Results: Twenty-one patients were enrolled (fifteen CYT107 group, six placebo group) at eight French and two US sites. The study was halted early because three of fifteen patients receiving intravenous CYT107 developed fever and respiratory distress approximately 5–8 h after drug administration. Intravenous administration of CYT107 resulted in a two–threefold increase in absolute lymphocyte counts (including in both CD4+ and CD8+ T cells (all p < 0.05)) compared to placebo. This increase was similar to that seen with intramuscular administration of CYT107, was maintained throughout follow-up, reversed severe lymphopenia and was associated with increase in organ support free days (OSFD). However, intravenous CYT107 produced an approximately 100-fold increase in CYT107 blood concentration compared with intramuscular CYT107. No cytokine storm and no formation of antibodies to CYT107 were observed. Conclusion: Intravenous CYT107 reversed sepsis-induced lymphopenia. However, compared to intramuscular CYT107 administration, it was associated with transient respiratory distress without long-term sequelae. Because of equivalent positive laboratory and clinical responses, more favorable pharmacokinetics, and better patient tolerability, intramuscular administration of CYT107 is preferable. Trial registration: Clinicaltrials.gov, NCT03821038. Registered 29 January 2019, https://clinicaltrials.gov/ct2/show/NCT03821038?term=NCT03821038&draw=2&rank=1. [ABSTRACT FROM AUTHOR]

MEDULLOBLASTOMA, HIPPOCAMPUS (Brain), CHILD patients, VOLUMETRIC-modulated arc therapy, BRAIN tumors, and SUBSTANCE abuse relapse

Background: Hippocampal avoidance (HA) has been shown to preserve cognitive function in adult patients with cancer treated with whole‐brain radiation therapy for brain metastases. However, the feasibility of HA in pediatric patients with brain tumors has not been explored because of concerns of increased risk of relapse in the peri‐hippocampal region. Our aim was to determine patterns of recurrence and incidence of peri‐hippocampal relapse in pediatric patients with medulloblastoma (MB). Methods and materials: We identified pediatric patients with MB treated with protons between 2002 and 2016 and who had recurrent disease. To estimate the risk of peri‐hippocampal recurrence, three hippocampal zones (HZs) were delineated corresponding to ≤5 mm (HZ‐1), 6 to 10 mm (HZ‐2), and >10 mm (HZ‐3) distance of the recurrence from the contoured hippocampi. To determine the feasibility of HA, three standard‐risk patients with MB were planned using either volumetric‐modulated arc therapy (VMAT) or intensity‐modulated proton therapy (IMPT) plans. Results: Thirty‐eight patients developed a recurrence at a median of 1.6 years. Of the 25 patients who had magnetic resonance imaging of the recurrence, no patients failed within the hippocampus and only two patients failed within HZ‐1. The crude incidence of peri‐hippocampal failure was 8%. Both HA‐VMAT and HA‐IMPT plans were associated with significantly reduced mean dose to the hippocampi (p <.05). HA‐VMAT and HA‐IMPT plans were associated with decreased percentage of the third and lateral ventricles receiving the prescription craniospinal dose of 23.4 Gy. Conclusions: Peri‐hippocampal failures are uncommon in pediatric patients with MB. Hippocampal avoidance should be evaluated in a prospective cohort of pediatric patients with MB. Plain Language Summary: In this study, the patterns of disease recurrence in patients with a pediatric brain tumor known as medulloblastoma treated with proton radiotherapy were examined. The majority of failures occur outside of an important structure related to memory formation called the hippocampus. Hippocampal sparing radiation plans using proton radiotherapy were generated and showed that dose to the hippocampus was able to be significantly reduced. The study provides the rationale to explore hippocampal sparing in pediatric medulloblastoma in a prospective clinical trial. The incidence of peri‐hippocampal failures in patients treated with proton radiotherapy for pediatric medulloblastoma was 8%.Hippocampal sparing plans were associated with significant reduction in the mean dose to the right and left hippocampi. [ABSTRACT FROM AUTHOR]

LEFT heart ventricle, PATIENT aftercare, CAUSES of death, CONFIDENCE intervals, MAGNETIC resonance imaging, GLOBAL longitudinal strain, SYSTEMIC scleroderma, TERTIARY care, DESCRIPTIVE statistics, RESEARCH funding, LOGISTIC regression analysis, ODDS ratio, LEFT heart atrium, HEART failure, and PROPORTIONAL hazards models

Objective This study aimed to determine whether lower values of feature-tracking cardiovascular magnetic resonance (CMR)-derived left atrial reservoir strain (LARS) and impaired left ventricular (LV) global longitudinal strain (GLS) were associated with the presence of symptoms and long-term prognosis in patients with SSc. Methods A total of 100 patients {54 [interquartile range (IQR) 46–64] years, 42% male} with SSc who underwent CMR imaging at two tertiary referral centres were included. All patients underwent analysis of LARS and LV GLS using feature-tracking on CMR and were followed-up for the occurrence of all-cause mortality. Results The median LV GLS was –21.8% and the median LARS was 36%. On multivariable logistic regression, LARS [odds ratio (OR) 0.964 per %, 95% CI 0.929, 0.998, P  = 0.049] was independently associated with New York Heart Association (NYHA) class II–IV heart failure symptoms. Over a median follow-up of 37 (21–62) months, a total of 24 (24%) patients died. Univariable Cox regression analysis demonstrated that LARS [hazard ratio (HR) 0.94 per 1%, 95% CI 0.91, 0.97, P  < 0.0001) and LV GLS (HR 1.10 per %, 95% CI 1.03, 1.17, P  = 0.005) were associated with all-cause mortality, while LV ejection fraction was not. Likelihood ratio tests demonstrated that LARS provided incremental value over prognostically important clinical and imaging parameters, including late gadolinium enhancement. Conclusion In patients with SSc, LARS was independently associated with the presence of NYHA class II–IV heart failure symptoms. Although both LARS and LV GLS were associated with all-cause mortality, only LARS provided incremental value over all evaluated variables known to be prognostically important in patients with SSc. [ABSTRACT FROM AUTHOR]

COVID-19 vaccines, ANTIBODY formation, HEART transplant recipients, LUNG transplantation, HIV seroconversion, and BOOSTER vaccines

Antibody response to a third dose of SARS-CoV-2 vaccine in heart and lung transplant recipients Morbidity and mortality from SARS-CoV-2 infection in heart (HT) and lung transplant (LT) recipients are high, especially for LT recipients, despite vaccination.[1] Despite severe COVID-19 outcomes, HT/LT recipients represent <10% of solid organ transplant recipients (SOTRs) included in cohort studies evaluating two and three dose regimens.[2] There is now strong evidence to support that SOTRs in a greater immunosuppressed state (common among HT/LT recipients) are at increased risk for persistent seronegative state post-D3.[[3]] Therefore, we evaluated antispike antibody responses before and after a third vaccine dose (D3) in HT/LT recipients to quantify post-D3 antibody responses. Effect of Mycophenolate mofetil dosing on antibody response to SARS-CoV-2 vaccination in heart and lung transplant recipients. [Extracted from the article]

GENETIC variation, SLEEP, MISSENSE mutation, GENETIC testing, CLOCK genes, SLEEP disorders, and EXOMES

Rare variants in ten genes have been reported to cause Mendelian sleep conditions characterised by extreme sleep duration or timing. These include familial natural short sleep (ADRB1, DEC2/BHLHE41, GRM1 and NPSR1), advanced sleep phase (PER2, PER3, CRY2, CSNK1D and TIMELESS) and delayed sleep phase (CRY1). The association of variants in these genes with extreme sleep conditions were usually based on clinically ascertained families, and their effects when identified in the population are unknown. We aimed to determine the effects of these variants on sleep traits in large population-based cohorts. We performed genetic association analysis of variants previously reported to be causal for Mendelian sleep and circadian conditions. Analyses were performed using 191,929 individuals with data on sleep and whole-exome or genome-sequence data from 4 population-based studies: UK Biobank, FINRISK, Health-2000-2001, and the Multi-Ethnic Study of Atherosclerosis (MESA). We identified sleep disorders from self-report, hospital and primary care data. We estimated sleep duration and timing measures from self-report and accelerometery data. We identified carriers for 10 out of 12 previously reported pathogenic variants for 8 of the 10 genes. They ranged in frequency from 1 individual with the variant in CSNK1D to 1,574 individuals with a reported variant in the PER3 gene in the UK Biobank. No carriers for variants reported in NPSR1 or PER2 were identified. We found no association between variants analyzed and extreme sleep or circadian phenotypes. Using sleep timing as a proxy measure for sleep phase, only PER3 and CRY1 variants demonstrated association with earlier and later sleep timing, respectively; however, the magnitude of effect was smaller than previously reported (sleep midpoint ~7 mins earlier and ~5 mins later, respectively). We also performed burden tests of protein truncating (PTVs) or rare missense variants for the 10 genes. Only PTVs in PER2 and PER3 were associated with a relevant trait (for example, 64 individuals with a PTV in PER2 had an odds ratio of 4.4 for being "definitely a morning person", P = 4x10-8; and had a 57-minute earlier midpoint sleep, P = 5x10-7). Our results indicate that previously reported variants for Mendelian sleep and circadian conditions are often not highly penetrant when ascertained incidentally from the general population. Author summary: Clinically ascertained family-based studies have previously identified rare genetic variation associated with causing life-long sleep conditions, specifically shorter sleep, and earlier or later sleep timing. However, the effects of previously reported genetic variants on sleep duration and timing when identified incidentally through population-based studies are not known. Here, we take advantage of up to 191,929 individuals from four population-based studies, including the UK Biobank, to estimate the effects of these variants on sleep duration and timing using self-reported and accelerometer-based sleep estimates coupled with sequencing data. Our analysis revealed no association between variants previously reported and extreme sleep conditions. Two variants located in two genes (PER3 and CRY1) showed evidence of association with sleep timing, but their estimated effects (~5 to 7 minutes) on sleep timing are much smaller relative to those previously reported. Our results indicate that previously reported variants are not causal for extreme sleep conditions in the general population. Finally, although we were unable to analyse a previously reported variant in the PER2 gene associated with sleep timing, additional analysis in the UK Biobank revealed carries of protein-truncating variants in this gene have an approximately 1-hour earlier sleep midpoint compared to non-carriers. These population-based estimates are important because of the recent dramatic increase in direct-to-consumer and health service genome-wide genetic testing. [ABSTRACT FROM AUTHOR]

ALCOHOL drinking, ENERGY consumption, WARNING labels, INCOME, WEIGHT gain, and CONSUMPTION (Economics)

Background: Alcohol is a discretionary, energy dense, dietary component. Compared to non-drinkers, people who consume alcohol report higher total energy intake and may be at increased risk of weight gain, overweight, and obesity, which are key preventable risk factors for illness. However, accurate consumer knowledge of the energy content in alcohol is low. To inform future behaviour change interventions among drinkers, this study investigated individual characteristics associated with changing alcohol consumption due to energy-related concerns.Methods: An online survey was undertaken with 801 Australian adult drinkers (18-59 years, 50.2% female), i.e. who consumed alcohol at least monthly. In addition to demographic and health-related characteristics, participants reported past-year alcohol consumption, past-year reductions in alcohol consumption, frequency of harm minimisation strategy use (when consuming alcohol), and frequency of changing alcohol consumption behaviours because of energy-related concerns.Results: When prompted, 62.5% of participants reported changing alcohol consumption for energy-related reasons at least 'sometimes'. Women, those aged 30-44 years, metropolitan residents, those with household income $80,001-120,000, and risky/more frequent drinkers had increased odds of changing consumption because of energy-related concerns, and unemployed respondents had reduced odds.Conclusions: Results indicate that some sociodemographic groups are changing alcohol consumption for energy-related reasons, but others are not, representing an underutilised opportunity for health promotion communication. Further research should investigate whether messaging to increase awareness of alcohol energy content, including through systems-based policy actions such as nutritional/energy product labelling, would motivate reduced consumption across a broader range of drinkers. [ABSTRACT FROM AUTHOR]

COVID-19 vaccines, TRANSPLANTATION of organs, tissues, etc., IMMUNE response, MESSENGER RNA, and SARS-CoV-2 Delta variant

Heterologous vaccination has been explored in small populations of solid organ transplant recipients (SOTRs),1-4 yet 38% of participants had persistently suboptimal response indicating potential role for further vaccine doses.1 The US CDC currently recommends immunocompromised adults who received an Ad26.COV2.S prime to receive one additional dose of SARS-CoV-2 mRNA vaccine, either BNT162b2 or mRNA-1273, followed by two mRNA vaccine boosters, although the efficacy of this strategy in immunocompromised persons is not known. A third dose of SARS-CoV-2 vaccine increases neutralizing antibodies against variants of concern in solid organ transplant recipients. Immunogenicity of Ad26.COV2.S prime and two subsequent doses of mRNA SARS-CoV-2 vaccines in solid organ transplant recipients: A case series. [Extracted from the article]

SEDENTARY lifestyles, GLOBAL Positioning System, HOME environment, SCHOOL environment, BUILT environment, SOCIAL support, CROSS-sectional method, SELF-evaluation, POPULATION geography, PHYSICAL activity, SOCIAL context, ACCELEROMETRY, SELF-efficacy, QUESTIONNAIRES, DESCRIPTIVE statistics, STATISTICAL models, and ADOLESCENCE

Background: A better understanding of the extent to which psychosocial and environmental correlates of physical activity are specific to locations would inform intervention optimization. Purpose: To investigate cross-sectional associations of location-general and location-specific variables with physical activity and sedentary time in three common locations adolescents spend time. Methods: Adolescents (N = 472,Mage = 14.1,SD = 1.5) wore an accelerometer and global positioning systems (GPS) tracker and self-reported on psychosocial (e.g., self-efficacy) and environmental (e.g., equipment) factors relevant to physical activity and sedentary time. We categorized each survey item based on whether it was specific to a location to generate psychosocial and environmental indices that were location-general or specific to either school, non-school, or home location. Physical activity (MVPA) and sedentary time were based on time/location match to home, school, or all "other" locations. Mixed-effects models investigated the relation of each index with location-specific activity. Results: The location-general and non-school physical activity psychosocial indices were related to greater MVPA at school and "other" locations. The school physical activity environment index was related to greater MVPA and less sedentary time at school. The home activity environment index was related to greater MVPA at home. The non-school sedentary psychosocial index was related to less sedentary time at home. Interactions among indices revealed adolescents with low support on one index benefited (i.e., exhibited more optimal behavior) from high support on another index (e.g., higher scores on the location-general PA psychosocial index moderated lower scores on the home PA environment index). Concurrent high support on two indices did not provide additional benefit. Conclusions: No psychosocial or environment indices, including location-general indices, were related to activity in all locations. Most of the location-specific indices were associated with activity in the matching location(s). These findings provide preliminary evidence that psychosocial and environmental correlates of activity are location specific. Future studies should further develop location-specific measures and evaluate these constructs and whether interventions may be optimized by targeting location-specific psychosocial and environmental variables across multiple locations. [ABSTRACT FROM AUTHOR]

United States. National Institutes of Health -- Analysis, Lipids -- Analysis, Genetic research -- Analysis -- Genetic aspects, Biological sciences, University of Oxford, University of Pennsylvania. Perelman School of Medicine, University of North Carolina at Chapel Hill, Harvard University. Harvard Medical School, University of Michigan, Boston University. School of Public Health, Rush University. Medical Center, and Stanford University. School of Medicine

Million Veterans Program Keywords lipid biology; fine-mapping; functional genomics; post-GWAS; regulatory mechanism; complex traits; variant prioritization Summary A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology. Author Affiliation: (1) Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA (2) Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA (3) Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI 48109, USA (4) William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, John Vane Science Centre, Charterhouse Square, London EC1M 6BQ, UK (5) Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, USA (6) VA Palo Alto Health Care Systems, Palo Alto, CA, USA (7) Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA (8) Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA (9) Endocrinology, Boston Childrens Hospital, Boston, MA 02115, USA (10) Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, 75 Ames street, Cambridge, MA 02142, USA (11) Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany (12) McDonnell Genome Institute and Department of Medicine, Washington University, St. Louis, MO 63108, USA (13) Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA (14) Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA (15) Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, EC1M 6BQ London, UK (16) Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA (17) Atlanta VA Health Care System, Decatur, GA, USA (18) Malcolm Randall VA Medical Center, Gainesville, FL, USA (19) Division of Vascular Surgery and Endovascular Therapy, University of Florida College of Medicine, Gainesville, FL, USA (20) deCODE genetics/Amgen, Inc., Sturlugata 8, Reykjavik 102, Iceland (21) School of Engineering and Natural Sciences, University of Iceland, Sæmundargötu 2, Reykjavik 102, Iceland (22) Department of Clinical Biochemistry, Landspitali - National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland (23) Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungbuk, South Korea (24) Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan (25) Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan (26) Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan (27) Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, The University of Tokyo, Tokyo, Japan (28) Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan (29) Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan (30) Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA (31) Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA (32) K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway (33) MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, BS8 2BN Bristol, UK (34) Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway (35) Division of Medicine and Laboratory Sciences, University of Oslo, Oslo, Norway (36) Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00014 Helsinki, Finland (37) Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland (38) Department of Genetics, Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA 19104, USA (39) Center for Genetic Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL 60611, USA (40) Department of Medicine (Medical Genetics), University of Washington, Seattle, WA, USA (41) Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA (42) Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA (43) Department of Cardiovascular Medicine and the Gonda Vascular Center, Mayo Clinic, Rochester, MN, USA (44) Tohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan (45) Wellcome Trust Sanger Institute, CB10 1SA Hinxton, UK (46) Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK (47) Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, WA 98109, USA (48) Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA 02215, USA (49) Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, EH4 2XU Edinburgh, UK (50) Usher Institute, The University of Edinburgh, Nine, Edinburgh Bioquarter, 9 Little France Road, EH16 4UX Edinburgh, UK (51) Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, OX3 7LF Oxford, UK (52) Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, OX3 7LF Oxford, UK (53) Center for Non-Communicable Diseases, Karachi, SD, Pakistan & Faisalabad Institute of Cardiology, Faislabad, Pakistan (54) Department of Population Medicine, Qatar University College of Medicine, QU Health, Doha, Qatar (55) Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA (56) Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA (57) Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA (58) Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA (59) Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa (60) Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK (61) Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA (62) Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, W2 1PG London, UK (63) Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, UB1 3HW Middlesex, UK (64) Imperial College Healthcare NHS Trust, Imperial College London, W12 0HS London, UK (65) Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden (66) MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, CB2 0QQ Cambridge, UK (67) Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, CB1 8RN Cambridge, UK (68) Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan (69) Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands (70) Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands (71) Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands (72) Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, EX2 5DW Exeter, UK (73) Department of Clinical Acupuncture and Moxibustion, Nanjing University of Chinese Medicine, Nanjing, Jiangsu 210029, China (74) Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany (75) Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany (76) Bristol Dental School, University of Bristol, Lower Maudlin Street, BS1 2LY Bristol, UK (77) Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield Grove, BS8 2BN Bristol, UK (78) Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117549, Singapore (79) Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark (80) Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark (81) The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Lundquist Institute for Biomedical Innovations (Formerly LABioMed) at Harbor-UCLA Medical Center, Torrance, CA 90502, USA (82) Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22903, USA (83) Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan; No. 1650, Sec. 4, Taiwan Boulevard, Taichung City 40705, Taiwan (84) Institute of Population Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhunan Town, Miaoli County 350, Taiwan, ROC (85) NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, EC1M 6BQ London, UK (86) Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark (87) Division of Cardiovascular Medicine, Radcliffe Department of Medicine, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK (88) Unit of Genomics of Complex Diseases. Sant Pau Biomedical Research Institute (IIB Sant Pau), Barcelona, Spain (89) Cardiovascular Medicine Unit, Department of Medicine, Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden (90) Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands (91) Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Rome, Italy (92) Dipartimento di Scienze Biomediche, Università degli Studi di Sassari, Sardinia, Italy (93) University Center for Primary Care and Public Health, University of Lausanne, Rte de Berne 113, 1010 Lausanne, Switzerland (94) Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland (95) Department of Medicine, Internal Medicine, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011 Lausanne, Switzerland (96) Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands (97) BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, UK (98) Institute for Cardiogenetics, University of Lübeck, DZHK (German Research Centre for Cardiovascular Research), partner site Hamburg/Lübeck/Kiel, University Heart Center Lübeck, Lübeck and Charité -- University Medicine Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute for Dental and Craniofacial Sciences, Department of Periodontology and Synoptic Dentistry, Berlin, Germany (99) Deutsches Herzzentrum München, Klinik für Herz- und Kreislauferkrankungen, Technische Universität München, Munich, Germany (100) Deutsches Zentrum für Herz-Kreislauf-Forschung (DZHK) e.V., partner site Munich Heart Alliance, Munich, Germany (101) Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China (102) Lund University Diabetes Centre, Lunds University, Malmö, Sweden (103) Institute of Genetic Epidemiology, Department of Genetics and Pharmacology, Medical University of Innsbruck, Innsbruck, Austria and German Chronic Kidney Disease Study, Austria (104) Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107 Leipzig, Germany (105) LIFE Research Centre for Civilization Diseases, University of Leipzig, Philipp-Rosenthal-Straße 27, 04103 Leipzig, Germany (106) Radboud university medical center, Radboud Institute for Health Sciences, Nijmegen, the Netherlands (107) Quantinuum Research LLC, Wayne, PA 19087, USA (108) Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA (109) Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15232, USA (110) Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Via Galvani 31, 39100 Bolzano, Italy (111) Department of Clinical Biochemistry, Lillebaelt Hospital, Vejle, Denmark (112) Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101, USA (113) Department of Anthropology, University of Toronto at Mississauga, Mississauga, ON L5L 1C6, Canada (114) Department of Computer Science, University of Toronto, Toronto, ON M5S 2E4, Canada (115) The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA (116) Department of Twin Research and Genetic Epidemiology, King's College London, SE1 7EH London, UK (117) NIHR Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, SE1 9RT London, UK (118) Department of Cardiology, University of Groningen, University Medical Center Groningen, 9700RB Groningen, the Netherlands (119) Institute of Cardiovascular Sciences, University College London, Gower Street, WC1E 6BT London, UK (120) Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, WC1E 6BT London, UK (121) Department of Surgery, University of Pennsylvania, Philadelphia, PA 19104, USA (122) Amsterdam UMC, Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, Amsterdam 1081HV, the Netherlands (123) Leiden University Medical Center, Department of Cell and Chemical Biology, Leiden 2333ZA, the Netherlands (124) Montreal Heart Institute, Université de Montréal, 5000 Belanger street, Montreal, QC H1T1C8, Canada (125) Icelandic Heart Association, 201 Kopavogur, Iceland (126) Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany (127) SYNLAB MVZ Humangenetik Mannheim GmbH, 68163 Mannheim, Germany (128) Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China (129) Biomedical Technology Research Center, Tokushima Research Institute, Otsuka Pharmaceutical Co., Ltd., Tokushima, Japan (130) School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China (131) Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia (132) Nuffield Department of Population Health, University of Oxford, Oxford, UK (133) Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (134) Section of Statistical Multi-omics, Department of Clinical and Experimental research, University of Surrey, Guildford, Surrey, UK (135) Laboratory of Neurogenetics, National Institute on Aging, NIH, Bethesda, MD, USA (136) Data Tecnica International, Glen Echo, MD, USA (137) MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK (138) Institute for Medical Informatics, Biometrie and Epidemiology, University of Duisburg-Essen, Essen, Germany (139) Centre for Public Health, Queen's University of Belfast, Belfast, Northern Ireland (140) Genomic Oncology Area, GENYO, Centre for Genomics and Oncological Research: Pfizer-University of Granada-Andalusian Regional Government, Granada, Spain (141) Hematology Department, Hospital Universitario Virgen de las Nieves, Granada, Spain (142) Instituto de Investigación Biosanitaria de Granada (ibs.GRANADA), Granada, Spain (143) Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (144) Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore (145) Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya 461-8673, Japan (146) University of Alabama at Birmingham, Epidemiology, School of Public Health, Birmingham, AL, USA (147) Tampere Centre for Skills Training and Simulation, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland (148) Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston TX 77030, USA (149) CONACYT, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Ciudad de Mexico, Mexico (150) Departamento de Genómica Computacional, Instituto Nacional de Medicina Genómica, Ciudad de Mexico, Mexico (151) Center for diabetes research, University of Bergen, Bergen, Norway (152) Genomic Research on Complex diseases (GRC Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India (153) Academy of Scientific and Innovative Research (AcSIR), CSIR-Human Resource Development Centre, New Delhi, India (154) Hunter Medical Research Institute, Newcastle, NSW, Australia (155) Medical Research Institute, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul 03181, Korea (156) Department of Clinical Research Design & Evaluation, SAIHST, Sungkyunkwan University, Seoul 06355, Korea (157) Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul 04514, Korea (158) Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul 03181, Korea (159) Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, UK (160) Thurston Arthritis Research Center, University of North Carolina, Chapel Hill, NC, USA (161) Health Services and Systems Research, Duke-NUS Medical School, 169857, Singapore (162) Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, Anschutz Medical Campus, University of Colorado, Denver, Aurora, CO 80045, USA (163) Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi 110020, India (164) Departments of Ophthalmology and Human Genetics, Radboud University Nijmegen Medical Center, Philips van Leydenlaan 15, Nijmegen 6525 EX, the Netherlands (165) Vanderbilt Epidemiology Center, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN, USA (166) Department of Pediatrics, University of California San Francisco, Oakland, CA 94609, USA (167) National Center for Global Health and Medicine, Tokyo 1628655, Japan (168) Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA (169) Department of Biostatistics and Epidemiology, University of Massachusetts-Amherst, Amherst, MA 01003, USA (170) Department of Cardiovascular Sciences, University of Leicester, Leicester, UK (171) NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK (172) Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology and Visual Sciences Key Laboratory, 17 Hougou Lane, Chong Wen Men, Beijing 100005, China (173) Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, 1 Dong Jiao Min Xiang, Dong Cheng District, Beijing 100730, China (174) Institute of Genetics and Biophysics 'Adriano Buzzati-Traverso' - CNR, Naples, Italy (175) IRCCS Neuromed, Pozzilli, Isernia, Italy (176) Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA (177) Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA (178) Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA (179) Department of Nephrology, University Hospital Regensburg, Regensburg, Germany (180) Institute for Maternal and Child Health--IRCCS, Burlo Garofolo, 34127 Trieste, Italy (181) Department of Molecular Epidemiology, German Institute of 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Groningen, Groningen 9700 RB, the Netherlands (191) Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland (192) Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland (193) Sleep Medicine and Circadian Disorders, Brigham and Women's Hospital, Boston, MA 02115, USA (194) Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA (195) Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands (196) Laboratory of Epidemiology and Population Science National Institute on Aging Intramural Research Program, NIH 251 Bayview Blvd, NIH Biomedical Research Center, Baltimore, MD 21224, USA (197) Fels Cancer Institute for Personalized Medicine, Temple University Lewis Katz School of Medicine, Philadelphia, PA, USA (198) Interfaculty Institute for Genetics and Functional 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Gothenburg, Gothenburg, Sweden (206) Institute of Medical Informatics and Statistics, Kiel University, Kiel, Germany (207) Institute of Translational Genomics, Helmholtz Zentrum München -- German Research Center for Environmental Health, Neuherberg, Germany (208) Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Oxford, UK (209) School of Medicine and Public Health, Faculty of Medicine and Health, University of Newcastle, Newcastle, NSW 2308, Australia (210) Center for Geriatrics and Gerontology, Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan (211) School of Medicine, National Yang-Ming University, Taipei, Taiwan (212) School of Medicine, National Defense Medical Center, Taipei, Taiwan (213) Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan (214) Department of Medicine, School of Medicine, National 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School of Medicine, Seoul, Korea (259) Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA 15232, USA (260) Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117545, Singapore (261) Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore 117609, Singapore (262) Department of Endocrinology and Metabolism, Kyung Hee University School of Medicine, Seoul 02447, Korea (263) Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany (264) Algebra University College, Ilica 242, Zagreb, Croatia (265) Paavo Nurmi Centre, Sports and Exercise Medicine Unit, Department of Physical Activity and Health, University of Turku, Turku, Finland (266) Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University of Groningen, University Medical Center Groningen, 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Hanover St., Baltimore, MD 21225, USA (321) The Eye Hospital, School of Ophthalmology & Optometry, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China (322) Synlab Academy, SYNLAB Holding Deutschland GmbH, Mannheim and Augsburg, Germany (323) Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria (324) Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland (325) Leiden University Medical Center, Department of Biomedical Data Sciences, Section Molecular Epidemiology, 2333ZA Leiden, the Netherlands (326) Amsterdam UMC, Department of General Practice and Elderly Care, Amsterdam Public Health Research Institute, 1081HV Amsterdam, the Netherlands (327) Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA (328) Corporal Michael Crescenz VA Medical Center, Philadelphia, PA 19104, USA (329) Institute of Social and Economic Research, University of Essex, Wivenhoe Park CO4 3SQ, UK (330) Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA (331) Unidad de Investigacion Medica en Bioquimica, Hospital de Especialidades, Centro Medico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico (332) Department of Health Services, University of Washington, Seattle, WA, USA (333) Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark (334) 16Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, 12 South Drive, Room 4047, Bethesda, MD 20892, USA (335) Danish Aging Research Center, University of Southern Denmark, Odense C, Denmark (336) Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland (337) Broad Institute of MIT and Harvard, Cambridge, MA, USA (338) Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA (339) Department of Pediatrics, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA (340) Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA (341) School of Medicine, Southern University of Science and Technology, Shenzhen, China (342) Netherlands Heart Institute, Utrecht, the Netherlands (343) Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA (344) Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA (345) Department of Medicine, Harvard Medical School, Boston, MA, USA (346) Northern Finland Birth Cohorts, Infrastructure for population studies, Faculty of Medicine, University of Oulu, Oulu, Finland (347) Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland (348) Biocenter of Oulu, University of Oulu, Oulu, Finland (349) Institute for Genetic and Biomedical Research, Italian National Council of Research (IRGB CNR), Cagliari, Italy (350) University of Sassari, Sassari, Italy (351) Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands (352) Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands (353) Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, the Netherlands (354) Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands (355) Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands (356) Population Health Research Institute, St George's, University of London, SW17 0RE London, UK (357) National Heart and Lung Institute, Imperial College London, W2 1PG London, UK (358) School of Public Health, Imperial College London, W12 7RH London, UK (359) Taichung Veterans General Hospital, Taichung, Taiwan; No. 1650, Sec. 4, Taiwan Boulevard, Xitun District Taichung City 40705, Taiwan (360) Division of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan; No. 201, Sec. 2, Shipai Road, Beitou District, Taipei City 112201, Taiwan (361) OCDEM, University of Oxford, Churchill Hospital, OX3 7LE Oxford, UK (362) NIHR Oxford Biomedical Research Centre, Churchill Hospital, Oxford, UK (363) Ocular Epidemiology, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore (364) Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore 169857, Singapore (365) Data Science, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore (366) German Center for Diabetes Research (DZD), Neuherberg, Germany (367) University of Exeter Medical School, University of Exeter, EX2 5DW Exeter, UK (368) Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (369) Framingham Heart Study, National Heart, Lung, and Blood Institute, US National Institutes of Health, Bethesda, MD, USA (370) Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran (371) Department of Genetics, Shanghai-MOST Key Laboratory of Health and Disease Genomics, Chinese National Human Genome Center at Shanghai, Shanghai 201203, China (372) Technical University of Munich (TUM) and Klinikum Rechts der Isar, TUM School of Medicine, Munich, Germany (373) Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia (374) Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland (375) Stanford Cardiovascular Institute, Stanford University, Stanford, CA 94305, USA (376) Stanford Diabetes Research Center, Stanford University, Stanford, CA 94305, USA (377) Regeneron Pharmaceuticals, Tarrytown, NY, USA (378) Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore (379) MRC-PHE Centre for Environment and Health, Imperial College London, London W2 1PG, UK (380) School of Electrical & Information Engineering, University of the Witwatersrand, Witwatersrand, South Africa (381) Institute for Minority Health Research, University of Illinois College of Medicine, Chicago, IL, USA (382) Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA (383) QIMR Berghofer Medical Research Institute, 300 Herston Road, Brisbane, QLD 4006, Australia (384) Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA (385) Department of Cardiology, Columbia University Irving Medical Center, New York, NY, USA (386) Big Data Instutute, University of Oxford, OX3 7LF Oxford, UK (387) Aberdeen Centre for Health Data Science,1:042 Polwarth Building School of Medicine, Medical Science and Nutrition University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, UK (388) Biomedical and Translational Informatics, Geisinger Health, Danville, PA 17822, USA (389) School of Basic and Medical Biosciences, Faculty of Life Sciences and Medicine, King's College London, London, UK (390) Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA (391) Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington, Seattle, WA, USA (392) Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center (CCHMC), Cincinnati, OH, USA (393) Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL 60611, USA (394) Department of Anthropology, Northwestern University, Evanston, IL 60208, USA (395) HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger 7600, Norway (396) Department of Medicine, Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger 7600, Norway (397) Department of Endocrinology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway (398) RIKEN Center for Integrative Medical Sciences, Yokohama, Japan (399) Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan (400) Laboratory of Statistical Immunology, WPI Immunology Frontier Research Center, Osaka University, Osaka, Japan (401) Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Osaka, Japan (402) Division of Molecular Pathology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan (403) Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, South Korea (404) VA Boston Healthcare System, Boston, MA, USA (405) VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA (406) University of Massachusetts, Boston, MA, USA (407) Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA (408) Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA (409) Department of Medicine, Brigham Women's Hospital, Boston, MA, USA (410) Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA (411) Departments of Pediatrics and Genetics, Harvard Medical School, Boston, MA, USA (412) Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA (413) Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA (414) Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK (415) Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia (416) Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA (417) Department of Statistics, The Pennsylvania State University, University Park, PA, USA (418) Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA (419) Department of Statistics, Stanford University, Stanford, CA, USA * Corresponding author Article History: Received 2 December 2021; Accepted 23 June 2022 (miscellaneous) Published: August 4, 2022 (footnote)420 These authors contributed equally Byline: Shweta Ramdas (1,420), Jonathan Judd (2,420), Sarah E. Graham (3,420), Stavroula Kanoni (4,420), Yuxuan Wang (5,420), Ida Surakka (3), Brandon Wenz (1), Shoa L. Clarke (6,7), Alessandra Chesi (8), Andrew Wells (1), Konain Fatima Bhatti (4), Sailaja Vedantam (9,10), Thomas W. Winkler (11), Adam E. Locke (12), Eirini Marouli (4), Greg J.M. Zajac (13), Kuan-Han H. Wu (14), Ioanna Ntalla (15), Qin Hui (16,17), Derek Klarin (10,18,19), Austin T. Hilliard (6), Zeyuan Wang (16,17), Chao Xue (3), Gudmar Thorleifsson (20), Anna Helgadottir (20), Daniel F. Gudbjartsson (20,21), Hilma Holm (20), Isleifur Olafsson (22), Mi Yeong Hwang (23), Sohee Han (23), Masato Akiyama (24,25), Saori Sakaue (26,27,28), Chikashi Terao (29), Masahiro Kanai (10,24,30), Wei Zhou (10,14,31), Ben M. Brumpton (32,33,34), Humaira Rasheed (32,33,35), Aki S. Havulinna (36,37), Yogasudha Veturi (38), Jennifer Allen Pacheco (39), Elisabeth A. Rosenthal (40), Todd Lingren (41), QiPing Feng (42), Iftikhar J. Kullo (43), Akira Narita (44), Jun Takayama (44), Hilary C. Martin (45), Karen A. Hunt (46), Bhavi Trivedi (46), Jeffrey Haessler (47), Franco Giulianini (48), Yuki Bradford (38), Jason E. Miller (38), Archie Campbell (49,50), Kuang Lin (51), Iona Y. Millwood (51,52), Asif Rasheed (53), George Hindy (54), Jessica D. Faul (55), Wei Zhao (56), David R. Weir (55), Constance Turman (57), Hongyan Huang (57), Mariaelisa Graff (58), Ananyo Choudhury (59), Dhriti Sengupta (59), Anubha Mahajan (60), Michael R. Brown (61), Weihua Zhang (62,63,64), Ketian Yu (13), Ellen M. Schmidt (13), Anita Pandit (13), Stefan Gustafsson (65), Xianyong Yin (13), Jian'an Luan (66), Jing-Hua Zhao (67), Fumihiko Matsuda (68), Hye-Mi Jang (23), Kyungheon Yoon (23), Carolina Medina-Gomez (69), Achilleas Pitsillides (5), Jouke Jan Hottenga (70,71), Andrew R. Wood (72), Yingji Ji (72), Zishan Gao (73,74,75), Simon Haworth (33,76), Ruth E. Mitchell (33,77), Jin Fang Chai (78), Mette Aadahl (79,80), Anne A. Bjerregaard (79), Jie Yao (81), Ani Manichaikul (82), Wen-Jane Lee (83), Chao Agnes Hsiung (84), Helen R. Warren (4,85), Julia Ramirez (4), Jette Bork-Jensen (86), Line L. Kårhus (79), Anuj Goel (60,87), Maria Sabater-Lleal (88,89), Raymond Noordam (90), Pala Mauro (91), Floris Matteo (91,92), Aaron F. McDaid (93,94), Pedro Marques-Vidal (95), Matthias Wielscher (62), Stella Trompet (90,96), Naveed Sattar (97), Line T. Møllehave (79), Matthias Munz (98), Lingyao Zeng (99,100), Jianfeng Huang (101), Bin Yang (101), Alaitz Poveda (102), Azra Kurbasic (102), Sebastian Schönherr (103), Lukas Forer (103), Markus Scholz (104,105), Tessel E. Galesloot (106), Jonathan P. Bradfield (107), Sanni E. Ruotsalainen (36), E. Warwick Daw (108), Joseph M. Zmuda (109), Jonathan S. Mitchell (110), Christian Fuchsberger (110), Henry Christensen (111), Jennifer A. Brody (112), Phuong Le (113,114), Mary F. Feitosa (108), Mary K. Wojczynski (108), Daiane Hemerich (115), Michael Preuss (115), Massimo Mangino (116,117), Paraskevi Christofidou (116), Niek Verweij (118), Jan W. Benjamins (118), Jorgen Engmann (119,120), Tsao L. Noah (121), Anurag Verma (1), Roderick C. Slieker (122,123), Ken Sin Lo (124), Nuno R. Zilhao (125), Marcus E. Kleber (126,127), Graciela E. Delgado (126), Shaofeng Huo (128), Daisuke D. Ikeda (129), Hiroyuki Iha (129), Jian Yang (130,131), Jun Liu (132,133), Ayse Demirkan (133,134), Hampton L. Leonard (135,136), Jonathan Marten (137), Carina Emmel (138), Börge Schmidt (138), Laura J. Smyth (139), Marisa Cañadas-Garre (139,140,141,142), Chaolong Wang (143,144), Masahiro Nakatochi (145), Andrew Wong (146), Nina Hutri-Kähönen (147), Xueling Sim (78), Rui Xia (148), Alicia Huerta-Chagoya (149), Juan Carlos Fernandez-Lopez (150), Valeriya Lyssenko (102,151), Suraj S. Nongmaithem (152), Alagu Sankareswaran (152,153), Marguerite R. Irvin (146), Christopher Oldmeadow (154), Han-Na Kim (155,156), Seungho Ryu (157,158), Paul R.H.J. Timmers (137,159), Liubov Arbeeva (160), Rajkumar Dorajoo (144,161), Leslie A. Lange (162), Gauri Prasad (153,163), Laura Lorés-Motta (164), Marc Pauper (164), Jirong Long (165), Xiaohui Li (81), Elizabeth Theusch (166), Fumihiko Takeuchi (167), Cassandra N. Spracklen (168,169), Anu Loukola (36), Sailalitha Bollepalli (36), Sophie C. Warner (170,171), Ya Xing Wang (172), Wen B. Wei (173), Teresa Nutile (174), Daniela Ruggiero (174,175), Yun Ju Sung (176), Shufeng Chen (101), Fangchao Liu (101), Jingyun Yang (177,178), Katherine A. Kentistou (159), Bernhard Banas (179), Anna Morgan (180), Karina Meidtner (181,182), Lawrence F. Bielak (56), Jennifer A. Smith (55,56), Prashantha Hebbar (183), Aliki-Eleni Farmaki (184,185), Edith Hofer (186,187), Maoxuan Lin (188), Maria Pina Concas (180), Simona Vaccargiu (189), Peter J. van der Most (190), Niina Pitkänen (191,192), Brian E. Cade (193,194), Sander W. van der Laan (195), Kumaraswamy Naidu Chitrala (196,197), Stefan Weiss (198), Amy R. Bentley (199), Ayo P. Doumatey (199), Adebowale A. Adeyemo (199), Jong Young Lee (200), Eva R.B. Petersen (201), Aneta A. Nielsen (202), Hyeok Sun Choi (203), Maria Nethander (204,205), Sandra Freitag-Wolf (206), Lorraine Southam (45,207), Nigel W. Rayner (45,60,207,208), Carol A. Wang (209), Shih-Yi Lin (210,211,212), Jun-Sing Wang (213,214), Christian Couture (215), Leo-Pekka Lyytikäinen (216,217), Kjell Nikus (218,219), Gabriel Cuellar-Partida (220), Henrik Vestergaard (86,221), Bertha Hidalgo (222), Olga Giannakopoulou (4), Qiuyin Cai (165), Morgan O. Obura (122), Jessica van Setten (223), Karen Y. He (224), Hua Tang (2), Natalie Terzikhan (133), Jae Hun Shin (203), Rebecca D. Jackson (225), Alexander P. Reiner (226), Lisa Warsinger Martin (227), Zhengming Chen (51,52), Liming Li (228), Takahisa Kawaguchi (68), Joachim Thiery (105,229), Joshua C. Bis (112), Lenore J. Launer (230), Huaixing Li (128), Mike A. Nalls (135,136), Olli T. Raitakari (191,192,231), Sahoko Ichihara (232), Sarah H. Wild (233), Christopher P. Nelson (170,171), Harry Campbell (159), Susanne Jäger (181,182), Toru Nabika (234), Fahd Al-Mulla (183), Harri Niinikoski (235,236), Peter S. Braund (170,171), Ivana Kolcic (237), Peter Kovacs (238), Tota Giardoglou (184), Tomohiro Katsuya (239,240), Dominique de Kleijn (241), Gert J. de Borst (241), Eung Kweon Kim (242), Hieab H.H. Adams (133,243), M. Arfan Ikram (133), Xiaofeng Zhu (224), Folkert W. Asselbergs (223), Adriaan O. Kraaijeveld (223), Joline W.J. Beulens (122,244), Xiao-Ou Shu (165), Loukianos S. Rallidis (245), Oluf Pedersen (86), Torben Hansen (86), Paul Mitchell (246), Alex W. Hewitt (247,248), Mika Kähönen (249,250), Louis Pérusse (215,251), Claude Bouchard (252), Anke Tönjes (238), Yii-Der Ida Chen (81), Craig E. Pennell (209), Trevor A. Mori (253), Wolfgang Lieb (254), Andre Franke (255), Claes Ohlsson (204,256), Dan Mellström (204,257), Yoon Shin Cho (203), Hyejin Lee (258), Jian-Min Yuan (109,259), Woon-Puay Koh (260,261), Sang Youl Rhee (262), Jeong-Taek Woo (262), Iris M. Heid (11), Klaus J. Stark (11), Martina E. Zimmermann (11), Henry Völzke (263), Georg Homuth (198), Michele K. Evans (230), Alan B. Zonderman (230), Ozren Polasek (237,264), Gerard Pasterkamp (195), Imo E. Hoefer (195), Susan Redline (193,194), Katja Pahkala (191,192,265), Albertine J. Oldehinkel (266), Harold Snieder (190), Ginevra Biino (267), Reinhold Schmidt (186), Helena Schmidt (268), Stefania Bandinelli (269), George Dedoussis (184), Thangavel Alphonse Thanaraj (183), Patricia A. Peyser (56), Norihiro Kato (167), Matthias B. Schulze (181,182,270), Giorgia Girotto (180,271), Carsten A. Böger (179,272,273), Bettina Jung (179,272,273), Peter K. Joshi (159), David A. Bennett (177,178), Philip L. De Jager (10,274), Xiangfeng Lu (101), Vasiliki Mamakou (275,276), Morris Brown (15,85), Mark J. Caulfield (4,85), Patricia B. Munroe (4,85), Xiuqing Guo (81), Marina Ciullo (174,175), Jost B. Jonas (172,277,278,279), Nilesh J. Samani (170,171), Jaakko Kaprio (36), Päivi Pajukanta (280), Teresa Tusié-Luna (281,282), Carlos A. Aguilar-Salinas (283,311), Linda S. Adair (284,285), Sonny Augustin Bechayda (286,287), H. Janaka de Silva (288), Ananda R. Wickremasinghe (289), Ronald M. Krauss (290), Jer-Yuarn Wu (291), Wei Zheng (165), Anneke I. den Hollander (164), Dwaipayan Bharadwaj (153,292), Adolfo Correa (293), James G. Wilson (294), Lars Lind (295), Chew-Kiat Heng (296), Amanda E. Nelson (160,297), Yvonne M. Golightly (58,160,298,299), James F. Wilson (137,159), Brenda Penninx (300,301), Hyung-Lae Kim (302), John Attia (154,209), Rodney J. Scott (154,209), D.C. Rao (176), Donna K. Arnett (303), Mark Walker (304), Laura J. Scott (13), Heikki A. Koistinen (37,305,306), Giriraj R. Chandak (152,153,307), Josep M. Mercader (308,309,310), Clicerio Gonzalez Villalpando (312), Lorena Orozco (313), Myriam Fornage (148,314), E. Shyong Tai (78,315), Rob M. van Dam (78,315), Terho Lehtimäki (216,217), Nish Chaturvedi (316), Mitsuhiro Yokota (317), Jianjun Liu (144), Dermot F. Reilly (318), Amy Jayne McKnight (139), Frank Kee (139), Karl-Heinz Jöckel (138), Mark I. McCarthy (60,208), Colin N.A. Palmer (319), Veronique Vitart (137), Caroline Hayward (137), Eleanor Simonsick (320), Cornelia M. van Duijn (132,133), Zi-Bing Jin (173,321), Fan Lu (321), Haretsugu Hishigaki (129), Xu Lin (128), Winfried März (126,322,323), Vilmundur Gudnason (125,324), Jean-Claude Tardif (124), Guillaume Lettre (124), Leen M. t Hart (122,123,325), Petra J.M. Elders (326), Daniel J. Rader (327,407), Scott M. Damrauer (121,328), Meena Kumari (329), Mika Kivimaki (120), Pim van der Harst (118), Tim D. Spector (116), Ruth J.F. Loos (86,115,330), Michael A. Province (108), Esteban J. Parra (113), Miguel Cruz (331), Bruce M. Psaty (112,226,332), Ivan Brandslund (111,333), Peter P. Pramstaller (110), Charles N. Rotimi (334), Kaare Christensen (335), Samuli Ripatti (36,336,337), Elisabeth Widén (36), Hakon Hakonarson (338,339), Struan F.A. Grant (327,339,340), Lambertus Kiemeney (106), Jacqueline de Graaf (106), Markus Loeffler (104,105), Florian Kronenberg (103), Dongfeng Gu (101,341), Jeanette Erdmann (98), Heribert Schunkert (99,100), Paul W. Franks (102), Allan Linneberg (79,80), J. Wouter Jukema (96,342), Amit V. Khera (10,343,345,346), Minna Männikkö (346), Marjo-Riitta Jarvelin (62,347,348), Zoltan Kutalik (93,94), Cucca Francesco (349,350), Dennis O. Mook-Kanamori (351,352), Ko Willems van Dijk (353,354,355), Hugh Watkins (87,88), David P. Strachan (356), Niels Grarup (86), Peter Sever (357), Neil Poulter (358), Wayne Huey-Herng Sheu (359,360), Jerome I. Rotter (81), Thomas M. Dantoft (79), Fredrik Karpe (361,362), Matt J. Neville (361,362), Nicholas J. Timpson (33,77), Ching-Yu Cheng (363,364), Tien-Yin Wong (363,364), Chiea Chuen Khor (144), Hengtong Li (365), Charumathi Sabanayagam (363,364), Annette Peters (75,100,366), Christian Gieger (74,75,366), Andrew T. Hattersley (367), Nancy L. Pedersen (368), Patrik K.E. Magnusson (368), Dorret I. Boomsma (70,301), Eco J.C. de Geus (70,301), L. Adrienne Cupples (5,369), Joyce B.J. van Meurs (69,133), Arfan Ikram (133), Mohsen Ghanbari (133,370), Penny Gordon-Larsen (284,285), Wei Huang (371), Young Jin Kim (23), Yasuharu Tabara (68), Nicholas J. Wareham (66), Claudia Langenberg (66), Eleftheria Zeggini (45,207,372), Jaakko Tuomilehto (37,336,373), Johanna Kuusisto (374), Markku Laakso (374), Erik Ingelsson (7,65,375,376), Goncalo Abecasis (13,377), John C. Chambers (62,63,64,378), Jaspal S. Kooner (63,64,357,379), Paul S. de Vries (61), Alanna C. Morrison (61), Scott Hazelhurst (59,380), Michèle Ramsay (59), Kari E. North (58), Martha Daviglus (381), Peter Kraft (57,382), Nicholas G. Martin (383), John B. Whitfield (383), Shahid Abbas (53), Danish Saleheen (53,384,385), Robin G. Walters (51,52,386), Michael V. Holmes (51,52,362), Corri Black (387), Blair H. Smith (319), Aris Baras (377), Anne E. Justice (388), Julie E. Buring (48,310), Paul M. Ridker (48,310), Daniel I. Chasman (48,310), Charles Kooperberg (47), Gen Tamiya (44), Masayuki Yamamoto (44), David A. van Heel (46), Richard C. Trembath (389), Wei-Qi Wei (390), Gail P. Jarvik (391), Bahram Namjou (392), M. Geoffrey Hayes (39,393,394), Marylyn D. Ritchie (38), Pekka Jousilahti (37), Veikko Salomaa (37), Kristian Hveem (32,395,396), Bjørn Olav Åsvold (32,395,397), Michiaki Kubo (398), Yoichiro Kamatani (24,399), Yukinori Okada (24,26,400,401), Yoshinori Murakami (402), Bong-Jo Kim (403), Unnur Thorsteinsdottir (20,324), Kari Stefansson (20,324), Jifeng Zhang (3), Y. Eugene Chen (3), Yuk-Lam Ho (404), Julie A. Lynch (405,406), Philip S. Tsao (6,7,408), Kyong-Mi Chang (328,407), Kelly Cho (404,409), Christopher J. O'Donnell (404,409), John M. Gaziano (404,409), Peter Wilson (17,410), Karen L. Mohlke (168), Timothy M. Frayling (72), Joel N. Hirschhorn (9,10,411), Sekar Kathiresan (10,344,345), Michael Boehnke (13), Struan Grant (1,340), Pradeep Natarajan (10,343,412,413), Yan V. Sun (16,17), Andrew P. Morris (414), Panos Deloukas (4,415), Gina Peloso (5), Themistocles L. Assimes (6,7,408), Cristen J. Willer (3,14,416), Xiang Zhu [xiangzhu@psu.edu] (6,417,418,419,*), Christopher D. Brown [chrbro@upenn.edu] (1,**)

MATURITY onset diabetes of the young, GRANULE cells, INSULIN, STEM cells, and INTRACELLULAR calcium

Mutations in HNF1A cause Maturity Onset Diabetes of the Young (HNF1A-MODY). To understand mechanisms of β-cell dysfunction, we generated stem cell-derived pancreatic endocrine cells with hypomorphic mutations in HNF1A. HNF1A-deficient β-cells display impaired basal and glucose stimulated-insulin secretion, reduced intracellular calcium levels in association with a reduction in CACNA1A expression, and accumulation of abnormal insulin granules in association with SYT13 down-regulation. Knockout of CACNA1A and SYT13 reproduce the relevant phenotypes. In HNF1A deficient β-cells, glibenclamide, a sulfonylurea drug used in the treatment of HNF1A-MODY patients, increases intracellular calcium, and restores insulin secretion. While insulin secretion defects are constitutive in β-cells null for HNF1A, β-cells heterozygous for hypomorphic HNF1A (R200Q) mutations lose the ability to secrete insulin gradually; this phenotype is prevented by correction of the mutation. Our studies illuminate the molecular basis for the efficacy of treatment of HNF1A-MODY with sulfonylureas, and suggest promise for the use of cell therapies. hPSCs model of Maturity Onset Diabetes of the Young caused by mutations in the transcription factor HNF1A (HNF1A-MODY), regulates the expression of genes required for the formation of dense-core insulin granules and calcium-dependent insulin secretion, demonstrating a basis to treat HNF1A-MODY patients with sulfonylureas. [ABSTRACT FROM AUTHOR]

COVID-19 vaccines, TRANSPLANTATION of organs, tissues, etc., VACCINES, and IMMUNE response

Fewer than 45% of solid organ transplant recipients (SOTRs) mount a detectable antispike antibody level after two doses of mRNA SARS-CoV-2 vaccination (D2).1 Various vaccination strategies, including mixing platforms, have been proposed, but there is no consensus on the optimal vaccination sequence to improve immunogenicity.2,3 Although using similar technology, the mRNA-1273 vaccine has been associated with higher peak antibody responses than the use of BNT162b2 in immunosuppressed populations, potentially related to a higher vaccine antigen dose.3,4 We therefore studied whether the use of mRNA-1273 versus BNT162b2 as a third primary vaccine dose (D3) might generate a more robust antibody response in SOTR who remained seronegative after two doses of BNT162b2. Improved humoral immunogenicity with mRNA-1273 versus BNT162b2 as third vaccine dose among solid organ transplant recipients seronegative after two BNT162b2 doses METHODS From our national observational study, approved by the Johns Hopkins Institutional Review Board (IRB00248540),4 we included adult SOTRs who tested seronegative after two doses of BNT162b2 and received either a D3-BNT162b2 or D3-mRNA-1273. [Extracted from the article]

MOTHERS, PARENT attitudes, SOCIAL norms, AGE distribution, CROSS-sectional method, INTERNET, FATHERS, SEX distribution, PARENTING, ALCOHOL drinking, DESCRIPTIVE statistics, PARENT-child relationships, and PARENTS

Aims This study aimed to examine perceived social norms, the effect of parental drinking on these norms, alcohol use in front of children, and how norms and consumption vary based on child age and gender of the parent. Methods A cross-sectional online panel survey was undertaken with n  = 1000 Australian adults (including 670 parents) aged 18–59 years. The survey assessed: alcohol consumption in front of children; normative attitudes towards drinking in the presence of children; and perceived social norms. Results Overall, 33.9% of parents reported drinking a glass of alcohol each day or a couple of times a week, 18.2% reported getting slightly drunk and 7.8% indicated getting visibly drunk each day or a couple of times a week with their children present. In total, 37.5% reported drinking in front of their children at least weekly. Fathers were more likely to drink in front of children than mothers. Most parents deemed drinking small amounts of alcohol in front of children as acceptable but did not accept drunkenness. Respondents were less concerned about a father drinking one or two drinks in front of their children than a mother. Social expectations were not related to child age, but norms related to others' perceived behaviour were. Conclusions Many parents, particularly fathers consume alcohol in front of their children. There is a need to target health promotion strategies to adults and parents consuming in excess of health guidelines, and to the many parents who are consuming alcohol at higher levels in front of their children. [ABSTRACT FROM AUTHOR]

BLACK feminism, HISTORY of feminism, FEMINISM, BLACK feminists, WORLD history, CONVERSATION, and RACISM

This roundtable stems from a Zoom event, "New Directions in Feminism and Global Race Studies (a Book Conversation)" with authors Tiffany N. Florvil, Kaiama L. Glover, Annette K. Joseph-Gabriel, Katherine M. Marino, Robin Mitchell, and Jacqueline-Bethel Tchouta Mougoué, hosted by Samantha Pinto. These scholars discussed their recently published books, which expand how we think about transnational feminism and global Black feminisms in the Americas, the Caribbean, Africa, and Europe. The lightly edited transcript of the conversation explores how putting Black women at the center of histories of global feminisms and race studies transforms these fields and the questions that are usually asked. The authors also discussed navigating research challenges and confronting racism in the sources and in the archives. The conversation underscores the importance of intellectual community, as well as the relevance and urgency of Black feminist scholarship today. [ABSTRACT FROM AUTHOR]

COVID-19, SARS-CoV-2, and REMDESIVIR

Profoundly B-cell-depleted patients can have prolonged severe acute respiratory syndrome coronavirus 2 infections with evidence of active viral replication, due to inability to mount an adequate humoral response to clear the virus. We present 3 B-cell-depleted patients with prolonged coronavirus disease 2019 infection who were successfully treated with a combination of casirivimab/imdevimab and remdesivir. [ABSTRACT FROM AUTHOR]

TEACHERS, TEACHING of controversial topics, STUDENTS, DISCUSSION in education, and SOCIAL conditions of students

Controversial topics may be uncomfortable for teachers to include in their in-class discussions. However, there are considerable cognitive and social-emotional benefits to engagement in controversial conversations, or classroom discussion about controversial topics. It is critical that teachers support students in respectful discussion to help them develop skills such as problem solving, critical thinking, and the ability to consider issues from multiple perspectives. These skills can enable students to meet larger educational goals such as engaged citizenship. The goal of this article is to highlight the benefits of controversial conversations in the classroom and describe teaching approaches that facilitate effective controversial conversations. First, we identify important factors for teachers' consideration in supporting effective and beneficial controversial conversations. Second, we provide examples of topics of conversations that may be appropriate for students of varying ages. Third, we review how the structure of conversation, scaffolding, classroom context, relationships, and students' individual differences can shape controversial conversations. [ABSTRACT FROM AUTHOR]

SOFT robotics, LYMPHEDEMA, SLEEVES, AIR pressure, MICROFLUIDICS, VALVES, MICROFLUIDIC devices, and DRAINAGE

A proof of concept of a novel air microfluidics-enabled soft robotic sleeve to enable lymphedema treatment is presented. Compression sleeves represent the current, suboptimal standard of care, and stationary pumps assist with lymph drainage; however, effective systems that are truly wearable while performing daily activities are very scarce. This problematic trade-off between performance and wearability requires a new solution, which is addressed by an innovative microfluidic device. Its novelty lies in the use of light, small, and inexpensive air microfluidic chips (35 × 20 × 5 mm3 in size) that bring three major advantages compared to their traditional counterparts. First, each chip is designed with 16 fluidic channels with a cross-sectional area varying from 0.04 to 1 mm2, providing sequential inflation and uniform deflation capability to eight air bladders, thereby producing intentional gradient compression to the arm to facilitate lymph fluid circulation. The design is derived from the fundamentals of microfluidics, in particular, hydraulic resistance and paths of least resistance. Second, the air microfluidic chip enables miniaturization of at least eight bulky energy-consuming valves to two miniature solenoid valves for control increasing wearability. Third, the air microfluidic chip has no moving parts, which reduces the noise and energy needed. The cost, simplicity, and scale-up potential of developing methods for making the system are also detailed. The sequential inflation, uniform deflation, and pressure gradient are demonstrated, and the resulted compression and internal air bladder pressure were evaluated. This air microfluidics-enabled sleeve presents tremendous potential toward future improvements in self-care lymphedema management. [ABSTRACT FROM AUTHOR]

COMMUNICABLE diseases, INFECTIOUS arthritis, HOSPITAL patients, CELLULITIS, DRUG abuse, DRUGS, and FISHER exact test

Injection drug use poses a public health challenge. Clinical experience indicates that people who inject drugs (PWID) are hospitalized frequently for infectious diseases, but little is known about outcomes when admitted. Charts were identified from local hospitals between 2013–2018 using consultation lists and hospital record searches. Included individuals injected drugs in the past six months and presented with infection. Charts were accessed using the hospital information system, undergoing primary and secondary reviews using Research Electronic Data Capture (REDCap). The Wilcoxon rank-sum test was used for comparisons between outcome categories. Categorical data were summarized as count and frequency, and compared using Fisher's exact test. Of 240 individuals, 33% were admitted to the intensive care unit, 36% underwent surgery, 12% left against medical advice (AMA), and 9% died. Infectious diagnoses included bacteremia (31%), abscess (29%), endocarditis (29%), cellulitis (20%), sepsis (10%), osteomyelitis (9%), septic arthritis (8%), pneumonia (7%), discitis (2%), meningitis/encephalitis (2%), or other (7%). Sixty-six percent had stable housing and 60% had a family physician. Fifty-four percent of patient-initiated discharges were seen in the emergency department within 30 days and 29% were readmitted. PWID are at risk for infections. Understanding their healthcare trajectory is essential to improve their care. [ABSTRACT FROM AUTHOR]

COVID-19, SEDENTARY behavior, PHYSICAL activity, HOSPITAL care, and PATIENTS' attitudes

Many patients with COVID-19 experience severe and even fatal disease. Survivors may have long-term health consequences, but data on physical activity and sedentary behaviour are scarce. Therefore, we objectively assessed physical activity (PA) patterns among post-hospitalised patients with COVID-19 and explored associations with patient characteristics, disease severity and cardiac dysfunction. We objectively assessed PA, sedentary behaviour and sleep duration for 24 h/day during 8 days at 3-6 months after COVID-19 hospitalisation. PA and sedentary time were compared across pre-defined subgroups based on patient and disease characteristics, cardiac biomarker release during hospitalisation, abnormal transthoracic echocardiogram at 3-6 months post-hospitalisation and persistence of symptoms post-discharge. PA and sedentary behaviour were assessed in 37 patients (60 ± 10 years old; 78% male). Patients spent 4.2 [3.2; 5.3] h/day light-intensity PA and 1.0 [0.8; 1.4] h/day moderate-to-vigorous intensity PA. Time spent sitting was 9.8 [8.7; 11.2] h/day, which was accumulated in 6 [5; 7] prolonged sitting bouts (≥30 min) and 41 [32; 48] short sitting bouts (<30 min). No differences in PA and sedentary behaviour were found across subgroups, but sleep duration was higher in patients with versus without persistent symptoms (9.1 vs. 8.3 h/day, p = 0.02). Taken together, high levels of sedentary time are common at 3–6 months after COVID-19 hospitalisation, whilst PA and sedentary behaviour are not impacted by patient or disease characteristics. [ABSTRACT FROM AUTHOR]

DISABILITY awareness, PEOPLE with disabilities, CRITICAL thinking, RESEARCH personnel, and STRATEGIC planning

Objective: The main objectives were to 1) search and map current disability awareness and training activities in Quebec, Canada, 2) collectively reflect on these practices, and 3) develop a five-year strategic plan.Methods: We used an integrated knowledge translation approach whereby researchers and community partners were involved in all stages. This project consisted of two sequential phases: 1) an environmental scan (web review and interview) of current practices, and 2) a reflection process with an external expert-facilitator in social transformation. Outcome results and process data are reported.Results: We identified 129 activities (71 training, 58 awareness) from 39 organizations (from 123 organizations initially invited). A wide range of characteristics were collected for each activity which allowed for the identification of gaps. The working group met seven times in one year to discuss results from phase 1 and co-create a five-year strategic plan. Main priorities are 1) the development of a methodology for measuring collective impact and 2) content synchronization of activities.Conclusion: Involvement of partners and researchers enabled a concerted and efficient approach to the development of a five-year strategic plan.Practice Implications: A transition committee led by partners will ensure implementation and sustainability of the plan across the province. [ABSTRACT FROM AUTHOR]

ANTIBODY formation, VACCINE effectiveness, HEART transplant recipients, SARS-CoV-2, and MESSENGER RNA

While several studies have observed that solid organ transplant recipients experience diminished antibody responses to SARS-CoV-2 mRNA vaccination, data specific to heart and lung transplant (HT/LT) recipients remains sparse. US adult HT and LT recipients completed their vaccine series between January 7 and April 10, 2021. Reactogencity and SARS-CoV-2 anti-spike antibody were assessed after a priming dose (D1) and booster dose (D2). Modified Poisson regression with robust variance estimator was used to evaluate associations between participant characteristics and antibody development. Of 134 heart recipients, there were 38% non-responders (D1-/D2-), 48% booster responders (D1-/D2+), and 14% priming dose responders (D1+/D2+). Of 103 lung recipients, 64% were non-responders, 27% were booster responders, and 9% were priming dose responders. Lung recipients were less likely to develop antibodies (p <.001). Priming dose antibody response was associated with younger recipient age (p =.04), transplant-to-vaccination time ≥6 years (p <.01), and lack of anti-metabolite maintenance immunosuppression (p <.001). Pain at injection site was the most commonly reported reaction (85% after D1, 76% after D2). Serious reactions were rare, the most common being fatigue (2% after D1 and 3% after D2). No serious adverse events were reported. HT and LT recipients experienced diminished antibody response following vaccination; reactogenicity was comparable to that of the general population. LT recipients may exhibit a more impaired antibody response than HT recipients. While current recommendations are to vaccinate eligible candidates and recipients, further studies characterizing the cell-mediated immune response and clinical efficacy of these vaccines in this population are needed. [ABSTRACT FROM AUTHOR]

PROFESSIONAL education, IDENTITY (Psychology), PROFESSIONAL identity, INTERPERSONAL conflict, CONFLICT management, and CURRICULUM

This article describes the development and assessment of teaching strategies to enhance student professional identity development by shifting the pedagogical focus from content knowledge to the practice of interpersonal and conflict resolution skills, and reflection to create awareness, observe growth, and find meaning. [ABSTRACT FROM AUTHOR]

GENDER mainstreaming and REHABILITATION

Marketers, filmmakers, and cinema-goers assume that genre has a large effect on how the audience responds to and engages with a film. However, trait measures such as transportability suggest that, in some cases, individual differences may shape audience engagement more than genre does. To investigate this disparity, we compared viewers' enjoyment, identification with characters, and story world absorption (including three subscales: Transportation, Attention, and Emotional Engagement) for film clips from two very different genres (an emotional family film vs. an action chase scene) in a within-subjects design. Across two studies--an exploratory study and a preregistered replication--we found that participants' feelings of being transported into the narrative (a dimension of story world absorption) were more highly correlated across films than other measures were and tended to be less related to genre preference than the other audience response measures were. This pattern of results suggests that feelings of transportation may be more dependent on individual differences, and less sensitive to genre, than other forms of audience response. An exploratory analysis of a short scale measuring trait transportability suggested this measure was not the basis of the individual differences theorized to underlie transportation. Our results further highlight the importance of examining viewer engagement with narrative as a multidimensional, rather than unitary, concept. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic, MEDICAL personnel, PEOPLE with epilepsy, SOCIAL distancing, and CAREGIVER attitudes

• The COVID-19 and Epilepsy (COV-E) global surveys were launched in Brazil during the first wave of the pandemic. • People with epilepsy reported worsening seizure control, psychosocial stress, and impaired mental health. • There were difficulties in obtaining drug supplies because of canceled appointments. • Discussion of risk, including SUDEP, was infrequent even before the pandemic. • The surveys remain open to enable new participants to enter data providing insights as the pandemic evolves. The COVID-19 pandemic has had an unprecedented impact on people and healthcare services. The disruption to chronic illnesses, such as epilepsy, may relate to several factors ranging from direct infection to secondary effects from healthcare reorganization and social distancing measures. As part of the COVID-19 and Epilepsy (COV-E) global study, we ascertained the effects of COVID-19 on people with epilepsy in Brazil, based on their perspectives and those of their caregivers. We also evaluated the impact of COVID-19 on the care delivered to people with epilepsy by healthcare workers. We designed separate online surveys for people with epilepsy and their caregivers. A further survey for healthcare workers contained additional assessments of changes to working patterns, productivity, and concerns for those with epilepsy under their care. The Brazilian arm of COV-E initially collected data from May to November 2020 during the country's first wave. We also examined national data to identify the Brazilian states with the highest COVID-19 incidence and related mortality. Lastly, we applied this geographic grouping to our data to explore whether local disease burden played a direct role in difficulties faced by people with epilepsy. Two hundred and forty-one people returned the survey, 20% were individuals with epilepsy (n = 48); 22% were caregivers (n = 53), and 58% were healthcare workers (n = 140). Just under half (43%) of people with epilepsy reported health changes during the pandemic, including worsening seizure control, with specific issues related to stress and impaired mental health. Of respondents prescribed antiseizure medication, 11% reported difficulty taking medication on time due to problems acquiring prescriptions and delayed or canceled medical appointments. Only a small proportion of respondents reported discussing significant epilepsy-related risks in the previous 12 months. Analysis of national COVID-19 data showed a higher disease burden in the states of Sao Paulo and Rio de Janeiro compared to Brazil as a whole. There were, however, no geographic differences observed in survey responses despite variability in the incidence of COVID-19. Our findings suggest that Brazilians with epilepsy have been adversely affected by COVID-19 by factors beyond infection or mortality. Mental health issues and the importance of optimal communication are critical during these difficult times. Healthcare services need to find nuanced approaches and learn from shared international experiences to provide optimal care for people with epilepsy as the direct burden of COVID-19 improves in some countries. In contrast, others face resurgent waves of the pandemic. [ABSTRACT FROM AUTHOR]

GENETIC variation, REWARD (Psychology), and BRAIN imaging