78 research outputs found

    Prescribed opioid use is associated with adverse cardiovascular outcomes in community-dwelling older persons

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    Aims: Prescribed opioids are commonly used in the older community-dwelling population for the treatment of chronic pain. Although the harmful effects of opioid abuse and overdose are well understood, little is known about the long-term cardiovascular (CV) effects of prescribed opioids. The aim of this study was to investigate the CV effects associated with prescribed opioid use. Methods and results: A post hoc analysis of participants in the Aspirin in Reducing Events in the Elderly (ASPREE) trial was conducted. Participants in the ASPREE trial included community-dwelling older adults without a prior history of CV disease (CVD). Prescribed opioid use was defined as opioid use at baseline and/or at the first annual visit (AV1). Cox proportional hazards regression was used to calculate hazard ratios and 95% confidence intervals (95% CI) for associations between opioid use and CVD events following AV1. Of the 17 701 participants included (mean age 75.2 years, 58.2% female), 813 took opioids either at baseline or at AV1. Over a median follow-up period of 3.58 years (IQR 2.50–4.62), CVD events, most notably heart failure hospitalization, occurred in 7% (n = 57) amongst opioid users and 4% (n = 680) amongst non-opioid users. After adjustment for multiple covariates, opiate use was associated with a 1.67-fold (CI 1.26–2.23, P < 0.001) increase in the hazard ratio for CVD events. Conclusions: These findings identify opioid use as a non-traditional risk factor for CVD events in community-dwelling older adults

    Pyruvate kinase M2 activation may protect against the progression of diabetic glomerular pathology and mitochondrial dysfunction

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    Diabetic nephropathy (DN) is a major cause of end-stage renal disease, and therapeutic options for preventing its progression are limited. To identify novel therapeutic strategies, we studied protective factors for DN using proteomics on glomeruli from individuals with extreme duration of diabetes (≥ 50 years) without DN and those with histologic signs of DN. Enzymes in the glycolytic, sorbitol, methylglyoxal and mitochondrial pathways were elevated in individuals without DN. In particular, pyruvate kinase M2 (PKM2) expression and activity were upregulated. Mechanistically, we showed that hyperglycemia and diabetes decreased PKM2 tetramer formation and activity by sulfenylation in mouse glomeruli and cultured podocytes. Pkm-knockdown immortalized mouse podocytes had higher levels of toxic glucose metabolites, mitochondrial dysfunction and apoptosis. Podocyte-specific Pkm2-knockout (KO) mice with diabetes developed worse albuminuria and glomerular pathology. Conversely, we found that pharmacological activation of PKM2 by a small-molecule PKM2 activator, TEPP-46, reversed hyperglycemia-induced elevation in toxic glucose metabolites and mitochondrial dysfunction, partially by increasing glycolytic flux and PGC-1α mRNA in cultured podocytes. In intervention studies using DBA2/J and Nos3 (eNos) KO mouse models of diabetes, TEPP-46 treatment reversed metabolic abnormalities, mitochondrial dysfunction and kidney pathology. Thus, PKM2 activation may protect against DN by increasing glucose metabolic flux, inhibiting the production of toxic glucose metabolites and inducing mitochondrial biogenesis to restore mitochondrial function

    Inflammatory profiles across the spectrum of disease reveal a distinct role for GM-CSF in severe COVID-19

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    While it is now widely accepted that host inflammatory responses contribute to lung injury, the pathways that drive severity and distinguish coronavirus disease 2019 (COVID-19) from other viral lung diseases remain poorly characterized. We analyzed plasma samples from 471 hospitalized patients recruited through the prospective multicenter ISARIC4C study and 39 outpatients with mild disease, enabling extensive characterization of responses across a full spectrum of COVID-19 severity. Progressive elevation of levels of numerous inflammatory cytokines and chemokines (including IL-6, CXCL10, and GM-CSF) were associated with severity and accompanied by elevated markers of endothelial injury and thrombosis. Principal component and network analyses demonstrated central roles for IL-6 and GM-CSF in COVID-19 pathogenesis. Comparing these profiles to archived samples from patients with fatal influenza, IL-6 was equally elevated in both conditions whereas GM-CSF was prominent only in COVID-19. These findings further identify the key inflammatory, thrombotic, and vascular factors that characterize and distinguish severe and fatal COVID-19

    Central coordination as an alternative for local coordination in a multicenter randomized controlled trial: the FAITH trial experience

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    Contains fulltext : 110505.pdf (publisher's version ) (Open Access)BACKGROUND: Surgeons in the Netherlands, Canada and the US participate in the FAITH trial (Fixation using Alternative Implants for the Treatment of Hip fractures). Dutch sites are managed and visited by a financed central trial coordinator, whereas most Canadian and US sites have local study coordinators and receive per patient payment. This study was aimed to assess how these different trial management strategies affected trial performance. METHODS: Details related to obtaining ethics approval, time to trial start-up, inclusion, and percentage completed follow-ups were collected for each trial site and compared. Pre-trial screening data were compared with actual inclusion rates. RESULTS: Median trial start-up ranged from 41 days (P25-P75 10-139) in the Netherlands to 232 days (P25-P75 98-423) in Canada (p = 0.027). The inclusion rate was highest in the Netherlands; median 1.03 patients (P25-P75 0.43-2.21) per site per month, representing 34.4% of the total eligible population. It was lowest in Canada; 0.14 inclusions (P25-P75 0.00-0.28), representing 3.9% of eligible patients (p < 0.001). The percentage completed follow-ups was 83% for Canadian and Dutch sites and 70% for US sites (p = 0.217). CONCLUSIONS: In this trial, a central financed trial coordinator to manage all trial related tasks in participating sites resulted in better trial progression and a similar follow-up. It is therefore a suitable alternative for appointing these tasks to local research assistants. The central coordinator approach can enable smaller regional hospitals to participate in multicenter randomized controlled trials. Circumstances such as available budget, sample size, and geographical area should however be taken into account when choosing a management strategy. TRIAL REGISTRATION: ClinicalTrials.gov: NCT00761813

    SARS-CoV-2 breakthrough infections among vaccinated individuals with rheumatic disease : Results from the COVID-19 Global Rheumatology Alliance provider registry

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    Funding Information: members of the COVID-19 Global Rheumatology Alliance and do not necessarily represent the views of the American College of Rheumatology (ACR), EULAR, the UK National Health Service (NHS), the National Institute for Health Research (NIHR), the UK Department of Health or any other organisation. Competing interests KLH reports she has received non-personal speaker’s fees from AbbVie and grant income from BMS, UCB and Pfizer, all unrelated to this manuscript; KLH is supported by the NIHR Manchester Biomedical Research Centre. LG reports personal consultant fees from AbbVie, Amgen, BMS, Biogen, Celgene, Gilead, Janssen, Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi-Aventis and UCB, and grants from Amgen, Lilly, Janssen, Pfizer, Sandoz, Sanofi and Galapagos, all unrelated to this manuscript. AS reports research grants from a consortium of 14 companies (among them AbbVie, BMS, Celltrion, Fresenius Funding Information: Kabi, Gilead/Galapagos, Lilly, Mylan/Viatris, Hexal, MSD, Pfizer, Roche, Samsung, Sanofi-Aventis and UCB) supporting the German RABBIT register and personal fees from lectures for AbbVie, MSD, Roche, BMS, Lilly and Pfizer, all unrelated to this manuscript. LC has not received fees or personal grants from any laboratory, but her institute works by contract for laboratories among other institutions, such as AbbVie Spain, Eisai, Gebro Pharma, Merck Sharp & Dohme España, Novartis Farmaceutica, Pfizer, Roche Farma, Sanofi-Aventis, Astellas Pharma, Actelion Pharmaceuticals España, Grünenthal and UCB Pharma. EF-M reports personal consultant fees from Boehringer Ingelheim Portugal and that LPCDR received support for specific activities: grants from AbbVie, Novartis, Janssen-Cilag, Lilly Portugal, Sanofi, Grünenthal, MSD, Celgene, Medac, Pharmakern and GAfPA; grants and non-financial support from Pfizer; and non-financial support from Grünenthal, outside the submitted work. IB reports personal consultant fees from AbbVie, Novartis, Pfizer and Janssen, all unrelated to this manuscript. JZ reports speaker fees from AbbVie, Novartis and Janssen/Johnson & Johnson, all unrelated to this manuscript. GR-C reports personal consultant fees from Eli Lilly and Novartis, all unrelated to this manuscript. JS is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant numbers: R01 AR077607, P30 AR070253 and P30 AR072577), and the R Bruce and Joan M Mickey Research Scholar Fund. JS has received research support from Amgen and Bristol Myers Squibb and performed consultancy for Bristol Myers Squibb, Gilead, Inova, Janssen and Optum, unrelated to this work. LW receives speaker’s bureau fees from Aurinia Pharma, unrelated to this manuscript. SB reports no competing interests related to this work. He reports non-branded consulting fees for AbbVie, Horizon and Novartis (all <10000).MGMhasnocompetinginterestsrelatedtothiswork.SheservesasapatientconsultantforBMS,BIJNJandAurinia(all<10 000). MGM has no competing interests related to this work. She serves as a patient consultant for BMS, BI JNJ and Aurinia (all <10 000). RG reports no competing interests related to this work. Outside of this work she reports personal and/or speaking fees from AbbVie, Janssen, Novartis, Pfizer and Cornerstones and travel assistance from Pfizer (all <10000).JHreportsnocompetinginterestsrelatedtothiswork.HeissupportedbygrantsfromtheRheumatologyResearchFoundationandhassalarysupportfromtheChildhoodArthritisandRheumatologyResearchAlliance.HehasperformedconsultingforNovartis,SobiandBiogen,allunrelatedtothiswork(<10 000). JH reports no competing interests related to this work. He is supported by grants from the Rheumatology Research Foundation and has salary support from the Childhood Arthritis and Rheumatology Research Alliance. He has performed consulting for Novartis, Sobi and Biogen, all unrelated to this work (<10 000). ESi reports non-financial support from Canadian Arthritis Patient Alliance, outside the submitted work. PS reports personal fees from the American College of Rheumatology/Wiley Publishing, outside the submitted work. ZW reports grant support from Bristol Myers Squibb and Principia/Sanofi and performed consultancy for Viela Bio and MedPace, outside the submitted work. His work is supported by grants from the National Institutes of Health. PMM has received consulting/speaker’s fees from AbbVie, BMS, Celgene, Eli Lilly, Galapagos, Janssen, MSD, Novartis, Orphazyme, Pfizer, Roche and UCB, all unrelated to this study. PMM is supported by the National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre (BRC). PCR reports no competing interests related to this work. Outside of this work PCR reports personal fees from AbbVie, Atom Bioscience, Eli Lilly, Gilead, GlaxoSmithKline, Janssen, Kukdong, Novartis, UCB, Roche and Pfizer; meeting attendance support from BMS, Pfizer and UCB; and grant funding from Janssen, Novartis, Pfizer and UCB Pharma (all <$10 000). JY reports no competing interests related to this work. Her work is supported by grants from the National Institutes of Health (K24 AR074534 and P30 AR070155). Outside of this work, she has received research grants or performed consulting for Gilead, BMS Foundation, Pfizer, Aurinia and AstraZeneca. Funding Information: Twitter Jean Liew @rheum_cat, Loreto Carmona @carmona_loreto, Pedro M Machado @pedrommcmachado and Philip C Robinson @philipcrobinson Contributors All authors contributed to the study design, data collection, interpretation of results and review/approval of the final submitted manuscript. JL and MG are guarantors for this manuscript. Funding MG reports grants from the National Institutes of Health, NIAMS, outside the submitted work. KLH is supported by the NIHR Manchester Biomedical Research Centre. JS is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant numbers: R01 AR077607, P30 AR070253 and P30 AR072577), and the R Bruce and Joan M Mickey Research Scholar Fund. JH is supported by grants from the Rheumatology Research Foundation. ZW is supported by grants from the National Institutes of Health. PMM is supported by the National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre (BRC). JY is supported by grants from the National Institutes of Health (K24 AR074534 and P30 AR070155). Publisher Copyright: ©Objective. While COVID-19 vaccination prevents severe infections, poor immunogenicity in immunocompromised people threatens vaccine effectiveness. We analysed the clinical characteristics of patients with rheumatic disease who developed breakthrough COVID-19 after vaccination against SARS-CoV-2.  Methods. We included people partially or fully vaccinated against SARS-CoV-2 who developed COVID-19 between 5 January and 30 September 2021 and were reported to the Global Rheumatology Alliance registry. Breakthrough infections were defined as occurring ≥14 days after completion of the vaccination series, specifically 14 days after the second dose in a two-dose series or 14 days after a single-dose vaccine. We analysed patients' demographic and clinical characteristics and COVID-19 symptoms and outcomes. Results SARS-CoV-2 infection was reported in 197 partially or fully vaccinated people with rheumatic disease (mean age 54 years, 77% female, 56% white). The majority (n=140/197, 71%) received messenger RNA vaccines. Among the fully vaccinated (n=87), infection occurred a mean of 112 (±60) days after the second vaccine dose. Among those fully vaccinated and hospitalised (n=22, age range 36-83 years), nine had used B cell-depleting therapy (BCDT), with six as monotherapy, at the time of vaccination. Three were on mycophenolate. The majority (n=14/22, 64%) were not taking systemic glucocorticoids. Eight patients had pre-existing lung disease and five patients died. Conclusion. More than half of fully vaccinated individuals with breakthrough infections requiring hospitalisation were on BCDT or mycophenolate. Further risk mitigation strategies are likely needed to protect this selected high-risk population.publishersversionPeer reviewe

    Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

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    BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

    Results From the Global Rheumatology Alliance Registry

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    Funding Information: We acknowledge financial support from the ACR and EULAR. The ACR and EULAR were not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Publisher Copyright: © 2022 The Authors. ACR Open Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.Objective: Some patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID-19 ARDS in this population and to create a simple risk score calculator for use in clinical settings. Methods: Data were derived from the COVID-19 Global Rheumatology Alliance Registry from March 24, 2020, to May 12, 2021. Seven machine learning classifiers were trained on ARDS outcomes using 83 variables obtained at COVID-19 diagnosis. Predictive performance was assessed in a US test set and was validated in patients from four countries with independent registries using area under the curve (AUC), accuracy, sensitivity, and specificity. A simple risk score calculator was developed using a regression model incorporating the most influential predictors from the best performing classifier. Results: The study included 8633 patients from 74 countries, of whom 523 (6%) had ARDS. Gradient boosting had the highest mean AUC (0.78; 95% confidence interval [CI]: 0.67-0.88) and was considered the top performing classifier. Ten predictors were identified as key risk factors and were included in a regression model. The regression model that predicted ARDS with 71% (95% CI: 61%-83%) sensitivity in the test set, and with sensitivities ranging from 61% to 80% in countries with independent registries, was used to develop the risk score calculator. Conclusion: We were able to predict ARDS with good sensitivity using information readily available at COVID-19 diagnosis. The proposed risk score calculator has the potential to guide risk stratification for treatments, such as monoclonal antibodies, that have potential to reduce COVID-19 disease progression.publishersversionepub_ahead_of_prin

    Associations of baseline use of biologic or targeted synthetic DMARDs with COVID-19 severity in rheumatoid arthritis : Results from the COVID-19 Global Rheumatology Alliance physician registry

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    Funding Information: Competing interests JAS is supported by the National Institute of Arthritis and Funding Information: Musculoskeletal and Skin Diseases (grant numbers K23 AR069688, R03 AR075886, L30 AR066953, P30 AR070253 and P30 AR072577), the Rheumatology Research Foundation (K Supplement Award and R Bridge Award), the Brigham Research Institute, and the R Bruce and Joan M Mickey Research Scholar Fund. JAS has received research support from Amgen and Bristol-Myers Squibb and performed consultancy for Bristol-Myers Squibb, Gilead, Inova, Janssen and Optum, unrelated to this work. ZSW reports grant support from Bristol-Myers Squibb and Principia/ Sanofi and performed consultancy for Viela Bio and MedPace, outside the submitted work. His work is supported by grants from the National Institutes of Health. MG is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant numbers K01 AR070585 and K24 AR074534; JY). KLH reports she has received speaker’s fees from AbbVie and grant income from BMS, UCB and Pfizer, all unrelated to this study. KLH is also supported by the NIHR Manchester Biomedical Research Centre. LC has not received fees or personal grants from any laboratory, but her institute works by contract for laboratories such as, among other institutions, AbbVie Spain, Eisai, Gebro Pharma, Merck Sharp & Dohme España, Novartis Farmaceutica, Pfizer, Roche Farma, Sanofi Aventis, Astellas Pharma, Actelion Pharmaceuticals España, Grünenthal and UCB Pharma. LG reports research grants from Amgen, Galapagos, Janssen, Lilly, Pfizer, Sandoz and Sanofi; consulting fees from AbbVie, Amgen, BMS, Biogen, Celgene, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi Aventis and UCB, all unrelated to this study. EFM reports that LPCDR received support for specific activities: grants from AbbVie, Novartis, Janssen-Cilag, Lilly Portugal, Sanofi, Grünenthal, MSD, Celgene, Medac, Pharma Kern and GAfPA; grants and non-financial support from Pfizer; and non-financial support from Grünenthal, outside the submitted work. AS reports grants from a consortium of 13 companies (among them AbbVie, BMS, Celltrion, Fresenius Kabi, Lilly, Mylan, Hexal, MSD, Pfizer, Roche, Samsung, Sanofi Aventis and UCB) supporting the German RABBIT register, and personal fees from lectures for AbbVie, MSD, Roche, BMS and Pfizer, outside the submitted work. AD-G has no disclosures relevant to this study. His work is supported by grants from the Centers for Disease Control and Prevention and the Rheumatology Research Foundation. KMD is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (T32-AR-007258) and the Rheumatology Research Foundation. NJP is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (T32-AR-007258). PD has received research support from Bristol-Myers Squibb, Chugai and Pfizer, and performed consultancy for Boehringer Ingelheim, Bristol-Myers Squibb, Lilly, Sanofi, Pfizer, Chugai, Roche and Janssen, unrelated to this work. NS is supported by the RRF Investigator Award and the American Heart Association. MFU-G reports grant support from Janssen and Pfizer. SB reports no competing interests related to this work. He reports non-branded consulting fees for AbbVie, Horizon, Novartis and Pfizer (all <10000).RGreportsnocompetinginterestsrelatedtothiswork.Outsideofthisworkshereportspersonaland/orspeakingfeesfromAbbVie,Janssen,Novartis,PfizerandCornerstones,andtravelassistancefromPfizer(all<10 000). RG reports no competing interests related to this work. Outside of this work she reports personal and/or speaking fees from AbbVie, Janssen, Novartis, Pfizer and Cornerstones, and travel assistance from Pfizer (all <10 000). JH reports no competing interests related to this work. He is supported by grants from the Rheumatology Research Foundation and the Childhood Arthritis and Rheumatology Research Alliance. He has performed consulting for Novartis, Sobi and Biogen, all unrelated to this work (<10000).JLhasreceivedresearchfundingfromPfizer,outsidethesubmittedwork.ESisaBoardMemberoftheCanadianArthritisPatientAlliance,apatientrun,volunteerbasedorganisationwhoseactivitiesarelargelysupportedbyindependentgrantsfrompharmaceuticalcompanies.PSreportsnocompetinginterestsrelatedtothiswork.HereportshonorariumfordoingsocialmediaforAmericanCollegeofRheumatologyjournals(<10 000). JL has received research funding from Pfizer, outside the submitted work. ES is a Board Member of the Canadian Arthritis Patient Alliance, a patient-run, volunteer-based organisation whose activities are largely supported by independent grants from pharmaceutical companies. PS reports no competing interests related to this work. He reports honorarium for doing social media for American College of Rheumatology journals (<10 000). PMM has received consulting/speaker’s fees from AbbVie, BMS, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche and UCB, all unrelated to this study (all <10000).PMMissupportedbytheNationalInstituteforHealthResearch(NIHR)UniversityCollegeLondonHospitals(UCLH)BiomedicalResearchCentre(BRC).PCRreportsnocompetinginterestsrelatedtothiswork.Outsideofthisworkhereportspersonalconsultingand/orspeakingfeesfromAbbVie,EliLilly,Janssen,Novartis,PfizerandUCB,andtravelassistancefromRoche(all<10 000). PMM is supported by the National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre (BRC). PCR reports no competing interests related to this work. Outside of this work he reports personal consulting and/or speaking fees from AbbVie, Eli Lilly, Janssen, Novartis, Pfizer and UCB, and travel assistance from Roche (all <10 000). JY reports no competing interests related to this work. Her work is supported by grants from the National Institutes of Health, Centers for Disease Control, and the Agency for Healthcare Research and Quality. She has performed consulting for Eli Lilly and AstraZeneca, unrelated to this project. Publisher Copyright: © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.Objective To investigate baseline use of biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drugs (DMARDs) and COVID-19 outcomes in rheumatoid arthritis (RA). Methods We analysed the COVID-19 Global Rheumatology Alliance physician registry (from 24 March 2020 to 12 April 2021). We investigated b/tsDMARD use for RA at the clinical onset of COVID-19 (baseline): abatacept (ABA), rituximab (RTX), Janus kinase inhibitors (JAKi), interleukin 6 inhibitors (IL-6i) or tumour necrosis factor inhibitors (TNFi, reference group). The ordinal COVID-19 severity outcome was (1) no hospitalisation, (2) hospitalisation without oxygen, (3) hospitalisation with oxygen/ventilation or (4) death. We used ordinal logistic regression to estimate the OR (odds of being one level higher on the ordinal outcome) for each drug class compared with TNFi, adjusting for potential baseline confounders. Results Of 2869 people with RA (mean age 56.7 years, 80.8% female) on b/tsDMARD at the onset of COVID-19, there were 237 on ABA, 364 on RTX, 317 on IL-6i, 563 on JAKi and 1388 on TNFi. Overall, 613 (21%) were hospitalised and 157 (5.5%) died. RTX (OR 4.15, 95% CI 3.16 to 5.44) and JAKi (OR 2.06, 95% CI 1.60 to 2.65) were each associated with worse COVID-19 severity compared with TNFi. There were no associations between ABA or IL6i and COVID-19 severity. Conclusions People with RA treated with RTX or JAKi had worse COVID-19 severity than those on TNFi. The strong association of RTX and JAKi use with poor COVID-19 outcomes highlights prioritisation of risk mitigation strategies for these people.publishersversionPeer reviewe

    A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants.

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    This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.3448Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.We thank all participants of all the studies included for enabling this research by their participation in these studies. Computer resources for this project have been provided by the high-performance computing centers of the University of Michigan and the University of Regensburg. Group-specific acknowledgments can be found in the Supplementary Note. The Center for Inherited Diseases Research (CIDR) Program contract number is HHSN268201200008I. This and the main consortium work were predominantly funded by 1X01HG006934-01 to G.R.A. and R01 EY022310 to J.L.H
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