72 research outputs found

    Antigen-specific peripheral shaping of the natural regulatory T cell population

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    Although regulatory T (T reg) cells are thought to develop primarily in the thymus, the peripheral events that shape the protective T reg cell population are unclear. We analyzed the peripheral CD4+ T cell receptor (TCR) repertoire by cellular phenotype and location in mice with a fixed TCRβ chain. We found that T reg (Foxp3+) cells showed a marked skewing of TCR usage by anatomical location in a manner similar to antigen-experienced (CD44hiFoxp3−) but not naive (CD44loFoxp3−) cells, even though CD44hi and T reg cells used mostly dissimilar TCRs. This was likely unrelated to peripheral conversion, which we estimate generates only a small percentage of peripheral T reg cells in adults. Conversion was readily observed, however, during the immune response induced by Foxp3− cells in lymphopenic hosts. Interestingly, the converted Foxp3+ and expanded Foxp3− TCR repertoires were different, suggesting that generation of Foxp3+ cells is not an automatic process upon antigen activation of Foxp3− T cells. Retroviral expression of these TCRs in primary monoclonal T cells confirmed that conversion did not require prior cellular conditioning. Thus, these data demonstrate that TCR specificity plays a crucial role in the process of peripheral conversion and in shaping the peripheral T reg cell population to the local antigenic landscape

    The methodology for developing a prospective meta-analysis in the family planning community

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    <p>Abstract</p> <p>Background</p> <p>Prospective meta-analysis (PMA) is a collaborative research design in which individual sites perform randomized controlled trials (RCTs) and pool the data for meta-analysis. Members of the PMA collaboration agree upon specific research interventions and outcome measures, ideally before initiation but at least prior to any individual trial publishing results. This allows for uniform reporting of primary and secondary outcomes. With this approach, heterogeneity among trials contributing data for the final meta-analysis is minimized while each site maintains the freedom to design a specific trial. This paper describes the process of creating a PMA collaboration to evaluate the impact of misoprostol on ease of intrauterine device (IUD) insertion in nulliparous women.</p> <p>Methods</p> <p>After the principal investigator developed a preliminary PMA protocol, he identified potential collaborating investigators at other sites. One site already had a trial underway and another site was in the planning stages of a trial meeting PMA requirements. Investigators at six sites joined the PMA collaborative. Each site committed to enroll subjects to meet a pre-determined total sample size. A final common research plan and site responsibilities were developed and agreed upon through email and face-to-face meetings. Each site committed to contribute individual patient data to the PMA collaboration, and these data will be analyzed and prepared as a multi-site publication. Individual sites retain the ability to analyze and publish their site's independent findings.</p> <p>Results</p> <p>All six sites have obtained Institutional Review Board approval and each has obtained individual funding to meet the needs of that site's study. Sites have shared resources including study protocols and consents to decrease costs and improve study flow. This PMA protocol is registered with the Cochrane Collaboration and data will be analyzed according to Cochrane standards for meta-analysis.</p> <p>Conclusions</p> <p>PMA is a novel research method that improves meta-analysis by including several study sites, establishing uniform reporting of specific outcomes, and yet allowing some independence on the part of individual sites with respect to the conduct of research. The inclusion of several sites increases statistical power to address important clinical questions. Compared to multi-center trials, PMA methodology encourages collaboration, aids in the development of new investigators, decreases study costs, and decreases time to publication.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00613366">NCT00613366</a>, <a href="http://www.clinicaltrials.gov/ct2/show/NCT00886834">NCT00886834</a>, <a href="http://www.clinicaltrials.gov/ct2/show/NCT01001897">NCT01001897</a>, <a href="http://www.clinicaltrials.gov/ct2/show/NCT01147497">NCT01147497</a> and <a href="http://www.clinicaltrials.gov/ct2/show/NCT01307111">NCT01307111</a></p

    SNAPSHOT USA 2019 : a coordinated national camera trap survey of the United States

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    This article is protected by copyright. All rights reserved.With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14-week period (17 August - 24 November of 2019). We sampled wildlife at 1509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian's eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the USA. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban-wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot-usa, as well as future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species-specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication.Publisher PDFPeer reviewe

    Mammal responses to global changes in human activity vary by trophic group and landscape

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    Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.Peer reviewe

    New genetic loci link adipose and insulin biology to body fat distribution.

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    Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

    SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

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    Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

    Abdominal aortic aneurysm is associated with a variant in low-density lipoprotein receptor-related protein 1

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    Abdominal aortic aneurysm (AAA) is a common cause of morbidity and mortality and has a significant heritability. We carried out a genome-wide association discovery study of 1866 patients with AAA and 5435 controls and replication of promising signals (lead SNP with a p value &lt; 1 × 10-5) in 2871 additional cases and 32,687 controls and performed further follow-up in 1491 AAA and 11,060 controls. In the discovery study, nine loci demonstrated association with AAA (p &lt; 1 × 10-5). In the replication sample, the lead SNP at one of these loci, rs1466535, located within intron 1 of low-density-lipoprotein receptor-related protein 1 (LRP1) demonstrated significant association (p = 0.0042). We confirmed the association of rs1466535 and AAA in our follow-up study (p = 0.035). In a combined analysis (6228 AAA and 49182 controls), rs1466535 had a consistent effect size and direction in all sample sets (combined p = 4.52 × 10-10, odds ratio 1.15 [1.10-1.21]). No associations were seen for either rs1466535 or the 12q13.3 locus in independent association studies of coronary artery disease, blood pressure, diabetes, or hyperlipidaemia, suggesting that this locus is specific to AAA. Gene-expression studies demonstrated a trend toward increased LRP1 expression for the rs1466535 CC genotype in arterial tissues; there was a significant (p = 0.029) 1.19-fold (1.04-1.36) increase in LRP1 expression in CC homozygotes compared to TT homozygotes in aortic adventitia. Functional studies demonstrated that rs1466535 might alter a SREBP-1 binding site and influence enhancer activity at the locus. In conclusion, this study has identified a biologically plausible genetic variant associated specifically with AAA, and we suggest that this variant has a possible functional role in LRP1 expression

    Clinical Characteristics, Racial Inequities, and Outcomes in Patients with Breast Cancer and COVID-19: A COVID-19 and Cancer Consortium (CCC19) Cohort Study

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    BACKGROUND: Limited information is available for patients with breast cancer (BC) and coronavirus disease 2019 (COVID-19), especially among underrepresented racial/ethnic populations. METHODS: This is a COVID-19 and Cancer Consortium (CCC19) registry-based retrospective cohort study of females with active or history of BC and laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection diagnosed between March 2020 and June 2021 in the US. Primary outcome was COVID-19 severity measured on a five-level ordinal scale, including none of the following complications, hospitalization, intensive care unit admission, mechanical ventilation, and all-cause mortality. Multivariable ordinal logistic regression model identified characteristics associated with COVID-19 severity. RESULTS: 1383 female patient records with BC and COVID-19 were included in the analysis, the median age was 61 years, and median follow-up was 90 days. Multivariable analysis revealed higher odds of COVID-19 severity for older age (aOR per decade, 1.48 [95% CI, 1.32-1.67]); Black patients (aOR 1.74; 95 CI 1.24-2.45), Asian Americans and Pacific Islander patients (aOR 3.40; 95 CI 1.70-6.79) and Other (aOR 2.97; 95 CI 1.71-5.17) racial/ethnic groups; worse ECOG performance status (ECOG PS ≥2: aOR, 7.78 [95% CI, 4.83-12.5]); pre-existing cardiovascular (aOR, 2.26 [95% CI, 1.63-3.15])/pulmonary comorbidities (aOR, 1.65 [95% CI, 1.20-2.29]); diabetes mellitus (aOR, 2.25 [95% CI, 1.66-3.04]); and active and progressing cancer (aOR, 12.5 [95% CI, 6.89-22.6]). Hispanic ethnicity, timing, and type of anti-cancer therapy modalities were not significantly associated with worse COVID-19 outcomes. The total all-cause mortality and hospitalization rate for the entire cohort was 9% and 37%, respectively however, it varied according to the BC disease status. CONCLUSIONS: Using one of the largest registries on cancer and COVID-19, we identified patient and BC-related factors associated with worse COVID-19 outcomes. After adjusting for baseline characteristics, underrepresented racial/ethnic patients experienced worse outcomes compared to non-Hispanic White patients. FUNDING: This study was partly supported by National Cancer Institute grant number P30 CA068485 to Tianyi Sun, Sanjay Mishra, Benjamin French, Jeremy L Warner; P30-CA046592 to Christopher R Friese; P30 CA023100 for Rana R McKay; P30-CA054174 for Pankil K Shah and Dimpy P Shah; KL2 TR002646 for Pankil Shah and the American Cancer Society and Hope Foundation for Cancer Research (MRSG-16-152-01-CCE) and P30-CA054174 for Dimpy P Shah. REDCap is developed and supported by Vanderbilt Institute for Clinical and Translational Research grant support (UL1 TR000445 from NCATS/NIH). The funding sources had no role in the writing of the manuscript or the decision to submit it for publication. CLINICAL TRIAL NUMBER: CCC19 registry is registered on ClinicalTrials.gov, NCT04354701
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