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Two mycobacteriophages were administered intravenously to a male with treatment-refractory Mycobacterium abscessus pulmonary infection and severe cystic fibrosis lung disease. The phages were engineered to enhance their capacity to lyse M. abscessus and were selected specifically as the most effective against the subject's bacterial isolate. In the setting of compassionate use, the evidence of phage-induced lysis was observed using molecular and metabolic assays combined with clinical assessments. M. abscessus isolates pre and post-phage treatment demonstrated genetic stability, with a general decline in diversity and no increased resistance to phage or antibiotics. The anti-phage neutralizing antibody titers to one phage increased with time but did not prevent clinical improvement throughout the course of treatment. The subject received lung transplantation on day 379, and systematic culturing of the explanted lung did not detect M. abscessus. This study describes the course and associated markers of a successful phage treatment of M. abscessus in advanced lung disease.

The CD4+ T cell response is critical to host protection against helminth infection. How this response varies across different hosts and tissues remains an important gap in our understanding. Using IL-4-reporter mice to identify responding CD4+ T cells to Nippostrongylus brasiliensis infection, T cell receptor sequencing paired with novel clustering algorithms revealed a broadly reactive and clonally diverse CD4+ T cell response. While the most prevalent clones and clonotypes exhibited some tissue selectivity, most were observed to reside in both the lung and lung-draining lymph nodes. Antigen-reactivity of the broader repertoires was predicted to be shared across both tissues and individual mice. Transcriptome, trajectory, and chromatin accessibility analysis of lung and lymph-node repertoires revealed three unique but related populations of responding IL-4+ CD4+ T cells consistent with T follicular helper, T helper 2, and a transitional population sharing similarity with both populations. The shared antigen reactivity of lymph node and lung repertoires combined with the adoption of tissue-specific gene programs allows for the pairing of cellular and humoral responses critical to the orchestration of anti-helminth immunity., Author summary Using various “omic” approaches, the CD4+ T cell receptor (TCR) repertoire was explored after primary helminth infection. Infection generated a broadly reactive and clonally diverse CD4+ T cell response with the most prevalent clonotypes and predicted antigen specificities residing in both the lung and lung-draining lymph nodes. Tissue-specific programming of responding CD4+ T cells directed the establishment of committed Tfh and Th2 cells, both critical for driving distinct hallmarks of type-2 inflammation. These datasets help to explore the diverse yet tissue-specific nature of anti-helminth immunity.

Understanding spatial inhomogeneity and clustering in point patterns arises in many contexts, ranging from disease outbreak monitoring to analyzing radiologically-based emphysema in biomedical images. This can often involve classifying individual points as being part of a feature/cluster or as being part of a background noise process. Existing methods for this task can struggle when there are differences in the size and/or density of individual clusters. In this work, we propose employing kernel density estimates of the underlying point process density function, using an existing data-driven approach to bandwidth selection, to separate feature points from noise. This is achieved by constructing a null distribution, either through asymptotic properties or Monte Carlo simulation, and comparing kernel density estimates to a given quantile of this distribution. We demonstrate that our method, termed Kernel Density and Simulation based Filtering (KDS-Filt), showed superior performance to existing alternative approaches, especially when there is inhomogeneity in cluster sizes and density. We also show the utility of KDS-Filt for identifying clinically relevant information about the spatial distribution of emphysema in lung computed tomography scans. The KDS-Filt methodology is available as part of the sncp R package, which can be downloaded at https://github.com/stop-pre16/sncp .

Pulmonary emphysema is a destructive disease of the lungs that is currently diagnosed via visual assessment of lung Computed Tomography (CT) scans by a radiologist. Visual assessment can have poor inter-rater reliability, is time consuming, and requires access to trained assessors. Quantitative methods that reliably summarize the biologically relevant characteristics of an image are needed to improve the way lung diseases are characterized. The goal of this work was to show how spatial point process models can be used to create a set of radiologically derived quantitative lung biomarkers of emphysema. We formalized a general framework for applying spatial point processes to lung CT scans, and developed a Shot Noise Cox Process to quantify how radiologically based emphysematous tissue clusters into larger structures. Bayesian estimation of model parameters was done using spatial Birth–Death MCMC (BD-MCMC). In simulations, we showed the BD-MCMC estimation algorithm is able to accurately recover model parameters. In an application to real lung CT scans from the COPDGene cohort, we showed variability in the clustering characteristics of emphysematous tissue across disease subtypes that were based on visual assessments of the CT scans.

SUMMARY The mononuclear phagocyte (MP) system consists of macrophages, monocytes, and dendritic cells (DCs). MP subtypes play distinct functional roles in steady-state and inflammatory conditions. Although murine MPs are well characterized, their pulmonary and lymph node (LN) human homologs remain poorly understood. To address this gap, we have created a gene expression compendium across 24 distinct human and murine lung and LN MPs, along with human blood and murine spleen MPs, to serve as validation datasets. In-depth RNA sequencing identifies corresponding human-mouse MP subtypes and determines marker genes shared and divergent across species. Unexpectedly, only 13%–23% of the top 1,000 marker genes(i.e., genes not shared across species-specific MP subtypes) overlap in corresponding human-mouse MP counterparts. Lastly, CD88 in both species helps distinguish monocytes/macrophages from DCs. Our cross-species expression compendium serves as a resource for future translational studies to investigate beforehand whether pursuing specific MP subtypes or genes will prove fruitful., Graphical Abstract, In Brief Understanding the homology of mononuclear phagocytes between humans and mice is essential for translating murine studies into human medicine. Leach et al. use in-depth RNA sequencing to define highly discriminatory marker genes for 15 human and 9 mouse MPs that align cross-species homologs and define conserved and divergent marker genes.

The prognostic value of peripheral blood mononuclear cell (PBMC) expression profiles, when used in patients with chronic hypersensitivity pneumonitis (CHP), as an adjunct to traditional clinical assessment is unknown. RNA-seq analysis on PBMC from 37 patients with CHP at initial presentation determined that (1) 74 differentially expressed transcripts at a 10% false discovery rate distinguished those with (n=10) and without (n=27) disease progression, defined as absolute FVC and/or diffusing capacity of the lungs for carbon monoxide (DLCO) decline of ≥10% and increased fibrosis on chest CT images within 24 months, and (2) classification models based on gene expression and clinical factors strongly outperform models based solely on clinical factors (baseline FVC%, DLCO% and chest CT fibrosis).

EgeUn###, Rationale: Several common and rare genetic variants have been associated with idiopathic pulmonary fibrosis, a progressive fibrotic condition that is localized to the lung. Objectives: To develop an integrated understanding of the rare and common variants located in multiple loci that have been reported to contribute to the risk of disease. Methods: We performed deep targeted resequencing (3.69 Mb of DNA) in cases (n = 3,624) and control subjects (n = 4,442) across genes and regions previously associated with disease. We tested for associations between disease and 1) individual common variants via logistic regression and 2) groups of rare variants via sequence kernel association tests. Measurements and Main Results: Statistically significant common variant association signals occurred in all 10 of the regions chosen based on genome-wide association studies. The strongest risk variant is the MUC5B promoter variant rs35705950, with an odds ratio of 5.45 (95% confidence interval, 4.91-6.06) for one copy of the risk allele and 18.68 (95% confidence interval, 13.34-26.17) for two copies of the risk allele (P = 9.60 3 102295). In addition to identifying for the first time that rare variation in FAM13A is associated with disease, we confirmed the role of rare variation in the TERT and RTEL1 gene regions in the risk of IPF, and found that the FAM13A and TERT regions have independent common and rare variant signals. Conclusions: A limited number of common and rare variants contribute to the risk of idiopathic pulmonary fibrosis in each of the resequencing regions, and these genetic variants focus on biological mechanisms of host defense and cell senescence. Copyright © 2019 by the American Thoracic Society, Háskóli Íslands, HI University of Chicago University of Ulsan, UOU Monash University, MU University of Nottingham University of Edinburgh University of Colorado Denver Universitat de Barcelona University of Pittsburgh, Pitt Harvard School of Dental Medicine Massachusetts General Hospital, MGH University of Pennsylvania, Penn University College Cork, UCC City, University of London, City University of California, San Francisco, UCSF School of Medicine, Vanderbilt University Ege Üniversitesi University of Virginia, UV Aarhus Universitetshospital Central Manchester University Hospitals NHS Foundation Trust Columbia University Novartis Sunovion COPD Foundation Pfizer National Heart, Lung, and Blood Institute, NHLBI: R01-HL097163, UH3-HL123442, P01-HL092870 U.S. Department of Defense, DOD: W81XWH-17-1-0597, U01 HL089897, U01 HL089856 AstraZeneca Siemens Foundation North Carolina GlaxoSmithKline Foundation, 1National Jewish Health, Denver, Colorado; 2School of Public Health; 3Department of Medicine, and 54Department of Immunology, University of Colorado Denver, Denver, Colorado; 4Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee; 5Brigham and Women’s Hospital, Harvard School of Medicine, Boston, Massachusetts; 6Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma;7Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea; 8MRC Centre for Inflammation Research, University of Edinburgh, Edinburgh, United Kingdom; 9Respiratory Medicine Unit, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom; 10Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom; 11Royal Brompton Hospital and Imperial College, London, United Kingdom; 12Simmons Center for Interstitial Lung Disease, University of Pittsburgh, Pittsburgh, Pennsylvania; 13Department of Medicine, University of California, San Francisco, San Francisco, California; 14Gilead Sciences, Foster City, California; 15Department of Medicine, University of Chicago, Chicago, Illinois; 16Department of Medicine, University of Virginia, Charlottesville, Virginia; 17Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; 18National Hospital Organization Kinki-Chuo Chest Medical Center, Osaka, Japan; 19National Hospital Organization Tokyo National Hospital, Tokyo, Japan; 20Helmholtz Zentrum München, Neuherberg, Germany; 21University Hospital Munich, Munich, Germany; 22Department of Pulmonology, Ege University Hospital, Bornova, Izmir, Turkey; 23Royal Prince Alfred Hospital and University of Sydney, Sydney, Australia; 24Alfred Hospital and Monash University, Melbourne, Australia; 25Pulmonary Medicine, GB Morgagni Hospital, Forlì, Italy; 26Department of Diseases of the Thorax, Ospedale GB Morgagni, Forlì, Italy; 27Université Paris Diderot and Hôpital Bichat, Paris, France; 28Royal Papworth Hospital and Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom; 29Respiratory Department, University Hospital of Bellvitge, University of Barcelona, Barcelona, Spain; 30National University Hospital of Iceland, University of Iceland, Reykjavik, Iceland; 31Department of Medicine, Columbia University Irving Medical Center, New York, New York; 32Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts; 33Department of Respiratory Diseases and Allergy, Aarhus University Hospital, Aarhus, Denmark; 34Instituto Nacional de Enfermedades Respiratorias “Ismael Cosio Villegas,” México City, México; 35Universidad Nacional Autónoma de México, México City, México; 36Cork University Hospital and University College Cork, Cork, Ireland; 37St. Vincent’s University Hospital, Dublin, Ireland; 38School of Medicine, University College Dublin, Dublin, Ireland; 39Department of Respiratory Medicine, First Faculty of Medicine Charles University and Thomayer Hospital, Prague, Czech Republic; 40University of British Columbia, Vancouver, Canada; 41Tokyo Medical and Dental University, Tokyo, Japan; 42Institute for Respiratory Health and; 43Centre for Cell Therapy and Regenerative Medicine, School of Biomedical Sciences, The University of Western Australia, Perth, Australia; 44Department of Medicine, Warren Alpert Medical School of Brown University, Providence, Rhode Island; 45Advanced Lung Disease and Transplant Program, Inova Fairfax Hospital, Falls Church, Virginia; 46Department of Pulmonary Medicine, Gazi University School of Medicine, Ankara, Turkey; 47Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama; 48Ruhrlandklinik, University Hospital, University of Duisburg-Essen, Essen, Germany; 49Department of Medicine, Tallaght University Hospital, Trinity College Dublin, Dublin, Ireland; 50CardioPulmonary Reserach Center, Alliance Pulmonary Group, Guaynabo, Puerto Rico; 51Department of Internal Medicine, University of Genoa, Genoa, Italy; 52Biomedical Genomics Center, University of Minnesota; Minneapolis, Minnesota; and 53Northwest Genomics Center, University of Washington, Seattle, Washington -- This research was supported by grants from the NHLBI (R01-HL097163, P01-HL092870, and UH3-HL123442) and the Department of Defense (W81XWH-17-1-0597). The COPDGene project was supported by Award Number U01 HL089897 and Award Number U01 HL089856 from the NHLBI. The COPDGene project was also supported by the COPD Foundation through contributions made to an industry advisory board comprised of AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Novartis, Pfizer, Siemens, and Sunovion.

Rationale and Objectives. A standard lung template could improve population-level analyses for computed tomography (CT) scans of the lung. We develop a fully-automated pre-processing pipeline for image analysis of the lungs using updated methodologies and R software that results in the creation of a standard lung template. We apply this pipeline to CT scans from a sarcoidosis population, exploring the influence of registration on radiomic analyses. Materials and Methods. Using 65 high-resolution CT scans from healthy adults, we create a standard lung template by segmenting the left and right lungs, non-linearly registering lung masks to an initial template mask, and using an unbiased, iterative procedure to converge to a standard lung shape (Dice similarity coefficient ≥0.99). We compare three-dimensional radiomic features between control and sarcoidosis patients, before and after registration to a study-specific lung template. Results. The final lung template had a right lung volume of 2967 cm3 and left lung volume of 2623 cm3, with a median HU = −862. Registration significantly affected radiomic features, shifting the HU distribution to the left, decreasing variability, and increasing smoothness (p

Sarcoidosis is an inflammatory disease, which is characterized by granulomas in the lungs, extrapulmonary inflammation, and can cause death by lung fibrosis. It is known that CD4+ T cell lung population increases in Sarcoidosis. However, the immunopathology remains unclear and no biomarker has been identified. Here we use RNA-seq to examine gene expression in CD4+ T cells of differential Sarcoidosis phenotypes and healthy donors. Our data showed that BATF, a Tfh inducer/key factor in Th17 differentiation was up-regulated while BCL6, a Th17 repressor is down-regulated in RNA-seq. IRF4 and BCL6 were identified as potential transcriptional upstream regulators using IPA. IL-4 and fibrosis related genes were differentially expressed with altered disease phenotype, indicating that type 2 immune response may participate in disease phenotype progression for development of fibrosis. In addition, we used ChIP-seq and ATAC-seq to examine genome-wide epigenetic histone signatures and global chromatin accessibility associated with Sarcoidosis phenotypes. TF binding-site analysis of ATAC-seq peaks revealed an enrichment of BATF binding motifs, highlighting the utility of integrating epigenetic and transcriptional signatures to suggest molecular drivers of Sarcoidosis. Our findings identified several potential immune related biomarkers and molecular mechanisms that may drive disease progression.

CITE-Seq enables simultaneous single cell transcriptome and proteome analysis via combining single cell RNA-seq with oligo-labeled antibodies. Conventional techniques such as flow or mass cytometry have caveats including the number of epitopes accurately detected or an inability to recover samples for transcriptome analysis. These limitations are prohibitive for multivariate analysis of limited clinical samples. We developed a CITE-seq assay that enables comprehensive immune cell profiling of Sarcoidosis. Sarcoidosis is a granulomatous lung disease characterized by abnormal CD4+ T cell Th1 activity. However, the disease etiology and course are variable and the underlying molecular drivers remain unknown. The long-term goal of this study is to utilize CITE-seq to identify immune molecular pathways of Sarcoidosis pathogenesis. In our initial studies, we analyzed PBMC’s by CITE-seq vs. flow cytometry and observed similar cell profiles. However, the synergy of protein detection coupled with transcriptome analysis via CITE-seq enhanced cell subset identification vs. flow or scRNA-seq alone. We utilized CITE-seq in an ongoing longitudinal study of Sarcoidosis subjects to enhance resolution of the immune components contributing to disease. We compared CITE-seq to a flow cytometry panel analyzing the differential contributions of various CD4+ T cell lineages. The enhanced granularity provided by CITE-seq elucidated molecular pathways associated with disease pathogenesis. Thus, moving forward CITE-seq can provide the resolution and multivariate data collection required to identify the inflammatory drivers of Sarcoidosis.

Introduction Studying innate sensitivity to ethanol can be an important first step toward understanding alcohol use disorders. In brain, we investigated transcripts, with evidence of miRNA modulation related to a predisposition to the hypnotic effect of ethanol, as measured by loss of righting reflex (LORR). Methods Expression of miRNAs (12 samples) and expression of mRNAs (353 samples) in brain were independently analyzed for an association with LORR in mice from the LXS recombinant inbred panel gathered across several small studies. These results were then integrated via a meta-analysis of miRNA-mRNA target pairs identified in miRNA-target interaction databases. Results We found 112 significant miRNA-mRNA pairs where a large majority of miRNAs and mRNAs were highly interconnected. Most pairs indicated a pattern of increased levels of miRNAs and reduced levels of mRNAs being associated with more alcohol-sensitive strains. For example, CaMKIIn1 was targeted by multiple miRNAs associated with LORR. CAMK2N1 is an inhibitor of CAMK2, which among other functions, phosphorylates, or binds to GABAA and NMDA receptors. Conclusions Our results suggest a novel role of miRNA-mediated regulation of an inhibitor of CAMK2 and its downstream targets including the GABAA and NMDA receptors, which have been previously implicated to have a role in ethanol-induced sedation and sensitivity.

Background Systemic inflammation is a characteristic of both HIV-1 infection and aging (“inflammaging”). Intestinal epithelial barrier damage (IEBD) and microbial translocation (MT) contribute to HIV-associated inflammation, but their impact on inflammaging remains unclear. Methods Plasma biomarkers for IEBD (iFABP), MT (LPS, sCD14), T-cell activation (sCD27), and inflammation (hsCRP, IL-6) were measured in 88 HIV-1 uninfected (HIVneg) and 83 treated, HIV-1-infected (HIVpos) adults from 20–100 years old. Results Age positively correlated with iFABP (r = 0.284, p = 0.008), sCD14 (r = 0.646, p =