The textures of sarcoidosis: quantifying lung disease through variograms.

Objective: Sarcoidosis is a granulomatous disease affecting the lungs in over 90% of patients. Qualitative assessment of chest CT by radiologists is standard clinical practice and reliable quantification of disease from CT would support ongoing efforts to identify sarcoidosis phenotypes. Standard imaging feature engineering techniques such as radiomics suffer from extreme sensitivity to image acquisition and processing, potentially impeding generalizability of research to clinical populations. In this work, we instead investigate approaches to engineering variogram-based features with the intent to identify a robust, generalizable pipeline for image quantification in the study of sarcoidosis. Approach: For a cohort of more than 300 individuals with sarcoidosis, we investigated 24 feature engineering pipelines differing by decisions for image registration to a template lung, empirical and model variogram estimation methods, and feature harmonization for CT scanner model, and subsequently 48 sets of phenotypes produced through unsupervised clustering. We then assessed sensitivity of engineered features, phenotypes produced through unsupervised clustering, and sarcoidosis disease signal strength to pipeline. Main results: We found that variogram features had low to mild association with scanner model and associations were reduced by image registration. For each feature type, features were also typically robust to all pipeline decisions except image registration. Strength of disease signal as measured by association with pulmonary function testing and some radiologist visual assessments was strong (optimistic AUC ≈ 0.9, p ≪ 0.0001 in models for architectural distortion, conglomerate mass, fibrotic abnormality, and traction bronchiectasis) and fairly consistent across engineering approaches regardless of registration and harmonization for CT scanner. Significance: Variogram-based features appear to be a suitable approach to image quantification in support of generalizable research in pulmonary sarcoidosis.

COPD with elevated sputum group 2 innate lymphoid cells is characterized by severe disease.

Rationale: Pulmonary innate immune cells play a central role in the initiation and perpetuation of chronic obstructive pulmonary disease (COPD), however the precise mechanisms that orchestrate the development and severity of COPD are poorly understood. Objectives: We hypothesized that the recently described family of innate lymphoid cells (ILCs) play an important role in COPD. Methods: Subjects with COPD and healthy controls were clinically evaluated, and their sputum samples were assessed by flow cytometry. A mouse model of spontaneous COPD [genetically deficient in surfactant protein-D (SP-D -/- )] and ozone (O 3 ) exposure were used to examine the mechanism by which lack of functional SP-D may skew ILC2s to produce IL-17A in combination with IL-5 and IL-13, leading to a mixed inflammatory profile and more severe disease. Measurements and Main Results: COPD was characterized by poor spirometry, sputum inflammation, and the emergence of sputum GATA3 + ILCs (ILC2s), but not T-bet + ILCs (ILC1s) nor RORγt + ILCs (ILC3s). COPD subjects with elevated sputum ILC2s (the ILC2 high group) had worse spirometry and sputum neutrophilia and eosinophilia than healthy and ILC2 low subjects. This was associated with the presence of dual-positive IL-5 + IL-17A + and IL-13 + IL-17A + ILCs and nonfunctional SP-D in the sputum in ILC2 high subjects. SP-D -/- mice showed spontaneous airway neutrophilia. Lack of SP-D in the mouse lung licensed ILC2s to produce IL-17A, which was dose-dependently inhibited by recombinant SP-D. SP-D -/- mice showed enhanced susceptibility to O 3 -induced airway neutrophilia, which was associated with the emergence of inflammatory IL-13 + IL-17A + ILCs. Conclusions: We report that the presence of sputum ILC2s predicts the severity of COPD, and unravel a novel pathway of IL-17A plasticity in lung ILC2s, prevented by the immunomodulatory protein SP-D.

Genetic predisposition to sarcoidosis.

Sarcoidosis is a complex systemic disease with clinical heterogeneity based on varying phenotypes and natural history. The detailed etiology of sarcoidosis remains unknown, but genetic predisposition as well as environmental exposures play a significant role in disease pathogenesis. We performed a comprehensive review of germline genetic (DNA) and transcriptomic (RNA) studies of sarcoidosis, including both previous studies and more recent findings. In this review, we provide an assessment of the following: genetic variants in sarcoidosis susceptibility and phenotypes, ancestry- and sex-specific genetic variants in sarcoidosis, shared genetic architecture between sarcoidosis and other diseases, and gene-environment interactions in sarcoidosis. We also highlight the unmet needs in sarcoidosis genetic studies, including the pressing requirement to include diverse populations and have consistent definitions of phenotypes in the sarcoidosis research community to help advance the application of genetic predisposition to sarcoidosis disease risk and manifestations.

Vaccine-elicited B- and T-cell immunity to SARS-CoV-2 is impaired in chronic lung disease patients.

Background: While vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) provides significant protection from coronavirus disease 2019, the protection afforded to individuals with chronic lung disease is less well established. This study seeks to understand how chronic lung disease impacts SARS-CoV-2 vaccine-elicited immunity. Methods: Deep immune phenotyping of humoral and cell-mediated responses to the SARS-CoV-2 vaccine was performed in patients with asthma, COPD and interstitial lung disease (ILD) compared to healthy controls. Results: 48% of vaccinated patients with chronic lung diseases had reduced antibody titres to the SARS-CoV-2 vaccine antigen relative to healthy controls. Vaccine antibody titres were significantly reduced among asthma (p<0.035), COPD (p<0.022) and a subset of ILD patients as early as 3-4 months after vaccination, correlating with decreased vaccine-specific memory B-cells in circulation. Vaccine-specific memory T-cells were significantly reduced in patients with asthma (CD8+ p<0.004; CD4+ p<0.023) and COPD (CD8+ p<0.008) compared to healthy controls. Impaired T-cell responsiveness was also observed in a subset of ILD patients (CD8+ 21.4%; CD4+ 42.9%). Additional heterogeneity between healthy and disease cohorts was observed among bulk and vaccine-specific follicular T-helper cells. Conclusions: Deep immune phenotyping of the SARS-CoV-2 vaccine response revealed the complex nature of vaccine-elicited immunity and highlights the need for more personalised vaccination schemes in patients with underlying lung conditions.

Genome-wide association study identifies multiple HLA loci for sarcoidosis susceptibility.

Sarcoidosis is a complex systemic disease. Our study aimed to (1) identify novel alleles associated with sarcoidosis susceptibility; (2) provide an in-depth evaluation of HLA alleles and sarcoidosis susceptibility and (3) integrate genetic and transcription data to identify risk loci that may more directly impact disease pathogenesis. We report a genome-wide association study of 1335 sarcoidosis cases and 1264 controls of European descent (EA) and investigate associated alleles in a study of African Americans (AA: 1487 cases and 1504 controls). The EA and AA cohort was recruited from multiple United States sites. HLA alleles were imputed and tested for association with sarcoidosis susceptibility. Expression quantitative locus and colocalization analysis were performed using a subset of subjects with transcriptome data. Forty-nine SNPs in the HLA region in HLA-DRA, -DRB9, -DRB5, -DQA1 and BRD2 genes were significantly associated with sarcoidosis susceptibility in EA, rs3129888 was also a risk variant for sarcoidosis in AA. Classical HLA alleles DRB1*0101, DQA1*0101 and DQB1*0501, which are highly correlated, were also associated with sarcoidosis. rs3135287 near HLA-DRA was associated with HLA-DRA expression in peripheral blood mononuclear cells and bronchoalveolar lavage from subjects and lung tissue and whole blood from GTEx. We identified six novel SNPs (out of the seven SNPs representing the 49 significant SNPs) and nine HLA alleles associated with sarcoidosis susceptibility in the largest EA population. We also replicated our findings in an AA population. Our study reiterates the potential role of antigen recognition and/or presentation HLA class II genes in sarcoidosis pathogenesis.

Vaccine-elicited B and T cell immunity to SARS-CoV-2 is impaired in chronic lung disease patients.

The protection afforded by vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to individuals with chronic lung disease is not well established. To understand how chronic lung disease impacts SARS-CoV-2 vaccine-elicited immunity we performed deep immunophenotyping of the humoral and cell mediated SARS-CoV-2 vaccine response in an investigative cohort of vaccinated patients with diverse pulmonary conditions including asthma, chronic obstructive pulmonary disease (COPD), and interstitial lung disease (ILD). Compared to healthy controls, 48% of vaccinated patients with chronic lung diseases had reduced antibody titers to the SARS-CoV-2 vaccine antigen as early as 3-4 months after vaccination, correlating with decreased vaccine-specific memory B cells. Vaccine-specific CD4 and CD8 T cells were also significantly reduced in patients with asthma, COPD, and a subset of ILD patients compared to healthy controls. These findings reveal the complex nature of vaccine-elicited immunity in high-risk patients with chronic lung disease.

Multi-Omic Signatures of Sarcoidosis and Progression in Bronchoalveolar Lavage Cells.

Introduction: Sarcoidosis is a heterogeneous, granulomatous disease that can prove difficult to diagnose, with no accurate biomarkers of disease progression. Therefore, we profiled and integrated the DNA methylome, mRNAs, and microRNAs to identify molecular changes associated with sarcoidosis and disease progression that might illuminate underlying mechanisms of disease and potential genomic biomarkers. Methods: Bronchoalveolar lavage cells from 64 sarcoidosis subjects and 16 healthy controls were used. DNA methylation was profiled on Illumina HumanMethylationEPIC arrays, mRNA by RNA-sequencing, and miRNAs by small RNA-sequencing. Linear models were fit to test for effect of diagnosis and phenotype, adjusting for age, sex, and smoking. We built a supervised multi-omics model using a subset of features from each dataset. Results: We identified 46,812 CpGs, 1,842 mRNAs, and 5 miRNAs associated with sarcoidosis versus controls and 1 mRNA, SEPP1 - a protein that supplies selenium to cells, associated with disease progression. Our integrated model emphasized the prominence of the PI3K/AKT1 pathway in sarcoidosis, which is important in T cell and mTOR function. Novel immune related genes and miRNAs including LYST, RGS14, SLFN12L, and hsa-miR-199b-5p, distinguished sarcoidosis from controls. Our integrated model also demonstrated differential expression/methylation of IL20RB, ABCC11, SFSWAP, AGBL4, miR-146a-3p, and miR-378b between non-progressive and progressive sarcoidosis. Conclusions: Leveraging the DNA methylome, transcriptome, and miRNA-sequencing in sarcoidosis BAL cells, we detected widespread molecular changes associated with disease, many which are involved in immune response. These molecules may serve as diagnostic/prognostic biomarkers and/or drug targets, although future testing will be required for confirmation.

Multiomic Signatures of Chronic Beryllium Disease Bronchoalveolar Lavage Cells Relate to T-Cell Function and Innate Immunity.

Chronic beryllium disease (CBD) is a Th1 granulomatous lung disease preceded by sensitization to beryllium (BeS). We profiled the methylome, transcriptome, and selected proteins in the lung to identify molecular signatures and networks associated with BeS and CBD. BAL cell DNA and RNA were profiled using microarrays from CBD (n = 30), BeS (n = 30), and control subjects (n = 12). BAL fluid proteins were measured using Olink Immune Response Panel proteins from CBD (n = 22) and BeS (n = 22) subjects. Linear models identified features associated with CBD, adjusting for covariation and batch effects. Multiomic integration methods identified correlated features between datasets. We identified 1,546 differentially expressed genes in CBD versus control subjects and 204 in CBD versus BeS. Of the 101 shared transcripts, 24 have significant cis relationships between gene expression and DNA methylation, assessed using expression quantitative trait methylation analysis, including genes not previously identified in CBD. A multiomic model of top DNA methylation and gene expression features demonstrated that the first component separated CBD from other samples and the second component separated control subjects from remaining samples. The top features on component one were enriched for T-lymphocyte function, and the top features on component two were enriched for innate immune signaling. We identified six differentially abundant proteins in CBD versus BeS, with two (SIT1 and SH2D1A) selected as important RNA features in the multiomic model. Our integrated analysis of DNA methylation, gene expression, and proteins in the lung identified multiomic signatures of CBD that differentiated it from BeS and control subjects.

Characteristics and outcomes of ambulatory patients with suspected COVID-19 at a respiratory referral center.

RATIONALE: SARS-CoV-2 continues to cause a global pandemic and management of COVID-19 in outpatient settings remains challenging. OBJECTIVE: We sought to describe characteristics of patients with chronic respiratory disease (CRD) experiencing symptoms consistent with COVID-19, who were seen in a novel Acute Respiratory Clinic, prior to widely available testing, emergence of variants, COVID-19 vaccination, and post-vaccination (breakthrough) SARS-CoV-2 infections. METHODS: Retrospective electronic medical record data were analyzed from 907 adults with presumed COVID-19 seen between March 16, 2020 and January 7, 2021. Data included demographics, comorbidities, medications, vital signs, laboratory tests, pulmonary function tests, patient disposition, and co-infections. The overdispersed data (aod) R package was used to create a logit model using COVID-19 diagnosis by PCR as the dichotomous outcome variable. Univariate, conventional multivariate and elastic net machine learning were used to analyze data. RESULTS: Male gender, elevated baseline temperature, and respiratory rate predicted COVID-19 diagnosis. Eosinopenia, neutrophilia, and lymphocytosis were also associated with COVID-19 diagnosis. However, asthma and COPD diagnoses were not associated with SARS-CoV-2 PCR positive test. Male gender, low oxygen saturation, and lower forced expiratory volume in 1 s (FEV1) were associated with higher hospital referral. CONCLUSIONS: CRD patients with acute respiratory symptoms in the ambulatory setting were more likely to have COVID-19 if male, febrile and tachypneic. Patients with lower pre-morbid FEV1 and lower SPO2 are more likely to be referred to the hospital. A composite of vitals sigs and WBC differential help risk stratify CRD patients seeking care for presumed COVID-19.

Clinical phenotyping in sarcoidosis using cluster analysis.

BACKGROUND: Most phenotyping paradigms in sarcoidosis are based on expert opinion; however, no paradigm has been widely adopted because of the subjectivity in classification. We hypothesized that cluster analysis could be performed on common clinical variables to define more objective sarcoidosis phenotypes. METHODS: We performed a retrospective cohort study of 554 sarcoidosis cases to identify distinct phenotypes of sarcoidosis based on 29 clinical features. Model-based clustering was performed using the VarSelLCM R package and the Integrated Completed Likelihood (ICL) criteria were used to estimate number of clusters. To identify features associated with cluster membership, features were ranked based on variable importance scores from the VarSelLCM model, and additional univariate tests (Fisher's exact test and one-way ANOVA) were performed using q-values correcting for multiple testing. The Wasfi severity score was also compared between clusters. RESULTS: Cluster analysis resulted in 6 sarcoidosis phenotypes. Salient characteristics for each cluster are as follows: Phenotype (1) supranormal lung function and majority Scadding stage 2/3; phenotype (2) supranormal lung function and majority Scadding stage 0/1; phenotype (3) normal lung function and split Scadding stages between 0/1 and 2/3; phenotype (4) obstructive lung function and majority Scadding stage 2/3; phenotype (5) restrictive lung function and majority Scadding stage 2/3; phenotype (6) mixed obstructive and restrictive lung function and mostly Scadding stage 4. Although there were differences in the percentages, all Scadding stages were encompassed by all of the phenotypes, except for phenotype 1, in which none were Scadding stage 4. Clusters 4, 5, 6 were significantly more likely to have ever been on immunosuppressive treatment and had higher Wasfi disease severity scores. CONCLUSIONS: Cluster analysis produced 6 sarcoidosis phenotypes that demonstrated less severe and severe phenotypes. Phenotypes 1, 2, 3 have less lung function abnormalities, a lower percentage on immunosuppressive treatment and lower Wasfi severity scores. Phenotypes 4, 5, 6 were characterized by lung function abnormalities, more parenchymal abnormalities, an increased percentage on immunosuppressive treatment and higher Wasfi severity scores. These data support using cluster analysis as an objective and clinically useful way to phenotype sarcoidosis subjects and to empower clinicians to identify those with more severe disease versus those who have less severe disease, independent of Scadding stage.

The landscape of transcriptomic and proteomic studies in sarcoidosis.

Multiple overlapping pathways are identified in tissue, BAL cells, PBMCs and a sarcoidosis in vitro granuloma model. Inferences from omic studies are constrained by small sample sizes. Studies comparing differences between sarcoidosis phenotypes are needed. https://bit.ly/30NaHz4.

National Temporal Trends in Hospitalization and Inpatient Mortality in Patients With Pulmonary Sarcoidosis in the United States Between 2007 and 2018.

BACKGROUND: Sarcoidosis-related hospitalizations have been increasing in the past decade. There is a paucity of data on mortality trends over time in patients with pulmonary sarcoidosis and respiratory failure who are hospitalized. RESEARCH QUESTION: What are the national temporal trends over time in hospitalization and inpatient mortality rates in patients with pulmonary sarcoidosis and respiratory failure hospitalized in the United States between 2007 and 2018? STUDY DESIGN AND METHODS: Hospitalization data between 2007 and 2018 were extracted from the National Inpatient Sample for subjects with pulmonary sarcoidosis. Inpatient mortality was stratified by age, respiratory failure, mechanical ventilation (MV), hospital location, and setting (rural vs urban, academic vs nonacademic). A Cochran-Armitage test for trend was used to assess the linear trend in mortality, respiratory failure, and need for MV. RESULTS: Hospitalizations in patients with pulmonary sarcoidosis increased from 258.5 per 1,000,000 hospitalizations in 2007 to 705.7 per 1,000,000 in 2018. Hospitalizations for respiratory failure increased ninefold from 25.9 to 239.4 per 1,000,000 hospitalizations, and the need for MV increased threefold from 9.4 per 1,000,000 in 2007 to 29.4 per 1,000,000 in 2018. All-cause inpatient mortality was 2.6%; however, mortality was 13 times higher in patients with respiratory failure (10.6% vs 0.8%) and 26 times higher in patients who required MV (31.2% vs 1.2%). Inpatient mortality associated with respiratory failure declined 50% from 17.2% in 2007 to 6.6% in 2018. Independent inpatient mortality predictors were older age (adjusted hazard ratio [aHR], 1.025), respiratory failure (aHR, 3.12), need for MV (aHR, 6.01), pulmonary hypertension (pHTN; aHR, 1.44), pulmonary embolism (aHR, 1.61), and frailty (aHR, 3.10). INTERPRETATION: Hospitalizations for respiratory failure in patients with pulmonary sarcoidosis are increasing; however, inpatient mortality from respiratory failure has declined. Older age, respiratory failure, pHTN, and frailty are important predictors of inpatient mortality in patients with pulmonary sarcoidosis who are hospitalized.

L-arginine as a potential GLP-1-mediated immunomodulator of Th17-related cytokines in people with obesity and asthma.

Obesity is considered as a risk factor for COVID-19 with insulin resistance and increased production of inflammatory cytokines as likely mechanisms. Glucagon-like peptide-1 (GLP-1) agonists and inhaled nitric oxide are proposed therapeutic approaches to treat COVID-19 because of their broad anti-inflammatory effects. One approach that might augment GLP-1 levels would be dietary supplementation with L-arginine. Beyond cytokines, multiple studies have started to investigate the relationship between new-onset diabetes and COVID-19. In a posthoc analysis of a randomized, placebo-controlled human clinical trial of L-arginine supplementation in people with asthma and predominantly with obesity, the results showed that 12 weeks of continuous L-arginine supplementation significantly decreased the level of IL-21 (p = 0.02) and increased the level of insulin (p = 0.02). A high arginine level and arginine/ADMA ratio were significantly associated with lower CCL-20 and TNF-α levels. The study also showed that L-arginine supplementation reduces cytokine levels and improves insulin deficiency or resistance, both are two big risk factors for COVID-19 severity and mortality. Given its safety profile and ease of accessibility, L-arginine is an attractive potential therapeutic option that allows for a cost-effective way to improve outcomes in patients. An expedition of further investigation or clinical trials to test these hypotheses is needed.

Blood Transcriptomics Predicts Progression of Pulmonary Fibrosis and Associated Natural Killer Cells.

Rationale: Disease activity in idiopathic pulmonary fibrosis (IPF) remains highly variable, poorly understood, and difficult to predict. Objectives: To identify a predictor using short-term longitudinal changes in gene expression that forecasts future FVC decline and to characterize involved pathways and cell types. Methods: Seventy-four patients from COMET (Correlating Outcomes with Biochemical Markers to Estimate Time-Progression in IPF) cohort were dichotomized as progressors (≥10% FVC decline) or stable. Blood gene-expression changes within individuals were calculated between baseline and 4 months and regressed with future FVC status, allowing determination of expression variations, sample size, and statistical power. Pathway analyses were conducted to predict downstream effects and identify new targets. An FVC predictor for progression was constructed in COMET and validated using independent cohorts. Peripheral blood mononuclear single-cell RNA-sequencing data from healthy control subjects were used as references to characterize cell type compositions from bulk peripheral blood mononuclear RNA-sequencing data that were associated with FVC decline. Measurements and Main Results: The longitudinal model reduced gene-expression variations within stable and progressor groups, resulting in increased statistical power when compared with a cross-sectional model. The FVC predictor for progression anticipated patients with future FVC decline with 78% sensitivity and 86% specificity across independent IPF cohorts. Pattern recognition receptor pathways and mTOR pathways were downregulated and upregulated, respectively. Cellular deconvolution using single-cell RNA-sequencing data identified natural killer cells as significantly correlated with progression. Conclusions: Serial transcriptomic change predicts future FVC decline. An analysis of cell types involved in the progressor signature supports the novel involvement of natural killer cells in IPF progression.

Association of inhaled and systemic corticosteroid use with Coronavirus Disease 2019 (COVID-19) test positivity in patients with chronic pulmonary diseases.

BACKGROUND: The effects of chronic inhaled and systemic corticosteroids use on COVID-19 susceptibility and severity are unclear. Since many patients with chronic pulmonary diseases rely on corticosteroids to control disease, it is important to understand the risks of their use during the pandemic. We aim to study if the use of inhaled or systemic corticosteroids affects the likelihood of developing COVID-19 infection. METHODS: We used the National Jewish Health electronic medical record research database to identify a cohort of all subjects who were tested for suspected COVID-19 between March 11 - June 23, 2020. Testing results, medication use, and comorbidities were obtained from the medical record. Following a comparison of different propensity score weighting methods, overlap propensity score weighting was used to analyze the association between medication use and COVID-19 diagnosis. RESULTS: The cohort consisted of 928 patients, of which 12% tested positive. The majority (66%) of patients had a history of chronic pulmonary diseases. There was no significant association between inhaled corticosteroid use and testing positive for COVID-19. Interestingly, systemic corticosteroid use was associated with a lower odds ratio (0.95, 95% CI: 0.91-0.99) of testing positive for COVID-19. Similar results were noted when the analysis was restricted to those with any chronic pulmonary diseases, with asthma or with chronic obstructive pulmonary disease (COPD). CONCLUSIONS: Our study supports the recommendation that patients with chronic pulmonary diseases, including asthma and COPD who require treatment with either inhaled or systemic corticosteroids, should continue their use during the COVID-19 pandemic.