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.

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.

5-Aminosalicylic Acid Modulates the Immune Response in Chronic Beryllium Disease Subjects.

INTRODUCTION: Chronic beryllium disease (CBD) is characterized by accumulation of macrophages and beryllium-specific CD4+ T cells that proliferate and produce Th1 cytokines. 5-Amino salicylic acid (5-ASA) is currently used to treat inflammatory bowel disease and has both antioxidant and anti-inflammatory actions. We hypothesized that 5-ASA may be a beneficial therapeutic in CBD. METHODS: Seventeen CBD patients were randomized 3:1 to receive 5-ASA 500-mg capsules or placebo four times daily for 6 weeks orally. Primary study endpoints included changes in beryllium lymphocyte proliferation (BeLPT). Secondary endpoints included changes in bronchoalveolar lavage (BAL) fluid, cells, serum, and blood cell glutathione (GSH) levels, BAL cell TNF-α levels, lung function, and quality of life measures. RESULTS: 5-ASA decreased BAL cell BeLPT by 20% within the 5-ASA treatment group. No significant changes were observed in serum, PBMCs, BALF, or BAL cell GSH levels in either the 5-ASA or placebo treatment group. 5-ASA treatment decreased ex vivo Be-stimulated BAL cell TNF-α levels within the 5-ASA group and when compared to placebo. Significant improvements were noted in quality of life measurements with 5-ASA treatment. CONCLUSIONS: 5-ASA's ability to decrease BAL cell BeLPT and Be-stimulated BAL cell TNF-α levels suggests that 5-ASA may impact the beryllium-specific immune response in CBD. 5-ASA use in other non-infectious granulomatous lung diseases, such as sarcoidosis, may prove to be a useful alternative treatment to corticosteroids for those with mild to moderate disease.

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.

Standardization of flow cytometry and cell sorting to enable a transcriptomic analysis in a multi-site sarcoidosis study.

The contribution and regulation of various CD4+ T cell lineages that occur with remitting vs progressive courses in sarcoidosis are poorly understood. We developed a multiparameter flow cytometry panel to sort these CD4+ T cell lineages followed by measurement of their functional potential using RNA-sequencing analysis at six-month intervals across multiple study sites. To obtain good quality RNA for sequencing, we relied on chemokine receptor expression to identify and sort lineages. To minimize gene expression changes induced by perturbations of T cells and avoid protein denaturation caused by freeze/thaw cycles, we optimized our protocols using freshly isolated samples at each study site. To accomplish this study, we had to overcome significant standardization challenges across multiple sites. Here, we detail standardization considerations for cell processing, flow staining, data acquisition, sorting parameters, and RNA quality control analysis that were performed as part of the NIH-sponsored, multi-center study, BRonchoscopy at Initial sarcoidosis diagnosis Targeting longitudinal Endpoints (BRITE). After several rounds of iterative optimization, we identified the following aspects as critical for successful standardization: 1) alignment of PMT voltages across sites using CS&T/rainbow bead technology; 2) a single template created in the cytometer program that was used by all sites to gate cell populations during data acquisition and cell sorting; 3) use of standardized lyophilized flow cytometry staining cocktails to reduce technical error during processing; 4) development and implementation of a standardized Manual of Procedures. After standardization of cell sorting, we were able to determine the minimum number of sorted cells necessary for next generation sequencing through analysis of RNA quality and quantity from sorted T cell populations. Overall, we found that implementing a multi-parameter cell sorting with RNA-seq analysis clinical study across multiple study sites requires iteratively tested standardized procedures to ensure comparable and high-quality results.

Genomic biomarkers in chronic beryllium disease and sarcoidosis.

Background Previous gene expression studies have identified genes IFNγ, TNFα, RNase 3, CXCL9, and CD55 as potential biomarkers for sarcoidosis and/or chronic beryllium disease (CBD). We hypothesized that differential expression of these genes could function as diagnostic biomarkers for sarcoidosis and CBD, and prognostic biomarkers for sarcoidosis. Study Design/Methods We performed RT-qPCR on whole blood samples from CBD (n = 132), beryllium sensitized (BeS) (n = 109), and sarcoidosis (n = 99) cases and non-diseased controls (n = 97) to determine differential expression of target genes. We then performed logistic regression modeling and generated ROC curves to determine which genes could most accurately differentiate: 1) CBD versus sarcoidosis 2) CBD versus BeS 3) sarcoidosis versus controls 4) non-progressive versus progressive sarcoidosis. Results CD55 and TNFα were significantly upregulated, while CXCL9 was significantly downregulated in CBD compared to sarcoidosis (p < 0.05). The ROC curve from the logistic regression model demonstrated high discriminatory ability of the combination of CD55, TNFα, and CXCL9 to distinguish between CBD and sarcoidosis with an AUC of 0.98. CD55 and TNFα were significantly downregulated in sarcoidosis compared to controls (p < 0.05). The ROC curve from the model showed a reasonable discriminatory ability of CD55 and TNFα to distinguish between sarcoidosis and controls with an AUC of 0.86. There was no combination of genes that could accurately differentiate between CBD and BeS or sarcoidosis phenotypes. Interpretation CD55, TNFα and CXCL9 expression levels can accurately differentiate between CBD and sarcoidosis, while CD55 and TNFα expression levels can accurately differentiate sarcoidosis and controls.

Defining CD4 T helper and T regulatory cell endotypes of progressive and remitting pulmonary sarcoidosis (BRITE): protocol for a US-based, multicentre, longitudinal observational bronchoscopy study.

INTRODUCTION: Sarcoidosis is a multiorgan granulomatous disorder thought to be triggered and influenced by gene-environment interactions. Sarcoidosis affects 45-300/100 000 individuals in the USA and has an increasing mortality rate. The greatest gap in knowledge about sarcoidosis pathobiology is a lack of understanding about the underlying immunological mechanisms driving progressive pulmonary disease. The objective of this study is to define the lung-specific and blood-specific longitudinal changes in the adaptive immune response and their relationship to progressive and non-progressive pulmonary outcomes in patients with recently diagnosed sarcoidosis. METHODS AND ANALYSIS: The BRonchoscopy at Initial sarcoidosis diagnosis Targeting longitudinal Endpoints study is a US-based, NIH-sponsored longitudinal blood and bronchoscopy study. Enrolment will occur over four centres with a target sample size of 80 eligible participants within 18 months of tissue diagnosis. Participants will undergo six study visits over 18 months. In addition to serial measurement of lung function, symptom surveys and chest X-rays, participants will undergo collection of blood and two bronchoscopies with bronchoalveolar lavage separated by 6 months. Freshly processed samples will be stained and flow-sorted for isolation of CD4 +T helper (Th1, Th17.0 and Th17.1) and T regulatory cell immune populations, followed by next-generation RNA sequencing. We will construct bioinformatic tools using this gene expression to define sarcoidosis endotypes that associate with progressive and non-progressive pulmonary disease outcomes and validate the tools using an independent cohort. ETHICS AND DISSEMINATION: The study protocol has been approved by the Institutional Review Boards at National Jewish Hospital (IRB# HS-3118), University of Iowa (IRB# 201801750), Johns Hopkins University (IRB# 00149513) and University of California, San Francisco (IRB# 17-23432). All participants will be required to provide written informed consent. Findings will be disseminated via journal publications, scientific conferences, patient advocacy group online content and social media platforms.