Developmental drugs for sarcoidosis.

Sarcoidosis is a multi-organ granulomatous inflammatory disease of unknown etiology. Over 50% of patients will require treatment at some point in their disease and 10%-30% will develop a chronic progressive disease with pulmonary fibrosis leading to significant morbidity and mortality. Recently published guidelines recommend immunosuppressive therapy for sarcoidosis patients at risk of increased disease-related morbidity and mortality, and in whom disease has negatively impacted quality of life. Prednisone the currently recommended first line therapy is associated with significant toxicity however none of the other guideline recommended steroid sparing therapy is approved by regulatory agencies for use in sarcoidosis, and data in support of their use is weak. For patients with severe refractory disease requiring prolonged therapy, treatment options are limited. The need for expanding treatment options in sarcoidosis has been emphasized. Well conducted large, randomized trials evaluating currently available therapeutic options as well as novel pathways for targeting disease are necessary to better guide treatment decisions. These trials will not be without significant challenges. Sarcoidosis is a rare disease with heterogenous presentation and variable progression and clinical outcome. There are no universally agreed upon biomarkers of disease activity and measurement of outcomes is confounded by the need to balance patient centric measures and objective measures of disease activity. Our paper provides an update on developmental drugs in sarcoidosis and outlines several novel pathways that may be targeted for future drug development. Currently available trials are highlighted and ongoing challenges to drug development and clinical trial design are briefly discussed.

Multi-omic signatures of sarcoidosis and progression in bronchoalveolar lavage cells.

BACKGROUND: Sarcoidosis is a heterogeneous granulomatous disease 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 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 sarcoidosis diagnosis and progression phenotype, adjusting for age, sex, smoking, and principal components of the data. We built a supervised multi-omics model using a subset of features from each dataset. RESULTS: We identified 1,459 CpGs, 64 mRNAs, and five miRNAs associated with sarcoidosis versus controls and four mRNAs associated with disease progression. Our integrated model emphasized the prominence of the PI3K/AKT1 pathway, 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 is required for confirmation.

Antimicrobial Evaluation of Two Polycyclic Polyprenylated Acylphloroglucinol Compounds: PPAP23 and PPAP53.

Polycyclic polyprenylated acylphloroglucinols (PPAPs) comprise a large group of compounds of mostly plant origin. The best-known compound is hyperforin from St. John's wort with its antidepressant, antitumor and antimicrobial properties. The chemical synthesis of PPAP variants allows the generation of compounds with improved activity and compatibility. Here, we studied the antimicrobial activity of two synthetic PPAP-derivatives, the water-insoluble PPAP23 and the water-soluble sodium salt PPAP53. In vitro, both compounds exhibited good activity against methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecium. Both compounds had no adverse effects on Galleria mellonella wax moth larvae. However, they were unable to protect the larvae from infection with S. aureus because components of the larval coelom neutralized the antimicrobial activity; a similar effect was also seen with serum albumin. In silico docking studies with PPAP53 revealed that it binds to the F1 pocket of human serum albumin with a binding energy of -7.5 kcal/mol. In an infection model of septic arthritis, PPAP23 decreased the formation of abscesses and S. aureus load in kidneys; in a mouse skin abscess model, topical treatment with PPAP53 reduced S. aureus counts. Both PPAPs were active against anaerobic Gram-positive gut bacteria such as neurotransmitter-producing Clostridium, Enterococcus or Ruminococcus species. Based on these results, we foresee possible applications in the decolonization of pathogens.

Limitations of Clustering with PCA and Correlated Noise.

It is now common to have a modest to large number of features on individuals with complex diseases. Unsupervised analyses, such as clustering with and without preprocessing by Principle Component Analysis (PCA), is widely used in practice to uncover subgroups in a sample. However, in many modern studies features are often highly correlated and noisy (e.g. SNP's, -omics, quantitative imaging markers, and electronic health record data). The practical performance of clustering approaches in these settings remains unclear. Through extensive simulations and empirical examples applying Gaussian Mixture Models and related clustering methods, we show these approaches (including variants of kmeans, VarSelLCM, HDClassifier, and Fisher-EM) can have very poor performance in many settings. We also show the poor performance is often driven by either an explicit or implicit assumption by the clustering algorithm that high variance features are relevant while lower variance features are irrelevant, called the variance as relevance assumption. We develop practical pre-processing approaches that improve analysis performance in some cases. This work offers practical guidance on the strengths and limitations of unsupervised clustering approaches in modern data analysis applications.

Response, resistance, and recovery of gut bacteria to human-targeted drug exposure.

Survival strategies of human-associated microbes to drug exposure have been mainly studied in the context of bona fide pathogens exposed to antibiotics. Less well understood are the survival strategies of non-pathogenic microbes and host-associated commensal communities to the variety of drugs and xenobiotics to which humans are exposed. The lifestyle of microbial commensals within complex communities offers a variety of ways to adapt to different drug-induced stresses. Here, we review the responses and survival strategies employed by gut commensals when exposed to drugs-antibiotics and non-antibiotics-at the individual and community level. We also discuss the factors influencing the recovery and establishment of a new community structure following drug exposure. These survival strategies are key to the stability and resilience of the gut microbiome, ultimately influencing the overall health and well-being of the host.

Integrating research on bacterial pathogens and commensals to fight infections-an ecological perspective.

The incidence of antibiotic-resistant bacterial infections is increasing, and development of new antibiotics has been deprioritised by the pharmaceutical industry. Interdisciplinary research approaches, based on the ecological principles of bacterial fitness, competition, and transmission, could open new avenues to combat antibiotic-resistant infections. Many facultative bacterial pathogens use human mucosal surfaces as their major reservoirs and induce infectious diseases to aid their lateral transmission to new host organisms under some pathological states of the microbiome and host. Beneficial bacterial commensals can outcompete specific pathogens, thereby lowering the capacity of the pathogens to spread and cause serious infections. Despite the clinical relevance, however, the understanding of commensal-pathogen interactions in their natural habitats remains poor. In this Personal View, we highlight directions to intensify research on the interactions between bacterial pathogens and commensals in the context of human microbiomes and host biology that can lead to the development of innovative and sustainable ways of preventing and treating infectious diseases.

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.

Chest CT Imaging Provides More Information Than Chest Radiography Alone in Determining Extent of Physiologic Impairment in Pulmonary Sarcoidosis.

BACKGROUND: Sarcoidosis staging primarily has relied on the Scadding chest radiographic system, although chest CT imaging is finding increased clinical use. RESEARCH QUESTION: Whether standardized chest CT scan assessment provides additional understanding of lung function beyond Scadding stage and demographics is unknown and the focus of this study. STUDY DESIGN AND METHODS: We used the National Heart, Lung, and Blood Institute study Genomics Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis cases of sarcoidosis (n = 351) with Scadding stage and chest CT scans obtained in a standardized manner. One chest radiologist scored all CT scans with a visual scoring system, with a subset read by another chest radiologist. We compared demographic features, Scadding stage, and CT scan findings and the correlation between these measures. Associations between spirometry results and Dlco, CT scan findings, and Scadding stage were determined using regression analysis (n = 318). Agreement between readers was evaluated using Cohen's κ value. RESULTS: CT scan features were inconsistent with Scadding stage in approximately 40% of cases. Most CT scan features assessed on visual scoring were associated negatively with lung function. Associations persisted for FEV1 and Dlco when adjusting for Scadding stage, although some CT scan feature associations with FVC became insignificant. Scadding stage was associated primarily with FEV1, and inclusion of CT scan features reduced significance in association between Scadding stage and lung function. Multivariable regression modeling to identify radiologic measures explaining lung function included Scadding stage for FEV1 and FEV1 to FVC ratio (P < .05) and marginally for Dlco (P < .15). Combinations of CT scan measures accounted for Scadding stage for FVC. Correlations among Scadding stage and CT scan features were noted. Agreement between readers was poor to moderate for presence or absence of CT scan features and poor for degree and location of abnormality. INTERPRETATION: CT scan features explained additional variability in lung function beyond Scadding stage, with some CT scan features obviating the associations between lung function and Scadding stage. Whether CT scan features, phenotypes, or endotypes could be useful for managing patients with sarcoidosis needs more study.

Rosacea Core Domain Set for Clinical Trials and Practice: A Consensus Statement.

Importance: Inconsistent reporting of outcomes in clinical trials of rosacea is impeding and likely preventing accurate data pooling and meta-analyses. There is a need for standardization of outcomes assessed during intervention trials of rosacea. Objective: To develop a rosacea core outcome set (COS) based on key domains that are globally relevant and applicable to all demographic groups to be used as a minimum list of outcomes for reporting by rosacea clinical trials, and when appropriate, in clinical practice. Evidence Review: A systematic literature review of rosacea clinical trials was conducted. Discrete outcomes were extracted and augmented through discussions and focus groups with key stakeholders. The initial list of 192 outcomes was refined to identify 50 unique outcomes that were rated through the Delphi process Round 1 by 88 panelists (63 physicians from 17 countries and 25 patients with rosacea in the US) on 9-point Likert scale. Based on feedback, an additional 11 outcomes were added in Round 2. Outcomes deemed to be critical for inclusion (rated 7-9 by ≥70% of both groups) were discussed in consensus meetings. The outcomes deemed to be most important for inclusion by at least 85% of the participants were incorporated into the final core domain set. Findings: The Delphi process and consensus-building meetings identified a final core set of 8 domains for rosacea clinical trials: ocular signs and symptoms; skin signs of disease; skin symptoms; overall severity; patient satisfaction; quality of life; degree of improvement; and presence and severity of treatment-related adverse events. Recommendations were also made for application in the clinical setting. Conclusions and Relevance: This core domain set for rosacea research is now available; its adoption by researchers may improve the usefulness of future trials of rosacea therapies by enabling meta-analyses and other comparisons across studies. This core domain set may also be useful in clinical practice.

Examination of eQTL Polymorphisms Associated with Increased Risk of Progressive Complicated Sarcoidosis in European and African Descent Subjects.

Background: A limited pool of SNPs are linked to the development and severity of sarcoidosis, a systemic granulomatous inflammatory disease. By integrating genome-wide association studies (GWAS) data and expression quantitative trait loci (eQTL) single nuclear polymorphisms (SNPs), we aimed to identify novel sarcoidosis SNPs potentially influencing the development of complicated sarcoidosis. Methods: A GWAS (Affymetrix 6.0) involving 209 African-American (AA) and 193 European-American (EA, 75 and 51 complicated cases respectively) and publicly-available GWAS controls (GAIN) was utilized. Annotation of multi-tissue eQTL SNPs present on the GWAS created a pool of ~46,000 eQTL SNPs examined for association with sarcoidosis risk and severity (Logistic Model, Plink). The most significant EA/AA eQTL SNPs were genotyped in a sarcoidosis validation cohort (n=1034) and cross-validated in two independent GWAS cohorts. Results: No single GWAS SNP achieved significance (p<1x10-8), however, analysis of the eQTL/GWAS SNP pool yielded 621 eQTL SNPs (p<10-4) associated with 730 genes that highlighted innate immunity, MHC Class II, and allograft rejection pathways with multiple SNPs validated in an independent sarcoidosis cohort (105 SNPs analyzed) (NOTCH4, IL27RA, BTNL2, ANXA11, HLA-DRB1). These studies confirm significant association of eQTL/GWAS SNPs in EAs and AAs with sarcoidosis risk and severity (complicated sarcoidosis) involving HLA region and innate immunity. Conclusion: Despite the challenge of deciphering the genetic basis for sarcoidosis risk/severity, these results suggest that integrated eQTL/GWAS approaches may identify novel variants/genes and support the contribution of dysregulated innate immune responses to sarcoidosis severity.