The advent of high throughput technologies has led to a wealth of publicly available ‘omics data coming from different sources, such as transcriptomics, proteomics, metabolomics. Combining such large-scale biological data sets can lead to the discovery of important biological insights, provided that relevant information can be extracted in a holistic manner. Current statistical approaches have been focusing on identifying small subsets of molecules (a ‘molecular signature’) to explain or predict biological conditions, but mainly for a single type of ‘omics. In addition, commonly used methods are univariate and consider each biological feature independently. We introduce mixOmics , an R package dedicated to the multivariate analysis of biological data sets with a specific focus on data exploration, dimension reduction and visualisation. By adopting a system biology approach, the toolkit provides a wide range of methods that statistically integrate several data sets at once to probe relationships between heterogeneous ‘omics data sets. Our recent methods extend Projection to Latent Structure (PLS) models for discriminant analysis, for data integration across multiple ‘omics data or across independent studies, and for the identification of molecular signatures. We illustrate our latest mixOmics integrative frameworks for the multivariate analyses of ‘omics data available from the package.

Systems biology can unravel complex biology but has not been extensively applied to human newborns, a group highly vulnerable to a wide range of diseases. We optimized methods to extract transcriptomic, proteomic, metabolomic, cytokine/chemokine, and single cell immune phenotyping data from <1 ml of blood, a volume readily obtained from newborns. Indexing to baseline and applying innovative integrative computational methods reveals dramatic changes along a remarkably stable developmental trajectory over the first week of life. This is most evident in changes of interferon and complement pathways, as well as neutrophil-associated signaling. Validated across two independent cohorts of newborns from West Africa and Australasia, a robust and common trajectory emerges, suggesting a purposeful rather than random developmental path. Systems biology and innovative data integration can provide fresh insights into the molecular ontogeny of the first week of life, a dynamic developmental phase that is key for health and disease.

BACKGROUND. Idiopathic multicentric Castleman disease (iMCD) is a hematologic illness involving cytokine-induced lymphoproliferation, systemic inflammation, cytopenias, and life-threatening multi-organ dysfunction. The molecular underpinnings of interleukin-6 (IL-6) blockade–refractory patients remain unknown; no targeted therapies exist. In this study, we searched for therapeutic targets in IL-6 blockade–refractory iMCD patients with the thrombocytopenia, anasarca, fever/elevated C-reactive protein, reticulin myelofibrosis, renal dysfunction, organomegaly (TAFRO) clinical subtype. METHODS. We analyzed tissues and blood samples from 3 IL-6 blockade–refractory iMCD-TAFRO patients. Cytokine panels, quantitative serum proteomics, flow cytometry of PBMCs, and pathway analyses were employed to identify novel therapeutic targets. To confirm elevated mTOR signaling, a candidate therapeutic target from the above assays, immunohistochemistry was performed for phosphorylated S6, a read-out of mTOR activation, in 3 iMCD lymph node tissue samples and controls. Proteomic, immunophenotypic, and clinical response assessments were performed to quantify the effects of administration of the mTOR inhibitor sirolimus. RESULTS. Studies of 3 IL-6 blockade–refractory iMCD cases revealed increased CD8⁺ T cell activation, VEGF-A, and PI3K/Akt/mTOR pathway activity. Administration of sirolimus substantially attenuated CD8⁺ T cell activation and decreased VEGF-A levels. Sirolimus induced clinical benefit responses in all 3 patients with durable and ongoing remissions of 66, 19, and 19 months. CONCLUSION. This precision medicine approach identifies PI3K/Akt/mTOR signaling as the first pharmacologically targetable pathogenic process in IL-6 blockade–refractory iMCD. Prospective evaluation of sirolimus in treatment-refractory iMCD is planned (NCT03933904). FUNDING. This study was supported by the Castleman’s Awareness & Research Effort/Castleman Disease Collaborative Network, Penn Center for Precision Medicine, University Research Foundation, Intramural NIH funding, and the National Heart Lung and Blood Institute.

Women have higher prevalence of asthma compared with men. In asthma, allergic airway inflammation is initiated by IL-33 signaling through ST2, leading to increased IL-4, IL-5, and IL-13 production and eosinophil infiltration. Foxp3⁺ Tregs suppress and ST2⁺ Tregs promote allergic airway inflammation. Clinical studies showed that the androgen dehydroepiandrosterone (DHEA) reduced asthma symptoms in patients, and mouse studies showed that androgen receptor (AR) signaling decreased allergic airway inflammation. Yet the impact of AR signaling on lung Tregs remains unclear. Using AR-deficient and Foxp3 fate-mapping mice, we determined that AR signaling increased Treg suppression during Alternaria extract (Alt Ext; allergen) challenge by stabilizing Foxp3⁺ Tregs and limiting the number of ST2⁺ ex-Tregs and IL-13⁺ Th2 cells and ex-Tregs. AR signaling also decreased Alt Ext–induced ST2⁺ Tregs in mice by limiting expression of Gata2, a transcription factor for ST2, and by decreasing Alt Ext–induced IL-33 production from murine airway epithelial cells. We confirmed our findings in human cells where 5α-dihydrotestosterone (DHT), an androgen, decreased IL-33–induced ST2 expression in lung Tregs and decreased Alt Ext–induced IL-33 secretion in human bronchial epithelial cells. Our findings showed that AR signaling stabilized Treg suppressive function, providing a mechanism for the sex difference in asthma.

Background: MicroRNAs are small non-coding RNAs that regulate gene expression at the post-transcriptional level. While they have been implicated in various diseases, the profile changes in allergen inhalation challenge are not clarified in human. We aimed to evaluate changes in the microRNA profiles in the peripheral blood of asthmatic subjects undergoing allergen inhalation challenge. Results: Seven mild asthmatic subjects participated in the allergen inhalation challenge. In addition, four healthy control subjects (HCs) were recruited. MicroRNA profiles in peripheral blood samples (pre-challenge and 2 hours post-challenge) were measured by the NanoString nCounter assay to determine changes in miRNA levels as these asthmatic subjects underwent an allergen inhalation challenge. One common miRNA, miR-192, was significantly expressed in both comparisons; HCs vs. pre-challenge and pre- vs. post-challenge, showing that miR-192 was significantly under-expressed in asthmatics compared to HCs and decreased in post-challenge at an FDR of 1%. Cell-specific statistical deconvolution attributed miR-192 expression in whole blood to PBMCs. MiR-192 was technically validated using real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR) showing that the level in asthmatics (pre-challenge) was significantly lower than HCs and that post-challenge was significantly lower than pre-challenge. The normalized relative miR-192 expression quantified using RT-qPCR specific to PBMCs was also validated. Ontology enrichment and canonical pathway analyses for target genes suggested several functions and pathways involved in immune response and cell cycle. Conclusions: The miRNA profile in peripheral blood was altered after allergen inhalation challenge. Change in miR-192 levels may be implicated in asthma mechanisms. These results suggest that allergen inhalation challenge is a suitable method to characterize peripheral miRNA profiles and potentially elucidate the mechanism of human asthma.

The imbalance between Th17 and Treg cells has been studied in various diseases including allergic asthma but their roles have not been fully understood in the development of the late phase asthmatic response. To determine changes in Th17 and Treg cell numbers between isolated early responders (ERs) and dual responders (DRs) undergoing allergen inhalation challenge. To identify gene expression profiles associated with Th17 and Treg cells. 14 participants (8 ERs and 6 DRs) with mild allergic asthma underwent allergen inhalation challenge. Peripheral blood was collected prior to and 2 hours post allergen challenge. DNA methylation analysis was used to quantifiy the relative frequencies of Th17, Tregs, total B cells, and total T cells. Gene expression from whole blood was measured using microarrays. Technical replication of selected genes was performed using nanoString nCounter Elements. The Th17/Treg ratio significantly increased in DRs compared to ERs post allergen challenge compared to pre-challenge. Genes significantly correlated to Th17 and Treg cell counts were inversely correlated with each other. Genes significantly correlated with Th17/Treg ratio included the cluster of genes of the leukocyte receptor complex located on chromosome 19q 13.4. Th17/Treg imbalance post-challenge may contribute to the development of the late phase inflammatory phenotype.