Innate Immune Responses and Gut Microbiomes Distinguish HIV-Exposed from HIV-Unexposed Children in a Population-Specific Manner.

In both high- and low-income countries, HIV-negative children born to HIV-positive mothers (HIV exposed, uninfected [HEU]) are more susceptible to severe infection than HIV-unexposed, uninfected (HUU) children, with altered innate immunity hypothesized to be a cause. Both the gut microbiome and systemic innate immunity differ across biogeographically distinct settings, and the two are known to influence each other. And although the gut microbiome is influenced by HIV infection and may contribute to altered immunity, the biogeography of immune-microbiome correlations among HEU children have not been investigated. To address this, we compared the innate response and the stool microbiome of 2-y-old HEU and HUU children from Belgium, Canada, and South Africa to test the hypothesis that region-specific immune alterations directly correlate to differences in their stool microbiomes. We did not detect a universal immune or microbiome signature underlying differences between HEU versus HUU that was applicable to all children. But as hypothesized, population-specific differences in stool microbiomes were readily detected and included reduced abundances of short-chain fatty acid-producing bacteria in Canadian HEU children. Furthermore, we did not identify innate immune-microbiome associations that distinguished HEU from HUU children in any population. These findings suggest that maternal HIV infection is independently associated with differences in both innate immunity and the stool microbiome in a biogeographical population-specific way.

Dibutyl phthalate exposure alters T-cell subsets in blood from allergen-sensitized volunteers.

Phthalates are ubiquitous environmental contaminants associated with allergic disease in epidemiological and animal studies. This investigation aims to support these associations by interrogating systemic immune effects in allergen-sensitized volunteers after controlled indoor air exposure to a known concentration of dibutyl phthalate (DBP). The phthalate-allergen immune response (PAIR) study enrolled 16 allergen-sensitized participants to a double-blinded, randomized, crossover exposure to two conditions (DBP or control air for 3 hr), each followed immediately by inhaled allergen challenge. Peripheral blood immune cell composition and activation along with inflammatory mediators were measured before and after exposure. DBP exposure prior to the inhaled allergen challenge increased the percentage of CD4+ T helper cells and decreased the percentage of regulatory T cells (3 hr and 20 hr post-exposure), while only modest overall effects were observed for inflammatory mediators. The cells and mediators affected by the phthalate exposure were generally not overlapping with the endpoints affected by allergen inhalation alone. Thus, in distinction to our previously published effects on lung function, DBP appears to alter endpoints in peripheral blood that are not necessarily enhanced by allergen alone. Further studies are needed to clarify the role of phthalate-induced systemic effects in disease pathogenesis.

Ontogeny of plasma cytokine and chemokine concentrations across the first week of human life.

INTRODUCTION/BACKGROUND & AIMS: Early life is marked by distinct and rapidly evolving immunity and increased susceptibility to infection. The vulnerability of the newborn reflects development of a complex immune system in the face of rapidly changing demands during the transition to extra-uterine life. Cytokines and chemokines contribute to this dynamic immune signaling network and can be altered by many factors, such as infection. Newborns undergo dynamic changes important to health and disease, yet there is limited information regarding human neonatal plasma cytokine and chemokine concentrations over the first week of life. The few available studies are limited by small sample size, cross-sectional study design, or focus on perturbed host states like severe infection or prematurity. To characterize immune ontogeny among healthy full-term newborns, we assessed plasma cytokine and chemokine concentrations across the first week of life in a robust longitudinal cohort of healthy, full-term African newborns. METHODS: We analyzed a subgroup of a cohort of healthy newborns at the Medical Research Council Unit in The Gambia (West Africa; N = 608). Peripheral blood plasma was collected from all study participants at birth (day of life (DOL) 0) and at one follow-up time point at DOL 1, 3, or 7. Plasma cytokine and chemokine concentrations were measured by bead-based cytokine multiplex assay. Unsupervised clustering was used to identify patterns in plasma cytokine and chemokine ontogeny during early life. RESULTS: We observed an increase across the first week of life in plasma Th1 cytokines such as IFNγ and CXCL10 and a decrease in Th2 and anti-inflammatory cytokines such as IL-6 and IL-10, and chemokines such as CXCL8. In contrast, other cytokines and chemokines (e.g. IL-4 and CCL5, respectively) remained unchanged during the first week of life. This robust ontogenetic pattern did not appear to be affected by gestational age or sex. CONCLUSIONS: Ontogeny is a strong driver of newborn plasma-based levels of cytokines and chemokines throughout the first week of life with a rising IFNγ axis suggesting post-natal upregulation of host defense pathways. Our study will prove useful to the design and interpretation of future studies aimed at understanding the neonatal immune system during health and disease.

Dibutyl Phthalate Augments Allergen-induced Lung Function Decline and Alters Human Airway Immunology. A Randomized Crossover Study.

Rationale: Phthalates are a group of chemicals used in common commercial products. Epidemiological studies suggest that phthalate exposure is associated with development or worsening of allergic diseases such as asthma. However, effects of dibutyl phthalate (DBP) or other phthalates found in high concentrations in indoor air have never been examined in allergic individuals in a controlled exposure setting.Objectives: To investigate the airway effects in humans caused by inhalation of a known concentration of a single phthalate, DBP.Methods: In a randomized crossover study, 16 allergen-sensitized participants were exposed to control air or DBP for 3 hours in an environmental chamber followed immediately by an allergen inhalation challenge. Bronchoalveolar wash and lavage were obtained 24 hours after exposure. Lung function, early allergic response, airway responsiveness, inflammation, immune mediators, and immune cell phenotypes were assessed after DBP exposure.Measurements and Main Results: DBP exposure increased the early allergic response (21.4% decline in FEV1 area under the curve, P = 0.03). Airway responsiveness was increased by 48.1% after DBP exposure in participants without baseline hyperresponsiveness (P = 0.01). DBP increased the recruitment of BAL total macrophages by 4.6% (P = 0.07), whereas the M2 macrophage phenotype increased by 46.9% (P = 0.04). Airway immune mediator levels were modestly affected by DBP.Conclusions: DBP exposure augmented allergen-induced lung function decline, particularly in those without baseline hyperresponsiveness, and exhibited immunomodulatory effects in the airways of allergic individuals. This is the first controlled human exposure study providing biological evidence for phthalate-induced effects in the airways.Clinical trial registered with www.clinicaltrials.gov (NCT02688478).

DIABLO: an integrative approach for identifying key molecular drivers from multi-omics assays.

MOTIVATION: In the continuously expanding omics era, novel computational and statistical strategies are needed for data integration and identification of biomarkers and molecular signatures. We present Data Integration Analysis for Biomarker discovery using Latent cOmponents (DIABLO), a multi-omics integrative method that seeks for common information across different data types through the selection of a subset of molecular features, while discriminating between multiple phenotypic groups. RESULTS: Using simulations and benchmark multi-omics studies, we show that DIABLO identifies features with superior biological relevance compared with existing unsupervised integrative methods, while achieving predictive performance comparable to state-of-the-art supervised approaches. DIABLO is versatile, allowing for modular-based analyses and cross-over study designs. In two case studies, DIABLO identified both known and novel multi-omics biomarkers consisting of mRNAs, miRNAs, CpGs, proteins and metabolites. AVAILABILITY AND IMPLEMENTATION: DIABLO is implemented in the mixOmics R Bioconductor package with functions for parameters' choice and visualization to assist in the interpretation of the integrative analyses, along with tutorials on http://mixomics.org and in our Bioconductor vignette. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Analytical Validation of HEARTBiT: A Blood-Based Multiplex Gene Expression Profiling Assay for Exclusionary Diagnosis of Acute Cellular Rejection in Heart Transplant Patients.

BACKGROUND: HEARTBiT is a whole blood-based gene profiling assay using the nucleic acid counting NanoString technology for the exclusionary diagnosis of acute cellular rejection in heart transplant patients. The HEARTBiT score measures the risk of acute cellular rejection in the first year following heart transplant, distinguishing patients with stable grafts from those at risk for acute cellular rejection. Here, we provide the analytical performance characteristics of the HEARTBiT assay and the results on pilot clinical validation. METHODS: We used purified RNA collected from PAXgene blood samples to evaluate the characteristics of a 12-gene panel HEARTBiT assay, for its linearity range, quantitative bias, precision, and reproducibility. These parameters were estimated either from serial dilutions of individual samples or from repeated runs on pooled samples. RESULTS: We found that all 12 genes showed linear behavior within the recommended assay input range of 125 ng to 500 ng of purified RNA, with most genes showing 3% or lower quantitative bias and around 5% coefficient of variation. Total variation resulting from unique operators, reagent lots, and runs was less than 0.02 units standard deviation (SD). The performance of the analytically validated assay (AUC = 0.75) was equivalent to what we observed in the signature development dataset. CONCLUSION: The analytical performance of the assay within the specification input range demonstrated reliable quantification of the HEARTBiT score within 0.02 SD units, measured on a 0 to 1 unit scale. This assay may therefore be of high utility in clinical validation of HEARTBiT in future biomarker observational trials.

Investigating Immune Gene Signatures in Peripheral Blood from Subjects with Allergic Rhinitis Undergoing Nasal Allergen Challenge.

Nasal allergen challenge (NAC) is a human model of allergic rhinitis (AR) that delivers standardized allergens locally to the nasal mucosa allowing clinical symptoms and biospecimens such as peripheral blood to be collected. Although many studies have focused on local inflammatory sites, peripheral blood, an important mediator and a component of the systemic immune response, has not been well studied in the setting of AR. We sought to investigate immune gene signatures in peripheral blood collected after NAC under the setting of AR. Clinical symptoms and peripheral blood samples from AR subjects were collected during NAC. Fuzzy c-means clustering method was used to identify immune gene expression patterns in blood over time points (before NAC and 1, 2, and 6 h after NAC). We identified and validated seven clusters of differentially expressed immune genes after NAC onset. Clusters 2, 3, and 4 were associated with neutrophil and lymphocyte frequencies and neutrophil/lymphocyte ratio after the allergen challenge. The patterns of the clusters and immune cell frequencies were associated with the clinical symptoms of the AR subjects and were significantly different from healthy nonallergic subjects who had also undergone NAC. Our approach identified dynamic signatures of immune gene expression in blood as a systemic immune response associated with clinical symptoms after NAC. The immune gene signatures may allow cross-sectional investigation of the pathophysiology of AR and may also be useful as a potential objective measurement for diagnosis and treatment of AR combined with the NAC model.

Novel Blood-based Transcriptional Biomarker Panels Predict the Late-Phase Asthmatic Response.

RATIONALE: The allergen inhalation challenge is used in clinical trials to test the efficacy of new treatments in attenuating the late-phase asthmatic response (LAR) and associated airway inflammation in subjects with allergic asthma. However, not all subjects with allergic asthma develop the LAR after allergen inhalation. Blood-based transcriptional biomarkers that can identify such individuals may help in subject recruitment for clinical trials as well as provide novel molecular insights. OBJECTIVES: To identify blood-based transcriptional biomarker panels that can predict an individual's response to allergen inhalation challenge. METHODS: We applied RNA sequencing to total RNA from whole blood (n = 36) collected before and after allergen challenge and generated both genome-guided and de novo datasets: genes, gene-isoforms (University of California, Santa Cruz, UCSC Genome Browser), Ensembl, and Trinity. Candidate biomarker panels were validated using the NanoString platform in an independent cohort of 33 subjects. MEASUREMENTS AND MAIN RESULTS: The Trinity biomarker panel consisting of known and novel biomarker transcripts had an area under the receiver operating characteristic curve of greater than 0.70 in both the discovery and validation cohorts. The Trinity biomarker panel was useful in predicting the response of subjects that elicited different responses (accuracy between 0.65 and 0.71) and subjects that elicit a dual response (accuracy between 0.70 and 0.75) upon repeated allergen inhalation challenges. CONCLUSIONS: Interestingly, the biomarker panel containing novel transcripts successfully validated compared with panels with known, well-characterized genes. These biomarker-blood tests may be used to identify subjects with asthma who develop the LAR, and may also represent members of novel molecular mechanisms that can be targeted for therapy.

Enumerateblood - an R package to estimate the cellular composition of whole blood from Affymetrix Gene ST gene expression profiles.

BACKGROUND: Measuring genome-wide changes in transcript abundance in circulating peripheral whole blood is a useful way to study disease pathobiology and may help elucidate the molecular mechanisms of disease, or discovery of useful disease biomarkers. The sensitivity and interpretability of analyses carried out in this complex tissue, however, are significantly affected by its dynamic cellular heterogeneity. It is therefore desirable to quantify this heterogeneity, either to account for it or to better model interactions that may be present between the abundance of certain transcripts, specific cell types and the indication under study. Accurate enumeration of the many component cell types that make up peripheral whole blood can further complicate the sample collection process, however, and result in additional costs. Many approaches have been developed to infer the composition of a sample from high-dimensional transcriptomic and, more recently, epigenetic data. These approaches rely on the availability of isolated expression profiles for the cell types to be enumerated. These profiles are platform-specific, suitable datasets are rare, and generating them is expensive. No such dataset exists on the Affymetrix Gene ST platform. RESULTS: We present 'Enumerateblood', a freely-available and open source R package that exposes a multi-response Gaussian model capable of accurately predicting the composition of peripheral whole blood samples from Affymetrix Gene ST expression profiles, outperforming other current methods when applied to Gene ST data. CONCLUSIONS: 'Enumerateblood' significantly improves our ability to study disease pathobiology from whole blood gene expression assayed on the popular Affymetrix Gene ST platform by allowing a more complete study of the various components of this complex tissue without the need for additional data collection. Future use of the model may allow for novel insights to be generated from the ~400 Affymetrix Gene ST blood gene expression datasets currently available on the Gene Expression Omnibus (GEO) website.

Controlled diesel exhaust and allergen coexposure modulates microRNA and gene expression in humans: Effects on inflammatory lung markers.

BACKGROUND: Air pollution's association with asthma may be due to its augmentation of allergenic effects, but the role of microRNA (miRNA) and gene expression in this synergy is unknown. OBJECTIVE: We sought to determine whether exposure to allergen, exposure to diesel exhaust (DE), or coexposures modulate miRNA, gene expression, or inflammatory pathways and whether these measurements are correlated. METHODS: Fifteen participants with atopy completed this controlled study of 2 hours of filtered air or DE (300 µg PM2.5/m3) exposure, followed by saline-controlled segmental bronchial allergen challenge. Gene and miRNA expression in bronchial brushings and lung inflammatory markers were measured 48 hours later, in study arms separated by approximately 4 weeks. Expression of miRNAs, messenger RNAs, and inflammatory markers and their interrelationships were determined using regression. RESULTS: Robust linear models indicated that DE plus saline and DE plus allergen significantly modulated the highest number of miRNAs and messenger RNAs, respectively, relative to control (filtered air plus saline). In mixed models, allergen exposure modulated (q ≤ 0.2) miRNAs including miR-183-5p, miR-324-5p, and miR-132-3p and genes including NFKBIZ and CDKN1A, but DE did not significantly modify this allergenic effect. Repression of CDKN1A by allergen-induced miR-132-3p may contribute to shedding of bronchial epithelial cells. CONCLUSIONS: Expression of specific miRNAs and genes associated with bronchial immune responses were significantly modulated by DE or allergen. However, DE did not augment the effect of allergen at 48 hours, suggesting that adjuvancy may be transient or require higher or prolonged exposure. In silico analysis suggested a possible mechanism contributing to epithelial wall damage following allergen exposure.

SABRE: a method for assessing the stability of gene modules in complex tissues and subject populations.

BACKGROUND: Gene network inference (GNI) algorithms can be used to identify sets of coordinately expressed genes, termed network modules from whole transcriptome gene expression data. The identification of such modules has become a popular approach to systems biology, with important applications in translational research. Although diverse computational and statistical approaches have been devised to identify such modules, their performance behavior is still not fully understood, particularly in complex human tissues. Given human heterogeneity, one important question is how the outputs of these computational methods are sensitive to the input sample set, or stability. A related question is how this sensitivity depends on the size of the sample set. We describe here the SABRE (Similarity Across Bootstrap RE-sampling) procedure for assessing the stability of gene network modules using a re-sampling strategy, introduce a novel criterion for identifying stable modules, and demonstrate the utility of this approach in a clinically-relevant cohort, using two different gene network module discovery algorithms. RESULTS: The stability of modules increased as sample size increased and stable modules were more likely to be replicated in larger sets of samples. Random modules derived from permutated gene expression data were consistently unstable, as assessed by SABRE, and provide a useful baseline value for our proposed stability criterion. Gene module sets identified by different algorithms varied with respect to their stability, as assessed by SABRE. Finally, stable modules were more readily annotated in various curated gene set databases. CONCLUSIONS: The SABRE procedure and proposed stability criterion may provide guidance when designing systems biology studies in complex human disease and tissues.

Discovery of novel plasma protein biomarkers to predict imminent cystic fibrosis pulmonary exacerbations using multiple reaction monitoring mass spectrometry.

BACKGROUND: Despite the significant morbidity and mortality related to pulmonary exacerbations in cystic fibrosis (CF), there remains no reliable predictor of imminent exacerbation. OBJECTIVE: To identify blood-based biomarkers to predict imminent (<4 months from stable blood draw) CF pulmonary exacerbations using targeted proteomics. METHODS: 104 subjects provided plasma samples when clinically stable and were randomly split into discovery (n=70) and replication (n=34) cohorts. Multiple reaction monitoring mass spectrometry (MRM-MS) was used to measure 117 peptides (79 proteins) from plasma. Plasma proteins with differential abundance between subjects who did versus did not develop an imminent exacerbation were analysed and proteins with fold difference >1.5 between the groups were included in an MRM-MS classifier model to predict imminent exacerbations. Performance characteristics were compared with clinical predictors and candidate plasma protein biomarkers. RESULTS: Six proteins were included in the final MRM-MS protein panel. The area under the curve (AUC) for the prediction of imminent exacerbations was highest for the MRM-MS protein panel (AUC 0.74) in comparison to FEV1% predicted (AUC 0.55) and the top candidate plasma protein biomarkers, including C-reactive protein (AUC 0.61) and interleukin-6 (AUC 0.60). The MRM-MS protein panel performed similarly in the replication cohort (AUC 0.73). CONCLUSIONS: Using MRM-MS, a six-protein panel measured from plasma can distinguish individuals with versus without an imminent exacerbation. With further replication and assay development, this biomarker panel may be clinically applicable for prediction of exacerbations in individuals with CF.

The Effect of Different Case Definitions of Current Smoking on the Discovery of Smoking-Related Blood Gene Expression Signatures in Chronic Obstructive Pulmonary Disease.

INTRODUCTION: Smoking is the number one modifiable environmental risk factor for chronic obstructive pulmonary disease (COPD). Clinical, epidemiological and increasingly "omics" studies assess or adjust for current smoking status using only self-report, which may be inaccurate. Objective measures such as exhaled carbon monoxide (eCO) may also be problematic owing to limitations in the measurements and the relatively short half life of the molecule. In this study, we determined the impact of different case definitions of current cigarette smoking on gene expression in peripheral blood of patients with COPD. METHODS: Peripheral blood gene expression from 573 former- and current-smokers with COPD in the ECLIPSE study was used to find genes whose expression was associated with smoking status. Current smoking was defined using self-report, eCO concentrations, or both. Linear regression was used to determine the association of current smoking status with gene expression adjusting for age, sex and propensity score. Pathway enrichment analyses were performed on genes with P < .001. RESULT: Using self-report or eCO, only two genes were differentially expressed between current and ex-smokers, with no enrichment in biological processes. When current smoking was defined using both eCO and self-report, four genes were differentially expressed (LRRN3, PID1, FUCA1, GPR15) with enrichment in 40 biological pathways related to metabolic processes, response to hypoxia and hormonal stimulus. Additionally, the combined definition provided better distributions of test statistics for differential gene expression. CONCLUSION: A combined phenotype of eCO and self report allows for better discovery of genes and pathways related to current smoking. IMPLICATIONS: Studies relying only on self report of smoking status to assess or adjust for the impact of smoking may not fully capture its effect and will lead to residual confounding of results.

Blood Transcriptomic and Inflammatory Protein Biomarkers Associated with Imminent Pulmonary Exacerbation Risk in Cystic Fibrosis.

RATIONALE: The factors that lead to poor pulmonary exacerbation (PEx) outcomes in individuals with cystic fibrosis (CF) are still being investigated; however, delayed diagnosis and treatment are likely contributory. Identifying individuals at imminent risk of PEx could enable closer monitoring and/or earlier initiation of therapies to improve outcomes. OBJECTIVE: The goal of this study was to develop blood-based biomarkers that associate with imminent PEx risk in CF individuals. METHODS: We examined the whole blood transcriptome and 55 inflammatory proteins from plasma and serum on 72 blood samples from 53 CF individuals. Biomarker candidate genes and proteins were selected from 14 CF individuals with paired stable and PEx visits (Cohort 1). The biomarker candidates were then estimated and tested to classify CF individuals who would experience a PEx within 4-months of a stable clinic visit or not (Cohort 2). RESULTS: A 16-gene panel and 9-protein panel were identified that could distinguish paired stable and PEx visits (AUC = 0.83 ± SE 0.28 and AUC = 0.92 ± SE 0.18, respectively). These two panels also demonstrated strong performance in classifying CF individuals who would experience a PEx within 4 months of a clinically stable visit or not (16-gene panel: AUC = 0.88; 9-protein panel: AUC = 0.83). In comparison, serum calprotectin and clinical variables (i.e. sex, ppFEV1, and the number of IV antibiotics in the preceding year) had AUCs of 0.75 and 0.71, respectively. CONCLUSION: Blood-based mRNA and protein biomarkers demonstrated strong performance in classifying CF individuals at risk of imminent PEx. If the findings from this study can be validated, there is the potential to use blood biomarkers to enable more personalized disease activity monitoring in CF.

Multi-level insights into the immuno-oncology-microbiome axis: From biotechnology to novel therapies.

The multifaceted interactions among the immune system, cancer cells and microbial components have established a novel concept of the immuno-oncology-microbiome (IOM) axis. Microbiome sequencing technologies have played a pivotal role in not only analyzing how gut microbiota affect local and distant tumors, but also providing unprecedented insights into the intratumor host-microbe interactions. Herein, we discuss the emerging trends of transiting from bulk-level to single cell- and spatial-level analyses. Moving forward with advances in biotechnology, microbial therapies, including microbiota-based therapies and bioengineering-inspired microbes, will add diversity to the current oncotherapy paradigm.