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1.
Article in English | MEDLINE | ID: mdl-38821318

ABSTRACT

BACKGROUND: Reaction threshold and severity in food allergy are difficult to predict, and there is a lack of non-invasive predictors. OBJECTIVES: We sought to determine the relationships between pre-challenge levels of peanut (PN)-specific antibodies in saliva and reaction threshold, severity, and organ-specific symptoms during peanut allergic reactions. METHODS: We measured PN-specific antibody levels in saliva collected from 127 children with suspected peanut allergy prior to double-blind, placebo-controlled peanut challenges where reaction threshold, severity, and symptoms were rigorously characterized. Low-threshold peanut allergy was defined as reaction to <300mg of peanut protein cumulatively consumed. A consensus severity grading system was used to grade severity. We analyzed associations between antibody levels and reaction threshold, severity, and organ-specific symptoms. RESULTS: Among the 127 children, those with high pre-challenge saliva PN IgE had higher odds of low-threshold peanut allergy (OR 3.9, 95%CI 1.6-9.5), while those with high saliva PN IgA: PN IgE or PN IgG4:PN IgE had lower odds of low-threshold peanut allergy (OR 0.3, 95%CI 0.1-0.8, and OR 0.4, 95%CI 0.2-0.9, respectively). Children with high pre-challenge saliva PN IgG4 had lower odds of severe peanut reactions (OR 0.4, 95%CI 0.2-0.9). Those with high saliva PN IgE had higher odds of respiratory symptoms (OR 8.0, 95%CI 2.2-26.8). Saliva PN IgE modestly correlated with serum PN IgE levels (Pearson r=0.31, P=0.0004). High and low saliva PN IgE levels further distinguished reaction threshold and severity in participants stratified by serum PN IgE, suggesting endotypes. CONCLUSION: Saliva PN antibodies could aid in non-invasive risk stratification of peanut allergy threshold, severity, and organ-specific symptoms.

2.
J Allergy Clin Immunol ; 153(6): 1721-1728, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38272374

ABSTRACT

BACKGROUND: Reaction thresholds in peanut allergy are highly variable. Elucidating causal relationships between molecular and cellular processes associated with variable thresholds could point to therapeutic pathways for raising thresholds. OBJECTIVE: The aim of this study was to characterize molecular and cellular systemic processes associated with reaction threshold in peanut allergy and causal relationships between them. METHODS: A total of 105 children aged 4 to 14 years with suspected peanut allergy underwent double-blind, placebo-controlled food challenge to peanut. The cumulative peanut protein quantity eliciting allergic symptoms was considered the reaction threshold for each child. Peripheral blood samples collected at 0, 2, and 4 hours after challenge start were used for RNA sequencing, whole blood staining, and cytometry. Statistical and network analyses were performed to identify associations and causal mediation between the molecular and cellular profiles and peanut reaction threshold. RESULTS: Within the cohort (N = 105), 81 children (77%) experienced allergic reactions after ingesting varying quantities of peanut, ranging from 43 to 9043 mg of cumulative peanut protein. Peripheral blood expression of transcripts (eg, IGF1R [false discovery rate (FDR) = 5.4e-5] and PADI4 [FDR = 5.4e-5]) and neutrophil abundance (FDR = 9.5e-4) were associated with peanut threshold. Coexpression network analyses revealed that the threshold-associated transcripts were enriched in modules for FcγR-mediated phagocytosis (FDR = 3.2e-3) and Toll-like receptor (FDR = 1.4e-3) signaling. Bayesian network, key driver, and causal mediation analyses identified key drivers (AP5B1, KLHL21, VASP, TPD52L2, and IGF2R) within these modules that are involved in bidirectional causal mediation relationships with neutrophil abundance. CONCLUSION: Key driver transcripts in FcγR-mediated phagocytosis and Toll-like receptor signaling interact bidirectionally with neutrophils in peripheral blood and are associated with reaction threshold in peanut allergy.


Subject(s)
Peanut Hypersensitivity , Humans , Peanut Hypersensitivity/immunology , Child , Child, Preschool , Male , Female , Adolescent , Transcriptome , Arachis/immunology , Allergens/immunology , Double-Blind Method , Flow Cytometry
3.
Allergy ; 2024 May 26.
Article in English | MEDLINE | ID: mdl-38796780

ABSTRACT

BACKGROUND: Allergic rhinitis is a common inflammatory condition of the nasal mucosa that imposes a considerable health burden. Air pollution has been observed to increase the risk of developing allergic rhinitis. We addressed the hypotheses that early life exposure to air toxics is associated with developing allergic rhinitis, and that these effects are mediated by DNA methylation and gene expression in the nasal mucosa. METHODS: In a case-control cohort of 505 participants, we geocoded participants' early life exposure to air toxics using data from the US Environmental Protection Agency, assessed physician diagnosis of allergic rhinitis by questionnaire, and collected nasal brushings for whole-genome DNA methylation and transcriptome profiling. We then performed a series of analyses including differential expression, Mendelian randomization, and causal mediation analyses to characterize relationships between early life air toxics, nasal DNA methylation, nasal gene expression, and allergic rhinitis. RESULTS: Among the 505 participants, 275 had allergic rhinitis. The mean age of the participants was 16.4 years (standard deviation = 9.5 years). Early life exposure to air toxics such as acrylic acid, phosphine, antimony compounds, and benzyl chloride was associated with developing allergic rhinitis. These air toxics exerted their effects by altering the nasal DNA methylation and nasal gene expression levels of genes involved in respiratory ciliary function, mast cell activation, pro-inflammatory TGF-ß1 signaling, and the regulation of myeloid immune cell function. CONCLUSIONS: Our results expand the range of air pollutants implicated in allergic rhinitis and shed light on their underlying biological mechanisms in nasal mucosa.

4.
Pediatr Allergy Immunol ; 35(1): e14065, 2024 Jan.
Article in English | MEDLINE | ID: mdl-38284919

ABSTRACT

As a potential link between genetic predisposition, environmental exposures, and food allergy outcomes, epigenetics has been a molecular variable of interest in ongoing efforts to understand food allergy mechanisms and outcomes. Here we review population-based investigations of epigenetic loci associated with food allergy, focusing on established clinical food allergy. We first provide an overview of epigenetic mechanisms that have been studied in cohorts with food allergy, predominantly DNA methylation but also microRNA. We then discuss investigations that have implemented epigenome-wide approaches aimed at genome-wide profiling and discovery. Such epigenome-wide studies have collectively identified differentially methylated and differentially regulated loci associated with T cell development, antigen presentation, reaction severity, and causal mediation in food allergy. We then discuss candidate-gene investigations that have honed in on Th1, Th2, T regulatory, and innate genes of a priori interest in food allergy. These studies have highlighted methylation changes in specific candidate genes as associated with T regulatory cell activity as well as differential methylation of Type 1 and Type 2 cytokine genes associated with various food allergies. Intriguingly, epigenetic loci associated with food allergy have also been explored as potential biomarkers for the clinical management of food allergy. We conclude by highlighting several priority directions for advancing population-based epigenomic and epigenetic understandings of food allergy.


Subject(s)
Food Hypersensitivity , MicroRNAs , Humans , Epigenomics , Food Hypersensitivity/genetics , Cell Differentiation , Epigenesis, Genetic
5.
J Allergy Clin Immunol ; 152(6): 1569-1580, 2023 12.
Article in English | MEDLINE | ID: mdl-37619819

ABSTRACT

BACKGROUND: Rising rates of peanut allergy (PA) motivate investigations of its development to inform prevention and therapy. Microbiota and the metabolites they produce shape food allergy risk. OBJECTIVE: We sought to gain insight into gut microbiome and metabolome dynamics in the development of PA. METHODS: We performed a longitudinal, integrative study of the gut microbiome and metabolome of infants with allergy risk factors but no PA from a multicenter cohort followed through mid-childhood. We performed 16S rRNA sequencing, short chain fatty acid measurements, and global metabolome profiling of fecal samples at infancy and at mid-childhood. RESULTS: In this longitudinal, multicenter sample (n = 122), 28.7% of infants developed PA by mid-childhood (mean age 9 years). Lower infant gut microbiome diversity was associated with PA development (P = .014). Temporal changes in the relative abundance of specific microbiota and gut metabolite levels significantly differed in children who developed PA. PA-bound children had different abundance trajectories of Clostridium sensu stricto 1 sp (false discovery rate (FDR) = 0.015) and Bifidobacterium sp (FDR = 0.033), with butyrate (FDR = 0.045) and isovalerate (FDR = 0.036) decreasing over time. Metabolites associated with PA development clustered within the histidine metabolism pathway. Positive correlations between microbiota, butyrate, and isovalerate and negative correlations with histamine marked the PA-free network. CONCLUSION: The temporal dynamics of the gut microbiome and metabolome in early childhood are distinct for children who develop PA. These findings inform our thinking on the mechanisms underlying and strategies for potentially preventing PA.


Subject(s)
Gastrointestinal Microbiome , Peanut Hypersensitivity , Child , Child, Preschool , Humans , Infant , Butyrates , Feces/microbiology , Gastrointestinal Microbiome/genetics , Metabolome , RNA, Ribosomal, 16S/genetics , Longitudinal Studies
6.
J Allergy Clin Immunol ; 150(5): 1232-1236, 2022 Nov.
Article in English | MEDLINE | ID: mdl-35718139

ABSTRACT

BACKGROUND: Genetic predisposition increases risk for asthma, and distinct nasal microbial compositions are associated with asthma. Host genetics might shape nasal microbiome composition. OBJECTIVE: We examined associations between host genetics and nasal microbiome composition. METHODS: Nasal samples were collected from 584 participants from the Mount Sinai Health System, New York. Seventy-seven follow-up samples were collected from a subset of 40 participants. 16S rRNA sequencing and RNA sequencing were performed on nasal samples. Beta diversity was calculated, variant calling on RNA sequencing data was performed, and genetic relatedness between individuals was determined. Using linear regression models, we tested for associations between genetic relatedness and nasal microbiome composition. RESULTS: The median age of the cohort was 14.6 (interquartile range 11.2-19.5) years, with participants representing diverse ancestries and 52.7% of the cohort being female. For participants who provided follow-up samples, the median time between samples was 5.1 (interquartile range 1.4-7.2) months. Nasal microbiome composition similarity as reflected by beta diversity was significantly higher within subjects over time versus between subjects (coefficient = 0.091, P = 2.84-7). There was no significant association between genetic relatedness and beta diversity (coefficient = -0.05, P = .29). Additional analyses exploring the relationship between beta diversity and genetic variance yielded similar results. CONCLUSION: Host genetics has little influence on nasal microbiome composition.


Subject(s)
Asthma , Microbiota , Humans , Female , Child , Adolescent , Young Adult , Adult , Male , RNA, Ribosomal, 16S/genetics , Microbiota/genetics , Nose , Cohort Studies
7.
J Allergy Clin Immunol ; 150(3): 714-720.e2, 2022 09.
Article in English | MEDLINE | ID: mdl-35550149

ABSTRACT

BACKGROUND: The oral and gut microbiomes have each been associated with food allergy status. Within food allergy, they may also influence reaction thresholds. OBJECTIVE: Our aim was to identify oral and gut microbiota associated with reaction thresholds in peanut allergy. METHODS: A total of 59 children aged 4 to 14 years with suspected peanut allergy underwent double-blind, placebo-controlled food challenge to peanut. Those children who reacted at the 300-mg or higher dose of peanut were classified as high-threshold (HT), those who reacted to lower doses were classified as low-threshold (LT), and those children who did not react were classified as not peanut allergic (NPA). Saliva and stool samples collected before challenge underwent DNA isolation followed by 16S rRNA sequencing and short-chain fatty acid measurement. RESULTS: The 59 participants included 38 HT children and 13 LT children. Saliva microbiome α-diversity (Shannon index) was higher in LT children (P = .017). We identified saliva and stool microbiota that distinguished HT children from LT children, including oral Veillonella nakazawae (amplicon sequence variant 1979), which was more abundant in the HT group than in the LT group (false discovery rate [FDR] = 0.025), and gut Bacteroides thetaiotaomicron (amplicon sequence variant 6829), which was less abundant in HT children than in LT children (FDR = 0.039). Comparison with NPA children revealed consistent ordinal trends between these discriminating species and reaction thresholds. Importantly, many of these threshold-associated species were also correlated with short-chain fatty acid levels at the respective body sites, including between oral V nakazawae and oral butyrate (r = 0.57; FDR = 0.049). CONCLUSION: Findings from this multiscale study raise the possibility of microbial therapeutics to increase reaction thresholds in children with food allergy.


Subject(s)
Peanut Hypersensitivity , Adolescent , Allergens , Arachis , Child , Child, Preschool , Double-Blind Method , Humans , Peanut Hypersensitivity/therapy , RNA, Ribosomal, 16S/genetics
8.
J Allergy Clin Immunol ; 148(1): 244-249.e4, 2021 07.
Article in English | MEDLINE | ID: mdl-33592204

ABSTRACT

BACKGROUND: Pet allergies are common in children with asthma. Microbiota and host responses may mediate allergen sensitization. OBJECTIVE: We sought to uncover host-microbe relationships in pet allergen sensitization via joint examination of the nasal microbiome and nasal transcriptome. METHODS: We collected nasal samples from 132 children with asthma for parallel 16S rRNA and RNA sequencing. Specific IgE levels for cat and dog dander were measured. Analyses of the nasal microbiome, nasal transcriptome, and their correlations were performed with respect to pet sensitization status. RESULTS: Among the 132 children, 91 (68.9%) were cat sensitized and 96 (72.7%) were dog sensitized. Cat sensitization was associated with lower nasal microbial diversity by Shannon index (P = .021) and differential nasal bacterial composition by weighted UniFrac distance (permutational multivariate ANOVA P = .035). Corynebacterium sp and Staphylococcus epidermidis were significantly less abundant, and the metabolic process "fatty acid elongation in mitochondria" was lower in pet-sensitized versus unsensitized children. Correlation networks revealed that the nasal expression levels of 47 genes representing inflammatory processes were negatively correlated with the relative abundances of Corynebacterium sp and S epidermidis. Thus, these species were directly associated not only with the absence of pet sensitization but also with the underexpression of host gene expression of inflammatory processes that contribute to allergen sensitization. Causal mediation analyses revealed that the associations between these nasal species and pet sensitization were mediated by nasal gene expression. CONCLUSIONS: Higher abundances of nasal Corynebacterium sp and S epidermidis are associated with absence of pet sensitization and correlate with lower expression of inflammatory genes.


Subject(s)
Microbiota/immunology , Nose/immunology , Nose/microbiology , Pets/immunology , Transcriptome/immunology , Allergens/immunology , Animals , Asthma/immunology , Cats , Child , Dogs , Female , Humans , Hypersensitivity/immunology , Immunoglobulin E/immunology , Male , RNA, Ribosomal, 16S/immunology
9.
J Allergy Clin Immunol ; 148(2): 627-632.e3, 2021 08.
Article in English | MEDLINE | ID: mdl-33819506

ABSTRACT

BACKGROUND: The oral mucosa is the initial interface between food antigens, microbiota, and mucosal immunity, yet, little is known about oral host-environment dynamics in food allergy. OBJECTIVE: Our aim was to determine oral microbial, metabolic, and immunologic profiles associated with peanut allergy. METHODS: We recruited 105 subjects (56 with peanut allergy and 49 healthy subjects) for salivary microbiome profiling using 16S ribosomal RNA sequencing, short-chain fatty acid (SCFA) metabolite assays using liquid chromatography/mass spectrometry, and measurement of oral secreted cytokines using multiplex assays. Analyses within and across data types were performed. RESULTS: The oral microbiome of individuals with peanut allergy was characterized by reduced species in the orders Lactobacillales, Bacteroidales (Prevotella spp), and Bacillales, and increased Neisseriales spp. The distinct oral microbiome of subjects with peanut allergy was accompanied by significant reductions in oral SCFA levels, including acetate, butyrate, and propionate, and significant elevation of IL-4 secretion. Decreased abundances of oral Prevotella spp and Veillonella spp in subjects with peanut allergy were significantly correlated with reduced oral SCFA levels (false discovery rate < 0.05), and increased oral Neisseria spp was correlated with lower oral SCFA levels (false discovery rate < 0.05). Additionally, oral Prevotella spp abundances were correlated with decreased local secretion of TH2-stimulating epithelial factors (IL-33 and thymic stromal lymphopoietin) and TH2 cytokines (IL-4, IL-5, and IL-13), whereas oral Neisseria spp abundance was positively associated with a TH2-skewed oral immune milieu. CONCLUSION: Our novel multidimensional analysis of the oral environment revealed distinct microbial and metabolic profiles associated with mucosal immune disturbances in peanut allergy. Our findings highlight the oral environment as an anatomic site of interest to examine host-microbiome dynamics in food allergy.


Subject(s)
Bacteria , Microbiota/immunology , Mouth , Peanut Hypersensitivity , Saliva , Adolescent , Bacteria/classification , Bacteria/immunology , Child , Cytokines/immunology , Female , Humans , Male , Mouth/immunology , Mouth/microbiology , Peanut Hypersensitivity/immunology , Peanut Hypersensitivity/microbiology , Saliva/immunology , Saliva/microbiology , Th2 Cells/immunology
10.
J Allergy Clin Immunol ; 147(3): 879-893, 2021 03.
Article in English | MEDLINE | ID: mdl-32828590

ABSTRACT

BACKGROUND: Nasal transcriptomics can provide an accessible window into asthma pathobiology. OBJECTIVE: Our goal was to move beyond gene signatures of asthma to identify master regulator genes that causally regulate genes associated with asthma phenotypes. METHODS: We recruited 156 children with severe persistent asthma and controls for nasal transcriptome profiling and applied network-based and probabilistic causal methods to identify severe asthma genes and their master regulators. We then took the same approach in an independent cohort of 190 adults with mild/moderate asthma and controls to identify mild/moderate asthma genes and their master regulators. Comparative analysis of the master regulator genes followed by validation testing in independent children with severe asthma (n = 21) and mild/moderate asthma (n = 154) was then performed. RESULTS: Nasal gene signatures for severe persistent asthma and for mild/moderate persistent asthma were identified; both were found to be enriched in coexpression network modules for ciliary function and inflammatory response. By applying probabilistic causal methods to these gene signatures and validation testing in independent cohorts, we identified (1) a master regulator gene common to asthma across severity and ages (FOXJ1); (2) master regulator genes of severe persistent asthma in children (LRRC23, TMEM231, CAPS, PTPRC, and FYB); and (3) master regulator genes of mild/moderate persistent asthma in children and adults (C1orf38 and FMNL1). The identified master regulators were statistically inferred to causally regulate the expression of downstream genes that modulate ciliary function and inflammatory response to influence asthma. CONCLUSION: The identified master regulator genes of asthma provide a novel path forward to further uncovering asthma mechanisms and therapy.


Subject(s)
Asthma/genetics , Nose/physiology , Adolescent , Child , Cohort Studies , Female , Forkhead Transcription Factors/genetics , Formins/genetics , Gene Expression Profiling , Humans , Intracellular Signaling Peptides and Proteins/genetics , Male , Models, Statistical , Phenotype , Transcriptome
11.
J Allergy Clin Immunol ; 142(3): 834-843.e2, 2018 09.
Article in English | MEDLINE | ID: mdl-29518419

ABSTRACT

BACKGROUND: Nasal microbiota may influence asthma pathobiology. OBJECTIVE: We sought to characterize the nasal microbiome of subjects with exacerbated asthma, nonexacerbated asthma, and healthy controls to identify nasal microbiota associated with asthma activity. METHODS: We performed 16S ribosomal RNA sequencing on nasal swabs obtained from 72 primarily adult subjects with exacerbated asthma (n = 20), nonexacerbated asthma (n = 31), and healthy controls (n = 21). Analyses were performed using Quantitative Insights into Microbial (QIIME); linear discriminant analysis effect size (LEfSe); Phylogenetic Investigation of Communities by Reconstruction of Unobserved States; and Statistical Analysis of Metagenomic Profiles (PICRUSt); and Statistical Analysis of Metagenomic Profiles (STAMP). Species found to be associated with asthma activity were validated using quantitative PCR. Metabolic pathways associated with differentially abundant nasal taxa were inferred through metagenomic functional prediction. RESULTS: Nasal bacterial composition significantly differed among subjects with exacerbated asthma, nonexacerbated asthma, and healthy controls (permutational multivariate ANOVA, P = 2.2 × 10-2). Relative to controls, the nasal microbiota of subjects with asthma were enriched with taxa from Bacteroidetes (Wilcoxon-Mann-Whitney, r = 0.33, P = 5.1 × 10-3) and Proteobacteria (r = 0.29, P = 1.4 × 10-2). Four species were differentially abundant based on asthma status after correction for multiple comparisons: Prevotella buccalis, Padj = 1.0 × 10-2; Dialister invisus, Padj = 9.1 × 10-3; Gardnerella vaginalis, Padj = 2.8 × 10-3; Alkanindiges hongkongensis, Padj = 2.6 × 10-3. These phyla and species were also differentially abundant based on asthma activity (exacerbated asthma vs nonexacerbated asthma vs controls). Quantitative PCR confirmed species overrepresentation in asthma relative to controls for Prevotella buccalis (fold change = 130, P = 2.1 × 10-4) and Gardnerella vaginalis (fold change = 160, P = 6.8 × 10-4). Metagenomic inference revealed differential glycerolipid metabolism (Kruskal-Wallis, P = 1.9 × 10-4) based on asthma activity. CONCLUSIONS: Nasal microbiome composition differs in subjects with exacerbated asthma, nonexacerbated asthma, and healthy controls. The identified nasal taxa could be further investigated for potential mechanistic roles in asthma and as possible biomarkers of asthma activity.


Subject(s)
Asthma/microbiology , Microbiota , Nose/microbiology , Adolescent , Adult , Aged , Bacteria/genetics , Bacteria/isolation & purification , Child , Female , Humans , Male , Microbiota/genetics , Middle Aged , RNA, Ribosomal, 16S/genetics , Young Adult
12.
Genome Med ; 15(1): 71, 2023 09 20.
Article in English | MEDLINE | ID: mdl-37730635

ABSTRACT

BACKGROUND: Systemic and local profiles have each been associated with asthma, but parsing causal relationships between system-wide and airway-specific processes can be challenging. We sought to investigate systemic and airway processes in asthma and their causal relationships. METHODS: Three hundred forty-one participants with persistent asthma and non-asthmatic controls were recruited and underwent peripheral blood mononuclear cell (PBMC) collection and nasal brushing. Transcriptome-wide RNA sequencing of the PBMC and nasal samples and a series of analyses were then performed using a discovery and independent test set approach at each step to ensure rigor. Analytic steps included differential expression analyses, coexpression and probabilistic causal (Bayesian) network constructions, key driver analyses, and causal mediation models. RESULTS: Among the 341 participants, the median age was 13 years (IQR = 10-16), 164 (48%) were female, and 200 (58.7%) had persistent asthma with mean Asthma Control Test (ACT) score 16.6 (SD = 4.2). PBMC genes associated with asthma were enriched in co-expression modules for NK cell-mediated cytotoxicity (fold enrichment = 4.5, FDR = 6.47 × 10-32) and interleukin production (fold enrichment = 2.0, FDR = 1.01 × 10-15). Probabilistic causal network and key driver analyses identified NK cell granule protein (NKG7, fold change = 22.7, FDR = 1.02 × 10-31) and perforin (PRF1, fold change = 14.9, FDR = 1.31 × 10-22) as key drivers predicted to causally regulate PBMC asthma modules. Nasal genes associated with asthma were enriched in the tricarboxylic acid (TCA) cycle module (fold enrichment = 7.5 FDR = 5.09 × 10-107), with network analyses identifying G3BP stress granule assembly factor 1 (G3BP1, fold change = 9.1 FDR = 2.77 × 10-5) and InaD-like protein (INADL, fold change = 5.3 FDR = 2.98 × 10-9) as nasal key drivers. Causal mediation analyses revealed that associations between PBMC key drivers and asthma are causally mediated by nasal key drivers (FDR = 0.0076 to 0.015). CONCLUSIONS: Integrated study of the systemic and airway transcriptomes in a well-phenotyped asthma cohort identified causal key drivers of asthma among PBMC and nasal transcripts. Associations between PBMC key drivers and asthma are causally mediated by nasal key drivers.


Subject(s)
Asthma , Leukocytes, Mononuclear , Female , Humans , Adolescent , Male , Transcriptome , Bayes Theorem , DNA Helicases , Poly-ADP-Ribose Binding Proteins , RNA Helicases , RNA Recognition Motif Proteins , Asthma/genetics
13.
Cell Rep ; 35(2): 108975, 2021 04 13.
Article in English | MEDLINE | ID: mdl-33852839

ABSTRACT

Although clinical and laboratory data have long been used to guide medical practice, this information is rarely integrated with multi-omic data to identify endotypes. We present Merged Affinity Network Association Clustering (MANAclust), a coding-free, automated pipeline enabling integration of categorical and numeric data spanning clinical and multi-omic profiles for unsupervised clustering to identify disease subsets. Using simulations and real-world data from The Cancer Genome Atlas, we demonstrate that MANAclust's feature selection algorithms are accurate and outperform competitors. We also apply MANAclust to a clinically and multi-omically phenotyped asthma cohort. MANAclust identifies clinically and molecularly distinct clusters, including heterogeneous groups of "healthy controls" and viral and allergy-driven subsets of asthmatic subjects. We also find that subjects with similar clinical presentations have disparate molecular profiles, highlighting the need for additional testing to uncover asthma endotypes. This work facilitates data-driven personalized medicine through integration of clinical parameters with multi-omics. MANAclust is freely available at https://bitbucket.org/scottyler892/manaclust/src/master/.


Subject(s)
Asthma/immunology , Epigenome , Microbiota/genetics , Proteomics/methods , Transcriptome , Unsupervised Machine Learning , Adolescent , Adult , Allergens/administration & dosage , Allergens/immunology , Asthma/etiology , Asthma/genetics , Asthma/microbiology , Atlases as Topic , Benchmarking , Case-Control Studies , Child , Child, Preschool , Cluster Analysis , Datasets as Topic , Feces/cytology , Feces/microbiology , Female , Gene Expression Profiling , Gene Expression Regulation , Humans , Male , Middle Aged , Nasal Cavity/cytology , Nasal Cavity/microbiology , Precision Medicine
14.
J Clin Invest ; 131(22)2021 11 15.
Article in English | MEDLINE | ID: mdl-34609967

ABSTRACT

Air pollution is a well-known contributor to asthma. Air toxics are hazardous air pollutants that cause or may cause serious health effects. Although individual air toxics have been associated with asthma, only a limited number of studies have specifically examined combinations of air toxics associated with the disease. We geocoded air toxic levels from the US National Air Toxics Assessment (NATA) to residential locations for participants of our AiRway in Asthma (ARIA) study. We then applied Data-driven ExposurE Profile extraction (DEEP), a machine learning-based method, to discover combinations of early-life air toxics associated with current use of daily asthma controller medication, lifetime emergency department visit for asthma, and lifetime overnight hospitalization for asthma. We discovered 20 multi-air toxic combinations and 18 single air toxics associated with at least 1 outcome. The multi-air toxic combinations included those containing acrylic acid, ethylidene dichloride, and hydroquinone, and they were significantly associated with asthma outcomes. Several air toxic members of the combinations would not have been identified by single air toxic analyses, supporting the use of machine learning-based methods designed to detect combinatorial effects. Our findings provide knowledge about air toxic combinations associated with childhood asthma.


Subject(s)
Air Pollutants/adverse effects , Asthma/etiology , Machine Learning , Acrylates/adverse effects , Adolescent , Air Pollutants/analysis , Child , Ethyl Chloride/adverse effects , Female , Humans , Hydroquinones/adverse effects , Male , Risk Factors
15.
JCI Insight ; 5(5)2020 03 12.
Article in English | MEDLINE | ID: mdl-32161195

ABSTRACT

Relatively little is known about interactions between the airway microbiome and airway host transcriptome in asthma. Since asthma affects and is affected by the entire airway, studying the upper (e.g., nasal) and lower (e.g., bronchial) airways together represents a powerful approach to understanding asthma. Here, we performed a systematic, integrative study of the nasal and bronchial microbiomes and nasal and bronchial host transcriptomes of children with severe persistent asthma and healthy controls. We found that (a) the microbiomes and host transcriptomes of asthmatic children are each distinct by site (nasal versus bronchial); (b) among asthmatic children, Moraxella and Alloiococcus are hub genera in the nasal microbiome, while there are no hubs among bronchial genera; (c) bronchial Actinomyces is negatively associated with bronchial genes for inflammation, suggesting Actinomyces may be protective; (d) compared with healthy children, asthmatic children express more nasal genes for ciliary function and harbor more nasal Streptococcus; and (e) nasal genera such as Corynebacterium are negatively associated with significantly more nasal genes for inflammation in healthy versus asthmatic children, suggesting a potentially stronger protective role for such nasal genera in healthy versus asthmatic children. Our systematic, integrative study provides a window into host-microbiome associations in asthma.


Subject(s)
Asthma/metabolism , Asthma/microbiology , Bronchi/metabolism , Bronchi/microbiology , Microbiota , Trachea/metabolism , Trachea/microbiology , Transcriptome , Adolescent , Case-Control Studies , Child , Humans
16.
J Allergy Clin Immunol Pract ; 7(5): 1591-1598.e4, 2019.
Article in English | MEDLINE | ID: mdl-30654198

ABSTRACT

BACKGROUND: Individuals often report allergy to specific aeroallergens, but allergy testing can reveal disparate sensitization. OBJECTIVE: To characterize the agreement between perceived and actual sensitization to individual aeroallergens in an urban pediatric population. METHODS: A total of 253 children were enrolled from pediatric clinics in New York, NY. Detailed questionnaires regarding perceived sensitization and serum specific IgE measurements to 10 common aeroallergens were completed. Agreement between perceived and actual sensitization (sIgE ≥ 0.35 kUA/L) to individual aeroallergens was assessed by Cohen's kappa. Multivariable logistic regression models adjusted for potential confounders were used to test for associations between perceived and actual sensitization. RESULTS: A total of 161 (63.6%) of 253 children reported perceived sensitization to 1 or more aeroallergen, and 203 (80.2%) were actually sensitized to 1 or more aeroallergen. Agreement between perceived and actual aeroallergen sensitization was fair for most aeroallergens, with greatest agreement for cat dander (κ, 0.42; 95% CI, 0.32-0.53) and dust (κ, 0.32; 95% CI, 0.20-0.44). Models adjusted for potential confounders showed nearly 6-fold odds of sensitization to cat dander given perceived cat allergy (adjusted odds ratio, 5.82; 95% CI, 2.91-11.64), and over 2-fold odds of sensitization to Dermatophagoides pteronyssinus, Dermatophagoides farinae, dog dander, or grass pollen given perceived sensitization to their respective allergens. Among children with no perceived sensitization, actual sensitization ranged from 5.4% to 30.4%, and was more common for indoor versus outdoor allergens, including cockroach. CONCLUSIONS: Children who perceive allergen sensitization to cat, dog, dust, or grass are likely to demonstrate actual sensitization to these individual allergens. Children with no perceived sensitization to allergens are nonetheless frequently sensitized.


Subject(s)
Antigens, Dermatophagoides/immunology , Dander/immunology , Immunoglobulin E/immunology , Poaceae/immunology , Pollen/immunology , Respiratory Hypersensitivity/epidemiology , Self Report , Adolescent , Allergens , Animals , Cats , Child , Dermatophagoides farinae , Dermatophagoides pteronyssinus , Dogs , Dust/immunology , Female , Fungi/immunology , Humans , Logistic Models , Male , Multivariate Analysis , Respiratory Hypersensitivity/diagnosis , Respiratory Hypersensitivity/immunology , Rhinitis, Allergic, Seasonal/diagnosis , Rhinitis, Allergic, Seasonal/epidemiology , Urban Population
17.
Sci Rep ; 9(1): 12970, 2019 09 10.
Article in English | MEDLINE | ID: mdl-31506535

ABSTRACT

Biological and regulatory mechanisms underlying many multi-gene expression-based disease biomarkers are often not readily evident. We describe an innovative framework, NeTFactor, that combines network analyses with gene expression data to identify transcription factors (TFs) that significantly and maximally regulate such a biomarker. NeTFactor uses a computationally-inferred context-specific gene regulatory network and applies topological, statistical, and optimization methods to identify regulator TFs. Application of NeTFactor to a multi-gene expression-based asthma biomarker identified ETS translocation variant 4 (ETV4) and peroxisome proliferator-activated receptor gamma (PPARG) as the biomarker's most significant TF regulators. siRNA-based knock down of these TFs in an airway epithelial cell line model demonstrated significant reduction of cytokine expression relevant to asthma, validating NeTFactor's top-scoring findings. While PPARG has been associated with airway inflammation, ETV4 has not yet been implicated in asthma, thus indicating the possibility of novel, disease-relevant discovery by NeTFactor. We also show that NeTFactor's results are robust when the gene regulatory network and biomarker are derived from independent data. Additionally, our application of NeTFactor to a different disease biomarker identified TF regulators of interest. These results illustrate that the application of NeTFactor to multi-gene expression-based biomarkers could yield valuable insights into regulatory mechanisms and biological processes underlying disease.


Subject(s)
Algorithms , Asthma/genetics , Asthma/pathology , Biomarkers/analysis , Gene Expression Regulation , Gene Regulatory Networks , Case-Control Studies , Cohort Studies , Gene Expression Profiling , Humans , Signal Transduction , Transcription Factors/genetics , Transcription Factors/metabolism
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