Person: Sordillo, Joanne
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Publication Effects of Endotoxin Exposure on Childhood Asthma Risk are Modified by a Genetic Polymorphism in ACAA1
(BioMed Central, 2011) Sordillo, Joanne; Sharma, Sunita; Poon, Audrey; Lasky-Su, Jessica; Belanger, Kathleen; Milton, Donald; Bracken, Michael B; Triche, Elizabeth W; Leaderer, Brian P; Gold, Diane; Litonjua, Augusto A.Background: Polymorphisms in the endotoxin-mediated TLR4 pathway genes have been associated with asthma and atopy. We aimed to examine how genetic polymorphisms in innate immunity pathways interact with endotoxin to influence asthma risk in children. Methods: In a previous analysis of 372 children from the Boston Home Allergens and the Connecticut Childhood Asthma studies, 7 SNPs in 6 genes (CARD15, TGFB1, LY96, ACAA1, DEFB1 and IFNG) involved in innate immune pathways were associated with asthma, and 5 SNPs in 3 genes (CD80, STAT4, IRAK2) were associated with eczema. We tested these SNPs for interaction with early life endotoxin exposure (n = 291), in models for asthma and eczema by age 6. Results: We found a significant interaction between endotoxin and a SNP (rs156265) in ACAA1 (p = 0.0013 for interaction). Increased endotoxin exposure (by quartile) showed protective effects for asthma in individuals with at least one copy of the minor allele (OR = 0.39 per quartile increase in endotoxin, 95% CI 0.15 to 1.01). Endotoxin exposure did not reduce the risk of asthma in children homozygous for the major allele. Conclusion: Our findings suggest that protective effects of endotoxin exposure on asthma may vary depending upon the presence or absence of a polymorphism in ACAA1.
Publication Genome-wide expression profiles identify potential targets for gene-environment interactions in asthma severity
(Elsevier BV, 2015) Sordillo, Joanne; Kelly, Roxanne; Bunyavanich, Supinda; McGeachie, Michael; Qiu, Weiliang; Croteau-Chonka, Damien; Soto-Quiros, Manuel; Avila, Lydiana; Celedón, Juan C.; Brehm, John M.; Weiss, Scott; Gold, Diane; Litonjua, Augusto A.Background: Gene by environment interaction (G × E) studies utilizing GWAS data are often underpowered after adjustment for multiple comparisons. Differential gene expression, in response to the exposure of interest, may capture the most biologically relevant genes at the genome-wide level.
Methods: We used differential genome-wide expression profiles from the Home Allergens and Asthma Birth cohort in response to Der f 1 allergen (sensitized vs. non-sensitized) to inform a G × E study of dust mite exposure and asthma severity. Polymorphisms in differentially expressed genes were identified in GWAS data from CAMP, a clinical trial in childhood asthmatics. Home dust mite allergen (< or ≥ 10µg/g dust) was assessed at baseline, and (≥ 1) severe asthma exacerbation (emergency room (ER) visit or hospitalization for asthma in the first trial year) served as the disease severity outcome. The Genetics of Asthma in Costa Rica (GACRS) study, and a Puerto Rico/Connecticut asthma cohortwere used for replication.
Results: IL-9, IL-5 and PRG2 expression was up-regulated in Der f 1 stimulated PBMCs from dust mite sensitized individuals (adj. p value <0.04). IL-9 polymorphisms (rs11741137, rs2069885, rs1859430) showed evidence for interaction with dust mite in CAMP (p=0.02 to 0.03), with replication in GACRS (p=0.04). Subjects with the dominant genotype for these IL-9 polymorphisms were more likely to report a severe asthma exacerbation if exposed to elevated dust mite.
Conclusions: Genome-wide differential gene expression in response to dust mite allergen identified IL-9, a biologically plausible gene target that may interact with environmental dust mite to increase severe asthma exacerbations in children.
Publication Longitudinal Prediction of the Infant Gut Microbiome with Dynamic Bayesian Networks
(Nature Publishing Group, 2016) McGeachie, Michael; Sordillo, Joanne; Gibson, Travis; Weinstock, George M.; Liu, Yang-Yu; Gold, Diane; Weiss, Scott; Litonjua, AugustoSequencing of the 16S rRNA gene allows comprehensive assessment of bacterial community composition from human body sites. Previously published and publicly accessible data on 58 preterm infants in the Neonatal Intensive Care Unit who underwent frequent stool collection was used. We constructed Dynamic Bayesian Networks from the data and analyzed predictive performance and network characteristics. We constructed a DBN model of the infant gut microbial ecosystem, which explicitly captured specific relationships and general trends in the data: increasing amounts of Clostridia, residual amounts of Bacilli, and increasing amounts of Gammaproteobacteria that then give way to Clostridia. Prediction performance of DBNs with fewer edges were overall more accurate, although less so on harder-to-predict subjects (p = 0.045). DBNs provided quantitative likelihood estimates for rare abruptions events. Iterative prediction was less accurate (p < 0.001), but showed remarkable insensitivity to initial conditions and predicted convergence to a mix of Clostridia, Gammaproteobacteria, and Bacilli. DBNs were able to identify important relationships between microbiome taxa and predict future changes in microbiome composition from measured or synthetic initial conditions. DBNs also provided likelihood estimates for sudden, dramatic shifts in microbiome composition, which may be useful in guiding further analysis of those samples.
Publication Diagnostic accuracy of the bronchodilator response in children
(Elsevier BV, 2013) Tse, Szewah; Gold, Diane; Sordillo, Joanne; Hoffman, Elaine Borland; Gillman, Matthew; Rifas-Shiman, Sheryl; Fuhlbrigge, Anne; Tantisira, Kelan; Weiss, Scott; Litonjua, Augusto A.Background: The bronchodilator response (BDR) reflects the reversibility of airflow obstruction and is recommended as an adjunctive test to diagnose asthma. The validity of the commonly used definition of BDR, a 12% or greater change in FEV1 from baseline, has been questioned in childhood.
Objectives: We sought to examine the diagnostic accuracy of the BDR test by using 3 large pediatric cohorts.
Methods: Cases include 1041 children with mild-to-moderate asthma from the Childhood Asthma Management Program. Control subjects (nonasthmatic and nonwheezing) were chosen from Project Viva and Home Allergens, 2 population-based pediatric cohorts. Receiver operating characteristic curves were constructed, and areas under the curve were calculated for different BDR cutoffs.
Results: A total of 1041 cases (59.7% male; mean age, 8.9 ± 2.1 years) and 250 control subjects (46.8% male; mean age, 8.7 ± 1.7 years) were analyzed, with mean BDRs of 10.7% ± 10.2% and 2.7% ± 8.4%, respectively. The BDR test differentiated asthmatic patients from nonasthmatic patients with a moderate accuracy (area under the curve, 73.3%). Despite good specificity, a cutoff of 12% was associated with poor sensitivity (35.6%). A cutoff of less than 8% performed significantly better than a cutoff of 12% (P = .03, 8% vs 12%).
Conclusions: Our findings highlight the poor sensitivity associated with the commonly used 12% cutoff for BDR. Although our data show that a threshold of less than 8% performs better than 12%, given the variability of this test in children, we conclude that it might be not be appropriate to choose a specific BDR cutoff as a criterion for the diagnosis of asthma.