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Sordillo, Joanne

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Sordillo

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Joanne

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Sordillo, Joanne
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Now showing 1 - 7 of 7
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    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.
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    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, Augusto
    Sequencing 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.
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    The metabolomics of asthma control: a promising link between genetics and disease
    (John Wiley & Sons, Ltd, 2015) McGeachie, Michael; Dahlin, Amber; Qiu, Weiliang; Croteau-Chonka, Damien; Savage, Jessica; Wu, Ann; Wan, Emily; Sordillo, Joanne; Al-Garawi, Amal; Martinez, Fernando D; Strunk, Robert C; Lemanske, Robert F; Liu, Andrew H; Raby, Benjamin; Weiss, Scott; Clish, Clary B; Lasky-Su, Jessica
    Short-acting β agonists (e.g., albuterol) are the most commonly used medications for asthma, a disease that affects over 300 million people in the world. Metabolomic profiling of asthmatics taking β agonists presents a new and promising resource for identifying the molecular determinants of asthma control. The objective is to identify novel genetic and biochemical predictors of asthma control using an integrative “omics” approach. We generated lipidomic data by liquid chromatography tandem mass spectrometry (LC-MS), ­ using plasma samples from 20 individuals with asthma. The outcome of interest was a binary indicator of asthma control defined by the use of albuterol inhalers in the preceding week. We integrated metabolomic data with genome-wide genotype, gene expression, and methylation data of this cohort to identify genomic and molecular indicators of asthma control. A Conditional Gaussian Bayesian Network (CGBN) was generated using the strongest predictors from each of these analyses. Integrative and metabolic pathway over-representation analyses (ORA) identified enrichment of known biological pathways within the strongest molecular determinants. Of the 64 metabolites measured, 32 had known identities. The CGBN model based on four SNPs (rs9522789, rs7147228, rs2701423, rs759582) and two metabolites—monoHETE_0863 and sphingosine-1-phosphate (S1P) could predict asthma control with an AUC of 95%. Integrative ORA identified 17 significantly enriched pathways related to cellular immune response, interferon signaling, and cytokine-related signaling, for which arachidonic acid, PGE2 and S1P, in addition to six genes (CHN1, PRKCE, GNA12, OASL, OAS1, and IFIT3) appeared to drive the pathway results. Of these predictors, S1P, GNA12, and PRKCE were enriched in the results from integrative and metabolic ORAs. Through an integrative analysis of metabolomic, genomic, and methylation data from a small cohort of asthmatics, we implicate altered metabolic pathways, related to sphingolipid metabolism, in asthma control. These results provide insight into the pathophysiology of asthma control.
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    Whole genome prediction and heritability of childhood asthma phenotypes
    (John Wiley and Sons Inc., 2016) McGeachie, Michael; Clemmer, George L.; Croteau‐Chonka, Damien C.; Castaldi, Peter; Cho, Michael; Sordillo, Joanne; Lasky‐Su, Jessica A.; Raby, Benjamin; Tantisira, Kelan; Weiss, Scott
    Abstract Introduction: While whole genome prediction (WGP) methods have recently demonstrated successes in the prediction of complex genetic diseases, they have not yet been applied to asthma and related phenotypes. Longitudinal patterns of lung function differ between asthmatics, but these phenotypes have not been assessed for heritability or predictive ability. Herein, we assess the heritability and genetic predictability of asthma‐related phenotypes. Methods: We applied several WGP methods to a well‐phenotyped cohort of 832 children with mild‐to‐moderate asthma from CAMP. We assessed narrow‐sense heritability and predictability for airway hyperresponsiveness, serum immunoglobulin E, blood eosinophil count, pre‐ and post‐bronchodilator forced expiratory volume in 1 sec (FEV1), bronchodilator response, steroid responsiveness, and longitudinal patterns of lung function (normal growth, reduced growth, early decline, and their combinations). Prediction accuracy was evaluated using a training/testing set split of the cohort. Results: We found that longitudinal lung function phenotypes demonstrated significant narrow‐sense heritability (reduced growth, 95%; normal growth with early decline, 55%). These same phenotypes also showed significant polygenic prediction (areas under the curve [AUCs] 56% to 62%). Including additional demographic covariates in the models increased prediction 4–8%, with reduced growth increasing from 62% to 66% AUC. We found that prediction with a genomic relatedness matrix was improved by filtering available SNPs based on chromatin evidence, and this result extended across cohorts. Conclusions: Longitudinal reduced lung function growth displayed extremely high heritability. All phenotypes with significant heritability showed significant polygenic prediction. Using SNP‐prioritization increased prediction across cohorts. WGP methods show promise in predicting asthma‐related heritable traits.
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    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.
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    Alu and LINE-1 methylation and lung function in the normative ageing study
    (BMJ Publishing Group, 2012) Lange, Nancy E; Sordillo, Joanne; Tarantini, Letizia; Bollati, Valentina; Sparrow, David; Vokonas, Pantel; Zanobetti, Antonella; Schwartz, Joel; Baccarelli, Andrea; Litonjua, Augusto A.; Demeo, Dawn
    Objectives: To investigate the association between methylation of transposable elements Alu and long-interspersed nuclear elements (LINE-1) and lung function. Design: Cohort study. Setting: Outpatient Veterans Administration facilities in greater Boston, Massachusetts, USA. Participants: Individuals from the Veterans Administration Normative Aging Study, a longitudinal study of aging in men, evaluated between 1999 and 2007. The majority (97%) were white. Primary and secondary outcome measures: Primary predictor was methylation, assessed using PCR-pyrosequencing after bisulphite treatment. Primary outcome was lung function as assessed by spirometry, performed according to American Thoracic Society/European Respiratory Society guidelines at the same visit as the blood draws. Results: In multivariable models adjusted for age, height, body mass index (BMI), pack-years of smoking, current smoking and race, Alu hypomethylation was associated with lower forced expiratory volume in 1 s (FEV1) (β=28 ml per 1% change in Alu methylation, p=0.017) and showed a trend towards association with a lower forced vital capacity (FVC) (β=27 ml, p=0.06) and lower FEV1/FVC (β=0.3%, p=0.058). In multivariable models adjusted for age, height, BMI, pack-years of smoking, current smoking, per cent lymphocytes, race and baseline lung function, LINE-1 hypomethylation was associated with more rapid decline of FEV1 (β=6.9 ml/year per 1% change in LINE-1 methylation, p=0.005) and of FVC (β=9.6 ml/year, p=0.002). Conclusions: In multiple regression analysis, Alu hypomethylation was associated with lower lung function, and LINE-1 hypomethylation was associated with more rapid lung function decline in a cohort of older and primarily white men from North America. Future studies should aim to replicate these findings and determine if Alu or LINE-1 hypomethylation may be due to specific and modifiable environmental exposures.
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    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.