Joanne E. Sordillo

Multiple microbial exposures in the home may protect against asthma or allergy in childhood

Background Experimental animal data on the gram‐negative bacterial (GNB) biomarker endotoxin suggest that persistence, dose, and timing of exposure are likely to influence its effects on allergy and wheeze. In epidemiologic studies, endotoxin may be a sentinel marker for a microbial milieu, including gram‐positive bacteria (GPB) as well as GNB, that may influence allergy and asthma through components (pathogen‐associated molecular patterns) that signal through innate Toll‐like receptor pathways.

Peanut, milk, and wheat intake during pregnancy is associated with reduced allergy and asthma in children.

BACKGROUND Maternal diet during pregnancy may affect childhood allergy and asthma. OBJECTIVE We sought to examine the associations between maternal intake of common childhood food allergens during early pregnancy and childhood allergy and asthma. METHODS We studied 1277 mother-child pairs from a US prebirth cohort unselected for any disease. Using food frequency questionnaires administered during the first and second trimesters, we assessed maternal intake of common childhood food allergens during pregnancy. In mid-childhood (mean age, 7.9 years), we assessed food allergy, asthma, allergic rhinitis, and atopic dermatitis by questionnaire and serum-specific IgE levels. We examined the associations between maternal diet during pregnancy and childhood allergy and asthma. We also examined the cross-sectional associations between specific food allergies, asthma, and atopic conditions in mid-childhood. RESULTS Food allergy was common (5.6%) in mid-childhood, as was sensitization to at least 1 food allergen (28.0%). Higher maternal peanut intake (each additional z score) during the first trimester was associated with 47% reduced odds of peanut allergic reaction (odds ratio [OR], 0.53; 95% CI, 0.30-0.94). Higher milk intake during the first trimester was associated with reduced asthma (OR, 0.83; 95% CI, 0.69-0.99) and allergic rhinitis (OR, 0.85; 95% CI, 0.74-0.97). Higher maternal wheat intake during the second trimester was associated with reduced atopic dermatitis (OR, 0.64; 95% CI, 0.46-0.90). Peanut, wheat, and soy allergy were each cross-sectionally associated with increased childhood asthma, atopic dermatitis, and allergic rhinitis (ORs, 3.6 to 8.1). CONCLUSION Higher maternal intake of peanut, milk, and wheat during early pregnancy was associated with reduced odds of mid-childhood allergy and asthma.

Home Characteristics as Predictors of Bacterial and Fungal Microbial Biomarkers in House Dust

Background Measurement of fungal and bacterial biomarkers can be costly, but it is not clear whether home characteristics can be used as a proxy of these markers, particularly if the purpose is to differentiate specific classes of biologic exposures that have similar sources but may have different effects on allergic disease risk. Objective We evaluated home characteristics as predictors of multiple microbial biomarkers, with a focus on common and unique determinants and with attention to the extent of their explanatory ability. Methods In 376 Boston-area homes enrolled in a cohort study of home exposures and childhood asthma, we assessed the relationship between home characteristics gathered by questionnaire and measured gram-negative bacteria (GNB) (endotoxin and C10:0, C12:0, and C14:0 3-hydroxy fatty acids), gram-positive bacteria (GPB) (N-acetyl muramic acid), and fungal biomarkers [ergosterol and (1→6) branched, (1→3) β-d glucans] in bed and family room dust. Results Home characteristics related to dampness were significant predictors of all microbial exposures; water damage or visible mold/mildew in the home was associated with a 20–66% increase in GNB levels. Report of cleaning the bedroom at least once a week was associated with reduced GNB, GPB, and fungi. Presence of dogs or cats predicted increases in home bacteria or fungi. The proportion of variance in microbial biomarkers explained by home characteristics ranged from 4.2% to 19.0%. Conclusions Despite their associations with multiple microbial flora, home characteristics only partially explain the variability in microbial biomarker levels and cannot substitute for specific microbial measurements in studies concerned with distinguishing effects of specific classes of microbes.

Peanut allergy prevalence among school-age children in a US cohort not selected for any disease

To the Editor: What is the prevalence of peanut allergy among US children? Given that 90% of US households consume peanut butter,1 this is an important question. The answer is not straightforward, however, as estimates of peanut allergy prevalence among US children differ by allergy definition, study population, and methodology.2 Previous estimates for US children have been based on self-report3–6 or specific IgE (sIgE) criteria,7 which are thought to be inaccurate.2 Estimates have varied according to whether they were based on telephone surveys,3 electronic surveys,4 or nationally representative surveys such as the National Health and Nutrition Examination Survey (NHANES) (Table 1).5–7 One must consider that self-report is hindered by reporting bias, surveys of food allergy are more likely to enlist those with the condition, and nationally representative surveys are limited in the extent of phenotyping possible given their wide scope. It can therefore be difficult to discern how differences in definition, study population, and methodology affect prevalence estimates across studies. Here we report and compare prevalence estimates of childhood peanut allergy according to varying criteria among 7–10 year-old children participating in a US birth cohort not selected for any disease. Table 1 Previously reported prevalence estimates of childhood peanut allergy in the US We determined prevalence of childhood peanut allergy based on reported symptoms, sIgE levels, clinical information, and combinations of these variables among participants of Project Viva. Project Viva is a large, observational cohort study based in eastern Massachusetts with enrollment from Harvard Vanguard Medical Associates, a multi-site group medical practice. Participants were not selected for any disease. The study was designed to examine maternal dietary and other factors that could influence child health outcomes, with health broadly defined.8 Enrollment occurred between 1999 and 2002 in early pregnancy and resulted in delivery of 2128 singleton children. Interviews and questionnaires on child health were administered when the children were age 6 months, 1 year, and annually thereafter. We collected outcome data for this study at the mid-childhood in-person visit (mean age 7.9 years). Among the 1277 children who presented for an in-person interview at mid-childhood, 699 (55%) had blood drawn, and 616 (87.7% of those with blood samples) had sIgE measured by Phadia ImmunoCAP. Compared to those who did not follow up, participants who did follow up showed higher proportions of maternal white race (69% vs. 62%), college or graduate education (69% vs. 58%), and annual household income (63% vs. 58%), but there were no significant differences in parental atopy (P value 0.13). Compared with the general US population, there was a higher proportion of blacks and lower proportion of Hispanics among participants. Further details regarding the comparability of the 616 children to the larger cohort have been previously described.8 We considered a child to have self-reported peanut allergy if his/her mother answered yes to, “Has your child ever had an allergic reaction to peanuts,” and yes to at least one of the following categories of allergic reaction symptoms with peanut ingestion: “Skin related (e.g. hives, swelling),” “Respiratory (e.g., shortness of breath, wheezing, cough),” “Cardiovascular (e.g. low blood pressure, dizziness or fainting,” “Gastrointestinal (e.g. vomiting, diarrhea),” or “Anaphylaxis (severe, multi-system allergic reaction).” These questions, which assess convincing symptoms of IgE-mediated reaction, are comparable to those used in previous studies of self-reported peanut allergy by Sicherer et al.3 We assessed prescription of an epinephrine auto-injector with the question, “Has a health care professional, such as a doctor, physician assistant or nurse practitioner, ever prescribed an EpiPen for your child?” The prevalence of self-reported peanut allergy in this cohort of US children not selected for any disease was 4.6% (Table 2), higher than previously reported estimates of self-reported peanut allergy among US children of comparable age (Table 1). Similarly, we observed a 5.0% prevalence of “clinical peanut allergy” according to sIgE-based criteria that previously resulted in a 2.7% prevalence among comparably aged children in the 2005–2006 NHANES study.7 Within Project Viva, the 4.9% prevalence of peanut allergy defined by both sensitization and prescribed epinephrine auto-injector was similar in magnitude to the estimates defined by self-reported allergy and sIgE-based “clinical allergy” criteria. Table 2 Prevalence of peanut allergy among school-age children in a US observational birth cohort not selected for any disease (N = 616) The relatively high prevalence rates we observed may reflect continued rise of peanut allergy prevalence in the US, consistent with the rising trend in self-reported peanut allergy that Sicherer et al. observed between 1997, 2002, and 2008.3 Additionally, our cohort was based in the Northeast, where rates of peanut sensitization may be higher relative to western US regions.9 Application of a more stringent definition for peanut allergy than self-reported allergy or “clinical allergy,” such as the peanut sIgE ≥ 14 kU/L decision point for 90% specificity reported by Sampson,10 yielded a prevalence of 2.9% (Table 2), which is still higher than previously reported estimates by any criteria (Table 1). Our strictest definition of peanut allergy, requiring peanut sIgE greater than the 90% specificity decision point and prescribed epinephrine auto-injector, yielded a prevalence of 2.0%. While it could be argued that despite Project Viva’s general health goals, the relatively high prevalence rates we observed could be due to food allergic families preferentially returning for mid-childhood visits, the rates of parental atopy (assessed prenatally) among those who did and did not present at mid-childhood were not significantly different, supporting that selection bias was not at play. As we assessed peanut allergy using different criteria within this cohort, we also assessed for agreement between the definitions. Agreement was the highest between self-reported peanut allergy and peanut allergy defined by both peanut sensitization and prescribed epinephrine auto-injector (Κ = 0.75, 95%CI 0.62–0.88). There was moderate agreement between self-reported peanut allergy and peanut allergy defined by both the 90% specificity decision point and prescribed epinephrine auto-injector (Κ = 0.57, 95%CI 0.38–0.76), and less agreement between self-reported peanut allergy and peanut allergy defined by the 90% specificity decision point only (Κ = 0.49, 95%CI 0.31–0.68). Each epidemiologic method for assessing peanut allergy prevalence has strengths and limitations. Double-blind, placebo-controlled food challenges are the gold standard for clinical peanut allergy diagnosis, but these are challenging to implement in large, unselected cohorts and have not been done in unselected US cohorts.2 As diagnostic adjuncts, component resolved diagnostics may also be increasingly implemented in epidemiologic cohorts going forward. In this letter, we have provided prevalence estimates according to several criteria that can be compared to one another and to previous estimates. Our results come from a US cohort of children not selected for allergy or any disease, and they support that peanut allergy is an increasingly prevalent condition.

Prenatal and Infant Exposure to Acetaminophen and Ibuprofen and the Risk for Wheeze and Asthma in Children

BACKGROUND Several studies have reported an association between use of over-the-counter antipyretics during pregnancy or infancy and increased asthma risk. An important potential limitation of these observational studies is confounding by indication. OBJECTIVES We investigated the association of antipyretic intake during pregnancy and during the first year of life (infancy) with asthma-related outcomes before and after controlling for early-life respiratory tract infections. METHODS We included 1490 mother-child pairs in Project Viva, a longitudinal prebirth cohort study. We categorized prenatal acetaminophen exposure as the maximum intake (never, 1-9 times, or ≥10 times) in early pregnancy or midpregnancy and ibuprofen intake as presence or absence in early pregnancy. We expressed intake of antipyretics in infancy as never, 1 to 5 times, 6 to 10 times, or more than 10 times. We examined the associations of acetaminophen and ibuprofen (per unit increase in exposure category) during pregnancy and infancy with wheeze, asthma, and allergen sensitization in early childhood (3-5 years of age, n = 1419) and midchildhood (7-10 years of age, n = 1220). RESULTS Unadjusted models showed an increased asthma risk in early childhood for higher infant acetaminophen (odds ratio [OR], 1.21; 95% CI 1.04-1.41) and ibuprofen (OR, 1.35; 95% CI, 1.19-1.52) intake. Controlling for respiratory tract infections attenuated estimates for acetaminophen (OR, 1.03; 95% CI, 0.88-1.22) and ibuprofen (OR, 1.19; 95% CI, 1.05-1.36). Prenatal acetaminophen was associated with increased asthma (OR, 1.26; 95% CI, 1.02-1.58) in early childhood but not midchildhood. CONCLUSIONS Adjustment for respiratory tract infections in early life substantially diminished associations between infant antipyretic use and early childhood asthma. Respiratory tract infections should be accounted for in studies of antipyretics and asthma to mitigate bias caused by confounding by indication.

Alu and LINE-1 methylation and lung function in the normative ageing study

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.

Allergen exposure modifies the relation of sensitization to fraction of exhaled nitric oxide levels in children at risk for allergy and asthma

BACKGROUND Studies on airway inflammation, measured as fraction of exhaled nitric oxide (FENO), have focused on its relation to control of asthma, but the contribution of allergen exposure to the increase in FENO levels is unknown. OBJECTIVE We evaluated (1) whether FENO levels were increased in children with allergic sensitization or asthma; (2) whether specific allergen exposure increased FENO levels in sensitized, but not unsensitized, children; and (3) whether sedentary behavior increased FENO levels independent of allergen exposures. METHODS At age 12 years, in a birth cohort of children with a parental history of allergy or asthma, we measured bed dust allergen (dust mite, cat, and cockroach) by means of ELISA, specific allergic sensitization primarily based on specific IgE levels, and respiratory disease (current asthma, rhinitis, and wheeze) and hours of television viewing/video game playing by means of questionnaire. Children performed spirometric maneuvers before and after bronchodilator responses and had FENO levels measured by using electrochemical detection methods (NIOX MINO). RESULTS FENO levels were increased in children with current asthma (32.2 ppb), wheeze (27.0 ppb), or rhinitis (23.2 ppb) compared with subjects without these respective symptoms/diagnoses (16.4-16.6 ppb, P < .005 for all comparisons). Allergic sensitization to indoor allergens (cat, dog, and dust mite) predicted higher FENO levels and explained one third of the variability in FENO levels. FENO levels were highest in children both sensitized and exposed to dust mite. Greater than 10 hours of weekday television viewing was associated with a 0.64-log increase in FENO levels after controlling for indoor allergen exposure, body mass index, and allergic sensitization. CONCLUSION Allergen exposures and sedentary behavior (television viewing/video game playing) might increase airway inflammation, which was measured as the FENO.

Asthma Metabolomics and the Potential for Integrative Omics in Research and the Clinic

&NA; Asthma is a complex disease well‐suited to metabolomic profiling, both for the development of novel biomarkers and for the improved understanding of pathophysiology. In this review, we summarize the 21 existing metabolomic studies of asthma in humans, all of which reported significant findings and concluded that individual metabolites and metabolomic profiles measured in exhaled breath condensate, urine, plasma, and serum could identify people with asthma and asthma phenotypes with high discriminatory ability. There was considerable consistency across the studies in terms of the reported biomarkers, regardless of biospecimen, profiling technology, and population age. In particular, acetate, adenosine, alanine, hippurate, succinate, threonine, and trans‐aconitate, and pathways relating to hypoxia response, oxidative stress, immunity, inflammation, lipid metabolism and the tricarboxylic acid cycle were all identified as significant in at least two studies. There were also a number of nonreplicated results; however, the literature is not yet sufficiently developed to determine whether these represent spurious findings or reflect the substantial heterogeneity and limited statistical power in the studies and their methods to date. This review highlights the need for additional asthma metabolomic studies to explore these issues, and, further, the need for standardized methods in the way these studies are conducted. We conclude by discussing the potential of translation of these metabolomic findings into clinically useful biomarkers and the crucial role that integrated omics is likely to play in this endeavor.

The metabolomics of asthma control: a promising link between genetics and disease

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.

Diagnostic accuracy of the bronchodilator response in children

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.