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1.
Proc Natl Acad Sci U S A ; 116(32): 15883-15888, 2019 Aug 06.
Artigo em Inglês | MEDLINE | ID: mdl-31332016

RESUMO

Childhood asthma is a major public health concern and has significant adverse impacts on the lives of the children and their families, and on society. There is an emerging link between air pollution, which is ubiquitous in our environment, particularly in urban centers, and incident childhood asthma. Here, using data from 3 successive cohorts recruited from the same 9 communities in southern California over a span of 20 y (1993 to 2014), we estimated asthma incidence using G-computation under hypothetical air pollution exposure scenarios targeting nitrogen dioxide (NO2) and particulate matter <2.5 µm (PM2.5) in separate interventions. We reported comparisons of asthma incidence under each hypothetical air pollution intervention with incidence under the observed natural course of exposure; results that may be more tangible for policymakers compared with risk ratios. Model results indicated that childhood asthma incidence rates would have been statistically significantly higher had the observed reduction in ambient NO2 in southern California not occurred in the 1990s and early 2000s, and asthma incidence rates would have been significantly lower had NO2 been lower than what it was observed to be. For example, compliance with a hypothetical standard of 20 ppb NO2 was estimated to result in 20% lower childhood asthma incidence (95% CI, -27% to -11%) compared with the exposure that actually occurred. The findings for hypothetical PM2.5 interventions, although statistically significant, were smaller in magnitude compared with results for the hypothetical NO2 interventions. Our results suggest a large potential public health benefit of air pollutant reduction in reduced incidence of childhood asthma.

2.
Environ Int ; 130: 104935, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31238265

RESUMO

BACKGROUND: Air pollution exposure has been shown to increase the risk of obesity and metabolic dysfunction in animal models and human studies. However, the metabolic pathways altered by air pollution exposure are unclear, especially in adolescents and young adults who are at a critical period in the development of cardio-metabolic diseases. OBJECTIVES: The aim of this study was to examine the associations between air pollution exposure and indices of fatty acid and amino acid metabolism. METHODS: A total of 173 young adults (18-23 years) from eight Children's Health Study (CHS) Southern California communities were examined from 2014 to 2018. Near-roadway air pollution (NRAP) exposure (freeway and non-freeway) and regional air pollution exposure (nitrogen dioxide, ozone and particulate matter) during one year before the study visit were estimated based on participants' residential addresses. Serum concentrations of 64 targeted metabolites including amino acids, acylcarnitines, non-esterified fatty acid (NEFA) and glycerol were measured in fasting serum samples. Principal component analysis of metabolites was performed to identify metabolite clusters that represent key metabolic pathways. Mixed effects models were used to analyze the associations of air pollution exposure with metabolomic principal component (PC) scores and individual metabolite concentrations adjusting for potential confounders. RESULTS: Higher lagged one-year averaged non-freeway NRAP exposure was associated with higher concentrations of NEFA oxidation byproducts and higher NEFA-related PC score (all p's ≤ 0.038). The effect sizes were larger among obese individuals (interaction p = 0.047). Among females, higher freeway NRAP exposure was also associated with a higher NEFA-related PC score (p = 0.042). Among all participants, higher freeway NRAP exposure was associated with a lower PC score for lower concentrations of short- and median-chain acylcarnitines (p = 0.044). CONCLUSIONS: Results of this study indicate that NRAP exposure is associated with altered fatty acid metabolism, which could contribute to the metabolic perturbation in obese youth.

3.
BMC Pregnancy Childbirth ; 19(1): 189, 2019 May 30.
Artigo em Inglês | MEDLINE | ID: mdl-31146718

RESUMO

BACKGROUND: The burden of childhood and adult obesity disproportionally affects Hispanic and African-American populations in the US, and these groups as well as populations with lower income and education levels are disproportionately affected by environmental pollution. Pregnancy is a critical developmental period where maternal exposures may have significant impacts on infant and childhood growth as well as the future health of the mother. We initiated the "Maternal And Developmental Risks from Environmental and Social Stressors (MADRES)" cohort study to address critical gaps in understanding the increased risk for childhood obesity and maternal obesity outcomes among minority and low-income women in urban Los Angeles. METHODS: The MADRES cohort is specifically examining whether pre- and postpartum environmental exposures, in addition to exposures to psychosocial and built environment stressors, lead to excessive gestational weight gain and postpartum weight retention in women and to perturbed infant growth trajectories and increased childhood obesity risk through altered psychological, behavioral and/or metabolic responses. The ongoing MADRES study is a prospective pregnancy cohort of 1000 predominantly lower-income, Hispanic women in Los Angeles, CA. Enrollment in the MADRES cohort is initiated prior to 30 weeks gestation from partner community health clinics in Los Angeles. Cohort participants are followed through their pregnancies, at birth, and during the infant's first year of life through a series of in-person visits with interviewer-administered questionnaires, anthropometric measurements and biospecimen collection as well as telephone interviews conducted with the mother. DISCUSSION: In this paper, we outline the study rationale and data collection protocol for the MADRES cohort, and we present a profile of demographic, health and exposure characteristics for 291 participants who have delivered their infants, out of 523 participants enrolled in the study from November 2015 to October 2018 from four community health clinics in Los Angeles. Results from the MADRES cohort could provide a powerful rationale for regulation of targeted chemical environmental components, better transportation and urban design policies, and clinical recommendations for stress-coping strategies and behavior to reduce lifelong obesity risk.

4.
Environ Int ; 128: 310-323, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31078000

RESUMO

BACKGROUND: Accurate estimation of nitrogen dioxide (NO2) and nitrogen oxide (NOx) concentrations at high spatiotemporal resolutions is crucial for improving evaluation of their health effects, particularly with respect to short-term exposures and acute health outcomes. For estimation over large regions like California, high spatial density field campaign measurements can be combined with more sparse routine monitoring network measurements to capture spatiotemporal variability of NO2 and NOx concentrations. However, monitors in spatially dense field sampling are often highly clustered and their uneven distribution creates a challenge for such combined use. Furthermore, heterogeneities due to seasonal patterns of meteorology and source mixtures between sub-regions (e.g. southern vs. northern California) need to be addressed. OBJECTIVES: In this study, we aim to develop highly accurate and adaptive machine learning models to predict high-resolution NO2 and NOx concentrations over large geographic regions using measurements from different sources that contain samples with heterogeneous spatiotemporal distributions and clustering patterns. METHODS: We used a comprehensive Kruskal-K-means method to cluster the measurement samples from multiple heterogeneous sources. Spatiotemporal cluster-based bootstrap aggregating (bagging) of the base mixed-effects models was then applied, leveraging the clusters to obtain balanced and less correlated training samples for less bias and improvement in generalization. Further, we used the machine learning technique of grid search to find the optimal interaction of temporal basis functions and the scale of spatial effects, which, together with spatiotemporal covariates, adequately captured spatiotemporal variability in NO2 and NOx at the state and local levels. RESULTS: We found an optimal combination of four temporal basis functions and 200 m scale spatial effects for the base mixed-effects models. With the cluster-based bagging of the base models, we obtained robust predictions with an ensemble cross validation R2 of 0.88 for both NO2 and NOx [RMSE (RMSEIQR): 3.62 ppb (0.28) and 9.63 ppb (0.37) respectively]. In independent tests of random sampling, our models achieved similarly strong performance (R2 of 0.87-0.90; RMSE of 3.97-9.69 ppb; RMSEIQR of 0.21-0.27), illustrating minimal over-fitting. CONCLUSIONS: Our approach has important implications for fusing data from highly clustered and heterogeneous measurement samples from multiple data sources to produce highly accurate concentration estimates of air pollutants such as NO2 and NOx at high resolution over a large region.

5.
JAMA ; 321(19): 1906-1915, 2019 05 21.
Artigo em Inglês | MEDLINE | ID: mdl-31112259

RESUMO

Importance: Exposure to air pollutants is a well-established cause of asthma exacerbation in children; whether air pollutants play a role in the development of childhood asthma, however, remains uncertain. Objective: To examine whether decreasing regional air pollutants were associated with reduced incidence of childhood asthma. Design, Setting, and Participants: A multilevel longitudinal cohort drawn from 3 waves of the Southern California Children's Health Study over a period of air pollution decline. Each cohort was followed up from 4th to 12th grade (8 years): 1993-2001, 1996-2004, and 2006-2014. Final follow-up for these data was June 2014. Population-based recruitment was from public elementary schools. A total of 4140 children with no history of asthma and residing in 1 of 9 Children's Health Study communities at baseline were included. Exposures: Annual mean community-level ozone, nitrogen dioxide, and particulate matter less than 10 µm (PM10) and less than 2.5 µm (PM2.5) in the baseline year for each of 3 cohorts. Main Outcomes and Measures: Prospectively identified incident asthma, collected via questionnaires during follow-up. Results: Among the 4140 children included in this study (mean [SD] age at baseline, 9.5 [0.6] years; 52.6% female [n = 2 179]; 58.6% white [n = 2273]; and 42.2% Hispanic [n = 1686]), 525 incident asthma cases were identified. For nitrogen dioxide, the incidence rate ratio (IRR) for asthma was 0.80 (95% CI, 0.71-0.90) for a median reduction of 4.3 parts per billion, with an absolute incidence rate decrease of 0.83 cases per 100 person-years. For PM2.5, the IRR was 0.81 (95% CI, 0.67-0.98) for a median reduction of 8.1 µg/m3, with an absolute incidence rate decrease of 1.53 cases per 100 person-years. For ozone, the IRR for asthma was 0.85 (95% CI, 0.71-1.02) for a median reduction of 8.9 parts per billion, with an absolute incidence rate decrease of 0.78 cases per 100 person-years. For PM10, the IRR was 0.93 (95% CI, 0.82-1.07) for a median reduction of 4.0 µg/m3, with an absolute incidence rate decrease of 0.46 cases per 100 person-years. Conclusions and Relevance: Among children in Southern California, decreases in ambient nitrogen dioxide and PM2.5 between 1993 and 2014 were significantly associated with lower asthma incidence. There were no statistically significant associations for ozone or PM10.


Assuntos
Poluentes Atmosféricos/efeitos adversos , Poluição do Ar/efeitos adversos , Asma/epidemiologia , Dióxido de Nitrogênio/efeitos adversos , Material Particulado/efeitos adversos , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Asma/etiologia , California/epidemiologia , Criança , Exposição Ambiental/efeitos adversos , Exposição Ambiental/análise , Feminino , Humanos , Incidência , Estudos Longitudinais , Masculino , Dióxido de Nitrogênio/análise , Ozônio/efeitos adversos , Ozônio/análise , Material Particulado/análise
6.
Int J Epidemiol ; 48(3): 899-907, 2019 Jun 01.
Artigo em Inglês | MEDLINE | ID: mdl-31005996

RESUMO

BACKGROUND: Observational associations between asthma and obesity are well established, but inferring causality is challenging. We leveraged publicly available summary statistics to ascertain the causal direction between asthma and obesity via Mendelian randomization in European-ancestry adults. METHODS: We performed two-sample bi-directional Mendelian randomization analysis using publicly available genome-wide association studies summary statistics. Single nucleotide polymorphisms associated with asthma and body mass index at genome-wide significance were combined using a fixed effect meta-analysis in each direction. An extensive sensitivity analysis was considered. RESULTS: There was evidence in support of increasing causal effect of body mass index on risk of asthma (odds ratio 1.18 per unit increase, 95% confidence interval (CI) (1.11, 1.25), P = 2 × 10-8. No significant causal effect of asthma on adult body mass index was observed [estimate -0.004, 95% CI (-0.018, 0.009), P = 0.553]. CONCLUSIONS: Our results confirmed that in European-ancestry populations, adult body mass index is likely to be causally linked to the risk of asthma; yet the effect of asthma on body mass index is small, if present at all.

7.
Gut Microbes ; : 1-8, 2019 Apr 16.
Artigo em Inglês | MEDLINE | ID: mdl-30991877

RESUMO

BACKGROUND: A western high fat, high carbohydrate diet has been shown to be associated with decreased gut bacterial diversity and reductions in beneficial bacteria. This gut bacteria dysbiosis could develop in early life and contribute to chronic disease risk such as obesity, type 2 diabetes and non-alcoholic fatty liver disease. OBJECTIVE: To determine how dietary macronutrients are associated with the relative abundance of gut bacteria in healthy adolescents. METHODS: Fifty-two obese participants (12-19 years) from two studies, many who were primarily of Hispanic background, provided fecal samples for 16S rRNA gene sequencing. Dietary macronutrients were assessed using 24-hour diet recalls and body composition was assessed using DEXA. General regression models assuming a negative binomial distribution were used to examine the associations between gut bacteria and dietary fiber, saturated fat, unsaturated fats, protein, added sugar, total sugar and free fructose after adjusting for age, gender, race/ethnicity, body fat percentage, study and caloric intake. RESULTS: The genera Eubacterium (Benjamini-Hochberg (BH) corrected p-value = 0.10) and Streptococcus (BH corrected p-value = 0.04) were inversely associated with dietary fructose intake. There were no other significant associations between abundances of gut microbes and other dietary macronutrients, including fiber, fat, protein, total sugar or added sugar. CONCLUSIONS: High dietary fructose was associated with lower abundance of the beneficial microbes Eubacterium and Streptococcus, which are involved with carbohydrate metabolism.

8.
BMC Med Res Methodol ; 19(1): 70, 2019 03 29.
Artigo em Inglês | MEDLINE | ID: mdl-30925901

RESUMO

BACKGROUND: Chronic respiratory symptoms involving bronchitis, cough and phlegm in children are underappreciated but pose a significant public health burden. Efforts for prevention and management could be supported by an understanding of the relative importance of determinants, including environmental exposures. Thus, we aim to develop a prediction model for bronchitic symptoms. METHODS: Schoolchildren from the population-based southern California Children's Health Study were visited annually from 2003 to 2012. Bronchitic symptoms over the prior 12 months were assessed by questionnaire. A gradient boosting model was fit using groups of risk factors (including traffic/air pollution exposures) for all children and by asthma status. Training data consisted of one observation per participant in a random study year (for 50% of participants). Validation data consisted of: (1) a random (later) year in the same participants (within-participant); (2) a random year in participants excluded from the training data (across-participant). RESULTS: At baseline, 13.2% of children had asthma and 18.1% reported bronchitic symptoms. Models performed similarly within- and across-participant. Previous year symptoms/medication use provided much of the predictive ability (across-participant area under the receiver operating characteristic curve (AUC): 0.76 vs 0.78 for all risk factors, in all participants). Traffic/air pollution exposures added modestly to prediction as did body mass index percentile, age and parent stress. CONCLUSIONS: Regardless of asthma status, previous symptoms were the most important predictors of current symptoms. Traffic/air pollution variables contribute modest predictive information, but impact large populations. Methods proposed here could be generalized to personalized exacerbation predictions in future longitudinal studies to support targeted prevention efforts.

9.
Environ Int ; 126: 445-453, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-30844580

RESUMO

OBJECTIVE: To examine the prospective associations between exposure to perfluoroalkyl substances (PFASs) and longitudinal measurements of glucose metabolism in high-risk overweight and obese Hispanic children. METHODS: Forty overweight and obese Hispanic children (8-14 years) from urban Los Angeles underwent clinical measures and 2-hour oral glucose tolerance tests (OGTT) at baseline and a follow-up visit (range: 1-3 years after enrollment). Baseline plasma perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), perfluorohexane sulfonic acid (PFHxS), and the plasma metabolome were measured by liquid-chromatography with high-resolution mass spectrometry. Multiple linear regression models were used to assess the association between baseline PFASs and changes in glucose homeostasis over follow-up. A metabolome-wide association study coupled with pathway enrichment analysis was performed to evaluate metabolic dysregulation associated with plasma PFASs concentrations. We performed a structural integrated analysis aiming to characterize the joint impact of all factors and to identify latent clusters of children with alterations in glucose homeostasis, based on their exposure and metabolomics profile. RESULTS: Each ln (ng/ml) increase in PFOA and PFHxS concentrations was associated with a 30.6 mg/dL (95% CI: 8.8-52.4) and 10.2 mg/dL (95% CI: 2.7-17.7) increase in 2-hour glucose levels, respectively. A ln (ng/ml) increase in PFHxS concentrations was also associated with 17.8 mg/dL increase in the glucose area under the curve (95% CI: 1.5-34.1). Pathway enrichment analysis showed significant alterations of lipids (e.g., glycosphingolipids, linoleic acid, and de novo lipogenesis), and amino acids (e.g., aspartate and asparagine, tyrosine, arginine and proline) in association to PFASs exposure. The integrated analysis identified a cluster of children with increased 2-h glucose levels over follow up, characterized by increased PFAS levels and altered metabolite patterns. CONCLUSIONS: This proof-of-concept analysis shows that higher PFAS exposure was associated with dysregulation of several lipid and amino acid pathways and longitudinal alterations in glucose homeostasis in Hispanic youth. Larger studies are needed to confirm these findings and fully elucidate the underlying biological mechanisms.

10.
BMC Public Health ; 19(1): 253, 2019 Feb 28.
Artigo em Inglês | MEDLINE | ID: mdl-30819155

RESUMO

BACKGROUND: Disproportionately high rates of maternal overweight and obesity among the Hispanic population before, during, and after pregnancy pose serious health concerns for both mothers (e.g., preeclampsia, gestational diabetes, weight retention) and children (e.g., elevated lifelong obesity risk). A growing body of evidence implicates environmental exposures (e.g., air pollution, metals) and social stressors (e.g., poverty, violence) in contributing to obesity-related biobehavioral processes, such as physical activity, dietary intake, perceived stress, and cortisol regulation. However, current understanding of the role of environmental exposures and social stressors on obesity-related biobehavioral processes is limited by infrequent, inter-individual measurement, and lack of personal exposure monitoring. METHODS: The "Maternal and Developmental Risks from Environmental and Social Stressors" (MADRES) real-time and personal sampling study examines the within-subject day-level effects of environmental and social stressors on maternal pre- and post-partum obesity-related biobehavioral responses. Among a cohort of 65 low-income, Hispanic women in urban Los Angeles, this study uses innovative personal, real-time data capture strategies (e.g., ecological momentary assessment [EMA], personal exposure monitoring, geolocation monitoring, accelerometry) to repeatedly assess obesity-related processes during the 1st and 3rd trimester, and at 4-6 months postpartum. Day-level effects of environmental exposures and social stressors on women's physical activity, diet, perceived stress and salivary cortisol measured across repeated days will be tested using multilevel modeling. DISCUSSION: Hispanic women of childbearing age bear a disproportionately high burden of obesity, and this population is also unduly exposed to numerous obesogenic settings. By using innovative real-time data capture strategies, the current study will uncover the daily impacts of environmental and social stressor exposures on women's obesity-related biobehavioral responses, which over time can lead to excessive gestational weight gain, postpartum weight retention and can pose serious consequences for both mother and child. Findings from the real-time and personal sampling study will identify key mechanistic targets for policy, clinical, and programmatic interventions, with the potential for broad-reaching public health impacts.


Assuntos
Exercício/psicologia , Hispano-Americanos/psicologia , Mães/psicologia , Obesidade/etiologia , Período Pós-Parto/psicologia , Pobreza/psicologia , Estresse Psicológico/complicações , Adulto , Feminino , Humanos , Estudos Longitudinais , Los Angeles , Mães/estatística & dados numéricos , Obesidade/psicologia , Pobreza/estatística & dados numéricos , Gravidez , Ganho de Peso
11.
Environ Int ; 125: 97-106, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30711654

RESUMO

BACKGROUND: Increasingly ensemble learning-based spatiotemporal models are being used to estimate residential air pollution exposures in epidemiological studies. While these machine learning models typically have improved performance, they suffer from exposure measurement error that is inherent in all models. Our objective is to develop a framework to formally assess shared, multiplicative measurement error (SMME) in our previously published three-stage, ensemble learning-based nitrogen oxides (NOx) model to identify its spatial and temporal patterns and predictors. METHODS: By treating the ensembles as an external dosimetry system, we quantified shared and unshared, multiplicative and additive (SUMA) measurement error components in our exposure model. We used generalized additive models (GAMs) with a smooth term for location to identify geographic locations with significantly elevated SMME and explain their spatial and temporal determinants. RESULTS: We found evidence of significant shared and unshared multiplicative error (p < 0.0001) in our ensemble-learning based spatiotemporal NOx model predictions. Unshared multiplicative error was 26 times larger than SMME. We observed significant geographic (p < 0.0001) and temporal variation in SMME with the majority (43%) of predictions with elevated SMME occurring in the earliest time-period (1992-2000). Densely populated urban prediction regions with complex air pollution sources generally exhibited highest odds of elevated SMME. CONCLUSIONS: We developed a novel statistical framework to formally evaluate the magnitude and drivers of SMME in ensemble learning-based exposure models. Our framework can be used to inform building future improved exposure models.

12.
JMIR Mhealth Uhealth ; 7(2): e11201, 2019 02 07.
Artigo em Inglês | MEDLINE | ID: mdl-30730297

RESUMO

BACKGROUND: Time-resolved quantification of physical activity can contribute to both personalized medicine and epidemiological research studies, for example, managing and identifying triggers of asthma exacerbations. A growing number of reportedly accurate machine learning algorithms for human activity recognition (HAR) have been developed using data from wearable devices (eg, smartwatch and smartphone). However, many HAR algorithms depend on fixed-size sampling windows that may poorly adapt to real-world conditions in which activity bouts are of unequal duration. A small sliding window can produce noisy predictions under stable conditions, whereas a large sliding window may miss brief bursts of intense activity. OBJECTIVE: We aimed to create an HAR framework adapted to variable duration activity bouts by (1) detecting the change points of activity bouts in a multivariate time series and (2) predicting activity for each homogeneous window defined by these change points. METHODS: We applied standard fixed-width sliding windows (4-6 different sizes) or greedy Gaussian segmentation (GGS) to identify break points in filtered triaxial accelerometer and gyroscope data. After standard feature engineering, we applied an Xgboost model to predict physical activity within each window and then converted windowed predictions to instantaneous predictions to facilitate comparison across segmentation methods. We applied these methods in 2 datasets: the human activity recognition using smartphones (HARuS) dataset where a total of 30 adults performed activities of approximately equal duration (approximately 20 seconds each) while wearing a waist-worn smartphone, and the Biomedical REAl-Time Health Evaluation for Pediatric Asthma (BREATHE) dataset where a total of 14 children performed 6 activities for approximately 10 min each while wearing a smartwatch. To mimic a real-world scenario, we generated artificial unequal activity bout durations in the BREATHE data by randomly subdividing each activity bout into 10 segments and randomly concatenating the 60 activity bouts. Each dataset was divided into ~90% training and ~10% holdout testing. RESULTS: In the HARuS data, GGS produced the least noisy predictions of 6 physical activities and had the second highest accuracy rate of 91.06% (the highest accuracy rate was 91.79% for the sliding window of size 0.8 second). In the BREATHE data, GGS again produced the least noisy predictions and had the highest accuracy rate of 79.4% of predictions for 6 physical activities. CONCLUSIONS: In a scenario with variable duration activity bouts, GGS multivariate segmentation produced smart-sized windows with more stable predictions and a higher accuracy rate than traditional fixed-size sliding window approaches. Overall, accuracy was good in both datasets but, as expected, it was slightly lower in the more real-world study using wrist-worn smartwatches in children (BREATHE) than in the more tightly controlled study using waist-worn smartphones in adults (HARuS). We implemented GGS in an offline setting, but it could be adapted for real-time prediction with streaming data.

13.
Nat Commun ; 10(1): 713, 2019 02 12.
Artigo em Inglês | MEDLINE | ID: mdl-30755607

RESUMO

Metabolic syndrome is characterized by disturbances in glucose homeostasis and the development of low-grade systemic inflammation, which increase the risk to develop type 2 diabetes mellitus (T2DM). Type-2 innate lymphoid cells (ILC2s) are a recently discovered immune population secreting Th2 cytokines. While previous studies show how ILC2s can play a critical role in the regulation of metabolic homeostasis in the adipose tissue, a therapeutic target capable of modulating ILC2 activation has yet to be identified. Here, we show that GITR, a member of the TNF superfamily, is expressed on both murine and human ILC2s. Strikingly, we demonstrate that GITR engagement of activated, but not naïve, ILC2s improves glucose homeostasis, resulting in both protection against insulin resistance onset and amelioration of established insulin- resistance. Together, these results highlight the critical role of GITR as a novel therapeutic molecule against T2DM and its fundamental role as an immune checkpoint for activated ILC2s.


Assuntos
Diabetes Mellitus Tipo 2/imunologia , Proteína Relacionada a TNFR Induzida por Glucocorticoide/imunologia , Linfócitos/imunologia , Linfócitos/metabolismo , Tecido Adiposo/imunologia , Tecido Adiposo/metabolismo , Animais , Citocinas/imunologia , Citocinas/metabolismo , Diabetes Mellitus Tipo 2/metabolismo , Proteína Relacionada a TNFR Induzida por Glucocorticoide/metabolismo , Glucose/metabolismo , Homeostase , Humanos , Imunidade Inata , Resistência à Insulina , Camundongos , Camundongos Endogâmicos C57BL , Camundongos Knockout , Células Th2/metabolismo
14.
Am J Clin Nutr ; 109(1): 99-108, 2019 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-30596809

RESUMO

Background: Air pollution exposures are novel contributors to the growing childhood obesity epidemic. One possible mechanism linking air pollution exposures and obesity is through changes in food consumption patterns. Objective: The aim of this study was to examine the longitudinal association between childhood exposure to air pollutants and changes in diet among adolescents. Design: School-age children were enrolled in the Southern California Children's Health Study during 1993-1994 (n = 3100) and were followed for 4-8 y. Community-level regional air pollutants [e.g., nitrogen dioxide (NO2), elemental carbon (EC), and fine particles with aerodynamic diameter <2.5 µm (PM2.5)] were measured at central monitoring stations. Line dispersion modeling was used to estimate concentrations of traffic-related air pollutants based on nitrogen oxides (NOx) at participants' residential addresses. In addition, self-reported diet information was collected annually using a structured youth/adolescent food-frequency questionnaire during 1997-2001. Generalized linear mixed-effects models were used in the association analyses. Results: Higher exposures to regional and traffic-related air pollutants were associated with intake of a high-trans-fat diet, after adjusting for confounders including socioeconomic status and access to fast food in the community. A 2-SD (12.2 parts per billion) increase in regional NO2 exposure was associated with a 34% increased risk of consuming a high-trans-fat diet compared with a low-trans-fat diet (OR: 1.34; 95% CI: 1.05, 1.72). In addition, higher exposures to acid vapor, EC, PM2.5, and non-freeway NOx were all associated with higher consumption of dietary trans fat (all P < 0.04). Notably, higher exposures to regional NO2, acid vapor, and EC were also associated with a higher consumption of fast food (all P < 0.05). Conclusions: Childhood exposures to regional and traffic-related air pollutants were associated with increased consumption by adolescents of trans fat and fast foods. Our results indicate that air pollution exposures may contribute to obesogenic behaviors. This study was registered at clinicaltrials.gov as NCT03379298.

15.
J Allergy Clin Immunol ; 143(6): 2062-2074, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30579849

RESUMO

BACKGROUND: Epigenetic mechanisms, including methylation, can contribute to childhood asthma. Identifying DNA methylation profiles in asthmatic patients can inform disease pathogenesis. OBJECTIVE: We sought to identify differential DNA methylation in newborns and children related to childhood asthma. METHODS: Within the Pregnancy And Childhood Epigenetics consortium, we performed epigenome-wide meta-analyses of school-age asthma in relation to CpG methylation (Illumina450K) in blood measured either in newborns, in prospective analyses, or cross-sectionally in school-aged children. We also identified differentially methylated regions. RESULTS: In newborns (8 cohorts, 668 cases), 9 CpGs (and 35 regions) were differentially methylated (epigenome-wide significance, false discovery rate < 0.05) in relation to asthma development. In a cross-sectional meta-analysis of asthma and methylation in children (9 cohorts, 631 cases), we identified 179 CpGs (false discovery rate < 0.05) and 36 differentially methylated regions. In replication studies of methylation in other tissues, most of the 179 CpGs discovered in blood replicated, despite smaller sample sizes, in studies of nasal respiratory epithelium or eosinophils. Pathway analyses highlighted enrichment for asthma-relevant immune processes and overlap in pathways enriched both in newborns and children. Gene expression correlated with methylation at most loci. Functional annotation supports a regulatory effect on gene expression at many asthma-associated CpGs. Several implicated genes are targets for approved or experimental drugs, including IL5RA and KCNH2. CONCLUSION: Novel loci differentially methylated in newborns represent potential biomarkers of risk of asthma by school age. Cross-sectional associations in children can reflect both risk for and effects of disease. Asthma-related differential methylation in blood in children was substantially replicated in eosinophils and respiratory epithelium.

16.
Environ Epidemiol ; 2(2)2018 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30519674

RESUMO

Background: Bronchitic symptoms in children pose a significant clinical and public health burden. Exposures to criteria air pollutants affect bronchitic symptoms, especially in children with asthma. Less is known about near-roadway exposures. Methods: Bronchitic symptoms (bronchitis, chronic cough, or phlegm) in the past 12 months were assessed annually with 8 to 9 years of follow-up on 6757 children from the southern California Children's Health Study. Residential exposure to freeway and non-freeway near-roadway air pollution was estimated using a line-source dispersion model. Mixed-effects logistic regression models were used to relate near-roadway air pollutant exposures to bronchitic symptoms among children with and without asthma. Results: Among children with asthma, a two standard deviation increase in non-freeway exposures (odds ratio [OR]: 1.44; 95% confidence interval [CI]: 1.17-1.78) and freeway exposures (OR: 1.31; 95% CI: 1.06-1.60) were significantly associated with increased risk of bronchitic symptoms. Among children without asthma, only non-freeway exposures had a significant association (OR: 1.14; 95% CI: 1.00-1.29). Associations were strongest among children living in communities with lower regional particulate matter. Conclusions: Near-roadway air pollution was associated with bronchitic symptoms, especially among children with asthma and those living in communities with lower regional particulate matter. Better characterization of traffic pollutants from non-freeway roads is needed since many children live in close proximity to this source.

17.
Obesity (Silver Spring) ; 26(12): 1938-1948, 2018 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-30358166

RESUMO

OBJECTIVE: Asthmatic children who develop obesity through adolescence have poorer disease outcomes compared with those who do not. This study aimed to characterize the biology of childhood asthma complicated by adult obesity. METHODS: Gene expression networks are powerful statistical tools for characterizing human disease that leverage the putative coregulatory relationships of genes to infer relevant biological pathways. Weighted gene coexpression network analysis of gene expression data was performed in whole blood from 514 adult asthmatic subjects. Then, module preservation and association replication analyses were performed in 418 subjects from two independent asthma cohorts (one pediatric and one adult). RESULTS: A multivariate model was identified in which three gene coexpression network modules were associated with incident obesity in the discovery cohort (each P < 0.05). Two module memberships were enriched for genes in pathways related to platelets, integrins, extracellular matrix, smooth muscle, NF-κB signaling, and Hedgehog signaling. The network structures of each of the obesity modules were significantly preserved in both replication cohorts (permutation P = 9.999E-05). The corresponding module gene sets were significantly enriched for differential expression in subjects with obesity in both replication cohorts (each P < 0.05). CONCLUSIONS: The gene coexpression network profiles thus implicate multiple interrelated pathways in the biology of an important endotype of asthma with obesity.

18.
Curr Epidemiol Rep ; 5(2): 79-91, 2018 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-30319933

RESUMO

Purpose of Review: Diabetes mellitus is a top contributor to the global burden of mortality and disability in adults. There has also been a slow, but steady rise in prediabetes and type 2 diabetes in youth. The current review summarizes recent findings regarding the impact of increased exposure to air pollutants on the type 2 diabetes epidemic. Recent Findings: Human and animal studies provide strong evidence that exposure to ambient and traffic-related air pollutants such as particulate matter (PM), nitrogen dioxide (NO2), and nitrogen oxides (NOx) play an important role in metabolic dysfunction and type 2 diabetes etiology. This work is supported by recent findings that have observed similar effect sizes for increased exposure to air pollutants on clinical measures of risk for type 2 diabetes in children and adults. Further, studies indicate that these effects may be more pronounced among individuals with existing risk factors, including obesity and prediabetes. Summary: Current epidemiological evidence suggests that increased air pollution exposure contributes to alterations in insulin signaling, glucose metabolism, and beta (ß)-cell function. Future work is needed to identify the specific detrimental pollutants that alter glucose metabolism. Additionally, advanced tools and new areas of investigation present unique opportunities to study the underlying mechanisms, including intermediate pathways, that link increased air pollution exposure with type 2 diabetes onset.

19.
Environ Health ; 17(1): 64, 2018 09 14.
Artigo em Inglês | MEDLINE | ID: mdl-30213262

RESUMO

BACKGROUND: Evidence suggests that childhood near-roadway air pollution (NRAP) exposures contribute to increased body mass index (BMI); however, effects of NRAP exposure during the vulnerable periods including in utero and first year of life have yet to be established. In this study, we examined whether exposure to elevated concentrations of NRAP during in utero and/or first year of life increase childhood BMI growth. METHODS: Participants in the Children's Health Study enrolled from 2002 to 2003 with annual visits over a four-year period and who changed residences before study entry were included (n = 2318). Annual height and weight were measured and lifetime residential NRAP exposures including in utero and first year of life periods were estimated by nitrogen oxides (NOx) using the California line-source dispersion model. Linear mixed effects models assessed in utero or first year near-road freeway and non-freeway NOx exposures and BMI growth after adjusting for age, sex, race/ethnicity, parental education, Spanish questionnaire, and later childhood near-road NOx exposure. RESULTS: A two-standard deviation difference in first year of life near-road freeway NOx exposure was associated with a 0.1 kg/m2 (95% confidence interval (CI): 0.03, 0.2) faster increase in BMI growth per year and a 0.5 kg/m2 (95% CI: 0.02, 0.9) higher attained BMI at age 10 years. CONCLUSIONS: Higher exposure to early life NRAP increased the rate of change of childhood BMI and resulted in a higher attained BMI at age 10 years that were independent of later childhood exposures. These findings suggest that elevated early life NRAP exposures contribute to increased obesity risk in children.

20.
Artigo em Inglês | MEDLINE | ID: mdl-30201514

RESUMO

BACKGROUND: Asthma is a common but complex disease with racial/ethnic differences in prevalence, morbidity, and response to therapies. OBJECTIVE: We sought to perform an analysis of genetic ancestry to identify new loci that contribute to asthma susceptibility. METHODS: We leveraged the mixed ancestry of 3902 Latinos and performed an admixture mapping meta-analysis for asthma susceptibility. We replicated associations in an independent study of 3774 Latinos, performed targeted sequencing for fine mapping, and tested for disease correlations with gene expression in the whole blood of more than 500 subjects from 3 racial/ethnic groups. RESULTS: We identified a genome-wide significant admixture mapping peak at 18q21 in Latinos (P = 6.8 × 10-6), where Native American ancestry was associated with increased risk of asthma (odds ratio [OR], 1.20; 95% CI, 1.07-1.34; P = .002) and European ancestry was associated with protection (OR, 0.86; 95% CI, 0.77-0.96; P = .008). Our findings were replicated in an independent childhood asthma study in Latinos (P = 5.3 × 10-3, combined P = 2.6 × 10-7). Fine mapping of 18q21 in 1978 Latinos identified a significant association with multiple variants 5' of SMAD family member 2 (SMAD2) in Mexicans, whereas a single rare variant in the same window was the top association in Puerto Ricans. Low versus high SMAD2 blood expression was correlated with case status (13.4% lower expression; OR, 3.93; 95% CI, 2.12-7.28; P < .001). In addition, lower expression of SMAD2 was associated with more frequent exacerbations among Puerto Ricans with asthma. CONCLUSION: Ancestry at 18q21 was significantly associated with asthma in Latinos and implicated multiple ancestry-informative noncoding variants upstream of SMAD2 with asthma susceptibility. Furthermore, decreased SMAD2 expression in blood was strongly associated with increased asthma risk and increased exacerbations.

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