The Exposome Approach to Decipher the Role of Multiple Environmental and Lifestyle Determinants in Asthma

Updated insights into adverse events associated with mepolizumab: a disproportionality analysis from the FDA adverse event reporting system database

Background

Mepolizumab, a monoclonal antibody targeting interleukin-5, is used to treat severe eosinophilic asthma and other eosinophilia-related conditions. Given its growing use, there is a pressing need for the latest data to improve the understanding and management of its adverse events (AEs). This study aimed to investigate the safety of mepolizumab by analyzing the pharmacovigilance database of the US Food and Drug Administration.

Methods

The AE signals associated with mepolizumab from 2015 to 2024 were analyzed and the correlations using reporting ratios (RORs) quantified. Subgroup analyses were conducted to understand AEs in individuals ≤ 18 years of age. We also used time-to-onset (TTO) analysis to examine AE occurrence patterns.

Results

In total, 82,478 AE reports linked to mepolizumab therapy were included. Our analysis, involving 24,156 patients, revealed a predominance of female patients, with the highest incidence of AEs occurring in those aged 18-65 years. Disproportionality analyses revealed significant signals across various system organ classifications (SOCs), most prominently respiratory, thoracic, and mediastinal disorders (ROR = 5.12, 95% confidence intervals [CI] 5.03-5.21), infections and infestations (ROR = 1.86, 95% CI 1.81-1.90), and immune system disorders (ROR = 1.14, 95% CI 1.08-1.21). The highest ROR was found for asthma crisis (ROR = 104.90, 95% CI 95.31-115.44) at the preferred term (PT) level, and the other notables were coronavirus infection (ROR = 7.33, 95% CI 6.05-8.88) and coronavirus disease 2019 (COVID-19) (ROR = 1.34, 95% CI 1.23-1.47). A subgroup analysis of patients ≤ 18 years old identified four significant SOC signals, with the highest ROR in respiratory, thoracic, and mediastinal disorders (ROR = 5.28, 95% CI 4.17-6.68). PT analysis revealed significant AEs, such as wheezing, bronchospasm, and chest discomfort. TTO analysis revealed that 18.5% of AEs occurred within the first 30 days of treatment. The Weibull shape parameter indicated an "early failure-type" pattern for mepolizumab-associated AEs, underscoring the need for vigilant monitoring during the initial stages of therapy.

Conclusion

Our study highlights the importance of post-market surveillance for monitoring the safety of mepolizumab, which revealed significant AE signals, particularly for respiratory diseases, infections, and immune system complications. The association with opportunistic infections, including COVID-19, highlights the need for vigilant surveillance and further research.

Urban environment exposures, energy balance-related behaviors and their combination in preschoolers from three European countries

BACKGROUND

Urban environments are characterized by many factors that may influence children's energy balance-related behaviors (EBRBs), but there is limited research on the impact of prospective exposure to multiple urban factors in preschoolers. We evaluated prospective associations between various urban exposures and EBRBs in preschoolers across Europe, with EBRBs considered both individually and combined into lifestyle patterns.

METHODS

We used data from 4,073 preschoolers (aged 3-4 years) participating in three European cohorts from the EU Child Cohort Network: BiB (United Kingdom), EDEN (France), and INMA (Spain). Eighteen built and food environment, green spaces, road traffic and ambient air pollution exposures were characterized at residential addresses. Various EBRBs were considered as the outcomes including screen time, sleep duration and diet (fruit, vegetables, discretionary sweet foods, sweet beverages) individually and combined into unhealthy lifestyle patterns, using principal components analysis. Associations between urban exposures and outcomes were estimated using a single-exposure analysis and the deletion-substitution-addition algorithm was used to construct multi-exposure models.

RESULTS

In multi-exposure models, greater walkability and smaller distance to the nearest road were associated with higher scores on the unhealthy lifestyle patterns. Likewise, greater walkability was associated with higher screen time and more frequent discretionary sweet food consumption. A smaller distance to the nearest road was also associated with lower sleep duration and more frequent sweet beverages consumption. On the other hand, higher levels of street connectivity showed an inverse association with the unhealthy lifestyle patterns. In the same vein, greater street connectivity was associated with decreased screen time.

CONCLUSION

This comprehensive examination of multiple urban exposures indicates that residing in walkable environments and in close proximity to roads in densely-populated areas may not be advantageous for children EBRBs, while residing in neighborhoods with higher street connectivity appears to supposedly be beneficial.

Assessing external exposome by implementing an Environmental Data Management System using Open Data

Due to the increasing importance of exposome in environmental epidemiology, feasibility and usefulness of an Environmental Data Management System (EDMS) using Open Data was evaluated. The EDMS includes data from 10 European cities (Celje (Slovenia), Łódź (Poland), Manchester (UK), Palermo (Italy), Paris (France), Porto (Portugal), Regensburg (Germany), Reus (Spain), Rijeka (Croatia), Thessaloniki (Greece)) about external non-specific and specific exposome factors at the city or country level (2017-2020). Findings showed that the highest values of life expectancy were in Reus females (86 years) and Palermo males (81 years). UK had the highest obesity rate (28%), Croatia the highest prescribed drug consumption (62%), Greece and Portugal the highest smoking rates (37%, 42%) and daily alcohol consumption (21%), respectively. The most polluted cities were Thessaloniki for PM10 (38 µg/m3), Łódź for PM2.5 (25 µg/m3), Porto for NO2 (62 µg/m3) and Rijeka for O3 (92 µg/m3). Thessaloniki had the highest grey space (98%) and Łódź the highest cumulative amount of pollen (39,041 p/m3). The highest daily noise levels ≥ 55 dB was in Reus (81% to traffic) and Regensburg (21% to railway). In drinking water, arsenic had the highest value in Thessaloniki (6.4 µg/L), boron in Celje (24 mg/L) and lead in Paris (46.7 µg/L). Portugal and Greece showed the highest pesticide residues in food (7%). In conclusion, utilizing open-access databases enables the translation of research findings into actionable strategies for public health interventions.

EAACI guidelines on environmental science for allergy and asthma: The impact of short-term exposure to outdoor air pollutants on asthma-related outcomes and recommendations for mitigation measures

The EAACI Guidelines on the impact of short-term exposure to outdoor pollutants on asthma-related outcomes provide recommendations for prevention, patient care and mitigation in a framework supporting rational decisions for healthcare professionals and patients to individualize and improve asthma management and for policymakers and regulators as an evidence-informed reference to help setting legally binding standards and goals for outdoor air quality at international, national and local levels. The Guideline was developed using the GRADE approach and evaluated outdoor pollutants referenced in the current Air Quality Guideline of the World Health Organization as single or mixed pollutants and outdoor pesticides. Short-term exposure to all pollutants evaluated increases the risk of asthma-related adverse outcomes, especially hospital admissions and emergency department visits (moderate certainty of evidence at specific lag days). There is limited evidence for the impact of traffic-related air pollution and outdoor pesticides exposure as well as for the interventions to reduce emissions. Due to the quality of evidence, conditional recommendations were formulated for all pollutants and for the interventions reducing outdoor air pollution. Asthma management counselled by the current EAACI guidelines can improve asthma-related outcomes but global measures for clean air are needed to achieve significant impact.

EUFOREUM Berlin 2023: Optimizing care for type 2 inflammatory diseases from clinic to AI: A pediatric focus

The European Forum for Research and Education in Allergy and Airways diseases (EUFOREA) organized its bi-annual forum EUFOREUM in Berlin in November 2023. The aim of EUFOREUM 2023 was to highlight pediatric action plans for prevention and optimizing care for type 2 inflammatory conditions starting in childhood, with a focus on early-stage diagnosis, ensuring neither under- nor overdiagnosis, optimal care, and suggestions for improvement of care. EUFOREA is an international not-for-profit organization forming an alliance of all stakeholders dedicated to reducing the prevalence and burden of chronic respiratory diseases through the implementation of optimal patient care via educational, research, and advocacy activities. The inclusive and multidisciplinary approach of EUFOREA was reflected in the keynote lectures and faculty of the virtual EUFOREUM 2023 (www.euforea.eu/euforeum) coming from the pediatric, allergology, pulmonology, ENT, dermatology, primary health care fields and patients around the central theme of type 2 inflammation. As most type 2 inflammatory conditions may start in childhood or adolescence, and most children have type 2 inflammation when suffering from a respiratory or skin disease, the moment has come to raise the bar of ambitions of care, including prevention, remission and disease modification at an early stage. The current report provides a comprehensive overview of key statements by the faculty of the EUFOREUM 2023 and the ambitions of EUFOREA allowing all stakeholders in the respiratory field to be updated and ready to join forces in Europe and beyond.

A machine-learning exploration of the exposome from preconception in early childhood atopic eczema, rhinitis and wheeze development

BACKGROUND

Most previous research on the environmental epidemiology of childhood atopic eczema, rhinitis and wheeze is limited in the scope of risk factors studied. Our study adopted a machine learning approach to explore the role of the exposome starting already in the preconception phase.

METHODS

We performed a combined analysis of two multi-ethnic Asian birth cohorts, the Growing Up in Singapore Towards healthy Outcomes (GUSTO) and the Singapore PREconception Study of long Term maternal and child Outcomes (S-PRESTO) cohorts. Interviewer-administered questionnaires were used to collect information on demography, lifestyle and childhood atopic eczema, rhinitis and wheeze development. Data training was performed using XGBoost, genetic algorithm and logistic regression models, and the top variables with the highest importance were identified. Additive explanation values were identified and inputted into a final multiple logistic regression model. Generalised structural equation modelling with maternal and child blood micronutrients, metabolites and cytokines was performed to explain possible mechanisms.

RESULTS

The final study population included 1151 mother-child pairs. Our findings suggest that these childhood diseases are likely programmed in utero by the preconception and pregnancy exposomes through inflammatory pathways. We identified preconception alcohol consumption and maternal depressive symptoms during pregnancy as key modifiable maternal environmental exposures that increased eczema and rhinitis risk. Our mechanistic model suggested that higher maternal blood neopterin and child blood dimethylglycine protected against early childhood wheeze. After birth, early infection was a key driver of atopic eczema and rhinitis development.

CONCLUSION

Preconception and antenatal exposomes can programme atopic eczema, rhinitis and wheeze development in utero. Reducing maternal alcohol consumption during preconception and supporting maternal mental health during pregnancy may prevent atopic eczema and rhinitis by promoting an optimal antenatal environment. Our findings suggest a need to include preconception environmental exposures in future research to counter the earliest precursors of disease development in children.

Prenatal dietary exposure to chemicals and allergy or respiratory diseases in children in the EDEN mother-child cohort

INTRODUCTION

Maternal exposure to food chemicals may increase the risk of allergy and respiratory disorders in offspring. We aimed to assess the association of prenatal dietary exposure to single chemicals and chemical mixtures with allergy or respiratory events reported before age 8 y in children.

METHODS

We included 1428 mother-child pairs enrolled in the EDEN mother-child cohort. Maternal dietary exposure to 209 chemicals and eight associated mixtures was investigated. Allergic and respiratory diseases (wheezing, asthma, allergic rhinitis, eczema and food allergy) were reported by parents between birth and age 8 y. Associations with the studied outcomes were evaluated with three approaches based on adjusted logistic regression, estimating odds ratios (ORs) and 95 % confidence intervals (CIs). First, food chemicals were considered individually, with correction for multiple testing. Second, chemicals selected by elastic net regression were considered simultaneously in a multiple exposure model. Third, predefined mixtures were introduced in the same adjusted logistic regression. Results are expressed as odds ratio (OR[95 % CI]).

RESULTS

Prenatal single exposure to 74 food chemicals was associated with higher risk of allergic rhinitis. Prenatal single exposure to 11 chemicals was associated with higher risk of wheezing. In the multi-exposure approach, risk of wheezing was associated with the pesticides diazinon and triadimenol, and polycyclic aromatic hydrocarbon 5-methylchrysene. Phytoestrogen resveratrol was negatively associated with lower risk of both wheezing and allergic rhinitis, and mycotoxin monoacetoxyscirpenol was negatively associated with risk of eczema. Finally, a chemical mixture composed mainly of trace elements, furans and polycyclic aromatic hydrocarbons, was associated with higher risk of allergic rhinitis (1.33 [1.02;1.73]).

CONCLUSION

Prenatal dietary exposure to chemicals was associated with risk of allergic rhinitis or wheezing up to age 8 y. A few chemicals were associated with other allergic and respiratory diseases. Larger prospective studies are needed to confirm these findings.

Integrating the social environment with an equity perspective into the exposome paradigm: A new conceptual framework of the Social Exposome

The importance of the social environment and social inequalities in disease etiology is well-known due to the profound research and conceptual framework on social determinants of health. For a long period, in exposome research with its classical orientation towards detrimental health effects of biological, chemical, and physical exposures, this knowledge remained underrepresented. But currently it gains great awareness and calls for innovations in rethinking the role of social environmental health determinants. To fill this gap that exists in terms of the social domain within exposome research, we propose a novel conceptual framework of the Social Exposome, to integrate the social environment in conjunction with the physical environment into the exposome concept. The iterative development process of the Social Exposome was based on a systematic compilation of social exposures in order to achieve a holistic portrayal of the human social environment - including social, psychosocial, socioeconomic, sociodemographic, local, regional, and cultural aspects, at individual and contextual levels. In order to move the Social Exposome beyond a mere compilation of exposures, three core principles are emphasized that underly the interplay of the multitude of exposures: Multidimensionality, Reciprocity, and Timing and continuity. The key focus of the conceptual framework of the Social Exposome is on understanding the underlying mechanisms that translate social exposures into health outcomes. In particular, insights from research on health equity and environmental justice have been incorporated to uncover how social inequalities in health emerge, are maintained, and systematically drive health outcomes. Three transmission pathways are presented: Embodiment, Resilience and Susceptibility or Vulnerability, and Empowerment. The Social Exposome conceptual framework may serve as a strategic map for, both, research and intervention planning, aiming to further explore the impact of the complex social environment and to alter transmission pathways to minimize health risks and health inequalities and to foster equity in health.

EAACI guidelines on environmental science in allergic diseases and asthma - Leveraging artificial intelligence and machine learning to develop a causality model in exposomics

Allergic diseases and asthma are intrinsically linked to the environment we live in and to patterns of exposure. The integrated approach to understanding the effects of exposures on the immune system includes the ongoing collection of large-scale and complex data. This requires sophisticated methods to take full advantage of what this data can offer. Here we discuss the progress and further promise of applying artificial intelligence and machine-learning approaches to help unlock the power of complex environmental data sets toward providing causality models of exposure and intervention. We discuss a range of relevant machine-learning paradigms and models including the way such models are trained and validated together with examples of machine learning applied to allergic disease in the context of specific environmental exposures as well as attempts to tie these environmental data streams to the full representative exposome. We also discuss the promise of artificial intelligence in personalized medicine and the methodological approaches to healthcare with the final AI to improve public health.

The exposome in respiratory diseases: multiple preventable risk factors from early life to adulthood

The increasing global burden of respiratory diseases over the last decades raises questions about the impact of environmental factors during industrialisation and urbanisation. Although the knowledge of environmental epidemiology is growing, it is still unclear what the most critical exposure windows are for respiratory health. In addition, the relationships between different environmental exposures can be complex. The exposome approach investigating all non-genetic factors on health has been developed in recent years but has been little applied in respiratory health to date. This journal club article reviews three recent publications investigating the effects of environmental exposures, considered separately or in an exposome approach with different exposure windows, on respiratory health outcomes. These three studies highlight targets for action in primary and secondary prevention. Two studies, using data from the INMA and RHINESSA cohorts, support the regulation and reduction of phthalates and air pollution, respectively. Moreover, the exposome approach conducted in the NutriNet-Santé cohort emphasises that risk reduction must involve a multi-interventional approach targeting both specific early-life risk factors and promotion of a healthy lifestyle in adulthood. These three articles also present research perspectives in environmental epidemiology.

Molecular Accounting and Profiling of Human Respiratory Microbial Communities: Toward Precision Medicine by Targeting the Respiratory Microbiome for Disease Diagnosis and Treatment

The wide diversity of microbiota at the genera and species levels across sites and individuals is related to various causes and the observed differences between individuals. Efforts are underway to further understand and characterize the human-associated microbiota and its microbiome. Using 16S rDNA as a genetic marker for bacterial identification improved the detection and profiling of qualitative and quantitative changes within a bacterial population. In this light, this review provides a comprehensive overview of the basic concepts and clinical applications of the respiratory microbiome, alongside an in-depth explanation of the molecular targets and the potential relationship between the respiratory microbiome and respiratory disease pathogenesis. The paucity of robust evidence supporting the correlation between the respiratory microbiome and disease pathogenesis is currently the main challenge for not considering the microbiome as a novel druggable target for therapeutic intervention. Therefore, further studies are needed, especially prospective studies, to identify other drivers of microbiome diversity and to better understand the changes in the lung microbiome along with the potential association with disease and medications. Thus, finding a therapeutic target and unfolding its clinical significance would be crucial.

Characterization of the external exposome and its contribution to the clinical respiratory and early biological effects in children: The PROMESA cohort study protocol

BACKGROUND

Air pollution contains a mixture of different pollutants from multiple sources. However, the interaction of these pollutants with other environmental exposures, as well as their harmful effects on children under five in tropical countries, is not well known.

OBJECTIVE

This study aims to characterize the external exposome (ambient and indoor exposures) and its contribution to clinical respiratory and early biological effects in children.

MATERIALS AND METHODS

A cohort study will be conducted on children under five (n = 500) with a one-year follow-up. Enrolled children will be followed monthly (phone call) and at months 6 and 12 (in person) post-enrolment with upper and lower Acute Respiratory Infections (ARI) examinations, asthma development, asthma control, and genotoxic damage. The asthma diagnosis will be pediatric pulmonologist-based and a standardized protocol will be used. Exposure, effect, and susceptibility biomarkers will be measured on buccal cells samples. For environmental exposures PM2.5 will be sampled, and questionnaires, geographic information, dispersion models and Land Use Regression models for PM2.5 and NO2 will be used. Different statistical methods that include Bayesian and machine learning techniques will be used for the ambient and indoor exposures-and outcomes. This study was approved by the ethics committee at Universidad Pontificia Bolivariana.

EXPECTED STUDY OUTCOMES/FINDINGS

To estimate i) The toxic effect of particulate matter transcending the approach based on pollutant concentration levels; ii) The risk of developing an upper and lower ARI, based on different exposure windows; iii) A baseline of early biological damage in children under five, and describe its progression after a one-year follow-up; and iv) How physical and chemical PM2.5 characteristics influence toxicity and children's health.

Estimating the Relative Contribution of Environmental and Genetic Risk Factors to Different Aging Traits by Combining Correlated Variables into Weighted Risk Scores

Genetic and exposomal factors contribute to the development of human aging. For example, genetic polymorphisms and exposure to environmental factors (air pollution, tobacco smoke, etc.) influence lung and skin aging traits. For prevention purposes it is highly desirable to know the extent to which each category of the exposome and genetic factors contribute to their development. Estimating such extents, however, is methodologically challenging, mainly because the predictors are often highly correlated. Tackling this challenge, this article proposes to use weighted risk scores to assess combined effects of categories of such predictors, and a measure of relative importance to quantify their relative contribution. The risk score weights are determined via regularized regression and the relative contributions are estimated by the proportion of explained variance in linear regression. This approach is applied to data from a cohort of elderly Caucasian women investigated in 2007-2010 by estimating the relative contribution of genetic and exposomal factors to skin and lung aging. Overall, the models explain 17% (95% CI: [9%, 28%]) of the outcome's variance for skin aging and 23% ([11%, 34%]) for lung function parameters. For both aging traits, genetic factors make up the largest contribution. The proposed approach enables us to quantify and rank contributions of categories of exposomal and genetic factors to human aging traits and facilitates risk assessment related to common human diseases in general. Obtained rankings can aid political decision making, for example, by prioritizing protective measures such as limit values for certain exposures.

Pollen exposure is associated with risk of respiratory symptoms during the first year of life

BACKGROUND

Pollen exposure is associated with respiratory symptoms in children and adults. However, the association of pollen exposure with respiratory symptoms during infancy, a particularly vulnerable period, remains unclear. We examined whether pollen exposure is associated with respiratory symptoms in infants and whether maternal atopy, infant's sex or air pollution modifies this association.

METHODS

We investigated 14,874 observations from 401 healthy infants of a prospective birth cohort. The association between pollen exposure and respiratory symptoms, assessed in weekly telephone interviews, was evaluated using generalized additive mixed models (GAMMs). Effect modification by maternal atopy, infant's sex, and air pollution (NO₂ , PM_2.5 ) was assessed with interaction terms.

RESULTS

Per infant, 37 ± 2 (mean ± SD) respiratory symptom scores were assessed during the analysis period (January through September). Pollen exposure was associated with increased respiratory symptoms during the daytime (RR [95% CI] per 10% pollen/m³ : combined 1.006 [1.002, 1.009]; tree 1.005 [1.002, 1.008]; grass 1.009 [1.000, 1.23]) and nighttime (combined 1.003 [0.999, 1.007]; tree 1.003 [0.999, 1.007]; grass 1.014 [1.004, 1.024]). While there was no effect modification by maternal atopy and infant's sex, a complex crossover interaction between combined pollen and PM_2.5 was found (p-value 0.003).

CONCLUSION

Even as early as during the first year of life, pollen exposure was associated with an increased risk of respiratory symptoms, independent of maternal atopy and infant's sex. Because infancy is a particularly vulnerable period for lung development, the identified adverse effect of pollen exposure may be relevant for the evolvement of chronic childhood asthma.

Impact of mixtures of persistent organic pollutants on breast cancer aggressiveness

INTRODUCTION

Breast cancer (BC) is frequent with a poor prognosis in case of metastasis. The role of the environment has been poorly evaluated in its progression. We searched to assess whether a mixture of pollutants could be responsible of BC aggressiveness.

METHODS

Patients undergoing surgery for their BC were prospectively included in the METAPOP cohort. Forty-two POPs were extracted, among them 17 dioxins (PCDD/F), 16 polychlorobiphenyls (PCB), 8 polybromodiphenylethers (PBDE) and 2,2',4,4',5,5'-hexabromobiphenyl (PBB153) were measured in the adipose tissue surrounding the tumor. BC aggressiveness was defined using tumor size and metastasis (distant or lymph nodes). Two complementary models were used to evaluate the impact of the mixture of pollutants: the BKMR (Bayesian Kernel machine regression) and WQS (weighted quantile sum regression) models. The WQS estimates the weight (positive or negative) of a certain chemical based on its quantile and the BKMR model applies a kernel-based approach to estimate posterior inclusion probabilities. The sub-group of patients with a body mass index (BMI) > 22 kg/ m² was also analyzed.

RESULTS

Ninety-one patients were included. Of these, 38 patients presented a metastasis, and the mean tumor size was 25.4 mm. The mean BMI was 24.5 kg/m² (+/- 4.1). No statistical association was found in the general population. However, in patients with a BMI > 22 kg/ m², our mixture was positively associated with tumor size (OR: 9.73 95 %CI: 1.30-18.15) and metastasis (OR = 3.98 95 %CI = 1.09-17.53) using the WQS model. Moreover, using the BKMR model on chemical families, dioxin like chemicals and PCDD were associated with a higher risk of metastasis.

DISCUSSION

These novel findings identified a mixture associated with breast cancer aggressiveness in patients with a BMI > 22 kg/ m².

Exposome Profiles and Asthma among French Adults

Rationale: Although previous studies in environmental epidemiology focused on single or a few exposures, a holistic approach combining multiple preventable risk factors is needed to tackle the etiology of multifactorial diseases such as asthma. Objectives: To investigate the association between combined socioeconomic, external environment, early-life environment, and lifestyle-anthropometric factors and asthma phenotypes. Methods: A total of 20,833 adults from the French NutriNet-Santé cohort were included (mean age, 56.2 yr; SD, 13.2; 72% women). The validated asthma symptom score (continuous) and asthma control (never asthma, controlled asthma, and uncontrolled asthma) were considered. The exposome (n = 87 factors) covered four domains: socioeconomic, external environment, early-life environment, and lifestyle-anthropometric. Cluster-based analyses were performed within each exposome domain, and the identified profiles were studied in association to asthma outcomes in negative binomial (asthma symptom score) or multinomial logistic (asthma control) regression models. Measurements and Main Results: In total, 5,546 (27%) individuals had an asthma symptom score ⩾1, and 1,206 (6%) and 194 (1%) had controlled and uncontrolled asthma, respectively. Three early-life exposure profiles ("high passive smoking-own dogs," "poor birth parameters-daycare attendance-city center," or "⩾2 siblings-breastfed" compared with "farm-pet owner-molds-low passive smoking") and one lifestyle-anthropometric profile ("unhealthy diet-high smoking-overweight" compared with "healthy diet-nonsmoker-thin") were associated with more asthma symptoms and uncontrolled asthma. Conclusions: This large-scale exposome-based study revealed early-life and lifestyle exposure profiles that were at risk for asthma in adults. Our findings support the importance of multiinterventional programs for the primary and secondary prevention of asthma, including control of specific early-life risk factors and promotion of a healthy lifestyle in adulthood.

Measuring and modelling perceptions of the built environment for epidemiological research using crowd-sourcing and image-based deep learning models

BACKGROUND

Perceptions of the built environment, such as nature quality, beauty, relaxation, and safety, may be key factors linking the built environment to human health. However, few studies have examined these types of perceptions due to the difficulty in quantifying them objectively in large populations.

OBJECTIVE

To measure and predict perceptions of the built environment from street-view images using crowd-sourced methods and deep learning models for application in epidemiologic studies.

METHODS

We used the Amazon Mechanical-Turk crowdsourcing platform where participants compared two street-view images and quantified perceptions of nature quality, beauty, relaxation, and safety. We optimized street-view image sampling methods to improve the quality and resulting perception data specific to participants enrolled in the Washington State Twin Registry (WSTR) health study. We used a transfer learning approach to train deep learning models by leveraging existing image perception data from the PlacePulse 2.0 dataset, which includes 1.1 million image comparisons, and refining based on new WSTR perception data. Resulting models were applied to WSTR addresses to estimate exposures and evaluate associations with traditional built environment measures.

RESULTS

We collected over 36,000 image comparisons and calculated perception measures for each image. Our final deep learning models explained 77.6% of nature quality, 68.1% of beauty, 72.0% of relaxation, and 64.7% of safety in pairwise image comparisons. Applying transfer learning with the new perception labels specific to the WSTR yielded an average improvement of 3.8% for model performance. Perception measures were weakly to moderately correlated with traditional built environment exposures for WSTR participant addresses; for example, nature quality and NDVI (r = 0.55), neighborhood area deprivation (r = -0.16), and walkability (r = -0.20), respectively.

SIGNIFICANCE

We were able to measure and model perceptions of the built environment optimized for a specific health study. Future applications will examine associations between these exposure measures and mental health in the WSTR.

IMPACT STATEMENT

Built environments influence health through complex pathways. Perceptions of nature quality, beauty, relaxation and safety may be particularly import for understanding these linkages, but few studies to-date have examined these perceptions objectively for large populations. For quantitative research, an exposure measure must be reproducible, accurate, and precise--here we work to develop such measures for perceptions of the urban environment. We created crowd-sourced and image-based deep learning methods that were able to measure and model these perceptions. Future applications will apply these models to examine associations with mental health in the Washington State Twin Registry.

[Markers of severity and predictors of response to treatment in severe asthma]

Asthma is a multifactorial disease with complex pathophysiology. Knowledge of its immunopathology and inflammatory mechanisms is progressing and has led to the development over recent years of increasingly targeted therapeutic strategies. The objective of this review is to pinpoint the different predictive markers of asthma severity and therapeutic response. Obesity, nasal polyposis, gastroesophageal reflux disease and intolerance to aspirin have all been considered as clinical markers associated with asthma severity, as have functional markers such as bronchial obstruction, low FEV1, small daily variations in FEV1, and high FeNO. While sinonasal polyposis and allergic comorbidities are associated with better response to omalizumab, nasal polyposis or long-term systemic steroid use are associated with better response to antibodies targeting the IL5 pathway. Elevated total IgE concentrations and eosinophil counts are classic biological markers regularly found in severe asthma. Blood eosinophils are predictive biomarkers of response to anti-IgE, anti-IL5, anti-IL5R and anti-IL4R biotherapies. Dupilumab is particularly effective in a subgroup of patients with marked type 2 inflammation (long-term systemic corticosteroid therapy, eosinophilia≥150/μl or FENO>20 ppb). Chest imaging may help to identify severe patients by seeking out bronchial wall thickening and bronchial dilation. Study of the patient's environment is crucial insofar as exposure to tobacco, dust mites and molds, as well as outdoor and indoor air pollutants (cleaning products), can trigger asthma exacerbation. Wider and more systematic use of markers of severity or response to treatment could foster increasingly targeted and tailored approaches to severe asthma.

OSA and Chronic Respiratory Disease: Mechanisms and Epidemiology

Obstructive sleep apnea (OSA) is a highly prevalent disorder that has profound implications on the outcomes of patients with chronic lung disease. The hallmark of OSA is a collapse of the oropharynx resulting in a transient reduction in airflow, large intrathoracic pressure swings, and intermittent hypoxia and hypercapnia. The subsequent cytokine-mediated inflammatory cascade, coupled with tractional lung injury, damages the lungs and may worsen several conditions, including chronic obstructive pulmonary disease, asthma, interstitial lung disease, and pulmonary hypertension. Further complicating this is the sleep fragmentation and deterioration of sleep quality that occurs because of OSA, which can compound the fatigue and physical exhaustion often experienced by patients due to their chronic lung disease. For patients with many pulmonary disorders, the available evidence suggests that the prompt recognition and treatment of sleep-disordered breathing improves their quality of life and may also alter the course of their illness. However, more robust studies are needed to truly understand this relationship and the impacts of confounding comorbidities such as obesity and gastroesophageal reflux disease. Clinicians taking care of patients with chronic pulmonary disease should screen and treat patients for OSA, given the complex bidirectional relationship OSA has with chronic lung disease.

Understanding exposures and latent disease risk within the National Institute of Environmental Health Sciences Superfund Research Program

Understanding the health effects of exposures when there is a lag between exposure and the onset of disease is an important and challenging topic in environmental health research. The National Institute of Environmental Health Sciences (NIEHS) Superfund Basic Research and Training Program (SRP) is a National Institutes of Health (NIH) grant program that uses a multidisciplinary approach to support biomedical and environmental science and engineering research. Because of the multidisciplinary nature of the program, SRP grantees are well-positioned to study exposure and latent disease risk across humans, animal models, and various life stages. SRP-funded scientists are working to address the challenge of connecting exposures that occur early in life and prior to conception with diseases that manifest much later, including developing new tools and approaches to predict how chemicals may affect long-term health. Here, we highlight research from the SRP focused on understanding the health effects of exposures with a lag between exposure and the onset of the disease as well as provide future directions for addressing knowledge gaps for this highly complex and challenging topic. Advancing the knowledge of latency to disease will require a multidisciplinary approach to research, the need for data sharing and integration, and new tools and computation approaches to make better predications about the timing of disease onset. A better understanding of exposures that may contribute to later-life diseases is essential to supporting the implementation of prevention and intervention strategies to reduce or modulate exposures to reduce disease burden.

Multi-Omics Profiling Approach to Asthma: An Evolving Paradigm

Asthma is a complex multifactorial and heterogeneous respiratory disease. Although genetics is a strong risk factor of asthma, external and internal exposures and their interactions with genetic factors also play important roles in the pathophysiology of asthma. Over the past decades, the application of high-throughput omics approaches has emerged and been applied to the field of asthma research for screening biomarkers such as genes, transcript, proteins, and metabolites in an unbiased fashion. Leveraging large-scale studies representative of diverse population-based omics data and integrating with clinical data has led to better profiling of asthma risk. Yet, to date, no omic-driven endotypes have been translated into clinical practice and management of asthma. In this article, we provide an overview of the current status of omics studies of asthma, namely, genomics, transcriptomics, epigenomics, proteomics, exposomics, and metabolomics. The current development of the multi-omics integrations of asthma is also briefly discussed. Biomarker discovery following multi-omics profiling could be challenging but useful for better disease phenotyping and endotyping that can translate into advances in asthma management and clinical care, ultimately leading to successful precision medicine approaches.

Microbiome Research and Multi-Omics Integration for Personalized Medicine in Asthma

Asthma is a multifactorial inflammatory disorder of the respiratory system characterized by high diversity in clinical manifestations, underlying pathological mechanisms and response to treatment. It is generally established that human microbiota plays an essential role in shaping a healthy immune response, while its perturbation can cause chronic inflammation related to a wide range of diseases, including asthma. Systems biology approaches encompassing microbiome analysis can offer valuable platforms towards a global understanding of asthma complexity and improving patients' classification, status monitoring and therapeutic choices. In the present review, we summarize recent studies exploring the contribution of microbiota dysbiosis to asthma pathogenesis and heterogeneity in the context of asthma phenotypes-endotypes and administered medication. We subsequently focus on emerging efforts to gain deeper insights into microbiota-host interactions driving asthma complexity by integrating microbiome and host multi-omics data. One of the most prominent achievements of these research efforts is the association of refractory neutrophilic asthma with certain microbial signatures, including predominant pathogenic bacterial taxa (such as Proteobacteria phyla, Gammaproteobacteria class, especially species from Haemophilus and Moraxella genera). Overall, despite existing challenges, large-scale multi-omics endeavors may provide promising biomarkers and therapeutic targets for future development of novel microbe-based personalized strategies for diagnosis, prevention and/or treatment of uncontrollable asthma.

The Exposome Approach in Allergies and Lung Diseases: Is It Time to Define a Preconception Exposome?

Emerging research suggests environmental exposures before conception may adversely affect allergies and lung diseases in future generations. Most studies are limited as they have focused on single exposures, not considering that these diseases have a multifactorial origin in which environmental and lifestyle factors are likely to interact. Traditional exposure assessment methods fail to capture the interactions among environmental exposures and their impact on fundamental biological processes, as well as individual and temporal factors. A valid estimation of exposure preconception is difficult since the human reproductive cycle spans decades and the access to germ cells is limited. The exposome is defined as the cumulative measure of external exposures on an organism (external exposome), and the associated biological responses (endogenous exposome) throughout the lifespan, from conception and onwards. An exposome approach implies a targeted or agnostic analysis of the concurrent and temporal multiple exposures, and may, together with recent technological advances, improve the assessment of the environmental contributors to health and disease. This review describes the current knowledge on preconception environmental exposures as related to respiratory health outcomes in offspring. We discuss the usefulness and feasibility of using an exposome approach in this research, advocating for the preconception exposure window to become included in the exposome concept.

Achieving Precision Medicine in Allergic Disease: Progress and Challenges

Allergic diseases (atopic dermatitis, food allergy, eosinophilic esophagitis, asthma and allergic rhinitis), perhaps more than many other traditionally grouped disorders, share several overlapping inflammatory pathways and risk factors, though we are still beginning to understand how the relevant patient and environmental factors uniquely shape each disease. Precision medicine is the concept of applying multiple levels of patient-specific data to tailor diagnoses and available treatments to the individual; ideally, a patient receives the right intervention at the right time, in order to maximize effectiveness but minimize morbidity, mortality and cost. While precision medicine in allergy is in its infancy, the recent success of biologics, development of tools focused on large data set integration and improved sampling methods are encouraging and demonstrates the utility of refining our understanding of allergic endotypes to improve therapies. Some of the biggest challenges to achieving precision medicine in allergy are characterizing allergic endotypes, understanding allergic multimorbidity relationships, contextualizing the impact of environmental exposures (the “exposome”) and ancestry/genetic risks, achieving actionable multi-omics integration, and using this information to develop adequately powered patient cohorts and refined clinical trials. In this paper, we highlight several recently developed tools and methods showing promise to realize the aspirational potential of precision medicine in allergic disease. We also outline current challenges, including exposome sampling and building the “knowledge network” with multi-omics integration.