Ecogenomics of respiratory diseases of public health significance

Pulmonary function assessment among conventional and organic cotton farmers exposed to pesticides in the Central-West region of Burkina Faso

BACKGROUND

Respiratory diseases have been associated with the exposure of populations to some environmental pollutants such as pesticides. To assess effects of pesticides on farmers' respiratory health, this study aimed to evaluate the pulmonary function of cotton farmers exposed to synthetic and natural pesticides in the Central-West region of Burkina Faso.

METHODS

A cross-sectional study was conducted from June to July 2022 among 281 conventional and 189 organic cotton farmers. After collecting information on pesticide use conditions, pulmonary function tests (PFTs) were performed on each farmer according to the American Thoracic Society/European Respiratory Society guidelines, in order to assess chronic respiratory effects among cotton producers. Binary logistic regression was used to assess factors associated with the occurrence of ventilatory changes.

RESULTS

Both conventional and organic cotton farmers reported similar chronic respiratory symptoms in different proportions. The main reported were rhinitis (54.45% conventional vs. 34.92% organic), chest pains (41.28% conventional vs. 23.81% organic), cough (33.45% conventional, 24.34% organic), breathlessness (31.67% conventional, 4.23% organic) (p<0.05). 16.18% and 27.50% of conventional male and female cotton farmers, respectively, had a restrictive defect. Among organic cotton farmers, 15.85% and 18.69%, respectively, of males and females had a restrictive defect. Furthermore, a significant increase in the predicted average percentage of FEV1/FVC ratio was observed among organic cotton farmers after salbutamol's use (p = 0.039). The type of cultivated cotton was not associated with ventilatory changes neither in the univariate analysis, nor in the multivariate analysis. Other factors such as farmers' age, BMI and insecticides use frequency per year were also important. Farmers who used insecticides more than 6 times per season had an increased risk of developing an obstructive defect (OR = 1.603; 95%CI: 0.484-5.309) compared to those who used them 6 times or less.

CONCLUSION

Chronic respiratory signs and ventilatory impairments were found among conventional and, to our knowledge, for the first time among organic cotton producers. However, these health effects were more prevalent among conventional cotton farmers than organic ones.

Pharmacokinetic Models for Inhaled Fluticasone Propionate and Salmeterol Xinafoate to Quantify Batch-to-Batch Variability

Advair Diskus is an essential treatment for asthma and chronic obstructive pulmonary disease. It is a dry powder inhaler with a combination of fluticasone propionate (FP) and salmeterol xinafoate (SX). However, the pharmacokinetics (PK) batch-to-batch variability of the reference-listed drug (RLD) hindered its generic product development. This work developed the PK models for inhaled FP and SX that could represent potential batch variability. Two batches each of the reference and the test product (R1, R2, T1, T2) of Advair Diskus (100 μg FP/50 μg SX inhalation) were administered to 60 healthy subjects in a 4-period, 4-sequence crossover study. The failure of the bioequivalence (BE) between R1 and R2 confirmed the high between-batch variability of the RLD. Non-linear mixed effect modeling was used to estimate the population mean PK parameters for each batch. For FP, a 2-compartment model with a sequential dual zero-order absorption best described the PK profile. For SX, a 2-compartment model with a first-order absorption model best fit the data. Both models were able to capture the plasma concentration, the maximum concentration, and the total exposure (AUCinf) adequately for each batch, which could be used to simulate the BE study in the future. In vitro properties were also measured for each batch, and the batch with a higher fraction of the fine particle (diameter < 1 µm, < 2 µm) had a higher AUCinf. This positive correlation for both FP and SX could potentially assist the batch selection for the PK BE study.

In Silico Bioinformatics Followed by Molecular Validation Using Archival FFPE Tissue Biopsies Identifies a Panel of Transcripts Associated with Severe Asthma and Lung Cancer

Simple Summary

The present study identified a panel of transcripts involved in the pathogenesis of both severe asthma and lung cancer. The genes identified using publicly available transcriptomics data were validated on cell lines, plasma samples, and archival tissue biopsies from asthmatic and lung cancer patients. The functional roles of the identified markers in both the diseases were ascertained from the literature. These molecular markers might be useful for diagnosing lung cancer at early stages.

Abstract

Severe asthma and lung cancer are both heterogeneous pathological diseases affecting the lung tissue. Whilst there are a few studies that suggest an association between asthma and lung cancer, to the best of our knowledge, this is the first study to identify common genes involved in both severe asthma and lung cancer. Publicly available transcriptomic data for 23 epithelial brushings from severe asthmatics and 55 samples of formalin-fixed paraffin-embedded (FFPE) lung cancer tissue at relatively early stages were analyzed by absolute gene set enrichment analysis (GSEA) in comparison to 37 healthy bronchial tissue samples. The key pathways enriched in asthmatic patients included adhesion, extracellular matrix, and epithelial cell proliferation, which contribute to tissue remodeling. In the lung cancer dataset, the main pathways identified were receptor tyrosine kinase signaling, wound healing, and growth factor response, representing the early cancer pathways. Analysis of the enriched genes derived from the pathway analysis identified seven genes expressed in both the asthma and lung cancer sets: BCL3, POSTN, PPARD, STAT1, MYC, CD44, and FOSB. The differential expression of these genes was validated in vitro in the cell lines retrieved from different lung cancer and severe asthma patients using real-time PCR. The effect of the expression of the seven genes identified in the study on the overall survival of lung cancer patients (n = 1925) was assessed using a Kaplan–Meier plot. In vivo validation performed in the archival biopsies obtained from patients diagnosed with both the disease conditions provided interesting insights into the pathogenesis of severe asthma and lung cancer, as indicated by the differential expression pattern of the seven transcripts in the mixed group as compared to the asthmatics and lung cancer samples alone.

Device Invariant Deep Neural Networks for Pulmonary Audio Event Detection Across Mobile and Wearable Devices

Mobile and wearable devices are being increasingly used for developing audio based machine learning models to infer pulmonary health, exacerbation and activity. A major challenge to widespread usage and deployment of such pulmonary health monitoring audio models is to maintain accuracy and robustness across a variety of commodity devices, due to the effect of device heterogeneity. Because of this phenomenon, pulmonary audio models developed with data from one type of device perform poorly when deployed on another type of device. In this work, we propose a framework incorporating feature normalization across individual frequency bins and combining task specific deep neural networks for model invariance across devices for pulmonary event detection. Our empirical and extensive experiments with data from 131 real pulmonary patients and healthy controls show that our framework can recover up to 163.6% of the accuracy lost due to device heterogeneity for four different pulmonary classification tasks across two broad classification scenarios with two common mobile and wearable devices: smartphone and smartwatch.Clinical relevance- The methods presented in this paper will enable efficient and easy portability of clinician recommended pulmonary audio event detection and analytic models across various mobile and wearable devices used by a patient.

Digital Inhalers for Asthma or Chronic Obstructive Pulmonary Disease: A Scientific Perspective

Impressive advances in inhalation therapy for patients with asthma and chronic obstructive pulmonary disease (COPD) have occurred in recent years. However, important gaps in care remain, particularly relating to poor adherence to inhaled therapies. Digital inhaler health platforms which incorporate digital inhalers to monitor time and date of dosing are an effective disease and medication management tool, promoting collaborative care between clinicians and patients, and providing more in-depth understanding of actual inhaler use. With advances in technology, nearly all inhalers can be digitalized with add-on or embedded sensors to record and transmit data quantitating inhaler actuations, and some have additional capabilities to evaluate inhaler technique. In addition to providing an objective and readily available measure of adherence, they allow patients to interact with the device directly or through their self-management smartphone application such as via alerts and recording of health status. Clinicians can access these data remotely and during patient encounters, to better inform them about disease status and medication adherence and inhaler technique. The ability for remote patient monitoring is accelerating interest in and the use of these devices in clinical practice and research settings. More than 20 clinical studies of digital inhalers in asthma or COPD collectively show improvement in medication adherence, exacerbation risk, and patient outcomes with digital inhalers. These studies support previous findings about patient inhaler use and behaviors, but with greater granularity, and reveal some new findings about patient medication-taking behaviors. Digital devices that record inspiratory flows with inhaler use can guide proper inhaler technique and may prove to be a clinically useful lung function measure. Adoption of digital inhalers into practice is still early, and additional research is needed to determine patient and clinician acceptability, the appropriate place of these devices in the therapeutic regimen, and their cost effectiveness.

Inhalation monoclonal antibody therapy: a new way to treat and manage respiratory infections

The route of administration of a therapeutic agent has a substantial impact on its success. Therapeutic antibodies are usually administered systemically, either directly by intravenous route, or indirectly by intramuscular or subcutaneous injection. However, treatment of diseases contained within a specific tissue necessitates a better alternate route of administration for targeting localised infections. Inhalation is a promising non-invasive strategy for antibody delivery to treat respiratory maladies because it provides higher concentrations of antibody in the respiratory airways overcoming the constraints of entry through systemic circulation and uncertainity in the amount reaching the target tissue. The nasal drug delivery route is one of the extensively researched modes of administration, and nasal sprays for molecular drugs are deemed successful and are presently commercially marketed. This review highlights the current state and future prospects of inhaled therapies, with an emphasis on the use of monoclonal antibodies for the treatment of respiratory infections, as well as an overview of their importance, practical challenges, and clinical trial outcomes.Key points• Immunologic strategies for preventing mucosal transmission of respiratory pathogens.• Mucosal-mediated immunoprophylaxis could play a major role in COVID-19 prevention.• Applications of monoclonal antibodies in passive immunisation.

Insomnia affects the levels of plasma bilirubin and protein metabolism: an observational study and GWGEIS in UK Biobank cohort

STUDY OBJECTIVES

We aim to explore the mechanism of relationship between insomnia and liver metabolism by examining the gene × insomnia interactions.

METHODS

Individual level genotypic and phenotypic data were obtained from the UK Biobank cohort. Regression analysis was first conducted to test the association of insomnia with plasma total bilirubin (TBil; n = 186,793), direct bilirubin (DBil; n = 159,854) and total protein (TP; n = 171,574) in UK Biobank cohort. Second, genome-wide gene-environment interaction study (GWGEIS) was conducted by PLINK 2.0, and FUMA platform was used to identify enriched pathway terms.

RESULTS

In UK Biobank cohort, we found that TP (P < 2.00 × 10^-16), DBil (P = 1.72 × 10^-3) and TBil (P = 3.38 × 10^-5) were significantly associated with insomnia. GWGEIS of both DBil and TBil observed significant G × INSOMNIA effects between insomnia and UDP Glucuronosyltransferase Family 1 (rs6431558, P = 6.26 × 10^-11) gene. GWGEIS of TP also detected several significant genes interacting with insomnia, such as KLF15, (rs70940816, P = 6.77 × 10^-10) and DOK7, (rs2344205, P = 1.37 × 10^-9). Multiple gene ontology (GO) terms were identified for bilirubin, such as GO_URONIC_ACID_METABOLIC_PROCESS (adjusted P = 4.15 × 10^-26).

CONCLUSION

Our study results suggested negative associations between insomnia and DBil and TBil; and a positive association between insomnia and TP.

Association of Electronic Cigarette Use With Incident Respiratory Conditions Among US Adults From 2013 to 2018

Importance

Generating robust and timely evidence about the respiratory health risks of electronic cigarettes (e-cigarettes) is critical for informing state and federal regulatory standards for product safety.

Objective

To examine the association of e-cigarette use with incident respiratory conditions, including chronic obstructive pulmonary disease (COPD), emphysema, chronic bronchitis, and asthma.

Design, Setting, and Participants

This prospective cohort study used data from the nationally representative cohort of US adults from the Population Assessment of Tobacco and Health (PATH) study, including wave 1 from 2013 to 2014, wave 2 from 2014 to 2015, wave 3 from 2015 to 2016, and wave 4 from 2016 to 2018. Individuals aged 18 years and older at baseline with no prevalent respiratory conditions were included in the analyses. Analyses were conducted from February to July 2020.

Exposures

e-Cigarette use was assessed by self-reported current use status (never, former, or current) at baseline.

Main Outcomes and Measures

Incident respiratory conditions, including COPD, emphysema, chronic bronchitis, and asthma, as well as a composite respiratory disease encompassing all 4 conditions.

Results

Among 21 618 respondents included in the analyses, 11 017 (491%) were men and 12 969 (65.2%) were non-Hispanic White. A total of 14 213 respondents were never e-cigarette users, 5076 respondents (11.6%) were former e-cigarette users, and 2329 respondents (5.2%) were current e-cigarette users. Adjusted for cigarette and other combustible tobacco product use, demographic characteristics, and chronic health conditions, there was an increased risk of respiratory disease among former e-cigarette uses (incidence rate ratio [IRR], 1.28; 95% CI, 1.09-1.50) and current e-cigarette users (IRR, 1.31; 95% CI, 1.08-1.59). Among respondents with good self-rated health, the IRR for former e-cigarette users was 1.21 (95%CI, 1.00-1.46) and the IRR for current e-cigarette users was 1.43 (95% CI, 1.14-1.79). For specific respiratory diseases among current e-cigarette users, the IRR was 1.33 (95% CI, 1.06-1.67) for chronic bronchitis, 1.69 (95% CI, 1.15-2.49) for emphysema, 1.57 (95% CI, 1.15-2.13) for COPD, and 1.31 (95% CI, 1.01-1.71) for asthma.

Conclusions and Relevance

This cohort study found that e-cigarette use was associated with an increased risk of developing respiratory disease independent of cigarette smoking. These findings add important evidence on the risk profile of novel tobacco products.

TLR5 participates in the TLR4 receptor complex and promotes MyD88-dependent signaling in environmental lung injury

Lung disease causes significant morbidity and mortality, and is exacerbated by environmental injury, for example through lipopolysaccharide (LPS) or ozone (O3). Toll-like receptors (TLRs) orchestrate immune responses to injury by recognizing pathogen- or danger-associated molecular patterns. TLR4, the prototypic receptor for LPS, also mediates inflammation after O3, triggered by endogenous hyaluronan. Regulation of TLR4 signaling is incompletely understood. TLR5, the flagellin receptor, is expressed in alveolar macrophages, and regulates immune responses to environmental injury. Using in vivo animal models of TLR4-mediated inflammations (LPS, O3, hyaluronan), we show that TLR5 impacts the in vivo response to LPS, hyaluronan and O3. We demonstrate that immune cells of human carriers of a dominant negative TLR5 allele have decreased inflammatory response to O3 exposure ex vivo and LPS exposure in vitro. Using primary murine macrophages, we find that TLR5 physically associates with TLR4 and biases TLR4 signaling towards the MyD88 pathway. Our results suggest an updated paradigm for TLR4/TLR5 signaling.

Aberrant MicroRNAomics in Pulmonary Complications: Implications in Lung Health and Diseases

Over the last few decades, evolutionarily conserved molecular networks have emerged as important regulators in the expression and function of eukaryotic genomes. Recently, miRNAs (miRNAs), a large family of small, non-coding regulatory RNAs were identified in these networks as regulators of endogenous genes by exerting post-transcriptional gene regulation activity in a broad range of eukaryotic species. Dysregulation of miRNA expression correlates with aberrant gene expression and can play an essential role in human health and disease. In the context of the lung, miRNAs have been implicated in organogenesis programming, such as proliferation, differentiation, and morphogenesis. Gain- or loss-of-function studies revealed their pivotal roles as regulators of disease development, potential therapeutic candidates/targets, and clinical biomarkers. An altered microRNAome has been attributed to several pulmonary diseases, such as asthma, chronic pulmonary obstructive disease, cystic fibrosis, lung cancer, and idiopathic pulmonary fibrosis. Considering the relevant roles and functions of miRNAs under physiological and pathological conditions, they may lead to the invention of new diagnostic and therapeutic tools. This review will focus on recent advances in understanding the role of miRNAs in lung development, lung health, and diseases, while also exploring the progress and prospects of their application as therapeutic leads or as biomarkers.

Genome-wide by environment interaction studies of depressive symptoms and psychosocial stress in UK Biobank and Generation Scotland

Stress is associated with poorer physical and mental health. To improve our understanding of this link, we performed genome-wide association studies (GWAS) of depressive symptoms and genome-wide by environment interaction studies (GWEIS) of depressive symptoms and stressful life events (SLE) in two UK population-based cohorts (Generation Scotland and UK Biobank). No SNP was individually significant in either GWAS, but gene-based tests identified six genes associated with depressive symptoms in UK Biobank (DCC, ACSS3, DRD2, STAG1, FOXP2 and KYNU; p < 2.77 × 10-6). Two SNPs with genome-wide significant GxE effects were identified by GWEIS in Generation Scotland: rs12789145 (53-kb downstream PIWIL4; p = 4.95 × 10-9; total SLE) and rs17070072 (intronic to ZCCHC2; p = 1.46 × 10-8; dependent SLE). A third locus upstream CYLC2 (rs12000047 and rs12005200, p < 2.00 × 10-8; dependent SLE) when the joint effect of the SNP main and GxE effects was considered. GWEIS gene-based tests identified: MTNR1B with GxE effect with dependent SLE in Generation Scotland; and PHF2 with the joint effect in UK Biobank (p < 2.77 × 10-6). Polygenic risk scores (PRSs) analyses incorporating GxE effects improved the prediction of depressive symptom scores, when using weights derived from either the UK Biobank GWAS of depressive symptoms (p = 0.01) or the PGC GWAS of major depressive disorder (p = 5.91 × 10-3). Using an independent sample, PRS derived using GWEIS GxE effects provided evidence of shared aetiologies between depressive symptoms and schizotypal personality, heart disease and COPD. Further such studies are required and may result in improved treatments for depression and other stress-related conditions.

Overlap of Asthma and Chronic Obstructive Pulmonary Disease in Patients in the United States: Analysis of Prevalence, Features, and Subtypes

Background

Although asthma and chronic obstructive pulmonary disease (COPD) are clinically distinct diseases, they represent biologically diverse and overlapping clinical entities and it has been observed that they often co-occur. Some research and theorizing suggest there is a common comorbid condition termed asthma-chronic obstructive pulmonary disease overlap (ACO). However, the existence of ACO is controversial.

Objective

The objective of this study is to describe patient characteristics and estimate prevalence, health care utilization, and costs of ACO using claims-based diagnoses confirmed with medical record information.

Methods

Eligible patients were commercial US health plan enrollees; ≥40 years; had asthma, COPD, or ACO; ≥3 prescription fills for asthma/COPD medications; and ≥2 spirometry tests. Records for a random sample of 5000 patients with ACO were reviewed to validate claims-based diagnoses.

Results

The estimated ACO prevalence was 6% (estimated 10,250/183,521) among 183,521 full study patients. In the claims-based cohorts, the comorbidity burden for ACO was greater versus asthma but similar to COPD cohorts. Medication utilization was higher in ACO versus asthma and COPD. Mean total health care costs were significantly higher for ACO versus asthma but similar to COPD. In confirmed diagnoses cohorts, mean total health care costs (medical plus pharmacy) were lower for ACO versus COPD but similar to asthma (US $20,035; P=.56). Among confirmed cases, where there was medical record evidence, smoking history was higher in ACO (300/343, 87.5%) versus asthma cohorts (100/181, 55.2%) but similar to COPD (68/84, 81%).

Conclusions

ACO had more comorbidities, medication utilization, and costs than patients with asthma or COPD but differences were not seen after confirmation with medical records.

Detecting Familial Aggregation

In addition to characterizing the distribution of genetic features of populations (mutation and allele frequencies; measures of Hardy-Weinberg equilibrium), genetic epidemiology and statistical genetics aim to explore and define the role of genomic variation in risk of disease or variation in traits of interest. To facilitate this kind of exploration, genetic epidemiology and statistical genetics address a series of questions: 1. Does the disease tend to cluster in families more than expected by chance alone? 2. Does the disease appear to follow a particular genetic model of transmission in families? 3. Does variation at a particular genomic position tend to cosegregate with disease in families? 4. Do specific genetic variants tend to be carried more frequently by those with disease than by those without these variants in a given population (or across families)? The first question can be examined using studies of familial aggregation or correlation. An ancillary question: "how much of the susceptibility to disease (or variation in disease-related traits) might be accounted for by genetic factors?" is typically answered by estimating heritability, the proportion of variance in a trait or in risk to a disease attributable to genetics. The second question can be formally tested using pedigrees for which disease affection status or trait values are available through a modeling approach known as segregation analysis. The third question can be answered with data on genomic markers in pedigrees with affected members informative for linkage, where meiotic cross-over events are estimated or assessed. The fourth question is answerable using genotype data on genomic markers on unrelated affected and unaffected individuals and/or families with affected members and unaffected members. All of these questions can also be explored for quantitative (or continuously distributed) traits by examining variation in trait values between family members or between unrelated individuals. While each of these questions and the analytical approaches for answering them is explored extensively in subsequent chapters (heritability in Chapters 8 and 9 ; segregation in Chapter 12 ; linkage in Chapters 13 - 17 ; and association in Chapters 18 - 20 ), this chapter focuses on statistical methods to address questions of familial aggregation of qualitative phenotypes (e.g., disease status) or quantitative phenotypes.While studies exploring genotype-phenotype correlations are arguably the most important and common type of statistical genetic study performed, these studies are performed under the assumption that genetic contributors at least partially explain risk of a disease or a trait of interest. This may not always be the case, especially with diseases or traits known to be strongly influenced by environmental factors. For this reason, before any of the last three questions described above can be answered, it is important to ask first whether the disease clusters among family members more than unrelated persons, as this constitutes evidence of a possible heritable contribution to disease, justifying the pursuit of studies answering the other questions. In this chapter, the underlying principles of familial aggregation studies are addressed to provide an understanding and set of analytical tools to help answer the question if diseases or traits of interest are likely to be heritable and therefore justify subsequent statistical genetic studies to identify specific genetic causes.

Frontiers in occupational and environmental lung disease research

Two central challenges in the field of occupational and environmental epidemiology include accurately measuring biologic responses to exposure and preventing subsequent disease. As exposure-related lung diseases continue to be identified, advances in exposure biology have introduced toxicogenomic approaches that detect biomarkers of exposure at the gene, protein, and metabolite levels. Moreover, genetic epidemiology research has focused more recently on common, low-penetrant (ie, low-relative-risk) genetic variants that may interact with commonly encountered exposures. A number of such gene by environment interactions have been identified for airways and interstitial lung diseases, with the goal of preventing disease among susceptible populations that may not otherwise have been identified. Exhaled breath condensate analysis has provided another noninvasive means of assessing toxicant exposures and systemic effects. As these technologies become more refined, clinicians and public health practitioners will need to appreciate the social implications of the individual- and population-level risks conferred by certain genetic polymorphisms or by biomarker evidence of exposure. At present, the primary approach to occupational and environmental lung disease prevention remains elimination or reduction of known hazardous exposures and requires continued application of local and international resources toward exposure control.

Detecting familial aggregation

Beyond calculating parameter estimates to characterize the distribution of genetic features of populations (frequencies of mutations in various regions of the genome, allele frequencies, measures of Hardy-Weinberg disequilibrium), genetic epidemiology aims to identify correlations between genetic variants and phenotypic traits, with considerable emphasis placed on finding genetic variants that increase susceptibility to disease and disease-related traits. However, determining correlation alone does not suffice: genetic variants common in an isolated ethnic group with a high burden of a given disease may show relatively high correlation with disease but, as markers of ethnicity, these may not necessarily have any functional role in disease. To establish a causal relationship between genetic variants and disease (or disease-related traits), proper statistical analyses of human data must incorporate epidemiologic approaches to examining sets of families or unrelated individuals with information available on individuals' disease status or related traits.Through different analytical approaches, statistical analysis of human data can answer several important questions about the relationship between genes and disease: 1. Does the disease tend to cluster in families more than expected by chance alone? 2. Does the disease appear to follow a particular genetic model of transmission in families? 3. Do variants at a particular genetic marker tend to cosegregate with disease in families? 4. Do specific genetic markers tend to be carried more frequently by those with disease than by those without, in a given population (or across families)? The first question can be examined using studies of familial aggregation or correlation. An ancillary question: "how much of the susceptibility to disease (or variation in disease-related traits) might be accounted for by genetic factors?" is typically answered by estimating heritability, the proportion of disease susceptibility or trait variation attributable to genetics. The second question can be formally tested using pedigrees for which disease affection status or trait values are available through a modeling approach known as segregation analysis. The third question can be answered with data on pedigrees with affected members and genotype information at markers of interest, using linkage analysis. The fourth question is answerable using genotype information at markers on unrelated affected and unaffected individuals and/or families with affected and unaffected members. All of these questions can also be explored for quantitative (or continuously distributed) traits by examining variation in trait values between family members or between unrelated individuals. While each of these questions and the analytical approaches for answering them is explored extensively in subsequent chapters (heritability in Chapters 9 and 10, segregation in Chapter 12, linkage in Chapters 13-17, and association in Chapters 18-21 and 23), this chapter focuses on statistical methods to answer questions of familial aggregation.

Allergic asthma: influence of genetic and environmental factors

Allergic asthma is a chronic airway inflammatory disease in which exposure to allergens causes intermittent attacks of breathlessness, airway hyper-reactivity, wheezing, and coughing. Allergic asthma has been called a "syndrome" resulting from a complex interplay between genetic and environmental factors. Worldwide, >300 million individuals are affected by this disease, and in the United States alone, it is estimated that >35 million people, mostly children, suffer from asthma. Although animal models, linkage analyses, and genome-wide association studies have identified numerous candidate genes, a solid definition of allergic asthma has not yet emerged; however, such studies have contributed to our understanding of the multiple pathways to this syndrome. In contrast with animal models, in which T-helper 2 (T(H)2) cell response is the dominant feature, in human asthma, an initial exposure to allergen results in T(H)2 cell-dependent stimulation of the immune response that mediates the production of IgE and cytokines. Re-exposure to allergen then activates mast cells, which release mediators such as histamines and leukotrienes that recruit other cells, including T(H)2 cells, which mediate the inflammatory response in the lungs. In this minireview, we discuss the current understanding of how associated genetic and environmental factors increase the complexity of allergic asthma and the challenges allergic asthma poses for the development of novel approaches to effective treatment and prevention.

The lung: the natural boundary between nature and nurture

Common lung diseases such as asthma, COPD, and pulmonary fibrosis cause significant morbidity and mortality in the U.S. and worldwide. Research investigating the mechanisms of disease etiology has clearly indicated that genetic attributes and environmental exposures each play important roles in the development of these diseases. Emerging evidence underscores the importance of the interplay between genetic predisposition and environmental factors in fully understanding the development of lung disease. Herein we discuss recent advances in knowledge and technology surrounding the role of genetics, the environment, and gene-environment interactions in these common lung diseases.

Effect of gene environment interactions on lung function and cardiovascular disease in COPD

Background:

The objective of this study was to determine if gene-environment interactions between cigarette smoking and interleukin-6 (IL6), interferon-γ (IFNG), interleukin-1β (IL1B), or interleukin-1 receptor antagonist (IL1RN) single nucleotide polymorphisms are associated with lung function decline and cardiovascular disease in chronic obstructive pulmonary disease (COPD).

Methods:

Single nucleotide polymorphisms (SNPs) in IL6, IFNG, IL1B, and IL1RN were genotyped in the Lung Health Study and correlated with rate of decline of forced expiratory volume in 1 second (FEV₁) over 5 years, baseline FEV₁, serum protein levels, cardiovascular disease, and interactions with smoking.

Results:

The IL6 rs2069825 single nucleotide polymorphism was associated with the rate of decline of prebronchodilator FEV₁ (P = 0.049), and was found to have a significant interaction (P = 0.004) with mean number of cigarettes smoked per day. There was also a significant interaction of IFNG rs2069727 with smoking on prebronchodilator (P = 0.008) and postbronchodilator (P =0.01) FEV_1. The IL6 polymorphism was also associated with cardiovascular disease in heterozygous individuals (P = 0.044), and was found to have a significant interaction with smoking (P = 0.024). None of the genetic variants were associated with their respective serum protein levels.

Conclusion:

The results suggest interactions of IL6 rs2069825 and IFNG rs2069727 single nucleotide polymorphisms with cigarette smoking on measures of lung function. The IL6 rs2069825 single nucleotide polymorphism also interacted with smoking to affect the risk of cardiovascular disease in COPD patients.

Gene-environment interactions in human disease: nuisance or opportunity?

Many environmental risk factors for common, complex human diseases have been revealed by epidemiologic studies, but how genotypes at specific loci modulate individual responses to environmental risk factors is largely unknown. Gene-environment interactions will be missed in genome-wide association studies and could account for some of the 'missing heritability' for these diseases. In this review, we focus on asthma as a model disease for studying gene-environment interactions because of relatively large numbers of candidate gene-environment interactions with asthma risk in the literature. Identifying these interactions using genome-wide approaches poses formidable methodological problems, and elucidating molecular mechanisms for these interactions has been challenging. We suggest that studying gene-environment interactions in animal models, although more tractable, might not be sufficient to shed light on the genetic architecture of human diseases. Lastly, we propose avenues for future studies to find gene-environment interactions.

Overview of the symposium on public health significance of genomics and eco-genetics

Genomic and genetic information is rapidly becoming a major element in public health research and emerging public health practice. This symposium reviews the methods, findings, and significance of genome-wide association studies from epidemiological and statistical points of view. We examine infectious and inflammatory components of gene-environment interaction in the respiratory system. We note the need for nutrient and dietary data and many other kinds of environmental exposure data in population-based genomic studies. Then we explore the sufficiency of a well-informed family history for public health and family counseling purposes. Finally, in an era of direct-to-consumer genomic test promotion, we review the evidence on the critical question, will genetic risk profiles motivate individuals and families to choose more healthful behaviors? This symposium builds on the foundation of the symposium on Public Health Genetics in Volume 21 (2000) of the Annual Review of Public Health.