Gene-environment interaction effects on lung function- a genome-wide association study within the Framingham heart study

Time-dependent gene-environment interactions are essential drivers of asthma initiation and persistence

Asthma is a clinical syndrome caused by heterogeneous underlying mechanisms with some of them having a strong genetic component. It is known that up to 82% of atopic asthma has a genetic background with the rest being influenced by environmental factors that cause epigenetic modification(s) of gene expression. The interaction between the gene(s) and the environment has long been regarded as the most likely explanation of asthma initiation and persistence. Lately, much attention has been given to the time frame the interaction occurs since the host response (immune or biological) to environmental triggers, differs at different developmental ages. The integration of the time variant into asthma pathogenesis is appearing to be equally important as the gene(s)-environment interaction. It seems that, all three factors should be present to trigger the asthma initiation and persistence cascade. Herein, we introduce the importance of the time variant in asthma pathogenesis and emphasize the long-term clinical significance of the time-dependent gene-environment interactions in childhood.

Airway inflammation in adolescents and elderly women: Chronic air pollution exposure and polygenic susceptibility

BACKGROUND AND AIM

The fractional exhaled nitric oxide (FeNO) concentration in the exhaled breath is a biomarker for eosinophilic airway inflammation. We explored the interplay between chronic air pollution exposure and polygenic susceptibility to airway inflammation at different critical age stages.

METHODS

Adolescents (15 yr) enrolled in the GINIplus/LISA birth cohorts (n = 2434) and 220 elderly women (75 yr on average) enrolled in the SALIA cohort with FeNO measurements available were investigated. Environmental main effects of the mean of ESCAPE land-use regression air pollutant concentrations within a time window of 15 years and main effects of the polygenic risk scores (PRS) using internal weights from elastic net regression of genome-wide derived single nucleotide polymorphisms were investigated. Furthermore, we examined gene-environment interaction (GxE) effects on natural log-transformed FeNO levels by adjusted linear regression models.

RESULTS

While we observed no significant environmental and polygenic main effects on airway inflammation in either age group, we found robust harmful effects of chronic nitrogen dioxide (NO₂) exposure in the GxE models for elderly women (16.2 % increase in FeNO, p-value = 0.027). Stratified analyses found GxE effects between the PRS and chronic NO₂ exposure in never-smoker elderly women and in adolescents without any inflammatory respiratory conditions.

CONCLUSIONS

FeNO measurement is a useful biomarker to detect higher risk of NO₂-induced eosinophilic airway inflammation in the elderly. There was limited evidence for GxE effects on airway inflammation in adolescents or the elderly. Further GxE studies in subpopulations should be conducted to investigate the assumption that susceptibility to airway inflammation differs between age stages.

Chronic air pollution-induced subclinical airway inflammation and polygenic susceptibility

Background

Air pollutants can activate low-grade subclinical inflammation which further impairs respiratory health. We aimed to investigate the role of polygenic susceptibility to chronic air pollution-induced subclinical airway inflammation.

Methods

We used data from 296 women (69–79 years) enrolled in the population-based SALIA cohort (Study on the influence of Air pollution on Lung function, Inflammation and Aging). Biomarkers of airway inflammation were measured in induced-sputum samples at follow-up investigation in 2007–2010. Chronic air pollution exposures at residential addresses within 15 years prior to the biomarker assessments were used to estimate main environmental effects on subclinical airway inflammation. Furthermore, we calculated internally weighted polygenic risk scores based on genome-wide derived single nucleotide polymorphisms. Polygenic main and gene-environment interaction (GxE) effects were investigated by adjusted linear regression models.

Results

Higher exposures to nitrogen dioxide (NO₂), nitrogen oxides (NO_x), particulate matter with aerodynamic diameters of ≤ 2.5 μm, ≤ 10 μm, and 2.5–10 µm significantly increased the levels of leukotriene (LT)B₄ by 19.7% (p-value = 0.005), 20.9% (p = 0.002), 22.1% (p = 0.004), 17.4% (p = 0.004), and 23.4% (p = 0.001), respectively. We found significant effects of NO₂ (25.9%, p = 0.008) and NO_x (25.9%, p-value = 0.004) on the total number of cells. No significant GxE effects were observed. The trends were mostly robust in sensitivity analyses.

Conclusions

While this study confirms that higher chronic exposures to air pollution increase the risk of subclinical airway inflammation in elderly women, we could not demonstrate a significant role of polygenic susceptibility on this pathway. Further studies are required to investigate the role of polygenic susceptibility.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02179-3.

Pathogenesis of chronic obstructive pulmonary disease: understanding the contributions of gene-environment interactions across the lifespan

The traditional view of chronic obstructive pulmonary disease (COPD) as a self-inflicted disease caused by tobacco smoking in genetically susceptible individuals has been challenged by recent research findings. COPD can instead be understood as the potential end result of the accumulation of gene-environment interactions encountered by an individual over the life course. Integration of a time axis in pathogenic models of COPD is necessary because the biological responses to and clinical consequences of different exposures might vary according to both the age of an individual at which a given gene-environment interaction occurs and the cumulative history of previous gene-environment interactions. Future research should aim to understand the effects of dynamic interactions between genes (G) and the environment (E) by integrating information from basic omics (eg, genomics, epigenomics, proteomics) and clinical omics (eg, phenomics, physiomics, radiomics) with exposures (the exposome) over time (T)-an approach that we refer to as GETomics. In the context of this approach, we argue that COPD should be viewed not as a single disease, but as a clinical syndrome characterised by a recognisable pattern of chronic symptoms and structural or functional impairments due to gene-environment interactions across the lifespan that influence normal lung development and ageing.

Interaction of Cigarette Smoking and Polygenic Risk Score on Reduced Lung Function

IMPORTANCE

The risk of airflow limitation and chronic obstructive pulmonary disease (COPD) is influenced by combinations of cigarette smoking and genetic susceptibility, yet it remains unclear whether gene-by-smoking interactions are associated with quantitative measures of lung function.

OBJECTIVE

To assess the interaction of cigarette smoking and polygenic risk score in association with reduced lung function.

DESIGN, SETTING, AND PARTICIPANTS

This UK Biobank cohort study included UK citizens of European ancestry aged 40 to 69 years with genetic and spirometry data passing quality control metrics. Data was analyzed from July 2020 to March 2021.

EXPOSURES

PRS of combined forced expiratory volume in 1 second (FEV1) and percent of forced vital capacity exhaled in the first second (FEV1/FVC), self-reported pack-years of smoking, ever- vs never-smoking status, and current- vs former- or never-smoking status.

MAIN OUTCOMES AND MEASURES

FEV1/FVC was the primary outcome. Models were used to test for interactions with models, including the main effects of PRS, different smoking variables, and their cross-product terms. The association between pack-years of smoking and FEV1/FVC were compared for those in the highest vs lowest decile of estimated genetic risk for low lung function.

RESULTS

We included 319 730 individuals, of whom 24 915 (8%) had moderate-to-severe COPD cases, and 44.4% were men. Participants had a mean (SD) age 56.5 of (8.02) years. The PRS and pack-years were significantly associated with lower FEV1/FVC (PRS: β, -0.03; 95% CI, -0.031 to -0.03; pack-years: β, -0.0064; 95% CI, -0.0064 to -0.0063) and the interaction term (β, -0.0028; 95% CI, -0.0029 to -0.0026). A stepwise increment in estimated effect sizes for these interaction terms was observed per 10 pack-years of smoking exposure. The interaction of PRS with 11 to 20, 31 to 40, and more than 50 pack-years categories were β (interaction) -0.0038 (95% CI, -0.0046 to -0.0031); -0.013 (95% CI, -0.014 to -0.012); and -0.017 (95% CI, -0.019 to -0.016), respectively. There was evidence of significant interaction between PRS with ever- or never- smoking status (β, interaction; -0.0064; 95% CI, -0.0068 to -0.0060) and current or not-current smoking (β, interaction; -0.0091; 95% CI, -0.0097 to -0.0084). For any given level of pack-years of smoking exposure, FEV1/FVC was significantly lower for individuals in the tenth decile (ie, highest risk) than the first decile (ie, lowest risk) of genetic risk. For every 20 pack-years of smoking, those in the tenth decile compared with the first decile of genetic risk showed nearly a 2-fold reduction in FEV1/FVC.

CONCLUSIONS AND RELEVANCE

COPD is characterized by diminished lung function, and our analyses suggest there is substantial interaction between genome-wide PRS and smoking exposures. While smoking was associated with decreased lung function across all genetic risk categories, the associations were strongest in individuals with higher estimated genetic risk.

The Cumulative Effect of Gene-Gene Interactions Between GSTM1, CHRNA3, CHRNA5 and SOD3 Gene Polymorphisms Combined with Smoking on COPD Risk

Background

Chronic obstructive pulmonary disease (COPD) is a multifactorial disorder which is affected by external and internal risk factors. People with no external risk factors may be significantly affected and develop pulmonary disease. The study aimed to define gene–gene and gene–environmental effects on COPD.

Methods

A case control study involved 181 COPD patients and 292 healthy individuals, with peripheral blood sampling and adequate questionnaires. Genotyping was done with various types of PCR design for GSTM1 (null del), GSTT1 (null del), EPHX1 (rs2234922 and rs1051740), GSTP1 (rs1695 and rs1138272), CHRNA3 (rs1051730 and rs12914385), CHRNA5 (rs16969968 and rs17486278), and SOD3 (rs1799895 and rs699473) gene polymorphisms. Gene–gene and gene–environmental interactions were investigated using multidimensional regression analysis.

Results

Frequency of risk alleles of rs1051730 (p = 0.001), rs16969968 (p <0.001), and rs1799895 (p <0.001) polymorphisms were significant in univariate analysis. For gene–gene interaction, GSTM1 null, rs1051730, rs16969968, and rs1799895 polymorphisms independently contributed to risk of COPD and any combinations of the risk genotypes have a higher risk of disease. A cumulative effect of the four risk polymorphisms increased the risk of COPD for the smoking index (cOR = 13.6, p <0.001), cigarettes per day (cOR = 32.08, p <0.01), nicotine dependence (cOR = 12.0, p <0.01), and smoking status (cOR = 17.02, p <0.01) for gene–environmental interaction.

Conclusion

Several pivotal genes showed distinct effects for COPD, and some synergistic effects affected the disease progression. The development of COPD was synergistically increased with gene–gene and gene–environmental risk factors.

The effects of gene × environment interactions on silver nanoparticle toxicity in the respiratory system: An adverse outcome pathway

The Adverse Outcome Pathway (AOP) framework is serving as a basis to integrate new data streams in order to enhance the power of predictive toxicology. AOP development for engineered nanomaterials (ENM), including silver nanoparticles (AgNP), is currently lagging behind other chemicals of regulatory interest due to our limited understanding of the mechanism by which underlying genetics or diseases directly modify host response to AgNP exposures. This also highlights the importance of considering the Aggregate Exposure Pathway (AEP) framework, which precedes the AOP framework and outlines source to target site exposure. The AEP and AOP frameworks interface at the target site, where a molecular initiating event (MIE) occurs and is followed by key events (KE) for adverse cellular and organ responses along a biological pathway and ends with the adverse organism response. The primary goal of this study is to use AgNP to interrogate the AEP-AOP framework by organizing and integrating in vitro dose-response data and in vivo exposure-response data from previous studies to evaluate the effects of interactions between host genetic and acquired factors, or gene × environment interactions (G × E), on AgNP toxicity in the respiratory system. Using this framework will help us to identify plausible key event relationships (KER) between MIE and adverse organism responses when KE are not measured using the same assay in order to derive future predictive models, guide research, and support development of tools for making risk-based, regulatory decisions on ENM. This article is categorized under: Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials Toxicology and Regulatory Issues in Nanomedicine > Regulatory and Policy Issues in Nanomedicine.

Biomarkers in Chronic Obstructive Pulmonary Disease: The Gateway to Precision Medicine

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease with limited adequate treatments. Biomarkers-which may relate to disease susceptibility, diagnosis, prognosis, or treatment response-are ideally suited to dissecting such a complex disease and form a critical component of the precision medicine paradigm. Not all potential candidates, however, make good biomarkers. To date, only plasma fibrinogen has been approved by regulatory bodies as a biomarker of exacerbation risk for clinical trial enrichment. This review outlines some of the challenges of biomarker research in COPD and highlights novel and promising biomarker candidates.

Spirometric traits show quantile-dependent heritability, which may contribute to their gene-environment interactions with smoking and pollution

Background

“Quantile-dependent expressivity” refers to a genetic effect that is dependent upon whether the phenotype (e.g., spirometric data) is high or low relative to its population distribution. Forced vital capacity (FVC), forced expiratory volume in 1 second (FEV₁), and the FEV₁/FVC ratio are moderately heritable spirometric traits. The aim of the analyses is to test whether their heritability (h²) is constant over all quantiles of their distribution.

Methods

Quantile regression was applied to the mean age, sex, height and smoking-adjusted spirometric data over multiple visits in 9,993 offspring-parent pairs and 1,930 sibships from the Framingham Heart Study to obtain robust estimates of offspring-parent (β_OP), offspring-midparent (β_OM), and full-sib regression slopes (β_FS). Nonparametric significance levels were obtained from 1,000 bootstrap samples. β_OPs were used as simple indicators of quantile-specific heritability (i.e., h² = 2β_OP/(1+r_spouse), where r_spouse was the correlation between spouses).

Results

β_OP ± standard error (SE) decreased by 0.0009 ± 0.0003 (P = 0.003) with every one-percent increment in the population distribution of FEV₁/FVC, i.e., β_OP ± SE were: 0.182 ± 0.031, 0.152 ± 0.015; 0.136 ± 0.011; 0.121 ± 0.013; and 0.099 ± 0.013 at the 10th, 25th, 50th, 75th, and 90th percentiles of the FEV₁/FVC distribution, respectively. These correspond to h² ± SEs of 0.350 ± 0.060 at the 10th, 0.292 ± 0.029 at the 25th, 0.262 ± 0.020 at the 50th, 0.234 ± 0.025 at the 75th, and 0.191 ± 0.025 at the 90th percentiles of the FEV₁/FVC ratio. Maximum mid-expiratory flow (MMEF) h² ± SEs increased 0.0025 ± 0.0007 (P = 0.0004) with every one-percent increment in its distribution, i.e.: 0.467 ± 0.046, 0.467 ± 0.033, 0.554 ± 0.038, 0.615 ± 0.042, and 0.675 ± 0.060 at the 10th, 25th, 50th, 75th, and 90th percentiles of its distribution. This was due to forced expiratory flow at 75% of FVC (FEF75%), whose quantile-specific h² increased an average of 0.0042 ± 0.0008 for every one-percent increment in its distribution. It is speculated that previously reported gene-environment interactions may be partially attributable to quantile-specific h², i.e., greater heritability in individuals with lower FEV₁/FVC due to smoking or airborne particles exposure vs. nonsmoking, unexposed individuals.

Conclusion

Heritabilities of FEV₁/FVC, MMEF, and FEF75% from quantile-regression of offspring-parent and sibling spirometric data suggest their quantile-dependent expressivity.

A genome-wide by PM10 interaction study identifies novel loci for lung function near BICD1 and IL1RN-IL1F10 genes in Korean adults

Although several genome-wide interaction studies (GWIS) have been performed in specific European populations to understand the missing link between genetic and environmental factors for lung function, GWIS of Asian samples remain rare. Therefore, we performed a GWIS of exposure to air pollution to identify loci for lung function in Korean adult men. A total of 1826 adult men recruited from two health check-up centers were included in the analysis and the annual mean concentrations of ambient particulate matter with an aerodynamic diameter ≤10 μm (PM₁₀) were used. In case of forced vital capacity (FVC), one SNP (rs12312730) that passed our genome-wide threshold of pint < 1 × 10-5 was detected in the intronic region of the BICD1 gene on chromosome 12. In addition, we found two variants (rs6743376 and rs17042888) located near the IL1RN-IL1F10 gene that were involved in the inflammatory response and associated with decreased FVC via interaction with PM₁₀ exposure. A stratified association analysis according to these SNP genotypes showed that PM₁₀ concentrations in subjects with one or two of the risk alleles, compared with those with the non-risk allele, were significantly correlated with a reduction in FVC. This pattern was replicated in another 892 Korean adult samples. The current study reports the first GWIS discovery in an Asian population: the BICD1 and IL1RN-IL1F10 genes may contribute to the decrease in FVC levels by interacting with PM₁₀ exposure.

Genetic susceptibility to asthma increases the vulnerability to indoor air pollution

INTRODUCTION

Indoor air pollution and maternal smoking during pregnancy are associated with respiratory symptoms in infants, but little is known about the direct association with lung function or interactions with genetic risk factors. We examined associations of exposure to indoor particulate matter with a 50% cut-off aerodynamic diameter of 10 µm (PM₁₀) and maternal smoking with infant lung function and the role of gene-environment interactions.

METHODS

Data from the Drakenstein Child Health Study, a South African birth cohort, were analysed (n=270). Lung function was measured at 6 weeks and 1 year of age, and lower respiratory tract infection episodes were documented. We measured pre- and postnatal PM₁₀ exposures using devices placed in homes, and prenatal tobacco smoke exposure using maternal urine cotinine levels. Genetic risk scores determined from associations with childhood-onset asthma in the UK Biobank were used to investigate effect modifications.

RESULTS

Pre- and postnatal exposure to PM₁₀ as well as maternal smoking during pregnancy were associated with reduced lung function at 6 weeks and 1 year as well as with lower respiratory tract infection in the first year. Due to a significant interaction between the genetic risk score and prenatal exposure to PM₁₀, infants carrying more asthma-related risk alleles were more susceptible to PM₁₀-associated reduced lung function (p_interaction=0.007). This interaction was stronger in infants with Black African ancestry (p_interaction=0.001) and nonexistent in children with mixed ancestry (p_interaction=0.876).

CONCLUSIONS

PM₁₀ and maternal smoking exposures were associated with reduced lung function, with a higher susceptibility for infants with an adverse genetic predisposition for asthma that also depended on the infant's ancestry.

Genetic underpinnings of lung function and COPD

Spirometry based measurement of lung function is a global initiative for chronic obstructive lung disease (GOLD) standard to diagnose chronic obstructive pulmonary disease (COPD), one of the leading causes of mortality worldwide. The environmental and behavioural risk factors for COPD includes tobacco smoking, air pollutants and biomass fuel exposure, which can induce one or more abnormal lung function patterns. While smoking remains the primary risk factor, only 15-20% smokers develop COPD, indicating that the genetic factors are also likely to play a role. According to the study of Global Burden of Disease 2015, ∼174 million people across the world have COPD. From a comprehensive literature search conducted using the 'PubMed' and 'GWAS Catalogue' databases, and reviewing the literature available, only a limited number of studies were identified which had attempted to investigate the genetics of COPD and lung volumes, implying a huge research gap. With the advent of genomewide association studies several genetic variants linked to lung function and COPD, like HHIP, HTR4, ADAM19 and GSTCD etc., have been found and validated in different population groups, suggesting their potential role in determining lung volume and risk for COPD. This article aims at reviewing the present knowledge of the genetics of lung function and COPD.

Omega-3 Fatty Acids and Genome-Wide Interaction Analyses Reveal DPP10-Pulmonary Function Association

RATIONALE

Omega-3 polyunsaturated fatty acids (n-3 PUFAs) have anti-inflammatory properties that could benefit adults with comprised pulmonary health.

OBJECTIVE

To investigate n-3 PUFA associations with spirometric measures of pulmonary function tests (PFTs) and determine underlying genetic susceptibility.

METHODS

Associations of n-3 PUFA biomarkers (α-linolenic acid, eicosapentaenoic acid, docosapentaenoic acid [DPA], and docosahexaenoic acid [DHA]) were evaluated with PFTs (FEV1, FVC, and FEV1/FVC) in meta-analyses across seven cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (N = 16,134 of European or African ancestry). PFT-associated n-3 PUFAs were carried forward to genome-wide interaction analyses in the four largest cohorts (N = 11,962) and replicated in one cohort (N = 1,687). Cohort-specific results were combined using joint 2 degree-of-freedom (2df) meta-analyses of SNP associations and their interactions with n-3 PUFAs.

RESULTS

DPA and DHA were positively associated with FEV1 and FVC (P < 0.025), with evidence for effect modification by smoking and by sex. Genome-wide analyses identified a novel association of rs11693320-an intronic DPP10 SNP-with FVC when incorporating an interaction with DHA, and the finding was replicated (P2df = 9.4 × 10-9 across discovery and replication cohorts). The rs11693320-A allele (frequency, ∼80%) was associated with lower FVC (PSNP = 2.1 × 10-9; βSNP = -161.0 ml), and the association was attenuated by higher DHA levels (PSNP×DHA interaction = 2.1 × 10-7; βSNP×DHA interaction = 36.2 ml).

CONCLUSIONS

We corroborated beneficial effects of n-3 PUFAs on pulmonary function. By modeling genome-wide n-3 PUFA interactions, we identified a novel DPP10 SNP association with FVC that was not detectable in much larger studies ignoring this interaction.

Genome-wide interaction study of gene-by-occupational exposures on respiratory symptoms

Respiratory symptoms are important indicators of respiratory diseases. Both genetic and environmental factors contribute to respiratory symptoms development but less is known about gene-environment interactions. We aimed to assess interactions between single nucleotide polymorphisms (SNPs) and occupational exposures on respiratory symptoms cough, dyspnea and phlegm. As identification cohort LifeLines I (n = 7976 subjects) was used. Job-specific exposure was estimated using the ALOHA + job exposure matrix. SNP-by-occupational exposure interactions on respiratory symptoms were tested using logistic regression adjusted for gender, age, and current smoking. SNP-by-exposure interactions with a p-value <10^-4 were tested for replication in two independent cohorts: LifeLines II (n = 5260) and the Vlagtwedde-Vlaardingen cohort (n = 1529). The interaction estimates of the replication cohorts were meta-analyzed using PLINK. Replication was achieved when the meta-analysis p-value was <0.05 and the interaction effect had the same direction as in the identification cohort. Additionally, we assessed whether replicated SNPs associated with gene expression by analyzing if they were cis-acting expression quantitative trait loci (eQTL) in lung tissue. In the replication meta-analysis, sixteen out of 477 identified SNP-by-occupational exposure interactions had a p-value <0.05 and 9 of these interactions had the same direction as in the identification cohort. Several identified loci were plausible candidates for respiratory symptoms, such as TMPRSS9, SERPINH1, TOX3, and ARHGAP18. Three replicated SNPs were cis-eQTLs for FCER1A, CHN1, and TIMM13 in lung tissue. Taken together, this genome-wide SNP-by-occupational exposure interaction study in relation to cough, dyspnea, and phlegm identified several suggestive susceptibility genes. Further research should determine if these genes are true susceptibility loci for respiratory symptoms in relation to occupational exposures.

An ancestry-based approach for detecting interactions

BACKGROUND

Epistasis and gene-environment interactions are known to contribute significantly to variation of complex phenotypes in model organisms. However, their identification in human association studies remains challenging for myriad reasons. In the case of epistatic interactions, the large number of potential interacting sets of genes presents computational, multiple hypothesis correction, and other statistical power issues. In the case of gene-environment interactions, the lack of consistently measured environmental covariates in most disease studies precludes searching for interactions and creates difficulties for replicating studies.

RESULTS

In this work, we develop a new statistical approach to address these issues that leverages genetic ancestry, defined as the proportion of ancestry derived from each ancestral population (e.g., the fraction of European/African ancestry in African Americans), in admixed populations. We applied our method to gene expression and methylation data from African American and Latino admixed individuals, respectively, identifying nine interactions that were significant at P<5×10-8. We show that two of the interactions in methylation data replicate, and the remaining six are significantly enriched for low P-values (P<1.8×10-6).

CONCLUSION

We show that genetic ancestry can be a useful proxy for unknown and unmeasured covariates in the search for interaction effects. These results have important implications for our understanding of the genetic architecture of complex traits.

Genome-wide interaction study of gene-by-occupational exposure and effects on FEV1 levels

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a complex disease characterized by impaired lung function and airway obstruction resulting from interactions between multiple genes and multiple environmental exposures. Thus far, genome-wide association studies have largely disregarded environmental factors that might trigger the development of lung function impairment and COPD, such as occupational exposures, which are thought to contribute to 15% to 20% of the COPD prevalence.

OBJECTIVES

We performed a genome-wide interaction study to identify novel susceptibility loci for occupational exposure to biological dust, mineral dust, and gases and fumes in relation to FEV1 levels.

METHODS

We performed an identification analysis in 12,400 subjects from the LifeLines cohort study and verified our findings in 1436 subjects from a second independent cohort, the Vlagtwedde-Vlaardingen cohort. Additionally, we assessed whether replicated single nucleotide polymorphisms (SNPs) were cis-acting expression (mRNA) quantitative trait loci in lung tissue.

RESULTS

Of the 7 replicated SNPs that interacted with one of the occupational exposures, several identified loci were plausible candidates that might be involved in biological pathways leading to lung function impairment, such as PCDH9 and GALNT13. Two of the 7 replicated SNPs were cis-acting expression quantitative trait loci associated with gene expression of PDE4D and TMEM176A in lung tissue.

CONCLUSION

This genome-wide interaction study on occupational exposures in relation to the level of lung function identified several novel genes. Further research should determine whether the identified genes are true susceptibility loci for occupational exposures and whether these SNP-by-exposure interactions consequently contribute to the development of COPD.

Kernel Approach for Modeling Interaction Effects in Genetic Association Studies of Complex Quantitative Traits

The etiology of complex traits likely involves the effects of genetic and environmental factors, along with complicated interaction effects between them. Consequently, there has been interest in applying genetic association tests of complex traits that account for potential modification of the genetic effect in the presence of an environmental factor. One can perform such an analysis using a joint test of gene and gene-environment interaction. An optimal joint test would be one that remains powerful under a variety of models ranging from those of strong gene-environment interaction effect to those of little or no gene-environment interaction effect. To fill this demand, we have extended a kernel machine based approach for association mapping of multiple SNPs to consider joint tests of gene and gene-environment interaction. The kernel-based approach for joint testing is promising, because it incorporates linkage disequilibrium information from multiple SNPs simultaneously in analysis and permits flexible modeling of interaction effects. Using simulated data, we show that our kernel machine approach typically outperforms the traditional joint test under strong gene-environment interaction models and further outperforms the traditional main-effect association test under models of weak or no gene-environment interaction effects. We illustrate our test using genome-wide association data from the Grady Trauma Project, a cohort of highly traumatized, at-risk individuals, which has previously been investigated for interaction effects.

Occupational exposures and longitudinal lung function decline

BACKGROUND

Few longitudinal studies have been conducted on occupational exposure and lung function. This study investigated occupational dust exposure effects on lung function and whether genetic variants influence such effects.

METHODS

The study population (1,332 participants) was from the Framingham Heart Study, in which participant lung function measures were available from up to five examinations over nearly 17 years. Occupational dust exposures were classified into "more" and "less" likely dust exposure. We used linear mixed effects models for the analysis.

RESULTS

Participants with more likely dust exposure had a mean 4.5 mL/year excess loss rate of FEV1 over time. However, occupational dust exposures alone or interactions with age or time had no significant effect on FEV1 /FVC. No statistically significant effects of genetic modifications in the different subgroups were identified for FEV1 loss.

CONCLUSIONS

Occupational dust exposures may accelerate the rate of FEV1 loss but not FEV1 /FVC loss.

Modification of the association between PM10 and lung function decline by cadherin 13 polymorphisms in the SAPALDIA cohort: a genome-wide interaction analysis

BACKGROUND

Both air pollution and genetic variation have been shown to affect lung function. Their interaction has not been studied on a genome-wide scale to date.

OBJECTIVES

We aimed to identify, in an agnostic fashion, genes that modify the association between long-term air pollution exposure and annual lung function decline in an adult population-based sample.

METHODS

A two-stage genome-wide interaction study was performed. The discovery (n = 763) and replication (n = 3,896) samples were derived from the multi-center SAPALDIA cohort (Swiss Cohort Study on Air Pollution and Lung Disease in Adults). Annual rate of decline in the forced mid-expiratory flow (FEF25-75%) was the main end point. Multivariate linear regression analyses were used to identify potential multiplicative interactions between genotypes and 11-year cumulative PM10 exposure.

RESULTS

We identified a cluster of variants intronic to the CDH13 gene as the only locus with genome-wide significant interactions. The strongest interaction was observed for rs2325934 (p = 8.8 × 10(-10)). Replication of the interaction between this CDH13 variant and cumulative PM10 exposure on annual decline in FEF25-75% was successful (p = 0.008). The interaction was not sensitive to adjustment for smoking or body weight.

CONCLUSIONS

CDH13 is functionally linked to the adipokine adiponectin, an inflammatory regulator. Future studies need to confirm the interaction and assess how the result relates to previously observed interactions between air pollution and obesity on respiratory function.

Gene-age interactions in blood pressure regulation: a large-scale investigation with the CHARGE, Global BPgen, and ICBP Consortia

Although age-dependent effects on blood pressure (BP) have been reported, they have not been systematically investigated in large-scale genome-wide association studies (GWASs). We leveraged the infrastructure of three well-established consortia (CHARGE, GBPgen, and ICBP) and a nonstandard approach (age stratification and metaregression) to conduct a genome-wide search of common variants with age-dependent effects on systolic (SBP), diastolic (DBP), mean arterial (MAP), and pulse (PP) pressure. In a two-staged design using 99,241 individuals of European ancestry, we identified 20 genome-wide significant (p ≤ 5 × 10(-8)) loci by using joint tests of the SNP main effect and SNP-age interaction. Nine of the significant loci demonstrated nominal evidence of age-dependent effects on BP by tests of the interactions alone. Index SNPs in the EHBP1L1 (DBP and MAP), CASZ1 (SBP and MAP), and GOSR2 (PP) loci exhibited the largest age interactions, with opposite directions of effect in the young versus the old. The changes in the genetic effects over time were small but nonnegligible (up to 1.58 mm Hg over 60 years). The EHBP1L1 locus was discovered through gene-age interactions only in whites but had DBP main effects replicated (p = 8.3 × 10(-4)) in 8,682 Asians from Singapore, indicating potential interethnic heterogeneity. A secondary analysis revealed 22 loci with evidence of age-specific effects (e.g., only in 20 to 29-year-olds). Age can be used to select samples with larger genetic effect sizes and more homogenous phenotypes, which may increase statistical power. Age-dependent effects identified through novel statistical approaches can provide insight into the biology and temporal regulation underlying BP associations.