Interaction of Interleukin 7 Receptor (<i>IL7R</i>) and <i>IL6</i> Gene Polymorphisms with Smoking Associated with Susceptibility to Asthma in Chinese Han Adults

Du, Junwei; Xu, Ze-Lan; Xu, Qinxing

doi:10.1080/08820139.2021.1941083

Cited by 6 publications

(6 citation statements)

References 33 publications

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“…The effects of the environment on the genetic composition and vice versa have been mostly investigated in childhood traits, except for two studies focused on adults. 29,30 Additionally, the exploration of gene interactions with early-life environmental exposure to tobacco smoke in asthma susceptibility remains the most studied setting (Table 1). As a result, these studies have suggested interaction effects of known asthma genes with environmental tobacco smoke exposure during childhood (IL1RN, NFE2L2), 31,32 and a novel locus for asthma susceptibility (NAT1) 33 (Table 2).…”

Section: Inter Ac Ti Ons B E T Ween G Ene S and The Environmentmentioning

confidence: 99%

“…To our knowledge, a total of 12 GxE studies have been published from April 2019 to the time of writing (February 2022; Table 1), including nine using a candidate‐gene interaction approach and only three GWIS. The effects of the environment on the genetic composition and vice versa have been mostly investigated in childhood traits, except for two studies focused on adults 29,30 . Additionally, the exploration of gene interactions with early‐life environmental exposure to tobacco smoke in asthma susceptibility remains the most studied setting (Table 1).…”

Section: Interactions Between Genes and The Environmentmentioning

confidence: 99%

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Gene‐environment interactions in childhood asthma revisited; expanding the interaction concept

Hernandez‐Pacheco

Kere

2022

Pediatric Allergy Immunology

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Investigation of gene‐environment interactions (GxE) may provide important insights into the gene regulatory framework in response to environmental factors of relevance for childhood asthma. Over the years, different methodological strategies have been applied, more recently using genome‐wide approaches. The best example to date is the major asthma locus on the 17q12‐21 chromosome region, viral infections, and airway epithelium processes where recent studies have shed much light on mechanisms in childhood asthma. However, there are challenges with the traditional single variant—single exposure interaction models, as they do not encompass the complexity and cumulative effects of multiple exposures or multiple genetic variants. As such, we need to redefine our traditional GxE thinking, and we propose in this review to expand the GxE concept by also evaluating other omics layers, such as epigenetics, transcriptomics, metabolomics, and proteomics. In addition, host factors such as age, gender, and other exposures are very likely to influence GxE effects and need firmly to be considered in future studies.

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Section: Inter Ac Ti Ons B E T Ween G Ene S and The Environmentmentioning

confidence: 99%

Section: Interactions Between Genes and The Environmentmentioning

confidence: 99%

Gene‐environment interactions in childhood asthma revisited; expanding the interaction concept

Hernandez‐Pacheco

Kere

2022

Pediatric Allergy Immunology

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“…It can also reduce the allergen threshold through oxidative stress suppressing PI3K-δ/Akt pathway, activating mTOR pathway, inducing cellular senescence and other mechanisms, thereby leading to an increase in IgE and augmenting Th2-type immune responses, and ultimately increasing the risk of asthma [25][26][27][28]. In addition, CS containing high concentrations of reactive oxygen species can activate airway epithelial cells to synthesize and release inflammatory mediators such as interleukin (IL)-6 and IL-8, as well as recruit and activate neutrophils and macrophages, resulting in increased neutrophils in lung tissue [25,[29][30][31]. Furthermore, it can also promote the further production of oxygen free radicals in the airway epithelium of asthmatic patients, aggravate original airway injury, lead to a higher number of inflammatory cells, more severe ciliary detachment, and thicker bronchial smooth muscle compared to non-smokers, ultimately accelerating airway remodeling [25,32].…”

Section: Discussionmentioning

confidence: 99%

Risk factor analysis and nomogram for predicting poor symptom control in smoking asthmatics

Ma,

Chen,

et al. 2024

BMC Pulm Med

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Background Smoking induces and modifies the airway immune response, accelerating the decline of asthmatics’ lung function and severely affecting asthma symptoms’ control level. To assess the prognosis of asthmatics who smoke and to provide reasonable recommendations for treatment, we constructed a nomogram prediction model. Methods General and clinical data were collected from April to September 2021 from smoking asthmatics aged ≥14 years attending the People’s Hospital of Zhengzhou University. Patients were followed up regularly by telephone or outpatient visits, and their medication and follow-up visits were recorded during the 6-months follow-up visit, as well as their asthma control levels after 6 months (asthma control questionnaire-5, ACQ-5). The study employed R4.2.2 software to conduct univariate and multivariate logistic regression analyses to identify independent risk factors for ‘poorly controlled asthma’ (ACQ>0.75) as the outcome variable. Subsequently, a nomogram prediction model was constructed. Internal validation was used to test the reproducibility of the model. The model efficacy was evaluated using the consistency index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve. Results Invitations were sent to 231 asthmatics who smoked. A total of 202 participants responded, resulting in a final total of 190 participants included in the model development. The nomogram established five independent risk factors (P<0.05): FEV1%pred, smoking index (100), comorbidities situations, medication regimen, and good or poor medication adherence. The area under curve (AUC) of the modeling set was 0.824(95%CI 0.765-0.884), suggesting that the nomogram has a high ability to distinguish poor asthma control in smoking asthmatics after 6 months. The calibration curve showed a C-index of 0.824 for the modeling set and a C-index of 0.792 for the self-validation set formed by 1000 bootstrap sampling, which means that the prediction probability of the model was consistent with reality. Decision curve analysis (DCA) of the nomogram revealed that the net benefit was higher when the risk threshold probability for poor asthma control was 4.5 − 93.9%. Conclusions FEV1%pred, smoking index (100), comorbidities situations, medication regimen, and medication adherence were identified as independent risk factors for poor asthma control after 6 months in smoking asthmatics. The nomogram established based on these findings can effectively predict relevant risk and provide clinicians with a reference to identify the poorly controlled population with smoking asthma as early as possible, and to select a better therapeutic regimen. Meanwhile, it can effectively improve the medication adherence and the degree of attention to complications in smoking asthma patients.

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“…A gene-smoking environmental interaction exists in asthmatic patients who carry the rs1800795 SNP of the IL-6 gene [ 149 ]. Although the uncommon rs2234678 SNP of the IL1RN gene is protective against the development of asthma in those without childhood tobacco exposure, those carrying this SNP with childhood environmental tobacco exposure, are at higher risk of early onset asthma [ 150 ].…”

Section: Interactions Between Genetic Polymorphisms and Environmental...mentioning

confidence: 99%

The Genetic Factors of the Airway Epithelium Associated with the Pathology of Asthma

Ranjbar

Whetstone

Omer

et al. 2022

Genes

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Asthma is a chronic disease of the airways characterized by inflammation, tightened muscles, and thickened airway walls leading to symptoms such as shortness of breath, chest tightness, and cough in patients. The increased risk of asthma in children of asthmatics parents supports the existence of genetic factors involved in the pathogenesis of this disease. Genome-wide association studies have discovered several single nucleotide polymorphisms associated with asthma. These polymorphisms occur within several genes and can contribute to different asthma phenotypes, affect disease severity, and clinical response to different therapies. The complexity in the etiology of asthma also results from interactions between environmental and genetic factors. Environmental exposures have been shown to increase the prevalence of asthma in individuals who are genetically susceptible. This review summarizes what is currently known about the genetics of asthma in relation to risk, response to common treatments, and gene-environmental interactions.

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Interaction of Interleukin 7 Receptor (IL7R) and IL6 Gene Polymorphisms with Smoking Associated with Susceptibility to Asthma in Chinese Han Adults

Cited by 6 publications

References 33 publications

Gene‐environment interactions in childhood asthma revisited; expanding the interaction concept

Gene‐environment interactions in childhood asthma revisited; expanding the interaction concept

Risk factor analysis and nomogram for predicting poor symptom control in smoking asthmatics

The Genetic Factors of the Airway Epithelium Associated with the Pathology of Asthma

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