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

Jong, Kim de; Vonk, Judith M.; Timens, Wim; Bossé, Yohan; Sin, Don D.; Hao, Ke; Kromhout, Hans; Vermeulen, Roel; Postma, Dirkje S.; Boezen, H. Marike

doi:10.1016/j.jaci.2015.03.042

Cited by 31 publications

(25 citation statements)

References 51 publications

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“…In the current study, we found that the G allele of the rs2910164 SNP (OR = 1.416, 95% CI 1.020-1.967, p < 0.037) is a risk factor for COPD development. Regarding rs473892, which is located in intergenic regions at chromosome 6 near the gene OLIG3, the T allele of rs473892 was associated with a higher FEV1 level in subjects with high exposure to mineral dust than in those without exposure in the LifeLines and Vlagtwedde-Vlaardingen samples [70]. In the present study, we found that the C allele of rs473892 (OR = 1.473, 95% CI 1.008-2.152, P < 0.045) was a risk factor for COPD development.…”

Section: The Role Of Six Risk Snps In Copdmentioning

confidence: 99%

Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population

Zhang³

et al. 2020

J Transl Med

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Background: Chronic obstructive pulmonary disease (COPD) is a major public health problem and cause of mortality worldwide. However, COPD in the early stage is usually not recognized and diagnosed. It is necessary to establish a risk model to predict COPD development. Methods: A total of 441 COPD patients and 192 control subjects were recruited, and 101 single-nucleotide polymorphisms (SNPs) were determined using the MassArray assay. With 5 clinical features as well as SNPs, 6 predictive models were established and evaluated in the training set and test set by the confusion matrix AU-ROC, AU-PRC, sensitivity (recall), specificity, accuracy, F1 score, MCC, PPV (precision) and NPV. The selected features were ranked.

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Section: The Role Of Six Risk Snps In Copdmentioning

confidence: 99%

Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population

Zhang³

et al. 2020

J Transl Med

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“…The LifeLines cohort study is a prospective population-based cohort studying health and health-related behavior of subjects from the three Northern provinces of the Netherlands [19, 20]. …”

Section: Methodsmentioning

confidence: 99%

“…The IlluminaCytoSNP-12 is an oligonucleotide chip designed to have a uniform spacing of markers across all chromosomes, with the majority of the markers on this chip reflecting common SNPs: 93% of the 301,232 markers on this chip reflect bi-allelic SNP markers. The applied genotyping quality control criteria in the LifeLines cohort and the Vlagtwedde-Vlaardingen cohort have been described before [19, 20]: Samples with call-rates of less than 95% were excluded as were samples of non-Caucasians and first degree relatives. SNPs were excluded if they had a genotype call-rate < 95%, minor allele frequency (MAF) < 1%, or a Hardy-Weinberg equilibrium (HWE) p- value < 10 −4 .…”

Section: Methodsmentioning

confidence: 99%

No convincing association between genetic markers and respiratory symptoms: results of a GWA study

et al. 2017

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BackgroundRespiratory symptoms are associated with accelerated lung function decline, and increased hospitalization and mortality rates in the general population. Although several environmental risk factors for respiratory symptoms are known, knowledge on genetic risk factors is lacking. We aim to identify genetic variants associated with respiratory symptoms by genome-wide association (GWA) analyses.MethodsWe conducted the first GWA study on cough, dyspnea and phlegm among 7,976 participants in the LifeLines I cohort and used the LifeLines II cohort (n = 5,260) and the Vlagtwedde-Vlaardingen cohort (n = 1,529) for replication.ResultsWe identified 50 SNPs that were assessed for replication. Rs16918212, located in the alpha-2-macroglobulin pseudogene 1 (A2MP1), was associated with cough in both the identification (odds ratio (OR) = 0.72, p = 5.41 × 10−5) and the meta-analyzed replication cohorts (OR = 0.83, p = 0.033). No other significant replicated associations were found.ConclusionsGiven that only 1 out of 50 SNPs showed significant replication (i.e. 2%) we conclude that we did not find a convincing association between genetic markers and respiratory symptoms. Since, environmental exposures are important risk factors for respiratory symptoms, the next step is to perform a genome-wide interaction (GWI) study to identify genetic susceptibility loci for respiratory symptoms in interaction with known harmful environmental exposures.Electronic supplementary materialThe online version of this article (doi:10.1186/s12931-016-0495-4) contains supplementary material, which is available to authorized users.

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“…Both genetic and environmental factors underlie the development of respiratory diseases like asthma and chronic obstructive pulmonary disease (COPD) [4]. Their interaction also plays a role, since individual differences in genetic susceptibility to environmental exposures exist [5,6]. Besides gene-by-environment interactions, epigenetic mechanisms have been hypothesised as the missing link between the genetic and environmental factors leading to disease [7].…”

Section: Environmental Exposures and Epigeneticsmentioning

confidence: 99%

Promoting respiratory public health through epigenetics research: an ERS Environment Health Committee workshop report

Barouki

Barry²,

Boezen

et al. 2018

Eur Respir J

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

Cited by 31 publications

References 51 publications

Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population

Comparison and development of machine learning tools for the prediction of chronic obstructive pulmonary disease in the Chinese population

No convincing association between genetic markers and respiratory symptoms: results of a GWA study

Promoting respiratory public health through epigenetics research: an ERS Environment Health Committee workshop report

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