Smoking Interaction with a Polygenic Risk Score for Reduced Lung Function

Kim, Won‐Seok; Moll, Matthew; Qiao, Dandi; Hobbs, Brian D.; Shrine, Nick; Sakornsakolpat, Phuwanat; Tobin, Martin D.; Dudbridge, Frank; Wain, Louise V.; Ladd‐Acosta, Christine; Chatterjee, Nilanjan; Silverman, EK; Cho, MH; Beaty, TH

doi:10.1101/2021.03.26.21254415

Cited by 4 publications

(5 citation statements)

References 39 publications

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“…Furthermore, in line with previous results in the literature, we observed a significant interaction with ever-smoking and pack-years of smoking for FEV1/FVC (Kim et al, 2021;Aschard et al, 2017).…”

Section: Resultssupporting

confidence: 92%

“…In addition, Aschard et al observed an interaction between a genetic risk score for FEV1/FVC and ever-smoking status (Aschard et al, 2017). Related, Kim et al also observed highly significant interactions between genome-wide polygenic risk scores for lung function and smoking variables (Kim et al, 2021). While detecting significant interactions on this aggregated level is encouraging, identification of individual genes and pathways is challenging based on such results.…”

Section: Introductionmentioning

confidence: 99%

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A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables

Hecker

Prokopenko

Moll

et al. 2021

Preprint

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The identification and understanding of gene-environment interactions can provide insights into the pathways and mechanisms underlying complex diseases. However, testing for gene-environment interaction remains a challenge since statistical power is often limited, the specification of environmental effects is nontrivial, and such misspecifications can lead to false positive findings. To address the lack of statistical power, recent methods aim to identify interactions on an aggregated level using, for example, polygenic risk scores. While this strategy increases power to detect interactions, identifying contributing key genes and pathways is difficult based on these global results.Here, we propose RITSS (Robust Interaction Testing using Sample Splitting), a gene-environment interaction testing framework for quantitative traits that is based on sample splitting and robust test statistics. RITSS can incorporate multiple genetic variants and/or multiple environmental factors. Using sample splitting, a screening step enables the selection and combination of potential interactions into scores with improved interpretability, based on the user’s unrestricted choices for statistical/machine learning approaches. In the testing step, the application of robust test statistics minimizes the susceptibility of the results to main effect misspecifications.Using extensive simulation studies, we demonstrate that RITSS controls the type 1 error rate in a wide range of scenarios. In an application to lung function phenotypes and human height in the UK Biobank, RITSS identified genome-wide significant interactions with subcomponents of genetic risk scores. While the contributing single variant interactions are moderate, our analysis results indicate interesting interaction patterns that result in strong aggregated signals that provide further insights into gene-environment interaction mechanisms.

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Section: Resultssupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables

Hecker

Prokopenko

Moll

et al. 2021

Preprint

Self Cite

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“…In addition, the PRS may be associated with genetic susceptibility to environmental exposure-induced injury and consequently the rate of early lung function decline. For example, genetic factors may modify the effect of cigarette smoking on the development of COPD [27][28][29][30].…”

Section: Discussionmentioning

confidence: 99%

A polygenic risk score and age of diagnosis of COPD

Zhang

Xu²,

Qiao³

et al. 2022

Eur Respir J

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Genetic susceptibility may be associated with earlier onset of chronic obstructive pulmonary disease (COPD). We hypothesised that a polygenic risk score (PRS) for COPD would be associated with earlier age of diagnosis of COPD. In 6647 non-Hispanic white (NHW) and 2464 African American (AA) participants from COPDGene, and 6812 participants from the Framingham Heart Study (FHS), we tested the relationship of the PRS and age of COPD diagnosis. Age at diagnosis was determined by: 1) self-reported age at COPD diagnosis, or 2) age at visits when moderate-to-severe airflow limitation (GOLD 2–4) was observed on spirometry. We used Cox regression to examine the overall and time-dependent effects of the PRS on incident COPD. In the COPDGene study, we also examined the PRS's predictive value for COPD at age<50 years (COPD50) using logistic regression and area-under-the-curve (AUC) analyses, with and without the addition of other risk factors present at early life (e.g., childhood asthma). In Cox models, the PRS demonstrated age-dependent associations with incident COPD, with larger effects at younger ages in both cohorts. The PRS was associated with COPD50 (OR [95% CI]: NHW 1.55 [1.41–1.71], AA 1.23 [1.05–1.43], FHS 2.47 [2.12–2.88]). In COPDGene, adding the PRS to known early-life risk factors improved prediction of COPD50 in NHW (AUC 0.69 versus 0.74, p<0.0001) and AA participants (AUC 0.61 versus 0.64, p=0.04). A COPD polygenic risk score is associated with earlier age of diagnosis of COPD and retains predictive value when added to known early-life risk factors.

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“…The many genomewide association studies (GWAS) of lung function measures [14][15][16][17][18][19][20][21][22][23][24][25] have implicated pathways related to lung development [20,[26][27][28], inflammation [26], and tissue repair [29], among others [29]. Lung function is also affected by environmental exposures, such as smoking [30][31][32] and air pollution [33], which can disrupt airway development in early life, increasing the risk of childhood asthma and perhaps other chronic obstructive diseases [8][9][10][11][12]34,35]. For under accession phs002921.v1.p1.…”

Section: Introductionmentioning

confidence: 99%

Multi-omic association study identifies DNA methylation-mediated genotype and smoking exposure effects on lung function in children living in urban settings

et al. 2023

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Impaired lung function in early life is associated with the subsequent development of chronic respiratory disease. Most genetic associations with lung function have been identified in adults of European descent and therefore may not represent those most relevant to pediatric populations and populations of different ancestries. In this study, we performed genome-wide association analyses of lung function in a multiethnic cohort of children (n = 1,035) living in low-income urban neighborhoods. We identified one novel locus at the TDRD9 gene in chromosome 14q32.33 associated with percent predicted forced expiratory volume in one second (FEV1) (p = 2.4x10-9; βz = -0.31, 95% CI = -0.41- -0.21). Mendelian randomization and mediation analyses revealed that this genetic effect on FEV1 was partially mediated by DNA methylation levels at this locus in airway epithelial cells, which were also associated with environmental tobacco smoke exposure (p = 0.015). Promoter-enhancer interactions in airway epithelial cells revealed chromatin interaction loops between FEV1-associated variants in TDRD9 and the promoter region of the PPP1R13B gene, a stimulator of p53-mediated apoptosis. Expression of PPP1R13B in airway epithelial cells was significantly associated the FEV1 risk alleles (p = 1.3x10-5; β = 0.12, 95% CI = 0.06–0.17). These combined results highlight a potential novel mechanism for reduced lung function in urban youth resulting from both genetics and smoking exposure.

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Smoking Interaction with a Polygenic Risk Score for Reduced Lung Function

Cited by 4 publications

References 39 publications

A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables

A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables

A polygenic risk score and age of diagnosis of COPD

Multi-omic association study identifies DNA methylation-mediated genotype and smoking exposure effects on lung function in children living in urban settings

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