Additional file 1: Table S1. of Mutations in TP53 increase the risk of SOX2 copy number alterations and silencing of TP53 reduces SOX2 expression in non-small cell lung cancer

Association between clinicopathological data and SOX2 gene status in NSCLC tumors. (PDF 101 kb

Chronic obstructive pulmonary disease and related phenotypes: polygenic risk scores in population-based and case-control cohorts

Background: Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes.Methods: We constructed a polygenic risk score using a genome wide association study of lung function (FEV1 and FEV1/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV1/FVC Findings: The polygenic risk score was associated with COPD in European (odds ratio [OR] per SD 1·81 [95% CI 1·74–1·88] and non-European (1·42 [1·34–1·51]) populations. Compared with the first decile, the tenth decile of the polygenic risk score was associated with COPD, with an OR of 7·99 (6·56–9·72) in European ancestry and 4·83 (3·45–6·77) in non-European ancestry cohorts. The polygenic risk score was superior to previously described genetic risk scores and, when combined with clinical risk factors (ie, age, sex, and smoking pack-years), showed improved prediction for COPD compared with a model comprising clinical risk factors alone (AUC 0·80 [0·79–0·81] vs 0·76 [0·75 0·76]). The polygenic risk score was associated with CT imaging phenotypes, including wall area percent, quantitative and qualitative measures of emphysema, local histogram emphysema patterns, and destructive emphysema subtypes. The polygenic risk score was associated with a reduced lung growth pattern. Interpretation: A risk score comprised of genetic variants can identify a small subset of individuals at markedly increased risk for moderate-to-severe COPD, emphysema subtypes associated with cigarette smoking, and patterns of reduced lung growth.</div

Genetic Associations and Architecture of Asthma-COPD Overlap

Background Some people have characteristics of both asthma and COPD (asthma-COPD overlap), and evidence suggests they experience worse outcomes than those with either condition alone. Research Question What is the genetic architecture of asthma-COPD overlap, and do the determinants of risk for asthma-COPD overlap differ from those for COPD or asthma? Study Design and Methods We conducted a genome-wide association study in 8,068 asthma-COPD overlap case subjects and 40,360 control subjects without asthma or COPD of European ancestry in UK Biobank (stage 1). We followed up promising signals (P Results We selected 31 independent variants for further investigation in stage 2, and discovered eight novel signals (P Interpretation We identified eight signals for asthma-COPD overlap, which may represent loci that predispose to type 2 inflammation, and serious long-term consequences of asthma.</p

Overview of populations.

<p>Populations and corresponding period of data collection, type of population, genotyping platform and soft-ware used for imputation.</p><p>NA = not applicable.</p

Percentage of subjects with chronic mucus hypersecretion (CMH) within genotypes (AA, AG and GG) of rs6577641 in the identification cohort (NELSON), and distributed among ex- and current smokers.

<p>Percentage of subjects with chronic mucus hypersecretion (CMH) within genotypes (AA, AG and GG) of rs6577641 in the identification cohort (NELSON), and distributed among ex- and current smokers.</p

<i>SATB1</i>, <i>MUC5AC</i> and <i>FOXJ1</i> mRNA expression levels during mucociliary human airway epithelial cell differentiation (n = 2 donors).

<p>Expression of <i>SATB1</i>, the identified gene in our study, <i>MUC5AC</i> a marker of mucus, and <i>FOXJ1</i>, representing ciliated cells in epithelial cell culture on air liquid interface.</p

Meta-analysis of top SNPs associated with CMH in replication cohorts, in identification and replication cohorts and corresponding direction of effect in all cohorts and associated feature and gene(s).

<p>MAF = minor allele frequency in NELSON;</p><p>*Direction of effect per cohort: each sign reflects one cohort, direction of effect is presented by: + = (OR>1.05), − = (OR<0.95), 0 = (0.95Table 2; OR is odds ratio; Q is p-value for heterogeneity;</p>#<p>means corresponding SNP is located in an intron in this gene.</p

Meta-analysis of the effect of rs6577641 on mRNA expression levels of <i>SATB1</i> in the lung^*.

<p>*To assess the effect of the SNP rs6577641 on gene expression, a Kruskal-Wallis test was performed. This test generates a p-value, but does not give a direction of the effect. To assess the direction of the effect, a Spearman's correlation test was performed. Next, a Z-score was calculated for each center and a meta-analysis performed for each of the three <i>SATB1</i> probes across all centers. Finally, a meta-analysis for all three <i>SATB1</i> probes was performed across all centers. This generated a Z-score of −5.87 and a corresponding p-value of 4.3*10⁻⁹, indicating that the susceptibility G allele of the SNP rs6577641 increases <i>SATB1</i> expression.</p

Meta-analysis of top SNPs associated with CMH across replication cohorts and across identification and replication cohorts, corrected for smoking and sex.

<p>P-value is fixed p-value if p-value for heterogeneity (Q) >0.005, and random p-value if p-value for heterogeneity (Q) <0.005; OR is Odds Ratio; OR is fixed OR if p-value for heterogeneity (Q) >0.005, and random OR if p-value for heterogeneity (Q) <0.005; Q is p-value for heterogeneity;</p><p>N = number of cohorts;</p><p>*means that the corresponding SNP is an intron in this gene.</p

Study design.

<p>We performed GWA studies in the NELSON cohort and in additional healthy controls. CMH was analyzed using logistic regression with adjustment for center (Groningen and Utrecht). Since current smoking can affect the presence of CMH, we additionally performed the GWAS in the NELSON cohort correcting for center and smoking. SNPs with a p-value<10-4 present in both GWA studies were selected for replication. To test for generalizability of associations with CMH in other populations, we compared our results with data in CMH-cases and controls with a smoking history of ≥20 pack-years with eleven replication populations using logistic regression with adjustment for sex and current smoking. Finally, we performed a meta-analysis on shared SNPs across the NELSON identification population and the 11 replication populations.</p