Integrative pathway genomics of lung function and airflow obstruction

Chronic respiratory disorders are important contributors to the global burden of disease. Genome-wide association studies (GWASs) of lung function measures have identified several trait-associated loci, but explain only a modest portion of the phenotypic variability. We postulated that integrating pathway-based methods with GWASs of pulmonary function and airflow obstruction would identify a broader repertoire of genes and processes influencing these traits. We performed two independent GWASs of lung function and applied gene set enrichment analysis to one of the studies and validated the results using the second GWAS. We identified 131 significantly enriched gene sets associated with lung function and clustered them into larger biological modules involved in diverse processes including development, immunity, cell signalling, proliferation and arachidonic acid. We found that enrichment of gene sets was not driven by GWAS-significant variants or loci, but instead by those with less stringent association P-values. Next, we applied pathway enrichment analysis to a meta-analysed GWAS of airflow obstruction. We identified several biologic modules that functionally overlapped with those associated with pulmonary function. However, differences were also noted, including enrichment of extracellular matrix (ECM) processes specifically in the airflow obstruction study. Network analysis of the ECM module implicated a candidate gene, matrix metalloproteinase 10 (MMP10), as a putative disease target. We used a knockout mouse model to functionally validate MMP10’s role in influencing lung’s susceptibility to cigarette smoke-induced emphysema. By integrating pathway analysis with population-based genomics, we unravelled biologic processes underlying pulmonary function traits and identified a candidate gene for obstructive lung disease

Image_1_A Genome-Wide Linkage Study for Chronic Obstructive Pulmonary Disease in a Dutch Genetic Isolate Identifies Novel Rare Candidate Variants.pdf

<p>Chronic obstructive pulmonary disease (COPD) is a complex and heritable disease, associated with multiple genetic variants. Specific familial types of COPD may be explained by rare variants, which have not been widely studied. We aimed to discover rare genetic variants underlying COPD through a genome-wide linkage scan. Affected-only analysis was performed using the 6K Illumina Linkage IV Panel in 142 cases clustered in 27 families from a genetic isolate, the Erasmus Rucphen Family (ERF) study. Potential causal variants were identified by searching for shared rare variants in the exome-sequence data of the affected members of the families contributing most to the linkage peak. The identified rare variants were then tested for association with COPD in a large meta-analysis of several cohorts. Significant evidence for linkage was observed on chromosomes 15q14–15q25 [logarithm of the odds (LOD) score = 5.52], 11p15.4–11q14.1 (LOD = 3.71) and 5q14.3–5q33.2 (LOD = 3.49). In the chromosome 15 peak, that harbors the known COPD locus for nicotinic receptors, and in the chromosome 5 peak we could not identify shared variants. In the chromosome 11 locus, we identified four rare (minor allele frequency (MAF) <0.02), predicted pathogenic, missense variants. These were shared among the affected family members. The identified variants localize to genes including neuroblast differentiation-associated protein (AHNAK), previously associated with blood biomarkers in COPD, phospholipase C Beta 3 (PLCB3), shown to increase airway hyper-responsiveness, solute carrier family 22-A11 (SLC22A11), involved in amino acid metabolism and ion transport, and metallothionein-like protein 5 (MTL5), involved in nicotinate and nicotinamide metabolism. Association of SLC22A11 and MTL5 variants were confirmed in the meta-analysis of 9,888 cases and 27,060 controls. In conclusion, we have identified novel rare variants in plausible genes related to COPD. Further studies utilizing large sample whole-genome sequencing should further confirm the associations at chromosome 11 and investigate the chromosome 15 and 5 linked regions.</p

Study populations included in GWI study on active smoking and adult onset asthma.

<p>Study populations included in GWI study on active smoking and adult onset asthma.</p

Forest plots for the meta-analysis and replication study on the genetic effect of SNP rs5011804 on chromosome 12 in subjects exposed and non-exposed to ever active tobacco smoking (identified in second approach).

<p>The bottom forest plot presents the interaction meta-analysis and replication study for this SNP. ORs are calculated using a fixed effect model.</p

Forest plot for meta-analysis on the association between ever active tobacco smoking and adult onset asthma, without including the genetic effect.

<p>Forest plot for meta-analysis on the association between ever active tobacco smoking and adult onset asthma, without including the genetic effect.</p

PRISMA flow diagram.

<p>PRISMA flow diagram.</p

Top SNPs that interact with active tobacco smoking in adult onset asthma identified in second approach (genetic effect in exposed)^#.

<p>Top SNPs that interact with active tobacco smoking in adult onset asthma identified in second approach (genetic effect in exposed)<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0172716#t003fn001" target="_blank">^#</a>.</p

Top SNPs that interact with active tobacco smoking in adult onset asthma identified in both approaches^#.

<p>Top SNPs that interact with active tobacco smoking in adult onset asthma identified in both approaches<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0172716#t004fn001" target="_blank">^#</a>.</p

Forest plots for the meta-analysis and replication study on the genetic effect of SNP rs9969775 on chromosome 9 in subjects exposed and non-exposed to ever active tobacco smoking (identified in first approach).

<p>The bottom forest plot presents the interaction meta-analysis and replication study for this SNP. ORs are calculated using a fixed effect model.</p

Top SNPs that interact with active tobacco smoking in adult onset asthma identified in first approach (overall interaction effect)^#.

<p>Top SNPs that interact with active tobacco smoking in adult onset asthma identified in first approach (overall interaction effect)<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0172716#t002fn001" target="_blank">^#</a>.</p