Genome-Wide Association Study Identifies Signals for Asthma-COPD Overlap

February 1, 2022
Armand Butera

Armand Butera is the assistant editor for HCPLive. He attended Fairleigh Dickinson University and graduated with a degree in communications with a concentration in journalism. Prior to graduating, Armand worked as the editor-in-chief of his college newspaper and a radio host for WFDU. He went on to work as a copywriter, freelancer, and human resources assistant before joining HCPLive. In his spare time, he enjoys reading, writing, traveling with his companion and spinning vinyl records. Email him at abutera@mjhlifesciences.com.

Dr. Shrine and colleagues conducted the largest genome-wide association study of coexisting asthma and COPD to date in a 2-stage design incorporating a total of 13 studies.

A recent genome-wide association study identified 8 signals for asthma-chronic obstructive pulmonary disease (COPD) overlap, which investigators believed represented loci that predispose to type 2 inflammation and serious long-term consequences of asthma.

Investigators led by Nick Shrine, PhD, Department of Health Sciences at the University of Leicester, UK, noted the substantial global impact of both asthma and COPD, and cited evidence that suggested that individuals with asthma-COPD overlap experienced worse outcomes than those with either condition alone.

To confirm this suggestion, Shrine and colleagues conducted the largest genome-wide association study of coexisting asthma and COPD to date in a 2-stage design incorporating a total of 13 studies.

The Methods

Investigators first defined cases of asthma-COPD overlap as individuals who had self-reported asthma and FEV1/FVC <0.7 with GOLD 2+ airflow limitation.

In stage 1 of the study, the team defined distinct signals passing a P-value threshold of P<5x10-6, as regions of association around the most strongly associated variant (sentinel variant) ±1Mb.

To ascertain the extent to which signals were driven by association with COPD and/or asthma alone, 2 additional “signal prioritization” analyses were undertaken.

In stage 2, single nucleotide polymorphisms (SNP) identified in the stage 1 signal prioritization analyses were tested for association in 12 independent studies of European ancestry cohorts (up to 4,301 cases and 48,609 controls, in CHS, COPDGene, deCODE, ECLIPSE, EPIC-Norfolk, FHS, Generation Scotland, GenKOLS, the Trondelag Health Study [HUNT], LOVELACE, Rotterdam Study, SPIROMICS) and one African American ancestry cohort (COPDGene; 297 cases, 1335 controls).

To assess whether associations with our Stage 1 signals changed according to age of asthma diagnosis, investigators divided cases into those who self-reported their age at asthma diagnosis as 25 years before they repeated the association tests in the UK Biobank.

The Findings

In stage 1, investigators selected 8068 cases of asthma-COPD overlap from UK Biobank, and 40360 as healthy controls free of asthma and COPD.

Another 16,762 individuals were selected as controls with COPD alone (without asthma), and 26,815 as controls with asthma alone (without COPD) for signal prioritization analyses.

A total of 83 distinct signals at P<5x10-6 were identified in stage 1, with 31 retaining significance (P<0.01) in signal prioritization analyses comparing cases of asthma-COPD overlap separately with either COPD cases or asthma cases to determine whether signals were driven by asthma or COPD alone.

Investigators added that the 31 signals suggested a spectrum of shared genetic influences, some of which predominantly influenced asthma such as FAM105A, GLB1, PHB, and TSLP, while other predominately influenced airflow obstruction such as IL17RD, C5orf56, and HLA-DQB1.

Regarding the novel intergenic ACO signal on chromosome 5 (rs80101740, effect allele frequency (EAF)=0.015, OR=1.42, P=3.72x10-8), the sentinel SNP had the largest posterior probability (0.77) of being the true causal variant, assuming the causal variant was genotyped/imputed.

The signal had not been previously associated with asthma, lung function, or COPD.

A subgroup analyses revealed that the effect sizes for the 31 signals amongst cases with childhood-onset asthma were highly correlated with those amongst individuals with adult onset asthma (R=0.883), as were effect sizes in ever- and never-smokers (R=0.911).

However, the analyses also suggested that associations at these eight signals were not driven by smoking or age at asthma diagnosis, and in phenome-wide scans, eosinophil counts, atopy and asthma traits were prominent.

“We focused on variants that tend towards an intermediate phenotype with features of both asthma and fixed airflow obstruction, with pathways implicating innate and adaptive immunity and potentially bone development, and signals for which the biology remains unclear,” the team wrote. “Further biological understanding is likely to be important for therapeutics to prevent the development of fixed airflow obstruction among people with asthma.”

The study, "Genetic associations and architecture of asthma-chronic obstructive pulmonary disease overlap," was published online in CHEST Journal.


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