Physiologic insights from the COPD genetic epidemiology study

William W. Stringer, Janos Porszasz, Surya P. Bhatt, Meredith C. McCormack, Barry J. Make, Richard Casaburi

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations


COPD Genetic Epidemiology Study (COPDGene®) manuscripts have provided important insights into chronic obstructive pulmonary disease (COPD) pathophysiology and outcomes, including a better understanding of COPD phenotypes relating computed tomography (CT) anatomic data to spirometric and patient-reported outcomes. Spirometry significantly underdiagnoses smoking-induced lung disease, and there is a marked improvement in sensitivity and specificity with CT scanning. This review also highlights the COPDGene® exploration of specific spirometry phenotypes (e.g.,PRISm), contributors to spirometric decline, composite physiologic measures, asthma-COPD overlap (ACO) syndrome, consequences of bronchodilator responsiveness, newer methods to assess small airway dysfunction, and spirometric correlates of comorbid diseases such as obesity and diabetes.

Original languageEnglish (US)
Pages (from-to)256-266
Number of pages11
JournalChronic Obstructive Pulmonary Diseases
Issue number3
StatePublished - 2019


  • Asthma-COPD overlap
  • COPD
  • COPD Genetic Epidemiology
  • COPDGene
  • Chronic obstructive pulmonary disease
  • PRISm
  • Preserved Ratio Impaired Spirometry

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine


Dive into the research topics of 'Physiologic insights from the COPD genetic epidemiology study'. Together they form a unique fingerprint.

Cite this