PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-4 (4)
 

Clipboard (0)
None
Journals
Year of Publication
Document Types
2.  Cluster Analysis in the COPDGene Study Identifies Subtypes of Smokers with Distinct Patterns of Airway Disease and Emphysema 
Thorax  2014;69(5):416-423.
Background
There is notable heterogeneity in the clinical presentation of patients with COPD. To characterize this heterogeneity, we sought to identify subgroups of smokers by applying cluster analysis to data from the COPDGene Study.
Methods
We applied a clustering method, k-means, to data from 10,192 smokers in the COPDGene Study. After splitting the sample into a training and validation set, we evaluated three sets of input features across a range of k (user-specified number of clusters). Stable solutions were tested for association with four COPD-related measures and five genetic variants previously associated with COPD at genome-wide significance. The results were confirmed in the validation set.
Findings
We identified four clusters that can be characterized as 1) relatively resistant smokers (i.e. no/mild obstruction and minimal emphysema despite heavy smoking), 2) mild upper zone emphysema predominant, 3) airway disease predominant, and 4) severe emphysema. All clusters are strongly associated with COPD-related clinical characteristics, including exacerbations and dyspnea (p<0.001). We found strong genetic associations between the mild upper zone emphysema group and rs1980057 near HHIP, and between the severe emphysema group and rs8034191 in the chromosome 15q region (p<0.001). All significant associations were replicated at p<0.05 in the validation sample (12/12 associations with clinical measures and 2/2 genetic associations).
Interpretation
Cluster analysis identifies four subgroups of smokers that show robust associations with clinical characteristics of COPD and known COPD-associated genetic variants.
doi:10.1136/thoraxjnl-2013-203601
PMCID: PMC4004338  PMID: 24563194
3.  Non-emphysematous chronic obstructive pulmonary disease is associated with diabetes mellitus 
BMC Pulmonary Medicine  2014;14:164.
Background
Chronic obstructive pulmonary disease (COPD) has been classically divided into blue bloaters and pink puffers. The utility of these clinical subtypes is unclear. However, the broader distinction between airway-predominant and emphysema-predominant COPD may be clinically relevant. The objective was to define clinical features of emphysema-predominant and non-emphysematous COPD patients.
Methods
Current and former smokers from the Genetic Epidemiology of COPD Study (COPDGene) had chest computed tomography (CT) scans with quantitative image analysis. Emphysema-predominant COPD was defined by low attenuation area at -950 Hounsfield Units (LAA-950) ≥10%. Non-emphysematous COPD was defined by airflow obstruction with minimal to no emphysema (LAA-950 < 5%).
Results
Out of 4197 COPD subjects, 1687 were classified as emphysema-predominant and 1817 as non-emphysematous; 693 had LAA-950 between 5–10% and were not categorized. Subjects with emphysema-predominant COPD were older (65.6 vs 60.6 years, p < 0.0001) with more severe COPD based on airflow obstruction (FEV1 44.5 vs 68.4%, p < 0.0001), greater exercise limitation (6-minute walk distance 1138 vs 1331 ft, p < 0.0001) and reduced quality of life (St. George’s Respiratory Questionnaire score 43 vs 31, p < 0.0001). Self-reported diabetes was more frequent in non-emphysematous COPD (OR 2.13, p < 0.001), which was also confirmed using a strict definition of diabetes based on medication use. The association between diabetes and non-emphysematous COPD was replicated in the ECLIPSE study.
Conclusions
Non-emphysematous COPD, defined by airflow obstruction with a paucity of emphysema on chest CT scan, is associated with an increased risk of diabetes. COPD patients without emphysema may warrant closer monitoring for diabetes, hypertension, and hyperlipidemia and vice versa.
Trial registration
Clinicaltrials.gov identifiers: COPDGene NCT00608764, ECLIPSE NCT00292552.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2466-14-164) contains supplementary material, which is available to authorized users.
doi:10.1186/1471-2466-14-164
PMCID: PMC4216374  PMID: 25341556
Airway disease; CT scan; Diabetes mellitus; Emphysema; Spirometry
4.  Xenobiotic metabolizing enzyme gene polymorphisms predict response to lung volume reduction surgery 
Respiratory Research  2007;8(1):59.
Background
In the National Emphysema Treatment Trial (NETT), marked variability in response to lung volume reduction surgery (LVRS) was observed. We sought to identify genetic differences which may explain some of this variability.
Methods
In 203 subjects from the NETT Genetics Ancillary Study, four outcome measures were used to define response to LVRS at six months: modified BODE index, post-bronchodilator FEV1, maximum work achieved on a cardiopulmonary exercise test, and University of California, San Diego shortness of breath questionnaire. Sixty-four single nucleotide polymorphisms (SNPs) were genotyped in five genes previously shown to be associated with chronic obstructive pulmonary disease susceptibility, exercise capacity, or emphysema distribution.
Results
A SNP upstream from glutathione S-transferase pi (GSTP1; p = 0.003) and a coding SNP in microsomal epoxide hydrolase (EPHX1; p = 0.02) were each associated with change in BODE score. These effects appeared to be strongest in patients in the non-upper lobe predominant, low exercise subgroup. A promoter SNP in EPHX1 was associated with change in BODE score (p = 0.008), with the strongest effects in patients with upper lobe predominant emphysema and low exercise capacity. One additional SNP in GSTP1 and three additional SNPs in EPHX1 were associated (p < 0.05) with additional LVRS outcomes. None of these SNP effects were seen in 166 patients randomized to medical therapy.
Conclusion
Genetic variants in GSTP1 and EPHX1, two genes encoding xenobiotic metabolizing enzymes, were predictive of response to LVRS. These polymorphisms may identify patients most likely to benefit from LVRS.
doi:10.1186/1465-9921-8-59
PMCID: PMC2048957  PMID: 17686149

Results 1-4 (4)