Influence of C-159T SNP of the CD14 gene promoter on lung function in smokers

Abstract

CD14, a co-receptor for endotoxin, plays a significant role in regulating the inflammatory response to this agent. The C-159T single nucleotide polymorphism (SNP) in the CD14 gene promoter is an important regulator of CD14 expression, with TT homozygotes having increased expression of CD14. This SNP has been linked to pathogenesis of asthma and with cardiovascular diseases in smokers. We hypothesize that CD14 also plays a role in the pathophysiology of COPD in smokers who are exposed to endotoxin contained in cigarette smoke as well as endotoxin derived from Gram-negative microbes colonizing their airways. To assess the effect of the C-159T SNP of the CD14 gene promoter on lung function, we recruited 246 smokers 40 years of age or older with a range of 10-156 pack-year smoking exposures. The TT genotype was associated with lower lung function in smokers with a moderate smoking history. However, the CC genotype was associated with decreased lung function in heavy smokers (>56 pack years). The effect of CC genotype on severity of COPD is analogous with the effect of this genotype in risk for asthma. CD14 may be a factor in the pathophysiology of COPD, as it is in asthma and smoking-related cardiovascular diseases.

Figure 1. Box plots across four quartiles of pack-year history, by genotype, for FEV1 (%predicted), FVC (%predicted), and FEV1/FVC ratio levels

Quartiles of the pack-year history are defined as 10–28 pack yr smoking for 1^st quartile (Q1); 28–38 pack yr for Q2; 38–56 pack yr for Q3 and 56–153 pack yr for Q4. The horizontal line in the interior of the box is located at the median of the data. The height of the box is equal to the interquartile distance (IQD) which is the difference between the third quartile of the data and the first quartile. The IQD indicates the spread or width of the distribution for the data. The whiskers extend to the extreme values of the data or a distance 1.5*IQD from the center, whichever is less. Data points which fall outside the whiskers may be outliers.

Figure 2. Non-linear smoother fit for FEV1 (%predicted), FVC, and FEV1/FVC ratio by genotype (Full data set)

The lines in the figures are the running means depicting the nonlinear relationship between the pack-year and COPD endpoints across different genotypes. The FEV1/FVC ratio is tested to be significant in the full data set while both FEV1 and FEV1/FVC ratio are tested significant in the ex-smoker subpopulation.