Three population stratification factors (PSFs) were identified in the genomic SNP dataset, accounting for a relatively large portion of total variance (6%).
We regressed each SNP with cumulative PM10 on FEF25 75% annual decline adjusting for study center, age, sex, height, never-smoking status, seasonal effects (sine and cosine function of day of examination), and population stratification factors.
In addition, confounding factors, such as population stratification, genetic heterogeneity, environmental factors, and interactions between genetic and environmental factors (which may vary with different populations and environments), may reduce the chance of GWA replication.
There were no effects of population stratification and confounding factors.
Second, population stratification, resulting from factors such as ancestral patterns of geographical migration and differences in mating practices and reproductive behaviors between populations, may confound genotype-phenotype associations and is often speculated to be the reason for non-replication of genetic associations [40].
The Q-Q plot for this GWAS based on allelic P-values by logistic regression revealed no significant population stratification with genomic inflation factor λ of 1.026 (Figure 1).
Prior to correction for population stratification the genomic inflation factor for the genome-wide association study was 1.15, and after correction with the CMH test λ was 1.05.
Without adjustment for population stratification the genomic control inflation factor was 1.21.
A quantile - quantile plot analysis indicated, that this procedure did not sufficiently account for population stratification in our dataset (inflation factor λ = 1.34).
In order to address whether country of origin or population stratification may be a confounding factor in response to r-hGH, a PCA was undertaken using the PLINK genetic analysis software (http://pngu.mgh.harvard.edu/∼purcell/plink/) by PGx Services.
