Modeling the effect of a genetic factor for a complex trait in a simulated population-0

<p><b>Copyright information:</b></p><p>Taken from "Modeling the effect of a genetic factor for a complex trait in a simulated population"</p><p></p><p>BMC Genetics 2005;6(Suppl 1):S87-S87.</p><p>Published online 30 Dec 2005</p><p>PMCID:PMC1866693.</p><p></p>er M. The second level shows, for each marker genotype, the index cases classified according to their IBD sharing with one affected sib (stratified IBD distribution)

Illustration of a Border Collie pedigree segregating PRA constructed by the Cyrillic 2

1 software. This pedigree is constituted of 80 dogs, 33 dogs are affected (30 males and 3 females).<p><b>Copyright information:</b></p><p>Taken from "Progressive Retinal Atrophy in the Border Collie: A new XLPRA"</p><p>http://www.biomedcentral.com/1746-6148/4/10</p><p>BMC Veterinary Research 2008;4():10-10.</p><p>Published online 3 Mar 2008</p><p>PMCID:PMC2324077.</p><p></p

Genetic and Environmental Factors Influencing the Placental Growth Factor (PGF) Variation in Two Populations

<div><p>Placental Growth Factor (PGF) is a key molecule in angiogenesis. Several studies have revealed an important role of PGF primarily in pathological conditions (e.g.: ischaemia, tumour formation, cardiovascular diseases and inflammatory processes) suggesting its use as a potential therapeutic agent. However, to date, no information is available regarding the genetics of PGF variability. Furthermore, even though the effect of environmental factors (e.g.: cigarette smoking) on angiogenesis has been explored, no data on the influence of these factors on PGF levels have been reported so far. Here we have first investigated PGF variability in two cohorts focusing on non-genetic risk factors: a study sample from two isolated villages in the Cilento region, South Italy (N = 871) and a replication sample from the general Danish population (N = 1,812). A significant difference in PGF mean levels was found between the two cohorts. However, in both samples, we observed a strong correlation of PGF levels with ageing and sex, men displaying PGF levels significantly higher than women. Interestingly, smoking was also found to influence the trait in the two populations, although differently. We have then focused on genetic risk factors. The association between five single nucleotide polymorphisms (SNPs) located in the <em>PGF</em> gene and the plasma levels of the protein was investigated. Two polymorphisms (rs11850328 and rs2268614) were associated with the PGF plasma levels in the Cilento sample and these associations were strongly replicated in the Danish sample. These results, for the first time, support the hypothesis of the presence of genetic and environmental factors influencing PGF plasma variability.</p> </div

Cumulative effect of the environmental and genetic factors on the PGF levels.

<p>Mean PGF levels (right vertical axis) are shown as solid black dots connected by solid lines for categories of the cumulative risk score. The standard error is reported as error bar. The shaded bars show the distribution of the cumulative risk score in the whole population (left vertical axis) in the Cilento (A) and Denmark (B) sample.</p

PGF levels according to sex in the Cilento and Denmark samples.

<p>Mean levels of the log-transformed PGF and the standard error are reported for each gender and population sample. A univariate analysis of variance including the log-PGF as a dependent variable, sex and village as fixed factors and age, menstruation, smoking and “disease status” as covariates was performed. The corresponding p-value for the PGF level difference between the population samples is shown in the left corner of the plot.</p

The baseline characteristics of the samples.

<p>The mean and the standard deviation (SD) are reported for the age, the median and the interquartile range (IQR) for the PGF levels.</p>*<p>Plasma levels for Cilento and serum levels for Denmark.</p

Association results between the SNPs in the <i>PGF</i> gene and the protein levels according to the best fitting models for the Cilento and Denmark samples.

<p>Association for the five <i>PGF</i> SNPs and the protein levels is reported for Cilento; only the SNPs associated in Cilento were tested in Denmark. Statistical associations are all adjusted for age, sex, menstruation, smoking, sex/smoking interaction (only for Cilento) and “disease status”.</p>*<p>Minor allele referred to the reverse strand according to <i>PGF</i> position.</p>†<p>The CEU sample was chosen as reference population of the HapMap data.</p>‡<p>Test corrected for relatedness between individuals. Multiple testing p-value threshold = 0.0127. Significant results are given in bold.</p>§<p>P-value from meta-analysis (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0042537#s2" target="_blank">Material and Methods</a> section for details).</p

PGF level according to smoking and sex in Cilento and Denmark.

<p>Mean levels of the log-transformed PGF and the standard error are reported. A linear regression model includes the log-PGF as a dependent variable, age, sex, menstruation, smoking, sex/smoking interaction, and “disease status” as independent variables for the Cilento sample (A) and age, sex, menstruation, smoking, and “disease status” as regressors for the Denmark sample (B). The p-values for sex, smoking and sex/smoking interaction are shown.</p