Variability in mRNA expression of fms-like tyrosine kinase-1 variants in normal and preeclamptic placenta

Background: Preeclampsia is a complication of pregnancy characterised by gestational hypertension and proteinuria and is a leading cause of morbidity and mortality in both mothers and infants. Certain anti-angiogenic factors have long been implicated in the pathogenesis of preeclampsia and the placental expression of factors such as soluble fms-like tyrosine kinase-1 (sFLT-1) are often reported in studies of normal and diseased placentae. Despite evidence showing significant differences in placental gene expression by collection site, many studies fail to provide sufficient details on sample selection and collection. Findings: With ourselves and others investigating and reporting on the expression of FLT-1 variants and other genes in the placenta of normotensive and preeclamptic patients, we felt it prudent to examine the variation in expression of FLT-1 variants across human placenta. We examined the differential expression of FLT-1 variants in samples obtained from 12 sites on normal and preeclamptic placentae and found expression to be highly variable between sites. We therefore developed an algorithim to calculate the mean expression for any number of these sites collected and in any combination. The coefficient of variation for all combinations of sites was then used to determine the minimum number of sites required to reduce coefficient of variation to below an acceptable 10%. We found that 10 and 11 sites had to be sampled in the normal and preeclamptic placentae respectively to ensure a representative expression pattern for all FLT-1 variants for an individual placenta. Conclusions: These findings demonstrate significant variation in expression levels of several commonly investigated genes across sites in both normal and preeclamptic placenta. This highlights both the importance of adequate sampling of human placenta for expression studies and the effective communication of sample selection and collection methods, for data interpretation and to ensure the reproducibility and reliability of results and conclusions drawn.