Analyzing the Genetics of Pre-Eclampsia and the Role of the EGF Receptor and Its Ligands - A Bioinformatics Approach for Detecting Possible Genetic Mechanisms

Abstract

Pre-eclampsia is a life threatening, multi-system disorder which is the de novo occurrence of both hypertension and protienuria in pregnancy. It is a major pregnancy problem among Sri Lankan women. Annually, it causes many deaths all over the world. The main objective of this research is to analyze the genetics of preeclampsia. There are two main goals that we intend to achieve, namely, to predict the risk of pre-eclampsia among Sri Lankan women and to compare the humans with other organisms in order to find out why it is only found in humans. If we can predict pre-eclampsia early in the pregnancy it will reduce the risk. However, it is difficult to achieve this without considering the other facts related to this disease. There are several interactions between the ligands themselves and between ligands and the EGF receptor. Here we have considered only one gene from a family of seven. However, biologists suspect that the entire EGF family would contribute to this disease and this hypothesis is not yet proved. It needs more research to fill this blank. In this research we have used a neural network approach to predict the risk and have used 120 sequences from patients and 120 sequences from healthy women to train the network. For testing, 50 sequences from each category were used. This system can predict the risk of preeclampsia for a given EGF sequence to some extent. According to our second objective, to find out whether there are any clues that can be used to understand why pre-eclampsia is found only in humans, we have followed several Bioinformatics techniques. We have selected four organisms to compare with the human: Chimpanzee, Monkey, Mouse and Boar. According to the results, we had to perform structural comparison to find an acceptable clue for the second objective.