Project: Exhaustive prediction of disease susceptibility to coding base changes in the human genome

Champion: Mounir Errami

Single Nucleotide Polymorphisms (SNPs) are the most abundant form of genomic variation and can cause phenotypic differences between individuals, including diseases. Bases are subject to various levels of selection pressure, reflected in their inter-species conservation. Our work has consisted in developing a method to score each coding base in the human genome reflecting the disease probability associated with its mutation. We subsequently scanned the entire genome with this predictive method. The results obtained strongly suggest that the highest scoring genes are enriched for those that might contribute to disease, if mutated. For instance, out of the 30 genes with the highest scores, 21 are directly associated with a disease. In contrast, out of the 30 genes with the lowest scores, only one is associated with a disease as found in published literature. This method provides valuable information to researchers to identify sensitive positions in genes that have a high disease probability, enabling them to optimize experimental designs and interpret data emerging from genetic and epidemiological studies.