Academic research community (GECIP)

In previous work we identified some genes, with variants that might put some people at a higher risk if infected with the coronavirus. Although this could be useful, it cannot be acted on or used, or further research justified until it is confirmed using the NGRL COVID data whether these candidates are in fact true genetic risk factors. In this collaboration with Genomics England, we will be using the NGRL COVID data which is of such quality and quantity that we will be able to conclusively answer this scientific question. We will also work to try to find other potential genes that can't be found in other smaller datasets that do not include full genome sequencing. If we are able to prove genetic risk factors for coronavirus infection, this could be of value to medical research, potentially impacting vaccine development, genetic tests that doctors use, and increase our understanding of the human immune reaction to infection from the virus.

This study will use as its starting point information on the biological helpers of genes involved in hereditary spastic paraplegia (HSP). HSPs are a relatively rare set of neurological disorders, in which affected people develop progressive weakness and stiffness of the legs, sometimes accompanied by other clinical features. We have a longstanding research interest in HSP, and have studied intensively how HSP genes, and the proteins for which they provide a recipe (i.e. encode), work in the cells of the body. Through this work we have identified many other proteins that function in the same pathways as HSP proteins - they can be regarded as "helpers". We would now like to find out if mistakes in the genes encoding these helper proteins also cause genetic disease. To do this, we will analyse the sequence of these genes in 100,000 genomes patients affected by rare diseases, to determine whether any patterns emerge.

When looking for the cause of disease, it is useful to examine the genomes of affected people. We compare them to the genomes of large numbers of people who don’t have the disease to find locations which have a specific characteristic in those with the disease. The larger the number of people we can compare to, the more precise the analysis is. The 100,000 Genomes Project has sequenced the parents of children with rare disease. We will extract summary information recording how often specific letters are observed at each location in the unaffected parent’s genomes. If the letter ‘T’ is present in a certain position in a tenth of the population, we can assume it will not cause a rare disease. We will also extract summary information from the genomes of people with cancer, which can be used in studies of diseases other than cancer as other diseases show different patterns.