Gene scanning techniques developed by Professor Ian Day and colleagues at the University of Southampton are set to have a major impact on healthcare in the future.
One of two gene mutation scanning techniques devised by Professor Day and his team in the Human Genetics Division of the University’s School of Medicine has been successfully applied to search for rare genetic mutations in the population at large.
Their method, called meltMADGE, which combines thermal ramp electrophoreisis with microplate array diagonal gel electrophoresis (MADGE), enables significantly higher levels of scanning at a fraction of the cost.
Using the Southampton technique a network of British medical researchers from the Universities of Southampton, Bristol and University College London, funded by the UK’s Medical Research Council, British Heart Foundation and Department of Health, studied a gene which affects blood cholesterol levels. In analyses of nearly 10,000 middle-aged individuals, they found some rare mutations associated with very high cholesterol, some with moderately high cholesterol and some with no effect.
This is the first time that it has been possible to find out whether there may be unknown rare genetic variations in the population which may cause mild forms of a particular disease or feature in just one or two individuals, or may even protect them against disease.
Professor Day commented: ‘This development enables us to look at the whole population and find rare and “special” individuals with gene changes which may have either mild, moderate, severe or protective disease effects, a bit like the medical equivalent of finding a needle in a haystack.
‘While this approach is currently at the research level, in the future it could lead to a very personalised genetic profile of a whole range of genes relevant to lifestyle, health and drug prescribing, leading to more personalised medicine and screening.’
Professor Day’s group is using combinations of meltMADGE and a second technology called endo VII MADGE to explore variations in the whole population of disease genes relevant to growth, obesity and cardiovascular disease.
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