Our genes can increase our risk of illness, but advances in understanding how they physically interact with each other already offer some better-tailored treatments. Donna Chisholm reports.
At just 24, Tyla Ridsdale calls himself a ticking time bomb. Because of his genes, he’s at substantially higher risk than most of us of developing heart disease, despite working out regularly and eating a healthy diet.
Tests a year ago confirmed Ridsdale has a genetic double whammy. He’s inherited a condition called familial hypercholesterolemia (FH), which causes high cholesterol levels from birth; he also carries a series of other genetic variations that together substantially elevate his risk of a heart attack or coronary disease. FH probably contributed to his grandfather’s death at 37, and also affects his mother and uncle.
The genetic tests put Ridsdale, a software instalment specialist, in the top 1% or less of the population for cardiac risk. The knowledge is potentially life-saving, in that it shows he’s three times more likely to respond to statin treatment than those at low risk, but it’s also, at times, depressing. The drugs he’s on have side effects including a slightly increased risk of diabetes, for example, and he knows that because of his FH and what doctors call his polygenic risk score for heart disease, lifestyle changes alone won’t be enough to alter his prognosis.
Polygenic risk scores are worked out from the total number of genetic variations in the genome that are either associated with, or protect from, disease. These genetic variations can be detected through genome sequencing, or gene chip technology that fragments DNA and can read up to one million variations.
Scientists’ rapidly expanding knowledge of the effect of not only single genetic mutations, but also more subtle variations, known as SNPs, in non-coding DNA – what used to be dubbed “junk” DNA – is about to revolutionise treatment for large numbers of us, and is already leading to faster diagnoses of rarer disorders that might otherwise take months to identify.
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