Blood biomarkers and genomics combo predicts common disease risk more accurately than only genomic information
Polygenic risk scores, where genomic information alone is used to assess the risk of developing diseases, have been receiving a lot of attention recently, but research to be presented at the annual conference of the European Society of Human Genetics on 10 June suggests that combining blood biomarkers with genomic information gives more accurate, cost-effective results.
The researchers used machine learning to build predictive models for individuals’ future risks of nine common diseases, based on their genetic information and the biomarkers that they measured. The diseases studied were ischaemic heart disease, stroke, lung cancer, diabetes, chronic obstructive pulmonary disease, Alzheimer’s and other dementias, depression, liver disease, and colon cancer.
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