Researchers have used the 'polygenic score' approach to analysing genomic data to help identify disease risk much earlier than current predictors.
The tests assess information from millions of different points in the genome to calculate risk for five diseases – coronary artery disease, atrial fibrillation, type 2 diabetes, inflammatory bowel disease, or breast cancer. This approach could identify large fractions of the population who have a higher risk of developing these diseases before clinical symptoms appear.
Common diseases such as these do not usually have a clear gene-to-risk cause. Instead, the risk of developing them is influenced by the combined effect of a huge number of genes, working together in complicated ways.
'We've known for a long time that there are people out there at high risk for disease based just on their overall genetic variation,' said Dr Sekar Kathiresan at the Broad Institute in Cambridge, Massachusetts, who led the study, published in Nature Genetics. 'Now we're able to measure that risk using genomic data in a meaningful way.'
In order to calculate this 'polygenic risk', the team analysed six million locations in the genomes of more than 400,000 individuals in the UK BioBank – a database of genomic data and medical information from people across the UK – to identify the multitude of genetic variants that might be associated with the five diseases.
For each disease, they applied an algorithm to combine the information from all these variants into a single number: the polygenic risk score.
A key finding of their analysis was that eight percent of the individuals assessed were more than three times as likely to develop coronary artery disease than the rest of the population as a result of their additive genetic variants, despite not yet showing any clinical symptoms associated with this condition.
'These individuals, who are at several times the normal risk for having a heart attack just because of the additive effects of many variations, are mostly flying under the radar,' said Dr Amit Khera, also at the Broad Institute and first author on the study.
Importantly a 'bad' risk score does not necessarily mean that an individual will definitely develop a given disease. Of the UK Biobank database, less than one percent of individuals with the lowest risk scores were diagnosed with coronary artery diseases, compared with 11 percent of individuals with the highest risk score.
The authors hope that this type of disease risk approach could be incorporated into clinical care in the future, and help people to make informed decisions about their lifestyles on the basis of any genetic predisposition.
'We envision polygenic risk scores as a way to identify people at high or low risk for a disease, perhaps as early as birth, and then use that information to target interventions to prevent disease,' said Dr Kathiresan.
The results of this study are largely based on the reference genomes of people of European ancestry. Diversifying the study to include other ethnic groups would be necessary to optimise the algorithms for the general population.