Access to vast banks of genomic data is powering a new wave of assessments and predictions that could offer a glimpse at how genetic variation might impact everything from Alzheimer’s Disease risk to IQ scores
Anatomic pathology groups and clinical laboratories have become accustomed to performing genetic tests for diagnosing specific chronic diseases in humans. Thanks to significantly lower costs over just a few years ago, whole-genome sequencing and genetic DNA testing are on the path to becoming almost commonplace in America. BRCA 1 and BRCA 2 breast cancer gene screenings are examples of specific genetic testing for specific diseases.
However, a much broader type of testing—called polygenic scoring—has been used to identify certain hereditary traits in animals and plants for years. Also known as a genetic-risk score or a genome-wide score, polygenic scoring is based on thousands of genes, rather than just one.
Now, researchers in Cambridge, Mass., are looking into whether it can be used in humans to predict a person’s predisposition to a range of chronic diseases. This is yet another example of how relatively inexpensive genetic tests are producing data that can be used to identify and predict how individuals get different diseases.
Assessing Heart Disease Risk through Genome-Wide Analysis
Sekar Kathiresan, MD, Co-Director of the Medical and Population Genetics program at Broad Institute of MIT/Harvard and Director of the Center for Genomics Medicine at Massachusetts General Hospital (Mass General); and Amit Khera, MD, Cardiology Fellow at Mass General, told MIT Technology Review “the new scores can now identify as much risk for disease as the rare genetic flaws that have preoccupied physicians until now.”
“Where I see this going is that, at a young age, you’ll basically get a report card,” Khera noted. “And it will say for these 10 diseases, here’s your score. You are in the 90th percentile for heart disease, 50th for breast cancer, and the lowest 10% for diabetes.”
However, as the MIT Technology Review article points out, predictive genetic testing, such as that under development by Khera and Kathiresan, can be performed at any age.
“If you line up a bunch of 18-year-olds, none of them have high cholesterol, none of them have diabetes. It’s a zero in all the columns, and you can’t stratify them by who is most at risk,” Khera noted. “But with a $100 test we can get stratification [at the age of 18] at least as good as when someone is 50, and for a lot of diseases.”
Polygenic Scores Show Promise for Cancer Risk Assessment
Khera and Kathiresan are not alone in exploring the potential of polygenic scores. Researchers at the University of Michigan’s School of Public Health looked at the association between polygenic scores and more than 28,000 genotyped patients in predicting squamous cell carcinoma.
“Looking at the data, it was surprising to me how logical the secondary diagnosis associations with the risk score were,” Bhramar Mukherjee, PhD, John D. Kalbfleisch Collegiate Professor of Biostatistics, and Professor of Epidemiology at U-M’s School of Public Health, stated in a press release following the publication of the U-M study, “Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative.”
“It was also striking how results from population-based studies were reproduced using data from electronic health records, a database not ideally designed for specific research questions and [which] is certainly not a population-based sample,” she continued.
Additionally, researchers at the University of California San Diego School of Medicine (UCSD) recently published findings in Molecular Psychiatry on their use of polygenic scores to assess the risk of mild cognitive impairment and Alzheimer’s disease.
The UCSD study highlights one of the unique benefits of polygenic scores. A person’s DNA is established in utero. However, predicting predisposition to specific chronic diseases prior to the onset of symptoms has been a major challenge to developing diagnostics and treatments. Should polygenic risk scores prove accurate, they could provide physicians with a list of their patients’ health risks well in advance, providing greater opportunity for early intervention.
Future Applications of Polygenic Risk Scores
In the January issue of the British Medical Journal (BMJ), researchers from UCSD outlined their development of a polygenic assessment tool to predict the age-of-onset of aggressive prostate cancer. As Dark Daily recently reported, for the first time in the UK, prostate cancer has surpassed breast cancer in numbers of deaths annually and nearly 40% of prostate cancer diagnoses occur in stages three and four. (See, “UK Study Finds Late Diagnosis of Prostate Cancer a Worrisome Trend for UK’s National Health Service,” May 23, 2018.)
An alternative to PSA-based testing, and the ability to differentiate aggressive and non-aggressive prostate cancer types, could improve outcomes and provide healthcare systems with better treatment options to reverse these trends.
While the value of polygenic scores should increase as algorithms and results are honed and verified, they also will most likely add to concerns raised about the impact genetic test results are having on patients, physicians, and genetic counselors.
And, as the genetic testing technology of personalized medicine matures, clinical laboratories will increasingly be required to protect and distribute much of the protected health information (PHI) they generate.
Nevertheless, when the data produced is analyzed and combined with other information—such as anatomic pathology testing results, personal/family health histories, and population health data—polygenic scores could isolate new biomarkers for research and offer big-picture insights into the causes of and potential treatments for a broad spectrum of chronic diseases.