Study Validates New Genetic Test's Ability to Predict Future Diseases, Distinguishing Disease Status Between Siblings
Research published in Nature's Scientific Reports validates the importance of genetic factors to long-term health, offers powerful screening capability for in vitro fertilization
NORTH BRUNSWICK, N.J., Sept. 29, 2020 /PRNewswire/ -- Researchers have published findings in the journal Nature Scientific Reports that validate the company Genomic Prediction's method for predicting future health risks based on genomic analysis. The study has profound implications for the in vitro fertilization (IVF) industry and the emerging field of predictive medicine.
In the article Sibling validation of polygenic risk scores and complex trait prediction, published in Nature Scientific Reports, researchers Louis Lello, Timothy Raben and Steve Hsu show that inexpensive genome analysis can predict individual risk for a range of diseases based on their unique polygenic risk scores (PRS), and rank siblings by likelihood of disease.
"New methods from machine learning and AI, combined with large genomic datasets, allow us to predict disease risk from DNA alone. In some cases, such as Breast Cancer, the new polygenic predictors can identify ten times as many high risk individuals as the older single gene tests," said Hsu, senior author of the study and co-founder of Genomic Prediction. "Our findings indicate unprecedented insight into an individual's disease risk during their lifetime, bringing us a meaningful step closer to personalized and ultimately, predictive, medicine."
The study shows that by computing the Polygenic Risk Score (PRS) for conditions such as breast cancer, diabetes or coronary artery disease, Genomic Prediction is able to correctly identify which individual out of a pair of siblings will develop the condition between 70 and 90 percent of the time, depending on the disease.
Studying sibling pairs minimizes the environmental differences that would exist between strangers during childhood and helps capture the underlying genetic causality behind roughly 30 common health conditions – and the technique is even more effective in comparing relative risk in random pairs of individuals.
"This is fantastically important and cutting-edge work," said Professor Simon Fishel, a pioneer in the field of IVF, and is also the Head of Genomic Prediction's Scientific Advisory Board. "The benefits of this science available today for families pursuing IVF, but in the not-too-distant future, I predict this kind of screening will be commonplace in healthcare systems everywhere." Professor Fishel was Deputy Scientific Director at the world's first IVF clinic, Bourn Hall, with the inventors of IVF, Edwards and Steptoe. Prof. Fishel worked with them for a number of years before the birth of the world's first IVF baby, Louise Brown, and before Edwards was awarded the Nobel Prize for this work.
The benefit for families pursuing IVF is the ability to screen for risks of serious illness before an embryo is even selected for transfer. This allows for a major potential positive impact on quality of life, and provides families and healthcare providers with advance knowledge of potential disease risk factors.
About Genomic Prediction: Genomic Prediction are the inventors of PGT-P: Preimplantation Genetic Testing for Polygenic disease, as well as the genomic index method of embryo ranking. This method has been validated in tens of thousands of pairs of siblings, demonstrating significantly reduced incidence of disease from genomic selection when compared to random selection. Genomic Prediction provides testing to over 100 clinics across the globe, and is a leader in preimplantation genetic testing, using state-of-the-art methods to provide would-be parents with the most accurate and actionable PGT results known to science. Genomic Prediction was Incorporated on May 1, 2017, and has been featured in The Economist, The Wall Street Journal, and New Scientist. For more information, visit www.genomicprediction.com.
Contact: Laurent Christian Asker Melchior Tellier, (646) 954-7144, [email protected]
SOURCE Genomic Prediction
Related Links
https://genomicprediction.com/
WANT YOUR COMPANY'S NEWS FEATURED ON PRNEWSWIRE.COM?
Newsrooms &
Influencers
Digital Media
Outlets
Journalists
Opted In
Share this article