Phenotypic data combined with artificial intelligence provides a new biomarker for genetic laboratories to use when diagnosing disease
Researchers are demonstrating that facial analysis and facial recognition technology can play a useful role in helping pathology and medical laboratory scientists diagnose disease. This is just the latest example of how advances in different technologies can add new sources of biomarkers for clinical laboratories.
Biomarkers used by clinical laboratories and anatomic pathologists are usually biological substances or states that can be measured during testing either in vivo or in vitro. However, clinical laboratories may soon be working with biomarkers based on measurable aspects of external human anatomy. One such biomarker employs facial analysis and facial recognition technology to produced phenotypic data that could help pathologists diagnose rare genetic disorders. A human phenotype is data comprised of a person’s “observable characteristics or traits.”
Phenotypic Data from Photographs
Three genomics companies: FDNA, GeneDx, and Blueprint Genetics, are collaborating on a unique project, dubbed Face2Gene Labs. They are using a facial recognition application called Face2Gene developed by FDNA. The application uses artificial intelligence (AI) and phenotyping technology to extract data from facial photographs of patients. The data is then examined and compared to a database of hundreds of thousands of patterns that were generated from photos of patients with known rare genetic disorders. The algorithm then compiles a list of possible diagnoses. The goal is to produce phenotypic data that clinicians can transmit in real-time directly to medical laboratories for analysis.
“Trying to diagnose patients with genetic sequencing is like searching for a pin in a 22,000-needle haystack,” stated Dekel Gelbman, CEO, FDNA, in a news release. “By providing accurate phenotypic and clinical data to the lab directly at the point of genetic interpretation, we are truly realizing the promise of precision medicine. And, with the power of artificial intelligence behind it, clinicians will be pointed toward potential diagnoses that they may have never otherwise considered.”
Solomon goes on to praise GeneDx and Blueprint Genetics as examples of innovative and renowned labs adopting technology that will lead the way in pinpointing rare disease and promote further medical advancements.
“This is an important collaboration for several reasons,” states Ben Solomon, MD, a Clinical Geneticist and Managing Director of GeneDx, in the news release. “It’s a great way to leverage clinical and genetic information and machine learning approaches to find answers for the clinicians, patients, and families GeneDx serves. Aside from providing answers, this integration will make the diagnostic testing process easier, smoother, and more enjoyable for clinicians.”
85% Increase in Diagnostic Yield with Addition of Phenotypic Data
A recent multi-center study called PEDIA (short for Prioritization of Exome Data by Image Analysis) looked into the accuracy of genetic testing when using FDNA’s Face2Gene tool. The study, conducted by researchers at the Berlin Institute of Health and Charité University of Medicine in Berlin, showed promising results of the collaboration.
“We estimate that the addition of phenotypic features [encoded in HPO terms] increases the diagnostic yield to about 60% [from 25% without],” stated Peter Krawitz, MD, PhD, and Principal Investigator for PEDIA. “When adding facial analysis, FDNA’s technology, to that process, the diagnostic yield increases to more than 85%,” he explained in the FDNA news release.
The Rarity Paradox and Diagnosing Genetic Disorders in Children
According to Global Genes, a rare disease patient advocacy non-profit organization, one in 10 Americans (approximately 30 million people) suffer from a rare genetic disorder. These disorders also affect the same percentage of people worldwide, or about 350 million people. There are more than 7,000 distinct rare diseases known to exist and approximately 80% of those illnesses are caused by faulty genes. In addition, about half of the people affected by rare genetic illnesses are children.
“We call it the rarity paradox,” stated Gelbman in an article published in Wired. “Each rare disease in itself affects very few people, but on aggregate the effect is pretty staggering.”
The three companies hope their collaboration will help clinicians determine faster, more accurate diagnoses, while diminishing anxiety among patients and their families regarding the unknowns of rare genetic disorders.
“Since 2012, Blueprint Genetics has been developing technological innovations in sequencing and clinical interpretation to improve the quality and performance of rare disease diagnostics,” noted Tero-Pekka Alastalo, MD, PhD, President, Chief Medical Officer of Blueprint Genetics, in the FDNA news release. “It’s great to see how these innovations are now helping the genetics community and patients suffering from inherited disorders. Combining these technological innovations with our transparent approach to diagnostics and next generation phenotyping tools like Face2Gene represents the next steps forward in molecular genetic diagnostics.”
Pathology groups and clinical laboratories are advised to monitor this exciting development in genomic research. It illustrates how unrelated technologies, such as facial analysis software, could soon be used for diagnostic purposes to detect the presence of genetic disorders, and to determine the best therapies for patients. Labs will want to be prepared to engage with clinicians who adopt this technology and to answer patients’ questions about it.