Could face recognition technology diagnose rare genetic disorders?
A computer algorithm can help identify people with rare genetic disorders from ordinary photographs.
Rare genetic disorders affect around 8% of people, many of whom live with symptoms that greatly reduce their quality of life. Genetic diagnoses can provide doctors with information that cannot be obtained by assessing clinical symptoms, and this allows them to select more suitable treatments for patients. However, only a minority of patients currently receive a genetic diagnosis.
Alterations in the face and skull are present in 30–40% of genetic disorders, and these alterations can help doctors to identify certain disorders, such as Down’s syndrome or Fragile X. Extending this approach, Quentin Ferry and co-workers trained a computer-based model to identify the patterns of facial abnormalities associated with different genetic disorders. The model compares data extracted from a photograph of the patient’s face with data on the facial characteristics of 90 disorders, and then provides a list of the most likely diagnoses for that individual. The model used 36 points to describe the space, including 7 for the jaw, 6 for the mouth, 7 for the nose, 8 for the eyes and 8 for the brow.
This approach of Ferry and co-workers has three advantages. First, it provides clinicians with information that can aid their diagnosis of a rare genetic disorder. Second, it can narrow down the range of possible disorders for patients who have the same ultra-rare disorder, even if that disorder is currently unknown. Third, it can identify groups of patients who can have their genomes sequenced in order to identify the genetic variants that are associated with specific disorders.
The work by Ferry and co-workers lays out the basic principles for automated approaches to analyze the shape of the face and skull. The next challenge is to integrate photos with genetic data for use in clinical settings.
To find out more
Listen to Christoffer Nellåker discuss a new approach to identifying rare genetic disorders in episode 13 of the eLife podcast.
Read the eLife research paper on which this story is based: “Diagnostically relevant facial gestalt information from ordinary photos” (June 24, 2014).
eLife is an open-access journal that publishes outstanding research in the life sciences and biomedicine.
