����ɫ��

Most children with rare genetic diseases spend years undergoing medical tests and waiting for a diagnosis — a long, exhausting process that takes its toll on children and families. Almost half of these children never get a definitive diagnosis.

An international team led by scientists and clinicians at the universities of Calgary, Colorado and California has developed a prototype tool based on three-dimensional (3D) facial imaging with potential to shorten that diagnostic odyssey by making it easier to diagnose genetic diseases.

• Photo above: A machine learning algorithm analyzed thousands of 3D facial images in a secure database to ID aspects of facial shape and structure that differentiate hundreds of genetic syndromes. Shown here are computer-generated images illustrating facial features that distinguish different syndromes. The names you see refer to genetic conditions. Courtesy of Genetics in Medicine

“Families tell us having a diagnosis for their child’s rare disease is life-changing,” says Dr. Benedikt Hallgrímsson, PhD, professor and head of the Department of Cell biology and Anatomy, and scientific director (basic science) at the in the at the ����ɫ��. “A diagnosis is essential to children getting the right treatments and connecting with other children and families with the same syndrome.”

Clinical geneticists have long relied on distinctive facial features as an important guide to diagnose genetic syndromes.

In a new study published in , the researchers created a unique library of 3D facial images of 7,057 participants from the United States, Canada, and the United Kingdom, including children and adults with 396 genetic syndromes, their relatives and other unaffected people. The secure database is hosted by FaceBase, an international consortium funded by the National Institute of Dental and Craniofacial Research, part of the National Institutes of Health (NIH).

The researchers then used this secure database to train a machine-learning algorithm to identify most of the genetic syndromes with moderate-to-high accuracy. Based on facial shape, 96 per cent of study subjects were correctly classified as either unaffected or having a syndrome, and for most, the algorithm was able to provide a prioritized list of likely diagnoses.

The COVID-19 pandemic has accelerated a rapid shift to telemedicine by genetics clinics, including those at UCalgary, the University of California San Francisco (UCSF), and the University of Colorado, but the study team says the field still lacks tools to replace many aspects of the in-person physical exam. The automated diagnostic approach developed in this study could extend the ability of clinical geneticists to diagnose patients. It could also help guide general practitioners on potential diagnoses, enabling them to connect patients with appropriate specialty care and community support.

“Clinical genetics is labour-intensive,” says Dr. Ophir Klein, MD, PhD, the Larry L. Hillblom Distinguished Professor in Craniofacial Anomalies and the Charles J. Epstein Professor of Human Genetics at UCSF, where he is chief of medical genetics. “Some clinics have a two-year waiting list to get in.

Using 3D imaging could dramatically enhance clinicians’ ability to diagnose children more quickly and inexpensively.

The current study represents an important proof-of-concept for facilitating genetic diagnoses, but the researchers emphasize further work is needed to deploy a privacy-protected clinical tool. Currently, the approach relies on expensive 3D cameras, but this is expected to change with advances in smartphone technologies.

“We have designed a prototype with significant potential to become a clinical tool around the world,” says Dr. Richard Spritz, MD, professor of paediatrics and director of the at the University of Colorado School of Medicine. “Our hope is that one day soon, our patients can securely take a photo of their face with a smartphone and send it to their doctor for analysis in a confidential database.”

“In low-income countries where genetic testing and medical geneticists aren’t available, this could become a transformational new tool,” adds Hallgrímsson, also a member of the at UCalgary.

This research was supported by the National Institutes of Health, the through the , and The Larry L. Hillblom Foundation.

Benedikt Hallgrímsson is professor and head of the Department of Cell Biology and Anatomy, a professor in the Department of Radiology, scientific director (basic science) at the Alberta Children’s Hospital Research Institute and a member of the McCaig Institute for Bone and Joint Health.

Nicholas Weiler is with the University of California San Francisco and Karen Thomas is with the Alberta Children’s Hospital Research Institute.