Population‑specific facial traits and diagnosis accuracy of genetic and rare diseases in an admixed Colombian population
Author
Other authors
Publication date
2023-04-27ISSN
2045-2322
Abstract
Up to 40% of rare disorders (RD) present facial dysmorphologies, and visual assessment is commonly
used for clinical diagnosis. Quantitative approaches are more objective, but mostly rely on
European descent populations, disregarding diverse population ancestry. Here, we assessed the
facial phenotypes of Down (DS), Morquio (MS), Noonan (NS) and Neurofibromatosis type 1 (NF1)
syndromes in a Latino‑American population, recording the coordinates of 18 landmarks in 2D images
from 79 controls and 51 patients. We quantified facial differences using Euclidean Distance Matrix
Analysis, and assessed the diagnostic accuracy of Face2Gene, an automatic deep‑learning algorithm.
Individuals diagnosed with DS and MS presented severe phenotypes, with 58.2% and 65.4% of
significantly different facial traits. The phenotype was milder in NS (47.7%) and non‑significant in NF1
(11.4%). Each syndrome presented a characteristic dysmorphology pattern, supporting the diagnostic
potential of facial biomarkers. However, population‑specific traits were detected in the Colombian
population. Diagnostic accuracy was 100% in DS, moderate in NS (66.7%) but lower in comparison
to a European population (100%), and below 10% in MS and NF1. Moreover, admixed individuals
showed lower facial gestalt similarities. Our results underscore that incorporating populations with
Amerindian, African and European ancestry is crucial to improve diagnostic methods of rare disorders.
Document Type
Article
Document version
Published version
Language
English
Subject (CDU)
61 - Medical sciences
616.8 - Neurology. Neuropathology. Nervous system
62 - Engineering. Technology in general
Keywords
Pages
15 p.
Publisher
Nature Publishing Group
Is part of
Scientific reports (Nature Publishing Group), 2023
This item appears in the following Collection(s)
Rights
© L'autor/a
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/