Next-generation phenotyping using computer vision algorithms in rare genomic neurodevelopmental disorders.

ABSTRACT:

Purpose

The interpretation of genetic variants after genome-wide analysis is complex in heterogeneous disorders such as intellectual disability (ID). We investigate whether algorithms can be used to detect if a facial gestalt is present for three novel ID syndromes and if these techniques can help interpret variants of uncertain significance.

Methods

Facial features were extracted from photos of ID patients harboring a pathogenic variant in three novel ID genes (PACS1, PPM1D, and PHIP) using algorithms that model human facial dysmorphism, and facial recognition. The resulting features were combined into a hybrid model to compare the three cohorts against a background ID population.

Results

We validated our model using images from 71 individuals with Koolen-de Vries sy

SUBMITTER: van der Donk R 

PROVIDER: S-EPMC6752476 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature