Up to 40% of genetic and rare disorders (RD) present facial dysmorphologies. Visual assessment of facial gestalt is commonly used for clinical diagnosis, health management and treatment monitoring. Quantitative approaches to facial phenotypes are more objective and provide first diagnoses of RD with relatively high accuracy, but are mainly based on populations of European descent, disregarding the influence of population ancestry. Here we assessed the facial phenotypes associated to four genetic disorders in a Latino-American population from Colombia. We recorded the coordinates of 18 facial landmarks in 2D images from 79 controls 51 pediatric individuals diagnosed with Down (DS), Morquio (MS), Noonan (NS) and Neurofibromatosis type 1 (NF1) syndromes. We quantified facial differences using Euclidean Distance Matrix Analysis (EDMA) and assessed the diagnostic accuracy of Face2gene, an automatic deep learning algorithm with widespread use in the clinical practice.Quantitative comparisons indicated that individuals diagnosed with DS and MS were associated with the most severe phenotypes, with 58.2% and 65.4% of facial traits significantly different as compared to controls. The percentage decreased to 47.7% in NS and to 11.4% in NF1. Each syndrome presented a characteristic pattern of facial dysmorphology, supporting the potential of facial biomarkers for disorder diagnosis. However, our results detected population-specific traits in the Colombian population as compared to the facial gestalt described in literature for DS, NS and NF1. When clinical diagnosis based on genetic testing was used to verify the diagnosis based on 2D facial pictures, our results showed that Face2Gene accuracy was very high in DS, moderate in NS and NF1, and very low in MS, with low gestalt similarity scores in highly admixed individuals. Our study underscores the added value of precise quantitative comparison of facial dysmorphologies in genetic and rare disorders and the need to incorporate populations with diverse contributions of Amerindian, African and European ancestry components to further improve automatic diagnostic methods.

Up to 40% of genetic and rare disorders (RD) present facial dysmorphologies, and visual assessment is commonly used for clinical diagnosis. Although quantitative approaches are more objective and accurate, most current methods based on European descent populations disregard population ancestry. Here we assessed the facial phenotypes associated to Down (DS), Morquio (MS), Noonan (NS) and Neurofibromatosis type 1 (NF1) syndromes in a Latino-American population from Colombia. We recorded the coordinates of 18 landmarks in 2D images from 79 controls and 51 pediatric 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 percentage decreased to 47.7% in NS and 11.4% in NF1. Each syndrome presented characteristic dysmorphology patterns, supporting the diagnostic potential of facial biomarkers. However, population-specific traits were detected, and the diagnostic accuracy of Face2Gene was affected by ancestry. Accuracy was high in DS, moderate in NS and NF1, but low in MS, with low facial gestalt similarity in admixed individuals. Our study underscores that facial quantitative analysis in populations with diverse Amerindian, African and European ancestry are crucial to improve diagnostic methods.

Currently there are more than 10,000 rare diseases that affect about 7% of the world's population. Up to 40% of rare genetic disorders present craniofacial dysmorphologies, which can vary from subtle facial anomalies to severe malformations. Visual assessment of facial dysmorphology is commonly used for clinical diagnosis, patient management and treatment monitoring. However, qualitative descriptions are usually vague and quantitative approaches using craniofacial phenotypes for the diagnosis of rare diseases are based on North American and European populations, disregarding the influence of population ancestry on facial variation, as in Latin‐America. In this study, we assessed facial dysmorphologies associated to three different genetic disorders (Down (DS), Morquio (MS) and Noonan syndrome (NS)) in a Latin‐American population from Cali (Colombia). We recorded the coordinates of 18 facial landmarks in 2D images from 34 pediatric patients (19 DS, 8 MS, 6 NS) and 75 controls and quantified facial differences between patients and control groups using Euclidean Distance Matrix Analysis (EDMA). Comparisons between control and syndromic phenotypes indicated that individuals diagnosed with DS and MS presented the largest percentage of dysmorphologies, with respectively 56.2% and 54.9% of significantly different facial traits. In NS, the percentage decreased to 12.4%. Each syndrome presented a characteristic facial pattern. In DS, all facial structures were affected, with a 6% increase of relative distance between the eyes and a 7‐10% reduction in facial height. The eyes and nose were most affected in MS, but not the mouth, with higher hypertelorism and facial reduction than in DS (9% and 8‐17%). In NS, facial differences were more subtle and affected mainly the eyes and mouth, reducing the relative distance between them from 1 to 4% in patients as compared to controls. Our study provides a precise quantitative comparison of facial dysmorphologies in three genetic disorders that in the future can be compared with other world‐wide populations to test whether facial traits associated to disease are altered by different evolutionary and adaptive histories of human populations.

Down syndrome (DS) is a genetic disorder occurring in 1 out of every 700 to 1,000 live births caused by trisomy of chromosome 21. The overexpression of the Amyloid Precursor Protein (APP) gene located on this chromosome leads to an early onset and rapid accumulation of ß‐amyloid (Aß) in the brain that invariably results in Alzheimer Disease (AD) in people with DS. Therefore, AD, the most common form of dementia, is currently one of the most relevant medical issues in people with DS. In this study, we assessed brain morphological patterns to quantify dysmorphologies associated with AD in Down syndrome. Brain shape and size analyses were performed using Geometric Morphometrics in a sample of 243 adults, including 153 euploid healthy controls (EU) and 90 individuals with DS at different stages of dementia: asymptomatic DS with no signs of AD‐related cognitive impairment (N=58), individuals with DS and prodromal AD (N=21) and individuals diagnosed with AD dementia (N=11). A set of 38 3D brain landmarks representing the overall shape of the brain and internal brain structures (ventricles, corpus callosum, cerebellum and pons) were located on magnetic resonance images of the head. Results showed a significant separation between EU and DS populations based on both global and local brain shape and size analyses. Individuals with DS displayed a smaller cerebellum, a protruding posterior midbody in the corpus callosum, a frontally projected brain and expanded ventricles. Significant brain shape differences were detected in individuals diagnosed with AD, which mainly affected the shape of enlarged brain ventricles. Remarkably, individuals at advanced stages of the disease displayed more severe dysmorphologies as compared to those individuals at prodromal stages and individuals with no signs of dementia, confirming a phenotypic continuum associated with the severity of dementia that highlights the impact of this neurodegenerative disorder in brain morphology.