RESUMO
Duplications of the 3q29 cytoband are rare chromosomal copy number variations (CNVs) (overlapping or recurrent ~1.6 Mb 3q29 duplications). They have been associated with highly variable neurodevelopmental disorders (NDDs) with various associated features or reported as a susceptibility factor to the development of learning disabilities and neuropsychiatric disorders. The smallest region of overlap and the phenotype of 3q29 duplications remain uncertain. We here report a French cohort of 31 families with a 3q29 duplication identified by chromosomal microarray analysis (CMA), including 14 recurrent 1.6 Mb duplications, eight overlapping duplications (>1 Mb), and nine small duplications (<1 Mb). Additional genetic findings that may be involved in the phenotype were identified in 11 patients. Focusing on apparently isolated 3q29 duplications, patients present mainly mild NDD as suggested by a high rate of learning disabilities in contrast to a low proportion of patients with intellectual disabilities. Although some are de novo, most of the 3q29 duplications are inherited from a parent with a similar mild phenotype. Besides, the study of small 3q29 duplications does not provide evidence for any critical region. Our data suggest that the overlapping and recurrent 3q29 duplications seem to lead to mild NDD and that a severe or syndromic clinical presentation should warrant further genetic analyses.
Assuntos
Duplicação Cromossômica , Cromossomos Humanos Par 3 , Variações do Número de Cópias de DNA , Fenótipo , Humanos , Feminino , Masculino , Cromossomos Humanos Par 3/genética , Duplicação Cromossômica/genética , Criança , Variações do Número de Cópias de DNA/genética , Pré-Escolar , Transtornos do Neurodesenvolvimento/genética , Transtornos do Neurodesenvolvimento/patologia , Adolescente , Estudos de Coortes , Deficiência Intelectual/genética , Deficiência Intelectual/patologia , Adulto , LactenteRESUMO
The field of dysmorphology has been changed by the use Artificial Intelligence (AI) and the development of Next Generation Phenotyping (NGP). The aim of this study was to propose a new NGP model for predicting KS (Kabuki Syndrome) on 2D facial photographs and distinguish KS1 (KS type 1, KMT2D-related) from KS2 (KS type 2, KDM6A-related). We included retrospectively and prospectively, from 1998 to 2023, all frontal and lateral pictures of patients with a molecular confirmation of KS. After automatic preprocessing, we extracted geometric and textural features. After incorporation of age, gender, and ethnicity, we used XGboost (eXtreme Gradient Boosting), a supervised machine learning classifier. The model was tested on an independent validation set. Finally, we compared the performances of our model with DeepGestalt (Face2Gene). The study included 1448 frontal and lateral facial photographs from 6 centers, corresponding to 634 patients (527 controls, 107 KS); 82 (78%) of KS patients had a variation in the KMT2D gene (KS1) and 23 (22%) in the KDM6A gene (KS2). We were able to distinguish KS from controls in the independent validation group with an accuracy of 95.8% (78.9-99.9%, p < 0.001) and distinguish KS1 from KS2 with an empirical Area Under the Curve (AUC) of 0.805 (0.729-0.880, p < 0.001). We report an automatic detection model for KS with high performances (AUC 0.993 and accuracy 95.8%). We were able to distinguish patients with KS1 from KS2, with an AUC of 0.805. These results outperform the current commercial AI-based solutions and expert clinicians.
Assuntos
Anormalidades Múltiplas , Inteligência Artificial , Face/anormalidades , Doenças Hematológicas , Doenças Vestibulares , Humanos , Mutação , Estudos Retrospectivos , Doenças Hematológicas/diagnóstico , Doenças Hematológicas/genética , Fenótipo , Histona Desmetilases/genética , GenótipoRESUMO
INTRODUCTION AND METHODS: We report two series of individuals with DDX3X variations, one (48 individuals) from physicians and one (44 individuals) from caregivers. RESULTS: These two series include several symptoms in common, with fairly similar distribution, which suggests that caregivers' data are close to physicians' data. For example, both series identified early childhood symptoms that were not previously described: feeding difficulties, mean walking age, and age at first words. DISCUSSION: Each of the two datasets provides complementary knowledge. We confirmed that symptoms are similar to those in the literature and provides more details on feeding difficulties. Caregivers considered that the symptom attention-deficit/hyperactivity disorder were most worrisome. Both series also reported sleep disturbance. Recently, anxiety has been reported in individuals with DDX3X variants. We strongly suggest that attention-deficit/hyperactivity disorder, anxiety, and sleep disorders need to be treated.