Clinical score of 62 Italian patients with Cornelia de Lange syndrome and correlations with the presence and type ofNIPBLmutation

2007 ◽  
Vol 72 (2) ◽  
pp. 98-108 ◽  
Author(s):  
A Selicorni ◽  
S Russo ◽  
C Gervasini ◽  
P Castronovo ◽  
D Milani ◽  
...  
2020 ◽  
Vol 21 (3) ◽  
pp. 1042 ◽  
Author(s):  
Ana Latorre-Pellicer ◽  
Ángela Ascaso ◽  
Laura Trujillano ◽  
Marta Gil-Salvador ◽  
Maria Arnedo ◽  
...  

Characteristic or classic phenotype of Cornelia de Lange syndrome (CdLS) is associated with a recognisable facial pattern. However, the heterogeneity in causal genes and the presence of overlapping syndromes have made it increasingly difficult to diagnose only by clinical features. DeepGestalt technology, and its app Face2Gene, is having a growing impact on the diagnosis and management of genetic diseases by analysing the features of affected individuals. Here, we performed a phenotypic study on a cohort of 49 individuals harbouring causative variants in known CdLS genes in order to evaluate Face2Gene utility and sensitivity in the clinical diagnosis of CdLS. Based on the profile images of patients, a diagnosis of CdLS was within the top five predicted syndromes for 97.9% of our cases and even listed as first prediction for 83.7%. The age of patients did not seem to affect the prediction accuracy, whereas our results indicate a correlation between the clinical score and affected genes. Furthermore, each gene presents a different pattern recognition that may be used to develop new neural networks with the goal of separating different genetic subtypes in CdLS. Overall, we conclude that computer-assisted image analysis based on deep learning could support the clinical diagnosis of CdLS.


2021 ◽  
Author(s):  
Maria Jesus Pablo ◽  
Pilar Pamplona ◽  
Maria Haddad ◽  
Isabel Benavente ◽  
Ana Latorre-Pellicer ◽  
...  

Abstract BackgroundCornelia de Lange Syndrome (CdLS) is a rare congenital disorder characterized by typical facial features, growth failure, limb abnormalities, and gastroesophageal dysfunction that may be caused by mutations in several genes that disrupt gene regulation early in development. Symptoms in individuals with CdLS suggest that the peripheral nervous system (PNS) is involved, yet there is little direct evidence.MethodSomatic nervous system was evaluated by conventional motor and sensory nerve conduction studies and autonomic nervous system by heart rate variability, sympathetic skin response and sudomotor testing. CdLS Clinical Score and genetic studies were also obtained.ResultsSympathetic skin response and sudomotor test were pathological in 35% and 34% of the individuals with CdLS, respectively. Nevertheless, normal values in large fiber nerve function studies.ConclusionsAutonomic nervous system (ANS) dysfunction is found in many individuals with Cornelia de Lange syndrome, and could be related to premature aging.


2015 ◽  
Vol 2015 (mar24 2) ◽  
pp. bcr2014209124-bcr2014209124 ◽  
Author(s):  
A. Galderisi ◽  
G. De Bernardo ◽  
E. Lorenzon ◽  
D. Trevisanuto

Diagnostics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 142
Author(s):  
Anca Maria Panaitescu ◽  
Simona Duta ◽  
Nicolae Gica ◽  
Radu Botezatu ◽  
Florina Nedelea ◽  
...  

Cornelia de Lange syndrome (CDLS) is caused by pathogenic variants in genes which are structural or regulatory components of the cohesin complex. The classical Cornelia de Lange (CDLS) phenotype is characterized by distinctive facial features, growth retardation, upper limb reduction defects, hirsutism, and developmental delay. Non-classical phenotypes make this condition heterogeneous. Although CDLS is a heterogeneous clinical and genetic condition, clear diagnostic criteria have been described by specialist consensus. Many of these criteria refer to features that can be seen on prenatal ultrasound. The aim of this paper is twofold: to present the ultrasound findings in fetuses affected by CDLS syndrome; to discuss the recent advances and the limitations in the ultrasound and genetic prenatal diagnosis of CDLS. Our review aims to offer, apart from the data needed to understand the genetics and the prenatal presentation of the disease, a joint perspective of the two specialists involved in the prenatal management of this pathology: the fetal medicine specialist and the geneticist. To better illustrate the data presented, we also include a representative clinical case.


2021 ◽  
Vol 11 (2) ◽  
pp. 710
Author(s):  
Ángel Matute-Llorente ◽  
Ángela Ascaso ◽  
Ana Latorre-Pellicer ◽  
Beatriz Puisac ◽  
Laura Trujillano ◽  
...  

The aim of this study was to evaluate bone health and body composition by dual-energy X-ray absorptiometry (DXA) in individuals with Cornelia de Lange Syndrome (CdLS). Overall, nine individuals with CdLS (five females, all Caucasian, aged 5–38 years) were assessed. Total body less head (TBLH) and lumbar spine (LS) scans were performed, and bone serum biomarkers were determined. Molecular analyses were carried out and clinical scores and skeletal features were assessed. Based on deep sequencing of a custom target gene panel, it was discovered that eight of the nine CdLS patients had potentially causative genetic variants in NIPBL. Fat and lean mass indices (FMI and LMI) were 3.4–11.1 and 8.4–17.0 kg/m2, respectively. For TBLH areal bone mineral density (aBMD), after adjusting for height for age Z-score of children and adolescents, two individuals (an adolescent and an adult) had low BMD (aBMD Z-scores less than –2.0 SD). Calcium, phosphorus, 25-OH-vitamin D, parathyroid hormone, and alkaline phosphatase levels were 2.08–2.49 nmol/L, 2.10–3.75 nmol/L, 39.94–78.37 nmol/L, 23.4–80.3 pg/mL, and 43–203 IU/L, respectively. Individuals with CdLS might have normal adiposity and low levels of lean mass measured with DXA. Bone health in this population seems to be less of a concern during childhood and adolescence. However, they might be at risk for impaired bone health due to low aBMD in adulthood.


1963 ◽  
Vol 63 (5) ◽  
pp. 1000-1020 ◽  
Author(s):  
Louis J. Ptacek ◽  
John M. Opitz ◽  
David W. Smith ◽  
Theo Gerritsen ◽  
Harry A. Waisman

2012 ◽  
Vol 158A (11) ◽  
pp. 2953-2955 ◽  
Author(s):  
Chiara Barboni ◽  
Anna Cereda ◽  
Milena Mariani ◽  
Cristina Gervasini ◽  
Paola Ajmone ◽  
...  

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