Cornelia de Lange Spectrum.

Cornelia de Lange syndrome (CdLS) is a rare congenital developmental disorder with multisystemic involvement. The clinical presentation is highly variable, but the classic phenotype, characterized by distinctive craniofacial features, pre- and postnatal growth retardation, extremity reduction defects, hirsutism and intellectual disability can be distinguished from the nonclassic phenotype, which is generally milder and more difficult to diagnose. In addition, the clinical features overlap with those of other neurodevelopmental disorders, so the use of consensus clinical criteria and artificial intelligence tools may be helpful in confirming the diagnosis. Pathogenic variants in NIPBL, which encodes a protein related to the cohesin complex, have been identified in more than 60% of patients, and pathogenic variants in other genes related to this complex in another 15%: SMC1A, SMC3, RAD21, and HDAC8. Technical advances in large-scale sequencing have allowed the description of additional genes (BRD4, ANKRD11, MAU2), but the lack of molecular diagnosis in 15% of individuals and the substantial clinical heterogeneity of the syndrome suggest that other genes and mechanisms may be involved. Although there is no curative treatment, there are symptomatic/palliative treatments that paediatricians should be aware of. The main medical complication in classic SCdL is gastro-esophageal reflux (GER), which should be treated early.

Endocrine Evaluation and Homeostatic Model Assessment in Patients with Cornelia de Lange Syndrome.

Objective: The aim of this study was to expand knowledge about endocrine disorders in individuals with Cornelia de Lange syndrome (CdLS), a rare developmental genetic disorder with anomalies in multiple organs and systems. Methods: Hormone levels, clinical scores, anthropometric measurements, and molecular analysis were assessed in 24 individuals with CdLS. Results: Hyperprolactinemia was the most common endocrine disorder. Three patients showed subclinical hypothyroidism. In the gonadotropic axis, mildly delayed puberty was observed, as well as genital anomalies, such as cryptorchidism. Despite short stature, levels of insulin-like growth factor 1 and insulin-like growth factor-binding protein 3 were normal, on average. Three prepubertal individuals without risk factors had higher than normal values for the homeostatic model assessment of insulin resistance (HOMA-IR) and for insulinemia, suggesting insulin resistance. Furthermore, two adults had elevated BMIs associated with HOMA-IR values over the cut-off values. Conclusion: CdLS can lead to dysregulation of the endocrine system, particularly in patients with high HOMA-IR values and insulinemia who are at risk of insulin resistance. Therefore, clinical follow-ups with hormonal assessments are proposed for individuals with CdLS.

Subclinical myocardial dysfunction is revealed by speckle tracking echocardiography in patients with Cornelia de Lange syndrome.

This study assesses a possible cardiac dysfunction in individuals with Cornelia de Lange syndrome (CdLS) without diagnosed congenital heart disease (CHD) and its association with other factors. Twenty patients and 20 controls were included in the study divided into three age-dependent groups (A: < 10 yrs, B: 10-20 yrs, C: > 20 yrs), and were evaluated using conventional echocardiography, tissue doppler imaging (TDI), two-dimensional speckle tracking and genetic and biochemical analyses. The left ventricular global longitudinal strain (GLS) was altered (< 15.9%) in 55% of patients, being pathological in the older group (A: 19.7 ± 6.6; B: -17.2 ± 4.7; C: -13.6 ± 2.9). The speckle tracking technique revealed a downward trend in the values of strain, strain rate and velocity, especially in the oldest group. Likewise, the ejection fraction (LVEF) and shortening fraction (LVFS) values, although preserved, also showed a decreased with age (p < 0.05). The analytical markers of cardiovascular risk and cardiac function showed no alterations. The molecular analyses revealed 16 individuals carrying pathogenic variants in NIPBL, two with variants in SMC1A, one with a variant in RAD21 and one with a HDAC8 variant. This is the first systematic approach that demonstrates that individuals with CdLS may present early cardiomyopathy, which can be detected by speckle tracking technique even before the appearance of clinical symptoms and the alteration of other echocardiographic or analytical parameters. For all these reasons, cardiological followup is suggested even in the absence of CHD, especially from adolescence onwards.

Molecular Basis of the Schuurs-Hoeijmakers Syndrome: What We Know about the Gene and the PACS-1 Protein and Novel Therapeutic Approaches.

The Schuurs−Hoeijmakers syndrome (SHMS) or PACS1 Neurodevelopment Disorder (PACS1-NDD) is a rare autosomal dominant disease caused by mutations in the PACS1 gene. To date, only 87 patients have been reported and, surprisingly, most of them carry the same variant (c.607C>T; p.R203W). The most relevant clinical features of the syndrome include neurodevelopment delay, seizures or a recognizable facial phenotype. Moreover, some of these characteristics overlap with other syndromes, such as the PACS2 or Wdr37 syndromes. The encoded protein phosphofurin acid cluster sorting 1 (PACS-1) is able to bind to different client proteins and direct them to their subcellular final locations. Therefore, although its main function is protein trafficking, it could perform other roles related to its client proteins. In patients with PACS1-NDD, a gain-of-function or a dominant negative mechanism for the mutated protein has been suggested. This, together with the fact that most of the patients carry the same genetic variant, makes it a good candidate for novel therapeutic approaches directed to decreasing the toxic effect of the mutated protein. Some of these strategies include the use of antisense oligonucleotides (ASOs) or targeting of its client proteins.

Clinical relevance of postzygotic mosaicism in Cornelia de Lange syndrome and purifying selection of NIPBL variants in blood.

Postzygotic mosaicism (PZM) in NIPBL is a strong source of causality for Cornelia de Lange syndrome (CdLS) that can have major clinical implications. Here, we further delineate the role of somatic mosaicism in CdLS by describing a series of 11 unreported patients with mosaic disease-causing variants in NIPBL and performing a retrospective cohort study from a Spanish CdLS diagnostic center. By reviewing the literature and combining our findings with previously published data, we demonstrate a negative selection against somatic deleterious NIPBL variants in blood. Furthermore, the analysis of all reported cases indicates an unusual high prevalence of mosaicism in CdLS, occurring in 13.1% of patients with a positive molecular diagnosis. It is worth noting that most of the affected individuals with mosaicism have a clinical phenotype at least as severe as those with constitutive pathogenic variants. However, the type of genetic change does not vary between germline and somatic events and, even in the presence of mosaicism, missense substitutions are located preferentially within the HEAT repeat domain of NIPBL. In conclusion, the high prevalence of mosaicism in CdLS as well as the disparity in tissue distribution provide a novel orientation for the clinical management and genetic counselling of families.

Evaluating Face2Gene as a Tool to Identify Cornelia de Lange Syndrome by Facial Phenotypes.

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.