Background Neurodevelopmental disorders, hypotonia, microcephaly or macrocephaly, poor growth and distinctive facial traits are some of the most common reasons to refer a child to an expert consultant. But which expert? A priori response might not be always predictable. Clinical experience teaches that it is not unusual to come across a metabolic diagnosis in a patient suspected of a genetic condition and vice versa. Still, although phenotypically convergent, genetic and metabolic disorders strongly diverge on therapeutic availability. In such an entangled scenario, new sequencing technologies may bring to light further uncertainties, detecting variants that often need a clinical confirm to be interpreted. Methods. In order to explore clinical convergence among metabolic and genetic disorders we present a cases’ collection of patients wrongly referred to metabolic disorder clinic or to medical genetic service in a third level Center in the North of Italy. Results. Data gained from this retrospective review demonstrate the striking importance of multi-disciplinary management of complex pediatric cases. Conclusions. In Hub Hospitals and in rare diseases’ Centers, it appears mandatory to promote a side by side collaboration embracing pediatricians, clinical geneticists and laboratory in order to take an all-around point of view of undiagnosed patients. What falls out of our competence might fall out of our view as well.

Background: The STAG1 gene has been related to a poorly known form of intellectual disability, known as Intellectual Developmental Disorder, Autosomal Dominant 47 (MRD47). Functionally, MRD47 is part of the Cohesinopathies, a small family of rare genetic disorders caused by defective cohesin complex, whose activity is essential for sister chromatid cohesion and therefore for chromatin organization. Chromatin state modulation is an entangled process finely modulated by a large number of actors that, if altered, give rise to the so-called Chromatinopathies. The clinical and biological overlap among these families of conditions on one hand poses significant challenges during diagnostic definition, and, on the other, may help delineate more accurate management guidelines. Methods: Starting from the report of a novel pathogenic variant in the STAG1 gene, we performed a retrospective clinical and molecular review of all previously reported patients affected by this rare disorder. Once clinical and photographic data of all published patients were collected, we used Face2Gene deep learning technology to analyze STAG1 facial phenotype, comparing it to both Chromatinopathy and Cohesinopathy profiles. Results: Our clinical and molecular re-evaluation of reported cases confirms MRD47 as a mainly neurodevelopmental disorder. Through artificial intelligence technology, we were able to first create the gestaltic profile of MRD47. Face2Gene analyses of this composite phenotype, although limited by the tool’s analysis modalities, demonstrates the strong overlap of STAG1 disorder with Chromatinopathies. Conclusions: The present literature review, together with gestaltic analyses of the STAG1-related phenotype, underscores the strong resemblance of MRD47 to epigenetic machinery disorders. The present case brings to light once more the biological and phenotypical entanglement of Cohesinopathies and Chromatinopathies, hinting at STAG1 as the joining chain.