Methyl CpG binding protein 2 (MECP2) is located at Xq28 and is a multifunctional gene with ubiquitous expression. Loss-of-function mutations in MECP2 are associated with Rett syndrome (RTT), which is a well-characterized disorder that affects mainly females. In boys, however, mutations in MECP2 can generate a wide spectrum of clinical presentations that range from mild intellectual impairment to severe neonatal encephalopathy and premature death. Thus, males can be more difficult to classify and diagnose than classical RTT females. In addition, there are some variants of unknown significance in MECP2, which further complicate the diagnosis of these children. Conversely, the entire duplication of the MECP2 gene is related to MECP2 duplication syndrome (MDS). Unlike in RTT, in MDS, males are predominantly affected. Usually, the duplication is inherited from an apparently asymptomatic carrier mother. Both syndromes share some characteristics, but also differ in some aspects regarding the clinical picture and evolution. In the following review, we present a thorough description of the different types of MECP2 variants and alterations that can be found in males, and explore several genotype–phenotype correlations, although there is still a lot to understand.

Introduction Phosphomannomutase-2 deficiency (PMM2-CDG) is associated with a recognisable facial pattern. There are no early severity predictors for this disorder and no phenotype–genotype correlation. We performed a detailed dysmorphology evaluation to describe facial gestalt and its changes over time, to train digital recognition facial analysis tools and to identify early severity predictors. Methods Paediatric PMM2-CDG patients were evaluated and compared with controls. A computer-assisted recognition tool was trained. Through the evaluation of dysmorphic features (DFs), a simple categorisation was created and correlated with clinical and neurological scores, and neuroimaging. Results Dysmorphology analysis of 31 patients (4–19 years of age) identified eight major DFs (strabismus, upslanted eyes, long fingers, lipodystrophy, wide mouth, inverted nipples, long philtrum and joint laxity) with predictive value using receiver operating characteristic (ROC) curveanalysis (p<0.001). Dysmorphology categorisation using lipodystrophy and inverted nipples was employed to divide patients into three groups that are correlated with global clinical and neurological scores, and neuroimaging (p=0.005, 0.003 and 0.002, respectively). After Face2Gene training, PMM2-CDG patients were correctly identified at different ages. Conclusions PMM2-CDG patients’ DFs are consistent and inform about clinical severity when no clear phenotype–genotype correlation is known. We propose a classification of DFs into major and minor with diagnostic risk implications. At present, Face2Gene is useful to suggest PMM2-CDG. Regarding the prognostic value of DFs, we elaborated a simple severity dysmorphology categorisation with predictive value, and we identified five major DFs associated with clinical severity. Both dysmorphology and digital analysis may help physicians to diagnose PMM2-CDG sooner.

Background: KBG syndrome is a highly variable neurodevelopmental disorder and clinical diagnostic criteria have changed as new patients have been reported. Both loss-of-function sequence variants and large deletions (copy number variations, CNVs) involving ANKRD11 cause KBG syndrome, but no genotype–phenotype correlation has been reported. Methods: 67 patients with KBG syndrome were assessed using a custom phenotypical questionnaire. Manifestations present in >50% of the patients and a ‘phenotypical score’ were used to perform a genotype–phenotype correlation in 340 patients from our cohort and the literature. Results: Neurodevelopmental delay, macrodontia, triangular face, characteristic ears, nose and eyebrows were the most prevalentf (eatures. 82.8% of the patients had at least one of seven main comorbidities: hearing loss and/or otitis media, visual problems, cryptorchidism, cardiopathy, feeding difficulties and/or seizures. Associations found included a higher phenotypical score in patients with sequence variants compared with CNVs and a higher frequency of triangular face (71.1% vs 42.5% in CNVs). Short stature was more frequent in patients with exon 9 variants (62.5% inside vs 27.8% outside exon 9), and the prevalence of intellectual disability/attention deficit hyperactivity disorder/autism spectrum disorder was lower in patients with the c.1903_1907del variant (70.4% vs 89.4% other variants). Presence of macrodontia and comorbidities were associated with larger deletion sizes and hand anomalies with smaller deletions. Conclusion: We present a detailed phenotypical description of KBG syndrome in the largest series reported to date of 67 patients, provide evidence of a genotype–phenotype correlation between some KBG features and specific ANKRD11 variants in 340 patients, and propose updated clinical diagnostic criteria based on our findings.