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AbstractDefects in histone methyltransferases (HMTs) are major contributing factors in neurodevelopmental disorders (NDDs). Heterozygous variants of SETD1A involved in histone H3 lysine 4 (H3K4) methylation were previously identified in individuals with schizophrenia. Here, we define the clinical features of the Mendelian syndrome associated with haploinsufficiency of SETD1A by investigating 15 predominantly pediatric individuals who all have de novo SETD1A variants. These individuals present with a core set of symptoms comprising global developmental delay and/or intellectual disability, subtle facial dysmorphisms, behavioral and psychiatric problems. We examined cellular phenotypes in three patient derived lymphoblastoid cell lines with three variants: p.Gly535Alafs*12, c.4582-2_4582delAG, and p.Tyr1499Asp. These patient cell lines displayed DNA damage repair defects that were comparable to previously observed RNAi-mediated depletion of SETD1A. This suggested that these variants, including the p.Tyr1499Asp in the catalytic SET domain, behave as Loss-of-Function (LoF) alleles. Previous studies demonstrated a role for SETD1A in cell cycle control and differentiation. However, individuals with SETD1A variants do not show major structural brain defects or severe microcephaly, suggesting that defective proliferation and differentiation of neural progenitors is unlikely the single underlying cause of the disorder. We show here that the Drosophila Melanogaster SETD1A orthologue is required in postmitotic neurons of the fly brain for normal memory, suggesting a role in post development neuronal function. Together, this study defines a neurodevelopmental disorder caused by dominant de novo LoF variants in SETD1A and further supports a role for H3K4 methyltransferases in the regulation of neuronal processes underlying normal cognitive functioning.

Since the introduction of next‐generation sequencing, an increasing number of disorders have been discovered to have genetic etiology. To address diverse clinical questions and coordinate research activities that arise with the identification of these rare disorders, we developed the Human Disease Genes website series (HDG website series): an international digital library that records detailed information on the clinical phenotype of novel genetic variants in the human genome (https://humandiseasegenes.info/). Each gene website is moderated by a dedicated team of clinicians and researchers, focused on specific genes, and provides up‐to‐date—including unpublished—clinical information. The HDG website series is expanding rapidly with 424 genes currently adopted by 325 moderators from across the globe. On average, a gene website has detailed phenotypic information of 14.4 patients. There are multiple examples of added value, one being the ARID1B gene website, which was recently utilized in research to collect clinical information of 81 new patients. Additionally, several gene websites have more data available than currently published in the literature. In conclusion, the HDG website series provides an easily accessible, open and up‐to‐date clinical data resource for patients with pathogenic variants of individual genes. This is a valuable resource not only for clinicians dealing with rare genetic disorders such as developmental delay and autism, but other professionals working in diagnostics and basic research. Since the HDG website series is a dynamic platform, its data also include the phenotype of yet unpublished patients curated by professionals providing higher quality clinical detail to improve management of these rare disorders.

The Koolen-de Vries syndrome (KdVS) is a multisystem syndrome with variable facial features caused by a 17q21.31 microdeletion or KANSL1 truncating variant. As the facial gestalt of KdVS has resemblance with the gestalt of the 22q11.2 deletion syndrome (22q11.2DS), we assessed whether our previously described hybrid quantitative facial phenotyping algorithm could distinguish between these two syndromes, and whether there is a facial difference between the molecular KdVS subtypes. We applied our algorithm to 2D photographs of 97 patients with KdVS (78 microdeletions, 19 truncating variants (likely) causing KdVS) and 48 patients with 22q11.2DS as well as age, gender and ethnicity matched controls with intellectual disability (n = 145). The facial gestalts of KdVS and 22q11.2DS were both recognisable through significant clustering by the hybrid model, yet different from one another (p = 7.5 × 10 −10 and p = 0.0052, respectively). Furthermore, the facial gestalts of KdVS caused by a 17q21.31 microdeletion and KANSL1 truncating variant (likely) causing KdVS were indistinguishable (p = 0.981 and p = 0.130). Further application to three patients with a variant of unknown significance in KANSL1 showed that these faces do not match KdVS. Our data highlight quantitative facial phenotyping not only as a powerful tool to distinguish syndromes with overlapping facial dysmorphisms but also to establish pathogenicity of variants of unknown clinical significance.

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