Purpose Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. Methods Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. Results The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20–89% and the top 10 accuracy rate by more than 5–99% for the disease-causing gene. Conclusion Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis.

Children with monogenic neurodevelopmental disorders often grow abnormally. Gene-specific growth charts would be useful but require large samples to construct them using the conventional LMS method. We transformed anthropometry to British 1990 reference z-scores for 328 UK and 264 international individuals with ANKRD11, ARID1B, ASXL3, DDX3X, KMT2A , or SATB2- related disorders, and modelled mean and standard deviation (SD) of the z-scores as gene-specific linear age trends adjusted for sex. Assuming the same skewness in the reference and rare disease distributions, we then back-transformed the mean ±2 SD lines to give gene-specific median, 2nd, and 98th centiles. The resulting z-score charts look plausible on several counts. Only KMT2A shows a (rising) age trend in median height, while BMI and weight increase for several genes, possibly reflecting population trends. Apart from SATB2 and DDX3X , the gene-specific medians are all below the reference (range 0.1th centile for height KMT2A to 36th centile for BMI ANKRD11 ). Median OFC z-score shows no age trend, with medians ranging from 10th to 30th centile, and ASXL3 is lowest, on the 3rd centile. In 19/24 cases, the centiles for the two sexes are the same on the z-score scale. Our LMSz method produces gene-specific growth charts for rare diseases, which, when used in the correct context, could be an important clinical tool. We plan to automate it within the DECIPHER platform, enabling availability for relevant genes.

Introduction: Children with monogenic neurodevelopmental disorders often grow abnormally. Gene-specific growth charts would be useful but require large samples to construct them using the conventional LMS method. Methods: We transformed anthropometry to British 1990 reference z-scores for 328 UK and 264 international probands with ANKRD11, ARID1B, ASXL3, DDX3X, KMT2A or SATB2- related disorders, and modelled mean and standard deviation (SD) of the z-scores as gene-specific linear age trends adjusted for sex. Back-transforming the mean ±2 SD lines provided gene-specific median, 2 ^nd and 98 ^th centiles. Results: The resulting z-score charts look plausible on several counts. Only KMT2A shows a (rising) age trend in median height, while BMI and weight increase in several genes, possibly reflecting population trends. Apart from SATB2 and DDX3X, the gene-specific medians are all below the reference (range 0.1 ^th centile for height KMT2A to 36 ^th centile for BMI ANKRD11 ). Median OFC shows no age trend, with medians ranging from 10 ^th -30 ^th centile, and ASXL3 lowest, on the 3 ^rd centile. There are no sex differences in 19/24 cases. Conclusions: Our LMSz method produces gene-specific growth charts for rare diseases, an essential clinical tool for paediatric care. We plan to automate it within the DECIPHER platform, enabling availability for all relevant genes.

Dysregulation of the epigenetic machinery is associated with neurodevelopmental defects in humans. Kleefstra syndrome (KS) is a neurodevelopmental syndrome caused by heterozygous alterations in the gene EHMT1 that cause loss-of-function. EHTM1 and EHMT2 are highly similar histone methyltransferases that play relevant roles in development. Despite their similarity, individuals with alterations in EHMT2 have never been described. Here, we describe a pediatric patient with a KS-overlapping phenotype and a single base de novo substitution in EHMT2 that causes the amino acid change p.Ala1077Ser in the catalytic SET domain. This change causes a reduction in the affinity of the catalytic domain for the H3 tail and in the activity of the enzyme by three- to five-fold. DNA methylation, histone methylation and gene expression profiles suggest a significant overlap between the EHMT2 p.Ala1077Ser variant and KS. Based on this evidence we suggest that EHMT2 haploinsufficiency causes a Kleefstra-like syndrome. Although we cannot rule out dominant negative effects caused by the EHMT2 p.Ala1077Ser variant, our data and previously published data suggest that loss of EHMT2 function is probably more detrimental to cells than loss of EHMT1, explaining why individuals with alterations in EHMT2 are very rare.

EHMT1 and EHMT2 genes encode human euchromatin histone lysine methyltransferase 1 and 2 (EHMT1 alias GLP; EHMT2 alias G9a) that form heteromeric GLP/G9a complexes with essential roles in epigenetic regulation of gene expression. While EHMT1 haploinsufficiency has been established as the cause of Kleefstra syndrome 1, the pathogenesis of G9a dysfunction in human disease remains largely unknown. We identified seven de novo EHMT2 variants in patients with clinical presentation, episignatures, histone modifications and transcriptomic profiles similar to those of Kleefstra syndrome 1. In vitro studies reveal that these variants encode for structurally stable G9a proteins that are catalytically incompetent due to aberrant interactions either with histone H3 tail or with S-adenosylmethionine. Heterozygous mice carrying a patient-derived variant exhibit growth retardation, facial/skull dysmorphia and aberrant behavior. Here we report pathogenic EHMT2 variants that likely exert dominant-negative effect on GLP/G9a complexes and thus genocopy the EHMT1 haploinsufficiency via a distinct molecular mechanism, defining an autosomal dominant EHMT2 -related Kleefstra syndrome.

EHMT1 and EHMT2 genes encode human euchromatin histone lysine methyltransferase 1 and 2 (EHMT1 alias GLP; EHMT2 alias G9a) that form heteromeric GLP/G9a complexes with essential roles in epigenetic regulation of gene expression. While EHMT1 haploinsufficiency has been established as the cause of Kleefstra syndrome 1, the pathogenesis of G9a dysfunction in human disease remains largely unknown. We identified seven de novo EHMT2 variants in patients with clinical presentation, episignatures, histone modifications and transcriptomic profiles similar to those of Kleefstra syndrome 1. In vitro studies revealed that these variants encode for structurally stable G9a proteins that are catalytically incompetent due to aberrant interactions either with histone H3 tail or with S-adenosylmethionine. Heterozygous mice carrying a patient-derived variant exhibited growth retardation, facial/skull dysmorphia and aberrant behavior. Here we report pathogenic EHMT2 variants that likely exert dominant-negative effect on GLP/G9a complexes and thus genocopy the EHMT1 haploinsufficiency via a distinct molecular mechanism, defining an autosomal dominant EHMT2 -related Kleefstra syndrome.