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An expanding range of genetic syndromes are characterized by genome-wide disruptions in DNA methylation profiles referred to as episignatures. Episignatures are distinct, highly sensitive and specific biomarkers that have recently been applied in clinical diagnosis of genetic syndromes. Episignatures are contained within the broader disorder-specific genome-wide DNA methylation changes which can share significant overlap amongst different conditions. In this study we performed functional genomic assessment and comparison of disorder-specific and overlapping genome-wide DNA methylation changes related to 65 genetic syndromes with previously described episignatures. We demonstrate evidence of disorder-specific and recurring genome-wide differentially methylated probes (DMPs) and regions (DMRs). The overall distribution of DMPs and DMRs across the majority of the neurodevelopmental genetic syndromes analyzed showed substantial enrichment in gene promoters and CpG islands, and under-representation of the more variable intergenic regions. Analysis showed significant enrichment of the DMPs and DMRs in gene pathways and processes related to neurodevelopment, including neurogenesis, synaptic signaling and synaptic transmission. This study expands beyond the diagnostic utility of DNA methylation episignatures by demonstrating correlation between the function of the mutated genes and the consequent genomic DNA methylation profiles as a key functional element in the molecular etiology of genetic neurodevelopmental disorders. This article is protected by copyright. All rights reserved.

The Matchmaker Exchange (MME) launched in 2015 to provide a robust mechanism to discover novel disease-gene relationships. This federated network connects databases holding relevant data, where two or more users are looking for a match for the same gene (two-sided matchmaking). The number of unique genes present across MME has steadily increased; there are currently >13,520 unique genes (~68% of all protein coding genes) connected across MME’s nodes, GeneMatcher, DECIPHER, PhenomeCentral, MyGene2, seqr, Initiative on Rare and Undiagnosed Disease, PatientMatcher, and the RD-Connect Genome-Phenome Analysis Platform. The dataset accessible across MME includes more than 120,000 cases from over 12,000 contributors in 98 countries. Discovery of potential new disease-gene relationships occurs daily and international collaborations are moving these connections forward to publication. Expansion of data sharing into routine clinical practice has ensured access to discovery for even more individuals with undiagnosed rare genetic disease. MME supports connections to the literature (PubCaseFinder) and to human and model organism resources (Monarch Initiative) and scientists (ModelMatcher). Efforts are underway to explore additional approaches to matchmaking where there is only one querier (one-sided matchmaking). Genomic matchmaking has proven its utility over the past 7 years and will continue to facilitate discoveries in years to come.

Purpose: Matchmaking has emerged as a useful strategy for building evidence toward causality of novel disease genes in patients with undiagnosed rare diseases. The Matchmaker Exchange (MME) is a collaborative initiative that facilitates international data sharing for matchmaking purposes; however, data on user experience is limited. Methods: Patients enrolled as part of the Finding of Rare Disease Genes in Canada (FORGE) and Care4Rare Canada research programs had their exome sequencing data reanalyzed by a multidisciplinary research team over a 2-year period. Compelling variants in genes not previously associated with a human phenotype were submitted through the MME node PhenomeCentral, and outcomes were collected. Results: In this study, 194 novel candidate genes were submitted to the MME, resulting in 1514 matches, and 15% of the genes submitted resulted in collaborations. Most submissions resulted in at least 1 match, and most matches were with GeneMatcher (82%), where additional email exchange was required to evaluate the match because of the lack of phenotypic or inheritance information. Conclusion: Matchmaking through the MME is an effective way to investigate novel candidate genes; however, it is a labor-intensive process. Engagement from the community to contribute phenotypic, genotypic, and inheritance data will ensure that matchmaking continues to be a useful approach in the future.

Kym Boycott is currently a Clinical Geneticist at the Children's Hospital of Eastern Ontario (CHEO) and a Senior Scientist at the CHEO Research Institute, in Canada, where she tries to better understand mechanisms of rare genetic diseases and improve the management of pediatric patients with these conditions. Her interest in Medical Genetics dates back to her undergraduate studies at Queen's University in Kingston, when she was captured by Dr Patrick MacLeod's lectures on this subject. Thus, she embarked on a PhD in Medical Genetics and joined Dr Torben Bech-Hansen's lab at the University of Calgary, where she investigated the cause of a rare genetic form of vision loss. After completion of her PhD, she attended the medical school program at the University of Calgary and obtained her MD in 2005. Having both a PhD and MD allowed her to have a translational perspective from the beginning of her career. At CHEO, Kym and her group aim to bridge basic and clinical knowledge to quickly diagnose – by using next-generation sequencing – and improve the management of rare diseases, also known as orphan diseases. Kym is co-leader of the Canadian Rare Diseases Models and Mechanisms (RDMM) project, the goal of which is to connect basic scientists who work with animal models to clinician investigators studying rare diseases, thereby catalyzing investigation of disease mechanism and in some instances facilitating therapeutic configuration for rare diseases. In this interview, Kym shares with us her unique experience and expertise, fighting on the front line against rare diseases.

PurposeThe purpose of this study was to develop a national program for Canadian diagnostic laboratories to compare DNA-variant interpretations and resolve discordant-variant classifications using the BRCA1 and BRCA2 genes as a case study.MethodsBRCA1 and BRCA2 variant data were uploaded and shared through the Canadian Open Genetics Repository (COGR; http://www.opengenetics.ca). A total of 5,554 variant observations were submitted; classification differences were identified and comparison reports were sent to participating laboratories. Each site had the opportunity to reclassify variants. The data were analyzed before and after the comparison report process to track concordant- or discordant-variant classifications by three different models.ResultsVariant-discordance rates varied by classification model: 38.9% of variants were discordant when using a five-tier model, 26.7% with a three-tier model, and 5.0% with a two-tier model. After the comparison report process, the proportion of discordant variants dropped to 30.7% with the five-tier model, to 14.2% with the three-tier model, and to 0.9% using the two-tier model.ConclusionWe present a Canadian interinstitutional quality improvement program for DNA-variant interpretations. Sharing of variant knowledge by clinical diagnostic laboratories will allow clinicians and patients to make more informed decisions and lead to better patient outcomes.

A 14-year-old male presented with a T4 sigmoid adenocarcinoma,10 colonic adenomas and multiple café-au-lait macules. Family history was not suggestive of a dominant hereditary form of colorectal cancer. Evaluation of the tumor revealed abnormal immunohistochemical staining of the PMS2 protein and high frequency microsatellite instability. Germline analysis identified biallelic PMS2 missense mutations. A new cancer syndrome caused by biallelic mutations in the mismatch repair genes, including PMS2, is now emerging and is characterized by café-au-lait macules, colonic polyps and a distinctive tumor spectrum.