Human disease genes website series: An international, open and dynamic library for up‐to‐date clinical information

Abstract

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by a dedicated team of clinicians and researchers, focused on specific genes, and provides up‐to‐date—including unpublished—clinical information.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 Since the HDG website series is a dynamic platform, its data also include the phenotype of yet unpublished patients curated by professionals providing higher quality clinical detail to improve management of these rare disorders.

Establishing the phenotypic spectrum of ZTTK syndrome by analysis of 52 individuals with variants in SON

“…For the novel cases, clinicians were asked to supply clinical and genomic data. To create an accessible and adaptable overview, all phenotypic data were collected in Human Phenotype Ontology (HPO) [21] terms, and subsequently entered in the SON page of the "Human Disease Genes (HDG)" website series [22] allowing the display of graphic representations of the clinical data. The frequency of each abnormality was determined to get a complete overview of the phenotypic spectrum.…”

KBG Syndrome: Prospective Videoconferencing and Use of AI-driven Facial Phenotyping in 25 New Patients

“…asking structured questions and visually assessing for facial and limb phenotypic characteristics. Every anomaly reported by these participants were compiled as standardized Human Phenotype Ontology (HPO) terms onto the open-source Human Disease Genes website series (HDG) [8]. The HDG is a research initiative that started at the Department of Human Genetics of the Radboud University Medical Center in Nijmegen, Netherlands, with the goal of collecting and providing clinical consequences of novel variants in the human genome on an international scale.…”

“…The copyright holder for this this version posted November 23, 2021. ; https://doi.org/10.1101/2021.11. 18.21266480 doi: medRxiv preprint series (HDG) [8]. The HDG is a research initiative that started at the Department of Human Genetics of the Radboud University Medical Center in Nijmegen, Netherlands, with the goal of collecting and providing clinical consequences of novel variants in the human genome on an international scale.…”

“…The increased use and security of videoconferencing technology allowed access to participants in parts of the world outside of the United States, broadening the generalizability of our results. Given limited data and awareness for rare disorders, sharing data in a public domain such as the HDG website [8] which is accessible to families, researchers and health care providers, can further facilitate the development and refining of tools for health care providers to screen for rare disorders. A protocol that enables data sharing will also benefit AI software such as DeepGestalt, which requires thousands of patient images to model a vast range of genetic disorders and accurately train deep convolutional neural networks.…”

Intellectual disability genomics: current state, pitfalls and future challenges

“…Nevertheless, assembly patients that comply to these characteristics is problematic, particularly in rare ID syndromes. To overcome this bottleneck several open-access online platforms allow data sharing: GeneMatcher ( https://genematcher.org ) [ 132 , 133 ], Human Disease Genes website series ( http://humandiseasegenes.info ) [ 134 ], PhenomeCentral ( https://www.phenomecentral.org ) [ 135 ], Leiden Open Variation Database (LOVD, https://www.lovd.nl ) [ 136 ], Clinvar ( https://www.ncbi.nlm.nih.gov/clinvar ) [ 117 ], and Solve-RD - solving the unsolved rare diseases ( https://solve-rd.eu ) [ 137 ], among others. …”