The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases.

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes.

The European Genome-phenome Archive in 2021.

The European Genome-phenome Archive (EGA - https://ega-archive.org/) is a resource for long term secure archiving of all types of potentially identifiable genetic, phenotypic, and clinical data resulting from biomedical research projects. Its mission is to foster hosted data reuse, enable reproducibility, and accelerate biomedical and translational research in line with the FAIR principles. Launched in 2008, the EGA has grown quickly, currently archiving over 4,500 studies from nearly one thousand institutions. The EGA operates a distributed data access model in which requests are made to the data controller, not to the EGA, therefore, the submitter keeps control on who has access to the data and under which conditions. Given the size and value of data hosted, the EGA is constantly improving its value chain, that is, how the EGA can contribute to enhancing the value of human health data by facilitating its submission, discovery, access, and distribution, as well as leading the design and implementation of standards and methods necessary to deliver the value chain. The EGA has become a key GA4GH Driver Project, leading multiple development efforts and implementing new standards and tools, and has been appointed as an ELIXIR Core Data Resource.

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics.

Probe-based quantitative PCR assay for detecting constitutional and somatic deletions in the NF1 gene: application to genetic testing and tumor analysis.

BACKGROUND: About 5% of patients with neurofibromatosis type 1 (NF1) bear constitutional microdeletions that encompass NF1 (neurofibromin 1) and neighboring genes. These patients are characterized by the development of a high number of dermal neurofibromas (dNFs), mental retardation, and an increased risk of developing a malignant peripheral nerve sheath tumor (MPNST). Additionally, 10% of somatic second hits identified in dNFs are caused by deletions involving the NF1 gene. To detect constitutional and somatic deletions, we developed a probe-based quantitative PCR (qPCR) assay for interrogating the copy number status of 11 loci distributed along a 2.8-Mb region around the NF1 gene. METHODS: We developed the qPCR assay with Universal ProbeLibrary technology (Roche) and designed a Microsoft Excel spreadsheet to analyze qPCR data for copy number calculations. The assay fulfilled the essential aspects of the MIQE (minimum information for publication of quantitative real-time PCR experiments) guidelines and used the qBase relative quantification framework for calculations. RESULTS: The assay was validated with a set of DNA samples with known constitutional or somatic NF1 deletions. The assay showed high diagnostic sensitivity and specificity and distinguished between Type-1, Type-2, and atypical constitutional microdeletions in 14 different samples. It also identified 16 different somatic deletions in dNFs. These results were confirmed by multiplex ligation-dependent probe amplification. CONCLUSIONS: The qPCR assay provides a methodology for detecting constitutional NF1 microdeletions that could be incorporated as an additional technique in a genetic-testing setting. It also permits the identification of somatic NF1 deletions in tissues with a high percentage of cells bearing 2 copies of the NF1 gene.

Applying microsatellite multiplex PCR analysis (MMPA) for determining allele copy-number status and percentage of normal cells within tumors.

The study of somatic genetic alterations in tumors contributes to the understanding and management of cancer. Genetic alterations, such us copy number or copy neutral changes, generate allelic imbalances (AIs) that can be determined using polymorphic markers. Here we report the development of a simple set of calculations for analyzing microsatellite multiplex PCR data from control-tumor pairs that allows us to obtain accurate information not only regarding the AI status of tumors, but also the percentage of tumor-infiltrating normal cells, the locus copy-number status and the mechanism involved in AI. We validated this new approach by re-analyzing a set of Neurofibromatosis type 1-associated dermal neurofibromas and comparing newly generated data with results obtained for the same tumors in a previous study using MLPA, Paralog Ratio Analysis and SNP-array techniques.Microsatellite multiplex PCR analysis (MMPA) should be particularly useful for analyzing specific regions of the genome containing tumor suppressor genes and also for determining the percentage of infiltrating normal cells within tumors allowing them to be sorted before they are analyzed by more expensive techniques.

Mosaic type-1 NF1 microdeletions as a cause of both generalized and segmental neurofibromatosis type-1 (NF1).

Mosaicism is an important feature of type-1 neurofibromatosis (NF1) on account of its impact upon both clinical manifestations and transmission risk. Using FISH and MLPA to screen 3500 NF1 patients, we identified 146 individuals harboring gross NF1 deletions, 14 of whom (9.6%) displayed somatic mosaicism. The high rate of mosaicism in patients with NF1 deletions supports the postulated idea of a direct relationship between the high new mutation rate in this cancer predisposition syndrome and the frequency of mosaicism. Seven of the 14 mosaic NF1 deletions were type-2, whereas four were putatively type-1, and three were atypical. Two of the four probable type-1 deletions were confirmed as such by breakpoint-spanning PCR or SNP analysis. Both deletions were associated with a generalized manifestation of NF1. Independently, we identified a third patient with a mosaic type-1 NF1 deletion who exhibited segmental NF1. Together, these three cases constitute the first proven mosaic type-1 deletions so far reported. In two of these three mosaic type-1 deletions, the breakpoints were located within PRS1 and PRS2, previously identified as hotspots for nonallelic homologous recombination (NAHR) during meiosis. Hence, NAHR within PRS1 and PRS2 is not confined to meiosis but may also occur during postzygotic mitotic cell cycles.

Dissecting loss of heterozygosity (LOH) in neurofibromatosis type 1-associated neurofibromas: Importance of copy neutral LOH.

Dermal neurofibromas (dNFs) are benign tumors of the peripheral nervous system typically associated with Neurofibromatosis type 1 (NF1) patients. Genes controlling the integrity of the DNA are likely to influence the number of neurofibromas developed because dNFs are caused by somatic mutational inactivation of the NF1 gene, frequently evidenced by loss of heterozygosity (LOH). We performed a comprehensive analysis of the prevalence and mechanisms of LOH in dNFs. Our study included 518 dNFs from 113 patients. LOH was detected in 25% of the dNFs (N = 129). The most frequent mechanism causing LOH was mitotic recombination, which was observed in 62% of LOH-tumors (N = 80), and which does not reduce the number of NF1 gene copies. All events were generated by a single crossover located between the centromere and the NF1 gene, resulting in isodisomy of 17q. LOH due to the loss of the NF1 gene accounted for a 38% of dNFs with LOH (N = 49), with deletions ranging in size from ∼80 kb to ∼8 Mb within 17q. In one tumor we identified the first example of a neurofibroma-associated second-hit type-2 NF1 deletion. Analysis of the prevalence of mechanisms causing LOH in dNFs in individual patients (possibly under genetic control) will elucidate whether there exist interindividual variation.