For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient’s data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe.

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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.

This study, performed in the largest cohort of patients screened so far for LHX4 mutations, describes 6 disease-causing mutations that are responsible for congenital hypopituitarism. LHX4 mutations were found to be associated with variable expressivity, and most of them with incomplete penetrance; their contribution to pituitary deficits that are associated with an ectopic posterior pituitary and/or a sella turcica defect is ∼1.4% in the 417 probands tested.

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Isolated growth hormone deficiency (IGHD) is a rare condition mainly caused by mutations in GH1. The aim of this study was to assess the contribution of GHRHR mutations to IGHD in an unusually large group of patients. All GHRHR coding exons and flanking intronic regions were sequenced in 312 unrelated patients with nonsyndromic IGHD. Functional consequences of all newly identified missense variants were assessed in vitro (i.e., study of the expression of recombinant GHRHRs and their ability to activate the cyclic adenosine monophosphate (cAMP) signaling pathway). Genotype‐phenotype correlation analyses were performed according to the nature of the identified mutation. We identified 20 different disease‐causing GHRHR mutations (truncating and missense loss‐of‐function mutations), among which 15 are novel, in 24 unrelated patients. Of note, about half (13/24) of those patients represent sporadic cases. The clinical phenotype of patients with at least one missense GHRHR mutation was found to be indistinguishable from that of patients with bi‐allelic truncating mutations. This study, which unveils disease‐causing GHRHR mutations in 8% (24/312) of IGHD cases, identifies GHRHR as the second IGHD gene most frequently involved after GH1. The finding that 8% of IGHD cases without GH1 mutations are explained by GHRHR molecular defects (including missense mutations), together with the high proportion of sporadic cases among those patients, has important implications for genetic counseling.

TRIP4 is one of the subunits of the transcriptional coregulator ASC-1, a ribonucleoprotein complex that participates in transcriptional coactivation and RNA processing events. Recessive variants in the TRIP4 gene have been associated with spinal muscular atrophy with bone fractures as well as a severe form of congenital muscular dystrophy. Here we present the diagnostic journey of a patient with cerebellar hypoplasia and spinal muscular atrophy (PCH1) and congenital bone fractures. Initial exome sequencing analysis revealed no candidate variants. Reanalysis of the exome data by inclusion in the Solve-RD project resulted in the identification of a homozygous stop-gain variant in the TRIP4 gene, previously reported as disease-causing. This highlights the importance of analysis reiteration and improved and updated bioinformatic pipelines. Proteomic profile of the patient’s fibroblasts showed altered RNA-processing and impaired exosome activity supporting the pathogenicity of the detected variant. In addition, we identified a novel genetic form of PCH1, further strengthening the link of this characteristic phenotype with altered RNA metabolism.