European Journal of Human Genetics

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ISSN / EISSN : 1018-4813 / 1476-5438
Current Publisher: Springer Science and Business Media LLC (10.1038)
Former Publisher: S. Karger AG (10.1159)
Total articles ≅ 5,532
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Catriona L. K. Barnes, , David J. Porteous, Harry Campbell, ,
European Journal of Human Genetics pp 1-9; doi:10.1038/s41431-021-00914-w

Abstract:
Orkney and Shetland, the population isolates that make up the Northern Isles of Scotland, are of particular interest to multiple sclerosis (MS) research. While MS prevalence is high in Scotland, Orkney has the highest global prevalence, higher than more northerly Shetland. Many hypotheses for the excess of MS cases in Orkney have been investigated, including vitamin D deficiency and homozygosity: neither was found to cause the high prevalence of MS. It is possible that this excess prevalence may be explained through unique genetics. We used polygenic risk scores (PRS) to look at the contribution of common risk variants to MS. Analyses were conducted using ORCADES (97/2118 cases/controls), VIKING (15/2000 cases/controls) and Generation Scotland (30/8708 cases/controls) data sets. However, no evidence of a difference in MS-associated common variant frequencies was found between the three control populations, aside from HLA-DRB1*15:01 tag SNP rs9271069. This SNP had a significantly higher risk allele frequency in Orkney (0.23, p value = 8 × 10–13) and Shetland (0.21, p value = 2.3 × 10–6) than mainland Scotland (0.17). This difference in frequency is estimated to account for 6 (95% CI 3, 8) out of 150 observed excess cases per 100,000 individuals in Shetland and 9 (95% CI 8, 11) of the observed 257 excess cases per 100,000 individuals in Orkney, compared with mainland Scotland. Common variants therefore appear to account for little of the excess burden of MS in the Northern Isles of Scotland.
Ana Töpf, Solve-RD SNV-indel working group, Angela Pyle, Helen Griffin, Leslie Matalonga, , Albert Sickmann, Ulrike Schara–Schmidt, Andreas Hentschel, Patrick F. Chinnery, et al.
European Journal of Human Genetics; doi:10.1038/s41431-021-00851-8

Abstract:
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.
Birte Zurek, Solve-RD consortium, , , Rebecca Schüle, , Ana Töpf, , , Leslie Matalonga, et al.
European Journal of Human Genetics; doi:10.1038/s41431-021-00859-0

Abstract:
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.
Iris B. A. W. Te Paske, José Garcia-Pelaez, Anna K. Sommer, Leslie Matalonga, , , Rachel S. van der Post, Jan Lubinski, Carla Oliveira, , et al.
European Journal of Human Genetics; doi:10.1038/s41431-021-00853-6

Abstract:
Hereditary diffuse gastric cancer (HDGC) is associated with germline deleterious variants in CDH1 and CTNNA1. The majority of HDGC-suspected patients are still genetically unresolved, raising the need for identification of novel HDGC predisposing genes. Under the collaborative environment of the SOLVE-RD consortium, re-analysis of whole-exome sequencing data from unresolved gastric cancer cases (n = 83) identified a mosaic missense variant in PIK3CA in a 25-year-old female with diffuse gastric cancer (DGC) without familial history for cancer. The variant, c.3140A>G p.(His1047Arg), a known cancer-related somatic hotspot, was present at a low variant allele frequency (18%) in leukocyte-derived DNA. Somatic variants in PIK3CA are usually associated with overgrowth, a phenotype that was not observed in this patient. This report highlights mosaicism as a potential, and understudied, mechanism in the etiology of DGC.
Elke de Boer, Solve-RD SNV-indel working group, , Leslie Matalonga, , , , Mirian Janssen, Dylan Henssen, , et al.
European Journal of Human Genetics; doi:10.1038/s41431-021-00900-2

Abstract:
The genetic etiology of intellectual disability remains elusive in almost half of all affected individuals. Within the Solve-RD consortium, systematic re-analysis of whole exome sequencing (WES) data from unresolved cases with (syndromic) intellectual disability (n = 1,472 probands) was performed. This re-analysis included variant calling of mitochondrial DNA (mtDNA) variants, although mtDNA is not specifically targeted in WES. We identified a functionally relevant mtDNA variant in MT-TL1 (NC_012920.1:m.3291T > C; NC_012920.1:n.62T > C), at a heteroplasmy level of 22% in whole blood, in a 23-year-old male with severe intellectual disability, epilepsy, episodic headaches with emesis, spastic tetraparesis, brain abnormalities, and feeding difficulties. Targeted validation in blood and urine supported pathogenicity, with heteroplasmy levels of 23% and 58% in index, and 4% and 17% in mother, respectively. Interestingly, not all phenotypic features observed in the index have been previously linked to this MT-TL1 variant, suggesting either broadening of the m.3291T > C-associated phenotype, or presence of a co-occurring disorder. Hence, our case highlights the importance of underappreciated mtDNA variants identifiable from WES data, especially for cases with atypical mitochondrial phenotypes and their relatives in the maternal line.
Leslie Matalonga, Solve-RD SNV-indel working group, , Davide Piscia, Rebecca Schüle, , Ana Töpf, , , Raul Tonda, et al.
European Journal of Human Genetics; doi:10.1038/s41431-021-00852-7

Abstract:
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.
Correction
Holger Hengel, , Marc Sturm, Tobias B. Haack, Yvonne Schelling, Muhammad Mahajnah, Rajech Sharkia, Abdussalam Azem, Ghassan Balousha, Zaid Ghanem, et al.
European Journal of Human Genetics pp 1-1; doi:10.1038/s41431-021-00909-7

, Ronald van Beek, Ernie M. H. F. Bongers, Dorien Lugtenberg, Peter. H. M. Klaren, , Ronald Roepman,
European Journal of Human Genetics pp 1-13; doi:10.1038/s41431-021-00907-9

Abstract:
Skeletal ciliopathies are a group of disorders caused by dysfunction of the cilium, a small signaling organelle present on nearly every vertebrate cell. This group of disorders is marked by genetic and clinical heterogeneity, which complicates accurate diagnosis. In this study, we developed a robust, standardized immunofluorescence approach to accurately diagnose a subset of these disorders. Hereto we determined and compared the cilium phenotype of healthy individuals to patients from three different ciliopathy subgroups, using skin-derived fibroblasts. The cilium phenotype assay consists of three parameters; (1) ciliogenesis, based on the presence or absence of cilium markers, (2) cilium length, measured by the combined signal of an axonemal and a cilium membrane marker, and (3) retrograde intraflagellar transport (IFT), quantified by the area of the ciliary tip. Analysis of the cilium phenotypic data yielded comparable and reproducible results and in addition, displayed identifiable clusters for healthy individuals and two ciliopathy subgroups, i.e. ATD and CED. Our results illustrate that standardized analysis of the cilium phenotype can be used to discriminate between ciliopathy subgroups. Therefore, we believe that standardization of functional assays analyzing cilium phenotypic data can provide additional proof for conclusive diagnosis of ciliopathies, which is essential for routine diagnostic care.
, Shiva Ganesan, Peter D. Galer, Katherine L. Helbig, Sarah E. McKeown, Margaret O’Brien, Pouya Khankhanian, Michael C. Kaufman, Alexander K. Gonzalez, Alex S. Felmeister, et al.
Published: 24 May 2021
European Journal of Human Genetics pp 1-11; doi:10.1038/s41431-021-00908-8

Abstract:
While genetic studies of epilepsies can be performed in thousands of individuals, phenotyping remains a manual, non-scalable task. A particular challenge is capturing the evolution of complex phenotypes with age. Here, we present a novel approach, applying phenotypic similarity analysis to a total of 3251 patient-years of longitudinal electronic medical record data from a previously reported cohort of 658 individuals with genetic epilepsies. After mapping clinical data to the Human Phenotype Ontology, we determined the phenotypic similarity of individuals sharing each genetic etiology within each 3-month age interval from birth up to a maximum age of 25 years. 140 of 600 (23%) of all 27 genes and 3-month age intervals with sufficient data for calculation of phenotypic similarity were significantly higher than expect by chance. 11 of 27 genetic etiologies had significant overall phenotypic similarity trajectories. These do not simply reflect strong statistical associations with single phenotypic features but appear to emerge from complex clinical constellations of features that may not be strongly associated individually. As an attempt to reconstruct the cognitive framework of syndrome recognition in clinical practice, longitudinal phenotypic similarity analysis extends the traditional phenotyping approach by utilizing data from electronic medical records at a scale that is far beyond the capabilities of manual phenotyping. Delineation of how the phenotypic homogeneity of genetic epilepsies varies with age could improve the phenotypic classification of these disorders, the accuracy of prognostic counseling, and by providing historical control data, the design and interpretation of precision clinical trials in rare diseases.
, Magdaléna von Jagwitz-Biegnitz, Ronny Baber, , Edgar Dahl, , Jörg Fuchs, Maike K. Groenewold, Mara Lena Hartung, Michael Hummel, et al.
Published: 24 May 2021
European Journal of Human Genetics pp 1-11; doi:10.1038/s41431-021-00905-x

Abstract:
Biobanks are important infrastructures facilitating biomedical research. After a decade of rolling out such infrastructures, a shift in attention to the sustainability of biobanks could be observed in recent years. In this regard, an increase in the as yet relatively low utilisation rates of biobanks has been formulated as a goal. Higher utilisation rates can only be achieved if the perspectives of potential users of biobanks—particularly researchers not yet collaborating with biobanks—are adequately considered. To better understand their perspectives, a survey was conducted at ten different research institutions in Germany hosting a centralised biobank. The survey targeted potential users of biobank services, i.e. researchers working with biosamples. It addressed the general demand for biosamples, strategies for biosample acquisition/storage and reasons for/against collaborating with biobanks. In total, 354 researchers filled out the survey. Most interestingly, only a minority of researchers (12%) acquired their biosamples via biobanks. Of the respondents not collaborating with biobanks on sample acquisition, around half were not aware of the (services of the) respective local biobank. Those who actively decided against acquiring biosamples via a biobank provided different reasons. Most commonly, respondents stated that the biosamples required were not available, the costs were too high and information about the available biosamples was not readily accessible. Biobanks can draw many lessons from the results of the survey. Particularly, external communication and outreach should be improved. Additionally, biobanks might have to reassess whether their particular collection strategies are adequately aligned with local researchers’ needs.
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