Combining targeted panel-based resequencing and copy-number variation analysis for the diagnosis of inherited syndromic retinopathies and associated ciliopathies

Inherited syndromic retinopathies are a highly heterogeneous group of diseases that involve retinal anomalies and systemic manifestations. They include retinal ciliopathies, other well-defined clinical syndromes presenting with retinal alterations and cases of non-specific multisystemic diseases. The heterogeneity of these conditions makes molecular and clinical characterization of patients challenging in daily clinical practice. We explored the capacity of targeted resequencing and copy-number variation analysis to improve diagnosis of a heterogeneous cohort of 47 patients mainly comprising atypical cases that did not clearly fit a specific clinical diagnosis. Thirty-three likely pathogenic variants were identified in 18 genes (ABCC6, ALMS1, BBS1, BBS2, BBS12, CEP41, CEP290, IFT172, IFT27, MKKS, MYO7A, OTX2, PDZD7, PEX1, RPGRIP1, USH2A, VPS13B, and WDPCP). Molecular findings and additional clinical reassessments made it possible to accurately characterize 14 probands (30% of the total). Notably, clinical refinement of complex phenotypes was achieved in 4 cases, including 2 de novo OTX2-related syndromes, a novel phenotypic association for the ciliary CEP41 gene, and the co-existence of biallelic USH2A variants and a Koolen-de-Vries syndrome–related 17q21.31 microdeletion. We demonstrate that combining next-generation sequencing and CNV analysis is a comprehensive and useful approach to unravel the extensive phenotypic and genotypic complexity of inherited syndromic retinopathiesFEDER (Fondo Europeo de Desarrollo Regional) | Ref. PI016/00425Instituto de Salud Carlos III | Ref. PT13/0010/001

Genetic landscape of 6089 inherited retinal dystrophies affected cases in Spain and their therapeutic and extended epidemiological implications

ESRETNET Study Group, The ERDC Study Group, The Associated Clinical Study Group.Inherited retinal diseases (IRDs), defined by dysfunction or progressive loss of photoreceptors, are disorders characterized by elevated heterogeneity, both at the clinical and genetic levels. Our main goal was to address the genetic landscape of IRD in the largest cohort of Spanish patients reported to date. A retrospective hospital-based cross-sectional study was carried out on 6089 IRD affected individuals (from 4403 unrelated families), referred for genetic testing from all the Spanish autonomous communities. Clinical, demographic and familiar data were collected from each patient, including family pedigree, age of appearance of visual symptoms, presence of any systemic findings and geographical origin. Genetic studies were performed to the 3951 families with available DNA using different molecular techniques. Overall, 53.2% (2100/3951) of the studied families were genetically characterized, and 1549 different likely causative variants in 142 genes were identified. The most common phenotype encountered is retinitis pigmentosa (RP) (55.6% of families, 2447/4403). The most recurrently mutated genes were PRPH2, ABCA4 and RS1 in autosomal dominant (AD), autosomal recessive (AR) and X-linked (XL) NON-RP cases, respectively; RHO, USH2A and RPGR in AD, AR and XL for non-syndromic RP; and USH2A and MYO7A in syndromic IRD. Pathogenic variants c.3386G > T (p.Arg1129Leu) in ABCA4 and c.2276G > T (p.Cys759Phe) in USH2A were the most frequent variants identified. Our study provides the general landscape for IRD in Spain, reporting the largest cohort ever presented. Our results have important implications for genetic diagnosis, counselling and new therapeutic strategies to both the Spanish population and other related populations.This work was supported by the Instituto de Salud Carlos III (ISCIII) of the Spanish Ministry of Health (FIS; PI16/00425 and PI19/00321), Centro de Investigación Biomédica en Red Enfermedades Raras (CIBERER, 06/07/0036), IIS-FJD BioBank (PT13/0010/0012), Comunidad de Madrid (CAM, RAREGenomics Project, B2017/BMD-3721), European Regional Development Fund (FEDER), the Organización Nacional de Ciegos Españoles (ONCE), Fundación Ramón Areces, Fundación Conchita Rábago and the University Chair UAM-IIS-FJD of Genomic Medicine. Irene Perea-Romero is supported by a PhD fellowship from the predoctoral Program from ISCIII (FI17/00192). Ionut F. Iancu is supported by a grant from the Comunidad de Madrid (CAM, PEJ-2017-AI/BMD7256). Marta del Pozo-Valero is supported by a PhD grant from the Fundación Conchita Rábago. Berta Almoguera is supported by a Juan Rodes program from ISCIII (JR17/00020). Pablo Minguez is supported by a Miguel Servet program from ISCIII (CP16/00116). Marta Corton is supported by a Miguel Servet program from ISCIII (CPII17/00006)

SpadaHC: a database to improve the classification of variants in hereditary cancer genes in the Spanish population

Accurate classification of genetic variants is crucial for clinical decision-making in hereditary cancer. In Spain, genetic diagnostic laboratories have traditionally approached this task independently due to the lack of a dedicated resource. Here we present SpadaHC, a web-based database for sharing variants in hereditary cancer genes in the Spanish population. SpadaHC is implemented using a three-tier architecture consisting of a relational database, a web tool and a bioinformatics pipeline. Contributing laboratories can share variant classifications and variants from individuals in Variant Calling Format (VCF) format. The platform supports open and restricted access, flexible dataset submissions, automatic pseudo-anonymization, VCF quality control, variant normalization and liftover between genome builds. Users can flexibly explore and search data, receive automatic discrepancy notifications and access SpadaHC population frequencies based on many criteria. In February 2024, SpadaHC included 18 laboratory members, storing 1.17 million variants from 4306 patients and 16 343 laboratory classifications. In the first analysis of the shared data, we identified 84 genetic variants with clinically relevant discrepancies in their classifications and addressed them through a three-phase resolution strategy. This work highlights the importance of data sharing to promote consistency in variant classifications among laboratories, so patients and family members can benefit from more accurate clinical management.Database URL: https://spadahc.ciberisciii.es/ Overview of SpadaHC and its main views. (A) List of existing variants in SpadaHC (in the image, search for the ATM gene). The 'Expert Cl.' column shows the classification made by a group of experts; the 'Lab Cl.' column shows a summary of the classifications made by the laboratories. (B) Allele frequency of a variant in the SpadaHC population according to clinical suspicion and sex. (C) Classifications provided by the laboratories for a variant. (D) List of patients carrying a variant. (E) Histogram showing the coverage and frequency (allele balance) with which the variant was detected in carrier patients. Alt text: SpadaHC overview; laboratories can share datasets of variant classifications (Excel) and variants from individuals (VCFs + Excel). The datasets undergo quality control, bioinformatics pipeline annotation and database integration before being displayed in SpadaHC. The graphical abstract also shows five views of SpadaHC

CIBERER : Spanish national network for research on rare diseases: A highly productive collaborative initiative

Altres ajuts: Instituto de Salud Carlos III (ISCIII); Ministerio de Ciencia e Innovación.CIBER (Center for Biomedical Network Research; Centro de Investigación Biomédica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on rare diseases (RDs) currently consists of 75 research groups belonging to universities, research centers, and hospitals of the entire country. CIBERER's mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical, and cellular research of RDs. This research is the basis for providing new tools for the diagnosis and therapy of low-prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this article, we intend to review CIBERER's 15-year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions toward the discovery of new therapies and novel genes associated to diseases, cooperation with patients' associations and many other topics related to RD research

Fetal Genotyping in Maternal Blood by Digital PCR: Towards NIPD of Monogenic Disorders Independently of Parental Origin

<div><p>Purpose</p><p>To date, non-invasive prenatal diagnosis (NIPD) of monogenic disorders has been limited to cases with a paternal origin. This work shows a validation study of the Droplet Digital PCR (ddPCR) technology for analysis of both paternally and maternally inherited fetal alleles. For the purpose, single nucleotide polymorphisms (SNPs) were studied with the only intention to mimic monogenic disorders.</p><p>Methods</p><p>NIPD SNP genotyping was performed by ddPCR in 55 maternal plasma samples. In 19 out of 55 cases, inheritance of the paternal allele was determined by presence/absence criteria. In the remaining 36, determination of the maternally inherited fetal allele was performed by relative mutation dosage (RMD) analysis.</p><p>Results</p><p>ddPCR exhibited 100% accuracy for detection of paternal alleles. For diagnosis of fetal alleles with maternal origin by RMD analysis, the technology showed an accuracy of 96%. Twenty-nine out of 36 were correctly diagnosed. There was one FP and six maternal plasma samples that could not be diagnosed.</p><p>Discussion</p><p>In this study, ddPCR has shown to be capable to detect both paternal and maternal fetal alleles in maternal plasma. This represents a step forward towards the introduction of NIPD for all pregnancies independently of the parental origin of the disease.</p></div

Results of Z-Score values.

<p>This figure shows the results of Z-Score values calculated in all thirty-six cases considered for Relative Mutation Dosage (RMD) to establish the fetal genotyping in maternal plasma samples. Balance and Imbalance allelic ratio was used to ascertain the fetal genotype. Blue circle = Homozygous fetus for Allele 2 (2>1); Blue triangle = Heterozygous Allele 1/ Allele 2 fetus (2 = 1); Blue square = Homozygous fetus for Allele 1 (1>2)and Red square = False Positive.</p

Schematic representation of the study design based on a SNP study showing: parental genotypes, the data analysis approach in maternal plasma and the inheritance pattern mimicked.

<p>Parental genotyping combination for allele 1/allele 2 of a certain SNP can be used to represent an inheritance pattern for a point mutation. The different parental genotype combinations and their correspondence with a specific inheritance pattern are detailed in the figure. Analysis of exclusive paternal sequences requires a detection approach while the study of maternal genomic regions requires a Relative Mutation Dosage (RMD) analysis. A simulation of an NIPD for a dominant disease with paternal origin can be done using a case in which the mother is homozygous for an SNP and the father is heterozygous (blue background). Presence/absence of the exclusive paternal allele could be associated with a fetal genotype. On the contrary, a heterozygous mother and a homozygous father will mimic a dominant disorder with a maternal origin (red background). This simulation can be also considered for recessive diseases in which both parents are carriers of a different mutation. NIPD for a recessive disease in which both parents are carriers of the same mutation can be simulated by taking as an example a couple in which the mother and the father are heterozygous for an SNP (yellow background). Finally, the simulation of NIPD for X-linked disorders can be done by a case in which mother is heterozygous for a SNP and the father is hemizygous (green background).</p

Clinical interpretation algorithm where Allele 1 (1) represents the maternal healthy allele and Allele 2 (2) represents the maternal mutated allele.

<p>Clinical interpretation algorithm where Allele 1 (1) represents the maternal healthy allele and Allele 2 (2) represents the maternal mutated allele.</p

Primer and probe sequences and ddPCR conditions.

<p>This figure also includes optimal Temperature of Annealing (Ta) for each Taqman assay for the multiplex <i>SRY/GAPDH</i> and <i>RASSSF1A/GAPDH</i> assays.</p