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Translational Diagnostics

An In-House Pipeline to Validate Genetic Variants in Children with Undiagnosed and Rare Diseases
  • Jordi Pijuan
    Affiliations
    Laboratory of Neurogenetics and Molecular Medicine–Pediatric Institute of Rare Diseases, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
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  • María Rodríguez-Sanz
    Affiliations
    Laboratory of Neurogenetics and Molecular Medicine–Pediatric Institute of Rare Diseases, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
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  • Daniel Natera-de Benito
    Affiliations
    Neuromuscular Unit, Department of Pediatric Neurology, Hospital Sant Joan de Déu, Barcelona, Spain
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  • Carlos Ortez
    Affiliations
    Neuromuscular Unit, Department of Pediatric Neurology, Hospital Sant Joan de Déu, Barcelona, Spain

    Centro de Investigación Biomédica en Red de Enfermedades Raras, Barcelona, Spain
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  • Arola Altimir
    Affiliations
    Laboratory of Neurogenetics and Molecular Medicine–Pediatric Institute of Rare Diseases, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
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  • Mireia Osuna-López
    Affiliations
    Laboratory of Neurogenetics and Molecular Medicine–Pediatric Institute of Rare Diseases, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
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  • Montserrat Roura
    Affiliations
    Laboratory of Neurogenetics and Molecular Medicine–Pediatric Institute of Rare Diseases, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
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  • Maddi Ugalde
    Affiliations
    Laboratory of Neurogenetics and Molecular Medicine–Pediatric Institute of Rare Diseases, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
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  • Liedewei Van de Vondel
    Affiliations
    Laboratory of Neurogenetics and Molecular Medicine–Pediatric Institute of Rare Diseases, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
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  • Judith Reina-Castillón
    Affiliations
    Laboratory of Neurogenetics and Molecular Medicine–Pediatric Institute of Rare Diseases, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
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  • Carme Fons
    Affiliations
    Centro de Investigación Biomédica en Red de Enfermedades Raras, Barcelona, Spain

    Department of Pediatric Neurology, Hospital Sant Joan de Déu, Barcelona, Spain
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  • Raúl Benítez
    Affiliations
    Automatic Control Department and Biomedical Engineering Research Center, Universitat Politècnica de Catalunya, Barcelona, Spain
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  • Andrés Nascimento
    Affiliations
    Neuromuscular Unit, Department of Pediatric Neurology, Hospital Sant Joan de Déu, Barcelona, Spain

    Centro de Investigación Biomédica en Red de Enfermedades Raras, Barcelona, Spain
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  • Janet Hoenicka
    Correspondence
    Janet Hoenicka, Ph.D., Laboratory of Neurogenetics and Molecular Medicine, Institut de Recerca Sant Joan de Déu, C/ Santa Rosa 39-57, 08950, Esplugues de Llobregat, Barcelona, Spain.
    Affiliations
    Laboratory of Neurogenetics and Molecular Medicine–Pediatric Institute of Rare Diseases, Institut de Recerca Sant Joan de Déu, Barcelona, Spain

    Centro de Investigación Biomédica en Red de Enfermedades Raras, Barcelona, Spain
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  • Francesc Palau
    Correspondence
    Address reprint requests to Francesc Palau, M.D., Ph.D., Department of Genetic Medicine, Hospital Sant Joan de Déu, Passeig Sant Joan de Déu, 2, 08950, Esplugues de Llobregat, Barcelona, Spain.
    Affiliations
    Laboratory of Neurogenetics and Molecular Medicine–Pediatric Institute of Rare Diseases, Institut de Recerca Sant Joan de Déu, Barcelona, Spain

    Centro de Investigación Biomédica en Red de Enfermedades Raras, Barcelona, Spain

    Department of Genetic Medicine–IPER, Hospital Sant Joan de Déu, Barcelona, Spain

    Clinic Institute of Medicine and Dermatology, Hospital Clínic, Barcelona, Spain

    Division of Pediatrics, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
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Open ArchivePublished:October 23, 2020DOI:https://doi.org/10.1016/j.jmoldx.2020.10.006
      Diagnosis is essential for the management and treatment of patients with rare diseases. In a group of patients, the genetic study identifies variants of uncertain significance or inconsistent with the phenotype; therefore, it is urgent to develop novel strategies to reach the definitive diagnosis. Herein, we develop the in-house Translational Diagnostics Program (TDP) to validate genetic variants as part of the diagnostic process with the close collaboration of physicians, clinical scientists, and research scientists. The first 7 of 33 consecutive patients for whom exome-based tests were not diagnostic were investigated. The TDP pipeline includes four steps: (i) phenotype assessment, (ii) literature review and prediction of in silico pathogenicity, (iii) experimental functional studies, and (iv) diagnostic decision-making. Re-evaluation of the phenotype and re-analysis of the exome allowed the diagnosis in one patient. In the remaining patients, the studies included either cDNA cloning or PCR-amplified genomic DNA, or the use of patients' fibroblasts. A comparative computational analysis of confocal microscopy images and studies related to the protein function was performed. In five of these six patients, evidence of pathogenicity of the genetic variant was found, which was validated by physicians. The current research demonstrates the feasibility of the TDP to support and resolve intramural medical problems when the clinical significance of the patient variant is unknown or inconsistent with the phenotype.
      A rare disease (RD) is defined as a condition that affects <5 per 10,000 inhabitants in the European Union and less than a total of 200,000 affected individuals in the United States. It is estimated that the number of different RDs is approximately 7000, and many of them are ultrarare. RDs usually are severe, chronic, disabling, and onset in pediatric life or young adulthood, and approximately 80% of them have a genetic origin.
      • Berman J.J.
      Rare Disease and Orphan Drugs.
      The symptoms and signs frequently are nonspecific, leading to difficulty and/or delay in diagnosis, which impedes adequate therapeutic planning and genetic counseling. A group of RDs remains undiagnosed, and it is urgent to deal with this category of undiagnosed RD (URD) by developing novel strategies and actions, including in-depth phenotyping and prompt genome analysis, to achieve a diagnosis.
      Next-generation sequencing technology has greatly improved the ability to identify causal genetic variants in patients with a particular RD.
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      Paediatric genomics: diagnosing rare disease in children.
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      Diagnostic impact and cost-effectiveness of whole-exome sequencing for ambulant children with suspected monogenic conditions.
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      • Macciocca I.
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      Prospective comparison of the cost-effectiveness of clinical whole-exome sequencing with that of usual care overwhelmingly supports early use and reimbursement.
      However, the massive number of variants of unknown significance (VUSs) derived from next-generation sequencing and, sometimes, the incongruence between the clinical phenotype and the candidate gene have hindered both downstream interpretations of genomic findings and translation into clinical practice. There is a necessity to define a reliable and valid in-house method for complex phenotype-genotype correlation and/or VUS classification in time to help clinical management. To assist in the process of variant classification relative to a patient's phenotype, the in-house Translational Diagnostics Program (TDP) was developed. The objective is to delineate the potential causality of VUS or the phenotype-genotype correlation through a holistic approach based on the triangle in-depth phenotyping–clinical genomics–functional genomics. Such a program combines four stages: (i) comprehensive phenotype evaluation, which integrates the enrichment and integrity of disease-phenotype annotations in the Human Phenotype Ontology
      • Robinson P.N.
      • Köhler S.
      • Bauer S.
      • Seelow D.
      • Horn D.
      • Mundlos S.
      The human phenotype ontology: a tool for annotating and analyzing human hereditary disease.
      ; (ii) exome sequencing and bioinformatic analysis to identify the genetic variant/s; (iii) functional validation of the genetic variant by reliable molecular, cellular, and imaging assays; and (iv) diagnostic decision-making of the referring physician based on recommendations of the variant pathogenic potential.
      The current research presents the results of TDP that was applied in seven pediatric URD patients. The effectiveness of this pipeline is shown in resolving clinical doubts when the clinical significance of the genetic variants is unknown or the relationship between phenotype and genotype is not congruent.

      Materials and Methods

       Ethical Considerations

      All procedures complied with the ethical guidelines of Sant Joan de Déu Children's Hospital and were approved by the Clinical Research Ethics Committee under references PIC-30-17 and PIC-223-19. Informed consent was obtained from the patients' parents or legal guardians.

       Study Design and Patients' Selection

      In January 2017, the Pediatric Institute of Rare Diseases and the Department of Genetic Medicine of Sant Joan de Déu Children's Hospital started exome-based testing in children with URD. Next-generation sequencing technology consisting of solution hybridization enrichment for clinical exome sequencing (TruSight One Sequencing Panel; Illumina, San Diego, CA) or whole exome sequencing (Nextera Flex for Enrichment; Illumina) was used and subsequent sequencing was performed on an Illumina NextSeq500 sequencer. The bioinformatics analysis was performed using a pipeline developed in the study department. The quality of the reads was determined (FastQC version 0.11.5; Babraham Institute, Cambridge, UK), the low-quality adapters and reads were removed (Cutadapt version 1.13; National Bioinformatics Infrastructure Sweden, Uppsala, Sweden), and subsequently aligned to the human reference genome (BWA-MEM version 0.7.15; Wellcome Trust Sanger Institute, Cambridge, UK). Low-mapping reads and duplicates [BEDtools version 2.26.0 (University of Utah, Salt Lake City, UT) and Picard version 2.9.0 (Broad Institute, Cambridge, MA)] were removed. Variants are detected with four different programs [SAMtools version 1.5 (Wellcome Trust Sanger Institute, Cambridge, UK), GATK version 3.7 (Broad Institute, Cambridge, MA), FreeBayes version 1.1.0 (Boston College, Boston, MA), and VarScan version 2.4.0 (Washington University, St. Louis, MO)], and the annotation (SnpEff version 4.3k; Wayne State University, Detroit, MI) included the databases 1000 Genomes, dbSnp, ExAc, and ClinVar. Deletions/duplications (copy number variations) were detected using the R exomeDepth version 1.1.10 package (R Inc., Boston, MA).
      To date, 33 patients from this clinical series have been included on the TDP to validate genetic variants. Patients were included in the TDP if the genetic variants found met any of the following criteria: (A) there was insufficient evidence of the pathogenicity of the variants despite being in genes already related to a clinical phenotype; (B) there was partial correlation or incomplete phenotype between the genotype and the clinical phenotype reported in Online Mendelian Inheritance in Man (MIM); and/or (C) the patient showed a complex phenotype, with discrepancies with the phenotype as described in the medical and scientific literature related to the candidate gene or atypical clinical expression (eg, Online Mendelian Inheritance in Man, www.omim.org, last accessed February 24, 2020). In addition, parental segregation studies were performed on available parents’ DNA by Sanger sequencing of the candidate variant. When necessary, paternity studies were performed using the PowerPlex 16HS system (Promega, Madison, WI), according to the manufacturer's protocol.

       Bioinformatic Analysis of Candidate Variants

      VarSome
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      VarSome: the human genomic variant search engine.
      (https://varsome.com, last accessed February 24, 2020) and American College of Medical Genetics and Genomics
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      ACMG Laboratory Quality Assurance Committee: Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.
      standards and guidelines were used as an interpretation of sequence variants. Genome Aggregation Database (https://gnomad.broadinstitute.org, last accessed February 24, 2020) and Centro de Investigación Biomédica en Red de Enfermedades Raras–Spanish Variant Server
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      267 Spanish exomes reveal population-specific differences in disease-related genetic variation.
      (http://csvs.babelomics.org, last accessed February 24, 2020) were used as the reference of total and Spanish population, respectively. Human Gene Mutation Database
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      • Phillips A.D.
      • Cooper D.N.
      The human gene mutation database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies.
      [http://www.hgmd.cf.ac.uk/ac/index.php (professional version 2019.4), last accessed February 24, 2020] collects variants published in the peer-reviewed literature as pathogenic variants for inherited disease in humans.
      To predict the effects and pathogenicity of variants on protein function, the following tools were used: Polymorphism Phenotyping version 2 (http://genetics.bwh.harvard.edu/pph2, last accessed February 24, 2020),
      • Adzhubei I.A.
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      A method and server for predicting damaging missense mutations.
      Protein Variation Effect Analyzer (http://provean.jcvi.org, last accessed February 24, 2020),
      • Choi Y.
      • Chan A.P.
      PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels.
      PMut (http://mmb.irbbarcelona.org/PMut/, last accessed February 24, 2020),
      • López-Ferrando V.
      • Gazzo A.
      • de la Cruz X.
      • Orozco M.
      • Gelpí J.L.
      PMut: a web-based tool for the annotation of pathological variants on proteins, 2017 update.
      MutationTaster (http://www.mutatiotaster.org, last accessed February 24, 2020),
      • Schwarz J.M.
      • Cooper D.N.
      • Schuelke M.
      • Seelow D.
      MutationTaster2: mutation prediction for the deep-sequencing age.
      Combined Annotation Dependent Depletion (https://cadd.gs.washington.edu, last accessed February 24, 2020),
      • Rentzsch P.
      • Witten D.
      • Cooper G.M.
      • Shendure J.
      • Kircher M.
      CADD: predicting the deleteriousness of variants throughout the human genome.
      probability of loss-function intolerance, and missense variation scores of Genome Aggregation Database (last accessed February 24, 2020).
      • Lek M.
      • Karczewski K.J.
      • Minikel E.V.
      • Samocha K.E.
      • Banks E.
      • Fennell T.
      • et al.
      Analysis of protein-coding genetic variation in 60,706 humans.
      ,
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      A framework for the interpretation of de novo mutation in human disease.
      Multiple protein sequence alignment among various species was performed by ClustalW.

       Cell Cultures, Expression Vectors, and Cell Transfection

      Human SH-SY5Y neuroblastoma and human embryonic kidney HEK293T cells were obtained from ATCC (Manassas, VA). SH-SY5Y cells were cultured in Dulbecco’s modified Eagle’s medium/F-12 HAM (Sigma-Aldrich, St. Louis, MO) supplemented with 10% (v/v) fetal bovine serum (Sigma-Aldrich), 2 mmol/L l-glutamine (Sigma-Aldrich), and 100 mg/mL penicillin-streptomycin (Sigma-Aldrich). HEK293T and skin human fibroblast cells were grown in Dulbecco’s modified Eagle’s medium high glucose (Sigma-Aldrich) supplemented with 10% (v/v) fetal bovine serum, 2 mmol/L l-glutamine, and 100 mg/mL penicillin-streptomycin. Cell cultures were maintained in a 5% CO2 humidified atmosphere at 37°C and grown until they reached 80% confluence for a maximum of 10 passages. Cells were periodically tested for Mycoplasma infection.
      For patient fibroblast studies, skin biopsies were performed after informed consent by patient representatives. Healthy control fibroblasts were obtained from Sant Joan de Déu Children's Hospital Biobank.
      SWI/SNF related matrix-associated actin-dependent regulator of chromatin subfamily A member 4 gene (SMARCA4) in entry pcDNA6.2/N-EmGFP-DEST mammalian expression vector was a gift from Kyle Miller (Addgene, Cambridge, MA; Addgene plasmid, number 65391),
      • Gong F.
      • Chiu L.Y.
      • Cox B.
      • Aymard F.
      • Clouaire T.
      • Leung J.W.
      • Cammarata M.
      • Perez M.
      • Agarwal P.
      • Brodbelt J.S.
      • Legube G.
      • Miller K.M.
      Screen identifies bromodomain protein ZMYND8 in chromatin recognition of transcription-associated DNA damage that promotes homologous recombination.
      zinc finger E-box binding homeobox 2 gene (ZEB2) in entry pRP[Exp]CMV>hZEB2 mammalian vector was generated by Cyagen (Santa Clara, CA) and cloned into the pEGFP-N1 expression plasmid, and dynein cytoplasmic 1 heavy chain 1 (DYNC1H1) in entry pDyn1 expression vector was a gift from Andrew Carter (Addgene plasmid, number 64067)
      • Schlager M.A.
      • Hoang H.T.
      • Urnavicius L.
      • Bullock S.L.
      • Carter A.P.
      In vitro reconstitution of a highly processive recombinant human dynein complex.
      , the region between linker and stalk was cloned into the pEGFP-N1 expression plasmid. SMARCA4 mutant (c.2194T>G; p.Y732D), ZEB2 mutant (c.2801A>G; p.H934R), and DYNC1H1 mutant (c.4867C>T; p.R1623W and c.4700G>A; p.R1567Q) were generated by site-directed mutagenesis with the QuickChange Lightning Site-Directed mutagenesis kit (Aligent Technologies, La Jolla, CA). Wild-type (WT) and mutant constructs were verified by Sanger sequencing. Cells were transfected with FuGene HD (Promega), according to the manufacturer's protocol, and analyzed 48 hours after transfection.

       Immunofluorescence

      For immunofluorescence staining, 9 × 104 cells (HEK293T or SH-5YHY) were seeded onto glass coverslip (HEK293T cells were plated on coverslip previously treated with poly-l-lysine, 40 μg/mL; Sigma-Aldrich). Two days after transfection with the indicated plasmid, all samples were harvested, washed in phosphate-buffered saline (PBS), and fixed in prewarmed 4% paraformaldehyde for 20 minutes at room temperature. After PBS washes, coverslips were mounted onto slide glasses in the presence of Fluoromont-G with DAPI (Thermo Fisher Scientific, Waltham, MA).
      Skin fibroblast cells (3 × 104) were washed in PBS and fixed in prewarmed 4% paraformaldehyde for 20 minutes at room temperature. Fibroblasts were permeabilized with 0.2% Triton X-100 in PBS for 30 minutes at room temperature and blocked with 1% bovine serum albumin and 4% serum in PBS for 1 hour at room temperature. Primary antibodies α-dynamin-related protein 1 gene (DRP1; 1:200; BD Transduction Laboratories, Franklin Lakes, NJ), α–translocase of outer mitochondrial membrane 20 (TOM20; 1:100; BD Transduction Laboratories), or α-mediator complex subunit 13 gene (MED13; 1:100; Novus Biological, Littleton, CO) were incubated overnight at 4°C. Primary antibodies were visualized using Alexa Fluor 488-labeled secondary antibody (1:500; Thermo Fisher Scientific). After 2 hours of incubation, fibroblasts were rinsed with PBS and mounted on a coverslip using Fluoromont-G with DAPI. To visualize mitochondria, cells were loaded with 200 nmol/L MitoTracker Deep Red (Thermo Fisher Scientific) for 30 minutes at 37°C; after PBS washes, coverslips were mounted using Fluoromont-G with DAPI.

       Subcellular Localization

      Cell counting was performed with a Leica DMI 3000B microscope (Leica Microsystems, Wetzlar, Germany) and 63× oil immersion objective. Five independent experiments were counted for each cell type (at least 100 random cells per experiment).

       Image Acquisition

      Super resolution images were acquired with a Leica TCS SP8 X White Light Laser confocal microscope with hybrid spectral detectors and HyVolution (Leica Microsystems) using the Leica LAS X software version 3.1.5 with 100× oil immersion objective (HCX Plan APO CS, 1.4 numerical aperture). Negative control samples were used for background setting before image acquisition. The original data were stored as 16-bit gray scale images with a spatial resolution from 792 × 792 to 1128 × 1128 pixels. Pixel sizes ranged from 0.018 × 0.018 to 0.031 × 0.031 μm. For the analysis of ZEB2 and SMARCA4 protein punctate pattern, image deconvolution was performed with Huygens Essential software version 4.4, supplied by Scientific Volume Imaging (Hilversum, the Netherlands). Z-stacks were acquired in 6.5 to 9.99 μm z-increments from each cell.

       Computational Image Analysis of GFP-SMARCA4 and GFP-ZEB2 Nuclear Punctate Pattern

      Because of the high image variability encountered, a two-stage unsupervised segmentation method was implemented for three-dimensional image segmentation of protein punctate pattern. The first stage estimated the nuclei of interest by contrast enhancement followed by image binarization (Otsu method) and labeling of the green channel [green fluorescent protein (GFP)-SMARCA4/ZEB2]. The resulting binary mask was applied to the original image to improve punctate pattern detection accuracy. In a second (segmentation) stage, nuclear punctate patterns were identified from the background by modeling the voxel intensity distribution as a univariate gaussian mixture. A model with five gaussian components was selected on the basis of the Akaike information criterion (Supplemental Figure S1). The gaussian component with the highest mean intensity was identified as the one corresponding to the punctate pattern. Feature extraction of the segmented images included punctate number and volume (μm3) of the nuclear protein punctate pattern. All the analyses were implemented and performed using the MATLAB software version R_2018a (The MathWorks Inc., Natick, MA).

       In Situ Proximity Ligation Assay

      SH-SY5Y cells (9 × 104) were seeded onto a glass coverslip and cultured for 24 hours; then, they were transfected with the indicated plasmid. After 48 hours of transfection, all samples were harvested, washed in PBS, and fixed in prewarmed 4% paraformaldehyde for 20 minutes at room temperature. After washes with PBS, cells were permeabilized with ice-cold methanol at −20°C for 20 minutes. After PBS washes and 1 hour of incubation at 37°C with the blocking solution in a preheated humidity chamber, cells were incubated overnight at 4°C with the specific primary antibodies: rabbit anti-GFP (1:100; Abcam, Cambridge, UK) and mouse anti-Dynactin 1 (1:100; Santa Cruz Biotechnology, Dallas, TX). Afterward, the proximity ligation assay was performed according to manufacturer's instructions [Duolink In Situ Detection Red Starter (Mouse/Rabbit) Kit; Sigma-Aldrich], and the coverslips were mounted with Duolink In Situ Mounting Medium with DAPI (Sigma-Aldrich). For each antibody, a negative control experiment was performed, where only one antibody was incubated with the proximity ligation assay probes.

       Analysis of Cell Cycle by Flow Cytometer

      Cells were grown in 12-well plates (2 × 105 cells/well) for 24 hours, and then were transfected with the indicated plasmid. After 48 hours of transfection, cells were harvested and fixed with 1% paraformaldehyde for 1 hour at 4°C, followed by 70% ice-cold ethanol for 2 hours at 4°C. After washing with PBS, the DNA was stained with DAPI solution containing: DAPI (final concentration, 1 μg/mL), 0.1% Triton X-100, and RNaseA (final concentration, 100 μg/mL) for 30 minutes at 37°C. Cells were acquired on ACEA NovoCyte Flow Cytometer (ACEA Biosciences, San Diego, CA). After collecting 20,000 events, cell cycle phase distributions were analyzed by using ACEA NovoExpress software version 1.4.1 (ACEA Biosciences) after gating out cell debris signal. Results were obtained from at least five independent experiments. Non-transfected cells were used as control.

       Analysis of Mitochondrial Oxidative Stress Levels in Fibroblasts by Flow Cytometer

      Fibroblasts were grown in 12-well plates (1 × 105 cells/well) for 48 hours, and then cells were trypsinized, washed with PBS, and resuspended in 5 μmol/L MitoSOX Red (Thermo Fisher Scientific). After 15 minutes of incubation in the dark at 37°C, cells were acquired on ACEA NovoCyte Flow Cytometer. For each assay, 10,000 events were collected and analyzed. Cells were treated with 500 μmol/L H2O2 (Sigma-Aldrich) for 15 minutes at 37°C as a positive control. Final values for MitoSOX fluorescence were calculated as relative fluorescence values over the mean of two independent healthy controls.

       Assessment of Mitochondrial Oxidative Stress Levels in Living Fibroblasts by Confocal Microscopy

      Fibroblast cells (1 × 105) were seeded onto glass coverslip in a 35-mm plate. After 24 hours, cells were washed with PBS and loaded with 2.5 μmol/L MitoSOX Red for 10 minutes in the dark at 37°C and washed three times with preheated PBS. As a positive control, cells were treated with 2 mmol/L H2O2. Images of cells were captured using a Leica TCS SP8 X White Light Laser confocal microscope (Leica Microsystems) with 100× oil immersion objective. Data analyses and intensity color maps (using royal lookup table model) were performed with ImageJ software version 1.52p (NIH, Bethesda, MD; https://imagej.nih.gov/ij, last accessed July 2, 2020). Final values for MitoSOX intensity were calculated as relative intensity values over the mean of two independent healthy controls.

       Splicing Reporter Minigene Assay

      Exon 7 of the GATA zinc finger domain-containing protein 2B gene (GATAD2B; NM_020699.2; 316 bp) and its flanking introns (48 bp at 5′ arm and 235 bp at 3′ arm) were PCR amplified from controls and patient human genomic DNA using Kapa HiFi DNA polymerase (Kapa Biosystems, Woburn, MA) and forward and reverse primers carrying restriction sites for XhoI and NheI (Thermo Fisher Scientific). PCR fragments were cloned into the pSPL3 exon trapping vector (Thermo Fisher Scientific) and were verified by Sanger sequencing. Wild-type and mutant constructs were transfected into HEK293T cells with FuGene HD (Promega) transfection reagent, according to the manufacturer's protocol. After 48 hours post-transfection, total RNA was isolated with Trizol reagent (Thermo Fisher Scientific) according to the instructions of the manufacturer using the QIAamp RNA kit (Thermo Fisher Scientific). cDNA was synthesized using Maxima first-strand cDNA synthesis kit for real-time quantitative RT-PCR (Thermo Fisher Scientific) and was amplified with Biotools DNA Polymerase (Biotools B&M Labs, Madrid, Spain) using the vector primers SD6 (forward: 5′-TCTGAGTCACCTGGACAACC-3′) and SA2 (reverse: 5′-ATCTCAGTGGTATTTGTGAGC-3′). Splice patterns of the minigene constructs were separated by electrophoresis and sequenced.

       Statistical Analysis

      All data are expressed as means ± SD or box plots, showing the median, box edges represent the 25th and 75th percentiles, and the whiskers extended to the minimum and maximum values. P values are indicated by asterisks: ∗P < 0.05, ∗∗P < 0.01, and ∗∗∗P < 0.001.
      The normality of data was assessed by the Kolmogorov-Smirnov test. Mantel-Haenszel χ2 test was performed to test potential differences in mean percentages of ZEB2, DYNC1H1, and SMARCA4 subcellular localization (case study 1, 2, and 5). The U-test was performed to evaluate differences in the nuclear punctate pattern of ZEB2 and SMARCA4 (Patients 1 and 5). Nonparametric Kruskal-Wallis test, followed by the Dunn post hoc test, was used to compare the number of dots per cell of DYNC1H1 (Patient 2) and the cell cycle distribution (Patients 1 and 5); in each case, the stacked bar represents means ± SD percentage of cells within G0/G1 phase, S phase, and G2/M phase. The parametric one-way analysis of variance test, followed by the Tukey post hoc test, was used to compare the oxidative stress levels (case study 6 and 7).
      Statistical computing and graphs were performed using the RStudio software version 1.1.447 (RStudio Inc., Boston, MA) or GraphPad Prism version 8.0.1 (GraphPad Software, Inc., La Jolla, CA).

      Results

      First, the clinical patient's phenotype and the medical records and the genetic data of the seven patients were updated (Table 1). The reanalysis yielded a diagnosis in one patient (Patient 3) and helped to design the functional validation of the remaining six patients. Functional validation of variants included two different strategies: cDNA cloning (genetic variants versus WT) and expression studies in human cell lines, and fibroblast culture (patients versus control) and studies of differences in cellular phenotypes (subcellular location and function).
      Table 1Summary of the Clinical and Genetic Findings in Seven Patients with URD
      Patient no.Recruitment criterion
      See patients' selection in Materials and Methods.
      Clinical phenotype (age at onset and sex)Exome findings:

      gene/variant (reference sequence)
      All patients present heterozygous variants (reference sequences are available from https://www.ncbi.nlm.nih.gov/nuccore).
      SegregationMIM no.: phenotypes/inheritanceGenotype-phenotype correlationVariant status at HGMD
      Variant class in HGMD, professional version 2019.4.
      gnomAD
      gnomAD allele frequency.
      /BIER
      BIER allele frequency.
      frequency
      CADD
      Scores ≥20 indicate the variant is predicted to be among the 1% most deleterious substitutions in the human genome.
      (score)
      Final diagnosis
      1AMild ID, speech delay, and gross and fine motor skills delay. Cerebellar syndrome and intention tremor, global progressive cerebellar atrophy, chronic motor and sensory axonal neuropathy, talipes equinovarus, (clumsy gait at 18 months, female)ZEB2/c.2801A>G p.H934R (NM_014795.3)M: not carrier
      Segregation studies were performed after functional validation studies; genetic variants in bold were further studied.


      F: carrier
      Segregation studies were performed after functional validation studies; genetic variants in bold were further studied.
      235730/ADPartialNRNR/NR3.9Impasse diagnosis/undiagnosed disease
      STIL/c.1455G>C p.L485F (rs139912214)

      (NM_001048166.1)
      M: not carrier
      Segregation studies were performed after functional validation studies; genetic variants in bold were further studied.


      F: carrier
      Segregation studies were performed after functional validation studies; genetic variants in bold were further studied.
      612703/ARNoDCM0.00211/0.00214.0
      CEP152/c.3313C>G p.L1105V (rs74553953)

      (NM_001194998.1)
      M: carrier
      Segregation studies were performed after functional validation studies; genetic variants in bold were further studied.


      F: not carrier
      Segregation studies were performed after functional validation studies; genetic variants in bold were further studied.
      613823/AR

      614852/AR
      NoPDCM0.00147/NR4.1
      2CID, distal weakness, and pes cavus, without developmental regression. Difficult and unstable gait and muscular atrophy of the lower extremities, especially distal. Motor neuropathy without sensory involvement. At 5 years, brain MRI showed a simplification of the sulcation pattern of preferential frontobasal, parietal, and temporal distribution; normal brainstem and cerebellum (early psychomotor delay with gait at 4 years, female)DYNC1H1/c.4867C>T p.R1623W (NM_001376.4)De novo614228/AD

      614563/AD

      158600/AD
      ComplexNRNR/NR27.9Lower extremity–predominant spinal muscular atrophy-1 (MIM no. 158600) and autosomal dominant mental retardation 13 (no. 614563)
      DYRK1A/c.1909A>G p.T637A (rs755674782)

      (NM_001396.3)
      M: carrier

      F: not carrier
      614104/ADPartialNR0.00000398/NR21.3
      3A, before segregationGlobal developmental delay, central hypotonia, mild deafness, oculomotor apraxia, ataxia, tremor, dysmetria, and progressive cerebellar atrophy (nonvisual contact at 4 months and stable sitting at 12 months, female)ITPR1
      • Sasaki M.
      • Ohba C.
      • Iai M.
      • Hirabayashi S.
      • Osaka H.
      • Hiraide T.
      • Saitsu H.
      • Matsumoto N.
      Sporadic infantile-onset spinocerebellar ataxia caused by missense mutations of the inositol 1,4,5-triphosphate receptor type 1 gene.
      /c.1736C>T p.T579I (NM_001168272)
      De novo206700/AD, AR

      606658/AD

      117360/AD
      YesDCMNR/NR26.4Spinocerebellar ataxia 29, congenital nonprogressive (MIM no. 117360)
      ANO10/c.1954A>G p.M652V (rs147989825)

      (NM_018075)
      De novo613728/ARPartialNR0.000549/NR0.4
      4BGlobal developmental delay, mild dysmorphic features, strabismus, central hypotonia, delayed postural control, and mild limb spasticity; abnormal behavior, which might be included within the autism spectrum disorder (infancy, male)GATAD2B/c.1216+2T>C (NM_020699.2)De novo615074/ADPartialNRNR/NR33Mental retardation, autosomal dominant 18 (MIM no. 615074)
      COL6A1/c.632G>A p.R211H (rs943925031)

      (NM_001848.2)
      M: not carrier

      F: carrier
      158810/AD, AR

      254090/AD, AR
      NoNR0.00000641/NR31.0
      GJB2/c.35dupG p.V13fs

      (rs80338939)

      (NM_004004.5)
      M: carrier

      F: not carrier
      220290/ARNoDCM0.0000241/0.005NA
      CANT1/c.898C>T p.R300C (rs267606701)

      NM_001159772.1
      M: not carrier

      F: carrier
      251450/AR

      617719/AR
      NoDCM0.0000175/NR34.0
      5BMotor retardation, speech and language development delay, coarse facial features, torticollis, scoliosis, equinovarus foot, hypoplasia of the fifth toenails but not in the fifth fingernails, no hypertrichosis (infancy, male)SMARCA4/c.2194T>G p.Y732D (NM_001128849.1)De novo614609/AD

      613325/AD
      PartialNRNR/NR28.4Coffin-Siris syndrome 4 (MIM no. 614609)
      FREM1/c.5212C>A p.Y1738M (rs138267253)

      (NM_144,966.5)
      M: carrier

      F: not carrier
      608980/NR

      614485/AD

      248450/AR
      NoNR0.00294/0.00419.0
      NPHS2/c.413G>A p.R138Q (rs74315342)

      (NM_014625.3)
      M: NA

      F: NA
      600995/ARNoDCM0.000577/026.8
      LAMA1/c.248G>A p.W827fs (rs922278637)

      (NM_005559.3)
      M: NA

      F: NA
      615960/ARNoNRNR/NR43.0
      6BProgressive spastic paraparesis, pyramidal signs in lower limbs, and spastic gait. Slight elevation of long-chain fatty acids and delayed conduction of visually evoked potentials (infancy, male)DRP1/c.223A>G p.K75E (NM_012062.3)De novo614388/AD, AR

      610708/AD
      PartialNRNR/NR20.1Hereditary spastic paraparesis
      7CRefractory epilepsy of neonatal onset, spastic tetraparesis (axial hypotonia and limb spasticity), pigmentary retinopathy, microcephaly, mental retardation with absent speech, dysmorphic facial features, retrognathia, hypertelorism, flat philtrum, nystagmus. hyperlactacidemia and metabolic acidosis, delayed myelination, trichorrhexis nodosa (infancy, male); the patient died at 8 years oldMED13/c.2489T>G p.L830R (NM_005121.2)De novo618009/ADPartialNRNR/NR31Intellectual developmental disorder 61 (MIM no. 618009, with complex phenotype)
      CACNA1F/c.5846G>A p.S1949N (NM_005183.3)M: carrier

      F: not carrier
      300600/XL

      30476/XLR

      300071/XL
      NoNRNR/NR1.87
      AD, autosomal dominant; AR, autosomal recessive; BIER, Centro de Investigación Biomédica en Red de Enfermedades Raras–Spanish Variant Server; CADD, Combined Annotation Dependent Depletion; DCM, disease-causing mutation; F, father; gnomAD, Genome Aggregation Database; HGMD, Human Gene Mutation Database; ID, intellectual disability; M, mother; MIM, Mendelian Inheritance in Man; MRI, magnetic resonance imaging; NA, not available; NR, not reported; PDCM, possible disease-causing mutation; URD, undiagnosed rare disease; XL, X linked; XLR, X-linked recessive.
      See patients' selection in Materials and Methods.
      All patients present heterozygous variants (reference sequences are available from https://www.ncbi.nlm.nih.gov/nuccore).
      Variant class in HGMD, professional version 2019.4.
      § gnomAD allele frequency.
      BIER allele frequency.
      Scores ≥20 indicate the variant is predicted to be among the 1% most deleterious substitutions in the human genome.
      ∗∗ Segregation studies were performed after functional validation studies; genetic variants in bold were further studied.

       Patient 1

      The patient was an 8-year–old girl with mild intellectual disability (ID) and remarkable difficulties in expressive language. Dysfunctions in gross and fine motor skills, intention tremors, and talipes equinovarus were also observed. Global and progressive cerebellar atrophy was detected through serial magnetic resonance imaging studies. Nerve conduction studies and electromyography revealed a chronic motor and sensory axonal neuropathy. First, a chromosomal microarray analysis (qChip CM, qGenomics, and Esplugues) was performed, and an approximately 746-Kb duplication on chromosome 19p13 of unknown significance was detected that is also unreported in databases such as DECIPHER, ISCA, and ClinVar. Then, an exome-targeted sequencing and bioinformatic analysis of 128 genes related to birth defects of brain development (Supplemental Table S1) was performed that revealed the heterozygous variant c.2801A>G (p.H934R) in ZEB2 (MIM ∗605,802). Segregation studies were initially unavailable for this patient (Table 1).
      This nuclear protein is a member of the ZEB zinc finger transcription factor family, involved in neurodevelopment processes
      • Epifanova E.
      • Babaev A.
      • Newman A.G.
      • Tarabykin V.
      Role of Zeb2/Sip1 in neuronal development.
      and cell cycle.
      • Shin J.O.
      • Lee J.M.
      • Bok J.
      • Jung H.S.
      Inhibition of the Zeb family prevents murine palatogenesis through regulation of apoptosis and the cell cycle.
      Haploinsufficiency of the ZEB2 gene has been extensively associated with Mowat-Wilson syndrome (MIM number 235730), a condition with ID and severe speech impairment. p.H934R is located in the exon 8 of ZEB2 like most of the previously reported variants
      • Saunders C.J.
      • Zhao W.
      • Ardinger H.H.
      Comprehensive ZEB2 gene analysis for Mowat-Wilson syndrome in a North American cohort: a suggested approach to molecular diagnostics.
      (Figure 1A). This variant affects an interdomain region near the C-terminal zinc-finger cluster domain (Figure 1A), and it is fully conserved among different species (data not shown). In silico studies predicted that p.H934R could be deleterious (Figure 1A and Supplemental Table S2).
      Figure thumbnail gr1
      Figure 1Nonconclusive results for the variant p.H934R of zinc finger E-box binding homeobox 2 (ZEB2). A: Top panel: ZEB2 domain structure (Uniprot: O60315) and the location of missense variant in Patient 1 (red) and those reported in Human Gene Mutation Database (black). Bottom panel: Density plot of all ZEB2 missense variants reported in Genome Aggregation Database (gnomAD). B: Nuclear expression of recombinant green fluorescent protein (GFP)–ZEB2 showing the absence (top panels) or the presence of punctate pattern (bottom panels) in HEK293T transfected cells. C: Cell percentage of nuclear punctate pattern in GFP-ZEB2WT versus GFP-ZEB2H934R [wild type (WT): 34.2 ± 8.3; and H934R: 54.5 ± 11.1; Mantel-Haenszel χ2 test: P = 2.2 × 10−6; number of independent experiments (N): 5, at least 100 random cells by experiment]. D: Nuclear punctate in GFP-ZEB2WT (top panels) and GFP-ZEB2H934R (bottom panels). E and F: Comparison of GFP-ZEB2 punctate number [WT: 61 (31) versus H934R: 55 (49.8); U-test: P = 0.93; E] and volume [WT: 0.17 (0.56) versus H934R: 0.14 (0.42); U-test: P = 0.57; F]. GFP-ZEB2WT: 10 cells and 562 nuclear punctates; and GFP-ZEB2H934R: 14 cells and 777 nuclear punctates. G: Cell cycle distribution of non-transfected cells (control), GFP-ZEB2WT cells, and GFP-ZEB2H934R cells. Comparison of WT versus H934R (Kruskal-Wallis test followed by Dunn post hoc multiple comparison test): G0/G1 phase, 61.4 ± 0.9 versus 64.5 ± 1.3 (P = 0.28); S phase, 28.2 ± 1.2 versus 25.3 ± 2.1 (P = 1.00); and G2/M phase, 8.9 ± 2.7 versus 6.8 ± 3.2 (P = 0.47); N: 5. Images were taken from confocal optical sections that are representative for the group averages. ∗∗∗P < 0.001. Scale bar = 5 μm (B and D). CID, CtBP-interacting domain; C-ZF, C-terminal zinc-finger cluster; HD, homeodomain; NIM, nucleosome remodeling and deacetylase-interaction motif; N-ZF, N-terminal zinc-finger cluster; S, SUMOylation sites; SBD, Smad-binding domain.
      GFP-ZEB2WT and GFP-ZEB2H934R were cloned to compare subcellular localization and cell cycle phases in the HEK293T cell line. The two GFP-tagged ZEB2 proteins showed nuclear localization with two different patterns: nonpunctate and punctate (Figure 1B). Significant differences were observed in the distribution of patterns between WT and p.H934R protein (P = 2.2 × 10−6) (Figure 1C). However, by super-resolution image technology, nonsignificant differences were observed in either the number (P = 0.93) or volume (P = 0.57) of nuclear punctate (Figure 1, D–F, and Supplemental Figure S1). Besides, the study of cell cycle phases after overexpression of GFP-tagged ZEB2 proteins also showed no differences (Figure 1G). Therefore, p.H934R was not found to affect ZEB2 nuclear localization or cell cycle. Collectively, the functional study changed p.H934R from VUS to likely benign. Parental DNA for segregation studies was available after functional validation studies and showed that the p.H934R variant was inherited from the father. Considering all aspects as a whole, the ZEB2 gene could not be completely discarded as the cause of the patient's disease.

       Patient 2

      The patient was an 8-year–old girl with a history of global psychomotor delay, ID, distal weakness, and pes cavus, without developmental regression. Nerve conduction studies and electromyogram showed a motor neuropathy without sensory involvement. Brain magnetic resonance imaging revealed malformations of cortical development. After exome sequencing, a de novo heterozygous variant c.4867C>T, p.R1623W was found in the dynein cytoplasmic 1 heavy chain 1 gene (DYNC1H1; MIM ∗600,112) (Table 1).
      Cytoplasmic dynein 1 is a component of multisubunit motor complex essential for retrograde axonal transport, trafficking of organelles, vesicles, and macromolecules toward microtubule minus end.
      • Yang M.L.
      • Shin J.
      • Kearns C.A.
      • Langworthy M.M.
      • Snell H.
      • Walker M.B.
      • Appel B.
      CNS myelination requires cytoplasmic dynein function.
      ,
      • Cosker K.E.
      • Courchesne S.L.
      • Segal R.A.
      Action in the axon: generation and transport of signaling endosomes.
      Three major phenotypes have been already associated with the DYNC1H1 gene (MIM number 614228 and MIM number 158600, related to peripheral neuropathy; and MIM number 614563, associated with cerebral dysgenesis with ID) (Table 1 and Figure 2A). Patient 2 showed a partial phenotype correlation with all of them. On the basis of de novo inheritance, p.R1623W was predicted to be likely pathogenic (Table 1 and Supplemental Table S2), and it is located at a conserved region of the tail domain linker of dynein 1 (Figure 2A).
      Figure thumbnail gr2
      Figure 2Dynein cytoplasmic 1 heavy chain 1 (DYNC1H1) p.R1623W variant affects the subcellular location of the protein and its binding capacity to Dynactin 1. A: Top panel: DYNC1H1 domain structure (Uniprot: Q14204) and the location of the variant in Patient 2 (red) and those reported in Human Gene Mutation Database (black), indicating associated diseases. Asterisk indicates the missense variant p.R1567Q used as a pathogenic control. Bottom panel: A density plot of all DYNC1H1 missense variants reported in Genome Aggregation Database (gnomAD). B: Cellular expression pattern found in recombinant green fluorescent protein (GFP)–DYNC1H1 either exclusively cytoplasmic (C; top panels) or nuclei and cytoplasm (NyC; bottom panels) in SH-SY5Y transfected cells. C: Comparison and quantification of GFP-DYNC1H1WT, GFP-DYNC1H1R1623W, and GFP-DYNC1H1R1567Q subcellular localization [wild type (WT): 84.9 ± 6.1 C and 15.1 ± 6.1 NyC; R1623W: 20.0 ± 6.4 C and 80.0 ± 8.1 NyC (Mantel-Haenszel χ2 test: P = 2.2 × 10−6) and R1567Q: 12.1 ± 4.0 C and 87.9 ± 4.0 NyC (Mantel-Haenszel χ2 test: P = 2.2 × 10−6)]. Six replicates were performed [number of independent experiments (N): 6; at least 100 random cells by experiment]. D: Proximity ligation assay (PLA) using α-GFP (DYNC1H1) and α-dynactin 1 (DCTN1) of GFP-DYNC1H1WT (top panels), GFP-DYNC1H1R1623W (middle panels), and GFP-DYNC1H1R1567Q (bottom panels) cells. E: Quantification of PLA in SH-SY5Y transfected cells [WT: 729 (97); R1623W: 433 (94.5) (Kruskal-Wallis test followed by Dunn post hoc multiple comparison test: P < 1 × 10−4) and R1567Q: 405 (97) (Kruskal-Wallis test followed by Dunn post hoc multiple comparison test: P < 1 × 10−4); N: 5]. Images were taken from confocal optical sections that are representative of the group averages. ∗∗∗P < 0.001. Scale bars = 10 μm (B and D). AAA (1 to 6), ATPase domains; DIC, interaction with DYNC1I2 domain; DLIC, interaction with DYNC1LI2 domain; Lk, linker.
      Because of the complex phenotype, the functional effect of the variant was investigated. To validate p.R1623W, GFP-tagged DYNC1H1 WT and variant construct that included amino acids 1444 (linker domain) to 3501 (stalk) were generated. After SH-SY5Y cell transfection, GFP-DYNC1H1WT was found mainly in the cytoplasm, whereas GFP-DYNC1H1R1623W was delocalized at the nuclei (P = 2.2 × 10−6) (Figure 2, B and C). Given that cytoplasmic dynein 1 interacts with dynactin 1 and this complex is required for the cargo transport along the microtubule cytoskeleton,
      • Urnavicius L.
      • Zhang K.
      • Diamant A.G.
      • Motz C.
      • Schlager M.A.
      • Yu M.
      • Patel N.A.
      • Robinson C.V.
      • Carter A.P.
      The structure of the dynactin complex and its interaction with dynein.
      this interaction was quantified using an in situ proximity ligation assay (Figure 2D). A significant reduction of GFP-DYNC1H1R1623W interaction with dynactin 1 was found when compared with GFP-DYNC1H1WT (P < 1 × 10−4) (Figure 2E). Therefore, it was demonstrated that p.R1623W affects the localization of cytoplasmic dynein 1 as well as its binding capacity to dynactin 1, which affects the protein function. For this first experimentally validated case in the TDP, another established missense pathogenic variant of DYNC1H1 (c.4700G>A, p.R1567Q)
      • Hoang H.T.
      • Schlager M.A.
      • Carter A.P.
      • Bullock S.L.
      DYNC1H1 mutations associated with neurological diseases compromise processivity of dynein-dynactin-cargo adaptor complexes.
      • Poirier K.
      • Lebrun N.
      • Broix L.
      • Tian G.
      • Saillour Y.
      • Boscheron C.
      • Parrini E.
      • Valence S.
      • Pierre B.S.
      • Oger M.
      • Lacombe D.
      • Geneviève D.
      • Fontana E.
      • Darra F.
      • Cances C.
      • Barth M.
      • Bonneau D.
      • Bernadina B.D.
      • N'guyen S.
      • Gitiaux C.
      • Parent P.
      • des Portes V.
      • Pedespan J.M.
      • Legrez V.
      • Castelnau-Ptakine L.
      • Nitschke P.
      • Hieu T.
      • Masson C.
      • Zelenika D.
      • Andrieux A.
      • Francis F.
      • Guerrini R.
      • Cowan N.J.
      • Bahi-Buisson N.
      • Chelly J.
      Mutations in TUBG1, DYNC1H1, KIF5C and KIF2A cause malformations of cortical development and microcephaly.
      • Scoto M.
      • Rossor A.M.
      • Harms M.B.
      • Cirak S.
      • Calissano M.
      • Robb S.
      • Manzur A.Y.
      • Martínez-Arroyo A.
      • Rodriguez-Sanz A.
      • Mansour S.
      • Fallon P.
      • Hadjikoumi I.
      • Klein A.
      • Yang M.
      • De Visser M.
      • Overweg-Plandsoen W.C.
      • Baas F.
      • Taylor J.P.
      • Benatar M.
      • Connolly A.M.
      • Al-Lozi M.T.
      • Nixon J.
      • de Goede C.G.
      • Foley A.R.
      • Mcwilliam C.
      • Pitt M.
      • Sewry C.
      • Phadke R.
      • Hafezparast M.
      • Chong W.K.
      • Mercuri E.
      • Baloh R.H.
      • Reilly M.M.
      • Muntoni F.
      Novel mutations expand the clinical spectrum of DYNC1H1-associated spinal muscular atrophy.
      was also studied as a pathogenic control. Results showed that GFP-DYNC1H1R1567Q has a similar localization pattern as GFP-DYNC1H1R1623W (P = 0.677) as well as decreased interaction with dynactin 1 (P > 0.999).
      These findings suggest that p.R1623W is a pathogenic variant and therefore it is the cause of the complex clinical phenotype observed in Patient 2. The broad clinical spectrum that involves both the peripheral and central nervous system in patient shows the complexity of DYNC1H1-related diseases, which can be expressed as a neuromuscular disorder, as well as malformation of cortical development with ID,
      • Chen Y.
      • Xu Y.
      • Li G.
      • Li N.
      • Yu T.
      • Yao R.E.
      • Wang X.
      • Shen Y.
      • Wang J.
      Exome sequencing identifies de novo DYNC1H1 mutations associated with distal spinal muscular atrophy and malformations of cortical development.
      but also with the full pathologic spectrum.

       Patient 4

      Patient 4 was a 3-year–old boy who presented with global developmental delay, mild dysmorphic features, strabismus, central hypotonia, delayed postural control, and behavioral changes. After exome sequencing trio, a de novo heterozygous variant c.1216+2T>C in GATAD2B (MIM ∗614,998) was found in the patient. GATAD2B encodes a zinc finger protein transcriptional repressor.
      • Feng Q.
      • Zhang Y.
      The MeCP1 complex represses transcription through preferential binding, remodeling, and deacetylating methylated nucleosomes.
      Variants in this gene cause ID and dysmorphic features (MIM number 615074)
      • Ueda K.
      • Yanagi K.
      • Kaname T.
      • Okamoto N.
      A novel mutation in the GATAD2B gene associated with severe intellectual disability.
      ,
      • Willemsen M.H.
      • Nijhof B.
      • Fenckova M.
      • Nillesen W.M.
      • Bongers E.M.
      • Castells-Nobau A.
      • Asztalos L.
      • Viragh E.
      • van Bon B.W.
      • Tezel E.
      • Veltman J.A.
      • Brunner H.G.
      • de Vries B.B.
      • de Ligt J.
      • Yntema H.G.
      • van Bokhoven H.
      • Isidor B.
      • Le Caignec C.
      • Lorino E.
      • Asztalos Z.
      • Koolen D.A.
      • Vissers L.E.
      • Schenck A.
      • Kleefstra T.
      GATAD2B loss-of-function mutations cause a recognisable syndrome with intellectual disability and are associated with learning deficits and synaptic undergrowth in Drosophila.
      that partially match the patient's phenotype (Table 1). c.1216+2T>C variant affects the splice donor site of GATAD2B intron 7 and was predicted to be damaging (Supplemental Table S2).
      For functional analysis, genomic DNA from both control and patient in the pSPL3 vector was cloned to perform a minigene assay. After RT-PCR and sequencing the PCR product, the emergence of a cryptic splice donor site was found in the exon 7 (position GRCh37:1:153788747) (Supplemental Figure S2A). This new splice site causes the loss of the GATAD2B open reading frame and a premature stop codon (Supplemental Figure S2B). Another splicing variant of GATAD2B was described as likely pathogenic in a patient with severe ID, epilepsy, and dysmorphic features.
      • Hamdan F.F.
      • Srour M.
      • Capo-Chichi J.M.
      • Daoud H.
      • Nassif C.
      • Patry L.
      • Massicotte C.
      • Ambalavanan A.
      • Spiegelman D.
      • Diallo O.
      • Henrion E.
      • Dionne-Laporte A.
      • Fougerat A.
      • Pshezhetsky A.V.
      • Venkateswaran S.
      • Rouleau G.A.
      • Michaud J.L.
      De novo mutations in moderate or severe intellectual disability.
      This splicing error in GATAD2B was concluded to be the cause of the developmental disorder of the patient, allowing the diagnosis of mental retardation, autosomal dominant 18.

       Patient 5

      Patient 5 was a 2-year–old boy exhibiting motor retardation, delays in speech and language development, coarse facial features, torticollis, scoliosis, equinovarus foot, and hypoplasia of the fifth toenails but not of the fifth fingernails. Exome sequencing revealed a de novo variant c.2194T>G in SMARCA4 (MIM 603,254). c.2194T>G variant changes tyrosine (Y) 732 to aspartic acid (D) in the SMARCA4 protein (Table 1).
      SMARCA4 is a nuclear protein of the catalytic subunit of BRG1/BRM-associated factor ATP dependent that functions as chromatin remodeling complex
      • Son E.Y.
      • Crabtree G.R.
      The role of BAF (mSWI/SNF) complexes in mammalian neural development.
      and cell cycle regulator.
      • Muchardt C.
      • Yaniv M.
      When the SWI/SNF complex remodels...the cell cycle.
      SMARCA4 gene variants cause Coffin-Siris syndrome 4 (MIM number 614609)
      • Errichiello E.
      • Mustafa N.
      • Vetro A.
      • Notarangelo L.D.
      • de Jonge H.
      • Rinaldi B.
      • Vergani D.
      • Giglio S.R.
      • Morbini P.
      • Zuffardi O.
      SMARCA4 inactivating mutations cause concomitant Coffin-Siris syndrome, microphthalmia and small-cell carcinoma of the ovary hypercalcaemic type.
      that partially matched the patient's clinical phenotype. The patient did not show some typical signs, such as feeding difficulties, and hypoplastic or absent fifth fingernails and fifth distal phalanges. p.Y732D position is conserved across different species (data not shown), and it is located in the interdomain region between the Brahma-kismet domain and SNF2 family N-terminal domain of SMARCA4 (Figure 3A). In silico analysis predicted p.Y732D to be deleterious, and it is located at protein position extremely intolerant to loss-of-function variation (probability of loss-function intolerance = 1.00) and missense variation (z-score = 8.36) (Supplemental Table S2 and Figure 3A).
      Figure thumbnail gr3
      Figure 3SWI/SNF related matrix-associated actin-dependent regulator of chromatin subfamily A member 4 (SMARCA4) p.Y732D variant affects the location and function of the protein. A: Top panel: SMARCA4 domain structure (Uniprot: P51532) and the location of the variant in Patient 5 (red) and missense variants associated with Coffin-Siris syndrome (Human Gene Mutation Database; black). Bottom panel: A density plot of all SMARCA4 missense variants reported in Genome Aggregation Database (gnomAD). B: Recombinant green fluorescent protein (GFP)–SMARCA4 subcellular localization at nuclei (N; top panels) or nuclei and cytoplasm (NyC; bottom panels) in SH-SY5Y cells. C: Percentage of N and NyC patterns in GFP-SMARCA4WT versus GFP-SMARCA4Y732D [wild type (WT): 80.2 ± 1.4 N and 19.8 ± 1.4 NyC versus Y732D: 49.4 ± 3.2 N and 50.6 ± 3.2 NyC; Mantel-Haenszel χ2 test: P = 2.2 × 10−6; number of independent experiments (N): 5, at least 100 random cells by experiment]. D: Nuclear punctate pattern in GFP-SMARCA4WT (top panels) and GFP-SMARCA4Y732D (bottom panels) cells. E and F: Comparison of number [WT: 143 (90) versus Y732D: 33 (38); U-test: P = 0.016; E] and volume [WT: 0.015 (0.08) versus Y732D: 0.030 (0.15); U-test: P = 0.004; F] of nuclear punctate in GFP-SMARCA4WT and GFP-SMARCA4Y732D cells. G: Cell cycle phases cellular distribution of non-transfected (control), GFP-SMARCA4WT, and GFP-SMARCA4Y732D cells [Kruskal-Wallis test followed by Dunn post hoc multiple comparison test: G0/G1 phase, 67.2 ± 4.2 versus 66.2 ± 3.5 (P = 0.916); S phase, 26.9 ± 4.2 versus 26.0 ± 4.4 (P = 1.00); G2/M phase, 4.4 ± 2.0 versus 7.3 ± 2.6 (P = 0.016); N: 5). Images were taken from confocal optical sections that are representative of the group averages. N = 5 cells (E and F, GFP-SMARCA4WT and GFP-SMARCA4Y732D); n = 738 nuclear punctate (E and F, GFP-SMARCA4WT); n = 181 nuclear punctate (E and F, GFP-SMARCA4Y732D). ∗P < 0.05, ∗∗P < 0.01, and ∗∗∗P < 0.001. Scale bars = 5 μm (B and D). BRK, brahma and kismet domain; Bromo, bromodomain; DEXDc, DEAD-like helicase superfamily domain; HSA, helicase/SANT-associated domain; HELICc, helicase superfamily C-terminal domain; SNF2_N, SNF2 family N-terminal domain; QLQ, Gln-Leu-Gln motif.
      GFP-SMARCA4 WT and variant were cloned to compare subcellular localization and cell cycle phases in the SH-SY5Y cell line. WT and p.Y732D proteins showed different cellular distribution: although GFP-SMARCA4WT was mainly located at nuclei, GFP-SMARCA4Y732D was delocalized in the cytoplasm (P = 2.2 × 10−6) (Figure 3, B and C). The GFP-SMARCA4 punctate pattern at nuclei was characterized using super-resolution imaging. The number of punctate GFP-SMARCA4Y732D was lower in comparison to GFP-SMARCA4WT (P = 0.016), and the volume was higher (P = 0.004) (Figure 3, D–F, and Supplemental Figure S1). Furthermore, cell cycle studies in transfected cells showed significant differences in the G2/M phase (P = 0.016). On the contrary, no differences in G0/G1 (P = 0.916) or S phases (P = 1.00) were found (Figure 3G). The functional interpretation of p.Y732D in SMARCA4 supports the variant as pathogenic in a patient expressing nontypical Coffin-Siris syndrome.

       Patient 6

      The patient was a 7-year–old patient affected by progressive spastic paraparesis, pyramidal signs in lower limbs, and spastic gait. Exome sequencing and bioinformatic analyses revealed a de novo heterozygous variant c. 223A>G (p.K75E) in the dynamin 1-like (MIM ∗603,850; alias DRP1) (Table 1).
      DRP1 is a member of the dynamin superfamily of cytoplasmic GTPases, which mediates membrane remodeling during a variety of cellular processes.
      • Nasca A.
      • Legati A.
      • Baruffini E.
      • Nolli C.
      • Moroni I.
      • Ardissone A.
      • Goffrini P.
      • Ghezzi D.
      Biallelic mutations in DNM1L are associated with a slowly progressive infantile encephalopathy.
      DRP1 translocates to the outer mitochondrial membrane and then forms helical oligomers that wrap around the outer mitochondrial membrane and scission it, playing an essential role in the mitochondrial fission process.
      • Fonseca T.B.
      • Sanchez-Guerrero A.
      • Milosevic I.
      • Raimundo N.
      Mitochondrial fission requires DRP1 but not dynamins.
      • Kalia R.
      • Wang R.Y.
      • Yusuf A.
      • Thomas P.V.
      • Agard D.A.
      • Shaw J.M.
      • Frost A.
      Structural basis of mitochondrial receptor binding and constriction by DRP1.
      • Ji W.K.
      • Hatch A.L.
      • Merrill R.A.
      • Strack S.
      • Higgs H.N.
      Actin filaments target the oligomeric maturation of the dynamin GTPase Drp1 to mitochondrial fission sites.
      The DRP1 gene mutations have been associated with optic atrophy 5 (MIM number 610708) and lethal encephalopathy due to defective mitochondrial and peroxisomal fission (MIM number 614388). The patient, however, showed spastic paraparesia, not previously associated with DRP1, and only a discreet and partial coincidence with the reported phenotypes (Table 1 and Figure 4A).
      Figure thumbnail gr4
      Figure 4Dynamin-related protein 1 (DRP1) p.K75E variant affects the mitochondrial network morphology and increases the mitochondrial oxidative stress. A: Top panel: DRP1 domain structure (Uniprot: O00429) and the location of the variant in Patient 6 (red) and those reported in Human Gene Mutation Database (black), indicating associated diseases. Bottom panel: A density plot of all DRP1 missense variants reported in Genome Aggregation Database (gnomAD). B: Mitochondrial network structure stained with MitoTracker Deep Red (MTDR) and DRP1 localization (green) in fibroblasts of control (top panels) and patient (bottom panels). Magnification of white dashed boxed region is shown in the panels immediately to the right (detail), and white arrowheads show mitochondrial chain-like structure. C: Translocase of outer mitochondrial membrane 20 (TOM20) mitochondrial marker immunofluorescence of control (top panels) and patient (bottom panels). The magnification of the white dashed boxed region is shown in the panels immediately to the right (detail). D: Mean MitoSOX fluorescence intensities relative to mean of two independent healthy controls by flow cytometry [CT (mean controls): 0.98 ± 0.05 versus Patient 6:1.61 ± 0.37; one-way analysis of variance test followed by Tukey post hoc multiple comparison test P = 0.004; number of independent experiments: 6]. As a positive control for increase of the reactive oxygen species levels (+) (CT+: 1.52 ± 0.19), cells were treated with 500 μmol/L H2O2. E: In vivo MitoSOX staining in control (top panels) and patient (bottom panels) fibroblasts and the corresponding scattering intensity color map. F: Quantification of in vivo MitoSOX intensity in control and patient fibroblasts [CT: 0.94 (0.36) versus Patient 6: 1.36 (0.45); one-way analysis of variance test followed by Tukey post hoc multiple comparison test P < 1 × 10−4]. As positive control, cells were treated with 2 mmol/L H2O2 (+) [CT+: 1.51 (0.17)]. Images were taken from confocal optical sections that are representative of the group averages. N = 42 control fibroblasts (E); N = 17 patient fibroblasts (E); N = 23 cells (F). ∗∗P < 0.01, ∗∗∗P < 0.001. Scale bars: 20 μm (B, C, and E); 1 μm (B and C, detail). GED, GTPase effector domain; MD, middle domain; r.u., relative units; VD, variable domain.
      p.K75E position is conserved across different species (data not shown), and it is located in the GTPase domain that it is necessary for mitochondrial fission process through a GTP-dependent mechanism
      • Heymann J.A.
      • Hinshaw J.E.
      Dynamins at a glance.
      (Figure 4A). The predictors used in the in silico studies revealed inconsistent results in the pathogenic prediction of the variant (Supplemental Table S2 and Table 1).
      For functional studies, the mitochondrial network structure and oxidative stress levels in controls and patient's fibroblasts were compared. DRP1 immunostaining of the control and patient fibroblasts revealed no differences in the mitochondrial location of the protein (Figure 4B). However, the patient showed an aberrant mitochondrial network, like other dynamin 1-like–associated cases.
      • Nasca A.
      • Legati A.
      • Baruffini E.
      • Nolli C.
      • Moroni I.
      • Ardissone A.
      • Goffrini P.
      • Ghezzi D.
      Biallelic mutations in DNM1L are associated with a slowly progressive infantile encephalopathy.
      Specifically, the staining of fibroblasts with both Mitotracker Deep Red (Figure 4B) and α-TOM20 (outer mitochondrial membrane protein) (Figure 4C) showed in patient's cells hyperfused mitochondria (including both network and elongated structures), whereas the control displayed branched mitochondria with distinguishable tips. Besides, mitochondrial oxidative stress was found in the fibroblasts of the patient by detecting MitoSOX, by either flow cytometry (P = 0.004) (Figure 4D) or the increase in signal intensity (in vivo imaging) in the patient's cells (P < 1 × 10−4) (Figure 4, E and F).
      All of these findings support the pathogenicity of p.K75E in the dynamin 1-like gene. The experimental study of this new disease-associated genetic variant suggests a novel relation between dynamin 1-like and heredity spastic paraparesis.

       Patient 7

      The patient was an 8-year–old boy with refractory epilepsy of neonatal onset, spastic tetraparesis (axial hypotonia and limb spasticity), pigmentary retinopathy, hyperlactacidemia, metabolic acidosis, delayed myelination, and trichorrhexis nodosa. After performing the exome sequencing, a de novo heterozygous variant c.2489T>G, p.L830R was found in MED13 (MIM ∗603,808) (Table 1).
      MED13 is a subunit of a multiprotein complex that plays an essential role in the RNA polymerase II–mediated transcription machinery required for regulating gene expression.
      • Napoli C.
      • Schiano C.
      • Soricelli A.
      Increasing evidence of pathogenic role of the mediator (MED) complex in the development of cardiovascular diseases.
      • Casamassimi A.
      • Napoli C.
      Mediator complexes and eukaryotic transcription regulation: an overview.
      • Calpena E.
      • Hervieu A.
      • Kaserer T.
      • Swagemakers S.M.A.
      • Goos J.A.C.
      • Popoola O.
      • Ortiz-Ruiz M.J.
      • Barbaro-Dieber T.
      • Bownass L.
      • Brilstra E.H.
      • Brimble E.
      • Foulds N.
      • Grebe T.A.
      • Harder A.V.E.
      • Lees M.M.
      • Monaghan K.G.
      • Newbury-Ecob R.A.
      • Ong K.R.
      • Osio D.
      • Reynoso Santos F.J.
      • Ruzhnikov M.R.Z.
      • Telegrafi A.
      • van Binsbergen E.
      • van Dooren M.F.
      • van der Spek P.J.
      • Blagg J.
      • Twigg S.R.F.
      • Mathijssen I.M.J.
      • Clarke P.A.
      • Wilkie A.O.M.
      Deciphering Developmental Disorders Study
      De novo missense substitutions in the gene encoding CDK8, a regulator of the mediator complex, cause a syndromic developmental disorder.
      Several studies performed in Saccharomyces cerevisiae show that MED13 has a role in the maintenance of the mitochondrial structure and the response to oxidative stress.
      • Khakhina S.
      • Cooper K.F.
      • Strich R.
      Med13p prevents mitochondrial fission and programmed cell death in yeast through nuclear retention of cyclin C.
      ,
      • Stieg D.C.
      • Willis S.D.
      • Ganesan V.
      • Ong K.L.
      • Scuorzo J.
      • Song M.
      • Grose J.
      • Strich R.
      • Cooper K.F.
      A complex molecular switch directs stress-induced cyclin C nuclear release through SCF(Grr1)-mediated degradation of Med13.
      Genetic variants in the MED13 gene have recently been associated with intellectual developmental disorder 61 (MIM number 618009).
      • Snijders Blok L.
      • Hiatt S.M.
      • Bowling K.M.
      • Prokop J.W.
      • Engel K.L.
      • Cochran J.N.
      • Bebin E.M.
      • Bijlsma E.K.
      • Ruivenkamp C.A.L.
      • Terhal P.
      • Simon M.E.H.
      • Smith R.
      • Hurst J.A.
      • McLaughlin H.
      • Person R.
      • Crunk A.
      • Wangler M.F.
      • Streff H.
      • Symonds J.D.
      • Zuberi S.M.
      • Elliott K.S.
      • Sanders V.R.
      • Masunga A.
      • Hopkin R.J.
      • Dubbs H.A.
      • Ortiz-Gonzalez X.R.
      • Pfundt R.
      • Brunner H.G.
      • Fisher S.E.
      • Kleefstra T.
      • Cooper G.M.
      DDD study
      De novo mutations in MED13, a component of the mediator complex, are associated with a novel neurodevelopmental disorder.
      The patient showed a complex phenotype with a discrete correlation with the reported phenotype and other different clinical characteristics (Table 1). p.L830R position is conserved across different species (data not shown), it is located between N- and C-terminal domains, and it was predicted to be damaging by in silico analyses (Figure 5A and Supplemental Table S2).
      Figure thumbnail gr5
      Figure 5Mediator complex subunit 13 (MED13) p.L830R variant changes the subcellular location of the protein and increases the mitochondrial oxidative stress. A: Top panel: MED13 domain structure (Uniprot: Q9UHV7) and the location of the variant in Patient 7 (red) and those reported in Human Gene Mutation Database (black). Bottom panel: A density plot of all MED13 missense variants reported in Genome Aggregation Database (gnomAD). B: The cellular expression pattern is exclusively nuclear in controls, whereas it is nuclear and cytoplasmic in the patient. C: Representative fluorescence intensity profiles of MED13 (green) and DAPI (nucleus; blue) in control (top panel) and patient (bottom panel) fibroblasts. The yellow lines are indicating the intensity profile regions, and the blue shaded regions are representing the nucleus profiles. D: Mean MitoSOX fluorescence intensity relative to mean controls (CT): 0.99 ± 0.04 versus Patient 7:1.42 ± 0.40; one-way analysis of variance test followed by Tukey post hoc multiple comparison test P = 0.05; number of independent experiments: 5] by flow cytometry. As a positive control (+) (CT+: 1.47 ± 0.17), cells were treated with 500 μmol/L H2O2. E: In vivo MitoSOX staining in control (top panels) and patient (bottom panels) fibroblasts and the corresponding scattering intensity color map. F: In vivo MitoSOX intensity quantification in control and patient fibroblasts [CT: 0.89 (0.36) versus Patient 7: 1.10 (0.54); one-way analysis of variance test followed by Tukey post hoc multiple comparison test P = 0.013]. As positive control, cells were treated with 2 mmol/L H2O2 (+) [CT+: 1.53 (0.27)]; images were taken from confocal optical sections that are representative of the group averages. N = 56 control fibroblasts (F); N = 31 patient fibroblasts (F); N = 36 positive control cells (F). ∗P < 0.05, ∗∗∗P < 0.001. Scale bars = 20 μm (B, C, and E). a.u., arbitrary units; r.u., relative units.
      The MED13 subcellular localization in patient and control fibroblasts was investigated. As expected, MED13 was located in the nuclei of fibroblasts; however, the patient also had MED13 delocalized in the cytoplasm (Figure 5B). DAPI staining confirmed the mislocalization of MED13 in the patient's cells (Figure 5C). In addition, nuclei abnormal substructures were observed in the patient's fibroblasts (Figure 5, B and C). A significant mitochondrial oxidative stress was also observed when compared with control cells by flow cytometry (P = 0.05) (Figure 5D) and using in vivo imaging (P = 0.013) (Figure 5, E and F).
      The functional analyses of p.L830R in fibroblasts showed both the alteration of MED13 cellular pattern and the increase in mitochondrial oxidative stress. These results and the clinical features suggest that p.L830R of MED13 is related to the complex encephalopathy intellectual developmental disorder 61 affecting the patient.

      Discussion

      The current study reports how the TDP, an in-house pipeline, can improve the genetic diagnosis yield of URD pediatric patients at the Sant Joan de Déu Children's Hospital. This is a key issue for URD patients and their families because genetic testing allows therapeutic planning and/or genetic counseling in these patients. Besides, genetic diagnosis in URD is the approach to make a precise etiologic diagnosis that will help to avoid further clinical examinations and laboratory tests to the patients.
      The TDP is based on comprehensive follow-up throughout the entire diagnostic process, embracing different imperative tasks—phenotype assessment, clinical genomics, functional genomics, and clinical validation—in a sequential pipeline (Figure 6). Therefore, the TDP is a circular procedure that begins with the clinical team's proposal of a patient in whom the diagnosis could not be reached despite in-depth phenotyping and cutting-edge genomic studies. Specifically, the TDP core team and clinical team evaluate candidate exome variants to prioritize the one to be studied on the basis of clinical phenotypic criteria, genetic inheritance, and biological effects. Regarding the predicted effect of the candidate variants, the TDP focuses on VUS and on likely pathogenic variants when the phenotype is complex; furthermore, the study of likely benign variants could be considered when the phenotype matches the genotype.
      Figure thumbnail gr6
      Figure 6Flow diagram showing the process of the in-house Translational Diagnostics Program (TDP). A: The clinical team proposes the patient study, providing clinical phenotype and genetic/genomic testing results, and discusses it with the TDP core team. B: When the case is accepted, the in silico reanalysis of the variant is performed. Literature review and data mining, variant classification, pathogenicity predictors, and three-dimensional (3D) prediction protein structure are performed to study and to categorize the candidate variant. C: Functional validation studies are performed by reliable molecular, cellular, and imaging assays related to specific protein function. After that, a final biological report is generated, integrating both in silico and experimental results. D: In the final step, the clinical team and TDP core team meet to evaluate all aspects of the final diagnostic decision. ∗Provided information: clinical description/phenotype and genetic/genomic testing results. Bioinformatic tools: pathogenicity predictors, 3D prediction protein structure, and literature review. Illustration generated with BioRender (https://biorender.com, last accessed September 7, 2020). HPO, Human Phenotype Ontology; LP, likely pathogenic; VUS, variant of uncertain significance.
      After going through the functional studies, the discussion with the referring physicians or the clinical team allows us to compare the results and make decisions about the diagnosis. This pipeline involves close collaborative work between physicians, clinical scientists, and research scientists in a single setting within the university hospital or the center of expertise.
      The TDP involves functional genomic studies that include both in silico analysis of the candidate variant and experimental studies to allow functional validation. First, the functional validation of patients' variants was performed using two different strategies: cloning cDNA or PCR-amplified genomic DNA or using fibroblasts from the patients. Second, the cellular expression pattern of the WT versus the patient's variant protein was compared using an appropriate machine-assisted image screening of confocal images, the essence of which is capturing the quantitative nature of the data, allowing a fast, reproducible, accurate, objective, and comparative evaluation. Third, by focusing on the particular function of the specific protein, a simple and optimal experimental approach for each variant was designed.
      Congruence between phenotype and genotype is an important issue that must be addressed. By using the TDP pipeline, including reanalysis, the pathogenic effect of the candidate variants was supported in six of the seven URD patients who were assessed. Admission of patients to the TDP helped the referring physicians in deciding on the etiologic diagnosis in their patients. Sometimes the incongruence was due to an incorrect genetic diagnosis (Patient 1), but at other times, there was partial correlation or incomplete phenotype between the genotype and the clinical phenotype reported in Online MIM (Patients 4, 5, and 6), or there was a complex or atypical phenotype that had not been previously reported (Patients 2 and 7).
      There are still challenges to reach a definitive diagnosis after the exome-based testing and functional validation of genetic variants. First, when a variant is identified in a non–disease-linked new gene, it is difficult to demonstrate causality having only one patient.
      • MacArthur D.G.
      • Manolio T.A.
      • Dimmock D.P.
      • Rehm H.L.
      • Shendure J.
      • Abecasis G.R.
      • Adams D.R.
      • Altman R.B.
      • Antonarakis S.E.
      • Ashley E.A.
      • Barrett J.C.
      • Biesecker L.G.
      • Conrad D.F.
      • Cooper G.M.
      • Cox N.J.
      • Daly M.J.
      • Gerstein M.B.
      • Goldstein D.B.
      • Hirschhorn J.N.
      • Leal S.M.
      • Pennacchio L.A.
      • Stamatoyannopoulos J.A.
      • Sunyaev S.R.
      • Valle D.
      • Voight B.F.
      • Winckler W.
      • Gunter C.
      Guidelines for investigating causality of sequence variants in human disease.
      If this is the case, the TDP could determine that patients' variant significantly alters the function of the gene and its product; however, other resources are necessary to reach the diagnosis of these patients. For instance, the websites GeneMatcher (https://www.genematcher.org, last accessed February 24, 2020; registration is required) and VariantMatcher (https://www.variantmatcher.org, last accessed February 24, 2020; registration is required) connect clinicians and researchers who share an interest in the same gene or variant, which would help to identify other patients carrying variants in the gene of interest.
      • Sobreira N.
      • Schiettecatte F.
      • Valle D.
      • Hamosh A.
      GeneMatcher: a matching tool for connecting investigators with an interest in the same gene.
      Second, as mentioned above, another limitation of TDP is that the selection of the patient's variant for functional evaluation relies on the clinical phenotype. Patients with URDs may show complex or atypical phenotypes; thus, the bias in variant selection could be detrimental to find out the genetic cause. Third, because most variants validated in this study were de novo, more functional studies for other types of variants are needed to expand the scope of application of the TDP.
      In any case, the current results show that TDP is possible and may lead to an in-house diagnosis in URD pediatric patients. These patients represent a great challenge for public health, the development of therapies, their medical care, and the quality of life of their families. It is necessary to incorporate experimental approaches, including cell and animal models,
      • Gall T.
      • Valkanas E.
      • Bello C.
      • Markello T.
      • Adams C.
      • Bone W.P.
      • et al.
      Defining disease, diagnosis, and translational medicine within a Homeostatic Perturbation Paradigm: the National Institutes of Health undiagnosed diseases program experience.
      as part of the diagnostic activity, and it is a necessary step that hospitals could take to offer a diagnosis when a VUS or a clinical incongruence is the result of exome test. To perform functional validation studies in hospitals, it would be necessary to incorporate an experimental laboratory as a translational tool in clinical medicine. Functional genomics and biology of genomic variants in URD patients should be progressively incorporated and funded in teaching hospitals via promoting in-house Translational Diagnostics Programs. Although this can be a challenging task and requires specific attention, the current study shows that it is possible. Besides, the TDP would provide a multidisciplinary in-house research platform that bridges the gap between phenotype and genotype that could help to ascertain the phenotypic expansion of undiagnosed and rare diseases.
      In summary, the in-house TDP is viable as a global diagnostic approach. This strategy shows how the integration of functional testing of genetic variants in close combination with genomic medicine and a thorough clinical assessment may be an effective method for an accurate and cost-effective diagnosis in a proportion of patients with URD.

      Acknowledgments

      We thank the patients and their families for participating in the study; Johanna Troya for the excellent technical assistance; the Confocal and Super-Resolution Microscopy Unit (Sant Joan de Déu Children's Hospital) for confocal microscopy studies; and Biobanc de l’Hospital Infantil Sant Joan de Déu per a la Investigació, integrated into the Spanish Biobank Network of the Instituto de Salud Carlos III, for the sample and data procurement.

      Authors Contributions

      F.P. and J.H. conceptualized and designed the study; J.H. and F.P. supervised the study; J.H. and F.P. provided administrative, technical, or material support; F.P. and J.H. obtained funding; J.P., M.R.-S., D.N.-d.B., C.O., A.A., M.O.-L., M.R., M.U., L.V.d.V., J.R.-C., C.F., R.B., A.N., J.H., and F.P. acquired, analyzed, or interpreted the data; J.P. and M.R.-S. performed statistical analysis; J.P., M.R.-S., J.H., and F.P. drafted the manuscript; and all authors critically revised the manuscript for important intellectual content. F.P. and J.H. had full access to all data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

      Supplemental Data

      • Supplemental Figure S1

        Scheme of the automated image analysis workflow for three-dimensional (3D) image segmentation of nuclear punctate pattern in green fluorescent protein (GFP)– SWI/SNF related matrix-associated actin-dependent regulator of chromatin subfamily A member 4 (SMARCA4) and GFP– zinc finger E-box binding homeobox 2 (ZEB2) transfected cells. A: Maximum intensity projection of an example confocal image of an HEK293T cell overexpressing GFP-ZEB2 (green channel; protein punctate pattern) and stained with DAPI (blue channel; nuclei). B: Nuclei mask estimated by contrast enhancement followed by Otsu binarization and labeling of green channel (A). C: Imposing nuclei mask on green channel (A). D and E: Results of Gaussian Mixture Model (GMM) algorithm on C. D: Histogram of C and gaussian distributions (solid lines) of the five GMM components. E: The corresponding reconstructed image with the five components. Component 5 represents the gaussian with the highest image intensity, corresponding to a nuclear punctate pattern (green). F: Volume rendered view of the extracted protein punctate pattern and nuclei for 3D image.

      • Supplemental Figure S2

        A splicing error in the GATAD2B gene causes intellectual disability in Patient 4. A: Splicing patterns of GATAD2BWT and c.1216+2T>C-GATAD2B were detected by RT-PCR, and products are shown in the red boxed areas through the agarose gel electrophoresis. Lanes 1 and 2: empty vector (pSPL3); lanes 3 and 4, GATAD2BWT; and lanes 5 and 6, c.1216+2T>C-GATAD2B. B: Schematic diagram of exons 7 to 8 in the GATAD2B gene shows the effect of the c.1216+2T>C on mRNA splicing, and the consequent frameshift variant results in a premature codon stop in the protein.

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