RESEARCH ARTICLE OPEN ACCESS Diagnosis of Genetic White Matter Disorders by Singleton Whole-Exome and Genome Sequencing Using Interactome-Driven Prioritization Agatha Schlüter, PhD,* Agustı́ Rodrı́guez-Palmero, MD,* Edgard Verdura, PhD,* Correspondence Valentina Vélez-Santamarı́a, MD, Montserrat Ruiz, PhD, Stéphane Fourcade, PhD, Laura Planas-Serra, MSc, Dr. Pujol Juan José Martı́nez, MSc, Cristina Guilera, MSc, Marisa Girós, PhD, Rafael Artuch, MD, Marı́a Eugenia Yoldi, MD, apujol@idibell.cat Mar O’Callaghan, MD, PhD, Angels Garcı́a-Cazorla, MD, PhD, Judith Armstrong, PhD, Itxaso Marti, MD, PhD, Elisabet Mondragón Rezola, MD, PhD, Claire Redin, PhD, Jean Louis Mandel, MD, PhD, David Conejo, MD, Concepción Sierra-Córcoles, MD, Sergi Beltrán, PhD, Marta Gut, PhD, Elida Vázquez, MD, Mireia del Toro, MD, PhD, Mónica Troncoso, MD, PhD, Luis A. Pérez-Jurado, MD, PhD, Luis G. Gutiérrez-Solana, MD, PhD, Adolfo López de Munain, MD, PhD, Carlos Casasnovas, MD, PhD, Sergio Aguilera-Albesa, MD, PhD, Alfons Macaya, MD, PhD, and Aurora Pujol, MD, PhD, on behalf of the GWMD working group ® Neurology 2022;98:e912-e923. doi:10.1212/WNL.0000000000013278 Abstract Background and Objectives Genetic white matter disorders (GWMD) are of heterogeneous origin, with >100 causal genes identified to date. Classic targeted approaches achieve a molecular diagnosis in only half of all patients. We aimed to determine the clinical utility of singleton whole-exome sequencing and whole- genome sequencing (sWES-WGS) interpreted with a phenotype- and interactome-driven prioriti- zation algorithm to diagnose GWMD while identifying novel phenotypes and candidate genes. Methods A case series of patients of all ages with undiagnosed GWMD despite extensive standard-of-care paraclinical studies were recruited between April 2017 and December 2019 in a collaborative study at the Bellvitge Biomedical Research Institute (IDIBELL) and neurology units of tertiary Spanish hospitals. We ran sWES and WGS and applied our interactome-prioritization algorithm based on the network expansion of a seed group of GWMD-related genes derived from the Human Phenotype Ontology terms of each patient. Results We evaluated 126 patients (101 children and 25 adults) with ages ranging from 1 month to 74 years. We obtained a first molecular diagnosis by singleton WES in 59% of cases, which increased to 68% after annual reanalysis, and reached 72% after WGS was performed in 16 of *These authors contributed equally to this work. From the Neurometabolic Diseases Laboratory (A.S., A.R.-P., E. Verdura, V.V.-S., M.R., S.F., L.P.-S., J.J.M., C.G., C.C., A.P.), Bellvitge Biomedical Research Institute (IDIBELL); Instituto de Salud Carlos III (ISCIII) (A.S., A.R.-P., E. Verdura, M.R., S.F., L.P.-S., J.J.M., C.G., R.A., M.O., A.G.-C., J.A., M.d.T., L.A.P.-J., A.M., A.P.) and Secció d’Errors Congènits del Metabolisme–IBC, Servei de Bioquı́mica i Genètica Molecular, Hospital Clı́nic, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) (M. Girós), Center for Biomedical Research on Rare Diseases (CIBERER); Pediatric Neurology Unit, Department of Pediatrics, Hospital Universitari Germans Trias i Pujol (A.R.-P.), and Pediatric Neurology Research Group, Vall d’Hebron Research Institute (A.M.), and Pediatric Neurology Department, Vall d’Hebron University Hospital (M.d.T., A.M.), Universitat Autònoma de Barcelona; Neuromuscular Unit, Neurology Department (V.V.-S., C.C.), Hospital Universitari de Bellvitge and Hospitalet de Llobregat, Universitat de Barcelona; Institut de Recerca Pediàtrica (R.A., M.O., A.G.-C.) and Molecular and Genetics Medicine Section (J.A.), Hospital Sant Joan de Déu (IRP-HSJD), Barcelona; Pediatric Neurology Unit, Department of Pediatrics (M.E.Y., S.A.-A.), Navarra Health Service, Navarrabiomed Research Foundation; Departments of Neuropediatrics (I.M.) and Neurology (E.M.R., A.L.d.M.), Hospital Universitario Donostia; Biodonostia Health Research Institute (Biodonostia HRI) (I.M., E.M.R., A.L.d.M.); University of the Basque Country (UPV-EHU) (I.M., A.L.d.M.), San Sebastian; Centro de Investigación Biomédica en Red para Enfermedades Neurodegenerativas (CIBERNED) (I.M., E.M.R., A.L.d.M.), Carlos III Health Institute, Madrid, Spain; Département de Médecine Translationnelle et Neurogénétique (C.R., J.L.M.), IGBMC, CNRS UMR 7104/INSERM U964/Université de Strasbourg, Illkirch; Laboratoire de Diagnostic Génétique (J.L.M.), Hôpitaux Universitaires de Strasbourg; Chaire de Génétique Humaine (J.L.M.), Collège de France, Illkirch; Complejo Asistencial Universitario de Burgos (D.C.); Department of Paediatric Neurology (C.S.-C.), Complejo Hospitalario Jaén; CNAG-CRG, Centre for Genomic Regulation (CRG) (S.B., M. Gut), Barcelona Institute of Science and Technology (BIST); Department of Pediatric Radiology (E. Vázquez), Hospital Materno-Infantil Vall d’Hebrón, Barcelona, Spain; Pediatric Neurology (M.T.), Hospital Clı́nico San Borja Arriarán, Central Campus Universidad de Chile; Genetics Service (L.A.P.-J.), Hospital del Mar Research Institute (IMIM); Department of Experimental and Health Sciences (L.A.P.-J.), Universitat Pompeu Fabra, Barcelona; Department of Paediatric Neurology (L.G.G.-S.), Children’s University Hospital Niño Jesús, Madrid; and Catalan Institution of Research and Advanced Studies (ICREA) (A.P.), Barcelona, Spain. GWMD working group coinvestigators are listed in Appendix 2 at the end of the article. Go to Neurology.org/N for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article. The Article Processing Charge was funded by the authors. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND), which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. e912 Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. Glossary aCGH = array comparative genomic hybridization; ACMG = American College of Medical Genetics and Genomics; CNV = copy number variant; GO = Gene Ontology; GWMD = genetic white matter disorders; HPO = Human Phenotype Ontology; NGS = next-generation sequencing; PBMC = peripheral blood mononuclear cells; sWES = singleton whole-exome sequencing; VUS = variants of uncertain significance; WES = whole-exome sequencing; WGS = whole-genome sequencing. the remaining negative cases. We identified variants in 57 different genes among 91 diagnosed cases, with the most frequent being RNASEH2B, EIF2B5, POLR3A, and PLP1, and a dual diagnosis underlying complex phenotypes in 6 families, under- scoring the importance of genomic analysis to solve these cases. We discovered 9 candidate genes causing novel diseases and propose additional putative novel candidate genes for yet-to-be discovered GWMD. Discussion Our strategy enables a high diagnostic yield and is a good alternative to trio WES/WGS for GWMD. It shortens the time to diagnosis compared to the classical targeted approach, thus optimizing appropriate management. Furthermore, the interactome- driven prioritization pipeline enables the discovery of novel disease-causing genes and phenotypes, and predicts novel putative candidate genes, shedding light on etiopathogenic mechanisms that are pivotal for myelin generation and maintenance. The advent of next-generation sequencing (NGS) in clinical ap- to December 2019. They were pediatric and adult patients with plications (especially targeted sequencing panels and whole-exome clinical and MRI patterns consistent with a GWMD defined as sequencing [WES]) has increased the diagnostic yield of hereditary symmetrical, confluent white matter involvement, in absence of neurologic diseases with high genetic heterogeneity and low mu- perinatal or vascular complications or suggestive of an autoim- tational burden.1-4 Genetic white matter disorders (GWMD) are a mune process. A molecular diagnosis could not be established by heterogeneous group of diseases with an MRI pattern suggestive of the referring physicians despite applying standard-of-care para- a genetic etiology, encompassing both leukodystrophies and ge- clinical studies (including mainly MRI, metabolic, neurophysio- netic leukoencephalopathies.5,6 The classic combined MRI, bio- logic, and genetic studies such as array comparative genomic chemical, and target gene-based approach leaves approximately half hybridization [aCGH], targeted Sanger sequencing, or NGS gene of patients with GWMD without a genetic diagnosis.7-10 In these panels). Clinical information, MRIs, and samples were collected undiagnosed cases, trio WES followed by whole-genome se- by the Neurometabolic Diseases laboratory of Bellvitge Bio- quencing (WGS) allowed a diagnosis in 62% of the cases in a medical Research Institute (IDIBELL) and although strict filtering recent study on a cohort of 71 pediatric patients.4,11 of cases by a neuroradiologist focused on leukodystrophies was not performed, re-evaluation by a team of experienced child and Despite continuous advances, the analysis of NGS data poses the adult neurologists and neuroradiologists under the URD-Cat challenge of variant selection and interpretation, which is espe- initiative for neurologic undiagnosed disorders was made be- cially relevant for singleton exomes, or when there is no possibility fore inclusion. This clinical team was driving the diagnostic to perform family cosegregation/linkage studies. WES genotypes process and exchanged information with the referring clinicians yield approximately 500–1,000 variants per individual, after fil- when required, both pre- and postvariant calling. MRI pattern tering by frequency below 1% and deleteriousness. Hence, was classified according to previous published articles.18,19 establishing a prioritization system based on the patient’s phenotype12,13 or gene interaction networks14-17 may prove useful Standard Protocol Approvals, Registrations, to improve rapid selection of candidate variants. and Patient Consents Written informed consent for genetic testing and publication We describe 126 families with patients displaying GWMD ana- was obtained by the parents or legal guardians of each patient lyzed by singleton WES–WGS (sWES-WGS). We interpret ge- at each site. The ethics committee of IDIBELL approved the netic data by integrating standardized phenotypic data in Human study with CEIC PR076/14. Phenotype Ontology (HPO) terms, as well as interaction and functional network information to facilitate the identification of See Supplemental Methods for NGS, variant calling and clas- causal genes and enable novel disease-gene discovery. sification, functional validation, and the interactome-driven gene prioritization method. Methods Data Availability Patient Recruitment Data not provided in the article because of space limitations Study participants were identified at child and adult neurology may be shared (anonymized) at the request of any qualified units from several tertiary hospitals around Spain from April 2017 investigator for purposes of replicating procedures and results. Neurology.org/N Neurology | Volume 98, Number 9 | March 1, 2022 e913 Results Table 1 Main Clinical Features of the 126 Index Cases Clinical Data N % We recruited 126 families with an undiagnosed GWMD. Based on cranial MRI findings, 86 cases (68%) were classi- Sex fied as non-hypomyelinating, whereas 40 of the cases Female 50 40 showed a hypomyelinating picture. The index cases included Male 76 60 50 female and 76 male patients, with ages ranging from 1 month to 74 years (median 10.3 years). The age at onset Age at onset, y ranged from the first month of life to 72 years (median 1 <3 86 68 year); age was lower than 18 years in 101 cases (80%) and higher in 25. The median evolution of disease before WES 3–18 15 12 testing was 6.3 years (1 month–34 years), and it was longer >18 25 20 than 10 years in 37% of patients. Consanguinity was repor- Consanguinity 18 14 ted in 18 families (14%). Clinical characteristics, MRI pat- terns, studies performed, and sWES-WGS results of every Main clinical features patient are summarized in Table 1 and eTable 1, links.lww. Motor symptoms com/WNL/B741. Pyramidal 94 74 Diagnostic Yield of WES and WGS in a Cohort of Extrapyramidal 34 27 Patients With GWMD Hypotonia 15 12 All the patients were initially studied by WES. The first diagnostic rate was 74/126 (59%), which increased to 86/ GDD/ID/cognitive decline 91 72 126 cases (68%) after a subsequent reanalysis 12–24 ASD/behavior/psychiatric manifestations 21 16 months later. The reasons for this increase in yield were Cerebellar 42 33 attributed to variants not initially identified because of fil- tering issues (3 cases); variants located in noncoding re- Epilepsy 36 28 gions (3 cases); pipeline update/technical issues (2 cases); Ophthalmologic 55 43 and newly reported disease-causing genes (3 cases). Next, Predominant MRI pattern we performed WGS in 16 of the remaining 38 negative cases, prioritized by availability of DNA from proband and Hypomyelination 40 31 parents, and solved 5 more cases involving intronic variants Nonhypomyelination or 39 UTR variants. Periventricular 49 39 This approach allowed us to identify 9 novel candidate genes, Diffuse 19 15 for which we gathered additional patients with very similar Frontal 12 9 phenotypes through collaboration with international Leuko- dystrophy Reference Centers and the platform Gene- Multifocal 3 2 Matcher.20 We functionally validated and reported 2 novel Parieto-occipital 2 1 disease genes (DEGS121 and PI4KA22) in 2 families each, whereas the other 5 validated cases are in preparation. Two Cerebellar 2 1 more candidate genes are awaiting additional patients while Complementary examinations functional studies are ongoing. Metabolic studies 116 92 Overall, we obtained a positive genetic diagnosis in 91 out of Neurophysiologic studies 99 78 126 GWMD cases (72%) (Figure 1, eFigure 1, and eTables 1 Karyotype/aCGH/NGS panel 65 51 and 2, links.lww.com/WNL/B741). The diagnostic rates by Targeted genetic studies 65 51 age group were 77% in those with onset before 3 years, 73% in those with onset between 3 and 18 years, and 60% in the Total cases 126 adult-onset group (Figure 1D). Considering the MRI pat- Abbreviations: aCGH = array comparative genomic hybridization; ASD = tern, the diagnostic rate was 57/86 (66%) in the non- autism spectrum disorder; GDD = global developmental delay; ID = in- hypomyelinating group and 34/40 (85%) in those with tellectual disability; NGS = next-generation sequencing. hypomyelination. Following the classification proposed in Vanderver et al.,5 46 (51%) of the diagnosed families had variants in genes associated with “canonical or classic leu- For the 33 cases that remained undiagnosed after WES/WGS, kodystrophies,” and the remaining 45 (49%) had variants in we noted a trend towards adulthood onset (30% of unsolved genes associated with “genetic leukoencephalopathies.” cases were adults vs 16% of adults in solved cases), cystic lesions e914 Neurology | Volume 98, Number 9 | March 1, 2022 Neurology.org/N Figure 1 Diagnostic Process Diagram and Diagnostic Yield (A) Number of cases included in the study and diagnostic process. (B) Global, whole-exome se- quencing (WES), and whole-genome sequencing (WGS) diagnostic yield. (C) Percentage of di- agnosis in the first WES analysis, obtained by WES reanalysis and by WGS. (D) Diagnostic percentage according to age. on MRI (12% of undiagnosed cases vs 5% in solved cases), and 1 gene (see Figure 2, eTable 4, and eResults for clinical absence of consanguinity (97% nonconsanguineous in un- summaries). Moreover, several cases with variants in the solved vs 82% in solved cases). classical spastic paraplegia genes SPG11 and CYP2U1 pre- sented clear white matter involvement, as shown in Figure 3. Although genetic heterogeneity in our cohort was very high, some genes were found to be more frequently mutated, in- According to the American College of Medical Genetics and cluding EIF2B5, POLR3A, and RNASEH2B, in 6 families Genomics (ACMG)/Association for Molecular Pathology each, and PLP1 variants in 5 families (eTable 3, links.lww. guidelines,23-25 86 out of the 91 diagnosed cases were classi- com/WNL/B741). New phenotypes were identified in 2 fied as definitively diagnosed with pathogenic or likely path- cases, atypical forms of presentation in 7, and 6 more cases ogenic variants. In 14 of these 86 cases, the functional were complex, blended phenotypes with variants in more than validation converted variants of uncertain significance (VUS) Neurology.org/N Neurology | Volume 98, Number 9 | March 1, 2022 e915 Figure 2 MRI Findings in Patients With New/Atypical and Blended Phenotypes (A) LNF-48, 5 years. PARS2; p.Arg186Gly/ p.Lys187Arg (COMP HTZ). Periatrial white matter (WM) hyperintensity (red arrows) with frontal-parietal atrophy, ven- triculomegaly, and thin corpus callosum (arrowheads) (axial T2 fluid-attenuated inversion recovery [FLAIR], sagittal T1- weighted images). (B) LNF-29, 10 months. PNPT1; p.Ala507Ser (HMZ). Bilateral per- iatrial and temporal anterior subcortical WM hyperintensities (red arrows) with temporal cystic lesions (arrowheads) (ax- ial T2 and coronal T2 FLAIR-weighted im- ages). (C) LNF-47, 2 years. POLR3A; c.1771- 7C > G/p.Leu1129 (COMP HTZ). Optic ra- diation mild WM hyperintensity (red ar- rows), striatal atrophy and hyperintensity (arrowheads), and superior cerebellar peduncles hyperintense signal (asterisks) (axial T2 images). (D) LNF-85, 48 years. PSEN1; p.Thr350Ile (HTZ). MRI showed diffuse WM hyperintensities (red arrows) with corpus callosum and cortical atrophy (arrowheads) (axial T2 and sagittal T1 FLAIR images). (E) LNF-88, 13 years. GFPT1; p.Asp296Val (HMZ). Axial T2 hyper- intensities involving deep cerebral WM (red arrows), cerebellar peduncles (white arrows), and middle blade of corpus cal- losum (arrowheads), sparing subcortical WM (axial T2 and sagittal T1-weighted images). (F) LNF-114, 5 months. SCN8A; p.Val409Met (HTZ). Important myelina- tion delay, thin corpus callosum and signs of cerebral and cerebellar atrophy (axial and sagittal T1-weighted images). (G) SPG- 25, 44 years. SOX10; p.Tyr83Asp (HTZ). Periventricular WM signal abnormality, sparing U fibers (red arrows), and thin isthmus of the corpus callosum (arrow- head) (axial T2-FLAIR and sagittal T1 weighted images). (H) LNF-40.0, 13 years. CYP2U1; p.Arg178Thr (HMZ) and LNF-40.4, 15 years. PAH; p.Thr380Met (HMZ). Peri- ventricular WM hyperintensities (red ar- rows) (axial T2 weighted images). (I) LNF- 56, 15 years. POLR3A; p.Cys724Tyr/ p.Pro705Ala (COMP HTZ) and CACNA1A; p.Tyr546Ter (HTZ). Periventricular sym- metric heterogeneous WM hyper- intensities (red arrows) and hypointensity in globus pallidus (arrowheads), thalamic anterolateral nuclei (asterisks), optic radi- ations, and pyramidal tracts, with mild atrophy of the cerebellar superior vermis (white arrow) (axial T2 and sagittal T1- weighted images). (J) LNF-89.3, 15 years. CP; p.Gly868GlufsTer26 (HMZ)/NDUFS1; p.Ser701Asn (HTZ). Periventricular sym- metric T2 hyperintensity with cystic de- generation and pyramidal tract involvement (red arrows) and corpus cal- losum atrophy. Accumulation of para- magnetic material in the substantia nigra (asterisks) (axial T2-FLAIR and axial sus- ceptibility-weighted imaging). into pathogenic or likely pathogenic variants. We analyzed the intronic variant in EIF2B5 (c.1156 + 13 G > A), which led to a effect of 8 variants on splicing using cDNA sequencing (from mild form of ovarioleukodystrophy.26 We also performed tar- RNA derived from peripheral blood mononuclear cells geted lipidomics, which proved a pathogenic role for variants in [PBMC] or fibroblasts) or minigene splicing assay26 (n = 3). genes related to lipid metabolism such as ACER3, DEGS1,21 and The minigene assays were instrumental to confirm the path- PI4KA,22 together with qRT-PCR, Western blots, or immuno- ogenic role of an intronic variant in MLC1 (c.597 + 37C > G), fluorescence as required (eTable 5, links.lww.com/WNL/ a gene not expressed in PBMC or fibroblasts, and another B741). In other cases that were not amenable to experimental e916 Neurology | Volume 98, Number 9 | March 1, 2022 Neurology.org/N Figure 3 MRI of Selected Cases With Variants in Hereditary Spastic Paraparesis Genes and White Matter Involvement T2 hyperintensity in the bilateral peri- ventricular white matter. (A, D) Axial T2 images. (B, C) Axial T2 fluid-attenuated inversion recovery images. validation (5 remaining until 91), we reported out VUS highly Management Implications of a compatible with the clinical and MRI picture and segregation Positive Diagnosis and were considered solved by expert assessment. Diagnosis allowed us to improve clinical management in 29 cases (eTable 1, links.lww.com/WNL/B741). In 22 of them, Among the 91 cases diagnosed, 60 harbored biallelic mutations it led to the consideration of a specific treatment option for (31 homozygous; 16 of them in consanguineous families), 22 the disease, such as hematopoietic stem cell transplant for in an autosomal dominant mode (12 de novo), and 7 X-linked Krabbe disease (LNF-18, SPG-72) and hereditary diffuse (5 of them de novo), whereas 2 cases had mutations in more leukoencephalopathy with spheroids (LNF-6, LNF-16, LNF- than 1 gene with different inheritance patterns (1 with auto- 70, LMSR), dietary management for phenylketonuria (LNF- somal dominant and autosomal recessive inheritance; 1 auto- 40.4), or pyridostigmine for myasthenic syndrome caused by somal dominant and X-linked) (eFigure 1, links.lww.com/ GFPT1 (LNF-88). In other cases, diagnosis led to an im- WNL/B741). Segregation by Sanger was performed in all but 8 provement in patient follow-up, such as screening for the patients due to the unavailability of parental samples. We appearance of tumors in PTEN (LNF-109) or preventative found several variants more than once in our patients: the measures for head trauma and infections in patients with RNASEH2B p.Ala177Thr variant in 6 independent families vanishing white matter disease. Finally, we identified and (frequency: 0.001306 in gnomAD [v2.1.1])27; the EIF2B5 reported incidental findings (according to Kalia et al.32) in 2 p.Leu106Phe variant (frequency: 0.00004943 in gnomAD patients: a pathogenic variant in the MYBPC3 gene [v2.1.1]) in 2 independent families and the EIF2B5 p.Arg113His (p.Trp792ValfsTer41) in SPG-14 and in SMAD3 (Loeys- variant (frequency: 0.00001647 in gnomAD [v2.1.1])28 in 5 Dietz syndrome) (p.Val363ThrfsTer3) in LNF-48. In both families; and the SPG11 frameshift variant p.Met245Valfs*2 cases, cardiologic follow-up will ensue, with cranial magnetic twice independently (frequency: 0.0001071 in gnomAD resonance angiography and orthopedic controls in the second [v2.1.1]).29 case. In addition to single-nucleotide variants and indels, we GWMD Expanded Network detected a pathogenic copy number variant (CNV) in 4 cases Starting with a seed list of 843 genes that are causative or (4.4%) by WES (eTable 6, links.lww.com/WNL/B741): a associated with GWMD according to OMIM, we built a 6930 Kb 1p36 heterozygous deletion in LNF-36 and validated protein interactome network based on the principle that by aCGH (eFigure 2), a 117 Kb duplication in 5q including physical and functional interacting genes may account for HNRNPH1 and RUFY1 genes in LNF-105,30 a 60.4 Kb du- related biological processes and cause similar diseases. We plication containing LMNB1 in LNF-34, and a 21.3 Kb ho- developed a prioritization method that identifies the most mozygous deletion encompassing TANG O 2 in LNF-97.31 likely disease-causing genes associated with each patient’s We validated the last 3 CNVs by Q-PCR (eTable 6). We also phenotype (standardized in HPO33 terms) using a global identified a uniparental disomy of maternal origin of chro- protein human interactome network built with functional and mosome 6 in LNF-68, harboring a loss-of-function homozy- physical interactions, represented by 20.146 genes (see Sup- gous variant in a novel candidate gene that was highly ranked plemental Methods and Results [eTables 8–11, links.lww. by our prioritization method (in preparation). com/WNL/B741]).14 We applied this prioritization tool to the respective clinical description in HPOs of the 843 proteins An added value of our study is that 73 of the 123 identified associated with GWMD to build a GWMD interactome or variants had not been previously reported in the literature, expanded network, resulting in 1,530 proteins and 18,288 Human Gene Mutation Database (public access), or ClinVar interactions (Figure 4). To evaluate the functional signature databases (eTable 7, links.lww.com/WNL/B741). of these 1,530 proteins, we performed an enrichment analysis Neurology.org/N Neurology | Volume 98, Number 9 | March 1, 2022 e917 Figure 4 GWMD Expanded Interactome (A) The genetic white matter disorder (GWMD) seeds + expanded network was generated by the network prioritization tool, resulting in 1,530 proteins. The seed genes known to be mutated in GWMD are shown in yellow circles, disease genes not previously associated with GWMD are shown in green, and new GWMD candi- dates are shown in blue. Comparison of statistical connectivity strength of the GWMD expanded network with 1,000 permutations of randomly selected pro- teins from the global human network. Red dots denote the value of the metric on the GWMD expanded network con- stituted by 1,530 proteins. Box and whis- ker plots denote matched null distributions (i.e., 1,000 permutations). (D, left) Within-group edge count (i.e., num- ber of edges between members of the query set). (D, right) distance is the aver- age path length in the network obtained by calculating the shortest paths between all pairs of proteins. (B–E) Zoom in the network for specific putative candidates as illustrative example of the GWMD ex- panded network potentiality. (B) Delta 4- desaturase, sphingolipid 1 (DEGS1); (C) phosphatidylinositol 4-kinase alpha (PI4KA); (D) mitochondrial ribosome-asso- ciated GTPase 1 (MTG1); and (E) potas- sium voltage-gated channel subfamily A regulatory beta subunit 2 (KCNAB2) pro- tein. *Recently associated with leukodys- trophy. White matter expanded network available in NDEx repository at public. ndexbio.org/#/network/fd5fc166-9ecc- 11eb-9e72-0ac135e8bacf? accesskey=a75ac048b59aca2c9310c04a6f1d96ea34052231d9204f284c5e1d420fc2ca26 of the Gene Ontology (GO) terms (eTables 8–10). In line purine metabolism pathway with RNA polymerases I and III with the hypothesis that genes associated with similar dis- (e.g., RNA polymerase III subunit A; POLR3A). Among the eases may converge towards specific biological pathways, 1,530 proteins, we identified (besides the 843 GWMD seed major modules emerged, which are involved in the patho- proteins) (1) 587 proteins associated with disease but not yet physiology of GWMD abnormalities: (1) the mitochon- with GWMD and (2) 100 novel candidates that were not pre- drial oxidative phosphorylation (OXPHOS) system (e.g., viously associated with GWMD or any disease (eTable 11). Of NADH-ubiquinone oxidoreductase Fe-S protein 1; particular interest among these last 100 proteins, we highlight NDUFS1), (2) the lysosome (e.g., the galactosylceramidase (1) the delta 4-desaturase sphingolipid 1 (DEGS1) in patients enzyme; GALC), (3) the peroxisome (peroxins) (e.g., with LNF-41 and LNF-42 (Figure 4B), causing hypomyelinating peroxin 6; PEX6), (4) the metabolism of ribonucleotides leukodystrophy 18 (HLD18, OMIM #615843),21 (2) the (e.g., ribonuclease H2 subunit B; RNASEH2B), and (5) the phosphatidylinositol 4-kinase alpha (PI4KA) recently associated e918 Neurology | Volume 98, Number 9 | March 1, 2022 Neurology.org/N with leukodystrophy and identified in patients LNF-107 and structural resources needed to optimize the cost–benefit VH-322,34 (Figure 4C), (3) the mitochondrial ribosome- ratio in every setting.37 associated GTPase 1 (MTG1) that plays a role in the regula- tion of mitochondrial ribosome assembly and translational ac- Our study enabled identification of disorders caused by genes tivity (Figure 4D), and (4) the potassium voltage-gated channel rarely associated with white matter involvement (PTEN, subfamily A regulatory beta subunit 2 protein (KCNAB2) GFPT1,40 CAPN141), the diagnosis of certain cases with (Figure 4E). While Genematcher was key to find additional cases atypical presentation (SCN8A,42 SOX10,43 POLR3A44), the for DEGS1 and PI4KA deficiencies, matches for putative can- characterization of families harboring variants in more than 1 didates such as MTG1 and KCNAB2 are yet to be found. causative gene with blended phenotypes, the identification of genes only recently associated with disease (i.e., PYCR245 or TMEM63A46), and the discovery of novel disease entities and candidate genes, which constitute important advantages over Discussion disease-specific panels or clinical exomes (see Figure 2, eTables This is the largest series of patients of GWMD studied by 1 and 4, and eResults for clinical summaries, links.lww.com/ WES/WGS reported to date and the first one including WNL/B741). Furthermore, in 9 families (10%), we identified patients of all ages offering a global vision of the GWMD variants in genes associated primarily with hereditary spastic diagnosis throughout life. We have proven the utility of paraplegia (SPG11, SPG7, SPAST, DDHD2, CAPN1, sWES-WGS combined with a phenotypic and interactome- CYP2U1) (Figure 3), underscoring the notion of a continuum driven prioritization method, reaching a diagnostic yield of of clinical spectrum, similarly to X-adrenoleukodystrophy, 72%. These results are superior to those recently reported PMD/SPG2, metachromatic dystrophy, or Alexander dis- by a reference genetic diagnostics company on 541 cases, ease.47 Moreover, half of the genes identified in this cohort are with a WES diagnostic yield for leukodystrophies of 32% linked to genetic leukoencephalopathies, not classically con- (including trio and singleton cases) and 22.6% when con- sidered leukodystrophy genes. Because many of these genes are sidering proband-only cases.35 In another report including not included in multigene panels, the WES/WGS-derived di- 100 patients with adult-onset leukodystrophy, the di- agnostic yield would be expected to be superior. As an example, agnostic rate was 26%.36 Our results are slightly better than the diagnostic yield of a leukodystrophies disease gene panel those reported in another study including 71 pediatric containing 134 genes was 46% in a recent study.48 cases.4,11 In a report by Vanderver et al.,4 a first trio WES allowed a definite diagnosis in 42% of cases, while in a Our report also exemplifies the genetic heterogeneity of second phase of the study11 including the 41 negative cases, GWMD (57 different genes among the 91 diagnosed cases), a molecular diagnosis was established in 9 more cases by which supports that WES/WGS should be considered a first- reanalysis and in 5 cases using WGS, representing 17% and tier diagnostic test when the clinical presentation and MRI 12%, respectively. We were able to increase diagnostic yield pattern do not point to a specific diagnosis, in agreement with 24% (12/50) by WES reanalysis and 31% (5/16) by sin- the recent randomized clinical trial on pediatric patients with gleton WGS. However, in the referred study, previous ex- GWMD.6 This would allow for gaining time, which is fun- pert filtering of cases led to a lower proportion of well- damental to establish appropriate genetic counseling and known or canonical leukodystrophy genes in their cohort4 specific treatment when available, usually indicated only in the in comparison to ours (36% vs 51% in our cohort), which early stages of these very severe diseases. On average, our may have an effect on our higher diagnostic yield. Com- patients reached a positive diagnosis at 6 months after study parison between the results of these cohorts is difficult inclusion, which stood in sharp contrast with the previous because of different study protocols and target population, diagnostic delay of 10 years of disease evolution on average. which comprised 20% adult GWMD in our case vs a Hence, reducing multiple unnecessary examinations with a pediatric-only population in Vanderver et al.4 It is likely low cost–benefit ratio, as is the case for some metabolic that the use of trio WES/WGS would have improved our studies in the context of nonspecific neuroimaging, would diagnostic yields, and certainly would have ameliorated entail substantial economic savings for the health care system, turnaround times. Because of the very late implantation of which together with the continued lowering of WES/WGS clinical exomes (instead of WES) in our health care system costs makes a clear case for the adoption of at least WES if not and limited research funding resources, we chose to apply WGS as a first-tier test for undiagnosed GWMD. However, singleton WES to help as many families as possible, as trio first-line metabolic tests that may identify potentially treatable studies may cost double37,38 to 3 times higher in our health cases should always be considered, prior to or in parallel with care system. The use of trio WES/WGS is recommended WES/WGS. when urgent diagnosis is required in intensive care unit settings.39 Thus, the decision to use a singleton or trio Our study protocol has certain limitations. Paraclinical studies sequencing strategy should depend on the clinical urgency, preceding inclusion are heterogeneous and depend on the the entities under study that determine the proportion of availability of resources in the different participating centers. dominant de novo expected inheritances, the family char- In addition, we reported as diagnosed 5 cases harboring VUS acteristics and availability of DNA, and funding or using technically strict ACMG criteria, as these variants could Neurology.org/N Neurology | Volume 98, Number 9 | March 1, 2022 e919 not be functionally validated. However, these cases with VUS were carefully reviewed by expert clinicians and considered to Appendix 1 Authors explain the phenotypic presentation with very high proba- Name Location Contribution bility, and were thus considered solved by expert assessment. Agatha Neurometabolic Diseases Drafting/revision of the Finally, WGS studies were prioritized in only 16 of the Schlüter, PhD Laboratory, Bellvitge manuscript for content, remaining 38 negative cases (42%) because of limited DNA Biomedical Research including medical writing availability of parents to perform segregation and funding Institute (IDIBELL), 08908 for content; Major role in L’Hospitalet de Llobregat, the acquisition of data; resources. Barcelona, Spain; Center for Study concept or design; Biomedical Research on Analysis or interpretation of Rare Diseases (CIBERER), data We provide evidence of the effectiveness of sWES-WGS ISCIII, Spain analysis based on a phenotype- and interactome-driven pri- Agustı́ Neurometabolic Diseases Drafting/revision of the oritization algorithm to diagnose GWMD and to identify new Rodrı́guez- Laboratory, Bellvitge manuscript for content, phenotypes and novel disease genes. We also provide a white Palmero, MD Biomedical Research including medical writing Institute (IDIBELL), 08908 for content; Major role in matter expanded interactome composed of known and pu- L’Hospitalet de Llobregat, the acquisition of data; tative new GWMD genes with the potential to aid in the Barcelona, Spain; Center for Study concept or design; Biomedical Research on Analysis or interpretation of validation of private mutations in genes found in single fam- Rare Diseases (CIBERER), data ilies and the identification of novel candidate genes. The ISCIII, Spain; Pediatric Neurology Unit, Department utilization of advanced computational methods together with of Pediatrics. Hospital the integration of a functional genomics laboratory capable of Universitari Germans Trias i Pujol, Universitat Autònoma experimental validation of VUS and candidate genes together de Barcelona, Spain with the direct implication of adult and pediatric neurologists in the process are determining factors for this high diagnostic Edgard Neurometabolic Diseases Drafting/revision of the Verdura, PhD Laboratory, Bellvitge manuscript for content, yield. Biomedical Research including medical writing Institute (IDIBELL), 08908 for content; Major role in L’Hospitalet de Llobregat, the acquisition of data; Acknowledgment Barcelona, Spain; Center for Study concept or design; The authors thank the patients and families for their Biomedical Research on Analysis or interpretation of Rare Diseases (CIBERER), data collaboration and the European Leukodystrophy Association ISCIII, Spain (ELA-Spain) and the CERCA Program/Generalitat de Valentina Neurometabolic Diseases Drafting/revision of the Catalunya for support. Vélez- Laboratory, Bellvitge manuscript for content, Santamarı́a, Biomedical Research including medical writing MD Institute (IDIBELL), 08908 for content; Major role in Study Funding L’Hospitalet de Llobregat, the acquisition of data; Barcelona, Spain; Analysis or interpretation of URDCat program (PERIS SLT002/16/00174) from the Neuromuscular Unit, data Autonomous Government of Catalonia, Centre for Bio- Neurology Department, Hospital Universitari de medical Research on Rare Diseases (CIBERER, ACCI19- Bellvitge, Universitat de 759), The Hesperia Foundation (Royal House of Spain), and Barcelona, Hospitalet de CNAG’s call “300 exomes to elucidate rare diseases” (A.P.); Llobregat, Spain the Instituto de Salud Carlos III and “Fondo Europeo de Montserrat Neurometabolic Diseases Drafting/revision of the Desarrollo Regional (FEDER), Unión Europea, una manera Ruiz, PhD Laboratory, Bellvitge manuscript for content, Biomedical Research Institute including medical writing de hacer Europa” (FIS PI20/00758) (C.C.); “La Marató de (IDIBELL), 08908 L’Hospitalet for content; Major role in TV3” Foundation (202006-30) (A.P., C.C.); AWS Cloud de Llobregat, Barcelona, the acquisition of data Spain; Center for Biomedical Credits for Research program (A.S.); Instituto de Salud Research on Rare Diseases Carlos III through the program Miguel Servet (CPII16/ (CIBERER), ISCIII, Spain 00016) (S.F.); Sara Borrell (CD19/00221) (E.Verdura); Rio Stéphane Neurometabolic Diseases Drafting/revision of the Hortega, CM18/00145, co-funded by the European Social Fourcade, Laboratory, Bellvitge manuscript for content, PhD Biomedical Research including medical writing Fund (V.V.-S.); Center for Biomedical Research on Rare Institute (IDIBELL), 08908 for content Diseases, an initiative of the Instituto de Salud Carlos III L’Hospitalet de Llobregat, Barcelona, Spain; Center for (M.R.); and European Reference Network for Rare Neuro- Biomedical Research on logic Diseases: Project ID 739510 (A.M., M.d.T.). Rare Diseases (CIBERER), ISCIII, Spain Disclosure Laura Planas- Neurometabolic Diseases Major role in the acquisition Serra, MSc Laboratory, Bellvitge of data The authors report no disclosures relevant to the manuscript. Biomedical Research Go to Neurology.org/N for full disclosures. Institute (IDIBELL), 08908 L’Hospitalet de Llobregat, Barcelona, Spain; Center for Publication History Biomedical Research on Rare Diseases (CIBERER), Received by Neurology May 1, 2021. Accepted in final form ISCIII, Spain December 21, 2021. e920 Neurology | Volume 98, Number 9 | March 1, 2022 Neurology.org/N Appendix 1 (continued) Appendix 1 (continued) Name Location Contribution Name Location Contribution Juan José Neurometabolic Diseases Major role in the acquisition Elisabet Biodonostia Health Major role in the acquisition Martı́nez, MSc Laboratory, Bellvitge of data Mondragón Research Institute of data Biomedical Research Institute Rezola, MD, (Biodonostia HRI), San (IDIBELL), 08908 L’Hospitalet PhD Sebastián, Spain; Centro de de Llobregat, Barcelona, Investigación Biomédica en Spain; Center for Biomedical Red para Enfermedades Research on Rare Diseases Neurodegenerativas (CIBERER), ISCIII, Spain (CIBERNED), Carlos III Health Institute, Madrid, Spain; Cristina Neurometabolic Diseases Major role in the acquisition Department of Neurology, Guilera, MSc Laboratory, Bellvitge of data Hospital Universitario Biomedical Research Institute Donostia, San Sebastián, (IDIBELL), 08908 L’Hospitalet Spain de Llobregat, Barcelona, Spain; Center for Biomedical Claire Redin, D épartement de M édecine Major role in the acquisition Research on Rare Diseases PhD translationnelle et of data; Analysis or (CIBERER), ISCIII, Spain Neurog én étique, IGBMC, interpretation of data CNRS UMR 7104/INSERM Marisa Girós, Secció d’Errors Congènits del Major role in the acquisition U964/Universit é de PhD Metabolisme-IBC, Servei de of data Strasbourg, Illkirch, Bioquı́mica i Genètica France Molecular, Hospital Clı́nic, IDIBAPS, CIBERER, Jean Louis Département de Médecine Major role in the acquisition Barcelona, Spain Mandel, MD, translationnelle et of data; Analysis or PhD Neurogénétique, IGBMC, interpretation of data Rafael Center for Biomedical Major role in the acquisition CNRS UMR 7104/INSERM Artuch, MD Research on Rare Diseases of data U964/Université de (CIBERER), ISCIII, Spain; Institut Strasbourg, Illkirch, France; de Recerca Pediàtrica- Laboratoire de Diagnostic Hospital Sant Joan de Déu Génétique, Hôpitaux (IRP-HSJD), Barcelona, Spain Universitaires de Strasbourg, Strasbourg, Marı́a Pediatric Neurology Unit, Major role in the acquisition France; Chaire de Génétique Eugenia Yoldi, Department of Pediatrics, of data Humaine, Collège de France, MD Navarra Health Service, Illkirch, France Navarrabiomed Research Foundation, Pamplona, Spain David Conejo, Complejo asistencial Major role in the acquisition MD universitario de Burgos, of data Mar Center for Biomedical Major role in the acquisition Burgos, Spain O’Callaghan, Research on Rare Diseases of data MD, PhD (CIBERER), ISCIII, Spain; Concepción Department of Paediatric Major role in the acquisition Institut de Recerca Sierra- Neurology, Complejo of data Pediàtrica-Hospital Sant Córcoles, MD Hospitalario Jaén, Jaén, Joan de Déu (IRP-HSJD), Spain Barcelona, Spain Sergi Beltran, CNAG-CRG, Centre for Major role in the acquisition Angels Center for Biomedical Major role in the acquisition PhD Genomic Regulation (CRG), of data; Analysis or Garcı́a- Research on Rare Diseases of data; Analysis or Barcelona Institute of interpretation of data Cazorla, MD, (CIBERER), ISCIII, Spain; interpretation of data Science and Technology PhD Institut de Recerca (BIST), Barcelona, Spain Pediàtrica-Hospital Sant Joan de Déu (IRP-HSJD), Marta Gut, CNAG-CRG, Centre for Major role in the acquisition Barcelona, Spain PhD Genomic Regulation (CRG), of data Barcelona Institute of Judith Center for Biomedical Major role in the acquisition Science and Technology Armstrong, Research on Rare Diseases of data (BIST), Barcelona, Spain PhD (CIBERER), ISCIII, Spain; Molecular and Genetics Elida Vázquez, Department of Pediatric Major role in the acquisition Medicine Section, Hospital Sant MD Radiology, Hospital of data Joan de Déu, Barcelona, Spain Materno-Infantil Vall d’Hebrón, Barcelona, Spain Itxaso Marti, Department of Major role in the acquisition MD, PhD Neuropediatrics, Hospital of data Mireia del Center for Biomedical Major role in the acquisition Universitario Donostia, San Toro, MD, PhD Research on Rare Diseases of data Sebastián, Spain; Biodonostia (CIBERER), ISCIII, Spain; Health Research Institute Pediatric Neurology (Biodonostia HRI), San Department, Vall d’Hebron Sebastián, Spain; University of University Hospital, the Basque Country (UPV-EHU), Universitat Autónoma de San Sebastian, Spain; Centro de Barcelona, Spain Investigación Biomédica en Red para Enfermedades Mónica Pediatric Neurology, Major role in the acquisition Neurodegenerativas Troncoso, Hospital Clı́nico San Borja of data (CIBERNED), Carlos III Health MD, PhD Arriarán, Central Campus Institute, Madrid, Spain Universidad de Chile, Chile Continued Neurology.org/N Neurology | Volume 98, Number 9 | March 1, 2022 e921 Appendix 1 (continued) Appendix 2 Coinvestigators Name Location Contribution Name Location Contribution Luis A. Pérez- Center for Biomedical Drafting/revision of the Hugo A. Arroyo, H. Garrahan, Argentina Major role in the Jurado, MD, Research on Rare Diseases manuscript for content, MD acquisition of data PhD (CIBERER), ISCIII, Spain; including medical writing Genetics Service, Hospital for content; Analysis or Andrés Barrios, H. San Borja Arriarán, Chile Major role in the del Mar Research Institute interpretation of data MD acquisition of data (IMIM), Barcelona, Spain; Department of Experimental Andrea Campo, H. Virgen Macarena, Sevilla, Major role in the and Health Sciences, MD Spain acquisition of data Universitat Pompeu Fabra, Barcelona, Spain Tamara Castillo, H. Donostia, Spain Major role in the MD acquisition of data Luis G. Department of Paediatric Major role in the acquisition Gutiérrez- Neurology, Children’s of data; Analysis or Rosario Cazorla, H. Puerta de Hierro, Madrid, Major role in the Solana, MD, University Hospital Niño interpretation of data MD Spain acquisition of data PhD Jesús, Madrid, Spain Marı́a Asunción H. Alcorcón, Madrid, Spain Major role in the Adolfo López Biodonostia Health Research Major role in the acquisition Garcı́a, MD acquisition of data de Munain, Institute (Biodonostia HRI), San of data; Analysis or MD, PhD Sebastián, Spain; University of interpretation of data Ainhoa Garcı́a, H. Cruces, Bilbao, Spain Major role in the the Basque Country (UPV-EHU), MD acquisition of data San Sebastian, Spain; Centro de Investigación Biomédica en Antonio Hedrera, H. Central de Asturias, Major role in the Red para Enfermedades MD Oviedo, Spain acquisition of data Neurodegenerativas (CIBERNED), Carlos III Health Juan Hernández, H. Universitario de Major role in the Institute, Madrid, Spain; MD Guadalajara, Spain acquisition of data Department of Neurology, Hospital Universitario Donostia, Nathalie Launay, IDIBELL, Barcelona, Spain Major role in the San Sebastián, Spain MD acquisition of data Carlos Neurometabolic Diseases Major role in the acquisition Maria Lorenzo, H. Infanta Cristina, Madrid, Major role in the Casasnovas, Laboratory, Bellvitge of data; Analysis or MD Spain acquisition of data MD, PhD Biomedical Research interpretation of data Institute (IDIBELL), 08908 Concepción H. Gregorio Marañón, Major role in the L’Hospitalet de Llobregat, Miranda, MD Madrid, Spain acquisition of data Barcelona, Spain; Neuromuscular Unit, Fermı́n Moreno, H. Donostia, Spain Major role in the Neurology Department, MD acquisition of data Hospital Universitari de Bellvitge, Universitat de Amaia Muñoz, MD H. Donostia, Donostia, Spain Major role in the Barcelona, Hospitalet de acquisition of data Llobregat, Spain Juan Narbona, MD Clı́nica U. Navarra, Major role in the Sergio Pediatric Neurology Unit, Drafting/revision of the Pamplona, Spain acquisition of data Aguilera- Department of Pediatrics, manuscript for content, Albesa, MD, Navarra Health Service, including medical writing for Ma Socorro Pérez, H. Marqués de Valdecilla, Major role in the PhD Navarrabiomed Research content; Major role in the MD Santander, Spain acquisition of data Foundation, Pamplona, acquisition of data; Analysis Spain or interpretation of data Maria Antonia H. Virgen del Camino, Major role in the Ramos, MD Pamplona, Spain acquisition of data Alfons Center for Biomedical Drafting/revision of the Macaya, MD, Research on Rare Diseases manuscript for content, Miquel Raspall- H. Vall d’Hebron, Barcelona, Major role in the PhD (CIBERER), ISCIII, Spain; including medical writing Chaure, MD Spain acquisition of data Pediatric Neurology for content; Major role in Department, Vall d’Hebron the acquisition of data; Manel Roig-Quilis, H. Vall d’Hebron, Barcelona, Major role in the University Hospital, Study concept or design; MD Spain acquisition of data Universitat Autónoma de Analysis or interpretation of Barcelona, Spain; Pediatric data Miguel Ángel H. Donostia, Spain Major role in the Neurology Research Group, Urtasun, MD acquisition of data Vall d’Hebron Research Institute, Universitat Marı́a Esther H. Lucus Augusti, Lugo, Major role in the Autònoma de Barcelona, Vázquez, MD Spain acquisition of data Barcelona, Spain Juan Francisco H. La Fe, Valencia, Spain Major role in the Aurora Pujol, Neurometabolic Diseases Drafting/revision of the Vázquez, MD acquisition of data MD, PhD Laboratory, Bellvitge manuscript for content, Biomedical Research including medical writing Institute (IDIBELL), 08908 for content; Major role in L’Hospitalet de Llobregat, the acquisition of data; References Barcelona, Spain; Center for Study concept or design; 1. Fogel BL, Lee H, Deignan JL, et al. Exome sequencing in the clinical diagnosis of Biomedical Research on Analysis or interpretation of sporadic or familial cerebellar ataxia. JAMA Neurol. 2014;71(10):1237-1246. Rare Diseases (CIBERER), data 2. Gonzaga-Jauregui C, Harel T, Gambin T, et al. Exome sequence analysis suggests that ISCIII, Spain; Catalan genetic burden contributes to phenotypic variability and complex neuropathy. Cell Institution of Research and Rep. 2015;12(7):1169-1183. Advanced Studies (ICREA), 3. van de Warrenburg BP, Schouten MI, de Bot ST, et al. 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