Validation of a Next-Generation Sequencing Pipeline for the Molecular Diagnosis of Multiple Inherited Cancer Predisposing Syndromes
2017; Elsevier BV; Volume: 19; Issue: 4 Linguagem: Inglês
10.1016/j.jmoldx.2017.05.001
ISSN1943-7811
AutoresPaula Paulo, Pedro Pinto, Ana Peixoto, Catarina Santos, Carla Pinto, Patrícia Rocha, Isabel Veiga, Gabriela Soares, Catarina Machado, Fabiana Ramos, Manuel R. Teixeira,
Tópico(s)Genomics and Rare Diseases
ResumoDespite the growing knowledge of the genetic background behind the cancers that occur in a context of hereditary predisposition, personal or family cancer history may not be clear enough to support directional gene testing. Defined targeted next-generation sequencing gene panels allow identification of the causative disease mutations of multigene syndromes and differential diagnosis for syndromes with phenotypically overlapping characteristics. Herein, we established a next-generation sequencing analysis pipeline for the molecular diagnosis of multiple inherited cancer predisposing syndromes using the commercially available target sequencing panel TruSight Cancer. To establish the analysis pipeline, we included 22 control samples with deleterious mutations covering all genes currently analyzed at our institution by standard Sanger sequencing. We tested the pipeline using 51 samples from patients with a clinical diagnosis of neurofibromatosis type 1 (NF1), 10 of which without previous molecular characterization of the causative NF1 mutations. We propose a thoroughly validated analysis pipeline that combines Isaac Enrichment, Burrows-Wheeler Aligner Enrichment, and NextGENe for the alignment and variant calling, and GeneticistAssistant for variant annotation and prioritization. This pipeline allowed the identification of disease-causing mutations in all 73 patients, including a large duplication of 37 bp in NF1. We show that high sensitivity and specificity can be achieved by using multiple bioinformatic tools for alignment and variant calling and careful variant filtering, having in mind the clinical question. Despite the growing knowledge of the genetic background behind the cancers that occur in a context of hereditary predisposition, personal or family cancer history may not be clear enough to support directional gene testing. Defined targeted next-generation sequencing gene panels allow identification of the causative disease mutations of multigene syndromes and differential diagnosis for syndromes with phenotypically overlapping characteristics. Herein, we established a next-generation sequencing analysis pipeline for the molecular diagnosis of multiple inherited cancer predisposing syndromes using the commercially available target sequencing panel TruSight Cancer. To establish the analysis pipeline, we included 22 control samples with deleterious mutations covering all genes currently analyzed at our institution by standard Sanger sequencing. We tested the pipeline using 51 samples from patients with a clinical diagnosis of neurofibromatosis type 1 (NF1), 10 of which without previous molecular characterization of the causative NF1 mutations. We propose a thoroughly validated analysis pipeline that combines Isaac Enrichment, Burrows-Wheeler Aligner Enrichment, and NextGENe for the alignment and variant calling, and GeneticistAssistant for variant annotation and prioritization. This pipeline allowed the identification of disease-causing mutations in all 73 patients, including a large duplication of 37 bp in NF1. We show that high sensitivity and specificity can be achieved by using multiple bioinformatic tools for alignment and variant calling and careful variant filtering, having in mind the clinical question. Hereditary cancer syndromes may account for 5% to 10% of all cancers, being overrepresented in patients with early onset or family history of the disease.1Garber J.E. Offit K. Hereditary cancer predisposition syndromes.J Clin Oncol. 2005; 23: 276-292Crossref PubMed Scopus (429) Google Scholar Despite the growing knowledge of the genetic background behind the most common inherited cancer syndromes, personal or family cancer history may not be clear enough to support directional gene testing. Cumbersome molecular diagnosis may be because of genetic heterogeneity (the same syndrome being caused by several genes), the fact that some cancers may be a feature of different predisposition syndromes, and sometimes a striking personal or familial history may not fit any recognizable syndrome, be that because of phenotypic heterogeneity or lack of complete information regarding family history. Moreover, even when clinical diagnosis is straightforward and directional gene testing of a single gene is mandatory, molecular diagnosis may prove difficult with standard sequencing techniques because of the large size of the gene and/or the absence of mutational hot-spots, as exemplified by the analysis of the NF1 gene in patients clinically diagnosed with neurofibromatosis type 1 (NF1).2Upadhyaya M. Neurofibromatosis type 1: diagnosis and recent advances.Expert Opin Med Diagn. 2010; 4: 307-322Crossref PubMed Scopus (31) Google Scholar Targeted next-generation sequencing (NGS) of defined gene packages offers the opportunity to cover the genomic heterogeneity of multigene syndromes, while allowing identification of causative disease mutations in genes associated with phenotypically overlapping syndromes. Some groups have established targeted NGS pipelines for the molecular diagnosis of specific inherited cancer syndromes, covering genes predisposing to hereditary breast/ovarian cancer,3Ozcelik H. Shi X. Chang M.C. Tram E. Vlasschaert M. Di Nicola N. Kiselova A. Yee D. Goldman A. Dowar M. Sukhu B. Kandel R. Siminovitch K. Long-range PCR and next-generation sequencing of BRCA1 and BRCA2 in breast cancer.J Mol Diagn. 2012; 14: 467-475Abstract Full Text Full Text PDF PubMed Scopus (50) Google Scholar, 4Chong H.K. Wang T. Lu H.M. Seidler S. Lu H. Keiles S. Chao E.C. Stuenkel A.J. Li X. Elliott A.M. The validation and clinical implementation of BRCAplus: a comprehensive high-risk breast cancer diagnostic assay.PLoS One. 2014; 9: e97408Crossref PubMed Scopus (62) Google Scholar, 5Dacheva D. Dodova R. Popov I. Goranova T. Mitkova A. Mitev V. Kaneva R. Validation of an NGS approach for diagnostic BRCA1/BRCA2 mutation testing.Mol Diagn Ther. 2015; 19: 119-130Crossref PubMed Scopus (23) Google Scholar, 6Castéra L. Krieger S. Rousselin A. Legros A. Baumann J.J. Bruet O. Brault B. Fouillet R. Goardon N. Letac O. Baert-Desurmont S. Tinat J. Bera O. Dugast C. Berthet P. Polycarpe F. Layet V. Hardouin A. Frébourg T. Vaur D. Next-generation sequencing for the diagnosis of hereditary breast and ovarian cancer using genomic capture targeting multiple candidate genes.Eur J Hum Genet. 2014; 22: 1305-1313Crossref PubMed Scopus (182) Google Scholar, 7Michils G. Hollants S. Dehaspe L. Van Houdt J. Bidet Y. Uhrhammer N. Bignon Y.J. Vermeesch J.R. Cuppens H. Matthijs G. Molecular analysis of the breast cancer genes BRCA1 and BRCA2 using amplicon-based massive parallel pyrosequencing.J Mol Diagn. 2012; 14: 623-630Abstract Full Text Full Text PDF PubMed Scopus (30) Google Scholar, 8Hernan I. Borràs E. de Sousa Dias M. Gamundi M.J. Mañé B. Llort G. Agúndez J.A. Blanca M. Carballo M. Detection of genomic variations in BRCA1 and BRCA2 genes by long-range PCR and next-generation sequencing.J Mol Diagn. 2012; 14: 286-293Abstract Full Text Full Text PDF PubMed Scopus (43) Google Scholar NF1,9Pasmant E. Parfait B. Luscan A. Goussard P. Briand-Suleau A. Laurendeau I. Fouveaut C. Leroy C. Montadert A. Wolkenstein P. Vidaud M. Vidaud D. Neurofibromatosis type 1 molecular diagnosis: what can NGS do for you when you have a large gene with loss of function mutations?.Eur J Hum Genet. 2015; 23: 596-601Crossref PubMed Scopus (79) Google Scholar, 10Balla B. Árvai K. Horváth P. Tobiás B. Takács I. Nagy Z. Dank M. Fekete G. Kósa J.P. Lakatos P. Fast and robust next-generation sequencing technique using ion torrent personal genome machine for the screening of neurofibromatosis type 1 (NF1) gene.J Mol Neurosci. 2014; 53: 204-210Crossref PubMed Scopus (18) Google Scholar pheochromocytomas and paragangliomas,11Rattenberry E. Vialard L. Yeung A. Bair H. McKay K. Jafri M. Canham N. Cole T.R. Denes J. Hodgson S.V. Irving R. Izatt L. Korbonits M. Kumar A.V. Lalloo F. Morrison P.J. Woodward E.R. Macdonald F. Wallis Y. Maher E.R. A comprehensive next generation sequencing-based genetic testing strategy to improve diagnosis of inherited pheochromocytoma and paraganglioma.J Clin Endocrinol Metab. 2013; 98: E1248-E1256Crossref PubMed Scopus (71) Google Scholar, 12Crona J. Verdugo A.D. Granberg D. Welin S. Stålberg P. Hellman P. Björklund P. Next-generation sequencing in the clinical genetic screening of patients with pheochromocytoma and paraganglioma.Endocr Connect. 2013; 2: 104-111Crossref PubMed Google Scholar or retinoblastomas.13Devarajan B. Prakash L. Kannan T.R. Abraham A.A. Kim U. Muthukkaruppan V. Vanniarajan A. Targeted next generation sequencing of RB1 gene for the molecular diagnosis of retinoblastoma.BMC Cancer. 2015; 15: 1-10Crossref PubMed Scopus (27) Google Scholar Others reported NGS pipelines aiming to cover a panel of hereditary cancer syndromes: whereas Kurian et al14Kurian A.W. Hare E.E. Mills M.A. Kingham K.E. McPherson L. Whittemore A.S. McGuire V. Ladabaum U. Kobayashi Y. Lincoln S.E. Cargill M. Ford J.M. Clinical evaluation of a multiple-gene sequencing panel for hereditary cancer risk assessment.J Clin Oncol. 2014; 32: 2001-2009Crossref PubMed Scopus (377) Google Scholar evaluated a panel of 42 genes associated with breast cancer predisposition in various syndromes, Guan et al15Guan Y. Hu H. Peng Y. Gong Y. Yi Y. Shao L. Liu T. Li G. Wang R. Dai P. Bignon Y.-J. Xiao Z. Yang L. Mu F. Xiao L. Xie Z. Yan W. Xu N. Zhou D. Yi X. Detection of inherited mutations for hereditary cancer using target enrichment and next generation sequencing.Fam Cancer. 2015; 14: 9-18Crossref PubMed Scopus (19) Google Scholar described a pipeline covering genes associated with most hereditary cancers, and Judkins et al16Judkins T. Leclair B. Bowles K. Gutin N. Trost J. McCulloch J. Bhatnagar S. Murray A. Craft J. Wardell B. Bastian M. Mitchell J. Chen J. Tran T. Williams D. Potter J. Jammulapati S. Perry M. Morris B. Roa B. Timms K. Development and analytical validation of a 25-gene next generation sequencing panel that includes the BRCA1 and BRCA2 genes to assess hereditary cancer risk.BMC Cancer. 2015; 15: 215Crossref PubMed Scopus (87) Google Scholar established a pipeline covering 25 genes involved in the eight most frequent cancers associated with inherited cancer syndromes. These studies, however, either included only control samples for BRCA1/BRCA2 mutations and/or reported HiSeq pipelines that may not be applicable to the more recent, affordable, NGS benchtop equipment. Considering the high-input requirements of high-throughput NGS sequencers to reduce costs per sample, benchtop NGS sequencers may constitute the best alternative for laboratories with average case load numbers. Herein, we validated a benchtop NGS pipeline for the molecular diagnosis of multiple inherited cancer predisposing syndromes using a commercially available sequencing panel that targets the coding and flanking regions of 94 genes associated with an increased risk for cancer development. To establish the pipeline, we included control samples for the 22 genes associated with inherited cancer predisposition for which we have deleterious germline mutations at the Department of Genetics of the Portuguese Oncology Institute of Porto (IPO Porto) (detected by standard Sanger sequencing). To test the pipeline, we used two test series, the first (test-I) comprising 10 samples from patients with clinical diagnosis of NF1 at our institution (NIH criteria17NIHNational Institutes of Health Consensus Development Conference Statement: Neurofibromatosis.Neurofibromatosis. 1988; 1: 172-178PubMed Google Scholar), but for whom molecular diagnosis was not available, and the second (test-II) comprising 41 DNA samples from patients with clinical and molecular diagnosis (point mutations) of NF1 contributed by three collaborative national Portuguese institutions (16 samples from Centro Hospitalar do Porto, Porto; 19 samples from Hospital de Santa Maria, Lisboa; and 6 samples from Hospital Pediátrico Carmona da Mota, Coimbra). DNA samples from the 22 controls (control series) and 10 NF1 patients (test-I series) were extracted from peripheral blood leukocytes by standard techniques. DNA samples from the 41 NF1 patients comprising the test series with known NF1 point mutations (test-II series) were provided by the three collaborating institutions and were blind tested (P.Pa. and P.Pi.). Samples were quantified using Qubit Fluorometer (Life Technologies, Darmstadt, Germany). To establish the NGS analysis pipeline, the mutational landscape of the control samples was selected to include a large diversity of mutation types (all deleterious mutations): single-nucleotide variants (SNVs) and insertions/deletions (INDELs; short and long) and coding and intronic, encompassing missense, nonsense, splice, and frameshift mutations (Table 1).Table 1Mutational Landscape of the 22 Control Samples Included in the Validation SeriesCase no.Clinical diagnosisMutated geneRefSeq transcript∗Available at http://www.ncbi.nlm.nih.gov/refseq.Chromosome position (CRCh37)Mutation consequenceMutation (reference)C1Hereditary retinoblastomaRB1NM_000321.213:49033874Frameshiftc.2011_2014del, p.(Glu672ThrfsTer4)†Reported in public databases.C2Familial adenomatous polyposisAPCNM_000038.55:112111384Nonsensec.481C>T, p.(Gln161Ter)†Reported in public databases.C3Li-Fraumeni syndromeTP53NM_000546.517:7577111Frameshiftc.818_827del, p.(Arg273ProfsTer69)‡Not reported.C4Hereditary melanomaCDKN2ANM_000077.49:21994135Splicec.193+3A>G, p.(?)18Demenais F. Mohamdi H. Chaudru V. Goldstein A.M. Newton Bishop J.A. Bishop D.T. et al.Association of MC1R variants and host phenotypes with melanoma risk in CDKN2A mutation carriers: a GenoMEL study.J Natl Cancer Inst. 2010; 102: 1568-1583Crossref PubMed Scopus (92) Google ScholarC5Von Hippel–Lindau syndromeVHLNM_000551.33:10183833Missensec.302T>G, p.(Leu101Arg)†Reported in public databases.C6Cowden syndromePTENNM_000314.410:89692921Frameshiftc.405dup, p.(Cys136MetfsTer44)‡Not reported.C7Hereditary breast and ovarian cancer syndromeBRCA1NM_007294.317:41245511Frameshiftc.2037delinsCC, p.(Lys679AsnfsTer4)19Peixoto A. Santos C. Pinto P. Pinheiro M. Rocha P. Pinto C. Bizarro S. Veiga I. Principe A.S. Maia S. Castro F. Couto R. Gouveia A. Teixeira M.R. The role of targeted BRCA1/BRCA2 mutation analysis in hereditary breast/ovarian cancer families of Portuguese ancestry.Clin Genet. 2015; 88: 41-48Crossref PubMed Scopus (22) Google ScholarC8Lynch syndromeMSH6NM_000179.22:48033635In framec.3848_3862del, p.(Ile1283_Tyr1287del)†Reported in public databases.C9Lynch syndromeMLH1NM_000249.33:37061938Frameshiftc.1023del, p.(Met342CysfsTer25)†Reported in public databases.C10Hereditary gastrointestinal stromal tumorsKITNM_000222.24:55599332Missensec.2458G>T, p.(Asp820Tyr)†Reported in public databases.C11Lynch syndromeMSH2NM_000251.22:47705560Frameshiftc.2360_2361dup, p.(Thr788LeufsTer25)†Reported in public databases.C12Hereditary paraganglioma/pheocromocytomaSDHBNM_003000.21:17371286Frameshiftc.166_170del, p.(Pro56TyrfsTer5)†Reported in public databases.C13Gorlin syndromePTCH1NM_000264.39:98231221Nonsensec.2062C>T, p.(Gln688Ter)†Reported in public databases.C14Hereditary paraganglioma/pheocromocytomaSDHDNM_003002.311:111965625Frameshiftc.411del, p.(Leu139PhefsTer29)†Reported in public databases.C15Peutz-Jeghers syndromeSTK11NM_000455.419:1221202Intron, splicec.735-10C>A, p.(?)†Reported in public databases.C16MUTYH-associated polyposisMUTYHNM_001128425.11:45797187Frameshiftc.1227_1228dup, p.(Glu410GlyfsTer43)†Reported in public databases.C17Lynch syndromePMS2NM_000535.57:6027185Frameshiftc.1210_1211del, p.(Pro404PhefsTer53)†Reported in public databases.C18Hereditary breast and ovarian cancer syndromeBRCA2NM_000059.313:32905054Splicec.682-2A>C, p.(?)19Peixoto A. Santos C. Pinto P. Pinheiro M. Rocha P. Pinto C. Bizarro S. Veiga I. Principe A.S. Maia S. Castro F. Couto R. Gouveia A. Teixeira M.R. The role of targeted BRCA1/BRCA2 mutation analysis in hereditary breast/ovarian cancer families of Portuguese ancestry.Clin Genet. 2015; 88: 41-48Crossref PubMed Scopus (22) Google ScholarC19Multiple endocrine neoplasia type 2RETNM_020975.410:43609948Missensec.1900T>A, p.(Cys634Ser)†Reported in public databases.C20Multiple endocrine neoplasia type 1MEN1NM_000244.311:64577458Missensec.124G>T, p.(Gly42Cys)†Reported in public databases.C21BAP1 tumor syndromeBAP1NM_004656.33:52440294Frameshiftc.758dup, p.(Thr254AspfsTer30)‡Not reported.C22Hereditary diffuse gastric cancerCDH1NM_004360.316:68856093Missense, splicec.1901C>T, p.(Ala634Val)20Suriano G. Oliveira C. Ferreira P. Machado J.C. Bordin M.C. De Wever O. Bruyneel E.A. Moguilevsky N. Grehan N. Porter T.R. Richards F.M. Hruban R.H. Roviello F. Huntsman D. Mareel M. Carneiro F. Caldas C. Seruca R. Identification of CDH1 germline missense mutations associated with functional inactivation of the E-cadherin protein in young gastric cancer probands.Hum Mol Genet. 2003; 12: 575-582Crossref PubMed Scopus (153) Google Scholar, 21Kaurah P. MacMillan A. Boyd N. Senz J. De Luca A. Chun N. et al.Founder and recurrent CDH1 mutations in families with hereditary diffuse gastric cancer.JAMA. 2007; 297: 2360-2372Crossref PubMed Scopus (359) Google Scholar∗ Available at http://www.ncbi.nlm.nih.gov/refseq.† Reported in public databases.‡ Not reported. Open table in a new tab For library preparation, we followed the manufacturer's instructions (TruSight Rapid Capture Kit; Illumina Inc., San Diego, CA). Briefly, 50 ng of DNA was subjected to tagmentation (fragmentation and addition of tags) at 58°C for 10 minutes, followed by capture and cleaning of tagged fragments. Index primers were added and samples were amplified in a 10-cycle PCR. After PCR cleanup, samples were pooled and enriched by hybridization of the TruSight Cancer Content Set Oligos (Illumina Inc.) to the specific target regions using an 18-cycle touch-down PCR amplification program, followed by incubation at 58°C for 2 hours. Hybridized probes were captured using streptavidin magnetic beads, washed, and eluted for a second round of hybridization at the same conditions, with a final incubation at 58°C for 15 to 17 hours. After streptavidin-based capture and washing, enriched samples were eluted and purified for a second round of PCR amplification in a 12-cycle program. Libraries were purified, quantified using Qubit HS Assay, and run in QIAxel (Qiagen GmbH, Hilden, Germany) for fragment size evaluation. A final 24-plex pool of 10 pmol/L denatured libraries was loaded in the reagent cartridge (MiSeq Reagent Kit version 2; 300-cycle kit; Illumina Inc.) and cluster generation and paired-end sequencing took place in a standard flow cell in a MiSeq platform (Illumina Inc.). Primary analysis was performed in MiSeq Reporter (version 2.5.1; Illumina Inc.). As an acceptance quality score, a cutoff value of 30 was considered. Duplicate reads were discarded for further analysis. For alignment to the human genome build 19 and variant calling, we used four different software programs: MiSeq Reporter version 2.5.1 (Illumina Inc.), Isaac Enrichment version 2.1.0 (Illumina's BaseSpace platform), Burrows-Wheeler Aligner (BWA) Enrichment version 2.1.0 (Illumina's BaseSpace platform), and NextGENe version 2.3.4.4 (Softgenetics, State College, PA), according to the manufacturer's protocols. A manifest file, containing the coordinates of the genomic regions targeted by the TruSight Cancer panel, was used for variant calling in the four analysis software programs. For variant annotation and filtering, .vcf (variant call format) files from the four software programs were imported into GeneticistAssistant (Softgenetics) and filtered for variant frequency in our in-house database, excluding variants present in >10% of the cases. Additional variant selection included those with coverage ≥20×, alternative variant frequency ≥15%, and minor allele frequency (MAF) 12 bp away from exon-intron boundaries. Exceptions for MAF filtering include variants in genes involved in recessive diseases (as is the case of MUTYH) for which a MAF 90% of the reads. The three aligners available from Illumina platforms (MiSeq and BaseSpace) showed similar coverage characteristics, using a padding of 150 bp (Supplemental Table S1). With NextGENe, padding was not available, rendering analysis not comparable. Overall, comparing variant call characteristics of pathogenic variants present in the control series, the four software programs showed similar coverages and alternative variant frequencies, either considering SNVs or INDELs (Figure 1). Coverage was more variable for the control SNV mutations than for the control INDELs (range, 36.4 versus 27.0), although the average variant coverage was lower for INDELs than for SNVs (P = 0.00034) (Supplemental Table S2). Variant calling with MiSeq Reporter missed one mutation, the TP53 mutation c.818_827del in sample C3, which comprises the largest INDEL of our control samples (Figure 1 and Supplemental Table S2). Visual inspection of the MiSeq Reporter .bam files in the Golden Helix GenomeBrowse (Golden Helix Inc., Bozeman, MT) confirmed the presence of the mutation in 16 of 70 reads (Supplemental Figure S1). With the remaining software programs, all pathogenic mutations from the 22 control samples were detected. However, applying our initial variant filtering criteria, the PTCH1 mutation c.2062C>T in sample C13 would be filtered out for its low read depth ( T, p.(Gln2413Ter)21745.221146.021545.620939.7N317:29665065Frameshiftc.6664del, p.(Ser2222ProfsTer22)16048.815548.715648.716047.5N417:29576119Frameshiftc.4092_4098del, p.(Cys1365ValfsTer18)––17651.516546.117250.6N517:29527549Nonsensec.998dup, p.(Tyr333Ter)35350.333251.133551.041447.1N617:29553492Nonsensec.2041C>T, p.(Arg681Ter)20354.719051.120254.520251.5N717:29497003Nonsensec.574C>T, p.(Arg192Ter)10840.710440.410840.712541.6N817:29553654Frameshiftc.2204_2213del, p.(Tyr735SerfsTer10)––27238.127833.830239.1N917:29541572Missensec.1496T>G, p.(Leu499Arg)24145.223345.523945.226744.2N1017:29541572Missensec.1496T>G, p.(Leu499Arg)16845.216245.716945.617040.6–, uncalled variants; Alt. allele frequency, percentage of reads with alternative allele. Open table in a new tab –, uncalled variants; Alt. allele frequency, percentage of reads with alternative allele. Although 8 of the 10 NF1 patients from the test-I series were characterized by a truncating NF1 mutation, two cases (N9 and N10) harbored the missense mutation c.1496T>G (p.Leu499Arg). Looking at the in silico pathogenicity predictors embedded in GeneticistAssistant, 12 of the 15 tools are indicative of a pathogenic variant in a highly conserved nucleotide (Supplemental Table S3).31Buitrago L. Rendon A. Liang Y. Simeoni I. Negri A. Filizola M. Ouwehand W.H. Coller B.S. ThromboGenomics ConsortiumαIIbβ3 variants defined by next-generation sequencing: predicting variants likely to cause Glanzmann thrombasthenia.Proc Natl Acad Sci U S A. 2015; 112: E1898-E1907Crossref PubMed Scopus (35) Google Scholar This variant is described de novo in one Italian patient in the LOVD database, where it is reported as pathogenic, and is not found in either the 1000 Genomes Project or Exome Aggregation Consortium database. Segregation analyses in affected and/or healthy relatives of both our index cases (Supplemental Figure S2), as well as its absence in other samples in our internal database of >500 tests with this gene panel, support the pathogenicity status reported in LOVD. Moreover, mu
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