Comparative genomic hybridisation as a first option in genetic diagnosis: 1000 cases and a cost–benefit analysis

array:25 ["pii" => "S2341287918300875" "issn" => "23412879" "doi" => "10.1016/j.anpede.2017.07.009" "estado" => "S300" "fechaPublicacion" => "2018-07-01" "aid" => "2303" "copyright" => "Asociación Española de Pediatría" "copyrightAnyo" => "2017" "documento" => "article" "crossmark" => 1 "licencia" => "http://creativecommons.org/licenses/by-nc-nd/4.0/" "subdocumento" => "fla" "cita" => "An Pediatr (Barc). 2018;89:3-11" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:2 [ "total" => 1705 "formatos" => array:3 [ "EPUB" => 165 "HTML" => 1101 "PDF" => 439 ] ] "Traduccion" => array:1 [ "es" => array:20 [ "pii" => "S1695403317303065" "issn" => "16954033" "doi" => "10.1016/j.anpedi.2017.07.011" "estado" => "S300" "fechaPublicacion" => "2018-07-01" "aid" => "2303" "copyright" => "Asociación Española de Pediatría" "documento" => "article" "crossmark" => 1 "licencia" => "http://creativecommons.org/licenses/by-nc-nd/4.0/" "subdocumento" => "fla" "cita" => "An Pediatr (Barc). 2018;89:3-11" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:2 [ "total" => 14773 "formatos" => array:3 [ "EPUB" => 186 "HTML" => 12926 "PDF" => 1661 ] ] "es" => array:13 [ "idiomaDefecto" => true "cabecera" => "ORIGINAL" "titulo" => "Array CGH como primera opción en el diagnóstico genético: 1.000 casos y análisis de coste-beneficio" "tienePdf" => "es" "tieneTextoCompleto" => "es" "tieneResumen" => array:2 [ 0 => "es" 1 => "en" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "3" "paginaFinal" => "11" ] ] "titulosAlternativos" => array:1 [ "en" => array:1 [ "titulo" => "Comparative genomic hybridisation as a first option in genetic diagnosis: 1,000 cases and a cost-benefit analysis" ] ] "contieneResumen" => array:2 [ "es" => true "en" => true ] "contieneTextoCompleto" => array:1 [ "es" => true ] "contienePdf" => array:1 [ "es" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0015" "etiqueta" => "Figura 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1391 "Ancho" => 3227 "Tamanyo" => 317644 ] ] "descripcion" => array:1 [ "es" => "Cálculo de los costes para cada una de las dos estrategias diagnósticas. A: cálculo del coste del uso del aCGH como primera opción diagnóstica. B: cálculo de los costes del uso del aCGH como tercera opción, tras el cariotipo y la MLPA. De los 140 casos diagnosticados mediante aCGH, 12 se hubieran diagnosticado mediante cariotipo (de los cuales 2 eran aneuploidías y 10 desequilibrios de más de 6Mb); 31 se habrían diagnosticado mediante MLPA con ensayos de anomalías subteloméricas y de síndromes genómicos recurrentes, y los 97 casos restantes se habrían diagnosticado mediante aCGH, después de un resultado normal de cariotipo y MLPA. Costes<a class="elsevierStyleCrossRef" href="#bib0260">16</a>: cariotipo 121,55 €/ensayo; MLPA 243,37 €/3ensayos MLPA; aCGH 355,39 €/ensayo. El enfoque tradicional de cariotipo y MLPA (estrategia B) hubiera conseguido menos de un tercio de los diagnósticos en nuestra población (43/140). Implementar el array para lograr el 100% de los desequilibrios multiplica por 1,97 el coste que supondría aplicar el array como primera y única opción (estrategia A)." ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Neus Castells-Sarret, Anna M. Cueto-González, Mar Borregan, Fermina López-Grondona, Rosa Miró, Eduardo Tizzano, Alberto Plaja" "autores" => array:7 [ 0 => array:2 [ "nombre" => "Neus" "apellidos" => "Castells-Sarret" ] 1 => array:2 [ "nombre" => "Anna M." "apellidos" => "Cueto-González" ] 2 => array:2 [ "nombre" => "Mar" "apellidos" => "Borregan" ] 3 => array:2 [ "nombre" => "Fermina" "apellidos" => "López-Grondona" ] 4 => array:2 [ "nombre" => "Rosa" "apellidos" => "Miró" ] 5 => array:2 [ "nombre" => "Eduardo" "apellidos" => "Tizzano" ] 6 => array:2 [ "nombre" => "Alberto" "apellidos" => "Plaja" ] ] ] ] ] "idiomaDefecto" => "es" "Traduccion" => array:1 [ "en" => array:9 [ "pii" => "S2341287918300875" "doi" => "10.1016/j.anpede.2017.07.009" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2341287918300875?idApp=UINPBA00005H" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S1695403317303065?idApp=UINPBA00005H" "url" => "/16954033/0000008900000001/v2_201807280406/S1695403317303065/v2_201807280406/es/main.assets" ] ] "itemSiguiente" => array:20 [ "pii" => "S2341287918300759" "issn" => "23412879" "doi" => "10.1016/j.anpede.2018.05.001" "estado" => "S300" "fechaPublicacion" => "2018-07-01" "aid" => "2286" "copyright" => "Asociación Española de Pediatría" "documento" => "article" "crossmark" => 1 "licencia" => "http://creativecommons.org/licenses/by-nc-nd/4.0/" "subdocumento" => "fla" "cita" => "An Pediatr (Barc). 2018;89:12-23" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:2 [ "total" => 1874 "formatos" => array:3 [ "EPUB" => 160 "HTML" => 1153 "PDF" => 561 ] ] "en" => array:13 [ "idiomaDefecto" => true "cabecera" => "Original Article" "titulo" => "Incidence of hypoxic-ischaemic encephalopathy and use of therapeutic hypothermia in Spain" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => array:2 [ 0 => "en" 1 => "es" ] "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "12" "paginaFinal" => "23" ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Incidencia de la encefalopatía hipóxico-isquémica e implementación de la hipotermia terapéutica por regiones en España" ] ] "contieneResumen" => array:2 [ "en" => true "es" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 4001 "Ancho" => 2483 "Tamanyo" => 444669 ] ] "descripcion" => array:1 [ "en" => "(A) Map showing the 90 hospitals that participated in the survey and their TH capabilities as of June 2015: active TH (solid black circle), passive TH (hollow triangle) or no TH (hollow circle). The autonomous cities of Ceuta and Melilla are not represented because they did not participate in the survey, since none of their hospitals have level III neonatal units and they refer patients requiring this level of care to hospitals in the Iberian peninsula. The progressive increase in the number of hospitals offering TH after its initial introduction in 2 centres in 2008 was of 10 hospitals in 2009, 9 hospitals in 2010, 10 hospitals in 2011, 9 hospitals in 2012, 7 hospitals in 2013, 8 hospitals in 2014 and 2 hospitals in 2015. (B) Distribution of NBs with a moderate-to-severe HIE diagnosis that received TH in the period under study by AC. Dark grey represents children that received active TH, light grey children that received passive TH, and while children that did not receive TH." ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Juan Arnaez, Alfredo García-Alix, Gemma Arca, Eva Valverde, Sonia Caserío, M. Teresa Moral, Isabel Benavente-Fernández, Simón Lubián-López" "autores" => array:9 [ 0 => array:2 [ "nombre" => "Juan" "apellidos" => "Arnaez" ] 1 => array:2 [ "nombre" => "Alfredo" "apellidos" => "García-Alix" ] 2 => array:2 [ "nombre" => "Gemma" "apellidos" => "Arca" ] 3 => array:2 [ "nombre" => "Eva" "apellidos" => "Valverde" ] 4 => array:2 [ "nombre" => "Sonia" "apellidos" => "Caserío" ] 5 => array:2 [ "nombre" => "M. 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Cueto-González, Mar Borregan, Fermina López-Grondona, Rosa Miró, Eduardo Tizzano, Alberto Plaja" "autores" => array:7 [ 0 => array:4 [ "nombre" => "Neus" "apellidos" => "Castells-Sarret" "email" => array:1 [ 0 => "ncastellssarret@gmail.com" ] "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "Anna M." "apellidos" => "Cueto-González" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "c" "identificador" => "aff0015" ] ] ] 2 => array:3 [ "nombre" => "Mar" "apellidos" => "Borregan" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "c" "identificador" => "aff0015" ] ] ] 3 => array:3 [ "nombre" => "Fermina" "apellidos" => "López-Grondona" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 4 => array:3 [ "nombre" => "Rosa" "apellidos" => "Miró" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] ] ] 5 => array:3 [ "nombre" => "Eduardo" "apellidos" => "Tizzano" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "d" "identificador" => "aff0020" ] ] ] 6 => array:3 [ "nombre" => "Alberto" "apellidos" => "Plaja" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] ] ] ] "afiliaciones" => array:4 [ 0 => array:3 [ "entidad" => "Àrea de Genètica Clínica i Molecular, Hospital Vall d’Hebron, Barcelona, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Departament de Biologia Cel·lular, Fisiologia i Immunologia, Universitat Autònoma de Barcelona, Bellaterra, Barcelona, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Facultat de Medicina, Departament de Ciències Morfològiques, Universitat Autònoma de Barcelona, Bellaterra, Barcelona, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "CIBERER, Barcelona, Spain" "etiqueta" => "d" "identificador" => "aff0020" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Array CGH como primera opción en el diagnóstico genético: 1.000 casos y análisis de coste-beneficio" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 2425 "Ancho" => 3170 "Tamanyo" => 546099 ] ] "descripcion" => array:1 [ "en" => "Cases of mosaicism detected by comparative genomic hybridisation. (A) Mosaic deletion at 1p36 in a patient with heart disease: detected by aCGH (1) and confirmed in 9.8% of cells analysed using FISH. There is only one signal in the nucleus of the image, marked by an arrow, corresponding to 1p36 (2). (B) 1q21.1-q32.1 duplication in a patient with epilepsy: detected by aCGH (1), confirmed in 1.2% of cells analysed with FISH. The three bottom signals in the nucleus of the image, pointed by the arrow, correspond to region 1q21q32.1 (2) and karyotype (3). (C) 18q21.31-q22.2 deletion in a patient with GDD: detected by aCGH (1) and confirmed in 43.3% of cells analysed by karyotyping (2)." ] ] ] "textoCompleto" => "IntroductionIn the general population, the prevalence of global developmental delay/intellectual disability (GDD/ID) is estimated at 1–3%,<a class="elsevierStyleCrossRef" href="#bib0180">1</a> the prevalence of autism spectrum disorder (ASD) at 0.7%,<a class="elsevierStyleCrossRef" href="#bib0185">2</a> and the prevalence of congenital anomalies (CAs) at 2–3%,<a class="elsevierStyleCrossRefs" href="#bib0180">1–3</a> constituting, overall, a significant health care and social burden. The genetic diagnosis of these patients is very useful in their clinical management, as it allows an accurate prognosis and, above all, is crucial to the prevention of new cases (genetic counselling for family planning). Until recently, these patients were assessed with a set of laboratory techniques, each with a low diagnostic yield in isolation. The most commonly used technique, conventional cytogenetic testing (karyotype analysis), can detect large losses or gains of genetic material and structural rearrangements in 3% to 5% of patients GDD/ID and/or CAs.<a class="elsevierStyleCrossRefs" href="#bib0180">1,4–6</a> To improve the diagnostic yield, conventional karyotype analysis has been supplemented with fluorescent in situ hybridisation (FISH) and multiplex ligation-dependent probe amplification (MLPA) techniques. Thanks to their introduction, the detection of abnormalities in patients with unexplained GDD/ID or CAs and normal results of karyotype analysis increased by 2.4–3.7% with subtelomere analysis<a class="elsevierStyleCrossRefs" href="#bib0210">7,8</a> and by 5.8% with screening for the most frequent microdeletion and microduplication syndromes.<a class="elsevierStyleCrossRef" href="#bib0220">9</a>The recent development of arrays for the detection of changes in gene dosage (single nucleotide polymorphism arrays [aSNPs] and comparative genomic hybridisation arrays [aCGHs]) has considerably increased the number of diagnoses, allowing molecular diagnosis in 15–20% of patients with GDD/ID, CAs or ASD.<a class="elsevierStyleCrossRef" href="#bib0200">5</a> Single nucleotide polymorphism arrays, originally designed to genotype human DNA at thousands of SNPs across the genome, also allow the assessment of the number of copies of DNA by comparing the intensity of patient DNA hybridisation with the signal intensity of the probes immobilised in the matrix or array.Comparative genomic hybridisation arrays allow the simultaneous examination of gene dosage at multiple loci of the genome by comparing the relative amount of DNA in 2 genomes (control and patient) marked with different fluorochromes bound to DNA fragments with a known sequence (probes) fixed to a glass slide or support. The fluorescence emitted at each point of the array reflects the relative amount of DNA, allowing the detection of gains or losses of genetic material in specific regions of the genome. A large number of aCGH commercial platforms are currently available, and their diagnostic yield varies significantly. Some platforms are based on bacterial artificial chromosomes (BAC) and others on oligonucleotides. Probes may be distributed at regular intervals to offer whole genome backbone coverage, placed in specific regions that have been associated with a specific disease, or a combination of both.<a class="elsevierStyleCrossRef" href="#bib0225">10</a> The International Standard Cytogenetic Array (ISCA) consortium has proposed standards that have been adopted by most array manufacturers. A multicentre study that compared the main commercial platforms currently available<a class="elsevierStyleCrossRef" href="#bib0230">11</a> concluded that oligonucleotide-based CGH arrays with an ISCA 8×60K design offer the highest benefit–cost ratio. For clinical and economic reasons, scientific guidelines recommend the use of array methods as the first-line diagnostic test in patients with ID/GDD, CA and/or ASD, replacing karyotype analysis, MLPA and FISH.<a class="elsevierStyleCrossRefs" href="#bib0200">5,12–16</a>In this article, we present our experience with the use of aCGH as a first-tier diagnostic test in 1000 patients with GDD/ID, CA, psychiatric disorders (ASD, ADHD, schizophrenia, bipolar disorder), epilepsy, short stature and other disorders (dysmorphic features, phenotypic abnormalities, myopathy, overgrowth), replacing techniques such as karyotype analysis, MLPA and FISH. This is the largest case series of these characteristics ever analysed in Spain, as studies published to date have had smaller samples or used aCGH as a third-tier test in patients with normal results of other diagnostic tests, such as karyotype analysis or MLPA.<a class="elsevierStyleCrossRef" href="#bib0260">17</a>Patients and methodsPatientsBetween January 2012 and January 2015, the Array Unit of the Section on Clinical and Molecular Genetics of the Hospital Universitario Vall d’Hebron of Barcelona performed a total of 1222 evaluations using the aCGH method. All these tests were preceded and also followed by a clinical visit. Of all these evaluations, 1000 corresponded to patients with one or more of the following disorders: GDD/ID, CA, psychiatric disorders (ASD, ADHD, schizophrenia, bipolar disorder), epilepsy, short stature, dysmorphic features, phenotypic abnormalities, myopathy or overgrowth syndrome. These patients had not yet undergone molecular testing of any kind and had been referred by the clinical genetics, neurology and paediatric endocrinology departments of the hospital. The remaining evaluations corresponded to 1 of the following 4 categories: (1) family screening (n=167); (2) evaluation of sonographic abnormalities in foetus (n=41); (3) characterisation of anomalies previously diagnosed with other methods, most frequently karyotype analysis (n=4) and (4) patients with positive results in previous genetic tests (n=10).MethodsTo determine the rate of detection of genetic abnormalities relative to the number of phenotypic abnormalities, we performed an exhaustive review of the health records of all patients to allow the correct interpretation of aCGH results. Through this review, we were able to establish a classification of the disorders present in the patients and count the number of patients whose phenotype fit into each of the categories. Patients included in the study could have 1 or more of the disorders in the classification (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>Patient DNA was purified from 3mL peripheral blood samples using the Gentra Puregene Blood kit (Cat. No. 158422, Qiagen, USA) following the directions of the manufacturer. In a few cases, DNA was purified using a variety of methods in other facilities or hospital laboratories.We obtained the informed consent of the parents before performing the diagnostic tests.We validated the aCGH method using 2 different oligonucleotide-based array platforms: the CGH Microarray kit 4×180K (Cat. No. G4426B, Agilent Technologies, USA), with ∼180000 evenly spaced backbone probes, and CGH Microarray Kit 8×60K ISCA (Cat. No. G4827A, Agilent Technologies, USA) with fewer probes (∼60000) including 40208 backbone probes and 18851 with denser spacing in ISCA-recommended regions. Tests were performed following the directions of the manufacturer. We decided to perform all aCGH tests using a 8×60K ISCA-design platform on account of its higher yield. The images were scanned at a 3-micron resolution (DNA microarray scanner, Cat. No. G2505C, Agilent Technologies, United States) and analysed with the software Cytogenomics 2.1 (Agilent Technologies, USA). To guide the interpretation of the potential pathogenicity of the copy-number variants (CNVs) detected by aCGH and their gene products, we used EasyArray, a software developed in house using the Python and Visual Basic programming languages. EasyArray compares each of the detected CNVs with the data of control individuals included in the Database of Genomic Variants (<a id="intr0010" class="elsevierStyleInterRef" href="http://dgv.tcag.ca/dgv/app/home">http://dgv.tcag.ca/dgv/app/home</a>) and an in-house database that includes the main microdeletion/microduplication syndromes, and also checks whether their gene products are included in the UniProt genetic disorder database (<a id="intr0015" class="elsevierStyleInterRef" href="http://www.uniprot.org/">http://www.uniprot.org/</a>). Lastly, EasyArray facilitates the consultation of the ISCA Consortium (<a id="intr0020" class="elsevierStyleInterRef" href="https://www.iscaconsortium.org/">https://www.iscaconsortium.org</a>), GeneCards (<a id="intr0025" class="elsevierStyleInterRef" href="http://www.genecards.org/">http://www.genecards.org</a>), OMIM (<a id="intr0030" class="elsevierStyleInterRef" href="http://www.omim.org/">http://www.omim.org</a>) and Decipher (<a id="intr0035" class="elsevierStyleInterRef" href="https://decipher.sanger.ac.uk/">https://decipher.sanger.ac.uk</a>) databases. The programme guides the classification of CNVs as pathogenic, benign or of uncertain significance, and facilitates the writing of reports in adherence to the guidelines of the American College of Medical Genetics.<a class="elsevierStyleCrossRef" href="#bib0240">13</a> To reduce the number of family screenings and achieve a balance between clinical and analytical sensibility, we did not explore CNVs of uncertain significance sized less than 400kb.<a class="elsevierStyleCrossRef" href="#bib0200">5</a> All detected CNVs known to be pathogenic or of uncertain significance were confirmed by FISH, MLPA, karyotype analysis or a second aCGH.We performed the statistical analysis with the software SPSS version 15.0, using the chi square test to assess the potential association between diagnostic power and the number of phenotypic abnormalities in a single patient.Finally, in order to compare the diagnostic yield and cost of the different techniques in our population, every abnormality detected by aCGH as the first-tier test was re-evaluated to determine whether it would have been detected with subtelomeric MLPA (P070 probemix, MRC Holland, Netherlands), MLPA assays for the detection of recurrent microdeletions and microduplications (P245 and P297, MRC Holland, Netherlands) and conventional karyotype analysis (aberrations >6Mb)<a class="elsevierStyleCrossRef" href="#bib0265">18</a> with changes in banding patterns considered sufficient by an experienced cytogeneticist. To analyse the cost per test, we followed the guidelines of the Consensus on the Use of Arrays in Clinical Genetics.<a class="elsevierStyleCrossRef" href="#bib0255">16</a>ResultsWhen we compared the results obtained with the 2 different aCGH microarray kits (4×180K and 8×60K ISCA v2, both from Agilent Technologies) we found a clearly higher specificity in the detection of pathogenic CNVs in the 8×60K ISCA v2 microarray. For example, a pathogenic 0.043Mb deletion was detected by only 4 probes using the 4×180K microarray compared to 11 probes using the 8×60K ISCA v2 microarray. In another instance, a pathogenic duplication that affected the entire RAF1 gene was detected by 10 probes using the 4×180K microarray and by 18 probes using the 8×60K ISCA v2 microarray. In light of these results, we decided to use the 8×60K ISCA v2 format, which detected pathogenic genetic imbalances in 14% of the patients (140/1000), and more than one pathogenic CNV in 17 cases. Genetic imbalances of more than 400kb of uncertain significance (variants of uncertain significance [VOUS]) were detected in 6.1% of the patients (61/1.000).Pathogenic CNVs were detected in 18.9% of patients with GDD/ID (77/406), 13.7% of patients with CAs (54/394), 9.76% of patients with psychiatric disorders (16/164), 7.02% of patients with epilepsy (4/57) and 13.3% of patients referred for evaluation of short stature (14/105). The diagnostic yield was 12.08% (36/298) for the heterogeneous group of disorders grouped under the “other” category (including dysmorphic features, phenotypic abnormalities, myopathy, paresis and overgrowth). The most frequent CAs were abnormalities of the central nervous system, corresponding to 14.9% of the total diagnoses (16/107), and congenital heart defects, corresponding to 10.6% (20/188). In the psychiatric disorders group, the greatest proportion corresponded to patients with ASD, which amounted to 8.9% (12/134) of the total diagnoses (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).When we grouped patients by number of phenotypic abnormalities, we found a statistically significant increase in diagnostic yield in patients with a greater number of phenotypic abnormalities (P=.0223) (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>).<elsevierMultimedia ident="tbl0010"></elsevierMultimedia>In our series, we detected mosaic microdeletions and microduplications, such as, for example, a 12.6Mb 1p36 deletion in a patient with heart disease that was confirmed by FISH in 9.8% of the cells in a blood culture sample, a 61.38Mb 1q21.1-q32.1 duplication in a patient with epilepsy confirmed by karyotype analysis and FISH in 1.2% of metaphase chromosomes, and a 14.6Mb l 18q21.31-q22.2 interstitial deletion in a patient with GDD that was not detected by the software but visually discernible in the data plot that it generated, with the deletion present in 43.3% of analysed metaphase chromosomes (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>).<elsevierMultimedia ident="fig0005"></elsevierMultimedia>Last of all, after re-evaluating the anomalies detected by aCGH in the 140 patients, we found that 43 (30.7%) would have been detected by other techniques: 6 (4.2%) with conventional karyotype analysis, 66 (4.3%) with karyotype analysis and MLPA, and 31 (22.1%) with MLPA.DiscussionThis article presents the largest series of patients with various diseases evaluated by aCGH as the first-tier test in Spain, as the series published to date had either been smaller or used aCGH as a third-tier test in patients that had normal results with other techniques, such as karyotype analysis and MLPA.<a class="elsevierStyleCrossRef" href="#bib0260">17</a>Since abnormalities were detected in 14% of patients (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>), our findings confirm that at present, aCGH is the technique with the highest diagnostic yield when used as a single test in patients with GDD/ID, CAs and ASD.<a class="elsevierStyleCrossRef" href="#bib0200">5</a> Its diagnostic yield is not homogeneous and varies widely depending on the type and number of phenotypic abnormalities in the patient (<a class="elsevierStyleCrossRefs" href="#tbl0005">Tables 1 and 2</a>), as observed in our study and those published by other authors (references in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).The classical indications for evaluation with aCGH include GDD/ID, ASD and CA,<a class="elsevierStyleCrossRef" href="#bib0200">5</a> for which the detection rates with this technique are 18.9%, 14.8% and 13.7%, respectively. Our results and those of other authors<a class="elsevierStyleCrossRef" href="#bib0270">19</a> suggest that short stature should also be considered an indication for evaluation with aCGH, as the test detected abnormalities in 13.3% (14/105) of these patients, of which only 21.42% (3/14) involved the SHOX gene. Our findings also suggest that isolated epilepsy in the absence of malformation of the central nervous system could also be an indication for aCGH screening, as the test allowed molecular diagnosis of 7% of these patients.As an added value, aCGH allows a more accurate characterisation of genetic abnormalities compared to commercial FISH or MLPA kits, which may have significant implications for reproductive counselling. For example, <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a> shows a deletion that affects the SHOX gene and other non-pseudoautosomal genes, such as ARSE, in female carriers with short stature and diseased males with a much more severe phenotype including short stature, chondrodysplasia punctata and GDD/ID.<elsevierMultimedia ident="fig0010"></elsevierMultimedia>The use of aCGH allows diagnosis of microdeletion syndromes with atypical breakpoints that may be undetectable by FISH, the most widely used diagnostic method. Specifically, our analysis of these series allowed us to detect a novel recurrent breakpoint in the Williams–Beuren syndrome critical region that, in cases of deletion, allows the partial hybridisation of the most widely used commercial FISH assays, resulting in false negatives.<a class="elsevierStyleCrossRef" href="#bib0275">20</a>Comparative genomic hybridisation can identify gains and losses of genetic material more precisely than karyotype analysis, but it cannot detect balanced rearrangements (mainly translocations and inversions) that may in some cases be pathological. However, we must take into account that such rearrangements account for a very small proportion of clinically relevant genetic abnormalities.<a class="elsevierStyleCrossRefs" href="#bib0200">5,21</a>Comparative genomic cytogenetic arrays detect the presence of mosaicism when intermediate levels of fluorescence are produced, although determining the level of mosaicism may be difficult. Our findings were heterogeneous in this regard, for while the system readily detected abnormalities that were only present in 9.8% or 1.2% of analysed metaphase chromosomes (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>A and B), some mosaics in which the abnormalities were present in more than 40% of metaphase chromosomes caused such subtle changes in fluorescence that they were not detected by the Cytogenomics analytical software, although they were visible in the plot that it generated (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>C). A possible explanation is that different techniques analyse different cell populations: T cells from cell cultures stimulated with phytohaemagglutinin for karyotype analysis and FISH assays, compared to every type of nucleated blood cell in aCGH.The differences in the detection rate based on the indication for testing may account for the disparity of the published results, with rates as extreme as the 7.6% reported by Shen et al.<a class="elsevierStyleCrossRef" href="#bib0285">22</a> and the 35% reported by Aradhya et al.<a class="elsevierStyleCrossRef" href="#bib0290">23</a> Both studies analysed the genome with a similar resolution (35kb) but differed as to the population under analysis: in the first study, the population was vaguely defined from a phenotypic standpoint, whereas the second study selected patients with phenotypes considered highly suggestive of the presence of CNVs. The large case series published in the literature that have used aCGH as the first-line diagnostic test, such as the series of 8300 patients published by Ahn et al.<a class="elsevierStyleCrossRef" href="#bib0295">24</a> and the series of 8789 patients published by Shaffer et al.,<a class="elsevierStyleCrossRef" href="#bib0205">6</a> identified a considerable number of pathogenic CNVs but provided little information about patient phenotypes. On the other hand, the case series that have documented patient phenotypes in detail have usually been small and focused on specific diseases, as occurred in the study published by Roselló et al.,<a class="elsevierStyleCrossRef" href="#bib0300">25</a> whose sample consisted of 246 patients with ID. Our case series presents the results obtained using aCGH as the first-tier test in 1000 patients with a detailed phenotypic characterisation.Thus, our study allowed us to reliably compare the effectiveness and efficiency of the approach of using aCGH as the first-tier diagnostic test for the detection of genetic imbalances compared to the conventional strategy of using karyotype analysis and MLPA with the possible addition of aCGH as a third-tier test (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>). Comparing published case series of patients evaluated by karyotype analysis, FISH, MLPA or aCGH poses challenges, as different studies analyse different populations. Our study allowed us to make an approximate assessment based on a single population, with the assumption that aCGH detects nearly all clinically relevant abnormalities. The traditional strategy of using karyotype analysis and the MLPA assays currently available for these diseases (2 kits for recurrent genomic imbalances and 1 kit for subtelomeric abnormalities) would have led to diagnosis in only 43 (30.7%) of the 140 patients with abnormalities detected by aCGH at an approximate cost of 326.000€ (1000 karyotype analyses+988 MLPA assays), to which we would have to add the cost of performing 957 aCGHs to reach a diagnosis in all 140 patients, for an overall cost of 702107€ (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>). The evaluation of the same patients using only aCGH would cost approximately 355.390€. In short, the traditional approach of using MLPA and karyotype analysis would have achieved less than one third of the diagnoses made in our sample, while achieving the detection of 100% of the abnormalities detectable by aCGH would increase the cost by a factor of 1.97.<elsevierMultimedia ident="fig0015"></elsevierMultimedia>Our findings illustrate the effectiveness and efficiency of using aCGH as the first-tier test for genetic diagnosis in patients with GDD/ID, CAs, ASD, short stature and epilepsy. These results and the cost–benefit analysis support the inclusion of this method in the Spanish public health system to supplement or substitute karyotype analysis, MLPA and FISH methods.Comparative genomic hybridisation methods are constantly evolving, and new array formats have been recently developed that include backbone and targeted probes designed according to the ISCA Consortium standards and that guarantee coverage of a significant number of genes at the exon level. In this context, further studies are needed to reassess and compare the costs and benefits 8×60K and 4×180K aCGH platforms.FundingThe study was partially funded by a grant from the Fondo de Investigaciones Sanitarias (Health Care Research Fund) of the Spanish Ministry of Health and Consumption (grant PS09/00632).Conflicts of interestThe authors have no conflicts of interest to declare." "textoCompletoSecciones" => array:1 [ "secciones" => array:11 [ 0 => array:3 [ "identificador" => "xres1066006" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background and objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Patients and method" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1013876" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1066007" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Fundamento y objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Pacientes y método" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1013875" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Patients and methods" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Patients" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Methods" ] ] ] 6 => array:2 [ "identificador" => "sec0025" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0030" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0035" "titulo" => "Funding" ] 9 => array:2 [ "identificador" => "sec0040" "titulo" => "Conflicts of interest" ] 10 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2017-04-05" "fechaAceptado" => "2017-07-19" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1013876" "palabras" => array:6 [ 0 => "Comparative genomic hybridisation array" 1 => "Microdeletion syndrome" 2 => "Intellectual disability" 3 => "Global developmental delay" 4 => "Autism spectrum disorders" 5 => "Congenital malformation" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1013875" "palabras" => array:6 [ 0 => "Array de hibridación genómica comparada" 1 => "Síndrome de microdeleción" 2 => "Discapacidad intelectual" 3 => "Retraso global del desarrollo" 4 => "Trastornos del espectro autista" 5 => "Malformación congénita" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "Background and objectiveConventional cytogenetics diagnoses 3–5% of patients with unexplained developmental delay/intellectual disability and/or multiple congenital anomalies. The Multiplex Ligation-dependent Probe Amplification increases diagnostic rates from between 2.4 and 5.8%. Currently the comparative genomic hybridisation array or aCGH is the highest performing diagnostic tool in patients with developmental delay/intellectual disability, congenital anomalies and autism spectrum disorders. Our aim is to evaluate the efficiency of the use of aCGH as first-line test in these and other indications (epilepsy, short stature). Patients and methodA total of 1000 patients referred due to one or more of the abovementioned disorders were analysed by aCGH. ResultsPathogenic genomic imbalances were detected in 14% of the cases, with a variable distribution of diagnosis according to the phenotypes: 18.9% of patients with developmental delay/intellectual disability; 13.7% of multiple congenital anomalies, 9.76% of psychiatric pathologies, 7.02% of patients with epilepsy, and 13.3% of patients with short stature. Within the multiple congenital anomalies, central nervous system abnormalities and congenital heart diseases accounted for 14.9% and 10.6% of diagnoses, respectively. Among the psychiatric disorders, patients with autism spectrum disorders accounted for 8.9% of the diagnoses. ConclusionsOur results demonstrate the effectiveness and efficiency of the use of aCGH as the first line test in genetic diagnosis of patients suspected of genomic imbalances, supporting its inclusion within the National Health System." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background and objective" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Patients and method" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "Fundamento y objetivoLa citogenética convencional detecta un 3-5% de los pacientes con retraso global del desarrollo/discapacidad intelectual y/o malformaciones congénitas. La amplificación de sondas múltiples dependientes de ligación permite incrementar la tasa diagnóstica entre 2,4-5,8%. Actualmente, los arrays de hibridación genómica comparada o aCGH son la herramienta diagnóstica con mayor rendimiento en estos pacientes, en malformaciones congénitas y trastornos del espectro autista. El objetivo del presente trabajo ha sido evaluar la eficiencia del uso del aCGH como técnica de primera línea diagnóstica en estas y otras indicaciones (epilepsia, talla baja). Pacientes y métodoSe ha estudiado a 1.000 pacientes afectados por las patologías mencionadas mediante la técnica de aCGH. ResultadosSe detectaron desequilibrios de efecto patogénico en un 14% de los pacientes (140/1.000). Según el fenotipo, se diagnosticaron un 18,9% de los pacientes afectados de retraso global del desarrollo/discapacidad intelectual; un 13,7% de las malformaciones congénitas; un 9,76% de las patologías psiquiátricas, un 7,02% de los casos con epilepsia y un 13,3% de los pacientes con talla baja. Dentro de las malformaciones congénitas destacan las del sistema nervioso central con un 14,9% y las cardiopatías congénitas con un 10,6% de diagnósticos. En las patologías psiquiátricas destacan los pacientes con trastornos del espectro autista, con un 8,9% de diagnósticos. ConclusionesNuestros resultados demuestran la efectividad y la eficiencia de la utilización del aCGH como test de primera línea en el diagnóstico genético de los pacientes con sospecha de desequilibrios genómicos. Todo ello avala su inclusión dentro del Sistema Nacional de Salud." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Fundamento y objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Pacientes y método" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] ] "NotaPie" => array:2 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "Please cite this article as: Castells-Sarret N, Cueto-González AM, Borregan M, López-Grondona F, Miró R, Tizzano E, et al. Array CGH como primera opción en el diagnóstico genético: 1.000 casos y análisis de coste-beneficio. An Pediatr (Barc). 2018;89:3–11." ] 1 => array:2 [ "etiqueta" => "☆☆" "nota" => "Previous presentations: part of this study has been included in the doctoral dissertation of Neus Castells Sarret, titled Array CGH como primera opción en el diagnóstico genético postnatal, defended on December 1, 2015 at the Hospital Universitario Vall d’Hebron, Universitat Autònoma de Barcelona. The study has also been presented as a poster titled 1.000 estudios de aCGH como técnica de primera línea: la experiencia del Hospital Vall d’Hebron at the XXVIII Congreso Nacional de la Asociación Española de Genética Humana (AEGH); May 13–15, 2015; Palma de Majorca, Spain. Part of this study was the subject of the article titled A novel recurrent breakpoint responsible for rearrangements in the Williams–Beuren region; Cytogenet Genome Res. 2015;146(3):181–186." ] ] "multimedia" => array:5 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 2425 "Ancho" => 3170 "Tamanyo" => 546099 ] ] "descripcion" => array:1 [ "en" => "Cases of mosaicism detected by comparative genomic hybridisation. (A) Mosaic deletion at 1p36 in a patient with heart disease: detected by aCGH (1) and confirmed in 9.8% of cells analysed using FISH. There is only one signal in the nucleus of the image, marked by an arrow, corresponding to 1p36 (2). (B) 1q21.1-q32.1 duplication in a patient with epilepsy: detected by aCGH (1), confirmed in 1.2% of cells analysed with FISH. The three bottom signals in the nucleus of the image, pointed by the arrow, correspond to region 1q21q32.1 (2) and karyotype (3). (C) 18q21.31-q22.2 deletion in a patient with GDD: detected by aCGH (1) and confirmed in 43.3% of cells analysed by karyotyping (2)." ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1824 "Ancho" => 2488 "Tamanyo" => 285009 ] ] "descripcion" => array:1 [ "en" => "(A) Pedigree of a family carrying a Xp22.33-p22.31 deletion. (B) Result of the analysis by aCGH, which evinced loss of the SHOX and ARSE genes, the main genes involved in the phenotypic abnormalities." ] ] 2 => array:7 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1391 "Ancho" => 3167 "Tamanyo" => 292087 ] ] "descripcion" => array:1 [ "en" => "Calculation of costs for each of the two approaches to diagnosis. (A) Calculation of the cost of using aCGH as the first-tier diagnostic test. (B) Calculation of the costs of using aCGH as the third-tier test after karyotype analysis and MLPA. Of the 140 cases diagnosed by means of aCGH, 12 would have been detected by karyotype analysis (of which 2 were aneuploidies and 10 genetic imbalances >6Mb); 31 would have been detected by MLPA using assays for assessment of subtelomeric and recurrent genetic imbalances, and the remaining 97 cases would have been diagnosed using aCGH in patients with normal results of karyotype analysis and MLPA. Costs<a class="elsevierStyleCrossRef" href="#bib0255">16</a>: karyotype 121.55€/test; MLPA 243.37€/3 MLPA assays; aCGH 355.39€/array. The traditional approach of karyotype analysis and MLPA (strategy B) would have achieved fewer than 1/3 of the diagnoses made in our sample (43/140). Adding performance of aCGH to diagnose 100% of abnormalities would increase the overall cost by a factor of 1.97 compared to using aCGH as the first and only diagnostic test (strategy A)." ] ] 3 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "Psychiatric disorders include: ASD, ADHD, schizophrenia/psychosis, bipolar disorder. Other includes: dysmorphic features, phenotypic abnormalities, myopathy, paresis, overgrowth syndrome. The patients had one or more of the described phenotypes.ASD, autism spectrum disorder; CHD, congenital heart defect; CNS, central nervous system; GDD/ID, global developmental delay/intellectual disability; ADHD, attention-deficit hyperactivity disorder." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Indication/disease \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Total patients tested (N=1000) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Patients with abnormal results (n=140) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Detection rate (%) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Detection rate in the literature (%) \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">GDD/ID \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">406 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">77 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">18.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">10–19<a class="elsevierStyleCrossRefs" href="#bib0305">26–28</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Malformation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">394 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">54 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">10–12<a class="elsevierStyleCrossRefs" href="#bib0200">5,28</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">CHD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">188 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">10.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">3.6–29<a class="elsevierStyleCrossRefs" href="#bib0320">29,30</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">CNS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">107 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">14.5–22.5<a class="elsevierStyleCrossRefs" href="#bib0330">31,10</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Autism spectrum disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">164 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">9.75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">ASD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">134 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7<a class="elsevierStyleCrossRef" href="#bib0335">32</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Epilepsy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7.01 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7.3–20<a class="elsevierStyleCrossRefs" href="#bib0340">33–35</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Short stature \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">105 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">14 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">13.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">10<a class="elsevierStyleCrossRef" href="#bib0270">19</a> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Other \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">298 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">36 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">12.08 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1817903.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Diagnostic detection rate achieved with aCGH for each of the phenotypes under study. Comparison with data from the literature." ] ] 4 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "The differences between groups were statistically significant (P=.0223)." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Number of phenotypic abnormalities documented in health records \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Total patients tested (n=1000) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Patients with abnormal aCGH results (n=140) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Diagnosis (%) \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " align="char" valign="top">>2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">68 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">20 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="char" valign="top">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">288 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">48 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">16.6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="char" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">644 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">77 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">11.9 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab1817904.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Proportion of patients that received a diagnosis by means of aCGH by number of phenotypic abnormalities presented by the patient." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:35 [ 0 => array:3 [ "identificador" => "bib0180" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Practice parameter: evaluation of the child with global developmental delay: report of the Quality Standards Subcommittee of the American Academy of Neurology and The Practice Committee of the Child Neurology Society" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "M. 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"vista" => "all" ] ] ] "idiomaDefecto" => "en" "url" => "/23412879/0000008900000001/v2_201807280416/S2341287918300875/v2_201807280416/en/main.assets" "Apartado" => array:4 [ "identificador" => "26005" "tipo" => "SECCION" "en" => array:2 [ "titulo" => "Original Articles" "idiomaDefecto" => true ] "idiomaDefecto" => "en" ] "PDF" => "https://static.elsevier.es/multimedia/23412879/0000008900000001/v2_201807280416/S2341287918300875/v2_201807280416/en/main.pdf?idApp=UINPBA00005H&text.app=https://analesdepediatria.org/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2341287918300875?idApp=UINPBA00005H"]

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Comparative genomic hybridisation as a first option in genetic diagnosis: 1000 cases and a cost–benefit analysis

Array CGH como primera opción en el diagnóstico genético: 1.000 casos y análisis de coste-beneficio

Neus Castells-Sarreta,b,

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ncastellssarret@gmail.com

Corresponding author.

, Anna M. Cueto-Gonzáleza,c, Mar Borreganc, Fermina López-Grondonaa, Rosa Mirób, Eduardo Tizzanoa,d, Alberto Plajaa,b

a Àrea de Genètica Clínica i Molecular, Hospital Vall d’Hebron, Barcelona, Spain

b Departament de Biologia Cel·lular, Fisiologia i Immunologia, Universitat Autònoma de Barcelona, Bellaterra, Barcelona, Spain

c Facultat de Medicina, Departament de Ciències Morfològiques, Universitat Autònoma de Barcelona, Bellaterra, Barcelona, Spain

d CIBERER, Barcelona, Spain

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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">In the general population&#44; the prevalence of global developmental delay&#47;intellectual disability &#40;GDD&#47;ID&#41; is estimated at 1&#8211;3&#37;&#44;<a class="elsevierStyleCrossRef" href="#bib0180"><span class="elsevierStyleSup">1</span></a> the prevalence of autism spectrum disorder &#40;ASD&#41; at 0&#46;7&#37;&#44;<a class="elsevierStyleCrossRef" href="#bib0185"><span class="elsevierStyleSup">2</span></a> and the prevalence of congenital anomalies &#40;CAs&#41; at 2&#8211;3&#37;&#44;<a class="elsevierStyleCrossRefs" href="#bib0180"><span class="elsevierStyleSup">1&#8211;3</span></a> constituting&#44; overall&#44; a significant health care and social burden&#46; The genetic diagnosis of these patients is very useful in their clinical management&#44; as it allows an accurate prognosis and&#44; above all&#44; is crucial to the prevention of new cases &#40;genetic counselling for family planning&#41;&#46; Until recently&#44; these patients were assessed with a set of laboratory techniques&#44; each with a low diagnostic yield in isolation&#46; The most commonly used technique&#44; conventional cytogenetic testing &#40;karyotype analysis&#41;&#44; can detect large losses or gains of genetic material and structural rearrangements in 3&#37; to 5&#37; of patients GDD&#47;ID and&#47;or CAs&#46;<a class="elsevierStyleCrossRefs" href="#bib0180"><span class="elsevierStyleSup">1&#44;4&#8211;6</span></a> To improve the diagnostic yield&#44; conventional karyotype analysis has been supplemented with fluorescent in situ hybridisation &#40;FISH&#41; and multiplex ligation-dependent probe amplification &#40;MLPA&#41; techniques&#46; Thanks to their introduction&#44; the detection of abnormalities in patients with unexplained GDD&#47;ID or CAs and normal results of karyotype analysis increased by 2&#46;4&#8211;3&#46;7&#37; with subtelomere analysis<a class="elsevierStyleCrossRefs" href="#bib0210"><span class="elsevierStyleSup">7&#44;8</span></a> and by 5&#46;8&#37; with screening for the most frequent microdeletion and microduplication syndromes&#46;<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">9</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">The recent development of arrays for the detection of changes in gene dosage &#40;single nucleotide polymorphism arrays &#91;aSNPs&#93; and comparative genomic hybridisation arrays &#91;aCGHs&#93;&#41; has considerably increased the number of diagnoses&#44; allowing molecular diagnosis in 15&#8211;20&#37; of patients with GDD&#47;ID&#44; CAs or ASD&#46;<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">5</span></a> Single nucleotide polymorphism arrays&#44; originally designed to genotype human DNA at thousands of SNPs across the genome&#44; also allow the assessment of the number of copies of DNA by comparing the intensity of patient DNA hybridisation with the signal intensity of the probes immobilised in the matrix or array&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">Comparative genomic hybridisation arrays allow the simultaneous examination of gene dosage at multiple loci of the genome by comparing the relative amount of DNA in 2 genomes &#40;control and patient&#41; marked with different fluorochromes bound to DNA fragments with a known sequence &#40;probes&#41; fixed to a glass slide or support&#46; The fluorescence emitted at each point of the array reflects the relative amount of DNA&#44; allowing the detection of gains or losses of genetic material in specific regions of the genome&#46; A large number of aCGH commercial platforms are currently available&#44; and their diagnostic yield varies significantly&#46; Some platforms are based on bacterial artificial chromosomes &#40;BAC&#41; and others on oligonucleotides&#46; Probes may be distributed at regular intervals to offer whole genome backbone coverage&#44; placed in specific regions that have been associated with a specific disease&#44; or a combination of both&#46;<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">10</span></a> The International Standard Cytogenetic Array &#40;ISCA&#41; consortium has proposed standards that have been adopted by most array manufacturers&#46; A multicentre study that compared the main commercial platforms currently available<a class="elsevierStyleCrossRef" href="#bib0230"><span class="elsevierStyleSup">11</span></a> concluded that oligonucleotide-based CGH arrays with an ISCA 8&#215;60K design offer the highest benefit&#8211;cost ratio&#46; For clinical and economic reasons&#44; scientific guidelines recommend the use of array methods as the first-line diagnostic test in patients with ID&#47;GDD&#44; CA and&#47;or ASD&#44; replacing karyotype analysis&#44; MLPA and FISH&#46;<a class="elsevierStyleCrossRefs" href="#bib0200"><span class="elsevierStyleSup">5&#44;12&#8211;16</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">In this article&#44; we present our experience with the use of aCGH as a first-tier diagnostic test in 1000 patients with GDD&#47;ID&#44; CA&#44; psychiatric disorders &#40;ASD&#44; ADHD&#44; schizophrenia&#44; bipolar disorder&#41;&#44; epilepsy&#44; short stature and other disorders &#40;dysmorphic features&#44; phenotypic abnormalities&#44; myopathy&#44; overgrowth&#41;&#44; replacing techniques such as karyotype analysis&#44; MLPA and FISH&#46; This is the largest case series of these characteristics ever analysed in Spain&#44; as studies published to date have had smaller samples or used aCGH as a third-tier test in patients with normal results of other diagnostic tests&#44; such as karyotype analysis or MLPA&#46;<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">17</span></a></p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Patients and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Patients</span><p id="par0025" class="elsevierStylePara elsevierViewall">Between January 2012 and January 2015&#44; the Array Unit of the Section on Clinical and Molecular Genetics of the Hospital Universitario Vall d&#8217;Hebron of Barcelona performed a total of 1222 evaluations using the aCGH method&#46; All these tests were preceded and also followed by a clinical visit&#46; Of all these evaluations&#44; 1000 corresponded to patients with one or more of the following disorders&#58; GDD&#47;ID&#44; CA&#44; psychiatric disorders &#40;ASD&#44; ADHD&#44; schizophrenia&#44; bipolar disorder&#41;&#44; epilepsy&#44; short stature&#44; dysmorphic features&#44; phenotypic abnormalities&#44; myopathy or overgrowth syndrome&#46; These patients had not yet undergone molecular testing of any kind and had been referred by the clinical genetics&#44; neurology and paediatric endocrinology departments of the hospital&#46; The remaining evaluations corresponded to 1 of the following 4 categories&#58; &#40;1&#41; family screening &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>167&#41;&#59; &#40;2&#41; evaluation of sonographic abnormalities in foetus &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>41&#41;&#59; &#40;3&#41; characterisation of anomalies previously diagnosed with other methods&#44; most frequently karyotype analysis &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>4&#41; and &#40;4&#41; patients with positive results in previous genetic tests &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>10&#41;&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Methods</span><p id="par0030" class="elsevierStylePara elsevierViewall">To determine the rate of detection of genetic abnormalities relative to the number of phenotypic abnormalities&#44; we performed an exhaustive review of the health records of all patients to allow the correct interpretation of aCGH results&#46; Through this review&#44; we were able to establish a classification of the disorders present in the patients and count the number of patients whose phenotype fit into each of the categories&#46; Patients included in the study could have 1 or more of the disorders in the classification &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0035" class="elsevierStylePara elsevierViewall">Patient DNA was purified from 3<span class="elsevierStyleHsp" style=""></span>mL peripheral blood samples using the Gentra Puregene Blood kit &#40;Cat&#46; No&#46; 158422&#44; Qiagen&#44; USA&#41; following the directions of the manufacturer&#46; In a few cases&#44; DNA was purified using a variety of methods in other facilities or hospital laboratories&#46;</p><p id="par0040" class="elsevierStylePara elsevierViewall">We obtained the informed consent of the parents before performing the diagnostic tests&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">We validated the aCGH method using 2 different oligonucleotide-based array platforms&#58; the CGH Microarray kit 4&#215;180K &#40;Cat&#46; No&#46; G4426B&#44; Agilent Technologies&#44; USA&#41;&#44; with &#8764;180<span class="elsevierStyleHsp" style=""></span>000 evenly spaced backbone probes&#44; and CGH Microarray Kit 8&#215;60K ISCA &#40;Cat&#46; No&#46; G4827A&#44; Agilent Technologies&#44; USA&#41; with fewer probes &#40;&#8764;60<span class="elsevierStyleHsp" style=""></span>000&#41; including 40<span class="elsevierStyleHsp" style=""></span>208 backbone probes and 18<span class="elsevierStyleHsp" style=""></span>851 with denser spacing in ISCA-recommended regions&#46; Tests were performed following the directions of the manufacturer&#46; We decided to perform all aCGH tests using a 8&#215;60K ISCA-design platform on account of its higher yield&#46; The images were scanned at a 3-micron resolution &#40;DNA microarray scanner&#44; Cat&#46; No&#46; G2505C&#44; Agilent Technologies&#44; United States&#41; and analysed with the software Cytogenomics 2&#46;1 &#40;Agilent Technologies&#44; USA&#41;&#46; To guide the interpretation of the potential pathogenicity of the copy-number variants &#40;CNVs&#41; detected by aCGH and their gene products&#44; we used EasyArray&#44; a software developed in house using the Python and Visual Basic programming languages&#46; EasyArray compares each of the detected CNVs with the data of control individuals included in the Database of Genomic Variants &#40;<a id="intr0010" class="elsevierStyleInterRef" href="http://dgv.tcag.ca/dgv/app/home">http&#58;&#47;&#47;dgv&#46;tcag&#46;ca&#47;dgv&#47;app&#47;home</a>&#41; and an in-house database that includes the main microdeletion&#47;microduplication syndromes&#44; and also checks whether their gene products are included in the UniProt genetic disorder database &#40;<a id="intr0015" class="elsevierStyleInterRef" href="http://www.uniprot.org/">http&#58;&#47;&#47;www&#46;uniprot&#46;org&#47;</a>&#41;&#46; Lastly&#44; EasyArray facilitates the consultation of the ISCA Consortium &#40;<a id="intr0020" class="elsevierStyleInterRef" href="https://www.iscaconsortium.org/">https&#58;&#47;&#47;www&#46;iscaconsortium&#46;org</a>&#41;&#44; GeneCards &#40;<a id="intr0025" class="elsevierStyleInterRef" href="http://www.genecards.org/">http&#58;&#47;&#47;www&#46;genecards&#46;org</a>&#41;&#44; OMIM &#40;<a id="intr0030" class="elsevierStyleInterRef" href="http://www.omim.org/">http&#58;&#47;&#47;www&#46;omim&#46;org</a>&#41; and Decipher &#40;<a id="intr0035" class="elsevierStyleInterRef" href="https://decipher.sanger.ac.uk/">https&#58;&#47;&#47;decipher&#46;sanger&#46;ac&#46;uk</a>&#41; databases&#46; The programme guides the classification of CNVs as pathogenic&#44; benign or of uncertain significance&#44; and facilitates the writing of reports in adherence to the guidelines of the American College of Medical Genetics&#46;<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">13</span></a> To reduce the number of family screenings and achieve a balance between clinical and analytical sensibility&#44; we did not explore CNVs of uncertain significance sized less than 400<span class="elsevierStyleHsp" style=""></span>kb&#46;<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">5</span></a> All detected CNVs known to be pathogenic or of uncertain significance were confirmed by FISH&#44; MLPA&#44; karyotype analysis or a second aCGH&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">We performed the statistical analysis with the software SPSS version 15&#46;0&#44; using the chi square test to assess the potential association between diagnostic power and the number of phenotypic abnormalities in a single patient&#46;</p><p id="par0055" class="elsevierStylePara elsevierViewall">Finally&#44; in order to compare the diagnostic yield and cost of the different techniques in our population&#44; every abnormality detected by aCGH as the first-tier test was re-evaluated to determine whether it would have been detected with subtelomeric MLPA &#40;P070 probemix&#44; MRC Holland&#44; Netherlands&#41;&#44; MLPA assays for the detection of recurrent microdeletions and microduplications &#40;P245 and P297&#44; MRC Holland&#44; Netherlands&#41; and conventional karyotype analysis &#40;aberrations &#62;6<span class="elsevierStyleHsp" style=""></span>Mb&#41;<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">18</span></a> with changes in banding patterns considered sufficient by an experienced cytogeneticist&#46; To analyse the cost per test&#44; we followed the guidelines of the Consensus on the Use of Arrays in Clinical Genetics&#46;<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">16</span></a></p></span></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Results</span><p id="par0060" class="elsevierStylePara elsevierViewall">When we compared the results obtained with the 2 different aCGH microarray kits &#40;4&#215;180K and 8&#215;60K ISCA v2&#44; both from Agilent Technologies&#41; we found a clearly higher specificity in the detection of pathogenic CNVs in the 8&#215;60K ISCA v2 microarray&#46; For example&#44; a pathogenic 0&#46;043<span class="elsevierStyleHsp" style=""></span>Mb deletion was detected by only 4 probes using the 4&#215;180K microarray compared to 11 probes using the 8&#215;60K ISCA v2 microarray&#46; In another instance&#44; a pathogenic duplication that affected the entire <span class="elsevierStyleItalic">RAF1</span> gene was detected by 10 probes using the 4&#215;180K microarray and by 18 probes using the 8&#215;60K ISCA v2 microarray&#46; In light of these results&#44; we decided to use the 8&#215;60K ISCA v2 format&#44; which detected pathogenic genetic imbalances in 14&#37; of the patients &#40;140&#47;1000&#41;&#44; and more than one pathogenic CNV in 17 cases&#46; Genetic imbalances of more than 400<span class="elsevierStyleHsp" style=""></span>kb of uncertain significance &#40;variants of uncertain significance &#91;VOUS&#93;&#41; were detected in 6&#46;1&#37; of the patients &#40;61&#47;1&#46;000&#41;&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall">Pathogenic CNVs were detected in 18&#46;9&#37; of patients with GDD&#47;ID &#40;77&#47;406&#41;&#44; 13&#46;7&#37; of patients with CAs &#40;54&#47;394&#41;&#44; 9&#46;76&#37; of patients with psychiatric disorders &#40;16&#47;164&#41;&#44; 7&#46;02&#37; of patients with epilepsy &#40;4&#47;57&#41; and 13&#46;3&#37; of patients referred for evaluation of short stature &#40;14&#47;105&#41;&#46; The diagnostic yield was 12&#46;08&#37; &#40;36&#47;298&#41; for the heterogeneous group of disorders grouped under the &#8220;other&#8221; category &#40;including dysmorphic features&#44; phenotypic abnormalities&#44; myopathy&#44; paresis and overgrowth&#41;&#46; The most frequent CAs were abnormalities of the central nervous system&#44; corresponding to 14&#46;9&#37; of the total diagnoses &#40;16&#47;107&#41;&#44; and congenital heart defects&#44; corresponding to 10&#46;6&#37; &#40;20&#47;188&#41;&#46; In the psychiatric disorders group&#44; the greatest proportion corresponded to patients with ASD&#44; which amounted to 8&#46;9&#37; &#40;12&#47;134&#41; of the total diagnoses &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46;</p><p id="par0070" class="elsevierStylePara elsevierViewall">When we grouped patients by number of phenotypic abnormalities&#44; we found a statistically significant increase in diagnostic yield in patients with a greater number of phenotypic abnormalities &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>&#46;0223&#41; &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">In our series&#44; we detected mosaic microdeletions and microduplications&#44; such as&#44; for example&#44; a 12&#46;6<span class="elsevierStyleHsp" style=""></span>Mb 1p36 deletion in a patient with heart disease that was confirmed by FISH in 9&#46;8&#37; of the cells in a blood culture sample&#44; a 61&#46;38<span class="elsevierStyleHsp" style=""></span>Mb 1q21&#46;1-q32&#46;1 duplication in a patient with epilepsy confirmed by karyotype analysis and FISH in 1&#46;2&#37; of metaphase chromosomes&#44; and a 14&#46;6<span class="elsevierStyleHsp" style=""></span>Mb l 18q21&#46;31-q22&#46;2 interstitial deletion in a patient with GDD that was not detected by the software but visually discernible in the data plot that it generated&#44; with the deletion present in 43&#46;3&#37; of analysed metaphase chromosomes &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#41;&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0080" class="elsevierStylePara elsevierViewall">Last of all&#44; after re-evaluating the anomalies detected by aCGH in the 140 patients&#44; we found that 43 &#40;30&#46;7&#37;&#41; would have been detected by other techniques&#58; 6 &#40;4&#46;2&#37;&#41; with conventional karyotype analysis&#44; 66 &#40;4&#46;3&#37;&#41; with karyotype analysis and MLPA&#44; and 31 &#40;22&#46;1&#37;&#41; with MLPA&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Discussion</span><p id="par0085" class="elsevierStylePara elsevierViewall">This article presents the largest series of patients with various diseases evaluated by aCGH as the first-tier test in Spain&#44; as the series published to date had either been smaller or used aCGH as a third-tier test in patients that had normal results with other techniques&#44; such as karyotype analysis and MLPA&#46;<a class="elsevierStyleCrossRef" href="#bib0260"><span class="elsevierStyleSup">17</span></a></p><p id="par0090" class="elsevierStylePara elsevierViewall">Since abnormalities were detected in 14&#37; of patients &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#44; our findings confirm that at present&#44; aCGH is the technique with the highest diagnostic yield when used as a single test in patients with GDD&#47;ID&#44; CAs and ASD&#46;<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">5</span></a> Its diagnostic yield is not homogeneous and varies widely depending on the type and number of phenotypic abnormalities in the patient &#40;<a class="elsevierStyleCrossRefs" href="#tbl0005">Tables 1 and 2</a>&#41;&#44; as observed in our study and those published by other authors &#40;references in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">The classical indications for evaluation with aCGH include GDD&#47;ID&#44; ASD and CA&#44;<a class="elsevierStyleCrossRef" href="#bib0200"><span class="elsevierStyleSup">5</span></a> for which the detection rates with this technique are 18&#46;9&#37;&#44; 14&#46;8&#37; and 13&#46;7&#37;&#44; respectively&#46; Our results and those of other authors<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">19</span></a> suggest that short stature should also be considered an indication for evaluation with aCGH&#44; as the test detected abnormalities in 13&#46;3&#37; &#40;14&#47;105&#41; of these patients&#44; of which only 21&#46;42&#37; &#40;3&#47;14&#41; involved the <span class="elsevierStyleItalic">SHOX</span> gene&#46; Our findings also suggest that isolated epilepsy in the absence of malformation of the central nervous system could also be an indication for aCGH screening&#44; as the test allowed molecular diagnosis of 7&#37; of these patients&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">As an added value&#44; aCGH allows a more accurate characterisation of genetic abnormalities compared to commercial FISH or MLPA kits&#44; which may have significant implications for reproductive counselling&#46; For example&#44; <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a> shows a deletion that affects the <span class="elsevierStyleItalic">SHOX</span> gene and other non-pseudoautosomal genes&#44; such as <span class="elsevierStyleItalic">ARSE</span>&#44; in female carriers with short stature and diseased males with a much more severe phenotype including short stature&#44; chondrodysplasia punctata and GDD&#47;ID&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0105" class="elsevierStylePara elsevierViewall">The use of aCGH allows diagnosis of microdeletion syndromes with atypical breakpoints that may be undetectable by FISH&#44; the most widely used diagnostic method&#46; Specifically&#44; our analysis of these series allowed us to detect a novel recurrent breakpoint in the Williams&#8211;Beuren syndrome critical region that&#44; in cases of deletion&#44; allows the partial hybridisation of the most widely used commercial FISH assays&#44; resulting in false negatives&#46;<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">20</span></a></p><p id="par0110" class="elsevierStylePara elsevierViewall">Comparative genomic hybridisation can identify gains and losses of genetic material more precisely than karyotype analysis&#44; but it cannot detect balanced rearrangements &#40;mainly translocations and inversions&#41; that may in some cases be pathological&#46; However&#44; we must take into account that such rearrangements account for a very small proportion of clinically relevant genetic abnormalities&#46;<a class="elsevierStyleCrossRefs" href="#bib0200"><span class="elsevierStyleSup">5&#44;21</span></a></p><p id="par0115" class="elsevierStylePara elsevierViewall">Comparative genomic cytogenetic arrays detect the presence of mosaicism when intermediate levels of fluorescence are produced&#44; although determining the level of mosaicism may be difficult&#46; Our findings were heterogeneous in this regard&#44; for while the system readily detected abnormalities that were only present in 9&#46;8&#37; or 1&#46;2&#37; of analysed metaphase chromosomes &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>A and B&#41;&#44; some mosaics in which the abnormalities were present in more than 40&#37; of metaphase chromosomes caused such subtle changes in fluorescence that they were not detected by the Cytogenomics analytical software&#44; although they were visible in the plot that it generated &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>C&#41;&#46; A possible explanation is that different techniques analyse different cell populations&#58; T cells from cell cultures stimulated with phytohaemagglutinin for karyotype analysis and FISH assays&#44; compared to every type of nucleated blood cell in aCGH&#46;</p><p id="par0120" class="elsevierStylePara elsevierViewall">The differences in the detection rate based on the indication for testing may account for the disparity of the published results&#44; with rates as extreme as the 7&#46;6&#37; reported by Shen et al&#46;<a class="elsevierStyleCrossRef" href="#bib0285"><span class="elsevierStyleSup">22</span></a> and the 35&#37; reported by Aradhya et al&#46;<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">23</span></a> Both studies analysed the genome with a similar resolution &#40;35<span class="elsevierStyleHsp" style=""></span>kb&#41; but differed as to the population under analysis&#58; in the first study&#44; the population was vaguely defined from a phenotypic standpoint&#44; whereas the second study selected patients with phenotypes considered highly suggestive of the presence of CNVs&#46; The large case series published in the literature that have used aCGH as the first-line diagnostic test&#44; such as the series of 8300 patients published by Ahn et al&#46;<a class="elsevierStyleCrossRef" href="#bib0295"><span class="elsevierStyleSup">24</span></a> and the series of 8789 patients published by Shaffer et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bib0205"><span class="elsevierStyleSup">6</span></a> identified a considerable number of pathogenic CNVs but provided little information about patient phenotypes&#46; On the other hand&#44; the case series that have documented patient phenotypes in detail have usually been small and focused on specific diseases&#44; as occurred in the study published by Rosell&#243; et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bib0300"><span class="elsevierStyleSup">25</span></a> whose sample consisted of 246 patients with ID&#46; Our case series presents the results obtained using aCGH as the first-tier test in 1000 patients with a detailed phenotypic characterisation&#46;</p><p id="par0125" class="elsevierStylePara elsevierViewall">Thus&#44; our study allowed us to reliably compare the effectiveness and efficiency of the approach of using aCGH as the first-tier diagnostic test for the detection of genetic imbalances compared to the conventional strategy of using karyotype analysis and MLPA with the possible addition of aCGH as a third-tier test &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46; Comparing published case series of patients evaluated by karyotype analysis&#44; FISH&#44; MLPA or aCGH poses challenges&#44; as different studies analyse different populations&#46; Our study allowed us to make an approximate assessment based on a single population&#44; with the assumption that aCGH detects nearly all clinically relevant abnormalities&#46; The traditional strategy of using karyotype analysis and the MLPA assays currently available for these diseases &#40;2 kits for recurrent genomic imbalances and 1 kit for subtelomeric abnormalities&#41; would have led to diagnosis in only 43 &#40;30&#46;7&#37;&#41; of the 140 patients with abnormalities detected by aCGH at an approximate cost of 326&#46;000<span class="elsevierStyleHsp" style=""></span>&#8364; &#40;1000 karyotype analyses<span class="elsevierStyleHsp" style=""></span>&#43;<span class="elsevierStyleHsp" style=""></span>988 MLPA assays&#41;&#44; to which we would have to add the cost of performing 957 aCGHs to reach a diagnosis in all 140 patients&#44; for an overall cost of 702<span class="elsevierStyleHsp" style=""></span>107<span class="elsevierStyleHsp" style=""></span>&#8364; &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#46; The evaluation of the same patients using only aCGH would cost approximately 355&#46;390<span class="elsevierStyleHsp" style=""></span>&#8364;&#46; In short&#44; the traditional approach of using MLPA and karyotype analysis would have achieved less than one third of the diagnoses made in our sample&#44; while achieving the detection of 100&#37; of the abnormalities detectable by aCGH would increase the cost by a factor of 1&#46;97&#46;</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia><p id="par0130" class="elsevierStylePara elsevierViewall">Our findings illustrate the effectiveness and efficiency of using aCGH as the first-tier test for genetic diagnosis in patients with GDD&#47;ID&#44; CAs&#44; ASD&#44; short stature and epilepsy&#46; These results and the cost&#8211;benefit analysis support the inclusion of this method in the Spanish public health system to supplement or substitute karyotype analysis&#44; MLPA and FISH methods&#46;</p><p id="par0135" class="elsevierStylePara elsevierViewall">Comparative genomic hybridisation methods are constantly evolving&#44; and new array formats have been recently developed that include backbone and targeted probes designed according to the ISCA Consortium standards and that guarantee coverage of a significant number of genes at the exon level&#46; In this context&#44; further studies are needed to reassess and compare the costs and benefits 8&#215;60K and 4&#215;180K aCGH platforms&#46;</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Funding</span><p id="par0140" class="elsevierStylePara elsevierViewall">The study was partially funded by a grant from the <span class="elsevierStyleGrantSponsor" id="gs1">Fondo de Investigaciones Sanitarias &#40;Health Care Research Fund&#41; of the Spanish Ministry of Health and Consumption</span> &#40;grant <span class="elsevierStyleGrantNumber" refid="gs1">PS09&#47;00632</span>&#41;&#46;</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Conflicts of interest</span><p id="par0145" class="elsevierStylePara elsevierViewall">The authors have no conflicts of interest to declare&#46;</p></span></span>"
    "textoCompletoSecciones" => array:1 [
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              "titulo" => "Background and objective"
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          "titulo" => "Introduction"
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          "titulo" => "Patients and methods"
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    "fechaRecibido" => "2017-04-05"
    "fechaAceptado" => "2017-07-19"
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          "clase" => "keyword"
          "titulo" => "Keywords"
          "identificador" => "xpalclavsec1013876"
          "palabras" => array:6 [
            0 => "Comparative genomic hybridisation array"
            1 => "Microdeletion syndrome"
            2 => "Intellectual disability"
            3 => "Global developmental delay"
            4 => "Autism spectrum disorders"
            5 => "Congenital malformation"
          ]
        ]
      ]
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        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Palabras clave"
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          "palabras" => array:6 [
            0 => "Array de hibridaci&#243;n gen&#243;mica comparada"
            1 => "S&#237;ndrome de microdeleci&#243;n"
            2 => "Discapacidad intelectual"
            3 => "Retraso global del desarrollo"
            4 => "Trastornos del espectro autista"
            5 => "Malformaci&#243;n cong&#233;nita"
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        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background and objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Conventional cytogenetics diagnoses 3&#8211;5&#37; of patients with unexplained developmental delay&#47;intellectual disability and&#47;or multiple congenital anomalies&#46; The Multiplex Ligation-dependent Probe Amplification increases diagnostic rates from between 2&#46;4 and 5&#46;8&#37;&#46; Currently the comparative genomic hybridisation array or aCGH is the highest performing diagnostic tool in patients with developmental delay&#47;intellectual disability&#44; congenital anomalies and autism spectrum disorders&#46; Our aim is to evaluate the efficiency of the use of aCGH as first-line test in these and other indications &#40;epilepsy&#44; short stature&#41;&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Patients and method</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">A total of 1000 patients referred due to one or more of the abovementioned disorders were analysed by aCGH&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Pathogenic genomic imbalances were detected in 14&#37; of the cases&#44; with a variable distribution of diagnosis according to the phenotypes&#58; 18&#46;9&#37; of patients with developmental delay&#47;intellectual disability&#59; 13&#46;7&#37; of multiple congenital anomalies&#44; 9&#46;76&#37; of psychiatric pathologies&#44; 7&#46;02&#37; of patients with epilepsy&#44; and 13&#46;3&#37; of patients with short stature&#46; Within the multiple congenital anomalies&#44; central nervous system abnormalities and congenital heart diseases accounted for 14&#46;9&#37; and 10&#46;6&#37; of diagnoses&#44; respectively&#46; Among the psychiatric disorders&#44; patients with autism spectrum disorders accounted for 8&#46;9&#37; of the diagnoses&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Our results demonstrate the effectiveness and efficiency of the use of aCGH as the first line test in genetic diagnosis of patients suspected of genomic imbalances&#44; supporting its inclusion within the National Health System&#46;</p></span>"
        "secciones" => array:4 [
          0 => array:2 [
            "identificador" => "abst0005"
            "titulo" => "Background and objective"
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          1 => array:2 [
            "identificador" => "abst0010"
            "titulo" => "Patients and method"
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        "titulo" => "Resumen"
        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Fundamento y objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">La citogen&#233;tica convencional detecta un 3-5&#37; de los pacientes con retraso global del desarrollo&#47;discapacidad intelectual y&#47;o malformaciones cong&#233;nitas&#46; La amplificaci&#243;n de sondas m&#250;ltiples dependientes de ligaci&#243;n permite incrementar la tasa diagn&#243;stica entre 2&#44;4-5&#44;8&#37;&#46; Actualmente&#44; los arrays de hibridaci&#243;n gen&#243;mica comparada o aCGH son la herramienta diagn&#243;stica con mayor rendimiento en estos pacientes&#44; en malformaciones cong&#233;nitas y trastornos del espectro autista&#46; El objetivo del presente trabajo ha sido evaluar la eficiencia del uso del aCGH como t&#233;cnica de primera l&#237;nea diagn&#243;stica en estas y otras indicaciones &#40;epilepsia&#44; talla baja&#41;&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Pacientes y m&#233;todo</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Se ha estudiado a 1&#46;000 pacientes afectados por las patolog&#237;as mencionadas mediante la t&#233;cnica de aCGH&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Se detectaron desequilibrios de efecto patog&#233;nico en un 14&#37; de los pacientes &#40;140&#47;1&#46;000&#41;&#46; Seg&#250;n el fenotipo&#44; se diagnosticaron un 18&#44;9&#37; de los pacientes afectados de retraso global del desarrollo&#47;discapacidad intelectual&#59; un 13&#44;7&#37; de las malformaciones cong&#233;nitas&#59; un 9&#44;76&#37; de las patolog&#237;as psiqui&#225;tricas&#44; un 7&#44;02&#37; de los casos con epilepsia y un 13&#44;3&#37; de los pacientes con talla baja&#46; Dentro de las malformaciones cong&#233;nitas destacan las del sistema nervioso central con un 14&#44;9&#37; y las cardiopat&#237;as cong&#233;nitas con un 10&#44;6&#37; de diagn&#243;sticos&#46; En las patolog&#237;as psiqui&#225;tricas destacan los pacientes con trastornos del espectro autista&#44; con un 8&#44;9&#37; de diagn&#243;sticos&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Nuestros resultados demuestran la efectividad y la eficiencia de la utilizaci&#243;n del aCGH como test de primera l&#237;nea en el diagn&#243;stico gen&#233;tico de los pacientes con sospecha de desequilibrios gen&#243;micos&#46; Todo ello avala su inclusi&#243;n dentro del Sistema Nacional de Salud&#46;</p></span>"
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as&#58; Castells-Sarret N&#44; Cueto-Gonz&#225;lez AM&#44; Borregan M&#44; L&#243;pez-Grondona F&#44; Mir&#243; R&#44; Tizzano E&#44; et al&#46; Array CGH como primera opci&#243;n en el diagn&#243;stico gen&#233;tico&#58; 1&#46;000 casos y an&#225;lisis de coste-beneficio&#46; An Pediatr &#40;Barc&#41;&#46; 2018&#59;89&#58;3&#8211;11&#46;</p>"
      ]
      1 => array:2 [
        "etiqueta" => "&#9734;&#9734;"
        "nota" => "<p class="elsevierStyleNotepara" id="npar0010">Previous presentations&#58; part of this study has been included in the doctoral dissertation of Neus Castells Sarret&#44; titled <span class="elsevierStyleItalic">Array CGH como primera opci&#243;n en el diagn&#243;stico gen&#233;tico postnatal</span>&#44; defended on December 1&#44; 2015 at the Hospital Universitario Vall d&#8217;Hebron&#44; Universitat Aut&#242;noma de Barcelona&#46; The study has also been presented as a poster titled <span class="elsevierStyleItalic">1&#46;000 estudios de aCGH como t&#233;cnica de primera l&#237;nea&#58; la experiencia del Hospital Vall d&#8217;Hebron</span> at the XXVIII Congreso Nacional de la Asociaci&#243;n Espa&#241;ola de Gen&#233;tica Humana &#40;AEGH&#41;&#59; May 13&#8211;15&#44; 2015&#59; Palma de Majorca&#44; Spain&#46; Part of this study was the subject of the article titled <span class="elsevierStyleItalic">A novel recurrent breakpoint responsible for rearrangements in the Williams&#8211;Beuren region</span>&#59; Cytogenet Genome Res&#46; 2015&#59;146&#40;3&#41;&#58;181&#8211;186&#46;</p>"
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          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Cases of mosaicism detected by comparative genomic hybridisation&#46; &#40;A&#41; Mosaic deletion at 1p36 in a patient with heart disease&#58; detected by aCGH &#40;1&#41; and confirmed in 9&#46;8&#37; of cells analysed using FISH&#46; There is only one signal in the nucleus of the image&#44; marked by an arrow&#44; corresponding to 1p36 &#40;2&#41;&#46; &#40;B&#41; 1q21&#46;1-q32&#46;1 duplication in a patient with epilepsy&#58; detected by aCGH &#40;1&#41;&#44; confirmed in 1&#46;2&#37; of cells analysed with FISH&#46; The three bottom signals in the nucleus of the image&#44; pointed by the arrow&#44; correspond to region 1q21q32&#46;1 &#40;2&#41; and karyotype &#40;3&#41;&#46; &#40;C&#41; 18q21&#46;31-q22&#46;2 deletion in a patient with GDD&#58; detected by aCGH &#40;1&#41; and confirmed in 43&#46;3&#37; of cells analysed by karyotyping &#40;2&#41;&#46;</p>"
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          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">&#40;A&#41; Pedigree of a family carrying a Xp22&#46;33-p22&#46;31 deletion&#46; &#40;B&#41; Result of the analysis by aCGH&#44; which evinced loss of the <span class="elsevierStyleItalic">SHOX</span> and <span class="elsevierStyleItalic">ARSE</span> genes&#44; the main genes involved in the phenotypic abnormalities&#46;</p>"
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          "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Calculation of costs for each of the two approaches to diagnosis&#46; &#40;A&#41; Calculation of the cost of using aCGH as the first-tier diagnostic test&#46; &#40;B&#41; Calculation of the costs of using aCGH as the third-tier test after karyotype analysis and MLPA&#46; Of the 140 cases diagnosed by means of aCGH&#44; 12 would have been detected by karyotype analysis &#40;of which 2 were aneuploidies and 10 genetic imbalances &#62;6<span class="elsevierStyleHsp" style=""></span>Mb&#41;&#59; 31 would have been detected by MLPA using assays for assessment of subtelomeric and recurrent genetic imbalances&#44; and the remaining 97 cases would have been diagnosed using aCGH in patients with normal results of karyotype analysis and MLPA&#46; Costs<a class="elsevierStyleCrossRef" href="#bib0255"><span class="elsevierStyleSup">16</span></a>&#58; karyotype 121&#46;55<span class="elsevierStyleHsp" style=""></span>&#8364;&#47;test&#59; MLPA 243&#46;37<span class="elsevierStyleHsp" style=""></span>&#8364;&#47;3 MLPA assays&#59; aCGH 355&#46;39<span class="elsevierStyleHsp" style=""></span>&#8364;&#47;array&#46;</p> <p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">The traditional approach of karyotype analysis and MLPA &#40;strategy B&#41; would have achieved fewer than 1&#47;3 of the diagnoses made in our sample &#40;43&#47;140&#41;&#46; Adding performance of aCGH to diagnose 100&#37; of abnormalities would increase the overall cost by a factor of 1&#46;97 compared to using aCGH as the first and only diagnostic test &#40;strategy A&#41;&#46;</p>"
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          "leyenda" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Psychiatric disorders include&#58; ASD&#44; ADHD&#44; schizophrenia&#47;psychosis&#44; bipolar disorder&#46; Other includes&#58; dysmorphic features&#44; phenotypic abnormalities&#44; myopathy&#44; paresis&#44; overgrowth syndrome&#46; The patients had one or more of the described phenotypes&#46;</p><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">ASD&#44; autism spectrum disorder&#59; CHD&#44; congenital heart defect&#59; CNS&#44; central nervous system&#59; GDD&#47;ID&#44; global developmental delay&#47;intellectual disability&#59; ADHD&#44; attention-deficit hyperactivity disorder&#46;</p>"
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                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Indication&#47;disease&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Total patients tested &#40;<span class="elsevierStyleItalic">N</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>1000&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Patients with abnormal results &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>140&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Detection rate &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Detection rate in the literature &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">GDD&#47;ID&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">406&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">77&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">18&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">10&#8211;19<a class="elsevierStyleCrossRefs" href="#bib0305"><span class="elsevierStyleSup">26&#8211;28</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Malformation&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">394&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">54&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">13&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">10&#8211;12<a class="elsevierStyleCrossRefs" href="#bib0200"><span class="elsevierStyleSup">5&#44;28</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">CHD&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">188&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">20&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">10&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">3&#46;6&#8211;29<a class="elsevierStyleCrossRefs" href="#bib0320"><span class="elsevierStyleSup">29&#44;30</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">CNS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">107&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">16&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">14&#46;9&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Autism spectrum disorder&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">10<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">19</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
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Article information

ISSN: 23412879
Original language: English

DOI:10.1016/j.anpede.2017.07.009

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Year/Month	Html	Pdf	Total

2024 November	1	3	4
2024 October	83	56	139
2024 September	66	39	105
2024 August	83	54	137
2024 July	62	34	96
2024 June	87	32	119
2024 May	98	45	143
2024 April	72	52	124
2024 March	65	54	119
2024 February	82	33	115
2024 January	75	30	105
2023 December	77	32	109
2023 November	81	32	113
2023 October	69	34	103
2023 September	56	23	79
2023 August	57	21	78
2023 July	76	28	104
2023 June	71	28	99
2023 May	80	34	114
2023 April	48	25	73
2023 March	127	33	160
2023 February	94	24	118
2023 January	78	40	118
2022 December	107	42	149
2022 November	98	61	159
2022 October	92	90	182
2022 September	59	41	100
2022 August	83	48	131
2022 July	75	45	120
2022 June	75	47	122
2022 May	85	44	129
2022 April	47	43	90
2022 March	93	62	155
2022 February	89	32	121
2022 January	109	63	172
2021 December	98	61	159
2021 November	93	62	155
2021 October	111	66	177
2021 September	96	42	138
2021 August	64	60	124
2021 July	93	28	121
2021 June	131	69	200
2021 May	124	53	177
2021 April	681	91	772
2021 March	128	38	166
2021 February	72	22	94
2021 January	59	29	88
2020 December	51	39	90
2020 November	56	21	77
2020 October	72	24	96
2020 September	70	26	96
2020 August	65	9	74
2020 July	63	29	92
2020 June	63	14	77
2020 May	77	25	102
2020 April	76	24	100
2020 March	42	15	57
2020 February	59	15	74
2020 January	66	21	87
2019 December	68	26	94
2019 November	57	15	72
2019 October	70	12	82
2019 September	44	17	61
2019 August	37	19	56
2019 July	37	17	54
2019 June	31	16	47
2019 May	64	16	80
2019 April	71	32	103
2019 March	56	25	81
2019 February	49	30	79
2019 January	44	21	65
2018 December	46	41	87
2018 November	143	34	177
2018 October	117	34	151
2018 September	77	54	131
2018 July	0	0	0
2018 June	0	5	5

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