DÄ internationalArchive12/2019Exome Sequencing in Children

Original article

Exome Sequencing in Children

Undiagnosed developmental delay and neurological illness

Dtsch Arztebl Int 2019; 116(12): 197-204; DOI: 10.3238/arztebl.2019.0197

Mahler, E A; Johannsen, J; Tsiakas, K; Kloth, K; Lüttgen, S; Mühlhausen, C; Alhaddad, B; Haack, T B; Strom, T M; Kortüm, F; Meitinger, T; Muntau, A C; Santer, R; Kubisch, C; Lessel, D; Denecke, J; Hempel, M

Background: In developed countries, global developmental disorders are encountered in approximately 1% of all children. The causes are manifold, and no exogenous cause can be identified in about half of the affected children. The parallel investigation of the coding sequences of all genes of the affected individual (whole exome sequencing, WES) has developed into a successful diagnostic method for identifying the cause of the problem. It is not yet clear, however, when WES should best be used in routine clinical practice in order to exploit the potential of this method to the fullest.

Methods: In an interdisciplinary study, we carried out standardized clinical phenotyping and a systematic genetic analysis (WES of the index patient and his or her parents, so-called trio WES) in 50 children with developmental disturbances of unclear etiology and with nonspecific neurological manifestations.

Results: In 21 children (42% of the collective), we were able to identify the cause of the disorder by demonstrating a mutation in a gene known to be associated with disease. Three of these children subsequently underwent specific treatment. In 22 other children (44%), we detected possibly etiological changes in candidate genes not currently known to be associated with human disease.

Conclusion: Our detection rate of at least 42% is high in comparison with the results obtained in other studies from Germany and other countries to date and implies that WES can be used to good effect as a differential diagnostic tool in pediatric neurology. WES should be carried out in both the index patient and his or her parents (trio-WES) and accompanied by close interdisciplinary collaboration of human geneticists and pediatricians, by comprehensive and targeted phenotyping (also after the diagnosis is established), and by the meticulous evaluation of all gene variants.

LNSLNS

Divergence from the expected psychomotor development (global developmental delay) is observed in around 1% of children in the industrialized countries (1, 2). Global developmental delay thus accounts for a considerable proportion of all cases of neuropediatric illness, although there are no reliable statistical data on the prevalence of neurological diseases in childhood. The symptoms of global developmental disorders are often unspecific, so that in many cases no precise diagnosis is possible. Establishment of the diagnosis is, however, a necessary precondition for initiating any disease-specific treatment that may be available, drawing up an individualized support and prevention program, assessment of the developmental prognosis, and accurate estimation of the risk of similar disorders in the patient’s siblings or other family members.

There are multiple different factors that may be responsible for developmental delay, and in around half of the children affected no causative exogenous factor is identified (3). Probably most of these cases are of genetic origin (39). Genetic techniques therefore play a crucial role in identifying the cause and pinpointing the diagnosis in this group of patients. In the past, molecular genetic tests were extremely laborious, usually proceeding “gene by gene.” However, the recently introduced “next-generation” sequencing (NGS) enables analysis of large numbers of genes (right up to the whole human genome) in a short amount of time at reasonable cost (1012) (Table 1).

Comparison of sequencing techniques
Comparison of sequencing techniques
Table 1
Comparison of sequencing techniques

The ethical aspects of such all-embracing genetic analysis techniques have been and continue to be widely discussed (1316). Particularly intensively debated topics are the explanation of and consent to genetic analysis, storage of and access to genetic data, and how to deal with incidental findings. The latter are genetic variants that happen to be identified in the course of NGS-based analyses. They are not related to the index patient’s illness, but mean there is an increased likelihood of a second, independent disease in the patient (and possibly his/her relatives). Country-specific and international guidelines and regulations vary widely in their recommendations on how to deal with incidental observations, and the debate is probably far from over. There is unanimity, however, on the need actively to include patients and guardians in the discussion of these questions.

Despite this, NGS methods have become established in routine genetic diagnosis. The technique generally used in Germany is “panel diagnostics,” in which a defined number of genes are investigated depending on the disease of interest. In highly heterogeneous illnesses (e.g., unspecific childhood developmental disorders) with hundreds of associated genes it does not make sense to limit the amount of genes to be analyzed. Patients affected by such diseases should be offered analysis of their entire genetic coding material (i.e., all genomic regions that are translated into proteins = all exons of the circa 20 000 human genes), known as whole-exome sequencing (WES).

Numerous studies from various countries have shown that the causes of developmental disorders and neurological illnesses in childhood can often be uncovered by means of WES (8, 1725). The success rate of WES has been reported as 25 to 68% and is particularly high when:

  • The study group is highly selected (17, 22)
  • The exome sequencing is extended to parents (trio exome sequencing) and/or other family members (family exome sequencing) (17, 26)
  • The analysis of the exome data embraces all known genes, not only those associated with a human illness at the given point in time (27, 28).

It has not yet been adequately investigated how exome sequencing can be effectively integrated into concrete clinical routine (5).

Many questions remain unanswered. These include what patients should be offered WES, to what extent it should be extended to the patient’s relatives, and in what clinical and analytical context it should take place.

To address these questions, we carried out a single-center pilot study of 50 children with undiagnosed developmental delay and neurological illness presumed to be of genetic origin. Thorough clinical examination, biochemical analyses, electroencephalography, and diagnostic imaging were accompanied by trio WES.

The aim of this study was to establish a practical procedure for phenotyping and genotyping that would achieve a high rate of diagnosis for unspecific neurological illnesses of childhood and could be accommodated into the clinical routine.

Method

Study design

The study was a joint project of the Department of Pediatrics and the Institute of Human Genetics at the University Medical Center Hamburg-Eppendorf, Germany. Over a period of 17 months, a total of 50 consecutive children with undiagnosed neurological illnesses underwent a standardized assessment program in the context of a complex neuropediatric diagnostic work-up (German surgical procedure code [OPS] 1–942) (Figure 1, eMethods). The inclusion criteria were as follows:

  • Neurological symptoms (e.g., global developmental delay, ataxia, seizures)
  • Suspected genetic etiology (i.e., no sign of serious perinatal complications, infection, injury, other exogenic factors)
  • No specific provisional diagnosis
  • Signed consent from the parents, following appropriate explanation, for exhaustive investigations including trio WES
Study protocol including evaluation algorithm for genetic variants
Study protocol including evaluation algorithm for genetic variants
Figure 1
Study protocol including evaluation algorithm for genetic variants

The study was approved by the ethics committee of the Hamburg Medical Association (project number PV3802).

Phenotype documentation

The comprehensive assessment program always included detailed questioning about the medical history of the patient and their family, extensive clinical evaluation by a neuropediatrician and a clinical geneticist, wide-ranging investigation of blood, urine, and cerebrospinal fluid parameters, diagnostic imaging (1.5-T or 3-T cranial magnetic resonance imaging (cMRI), and electroencephalography (EEG). Depending on the clinical findings, other tests were added in individual patients, for example further diagnostic imaging procedures ( e.g., MR spectroscopy), audiometry, echocardiography, or ophthalmological examination. We documented the reported medical history and the clinical data systematically using the Phenomizer software (29), which is based on Human Phenotype Ontology (HPO) (30). The degree of cognitive and/or physical impairment was classified according to Zhang et al. (31) (eTable 1).

Classification of mental retardation (MR) according to Zhang et al. (e5)
Classification of mental retardation (MR) according to Zhang et al. (e5)
eTable 1
Classification of mental retardation (MR) according to Zhang et al. (e5)

Genotype documentation

The genetic data were obtained from WES of EDTA blood from each index patient and their biological parents (trio WES). The WES procedure is described in the eMethods. Closer attention was paid to genetic variants which were very rarely identified in the population (minor alleles frequency [MAF]; occurrence of the rarer allele in the population <0.01%) and which, according to several different bioinformatic prediction algorithms, impact negatively on gene function (functionally relevant variants). The variants filtered out in this way were mostly nonsynonymous point mutations (variants that changed the amino acid sequence in the coded protein), losses/gains of one or several base pairs (indels) or losses/gains of submicroscopic chromosome regions (microdeletions/microduplications; copy number variations [CNVs]). These affected a known disease gene or a candidate gene. More detailed information on the WES procedure and the classification of variants and genes can be found in the eMethods.

Interdisciplinary interpretation of findings and reverse phenotyping

In each individual case, the members of a multidisciplinary team consisting at least of pediatricians and human geneticists discussed the findings and assessed the potential relevance of the genetic variants identified in the context of the medical history and the patient’s symptoms. Whenever necessary, other experts (e.g., neuroradiologists) were added to the panel. In many cases the team ordered additional specific clinical investigations (reverse phenotyping) to enable more detailed assessment of a genetic variant. The results of reverse phenotyping were then interpreted by the assembled team.

Statistical analysis

Descriptive statistical analyses were carried out using the Statistical Package for the Social Sciences (SPSS, version 23).

Results

Study participants

The median age of the 50 unrelated children (19 girls [38%], 31 boys [62%]) at study inclusion was 2.5 years (range 4 days to 18 years; Figure 2). Thirty-three (66%) of them had already undergone genetic testing (chromosome analysis, array-based comparative genomic hybridization [array CGH]), and/or single-gene sequencing. In no case had the results been abnormal (for details see the eMethods).

Age at onset of illness (square) and age at inclusion in study (circle) for each of the 50 patients
Age at onset of illness (square) and age at inclusion in study (circle) for each of the 50 patients
Figure 2
Age at onset of illness (square) and age at inclusion in study (circle) for each of the 50 patients

Results of phenotyping

The first symptoms were observed at a median age of 2 months (0 days to 6 years; Figure 2). Sixteen patients (32%) had delayed development of motor functions and/or speech, six (12%) showed abdominal symptoms (e.g., omphalocele, esophageal stenosis/atresia, feeding difficulties), and five (10%) evinced ophthalmological abnormalities (e.g., congenital cataract, nystagmus, strabismus). A median 2.4 years (4 days to 18 years; Figure 2) elapsed between occurrence of the first symptoms and inclusion in the study.

In line with the inclusion criteria, all 50 patients had neurological symptoms at the time of entry into the study. These comprised global developmental delay (88%), cognitive impairment without motor symptoms (4%), or motor symptoms without cognitive impairment (8%). As classified according to Zhang et al. (31), the developmental disorder was mild in 10% of patients, moderate in 32%, severe in 56%, and profound in one patient. Psychomotor development was categorized in 68% of patients as “gradually progressive,” in 6% as “stagnating,” and in 26% as “regressive.” At the time of clinical examination, body weight, body length, and head circumference were abnormal (˂− 2 standard deviations [SD] or ˃ + 2 SD according to Kromeyer-Hauschild et al. [32]) in 13 (26%), 12 (24%), and 21 (42%) of patients, respectively. Thirty-six patients (72%) showed abnormalities of the head and neck (e.g., facial dysmorphism), 34 (68%) had abnormalities of the musculature (e.g., muscular hypotonia), and 28 (56%) exhibited ocular abnormalities (e.g., strabismus) (Figure 3). Further details of the phenotyping findings are documented in the eMethods and in eTable 2.

Clinical characterization of the study group according to the HPO system (HPO, Human Phenotype Ontology)
Clinical characterization of the study group according to the HPO system (HPO, Human Phenotype Ontology)
Figure 3
Clinical characterization of the study group according to the HPO system (HPO, Human Phenotype Ontology)
Findings of instrument-based diagnostic methods
Findings of instrument-based diagnostic methods
eTable 2
Findings of instrument-based diagnostic methods

Results of genotyping

In 21 patients (42%) we found a pathogenic variant (mutation) in a disease gene known at the time of analysis or a known disease-related microdeletion (Table 2, eTable 3). Twelve (57.1%) of these 21 mutations were de novo events, i.e., they had arisen in the index patient. In nine index patients (42.9%) the mutations were biallelic (on both alleles of the gene affected), so that the inheritance was autosomal recessive. Strikingly, during the course of our study variants in three genes (CHAMP1, SSR4, and SON) initially classified as candidate genes were convincingly shown by newly published data to be mutations in new disease genes.

Findings of whole-exome sequencing (WES)
Findings of whole-exome sequencing (WES)
Table 2
Findings of whole-exome sequencing (WES)

In an additional 22 patients (44%) we identified a variant in candidate genes that probably caused illness. The disease association of these candidate genes has been or is currently being investigated in international cooperation projects. Since the conclusion of our work, two of these 22 candidate genes have been confirmed as disease genes and the research to date supports a disease association for some of the others.In only seven patients there (14%) were no abnormal genetic findings.

Consequences for clinical care

In 17 (81%) of the 21 patients with a mutation in a known disease gene, diagnosis resulted in recommendations to change/modify the clinical management. In 14 children (66.7%) the recommendations affected the prevention and monitoring program (e.g., the institution of new follow-up investigations or discontinuation of existing investigations), and in 13 patients (62%) the individual support measures (e.g., use of sign language or a talker, planning of future education) were involved. Moreover, three patients (3/21 = 14%; 3/50 = 6%) were offered specific treatment: In an 11-month-old girl with developmental regression, severe muscular hypotonia, and eye movement disorders, treatment with L-Dopa was initiated immediately after the detection of compound heterozygous mutations in the tyrosine hydroxylase gene (TH-Segawa syndrome, OMIM #605407). This led to swift regression of the neurological symptoms and to catch-up development over the course of time. In a 4-year-old boy with global developmental delay, dystonia, and gait abnormality, treatment with trihexyphenidyl was started after identification of a de novo mutation in SGCE (dystonia type 11, OMIM #159900). Follow-up showed decreased severity of the dystonic movement disorder and improved gait. Detection of a homozygous mutation in ARSA (metachromatic leukodystrophy, OMIM #250100) in a 3-year-old boy with peripheral neuropathy and leukodystrophy led to his inclusion in a treatment study (eTable 4 and eTable 5).

Overview of recommendations for management of treatment in the 21 patients with a genetic diagnosis
Overview of recommendations for management of treatment in the 21 patients with a genetic diagnosis
eTable 5
Overview of recommendations for management of treatment in the 21 patients with a genetic diagnosis

Systematic documentation and comparative statistical evaluation of the implementation of the treatment recommendations and their success were not among the aims of our study and were in any case not compatible with the selected study design.

Discussion

Our standardized search for the cause of undiagnosed developmental delay and neurological illnesses in a pediatric collective revealed mutations in known disease genes compatible with the phenotype in 21 (42%) of 50 patients. This involved wide-ranging clinical, biochemical, and instrument-based investigations together with trio WES. Our rate of identification of the cause of developmental disorders in a general pediatric cohort is towards the high end of the spectrum of results from international research: comparable studies from, among other countries, Israel, the UK, and the USA report diagnosis rates of 25 to 49% (8, 20, 22, 24). Our findings emphasize that pediatric patients with unspecific neurological symptoms can often be helped by means of the powerful genetic diagnostic technique of exome sequencing.

Individual out-of-hospital exome sequencing is covered by German health insurance under EBM fee schedule code number 11514 (remuneration currently circa €3300). However, the necessary individual approval by the health insurance provider is rarely forthcoming. In the hospital setting, genetic diagnosis, including WES, can be carried out under OPS code 1-942.

The mutations affected 20 different disease genes in the 21 confidently diagnosed patients, reflecting the extreme heterogeneity of childhood developmental disorders and neuropediatric disorders and underlining the necessity of systematic genetic analyses (WES) in this group. Our experience leads us to recommend trio WES, because confident and effective identification of de novo (newly arising) mutations is facilitated by comparing the genetic variants in the index patient with those found in the patient’s parents. In fact, de novo mutations comprise a high proportion of the genetic causes of disease: in our study 57% of the mutations arose de novo, and in the DDD study the figure was as high as 65% (9).

Analysis of the genetic data was not limited to known disease genes, and indeed a high number of probably disease-relevant variants were found in various candidate genes. Even before the conclusion of the study, three genes we had originally categorized as candidate genes (CHAMP1, SSR4, SON) were reclassified as “new disease genes” (33, 34). After completion of the study there were 22 index patients (44%) with a probably disease-relevant variant in a candidate gene. We are convinced, on the basis of the trio WES data, bioinformatic predictions, published research, and data from cooperating study groups, that in the course of time most of these candidate genes will be confirmed as disease relevant and reclassified as new disease genes. As of November 2018, two of them (DHX30, ANO3) had already been reclassified, increasing our rate of diagnosis to 46% (23 of the 50 index patients).

Conclusion

This pilot study has confirmed the high diagnostic potential of exome sequencing in a heterogeneous cohort of neuropediatric patients whose unspecific symptoms gave no clues to the diagnosis. The high rate of successful diagnosis was achieved by means of a interdisciplinary clinical–genetic approach, with:

  • Detailed phenotyping, followed, whenever necessary, by specific investigations (reverse phenotyping)
  • Exome sequencing of the index patient and their parents (trio WES)
  • Comprehensive evaluation of the entire data obtained by exome sequencing
  • Interdisciplinary interpretation of the clinical and genetic data
  • Close cooperation and data sharing with physicians and study groups in Germany and other countries

Under these conditions exome sequencing is a highly powerful genetic investigation technique that can be used in patients with disease of probable genetic origin in whom no specific diagnosis is suspected. In pinpointing the diagnosis, it opens the door to the specific treatments that are increasingly becoming available for genetic diseases.

Limitations

One limitation of our study is the relatively small number of patients. However, data from independent international studies seem to show that the central results can be reproduced in a larger cohort of patients. It must be borne in mind that the detection rates relate to the data available at the time the study was carried out.

Acknowledgments
We are grateful to the patients who took part in this study and their families. We also thank all the clinicians who contributed data as well as the molecular geneticists, bioinformaticians, and laboratory technicians who lent us their assistance.

Compliance with ethical standards
We obtained signed consent from each study participant or, if applicable, their parents. All procedures in studies with human participants complied with the ethical standards of the institution and country concerned and adhered to the tenets of the Helsinki Declaration of 1964 and its subsequent revisions or to comparable ethical standards.

Conflict of interest statement
Prof. Meitinger is the director of a molecular genetics laboratory authorized to issue private invoices at Rechts der Isar Hospital, TUM, Munich.

Dr. Hempel and Prof. Kubisch also work at the Martin Zeitz Center for Rare Diseases in Hamburg. This center is a project partner of the health care project TRANSLATE NAMSE.

Prof. Muntau is a project partner of the health care project TRANSLATE NAMSE.

The remaining authors declare that no conflict of interest exists.

Manuscript submitted on 27 July 2018, revised version accepted on 17 January 2019

Translated from the original German by David Roseveare

Corresponding author
Dr. med. Maja Hempel
Institut für Humangenetik,
Universitätsklinikum Hamburg-Eppendorf
Martinistr. 52, 20246 Hamburg, Germany
m.hempel@uke.de

Supplementary material
For eReferences please refer to:
www.aerzteblatt-international.de/ref1219

eMethods, eTables:
www.aerzteblatt-international.de/19m0197

1.
Maulik PK, Mascarenhas MN, Mathers CD, Dua T, Saxena S: Prevalence of intellectual disability: a meta-analysis of population-based studies. Res Dev Disabil 2011; 32: 419–36 CrossRef MEDLINE
2.
McKenzie K, Milton M, Smith G, Ouellette-Kuntz H: Systematic review of the prevalence and incidence of intellectual disabilities: Current trends and issues. Curr Dev Disord Rep 2016; 3: 104–15 CrossRef
3.
McLaren J, Bryson SE: Review of recent epidemiological studies of mental retardation: prevalence, associated disorders, and etiology. Am J Ment Retard 1987; 92: 243–54 MEDLINE
4.
Karam SM, Barros AJ, Matijasevich A, et al.: Intellectual disability in a birth cohort: prevalence, etiology, and determinants at the age of 4 years. Public Health Genomics 2016; 19: 290–7 CrossRef MEDLINE PubMed Central
5.
Shashi V, McConkie-Rosell A, Rosell B, et al.: The utility of the traditional medical genetics diagnostic evaluation in the context of next-generation sequencing for undiagnosed genetic disorders. Genet Med 2014; 16: 176–82 CrossRef MEDLINE
6.
Vasudevan P, Suri M: A clinical approach to developmental delay and intellectual disability. Clin Med (Lond) 2017; 17: 558–61 CrossRef MEDLINE PubMed Central
7.
Rauch A, Hoyer J, Guth S, et al.: Diagnostic yield of various genetic approaches in patients with unexplained developmental delay or mental retardation. Am J Med Genet A 2006; 140: 2063–74 CrossRef MEDLINE
8.
Wright CF, Fitzgerald TW, Jones WD, et al.: Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data. Lancet 2015; 385: 1305–14 CrossRef
9.
Prevalence and architecture of de novo mutations in developmental disorders. Nature 2017; 542: 433–8 CrossRef MEDLINE PubMed Central
10.
Flore LA, Milunsky JM: Updates in the genetic evaluation of the child with global developmental delay or intellectual disability. Semin Pediatr Neurol 2012; 19: 173–80 CrossRef MEDLINE
11.
van Dijk EL, Auger H, Jaszczyszyn Y, Thermes C: Ten years of next-generation sequencing technology. Trends Genet 2014; 30: 418–26 CrossRef MEDLINE
12.
Biesecker LG, Green RC: Diagnostic clinical genome and exome sequencing. N Engl J Med 2014; 371: 1170 CrossRef
13.
Green RC, Berg JS, Grody WW, et al.: ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med 2013; 15: 565–74 CrossRef MEDLINE PubMed Central
14.
Claustres M, Kozich V, Dequeker E, et al.: Recommendations for reporting results of diagnostic genetic testing (biochemical, cytogenetic and molecular genetic). Eur J Hum Genet 2014; 22: 160–70 CrossRef MEDLINE PubMed Central
15.
Matthijs G, Souche E, Alders M, et al.: Guidelines for diagnostic next-generation sequencing. Eur J Hum Genet 2016; 24: 2–5 CrossRef CrossRef PubMed Central
16.
Bauer P, Wildhardt G, Gläser D, et al.: S1 Leitlinie: Molekulargenetische Diagnostik mit Hochdurchsatzverfahren, beispielsweise mit Next-Generation Sequencing 2017. www.gfhev.de/de/leitlinien/LL_und_Stellungnahmen/2017_09_15_GfH-S1-LL_NGS-Diagnostik_final.pdf (last accessed on 8 February 2019).
17.
Tarailo-Graovac M, Shyr C, Ross CJ, et al.: Exome sequencing and the management of neurometabolic disorders. N Engl J Med 2016; 374: 2246–55 CrossRef MEDLINE PubMed Central
18.
Thevenon J, Duffourd Y, Masurel-Paulet A, et al.: Diagnostic odyssey in severe neurodevelopmental disorders: toward clinical whole-exome sequencing as a first-line diagnostic test. Clin Genet 2016; 89: 700–7 CrossRef MEDLINE
19.
Stark Z, Tan TY, Chong B, et al.: A prospective evaluation of whole-exome sequencing as a first-tier molecular test in infants with suspected monogenic disorders. Genet Med 2016; 18: 1090–6 CrossRef MEDLINE
20.
Kuperberg M, Lev D, Blumkin L, et al.: Utility of whole exome sequencing for genetic diagnosis of previously undiagnosed pediatric neurology patients. J Child Neurol 2016; 31: 1534–9 CrossRef MEDLINE
21.
Lee H, Deignan JL, Dorrani N, et al.: Clinical exome sequencing for genetic identification of rare Mendelian disorders. JAMA 2014; 312: 1880–7 CrossRef CrossRef MEDLINE PubMed Central
22.
Yang Y, Muzny DM, Xia F, et al.: Molecular findings among patients referred for clinical whole-exome sequencing. JAMA 2014; 312: 1870–9 CrossRef MEDLINE PubMed Central
23.
Srivastava S, Cohen JS, Vernon H, et al.: Clinical whole exome sequencing in child neurology practice. Ann Neurol 2014; 76: 473–83 CrossRef MEDLINE
24.
Farwell KD, Shahmirzadi L, El-Khechen D, et al.: Enhanced utility of family-centered diagnostic exome sequencing with inheritance model-based analysis: results from 500 unselected families with undiagnosed genetic conditions. Genet Med 2015; 17: 578–86 CrossRef MEDLINE
25.
Sawyer SL, Hartley T, Dyment DA, et al.: Utility of whole-exome sequencing for those near the end of the diagnostic odyssey: time to address gaps in care. Clin Genet 2016; 89: 275–84 CrossRef MEDLINE PubMed Central
26.
Eldomery MK, Coban-Akdemir Z, Harel T, et al.: Lessons learned from additional research analyses of unsolved clinical exome cases. Genome Med 2017; 9: 26 CrossRef MEDLINE PubMed Central
27.
Gambin T, Yuan B, Bi W, et al.: Identification of novel candidate disease genes from de novo exonic copy number variants. Genome Med 2017; 9: 83 CrossRef MEDLINE PubMed Central
28.
Hartley T, Wagner JD, Warman-Chardon J, et al.: Whole-exome sequencing is a valuable diagnostic tool for inherited peripheral neuropathies: outcomes from a cohort of 50 families. Clin Genet 2018; 93: 301–9 CrossRef MEDLINE
29.
Kohler S, Doelken SC, Mungall CJ, et al.: The Human Phenotype Ontology Project: linking molecular biology and disease through phenotype data. Nucleic Acids Res 2014; 42: D966–74 CrossRef MEDLINE PubMed Central
30.
Kohler S, Vasilevsky NA, Engelstad M, et al.: The Human Phenotype Ontology in 2017. Nucleic Acids Res 2017; 45: D865−76 CrossRef MEDLINE PubMed Central
31.
Zhang X, Snijders A, Segraves R, et al.: High-resolution mapping of genotype-phenotype relationships in cri du chat syndrome using array comparative genomic hybridization. Am J Hum Genet 2005; 76: 312–26 CrossRef MEDLINE PubMed Central
32.
Kromeyer-Hauschild K, Wabitsch M, Kunze D, et al.: Perzentile für den Body-mass-Index für das Kindes- und Jugendalter unter Heranziehung verschiedener deutscher Stichproben. Monatsschrift Kinderheilkunde 2001; 149: 807–18 CrossRef
33.
Hempel M, Cremer K, Ockeloen CW, et al.: De novo mutations in CHAMP1 cause intellectual disability with severe speech impairment. Am J Hum Genet 2015; 97: 493–500 CrossRef MEDLINE PubMed Central
34.
Kim JH, Shinde DN, Reijnders MRF, et al.: De novo mutations in SON sisrupt RNA splicing of genes essential for brain development and metabolism, causing an intellectual-disability syndrome. Am J Hum Genet 2016; 99: 711–9 CrossRef MEDLINE PubMed Central
e1.
Lek M, Karczewski KJ, Minikel EV, et al.: Analysis of protein-coding genetic variation in 60,706 humans. Nature 2016; 536: 285–91 CrossRef MEDLINE PubMed Central
e2.
Amberger JS, Bocchini CA, Schiettecatte F, Scott AF, Hamosh A: OMIM.org: Online Mendelian Inheritance in Man (OMIM(R)), an online catalog of human genes and genetic disorders. Nucleic Acids Res 2015; 43: D789–98 CrossRef MEDLINE PubMed Central
e3.
Sobreira N, Schiettecatte F, Valle D, Hamosh A: GeneMatcher: a matching tool for connecting investigators with an interest in the same gene. Hum Mutat 2015; 36: 928–30 CrossRef MEDLINE PubMed Central
e4.
Voigt M, Fusch C, Olbertz D: Analyse des Neugeborenenkollektivs der Bundesrepublik Deutschland 12. Mitteilung: Vorstellung engmaschiger Perzentilwerte (-kurven) für die Körpermaße Neugeborener. Geburtsh Frauenheilk 2006; 66: 956–70 CrossRef
e5.
Zhang X, Snijders A, Segraves R, et al.: High-resolution mapping of genotype-phenotype relationships in cri du chat syndrome using array comparative genomic hybridization. Am J Hum Genet 2005; 76: 312–26 CrossRef MEDLINE PubMed Central
*Joint last authors
Institute of Human Genetics, University Medical Center Hamburg-Eppendorf:
Elisa A. Mahler, Dr. Katja Kloth, Dr. Sabine Lüttgen, Dr. Fanny Kortüm,
Prof. Christian Kubisch, Dr. Davor Lessel, Dr. Maja Hempel
Department of Pediatrics, University Medical Center Hamburg-Eppendorf:
Dr. Jessika Johannsen, Dr. Konstantinos Tsiakas, Prof. Chris Mühlhausen,
Prof. Ania C. Muntau, Prof. René Santer, PD Dr. Jonas Denecke
Institute of Human Genetics, Klinikum Rechts der Isar, TUM, Munich: Bader Alhaddad, Dr. Tobias B. Haack, PD Dr. Tim M. Strom, Prof. Thomas Meitinger
Institute of Medical Genetics and Applied Genomics, University Hospital Tübingen:
Dr. Tobias B. Haack
Institute of Human Genetics, Helmholtz Center Munich: PD Dr. Tim M. Strom,
Prof. Thomas Meitinger
Undiagnosed Disease Program at the University Medical Center Hamburg-Eppendorf (UDP-UKE): Prof. Christian Kubisch, Dr. Maja Hempel
Study protocol including evaluation algorithm for genetic variants
Study protocol including evaluation algorithm for genetic variants
Figure 1
Study protocol including evaluation algorithm for genetic variants
Age at onset of illness (square) and age at inclusion in study (circle) for each of the 50 patients
Age at onset of illness (square) and age at inclusion in study (circle) for each of the 50 patients
Figure 2
Age at onset of illness (square) and age at inclusion in study (circle) for each of the 50 patients
Clinical characterization of the study group according to the HPO system (HPO, Human Phenotype Ontology)
Clinical characterization of the study group according to the HPO system (HPO, Human Phenotype Ontology)
Figure 3
Clinical characterization of the study group according to the HPO system (HPO, Human Phenotype Ontology)
Key messages
Comparison of sequencing techniques
Comparison of sequencing techniques
Table 1
Comparison of sequencing techniques
Findings of whole-exome sequencing (WES)
Findings of whole-exome sequencing (WES)
Table 2
Findings of whole-exome sequencing (WES)
Classification of mental retardation (MR) according to Zhang et al. (e5)
Classification of mental retardation (MR) according to Zhang et al. (e5)
eTable 1
Classification of mental retardation (MR) according to Zhang et al. (e5)
Findings of instrument-based diagnostic methods
Findings of instrument-based diagnostic methods
eTable 2
Findings of instrument-based diagnostic methods
Overview of recommendations for management of treatment in the 21 patients with a genetic diagnosis
Overview of recommendations for management of treatment in the 21 patients with a genetic diagnosis
eTable 5
Overview of recommendations for management of treatment in the 21 patients with a genetic diagnosis
1.Maulik PK, Mascarenhas MN, Mathers CD, Dua T, Saxena S: Prevalence of intellectual disability: a meta-analysis of population-based studies. Res Dev Disabil 2011; 32: 419–36 CrossRef MEDLINE
2.McKenzie K, Milton M, Smith G, Ouellette-Kuntz H: Systematic review of the prevalence and incidence of intellectual disabilities: Current trends and issues. Curr Dev Disord Rep 2016; 3: 104–15 CrossRef
3.McLaren J, Bryson SE: Review of recent epidemiological studies of mental retardation: prevalence, associated disorders, and etiology. Am J Ment Retard 1987; 92: 243–54 MEDLINE
4.Karam SM, Barros AJ, Matijasevich A, et al.: Intellectual disability in a birth cohort: prevalence, etiology, and determinants at the age of 4 years. Public Health Genomics 2016; 19: 290–7 CrossRef MEDLINE PubMed Central
5.Shashi V, McConkie-Rosell A, Rosell B, et al.: The utility of the traditional medical genetics diagnostic evaluation in the context of next-generation sequencing for undiagnosed genetic disorders. Genet Med 2014; 16: 176–82 CrossRef MEDLINE
6.Vasudevan P, Suri M: A clinical approach to developmental delay and intellectual disability. Clin Med (Lond) 2017; 17: 558–61 CrossRef MEDLINE PubMed Central
7.Rauch A, Hoyer J, Guth S, et al.: Diagnostic yield of various genetic approaches in patients with unexplained developmental delay or mental retardation. Am J Med Genet A 2006; 140: 2063–74 CrossRef MEDLINE
8.Wright CF, Fitzgerald TW, Jones WD, et al.: Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data. Lancet 2015; 385: 1305–14 CrossRef
9.Prevalence and architecture of de novo mutations in developmental disorders. Nature 2017; 542: 433–8 CrossRef MEDLINE PubMed Central
10.Flore LA, Milunsky JM: Updates in the genetic evaluation of the child with global developmental delay or intellectual disability. Semin Pediatr Neurol 2012; 19: 173–80 CrossRef MEDLINE
11.van Dijk EL, Auger H, Jaszczyszyn Y, Thermes C: Ten years of next-generation sequencing technology. Trends Genet 2014; 30: 418–26 CrossRef MEDLINE
12.Biesecker LG, Green RC: Diagnostic clinical genome and exome sequencing. N Engl J Med 2014; 371: 1170 CrossRef
13.Green RC, Berg JS, Grody WW, et al.: ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med 2013; 15: 565–74 CrossRef MEDLINE PubMed Central
14.Claustres M, Kozich V, Dequeker E, et al.: Recommendations for reporting results of diagnostic genetic testing (biochemical, cytogenetic and molecular genetic). Eur J Hum Genet 2014; 22: 160–70 CrossRef MEDLINE PubMed Central
15.Matthijs G, Souche E, Alders M, et al.: Guidelines for diagnostic next-generation sequencing. Eur J Hum Genet 2016; 24: 2–5 CrossRef CrossRef PubMed Central
16.Bauer P, Wildhardt G, Gläser D, et al.: S1 Leitlinie: Molekulargenetische Diagnostik mit Hochdurchsatzverfahren, beispielsweise mit Next-Generation Sequencing 2017. www.gfhev.de/de/leitlinien/LL_und_Stellungnahmen/2017_09_15_GfH-S1-LL_NGS-Diagnostik_final.pdf (last accessed on 8 February 2019).
17.Tarailo-Graovac M, Shyr C, Ross CJ, et al.: Exome sequencing and the management of neurometabolic disorders. N Engl J Med 2016; 374: 2246–55 CrossRef MEDLINE PubMed Central
18.Thevenon J, Duffourd Y, Masurel-Paulet A, et al.: Diagnostic odyssey in severe neurodevelopmental disorders: toward clinical whole-exome sequencing as a first-line diagnostic test. Clin Genet 2016; 89: 700–7 CrossRef MEDLINE
19.Stark Z, Tan TY, Chong B, et al.: A prospective evaluation of whole-exome sequencing as a first-tier molecular test in infants with suspected monogenic disorders. Genet Med 2016; 18: 1090–6 CrossRef MEDLINE
20.Kuperberg M, Lev D, Blumkin L, et al.: Utility of whole exome sequencing for genetic diagnosis of previously undiagnosed pediatric neurology patients. J Child Neurol 2016; 31: 1534–9 CrossRef MEDLINE
21. Lee H, Deignan JL, Dorrani N, et al.: Clinical exome sequencing for genetic identification of rare Mendelian disorders. JAMA 2014; 312: 1880–7 CrossRef CrossRef MEDLINE PubMed Central
22.Yang Y, Muzny DM, Xia F, et al.: Molecular findings among patients referred for clinical whole-exome sequencing. JAMA 2014; 312: 1870–9 CrossRef MEDLINE PubMed Central
23.Srivastava S, Cohen JS, Vernon H, et al.: Clinical whole exome sequencing in child neurology practice. Ann Neurol 2014; 76: 473–83 CrossRef MEDLINE
24.Farwell KD, Shahmirzadi L, El-Khechen D, et al.: Enhanced utility of family-centered diagnostic exome sequencing with inheritance model-based analysis: results from 500 unselected families with undiagnosed genetic conditions. Genet Med 2015; 17: 578–86 CrossRef MEDLINE
25.Sawyer SL, Hartley T, Dyment DA, et al.: Utility of whole-exome sequencing for those near the end of the diagnostic odyssey: time to address gaps in care. Clin Genet 2016; 89: 275–84 CrossRef MEDLINE PubMed Central
26.Eldomery MK, Coban-Akdemir Z, Harel T, et al.: Lessons learned from additional research analyses of unsolved clinical exome cases. Genome Med 2017; 9: 26 CrossRef MEDLINE PubMed Central
27.Gambin T, Yuan B, Bi W, et al.: Identification of novel candidate disease genes from de novo exonic copy number variants. Genome Med 2017; 9: 83 CrossRef MEDLINE PubMed Central
28.Hartley T, Wagner JD, Warman-Chardon J, et al.: Whole-exome sequencing is a valuable diagnostic tool for inherited peripheral neuropathies: outcomes from a cohort of 50 families. Clin Genet 2018; 93: 301–9 CrossRef MEDLINE
29.Kohler S, Doelken SC, Mungall CJ, et al.: The Human Phenotype Ontology Project: linking molecular biology and disease through phenotype data. Nucleic Acids Res 2014; 42: D966–74 CrossRef MEDLINE PubMed Central
30.Kohler S, Vasilevsky NA, Engelstad M, et al.: The Human Phenotype Ontology in 2017. Nucleic Acids Res 2017; 45: D865−76 CrossRef MEDLINE PubMed Central
31.Zhang X, Snijders A, Segraves R, et al.: High-resolution mapping of genotype-phenotype relationships in cri du chat syndrome using array comparative genomic hybridization. Am J Hum Genet 2005; 76: 312–26 CrossRef MEDLINE PubMed Central
32.Kromeyer-Hauschild K, Wabitsch M, Kunze D, et al.: Perzentile für den Body-mass-Index für das Kindes- und Jugendalter unter Heranziehung verschiedener deutscher Stichproben. Monatsschrift Kinderheilkunde 2001; 149: 807–18 CrossRef
33.Hempel M, Cremer K, Ockeloen CW, et al.: De novo mutations in CHAMP1 cause intellectual disability with severe speech impairment. Am J Hum Genet 2015; 97: 493–500 CrossRef MEDLINE PubMed Central
34.Kim JH, Shinde DN, Reijnders MRF, et al.: De novo mutations in SON sisrupt RNA splicing of genes essential for brain development and metabolism, causing an intellectual-disability syndrome. Am J Hum Genet 2016; 99: 711–9 CrossRef MEDLINE PubMed Central
e1.Lek M, Karczewski KJ, Minikel EV, et al.: Analysis of protein-coding genetic variation in 60,706 humans. Nature 2016; 536: 285–91 CrossRef MEDLINE PubMed Central
e2. Amberger JS, Bocchini CA, Schiettecatte F, Scott AF, Hamosh A: OMIM.org: Online Mendelian Inheritance in Man (OMIM(R)), an online catalog of human genes and genetic disorders. Nucleic Acids Res 2015; 43: D789–98 CrossRef MEDLINE PubMed Central
e3. Sobreira N, Schiettecatte F, Valle D, Hamosh A: GeneMatcher: a matching tool for connecting investigators with an interest in the same gene. Hum Mutat 2015; 36: 928–30 CrossRef MEDLINE PubMed Central
e4. Voigt M, Fusch C, Olbertz D: Analyse des Neugeborenenkollektivs der Bundesrepublik Deutschland 12. Mitteilung: Vorstellung engmaschiger Perzentilwerte (-kurven) für die Körpermaße Neugeborener. Geburtsh Frauenheilk 2006; 66: 956–70 CrossRef
e5.Zhang X, Snijders A, Segraves R, et al.: High-resolution mapping of genotype-phenotype relationships in cri du chat syndrome using array comparative genomic hybridization. Am J Hum Genet 2005; 76: 312–26 CrossRef MEDLINE PubMed Central