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One test for all: whole exome sequencing significantly improves the diagnostic yield in growth retarded patients referred for molecular testing for Silver–Russell syndrome

Abstract

Background

Silver-Russell syndrome (SRS) is an imprinting disorder which is characterised by severe primordial growth retardation, relative macrocephaly and a typical facial gestalt. The clinical heterogeneity of SRS is reflected by a broad spectrum of molecular changes with hypomethylation in 11p15 and maternal uniparental disomy of chromosome 7 (upd(7)mat) as the most frequent findings. Monogenetic causes are rare, but a clinical overlap with numerous other disorders has been reported. However, a comprehensive overview on the contribution of mutations in differential diagnostic genes to phenotypes reminiscent to SRS is missing due to the lack of appropriate tests. With the implementation of next generation sequencing (NGS) tools this limitation can now be circumvented.

Main body

We analysed 75 patients referred for molecular testing for SRS by a NGS-based multigene panel, whole exome sequencing (WES), and trio-based WES. In 21/75 patients a disease-causing variant could be identified among them variants in known SRS genes (IGF2, PLAG1, HMGA2). Several patients carried variants in genes which have not yet been considered as differential diagnoses of SRS.

Conclusions

WES approaches significantly increase the diagnostic yield in patients referred for SRS testing. Several of the identified monogenetic disorders have a major impact on clinical management and genetic counseling.

Background

Growth retardation is a common condition and often manifests during pregnancy. Though several non-genetic factors have been identified, a significant number of patients with growth retardation carry genetic alterations. Severe intrauterine and postnatal growth failure is a typical feature of Silver-Russell syndrome (SRS, OMIM#180860), a congenital disorder which is additionally characterised by relative macrocephaly (head circumference at birth ≥ 1.5 SDS above birth weight and/or length SDS), asymmetry, a typical triangular face with a prominent forehead, and feeding difficulties. However, due to the low specificity and heterogeneity of features the clinical diagnosis of SRS is difficult, and therefore the Netchine–Harbison clinical scoring system (NH-CSS) has been suggested to standardise the subjective clinical diagnosis [1, 2] (see Additional file 1: Table 1). Additionally, the clinical diagnosis is complicated by the lack of specificity of several symptoms and the phenotypic overlap with other (growth retardation) disorders.

Table 1 Overview on the molecular and major clinical findings in the 15 newly identified patients carrying pathogenic variants. For further details see supplementary patients descriptions (ACMG American College of Medical Genetics and Genomics [9]; VUS Variant of Unknown Significance; SDS standard deviation score; ND not determined; NA not available; gw gestational week; DD developmental delay; ad autosomal dominant, ar autosomal recessive; hom homozygous, het heterozygous, hem hemizygous, com het compound heterozygous, imp imprinted; pat paternal, mat maternal; *published by Hübner et al. [17], ** published by Meyer et al. [25, 26]; *** according to the ACMG guidelines, these variants should be classified as VUS. However, in this study they were classified as (likely) pathogenic, see Additional file 3: Table 3)

The clinical heterogeneity of SRS is reflected by a broad spectrum of molecular disturbances. With nearly 40%, the major finding in patients with the typical SRS phenotype is loss of methylation (LOM) of the imprinting centre region 1 (IC1, H19/IGF2:IG-DMR) in 11p15.5 (for review: [2]). Up to 10% of SRS patients exhibit a maternal uniparental disomy of chromosome 7 (upd(7)mat), and a relevant number of patients carry alterations of chromosome 14q32 which are typically associated with Temple syndrome (TS14, OMIM#616222). In fact, TS14 patients show a clinical overlap with SRS, but both carriers of upd(7)mat and 14q32 alterations exhibit a less typical SRS phenotype compared to patients with an IC1-LOM [1, 3]. Nevertheless, even in the IC1-LOM group the clinical picture is variable. Additional molecular alterations in SRS comprise less common genetic variants, i.e. UPDs of chromosome 20, diverse submicroscopic deletions and duplications (copy number variants, CNV) [4], and pathogenic variants in single genes. These molecular changes are either associated with typical SRS phenotypes (e.g. microdeletions in 12q14, pathogenic variants in IGF2, CDKN1C, PLAG1, HMGA2) [4,5,6], or with differential diagnoses of SRS (see [2]).

Both clinical and molecular heterogeneity make the decision on the diagnostic procedure in SRS challenging. To address this issue, a stepwise testing procedure has been consented, starting with IC1 LOM analysis as the first step, followed by testing for upd(7)mat, 14q32 and CNVs [2]. However, the subsequent testing strategies have not yet been defined, and the knowledge on further SRS (spectrum) causing genes or associated genomic variants are mainly based on single reports as systematic screening studies aiming on the contribution of monogenic variants to the molecular SRS spectrum are still missing. With the implementation of next generation sequencing (NGS)-based assays in genetic testing, comprehensive approaches to address a broad spectrum of monogenetic diseases have become available. Our group has recently demonstrated the suitability of targeted multigene NGS panels to increase the diagnostic yield in patients with SRS features [7], and first data from whole exome sequencing were promising as well [8].

We now report on the results of a systematic WES approach in a cohort of growth-retarded patients referred for SRS diagnostics, and compare the results with targeted multigene NGS panel data in the same cohort.

Study cohort

The total cohort consisted of 75 patients with SRS but negatively tested for the typical molecular SRS findings (IC1 LOM, upd(7)mat, 14q32 alterations). WES data were available from 60 patients, the remaining 15 datasets were taken from a targeted NGS approach published recently [7]. In addition to 14 patients not previously analysed by NGS approaches, the cohort included patients already analysed with a targeted NGS approach (n = 47) [7] and from a recent pilot WES study (n = 45) [8], which also partially overlaps (n = 31).

In 22 of these patients, the parents were also analysed by WES (trio-based WES).

To determine the detection rate by the three strategies—targeted NGS, index-based WES and trio-based WES—datasets from all 75 patients were included.

Clinical scoring was leaned on the NH-CSS [1, 2]. The study was approved by the ethical committee of the Medical Faculty of the RWTH Aachen (EK303-18).

Materials and methods

The first step molecular diagnostic testing in all patients comprised analyses of IC1 LOM and upd(7)mat analysis by methylation-sensitive multiplex ligation-dependent probe amplification assays, which also covers 14q32 alterations (MS-MLPA)(ME030, ME032; MRC Holland, Amsterdam/NL). This initial screening was conducted by the authors or by external laboratories. After exclusion of these (epi)mutations, all samples were screened for upd(20)mat, upd(16)mat and submicroscopic copy number variations (> 50 kb) by microsatellite typing, MS-MLPA (ME034), MS single nucleotide primer extension and SNP array analysis (deletions/duplications > 50 kb, CytoScan® HD Array (Affymetrix, Santa Clara/CA, USA)). Nearly all patients were negatively tested with one exception with an OBSL1 microdeletion (patient 7).

For whole exome sequencing of the index patients and their parents DNA samples isolated from peripheral blood were enriched using the Nextera Rapid Capture Exome (v.1.2) (Illumina, San Diego, CA, USA). The enriched libraries were sequenced on a NextSeq500 Sequencer with 2 × 75 cycles on a high-output flow cell. Fastq file generation and adapter trimming was performed using bcl2fastq2 (Illumina, San Diego, CA, USA). The automated SeqMule pipeline (v1.2.6) was used for fastq quality assessment (FastQC, v.0.11.2), alignment (BWA-MEM, v.0.7.8-r455), duplicate removal (SAMtools, rmdup, v.0.1.19–44,428 cd), Indel Realignment (GATKLite realign; v.2.3–9)) and variant calling. Three different variant callers were used (GATKLite, (UnifiedGenotyper version: 2.3–9), SAMtools (mpileup; v.0.1.19–44428 cd), FreeBayes (v.0.9.14–14-gb00b735)) for variant detection, and variants shared by at least two out of three variant callers were considered for further analysis. Annotation and bioinformatic prioritization of variants was performed using KGGSeq (v1.0, 20/Jun./2018). Variants with a minor allele frequency (MAF) higher than 0.75% in public databases (i.e. gnomAD, EXAC, 1000 GP, ESP) and synonymous variants were excluded. Sequencing variants were classified according to the ACMG criteria [9]. Variants identified as pathogenic or likely pathogenic were confirmed by Sanger sequencing on an ABI3500 platform (Applied Biosystems, Foster City, CA, USA) and segregation analysis in the family was performed if possible.

WES data were analyzed for variants in the genes included in the panel approach (for the list of genes see Additional file 2: Table 2 [7]). The achieved WES data from our cohort were filtered for pathogenic variants in all genes listed in OMIM. In 22 patients, parental DNA samples could be used for trio WES analysis. The comparison of detection rates of the three strategies was then restricted to the subcohort from [7] as these patients were analyzed by all three approaches.

Results

In a cohort of 75 patients referred for SRS testing, NGS data were analysed to identify the disease-causing genetic alterations. WES data were available for 59 patients: For 14 patients these datasets were newly generated, for the remaining 45 cases data from a recent study were compiled [8]. In 16 patients, only panel-based NGS data were considered. In 22 out of the 59 patients analysed by WES, parental samples were available for trio-based analysis.

In the total cohort, pathogenic variants explaining the growth retardation phenotypes could be detected in 21 cases (28.0%), six of them had been published recently [7, 8]. The molecular and clinical data of the newly identified 15 patients are listed in Table 1 and a short description is given in the Additional file 3: Table 3.

For comparison of the diagnostic yield of the different approaches, detection rates of the WES (index only) and WES trio strategies were restricted to those 47 patients originally analysed with a targeted multigene panel by Meyer et al. [7] (Fig. 1). In 31 negatively tested samples from this subcohort, WES was performed, and allowed the identification of four genetic variants (4 out of 31 patients: 12.9%), affecting the genes ORC1, FDG1, KMTC2, and PTPN11. Trio analysis in 16 families out of this group revealed four additional pathogenic variants (4 out of 16 families: 25.0%) in the FANCA, MBTPS1, CNOT3, and NF1 genes. In total, a cumulative detection rate of more than 40% could be achieved by this step-wise procedure.

Fig. 1
figure1

Detection rates of different NGS approaches in the cohort of patients referred for SRS testing, and discrimination of the diagnostic yields between patients for whom the clinical score was applicable, and NH-CSS positive cases (NH-CSS ≥ 4 items) and patients without sufficient clinical data (for number see Additional file 4). Comparison of the detection rates between the multigene panel approach [7] with those obtained by WES approaches revealed a significant increase in patients with a positive NH-CSS score as we well as in patients for whom clinical scoring was not possible

The correlation of the clinical data with the genetic findings confirmed that patients carrying mutations in genes associated with SRS generally showed a higher NH-CSS score (PLAG1 in patient 1, IGF2 in patient 5a and her sister 5b, HMGA2 in patient 6). However, despite a scoring of at least 4 out of 6 criteria, none of them exhibited both key features, relative macrocephaly at birth and protruding forehead. Whereas protruding forehead was present in the majority of patients, relative macrocephaly at birth was observed only in the patient with a homozygous MBTPS1 variant (patient 8). In general, intrauterine and postnatal growth retardation associated with a triangular face were the major reasons for referral to diagnostic testing and led to the clinical diagnosis of SRS, though several patients did not fulfil the NH-CSS criteria.

Though clinical scoring was not applicable in all cases, the correlation between clinical scoring and the testing strategies showed that pathogenic variants in several patients with a positive NH-CSS score could be identified only by (Trio) WES but not by the panel-based approach (Fig. 1).

Discussion

The identification of molecular causes of growth retardation is hampered by the large number of genetic factors contributing to growth. Even in SRS as a recognizable phenotype the spectrum of pathogenic variants is broad, and only in up to 60% of patients with the typical SRS features the disease-specific molecular alterations (IC1-LOM, upd(7)mat, 14q32 alterations) can be detected [10]. Thus, a significant number of patients remain without a molecular confirmation of their diagnosis, and only some of them might be explained by mosaicism of the IC1-LOM in 11p15.5 which escapes detection in case of an extremely discrepant distribution in the body [11]. In single families pathogenic variants in genes localized in 11p15.5 (IGF2, CDKN1C) or members of the HMGA2-PLAG1-IGF2 pathway have been identified [12,13,14].

The clinical diagnosis of SRS is additionally hampered by the lack of specificity of its major symptoms, and the overlap with other congenital disorders. As array based studies show, several patients with SRS features carry pathogenic submicroscopic copy number variations associated with differential diagnoses of SRS (CNVs) [4]. Accordingly, small variants in differential diagnostic genes have also been described in SRS patients [2, 7]. To encompass this broad range of putative disease-causing genes, NGS based strategies are a valuable tool as they have the potential to cover all genes and genomic variants which might contribute to a specific phenotype. First studies have already confirmed the power of targeted and whole exome NGS approaches to increase the diagnostic yield in growth retarded patients [7, 8, 15, 16].

In our cohort of patients referred for SRS testing, we now substantiate the need of NGS-based assays in the molecular diagnostic workup in this heterogeneous cohort, and in agreement with findings from other heterogeneous disorders we show that the application of WES significantly improves the detection rate (21.41% versus 8.5% in the cohort analysed by Meyer et al. [7]) for comparable hands-on time and costs. As our data show, a further increase can be achieved by trio analysis, both in patients fulfilling the clinical SRS criteria according to the NH-CSS score as well as in clinically unselected patients referred for SRS testing (Fig. 1).

Our molecular findings reflect the molecular heterogeneity in patients referred for SRS testing as we could identify pathogenic variants in (a) already known SRS genes, in (b) genes associated with differential diagnoses of SRS, in (c) genes causing phenotypes overlapping with SRS.

SRS genes (Table 1a)

Up to now, pathogenic variants which might cause the characteristic SRS phenotype have been identified in four genes. The imprinted genes CDKN1C and IGF2 are localized in 11p15.5, and HMGA2 and PLAG1 interact with IGF2 [14]. In our cohort, we identified pathogenic variants in three of them. In two sibs affected by SRS (patients 2a/b), an IGF2 variant was inherited from the healthy father which corresponds to the paternal expression of the gene. In contrast to IGF2, the mode of inheritance of variants in HMGA2 and PLAG1 is not influenced by the sex of the parent contributing the affected allele as these genes are not imprinted. To the best of our knowledge, the frameshift variant in patient 1 is the third PLAG1 variant reported in the literature [14], and its de-novo occurrence supports the autosomal-dominant mode of inheritance. The HMGA2 variants from our cohort (patients 3, 4a/b) have been reported recently [17]. Clinically, the patients show growth retardation and SRS features, and the NH-CSS scoring ranges between 4 and 5 parameters. Protruding forehead as one of the two key features of SRS was present in all of them, but relative macrocephaly as the second main sign was absent. For HMGA2, the clinical findings correspond to cases recently overviewed by Leszenski et al. [18].

Genes associated with already identified differential diagnoses of SRS (Table 1b)

As it could be expected from previous reports [2], several differential diagnoses have now been identified in our cohort, including a disturbance of IGF1R (patient 5), Meier-Gorlin syndrome 1 (MGS1; ORC1, patient 6), and 3 M syndrome 2 (OBSL1, patient 7). In all these patients, severe postnatal (and intrauterine) growth retardation was reported, and this feature was the reason for inclusion in the study. However, microcephaly is the clinical feature which allows the discrimination between SRS and the majority of its differential diagnosis, in our cohort IGF1R disturbances and MGS1 [19, 20]. Nevertheless, it should be noted that the patient with the OBSL1 variant exhibited relative macrocephaly at least at the age of 2 years 5 months, and our case confirms that 3-M syndrome is a relevant differential diagnosis of SRS [21].

Genes causing phenotypes overlapping with SRS (Table 1c)

The results from exome wide screening for pathogenic variants in our cohort confirms that there is a broad clinical overlap between SRS and other congenital disorders. Therefore, the restriction to a selection of genes with higher degree of clinical concordance should be discussed, as the application of targeted panel will miss the detection of relevant mutations, in particular in tumour predisposition genes.

The only patient with relative macrocephaly at birth and positive NH-CSS scoring is homozygous for a MBTPS1 variant (patient 8). Interestingly, the same variant has already been reported in another growth retarded patient for whom the diagnosis of SRS was also discussed [22]. Thus, we suggest to add MBTPS1-associated disorders to the list of differential diagnosis of SRS.

In two patients (patients 9 and 10), we identified pathogenic variants in tumour predisposition syndromes. These growth retarded patients were reported to show the typical facial gestalt of SRS, and were born small for gestational age. FANCA-associated Fanconi anemia has not yet been reported as differential diagnosis of SRS, but the clinical overlap is obvious. In patient 9 from this report, Fanconi anemia was diagnosed at the age of 11 years 9 months. In contrast, patient 10 with a pathogenic NF1 variant only showed slight symptoms of neurofibromatosis type 1 but symptoms consistent with SRS. The variant of our patient has already been reported in an NF1 patient in combination with short stature [23].

In five further patients (patients 11–15), pathogenic variants compatible with their clinical features could be identified. None of the associated disorders has already been suggested as differential diagnosis of SRS, and clinical scoring shows that none of these individuals had the typical SRS picture. All were ascertained due to growth retardation and a facial gestalt described as “triangular”.

The results from our study cohort confirm the strengths of NGS-based strategies to decipher the molecular basis of congenital disorders (for review: [24]), and the comparison between them also demonstrates their chances and challenges. Whereas the increase of the detection rate by WES in comparison to the targeted multigene panel approach does not need further explanation, the reason for an additional chance to detect disease-causing variants by trio analysis needs some further comments:

Trio WES includes additional information and allows phasing of the detected variants. Thereby it enables the detection of true compound-heterozygous and de novo variants. Furthermore, it helps to determine if a variant in an imprinted gene affects the expressed or the silenced copy. The estimation of pathogenicity of variants in imprinted genes requires this further information on inheritance and imprinting status. Even a variant with a severe functional impact might be without clinical relevance when the affected copy of the imprinted gene is silenced (i.e. maternal IGF2 variants).

The detection of a de novo occurrence of a variant can decisively influence the assessment of its pathogenicity. As stated in the ACMG guidelines, de novo occurrence represents a strong criteria for pathogenicity [9]. Trio WES allows the time-saving determination of the pathogenicity of variants of uncertain significance, and the confirmation of compound heterozygosity and of parenthood which is a key criteria for classification [9].

In fact, our study has several limitations. It is based on a cohort of patients referred for SRS diagnostic, but with only limited clinical information (Additional file 3: Table 3). The study population therefore includes a considerable number of patients who do not fulfill clinical criteria of SRS [1]. However, this situation reflects the routine diagnostic workup of a clinically heterogeneous group of patients, for which clinical data are rarely provided. As a consequence, this dataset does not reflect the relative contribution of different monogenic causes to the SRS phenotype, but it allows to broaden the spectrum of disorders with a clinical overlap with SRS. Interestingly, even three out of four patients with typical SRS alterations (i.e. PLAG1, IGF2, HMGA2) would not be diagnosed as “clinical SRS” according to diagnostic criteria consented recently [2]. The identification of two patients with tumor predisposition variants (FANCA, NF1) again confirms that the strategy of a broad testing is needed in patients diagnosed with SRS. In these situations, the testing result provides the basis for a more precise therapeutic management, which includes the decision on or against growth hormone treatment and tumor monitoring.

The comparison between the different NGS strategies is also difficult as the targeted multigene panel used in this study does not reflect the current knowledge on genes contributing to the SRS phenotype. In fact, the use of panel based NGS assays avoids the detection of unsolicited findings, but it is only of limited value for heterogeneous disorders like SRS. As we could show, more than half of the pathogenic variants would be missed by application of a targeted gene panel because several of the identified genes were not included in the multigene panel assay. Furthermore, a multigene panel reflects the knowledge at the time of the panel design. As the variant in the SRS gene PLAG1 shows, it was missed in our targeted NGS approach as at the time of the panel design [7] PLAG1 had not yet been identified as SRS gene. A targeted multigene panel can certainly be upgraded, and further genes can be added to a new panel version or spiked in into an existing enrichment kit, but samples analysed by a previous version cannot be reanalysed.

We therefore suggest WES as a general wet-lab enrichment strategy. To avoid incidental findings and a huge number of variants of unknown significance, the WES data might be filtered by a step-wise virtual multigene panel. If new disease-causing genes are identified, these data can then be reanalysed without generation of new NGS data. In addition, the WES data can be analysed repeatedly to identify pathogenic variants in differential diagnosis genes which are not in the focus and would be missed by multigene panels. In case WES in a single case is negative, a trio analysis might be considered. Additionally, the upcoming implementation of whole genome sequencing (WGS) in molecular genetic testing trials will show whether the detection rates can be further increased.

Conclusions

Our data confirm that WES is a suitable tool to achieve a significant increase of the diagnostic yield in patients referred for SRS testing. The data further contribute to the heterogeneous molecular spectrum of SRS and clinically overlapping disorders, the identified cases demonstrate the need for precise molecular confirmation as the basis for precision medicine. The foreseeable diagnostic implementation of WGS, long read sequencing (third generation sequencing) in combination with transcriptomics will allow the identification of all molecular alterations in one analysis.

Databases

ClinVar: https://www.ncbi.nlm.nih.gov/clinvar/.gnomAD: https://gnomad.broadinstitute.org/. dbSNP: https://www.ncbi.nlm.nih.gov/snp/.

Availability of data and materials

Data are available on request.

Abbreviations

ACMG:

American College of Medical Genetics and Genomics

CNV:

Copy number variation

IC1:

Imprinting Center 1 in 11p15.5

LOM:

Loss of Methylation

NGS:

Next Generation Sequencing

NH-CSS:

Netchine-Harbison Clinical Scoring System

SRS:

Silver-Russell syndrome

UPD:

Uniparental Disomy

WES:

Whole Exome Sequencing

WGS:

Whole Genome Sequencing

References

  1. 1.

    Azzi S, Salem J, Thibaud N, Chantot-Bastaraud S, Lieber E, Netchine I, Harbison MD. A prospective study validating a clinical scoring system and demonstrating phenotypical-genotypical correlations in Silver-Russell syndrome. J Med Genet. 2015;52(7):446–53.

    CAS  Article  Google Scholar 

  2. 2.

    Wakeling EL, Brioude F, Lokulo-Sodipe O, O’Connell SM, Salem J, Bliek J, Canton AP, Chrzanowska KH, Davies JH, Dias RP, Dubern B, Elbracht M, Giabicani E, Grimberg A, Gronskov K, Hokken-Koelega AC, Jorge AA, Kagami M, Linglart A, Maghnie M, Mohnike K, Monk D, Moore GE, Murray PG, Ogata T, Petit IO, Russo S, Said E, Toumba M, Tumer Z, Binder G, Eggermann T, Harbison MD, Temple IK, Mackay DJ, Netchine I. Diagnosis and management of Silver–Russell syndrome: first international consensus statement. Nat Rev Endocrinol. 2017;13(2):105–24.

    CAS  Article  Google Scholar 

  3. 3.

    Geoffron S, Abi Habib W, Chantot-Bastaraud S, Dubern B, Steunou V, Azzi S, Afenjar A, Busa T, Pinheiro Canton A, Chalouhi C, Dufourg MN, Esteva B, Fradin M, Genevieve D, Heide S, Isidor B, Linglart A, Morice Picard F, Naud-Saudreau C, Oliver Petit I, Philip N, Pienkowski C, Rio M, Rossignol S, Tauber M, Thevenon J, Vu-Hong TA, Harbison MD, Salem J, Brioude F, Netchine I, Giabicani E. Chromosome 14q32.2 imprinted region disruption as an alternative molecular diagnosis of Silver–Russell syndrome. J Clin Endocrinol Metab. 2018;103(7):2436–46.

  4. 4.

    Tumer Z, Lopez-Hernandez JA, Netchine I, Elbracht M, Gronskov K, Gede LB, Sachwitz J, den Dunnen JT, Eggermann T. Structural and sequence variants in patients with Silver–Russell syndrome or similar features-Curation of a disease database. Hum Mutat. 2018;39(3):345–64.

    Article  Google Scholar 

  5. 5.

    Brioude F, Oliver-Petit I, Blaise A, Praz F, Rossignol S, Le Jule M, Thibaud N, Faussat AM, Tauber M, Le Bouc Y, Netchine I. CDKN1C mutation affecting the PCNA-binding domain as a cause of familial Russell–Silver syndrome. J Med Genet. 2013;50(12):823–30.

    CAS  Article  Google Scholar 

  6. 6.

    Begemann M, Zirn B, Santen G, Wirthgen E, Soellner L, Buttel HM, Schweizer R, van Workum W, Binder G, Eggermann T. Paternally inherited IGF2 mutation and growth restriction. N Engl J Med. 2015;373(4):349–56.

    CAS  Article  Google Scholar 

  7. 7.

    Meyer R, Soellner L, Begemann M, Dicks S, Fekete G, Rahner N, Zerres K, Elbracht M, Eggermann T. Targeted next generation sequencing approach in patients referred for Silver–Russell syndrome testing increases the mutation detection rate and provides decisive information for clinical management. J Pediatr. 2017;187:206–12.

    CAS  Article  Google Scholar 

  8. 8.

    Neuheuser L, Meyer R, Begemann M, Elbracht M, Eggermann T. Next generation sequencing and imprinting disorders: current applications and future perspectives: lessons from Silver–Russell syndrome. Mol Cell Probes. 2019;44:1–7.

    CAS  Article  Google Scholar 

  9. 9.

    Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody WW, Hegde M, Lyon E, Spector E, Voelkerding K, Rehm HL, Committee ALQA. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17(5):405–24.

    Article  Google Scholar 

  10. 10.

    Eggermann K, Bliek J, Brioude F, Algar E, Buiting K, Russo S, Tumer Z, Monk D, Moore G, Antoniadi T, Macdonald F, Netchine I, Lombardi P, Soellner L, Begemann M, Prawitt D, Maher ER, Mannens M, Riccio A, Weksberg R, Lapunzina P, Gronskov K, Mackay DJ, Eggermann T. EMQN best practice guidelines for the molecular genetic testing and reporting of chromosome 11p15 imprinting disorders: Silver–Russell and Beckwith–Wiedemann syndrome. Eur J Hum Genet. 2016;24(10):1377–87.

    CAS  Article  Google Scholar 

  11. 11.

    Azzi S, Rossignol S, Steunou V, Sas T, Thibaud N, Danton F, Le Jule M, Heinrichs C, Cabrol S, Gicquel C, Le Bouc Y, Netchine I. Multilocus methylation analysis in a large cohort of 11p15-related foetal growth disorders (Russell Silver and Beckwith Wiedemann syndromes) reveals simultaneous loss of methylation at paternal and maternal imprinted loci. Hum Mol Genet. 2009;18(24):4724–33.

    CAS  Article  Google Scholar 

  12. 12.

    Masunaga Y, Inoue T, Yamoto K, Fujisawa Y, Sato Y, Kawashima-Sonoyama Y, Morisada N, Iijima K, Ohata Y, Namba N, Suzumura H, Kuribayashi R, Yamaguchi Y, Yoshihashi H, Fukami M, Saitsu H, Kagami M, Ogata T. IGF2 Mutations. J Clin Endocrinol Metab. 2020;105(1).

  13. 13.

    Brioude F, Kalish JM, Mussa A, Foster AC, Bliek J, Ferrero GB, Boonen SE, Cole T, Baker R, Bertoletti M, Cocchi G, Coze C, De Pellegrin M, Hussain K, Ibrahim A, Kilby MD, Krajewska-Walasek M, Kratz CP, Ladusans EJ, Lapunzina P, Le Bouc Y, Maas SM, Macdonald F, Ounap K, Peruzzi L, Rossignol S, Russo S, Shipster C, Skorka A, Tatton-Brown K, Tenorio J, Tortora C, Gronskov K, Netchine I, Hennekam RC, Prawitt D, Tumer Z, Eggermann T, Mackay DJG, Riccio A, Maher ER. Expert consensus document: clinical and molecular diagnosis, screening and management of Beckwith–Wiedemann syndrome: an international consensus statement. Nat Rev Endocrinol. 2018;14(4):229–49.

    Article  Google Scholar 

  14. 14.

    Abi Habib W, Brioude F, Edouard T, Bennett JT, Lienhardt-Roussie A, Tixier F, Salem J, Yuen T, Azzi S, Le Bouc Y, Harbison MD, Netchine I. Genetic disruption of the oncogenic HMGA2-PLAG1-IGF2 pathway causes fetal growth restriction. Genet Med. 2018;20(2):250–8.

    CAS  Article  Google Scholar 

  15. 15.

    Shapiro L, Chatterjee S, Ramadan DG, Davies KM, Savage MO, Metherell LA, Storr HL. Whole-exome sequencing gives additional benefits compared to candidate gene sequencing in the molecular diagnosis of children with growth hormone or IGF-1 insensitivity. Eur J Endocrinol. 2017;177(6):485–501.

    CAS  Article  Google Scholar 

  16. 16.

    Hauer NN, Popp B, Schoeller E, Schuhmann S, Heath KE, Hisado-Oliva A, Klinger P, Kraus C, Trautmann U, Zenker M, Zweier C, Wiesener A, Abou Jamra R, Kunstmann E, Wieczorek D, Uebe S, Ferrazzi F, Buttner C, Ekici AB, Rauch A, Sticht H, Dorr HG, Reis A, Thiel CT. Clinical relevance of systematic phenotyping and exome sequencing in patients with short stature. Genet Med. 2018;20(6):630–8.

    CAS  Article  Google Scholar 

  17. 17.

    Hübner CT, Meyer R, Kenawy A, Ambrozaityte L, Matuleviciene A, Kraft F, Begemann M, Elbracht M, Eggermann T. HMGA2 variants in Silver-Russell syndrome: homozygous and heterozygous occurrence. J Clin Endocrinol Metab. 2020;105(7):2401–7.

    Article  Google Scholar 

  18. 18.

    Leszinski GS, Warncke K, Hoefele J, Wagner M. A case report and review of the literature indicate that HMGA2 should be added as a disease gene for Silver-Russell syndrome. Gene. 2018;663:110–4.

    CAS  Article  Google Scholar 

  19. 19.

    Giabicani E, Willems M, Steunou V, Chantot-Bastaraud S, Thibaud N, Abi Habib W, Azzi S, Lam B, Berard L, Bony-Trifunovic H, Brachet C, Brischoux-Boucher E, Caldagues E, Coutant R, Cuvelier ML, Gelwane G, Guemas I, Houang M, Isidor B, Jeandel C, Lespinasse J, Naud-Saudreau C, Jesuran-Perelroizen M, Perrin L, Piard J, Sechter C, Souchon PF, Storey C, Thomas D, Le Bouc Y, Rossignol S, Netchine I, Brioude F. Increasing knowledge in IGF1R defects: lessons from 35 new patients. J Med Genet. 2020;57(3):160–8.

    CAS  Article  Google Scholar 

  20. 20.

    de Munnik SA, Hoefsloot EH, Roukema J, Schoots J, Knoers NV, Brunner HG, Jackson AP, Bongers EM. Meier-Gorlin syndrome. Orphanet J Rare Dis. 2015;10:114.

    Article  Google Scholar 

  21. 21.

    Akawi NA, Ali BR, Hamamy H, Al-Hadidy A, Al-Gazali L. Is autosomal recessive Silver–Russel syndrome a separate entity or is it part of the 3-M syndrome spectrum? Am J Med Genet A. 2011;155A(6):1236–45.

    Article  Google Scholar 

  22. 22.

    Kondo Y, Fu J, Wang H, Hoover C, McDaniel JM, Steet R, Patra D, Song J, Pollard L, Cathey S, Yago T, Wiley G, Macwana S, Guthridge J, McGee S, Li S, Griffin C, Furukawa K, James JA, Ruan C, McEver RP, Wierenga KJ, Gaffney PM, Xia L. Site-1 protease deficiency causes human skeletal dysplasia due to defective inter-organelle protein trafficking. JCI Insight. 2018;3(14).

  23. 23.

    Wimmer K, Decker M, Mayatepek E, Beiglbock H, Eggermann T, Kehrer-Sawatzki H, Fonatsch C, Rosenbaum T. Silver–Russell syndrome-like features in a patient carrying a novel NF1 mutation. Pediatr Res. 2005;58(6):1265–8.

    Article  Google Scholar 

  24. 24.

    Eggermann T, Elbracht M, Kurth I, Juul A, Johannsen TH, Netchine I, Mastorakos G, Johannsson G, Musholt TJ, Zenker M, Prawitt D, Pereira AM, Hiort O, European Reference Network on Rare Endocrine C. Genetic testing in inherited endocrine disorders: joint position paper of the European reference network on rare endocrine conditions (Endo-ERN). Orphanet J Rare Dis. 2020;15(1):144.

  25. 25.

    Meyer R, Elbracht M, Opladen T, Eggermann T. Patient with an autosomal-recessive MBTPS1-linked phenotype and clinical features of Silver-Russell syndrome. Am J Med Genet Part A. 2020;182(11):2727–30.

    CAS  Article  Google Scholar 

  26. 26.

    Meyer R, Begemann M, Demuth S, Kraft F, Dey D, Schüler H, Busse S, Häusler M, Zerres K, Kurth I, Eggermann T, Elbracht M. Inherited cases of CNOT3-associated intellectual developmental disorder with speech delay, autism, and dysmorphic facies. Clin Genet. 2020;98(4):408–12.

    CAS  Article  Google Scholar 

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Acknowledgements

We thank the patients and their families for participation in our study.

Funding

Open Access funding enabled and organized by Projekt DEAL. The study has been supported by the Deutsche Forschungsgemeinschaft (DFG, EG110/15-1).

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Affiliations

Authors

Contributions

RM, ME and TE have prepared and finalized the manuscript. RM, MB, CTH have conducted the NGS and laboratory experiments and analysed the data. DD and MB have prepared the bioinformatics pipeline and conducted the bioinformatics analyses. AK, ME, US, LA, BB, CS, PK, SD, GF and TO were in contact with the families, they have correlated the clinical data with the molecular results, and provided the clinical data. TE has supervised the study. All authors have contributed their parts to the paper and revised the final versions. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Thomas Eggermann.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the ethical committee of the Medical Faculty of the RWTH Aachen (EK303-18).

Consent for publication

All participants gave their informed content for participation in this study.

Competing interests

The authors declare that they have no competing interests.

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Supplementary information

Additional file 1

. Table 1 NH-CSS parameter (from [2]).

Additional file 2

. Table 2 List of genes used for targeted NGS analysis. It should be noted that the list is based on that from Meyer et al. [7] and does not include the recently identified SRS gene PLAG1 [14].

Additional file 3

. Table 3: Overview on the availability of clinical data for the patients from the three different NGS strategies.

Additional file 4

. File 4: Patients description.

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Meyer, R., Begemann, M., Hübner, C.T. et al. One test for all: whole exome sequencing significantly improves the diagnostic yield in growth retarded patients referred for molecular testing for Silver–Russell syndrome. Orphanet J Rare Dis 16, 42 (2021). https://doi.org/10.1186/s13023-021-01683-x

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Keywords

  • Silver–Russell syndrome
  • Next generation sequencing
  • Diagnostic detection rate
  • Whole exome sequencing
  • Targeted multigene panel NGS