Next generation sequencing (NGS) to improve the diagnosis and management of patients with disorders of sex development (DSD)

Introduction

Disorders of sex development (DSD) encompass a wide range of conditions with diverse clinical features, pathophysiology and clinical management (1, 2, 3). The recently revised stratified DSD diagnostic pathway consists of clinical examination, biochemical investigations and karyotype determination (4, 5). Once a presumptive diagnosis has been made, targeted sequencing of candidate genes may then be performed at a later stage (5). Whilst reaching the correct diagnosis has a significant impact on management decisions, determining the aetiology of genital ambiguity in patients with DSD on the basis of clinical and biochemical assessment remains challenging (6). In DSD where no clear abnormality in the steroidogenesis pathway is present, the yield from genetic testing had historically remained low, and with single-gene sequencing, was both costly and time consuming (4).

Improvements in gene sequencing technology in conjunction with rapidly falling costs have led to the use of targeted next generation sequencing (NGS) assays. These enable multiple known disease-causative genes to be sequenced in parallel alongside initial clinical assessment and biochemical investigations, potentially avoiding the need for additional expensive biochemical and radiological investigations (7). Reaching a timely diagnosis is extremely important as it ends diagnostic uncertainty, avoids further unnecessary investigations, enables appropriate disease-specific counselling (including assessment of future fertility potential and malignancy risk) and implementation of personalised medical plans in accordance with current disease-specific consensus guidelines (8). Additionally, in the long term, accurate early diagnosis will support the development of better-designed outcome studies.

The use of targeted NGS panels for molecular diagnosis of DSD patients has already been reported successfully in several previous publications (9, 10, 11, 12). These publications show diagnostic yield and clinical utility in predominantly 46,XY DSD cohorts using panels of 64–219 genes. We present our data showing sequence analysis of a cohort of 80 DSD patients using a 30-gene panel.

Materials and methods

Results

The DSD NGS panel provided a molecular diagnosis in 25 out of the 80 patients tested (Table 3). A diagnosis was deemed as confirmed where variants of class 4 or class 5 were identified which were consistent with the inheritance pattern for that gene, and where disruption of the gene was in keeping with the patient’s phenotype. On four occasions, a class 3 variant was found in combination with a class 5 mutation (patients 2, 11, 15 and 20). Although technically class 3 variants are of uncertain significance, their presence in combination with a class 5 variant in these patients, when considered with the clinical information provided led us to believe that these findings were causally related to the clinical features. The overall diagnostic yield for this panel is therefore currently 25/80 for all samples and 25/73 for 46,XY DSD. This figure represents the likely minimum detection rate of this panel as some samples were received with an initial request for Sanger sequencing of a specific gene, and typically only included for panel testing if negative on Sanger sequencing.

Class 3 variants (listed in Table 4) were typically missense mutations which had not been previously reported, and therefore, no clinical information was available. These were included in the clinical report with a statement that a diagnosis had not been confirmed due to the uncertainty around the pathogenicity of such variants. Where only class 1 and/or 2 variants were identified, patient reports stated that no evidence of a pathogenic mutation had been identified. A summary of the findings can be seen in Fig. 1. Both previously reported and novel pathogenic mutations and variants were identified in AMH, AMHR2, AR, DHCR7, HSD17B3, HSD3B2, LHCGR, MAMLD1, NR5A1, SRD5A2 and WT1 (Table 5). Diagnosis due to mutations in the AR gene (seven patients) were the most commonly observed (Table 3) followed by diagnosis due to HSD17B3 (five patients) and SRD5A2 (four patients).

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Summary of findings of DSD panel. Results of the panel are separated by karyotype (XX or XY) and by result. ‘Diagnosis confirmed’ indicates patients where a pathogenic variant was detected compatible with the patient’s phenotype. ‘VOUS (variant of uncertain significance) only’ indicates solely class 3 variants were detected and therefore a diagnosis could not be confirmed. ‘No mutation’ indicates only class 1 (clearly not pathogenic) or class 2 variants (unlikely to be pathogenic) were detected.

Citation: Endocrine Connections 8, 2; 10.1530/EC-18-0376

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Discussion

DSDs, estimated to be present in 1.7% of live births (14), are a diagnostic challenge due to variable expressivity and pleiotrophy, clinical overlap of the different DSD and their significant aetiological heterogeneity. Historically a genetic diagnosis was made in as few as 13% of cases (15). We present data from 80 patients who underwent routine diagnostic testing for DSD using a 30-gene NGS panel. This diagnostic DSD panel was utilised irrespective of clinical and biochemical features, unless a specific single Sanger sequence request was made based on phenotypic assessment. The diagnostic yield of this DSD panel was shown to be 25/80 for all DSDs, higher for 46,XY DSD (25/73) and would have been higher in this cohort if all cases with a suspected diagnosis (all subsequently confirmed on Sanger sequencing) had not been filtered out prior to implementation of the panel test. Pathogenic (or likely pathogenic) mutations in the AMH, AMHR2, AR, HSD17B3, HSD3B2, MAMLD1, NR5A1, SRD5A2 and WT1 genes were identified. Our detection rate and findings are similar to those in previous studies and are summarised in Table 6. Dong et al. demonstrated an increased detection rate of 9/13 in 46,XY DSD patients using a panel of 219 genes (10); however, the study included small patient numbers and so may not be representative.

Separating out analysis of 46,XY DSD from those with 46,XX DSD results in an improved 46,XY yield to 25/73 but highlights the 0/7 diagnostic yield of individuals with a 46,XX DSD. Difficulty in confirming a molecular diagnosis in those with an 46,XX DSD has also been seen in other studies (11, 12). Sample numbers for those with 46,XX DSD are very small in this study and therefore are unlikely to be representative of the true diagnostic capability of the panel for these patients. In addition, other causes of 46,XX DSD such as translocation of SRY to the X chromosome, duplications of SOX9 or CAH due to CYP21A2 deficiency are not detectable by this method. Patients would typically have had karyotype and/or microarray prior to testing on the panel and would have been tested separately for CYP21A2 deficiency if CAH was suspected. Increased sample numbers and incorporation of more 46,XX DSD-associated genes as they are identified may allow a more accurate estimate of the panel’s usefulness for those with 46,XX DSD. It will also be important to include new 46,XX DSD genes that are likely to be identified in current international exome/genome sequencing projects such as the 100,000 genome project in England (16).

Novel mutations and variants in several genes were identified where functional studies were not available. Variants were considered likely to be causative if they were observed in trans (on opposite chromosome alleles) with a known pathogenic mutation, in a disease gene showing autosomal recessive inheritance (four patients in our cohort). In some cases, segregation studies confirming the bi-allelic nature of the findings also supported a likely pathogenic role. This information has expanded our knowledge of likely diagnostic DSD variants for future investigation of DSD patients. Novel VOUS in the absence of a confirmed diagnosis were also seen. Whilst their significance currently remains uncertain, wider data sharing through publication of studies such as this is crucial to further our understanding of such variants. The large number of VOUS in this cohort is predominantly due to limited clinical information related to some DSD-related genes, for example, only VOUS were detected in the CBX2 gene. Clinicians will have to manage any patient confusion or anxiety within the current uncertainty until more data are available. When designing future NGS DSD panels, it will remain important to recognise that increasing the number of genes, especially those with limited data, will generate greater numbers of VOUS with increased cost and complexity of analysis. This should be balanced against the potential for gene discovery.

Segregation studies have been helpful in the determination of pathogenicity in several families, as illustrated by patient 23, who had an AR variant initially reported as a VOUS. The patient’s older brother, previously shown to have a 47,XXY karyotype and a ‘milder’ phenotype, was subsequently shown to have the same AR variant. Given his additional X chromosome, without skewed X inactivation a milder phenotype would be expected. This increased our confidence in calling the variant a ‘likely pathogenic’ mutation and highlights the importance of reviewing interpretation of variants when new information becomes available.

NGS technology has also allowed the identification of mosaic mutations in the AR gene, which may have gone undetected by other methods. Identification of an accurate number of reads enhances our knowledge of the level of mosaicism present. It should be noted, however, that the results represent the mutation load in peripheral blood (70% patient 8 and 30% patient 24) and not necessarily other relevant tissues. Of the mutations identified, both had been previously reported in non-mosaic form in the literature (17, 18). Mosaic mutations have however been reported in the AR gene (19, 20) and taken together with the clinical features, allowed us to conclude that these mutations in mosaic form were likely to be contributing to the phenotype in these patients. Importantly for patient management, AR mutations in mosaic form are believed to pose a risk of virilisation in patients due to the presence of wildtype androgen receptor (19). Distinguishing mosaic from non-mosaic forms therefore can have significant consequences for patient management and genetic recurrence risk.

Identifying the correct genetic diagnosis modifies the patient management and impacts on the accuracy of information and choices available to family members. The former is clearly illustrated in case 21 where mutations in two different DSD-related genes were present in the same family – HSD17B3 and AR. The family were requesting gonadectomy pre-adolescence in a 46,XY DSD female, on the basis that her cousins who were 46,XY DSD females, due to a homozygous HSD17B3 mutations, had virilised and been managed with gonadectomy in another centre. Identification of a previously unidentified mutation in AR in this family meant three girls with 46,XY changed their subsequent management. In four cases, the diagnosis in affected siblings has been confirmed (listed in Table 3 patients 7, 17, 21 and 23) including cases enabling early prenatal (patient 20) or neonatal (patient 17) diagnosis, and thus, implementation of appropriate management from birth. This highlights the importance of identifying the molecular diagnosis not only for the proband but also for the wider family.

The panel also identified pathogenic mutations which were thought to be co-incidental and not to be related to the initial clinical presentation in the proband. In patient 18 with CAH due to HSD3B2 deficiency, the patient was also shown to be a carrier for the common splice mutation c.964-1G>C in the DHCR7 gene which is linked to Smith Lemli Opitz syndrome (SLOS). Whilst such incidental findings can be challenging for patient counselling, the information provided may also be of great significance. This will be especially true when previously undetected autosomal recessive mutations are uncovered in highly consanguineous families, which are common within many DSD cohorts.

Where a clinician has a strong suspicion of the involvement of a specific gene, Sanger sequencing may be more cost effective, especially where the number of amplicons is relatively small. For example, pathogenic mutations in the AMH, AMHR2, AR and SRD5A2 gene were identified in this way. When the original clinical diagnosis is incorrect, however, the potential cost savings rapidly disappear if sequential Sanger sequencing is required, and therefore, any benefit is highly dependent on the clinical expertise and the specificity of the additional non-genetic investigations. There may also be atypical presentations not yet recognised for mutations in some genes, and therefore, a wider panel approach has the potential to address this.

Despite the diagnostic rate of 25/73 for 46,XY DSD, the failure to achieve a diagnosis in 55 patients confirms the need for further development. Of note, the panel cannot currently detect copy number changes (CNVs), and so further development should include the detection of CNVs that are below the resolution of the current chromosomal microarray assay. The 30 genes in our panel were selected due to published evidence of their involvement in DSD, but new gene discoveries in studies such as the 100,000 genome project (16) should enhance the diagnostic utility, especially for 46,XX DSD. Eggers et al. demonstrated a 118/278 diagnostic rate for 46,XY DSD patients by including 64 DSD genes (11) and Dong et al. reported a 6/13 rate by including 219 genes (10); thus, diagnostic capability may be improved by increasing the gene number. These benefits may be marginal however as only one likely pathogenic mutation in the Dong series was in the additional 179 genes not included in this 30-gene panel. Comparison of these studies could indicate that a greater impact on the detection rate may be due to patient selection. It will be important, therefore, that further candidate gene inclusion is critically evaluated as the addition of genes without clear clinical utility will likely result in increasing cost and numbers of VOUS without necessarily increasing diagnostic capability. The future of this investigative pathway may well be transformed by implementation of whole exome or whole genome sequencing, but any benefits of diagnostic detection will have to be weighed against increased cost and clinical complexities resulting from VOUS and co-incidental findings. It therefore remains important to optimise such NGS panels for DSD so that a valid comparison can be made in future.

These data demonstrate clear advantages of an NGS panel approach for highly heterogenous conditions such as DSD. Despite the limitations of the panel including incomplete coverage and inability to detect copy number changes, the results presented here demonstrate that an NGS-based panel approach is a useful frontline tool for diagnosing DSDs. In addition to a diagnostic yield of at least 25/80 we have shown examples of cases where the information provided from the panel has identified diagnoses in complex families with the potential for multiple aetiologies, cases where panel findings have significantly impacted management and treatment decisions and examples of novel variants being identified, thus expanding our current knowledge. As more and more patients are tested, the information provided by such panels will continue to grow and improve our understanding of these complex conditions and hopefully improve the diagnostic capability of such tests. Despite its limitations, the clinical benefit of this approach is clearly demonstrated for DSD patients allowing for timely accurate diagnoses, more informed management strategies and improved counselling for patients and their families.

Declaration of interest

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Funding

This work did not receive any specific grant from any funding agency in the public, commercial, or not-for-profit sector.