Discussion
In this study we report the clinical application of WES in the diagnosis
of 162 cases referred to a single academic genetics center. The overall
molecular diagnostic yield reached 52.5%, slightly higher of that
reported in many previous studies (Jalkh et al., 2019; Sawyer et al.,
2016; Seaby et al., 2016; Valencia et al., 2015). This rate was observed
to vary depending on the disease category (Figure 3), but is also likely
influenced by the strategy applied. In our department, the strategy
included: (1) Analytical clinical description of the patient’s phenotype
along with comprehensive family and medical history to include as many
data; (2) Stringent phenotype-driven strategies adopted for variant
filtration and interpretation (Figure 2); (3) Close collaborations
between clinicians and laboratory geneticists for variant evaluation and
phenotype-genotype correlation; (4) Family segregation strategies with
Sanger sequencing to support evaluation of variant pathogenicity when
necessary. Besides potentially optimizing the diagnostic yield, the
strategy supported a reduction of the number of variants in need of
classification and an acceptable turn-around time and reduced the
overall cost to the patient, paramount in the absence of
NGS-reimbursement in Greece. Every attempt was made to use new and/or
updated annotation and pathogenicity prediction tools and variant
databases, of great value in the context of variant evaluation.
Recognizing the importance of data sharing, 48 novel pathogenic or
likely pathogenic variants were identified in this cohort and uploaded
to public databases.
A few cases in this cohort demonstrated that complex phenotypes may be
caused by complex genotypes, potentially complicating both clinical
evaluation and data interpretation. For example, in cases 8039 and 9151
(Table 2), the findings in TGFB3 and MYH7 genes
respectively, were classified as VUS due to the lack of cardiological
data at the time of WES analysis and the report included a
recommendation for subsequent re-evaluation.
Rare genetic phenomena including variable expressivity, incomplete
penetrance and genetic heterogeneity, should also be considered when
assessing WES results. At least 2 cases had secondary variants
potentially contributing to the clinical expression of the primary
condition. In case 9081 (Table 2), referred with polycystic kidney
disease at the age of 31, the detection of the co-inheritance of the
pathogenic PKD2: c.1837C>T variant associated with
autosomal dominant PKD2, and variant c.6992T>A in thePKHD1 gene, (associated with autosomal recessive PKD4) could
explain the relative early onset of the disease, althoughPKHD1 :c.6992T>A classification is VUS (Bergmann et
al., 2011).
Case 9115 (Table 1) presented with spastic paraplegia with lower limb
spasticity and weakness. WES identified a known pathogenic variant
c.1245+5G>A (Polymeris et al., 2016) of paternal origin inSPAST gene, along with a known modifier polymorphism
c.131C>T of maternal origin in the same gene (Parodi et
al., 2018). Usually variants in SPAST are associated with spastic
paraplegia type 4, where the age of onset ranges between 20 to 60 years;
the infantile onset in this case might be attributed to the presence of
the modifying polymorphism in trans .
Case 9045 (Table 1), highlights the importance of adjunct genetic
analysis, such as classic karyotyping, since ZFPM2 pathogenic
variant are disease causative only in 46,XY individuals. A 6 years-old
female with a 46,XY karyotype, was referred for Disorders of Sex
Development (DSD). A novel, likely pathogenic variant
c.192T>G of maternal origin was detected in theZFPM2 (FOG2 ), related to 46,XY sex reversal 9 (SRXY9).
Functional studies have suggested that failure of testis development is
most likely caused by impaired or no interactions of the mutant ZFPM2
(proteins) with GATA4 gene, which regulates early testis
development (Bashamboo et al., 2014).
Pleiotropy was another interesting observation in this cohort.GJB2 gene is associated with autosomal recessive deafness or
autosomal dominant Vohwinkel syndrome (De Zwart-Storm et al., 2011). Two
unrelated patients with deafness (Table 1) were homozygous for
pathogenic variants c.71G>A (case 8016) and c.35delG (case
8039) in GJB2 . Interestingly, a likely pathogenic variant
c.524C>G was revealed in the same gene in case 9088 (Table
1) with ichthyosis and keratitis but no hearing impairment;
heterozygosity of GJB2: c.524C>G likely explains the
dermatological findings. Unlike recessive GJB2 variants, in which
the spectrum and phenotype-genotype correlations have been analyzed
clearly, only a few studies of GJB2 dominant variants have been
reported. However approximately two-thirds of dominant GJB2mutations are shown to cause syndromic hearing loss associated with
diverse skin lesions(H. Wang et al., 2017).
In cases where one gene is linked to more than one disease or disease
variants, like PTPN11, distinction may be based on differential
clinical features or previous reports of the specific variant.PTPN11 is usually associated with Noonan syndrome 1, as
additionally supported by findings concerning 5 unrelated patients in
this study (8112, 8133, 9080, 9138, 9148) (Table 1). In case 9165 (Table
1), a PTPN11 variant c.1381G>T was associated with
Leopard syndrome 1 (Carcavilla et al., 2013), but the patients’
diagnosis was based on the phenotypic findings rather than the genotype
(Osawa et al. 2009). Diligent clinical examination, biochemical tests
and other pre-WES genetic tests, such as conventional and molecular
karyotype, all have important roles in supporting the interpretation of
WES results.
In conclusion, classical genetic diagnosis strategies involve targeted
single gene/exon analysis often with negative or inconclusive results.
Within the referred period that our academic diagnostic laboratory uses
WES, 85 cases were resolved upon the detection of 94 pathogenic variants
48 of which were novel contributing valuable information to the genotype
spectrum of the disease. Despite the technical and diagnostic challenges
associated with NGS, (phenotyping, clinical and genetic heterogeneity
and variable expressivity), WES provides a unique opportunity to resolve
the genetic etiology of disorders, end diagnostic odysseys and support
the provision of appropriate medical management and genetic counseling.
When used within the context of effective multidisciplinary
collaboration between clinicians and laboratories, the clinical WES
diagnostic tool becomes efficient and cost-effective and thus
appropriate for first-tier genomic analysis.
However, it is important to recognize the limitations of WES, including
low coverage of coding regions, inefficient capture of GC-rich regions,
misalignment of reads to reference genome, presence of pseudogenes,
homologous or repetitive regions, large deletions/duplications, complex
rearrangements, triplet repeat and imprinting variants (Bertier et al.
2016; Taylor et al. 2015; White et al. 2017). Polygenic and/or
multifactorial diseases and limited data on VUS in coding genes not yet
associated with human diseases hinder interpretation and call for
alternative approaches, such as functional studies. Finally, Whole
Genome Sequencing potentially addresses many of the limitations of WES
and can additionally detect non-coding (deep intronic or non-coding
RNAs) and structural variants (Smith et al., 2019).