Additional Assays Increase Exome Sequencing Diagnostic Yield in Rare Neurogenetic Disorders
Investigators obtained a molecular diagnostic yield of 39% in 66 sequential, unselected individuals with diverse presentations of rare neurogenetic disorders when using a model that integrates additional assays.
Christopher Grunseich, MD
A multimodal approach that included deep phenotyping, gene filter algorithms, and biological assays helped improve the diagnostic efficacy of whole exome sequencing (WES) in patients with atypical presentations of rare neurogenetic diseases. Investigators used the approach to redefine practice, identify new disease-associated variants, expand the phenotypic spectrum of rare diseases, and offer improved care to patients and at-risk family members.
Lead author Christopher Grunseich, MD, staff clinician, National Institute of Neurological Disorders and Stroke (NINDS), and colleagues performed WES on 66 individuals with neurogenetic diseases using candidate gene filters and stringent algorithms for assessing sequence variants. Silico prediction tools, family segregation analysis, previous publications of disease association, and relevant biological assays were used to interpret pathogenic or likely pathogenic missense variants.
Despite that WES is well-established in the research and diagnostic fields, Grunseich et al wrote that “additional methods and approaches are needed for the interpretation and confirmation of this data, and the interface between the neurologist and the patient needs to be better described so that more physicians can decide which next steps are appropriate in the subsequent evaluation and validation of genetic testing data.” Their approach, they noted, utilized tools which are feasible for clinical practice, including predictive algorithms, bioinformatics, family segregation studies, clinical diagnostic tests, and biological assays.
The NimbleGen SeqCap EZ V.3.0+ UTR capture kit was used to cover 96 Mb of genomic DNA. Following this, DNA was sequenced using Illumina HiSeq to provide coverage to call most probable genotypes with a score of 10 in at least 85% of targeted bases. Reads were mapped to NCBI build 37 using the Efficient Large-scale Alignment of Nucleotide Databases.
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A molecular genetic diagnosis was made in 39% (n = 26) of patients tested, with the highest yield in patients with affected family members (88%; 14 of 16) and those with a complex phenotype (63%; 5 of 8). Sixteen individuals (59%) with disease onset before 20 years of age received a genetic diagnosis, whereas the yield was relatively lower (27%) in older individuals with disease onset after 40 years of age.
Overall, 37% (10 of 27) of myopathy, 41% (9 of 22) of neuropathy, 22% (2 of 9) of motor neuron disease (MND) and 63% (5 of 8) of complex phenotypes were given genetic diagnosis. Ten novel pathogenic variants in FBX038, LAMA2, MFN2, MYH7, PNPLA6, Sh3TC2, and SPTLC1, were identified in patients with myopathy (n = 3), neuropathy (n = 5) and MND (n = 2). Each of these variants occurred in important functional domains of the proteins considered as hotspots for disease-associated variants.
Investigators noted that they believe this approach is more successful than panel testing, demonstrated by the ability to diagnosis 47% (11 of 23) of patients with previous negative gene panel sequencing. The approach was also effective in diagnosing rare and potentially treatable diseases such as cerebrotendinous xanthomatosis (CTX) and homozygous DOK7 mutation. Additionally, they noted that in comparison to panel testing, WES is more cost effective and rapid.
WES analysis also extended phenotypes in patients with novel as well as established disease-associated variants (n = 16). Atypical features such as optic neuropathy in adult polyglucosan body disease, facial dysmorphism and skeletal anomalies in CTX, and steroid-responsive weakness in congenital myasthenia syndrome 10 were all observed among established disease-associated variants.
Limitations of WES included the inability to interrogate multiple variants that occur in regions of genome not currently recognized as a functional or regulatory region or resulting in large genomic reorganizations such as repeat extensions, deletions, or duplications. Incomplete capture and coverage of genes may result in a failure to make a molecular diagnosis, according to study authors.
