Shariant platform: Enabling evidence sharing across Australian clinical genetic-testing laboratories to support variant interpretation.

Sharing genomic variant interpretations across laboratories promotes consistency in variant assertions. A landscape analysis of Australian clinical genetic-testing laboratories in 2017 identified that, despite the national-accreditation-body recommendations encouraging laboratories to submit genotypic data to clinical databases, fewer than 300 variants had been shared to the ClinVar public database. Consultations with Australian laboratories identified resource constraints limiting routine application of manual processes, consent issues, and differences in interpretation systems as barriers to sharing. This information was used to define key needs and solutions required to enable national sharing of variant interpretations. The Shariant platform, using both the GRCh37 and GRCh38 genome builds, was developed to enable ongoing sharing of variant interpretations and associated evidence between Australian clinical genetic-testing laboratories. Where possible, two-way automated sharing was implemented so that disruption to laboratory workflows would be minimized. Terms of use were developed through consultation and currently restrict access to Australian clinical genetic-testing laboratories. Shariant was designed to store and compare structured evidence, to promote and record resolution of inter-laboratory classification discrepancies, and to streamline the submission of variant assertions to ClinVar. As of December 2021, more than 14,000 largely prospectively curated variant records from 11 participating laboratories have been shared. Discrepant classifications have been identified for 11% (28/260) of variants submitted by more than one laboratory. We have demonstrated that co-design with clinical laboratories is vital to developing and implementing a national variant-interpretation sharing effort. This approach has improved inter-laboratory concordance and enabled opportunities to standardize interpretation practices.

A Multi-Disciplinary Team Approach to Genomic Testing for Drug-Resistant Epilepsy Patients-The GENIE Study.

BACKGROUND: The genomic era has led to enormous progress in clinical care and a multi-disciplinary team (MDT) approach is imperative for integration of genomics into epilepsy patient care. METHODS: The MDT approach involved patient selection, genomic testing choice, variant discussions and return of results. Genomics analysis included cytogenomic testing and whole exome sequencing (WES). Neurologist surveys were undertaken at baseline and after genomic testing to determine if genomic diagnoses would alter their management, and if there was a change in confidence in genomic testing and neurologist perceptions of the MDT approach. RESULTS: The total diagnostic yield from all genomic testing was 17% (11/66), with four diagnoses from cytogenomic analyses. All chromosomal microarray (CMA) diagnoses were in patients seen by adult neurologists. Diagnostic yield for WES was 11% (7/62). The most common gene with pathogenic variants was DCX, reported in three patients, of which two were mosaic. The genomic diagnosis impacted management in 82% (9/11). There was increased confidence with integrating genomics into clinical care (Pearson chi square = 83, p = 0.004) and qualitative comments were highly supportive of the MDT approach. CONCLUSIONS: We demonstrated diagnostic yield from genomic testing, and the impact on management in a cohort with drug-resistant epilepsy. The MDT approach increased confidence in genomic testing and neurologists valued the input from this approach. The utility of CMA was demonstrated in epilepsy patients seen by adult neurologists as was the importance of considering mosaicism for previously undiagnosed patients.

Paediatric genomic testing: Navigating medicare rebatable genomic testing.

Genomic testing for a genetic diagnosis is becoming standard of care for many children, especially those with a syndromal intellectual disability. While previously this type of specialised testing was performed mainly by clinical genetics teams, it is increasingly being 'mainstreamed' into standard paediatric care. With the introduction of a new Medicare rebate for genomic testing in May 2020, this type of testing is now available for paediatricians to order, in consultation with clinical genetics. Children must be aged less than 10 years with facial dysmorphism and multiple congenital abnormalities or have global developmental delay or moderate to severe intellectual disability. This rebate should increase the likelihood of a genetic diagnosis, with accompanying benefits for patient management, reproductive planning and diagnostic certainty. Similar to the introduction of chromosomal microarray into mainstream paediatrics, this genomic testing will increase the number of genetic diagnoses, however, will also yield more variants of uncertain significance, incidental findings, and negative results. This paper aims to guide paediatricians through the process of genomic testing, and represents the combined expertise of educators, clinical geneticists, paediatricians and genomic pathologists around Australia. Its purpose is to help paediatricians navigate choosing the right genomic test, consenting patients and understanding the possible outcomes of testing.

ClinSV: clinical grade structural and copy number variant detection from whole genome sequencing data.

Whole genome sequencing (WGS) has the potential to outperform clinical microarrays for the detection of structural variants (SV) including copy number variants (CNVs), but has been challenged by high false positive rates. Here we present ClinSV, a WGS based SV integration, annotation, prioritization, and visualization framework, which identified 99.8% of simulated pathogenic ClinVar CNVs > 10 kb and 11/11 pathogenic variants from matched microarrays. The false positive rate was low (1.5-4.5%) and reproducibility high (95-99%). In clinical practice, ClinSV identified reportable variants in 22 of 485 patients (4.7%) of which 35-63% were not detectable by current clinical microarray designs. ClinSV is available at https://github.com/KCCG/ClinSV .

Genomic diagnostics in polycystic kidney disease: an assessment of real-world use of whole-genome sequencing.

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is common, with a prevalence of 1/1000 and predominantly caused by disease-causing variants in PKD1 or PKD2. Clinical diagnosis is usually by age-dependent imaging criteria, which is challenging in patients with atypical clinical features, without family history, or younger age. However, there is increasing need for definitive diagnosis of ADPKD with new treatments available. Sequencing is complicated by six pseudogenes that share 97% homology to PKD1 and by recently identified phenocopy genes. Whole-genome sequencing can definitively diagnose ADPKD, but requires validation for clinical use. We initially performed a validation study, in which 42 ADPKD patients underwent sequencing of PKD1 and PKD2 by both whole-genome and Sanger sequencing, using a blinded, cross-over method. Whole-genome sequencing identified all PKD1 and PKD2 germline pathogenic variants in the validation study (sensitivity and specificity 100%). Two mosaic variants outside pipeline thresholds were not detected. We then examined the first 144 samples referred to a clinically-accredited diagnostic laboratory for clinical whole-genome sequencing, with targeted-analysis to a polycystic kidney disease gene-panel. In this unselected, diagnostic cohort (71 males :73 females), the diagnostic rate was 70%, including a diagnostic rate of 81% in patients with typical ADPKD (98% with PKD1/PKD2 variants) and 60% in those with atypical features (56% PKD1/PKD2; 44% PKHD1/HNF1B/GANAB/ DNAJB11/PRKCSH/TSC2). Most patients with atypical disease did not have clinical features that predicted likelihood of a genetic diagnosis. These results suggest clinicians should consider diagnostic genomics as part of their assessment in polycystic kidney disease, particularly in atypical disease.

Genome sequencing as a first-line genetic test in familial dilated cardiomyopathy.

PURPOSE: We evaluated genome sequencing (GS) as an alternative to multigene panel sequencing (PS) for genetic testing in dilated cardiomyopathy (DCM). METHODS: Forty-two patients with familial DCM underwent PS and GS, and detection rates of rare single-nucleotide variants and small insertions/deletions in panel genes were compared. Loss-of-function variants in 406 cardiac-enriched genes were evaluated, and an assessment of structural variation was performed. RESULTS: GS provided broader and more uniform coverage than PS, with high concordance for rare variant detection in panel genes. GS identified all PS-identified pathogenic or likely pathogenic variants as well as two additional likely pathogenic variants: one was missed by PS due to low coverage, the other was a known disease-causing variant in a gene not included on the panel. No loss-of-function variants in the extended gene set met clinical criteria for pathogenicity. One BAG3 structural variant was classified as pathogenic. CONCLUSION: Our data support the use of GS for genetic testing in DCM, with high variant detection accuracy and a capacity to identify structural variants. GS provides an opportunity to go beyond suites of established disease genes, but the incremental yield of clinically actionable variants is limited by a paucity of genetic and functional evidence for DCM association.

Characterization of a 520 kb deletion on chromosome 15q26.1 including ST8SIA2 in a patient with behavioral disturbance, autism spectrum disorder, and epilepsy.

We present a patient with a behavioral disorder, epilepsy, and autism spectrum disorder who has a 520 kb chromosomal deletion at 15q26.1 encompassing three genes: ST8SIA2, C15orf32, and FAM174B. Alpha-2,8-Sialyltransferase 2 (ST8SIA2) is expressed in the developing brain and appears to play an important role in neuronal migration, axon guidance and synaptic plasticity. It has recently been implicated in a genome wide association study as a potential factor underlying autism, and has also been implicated in the pathogenesis of bipolar disorder and schizophrenia. This case provides supportive evidence that ST8SIA2 haploinsufficiency may play a role in neurobehavioral phenotypes.