Adopting High-Resolution Allele Frequencies Substantially Expedites Variant Interpretation in Genetic Diagnostic Laboratories.

A cohort of 1242 individuals tested in a clinical diagnostic laboratory was used to test whether the filtering allele frequencies (FAFs)-based framework, recently recommended for MHY7-associated cardiomyopathy, is extendable to 45 cardiomyopathy genes. Statistical analysis revealed a threshold of 0.00164% for the extreme outlier allele frequencies (AFs), based on the Genome Aggregation Database (exome fraction) total AFs of 138 unique pathogenic and likely pathogenic variants; 135 of them (97.8%) had AFs of <0.004%, the recommended threshold to apply moderate pathogenicity evidence for MYH7-associated cardiomyopathy. Of the 460 cases reported with only variant(s) of unknown clinical significance (VUCSs), 97 (21%) solely had VUCSs with FAFs >0.03%, frequencies above which were estimated herein as strong evidence against pathogenicity. Interestingly, 74.5% (172/231) of the unique VUCSs with FAFs >0.03% had Genome Aggregation Database maximum allele frequencies across all populations AFs >0.1%, deemed herein as stand-alone evidence against pathogenicity. Accordingly, using an FAF threshold of >0.1%, compared with AF >1%, led us to issue considerably more (25.9% versus 41.3%) negative patient reports. Also, 82.7% (N = 629) of the unique classified benign or likely benign variants with AFs <1% had FAFs >0.1%, reinforcing the use of this filtering strategy. Together, these data demonstrate that implementing FAF thresholds may considerably decrease the amount of variant interpretations and significantly reduce the cost of genetic testing for clinical genetic laboratories, without compromising the accuracy of genetic diagnostic services.

Leveraging the power of new molecular technologies in the clinical setting requires unprecedented awareness of limitations and drawbacks: experience of one diagnostic laboratory.

BACKGROUND: Advances in molecular technologies and in-silico variant prediction tools offer wide-ranging opportunities in diagnostic settings, yet they also present with significant limitations. OBJECTIVE: Here, we contextualise the limitations of next-generation sequencing (NGS), multiplex ligation-dependent probe amplification (MLPA) and in-silico prediction tools routinely used by diagnostic laboratories by reviewing specific experiences from our diagnostic laboratory. METHODS: We investigated discordant annotations and/or incorrect variant 'callings' in exons of 56 genes constituting our cardiomyopathy and connective tissue disorder NGS panels. Discordant variants and segmental duplications (SD) were queried using the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool and the University of California Santa Cruz genome browser, respectively, to identify regions of high homology. Discrepant variant analyses by in-silico models were re-evaluated using updated file entries. RESULTS: We observed a 5% error rate in MYH7 variant 'calling' using MLPA, which resulted from >90% homology of the MYH7 probe-binding site to MYH6. SDs were detected in TTN, PKP2 and MYLK. SDs in MYLK presented the highest risk (15.7%) of incorrect variant 'calling'. The inaccurate 'callings' and discrepant in-silico predictions were resolved following detailed investigation into the source of error. CONCLUSION: Recognising the limitations described here may help avoid incorrect diagnoses and leverage the power of new molecular technologies in diagnostic settings.