Bionano Genomics, Inc. announced a peer-reviewed publication detailing results from the second phase of a large multisite clinical study designed to support establishing optical genome mapping (OGM) as part of the standard of care (SOC) in diagnosis of genetic disease for postnatal patients. The clinical study is designed to compare OGM to current SOC techniques, including concordance, reproducibility, technical success rate and the rate of detecting reportable findings in cases. The published first phase of this multisite study demonstrated OGM?s technical performance and reproducibility across sites versus SOC analysis.

This second phase extended the study to include additional samples to further assess the technical performance and clinical utility of OGM for postnatal constitutional disorders and to evaluate OGM in prospective samples and in samples from subjects with neurodevelopmental disorders, including developmental delay, intellectual disability and autism spectrum disorder (ASD). The sites conducting the study and their principal investigators are as follows: University of Rochester Medical Center (Dr. M. Anwar Iqbal); Medical College of Wisconsin (Dr. Ulrich Broeckel); Columbia University Medical Center (Dr. Brynn Levy); Greenwood Genetic Center (Dr. Roger Stevenson); Medical College of Georgia, Augusta University (Dr. Ravindra Kolhe); Praxis Genomics (Dr. Peter L. Nagy); University of Iowa Hospitals & Clinics (Aaron Stence); and H. Lee Moffitt Cancer Center (Dr. Aaron Bossler). Key Findings: The peer-reviewed publication describes OGM performance metrics compared to SOC methods for challenging samples from diagnosed and undiagnosed rare diseases.

The key findings are: OGM concordance for pathogenic variants in all combined samples against SOC methods was 99.5% (995 out of 1,000 samples). OGM increased the rate of finding pathogenic or likely pathogenic (P/LP) variants over that of SOC by a factor of 6% to as much as 50% depending on the patient population. Key Takeaways: The study authors reported that results demonstrate the ability of an OGM workflow to detect all classes of structural variants (SVs) with higher resolution compared to current SOC methods, including aneuploidies, triploidy, translocations, inversions, insertions, microdeletions, microduplications, nucleotide repeat expansions or contractions, and absence of heterozygosity (AOH).

In contrast to variants that are detected by microarray, which are limited to gains and losses, the variants reported by OGM include all classes of SVs, several of which reside in candidate genes associated with the phenotype. The authors concluded that OGM can offer a simple and streamlined workflow that can detect relevant genomic aberrations and mitigate the need for numerous testing platforms and time-consuming wet lab work, potentially improving lab performance by reducing the associated time and costs.