Microarray analysis has shown substantial benefits in diagnosing certain congenital disorders. However, one of the challenges with using chromosomal microarray analyses for clinical applications is the inconsistent reimbursement for testing, as third-party payers often consider them to be an experimental tool because of a lack of evidence that microarray testing affects patient management or clinical outcomes.
“There is not a lot of information out there published on this, and this was the reason why we tried to gather evidence to show that microarray analysis actually provides useful information for patients,” says Jay W. Ellison, M.D., Ph.D., medical director at Signature Genomics at PerkinElmer.
Dr. Ellison and colleagues selected specific medical conditions that can be diagnosed with microarray technologies and have specific clinical features that require medical follow-up. Many times, patients diagnosed with these conditions might not be aware of their risk to develop certain medical problems.
“We tallied the frequency with which these actionable diagnoses were made, and it was quite high. Up to one-third of the diagnoses that were made had features that would require specific medical or clinical actions. This was the major take-home message from this study,” explains Dr. Ellison.
In addition, the authors tracked a subset of patients to see whether physicians responded to the test results with specific clinical actions that are related to the diagnosis, and reported that specific and appropriate clinical actions were taken approximately 90% of the time, an aspect that awaits further work to be explored in more detail.
“The best future studies will be within provider systems where one can capture those individuals who were tested by chromosomal microarrays and look at the clinical outcomes that result from receiving the result of the microarray,” explains Marc S. Williams, M.D., director of the Genomic Medicine Institute at Geisinger Health System.
In the short time that elapsed since the extent of genomic copy-number variation was discovered, its role in biomedical areas as diverse as physiological development, disease pathogenesis, pharmacogenomics, and evolution has become increasingly apparent. In parallel, technological advances have fundamentally contributed to measuring specific copy-number variants and characterizing their significance.
These strides promise to catalyze the incorporation of this relatively newly discovered source of interindividual genomic variability into routine clinical applications, forecasting one of the most exciting times that medicine and biology have seen.