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Aug 1, 2012 (Vol. 32, No. 14)

Harnessing the Promise of Array CGH

  • Clinical Applications

    Several articles from Dr. Snyder’s lab illustrate the strength that CGH arrays provide in clinical medicine. By using CGH arrays to map segmental trisomies in patients with Down syndrome, the investigators recently generated the highest phenotypic resolution map for this condition to date. This helped narrow down the chromosomal region associated with Down Syndrome-specific congenital heart disease, a major phenotype that accompanies this condition, to a <2 Mb region, and excluded the requirement for several genes that were previously implicated by other studies.

    Moreover, the phenotypic map helped test specific hypotheses that were advanced in the past regarding the etiology of this condition. “Next-generation sequencing is clearly stepping into this area, but arrays are still the perfect tool for confirmation, and they are cheaper, and orthogonal,” emphasizes Dr. Snyder.

    Another recent advancement in Dr. Snyder’s lab was the development of a personalized -omics profile, in a strategy that involved high-accuracy sequencing of several genomes, including his own, combined with the analysis of -omics components, and the examination of personal RNA and protein variants, in a study that included over 3 billion molecular components across multiple time points that spanned 14 months.

    “The data predicted that I will develop diabetes, and I did,” says Dr. Snyder, and the early discovery of this condition helped him implement timely nonpharmacological interventions, including dietary changes and increased exercise, which most likely would not have been able to control the condition by themselves had it been discovered later on at a routine checkup.

  • Reimbursement Woes

    Click Image To Enlarge +
    Microarray data demonstrating a submicroscopic deletion of chromosome 17 in a 4-year-old boy with developmental delay. One or more of the genes (purple) in the deleted region (blue-shaded) is suspected to be responsible for the boy’s developmental delay. Deletion of the HNF1B gene (green) puts the boy at high risk of developing renal abnormalities and diabetes mellitus, neither of which was suspected.

    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.


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