Chipping Away at Disease

Three SAS Researchers Use JMP Genomics to Analyze Data in Major FDA Study.

Can a dime-sized glass chip containing an array of genetic information hold the key to faster, more accurate diagnoses and customized treatment of diseases? Or has the promise of personalized medicine been overhyped, as some critics contend?

That’s the question that more than 150 scientists from across the nation -– including three SAS researchers -– set out to answer 18 months ago in a sweeping study of DNA microarray technology sponsored by the U.S. Food and Drug Administration. The study was undertaken by the MicroArray Quality Control (MAQC) Consortium.

"Personalized medicine and proactive health are two ultimate goals, and we will achieve them in stages," explained Russ Wolfinger, SAS Director of Scientific Discovery and Genomics.

Dr. Wolfinger and two SAS colleagues, Tzu-Ming Chu and Wenjun Bao, were three of the co-authors on two articles about the MAQC study published in the September issue of Nature Biotechnology. The publication hailed the study as "a landmark in DNA microarray research" achieved by "an unprecedented, community-wide effort."

The SAS team also made significant contributions to another journal article documenting the interplatform and intraplatform reproducibility of expression measurement that also was published in the September 2006 issue of Nature Biotechnology.

"Large-scale, consortium-driven data sets like these are becoming more and more prominent," Wolfinger said, "and our SAS technologies are up to the ever-increasing challenges." JMP Genomics, which relies on SAS macros for the heavy-duty data processing, offers a JMP-driven menu system to simplify parameter selection at the start of the process and data-visualization capabilities to translate results into dynamic, interactive graphical displays at the end.

As part of the study, the SAS team used JMP Genomics software to analyze the data from more than 1,300 microarrays tested at 18 labs using instrumentation from all major array manufacturers. The team compared results from one- and two-color labeling designs, using two independent RNA samples tested on each of three different microarray platforms. The results indicate that data quality is essentially equivalent between the one- and two-color approaches and strongly suggest that this variable need not be a primary factor in decisions regarding experimental microarray design.

Results show that microarray technology yields reliable, reproducible results. That critical finding gives the FDA the validation it needs to consider whether microarrays should be added to the arsenal of diagnostic and drug-testing procedures it sanctions.

The full findings of the MAQC study are reported in the September 2006 issue of Nature Biotechnology. The detailed results of the project led by Russ Wolfinger are found in "Performance comparison of one-color and two-color platforms within the Microarray Quality Control (MAQC) project."

In the study’s next phase, MAQC researchers expect to spend up to two more years determining whether genetic readouts from various "biomarkers" can reliably predict how a disease is likely to progress in a certain patient, and which drug should produce the best treatment result in that patient.

"If we didn’t pass Phase One, we were dead in the water; but Phase Two is much more important to human health and the viability of this technology," said Wolfinger.

JMP Genomics software includes 100 SAS stored processes, many of which are generic in nature and can be leveraged into other disciplines. The genomics-specific processes extract information from molecular data and present the results in an understandable way.

Figure

Figure 1.
MAQC study findings: JMP Genomics volcano plots depicting estimated fold change (log2, x-axis) and statistical significance (-log10P value, y-axis).*
* For full details, see Nature Biotechnology, September 2006.