The biotechnology revolution has led to unprecedented progress in elucidating the structure of the human genome and determining patterns of gene expression relevant to disease pathogenesis. Each new breakthrough produces an immediate and often intense flurry of activity as investigators explore its place in the scientific repertoire and determine the insights it provides for understanding disease. Polymerase chain reaction (PCR) is an example of such a transforming technology which, in a short time, facilitated a quantum leap in our ability to clone novel genes and quantify gene expression at the level of messenger RNA (mRNA). As with all “hot” new methods, many years passed before the strengths and weaknesses of PCR were recognized and more powerful applications, such as real-time PCR, were developed and refined. Microarray technology represents another cutting-edge technology that promises extraordinary advances in the study of disease. As described in an article by Grant et al in this issue of Arthritis & Rheumatism (1), microarray technology provides scientists the tools to scan simultaneously the array of expressed genes in a cell and glean myrid information about cellular function. In the face of such power and precision, it may appear as if hypotheses are superfluous to the pursuit of research and that specific questions need no longer be asked. Indeed, microarray technology, buttressed by elaborate computer software of great sophistication, can give the illusion that all of the information can be “downloaded” from the cell and its secrets revealed to the inquisitive mind. The siren song of microarrays is indeed strong and tantalizing. Of course, research is never quite that simple. With every new technology, the siren song gives way to harsh reality. Experience with a technology is often sobering, reminding investigators of the complexity of life processes as well as scientific investigation. In the case of microarrays, this complexity comes with an unprecedented amount of data that variously seems to be a treasure chest, a morass, and an assault. Like all emerging technologies, microarrays necessitate great respect and caution lest the resulting data be misused if not abused. In the last year, Arthritis & Rheumatism has received a large number of manuscripts describing studies using microarray technology. These manuscripts address the full gamut of rheumatologic disease and involve material from patients, animal models, and in vitro cell models. By their nature, these studies, which entail a field in its infancy, raise difficult questions concerning the criteria for judging the technical aspects of the research as well as its scientific validity. Because of the confusion that faces the investigator, reviewer, and reader confronted with microarray data, we have long pondered how best to promote the publication of articles describing studies using this technology. As a result of extensive discussion among members of the editorial board of Arthritis & Rheumatism, we have developed suggested guidelines for the submission and review of reports of investigations involving microarray technology. These guidelines acknowledge the strengths and limitations of this technology and indicate the rigor we believe necessary to publish reports of microarray-based studies in our journal. The guidelines are tentative and should be viewed as a work in progress that will be revisited as the field progresses. Nevertheless, with these guidelines, we hope to provide the scientific community with broad criteria that investigators can use in the design of their studies and, in turn, Gary S. Firestein, MD: University of California, San Diego School of Medicine, La Jolla, Deputy Editor, Arthritis & Rheumatism; David S. Pisetsky, MD, PhD: Durham VAMC and Duke University Medical Center, Durham, North Carolina, Editor, Arthritis & Rheumatism. Address correspondence and reprint requests to David S. Pisetsky, MD, PhD, Durham VA Medical Center, 151G, 508 Fulton Street, Durham, NC 27705. Submitted for publication December 19, 2001; accepted December 20, 2001.
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Firestein et al. (2002) studied this question.
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