Critical care medicine is a multidisciplinary endeavor that crosses traditional departmental and specialty lines. Despite large health care expenditures for critical care services, no single institute at the NIH specifically focuses on the critically ill or injured patient. On the functional genomics side, the massive amount of data generated by its technologies calls out for further collaboration, not just among medical specialties but between the medical community and biostatisticians, mathematicians, computer scientists, and computational biologists. To focus attention on both the integrative demands of critical care medicine and the need for close communication with experts in functional genomic technologies, the NIH sponsored its first symposium on Functional Genomics of Critical Illness and Injury, which was held at the Clinical Center in April 2002. This gathering was sponsored jointly by the Clinical Center, NIGMS, NIAMS, NHLBI, NHGRI, and NIAID with the help of the NIH Foundation and support from four international medical societies. Health care providers, physiologists, molecular biologists, genomicists, and biostatisticians gathered for three days to discuss the impact of genomics and proteomics on the science and practice of critical care medicine.

Four hundred participants representing more than ten countries heard presentations spanning a range of biologic complexity, from genome to population. Thirty leaders in their respective fields spoke on topics such as the clinical epidemiology of critical illness and injury, biocomplexity, investigational therapies, genome-wide expression profiles in trauma and infection, functional aspects of genetic variability in the intensive care unit, genomic studies of host-pathogen interactions, applications for defense against bioterrorism, and the future of computational genomics.

Attendees uniformly hailed the conference as a watershed event. Three general themes emerged from comments and suggestions of the participants: First and most importantly, the symposium should be held annually. Second, increased collaboration should develop between those who generate the data (experimentalists) and those who analyze it (informaticists). Third, the experimental designs and analytic standards developed by centers with the greatest expertise should be shared widely to optimize the use of resources and data.