Biomarker identification in neurologic diseases: Improving diagnostics and therapeutics

Identification of biomarkers in neurological disease remains impeded by many obstacles. Among them are the availability of tissue at the site of pathology, poor clinical diagnostics, the complexity of the brain and a general dearth of functional end points and models for validation. However, advances in technology have helped to overcome these challenges. Some of these advances include standardization and increased efficiency in brain banking, novel techniques for brain imaging, improved methods for reducing tissue heterogeneity including laser capture microdissection, high-throughput genomics, new functional validation techniques such as RNA interference, and the development of new animal models of neurologic disease. In order to efficiently handle the wealth of information that will be gleaned from these new technologies, new integrated databasing protocols will be necessary. Access to these databases by researchers and clinicians is critical to the continued progress being made in biomarker identification in neurological disease. These challenges and ways to overcome them are presented here in the context of a disease known to be a robust model for biomarker identification, Alzheimer's disease.