Toward an Alzheimer's disease diagnosis via high-resolution blood gene expression.

BACKGROUND: There is a significant need for reliable molecular biomarkers to aid in Alzheimer's disease (AD) clinical diagnosis. METHODS: We performed a genome-wide investigation of the human transcriptome, taking into account the discriminatory power of splice variations from the blood of 80 AD patients and 70 nondemented control (NDC) individuals. RESULTS: We characterized a blood RNA signature composed of 170 oligonucleotide probe sets associated with 133 genes that can correctly distinguish AD patients from NDC with a sensitivity of 100% and specificity of 96%. Functionally, this signature highlights genes involved in pathways that were associated with macrophages and lymphocytes within AD patients: Transforming growth factor (TGF-beta) signaling, oxidative stress, innate immunity and inflammation, cholesterol homeostasis, and lipid-raft perturbation, whereas other genes may also provide new insights in the biology of AD. CONCLUSIONS: This study provides proof-of-concept that whole-blood profiling can generate an AD-associated classification signature via the specific relative expression of biologically relevant RNAs. Such a signature will need to be validated with extended patient cohorts, and evaluated to learn whether it can differentiate AD from others types of dementia.

High resolution analysis of the human transcriptome: detection of extensive alternative splicing independent of transcriptional activity.

BACKGROUND: Commercially available microarrays have been used in many settings to generate expression profiles for a variety of applications, including target selection for disease detection, classification, profiling for pharmacogenomic response to therapeutics, and potential disease staging. However, many commercially available microarray platforms fail to capture transcript diversity produced by alternative splicing, a major mechanism for driving proteomic diversity through transcript heterogeneity. RESULTS: The human Genome-Wide SpliceArray(TM) (GWSA), a novel microarray platform, utilizes an existing probe design concept to monitor such transcript diversity on a genome scale. The human GWSA allows the detection of alternatively spliced events within the human genome through the use of exon body and exon junction probes to provide a direct measure of each transcript, through simple calculations derived from expression data. This report focuses on the performance and validation of the array when measured against standards recently published by the Microarray Quality Control (MAQC) Project. The array was shown to be highly quantitative, and displayed greater than 85% correlation with the HG-U133 Plus 2.0 array at the gene level while providing more extensive coverage of each gene. Almost 60% of splice events among genes demonstrating differential expression of greater than 3 fold also contained extensive splicing alterations. Importantly, almost 10% of splice events within the gene set displaying constant overall expression values had evidence of transcript diversity. Two examples illustrate the types of events identified: LIM domain 7 showed no differential expression at the gene level, but demonstrated deregulation of an exon skip event, while erythrocyte membrane protein band 4.1 -like 3 was differentially expressed and also displayed deregulation of a skipped exon isoform. CONCLUSION: Significant changes were detected independent of transcriptional activity, indicating that the controls for transcript generation and transcription are distinct, and require novel tools in order to detect changes in specific transcript quantity. Our results demonstrate that the SpliceArray(TM) design will provide researchers with a robust platform to detect and quantify specific changes not only in overall gene expression, but also at the individual transcript level.