Recent advances have facilitated the use of blood-derived RNA to conduct genomic analyses of human diseases. This emerging technology represents a rigorous and convenient alternative to traditional tissue biopsy-derived RNA, as it allows for larger sample sizes, better standardization of technical procedures, and the ability to non-invasively profile human subjects. In the present pilot study, we have collected RNA from blood of patients diagnosed with schizophrenia or bipolar disorder (BPD), as well as normal control subjects. Using microarray analysis, we found that each disease state exhibited a unique expressed genome signature, allowing us to discriminate between the schizophrenia, BPD, and control groups. In addition, we validated changes in several potential biomarker genes for schizophrenia and BPD by RT-PCR, and some of these were found to code to chromosomal loci previously linked to schizophrenia. Linear and non-linear combinations of eight putative biomarker genes (APOBEC3B, ADSS, ATM, CLC, CTBP1, DATF1, CXCL1, and S100A9) were able to discriminate between schizophrenia, BPD, and control samples, with an overall accuracy of 95%-97% as indicated by receiver operating characteristic (ROC) curve analysis. We therefore propose that blood cell-derived RNA may have significant value for performing diagnostic functions and identifying disease biomarkers in schizophrenia and BPD.

Linear combinations of blood RNA biomarkers offer a substantial improvement over currently available diagnostic tools for mild OA. Blood-derived RNA biomarkers may be of significant clinical value for the diagnosis of early, asymptomatic OA of the knee.

Several studies have evaluated the potential utility of blood-based whole-transcriptome signatures as a source of biomarkers for schizophrenia. This endeavor has been complicated by the fact that individuals with schizophrenia typically differ from appropriate comparison subjects on more than just the presence of the disorder; for example, individuals with schizophrenia typically receive antipsychotic medications, and have been dealing with the sequelae of this chronic illness for years. The inability to control such factors introduces a considerable degree of uncertainty in the results to date. To overcome this, we performed a blood-based gene-expression profiling study of schizophrenia patients (n=9) as well as their unmedicated, nonpsychotic, biological siblings (n=9) and unaffected comparison subjects (n=12). The unaffected biological siblings, who may harbor some of the genetic predisposition to schizophrenia, exhibited a host of gene-expression differences from unaffected comparison subjects, many of which were shared by their schizophrenic siblings, perhaps indicative of underlying risk factors for the disorder. Several genes that were dysregulated in both individuals with schizophrenia and their siblings related to nucleosome and histone structure and function, suggesting a potential epigenetic mechanism underlying the risk state for the disorder. Nonpsychotic siblings also displayed some differences from comparison subjects that were not found in their affected siblings, suggesting that the dysregulation of some genes in peripheral blood may be indicative of underlying protective factors. This study, while exploratory, illustrated the potential utility and increased informativeness of including unaffected first-degree relatives in research in pursuit of peripheral biomarkers for schizophrenia.

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