Blood gene expression profile for diagnosis of mental illness

Release date: 2007-04-09

Blood gene expression profiling Diagnosing mental illness Four unique diagnostic gene expression profiles were used to detect blood samples from patients with schizophrenia/irritosis and bipolar depression, with statistical significance (p < 0.001). The genes of 115 patients with schizophrenia/irritosis and bipolar disease and matched control patients were analyzed. The results of the analysis showed that only one group of each patient/control group of subgroups was identical, and each subgroup was associated with a unique and limited number of genes. The genes found in each subgroup include known and new drug targets and biomarkers, and the specificity and sensitivity of blood tests are tested. Blood test results were consistent with two independent Curidium (London, UK) using the company's tool Homomatrix brain findings. Homomatrix is ​​a fully automated detection tool that uses patent pattern recognition tools and mathematical algorithm sequences and statistical methods to objectively analyze massive gene expression and biological data from heterogeneous populations. These assays can facilitate the development of therapeutic-response and/or patient subgroup diagnostic methods, signaling pathways, and drug targets. Gene Expression Profiles in Blood Diagnosed Mental Illness Four unique and statistically signdiagnostic gene expression profiles were identschizophrenia/bipolar disorder patients. The gene expression profiles of 115 schizophrenia/bipolar disorder patients and matched controls were analyzed. The result of this analysis showed that each patient/ Controls a member of only one of four subgroups and each subgroup was associated with a unique and finite number of genes. The genes identdrug targets and biomarkers, and the specpotential blood diagnostic test are being determined. These results in blood are in line with the Homomatrix is ​​a fully automated analysis tool that uses proprietary pattern recognition tools and sequences of mathematic algorithms together with statistical methods to objectively analyze large sets of gene expression and biological Data from heterogeneous populations. Thes E analyses can potentially lead to the development of diagnostics that identpathways as well as drug targets.--Medical