Microarray techniques hold great promise for identifying risk factors for schizophrenia (SZ) but have not yet generated widely reproducible results due to methodological differences between studies and the high risk of type I inferential errors. Here we established a protocol for conservative analysis and interpretation of gene expression data from the dorsolateral prefrontal cortex of SZ patients using statistical and bioinformatic methods that limit false positives. We also compared brain gene expression profiles with those from peripheral blood cells of a separate sample of SZ patients to identify disease-associated genes that generalize across tissues and populations and further substantiate the use of gene expression profiling of blood for detecting valid SZ biomarkers. Implementing this systematic approach, we: (i) discovered 177 putative SZ risk genes in brain, 28 of which map to linked chromosomal loci; (ii) delineated six biological processes and 12 molecular functions that may be particularly disrupted in the illness; (iii) identified 123 putative SZ biomarkers in blood, 6 of which (BTG1, GSK3A, HLA-DRB1, HNRPA3, SELENBP1, and SFRS1) had corresponding differential expression in brain; (iv) verified the differential expression of the strongest candidate SZ biomarker (SELENBP1) in blood; and (v) demonstrated neuronal and glial expression of SELENBP1 protein in brain. The continued application of this approach in other brain regions and populations should facilitate the discovery of highly reliable and reproducible candidate risk genes and biomarkers for SZ. The identification of valid peripheral biomarkers for SZ may ultimately facilitate early identification, intervention, and prevention efforts as well.