Pharmacotherapy of Schizophrenic Patients: Preponderance of Off-Label Drug Use

Multiple drug class combinations are often prescribed for the treatment of schizophrenia, although antipsychotic monotherapy reflects FDA labeling and scientific justification for combinations is highly variable. This study was performed to gain current data regarding drug treatment of schizophrenia as practiced in the community and to assess the frequencies of off-label drug class combinations. 200 DSM IV-diagnosed schizophrenic patients recruited from community treatment sources participated in this cross-sectional study of community based schizophrenic patients. Drug class categories include First and Second Generation Antipsychotic drugs (FGA and SGA, respectively), mood stabilizers, antidepressants and anti-anxiety drugs. 25.5% of patients received antipsychotic monotherapy; 70% of patients received an antipsychotic and another drug class. A total of 42.5% of patients received more than one antipsychotic drug. The most common drug class combination was antipsychotic and a mood stabilizer. Stepwise linear discriminant function analysis identified the diagnosis of schizoaffective schizophrenia, history of having physically hurt someone and high scores on the General Portion of the PANSS rating scale predicted the combined use of an antipsychotic drug and a mood stabilizer. “Real world” pharmacotherapy of schizophrenia has developed its own established practice that is predominantly off-label and may have outstripped current data support. The economic implications for public sector payers are substantial as well as for the revenue of the pharmaceutical industry, whose promotion of off-label drug use is an increasingly problematic. These data are consistent with the recognition of the therapeutic limitations of both first and second generation antipsychotic drugs

Evidence for Antisense Transcription Associated with MicroRNA Target mRNAs in Arabidopsis

Antisense transcription is a pervasive phenomenon, but its source and functional significance is largely unknown. We took an expression-based approach to explore microRNA (miRNA)-related antisense transcription by computational analyses of published whole-genome tiling microarray transcriptome and deep sequencing small RNA (smRNA) data. Statistical support for greater abundance of antisense transcription signatures and smRNAs was observed for miRNA targets than for paralogous genes with no miRNA cleavage site. Antisense smRNAs were also found associated with MIRNA genes. This suggests that miRNA-associated “transitivity” (production of small interfering RNAs through antisense transcription) is more common than previously reported. High-resolution (3 nt) custom tiling microarray transcriptome analysis was performed with probes 400 bp 5′ upstream and 3′ downstream of the miRNA cleavage sites (direction relative to the mRNA) for 22 select miRNA target genes. We hybridized RNAs labeled from the smRNA pathway mutants, including hen1-1, dcl1-7, hyl1-2, rdr6-15, and sgs3-14. Results showed that antisense transcripts associated with miRNA targets were mainly elevated in hen1-1 and sgs3-14 to a lesser extent, and somewhat reduced in dcl11-7, hyl11-2, or rdr6-15 mutants. This was corroborated by semi-quantitative reverse transcription PCR; however, a direct correlation of antisense transcript abundance in MIR164 gene knockouts was not observed. Our overall analysis reveals a more widespread role for miRNA-associated transitivity with implications for functions of antisense transcription in gene regulation. HEN1 and SGS3 may be links for miRNA target entry into different RNA processing pathways