Future of individualized psychiatric treatment
2008; Future Medicine; Volume: 9; Issue: 5 Linguagem: Inglês
10.2217/14622416.9.5.493
ISSN1744-8042
AutoresJerry L. Campbell, Pat Levitt,
Tópico(s)Schizophrenia research and treatment
ResumoPharmacogenomicsVol. 9, No. 5 EditorialFree AccessFuture of individualized psychiatric treatmentDaniel B Campbell & Pat LevittDaniel B Campbell† Author for correspondenceVanderbilt University, Department of Pharmacology and Vanderbilt Kennedy Center for Research on Human Development, 8114 MRB3, 465 21st Avenue South, Nashville, TN 37232, USA. & Pat LevittVanderbilt University, Department of Pharmacology and Vanderbilt Kennedy Center for Research on Human Development, PO Box 40 Peabody, 230 Appleton Place, Nashville, TN 37203, USA. Published Online:9 May 2008https://doi.org/10.2217/14622416.9.5.493AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinkedInReddit Antipsychotic medications are the preferred treatment for schizophrenia. Given that there are differences in individual responses to different antipsychotic medications, a significant challenge to enhancing treatment is to move beyond trial-and-error approaches to more individualized care that maximizes treatment success. The era of the human genome provides new hope for patients through the application of pharmacogenomics [1,2], the use of sequence variation in schizophrenia risk genes that may more accurately predict response to treatment.We recently published an exploratory pharmacogenomics study reporting that variants of the gene encoding regulator of G-protein signaling 4 (RGS4) predict antipsychotic treatment response in schizophrenia [3]. RGS4 had been identified by ourselves and others as a candidate risk gene for schizophrenia [4,5]. We genotyped eight RGS4 gene SNPs in individuals with schizophrenia from the Clinical Antipsychotics Trials of Intervention Effectiveness (CATIE), which included DNA that was available from 198 individuals of inferred African ancestry and 397 individuals of inferred European ancestry. Ethnic stratification was performed, as the allele frequencies of the RGS4 genetic variants differed between the two groups. Two RGS4 SNPs, rs951439 and rs2842030, were associated with differential antipsychotic treatment response in individuals of inferred African ancestry. Individuals of African descent and RGS4 rs951439 genotype CC responded significantly better to perphenazine treatment compared with ziprasidone treatment. These individuals continued on perphenazine treatment three-times longer (391 vs 124 days) and had a 21% improvement during perphenazine treatment on the Positive and Negative Symptoms Scale (PANSS) total score compared with a 5% worsening of symptoms on ziprasidone. Similarly, individuals of African descent and RGS4 rs2842030 genotype TT responded significantly better to perphenazine treatment (24% improvement in PANSS symptoms) than treatment by quetiapine, risperidone or ziprasidone (5% worsening of PANSS symptoms). Among individuals of European descent, risperidone treatment was more effective in those with rs951439 genotype TT compared with those with genotype CC. Similarly, individuals of European descent and rs2842030 genotype GG responded better to risperidone treatment than those of genotype TT [3]. An independent study of Chinese individuals with schizophrenia found that RGS4 SNP rs2661319, which lies between rs951439 and rs2842030 on chromosome 1, predicts differential response to risperidone [6]. Thus, two independent reports provide evidence that RGS4 variants can be used to predict the effectiveness of antipsychotic treatment response in three different ethnic groups.RGS4 has been of particular interest biologically, as the protein regulates the activity of the same G-protein-coupled receptors (GPCRs) that are targeted by antipsychotic drugs, including those receptors activated by dopamine, acetylcholine and serotonin. RGS4 is part of a large family of regulators of G-protein signaling, all of which act by shortening the duration of neurotransmitter signaling through GPCRs. We recently tested a hypothesis regarding the specificity of RGS4 in predicting antipsychotic treatment response by genotyping 59 SNPs spanning the RGS2, RGS5, RGS8 and RGS16 genes in the CATIE sample. Each of these GPCR-regulating genes lies near the RGS4 gene on chromosome 1 and is expressed in brain regions implicated in schizophrenia. The results of the genetic studies indicate that only RGS4 variants correlate with antipsychotic treatment response [7]. The biological basis of the specificity of RGS4 is being investigated currently.The two reports of RGS4 genotype predicting antipsychotic treatment response add to a substantial body of evidence implicating RGS4 in schizophrenia. The initial focus on RGS4 came from our laboratory's gene microarray and in situ hybridization studies, which demonstrated decreased expression levels of RGS4 transcript across cortical regions [8]. Decreased levels of RGS4 protein were subsequently demonstrated in the frontal cortex [9]. Genetic association of RGS4 variants with schizophrenia diagnosis was originally described in three small, independent family-based samples [10]. Like all risk genes for schizophrenia to date, there is both replication and nonreplication of genetic association that may be due to a number of factors, including disease heterogeneity [5]. However, a recent meta-analysis of more than 13,000 samples demonstrated support for genetic association of RGS4 with schizophrenia in the context of etiological heterogeneity [11]. There are also biological indicators that RGS4 is an important risk factor in schizophrenia. RGS4 genotype is associated with reduced volume of the dorsolateral prefrontal cortex in first-episode patients with schizophrenia and in healthy controls [12], and with functional activity and connectivity during working memory tasks [13]. Finally, recent independent studies, in European ancestry and Chinese samples, also indicated association of RGS4 genotypes with baseline schizophrenia symptom severity as measured by the PANSS total score [3,14].As RGS4 may be critical to both etiology and predicting treatment effectiveness in schizophrenia, one priority should be to determine the function of the genetically associated variants. Two reports have begun to address the function of RGS4 variants. Chowdari et al.[15] used transcription assays to identify a 311-bp enhancer region and two larger (∼2-kb) regions containing strong transcriptional repressor elements. Ding et al.[16] identified five splice variants of RGS4 that use three different transcription start sites. Each of the splice variants is expressed in the human cerebral cortex, and higher levels of each transcript are observed in the prefrontal cortex compared with the visual cortex [16]. Future experiments should focus on determining whether the genetic variants associated with schizophrenia and antipsychotic treatment response specifically influence RGS4 transcript isoform expression.RGS4 is one of a small group of promising schizophrenia susceptibility genes [4,5]. Ongoing genome-wide association studies will likely identify additional genes involved in the etiology of schizophrenia [17,18]. It is likely that these genome-wide association studies will not immediately lead to new drug discovery for the treatment of schizophrenia, as identification of potential risk genes is just the first of many steps required to understand the neurobiological consequences of dysfunction of the candidate gene in schizophrenia. Furthermore, one conclusion drawn from the CATIE study is that second-generation antipsychotic drugs are not a dramatic improvement over the first-generation antipsychotics that have been available for over 50 years [19]. The treatment field need not wait passively for new drug discoveries. We suggest that a more immediate solution to improve patient care is to maximize current treatment effectiveness by using genetic information, perhaps by using a combination of variants of multiple risk genes, to enhance individual responsiveness to antipsychotic medication. Companies developing technologies for genetic diagnosis of mental illness [20] might also consider focusing their efforts to develop the type of individualized medicine strategy described here.We make one additional recommendation. All clinical trials of antipsychotic medications should include in the study design the collection of DNA from blood samples. The benefit:cost ratio for this design is extremely high. With reference to our study, not all individuals in the original CATIE study had their DNA collected, which resulted in a smaller than optimal sample size and thus a more challenging design of our exploratory analysis. However, the collection of DNA samples from another seemingly underpowered sample of only 120 patients has provided new insight into the ability of genetic variants to predict the efficacy of the antipsychotic medication risperidone. The results of these genetic analyses indicate that risperidone treatment efficacy is predicted by genetic variants in dopamine receptors [21,22], serotonin receptors [23] and, most recently, RGS4 [6]. A more comprehensive genetic analysis of risperidone treatment success may indicate other important genetic indicators or combinations of genetic predictors.Finally, all clinical trials should, like CATIE, include substantial representation of hitherto under-represented ethnic groups. 'Population stratification' is generally considered to be undesirable in genetic association studies, as the requirement to stratify typically reduces the power to detect significant genetic differences. However, our exploratory study illustrates that, given sufficient power in each stratum, population stratification should be encouraged. As noted above, we found that the allele frequencies of the RGS4 SNPs differed markedly between individuals of European descent and individuals of African descent. In the absence of a known functional variant, we have to assume that the same alleles mark different inheritance patterns of a functional variant in RGS4 in the two strata. A new focus on these differences across ethnic groups can lead to better treatment access for those individuals typically underserved by the medical community, and implementation of more successful treatment strategies for all who use antipsychotic medications for the treatment of schizophrenia.Financial & competing interests disclosureOne of the authors holds a patent related to RGS4 (PL), but neither author has current financial interests to report. We wish to acknowledge the endowment of the Annette Schaffer Eskind Chair (PL) and project 4 of the Pittsburgh Conte Center grant MH045156 (D Lewis, PI) for partially supporting the work reported here. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.Bibliography1 Reynolds GP: The impact of pharmacogenetics on the development and use of antipsychotic drugs. Drug Discov. Today12,953–959 (2007).Crossref, Medline, CAS, Google Scholar2 Arranz MJ, de Leon J: Pharmacogenetics and pharmacogenomics of schizophrenia: a review of last decade of research. Mol. Psychiatry12,707–747 (2007).Crossref, Medline, CAS, Google Scholar3 Campbell DB, Ebert PJ, Skelly T et al.: Ethnic stratification of the association of RGS4 variants with antipsychotic treatment response in schizophrenia. Biol. Psychiatry63,32–41 (2008).Crossref, Medline, CAS, Google Scholar4 Levitt P, Ebert P, Mirnics K, Nimgaonkar VL, Lewis DA: Making the case for a candidate vulnerability gene in schizophrenia: convergent evidence for regulator of G-protein signaling 4 (RGS4). Biol. Psychiatry60,534–537 (2006).Crossref, Medline, CAS, Google Scholar5 Sullivan PF: The genetics of schizophrenia. PLoS Med. 2,E212 (2005).Crossref, Medline, Google Scholar6 Lane HY, Liu YC, Huang CL et al.: RGS4 polymorphisms predict clinical manifestations and responses to risperidone treatment in patients with schizophrenia. J. Clin. Psychopharmacol.28,64–68 (2008).Crossref, Medline, CAS, Google Scholar7 Campbell DB, Lange LA, Skelly T, Lieberman J, Levitt P, Sullivan PF: Association of RGS2 and RGS5 variants with schizophrenia symptom severity. Schizophr. Res. (2008) (Epub ahead of print).Google Scholar8 Mirnics K, Middleton FA, Stanwood GD, Lewis DA, Levitt P: Disease-specific changes in regulator of G-protein signaling 4 (RGS4) expression in schizophrenia. Mol. Psychiatry6,293–301 (2001).Crossref, Medline, CAS, Google Scholar9 Erdely HA, Tamminga CA, Roberts RC, Vogel MW: Regional alterations in RGS4 protein in schizophrenia. Synapse59,472–479 (2006).Crossref, Medline, CAS, Google Scholar10 Chowdari KV, Mirnics K, Semwal P et al.: Association and linkage analyses of RGS4 polymorphisms in schizophrenia. Hum. Mol. Genet.11,1373–1380 (2002).Crossref, Medline, CAS, Google Scholar11 Talkowski ME, Seltman H, Bassett AS et al.: Evaluation of a susceptibility gene for schizophrenia: genotype based meta-analysis of RGS4 polymorphisms from thirteen independent samples. Biol. Psychiatry60(2),152–162 (2006).Crossref, Medline, CAS, Google Scholar12 Prasad KM, Chowdari KV, Nimgaonkar VL, Talkowski ME, Lewis DA, Keshavan MS: Genetic polymorphisms of the RGS4 and dorsolateral prefrontal cortex morphometry among first episode schizophrenia patients. Mol. Psychiatry10,213–219 (2005).Crossref, Medline, CAS, Google Scholar13 Buckholtz JW, Meyer-Lindenberg A, Honea RA et al.: Allelic variation in RGS4 impacts functional and structural connectivity in the human brain. J. Neurosci.27,1584–1593 (2007).Crossref, Medline, CAS, Google Scholar14 So HC, Chen RY, Chen EY, Cheung EF, Li T, Sham PC: An association study of RGS4 polymorphisms with clinical phenotypes of schizophrenia in a Chinese population. Am. J. Med. Genet. B Neuropsychiatr. Genet.147,77–85 (2008).Crossref, Google Scholar15 Chowdari KV, Bamne M, Wood J et al.: Linkage disequilibrium patterns and functional analysis of RGS4 polymorphisms in relation to schizophrenia. Schizophr. Bull.34,118–126 (2008).Crossref, Medline, Google Scholar16 Ding L, Mychaleckyj JC, Hegde AN: Full length cloning and expression analysis of splice variants of regulator of G-protein signaling RGS4 in human and murine brain. Gene401,46–60 (2007).Crossref, Medline, CAS, Google Scholar17 Sullivan PF: Schizophrenia genetics: the search for a hard lead. Curr. Opin. Psychiatry21,157–160 (2008).Crossref, Medline, Google Scholar18 Sullivan PF, Lin D, Tzeng JY et al.: Genomewide association for schizophrenia in the study CATIE: results of stage 1. Mol. Psychiatry (2008) (Epub ahead of print).Google Scholar19 Lewis S, Lieberman J: CATIE and CUtLASS: can we handle the truth? Br. J. Psychiatry192,161–163 (2008).Crossref, Medline, Google Scholar20 Couzin J: Science and commerce. Gene tests for psychiatric risk polarize researchers. Science319,274–277 (2008).Crossref, Medline, CAS, Google Scholar21 Lane HY, Lee CC, Chang YC, Lu CT, Huang CH, Chang WH: Effects of dopamine D2 receptor Ser311Cys polymorphism and clinical factors on risperidone efficacy for positive and negative symptoms and social function. Int. J. Neuropsychopharmacol.7,461–470 (2004).Crossref, Medline, CAS, Google Scholar22 Lane HY, Hsu SK, Liu YC, Chang YC, Huang CH, Chang WH: Dopamine D3 receptor Ser9Gly polymorphism and risperidone response. J. Clin. Psychopharmacol.25,6–11 (2005).Crossref, Medline, CAS, Google Scholar23 Lane HY, Chang YC, Chiu CC, Chen ML, Hsieh MH, Chang WH: Association of risperidone treatment response with a polymorphism in the 5-HT(2A) receptor gene. Am. J. Psychiatry159,1593–1595 (2002).Crossref, Medline, Google ScholarFiguresReferencesRelatedDetailsCited ByDrug–drug interactions involving combinations of antipsychotic agents with antidiabetic, lipid-lowering, and weight loss drugs22 November 2022 | Expert Opinion on Drug Metabolism & Toxicology, Vol. 26Tying comparative effectiveness information to decision-making and the future of comparative effectiveness research designs: the case for antipsychotic drugsAnirban Basu & Herbert Y Meltzer5 March 2012 | Journal of Comparative Effectiveness Research, Vol. 1, No. 2 Vol. 9, No. 5 Follow us on social media for the latest updates Metrics History Published online 9 May 2008 Published in print May 2008 Information© Future Medicine LtdFinancial & competing interests disclosureOne of the authors holds a patent related to RGS4 (PL), but neither author has current financial interests to report. We wish to acknowledge the endowment of the Annette Schaffer Eskind Chair (PL) and project 4 of the Pittsburgh Conte Center grant MH045156 (D Lewis, PI) for partially supporting the work reported here. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.No writing assistance was utilized in the production of this manuscript.PDF download
Referência(s)