"Omics" approaches applied to treatment response phenotype, particularly pharmacogenomics, might not only serve as predictive tools to guide treatment decision making, but also identify new molecular targets and pathways to expand the pharmacological armamentarium. This is crucial in psychiatry, where the pharmacological pipeline has lagged behind in the past decade, and it is even more important in the presence of treatment resistance, particularly in a severe and chronic mental illness such as schizophrenia.
Schizophrenia (SCZ) is a severe mental disorder with a prevalence of about 1% in the general population. Antipsychotics remain the mainstay for the treatment of core symptoms of SCZ. However, a substantial proportion of patients (20–30%) present little or no response to such drugs. This population of treatment resistant SCZ (TRS) patients shows persistent symptoms, longer duration of hospital admissions and higher treatment costs compared to patients responsive to antipsychotics. This makes the impact of TRS enormous. Indeed, TRS patients show more severe psychopathology, more impaired cognitive functioning, and poorer psychosocial adjustment, which result in worst community functioning, compared to non-TRS patients. The advent of “omics” technologies in the investigation of the molecular underpinnings of treatment response in schizophrenia might help decreasing the burden of TRS. This is particularly true for pharmacogenomics, which may not only guide a more accurate treatment decision making, but also be instrumental in identifying new molecular targets and pathways for drug development. Indeed, there is consensus that a specific genetic architecture underlies TRS. First, genome-wide based polygenic risk score analysis show that TRS patients, particularly those responsive to clozapine, show a higher genetic loading for SCZ compared to antipsychotic responsive subjects. Second, TRS patients have an excess of rare disruptive variants in gene targets of antipsychotics and in genes with evidence for a role in antipsychotic efficacy. These data suggest that pharmacogenomics might inform the identification of new molecular targets for TRS, particularly if, rather than limiting to the effects of single genes, entire molecular pathways are evaluated.
With the present Research Topic, we aim to gather a number of original research studied and reviews (particularly meta-analysis and opinion papers) on pharmacogenomics of TRS and on their implications for drug discovery pipeline. Specifically, manuscripts should not be limited to the potential predictive role of genetic determinants in TRS, but rather focus on the feasibility of studying these targets in the context of a polygenic and likely poly-pathway trait such as TRS to facilitate the drug discovery pipeline. Therefore, this should include studies on animal models, and on bioinformatic screening of large genetic datasets.
"Omics" approaches applied to treatment response phenotype, particularly pharmacogenomics, might not only serve as predictive tools to guide treatment decision making, but also identify new molecular targets and pathways to expand the pharmacological armamentarium. This is crucial in psychiatry, where the pharmacological pipeline has lagged behind in the past decade, and it is even more important in the presence of treatment resistance, particularly in a severe and chronic mental illness such as schizophrenia.
Schizophrenia (SCZ) is a severe mental disorder with a prevalence of about 1% in the general population. Antipsychotics remain the mainstay for the treatment of core symptoms of SCZ. However, a substantial proportion of patients (20–30%) present little or no response to such drugs. This population of treatment resistant SCZ (TRS) patients shows persistent symptoms, longer duration of hospital admissions and higher treatment costs compared to patients responsive to antipsychotics. This makes the impact of TRS enormous. Indeed, TRS patients show more severe psychopathology, more impaired cognitive functioning, and poorer psychosocial adjustment, which result in worst community functioning, compared to non-TRS patients. The advent of “omics” technologies in the investigation of the molecular underpinnings of treatment response in schizophrenia might help decreasing the burden of TRS. This is particularly true for pharmacogenomics, which may not only guide a more accurate treatment decision making, but also be instrumental in identifying new molecular targets and pathways for drug development. Indeed, there is consensus that a specific genetic architecture underlies TRS. First, genome-wide based polygenic risk score analysis show that TRS patients, particularly those responsive to clozapine, show a higher genetic loading for SCZ compared to antipsychotic responsive subjects. Second, TRS patients have an excess of rare disruptive variants in gene targets of antipsychotics and in genes with evidence for a role in antipsychotic efficacy. These data suggest that pharmacogenomics might inform the identification of new molecular targets for TRS, particularly if, rather than limiting to the effects of single genes, entire molecular pathways are evaluated.
With the present Research Topic, we aim to gather a number of original research studied and reviews (particularly meta-analysis and opinion papers) on pharmacogenomics of TRS and on their implications for drug discovery pipeline. Specifically, manuscripts should not be limited to the potential predictive role of genetic determinants in TRS, but rather focus on the feasibility of studying these targets in the context of a polygenic and likely poly-pathway trait such as TRS to facilitate the drug discovery pipeline. Therefore, this should include studies on animal models, and on bioinformatic screening of large genetic datasets.