Prefrontal Coexpression of Schizophrenia Risk Genes Is Associated With Treatment Response in Patients

Giulio Pergola, Pasquale Di Carlo, Andrew Jaffe, Marco Papalino, Qiang Chen, Thomas Hyde, Joel Kleinman, Joo Heon Shin, Antonio Rampino, Giuseppe Blasi, Daniel Weinberger, Alessandro Bertolino

Research output: Contribution to journalArticle

Abstract

Background: Gene coexpression networks are relevant to functional and clinical translation of schizophrenia risk genes. We hypothesized that schizophrenia risk genes converge into coexpression pathways that may be associated with gene regulation mechanisms and with response to treatment in patients with schizophrenia. Methods: We identified gene coexpression networks in two prefrontal cortex postmortem RNA sequencing datasets (n = 688) and replicated them in four more datasets (n = 1295). We identified and replicated (p values < .001) a single module enriched for schizophrenia risk loci (13 risk genes in 10 loci). In silico screening of potential regulators of the schizophrenia risk module via bioinformatic analyses identified two transcription factors and three microRNAs associated with the risk module. To translate postmortem information into clinical phenotypes, we identified polymorphisms predicting coexpression and combined them to obtain an index approximating module coexpression (Polygenic Coexpression Index [PCI]). Results: The PCI-coexpression association was successfully replicated in two independent brain transcriptome datasets (n = 131; p values < .05). Finally, we tested the association between the PCI and short-term treatment response in two independent samples of patients with schizophrenia treated with olanzapine (n = 167). The PCI was associated with treatment response in the positive symptom domain in both clinical cohorts (p values < .05). Conclusions: In summary, our findings in 1983 samples of human postmortem prefrontal cortex show that coexpression of a set of genes enriched for schizophrenia risk genes is relevant to treatment response. This coexpression pathway may be coregulated by transcription factors and microRNA associated with it.

Original languageEnglish (US)
JournalBiological psychiatry
DOIs
StatePublished - Jan 1 2019

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Schizophrenia
Genes
Gene Regulatory Networks
olanzapine
Prefrontal Cortex
MicroRNAs
Therapeutics
Transcription Factors
RNA Sequence Analysis
Computational Biology
Transcriptome
Computer Simulation
Phenotype
Brain
Datasets

Keywords

  • Dorsolateral prefrontal cortex
  • Gene coexpression networks
  • Olanzapine
  • RNA sequencing
  • Schizophrenia

ASJC Scopus subject areas

  • Biological Psychiatry

Cite this

Prefrontal Coexpression of Schizophrenia Risk Genes Is Associated With Treatment Response in Patients. / Pergola, Giulio; Di Carlo, Pasquale; Jaffe, Andrew; Papalino, Marco; Chen, Qiang; Hyde, Thomas; Kleinman, Joel; Shin, Joo Heon; Rampino, Antonio; Blasi, Giuseppe; Weinberger, Daniel; Bertolino, Alessandro.

In: Biological psychiatry, 01.01.2019.

Research output: Contribution to journalArticle

Pergola, Giulio ; Di Carlo, Pasquale ; Jaffe, Andrew ; Papalino, Marco ; Chen, Qiang ; Hyde, Thomas ; Kleinman, Joel ; Shin, Joo Heon ; Rampino, Antonio ; Blasi, Giuseppe ; Weinberger, Daniel ; Bertolino, Alessandro. / Prefrontal Coexpression of Schizophrenia Risk Genes Is Associated With Treatment Response in Patients. In: Biological psychiatry. 2019.
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abstract = "Background: Gene coexpression networks are relevant to functional and clinical translation of schizophrenia risk genes. We hypothesized that schizophrenia risk genes converge into coexpression pathways that may be associated with gene regulation mechanisms and with response to treatment in patients with schizophrenia. Methods: We identified gene coexpression networks in two prefrontal cortex postmortem RNA sequencing datasets (n = 688) and replicated them in four more datasets (n = 1295). We identified and replicated (p values < .001) a single module enriched for schizophrenia risk loci (13 risk genes in 10 loci). In silico screening of potential regulators of the schizophrenia risk module via bioinformatic analyses identified two transcription factors and three microRNAs associated with the risk module. To translate postmortem information into clinical phenotypes, we identified polymorphisms predicting coexpression and combined them to obtain an index approximating module coexpression (Polygenic Coexpression Index [PCI]). Results: The PCI-coexpression association was successfully replicated in two independent brain transcriptome datasets (n = 131; p values < .05). Finally, we tested the association between the PCI and short-term treatment response in two independent samples of patients with schizophrenia treated with olanzapine (n = 167). The PCI was associated with treatment response in the positive symptom domain in both clinical cohorts (p values < .05). Conclusions: In summary, our findings in 1983 samples of human postmortem prefrontal cortex show that coexpression of a set of genes enriched for schizophrenia risk genes is relevant to treatment response. This coexpression pathway may be coregulated by transcription factors and microRNA associated with it.",
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AU - Di Carlo, Pasquale

AU - Jaffe, Andrew

AU - Papalino, Marco

AU - Chen, Qiang

AU - Hyde, Thomas

AU - Kleinman, Joel

AU - Shin, Joo Heon

AU - Rampino, Antonio

AU - Blasi, Giuseppe

AU - Weinberger, Daniel

AU - Bertolino, Alessandro

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N2 - Background: Gene coexpression networks are relevant to functional and clinical translation of schizophrenia risk genes. We hypothesized that schizophrenia risk genes converge into coexpression pathways that may be associated with gene regulation mechanisms and with response to treatment in patients with schizophrenia. Methods: We identified gene coexpression networks in two prefrontal cortex postmortem RNA sequencing datasets (n = 688) and replicated them in four more datasets (n = 1295). We identified and replicated (p values < .001) a single module enriched for schizophrenia risk loci (13 risk genes in 10 loci). In silico screening of potential regulators of the schizophrenia risk module via bioinformatic analyses identified two transcription factors and three microRNAs associated with the risk module. To translate postmortem information into clinical phenotypes, we identified polymorphisms predicting coexpression and combined them to obtain an index approximating module coexpression (Polygenic Coexpression Index [PCI]). Results: The PCI-coexpression association was successfully replicated in two independent brain transcriptome datasets (n = 131; p values < .05). Finally, we tested the association between the PCI and short-term treatment response in two independent samples of patients with schizophrenia treated with olanzapine (n = 167). The PCI was associated with treatment response in the positive symptom domain in both clinical cohorts (p values < .05). Conclusions: In summary, our findings in 1983 samples of human postmortem prefrontal cortex show that coexpression of a set of genes enriched for schizophrenia risk genes is relevant to treatment response. This coexpression pathway may be coregulated by transcription factors and microRNA associated with it.

AB - Background: Gene coexpression networks are relevant to functional and clinical translation of schizophrenia risk genes. We hypothesized that schizophrenia risk genes converge into coexpression pathways that may be associated with gene regulation mechanisms and with response to treatment in patients with schizophrenia. Methods: We identified gene coexpression networks in two prefrontal cortex postmortem RNA sequencing datasets (n = 688) and replicated them in four more datasets (n = 1295). We identified and replicated (p values < .001) a single module enriched for schizophrenia risk loci (13 risk genes in 10 loci). In silico screening of potential regulators of the schizophrenia risk module via bioinformatic analyses identified two transcription factors and three microRNAs associated with the risk module. To translate postmortem information into clinical phenotypes, we identified polymorphisms predicting coexpression and combined them to obtain an index approximating module coexpression (Polygenic Coexpression Index [PCI]). Results: The PCI-coexpression association was successfully replicated in two independent brain transcriptome datasets (n = 131; p values < .05). Finally, we tested the association between the PCI and short-term treatment response in two independent samples of patients with schizophrenia treated with olanzapine (n = 167). The PCI was associated with treatment response in the positive symptom domain in both clinical cohorts (p values < .05). Conclusions: In summary, our findings in 1983 samples of human postmortem prefrontal cortex show that coexpression of a set of genes enriched for schizophrenia risk genes is relevant to treatment response. This coexpression pathway may be coregulated by transcription factors and microRNA associated with it.

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