Polygenic overlap between schizophrenia risk and antipsychotic response: A genomic medicine approach

Douglas M. Ruderfer, Alexander W. Charney, Benjamin Readhead, Brian A. Kidd, Anna K. Kähler, Paul J. Kenny, Michael J. Keiser, Jennifer L. Moran, Christina M. Hultman, Stuart A. Scott, Patrick F. Sullivan, Shaun M. Purcell, Joel T. Dudley, Pamela Sklar

Research output: Contribution to journalArticle

41 Citations (Scopus)

Abstract

Background: Therapeutic treatments for schizophrenia do not alleviate symptoms for all patients and efficacy is limited by common, often severe, side-effects. Genetic studies of disease can identify novel drug targets, and drugs for which the mechanism has direct genetic support have increased likelihood of clinical success. Large-scale genetic studies of schizophrenia have increased the number of genes and gene sets associated with risk. We aimed to examine the overlap between schizophrenia risk loci and gene targets of a comprehensive set of medications to potentially inform and improve treatment of schizophrenia. Methods: We defined schizophrenia risk loci as genomic regions reaching genome-wide significance in the latest Psychiatric Genomics Consortium schizophrenia genome-wide association study (GWAS) of 36 989 cases and 113 075 controls and loss of function variants observed only once among 5079 individuals in an exome-sequencing study of 2536 schizophrenia cases and 2543 controls (Swedish Schizophrenia Study). Using two large and orthogonally created databases, we collated drug targets into 167 gene sets targeted by pharmacologically similar drugs and examined enrichment of schizophrenia risk loci in these sets. We further linked the exome-sequenced data with a national drug registry (the Swedish Prescribed Drug Register) to assess the contribution of rare variants to treatment response, using clozapine prescription as a proxy for treatment resistance. Findings: We combined results from testing rare and common variation and, after correction for multiple testing, two gene sets were associated with schizophrenia risk: agents against amoebiasis and other protozoal diseases (106 genes, p=0·00046, pcorrected =0·024) and antipsychotics (347 genes, p=0·00078, pcorrected=0·046). Further analysis pointed to antipsychotics as having independent enrichment after removing genes that overlapped these two target sets. We noted significant enrichment both in known targets of antipsychotics (70 genes, p=0·0078) and novel predicted targets (277 genes, p=0·019). Patients with treatment-resistant schizophrenia had an excess of rare disruptive variants in gene targets of antipsychotics (347 genes, p=0·0067) and in genes with evidence for a role in antipsychotic efficacy (91 genes, p=0·0029). Interpretation: Our results support genetic overlap between schizophrenia pathogenesis and antipsychotic mechanism of action. This finding is consistent with treatment efficacy being polygenic and suggests that single-target therapeutics might be insufficient. We provide evidence of a role for rare functional variants in antipsychotic treatment response, pointing to a subset of patients where their genetic information could inform treatment. Finally, we present a novel framework for identifying treatments from genetic data and improving our understanding of therapeutic mechanism. Funding: US National Institutes of Health.

Original languageEnglish (US)
Pages (from-to)350-357
Number of pages8
JournalThe Lancet Psychiatry
Volume3
Issue number4
DOIs
StatePublished - Apr 1 2016
Externally publishedYes

Fingerprint

Antipsychotic Agents
Schizophrenia
Medicine
Genes
Therapeutics
Exome
Pharmaceutical Preparations
Pharmaceutical Databases
Amebiasis
Inborn Genetic Diseases
Clozapine
Genome-Wide Association Study
National Institutes of Health (U.S.)
Proxy
Genomics
Prescriptions
Psychiatry
Registries
Genome

ASJC Scopus subject areas

  • Psychiatry and Mental health
  • Biological Psychiatry

Cite this

Polygenic overlap between schizophrenia risk and antipsychotic response : A genomic medicine approach. / Ruderfer, Douglas M.; Charney, Alexander W.; Readhead, Benjamin; Kidd, Brian A.; Kähler, Anna K.; Kenny, Paul J.; Keiser, Michael J.; Moran, Jennifer L.; Hultman, Christina M.; Scott, Stuart A.; Sullivan, Patrick F.; Purcell, Shaun M.; Dudley, Joel T.; Sklar, Pamela.

In: The Lancet Psychiatry, Vol. 3, No. 4, 01.04.2016, p. 350-357.

Research output: Contribution to journalArticle

Ruderfer, DM, Charney, AW, Readhead, B, Kidd, BA, Kähler, AK, Kenny, PJ, Keiser, MJ, Moran, JL, Hultman, CM, Scott, SA, Sullivan, PF, Purcell, SM, Dudley, JT & Sklar, P 2016, 'Polygenic overlap between schizophrenia risk and antipsychotic response: A genomic medicine approach', The Lancet Psychiatry, vol. 3, no. 4, pp. 350-357. https://doi.org/10.1016/S2215-0366(15)00553-2
Ruderfer, Douglas M. ; Charney, Alexander W. ; Readhead, Benjamin ; Kidd, Brian A. ; Kähler, Anna K. ; Kenny, Paul J. ; Keiser, Michael J. ; Moran, Jennifer L. ; Hultman, Christina M. ; Scott, Stuart A. ; Sullivan, Patrick F. ; Purcell, Shaun M. ; Dudley, Joel T. ; Sklar, Pamela. / Polygenic overlap between schizophrenia risk and antipsychotic response : A genomic medicine approach. In: The Lancet Psychiatry. 2016 ; Vol. 3, No. 4. pp. 350-357.
@article{effb168b3295429588e52c22580735ab,
title = "Polygenic overlap between schizophrenia risk and antipsychotic response: A genomic medicine approach",
abstract = "Background: Therapeutic treatments for schizophrenia do not alleviate symptoms for all patients and efficacy is limited by common, often severe, side-effects. Genetic studies of disease can identify novel drug targets, and drugs for which the mechanism has direct genetic support have increased likelihood of clinical success. Large-scale genetic studies of schizophrenia have increased the number of genes and gene sets associated with risk. We aimed to examine the overlap between schizophrenia risk loci and gene targets of a comprehensive set of medications to potentially inform and improve treatment of schizophrenia. Methods: We defined schizophrenia risk loci as genomic regions reaching genome-wide significance in the latest Psychiatric Genomics Consortium schizophrenia genome-wide association study (GWAS) of 36 989 cases and 113 075 controls and loss of function variants observed only once among 5079 individuals in an exome-sequencing study of 2536 schizophrenia cases and 2543 controls (Swedish Schizophrenia Study). Using two large and orthogonally created databases, we collated drug targets into 167 gene sets targeted by pharmacologically similar drugs and examined enrichment of schizophrenia risk loci in these sets. We further linked the exome-sequenced data with a national drug registry (the Swedish Prescribed Drug Register) to assess the contribution of rare variants to treatment response, using clozapine prescription as a proxy for treatment resistance. Findings: We combined results from testing rare and common variation and, after correction for multiple testing, two gene sets were associated with schizophrenia risk: agents against amoebiasis and other protozoal diseases (106 genes, p=0·00046, pcorrected =0·024) and antipsychotics (347 genes, p=0·00078, pcorrected=0·046). Further analysis pointed to antipsychotics as having independent enrichment after removing genes that overlapped these two target sets. We noted significant enrichment both in known targets of antipsychotics (70 genes, p=0·0078) and novel predicted targets (277 genes, p=0·019). Patients with treatment-resistant schizophrenia had an excess of rare disruptive variants in gene targets of antipsychotics (347 genes, p=0·0067) and in genes with evidence for a role in antipsychotic efficacy (91 genes, p=0·0029). Interpretation: Our results support genetic overlap between schizophrenia pathogenesis and antipsychotic mechanism of action. This finding is consistent with treatment efficacy being polygenic and suggests that single-target therapeutics might be insufficient. We provide evidence of a role for rare functional variants in antipsychotic treatment response, pointing to a subset of patients where their genetic information could inform treatment. Finally, we present a novel framework for identifying treatments from genetic data and improving our understanding of therapeutic mechanism. Funding: US National Institutes of Health.",
author = "Ruderfer, {Douglas M.} and Charney, {Alexander W.} and Benjamin Readhead and Kidd, {Brian A.} and K{\"a}hler, {Anna K.} and Kenny, {Paul J.} and Keiser, {Michael J.} and Moran, {Jennifer L.} and Hultman, {Christina M.} and Scott, {Stuart A.} and Sullivan, {Patrick F.} and Purcell, {Shaun M.} and Dudley, {Joel T.} and Pamela Sklar",
year = "2016",
month = "4",
day = "1",
doi = "10.1016/S2215-0366(15)00553-2",
language = "English (US)",
volume = "3",
pages = "350--357",
journal = "The Lancet Psychiatry",
issn = "2215-0366",
publisher = "Elsevier Limited",
number = "4",

}

TY - JOUR

T1 - Polygenic overlap between schizophrenia risk and antipsychotic response

T2 - A genomic medicine approach

AU - Ruderfer, Douglas M.

AU - Charney, Alexander W.

AU - Readhead, Benjamin

AU - Kidd, Brian A.

AU - Kähler, Anna K.

AU - Kenny, Paul J.

AU - Keiser, Michael J.

AU - Moran, Jennifer L.

AU - Hultman, Christina M.

AU - Scott, Stuart A.

AU - Sullivan, Patrick F.

AU - Purcell, Shaun M.

AU - Dudley, Joel T.

AU - Sklar, Pamela

PY - 2016/4/1

Y1 - 2016/4/1

N2 - Background: Therapeutic treatments for schizophrenia do not alleviate symptoms for all patients and efficacy is limited by common, often severe, side-effects. Genetic studies of disease can identify novel drug targets, and drugs for which the mechanism has direct genetic support have increased likelihood of clinical success. Large-scale genetic studies of schizophrenia have increased the number of genes and gene sets associated with risk. We aimed to examine the overlap between schizophrenia risk loci and gene targets of a comprehensive set of medications to potentially inform and improve treatment of schizophrenia. Methods: We defined schizophrenia risk loci as genomic regions reaching genome-wide significance in the latest Psychiatric Genomics Consortium schizophrenia genome-wide association study (GWAS) of 36 989 cases and 113 075 controls and loss of function variants observed only once among 5079 individuals in an exome-sequencing study of 2536 schizophrenia cases and 2543 controls (Swedish Schizophrenia Study). Using two large and orthogonally created databases, we collated drug targets into 167 gene sets targeted by pharmacologically similar drugs and examined enrichment of schizophrenia risk loci in these sets. We further linked the exome-sequenced data with a national drug registry (the Swedish Prescribed Drug Register) to assess the contribution of rare variants to treatment response, using clozapine prescription as a proxy for treatment resistance. Findings: We combined results from testing rare and common variation and, after correction for multiple testing, two gene sets were associated with schizophrenia risk: agents against amoebiasis and other protozoal diseases (106 genes, p=0·00046, pcorrected =0·024) and antipsychotics (347 genes, p=0·00078, pcorrected=0·046). Further analysis pointed to antipsychotics as having independent enrichment after removing genes that overlapped these two target sets. We noted significant enrichment both in known targets of antipsychotics (70 genes, p=0·0078) and novel predicted targets (277 genes, p=0·019). Patients with treatment-resistant schizophrenia had an excess of rare disruptive variants in gene targets of antipsychotics (347 genes, p=0·0067) and in genes with evidence for a role in antipsychotic efficacy (91 genes, p=0·0029). Interpretation: Our results support genetic overlap between schizophrenia pathogenesis and antipsychotic mechanism of action. This finding is consistent with treatment efficacy being polygenic and suggests that single-target therapeutics might be insufficient. We provide evidence of a role for rare functional variants in antipsychotic treatment response, pointing to a subset of patients where their genetic information could inform treatment. Finally, we present a novel framework for identifying treatments from genetic data and improving our understanding of therapeutic mechanism. Funding: US National Institutes of Health.

AB - Background: Therapeutic treatments for schizophrenia do not alleviate symptoms for all patients and efficacy is limited by common, often severe, side-effects. Genetic studies of disease can identify novel drug targets, and drugs for which the mechanism has direct genetic support have increased likelihood of clinical success. Large-scale genetic studies of schizophrenia have increased the number of genes and gene sets associated with risk. We aimed to examine the overlap between schizophrenia risk loci and gene targets of a comprehensive set of medications to potentially inform and improve treatment of schizophrenia. Methods: We defined schizophrenia risk loci as genomic regions reaching genome-wide significance in the latest Psychiatric Genomics Consortium schizophrenia genome-wide association study (GWAS) of 36 989 cases and 113 075 controls and loss of function variants observed only once among 5079 individuals in an exome-sequencing study of 2536 schizophrenia cases and 2543 controls (Swedish Schizophrenia Study). Using two large and orthogonally created databases, we collated drug targets into 167 gene sets targeted by pharmacologically similar drugs and examined enrichment of schizophrenia risk loci in these sets. We further linked the exome-sequenced data with a national drug registry (the Swedish Prescribed Drug Register) to assess the contribution of rare variants to treatment response, using clozapine prescription as a proxy for treatment resistance. Findings: We combined results from testing rare and common variation and, after correction for multiple testing, two gene sets were associated with schizophrenia risk: agents against amoebiasis and other protozoal diseases (106 genes, p=0·00046, pcorrected =0·024) and antipsychotics (347 genes, p=0·00078, pcorrected=0·046). Further analysis pointed to antipsychotics as having independent enrichment after removing genes that overlapped these two target sets. We noted significant enrichment both in known targets of antipsychotics (70 genes, p=0·0078) and novel predicted targets (277 genes, p=0·019). Patients with treatment-resistant schizophrenia had an excess of rare disruptive variants in gene targets of antipsychotics (347 genes, p=0·0067) and in genes with evidence for a role in antipsychotic efficacy (91 genes, p=0·0029). Interpretation: Our results support genetic overlap between schizophrenia pathogenesis and antipsychotic mechanism of action. This finding is consistent with treatment efficacy being polygenic and suggests that single-target therapeutics might be insufficient. We provide evidence of a role for rare functional variants in antipsychotic treatment response, pointing to a subset of patients where their genetic information could inform treatment. Finally, we present a novel framework for identifying treatments from genetic data and improving our understanding of therapeutic mechanism. Funding: US National Institutes of Health.

UR - http://www.scopus.com/inward/record.url?scp=84962381476&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84962381476&partnerID=8YFLogxK

U2 - 10.1016/S2215-0366(15)00553-2

DO - 10.1016/S2215-0366(15)00553-2

M3 - Article

C2 - 26915512

AN - SCOPUS:84962381476

VL - 3

SP - 350

EP - 357

JO - The Lancet Psychiatry

JF - The Lancet Psychiatry

SN - 2215-0366

IS - 4

ER -