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J Mol Neurosci. 2018 Jan;64(1):62-74. doi: 10.1007/s12031-017-1002-1. Epub 2017 Nov 21.

Genetic Variants Within Molecular Targets of Antipsychotic Treatment: Effects on Treatment Response, Schizophrenia Risk, and Psychopathological Features.

Author information

1
Department of Biomedical and Dental Sciences and Morphofunctional Images, Division of Medical Biotechnologies and Preventive Medicine, University of Messina, Messina, Italy.
2
Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.
3
Department of Psychiatry, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea.
4
Department of Psychiatry, Korea University, College of Medicine, Seoul, Republic of Korea.
5
Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA.
6
Global Medical Education, New York, NY, USA.
7
Academic Medicine Education Institute, Duke-NUS Medical School, Singapore, Singapore.
8
Department of Neuroscience, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy.
9
Center for Applied Biomedical Research (CRBA, St. Orsola University Hospital, Bologna, Italy.
10
Department of Psychiatry, The Catholic University of Korea College of Medicine, Seoul, Republic of Korea. pae@catholic.ac.kr.
11
Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA. pae@catholic.ac.kr.
12
Department of Psychiatry, Bucheon St. Mary's Hospital, The Catholic University of Korea College of Medicine, 2 Sosa-Dong, Wonmi-Gu, Bucheon, Kyeonggi-Do, 420-717, Republic of Korea. pae@catholic.ac.kr.
13
Cell Death Disease Research Center, College of Medicine, The Catholic University of Korea, Seoul, Korea. pae@catholic.ac.kr.

Abstract

Schizophrenia (SCZ) is a common and severe mental disorder. Genetic factors likely play a role in its pathophysiology as well as in treatment response. In the present study, we investigated the effects of several single nucleotide polymorphisms (SNPs) within 9 genes involved with antipsychotic (AP) mechanisms of action. Two independent samples were recruited. The Korean sample included 176 subjects diagnosed with SCZ and 326 healthy controls, while the Italian sample included 83 subjects and 194 controls. AP response as measured by the positive and negative syndrome scale (PANSS) was the primary outcome, while the secondary outcome was the SCZ risk. Exploratory analyses were performed on (1) symptom clusters response (as measured by PANSS subscales); (2) age of onset; (3) family history; and (4) suicide history. Associations evidenced in the primary analyses did not survive to the FDR correction. Concerning SCZ risk, we partially confirmed the associations among COMT and MAPK1 genetic variants and SCZ. Finally, our exploratory analysis suggested that CHRNA7 and HTR2A genes may modulate both positive and negative symptoms responses, while PLA2G4A and SIGMAR1 may modulate respectively positive and negative symptoms responses. Moreover, GSK3B, HTR2A, PLA2G4A, and S100B variants may determine an anticipation of SCZ age of onset. Our results did not support a primary role for the genes investigated in AP response as a whole. However, our exploratory findings suggested that these genes may be involved in symptom clusters response.

KEYWORDS:

Antipsychotics; Deep phenotyping; Genetics; Schizophrenia

PMID:
29164477
DOI:
10.1007/s12031-017-1002-1
[Indexed for MEDLINE]

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