| Title |
Hot Genes in Schizophrenia: How Clinical Datasets Could Help to Refine their Role
|
|---|---|
| Published in |
Journal of Molecular Neuroscience, December 2017
|
| DOI | 10.1007/s12031-017-1016-8 |
| Pubmed ID | |
| Authors |
Stefano Porcelli, Soo-Jung Lee, Changsu Han, Ashwin A. Patkar, Diego Albani, Tae-Youn Jun, Chi-Un Pae, Alessandro Serretti |
| Abstract |
We investigated the effect of a set of SNPs within 5 genes identified by GWASs as possible risk genes for schizophrenia (SCZ) in two independent samples, comprising 176 SCZ patients and 326 controls of Korean origin and 83 SCZ patients and 194 controls of Italian origin. The PANSS was used to assess psychopathology severity and antipsychotic response (AR). Several clinical features were assessed at recruitment. In the Korean sample, the SP4 gene haplotype rs2282888-rs2237304-rs10272006-rs12673091 (p = 0.02) was associated with SCZ. In the Italian sample, PPP3CC rs11780915 (genotypic: p = 0.006; allelic: p = 0.001) and rs2249098 (genotypic: p = 0.0004; allelic: p = 0.00006) were associated with SCZ, as well as the PPP3CC rs11780915-rs10108011-rs2249098 and the ZNF804A rs7603001-rs1344706 haplotypes (p = 0.03 and p = 0.02). Several RORA variants were associated with AR in both the samples, although only the haplotype rs1020729-rs1871858 in the Korean sample survived to the statistical correction (p = 0.01). Exploratory analyses suggested that: (1) PPP3CC, ST8SIA2, and SP4 genes may modulate psychotic symptoms, and (2) RORA and ZNF804A genes may influence AR. Our results partially support a role for these genes in SCZ and AR. Analyses in well phenotyped samples may help to refine the role of the genes identified by GWASs. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
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| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 3 | 13% |
| Other | 2 | 9% |
| Student > Bachelor | 2 | 9% |
| Student > Doctoral Student | 1 | 4% |
| Lecturer > Senior Lecturer | 1 | 4% |
| Other | 4 | 17% |
| Unknown | 10 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 17% |
| Medicine and Dentistry | 2 | 9% |
| Veterinary Science and Veterinary Medicine | 1 | 4% |
| Psychology | 1 | 4% |
| Agricultural and Biological Sciences | 1 | 4% |
| Other | 2 | 9% |
| Unknown | 12 | 52% |
Attention Score in Context
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