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http://ir.nhri.org.tw/handle/3990099045/16403
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| 題名: | Identification of hub genes involved in early-onset schizophrenia using genetically predicted regulated gene-expression risk score for schizophrenia |
| 作者: | Jen, YW;Yu, SL;Hsiao, PC;Liu, CM;Liu, CC;Hwang, TJ;Hsieh, MH;Huang, HL;Chandler, SD;Faraone, S;Neale, B;McCarroll, S;Tsuang, MT;Hwu, HG;Chen, WJ |
| 貢獻者: | Center for Neuropsychiatric Research |
| 摘要: | Background: Genome-wide association studies (GWAS) have unveiled the polygenic architecture of schizophrenia (SZ). Early-onset SZ (EOS), a more homogeneous SZ subtype, may aid in dissecting the genetic etiology of SZ and further understanding its genetic architecture. Gene-expression imputation enabled the translation of GWAS results into regulatory mechanisms and made it possible to construct genetically regulated gene-expression risk scores for SZ (SZ-GeRS). We utilized a rich collection of SZ patients with varying familial loadings and applied the GeRS approach to assess the association between SZ-GeRS and EOS. This study aims to (1) assess SZ-GeRS utility in distinguishing EOS from late-onset SZ (LOS), (2) determine if SZ-GeRS adds additional value over SZ-PRS in differentiating EOS from LOS, and (3) identify potential hub genes linked to EOS. Methods: Participants in this study included 595 SZ patients from 314 multiplex families and 595 sex- and onset age-matched SZ patients from simplex families. Initially, genetically regulated gene expressions were predicted by integrating GWAS-based genotype data in our samples with an existing SNP-expression prediction model of DLPFC brain tissue. SZ-GeRS was then calculated for each gene by weighting its genetically predicted expression with the corresponding effect size of transcriptome-wide association studies of SZ. Additionally, module-based SZ-GeRS was calculated by summing SZ-GeRS for each gene within psychiatric disorder-related modules from a previous study. Associations between each module-based SZ-GeRS and EOS were assessed by mixed-effects logistic regression model, with significant modules validated by another independent sample. Hub genes within the EOS-related module were identified through network analysis using Ingenuity Pathway Analysis software, exploring their biological functions. Finally, the effectiveness of two types of module-based SZ-GeRS, i.e., SZ-GeRS based on all genes and hub genes in EOS-related module, and SZ-PRS in distinguishing EOS from LOS was compared in samples with different familial loading. Results: Among 595 SZ patients, 223 were EOS and the remaining 372 were LOS. We found one module-based SZ-GeRS, i.e., module 10 (M10-GeRS), was associated with EOS in both discovery and replication samples. Subjecting genes in module 10 to IPA network analysis, six hub genes were identified, which include RUVBL2, COPS6, TUBA4A, PSMB5, PSMB2, and LRPPRC. The module-based SZ-GeRS based on these hub genes, dubbed as M10hub-GeRS, remained the direction of effect on EOS in both samples. Furthermore, both M10-GeRS and M10hub-GeRS explained more variance than the conventional SZ-PRS in both discovery and replication samples, accounting for additional variance in EOS (2.5% and 0.7 %, respectively). Discussion: Our results suggest incorporating SZ-GeRS into SZ-PRS enhances the ability to distinguish EOS from LOS. Also, we identified hub genes for EOS that have been reported to be related to neurological diseases in previous studies, potentially serving as 'mixed genes' for SZ, influencing susceptibility and early-onset status. Understanding genetically regulated gene expression in EOS will enrich potential pathway research, enhancing psychiatric classification in personalized medicine. Our study reveals the value of integrating large genetic study results with a rich collection of SZ patients with different familial loading to explore the biological functions of EOS and identify hub genes. |
| 日期: | 2024-10 |
| 關聯: | European Neuropsychopharmacology. 2024 Oct;87(Suppl. 1):64-65. |
| Link to: | http://dx.doi.org/10.1016/j.euroneuro.2024.08.144 |
| JIF/Ranking 2023: | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=&DestApp=IC2JCR |
| Cited Times(WOS): | https://www.webofscience.com/wos/woscc/full-record/WOS:001336799000117 |
| 顯示於類別: | [陳為堅] 會議論文/會議摘要
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