Table_1_A Weighted Gene Co-expression Network Analysis Reveals lncRNA Abnormalities in the Peripheral Blood Associated With Ultra-High-Risk for Psychosis.XLSX

Objective: The primary study aim was to identify long non-coding RNA (lncRNA) abnormalities associated with ultra-high-risk (UHR) for psychosis based on a weighted gene co-expression network analysis.Methods: UHR patients were screened by the structured interview for prodromal syndromes (SIPS). We performed a WGCNA analysis on lncRNA and mRNA microarray profiles generated from the peripheral blood samples in 14 treatment-seeking patients with UHR who never received psychiatric medication and 18 demographically matched typically developing controls. Gene Ontology (GO) analysis and canonical correlation analysis were then applied to reveal functions and correlation between lncRNAs and mRNAs.Results: The lncRNAs were organized into co-expressed modules by WGCNA, two modules of which were strongly associated with UHR. The mRNA networks were constructed and two disease-associated mRNA modules were identified. A functional enrichment analysis showed that mRNAs were highly enriched for immune regulation and inflammation. Moreover, a significant correlation between lncRNAs and mRNAs were verified by a canonical correlation analysis.Conclusion: We identified novel lncRNA modules related to UHR. These results contribute to our understanding of the molecular basis of UHR from the perspective of systems biology and provide a theoretical basis for early intervention in the assumed development of schizophrenia.

研究目标：本研究的主要目的是基于加权基因共表达网络分析，识别与精神分裂症超高风险（UHR）相关的长非编码RNA（lncRNA）异常。研究方法：通过结构化访谈对产前综合征（SIPS）进行超高风险患者筛选。我们对14名未接受过精神药物治疗的超高风险治疗寻求者以及18名人口统计学上匹配的正常发展对照者的外周血样本中的lncRNA和mRNA微阵列图谱进行了加权基因共表达网络分析（WGCNA）。随后，应用基因本体（GO）分析和典型相关分析以揭示lncRNA与mRNA之间的功能及相关性。研究结果：lncRNA通过WGCNA组织成共表达模块，其中两个模块与UHR高度相关。构建了mRNA网络，并确定了两个疾病相关mRNA模块。功能富集分析表明，mRNA在免疫调节和炎症方面高度富集。此外，通过典型相关分析验证了lncRNA与mRNA之间存在显著的相关性。研究结论：我们鉴定了与UHR相关的 novel lncRNA模块。这些结果从系统生物学的角度加深了我们对UHR分子基础的理解，并为早期干预假定的精神分裂症发展提供了理论依据。