{"title":"阐明与情绪障碍病因基因变异有关的分子过程和生物标志物","authors":"Hai Duc Nguyen , Giang Huong Vu , Woong-Ki Kim","doi":"10.1016/j.pmip.2024.100128","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><p>We aimed to identify the significant genetic variations and molecular mechanisms associated with the pathogenesis of mood disorders associated with genetic variants.</p></div><div><h3>Methods</h3><p>Genome-wide association studies (GWAS, ID: EFO_0003761), ClueGO plug-in, and GEO database were the main approaches.</p></div><div><h3>Results</h3><p>Ten biomarkers that are frequently related to mood disorders were identified across all studies. In terms of mood disorders, a collection of biomarkers has been found, with specific attention given to seven fundamental genetic variations. A comprehensive analysis revealed a total of five central biomarkers that exhibited a significant association with unipolar depression, with an additional five central biomarkers that demonstrated a significant association with mixed traits. Biomarkers that have been linked to an increased vulnerability to mood disorders have been found to disrupt many cellular processes in neuronal development, including cell morphogenesis, cell projection organization, and cell adhesion. The main signaling pathways associated with biomarkers that contribute to a reduced susceptibility to mood disorders encompass the activation of neuro projection morphogenesis, O-linked glycosylation, modulation of chemical synaptic transmission, and G-protein-coupled glutamate receptor activity. hsa-miR-3937, hsa-miR-4499, and hsa-miR-7106-5p exhibited the most significant downregulation in the GSE182194 dataset. A microRNA (hsa-miR-26b-5p) and transcription factors (zinc finger proteins) were found to have a pivotal role in the elucidation of genetic variations linked to mood disorders across different datasets (EFO_0003761, GSE101521, and GSE217811).</p></div><div><h3>Conclusions</h3><p>Our findings provide a foundational framework for prospective therapeutic approaches aimed at addressing mood disorders, specifically focusing on the genetic variants and pathways linked to this condition.</p></div>","PeriodicalId":19837,"journal":{"name":"Personalized Medicine in Psychiatry","volume":"45 ","pages":"Article 100128"},"PeriodicalIF":0.0000,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2468171724000140/pdfft?md5=923a3140905b2bc33887a321137d1e24&pid=1-s2.0-S2468171724000140-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Elucidation of molecular processes and biomarkers linked to the genetic variations driving the etiology of mood disorders\",\"authors\":\"Hai Duc Nguyen , Giang Huong Vu , Woong-Ki Kim\",\"doi\":\"10.1016/j.pmip.2024.100128\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objectives</h3><p>We aimed to identify the significant genetic variations and molecular mechanisms associated with the pathogenesis of mood disorders associated with genetic variants.</p></div><div><h3>Methods</h3><p>Genome-wide association studies (GWAS, ID: EFO_0003761), ClueGO plug-in, and GEO database were the main approaches.</p></div><div><h3>Results</h3><p>Ten biomarkers that are frequently related to mood disorders were identified across all studies. In terms of mood disorders, a collection of biomarkers has been found, with specific attention given to seven fundamental genetic variations. A comprehensive analysis revealed a total of five central biomarkers that exhibited a significant association with unipolar depression, with an additional five central biomarkers that demonstrated a significant association with mixed traits. Biomarkers that have been linked to an increased vulnerability to mood disorders have been found to disrupt many cellular processes in neuronal development, including cell morphogenesis, cell projection organization, and cell adhesion. The main signaling pathways associated with biomarkers that contribute to a reduced susceptibility to mood disorders encompass the activation of neuro projection morphogenesis, O-linked glycosylation, modulation of chemical synaptic transmission, and G-protein-coupled glutamate receptor activity. hsa-miR-3937, hsa-miR-4499, and hsa-miR-7106-5p exhibited the most significant downregulation in the GSE182194 dataset. A microRNA (hsa-miR-26b-5p) and transcription factors (zinc finger proteins) were found to have a pivotal role in the elucidation of genetic variations linked to mood disorders across different datasets (EFO_0003761, GSE101521, and GSE217811).</p></div><div><h3>Conclusions</h3><p>Our findings provide a foundational framework for prospective therapeutic approaches aimed at addressing mood disorders, specifically focusing on the genetic variants and pathways linked to this condition.</p></div>\",\"PeriodicalId\":19837,\"journal\":{\"name\":\"Personalized Medicine in Psychiatry\",\"volume\":\"45 \",\"pages\":\"Article 100128\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2468171724000140/pdfft?md5=923a3140905b2bc33887a321137d1e24&pid=1-s2.0-S2468171724000140-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Personalized Medicine in Psychiatry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468171724000140\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Personalized Medicine in Psychiatry","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468171724000140","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Elucidation of molecular processes and biomarkers linked to the genetic variations driving the etiology of mood disorders
Objectives
We aimed to identify the significant genetic variations and molecular mechanisms associated with the pathogenesis of mood disorders associated with genetic variants.
Methods
Genome-wide association studies (GWAS, ID: EFO_0003761), ClueGO plug-in, and GEO database were the main approaches.
Results
Ten biomarkers that are frequently related to mood disorders were identified across all studies. In terms of mood disorders, a collection of biomarkers has been found, with specific attention given to seven fundamental genetic variations. A comprehensive analysis revealed a total of five central biomarkers that exhibited a significant association with unipolar depression, with an additional five central biomarkers that demonstrated a significant association with mixed traits. Biomarkers that have been linked to an increased vulnerability to mood disorders have been found to disrupt many cellular processes in neuronal development, including cell morphogenesis, cell projection organization, and cell adhesion. The main signaling pathways associated with biomarkers that contribute to a reduced susceptibility to mood disorders encompass the activation of neuro projection morphogenesis, O-linked glycosylation, modulation of chemical synaptic transmission, and G-protein-coupled glutamate receptor activity. hsa-miR-3937, hsa-miR-4499, and hsa-miR-7106-5p exhibited the most significant downregulation in the GSE182194 dataset. A microRNA (hsa-miR-26b-5p) and transcription factors (zinc finger proteins) were found to have a pivotal role in the elucidation of genetic variations linked to mood disorders across different datasets (EFO_0003761, GSE101521, and GSE217811).
Conclusions
Our findings provide a foundational framework for prospective therapeutic approaches aimed at addressing mood disorders, specifically focusing on the genetic variants and pathways linked to this condition.