Jing Guo, Changyi He, Huimiao Song, Huiwu Gao, Shi Yao, Shan-Shan Dong, Tie-Lin Yang
{"title":"从临床和遗传学角度揭示治疗精神分裂症的前景良好的神经影像生物标志物。","authors":"Jing Guo, Changyi He, Huimiao Song, Huiwu Gao, Shi Yao, Shan-Shan Dong, Tie-Lin Yang","doi":"10.1007/s12264-024-01214-1","DOIUrl":null,"url":null,"abstract":"<p><p>Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.</p>","PeriodicalId":19314,"journal":{"name":"Neuroscience bulletin","volume":" ","pages":"1333-1352"},"PeriodicalIF":5.9000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11365900/pdf/","citationCount":"0","resultStr":"{\"title\":\"Unveiling Promising Neuroimaging Biomarkers for Schizophrenia Through Clinical and Genetic Perspectives.\",\"authors\":\"Jing Guo, Changyi He, Huimiao Song, Huiwu Gao, Shi Yao, Shan-Shan Dong, Tie-Lin Yang\",\"doi\":\"10.1007/s12264-024-01214-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.</p>\",\"PeriodicalId\":19314,\"journal\":{\"name\":\"Neuroscience bulletin\",\"volume\":\" \",\"pages\":\"1333-1352\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11365900/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuroscience bulletin\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s12264-024-01214-1\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/5/4 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroscience bulletin","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12264-024-01214-1","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/4 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Unveiling Promising Neuroimaging Biomarkers for Schizophrenia Through Clinical and Genetic Perspectives.
Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.
期刊介绍:
Neuroscience Bulletin (NB), the official journal of the Chinese Neuroscience Society, is published monthly by Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS) and Springer.
NB aims to publish research advances in the field of neuroscience and promote exchange of scientific ideas within the community. The journal publishes original papers on various topics in neuroscience and focuses on potential disease implications on the nervous system. NB welcomes research contributions on molecular, cellular, or developmental neuroscience using multidisciplinary approaches and functional strategies. We feature full-length original articles, reviews, methods, letters to the editor, insights, and research highlights. As the official journal of the Chinese Neuroscience Society, which currently has more than 12,000 members in China, NB is devoted to facilitating communications between Chinese neuroscientists and their international colleagues. The journal is recognized as the most influential publication in neuroscience research in China.