Tim van der Es, Sourena Soheili-Nezhad, Nina Roth Mota, Barbara Franke, Jan Buitelaar, Emma Sprooten
{"title":"利用多基因神经成像衍生评分探索大脑结构和多动症的遗传结构。","authors":"Tim van der Es, Sourena Soheili-Nezhad, Nina Roth Mota, Barbara Franke, Jan Buitelaar, Emma Sprooten","doi":"10.1002/ajmg.b.32987","DOIUrl":null,"url":null,"abstract":"<p>Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of neuropsychiatric disorders and highlighted their complexity. Careful consideration of the polygenicity and complex genetic architecture could aid in the understanding of the underlying brain mechanisms. We introduce an innovative approach to polygenic scoring, utilizing imaging-derived phenotypes (IDPs) to predict a clinical phenotype. We leveraged IDP GWAS data from the UK Biobank, to create polygenic imaging-derived scores (PIDSs). As a proof-of-concept, we assessed genetic variations in brain structure between individuals with ADHD and unaffected controls across three NeuroIMAGE waves (<i>n</i> = 954). Out of the 94 PIDS, 72 exhibited significant associations with their corresponding IDPs in an independent sample. Notably, several global measures, including cerebellum white matter, cerebellum cortex, and cerebral white matter, displayed substantial variance explained for their respective IDPs, ranging from 3% to 5.7%. Conversely, the associations between each IDP and the clinical ADHD phenotype were relatively weak. These findings highlight the growing power of GWAS in structural neuroimaging traits, enabling the construction of polygenic scores that accurately reflect the underlying polygenic architecture. However, to establish robust connections between PIDS and behavioral or clinical traits such as ADHD, larger samples are needed. Our novel approach to polygenic risk scoring offers a valuable tool for researchers in the field of psychiatric genetics.</p>","PeriodicalId":7673,"journal":{"name":"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics","volume":"198 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.b.32987","citationCount":"0","resultStr":"{\"title\":\"Exploring the genetic architecture of brain structure and ADHD using polygenic neuroimaging-derived scores\",\"authors\":\"Tim van der Es, Sourena Soheili-Nezhad, Nina Roth Mota, Barbara Franke, Jan Buitelaar, Emma Sprooten\",\"doi\":\"10.1002/ajmg.b.32987\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of neuropsychiatric disorders and highlighted their complexity. Careful consideration of the polygenicity and complex genetic architecture could aid in the understanding of the underlying brain mechanisms. We introduce an innovative approach to polygenic scoring, utilizing imaging-derived phenotypes (IDPs) to predict a clinical phenotype. We leveraged IDP GWAS data from the UK Biobank, to create polygenic imaging-derived scores (PIDSs). As a proof-of-concept, we assessed genetic variations in brain structure between individuals with ADHD and unaffected controls across three NeuroIMAGE waves (<i>n</i> = 954). Out of the 94 PIDS, 72 exhibited significant associations with their corresponding IDPs in an independent sample. Notably, several global measures, including cerebellum white matter, cerebellum cortex, and cerebral white matter, displayed substantial variance explained for their respective IDPs, ranging from 3% to 5.7%. Conversely, the associations between each IDP and the clinical ADHD phenotype were relatively weak. These findings highlight the growing power of GWAS in structural neuroimaging traits, enabling the construction of polygenic scores that accurately reflect the underlying polygenic architecture. However, to establish robust connections between PIDS and behavioral or clinical traits such as ADHD, larger samples are needed. Our novel approach to polygenic risk scoring offers a valuable tool for researchers in the field of psychiatric genetics.</p>\",\"PeriodicalId\":7673,\"journal\":{\"name\":\"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics\",\"volume\":\"198 1\",\"pages\":\"\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-07-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.b.32987\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/ajmg.b.32987\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ajmg.b.32987","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Exploring the genetic architecture of brain structure and ADHD using polygenic neuroimaging-derived scores
Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of neuropsychiatric disorders and highlighted their complexity. Careful consideration of the polygenicity and complex genetic architecture could aid in the understanding of the underlying brain mechanisms. We introduce an innovative approach to polygenic scoring, utilizing imaging-derived phenotypes (IDPs) to predict a clinical phenotype. We leveraged IDP GWAS data from the UK Biobank, to create polygenic imaging-derived scores (PIDSs). As a proof-of-concept, we assessed genetic variations in brain structure between individuals with ADHD and unaffected controls across three NeuroIMAGE waves (n = 954). Out of the 94 PIDS, 72 exhibited significant associations with their corresponding IDPs in an independent sample. Notably, several global measures, including cerebellum white matter, cerebellum cortex, and cerebral white matter, displayed substantial variance explained for their respective IDPs, ranging from 3% to 5.7%. Conversely, the associations between each IDP and the clinical ADHD phenotype were relatively weak. These findings highlight the growing power of GWAS in structural neuroimaging traits, enabling the construction of polygenic scores that accurately reflect the underlying polygenic architecture. However, to establish robust connections between PIDS and behavioral or clinical traits such as ADHD, larger samples are needed. Our novel approach to polygenic risk scoring offers a valuable tool for researchers in the field of psychiatric genetics.
期刊介绍:
Neuropsychiatric Genetics, Part B of the American Journal of Medical Genetics (AJMG) , provides a forum for experimental and clinical investigations of the genetic mechanisms underlying neurologic and psychiatric disorders. It is a resource for novel genetics studies of the heritable nature of psychiatric and other nervous system disorders, characterized at the molecular, cellular or behavior levels. Neuropsychiatric Genetics publishes eight times per year.