Max Korbmacher , Dennis van der Meer , Dani Beck , Daniel E. Askeland-Gjerde , Eli Eikefjord , Arvid Lundervold , Ole A. Andreassen , Lars T. Westlye , Ivan I. Maximov
{"title":"英国生物样本库中不同的纵向脑白质微结构变化与常见精神疾病和阿尔茨海默病的相关多基因风险","authors":"Max Korbmacher , Dennis van der Meer , Dani Beck , Daniel E. Askeland-Gjerde , Eli Eikefjord , Arvid Lundervold , Ole A. Andreassen , Lars T. Westlye , Ivan I. Maximov","doi":"10.1016/j.bpsgos.2024.100323","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>During the course of adulthood and aging, white matter (WM) structure and organization are characterized by slow degradation processes such as demyelination and shrinkage. An acceleration of such aging processes has been linked to the development of a range of diseases. Thus, an accurate description of healthy brain maturation, particularly in terms of WM features, is fundamental to the understanding of aging.</p></div><div><h3>Methods</h3><p>We used longitudinal diffusion magnetic resonance imaging to provide an overview of WM changes at different spatial and temporal scales in the UK Biobank (UKB) (<em>n</em> = 2678; age<sub>scan 1</sub> = 62.38 ± 7.23 years; age<sub>scan 2</sub> = 64.81 ± 7.1 years). To examine the genetic overlap between WM structure and common clinical conditions, we tested the associations between WM structure and polygenic risk scores for the most common neurodegenerative disorder, Alzheimer’s disease, and common psychiatric disorders (unipolar and bipolar depression, anxiety, obsessive-compulsive disorder, autism, schizophrenia, attention-deficit/hyperactivity disorder) in longitudinal (<em>n</em> = 2329) and cross-sectional (<em>n</em> = 31,056) UKB validation data.</p></div><div><h3>Results</h3><p>Our findings indicate spatially distributed WM changes across the brain, as well as distributed associations of polygenic risk scores with WM. Importantly, brain longitudinal changes reflected genetic risk for disorder development better than the utilized cross-sectional measures, with regional differences giving more specific insights into gene-brain change associations than global averages.</p></div><div><h3>Conclusions</h3><p>We extend recent findings by providing a detailed overview of WM microstructure degeneration on different spatial levels, helping to understand fundamental brain aging processes. Further longitudinal research is warranted to examine aging-related gene-brain associations.</p></div>","PeriodicalId":72373,"journal":{"name":"Biological psychiatry global open science","volume":"4 4","pages":"Article 100323"},"PeriodicalIF":4.0000,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667174324000363/pdfft?md5=9cbaf26cc3387fbc0c5b8f6e21874558&pid=1-s2.0-S2667174324000363-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Distinct Longitudinal Brain White Matter Microstructure Changes and Associated Polygenic Risk of Common Psychiatric Disorders and Alzheimer’s Disease in the UK Biobank\",\"authors\":\"Max Korbmacher , Dennis van der Meer , Dani Beck , Daniel E. Askeland-Gjerde , Eli Eikefjord , Arvid Lundervold , Ole A. Andreassen , Lars T. Westlye , Ivan I. Maximov\",\"doi\":\"10.1016/j.bpsgos.2024.100323\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>During the course of adulthood and aging, white matter (WM) structure and organization are characterized by slow degradation processes such as demyelination and shrinkage. An acceleration of such aging processes has been linked to the development of a range of diseases. Thus, an accurate description of healthy brain maturation, particularly in terms of WM features, is fundamental to the understanding of aging.</p></div><div><h3>Methods</h3><p>We used longitudinal diffusion magnetic resonance imaging to provide an overview of WM changes at different spatial and temporal scales in the UK Biobank (UKB) (<em>n</em> = 2678; age<sub>scan 1</sub> = 62.38 ± 7.23 years; age<sub>scan 2</sub> = 64.81 ± 7.1 years). To examine the genetic overlap between WM structure and common clinical conditions, we tested the associations between WM structure and polygenic risk scores for the most common neurodegenerative disorder, Alzheimer’s disease, and common psychiatric disorders (unipolar and bipolar depression, anxiety, obsessive-compulsive disorder, autism, schizophrenia, attention-deficit/hyperactivity disorder) in longitudinal (<em>n</em> = 2329) and cross-sectional (<em>n</em> = 31,056) UKB validation data.</p></div><div><h3>Results</h3><p>Our findings indicate spatially distributed WM changes across the brain, as well as distributed associations of polygenic risk scores with WM. Importantly, brain longitudinal changes reflected genetic risk for disorder development better than the utilized cross-sectional measures, with regional differences giving more specific insights into gene-brain change associations than global averages.</p></div><div><h3>Conclusions</h3><p>We extend recent findings by providing a detailed overview of WM microstructure degeneration on different spatial levels, helping to understand fundamental brain aging processes. Further longitudinal research is warranted to examine aging-related gene-brain associations.</p></div>\",\"PeriodicalId\":72373,\"journal\":{\"name\":\"Biological psychiatry global open science\",\"volume\":\"4 4\",\"pages\":\"Article 100323\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2667174324000363/pdfft?md5=9cbaf26cc3387fbc0c5b8f6e21874558&pid=1-s2.0-S2667174324000363-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biological psychiatry global open science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667174324000363\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biological psychiatry global open science","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667174324000363","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Distinct Longitudinal Brain White Matter Microstructure Changes and Associated Polygenic Risk of Common Psychiatric Disorders and Alzheimer’s Disease in the UK Biobank
Background
During the course of adulthood and aging, white matter (WM) structure and organization are characterized by slow degradation processes such as demyelination and shrinkage. An acceleration of such aging processes has been linked to the development of a range of diseases. Thus, an accurate description of healthy brain maturation, particularly in terms of WM features, is fundamental to the understanding of aging.
Methods
We used longitudinal diffusion magnetic resonance imaging to provide an overview of WM changes at different spatial and temporal scales in the UK Biobank (UKB) (n = 2678; agescan 1 = 62.38 ± 7.23 years; agescan 2 = 64.81 ± 7.1 years). To examine the genetic overlap between WM structure and common clinical conditions, we tested the associations between WM structure and polygenic risk scores for the most common neurodegenerative disorder, Alzheimer’s disease, and common psychiatric disorders (unipolar and bipolar depression, anxiety, obsessive-compulsive disorder, autism, schizophrenia, attention-deficit/hyperactivity disorder) in longitudinal (n = 2329) and cross-sectional (n = 31,056) UKB validation data.
Results
Our findings indicate spatially distributed WM changes across the brain, as well as distributed associations of polygenic risk scores with WM. Importantly, brain longitudinal changes reflected genetic risk for disorder development better than the utilized cross-sectional measures, with regional differences giving more specific insights into gene-brain change associations than global averages.
Conclusions
We extend recent findings by providing a detailed overview of WM microstructure degeneration on different spatial levels, helping to understand fundamental brain aging processes. Further longitudinal research is warranted to examine aging-related gene-brain associations.