Nira Cedres, Urban Ekman, Konstantinos Poulakis, Sara Shams, Lena Cavallin, Sebastian Muehlboeck, Tobias Granberg, Lars-Olof Wahlund, Daniel Ferreira, Eric Westman
{"title":"阿尔茨海默病的脑萎缩亚型和ATN分类方案。","authors":"Nira Cedres, Urban Ekman, Konstantinos Poulakis, Sara Shams, Lena Cavallin, Sebastian Muehlboeck, Tobias Granberg, Lars-Olof Wahlund, Daniel Ferreira, Eric Westman","doi":"10.1159/000515322","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>We investigated the association between atrophy subtypes of Alzheimer's disease (AD), the ATN classification scheme, and key demographic and clinical factors in 2 cohorts with different source characteristics (a highly selective research-oriented cohort, the Alzheimer's Disease Neuroimaging Initiative [ADNI]; and a naturalistic heterogeneous clinically oriented cohort, Karolinska Imaging Dementia Study [KIDS]).</p><p><strong>Methods: </strong>A total of 382 AD patients were included. Factorial analysis of mixed data was used to investigate associations between AD subtypes based on brain atrophy patterns, ATN profiles based on cerebrospinal fluid biomarkers, and age, sex, Mini Mental State Examination (MMSE), cerebrovascular disease (burden of white matter signal abnormalities, WMSAs), and APOE genotype.</p><p><strong>Results: </strong>Older patients with high WMSA burden, belonging to the typical AD subtype and showing A+T+N+ or A+T+N- profiles clustered together and were mainly from ADNI. Younger patients with low WMSA burden, limbic-predominant or minimal atrophy AD subtypes, and A+T-N- or A+T-N+ profiles clustered together and were mainly from KIDS. APOE ε4 carriers more frequently showed the A+T-N- and A+T+N- profiles.</p><p><strong>Conclusions: </strong>Our findings align with the recent framework for biological subtypes of AD: the combination of risk factors, protective factors, and brain pathologies determines belonging of AD patients to distinct subtypes.</p>","PeriodicalId":19115,"journal":{"name":"Neurodegenerative Diseases","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000515322","citationCount":"4","resultStr":"{\"title\":\"Brain Atrophy Subtypes and the ATN Classification Scheme in Alzheimer's Disease.\",\"authors\":\"Nira Cedres, Urban Ekman, Konstantinos Poulakis, Sara Shams, Lena Cavallin, Sebastian Muehlboeck, Tobias Granberg, Lars-Olof Wahlund, Daniel Ferreira, Eric Westman\",\"doi\":\"10.1159/000515322\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>We investigated the association between atrophy subtypes of Alzheimer's disease (AD), the ATN classification scheme, and key demographic and clinical factors in 2 cohorts with different source characteristics (a highly selective research-oriented cohort, the Alzheimer's Disease Neuroimaging Initiative [ADNI]; and a naturalistic heterogeneous clinically oriented cohort, Karolinska Imaging Dementia Study [KIDS]).</p><p><strong>Methods: </strong>A total of 382 AD patients were included. Factorial analysis of mixed data was used to investigate associations between AD subtypes based on brain atrophy patterns, ATN profiles based on cerebrospinal fluid biomarkers, and age, sex, Mini Mental State Examination (MMSE), cerebrovascular disease (burden of white matter signal abnormalities, WMSAs), and APOE genotype.</p><p><strong>Results: </strong>Older patients with high WMSA burden, belonging to the typical AD subtype and showing A+T+N+ or A+T+N- profiles clustered together and were mainly from ADNI. Younger patients with low WMSA burden, limbic-predominant or minimal atrophy AD subtypes, and A+T-N- or A+T-N+ profiles clustered together and were mainly from KIDS. APOE ε4 carriers more frequently showed the A+T-N- and A+T+N- profiles.</p><p><strong>Conclusions: </strong>Our findings align with the recent framework for biological subtypes of AD: the combination of risk factors, protective factors, and brain pathologies determines belonging of AD patients to distinct subtypes.</p>\",\"PeriodicalId\":19115,\"journal\":{\"name\":\"Neurodegenerative Diseases\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1159/000515322\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neurodegenerative Diseases\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1159/000515322\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/3/31 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neurodegenerative Diseases","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1159/000515322","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/3/31 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Brain Atrophy Subtypes and the ATN Classification Scheme in Alzheimer's Disease.
Introduction: We investigated the association between atrophy subtypes of Alzheimer's disease (AD), the ATN classification scheme, and key demographic and clinical factors in 2 cohorts with different source characteristics (a highly selective research-oriented cohort, the Alzheimer's Disease Neuroimaging Initiative [ADNI]; and a naturalistic heterogeneous clinically oriented cohort, Karolinska Imaging Dementia Study [KIDS]).
Methods: A total of 382 AD patients were included. Factorial analysis of mixed data was used to investigate associations between AD subtypes based on brain atrophy patterns, ATN profiles based on cerebrospinal fluid biomarkers, and age, sex, Mini Mental State Examination (MMSE), cerebrovascular disease (burden of white matter signal abnormalities, WMSAs), and APOE genotype.
Results: Older patients with high WMSA burden, belonging to the typical AD subtype and showing A+T+N+ or A+T+N- profiles clustered together and were mainly from ADNI. Younger patients with low WMSA burden, limbic-predominant or minimal atrophy AD subtypes, and A+T-N- or A+T-N+ profiles clustered together and were mainly from KIDS. APOE ε4 carriers more frequently showed the A+T-N- and A+T+N- profiles.
Conclusions: Our findings align with the recent framework for biological subtypes of AD: the combination of risk factors, protective factors, and brain pathologies determines belonging of AD patients to distinct subtypes.
期刊介绍:
''Neurodegenerative Diseases'' is a bimonthly, multidisciplinary journal for the publication of advances in the understanding of neurodegenerative diseases, including Alzheimer''s disease, Parkinson''s disease, amyotrophic lateral sclerosis, Huntington''s disease and related neurological and psychiatric disorders.