Ru Zhang, Leon Aksman, Dilmini Wijesinghe, John M Ringman, Danny J J Wang, Kay Jann
{"title":"进行性阿尔茨海默病脑功能复杂性的纵向研究。","authors":"Ru Zhang, Leon Aksman, Dilmini Wijesinghe, John M Ringman, Danny J J Wang, Kay Jann","doi":"10.1002/dad2.70059","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Cross-sectional resting-state functional magnetic resonance imaging (rsfMRI) studies have revealed altered complexity with advanced Alzheimer's disease (AD) stages. The current study conducted longitudinal rsfMRI complexity analyses in AD.</p><p><strong>Methods: </strong>Linear mixed-effects (LME) models were implemented to evaluate altered rates of disease progression in complexity across disease groups.</p><p><strong>Results: </strong>The LME models revealed complexity of the higher frequency in the CNtoMCI group (those converted from cognitively normal [CN] to mild cognitive impairment [MCI]) decayed faster over time versus CN in the prefrontal and lateral occipital cortex; complexity of the lower frequency decayed faster in AD versus CN in various frontal and temporal regions (<i>p</i> < 0.05 & Benjamini-Hochberg corrected with <i>q</i> < 0.05).</p><p><strong>Discussion: </strong>Local functional brain activities decayed in the early stage of the disease, and long-range communications were impacted in the later stage. Our study demonstrated longitudinal changes in AD-related rsfMRI complexity, indicating its potential as an imaging biomarker of AD.</p><p><strong>Highlights: </strong>We conducted longitudinal resting state functional magnetic resonance imaging (rsfMRI) complexity analyses using the Alzheimer's Disease Neuroimaging Initiative dataset.Higher-frequency complexity in the CNtoMCI group (those transitioning from cognitively normal [CN] to mild cognitive impairment [MCI]) was found to decay faster over time compared to CN, specifically in the prefrontal and lateral occipital cortex.Lower-frequency complexity was found to decay faster in AD versus CN in various frontal and temporal regions.This study demonstrated that longitudinal changes in rsfMRI complexity could serve as a potential imaging biomarker for Alzheimer's disease.</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"17 1","pages":"e70059"},"PeriodicalIF":4.0000,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11736706/pdf/","citationCount":"0","resultStr":"{\"title\":\"A longitudinal study of functional brain complexity in progressive Alzheimer's disease.\",\"authors\":\"Ru Zhang, Leon Aksman, Dilmini Wijesinghe, John M Ringman, Danny J J Wang, Kay Jann\",\"doi\":\"10.1002/dad2.70059\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Cross-sectional resting-state functional magnetic resonance imaging (rsfMRI) studies have revealed altered complexity with advanced Alzheimer's disease (AD) stages. The current study conducted longitudinal rsfMRI complexity analyses in AD.</p><p><strong>Methods: </strong>Linear mixed-effects (LME) models were implemented to evaluate altered rates of disease progression in complexity across disease groups.</p><p><strong>Results: </strong>The LME models revealed complexity of the higher frequency in the CNtoMCI group (those converted from cognitively normal [CN] to mild cognitive impairment [MCI]) decayed faster over time versus CN in the prefrontal and lateral occipital cortex; complexity of the lower frequency decayed faster in AD versus CN in various frontal and temporal regions (<i>p</i> < 0.05 & Benjamini-Hochberg corrected with <i>q</i> < 0.05).</p><p><strong>Discussion: </strong>Local functional brain activities decayed in the early stage of the disease, and long-range communications were impacted in the later stage. Our study demonstrated longitudinal changes in AD-related rsfMRI complexity, indicating its potential as an imaging biomarker of AD.</p><p><strong>Highlights: </strong>We conducted longitudinal resting state functional magnetic resonance imaging (rsfMRI) complexity analyses using the Alzheimer's Disease Neuroimaging Initiative dataset.Higher-frequency complexity in the CNtoMCI group (those transitioning from cognitively normal [CN] to mild cognitive impairment [MCI]) was found to decay faster over time compared to CN, specifically in the prefrontal and lateral occipital cortex.Lower-frequency complexity was found to decay faster in AD versus CN in various frontal and temporal regions.This study demonstrated that longitudinal changes in rsfMRI complexity could serve as a potential imaging biomarker for Alzheimer's disease.</p>\",\"PeriodicalId\":53226,\"journal\":{\"name\":\"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring\",\"volume\":\"17 1\",\"pages\":\"e70059\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2025-01-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11736706/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/dad2.70059\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/dad2.70059","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
A longitudinal study of functional brain complexity in progressive Alzheimer's disease.
Introduction: Cross-sectional resting-state functional magnetic resonance imaging (rsfMRI) studies have revealed altered complexity with advanced Alzheimer's disease (AD) stages. The current study conducted longitudinal rsfMRI complexity analyses in AD.
Methods: Linear mixed-effects (LME) models were implemented to evaluate altered rates of disease progression in complexity across disease groups.
Results: The LME models revealed complexity of the higher frequency in the CNtoMCI group (those converted from cognitively normal [CN] to mild cognitive impairment [MCI]) decayed faster over time versus CN in the prefrontal and lateral occipital cortex; complexity of the lower frequency decayed faster in AD versus CN in various frontal and temporal regions (p < 0.05 & Benjamini-Hochberg corrected with q < 0.05).
Discussion: Local functional brain activities decayed in the early stage of the disease, and long-range communications were impacted in the later stage. Our study demonstrated longitudinal changes in AD-related rsfMRI complexity, indicating its potential as an imaging biomarker of AD.
Highlights: We conducted longitudinal resting state functional magnetic resonance imaging (rsfMRI) complexity analyses using the Alzheimer's Disease Neuroimaging Initiative dataset.Higher-frequency complexity in the CNtoMCI group (those transitioning from cognitively normal [CN] to mild cognitive impairment [MCI]) was found to decay faster over time compared to CN, specifically in the prefrontal and lateral occipital cortex.Lower-frequency complexity was found to decay faster in AD versus CN in various frontal and temporal regions.This study demonstrated that longitudinal changes in rsfMRI complexity could serve as a potential imaging biomarker for Alzheimer's disease.
期刊介绍：
Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.
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