Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring最新文献

{"title":"Multi-modal machine learning for predicting amyloid positivity using on-ramp driving.","authors":"Sai Santosh Reddy Danda, Yi Lu Murphey, Amanda Maher, Carol Persad, Savannah Rose, Robert Koeppe, Bruno Giordani","doi":"10.1002/dad2.70161","DOIUrl":"10.1002/dad2.70161","url":null,"abstract":"<p><strong>Introduction: </strong>Early detection of amyloid p is critical for Alzheimer's disease (AD) risk identification. This study leverages machine learning of multi-modal attributes, including vehicular, physiological, and demographic data, to classify older adults with and without amyloid positivity.</p><p><strong>Methods: </strong>Driving data and physiological responses from 53 cognitively normal older drivers with known positron emission tomography amyloid status were collected during freeway on-ramp, merging, and post-merge stages of a fixed-course drive. Statistically significant features (<i>P ≤</i> 0.05) were used to train random forest and XGBoost classifiers to classify amyloid-positive and -negative participants, with feature importance evaluated based on model performance.</p><p><strong>Results: </strong>Integrating multiple data modalities (demographics, vehicular, and physiological features) improved classification performance, distinguishing amyloid status. XGBoost with all statistically significant features achieved the highest accuracy (85.1%). Vehicular data provided the most predictive power, highlighting driving behavior relevance for classification.</p><p><strong>Discussion: </strong>Results underscore the importance of complementary insights from on-ramp multi-modal data to predict amyloid status and potential early AD detection.</p><p><strong>Highlights: </strong>We analyzed driving behavior and physiological signals for cognitive decline detection.Artificial intelligence (AI) models (random forest, XGBoost) effectively classified amyloid beta positive and negative participants.Interpretable AI identified on-ramp driving, that is, ZOI_1, as key for classification.Multi-modal analysis during on-ramp driving aids early cognitive decline detection.Challenging traffic environments enable non-invasive cognitive health monitoring.</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"17 3","pages":"e70161"},"PeriodicalIF":4.4,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12340426/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144838519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sex and ethnicity in early-onset Alzheimer's disease biomarkers and global function.","authors":"Breton M Asken, Wei-En Wang, Franchesca Arias, Shellie-Anne Levy, Warren W Barker, Monica Rosselli, Rosie Curiel Cid, Michael Marsiske, Melissa J Armstrong, David E Vaillancourt, David A Loewenstein, Glenn E Smith, Ranjan Duara","doi":"10.1002/dad2.70157","DOIUrl":"10.1002/dad2.70157","url":null,"abstract":"<p><strong>Introduction: </strong>Early-onset Alzheimer's disease (EOAD) may have distinct biomarker and clinical features from late-onset AD (LOAD). EOAD is understudied in ethnically heterogeneous populations.</p><p><strong>Methods: </strong>We studied EOAD (<i>N</i> = 44, age 64.7 ± 5.5, 55% female, 52% Hispanic/Latino), LOAD (<i>N</i> = 113), early-onset non-AD (EOnonAD, <i>N</i> = 114), and clinically normal (CN, <i>N</i> = 93) individuals from the 1Florida Alzheimer's Disease Research Center. Group differences and demographic interactions were evaluated in plasma (phosphorylated tau217, glial fibrillary acidic protein, neurofilament light chain), neuroimaging (amyloid positron emission tomography, brain magnetic resonance imaging), and global function (Mini-Mental State Examination, Clinical Dementia Rating Sum of Boxes).</p><p><strong>Results: </strong>AD-related biomarkers and global function were consistently worse in EOAD than EOnonAD and CN, and similar or worse than LOAD. Among EOAD, younger age related to greater amyloid burden among non-Hispanic/Latino individuals only. AD-related biomarker changes were more severe in females than males among non-Hispanic/Latino EOAD, but more severe among males in Hispanic/Latino EOAD.</p><p><strong>Discussion: </strong>The biological and clinical features of EOAD may differ by sex and ethnicity.</p><p><strong>Highlights: </strong>Alzheimer's disease (AD) biomarkers and global functional measures were measured in Hispanic and non-Hispanic individuals with early-onset AD (EOAD).Overall, AD-related biomarkers and global function were consistently worse in EOAD than non-AD cognitive decline and controls, and similar or worse than late-onset AD.Younger age related to greater amyloid burden among non-Hispanic EOAD, but not Hispanic EOAD.Hispanic EOAD males had more severe changes than females, contrasting findings in non-Hispanic EOAD (females more severe than males).</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"17 3","pages":"e70157"},"PeriodicalIF":4.4,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12340424/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144838520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Divergent effects of age on imaging-based ATN biomarkers and cognition in Alzheimer's disease.","authors":"Lars Frings, Sabine Hellwig, Joachim Brumberg, Alexander Rau, Michael Mix, Ganna Blazhenets, Horst Urbach, Philipp T Meyer","doi":"10.1002/dad2.70142","DOIUrl":"10.1002/dad2.70142","url":null,"abstract":"<p><strong>Introduction: </strong>We investigated whether age of patients with Alzheimer's disease (AD) at first visit to a memory clinic predicts biomarker findings along the amyloid beta deposition, pathologic tau, and neurodegeneration (ATN) scheme and moderates the association between ATN biomarkers and cognition.</p><p><strong>Methods: </strong>We evaluated [¹¹C]Pittsburgh compound B positron emission tomography (PET), florzolotau (¹⁸F) PET, [¹⁸F]fluorodeoxyglucose PET, T1-weighted magnetic resonance imaging, and cognitive assessments (<i>N</i> = 190/63/252/687/2198) of a total of 2355 AD patients. We assessed direct and moderating effects of age.</p><p><strong>Results: </strong>Tau burden and hypometabolism were more severe in younger AD patients. Gray matter volume of the medial temporal lobe (MTL) was reduced to a greater extent in older patients. Relationships between different imaging modalities or between single imaging modalities and cognition were not moderated by age.</p><p><strong>Discussion: </strong>In contrast to more severe tau burden and hypometabolism in younger patients, MTL atrophy was more pronounced in older patients. Relationships between markers of pathology and those of neurodegeneration were not associated with age.</p><p><strong>Highlights: </strong>Amyloid beta load as a biomarker of pathology burden was not associated with age at first visit to a memory clinic.Tau burden was higher, and glucose metabolism was lower in younger Alzheimer's disease (AD) patients.By contrast, medial temporal lobe atrophy was less severe in younger AD patients.Younger AD patients showed more severe memory deficits with respect to age-appropriate normative data.Age had no moderating effect on relationships between different imaging variables or between single imaging variables and cognition.</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"17 3","pages":"e70142"},"PeriodicalIF":4.4,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12337748/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144823181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Alzheimer's disease prediction through ensemble learning and feature interpretability with SHAP-based feature analysis.","authors":"Md Kamrul Hossain, Afrina Ashraf, Md Mominul Islam, Shoriful Hassan Sourav, Md Monir Hossain Shimul","doi":"10.1002/dad2.70162","DOIUrl":"10.1002/dad2.70162","url":null,"abstract":"<p><strong>Introduction: </strong>Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia. Early diagnosis is vital. We developed an interpretable machine learning (ML) model for early AD prediction using open clinical data.</p><p><strong>Methods: </strong>Data from 2149 adults (60-90 years) were obtained from Kaggle. After preprocessing and feature engineering, tree-based models were trained. A stacking ensemble model combining Gradient Boosting and XGBoost was trained, with Logistic Regression as the meta-learner. SHapley Additive exPlanations (SHAP) provided interpretability. Performance was measured by accuracy, precision, recall, F1 score, ROC and AUC.</p><p><strong>Results: </strong>The stacked ensemble achieved 97% accuracy (AUC 0.97), with 0.97 precision, 0.94 recall, and 0.96 F1 score for AD. SHAP identified memory complaints, Mini-Mental State Examination (MMSE), functional assessment, behavioral symptoms, cholesterol, and lifestyle factors (activity, diet, sleep) as top predictors.</p><p><strong>Conclusion: </strong>The ensemble model, enhanced by SHAP analysis, provides accurate and interpretable AD risk predictions with potential applicability in future clinical decision support systems.</p><p><strong>Highlights: </strong>Developed an ensemble machine learning (ML) model for early Alzheimer's disease (AD) prediction.Achieved 97% accuracy using stacked XGBoost and Gradient Boosting.SHapley Additive exPlanations (SHAP) analysis identified key cognitive and lifestyle-related risk factors.Model interprets AD risk using explainable artificial intelligence (AI) for clinical applicability.Utilized open-access dataset to ensure reproducibility and transparency.</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"17 3","pages":"e70162"},"PeriodicalIF":4.4,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12333869/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144818225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to \"Incidence of dementia in the German Heinz Nixdorf Recall study over 20 years\".","authors":"","doi":"10.1002/dad2.70096","DOIUrl":"https://doi.org/10.1002/dad2.70096","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1002/dad2.70061.].</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"17 3","pages":"e70096"},"PeriodicalIF":4.4,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12329562/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144800909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-world use of diagnostic tests for mild cognitive impairment, Alzheimer's disease, and other dementias in Medicare fee-for-service beneficiaries.","authors":"Jessie T Yan, Allison Dillon, Tong Meng, Viviktha Ramesh, Marwan Noel Sabbagh, Vishakha Sharma, Sophie Roth","doi":"10.1002/dad2.70156","DOIUrl":"10.1002/dad2.70156","url":null,"abstract":"<p><strong>Introduction: </strong>This study assessed real-world use of diagnostic tests, such as neuroimaging (e.g., magnetic resonance imaging [MRI], or positron emission tomography [PET]), and computed tomography (CT), cerebrospinal fluid (CSF) biomarker, and blood tests for mild cognitive impairment (MCI), Alzheimer's disease (AD), and other dementias in a large US elderly population.</p><p><strong>Methods: </strong>Medicare fee-for-service data (2015-2020) were used to identify patients aged ≥ 67 newly diagnosed with MCI, AD, or other dementias. Descriptive analyses were conducted to understand the test use within 1 year before disease diagnosis and trends.</p><p><strong>Results: </strong>Among 653,420 patients (9.1% MCI, 30.3% AD, 60.6% other dementias), 71.9% had blood tests, 53.9% neuroimaging (46.4% CT, 17.7% MRI, and 0.7% PET), and 2.2% CSF test. Test use slightly increased from 2015 to 2020.</p><p><strong>Discussion: </strong>Findings from this study suggest low use of diagnostic tests, especially PET and CSF.</p><p><strong>Highlights: </strong>Blood tests, magnetic resonance imaging, and computed tomography were predominant for diagnosing mild cognitive impairment, Alzheimer's disease, or other dementias prior to the arrival of disease-modifying therapies.Cerebrospinal fluid biomarker and positron emission tomography tests were infrequently used despite their diagnostic value.The study indicates a modest increase in diagnostic test usage over 6 years between 2015 and 2020.Patients often received combined or repeated diagnostic tests.</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"17 3","pages":"e70156"},"PeriodicalIF":4.4,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12321507/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144790719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validating remote cognitive tests in the Wisconsin Registry for Alzheimer's Prevention.","authors":"Erin M Jonaitis, Rachel L Studer, Bailey Wheelock, Mary E Murphy, Caitlin A Artz, Rachel N Weinberg, Sterling C Johnson, Bruce P Hermann, Kimberly D Mueller, Rebecca E Langhough","doi":"10.1002/dad2.70153","DOIUrl":"10.1002/dad2.70153","url":null,"abstract":"<p><strong>Introduction: </strong>Remote cognitive assessment addresses barriers to research participation for older participants, but continuity in longitudinal studies is a challenge. We examined whether scores from telephone-based assessments (T-COG) were valid and reliable estimates of in-person traditional neuropsychological findings.</p><p><strong>Methods: </strong>Participants in the Wisconsin Registry for Alzheimer's Prevention (WRAP) who had completed in-person testing within the prior 12 months were invited to complete a follow-up T-COG visit. Bland-Altman plots and intraclass correlations were used to assess repeatability and bias.</p><p><strong>Results: </strong>Correlations between in-person and T-COG scores were of moderate to large magnitude (Pearson <i>r</i>: 0.57 to 0.80, intraclass correlation coefficients: 0.52 to 0.79). Bland-Altman plots revealed moderately wide limits of agreement, but no clear bias.</p><p><strong>Discussion: </strong>The WRAP-abbreviated T-COG battery can be completed in less than an hour and shows good concordance with in-person test administration. Availability of the T-COG option may reduce missing data and/or enhance retention when obstacles to in-person attendance arise.</p><p><strong>Highlights: </strong>Remote testing had adequate validity compared to in-person assessment.A telephone preclinical Alzheimer's composite correlated well with the original.Remote options may reduce missing data when barriers exist to in-person testing.Teleassessment may facilitate participant recruitment and retention.</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"17 3","pages":"e70153"},"PeriodicalIF":4.4,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12311312/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144762333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Loneliness trajectories and dementia risk: Insights from the HUNT cohort study.","authors":"Ragnhild Holmberg Aunsmo, Bjørn Heine Strand, Sverre Bergh, Thomas Hansen, Mika Kivimäki, Sebastian Köhler, Steinar Krokstad, Ellen M Langballe, Gill Livingston, Fiona E Matthews, Geir Selbæk","doi":"10.1002/dad2.70154","DOIUrl":"10.1002/dad2.70154","url":null,"abstract":"<p><strong>Introduction: </strong>Loneliness is postulated to be a risk factor for dementia. However, the findings are inconsistent, and long-term studies on this association remain scarce.</p><p><strong>Methods: </strong>In all, 9389 participants self-reported loneliness in the Trøndelag Health Study (HUNT) in HUNT1 (1984-1986), HUNT2 (1995-1997), and/or HUNT3 (2006-2008) and underwent cognitive assessment in HUNT4 (2017-2019) at age 70 years or older. Logistic regression was employed to analyze the association between the course of loneliness and dementia, with those never lonely as a reference.</p><p><strong>Results: </strong>In the fully adjusted model, the odds ratio (OR) for persistent loneliness was 1.47 (95% confidence interval [CI] 1.10, 1.95). This attenuated when adjusting for depression (OR 1.28, 95% CI 0.95, 1.72).</p><p><strong>Discussion: </strong>Persistent loneliness from midlife into older age, as well as becoming lonely, were associated with increased odds of dementia, whereas transient loneliness in midlife was not. These findings underscore the importance of reducing loneliness.</p><p><strong>Clinical trial registration: </strong>The study was registered with ClinicalTrials.gov (NCT04786561) and is available online .</p><p><strong>Highlights: </strong>Persistent and incident loneliness was associated with a higher risk of dementia.Transient loneliness was not associated with a higher risk of dementia.Loneliness 11 years before to the cognitive assessment was associated with dementia.Reducing the sense of loneliness might reduce or delay the onset of dementia.</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"17 3","pages":"e70154"},"PeriodicalIF":4.4,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12305116/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144745951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Apathy and affective symptoms associated with elevated plasma neurofilament light but not p-tau181 in Alzheimer's disease.","authors":"Matthew J Y Kang, Dhamidhu Eratne, Samantha M Loi, Christa Dang, Alexander F Santillo, Henrik Zetterberg, Kaj Blennow, Philip B Mitchell, Malcolm Hopwood, Charles B Malpas, Dennis Velakoulis","doi":"10.1002/dad2.70151","DOIUrl":"10.1002/dad2.70151","url":null,"abstract":"<p><strong>Introduction: </strong>Apathy and affective neuropsychiatric symptoms (NPS) are prevalent in Alzheimer's disease (AD), yet their neurobiological cause is still unclear. We examined associations between plasma neurofilament light chain (NfL) and tau pathology (p-tau181) with apathy and affective symptoms in mild cognitive impairment (MCI) and AD dementia.</p><p><strong>Methods: </strong>This longitudinal study analyzed data from 781 participants with MCI and AD dementia enrolled in ADNI, with annual blood samples collected over 4 years. NPS were assessed via the Neuropsychiatric Interview (NPI), and biomarker trajectories were analyzed using mixed-effects models.</p><p><strong>Results: </strong>Elevated plasma NfL levels were associated with apathy, anxiety and depression in MCI and AD dementia, with apathy linked to a significantly higher rate of NfL increase, indicating accelerated neurodegeneration.</p><p><strong>Discussion: </strong>Apathy and affective symptoms may indicate greater neurodegenerative burden in AD independent of tau-related pathology. Apathy was associated with a steeper rise in plasma NfL, suggesting a more aggressive disease progression.</p><p><strong>Highlights: </strong>Apathy and affective neuropsychiatric symptoms (NPS) are highly prevalent in clinical Alzheimer's disease (AD).The presence of apathy, depression or anxiety was associated with higher plasma levels of neurofilament light chain (NfL).Apathy was associated with an accelerated increase in plasma NfL levels over time.Apathy and affective NPS were not associated with p-tau181 levels in plasma.</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"17 3","pages":"e70151"},"PeriodicalIF":4.4,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12305118/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144745950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Amyloid accumulation, brain atrophy, and cognitive decline in emergent Alzheimer's disease.","authors":"Ying Xia, Pierrick Bourgeat, Vincent Doré, Jurgen Fripp, Yen Ying Lim, Simon M Laws, Christopher Fowler, Christopher C Rowe, Colin L Masters, Elizabeth J Coulson, Paul Maruff","doi":"10.1002/dad2.70155","DOIUrl":"10.1002/dad2.70155","url":null,"abstract":"<p><strong>Introduction: </strong>Emergent Alzheimer's disease (AD) represents a transitional stage where cognitively unimpaired (CU) individuals exhibit subthreshold but increasing amyloid-β (Aβ) levels. The impact of Aβ accumulation on brain volume loss and cognition during this early stage remains unclear.</p><p><strong>Methods: </strong>This retrospective cohort study analyzed data from 408 CU participants who were initially Aβ- (< 15 Centiloids) and followed for up to 15 years. Changes in basal forebrain and hippocampal volume, along with domain-specific cognitive performance, were compared between those who progressed to Aβ+ (≥20 Centiloids) and those who remained Aβ-.</p><p><strong>Results: </strong>Sixty-five CU participants progressed to Aβ+, indicating emergent AD, and showed faster Aβ accumulation and subtle memory decline. However, no significant differences in rate of BF and hippocampal atrophy were observed between groups.</p><p><strong>Discussion: </strong>The results suggest that during this emergent phase of AD, Aβ accumulation is associated with episodic memory loss, in the absence of detectable accelerated brain atrophy.</p><p><strong>Highlights: </strong>Identified cognitively unimpaired individuals in the emergent stage of Alzheimer's disease (AD).Emergent AD exhibits a greater rate of amyloid-β (Aβ) accumulation.No accelerated volume loss detected in the basal forebrain or hippocampus.Emergent AD is also associated with a subtle decline in memory.Early Aβ accumulation may impair cognitive function before structural atrophy.</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"17 3","pages":"e70155"},"PeriodicalIF":4.4,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12305117/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144745949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}