ArticleNeurology2023
Predicting Cognitive Decline in Older Adults Using Baseline Metrics of AD Pathologies, Cerebrovascular Disease, and Neurodegeneration.
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Article in Neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15citing papers in PubMed
2.5field-weighted citation impact, top 10% of its field
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Who cites it
15 citing papers in PubMed, 20 citations in OpenAlex.
- Comment on: "Eye-Tracking-Based Cognitive Assessment Predicts the Risk of Memory Decline: A Community-Based Cohort Study".Geriatrics & gerontology international · 2026Article
- A Biomarker Out of Context: Understanding High p-tau217 in the Developing Brain.Molecular neurobiology · 2026Review
- Deep survival modeling to predict future cognitive impairment in unimpaired adults.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026Article
- Eye-Tracking-Based Cognitive Assessment Predicts the Risk of Memory Decline: A Community-Based Cohort Study.Geriatrics & gerontology international · 2026Article
- Deep learning to predict future cognitive decline: a multimodal approach using brain MRI and clinical data.Frontiers in neuroimaging · 2026Article
- Cerebrovascular disease in Alzheimer's disease: Brain structure as a critical mediator of cognitive decline.The journal of prevention of Alzheimer's disease · 2025Article
- Dissecting the clinical and pathological prognosis of MCI patients who reverted to normal cognition: a longitudinal study.BMC medicine · 2025Article
- Physical activity and the outcome of cognitive trajectory: a machine learning approach.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2025Article
- Biomarker pathway heterogeneity of amyloid-positive individuals.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Clinical variables contributing to the identification of biologically defined subgroups within cognitively unimpaired and mild cognitive impairment individuals.European journal of neurology · 2024Article
- Clinically feasible automated MRI volumetry of the brain as a prognostic marker in subjective and mild cognitive impairment.Frontiers in neurology · 2024Article
- Article
- [Myelination as a modulating factor in memory circuitry].Revista de neurologia · 2023Review
- Detecting short-interval longitudinal cortical atrophy in neurodegenerative dementias via cluster scanning: A proof of concept.Imaging neuroscience (Cambridge, Mass.)Article
- Neurocognitive profiles are associated with subsequent brain integrity in a sample of Hispanics/Latinos: Findings from the SOL-INCA-MRI study (HCHS/SOL).Alzheimer's & dementia (Amsterdam, Netherlands)Article
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Authors and funding
13 authors at 2 institutions in 2 countries.
Lloyd ProsserFrom the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands. l.prosser@ucl.ac.uk.ORCID 0000-0003-0299-1525
Amy MacdougallFrom the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.ORCID 0000-0002-2900-9602
Carole H SudreFrom the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.ORCID 0000-0001-5753-428X
Emily N ManningFrom the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.ORCID 0000-0002-4505-3611
Ian B MaloneFrom the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.ORCID 0000-0001-7512-7856
Phoebe WalshFrom the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.ORCID 0000-0001-6584-3111
Olivia GoodkinFrom the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.ORCID 0000-0001-9283-9716
Hugh PembertonFrom the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.ORCID 0000-0001-8419-6423
Frederik BarkhofFrom the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.ORCID 0000-0003-3543-3706
Geert Jan BiesselsFrom the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.ORCID 0000-0001-6862-2496
David M CashFrom the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.ORCID 0000-0001-7833-616X
Josephine BarnesFrom the Department of Neurodegenerative Disease (L.P., A.M., C.H.S., E.N.M., I.B.M., P.W., H.P., D.M.C., J.B.), Dementia Research Centre, UCL Queen Square Institute of Neurology, London; Medical Statistics (A.M.), London School of Hygiene and Tropical Medicine; School of Biomedical Engineering and Imaging Sciences (C.H.S.), King's College London; Centre for Medical Image Computing (C.H.S., O.G., H.P., F.B.) and Department of Population Sciences and Experimental Medicine (C.H.S.), MRC Unit for Lifelong Health and Ageing at UCL, University College London, United Kingdom; Department of Radiology and Nuclear Medicine (F.B.), VU University Medical Center, Amsterdam Neuroscience; and Department of Neurology and Neurosurgery (G.J.B.), UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.
Alzheimer's Disease Neuroimaging Initiative
London School of Hygiene & Tropical Medicine · GBKing's College London · GB
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivesDementia is a growing socioeconomic challenge that requires early intervention. Identifying biomarkers that reliably predict clinical progression early in the disease process would better aid selection of individuals for future trial participation. Here, we compared the ability of baseline, single time-point biomarkers (CSF amyloid 1-42, CSF ptau-181, white matter hyperintensities (WMH), cerebral microbleeds, whole-brain volume, and hippocampal volume) to predict decline in cognitively normal individuals who later converted to mild cognitive impairment (MCI) (CNtoMCI) and those with MCI who later converted to an Alzheimer disease (AD) diagnosis (MCItoAD).
methodsStandardized baseline biomarker data from AD Neuroimaging Initiative 2 (ADNI2)/GO and longitudinal diagnostic data (including ADNI3) were used. Cox regression models assessed biomarkers in relation to time to change in clinical diagnosis using all follow-up time points available. Models were fit for biomarkers univariately and together in a multivariable model. Hazard ratios (HRs) were compared to evaluate biomarkers. Analyses were performed separately in CNtoMCI and MCItoAD groups.
resultsFor CNtoMCI (n = 189), there was strong evidence that higher WMH volume (individual model: HR 1.79, DISCUSSION: Lower hippocampal volume was a consistent predictor of clinical conversion to MCI and AD. CSF and brain volume biomarkers were predictive of conversion to AD from MCI, whereas WMH were predictive of conversion to MCI from cognitively normal. The predictive ability of WMH in the CNtoMCI group may be interpreted as some being on a different pathologic pathway, such as vascular cognitive impairment.
Indexed as
Alzheimer DiseaseCerebrovascular DisordersCognitive DysfunctionAgedAmyloid beta-PeptidesBiomarkersDisease ProgressionHumanstau ProteinsAmyloid beta-PeptidesBiomarkerstau Proteins
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.