Observational studyeLife2023
Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study.
Observational study in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
43 citing papers in PubMed, 2 syntheses or guidelines pooled it, 67 citations in OpenAlex.
- A systematic review of brain health in adults with chronic pain.Anaesthesia · 2026Pooled it
- BrainAGE, brain health, and mental disorders: A systematic review.Neuroscience and biobehavioral reviews · 2024Pooled it
- Cognitive and Brain Reserve as Modifiers of Early Alzheimer Disease-Related Cognitive Vulnerability.Neurology · 2026Trial
- Investigating the Contribution of Molecular-Enriched Functional Connectivity to Brain-Age Analysis.Human brain mapping · 2026Article
- Aging beyond diagnosis: the MRI brain age gap across disorders.GeroScience · 2026Review
- Spatial amyloid-informed multimodal brain age as an early marker of Alzheimer's-related vulnerability and risk stratification.The journal of prevention of Alzheimer's disease · 2026Article
- A physically and mentally active lifestyle relates to younger brain and cognitive age.GeroScience · 2026Article
- Brain Age as a Biomarker in Alzheimer's Disease: Narrative Perspectives on Imaging, Biomarkers, Machine Learning, and Intervention Potential.Brain sciences · 2025Review
- Biological organ ages associate with risk of chronic diseases in a community-based population.JCI insight · 2025Article
- The Knight Alzheimer Research Imaging (KARI) dataset: a comprehensive multimodal resource for exploring aging, preclinical, and symptomatic Alzheimer disease pathology.Research square · 2025Article
- Investigating the Contribution of Molecular-Enriched Functional Connectivity to Brain-Age Analysis.bioRxiv : the preprint server for biology · 2025Article
- When Age Is More Than a Number: Acceleration of Brain Aging in Neurodegenerative Diseases.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2025Article
- Brain age prediction from MRI scans in neurodegenerative diseases.Current opinion in neurology · 2025Review
- The role of cognitive and brain reserve in the clinical presentation and progression of amyotrophic lateral sclerosis.Scientific reports · 2025Article
- AI-powered integration of multimodal imaging in precision medicine for neuropsychiatric disorders.Cell reports. Medicine · 2025Review
- miR-484 in Hippocampal Astrocytes of Aged and Young Rats Targets CSF-1 to Regulate Neural Progenitor/Stem Cell Proliferation and Differentiation Into Neurons.CNS neuroscience & therapeutics · 2025Article
- Complementary value of molecular, phenotypic, and functional aging biomarkers in dementia prediction.GeroScience · 2025Article
- Cross-Sectional Comparison of Structural MRI Markers of Impairment in a Diverse Cohort of Older Adults.Human brain mapping · 2025Article
- Brain Age Modeling and Cognitive Outcomes in Young Adults With and Without Sickle Cell Anemia.JAMA network open · 2025Article
- Distinct changes in the morphology of cortical and subcortical grey matter associated with age-related hearing loss and tinnitus in the UK Biobank participants.Brain communications · 2025Article
Corrections and comments
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Authors and funding
18 authors at 6 institutions in 4 countries.
Funding
Abstract
Background: Estimates of 'brain-predicted age' quantify apparent brain age compared to normative trajectories of neuroimaging features. The brain age gap (BAG) between predicted and chronological age is elevated in symptomatic Alzheimer disease (AD) but has not been well explored in presymptomatic AD. Prior studies have typically modeled BAG with structural MRI, but more recently other modalities, including functional connectivity (FC) and multimodal MRI, have been explored. Methods: We trained three models to predict age from FC, structural (S), or multimodal MRI (S+FC) in 390 amyloid-negative cognitively normal (CN/A-) participants (18-89 years old). In independent samples of 144 CN/A-, 154 CN/A+, and 154 cognitively impaired (CI; CDR > 0) participants, we tested relationships between BAG and AD biomarkers of amyloid and tau, as well as a global cognitive composite. Results: All models predicted age in the control training set, with the multimodal model outperforming the unimodal models. All three BAG estimates were significantly elevated in CI compared to controls. FC-BAG was significantly reduced in CN/A+ participants compared to CN/A-. In CI participants only, elevated S-BAG and S+FC BAG were associated with more advanced AD pathology and lower cognitive performance. Conclusions: Both FC-BAG and S-BAG are elevated in CI participants. However, FC and structural MRI also capture complementary signals. Specifically, FC-BAG may capture a unique biphasic response to presymptomatic AD pathology, while S-BAG may capture pathological progression and cognitive decline in the symptomatic stage. A multimodal age-prediction model improves sensitivity to healthy age differences. Funding: This work was supported by the National Institutes of Health (P01-AG026276, P01- AG03991, P30-AG066444, 5-R01-AG052550, 5-R01-AG057680, 1-R01-AG067505, 1S10RR022984-01A1, and U19-AG032438), the BrightFocus Foundation (A2022014F), and the Alzheimer's Association (SG-20-690363-DIAN).
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Registered trials
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 OpenQuestion graph.