ReviewBiological psychiatry2020
Disentangling Heterogeneity in Alzheimer's Disease and Related Dementias Using Data-Driven Methods.
Review in Biological psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 108 papers, 3 of them syntheses that pooled it.
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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.
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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
108 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Meta-analysis of the make-up and properties of in vitro models of the healthy and diseased blood-brain barrier.Nature biomedical engineering · 2025Pooled it
- Frontotemporal dementia: a systematic review of artificial intelligence approaches in differential diagnosis.Frontiers in aging neuroscience · 2025Pooled it
- The hippocampal sparing subtype of Alzheimer's disease assessed in neuropathology and in vivo tau positron emission tomography: a systematic review.Acta neuropathologica communications · 2022Pooled it
- Beyond statistical thresholds: Mapping sequential ATN cascade transitions via brain structural topography in Alzheimer's disease.Science advances · 2026Article
- Cognitive heterogeneity in mild cognitive impairment due to Alzheimer's disease pathology.Neural regeneration research · 2026Article
- Multimodal axes reveal individualized amyloid-medRxiv : the preprint server for health sciences · 2026Article
- Literature-derived serum miRNA signatures associated with cognitive decline in Alzheimer's disease: integrated analysis and machine learning-based diagnostic modeling.Alzheimer's research & therapy · 2026Article
- Stratification of Alzheimer's disease patients using knowledge-guided unsupervised latent factor clustering with electronic health record data.Communications medicine · 2026Article
- Magnetic resonance microscopy maps widespread effects of Alzheimer's disease on brain structures and behavior in mice.Nature neuroscience · 2026Article
- Heterogeneous patterns of cognitive decline in Alzheimer's disease across three domains of cognition.Journal of Alzheimer's disease : JAD · 2026Article
- Identifying Alzheimer's Disease Progression Subphenotypes Via a Graph-based Framework Using Electronic Health Records.Journal of healthcare informatics research · 2026Article
- A neuroimaging biomarker for disease staging in clinically diagnosed Alzheimer's disease.BMC medicine · 2026Article
- ATN Classification and Machine-Learned Plasma Biomarker Phenotypes Reveal Distinct Alzheimer's Pathology in a Population-Based Cohort.medRxiv : the preprint server for health sciences · 2026Article
- Evaluating the correspondence of neuropsychological profiles with clinical diagnostic criteria for frontotemporal lobar degeneration and Alzheimer's disease: insights fromFrontiers in dementia · 2026Article
- Tau topography subtypes account for clinical heterogeneity and longitudinal trajectories in early-onset Alzheimer's disease.Brain communications · 2026Article
- Dissecting real-world memory clinical cohort heterogeneity: analysis of neuroanatomical subtypes using HYDRA.Alzheimer's research & therapy · 2025Article
- Differential MRI atrophy profiles and incident dementia: A cross-national comparison.Journal of Alzheimer's disease : JAD · 2025Article
- A Comparative Analysis of Subtyping Methodologies on Cross-sectional sMRI Data.Neuroscience bulletin · 2025Article
- Machine Learning in Adolescent Mental Health: Advanced Comorbidity Analysis and Text Mining Insights.Healthcare (Basel, Switzerland) · 2025Article
- Hypometabolic subtypes of AD are linked to comorbid hippocampal sclerosis and Lewy body pathology.Alzheimer's research & therapy · 2025Observational
48 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Brain aging is a complex process that includes atrophy, vascular injury, and a variety of age-associated neurodegenerative pathologies, together determining an individual's course of cognitive decline. While Alzheimer's disease and related dementias contribute to the heterogeneity of brain aging, these conditions themselves are also heterogeneous in their clinical presentation, progression, and pattern of neural injury. We reviewed studies that leveraged data-driven approaches to examining heterogeneity in Alzheimer's disease and related dementias, with a principal focus on neuroimaging studies exploring subtypes of regional neurodegeneration patterns. Over the past decade, the steadily increasing wealth of clinical, neuroimaging, and molecular biomarker information collected within large-scale observational cohort studies has allowed for a richer understanding of the variability of disease expression within the aging and Alzheimer's disease and related dementias continuum. Moreover, the availability of these large-scale datasets has supported the development and increasing application of clustering techniques for studying disease heterogeneity in a data-driven manner. In particular, data-driven studies have led to new discoveries of previously unappreciated disease subtypes characterized by distinct neuroimaging patterns of regional neurodegeneration, which are paralleled by heterogeneous profiles of pathological, clinical, and molecular biomarker characteristics. Incorporating these findings into novel frameworks for more differentiated disease stratification holds great promise for improving individualized diagnosis and prognosis of expected clinical progression, and provides opportunities for development of precision medicine approaches for therapeutic intervention. We conclude with an account of the principal challenges associated with data-driven heterogeneity analyses and outline avenues for future developments in the field.
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