ArticleProceedings of the National Academy of Sciences of the United States of America2016
Bayesian model reveals latent atrophy factors with dissociable cognitive trajectories in Alzheimer's disease.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 112 papers, 1 of them a synthesis that pooled it.
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Who cites it
112 citing papers in PubMed, 1 synthesis or guideline pooled it, 189 citations in OpenAlex.
- Pooled it
- B-Vitamin Therapy for Kidney Transplant Recipients Lowers Homocysteine and Improves Selective Cognitive Outcomes in the Randomized FAVORIT Ancillary Cognitive Trial.The journal of prevention of Alzheimer's disease · 2017Trial
- Machine learning-derived Alzheimer's disease dimensions: neuroanatomical, cognitive, clinical, functional, and genetic risk heterogeneity signatures.medRxiv : the preprint server for health sciences · 2026Article
- Bayesian modelling demonstrates clinically relevant heterogeneity in Tau PET patterns in Alzheimer's disease.European journal of nuclear medicine and molecular imaging · 2026Article
- Decomposing heterogeneity in disease progression speeds and pathways.NPJ digital medicine · 2026Article
- Coupled cross-sectional and longitudinal non-negative matrix factorization reveals dominant brain aging trajectories in 48,949 individuals.Nature communications · 2026Article
- Sleep disturbances and Alzheimer's disease: a multiscale approach from exposome to neurobiology and precision medicine.GeroScience · 2026Review
- Mapping latent neuroanatomical substrates of behavioral and emotional dysregulation in ADHD.Psychological medicine · 2026Article
- Morphometric Latent Factors in Autism and Their Association with Receptor Profiles and Behavior.bioRxiv : the preprint server for biology · 2025Article
- Functional network collapse in neurodegenerative disease.Nature communications · 2025Article
- Distinct neuroimaging subtypes of ADHD among adolescents based on semi-supervised learning.Translational psychiatry · 2025Article
- Neuroimaging endophenotypes reveal underlying mechanisms and genetic factors contributing to progression and development of four brain disorders.Nature biomedical engineering · 2025Article
- Magnetic Resonance Imaging and Cerebrospinal Fluid Biomarker Clustering Defines Biological Subtypes of Alzheimer's Disease.Biomedicines · 2025Article
- Dissecting real-world memory clinical cohort heterogeneity: analysis of neuroanatomical subtypes using HYDRA.Alzheimer's research & therapy · 2025Article
- A Comparative Analysis of Subtyping Methodologies on Cross-sectional sMRI Data.Neuroscience bulletin · 2025Article
- Three Latent Factors in Major Depressive Disorder Base on Functional Connectivity Show Different Treatment Preferences.Human brain mapping · 2025Article
- Global incidence trends and projections of Alzheimer disease and other dementias: an age-period-cohort analysis 2021.Journal of global health · 2025Article
- Analyzing heterogeneity in Alzheimer disease using multimodal normative modeling on imaging-based ATN biomarkers.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Major depressive disorder on a neuromorphic continuum.Nature communications · 2025Article
- Common neuroanatomical differential factors underlying heterogeneous gray matter volume variations in five common psychiatric disorders.Communications biology · 2025Article
52 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
We used a data-driven Bayesian model to automatically identify distinct latent factors of overlapping atrophy patterns from voxelwise structural MRIs of late-onset Alzheimer's disease (AD) dementia patients. Our approach estimated the extent to which multiple distinct atrophy patterns were expressed within each participant rather than assuming that each participant expressed a single atrophy factor. The model revealed a temporal atrophy factor (medial temporal cortex, hippocampus, and amygdala), a subcortical atrophy factor (striatum, thalamus, and cerebellum), and a cortical atrophy factor (frontal, parietal, lateral temporal, and lateral occipital cortices). To explore the influence of each factor in early AD, atrophy factor compositions were inferred in beta-amyloid-positive (Aβ+) mild cognitively impaired (MCI) and cognitively normal (CN) participants. All three factors were associated with memory decline across the entire clinical spectrum, whereas the cortical factor was associated with executive function decline in Aβ+ MCI participants and AD dementia patients. Direct comparison between factors revealed that the temporal factor showed the strongest association with memory, whereas the cortical factor showed the strongest association with executive function. The subcortical factor was associated with the slowest decline for both memory and executive function compared with temporal and cortical factors. These results suggest that distinct patterns of atrophy influence decline across different cognitive domains. Quantification of this heterogeneity may enable the computation of individual-level predictions relevant for disease monitoring and customized therapies. Factor compositions of participants and code used in this article are publicly available for future research.
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