ArticleMolecular psychiatry2023
Decoding the heterogeneity of Alzheimer's disease diagnosis and progression using multilayer networks.
Article in Molecular psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Investigating neuropathological correlates of hyperactive and psychotic symptoms in dementia: a systematic review.Frontiers in dementia · 2025Pooled it
- Epigenetic aging in Alzheimer's disease: Relation to proteome.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Decoupling MCI-specific signatures from shared neurobiological substrates of cognitive aging via deep learning.NPJ digital medicine · 2026Article
- Clinical impact of the Alzheimer's Disease Neuroimaging Initiative: A review of studies using ADNI data (2023 to June 2025).Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Review
- Real-World Multimodal Machine Learning for Risk Enrichment Across the Alzheimer's Disease Spectrum.Journal of clinical medicine · 2026Article
- Resolving Heterogeneity in the Diagnosis of Alzheimer's Disease and its Progression Using Multimodal Data.Journal of molecular neuroscience : MN · 2026Article
- An interpretable multimodal ensemble assessment framework for Alzheimer's disease cognitive staging.Frontiers in neurology · 2026Article
- Spatiotemporal profiling of functional network overlapping modules in Alzheimer's disease.Network neuroscience (Cambridge, Mass.) · 2026Article
- Integrating imaging and omics for enhanced subtyping of mild cognitive impairment associated with Alzheimer's disease.Journal of translational medicine · 2025Article
- Targeting Oligodendrocyte Dysfunction in Alzheimer's Disease: a New Frontier for Drug Repurposing with Antihistamines and Serotonin Receptor Agonists.Journal of molecular neuroscience : MN · 2025Review
- Multiscale networks in Alzheimer's disease identify brain hypometabolism as central across biological scales.PLoS computational biology · 2025Article
- Multilayer Integration of Networks Toolbox (MINT).Communications biology · 2025Article
- Isoforms of Phosphorylated Tau as Potential Biomarkers for Alzheimer's Disease: The Contribution of Mass Spectrometry-Based Proteomics.NeuroSci · 2025Review
- Revealing heterogeneity in mild cognitive impairment based on individualized structural covariance network.Alzheimer's research & therapy · 2025Article
- Uncovering stage-specific neural and molecular progression in Alzheimer's disease: Implications for early screening.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Intranasal amyloid model of Alzheimer's disease - potential opportunities and challenges.Pharmacological reports : PR · 2025Review
- Exercise as a Therapeutic Intervention for Alzheimer's Disease.Advances in neurobiology · 2025Review
- Heterogeneity Analysis of Associations Involving the Large-Scale Online MindCrowd Survey Memory Test.Gerontology · 2025Article
- Are current etiological theories of Alzheimer's disease falsifiable? An epistemological assessment.Frontiers in aging neuroscience · 2025Article
- Beyond the usual suspects: multi-factorial computational models in the search for neurodegenerative disease mechanisms.Translational psychiatry · 2024Review
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Authors and funding
5 authors.
Funding
Abstract
Alzheimer's disease (AD) is a multifactorial and heterogeneous disorder, which makes early detection a challenge. Studies have attempted to combine biomarkers to improve AD detection and predict progression. However, most of the existing work reports results in parallel or compares normalized findings but does not analyze data simultaneously. We tested a multi-dimensional network framework, applied to 490 subjects (cognitively normal [CN] = 147; mild cognitive impairment [MCI] = 287; AD = 56) from ADNI, to create a single model capable of capturing the heterogeneity and progression of AD. First, we constructed subject similarity networks for structural magnetic resonance imaging, amyloid-β positron emission tomography, cerebrospinal fluid, cognition, and genetics data and then applied multilayer community detection to find groups with shared similarities across modalities. Individuals were also followed-up longitudinally, with AD subjects having, on average, 4.5 years of follow-up. Our findings show that multilayer community detection allows for accurate identification of present and future AD (≈90%) and is also able to identify cases that were misdiagnosed clinically. From all MCI participants who developed AD or reverted to CN, the multilayer model correctly identified 90.8% and 88.5% of cases respectively. We observed similar subtypes across the full sample and when examining multimodal data from subjects with no AD pathology (i.e., amyloid negative). Finally, these results were also validated using an independent testing set. In summary, the multilayer framework is successful in detecting AD and provides unique insight into the heterogeneity of the disease by identifying subtypes that share similar multidisciplinary profiles of neurological, cognitive, pathological, and genetics information.
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