{
  "abstract": "Interindividual heterogeneity in Alzheimer's disease (AD) remains poorly understood, as disparate single-cell studies leave it unclear whether findings reflect shared architecture or dataset-specific idiosyncrasies. Here, we present panAD, a transcriptomic atlas of >3 million nuclei from 791 individuals across 13 studies, spanning AD, mild cognitive impairment, and cognitively normal aging. AD converges on a reproducible, cell-type-specific molecular architecture: co-expression modules track neuropathology and cognitive decline; GWAS risk genes act predominantly as downstream targets of transcription factor hubs such as microglial SPI1; intercellular communication is remodeled with disease stage; and sex differences concentrate in microglial immune-activation programs. To model patient-level transcriptomic heterogeneity, we developed the Multi-seed Optimization of Neural Embeddings for subTyping (MONET) framework, in which a masked variational autoencoder applied to covariate-adjusted, multi-cell-type profiles resolves four subtypes (Metal-Ion Stress, Neuroinflammatory, Synaptic Integrity, and Tissue Remodeling) that dissociate neuropathological burden from cognitive impairment and nominate predominantly non-overlapping candidate therapeutics. Finally, Stellar Atlas provides an AI-native conversational interface to the atlas.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Neurobiology and Behavior, Charlie Dunlop School of Biological Sciences, University of California, Irvine, CA, USA."
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "name": "N. Rahimzadeh"
    },
    {
      "name": "S. Morabito"
    },
    {
      "name": "S. Khullar"
    },
    {
      "name": "Z. Shi"
    },
    {
      "name": "Z. Cao"
    },
    {
      "affs": [
        0
      ],
      "name": "V. Swarup"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/apczmz72cbtm6.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.03.747935",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.03.747935v1.full",
  "id": "apczmz72cbtm6",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.03.747935v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "neuroscience"
    ],
    [
      "openalex",
      "1312|Single-cell and spatial transcriptomics"
    ]
  ],
  "openalex": "W7208718634",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.03.747935v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-03",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/apczmz72cbtm6.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:23Z",
      "native_id": "10.64898/2026.09.03.747935",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.03.747935v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:neuroscience",
      "subfield": "neuroscience"
    }
  ],
  "title": "An Integrated Single-Nucleus Atlas Resolves Cell-Type-Specific Programs and Molecular Subtypes in Alzheimer's Disease",
  "title_text": "An Integrated Single-Nucleus Atlas Resolves Cell-Type-Specific Programs and Molecular Subtypes in Alzheimer's Disease",
  "type": "preprint",
  "updated_at": "2026-10-30T12:19:23Z",
  "url": "https://research.draconitic.com/paper/apczmz72cbtm6",
  "venue": "bioRxiv",
  "versions": []
}