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Single cell transcriptomes and multiscale networks from persons with and without Alzheimer’s disease

  • Qi Wang
  • , Jerry Antone
  • , Eric Alsop
  • , Rebecca Reiman
  • , Cory Funk
  • , Jaroslav Bendl
  • , Joel T. Dudley
  • , Winnie S. Liang
  • , Timothy L. Karr
  • , Panos Roussos
  • , David A. Bennett
  • , Philip L. de Jager
  • , Geidy E. Serrano
  • , Thomas G. Beach
  • , Kendall van Keuren-Jensen
  • , Diego Mastroeni
  • , Eric M. Reiman
  • , Benjamin P. Readhead*
  • *Corresponding author for this work
  • Arizona State University
  • Translational Genomics Research Institute
  • Institute for Systems Biology
  • Icahn School of Medicine at Mount Sinai
  • Rush University
  • Columbia University Medical Center
  • Banner Health
  • Banner Alzheimer's Institute

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

The emergence of single nucleus RNA sequencing (snRNA-seq) offers to revolutionize the study of Alzheimer’s disease (AD). Integration with complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link cell subpopulations and molecular networks with a broader disease-relevant context. We report snRNA-seq profiles from superior frontal gyrus samples from 101 well characterized subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in hematological parameters. We observed an AD-associated CD83(+) microglial subtype with unique molecular networks and which is associated with immunoglobulin IgG4 production in the transverse colon. Our major observations were replicated in two additional, independent snRNA-seq data sets. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal disease biology.
Original languageEnglish
Article number5815
JournalNature communications
Volume15
Issue number1
DOIs
Publication statusPublished - 1 Dec 2024
Externally publishedYes

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