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Basic Science and Pathogenesis.

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  • 1University of California Davis, Davis, CA, USA.

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Microglia villages enable studying late-onset Alzheimer's disease (LOAD) genetics in hundreds of patient-derived cells. This method accurately identifies genetic impacts on microglia function and uncovers new disease-associated variants.

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Area of Science:

  • Neuroscience
  • Genetics
  • Cell Biology

Background:

  • Genome-wide association studies (GWAS) have identified genetic risk factors for late-onset Alzheimer's disease (LOAD), such as APOE and TREM2, but explain only a fraction of heritability.
  • Complex genetic architectures, including polygenic and oligogenic contributions, are increasingly implicated in LOAD.
  • Induced pluripotent stem cell-derived microglia (iMG) offer a model to study the impact of genetic risk on disease progression, as risk genes are expressed in myeloid cells like microglia.

Purpose of the Study:

  • To develop and validate a scalable method for studying the impact of LOAD genetics using patient-derived microglia.
  • To investigate the functional consequences of LOAD-associated genetic variants on microglia phenotypes.
  • To identify novel genetic modifiers of microglia function in the context of LOAD.

Main Methods:

  • Adapted a pooled culture technique called 'villages' to culture iMG from multiple donors simultaneously.
  • Linked donor-specific phenotypes to individuals using unique genetic variants within the pooled culture.
  • Utilized in vitro and xenograft models to assess microglia states, transcriptional signatures, and functions across diverse donors.

Main Results:

  • Microglia villages successfully recapitulated in vitro and in vivo microglia states, with donors evenly distributed across transcriptional signatures, including disease-associated microglia.
  • Confirmed phagocytosis defects in donors carrying the TREM2R47H variant.
  • Identified TMEM106B as a novel modifier of microglia phagocytosis in a pool of 25 cell lines.

Conclusions:

  • Microglia villages provide an accurate and scalable platform for studying LOAD genetics across numerous patients, including diverse sexes and genetic ancestries.
  • This method bridges the gap between transcriptomic signatures and microglia function, enabling the identification of regulators of microglia states and functions.
  • The findings highlight the potential of microglia villages for uncovering complex genetic contributions to LOAD and identifying therapeutic targets.