Lipid-Associated Macrophages Control Metabolic Homeostasis in a Trem2-Dependent Manner

Diego Adhemar Jaitin, Lorenz Adlung, Christoph A. Thaiss, Assaf Weiner, Baoguo Li, Hélène Descamps, Patrick Lundgren, Camille Bleriot, Zhaoyuan Liu, Aleksandra Deczkowska, Hadas Keren-Shaul, Eyal David, Niv Zmora, Shai Meron Eldar, Nir Lubezky, Oren Shibolet, David A. Hill, Mitchell A. Lazar, Marco Colonna, Florent GinhouxHagit Shapiro, Eran Elinav, Ido Amit

Research output: Contribution to journalArticlepeer-review

596 Scopus citations


Immune cells residing in white adipose tissue have been highlighted as important factors contributing to the pathogenesis of metabolic diseases, but the molecular regulators that drive adipose tissue immune cell remodeling during obesity remain largely unknown. Using index and transcriptional single-cell sorting, we comprehensively map all adipose tissue immune populations in both mice and humans during obesity. We describe a novel and conserved Trem2+ lipid-associated macrophage (LAM) subset and identify markers, spatial localization, origin, and functional pathways associated with these cells. Genetic ablation of Trem2 in mice globally inhibits the downstream molecular LAM program, leading to adipocyte hypertrophy as well as systemic hypercholesterolemia, body fat accumulation, and glucose intolerance. These findings identify Trem2 signaling as a major pathway by which macrophages respond to loss of tissue-level lipid homeostasis, highlighting Trem2 as a key sensor of metabolic pathologies across multiple tissues and a potential therapeutic target in metabolic diseases.

Original languageEnglish
Pages (from-to)686-698.e14
Issue number3
StatePublished - Jul 25 2019


  • Alzheimer disease
  • Trem2 pathway
  • fatty liver diseases
  • immunology
  • macrophages
  • metabolic diseases
  • metabolism
  • obesity
  • single-cell genomics
  • systems biology


Dive into the research topics of 'Lipid-Associated Macrophages Control Metabolic Homeostasis in a Trem2-Dependent Manner'. Together they form a unique fingerprint.

Cite this