An integrated single cell and spatial transcriptomic map of human white adipose tissue

Lucas Massier(Karolinska University Hospital), Jutta Jalkanen(Karolinska University Hospital), Merve Elmastas(Karolinska University Hospital), Jiawei Zhong(Karolinska University Hospital), Tongtong Wang(Board of the Swiss Federal Institutes of Technology), Pamela A. Nono Nankam(Helmholtz Zentrum München), Scott Frendo‐Cumbo(Karolinska University Hospital), Jesper Bäckdahl(Karolinska University Hospital), N Subramanian(Karolinska University Hospital), Takuya Sekine(Karolinska University Hospital), Alastair G. Kerr(Karolinska University Hospital), Ben T. P. Tseng(Karolinska University Hospital), Jurga Laurencikiene(Karolinska University Hospital), Marcus Buggert(Karolinska University Hospital), Magda Lourda(Karolinska University Hospital), Karolina Kublickiene(Karolinska University Hospital), Nayanika Bhalla(Science for Life Laboratory), Alma Andersson(Science for Life Laboratory), Armand Valsesia(Nestlé (Switzerland)), Arne Astrup(Novo Nordisk Foundation), Ellen E. Blaak(Maastricht University Medical Centre), Patrik L. Ståhl(Science for Life Laboratory), Nathalie Viguerie(Université Toulouse III - Paul Sabatier), Dominique Langin(Université Toulouse III - Paul Sabatier), Christian Wolfrum(Board of the Swiss Federal Institutes of Technology), Matthias Blüher(Helmholtz Zentrum München), Mikael Rydén(Karolinska University Hospital), Niklas Mejhert(Karolinska University Hospital)
Nature Communications
March 15, 2023
Cited by 185Open Access
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Abstract

To date, single-cell studies of human white adipose tissue (WAT) have been based on small cohort sizes and no cellular consensus nomenclature exists. Herein, we performed a comprehensive meta-analysis of publicly available and newly generated single-cell, single-nucleus, and spatial transcriptomic results from human subcutaneous, omental, and perivascular WAT. Our high-resolution map is built on data from ten studies and allowed us to robustly identify >60 subpopulations of adipocytes, fibroblast and adipogenic progenitors, vascular, and immune cells. Using these results, we deconvolved spatial and bulk transcriptomic data from nine additional cohorts to provide spatial and clinical dimensions to the map. This identified cell-cell interactions as well as relationships between specific cell subtypes and insulin resistance, dyslipidemia, adipocyte volume, and lipolysis upon long-term weight changes. Altogether, our meta-map provides a rich resource defining the cellular and microarchitectural landscape of human WAT and describes the associations between specific cell types and metabolic states.


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