ACE2 expression in adipose tissue is associated with cardio-metabolic risk factors and cell type composition—implications for COVID-19
Year: 2022
Type: article
Abstract: Background COVID-19 severity varies widely. Although some demographic and cardio-metabolic factors, including age and obesity, are associated with increasing risk of severe illness, the underlying mechanism(s) are uncertain. Subjects/methods In a meta-analysis of three independent studies of 1471 participants in total, we investigated phenotypic and genetic factors associated with subcutaneous adipose tissue expression of Angiotensin I Converting Enzyme 2 ( ACE2 ), measured by RNA-Seq, which acts as a receptor for SARS-CoV-2 cellular entry. Results Lower adipose tissue ACE2 expression was associated with multiple adverse cardio-metabolic health indices, including type 2 diabetes (T2D) ( P = 9.14 × 10 −6 ), obesity status ( P = 4.81 × 10 −5 ), higher serum fasting insulin ( P = 5.32 × 10 −4 ), BMI ( P = 3.94 × 10 −4 ), and lower serum HDL levels ( P = 1.92 × 10 −7 ). ACE2 expression was also associated with estimated proportions of cell types in adipose tissue: lower expression was associated with a lower proportion of microvascular endothelial cells ( P = 4.25 × 10 −4 ) and higher proportion of macrophages ( P = 2.74 × 10 −5 ). Despite an estimated heritability of 32%, we did not identify any proximal or distal expression quantitative trait loci (eQTLs) associated with adipose tissue ACE2 expression. Conclusions Our results demonstrate that individuals with cardio-metabolic features known to increase risk of severe COVID-19 have lower background ACE2 levels in this highly relevant tissue. Reduced adipose tissue ACE2 expression may contribute to the pathophysiology of cardio-metabolic diseases, as well as the associated increased risk of severe COVID-19.
Source: International Journal of Obesity
Authors: Julia S. El-Sayed Moustafa, Anne U. Jackson, Sarah M. Brotman, Li Guan, Sergio Villicaña, Amy L. Roberts, Antonino Zito, Lori Bonnycastle, Michael R. Erdos, Narisu Narisu, Heather M. Stringham, Ryan Welch, Tingfen Yan, Timo Lakka, Stephen Parker, Jaakko Tuomilehto, Jeffrey Seow, Carl Graham, Isabella Huettner, Sam Acors, Neophytos Kouphou, Samuel Wadge, Emma L. Duncan, Claire J. Steves, Katie J. Doores, Michael H. Malim, Francis S. Collins, Päivi Pajukanta, Michael Boehnke, Heikki A. Koistinen, Markku Laakso, Mario Falchi, Jordana T. Bell, Laura J. Scott, Karen L. Mohlke, Kerrin S. Small
Institutions: King's College London, University of Michigan, University of North Carolina at Chapel Hill, Harvard University, Massachusetts General Hospital, National Institutes of Health, National Human Genome Research Institute, University of Eastern Finland, Kuopio University Hospital, University of Helsinki, King Abdulaziz University, Helsinki University Hospital, University of California, Los Angeles, Finnish Institute for Health and Welfare, Minerva Foundation
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,390
Funders: South London and Maudsley NHS Foundation Trust, Wellcome Trust, Chronic Disease Research Foundation, Maudsley Charity, National Institute for Health and Care Research, Department of Health and Social Care, King's College London, European Commission, Academy of Finland, Consejo Nacional de Ciencia y Tecnología, Versus Arthritis, National Institutes of Health, Medical Research Council, Menzies Centre for Australian Studies, King's College London, University of London, National Heart, Lung, and Blood Institute, National Human Genome Research Institute, National Institute of General Medical Sciences, National Institute of Diabetes and Digestive and Kidney Diseases
Awards: G2082591074, G2306515209, G2335242333, Genetic analysis of type II diabetes in Finnish population, G2478079187, Genetic and environmental determinants of age-acquired skewed X-inactivation and escape from X-inactivation, G2988741787, G301048564, G3226476464, NRSA in Genetics, G434337789, A systems based approach to integrating genetic and longitudinal omics data to support diagnosis and prediction of common chronic disease, G491034554, G4940423171, Smoothness of the invariant Hilbert scheme of affine spherical varieties for the existence of wonderful varieties, G5501438795, G5514976981, G5918494183, G6122222817, Wellcome Longitudinal Population Study COVID-19 Steering Group and Secretariat, Wellcome Longitudinal Population Study COVID-19 Steering Group and Secretariat, G7456496496, G8108155134, G8415457339, G866671421, G9000023558, G9000051584, G9000078064, G9000151782, G9000239990, G9000269153, G9000321097, Michigan Diabetes Research Center (MDRC), Identifying Genes for Type 2 Diabetes: FUSION
OpenAlex ID: W4280625549