ACE2 expression in adipose tissue is associated with cardio-metabolic risk factors and cell type composition-implications for COVID-19

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.

Fig. 1. Associations of adipose tissue ACE2 expression levels with cardio-metabolic and demographic traits in the TwinsUK, METSIM and FUSION cohorts.

Squares with error bars represent the standardised β coefficients and their 95% confidence intervals for association of ACE2 expression levels with each trait (derived from linear/linear mixed effects regression models), with meta-analysis effect sizes and 95% confidence intervals (random-effects meta-analysis) shown as black diamonds. N represents the sample size for each analysis. a serum fasting insulin, (b) fasting plasma glucose, (c) BMI (d) serum HDL cholesterol, (e) serum LDL cholesterol, (f) serum total triglycerides, (g) systolic blood pressure, (h) diastolic blood pressure, (i) age, (j) obesity status. Association of ACE2 expression with (k) type 2 diabetes status in TwinsUK and (l) sex in the FUSION study. Boxplots (k, l) display the median and inter-quartile range (IQR), with whiskers corresponding to ±1.5*IQR.

Fig. 2. Adipose tissue estimated cell type proportions and their association with ACE2 expression levels across the TwinsUK, METSIM and FUSION studies.

Density plots of estimated cell type proportions of (a) microvascular endothelial cells (MVEC), (b) macrophages, (c) adipocytes in each of the TwinsUK, METSIM, and FUSION studies. Vertical dashed lines correspond to the study mean. Association of adipose tissue ACE2 expression levels with estimated (d) MVEC, (e) macrophage and (f) adipocyte proportions. Squares with error bars represent the standardised β coefficients and their 95% confidence intervals for association of ACE2 expression levels with each of the traits (derived from linear/linear mixed effects regression models), with the meta-analysis effect sizes and 95% confidence intervals (random-effects meta-analysis) shown as black diamonds. N represents the sample size for each analysis.

Fig. 3. Adipose tissue ACE2 expression in SARS-CoV-2 seropositive subjects.

Adipose tissue ACE2 expression residuals (adjusted for age, BMI and RNA-Seq technical covariates) are shown in SARS-CoV-2 seropositive TwinsUK participants who reported presenting one or more classic or severe COVID-19 symptoms compared to seropositive individuals who did not display any of the classic or severe COVID-19 symptoms. Boxplots display the median and inter-quartile range (IQR), with whiskers corresponding to ±1.5*IQR. Effect size and P value were calculated using a logistic regression model adjusting for current age and BMI.