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. 2021 Jun 4;16(6):e0252799. doi: 10.1371/journal.pone.0252799

Plasma ACE2 predicts outcome of COVID-19 in hospitalized patients

Tue W Kragstrup 1,2,*, Helene Søgaard Singh 1, Ida Grundberg 3, Ane Langkilde-Lauesen Nielsen 1,4, Felice Rivellese 5, Arnav Mehta 6,7, Marcia B Goldberg 8,9, Michael R Filbin 10, Per Qvist 1,11,12, Bo Martin Bibby 13
Editor: Michael Bader14
PMCID: PMC8177449  PMID: 34086837

Abstract

Aims

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binds to angiotensin converting enzyme 2 (ACE2) enabling entrance of the virus into cells and causing the infection termed coronavirus disease of 2019 (COVID-19). Here, we investigate associations between plasma ACE2 and outcome of COVID-19.

Methods and results

This analysis used data from a large longitudinal study of 306 COVID-19 positive patients and 78 COVID-19 negative patients (MGH Emergency Department COVID-19 Cohort). Comprehensive clinical data were collected on this cohort, including 28-day outcomes. The samples were run on the Olink® Explore 1536 platform which includes measurement of the ACE2 protein. High admission plasma ACE2 in COVID-19 patients was associated with increased maximal illness severity within 28 days with OR = 1.8, 95%-CI: 1.4–2.3 (P < 0.0001). Plasma ACE2 was significantly higher in COVID-19 patients with hypertension compared with patients without hypertension (P = 0.0045). Circulating ACE2 was also significantly higher in COVID-19 patients with pre-existing heart conditions and kidney disease compared with patients without these pre-existing conditions (P = 0.0363 and P = 0.0303, respectively).

Conclusion

This study suggests that measuring plasma ACE2 is potentially valuable in predicting COVID-19 outcomes. Further, ACE2 could be a link between COVID-19 illness severity and its established risk factors hypertension, pre-existing heart disease and pre-existing kidney disease.

Introduction

Since December 2019, a previously undiscovered virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a devastating global pandemic. The disease caused by SARS-CoV-2 infection has been termed coronavirus disease of 2019 (COVID-19) with clinical manifestations ranging from asymptomatic and subclinical infection to severe hyperinflammatory syndrome and death [1]. Risk factors for fatal infection are male gender, increased age and comorbidities including pre-existing hypertension, heart disease, lung disease, diabetes, kidney disease and immune suppression [2, 3].

SARS-CoV-2 binds to the angiotensin converting enzyme 2 (ACE2) receptor enabling entrance into cells through membrane fusion and endocytosis [4–8]. The ACE2-receptor is distributed in different tissues including vascular endothelial cells, smooth muscle cells, nasal and oral mucosa, enterocytes within the intestines, and is especially abundant in the kidneys [9, 10] and type II alveolar pneumocytes in the lungs [11, 12]. This distribution explains possible entry routes for the virus, and why target cells such as the pneumocytes are highly vulnerable to viral infection [12].

ACE2 is part of the renin-angiotensin-aldosterone-system (RAAS). Renin cleaves angiotensinogen leading to formation of angiotensin I (Ang I). Ang I is then converted to the vasoconstricting angiotensin II (Ang II) through cleavage by angiotensin-converting-enzyme (ACE), which is found in the vascular endothelium and more plentifully in the pulmonary endothelium [13, 14]. ACE2 opposes the effects of the RAAS by cleavage of Ang II into angiotensin (1–7), thereby attenuating increases in blood pressure [15]. Dysregulation of RAAS is therefore implicated in many diseases including hypertension and kidney disease [14, 16].

ACE2 is a tissue enzyme and thus circulating levels are low; the significance of measuring circulating ACE2 in pathologic conditions remains uncertain [17–19]. However, circulating ACE2 is elevated in patients with active COVID-19 disease and in the period after infection [20–23]. Further, elevated circulating ACE2 has been measured in patients with risk factors for severe COVID-19 disease. In patients with heart failure, plasma levels of ACE2 were higher in men compared with women and in patients with aortic stenosis [24, 25]. Increased circulating ACE2 has also been associated with increased risk of major cardiovascular events [26]. Finally, ACE2 levels were recently shown to be significantly elevated in serum from smokers, obese and diabetic individuals [27]. Therefore, strategies to use soluble recombinant ACE2 as a treatment in COVID-19 are being investigated [28].

This study is the first description of the association between circulating ACE2 and disease outcomes in patients with COVID-19 disease. Data were obtained from a large longitudinal COVID-19 study [29], with a publicly-available dataset including proteomics provided by Olink Proteomics.

Methods

Study populations

Data were downloaded from https://www.olink.com/mgh-covid-study/ on 14 Sep 2020. A detailed description is available online (https://www.olink.com/mgh-covid-study/) (Fig 1) and has been published previously [29]. Subjects included patients 18 years or older, who were in acute respiratory distress with a clinical concern for COVID-19 upon arrival to the Emergency Department. Of the 384 patients enrolled, 306 (80%) tested positive and 78 tested negative for SARS-CoV-2. COVID-19-positive patients had blood samples drawn on days 0, 3, and 7, while virus-negative patients only had samples drawn on day 0. Clinical data collected included 28-day outcome classification based on the maximal illness severity (Acuity max, A1-A5) experience during the first 28 days after enrollment: A1 = Death. A2 = Intubated, ventilated, survived. A3 = Hospitalized, supplementary O2 required. A4 = Hospitalized, no supplementary O2 required. A5 = Discharged directly from ED and not subsequently hospitalized within 28 days. We also defined a dichotomous severity outcome with severe as A1-A2, and non-severe as A3-5. Discharged directly from ED and not subsequently hospitalized within 28 days [30]. Patient age, body mass index (BMI) and pre-existing medical conditions were recorded, including heart conditions (coronary artery disease, congestive heart failure, valvular disease), kidney disease (chronic kidney disease, baseline creatinine >1.5, end stage renal disease), lung disease (asthma, chronic obstructive lung disease, requiring home O2, any chronic lung condition), diabetes (pre-diabetes, insulin and non-insulin dependent diabetes), and immunosuppressive conditions (active cancer, chemotherapy, transplant, immunosuppressive agents, asplenia). Laboratory tests used in the analyses of this study were C-reactive protein (CRP), absolute neutrophil count, and D-dimer. Continuous variables were categorized to make the dataset anonymized. Age (years) categories were 1 = 20–34, 2 = 35–49, 3 = 50–64, 4 = 65–79, 5 = 80+. BMI (kg/m2) categories were 0 = <18.5 (underweight), 1 = 18.5–24.9 (normal), 2 = 25.0–29.9 (overweight), 3 = 30.0–39.9 (obese), 4 = 40+ (severely obese), 5 = Unknown (these were excluded from analysis on BMI). CRP (mg/L) categories were 1 = 0–19.9, 2 = 20–59.0, 3 = 60–99.9, 4 = 100–179, 5 = 180+. Absolute neutrophil count (109/L) categories were 1 = 0–0.99, 2 = 1.0–3.99, 3 = 4.0–7.99, 4 = 8.0–11.99, 5 = 12+. D-dimer (fibrinogen-equivalent units) categories were 1 = 0–499, 2 = 500–999, 3 = 1000–1999, 4 = 2000–3999, 5 = 4000+.

Fig 1. Diagram of study work flow.

Fig 1

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Link https://www.olink.com/mgh-covid-study/. Modified and used with permission.

COVID-19-negative subjects enrolled were older than COVID-19-positive patients, less Hispanic, and with greater baseline burden of chronic illnesses. Of the 78 COVID-19-negative subjects, 37 (47%) were diagnosed with non-COVID-19 pneumonia or acute lung injury (e.g., aspiration), 12 (15%) with congestive heart failure exacerbation, 6 (7.7%) with COPD exacerbation, 3 (3.8%) with acute pulmonary embolus, 11 (14%) with non-pulmonary sepsis or infection, and 8 (10%) with other illnesses. COVID-19-negative patients were significantly less inflamed than COVID-19-positive patients, median CRP 22 [IQR 9–67] versus 105 [IQR 48–161], p-value < 0.05, but illness acuity and outcomes were very similar between the two groups [29].

Ethics

Sample collection and analysis was approved by Partners Human Research Committee (PHRC). The need for informed consent was waived by this committee.

Quantification of ACE2 and Olink data analysis

Detailed description is available online (https://www.olink.com/mgh-covid-study/) (Fig 1) and has been published previously [29]. Briefly, the samples were analyzed by the Olink® Explore 1536 platform which includes measurement of the ACE2 protein. The Olink platform is based on Proximity Extension Assay (PEA) technology and has been validated previously [31]. Data generation consists of three main steps: normalization to known standard (extension control), log2-transformation, and level adjustment using the plate control. The generated data represent relative protein values, Normalized Protein eXpression (NPX), on a log2 scale where a larger number represents a higher protein level in the sample. For more information about Olink® Explore 1536, PEA and NPX, please visit www.olink.com.

Statistical analyses

Group comparisons were made using non-parametric tests. The diagnostic value of plasma ACE2 at baseline was further tested with a receiver operating characteristic (ROC) curve for severe (A1-A2) vs non-severe (A3-A5). The comparison of outcome group differences between COVID-19 positive and negative patients was done using a two-way ANOVA. The association between clinical outcome (response variable) and plasma ACE2 (explanatory variable) was also investigated using ordered logistic regression and results are presented as odds ratios (OR) for worse outcome scores per unit increase in plasma ACE2. The specific statistical method tests used for each analysis is described in the table and figure legends. For all tests, the level of significance was a two-sided P value of less than 0.05. Figures were made using GraphPad Prism 8 for Mac (GraphPad Software).

Results

Association between day 0 plasma ACE2 and worst clinical outcome group during the 28-day period in COVID-19 patients

First, we investigated the association between circulating ACE2 at day 0 and maximal acuity outcome group during the 28-day study period (Acuity max, A1-A5). Elevated baseline plasma ACE2 from COVID-19 patients was significantly associated with Acuity max with OR = 1.8, 95%-CI: 1.4–2.3 (P < 0.0001) (Table 1 and Fig 2A). The receiver operating characteristic (ROC) curve in Fig 2B depicts ability for ACE2 level at day 0 to discriminate severe (A1-A2) versus non-severe (A3-A5) outcome during the 28-day study period; the area under the curve (AUC) was 0.67, 95%-CI: 0.60–0.73. The association between circulating ACE2 at day 0 and Acuity max was also tested in regression models with correction for baseline characteristics, pre-existing medical conditions, and laboratory test results. In models correcting for age, body mass index, hypertension, and pre-existing heart conditions, kidney disease, lung disease, diabetes, and immunosuppressive conditions, significant associations were still observed between plasma ACE2 at day 0 and Acuity max (Table 1). Furthermore, we analyzed the association between plasma ACE2 at day 0 and Acuity max after correcting for CRP, absolute neutrophil count, and D-dimer to evaluate whether plasma ACE2 adds to the information already achieved by these laboratory test results. The association between elevated plasma ACE2 and Acuity max remained significant (Table 1).

Table 1. Associations between day 0 plasma ACE2 and maximal acuity within 28 days in COVID-19 positive patients in ordered logistic regression models.

Model n OR 95%-CI p
1 285 1.8 1.4–2.3 <0.0001
2 285 1.9 1.4–2.4 <0.0001
3 285 1.9 1.4–2.4 <0.0001
4 265 1.4 1.1–1.9 0.007
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The outcome is the maximum acuity score during the 28-day period with death (A1) being the highest acuity possible, and discharge without requiring admission within 28 days (A5) the least acuity possible.

Models (predictors): 1) Plasma ACE2. 2) Plasma ACE2, age, body mass index (BMI). 3) Plasma ACE2, age, body mass index (BMI), pre-existing hypertension, pre-existing heart disease, pre-existing lung disease, pre-existing kidney disease, pre-existing diabetes, pre-existing immunosuppressive condition. 4) Plasma ACE2, C-reactive protein (CRP), absolute neutrophile count, and D-dimer.

n = number of patients included in statistical analysis. OR = Odds ratio for a higher clinical outcome category per unit increase in plasma ACE2, 95%-CI = 95% confidence interval, p = p-value.

Fig 2. Day 0 plasma ACE2 in COVID-19 positive patients by clinical outcome group and ROC curve.

Fig 2

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A. Acuity max group is the maximum acuity score attained within the first 28 days with death being the maximum possible. A1 = Death within 28 days. A2 = Intubated, ventilated, survived to 28 days. A3 = Hospitalized, supplementary O2 required. A4 = Hospitalized, no supplementary O2 required. A5 = Discharged directly from ED and not subsequently hospitalized within 28 days. Data were analyzed using the Kruskal-Wallis test. Bars indicate median and interquartile range. **** P < 0.0001. B. Receiver operating characteristic (ROC) curve comparing severe outcome groups A1-A2 vs non-severe outcome groups A3-A5 during the 28-day period.

Association between plasma ACE2 at day 0, day 3, and day 7 and acuity group A2 (intubated) versus A3-A4 (not intubated) in hospitalized COVID-19 patients

Next, we tested whether circulating ACE2 at day 0, day 3, and day 7 was associated with clinical status at the time of blood sampling. Hospitalized patients were grouped according to outcome categories A2 (intubated at the time of sample collection) or A3-A4 (not intubated at the time of sample collection). Elevated plasma ACE2 in COVID-19 patients was significantly associated with higher acuity category at the time of blood sampling at day 0, day 3, and day 7 (P = 0.0004, P < 0.0001, and P < 0.0001, respectively) (Fig 3). We performed the same analysis in the patients with a plasma ACE2 measurement for all three time points (n = 130). In this analysis as well, plasma ACE2 in COVID-19 patients was significantly elevated in patients with outcome category A2 (intubated and survived) compared with outcome categories A3-A4 (not intubated) at the time of blood sampling at day 0, day 3, and day 7 (P = 0.0016, P < 0.0001, and P < 0.0001, respectively) (S1 Fig).

Fig 3. Plasma ACE2 in hospitalized COVID-19 positive patients segregated by acuity groups A2 (intubated) versus A3-A4 (not intubated).

Fig 3

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A. Day 0 plasma ACE2 in hospitalized COVID-19 positive patients by acuity groups A2 (intubated) or A3-A4 (not intubated) for day 0 study window (enrollment plus 24 hours). B. Day 3 plasma ACE2 in hospitalized COVID-19 positive patients by acuity groups A2 versus A3-A4 for day 3 study window. C. Day 7 plasma ACE2 in hospitalized COVID-19 positive patients by acuity groups A2 or A3-A4 for day 7 study window. Acuity categories: A2 = Intubated, ventilated. A3 = Hospitalized, supplementary O2 required. A4 = Hospitalized, no supplementary O2 required. Bars indicate median and interquartile range. Data were analyzed using the Mann Whitney test. *** P< 0.001. **** P < 0.0001.

Association between plasma ACE2 and comorbidities in COVID-19 patients

We then analyzed the relationship between ACE2 and comorbidities. Circulating ACE2 in COVID-19-positive patients with hypertension was significantly elevated compared with patients without hypertension (P = 0.0045) (Fig 4). Circulating ACE2 was also significantly elevated in patients with pre-existing heart conditions and in patients with pre-existing kidney disease compared with patients without these pre-existing conditions (P = 0.0363 and P = 0.0303, respectively) (Fig 4). There was no significant difference in plasma ACE2 comparing patients with or without pre-existing lung disease, diabetes, or immunosuppressive conditions (P = 0.953, P = 0.291, and P = 0.237, respectively) (Fig 4).

Fig 4. Plasma ACE2 in COVID-19-positive patients with comorbidities.

Fig 4

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A. Plasma ACE2 in COVID-19-positive patients with or without pre-existing hypertension. B. Plasma ACE2 in COVID-19-positive patients with or without pre-existing heart disease (coronary artery disease, congestive heart failure, valvular disease). C. Plasma ACE2 in COVID-19-positive patients with or without pre-existing lung disease (asthma, COPD, requiring home O2, any chronic lung condition). D. Plasma ACE2 in COVID-19-positive patients with or without pre-existing kidney disease (chronic kidney disease, baseline creatinine >1.5, ESRD). E. Plasma ACE2 in COVID-19-positive patients with or without pre-existing diabetes (pre-diabetes, insulin and non-insulin dependent diabetes). F. Plasma ACE2 in COVID-19-positive patients with or without pre-existing immunocompromised condition (active cancer, chemotherapy, transplant, immunosuppressant agents, asplenic). Data were analyzed using the Mann Whitney test. Bars indicate median and interquartile range. * P< 0.05. ** P< 0.01. ns = not significant.

Association of plasma ACE2 with age and BMI in COVID-19 patients

We further tested associations of circulating ACE2 with age and body mass index (BMI). Elevated plasma ACE2 in COVID-19-positive patients was significantly associated with increasing age (P = 0.0001) (Fig 5). There was no significant association between plasma ACE2 and BMI (P = 0.497) (Fig 5).

Fig 5. Plasma ACE2 in COVID-19-positive patients in relation to age and BMI.

Fig 5

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A. Plasma ACE2 in COVID-19-positive patients by age groups. B. Plasma ACE2 in COVID-19 positive patients by body mass index (BMI) groups. Data were analyzed using the Kruskal-Wallis test. *** P< 0.001. ns = not significant.

Association of day 0 plasma ACE2 with severe (A1-A2) versus non-severe (A3-A5) in COVID-19 positive and negative patients

Next, we analyzed whether circulating ACE2 differed between COVID-19 patients and non-COVID-19 patients with respiratory symptoms. Plasma ACE2 showed a clear overlap between the two groups. There was no significant difference between plasma ACE2 in COVID-19-positive versus negative patients (P = 0.13). Finally, we tested whether the association between plasma ACE2 and the maximal acuity score during the 28-day period was found in both COVID-19 positive and negative patients. The patients were grouped according to severe (A1-A2) or non-severe (A3-A5). Elevated plasma ACE2 in COVID-19-positive patients was significantly associated with maximal severity during the 28-day period (P < 0.0001), whereas there was no significant association between plasma ACE2 and outcome category in COVID-19 negative patients (P = 0.085) (Fig 6). To examine whether plasma ACE2 was differentially distributed among the clinical outcome groups in COVID-19-positive versus negative patients, we also conducted a two-way analysis of variance (ANOVA). Elevated plasma ACE2 was significantly associated with higher Acuity max during the 28-day period in COVID-19-positive patients and not in COVID-19-negative patients. However, differences were not statistically different (Table 2).

Fig 6. Plasma ACE2 and maximal acuity group during the 28-day period in COVID-19 positive and negative patients.

Fig 6

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A. Plasma ACE2 and outcome group in COVID-19-positive patients. B. Plasma ACE2 and outcome group in COVID-19 negative patients. The acuity group is the maximum acuity group during the 28-day period with death being the maximum possible. A1 = Death within 28 days. A2 = Intubated, ventilated, survived to 28 days. A3 = Hospitalized, supplementary O2 required. A4 = Hospitalized, no supplementary O2 required. A5 = Discharged directly from ED and not subsequently hospitalized within 28 days. Data were analyzed using the Mann Whitney test. Bars indicate median and interquartile range. **** P < 0.0001. ns = not significant.

Table 2. Associations between day 0 plasma ACE2 and maximal acuity group during the 28-day period (Acuity max) in COVID-19-positive and negative patients in two-way analysis of variance (ANOVA).

Outcome group A1-2 vs. A3-5 p 95%-CI
COVID-19-negative 0.33 0.15 -0.12–0.77
COVID-19-positive 0.49 <0.0001 0.27–0.71
Difference 0.16 0.52 -0.34–0.66
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Maximal acuity category at 28 days is the maximum score within first 28 days with death (A1) being the highest acuity possible, and discharge without requiring admission within 28 days (A5) the least acuity possible.

p = p-value, 95%-CI = 95% confidence interval.

Discussion

SARS-CoV-2 uses ACE2 as a functional receptor for entry into cells [32]. Circulating ACE2 is increased in patients with active COVID-19 infection compared with healthy controls [21–23]. Our analysis is the first description of circulating ACE2 in association with clinical outcomes in patients with COVID-19 disease. Data were obtained from a large longitudinal COVID-19 study with proteomics and clinical data, including disease severity evaluated through 28 days [29].

Elevated baseline plasma ACE2 in COVID-19 patients was significantly associated with increased disease severity during the 28-day study period. This indicates that abundant ACE2 production could be involved in increased viral spread and disease burden, as previously shown in experimental models of SARS-CoV infection [32, 33], with similar mechanisms postulated to be relevant for SARS-CoV-2 infection [34]. The association of elevated plasma ACE2 with higher clinical acuity and worse outcomes would in theory support blockade of ACE2 as a therapeutic strategy. ACE2 is expressed in the type II alveolar pneumocytes [12], which produce surfactant and act as progenitors for the type I alveolar pneumocytes [35]. The binding of the virus to ACE2 on the type II alveolar pneumocytes and subsequent infection leads to depletion of these cells, resulting in a decrease in the production and secretion of surfactant, as well as a lack of ability to regenerate and repair injured lung tissue, leading to the exacerbation of lung injury in severe COVID-19 [35, 36]. This interpretation is however not supported by findings in animal models, showing how ACE2 protects from severe acute lung injury induced by acid aspiration or sepsis [37]. After induction of severe acute lung injury through acid aspiration, ACE2-knockout mice had worsened oxygenation, massive pulmonary edema, and increased inflammatory cell infiltration compared to the wild type mice. In wild type mice, acid aspiration provoked a marked downregulation of ACE2 and an increase in Ang II levels without affecting ACE levels. In ACE2-knockout mice, Ang II levels increased to a greater extent, promoting further lung damage. Moreover, Ang II has been found to activate several cells within the immune system, such as macrophages, leading to a higher production of proinflammatory cytokines like IL-6 and TNFα [35, 36, 38]. Therefore, the direct blockade of ACE2, by removing the physiological brakes on the angiotensin system, could have detrimental effects on COVID-19 disease. For these reasons, an alternative strategy to inhibit the interaction of SARS-CoV-2 with ACE2 could be the administration of recombinant soluble ACE2 as a decoy receptor, which has been previously tested in small clinical trials in acute respiratory distress syndrome [39] and is now being explored in COVID-19 disease [40–42]. However, the level of circulating ACE2 does not necessarily reflect the expression of ACE2 in the plasma membrane of host cells. Thus, high levels of ACE2 in the plasma might result from increased lysis of ACE2-expressing cells as a consequence of a more severe infection.

It is desirable to predict disease outcomes in order to specialize treatment, since the drugs used in the treatment of COVID-19 can have deleterious side effects [43]. The ROC curve showed moderate value of baseline ACE2 levels for discriminating patients with severe (death or intubation) vs non-severe disease within 28 days. Further, difference in median plasma ACE2 levels between groups A2 (intubated, survived) versus A3-A4 (hospitalized but not intubated) increased over time on day 3 and day 7 of admission. Therefore, repeated analysis of plasma ACE2 may provide increased predictive value. This is in line with a recent study showing increasing SARS-CoV-2 viral load during hospitalization and prolonged viral shedding in more severe COVID-19 disease [44]. Further, it is interesting that the association between plasma ACE2 and maximal acuity within 28 days in COVID-19 patients was statistically significant also after correction for age, BMI, pre-existing medical conditions, and the laboratory tests CRP, absolute neutrophil count and D-dimer. This suggests that measuring plasma ACE2 adds to the value of clinically available data to help predict disease outcome in COVID-19. ACE2 is a membrane-bound enzyme, and therefore measuring the circulating and urine levels of ACE2 is complex [38]. Soluble ACE2 is the result of the cleavage of the membrane-bound ACE2 by disintegrin and metalloprotease 17. Interestingly, there is a correlation between plasma ACE1 activity and ACE2 activity in healthy individuals [45]. If this same correlation is seen in patients with COVID-19, plasma ACE1 levels (serum ACE) could be used to approximate the activity of ACE2 in COVID-19 positive patients. This is noteworthy because serum ACE analysis is a standardized test in most international hospitals.

Circulating ACE2 in COVID-19-positive patients with hypertension was significantly increased compared with plasma from patients without hypertension. Patients with hypertension are often treated with ACE-inhibitors and AT1R-blockers. During this pandemic, it has been highly debated whether or not the use of these antihypertensive medications should be discontinued in patients with COVID-19. A study performed on rats showed that the use of ACE inhibitors and/or use of AT1R-blocker led to an increased expression of ACE2 in cardiac tissue [46]. Others found a decrease of kidney ACE2 expression and no effect on lung ACE2 expression with ACE-inhibitors and AT1R-blockers [47]. These findings have raised the concern that patients with hypertension, who are treated with ACE2-modulating drugs like ACE-inhibitors or AT1R-blockers might be at a higher risk for severe COVID-19 infection, since it could alter the entry-way for the virus [48]. A recent study showed that plasma ACE2 activity is increased in COVID-19 patients treated with ACE inhibitors [49]. However, more severe COVID-19 disease in patients treated with ACE-inhibitors or AT1R-blockers has not been supported by recent population based data [50]. Circulating ACE2 was also significantly increased in patients with pre-existing heart conditions and in patients with pre-existing kidney disease. This is in line with the central role of RAAS in these conditions. Importantly, the changes in circulating ACE2 in COVID-19 disease observed here are small and are likely not to be of any significance regarding the metabolism of the substrates of ACE2.

In contrast, differences in plasma ACE2 does not seem to explain the risk of severe COVID-19 disease associated with pre-existing lung disease, diabetes, or immunosuppression. Plasma ACE2 was associated with age, which is in line with recent observations showing higher serum levels of ACE2 in adults compared to a pediatric cohort [51]. There were no associations between plasma ACE2 and BMI.

Baseline plasma ACE2 was not significantly different between COVID-19-positive and negative patients, which is in line with the results of a recent study with a much smaller sample size [52]. The association between elevated plasma ACE2 and maximal acuity within 28 days were more pronounced in COVID-19-positive patients compared with COVID-19-negative patients, but the difference was not significant in a two-way ANOVA analysis. It is therefore not possible with this dataset to conclude that the observed association between circulating ACE2 and disease outcome is specific to patients with COVID-19-positive respiratory disease.

There are some overall limitations of this study. First, plasma ACE2 was measured as relative protein concentrations using NPX (Normalized Protein eXpression) values. Therefore, it is not possible to determine a plasma ACE2 cut-off value to predict severe outcome or to compare findings in this study with results in studies measuring protein concentration or enzymatic activity. Second, several continuous variables were categorized in the publicly available data set. This decreases the statistical power of some of the analysis. Third, some potentially important variables such as gender and treatment were not available. Fourth, severity driven recruitment criteria (respiratory distress at emergency department) might have introduced a bias. Thus, patients with more severe COVID-19 at admission have both higher ACE2 at time of inclusion and a poorer prognosis. However, our study reflects clinical practice where laboratory tests are performed when patients are admitted to the hospital. Finally, causality of associations between plasma ACE2 and severity of COVID-19 disease cannot be drawn from this study.

Conclusions

Overall, this study suggests a potential utility of measuring ACE2 in COVID-19 to predict disease outcome. Further, circulating ACE2 could be a link between severe COVID-19 disease and its risk factors, namely hypertension, pre-existing heart disease and pre-existing kidney disease. The design of the data analysis using the Olink platform does not allow assessment of quantitative differences. However, previous studies have described a positive correlation between plasma ACE2 and ACE1 activity. This is interesting because ACE1 (serum ACE) analysis is a standardized test in most hospital laboratories. Therefore, our study encourages quantitative investigations of both plasma ACE 1 and 2 in COVID-19.

Supporting information

S1 Fig. Plasma ACE2 in hospitalized COVID-19 positive patients with samples analyzed at all time points divided in clinical outcome groups 2 (intubated) or 3–4 (not intubated).

A. Day 0 plasma ACE2 in hospitalized COVID-19 positive patients divided in outcome groups 2 (intubated) or 3–4 (not intubated) for day 0 study window (enrollment plus 24 hours). B. Day 3 plasma abundance of ACE2 in hospitalized COVID-19 positive patients divided in outcome groups 2 (intubated) or 3–4 (not intubated) for day 3 study window. C. Day 7 plasma ACE2 in hospitalized COVID-19 positive patients divided in outcome groups 2 (intubated) or 3–4 (not intubated) for day 7 study window. The acuity groups: 2 = Intubated, ventilated. 3 = Hospitalized, supplementary O2 required. 4 = Hospitalized, no supplementary O2 required. Bars indicate median and interquartile range. Data were analyzed using the Mann Whitney test. ** P< 0.01. **** P < 0.0001.

(DOCX)

Click here for additional data file. (194.3KB, docx)

Acknowledgments

Data provided by the MGH Emergency Department COVID-19 Cohort (Filbin, Goldberg, Hacohen) with Olink Proteomics. We want to thank Aparna Udupi, Department of Biostatistics, Aarhus University for technical assistance running the statistical analyses.

Abbreviations

ACE

Angiotensin converting enzyme

Ang I

Angiotensin I

Ang II

Angiotensin II

ANOVA

Analysis of variance

AT1R

Type 1 angiotensin II receptor

AUC

Area under the curve

BMI

Body mass index

CoV

Coronavirus

COVID-19

Corona virus disease 2019

CRP

C-reactive protein

IL

Interleukin

NPX

Normalized Protein eXpression

PEA

Proximity extension assay

RAAS

Renin-angiotensin-aldosterone-system

ROC

receiver operating characteristic

SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2

TNF

Tumor necrosis factor

Data Availability

Data is available from https://www.olink.com/mgh-covid-study/.

Funding Statement

American Lung Association COVID-19 Action Initiative award (MBG). Independent Research Fund Denmark clinician scientist award (9039-00015B, TWK). Olink Proteomics financed and performed the proteomics assays presented in this work as part of the collaboration with Massachusetts General Hospital (MGH and the Broad Institute on the MGH Emergency Department COVID-19 Cohort. Olink Proteomics provided support in the form of salaries for IG, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of all authors are articulated in the ‘author contributions’ section.

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Decision Letter 0

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PONE-D-21-06434

Plasma ACE2 levels predict outcome of COVID-19 in hospitalized patients

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Reviewer #2: Yes

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Reviewer #1: In the current paper, the authors investigate the link of ACE2 signals obtained from a proximal extension assay multiplex panel in a cohort of 306 COVID-19 patients and 78 SARS-CoV-2 negative controls. The authors suggest a link between baseline signals for ACE2 obtained from a commercially available proximal extension assay and the outcome of COVID-19 disease. The findings are interesting and in-line with previous observations regarding ACE2 regulation during COVID-19. The authors should also check for more recent literature on the topic, describing a link between soluble ACE2 activity and COVID-19 severity.

The aspect of a prognostic value of baseline ACE2 for COVID-19 outcome appears to be interesting at the first glance, but considering the design of the clinical readout, it might be introduced by the fact that "Day 0" in the current study was actually the admission to the emergency department respiratory distress, which could happen at very variable time points related to disease onset. Knowing that COVID-19 severity is linked to plasma ACE2 activity with a peak in concentrations between 1 and 2 weeks after disease onset, severity driven recruitment criteria (respiratory distress at emergency department) might have introduces a certain bias, as more severe cases have higher ACE2 at time of inclusion, with obviously having poorer outcomes.

In other words, patients being included with a more severe disease manifestation ion day 0 (e.g. higher ACE2), may just be at another time-point in the course of COVID-19 disease, with an already pre-determined worse outcome. It would add a lot of valuer to the study, if the measurement time points would be related to the time of symptom onset, first positive test result or any other earlier time point that may would assure the direct comparability of disease severity groups. The authors should further describe the control group of 78 Covid-negative patients described more clearly. Why did these patients at emergency units with respiratory distress?

Finally, the use of terminology within the whole paper is misleading, as the authors keep using the terms "ACE2 levels" and "ACE2 concentrations". Of note, the result of the proximal extension assay the authors used as a basis for their interpretation is given in the form of an artificial unit (NPX), that has been calculated by the manufacturer by arithmetically linking a series of Ct value based correction algorithms. Even the manufacturers point out on their webpage that the given readout cannot be compared to actual protein levels, which disables comparability to other studies.

From a technical perspective, the big open question is why no calibration of the readout is performed to be able to provide actual protein levels. With a highly reproducible and standardized method as described by the manufacturers on their webpage, it should be easy to retrospectively include a valid calibration allowing for providing actual ACE2 concentrations instead of manufacturer invented units that prevent comparability with other studies. Moreover, a certain analytical validation vor ACE2 in the used PEA panel should be shown that compares the used "NPX" values with real concentration units or standard activity units in a defined set of clinical samples. It should also be noted that reading the method section needs some revision as it currently reads like an advertisement for the used (commercially available) technology rather than an objective method description to be published in a research paper.

Reviewer #2: .This study investigated the association between plasma ACE2 levels and outcomes of COVID-19 patients, using clinical data and plasma samples from 306 COVID-19 positive and 76 COVID-19 negative patients. High baseline plasma ACE2 levels are reported to be associated with worse COVID-19 outcomes and patients with hypertension, pre-existing heart conditions or kidney disease had higher plasma ACE2 levels than those without.

Even as a marker I doubt very much that it will be useful for COVID-19 because the changes found in figure 2 are so small.

Main criticisms and suggestions for improvement:

- Overall, the paper is an excellent contribution but the authors should acknowledge the limitations of measurements of ACE2 in plasma where the levels are usually very low and even when mildly elevated in pathological conditions the significance remains uncertain. Specifically, it must be stated that ACE2 is a tissue enzyme and that the levels in the circulation are low in all species studied, including humans. Appropriate references should be given.

Please acknowledge that the changes in COVID-19 are so small that they are not likely to be of any significance regarding the metabolism of the substrates of ACE2

- In the introduction the part on ACE2 receptor distribution must be modified to include the kidney as a main site of ACE2 . The authors do not seem aware of a critical important observation, namely that the expression of ACE2 in the lung is very low as shown by Serfozo et al using western blot and confirmed by others

See https://doi.org/10.1161/HYPERTENSIONAHA.119.14071 and https://doi.org/10.1038/s41467-020-19145-6

These references must be cited as well as others showing that the kidney is next to the intestine the organ that has the highest abundance of ACE2.

- Perhaps the authors are not aware that ACE2 RNA levels do not necessarily imply protein levels. Actually, ACE2 can be post translationally regulated and be increased when the levels of mRNA are not. The authors may consult and cite a review on this by Lores et al. https://doi.org/10.1042/CS20200484

- In the discussion it is stated that “ACE2 as a decoy receptor… is now being explored in COVID-19 disease.” Appropriate references should be given to be faithful to the literature. Perhaps they are not aware of these papers because they are recent but they should be cited. For instance, https://doi.org/10.1042/CS20200163 and https://doi.org/10.1681/ASN.2020101537

- “A study performed on rats showed that the use of ACE inhibitors and/or use of AT1R-blocker led to an increased expression of ACE2”. It should be specified that in ref 34 ACE2 was only examined in cardiac tissue and not kidney or lung. Others found a decrease of kidney ACE2 after ACEi and ARBs and no effect on lungs. For instance, see https://doi.org/10.1681/ASN.2020050667

- “The population sampled on day 3 and day 7 therefore consists of patients with more severe disease compared with day 0.” Maybe ACE2 for day 3 and day 7 should be shown in a way that they are only compared to their matching samples of day 0?

**********

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PLoS One. 2021 Jun 4;16(6):e0252799. doi: 10.1371/journal.pone.0252799.r002

Author response to Decision Letter 0

20 May 2021

Response letter

Dear editor and reviewers,

We are very pleased with a constructive review of our paper. We readily acknowledge that reviewers have in depth knowledge on ACE2 physiology and the role of this protein in COVID-19 disease. We are therefore very happy to accommodate all suggestions made by the reviewers.

Three native speaking authors have carefully proof read the manuscript. This included a few changes worth mentioning.

1) The Odds ratios have been inverted to report odds ratios for a smaller category instead of a larger category. Seems like it would make more intuitive sense to have higher severity as the primary outcome in analyses. The text as written supports this approach.

2) Fig 2B has been changed to better align with the other figures (no colors).

We have made two general corrections throughout the manuscript based on reviewer suggestions and co-author comments after seeing the review. These changes are not highlighted in the manuscript because the corrections are found abundantly throughout.

1) As suggested by reviewer #1 we have replaced all mentions of ”levels” and ”concentrations” with ”plasma ACE2” or ”circulating ACE2”.

2) We have also systematically changed the terminology of the disease groups from “WHO groups” to “clinical outcome groups/Acuity groups”. “WHO groups” was part of the publicly available information downloaded from the source link at the Olink website. However, the scores were not based on the WHO Outcome scale. This is because COVID19 is not treated with non-invasive ventilation or high-flow nasal cannula (therefore, no patients were categorized in previous group 3). The group definitions are the same but have been renamed accordingly. 1 = Death. 2 = Intubated, ventilated, survived. 3 = Hospitalized, supplementary O2 required. 4 = Hospitalized, no supplementary O2 required. 5 = Not hospitalized. These changes are not highlighted in the manuscript.

All other changes have been highlighted in the revised manuscript.

We believe the paper has been greatly improved. Thank you.

On behalf of the authors,

Tue Wenzel Kragstrup

Tue Wenzel Kragstrup

Associate Professor, MD, PhD

E-mail: kragstrup@biomed.au.dk

Biomedicine, Health

Aarhus University

Wilhelm Meyers Alle 4, 4fl.

DK-8000 Aarhus C

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Response: The data is fully available without restriction and can be downloaded from https://www.olink.com/mgh-covid-study/. This has been highlighted in the Methods section.

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Reviewer #1: In the current paper, the authors investigate the link of ACE2 signals obtained from a proximal extension assay multiplex panel in a cohort of 306 COVID-19 patients and 78 SARS-CoV-2 negative controls. The authors suggest a link between baseline signals for ACE2 obtained from a commercially available proximal extension assay and the outcome of COVID-19 disease. The findings are interesting and in-line with previous observations regarding ACE2 regulation during COVID-19. The authors should also check for more recent literature on the topic, describing a link between soluble ACE2 activity and COVID-19 severity.

Response: We would like to thank the Reviewer for taking time to carefully read our paper. We agree with all his/her comments. We believe that we have addressed all comments and this is a great improvement to the manucript.

We reviewed the literature again and found the very recent publications below evaluating circulating ACE2 in COVID-19. They have been cited in the manuscript.

Lundström A, Ziegler L, Havervall S, Rudberg A-S, von Meijenfeldt F, Lisman T, et al. Soluble angiotensin-converting enzyme 2 is transiently elevated in COVID-19 and correlates with specific inflammatory and endothelial markers. medRxiv. 2021:2021.03.03.21252841. doi: 10.1101/2021.03.03.21252841.

Nagy B, Jr., Fejes Z, Szentkereszty Z, Suto R, Varkonyi I, Ajzner E, et al. A dramatic rise in serum ACE2 activity in a critically ill COVID-19 patient. Int J Infect Dis. 2021;103:412-4. Epub 2020/11/30. doi: 10.1016/j.ijid.2020.11.184. PubMed PMID: 33249290;

van Lier D, Kox M, Santos K, van der Hoeven H, Pillay J, Pickkers P. Increased blood angiotensin converting enzyme 2 activity in critically ill COVID-19 patients. ERJ Open Res. 2021;7(1). Epub 2021/03/20. doi: 10.1183/23120541.00848-2020.

Fagyas M, Kertesz A, Siket IM, Banhegyi V, Kracsko B, Szegedi A, et al. Level of the SARS-CoV-2 receptor ACE2 activity is highly elevated in old-aged patients with aortic stenosis: implications for ACE2 as a biomarker for the severity of COVID-19. Geroscience. 2021. Epub 2021/01/21. doi: 10.1007/s11357-020-00300-2.

And per request from reviewer #2 we added these publications better refelcting the current litterature:

Lores E, Wysocki J, Batlle D. ACE2, the kidney and the emergence of COVID-19 two decades after ACE2 discovery. Clin Sci (Lond). 2020;134(21):2791-2805.

Lee IT, Nakayama T, Wu CT, et al. ACE2 localizes to the respiratory cilia and is not increased by ACE inhibitors or ARBs. Nat Commun. 2020;11(1):5453.

Serfozo P, Wysocki J, Gulua G, et al. Ang II (Angiotensin II) Conversion to Angiotensin-(1-7) in the Circulation Is POP (Prolyloligopeptidase)-Dependent and ACE2 (Angiotensin-Converting Enzyme 2)-Independent. Hypertension. 2020;75(1):173-182.

Batlle D, Wysocki J, Satchell K. Soluble angiotensin-converting enzyme 2: a potential approach for coronavirus infection therapy? Clin Sci (Lond). 2020;134(5):543-545.

Wysocki J, Ye M, Hassler L, et al. A Novel Soluble ACE2 Variant with Prolonged Duration of Action Neutralizes SARS-CoV-2 Infection in Human Kidney Organoids. J Am Soc Nephrol. 2021.

Epelman S, Shrestha K, Troughton RW, et al. Soluble angiotensin-converting enzyme 2 in human heart failure: relation with myocardial function and clinical outcomes. J Card Fail. 2009;15(7):565-571.

Tikellis C, Bialkowski K, Pete J, et al. ACE2 deficiency modifies renoprotection afforded by ACE inhibition in experimental diabetes. Diabetes. 2008;57(4):1018-1025.

Yamaleyeva LM, Gilliam-Davis S, Almeida I, Brosnihan KB, Lindsey SH, Chappell MC. Differential regulation of circulating and renal ACE2 and ACE in hypertensive mRen2.Lewis rats with early-onset diabetes. Am J Physiol Renal Physiol. 2012;302(11):F1374-1384.

Wysocki J, Lores E, Ye M, Soler MJ, Batlle D. Kidney and Lung ACE2 Expression after an ACE Inhibitor or an Ang II Receptor Blocker: Implications for COVID-19. J Am Soc Nephrol. 2020;31(9):1941-1943.

The aspect of a prognostic value of baseline ACE2 for COVID-19 outcome appears to be interesting at the first glance, but considering the design of the clinical readout, it might be introduced by the fact that "Day 0" in the current study was actually the admission to the emergency department respiratory distress, which could happen at very variable time points related to disease onset. Knowing that COVID-19 severity is linked to plasma ACE2 activity with a peak in concentrations between 1 and 2 weeks after disease onset, severity driven recruitment criteria (respiratory distress at emergency department) might have introduces a certain bias, as more severe cases have higher ACE2 at time of inclusion, with obviously having poorer outcomes. In other words, patients being included with a more severe disease manifestation ion day 0 (e.g. higher ACE2), may just be at another time-point in the course of COVID-19 disease, with an already pre-determined worse outcome. It would add a lot of valuer to the study, if the measurement time points would be related to the time of symptom onset, first positive test result or any other earlier time point that may would assure the direct comparability of disease severity groups.

Response: We agree with this comment. However, we are not able to get access to a longitudinal study of samples included at symptom onset or at the time of a positive test result. We have included the comment from the reviewer in the discussion because it is obviously a limitation to the study (page 22 line 16). We also mention that our study likely reflects clinical pratice were prognostic tests will not be carried our with no or mild symptoms. We would like to thank the Reviewer for bringing up this relevant point.

”Fourth, severity driven recruitment criteria (respiratory distress at emergency department) might have introduces a bias. Thus, patients with more severe COVID-19 at admission have both higher ACE2 at time of inclusion and a poorer prognosis. However, our study reflects clinical practice where laboratory tests are performed when patients are admitted to the hospital.”

The authors should further describe the control group of 78 Covid-negative patients described more clearly. Why did these patients at emergency units with respiratory distress?

Response: We agree with this comment. We included a description of the control group as below, while we are also referencing the original study where full patient characteristics are provided (page 7 line 5).

”COVID-19-negative subjects enrolled were older than COVID-19-positive patients, less Hispanic, and with greater baseline burden of chronic illnesses. Of the 78 COVID-19-negative subjects, 37 (47%) were diagnosed with non-COVID-19 pneumonia or acute lung injury (e.g., aspiration), 12 (15%) with congestive heart failure exacerbation, 6 (7.7%) with COPD exacerbation, 3 (3.8%) with acute pulmonary embolus, 11 (14%) with non-pulmonary sepsis or infection, and 8 (10%) with other illnesses. COVID-19-negative patients were significantly less inflamed than COVID-19-positive patients, median CRP 22 [IQR 9-67] versus 105 [IQR 48-161], p-value < 0.05, but illness acuity and outcomes were very similar between the two groups.”

Finally, the use of terminology within the whole paper is misleading, as the authors keep using the terms "ACE2 levels" and "ACE2 concentrations". Of note, the result of the proximal extension assay the authors used as a basis for their interpretation is given in the form of an artificial unit (NPX), that has been calculated by the manufacturer by arithmetically linking a series of Ct value based correction algorithms. Even the manufacturers point out on their webpage that the given readout cannot be compared to actual protein levels, which disables comparability to other studies. From a technical perspective, the big open question is why no calibration of the readout is performed to be able to provide actual protein levels. With a highly reproducible and standardized method as described by the manufacturers on their webpage, it should be easy to retrospectively include a valid calibration allowing for providing actual ACE2 concentrations instead of manufacturer invented units that prevent comparability with other studies. Moreover, a certain analytical validation vor ACE2 in the used PEA panel should be shown that compares the used "NPX" values with real concentration units or standard activity units in a defined set of clinical samples.

Response: We of course agree with these limitations. Unfortunately, many factors hinder us in generating actual protein concentrations. The manufacturer cannot generate protein levels from current data, we are not able to re-analyse the same samples in a different assay, and we are not in a position to collect samples from a validation cohort. We highlighted this in the limitations as described below (page 22 line 10). We have also reworded all mentions of ”levels” and ”concentrations” with ”plasma ACE2” or ”circulating ACE”.

“The plasma ACE2 levels were measured as relative protein concentrations using NPX (Normalized Protein eXpression) values. Therefore, it is not possible to determine a plasma ACE2 cut-off value to predict severe outcome or to compare findings in this study with results in studies measuring protein concentration or enzymatic activity.”

It should also be noted that reading the method section needs some revision as it currently reads like an advertisement for the used (commercially available) technology rather than an objective method description to be published in a research paper.

Response: We specifically referred to the website where the data is publicly available, although we agree that the methods should be tailored for scientists and we have therefore removed the unnecessary text about the technology. Thanks for this comment.

”Detailed description is available online (https://www.olink.com/mgh-covid-study/) (Fig 1) and has been published previously.[29] Briefly, the samples were analyzed by the Olink® Explore 1536 platform which includes measurement of the ACE2 protein. The Olink platform is based on Proximity Extension Assay (PEA) technology and has been validated previously.[31] Data generation consists of three main steps: normalization to known standard (extension control), log2-transformation, and level adjustment using the plate control. The generated data represent relative protein values, Normalized Protein eXpression (NPX), on a log2 scale where a larger number represents a higher protein level in the sample. For more information about Olink® Explore 1536, PEA and NPX, please visit www.olink.com.”

Reviewer #2: .This study investigated the association between plasma ACE2 levels and outcomes of COVID-19 patients, using clinical data and plasma samples from 306 COVID-19 positive and 76 COVID-19 negative patients. High baseline plasma ACE2 levels are reported to be associated with worse COVID-19 outcomes and patients with hypertension, pre-existing heart conditions or kidney disease had higher plasma ACE2 levels than those without.

Even as a marker I doubt very much that it will be useful for COVID-19 because the changes found in figure 2 are so small.

Response: We would like to thank the Reviewer for taking the time to help improving our manuscript. We really appreciate it. We agree with the comment that changes in ACE2 are small. Our study will require validation by others in assays designed to measure protein concentration or as mentioned further investigation with measuring ACE(1) as mentioned in the paper. We have reviewed our discussion and believe that the conclusions are balanced and in line with the reviewers comments, particularly as we have now included additional limitations of the study.

Main criticisms and suggestions for improvement:

- Overall, the paper is an excellent contribution but the authors should acknowledge the limitations of measurements of ACE2 in plasma where the levels are usually very low and even when mildly elevated in pathological conditions the significance remains uncertain. Specifically, it must be stated that ACE2 is a tissue enzyme and that the levels in the circulation are low in all species studied, including humans. Appropriate references should be given.

Response: Thank you for the comment. We completely agree that citing previous studies on measuring circulating ACE2 levels is a valuable adition. We have now added the following referneces and included a comment to highlight the limitation that ACE2 levels in circulations are low (page 4 line 22).

Epelman S, Shrestha K, Troughton RW, et al. Soluble angiotensin-converting enzyme 2 in human heart failure: relation with myocardial function and clinical outcomes. J Card Fail. 2009;15(7):565-571.

Tikellis C, Bialkowski K, Pete J, et al. ACE2 deficiency modifies renoprotection afforded by ACE inhibition in experimental diabetes. Diabetes. 2008;57(4):1018-1025.

Yamaleyeva LM, Gilliam-Davis S, Almeida I, Brosnihan KB, Lindsey SH, Chappell MC. Differential regulation of circulating and renal ACE2 and ACE in hypertensive mRen2.Lewis rats with early-onset diabetes. Am J Physiol Renal Physiol. 2012;302(11):F1374-1384.

”ACE2 is a tissue enzyme and circulation levels are low and the significance of measuring circulating ACE2 in pathologic conditions remains uncertain.”

Please acknowledge that the changes in COVID-19 are so small that they are not likely to be of any significance regarding the metabolism of the substrates of ACE2

Response: Thank you for bringing this to our attention. We did not consider this previously. It is an important perspective. We have mentioned this in the Discussion with the below wording (page 21 line 19):

”Importantly, changes in ACE2 levels in COVID-19 disease observed here are small and are likely not to be of any significance regarding the metabolism of the substrates of ACE2.”

- In the introduction the part on ACE2 receptor distribution must be modified to include the kidney as a main site of ACE2 . The authors do not seem aware of a critical important observation, namely that the expression of ACE2 in the lung is very low as shown by Serfozo et al using western blot and confirmed by others

See https://doi.org/10.1161/HYPERTENSIONAHA.119.14071 and https://doi.org/10.1038/s41467-020-19145-6

These references must be cited as well as others showing that the kidney is next to the intestine the organ that has the highest abundance of ACE2.

Response: We agree and have added the below sentence including the mentioned references (page 4 line 12).

- Perhaps the authors are not aware that ACE2 RNA levels do not necessarily imply protein levels. Actually, ACE2 can be post translationally regulated and be increased when the levels of mRNA are not. The authors may consult and cite a review on this by Lores et al. https://doi.org/10.1042/CS20200484

Response: We would like to thank the reviewer for underlining this, we have now included this important reference. However, the Olink assay measures protein, albeit with all the limitations already discussed above, therefore we did not measure RNA levels of ACE2.

- In the discussion it is stated that “ACE2 as a decoy receptor… is now being explored in COVID-19 disease.” Appropriate references should be given to be faithful to the literature. Perhaps they are not aware of these papers because they are recent but they should be cited. For instance, https://doi.org/10.1042/CS20200163 and https://doi.org/10.1681/ASN.2020101537

Response: Thank you very much for bringing these references to our attention. Indeed, we were not aware of this progress. We have included both citations.

- “A study performed on rats showed that the use of ACE inhibitors and/or use of AT1R-blocker led to an increased expression of ACE2”. It should be specified that in ref 34 ACE2 was only examined in cardiac tissue and not kidney or lung. Others found a decrease of kidney ACE2 after ACEi and ARBs and no effect on lungs. For instance, see https://doi.org/10.1681/ASN.2020050667

Response: Again we can only thank the reviewer for updating us and improving the manuscript. We have included this in the paper.

”Others found a decrease of kidney ACE2 expression and no effect on lung ACE2 expression with ACE-inhibitors and AT1R-blockers.”

- “The population sampled on day 3 and day 7 therefore consists of patients with more severe disease compared with day 0.” Maybe ACE2 for day 3 and day 7 should be shown in a way that they are only compared to their matching samples of day 0?

Response: Thank you for this suggestion. We agree that this gives a nice representation of the data. We have included this in the Results section and shown data as Supplementary figure S1. The results are the same. We have therefore removed the above mentioned sentance in the Discussion.

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Decision Letter 1

Michael Bader

24 May 2021

Plasma ACE2 predicts outcome of COVID-19 in hospitalized patients

PONE-D-21-06434R1

Dear Dr. Kragstrup,

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Acceptance letter

Michael Bader

26 May 2021

PONE-D-21-06434R1

Plasma ACE2 predicts outcome of COVID-19 in hospitalized patients

Dear Dr. Kragstrup:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Plasma ACE2 in hospitalized COVID-19 positive patients with samples analyzed at all time points divided in clinical outcome groups 2 (intubated) or 3–4 (not intubated).

    A. Day 0 plasma ACE2 in hospitalized COVID-19 positive patients divided in outcome groups 2 (intubated) or 3–4 (not intubated) for day 0 study window (enrollment plus 24 hours). B. Day 3 plasma abundance of ACE2 in hospitalized COVID-19 positive patients divided in outcome groups 2 (intubated) or 3–4 (not intubated) for day 3 study window. C. Day 7 plasma ACE2 in hospitalized COVID-19 positive patients divided in outcome groups 2 (intubated) or 3–4 (not intubated) for day 7 study window. The acuity groups: 2 = Intubated, ventilated. 3 = Hospitalized, supplementary O2 required. 4 = Hospitalized, no supplementary O2 required. Bars indicate median and interquartile range. Data were analyzed using the Mann Whitney test. ** P< 0.01. **** P < 0.0001.

    (DOCX)

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    Attachment

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    Data Availability Statement

    Data is available from https://www.olink.com/mgh-covid-study/.

    Articles from PLoS ONE are provided here courtesy of PLOS

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