| Title:
|
Abnormal Upregulation of Cardiovascular Disease Biomarker PLA2G7 Induced by Proinflammatory Macrophages in COVID-19 patients |
| Abstract:
|
BACKGROUND. Coronavirus disease 2019 (COVID-19) triggers distinct patterns of pneumonia progression with multiorgan disease calling for cell- and/or tissue-type specific host injury markers. METHODS. An integrated hypothesis-free single biomarker analysis framework was performed on nasal swabs (n=484) from patients with COVID-19 in GSE152075. The origin of candidate biomarker was assessed in single-cell RNA data (GSE145926). The candidate biomarker was validated in a cross-sectional cohort (n=564) at both nucletide and protein levels. RESULTS. Phospholipase A2 group VII (PLA2G7) was identified as a candidate biomarker in COVID-19. PLA2G7 was predominantly expressed by proinflammatory macrophages in lungs emerging with progression of COVID-19. In the validation stage PLA2G7 was found in patients with COVID-19 and pneumonia especially in severe pneumonia rather than patients suffered mild H1N1 influenza infection. The positive rates of PLA2G7 ranging from 29.37% to 100.00% were positively correlated with not only viral loads in patients with COVID-19 but also severity of pneumonia in non COVID-19 patients. Although Ct values of PLA2G7 in severe pneumonia was siginificantly lower than that in moderate pneumonia (P=7.2e-11) no differences were observed in moderate pneumonia with COVID-19 between severe pneumonia without COVID-19 (P=0.81). Serum protein levels of PLA2G7 also known as lipoprotein-associated phospholipase A2 (Lp-PLA2) were further found to be elevated and beyond the upper limit of normal in patients with COVID-19 especially among the re-positive patients. CONCLUSIONS. We firstly identified and validated PLA2G7 a biomarker for cardiovascular diseases (CVDs) was abnormally enhanced in COVID-19 patients at both nucletide and protein aspects. These findings provided indications into the prevalence of cardiovascular involvements seen in COVID-19 patients. PLA2G7 could be a hallmark of COVID-19 for monitoring disease progress and therapeutic response. |
| Published:
|
2020-08-18 |
| DOI:
|
10.1101/2020.08.16.20175505 |
| DOI_URL:
|
http://doi.org/10.1101/2020.08.16.20175505 |
| Author Name:
|
LI Y |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/li_y |
| Author Name:
|
JIANG Y |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/jiang_y |
| Author Name:
|
ZHANG Y |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/zhang_y |
| Author Name:
|
LI N |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/li_n |
| Author Name:
|
YIN Q |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/yin_q |
| Author Name:
|
LIU L |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/liu_l |
| Author Name:
|
LV X |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/lv_x |
| Author Name:
|
LIU Y |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/liu_y |
| Author Name:
|
LI A |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/li_a |
| Author Name:
|
FANG B |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/fang_b |
| Author Name:
|
LI J |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/li_j |
| Author Name:
|
YE H |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/ye_h |
| Author Name:
|
YANG G |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/yang_g |
| Author Name:
|
CUI X |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/cui_x |
| Author Name:
|
QU Y |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/qu_y |
| Author Name:
|
LI C |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/li_c |
| Author Name:
|
LI D |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/li_d |
| Author Name:
|
WANG S |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/wang_s |
| Author Name:
|
GAI Z |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/gai_z |
| Author Name:
|
ZHAN F |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/zhan_f |
| Author Name:
|
LIANG M |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/liang_m |
| sha:
|
134b2171a534e1b0157d02a57e21b9f2c4abdb7f |
| license:
|
medrxiv |
| source_x:
|
MedRxiv; WHO |
| source_x_url:
|
https://www.who.int/ |
| url:
|
https://doi.org/10.1101/2020.08.16.20175505
http://medrxiv.org/cgi/content/short/2020.08.16.20175505v1?rss=1 |
| has_full_text:
|
TRUE |
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https://doi.org/10.1101/2020.08.16.20175505 doi
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https://doi.org/10.1101/2020.08.16.20175505 doi |
| Extracted Text Content in Record:
|
First 5000 Characters:34
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel enveloped 67 RNA betacoronavirus that emerged in December 2019 in Wuhan, China, and is the 68 causative etiology of coronavirus disease 2019 (COVID-19)(1, 2). Typical clinical 69 presentation of COVID-19 was a lung involvement, as evidenced by image tests, with 70 fever, cough and dyspnea(3, 4). Severe cases often developed acute respiratory distress 71 syndrome (ARDS) or even death(3, 4). The risk factors for increased disease severity 72 in patients with COVID-19 has been reported as older age (e.g., over 50 years old) and 73 the presence of comorbidities, including hypertension, diabetes mellitus, cardiovascular 74 disease etc.(5, 6). However, it rapidly became obvious that severe COVID-19 can also 75 occur in younger patients with no pre-existing comorbidities(7). 76 77 On-going data characterizing immunological features in patients with COVID-19 were 78 starting to emerge. Host response to SARS-CoV-2 infection was distinct in comparison 79 with other highly pathogenic coronaviruses and common respiratory viruses in cell 80 lines(8). Notably, reduced type I interferon activities were observed in both in vitro (8) 81 and in vivo(9) data. Delayed production of type I interferon resulted in boosted 82 cytopathic effects (CPE) and increased sensing of SARS-COV-2 threats promoted the 83 enhanced release of monocyte chemoattractants, such as CCL2(10), which contributed 84 an influx of monocytes into lungs(7). Autopsy studies have shown diffuse thickening 85 of the alveolar wall with mononuclear cells and macrophages infiltrating airspaces(11). 86 However, it is still mysterious why there were various complications of 87 including impaired function of the organs, especially heart(7). Among 1,216 88 hospitalized COVID-19 patients across 69 countries who did not have pre-existing 89 heart complications, almost half showed scan abnormalities that resemble the early 90 stages of heart failure(12). 91 92 Hypothesis-free biomarker studies could allow researchers to gain in depth insights into 93 patho-mechanisms underlying COVID-19. Several attempts have been made. 94
Expression of monocyte CD169 (mCD169), also known as sialic acid binding Ig like 95 lectin 1 (SIGLEC1), has been suggested as a biomarker in the early diagnosis of 96 COVID-19(13). But expression of SIGLEC1 could be enhanced by other viruses(14). 97 . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.
is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted August 18, 2020. showed PLA2G7 was expressed principally by macrophages (Figure 2A is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted August 18, 2020. . https://doi.org/10.1101/2020.08.16.20175505 doi: medRxiv preprint 6 S10-11). It was worth of noting that the expression profile of PLA2G7 shared a close 161 pattern to SPP1 ( Figure 2D ), which played an important role in idiopathic pulmonary 162 fibrosis(28). Macrophages with FABP4, also known as the alveolar macrophages, were 163 reduced with progression of COVID-19 while macrophages with FCN1 and SPP1, 164 considered as the proinflammatory macrophages, were strikingly increased ( Figure 2E) . 165
In addition, strong correlation between expression of PLA2G7 and progression of 166 COVID-19 was discovered (r = 0.927, P = 1.4e-4) ( Figure 2F ). On the whole, PLA2G7 167 was predominantly expressed by these proinflammatory macrophages emerging along 168 with progression of COVID-19. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted August 18, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted August 18, 2020. . https://doi.org/10.1101/2020.08.16.20175505 doi: medRxiv preprint 8 necessary to better identify biomarkers, especially these represented the therapeutic and 224 diagnostic targets. It has been suggested that cytokine blood RNA level was not always 225 correlated with the protein plasma level(9). We therefore applied our previous 226 established hypothesis-free single biomarker analysis framework on nasal swabs from 227 more than 400 donors with COVID-19 in GSE152075. Finally, upregulated PLA2G7, 228 a biomarker for cardiovascular diseases (CVDs)(29), was identified as a hub gene in 229 SARS-COV-2 infection (Figure 1) . Coincidentally, phospholipase A2 Group IID 230 (PLA2G2D), belonged to the same PLA2 superfamily as PLA2G7 did, was considered 231 as an increase factor to result in worse outcomes of mice infected by SARS-CoV |
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