A Preliminary Study on Blood Lipid Prole in Patients with COVID-19

Background: Recently, dyslipidemia was observed in the patients with coronavirus disease 2019 (COVID-19). This study aimed to investigate the blood lipid prole in the patients with COVID-19, and explore their predictive value for COVID-19 severity. Methods: 142 consecutive patients with COVID-19 admitted to HwaMei Hospital, University of Chinese Academy of Sciences, from January 23 to April 20, 2020, and 77 age- and gender-matched healthy subjects were included in this retrospective study. The blood lipid prole in the patients with COVID-19 were investigated, and their predictive values for COVID-19 severity were analysed. Results: There were 125 and 17 cases in the non-severe and severe group, respectively. Total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and apolipoprotein A1 (ApoA1) gradually decreased across healthy controls, non-severe group, and severe group. ApoA1 was recognized as an independent risk factor for COVID-19 severity (cid:0) and had the highest area under the receiver operator characteristic curve (AUC) among all the single markers (AUC: 0.896, 95% CI: 0.834-0.941). Moreover, the risk model established using ApoA1 and IL-6 enhanced the prediction eciency (AUC: 0.977, 95% CI: 0.932-0.995). Conclusion: The blood lipid prole in the patients with COVID-19 is quite abnormal from healthy subjects, especially in the severe cases. Serum ApoA1 might serve as a good indictor to reect the severity of COVID-19. COVID-19: coronavirus disease 2019, HDL-C: high-density lipoprotein cholesterol, LDL-C: low-density lipoprotein cholesterol, ApoA1: apolipoprotein IL-6: interleukin-6.


Introduction
The recently emerged pathogenic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible coronavirus that has caused an ever-increasing number of Coronavirus Disease 2019 (COVID- 19) infections since December 2019 and spread rapidly worldwide. Although approximately 80% patients infected with SARS-CoV2 exhibit mild symptoms [1], the remaining severe cases may experience acute respiratory distress, multi-organ failure and loss of life [2]. Therefore, it is necessary to discriminate between severe and mild cases.
Previous studies have found that the development of severe COVID-19 is associated with age and underlying disease, and severe patients are likely to suffer from aberrant in ammation reaction and cytokine storm [1,3]. Consequently, some clinical characteristics, the in ammation index and cytokine levels have been used as indictors to re ect the severity of COVID-19 by us and others [4,5]. Recently, emerging evidence suggested that lipid metabolism dysregulation might promote the progression of COVID-19 as revealed by mass spectrometry (MS)-based proteomics analysis [6,7]. Although MS analysis is not commonly performed, blood lipid is routinely examined using automatic biochemical instruments in clinical laboratories. Thus, blood lipid may be considered as a potential and available indictor of COVID-19 severity.
To investigate the blood lipid pro le in the patients with COVID-19 and determine their predictive value for COVID-19 severity, a retrospective study was performed.

Study design and patient selection
This was a single-centre retrospective study approved by the institutional ethics board of HwaMei Hospital, University of Chinese Academy of Science (PJ-NBEY-KY-2020-061-01). A total of 142 consecutive patients with COVID-19, from January 23 to April 20, 2020, and 77 age-and gender-matched healthy subjects were included.
The diagnosis of COVID-19 and its severity were determined according to the National Diagnosis and Treatment Protocol for Novel Coronavirus Infection-Induced Pneumonia (6th Trial Version). Patients with con rmed COVID-19 were diagnosed based on a positive SARS-CoV-2 nucleic acid RT-PCR result, using specimens derived from sputum, throat swab or nasopharynx swab. Severe patients exhibited one of the following features: a) respiratory distress with respiration rate (RR) greater than 30 times per minute; b) blood oxygen saturation less than 93% at a state of rest; c) arterial blood oxygen partial pressure/inhaled oxygen concentration less than 300 mmHg (1 mmHg = 0.133 kPa); or d) lesion rapidly progressed by more than 50% within one or two days on pulmonary imaging.
General clinical characteristics, including gender, age, comorbidities and initial symptoms, treatment, and laboratory test data were collected from the electronic medical record (EMR).

Determination of blood lipid
Blood lipid was tested using a fully automatic biochemical analyser (ADVIA2400, Siemens, Germany) according to the manufacturer's instructions (Purebio Biotechnology Co., Ltd, Ningbo, Zhejiang, China).
Brie y, total cholesterol (TC) was measured using the cholesterol oxidase-p-aminophenazone (CHOD-PAP) method; triglyceride (TG) was assessed using the glycerol phosphate oxidase-p-aminophenazone (GPO-PAP) method; high-density lipoprotein cholesterol (HDL-C) was assessed using the direct-hydrogen peroxide method; low-density lipoprotein cholesterol (LDL-C) was assessed using the direct-surfactant removal method; apolipoprotein A1 (ApoA1), ApoB and lipoprotein (a) were assessed using the immunoturbidimetric method.
Statistical analysis SPSS software, version 16.0 (IBM, Armonk, NY, USA) were used for statistical analysis. Normally and nonnormally distributed continuous data were expressed as the mean ± SD (standard deviation) and median (interquartile range [IQR]), respectively. Categorical variables were reported as numbers (%). Kruskal-Wallis test was used to compare the blood lipids among severe group, non-severe group and healthy subjects, and post hoc pairwise comparisons using the Nemenyi test. The differences between two groups were assessed using Student's t-test and Mann-Whitney U test for normally and non-normally distributed continuous data, respectively, and chi square or Fisher's exact tests were used for categorical variables.
Multivariate logistic regression analysis was adopted to explore independent risk factors of the COVID-19 severity, and receiver operator characteristic (ROC) curves were generated and the aeras under ROC curves (AUCs) were calculated to evaluate their prediction e ciency. A P-value < 0.05 indicates statistical signi cance.
Among the 142 patients, 17 (11.97%) and 125 (88.03%) patients were classi ed into the severe and nonsevere group, respectively. Signi cant differences in age, body mass index (BMI), hypertension and fever were noted between the severe and non-severe groups. Regarding clinical treatment, a greater proportion of patients in the severe group received glucocorticoids, antibiotics, oxygen, invasive mechanical ventilation and intensive care unit treatment (Table 1). Table 1 General clinical characteristics of patients with con rmed COVID-19.

Baseline blood lipid
The baseline blood lipid was obtained within 5 days of admission. It was showed that TC, HDL-C, LDL-C and ApoA1 gradually decreased across healthy controls, non-severe group, and severe group. TG was higher in the non-severe group when compared with healthy controls, however, no signi cant differences Page 7/20 were found between the severe and non-severe group, and the severe group and healthy controls. There were no signi cant differences in ApoB and lipoprotein (a) among the three groups (Fig. 1).

Discussion
In this study, Blood lipid pro le in the patients with COVID-19 patients was abnormal from healthy subjects. Speci cally, baseline TC, HDL-C, LDL-C, and ApoA1 gradually decreased across healthy controls, non-severe group, and severe group, whereas ApoB and lipoprotein (a) exhibited no signi cant differences among the three groups. Although TG was higher in the non-severe group when compared with healthy controls, no signi cant differences were found between the severe and non-severe group, and the severe group and healthy controls. Additionally, ApoA1 was recognized as an independent risk factor of disease severity using multivariate logistic analysis, and had the highest AUC, sensitivity and speci city among all the single markers for COVID-19 severity. Moreover, the combination of ApoA1 and IL-6 yielded a higher prediction e ciency.
Previous studies have reported that lipid metabolism impairment may be involved in the pathogenesis of sepsis secondary to pneumonia and in uenza [8][9][10]. Similarly, recent studies observed dyslipidemia in patients infected with SARS-CoV-2, using MS analysis [6,7] and routine laboratory lipid tests [11], indicating that blood lipid might involve in the pathogenesis of COVID-19. In the study of Wei et al. [11], a serum hypolipidemia was found in the COVID-19 patients, which showed that the serum level of TC, HDL-C and LDL-C in the patients with COVID-19 were signi cantly lower than healthy subjects, especially in the severe and critical cases. The above phenomenon was revealed again in the present. However, the former study did not analyse other blood lipid component, such as ApoA1, ApoB and lipoprotein (a), which were also routine tested, and their predictive values for COVID-19 severity were not fully understood. Among the altered lipids in this study, ApoA1 was signi cantly decreased, and serve as an independent risk factor for the COVID-19 severity.
ApoA1, a major protein component of the HDL complex, is involved in "reverse cholesterol transport" by transporting excess cholesterol from peripheral cells back to the liver for excretion. Besides, ApoA1 has an anti-in ammatory characteristic [12], suggest its role in the in ammatory diseases. Previous studies have revealed that serum ApoA1 was associated with the outcome of patients with sepsis and acute respiratory distress syndrome induced by pneumonia, as well as critically ill patients [13][14][15][16]. In acute in ammatory disease, serum amyloid A (SAA), an acute phase protein, displaces ApoA1 from the HDL complex; then, free ApoA1 is easily eliminated by the kidney, resulting in low levels in the peripheral blood [17]. On the other hand, liver is susceptible to attack by SARS-CoV-2, especially in severe cases [18]; therefore, reduced synthesis by the injured liver may also play a role.
IL-6 plays a key role in the development of COVID-19, and its predictive value has been revealed previously by us and others [4,19]. In this study, IL-6 and ApoA1 were identi ed as independent risk factors. The risk model established by these two markers exhibited the highest predictive value, with an AUC of 0.977 (95% CI: 0.932-0.995).
ApoA1 and its mimetic peptide D-amino acids (D-4F) exhibit therapeutic potential in treating cancer, in uenza, sepsis and a variety of lung diseases, such as acute respiratory distress syndrome (ARDS), mainly due to its anti-in ammatory, anti-oxidant and anti-apoptotic properties [12,[20][21][22][23]. In addition, it is noteworthy that ApoA1 inhibits IL-6 release and reduces macrophage activation [21]. IL-6 is the main participant in the cytokine storm, and macrophages are the primary source of IL-6. Therefore, ApoA1 may exhibit therapeutic potential in treating patients with COVID-19. It might be worthwhile to test the e cacy and safety of ApoA1 in these patients.
The main strength of this study was that the patients included in this study were treated without delay when infected by SARS-CoV-2, which may represent the early stage of the disease. Second, it enrolled healthy controls to analysis the trends of blood lipid among healthy subjects, non-severe cases and severe cases. Third, the predictive values of veri ed clinical characteristics and laboratory parameters were selected to compared with blood lipid, which made the results more credible. Last, blood lipids were routinely tested by automatic biochemical analyser, with clinical application value.
The weakness of this study was that it was a single-centre retrospective study with relatively small sample size, and not validated with internal and external cohorts. Therefore, a prospective study with a large sample size is strongly encouraged.

Conclusion
In conclusion, this study shed light on an abnormal blood lipid pro le in patients with COVID-19 from healthy subjects, especially in the severe cases. Speci cally, TC, HDL-C, LDL-C, and ApoA1 gradually decrease across healthy controls, non-severe group, and severe group. Additionally, ApoA1 is a good indicator of COVID-19 severity, and the combination of ApoA1 and IL-6 enhances the predictability. These ndings might be helpful in disclosing the pathogenesis of and developing novel therapeutic strategies for COVID-19.