Association between lipid profile and clinical outcomes in COVID-19 patients | Scientific Reports – Nature.com

This research provide a comprehensive examination of the impact of clinical, demographic, and lipid-related factors on the severity and mortality of patients with COVID-19. The findings presented in our study indicate that there are no statistically significant differences between critical and non-critical cases when considering gender. Nevertheless, it is worth noting that there was a discernible pattern linked to age, as older people were overrepresented among patients who experienced severe outcomes or did not survive. These data provide support for the widely accepted scientific consensus that age is a significant risk factor for negative outcomes related to COVID-19, such as hospitalization, admission to critical care units, and death33.

The substantial proportion of the cohort with diabetes and hypertension in this study is consistent with previous research indicating that these comorbidities are associated with worse outcomes in COVID-1934. These conditions are known to exacerbate the inflammatory response and contribute to endothelial dysfunction, which may enhance the severity of SARS-CoV-2 infection. This suggest that COVID-19 patients with comorbidities like diabetes and hypertension may be at higher risk of disease severity and mortality35. Therefore, it is significant to identify and manage these comorbidities in COVID-19 patients to improve their outcomes.

However, variables including sex, diabetes, and obesity, were not significantly associated with survival outcomes. Previous studies have identified these as potential risk factors for severe COVID-19 outcomes36,37, which is unexpected. The absence of an association in the present study may be attributable to the small sample size, necessitating additional research in larger cohorts.

When comparingthe lipid profiles of COVID-19 patientsbetween severity and survival outcome groups, no significant differences in cholesterol levels across severity or outcome groups in COVID-19 patients. The median cholesterol levels were comparable across all groups, with non-critical patients exhibiting slightly higher levels than critical patients. Similarly, the study found no significant differences in high-density lipoprotein cholesterol (HDL-c) levels among severity and outcome groups. The values were closely matched in all groups, with non-critical patients and survivors marginally higher than their counterparts. The study found slightly lower median values of low-density lipoprotein cholesterol (LDL-c) in critical compared to non-critical patients, but this difference was insignificant. This finding is consistent with a study by Zhang et al. that found that LDL-c levels were lower in COVID-19 patients with severe disease than those with mild disease8.

Triglyceride levels showed a statistically significant difference between survival outcome groups, with non-survivors exhibiting higher median levels. This suggests a potential association between elevated triglycerides, reduced HDL-c levels, and increased mortality risk in COVID-19 patients. According to additional studies, high triglyceride levels and low HDL-c levels are predictors of COVID-19 severity and mortality6,10,19,38. Nevertheless, the relationship between lipid profiles and COVID-19 outcomes is not yet fully understood, and additional research is required to identify the precise mechanisms underlying this association. According to the lipid profile changes, elevated triglycerides are associated with COVID-19 severity and mortality; this finding is consistent with a recent meta-analysis that linked elevated triglycerides to COVID-19 severity and mortality10.

Similarly, Masana et al.19 identified low HDL cholesterol and elevated triglycerides as predictors of COVID-19severity. However, the conclusions drawn from previous studies regarding the alterations in serum lipids in COVID-19 patients are inconsistent. For instance, Liu et al. found that dyslipidemia was not associated with COVID-19 severity or mortality39. Different study designs, patient populations, and lipid profile measurements may account for these discrepancies.

The present study also evaluated the ability of lipid profile variables to predict COVID-19 severity and mortality using AUC-ROC curves. The study found that all lipid profile components had moderate discriminatory ability, with AUC values ranging from 0.79 to 0.89. The study also established optimal cut-off points for each lipid variable based on the Youden's index J and found that each lipid variable, except for Tryg, showed a significant association with mortality outcome in logistic regression analysis. The multivariate logistic regression model revealed that the lipid variables had substantial predictive value for severity and mortality outcome, even after adjusting for potential confounders such as age, sex, diabetes, hypertension, and obesity.

These findings are consistent with previous research showing that lipid profile alterations are associated with COVID-19 severity and mortality40. Moreover, the present study's findings suggest that lipid profile variables may be useful in predicting COVID-19 outcomes and could be used as a readily available biological marker to predict the severity and mortality of COVID-19 infection41. However, it is essential to note that lipid profile variables are just one of many factors that may influence COVID-19 outcomes. Other factors, such as treatment adherence on chronic diseases42, albumin levels43, Leukocyte glucose index44, and neutrophillymphocyte ratio41, have also been identified as predictors of COVID-19 outcomes.

Other research indicates that comorbidities may moderate the relationship between lipid profile and COVID-19 outcomes. For instance, Kumari et al.45 found that lipid profiles may be a potential marker for determining the disease prognosis for COVID-19 patients, but they did not examine the impact of comorbidities. The precise mechanisms coupling these comorbidities to worse outcomes are not fully understood, but they could involve a combination of factors, such as chronic inflammation, impaired immune function, and increased susceptibility to viral entry and replication.

In addition, the findings of the presented study may have substantial implications for the treatment of COVID-19 patients. Age and hypertension were identified as significant survival predictors in COVID-19 patients, particularly in the context of early identification and management of comorbidities. Findings regarding triglycerides suggest that surveillance and treatment of lipid profile abnormalities may be necessary for enhancing COVID-19 outcomes. In addition, further research is necessary to thoroughly comprehend the mechanisms underlying the association between COVID-19 and lipid profile levels and to develop effective interventions for preventing and treating dyslipidemia caused by COVID-19. Furthermore, this study emphasizes the significance of considering comorbidities such as diabetes and hypertension when assessing the severity and mortality of COVID-19. Age and hypertension were significant survival predictors in both univariate and multivariate Cox proportional hazards regression models. Additionally, the survival analysis for HDL-c levels also revealed interesting findings.

The present study found that COVID-19 patients with higher HDL-c levels may have a greater chance of survival. This finding aligns with previous research suggesting that HDL-c, known for its anti-inflammatory and antioxidant properties, may have a protective role in COVID-19. In this sense, some studies evaluated the HDL-c anti-inflammatory and antioxidant activity, proving that the Serum amyloid A (SAA), Apolipoprotein A-1, Alpha-1 antitrypsin, and paraoxonase 1 (PON-1) (HDL-c associated proteins) are altered in SARS-CoV-2 infection which could be related to decreased functionality of HDL-c in COVID-19 severity23,46.

Moreover, evidence suggests that cholesterol-rich lipid rafts and receptors, such as HDL scavenger receptor B type 1 (SR-B1), which regulate lipid entry into cells can enhance SARS-CoV-2 entry17. HDL-c mobilizes the cholesterol of cholesterol-rich lipid rafts for traffic and re-localizes SARS-CoV-2 receptors, which promote the viral entry into cells17.Because HDL-c has immunomodulatory effects, it could be hypothesized that low HDL-c levels during infection are associated with the regulation of immune cells in COVID-19 severity47,48. A study evaluating lymphocytes, macrophage activation, dendritic cells, inflammatory mediators, cytokines, and their correlation with HDL-c levels during SARS-CoV-2 infection is required to test this hypothesis.

Stadler et al. demonstrated that the cholesterol efflux capacity is associated with mortality, ApoA-I protein, HDL-ApoA-I protein, HDL-c, total ApoA-II protein, HDL-free cholesterol, and HDL phospholipids in patients with COVID-1949. Another study demonstrating the importance of HDL-c during SARS-CoV-2 infection showed that a ratio of triglyceride to HDL-c was related to the risk of severe COVID-1950.

Changes in lipid profile levels could have clinical applicability in providing timely treatment for patients with COVID-19. In this regard, a study of lipid profiletrajectories during the two years before COVID-19 testing revealed that higher antecedent HDL-c levels were associated with a lower SARS-CoV-2 infection risk. These levels, however, declined during viral infection51. On the other hand, Jin et al. reported that the patients infected during the first wave of COVID-19 with high levels of low-density lipoprotein cholesterol (LDL-c), triglyceride, and total cholesterol before infection and on admission had a poor progression of COVID-197. Moreover, HDL-c, LDL-c, total cholesterol, and triglyceride were significantly lower in the patients with COVID-19 during the first wave of COVID-19, demonstrating that lipid profile predicts the severity of SARS-CoV-2 infection52. Al-Zadjali et al. demonstrated that low HDL-c levels areassociated with increase long-term COVID-19 severity in unvaccinated patients infected with SARS-CoV-2 after the first wave of COVID-1953. Regarding vaccination, a study focused on analyzing the lipid profile before and after the two doses of the COVID-19 vaccination in patients without exposure to SARS-CoV-2 infection revealed that triglyceride levels were significantly decreased and cholesterol, HDL-c, and LDL-c levels were significantly increased in patients who received the mRNA-1273 (Moderna) vaccine54. Individuals vaccinated with the BNT162b2 (Pfizer-BioNTech) vaccine had a significant increase in HDL-c, while patients vaccinated with ChAdOx1 nCov-19 (Oxford-AstraZeneca) had no change in lipid profile after follow-up54. Szczerbiski et al. reported an absence of statistically significant correlation between the total cholesterol, HDL-c, and LDL-c levels and anti-SARS-CoV-2 S antibodies concentration at the end-of-observation-19 weeks in patients vaccinated with the second dose of BNT162b2 mRNA COVID-19 vaccine55. On the other hand, in the patients who received the COVID-19 vaccine and were diagnosed with SARS-CoV-2 infection after the first wave of COVID-19, the total cholesterol, HDL-c, and LDL-c were significantly lower in non-survivors and these values were associated with the mortality risk56. Furthermore, patients with low levels of LDL-c, total cholesterol, and anti-SARS-CoV-2 antibodies had the highest mortality rates56. Thus, lipid profile, emerging SARS-CoV-2 variants, and the immune response in COVID-19 vaccine recipients (neutralizing antibodies against SARS-CoV-2) could be strongly related with COVID-19 mortality through a pathophysiological mechanism where the statin therapy would improve the chances of survival57.

Despite the emergence of new SARS-CoV-2 variants, our findings remain clinically relevant, offering insights into the prognostic value of lipid profiles in COVID-19 patients. These insights are pivotal for risk stratification and the development of management strategies that are adaptable to the evolving pandemic landscape. Furthermore, this study elucidates the critical associations between lipid profile abnormalities and COVID-19 severity and mortality, thereby contributing significantly to existing literature. However, the study is not without limitations. The retrospective design, small sample size, and absence of control groups introduce potential biases and limit the generalizability of our findings. Additionally, uncontrolled confounding variables and population heterogeneity further constrain the study's applicability. Despite these constraints, this researchmakes a significant contribution to the field. Future investigations should adopt a prospective methodology, incorporate larger and more diverse cohorts, and include control groups. Employing advanced statistical techniques to control confounders and conducting mechanistic studies will refine our understanding and facilitate targeted interventions, thereby enhancing the study's global scientific impact.

Our findings suggest that patients with comorbidities should be classified with caution based on their lipid profile values when assessing the prognosis of COVID-19 patients. In addition, the relationship between lipid profile, disease outcome, and comorbidities must be understood to guide adequate risk stratification and treatment planning for COVID-19 patients. Similarly, the underlying mechanisms and potential interventions for dyslipidemia in COVID-19 patients require additional research. Despite its moderate AUC, the logistic regression model suggests a limited yet non-negligible ability to discriminate between patient outcomes based on lipid profiles. While the model exhibits high sensitivity, its specificity is notably low, indicating a propensity for false positive predictions, which could limit its clinical utility. In contrast, the Cox model's incorporation of time-to-event data provides a more granular analysis of risk factors, reinforcing the prognostic significance of age and hypertension. These results are consistent with existing literature that highlights the exacerbation of COVID-19 severity by underlying health conditions. Our findings corroborate previous studies that have identified age and hypertension as critical determinants of COVID-19 prognosis. However, the unique contribution of this study lies in its analytical approach, combining logistic regression with Cox proportional hazards modeling to enhance the depth of prognostic assessments. This study's primary limitations stem from its reliance on available clinical data, which may not capture all potential confounders. Future research should explore the inclusion of additional variables, such as genetic markers and patient lifestyle factors, which could further refine the predictive models presented herein. However, this study advances knowledge by shedding light on the prognostic significance of the lipid profile of COVID-19 infection. It also highlights the significance of considering lipid metabolism in treating and staging the disease.

When understanding the usefulness of lipid profiles in the prognosis of COVID-19, the classification of patients based on clinical guidelines or other clinical parameters should be considered. Our study classified the patients according to the Diagnosis and Treatment Protocol for Novel Coronavirus Pneumonia, issued by the Chinese Centers for Disease Control and Prevention. Other studies that validated a clinical risk score or analyzed intermediates of cholesterol biosynthesis and their association with the clinical outcomes of SARS-CoV-2 infection classified the severity of COVID-19 based on the American Thoracic Society guidelines and the National Institutes of Health recommendations, respectively58,59. Hence, these and other classifications should be considered when comparing study results to avoid errors in interpreting severity and mortality predictors for COVID-19.

A comprehensive understanding of the effect of lipid profiles on COVID-19 outcomes may lead to improved clinical decision-making and patient care. In conclusion, this study advances our understanding of the factors influencing COVID-19 outcomes, emphasizing the role of systemic health issues such as hypertension. The dual analytical approach utilized herein not only highlights significant predictors but also underscores the complexity of prognostic modeling in infectious diseases.

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Association between lipid profile and clinical outcomes in COVID-19 patients | Scientific Reports - Nature.com