Diagnostic Potential of the Plasma Lipidome in Infectious Disease: Application to Acute SARS-CoV-2 Infection.

Nicola Gray,Elaine Holmes,Julien Wist,Nieves Embade,Chiara Bruzzone,Luke Whiley,Nathan Lawler,Monique Ryan,Oscar Millet,Sze Bong,Jeremy Nicholson,Annie Zeng,Berin Boughton,Maider Bizkarguenaga

doi:10.3390/metabo11070467

Abstract

Improved methods are required for investigating the systemic metabolic effects of SARS-CoV-2 infection and patient stratification for precision treatment. We aimed to develop an effective method using lipid profiles for discriminating between SARS-CoV-2 infection, healthy controls, and non-SARS-CoV-2 respiratory infections. Targeted liquid chromatography–mass spectrometry lipid profiling was performed on discovery (20 SARS-CoV-2-positive; 37 healthy controls; 22 COVID-19 symptoms but SARS-CoV-2negative) and validation (312 SARS-CoV-2-positive; 100 healthy controls) cohorts. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) and Kruskal–Wallis tests were applied to establish discriminant lipids, significance, and effect size, followed by logistic regression to evaluate classification performance. OPLS-DA reported separation of SARS-CoV-2 infection from healthy controls in the discovery cohort, with an area under the curve (AUC) of 1.000. A refined panel of discriminant features consisted of six lipids from different subclasses (PE, PC, LPC, HCER, CER, and DCER). Logistic regression in the discovery cohort returned a training ROC AUC of 1.000 (sensitivity = 1.000, specificity = 1.000) and a test ROC AUC of 1.000. The validation cohort produced a training ROC AUC of 0.977 (sensitivity = 0.855, specificity = 0.948) and a test ROC AUC of 0.978 (sensitivity = 0.948, specificity = 0.922). The lipid panel was also able to differentiate SARS-CoV-2-positive individuals from SARS-CoV-2-negative individuals with COVID-19-like symptoms (specificity = 0.818). Lipid profiling and multivariate modelling revealed a signature offering mechanistic insights into SARS-CoV-2, with strong predictive power, and the potential to facilitate effective diagnosis and clinical management.

Highlights

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus2 (SARS-CoV-2), remains a threat to public health across the world, with emerging variants and growing evidence of long-term health concerns post-infection
The present study has shown that SARS-CoV-2 infection causes significant perturbations in plasma and serum lipid profiles compared to healthy controls
Following liquid chromatography–mass spectrometry (LC–MS)/MS quantitative lipidomics and multivariate data interrogation, a targeted panel of lipid biomarkers was developed and evaluated for their diagnostic potential for SARS-CoV-2 in two independent cohorts collected in different countries

Summary

Introduction

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus. 2 (SARS-CoV-2), remains a threat to public health across the world, with emerging variants and growing evidence of long-term health concerns post-infection. The gold standard for the diagnosis of SARS-CoV-2 infection is reverse transcription PCR (RT-PCR). Its effectiveness has been questioned throughout the pandemic, with a false negative rate reported to be up to 20%, dependent on factors including sampling time post-infection, low virus titre, sampling error, and experimental error [1]. RT-PCR testing only has a small sampling time window, and gives no indication of subsequent clinical outcome—for example, the risk of severe disease, or post-acute COVID-19 syndrome (PACS). There is an urgent need for new tools that can better stratify patients and help to augment existing RT-PCR strategies and mitigate the diagnostic limitations in the clinical management of the disease

Objectives

Methods

Results

Discussion

Conclusion