Summary
Early
detection and effective treatment of severe COVID-19 patients remain
major challenges. Here, we performed proteomic and metabolomic profiling
of sera from 46 COVID-19 and 53 control individuals. We then trained a
machine learning model using proteomic and metabolomic measurements from
a training cohort of 18 non-severe and 13 severe patients. The model
was validated using 10 independent patients, 7 of which were correctly
classified. Targeted proteomics and metabolomics assays were employed to
further validate this molecular classifier in a second test cohort of
19 COVID-19 patients, leading to 16 correct assignments. We identified
molecular changes in the sera of COVID-19 patients compared to other
groups implicating dysregulation of macrophage, platelet degranulation,
complement system pathways, and massive metabolic suppression. This
study revealed characteristic protein and metabolite changes in the sera
of severe COVID-19 patients, which might be used in selection of
potential blood biomarkers for severity evaluation.
Introduction
Coronavirus
disease 2019 (COVID-19) is an unprecedented global threat caused by
severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It is
currently spreading around the world rapidly. The sudden outbreak and
accelerated spreading of SARS-CoV-2 infection have caused substantial
public concerns. Within about 3 months, over 2 million individuals
worldwide have been infected, leading to over 150,000 deaths.
Most COVID-19 studies have focused on its epidemiological and clinical characteristics (
,
).
About 80% of patients infected with SARS-CoV-2 displayed mild symptoms
with good prognosis. They usually recover with, or even without,
conventional medical treatment and therefore are classified as mild or
moderate COVID-19 (
).
However, about 20% of patients suffer from respiratory distress and
require immediate oxygen therapy or other inpatient interventions,
including mechanical ventilation (
,
).
These patients, classified as clinically severe or critical
life-threatening infections, are mainly diagnosed empirically based on a
set of clinical characteristics, such as respiratory rate (≥30
times/min), mean oxygen saturation (≤93% in the resting state), or
arterial blood oxygen partial pressure/oxygen concentration (≤300 mmHg).
However, patients exhibiting these clinical manifestations have already
progressed to a clinically severe phase and require immediate access to
specialized intensive care; otherwise, they may die rapidly. Therefore,
it is critical to develop new approaches to assess early which cases
will likely become clinically severe. In addition, effective therapy for
severe patients remains speculative, largely due to limited
understanding of SARS-CoV-2 pathogenesis.
In
this study, we hypothesized that SARS-CoV-2 induces characteristic
molecular changes that can be detected in the sera of severe patients.
These molecular changes may shed light on therapy development for
COVID-19 patients. To test this hypothesis, we applied proteomic (
,
) and metabolomic (
,
) technologies to analyze the proteome and metabolome of sera from COVID-19 patients and several control groups.
Results
Proteomic and Metabolomic Profiling of COVID-19 Sera
We procured a cohort of patients (
)
containing 28 severe COVID-19 patients. The detailed patient
descriptions including the sampling date for each patient are shown in Figure 1A, Table 1, and Table S1.
Controls with matched epidemiological features were included to
identify severity-related molecular alterations. These controls were 28
healthy subjects, 25 non-COVID-19 patients (negative for the SARS-CoV-2
nucleic acid test) with similar clinical characteristics as COVID-19
patients, and 25 non-severe COVID-19 patients. A serum sample was
obtained from each patient within a few days after hospital admission,
with a few exceptions when samplings were performed at later disease
stages. We analyzed 12 clinical measurements of the COVID-19 and
non-COVID-19 patients (Figure S1),
including white blood cell count, lymphocyte count, monocyte count,
platelet count, C-reactive protein (CRP), alanine aminotransferase
(ALT), aspartate aminotransferase (AST), glutamyltransferase (GGT),
total bilirubin (TBIL), direct bilirubin (DBIL), creatinine, and
glucose. Compared to non-severe patients, severe patients showed
significant suppression of lymphocyte count and monocyte count, as well
as increase of CRP and AST (Figure S1).
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