Rapid Detection of COVID-19 Using MALDI-TOF-Based Serum Peptidome Profiling

The outbreak of coronavirus disease
2019 (COVID-19) caused by SARS
CoV-2 is ongoing and a serious threat to global public health. It
is essential to detect the disease quickly and immediately to isolate
the infected individuals. Nevertheless, the current widely used PCR
and immunoassay-based methods suffer from false negative results and
delays in diagnosis. Herein, a high-throughput serum peptidome profiling
method based on matrix-assisted laser desorption/ionization time-of-flight
mass spectrometry (MALDI-TOF MS) is developed for efficient detection
of COVID-19. We analyzed the serum samples from 146 COVID-19 patients
and 152 control cases (including 73 non-COVID-19 patients with similar
clinical symptoms, 33 tuberculosis patients, and 46 healthy individuals).
After MS data processing and feature selection, eight machine learning
methods were used to build classification models. A logistic regression
machine learning model with 25 feature peaks achieved the highest
accuracy (99%), with sensitivity of 98% and specificity of 100%, for
the detection of COVID-19. This result demonstrated a great potential
of the method for screening, routine surveillance, and diagnosis of
COVID-19 in large populations, which is an important part of the pandemic
control.