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US 2023/0147592 A1Published application
Alterations in the molecular composition of urine from covid19 patients, detected using raman spectroscopic and computational analysis
OwnerJohn L. Robertson, Ryan Sengerinventors
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Abstract
The present invention comprises methods of detecting and classifying COVID-19 disease using Raman spectra obtained from subject urine samples. Raman spectra from subject urine samples are analyzed using models prepared from reference Raman samples obtained from urine samples of individuals with and without COVID-19. The spectral fingerprints of urine from subjects with and without COVID-19 allow for identification of disease-associated changes in urine molecular composition.
Claims20
A method for determining COVID-19 status of a subject, comprising:
- obtaining a test Raman spectrum from a urine sample from a test subject;
- obtaining at least one positive reference Raman spectrum from a urine sample from a COVID-19 positive subject and at least one negative reference Raman spectrum from a urine sample from a COVID-19 negative subject;
- identifying at least one significant Raman shift;
- analyzing the test Raman spectrum, positive Raman spectrum, and negative Raman spectrum by performing principal component analysis (PCA) and/or discriminant analysis of principal components (DAPC) using the at least one significant Raman shift;
- and
- classifying the test subject as COVID-19 positive or COVID-19 negative based on the analyzing.
3 more elements
A method of identifying a condition of a subject, comprising:
- obtaining Raman spectra from a urine sample from a subject;
- comparing the Raman spectra of the urine sample to a selected model;
- wherein the selected model is constructed from various Raman spectra of urine from individuals having and not having COVID-19, and by:
- (a) applying baseline correction to a range of wavenumbers of the various Raman spectra to obtain baseline corrected Raman spectra;
- (b) performing normalization of the baseline corrected Raman spectra to obtain normalized Raman spectra;
- (c) performing principal component analysis (PCA) of the normalized Raman spectra to identify principal components (PCs) of the urine from the individuals having and not having COVID-19;
- (d) performing one or more analysis selected from discriminant analysis of principal components (DAPC), Partial Least Squares (PLS), machine learning, and/or neural networks (NN), to obtain one or more chemometric models based on one or more of the PCs and for the DAPC analysis, comprising canonicals equal in number to the PCs;
- (e) for the DAPC analysis, determining a fractional contribution of each wavenumber to each canonical of one or more of the chemometric models to determine which wavenumbers give rise to separations seen in a plot of two or more of the canonicals;
- and
- (f) identifying statistically significant spectral differences between the urine from the individuals having the specified condition and the urine from individuals not having COVID-19 by performing total principal component distance (TPD) and/or total spectral distance (TSD);
- wherein the comparing of the Raman spectra of the urine sample to the selected model comprises identifying whether the urine sample is classified according to the selected model as being urine either from a subject who has or does not have COVID-19.
8 more elements
Dependencies are inferred from the claim text.