Abstract: Provided by the inventive concept is a DNA methylation-based platform, and machine learning algorithms, for diagnosing respiratory pathogens including SARS-CoV-2 and predicting COVID-19 related outcomes, and methods of using the same, such as in identifying the presence of a viral infection, such as a SARS-CoV-2 infection, determining whether a subject has COVID-19, and/or whether a subject with COVID-19 is likely to develop acute respiratory distress syndrome or multisystem inflammatory syndrome in children.

Abstract: The present invention provides methods of identifying a subject having an increased or decreased ability to convert medium chain-polyunsaturated fatty acids (MC-PUFAs) to long chain polyunsaturated fatty acids (LC-PUFAs), comprising: (a) correlating the presence of one or more than one genetic marker in chromosome 11ql2-13, between build 37.1 position 61548559 and build 37.1 position 61560261, with an increased ability to convert MC-PUFAs to LC-PUFAs; and b) detecting the one or more than one genetic marker of step (a) in the subject, thereby identifying the subject as having an increased ability to convert MC-PUFAs to LC-PUFAs. Also provided are methods of correlating one or more genetic markers with an ability to convert MC-PUFAs to LC-PUFAs.