WO2024259532A1 - Méthode d'identification et de traitement de l'affection post-covid-19 chez des sujets - Google Patents

Méthode d'identification et de traitement de l'affection post-covid-19 chez des sujets Download PDF

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WO2024259532A1
WO2024259532A1 PCT/CA2024/050833 CA2024050833W WO2024259532A1 WO 2024259532 A1 WO2024259532 A1 WO 2024259532A1 CA 2024050833 W CA2024050833 W CA 2024050833W WO 2024259532 A1 WO2024259532 A1 WO 2024259532A1
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covid
long
lysopc
lysophosphatidylcholine
proteins
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Mohammad Ashraful Anwar
Zhengnan Wang
Ana MADDOX
Ammar Hassanzadeh KESHTELI
Robert Fraser
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Molecular You Corp
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/569—Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
    • G01N33/56983—Viruses
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
    • A61K31/00—Medicinal preparations containing organic active ingredients
    • A61K31/70—Carbohydrates; Sugars; Derivatives thereof
    • A61K31/7088—Compounds having three or more nucleosides or nucleotides
    • A61K31/713—Double-stranded nucleic acids or oligonucleotides
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/92—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving lipids, e.g. cholesterol, lipoproteins, or their receptors
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/94—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving narcotics or drugs or pharmaceuticals, neurotransmitters or associated receptors
    • G01N33/9406—Neurotransmitters
    • G01N33/942—Serotonin, i.e. 5-hydroxy-tryptamine
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/005—Assays involving biological materials from specific organisms or of a specific nature from viruses
    • G01N2333/08—RNA viruses
    • G01N2333/165—Coronaviridae, e.g. avian infectious bronchitis virus
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/46—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans from vertebrates
    • G01N2333/47—Assays involving proteins of known structure or function as defined in the subgroups
    • G01N2333/4701—Details
    • G01N2333/4716—Complement proteins, e.g. anaphylatoxin, C3a, C5a
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/78—Connective tissue peptides, e.g. collagen, elastin, laminin, fibronectin, vitronectin, cold insoluble globulin [CIG]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/81—Protease inhibitors
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2405/00—Assays, e.g. immunoassays or enzyme assays, involving lipids
    • G01N2405/04—Phospholipids, i.e. phosphoglycerides
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2570/00—Omics, e.g. proteomics, glycomics or lipidomics; Methods of analysis focusing on the entire complement of classes of biological molecules or subsets thereof, i.e. focusing on proteomes, glycomes or lipidomes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/50—Determining the risk of developing a disease
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/56—Staging of a disease; Further complications associated with the disease

Definitions

  • the present disclosure relates generally to the field of identifying whether a subject has Long COVID and treatment thereof.
  • COVID-19 caused by the SARS-CoV-2 virus, is a highly contagious respiratory illness that has become a global pandemic.
  • the virus primarily spreads through respiratory droplets when an infected individual talks, coughs, or sneezes. Once a person is infected, the virus attaches to cells in the respiratory tract and uses a specific protein called the spike protein to enter and infect these cells. The virus then replicates in the cells and causes them to produce cytokines, which trigger an immune response that can lead to inflammation and damage to lung tissue. This immune response can also result in a cytokine storm, an overactive immune response that can cause severe inflammation and organ damage in severe cases of COVID-19.
  • the exact mechanisms behind COVID-19 are still being studied, but understanding the disease mechanisms can help not only uncover clues as to the disease process but also future consequences resulting from infection and re-infection.
  • Post-COVID-19 condition often referred to as Long COVID can be described as the persistence of symptoms for weeks or months following acute COVID-19 infection. These symptoms can range from fatigue, shortness of breath, and joint pain to neurological problems such as headaches, cognitive impairment, mood disorders, among other symptoms. The exact mechanisms behind Long COVID are still not fully understood, but it is believed to be related to ongoing inflammation and immune response following the initial infection. Some people may also have an ongoing viral infection or other underlying medical conditions that contribute to their symptoms.
  • the present disclosure provides a method for identifying and treating long COVID.
  • a new metabolomic profile is used to identify a subject as having long COVID and to treat and/or ameliorate the disease.
  • the combination of metabolites and/or proteins, peptides or fragments thereof described herein are a subset of COVID markers that have a predictive value of at least 80%, 85%, 90% or more, as determined by a VIP plot.
  • At least one, two, three, four or five metabolites are selected from 3 -Hydroxy oleoylcamitine (C18: 1-OH); Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0); Beta-alanine; Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine C16: l (lysoPC Cl 6: 1); Lysophosphatidylcholine, Cl 6:0 (lysoPC Cl 6:0); Hydroxy sphingomyelin (SM (OH)) C22:2; Dodecanedioylcarnitine (C12-DC); Succinic acid; and Propionic acid.
  • 3 -Hydroxy oleoylcamitine C18: 1-OH
  • Lysophosphatidylcholine, Cl 8:0 lysoPC Cl 8:0
  • At least one, two, three, four or five metabolites are selected from 3- Hydroxyoleoylcamitine (C18: 1-OH); Lysophosphatidylcholine, C18:0 (lysoPC C18:0); Betaalanine; Phosphatidylcholine diacyl C32:2 (PC aa C32:2); and Lysophosphatidylcholine C16: l (lysoPC Cl 6: 1).
  • At least one, two, three, four or five proteins are selected from Fibronectin; Lumican; Ficolin-2; Hemoglobin subunit alpha 1; Extracellular matrix protein 1; Complement Component C7; Plasminogen; Attractin; Vitamin K-dependent protein S; and Complement factor H.
  • at least one, two, three, four or five proteins are selected from Fibronectin; Lumican; Ficolin-2; Hemoglobin subunit alpha 1; and Extracellular matrix protein 1.
  • the new metabolomic and/or proteomic profile is used to monitor disease progression or provide improvements in the disease condition.
  • a method for diagnosing and treating Long COVID in a subject comprising: (a) providing a biological sample obtained from the subject; (b) measuring concentration levels from the obtained sample, at least one, at least two, at least three, at least four or at least five Long COVID-related metabolites selected from Lysophosphatidylcholine, C18:0 (lysoPC C18:0); Lysophosphatidylcholine, C16:0 (lysoPC C16:0); 3 -Hydroxy oleoylcamitine (C18: 1-OH); Succinic acid; Hydroxy sphingomyelin C22:2 (SM (OH) C22:2); Phosphatidylcholine diacyl C32:2 (PC aa C32:2)
  • the Long COVID-related metabolites are selected from at least one, at least two, at least three, at least four or at least five of 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Lysophosphatidylcholine, C18:0 (lysoPC C18:0); Beta-alanine; Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine C16: l (lysoPC C16: l); Lysophosphatidylcholine, C16:0 (lysoPC C16:0); Hydroxysphingomyelin (SM (OH)) C22:2; Dodecanedioylcarnitine (C12-DC); Succinic acid; and Propionic acid.
  • C18: 1-OH Lysophosphatidylcholine, C18:0 (lysoPC C18:0
  • Beta-alanine P
  • the Long COVID-related metabolites are selected from at least one, at least two, at least three, at least four or at least five of 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Lysophosphatidylcholine, C18:0 (lysoPC C18:0); Beta-alanine; Phosphatidylcholine diacyl C32:2 (PC aa C32:2); and Lysophosphatidylcholine C16: l (lysoPC C16: l).
  • C18 3 -Hydroxy oleoylcarnitine
  • Lysophosphatidylcholine, C18:0 lysoPC C18:0
  • Beta-alanine Phosphatidylcholine diacyl C32:2 (PC aa C32:2)
  • Lysophosphatidylcholine C16: l lysoPC C16: l
  • the Long COVID-related proteins are selected from at least one, at least two, at least three, at least four or at least five of Fibronectin; Lumican; Ficolin-2; Hemoglobin subunit alpha 1; Extracellular matrix protein 1; Complement Component C7; Plasminogen; Attractin; Vitamin K-dependent protein S; and Complement factor H.
  • the Long COVID-related proteins are selected from at least at least one, at least two, at least three, at least four or at least five of Fibronectin; Lumican; Ficolin- 2; Hemoglobin subunit alpha 1; and Extracellular matrix protein 1.
  • a method for diagnosing and treating Long COVID in a subject comprising: (a) providing a biological sample obtained from the subject; (b) measuring from the obtain sample or having measured in a spectroscopy unit the concentration levels of at least one, at least two, at least three, at least four or at least five Long COVID-related metabolites selected from Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0); Lysophosphatidylcholine, C16:0 (lysoPC C16:0); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Succinic acid; Hydroxysphingomyelin (SM (OH)); C22:2 Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine, C20:4 (lysoPC C20:4); Lysophosphati
  • the Long COVID-related metabolites are selected from at least one, at least two, at least three, at least four or at least five of 3- Hydroxyoleoylcamitine (C18: 1-OH); Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0); Betaalanine; Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine C16: l (lysoPC Cl 6: 1); Lysophosphatidylcholine, Cl 6:0 (lysoPC Cl 6:0); Hydroxy sphingomyelin (SM (OH)) C22:2; Dodecanedioylcamitine (C12-DC); Succinic acid; and Propionic acid.
  • C18 3- Hydroxyoleoylcamitine
  • C18 1-OH
  • Lysophosphatidylcholine, Cl 8:0 lysoPC Cl 8:
  • the Long COVID-related metabolites are selected from at least one, at least two, at least three, at least four or at least five of 3- Hydroxyoleoylcamitine (C18: 1-OH); Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0); Betaalanine; Phosphatidylcholine diacyl C32:2 (PC aa C32:2); and Lysophosphatidylcholine C16: l (lysoPC Cl 6: 1).
  • the Long COVID-related proteins are selected from at least one, at least two, at least three, at least four or at least five of Fibronectin; Lumican; Ficolin-2; Hemoglobin subunit alpha 1; Extracellular matrix protein 1; Complement Component C7; Plasminogen; Attractin; Vitamin K-dependent protein S; and Complement factor H.
  • the Long COVID-related proteins are selected from at least one, at least two, at least three, at least four or at least five of Fibronectin; Lumican; Ficolin-2; Hemoglobin subunit alpha 1; and Extracellular matrix protein 1.
  • the Long CO VID treatment regime comprises adjusting the blood levels of one or more of the Long COVID-related metabolites and/or proteins in the subject diagnosed as having the Long CO VID or predisposed of developing the Long CO VID or a combination thereof.
  • the adjustment of the blood levels of one or more of the Long COVID-related metabolites and/or proteins in the subject occurs until an improvement in the Long COVID symptoms in the subject is observed.
  • the adjustment of the blood levels of one or more of the Long COVID-related metabolites comprises adjusting the composition of gut microbiota in the subject.
  • the identifying step occurs upon determination that the concentration levels of at least one, at least two, at least three, at least four or at least five of the Long COVID-related metabolites and/or proteins from the obtained sample differ by about 20% or more, about 30% or more, about 40% or more, about 50% or more, about 60% or more, or about 70% or more relative to the concentration levels of the reference Long COVID-related metabolites and/or proteins from the Long COVID-negative sample.
  • the obtained sample is blood or urine, preferably serum, plasma or urine.
  • the Long COVID-related metabolites and/or proteins are measured by a spectroscopic technique, wherein the spectroscopic technique is selected from the group consisting of liquid chromatography, gas chromatography, liquid chromatography mass spectrometry, gas chromatography mass spectrometry, high performance liquid chromatography mass spectrometry, capillary electrophoresis mass spectrometry, nuclear magnetic resonance spectrometry (NMR), raman spectroscopy, and infrared spectroscopy.
  • the spectroscopic technique is selected from the group consisting of liquid chromatography, gas chromatography, liquid chromatography mass spectrometry, gas chromatography mass spectrometry, high performance liquid chromatography mass spectrometry, capillary electrophoresis mass spectrometry, nuclear magnetic resonance spectrometry (NMR), raman spectroscopy, and infrared spectroscopy.
  • the comparison of the concentration levels of the Long COVID-related metabolites and/or proteins from the obtained sample to the concentration levels of the reference Long COVID-related metabolites and/or proteins from the Long COVID-negative sample comprises using multivariate statistical analysis.
  • the multivariate statistical analysis is selected from principal component analysis (PCA), or partial least squares projects to latent structures discriminant analysis (PLS-DA).
  • PCA principal component analysis
  • PLS-DA latent structures discriminant analysis
  • a method of monitoring Long COVID progression and treating the Long COVID in a subject comprising: (a) providing a first biological sample obtained from the subject at a first time; (b) assessing a first Long COVID-related metabolite and/or proteomic profile by measuring concentration levels of at least one, at least two, at least three, at least four or at least five Long COVID-related metabolites selected from Long COVID-related metabolites selected from Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0); Lysophosphatidylcholine, Cl 6:0 (lysoPC Cl 6:0); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Succinic acid; Hydroxysphingomyelin (SM (OH)); C22:2 Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Ly
  • kits for use in the method of any one of the foregoing aspects or embodiments thereof comprising reagents for measuring concentration levels of the Long COVID-related metabolites and/or the Long COVID-related proteins, optionally together with instructions for use.
  • kits for diagnosis Long COVID comprising: (a) a detector configured to detect concentration levels of at least one, at least two, at least three, at least four or at least five Long COVID-related metabolites selected from Lysophosphatidylcholine, C18:0 (lysoPC C18:0); Lysophosphatidylcholine, C16:0 (lysoPC C16:0); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Succinic acid; Hydroxysphingomyelin (SM (OH)); C22:2 Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine, C20:4 (lysoPC C20:4); Lysophosphatidylcholine C16: l (lysoPC C16: l); Hydroxysphingomyelin (SM (OH)
  • the Long COVID-related metabolites are selected from at least one, at least two, at least three, at least four or at least five of 3- Hydroxyoleoylcamitine (C18: 1-OH); Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0); Betaalanine; Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine C16: l (lysoPC Cl 6: 1); Lysophosphatidylcholine, Cl 6:0 (lysoPC Cl 6:0); Hydroxy sphingomyelin (SM (OH)) C22:2; Dodecanedioylcamitine (C12-DC); Succinic acid; and Propionic acid.
  • C18 3- Hydroxyoleoylcamitine
  • C18 1-OH
  • Lysophosphatidylcholine, Cl 8:0 lysoPC Cl 8:
  • the Long COVID-related metabolites are selected from at least one, at least two, at least three, at least four or at least five of 3- Hydroxyoleoylcamitine (C18: 1-OH); Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0); Betaalanine; Phosphatidylcholine diacyl C32:2 (PC aa C32:2); and Lysophosphatidylcholine C16: l (lysoPC Cl 6: 1).
  • the Long COVID-related proteins are selected from at least one, at least two, at least three, at least four or at least five of Fibronectin; Lumican; Ficolin-2; Hemoglobin subunit alpha 1; Extracellular matrix protein 1; Complement Component C7; Plasminogen; Attractin; Vitamin K-dependent protein S; and Complement factor H.
  • the Long COVID-related proteins are selected from at least one, at least two, at least three, at least four or at least five of Fibronectin; Lumican; Ficolin-2; Hemoglobin subunit alpha 1; and Extracellular matrix protein 1.
  • the detector comprises a multi -metabolite detector and/or multi -proteomic detector configured to measure the levels of the Long COVID- related metabolites and/or the proteins.
  • a computer-implemented method for processing a biological sample of a subject, diagnosing Long CO VID and causing the treating the Long COVID comprising: (a) receiving a biological sample obtained from the subject; (b) processing the sample in a spectroscopy unit directly or wirelessly linked to a processing device, the processing device having memory for storing measurement data from the spectroscopy unit; (c) in the spectroscopy unit, measuring levels of at least one, at least two, at least three, at least four or at least five Long COVID-related metabolites selected from Long COVID-related metabolites selected from Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0); Lysophosphatidylcholine, C16:0 (lysoPC C16:0); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Succinic acid; Hydroxysphingomye
  • the Long COVID-related metabolites are selected from at least one, at least two, at least three, at least four or at least five of 3- Hydroxyoleoylcamitine (C18: 1-OH); Lysophosphatidylcholine, C18:0 (lysoPC C18:0); Betaalanine; Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine C16: l (lysoPC Cl 6: 1); Lysophosphatidylcholine, Cl 6:0 (lysoPC Cl 6:0); Hydroxy sphingomyelin (SM (OH)) C22:2; Dodecanedioylcamitine (C12-DC); Succinic acid; and Propionic acid.
  • C18: 1-OH 3- Hydroxyoleoylcamitine
  • Lysophosphatidylcholine, C18:0 lysoPC C18:0
  • the Long COVID-related metabolites are selected from at least one, at least two, at least three, at least four or at least five of 3- Hydroxy oleoylcamitine (C18: 1-OH); Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0); Betaalanine; Phosphatidylcholine diacyl C32:2 (PC aa C32:2); and Lysophosphatidylcholine C16: l (lysoPC Cl 6: 1).
  • the Long COVID-related proteins are selected from at least one, at least two, at least three, at least four or at least five of Fibronectin; Lumican; Ficolin-2; Hemoglobin subunit alpha 1; Extracellular matrix protein 1; Complement Component C7; Plasminogen; Attractin; Vitamin K-dependent protein S; and Complement factor H.
  • the Long COVID-related proteins are selected from at least one, at least two, at least three, at least four or at least five of of Fibronectin; Lumican; Ficolin-2; Hemoglobin subunit alpha 1; and Extracellular matrix protein 1.
  • a method for diagnosing and treating Long CO VID comprising: (a) obtaining a signature of metabolites and proteins from a biological sample of a patient, the signature obtained by measuring Long COVID-related metabolites selected from Lysophosphatidylcholine, C18:0 (lysoPC C18:0); Lysophosphatidylcholine, C16:0 (lysoPC C16:0); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Succinic acid; Hydroxysphingomyelin (SM (OH)); C22:2 Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine, C20:4 (lysoPC C20:4); Lysophosphatidylcholine C16: l (lysoPC C16: l); Hydroxysphingomyelin (SM (OH)); C22:2 Phosphat
  • the Long COVID-related metabolites are selected from at least one, at least two, at least three, at least four or at least five of of 3 -Hydroxy oleoylcamitine (C18: 1-OH); Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0); Betaalanine; Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine C16: l (lysoPC Cl 6: 1); Lysophosphatidylcholine, Cl 6:0 (lysoPC Cl 6:0); Hydroxy sphingomyelin (SM (OH)) C22:2; Dodecanedioylcamitine (C12-DC); Succinic acid; and Propionic acid.
  • C18 3 -Hydroxy oleoylcamitine
  • Lysophosphatidylcholine, Cl 8:0
  • the Long COVID-related metabolites are selected from at least one, at least two, at least three, at least four or at least five of 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Lysophosphatidylcholine, C18:0 (lysoPC C18:0); Betaalanine; Phosphatidylcholine diacyl C32:2 (PC aa C32:2); and Lysophosphatidylcholine C16: l (lysoPC Cl 6: 1).
  • the Long COVID-related proteins are selected from at least one, at least two, at least three, at least four or at least five of Fibronectin; Lumican; Ficolin-2; Hemoglobin subunit alpha 1; Extracellular matrix protein 1; Complement Component C7; Plasminogen; Attractin; Vitamin K-dependent protein S; and Complement factor
  • the Long COVID-related proteins are selected from at least one, at least two, at least three, at least four or at least five of of Fibronectin; Lumican; Ficolin-2; Hemoglobin subunit alponeha 1; and Extracellular matrix protein
  • the method further comprises adjusting or causing the adjustment of the levels of the metabolites and/or proteins comprises nucleic acid therapy.
  • the nucleic acid therapy comprises reducing the level of a protein expressed or metabolite produced by siRNA or antisense therapy.
  • the nucleic acid therapy comprises increasing the level of a protein expressed or metabolite produced by mRNA therapy.
  • the metabolite and/or proteome profile measured is based on a profile identified in a previous computer-implemented statistical analysis model that has a predictive value of at least 90% and comprises at least one of means comparison, PC A, PLS-DA or recursive SVM data analyses.
  • the metabolite and/or proteome profile has been previously identified as having the predictive value by classifying disease and non-disease samples into the two groups by a computer-implemented method based on the predicted metabolites and/or proteins used in the computer model and assessing whether the groups are separated.
  • a method of identifying a subject’s risk of developing Long COVID or identifying the subject as having Long COVID comprising: (a) obtaining one or more biological samples from the subject; (b) conducting a metabolomic and proteomic analysis of the one or more biological samples; (c) measuring at least at least one, two or all metabolites selected Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0); Lysophosphatidylcholine, C16:0 (lysoPC C16:0); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Succinic acid; Hydroxysphingomyelin (SM (OH)); C22:2 Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine, C20:4 (lysoPC C20:4); Lysophosphat
  • a computer system comprising: (a) a high throughput spectroscopy unit for receiving one or more biological samples from a subject, and conducting a metabolomic and proteomic analysis of a panel of at least 25 metabolic and proteomic markers in the one or more biological samples; (b) optionally a computer processor for outputting a digital metabolomic and proteomic signature of the subject; (c) a computer processor for determining whether at least three Long COVID-related predictive metabolites are present at levels that differ from a control reference, thereby indicative of Long Covid, the predictive metabolites selected from 3 -Hydroxy oleoylcamitine (C18: 1-OH); Lysophosphatidylcholine, C18:0 (lysoPC C18:0); Beta-alanine; Phosphatidylcholine diacyl C32:2 (PC aa C32:2); and Lysophosphatidylcholine C
  • Fig. 1A and IB show box plots for the short COVID vs. health control metabolites tested in Example 1.
  • Fig. 2A and 2B show box plots for the short CO VID vs. health control proteins tested in Example 1.
  • FIG. 3A and Fig. B show box plots for the short COVID vs. long COVID control metabolites tested in Example 2.
  • Fig. 4 shows box plots for the short COVID vs. long COVID control proteins tested in Example 2.
  • Fig. 5 shows a PCA scatter plot for short COVID vs. healthy controls metabolomics data of Example 3.
  • Fig. 6 shows a PCA scatter plot for short COVID vs. healthy controls proteomics data of Example 3.
  • Fig. 7 shows a PCA scatter plot for short COVID vs. long COVID controls metabolomics data of Example 3.
  • Fig. 8 shows a PCA scatter plot for short COVID vs. long COVID controls proteomics data of Example 3.
  • Fig. 9 shows a Partial Lease Squares Discriminate Analysis (PLS-DA) scatter plot for short CO VID vs. healthy controls metabolomics data of Example 4.
  • Fig. 10 shows a ROC curve for short COVID vs. healthy controls metabolomics data of Example 4.
  • Fig. 11 shows VIP scores for the metabolites identified by the short COVID vs. healthy controls metabolomics data of Example 4.
  • Fig. 12 shows a Partial Lease Squares Discriminate Analysis (PLS-DA) scatter plot for short CO VID vs. healthy controls proteomics data of Example 4.
  • Fig. 13 shows a ROC curve for short COVID vs. healthy controls proteomics data of Example 4.
  • Fig. 14 shows VIP scores for the proteins identified by the short COVID vs. healthy controls proteomics data of Example 4.
  • Fig. 15 shows a Partial Lease Squares Discriminate Analysis (PLS-DA) scatter plot for long CO VID vs. short CO VID metabolomics data of Example 5.
  • Fig. 16 shows a ROC curve for long COVID vs. short COVID controls metabolomics data of Example 5.
  • Fig. 17 shows VIP scores for the proteins identified by long COVID vs. short COVID metabolomics data of Example 5.
  • Fig. 18 shows a Partial Lease Squares Discriminate Analysis (PLS-DA) scatter plot for long CO VID vs. short CO VID proteomics data of Example 5.
  • Fig. 19 shows a ROC curve for long COVID vs. short COVID controls proteomics data of Example 5.
  • Fig. 20 shows VIP scores for the proteins identified by long CO VID vs. short COVID proteomics data of Example 5.
  • Long COVID and “Post-COVID Condition” are used interchangeably to generally describe a condition caused or suspected of being caused by an earlier infection with the Sars-Cov-2 virus.
  • Long COVID-negative generally refers to a biological sample from an individual that does not suffer from Long COVID.
  • Long CO VID treatment regime generally refers to an intervention made in response to a subject suffering from Long COVID.
  • the aim of the regime may include, but is not limited to, one or more of the alleviation or prevention of symptoms, slowing or stopping the progression or worsening of Long COVID and the remission of Long COVID.
  • Long COVID treatment regime refers to therapeutic treatment (e.g., changing Long COVID-related metabolite levels and/or protein levels), dietary adjustments, and/or nutritional supplements.
  • Metabolites generally refers to any molecule involved in metabolism. Metabolites can be products, substrates or intermediates in metabolic processes. Metabolites may include, without limitation, amino acids, peptides, acylcamitines, monosaccharides, lipids and phospholipids, lysophospholipid, sphingolipids, glycerophospholipids, glucose, prostaglandins, hydroxy eicosatetraenoic acids, hydroxy octadecadienoic acids, steroids, bile acids, glycolipids and phospholipids, including but not limited to lysophospholipids.
  • protein generally refers to a protein, fragment or peptide thereof unless otherwise specified.
  • Long COVID-related metabolite or “metabolomic profile” generally refers to metabolites associated with Long COVID comprising one, two or more metabolites described herein or a combination thereof.
  • Long COVID-related protein or “proteomic profile” generally refers to a profile of proteins, protein fragments and/or peptides associated with Long COVID comprising two or more, three or more, four or more, or five or more proteins described herein or a combination thereof.
  • quantification of a protein can comprise quantifying a fragment or peptide thereof.
  • preventing and “prevention” are used interchangeably and generally refer to any activity that leads to a reduction in risk of developing Long COVID in the subject.
  • subject or “patient” is used without limitation and generally refers to a vertebrate, such as a mammal.
  • mammal is defined as individual belonging to the class Mammalia and includes, without limitation, humans, domestic and farm animals, and zoo, sports or pet animals, such as sheep, dogs, horses, cats or cattle. In some embodiments, the subject is human.
  • treating generally refers to an intervention made in response to Long CO VID or associated symptoms manifested by a subject.
  • the aim of treatment may include, but is not limited to, one or more of the alleviation or prevention of Long COVID, slowing or stopping the progression or worsening of Long COVID and the remission of Long COVID.
  • treatment refers to therapeutic, dietary and/or supplemental therapy.
  • the present disclosure relates to methods for diagnosis and treatment of Long COVID, and any associated symptoms, in a subject.
  • the disclosure is based, at least in part, on the identification of new metabolites and/or new proteins that provide for metabolite-based and/or protein/peptide-based identification of Long COVID in a subject that can lead to more effective therapy.
  • metabolic and/or proteomic profiling as described herein can provide molecular-based tests that aid in individualized treatment regimes.
  • metabolomic and/or proteomic based analyses as disclosed herein have the advantage of identifying marker profiles derived from an individual’s inherited genes and/or the interactions of the individual’s current lifestyle behaviors (e.g., smoking, alcohol consumption, sleep behaviours, physical activity and the like), gut microbiome, dietary, and environmental factors that contribute to the unique metabolic profile and/or proteomic profile of a subject with Long COVID. Therefore, the present disclosure provides an advancement in the art.
  • the metabolomic profile for Long COVID comprises at least one, at least two, at least three, at least four or at least five Long COVID-related metabolites selected from Lysophosphatidylcholine, C18:0 (lysoPC C18:0); Lysophosphatidylcholine, C16:0 (lysoPC C16:0); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Succinic acid; Hydroxysphingomyelin (SM (OH)); C22:2 Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine, C20:4 (lysoPC C20:4); Lysophosphatidylcholine C16: l (lysoPC C16: l); Hydroxysphingomyelin (SM (OH)) C22:l; Beta-alanine; Serotonin; Is
  • the metabolomic profile for Long CO VID comprises at least one, at least two, at least three, at least four or at least five Long COVID-related metabolites selected from spermine, pyruvic acid; 3 -(3 -hydroxyphenyl)-3 -hydroxypropionic acid (HPHPA); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); phosphatidylcholine diacyl C32:2 (PC aa C32:2); hydroxysphingomyelin (SM (OH)) C22:2; lysophosphatidylcholine, C18:0 (lysoPC C18:0); and succinic acid.
  • HPHPA 3 -(3 -hydroxyphenyl)-3 -hydroxypropionic acid
  • HPHPA 3 -Hydroxy oleoylcarnitine
  • PC aa C32:2 phosphatidylcholine diacyl C32:2
  • the metabolomic profile for Long COVID comprises at least one, at least two or all of the Long COVID-related metabolites selected from spermine, pyruvic acid; 3 -(3 -hydroxyphenyl)-3 -hydroxypropionic acid (HPHPA) and 3- Hydroxyoleoylcamitine (C 18 : 1 -OH).
  • a new proteomic profile for Long COVID is identified in a subject having Long COVID.
  • the proteomic profile for Long COVID comprises at least one, at least two, at least three, at least four or at least five Long COVID-related proteins, peptides or fragments thereof selected from Fibronectin; Ficolin-2; Hemoglobin subunit alpha 1; Lumican; Extracellular matrix protein 1; Alpha- 1 -antitrypsin; Complement C2; Complement factor I; Coagulation factor XIII B chain; Complement C3; Complement factor H; Plasma protease Cl Inhibitor; Coagulation factor X; Plasma serine protease inhibitor; and Complement C5.
  • the proteomic profile for Long COVID comprises at least one, at least two, at least three, at least four or at least five Long COVID-related proteins, peptides or fragments thereof selected from carboxypeptidase N subunit 2; inter-alpha-trypsin; extracellular matrix 1; zinc-alpha-2-gly coprotein; coagulation factor X; complement C2; lumican; and complement factor H.
  • the proteomic profile for Long COVID comprises at least one, at least two or all of the Long COVID-related proteins selected from carboxypeptidase N subunit 2; inter-alpha-trypsin; and extracellular matrix 1.
  • the metabolomic profile and/or proteomic profile are altered in a subject suffering from CO VID as compared to non-COVID individual.
  • the levels of the Long COVID-related metabolites and/or Long COVID-related proteins may be altered in circulation of the subject having Long CO VID as compared to a non-Long COVID individual.
  • the levels of the Long COVID-related metabolites and/or Long COVID-related proteins are altered in the blood (e.g., serum, plasma), body fluids (e.g., cerebrospinal fluid, pleural fluid, amniotic fluid, semen, or saliva), urine, and/or feces of the subject having Long CO VID.
  • body fluids e.g., cerebrospinal fluid, pleural fluid, amniotic fluid, semen, or saliva
  • urine e.g., urine, and/or feces of the subject having Long CO VID.
  • the Long COVID-related metabolites and/or Long COVID-related proteins play a causative role in the development of Long COVID-related symptoms in the subject having Long COVID.
  • the present disclosure provides for a method for diagnosing and treating Long COVID in a subject.
  • the method comprises step (a) providing a biological sample obtained from the subject, preferably a human.
  • a biological sample obtained from the subject preferably a human.
  • any type of biological sample that originates anywhere from the body of a subject may be tested, including but not limited to, blood (including, but not limited to serum or plasma), cerebrospinal fluid (“CSF”), pleural fluid, urine, stool, sweat, tears, breath condensate, saliva vitreous humour, a tissue sample, amniotic fluid, a chorionic villus sampling, brain tissue, a biopsy of any solid tissue 1 including tumor, adjacent normal, smooth and skeletal muscle, adipose tissue, liver, skin, hair, brain, kidney, pancreas, lung or the like may be used.
  • the biological sample obtained from a live subject is urine.
  • the Long COVID-related metabolites and/or proteins may be extracted from their biological source
  • the method further comprises step (b) measuring from the obtained sample, concentration levels of at least one, at least two, at least three, at least four or at least five Long COVID-related metabolites selected from Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0); Lysophosphatidylcholine, C16:0 (lysoPC C16:0); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Succinic acid; Hydroxysphingomyelin (SM (OH)); C22:2 Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine, C20:4 (lysoPC C20:4); Lysophosphatidylcholine C16: l (lysoPC C16: 1); Hydroxysphingomyelin (SM (OH)) C22: l; Beta-alanine; Serot
  • the method comprises measuring at least 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20 Long COVID-related metabolites and/or proteins from the obtained sample.
  • the measurement of the concentration levels of the Long COVID-related metabolites and/or proteins may be through mass spectrometry, including but not limited to gas chromatography mass spectrometry (GC-MS) GC and liquid chromatography mass spectrometry (e.g., LC-MS, LC-MS-MS, LC-MRM, LC-SIM, and LC-SRM).
  • mass spectrometry including but not limited to gas chromatography mass spectrometry (GC-MS) GC and liquid chromatography mass spectrometry (e.g., LC-MS, LC-MS-MS, LC-MRM, LC-SIM, and LC-SRM).
  • the Long COVID-related metabolites are measured by a spectroscopic technique, wherein the spectroscopic technique is selected from the group consisting of liquid chromatography, gas chromatography, liquid chromatography mass spectrometry, gas chromatography mass spectrometry, high performance liquid chromatography mass spectrometry, capillary electrophoresis mass spectrometry, nuclear magnetic resonance spectrometry (NMR), raman spectroscopy, and infrared spectroscopy.
  • the measurement may also be performed under other methodology, such as for example, a colorimetric, enzymatic, immunological methodology, and gene expression analysis including, for example, real-time PCR, RT-PCT, northern analysis, and in situ hybridization.
  • the mass spectrometry process for determining whether the Long COVID-related proteins are elevated comprises enzymatic or chemical digestion of the proteins or peptide fragments thereof of a sample obtained from a subject into peptide fragments.
  • the peptide fragments are optionally separated and/or ionized and captured by mass spectrometry.
  • the digestion may comprise a proteolytic digestion involving treating a preparation comprising the Long COVID-related proteins with an acid, base, or an enzyme such as trypsin or other proteolytic enzyme.
  • One embodiment comprises a shotgun proteomics quantification in which the whole proteins in a complex mixture, such as serum, urine, and cell lysates, are hydrolyzed or otherwise cut into peptides and followed by multidimensional HPLC-MS, which aims to generate a global profile of protein mixtures as genome “shotgun” sequencing.
  • a complex mixture such as serum, urine, and cell lysates
  • a method for determining whether Long COVID-related proteins, or peptide fragments thereof, are elevated in a sample obtained from a subject the Long COVID-related proteins, peptides or fragments thereof being selected from at least one of Fibronectin; Ficolin-2; Hemoglobin subunit alpha 1; Lumican; Extracellular matrix protein 1; Alpha- 1 -antitrypsin; Complement C2; Complement factor I; Coagulation factor XIII B chain; Complement C3; Complement factor H; Plasma protease Cl Inhibitor; Coagulation factor X; Plasma serine protease inhibitor; and Complement C5, the method comprising enzymatic or chemical digestion of the proteins or peptide fragments thereof of the sample obtained from a subject into peptide fragments to produce peptide fragments thereof; introducing a solution comprising the peptide fragments to a mass spectrometer, optionally after one or more treatments
  • the peptide fragments include at least one, at least two, at least three, at least four or at least five Long COVID-related protein fragments selected from Fibronectin; Ficolin-2; Hemoglobin subunit alpha 1; Lumican; Extracellular matrix protein 1; Alpha- 1 -antitrypsin; Complement C2; Complement factor I; Coagulation factor XIII B chain; Complement C3; Complement factor H; Plasma protease Cl Inhibitor; Coagulation factor X; Plasma serine protease inhibitor; and Complement C5.
  • Long COVID-related protein fragments selected from Fibronectin; Ficolin-2; Hemoglobin subunit alpha 1; Lumican; Extracellular matrix protein 1; Alpha- 1 -antitrypsin; Complement C2; Complement factor I; Coagulation factor XIII B chain; Complement C3; Complement factor H; Plasma protease Cl Inhibitor; Coagulation factor X; Plasma serine proteas
  • the peptide fragments include at least one, at least two, at least three, at least four or at least five Long COVID-related proteins selected from Fibronectin; Ficolin-2; Hemoglobin subunit alpha 1; Lumican; Extracellular matrix protein 1; Alpha- 1- antitrypsin; Complement C2; Complement factor I; Coagulation factor XIII B chain; Complement C3; Complement factor H; Plasma protease Cl Inhibitor; Coagulation factor X; Plasma serine protease inhibitor; and Complement C5.
  • Long COVID-related proteins selected from Fibronectin; Ficolin-2; Hemoglobin subunit alpha 1; Lumican; Extracellular matrix protein 1; Alpha- 1- antitrypsin; Complement C2; Complement factor I; Coagulation factor XIII B chain; Complement C3; Complement factor H; Plasma protease Cl Inhibitor; Coagulation factor X; Plasma serine protease inhibitor; and Complement C5.
  • the peptide fragments for Long COVID comprises at least one, at least two, at least three, at least four or at least five Long COVID-related proteins selected from Fibronectin; Ficolin-2; Hemoglobin subunit alpha 1; Lumican; Extracellular matrix protein 1; Alpha- 1 -antitrypsin; Complement C2; Complement factor I; Coagulation factor XIII B chain; Complement C3; Complement factor H; Plasma protease Cl Inhibitor; Coagulation factor X; Plasma serine protease inhibitor; and Complement C5.
  • Long COVID-related proteins selected from Fibronectin; Ficolin-2; Hemoglobin subunit alpha 1; Lumican; Extracellular matrix protein 1; Alpha- 1 -antitrypsin; Complement C2; Complement factor I; Coagulation factor XIII B chain; Complement C3; Complement factor H; Plasma protease Cl Inhibitor; Coagulation factor X; Plasma serine protea
  • the methods may further include measuring the concentration levels of one or more additional Long COVID-related metabolites and/or proteins, including, but not limited to, any of those described herein and/or additional markers known in the art.
  • the novel approach of the present disclosure identifies biomarkers that have high predictive value for a subset of the diagnostic class (i.e., Long COVID in this case).
  • the advantage of including additional Long COVID-related metabolites and/or proteins is to increase the overall sensitivity of the diagnostic method.
  • the method described herein further comprises step (c) comparing the concentration levels of the Long COVID-related metabolites and/or proteins from the obtained sample to the concentration levels of reference Long COVID-related metabolites and/or proteins from an Long COVID-negative sample.
  • references can be established as a value representative of the level of Long COVID-related metabolites and/or proteins in a non- Long COVID population that do not suffer from Long COVID for the comparison.
  • Various criteria may be used to determine the inclusion and/or exclusion of a particular subject in the reference population, including age of the subject (e.g., the reference subject can be within the same age group as the subject in need of treatment) and gender of the subject (e.g., the reference subject can be the same gender as the subject in need of treatment).
  • the method described herein further comprises step (d) identifying the subject as having Long COVID if the concentration levels of the Long COVID-related metabolites and/or proteins, peptides or fragments thereof from the obtained sample are different relative to the concentration levels of the reference.
  • the identifying step (d) occurs upon determination that the concentration level of the at least one Long COVID-related metabolite and/or protein, peptide or fragments thereof from the obtained sample differs by about 20% or more, about 30% or more, about 40% or more, about 50% or more, about 60% or more, or about 70% or more relative to the concentration level of the at least one reference Long COVID-related metabolites and/or proteins from the Long COVID-negative sample.
  • the identifying step (d) occurs upon determination that the concentration levels of at least two, at least three, at least four or at least five Long COVID-related metabolites and/or proteins from the obtained sample differ by about 20% or more, about 30% or more, about 40% or more, about 50% or more, about 60% or more, or about 70% or more relative to the concentration levels of the reference Long COVID- related metabolites and/or proteins from the Long COVID-negative sample.
  • the method described herein further comprises step (e) treating the subject so identified as having Long COVID with a Long COVID treatment regime.
  • the comparison of the concentration level of the at least one Long COVID-related metabolite and/or protein from the obtained sample to the concentration level of the reference Long COVID-related metabolite and/or protein from the Long COVID-negative sample comprises using multivariate statistical analysis.
  • the multivariate statistical analysis is selected from principal component analysis (“PC A”), or partial least squares projects to latent structures discriminant analysis (“PLS-DA”).
  • PC A principal component analysis
  • PLS-DA latent structures discriminant analysis
  • a computer is used for statistical analysis. Data for statistical analysis can be extracted from chromatograms (i.e., spectra of mass signals) using software for statistical methods known in the art.
  • the present disclosure relates to a method of monitoring Long COVID progression and treating Long CO VID in a subject.
  • the method includes quantifying the Long COVID-related metabolites and/or proteins at one or more time points after the initiation of treatment to monitor Long COVID progression (e.g., rate of decline or rate of improvement of Long CO VID progression) in a subject.
  • the method comprises: (a) providing a first biological sample obtained from the subject at a first time; (b) assessing a first Long COVID-related metabolite profile by measuring concentration levels of at least one, at least two, at least three, at least four or at least five Long COVID-related metabolites selected from Lysophosphatidylcholine, C18:0 (lysoPC Cl 8:0); Lysophosphatidylcholine, Cl 6:0 (lysoPC Cl 6:0); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Succinic acid; Hydroxysphingomyelin (SM (OH)); C22:2 Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine, C20:4 (lysoPC C20:4); Lysophosphatidylcholine C16: l (lysoPC C
  • the period between the first time and the second time is at least 1 month, at least 2 months, at least 3 months, at least 6 months, at least 9 months, or at least 12 months, preferably at least 3 months.
  • the treatment has been administered to the subject before the first two biological samples have been obtained. In other embodiments, the treatment has been administered to the subject in the interval(s) between the taking of the biological samples.
  • the first biological sample, the second biological sample, or both are blood or urine, preferably serum, plasma or urine.
  • the metabolomic profile for Long COVID comprises at least one, at least two, at least three, at least four or at least five Long COVID-related metabolites selected from spermine, pyruvic acid; 3 -(3 -hydroxyphenyl)-3 -hydroxypropionic acid (HPHPA); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); phosphatidylcholine diacyl C32:2 (PC aa C32:2); hydroxysphingomyelin (SM (OH)) C22:2; lysophosphatidylcholine, C18:0 (lysoPC C18:0); and succinic acid.
  • HPHPA 3 -(3 -hydroxyphenyl)-3 -hydroxypropionic acid
  • HPHPA 3 -Hydroxy oleoylcarnitine
  • PC aa C32:2 phosphatidylcholine diacyl C32:2
  • the metabolomic profile for Long COVID comprises at least one, at least two or all of the Long COVID-related metabolites selected from spermine, pyruvic acid; 3 -(3 -hydroxyphenyl)-3 -hydroxypropionic acid (HPHPA) and 3-
  • the proteomic profile for Long CO VID comprises at least one, at least two, at least three, at least four or at least five Long COVID-related proteins selected from carboxypeptidase N subunit 2; inter-alpha-trypsin; extracellular matrix 1; zinc-alpha-2-glycoprotein; coagulation factor X; complement C2; lumican; and complement factor
  • the proteomic profile for Long CO VID comprises at least one, at least two, at least three, at least four or at least five Long COVID-related proteins selected from carboxypeptidase N subunit 2; inter-alpha-trypsin; and extracellular matrix
  • the Long COVID treatment regime has the effect of adjusting the concentration levels of one or more of the Long COVID-related metabolites and/or proteins in the subject identified as having Long COVID towards the corresponding levels of the reference Long COVID-related metabolites and/or proteins from the Long COVID-negative sample.
  • Various methods can be used to adjust the concentration level, for example blood level (e.g., serum level), of the Long COVID-related metabolite and/or protein in the subject.
  • blood level e.g., serum level
  • the adjustment of the concentration level of the one or more Long COVID-related metabolites in the subject occurs until an improvement in symptoms in the subject is observed.
  • an antibody that specifically binds the Long COVID-related metabolite, an intermediate for the in vivo synthesis of the Long COVID-related metabolite, or a substrate for the in vivo synthesis of the Long COVID-related metabolite can be administered to the subject.
  • an antibody that specifically binds one or more of metabolites and/or proteins on the metabolomic and/or proteomic profile can be used to reduce the levels thereof in the subject.
  • the concentration level, for example blood level (e g., serum level), of the one or more Long COVID-related metabolites is adjusted by adjusting the composition of gut microbiota in the subject.
  • nucleic acid therapy can be used to reduce the concentration of a protein (which includes a peptide) by using, for example, siRNA or antisense oligonucleotides to reduce expression of the protein.
  • nucleic acid therapy can be used to express a protein that is present at lower levels in the Long COVID-free reference using mRNA therapy.
  • the therapeutic nucleic acid can be encapsulated in a suitable delivery vehicle.
  • Nucleic acid therapy can also be used to increase the level of a metabolite described herein by using, for example, mRNA, antisense or siRNA therapy by, for example, modulating the activity of a protein that is involved in metabolism.
  • the subject diagnosed or identified as being predisposed to developing Long COVID is treated or caused to be treated with an approved Long COVID therapeutic, such as a drug.
  • the drug may be approved by any applicable regulator.
  • An example of a Long COVID drug is nirmatrelvir/ritonavir (Paxlovid).
  • Other examples include beta blockers or metformin.
  • the Long COVID drug is selected from Paxlovid or metformin.
  • the metabolomic and/or proteomic profile described herein may be utilized in tests, assays, methods, kits for diagnosing, predicting, modulating or monitoring Long COVID, including ongoing assessment, monitoring and/or susceptibility assessment.
  • the present disclosure includes a kit for diagnosis of Long COVTD by measuring and identifying at least one or more Long COVID-related metabolites and/or protein associated with Long COVID.
  • the kit may comprise appropriate Long COVID treatment regime to be initiated upon the determination of Long COVID.
  • the kit comprises (a) a detector configured to detect concentration levels of at least one, at least two, at least three, at least four or at least five Long COVID-related metabolites selected from Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0); Lysophosphatidylcholine, C16:0 (lysoPC C16:0); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Succinic acid; Hydroxysphingomyelin (SM (OH)); C22:2 Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine, C20:4 (lysoPC C20:4); Lysophosphatidylcholine C16: l (lysoPC C16: 1); Hydroxysphingomyelin (SM (OH)) C22: l; Beta-alanine; Serotonin;
  • the kit may be for the measurement of the Long COVID-related metabolites and/or proteins by a physical separation technique (as described herein above). In some aspects, the kit may be for measurement of the Long COVID-related metabolites and/or proteins by a methodology other than a physical separation method, such as for non-limiting example, a colorimetric, enzymatic, and immunological methodology.
  • the kit may also include one or more appropriate negative and/or positive controls. Kits of the present disclosure may include other reagents such as buffers and solutions needed to perform the tests.
  • the metabolite and/or proteome profile measured is based on a profile identified in a previous computer-implemented statistical analysis model that has a predictive value of at least 80%, 85%, 90%, 92%, 94% or 96% and comprises at least one of means comparison, PC A, PLS-DA or recursive SVM data analyses.
  • the metabolite and/or proteome profile is identified as having the predictive value by classifying the samples into the two groups by a computer-implemented method based on the predicted metabolites and/or proteins used in the computer model, wherein the data from two groups are sufficiently separated, such as on a scores plot (e.g., see Examples below and Figures 4 and 12 that exemplify separation of a control and COVID cohorts).
  • the disclosure is also directed to a computer-implemented method for processing a biological sample of a subject, diagnosing aLong CO VID and treating (or causing treatment thereof) of the subject diagnosed with Long COVID.
  • the computer- implemented method may further allow monitoring of Long COVID progression across multiple time points to support a more effective treatment regime.
  • the computer-implemented method comprises receiving a biological sample from the subject; processing the sample in a spectroscopy unit directly or wirelessly linked, or may utilize any suitable communication technology, to a processing device, the processing device having memory for storing measurement data from the spectroscopy unit; and in the spectroscopy unit, measuring levels of least one, at least two, at least three, at least four or at least five Long COVID- related metabolites selected from Lysophosphatidylcholine, C18:0 (lysoPC C18:0); Lysophosphatidylcholine, C16:0 (lysoPC C16:0); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Succinic acid; Hydroxysphingomyelin (SM (OH)); C22:2 Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine, C20:4 (lyso
  • the processing device comprises one or more data storage devices that may be configured or adapted to store data related to the method.
  • the data storage device may be configured or adapted to store measurement data from the spectroscopy unit.
  • the data storage device may also comprise computer program code stored thereon.
  • the program code of this embodiment may include program code for at least performing the steps of the method aspect upon execution thereof.
  • the computer-implemented method further comprises comparing the stored measurement data to a value in the memory representing an Long COVID-negative sample using multivariate statistical analysis; storing on the processing device a result corresponding to at least one, at least two, at least three, at least four or at least five Long COVID-related metabolites selected from Lysophosphatidylcholine, C18:0 (lysoPC C18:0); Lysophosphatidylcholine, C16:0 (lysoPC C16:0); 3 -Hydroxy oleoylcarnitine (C18: 1-OH); Succinic acid; Hydroxysphingomyelin (SM (OH)); C22:2 Phosphatidylcholine diacyl C32:2 (PC aa C32:2); Lysophosphatidylcholine, C20:4 (lysoPC C20:4); Lysophosphatidylcholine C16: l (lysoPC C
  • the displayed treatment regime comprises electronic text, optionally with graphical icons, on a graphical user interface describing one or more of: dietary adjustments, nutritional supplements, behavior training or a combination thereof, to the subject diagnosed as having or predisposed of developing the Long COVID, or adjusting the blood levels of one or more of the Long COVID- related metabolites and/or proteins in the subject diagnosed as having or predisposed of developing the Long COVID until an improvement in the cognitive and/or behavioral performance in the subject is observed; preferably the adjustment of the blood levels of one or more of the Long COVID-related metabolites comprises adjusting the composition of gut microbiota in the subject.
  • a wireless smart device comprising an application receives results from a metabolomic and/or proteomic analysis of the subject.
  • the wireless smart device displays results of the metabolomic and proteomic analysis via the application.
  • the application may have a dashboard displaying an assigned score for the Long COVID-related metabolites and proteins, and optionally displays a treatment regime based on the assigned scores of the predictive metabolites and proteins.
  • the smart device receives data from a database comprising the results of the metabolomic and proteomic analysis.
  • a graphical user interface comprises a dashboard with the graphical icons describing one or more treatment regimes.
  • Supervised machine learning is a type of artificial intelligence that can be used to build predictive models for disease prediction.
  • the process uses a large dataset of labeled patient information, which can include demographic information, medical and family history, and clinical results, to train a machine learning algorithm to identify patterns and relationships that are associated with a particular risk of developing that disease.
  • the inventors used this method to classify the molecular profile of long COVID and healthy controls as well as long CO VID verses short CO VID to develop a machine learning (ML) model that can predict if a new sample belongs to each category.
  • the demographics for the data sets used in the analysis are set forth in Table 1 and Table 2 below. Table 1 shows the demographics for the short COVID samples and the controls, which were healthy age and sex- matched.
  • Table 2 shows the demographics for the long CO VID and the short CO VID samples. This comparison was to determine if there were any distinguishing features for patients with long-COVID.
  • Example 1 Student T-test and box plots for short CO VID vs. healthy control
  • a means comparison using a student t-test was conducted on transformed metabolomic and proteomic data for short COVID vs. healthy controls.
  • the first 10 rows of the T-test output for the metabolites are displayed below (Table 3).
  • the biomarkers are sorted by the lowest P- value (FDR) first, followed by the highest fold change.
  • Example 2 Student T-test and box plots for long COVID vs. short COVID control
  • Example 3 Principal component analysis (PCA) of metabolomic and proteomic data for short COVID vs healthy controls and long COVID vs. short COVID controls
  • PCA principal component analysis
  • a PCA scores plot is a graphical representation of the results of a principal component analysis (PCA) carried out on a dataset.
  • PCA is a statistical technique that is used to reduce the dimensionality of a dataset by identifying and removing redundant or correlated variables and projecting the data onto a smaller number of orthogonal (uncorrelated) dimensions, called principal components.
  • a PCA scores plot is a scatterplot that shows the projection of the data onto the first two principal components.
  • Each point on the plot represents a single data point from the original dataset, and the position of the point reflects the values of the data point on the two principal components.
  • the x-axis of the plot represents the first principal component, and the y-axis represents the second principal component.
  • Example 4 Partial least squares discriminant analysis (PLS-DA) of metabolomic and proteomic data for short COVID vs healthy controls
  • PLS-DA is a supervised learning technique that combines partial least squares regression (PLS) and linear discriminant analysis (LDA) to classify data into different classes.
  • the analysis is a non-linear technique based on the relationship between predictor and response variables.
  • PLS- DA is used to find latent variables that best discriminate between classes.
  • the PC A scatter plot for short COVID vs. healthy controls metabolomics data is shown in Figure 9.
  • the model metrics are shown in Table 7 below:
  • ROC Receiver Operating Curve
  • the Receiver Operating Curve (ROC) curve for short COVID vs. healthy controls metabolomics data is shown in Figure 10.
  • the CI is between 0.9 and 0.93.
  • ROC is a graphical representation of the performance of a binary classification model. It is plotted on a two- dimensional graph with the true positive rate on the y-axis and the false positive rate on the x-axis. A model with a higher true positive rate and a lower false positive rate will have a better performance.
  • Area under the curve (AUC) is a measure of the separability of the classes in the data. It is calculated as the area under the Receiver Operating Characteristic (ROC) curve, which plots the true positive rate (sensitivity) against the false positive rate (1 -specificity) at various threshold settings.
  • AUC is a single value between 0 and 1 that represents the overall performance of the model, regardless of the decision threshold. AUC is insensitive to changes in the class distribution and it does not rely on a specific decision threshold
  • Figure 11 shows VIP scores for each metabolite ranked based on average importance.
  • Table 8 summarizes the top 15 predictive COVID-related metabolites.
  • Table 8 Top 15 predictive COVID-related metabolites identified by short COVID vs. healthy control data
  • the inventors’ model identified Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0) and Lysophosphatidylcholine, C16:0 (lysoPC C16:0) as having the highest average importance among the metabolites tested. Both metabolites were present at higher concentrations in COVID patients relative to the control samples.
  • the inventors’ model also identified 3 -Hydroxy oleoylcarnitine (C18: 1-OH) and Succinic acid as having a high average importance among the metabolites tested. Both metabolites were present at lower concentrations in COVID patients relative to the control samples.
  • Figure 14 shows VIP scores for each protein ranked based on average importance.
  • Table 10 summarizes the top 15 predictive COVID-related proteins.
  • Table 10 Top 15 predictive proteins/peptides of COVID identified by short COVID vs. healthy control data [00168]
  • the inventors’ machine learning model identified Fibronectin as having the highest average importance among the proteins/peptides tested. Fibronectin was present at higher concentrations in COVID patients relative to the control samples.
  • Ficolin-2 and Hemoglobin subunit alpha 1 were identified as having a high average importance among the proteins and peptides tested. Ficolin-2 was present at lower concentrations in COVID patients relative to the control samples and Hemoglobin subunit alpha 1 was present at higher concentrations.
  • Example 5 Partial least squares discriminant analysis (PLS-DA) of metabolomic and proteomic data for long COVID vs short COVID controls
  • Figure 17 shows VIP scores for each metabolite ranked based on average importance.
  • Table 12 summarizes the top 15 predictive COVID-related metabolites based on the long vs. short COVID metabolomics data.
  • Table 12 Top 15 predictive metabolites of COVID identified by long COVID vs. short COVID control data
  • the inventors’ model identified Lysophosphatidylcholine, Cl 8:0 (lysoPC Cl 8:0) and Lysophosphatidylcholine, Cl 6:0 (lysoPC Cl 6:0) as having high average importance among the metabolites tested. Both metabolites were present at higher concentrations in COVID patients relative to the control samples (Example 4 above) as well as in long vs. short COVID patients (Table 12 above).
  • the inventors’ model also identified 3 -Hydroxy oleoylcarnitine (C18: 1-OH) as having a high average importance among the metabolites tested. This metabolite was present at lower concentrations in long vs. short COVID patients (Table 12 above) as well as in short COVID vs. health controls (Example 4). Proteomics
  • Figure 20 shows VIP scores for each protein ranked based on average importance.
  • Table 14 summarizes the top 15 predictive COVID-related proteins based on the long and short COVID data analysis.
  • Table 14 Top 15 predictive proteins/peptides of COVID identified by long vs short COVID control data
  • Fibronectin was present at higher concentrations in COVID patients relative to the control samples as well as in long vs. short COVID patients.
  • Ficolin-2 and Hemoglobin subunit alpha 1 were identified as having a high average importance among the proteins and peptides tested. Ficolin-2 was present at lower concentrations in long COVID patients relative to the short COVID samples and Hemoglobin subunit alpha 1 was present at higher concentrations in both data sets (both Examples 4 and 5).
  • Lumican was also identified as having a high average importance among the proteins and peptides tested in both data sets (Examples 4 and 5).
  • the inventors have identified a surprising and highly predictive combination of metabolites and proteins/peptides for determining whether subjects have long COVID. Such results can be used to accurately predict long COVID in patients using a simple blood test.

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Abstract

L'invention propose une méthode de diagnostic et de traitement de l'affection post-COVID-19, comprenant : (a) la fourniture d'un échantillon biologique obtenu à partir du sujet ; (b) la mesure de niveaux de concentration à partir de l'échantillon obtenu d'un ou de plusieurs métabolites liés à la COVID-19 décrits ici et/ou d'une ou plusieurs protéines liées à l'affection post-COVID-19 décrites dans la description ; (c) la comparaison des niveaux de concentration des métabolites et/ou des protéines liées à l'affection post-COVID-19 de l'échantillon obtenu aux niveaux de concentration ou aux métabolites et/ou protéines liés à l'affection post-COVID-19 de référence correspondants à partir d'un échantillon de l'affection post-COVID-19 négatif ; (d) l'identification du sujet comme étant atteint d'une affection post-COVID-19 si les niveaux de concentration des métabolites et/ou des protéines liés à l'affection post-COVID-19 à partir de l'échantillon obtenu sont différents par rapport aux niveaux de concentration des métabolites et/ou des protéines liés à l'affection post-COVID-19 de référence à partir de l'échantillon de l'affection post-COVID-19 négatif ; et (e) la provocation du traitement du sujet.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021207858A1 (fr) * 2020-04-17 2021-10-21 London Health Sciences Centre Research Inc. Diagnostic et traitement de la covid-19
WO2021209575A2 (fr) * 2020-04-17 2021-10-21 Cbmed Gmbh Center For Biomarker Research In Medicine Biomarqueur pour la surveillance d'une maladie de coronavirus 2019
WO2022185295A1 (fr) * 2021-03-03 2022-09-09 Qatar University Biomarqueurs pour prédiction de la durée de séjour en unité de soins intensifs pour des patients atteints de covid-19 sous ventilation mécanique

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021207858A1 (fr) * 2020-04-17 2021-10-21 London Health Sciences Centre Research Inc. Diagnostic et traitement de la covid-19
WO2021209575A2 (fr) * 2020-04-17 2021-10-21 Cbmed Gmbh Center For Biomarker Research In Medicine Biomarqueur pour la surveillance d'une maladie de coronavirus 2019
WO2022185295A1 (fr) * 2021-03-03 2022-09-09 Qatar University Biomarqueurs pour prédiction de la durée de séjour en unité de soins intensifs pour des patients atteints de covid-19 sous ventilation mécanique

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
VALDÉS ALBERTO, MORENO LORENA ORTEGA, RELLO SILVIA ROJO, ORDUÑA ANTONIO, BERNARDO DAVID, CIFUENTES ALEJANDRO: "Metabolomics study of COVID-19 patients in four different clinical stages", SCIENTIFIC REPORTS, NATURE PUBLISHING GROUP, US, vol. 12, no. 1, US , XP093258505, ISSN: 2045-2322, DOI: 10.1038/s41598-022-05667-0 *

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