WO2022172039A1 - Procédé de détermination d'un risque d'infection virale - Google Patents

Procédé de détermination d'un risque d'infection virale Download PDF

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Publication number
WO2022172039A1
WO2022172039A1 PCT/GB2022/050405 GB2022050405W WO2022172039A1 WO 2022172039 A1 WO2022172039 A1 WO 2022172039A1 GB 2022050405 W GB2022050405 W GB 2022050405W WO 2022172039 A1 WO2022172039 A1 WO 2022172039A1
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WO
WIPO (PCT)
Prior art keywords
glycine
subject
viral infection
determining
risk
Prior art date
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PCT/GB2022/050405
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English (en)
Inventor
Deborah O'neil
Douglas FRASER-PITT
Original Assignee
Novabiotics Limited
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by Novabiotics Limited filed Critical Novabiotics Limited
Publication of WO2022172039A1 publication Critical patent/WO2022172039A1/fr

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Classifications

    • 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
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6803—General methods of protein analysis not limited to specific proteins or families of proteins
    • G01N33/6806—Determination of free amino acids
    • G01N33/6812—Assays for specific amino acids
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/26—Infectious diseases, e.g. generalised sepsis
    • 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 invention relates to prognostic methods for determining the risk of mortality of a subject with a viral infection, and a kit for performing the methods.
  • the prognostic biomarker is glycine. Therefore, the invention also relates to the use of glycine as a prognostic marker.
  • the invention also relates to a method of determining the susceptibility of a subject to a viral infection and a kit for performing the method.
  • the susceptibility marker is glycine.
  • the invention also relates to the use of glycine as a susceptibility marker.
  • Emerging viral infections such as COVID-19 targeted certain groups of people disproportionately causing respiratory failure and a high mortality rate. However, it also targeted healthy individuals with no underlying conditions.
  • glycine levels are correlated with severity of Covid-19 disease. Patients with dysregulated levels of glycine were found to be more likely to have severe symptoms.
  • a prognostic method for determining the risk of mortality of a subject with a viral infection comprising: a) determining the level of glycine in a sample obtained from a subject, and b) comparing the level of glycine to a control range or control mean, wherein dysregulation of the glycine level compared to the control indicates a higher risk of mortality.
  • a prognostic method for determining the risk of mortality of a subject with a viral infection comprising: a) determining the level of glycine in a sample obtained from the subject at a first time point; b) determining the level of glycine in a sample obtained from the same subject at a second later time point, wherein a higher risk of mortality is indicated by a decrease in glycine from the first time point to the second time point.
  • glycine for use as a prognostic marker for the risk of mortality in a subject with a viral infection.
  • kits for determining the risk of mortality of a subject with a viral infection comprising reagents for determining the presence of glycine in a sample, and instructions for use in the methods above.
  • a method for determining the susceptibility of a subject to a viral infection comprising: a) determining the level of glycine in a sample obtained from a subject, and b) comparing the level of glycine to a control range or control mean, wherein dysregulation of the glycine level compared to the control indicates higher susceptibility to a viral infection.
  • glycine for use as a marker for the susceptibility of a subject to a viral infection.
  • kits for determining the susceptibility of a subject to a viral infection comprising reagents for determining the presence of glycine in a sample, and instructions for use in the method above.
  • Glycine is an amino acid with the following structure:
  • the lUPAC name is 2-aminoacetic acid.
  • prognostic means providing a forecast or prediction of the probable course or outcome of the viral infection.
  • the sample may be a blood sample.
  • the blood sample may be fractionated to obtain the plasma.
  • the sample may also be a urine sample.
  • the urine may be collected over the course of 24 hours to ascertain the total glycine in urine over this period, i.e. a 24 hour urine collection.
  • the sample may also be a saliva sample.
  • the method may additionally involve obtaining the sample from the subject.
  • the level of glycine can be determined by any means available to those of ordinary skill in the art.
  • the probe then providing a signal.
  • the intensity of the signal is proportional to the amount of glycine in the sample.
  • the probe may be a fluorescent probe and the signal is therefore a fluorescent signal.
  • AbeamTM provides a glycine fluorometric test. Glycine levels may also be measured by mass spectrometry for example.
  • the level can be normalised to a control.
  • Reagents for use in testing glycine may be provided in the form of a kit, with instructions for use with the methods of the claims.
  • Control concentrations vary for glycine by weight and other factors. Normal physiological plasma concentrations of glycine vary between 200-300 pmol/L. Control range or mean may be more generally referred to as a control and include any other average to which glycine levels may be compared to assess dysregulation, i.e. levels out with the norm.
  • Example ranges for different groups and in different samples are provided below.
  • Plasma levels are consistently at the lower end of this range in obese and diabetic subjects. For example, obesity reduces the mean glycine level by around 10%.
  • Dysregulation of glycine is a glycine level at the extremes of the control range, or outside the control range.
  • glycine is below or above the specified control range.
  • the glycine may be in the upper or lower 10% of the control range.
  • the glycine may be in the upper or lower 15% of the control range.
  • the glycine may be in the upper or lower 20% of the control range.
  • the glycine may be in the upper or lower 25% of the control range.
  • the glycine may be in the upper or lower 30% of the control range.
  • the glycine may be in the upper or lower 35% of the control range.
  • the glycine may be in the upper or lower 40% of the control range.
  • the glycine may be in the upper or lower 45% of the control range.
  • the glycine may be in the upper or lower 50% of the control range.
  • the glycine may be below the range or in the lower 10% of the range.
  • the glycine may be below the range or in the lower 20% of the range.
  • the glycine may be below the range or in the lower 30% of the range.
  • the glycine may be below the range or in the lower 40% of the range.
  • the level may be in the upper or fourth quartile.
  • control range for a subject dependent on their age, weight and health condition can be calculated by the skilled person in the art, for example a physician.
  • control range will vary for subjects with Type 2 diabetes and obesity.
  • the control range in plasma for healthy adults is 120-554 with average levels of between 200-300 pmol/L. Therefore, the glycine may be below 120 or from 120-200 pmol/L; or 300- 554 or above 554 pmol/L.
  • the glycine may be below 120 or from 120-150 pmol/L; or 400-554 or above 554 pmol/L.
  • the glycine may be below 200-300 pmol/L; or above 200-300 pmol/L.
  • the glycine may be below 200-300 pmol/L; or above 200-300 pmol/L.
  • the glycine level may be above or below the mean glycine levels in the table above, For example, 10% above or below; 20% above or below; 30% above or below; 40% above or below; 50% above or below.
  • the glycine may be below 190, 180, 170, 160, 150, 140, 130 or 120 pmol/L.
  • the glycine may be above 190, 200, 210, 220, 230, 240, 250, 260, 270, 280, 290, 300, 310, 320, 330, 340, 350, 360, 370, 380, 390, 400, 410, 420, 430, 440, 450 pmol/L.
  • the glycine levels may be at the lower end of the control ranges, below the control range or below the mean value, i.e. below any control used.
  • the dysregulation may be that the glycine levels change over time.
  • the glycine levels may decrease from a first time point to a second later time point.
  • the decrease may be a 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25 or 30% decrease to the glycine level detected at the first time point (or any range from this list, for example 5-10% decrease, or 5-20% decrease).
  • This may be per 24 hour period or any of the further time points below.
  • the glycine may decrease from 450pM (first time point) to 405pM (second time point) representing a decrease in 45pM, i.e. 10% of the first time point.
  • the time points may be 24 hours, 36 hours, 48 hours or 72 hours apart. Further time points may be incorporated into the clinical test, at a third and fourth time point for example. This may be calculated by linear regression.
  • the infection may be caused by any virus.
  • influenza virus The viral infection can be a Ribovirus.
  • the viral infection can be any of ebola, coronavirus, hepatitis C, hepatitis E , West Nile Fever, Norovirus, Rotavirus, Polio, rabies, measles, rhinovurus.
  • the viral infection may be any RNA respiratory virus.
  • Respiratory viruses include rhinoviruses and enteroviruses (Picornaviridae), influenza viruses (Orthomyxoviridae), parainfluenza, metapneumoviruses and respiratory syncytial viruses (Paramyxoviridae), coronaviruses (Coronaviridae), and several adenoviruses.
  • the viral infection may be a Coronavirus infection.
  • a Coronavirus infection for example, any virus of the family Coronaviridae.
  • the virus can be SARS-CoV, MERS-CoV , SARS-CoV-2, HCoV-299E, HCoV-OC43, HCoV-NL63, C0V-HKUI , Human Coronavirus 229E (ATCC No. VR/740) or any combination thereof.
  • the virus is preferably SARS-CoV-2 (Covid-19).
  • risk of mortality is meant a relative degree of risk which allows the stratification of patients into high risk, medium risk and low risk groups. This in turn allows physicians to prioritise patients who are at higher risk of progressing to severe disease, and requiring for example rigorous intervention and/or intensive care.
  • the patient to be tested may have been designated as low-medium clinical risk by for example the NEWS scoring system.
  • This is a known scoring system applied by clinicians to assess the severity of the disease of the patient as they present.
  • Chart 2 NEWS thresholds and triggers
  • Chart 1 The NEWS scoring system
  • the patient may be alert and/or not require additional oxygen.
  • the patient may have a temperature of 35.1-36 or 38.1 -39.0°C; and/or SpC>2 Scale 1 of 92- 95%; and/or Sp0 2 Scale 2 of 84-87%; and/or systolic blood pressure (mmHg) of 91 -110; and/or pulse (per minute) of 91-130.
  • mmHg systolic blood pressure
  • the patient may have: Sp02 Scale 1 of 92-95%; and/or pulse (per minute) of 91-110 or 91-130; and/or temperature of 38.1-39.1 °C.
  • the patient tested may have high glycine levels. For example, above the mean glycine for the subject, or in the upper 50%, 40%, 30%, 20% or 10% of the control range. For example, in the fourth quartile.
  • the patient may have high glycine levels and any of the indicators above, for example, Sp02 Scale 1 of 92-95%; and/or pulse (per minute) of 91-110 or 91- 130; and/or temperature of 38.1 -39.1 °C.
  • the patients tested may have low glycine levels if in a susceptible group which decreases further. For example, lower than the mean glycine for the subject or in the lower 50%, 40%, 30%, 20% or 10% of the control range. For example in the first quartile.
  • risk of susceptibility is meant a relative degree of risk which allows the stratification of subjects or patients into high risk, medium risk and low risk groups. This in turn allows physicians to prioritise subjects or patients which may be, for example, at higher risk of contracting (being infected with) a viral infection or at higher risk of experiencing severe symptoms if infected by a virus. Risk is relative to a patient who has less dysregulation.
  • the glycine level detected in the subject without an infection may be at the lower end of the control ranges specified above. For example, the lower 50%, the lower 40%, the lower 30%, the lower 20% or the lower 10% of the ranges, or below the lower limit of the control range. Or the glycine may be below the mean or more generally below any other control used.
  • severe symptoms is meant pneumonia, severe hypoxemia (oximetry reading of ⁇ 92%), acute respiratory distress syndrome (ARDS) or death.
  • ARDS acute respiratory distress syndrome
  • subject this is a mammalian, particularly human.
  • the subject tested is a healthy, non-infected individual. That is, the patient may have been tested for viral infection and the test was negative for viral infection.
  • the subject tested In testing for the risk of mortality, the subject tested is infected with a virus.
  • the methods may also comprise a further step of administering anti-viral medication.
  • the methods may be computer-implemented methods. There may therefore be provided a computer program comprising instructions which when the program is executed by a computer, cause the computer to carry out the methods.
  • Also provided is a computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out any of the methods described herein.
  • circuitry may be general purpose processor circuitry configured by program code to perform specified processing functions.
  • the circuitry may also be configured by modification to the processing hardware. Configuration of the circuitry to perform a specified function may be entirely in hardware, entirely in software or using a combination of hardware modification and software execution.
  • Program instructions may be used to configure logic gates of general purpose or special-purpose processor circuitry to perform a processing function.
  • Circuitry may be implemented, for example, as a hardware circuit comprising custom Very Large Scale Integrated, VLSI, circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. Circuitry may also be implemented in programmable hardware devices such as field programmable gate arrays, FPGA, programmable array logic, programmable logic devices, A System on Chip, SoC, or the like.
  • Machine readable program instructions may be provided on a transitory medium such as a transmission medium or on a non-transitory medium such as a storage medium.
  • Such machine readable instructions (computer program code) may be implemented in a high level procedural or object oriented programming language. However, the program(s) may be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language, and combined with hardware implementations.
  • Program instructions may be executed on a single processor or on two or more processors in a distributed manner.
  • Figure 1 shows Plasma glycine distribution in one cohort of Covid-19 patients
  • Figure 2 shows glycine dysregulation in patients as they progress with disease. Patients with a higher risk of mortality have glycine which decreases over time.
  • Example 1 Glycine levels in the blood are dysregulated in patients in hospital with Covidin
  • Plasma samples were prepared from blood collected (in K2 EDTA tubes) from study participants who were all adult patients hospitalised with suspected COVID-19. Plasma glycine concentration was determined for each participant where COVID-19 infection had been confirmed by a positive PCR test for SARS CoV-2. 39 participants were included in the per protocol population.
  • Plasma glycine concentrations were determined by an LC-MS/MS analytical method qualified for determining concentrations along a linear range from 7.5-75.0 pg/ml. Plasma glycine concentrations were reported in pg/ml and converted to pM. Figure 1 shows that plasma glycine concentrations were not normally distributed. The distribution had a skewness of 1.4 and Kurtosis of 3.08. Summary of results
  • Example 2 Susceptibility is indicated by dysregulation with low levels of glycine
  • Example 1 Samples were taken as indicated in Example 1. The only difference with the samples for examples 2 and 3 was that glycine from serum was measured. Baseline measurements were mostly taken 1 day after admission with a maximum of 2 days after admission.
  • Table 1 shows when the cohort of COVID-19 patients is split into two halves based upon serum glycine levels at baseline, most of the type II diabetic patients cluster into the lower 50%.
  • the test for low glycine levels may be used to indicate subjects who are more likely to experience severe symptoms (yet are not infected presently). Additionally, this test may be useful to accompany lateral flow or other diagnostic tests, to indicate when first infected, that severe infection is likely in that subject.
  • Example 3 Increased risk of mortality is indicated by dysregulation with levels of decreasing glycine overtime
  • a decrease in glycine level in severe covid-19 indicates a higher risk of death / lower survival rate.
  • This decrease may be due to a faster turnover of glycine into nucleotides which in turn fuels further viral particle formation, reduces antiviral defences and increases inflammation.
  • This glycine turnover rate may be as a result of the activity of Glycine Decarboxylase.
  • This enzyme catalyses the conversion of glycine into the building blocks for nucleotides. Therefore, an overactive enzyme activity in some individuals would result in higher turnover of glycine, leading to lower levels relative to others.
  • the acute disease state, respiratory distress, prior to hospital interventions will raise glycine levels for all patients with severe COVID-19, but some individuals may still have higher GLDC activity, increased susceptibility and poorer prognosis.

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Abstract

La présente invention concerne un procédé de pronostic permettant de déterminer le risque de mortalité d'un sujet atteint d'une infection virale, ainsi qu'un kit destiné à mettre en œuvre le procédé. Le marqueur biologique pronostique est la glycine. Par conséquent, l'invention concerne également l'utilisation de glycine en tant que marqueur pronostique. L'invention concerne en outre un procédé de détermination de la susceptibilité d'un sujet à une infection virale et un kit destiné à mettre en œuvre le procédé. Le marqueur de susceptibilité est la glycine. Par conséquent, l'invention concerne en outre l'utilisation de glycine en tant que marqueur de susceptibilité.
PCT/GB2022/050405 2021-02-15 2022-02-15 Procédé de détermination d'un risque d'infection virale WO2022172039A1 (fr)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2010109192A1 (fr) * 2009-03-24 2010-09-30 Anamar Ab Profils métaboliques
WO2012104585A2 (fr) * 2011-01-31 2012-08-09 Imperial Innovations Ltd. Méthode de diagnostic
US20200386766A1 (en) * 2016-12-22 2020-12-10 Metabolomycs, Inc. Metabolic signatures associated with diagnosis, disease progression, and immunological response to treatment of patients with covid-19

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2010109192A1 (fr) * 2009-03-24 2010-09-30 Anamar Ab Profils métaboliques
WO2012104585A2 (fr) * 2011-01-31 2012-08-09 Imperial Innovations Ltd. Méthode de diagnostic
US20200386766A1 (en) * 2016-12-22 2020-12-10 Metabolomycs, Inc. Metabolic signatures associated with diagnosis, disease progression, and immunological response to treatment of patients with covid-19

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
ALPTUG A. ET AL.: "The serum amino acid profile in COVID-19", AMINO ACIDS, vol. 53, no. 10, 4 October 2021 (2021-10-04), pages 1569 - 1588, XP037590740 *
BARBERIS E. ET AL.: "Large-scale plasma analysis revealed new mechanisms and molecules associated with the host response to SARS-CoV-2", INT. J. MOL. SCI., vol. 21, no. 22, 8623, 16 November 2020 (2020-11-16), pages 1 - 25, XP055854390 *
FRASER D.D. ET AL.: "Metabolomics profiling of critically ill Coronavirus disease 2019 patients: Identification of diagnostic and prognostic biomarkers", CRIT. CARE EXPL., vol. 2, no. 10, E0272, January 2020 (2020-01-01), pages 1 - 9, XP055854676 *
YANG L. ET AL.: "Covariation analysis of serumal and urinary metabolites suggests aberrant glycine and fatty acid metabolism in chronic hepatitis B", PLOS ONE, vol. 11, no. 5, E0156166, 26 May 2016 (2016-05-26), pages 1 - 12, XP055854383 *

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