WO2021009260A1 - Méthode de pronostic et de diagnostic de la pré-éclampsie - Google Patents

Méthode de pronostic et de diagnostic de la pré-éclampsie Download PDF

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WO2021009260A1
WO2021009260A1 PCT/EP2020/070050 EP2020070050W WO2021009260A1 WO 2021009260 A1 WO2021009260 A1 WO 2021009260A1 EP 2020070050 W EP2020070050 W EP 2020070050W WO 2021009260 A1 WO2021009260 A1 WO 2021009260A1
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preeclampsia
subject
develop
biomarkers
pigf
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PCT/EP2020/070050
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Maris LAAN
Kaspar RATNIK
Kristiina RULL
Kalle KISAND
Ele HANSON
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University Of Tartu
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Priority to EP20737504.9A priority Critical patent/EP3999855A1/fr
Publication of WO2021009260A1 publication Critical patent/WO2021009260A1/fr

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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
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/689—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to pregnancy or the gonads
    • 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
    • G01N2333/475—Assays involving growth factors
    • 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
    • G01N2333/575—Hormones
    • 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
    • G01N2333/90—Enzymes; Proenzymes
    • G01N2333/91—Transferases (2.)
    • G01N2333/912—Transferases (2.) transferring phosphorus containing groups, e.g. kinases (2.7)
    • 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
    • G01N2333/90—Enzymes; Proenzymes
    • G01N2333/914—Hydrolases (3)
    • G01N2333/948—Hydrolases (3) acting on peptide bonds (3.4)
    • G01N2333/95—Proteinases, i.e. endopeptidases (3.4.21-3.4.99)
    • G01N2333/964—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue
    • G01N2333/96425—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue from mammals
    • G01N2333/96427—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue from mammals in general
    • G01N2333/9643—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue from mammals in general with EC number
    • G01N2333/96486—Metalloendopeptidases (3.4.24)
    • G01N2333/96491—Metalloendopeptidases (3.4.24) with definite EC number
    • G01N2333/96494—Matrix metalloproteases, e. g. 3.4.24.7
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/36—Gynecology or obstetrics
    • G01N2800/368—Pregnancy complicated by disease or abnormalities of pregnancy, e.g. preeclampsia, preterm labour
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/60—Complex ways of combining multiple protein biomarkers for diagnosis

Definitions

  • the present invention relates to a method of prognosing or diagnosing preeclampsia in a subject.
  • the method comprises the measuring of biomarker levels in a sample, e.g. blood sample, taken from the subject, optionally determining at least one clinical cofactor from the subject, and generating a prediction value which indicates whether the subject will develop or will not develop preeclampsia within a time period, or has preeclampsia.
  • PE Preeclampsia
  • PE farnesoid pulmonary hypertension
  • pulmonary oedema cerebral and visual impairment and uteroplacental dysfunction
  • the disease may progress to eclampsia characterized by severe epileptic seizures due to cerebral oedema and cause maternal and foetal death.
  • the challenge in the clinical management is to distinguish pregnancies with isolated gestational hypertension or increased protein levels in urine from the cases when these symptoms refer to the development of PE.
  • the only truly curative intervention for PE is delivery of the baby. However, in a large proportion of PE cases it brings along premature birth ( ⁇ 37 gestational weeks) with a broad palette of complications to the new born.
  • PE is considered a‘disease of placenta’, caused by defective placental formation and/or its impaired functional capacity.
  • Placental secreted molecules that are released into the maternal blood stream have been the most popular source to identify non-invasive biomarkers for PE.
  • sFItl soluble fms-like tyrosine kinase-1
  • PIGF placental growth factor
  • the test has an especially high fraction of inconclusive results in predicting PE development after 34 gestational weeks. This clinical group is critical as it represents >90% of all PE cases and typically the patients have no clearly identifiable placental developmental pathology. Thirdly, false-positive predictions based on solely sFlt1/PIGF ratio may arise due to placental malfunction for other reasons or fetal growth restriction, both reflected by low PIGF values. Lastly, the current offered tests are expensive for clinical routine and thus, cannot be developed further as a screening tool to be offered to a wide community of pregnant women.
  • the method of the present invention allows for a precise and usable prognosis or diagnosis of preeclampsia (PE), i.e. whether the subject will develop or will not develop PE or whether the subject has PE.
  • PE preeclampsia
  • precision and usability enables accurate early prediction or diagnosis of PE allowing the application of interventions to minimise the worst consequences of PE.
  • the exclusion or ruling out of the development of PE will minimise any further follow up and reduce maternal stress during pregnancy.
  • a method of prognosing or diagnosing preeclampsia in a subject comprising, measuring the level of at least four biomarkers in a blood sample from the subject; optionally determining at least one clinical cofactor from the subject; generating a prediction value, wherein the prediction value indicates whether the subject will develop or will not develop preeclampsia, or has preeclampsia; the prediction value being based on the levels of the at least four biomarkers in the sample, e.g.
  • the at least four biomarkers are sFItl , PIGF, ADAM 12, sENG and optionally leptin;
  • the at least one optional clinical cofactor is selected from gestational age and the weight of the subject, wherein a high sFItl , low PIGF, low ADAM12 and high sENG level as compared with control indicates an increased probability of the subject developing preeclampsia or increased probability that the subject has preeclampsia; and if included in the calculation of the prediction value, a high leptin level as compared with control indicates an increased probability of the subject developing preeclampsia or increased probability that the subject has preeclampsia; and if included in the calculation of prediction value, a low gestational age and high weight of the subject at blood sampling indicates an increased probability of the subject to developing preeclampsia or increased probability that the subject has preeclampsia.
  • the method may be used to prognose, i.e. whether the subject will develop PE or will not develop PE, or diagnose PE development in pregnant women on or after the 179 th gestational day.
  • the method comprises measuring the level of at least four biomarkers in a sample, e.g. blood sample, from the subject, preferably the at least four biomarkers are selected from sFItl , PIGF, ADAM 12 and sENG.
  • at least one clinical cofactor from the subject is also determined, preferably the at least one clinical cofactor is selected from gestational age at blood sampling.
  • the biomarkers are sFItl , PIGF, ADAM 12 and sENG or sFItl , PIGF, ADAM12, sENG and leptin and the clinical cofactors at blood sampling are gestational age and the weight of the subject.
  • the prediction value may, for example, be calculated using the following formulas:
  • a prediction value (p(i)) lower or less than a threshold value indicates that the subject will not develop preeclampsia within a two-month period from blood draw/blood sampling, i.e. excludes the risk of developing PE.
  • Figure 1 shows the study design, workflow and key stages in the Luminex® 6PLEX assay development.
  • the workflow included the following steps: selection of preeclampsia biomarkers (I); development and quality assessment of singleplex and multiplex immunoassays (II); experimental evaluation; the applicability and reliability of the developed Luminex® 6PLEX assay implemented on serum samples drawn from pregnant women (Table 5) (III); and development of preeclampsia prediction model based on Luminex® 6PLEX assay (IV).
  • Figure 2 shows the estimated analytical accuracy of the singleplex measurements of standard reference proteins in General Assay Diluent (GAD).
  • GAD General Assay Diluent
  • the solid line shows the actual measured median fluorescence (MFI) values of the serial dilutions of each biomarker (from Standard-8 to Standard-1).
  • MFI median fluorescence
  • the analytical accuracy shows the closeness of expected and calculated concentration values of standard proteins, reported in percentage (accuracy %; dashed line).
  • Standard-1 represents only GAD. Additional details are provided in Tables 1 ; 2; 3; 4.
  • Figure 3 shows the estimated analytical accuracy of the multiplex measurements of standard reference proteins in the General Assay Diluent (GAD). Biomarker measurements were determined with the developed Luminex® 6PLEX assay. The solid line shows the actual measured MFI values of the serial dilutions of each biomarker (from Standard-8 to Standard l The analytical accuracy expresses the closeness of expected and calculated
  • Standard-1 concentration values of standard proteins, reported in percentage (accuracy %; dashed line). Standard-1 represents only GAD. Additional details are provided in Tables 1 ; 2; 3; 4.
  • FIG. 4 shows the Singleplex vs 6PLEX Luminex® assay performance.
  • MFI median fluorescence intensity
  • the median fluorescence intensity (MFI) values of the reference proteins measured in singleplex and multiplex assay formats were highly correlated across the tested concentration ranges (Spearman correlation coefficient, r 1.00, P ⁇ 0.0005).
  • Figure 5 shows the comparison of the performance of the Luminex® 6PLEX assay developed in the current study and the B R A H M S assays for sFItl and PIGF (Thermo Fisher Scientific).
  • 61 serum samples were measured drawn from pregnant women during III trimester of gestation.
  • A, A’, A Correlation (Spearman R) between the two assays for the measured sFItl and PIGF and the estimated sFlt1/PIGF ratio.
  • the diamond symbol refers to sample III-9 with an outlier PIGF value.
  • Figure 6 shows the performance of the Luminex® 6PLEX assay measurements of serum sENG, ADAM12 and leptin among pregnant women. Highly correlated measurements of serum sENG and sFItl levels in pregnant women.
  • A R, Pearson correlation coefficient
  • B Distribution of the sENG
  • C ADAM12
  • D leptin. Circulating levels in clinical subgroups stratified by the symptoms and time to the onset of preeclampsia relative from the blood draw. Statistical significance for the distributions between subgroups was assessed using Mann-Whitney test.
  • FIG. 7 shows Receiver Operating Characteristic (ROC) curves for the preeclampsia (PE) prediction derived from the alternative modelling approaches of Luminex® 6PLEX assay data compared to the sFlt1/PIGF ratio based estimates using the B R A H M S
  • Model A combined additively the measurements of five biomarkers (ADAM12, sEng, sFIt, leptin, PIGF), whereas Model C excluded leptin in the PE prediction formula.
  • Model J was based on sFlt1/PIGF ratio estimated from either the Luminex® 6PLEX assay or the B R A H M S immunoassay measurements. All models were tested using three alternative analytical settings.
  • Setting 1 utilized solely biomarker data. In Setting 2, biomarker measurements were adjusted to gestational age and in addition, prior to modelling the leptin serum concentrations were corrected to maternal weight as
  • an and“the” include plural referents unless the content clearly dictates otherwise.
  • reference to“an inhibitor” includes two or more such inhibitors, or reference to “an oligonucleotide” includes two or more such oligonucleotide and the like.
  • biomarker is widespread in the art and may broadly denote a biological molecule and/or a detectable portion thereof whose qualitative and/or quantitative evaluation in a subject is, alone or combined with other data, predictive and/or informative (e.g., predictive, diagnostic and/or prognostic) with respect to one or more aspects of the subject's phenotype and/or genotype, such as, for example, with respect to the status of the subject as to a given disease or condition.
  • biomarkers may be metabolite-, RNA- (esp. mRNA-), peptide-, polypeptide- or protein-based, preferably peptide-, polypeptide- or protein-based.
  • gestational age may be defined as the age of the pregnancy from the last normal menstrual period.
  • Normal term pregnancy may be defined as a length of 259 gestational days and longer (up to 294 days), preferably 280 days.
  • a human pregnancy of normal gestation may alternatively be defined as between about 38 and 42 weeks, preferably about 40 weeks.
  • the method of the invention has utility in a number of applications including prognosing preeclampsia, predicting whether a subject, specifically a pregnant subject, will develop preeclampsia or whether preeclampsia risk can be excluded, and diagnosing preeclampsia.
  • the method of the invention prognoses preeclampsia.
  • the method of the invention may also have utility in choosing optimal management of preeclampsia in a subject and/or monitoring the effect of a possible treatment or treatments.
  • the method of the invention has utility in prognosing preeclampsia, predicting whether a subject, in particular a pregnant subject, will or will not develop preeclampsia and diagnosing preeclampsia at the beginning, start of, or during the third trimester of pregnancy or after the 179 th gestational day.
  • the method of the invention facilitates determining an appropriate treatment regimen for the subject.
  • preeclampsia or“ pre-eclampsia” (PE) means a multisystem complication of pregnancy comprising high blood pressure or hypertension and one or more additional symptoms selected from: swelling of the hands, feet and/or face (oedema), persisting headache, visual disturbances, liver, renal or hematologic dysfunction (including proteinuria, elevated liver enzymes, hemolysis, thrombocytopenia), epigastric pain and eclamptic seizures and uteroplacental dysfunction.
  • PE generally denotes a pregnancy-associated disease or condition that resolves by 12 weeks postpartum.
  • preeclampsia can be diagnosed when gestational hypertension is accompanied by 31 of the following new-onset conditions at or after 20 weeks’ gestation:
  • Proteinuria protein 1 + by dipstick on urine analysis, >300 mg of protein in a 24-hour urine collection, or a single random urine sample having a protein/creatinine ratio >0.3 mg/mg
  • Uteroplacental dysfunction such as fetal growth restriction, abnormal umbilical artery Doppler wave form analysis, or stillbirth
  • Gestational hypertension is defined as a systolic blood pressure (BP)>140 mmHg and/or a diastolic BP>90 mmHg after 20 weeks gestation (generally measured on two occasions over 4 hours apart, e.g. about 4 to about 100 hours apart).
  • BP systolic blood pressure
  • Preeclampsia typically occurs in the third trimester of pregnancy, i.e. on or after 28 th week of pregnancy. Preeclampsia may already occur on or after the 20 th week of pregnancy. If preeclampsia is not treated, it can lead to brain oedema that causes eclamptic seizures that are not related to a pre-existing neural condition, and even death of the mother and/or baby. In an embodiment of the present invention, prediction of development or diagnosis of the preeclampsia can be made on or after the 179 th gestational day. Preeclampsia may occur on or after 28 th week of pregnancy.
  • Prognosing preeclampsia or preeclampsia prognosis means providing a prediction of whether a subject will or is likely to develop preeclampsia.
  • Prognosing preeclampsia or preeclampsia prognosis is a preeclampsia prediction or prediction of preeclampsia onset.
  • Prognosing preeclampsia is a prediction of the subject’s susceptibility or risk of developing preeclampsia; a prediction of the course of disease progression and/or disease outcome, for example expected onset of the preeclampsia, expected severity and course of the preeclampsia, expectations as to whether the preeclampsia will develop into eclampsia; a prediction of the subject’s responsiveness to treatment for the preeclampsia, for example, a prediction of a subject’s responsiveness to treatment for the preeclampsia, for example positive response, a negative response, no response at all.
  • Prognosis includes predicting whether or not an individual will develop preeclampsia, whether or not they will need treatment and/or whether the progress of the disease will be fast or slow.
  • a prediction value is generated wherein the prediction value indicates whether the subject will develop or will not develop preeclampsia, or has preeclampsia.
  • Diagnosing preeclampsia or preeclampsia diagnosis means providing a determination of whether a subject has preeclampsia.
  • Diagnosing preeclampsia is a determination as to whether a subject, for example a subject that has some clinical symptoms of preeclampsia, a subject that is asymptomatic for preeclampsia but has risk factors associated with preeclampsia, a subject that is asymptomatic for preeclampsia and has no risk factors associated with preeclampsia, is presently affected by preeclampsia; a classification of the subject’s preeclampsia into a subtype of the disease or disorder; a determination of the severity of preeclampsia.
  • Monitoring preeclampsia means monitoring a subject’s condition, for example to inform a preeclampsia diagnosis, to inform a preeclampsia prognosis and/or to provide information as to the effect or efficacy of a preeclampsia treatment.
  • Treating preeclampsia means prescribing or providing treatment of preeclampsia in a woman and may include preventing the preeclampsia from occurring in a subject which may be predisposed to preeclampsia but has not yet been diagnosed as having preeclampsia; inhibiting preeclampsia, i.e.
  • preeclampsia is arrested; relieving, curing or regressing preeclampsia. If no preeclampsia is predicted in the subject, no special monitoring of the subject is required for at least two months. If preeclampsia is predicted, the subject has to be monitored regularly, for example appointments with the subject each week to measure blood pressure; to test urine protein level; documenting excessive weight gain; monitoring of fetal wellbeing; measuring blood liver enzymes; hemogram; coagulogram; headache frequency; visual disturbances;
  • the terms“individual,”“subject,”“host,” and“patient,” are used interchangeably herein and refer to any subject for whom diagnosis, treatment, monitoring or therapy is desired.
  • An individual, subject, host or patient may be a human.
  • the individual, subject, host or patient is preferably a human.
  • the subject may be asymptomatic for preeclampsia.
  • the subject may already have some preeclampsia symptom(s), preferably the subject has some preeclampsia symptoms but has not been diagnosed as having preeclampsia.
  • the subject may have one or more preeclampsia symptoms, preferably one preeclampsia symptom.
  • the subject may not have been diagnosed as having preeclampsia but presents with one or more
  • preeclampsia symptoms may be selected from the list consisting of increased blood pressure or hypertension, increased urine protein or proteinuria, water retention (oedema), elevated liver enzyme levels, headache, visual disturbances, reduced urine output or oliguria, epigastric pain, eclamptic seizures, reduced platelet count and uteroplacental dysfunction.
  • the subject may have an increased blood pressure or hypertension, and/or an increased urine protein or proteinuria.
  • biological sample encompasses a variety of sample types obtained from an organism and can be used in a diagnostic, prognostic or monitoring assay.
  • the biological sample may be any sample derived from the subject. Samples may include, without limitation, whole blood, plasma, serum, red blood cells, white blood cells (e.g., peripheral blood mononuclear cells), saliva, urine, stool (i.e.
  • the biological sample may be a blood sample or other liquid samples of biological origin.
  • Biological sample may refer to samples that have been manipulated in any way after their procurement, such as by treatment with reagents, solubilisation, or enrichment for certain components.
  • the term encompasses a clinical sample and also serum, plasma, biological fluids and tissue samples.
  • the sample is a blood sample, for example whole blood, serum or plasma.
  • the sample may be a blood serum sample.
  • the sample e.g. blood sample is typically obtained from the individual any time after confirmation of pregnancy, preferably during the first, second or third trimester of gestation.
  • the sample may be collected between the 11 th and 14 th gestational week during the first trimester.
  • the sample may be collected at the 180th gestational day i.e. 25 gestational weeks and 5 gestational days.
  • the sample, e.g. blood sample may be collected in the third trimester of pregnancy.
  • the sample for example the blood sample, may be collected after the 140 th , 150 th , 160 th , 170 th , 175 th , 176 th , 177 th or 178 th gestational day.
  • the sample e.g. blood sample is collected after the 179 th gestational day.
  • Gestation means the duration of pregnancy in a human, i.e. the time interval of development from fertilisation until birth, plus two weeks, i.e. to the first day of the last menstrual period.
  • gestational age is defined as the age of the pregnancy from the last menstrual period.
  • the second or third trimester means the second or third portions of gestation, each segment being three months long.
  • the first trimester means from the first day of the last menstrual period through the 13th week of gestation; the second trimester means from the 14th through to the 27th week of gestation; the third trimester means from the 28th week through to birth, i.e. 38-42 weeks of gestation.
  • a sample may be obtained at about weeks 11 through 42 of gestation, at about weeks 14 through 42 of gestation, at about weeks 18 through 42 of gestation, at about weeks 20 through 42 of gestation, at about weeks 22 through 42 of gestation, at about weeks 24 through 42 of gestation, at about 28 weeks through 42 of gestation, at about weeks 30 through 42 of gestation, at about weeks 34 through 42 of gestation, at about weeks 38 through 42 of gestation.
  • the subject sample may be obtained early in gestation, e.g. at week 11 or more of gestation, e.g.
  • the subject sample may be obtained late in gestation, for example, after 34 weeks of gestation, e.g. at week 35, 36, 37, 38, 39, 40, or week 41 of gestation.
  • the preeclampsia prognosis or diagnosis is made after the 179 th gestational day.
  • the sample for example the blood sample, is collected after the 179 th , 180 th , 181 st , 182 nd , 183 rd , 184 th , 185 th or 200 th gestational day.
  • the sample should be taken before the 259 th gestational day.
  • Samples may include samples derived from humans.
  • Biomarkers or preeclampsia biomarkers are molecular entities whose representation or determination in a sample, for example a blood sample, is associated with a preeclampsia phenotype. Biomarker concentrations follow tight gestational dynamics, i.e. the normal expected range of concentrations of a specific biomarker is dependent on the gestational age. For example, the concentration of a biomarker in a sample may be high in early pregnancy, but decrease or drop in the late pregnancy or vice versa, the concentration of biomarker in a sample may be low in early pregnancy, but increase in the late pregnancy.
  • Biomarkers may be differentially represented, i.e. represented at a different level, in a sample from an individual that will develop or has developed preeclampsia as compared to a healthy individual. In some instances, an elevated level of biomarker at the gestational age of sampling is associated with the preeclampsia phenotype.
  • the concentration of biomarker in a sample may be 1.5-fold, 2-fold, 2.5-fold, 3-fold, 4-fold, 5-fold, 7.5-fold, 10- fold, or greater more concentrated in a sample associated with the preeclampsia phenotype than in a sample not associated with the preeclampsia phenotype or the concentration of marker in a sample may be 10%, 20%, 30%, 40%, 50% or greater more concentrated in a sample associated with the preeclampsia phenotype than in a sample not associated with the preeclampsia phenotype.
  • a reduced level of the biomarker at the gestational age of sampling is associated with the preeclampsia phenotype.
  • the concentration of marker in a sample may be 1.5-fold, 2-fold, 2.5-fold, 3-fold, 4-fold, 5- fold, 7.5-fold, 10-fold, or greater less concentrated in a sample associated with the preeclampsia phenotype than in a sample not associated with the preeclampsia phenotype or the concentration of the biomarker in a sample may be 10%, 20%, 30%, 40%, 50% or more less concentrated in a sample associated with the preeclampsia phenotype than in a sample not associated with the preeclampsia phenotype.
  • Preeclampsia biomarkers used in the method of the present invention include sFItl , PIGF, ADAM 12, sENG and leptin.
  • the level of at least three, three, at least four, four, at least five or five biomarkers are measured in the sample, preferably a blood sample, from the patient.
  • the level of three or more, four or more, or five or more biomarkers are measured in the sample, preferably a blood sample, from the patient.
  • the levels of the biomarkers in the sample find use in providing a preeclampsia assessment, for example making a
  • the method comprises measuring the level of at least three, at least four biomarkers or at least five biomarkers.
  • the method may comprise measuring the level of at least three biomarkers, wherein the at least three biomarkers are selected from sFItl , PIGF and sENG and optionally one or more additional biomarkers selected from ADAM 12 and leptin.
  • the method may comprise measuring the level of at least four biomarkers, wherein the at least four biomarkers are selected from sFItl , PIGF,
  • the method comprises measuring the level of four biomarkers wherein the four biomarkers are sFItl , PIGF, ADAM 12 and sENG.
  • the method may comprise measuring the level of at least five biomarkers, wherein the at least five biomarkers are selected from sFItl , PIGF, ADAM12, sENG and leptin.
  • the method comprises measuring the level of five biomarkers wherein the five biomarkers are sFItl , PIGF, ADAM 12, sENG and leptin.
  • the level(s) of preeclampsia arker(s) in the biological sample from an individual are measured or evaluated.
  • the terms“evaluating”,“assaying”,“measuring”,“assessing,” and “determining” are used interchangeably to refer to any form of measurement, including determining if an element is present or not, and including both quantitative and qualitative determinations. Evaluating may be relative or absolute.
  • preeclampsia markers in the subject sample may be measured or evaluated by any convenient method.
  • methods may include biochemical assay methods, immunoassay methods, mass spectrometry analysis methods, or chromatography methods, or combinations thereof.
  • immunoassay generally refers to methods for detecting one or more molecules or analytes of interest in a sample, wherein specificity of an immunoassay for the molecule(s) or analyte(s) of interest is conferred by specific binding between a specific-binding agent, commonly an antibody, and the molecule(s) or analyte(s) of interest.
  • preeclampsia biomarker levels may be detected using any immunoassay-based technology, multiplex platform or other microsphere-based platform, ELISA, RIA, EIA, EMIT, FIA, FPFIA, TRFIA, CLIA, LIA or LIPs.
  • Preeclampsia biomarker levels may be detected using mass spectrometry, proteomic arrays, flow cytometry, western blotting or immunohistochemistry.
  • the immunoassay-based technology used in the present invention is a multiplex platform e.g. a microsphere-based platform. More preferably, the immunoassay-based technology used in the present invention is a multiplex platform that is a microsphere-based platform e.g. xMAP (sometimes referred to as xMAP technology e.g. as supplied by Luminex).
  • the present invention the present invention the immunoassay-based technology used in the present invention is a multiplex platform that is a microsphere-based platform e.g.
  • microsphere-based platform used in the present invention is xMAP technology.
  • the methods of preeclampsia assessment e.g., the methods of preeclampsia assessment, e.g.
  • diagnosing preeclampsia, prognosing preeclampsia, monitoring preeclampsia may comprise additional assessment(s) that are employed in conjunction with the biomarker measurement.
  • the subject methods may further comprise measuring one or more clinical cofactors associated with preeclampsia.
  • One such clinical cofactor is gestational age at blood sampling or blood draw. Another is the weight of the subject at blood sampling or blood draw.
  • the method comprises measuring at least one or two clinical cofactors.
  • the method comprises measuring at least one clinical cofactor that is gestational age.
  • the method comprises measuring at least one clinical cofactor selected from gestational age and optionally the weight of the subject.
  • the method comprises measuring two clinical cofactors selected from gestational age and weight of the subject.
  • a subject may be assessed for one or more clinical cofactors at about week 11 or more of gestation, e.g. week 12,13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, 35, 36, 37 or more of gestation, wherein the clinical cofactors are used in combination with the marker level representation to provide a preeclampsia diagnosis, a preeclampsia prognosis, to monitor the preeclampsia.
  • the clinical cofactors may be measured prior to obtaining the preeclampsia marker level representation.
  • the clinical cofactors may be measured after obtaining the preeclampsia marker level representation.
  • the clinical cofactors are measured at the same time as the sample draw from the subject. In some other embodiments of the invention, the clinical cofactors are measured +/- 1 , 2, 3 or 4 days from the sampling of the subject. In an embodiment of the invention, the method comprises measuring at least one clinical cofactor at the blood draw or blood sampling selected from gestational age and the weight of the subject.
  • the measurements of the preeclampsia biomarkers and optionally the clinical cofactors may be analysed collectively to arrive at a single preeclampsia prediction value.
  • Prediction value means a single metric value that represents the weighted levels of each of the preeclampsia biomarkers and optionally clinical cofactors measured.
  • the method comprises detecting the level of biomarkers in the sample and optionally determining at least one clinical cofactor and calculating a prediction value based on the levels of the preeclampsia biomarkers and optionally the at least one clinical cofactor.
  • the prediction value is compared to a cut off or threshold value and a prediction of whether the subject will develop or has preeclampsia will be made based on that comparison.
  • the prediction value represents a prediction as to whether the subject will develop or not preeclampsia within a given time period, e.g. 1 week, 2 weeks, 3 weeks, 4 weeks, 5 weeks, 6 weeks, 7 weeks, 8 weeks, 1 month, two months, three month, four months, five months or six months.
  • the prediction value represents a prediction as to whether the subject will develop or not develop preeclampsia within a two-month period.
  • the prediction value calculated at the 11 th , 12 th , 13 th or 14 th gestational week may predict whether the subject will develop or will not develop preeclampsia with an onset on or after 20 th , 21 st , 22 nd , 23 rd , 24 th , 25 th , 26 th , 27 th 28 th , 29 th , 30 th , 31 st , 32 nd , 33 rd , 34 th , 35 th or 36 th gestational week.
  • the method comprises generating a prediction value based on the levels of the at least four biomarkers in the blood sample from the subject and optionally based on the at least one clinical cofactor and generating a prediction value that is compared to a threshold value.
  • the prediction value calculated using the serum biomarker and clinical data of the patient at the time of blood sampling, is equal to, above or larger than the threshold value, for example, the prediction value is above the threshold value, the subject is predicted to have a risk of developing PE, i.e. PE is ruled-in.
  • the risk to PE can is predicted to be zero, i.e. ruled out.
  • the threshold value may be between 0.1 and 0.5. In some embodiments of the invention, the threshold value is 0.175 ⁇ 0.005. In other embodiments of the invention the threshold value is 0.204 ⁇ 0.005. In yet further
  • the threshold value is 0.443 ⁇ 0.005.
  • the method of the present invention predicts whether the subject has, will or will not develop preeclampsia within a two-month period.
  • a high sFItl , low PIGF, low ADAM12 and high sENG level as compared with control indicates an increased susceptibility of the subject developing preeclampsia or increased probability that the subject has preeclampsia and if included in the calculation of prediction value
  • a high leptin level as compared with control indicates an increased probability of the subject developing preeclampsia or increased probability that the subject has preeclampsia
  • a low gestational age and a high weight of the subject indicates an increased probability of the subject to develop preeclampsia or increased probability that the subject has preeclampsia.
  • the prediction value is based on gestational age and the weight of the
  • the prediction value is typically compared to a threshold value.
  • the prediction of whether the subject will develop PE is by reference to a threshold value.
  • the prediction value is compared to a threshold value, it indicates whether the subject will develop or not PE within a time period.
  • the indication that the subject will develop PE typically means that the subject will develop PE within 2, 4, 6 or 8 weeks, 1 , 2, 3, 4, 5, 6, 7 or 8 months.
  • the person will typically develop PE within 1 month e.g. within 1 , 2, 3 or 4 weeks, in 1 month, within 2 months or in 2 months or longer. If the comparison of the prediction value to the threshold indicates that the subject will not develop PE, this means that the subject will not develop PE within 2 months. This is informative to the patient management as no specific follow up needed within 2 months.
  • a prediction value ( (i )) for a patient sample may be calculated by an algorithm for using biomarker concentrations.
  • the algorithm may be according to the following formula:
  • coefficients a, b, c, d, e, f, g, h, and i are integers or numbers a is different from 0. At least 3 of the coefficients selected from b, c, d, e, f, and i may be different from 0 and optionally at least one coefficient selected from g, and h may be different from 0. Coefficient i may be 0 or different from 0.
  • the algorithm may be according to the following formula:
  • coefficients a, b, c, d, e, f, g, and h are integers or numbers a is different from 0. At least 3 of the coefficients selected from b, c, d, e, and f may be different from 0 and optionally at least one coefficient selected from g, and h may be different from 0.
  • the coefficient values may be as follows: a may be between -175 and -7; and/or b may be between -6 and -0.5; and/or c may be c between 2 and 36; and/or d may be between -20 and -0.5; and/or e may be between -12 and -0.3; and/or f may be between -3 and -0.1 ; and/or g may be between -0.3 and -0.05; and/or h may be between -0.2 and -0.01 ;
  • the threshold value may be between 0.1 and 0.5, and a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • the algorithm may be according to the following formula: wherein the coefficients a, b, d, e, f, g, h, and i are integers or number a is different from 0. At least 2 of the coefficients selected from b, d, e, f, and i are different from 0 and optionally at least one coefficient selected from g and h is different from 0.
  • the algorithm may be according to the following formula:
  • the coefficients a, b, c, d, e, f are integers or numbers a is different from 0. At least 3 of the coefficients selected from b, c, d, e, and f are different from 0.
  • the coefficients values are as following: a is comprised between -57 and -15; and/or b is comprised between -1 ,6 and -0.6; and/or c is comprised between 2 and 9.5; and/or d is comprised between -5 and -0,5; and/or e is comprised between -4.5 and -0.9; and/or f is comprised between -0.25 and -0.15;
  • the threshold value may be between 0.12 and 0.42, and a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • the algorithm may be according to the following formula:
  • coefficients a, b, d, e, and f are negative integers or numbers and c is a positive integer or number.
  • the threshold value may be 0.339 ⁇ 0.005, and a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • the algorithm may be according to the following formula:
  • coefficients a, b, d, e, and f are negative integers or number and c is a positive integer or number.
  • the threshold value may be 0.319 ⁇ 0.005, and a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • the algorithm may be according to the following formula:
  • coefficients a, b, d, e, and f are integers or numbers a is different from 0. At least 2 of the coefficients selected from b, d, e, and f may be different from 0.
  • the algorithm may be according to the following formula:
  • coefficients a, b, c, d, e, f, and g are integers or numbers a is different from 0, g may be different from 0. At least 3 of the coefficients selected from b, c, d, e, and f may be different from 0.
  • the coefficients values may be as follow: a is comprised between -125 and -17; and/or b is comprised between -3.9 and -0.8; and/or c is comprised between 3.2 and 22; and/or d is comprised between -11.4 and -2,2; and/or e is comprised between -5.5 and -0.3; and/or f is comprised between -2.8 and -2.2; and/or g is comprised between -0.8 and -0.06;
  • the threshold value may be comprised between 0.26 and 0.492, and a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • the algorithm may be according to the following formula:
  • coefficients a, b, d, e, f and g are negative numbers and c is a positive number.
  • the threshold value may be 0.443 ⁇ 0.005, and a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • the algorithm may be according to the following formula:
  • coefficients a, b, d and e are negative integers or numbers and c is a positive integer or number.
  • the threshold value may be 0.447 ⁇ 0.005, and a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • the algorithm may be according to the following formula:
  • coefficients a, b, d, e, f and g are integers or numbers a is different from 0, g may be different from 0. At least 2 of the coefficients selected from b, d, e, and f may be different from 0.
  • the algorithm may be according to the following formula:
  • coefficients a, b, c, d, e, f, g, and h are integers or numbers a is different from 0, g and h may be different from 0. At least 3 of the coefficients selected from b, c, d, e, and f may be different from 0.
  • the coefficients values may be as follows: a may be between -175 and -13.9; and/or b may be between -5.3 and -0.9; and/or c may be between 3.2 and 36; and/or d may be between -19.8 and -3.5; and/or e may be between -11.4 and -0.36; and/or f may be between -2.4 and -1.7; and/or g may be between -0.22 and -0.06; and/or h may be between -0.22 and -0.018;
  • the threshold value may be between 0.157 and 0.372, and a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • the algorithm may be according to the following formula:
  • coefficients a, b, d, e, f, g and h are negative integers or numbers and c is a positive integer or number.
  • the threshold value may be 0.175 ⁇ 0.005, and a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • the algorithm may be according to the following formula:
  • coefficients a, b, d, e, g and h are negative integers or numbers and c is a positive integer or number.
  • the threshold value may be 0.204 ⁇ 0.005, and a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • the algorithm may be according to the following formula:
  • coefficients a, b, d, g, and h are negative integers or numbers and c is a positive integer or number.
  • the threshold value may be 0.341 ⁇ 0.005, and a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • the algorithm may be according to the following formula:
  • coefficients a, b, d, e, f, g and h are integers or numbers a is different from 0, g and h may be different from 0. At least 2 of the coefficients selected from b, d, e, and f are different from 0.
  • the algorithm may be according to the following formula: wherein the coefficients a, b, c, d, e, f, g and h are numbers.
  • a, b, d, e, f, g and h are negative numbers and c is a positive number a is different from 0.
  • At least 4 of the coefficients selected from b, c, d and e are different from 0 and optionally at least one coefficient selected from f, g, and h is zero or different from 0.
  • the algorithm is according to formula (I):
  • a, b, d, e, f, g and h are negative numbers and c is a positive number; or one or more of f, g and h are 0.
  • the algorithm is according to formula (I), wherein the coefficients are as follows: a is -158.3 ⁇ 10%; b is -4.8 ⁇ 10%; c is 31.9 ⁇ 10%; d is -17.8 ⁇ 10%; e is -10.3 ⁇ 10%; f is -2.1 ⁇ 10%; g is -0.2 ⁇ 10%; and h is -0.1 ⁇ 10%.
  • the threshold value is 0.175 ⁇ 0.005
  • a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • the algorithm is according to formula (II):
  • a, b, d, e, g and h are negative numbers and c is a positive number; or one or more of g and h are 0.
  • the threshold value is 0.204 ⁇ 0.005
  • a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • the algorithm is according to formula (III):
  • coefficients a, b, c, d, e, f and g are numbers.
  • a, b, d, e, f and g are negative numbers and c is a positive number a is different from 0; or one or more of f and g are 0.
  • g may be different from 0.
  • At least 4 of the coefficients selected from b, c, d, e and f are different from 0.
  • the coefficients are as follows: a is -114 ⁇ 10%; b is -3.7 ⁇ 10%; c is 19.9 ⁇ 10%; d is 10.3 ⁇ 10%; e is -5 ⁇ 10%; f is -2.5 ⁇ 10%; and g is -0.2 ⁇ 10%.
  • the threshold value is 0.443 ⁇ 0.005
  • a p(i) value equal to or above the threshold value indicates the subject will develop preeclampsia or a p(i) value below the threshold value indicates the subject will not develop preeclampsia.
  • [PIGF] is the concentration of PIGF in the sample in [pg/mL]
  • [sFItl] is the concentration of sFItl in the sample in [pg/mL]
  • [sENG] is the concentration of sENG in the sample in [ng/mL]
  • ADAM12 is the concentration of ADAM12 in the sample in [ng/mL]
  • [leptin] is the concentration of leptin in the sample in [ng/mL]
  • gest age is the gestational age in days at sampling weight is the maternal weight at sampling in [kg]
  • [leptin]/weight is the concentration of leptin in the sample in [ng/mL] adjusted to maternal weight
  • the caret refers to the exponentiation operator.
  • Luminex xMAP® technology xMAP® suspension array technology is based on polystyrene beads with a diameter of 5.6 mm that are internally dyed with various ratios of two spectrally distinct fluorophores (Luminex® Corporation, Austin, TX, USA). As a result, an array of up to 500 different bead sets with specific absorption spectra is created. Various biological molecules, such as individual oligonucleotide probes, proteins or antibodies, can be coupled to alternative sets of beads. These sets are combined to a suspension array and due to their unique absorption spectra, it is possible to measure simultaneously up to 500 different probes in a single multiplex reaction.
  • the technology is capable of performing both protein- and nucleic acid-based analyses, enabling both quantitative protein assays and qualitative DNA-based detection assays.
  • Luminex® technology https://www.luminexcorp.com/research/our-technology/xmap- technology/ Reagents for the Luminex® sandwich immunoassays
  • Luminex® magnetic microspheres #MC100
  • Antibody Coupling Kit #40-50016
  • Capture and detection antibodies, and reference proteins were purchased from R&D Systems (Minneapolis, MN, USA) with the exception of STC1 reference protein (Abnova, Taipei City, Taiwan) (Table 1).
  • Antibodies were covalently linked to the surface of the fluorescently labeled Luminex® microspheres according to the manufacturer s protocol and kept in dark at +4 °C until use.
  • Stock solutions of each reference protein were prepared according to respective manufacturer s instruction. For each biomarker, expected concentration ranges to be measured in the sera of pregnant women were derived from the literature (Table 2).
  • Stock solutions were further diluted in 1 % BSA (#810685; Merck KGaA, Darmstadt, Germany) to prepare the 10X Standard-8 solutions of either individual or multiplexed reference proteins, corresponding to 10-fold higher concentration of the maximum expected value of each analyte (Table 3).
  • Standard-8 and its two-fold serial dilutions (Standard-7 and subsequent dilutions representing decreasing concentrations) were prepared in General Assay Diluent (GAD; #620; ImmunoChemistry Technologies LLC, Minnesota, USA).
  • GAD represents a mammalian protein-based immunoassay additive and it served as a blank measurement (Standard-1) for each analyzed biomarker in all experiments. All antibodies, stocks and 10X Standard-8 solutions of reference proteins were kept at -80 °C.
  • Luminex® singleplex and multiplex immunoassay development and quality assessment (Stage ll-lll, Figure 1) was performed using commercially available standardized pool of human serum samples, referred as Serum Matrix (S1-100ML, Human Serum; Merck KGaA, Darmstadt, Germany). Reference proteins were spiked into the Serum Matrix either in singleplex or multiplex format in three analyte concentrations. The High concentration of each biomarker corresponded to the respective Standard-8 (Table 3), whereas Medium and Low concentrations represented 1 :10 and 1 :100 dilutions of High values, respectively.
  • testing Serum Samples Eight individual human serum samples, available in the in-house ‘Happy Pregnancy’ biobank (see below) and referred throughout the text as the Testing Serum Samples, were included into the experiments of multiplex assay development and quality assessment.
  • the testing set of blood samples had been drawn from healthy pregnant women at 12, 16, 25, 26, 33, and 36 gestational weeks and from two non-pregnant reproductive age women. All blood samples were collected into Becton Dickinson Vacutainer® SSTTM Serum Separation Tubes containing spray-coated silica and a polymer gel (Becton Dickinson Company, Franklin Lake, NJ, USA).
  • Serum was separated in the service laboratory (United Laboratories, Tartu University Hospital) using routine procedures according to manufacturer’s instructions (centrifugation at 1 ,800 g for 10 min at room temperature, RT). Serum samples were kept at -80°C before further aliquoting and subsequent analysis.
  • the Serum Matrix, the Serum Matrix with the spiked proteins and the Testing Serum Samples were diluted in GAD.
  • 96-well round bottom microplates (#734-1642 Corning, NY, USA) were treated for 10 min with Blocking Buffer (BB; 100 mL per well; 1 % BSA, 0.02% Tween-20 in PBS at pH 7.4).
  • Blocking Buffer BB
  • capture antibody coupled microbead solution prepared in WB (50 mL per well containing 2,500 beads of each analyte) and tested samples ( Standards8- 1' or sera diluted in GAD; 50 mL/well) were pipetted to microplates. The mixture was incubated together for 2 h, followed by a washing step.
  • a biotinylated monoclonal or polyclonal detection antibody (or mixture of antibodies for multiplex assays; 100 mL/ well) diluted in WB was incubated for 1 h with a subsequent washing step.
  • a fluorescent reporter For the labeling of the immunoassay with a fluorescent reporter, incubation with streptavidin-phycoerythrin conjugate (100 mL of 1 mg/mL solution in WB; #PZPJ39S, Europa Bioproducts Ltd, Cambridge, UK) was applied for 30 min, followed by two rounds of washings.
  • microbeads were resuspended in 75 mI_ of WB, a minimum of 50 biomarker-specific beads were collected from each well and analysed on Luminex® MAGPIX analyzer (Luminex® Corporation, Austin TX, USA) using weighted 5-parameter logistic model implemented in Luminex® xPONENT 4.1 software (Luminex® Corporation, Austin TX, USA).
  • The‘Happy Pregnancy’ study (full name:‘Development of novel non-invasive biomarkers for fertility and healthy pregnancy’, 2013-2015) recruited 2,334 unselected pregnant women at their first antenatal visit at the Women Clinic of Tartu University Hospital, Estonia.
  • the study was approved by the Ethics Review Committee of Human Research of the University of Tartu, Estonia (permissions no 221/T-6, 17.12.2012; 286/M-18, 31.01.2018).
  • Informed consent was obtained from every subject at first antenatal visit.
  • longitudinal anthropometric, epidemiological (three questionnaires across gestation), clinical data and biological material throughout the pregnancy and at the delivery were collected.
  • All study participants had been monitored for their weight gain, arterial blood pressure dynamics, symptoms of proteinuria and signs of PE.
  • the data about the further course and pregnancy outcome including fetal parameters were obtained from medical documentation.
  • the women selected for the current study included 16 pregnancies with neither symptoms nor development PE, 15 cases with isolated symptoms alerting potentially to PE development but continuing until delivery without additional complications and 22 patients who eventually developed PE.
  • Clinical signs at routine antenatal visits alerting to PE were considered single measurements of increased blood pressure (systolic blood pressure, SBP 3140 mmHg, diastolic blood pressure, DBP 390 mmHg), signs of proteinuria (amount of protein in urine 30.3 g/l) or development of gestational hypertension after 20th week of pregnancy. Hypertension was confirmed when the abnormal measurements were obtained in sitting position in two occasions at least 4 hours apart while the patient has been resting for at least 15 minutes.
  • PE Diagnosis of PE was based on the criteria recommended by American College of Obstetricians and Gynecologists (ACOG, 2013). In the included cases, PE was assigned at the onset of both hypertension (SBP 3140 mmHg; DBP 390 mmHg) and proteinuria (2+ protein or greater on dipstick urinalysis, 3300 mg of protein per 24-h urine collection). Alternative to increased urinary protein, other relevant clinical symptoms were considered, such as headache resistant to analgesics or visual disturbances, epigastric pain, severe edema, and oliguria after 20 gestational weeks.
  • Luminex ® xMAP tests were developed for preeclampsia biomarkers reported in the literature.
  • the quality assessment included measurements of the reference proteins in a commercially available serum equivalent, as well as the biomarker levels in native human blood samples.
  • a multiplex Luminex ® immunoassay was developed for the analytes that passed all quality criteria in the singleplex test and showed highly correlated performance in the singleplex versus multiplex formats.
  • the established Luminex ® 6PLEX assay was further tested for the technical performance (e.g. inter- and intra-assay variability, the effect of freeze-thaw cycles) and subsequently utilized to measure biomarker levels in 61 serum samples drawn from pregnant women with variable gestational scenarios (Table 5). The data for the measured sFItl and PIGF levels were compared to the currently available commercial test
  • Luminex ® xMAP based multiplexed assay was targeted to nine previously established maternal serum biomarkers for preeclampsia ( Figure 1).
  • biomarkers the optimization series tested 20 alternative combinations of 0.24-30 mg capture antibody (bound to 1.25x10 6 magnetic beads) and 1-4 mg/mL monoclonal or polyclonal detection antibody. The range of titrated and tested concentrations followed the
  • Luminex ® singleplex and multiplex immunoassay development and quality assessment (Stage ll-lll, Figure 1) was performed using commercially available standardized pool of human serum samples, referred as the Serum Matrix throughout the paper (S1-100ML, Human Serum; Merck KGaA, Darmstadt, Germany). Additionally, eight native human serum samples, available in the in-house Happy Pregnancy study biobank (see below) and referred throughout the text the Testing Serum Samples, were included into the experiments of multiplex assay development and quality assessment. The testing set of blood samples had been drawn from healthy pregnant women at 12, 16, 25, 26, 33, and 36 gestational weeks and from two non-pregnant reproductive age women.
  • Analytical accuracy expresses the closeness of expected and calculated concentration values of standard proteins in GAD, reported in percentage (accuracy %). It was estimated for each analyzed biomarker in the developed singleplex and multiplex assays based on the recovery of expected concentrations of reference proteins implementing in the analysis of decreasing concentration gradient from the Standards-8 to Standards-1.
  • Serum Matrix Coefficient represents the ratio of MFI measurements of the analytes spiked into the sample matrix relative to respective proteins diluted in GAD.
  • SMCf was estimated using reference proteins spiked into the Serum Matrix ( High , Medium and Low concentrations relative to respective measured values in GAD (Table
  • LoD was calculated as mean + 2SD from four independent MFI measurements. In all subsequent experiments the measured concentration values below LoD were replaced with respective biomarker LoD.
  • the current study included 53 Happy Pregnancy study cases with a spontaneously conceived single pregnancy and representing alternative pregnancy curricula with the respect to the development of PE (Table 6).
  • the intra-assay variation was calculated for sFItl 5.28%, sENG 5.39%, leptin 5.83%, ADAM12 9.99% and PIGF 11.11 %. Due to the measurements of PTX3 at the bottom distribution of its detection range the respective estimated intra-assay variability (22.26%) was considered unreliable (Table 9). Inter-assay variation for each biomarker was calculated for the artificial control sample (biomarker reference proteins spiked into the Serum Matrix) analyzed in the same experiment on two parallel plates.
  • the current rule-out and the rule-in thresholds for the short-term (4 weeks) prediction of PE are considered ⁇ 38 and >85 for gestational age 20 weeks to 33 weeks and 6 days, or >110 (or gestational age 34 weeks to delivery, respectively (Verlohren et al 2014).
  • Luminex® immunoassay was developed using commercial standard proteins and respective antibodies for each biomarker (Table 1). For the standard proteins, the range of clinically relevant biomarker concentrations to be measurable with the assay was derived from the literature data (Table 2). A series of concentrations of the capture and detection antibodies were titrated according to Luminex® recommendations (Table 3) and the most optimal concentrations were selected (Table 4). Applying these selected conditions, satisfactory fluorescence signal response was detected for ADAM 12, adiponectin, sENG, leptin,
  • Pentraxin3, PIGF and sFItl values rising >1000 MFI; Figure 2.
  • STC1 and TRAIL measurements exhibited low MFI values ( ⁇ 200 MFI) across the entire range of biomarker concentrations and were excluded from the assay development.
  • the analytical accuracy in measuring the concentrations of the standard proteins was 90-100%.
  • ADAM12, adiponectin, sENG, leptin, PTX3, PIGF and sFItl were taken forward to test the performance of the standard proteins spiked into the commercial Serum Matrix (1 :10 dilution) using three alternative biomarker concentrations.
  • the estimated Serum Matrix Coefficient (SMCf) varied the least for the spiked ADAM 12 (78-92%), PIGF (76-98%), PTX3 (78-97%), sENG (80-131 %) and sFItl (128-184%) reference proteins (Table 7).
  • SMCf Serum Matrix Coefficient
  • adiponectin In case of adiponectin, a high variability in the confounding effect of the Serum Matrix on the measured MFI values was detected across alternative biomarker concentrations, ranging from 15% to 1611%. Thus, adiponectin was excluded from multiplex immunoassay development due to expected unreliable estimates of the biomarker concentrations.
  • ADAM 12 sENG, leptin, Pentraxin3, PIGF and sFItl were taken forward to the next step aiming to develop a multiplex assay.
  • the multiplex assay targeted simultaneously all the six retained biomarkers in a single well experiment (as detailed in the materials and methods). From here onward we refer to the developed multiplex testing protocol as a 6PLEX assay.
  • the estimated inter-assay variability was consistently low for all targeted biomarkers.
  • the coefficient of variation (CV%) of ADAM12, leptin, PTX3, PIGF, sENG and sFItl between independent experiments was estimated 5.29, 1.88, 2.0, 7.84, 5.60 and 4.18%, respectively (Table 9).
  • Luminex ® 6PLEX assay results were analyzed 61 serum samples drawn during the 3rd trimester of human pregnancy (180-275 g.d; Table 5, Table 6).
  • the measured sample set included 25 samples from the women with a later onset of PE (4-62 days after blood draw; median 21 d) and 32 serums representing controls without PE until delivery. Additionally, four samples drawn at the diagnosis of PE were utilized in the analysis as the reference levels of the biomarkers at the disease onset.
  • the sFlt1/PIGF ratio estimated from both assays was able to discriminate with high confidence the cases who developed PE within 27 days (Group I vs. Ill, Mann-Whitney test, P ⁇ 0.0005; Figure 5 B, C).
  • sFlt1/PIGF ratios of both tests also discriminated equally well patients with isolated clinical symptoms (gestational hypertension, proteinuria) that progressed to PE within 4-43 days (Groups IV vs. V, Mann-Whitney test, P ⁇ 0.0005).
  • Luminex ® 6PLEX assay was able to measure statistically significant increased sFItl levels already earlier than 28 days before the onset of PE (Groups I vs. II, Mann-Whitney test, P ⁇ 0.05). This might reflect increased sensitivity of the sFItl measurements using Luminex ® 6PLEX compared to B R A H M S assay due to a broader measurement range. Notably, neither of the assays showed discriminative values in the PIGF measurements between Group I vs. II.
  • Model 2A exhibited high sensitivity and specificity (91.7% and 96.9%, respectively) for PE prediction.
  • p(i) > 0.443 and p(i) £ 0.443 were estimated to represent the rule-in and rule-out threshold for the risk to develop PE within 2 months.
  • Model 3A also exhibited the best combination of sensitivity and specificity (100% and 96.9%, respectively) for PE prediction.
  • p(i) > 0.175 and p(i) £ 0.175 were estimated to represent the rule-in and rule-out threshold for the risk to develop PE within 2 months.
  • Models 3A compared to currently commercially applied B R A H M S sFlt1/PIGF (Model 1J) in predicting PE development in individual cases, the formula was retrospectively applied to the measured serum samples from either the women who eventually developed PE or respective controls.
  • the 6PLEX assay was able to predict or reject PE development for 53/57 serum samples (93.0%) using Model 2A and 55/57 (96.5%) for Model 3A (Table 15; Table 16).
  • Model 3A resulted in no false-negative predictions (sensitivity 100%).
  • the only false negative result with Model 2A was measured for a sample drawn 62 days before the onset of PE, at gestational day 216 (sample II-6). However, the follow-up serum sample drawn for the same women 48 days later (14 days before the PE confirmation) was already convincingly alerting to the PE risk (sample V-8).
  • the three false-positive cases predicted by the Model 2A represented other severe adverse pregnancy outcomes than PE, and none of these cases proceeded until normal vaginal delivery. Thus, the test cannot be reliably interpreted as the false-positive outcome, because the probability of eventually developing PE during these gestations cannot be ruled out.
  • One of these samples (I-5) was drawn from a pregnancy case complicated with gestational diabetes and intrahepatic cholestasis with extremely elevated liver enzymes. The patient also developed hypertension 16 days after the blood draw and eventually underwent labour induction and vacuum extraction due to fetal distress (sex: girl; gestational age at birth: 38 weeks and 5 days; birth weight: 3558 grams).
  • Sample I-2 also provided false-positive PE prediction, when using Model 3A. There was only one unclear PE prediction using Luminex ® 6PLEX assay data (Model 3A, sample 1-10) as no pregnancy complications were observed until delivery. Coincidentally combination of incorporated biomarkers may result in borderline estimates relative to the threshold value of the model. For 1-10, p(i) of the Model 3A was estimated to be 0.1754, very close to the threshold of the formula (0.1750).
  • Luminex ® 6PLEX Models 3A and 3C that incorporating also the presence/absence of PE symptoms at the blood draw provided the most accurate prediction, reaching the outcome of no false-positives and no-false negatives in our dataset. Clinically applicable formulae along with accurate coefficient and thresholds are under development.
  • the high quality performance of the method of the present invention allowed precise measurement of all six biomarkers. Both in singleplex and in multiplex the analytical accuracy was very high. In addition, the multiplexing did not interfere the signal intensities and no cross-disturbance was detected yielding high correlation against singleplex approach.
  • ADAM12 ADAM Metallopeptidase Domain 12
  • AUC area under the curve
  • Verlohren S Herraiz I, Lapaire O, Schlembach D, Zeisler H, Calda P, Sabria J,Markfeld-Erol F, Galindo A, Schoofs K, Denk B, Stepan H. New gestational phase-specific cut-off values for the use of soluble fms-like tyrosine kinase-1/placental growth factor ratio as diagnostic test for preeclampsia. Hypertension 2014; 63: 346-352.
  • Table 13 Formulas coefficients and thresholds for preeclampsia prediction.

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Abstract

La présente invention concerne une méthode de pronostic ou de diagnostic de la pré-éclampsie chez un sujet, la méthode comprenant la mesure du niveau d'au moins quatre biomarqueurs dans un échantillon de sang prélevé sur le sujet ; la détermination facultative d'au moins un cofacteur clinique provenant du sujet ; la génération d'une valeur de prédiction, la valeur de prédiction indiquant si le sujet développera ou non une pré-éclampsie ou si une pré-éclampsie est présente, la valeur de prédiction étant fondée sur les niveaux desdits biomarqueurs dans l'échantillon de sang prélevé sur le sujet et facultativement en fonction dudit cofacteur clinique.
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Publication number Priority date Publication date Assignee Title
CN114324856A (zh) * 2022-01-08 2022-04-12 北京华诺奥美基因医学检验实验室有限公司 妊娠中期预测子痫前期发病风险的检测试剂盒及其检测方法

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