WO2018076134A1

WO2018076134A1 - Methods and kits for providing a preeclampsia assessment and prognosing preterm birth

Info

Publication number: WO2018076134A1
Application number: PCT/CN2016/103060
Authority: WO
Inventors: Wenkai XIANG
Original assignee: Ldx Prognostics Limited Co.
Priority date: 2016-10-24
Filing date: 2016-10-24
Publication date: 2018-05-03
Also published as: CN109891239B; CN109891239A

Abstract

A method of providing a preeclampsia assessment and prognosing preterm birth for a subject, comprises: developing and training a random forest model to derive a scoring metric to differentiate among a normal subject, a preeclampsia subject and a preterm birth subject; evaluating a panel of markers from the subject to determine the level of each of the panel of markers; and feeding the level of each of the panel of markers into the random forest model to provide the preeclampsia assessment and prognose preterm birth. The panel of markers comprises inhibin beta A (Activin A) and at least one selected from a group consisting of ADAM metallopeptidase domain 12 (ADAM12), body mass index (BMI) and white blood cell count (WBC).

Description

METHODS AND KITS FOR PROVIDING A PREECLAMPSIA ASSESSMENT AND PROGNOSING PRETERM BIRTH

FIELD OF THE INVENTION

This disclosure pertains to methods and kits for providing a preeclampsia assessment and prognosing preterm birth.

BACKGROUND OF THE INVENTION

Preeclampsia is a serious multisystem complication of pregnancy with adverse effects for mothers and babies. The incidence of the disorder is around 5-8％of all pregnancies in the U.S. and worldwide, and the disorder is responsible for 18％of all maternal deaths in the U.S. The causes and pathogenesis of preeclampsia remain uncertain, and the diagnosis relies on nonspecific laboratory and clinical signs and symptoms that occur late in the disease process, sometimes making the diagnosis and clinical management decisions difficult. Earlier and more reliable disease diagnosing, prognosing and monitoring will lead to more timely and personalized preeclampsia treatments and significantly advance our understanding of preeclampsia pathogenesis.

Nearly 11％of all pregnancies in the US are result in preterm birth (<37 weeks gestation) , contributing greatly to perinatal morbidity and mortality (Goldenberg, R.L. and Rouse, D.J. (1998) . Prevention of premature birth. N Engl J Med 339, 313-20) . Etiologies of preterm birth are largely unknown, and predictive biomarkers have yet to be adequately developed.

SUMMARY OF THE INVENTION

Preeclampsia/preterm birth markers, preeclampsia/preterm birth marker panels, and methods for differentiating among a normal subject, a preeclampsia subject and a preterm birth subject are provided. These methods find use in a number of applications, including, for example, diagnosing preeclampsia, prognosing a preeclampsia or preterm birth, monitoring a subject with preeclampsia or with risk of preterm birth, and determining a treatment for preeclampsia or preterm birth. In addition, systems, devices and kits thereof that find use in practicing the subject methods are provided.

In some aspects of the invention, a method for providing a preeclampsia assessment and prognosing preterm birth for a specific subject is provided, which comprises (i) developing and training a random forest model using a plurality of clinical and laboratory test variables of randomly selected subjects, in order to derive a scoring metric to differentiate among a normal subject, a preeclampsia subject and a preterm birth subject； (ii) evaluating a panel of markers from the specific subject to determine the level of each of the panel of markers； and (iii) feeding the level of each of the panel of markers into the random forest model to provide the preeclampsia assessment and prognose preterm birth, wherein the panel of markers comprises inhibin beta A (Activin A) and at least one selected from a group consisting of ADAM metallopeptidase domain 12 (Adam12) , body mass index (BMI) and white blood cell count (WBC) .

In some embodiments of the invention, the plurality of clinical and laboratory test variables comprises at least two variables selected from a group consisting of systolic blood pressure, diastolic blood pressure, Activin A, gestational age, proteinuria, preeclampsia history, white blood cell count, preterm times, number of full-term pregnancy, dducation, ADAM12, multiple pregnancy, maternal height, maternal weight, BMI, abortion time, and age at blood collection. In some embodiments, the plurality of clinical and laboratory test variables comprises inhibin beta A (Activin A) and at least one selected from a group consisting of ADAM metallopeptidase domain 12 (Adam12) , body mass index (BMI) and white blood cell count (WBC) .

In some aspects of the invention, a panel of preeclampsia and preterm birth markers is provided, the panel comprising inhibin beta A (Activin A) and one or more markers selected from the group consisting of Adam12 (ADAM metallopeptidase domain 12) , body mass index (BMI) and white blood cell count (WBC) .

In one embodiment, the methods do not include measurement of expression levels of FSTL3, APLN, LEP, INHA, PIK3CB, SLC2A1, CRH, HSD17B1, SIGLEC6, PVRL4, HEXB, IL1 RAP, MFAP5, HTRA1, EBI3, HTRA4. In one embodiment, the methods do not include measurement of expression levels of FN1, PEG10, EPAS1, F5, FBN1, HGF, IGF2, AGO2, ATF2, KDM6A, KRAS, MECOM, PDPK1, S100A8, SPTBN1, TRA2B, VEGFA, WNK1, ACSS1, BMP7, CGB, CYP19A1, DLX4, ELOVL2, EZR, HBB, IL6ST, MFSD2A, PEG3, and/or SVEP1.

In one embodiment, the methods of the present disclosure do not include measurement of expression levels of PAPPA2.

In one embodiment, the methods do not include measurement of the expression level of FSTL3. In one embodiment, the methods do not include measurement of the expression level of APLN. In one embodiment, the methods do not include measurement of the expression level of LEP. In one embodiment, the methods do not include measurement of the expression level of INHA. In one embodiment, the methods do not include measurement of the expression level of PIK3CB. In one embodiment, the methods do not include measurement of the expression level of SLC2A1. In one embodiment, the methods do not include measurement of the expression level of CRH. In one embodiment, the methods do not include measurement of the expression level of HSD17B1. In one embodiment, the methods do not include measurement of the expression level of SIGLEC6. In one embodiment, the methods do not include measurement of the expression level of PVRL4. In one embodiment, the methods do not include measurement of the expression level of HEXB. In one embodiment, the methods do not include measurement of the expression level of IL1 RAP. In one embodiment, the methods do not include measurement of the expression level of MFAP5. In one embodiment, the methods do not include measurement of the expression level of HTRA1. In one embodiment, the methods do not include measurement of the expression level of EBI3. In one embodiment, the methods do not include measurement of the expression level of HTRA4. In one embodiment, the methods do not include measurement of the expression level of F5. In one embodiment, the methods do not include measurement of the expression level of FBN1. In one embodiment, the methods do not include measurement of the expression level of HGF. In one embodiment, the methods do not include measurement of the expression level of IGF2. In one embodiment, the methods do not include measurement of the expression level of AGO2. In one embodiment, the methods do not include measurement of the expression level of ATF2. In one embodiment, the methods do not include measurement of the expression level of KDM6A. In one embodiment, the methods do not include measurement of the expression level of KRAS. In one embodiment, the methods do not include measurement of the expression level of MECOM. In one embodiment, the methods do not include measurement of the expression level of PDPK1. In one embodiment, the methods do not include measurement of the expression level of S100A8. In one embodiment, the methods do not include measurement of the expression level of SPTBN1. In one embodiment, the methods do not include measurement of the expression level of TRA2B. In one embodiment, the methods do not include measurement of the expression level of VEGFA. In one embodiment, the methods do not include measurement of the expression level of WNK1. In one embodiment, the methods do not include measurement of the expression level of ACSS1. In one embodiment, the methods do not include measurement of the expression level of BMP7. In one embodiment, the methods do not include measurement of the expression level of CGB. In one embodiment, the methods do not include measurement of the expression level of CYP19A1. In one embodiment, the methods do not include measurement of the expression level of DLX4. In one embodiment, the methods do not include measurement of the expression level of ELOVL2. In one embodiment, the methods do not include measurement of the expression level of EZR. In one embodiment, the methods do not include measurement of the expression level of HBB. In one embodiment, the methods do not include measurement of the expression level of IL6ST. In one embodiment, the methods do not include measurement of the expression level of MFSD2A. In one embodiment, the methods do not include measurement of the expression level of PEG3. In one embodiment, the methods do not include measurement of the expression level of SVEP1.

The methods may be particularly suitable for certain pregnant women, such as those that have history of preeclampsia, have obesity, have babies less than two years or more than 10 years apart, are older than 40, have history of certain conditions including chronic high blood pressure, migraine headaches, type 1 or type 2 diabetes, kidney disease, a tendency to develop blood clots, or lupus.

The methods of the present disclosure are suitable for women at different stages of pregnancy, which is unexpected given typically such prognosis is only made for women that are pregnant for more than 32 weeks. In one embodiment, the woman is pregnant for 16-27 weeks. In one embodiment, the woman is pregnant for 28-31 weeks. In one embodiment, the woman is pregnant for 16-31 weeks. In one embodiment, the woman is pregnant for less than 32 weeks. In one embodiment, the woman is pregnant for 32-36 weeks.

The methods may be particularly suitable for certain pregnant women, such as those that smoke or consume alcohol, are younger than 17 or older than 35, have preterm birth history and/or are stressed or unhealthy.

Once the diagnosis of preeclampsia is determined, the woman can be subject to a procedure that helps ameliorate the preeclampsia. Examples of such procedures include, without limitation, medications to lower blood pressure, use of corticosteroids, anticonvulsant medication such as magnesium sulfate, bed rest, and consideration of delivery if the diagnosis was made at or after 37 gestational weeks.

Once the preterm risk is determined, the woman can be subject to a procedure that helps ameliorate the preterm birth risk. Examples of such procedures include, without limitation, administration of corticosteroid, magnesium sulfate, an antibiotic, or progestin, and cervical cerclage and combinations thereof.

In some aspects of the invention, a kit is provided for making a preeclampsia and preterm birth assessment for a sample. In some embodiments, the preeclampsia assessment is a preeclampsia diagnosis. In some embodiments, the preterm birth assessment is a preterm birth prognosis. In some embodiments, the kit comprises one or more detection elements for measuring the amount of marker in a sample for a panel of preeclampsia and preterm birth markers comprising inhibin beta A (Activin A) . In some embodiments, the kit comprises one or more detection elements for measuring the amount of marker in a sample for a panel of preeclampsia and preterm birth markers comprising inhibin beta A (Activin A) and Adam12 (ADAM metallopeptidase domain 12) . In some embodiments, the kit comprises one or more detection elements for measuring the amount of marker in a sample for a panel of preeclampsia and preterm birth markers comprising inhibin beta A (Activin A) and body mass index (BMI) . In some embodiments, the kit comprises one or more detection elements for measuring the amount of marker in a sample for a panel of preeclampsia and preterm birth markers comprising inhibin beta A (Activin A) and white blood cell count (WBC) . In some embodiments, the kit further comprises a preeclampsia phenotype determination element. In some embodiments, the kit comprises one or more detection elements for measuring the amount of marker in a sample for a panel of preeclampsia and preterm birth markers comprising one or more markers selected from the group consisting of inhibin beta A (Activin A) and Adam12 (ADAM metallopeptidase domain 12) ； and a preeclampsia and preterm birth phenotype determination element. In some embodiments, the one or more detection elements detect the level of marker polypeptides in the sample.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention is best understood from the following detailed description when read in conjunction with the accompanying drawings. The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing (s) will be provided by the Office upon request and payment of the necessary fee. It is emphasized that, according to common practice, the various features of the drawings are not to-scale. On the contrary, the dimensions of the various features are arbitrarily expanded or reduced for clarity. Included in the drawings are the following figures.

Figure 1. Study outline of the multi- ‘omics’ , based discovery and validation of PE biomarkers.

Figure 2. Study outline of the multi- ‘omics’ , based discovery and validation of PTB biomarkers.

Figure 3. Identification of PE biomarkers using a combination of meta-analysis, protein atlas analysis, and human orthologues analysis.

Figure 4. Identification of PTB biomarkers using a combination of meta-analysis, protein atlas analysis, and human orthologues analysis.

Figure 5. Expression comparative analysis of PE biomarkers (PE versus controls) . Forest plot summarizes the results of placenta mRNA expression meta analysis, and maternal serum analyte abundance quantification at different early and late gestational age weeks. Line plot represents 95％confidence interval.

Figure 6. Transcription analysis of the candidate genes for preterm birth. Left panel: Placenta gene expression (unit: FPKM) ； middle panel: gene expression ratio between placenta and other organ tissues； right panel: gene expression ratio of the placenta tissue between preterm birth and normal controls.

Figure 7. A: Boxplot display and scatter plot of biomarker distribution for Activin A at different gestational age weeks at blood sample collection in PE, PTB, and control groups. Horizontal box boundaries and midline denote sample quartiles. B: Scatter plots of biomarker distribution for Activin A as a function of gestational age weeks at blood sample collection (Top) , delivery (Bottom) , and the gap in between (Middle) .

Figure 8. A: Boxplot display and scatter plot of biomarker distribution for Adam12 at different gestational age weeks at blood sample collection in PE, PTB, and control groups. Horizontal box boundaries and midline denote sample quartiles. B: Scatter plots of biomarker distribution for Adam12 as a function of gestational age weeks at blood sample collection (Top) , delivery (Bottom) , and the gap in between (Middle) .

Figure 9. A: Score distribution for each sample. B: Importance of each feature in the algorithm. The scores and feature importance were produced by a random forest algorithm developed with a panel of Activin A and Adam12.

Figure 10. A: Score distribution for each sample. B: Importance of each feature in the algorithm. The scores and feature importance were produced by a random forest algorithm developed with a panel of Activin A and BMI.

Figure 11. A: Score distribution for each sample. B: Importance of each feature in the algorithm. The scores and feature importance were produced by a random forest algorithm developed with a panel of Activin A and white blood counts.

DETAILED DESCRIPTION OF THE INVENTION

Preeclampsia and preterm birth markers, preeclampsia and preterm birth marker panels, and methods for obtaining a preeclampsia and preterm birth marker level representation for a sample are provided. These compositions and methods find use in a number of applications, including, for example, diagnosing preeclampsia, prognosing a preeclampsia or preterm birth, monitoring a subject with preeclampsia or risks of preterm birth, and determining a treatment for preeclampsia and preterm birth. In addition, systems, devices and kits thereof that find use in practicing the subject methods are provided. These and other objects, advantages, and features of the invention will become apparent to those persons skilled in the art upon reading the details of the compositions and methods as more fully described below.

Before the present methods and compositions are described, it is to be understood that this invention is not limited to particular method or composition described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only by the appended claims.

Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limits of that range is also specifically disclosed. Each smaller range between any stated value or intervening value in a stated range and any other stated or intervening value in that stated range is encompassed within the invention. The upper and lower limits of these smaller ranges may independently be included or excluded in the range, and each range where either, neither or both limits are included in the smaller ranges is also encompassed within the invention, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the invention.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, some potential and preferred methods and materials are now described. All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and/or materials in connection with which the publications are cited. It is understood that the present disclosure supersedes any disclosure of an incorporated publication to the extent there is a contradiction.

As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present invention. Any recited method can be carried out in the order of events recited or in any other order which is logically possible.

It must be noted that as used herein and in the appended claims, the singular forms "a" , "an" , and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a cell" includes a plurality of such cells and reference to "the peptide" includes reference to one or more peptides and equivalents thereof, e.g. polypeptides, known to those skilled in the art, and so forth.

The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention. Further, the dates of publication provided may be different from the actual publication dates which may need to be independently confirmed.

As summarized above, aspects of the subject invention include methods, compositions, systems and kits that find use in providing a preeclampsia and preterm birth assessment, e.g. diagnosing, prognosing, monitoring, and/or treating preeclampsia and/or preterm birth in a subject.

By "preeclampsia" or "pre-eclampsia" it is meant a multisystem complication of pregnancy that may be accompanied by one or more of high blood pressure, proteinuria, swelling of the hands and face/eyes (edema) , sudden weight gain, higher-than-normal liver enzymes, and thrombocytopenia. Preeclampsia typically occurs in the third trimester of pregnancy, but in severe cases, the disorder occur in the second trimester, e.g., after about the 22^nd week of pregnancy. If unaddressed, preeclampsia can lead to eclampsia, i.e. seizures that are not related to a preexisting brain condition. “Preterm birth” or “spontaneous preterm birth” refers to preterm birth, also known as premature birth, which is the birth of a baby at less than 37 weeks gestational age. These babies are known as preemies or premmies. Symptoms of preterm labor include uterine contractions which occur more often than every ten minutes or the leaking of fluid from the vagina. Premature infants are at greater risk for cerebral palsy, delays in development, hearing problems, and problems seeing. These risks are greater the earlier a baby is born. By "diagnosing" a preeclampsia/preterm birth or "providing a preeclampsia/preterm birth diagnosis, "it is generally meant providing a preeclampsia/preterm birth determination, e.g. a determination as to whether a subject (e.g. a subject that has clinical symptoms of preeclampsia/preterm birth, a subject that is asymptomatic for preeclampsia/preterm birth but has risk factors associated with preeclampsia, a subject that is asymptomatic for preeclampsia and has no risk factors associated with preeclampsia/preterm birth) is presently affected by preeclampsia； a classification of the subject's preeclampsia/preterm birth into a subtype of the disease or disorder； a determination of the severity of preeclampsia/preterm birth； and the like. By “prognosing” a preeclampsia/preterm birth, or "providing a preeclampsia/preterm birth prognosis, "it is generally meant providing a preeclampsia/preterm birth prediction, e.g. a prediction of a subject's susceptibility, or risk, of developing preeclampsia/preterm birth； a prediction of the course of disease progression and/or disease outcome, e.g. expected onset of the preeclampsia/preterm birth, expected duration of the preeclampsia, expectations as to whether the preeclampsia will develop into eclampsia, etc. ； a prediction of a subject's responsiveness to treatment for the preeclampsia/preterm birth, e.g., positive response, a negative response, no response at all； and the like. By "monitoring"a preeclampsia/preterm birth, it is generally meant monitoring a subject's condition, e.g. to inform a preeclampsia/preterm birth diagnosis, to inform a preeclampsia/preterm birth prognosis, to provide information as to the effect or efficacy of a preeclampsia/preterm birth treatment, and the like. By "treating" a preeclampsia/preterm birth it is meant prescribing or providing any treatment of a preeclampsia/preterm birth in a mammal, and includes: (a) preventing the preeclampsia/preterm birth from occurring in a subject which may be predisposed to preeclampsia/preterm birth but has not yet been diagnosed as having it； (b) inhibiting the preeclampsia/preterm birth, i.e., arresting its development； or (c) relieving the preeclampsia/preterm birth, i.e., causing regression of the preeclampsia/preterm birth.

In aspects of the disclosure, methods, kits and reagents are provided for prognosing a preterm birth condition. “Prognosis” as used herein generally includes a prediction of a subject’s susceptibility to a disease or disorder, i.e. preterm birth； a determination, or diagnosis, as to whether a subject is presently affected by a disease or disorder, i.e. preterm birth； a prediction for a subject affected by a disease or disorder (e.g., determination of the severity of preterm birth, likelihood that a preterm birth condition will develop into early delivery) ； a prediction of a subject’s responsiveness to treatment for the disease or disorder； and the monitoring a subject’s condition to provide information as to the effect or efficacy of therapy. The terms “treatment” , “treating” and the like are used herein to generally mean obtaining a desired pharmacologic and/or physiologic effect. The effect may be prophylactic in terms of completely or partially preventing a disease or symptom thereof and/or may be therapeutic in terms of a partial or complete cure for a disease and/or adverse effect attributable to the disease. “Treatment” as used herein covers any treatment of a disease in a mammal, and includes: (a) preventing the disease from occurring in a subject which may be predisposed to the disease but has not yet been diagnosed as having it； (b) inhibiting the disease, i.e., arresting its development； or (c) relieving the disease, i.e., causing regression of the disease. The therapeutic agent may be administered before, during or after the onset of disease or injury. The treatment of ongoing disease, where the treatment stabilizes or reduces the undesirable clinical symptoms of the patient, is of particular interest. Such treatment is desirably performed prior to complete loss of function in the affected tissues. The subject therapy will desirably be administered during the symptomatic stage of the disease, and in some cases after the symptomatic stage of the disease. The terms “individual, ” “subject, ” “host, ” and “patient, ” are used interchangeably herein and refer to any mammalian subject for whom diagnosis, treatment, or therapy is desired, particularly humans.

The body mass index (BMI) , also known as Quetelet index, is a value derived from the mass (weight) and height of an individual. The BMI is defined as the body mass divided by the square of the body height, and is universally expressed in units of kg/m², resulting from mass in kilograms and height in metres. The BMI is an attempt to quantify the amount of tissue mass (muscle, fat, and bone) in an individual, and then categorize that person as underweight, normal weight, overweight, or obese based on that value. Commonly accepted BMI ranges are underweight: under 18.5 kg/m², normal weight: 18.5 to 25, overweight: 25 to 30, obese: over 30.

White blood cells (WBCs) , also called leukocytes, are an important part of the immune system. These cells help fight infections by attacking bacteria, viruses, and germs that invade the body. White blood cells originate in the bone marrow, but circulate throughout the bloodstream. There are five major types of white blood cells: neutrophils, lymphocytes, eosinophils, monocytes, and basophils. A WBC count is a test that measures the number of white blood cells in your body. This test is often included with a complete blood count (CBC) . Blood contains a percentage of each type of white blood cell. Sometimes, however, white blood cell count can fall or rise out of the healthy range due to medical conditions, such as fever, chills, infections and so on.

In describing the subject invention, compositions useful for providing a preeclampsia assessment will be described first, followed by methods, systems and kits for their use.

PREECLAMPSIA AND PRETERM BIRTH MARKERS AND PANELS

In some aspects of the invention, preeclampsia and preterm birth markers and panels of preeclampsia and preterm birth markers are provided. By a "preeclampsia and preterm birth marker"it is meant a molecular entity whose representation in a sample is associated with a preeclampsia phenotype or preterm birth phenotype. For example, a preeclampsia and preterm birth marker may be differentially represented, i.e. represented at a different level, in a sample from an individual that will develop or has developed preeclampsia or will have preterm birth as compared to a healthy individual； and in a sample from an individual that will develop or has developed preeclampsia as compared to a healthy individual who will have preterm birth. In some instances, an elevated level of marker is associated with the preeclampsia phenotype and/or preterm birth phenotype. For example, 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 in a sample associated with the preeclampsia phenotype or preterm birth phenotype than in a sample not associated with the preeclampsia phenotype or preterm phenotype； or 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 in a sample associated with the preeclampsia phenotype than in a sample associated with preterm phenotype. In other instances, a reduced level of marker is associated with the preeclampsia phenotype or preterm birth phenotype. For example, the concentration of marker in a sample may be 10％less, 20％less, 30％less, 40％less, 50％less or more in a sample associated with the preeclampsia or preterm birth phenotype than in a sample not associated with the preeclampsia or preterm birth phenotype； or the concentration of marker in a sample may be 10％less, 20％less, 30％less, 40％less, 50％less or more in a sample associated with the preeclampsia phenotype than in a sample associated with the preterm birth phenotype.

Preeclampsia and preterm birth markers may include proteins associated with preeclampsia, preterm birth, and their corresponding genetic sequences, i.e. mRNA, DNA, etc. By a "gene" or "recombinant gene" it is meant a nucleic acid comprising an open reading frame that encodes for the protein.

The boundaries of a coding sequence are determined by a start codon at the 5'(amino) terminus and a translation stop codon at the 3' (carboxy) terminus. A transcription termination sequence may be located 3'to the coding sequence. In addition, a gene may optionally include its natural promoter (i.e., the promoter with which the exons and introns of the gene are operably linked in a non-recombinant cell, i.e., a naturally occurring cell) , and associated regulatory sequences, and may or may not have sequences upstream of the AUG start site, and may or may not include untranslated leader sequences, signal sequences, downstream untranslated sequences, transcriptional start and stop sequences, polyadenylation signals, translational start and stop sequences, ribosome binding sites, and the like.

As demonstrated in the examples of the present disclosure, the inventors have identified a number of molecular entities that are associated with preeclampsia or preterm birth and that find use in combination (i.e. as a panel) in providing a preeclampsia and preterm birth assessment, e.g. diagnosing preeclampsia, prognosing a preeclampsia and preterm birth, monitoring a subject with preeclampsia and/or preterm birth, determining a treatment for a subject affected with preeclampsia or preterm birth, and the like. These include, but are not limited to, inhibin beta A (Activin A, Genbank Accession No. NM_002192) ； ADAM metallopeptidase domain 12 (Adam12, GenBank Accession No. NP_001275903.1, NM_001288974.1 [O43184-4] ； NP_001275904.1. NM_001288975.1. [O43184-3] , NP_003465.3, NM_003474.5, [O43184-1] , NP_067673.2. NM_021641.4. [O43184-2] ) .

As mentioned above, also provided herein are preeclampsia and preterm birth panels. By a “panel” of preeclampsia and preterm birth markers it is meant two or more preeclampsia and preterm birth markers, e.g. 3 or more, 4 or more, or 5 or more markers, whose levels, when considered in combination, find use in providing a preeclampsia and preterm birth assessment, e.g. making a preeclampsia and preterm birth risk diagnosis, prognosis, monitoring, and/or treatment. Of particular interest are panels that comprise the preeclampsia and preterm birth marker Activin A and Adam12. For example, in some embodiments, the preeclampsia panel may comprise Activin A and Adam12. .

Other combinations of preeclampsia and preterm birth markers that find use as preeclampsia panels in the subject methods may be readily identified by the ordinarily skilled artisan using any convenient statistical methodology, e.g. as known in the art or described in the working examples herein. For example, the panel of analytes may be selected by combining genetic algorithm (GA) and all paired (AP) support vector machine (SVM) methods for preeclampsia classification analysis. Predictive features are automatically determined, e.g. through iterative GA/SVM, leading to very compact sets of non-redundant preeclampsia-relevant analytes with the optimal classification performance. While different classifier sets will typically harbor only modest overlapping gene features, they will have similar levels of accuracy in providing a preeclampsia assessment to those described above and in the working examples herein.

METHODS

In some aspects of the invention, methods are provided for providing a preeclampsia assessment and prognosing preterm birth for a specific subject. To initiate the methods, a random forest model needs to be developed and trained using a plurality of clinical and laboratory test variables of randomly selected subjects, in order to derive a scoring metric to differentiate among a normal subject, a preeclampsia subject and a preterm birth subject.

A random forest model is a model generated through the random forest algorithm. Random forests or random decision forests are an ensemble learning method for classification, regression and other tasks, that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification) or mean prediction (regression) of the individual trees. The first algorithm for random decision forests was created by Tin Kam Ho using the random subspace method which, in Ho's formulation, is a way to implement the "stochastic discrimination" approach to classification proposed by Eugene Kleinberg. An extension of the algorithm was developed by Leo Breiman and Adele Cutler and "Random Forests" is their trademark. The extension combines Breiman's "bagging" idea and random selection of features, introduced first by Ho and later independently by Amit and Geman in order to construct a collection of decision trees with controlled variance.

A “forest” comprises a plurality of binary “trees” , and at each node, “trees” were split by choosing a split variable value producing the maximum node separation. “Trees” were constructed until each of the terminal nodes reached a sample size of 1. Final decisions were reached by averaging the decisions of each tree (Breiman L. Random forests. Machine Learning 2001； 45: 5-32； Breiman L. Bagging predictors. Machine Learning 1996； 24: 123-40. ) . An exemplary random forest model was constructed in a literature (See, e.g., Shiying Hao et. al. Classification Tool for Differentiation of Kawasaki Disease from Other Febrile Illnesses, The Journal of Pediatrics, Volume 176, September 2016, Pages 114–120. e8) .

To practice the methods, a plurality of clinical and laboratory test variables of randomly selected subjects are used. The plurality of clinical and laboratory test variables comprises at least two variables selected from physiological and/or biochemical factors, including but are not limited to systolic blood pressure, diastolic blood pressure, Activin A, gestational age, proteinuria, preeclampsia history, white blood cell count, preterm times, number of full-term pregnancy, education, ADAM12, multiple pregnancy, maternal height, maternal weight, BMI, abortion time, and age at blood collection. In some embodiments, the plurality of clinical and laboratory test variables comprises inhibin beta A (Activin A) and at least one selected from a group consisting of ADAM metallopeptidase domain 12 (Adam12) , body mass index (BMI) and white blood cell count (WBC) .

The term "biological sample" encompasses a variety of sample types obtained from an organism and can be used in a diagnostic, prognostic, or monitoring assay. The term encompasses blood and other liquid samples of biological origin or cells derived therefrom and the progeny thereof. The term encompasses samples that have been manipulated in any way after their procurement, such as by treatment with reagents, solubilization, or enrichment for certain components. The term encompasses a clinical sample, and also includes cell supernatants, cell lysates, serum, plasma, biological fluids, and tissue samples. Clinical samples for use in the methods of the invention may be obtained from a variety of sources, particularly blood samples.

In some embodiments the sample is a serum or serum-derived sample. Any convenient methodology for producing a fluid serum sample may be employed. In many embodiments, the method employs drawing venous blood by skin puncture (e.g., finger stick, venipuncture) into a clotting or serum separator tube, allowing the blood to clot, and centrifuging the serum away from the clotted blood. The serum is then collected and stored until assayed. Once the patient derived sample is obtained, the sample is assayed to determine the level of preeclampsia marker (s) .

The subject sample is typically obtained from the individual during the second or third trimester of gestation. By "gestation" it is meant the duration of pregnancy in a mammal, i.e. the time interval of development from fertilization until birth, plus two weeks, i.e. to the first day of the last menstrual period. By the second or third trimester, it is meant the second or third portions of gestation, each segment being 3 months long. Thus, for example, by the "first trimester" is meant from the first day of the last menstrual period through the 13th week of gestation； by the "second trimester" it is meant from the 14th through 27th week of gestation； and by the "third trimester" it is meant from the 28th week through birth, i.e. 38 -42 weeks of gestation. Put another way, a subject sample may be obtained 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 24 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. Thus, in some embodiments, the subject sample may be obtained early in gestation, e.g. at week 14 or more of gestation, e.g. at

week

14, 15, 16, 17, 18, 19, 20, 21, 22, or 23 or more of gestation, more often at

week

24, 25, 26, 27, 28, 29, 30, 31, 32, or week 33 or more of gestation. In other embodiments, the subject sample may be obtained late in gestation, for example, at or after 34 weeks of gestation, e.g. at

week

35, 36, 37, 38, 39, 40, or week 41 of gestation.

Once a sample is obtained, it can be used directly, frozen, or maintained in appropriate culture medium for short periods of time. Typically the samples will be from human patients, although animal models may find use, e.g. equine, bovine, porcine, canine, feline, rodent, e.g. mice, rats, hamster, primate, etc. Any convenient tissue sample that demonstrates the differential representation in a patient with preeclampsia of the one or more preeclampsia markers disclosed herein may be evaluated in the subject methods. Typically, a suitable sample source will be derived from fluids into which the molecular entity of interest, i.e. the RNA transcript or protein, has been released.

The subject sample may be treated in a variety of ways so as to enhance detection of the one or more preeclampsia markers. For example, where the sample is blood, the red blood cells may be removed from the sample (e.g., by centrifugation) prior to assaying. Such a treatment may serve to reduce the non-specific background levels of detecting the level of a preeclampsia and preterm birth marker using an affinity reagent. Detection of a preeclampsia and preterm birth marker may also be enhanced by concentrating the sample using procedures well known in the art (e.g. acid precipitation, alcohol precipitation, salt precipitation, hydrophobic precipitation, filtration (using a filter which is capable of retaining molecules greater than 30 kD, e.g. Centrim 30^TM) , affinity purification) . In some embodiments, the pH of the test and control samples will be adjusted to, and maintained at, a pH which approximates neutrality (i.e. pH 6.5-8.0) . Such a pH adjustment will prevent complex formation, thereby providing a more accurate quantitation of the level of marker in the sample. In embodiments where the sample is urine, the pH of the sample is adjusted and the sample is concentrated in order to enhance the detection of the marker.

In practicing the subject methods, the level (s) of preeclampsia and preterm birth marker (s) in the biological sample from an individual are evaluated. The level of one or more preeclampsia and preterm birth markers in the subject sample may be evaluated by any convenient method. For example, preeclampsia/preterm birth gene expression levels may be detected by measuring the levels/amounts of one or more nucleic acid transcripts, e.g. mRNAs, of one or more preeclampsia genes. Protein markers may be detected by measuring the levels/amounts of one or more proteins/polypeptides. 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.

For example, the level of at least one preeclampsia and preterm birth marker may be evaluated by detecting in a sample the amount or level of one or more proteins/polypeptides or fragments thereof to arrive at a protein level representation. The terms "protein"and "polypeptide" as used in this application are interchangeable. "Polypeptide" refers to a polymer of amino acids (amino acid sequence) and does not refer to a specific length of the molecule. Thus peptides and oligopeptides are included within the definition of polypeptide. This term also refers to or includes post-translationally modified polypeptides, for example, glycosylated polypeptide, acetylated polypeptide, phosphorylated polypeptide and the like. Included within the definition are, for example, polypeptides containing one or more analogs of an amino acid, polypeptides with substituted linkages, as well as other modifications known in the art, both naturally occurring and non-naturally occurring.

When protein levels are to be detected, any convenient protocol for evaluating protein levels may be employed wherein the level of one or more proteins in the assayed sample is determined. For example, one representative and convenient type of protocol for assaying protein levels is ELISA. In ELISA and ELISA-based assays, one or more antibodies specific for the proteins of interest may be immobilized onto a selected solid surface, preferably a surface exhibiting a protein affinity such as the wells of a polystyrene microtiter plate. After washing to remove incompletely adsorbed material, the assay plate wells are coated with a non-specific "blocking" protein that is known to be antigenically neutral with regard to the test sample such as bovine serum albumin (BSA) , casein or solutions of powdered milk. This allows for blocking of non-specific adsorption sites on the immobilizing surface, thereby reducing the background caused by non-specific binding of antigen onto the surface. After washing to remove unbound blocking protein, the immobilizing surface is contacted with the sample to be tested under conditions that are conducive to immune complex (antigen/antibody) formation. Such conditions include diluting the sample with diluents such as BSA or bovine gamma globulin (BGG) in phosphate buffered saline (PBS) /Tweenor PBSATriton-X 100, which also tend to assist in the reduction of nonspecific background, and allowing the sample to incubate for about 2-4 hrs at temperatures on the order of about 25°-27℃ (although other temperatures may be used) . Following incubation, the antisera-contacted surface is washed so as to remove non-immunocomplexed material. An exemplary washing procedure includes washing with a solution such as PBS/Tween, PBS/Triton-X 100, or borate buffer. The occurrence and amount of immunocomplex formation may then be determined by subjecting the bound immunocomplexes to a second antibody having specificity for the target that differs from the first antibody and detecting binding of the second antibody. In certain embodiments, the second antibody will have an associated enzyme, e.g. urease, peroxidase, or alkaline phosphatase, which will generate a color precipitate upon incubating with an appropriate chromogenic substrate. For example, a urease or peroxidase-conjugated anti-human IgG may be employed, for a period of time and under conditions which favor the development of immunocomplex formation (e.g., incubation for 2 hrs at room temperature in a PBS-containing solution such as PBS/Tween) . After such incubation with the second antibody and washing to remove unbound material, the amount of label is quantified, for example by incubation with a chromogenic substrate such as urea and bromocresol purple in the case of a urease label or 2, 2'-azino-di- (3-ethyl-benzthiazoline) -6-sulfonic acid (ABTS) and H₂O₂, in the case of a peroxidase label. Quantitation is then achieved by measuring the degree of color generation, e.g., using a visible spectrum spectrophotometer.

The preceding format may be altered by first binding the sample to the assay plate. Then, primary antibody is incubated with the assay plate, followed by detecting of bound primary antibody using a labeled second antibody with specificity for the primary antibody.

The solid substrate upon which the antibody or antibodies are immobilized can be made of a wide variety of materials and in a wide variety of shapes, e.g., microtiter plate, microbead, dipstick, resin particle, etc. The substrate may be chosen to maximize signal to noise ratios, to minimize background binding, as well as for ease of separation and cost. Washes may be effected in a manner most appropriate for the substrate being used, for example, by removing a bead or dipstick from a reservoir, emptying or diluting a reservoir such as a microtiter plate well, or rinsing a bead, particle, chromatograpic column or filter with a wash solution or solvent.

Alternatively, non-ELISA based-methods for measuring the levels of one or more proteins in a sample may be employed. Representative examples include but are not limited to mass spectrometry, proteomic arrays, xMAP^TM microsphere technology, flow cytometry, western blotting, and immunohistochemistry.

As another example, the level of at least one preeclampsia and preterm birth marker may be evaluated by detecting in a patient sample the amount or level of one or more RNA transcripts or a fragment thereof encoded by the gene of interest to arrive at a nucleic acid marker representation. The level of nucleic acids in the sample may be detected using any convenient protocol. While a variety of different manners of detecting nucleic acids are known, such as those employed in the field of differential gene expression analysis, one representative and convenient type of protocol for generating marker representations is array-based gene expression profiling protocols. Such applications are hybridization assays in which a nucleic acid that displays "probe" nucleic acids for each of the genes to be assayed/profiled in the marker representation to be generated is employed. In these assays, a sample of target nucleic acids is first prepared from the initial nucleic acid sample being assayed, where preparation may include labeling of the target nucleic acids with a label, e.g., a member of signal producing system. Following target nucleic acid sample preparation, the sample is contacted with the array under hybridization conditions, whereby complexes are formed between target nucleic acids that are complementary to probe sequences attached to the array surface. The presence of hybridized complexes is then detected, either qualitatively or quantitatively.

Specific hybridization technology which may be practiced to generate the marker representations employed in the subject methods includes the technology described in U.S. Patent Nos. : 5,143,854； 5,288,644； 5,324,633； 5,432,049； 5,470,710； 5,492,806； 5,503,980； 5,510,270； 5,525,464； 5,547,839； 5,580,732； 5,661,028； 5,800,992； the disclosures of which are herein incorporated by reference； as well as WO 95/21265； WO 96/31622； WO 97/10365； WO 97/27317； EP 373 203； and EP 785 280. In these methods, an array of "probe" nucleic acids that includes a probe for each of the phenotype determinative genes whose expression is being assayed is contacted with target nucleic acids as described above. Contact is carried out under hybridization conditions, e.g., stringent hybridization conditions, and unbound nucleic acid is then removed. The term "stringent assay conditions" as used herein refers to conditions that are compatible to produce binding pairs of nucleic acids, e.g., surface bound and solution phase nucleic acids, of sufficient complementarity to provide for the desired level of specificity in the assay while being less compatible to the formation of binding pairs between binding members of insufficient complementarity to provide for the desired specificity. Stringent assay conditions are the summation or combination (totality) of both hybridization and wash conditions.

The resultant pattern of hybridized nucleic acid provides information regarding expression for each of the genes that have been probed, where the expression information is in terms of whether or not the gene is expressed and, typically, at what level, where the expression data, i.e., marker representation (e.g., in the form of a transcriptosome) , may be both qualitative and quantitative.

Alternatively, non-array based methods for quantitating the level of one or more nucleic acids in a sample may be employed, including those based on amplification protocols, e.g., Polymerase Chain Reaction (PCR) -based assays, including quantitative PCR, reverse-transcription PCR (RT-PCR) , real-time PCR, and the like.

General methods in molecular and cellular biochemistry can be found in such standard textbooks as Molecular Cloning: A Laboratory Manual, 3rd Ed. (Sambrook et al., HaRBor Laboratory Press 2001) ； Short Protocols in Molecular Biology, 4th Ed. (Ausubel et al. eds., John Wiley &Sons 1999) ； Protein Methods (Bollag et al., John Wiley &Sons 1996) ； Nonviral Vectors for Gene Therapy (Wagner et al. eds., Academic Press 1999) ； Viral Vectors (Kaplift &Loewy eds., Academic Press 1995) ； Immunology Methods Manual (I. Lefkovits ed., Academic Press 1997) ； and Cell and Tissue Culture: Laboratory Procedures in Biotechnology (Doyle &Griffiths, John Wiley &Sons 1998) , the disclosures of which are incorporated herein by reference. Reagents, cloning vectors, and kits for genetic manipulation referred to in this disclosure are available from commercial vendors such as BioRad, Stratagene, Invitrogen, Sigma-Aldrich, and ClonTech.

The resultant data provides information regarding levels in the sample for each of the markers that have been probed, wherein the information is in terms of whether or not the marker is present and, typically, at what level, and wherein the data may be both qualitative and quantitative. As such, where detection is qualitative, the methods provide a reading or evaluation, e.g., assessment, of whether or not the target marker, e.g., nucleic acid or protein, is present in the sample being assayed. In yet other embodiments, the methods provide a quantitative detection of whether the target marker is present in the sample being assayed, i.e., an evaluation or assessment of the actual amount or relative abundance of the target analyte, e.g., nucleic acid or protein in the sample being assayed. In such embodiments, the quantitative detection may be absolute or, if the method is a method of detecting two or more different analytes, e.g., target nucleic acids or protein, in a sample, relative. As such, the term "quantifying"when used in the context of quantifying a target analyte, e.g., nucleic acid (s) or protein (s) , in a sample can refer to absolute or to relative quantification. Absolute quantification may be accomplished by inclusion of known concentration (s) of one or more control analytes and referencing the detected level of the target analyte with the known control analytes (e.g., through generation of a standard curve) . Alternatively, relative quantification can be accomplished by comparison of detected levels or amounts between two or more different target analytes to provide a relative quantification of each of the two or more different analytes, e.g., relative to each other.

Once the level of the one or more preeclampsia and preterm birth markers has been determined, the level of each of the panel of markers is fed, by for example inputting to a computer, into the random forest model to provide the preeclampsia assessment and prognose preterm birth.

UTILITY

The preeclampsia assessment and preterm birth prognosing may be employed to diagnose a preeclampsia and predict preterm birth； that is, to provide a determination as to whether a subject is affected by preeclampsia or will be affected by preterm birth, the type of preeclampsia and/or preterm birth, the severity of preeclampsia and/or preterm birth, etc. In some instances, the subject may present with clinical symptoms of preeclampsia, e.g. elevated blood pressure (e.g. 140/90 mm/Hg or higher) , proteinuria, sudden weight gain (over 1 -2 days or more than 2 pounds a week) , water retention (edema) , elevated liver enzymes, and/or thrombocytopenia (a depressed platelet count less than 100,000) . In other instances, subject may be asymptomatic for preeclampsia but has risk factors associated with preeclampsia, e.g. a medical condition such as gestational diabetes, type I diabetes, obesity, chronic hypertension, renal disease, a thrombophilia； African-American or Filipino descent； age of greater than 35 years or less than 20 years； a family history of preeclampsia； nulliparity； preeclampsia in a previous pregnancy； and/or stress. In other instances, the subject may present with risk factors of preterm birth, e.g. diabetes, high blood pressure, being pregnant with more than one baby, being either obese or underweight, a number of vaginal infections, tobacco smoking, and psychological stress, among others. In yet other instances, the subject may be asymptomatic for preeclampsia/preterm birth and have no risk factors associated with preeclampsia/preterm birth.

As another example, the preeclampsia assessment and preterm birth prognosing may be employed to prognose a preeclampsia and/or preterm birth； that is, to provide a preeclampsia and/or preterm birth prognosis. For example, the preeclampsia and preterm birth marker level representation may be used to predict a subject's susceptibility, or risk, of developing preeclampsia and preterm birth. By "predicting if the individual will develop preeclampsia and preterm birth" , it is meant determining the likelihood that an individual will develop preeclampsia and preterm birth in the next week, in the next 2 weeks, in the next 3 weeks, in the next 5 weeks, in the next 2 months, in the next 3 months, e.g. during the remainder of the pregnancy. The preeclampsia and preterm birth marker level representation may be used to predict the course of disease progression and/or disease outcome, e.g. expected onset of the preeclampsia and/or preterm birth, expected duration of the preeclampsia, expectations as to whether the preeclampsia will develop into eclampsia, etc. The preeclampsia and preterm birth marker level representation may be used to predict a subject's responsiveness to treatment for the preeclampsia and preterm birth, e.g., positive response, a negative response, no response at all.

As another example, the preeclampsia assessment and preterm birth prognosing may be employed to monitor a preeclampsia or preterm birth. By "monitoring" a preeclampsia or preterm birth, it is generally meant monitoring a subject's condition, e.g. to inform a preeclampsia/preterm birth diagnosis, to inform a preeclampsia/preterm birth prognosis, to provide information as to the effect or efficacy of a preeclampsia/preterm birth treatment, and the like.

As another example, the preeclampsia assessment and preterm birth prognosing may be employed to determine a treatment for a subject. The terms "treatment" , "treating" and the like are used herein to generally mean obtaining a desired pharmacologic and/or physiologic effect. The effect may be prophylactic in terms of completely or partially preventing a disease or symptom thereof and/or may be therapeutic in terms of a partial or complete cure for a disease and/or adverse effect attributable to the disease. "Treatment" as used herein covers any treatment of a disease in a mammal, and includes: (a) preventing the disease from occurring in a subject which may be predisposed to the disease but has not yet been diagnosed as having it； (b) inhibiting the disease, i.e., arresting its development； or (c) relieving the disease, i.e., causing regression of the disease. The therapeutic agent may be administered before, during or after the onset of disease or injury. The treatment of ongoing disease, where the treatment stabilizes or reduces the undesirable clinical symptoms of the patient, is of particular interest. The subject therapy may be administered prior to the symptomatic stage of the disease, and in some cases after the symptomatic stage of the disease. The terms "individual, " "subject, " "host, "and "patient, " are used interchangeably herein and refer to any mammalian subject for whom diagnosis, treatment, or therapy is desired, particularly humans. Preeclampsia treatments are well known in the art, and may include bed rest, drinking extra water, a low salt diet, medicine to control blood pressure, corticosteroids, inducing pregnancy, and the like.

In some embodiments, the subject methods of providing a preeclampsia/preterm birth assessment, e.g. diagnosing a preeclampsia/preterm birth, prognosing a preeclampsia/preterm birth, monitoring the preeclampsia/preterm birth, and the like, may comprise additional assessment (s) that are employed in conjunction with the methods stated above. For example, the subject methods may further comprise measuring one or more clinical parameters/factors associated with preeclampsia, e.g. blood pressure, urine protein, weight changes, water retention (edema) , liver enzyme levels, and platelet count. For example, a subject maybe assessed for one or more clinical symptoms, e.g. hypertension, proteinuria, etc., at about week 14 or more of gestation,

e.g. week

15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,32, 33, 34 35, 36, 37, 38, 39, 40 or more of gestation, wherein a positive outcome of the clinical assessment (i.e. the detection of one or more symptoms associated with preeclampsia/preterm birth) is used in combination with the marker level representation to provide a preeclampsia/preterm birth diagnosis, a preeclampsia/preterm birth prognosis, to monitor the preeclampsia/preterm birth, etc. In some instances, the clinical parameters may be measured prior to obtaining the preeclampsia and preterm birth marker level representation, for example, to inform the artisan as to whether a preeclampsia and preterm birth marker level representation should be obtained, e.g. to make or confirm a preeclampsia/preterm birth diagnosis. In some instances, the clinical parameters may be measured after obtaining the preeclampsia and preterm birth marker level representation, e.g. to monitor a preeclampsia/preterm birth.

As another example, the subject methods of providing a preeclampsia assessment and prognosing preterm birth may further comprise assessing one or more factors associated with the risk of developing preeclampsia/preterm birth. Non-limiting examples of preeclampsia/preterm birth risk factors include, for example, a medical condition such as gestational diabetes, obesity, chronic hypertension, renal disease, a thrombophilia； age of greater than 35 years or less than 20 years； a family history of preeclampsia； nulliparity； preeclampsia in a previous pregnancy； stress； being pregnant with more than one baby； being either obese or underweight； a number of vaginal infections； tobacco smoking. For example, a subject maybe assessed for one or more risk factors, e.g. medical condition, family history, etc., when pregnancy is first confirmed or thereafter, wherein a positive outcome of the risk assessment (i.e. the determination of one or more risk factors associated with preeclampsia/preterm birth) is used in combination with the marker level representation to provide a preeclampsia/preterm birth diagnosis, a preeclampsia/preterm birth prognosis, to monitor the preeclampsia/preterm birth, etc.

The subject methods may be employed for a variety of different types of subjects. In many embodiments, the subjects are within the class mammalian, including the orders carnivore (e.g., dogs and cats) , rodentia (e.g., mice, guinea pigs, and rats) , lagomorpha (e.g. rabbits) and primates (e.g., humans, chimpanzees, and monkeys) . In certain embodiments, the animals or hosts, i.e., subjects (also referred to herein as patients) , are humans.

In some embodiments, the subject methods of providing a preeclampsia assessment and prognosing preterm birth include providing a diagnosis, prognosis, or result of the monitoring. In some embodiments, the preeclampsia/preterm birth assessment of the present disclosure is provided by providing, i.e. generating, a written report that includes the artisan's assessment, for example, the artisan's determination of whether the patient is currently affected by preeclampsia/preterm birth, of the type, stage, or severity of the subject's preeclampsia/preterm birth, etc. (a "preeclampsia/preterm birth diagnosis") ； the artisan's prediction of the patient's susceptibility to developing preeclampsia/preterm birth, of the course of disease progression, of the patient's responsiveness to treatment, etc. (i.e., the artisan's "preeclampsia/preterm birth prognosis" ) ； or the results of the artisan's monitoring of the preeclampsia/preterm birth. Thus, the subject methods may further include a step of generating or outputting a report providing the results of an artisan's assessment, which report can be provided in the form of an electronic medium (e.g., an electronic display on a computer monitor) , or in the form of a tangible medium (e.g., a report printed on paper or other tangible medium) . Any form of report may be provided, e.g. as known in the art or as described in greater detail below.

REPORTS

A "report, "as described herein, is an electronic or tangible document which includes report elements that provide information of interest relating to the assessment of a subject and its results. In some embodiments, a subject report includes at least a preeclampsia and preterm birth marker representation, e.g. a preeclampsia/preterm birth profile or a preeclampsia/preterm birth score, as discussed in greater detail above. In some embodiments, a subject report includes at least an artisan's preeclampsia/preterm birth assessment, e.g. preeclampsia/preterm birth diagnosis, preeclampsia/preterm birth prognosis, an analysis of a preeclampsia/preterm birth monitoring, a treatment recommendation, etc. A subject report can be completely or partially electronically generated. A subject report can further include one or more of: 1) information regarding the testing facility； 2) service provider information； 3) patient data； 4) sample data； 5) an assessment report, which can include various information including: a) reference values employed, and b) test data, where test data can include, e.g., a protein level determination； 6) other features.

The report may include information about the testing facility, which information is relevant to the hospital, clinic, or laboratory in which sample gathering and/or data generation was conducted. Sample gathering can include obtaining a fluid sample, e.g. blood, saliva, urine etc. ； a tissue sample, e.g. a tissue biopsy, etc. from a subject. Data generation can include measuring the marker concentration in preeclampsia/preterm birth patients versus healthy individuals, i.e. individuals that do not have and/or do not develop preeclampsia/preterm birth. This information can include one or more details relating to, for example, the name and location of the testing facility, the identity of the lab technician who conducted the assay and/or who entered the input data, the date and time the assay was conducted and/or analyzed, the location where the sample and/or result data is stored, the lot number of the reagents (e.g., kit, etc. ) used in the assay, and the like. Report fields with this information can generally be populated using information provided by the user.

The report may include information about the service provider, which may be located outside the healthcare facility at which the user is located, or within the healthcare facility. Examples of such information can include the name and location of the service provider, the name of the reviewer, and where necessary or desired the name of the individual who conducted sample gathering and/or data generation. Report fields with this information can generally be populated using data entered by the user, which can be selected from among pre-scripted selections (e.g., using a drop-down menu) . Other service provider information in the report can include contact information for technical information about the result and/or about the interpretive report.

The report may include a patient data section, including patient medical history (which can include, e.g., age, race, serotype, prior preeclampsia/preterm birth episodes, and any other characteristics of the pregnancy) , as well as administrative patient data such as information to identify the patient (e.g., name, patient date of birth (DOB) , gender, mailing and/or residence address, medical record number (MRN) , room and/or bed number in a healthcare facility) , insurance information, and the like) , the name of the patient's physician or other health professional who ordered the monitoring assessment and, if different from the ordering physician, the name of a staff physician who is responsible for the patient's care (e.g., primary care physician) .

The report may include a sample data section, which may provide information about the biological sample analyzed in the monitoring assessment, such as the source of biological sample obtained from the patient (e.g. blood, saliva, or type of tissue, etc. ) , how the sample was handled (e.g. storage temperature, preparatory protocols) and the date and time collected. Report fields with this information can generally be populated using data entered by the user, some of which may be provided as pre-scripted selections (e.g., using a drop-down menu) . The report may include a results section. For example, the report may include a section reporting the results of a protein level determination assay (e.g., "6.0 ng/ml Activin A in serum" ) , or a calculated preeclampsia/preterm birth score.

The report may include an assessment report section, which may include information generated after processing of the data as described herein. The interpretive report can include a prediction of the likelihood that the subject will develop preeclampsia/preterm birth. The interpretive report can include a diagnosis of preeclampsia/preterm birth. The interpretive report can include a characterization of preeclampsia/preterm birth. The assessment portion of the report can optionally also include a recommendation (s) . For example, where the results indicate that preeclampsia/preterm birth is likely, the recommendation can include a recommendation that diet be altered, blood pressure medicines administered, etc., as recommended in the art.

It will also be readily appreciated that the reports can include additional elements or modified elements. For example, where electronic, the report can contain hyperlinks which point to internal or external databases which provide more detailed information about selected elements of the report. For example, the patient data element of the report can include a hyperlink to an electronic patient record, or a site for accessing such a patient record, which patient record is maintained in a confidential database. This latter embodiment may be of interest in an in-hospital system or in-clinic setting. When in electronic format, the report is recorded on a suitable physical medium, such as a computer readable medium, e.g., in a computer memory, zip drive, CD, DVD, etc.

It will be readily appreciated that the report can include all or some of the elements above, with the proviso that the report generally includes at least the elements sufficient to provide the analysis requested by the user (e.g. a calculated preeclampsia and preterm birth marker level representation； a prediction, diagnosis or characterization of preeclampsia/preterm birth) .

REAGENTS, SYSTEMS AND KITS

Also provided are reagents, systems and kits thereof for practicing one or more of the above-described methods. The subject reagents, systems and kits thereof may vary greatly. Reagents of interest include reagents specifically designed for use in determining the level of preeclampsia and preterm birth markers from a sample, for example, one or more detection elements, e.g. antibodies or peptides for the detection of protein, oligonucleotides for the detection of nucleic acids, etc. In some instances, the detection element comprises a reagent to detect the expression of a single preeclampsia and preterm birth marker, for example, the detection element may be a dipstick, a plate, an array, or cocktail that comprises one or more detection elements, e.g. one or more antibodies, one or more oligonucleotides, one or more sets of PCR primers, etc. which may be used to detect the expression of one or more preeclampsia and preterm birth marker simultaneously,

One type of reagent that is specifically tailored for determining the level is a collection of antibodies that bind specifically to the protein markers, e.g. in an ELISA format, in an xMAP^TM microsphere format, on a proteomic array, in suspension for analysis by flow cytometry, by western blotting, by dot blotting, or by immunohistochemistry. Methods for using the same are well understood in the art. These antibodies can be provided in solution. Alternatively, they may be provided pre-bound to a solid matrix, for example, the wells of a multi-well dish or the surfaces of xMAP microspheres.

Another type of such reagent is an array of probe nucleic acids in which the genes of interest are represented. A variety of different array formats are known in the art, with a wide variety of different probe structures, substrate compositions and attachment technologies (e.g., dot blot arrays, microarrays, etc. ) . Representative array structures of interest include those described in U.S. Patent Nos. : 5,143,854； 5,288,644； 5,324,633； 5,432,049； 5,470,710； 5,492,806； 5,503,980； 5,510,270； 5,525,464； 5,547,839； 5,580,732； 5,661,028； 5,800,992； the disclosures of which are herein incorporated by reference； as well as WO 95/21265； WO 96/31622； WO 97/10365； WO 97/27317； EP 373 203； and EP 785 280.

Another type of reagent that is specifically tailored for determining the level of genes, e.g. preeclampsia/preterm birth genes, is a collection of gene specific primers that is designed to selectively amplify such genes (e.g., using a PCR-based technique, e.g., real-time RT-PCR) . Gene specific primers and methods for using the same are described in U.S. Patent No. 5,994,076, the disclosure of which is herein incorporated by reference.

Of particular interest are arrays of probes, collections of primers, or collections of antibodies that include probes, primers or antibodies (also called reagents) that are specific for at least 1 gene/protein selected from the group consisting of Activin A and Adam12, or a biochemical substrate specific for the cofactor/prosthetic group heme, in some instances for a plurality of these genes/polypeptides, e.g., at least 2, 3, 4, 5, 6, 7, 8 or more genes/polypeptides. In certain embodiments, the collection of probes, primers, or antibodies includes reagents specific for Activin A and Adam12 as well as a biochemical substrate specific for heme. The subject probe, primer, or antibody collections or reagents may include reagents that are specific only for the genes/proteins/cofactors that are listed above, or they may include reagents specific for additional genes/proteins/cofactors that are not listed above, such as probes, primers, or antibodies specific for genes/proteins/cofactors whose expression pattern are known in the art to be associated with preeclampsia/preterm birth.

In some instances, a system may be provided. As used herein, the term “system” refers to a collection of reagents, however compiled, e.g., by purchasing the collection of reagents from the same or different sources. In some instances, a kit may be provided. As used herein, the term "kit" refers to a collection of reagents provided, e.g., sold, together. For example, the nucleic acid-or antibody-based detection of the sample nucleic acid or protein, respectively, may be coupled with an electrochemical biosensor platform that will allow multiplex determination of these biomarkers for personalized preeclampsia/preterm birth care.

The systems and kits of the subject invention may include the above-described arrays, gene-specific primer collections, or protein-specific antibody collections. The systems and kits may further include one or more additional reagents employed in the various methods, such as primers for generating target nucleic acids, dNTPs and/or rNTPs, which may be either premixed or separate, one or more uniquely labeled dNTPs and/or rNTPs, such as biotinylated or Cy3 or Cy5 tagged dNTPs, gold or silver particles with different scattering spectra, or other post synthesis labeling reagent, such as chemically active derivatives of fluorescent dyes, enzymes, such as reverse transcriptases, DNA polymerases, RNA polymerases, and the like, various buffer mediums, e.g. hybridization and washing buffers, prefabricated probe arrays, labeled probe purification reagents and components, like spin columns, etc., signal generation and detection reagents, e.g. labeled secondary antibodies, streptavidin-alkaline phosphatase conjugate, chemifluorescent or chemiluminescent substrate, and the like.

In addition to the above components, the subject kits will further include instructions for practicing the subject methods. These instructions may be present in the subject kits in a variety of forms, one or more of which may be present in the kit. One form in which these instructions may be present is as printed information on a suitable medium or substrate, e.g., a piece or pieces of paper on which the information is printed, in the packaging of the kit, in a package insert, etc. Yet another means would be a computer readable medium, e.g., diskette, CD, etc., on which the information has been recorded. Yet another means that may be present is a website address which may be used via the internet to access the information at a removed site. Any convenient means may be present in the kits.

The following examples are offered by way of illustration and not by way of limitation.

EXAMPLES

The following examples are put forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how to make and use the present invention, and are not intended to limit the scope of what the inventors regard as their invention nor are they intended to represent that the experiments below are all or the only experiments performed. Efforts have been made to ensure accuracy with respect to numbers used (e.g. amounts, temperature, etc. ) but some experimental errors and deviations should be accounted for. Unless indicated otherwise, parts are parts by weight, molecular weight is weight average molecular weight, temperature is in degrees Centigrade, and pressure is at or near atmospheric.

Example 1

As the leading cause of maternal morbidity and mortality, preeclampsia (PE) is a pregnancy-related vascular disorder affecting 5％-8％of all pregnancies (Berg et al. Overview of maternal morbidity during hospitalization for labor and delivery in the United States: 1993-1997 and 2001-2005. Obstetrics and gynecology 2009； 113: 1075-81； Mackay et al. Pregnancy-related mortality from preeclampsia and eclampsia. Obstetrics and gynecology 2001； 97: 533-8) . PE, which often causes fetal growth restriction and pre-term delivery as well as fetal mortality and morbidity, can be remedied by delivery of the placenta and fetus (Powe et al. Preeclampsia, a disease of the maternal endothelium: the role of antiangiogenic factors and implications for later cardiovascular disease. Circulation 2011； 123: 2856-69) . The etiology of PE is incompletely understood. Current diagnosis of PE is based on the signs of hypertension and proteinuria (Gynecologists ACOOA ACOG practice bulletin. Diagnosis and management of preeclampsia and eclampsia. Number 33, January 2002. Obstetrics and gynecology 2002； 99: 159-67) , but lacks sensitivity and specificity and carries a poor prognosis for adverse maternal and fetal outcomes (Zhang et al. Prediction of adverse outcomes by common definitions of hypertension in pregnancy. Obstetrics and gynecology 2001； 97: 261-7) . Thus, there is a need to identify PE biomarkers that can provide a definitive diagnosis with the opportunity for better monitoring of the condition's progression, and thus improved outcomes and economic benefits.

Although the pathophysiology remains largely elusive, PE is a multisystem disorder of pregnancy with the placenta playing a pivotal role. Investigators have used genetic, genomic and proteomic approaches to compare PE and control placental tissues. Transcriptional profiling of case-control samples has identified disease-specific expression patterns, canonical pathways and gene-gene networks (Lapaire et al. Microarray screening for novel preeclampsia biomarker candidates. Fetal diagnosis and therapy 2012； 31: 147-53； Nishizawa et al. Microarray analysis of differentially expressed fetal genes in placenta tissue derived from early and late onset severe preeclampsia. Placenta 2007； 28: 487-97； Loset et al. transcriptional profile of the decidua in preeclampsia. American journal of obstetrics and gynecology 2011； 204: 84 e1-27； Johansson et al. Partial correlation network analyses to detect altered gene interactions in human disease: using preeclampsia as a model. Human genetics 2011； 129: 25-34； Sitras et al. Differential placental gene expression in severe preeclampsia. Placenta 2009； 30: 424-33； Tsai et al. Transcriptional profiling of human placentas from pregnancies complicated by preeclampsia reveals disregulation of sialic acid acetylesterase and immune signaling pathways. Placenta 2011； 32: 175-82； Winn et al. Severe preeclampsia-related changes in gene expression at the maternal-fetal interface include sialic acid-binding immunoglobulin-like lectin-6 and pappalysin-2. Endocrinology 2009； 150: 452-62) . Proteomics-based biomarker studies (Kolia et al. Quantitative proteomic (iTRAQ) analysis of 1st trimester maternal plasma samples in pregnancies at risk for preeclampsia. Journal of biomedicine &biotechnology 2012； 2012: 305964； Mary et al. Dynamic proteome in enigmatic preeclampsia: an account of molecular mechanisms and biomarker discovery. Proteomics Clinical applications 2012； 6: 79-90； Carty et al. Urinary proteomics for prediction of preeclampsia. Hypertension 2011； 57: 561-9) have also revealed candidate biomarkers for future testing. Placental angiogenic and anti-angiogenic factor imbalance, elevated soluble fms-like tyrosine kinase (sFlt-1) and decreased placental growth factor (PIGF) levels, are suggested in the pathogenesis of PE (Shibata et al. Soluble fms-like tyrosine kinase 1 is increased in preeclampsia but not in normotensive pregnancies with small-for-gestational-age neonates: relationship to circulating placental growth factor. The Journal of clinical endocrinology and metabolism 2005； 90: 4895-903； Maynard et al. Excess placental soluble fms-like tyrosine kinase 1 (sFIt-1) may contribute to endothelial dysfunction, hypertension, and proteinuria in preeclampsia. The Journal of clinical investigation 2003； 111: 649-58； Wolf et al. Circulating levels of the antiangiogenic marker sFLT-1 are increased in first versus second pregnancies. American journal of obstetrics and gynecology 2005； 193: 16-22； Rajakumar et al. Extra-placental expression of vascular endothelial growth factor receptor-1, (Flt-1) and soluble Flt-1 (sFlt-1) , by peripheral blood mononuclear cells (PBMCs) in normotensive and preeclamptic pregnant women. Placenta 2005； 26: 563-73； Taylor et al. Altered tumor vessel maturation and proliferation in placenta growth factor-producing tumors: potential relationship to post-therapy tumor angiogenesis and recurrence. International journal of cancer Journal international du cancer 2003； 105: 158-64； Tidewell et al. Low maternal serum levels of placenta growth factor as an antecedent of clinical preeclampsia. American journal of obstetrics and gynecology 2001； 184: 1267-72； Torry et al. Preeclampsia is associated with reduced serum levels of placenta growth factor. American journal of obstetrics and gynecology 1998； 179: 1539-44) , and the sFlt-1/PIGF ratio has been proposed as a useful index in the diagnosis and management of PE (Stepan et al. [use of angiogenic factors (sflt-1/plgf ratio) to confirm the diagnosis of preeclampsia in clinical routine: First experience] . Zeitschrift fur Geburtshilfe und Neonatologie. 2010； 214: 234-238； Verlohren et al. An automated method for the determination of the sflt-1/pigf ratio in the assessment of preeclampsia. Am. J. Obst. And Gyn. 2010； 202: 161 e161-161 e111) . However, no widely applicable, sensitive and specific molecular PE test in routine clinical practice is currently available.

The cause of preterm birth (PTB) is often not known. Risk factors include diabetes, high blood pressure, being pregnant with more than one baby, being either obese or underweight, a number of vaginal infections, tobacco smoking, and psychological stress, among others. It is recommended that labor not be medically induced before 39 weeks unless required for other medical reasons. The same recommendation applies to cesarean section. Preterm labor and delivery continue to plague modern obstetrics. The preterm birth rate still rests at approximately 11％of deliveries, with ensuing neonatal morbidity and death. This is unchanged despite research into strategies such as tocolytics, risk assessment, and regionalization. Neonatal survival has improved by advances in the neonatal intensive care unit and the use of antepartum steroid administration to reduce the incidence of outcomes (such as respiratory distress syndrome and intraventricular hemorrhage) . There has recently been a strong push toward the identification of patients at risk for preterm birth before the onset of labor symptoms. The use of different markers, most notably the presence of bacterial vaginosis, assessment of cervicovaginal fetal fibronectin, and cervical length determined by ultrasound scanning, has been studied in the hopes of targeting those women who are at risk for premature delivery, thereby aiding the clinician in decision making to treat specific patients with different modalities (eg, tocolytics, steroids, antibiotics, cerclage) . A serum molecular marker would be advantageous because cervical length, fetal fibronectin, and bacterial vaginosis status involve cervical/vaginal evaluation.

In light of these considerations, there is a strong rationale and need to discover diagnostic and prognostic biomarkers for PE and PTB. We employed a comprehensive unbiased multi- ‘omics’a pproach, integrating results from microarray multiplex meta-analysis, and proteomic identification by two-dimensional (2D) gel analysis. Our applied parametric method (Morgan et al. Comparison of multiplex meta analysis techniques for understanding the acute rejection of solid organ transplants. BMC bioinformatics 2010； 11 Suppl 9: S6； Chen et al. Differentially expressed RNA from public microarray data identifies serum protein biomarkers for cross-organ transplant rejection and other conditions. PLoS computational biology 2010； 6) in meta-analysis allowed us to identify consistent and significant differential gene expression across experiments to develop biomarkers for downstream experimental validation. Serum proteins are routinely used to diagnose diseases, but sensitive and specific biomarkers are hard to find and may be due to their low serological abundance, which can easily be masked by highly abundant proteins. Our serum protein marker discovery method (Ling et al. Plasma profiles in active systemic juvenile idiopathic arthritis: Biomarkers and biological implications. Proteomics 2010) combines antibody-based serum abundant protein depletion and 2D gel comparative profiling to discover differential protein gel spots between PE and control sera for subsequent protein mass spectrometric identification. We hypothesized that there would be differential serological signatures allowing PE/PTB diagnosis. To validate our discovery findings, we tested all the candidates with available ELISA assays, a higher-throughput method. To construct and optimize a sensitive and specific biomarker panel with the least number of protein analytes, a genetic algorithm was used. Close examination of the biomarkers from comparative transcriptomics and proteomics, and their associated pathways led to new hypothesis about their role in PE/PTB pathophysiology.

The presented results validated our hypothesis that sensitive and specific serological biomarker panels can be constructed to differentiate PE, PTB, and normal subjects. To our knowledge, this represents the first study to employ a muti- ‘omics’ -based biomarker approach to uncover novel PE/PTB biomarkers including Activin A and Adam12. We believe that the functional significance of these PE/PTB biomarkers and their associated pathways will provide new insights into the disease pathogenesis and lead to effective novel therapeutics.

MATERIALS AND METHODS

Study design. The overall sample allocation, PE/PTB biomarker discovery, validation, and predictive panel construction steps are illustrated in Figures 1 and 2. Our study was conducted in two phases: (1) the discovery phase, which included meta analysis of microarray datasets (6 PE datasets, n＝98 PE and n＝111 control placenta samples； 3 PTB datasets, n＝20 preterm birth and n＝38 control placenta samples) , extraction of placenta specific protein from database of protein atlas and obtainment of human orthologous gene with placenta dysfunction in mouse model from MGI database. (2) the validation phase, which was comprised of the analysis of independent cohorts for PE analysis (PE, n＝100； control, n＝100) and for PTB analysis (PTB, n＝109； control, n＝89) . The candidates for further validation were selected by the fold change > 1.2 and p value < 0.05 in the meta analysis and by ELISA assay kits available. Then the common candidates for PE and PTB were selected (Activin A and Adam12) .

Clinical cohort design and sample collection. All the serum samples were purchased from R&D systems (MN 55413, https: //www. rndsystems. com/) , Diagnostica Stago Inc. (NJ 07054, http: //www. stago-us. com/) . All serum samples were collected after informed consent was obtained, and included detailed case report forms. Patients who were diagnosed with antiphospholipid syndrome (APS) , or systemic lupus erythematosus (SLE) or any other concurrent autoimmune diseases or under long term corticosteroid treatment were excluded from PE cohort； Patients who were diagnosed with suspected placenta previa, cervical cerclage, and trauma precipitating the patient’s preterm laboring symptoms (regular uterine contractions, low abdominal cramping, low back pain, pelvic pressure, vaginal bleeding, and increased vaginal discharge) were excluded from PTB cohort； patients who were diagnosed with preterm birth, or intrauterine growth retardation (IUGR) , HELLP syndrome, and PE were excluded from control cohort. PE, PTB, and control (normal pregnant) cohorts were matched for gestational age and ethnicity.

Multiplex meta-analysis of expression comparing PE and control placentas. As shown in Tables 1 and 2 below, six PE placenta expression studies (Nishizawa et al. Microarray analysis of differentially expressed fetal genes in placenta tissue derived from early and late onset severe preeclampsia. Placenta 2007； 28: 487-97； Sitras et al. Differential placental gene expression in severe preeclampsia. Placenta 2009； 30: 424-33； Tsai et al. Transcriptional profiling of human placentas from pregnancies complicated by preeclampsia reveals disregulation of sialic acid acetylesterase and immune signalling pathways. Placenta 2011； 32: 175-82； Nishizawa et al. Comparative gene expression profiling of placentas from patients with severe preeclampsia and unexplained fetal growth restriction. Reproductive biology and endocrinology 2011； 9: 107； Blair JD et al. Widespread DNA hypomethylation at gene enhancer regions in placentas associated with early-onset pre-eclampsia. Molecular Human Reproduction 2013； 19: 697-708； Jebbink JM et al. Increased glucocerebrosidase expression and activity in preeclamptic placenta. Placenta 2013； 36: 160-169) and three placenta expression studies (PMID: 22496790； 23290504； 18818296/17170095) were combined and subjected to multiplex meta-analysis with the method we previously developed (Morgan et al. Comparison of multiplex meta-analysis techniques for understanding the acute rejection of solid organ transplants. BMC bioinformatics 2010； 11 Suppl 9: S6； Chen et al. Differentially expressed RNA from public microarray data identifies serum protein biomarkers for cross-organ transplant rejection and other conditions. PLoS computational biology 2010； 6) . For each of the 22, 394 genes tested, we calculated the meta-fold change across all studies. Significant genes were selected if they were measured in 5 or more studies and the meta effect p value was less than 0.05 and the meta-fold change higher than 1.2.

Protein Atlas analysis. According to Uhlén M et al (Proteomics. Tissue-based map of the human proteome. Science. 2015 Jan 23； 347 (6220) : 1260419. ) , the placenta genes were extracted from five tissue categories: tissue enriched, group enriched, tissue enhanced, expressed in all (FPKM>100) , mixed. (FPKM>100)

Human orthologous gene with placenta dysfunction in mouse model from MGI database. To understand the functional significance of placenta genes in pregnancy disorders, the human orthologous genes whose mouse orthologs were associated with abnormal placental phenotypes when disrupted were obtained from MGI database. Three MGI phenotypes were included: abnormal extraembryonic boundary morphology MP: 0003836, abnormal extraembryonic tissue physiology MP: 0004264 and abnormal extraembryoic tissue morphology MP: 0002086.

ELISA assays validating PE and PTB marker candidates. All assays were ELISA assays, and performed using commercial kits following vendors'instructions. All assays were performed to measure serum levels of selected analytes as summarized in Table 9 and 10 for the analytes of: inhibin beta A (Activin A) , Adam12 (ADAM metallopeptidase domain 12) .

Statistical analyses. Patient demographic and clinical data were analyzed using the "Epidemiological calculator" (R epicalc package) . Student's t-test and Mann–Whitney U-test were performed to calculate p values for continuous variables, and Fisher’s exact test and Chi-squared test were used for comparative analysis of categorical variables. A group of clinical risk factors of preeclampsia/preterm birth were determined by literature review, and their impacts on differentiation were explored by uni-and multivariate analysis. Forest plotting with R rmeta package was used both to represent the placental expression meta analysis and to graphically summarize the serum protein ELISA results. PE, PTB, and control samples are not paired； thus the initial serum protein forest plot analysis should be interpreted with caution. Bootstrapping method was used to create "paired" samples from case and control groups for the subsequent forest plotting analysis of the ELISA results. Therefore, serum protein forest plot analysis provides an overall effect estimation of each analyte's capability in discriminating PE, PTB, and normal pregnant control subjects. Hypothesis testing was performed using Student's t-test (two tailed) and Mann-Whitney U-test (two tailed) , and local FDR (Efron et al. Empirical bayes analysis of microarray experiment. J Am Stat Assoc 2001； 96: 1151 -60) to correct for multiple hypothesis testing issues. Biomarker feature selection and panel optimization was performed using a genetic algorithm (R genalg package) . The predictive performance of each biomarker panel analysis was evaluated by ROC curve analysis (Zweig et al. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clinical chemistry 1993； 39: 561-77； Sing et al. ROCR: visualizing classifier performance in R. Bioinformatics 2005； 21: 3940-1) . A composite panel combining all significant biomarkers was developed using random forest algorithm. The biomarker panel score was defined as the majority votes of all trees in random forest algorithm.

RESULTS

Multi- ‘Omics’ -based discovery revealing PE and PTB marker candidates. As shown in Figures 1-4, previous placental expression studies were combined for a multiplex meta-analysis, as well as Protein Atlas analysis and human orthologous gene analysis, to discover biomarker candidates diagnosing PE and PTB from normal controls. This effort identified Activin A and Adam12 as differential placental biomarkers for both PE and PTB from normal controls.

Sample characteristics. There are 100 PE, 102 PTB, and 129 control subjects used for serological protein biomarker validation. As summarized in Table 3 below, no significant differences (p value < 0.05) in age (p value＝0.374) at enrollment, ethnicity (p value＝0.281) were observed. The gap between the blood sample collection and the delivery was 1.8±3.1 weeks for PE, 0.9±1.4 and 6.8±5.1 weeks for control subjects.

Patient demographics, including body mass index (BMI, prior to pregnancy) , blood pressure (BP) , pregnancy history, proteinuria, maternal height and weight, and delivery outcomes were shown in Table 4.

Analysis on risk factors of preeclampsia and preterm birth. A group of risk factors (PE: BMI, age, and concurrent diabetes during pregnancy； PTB: BMI, whole blood cell count, education level, and neutrophil percentage during pregnancy) were selected by literature review. The impact of these risk factors was investigated by univariate and multivariate analysis with or without adjustment of gestational age at blood sample collection, respectively (Tables 5-8) . Results of odds ratio and hazard ratio showed that BMI had significant, positive impact (p<0.05) on preeclampsia； education level, whole blood cell count, and neutrophil differential abnormality (p<0.05) are potential risk factors on preterm birth.

Biomarker validation using PE, PTB, and control maternal serum samples. To identify whether the PE serological protein panel could enable development of an immediate practical clinical tool, based on available ELISA assays, biomarker candidates, from expression meta-analysis and 2D gel profiling, were validated with available serum assays using PE (n＝100) , PTB (n＝102) , and control samples (n＝129) . Detailed with whisker box and scatter plots in Figures 7-8, two proteins were validated by ELISA assays (Mann–Whitney U-test) . Figures 7-8 also demonstrated the distribution of maternal serum abundance of each validated protein over the gestational age (weeks) of blood sample collection, delivery, and the gap in between. Each validated biomarker's median, mean and standard deviation of maternal serum abundance, in PE, PTB, and control samples, are summarized in Table 9 and 10.

Forest plots (Figures 5 and 6) summarize the PE to control ratios of 21 PE markers and PTB to control ratios of 32 PTB markers across placental expression meta-analyses. The biomarkers derived from the proteomic and expression meta-analyses consistently shared the same trend of up-or down-regulation between PE, PTB, and control samples.

Univariate and multivariate analysis of validated biomarkers. Univariate and multivariate analyses were performed on each of the two validated PE biomarkers (Tables 11-14) . Results of odds ratios and hazard ratios in univariate analysis showed that Activin A had significant impact (p<0.05) on preeclampsia, and all two markers had significant impact (p<0.05) on preterm birth. Multivariate analysis of odds ratio showed that Activin A had significant impact (p<0.05) on preeclampsia, and had significant impact (p<0.05) on preterm birth. The results indicate panels consisting of these biomarkers may achieve optimum classification performance of PE and control subjects.

Biomarker panel construction. Using data from the ELISA assays, we constructed a random forest algorithm of the two protein analyte panel (Activin A and Adam12) , plus clinical parameters (Figures 9-11) . We sought to identify biomarker panels of optimal feature number, balancing the need for small panel size, accuracy of classification, goodness of class separation (case versus control) , and sufficient sensitivity and specificity. Figures 9-11 shows that all the panels having 100％sensitivity and 100％specificity.

Pathway analysis of biomarkers. We analyzed the validated biomarkers that are significantly differentially expressed in preterm birth as a composite, using PathVisio software (version 3.2.1, an open-source pathway analysis and drawing software) (Martijn et al. Presenting and exploring biological pathways with PathVisio. BMC Bioinformatics 2008； 9 (1) : 399) . In addition to the angiogenesis and focal adhesion pathway involved well-studied angiogenesis biomarker FLT1, our pathway analysis led to the identification of the following statistically significant canonical pathways which may play important roles in preterm birth pathophysiology: Activin A is a homodimeric protein that consists of 2 βA subunits. Activin A is a member of the transforming growth factor-β family and is related to inhibin A. It has pleotropic actions, including the stimulation of follicle-stimulating hormone release in the anterior pituitary, a role in neuronal health, and an effect on body axis development； it is produced in a variety of tissues, such as brain, pituitary gland, gonads, bone marrow, and placenta； evidence that supports an Activin A role in pregnancy results from both in vitro and clinical studies. All of these support our hypothesis that preterm birth is associated with increased shedding of placental debris leading to increased plasma levels of biomarker proteins, which could contribute to the inflammatory response, hormone imbalance, and endothelial dysfunction.

We have applied a multi- ‘omics’a pproach to develop validated PE and PTB biomarkers, integrating discoveries from placental mRNA expression meta-analysis and depleted serological proteome 2D gel comparative profiling. Comparing PE, PTB, and control sera with commercially available ELISA assays, we have validated 2 protein markers, including Activin A and Adam12. The concept of combining a transcriptomic approach in placenta tissue with a proteomic approach in serum is novel. It combines the advantages of a study in tissue which is closer to the focus of the pathophysiology with those of a study in serum which is more appropriate for clinical use. Taking proteins that have been discovered/predicted from the discovery phase to an ELISA-based validation phase makes the findings of this study translatable into clinical practice.

Example 2

The protein levels of a panel of preeclampsia markers (Activin A and Adam12) was statistically assessed to determine how to weigh the contribution of each polypeptide to a preeclampsia and preterm birth score for a sample based on this panel.

Using the random forest algorithm, of the two markers, Adam12 levels were determined to be least significant； and Activin A levels were determined to be most significant, i.e. about 11.6-fold more significant than Adam12.

The preceding merely illustrates the principles of the invention. It will be appreciated that those skilled in the art will be able to devise various arrangements which, although not explicitly described or shown herein, embody the principles of the invention and are included within its spirit and scope. Furthermore, all examples and conditional language recited herein are principally intended to aid the reader in understanding the principles of the invention and the concepts contributed by the inventors to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the invention as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents and equivalents developed in the future, i.e.， any elements developed that perform the same function, regardless of structure. The scope of the present invention, therefore, is not intended to be limited to the exemplary embodiments shown and described herein. Rather, the scope and spirit of the present invention is embodied by the appended claims.

Tables

Table 1. The microarray datasets of preeclampsia studied in present work.

Table 2. The microarray datasets of preterm birth studied in present work.

Table 3. Demographics of enrolled pregnant subjects. a. Fisher’s exact test； b. Kruskal-Wallis test.

Table 4. Clinical information of the enrolled case and control subjects. Clinical information was unavailable for one control subject. a. Kruskal-Wallis test； b. Chi-squared test.

Table 5. Univariate odds ratio analysis of the patient characteristics.

5A. PE and control patients； without adjustment of gestational age at blood sample collection.

5B. PE and control patients； with adjustment of gestational age at blood sample collection.

5C. PTB and control patients； without adjustment of gestational age at blood sample collection.

5D. PTB and control patients； with adjustment of gestational age at blood sample collection.

Table 6. Multivariate odds ratio analysis of the patient characteristics.

6A. PE and control patients； without adjustment of gestational age at blood sample collection.

6B. PE and control patients； with adjustment of gestational age at blood sample collection.

6C. PTB and control patients； without adjustment of gestational age at blood sample collection.

6D. PTB and control patients； with adjustment of gestational age at blood sample collection.

Table 7. Univariate hazard ratio analysis of the patient characteristics.

7A. PE and control patients； without adjustment of gestational age at blood sample collection.

7B. PE and control patients； with adjustment of gestational age at blood sample collection.

7C. PTB and control patients； without adjustment of gestational age at blood sample collection.

7D. PTB and control patients； with adjustment of gestational age at blood sample collection.

Table 8. Multivariate hazard ratio analysis of the patient characteristics.

8A. PE and control patients； without adjustment of gestational age at blood sample collection.

8B. PE and control patients； with adjustment of gestational age at blood sample collection.

8C. PTB and control patients； without adjustment of gestational age at blood sample collection.

8D. PTB and control patients； with adjustment of gestational age at blood sample collection.

Table 9. Levels of biomarker analyte (ng/ml) in pregnant individuals with preeclampsia outcome. Median IRQ and mean SD values are provided.

Table 10. Levels of biomarker analyte (ng/ml) in pregnant individuals with preterm birth outcome. Median IRQ and mean SD values are provided.

Table 11. Univariate odds ratio analysis of the validated markers.

11A. PE and control patients； without adjustment of gestational age at blood sample collection.

11B. PE and control patients； with adjustment of gestational age at blood sample collection.

11C. PTB and control patients； without adjustment of gestational age at blood sample collection.

11D. PTB and control patients； with adjustment of gestational age at blood sample collection.

Table 12. Multivariate odds ratio analysis of the validated markers.

12A. PE and control patients； without adjustment of gestational age at blood sample collection.

12B. PE and control patients； with adjustment of gestational age at blood sample collection.

12C. PTB and control patients； without adjustment of gestational age at blood sample collection.

12D. PTB and control patients； with adjustment of gestational age at blood sample collection.

Table 13. Univariate hazard ratio analysis of the validated markers.

13A. PE and control patients； without adjustment of gestational age at blood sample collection.

13B. PE and control patients； with adjustment of gestational age at blood sample collection.

13C. PTB and control patients； without adjustment of gestational age at blood sample collection.

13D. PTB and control patients； with adjustment of gestational age at blood sample collection.

Table 14. Multivariate hazard ratio analysis of the validated markers.

14A. PE and control patients； without adjustment of gestational age at blood sample collection.

14B. PE and control patients； with adjustment of gestational age at blood sample collection.

14C. PTB and control patients； without adjustment of gestational age at blood sample collection.

14D. PTB and control patients； with adjustment of gestational age at blood sample collection.

Claims

A method of providing a preeclampsia assessment and prognosing preterm birth for a specific subject, the method comprising:

developing and training a random forest model using clinical and laboratory test variables of randomly selected subjects, in order to derive a scoring metric to differentiate among a normal subject, a preeclampsia subject and a preterm birth subject；

evaluating a panel of markers from the specific subject to determine the level of each of the panel of markers；

and

feeding the level of each of the panel of markers into the random forest model to provide the preeclampsia assessment and prognose preterm birth,

wherein the panel of markers comprise inhibin beta A (Activin A) and at least one selected from a group consisting of ADAM metallopeptidase domain 12 (Adam12) , body mass index (BMI) and white blood cell count (WBC) .
The method of claim 1, wherein the plurality of clinical and laboratory test variables comprises at least two variables selected from a group consisting of systolic blood pressure, diastolic blood pressure, Activin A, gestational age, proteinuria, preeclampsia history, white blood cell count, preterm times, number of full-term pregnancy, dducation, ADAM12, multiple pregnancy, maternal height, maternal weight, BMI, abortion time, and age at blood collection.
The method of claim 2, wherein the plurality of clinical and laboratory test variables comprises inhibin beta A (Activin A) and at least one selected from a group consisting of ADAM metallopeptidase domain 12 (Adam12) , body mass index (BMI) and white blood cell count (WBC) .
The method of claim 1, wherein the panel of markers comprises no more than five markers for the subject.
The method of claim 1, wherein the panel of markers comprises no more than three markers for the subject.
The method according to claim 1, wherein the panel of markers consists of inhibin beta A (Activin A) and Adam12 (ADAM metallopeptidase domain 12) .
The method according to claim 1, wherein the panel of markers consists of inhibin beta A (Activin A) and body mass index (BMI) .
The method according to claim 1, wherein the panel of markers consists of inhibin beta A (Activin A) and white blood cell count (WBC) .
The method according to claim 1, further comprising providing a report of thepreeclampsia assessment and preterm birth prognose.
The method according to claim 1, wherein the preeclampsia assessment is preeclampsia diagnosis and the prognosing preterm birth is preterm birth prediction.
The method according to claim 1, wherein the specific subject has risk factors associated with preeclampsia or preterm birth.
The method according to claim 1, wherein the panel of markers is collected at 16-33 weeks of gestation.
The method according to claim 12, wherein the panel of markers is collected at 34 or more weeks of gestation.
The method of any one of claims 1-13 wherein the specific subject:

(a) has history of preeclampsia；

(b) is older than 40；

(c) has babies less than two years or more than 10 years apart；

(d) has obesity； or

(e) has history of certain conditions including chronic high blood pressure, migraine headaches, type 1 or type 2 diabetes, kidney disease, a tendency to develop blood clots, or lupus.
The method of any one of claims 1-13, wherein the specific subject:

(a) smokes or consumes alcohol；

(b) is younger than 17 or older than 35；

(c) has preterm birth history； or

(d) is stressed or unhealthy.
The method of any one of claims 1-13, further comprising administering to the subject identified as preeclampsia a procedure to ameliorate the preeclampsia.
The method of any one of claims 1-13, further comprising administering to the subject identified at risk of preterm birth a procedure to ameliorate the preterm birth.
The method of claim 16, wherien the procedure is selected from the group consisting of medications to lower blood pressure, use of corticosteroids, anticonvulsant medication such as magnesium sulfate, bed rest, and consideration of delivery if the diagnosis was made at or after 37 gestational weeks.
The method of claim 17, wherien the procedure is selected from the group consisting of administration of corticosteroid, magnesium sulfate, an antibiotic, or progestin, and cervical cerclage and combinations thereof.
A method of treating a pregnant woman as at preeclampsia or preterm birth, comprising:

(a) identifying whether the woman is at risk of preeclampsia or preterm birth；

(b) administering to the woman a procedure to ameliorate the preeclampsia or preterm birth when the woman is identified as preeclampsia or at risk of preterm birth；

wherein the identifying procedure comprises:

(i) developing and training a random forest model using clinical and laboratory test variables of randomly selected subjects, in order to derive a scoring metric to differentiate among a normal subject, a preeclampsia subject and a preterm birth subject；

(ii) evaluating a panel of markers from the women to determine the level of each of the panel of markers； and

(iii) feeding the level of each of the panel of markers into the random forest model to identify whether the woman is at risk of preeclampsia or preterm birth,

wherein the panel of markers comprise inhibin beta A (Activin A) and at least one selected from a group consisting of ADAM metallopeptidase domain 12 (Adam12) , body mass index (BMI) and white blood cell count (WBC) .
The method of claim 20, wherein the panel of markers comprises no more than five markers for the subject.
The method of claim 20, wherein the panel of markers comprises no more than three markers for the subject.
The method according to claim 20, wherein the panel of markers consists of inhibin beta A (Activin A) and Adam12 (ADAM metallopeptidase domain 12) .
The method according to claim 20, wherein the panel of markers consists of inhibin beta A (Activin A) and body mass index (BMI) .
The method according to claim 20, wherein the panel of markers consists of inhibin beta A (Activin A) and white blood cell count (WBC) .
The method of claim 20, wherein the procedure is selected from the group consisting of medications to lower blood pressure, use of corticosteroids, anticonvulsant medication such as magnesium sulfate, bed rest, and consideration of delivery if the diagnosis was made at or after 37 gestational weeks.
The method of claim 20, wherein the procedure is selected from the group consisting of administration of corticosteroid, magnesium sulfate, an antibiotic, or progestin, and cervical cerclage and combinations thereof.
The method of claim 20, wherein the panel of markers is collected at 16-33 weeks of gestation.
The method of claim 20, wherein the panel of markers is collected at 34 or more weeks of gestation.
A kit for making a preeclampsia diagnosis and preterm birth prediction, comprising:

(a) one or more detection elements for measuring the amount of marker in a sample for a panel of markers comprising inhibin beta A (Activin A) .
The kit of claim 30, further comprising (b) one or more detection elements for measuring the amount of ADAM metallopeptidase domain 12 (Adam12) in the sample.
The kit of claim 30, further comprising (c) one or more detection elements for measuring the white blood cell count (WBC) in the sample.
The kit of any one of claims 30 to 32, wherein the one or more detection elements are antibodies directed to any one or more of the markers, probe nucleic acids directed to genes encoding any one or more of the markers, or gene specific primers directed to a fragment of a gene encoding any one or more of the markers.
The kit of any one of claims 30 to 32, wherein the one or more detection elements comprising antibodies directed to no more than seven markers beside a control antibody.