Cell free DNA signaling as biomarker of preeclampsia

Abstract

The present invention includes a method and computer program for detecting preeclampsia and / or determining an elevated risk of preeclampsia in a pregnant woman, the method comprising identifying cell free DNA signals, including concentration, fetal fraction and fragment size distribution, in a biological sample obtained from a pregnant woman. These methods provide for identifying patients at risk of preeclampsia three months before pregnancy.

Description

[0001] Continuing application data

[0002] This application claims the benefit of U.S. Provisional Application Serial No. 63 / 446,404, filed on February 17, 2023, and U.S. Provisional Application Serial No. 63 / 552,234, filed on February 12, 2024, each of which is incorporated herein by reference. Technical Field

[0003] The present invention generally relates to methods and materials for the detection and early risk assessment of the pregnancy complication pre-eclampsia. Background Art

[0004] Preeclampsia is a condition that occurs only during pregnancy, affecting 5% to 8% of all pregnancies. It is the direct cause of 10% to 15% of maternal deaths and 40% of fetal deaths. The three main symptoms of preeclampsia can include high blood pressure, swelling of the hands and feet, and excess protein in the urine (proteinuria) that develop after the 20th week of pregnancy. Other signs and symptoms of preeclampsia can include severe headaches caused by fluid in the lungs, vision changes (including temporary loss of vision, blurred vision, or light sensitivity), nausea or vomiting, decreased urine output, low levels of platelets (thrombocytopenia), impaired liver function, and shortness of breath. See, e.g., Steegers et al., 2010, Lancet, 376:631-644. doi: 10.1016 / 80140-6736(10)60279-6; and Miller et al., 2008, Semin Perinatal; 32:274-280. doi: 10.1053 / j.semperi.2008.04.010.

[0005] The more severe the preeclampsia is and the earlier it occurs in pregnancy, the greater the risk to the mother and fetus. Preeclampsia may require induced labor or cesarean section delivery. If untreated, preeclampsia can lead to serious, even fatal complications for both the mother and the fetus. Complications of preeclampsia include fetal growth restriction, low birth weight, premature birth, placental abruption, HELLP syndrome (hemolysis, elevated liver enzymes, and low platelet count syndrome), eclampsia (a severe form of preeclampsia that causes seizures), organ damage (including kidney, liver, lung, heart, eye damage), stroke or other brain damage. See, for example, "Preeclampsia - Symptoms and causes - Mayo Clinic" on April 15, 2022, which is available on the World Wide Web at the link mayoclinic.org / diseases-conditions / preeclampsia / symptoms-causes / syc-20355745.

[0006] In terms of early detection and treatment, if preeclampsia is detected early and treated with routine prenatal care, most women can deliver healthy babies. Although various protein biomarkers show changes in maternal serum levels in the presymptomatic stage, these biomarkers lack discriminatory and predictive power in individual patients (Karumanchi and Granger, 2016, Hypertension; 67(2): 238-242). Therefore, the identification of biomarkers for early detection of preeclampsia is crucial for the early diagnosis and treatment of preeclampsia. Summary of the invention

[0007] In one aspect, the present disclosure describes a method of detecting pre-eclampsia and / or determining an increased risk of pre-eclampsia in a pregnant female subject, the method comprising:

[0008] Providing cell-free DNA (cfDNA) sequence information obtained from a biological sample obtained from a pregnant female subject; and

[0009] From cfDNA sequence information:

[0010] Determine cell-free DNA (cfDNA) concentration;

[0011] Determine the fetal fraction within the cfDNA; and / or

[0012] Determine the fragment size distribution within cfDNA;

[0013] in:

[0014] Higher cfDNA concentrations relative to normal controls;

[0015] A lower fetal fraction in cfDNA relative to normal controls;

[0016] Higher fragment size distribution relative to normal controls; and / or

[0017] The ratio of fetal fraction to fragment size distribution is less than that in normal controls

[0018] Indicated for pre-eclampsia and / or increased risk of pre-eclampsia in pregnant females.

[0019] In some aspects of the methods disclosed herein, the cfDNA sequence information is obtained from a sequencing-based non-invasive prenatal testing (NIPT) test.

[0020] In one aspect, the present disclosure describes a method of detecting pre-eclampsia and / or determining an increased risk of pre-eclampsia in a pregnant female subject, the method comprising:

[0021] removing intact cells from biological samples obtained from pregnant females;

[0022] Isolation of cell-free DNA (cfDNA) molecules from biological samples;

[0023] Sequencing the enriched cfDNA to obtain cfDNA sequence information; and

[0024] From cfDNA sequence information:

[0025] Determine cell-free DNA (cfDNA) concentration;

[0026] Determine the fetal fraction within the cfDNA; and / or

[0027] Determine the fragment size distribution within cfDNA;

[0028] in:

[0029] Higher cfDNA concentrations relative to normal controls;

[0030] A lower fetal fraction in cfDNA relative to normal controls;

[0031] Higher fragment size distribution relative to normal controls; and / or

[0032] The ratio of fetal fraction to fragment size distribution is less than that in normal controls

[0033] Indicated for pre-eclampsia and / or increased risk of pre-eclampsia in pregnant females.

[0034] In some aspects of the methods disclosed herein, the method comprises:

[0035] Determining the fetal fraction within the cfDNA; and

[0036] Determine the fragment size distribution within cfDNA;

[0037] in:

[0038] A lower fetal fraction in cfDNA relative to normal controls; and

[0039] higher fragment size distribution relative to normal controls;

[0040] Indicated for pre-eclampsia and / or increased risk of pre-eclampsia in pregnant females.

[0041] In some aspects of the methods disclosed herein, the method comprises:

[0042] Determine cell-free DNA (cfDNA) concentration;

[0043] Determining the fetal fraction within the cfDNA; and

[0044] Determine the fragment size distribution within cfDNA;

[0045] in:

[0046] Higher cfDNA concentrations relative to normal controls;

[0047] A lower fetal fraction in cfDNA relative to normal controls; and

[0048] higher fragment size distribution relative to normal controls;

[0049] Indicated for pre-eclampsia and / or increased risk of pre-eclampsia in pregnant females.

[0050] In one aspect, the present disclosure describes a method comprising:

[0051] a) Access sequence reads from cfDNA and determine:

[0052] i) cfDNA concentration;

[0053] ii) fetal fraction within cfDNA;

[0054] iii) fragment size distribution within cfDNA; and / or

[0055] iv) parameters including fetal fraction and fragment size distribution;

[0056] b) Comparison

[0057] i) cfDNA concentration and a first threshold amount;

[0058] ii) fetal fraction and a second threshold amount;

[0059] iii) fragment size distribution and a third threshold amount; and / or

[0060] iv) parameters including fetal fraction and fragment size distribution and a fourth threshold amount;

[0061] wherein the first threshold amount, the second threshold amount, the third threshold amount, and the fourth threshold amount are determined based on a plurality of normal samples;

[0062] c) determining that a pregnant female subject has pre-eclampsia and / or is at increased risk for pre-eclampsia, wherein

[0063] i) the cfDNA concentration is above a first threshold amount;

[0064] ii) the fetal fraction is less than a second threshold amount;

[0065] iii) the fragment size distribution is above a third threshold amount; and / or

[0066] iv) parameters including fetal fraction and fragment size distribution are less than a fourth threshold amount;

[0067] Indicated for pre-eclampsia and / or increased risk of pre-eclampsia in pregnant females.

[0068] In some aspects of the methods disclosed herein, the biological sample is obtained from a pregnant female at less than 16 weeks gestation.

[0069] In some aspects of the methods disclosed herein, the biological sample is obtained from a pregnant female subject at a gestational period of about 11 weeks to about 14.2 weeks.

[0070] In some aspects of the methods disclosed herein, the biological sample is obtained from a pregnant female at a gestational age greater than 20 weeks.

[0071] In some aspects of the methods disclosed herein, the biological sample is obtained from a pregnant female subject at a gestational period of about 17.6 weeks to about 25.5 weeks.

[0072] In some aspects of the methods disclosed herein, detecting pre-eclampsia and / or determining an increased risk of pre-eclampsia comprises detecting early-onset pre-eclampsia and / or determining an increased risk of early-onset pre-eclampsia.

[0073] In some aspects of the methods disclosed herein, detecting pre-eclampsia and / or determining an increased risk of pre-eclampsia comprises detecting late-onset pre-eclampsia and / or determining an increased risk of late-onset pre-eclampsia.

[0074] In some aspects of the methods disclosed herein, the biological sample comprises whole blood, serum, or plasma.

[0075] In some aspects of the methods disclosed herein, the method further comprises providing the pregnant female with a therapeutic intervention selected from the group consisting of increasing the frequency of prenatal visits, antihypertensive medications to lower blood pressure, corticosteroid medications, anticonvulsant medications, bed rest, hospitalization, early delivery, and combinations thereof, and / or treating the pregnant female with low-dose aspirin, wherein the low-dose aspirin comprises about 50 mg to about 150 mg per day.

[0076] In one aspect, the present disclosure describes a system comprising one or more microprocessors and a memory, the memory comprising instructions executable by the one or more microprocessors, and the memory comprising sequence reads mapped to a reference genome, wherein the sequence reads are reads of cfDNA from a test sample from a pregnant female subject, and wherein the instructions executable by the one or more microprocessors are configured to perform the methods described herein.

[0077] In one aspect, the present disclosure describes a machine comprising one or more microprocessors and a memory, the memory comprising instructions executable by the one or more microprocessors, and the memory comprising sequence reads mapped to a reference genome, wherein the sequence reads are reads of cfDNA from a test sample from a pregnant female subject, and wherein the instructions executable by the one or more microprocessors are configured to perform the methods described herein.

[0078] In one aspect, the present disclosure describes a non-transitory computer-readable storage medium on which an executable program is stored, wherein the program instructs a microprocessor to access sequence reads mapped to a reference genome and to perform the methods described herein.

[0079] As used herein, the term "nucleic acid" is intended to be consistent with its use in the art, and includes naturally occurring nucleic acids or functional analogs thereof. Particularly useful functional analogs can hybridize with nucleic acids in a sequence-specific manner or can be used as a template for replicating a specific nucleotide sequence. Naturally occurring nucleic acids generally have a backbone comprising a phosphodiester bond. Similar structures may have alternative backbone bonds, including any of a variety of backbone bonds known in the art. Naturally occurring nucleic acids generally have deoxyribose (e.g., present in deoxyribonucleic acid (DNA)) or ribose (e.g., present in ribonucleic acid (RNA)). Nucleic acids may include any of a variety of analogs of these sugar moieties known in the art. Nucleic acids may include natural or non-natural bases. In this regard, natural deoxyribonucleic acids may have one or more bases selected from the group consisting of adenine, thymine, cytosine or guanine, and ribonucleic acids may have one or more bases selected from the group consisting of uracil, adenine, cytosine or guanine. Useful non-natural bases that may be included in nucleic acids are known in the art. The terms "template" and "target" when used in reference to nucleic acids are intended as semantic identifiers of nucleic acids in the context of the methods or compositions described herein, and do not necessarily limit the structure or function of the nucleic acids, unless otherwise expressly indicated.

[0080] As used herein, "amplification" or "amplification reaction" and its derivatives generally refer to any action or process in which at least a portion of a nucleic acid molecule is replicated or copied to at least one other nucleic acid molecule. The other nucleic acid molecules optionally contain sequences that are substantially identical or substantially complementary to at least some portions of the target nucleic acid molecule. The target nucleic acid molecule may be single-stranded or double-stranded, and the other nucleic acid molecules may independently be single-stranded or double-stranded. Amplification optionally includes linear or exponential replication of nucleic acid molecules. In some embodiments, such amplification can be performed using isothermal conditions; in other embodiments, such amplification may include thermal cycling. In some embodiments, amplification is multiplex amplification, which includes simultaneously amplifying multiple target sequences in a single amplification reaction. In some embodiments, "amplification" includes amplifying at least some portions of DNA- and RNA-based nucleic acids, either alone or in combination. The amplification reaction may include any amplification process known to those of ordinary skill in the art. In some embodiments, the amplification reaction includes polymerase chain reaction (PCR).

[0081] As used herein, "amplification conditions" and its derivatives generally refer to conditions suitable for amplifying one or more nucleic acid sequences. Such amplification can be linear or exponential. In some embodiments, the amplification conditions may include isothermal conditions, or alternatively may include thermal cycling conditions, or a combination of isothermal conditions and thermal cycling conditions. In some embodiments, conditions suitable for amplifying one or more nucleic acid sequences include polymerase chain reaction (PCR) conditions. Generally, amplification conditions refer to a reaction mixture sufficient to amplify nucleic acids (e.g., one or more target sequences) or to amplify target sequences connected to one or more adapters (e.g., adapter-connected amplified target sequences). Generally speaking, amplification conditions include a catalyst for amplification or for nucleic acid synthesis, such as a polymerase; a primer having a certain degree of complementarity with the nucleic acid to be amplified; and nucleotides, such as deoxyribonucleotide triphosphates (dNTPs), thereby promoting the extension of the primer once hybridized with the nucleic acid. Amplification conditions may require hybridization or annealing of primers to nucleic acids, extension of primers, and a denaturation step in which the extended primers are separated from the nucleic acid sequence undergoing amplification. Typically, but not necessarily, amplification conditions may include thermal cycling; in some embodiments, amplification conditions include multiple cycles in which the steps of annealing, extension, and separation are repeated. Typically, amplification conditions include cations such as Mg ++ or Mn ++ , and may also include various ionic strength modifiers.

[0082] As used herein, the term "polymerase chain reaction" ("PCR") refers to the method of U.S. Pat. Nos. 4,683,195 and 4,683,202, which describes a method for increasing the concentration of a segment of a polynucleotide of interest in a mixture of genomic DNA without cloning or purification. The method of amplifying the polynucleotide of interest includes introducing a large excess of two oligonucleotide primers into a DNA mixture containing the desired polynucleotide of interest, and then performing a series of thermal cycles in the presence of a DNA polymerase. The two primers are complementary to the strands of their corresponding double-stranded polynucleotides of interest. The mixture is first denatured at a higher temperature, and then the primers are annealed to the complementary sequences within the polynucleotide molecule of interest. After annealing, the primers are extended with a polymerase to form a pair of new complementary chains. The steps of denaturation, primer annealing, and polymerase extension can be repeated multiple times (referred to as thermal cycling) to obtain a high concentration of amplified fragments of the desired polynucleotide of interest. The length of the amplified fragment of the desired polynucleotide of interest (amplicon) is determined by the relative positions of the primers relative to each other, and therefore, the length is a controllable parameter. Because the process is repeated, the method is referred to as a "polymerase chain reaction" (hereinafter "PCR"). Because the desired amplified segments of the polynucleotide of interest become the predominant nucleic acid sequences (in terms of concentration) in the mixture, they are considered "PCR amplified." In a modified form of the above method, multiple different primer pairs (in some cases, one or more primer pairs per target nucleic acid molecule of interest) can be used to PCR amplify the target nucleic acid molecules, thereby forming a multiplex PCR reaction.

[0083] As used herein, the term "primer" and its derivatives generally refer to any polynucleotide that can hybridize with a target sequence of interest. Typically, a primer is used as a substrate to which nucleotides can be polymerized by a polymerase; however, in some embodiments, a primer can be incorporated into a synthetic nucleic acid chain and provide a site to which another primer can hybridize to initiate the synthesis of a new chain complementary to the synthetic nucleic acid molecule. A primer may include any combination of nucleotides or their analogs. In some embodiments, a primer is a single-stranded oligonucleotide or polynucleotide. The terms "polynucleotide" and "oligonucleotide" are used interchangeably herein to refer to a polymeric form of nucleotides of any length, and may include ribonucleotides, deoxyribonucleotides, their analogs, or mixtures thereof. These terms should be understood to include analogs of DNA or RNA made from nucleotide analogs as equivalents, and are applicable to single-stranded (such as sense or antisense) and double-stranded polynucleotides. As used herein, the term also encompasses cDNA, i.e., complementary DNA or copy DNA produced by an RNA template, for example, by the action of a reverse transcriptase. The term refers only to the primary structure of the molecule. Thus, the term includes triple-, double-, and single-stranded deoxyribonucleic acid ("DNA"), and triple-, double-, and single-stranded ribonucleic acid ("RNA").

[0084] As used herein, the terms "library" and "sequencing library" refer to a collection of template molecules or a plurality of template molecules that share a common sequence at their 5' end and a common sequence at their 3' end. A collection of template molecules containing a known common sequence at their 3' end and 5' end may also be referred to as a 3' and 5' modified library.

[0085] As used herein, the term "flow cell" refers to a chamber comprising a solid surface through which one or more fluid reagents can flow. Examples of flow cells and associated fluid systems and detection platforms that can be easily used in the methods of the present disclosure are described in, for example, Bentley et al., Nature 456:53-59 (2008); WO 04 / 018497; US 7,057,026; WO 91 / 06678; WO 07 / 123744; US 7,329,492; US 7,211,414; US 7,315,019; US 7,405,281 and US 2008 / 0108082.

[0086] As used herein, the term "array" refers to a group of sites that can be distinguished from each other based on relative position. Different molecules located at different sites of the array can be distinguished from each other based on the position of the site in the array. A single site of an array may contain one or more specific types of molecules. For example, a site may contain a single target nucleic acid molecule with a specific sequence, or a site may contain several nucleic acid molecules with the same sequence (and / or its complementary sequence). The sites of an array may be different features located on the same substrate. Exemplary features include, but are not limited to, holes in a substrate, beads (or other particles) in or on a substrate, protrusions of a substrate, ridges on a substrate, or channels in a substrate. The sites of an array may be separate substrates each with different molecules. Different molecules attached to separate substrates may be identified based on the position of the substrate on a surface associated with the substrate, or based on the position of the substrate in a liquid or gel. Exemplary arrays in which separate substrates are located on a surface include, but are not limited to, those arrays with beads in holes.

[0087] The term "next generation sequencing (NGS)" herein refers to sequencing methods that allow for massively parallel sequencing of clonally amplified molecules and single nucleic acid molecules. Non-limiting examples of NGS include sequencing by ligation and sequencing by synthesis using reversible dye terminators.

[0088] The term "sensitivity" as used herein is equal to the number of true positives divided by the sum of true positives and false negatives.

[0089] The term "specificity" as used herein is equal to the number of true negatives divided by the sum of true negatives and false positives.

[0090] The term "enrichment" herein refers to the process of amplifying nucleic acids contained in a portion of a sample. Enrichment includes specific enrichment targeting a specific sequence (eg, a polymorphic sequence), and non-specific enrichment of the whole genome of amplified sample DNA fragments.

[0091] As used herein, the term "maternal sample" refers to a biological sample obtained from a pregnant subject (eg, a female).

[0092] The term "biological fluid" herein refers to a liquid taken from a biological source, and includes, for example, blood, serum, plasma, sputum, lavage fluid, cerebrospinal fluid, urine, semen, sweat, tears, saliva, etc. As used herein, the terms "blood", "plasma" and "serum" explicitly encompass fractions or processed portions thereof. Similarly, in the case where the sample is taken from a biopsy, swab, smear, etc., the "sample" explicitly encompasses processed fractions or portions derived from a biopsy, swab, smear, etc.

[0093] As used herein, the terms "maternal nucleic acid" and "fetal nucleic acid" refer to nucleic acid from a pregnant female subject and nucleic acid from a fetus carried by the pregnant female subject, respectively.

[0094] As used herein, the term "fetal fraction" refers to the fraction of fetal nucleic acid present in a sample comprising fetal and maternal nucleic acid. Fetal fraction is often used to characterize cfDNA in maternal blood.

[0095] As used herein, the terms "each," when used in reference to a collection of reference items, are intended to identify an individual item in the collection, but not necessarily every item in the collection unless the context clearly indicates otherwise.

[0096] As used herein, "providing" in the context of a composition, preparation, nucleic acid, or cell nucleus means preparing the composition, preparation, nucleic acid, or cell nucleus, purchasing the composition, preparation, nucleic acid, or cell nucleus, or otherwise obtaining the compound, composition, preparation, or cell nucleus.

[0097] The term "and / or" means one or all of the listed elements, or a combination of any two or more of the listed elements. The words "preferred" and "preferably" refer to embodiments of the present disclosure that may provide certain benefits in certain circumstances. However, other embodiments may also be preferred under the same or other circumstances. In addition, the recitation of one or more preferred embodiments does not mean that other embodiments are not useful, nor is it intended to exclude other embodiments from the scope of the present disclosure.

[0098] The terms "include" and variations thereof do not have a limiting meaning where these terms appear in the description and claims.

[0099] It should be understood that anywhere an embodiment is described herein with the language "comprising," "including," or "containing," etc., other similar embodiments described with "consisting of" and / or "consisting essentially of" are also provided.

[0100] Unless otherwise specified, "a," "an," "the," and "at least one" are used interchangeably to mean one or more than one.

[0101] Also herein, the recitations of numerical ranges by endpoints include all numbers subsumed within that range (eg, 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.80, 4, 5, etc.).

[0102] References throughout this specification to "one embodiment," "embodiment," "certain embodiments," or "some embodiments" and the like mean that a particular feature, configuration, composition, or characteristic described in conjunction with the embodiment is included in at least one embodiment of the present disclosure. Therefore, multiple appearances of such phrases throughout this specification do not necessarily refer to the same embodiment of the present disclosure. Furthermore, in one or more embodiments, the particular features, configurations, compositions, or characteristics may be combined in any suitable manner.

[0103] For any method disclosed herein that includes discrete steps, the steps may be performed in any feasible order. Also, any combination of two or more steps may be performed simultaneously, as appropriate.

[0104] The above summary of the invention of the present disclosure is not intended to describe each disclosed embodiment or each specific implementation of the present disclosure. The following description more specifically illustrates exemplary embodiments. In several places throughout the application, guidance is provided by lists of examples, which can be used in various combinations. In each case, the cited lists are used only as representative groups and should not be interpreted as exclusive lists. BRIEF DESCRIPTION OF THE DRAWINGS

[0105] Figures 1A to 1D At time point A, the cfDNA signal was used to distinguish between late PE, early PE, and control samples. The concentration at time point A was used to distinguish between the three patient groups ( Figure 1A ); The fragment size distribution at time point A was used to distinguish the three patient groups ( Figure 1B ); The fetal fraction at time point A was used to distinguish the three patient groups ( Figure 1C ); Linear regression curves show the use of fetal fraction and fragment size distribution to distinguish PE samples from control samples at time point A ( Figure 1D ). Asterisks (*) indicate significant differences between a specific PE group and the control group.

[0106] Figures 2A-2DAt time point B, the cfDNA signal was used to distinguish between late PE, early PE, and control samples. The concentration at time point B was used to distinguish between the three patient groups ( Figure 2A ); The fragment size distribution at time point B was used to distinguish the three patient groups ( Figure 2B ); fetal fraction at time point B was used to distinguish the three patient groups ( Figure 2C ); Linear regression curve plot shows the use of fetal fraction and fragment size distribution to distinguish PE samples from control samples at time point B ( Figure 2D ). Asterisks (*) indicate significant differences between a specific PE group and the control group.

[0107] Figure 3A and Figure 3B . Figure 3A is a plot of fetal fraction at time point A versus fragment size distribution versus concentration. Figure 3B is a plot of fetal fraction versus fragment size distribution versus concentration at time point B.

[0108] Figure 4 . Figure 4 is a linear regression curve graph showing the use of fetal fraction and fragment size distribution to distinguish PE samples from control samples at time point A. PE samples are represented by squares. Control samples are represented by squares.

[0109] Figure 5 . Figure 5 is a graph of probability versus outcome.

[0110] The schematic diagrams are not necessarily drawn to scale. Like reference numerals used in the drawings may refer to similar components. However, it should be understood that the use of numbers to refer to components in a given figure is not intended to limit the components labeled with the same number in another figure. In addition, the use of different numbers to refer to components is not intended to indicate that the differently numbered components cannot be the same or similar to the other numbered components. DETAILED DESCRIPTION

[0111] The present disclosure determines that cell-free DNA (cfDNA) can be used as an efficient biomarker for identifying patients at risk of developing preeclampsia (PE). Using a logistic regression model, three cfDNA signals, concentration, fetal fraction, and fragment size distribution, are associated with clinical outcomes. For example, at time point A (about 11 to about 14.2 weeks of gestation), significant differences in all three cfDNA signals were observed between PE patients and control cases, while at time point B (about 17.6 to about 25.5 weeks of gestation), both fetal fraction and concentration were significantly different between PE patients and control cases. Overall, at time point A, the model had a sensitivity of up to 100% and a specificity of up to 87.5%. The use of this logistic regression model can identify patients at risk in the first three months of pregnancy.

[0112] The present disclosure includes methods for detecting pre-eclampsia and / or determining an increased risk of pre-eclampsia in a pregnant female subject, the methods comprising providing cfDNA sequence information obtained from a biological sample obtained from the pregnant female subject, and determining the cfDNA concentration, determining the fetal fraction within the cfDNA, and / or determining a fragment size distribution from the cfDNA sequence information.

[0113] By the methods disclosed herein, a higher cfDNA concentration relative to a normal control, a lower fetal fraction within cfDNA relative to a normal control, a higher fragment size distribution relative to a normal control, and / or a ratio of fetal fraction to fragment size distribution that is less than this ratio in a normal control indicates pre-eclampsia and / or an increased risk of pre-eclampsia in a pregnant female.

[0114] In some embodiments, two of these three cfDNA signals can be measured, and can indicate that the risk of pre-eclampsia and / or pre-eclampsia in pregnant women is increased. For example, cfDNA concentration and fetal fraction can be determined, wherein the higher cfDNA concentration relative to the normal control and the lower cfDNA relative to the normal control indicate that the risk of pre-eclampsia and / or pre-eclampsia in pregnant women is increased. In some embodiments, cfDNA concentration and fragment size distribution can be determined, wherein the higher cfDNA concentration relative to the normal control and the higher fragment size distribution relative to the normal control indicate that the risk of pre-eclampsia and / or pre-eclampsia in pregnant women is increased. Alternatively, fetal fraction and fragment size distribution can be determined, wherein the lower fetal fraction relative to the cfDNA of the normal control and the higher fragment size distribution relative to the normal control indicate that the risk of pre-eclampsia and / or pre-eclampsia in pregnant women is increased.

[0115] In some embodiments, two of the three cfDNA signals can be determined and can indicate an increased risk of pre-eclampsia and / or pre-eclampsia in a pregnant female. For example, the cfDNA concentration, fetal fraction, and fragment size distribution are determined, wherein a higher cfDNA concentration relative to a normal control, a lower fetal fraction within the cfDNA relative to a normal control, and a higher fragment size distribution relative to a normal control indicate an increased risk of pre-eclampsia and / or pre-eclampsia in a pregnant female.

[0116] In some embodiments, the ratio of two of the three cfDNA signals can indicate an increased risk of pre-eclampsia and / or pre-eclampsia in a pregnant woman. For example, a ratio of a fetal fraction to a fragment size distribution that is less than the ratio in a normal control indicates an increased risk of pre-eclampsia and / or pre-eclampsia in a pregnant woman. In another embodiment, relative to the ratio in a normal control, the ratio of cfDNA concentration to fetal fraction can indicate an increased risk of pre-eclampsia and / or pre-eclampsia in a pregnant woman. In another embodiment, relative to the ratio in a normal control, the ratio of cfDNA concentration to fragment size distribution can indicate an increased risk of pre-eclampsia and / or pre-eclampsia in a pregnant woman.

[0117] The concentration of cell-free DNA (cfDNA) of fetal origin circulating in maternal plasma is called the fetal fraction (FF). The fetal fraction concentration is the percentage of total cell-free DNA (cfDNA) in a sample that originates from the fetus.

[0118] In some implementations, the one or more fetal fraction values ​​include a fetal fraction value calculated using information about cell-free nucleic acid fragment sizes. In some implementations, the fetal fraction value is calculated by obtaining a frequency distribution of fragment sizes; and applying the frequency distribution to a model that relates fetal fraction to the frequency of fragment sizes to obtain a fetal fraction value. In some implementations, the model that relates fetal fraction to the frequency of fragment sizes includes a general linear model with multiple terms and coefficients for multiple fragment sizes.

[0119] In some implementations, the one or more fetal score values ​​include a fetal score value calculated using coverage information of a bin of a reference genome. In some implementations, the fetal score value is calculated by applying the coverage values ​​of multiple bins to a model that relates the fetal score to the coverage of the bin to obtain a fetal score value. In some implementations, the model that relates the fetal score to the coverage of the bin includes a general linear model with multiple terms and coefficients for multiple bins. In some implementations, the multiple bins have a high correlation between the fetal score and the coverage in the training sample. An example of this method is described in U.S. Patent No. 10,622,094, the contents of which are incorporated herein by reference in their entirety.

[0120] In some implementations, the one or more fetal fraction values ​​include a fetal fraction value calculated using the frequencies of a plurality of 8-mers found in the read. In some implementations, the fetal fraction value is calculated by applying the frequencies of the plurality of 8-mers to a model that relates fetal fraction to the frequencies of the 8-mers to obtain a fetal fraction value. In some implementations, the model that relates fetal fraction to the frequencies of the 8-mers includes a general linear model with a plurality of terms and coefficients for the plurality of 8-mers. In some implementations, the plurality of 8-mers have a high correlation between the fetal fraction and the frequencies of the 8-mers.

[0121] In some implementations, the one or more fetal fraction values ​​include a fetal fraction value calculated using coverage information for bins of sex chromosomes.

[0122] In certain embodiments, the genotype is determined based on markers that are specific to the male fetus (e.g., Y-chromosome STR markers (e.g., DYS 19, DYS 385, DYS 392 markers); RhD markers for RhD-negative females), allele ratios of polymorphic sequences, or based on one or more markers that are specific to fetal nucleic acid but not maternal nucleic acid (e.g., differential epigenetic biomarkers between mother and fetus (e.g., methylation; described in further detail below) or fetal RNA markers in maternal plasma).

[0123] Determination of fetal nucleic acid content (e.g., fetal fraction) is sometimes performed using fetal quantitative analysis (FQA). This type of assay allows for the detection and quantification of fetal nucleic acid in a maternal sample based on the methylation status of the nucleic acid in the sample. In certain embodiments, the amount of fetal nucleic acid from a maternal sample can be determined relative to the total amount of nucleic acid present, thereby providing a percentage of fetal nucleic acid in the sample. Methods for distinguishing nucleic acids based on methylation status include, but are not limited to, methylation-sensitive capture, such as using an MBD2-Fc fragment in which the methyl-binding domain of MBD2 is fused to the Fc fragment of an antibody (MBD-FC); methylation-specific antibodies; bisulfite conversion methods, such as MSP (methylation-sensitive PCR), COBRA, methylation-sensitive single nucleotide primer extension (Ms-SNuPE), or Sequenom MassCLEAVE ™ Techniques; and the use of methylation-sensitive restriction enzymes (e.g., using one or more methylation-sensitive restriction enzymes to digest maternal DNA in a maternal sample to enrich for fetal DNA). Methyl-sensitive enzymes can also be used to distinguish nucleic acids based on methylation status, such as preferentially or substantially cleaving or digesting at their DNA recognition sequences when they are unmethylated. Thus, unmethylated DNA samples will be cut into smaller fragments than methylated DNA samples, while highly methylated DNA samples will not be cleaved.

[0124] In certain embodiments, the fetal fraction can be determined based on the allele ratio of a polymorphic sequence (e.g., a single nucleotide polymorphism (SNP)). In such methods, nucleotide sequence reads are obtained for a maternal sample, and the fetal fraction is determined by comparing the total number of nucleotide sequence reads mapped to the first allele at an informative polymorphic site (e.g., SNP) in a reference genome with the total number of nucleotide sequence reads mapped to the second allele. In certain embodiments, fetal alleles are identified by, for example, the relatively small contribution of the fetal allele to the mixture compared to the larger contribution of the maternal nucleic acid to the mixture in a mixture of fetal and maternal nucleic acids in the sample. Therefore, for each of the two alleles of the polymorphic site, the relative abundance of fetal nucleic acid in the maternal sample can be determined as a parameter of the total number of unique sequence reads mapped to the target nucleic acid sequence on the reference genome.

[0125] The distribution of fragments of different sizes in a sample of cfDNA can be measured and compared with the fragment size distribution of a reference sample. One way to measure the fragment size distribution is to use a cumulative distribution function. Any of many methods known to those skilled in the art can be used to compare the fragment size distribution of a test sample with a reference (or desired) distribution. In some embodiments, the Kolmogorov- Smirnov test (KS test) can be applied to compare the sample distribution with a reference probability distribution. In some embodiments, autocorrelation can be applied to compare the sample distribution with a reference probability distribution. In some embodiments, cross-correlation can be applied to compare the sample distribution with a reference probability distribution. For example, in the embodiments presented herein, "frag_size_dist" is a metric generated during the analysis of cfDNA and is defined as the standard deviation of the difference between the actual and desired cumulative fragment size distributions.

[0126] A suitable control may be a normal control, for example, a sample from a healthy, gestational age-matched pregnant female. In some embodiments, the results of the appropriate controls have been previously obtained and recorded and stored as historical results, for example, on an electronic storage medium.

[0127] Although most of the DNA and RNA in the body is located inside cells, extracellular nucleic acids may also be found circulating freely in the blood. Cell-free DNA (cfDNA) refers to DNA in the bloodstream that is not packaged. Cell-free DNA is short fragments of DNA that are released into the bloodstream through the natural process of cell death. It was first discovered by Mandel and Metais in 1948 (Mandel and Metais, 1948, CR Seances Soc Biol Fil; 142:241-243). cfDNA can be found in plasma and other body fluids.

[0128] Previous studies have indicated that most plasma cfDNA molecules originate from the hematopoietic system of healthy individuals (Lui et al., 2002, Clin Chem; 48:421-427; and Sun et al., 2015, Proc Natl Acad Sci USA; 112:E5503-E5512). However, under certain physiological or pathological conditions, such as pregnancy, organ transplantation, and cancer, the relevant / affected tissues release additional DNA into the peripheral circulation (Leon et al., 1977, Cancer Res; 37:646-650; Lo et al., 1997, Lancet; 350:485-487; and Lo et al., 1998, Lancet; 351: 1329-1330).

[0129] In recent years, a variety of technologies based on cfDNA analysis have emerged for non-invasive prenatal testing (NIPT) (Lo et al., 1997, Lancet; 350:485-487; Lo et al., 2007, Proc Natl Acad Sci USA; 104:13116-13121; Hyett et al., 2005, Prenat Diagn; 25: 1111-1116; Wong and Lo, 2015, Trends Mol Med; 21:98-108; Hudecova and Chiu, 2017, Best Pract Res Clin Obstet Gynaecol; 39:63-73; Bianchi and Chiu, 2018, N Engl J Med; 379:464-473; Malan et al., 2018, JAMA; 320:557-565; Vivanti et al., 2019, Ultrasound Obstet Gynecol; 53:87-94; and Zhang J. et al., 2019, Nat Med; 25:439-447), for monitoring organ transplantation (Lo et al., 1998, Lancet; 351:1329-1330; Gielis et al., 2015, Am J Transplant; 15:2541-2551; Gala-Lopez et al., 2018, Transplantation; 102:978-985; and Sherwood and Weimer, 2018), and for detecting immune diseases (Zhang et al., 2014; Beranek et al., 2017, Arch Dermatol Res; 309:815-821; Dunaeva et al., 2018, Mol Neurobiol; 55:4681-4688; Xu et al., 2018, Eur J Clin Invest; 48:el3015; and Duvvuri and Lood, 2019, Front Immunol; 10:502) and cancer.

[0130] During pregnancy, the mother's blood contains cell-free DNA (cfDNA), both from her own tissues and from the fetus via the placenta. Approximately 2%-20% of the total cfDNA in maternal blood is placental (Barrett et al., 2011, PLoS One; 6(10):e25202; and Nigam et al., 2012, J Interntl Med Sci Acad; 25(3): 119-120).

[0131] In recent years, prenatal testing has been moving toward non-invasive methods to determine the risk of fetal genetic diseases. In October 2011, non-invasive prenatal testing (NIPT) for fetal chromosomal abnormalities using cfDNA in maternal circulation became clinically available in the United States. Cell-free fetal DNA present in maternal plasma is now used to identify a series of fetal chromosomal aneuploidies, such as, for example, trisomy 21, trisomy 13, and trisomy 18, determine the sex of the fetus, and identify various gene mutations, such as, for example, Tay-Sachs disease, sickle cell anemia, thalassemia, cystic fibrosis, muscular dystrophy, and fragile X syndrome, by using cell-free DNA in maternal circulation for fetal chromosomal abnormalities. Non-invasive prenatal testing can be used for screening purposes or for diagnostic purposes.

[0132] The detection, quantification and / or characterization of cfDNA in maternal circulation associated with the diagnosis of pre-eclampsia or the risk of developing pre-eclampsia of the methods described herein can involve any of a variety of techniques, including but not limited to any of a variety of high-throughput sequencing techniques. For example, the method for determining cfDNA includes but is not limited to the method described herein or the method used in the examples provided herein.

[0133] In some embodiments, the detection, quantification and / or characterization of cfDNA in the maternal circulation associated with the diagnosis of pre-eclampsia or the risk of developing pre-eclampsia of the method can be performed as part of the NIPT aneuploidy screening of maternal samples. The detection, quantification and / or characterization of cfDNA in the maternal circulation associated with the diagnosis of pre-eclampsia or the risk of developing pre-eclampsia can be performed before, at the same time or after, for example, such NIPT analysis is performed. In certain embodiments presented here, the detection of pre-eclampsia or the risk of developing pre-eclampsia utilizes certain metrics obtained during NIPT analysis. For example, some metrics that can be determined in NIPT analysis include total cfDNA concentration, fragment size, fragment size distribution and fetal fraction. Since maternal plasma samples represent a mixture of maternal and fetal cfDNA, the success of any given NIPT method depends on its sensitivity to detecting copy number variation in low fetal fraction samples. For counting-based methods, their sensitivity depends on the ability of (a) sequencing depth and (b) data normalization to reduce technical differences. Analytical methods for NIPT and other applications can include inferring fragment size information from, for example, paired-end reads and using this information in the analytical pipeline. The improved analytical sensitivity provides the ability to apply NIPT methods at reduced coverage (e.g., reduced sequencing depth), which enables the technology to be used for low-cost testing of average-risk pregnancies.

[0134] A typical NIPT analysis pipeline involves determining the copy number and copy number variation (CNV) of different sequences of interest in a test sample that contains a mixture of nucleic acids derived from two or more different genomes and is known or suspected to contain different amounts of one or more sequences of interest. Copy number variations determined by this method include gains or losses of entire chromosomes, alterations involving very large chromosomal segments visible under a microscope, and numerous submicroscopic copy number variations of DNA fragments ranging from single nucleotides to kilobases (kb) to megabases (Mb) in size.

[0135] Some specific implementations of NIPT analysis include fragment length (or fragment size) of cfDNA to improve the sensitivity and specificity of detecting fetal aneuploidy from cfDNA in maternal plasma. Some embodiments are implemented using PCR-free library preparation plus paired-end DNA sequencing. In some embodiments, fragment size and coverage are used to enhance fetal aneuploidy detection. In some embodiments, the method includes combining independent counts of shorter fragments with the relative fractions of shorter fragments in bins across the genome.

[0136] Some specific implementations of NIPT analysis include methods for improving the sensitivity and / or specificity of sequence data analysis by removing GC content bias within a sample. In some embodiments, removal of GC content bias within a sample is based on sequence data corrected for systematic variation common across unaffected training samples.

[0137] Some specific implementations of NIPT analysis include methods for obtaining parameters with high signal-to-noise ratios from cell-free nucleic acid fragments for determining various genetic conditions related to copy number and CNV, with improved sensitivity, selectivity and / or efficiency relative to conventional methods. These parameters include, but are not limited to, coverage, fragment size-weighted coverage, the fraction or ratio of fragments within a defined range, methylation levels of fragments, t statistics obtained from coverage, fetal fraction estimates obtained from coverage information, and the like. The described process has been found to be particularly effective in improving signals in samples with relatively low fractions of DNA from the genome under consideration (e.g., the genome of a fetus). An example of such a sample is a maternal blood sample from an individual pregnant with fraternal twins, triplets, etc., where the process assesses copy number variation in the genome of one of the fetuses.

[0138] In some specific implementations of NIPT analysis, very low cfDNA input that does not require PCR amplification can be used to achieve high analytical sensitivity and specificity through simple library preparation. PCR-free methods simplify workflows, improve turnaround times, and eliminate biases inherent in PCR methods. In some embodiments, detection of fetal aneuploidies from maternal plasma can be more robust and efficient than conventional methods, requiring fewer unique cfDNA fragments. The combination of the two achieves improved analytical sensitivity and specificity with very low numbers of cfDNA fragments and very fast turnaround times. This has the potential to enable NIPT to be performed at a much lower cost to promote its use in the general obstetric population.

[0139] In various implementations of NIPT analysis, PCR-free library preparation is possible using the disclosed methods. Some implementations eliminate the inherent bias of PCR methods, reduce assay complexity, reduce the required sequencing depth (2.5x lower), provide faster turnaround time, such as one-day turnaround, enable in-process fetal fraction (FF) measurement, and facilitate the use of fragment size information to distinguish between maternal and fetal / placental cfDNA.

[0140] In some embodiments, as part of a NIPT protocol, detection, quantification, and / or characterization of maternal circulating cfDNA associated with diagnosis of preeclampsia or risk of developing preeclampsia is performed using methods such as those described in U.S. Pat. No. 10,095,831, the contents of which are incorporated herein by reference in their entirety. In some embodiments, as part of a NIPT protocol, a VERISEQ ™ The NIPT Solution v2 assay (Illumina, Inc., Foster City, CA) is used to detect, quantify, and / or characterize maternal circulating cfDNA as it relates to the diagnosis of pre-eclampsia or the risk of developing pre-eclampsia.

[0141] The sample can be a biological sample, including but not limited to blood, serum, plasma, sweat, tears, urine, sputum, lymph, saliva, amniotic fluid, tissue biopsy, swab or smear, including, for example but not limited to placental tissue samples. In some preferred embodiments, the biological sample is a cell-free plasma sample. The biological sample can be a maternal sample obtained from a pregnant female subject.

[0142] As used herein, the term "subject" refers to human subjects as well as non-human mammalian subjects. Although the embodiments herein relate to humans and the language is primarily directed to human issues, the concepts of the present disclosure are applicable to any mammal and can be used in veterinary medicine, animal science, research laboratories, and the like.

[0143] The subject can be a pregnant woman, including a pregnant woman at any stage of pregnancy. The stage of pregnancy can be, for example, the first trimester, the second trimester (including the third trimester), or the third trimester (including the early third trimester).

[0144] In some embodiments, the gestational stage of pregnancy can be, for example, before about 10 weeks of pregnancy, before about 11 weeks of pregnancy, before about 12 weeks of pregnancy, before about 16 weeks of pregnancy, before about 20 weeks of pregnancy, or before about 25 weeks of pregnancy.

[0145] In some embodiments, the gestational stage of pregnancy can be, for example, about 10 weeks gestation, about 11 weeks gestation, about 12 weeks gestation, about 13 weeks gestation, about 14 weeks gestation, about 15 weeks gestation, about 16 weeks gestation, about 17 weeks gestation, about 18 weeks gestation, about 19 weeks gestation, about 20 weeks gestation, about 21 weeks gestation, about 22 weeks gestation, about 23 weeks gestation, about 24 weeks gestation, about 25 weeks gestation, about 26 weeks gestation, about 27 weeks gestation, about 28 weeks gestation, about 29 weeks gestation, about 30 weeks gestation, about 31 weeks gestation, about 32 weeks gestation, about 33 weeks gestation, about 34 weeks gestation, about 35 weeks gestation, about 36 weeks gestation, or any range thereof. For example, in some embodiments, the gestational stage of pregnancy can be, for example, from about 8 to about 18 weeks of gestation, from about 9 to about 12 weeks of gestation, from about 9 to about 14 weeks of gestation, from about 10 to about 14 weeks of gestation, from about 10 to about 15 weeks of gestation, from about 11 to about 14 weeks of gestation, from about 11 to about 13 weeks of gestation, from about 11 to about 15 weeks of gestation, from about 12 to about 13 weeks of gestation, from about 12 to about 14 weeks of gestation, from about 12 to about 28 weeks of gestation, from about 13 to about 16 weeks of gestation, from about 17 to about 20 weeks of gestation, from about 17 to about 25 weeks of gestation, from about 17 to about 26 weeks of gestation, from about 18 to about 26 weeks of gestation, from about 21 to about 24 weeks of gestation, from about 24 to about 27 weeks of gestation, or from about 25 to about 28 weeks of gestation.

[0146] In some embodiments, the gestational stage of pregnancy can be, for example, from about 11 to about 14.2 weeks gestation or from 17.6 to about 25.5 weeks gestation.

[0147] In some embodiments, the methods described herein can detect early-onset pre-eclampsia and / or determine an increased risk of early-onset pre-eclampsia, wherein early-onset pre-eclampsia is pre-eclampsia that occurs before about 34 weeks of gestation.

[0148] In some embodiments, the methods described herein can detect late-onset pre-eclampsia and / or determine an increased risk of late-onset pre-eclampsia, wherein late-onset pre-eclampsia is pre-eclampsia that develops at or after about 34 weeks of gestation.

[0149] The present disclosure includes kits for diagnosing pre-eclampsia and identifying pregnant women at risk of developing pre-eclampsia. A kit is any article (e.g., a package or container) comprising at least one reagent for specific detection, quantification, and / or characterization of cfDNA signals of concentration, fetal fraction, and / or fragment size distribution in maternal circulation indicating pre-eclampsia or the risk of developing pre-eclampsia as described herein. The kit can be promoted, distributed, or sold as a unit for performing the method of the present disclosure.

[0150] The cell-free DNA biomarkers of the indication of pre-eclampsia found in the maternal circulation can be combined with appropriate monitoring and medical management for the purposes of the non-invasive method for diagnosing pre-eclampsia and identifying the pregnant women with the risk of developing pre-eclampsia. For example, further testing may be required. This test may include, for example, a blood test for measuring liver function, renal function and / or platelets and various coagulation proteins, a urinalysis for measuring protein or creatinine levels, a fetal ultrasound for measuring monitoring fetal growth, weight and amniotic fluid, a stress-free test for measuring fetal heart rate by fetal movement, and / or using ultrasound to measure the fetal physiological activity assessment of fetal breathing, muscle tension and movement and the amniotic fluid volume that may be needed. Therapeutic interventions may include, for example, increasing the frequency of antenatal visits, antihypertensive drugs to lower blood pressure, corticosteroids, anticonvulsants, bed rest, hospitalization and / or early delivery. See, e.g., Townsend et al., 2016 “Current best practice in the management of hypertensive disorders in pregnancy,” Integr Blood Press Control; 9: 79-94.

[0151] Treatment interventions may include administering low-dose aspirin to pregnant women identified as at risk for developing preeclampsia. A recent multicenter, double-blind, placebo-controlled trial demonstrated that treatment of women at high risk for preterm preeclampsia with low-dose aspirin resulted in a lower incidence of this diagnosis compared with placebo (Rolnik et al., 2017, NEngl J Med; 377(7):613-622). Meta-analyses of randomized trials found that adequate daily doses of aspirin initiated before 16 weeks of gestation can prevent most cases of PE and its associated complications (Bujold, 2022, Hypertension; 79:323-324; Bujold et al., 2010, Obstet Gynecol; 116:402-414; and Roberge et al., 2018, Am J Obstet Gynecol; 218(3):287-293el). The American College of Obstetricians and Gynecologists (ACOG) recommends that women with any high risk factor for PE and women with more than one moderate risk factor should start receiving low-dose aspirin between 12 and 28 weeks of gestation (preferably before 16 weeks of gestation) until delivery (ACOGPractice Bulletin, Number 222. Gestational Hypertension and Preeclampsia. Obstetrics and gynecology 2020, 135, e237-e260, doi: 10.1097 / aog.0000000000003891). Therefore, PE screening is best performed in the first trimester.

[0152] Doses of low-dose aspirin include, but are not limited to, about 50 mg to about 150 mg per day, about 60 mg to about 80 mg per day, about 100 mg or more per day, or about 150 mg per day. Administration may be, for example, at or before 16 weeks of pregnancy, or from 11 to 14 weeks of pregnancy. Administration may continue until 36 weeks of pregnancy.

[0153] The present disclosure also includes a system comprising one or more microprocessors and a memory, the memory comprising instructions executable by the one or more microprocessors, and the memory comprising sequence reads mapped to a reference genome, wherein the sequence reads are reads of cfDNA from a test sample from a pregnant female subject, and wherein the instructions executable by the one or more microprocessors are configured to perform the methods described herein.

[0154] The present disclosure also includes a machine comprising one or more microprocessors and a memory, the memory comprising instructions executable by the one or more microprocessors, and the memory comprising sequence reads mapped to a reference genome, wherein the sequence reads are reads of cfDNA from a test sample from a pregnant female subject, and wherein the one or more microprocessor executable instructions are configured to perform the methods described herein.

[0155] The present disclosure also includes a non-transitory computer-readable storage medium on which an executable program is stored, wherein the program instructs a microprocessor to access sequence reads mapped to a reference genome and to perform the methods described herein.

[0156] Exemplary Aspects

[0157] The invention is defined in the claims. However, a non-exhaustive list of non-limiting exemplary aspects is provided below. Any one or more of the features of these aspects may be combined with any one or more features of another example, embodiment or aspect described herein. Exemplary embodiments of the invention include, but are not limited to, the following:

[0158] Aspect 1 includes a method for detecting pre-eclampsia and / or determining an increased risk of pre-eclampsia in a pregnant female subject, the method comprising:

[0159] providing cell-free DNA (cfDNA) sequence information obtained from a biological sample obtained from the pregnant female subject; and

[0160] From the cfDNA sequence information:

[0161] Determine cell-free DNA (cfDNA) concentration;

[0162] determining a fetal fraction within the cfDNA; and / or

[0163] determining fragment size distribution within the cfDNA;

[0164] in:

[0165] Higher cfDNA concentrations relative to normal controls;

[0166] A lower fetal fraction in the cfDNA relative to a normal control;

[0167] Higher fragment size distribution relative to normal controls; and / or

[0168] The ratio of fetal fraction to fragment size distribution is less than that in normal controls

[0169] Indicating pre-eclampsia and / or an increased risk of pre-eclampsia in the pregnant female.

[0170] Aspect 2 is a method according to aspect 1, wherein the cfDNA sequence information is obtained from a sequencing-based non-invasive prenatal testing (NIPT) test.

[0171] Aspect 3 is a method for detecting pre-eclampsia and / or determining an increased risk of pre-eclampsia in a pregnant female subject, the method comprising:

[0172] removing intact cells from a biological sample obtained from the pregnant female;

[0173] isolating cell-free DNA (cfDNA) molecules from the biological sample;

[0174] Sequencing the enriched cfDNA to obtain cfDNA sequence information; and

[0175] From the cfDNA sequence information:

[0176] Determine cell-free DNA (cfDNA) concentration;

[0177] determining a fetal fraction within the cfDNA; and / or

[0178] determining fragment size distribution within the cfDNA;

[0179] in:

[0180] Higher cfDNA concentrations relative to normal controls;

[0181] A lower fetal fraction in the cfDNA relative to a normal control;

[0182] Higher fragment size distribution relative to normal controls; and / or

[0183] The ratio of fetal fraction to fragment size distribution is less than that in normal controls

[0184] Indicating pre-eclampsia and / or an increased risk of pre-eclampsia in the pregnant female.

[0185] Aspect 4 is a method according to any one of aspects 1 to 3, the method comprising:

[0186] determining a fetal fraction within the cfDNA; and

[0187] determining fragment size distribution within the cfDNA;

[0188] in:

[0189] a lower fetal fraction in the cfDNA relative to a normal control; and

[0190] higher fragment size distribution relative to normal controls;

[0191] Indicating pre-eclampsia and / or an increased risk of pre-eclampsia in the pregnant female.

[0192] Aspect 5 is a method according to any one of aspects 1 to 4, the method comprising:

[0193] Determine cell-free DNA (cfDNA) concentration;

[0194] determining a fetal fraction within the cfDNA; and

[0195] determining fragment size distribution within the cfDNA;

[0196] in:

[0197] Higher cfDNA concentrations relative to normal controls;

[0198] a lower fetal fraction in the cfDNA relative to a normal control; and

[0199] higher fragment size distribution relative to normal controls;

[0200] Indicating pre-eclampsia and / or an increased risk of pre-eclampsia in the pregnant female.

[0201] Aspect 6 is a method, comprising:

[0202] a) Access sequence reads from cfDNA and determine:

[0203] i) cfDNA concentration;

[0204] ii) the fetal fraction within the cfDNA;

[0205] iii) fragment size distribution within the cfDNA; and / or

[0206] iv) parameters including said fetal fraction and said fragment size distribution;

[0207] b) Comparison

[0208] i) the cfDNA concentration and a first threshold amount;

[0209] ii) the fetal fraction and a second threshold amount;

[0210] iii) the fragment size distribution and a third threshold amount; and / or

[0211] iv) said parameters including said fetal fraction and said fragment size distribution and a fourth threshold amount;

[0212] wherein the first threshold amount, the second threshold amount, the third threshold amount, and the fourth threshold amount are determined based on a plurality of normal samples;

[0213] c) determining that the pregnant female subject has pre-eclampsia and / or an increased risk of pre-eclampsia, wherein

[0214] i) the cfDNA concentration is above the first threshold amount;

[0215] ii) the fetal fraction is less than the second threshold amount;

[0216] iii) the fragment size distribution is above the third threshold amount; and / or

[0217] iv) said parameters including said fetal fraction and said fragment size distribution are less than said fourth threshold amount;

[0218] Indicating pre-eclampsia and / or an increased risk of pre-eclampsia in the pregnant female.

[0219] Aspect 7 is a method according to any one of aspects 1 to 6, wherein the biological sample is obtained from the pregnant female at a gestational age of less than 16 weeks.

[0220] Aspect 8 is a method according to any one of aspects 1 to 7, wherein the biological sample is obtained from the pregnant female subject at a gestational period of about 11 weeks to about 14.2 weeks.

[0221] Aspect 9 is a method according to any one of aspects 1 to 6, wherein the biological sample is obtained from the pregnant female at a gestational age of greater than 20 weeks.

[0222] Aspect 10 is a method according to any one of aspects 1 to 6, wherein the biological sample is obtained from the pregnant female subject at a gestational period of about 17.6 weeks to about 25.5 weeks.

[0223] Aspect 11 is a method according to any one of aspects 1 to 10, wherein detecting pre-eclampsia and / or determining an increased risk of pre-eclampsia comprises detecting early-onset pre-eclampsia and / or determining an increased risk of early-onset pre-eclampsia.

[0224] Aspect 12 is a method according to any one of aspects 1 to 10, wherein detecting pre-eclampsia and / or determining an increased risk of pre-eclampsia comprises detecting late-onset pre-eclampsia and / or determining an increased risk of late-onset pre-eclampsia.

[0225] Aspect 13 is a method according to any one of aspects 1 to 12, wherein the biological sample comprises whole blood, serum or plasma.

[0226] Aspect 14 is a method according to any one of Aspects 1 to 13, further comprising providing the pregnant female with a therapeutic intervention selected from the group consisting of increasing the frequency of prenatal visits, antihypertensive drugs to lower blood pressure, corticosteroids, anticonvulsants, bed rest, hospitalization, early delivery, and combinations thereof, and / or treating the pregnant female with low-dose aspirin, wherein the low-dose aspirin comprises about 50 mg to about 150 mg per day.

[0227] Aspect 15 is a system comprising one or more microprocessors and a memory, the memory comprising instructions executable by the one or more microprocessors, and the memory comprising sequence reads mapped to a reference genome, wherein the sequence reads are reads of cfDNA from a test sample from a pregnant female subject, and wherein the instructions executable by the one or more microprocessors are configured to perform a method according to any one of Aspects 1 to 14.

[0228] Aspect 16 is a machine comprising one or more microprocessors and a memory, the memory comprising instructions executable by the one or more microprocessors, and the memory comprising sequence reads mapped to a reference genome, wherein the sequence reads are reads of cfDNA from a test sample from a pregnant female subject, and wherein the instructions executable by the one or more microprocessors are configured to perform a method according to any one of Aspects 1 to 14.

[0229] Aspect 17 is a non-transitory computer-readable storage medium on which an executable program is stored, wherein the program instructs a microprocessor to access sequence reads mapped to a reference genome and perform a method according to any one of aspects 1 to 14.

[0230] The present invention is illustrated by the following examples.It is to be understood that the specific examples, materials, amounts and procedures are to be interpreted broadly in accordance with the scope and spirit of the invention as described herein.

[0231] Example

[0232] Example 1

[0233] Using cell-free DNA signals as a biomarker for early and simple prediction of preeclampsia

[0234] Preeclampsia (PE) is the leading cause of maternal and perinatal morbidity worldwide. However, current screening methods are complex and require special skills requirements. In this embodiment, cell-free (cf) DNA was evaluated as an efficient biomarker for identifying patients at risk. One hundred patients attending a private prenatal clinic in Canada were registered in their first three months of pregnancy and blood was drawn at 11.0-14.2 weeks (time point A) and 17.6-25.5 weeks (time point B) of gestation. Twelve patients developed PE, four of whom were early PE and eight were late PE. CfDNA signals, i.e., concentration, fetal fraction, and fragment size distribution, were associated with clinical outcomes of the test population to establish a logistic regression model. At time point A, significant differences in all three cfDNA signals were observed between PE patients and control cases, while at time point B, both fetal fractions and concentrations were significantly different between PE patients and control cases. Overall, the model had a sensitivity of up to 100% and a specificity of up to 87.5% at time point A. This study demonstrated that patients at risk for preeclampsia can be identified during the first trimester using this logistic regression model.

[0235] Overview

[0236] Preeclampsia (PE) affects 2%-8% of pregnancies worldwide and is one of the leading causes of maternal and perinatal morbidity (Steegers et al., 2010, Lancet, 376(9741):631-644). Severe PE can lead to premature birth, fetal growth restriction, maternal multi-organ dysfunction, maternal seizures, and perinatal death, killing 76,000 women and 500,000 infants each year (Poon et al., 2019, Int J Gynaecol Obstet;145(Suppl 1):1-33; and Bujold, 2022, Hypertension;79:323-324). Furthermore, mothers with PE and children from affected pregnancies are at increased risk for long-term cardiovascular and chronic diseases, and women who develop preterm PE have an average reduction in life expectancy of 10 years (Poon et al., 2019, Int J Gynaecol Obstet; 145(Suppl1): 1-33; and Chaemsaithong et al., 2022, Am J Obstet Gynecol; 226(2S):S1071-S1097.e2). Preeclampsia is a multifaceted syndrome with highly variable clinical presentations and can be divided into two main subtypes, early-onset PE and late-onset PE. The International Society for the Study of Hypertension in Pregnancy (ISSHP) classifies (new) PE as pregnancy-induced hypertension with one of three new-onset conditions at ≥20 weeks of gestation, namely proteinuria, other maternal end-organ dysfunction, or uteroplacental dysfunction (Magee et al., 2022, Pregnancy Hypertens; 27:148-169).

[0237] There are many risk factors associated with the development of PE, including advanced maternal age, chronic hypertension, autoimmune diseases such as antiphospholipid antibody syndrome and systemic lupus erythematosus, pre-gestational diabetes, and multiple pregnancies (Poon et al., 2019, Int J Gynaecol Obstet; 145(Suppl 1): 1-33; and Burton et al., 2019, BMJ; 366:12381). Currently, there is no specific treatment for PE, and premature induction of labor is the only treatment for severe cases. Meta-analyses of randomized trials have found that appropriate daily doses of aspirin initiated before 16 weeks of gestation can prevent most cases of PE and its associated complications (Bujold, 2022, Hypertension; 79:323-324; Bujold et al., 2010, Obstet Gynecol; 116:402-414; and Roberge et al., 2018, Am J Obstet Gynecol; 218(3):287-293e1). The American College of Obstetricians and Gynecologists (ACOG) recommends that women with any high risk factor for PE and women with more than one moderate risk factor should start receiving low-dose aspirin between 12 and 28 weeks of gestation (preferably before 16 weeks of gestation) until delivery (ACOG Practice Bulletin, Number 222. Gestational Hypertension and Preeclampsia. Obstetrics and gynecology 2020, 135, e237-e260, doi:10.1097 / aog.0000000000003891). Therefore, PE screening is best performed in the first trimester of pregnancy.

[0238] Various different approaches have been proposed to screen patients for PE during pregnancy. One of the main screening methods currently used is based on the Bayesian competing risks (CR) model. This PE screening approach combines maternal characteristics and obstetric history with biomarkers for risk assessment, including mean arterial pressure, uterine artery pulsatility index, and placental growth factor (PlGF) (Poon et al., 2009, Hypertension; 53:812-818; and Wright et al., 2015, Am JObstet Gynecol; 213:62). Although this approach is superior to traditional methods based solely on maternal history and demographic characteristics, it is complex and requires multiple different tests and information to calculate a PE risk estimate.

[0239] This example establishes that cell-free (cf) DNA can be used as a highly effective biomarker for identifying patients at risk of developing preeclampsia (PE). Currently, cfDNA obtained from maternal blood drawn during pregnancy is widely used for prenatal aneuploidy screening. This example observes whether cfDNA-based signals at two different time points (11.0-14.2 weeks of gestation and 17.6-25.5 weeks of gestation) differ between patients who do and do not develop preeclampsia during their pregnancy. It also compares the screening performance of the proposed model with that of the CR model. This example found that the proposed model was able to distinguish PE from control cases using cfDNA signals from the first trimester of pregnancy in a logistic regression model with a sensitivity of up to 100% and a specificity of up to 87.5%.

[0240] Materials and methods

[0241] The testing population for the proposed model consisted of samples from pregnant patients from a private prenatal clinic in Quebec City (CliniquesPrenato, Canada) who underwent routine non-invasive prenatal testing (NIPT) in the first trimester to check for aneuploidy and other adverse obstetric outcomes. From July 2020 to May 2021, visits were conducted at 11.0-25.5 weeks of gestation, during which nurses recorded maternal characteristics and medical history, including maternal age; gestational age; maternal height and weight; ethnic origin; if the patient smoked during pregnancy; if the patient's mother had any history of PE; and the method of conception of the current pregnancy. This was then examined by a specialized physician. Patients also had blood drawn for PlGF serum levels, had their mean arterial pressure measured, and had transabdominal color Doppler ultrasonography used to measure the pulsatility index of the left and right uterine arteries. Patients were included in the study if they were at least 18 years old, had a singleton pregnancy, and had a gestational age (GA) of 11.0-14.2 weeks. Patients were excluded from the study if they had chronic hypertension, were taking aspirin or any anticoagulant medication, were using immunosuppressants, or had current or previous cancer.

[0242] For the purpose of this study, blood samples were collected at 11.0-14.2 weeks of gestation (time point A) as part of the routine NIPT screening process and were repeated at 17.6-25.5 weeks of gestation (time point B). ™ Laboratory-opened tests (Illumina's VERISEQ ™Blood samples from time point A were processed using an adapted version of the NIPT Solution v2 assay (Illumina, Inc. clinical services laboratory, Foster City, CA). Blood samples from time point B were run on the RUO version. NIPT results for rare autosomal trisomies or copy number variations from time point A or time point B were not reported to the patients. Only validation results for trisomy 21, trisomy 18, and trisomy 13 from time point A were returned to the patients. All women gave written consent to participate and to share the data obtained in the study. This project was approved by the Institutional Research Review Board of the Prenatal Clinic (approval number 12302019-2).

[0243] All study participants were followed up until delivery. Neonatal examination reports were collected if adverse outcomes were reported. Outcome information included birth weight, GA at delivery, mode of delivery, and the presence of any delivery complications. Outcomes included PE or delivery complicated by PE and other adverse pregnancy / delivery outcomes; PE was defined according to the International Society for the Study of Hypertension in Pregnancy (Brown et al., 2001, Hypertens Pregnancy; 20(l):IX-XIV).

[0244] CfDNA parameters from bioinformatic analysis of NIPT at time point A were used for model development. A multivariate logistic regression model was fitted with preeclampsia outcome as a binary dependent variable and cfDNA fetal fraction and fragment size distribution (FragSizeDist), + / - concentration (Conc) as independent variables. Specifically, logistic regression predicted the probability of preeclampsia based on FragSizeDist as an independent variable, and interaction terms including FF and Conc. A supervised 5-fold cross-validation was performed on the model using a minimum number of PE cases in both the training and test sets. The selected model was trained using -80% of the patient data (n = 75, 8 PE cases + 67 non-PE cases), with -20% of the patient data (n = 20, 4 PE cases + 16 non-PE cases) used in the test set. The model presented an accuracy of 90%.

[0245] All bioinformatics statistical analyses were performed using the RStudio software program v 2022.07.2 build 576 © It will be held from 2009 to 2022.

[0246] result

[0247] For this embodiment, a total of 100 samples are expected to be collected from pregnant patients. Five samples had no outcome data and were therefore excluded from the study. Twelve patients developed PE, four of which were early (before 34 weeks of gestation) and eight were late PE (after 34 weeks of gestation); no aneuploidy was detected in the patient group that developed PE. The patient demographics of the test population are shown in Table 1. Patients were divided into four separate categories based on the observed PE results and the screening-positive status of the competing risk model or the cfDNA signal model of this embodiment. Patients with any adverse pregnancy outcomes were excluded from the control group. Biomarker levels were measured for all study participants, including blood pressure, uterine artery pulsatility index, and PlGF. Details of each of the four groups are also shown in Table 1.

[0248] For the proposed model, three different cfDNA signals were considered, namely, cfDNA concentration, fetal fraction, and fragment size distribution. Figure 1A-Figure 1C The effect of these different cfDNA signals on distinguishing early and late PE patient cases from control samples at time point A (gestational age 11.0-14.2 weeks) is shown. Figure 1A As can be seen, the concentration of cfDNA from early PE cases was significantly higher compared to control samples (p=0.048), while no significant difference was observed between the late PE group and controls. The fragment size distribution was found to be significantly higher in late PE cases compared to controls (p=0.036; Figure 1B ), and found that the fetal fraction was significantly lower in the late PE group compared with the control (p = 0.028; Figure 1C ). In addition, the linear regression plot showed that, except for one outlier (Case # 85; Figure 1D ), the use of fetal fraction and fragment size distribution may help distinguish PE cases from controls. Figure 3A Linear regression plots of time point A and all three cfDNA signals are shown.

[0249] Table 1. Maternal demographics and pregnancy history of study participants .

[0250]

[0251] Data are expressed as median (interquartile range) or n (%) unless otherwise indicated. APO, adverse pregnancy outcome; MoM, multiple of the median; Pe, preeclampsia; PlGF, placental growth factor; UAPI, uterine artery pulsatility index; wk, week; yr, year.

[0252] *Based on test set.

[0253] **Based on one patient only.

[0254] For time point B (gestational age 17.6-25.5 weeks; Figure 2A-2C ), cfDNA concentrations were significantly higher in both early (p=0.021) and late (p=0.007) PE cases compared with controls, whereas FF was significantly lower in both early (p=0.044) and late (p=0.015) PE cases compared with controls. No significant differences in fragment size distribution were observed at time point B. Similar to time point A, linear regression plots show that the use of fetal fraction and fragment size distribution can help distinguish PE cases from controls ( Figure 2D ). It can be seen that the outlier case (#85) from time point A is consistent with the PE case at time point B. Figure 3B Linear regression plots of time point A and all three cfDNA signals are shown.

[0255] In the final step, the performance of the proposed model (based on the test dataset) was compared with the established CR model at both time point A and time point B. As can be seen in Table 2, at time point A (first trimester), the immediate model had higher sensitivity (100% vs. 58.3%) and higher PPV (66.7% vs. 41.0%) compared with the CR model, and the same specificity (87.5%) was observed for both models.

[0256] Table 2. Summary of test performance for cfDNA screening methods (n = 20) and competing risk methods (n = 95) .

[0257]

[0258] discuss

[0259] This example establishes that cfDNA-based signals can be used to distinguish patients who develop PE during pregnancy from those who do not. Using the cfDNA signal in a logistic regression model enabled identification of at-risk patients, with significant differences in concentration, fetal fraction, and fragment size distribution observed between PE patients and control cases.

[0260] As proposed in this example, at time point A, the cfDNA concentration of early PE patients was significantly higher than that of control cases, while at time point B, the cfDNA concentration of both early and late PE patients was significantly higher. Similar to this example, many other studies have also noted the connection between cfDNA concentration and preeclampsia. Lo et al. first demonstrated in 1999 that the median concentration of circulating fetal DNA in patients with preeclampsia was much higher than that in non-preeclamptic patients (Lo et al., 1999, Clin Chem; 45(2): 184-188). The authors proposed that the measurement of circulating DNA may be a useful marker for diagnosing PE. More recent studies have found that total cfDNA is significantly higher in preeclampsia at diagnosis, and this higher total cfDNA is associated with earlier gestational age and higher systolic blood pressure at delivery (Kolarova et al., 2021, J Am Heart Assoc; 10(15): e021477). Another study also found that PE was associated with higher maternal serum total cfDNA concentrations compared with normal pregnancies (Rafaeli-Yehudai et al., 2018, PloS One; 13(7):e0200360). Although the study by Rolnik et al. showed that median total cfDNA was significantly increased in patients with early PE compared with controls, the authors found that measuring total cfDNA at 11-13 and 20-24 weeks of gestation did not predict PE (Rolnik et al., 2015, Ultrasound Obstet Gynecol; 45:106-111). This example also found that using concentration in a logistic regression model was the least significant predictor of the three cfDNA parameters tested for time point A, but became highly significant and predictive for time point B. The low n in this example precluded differentiation of patients with early PE from those with late PE for this model, but preliminary data suggest that concentration may be important for future model development.

[0261] The concentration dynamics between time points A and B deserve further exploration and understanding as it may be associated with the onset of PE and will further inform the optimal time for cfDNA screening. In this example, at time point A, patients with late PE had significantly reduced fetal fractions compared to patients who did not develop PE, while at time point B, both early and late PE patients had significantly reduced fetal fractions. Other studies have also shown that low FF is associated with PE (Becking et al., 2021, Prenat Diag; 41(10): 1296-1304; Gerson et al., 2019, Pregnancy Hypertens; 16: 148-153; Yuan et al., 2020, Pregnancy Hypertens; 22: 101-108; and Sapantzoglou et al., 2021, J MaternFetal Neonat Med; 35(25): 5363-5368). Rolnik et al. found a significant correlation between FF results and first-trimester markers of adverse pregnancy outcomes, including PAPP-A and P1GF, and their results showed that patients at increased risk for PE tended to have lower fetal fractions (Rolnik et al., 2018, Ultrasound Obstet Gynecol; 52:722-727).

[0262] A great deal of research has been done to enable easy and effective first-trimester screening for patients who will develop PE during pregnancy. However, to date, no effective biomarkers have been identified that would enable this in a unique blood draw, which may help to explain, in part, why PE screening has not become widespread worldwide. One of the main advantages of this study is that it was able to develop and test a novel PE screening model that integrates multiple cfDNA signals. The proposed cfDNA model appears to have improved sensitivity compared to the competing risk model, which is considered the gold standard for screening PE and is therefore likely to be more effective. In addition, this is the first time that cfDNA fragment size data have been reported in patients who will or will not develop PE. Another advantage of this cfDNA model is that it is easy to use and therefore avoids many of the complications and special skills required by other PE screening methods. In theory, it could also be easily incorporated into routine non-invasive prenatal screening. In addition to including other key variables, future iterations of the model will likely expand the model to delineate early versus late preeclampsia.

[0263] As shown in the data from time point A, results can be obtained before 16 weeks of gestation, which will allow the implementation of preventive treatment with aspirin recommended by ACOG (ACOG Practice Bulletin, Number 222. Gestational Hypertension and Preeclampsia. Obstetrics and gynecology 2020, 135, e237-e260, doi: 10.1097 / aog.0000000000003891). However, the drawback of this embodiment is the small sample size, with only 12 PE patients in our test population. Future prospective studies will need to be conducted in larger groups of pregnant patients to determine the feasibility of our proposed model in identifying patients at risk.

[0264] In conclusion, logistic regression modeling of preeclampsia outcomes using cfDNA fetal fraction, fragment size distribution, and concentration may facilitate probabilistic prediction of pregnancies at risk of developing preeclampsia. The proposed model is theoretically a useful additional tool for screening and subsequent counseling of patients regarding the risk and prevention of the development of preeclampsia.

[0265] This embodiment is now published as Gekas et al., “Use of cell-free signals as biomarkersfor early and easy prediction of preeclampsia,” Frontiers in Medicine, May 24, 2023: 10:1191163. doi: 10.3389 / fmed.2023.1191163. eCollection 2023, which is incorporated herein by reference in its entirety.

[0266] Example 2

[0267] Further analysis using cell-free DNA signal as a biomarker for detecting pre-eclampsia

[0268] The data of Example 1 were further analyzed using the following formula:

[0269] y i = β0 - β1 (FragSizeDist) + β2 (FragSizeDist:FF) - β3 (FragSizeDist:FF:Conc).

[0270] This formula continued to determine the separation between PE and non-PE samples with a final sensitivity of 83% and a specificity of 62%. Figure 4 is a linear regression curve graph showing the use of fetal fraction and fragment size distribution to distinguish PE samples from control samples at time point A. PE samples are represented by circles. Control samples are represented by squares. Figure 5 is a plot of probability versus outcome; cutoff = 0.098; accuracy: 0.6526; sensitivity: 0.8333; and specificity 0.6265.

[0271] The complete disclosures of all patents, patent applications, and publications cited herein, as well as electronically available materials (including, for example, nucleotide sequence submissions in, for example, GenBank and RefSeq, amino acid sequence submissions in, for example, SwissProt, PIR, PRF, PDB, and translations of annotated coding regions from GenBank and RefSeq) are incorporated by reference in their entirety. Supplementary materials cited in publications (such as supplementary tables, supplementary figures, supplementary materials and methods, and / or supplementary experimental data) are also incorporated by reference in their entirety. In the event of any inconsistency between the disclosure of the present application and the disclosure of any document incorporated herein by reference, the disclosure of the present application shall prevail. The above detailed description and examples are given only for a clear understanding of the present invention. They should not be construed as unnecessary limitations. The present disclosure is not limited to the exact details shown and described, as variations obvious to those skilled in the art will be included in the disclosure defined by the claims.

[0272] Unless otherwise indicated, all numbers used in the specification and claims expressing the amount of components, molecular weight, etc., are to be understood as being modified in all cases by the term "about". Therefore, unless otherwise indicated, the numerical parameters listed in the specification and claims are approximate values, which may vary depending on the desired properties sought to be obtained by the present disclosure. At the very least, and not attempting to limit the doctrine of equivalents to the scope of the claims, each numerical parameter should at least be interpreted in light of the number of reported significant digits and by applying customary rounding techniques.

[0273] Although the numerical ranges and parameters setting forth the broad scope of the present disclosure are approximations, the numerical values ​​set forth in the specific examples are reported as precisely as possible. However, all numerical values ​​inherently contain a range necessarily resulting from the standard deviation found in their respective testing measurements.

[0274] Unless otherwise indicated, all headings are for the convenience of the reader and should not be used to limit the meaning of the text that follows the heading.

Claims

1. A method for detecting pre-eclampsia and / or determining an increased risk of pre-eclampsia in a pregnant female subject, the method comprising: providing cell-free DNA (cfDNA) sequence information obtained from a biological sample obtained from the pregnant female subject; as well as From the cfDNA sequence information: Determine cell-free DNA (cfDNA) concentration; determining a fetal fraction within the cfDNA; and / or determining fragment size distribution within the cfDNA; in: Higher cfDNA concentrations relative to normal controls; A lower fetal fraction in the cfDNA relative to a normal control; Higher fragment size distribution relative to normal controls; and / or A ratio of fetal fraction to fragment size distribution that is less than that in a normal control indicates pre-eclampsia and / or an increased risk of pre-eclampsia in the pregnant female.

2. Wherein the cfDNA sequence information is obtained from a sequencing-based non-invasive prenatal testing (NIPT) test.

3. A method for detecting pre-eclampsia and / or determining an increased risk of pre-eclampsia in a pregnant female subject, the method comprising: removing intact cells from a biological sample obtained from the pregnant female; isolating cell-free DNA (cfDNA) molecules from the biological sample; Sequencing the enriched cfDNA to obtain cfDNA sequence information; as well as From the cfDNA sequence information: Determine cell-free DNA (cfDNA) concentration; determining a fetal fraction within the cfDNA; and / or determining fragment size distribution within the cfDNA; in: Higher cfDNA concentrations relative to normal controls; A lower fetal fraction in the cfDNA relative to a normal control; Higher fragment size distribution relative to normal controls; and / or A ratio of fetal fraction to fragment size distribution that is less than that in a normal control indicates pre-eclampsia and / or an increased risk of pre-eclampsia in the pregnant female.

4. The method according to any one of claims 1 to 3, comprising: determining a fetal fraction within the cfDNA; as well as determining fragment size distribution within the cfDNA; in: A lower fetal fraction in the cfDNA relative to a normal control; as well as higher fragment size distribution relative to normal controls; Indicating pre-eclampsia and / or an increased risk of pre-eclampsia in the pregnant female.

5. The method according to any one of claims 1 to 4, comprising: Determine cell-free DNA (cfDNA) concentration; determining a fetal fraction within the cfDNA; as well as determining fragment size distribution within the cfDNA; in: Higher cfDNA concentrations relative to normal controls; A lower fetal fraction in the cfDNA relative to a normal control; as well as higher fragment size distribution relative to normal controls; Indicating pre-eclampsia and / or an increased risk of pre-eclampsia in the pregnant female.

6. A method comprising: a) Access sequence reads from cfDNA and determine: i) cfDNA concentration; ii) the fetal fraction within the cfDNA; iii) fragment size distribution within the cfDNA; and / or iv) parameters including said fetal fraction and said fragment size distribution; b) Comparison i) the cfDNA concentration and a first threshold amount; ii) the fetal fraction and a second threshold amount; iii) the fragment size distribution and a third threshold amount; and / or iv) said parameters including said fetal fraction and said fragment size distribution and a fourth threshold amount; wherein the first threshold amount, the second threshold amount, the third threshold amount, and the fourth threshold amount are determined based on a plurality of normal samples; c) determining that the pregnant female subject has pre-eclampsia and / or an increased risk of pre-eclampsia, wherein i) the cfDNA concentration is above the first threshold amount; ii) the fetal fraction is less than the second threshold amount; iii) the fragment size distribution is above the third threshold amount; and / or iv) said parameters including said fetal fraction and said fragment size distribution are less than said fourth threshold amount; Indicating pre-eclampsia and / or an increased risk of pre-eclampsia in the pregnant female.

7. The method according to any one of claims 1 to 6, wherein the biological sample is obtained from the pregnant female at a gestational age of less than 16 weeks.

8. The method of any one of claims 1 to 7, wherein the biological sample is obtained from the pregnant female subject at a gestational period of about 11 weeks to about 14.2 weeks.

9. The method according to any one of claims 1 to 6, wherein the biological sample is obtained from the pregnant female at a gestational period of more than 20 weeks.

10. The method of any one of claims 1 to 6, wherein the biological sample is obtained from the pregnant female subject at a gestational period of about 17.6 weeks to about 25.5 weeks.

11. The method according to any one of claims 1 to 10, wherein detecting pre-eclampsia and / or determining an increased risk of pre-eclampsia comprises detecting early-onset pre-eclampsia and / or determining an increased risk of early-onset pre-eclampsia.

12. The method according to any one of claims 1 to 10, wherein detecting pre-eclampsia and / or determining an increased risk of pre-eclampsia comprises detecting late-onset pre-eclampsia and / or determining an increased risk of late-onset pre-eclampsia.

13. The method of any one of claims 1 to 12, wherein the biological sample comprises whole blood, serum or plasma.

14. The method of any one of claims 1 to 13, further comprising providing the pregnant female with a therapeutic intervention selected from the group consisting of increasing the frequency of prenatal visits, antihypertensive medications to lower blood pressure, corticosteroid medications, anticonvulsant medications, bed rest, hospitalization, early delivery, and combinations thereof, and / or treating the pregnant female with low-dose aspirin, wherein low-dose aspirin comprises about 50 mg to about 150 mg per day.

15. A system comprising one or more microprocessors and a memory, the memory comprising instructions executable by the one or more microprocessors, and the memory comprising sequence reads mapped to a reference genome, wherein the sequence reads are reads of cfDNA from a test sample from a pregnant female subject, and wherein the instructions executable by the one or more microprocessors are configured to perform a method according to any one of claims 1 to 14.

16. A machine comprising one or more microprocessors and a memory, the memory comprising instructions executable by the one or more microprocessors, and the memory comprising sequence reads mapped to a reference genome, wherein the sequence reads are reads of cfDNA from a test sample from a pregnant female subject, and wherein the instructions executable by the one or more microprocessors are configured to perform a method according to any one of claims 1 to 14.

17. A non-transitory computer-readable storage medium on which an executable program is stored, wherein the program instructs a microprocessor to access sequence reads mapped to a reference genome and to perform the method according to any one of claims 1 to 14.

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