Preeclampsia-related methods and compositions

Abstract

Provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia. Methods of modulating gene expression levels include administering to the subject identified as having preeclampsia or being at risk of having preeclampsia a drug described herein in an amount effective to modulate gene expression levels in the subject. Also provided are methods of treating preeclampsia in a subject. Methods of treating preeclampsia include assessing gene expression levels in the subject, identifying the subject as having preeclampsia or being at risk of having preeclampsia and administering a preeclampsia therapy. Also provided are pharmaceutical compositions. The pharmaceutical compositions include a drug described herein in an amount effective to modulate gene expression levels in a subject, where the pharmaceutical composition is adapted for intravaginal administration of the drug to the subject.

Description

[0001] Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0)

[0002] PREECLAMPSIA-RELATED METHODS AND COMPOSITIONS CROSS-REFERENCE TO RELATED APPLICATIONS

[0003] This application claims the benefit of U.S. Provisional Patent Application No.

[0004] 63 / 765,227, filed February 28, 2025, which application is incorporated herein by reference in its entirety.

[0005] INTRODUCTION

[0006] Preeclampsia is an idiopathic inflammatory pregnancy disorder that affects ~5% of pregnancies, and is a major cause of perinatal morbidity and mortality (1, 2). Preeclampsia typically develops after 20 weeks of gestation and is characterized by maternal high blood pressure, often alongside proteinuria or organ dysfunction. After pregnancy, women with preeclampsia have increased long-term risk of hypertension, cardiovascular disease, stroke, and metabolic disorders (3), and children born through preeclamptic pregnancies are at increased risk for complications like preterm birth, low birth weight, and chronic conditions such as hypertension (4).

[0007] The pathogenesis of preeclampsia is complex and multifactorial, often described using a two-stage model that highlights the interplay between placental dysfunction and systemic maternal responses. In the first stage, abnormal placentation occurs due to impaired trophoblast invasion, which hinders the proper remodeling of maternal spiral arteries into low-resistance, high-capacity vessels. These perturbations cause placental hypoxia and oxidative stress, creating an environment marked by inflammation and antiangiogenic activity. The second stage arises when the hypoxic placenta releases antiangiogenic factors such as soluble fms-like tyrosine kinase-1 (sFlt-1) and endoglin (sEng), along with pro-inflammatory cytokines, into the maternal circulation. These factors disrupt angiogenesis by sequestering VEGF and placental growth factor (PIGF), promoting systemic endothelial dysfunction, increased vascular permeability, vasoconstriction, and widespread inflammation. Additionally, oxidative stress, driven by hypoxia-reoxygenation injury within the placenta, results in excessive reactive oxygen species (ROS) production, which damages cellular structures and amplifies inflammatory pathways. Together, these processes underlie the clinical manifestations of preeclampsia, including hypertension, proteinuria, edema, and multi-organ damage. Immune dysregulation also plays a crucial role in preeclampsia. Reduced activity of Tregs, coupled with increased activation of macrophages and natural killer (NK) cells, further impairs placental development and exacerbates systemic inflammation. This intricate interplay between immune, vascular, andAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) oxidative pathways highlights the complexity of preeclampsia pathogenesis and underscores the need for targeted therapeutic strategies.

[0008] The ability to identify at-risk pregnancies and therapies are each rudimentary. The only definitive treatment for preeclampsia remains delivery, with preventive strategies such as low-dose aspirin (LDA) offering modest benefits in high-risk groups. This underscores existing knowledge gaps regarding disease pathophysiology required for targeted, diseasemodifying therapies.

[0009] SUMMARY

[0010] Provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia. Methods of modulating gene expression levels include administering to the subject identified as having preeclampsia or being at risk of having preeclampsia a drug described herein in an amount effective to modulate gene expression levels in the subject. Also provided are methods of treating preeclampsia in a subject. Methods of treating preeclampsia include assessing gene expression levels in the subject, identifying the subject as having preeclampsia or being at risk of having preeclampsia and administering a preeclampsia therapy. Also provided are pharmaceutical compositions. The pharmaceutical compositions include a drug described herein in an amount effective to modulate gene expression levels in a subject, where the pharmaceutical composition is adapted for intravaginal administration of the drug to the subject. Kits that find use in practicing the methods of the present disclosure are also provided.

[0011] BRIEF DESCRIPTION OF THE FIGURES FIGS. 1A-1D: Transcriptomics analysis leads to characterization of preeclampsia pathophysiology, biomarker identification and candidate drug discovery. (FIG. 1A) Six publicly available placental datasets were collected from the Gene Expression Omnibus (GEO) to investigate the molecular underpinnings of preeclampsia. Meta-analysis was employed to define a large, comprehensive preeclampsia-specific disease signature (left panel). The MINT integration method was used to derive a concise predictive gene signature optimized for biomarker discovery (top portions of left and right panels). In parallel, meta-analysis was also used for pathway activity and cell type analyses to characterize the pathophysiology of the condition (bottom portions of left and right panels). (FIG. IB) Key genes from the MINT signature were then analyzed in blood to identify robust candidate biomarkers. (FIG. 1C) The broader meta-analysis signature served as the foundation for the drug repurposing analysis, leading to the identification of 63 candidate therapeutics forAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) preeclampsia. (FIG. 1 D) Lansoprazole, the top-ranked candidate, was validated for efficacy in a preeclampsia mouse model, reinforcing its potential for future clinical applications.

[0012] FIGS. 2A-2E: Cross-tissue transcriptomics analysis of early-onset preeclampsia identifies key pathways, cell types and biomarkers. (FIG. 2A) Using the MINT method, a concise, predictive gene signature for preeclampsia was identified from the six placental datasets. This 23-gene signature includes several well-established biomarkers such as FLT1, along with ENG, LEP, and PAPPA2, all known to be implicated in preeclampsia or pregnancy-related processes. Additionally, less-studied genes such as BCL6 and NEK11 emerged as potential novel biomarkers. (FIG. 2B) To assess the biomarker potential of the MINT signature, a longitudinal blood dataset was analyzed to evaluate expression changes over the course of pregnancies affected by preeclampsia versus controls. Seven of the 23 MINT genes showed significant differential expression (p <0.05), with BCL6 and NEK11 displaying interesting trends. (FIG. 2C) Meta-analysis was employed to define a larger, more comprehensive preeclampsia gene signature, integrating results from the six datasets. The volcano plot displays the final signature, which consists of 1,010 differentially expressed genes after filtering for FDR <0.05, significance in at least two datasets, and an absolute effect size >1. Pathway analysis using ssGSEA combined with meta-analysis identified significantly deregulated pathways in preeclampsia. (FIG. 2D) The bar plot highlights upregulated pathways, including hypoxia and leptin signaling, both well-established in preeclampsia pathophysiology, alongside immune and inflammatory pathways. Downregulated pathways were predominantly metabolic, reflecting disruptions in placental metabolism. (FIG. 2E) Cell-mixture deconvolution was performed with meta-analysis to identify differentially abundant cell types in the placentas of preeclampsia cases versus controls. Immune cell populations, including neutrophils, M2 macrophages, and B cells, showed significant changes, highlighting their roles in the immune dysregulation and inflammatory polarization that characterize preeclampsia.

[0013] FIGS. 3A-3C: Computational drug repurposing identifies lansoprazole as the top candidate for preeclampsia treatment. (FIG. 3A) Using the meta-analysis gene signature as input, a drug repurposing pipeline was employed that utilizes a nonparametric rank-based method to assess the concordance between disease-associated gene expression profiles and drug-induced expression signatures. After filtering for statistical significance and CMap scores <0, 63 drugs predicted to reverse the preeclampsia signature were identified. (FIG.

[0014] 3B) Among the 63 drugs identified, the top-ranked candidate was lansoprazole, a widely available over-the-counter proton pump inhibitor classified as pregnancy category B, suggesting it is safe for use during pregnancy. (FIG. 3C) SPOKE knowledge network reveals potential mechanistic links between lansoprazole and preeclampsia treatment. The networkAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) highlights relationships among compounds, genes, diseases, and pharmacologic classes using shortest paths. Lansoprazole is connected to preeclampsia through key gene nodes, including FLT1, VEGFA, and PGF A specific pathway, "Lansoprazole -DOWNREGULATES^ VEGFA (Gene) ^(Gene Product) UPREGULATES(Gene)- FLT1 (Gene) <— ASSOCIATES- pre-eclampsia," illustrates a potential mechanism where FLT1, associated with preeclampsia, upregulates VEGFA, which is subsequently downregulated by lansoprazole. Nodes indicate genes, diseases (star shape), pharmacologic classes (blue shape), and compounds (horizontal line shape), with edge types reflecting distinct biological and pharmacological relationships (C).

[0015] FIGS. 4A-4B: Partial transient maternal FOXP3+ Treg depletion selectively induces sFLT1. (FIG. 4A) Breeding scheme and experimental schematic were FOXP3DTR / WTor FOXP3WT / WTfemale mice each on the C57BL / 6 background midgestation during allogeneic pregnancy sired by males on the Balb / c background are administered daily diphtheria toxin (DT) from embryonic day E11.5 to E13.5 to partially deplete maternal FOXP3+ Tregs. (FIG.

[0016] 4B) Serum sFLT1 and CRP levels after initiating DT treatment for each group of mice. Error bars represent mean ± SEM.

[0017] FIGS. 5A-5C: Lansoprazole protects against fetal wastage triggered partial transient maternal FOXP3 cell depletion. (FIG. 5A) Breeding scheme and experimental schematic were allogeneic pregnancy in FOXP3DTR / WTfemale mice on the C57BU6 background are sired by Act-OVA males on the Balb / c background transforming OVA into a surrogate fetal antigen. (FIG. 5B) Percent fetal wastage (top graph) and number of live concepti per litter (bottom graph) for FOXP3DTR / WTmidgestation mice treated with DT alone or DT plus lansoprazole. (FIG. 5C) CD8+ T cells with fetal-OVA specificity identified by H-2Kb:OVA257-264 tetramer staining among splenocytes (top graph) or decidual leukocytes (bottom graph) for FOXP3DTR / WTmidgestation mice treated with DT alone or DT plus lansoprazole. Error bars represent mean ± SEM. ns, not significant; *p <0.05; **p <0.01 ; ***p <0.001. Error bars represent mean ± SEM.

[0018] FIGS. 6A-6B: Projection of latent structures (PLS) plots from the MINT sPLS-DA analysis for preeclampsia datasets. (FIG. 6A) Individual PLS plots for each of the six placental datasets (GSE74341 , GSE75010, GSE25906, GSE114691, GSE218039, and GSE54618). The x- and y-axes represent the first two latent components, with each point representing a sample. MINT successfully distinguishes between preeclampsia and control groups within individual datasets, despite heterogeneity between studies. (FIG. 6B) Combined projection of all six datasets after MINT integration. The x- and y-axes represent the first two common latent components derived from the integrated data, and shaped by dataset. The ellipses represent the 95% confidence regions for each condition. This plot demonstrates successful integration of multi-study data, showing clear separation betweenAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) preeclampsia and control samples, validating MINT'S capability to adjust for study-specific biases while preserving disease-specific signals.

[0019] FIG. 7: Longitudinal sampling timeline of blood draws for the GSE149437 dataset. The x-axis represents the gestational age (GA) at the time of each blood draw, while the y-axis shows individual participants. Each horizontal line corresponds to a participant, with symbols indicating key events: diagnosis (circles), delivery (triangles), and instances where both diagnosis and delivery occurred on the same day (squares). Blood draws are represented by tick marks along the lines. This longitudinal structure captures multiple sampling points per participant, allowing for the dynamic analysis of gene expression changes over time and comparison between preeclamptic and control pregnancies.

[0020] FIGS. 8A-8D: Sensitivity analysis removing pre-term birth signal from preeclampsia signature. (FIG. 8A) Volcano plot showing the results of meta-analysis for the preterm birthspecific signature. The x-axis represents the effect size, and the y-axis represents the -log10(FDR) of the meta-analysis. Highlighted differentially expressed genes (DEGs)are downregulated or upregulated. (FIG. 8B) Venn diagrams comparing differentially expressed genes (DEGs) between the preeclampsia-specific signature and the preterm birth-specific signature. The top diagram shows overlap among downregulated genes, and the bottom diagram shows overlap among upregulated genes. (FIG. 8C) Correlation between CMap scores of the drug candidates identified from the preeclampsia analysis before and after removing the preterm birth signature. The high correlation (R = 0.97, p <2.2e-16) demonstrates that the drug predictions are nearly identical in both cases, confirming that the preeclampsia drug repurposing results are not influenced by signals associated with preterm birth. (FIG. 8D) Venn diagram showing the overlap of drug candidates identified for preeclampsia before and after removing the preterm birth signature. Of the 63 drugs identified for preeclampsia, 59 overlapped with the candidates identified after adjusting for the preterm birth signal, indicating high consistency in the drug repurposing results and further validating the robustness of the preeclampsia-specific signature.

[0021] DETAILED DESCRIPTION

[0022] As reviewed above, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia. Methods of modulating gene expression levels include administering to the subject identified as having preeclampsia or being at risk of having preeclampsia a drug described herein in an amount effective to modulate gene expression levels in the subject. Also provided are methods of treating preeclampsia in a subject. Methods of treating preeclampsia include assessing geneAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) expression levels in the subject, identifying the subject as having preeclampsia or being at risk of having preeclampsia and administering a preeclampsia therapy. Also provided are pharmaceutical compositions. The pharmaceutical compositions include a drug described herein in an amount effective to modulate gene expression levels in a subject, where the pharmaceutical composition is adapted for intravaginal administration of the drug to the subject. Kits that find use in practicing the methods of the present disclosure are also provided.

[0023] Before the methods, compositions and kits of the present disclosure are described in greater detail, it is to be understood that the methods, compositions and kits are not limited to particular embodiments described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the methods, compositions and kits will be limited only by the appended claims.

[0024] Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limit of that range and any other stated or intervening value in that stated range, is encompassed within the methods, compositions and kits. The upper and lower limits of these smaller ranges may independently be included in the smaller ranges and are also encompassed within the methods, compositions and kits, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the methods, compositions and kits.

[0025] Certain ranges are presented herein with numerical values being preceded by the term “about.” The term “about” is used herein to provide literal support for the exact number that it precedes, as well as a number that is near to or approximately the number that the term precedes. In determining whether a number is near to or approximately a specifically recited number, the near or approximating unrecited number may be a number which, in the context in which it is presented, provides the substantial equivalent of the specifically recited number.

[0026] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the methods, compositions and kits belong. Although any methods, compositions and kits similar or equivalent to those described herein can also be used in the practice or testing of the methods, compositions and kits, representative illustrative methods, compositions and kits are now described.Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) All publications and patents cited in this specification are herein incorporated by reference as if each individual publication or patent were specifically and individually indicated to be incorporated by reference and are incorporated herein by reference to disclose and describe the materials and / or methods in connection with which the publications are cited. The citation of any publication is for its disclosure prior to the filing date and should not be construed as an admission that the present methods, compositions and kits are not entitled to antedate such publication, as the date of publication provided may be different from the actual publication date which may need to be independently confirmed.

[0027] It is noted that, as used herein and in the appended claims, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise. It is further noted that the claims may be drafted to exclude any optional element. As such, this statement is intended to serve as antecedent basis for use of such exclusive terminology as “solely,” “only” and the like in connection with the recitation of claim elements, or use of a “negative” limitation.

[0028] It is appreciated that certain features of the methods, compositions and kits, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the methods, compositions and kits, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable sub-combination. All combinations of the embodiments are specifically embraced by the present disclosure and are disclosed herein just as if each and every combination was individually and explicitly disclosed, to the extent that such combinations embrace operable processes and / or compositions. In addition, all sub-combinations listed in the embodiments describing such variables are also specifically embraced by the present methods, compositions and kits and are disclosed herein just as if each and every such sub-combination was individually and explicitly disclosed herein.

[0029] As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present methods. Any recited method can be carried out in the order of events recited or in any other order that is logically possible.

[0030] METHODS

[0031] Aspects of the present disclosure include methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia. As demonstrated in the Experimental section herein, the inventors elucidated geneAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) expression signatures for patients with preeclampsia (e.g., early-onset preeclampsia), and further identified the drugs provided in FIG. 3B as those known to have opposite transcriptional effects with respect to the preeclampsia (e.g., early-onset preeclampsia) gene expression signatures. That is, the drugs in FIG. 3B are reasonably expected to normalize (partially or completely) gene expression patterns associated with preeclampsia, and therefore find use in modulating gene expression levels in subjects identified as having preeclampsia or being at risk of having preeclampsia, e.g., to treat or prevent preeclampsia. Moreover, as proof of concept and also demonstrated in the Experimental section herein, a drug identified by the inventors as having an opposite transcriptional effect with respect to the preeclampsia gene expression signature was determined to be efficacious in an established animal model of preeclampsia. Accordingly, in certain embodiments, the methods find use in treating preeclampsia, e.g., resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject. Details regarding the methods of the present disclosure will now be provided.

[0032] The types of subjects may vary and generally include females (e.g., human females) that are pregnant or have been recently pregnant. For example, the subject may be a human female (e.g., pregnant human female) of age 15-45, e.g., 20-45, such as a human female 20-40 years of age. In some embodiments, the subject is pregnant. In some embodiments, the subject (e.g., human female) is 20 to 40 weeks pregnant (e.g., 20 weeks pregnant, 21 weeks pregnant, 22 weeks pregnant, 23 weeks pregnant, 24 weeks pregnant, 25 weeks pregnant, 26 weeks pregnant, 27 weeks pregnant, 28 weeks pregnant, 29 weeks pregnant, 30 weeks pregnant, 31 weeks pregnant, 32 weeks pregnant, 33 weeks pregnant, 34 weeks pregnant, 35 weeks pregnant, 36 weeks pregnant, 37 weeks pregnant, 38 weeks pregnant, 39 weeks pregnant or 40 weeks pregnant) including, e.g., 20 to 34 weeks pregnant, 26 to 34 weeks pregnant or 30 to 34 weeks pregnant. In some embodiments, the subject may be identified as having early-onset preeclampsia or at risk of having early-onset preeclampsia. By “early-onset preeclampsia” it is meant the subject is identified as having preeclampsia prior to 34 weeks of pregnancy. In some embodiments, the subject has recently been pregnant (e.g., recently delivered a baby). In some embodiments, the subject is identified as having postpartum preeclampsia or being at risk of having postpartum preeclampsia. By “postpartum preeclampsia” it is meant the subject is identified as having preeclampsia after giving birth (e.g., one day to two weeks after giving birth). In some embodiments, the subject identified as having postpartum preeclampsia or being at risk of having postpartum preeclampsia has given birth in the range of 0 days to 2 weeks ago including, e.g., 1 day to 2 weeks ago, 2 days to 2 weeks ago, 3 days to 1 week ago or 3 days to 6 days ago.Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) In some embodiments, the methods include administering to the subject identified as having preeclampsia or being at risk of having preeclampsia a drug disclosed herein (e.g., a drug from FIG. 3B) in an amount effective to modulate gene expression levels in the subject. By “a subject identified as having preeclampsia or being at risk of having preeclampsia” is meant it is known, prior to administering the drug, that the subject has preeclampsia or is at risk of having preeclampsia, and the drug is administered to the subject on the basis that the subject has preeclampsia or is at risk of having preeclampsia.

[0033] According to some embodiments, the methods further comprise identifying the subject as having preeclampsia or being at risk of having preeclampsia. In some embodiments, the subject was identified as having preeclampsia or being at risk of having preeclampsia based on the expression levels of one or more of: FMS related receptor tyrosine kinase 1 (FLT1 ), leptin (LEP), endoglin (ENG), follistatin-like 3 (FSTL3), pregnancy-associated plasma protein A2 (PAPPA2), B-cell lymphoma 6 (BCL6) and never in mitosis gene A-related kinase (NEK11). In some embodiments, the gene expression levels are increased or decreased compared to control expression levels.

[0034] In some embodiments, the subject was identified as having preeclampsia or being at risk of having preeclampsia based on the expression level of FLT1 (e.g., an increased expression level of FLT1). In some embodiments, the subject’s FLT1 expression level was increased compared to a control FLT1 expression level (e.g., a predetermined control FLT1 expression level). In some embodiments, the subject was identified as having preeclampsia or being at risk of having preeclampsia based on the expression level of LEP (e.g., an increased expression level of LEP). In some embodiments, the subject’s LEP expression level was increased compared to a control LEP expression level (e.g., a predetermined control LEP expression level). In some embodiments, the subject was identified as having preeclampsia or being at risk of having preeclampsia based on the expression level of ENG (e.g., an increased expression level of ENG). In some embodiments, the subject’s ENG expression level was increased compared to a control ENG expression level (e.g., a predetermined control ENG expression level). In some embodiments, the subject was identified as having preeclampsia or being at risk of having preeclampsia based on the expression level of FSTL3 (e.g., an increased expression level of FSTL3). In some embodiments, the subject’s FSTL3 expression level was increased compared to a control FSTL3 expression level (e.g., a predetermined control FSTL3 expression level). In some embodiments, the subject was identified as having preeclampsia or being at risk of having preeclampsia based on the expression level of PAPPA2 (e.g., an increased expression level of PAPPA2). In some embodiments, the subject’s PAPPA2 expression level was increased compared to a control PAPPA2 expression level (e.g., a predetermined control PAPPA2Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) expression level). In some embodiments, the subject was identified as having preeclampsia or being at risk of having preeclampsia based on the expression level of BCL6 (e.g., an decreased expression level of BCL6). In some embodiments, the subject’s BCL6 expression level was decreased compared to a control BCL6 expression level (e.g., a predetermined control BCL6 expression level). In some embodiments, the subject was identified as having preeclampsia or being at risk of having preeclampsia based on the expression level of NEK11 (e.g., an increased expression level of NEK11). In some embodiments, the subject’s NEK11 expression level was increased compared to a control NEK11 expression level (e.g., a predetermined control NEK11 expression level).

[0035] In some embodiments, methods of identifying a subject as having preeclampsia or being at risk of having preeclampsia include identifying and / or diagnosing a subject based upon the subject’s symptoms. Such symptoms include, but are not limited to, high blood pressure (hypertension), protein in urine (proteinuria), decreased levels of platelets in the blood (thrombocytopenia), increased liver enzymes, sudden swelling (e.g., sudden swelling in the face, hands and feet), severe headaches, changes in vision (e.g., blurred vision, vision with flashing lights, temporary loss of vision, light sensitivity), abdominal pain (e.g., right-side abdominal pain), nausea, vomiting, shortness of breath and decreased urine output. In some embodiments, the subject is identified as having preeclampsia based upon a combination of two or more symptoms (e.g., hypertension and proteinuria). In some embodiments, the subject is identified as being at risk of having preeclampsia based on one or more risk factors. Risk factors include, but are not limited to, preeclampsia in a previous pregnancy, family history of preeclampsia, being pregnant with more than one baby, chronic high blood pressure, type 1 or type 2 diabetes before pregnancy, kidney disease, autoimmune disorders, use of in vitro fertilization, obesity, maternal age of 35 or older and more than 10 years since a previous pregnancy.

[0036] In some embodiments, the drug (e.g., a drug from FIG. 3B) is administered in an amount effective to modulate gene expression levels in the subject. By “effective amount” or “therapeutically effective amount” is meant a dosage sufficient to produce a desired result, e.g., modulate gene expression levels in the subject (e.g., an amount effective to normalize (partially or completely) the subject’s gene expression patterns associated with preeclampsia or risk or preeclampsia), an amount sufficient to effect beneficial or desired therapeutic (including preventative) results, such as a reduction in a symptom of preeclampsia. For example, the drug may be administered in an amount effective to modulate gene expression resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject. Non-limiting examples of symptoms which may be ameliorated according to the methods of the present disclosure include hypertension, proteinuria, swelling headaches, changes inAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) vision, abdominal pain, nausea, vomiting and any combination thereof. The drugs provided in FIG. 3B are known, as is information regarding their pharmacokinetics and the like which a physician may use to determine a suitable dosage and / or dosage regimen to modulate (e.g., normalize partially or completely) gene expression levels associated with preeclampsia as desired in the subject.

[0037] In some embodiments, the methods include methods of treating preeclampsia in a subject. By “treat” or “treatment” is meant at least an amelioration of the symptoms associated with the preeclampsia, where amelioration is used in a broad sense to refer to at least a reduction in the magnitude of a parameter, e.g., symptom, associated with the preeclampsia being treated. As such, treatment also includes situations where the preeclampsia, or at least symptoms associated therewith, are completely inhibited, e.g., prevented from happening, or stopped, e.g., terminated, such that the subject no longer suffers from the preeclampsia, or at least the symptoms that characterize the preeclampsia.

[0038] Methods of treating preeclampsia in a subject include assessing gene expression levels in the subject of one or more of: FMS related receptor tyrosine kinase 1 (FLT1), leptin (LEP), endoglin (ENG), follistatin-like 3 (FSTL3), pregnancy-associated plasma protein A2 (PAPPA2), B-cell lymphoma 6 (BCL6) and never in mitosis gene A-related kinase (NEK11), identifying the subject as having preeclampsia or being at risk of having preeclampsia based on the expression levels, and administering a preeclampsia therapy to the subject in an amount effective to treat the preeclampsia, wherein the preeclampsia therapy comprises administering a drug. In some embodiments, the preeclampsia therapy includes administering a drug, where the drug is a drug from FIG. 3B.

[0039] Dosing of a drug may be dependent on severity and responsiveness of the disease state to be treated. Optimal dosing schedules can be calculated from measurements of drug accumulation in the body of the subject. The administering physician can determine optimum dosages, dosing methodologies and repetition rates. Optimum dosages may vary depending on the relative potency of individual therapeutic agents, and can generally be estimated based on ECsoS found to be effective in in vitro and in vivo animal models, etc. In general, dosage is from about 0.01 pg to about 100 g per kg of body weight, and may be given once or more daily, weekly, monthly or yearly. In certain aspects, the dosage is from about 1 pg / kg to 100 mg / kg or more, depending on the factors mentioned above. The treating physician can estimate repetition rates for dosing based on measured residence times and concentrations of the therapeutic agent in bodily fluids or tissues. Following successful treatment, it may be desirable to have the subject undergo maintenance therapy to prevent the recurrence of the disease state, where the therapeutic agent is administered in maintenance doses, ranging from about 0.01 pg to about 100 g per kg of body weight, onceAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) or more daily, to once every several months, once every six months, once every year, or at any other suitable frequency.

[0040] The therapeutic methods of the present disclosure may include administering a single type of active agent to the subject, or may include administering two or more types of active agents to the subject separately or by administration of a cocktail of different active agents. In some embodiments, a drug from FIG. 3B is the only active agent administered to the subject. In other embodiments, two or more drugs independently selected from FIG. 3B may be administered to the subject, e.g., two or more, three or more, four or more, or five or more drugs from FIG. 3B. According to some embodiments, one or more (e.g., two or more) drugs from FIG. 3B are administered to the subject, in combination with an existing treatment for preeclampsia. Such existing treatments include, but are not limited to, administration of an effective amount of a blood pressure medication (e.g., methyldopa, labetalol, hydralazine, nefidipine), magnesium sulfate, steroids (e.g., corticosteroids), or any combination thereof.

[0041] The one or more drugs may be administered to an subject using any available method and route suitable for drug delivery, including in vivo and ex vivo methods, as well as systemic and localized routes of administration. Conventional and pharmaceutically acceptable routes of administration include oral and parenteral routes of administration. Parenteral routes of administration of interest include, but are not limited to, injection (e.g., intravenous, intraarterial, local, subcutaneous, or intramuscular injection), intrauterine, intravaginal, intranasal, intra-tracheal, intradermal, topical application, ocular, nasal, and other parenteral routes of administration. Routes of administration may be combined, if desired, or adjusted depending upon the drug and / or the desired effect. The drug may be administered in a single dose or in multiple doses. In some embodiments, the drug is administered intravenously. In some embodiments, the drug or pharmaceutical composition is administered by injection, e.g., for systemic delivery (e.g., intravenous infusion) or to a local site.

[0042] In certain embodiments, the drug is administered to the subject by intravaginal administration. Non-limiting examples of intravaginal administration include administering (e.g., by placement inside the vagina) a vaginal suppository comprising the drug releasable therefrom or a vaginal ring comprising the drug releasable therefrom to the subject. Approaches and considerations for intravaginal drug delivery are known and described, e.g., in Woolfson & Gallagher (2000) Grit Rev Ther Drug Carrier Syst. 17(5):509-55; Friend (2011) Drug Deliv Transl Res. 1 (3) : 185-93; Hussain & Ahsan (2005) J Control Release. 103(2):301 -13; Mohideen et al. (2017) Biomaterials. 144:144-154; das Neves & Bahia (2006) Int J Pharm. 318(1 -2):1 -14; Alexander et al. (2004) Fertil Steril. 82(1 ):1 -12; and de Araujo Pereira & Bruschi (2012) Drug Dev Ind Pharm. 38(6):643-52; the disclosures of which are incorporated herein by reference in their entireties for all purposes. For example, knownAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) approaches and formulations that may be employed for intravaginal delivery of one or more drugs from FIG. 3B (e.g., lansoprazole, methotrexate, halofantrine, streptozocin, levopropoxyphene, domperidone, fulvestrant, haloperidol, metformin, estradiol, sirolimus, fludrocortisone, dapsone, rosiglitazone, guanabenz) include hydrogels, vaginal tablets, pessaries / suppositories, particulate systems, and intravaginal rings.

[0043] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or being at risk of having preeclampsia lansoprazole in an amount effective to modulate gene expression levels in the subject. The lansoprazole may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the lansoprazole is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0044] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or being at risk of having preeclampsia methotrexate in an amount effective to modulate gene expression levels in the subject. The methotrexate may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the methotrexate is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0045] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or being at risk of having preeclampsia halofantrine in an amount effective to modulate gene expression levels in the subject. The halofantrine may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the halofantrine is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0046] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or being at risk of having preeclampsia streptozocin in an amount effective to modulate geneAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) expression levels in the subject. The streptozocin may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the streptozocin is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0047] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or being at risk of having preeclampsia levopropoxyphene in an amount effective to modulate gene expression levels in the subject. The levopropoxyphene may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the levopropoxyphene is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0048] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or being at risk of having preeclampsia domperidone in an amount effective to modulate gene expression levels in the subject. The domperidone may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the domperidone is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0049] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or being at risk of having preeclampsia fulvestrant in an amount effective to modulate gene expression levels in the subject. The fulvestrant may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the fulvestrant is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0050] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or beingAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) at risk of having preeclampsia haloperidol in an amount effective to modulate gene expression levels in the subject. The haloperidol may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the haloperidol is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0051] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or being at risk of having preeclampsia metformin in an amount effective to modulate gene expression levels in the subject. The metformin may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the metformin is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0052] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or being at risk of having preeclampsia estradiol in an amount effective to modulate gene expression levels in the subject. The estradiol may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the estradiol is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0053] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or being at risk of having preeclampsia sirolimus in an amount effective to modulate gene expression levels in the subject. The sirolimus may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the sirolimus is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0054] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or beingAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) at risk of having preeclampsia fludrocortisone in an amount effective to modulate gene expression levels in the subject. The fludrocortisone may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the fludrocortisone is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0055] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or being at risk of having preeclampsia dapsone in an amount effective to modulate gene expression levels in the subject. The dapsone may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the dapsone is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0056] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or being at risk of having preeclampsia rosiglitazone in an amount effective to modulate gene expression levels in the subject. The rosiglitazone may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the rosiglitazone is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.

[0057] In certain embodiments, provided are methods of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the methods comprising administering to the subject identified as having preeclampsia or being at risk of having preeclampsia guanabenz in an amount effective to modulate gene expression levels in the subject. The guanabenz may be administered in an amount effective to normalize (partially or completely) the gene expression pattern associated with preeclampsia as desired in the subject. According to some embodiments, the guanabenz is administered in an amount effective to treat the preeclampsia of the subject, e.g., by resulting in at least an amelioration of one or more symptoms of preeclampsia in the subject.Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0)

[0058] COMPOSITIONS

[0059] Aspects of the present disclosure further include compositions. In some embodiments, the compositions find use, e.g., in practicing the methods of the present disclosure.

[0060] In certain embodiments, a composition of the present disclosure comprises one or more drugs described elsewhere herein, including any of the drugs from FIG. 3B. Non-limiting examples of such drugs which may be comprised in a composition (e.g., a pharmaceutical composition) include lansoprazole, methotrexate, halofantrine, streptozocin, levopropoxyphene, domperidone, fulvestrant, haloperidol, metformin, estradiol, sirolimus, fludrocortisone, dapsone, rosiglitazone or guanabenz, or any combination thereof.

[0061] According to some embodiments, a composition of the present disclosure includes the one or more drugs present in a liquid medium. The liquid medium may be an aqueous liquid medium, such as water, a buffered solution, or the like. One or more additives such as a salt (e.g., NaCI, MgCh, KCI, MgSOzi), a buffering agent (a Tris buffer, N-(2-Hydroxyethyl)piperazine-N'-(2-ethanesulfonic acid) (HEPES), 2-(N-Morpholino)ethanesulfonic acid (MES), 2-(N-Morpholino)ethanesulfonic acid sodium salt (MES), 3-(N-Morpholino)propanesulfonic acid (MOPS), N-tris[Hydroxymethyl]methyl-3-aminopropanesulfonic acid (TAPS), etc.), a solubilizing agent, a detergent (e.g., a non-ionic detergent such as Tween-20, etc.), a nuclease inhibitor, a protease inhibitor, glycerol, a chelating agent, and the like may be present in such compositions.

[0062] Pharmaceutical compositions are also provided. The pharmaceutical compositions of the present disclosure include one or more drugs from FIG. 3B and a pharmaceutically acceptable carrier. In certain embodiments, a pharmaceutical composition of the present disclosure comprises lansoprazole, methotrexate, halofantrine, streptozocin, levopropoxyphene, domperidone, fulvestrant, haloperidol, metformin, estradiol, sirolimus, fludrocortisone, dapsone, rosiglitazone or guanabenz, or any combination thereof. In some instances, a pharmaceutical composition of the present disclosure comprises lansoprazole (e.g., as the only drug in the composition, or in combination with one or more additional drugs). Any pharmaceutical composition of the present disclosure may include - in addition to the one or more drugs from FIG. 3B - an additional agent that finds use, e.g., in treating preeclampsia, e.g., a blood pressure medication (e.g., methyldopa, labetalol, hydralazine, nefidipine), magnesium sulfate, steroids (e.g., corticosteroids), or any combination thereof. The one or more drugs from FIG. 3B can be incorporated into a variety of formulations for administration to a subject. More particularly, the one or more drugs from FIG. 3B can be formulated into pharmaceutical compositions by combination with appropriate, pharmaceutically acceptable excipients or diluents, and may be formulated into preparationsAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) in solid, semi-solid, liquid or gaseous forms, such as tablets, capsules, powders, granules, ointments, solutions, injections, inhalants and aerosols.

[0063] Formulations of the one or more drugs from FIG. 3B suitable for administration to an subject (e.g., suitable for human administration) are generally sterile and may further be free of detectable pyrogens or other contaminants contraindicated for administration to a subject according to a selected route of administration. The following methods and carriers / excipients are merely examples and are in no way limiting.

[0064] For oral preparations, the one or more drugs from FIG. 3B can be used alone or in combination with appropriate additives to make tablets, powders, granules or capsules, for example, with conventional additives, such as lactose, mannitol, corn starch or potato starch; with binders, such as crystalline cellulose, cellulose derivatives, acacia, corn starch or gelatins; with disintegrators, such as corn starch, potato starch or sodium carboxymethylcellulose; with lubricants, such as talc or magnesium stearate; and if desired, with diluents, buffering agents, moistening agents, preservatives and flavoring agents.

[0065] The one or more drugs from FIG. 3B can be formulated for parenteral (e.g., intravenous, intra-arterial, intraosseous, intramuscular, intracerebral, intracerebroventricular, intracranial, intrathecal, subcutaneous, etc.) administration. In some embodiments, the one or more drugs from FIG. 3B is formulated for intrauterine (e.g., in the form of an intrauterine device (IUD) comprising the one or more drugs releasable therefrom), intravaginal (e.g., in the form of a vaginal suppository or vaginal ring comprising the one or more drugs releasable therefrom), oral, parenteral, intranasal, intrathecal, or transdermal administration. In some embodiments, the composition is formulated as a vaginal suppository. In some embodiments, the composition is a vaginal ring. In some embodiments, the one or more drugs from FIG.

[0066] 3B is formulated for injection by dissolving, suspending or emulsifying the one or more drugs in an aqueous or non-aqueous solvent, such as vegetable or other similar oils, synthetic aliphatic acid glycerides, esters of higher aliphatic acids or propylene glycol; and if desired, with conventional additives such as solubilizers, isotonic agents, suspending agents, emulsifying agents, stabilizers and preservatives.

[0067] Pharmaceutical compositions that include the one or more drugs from FIG. 3B may be prepared by mixing the one or more drugs having the desired degree of purity with optional physiologically acceptable carriers, excipients, stabilizers, surfactants, buffers and / or tonicity agents. Acceptable carriers, excipients and / or stabilizers are nontoxic to recipients at the dosages and concentrations employed, and include buffers such as phosphate, citrate, and other organic acids; antioxidants including ascorbic acid, glutathione, cysteine, methionine and citric acid; preservatives (such as ethanol, benzyl alcohol, phenol, m-cresol, p-chlor-m-cresol, methyl or propyl parabens, benzalkonium chloride, or combinations thereof); aminoAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) acids such as arginine, glycine, ornithine, lysine, histidine, glutamic acid, aspartic acid, isoleucine, leucine, alanine, phenylalanine, tyrosine, tryptophan, methionine, serine, proline and combinations thereof; monosaccharides, disaccharides and other carbohydrates; low molecular weight (less than about 10 residues) polypeptides; proteins, such as gelatin or serum albumin; chelating agents such as EDTA; sugars such as trehalose, sucrose, lactose, glucose, mannose, maltose, galactose, fructose, sorbose, raffinose, glucosamine, N-methylglucosamine, galactosamine, and neuraminic acid; and / or non-ionic surfactants such as Tween, Brij Pluronics, Triton-X, or polyethylene glycol (PEG).

[0068] The pharmaceutical composition may be in a liquid form, a lyophilized form or a liquid form reconstituted from a lyophilized form, wherein the lyophilized preparation is to be reconstituted with a sterile solution prior to administration. The standard procedure for reconstituting a lyophilized composition is to add back a volume of pure water (typically equivalent to the volume removed during lyophilization); however solutions comprising antibacterial agents may be used for the production of pharmaceutical compositions for parenteral administration.

[0069] An aqueous formulation of the one or more drugs from FIG. 3B may be prepared in a pH-buffered solution, e.g., at pH ranging from about 4.0 to about 7.0, or from about 5.0 to about 6.0, or alternatively about 5.5. Examples of buffers that are suitable for a pH within this range include phosphate-, histidine-, citrate-, succinate-, acetate-buffers and other organic acid buffers. The buffer concentration can be from about 1 mM to about 100 mM, or from about 5 mM to about 50 mM, depending, e.g., on the buffer and the desired tonicity of the formulation.

[0070] A tonicity agent may be included in the formulation to modulate the tonicity of the formulation. Example tonicity agents include sodium chloride, potassium chloride, glycerin and any component from the group of amino acids, sugars as well as combinations thereof. In some embodiments, the aqueous formulation is isotonic, although hypertonic or hypotonic solutions may be suitable. The term "isotonic" denotes a solution having the same tonicity as some other solution with which it is compared, such as physiological salt solution or serum. Tonicity agents may be used in an amount of about 5 mM to about 350 mM, e.g., in an amount of 100 mM to 350 mM.

[0071] A surfactant may also be added to the formulation to reduce aggregation and / or minimize the formation of particulates in the formulation and / or reduce adsorption. Example surfactants include polyoxyethylensorbitan fatty acid esters (Tween), polyoxyethylene alkyl ethers (Brij), alkylphenylpolyoxyethylene ethers (Triton-X), polyoxyethylenepolyoxypropylene copolymer (Poloxamer, Pluronic), and sodium dodecyl sulfate (SDS). Examples of suitable polyoxyethylenesorbitan-fatty acid esters are polysorbate 20, (soldAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) under the trademark Tween 20™) and polysorbate 80 (sold under the trademark Tween 80™). Examples of suitable polyethylene-polypropylene copolymers are those sold under the names Pluronic® F68 or Poloxamer 188™. Examples of suitable Polyoxyethylene alkyl ethers are those sold under the trademark Brij™ . Example concentrations of surfactant may range from about 0.001% to about 1% w / v.

[0072] A lyoprotectant may also be added in order to protect the one or more drugs from FIG.

[0073] 3B against destabilizing conditions during a lyophilization process. For example, known lyoprotectants include sugars (including glucose and sucrose); polyols (including mannitol, sorbitol and glycerol); and amino acids (including alanine, glycine and glutamic acid). Lyoprotectants can be included in an amount of about 10 mM to 500 nM.

[0074] In some embodiments, the pharmaceutical composition includes the one or more drugs from FIG. 3B, and one or more of the above-identified agents (e.g., a surfactant, a buffer, a stabilizer, a tonicity agent) and is essentially free of one or more preservatives, such as ethanol, benzyl alcohol, phenol, m-cresol, p-chlor-m-cresol, methyl or propyl parabens, benzalkonium chloride, and combinations thereof. In other embodiments, a preservative is included in the formulation, e.g., at concentrations ranging from about 0.001 to about 2% (w / v).

[0075] KITS

[0076] Also provided by the present disclosure are kits. In some embodiments, the kits find use, e.g., in practicing the methods of the present disclosure.

[0077] In some embodiments, a kit of the present disclosure includes one or more of any of the drugs described elsewhere herein, including one or more drugs from FIG. 3B. Nonlimiting examples of such drugs which may be included in a kit of the present disclosure include lansoprazole, methotrexate, halofantrine, streptozocin, levopropoxyphene, domperidone, fulvestrant, haloperidol, metformin, estradiol, sirolimus, fludrocortisone, dapsone, rosiglitazone or guanabenz, or any combination thereof.

[0078] In some embodiments, a kit of the present disclosure includes a pharmaceutical composition including one or more drugs from FIG. 3B and a pharmaceutically acceptable carrier. For example, provided are kits that include any of the pharmaceutical compositions of the present disclosure, including any of the pharmaceutical compositions described in the Compositions section hereinabove. In some embodiments, a kit of the present disclosure includes a pharmaceutical composition that - in addition to the one or more drugs from FIG.

[0079] 3B - further includes an additional agent that finds use, e.g., in treating preeclampsia, e.g., a blood pressure medication (e.g., methyldopa, labetalol, hydralazine, nefidipine), magnesium sulfate, steroids (e.g., corticosteroids), or any combination thereof.Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) Kits for practicing the subject methods may include a quantity of the one or more drugs from FIG. 3B (and optionally, an additional agent as described above), present in unit dosages, e.g., vaginal suppositories, vaginal rings, ampoules, tablets, capsules, or a multidosage format. As such, in certain embodiments, the kits may include one or more (e.g., two or more) unit dosages (e.g., vaginal suppositories, vaginal rings, ampoules, tablets, capsules) of a pharmaceutical composition that includes the one or more drugs from FIG.

[0080] 3B.

[0081] The term “unit dosage”, as used herein, refers to physically discrete units suitable as unitary dosages for human and animal subjects, each unit containing a predetermined quantity of the composition calculated in an amount sufficient to produce the desired effect. The amount of the unit dosage depends on various factors, such as the particular one or more drugs from FIG. 3B employed, the effect to be achieved, and the pharmacodynamics associated with the one or more drugs, in the subject. In yet other embodiments, the kits may include a single multi dosage amount of a composition including the one or more drugs from FIG. 3B (and optionally, an additional agent as described above).

[0082] Components of the kits may be present in separate containers, or multiple components may be present in a single container. For example, in a kit that includes two or more drugs from FIG. 3B, the two or more drugs may be provided in the same composition (e.g., in one or more containers) or may be provided in separate compositions in separate containers. Suitable containers include individual tubes (e.g., vials), ampoules, sealed packages (e.g., containing one or more vaginal suppositories, vaginal rings, ampoules, tablets, capsules, and / or the like), etc.

[0083] A kit of the present disclosure may further include instructions. For example, a kit that includes one or more drugs from FIG. 3B may include instructions for administering the one or more drugs (e.g., present in one or more pharmaceutical compositions) to a subject identified as having preeclampsia or at risk of having preeclampsia.

[0084] The instructions may be recorded on a suitable recording medium. For example, the instructions may be printed on a substrate, such as paper or plastic, etc. As such, the instructions may be present in the kits as a package insert, in the labeling of the container of the kit or components thereof (i.e., associated with the packaging or sub-packaging) etc. In other embodiments, the instructions are present as an electronic storage data file present on a suitable computer readable storage medium, e.g., portable flash drive, DVD, CD-ROM, diskette, etc. In yet other embodiments, the actual instructions are not present in the kit, but means for obtaining the instructions from a remote source, e.g. via the internet, are provided. An example of this embodiment is a kit that includes a web address where the instructionsAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) can be viewed and / or from which the instructions can be downloaded. As with the instructions, the means for obtaining the instructions is recorded on a suitable substrate.

[0085] Non-limiting aspects and embodiments of the present disclosure are further disclosed in the following numbered clauses.

[0086] 1. A method of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the method comprising:

[0087] administering to the subject identified as having preeclampsia or being at risk of having preeclampsia a drug from FIG. 3B in an amount effective to modulate gene expression levels in the subject.

[0088] 2. The method according to clause 1, wherein the subject was identified as having preeclampsia or being at risk of having preeclampsia based on the expression levels of one or more of:

[0089] FMS related receptor tyrosine kinase 1 (FLT1), leptin (LEP), endoglin (ENG), follistatin-like 3 (FSTL3), pregnancy-associated plasma protein A2 (PAPPA2), B-cell lymphoma 6 (BCL6) and never in mitosis gene A-related kinase (NEK11 ).

[0090] 3. The method according to clause 1 or clause 2, wherein the modulation of gene expression levels results in at least an amelioration of one or more symptoms of preeclampsia in the subject or a prevention of one or more symptoms of preeclampsia in the subject.

[0091] 4. A method of treating preeclampsia in a subject, the method comprising:

[0092] assessing gene expression levels in the subject of one or more of:

[0093] FMS related receptor tyrosine kinase 1 (FLT1), leptin (LEP), endoglin (ENG), follistatin-like 3 (FSTL3), pregnancy-associated plasma protein A2 (PAPPA2), B-cell lymphoma 6 (BCL6) and never in mitosis gene A-related kinase (NEK11); identifying the subject as having preeclampsia or being at risk of having preeclampsia based on the gene expression levels; and

[0094] administering a preeclampsia therapy to the subject in an amount effective to treat the preeclampsia, wherein the preeclampsia therapy comprises administering a drug.

[0095] 5. The method of clause 4, wherein the drug is a drug from FIG. 3B.

[0096] 6. The method of clause 5, wherein the drug is lansoprazole.

[0097] 7. The method of any one of clauses 1-3, 5 or 6, wherein the drug from FIG. 3B is the only active agent administered to the subject.

[0098] 8. The method of any one of clauses 1-3, 5 or 6, wherein two or more drugs from FIG.

[0099] 3B are administered to the subject.Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) 9. The method according to any one of clauses 1 to 8, wherein the administering comprises administering the drug intravaginally.

[0100] 10. The method according to clause 9, wherein administering the drug intravaginally comprises administering a vaginal suppository comprising the drug to the subject.

[0101] 11. The method according to clause 9, wherein administering the drug intravaginally comprises administering a vaginal ring comprising the drug to the subject.

[0102] 12. The method according to any one of clauses 1 to 11 , wherein the drug is lansoprazole, methotrexate, halofantrine, streptozocin, levopropoxyphene, domperidone, fulvestrant, haloperidol, metformin, estradiol, sirolimus, fludrocortisone, dapsone, rosiglitazone or guanabenz.

[0103] 13. The method according to any one of clauses 1 to 11 , wherein the drug is lansoprazole.

[0104] 14. The method according to clause 1 or clause 2, wherein the drug is lansoprazole. 15. A pharmaceutical composition, comprising:

[0105] a drug from FIG. 3B in an amount effective to modulate gene expression levels in a subject, wherein the pharmaceutical composition is adapted for intravaginal administration of the drug to the subject.

[0106] 16. The pharmaceutical composition of clause 15, wherein the drug is lansoprazole, methotrexate, halofantrine, streptozocin, levopropoxyphene, domperidone, fulvestrant, haloperidol, metformin, estradiol, sirolimus, fludrocortisone, dapsone, rosiglitazone, or guanabenz.

[0107] 17. The pharmaceutical composition of clause 15, wherein the drug is lansoprazole. 18. The pharmaceutical composition of any one of clauses 15-17, wherein the composition is a vaginal suppository.

[0108] 19. The pharmaceutical composition of any one of clauses 15-17, wherein the composition is a vaginal ring.

[0109] 20. A kit comprising:

[0110] a pharmaceutical composition comprising a drug from FIG. 3B in an amount effective to modulate gene expression levels in a subject; and

[0111] instructions for administering the pharmaceutical composition to a subject identified as having preeclampsia or being at risk of having preeclampsia.

[0112] The following examples are offered by way of illustration and not by way of limitation.Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0)

[0113] EXPERIMENTAL

[0114] of Placenta Identifies Potential

[0115]

[0116] In this study, publicly available transcriptomics datasets were used to gain insights into the molecular underpinnings of preeclampsia and to identify therapeutic strategies through computational drug repurposing (FIG. 1). Six placental transcriptomics datasets from the GEO database were analyzed to identify robust biomarkers for early-onset (EO) preeclampsia, defined as onset at gestational age (GA) <34 weeks. These datasets included a total of 151 samples from women with EO preeclampsia and 96 preterm controls (GA <37 weeks), ensuring GA-matched comparisons. The datasets were generated from multiple sequencing technologies, including both microarray (GSE25906 (23), GSE74341 (24), GSE75010 (25), and GSE54618 (26)) and RNA-seq platforms (GSE114691 (27) and GSE218039 (28)). The distribution of samples across datasets ranged from 7 to 58 EO preeclampsia cases per study and 5 to 43 preterm controls (Table 1).

[0117] Study Sequencing EO preeclampsia Pre-term controls technology (ga <34 weeks) (ga <37 weeks) GSE25906 microarray (GPL6102) 10 5

[0118]

[0119]

[0120] Table 1. Overview of the six placental transcriptomics dataset. Six publicly available placental datasets were collected from GEO and samples were profiled from women with or without a diagnosis of preeclampsia. For the analysis, women with early-onset (EO) preeclampsia were identified, applying the canonical threshold of GA <34 weeks. As controls, preterm samples (GA <37 weeks) were selected to ensure appropriate matching for GA. This approach aimed to minimize confounding due to differences in pregnancy duration while isolating the molecular features of preeclampsia.

[0121] To integrate these datasets and minimize inter-study variability, the MINT (Multivariate INTegrative) method (29) and used and implemented in the mixOmics RAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) package (30). MINT integrates datasets while extracting common biological signals and minimizing cohort-specific biases. This approach revealed a shared gene expression signature associated with EO preeclampsia across all cohorts. Before integration, dimensionality reduction of individual datasets revealed clear intra-study disease state clustering (FIG. 6A). After integration, the MINT method aligned the datasets by extracting common components shared across all cohorts. In the resulting sPLS-DA plot, samples were grouped by disease state rather than by study, indicating that the integration successfully uncovered shared transcriptomic patterns linked to EO preeclampsia (FIG. 6B).

[0122] The heatmap illustrates the expression levels of the identified signature genes (FIG.

[0123] 2A). This concise gene signature includes well-known players in preeclampsia and pregnancy-related processes, such as Fms Related Receptor Tyrosine Kinase 1 (FLT1), Leptin (LEP), Endoglin (ENG), Follistatin-like 3 (FSTL3), and Pregnancy-associated plasma protein A2 (PAPPA2). sFLT1 (Soluble fms-like tyrosine kinase-1) is a key regulator of angiogenesis and a well-established biomarker for preeclampsia. Dysregulation of sFLT1 is associated with the imbalance of pro- and anti-angiogenic factors, hallmarks of the disease (31-33). LEP plays a critical role in placental development and energy homeostasis. Altered LEP expression has been linked to several complications during pregnancy (34). ENG is a co-receptor for TGF-beta signaling that contributes to vascular homeostasis. Dysregulation of ENG has been implicated in the endothelial dysfunction characteristic of preeclampsia (35). FSTL3 is involved in regulating inflammation and trophoblast invasion, processes essential for healthy pregnancy (36). Finally, PAPPA2 modulates insulin-like growth factor signaling, which is crucial for placental growth and fetal development (37). Thus, the presence of genes known to play roles in pregnancy further validates the robustness of the signature. Importantly, the remaining genes may represent novel biomarkers for preeclampsia, offering promising avenues for further exploration.

[0124] Example 2 - Longitudinal Peripheral Sampling Validates Machine Learning-Based Biomarker Discovery

[0125] To further explore the potential of the MINT signature genes as biomarkers for preeclampsia, analyses were extended to blood samples, aiming to assess their behavior across tissues. Given the scarcity of blood transcriptomics datasets in GEO that meet the criteria for integration analysis, this study leveraged a longitudinal dataset available for preeclampsia (38). This allowed for maximizing the utility of existing data to uncover meaningful insights into preeclampsia biology (FIG. 7). The dataset (GSE149437) included 13 EO preeclampsia patients, defined by a GA <34 weeks, and 71 preterm controls (GA <37 weeks). In total, the analysis included 66 samples from EO preeclampsia cases and 355 samples from controls, with multiple time points sampled per patient, averaging 5.08 samplesAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) per case and 5.00 samples per control throughout pregnancy. The GAs for EO preeclampsia cases and controls were overall well-matched. The mean GA at delivery was 31.69 weeks for cases and 34.1 weeks for controls. Similarly, the mean GAs at diagnosis were 31.13 and 33.74 weeks for cases and controls, respectively. Blood samples were collected slightly earlier on average in cases (mean: 22.25 weeks) compared to controls (mean: 24.36 weeks). The longitudinal design of the dataset provided a unique opportunity to identify potential dynamic changes in gene expression over time, capturing the progression of EO preeclampsia and its associated molecular signatures.

[0126] Given the longitudinal nature of the dataset, where multiple samples were collected from the same patient over time, a linear mixed-effects model was employed to analyze the data. This approach accounts for repeated measurements from individual patients while assessing the impact of disease state and time on gene expression. Specifically, the model included: (a) a fixed effect for time (to capture temporal trends) and disease state (preeclampsia vs. control) and (b) a random effect for patient ID (to account for intra-patient correlations due to repeated sampling). This formulation ensured that the shared variance between samples from the same patient was appropriately accounted for, thereby providing unbiased estimates of the effects of disease state and time on gene expression.

[0127] Out of the 23 genes in the MINT-derived preeclampsia placental signature, seven showed statistically significant differences in expression over time between preeclamptic and control pregnancies in the periphery. These findings underscore the dynamic nature of these genes and their potential as biomarkers for monitoring preeclampsia progression (FIG. 2B).

[0128] Among the significant genes, FLT1 re-emerged as a key player, serving as a positive control and further validating its critical role in preeclampsia. In addition to FLT1, two genes, B-cell lymphoma 6 (BCL6) and Never in mitosis gene A-related kinase 11 (NEK11), exhibited interesting trends in expression (FIG. 2B). BCL6 is a transcriptional repressor involved in the regulation of immune responses and inflammation (39). Its decreased expression in preeclampsia suggests a potential role in modulating the heightened immune activity and inflammation observed in the disease. NEK11 is a kinase involved in DNA damage response and cell cycle regulation (40). Dysregulation of NEK11 in preeclampsia may reflect cellular stress and impaired placental function, both of which are hallmark features of the condition.

[0129]

[0130] Meta

[0131]

[0132] Reveals

[0133]

[0134] Insights into

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[0136] and Therapeutic Potential While the MINT method was instrumental in identifying a concise biomarker signature for preeclampsia, it was desired to expand the analysis to identify a more comprehensive set of differentially expressed genes (DEGs) associated with the disease. For this purpose, the Metaintegrator framework (41), a tool for performing meta-analysis of gene expression data,Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) was employed. Unlike MINT, which is designed for biomarker discovery and dimensionality reduction, Metaintegrator focuses on integrating datasets to identify DEGs by combining effect sizes across studies. This enables the detection of a broader disease signature by leveraging the collective strength of multiple datasets while mitigating the impact of cohortspecific biases.

[0137] The six placental datasets were aggregated, and standardized preprocessing steps were implemented to ensure consistency and reduce technical variability across studies. Metaintegrator computes effect sizes and statistical significance for each gene within each dataset and then combines these metrics across studies using a random-effects model. The resulting meta-analysis identified a set of 1,010 DEGs (330 upregulated and 680 downregulated) (data not shown) in preeclampsia compared to controls, after filtering for statistical significance (FDR <0.05) and absolute effect size value (abs(ES) >1) (FIG. 2C).

[0138] These genes represented a comprehensive disease signature, capturing both well-known players in preeclampsia biology and novel candidates for further investigation. Thus, integrating results from targeted biomarker discovery of MINT with the hypothesis-free, large-scale integration of meta-analysis allowed for a more holistic understanding of the transcriptomics landscape of preeclampsia. This integrative approach strengthens the foundation for identifying potential therapeutic targets and understanding disease mechanisms.

[0139]

[0140] ia, LEP Signaling, and Immune

[0141]

[0142] To gain more interpretable insights into the molecular mechanisms of preeclampsia, a pathway activity analysis was conducted. For each sample in the six placental datasets, the single-sample Gene Set Enrichment Analysis (ssGSEA) method was employed (42, 43). This approach allows the estimation of pathway activity for individual samples by calculating enrichment scores for predefined gene sets. Unlike traditional GSEA, which compares groups of samples, ssGSEA evaluated the relative expression ranks of genes within a single sample. It assigns higher scores to pathways where genes are consistently expressed at the top or bottom of the ranked list, providing a quantitative measure of pathway activity.

[0143] Pathway collections from the Molecular Signatures Database (MSigDB) (44), including curated gene sets (Hallmark pathways, KEGG pathways and Wiki Pathways), were utilized, resulting in a total of 900 gene sets for the analysis. A meta-analysis was performed to identify pathways that were significantly differentially active between preeclampsia and control samples. Using thresholds of FDR <0.05 and abs(ES) >1, 43 differentially active pathways were identified, with 25 upregulated and 18 downregulated (FIG. 2D and data not shown). Hypoxia emerged as a key upregulated pathway, reflecting the well-established roleAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) of placental hypoxia in preeclampsia (45), where abnormal placentation restricts blood flow, triggering anti-angiogenic factor release and systemic dysfunction. Another notable pathway is the leptin signaling, which is essential for energy homeostasis and placental function (46). Dysregulated LEP levels have been implicated in complications during pregnancy, including inflammation and vascular stress, both of which are prominent in preeclampsia (47). Additionally, several inflammatory and immune-related pathways were found upregulated, including IL-1 signaling and innate immune signaling, highlighting the central role of immune dysregulation in the disease’s pathophysiology (48). Conversely, downregulated pathways were predominantly metabolic, including glycolysis / gluconeogenesis and fatty acid metabolism, suggesting disrupted energy metabolism in preeclampsia (49) (FIG. 2D).

[0144] Together, these findings offer a comprehensive view of the biological processes underlying the condition and provide mechanistic insights into the complex interplay between hypoxia, immune activation and metabolic dysfunction. Such pathway-level analyses not only deepen understanding of preeclampsia but also pave the way to identifying targeted interventions to address these dysregulated processes.

[0145] Example 5 - Cell-Mixture Deconvolution Identifies Neutrophils, Macrophages, and B Cells as Key Players in Preeclampsia Immune Dysregulation

[0146] Cell-mixture deconvolution was employed to analyze the six placental datasets, using the ImmunoStates basis matrix to estimate the proportions of 20 distinct immune cell types in the datasets (FIG. 2E). The focus on immune cells is driven by their critical role in the pathophysiology of preeclampsia. Immune cells are key regulators of placental development and maternal-fetal immune tolerance, processes that are often dysregulated in preeclampsia. Using the ImmunoStates basis matrix (50), which is specifically designed to estimate immune cell proportions, allowed for deeper insights into the immune landscape of the placenta. This approach allows for identification of potential immune imbalances, such as changes in inflammatory or regulatory cell populations, which may contribute to the onset and progression of the disease. Understanding these immune alterations is essential for characterizing preeclampsia’s molecular mechanisms and identifying potential targets for therapeutic intervention.

[0147] To integrate observations across datasets, Metaintegrator was used to perform a meta-analysis. For each cell type, a pooled effect size representing its differential abundance was calculated in preeclamptic compared to control placentas. Filtering by statistical significance (FDR <0.05 and abs(effectSize) >0.5), six cell types of interest were identified: mast cells, neutrophils, and memory B cells were more abundant in preeclampsia, while hematopoietic progenitors, M2 macrophages, and naive B cells were less abundant (FIG.2E and data not shown). Neutrophils, macrophages, and B cells appear to be key drivers ofAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) immune dysregulation in preeclampsia. Dysregulated neutrophils might contribute to endothelial damage and oxidative stress (48), while a shift toward pro-inflammatory M1 macrophages could sustain inflammation and impair placental function (48). Similarly, an increase in memory B cells (48) might disrupt immune tolerance, contributing to the inflammatory and vascular dysfunction characteristic of the condition.

[0148] Example 6 - Computational Drug Repurposing Identifies Lansoprazole as a Potential Therapeutic for Early-Onset Preeclampsia

[0149] After identifying a robust preeclampsia-associated gene signature through metaanalysis of the six integrated placental datasets, a list of differentially expressed genes distinguishing preeclamptic from control samples was obtained. Of the 1,010 genes in the preeclampsia signature, 702 overlapped with the CMap database (data not shown). This disease signature was subsequently utilized as input for the drug repurposing pipeline (20), which leverages a rank-based, nonparametric method to evaluate concordance between disease-associated gene expression profiles and drug-induced expression signatures in the Connectivity Map (CMap) database (18) (FIG. 3). The pipeline identified 63 drugs with significant potential to reverse the preeclampsia signature, defined by a q-value <0.05 and a negative CMap score (<0), indicating strong negative correlation with the disease signature (FIGS.3A and 3B and data not shown). Among these candidates, several, such as irinotecan and camptothecin, have previously been proposed as potential therapies for preeclampsia in independent studies (51), demonstrating overlap between the findings and prior evidence. The top-ranked drug in the analysis was lansoprazole, a proton pump inhibitor widely used to manage gastric conditions, including acid reflux and peptic ulcers (52). Lansoprazole is an over-the-counter medication categorized as pregnancy category B, signifying a reassuring safety profile with no evidence of fetal harm in animal studies.

[0150] Drawing upon prior publications and knowledge via shortest paths among the SPOKE knowledge network, relevant relationships between comorbidities, compounds, and genes were identified that may explain how lansoprazole can be beneficial in the treatment of preeclampsia (FIG. 3C). Some specific gene nodes identified among the shortest paths include FLT1 , VEGFA, and PGF. One specific path “Lansoprazole -DOWNREGULATES^ VEGFA (Gene) <— (Gene Product)_UPREGULATES_(Gene)- FLT1 (Gene) <— ASSOCIATES- pre-eclampsia” indicates that the FLT1 gene product, linked to preeclampsia, upregulates VEGFA. Lansoprazole may mitigate this effect by downregulating VEGFA. Building on these findings, lansoprazole was a lead candidate for further investigation. To rigorously assess its therapeutic potential in preeclampsia, conducted studies have been conducted using mouse models that recapitulate key features of the disease to evaluate lansoprazole's efficacy.Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) as the top candidate for

[0151]

[0152]

[0153] As reported above six independent placenta datasets were utilized to identify a disease signature specific to preeclampsia. Within each dataset, cases of EO preeclampsia (defined as GA <34 weeks) were selected as the disease group and preterm birth samples (GA <37 weeks) were selected as controls, in order to match for GA. Using meta-analysis across these datasets, a robust preeclampsia-associated gene signature was identified that was then used to run the drug repurposing pipeline. However, because both preeclampsia and preterm birth are pregnancy complications and can share biological pathways - such as inflammation, altered placental development, and vascular dysfunction - a sensitivity analysis was conducted to ensure that the identified preeclampsia signature was specific to the disease and not confounded by preterm birth-related signals.

[0154] To perform this analysis, the same placenta datasets were utilized but analysis was focused on a different comparison: preterm birth controls (GA <37 weeks) versus term controls (GA >37 weeks). By applying meta-analysis to this comparison, a preterm birthspecific gene signature was generated that captured molecular features unique to preterm birth. After filtering for statistical significance (FDR <0.05), a disease signature consisting of 784 differentially expressed genes was identified, with 399 upregulated and 385 downregulated (data not shown). The original preeclampsia signature was then adjusted by subtracting the preterm birth signature, effectively isolating features uniquely associated with preeclampsia. This adjusted signature was then used as input for the drug repurposing pipeline. The results of the sensitivity analysis demonstrated that removing the preterm birth signal from the preeclampsia signature did not alter the outcomes of the drug repurposing pipeline. Specifically, nearly identical drug candidates were identified, and their rankings remained largely unchanged, even after accounting for potential confounding effects from preterm birth-related signals (FIG. 8). This consistency suggested that the preeclampsia signature driving the drug repurposing analysis is robust and uniquely reflective of preeclampsia biology, rather than being influenced by overlapping or shared gene expression patterns with preterm birth.

[0155] Example 8 - Lansoprazole protects against fetal wastage in mice

[0156] Potential protective effects of lansoprazole were further evaluated using a murine preclinical model of preeclampsia (FIG. 4A). A hallmark feature of human pregnancy is expansion of CD4+ T cells with immune suppressive function identified by the FOXP3 transcription factor, called Tregs (53). Pregnancy induced expansion of maternal Tregs has been proposed to sustain fetal tolerance, since inflammatory pregnancy complications suchAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) as preeclampsia are consistently associated with blunted expansion of maternal FOXP3+ CD4+T cells in the blood and decidual tissues (53). A similar pregnancy-induced Treg expansion has been shown in mice, whereas partial transient depletion of maternal FOXP3+ cells results in fetal wastage with reciprocal loss of live pups (54). This experimental platform using transgenic mice with co-expression of the high-affinity simian diphtheria toxin receptor (DTR) with FOXP3, exploits the X-linked inheritance of Foxp3 shared between mice and humans, and random inactivation of this chromosome in females, allowing for partial depletion of maternal Tregs after diphtheria toxin (DT) administration to FOXP3DTR / WTmothers (54, 55).

[0157] Partial depletion of maternal Tregs induced by DT administration to FOXP3DTR / WTmidgestation pregnant mice causes sharply increased serum levels of sFLT1 specific to preeclampsia in humans and non-human primates (56, 57) (FIG. 4B). Sustained background levels in DT-treated control FOXP3WT / WTpregnant mice demonstrate DT-induced sFLT1 in FOXP3DTR / WTpregnant mice is specific to maternal Treg depletion, and not explained by potential non-specific effect of DT (FIG.4B). Perturbations after partial depletion of maternal FOXP3+ Tregs in this context causing fetal wastage also do not reflect non-specific inflammation given background serum C reactive protein (CRP) levels in both DT treated FOXP3DTR / WTand FOXP3WT / WTmice (FIG. 4B). Thus, partial depletion of maternal Tregs to pre-pregnancy levels in mice, and blunted expansion of maternal Tregs in human preeclampsia share increased circulating sFLT1 as a common molecular signature. In turn, increased sFLT1 after partial depletion of maternal FOXP3+ Tregs cells dovetails nicely with the aforementioned analytical data highlighting differential expression of this VEGFR in human preeclampsia, and the necessity for sFLT1 in non-human primate preeclampsia models (56).

[0158] Next, the impacts of lansoprazole were evaluated in this preeclampsia model using FOXP3DTR / WTwith allogeneic pregnancy sired by male mice engineered to constitutively express a cell surface recombinant protein containing the model antigen OVA, thereby transforming OVA into a surrogate fetal antigen (58) (FIG. 5A). These experiments showed the expected -40% fetal wastage in FOXP3DTR / WTmidgestation pregnant mice after initiation of DT treatment midgestation with reciprocal loss of live concepti (FIG. 5B). Remarkably, each of these consequences associated with partial maternal Treg depletion were significantly attenuated in mice administered lansoprazole one day prior to DT administration (FIG. 5B). Thus, lansoprazole protected against fetal wastage induced by partial depletion of maternal Tregs. Fetal injury induced by maternal Treg depletion is associated with expansion and decidual infiltration of activated effector CD8+T cells with fetal specificity which drive fetal wastage (59, 60). To investigate how lansoprazole impacts the dynamics andAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) distribution of maternal effector T cells, CD8+T cells with fetal OVA-specificity were enumerated after staining with H2Kb:OVA257-264 tetramers. These analyses showed expansion of fetal-OVA-specific CD8+T cells in the spleen and decidua in mice with fetal wastage induced by partial transient depletion of maternal FOXP3+ Tregs became overturned in lansoprazole treated mice (FIG. 5C). The effects of lansoprazole were most pronounced in the decidua where fetal-OVA CD8+T cells were reduced to background levels found in control mice without DT treatment (FIG. 5C). Thus, improved pregnancy outcomes in lansoprazole treated mice was associated with reduced systemic and decidual infiltration of activated maternal CD8+T cells with fetal-specificity.

[0159] Discussion

[0160] Here, public transcriptomics data was leveraged to investigate early-onset preeclampsia pathophysiology, identify disease-specific gene signatures, and propose candidate therapeutic interventions. Additionally, computational findings were validated through experimental studies, including a preeclampsia mouse model to establish translational potential.

[0161] Firstly, a cross-tissue analysis was performed, focusing on six placental datasets profiling samples from both preeclamptic and control individuals. Using multiple datasets allowed for mitigation of study-specific biases, ensuring that the observations were robust, reliable, and broadly reproducible. Data integration was central to the approach, therefore, multiple methodologies were employed, with each being tailored to the specific objectives of the analysis.

[0162] The MINT algorithm was applied, which facilitated the identification of a concise predictive signature for preeclampsia. Normalized gene expression matrices were input for each cohort into MINT, including the disease state (early-onset (EO) preeclampsia vs. preterm controls) as the response variable. Using data integration and the sPLS-DA within the MINT framework, a 23-gene signature with strong predictive potential was identified. This 23-gene signature presents a significant opportunity for biomarker discovery, offering a focused set of candidates for further development as diagnostic or prognostic tools. Among the most prominent genes identified was FLT1. The inclusion of FLT1 as part of the EO preeclampsia signature is noteworthy, as it is a well-characterized biomarker for preeclampsia, usually showing increasing expression over pregnancy. sFLT1 plays a key role in regulating angiogenesis, and its dysregulation is a hallmark of preeclampsia, reflecting the imbalance between pro- and anti-angiogenic factors that drive placental dysfunction. Other noteworthy genes included ENG, linked to vascular dysfunction, and LEP, FSTL3, and PAPPA2, which are involved in inflammation, placental development, and growth factor signaling, respectively. Interestingly, the MINT analysis also identified genes not yetAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) extensively characterized in the context of preeclampsia, including BCL6 and NEK11. This demonstrates MINT'S ability to go beyond validating established biomarkers by identifying novel candidates, offering new opportunities for advancing research into the disease To broaden the analysis across tissues, the expression of the identified genes was examined in a blood dataset. Blood-based biomarkers offer a significant clinical advantage due to the ease and non-invasive nature of sample collection, enabling earlier diagnosis and potential intervention prior to delivery. Additionally, the dataset was longitudinal, capturing multiple time points during pregnancy. This longitudinal design provided crucial insights into the temporal dynamics of gene expression changes associated with preeclampsia, enhancing the understanding of the disease’s progression over time. The GSE149437 dataset (38) was leveraged, which profiled blood samples from both preeclamptic and control individuals at multiple time points during pregnancy. Focusing on the MINT-derived gene signature from the placental analysis, linear mixed-effects models were utilized to assess the behavior of these genes in the blood over time. Remarkably, seven out of the 23 placental-derived genes showed significant p-values, indicating that their expression levels differed significantly between the disease and control groups over the course of pregnancy. Among these, FLT1 once again served as a positive control, reaffirming its established role in preeclampsia. Additionally, genes like NEK11 and BCL6 emerged as intriguing candidates for further investigation. These genes, while not as widely studied in the context of preeclampsia, demonstrated significant and distinct expression patterns, suggesting their potential as biomarkers. Future validation in independent cohorts will be crucial to confirm their relevance and utility in the clinical setting.

[0163] While MINT is highly effective for identifying small, predictive signatures suitable for biomarker discovery, it was also desired to define a larger and more comprehensive preeclampsia gene signature by focusing on differentially expressed genes across studies. To accomplish this, meta-analysis, a statistical method that synthesizes results from multiple studies to calculate a pooled effect size, was used. This approach allowed for determination of the overall differential expression of each gene by integrating data across the six placental datasets. This approach yielded a robust preeclampsia gene signature consisting of 1,010 differentially expressed genes, with 330 upregulated and 680 downregulated. Notably, all 23 genes from the MINT-derived signature were also present in the meta-analysis signature, underscoring the robustness and consistency of the methodologies. The meta-analysis signature provided a broader view of the transcriptional landscape of preeclampsia and served as the foundation for the next stage of the research, namely the drug repurposing analysis. This expanded gene set was leveraged to identify therapeutic candidates capable of targeting the molecular mechanisms implicated in the disease.Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) It was next desired to further characterize the pathophysiology of preeclampsia by employing featurization methods to derive higher-order, more interpretable features from the gene expression data. Specifically, pathway activity and cell type analyses were performed on the six preeclampsia datasets offering a deeper biological context and insight into the underlying mechanisms.

[0164] For the pathway analysis, pathway activity scores were computed for each patient within each dataset, enabling quantification of the activity of specific biological pathways. By applying meta-analysis to pool observations across datasets, differentially active pathways associated with preeclampsia were identified. Notably, the results highlighted the upregulation of pathways related to hypoxia and lipid metabolism, two well-established mechanisms in preeclampsia pathophysiology. Hypoxia, driven by abnormal placentation, is a hallmark of the disease, contributing to the release of anti-angiogenic factors and systemic dysfunction. Similarly, lipid metabolism dysregulation, particularly involving leptin, emerged as a key pathway. LEP, a hormone critical for energy balance and placental function, has been implicated in the progression of pregnancy-related complications. Additionally, upregulation in immune response pathways was observed, underscoring the interplay between inflammation, immunity and preeclampsia development.

[0165] To investigate the relationship between altered biological pathways and immune cell behavior in preeclampsia, cell mixture deconvolution was used to estimate cell-type proportions in placental samples. Meta-analysis of these estimates revealed significant shifts in immune cell populations, with neutrophils, macrophages, and B cells standing out as key players in the disease's pathology. Neutrophils are particularly striking because of their complex roles in both healthy pregnancies and preeclampsia. Under normal conditions, neutrophils contribute to placental development by producing IL-8, a chemokine that supports angiogenesis, endothelial activation, and cell migration. However, in preeclampsia, these processes become dysregulated. Excessive neutrophil infiltration into vascular tissues leads to the release of oxidative stress molecules, exacerbating endothelial dysfunction. Beyond their structural roles, neutrophils also modulate the immune environment by regulating cytokine production and T cell activity (48). In preeclampsia, this immunoregulatory function appears disrupted, contributing to immune imbalance and amplifying systemic inflammation.

[0166] Macrophages also reflect the altered immune landscape in preeclampsia. During a healthy pregnancy, anti-inflammatory M2 macrophages dominate after the second trimester, supporting tissue repair, angiogenesis, and immune tolerance. This balance naturally shifts toward pro-inflammatory M1 macrophages during labor, but in preeclampsia, this shift occurs prematurely, sustaining chronic inflammation, impairing placental function, and intensifying systemic inflammatory responses (48).Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) B cells play a similarly pivotal role in immune regulation during pregnancy. Normally, B cells foster a tolerant immune environment, often through interactions with Tregs. In preeclampsia, however, an increase in memory B cells undermines this balance. While Tregs retain their suppressive activity on B cell proliferation, the dysregulation of memory B cells fuels a pro-inflammatory environment that destabilizes immune tolerance and disrupts placental development (48).

[0167] Together, these findings reinforce the critical role of immune dysregulation in preeclampsia and provide further evidence of the complex interplay between immune activation, oxidative stress, and inflammation in the disease. Use of publicly available transcriptomic datasets posed challenges due to the inherent heterogeneity among studies, including differences in patient populations, sample preparation methods, and analytical platforms. These issues were addressed by employing integration methods such as MINT and meta-analysis, which allowed for data to be pooled effectively to produce robust, reproducible findings. These analyses offered valuable insights into the molecular and cellular mechanisms underlying preeclampsia, providing a biologically rich context that informed the subsequent drug repurposing phase of the study.

[0168] The meta-analysis-derived preeclampsia gene signature was subsequently utilized in the drug repurposing pipeline to identify potential therapeutic candidates. After filtering for statistical significance and selecting drugs with a CMap score <0, 63 candidates were identified, with lansoprazole emerging as the top hit. Lansoprazole, a widely used over-the-counter proton pump inhibitor for gastric conditions, is classified as pregnancy category B, indicating a favorable safety profile for use during pregnancy. This classification is particularly important given the necessity of balancing efficacy and safety in therapeutic agents during pregnancy. While lansoprazole’s primary mechanism of action involves inhibition of the gastric proton pump (H+ / K+ATPase) to reduce gastric acid secretion, its potential benefits in preeclampsia suggest additional mechanisms may be involved, possibly related to its antiinflammatory or vascular effects.

[0169] To test lansoprazole’s efficacy in preeclampsia, a mouse model designed to replicate critical features of the disease was employed, which included elevated sFLT1 levels, a hallmark of preeclampsia associated with anti-angiogenic imbalances and systemic dysfunction. This model was particularly valuable because it also mimicked the maternal immune adaptations that occur during pregnancy, with a focus on the role of Tregs. Tregs, identified by their expression of FOXP3, are essential for maternal immune tolerance, preventing the rejection of the genetically foreign fetus by suppressing excessive immune activation. Impaired expansion or function of Tregs is strongly linked to pregnancy complications such as preeclampsia and spontaneous abortion. In this model, the consequences of partial depletion of Tregs to mimic immune dysfunction observed inAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) preeclampsia was investigated. This was achieved by exploiting the co-expression of the FOXP3 receptor with the diphtheria toxin receptor (DTR) in Tregs. Administration of diphtheria toxin led to a controlled reduction of maternal Tregs to pre-pregnancy levels. This depletion resulted in a phenotype characterized by increased fetal wastage and reduced numbers of live pups. Mechanistically, this fetal loss was associated with heightened activation of maternal CD8+T cells in the decidua, which targeted fetal antigens in a manner analogous to graft rejection in organ transplantation. The accumulation of these activated cytotoxic T cells underscores the importance of Tregs in maintaining immune balance and protecting the fetus. The model's ability to recapitulate both immune dysregulation and elevated sFLT1 levels provided a robust platform for testing lansoprazole. Remarkably, treatment with lansoprazole significantly mitigated the effects of Treg depletion. The drug not only reduced the accumulation of activated CD8+T cells in both the decidua and systemic circulation, but also restored pregnancy outcomes by preventing fetal wastage. These findings suggest that lansoprazole enhances maternal immune tolerance, potentially by supporting Treg function or counteracting the pro-inflammatory environment associated with their depletion. Overall, the mouse model highlights the interplay between immune tolerance mechanisms, vascular dysregulation, and preeclampsia pathology. Lansoprazole’s efficacy in this system provides strong evidence of its therapeutic potential, making it a compelling candidate for further investigation in preclinical and clinical settings aimed at addressing the multifaceted challenges of preeclampsia.

[0170] Methods

[0171] Sex as a biological variable:

[0172] This study used a preclinical mouse model of preeclampsia, focusing exclusively on pregnant female mice, as the condition is inherently specific to pregnancy and maternal-fetal interactions. The experimental design leveraged transgenic female FOXP3DTR / WTmice, which allowed for partial depletion of maternal Tregs during pregnancy through diphtheria toxin administration. This depletion recapitulated hallmark features of human preeclampsia, including increased circulating sFLT1 levels, fetal wastage, and decidual infiltration of activated CD8+T cells. Male mice were included in the breeding pairs to create allogeneic pregnancies, with the males engineered to constitutively express the model antigen OVA as a surrogate fetal antigen. This setup ensured the investigation of maternal immune responses specific to fetal antigens. Given the focus on pregnancy-specific mechanisms and maternal immune adaptations, male mice were not used beyond their role in breeding. The findings are directly relevant to female physiology during pregnancy and are not expected to vary across sexes, as preeclampsia exclusively affects females. This sex-specific approachAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) provided means to model and study the pathophysiology of preeclampsia while testing the therapeutic potential of lansoprazole in mitigating pregnancy complications.

[0173] Data:

[0174] Six independent datasets from the Gene Expression Omnibus (GEO) repository, each profiling placental tissue from pregnant individuals under varying clinical conditions (Table 1) totaling 151 cases and 96 controls. To ensure a focused and biologically meaningful analysis, samples representing pregnancies affected by early-onset (EO) preeclampsia (GA <34 weeks) were selected as cases. For the control group, samples from pregnancies resulting in preterm births (GA <37 weeks) were selected, matching for GA to minimize confounding effects. This stringent selection criteria enabled isolation of transcriptomics differences attributable specifically to early-onset preeclampsia, enhancing the robustness and interpretability of the findings.

[0175] To further extend the analysis and enable cross-tissue comparisons, a longitudinal transcriptomics dataset profiling blood samples from pregnant individuals over time was incorporated (13 cases and 71 controls) (Table 2). This dataset captures dynamic changes in gene expression throughout gestation, offering a unique opportunity to investigate temporal patterns associated with preeclampsia. Leveraging longitudinal samples allows for uncovering temporal biomarkers and tracking molecular shifts, providing valuable insights into the systemic manifestations of the disease and aiding in the discovery of potential biomarkers for early diagnosis and monitoring.

[0176]

[0177] Table 2. Overview of the blood longitudinal dataset. To enable cross-tissue analysis between placenta and blood, we collected a longitudinal blood dataset to support biomarker discovery, as blood is easier to collect and more practical for clinical use. We filtered the dataset to include 84 women: 13 with early-onset preeclampsia (EO) (defined as GA <34 weeks) and 71 preterm controls (defined as GA <37 weeks). Each participant was sampled multiple times during pregnancy, resulting in 66 samples from preeclamptic women and 355 from controls. This longitudinal dataset allowed us to track gene expression changes over time, offering valuable insights into the progression of preeclampsia and aiding in the identification of potential biomarkers.Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) Metalnteqrator:

[0178] For the meta-analysis of gene expression datasets, the Metaintegrator framework was employed (41), which is an established computational method specifically designed to integrate and analyze transcriptomic data from multiple independent studies. Meta-analysis of gene expression data is crucial in consolidating findings across different datasets, enabling the identification of robust and reproducible gene signatures associated with the condition of interest, even in the presence of biological and technical variability.

[0179] Meta Integrator calculates effect sizes for each gene across all datasets, using the standardized mean differences (SMDs) to quantify the magnitude and direction of association between gene expression and disease state:

[0180]

[0181]

[0182] is the mean of group 2, n s the number of observations in group 1 , n2is the number of observations in group 2, s is the variance of group 1 and s2is the variance of group 2. spooiedis therefore the pooled standard deviation, which is a weighted average of the standard deviations of the two groups.

[0183] To address inter-study heterogeneity — a common issue in meta-analysis — the method uses a random-effects model. This statistical approach assumes that effect sizes may vary across studies, accounting for both within- and between-study variability. The random-effects model thus provides a more generalizable estimate of effect size, reducing the risk of bias that might arise from directly pooling data.

[0184] Gene signatures are then identified based on combined effect sizes and significance thresholds, prioritizing genes with consistent associations across studies. This rigorous approach provides a robust and reproducible set of candidate genes for further validation and exploration, particularly valuable for complex diseases where single-cohort studies may lack sufficient power.

[0185] MINT:

[0186] The MINT (Multivariate INTegrative) method was employed to integrate gene expression data across multiple cohorts, leveraging the multiblock framework within the mixOmics R package. MINT is specifically designed to handle multiple datasets, or "blocks", which represent data from independent studies. This method enables identification of robust gene signatures associated with a phenotype of interest across heterogeneous datasets by maximizing the covariance between the predictors (gene expression) and the response variable (e.g., disease status), while accounting for variations between studies.

[0187] MINT operates by optimizing a multivariate model for each block, where the data matrix Xik)for the k-th study (block) contains observations (e.g., samples) as rows andAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) features (e.g., gene expression levels) as columns. To capture both inter-study and intrastudy variations, MINT decomposes each block-specific data matrix into two parts: a common component that captures shared patterns across studies, and a residual component unique to each block. The method seeks to maximize the covariance between the common components of the predictors and the response variable using a sparse partial least squares (sPLS) approach, which selects only the most relevant features to avoid overfitting and to enhance biological interpretability.

[0188] Formally, given K blocks, MINT maximizes the following criterion:

[0189]

[0190] , nd Y is the response matrix. The method iteratively estimates

[0191]

[0192] for each block, balancing both within-block relevance and across-block consistency.

[0193] By integrating multiple datasets in this way, MINT provides a unified model that can generalize well across different cohorts. The resulting signature thus reflects features that consistently correlate with the disease or phenotype across all studies, minimizing the influence of cohort-specific biases. This integrative approach is particularly beneficial for multi-cohort studies, as it enables the identification of biomarkers with cross-cohort stability and potential clinical relevance.

[0194] Longitudinal Analysis:

[0195] A linear mixed-effects modeling approach was applied to analyze longitudinal blood gene expression data from preeclamptic patients and controls, focusing on genes identified in the MINT signature from placental tissue. Using the Ime4 package in R, a model was constructed that was tailored to capture both the fixed effects of disease class and gestational age, as well as the random effects inherent to repeated measures within individuals. The model was defined as:

[0196] expr Value ~ class * poly gaBloodDraw, degree = 2) + (1 | patient id)

[0197] The fixed effects included the disease class (control or preeclampsia) and its interaction with a second-degree polynomial of gestational age at the time of blood draw (gaBloodDraw). This allowed for modeling of complex, non-linear trajectories of gene expression over the course of pregnancy, providing detailed insights into how these changes diverge between preeclamptic and healthy pregnancies. The inclusion of interaction terms was crucial for capturing the dynamic interplay between disease status and temporal gene expression patterns. To account for within-subject variability, a random intercept was included for patient id, addressing the correlation between repeated measures from theAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) same individual. This approach enabled isolation of individual-specific baseline expression levels, enhancing the precision of the estimates for the population-level effects. By integrating this rigorous mixed-effects framework, longitudinal data was leveraged to uncover temporal gene expression dynamics associated with preeclampsia. This analysis provides a robust link between tissue-derived MINT signatures and their manifestation in blood, advancing the understanding of systemic molecular disruptions during pregnancy and offering a foundation for future investigations into predictive biomarkers or therapeutic targets.

[0198] Cell-mixture deconvolution:

[0199] Cell-mixture deconvolution is a computational approach designed to infer the proportions of distinct cell types present within a bulk tissue sample. This method enables the dissection of complex biological samples into their cellular components, offering a deeper understanding of the sample's cellular heterogeneity. For this analysis, the ImmunoStates basis matrix was utilized (50), which is a reference framework comprising gene expression profiles for well-characterized immune cell types, including T cells, B cells, monocytes, and natural killer cells, among others. The deconvolution process leverages a set of marker genes that are selectively expressed by specific cell types. By comparing the expression levels of these markers in the sample to those in the reference basis matrix, a linear modeling framework is applied to estimate the relative proportions of each cell type. This quantitative inference is crucial for studying immune-related diseases and for understanding how shifts in cellular composition may reflect pathological states or therapeutic responses. Importantly, this method enables the analysis of bulk RNA-sequencing data, which represents the averaged expression across all cells in a sample, and resolves it into meaningful contributions from individual cell types. By using the ImmunoStates matrix, the analysis was tailored to focus on immune cells, offering insights into the immune landscape of the disease. This approach not only enhances the ability to interpret gene expression data but also provides a critical foundation for identifying potential biomarkers, exploring disease mechanisms, and developing targeted therapies.

[0200] Computational Drug Repurposing Pipeline:

[0201] Inspired by the Kolmogorov-Smirnov statistic and the framework introduced by Lamb et al. (61) in the original CMap database, the pipeline employs a nonparametric rank-based method to evaluate the concordance between disease-associated gene expression profiles and drug-induced expression signatures. A prefiltering step was applied to refine the input data. Genome-wide differential expression profiles from the CMap database were then analyzed, and candidate drugs were ranked based on the statistical significance of their reverse correlation with the preeclampsia signature, with adjustments for multiple testing. For drugs tested under varying conditions, the profile with the strongest reversal was selected for each compound.Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) Network Analysis:

[0202] To better understand the potential relationship between the top drug and preeclampsia, the relationships between genes, compounds, and related diseases was explored via the SPOKE knowledge network (62), which includes information from DrugBank, ChEMBL, and Gene Ontology. Shortest paths between lansoprazole (CHEMBL ID: 480) and pre-eclampsia (Disease Ontology ID: 10591) were identified and combined.

[0203] All shortest paths were filtered with inclusion of:

[0204] • Nodes: Compound, Pharmacologic Class, Gene, and Disease nodes (exclusion of Anatomy, SideEffect, Protein, MiRNA, and CellularComponent nodes)

[0205] • Edges: Associates_DaG, Downregulates_CdG, Downregulates_GpdG, Downregulates_KGdG, DownregulatesjDGdG, Hasrole_ChC, lncludes_PCiC, lsa_DiD, Marker_Pos_GmpD, Treats_CtD, Upregulates_CuG, Upregulates_GpuG, Upregulates_KGuG edges (exclusion of Contraindicates_CcD, Affects_CamG, Resembles_DrD edges).

[0206] o Edge attribute filters include Treats_CtD with at compound in clinical trial phase 3 or greater; Upregulates_KGuG, Downregulates_KGdG, and Presents_DpS with p-value <1e-4 based on statistical tests from edge-specific database sources.

[0207] Some more information of select edges:

[0208] • CdG or CuG: Compound downregulates / upregulates gene: according to transcriptional profiles from LINCS L1000

[0209] • GpdG or GpuG: Gene product downregulates / upregulates gene: according to transcriptional profiles from LINCS L1000

[0210] • KGdG or KGuG: Knockdown of gene downregulates / upregulates gene: knockdown or knockout (using short hairpin RNA or CRISPR) of one gene affects another according to transcriptional profiles from LINCS L1000

[0211] • OGdG or OGuG: Overexpression of gene downregulates / upregulates gene:

[0212] according to transcriptional profiles from LINCS L1000

[0213] • CtD: Compound treats disease. Sources include ChEMBL, DrugCentral, and DrugMatrix.

[0214] More details can be found from the SPOKE publication (62).

[0215] Animals:

[0216] C57BL / 6 (H-2b) and Balb / c (H-2d) mice were purchased from the National Cancer Institute colony at Charles River Laboratories. FOXP3DTR / WTmice where half the maternal FOXP3+ cells are susceptible to diphtheria toxin induced ablation have been described (54, 55, 63). OVA+ transgenic mice were maintained on the Balb / c background after backcrossingAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) for >10 generations, and the breeding strategy using OVA+ males to sire allogeneic pregnancy in non-transgenic females has been described (54, 64). For maternal FOXP3+ cell depletion, FOXP3DTR / WTor FOXP3WT / WTcontrol mice were administered purified diphtheria toxin daily (Sigma-Aldrich, USA) (0.5 pg first dose (E11.5), followed by 0.1 pg each day thereafter for 2 additional days. Lansoprazole (4 mg / ml) was dissolved in sterile saline supplemented with 5% DMSO, and 150 pl (0.6 mg) was administered E10.5 to some mice one day prior to initiating DT treatment. All experiments were performed under Cincinnati Children’s Hospital IACUC approved protocols.

[0217] ELISA:

[0218] Levels of Flt1 / sVEGFR1 and C-reactive protein in mouse sera were quantified by ELISA using commercial kits (R&D Systems; DY471 [Flt1 ] and DY1829 (CRP).

[0219] Tetramer staining and flow cytometry:

[0220] Single cell splenocytes suspensions were prepared by gentle tissue dissociation. Decidua tissue was isolated and processed by removing individual placentas from fetuses with separation at the labyrinth and junctional zone interface as described (59). Tissue was placed in RBC lysis buffer and single-cell suspension was generated by grinding between frosted glass slides. Complete DMEM was used to quench the lysis reaction and samples were then filtered through 70 micron cell strainers and pelleted by centrifugation (530 g for 5 min). For tracking CD8+ T cells with H-2Kb:OVA257-264 specificity, single cell suspensions from each tissue were incubated with PE-conjugated or APC-conjugated tetramers, with further enrichment of splenocytes using anti-fluorochrome microbeads (Miltenyi Biotec). Cells were analyzed on a FACSCanto cytometer (BD Biosciences) and analyzed using FlowJo (TreeStar) software.

[0221] Statistics:

[0222] A comprehensive suite of statistical methods was employed to ensure robust and reliable analysis across the multi-cohort and multidimensional datasets. For the metaanalysis of gene expression data, pathways and cell types, the Metaintegrator framework was utilized, which calculates standardized mean differences and applies a random-effects model to account for inter-study variability. To control for multiple hypothesis testing and reduce the likelihood of false positives, the framework implements FDR correction, thereby identifying significant genes, pathways or cell types associated with early-onset preeclampsia with greater confidence.

[0223] Cell mixture deconvolution was performed using a linear modeling approach, leveraging the ImmunoStates basis matrix and marker gene expression to estimate immune cell proportions within bulk RNA-sequencing samples.

[0224] For the analysis of longitudinal transcriptomic data, a linear mixed-effects model was applied with fixed effects for disease class and gestational age (modeled as a second-degreeAtty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) polynomial), and random intercepts for individual patients to account for intra-subject variability due to repeated measures. In the computational drug repurposing pipeline, a nonparametric rank-based approach inspired by the Kolmogorov-Smirnov statistic was employed to assess the concordance between disease-associated and drug-induced gene expression profiles. Permutation analysis was carried out to evaluate the statistical significance of drug-disease profile concordance, and drug candidates with q-values <0.05 and reversal scores <0 (indicating signature reversal) were prioritized for further investigation.

[0225] Network analysis was conducted using the SPOKE knowledge network, where shortest paths between preeclampsia and candidate drugs were evaluated. Statistically significant edges (e.g., p-value <1e-4) were identified based on edge-specific database sources, providing insights into the relationships among genes, compounds, and diseases.

[0226] For experimental validation, female mice were randomly assigned to experimental or control groups. One-way ANOVA was used to analyze mean differences between two or more groups (Prism, GraphPad). For each analysis, a p value of <0.05 was taken as statistical significance. All statistical analyses were conducted using appropriate software packages in R, ensuring reproducibility and transparency in the approach.

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[0299] Accordingly, the preceding merely illustrates the principles of the present disclosure. It will be appreciated that those skilled in the art will be able to devise various arrangements which, although not explicitly described or shown herein, embody the principles of the invention and are included within its spirit and scope. Furthermore, all examples and conditional language recited herein are principally intended to aid the reader in understanding the principles of the invention and the concepts contributed by the inventors to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the invention as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents and equivalents developed in the future, i.e., any elements developed that perform the same function, regardless of structure. The scope of the present invention, therefore, is not intended to be limited to the exemplary embodiments shown and described herein.

Claims

Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) WHAT IS CLAIMED IS:

1. A method of modulating gene expression levels in a subject identified as having preeclampsia or being at risk of having preeclampsia, the method comprising:administering to the subject identified as having preeclampsia or being at risk of having preeclampsia a drug from FIG. 3B in an amount effective to modulate gene expression levels in the subject.

2. The method according to claim 1 , wherein the subject was identified as having preeclampsia or being at risk of having preeclampsia based on the expression levels of one or more of:FMS related receptor tyrosine kinase 1 (FLT1), leptin (LEP), endoglin (ENG), follistatin-like 3 (FSTL3), pregnancy-associated plasma protein A2 (PAPPA2), B-cell lymphoma 6 (BCL6) and never in mitosis gene A-related kinase (NEK11 ).

3. The method according to claim 1 or claim 2, wherein the modulation of gene expression levels results in at least an amelioration of one or more symptoms of preeclampsia in the subject or a prevention of one or more symptoms of preeclampsia in the subject.

4. A method of treating preeclampsia in a subject, the method comprising:assessing gene expression levels in the subject of one or more of:FMS related receptor tyrosine kinase 1 (FLT1), leptin (LEP), endoglin (ENG), follistatin-like 3 (FSTL3), pregnancy-associated plasma protein A2 (PAPPA2), B-cell lymphoma 6 (BCL6) and never in mitosis gene A-related kinase (NEK11); identifying the subject as having preeclampsia or being at risk of having preeclampsia based on the gene expression levels; andadministering a preeclampsia therapy to the subject in an amount effective to treat the preeclampsia, wherein the preeclampsia therapy comprises administering a drug.

5. The method of claim 4, wherein the drug is a drug from FIG. 3B.

6. The method of claim 5, wherein the drug is lansoprazole.

7. The method of any one of claims 1-3, 5 or 6, wherein the drug from FIG. 3B is the only active agent administered to the subject.Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) 8. The method of any one of claims 1-3, 5 or 6, wherein two or more drugs from FIG.3B are administered to the subject.

9. The method according to any one of claims 1 to 8, wherein the administering comprises administering the drug intravaginally.

10. The method according to claim 9, wherein administering the drug intravaginally comprises administering a vaginal suppository comprising the drug to the subject.

11. The method according to claim 9, wherein administering the drug intravaginally comprises administering a vaginal ring comprising the drug to the subject.

12. The method according to any one of claims 1 to 11 , wherein the drug is lansoprazole, methotrexate, halofantrine, streptozocin, levopropoxyphene, domperidone, fulvestrant, haloperidol, metformin, estradiol, sirolimus, fludrocortisone, dapsone, rosiglitazone or guanabenz.

13. The method according to any one of claims 1 to 11 , wherein the drug is lansoprazole.

14. The method according to claim 1 or claim 2, wherein the drug is lansoprazole.

15. A pharmaceutical composition, comprising:a drug from FIG. 3B in an amount effective to modulate gene expression levels in a subject, wherein the pharmaceutical composition is adapted for intravaginal administration of the drug to the subject.

16. The pharmaceutical composition of claim 15, wherein the drug is lansoprazole, methotrexate, halofantrine, streptozocin, levopropoxyphene, domperidone, fulvestrant, haloperidol, metformin, estradiol, sirolimus, fludrocortisone, dapsone, rosiglitazone, or guanabenz.

17. The pharmaceutical composition of claim 15, wherein the drug is lansoprazole.

18. The pharmaceutical composition of any one of claims 15-17, wherein the composition is a vaginal suppository.Atty. Docket: UCSF-854WO (SF-2025-105-2-PCT-0) 19. The pharmaceutical composition of any one of claims 15-17, wherein the composition is a vaginal ring.

20. A kit comprising:a pharmaceutical composition comprising a drug from FIG. 3B in an amount effective to modulate gene expression levels in a subject; andinstructions for administering the pharmaceutical composition to a subject identified as having preeclampsia or being at risk of having preeclampsia.

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