Biomarkers for pre-eclampsia

Abstract

Provided herein are methods for diagnosing pre-eclampsia, methods for determining the risk of a subject developing pre-eclampsia, as well as methods for preventing and treating pre-eclampsia should the subject be found to have, or be at risk of developing, pre-eclampsia. The methods involve determining a level of at least three transposable element subfamilies in a sample, wherein differential expression of the transposable element subfamilies relative to reference values indicates that the subject is at risk of developing, or has, pre-eclampsia.

Description

[0001] BIOMARKERS FOR PRE-ECLAMPSIA

[0002] FIELD OF THE INVENTION

[0003] The invention relates to methods for diagnosing pre-eclampsia and for determining the risk of a subject developing pre-eclampsia, as well as methods for preventing and treating pre-eclampsia should the subject be found to have, or be at risk of developing, pre-eclampsia. The methods involve determining a level of at least 3 transposable element subfamilies in a sample, wherein differential expression of the transposable element subfamilies relative to reference values indicates that the subject is at risk of developing, or has, pre-eclampsia.

[0004] BACKGROUND

[0005] Preeclampsia (PE) is a serious and complex pregnancy-specific hypertensive disorder affecting mothers and infants. PE accounts for 14% of maternal deaths each year and is a major cause of premature births1 2. PE can also lead to other complications, including HELLP syndrome, premature birth, foetal growth restriction and stillbirth. The human placenta has a compressed lifespan, governs pregnancy outcomes, and plays a vital role in the offspring’s health. Abnormal placentation leads to pregnancy complications, including PE, early onset (<34 weeks) PE (EOPE), PE with intrauterine growth restriction (PE+IUGR) or severe PE (~2% of the pregnancies). Although mechanisms of pathophysiology are unclear, epigenetic changes in placentas are linked to PE34. Early prediction of subsequent development of PE before 16-week gestation in pregnancy is hugely vital as prophylaxis at this stage prevents preterm PE associated complications56.

[0006] Transposable elements (TEs) constitute nearly 53% of the human genome and have significantly contributed to rewiring the gene-regulatory landscape by acting as species and tissue-specific transcriptional enhancers7-13. Long terminal repeats (LTRs) of endogenous ERVs are exapted to function as tissue-specific enhancers, including placental-specific enhancers7 13-17. Moreover, ERV envelope-derived genes such as Syncytins have co-opted the fusogenic role in villous cytotrophoblasts (VCTs) to form multinucleated syncytiotrophoblasts (SCTs)18. Despite these intriguing connections between TEs and placental development, evolution and function, epigenetic factors contributing to TE regulation in the placenta and the effect of TE deregulation are unclear. The loss of heterochromatin and DNA methylation associated with ageing, senescence, cancer and neurological diseases causes deregulation of L1 , HERV and Alu TE families, which leads to elevated IFN-I innate immune pathway19-27. Similarly, in the Drosophila ageing model, stimulating retrotransposon activity increases mortality and accelerates a subset of ageing phenotypes28. The cytotrophoblast epigenome is shown to be dramatically reprogrammed during pregnancy, which is associated with an increased global level of DNA methylation and heterochromatic marks (H3K9me3) with gestational age (GA). In contrast, the H3K27ac level reduces with GA4. H4K16ac is a highly abundant mark enriched at euchromatin, particularly at gene bodies, enhancers and TEs1329. H4K16ac is implicated in ageing and senescence, as its level increases at specific genomic loci with age and senescent mammalian cells30-32. We have recently demonstrated that H4K16ac regulates the transcription of TEs in stem cells13. TEs are repressed in somatic tissues but are detected at higher levels during early development, embryonic stem cells and placenta33-35. The preeclamptic placenta displays senescence and accelerated ageing phenotype, together with associated DNA methylation and gene expression signatures33637.

[0007] A better understanding of PE's pathogenesis and mechanism will aid in improving its early prediction accuracy. Recently, works have suggested that maternal circulating cell-free RNA (cfRNA) and cell- free DNA (cfDNA) sequencing data can identify PE-associated transcripts and DNA methylation signatures that may predict PE38-41. However, there remains a need for approaches with improved positive and negative predictive value, as well as approaches that can predict pre-eclampsia early in pregnancy.

[0008] Here, the inventors identify a PE-specific increase in H4K16ac domains associated with the upregulation of TEs, which correlates with elevated IFN-I pathway. Further analysis of maternal cfRNAseq datasets revealed PE-specific differential levels of TEs in maternal circulation. Using the machine learning approach, the inventors identify TE transcript signatures that can accurately predict PE early in pregnancy, with greater sensitivity than existing methods.

[0009] SUMMARY OF THE INVENTION

[0010] In a first aspect, the invention provides a method for determining the risk of developing pre-eclampsia, the method comprising determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; and comparing the expression level to a reference level for each of the transposable element subfamilies.

[0011] In a second aspect, the invention provides a method for diagnosing pre-eclampsia, the method comprising: determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; and comparing the expression level to a reference level for each of the transposable element subfamilies. In a third aspect, the invention provides a method for treating pre-eclampsia in a subject, the method comprising: a. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9- int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; b. comparing the expression level to a reference level for each of the transposable element subfamilies; and c. administering a treatment for pre-eclampsia to the subject if the at least 3 transposable element subfamilies are differentially expressed relative to the reference levels.

[0012] In a fourth aspect, the invention provides a method for preventing pre-eclampsia in a subject, the method comprising: a. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9- int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; b. comparing the expression level to a reference level for each of the transposable element subfamilies; and c. administering a prophylactic treatment for pre-eclampsia to the subject if the at least 3 transposable element subfamilies are differentially expressed relative to the reference levels.

[0013] In a fifth aspect, the invention provides a method of selecting a treating regimen for a subject, the method comprising: a. determining if the subject has, or is at risk of developing, pre-eclampsia, the method comprising: i. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 , ii. comparing the expression level to a reference level for each of the transposable element subfamilies, and

[0014] Hi. determining the subject has, or is at risk of developing, pre-eclampsia if the at least 3 transposable element subfamilies are differentially expressed relative to the reference levels; and b. selecting a treatment regimen for the subject if the subject has, or is at risk of developing, pre-eclampsia, the treatment regimen comprising one or more selected from the group consisting of: blood pressure monitoring, blood testing, urine testing, treatment with an antihypertensive agent, treatment with an anti-inflammatory agent, treatment with aspirin, foetal ultrasound, cardiotocography, treatment with an anticonvulsant agent, treatment with steroids, and induction of labour, or a combination thereof.

[0015] In a sixth aspect, the invention provides a method of analysing a sample, comprising: a. isolating RNA, DNA and / or protein from the sample, and b. using the isolated RNA, DNA and / or protein to detect an expression level of at least 3 transposable element subfamilies, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1.

[0016] In a seventh aspect, the invention provides a kit for determining the risk of developing pre-eclampsia, comprising means for measuring a level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B and at least one selected from the group consisting of HERVK9-int, MER11 B, L1 PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1.

[0017] BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 - Genes and Pathways dysregulated in PE - a) The study design for the cohort used in this study b) Placental biopsy cohorts analysed in this study with details of PE classifications, number of samples, and gestational age (GA) of the biopsies, c) Volcano plot showing significant (p adj or FDR <0.05) differentially expressed genes in PE vs healthy control placentas. Genes known to be upregulated in PE are labelled, d) Genome-browser (hg38) snapshots showing average RNAseq reads across PE-associated LEP and FSTL3 genes in control, PE and PE+IUGR samples.

[0019] Figure 2 - RNAseq analysis recapitulates the genes and pathways dysregulated in PE a)Principal component analysis (PCA) plot showing the variance between samples (CT, PE and PE+IUGR) for RNA-seq. b) Volcano plot describing the differentially expressed genes (DEGs in red, FDR <0.05 and Iog2 foldchange ±1) in PE+IUGR (n=4) against normotensive controls (n=6). c) The network plot shows the processes significantly affected by PE+IUGR. d) Bar plot depicting odds ratio (X-axis) for significantly altered pathways and processes (Y-axis) in PE compared to Control identified using EnrichR on DEGs from fig 1c. Figure 3 - CUT&Tag data from individual samples - a) Genome browser tracks for H4K16ac (top) and H3K27ac (bottom) CUT&Tag data from healthy control, PE and PE+IUGR. Two replicates of CUT&Tag data were generated per placental sample, data from individual replicates are shown, b) Distribution of H4K16 hyper- and hypo-acetylated domains based on the similarity profile for multiple histone modifications (x-axis) across multiple cell lines based on the GIGGLE score (detailed in methods) for similarity (y-axis) obtained with Cistrome database.

[0020] Figure 4 - H4K16ac levels correlate with TE expression in PE - a) Violin plots for the RNAseq (RPKM), H3K27ac and H4K16ac CUT&Tag read counts per million (CPM) for the up-regulated genes (n = 88) in PE+IUGR compared to control, b) Meta profile for average H4K16ac and H3K27ac CUT&Tag reads in control, PE and PE+IUGR placentas across protein-coding genes (n=19291). c) Volcano plots showing significant (FDR <0.05, red) differential H4K16ac (10kb) and H3K27ac (1 kb) genomic domains in PE+IUGR compared to healthy controls, d) Bar plots for the number of proteincoding genes (genes) along with full-length L1 (>5kb), Alu and LTR elements for H4K16ac (left) and H3K27ac (right) domains in PE (c). e) Heatmaps for IgG normalised H4K16ac signal across LTRs, Alus and full-length L1s overlapping hyper (top) and hypo (bottom) acetylated H4K16 domains in PE+IUGR compared to control, f) Metaplot for H3K4me1 , H3K4me3 and H3K9me3 from chorionic villi at full-length LINEIs that are hyperacetylated in control (left) and in PE+IUGR (right). P values for violin plots represent Friedman test from non-parametric paired ANOVA for multiple comparisons.

[0021] Figure 5 - H4K16ac-marked TEs enriched with enhancer features - a) Table showing the ratio and the number of genomic elements (Genes, Alu, LTR and L1 >=5kb) overlapping with differentially acetylated regions (DARs) identified for H4K16ac and H3K27ac in PE+IUGR. b) Box plots comparing the gene expression (log 10 FPKM, y-axis) for the genes proximal (<=50kb) and distal (>50kb) to the H4K16ac-rich L1 . c) Histone-marks profile (Iog2 FC over input) for H3K4me1 (green), H3K4me3 (blue) and H3K9me3 (red) from human chorion villi plotted on the H4K16ac-rich LTRs for Control (left) and PE+IUGR (right), d) same as c, but for H4K16ac-rich Alu in Control (left panel) or PE+IUGR (right panel), e) Gene expression (log 10 FPKM, y-axis) comparison for the genes within 10kb, 10-50kb, 50-1 OOkb and 100-200kb genomic distance bins from the H4K16ac-rich LTRs (left panel), H4K16ac-poor LTRs (middle panel) and H4K16ac-rich Alus (right panel) for Control (left) or PE+IUGR (right) of each panel, f) Histone-marks profile (Iog2 FC over input) for H3K4me1 (green), H3K4me3 (blue) and H3K9me3 (red) from chorion villi plotted on the H4K16ac-poor L1 (left), LTR (middle) and Alu (right), p values for box-plots were calculated using ANOVA and the Kruskal-Wallis test for multiple comparisons.

[0022] Figure 6 - Differentially expressed TE-subfamilies in PE - a, b) Volcano plots (padj < 0.05) showing differentially expressed LTRs (a) and full-length L1s (b) at individual element levels between PE+IUGR and control, b) Similar to Fig. 7a, but only for differentially expressed TEs in PE+IUGR (red) against control (green) heatmap vst z-score. Highlighted (triangle) TE-subfamilies show consistent expression patterns with multiple published cohorts (Fig 7a). d) Similar to 7a but only for LINE1 subfamilies that are differentially expressed with (p-value <0.05).

[0023] Figure 7 - Multiple TE subfamilies are deregulated in preeclamptic placentas - a) Heatmap of the z-scores on Variance Stabilizing Transformation (VST) normalised counts of TE-subfamilies that are differentially expressed in preeclamptic placentas from five independent cohorts (Fig. 1 b) with different PE conditions as annotated in each cohort (p adj < 0.05). b) Heatmap of RNAseq reads (Iog2 PE+IUGR / controls) for candidate TE-subfamilies across individual TE loci, c and d) RTqPCR quantification of HERVH and L1 5'-UTR and L1 ORF1 transcripts (normalised to PSIP1) in controls, pregnancy-induced hypertension (PIH) and PE (PE and PE+IUGR) placentas, e) Scattered dot plots comparing the expression of full-length intergenic L1s (as RPKM on the y-axis) across control, PE and PE+IUGR samples (p values indicate the significance of non-parametric Friedman test for multiple paired comparisons), f) Genome-browser snapshot of representative L1 and HERV LTR loci showing RNA (RPKM) and H4K16ac counts per million (CPM) levels, g) ELISA based L1 5-methyl Cytosine (5- mC, DNA-methylation) assay showing the percentage of L1 5 -UTR methylation between control, PE and PE+IUGR samples, p values for DNA methylation and RT-qPCR assays were calculated using ANOVA and the Kruskal-Wallis test for multiple comparisons.

[0024] Figure 8 - Type 1 IFN pathway is upregulated PE placenta, a) Like Fig 7a. but for differentially expressed IFN genes, b) Gene ontology network analysis (using metascape) of upregulated and downregulated IFN-related genes (p adj < 0.05). c) Genome-browser track showing average RNAseq reads from control (n=6), PE (n=5), and PE+IUGR (n=4), each having two biological replicates at IFN- 1 (IFNA1 , IFNA13, IFNE, ISG15) and IFN-II (IFNGR1) gene loci, d) RT-qPCR in PE+IUGR and control samples for IFNB, IFIT1 , and IFNA primers (Table 2) that amplify multiple IFNA cluster genes, p- values for RT-qPCR assays were calculated using ANOVA and the Kruskal-Wallis test for multiple comparisons.

[0025] Figure 9 - IFN-1 pathway genes are upregulated in PE - Box plots compare the expression of IFN- responsive genes in PE (red) and control (green) samples for GSE10588 obtained from

[0026] Figure 10 - TEs transcript levels in maternal cfRNA. a) Heatmap of 133 TE-subfamilies that showed differential expression between PE and control plasma RNA samples collected >13 weeks of gestation, b) Boxplot for vst normalised RNAseq reads for healthy control and PE for a subset of TE subfamilies from (a). P values for box plots indicate the significance for the dunn-test for comparison as an ad-hoc test for the Kruskal Wallis test for non-parametric comparisons.

[0027] Figure 11 - LDA modelling of TE signatures effectively predicts PE - TEs transcript levels in maternal cfRNA. a) Heatmap of 133 TE-subfamilies that showed differential expression between PE and control plasma RNA samples collected >13 weeks of gestation, b) Boxplot for vst normalised RNAseq reads for healthy control and PE for a subset of TE subfamilies from (a). P values for box plots indicate the significance for the dunn-test for comparison as an ad-hoc test for the Kruskal Wallis test for non-parametric comparisons.

[0028] Figure 12 - TE signature accurately predicts PE - a) Linear Discriminant (LD) coefficients (y-axis) of the TEs (x-axis) used for LDA modelling (n of TEs=27). b) Schematics (left) showing the training models used to identify the final TE signature that predicts PE. Area under the curve (AUC) with 95% confidence interval (right) for >13, >20 and 5-16 week gestation age (GA) showing sensitivity (y-axis) and specificity (x-axis) for PE prediction model using the final list of 11 TEs (Table 3) for discovery (blue) and validation (red, grey and orange) samples, c) Split-violin plots showing the distribution of the predictions (x-axis) of indeed predicted (Yes) and falsely predicted (No) controls (blue) and PE (red) cases across the gestational ages (GA) (y-axis) for >13 weeks discovery, validation and GA 5- 13 weeks samples using LDA model for TE signature, d) Distribution of the probability of PE prediction values for the control and PE samples across the discovery, validation GA> 13 weeks and GA 5-13 weeks samples for TE signature, e) Unsupervised clustering of discovery and validation samples based on expression level (vst counts) of TE signature for control and PE cfRNA samples with GA group (13-20 weeks and >20 weeks) and disease severity (PE, severe PE and control).

[0029] Figure 13 - UCSC genome browser showing CUT&RUN counts per million for Layered H3K27ac at the intron of MECOM gene containing rs9855086 SNP that associate with PE at the 5’ UTR of L1 P370.

[0030] DETAILED DESCRIPTION

[0031] The inventors have shown that certain transposable element (TE) subfamilies are differentially expressed in subjects at risk of developing pre-eclampsia, relative to pregnant subjects who are not at risk of developing pre-eclampsia, and have identified a TE transcript signature that can be used to accurately predict the risk of pre-eclampsia developing in a subject. The TE transcript signature (comprising expression levels of a defined set of TE subfamilies) can be assessed in readily available sample types which are non-invasive to collect, such as cell free RNA samples, and exceed the sensitivity and specificity of existing methods for predicting pre-eclampsia risk. Further, the TE transcript signatures described herein can predict the risk of pre-eclampsia developing at early timepoints in pregnancy, including from 13 weeks gestational age, with greater predictive value compared to existing methods.

[0032] Accordingly, described herein is a method for determining the risk of developing pre-eclampsia, the method comprising determining an expression level of at least 3 transposable element subfamilies in a sample. Generally, the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61- int, AluSx4, MLT2B3, and HAL1 . The method typically further comprises comparing the expression level to a reference level for each of the transposable element subfamilies. A subject may be at risk of developing pre-eclampsia if the at least 3 transposable element subfamilies are differentially expressed relative to the respective reference levels.

[0033] Also described herein is a method for diagnosing pre-eclampsia, the method comprising determining an expression level of at least 3 transposable element subfamilies in a sample. Generally, the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 . The method typically further comprises comparing the expression level to a reference level for each of the transposable element subfamilies.

[0034] Each of the transposable element subfamilies identified herein may be differentially expressed in subjects at risk of developing pre-eclampsia (or in subjects with pre-eclampsia) compared to a reference level (such as an expression level determined in pregnant subjects who are not at risk of developing pre-eclampsia or who do not have pre-eclampsia). Expression levels for each of the transposable element subfamilies are typically assessed relative to their own corresponding reference level. For example, the expression level of HERVK9-int can be measured in a subject and compared to a reference level for HERVK9-int expression determined in a pregnant subject without pre- eclampsia, while the expression level of MER11 B can be measured in a subject and compared to a reference level for MER11 B expression determined in a pregnant subject without pre-eclampsia. Some transposable element subfamilies have an expression level which is increased in subjects at risk of developing pre-eclampsia (or in subjects who have pre-eclampsia) compared to a reference level. For example, the subject may be at risk of developing, or may have, pre-eclampsia if the expression level of HERVK9-int, MER11 B, L1 PA6, and / or AluSx4 is increased relative to the respective reference level. Other transposable element subfamilies have an expression level which is decreased in subjects at risk of developing, or who have, pre-eclampsia compared to a reference level. For example, the subject may be at risk of developing, or may have, pre-eclampsia if the expression level of L1 PA7, L1M7, MER61-int, and / or HAL1 is decreased relative to the respective reference level. The subject may be at risk of developing, or may have, pre-eclampsia, if the expression levels of HERVK9-int and MER11 B are increased relative to the respective reference levels, and if at least one further transposable element subfamily is differentially expressed relative to a reference level.

[0035] Any of the methods described herein may comprise determining an expression level of at least 3 transposable element subfamilies, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B and L1 PA7.

[0036] Provided herein is a method for determining the risk of developing pre-eclampsia, the method comprising determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and L1PA7; and comparing the expression level to a reference level for each of the transposable element subfamilies. A subject (from whom the sample is obtained) may be at risk of developing preeclampsia if the at least 3 transposable element subfamilies are differentially expressed in the sample compared to the respective reference levels. The subject may be at risk of developing pre-eclampsia if the expression levels of HERVK9-int and MER11 B are increased relative to the respective reference levels, and the expression level of L1 PA7 is decreased relative to the reference level. Also provided herein is a method for diagnosing pre-eclampsia, the method comprising determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and L1 PA7; and comparing the expression level to a reference level for each of the transposable element subfamilies. The subject may be diagnosed with pre-eclampsia if the expression levels of HERVK9-int and MER11 B are increased relative to the respective reference levels, and the expression level of L1 PA7 is decreased relative to the reference level.

[0037] The methods described herein may comprise determining an expression level of at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, or at least 11 transposable element subfamilies.

[0038] Any of the methods described herein may comprise determining an expression level of at least 6 transposable element subfamilies, wherein the at least 6 transposable element subfamilies comprise HERVK9-int, MER11 B, L1 PA6, MIR3, L1M7, and MLT2B3.

[0039] Provided herein is a method for determining the risk of developing pre-eclampsia, the method comprising determining an expression level of at least 6 transposable element subfamilies in a sample, wherein the at least 6 transposable element subfamilies comprise HERVK9-int, MER11 B, L1PA6, MIR3, L1M7, and MLT2B3; and comparing the expression level to a reference level for each of the transposable element subfamilies. A subject (from whom the sample is obtained) may be at risk of developing pre-eclampsia if the at least 6 transposable element subfamilies are differentially expressed in the sample compared to the respective reference levels. The subject may be at risk of developing pre-eclampsia if the expression levels of HERVK9-int, MER11 B, and L1 PA6 are increased relative to the respective reference levels, and the expression level of L1M7 is decreased relative to the reference level. Also provided herein is a method for diagnosing pre-eclampsia, the method comprising determining an expression level of at least 6 transposable element subfamilies in a sample, wherein the at least 6 transposable element subfamilies comprise HERVK9-int, MER11 B, L1PA6, MIR3, L1M7, and MLT2B3; and comparing the expression level to a reference level for each of the transposable element subfamilies. The subject may be diagnosed with pre-eclampsia if the expression levels of HERVK9-int, MER11 B, and L1 PA6 are increased relative to the respective reference levels, and the expression level of L1M7 is decreased relative to the reference level.

[0040] Any of the methods described herein may comprise determining an expression level of at least 11 transposable element subfamilies, wherein the at least 11 transposable element subfamilies comprise HERVK9-int, MER11 B, L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1.

[0041] Provided herein is a method for determining the risk of developing pre-eclampsia, the method comprising determining an expression level of at least 11 transposable element subfamilies in a sample, wherein the at least 11 transposable element subfamilies comprise HERVK9-int, MER11 B, L1PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; and comparing the expression level to a reference level for each of the transposable element subfamilies. A subject (from whom the sample is obtained) may be at risk of developing pre-eclampsia if the at least 11 transposable element subfamilies are differentially expressed in the sample compared to the respective reference levels. The subject may be at risk of developing pre-eclampsia if the expression levels of HERVK9-int, MER11 B, L1 PA6, and AluSx4 are increased relative to the respective reference levels, and the expression levels of L1 PA7, L1M7, MER61-int, and HAL1 are decreased relative to the respective reference levels. Also provided herein is a method for diagnosing pre-eclampsia, the method comprising determining an expression level of at least 11 transposable element subfamilies in a sample, wherein the at least 11 transposable element subfamilies comprise HERVK9-int, MER11 B, L1PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; and comparing the expression level to a reference level for each of the transposable element subfamilies. The subject may be diagnosed with pre-eclampsia if the expression levels of HERVK9-int, MER11 B, L1 PA6, and AluSx4 are increased relative to the respective reference levels, and the expression levels of L1 PA7, L1M7, MER61-int, and HAL1 are decreased relative to the respective reference levels.

[0042] The expression level may comprise a level of transposable element subfamily RNA in the sample. For example, the method may comprise quantifying the amount of RNA for each transposable element subfamily that is present in the sample. The expression level may comprise a level of transposable element subfamily DNA in the sample. The expression level may comprise a level of transcript for the transposable element subfamily in the sample. In some cases, the expression level may comprise a level of protein encoded by the transposable element subfamily in the sample. In some cases, the methods described herein may comprise measuring both a level of nucleic acid (e.g. DNA and / or RNA) and a level of protein encoded by the transposable element subfamily. The methods described herein may also comprise measuring a level of RNA and / or DNA for some transposable element subfamilies, and a level of protein expression for other transposable element subfamilies. This may be particularly the case if the transposable element subfamily is non-coding. Owing to the nature of transposons, each transposable element may be expressed at multiple locations in the genome. Consequently, references herein are generally made to expression levels of the transposable element subfamily overall, rather than to individual transposable elements (e.g. individual copies of HERVK9- int, which might be present at multiple locations in the genome.

[0043] The term “sample” or “biological sample” as used herein includes any biological material obtained from a subject. In particular, the sample may be a whole blood sample, serum sample, plasma sample, blood cells, urine sample, or may comprise cell free nucleic acids isolated from a blood sample (such as cell free RNA and cell free DNA). The sample may be a cell free RNA sample (cfRNA). The sample may be a cell free DNA sample (cfDNA). The sample may comprise circulating cell free nucleic acids. The sample may also comprise a tissue biopsy, such as a placental biopsy. Generally, the sample has been previously obtained from a subject prior to the methods described herein being carried out.

[0044] As used herein, the term “subject” generally refers to an animal, preferably a mammal, in particular a human. The subject is generally a pregnant subject.

[0045] The reference level is typically measured in or obtained from a pregnant subject (or group of subjects) without pre-eclampsia. The reference level may be obtained from a pregnant subject or subjects matched in gestational age to the subject. The reference level may be obtained from a normotensive pregnant subject or group of subjects. Generally, the reference level is measured in the same way as the expression level in the subject. For example, if the level of transposable element subfamily RNA is used to determine the expression level in the subject, this is compared to a reference level of transposable element subfamily RNA.

[0046] The expression level of each transposable element subfamily may be measured using any suitable method known in the art. The method may be selected depending on whether the expression level being measured is a level of nucleic acid (e.g. a transcript) or a level of protein. The expression level may be measured using a method selected from the group consisting of PCR, RT-qPCR, sequencing, RNA sequencing, in situ hybridisation, Western blot, immunoassay, ELISA, antibody-based assay, or a combination thereof.

[0047] The methods described herein are particularly useful in early pregnancy for determining the risk of developing pre-eclampsia. For example, the method may be carried out on a sample from a pregnant subject, wherein the gestational age of the pregnancy is 13 weeks or more. The gestational age may be 14 weeks or more, 15 weeks or more, 16 weeks or more, 17 weeks or more, 18 weeks or more, 19 weeks or more, 20 weeks or more, 21 weeks or more, 22 weeks or more, 23 weeks or more, or 24 weeks or more. The gestational age may be less than 24 weeks, less than 23 weeks, less than 22 weeks, less than 21 weeks, less than 20 weeks, less than 19 weeks, less than 18 weeks, less than 17 weeks, less than 16 weeks, less than 15 weeks, or less than 14 weeks. In some cases, the methods described herein may be carried out at a gestational age between 5 and 16 weeks. In some cases, the methods described herein may be carried out at a gestational age between 13 and 20 weeks.

[0048] Methods for treating and preventing pre-eclampsia

[0049] Also provided herein are methods of treating and / or preventing pre-eclampsia, when a subject has been found to be at risk of developing, or to have, pre-eclampsia using the methods described above. For example, provided herein is a method for treating pre-eclampsia in a subject, the method comprising: a. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; b. comparing the expression level to a reference level for each of the transposable element subfamilies; and c. administering a treatment for pre-eclampsia to the subject if the at least 3 transposable element subfamilies are differentially expressed relative to the reference levels.

[0050] Differential expression relative to the reference levels may be determined as described above. For example, the subject may be administered a treatment for pre-eclampsia if the expression levels of HERVK9-int and MER11 B are increased relative to the respective reference levels, and the expression level of L1 PA7 is decreased relative to the reference level.

[0051] Also provided herein is a method for treating pre-eclampsia in a subject, the method comprising: a. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and L1PA7; b. comparing the expression level to a reference level for each of the transposable element subfamilies; and c. administering a treatment for pre-eclampsia to the subject if the expression levels of HERVK9- int and MER11 B are increased relative to the respective reference levels, and the expression level of L1 PA7 is decreased relative to the reference level.

[0052] Also provided herein is a method for treating pre-eclampsia in a subject, the method comprising: a. determining an expression level of at least 6 transposable element subfamilies in a sample, wherein the at least 6 transposable element subfamilies comprise HERVK9-int, MER11 B, L1PA6, MIR3, L1M7, and MLT2B3; b. comparing the expression level to a reference level for each of the transposable element subfamilies; and c. administering a treatment for pre-eclampsia to the subject if the expression levels of HERVK9- int, MER11 B, and L1 PA6 are increased relative to the respective reference levels, and the expression level of L1M7 is decreased relative to the reference level.

[0053] Also provided herein is a method for treating pre-eclampsia in a subject, the method comprising: a. determining an expression level of at least 11 transposable element subfamilies in a sample, wherein the at least 11 transposable element subfamilies comprise HERVK9-int, MER11 B, L1PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; b. comparing the expression level to a reference level for each of the transposable element subfamilies; and c. administering a treatment for pre-eclampsia to the subject if the expression levels of HERVK9- int, MER11 B, L1 PA6, and AluSx4 are increased relative to the respective reference levels, and the expression levels of L1 PA7, L1M7, MER61-int, and HAL1 are decreased relative to the respective reference levels.

[0054] The treatment for pre-eclampsia may comprise any suitable treatment known in the art. The treatment may comprise an anti-hypertensive agent. The treatment may comprise an anti-inflammatory agent. The treatment may comprise an anti-convulsant agent. The treatment may comprise aspirin. The treatment may be administered in a therapeutically effective amount.

[0055] The terms “treatment” and “treating,” as used herein, are intended to refer to all processes wherein there may be a slowing, interrupting, arresting or stopping of the progression of a disorder, or amelioration of one or more symptoms thereof, but does not necessarily indicate a total elimination of all symptoms.

[0056] The term “therapeutically effective amount” as used herein generally means an amount of active compound or pharmaceutical agent that elicits the biological or medicinal response in a tissue system, animal or human that is being sought by a researcher, veterinarian, medicinal doctor or other clinician, which includes alleviation or reversal of the symptoms of the disease or disorder being treated.

[0057] Also provided herein is a method for preventing pre-eclampsia in a subject, the method comprising: a. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; b. comparing the expression level to a reference level for each of the transposable element subfamilies; and c. administering a prophylactic treatment for pre-eclampsia to the subject if the at least 3 transposable element subfamilies are differentially expressed relative to the reference levels.

[0058] Differential expression relative to the reference levels may be determined as described above. For example, the subject may be administered a prophylactic treatment for pre-eclampsia if the expression levels of HERVK9-int and MER11 B are increased relative to the respective reference levels, and the expression level of L1 PA7 is decreased relative to the reference level. The prophylactic treatment may comprise an anti-hypertensive agent, an anti-inflammatory agent, and / or an anti-convulsant agent. The prophylactic treatment may comprise aspirin.

[0059] Also provided herein is a method for preventing pre-eclampsia in a subject, the method comprising: a. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and L1PA7; b. comparing the expression level to a reference level for each of the transposable element subfamilies; and c. administering a prophylactic treatment for pre-eclampsia to the subject if the expression levels of HERVK9-int and MER11 B are increased relative to the respective reference levels, and the expression level of L1 PA7 is decreased relative to the reference level.

[0060] Also provided herein is a method for preventing pre-eclampsia in a subject, the method comprising: d. determining an expression level of at least 6 transposable element subfamilies in a sample, wherein the at least 6 transposable element subfamilies comprise HERVK9-int, MER11 B, L1PA6, MIR3, L1M7, and MLT2B3; e. comparing the expression level to a reference level for each of the transposable element subfamilies; and f. administering a prophylactic treatment for pre-eclampsia to the subject if the expression levels of HERVK9-int, MER11 B, and L1 PA6 are increased relative to the respective reference levels, and the expression level of L1M7 is decreased relative to the reference level.

[0061] Also provided herein is a method for preventing pre-eclampsia in a subject, the method comprising: a. determining an expression level of at least 11 transposable element subfamilies in a sample, wherein the at least 11 transposable element subfamilies comprise HERVK9-int, MER11 B, L1PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; b. comparing the expression level to a reference level for each of the transposable element subfamilies; and c. administering a prophylactic treatment for pre-eclampsia to the subject if the expression levels of HERVK9-int, MER11 B, L1 PA6, and AluSx4 are increased relative to the respective reference levels, and the expression levels of L1 PA7, L1M7, MER61-int, and HAL1 are decreased relative to the respective reference levels.

[0062] The term “preventing” in the context of preventing a disease may also be used to refer to delaying the onset of a disease or disorder, for example until a later time than the disease or disorder would otherwise have presented, and does not necessarily indicate indefinite prevention.

[0063] In determining the risk of a subject developing pre-eclampsia, the methods described herein may also be used to select an appropriate treatment regimen for the subject, for example one that reduces the risk of developing pre-eclampsia or which controls the symptoms of pre-eclampsia, such as administering an anti-hypertensive agent. Accordingly, also provided herein is a method of selecting a treatment regimen for a subject, the method comprising: a. determining if the subject has, or is at risk of developing, pre-eclampsia, the method comprising: i. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9- int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 , ii. comparing the expression level to a reference level for each of the transposable element subfamilies, and

[0064] Hi. determining the subject has, or is at risk of developing, pre-eclampsia if the at least 3 transposable element subfamilies are differentially expressed relative to the reference levels; and b. selecting a treatment regimen for the subject if the subject has, or is at risk of developing, pre- eclampsia, the treatment regimen comprising one or more selected from the group consisting of: blood pressure monitoring, blood testing, urine testing, treatment with an antihypertensive agent, treatment with an anti-inflammatory agent, treatment with aspirin, foetal ultrasound, cardiotocography, treatment with an anticonvulsant agent, treatment with steroids, and induction of labour, or a combination thereof.

[0065] As with the methods described above, a method of selecting a treatment regimen for a subject may comprise determining an expression level of at least 3 transposable element subfamilies, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B and L1 PA7; at least 6 transposable element subfamilies, wherein the at least 6 transposable element subfamilies comprise HERVK9-int, MER11 B, L1 PA6, MIR3, L1M7, and MLT2B3, or at least 11 transposable element subfamilies, wherein the at least 11 transposable element subfamilies comprise HERVK9-int, MER11 B, L1 PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1.

[0066] Methods of sample analysis

[0067] Also provided herein are methods for analysing a sample. The methods may comprise isolating RNA, DNA and / or protein from the sample, and using the isolated RNA, DNA and / or protein to detect an expression level of at least 3 transposable element subfamilies, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HALT

[0068] Isolating RNA and / or DNA from the sample may comprise isolating cell free RNA and / or DNA, for example through the removal of white and red blood cells from a whole blood sample. Detecting the expression level of the transposable element subfamilies may comprise treating the isolated DNA and / or RNA with a nucleic acid having a sequence that is complementary to a sequence of a transposable element subfamily. For example, said detecting may comprise treating the sample with primers for each of the transposable element subfamilies. In other cases, said detecting may comprise treating the isolated protein with an antigen binding domain (such as an antibody or fragment thereof) that specifically binds to a protein encoded by a transposable element subfamily. Said detecting may be performed using PCR, RT-qPCR, sequencing, RNA sequencing, in situ hybridisation, Western blot, immunoassay, ELISA, antibody-based assay, or a combination thereof.

[0069] The RNA and / or DNA may be maternal RNA and / or maternal DNA. The method may comprise a step of separating maternal RNA and / or DNA from foetal RNA and / or DNA. The method may comprise a step of enriching the RNA and / or DNA for maternal RNA and / or DNA.

[0070] The sample may be a blood sample, a plasma sample, a serum sample, a cell-free RNA sample, a cell-free DNA sample, a placental biopsy, or a combination thereof.

[0071] Kits

[0072] Also provided herein is a kit for determining the risk of developing pre-eclampsia. The kit may comprise means for measuring a level of at least 3 transposable element subfamilies in a sample, wherein the transposable element subfamilies are selected from the group consisting of HERVK9-int, MER11 B, L1 PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HALT The kit may further comprise instructions for using the kit. The kit may comprise means for measuring a level of at least 3 transposable element subfamilies in a sample, wherein the transposable element subfamilies comprise HERVK9-int, MER11 B, and at least one selected from the group consisting of L1 PA6, L1PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HALT

[0073] The kit may comprise means for measuring the level of HERVK9-int, MER11 B and L1 PA7. The kit may comprise means for measuring HERVK9-int, MER11 B, L1 PA6, MIR3, L1 M7, and MLT2B3. The kit may comprise means for measuring HERVK9-int, MER11 B, L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HALT

[0074] The means for measuring may comprise a nucleic acid having a sequence which is complementary to the sequence of a transposable element subfamily. The presence of the nucleic acid may be detected and quantified to indicate the level of the transposable element subfamily present in the sample. For example, the means for measuring may comprise an oligonucleotide or RNA probe that is complementary to (or substantially complementary to) the sequence of the transposable element subfamily being measured. The nucleic acid (e.g. the oligonucleotide or RNA probe) may be labelled for subsequent detection by autoradiography, fluorescence microscopy, or immunohistochemistry. The means for measuring may comprise reagents suitable for performing in situ hybridisation to determine a level of each transposable element subfamily present in the sample.

[0075] The means for measuring may comprise at least one primer for each of the transposable element subfamilies. For example, the means for measuring may comprise a forward and / or reverse primer that is complementary to at least a portion of the transposable element subfamily sequence. The means for measuring may comprise reagents suitable for performing PCR (such as real-time PCR or quantitative PCR) to determine a level of each transposable element subfamily present in the sample.

[0076] The means for measuring may comprise an antigen binding domain that specifically binds to a protein encoded by a transposable element subfamily. The antigen binding domain may comprise an antibody or a fragment thereof that retains antigen binding capability. The means for measuring may comprise reagents suitable for performing Western blot, ELISA, or immunohistochemistry to determine a level of each transposable element subfamily present in the sample.

[0077] Any of the kits described herein may further comprise means for extracting DNA, RNA and / or protein from the sample, such as suitable buffers and extraction reagents.

[0078] Aspects and embodiments described herein with the term “comprising” may include other features or steps within the scope. It is also understood that aspects and embodiments described as “comprising” also describes aspect and embodiments wherein the term “comprising” is replaced by the term “consisting essentially of’ or “consisting of’.

[0079] The phrase "selected from the group comprising" may be substituted with the phrase "selected from the group consisting of and vice versa, wherever they occur herein.

[0080] It is also understood that the application discloses all combinations of any of the above aspects and embodiments described above with each other, unless the context demands otherwise. Similarly, the application discloses all combinations of the preferred and / or optional features either singly or together with any of the other aspects, unless the context demands otherwise.

[0081] The invention will now be further described by way of the following Examples, which are meant to serve to assist one of ordinary skill in the art in carrying out the invention and are not intended in any way to limit the scope of the invention, with reference to the Figures.

[0082] EXAMPLES

[0083] Ethics statement

[0084] Patients were enrolled at the Royal London Hospital, Barts Health Trust from May 2021 to March 2022 as a part of a PE Epigenetics study with written informed consent before participating and ethical committee approval (REC 21 / SS / 0010) from the UK Health Research Authority. Demographic and clinical details were obtained from the Clinical Record Service (CRS) Cerner Millennium and BadgerNet Clevermed database. Immediately after birth, the inventors collected the samples from the fresh placenta. Four samples (1 cm x 1 cm) each were collected in a 1 .5ml aliquot from the foetal side of the umbilicus, near the umbilical cord insertion, after trimming the foetal membrane using a scalpel. A superficial bunch of placental tissues containing mostly chorionic villi were taken. The samples were immediately snap-frozen and stored at -80C. The inventors performed two replicates of CUT&Tag for H3K27ac and H4K16ac and polyA-RNAseq from different parts of the placenta biopsies. Recruitment criteria

[0085] Babies born to women with PE were defined as recommendations from the International

[0086] Society for the Study of Hypertension in Pregnancy (ISSHP)61, PIH, and normotensive control who delivered at the Royal London Hospital and were willing to provide informed consent. Exclusion criteria: Infants who were critically ill and babies with significant congenital and genetic abnormalities. Three groups were recruited, normotensive control, PE with GA> 37 weeks without IUGR, and PE <37 weeks and IUGR. IUGR is defined as weight for GA < 5th centile. The last group contain four preterm pregnancies < 37 weeks and one pregnancy > 37 but with IUGR (Table 1).

[0087] Table 1 : Placental Samples used for CUT&Tag and RNA Seq PE, PE; IUGR, intrauterine growth restriction; EMCS, emergency caesarean section; IQR, interquartile range; GDM, gestational diabetes mellitus; * statistically significant different across study groups using nonparametric Kruskal Wallis test. RNA isolation and RT-qPCR

[0088] Total RNA from Placental biopsies RNA using TRI reagent solution (ThermoFisher Scientific, AM9738), genomic DNA was eliminated by treating RNA samples with Turbo RNAse free DNAsel (ThermoFisher Scientific AM1907). For reverse transcriptase-polymerase chain reaction (RT-qPCR), cDNAs were prepared with LunaScript® RT SuperMix Kit (NEB, E3010). qPCR was performed using qPCRBIO SyGreen Mix Lo-ROX (PCRBio) in LightCycler 480 instrument (Roche). Primer pairs for human L1 5’ UTR and L1 ORF1 to human L1s were designed to amplify elements of the humanspecific L1 HS preferentially and evolutionarily recent primate-specific L1 PA (L1 PA2-L1 PA6) subfamilies were taken from53. Primers to the human IFNA family against a consensus sequence of all human IFNA gene sequences(IFNA1 , IFNA2, IFNA4, IFNA5, IFNA6, IFNA7, IFNA8, IFNA10, IFNA13, IFNA1 4, IFNA16, IFNA17 and IFNA21) and IFNB1 are taken from53. The list of all primers used for RTqPCR is in Table 2. Data were normalised to p-actin or PSIP1 .

[0089] Table 2: Primers used in this study RNA sequencing

[0090] RNA was isolated from placental biopsies using TRI reagent solution (ThermoFisher Scientific, AM9738), and genomic DNA was eliminated by treating RNA samples with Turbo RNAse free DNAsel (ThermoFisher Scientific AM1907). RNA sequencing library preparation using NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina® (NEB #E7765), followed by libraries, were sequenced as 150 bp paired-end reads using Novaseq 6000.

[0091] LINE1 DNA methylation assay

[0092] Genomic DNA from placental tissues was isolated using a Quick-DNA mini prep plus kit according to the manufacturer’s instructions (Zymo Research D4068). LINE-1 methylation levels were quantified using an ELISA-based Global DNA Methylation Assay LINE-1 kit; the assay was performed as described by the manufacturer (Active Motif cat. no. 55017). Briefly, genomic DNA from each sample was digested overnight with Msel enzyme (10 U / pL) at 37 °C. 100 ng of digested gDNA was hybridised with a LINE-1 probe in a thermal cycler (98 °C for 10 min, 68 °C for 1 hr, followed by a quick ramp to 25 °C). LINE-1 probe is a 5’ biotinylated oligo designed to hybridise to a 290 bp region of the LINE-1 repeat element, containing 88 cytosine residues, of which 12 are in a CpG context. Reactions were performed in triplicate along with the methylated and non-methylated DNA standard samples, prepared in parallel with placental genomic DNA samples. Digested DNA was transferred to a streptavidin-coated plate and incubated for 1 h at room temperature with mild agitation. Then, a 1 :100 dilution of 5-methylcytosine monoclonal antibody was incubated for 1 hr at room temperature, followed by 1 hr of HRP-conjugated secondary antibody. The developing solution was added and incubated for 3 min; the stop solution was added when the standard samples showed colour change. Finally, the plate was read at 450 nm and 655 nm.

[0093] CUT&Tag

[0094] CUT&Tag from placental biopsies was performed according to the Steve Henikoff lab protocol62, with modifications to tissue processing as described below. Different parts of placental biopsies were processed to perform replicates of H3K27ac and H4K16ac CUT&Tag. To adapt CUT&Tag tissue sections, flash-frozen placental tissues (approximately 3-4 mm size) were manually homogenised with tight homogenisers in wash buffer (20 mM HEPES pH 7.5, 150 mM NaCI, 0.1% BSA, 0.5 mM Spermidine and complete EDTA-free protease inhibitor tablet) into a homogenous suspension of intact cells. Cells were transferred to 1 .5-ml low DNA binding tubes (Eppendorf), and solutions were exchanged on a magnetic stand (DynaMag-2, Thermo Fisher Scientific). Cells were pelleted by centrifugation for 3 min 600 xg at room temperature and resuspended in 500 pl of ice-cold NE1 buffer (20 mM HEPES-KOH pH 7.9, 10 mM KCI, 0.5 mM spermidine, 1% Triton X-100, and 20% glycerol and complete EDTA-free protease inhibitor tablet) and let it sit for 10 min on ice. Nuclei were pelleted by centrifugation for 4 min 1300xg at 4 °C and resuspended in 500 pl of wash buffer, and the wash buffer by placing the tubes on a magnet stand to clear and withdraw the liquid, then resuspended in 1 .0 ml wash buffer and held on ice until beads are ready. In total, 10 pl of BioMag Plus Concanavalin-A- conjugated magnetic beads (ConA beads, Polysciences, Inc) in binding buffer (20 mM HEPES-KOH pH 7.9, 10 mM KCI, 1 mM CaCI2, and 1 mM MnCI2) was added to each tube containing cells and rotated on an end-to-end rotator for 10 min. After a quick spin to remove liquid from the cap, tubes were placed on a magnet stand to clear and withdraw the liquid, and 800 pl of antibody buffer containing 1 pl of primary antibodies (normal rabbit IgG, Santa Cruz Cat no sc-2027, H3K27ac (Abeam, ab4729), H4K16ac (Abeam, ab109463) was added and incubated at 4 °C overnight in a nutator. Secondary antibodies (guinea pig a-rabbit antibody, Antibodies online cat. no. ABIN101961) were added 1 :100 in Dig-wash buffer (5% digitonin in wash buffer) and squirt in 100 pl per sample while gently vortexing to allow the solution to dislodge the beads from the sides and incubated for 60 min on a nutator. Unbound antibodies were washed in 1 ml of Dig-wash buffer for a total of three times. In total, 100 pl of (1 :250 diluted) protein-A-Tn5 loaded with adapters in Dig-300 buffer (20 mM HEPES pH 7.5, 300 mM NaCI, 0.5 mM spermidine with Roche complete EDTA-free protease inhibitor) was placed on a nutator for 1 hr and washed three times in 1 ml of Dig-300 buffer to remove unbound pA-Tn5. Then, 300 pl tagmentation buffer (Dig-300 buffer + 5 mM MgCI2) was added while gently vortexing and incubated at 37 °C for 1 hr on an incubator. Tagmentation was stopped by adding 10 pl 0.5 M EDTA, 3 pl 10% SDS, and 2.5 pl 20 mg / ml Proteinase K to each sample. All were mixed by full-speed vortexing for ~ 2 s and incubated for 1 h at 55 °C to digest. DNA was purified by phenol: chloroform extraction using phase lock tubes followed by ethanol precipitation. Libraries were prepared using NEBNext HiFi 2x PCR Master mix (Cat number M0541S) with a 72 °C gap filling step followed by 13 cycles of PCR with 10-s combined annealing and extension for enrichment of short DNA fragments. Pooled libraries were run on 1 .5% ultrapure agarose gel, 200-700bp smear was excised, and DNA was extracted using Monarch gel extraction kit (NEB cat. No. T1020). Libraries were sequenced in Novaseq 6000 with 150bp paired-end reads at the Novogene sequencing service.

[0095] Analysis of CUT&Tag data Mapping

[0096] 150bp paired-end reads for the CUT&Tag-seq were trimmed for adapters using the Trimmomatic tool and aligned locally to the hg38 genome through Bowtie2 (version 2.4.5) with these parameters for pair-end mapping: -very-sensitive-local -no-unal -no-mixed -no-discordant -phred33 -I 10 -X 70063. For multiple aligned reads, the best alignment was retained using default bowtie2 options. The bam files were sorted, indexed, and used to generate bigwigs for individual replicates of H3K27ac and H4K16ac. Merged bam files were obtained across Control, PE and PE+IUGR using samtools merge64. These bam files were then sorted followed by indexing and generating bed and bigwigs for individual modifications.

[0097] Histone acetylation domain analysis

[0098] Counts were obtained for the H4K16ac and H3K27ac for either 10kb with a sliding window of 5kb (for H4K16ac) or 1 kb with 500bp sliding window (for H3K27ac) genomic bins on hg38 genome across Control, PE and PE+IUGR groups using bedtools multicov tool. Domains containing less than 50 reads sum across all samples were filtered out from analysis for H4K16ac, and non-zero counts were used for H3K27ac analysis. DESeq was performed on these counts and plotted using the r- package Enhanced Volcano for the differentially acetylated regions (DARs). The number of genomic elements (protein-coding genes, LTRs, Alu and full-length L1 >= 5kb) overlapping with the differentially acetylated regions were obtained for H4K16ac and H3K27ac respectively, using the bedtools intersect tool. Overlapping histone modification profiles were generated by submitting the DARs to the Cistrome browser65for H4K16ac and H3K27ac, respectively.

[0099] Bigwig generation and plotting

[0100] Sorted bam files were subjected to bigwig generation via deepTools (version 3.5.1)66bamCoverage tool with -binSize 20 -normalizeUsing CPM -scaleFactor=1 .0 -smoothLength 60 - extendReads 150 -centerReads options. The signal was normalised to IgG through bigwigCompare. The bigwig files were used for plotting signals or visualisation in the genome browser. The genomebrowser views were obtained by viewing the signal tracks in the UCSC genome browser or IGV. Signal plotting at various genomic landmarks and bed coordinates was done using deepTools. Matrices were generated using deepTools computeMatrix reference-point or scale-regions option. These matrices were used for plotting heatmaps or average summary plots by plotHeatmap or plotProfile function in deepTools. Further comparisons on the hyper- or hypo-acetylated (H4K16ac) TEs for their potential as enhancers were confirmed by comparing the H3K4me1 (ENCFF710ASO), H3K4me3 (ENCFF169MHR) and H3K9me3 (ENCFF541CWH) available from the ENCODE datasets for Chorion villi. Genes overlapping across various genomic distance bins from the H4K16ac or H4K16ac poor TEs were obtained using bedtools closest function, then by comparing these genes' FPKM values as boxplots plotted using GraphPad Prism 10.

[0101] RNA-seq data analysis

[0102] The reads obtained from public placental RNAseq datasets (Fig. 1 b) and our cohorts (two biological replicates per sample) were mapped to the human genome using STAR67. The bam files were merged for the replicates, followed by indexing and bigwig generation using the tools described for CUT&Tag samples earlier, with normalisation using RPKM. The counts for the genes were obtained using the featurecounts tool from the SubRead package, and TE counts at the subfamily were obtained using the TEtranscript tool with default options. The count matrices (genes or TEs) were subjected to DESeq2 for the differential analysis with default options. The PCA plot was generated using plotPCA function on rlog transformed data for RNAseq data generated in this study. While doing a combined analysis of the public and our cohorts, the batch effect removal was performed for the differences in cohorts using limma::removeBatchEffect on the vst transformed count matrix. Differentially expressed genes (DEGs) or differentially expressed TE subfamilies were counted as those having FDR (padj) <=0.05. The DEGs were functionally annotated using EnrichR and Metascape for combined analysis. For our cohort, the functional enrichment was performed using clusterProfiler (PMID: 22455463). The differential expression of DEGs and TE-subfamilies was visualised as volcano plots or heat maps using EnhancedVolcano or pheatmap packages, respectively. For the heatmap, z-scores obtained on vst counts were used to compare the Control and PE cases.

[0103] For differential enrichment analysis at individual TE element level, the fragment counts for each dataset was obtained using the featurecounts tool from the SubRead package for different TE classes (L1 and LTR), with the gtf fetched from the UCSC table browser. These feature counts were used for the differential enrichment analyses using the DESeq2 package in R. The differential expression of genes or TEs was visualised as a volcano plot. For analysis of interferon-regulated genes, IFN- regulated gene lists were downloaded from the Interferome database68. For comparison as a heatmap or functional annotation, only genes which are significantly dysregulated (p adj <0.05) for PE vs Control (for all cohort combined analysis) comparison were used. Functional annotation was done using Metascape.

[0104] The RNA signal across the various subfamilies of TEs, as well as genes in the flanks (<1 Ok, 10-50k, 50-100k and 100-200k) of the H4K16ac, marked LTR, Alu and full-length L1 (<50k and >=50k), were calculated as FPKM from the read counts obtained for each gene or TEs across the Control and PE+IUGR samples The FPKM signal was then plotted as a box-plot using GraphPad Prism 10. The signal was plotted as the Iog10 value of the FPKM on the Y-axis. The statistical analyses for all the violin plot comparisons were performed using the Dunn test with Bonferroni correction.

[0105] The RNAseq data for the cell-free (cfRNA) or plasma RNA was obtained from NCBI for the GEO series GSE192902 for the samples (Source data table). The reads were mapped onto the hg38 genome following a similar pipeline as for the placental RNAseq data described earlier. The counts for the TE-subfamilies were obtained using the TEtranscript tool with default options using gtf for genes and repeats (rmsk) from ENSEMBL. The TE count matrix was used to perform DESeq analysis. The comparisons were made within gestational age groups: GA <13 weeks, GA 13-20 weeks, and GA >20 weeks for either PE vs control or sevPE vs control. The inventors initially compared the differential TE presence for PE (sevPE, also annotated as PE) vs Control across samples having gestational age >13 weeks. The inventors obtained 133 TE-subfamilies which have significant (p adj <= 0.05, log2FC > or < ± 0.5) differential presence in PE cases (77 upregulated and 56 downregulated) as seen in the volcano plot (Fig. 10a). The inventors plotted these individual TE subfamilies as a heatmap for all samples used in comparison using pheatmap tool, with k-means clustering on the z-scores obtained for the vst normalised counts. Further, representatives of the most significant TE-subfamilies for directional change (up- or down-regulated) were compared as boxplots for control and PE cases. DESeq2 analysis was also performed for Discovery and Validation cohorts as well as for GA <13 and GA 5-16 weeks for further downstream usage in model signature selection and predictions. Prediction model training and validation

[0106] The inventors began with feature reduction on the vst normalised counts of significant differentially present TE-subfamilies in PE cfRNA (n=133) by applying the RRF (regularised Random Forest) algorithm. The inventors selected the 41 TE-subfamilies (variable importance >0.5) to model using Linear Discrimant Analysis (LDA). The inventors further used a combination of RRF variable importance and the differential presence of TEs in discovery cohort to narrow the number of TE- subfamilies to 11 and further model using LDA. The models were trained on the Discovery cohort and tested on the validation sets (Validation 1 , GA <13 weeks, GA 5-16 weeks, 13-20 weeks, and GA >20 weeks) using LDA modelling. The AUC values were obtained using the pROC package, with confidence intervals (DeLong) of 95% calculated using ci.AUC. The following matrices were generated using the predictions obtained for the TE-subfamilies as listed in (Source Table 1) sensitivity = TP / (TP + FN); (2) specificity = TN / (TN + FP); (3) PV = TP / (TP + FP);(4)NPV = TN / (TN + FN), 5) accuracy = correct predictions (TP + TN) / all predictions (TP+FP+TN+FN) TP =True Positive, FP = False Positive, TN = True Negative and FN = False Negative. Comparison of the probabilities to predict PE were used to plot between Control and PE for discovery and validation cohorts (Validation 1 and GA 5-13 weeks) using the posterior values for PE for the LDA model trained or tested on them, respectively. The split violin plots were plotted using ggplot2.

[0107] Statistical tests

[0108] For box-plots comparison of differentially expressed TE-subfamilies, Dunn test function in the R tool rstatix with Bonferroni correction was used for multiple-group comparisons between the groups. All DESeq2 output was filtered for either FDR / Benjamini-Hochberg adjusted p-value (padj < 0.05) or Wald test p-value (p < 0.05) as mentioned in the figure legends, p-values for RT-qPCR assays and gene-distance box-plots were calculated using ANOVA Kruskal-Wallis test for multiple comparisons using GraphPad PrismI O. Paired violin-plots comparisons were compared using ANOVA Friedman test for multiple paired data.

[0109] Results

[0110] The inventors recruited pregnancies with PE and preterm PE with intrauterine growth restriction (PE+IUGR) and matched healthy normotensive controls (Table 1). The foetal side of the placental biopsies containing chorionic villus tissues was banked to investigate altered histone acetylation and transcriptomic changes associated with PE. The inventors also included four public RNAseq datasets from PE cohorts (Figs. 1 a and 1 b, and Fig. 2a)42-45. Expectedly, transcripts associated with PE, such as IGFBP1 , FSTL3, LEPTIN, HTRA4 and FLT1 , are upregulated in PE placentas (Fig. 1 c, and 1d, Fig. 2b). Gene ontology analysis revealed enrichment of angiogenesis, hypoxia, inflammatory response, extravillous trophoblast cell types and metabolic pathways, including glycolysis associated with the altered Acetyl-CoA levels (Fig. 2c and 2d)46.

[0111] H4K16 and H3K27 hyperacetylation in preeclamptic placentas To elucidate the chromatin and gene regulatory landscape in the preeclamptic placentas, the inventors mapped genome-wide enrichment of acetylation of H4K16ac and H3K27ac by performing two replicates of CUT&Tag from different parts of placental biopsies from healthy controls, PE and PE+IUGR biopsies (Fig. 1 a and Table 1). The inventors evaluated the overall data quality and similarity among CUT&Tag data from independent placental samples and replicates (Fig. 3a). In agreement with the previous findings showing H4K16ac level does not directly impact expression of genes1347 48H3K27ac but not H4K16ac level correlated with gene expression level in PE compared to control (Fig. 4a). Meta-analysis revealed expected enrichment of H3K27ac at promoter features and gene transcription start sites, but H4K16ac is enriched at gene bodies and enhancer features in PE and PE+IUGR compared to control (Fig. 4b, Fig. 3a and b).

[0112] Further, to assess the changes in acetylation levels across the genome, the inventors analysed the enrichment of CUT&Tag reads across genomic bins of 1 kb with 0.5kb sliding windows for H3K27ac and 10 kb with 5kb sliding windows for H4K16ac due to its broad enrichment pattern47. Reproducible H3K27ac and H4K16ac domains were higher in PE+IUGR samples than controls (Fig. 4c). H3K27ac domains specific to PE+IUGR are enriched at genes, LTR and Alu but not L1s (Fig. 4d). While H4K16ac domains specific to PE+IUGR are particularly enriched at full-length L1s, Alu and LTR elements but not at genes (Fig. 4d and 4e). H4K16ac-enriched TEs are associated with chromatin features associated with active enhancers (Fig. 3b, 5b-f). Genes closer to H4K16ac marked L1 , Alu and LTRs are expressed at higher levels than away genes compared to TEs that lacked H4K16ac in control and PE+IUGR (Figs. 5b, e and f). This agrees with the previous findings showing that H4K16ac is enriched at TEs, and these TEs regulate gene expression in cis13.

[0113] TEs are upregulated in preeclamptic placentas

[0114] RNAseq data revealed many L1 and LTRs were significantly upregulated at individual loci and subfamily levels in the PE+IUGR placentas compared to control (Figs. 6a-c). Unsupervised clustering of differentially expressed TEs from 5 different cohorts led to a clear separation of PE from healthy control samples, irrespective of the disease severity (PE, severe PE and PE with IUGR, superimposed PE) and timing of the onset of PE (early or late) (Fig. 7a). Some of the consistently upregulated TE subfamilies in PE placentas included several HERV LTRs (p adj < 0.05 Figs. 7a and 7b). Many L1s are also upregulated in PE, although with lower fold change (p adj < 0.05 Fig. 6d). Upregulation of HERVs and L1 s in PE is validated by RT-qPCR using primers that detect HERVH family and L1 5’ UTRs of evolutionarily young L1 elements (L1 HS-L1 PA5) and L1 ORF1 (Figs. 7c and 7g). Interestingly, TEs are not significantly deregulated in pregnancy-induced hypertension without proteinuria (PIH, gestational hypertension), suggesting that the upregulation of TEs is specific to PE (Figs. 7c and 7d).

[0115] L1s are hypo-methylated in PE placentas

[0116] A higher level of H4K16ac at L1 5’ UTRs at PE+IUGR (Fig. 4e) and significant upregulation of full-length L1s located outside the genes (Fig. 7d and 7g), confirming L1 upregulation is not due to readthrough transcription of introns of genes harbouring L1s. H4K16ac level also increases globally with ageing and is associated with the loss of heterochromatin in senescent cells31 32. Reduced heterochromatin and DNA methylation contribute to ageing and senescence-associated increases in TE transcription24. Thus, the inventors measured 5-methylCytosine (5-mC) across L1 repeats in placental biopsies. PE and PE+IUGR placentas showed hypomethylation at L1s compared to the control placenta (Fig. 7f). DNA hypomethylation and histone hyperacetylation together with the upregulation of TE transcripts in the preeclamptic placenta, further establish the epigenetic deregulation of TEs in PE.

[0117] Elevated type-l interferon pathway in PE placenta

[0118] Due to structural similarities between TE-derived viral nucleic acids, cells can sense TE-derived transcripts as invading viruses and trigger the major antiviral IFN-I innate immune pathway21. Differential gene expression analysis of IFN-regulated genes in the RNAseq data from multiple cohorts, including RNAseq and RT-qPCR validations in our placental biopsies, revealed PE-specific upregulation of IFN-I but not IFN-II pathway (Fig. 8a-d and, Fig. 9). Our findings suggests that higher level of L1 and ERV LTRs in the PE placenta could lead to elevated level of antiviral IFN-I pathway, that could be contributing to inflammation in PE.

[0119] Differential level TEs in cfRNA from preeclampsia cohort.

[0120] Placental cells undergoing necrosis and apoptosis are known to contribute significantly to circulating nucleic acids in the maternal blood, which can provide a non-invasive and early prognosis of PE38-40. TEs are highly cell-type specific and are expressed at higher levels during early development, particularly in the placenta3435. Thus, the inventors asked whether TEs showing altered levels in the term placenta can be detected in maternal cfRNA by performing TE-focussed analysis of publicly available cfRNAseq data39. Analysis of >13 gestational age (GA) cfRNAseq data showed a significant difference in levels of 133 TE subfamilies between healthy control and PE samples (p adj<0.05). Unsupervised clustering of these TEs based on expression level segregated PE samples from controls (Fig. 10a and 10b, Fig. 1 1 a). Many L1 s (L1 PA2, L1 PA6, L1 PA17, L1 M), ERV LTRs (MER11 B, LTR25-int, LTR-12, HERVK9-int and HERV1-int) and Alu (AluSx4) were detected at a significantly higher level in pregnancies that later developed PE (Fig. 10a and 10b).

[0121] TEs are upregulated in early developmental stages, including embryonic stem cells and the trophectoderm from which the placenta is derived3435. Notably, many TEs that show differential levels in cfRNA data, such as MER61 , MER39B, MER11 B, MER11 A, MLT1 , MLT2, MLT2B1 and L1 subfamilies are also differentially expressed in preeclamptic placental biopsies compared to healthy controls (Fig. 7a). Altered proliferation, senescence and necrosis of placental cell types could contribute to TE transcripts detected in cfRNA, as preeclamptic placental cells have higher senescence and accelerated ageing phenotype in PE3 37 49.

[0122] TE-cfRNA signature predicts PE The inventors aimed to train models that predict PE based on TE level in cfRNA; the inventors split >GA13 samples into discovery (60 control and 29 PE cases) and validation (55 control and 29 PE cases) samples and compared the variance stabilised (vst) counts for predictions. The inventors first performed feature reduction by applying a regularised random forest (RRF) algorithm on 133 differentially enriched TEs (Fig. 10a and Fig. 9) for all samples >13 weeks GA and selected 41 TE subfamilies with variable importance of >0.5, which effectively segregated samples into control and PE (Fig. 11 a and 11 b). Linear Discriminant Analysis (LDA) on these TEs to train the model resulted in a near-perfect AUC of 0.99 for the discovery and 0.77 for the validation samples (Fig. 11 b and 11c). Final signature after selecting 11 TEs based on linear-discriminant (LD) coefficients (Fig. 12a) and differential expression in discovery cohort (source data), improved the predictability with the AUC of 0.97 for discovery and 0.88 for validation samples with 81% sensitivity, 84% specificity, 74% positive predictor value (PPV) and 88% negative predictor value (NPV) (Figs. 12b and 12c, Table 3 and 4). These prediction scores are superior to previous mRNA- and noncoding RNA-based predictions that showed 75% sensitivity and 32.3% PPV40. The synergistic contribution of these TE-subfamilies could effectively predict PE (Fig. 11d). Moreover, this signature showed increased AUC values when compared for prediction across different gestational age groups (Fig 12b and Fig 11e). Interestingly, further sub-set of 6 and 3 TEs showed an AUC of 0.83 in the validation cohort, suggesting that PE prediction can be achieved using small TE subfamilies (Fig. 11f and Table 4).

[0123] Table 3: TE Subfamilies and AUC details for final TE signatures

[0124] Table 4: TE Signature statistics

[0125]

[0126] In comparison to the recent gene expression signature for early GA (5-16 weeks) that showed 28% PPV, 71% NPV39, our TE signature in validation samples of the same GA showed 57% PPV and 81% NPV (Table 4). The identified TE-cfRNA signature showed consistent predictability of PE cases with a higher probability distribution (>0.5) for predicted PE cases compared to controls (<0.5) (Fig. 12d). Expression level of this final TE signature was sufficient to segregate >13 weeks GA control and PE samples irrespective of the GA and PE severity (Fig. 12e). Thus, suggesting these TE transcript levels can be used to predict the PE cases early in pregnancy independent of the GA and PE severity.

[0127] Discussion

[0128] The majority of pregnancy complications, including PE, IUGR, premature birth and stillbirth, are associated with placentation defects and inflammation. Although inflammation during pregnancy is a major cause of pregnancy complications leading to long-term effects on both mother and child, it is unclear what causes inflammation during pregnancy. Here, the inventors demonstrate that TE deregulation associated with H4K16ac hyperacetylation leads to the activation of the antiviral IFN-I pathway, suggesting the role of deregulated TEs in inflammation in preeclamptic placentas. Using these insights, the inventors have discovered cfRNA TE signatures that can be utilised for early diagnosis of pregnant women at risk of developing PE, which enables targeted surveillance and obstetric care.

[0129] PE-specific hyperacetylation at TEs leading to their upregulation could contribute to the preeclamptic placenta, as accelerated ageing-like state and senescence are implicated in the pathophysiology of PE 3,37,49. Theinventors found a higher level of acetylation in PE placenta with IUGR but not in late- onset PE, suggesting an altered level of acetylation could be linked to different pathophysiology as it is known that early- and late-onset PE have different pathophysiology50. H4K16ac is linked to ageing and senescence3032, suggesting the contribution of TE-specific hyperacetylation to the PE phenotype. What causes altered H4K16ac levels in PE is not clear. It is possible that altered glycolysis and hypoxia pathways observed in our RNAseq data could alter acetyl-CoA levels in PE placenta (Fig. 2d). The contribution of diet-induced changes in acetyl-CoA in altered levels of histone acetylation at TEs also cannot be ruled out, as the higher levels of nucleocytoplasmic acetyl-CoA can serve as a substrate for histone acetylation in growth or fed conditions compared to starved conditions (reviewed in)51. Chromatin modifications enriched at TEs, constituting nearly 50% of the genome, can be a source or sink for metabolic by-products such as acetyl-CoA (discussed in)52. One limitation of analysing bulk epigenome and transcriptome of placental biopsies is the confounding effect of the complexity of cell types in the placenta. Thus, in-vitro experimentation is needed to decipher the direct impact of acetylation-mediated TE deregulation and its effect on triggering the IFN-I pathway using the trophoblast stem cell model.

[0130] DNA methylation plays a vital role in transcriptional repression of retroelements in somatic tissues. The reactivation of HERVs and L1s associated with reduced DNA methylation increases with age5354. Our findings show hypo-methylation across L1 elements and a higher level of L1 transcripts in the PE placenta. Since L1s constitute -18% of the human genome, hypomethylation at these elements in PE suggests possible global hypomethylation in PE, consistent with the hypo-methylation signatures associated with PE41. These studies demonstrate altered epigenome in the placenta that could contribute to preeclampsia pathogenesis.

[0131] TEs are known to be upregulated during early development, embryonic stem cells and trophectoderm-derived trophoblast stem cells in the placenta33-35. Trophectoderm gained repressive H3K9me3 domains are preferentially deposited at hominoid specific TEs such as LTR12, MER11 B, HERVH, and HERVK9-int that are differentially enriched in PE cfRNA and placenta55. PE is a human-specific disorder. Epigenetic remodelling of hominoid-specific TEs, which have co-opted placental-specific functions, is essential for early development, and their deregulation can lead to defective placentation or embryo implantation34. Many LTRs such as MER84, MER61 E, MLT1 MER11 , LTR12, MLT1J2 and MER39B that are differentially expressed in cfRNA are suggested to function as cis-regulatory elements for placental or trophoblast-specific genes16’17’35, supporting the contribution of placental cell types to maternal cfRNA signature. Increasing PE prediction accuracy for >20 weeks GA with 83% PPV, 0.96 AUC and 0.91 sensitivity compared to 5-16 weeks GA with 65% PPV, 0.75 AUC (Fig 12b, Table 4) further supports the increased placental contribution to TE-cfRNA signature with the gestation56. Preeclamptic placental biopsies are significantly enriched with EVTs and depleted of SCTs57. Early onset PE is associated with a smaller birth and placental weight58. This suggests an altered cellular composition of placental cell types in early-onset PE due to senescence or necrosis can contribute to TEs-cfRNA levels. A higher level of IFITM (an IFN-1- regulated gene) is shown to inhibit cell fusion in SCTs and has been suggested to contribute to pregnancy complications59. The findings herein demonstrate that elevated IFN-1 pathways and reduced SCTs in PE placentas suggest a possible role of the IFN-1 pathway in altered trophoblast differentiation.

[0132] In summary, TE expression signatures identified here will provide accurate and non-invasive methods to predict PE early in pregnancy. The current PE screening models are based on maternal characteristics and medical history or on specialised ultrasound, blood analyte and hypertension measurements, which are insufficient for effective risk prediction. The TE signature identified herein with 83% PPV is superior to the sFlt-1 :PIGF ratio test currently recommended for 20 to 35 weeks GA with suspected PE, which provides a PPV of 36.7%60. TEs cfRNA-based prediction also performs better than the non-TE RNA-based prediction approach394°. The TE-cfRNA-based approach of predictability of PE across the gestational ages can be used for stratification of pregnancies for close monitoring and therapeutic interventions that may improve maternal and neonatal outcomes.

[0133] References

[0134] 1. Say, L., Chou, D., Gemmill, A., Tunpalp, O., Moller, A.B., Daniels, J., Gulmezoglu, A.M., Temmerman, M., and Alkema, L. (2014). Global causes of maternal death: A WHO systematic analysis. Lancet Glob Health 2. 10.1016 / S2214-109X(14)70227-X.

[0135] 2. Goldenberg, R.L., Culhane, J.F., lams, J.D., and Romero, R. (2008). Epidemiology and causes of preterm birth. Preprint, 10.1016 / S0140-6736(08)60074-4 10.1016 / S0140- 6736(08)60074-4.

[0136] 3. Suvakov, S., Cubro, H., White, W.M., Butler Tobah, Y.S., Weissgerber, T.L., Jordan, K.L., Zhu, X.Y., Woollard, J.R., Chebib, F.T., Milic, N.M., et al. (2019). Targeting senescence improves angiogenic potential of adipose-derived mesenchymal stem cells in patients with preeclampsia. Biol Sex Differ 10. 10.1186 / s13293-019-0263-5.

[0137] 4. Zhang, B., Kim, M.Y., Elliot, G.N., Zhou, Y., Zhao, G., Li, D., Lowdon, R.F., Gormley, M., Kapidzic, M., Robinson, J.F., et al. (2021). Human placental cytotrophoblast epigenome dynamics over gestation and alterations in placental disease. Dev Cell 56, 1238-1252. e5. 10.1016 / j.devcel.2O21 .04.001 .

[0138] 5. Rolnik, D.L., Wright, D., Poon, L.C., O’Gorman, N., Syngelaki, A., de Paco Matallana, C., Akolekar, R., Cicero, S., Janga, D., Singh, M., et al. (2017). Aspirin versus Placebo in Pregnancies at High Risk for Preterm Preeclampsia. New England Journal of Medicine 377, 613-622. 10.1056 / nejmoa1704559.

[0139] 6. Roberge, S., Bujold, E., and Nicolaides, K.H. (2018). Aspirin for the prevention of preterm and term preeclampsia: systematic review and metaanalysis. Preprint at Mosby Inc., 10.1016 / j.ajog.2017.11 .561 10.1016 / j.ajog.2017.11 .561 .

[0140] 7. Todd, C.D., Deniz, O., Taylor, D., and Branco, M.R. (2019). Functional evaluation of transposable elements as enhancers in mouse embryonic and trophoblast stem cells. Elife 8. 10.7554 / eLife.44344.

[0141] 8. Chuong, E.B., Eide, N.C., and Feschotte, C. (2017). Regulatory activities of transposable elements: From conflicts to benefits. Preprint at Nature Publishing Group, 10.1038 / nrg.2016.139 10.1038 / nrg.2016.139.

[0142] 9. Sundaram, V., Cheng, Y., Ma, Z., Li, D., Xing, X., Edge, P., Snyder, M.P., and Wang, T. (2014). Widespread contribution of transposable elements to the innovation of gene regulatory networks. Genome Res 24, 1963-1976. 10.1101 / gr.168872.113.

[0143] 10. Kunarso, G., Chia, N.Y., Jeyakani, J., Hwang, C., Lu, X., Chan, Y.S., Ng, H.H., and Bourque, G. (2010). Transposable elements have rewired the core regulatory network of human embryonic stem cells. Nat Genet 42, 631-634. 10.1038 / ng.600.

[0144] 11. Jacques, P.E., Jeyakani, J., and Bourque, G. (2013). The Majority of Primate-Specific Regulatory Sequences Are Derived from Transposable Elements. PLoS Genet 9.

[0145] 10.1371 / journal, pgen.1003504.

[0146] 12. Sundaram, V., and Wysocka, J. (2020). Transposable elements as a potent source of diverse cis-regulatory sequences in mammalian genomes. Preprint at Royal Society Publishing, 10.1098 / rstb.2019.0347 10.1098 / rstb.2019.0347.

[0147] 13. Pal, D., Patel, M., Boulet, F., Sundarraj, J., Grant, O.A., Branco, M.R., Basu, S.,

[0148] Santos, S.D.M., Zabet, N.R., Scaffidi, P., et al. (2023). H4K16ac activates the transcription of transposable elements and contributes to their cis-regulatory function. Nat Struct Mol Biol.

[0149] 10.1038 / S41594-023-01016-5.

[0150] 14. Chuong, E.B. (2018). The placenta goes viral: Retroviruses control gene expression in pregnancy. Preprint at Public Library of Science, 10.1371 / journal.pbio.3000028

[0151] 10.1371 / journal, pbio.3000028.

[0152] 15. Chuong, E.B., Rumi, M.A.K., Soares, M.J., and Baker, J.C. (2013). Endogenous retroviruses function as species-specific enhancer elements in the placenta. Nat Genet 45, 325-329. 10.1038 / ng.2553.

[0153] 16. Frost, J.M., Amante, S.M., Okae, H., Jones, E.M., Ashley, B., Lewis, R.M., Cleal,

[0154] J.K., Caley, M.P., Arima, T., Maffucci, T., et al. (2023). Regulation of human trophoblast gene expression by endogenous retroviruses. Nat Struct Mol Biol 30, 527- 538. 10.1038 / s41594- 023-00960-6.

[0155] 17. Yu, M„ Hu, X., Pan, Z., Du, C„ Jiang, J., Zheng, W., Cai, H„ Wang, Y., Deng, W„ Wang, H., et al. (2023). Endogenous retrovirus-derived enhancers confer the transcriptional regulation of human trophoblast syncytialization. Nucleic Acids Res 51 , 4745-4759. 10.1093 / nar / gkad109. 18. Mi, S., Lee, X., Li, and Xiang-ping (2000). Nature

[0156] 19. De Cecco, M., Criscione, S.W., Peckham, E.J., Hillenmeyer, S., Hamm, E.A., Manivannan, J., Peterson, A.L., Kreiling, J.A., Neretti, N., and Sedivy, J.M. (2013). Genomes of replicatively senescent cells undergo global epigenetic changes leading to gene silencing and activation of transposable elements. Aging Cell 12, 247-256. 10.1111 / acel.12047.

[0157] 20. Dopkins, N., and Nixon, D.F. (2023). Activation of human endogenous retroviruses and its physiological consequences. Preprint at Nature Research, 10.1038 / s41580-023- 00674-z 10.1038 / S41580-023-00674-z.

[0158] 21. Gazquez-Gutierrez, A., Witteveldt, J., Heras, S.R., and Macias, S. (2021). Sensing of transposable elements by the antiviral innate immune system. 10.1261 / rna.

[0159] 22. Marasca, F., Sinha, S., Vadala, R., Polimeni, B., Ranzani, V., Paraboschi, E.M., Burattin, F.V., Ghilotti, M., Crosti, M., Negri, M.L., et al. (2022). LINE1 are spliced in non-canonical transcript variants to regulate T cell quiescence and exhaustion. Nat Genet 54, 180-193.

[0160] 10.1038 / S41588-021-00989-7.

[0161] 23. Della Valle, F., Reddy, P., Yamamoto, M., Liu, P., Saera-Vila, A., Bensaddek, D., Zhang, H., Prieto Martinez, J., Abassi, L., Celii, M., et al. (2022). LINE-1 RNA causes heterochromatin erosion and is a target for amelioration of senescent phenotypes in progeroid syndromes.

[0162] 24. Gorbunova, V., Seluanov, A., Mita, P., McKerrow, W., Fenyo, D., Boeke, J.D., Linker, S.B., Gage, F.H., Kreiling, J.A., Petrashen, A.P., et al. (2021). The role of retrotransposable elements in ageing and age-associated diseases. Preprint at Nature Research,

[0163] 10.1038 / S41586-021 -03542-y 10.1038 / s41586-021 -03542-y.

[0164] 25. Mehdipour, P., Marhon, S.A., Ettayebi, I., Chakravarthy, A., Hosseini, A., Wang, Y., de Castro, F.A., Loo Yau, H., Ishak, C., Abelson, S., et al. (2020). Epigenetic therapy induces transcription of inverted SINEs and ADAR1 dependency. Nature 588, 169-173.

[0165] 10.1038 / S41586-020-2844-1 .

[0166] 26. Simon, M., Van Meter, M., Ablaeva, J., Ke, Z., Gonzalez, R.S., Taguchi, T., De Cecco, M., Leonova, K.L, Kogan, V., Helfand, S.L., et al. (2019). LINE1 Derepression in Aged Wild-Type and SIRT6-Deficient Mice Drives Inflammation. Cell Metab 29, 871-885. e5. 10.1016 / j.cmet.2019.02.014.

[0167] 27. Liu, X., Liu, Z., Wu, Z., Ren, J., Fan, Y., Sun, L., Cao, G., Niu, Y., Zhang, B., Ji, Q., et al. (2023). Resurrection of endogenous retroviruses during aging reinforces senescence. Cell 186, 287-304. e26. 10.1016 / j.cell.2022.12.017.

[0168] 28. Rigal, J., Anduaga, A.M., Bitman, E., Rivellese, E., Kadener, S., and Marr, M.T. (2022). Artificially stimulating retrotransposon activity increases mortality and accelerates a subset of aging phenotypes in Drosophila. Elife 11. 10.7554 / ELIFE.80169.

[0169] 29. Taylor, G.C.A., Eskeland, R., Hekimoglu-Balkan, B., Pradeepa, M.M., and Bickmore, W.A. (2013). H4K16 acetylation marks active genes and enhancers of embryonic stem cells, but does not alter chromatin compaction. Genome Res 23, 2053-2065. 10.1101 / gr.155028.113. 30. Dang, W., Steffen, K.K., Perry, R., Dorsey, J.A., Johnson, F.B., Shilatifard, A., Kaeberlein, M., Kennedy, B.K., and Berger, S.L. (2009). Histone H4 lysine 16 acetylation regulates cellular lifespan. Nature 459, 802-807. 10.1038 / nature08085.

[0170] 31. Nativio, R., Donahue, G., Berson, A., Lan, Y., Amlie-Wolf, A., Tuzer, F., Toledo, J.B., Gosai, S.J., Gregory, B.D., Torres, C., et al. (2018). Dysregulation of the epigenetic landscape of normal aging in Alzheimer’s disease. Nat Neurosci 21 , 497-505. 10.1038 / s41593-018-0101 -9.

[0171] 32. Rai, T.S., Cole, J.J., Nelson, D.M., Dikovskaya, D., Faller, W.J., Vizioli, M.G., Hewitt, R.N., Anannya, O., McBryan, T., Manoharan, L, et al. (2014). HIRA orchestrates a dynamic chromatin landscape in senescence and is required for suppression of Neoplasia. Genes Dev 28, 2712-2725. 10.1101 / gad.247528.114.

[0172] 33. Garcia-Perez, J.L., Widmann, T.J., and Adams, LR. (2016). The impact of transposable elements on mammalian development. Preprint at Company of Biologists Ltd,

[0173] 10.1242 / dev.132639 10.1242 / dev.132639.

[0174] 34. DiRusso, J.A., and Clark, A.T. (2023). Transposable elements in early human embryo development and embryo models. Preprint at Elsevier Ltd, 10.1016 / j.gde.2O23.102086 10.1016 / j.gde.2023.102086.

[0175] 35. Pavlicev, M., Hiratsuka, K., Swaggart, K.A., Dunn, C., and Muglia, L. (2015). Detecting endogenous retrovirus-driven tissue-specific gene transcription. Genome Biol Evol 7, 1082- 1097. 10.1093 / gbe / evv049.

[0176] 36. Siddique, N., and Cox, B. (2022). Computational analysis identified accelerated senescence as a significant contribution to preeclampsia pathophysiology. Placenta 121 , 70-78. 10.1016 / j. placenta.2022.03.005.

[0177] 37. Mayne, B.T., Leemaqz, S.Y., Smith, A.K., Breen, J., Roberts, C.T., and Bianco- Miotto, T. (2017). Accelerated placental aging in early onset preeclampsia pregnancies identified by DNA methylation. Epigenomics 9, 279-289. 10.2217 / epi-2016-0103.

[0178] 38. Munchel, S., Rohrback, S., Randise-Hinchliff, C., Kinnings, S., Deshmukh, S., Alla, N., Tan, C., Kia, A., Greene, G., Leety, L., et al. (2020). Circulating transcripts in maternal blood reflect a molecular signature of early-onset preeclampsia.

[0179] 39. Moufarrej, M.N., Vorperian, S.K., Wong, R.J., Campos, A.A., Quaintance, C.C., Sit, R. V., Tan, M., Detweiler, A.M., Mekonen, H., Neff, N.F., et al. (2022). Early prediction of preeclampsia in pregnancy with cell-free RNA. Nature 602, 689-694.10.1038 / s41586-022-04410-z.

[0180] 40. Rasmussen, M., Reddy, M., Nolan, R., Camunas-Soler, J., Khodursky, A., Scheller, N.M., Cantonwine, D.E., Engelbrechtsen, L., Mi, J.D., Dutta, A., et al. (2022). RNA profiles reveal signatures of future health and disease in pregnancy. Nature 601 , 422- 427. 10.1038 / s41586- 021-04249-w.

[0181] 41. De Borre, M., Che, H., Yu, Q., Lannoo, L., De Ridder, K., Vancoillie, L., Dreesen, P.,Van Den Ackerveken, M., Aerden, M., Galle, E., et al. (2023). Cell-free DNA methylome analysis for early preeclampsia prediction. Nat Med 29, 2206-2215. 10.1038 / s41591 -023-02510-5. 42. Yang, X., Yang, J., Liang, X., Chen, Q., Jiang, S., Liu, H., Gao, Y., Ren, Z., Shi, Y.W., Li, S., et al. (2020). Landscape of Dysregulated Placental RNA Editing Associated with Preeclampsia. Hypertension 75, 1532-1541. 10.1161 / HYPERTENSIONAHA.120.14756.

[0182] 43. Hesson, A.M., Langen, E.S., Plazyo, O., Gudjonsson, J.E., and Ganesh, S.K. (2023). Placental transcriptome analysis of hypertensive pregnancies identifies distinct gene expression profiles of preeclampsia superimposed on chronic hypertension. BMC Med Genomics 16. 10.1186 / s 12920-023-01522-x.

[0183] 44. Horii, M., To, C., Morey, R., Jacobs, M.B., Li, Y., Nelson, K.K., Meads, M., Siegel, B.A., Pizzo, D., Adami, R., et al. (2023). Histopathologic and Transcriptomic Profiling Identifies Novel Trophoblast Defects in Patients With Preeclampsia and Maternal Vascular Malperfusion. Mod Pathol 36, 100035. 10.1016 / j.modpat.2022.100035.

[0184] 45. Awamleh, Z., Gloor, G.B., and Han, V.K.M. (2019). Placental microRNAs in pregnancies with early onset intrauterine growth restriction and preeclampsia: Potential impact on gene expression and pathophysiology. BMC Med Genomics 12. 10.1186 / s 12920-019-0548-x.

[0185] 46. Maynard, S.E., Min, J.Y., Merchan, J., Lim, K.H., Li, J., Mondal, S., Libermann, T.A., Morgan, J.P., Sellke, F.W., Stillman, LE., et al. (2003). Excess placental soluble fms- like tyrosine kinase 1 (sFItl) may contribute to endothelial dysfunction hypertension, and proteinuria in preeclampsia. Journal of Clinical Investigation 111 , 649-658. 10.1172 / JC117189.

[0186] 47. Radzisheuskaya, A., Shliaha, P. V., Grinev, V. V., Shlyueva, D., Damhofer, H., Koche, R., Gorshkov, V., Kovalchuk, S., Zhan, Y., Rodriguez, K.L., et al. (2021). Complex-dependent histone acetyltransferase activity of KAT8 determines its role in transcription and cellular homeostasis. Mol Cell 81 , 1749-1765.e8.10.1016 / j.molcel.2021 .02.012.

[0187] 48. Monserrat, J., Morales Torres, C., Richardson, L., Wilson, T.S., Patel, H., Domart, M.C., Horswell, S., Song, O.R., Jiang, M., Crawford, M., et al. (2021). Disruption of the MSL complex inhibits tumour maintenance by exacerbating chromosomal instability. Nat Cell Biol 23, 401-412. 10.1038 / S41556-021 -00657-2.

[0188] 49. Harmon, A.C., Cornelius, D.C., Amaral, L.M., Faulkner, J.L., Cunningham, M.W., Wallace, K., and LaMarca, B. (2016). The role of inflammation in the pathology of preeclampsia. Preprint at Portland Press Ltd, 10.1042 / CS20150702 10.1042 / CS20150702.

[0189] 50. Valensise, H., Vasapollo, B., Gagliardi, G., and Novelli, G.P. (2008). Early and Late preeclampsia: Two different maternal hemodynamic states in the latent phase of the disease. Hypertension 52, 873-880. 10.1161 / HYPERTENSIONAHA.108.117358.

[0190] 51. Shi, L., and Tu, B.P. (2015). Acetyl-CoA and the regulation of metabolism: Mechanisms and consequences. Preprint at Elsevier Ltd, 10.1016 / j.ceb.2015.02.003 10.1016 / j.ceb.2015.02.003.

[0191] 52. Murphy, P.J., and Berger, F. (2023). The chromatin source-sink hypothesis: A shared mode of chromatin-mediated regulations. Development (Cambridge) 150. 10.1242 / dev.201989.

[0192] 53. De Cecco, M., Ito, T., Petrashen, A.P., Elias, A.E., Skvir, N.J., Criscione, S.W., Caligiana, A., Brocculi, G., Adney, E.M., Boeke, J.D., et al. (2019). L1 drives IFN in senescent cells and promotes age-associated inflammation. Nature 566, 73-78. 10.1038 / s41586-018-0784-9. 54. Liu, X., Liu, Z., Wu, Z., Ren, J., Fan, Y., Sun, L., Cao, G., Niu, Y., Zhang, B., Ji, Q., et al. (2023). Resurrection of endogenous retroviruses during aging reinforces senescence. Cell 186, 287-304. e26. 10.1016 / j.cell.2022.12.017.

[0193] 55. Yu, H., Chen, M., Hu, Y., Ou, S., Yu, X., Liang, S„ Li, N., Yang, M„ Kong, X., Sun, C„ et al. (2022). Dynamic reprogramming of H3K9me3 at hominoid-specific retrotransposons during human preimplantation development. Cell Stem Cell 29, 1031- 1050. e12.

[0194] 10.1016 / j. stem.2022.06.006.

[0195] 56. Koh, W., Pan, W., Gawad, C., Christina Fan, H., Kerchner, G.A., Wyss-Coray, T., Blumenfeld, Y.J., El-Sayed, Y.Y., and Quake, S.R. (2014). Noninvasive in vivo monitoring of tissue-specific global gene expression in humans. Proc Natl Acad Sci U S A 111 , 7361-7366.

[0196] 10.1073 / pnas.1405528111.

[0197] 57. Tsang, J.C.H., Vong, J.S.L., Ji, L., Poon, L.C.Y., Jiang, P., Lui, K.O., Ni, Y.B., To, K.F., Cheng, Y.K.Y., Chiu, R.W.K., et al. (2017). Integrative single-cell and cell-free plasma RNA transcriptomics elucidates placental cellular dynamics. Proc Natl Acad Sci U S A 114, E7786- E7795. 10.1073 / pnas.1710470114.

[0198] 58. Dahlstram, B., Romundstad, P., 0ian, P., Vatten, L.J., and Eskild, A. (2008). Placenta weight in pre-eclampsia. Acta Obstet Gynecol Scand 87, 608-611 . 10.1080 / 00016340802056178.

[0199] 59. Buchrieser, J., Degrelle, S.A., Couderc, T., Nevers, Q., Disson, O., Manet, C., Donahue, D.A., Porrot, F., Hillion, K.-H., Perthame, E., et al. (2019). IFITM proteins inhibit placental syncytiotrophoblast formation and promote fetal demise.

[0200] 60. Zeisler, H., Llurba, E., Chantraine, F., Vatish, M., Staff, A.C., Sennstrom, M., Olovsson, M., Brennecke, S.P., Stepan, H., Allegranza, D., et al. (2016). Predictive Value of the sFlt-1 :PIGF Ratio in Women with Suspected Preeclampsia. New England Journal of Medicine 374, 13-22. 10.1056 / nejmoa1414838.

[0201] 61. Tranquilli, A.L., Dekker, G., Magee, L., Roberts, J., Sibai, B.M., Steyn, W., Zeeman, G.G., and Brown, M.A. (2014). The classification, diagnosis and management of the hypertensive disorders of pregnancy: A revised statement from the ISSHP. Preprint at Elsevier B.V., 10.1016 / j.preghy.2014.02.001 10.1016 / j.preghy.2014.02.001.

[0202] 62. Kaya-Okur, H., and Henikoff, S. (2019). Bench top CUT&Tag V.2 Nature Communications Human Cell Atlas Method Development Community. 10.17504 / protocols.io.z6hf9b6.

[0203] 63. Langmead, B., Trapnell, C., Pop, M., and Salzberg, S.L. (2009). Ultrafast and memoryefficient alignment of short DNA sequences to the human genome. Genome Biol 10. 10.1186 / gb-2009-10-3-r25.

[0204] 64. Danecek, P., Bonfield, J.K., Liddle, J., Marshall, J., Ohan, V., Pollard, M.O., Whitwham, A., Keane, T., McCarthy, S.A., and Davies, R.M. (2021). Twelve years of SAMtools and BCFtools. Gigascience 10. 10.1093 / gigascience / giab008.

[0205] 65. Liu, T., Ortiz, J.A., Taing, L., Meyer, C.A., Lee, B., Zhang, Y., Shin, H., Wong, S.S., Ma, J., Lei, Y., et al. (2011). Cistrome: An integrative platform for transcriptional regulation studies. Genome Biol 12. 10.1186 / gb-2011-12-8-r83. 66. Ramirez, F., Dundar, F., Diehl, S., Gruning, B.A., and Manke, T. (2014). DeepTools: A flexible platform for exploring deep-sequencing data. Nucleic Acids Res 42. 10.1093 / nar / gku365.

[0206] 67. Dobin, A., Davis, C.A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., and Gingeras, T.R. (2013). STAR: Ultrafast universal RNA-seq aligner. Bioinformatics 29, 15-21. 10.1093 / bioinformatics / bts635.

[0207] 68. Rusinova, I., Forster, S., Yu, S., Kannan, A., Masse, M., Cumming, H., Chapman, R., and Hertzog, P.J. (2013). INTERFEROME v2.0: An updated database of annotated interferon- regulated genes. Nucleic Acids Res 41. 10.1093 / nar / gks1215. TABLE OF SEQUENCES

[0208] EQUIVALENTS AND SCOPE

[0209] Those skilled in the art will appreciate that the present invention is defined by the appended claims and not by the Examples or other description of certain embodiments included herein.

[0210] Similarly, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise.

[0211] Unless defined otherwise above, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present invention. Generally, nomenclatures used in connection with, and techniques of, cell and tissue culture, molecular biology, immunology, genetics and protein and nucleic acid chemistry described herein are those well-known and commonly used in the art, or according to manufacturer’s specifications.

[0212] All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and / or materials in connection with which the publications are cited. EMBODIMENTS

[0213] The invention may also be understood by reference to the following numbered embodiments.

[0214] 1 . A method for determining the risk of developing pre-eclampsia, the method comprising determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; and comparing the expression level to a reference level for each of the transposable element subfamilies.

[0215] 2. The method of embodiment 1 , wherein the method comprises determining an expression level of at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, or at least 11 transposable element subfamilies.

[0216] 3. The method of any preceding embodiment, wherein a subject is at risk of developing preeclampsia if the expression level of HERVK9-int, MER11 B, L1 PA6, and / or AluSx4 is increased relative to the respective reference level.

[0217] 4. The method of any preceding embodiment, wherein a subject is at risk of developing preeclampsia if the expression level of L1 PA7, L1 M7, MER61-int and / or HAL1 is decreased relative to the respective reference level.

[0218] 5. The method of any preceding embodiment, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B and L1 PA7.

[0219] 6. The method of any preceding embodiment, wherein a subject is at risk of developing preeclampsia if the expression levels of HERVK9-int and MER11 B are increased relative to the respective reference levels, and the expression level of L1 PA7 is decreased relative to the reference level.

[0220] 7. The method of any preceding embodiment, wherein the method comprises determining an expression level of at least 6 transposable element subfamilies in the sample.

[0221] 8. The method of any preceding embodiment, wherein the at least 6 transposable element subfamilies comprise HERVK9-int, MER11 B, L1 PA6, MIR3, L1 M7, and MLT2B3.

[0222] 9. The method of any preceding embodiment, wherein a subject is at risk of developing preeclampsia if the expression levels of HERVK9-int, MER11 B, and L1 PA6 are increased relative to the respective reference levels, and the expression level of L1M7 is decreased relative to the reference level.

[0223] 10. The method of any preceding embodiment, wherein the method comprises determining an expression level of at least 11 transposable element subfamilies in the sample.

[0224] 11. The method of any preceding embodiment, wherein the at least 11 transposable element subfamilies comprise HERVK9-int, MER11B, L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61- int, AluSx4, MLT2B3, and HALT

[0225] 12. The method of any preceding embodiment, wherein a subject is at risk of developing preeclampsia if the expression levels of HERVK9-int, MER11 B, L1 PA6, and AluSx4 are increased relative to the respective reference levels, and the expression levels of L1 PA7, L1M7, MER61-int, and HAL1 are decreased relative to the respective reference levels.

[0226] 13. The method of any preceding embodiment, wherein the reference level is obtained from a pregnant subject without pre-eclampsia.

[0227] 14. The method of any preceding embodiment, wherein the expression level comprises a level of transposable element subfamily RNA in the sample.

[0228] 15. The method of any preceding embodiment, wherein the expression level comprises a level of transposable element subfamily DNA in the sample.

[0229] 16. The method of any preceding embodiment, wherein the expression level comprises a level of transcript for the transposable element subfamily in the sample.

[0230] 17. The method of any preceding embodiment, wherein the expression level comprises a level of protein encoded by the transposable element subfamily in the sample.

[0231] 18. The method of any preceding embodiment, wherein the sample is a blood sample, a plasma sample, a serum sample, a cell-free RNA sample, a cell-free DNA sample, a placental biopsy, or a combination thereof.

[0232] 19. The method of any preceding embodiment, wherein the sample is a cell-free RNA sample.

[0233] 20. The method of any preceding embodiment, wherein the expression level of each transposable element subfamily is measured using a method selected from the group consisting of: PCR, RT-qPCR, sequencing, RNA sequencing, in situ hybridisation, Western blot, immunoassay, ELISA, antibody-based assay, or a combination thereof. 21. The method of any preceding embodiment, wherein the method determines the risk of developing pre-eclampsia in a pregnant subject, and the gestational age of the pregnancy is 13 weeks or more.

[0234] 22. The method of any preceding embodiment, wherein the method determines the risk of developing pre-eclampsia in a pregnant subject, wherein the subject is a human.

[0235] 23. A method for diagnosing pre-eclampsia, the method comprising: determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; and comparing the expression level to a reference level for each of the transposable element subfamilies.

[0236] 24. The method of embodiment 23, wherein the method comprises determining an expression level of at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, or at least 11 transposable element subfamilies.

[0237] 25. The method of embodiment 23 or 24, wherein a subject is diagnosed with pre-eclampsia if the expression level of HERVK9-int, MER11 B, L1 PA6, and / or AluSx4 is increased relative to the respective reference level.

[0238] 26. The method of any of embodiments 23-25, wherein a subject is diagnosed with pre-eclampsia if the expression level of L1 PA7, L1M7, MER61-int, and / or HAL1 is decreased relative to the respective reference level.

[0239] 27. The method of any of embodiments 23-26, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B and L1 PA7.

[0240] 28. The method of any of embodiments 23-27, wherein a subject is diagnosed with pre-eclampsia if the expression levels of HERVK9-int and MER11 B are increased relative to the respective reference levels, and the expression level of L1 PA7 is decreased relative to the reference level.

[0241] 29. The method of any of embodiments 23-28, wherein the method comprises determining an expression level of at least 6 transposable element subfamilies in the sample.

[0242] 30. The method of any of embodiments 23-29, wherein the at least 6 transposable element subfamilies comprise HERVK9-int, MER11 B, L1 PA6, MIR3, L1 M7, and MLT2B3. 31. The method of any of embodiments 23-30, wherein a subject is diagnosed with pre-eclampsia if the expression levels of HERVK9-int, MER11 B, and L1 PA6 are increased relative to the respective reference levels, and the expression level of L1M7 is decreased relative to the reference level.

[0243] 32. The method of any of embodiments 23-31 , wherein the method comprises determining an expression level of at least 11 transposable element subfamilies in the sample.

[0244] 33. The method of any of embodiments 23-32, wherein the at least 11 transposable element subfamilies comprise HERVK9-int, MER11 B, L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61- int, AluSx4, MLT2B3, and HALT

[0245] 34. The method of any of embodiments 23-33, wherein a subject is diagnosed with pre-eclampsia if the expression levels of HERVK9-int, MER11 B, L1 PA6, and AluSx4 are increased relative to the respective reference levels, and the expression levels of L1 PA7, L1M7, MER61-int, and HAL1 are decreased relative to the respective reference levels.

[0246] 35. The method of any of embodiments 23-34, wherein the reference level is obtained from a pregnant subject without pre-eclampsia.

[0247] 36. The method of any of embodiments 23-35, wherein the expression level comprises a level of transposable element subfamily RNA in the sample.

[0248] 37. The method of any of embodiments 23-36, wherein the expression level comprises a level of transposable element subfamily DNA in the sample.

[0249] 38. The method of any of embodiments 23-37, wherein the expression level comprises a level of transcript for the transposable element subfamily in the sample.

[0250] 39. The method of any of embodiments 23-38, wherein the expression level comprises a level of protein encoded by the transposable element subfamily in the sample.

[0251] 40. The method of any of embodiments 23-39, wherein the sample is a blood sample, a plasma sample, a serum sample, a cell-free RNA sample, a cell-free DNA sample, a placental biopsy, or a combination thereof.

[0252] 41. The method of any of embodiments 23-40, wherein the sample is a cell-free RNA sample.

[0253] 42. The method of any of embodiments 23-41 , wherein the expression level of each transposable element subfamily is measured using a method selected from the group consisting of: PCR, RT-qPCR, sequencing, RNA sequencing, in situ hybridisation, Western blot, immunoassay, ELISA, antibody-based assay, or a combination thereof. The method of any of embodiments 23-42, wherein the method diagnoses pre-eclampsia in a pregnant subject, and the gestational age of the pregnancy is 13 weeks or more. The method of any of embodiments 23-43, wherein the method diagnoses pre-eclampsia in a pregnant subject, wherein the subject is a human. A method for treating pre-eclampsia in a subject, the method comprising: a. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9- int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; b. comparing the expression level to a reference level for each of the transposable element subfamilies; and c. administering a treatment for pre-eclampsia to the subject if the at least 3 transposable element subfamilies are differentially expressed relative to the reference levels. The method of embodiment 45, wherein the treatment comprises an anti-hypertensive agent, an anti-inflammatory agent, and / or an anti-convulsant agent. A method for preventing pre-eclampsia in a subject, the method comprising: a. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9- int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; b. comparing the expression level to a reference level for each of the transposable element subfamilies; and c. administering a prophylactic treatment for pre-eclampsia to the subject if the at least 3 transposable element subfamilies are differentially expressed relative to the reference levels. A method of selecting a treating regimen for a subject, the method comprising: a. determining if the subject has, or is at risk of developing, pre-eclampsia, the method comprising: i. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 , ii. comparing the expression level to a reference level for each of the transposable element subfamilies, and

[0254] Hi. determining the subject has, or is at risk of developing, pre-eclampsia if the at least 3 transposable element subfamilies are differentially expressed relative to the reference levels; and b. selecting a treatment regimen for the subject if the subject has, or is at risk of developing, pre-eclampsia, the treatment regimen comprising one or more selected from the group consisting of: blood pressure monitoring, blood testing, urine testing, treatment with an antihypertensive agent, treatment with an anti-inflammatory agent, treatment with aspirin, foetal ultrasound, cardiotocography, treatment with an anticonvulsant agent, treatment with steroids, and induction of labour, or a combination thereof.

[0255] 49. A method of analysing a sample, comprising: a. isolating RNA, DNA and / or protein from the sample, and b. using the isolated RNA, DNA and / or protein to detect an expression level of at least 3 transposable element subfamilies, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1.

[0256] 50. The method of embodiment 49, wherein the RNA and / or DNA is maternal RNA and / or DNA.

[0257] 51. The method of embodiment 49 or 50, comprising separating maternal RNA and / or DNA from foetal RNA and / or DNA.

[0258] 52. The method of any of embodiments 49-51 , comprising enriching the RNA and / or DNA for maternal RNA and / or DNA.

[0259] 53. The method of any of embodiments 49-52, wherein said detecting comprises PCR, RT-qPCR, sequencing, RNA sequencing, in situ hybridisation, Western blot, immunoassay, ELISA, antibody-based assay, or a combination thereof.

[0260] 54. The method of any of embodiments 49-53, wherein said detecting comprises treating the sample with primers for each of the transposable element subfamilies.

[0261] 55. The method of any of any of embodiments 49-54, wherein the sample is a blood sample, a plasma sample, a serum sample, a cell-free RNA sample, a cell-free DNA sample, a placental biopsy, or a combination thereof. 56. A kit for determining the risk of developing pre-eclampsia, comprising means for measuring a level of at least 3 transposable element subfamilies in a sample, wherein the transposable element subfamilies are selected from the group consisting of HERVK9-int, MER11 B, L1 PA6, L1PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 , and instructions for using the kit.

[0262] 57. The kit of embodiment 56, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B and at least one selected from the group consisting of HERVK9-int, MER11 B, L1 PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HALT

[0263] 58. The kit of embodiment 56 or 57, wherein the kit comprises means for measuring the level of HERVK9-int, MER11 B and L1 PA7.

[0264] 59. The kit of any of embodiments 56-58, wherein the kit comprises means for measuring HERVK9-int, MER11 B, L1 PA6, MIR3, L1M7, and MLT2B3.

[0265] 60. The kit of any of embodiments 56-59, wherein the kit comprises means for measuring HERVK9-int, MER11 B, L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 .

[0266] 61. The kit of any of embodiments 56-60, wherein the means for measuring comprises a nucleic acid having a sequence which is complementary to a sequence of a transposable element subfamily.

[0267] 62. The kit of any of embodiments 56-61 , wherein the means for measuring comprises a primer for each of the transposable element subfamilies.

[0268] 63. The kit of any of embodiments 56-62, wherein the means for measuring comprises an antigen binding domain that specifically binds to a protein encoded by a transposable element subfamily.

[0269] 64. The kit of any of embodiments 56-63, comprising means for extracting DNA, RNA and / or protein from the sample.

Claims

1. CLAIMS1 . A method for determining the risk of developing pre-eclampsia, the method comprising determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; and comparing the expression level to a reference level for each of the transposable element subfamilies.

2. The method of claim 1 , wherein the method comprises determining an expression level of at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, or at least 11 transposable element subfamilies.

3. The method of any preceding claim, wherein a subject is at risk of developing pre-eclampsia if the expression level of HERVK9-int, MER11 B, L1 PA6, and / or AluSx4 is increased relative to the respective reference level.

4. The method of any preceding claim, wherein a subject is at risk of developing pre-eclampsia if the expression level of L1 PA7, L1M7, MER61-int, and / or HAL1 is decreased relative to the respective reference level.

5. The method of any preceding claim, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B and L1 PA7.

6. The method of any preceding claim, wherein a subject is at risk of developing pre-eclampsia if the expression levels of HERVK9-int and MER11 B are increased relative to the respective reference levels, and the expression level of L1 PA7 is decreased relative to the reference level.

7. The method of any preceding claim, wherein the method comprises determining an expression level of at least 6 transposable element subfamilies in the sample.

8. The method of any preceding claim, wherein the at least 6 transposable element subfamilies comprise HERVK9-int, MER11 B, L1 PA6, MIR3, L1 M7, and MLT2B3.

9. The method of any preceding claim, wherein a subject is at risk of developing pre-eclampsia if the expression levels of HERVK9-int, MER11 B, and L1 PA6 are increased relative to the respective reference levels, and the expression levels of MIR3, L1M7, and MLT2B3 are decreased relative to the respective reference levels.

10. The method of any preceding claim, wherein the method comprises determining an expression level of at least 11 transposable element subfamilies in the sample.

11. The method of any preceding claim, wherein the at least 11 transposable element subfamilies comprise HERVK9-int, MER11B, L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HALT12. The method of any preceding claim, wherein a subject is at risk of developing pre-eclampsia if the expression levels of HERVK9-int, MER11 B, L1 PA6, MLT2D, and AluSx4 are increased relative to the respective reference levels, and the expression levels of L1 PA7, MIR3, L1M7, MER61-int, MLT2B3, and HAL1 are decreased relative to the respective reference levels.

13. A method for diagnosing pre-eclampsia, the method comprising: determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; and comparing the expression level to a reference level for each of the transposable element subfamilies.

14. The method of any preceding claim, wherein the sample is a blood sample, a plasma sample, a serum sample, a cell-free RNA sample, a cell-free DNA sample, a placental biopsy, or a combination thereof.

15. The method of any preceding claim, wherein the sample is a cell-free RNA sample.

16. The method of any preceding claim, wherein the method determines the risk of developing pre-eclampsia in a pregnant subject, or diagnoses pre-eclampsia in a pregnant subject, wherein the gestational age of the pregnancy is 13 weeks or more.

17. A method for treating pre-eclampsia in a subject, the method comprising: a. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9- int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; b. comparing the expression level to a reference level for each of the transposable element subfamilies; and c. administering a treatment for pre-eclampsia to the subject if the at least 3 transposable element subfamilies are differentially expressed relative to the reference levels.

18. The method of claim 17, wherein the treatment comprises an anti-hypertensive agent, an antiinflammatory agent and / or an anti-convulsant agent.

19. A method for preventing pre-eclampsia in a subject, the method comprising: a. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9- int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 ; b. comparing the expression level to a reference level for each of the transposable element subfamilies; and c. administering a prophylactic treatment for pre-eclampsia to the subject if the at least 3 transposable element subfamilies are differentially expressed relative to the reference levels.

20. A method of selecting a treating regimen for a subject, the method comprising: a. determining if the subject has, or is at risk of developing, pre-eclampsia, the method comprising: i. determining an expression level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from the group consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1 , ii. comparing the expression level to a reference level for each of the transposable element subfamilies, andHi. determining the subject has, or is at risk of developing, pre-eclampsia if the at least 3 transposable element subfamilies are differentially expressed relative to the reference levels; and b. selecting a treatment regimen for the subject if the subject has, or is at risk of developing, pre-eclampsia, the treatment regimen comprising one or more selected from the group consisting of: blood pressure monitoring, blood testing, urine testing, treatment with an antihypertensive agent, treatment with an anti-inflammatory agent, treatment with aspirin, foetal ultrasound, cardiotocography, treatment with an anticonvulsant agent, treatment with steroids, and induction of labour, or a combination thereof.

21. A method of analysing a sample, comprising: a. isolating RNA, DNA and / or protein from the sample, and b. using the isolated RNA, DNA and / or protein to detect an expression level of at least 3 transposable element subfamilies, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B, and one or more selected from thegroup consisting of: L1 PA6, L1 PA7, MIR3, L1M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1.

22. A kit for determining the risk of developing pre-eclampsia, comprising means for measuring a level of at least 3 transposable element subfamilies in a sample, wherein the at least 3 transposable element subfamilies comprise HERVK9-int, MER11 B and at least one selected from the group consisting of HERVK9-int, MER11 B, L1 PA6, L1 PA7, MIR3, L1 M7, MLT2D, MER61-int, AluSx4, MLT2B3, and HAL1.

23. The kit of claim 22, wherein the means for measuring comprises a nucleic acid having a sequence which is complementary to a sequence of a transposable element subfamily.

24. The kit of claim 22 or 23, wherein the means for measuring comprises a primer for each of the transposable element subfamilies.

25. The kit of any of claims 22-24, wherein the means for measuring comprises an antigen binding domain that specifically binds to a protein encoded by a transposable element subfamily.

Images