EP4229417A1

EP4229417A1 - Proteome analysis in pulmonary hypertension

Info

Publication number: EP4229417A1
Application number: EP21801202.9A
Authority: EP
Inventors: Christopher Rhodes; Martin Wilkins; John Wharton
Original assignee: Imperial College Innovations Ltd
Current assignee: Ip2ipo Innovations Ltd
Priority date: 2020-10-15
Filing date: 2021-10-15
Publication date: 2023-08-23
Also published as: GB202016349D0; WO2022079448A1

Abstract

The present invention relates to biomarkers associated with pulmonary hypertension. In particular, the invention relates to methods for prognosis and diagnosis of pulmonary hypertension using said biomarkers. The invention further relates to the optimisation of therapy for subjects with pulmonary hypertension using said biomarkers.

Description

PROTEOME ANALYSIS IN PULMONARY HYPERTENSION FIELD OF THE INVENTION The present invention relates to biomarkers associated with pulmonary hypertension. In particular, the invention relates to methods for prognosis and diagnosis of pulmonary hypertension using said biomarkers. The invention further relates to the optimisation of therapy for subjects with pulmonary hypertension using said biomarkers. BACKGROUND OF THE INVENTION Pulmonary Hypertension (PH) is a fatal disease characterized by lung blood vessel obstruction due to excessive proliferation of vascular cells and inflammation. Similar to the Warburg effect in cancer, a shift from mitochondrial oxidation to glycolysis occurs in diseased pulmonary vessels, the infiltrated inflammatory cells and the right ventricle, as well as other molecular, translational and clinical concepts centred on the mitochondria, leading to chronic elevation of pulmonary artery pressure. The increased pulmonary pressure causes hypertrophy of the right heart and eventually failure, resulting in premature death. PH is currently classified into five separate groups with distinct pathophysiological characteristics. Rare forms include pulmonary arterial hypertension (PAH, Group 1) and PH due to pulmonary artery obstructions (Group 4, primarily chronic thromboembolic PH [CTEPH]). More common forms include usually mild elevations of pressure seen in significant cardiac (PH due to left heart disease, Group 2) and respiratory disease (PH due to lung diseases and/or hypoxia, Group 3) and PH with unclear and/or multifactorial mechanisms (Group 5). The most common symptoms of PAH are progressive breathlessness, fatigue, syncope, and clinical signs of heart failure. The mechanisms underlying PAH are complex, with multiple genetic, epigenetic and environmental mechanisms resulting in remodelling of the pulmonary vasculature. Pulmonary vascular remodelling in PAH involves medial hypertrophy/hyperplasia, intimal and adventitial fibrosis, (in situ) thrombotic lesions, and plexiform lesions, as well as perivascular infiltration of inflammatory cells (B‐ and T‐lymphocytes, mast cells, dendritic cells, macrophages, etc.). It affects mainly distal muscular‐type pulmonary arterial vessels and small pre‐capillary arterioles, but post‐capillary veins and bronchial arteries are also affected. Multiple cell types, including pulmonary arterial endothelial cells, fibroblasts, pulmonary arterial smooth muscle cells, myofibroblasts and pericytes are involved in the process of pulmonary vascular remodelling. Remodelling can be trigged by multiple factors, including trauma, environmental factors such as air

pollution and smoke exposure, and can be exacerbated by genetic/epigenetic susceptibility. PAH can also be promoted by circulating factors such as hormones and metabolites. The current licensed treatments for PAH may improve symptoms, but the benefits can be short lived and the clinical response variable between subjects. Around a third of subjects with PAH are classified as idiopathic, heritable or drug‐induced and the annual mortality in this group, even in the most experienced treatment centres, averages 10%. Despite common features in the vascular pathology on histological examination, there is evidence of heterogeneity within this subject subgroup, as seen in the individual response to specific drugs, for example, the response to calcium antagonists, and in the emerging underlying genetic architecture. Early effective intervention is thought to be beneficial, leading to the use of combination, specifically dual or triple, drug therapy from diagnosis, and to interest in screening the relatives of subjects with a family history of PAH to detect the early onset of pulmonary hypertension. Current screening strategies for PAH are based on studies in at‐risk disease populations, such as systemic sclerosis, and involve a combination of biochemistry and non‐invasive clinical assessments. The penetrance of pathogenic mutations in PAH is low, with best estimates suggesting that around a fifth of carriers will develop the disease in their lifetime. Attempts to screen these individuals once a year by formal clinical examination at specialist centres is challenging; individuals who feel well frequently do not attend. Furthermore, the only current biomarkers for PAH are N‐terminal pro‐ brain natriuretic peptide (NT‐proBNP) and troponin. Both of these are cardiac markers (reporting on cardiac function) and as such its expression is typically increased in late‐stage disease where include an element of heart failure. To‐date, no biomarkers for early stage PAH have been proven for clinical use. Accordingly, there is an urgent need in the art for effective means for the early diagnosis and prognosis of PH, particularly PAH, especially in the form of point‐of‐care (POC) testing. In particular, a blood test for the early detection of PAH would be highly desirable. There is also a need for a better understanding of the molecular drivers of PAH to assist in the development of improved drugs. It is an object of the present invention to address these challenges and to provide an effective means for screening subjects for PH, particularly PAH, as well as new therapeutic targets for PH, particularly PAH. SUMMARY OF THE INVENTION The plasma proteome, the totality of proteins in plasma secreted and leaked from tissues, including the vascular bed, offers a measure of health as circulating levels change with disease. To‐ date, this has been under‐explored in PAH. The inventors have used plasma proteomics to separate

subjects with PAH into low‐ and high‐risk groups using an aptamer‐based assay. In particular, the inventors have quantified more than 4000 proteins, to develop a small panel of plasma proteins identified from an unbiased screen. The inventors have surprisingly demonstrated that a panel of 6 proteins can successfully classify risk, inform the response to treatment and predict the emergence of PAH in relatives of subjects with PAH. The six proteins which may be used as biomarkers for PH, particularly for PAH, are neuropilin‐1 (NRP1), peroxiredoxin‐4 (PRDX4), peroxidasin homolog (PXDN), sushi, von Willebrand factor type A, EGF and pentraxin domain‐containing protein 1 (SVEP1), thrombosponin‐2 (TSP2) and renin. The biomarkers of the invention report directly upon vascular remodelling that occurs during PH (e.g. PAH), and as such changes in the levels of these biomarkers precedes cardiac pathology. Advantageously, therefore, the biomarker panel of the invention allows for accurate prediction in right heart strain and cardiac function, enabling earlier diagnosis or prognostic determination. In the context of optimising treatment, use of these earlier biomarkers for PH (e.g. PAH) allow for greater granularity in the stratification of clinical risk, potentially allowing clinicians to make decisions about treatment options earlier, and ultimately improving clinical outcome. Furthermore, the inventors have demonstrated that the biomarker panel of the invention has utility independent of established clinical diagnostic/prognostic tools, meaning that it could be used as a standalone assay, or in combination with one or more of the established tools. The inventors have further demonstrated that netrin‐4, TSP2 and endoglin are all causally linked with PH, particularly PAH. In particular, netrin‐4 activity is increased in PAH, and TSP2 and endoglin activity is decreased in PAH. The invention further relates to therapy for PH (particularly PAH) using an agent which inhibits netrin‐4 activity; an agent which increases TSP2 activity; an agent which increase endoglin activity. Accordingly, the present invention provides a method for diagnosing or determining a prognosis for pulmonary arterial hypertension (PAH), the method comprising: (a) quantifying the amount of two or more biomarkers present in a sample obtained from a subject, wherein the two or more biomarkers are selected from Sushi, Von Willebrand Factor Type A, EGF And Pentraxin Domain‐Containing Protein 1 (SVEP1), peroxidasin (PXDN), renin, neuropilin 1 (NRP1), thrombospondin 2 (TSP2) and peroxiredoxin‐4 (PRDX4); (b) comparing the amount of the two or more biomarkers with the amount of the same two or more biomarkers in a reference standard; and thereby diagnosing or determining a prognosis for PAH. The invention further provides a method for optimising therapy for a subject undergoing treatment for PAH, the method comprising: (a) quantifying the amount of two or more biomarkers present in a sample obtained from a subject, wherein the two or more biomarkers are selected from

SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4; (b) comparing the amount of the two or more biomarkers with the amount of the same two or more biomarkers in a reference standard; and (i) changing the therapy if the amount of the two or more biomarkers is increased relative to the reference standard; or (ii) maintaining the therapy if the amount of the two or more biomarkers is the same or lower relative to the reference standard. The step of comparing the amount of the two or more biomarkers with the amount of the same two or more biomarkers in a reference standard in a method of the invention may comprise calculating a single protein score for the two or more biomarkers. The single protein score may be a weighted combination score of the two or more biomarkers. Calculating the single protein score may comprise calculating z‐scores for the two or more biomarkers relative to the two or more biomarkers in the reference standard, weighting the z‐scores and adding the z‐scores for the two or more biomarkers to arrive at the single protein score. Weighting the z‐scores may comprise multiplying the z‐scores for the two or more biomarkers by the corresponding coefficient set out in Table 1. A method of the invention may comprise (a) (i) diagnosing PAH when the single protein score is at least 1; or (ii) not diagnosing PAH when the single protein score is less than 1; (b) (i) determining a prognosis for PAH of the subject being at high risk of PAH progression when the single protein score is at least 0.57; or (ii) determining a prognosis for PAH of the subject being at low risk of PAH progression when the single protein score is less than 0.57; or (c) (i) changing the subject’s therapy when the single protein score is at least 0.57; or (ii) maintaining the subject’s therapy when the single protein score is less than 0.57. A method of the invention may comprise quantifying the amount of two, three, four, five or six of the biomarkers. The two or more biomarkers may comprise or consist of: (a) at least one of SVEP1, PXDN, NRP1 and TSP2; (b) renin and TSP2; (c) renin, NRP1 and TSP2; (d) renin, NRP1, TSP2 and PRDX4; (e) PXDN, renin, NRP1, TSP2 and PRDX4; or (f) SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4. The amount of each the two or more biomarkers may be quantified in a method of the invention using an aptamer‐based assay, ELISA, microarray analysis and/or quantitative real‐time PCR (qPCR). Said aptamer‐based assay may use slow off‐rate modified aptamers; and/or be a multiplex aptamer‐based assay. The method of the invention may use a sample which is a biofluid sample, preferably the sample may be a blood sample a serum sample or a plasma sample. The method of the invention may use a reference standard that is: (i) a non‐PAH reference standard; or (ii) a PAH reference standard.

The method of the invention may further comprise: (a) quantifying the amount of one or more additional biomarker for PAH, wherein preferably said one or more additional biomarker for PAH is N‐terminal prohormone of brain natriuretic peptide (NT‐proBNP) in the sample; (b) measuring the pulmonary arterial pressure (PAP) of the subject; (c) measuring the cardiac index of the subject; and/or (d) determining the six‐minute walk distance (6MWD) of the subject. The method of the invention may comprise determining the amount of two or more biomarkers in the subject at least twice using a separate sample taken each time the amount of the two or more biomarkers is quantified. The method of the invention may comprise the use of a sample, wherein: (a) the sample is taken before treatment initiation; (b) the sample is taken after treatment initiation; or (c) separate samples are taken before and after treatment initiation. The method of the invention may further comprise recording the output of at least one step on a data‐storage medium. The invention further provides a data‐storage medium comprising data obtained by a method of the invention. The invention also provides a computer program product comprising program instructions to cause a processor to perform a method of the invention. The invention further provides a method of treating PAH, the method comprising: (a) obtaining the results of a method of diagnosis, a method of determining a prognosis or a method for optimising therapy according to the invention; (b) administering a PAH therapy when PAH is diagnosed (or a prognosis of high‐risk is determined or a current therapy deemed ineffective); and (c) optionally administering a different therapy when PAH is not diagnosed (or a prognosis of low‐ risk is determined or a current therapy deemed effective). A PAH therapy for use in a method of treatment of the invention may be selected from a TGFβ superfamily ligand trap, an endothelin receptor antagonist, particularly a selective ET_A receptor antagonist, a phosphodiesterase type 5 (PDE5) inhibitor, a prostanoid analogue or agonist, particularly a prostaglandin I2 (PGI₂) analogue or agonist, a nitric oxide stimulator, a tyrosine kinase inhibitor, or a combination thereof; wherein optionally the PAH therapy is selected from sotatercept, sildenafil, ambrisentan, iloprost, macitentan,imatinib, epoprostenol, riociguat, selexipag, tadalafil and bosentan or a combination thereof. The invention further provides the use of two or more of SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4 as biomarkers for PAH. The invention also provides a device for carrying out a method of diagnosis, a method of determining a prognosis or a method for optimising therapy according to the invention, which

comprises reagents for quantification of the two or more biomarkers; wherein optionally the device further comprises an internal control. The reagents for quantification of the two or more biomarkers comprised in a device of the invention may comprise: (a) one or more aptamer specific for each of the two or more biomarkers; (b) one or more antibody specific for each of the two or more biomarkers; or (c) one or more antibody for at least one of the two or more biomarkers, and one or more aptamer specific for the two or more biomarkers for which an antibody is not provided. The invention further provides a kit comprising reagents for quantification of two or more biomarkers selected from SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4, wherein preferably the kit comprises reagents for the quantification of SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4. The reagents for quantification of the two or more biomarkers in a kit of the invention may be for quantification of the two or more biomarkers by an aptamer‐based assay or by ELISA. The kit may further comprise standards for use in quantifying the two or more biomarkers by an aptamer‐ based assay or by ELISA. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1: Study flow‐chart Figure 2: Hazard ratios for protein aptamers associated with outcomes in PAH subjects. Thirty‐three aptamers (detecting 31 proteins) were independent of both 6MWD (A) and NT‐proBNP (B). Dashed line, p<0.05 Figure 3: Accuracy of the prognostic model in the cross‐validation analysis. Plot shows a combination of 19 proteins plus age and sex (left dashed line, minimum error) and 6 proteins (right dashed line, minimum error plus 1 standard error to reduce over‐fitting) selected by LASSO analysis. Figure 4: ROC analysis of NT‐proBNP and 6 protein model score, individually and combined. Figure 5: NT‐proBNP, 6‐protein model and ‘proteins plus NT‐proBNP’ model scores in relatives being screened for PAH. Figure 6: Relatives who developed PAH during screening periods of 2‐4 years. Zero point on x‐axis indicates date of catheterisation measuring pulmonary artery pressure above 25 mmHg (PA Mean Baseline plotted). Treatment started following diagnosis. NT‐proBNP, plasma N‐terminal pro‐brain natriuretic peptide, measured by aptamer; 6MWD, six‐minute walk distance (scaled by 10m increment on second y‐axis). Figure 7: Relative of subject with PAH who developed pulmonary hypertension and left ventricular diastolic dysfunction after 10 yrs follow up. Zero point on x‐axis indicates date of catheterisation

measuring pulmonary artery pressure above 25 mmHg (PA Mean Baseline plotted). NT‐proBNP, plasma N‐terminal pro‐brain natriuretic peptide, measured by aptamer; 6MWD, six‐minute walk distance (scaled by 10m increment on second y‐axis). Figure 8: PAH subject who responded after commencing two experimental PAH therapies, after deterioration of PAH following standard therapies over a follow‐up of over 6 years. Zero point on x‐ axis indicates date of catheterisation measuring pulmonary artery pressure above 25 mmHg (PA Mean Baseline plotted). NT‐proBNP, plasma N‐terminal pro‐brain natriuretic peptide, measured by aptamer; 6MWD, six‐minute walk distance (scaled by 10m increment on second y‐axis). Figure 9: ROC analysis of individual proteins from the 6‐protein panel, as well as 2‐, 3‐, 4‐ and 5‐ protein combinations. Figure 10: Chart illustrating power of the panel with 2‐, 3‐, 4‐ and 5‐protein combinations (loss of best/worst proteins for each). Figure 11: Proteomics and genomics analytic workflow leading to the Mendelian randomisation studies. Figure 12: Protein association with PAH compared to healthy controls. (A) A volcano plot of aptamers representing 208 independent proteins that met FDR (q<0.05, blue dots) in both discovery and replication analysis. Dependent proteins were no longer associated after correcting for renal function or anticoagulation therapy. ‘Not replicated’ proteins only met FDR in the discovery analysis and those ‘Not associated’ failed to meet FDR in discovery analysis. (B) Protein interaction network derived from STRING database. Proteins are coloured by clusters using the MCL algorithm and only proteins with high confidence (interaction score>0.9) are depicted. Figure 13: Venn diagram shows overlap between proteins that discriminate subjects with PAH from healthy control subjects, proteins associated with prognosis in PAH, and protein instruments for Mendelian randomisation studies. Figure 14: Increased Netrin‐4 protein expression in human IPAH lungs. Immunohistochemical Netrin‐ 4 staining in human non‐PAH donor (upper panel) and idiopathic pulmonary arterial hypertension (IPAH, lower panel) lung sections, demonstrating increased Netrin‐4 protein expression in distal pulmonary vessels of idiopathic PAH subjects. n=3 subjects. Scale bar: 20um. Figure 15: ROC analysis directly compares performance in predicting 5‐year survival of novel 6‐ protein model and published 9‐protein panel score. Figure 16: Confirmation of proteomic measurements of four proteins of interest by targeted commercial assays in PAH patient plasma samples selected with a range of protein levels from the proteomic data. A. Thrombospondin‐2 (TSP‐2, n=20) B. Neuropilin‐1 (NRP1, n=20), C. Renin (n=80), D. PRDX4 (n=62).

DETAILED DESCRIPTION OF THE INVENTION Definitions Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. Singleton, et al., DICTIONARY OF MICROBIOLOGY AND MOLECULAR BIOLOGY, 20 ED., John Wiley and Sons, New York (1994), and Hale & Marham, THE HARPER COLLINS DICTIONARY OF BIOLOGY, Harper Perennial, NY (1991) provide the skilled person with a general dictionary of many of the terms used in this disclosure. The meaning and scope of the terms should be clear; however, in the event of any latent ambiguity, definitions provided herein take precedent over any dictionary or extrinsic definition. It should be understood that this invention is not limited to the particular methodology, protocols, and reagents, etc., described herein and as such can vary. This disclosure is not limited by the exemplary methods and materials disclosed herein, and any methods and materials similar or equivalent to those described herein can be used in the practice or testing of embodiments of this disclosure. The terminology used herein is for the purpose of describing particular embodiments only, and is not intended to limit the scope of the present invention, which is defined solely by the claims. The description of embodiments of the disclosure is not intended to be exhaustive or to limit the disclosure to the precise form disclosed. While specific embodiments of, and examples for, the disclosure are described herein for illustrative purposes, various equivalent modifications are possible within the scope of the disclosure, as those skilled in the relevant art will recognize. For example, while method steps or functions are presented in a given order, alternative embodiments may perform functions in a different order, or functions may be performed substantially concurrently. The teachings of the disclosure provided herein can be applied to other procedures or methods as appropriate. The various embodiments described herein can be combined to provide further embodiments. Aspects of the disclosure can be modified, if necessary, to employ the compositions, functions and concepts of the above references and application to provide yet further embodiments of the disclosure. Moreover, due to biological functional equivalency considerations, some changes can be made in protein structure without affecting the biological or chemical action in kind or amount. These and other changes can be made to the disclosure in light of the detailed description. All such modifications are intended to be included within the scope of the appended claims. Unless otherwise indicated, any nucleic acid sequences are written left to right in 5' to 3' orientation; amino acid sequences are written left to right in amino to carboxy orientation, respectively

The headings provided herein are not limitations of the various aspects or embodiments of this disclosure. As used herein, the term "capable of' when used with a verb, encompasses or means the action of the corresponding verb. For example, "capable of interacting" also means interacting, "capable of cleaving" also means cleaves, "capable of binding" also means binds and "capable of specifically targeting…" also means specifically targets. Other definitions of terms may appear throughout the specification. Before the exemplary embodiments are described in more detail, it is to be understood that this disclosure is not limited to particular embodiments described, and as such may vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present disclosure will be defined only by the appended claims. Numeric ranges are inclusive of the numbers defining the range. Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limits of that range is also specifically disclosed. Each smaller range between any stated value or intervening value in a stated range and any other stated or intervening value in that stated range is encompassed within this disclosure. The upper and lower limits of these smaller ranges may independently be included or excluded in the range, and each range where either, neither or both limits are included in the smaller ranges is also encompassed within this disclosure, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in this disclosure. As used herein, the articles "a" and “an” may refer to one or to more than one (e.g. to at least one) of the grammatical object of the article. Further, unless otherwise required by context, singular terms shall include pluralities and plural terms shall include the singular. In this application, the use of "or" means "and/or" unless stated otherwise. Furthermore, the use of the term "including", as well as other forms, such as "includes" and "included", is not limiting. “About” may generally mean an acceptable degree of error for the quantity measured given the nature or precision of the measurements. Exemplary degrees of error are within 20 percent (%), typically, within 10%, and more typically, within 5% of a given value or range of values. Preferably, the term “about” shall be understood herein as plus or minus (±) 5%, preferably ± 4%, ± 3%, ± 2%, ± 1%, ± 0.5%, ± 0.1%, of the numerical value of the number with which it is being used.

The term "consisting of'' refers to compositions, methods, and respective components thereof as described herein, which are exclusive of any element not recited in that description of the invention. As used herein the term "consisting essentially of'' refers to those elements required for a given invention. The term permits the presence of elements that do not materially affect the basic and novel or functional characteristic(s) of that invention (i.e. inactive or non‐immunogenic ingredients). Embodiments described herein as “comprising” one or more features may also be considered as disclosure of the corresponding embodiments “consisting of” and/or “consisting essentially of” such features. Concentrations, amounts, volumes, percentages and other numerical values may be presented herein in a range format. It is also to be understood that such range format is used merely for convenience and brevity and should be interpreted flexibly to include not only the numerical values explicitly recited as the limits of the range but also to include all the individual numerical values or sub‐ranges encompassed within that range as if each numerical value and sub‐range is explicitly recited. Amino acids are referred to herein using the name of the amino acid, the three‐letter abbreviation or the single letter abbreviation. As used herein, the terms "protein" and "polypeptide" are used interchangeably herein to designate a series of amino acid residues, connected to each other by peptide bonds between the alpha‐amino and carboxyl groups of adjacent residues. The terms "protein", and "polypeptide" refer to a polymer of amino acids, including modified amino acids (e.g., phosphorylated, glycated, glycosylated, etc.) and amino acid analogues, regardless of its size or function. "Protein" and "polypeptide" are often used in reference to relatively large polypeptides, whereas the term "peptide" is often used in reference to small polypeptides, but usage of these terms in the art overlaps. The terms "protein" and "polypeptide" are used interchangeably herein when referring to a gene product and fragments thereof. Thus, exemplary polypeptides or proteins include gene products, naturally occurring proteins, homologs, orthologs, paralogs, fragments and other equivalents, variants, fragments, and analogues of the foregoing. Minor variations in the amino acid sequences of proteins of the invention are contemplated as being encompassed by the present invention, providing that the variations in the amino acid sequence(s) maintain at least 60%, at least 70%, more preferably at least 80%, at least 85%, at least 90%, at least 95%, and most preferably at least 97% or at least 99% sequence identity to the proteins of the invention or an immunogenic fragment thereof as defined anywhere herein. The term

homology is used herein to mean identity. As such, the sequence of a variant or analogue sequence of a protein of the invention may differ on the basis of substitution (typically conservative substitution) deletion or insertion. Proteins of the invention may include variants in which amino acid residues from one species are substituted for the corresponding residue in another species, either at the conserved or non‐conserved positions. Variants of protein molecules disclosed herein may be produced and used in the present invention. Following the lead of computational chemistry in applying multivariate data analysis techniques to the structure/property‐activity relationships [see for example, Wold, et al. Multivariate data analysis in chemistry. Chemometrics‐Mathematics and Statistics in Chemistry (Ed.: B. Kowalski); D. Reidel Publishing Company, Dordrecht, Holland, 1984 (ISBN 90‐277‐1846‐6] quantitative activity‐property relationships of proteins can be derived using well‐known mathematical techniques, such as statistical regression, pattern recognition and classification [see for example Norman et al. Applied Regression Analysis. Wiley‐lnterscience; 3rd edition (April 1998) ISBN: 0471170828; Kandel, Abraham et al. Computer‐Assisted Reasoning in Cluster Analysis. Prentice Hall PTR, (May 11, 1995), ISBN: 0133418847; Krzanowski, Wojtek. Principles of Multivariate Analysis: A User's Perspective (Oxford Statistical Science Series, No 22 (Paper)). Oxford University Press; (December 2000), ISBN: 0198507089; Witten, Ian H. et al Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann; (October 11, 1999), ISBN:1558605525; Denison David G. T. (Editor) et al Bayesian Methods for Nonlinear Classification and Regression (Wiley Series in Probability and Statistics). John Wiley & Sons; (July 2002), ISBN: 0471490369; Ghose, Arup K. et al. Combinatorial Library Design and Evaluation Principles, Software, Tools, and Applications in Drug Discovery. ISBN: 0‐8247‐0487‐8]. The properties of proteins can be derived from empirical and theoretical models (for example, analysis of likely contact residues or calculated physicochemical property) of proteins sequence, functional and three‐dimensional structures and these properties can be considered individually and in combination. Amino acids are referred to herein using the name of the amino acid, the three‐letter abbreviation or the single letter abbreviation. The term “protein", as used herein, includes proteins, polypeptides, and peptides. As used herein, the term “amino acid sequence” is synonymous with the term “polypeptide” and/or the term “protein”. In some instances, the term “amino acid sequence” is synonymous with the term “peptide”. The terms "protein" and "polypeptide" are used interchangeably herein. In the present disclosure and claims, the conventional one‐letter and three‐ letter codes for amino acid residues may be used. The 3‐letter code for amino acids as defined in conformity with the IUPACIUB Joint Commission on Biochemical Nomenclature (JCBN). It is also

understood that a polypeptide may be coded for by more than one nucleotide sequence due to the degeneracy of the genetic code. Amino acid residues at non‐conserved positions may be substituted with conservative or non‐conservative residues. In particular, conservative amino acid replacements are contemplated. A “conservative amino acid substitution” is one in which the amino acid residue is replaced with an amino acid residue having a similar side chain. Families of amino acid residues having similar side chains have been defined in the art, including basic side chains (e.g., lysine, arginine, or histidine), acidic side chains (e.g., aspartic acid or glutamic acid), uncharged polar side chains (e.g., glycine, asparagine, glutamine, serine, threonine, tyrosine, or cysteine), nonpolar side chains (e.g., alanine, valine, leucine, isoleucine, proline, phenylalanine, methionine, or tryptophan), beta‐ branched side chains (e.g., threonine, valine, isoleucine) and aromatic side chains (e.g., tyrosine, phenylalanine, tryptophan, or histidine). Thus, if an amino acid in a polypeptide is replaced with another amino acid from the same side chain family, the amino acid substitution is considered to be conservative. The inclusion of conservatively modified variants in a protein of the invention does not exclude other forms of variant, for example polymorphic variants, interspecies homologs, and alleles. “Non‐conservative amino acid substitutions” include those in which (i) a residue having an electropositive side chain (e.g., Arg, His or Lys) is substituted for, or by, an electronegative residue (e.g., Glu or Asp), (ii) a hydrophilic residue (e.g., Ser or Thr) is substituted for, or by, a hydrophobic residue (e.g., Ala, Leu, Ile, Phe or Val), (iii) a cysteine or proline is substituted for, or by, any other residue, or (iv) a residue having a bulky hydrophobic or aromatic side chain (e.g., Val, His, Ile or Trp) is substituted for, or by, one having a smaller side chain (e.g., Ala or Ser) or no side chain (e.g., Gly). “Insertions” or “deletions” are typically in the range of about 1, 2, or 3 amino acids. The variation allowed may be experimentally determined by systematically introducing insertions or deletions of amino acids in a protein using recombinant DNA techniques and assaying the resulting recombinant variants for activity. This does not require more than routine experiments for a skilled person. A “fragment” of a polypeptide comprises at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95%, at least 97% or more of the original polypeptide. A typical antibody comprises at least two “light chains” (LC) and two "heavy chains” (HC). The light chains and heavy chains of such antibodies are polypeptides consisting of several domains. Each heavy chain comprises a heavy chain variable region (abbreviated herein as “VH”) and a heavy chain constant region (abbreviated herein as “CH”). The heavy chain constant region comprises the heavy chain constant domains CH1, CH2 and CH3 (antibody classes IgA, IgD, and IgG) and optionally

the heavy chain constant domain CH4 (antibody classes IgE and IgM). Each light chain comprises a light chain variable domain (abbreviated herein as “VL”) and a light chain constant domain (abbreviated herein as “CL”). The variable regions VH and VL can be further subdivided into regions of hypervariability, termed complementarity determining regions (CDR), interspersed with regions that are more conserved, termed framework regions (FR). Each VH and VL is composed of three CDRs and four FRs, arranged from amino‐terminus to carboxy‐terminus in the following order: FR1, CDR1, FR2, CDR2, FR3, CDR3, FR4. The “constant domains” of the heavy chain and of the light chain are not involved directly in binding of an antibody to a target, but exhibit various effector functions. Binding between an antibody and its target antigen or epitope is mediated by the Complementarity Determining Regions (CDRs). The CDRs are regions of high sequence variability, located within the variable region of the antibody heavy chain and light chain, where they form the antigen‐binding site. The CDRs are the main determinants of antigen specificity. Typically, the antibody heavy chain and light chain each comprise three CDRs which are arranged non‐ consecutively. The antibody heavy and light chain CDR3 regions play a particularly important role in the binding specificity/affinity of the antibodies according to the invention and therefore provide a further aspect of the invention. Thus, the term “antigen binding fragment” as used herein incudes any naturally‐occurring or artificially‐constructed configuration of an antigen‐binding polypeptide comprising one, two or three light chain CDRs, and/or one, two or three heavy chain CDRs, wherein the polypeptide is capable of binding to the antigen. The sequence of a CDR may be identified by reference to any number system known in the art, for example, the Kabat system (Kabat, E. A., et al., Sequences of Proteins of Immunological Interest, 5th ed., Public Health Service, National Institutes of Health, Bethesda, MD (1991); the Chothia system (Chothia &, Lesk, “Canonical Structures for the Hypervariable Regions of Immunoglobulins,” J. Mol. Biol. 196, 901–917 (1987)); or the IMGT system (Lefranc et al., “IMGT Unique Numbering for Immunoglobulin and Cell Receptor Variable Domains and Ig superfamily V‐ like domains,” Dev. Comp. Immunol. 27, 55–77 (2003)). For heavy chain constant region amino acid positions discussed in the invention, numbering is according to the EU index first described in Edelman, G.M., et al., Proc. Natl. Acad. Sci. USA 63 (1969) 78‐85). The EU numbering of Edelman is also set forth in Kabat et al. (1991) (supra.). Thus, the terms “EU index as set forth in Kabat”, “EU Index”. “EU index of Kabat” or “EU numbering” in the context of the heavy chain refers to the residue numbering system based on the human lgG1 EU antibody of Edelman et al. as set forth in Kabat et al. (1991). The numbering system used for the light chain constant region amino acid sequence is similarly set forth in Kabat et al. (supra.). Thus, as

used herein, “numbered according to Kabat” refers to the Kabat numbering system set forth in Kabat et al. (supra.). The antibodies of the invention or antigen‐binding fragments thereof are preferably monoclonal antibodies. More preferably, the antibodies of the invention or antigen‐binding fragments thereof are isolated monoclonal antibodies. The term “humanized antibody” refers to antibodies in which the framework or “complementarity determining regions” (CDRs) have been modified to comprise the CDR of an immunoglobulin of different specificity as compared to that of the parent immunoglobulin. For example, a murine CDR may be grafted into the framework region of a human antibody to prepare the “humanized antibody.” See, e.g., Riechmann, L., et al., Nature 332 (1988) 323‐327; and Neuberger, M.S., et al., Nature 314 (1985) 268‐270. In some embodiments, “humanized antibodies” are those in which the constant region has been additionally modified or changed from that of the original antibody to generate the properties of the antibodies according to the invention, especially in regard to Clq binding and/or Fc receptor (FcR) binding. The term “chimeric antibody” refers to an antibody comprising a variable region, i.e., binding region, from one source or species and at least a portion of a constant region derived from a different source or species, usually prepared by recombinant DNA techniques. Chimeric antibodies comprising a murine variable region and a human constant region are preferred. Other preferred forms of “chimeric antibodies” encompassed by the present invention are those in which the constant region has been modified or changed from that of the original antibody to generate the properties of the antibodies according to the invention, especially in regard to Clq binding and/or Fc receptor (FcR) binding. Such chimeric antibodies are also referred to as “class‐switched antibodies”. Chimeric antibodies are the product of expressed immunoglobulin genes comprising DNA segments encoding immunoglobulin variable regions and DNA segments encoding immunoglobulin constant regions. Methods for producing chimeric antibodies involving conventional recombinant DNA and gene transfection techniques are well known in the art. See, e.g., Morrison, S.L., et al., Proc. Natl. Acad. Sci. USA 81 (1984) 6851‐6855; US Patent Nos. 5,202,238 and 5,204,244. The terms “Fc region”, “Fc part” and “Fc” are used interchangeably herein and refer to the portion of a native immunoglobulin that is formed by two Fc chains. Each “Fc chain” comprises a constant domain CH2 and a constant domain CH3. Each Fc chain may also comprise a hinge region. A native Fc region is homodimeric. In some embodiments, the Fc region may be heterodimeric because it may contain modifications to enforce Fc heterodimerization. There are five major classes of heavy chain constant region, classified as IgA, IgG, IgD, IgE and IgM, each with characteristic effector functions designated by isotype. For example, IgG is

separated into four subclasses known as IgGl, IgG2, IgG3, and IgG4. Ig molecules interact with multiple classes of cellular receptors. For example, IgG molecules interact with three classes of Fcγ receptors (FcγR) specific for the IgG class of antibody, namely FcγRI, FcγRII, and FcγRIII. The important sequences for the binding of IgG to the FcγR receptors have been reported to be located in the CH2 and CH3 domains. The antibodies of the invention or antigen‐binding fragments thereof may be any isotype, i.e. IgA, IgD, IgE, IgG and IgM, and synthetic multimers of the four‐chain immunoglobulin (Ig) structure. The terms “Fab fragment” and “Fab” are used interchangeably herein and contain a single light chain (e.g. a constant domain CL and a VL) and a single heavy chain (e.g. the constant domain CH1 and a VH). The heavy chain of a Fab fragment is not capable of forming a disulfide bond with another heavy chain. A “Fab' fragment” contains a single light chain and a single heavy chain but in addition to the CH1 and the VH, a “Fab' fragment” contains the region of the heavy chain between the CH1 and CH2 domains that is required for the formation of an inter‐chain disulfide bond. Thus, two “Fab' fragments” can associate via the formation of a disulphide bond to form a F(ab')2 molecule. A “F(ab')2 fragment” contains two light chains and two heavy chains. Each chain includes a portion of the constant region necessary for the formation of an inter‐chain disulfide bond between two heavy chains. An “Fv fragment” contains only the variable regions of the heavy and light chain. It contains no constant regions. A “single‐domain antibody” is an antibody fragment containing a single antibody domain unit (e.g., VH or VL). A “single‐chain Fv” (“scFv”) is antibody fragment containing the VH and VL domain of an antibody, linked together to form a single chain. A polypeptide linker is commonly used to connect the VH and VL domains of the scFv. A “tandem scFv”, also known as a TandAb®, is a single‐chain Fv molecule formed by covalent bonding of two scFvs in a tandem orientation with a flexible peptide linker. A “bi‐specific T cell engager” (BiTE®) is a fusion protein consisting of two single‐chain variable fragments (scFvs) on a single peptide chain. One of the scFvs binds to T cells via the CD3 receptor, and the other to a tumour cell antigen. A “diabody” is a small bivalent and bispecific antibody fragment comprising a heavy (VH) chain variable domain connected to a light chain variable domain (VL) on the same polypeptide chain (VH‐VL) connected by a peptide linker that is too short to allow pairing between the two

domains on the same chain (Kipriyanov, Int. J. Cancer 77 (1998), 763‐772). This forces pairing with the complementary domains of another chain and promotes the assembly of a dimeric molecule with two functional antigen binding sites. The antibodies of the invention or antigen‐binding fragments thereof also include derivatives that are modified (e.g., by the covalent attachment of any type of molecule to the antibody) such that covalent attachment does not prevent the antibody from binding to its epitope, or otherwise impair the biological activity of the antibody. Examples of suitable derivatives include, but are not limited to fucosylated antibodies, glycosylated antibodies, acetylated antibodies, PEGylated antibodies, phosphorylated antibodies, and amidated antibodies. Further embodiments are multispecific antibodies (bispecific, trispecific etc.) and other conjugates, e.g. with cytotoxic small molecules. As used herein, the terms “polynucleotides”, "nucleic acid" and "nucleic acid sequence" refers to any molecule, preferably a polymeric molecule, incorporating units of ribonucleic acid, deoxyribonucleic acid or an analogue thereof. The nucleic acid can be either single‐stranded or double‐stranded. A single‐stranded nucleic acid can be one nucleic acid strand of a denatured double‐ stranded DNA Alternatively, it can be a single‐stranded nucleic acid not derived from any double‐stranded DNA. In one aspect, the nucleic acid can be DNA. In another aspect, the nucleic acid can be RNA Suitable nucleic acid molecules are DNA, including genomic DNA or cDNA. Other suitable nucleic acid molecules are RNA, including siRNA, shRNA, and antisense oligonucleotides. In the context of the present invention, a "biomarker" is a protein or a fragment or peptide thereof, that is present in the biological sample and that may be isolated from, or measured in, the biological sample. A biomarker can be the entire intact molecule, or it can be a portion thereof that may be partially functional or recognized, for example, by an antibody or other specific binding member. A biomarker is considered to be informative if a measurable aspect or characteristic of the biomarker is associated with a given state of a subject, such as the presence of PH, particularly PAH. Such a measurable aspect or characteristic may include, for example, the presence, absence, or concentration of the biomarker in the biological sample from the individual and/or its presence as part of a profile of biomarkers. Such a measurable aspect of a biomarker is defined herein as a "feature." For example, the presence of a biomarker may be a feature. As another example, the amount of a biomarker in a sample, or the amount of a biomarker in a sample compared with a control or reference sample may be a feature. A feature may also be a ratio of two or more measurable aspects of biomarkers, which biomarkers may or may not be of known identity, for example. A "biomarker profile" comprises at least two such features, where the features can correspond to the same or different classes of biomarkers such as, for example, two proteins or a

nucleic acid and a protein. A biomarker profile may also comprise at least multiple features. A biomarker profile may comprise at least one measurable aspect of at least one internal standard. Exemplary, but non‐limiting amino acid sequences of NRP1, PRDX4, PXDN, SVEP1, TSP2 and renin may comprise or consist of: ^ NRP1 – UniProt Accession No. O14786 (version 3 of the sequence, sequence for the entry last modified 23 September 2008), SEQ ID NO: 1; ^ PRDX4 – UniProt Accession No. Q13162 (version 1 of the sequence, sequence for the entry last modified 01 November 1996), SEQ ID NO: 2; ^ PXDN – UniProt Accession No. Q92626 (version 2 of the sequence, sequence for the entry last modified 26 February 2008), SEQ ID NO: 3; ^ SVEP1 – UniProt Accession No. Q4LDE5 (version 3 of the sequence, sequence for the entry last modified 18 May 2010), SEQ ID NO: 4; ^ TSP2 – UniProt Accession No. P35442 (version 2 of the sequence, sequence for the entry last modified 25 November 2008), SEQ ID NO: 5; and ^ renin – UniProt Accession No. P00797 (version 1 of the sequence, sequence for the entry last modified 1 January 1988), SEQ ID NO: 6. Variants and fragments of NRP1, PRDX4, PXDN, SVEP1, TSP2 and renin are also envisaged as biomarkers according to the invention. The terms "decrease", "reduced", "reduction", or "inhibit" are all used herein to mean a decrease by a statistically significant amount. The terms "reduce," "reduction" or "decrease" or "inhibit" typically means a decrease by at least 10% as compared to a reference level (e.g. the absence of a given treatment) and can include, for example, a decrease by at least about 10%, at least about 20%, at least about 25%, at least about 30%, at least about 35%, at least about 40%, at least about 45%, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 98%, at least about 99% , or more. As used herein, "reduction" or "inhibition" encompasses a complete inhibition or reduction as compared to a reference level. "Complete inhibition" is a 100% inhibition (i.e. abrogation) as compared to a reference level. A decrease can be preferably down to a level accepted as within the range of normal for an individual without a given disorder. The terms "increased", "increase", "enhance", or "activate" are all used herein to mean an increase by a statically significant amount. The terms "increased", "increase", "enhance", or "activate" can mean an increase of at least 10% as compared to a reference level, for example an increase of at least about 20%, or at least about 30%, or at least about 40%, or at least about 50%, or

at least about 60%, or at least about 70%, or at least about 80%, or at least about 90% or up to and including a 100% increase or any increase between 10‐100% as compared to a reference level, or at least about a 2‐fold, or at least about a 3‐fold, or at least about a 4‐fold, or at least about a 5‐fold or at least about a 10‐fold increase, or any increase between 2‐fold and 10‐fold or greater as compared to a reference level. In the context of a marker or symptom, an "increase" is a statistically significant increase in such level. The terms "individual”, "subject”, and "patient”, are used interchangeably herein to refer to a mammalian subject for whom diagnosis, prognosis, disease monitoring, treatment, therapy, and/or therapy optimisation is desired. The mammal can be (without limitation) a human, non‐ human primate, mouse, rat, dog, cat, horse, or cow. In a preferred embodiment, the individual, subject, or patient is a human. An “individual” may be an adult, juvenile or infant. An “individual” may be male or female. A "subject in need" of treatment for a particular condition can be an individual having that condition, diagnosed as having that condition, or at risk of developing that condition. A subject can be one who has been previously diagnosed with or identified as suffering from or having a condition in need of treatment or one or more complications related to such a condition, and optionally, have already undergone treatment for a condition as defined herein or the one or more complications related to said condition. Alternatively, a subject can also be one who has not been previously diagnosed as having a condition as defined herein or one or more complications related to said condition. For example, a subject can be one who exhibits one or more risk factors for a condition, or one or more complications related to said condition or a subject who does not exhibit risk factors. As used herein, the term “healthy individual” refers to an individual or group of individuals who are in a healthy state, e.g. individuals who have not shown any symptoms of the disease, have not been diagnosed with the disease and/or are not likely to develop the disease (i.e. PH, particularly PAH). Preferably said healthy individual(s) is not on medication affecting PH (e.g. PAH) and has not been diagnosed with any other disease. The one or more healthy individuals may have a similar sex, age, and/or body mass index (BMI) as compared with the test individual. Application of standard statistical methods used in medicine permits determination of normal levels of expression in healthy individuals, and significant deviations from such normal levels. As used herein, the term “disease progression” means a change in the way a disease or condition affects a subject over time. For chronic and/or incurable diseases, “progression” typically describes the worsening of a disease or symptoms of said disease over time. Thus, in the context of

PH (e.g. PAH), progression may be defined as a worsening of PH (e.g. PAH) or the symptoms thereof. Progression may be defined by any established clinical measure, such as those described herein. As used herein, the terms “risk” and “high risk” of PH (e.g. PAH) progression are used interchangeably to mean to that a subject is statistically likely to exhibit PH (e.g. PAH) progression within a set time period. By way of non‐limiting example, a high‐risk of progression may based on five‐ or eight‐ year outcomes (e.g. measured by all‐cause mortality or lung‐transplantation). As used herein, the terms “low risk” and “no risk” of PH (e.g. PAH) progression are used interchangeably to mean to that a subject is statistically unlikely to exhibit PH (e.g. PAH) progression within a set time period. By way of non‐limiting example, a low‐risk of progression may based on five‐ or eight‐ year outcomes (e.g. measured by all‐cause mortality or lung‐transplantation). Classification of a subject by a diagnostic/prognostic method of the invention does not require perfect classification. Classification may be characterised by its "sensitivity." Diagnosis/prognosis may be characterized by its "sensitivity". "Sensitivity" of diagnosis relates to the percentage of individuals with PH (e.g. PAH) who were correctly identified as having PH (e.g. PAH). "Sensitivity" of prognosis relates to the percentage of individuals with PH (e.g. PAH) whose risk category was correctly identified as high‐risk for progression. "Sensitivity" is defined in the art as the number of true positives divided by the sum of true positives and false negatives. The "specificity" of a diagnosis is defined as the percentage of patients who were correctly identified as not having PH (e.g. PAH), compared with a healthy control(s). "Sensitivity" of prognosis relates to the percentage of individuals with PH (e.g. PAH) whose risk category was correctly identified not having high‐risk for progression. That is, "specificity" relates to the number of true negatives divided by the sum of true negatives and false positives. “Accuracy” is defined as the rate or frequency by which subjects can be allocated to the correct group, and is defined mathematically as: Accuracy = (true negatives + true positives)/( true negatives + true positives + false positives + false negatives). Herein the terms “control” and “reference population” are used interchangeably. The term “pharmaceutically acceptable” as used herein means approved by a regulatory agency of the Federal or a state government, or listed in the U.S. Pharmacopeia, European Pharmacopeia or other generally recognized pharmacopeia The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that such publications constitute prior art to the claims appended hereto. Disclosure related to the various methods of the invention are intended to be applied equally to other methods, therapeutic uses or methods, the data storage medium or device, the computer program product, and vice versa. Pulmonary Hypertension The present invention relates to biomarkers for the diagnosis and/or prognosis of pulmonary hypertension (PH), as well as methods for optimising therapy for PH, as described herein. Typically the invention relates to biomarkers for the diagnosis and/or prognosis of pulmonary arterial hypertension (PAH), as well as methods for optimising therapy for PAH, as described herein. PH is a fatal disease characterized by lung blood vessel obstruction due to excessive proliferation of vascular cells and inflammation. As used herein, PH may be defined as an increase in mean pulmonary arterial pressure (mPAP) of ≥ 25 mmHg. mPAP is typically determined clinically by right heart catheterization. PAH is a subset of PH, which may be further defined by a pulmonary artery wedge pressure (PAWP, referred to interchangeably as pulmonary capillary wedge pressure or PCWP) ≤ 15 mmHg and a pulmonary vascular resistance (PVR) >3 Wood units (WU) in the absence of other causes of pre‐capillary PH such as PH due to lung diseases, chronic thromboembolic pulmonary hypertension or other rare diseases. Shared aetiology between PH and PAH means that methods and biomarkers useful for diagnosis/prognosis/therapy optimisation/treatment of PH have potential in the context of PAH, and vice versa. The biomarkers and methods of the invention may be used independently, or may be used in combination with any other appropriate clinical diagnostic/prognostic tool, biomarker or classification measure. Established examples of such clinical measures include measures of right ventricular (RV) function, such as mPAP, cardiac index (CI), contractile reserve (PAP during exercise), right atrial (RA) pressure, mixed venous oxygen saturation (SvO₂); measures of exercise capacity, such as the six‐minute walking distance (6MWD) test and cardiopulmonary exercise testing (CPET) to measure end‐tidal partial pressure of carbon dioxide (pCO₂), ventilator equivalents for CO₂ (VE/VCO₂), oxygen pulse (VO₂/HR) and peak oxygen uptake (peak VO₂); and biomarkers such as NT‐ proBNP and brain natriuretic peptide (BNP). Biomarkers for Pulmonary Hypertension The inventors have used plasma proteomics to identify biomarkers for PH, particularly for PAH. In particular the inventors have identified six proteins which may be used as biomarkers for PH, particularly for PAH: NRP1, PRDX4, PXDN, SVEP1, TSP2 and renin (referred to interchangeably herein as " the six biomarkers " andthe“six protein ”).

Each of the six biomarkers may be used alone, in combination with any of the other biomarkers, and/or in combination with one or more additional biomarker for PH, particularly PAH, and/or in combination with any other appropriate clinical diagnostic/prognostic tool, biomarker or classification measure, as disclosed herein. The invention provides the use of any one of NRP1, PXDN, SVEP1 and TSP2 for the diagnosis and/or prognosis of PH (particularly PAH), as well as methods for optimising therapy for PH (particularly PAH), methods of treatment and methods of monitoring as described herein. Typically, the invention relates to the use of two of more of NRP1, PRDX4, PXDN, SVEP1, TSP2 and renin for the diagnosis and/or prognosis of PH (particularly PAH), as well as methods for optimising therapy for PH (particularly PAH), methods of treatment and methods of monitoring as described herein. Thus, the invention relates to the use of any two, any three, any four, any five or all six of NRP1, PRDX4, PXDN, SVEP1, TSP2 and renin for the diagnosis and/or prognosis of PH (particularly PAH), as well as methods for optimising therapy for PH (particularly PAH), methods of treatment and methods of monitoring as described herein. Preferably the invention relates to the use of three or more (i.e. any three, four, five or all six), four of more (i.e. any four, five or all six), or five or more (i.e. any five or all six) of NRP1, PRDX4, PXDN, SVEP1, TSP2 and renin for the diagnosis and/or prognosis of PH (particularly PAH), as well as methods for optimising therapy for PH (particularly PAH), methods of treatment and methods of monitoring as described herein. In some particularly preferred embodiments all six of NRP1, PRDX4, PXDN, SVEP1, TSP2 and renin for the diagnosis and/or prognosis of PH (particularly PAH), as well as methods for optimising therapy for PH (particularly PAH), methods of treatment and methods of monitoring as described herein. Accordingly, the invention may relate to the use of any two of the six biomarkers: NRP1 and PRDX4; NRP1 and PXDN; NRP1 and SVEP1; NRP1 and TSP2; NRP1 and renin; PRDX4 and PXDN; PRDX4 and SVEP1; PRDX4 and TSP2; PRDX4 and renin; PXDN and SVEP1; PXDN and TSP2; PXDN and renin; SVEP1 and TSP2; SVEP1 and renin; or TSP2 and renin. Preferably, the invention may relate to the use of TSP2 and renin. The invention may relate to the use of any three of the six biomarkers: renin, TSP2 and SVEP1; renin, TSP2 and PXDN; renin, TSP2 and PRDX4; renin, TSP2 and NRP1; renin, SVEP1 and PXDN; renin, SVEP1 and PRDX4; renin, SVEP1 and NRP1; renin, PXDN and PRDX4; renin, PXDN and NRP1; renin, PRDX4 and NRP1; TSP2, SVEP1 and PXDN; TSP2, SVEP1 and PRDX4; TSP2, SVEP1 and NRP1; TSP2, PXDN and PRDX4; TSP2, PXDN and NRP1; TSP2, PRDX4 and NRP1; SVEP1, PXDN and PRDX4; SVEP1, PXDN and NRP1; SVEP1, PRDX4 and NRP1; or PXDN, PRDX4 and NRP1. Preferably, the invention may relate to the use of NRP1, TSP2 and renin.

The invention may relate to the use of any four of the six biomarkers: NRP1, PRDX4, PXDN and SVEP1; NRP1, PRDX4, PXDN and TSP2; NRP1, PRDX4, PXDN and renin; NRP1, PRDX4, SVEP1 and TSP2; NRP1, PRDX4, SVEP1 and renin; NRP1, PRDX4, TSP2 and renin; NRP1, PXDN, SVEP1 and TSP2; NRP1, PXDN, SVEP1 and renin; NRP1, PXDN, TSP2 and renin; NRP1, SVEP1, TSP2 and renin; PRDX4, PXDN, SVEP1 and TSP2; PRDX4, PXDN, SVEP1 and renin; PRDX4, PXDN, TSP2 and renin; PRDX4, SVEP1, TSP2 and renin; or PXDN, SVEP1, TSP2 and renin. Preferably, the invention may relate to the use of NRP1, PRDX4, TSP2 and renin. The invention may relate to the use of any five of the six biomarkers: NRP1, PRDX4, PXDN, SVEP1 and TSP2; NRP1, PRDX4, PXDN, SVEP1 and renin; NRP1, PRDX4, PXDN, TSP2 and renin; NRP1, PRDX4, SVEP1, TSP2 and renin; NRP1, PXDN, SVEP1, TSP2 and renin; or PRDX4, PXDN, SVEP1, TSP2 and renin. Preferably, the invention may relate to the use of NRP1, PRDX4, PXDN, TSP2 and renin. The invention may relate to the use of all six biomarkers: NRP1, PRDX4, PXDN, SVEP1, TSP2 and renin. One of skill in the art would understand that biomarker combinations of the invention may be defined in terms of the biomarkers included (as above), or in terms of biomarkers omitted. By way of non‐limiting example, the combination NRP1, PRDX4, PXDN, TSP2 and renin may be described positively as such, or alternatively as a five combination/panel, lacking SVEP1, and the skilled person would understand these two definitions to describe the same marker combination. By way of further non‐limiting examples: the combination NRP1, PRDX4, TSP2 and renin may alternatively be described as a four combination/panel, lacking SVEP1 and PXDN; and the combination NRP1, TSP2 and renin may alternatively be described as a three combination/panel, lacking SVEP1, PRDX4 and PXDN. Each biomarker may be independently selected from the protein of NRP1, PRDX4, PXDN, SVEP1, TSP2 and renin, or a fragment or variant thereof (as defined herein), or a nucleic acid encoding for said protein. Accordingly, the invention also envisages the use of nucleic acids (e.g. RNA or DNA) encoding NRP1, PRDX4, PXDN, SVEP1, TSP2 and/or renin, particularly encoding the exemplary amino acid sequences described herein or encoding fragments thereof, as biomarkers according to the invention. Typically each of the biomarker is a protein, or a fragment or variant thereof (as described herein). The invention also relates to methods of quantification of a biomarker of the invention, particularly to combinations of the biomarkers of the invention. Any standard technique or assay for biomarker quantification known in the art may be used for quantification according to the invention.

Non‐limiting examples of methods, assays and techniques for quantification of biomarkers of the invention are described herein. Any reference herein to a biomarker of the invention applies equally and without reservation to any and all combinations of the six biomarkers of the invention, including all six biomarkers, unless expressly stated otherwise. Diagnostic and Prognostic Methods and Uses The present invention provides a method for diagnosing or determining a prognosis for pulmonary hypertension (PH), the method comprising: (a) quantifying the amount of two or more biomarkers present in a sample obtained from a subject, wherein the two or more biomarkers are selected from SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4; (b) comparing the amount of the two or more biomarkers with the amount of the same two or more biomarkers in a reference standard; and thereby diagnosing or determining a prognosis for PH. Any combination of the six biomarkers as described herein may be used according to the present invention. The diagnostic and prognostic methods of the present invention are in vitro methods. Thus, the invention can be carried out in vitro on an isolated sample that has previously been obtained from a subject. As used herein, the terms “diagnosis”, “diagnosing” and “diagnose(d)” refer to the process or act of recognising, deciding on or concluding on a disease or condition in a subject on the basis of symptoms and signs and/or from results of various diagnostic procedures (such as for example, from knowing the presence, absence or quantity of biomarkers or other clinical measures characteristic of the diagnosed disease or condition). Thus, “diagnosing PH (e.g. PAH)” may interchangeably be referred to as “diagnosing whether a subject has or is at risk of having PH (e.g. PAH)”, meaning determining whether the subject has or is at risk of having PH (e.g. PAH). “Diagnosing PH (e.g. PAH)” or “diagnosing whether a subject has or is at risk of having PH (e.g. PAH)” may mean confirming the presence (or absence) of PH (e.g. PAH) in a subject suspected of having or being at risk of PH (e.g. PAH). As used herein, the terms “prognosis”, “prognosing” and “prognose(d)” refer to the process or act of recognising, deciding on or concluding on a the likely course or progression of disease or condition, or predicting the outcome of said disease or condition in a subject on the basis of symptoms and signs and/or from results of various prognostic procedures (such as for example, from knowing the presence, absence or quantity of biomarkers or other clinical measures characteristic of the diagnosed disease or condition).

Thus, “prognosing PH (e.g. PAH)” may interchangeably be referred to as “determining a prognosis for PH (e.g. PAH)”, meaning determining the likely course or progression of PH (e.g. PAH) in a subject with PH (e.g. PAH). “Prognosing PH (e.g. PAH)” or “determining a prognosis for PH (e.g. PAH)” may mean determining whether a subject with PH (e.g. PAH) is at low‐risk or high‐risk of the PH (e.g. PAH) progressing. As defined herein, progression of PH (e.g. PAH) may be defined as a worsening of PH (e.g. PAH) or the symptoms thereof. Progression may be defined by any established clinical measure, such as those described herein. By way of non‐limiting example, progression of PH (e.g. PAH) may be defined by and/or associated with a decrease in RV function (e.g. an increase in mPAP, decrease in CI, decrease in PAWP); a decrease in exercise capacity (e.g. an decrease in 6MWD); and/or an increase in NT‐proBNP and/or BNP. Conventionally, a subject is deemed of low risk of PH (e.g. PAH) progression if targets for two or more clinical measures (e.g. selected from the established WHO functional class (as explained at https://www.phaeurope.org/about‐ph/classification‐and‐who‐functional‐class/, amongst other sources), 6MWD, CI and NT‐proBNP and/or BNP) are met. The five‐year survival of low‐risk subjects is typically ≥ about 70%, preferably ≥ about 75%, more preferably ≥ about 80%, even more preferably ≥ about 90%. Accordingly, low‐risk of PH (e.g. PAH) progression may be defined as the likelihood of five‐year survival of ≥ about 70%, preferably ≥ about 75%, more preferably ≥ about 80%, even more preferably ≥ about 90%. The five‐year survival of high‐risk subjects is ≤ about 70%, ≤ about 60%, such as ≤ about 55%, ≤ 50%, and it typically about 50%. Accordingly, high‐risk of PH (e.g. PAH) progression may be defined as the likelihood of five‐year survival of ≤ about 70%, ≤ about 60%, such as ≤ about 55%, ≤ 50%, and it typically about 50%. The eight‐year survival of low‐risk subjects is typically ≥ about 70%, preferably ≥ about 75%, more preferably ≥ about 80%. Accordingly, low‐risk of PH (e.g. PAH) progression may be defined as the likelihood of eight‐year survival of ≥ about 70%, preferably ≥ about 75%, more preferably ≥ about 80%. The eight‐year survival of high‐risk subjects is ≤ about 60%, such as ≤ about 55%, ≤ 50%, and it typically about 50%. Accordingly, high‐risk of PH (e.g. PAH) progression may be defined as the likelihood of eight‐year survival of ≤ about 60%, such as ≤ about 55%, ≤ 50%, and it typically about 50%. The methods of the invention may be useful in identifying subjects who have not previously been diagnosed with PH (e.g. PAH), or a symptom thereof or disease associated therewith. Subjects may have one or more symptom of PH/PAH, or may be asymptomatic for PH/PAH (or symptom thereof or disease associated therewith). Subjects may have been identified as being at risk of developing PH (e.g. PAH), for example due to a subject exhibiting one or more risk factor for

PH/PAH. The subject may therefore be one who is suffering from or is at risk of developing PH/PAH (or symptom thereof or disease associated therewith). By way of non‐limiting example, a subject may have been identified as at risk of PH (e.g. PAH) because they are a relative of an individual who has previously been diagnosed with PH (e.g. PAH). Thus, the methods of the present invention are particularly useful in diagnosing or determining a prognosis for a subject who is a relative of an individual who has previously been diagnosed with PH (e.g. PAH). The methods of the invention comprise a step of “quantifying biomarkers” in a sample obtained from a subject. As used herein, the phrase “quantifying biomarkers” means determining the amount of the markers that are present in a sample obtained from a test subject. When determining the amount of the biomarkers that are present in the sample this means quantifying each biomarker by determining, for example, the relative or absolute amount of the biomarker. It will be appreciated that the assay methods do not necessarily require measurement of absolute values of biomarker, unless it is desired, because relative values are sufficient for many applications of the invention. Accordingly, the "amount" can be the (absolute) total amount of the biomarker (e.g. mass, molar amount, concentration or molarity) that is detected in a sample, or it can be a "relative" amount, e.g., the difference between the biomarker detected in a sample and e.g. another constituent of the sample. The amount of the biomarker may be expressed by its concentration in a sample, or by the concentration of a reagent that detects the marker. The amount of a biomarker of the invention may be determined by quantitative and/or qualitative analysis. The amount of the biomarker may be given in any appropriate units. For example, the concentration of the one or more biomarker may be given in pg/ml, ng/ml or μg/ml. Measurement of the biomarkers of the invention can be performed by any method that provides satisfactory analytical specificity, sensitivity and precision. The invention thus encompasses the use of those methods known to a person skilled in the art to measure the amount of biomarker(s) for each of the purposes of diagnosing, determining a prognosis, treating, optimising therapy and/or monitoring PH (e.g. PAH) according to the invention. A biomarker of the invention may be detected at the nucleic acid or protein level. Thus, a biomarker of the invention may be DNA, RNA or protein and may be quantified using any appropriate technique. Typically biomarkers of the invention are detected at the protein level. The amount of a biomarker of the invention may be measured directly or indirectly. The relative amount of a biomarker of the invention may be determined using any appropriate technique. Suitable standard techniques are known in the art, for example aptamer‐based assays or antibody‐based assays such as Western blotting and enzyme‐linked immunosorbent assays (ELISAs). Other non‐ limiting examples of standard techniques that may be used include microarray analysis, quantitative

real‐time PCR (qPCR), high Performance Liquid Chromatography (HPLC) and mass spectrometry (e.g. matrix‐assisted laser desorption/ionization mass spectrometry (MALDI MS), surface‐enhanced laser desorption/ionization mass spectrometry (SELDI MS), time of flight mass spectrometry (TOF MS) and liquid chromatography mass spectrometry (LC MS)). Preferred methods include aptamer‐based assays (as used in the Examples) and antibody‐based assays. Particularly preferred are aptamer‐ based assays, non‐limiting examples of which use slow off‐rate modified aptamers (SOMAers). Quantification means, preferably aptamer‐based assays, may be in multiplex form. Multiplexed assays advantageously allow for quantification of biomarker combinations at minimal additional cost and uses instrumentation that is now widely available with increasing extent of automation and availability for non‐specialist use. Different biomarkers may be quantified using different detection methods according to the present invention. For example one or more biomarker of the invention may be quantified using an aptamer‐based assay (e.g. using one or more SOMAer, such as a SomaScan‐V4), and a different one or more biomarker of the invention may be quantified using an antibody‐based assay (e.g. an ELISA). By way of non‐limiting example, any one, two, three, four or five of NRP1, PXDN, renin, SVEP1 and TSP2 may be detected using an aptamer‐based assay (e.g. using one or more SOMAer for each biomarker), and PRDX4 may be quantified using an antibody‐based assay (e.g. an ELISA). When the amounts of two or more biomarker are determined, the methods of the present invention typically determine the amount of each biomarker. Alternatively, the methods of the invention may determine the cumulative amount of all the markers. Alternatively, the amount of the biomarkers can be combined with each other in a formula to form an index value. Agents for the quantification of a biomarker by the invention typically bind to said biomarker. Such agents may bind specifically to the biomarker. The agent for the quantification of a biomarker may be an aptamer (particularly a SOMAer), antibody or other binding agent specific for the biomarker. By specific, it will be understood that the agent binds to the molecule of interest, in this case the biomarker, with no significant cross‐reactivity to any other molecule, particularly any other protein. For example, an agent (e.g. aptamer) that is specific for NRP1 will show no significant cross‐reactivity with human neutrophil elastase. Cross‐reactivity may be assessed by any suitable method. Cross‐reactivity of an agent for a biomarker with a molecule other than the biomarker may be considered significant if the agent binds to the other molecule at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90% or 100% as strongly as it binds to the biomarker. An agent that is specific for the biomarker may bind to another molecule such as human neutrophil elastase at less than 90%, 85%, 80%, 75%, 70%, 65%, 60%, 55%, 50%, 45%, 40%, 35%, 30%, 25% or 20% the strength that it binds to the one or more biomarker. Preferably, the

agent binds to the other molecule at less than 20%, less than 15%, less than 10% or less than 5%, less than 2% or less than 1% the strength that it binds to the biomarker. The methods of the invention comprise a step of “comparing the amount” of the biomarkers with the amount of the same biomarkers in a reference standard. The “reference standard” refers to a value obtained from a population of individual(s) whose disease status is known. A reference standard can be determined for any particular population, subpopulation, or group of individuals according to standard methods well known to those of skill in the art. The reference standard can be generated from one individual or a population of two or more individuals. The control or reference population, for example, may comprise three, four, five, ten, 15, 20, 30, 40, 50 or more individuals, preferably at least ten individuals. The reference standard may be the amount of a biomarker in a sample or samples derived from one individual. Alternatively, the reference standard may be derived by pooling data obtained from multiple individuals, and calculating an average (for example, mean or median) amount for a biomarker. Thus, the reference standard may reflect the average amount of a biomarker in multiple individuals. Said amounts may be expressed in absolute or relative terms, in the manner as described above in relation to the sample that is to be tested using the method of the invention. The reference standard is typically obtained from a reference sample, i.e. a sample of the same sample type (e.g. biofluid, tissue or cells) as the sample(s) obtained from the subject, wherein the reference sample is obtained from a reference population. By way of non‐limiting example, if the sample obtained from a subject is a blood sample (e.g. a whole blood, plasma or serum sample), the reference standard is also obtained from a blood sample (e.g. a whole blood, plasma or serum sample, as appropriate). The amount of a biomarker of the invention may be assessed and compared with the corresponding value for the same biomarker from the reference standard. Alternatively, the amount of a biomarker of the invention may be compared with that of the reference standard without quantifying the mass, molar amount, concentration or molarity of the one or more biomarker. When comparing between the sample and the reference standard, the way in which the amounts are expressed is matched between the sample and the reference standard. Thus, an absolute amount is compared with an absolute amount, and a relative amount is compared with a relative amount. When the amounts of two or more biomarkers are determined, the method may comprise comparing the amount of each biomarker to its corresponding reference standard. When the cumulative amount of all the biomarkers is determined, the method may comprise comparing the cumulative amount to a corresponding reference standard.

The reference standard may be obtained either within (i.e. constituting a step of) or separately to (i.e. not constituting a step of) the methods of the invention. The methods of the invention may comprise a step of establishing a reference standard for the quantity of the biomarkers. Alternatively, the reference standard may be obtained separately to the method of the invention and accessed during the comparison step of the invention. The reference standard and the subject’s (test) sample that are compared in the methods of the present invention may be generated from the same individual, provided that the sample and reference standard are generated from biological samples taken at different time points and compared to one another. For example, a sample may be obtained from a subject at the start of a study period and serve as a reference standard. This reference standard may then be compared to the amount of the biomarkers of the invention generated from subsequent samples from the same subject. Such a comparison may be used, for example, to determine the progression of PH (e.g. PAH) in the subject by repeating the method over time, to monitor a subject for PH (e.g. PAH) or progression thereof, or for optimising therapy, as described herein. The reference standard may be obtained, for example, from a population of non‐PH (e.g. non‐PAH) individual(s), i.e. individual(s) without PH (e.g. without PAH). Typically the reference standard may be obtained from a population of healthy individual(s), as defined herein. Healthy and non‐PH (e.g. non‐PAH) reference standards may be interchangeably referred to herein as “non‐PH (non‐PAH) reference standards”. Alternatively, the reference standard may be obtained, for example, from a population of PH (e.g. PAH) individual(s), i.e. individual(s) with PH (e.g. with PAH). Such reference standards may be interchangeably referred to herein as “PH (PAH) reference standards”. These PH (e.g. PAH) individual(s) may be different to the subject, or may be the subject at a different time point (as described above). If the PH (e.g. PAH) individual(s) are different to the subject, such individual(s) preferably have similar sex, age, and body mass index (BMI) as compared with the test subject. Multiple separate reference standards may be used in the methods of the invention for each marker. For example, reference standards obtained from a population of individual(s) with PH (e.g. PAH) and reference standards obtained from a population of healthy individuals may be used according to the present invention. By comparing the amount of biomarkers quantified in a sample obtained from a subject to the amount of markers quantified for a reference standard (such as that obtained from a population of healthy individuals, or from a population of individuals known to have PH (e.g. PAH)), it is possible to diagnose whether a subject has PH (e.g. PAH).

The methods of the invention permit classification of the subject as belonging to or not belonging to the reference population (i.e. by determining whether the amounts of biomarker quantified in the subject are statistically similar to the reference standard or statistically deviate from the reference standard). Hence, classification of the subject’s biomarker profile (i.e. the overall pattern of change observed for the biomarkers quantified) as corresponding to a particular reference standard is predictive that the individual falls (or does not fall) within the reference population from which the reference standard was derived. A subject may be diagnosed as having or being at risk of PH (e.g. PAH) when the amount of biomarker(s) quantified is statistically similar to the amount determined for the corresponding values obtained in a PH (e.g. PAH) reference standard. Alternatively, a subject may be diagnosed as not having or not being at risk of having PH (e.g. PAH) when the amount of biomarker(s) quantified is statistically similar to the amount determined for the corresponding values obtained in a non‐PH (e.g. non‐PAH) reference standard. A subject may be diagnosed as having or being at risk of PH (e.g. PAH) when the amount of biomarker(s) quantified statistically deviates from the amount determined for the corresponding values obtained in a non‐PH (e.g. non‐PAH) reference standard. Alternatively, a subject may be diagnosed as not having or not being at risk of having PH (e.g. PAH) when the amount of biomarker(s) quantified statistically deviates from the amount determined for the corresponding values obtained in a PH (e.g. PAH) reference standard. By comparing the amount of biomarkers quantified in a sample obtained from a subject to the amount of markers quantified for a reference standard (such as that obtained from a population of healthy individuals, or from a population of individuals known to have PH (e.g. PAH)), it is possible to determine a prognosis for a PH (e.g. PAH) in a subject, such as a subject with PH (e.g. PAH). The methods of the invention permit classification of the subject as being at risk of PH (e.g. PAH) progression by determining whether the amounts of biomarker quantified in the subject are statistically similar to the reference standard or statistically deviate from the reference standard. A prognosis of a subject being at risk of PH progression (e.g. PAH progression) may be determined when the amount of biomarker(s) quantified is statistically similar to the amount determined for the corresponding values obtained in a PH (e.g. PAH) reference standard. Alternatively, a prognosis of a subject not being at risk of PH progression (e.g. PAH progression) may be determined when the amount of biomarker(s) quantified is statistically similar to the amount determined for the corresponding values obtained in a non‐PH (e.g. non‐PAH) reference standard. A prognosis of a subject being at risk of PH progression (e.g. PAH progression) may be determined when the amount of biomarker(s) quantified statistically deviates from the amount

determined for the corresponding values obtained in a non‐PH (e.g. non‐PAH) reference standard. Alternatively, a prognosis of a subject not being at risk of PH progression (e.g. PAH progression) may be determined when the amount of biomarker(s) quantified statistically deviates from the amount determined for the corresponding values obtained in a PH (e.g. PAH) reference standard. The methods of the invention allow for stratification of risk of PH (e.g. PAH) progression. In particular, the methods of the invention may provide improved granularity of risk of progression compared with established clinical measures (as described herein). Accordingly, a prognosis of a subject being at risk of PH progression (e.g. PAH progression) may be determined when the amount of biomarker(s) quantified is statistically similar to the amount determined for the corresponding values obtained in a PH (e.g. PAH) reference standard, even if the subject is deemed of low risk of PH (e.g. PAH) progression using established clinical measures (as described herein). Alternatively, a prognosis of a subject not being at risk of PH progression (e.g. PAH progression) may be determined when the amount of biomarker(s) quantified is statistically similar to the amount determined for the corresponding values obtained in a non‐PH (e.g. non‐PAH) reference standard, even if the subject is deemed of high risk of PH (e.g. PAH) progression using established clinical measures (as described herein). A prognosis of a subject being at risk of PH progression (e.g. PAH progression) may be determined when the amount of biomarker(s) quantified statistically deviates from the amount determined for the corresponding values obtained in a non‐PH (e.g. non‐PAH) reference standard, even if the subject is deemed of low risk of PH (e.g. PAH) progression using established clinical measures (as described herein). Alternatively, a prognosis of a subject not being at risk of PH progression (e.g. PAH progression) may be determined when the amount of biomarker(s) quantified statistically deviates from the amount determined for the corresponding values obtained in a PH (e.g. PAH) reference standard, even if the subject is deemed of high risk of PH (e.g. PAH) progression using established clinical measures (as described herein). As used herein, the term “statistically similar” means that the amounts of biomarker quantified for the subject are similar to those quantified for the reference standard to a statistically significant level. The term “statistically significant” means that the alteration is greater than what might be expected to happen by chance alone (p = < 0.05). Statistical significance can be determined by any method known in the art. As used herein, the term “statistically deviates” means that the amounts of biomarker quantified for the subject differs from those quantified for the reference standard to a statistically significant level. The term “statistically significant” means that the alteration is greater than what might be expected to happen by chance alone (p = < 0.05). Statistical significance can be determined

by any method known in the art. The deviation in marker abundance may be an increase or decrease. The increase or decrease may be statistically significant. Typically, comparing the amount of the biomarker relative to the reference standard and determining an increase indicates that the subject has or is at risk of having PH (e.g. PAH) or PH (e.g. PAH) progression. The increase can be, for example, at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, or at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 100%, at least 110%, at least 120%, at least 130%, at least 140% or at least 150% of the reference value. The increase in the amount of the markers may be statistically significant. Typically, comparing the amount of the biomarker relative to the reference standard and determining a decrease indicates that the subject does not have or is not at risk of having PH (e.g. PAH) or PH (e.g. PAH) progression. The decrease can be, for example, at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, or at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95%, or at least 99% of the reference value. The decrease in the amount of the markers may be statistically significant. Thus, a subject may be diagnosed with PH (e.g. PAH) or at risk of PH (e.g. PAH) progression when there is an increase in any biomarker or biomarker combination of the invention relative to the corresponding reference standard obtained from a population of healthy individuals. Likewise, a subject may be diagnosed as not having PH (e.g. PAH) or not at risk of PH (e.g. PAH) progression when there is a decrease in any biomarker or biomarker combination of the invention relative to the corresponding reference standard obtained from a population of healthy individuals. The sensitivity of the methods of the invention (as defined herein) may be at least about 90%, at least about 89%, at least about 88%, at least about 87%, at least about 86%, at least about 85%, at least about 80%, at least about 75%, at least about 70%, or at least about 65%. The specificity of the methods of the invention (as defined herein) may be at least about 90%, at least about 89%, at least about 88%, at least about 87%, at least about 86%, at least about 85%, at least about 80%, at least about 75%, at least about 70%, or at least about 65%. The method of the invention for diagnosing or determining a prognosis for PH (e.g. PAH) can be used in combination with other methods to diagnose/prognose PH (e.g. PAH). Established clinical measures for diagnosing/prognosing PH (e.g. PAH) are known in the art, and non‐limiting examples are described herein.

The step of comparing the amount of any biomarker of the invention with the amount of the same biomarker in a reference standard may comprise calculating a score (referred to interchangeably as a “protein score”) for the biomarker. A protein score may be calculated by taking the amount (quantification value) for a biomarker and scaling it against the amount (quantification value) for the same biomarker in the reference standard to produce a scaled score (referred to interchangeably as a “z‐score”). Scaling/z‐ score calculation is routine in the art. Briefly, the formula for calculating a z‐score is z= (x‐μ)/σ, where μ is the population mean and σ is the population standard deviation. Scaling may be based on the amount (quantification value) of a biomarker in a non‐PH (e.g. non‐PAH) reference standard, such that the non‐PH (e.g. non‐PAH) reference standard will have an average amount (z‐score) of zero (0) with a standard deviation of one (1), and the scaled amount (z‐ score) of the corresponding biomarker in a subject with PH (e.g. PAH) is greater than zero. The z‐score for a biomarker may then be multiplied by a weighting coefficient to produce a weighted score (weighted z‐score) for an individual biomarker. Preferred weighting coefficients determined by the inventors in the Examples are set out below in Table 1. Table 1: Proteins selected by cross‐validation analysis. LASSO analysis selected six proteins to create a single model score predicting prognosis in the combined discovery and validation subjects. Representative weighting coefficients for profiles of five, four, three and two biomarkers are also given.

The weighting coefficient will typically be dependent on the reference population/reference standard used, and the assay used for quantification. Calculation of a weighting coefficient is routine in the art and a skilled person would if required readily be able to calculate weighting coefficients for each biomarker of the invention. One non‐limiting example of a quantification assay and associated weighting coefficients is described in the Examples, with the resulting weighting coefficients given in Table 1 (above). Table 1 also gives representative weighting coefficients that may alternatively be used with profiles of five, four, three and two biomarkers (although the respective weighting coefficients determined using the six‐biomarker profile in the Examples are preferred). Using a different quantification assay, it would be routine for one of skill in the art to determine a distribution for scaling based on that assay, and hence to calculate z‐scores from the quantified amount. A weighted z‐score for a biomarker could then be calculated using any appropriate weighting coefficient, such as the weighting coefficients described herein (e.g. in Table 1). Separate scores (scaled and optionally weighted) may be calculated for each biomarker, or a combined score for two or more biomarkers may be calculated to give a single score for all biomarkers quantified. Such a (weighted) combination score may be referred to interchangeably herein as a “single score”, “single protein score”, “model score”, “model protein score”, “composite score”, “composite protein score” or “model single protein score”. To calculate a single protein score, z‐scores for each biomarker of interest are calculated and weighted as described above. The weighted z‐scores for each biomarker are then added together to give the single protein score. As for the separate z‐scores for individual biomarkers, a non‐PH (e.g. non‐PAH) reference standard will have an average single protein score of zero (0) with a standard deviation of one (1), and the scaled amount (z‐score) of the single protein score for the corresponding biomarkers in a subject with PH (e.g. PAH) is greater than zero. The step of comparing the amount of a biomarker (particularly two or more biomarkers) of the invention with the amount of the same biomarker (particularly two or more biomarkers) in a reference standard in a method of the invention may therefore comprise calculating a single protein score that is a weighted combination score of the biomarker (particularly two or more biomarkers). The step of comparing the amount of a two or more biomarkers of the invention with the amount of the same two or more biomarkers in a reference standard in a method of the invention

may therefore comprise calculating a single protein score, wherein calculating the single protein score comprises calculating z‐scores for the two or more biomarkers relative to the two or more biomarkers in the reference standard, weighting the z‐scores and adding the z‐scores for the two or more biomarkers to arrive at the single protein score. The present inventors have surprisingly demonstrated that a single protein score using two or more of the biomarkers of the invention is capable of diagnosing PH (e.g. PAH), or determining a prognosis for PH (e.g. PAH). In particular, as shown in the Examples, the inventors have demonstrated that a score threshold of 0.57 (using the weighting coefficients of Table 1 and the full panel of the six biomarkers of the invention) was good at separating high and low risk patients from a majority subset (64/79) who met two or more of four standard clinical measures of low risk/treatment success (6MWD, WHO functional class, CI and BNP/NT‐proBNP thresholds associated with good outcomes). Accordingly, the methods of the invention may be used to diagnose PH (e.g. PAH), or to determine a prognosis of a subject being at high risk of PH (e.g. PAH) progression if the single protein score is greater than or equal to a threshold value. Similarly, the methods of the invention may be used to not diagnose PH (e.g. PAH) (i.e. to exclude PH/PAH as a diagnosis), or to determine a prognosis of a subject being at low risk of PH (e.g. PAH) progression if the single protein score is below the threshold value. In particular, in a method of the invention, a single protein score greater than or equal to a threshold value of greater than or equal to 1 (such as a threshold value of about 1.0, 1.1, 1.2, 1.5, or in the range of about 1.0 to about 1.5, about 1.0 to 1.25 or 1.0 to 1.1) may be used to diagnose PH (e.g. PAH). In a method of the invention, a single protein score below a threshold value of greater than or equal to 1 (such as a threshold value of about 1.0, 1.1, 1.2, 1.5, or in the range of about 1.0 to about 1.5, about 1.0 to 1.25 or 1.0 to 1.1) may be used to not diagnose PH (e.g. PAH) i.e. to exclude PH/PAH as a diagnosis. Preferably, a single protein score of greater than or equal to a threshold value of about 1 is used to diagnose PH (e.g. PAH). Preferably, a single protein score of below a threshold value of about 1 is used to not diagnose PH (e.g. PAH), i.e. to exclude PH/PAH as a diagnosis. A threshold value of about 1 is particularly preferred for diagnosis when the all six biomarkers of the invention are quantified in a method of the invention and used to calculate a single protein score. These threshold values are typically used when a single protein score is calculated using the respective weighting coefficients for the biomarkers determined using the six‐ biomarker profile in the Examples. In particular, in a method of the invention, a single protein score greater than or equal to a threshold value in the range of about 0.4 to about 0.7, preferably about 0.5 to about 0.6, more

preferably about 0.55 to about 0.6 may be used to determine a prognosis for PH (e.g. PAH) of the subject being at high risk of PH (e.g. PAH) progression. In a method of the invention, a single protein score below a threshold value in the range of about 0.4 to about 0.7, preferably about 0.5 to about 0.6, more preferably about 0.55 to about 0.6 may be used to determine a prognosis for PH (e.g. PAH) of the subject being at low risk of PH (e.g. PAH) progression. Preferably, a single protein score of greater than or equal to a threshold value of about 0.57 is used to determine a prognosis for PH (e.g. PAH) of the subject being at high risk of PH (e.g. PAH) progression. Preferably, a single protein score of below a threshold value of about 0.57 is used to determine a prognosis for PH (e.g. PAH) of the subject being at low risk of PH (e.g. PAH) progression. A threshold value of about 0.57 is particularly preferred for determining a prognosis when the all six biomarkers of the invention are quantified in a method of the invention and used to calculate a single protein score. These threshold values are typically used when a single protein score is calculated using the respective weighting coefficients for the biomarkers determined using the six‐biomarker profile in the Examples. Alternatively, in a method of the invention, a single protein score greater than or equal to a threshold value in the range of about 1.2 to 2.0, preferably about 1.3 to about 1.8, more preferably about 1.35 to about 1.75 may be used to determine a prognosis for PH (e.g. PAH) of the subject being at high risk of PH (e.g. PAH) progression. In a method of the invention, a single protein score below a threshold value in the range of about 1.2 to 2.0, preferably about 1.3 to about 1.8, more preferably about 1.35 to about 1.75 may be used to determine a prognosis for PH (e.g. PAH) of the subject being at low risk of PH (e.g. PAH) progression. Preferably, a single protein score of greater than or equal to a threshold value of about 1.35 is used to determine a prognosis for PH (e.g. PAH) of the subject being at high risk of PH (e.g. PAH) progression. Preferably, a single protein score of below a threshold value of about 1.35 is used to determine a prognosis for PH (e.g. PAH) of the subject being at low risk of PH (e.g. PAH) progression. These threshold values are typically used when a single protein score is calculated using the respective weighting coefficients for the biomarkers determined using the TSP2, renin or any of combination of two, three, four or five of the six biomarkers of the invention using the weighting coefficients for TSP2, renin or any of combination of two, three, four or five of the six biomarkers as set out in Table 1. A threshold value for diagnostic and/or prognostic methods of the invention may be set based on a baseline value from a reference standard as described herein, particularly a non‐PH/non‐ PAH reference standard. Alternatively, the threshold value may be relative to a subject’s own baseline score (e.g. as determined over a period of time, such as three months, six months, nine months, 12 months, 18 months or more). Thus, an increase in the single protein score of greater than about 1 from a subject’s own base line may be used to diagnose PA/PAH, where an increase in

in the single protein score of below about 1 from a subject’s own base line may be used to not diagnose PA/PAH, i.e. to exclude PH/PAH as a diagnosis. All the disclosure herein relating to quantification of biomarkers of the invention, reference values, diagnosis, prognosis, etc. applies equally and without reservation to methods in which the comparison step comprises calculating a single protein score. The methods of the present invention may use samples that have undergone minimal or zero processing before testing. The methods may use samples that have been manipulated, in any way, after procurement, such as by treatment with reagents, solubilisation, or enrichment for certain components. The methods of the invention may use samples that have undergone minimal or zero processing before testing. This provides a significant advantage over prior art methods in terms of time, cost and practicality. By way of example, a blood sample obtained from a test subject may be tested directly using the method of the present invention, without further processing. Serum and plasma samples can be readily obtained from blood samples using simple and readily available techniques that are well known in the art, as described above. A sample for use in a method of the invention may be a cell‐free sample. In other words, the sample of the invention may be processed to remove cells. The term “cell‐free samples” are samples that contain substantially no cells. The term “substantially no” when used in the context of cells herein may mean less than 10,000, 5,000, 1,000, 100 or 10 cells/ml. The term “substantially no” when used in the context of cells herein preferably means less than 1,000 cells/ml, more preferably no cells. In some embodiments, the term “substantially no” when used in the context of cells herein may be expressed in absolute amounts. For example, the term “substantially no” when used in the context of cells herein may mean less than 10,000, 5,000, 1,000, 100 or 10 cells. Preferably less than 1,000 cells, more preferably no cells. The sample obtained from a subject may be any suitable biological material, for example blood, plasma, saliva, serum, sputum, urine, cerebral spinal fluid, cells, a cellular extract, a tissue sample, a tissue biopsy, a stool sample and the like. The precise biological sample that is taken from the subject may vary, but the sampling preferably is minimally invasive and is easily performed by conventional techniques. Typically the sample is biofluid, preferably a blood sample (whole blood, serum or plasma). The term blood comprises whole blood, blood serum (henceforth “serum”) and blood plasma (henceforth “plasma”). Serum and plasma are derived from blood and thus may be considered as specific subtypes within the broader genus “blood”. Particularly preferred are plasma samples. Processes for obtaining serum or plasma from blood are known in the art. For example, it is known

in the art that blood can be subjected to centrifugation in order to separate red blood cells, white blood cells, and plasma. Serum is defined as plasma that lacks clotting factors. Serum can be obtained by centrifugation of blood in which the clotting process has been triggered. Optionally, this can be carried out in specialised centrifuge tubes designed for this purpose. Preferably a blood sample is taken without the subject fasting beforehand. A biological sample may be taken from the subject before the subject shows any symptoms of PH (e.g. PAH), e.g. to establish a base line for said subject. A biological sample may be taken from the subject before the subject shows on or after the onset of symptoms of PH (e.g. PAH), e.g. for the purpose of diagnosing PH (e.g. PAH). A biological sample may be taking, during, and/or after treatment for PH (e.g. PAH), for example after a change in treatment. In this way, the methods of the invention can be used to assess a subject’s response to treatment, as described herein. The amount of a biomarker of the invention may be quantified once, or multiple times (e.g. at least twice, at least three times, at least four times, at least five times, at least six times, at least seven times, at least eight times, at least nine times, at least ten times, or more). In other words, the method of the invention may be conducted once or multiple times. When the amount of a biomarker in the subject is determined multiple times, typically a separate sample taken each time the amount of the biomarker is quantified. Typically multiple quantifications are used for monitoring or optimising therapy, as described herein. A sample may be obtained for a subject before treatment initiation, after treatment initiation; or separate samples may be taken before and after treatment initiation. Although the invention does not require a monitoring period for diagnosis/prognosis, it will be understood that repeated samples may be taken from a subject may be taken and assessed according to the invention over time until the individual is no longer at risk. A biomarker may be quantified in a sample obtained from the subject at one time point and may be compared to the amount of the biomarker in one or more sample obtained from the same subject at different points in time. A method of the invention may be used as a standalone method, or in combination with any other diagnostic or prognostic method, tool or measure for PH (e.g. PAH). Established clinical measures for the diagnosis and/or prognosis of PH (e.g. PAH) are known in the art, and non‐limiting examples are described herein. Accordingly, the method of the invention may further comprise: (a) quantifying the amount of one or more additional biomarker for PAH, wherein preferably said one or more additional biomarker for PAH is NT‐proBNP in the sample; (b) measuring the PAP of the subject; (c) measuring the CI of the subject; and/or (d) determining the 6MWD of the subject. As described herein, the methods of the invention advantageously allow for additional stratification of

risk of PH (e.g. PAH) progression. Thus, using the methods of the invention in combination with established clinical diagnostic/prognostic measures for PH (e.g. PAH) may provide improved granularity of risk of progression, allowing subjects to be identified for monitoring and/or treatment who may otherwise not be identified. The method of the invention may further comprise recording the output of at least one step on a data‐storage medium. By way of example, the methods of the present invention can generate data relating to the subject, such data being recordable on a data‐storage medium (for example, a form of computer memory such as a hard disk, compact disc, floppy disk, or solid‐state drive). Such data can comprise (or consist of) data relating to the concentration in a sample (from said subject) of any of the biomarkers (as described herein) and/or data relating to a protein score for each biomarker, or single protein score for two or more biomarkers, as described herein. The invention also provides the use of two or more of SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4 as biomarkers for PH (e.g. PAH). All embodiments described above for the method for diagnosing or determining a prognosis for PH (e.g. PAH) apply equally to the uses of the invention as defined herein. The invention also provides a data‐storage medium, comprising data obtained by a method according to the present invention. The invention also provides a computer program and a computer program product for carrying out any of the methods and uses described herein, wherein said computer program or computer program product comprise program instructions to cause a processor to perform a method according to the invention or part of said method. The invention also provides a computer readable medium having stored thereon said program for carrying out any of the methods/ uses described herein. The invention also provides a signal embodying a computer program for carrying out any of the methods and uses described herein, a method of transmitting such a signal, and a computer product having an operating system which supports a computer program for carrying out any of the methods and uses described herein. Features implemented in hardware may generally be implemented in software, and vice versa. Any reference to software and hardware features herein should be construed accordingly. Methods of Treatment and for Optimising Therapy Any of the aforementioned methods may further include treating or preventing PH (e.g. PAH) in a subject, wherein said subject has or is at risk of having PH (e.g. PAH).

For example, the method may comprise treating or preventing one or more symptoms associated with PH (e.g. PAH). The method of the invention may include, responsive to the amount of the biomarker(s) in a sample obtained from a subject, administering to the individual a therapy for PH (e.g. PAH). Accordingly, the invention provides a method for treating or preventing PH (e.g. PAH), the method comprising: (a) obtaining the results of a method of diagnosis or determining a prognosis according to the invention; (b) administering a PH (e.g. PAH) therapy when PH (e.g. PAH) is diagnosed; and (c) optionally administering a different therapy when PH (e.g. PAH) is not diagnosed. In other words, the invention provides for a diagnostic or prognostic method, followed by selection and use of a PH (e.g. PAH) therapy depending on the outcome of said diagnosis/prognosis. Said method may comprise: (a) obtaining the results of a method of diagnosis or determining a prognosis according to the invention; (b) making a determination to administer a PH (e.g. a PAH) therapy when PH (e.g. PH) is diagnosed; and (c) optionally making a determination to administer a different therapy when PH (e.g. PAH) is not diagnosed. In other words, a method of the invention may be comprise determining an appropriate therapy, but not comprise an therapeutic method. As the biomarkers of the invention allow for determination of a prognosis for PH (e.g. PAH) more rapidly than the established clinical measures, the invention also provides for the optimisation of therapy for a subject undergoing treatment for PH (e.g. PAH). Accordingly, any of the aforementioned methods may further include a step of changing a subject’s therapy if the amount of the biomarker(s) is increased relative to the reference standard; or maintaining the subject’s therapy if the amount of the biomarker(s) is the same or lower relative to the reference standard. The invention therefore provides a method for optimising therapy for a subject undergoing treatment for PAH, the method comprising: (a) quantifying the amount of a biomarker (typically two or more biomarkers) of the invention as described herein present in a sample obtained from a subject, wherein the biomarker(s) are selected from SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4; (b) comparing the amount of the biomarker(s) with the amount of the same biomarker(s) in a reference standard; and (c) (i) changing the therapy if the amount of the biomarker(s) is increased relative to the reference standard; or (ii) maintaining the therapy if the amount of the biomarker(s) is the same or lower relative to the reference standard. The invention also provides a method for optimising therapy for a subject undergoing treatment for PAH, the method comprising: (a) quantifying the amount of two or more biomarkers present in a sample obtained from a subject, wherein the two or more biomarkers are selected from SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4; (b) comparing the amount of the two or more biomarkers with the amount of the same two or more biomarkers in a

reference standard; and (c) (i) making a determination to change the therapy if the amount of the two or more biomarkers is increased relative to the reference standard; or (ii) making a determination to maintain the therapy if the amount of the two or more biomarkers is the same or lower relative to the reference standard. Any disclosure herein relating to methods of optimising therapy comprising changing or maintaining a therapy as appropriate apply equally and without reservation to methods of optimising therapy according to the invention which comprise making a determination to change or maintain a therapy. Methods of optimising therapy may be carried out at regular intervals during ongoing treatment of a subject, to monitor is a subject becomes resistant to a particular therapy. For example, such a method may be conducted at any clinically appropriate interval, for example at least monthly, every two months, every three months, every six months, annually. Methods of optimising therapy may be carried out on an ad hoc basis, for example if a subject reports a new symptom, a worsening of an existing symptom, and/or a deterioration in quality of life. Methods of optimising therapy may be conducted if there is a change (particularly a statistically significant change) in an established clinical measure for PH (e.g. PAH), such as those measures described herein. Methods of optimising therapy may also be carried out following a change in treatment, to assess the efficacy of the new treatment. In such instances, the method may be carried out one week, two weeks, three weeks, one month, two months, three months, four months, five months, six month, nine months, 12 months, 18 months, 2 years or more following the change in treatment. Any and all disclosure herein in relation to the comparing the amount of a biomarker with a reference standard comprising calculating a protein score (typically a single protein score for two or more biomarkers of the invention) applies equally and without reservation to methods of optimising therapy according to the invention. In particular, in a method of optimising therapy according to the invention, a single protein score greater than or equal to a threshold value in the range of about 0.4 to about 0.7, preferably about 0.5 to about 0.6, more preferably about 0.55 to about 0.6 may be used to justify changing a subject’s therapy for PH (e.g. PAH). In a method of the invention, a single protein score below a threshold value in the range of about 0.4 to about 0.7, preferably about 0.5 to about 0.6, more preferably about 0.55 to about 0.6 may be used to justify maintaining a subject’s therapy for PH (e.g. PAH). Preferably, a single protein score of greater than or equal to a threshold value of about 0.57 is used to justify changing a subject’s therapy for PH (e.g. PAH). Preferably, a single protein score of below a threshold value of about 0.57 is used to justify maintaining a subject’s therapy for PH (e.g. PAH). A threshold value of about 0.57 is particularly preferred for optimising a subject’s therapy

when the all six biomarkers of the invention are quantified in a method of the invention and used to calculate a single protein score. These threshold values are typically used when a single protein score is calculated using the respective weighting coefficients for the biomarkers determined using the six‐biomarker profile in the Examples. Alternatively, in a method of the invention, a single protein score greater than or equal to a threshold value in the range of about 1.2 to 2.0, preferably about 1.3 to about 1.8, more preferably about 1.35 to about 1.75 may be used to justify changing a subject’s therapy for PH (e.g. PAH). In a method of the invention, a single protein score below a threshold value in the range of about 1.2 to 2.0, preferably about 1.3 to about 1.8, more preferably about 1.35 to about 1.75 may be used to justify maintaining a subject’s therapy for PH (e.g. PAH). Preferably, a single protein score of greater than or equal to a threshold value of about 1.35 is used to justify changing a subject’s therapy for PH (e.g. PAH). Preferably, a single protein score of below a threshold value of about 1.35 is used to justify maintaining a subject’s therapy for PH (e.g. PAH). These threshold values are typically used when a single protein score is calculated using the respective weighting coefficients for the biomarkers determined using the TSP2, renin or any of combination of two, three, four or five of the six biomarkers of the invention using the weighting coefficients for TSP2, renin or any of combination of two, three, four or five of the six biomarkers as set out in Table 1. The PH therapy (e.g. PAH therapy) to be administered is not particularly limited. A clinician would be able to select an appropriate therapy, and determine an appropriate dose and dosing regime using routine practice. Examples of licensed therapies that may be used according to the invention are known in the art. By way of non‐limiting example, a PH therapy (e.g. PAH therapy) may be selected from a TGFβ superfamily ligand trap, an endothelin receptor antagonist, particularly a selective ET_A receptor antagonist, a phosphodiesterase type 5 (PDE5) inhibitor, a prostanoid analogue or agonist, particularly a prostaglandin I2 (PGI₂) analogue or agonist, a nitric oxide stimulator or activator, a tyrosine kinase inhibitor, or a combination thereof. Preferred examples of PH (particularly PAH) therapy include sotatercept, sildenafil, ambrisentan, iloprost, macitentan,imatinib, epoprostenol, riociguat, selexipag, tadalafil and bosentan, or a combination thereof. As demonstrated in the Examples herein, netrin‐4, TSP2 and endoglin are all causally linked with PH, particularly PAH. In particular, netrin‐4 activity is increased in PAH, and TSP2 and endoglin activity is decreased in PAH. Therefore, a therapy according to the invention may comprise an agent which inhibits netrin‐4 activity; an agent which increases TSP2 activity; an agent which increase endoglin activity; or a combination thereof. The invention therefore provides a pharmaceutical composition comprising a PH therapy for use in the treatment of PH, wherein a patient to be treated has been diagnosed or prognosed using a method of the invention.

In certain embodiments, the method of treatment includes one therapy for PH (e.g. PAH). In certain embodiments, the method of treatment includes a combination of two or more such therapies. The term “disorder” as used herein also encompasses a “disease”. The disorder may be a disease. The disorder treated in accordance with the invention is PH, particularly PAH. The term “treat” or “treating” as used herein encompasses prophylactic treatment (e.g. to prevent onset of a disorder) as well as corrective treatment (treatment of a subject already suffering from a disorder). Preferably “treat” or “treating” as used herein means corrective treatment. The term “treat” or “treating” as used herein refers to the disorder and/or a symptom thereof. Therefore, a therapeutic may be administered to a subject in a therapeutically effective amount or a prophylactically effective amount. A “therapeutically effective amount” is any amount of a therapeutic formulation, which when administered alone or in combination to a subject for treating said disorder (or a symptom thereof) is sufficient to effect such treatment of the disorder, or symptom thereof. A “prophylactically effective amount” is any amount of a therapeutic formulation that, when administered alone or in combination to a subject inhibits or delays the onset or reoccurrence of a disorder (or a symptom thereof). In some embodiments, the prophylactically effective amount prevents the onset or reoccurrence of a disorder entirely. “Inhibiting” the onset means either lessening the likelihood of a disorder’s onset (or symptom thereof), or preventing the onset entirely. Administration may be by any route known in the art and will typically be dependent on the nature of the therapeutic to be administered. For example, a therapeutic may be administered orally or parenterally. Methods of parenteral delivery include topical, intra‐arterial, intramuscular, subcutaneous, intramedullary, intrathecal, intra‐ventricular, intravenous, intraperitoneal, or intranasal administration. The present inventors have demonstrated for the first time that netrin‐4, TSP2 and endoglin are all causally linked with PH. Accordingly, the present invention provides a method of treating and/or preventing PH (particularly PAH) by administering a therapeutically effect amount of an agent which inhibits netrin‐4 activity; an agent which increases TSP2 activity; an agent which increase endoglin activity; or a combination thereof, to a subject in need thereof. The invention further provides an agent which inhibits netrin‐4 activity; an agent which increases TSP2 activity; an agent which increase endoglin activity; or a combination thereof for use in a method of treating and/or preventing PH, particularly PAH. The invention further provides the use of an agent which inhibits netrin‐4 activity; an agent which increases TSP2 activity; an agent which increase endoglin activity; or a combination thereof in the manufacture of a medicament for the treatment and/or prevention of PH, particularly PAH. All embodiments of the “method for diagnosing or determining a prognosis for PH (e.g. PAH)” as described herein apply equally and without reservation to the treatments and treatment methods of the invention and to the methods for optimising therapy according to the invention. Monitoring Any of the aforementioned methods may be used to monitor the health of a subject diagnosed PH (e.g. PAH), or at risk of PH (e.g. PAH) due to one or more disease risk factors as described herein. In addition to monitoring patients with PH (e.g. PAH), the invention particularly relates to monitoring subjects who are related to individuals who have been diagnosed with PH (e.g. PAH). The methods described herein may thus further comprise repeating the ‘quantification’ and ‘comparison’ steps of the method after a selected time interval and the amount of a biomarker quantified after said time interval is compared to the amount quantified for each biomarker at an earlier time point, to determine whether the health of the subject has improved, worsened, or remained stable. The monitoring methods of the present invention may (a) provide an indication as to disease severity, (b) aid determination as to the correct course of treatment, (c) permit evaluation of response to treatment, (d) permit determination as to whether to continue or cease treatment, (e) provide a means of disease staging or (f) permit determination as to clinical outcome. Monitoring may take place for any clinically appropriate period of time, for example at least six months, at least nine months, at least 12 months, at least 18 months, at least 2 years, at least 5 years, or more. Given the chronic nature of PH (e.g. PAH), monitoring may take place indefinitely, and/or for the life of the subject. Monitoring may be conducted at any clinically appropriate interval, for example at least monthly, every two months, every three months, every six months, annually. Monitoring may be carried out on an ad hoc basis, for example if a subject reports a new symptom, a worsening of an existing symptom, and/or a deterioration in quality of life. Monitoring according to the invention may be conducted if there is a change (particularly a statistically significant change) in an established clinical measure for PH (e.g. PAH), such as those measures described herein. Monitoring may be conducted following a change in treatment, to assess the efficacy of the new treatment. In this way, the methods of the invention can be used to optimise therapy for a subject undergoing treatment for PH (e.g. PAH), as described herein.

Kits and Devices The present invention also provides kits and devices that are useful for carrying out the methods of the invention, in particular for carrying out the diagnostic and prognostic methods of the invention, the treatment methods of the invention, the methods for optimising therapy of the invention, and the monitoring methods of the invention. The kits and devices of the invention comprise reagents for quantification of a biomarker of the invention, or any combination thereof as described herein. A kit or device of the invention may comprise reagents for quantification of any combination of two or more (e.g. three or more, four or more, five or more, or all six) biomarkers selected from: NRP1, PRDX4, PXDN, renin, SVEP1 and/or TSP2. Preferably, the kit or device comprises reagents for the quantification of NRP1, PRDX4, PXDN, renin, SVEP1 and TSP2. As described above, different biomarkers may be quantified using different detection methods according to the present invention. For example one or more biomarker of the invention may be quantified using an aptamer‐based assay (e.g. using one or more SOMAer, such as a SomaScan‐V4), and a different one or more biomarker of the invention may be quantified using an antibody‐based assay (e.g. an ELISA). Accordingly, the reagents for quantification of two or more biomarkers in a kit or device of the invention may comprise: (a) one or more aptamer specific for each of the two or more biomarkers; (b) one or more antibody specific for each of the two or more biomarkers; or (c) one or more antibody for at least one of the two or more biomarkers, and one or more aptamer specific for the two or more biomarkers for which an antibody is not provided. By way of non‐limiting example, a kit or device may comprise one or more aptamer (e.g. SOMAer) specific for any two, three, four or five of NRP1, PXDN, renin, SVEP1 and TSP2, and one or more antibody specific for PRDX4. The reagents for quantification of biomarkers may be for quantifying the biomarkers in a body fluid sample obtained from a subject. Preferably, the reagents for quantifying biomarkers are for quantifying the biomarkers in a blood sample (e.g. whole blood, plasma or serum) from subject. As used herein, the “reagents for quantification of biomarkers” may comprise any reagent that allows the amount of the biomarkers described herein to be determined. Preferably, the reagents are for quantification of the biomarker(s) by an aptamer‐based assay or by ELISA, particularly preferably for quantification of the biomarker(s) using SOMAers and/or in a multiplex aptamer‐based assay. The kit or device may further comprise standards for use in quantifying the biomarker(s), for example by an aptamer‐based assay or by ELISA.

The kits and devices of the invention may further comprise a reference standard for the biomarker(s) or means for establishing a reference standard. The reference standard is as defined herein for the methods of the invention. The reference standard may represent a population of individuals known to have PH (e.g. PAH), as defined herein for the methods of the invention. Alternatively, or in addition, the reference standard may represent a population of healthy individuals, as defined herein for the methods of the invention. The kits and devices of the invention may comprise one or any combination of the described reference standards. For example, the kit or device may comprise a reference standard representing a population of individuals known to have PH (e.g. PAH), as defined herein for the methods of the invention and a reference standard representing a population of healthy individuals, as defined herein for the methods of the invention, or means for establishing these reference standards. The kits and devices of the invention may further comprise a known quantity or concentration of the biomarker(s) described herein for use as a standard. By way of non‐limiting example, when the kit or device comprises a reagent for quantification of NRP1, the kit or device may further comprise a known quantity of NRP1; when the kit or device comprises a reagent for quantification of PRDX4, the kit or device may further comprise a known quantity of PRDX4; when the kit or device comprises a reagent for quantification of PXDN, the kit or device may further comprise a known quantity of PXDN; when the kit or device comprises a reagent for quantification of renin, the kit or device may further comprise a known quantity of renin; when the kit or device comprises a reagent for quantification of SVEP1, the kit or device may further comprise a known quantity of SVEP1; and/or when the kit or device comprises a reagent for quantification of TSP2, the kit or device may further comprise a known quantity of TSP2. The kit of the invention may further comprise instructions for carrying out the methods and uses of the invention as described herein. Generally, the reagents of the kit or biomarker will bind, with at least some specificity, to the biomarker(s) contained in the sample being tested. Examples of classes of compounds of the kit or device include, but are not to, aptamers, antibodies and fragments thereof, peptides, polypeptides, proteoglycans, glycoproteins, lipoproteins, carbohydrates, lipids, nucleic acids, organic and inorganic chemicals, and natural and synthetic polymers. The reagents may be part of an array, or the reagents may be packaged separately and/or individually. The reagents may be immobilised on an inert support, or may be used to immobilise the biomarker(s) on an inert support during use. The kit or device may also comprise at least one internal standard. Likewise, the internal standards can be any of the classes of compounds described above.

The kits and devices of the present invention also may contain reagents that can be used to detectably label biomarker(s) contained in a sample to be tested. The kits and devices of the present invention may also include pharmaceutical excipients, diluents and/or adjuvants when the biomarker is to be used to raise an antibody. Examples of pharmaceutical adjuvants include, but are not limited to, preservatives, wetting agents, emulsifying agents, and dispersing agents. Prevention of the action of microorganisms can be ensured by the inclusion of various antibacterial and antifungal agents, for example, paraben, chlorobutanol, phenol sorbic acid, and the like. It may also be desirable to include isotonic agents such as sugars, sodium chloride, and the like. SEQUENCE HOMOLOGY Any of a variety of sequence alignment methods can be used to determine percent identity, including, without limitation, global methods, local methods and hybrid methods, such as, e.g., segment approach methods. Protocols to determine percent identity are routine procedures within the scope of one skilled in the art. Global methods align sequences from the beginning to the end of the molecule and determine the best alignment by adding up scores of individual residue pairs and by imposing gap penalties. Non‐limiting methods include, e.g., CLUSTAL W, see, e.g., Julie D. Thompson et al., CLUSTAL W: Improving the Sensitivity of Progressive Multiple Sequence Alignment Through Sequence Weighting, Position‐ Specific Gap Penalties and Weight Matrix Choice, 22(22) Nucleic Acids Research 4673‐4680 (1994); and iterative refinement, see, e.g., Osamu Gotoh, Significant Improvement in Accuracy of Multiple Protein. Sequence Alignments by Iterative Refinement as Assessed by Reference to Structural Alignments, 264(4) J. MoI. Biol. 823‐838 (1996). Local methods align sequences by identifying one or more conserved motifs shared by all of the input sequences. Non‐limiting methods include, e.g., Match‐box, see, e.g., Eric Depiereux and Ernest Feytmans, Match‐Box: A Fundamentally New Algorithm for the Simultaneous Alignment of Several Protein Sequences, 8(5) CABIOS 501 ‐509 (1992); Gibbs sampling, see, e.g., C. E. Lawrence et al., Detecting Subtle Sequence Signals: A Gibbs Sampling Strategy for Multiple Alignment, 262(5131 ) Science 208‐214 (1993); Align‐M, see, e.g., Ivo Van WaIIe et al., Align‐M ‐ A New Algorithm for Multiple Alignment of Highly Divergent Sequences, 20(9) Bioinformatics:1428‐1435 (2004). Thus, percent sequence identity is determined by conventional methods. See, for example, Altschul et al., Bull. Math. Bio. 48: 603‐16, 1986 and Henikoff and Henikoff, Proc. Natl. Acad. Sci. USA 89:10915‐19, 1992. Briefly, two amino acid sequences are aligned to optimize the alignment scores using a gap opening penalty of 10, a gap extension penalty of 1, and the "blosum 62" scoring matrix

of Henikoff and Henikoff (ibid.) as shown below (amino acids are indicated by the standard one‐ letter codes). The "percent sequence identity" between two or more nucleic acid or amino acid sequences is a function of the number of identical positions shared by the sequences. Thus, % identity may be calculated as the number of identical nucleotides / amino acids divided by the total number of nucleotides / amino acids, multiplied by 100. Calculations of % sequence identity may also take into account the number of gaps, and the length of each gap that needs to be introduced to optimize alignment of two or more sequences. Sequence comparisons and the determination of percent identity between two or more sequences can be carried out using specific mathematical algorithms, such as BLAST, which will be familiar to a skilled person. ALIGNMENT SCORES FOR DETERMINING SEQUENCE IDENTITY A R N D C Q E G H I L K M F P S T W Y V A 4 R ‐1 5 N ‐2 0 6 D ‐2 ‐2 1 6 C 0 ‐3 ‐3 ‐3 9 Q ‐1 1 0 0 ‐3 5 E ‐1 0 0 2 ‐4 2 5 G 0 ‐2 0 ‐1 ‐3 ‐2 ‐2 6 H ‐2 0 1 ‐1 ‐3 0 0 ‐2 8 I ‐1 ‐3 ‐3 ‐3 ‐1 ‐3 ‐3 ‐4 ‐3 4 L ‐1 ‐2 ‐3 ‐4 ‐1 ‐2 ‐3 ‐4 ‐3 2 4 K ‐1 2 0 ‐1 ‐3 1 1 ‐2 ‐1 ‐3 ‐2 5 M ‐1 ‐1 ‐2 ‐3 ‐1 0 ‐2 ‐3 ‐2 1 2 ‐1 5 F ‐2 ‐3 ‐3 ‐3 ‐2 ‐3 ‐3 ‐3 ‐1 0 0 ‐3 0 6 P ‐1 ‐2 ‐2 ‐1 ‐3 ‐1 ‐1 ‐2 ‐2 ‐3 ‐3 ‐1 ‐2 ‐4 7 S 1 ‐1 1 0 ‐1 0 0 0 ‐1 ‐2 ‐2 0 ‐1 ‐2 ‐1 4 T 0 ‐1 0 ‐1 ‐1 ‐1 ‐1 ‐2 ‐2 ‐1 ‐1 ‐1 ‐1 ‐2 ‐1 1 5 W ‐3 ‐3 ‐4 ‐4 ‐2 ‐2 ‐3 ‐2 ‐2 ‐3 ‐2 ‐3 ‐1 1 ‐4 ‐3 ‐2 11 Y ‐2 ‐2 ‐2 ‐3 ‐2 ‐1 ‐2 ‐3 2 ‐1 ‐1 ‐2 ‐1 3 ‐3 ‐2 ‐2 2 7 V 0 ‐3 ‐3 ‐3 ‐1 ‐2 ‐2 ‐3 ‐3 3 1 ‐2 1 ‐1 ‐2 ‐2 0 ‐3 ‐1 4

The percent identity is then calculated as: Total number of identical matches __________________________________________ x 100 [length of the longer sequence plus the number of gaps introduced into the longer sequence in order to align the two sequences] Substantially homologous polypeptides are characterized as having one or more amino acid substitutions, deletions or additions. These changes are preferably of a minor nature, that is conservative amino acid substitutions (as described herein) and other substitutions that do not significantly affect the folding or activity of the polypeptide; small deletions, typically of one to about 30 amino acids; and small amino‐ or carboxyl‐terminal extensions, such as an amino‐terminal methionine residue, a small linker peptide of up to about 20‐25 residues, or an affinity tag. In addition to the 20 standard amino acids, non‐standard amino acids (such as 4‐ hydroxyproline, 6‐N‐methyl lysine, 2‐aminoisobutyric acid, isovaline and α ‐methyl serine) may be substituted for amino acid residues of the polypeptides of the present invention. A limited number of non‐conservative amino acids, amino acids that are not encoded by the genetic code, and unnatural amino acids may be substituted for polypeptide amino acid residues. The polypeptides of the present invention can also comprise non‐naturally occurring amino acid residues. Non‐naturally occurring amino acids include, without limitation, trans‐3‐methylproline, 2,4‐ methano‐proline, cis‐4‐hydroxyproline, trans‐4‐hydroxy‐proline, N‐methylglycine, allo‐threonine, methyl‐threonine, hydroxy‐ethylcysteine, hydroxyethylhomo‐cysteine, nitro‐glutamine, homoglutamine, pipecolic acid, tert‐leucine, norvaline, 2‐azaphenylalanine, 3‐azaphenyl‐alanine, 4‐ azaphenyl‐alanine, and 4‐fluorophenylalanine. Several methods are known in the art for incorporating non‐naturally occurring amino acid residues into proteins. For example, an in vitro system can be employed wherein nonsense mutations are suppressed using chemically aminoacylated suppressor tRNAs. Methods for synthesizing amino acids and aminoacylating tRNA are known in the art. Transcription and translation of plasmids containing nonsense mutations is carried out in a cell free system comprising an E. coli S30 extract and commercially available enzymes and other reagents. Proteins are purified by chromatography. See, for example, Robertson et al., J. Am. Chem. Soc. 113:2722, 1991; Ellman et al., Methods Enzymol. 202:301, 1991; Chung et al., Science 259:806‐9, 1993; and Chung et al., Proc. Natl. Acad. Sci. USA 90:10145‐9, 1993). In a second method, translation is carried out in Xenopus oocytes by microinjection of mutated mRNA

and chemically aminoacylated suppressor tRNAs (Turcatti et al., J. Biol. Chem. 271:19991‐8, 1996). Within a third method, E. coli cells are cultured in the absence of a natural amino acid that is to be replaced (e.g., phenylalanine) and in the presence of the desired non‐naturally occurring amino acid(s) (e.g., 2‐azaphenylalanine, 3‐azaphenylalanine, 4‐azaphenylalanine, or 4‐fluorophenylalanine). The non‐naturally occurring amino acid is incorporated into the polypeptide in place of its natural counterpart. See, Koide et al., Biochem. 33:7470‐6, 1994. Naturally occurring amino acid residues can be converted to non‐naturally occurring species by in vitro chemical modification. Chemical modification can be combined with site‐directed mutagenesis to further expand the range of substitutions (Wynn and Richards, Protein Sci. 2:395‐403, 1993). A limited number of non‐conservative amino acids, amino acids that are not encoded by the genetic code, non‐naturally occurring amino acids, and unnatural amino acids may be substituted for amino acid residues of polypeptides of the present invention. Essential amino acids in the polypeptides of the present invention can be identified according to procedures known in the art, such as site‐directed mutagenesis or alanine‐scanning mutagenesis (Cunningham and Wells, Science 244: 1081‐5, 1989). Sites of biological interaction can also be determined by physical analysis of structure, as determined by such techniques as nuclear magnetic resonance, crystallography, electron diffraction or photoaffinity labeling, in conjunction with mutation of putative contact site amino acids. See, for example, de Vos et al., Science 255:306‐ 12, 1992; Smith et al., J. Mol. Biol. 224:899‐904, 1992; Wlodaver et al., FEBS Lett. 309:59‐64, 1992. The identities of essential amino acids can also be inferred from analysis of homologies with related components (e.g. the translocation or protease components) of the polypeptides of the present invention. Multiple amino acid substitutions can be made and tested using known methods of mutagenesis and screening, such as those disclosed by Reidhaar‐Olson and Sauer (Science 241:53‐7, 1988) or Bowie and Sauer (Proc. Natl. Acad. Sci. USA 86:2152‐6, 1989). Briefly, these authors disclose methods for simultaneously randomizing two or more positions in a polypeptide, selecting for functional polypeptide, and then sequencing the mutagenized polypeptides to determine the spectrum of allowable substitutions at each position. Other methods that can be used include phage display (e.g., Lowman et al., Biochem. 30:10832‐7, 1991; Ladner et al., U.S. Patent No. 5,223,409; Huse, WIPO Publication WO 92/06204) and region‐directed mutagenesis (Derbyshire et al., Gene 46:145, 1986; Ner et al., DNA 7:127, 1988). Multiple amino acid substitutions can be made and tested using known methods of mutagenesis and screening, such as those disclosed by Reidhaar‐Olson and Sauer (Science 241:53‐7, 1988) or Bowie and Sauer (Proc. Natl. Acad. Sci. USA 86:2152‐6, 1989). Briefly, these authors disclose methods for simultaneously randomizing two or more positions in a polypeptide, selecting for functional polypeptide, and then sequencing the mutagenized polypeptides to determine the spectrum of allowable substitutions at each position. Other methods that can be used include phage display (e.g., Lowman et al., Biochem. 30:10832‐7, 1991; Ladner et al., U.S. Patent No. 5,223,409; Huse, WIPO Publication WO 92/06204) and region‐directed mutagenesis (Derbyshire et al., Gene 46:145, 1986; Ner et al., DNA 7:127, 1988). SEQUENCE INFORMATION: SEQ ID NO: 1 – NRP1 amino acid sequence (UniProt Accession No. O14786) MERGLPLLCAVLALVLAPAGAFRNDKCGDTIKIESPGYLTSPGYPHSYHPSEKCEWLIQAPDPYQRIMINFNPHF DLEDRDCKYDYVEVFDGENENGHFRGKFCGKIAPPPVVSSGPFLFIKFVSDYETHGAGFSIRYEIFKRGPECSQN YTTPSGVIKSPGFPEKYPNSLECTYIVFVPKMSEIILEFESFDLEPDSNPPGGMFCRYDRLEIWDGFPDVGPHIG RYCGQKTPGRIRSSSGILSMVFYTDSAIAKEGFSANYSVLQSSVSEDFKCMEALGMESGEIHSDQITASSQYSTN WSAERSRLNYPENGWTPGEDSYREWIQVDLGLLRFVTAVGTQGAISKETKKKYYVKTYKIDVSSNGEDWITIKEG NKPVLFQGNTNPTDVVVAVFPKPLITRFVRIKPATWETGISMRFEVYGCKITDYPCSGMLGMVSGLISDSQITSS NQGDRNWMPENIRLVTSRSGWALPPAPHSYINEWLQIDLGEEKIVRGIIIQGGKHRENKVFMRKFKIGYSNNGSD WKMIMDDSKRKAKSFEGNNNYDTPELRTFPALSTRFIRIYPERATHGGLGLRMELLGCEVEAPTAGPTTPNGNLV DECDDDQANCHSGTGDDFQLTGGTTVLATEKPTVIDSTIQSEFPTYGFNCEFGWGSHKTFCHWEHDNHVQLKWSV LTSKTGPIQDHTGDGNFIYSQADENQKGKVARLVSPVVYSQNSAHCMTFWYHMSGSHVGTLRVKLRYQKPEEYDQ LVWMAIGHQGDHWKEGRVLLHKSLKLYQVIFEGEIGKGNLGGIAVDDISINNHISQEDCAKPADLDKKNPEIKID ETGSTPGYEGEGEGDKNISRKPGNVLKTLDPILITIIAMSALGVLLGAVCGVVLYCACWHNGMSERNLSALENYN FELVDGVKLKKDKLNTQSTYSEA SEQ ID NO: 2 – PRDX4 amino acid sequence (UniProt Accession No. Q13162) MEALPLLAATTPDHGRHRRLLLLPLLLFLLPAGAVQGWETEERPRTREEECHFYAGGQVYPGEASRVSVADHSLH LSKAKISKPAPYWEGTAVIDGEFKELKLTDYRGKYLVFFFYPLDFTFVCPTEIIAFGDRLEEFRSINTEVVACSV DSQFTHLAWINTPRRQGGLGPIRIPLLSDLTHQISKDYGVYLEDSGHTLRGLFIIDDKGILRQITLNDLPVGRSV DETLRLVQAFQYTDKHGEVCPAGWKPGSETIIPDPAGKLKYFDKLN SEQ ID NO: 3 – PXDN amino acid sequence (UniProt Accession No. Q92626) MAKRSRGPGRRCLLALVLFCAWGTLAVVAQKPGAGCPSRCLCFRTTVRCMHLLLEAVPAVAPQTSILDLRFNRIR EIQPGAFRRLRNLNTLLLNNNQIKRIPSGAFEDLENLKYLYLYKNEIQSIDRQAFKGLASLEQLYLHFNQIETLD PDSFQHLPKLERLFLHNNRITHLVPGTFNHLESMKRLRLDSNTLHCDCEILWLADLLKTYAESGNAQAAAICEYP RRIQGRSVATITPEELNCERPRITSEPQDADVTSGNTVYFTCRAEGNPKPEIIWLRNNNELSMKTDSRLNLLDDG TLMIQNTQETDQGIYQCMAKNVAGEVKTQEVTLRYFGSPARPTFVIQPQNTEVLVGESVTLECSATGHPPPRISW TRGDRTPLPVDPRVNITPSGGLYIQNVVQGDSGEYACSATNNIDSVHATAFIIVQALPQFTVTPQDRVVIEGQTV

DFQCEAKGNPPPVIAWTKGGSQLSVDRRHLVLSSGTLRISGVALHDQGQYECQAVNIIGSQKVVAHLTVQPRVTP VFASIPSDTTVEVGANVQLPCSSQGEPEPAITWNKDGVQVTESGKFHISPEGFLTINDVGPADAGRYECVARNTI GSASVSMVLSVNVPDVSRNGDPFVATSIVEAIATVDRAINSTRTHLFDSRPRSPNDLLALFRYPRDPYTVEQARA GEIFERTLQLIQEHVQHGLMVDLNGTSYHYNDLVSPQYLNLIANLSGCTAHRRVNNCSDMCFHQKYRTHDGTCNN LQHPMWGASLTAFERLLKSVYENGFNTPRGINPHRLYNGHALPMPRLVSTTLIGTETVTPDEQFTHMLMQWGQFL DHDLDSTVVALSQARFSDGQHCSNVCSNDPPCFSVMIPPNDSRARSGARCMFFVRSSPVCGSGMTSLLMNSVYPR EQINQLTSYIDASNVYGSTEHEARSIRDLASHRGLLRQGIVQRSGKPLLPFATGPPTECMRDENESPIPCFLAGD HRANEQLGLTSMHTLWFREHNRIATELLKLNPHWDGDTIYYETRKIVGAEIQHITYQHWLPKILGEVGMRTLGEY HGYDPGINAGIFNAFATAAFRFGHTLVNPLLYRLDENFQPIAQDHLPLHKAFFSPFRIVNEGGIDPLLRGLFGVA GKMRVPSQLLNTELTERLFSMAHTVALDLAAINIQRGRDHGIPPYHDYRVYCNLSAAHTFEDLKNEIKNPEIREK LKRLYGSTLNIDLFPALVVEDLVPGSRLGPTLMCLLSTQFKRLRDGDRLWYENPGVFSPAQLTQIKQTSLARILC DNADNITRVQSDVFRVAEFPHGYGSCDEIPRVDLRVWQDCCEDCRTRGQFNAFSYHFRGRRSLEFSYQEDKPTKK TRPRKIPSVGRQGEHLSNSTSAFSTRSDASGTNDFREFVLEMQKTITDLRTQIKKLESRLSTTECVDAGGESHAN NTKWKKDACTICECKDGQVTCFVEACPPATCAVPVNIPGACCPVCLQKRAEEKP SEQ ID NO: 4 – SVEP1 amino acid sequence (UniProt Accession No. Q4LDE5) MWPRLAFCCWGLALVSGWATFQQMSPSRNFSFRLFPETAPGAPGSIPAPPAPGDEAAGSRVERLGQAFRRRVRLL RELSERLELVFLVDDSSSVGEVNFRSELMFVRKLLSDFPVVPTATRVAIVTFSSKNYVVPRVDYISTRRARQHKC ALLLQEIPAISYRGGGTYTKGAFQQAAQILLHARENSTKVVFLITDGYSNGGDPRPIAASLRDSGVEIFTFGIWQ GNIRELNDMASTPKEEHCYLLHSFEEFEALARRALHEDLPSGSFIQDDMVHCSYLCDEGKDCCDRMGSCKCGTHT GHFECICEKGYYGKGLQYECTACPSGTYKPEGSPGGISSCIPCPDENHTSPPGSTSPEDCVCREGYRASGQTCEL VHCPALKPPENGYFIQNTCNNHFNAACGVRCHPGFDLVGSSIILCLPNGLWSGSESYCRVRTCPHLRQPKHGHIS CSTREMLYKTTCLVACDEGYRLEGSDKLTCQGNSQWDGPEPRCVERHCSTFQMPKDVIISPHNCGKQPAKFGTIC YVSCRQGFILSGVKEMLRCTTSGKWNVGVQAAVCKDVEAPQINCPKDIEAKTLEQQDSANVTWQIPTAKDNSGEK VSVHVHPAFTPPYLFPIGDVAIVYTATDLSGNQASCIFHIKVIDAEPPVIDWCRSPPPVQVSEKVHAASWDEPQF SDNSGAELVITRSHTQGDLFPQGETIVQYTATDPSGNNRTCDIHIVIKGSPCEIPFTPVNGDFICTPDNTGVNCT LTCLEGYDFTEGSTDKYYCAYEDGVWKPTYTTEWPDCAKKRFANHGFKSFEMFYKAARCDDTDLMKKFSEAFETT LGKMVPSFCSDAEDIDCRLEENLTKKYCLEYNYDYENGFAIGPGGWGAANRLDYSYDDFLDTVQETATSIGNAKS SRIKRSAPLSDYKIKLIFNITASVPLPDERNDTLEWENQQRLLQTLETITNKLKRTLNKDPMYSFQLASEILIAD SNSLETKKASPFCRPGSVLRGRMCVNCPLGTYYNLEHFTCESCRIGSYQDEEGQLECKLCPSGMYTEYIHSRNIS DCKAQCKQGTYSYSGLETCESCPLGTYQPKFGSRSCLSCPENTSTVKRGAVNISACGVPCPEGKFSRSGLMPCHP CPRDYYQPNAGKAFCLACPFYGTTPFAGSRSITECSSFSSTFSAAEESVVPPASLGHIKKRHEISSQVFHECFFN PCHNSGTCQQLGRGYVCLCPLGYTGLKCETDIDECSPLPCLNNGVCKDLVGEFICECPSGYTGQRCEENINECSS SPCLNKGICVDGVAGYRCTCVKGFVGLHCETEVNECQSNPCLNNAVCEDQVGGFLCKCPPGFLGTRCGKNVDECL SQPCKNGATCKDGANSFRCLCAAGFTGSHCELNINECQSNPCRNQATCVDELNSYSCKCQPGFSGKRCETEQSTG FNLDFEVSGIYGYVMLDGMLPSLHALTCTFWMKSSDDMNYGTPISYAVDNGSDNTLLLTDYNGWVLYVNGREKIT NCPSVNDGRWHHIAITWTSANGIWKVYIDGKLSDGGAGLSVGLPIPGGGALVLGQEQDKKGEGFSPAESFVGSIS QLNLWDYVLSPQQVKSLATSCPEELSKGNVLAWPDFLSGIVGKVKIDSKSIFCSDCPRLGGSVPHLRTASEDLKP GSKVNLFCDPGFQLVGNPVQYCLNQGQWTQPLPHCERISCGVPPPLENGFHSADDFYAGSTVTYQCNNGYYLLGD SRMFCTDNGSWNGVSPSCLDVDECAVGSDCSEHASCLNVDGSYICSCVPPYTGDGKNCAEPIKCKAPGNPENGHS

SGEIYTVGAEVTFSCQEGYQLMGVTKITCLESGEWNHLIPYCKAVSCGKPAIPENGCIEELAFTFGSKVTYRCNK GYTLAGDKESSCLANSSWSHSPPVCEPVKCSSPENINNGKYILSGLTYLSTASYSCDTGYSLQGPSIIECTASGI WDRAPPACHLVFCGEPPAIKDAVITGNNFTFRNTVTYTCKEGYTLAGLDTIECLADGKWSRSDQQCLAVSCDEPP IVDHASPETAHRLFGDIAFYYCSDGYSLADNSQLLCNAQGKWVPPEGQDMPRCIAHFCEKPPSVSYSILESVSKA KFAAGSVVSFKCMEGFVLNTSAKIECMRGGQWNPSPMSIQCIPVRCGEPPSIMNGYASGSNYSFGAMVAYSCNKG FYIKGEKKSTCEATGQWSSPIPTCHPVSCGEPPKVENGFLEHTTGRIFESEVRYQCNPGYKSVGSPVFVCQANRH WHSESPLMCVPLDCGKPPPIQNGFMKGENFEVGSKVQFFCNEGYELVGDSSWTCQKSGKWNKKSNPKCMPAKCPE PPLLENQLVLKELTTEVGVVTFSCKEGHVLQGPSVLKCLPSQQWNDSFPVCKIVLCTPPPLISFGVPIPSSALHF GSTVKYSCVGGFFLRGNSTTLCQPDGTWSSPLPECVPVECPQPEEIPNGIIDVQGLAYLSTALYTCKPGFELVGN TTTLCGENGHWLGGKPTCKAIECLKPKEILNGKFSYTDLHYGQTVTYSCNRGFRLEGPSALTCLETGDWDVDAPS CNAIHCDSPQPIENGFVEGADYSYGAIIIYSCFPGFQVAGHAMQTCEESGWSSSIPTCMPIDCGLPPHIDFGDCT KLKDDQGYFEQEDDMMEVPYVTPHPPYHLGAVAKTWENTKESPATHSSNFLYGTMVSYTCNPGYELLGNPVLICQ EDGTWNGSAPSCISIECDLPTAPENGFLRFTETSMGSAVQYSCKPGHILAGSDLRLCLENRKWSGASPRCEAISC KKPNPVMNGSIKGSNYTYLSTLYYECDPGYVLNGTERRTCQDDKNWDEDEPICIPVDCSSPPVSANGQVRGDEYT FQKEIEYTCNEGFLLEGARSRVCLANGSWSGATPDCVPVRCATPPQLANGVTEGLDYGFMKEVTFHCHEGYILHG APKLTCQSDGNWDAEIPLCKPVNCGPPEDLAHGFPNGFSFIHGGHIQYQCFPGYKLHGNSSRRCLSNGSWSGSSP SCLPCRCSTPVIEYGTVNGTDFDCGKAARIQCFKGFKLLGLSEITCEADGQWSSGFPHCEHTSCGSLPMIPNAFI SETSSWKENVITYSCRSGYVIQGSSDLICTEKGVWSQPYPVCEPLSCGSPPSVANAVATGEAHTYESEVKLRCLE GYTMDTDTDTFTCQKDGRWFPERISCSPKKCPLPENITHILVHGDDFSVNRQVSVSCAEGYTFEGVNISVCQLDG TWEPPFSDESCSPVSCGKPESPEHGFVVGSKYTFESTIIYQCEPGYELEGNRERVCQENRQWSGGVAICKETRCE TPLEFLNGKADIENRTTGPNVVYSCNRGYSLEGPSEAHCTENGTWSHPVPLCKPNPCPVPFVIPENALLSEKEFY VDQNVSIKCREGFLLQGHGIITCNPDETWTQTSAKCEKISCGPPAHVENAIARGVHYQYGDMITYSCYSGYMLEG FLRSVCLENGTWTSPPICRAVCRFPCQNGGICQRPNACSCPEGWMGRLCEEPICILPCLNGGRCVAPYQCDCPPG WTGSRCHTAVCQSPCLNGGKCVRPNRCHCLSSWTGHNCSRKRRTG SEQ ID NO: 5 – TSP2 amino acid sequence (UniProt Accession No. P35442) MVWRLVLLALWVWPSTQAGHQDKDTTFDLFSISNINRKTIGAKQFRGPDPGVPAYRFVRFDYIPPVNADDLSKIT KIMRQKEGFFLTAQLKQDGKSRGTLLALEGPGLSQRQFEIVSNGPADTLDLTYWIDGTRHVVSLEDVGLADSQWK NVTVQVAGETYSLHVGCDLIDSFALDEPFYEHLQAEKSRMYVAKGSARESHFRGLLQNVHLVFENSVEDILSKKG CQQGQGAEINAISENTETLRLGPHVTTEYVGPSSERRPEVCERSCEELGNMVQELSGLHVLVNQLSENLKRVSND NQFLWELIGGPPKTRNMSACWQDGRFFAENETWVVDSCTTCTCKKFKTICHQITCPPATCASPSFVEGECCPSCL HSVDGEEGWSPWAEWTQCSVTCGSGTQQRGRSCDVTSNTCLGPSIQTRACSLSKCDTRIRQDGGWSHWSPWSSCS VTCGVGNITRIRLCNSPVPQMGGKNCKGSGRETKACQGAPCPIDGRWSPWSPWSACTVTCAGGIRERTRVCNSPE PQYGGKACVGDVQERQMCNKRSCPVDGCLSNPCFPGAQCSSFPDGSWSCGSCPVGFLGNGTHCEDLDECALVPDI CFSTSKVPRCVNTQPGFHCLPCPPRYRGNQPVGVGLEAAKTEKQVCEPENPCKDKTHNCHKHAECIYLGHFSDPM YKCECQTGYAGDGLICGEDSDLDGWPNLNLVCATNATYHCIKDNCPHLPNSGQEDFDKDGIGDACDDDDDNDGVT DEKDNCQLLFNPRQADYDKDEVGDRCDNCPYVHNPAQIDTDNNGEGDACSVDIDGDDVFNERDNCPYVYNTDQRD TDGDGVGDHCDNCPLVHNPDQTDVDNDLVGDQCDNNEDIDDDGHQNNQDNCPYISNANQADHDRDGQGDACDPDD DNDGVPDDRDNCRLVFNPDQEDLDGDGRGDICKDDFDNDNIPDIDDVCPENNAISETDFRNFQMVPLDPKGTTQI DPNWVIRHQGKELVQTANSDPGIAVGFDEFGSVDFSGTFYVNTDRDDDYAGFVFGYQSSSRFYVVMWKQVTQTYW

EDQPTRAYGYSGVSLKVVNSTTGTGEHLRNALWHTGNTPGQVRTLWHDPRNIGWKDYTAYRWHLTHRPKTGYIRV LVHEGKQVMADSGPIYDQTYAGGRLGLFVFSQEMVYFSDLKYECRDI SEQ ID NO: 6 – renin amino acid sequence (UniProt Accession No. P00797) MDGWRRMPRWGLLLLLWGSCTFGLPTDTTTFKRIFLKRMPSIRESLKERGVDMARLGPEWSQPMKRLTLGNTTSS VILTNYMDTQYYGEIGIGTPPQTFKVVFDTGSSNVWVPSSKCSRLYTACVYHKLFDASDSSSYKHNGTELTLRYS TGTVSGFLSQDIITVGGITVTQMFGEVTEMPALPFMLAEFDGVVGMGFIEQAIGRVTPIFDNIISQGVLKEDVFS FYYNRDSENSQSLGGQIVLGGSDPQHYEGNFHYINLIKTGVWQIQMKGVSVGSSTLLCEDGCLALVDTGASYISG STSSIEKLMEALGAKKRLFDYVVKCNEGPTLPDISFHLGGKEYTLTSADYVFQESYSSKKLCTLAIHAMDIPPPT GPTWALGATFIRKFYTEFDRRNNRIGFALAR EXAMPLES The invention will be further clarified by the following examples, which are intended to be purely exemplary of the invention and are in no way limiting. Materials and methods Study samples Subjects with prevalent idiopathic, heritable, or drug‐induced pulmonary arterial hypertension aged 18‐65 years (PAH, n=357) from the UK National Cohort Study of Idiopathic and Heritable Pulmonary Arterial Hypertension (clinicaltrials.gov NCT01907295) were recruited between 19th February 2014 and 6th November 2018. The diagnostic criteria for idiopathic IPAH (IPAH)/heritable PAH (HPAH) over the course of this study was stable ‐ raised mean pulmonary arterial pressure (mPAP) ≥ 25 mmHg with pulmonary capillary wedge pressure (PCWP) ≤ 15 mmHg (and pulmonary vascular resistance (PVR) ≥ 3 mmHg‐min/L, or Woods units) at rest with exclusion of known associated diseases according to contemporary international consensus. 70 age‐ and sex‐ matched healthy controls without cardiovascular or respiratory diseases and 49 healthy relatives of subjects with PAH were recruited over the same period from the same centres. A subset of 262 subjects was re‐sampled at follow‐up visits averaging 6‐32 months apart (25‐75% was 10.2 ‐ 13.6). Survival status for PAH subjects was censored on 14 March 2020. After a median follow‐up of 4.7 years, 65 deaths and 13 transplants had occurred. 20 additional samples from three of the relatives and one PAH case were sourced from the local biobank at Hammersmith Hospital, London. Peripheral venous plasma EDTA samples were collected as described in Rhodes et al. (Circulation 2017;135:460‐475) and were obtained with informed consent and research ethics committee approval (13/EE/0203, 17/LO/0563 and 17/LO/0565). Subjects were not fasting and were sampled at their routine clinical appointment visits. The plasma samples underwent one freeze‐thaw

cycle to aliquot 120 µL for SomaScan™ assay and provide other aliquots for NT‐proBNP and targeted assays. Clinical and biochemical data were collected within 30 days and 7 days respectively of blood sampling. Proteomics analysis Proteomic analysis was performed using the SOMAscan version 4 assay (Somalogic Inc. Boulder, CO, USA) and technicians were blinded to subject status. 4349 somamers targeting 4152 unique proteins were included for analysis following removal of non‐human/non‐protein aptamers and quality control to select only those with stable measurements defined as <20% coefficient of variance in the repeated pooled plasma assay controls. Relative fluorescence units were log₁₀ transformed to normalise protein levels, then corrected for the first two principal components by linear regression to correct for population stratification or sample quality differences. Finally, protein levels were standardised to the healthy control levels for ease of interpretation of results and comparability of proteins. Statistical analysis Subjects and controls from the dataset were randomised into discovery and validation groups in a 2:1 ratio to adequately power discovery analysis of all proteins, and validation of proteins meeting statistical significance (Table 1). Protein levels were compared between healthy controls and subjects by logistic regression analysis, correcting for age and sex. Sensitivity analyses were performed to confirm protein differences were independent of haemolysis (cell free haemoglobin as covariate), anticoagulation therapy (coagulation factor X) or renal function (cystatin‐ c). These markers were obtained through the aptamer assay. All comparisons were corrected for multiple testing using Benjamini‐Hochberg false discovery rate (FDR). Prognostic proteins were identified by cox regression analysis correcting for age and sex and all‐cause mortality or lung transplant for severe PAH were included as events. To prioritise proteins independent of known prognostic factors models including 6‐minute walk distance (6MWD) or NT‐ proBNP were constructed. To identify the combination of markers which best predicted prognosis a least absolute shrinkage and selection operator (lasso) modelling approach using k‐fold cross‐ validation (k=10) was applied, with regularisation parameter (lambda) determined by the lowest error plus 1 standard error (to minimise over‐fitting) using the glmnet v2.0‐18 R package from CRAN. This produces a protein score from a linear weighted combination of the proteins identified by the lasso analysis. Receiver operating characteristic (ROC) analysis was performed using the pROC v1.14.0 and survivalROC v1.0.3 R packages.

This prognostic protein lasso score was then compared with risk indicators (clinical targets) as described by the international guidelines for PAH: WHO functional class=I or II, 6MWD >= 400m, cardiac index (CI) >= 2.4 L/min/m², BNP or NT‐proBNP < 150ng/L or 700ng/L, respectively. The WHO guidelines give cut‐offs for low risk as follows: 6MWD 440m, CI 2.5 L/min/m²m, BNP or NT‐proBNP 50/300 ng/L respectively. Kaplan Meier survival estimates were calculated and plotted using the survival v3.1‐8 R package. Data are presented as percentages, mean (±standard deviation, SD), 95% confidence interval (95% CI) or median and percentile range. Analysis was performed in R (v.3.6.3) and SPSS (v26, IBM, Armonk, NY, US). Protein genome‐wide association studies Whole genome sequence data were accessed for PAH subjects through the UK National Institute for Health Research BioResource (NIHRBR) Rare Diseases study. A genome‐wide association analysis was performed for protein levels and autosomal variants with a minor allele frequency (MAF) above 1%. Prior to analysis, log‐transformed protein levels were adjusted for age at sampling, gender, the first two principle components of proteomic data and the first three principle components of genomic data in linear regression models. Residuals from this linear regression were then rank‐inverse normalized and z‐scored. Genome‐wide association studies (GWAS) were performed using an additive model in linear regression with the SNPTEST software tool. The cis‐ region was defined as a ±500kb window from the transcription start site. Additional protein quantitative trait loci (pQTL) were curated from three publicly available protein GWAS and validated in the PAH cohort. Together with pQTL from the GWAS, these were then pruned for linkage disequilibrium (LD) using European individuals from the 1000 Genomes phase 3 as reference panel in the PLINK software tool (LD r²<0.001 within ±10 Mb). Mendelian randomisation studies To prioritize for a causal relationship between genetically influenced protein levels and risk of PAH, we applied two‐sample Mendelian randomisation (MR) analysis using the lead variants at a given pQTL (exposure) and an international GWAS of PAH (outcome) as instruments variables. The PAH GWAS combined genetic information on 11,744 individuals with European ancestry, including 2,085 cases with idiopathic or heritable PAH. The Wald ratio method was used to perform the MR analyses if the protein instrument consisted only of a single variant and the random‐effects inverse‐variance weighted method if two or more independent variants were available as implemented in the TwoSampleMR v0.5.3 R‐

package. Variants of the exposure and outcomes instrument were harmonised on the positive strand and allele frequencies were used for palindromic variants. Only variants that were directly called in the PAH GWAS were considered. For MR analyses proteins were selected that were associated with PAH against healthy controls in the discovery and replication subgroups independent of possible confounders and that were linked to clinical outcomes in PAH. Immunohistochemistry Formalin‐fixed paraffin‐embedded human lung tissue blocks from idiopathic PAH subjects and unused non‐PAH donors (n=3 each) were sectioned (2µm thickness), de‐paraffinized and re‐ hydrated and immunohistochemistry was performed. Briefly, antigen retrieval was achieved through pressure cooking in Tris‐EDTA buffer (pH 9.0) followed by BSA (10%) blocking and anti‐Netrin‐4 antibody incubation (1:25, HPA049832, Lot#R59752, Sigma‐Aldrich, St. Louis, MO, USA). Netrin‐4 protein expression was visualized via an alkaline phosphatase reaction using the ZytoChem‐Plus AP Polymer‐Kit (#POLAP‐100, Zytomed Systems, Berlin, Germany), and tissue counter‐stained with haematoxylin. Example 1 – Identifying circulating proteins associated with PAH Table 2 details the baseline characteristics of the study groups, analysed as summarised in Figure 1. Discovery and validation subgroups of PAH subjects were used to investigate the association of 4,152 plasma protein levels with survival. All 4,349 aptamers were used in Cox regression models adjusted for age and sex. 622 and 53 exceeded FDR (q<0.05) in the discovery and validation cohorts, respectively. 6MWD and plasma NT‐proBNP levels are established, non‐invasive risk assessment tools in PAH. 48 of 53 aptamers predicted survival independent of 6MWD and 33 aptamers, representing 31 proteins, were also independent of NT‐proBNP, age and sex (p<0.05; Figure 2 and Table 3). Example 2 – Selection of PAH biomarker panel To avoid analysing tenascin and SVEP1 more than once, the most significant aptamer from the analysis against NT‐proBNP was chosen for these two proteins. LASSO analysis of combinations of proteins in a Cox survival regression model selected six proteins (SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4) to create a single model score in the pooled discovery and validation subject subgroups (Table 1, Figure 3). The score accurately discriminated 5‐year transplant‐free survivors from non‐ survivors in the entire UK PAH cohort (area under the curve 0.77, Figure 4).

Example 3 – Screening in relatives of PAH subjects The protein score in samples taken from relatives of PAH cases undergoing screening for PAH was calculated (Figure 5). The relatives (1.26 female:male, median age 40 years, Q25/75^th 30‐ 56) were recruited between 15‐April‐2014 and 9‐April‐2019 and 24 were re‐sampled after 12 months (range 6‐17). During the follow‐up period (median 40 months, Q25/75^th 28‐43), 3/49 individuals had developed PAH and the second samples from these subjects had significantly higher NT‐proBNP levels and protein scores. Similarly, the change in NT‐proBNP (p=1.08x10^‐8), protein model (p=2.06x10^‐9) or combined model (p=1.82x10^‐10) was significantly greater in those individuals who developed PAH (Figure 5). A more detailed analysis of the three individuals who developed PAH showed two responded to targeted therapies which was associated with a drop in mean PAP and prognostic protein levels (Figure 6), whereas the third subject developed PH and died four months. Thus, the protein score predicted development of PAH (p=2.57x10^‐7) and response to therapy in previously healthy relatives. Example 4 – Monitoring of therapeutic response in a PAH subject The protein score was calculated using serial samples taken from a PAH subject who had been exposed to multiple PAH targeted therapies without significant improvement over a period of 6 years but subsequently responded to treatment with two experimental PAH therapies, the tyrosine kinase inhibitor imatinib and the activin receptor type IIA fusion protein sotatercept that acts as a ligand trap. Consistent with a gradual increase in mean PAP and reduced exercise capacity over time, the protein score and NT‐proBNP levels rose steadily in the subject over the years on standard therapies. After the initiation of imatinib treatment, the subject’s protein score improved distinctly, in agreement with improved 6MWD and a modest drop in mean PAP from 70 mmHg to 62 mmHg, whilst NT‐proBNP levels remained high. Subsequently, after starting sotatercept, a dramatic decrease in NT‐proBNP was observed, paired with a substantial drop in mean PAP from 62 mmHg to 34 mmHg and continued decline of the protein score (Figure 8). Thus, the protein score predicted response to therapy in a PAH subject monitored over 8 years with a dramatic response to investigational therapies. Example 5 – Interrogation of the panel’s robustness ROC analysis was performed on the UK cohort using the pROC v1.14.0 and survivalROC v1.0.3 R packages to assess robustness of the panel. Combinations of 2, 3, 4 or 5 markers from the panel were compared with complete 6‐protein panel. As shown in Figures 9 and 10, the protein score produced by the panel is robust. Whilst there was some decrease in the area under the curve g. .⁰²⁵⁸¹ ^.88E‐8 ^.93E‐7 ^.51E‐7 ^.24E‐6 ^.39E‐5 ^.91E‐8 ^.00918 ^.25E‐5 ^.55E‐6 ^.00023 ^.00079 ^.00369 ^.00278 ^.62E‐7 ^.87E‐5 ^.00043 ^.71E‐6 ^.00715 ^.62E‐6 ^.00065 ^.00037 ^0.0053 ^.00058 ^.00258 ^.92E‐5 ^.18E‐6 ^.02206 ^.00543 ^.00686 ^.00147 ^{00085 0.01733 1.14 0.07 0.04788 1.29 0.09 0.00265} ^{00184 0.02866 0.87 0.07 0.04835 0.77 0.08 0.00057} ^{00312 0.04217 1.21 0.05 0.00026 1.10 0.05 0.07223} ^{00207 0.03146 1.09 0.04 0.04225 1.12 0.07 0.11978} ^{00068 0.01694 1.07 0.03 0.05441 1.47 0.10 0.00011} ^{00092 0.0178 1.10 0.05 0.06037 1.22 0.08 0.01089} ^{00024 0.01127 1.13 0.07 0.07863 1.39 0.07 9.04E‐7} ^{47E‐5 0.00715 1.15 0.08 0.08251 1.32 0.09 0.00123} ^{00029 0.0117 1.15 0.09 0.12839 1.49 0.08 1.32E‐6} ^{00032 0.0117 1.32 0.19 0.15337 1.70 0.23 0.01908} ^{00032 0.0117 0.90 0.08 0.18132 0.68 0.09 7.85E‐6} ^{00252 0.03738 1.13 0.10 0.2259 1.49 0.13 0.00165} ^{00018 0.01127 0.94 0.11 0.55829 1.29 0.06 2.25E‐5} 71E‐5 0.00433 1.04 0.07 0.55872 1.27 0.07 0.00093 ^{00077 0.01733 1.03 0.08 0.70009 1.33 0.09 0.00198} 30E‐5 0.00433 0.98 0.11 0.86243 0.65 0.12 0.00027 ^{00387 0.04788 0.99 0.07 0.91457 1.30 0.06 1.96E‐5} ^{00322 0.04261 0.99 0.07 0.92702 1.26 0.08 0.00344} ^{19E‐5 0.00715 NA 0.00 NA 1.45 0.07 1.78E‐7} ^{00393 0.04788 0.85 0.10 0.08738 1.05 0.10 0.62092} ^{00272 0.03845 1.13 0.13 0.34499 1.38 0.17 0.05511} ^{00388 0.04788 1.02 0.04 0.62627 1.10 0.06 0.11086}hi, von Willebrand factor type A, EGF and pentraxin domain‐tor type A, EGF and pentraxin domain‐containing protein 1; nger receptor class F member 2; Renin, Renin; MIC‐1, ndin‐2; Collagen α‐3(VI), Collagen alpha‐3(VI) chain; CSF‐1, RhoC; BMP‐6, Bone morphogenetic protein 6; Tenascin, or ID‐2; Endoglin, Endoglin; S22AG, Solute carrier family 22 urtransferase; OLFL3, Olfactomedin‐like protein 3; CA125, a‐3; TRAIL R2, Tumor necrosis factor receptor superfamily nase; Angiopoietin‐2, Angiopoietin‐2; RGS1, Regulator of G‐ erase 15; BNP, Natriuretic peptides B; IGFBP‐7, Insulin‐like 9, Interleukin‐19; NT‐proBNP, N‐terminal pro‐BNP; Activin

(AUC), even 2‐protein combinations have prognostic utility. Indeed, even some single proteins, notably TSP2, PXDN, SVEP1 and NRP1 have prognostic potential when used individually (Tables 4 and 5). Cox regression analysis was then repeated to establish survival models using exemplary combinations of two, three, four and five of the six proteins, as well as for each protein individually, and calculated cut‐offs for each model and protein based on the 5‐year outcomes (all‐cause mortality or lung‐transplantation) in the UK PAH cohort (Table 6). Example 6 – differences in the plasma proteome between PAH subjects and controls The integrated proteomic and genomic analytic workflow to identify proteins associated with PAH, outcomes (transplant‐free survival) and genetic control (pQTLs) leading to Mendelian randomisation studies on those proteins that share all three features is presented in Figure 11. Details of the subjects and healthy subjects that provided plasma samples are given in Table 2. The association of 4,349 aptamers (representing 4,152 proteins) with PAH was tested using logistic regression models in discovery (n=69 controls, 239 PAH subjects) and 654 aptamers in replication (n=34 controls and 119 PAH subjects), correcting for age, sex and other confounders (Table 2). In recognition of the systemic consequences of PAH, 10 proteins associated with impaired renal function (exemplified by elevated cystatin C), and eleven due to anticoagulation treatment (exemplified by suppressed coagulation factor X) were excluded. None were associated due to haemolysis (exemplified by cellular‐free haemoglobin; data not shown). 208 proteins (measured by 215 aptamers) were identified that were independently associated with PAH (FDR q<0.05) (Figure 12A). Overrepresentation analysis did not find enriched biological processes after correction for multiple testing, but nominally significant pathways of interest included cellular response to starvation FDR q=0.39, P=0.00019 (e.g. GABA type A receptor‐associated protein and inhibin subunit beta B), BMP signaling pathway FDR q=0.39, P=0.00061 (e.g. endoglin, BMP binding endothelial regulator, hemojuvelin, notch receptor 1, RGMA/B, transforming growth factor beta receptor 3) regulation of cell growth FDR q=0.39, P=0.00049 (e.g. cyclin dependent kinase inhibitor 2D, endothelin 1, epidermal growth factor receptor, insulin like growth factor 1, vascular endothelial growth factor A); extracellular structure organization FDR q=0.39, P=0.00048 (e.g. COL18A1, fibulin 5, fibrinogen alpha, furin, hyaluronidase 1, TIMP1) and cell adhesion FDR q=0.39, P=0.0010 (e.g. ANTXR1, CD209, CD5, CSF1, integrin binding sialoprotein, spondin.1 and thrombospondin‐2). Table 4: ROC analysis of individual proteins from the 6‐protein panel, as well as 2‐, 3‐, 4‐ and 5‐ protein combinations. Table 5: Comparison of the ROC analysis for the best/worst 2‐, 3‐, 4‐ and 5‐protein combinations, compared with the full 6‐protein panel. Table 6: ROC‐derived cut‐offs for models (exemplary two/three/four/five protein combinations) and individual proteins. Proteins are expressed as z‐scores normalised to healthy control levels, such that 0 is the mean of healthy controls and units are standard deviations within healthy control group.

Many of the proteins associated with PAH demonstrate protein‐protein interactions and form clusters of strongly related proteins (Figure 12B). The effect of targeted PAH therapies endothelin receptor antagonists (ERA) and phosphodiesterase 5 (PDE5) inhibitors on circulating levels of the 208 proteins of interest was small compared to the effect of the diagnosis of PAH (mean ratio of absolute effect sizes of drug treatment:diagnosis of PAH was 0.22 for PDE5 inhibitor and 0.15 for ERA, Supplementary Figure 1). Apart from PDE5 inhibitors and circulating PDE5A levels, no strong single effect of targeted PAH therapies on protein levels was observed data not shown) Example 7 – Circulating proteins associated with genetic variation in PAH subjects To identify pQTL as instruments for Mendelian randomisation analysis, whole genome sequence data for 356 PAH subjects of European descent that contributed samples for the proteomic analysis were accessed. A GWAS using 8.1 million autosomal variants with a minor allele frequency (MAF) above 1% and protein level data from baseline plasma samples revealed 524 aptamer‐variant pairs, with a Bonferroni‐adjusted significance threshold for trans‐acting loci at P<1.5x10^‐11 (5x10^‐8/4,349) and a genome‐wide significance threshold for cis‐acting loci at P<5x10^‐8. Each association pair contained the sentinel variant with the lowest p‐value within a clump of correlated variants (LD r²<0.001 within ±10 Mb). 510/524 aptamer‐variant pairs were replicated in 262 follow‐up plasma samples from the same subject population with a Bonferroni‐adjusted significance threshold (P<9.54x10^‐5 = 0.05/524). These aptamers targeted 486 distinct proteins and 383 (75%) variants were in cis in relation to the encoding gene (data not shown). The location and consequence of variants, the relation of MAF and effect size, as well as the proportion of variability in plasma protein explained, mirror findings from protein GWAS in a population‐based cohort (data not shown). The effect size and p‐value of aptamer‐variant pairs were generally stable over time (data not shown). These pQTL were cross‐validated with a list curated from protein GWAS in three cohorts, namely, INTERVAL (Sun et al. Nature 2018;558:73‐79), KORA (Suhre et al. Nature communications 2017;8:14357) and AGES (Emilsson et al. Science (New York, NY) 2018;361:769‐773), and found that 1,377 protein‐variant pairs were replicated in our PAH cohort at nominal significance and with shared effect direction (p<0.05; Supplementary Table 6). Conversely, 117 variant‐aptamer pairs (69 in cis and 48 in trans) identified in our PAH cohort were not in public databases and so represent newly discovered pQTLs. Example 8 – Association of pQTL with PAH All pQTLs discovered in PAH subjects or replicated in PAH from three external populations were then merged and pruned (LD r²<0.001 within ±10 Mb) to give 1,046 aptamer‐variant pairs as potential instruments for Mendelian randomisation analysis (data not shown). To enrich for high‐ value proteins, these aptamer‐variant pairs were filtered for proteins that were both different between PAH subjects and controls in the case‐control comparison and predicted clinical outcomes in this subject population (Figure 13). This exercise yielded 8 circulating proteins (9 aptamers and 8 pQTLs). Mendelian randomisation analysis was conducted on these 8 proteins and 3 were associated with risk for PAH at Bonferroni‐adjusted level of significance (p<0.0056=0.05/9); namely, netrin‐4 (NET4, encoded by NTN4), thrombospondin‐2 (TSP2, encoded by THBS2) and endoglin (ENG; Figure 13, Table 7). While the NET4 and TSP2 pQTL were cis, the pQTL for ENG was trans and located in proximity to the ABO gene locus. Across non‐diseased human tissues, relative gene expression levels for NET4, TSP2 and ENG are highest in arterial vessels (data not shown). We observed an increase in protein staining for NET4 in distal pulmonary vessels in lung sections from PAH subjects (Figure 14). From these results, we conclude that the proteins netrin‐4, TSP2 and endoglin are causally related to PAH. Example 9 – Reproducibility of the new 6‐protein score and outperforms a previous prognostic panel A previous panel of nine proteins (consisting of interleukin‐1 receptor‐like 1 (IL1R1/ST2), tissue inhibitor of metalloproteinase 1 (TIMP‐1), tissue inhibitor of metalloproteinase 2(TIMP‐2), plasminogen, apolipoprotein‐E (ApoE), erythropoietin (EPO), complement factor H, complement factor D and insulin‐like growth factor binding protein‐1 (IFGBP‐1)) was compared with the single protein score from the 6‐protein panel selected in Example 2. The previous 9‐protein panel was outperformed by the novel 6‐protein score in 5‐year ROC analysis (Figure 15). The SomaLogic proteomic measurements of four of the proteins of the 6‐protein panel, TSP‐2, renin, PXDN and NRP‐1, were validated using commercially available targeted ELISA assays from R&D Systems (DTSP20 1:5 dilution in standard buffer, DNRP10 1:200 dilution in standard buffer) in twenty PAH patient plasma samples selected for having a wide range of protein values from the proteomic measurements. The results are shown in Figure 16, Spearman’s Rho>=0.3‐0.9, p<0.05 for all). Analysis of the power to predict survival of models constructed without 1 or more of the proteins demonstrated that loss of 1 or 2 proteins could be well tolerated in the dataset, where the model

combining the 4 proteins validated by ELISA achieved an AUC of 0.841+/‐0.026, p=2.7x10‐19 (Tables 4 and 5). Discussion These experiments use an aptamer‐based assay to investigate how plasma levels of over 4000 proteins relate to clinical outcome in a large well‐phenotyped UK cohort of subjects with idiopathic, heritable or drug‐induced PAH. A prognostic score based on 6 proteins was developed and validated, which predicts survival independently of NT‐proBNP and 6MWD. The score tracked the development of PAH in relatives at risk of heritable PAH and the response of those relatives and a subject to successful therapeutic intervention using experimental therapies. Table 7: Results from Mendelian randomisation studies on 8 circulating proteins (9 aptamers). Odds 95% Confidence Genetic pQTL Gene UniPROT ratio interval p‐value variant location NTN4 Q9HB63 1.55 1.16 2.08 0.0035 rs17288108 CIS THBS2 P35442 0.83 0.74 0.94 0.0040 rs73043857 CIS ENG P17813 0.78 0.66 0.92 0.0042 rs651007 TRANS GDF15 Q99988 1.09 0.94 1.26 0.24 rs45543339 CIS RNASE1 P07998 1.20 0.85 1.68 0.29 rs17254387 CIS SVEP1 Q4LDE5 1.10 0.92 1.32 0.30 rs61751937 CIS SVEP1 Q4LDE5 1.11 0.91 1.36 0.30 rs61751937 CIS IGFBP7 Q16270 0.98 0.78 1.23 0.87 rs10832169 CIS SPON1 Q9HCB6 1.01 0.85 1.22 0.88 rs1718849 CIS The biomarkers identified in this study are report directly upon the vascular remodelling process and track survival independent of NT‐proBNP and 6MWD. The score was prognostic independent of the combination of functional class, 6MWD, cardiac index and BNP/NT‐proBNP targets, suggesting it could be used in combination with these established factors. Specifically, the protein score added greater granularity to risk stratification by clinical targets based on functional class, 6‐MWD, cardiac index, mean right atrial pressure and BNP/NT‐proBNP, and identified subjects

at risk even if 2 or more clinical targets were met at follow‐up, suggesting it has potential utility in combination with these established factors. The 6 proteins that comprise the score emerged from statistical modelling but have biological plausibility. Two of them have clear functional links to vascular remodelling and fibrosis. Peroxidasin homolog (PXDN) is induced by TGF‐beta in human pulmonary fibroblasts and the secreted protein is incorporated into the extracellular matrix, colocalising with fibronectin and harnessing bromine to stabilise collagen IV scaffolds. It promotes angiogenesis through activation of Akt and FAK (focal adhesion kinase). SVEP1, also known as Polydom, is a ligand for integrin α9β1 and a breast cancer antigen, with genetic links to cardiovascular and specifically coronary diseases. It also has a crucial conserved role in lymphatic development. Two other proteins have links to endothelial function. Neuropilin‐1 (NRP1) is implicated in angiogenesis, cell survival and migration, acting as a coreceptor for vascular endothelial growth factor (VEGF) and semaphorins, and in cardiac regeneration in zebrafish. Recently, NRP1 has been shown to be essential for the signalling of angiopoietin‐like 4 (ANGPTL4). Treatment with a soluble fragment of NRP1 (sNRP1) prevented ANGPTL4 from binding to NRP1, blocking ANGPTL4‐induced activation of RhoA and endothelial permeability in vitro and retinal vascular leakage in vivo. NRP1 is hypoxia‐sensitive and upregulation has been reported in studies of adaptation to high altitude. Thrombospondin‐2 (TSP2) is a secreted matricellular protein and raised levels are found in heart failure, with cardiac fibroblasts being a potential source. However, gene expression in arterial tissue is high relative to other non‐diseased human tissues (Genotype‐Tissue Expression database, V8 Release) and changes in gene expression found in laser micro‐dissected pulmonary vessels from subjects with pulmonary hypertension associated with pulmonary fibrosis. TSP2 inhibits human microvascular endothelial cell proliferation and TSP2 knockout mice show enhanced angiogenesis. Impaired TSP2 activity would appear to be detrimental to vascular and cardiac homeostasis, this being supported by recent Mendelian randomisation analysis using a pQTL for TSP2 as a genetic instrument. Elevated circulating TSP2 would be consistent with a compensatory response in PAH, in an attempt to reduce pulmonary vascular damage. Peroxiredoxin‐4 (PRDX4) is an antioxidant enzyme that regulates the activation of NF‐kappa‐B in the cytosol by a modulation of I‐kappa‐B‐alpha phosphorylation. PRDX4 levels are elevated in idiopathic pulmonary fibrosis and overexpression worsens bleomycin induced IPF in mice. Galectin‐3 (which is elevated in heart failure) inhibits PRDX4 levels, promoting cardiac fibrosis. Finally, renin levels likely relate to the systemic consequences of PAH and the cross‐talk between right heart function and the kidney. Reduced cardiac output affects efferent renal arteriolar blood flow, which stimulates release of renin from juxtaglomerular cells.

Plasma levels of NT‐proBNP and the 6‐protein panel score increased with the development of pulmonary hypertension in the three relatives studied, illustrating the value of serial measurements and a rising level/score within an individual should be of great concern. From the data available on these relatives, NT‐proBNP and the protein panel score track together. Interestingly, serial measurements of the 6‐protein panel score in a subject who received and symptomatically improved on imatinib, a drug hypothesised to act by addressing remodelling directly, show that the 6‐panel score responded, along with an increase in 6MWD, before a fall in NT‐proBNP, suggesting that a change in the 6‐panel score has potential to inform drug response and therapy selection before a change is observed in NT‐proBNP. These experiments also provide a systematic unbiased analysis of the perturbed plasma proteome of a cohort of subjects with clinically defined idiopathic or heritable PAH followed over a median of 4.7 years. Using stringent criteria, the investigation searched for proteins where circulating levels discriminate PAH from health, carry prognostic information, and are controlled genetically; that is, have a pQTL validated in our PAH cohort. Eight proteins satisfied all three conditions. Mendelian randomisation analysis using pQTLs for these 8 proteins implicate 3 as causally related to PAH; netrin‐4, thrombospondin‐2 (TSP2) and endoglin. All three of netrin‐4, TSP2 and endoglin are biologically plausible candidates for a role in pulmonary vascular disease. Netrin‐4 (NET4) is a secreted protein, highly expressed in vascular endothelium and upregulated by laminar shear stress. Functionally, it has been shown to modulate angiogenic activity in a variety of experimental models. Studies in cell culture support a pro‐survival role for netrin‐4 at physiological concentrations. Plasma levels were elevated in the PAH subjects, consistent with increased protein staining in distal pulmonary vessels in lung sections from PAH subjects, and associated with a poor prognosis. Mendelian randomisation analysis supported a causative association between increased levels and PAH. Recent structural biology and kinetic binding studies suggest that netrin‐4 does not bind to the canonical receptors in the netrin family. Rather, the angiogenic effects of netrin‐4 may depend, at least at higher concentrations, on direct binding to extracellular matrix components, such as laminin γ1 chains in the basement membrane or integrin α6β1, the main receptor for vascular laminins on endothelial cells. High‐affinity binding of netrin‐4 to laminin could potentially disrupt pre‐existing laminin networks and impair the integrity of the endothelial basement membrane and vessel wall. TSP2 is discussed above in the context of the 6‐protein panel. The direction of the relationship in our Mendelian randomisation analysis suggests that reduced TSP2 is harmful, which is in keeping with the essential role of TSP2 in maintaining matrix integrity and adaptation to haemodynamic stress. While the Mendelian randomisation analysis may seem at odds with the

relationship of plasma levels to prognosis, an analogy can be drawn with NT‐proBNP; elevated levels of NT‐proBNP are also associated with a poor prognosis but, given the properties of this peptide, this is interpreted as an ameliorating compensatory response rather than seen as pathological. Endoglin (ENG) is a homodimeric transmembrane glycoprotein strongly expressed on vascular endothelial cells. It has a large extracellular domain that is cleaved and circulates as soluble endoglin. Elevated plasma soluble endoglin levels, measured by ELISA, in PAH, together with increased staining for the protein in the small vessels and plexiform lesions in lungs from PAH subjects, has been documented previously. Consistent with these findings, elevated soluble endoglin levels are associated with a poor clinical outcome. This seems at odds with family studies showing loss‐of‐function mutations in ENG, which is a co‐receptor for BMP9 signalling, associated with hereditary haemorrhagic telangiectasia and PAH. Although soluble endoglin binds BMP9, a protein that promotes endothelial survival and quiescence, with high affinity, it does not appear to inhibit BMP9 signalling; the soluble endoglin:BMP9 complex can signal in endothelial cells with the same potency as BMP9. Thus elevated endoglin levels, like elevated NT‐proBNP, likely reflect an attempt to protect the vascular endothelium as opposed to disrupt it. The proteins that comprise the 6‐protein panel/single protein score emerged from robust statistical modelling of the largest plasma proteome study in PAH to date. The 6‐protein composite score was generated as a practical tool for risk stratification to be used in addition to NT‐proBNP and clinical risk factors, and has been validated by ELISA for four of the proteins. To conclude, circulating proteins can be used to predict prognosis in PAH and report on mechanisms distinct from established factors in PAH, such as NT‐proBNP. The risk score developed was robust in an external cohort of incident cases, appears to have potential for utility in screening and treatment monitoring. In addition, Mendelian randomisation analysis suggests that therapeutic interventions that inhibit netrin‐4 activity or augment TSP2 and endoglin activity may be beneficial in PAH.

Claims

CLAIMS 1. A method for diagnosing or determining a prognosis for pulmonary arterial hypertension (PAH), the method comprising: (a) quantifying the amount of two or more biomarkers present in a sample obtained from a subject, wherein the two or more biomarkers are selected from Sushi, Von Willebrand Factor Type A, EGF And Pentraxin Domain‐Containing Protein 1 (SVEP1), peroxidasin (PXDN), renin, neuropilin 1 (NRP1), thrombospondin 2 (TSP2) and peroxiredoxin‐4 (PRDX4); (b) comparing the amount of the two or more biomarkers with the amount of the same two or more biomarkers in a reference standard; and thereby diagnosing or determining a prognosis for PAH.

2. A method for optimising therapy for a subject undergoing treatment for PAH, the method comprising: (a) quantifying the amount of two or more biomarkers present in a sample obtained from a subject, wherein the two or more biomarkers are selected from SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4; (b) comparing the amount of the two or more biomarkers with the amount of the same two or more biomarkers in a reference standard; and (c) (i) changing the therapy if the amount of the two or more biomarkers is increased relative to the reference standard; or (ii) maintaining the therapy if the amount of the two or more biomarkers is the same or lower relative to the reference standard.

3. The method according to claim 1 or 2, wherein the step of comparing the amount of the two or more biomarkers with the amount of the same two or more biomarkers in a reference standard comprises calculating a single protein score for the two or more biomarkers.

4. The method according to claim 3, wherein:

(a) the single protein score is a weighted combination score of the two or more biomarkers; and/or (b) calculating the single protein score comprises calculating z‐scores for the two or more biomarkers relative to the two or more biomarkers in the reference standard, weighting the z‐scores and adding the z‐scores for the two or more biomarkers to arrive at the single protein score.

5. The method according to claim 4, wherein weighting the z‐scores comprises multiplying the z‐scores for the two or more biomarkers by the corresponding coefficient set out in Table 1.

6. The method of claim 5, wherein the method comprises: (a) (i) diagnosing PAH when the single protein score is at least 1; or (ii) not diagnosing PAH when the single protein score is less than 1; (b) (i) determining a prognosis for PAH of the subject being at high risk of PAH progression when the single protein score is at least 0.57; or (ii) determining a prognosis for PAH of the subject being at low risk of PAH progression when the single protein score is less than 0.57; or (c) (i) changing the subject’s therapy when the single protein score is at least 0.57; or (ii) maintaining the subject’s therapy when the single protein score is less than 0.57.

7. The method according to any one of the preceding claims, which comprises quantifying the amount of two, three, four, five or six of the biomarkers.

8. The method according to any one of the preceding claims, wherein the two or more biomarkers comprise or consist of: (a) at least one of SVEP1, PXDN, NRP1 and TSP2; (b) renin and TSP2; (c) renin, NRP1 and TSP2; (d) renin, NRP1, TSP2 and PRDX4; (e) PXDN, renin, NRP1, TSP2 and PRDX4; or (f) SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4.

9. The method according to any one of the preceding claims, wherein the amount of each the two or more biomarkers is quantified using an aptamer‐based assay, ELISA, microarray analysis and/or quantitative real‐time PCR (qPCR).

10. The method according to claim 9, wherein the aptamer‐based assay: (a) uses slow off‐rate modified aptamers; and/or (b) is a multiplex aptamer‐based assay.

11. The method according to any one of the preceding claims, wherein the sample is a biofluid sample, preferably wherein the sample is a blood sample a serum sample or a plasma sample.

12. The method according to any one of the preceding claims, wherein the reference standard is: (i) a non‐PAH reference standard; or (ii) a PAH reference standard.

13. The method according to any one of the preceding claims, which further comprises: (a) quantifying the amount of one or more additional biomarker for PAH, wherein preferably said one or more additional biomarker for PAH is N‐terminal prohormone of brain natriuretic peptide (NT‐proBNP) in the sample; (b) measuring the pulmonary arterial pressure (PAP) of the subject; (c) measuring the cardiac index of the subject; and/or (d) determining the six‐minute walk distance (6MWD) of the subject.

14. The method according to any one of the preceding claims, wherein the amount of two or more biomarkers in the subject is determined at least twice using a separate sample taken each time the amount of the two or more biomarkers is quantified.

15. The method according to any one of the preceding claims, wherein: (a) the sample is taken before treatment initiation; (b) the sample is taken after treatment initiation; or (c) separate samples are taken before and after treatment initiation.

16. The method according to any one of the preceding claims further comprising recording the output of at least one step on a data‐storage medium.

17. A data‐storage medium comprising data obtained by the method of any preceding claim.

18. A computer program product comprising program instructions to cause a processor to perform the method of any one of claims 1 to 15.

19. A method of treating PAH, the method comprising: (a) obtaining the results of a method according to any one of claims 1 to 15; (b) administering a PAH therapy when PAH is diagnosed; and (c) optionally administering a different therapy when PAH is not diagnosed.

20. The method according to claim 19, wherein the PAH therapy is selected from a TGFβ superfamily ligand trap, an endothelin receptor antagonist, particularly a selective ET_A receptor antagonist, a phosphodiesterase type 5 (PDE5) inhibitor, a prostanoid analogue or agonist, particularly a prostaglandin I2 (PGI₂) analogue or agonist, a nitric oxide stimulator, a tyrosine kinase inhibitor, or a combination thereof; wherein optionally the PAH therapy is selected from sotatercept, sildenafil, ambrisentan, iloprost, macitentan,imatinib, epoprostenol, riociguat, selexipag, tadalafil and bosentan or a combination thereof.

21. Use of two or more of SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4 as biomarkers for PAH.

22. A device for carrying out the method according to any one of claims 1 to 15, which comprises reagents for quantification of the two or more biomarkers; wherein optionally the device further comprises an internal control.

23. The device according to claim 22, wherein the reagents for quantification of the two or more biomarkers comprise: (a) one or more aptamer specific for each of the two or more biomarkers; (b) one or more antibody specific for each of the two or more biomarkers; or

(c) one or more antibody for at least one of the two or more biomarkers, and one or more aptamer specific for the two or more biomarkers for which an antibody is not provided.

24. A kit comprising reagents for quantification of two or more biomarkers selected from SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4, wherein preferably the kit comprises reagents for the quantification of SVEP1, PXDN, renin, NRP1, TSP2 and PRDX4.

25. The kit according to claim 24, wherein: (a) the reagents are for quantification of the two or more biomarkers by an aptamer‐based assay or by ELISA; and/or (b) the kit further comprises standards for use in quantifying the two or more biomarkers by an aptamer‐based assay or by ELISA.