CN113493829B - Application of biomarker in pulmonary hypertension diagnosis and treatment - Google Patents

Abstract

The invention discloses application of a biomarker in pulmonary hypertension diagnosis and treatment. Compared with normal control, the invention discovers that CLEC2L and FAM86B1 are obviously up-regulated in pulmonary hypertension and SPNS3 is obviously down-regulated, and the diagnosis of the pulmonary hypertension can be accurately, sensitively and specifically realized by detecting the expression level of CLEC2L, SPNS3 and/or FAM86B 1.

Description

Application of biomarker in pulmonary hypertension diagnosis and treatment

Technical Field

The invention relates to the field of biomedicine, and relates to application of a biomarker in pulmonary hypertension diagnosis and treatment.

Background

Pulmonary Hypertension (PH) is a clinical-pathophysiological syndrome characterized by progressive increases in pulmonary artery pressure and pulmonary small vessel resistance (Hoeper MM, Bogaard HJ, Condliffe R, et al, Definitions and diagnostics of pulmonary hypertension [ J ]. J Am col cardiac 1,2013,62: 42-50), manifested primarily by pulmonary vessel over-constriction, pulmonary small vessel remodeling, leading to an increase in pulmonary vessel resistance to achieve a gradual increase in pulmonary artery pressure, ultimately leading to heart failure and life-threatening. Epidemiological statistics in the United states indicate that the prevalence of PH is at least 10.6/100 million and the annual incidence of PH is at least 2/100 million (McGoon Michael D, Benza Raymond L, Escribeno-Subias Pilar, et a1. Pulmony aromatic hypertension: epidemic and regions [ J ]. Turn Kardiyol der Ars, 2014, null: 67-77). PH patients have a very poor clinical prognosis, with about 1 million people currently threatened by PH worldwide, with high mortality rates due to poor Treatment and rapid progression of disease irreversibility, such as untimely control of diagnosed PH, with median survival expected for only 2.8 years (Hoeper MM, Mc LVV, Dalaan AM, et a1, Treatment of pulmony hypertension [ J ]. Lancet Respir Med,2016,4(4): 323-336).

The occurrence of PH is related to various factors such as genetics, individuals and environment, and is defined as mean pulmonary artery pressure under resting state) 25mmHg, european cardiology/european respiratory society (ESC/ERS issued on 2015 latest edition of guidelines for diagnosis and treatment of pulmonary hypertension), which is divided into five categories of arterial PH, PH related to left heart disease, pulmonary disease and/or PH caused by hypoxia, chronic thromboembolic PH and mechanism deficits and/or PH caused by multiple factors, but current research finds that there is a common pathological basis for the development of different types of PH, including: pulmonary vasoconstriction, Pulmonary vascular remodeling, in situ thrombosis, wherein Pulmonary arteriolar remodeling is a major link (Bujak R, Mateo J, Blanco I, et al, New Biochemical instruments into the mechanics of Pulmonary arthritis Hypertension in Humans [ J ]. PLoSol, 2016, 11: e 0160505.).

Before symptoms of PH appear, a considerable proportion of the pulmonary vascular bed has disappeared, and pulmonary vascular resistance has increased significantly even in patients with PH, which is mildly symptomatic. The diagnosis of early PH is difficult in the existing cardiac catheterization and imaging examination. Therefore, the search for new biomarkers is of great clinical significance.

Disclosure of Invention

In order to make up the defects of the prior art, the invention researches biomarkers related to the occurrence and development of the pulmonary hypertension based on the function of the gene in the occurrence and development of the pulmonary hypertension, thereby providing a new means for diagnosing and treating the pulmonary hypertension.

The invention provides application of a reagent for detecting biomarkers, wherein the biomarkers comprise CLEC2L, SPNS3 and/or FAM86B1, in preparation of products for diagnosing pulmonary hypertension.

Further, the expression level of CLEC2L, FAM86B1 was up-regulated in pulmonary hypertension patients and the expression level of SPNS3 was down-regulated in pulmonary hypertension patients, compared to normal controls.

Further, the reagent comprises:

a probe that specifically recognizes CLEC2L, SPNS3, or FAM86B1 gene;

primers for specifically amplifying CLEC2L, SPNS3 or FAM86B1 genes; or

A binding agent that specifically binds to a protein encoded by CLEC2L, SPNS3, or FAM86B 1.

Further, the sample is selected from the group consisting of tissue, blood.

Further, the sample is selected from blood.

The invention provides a product for diagnosing pulmonary hypertension, which comprises a reagent for detecting the levels of biomarkers CLEC2L, SPNS3 and/or FAM86B 1.

Further, the reagent includes a reagent for detecting the expression level of the biomarkers CLEC2L, SPNS3, and/or FAM86B1 at the mRNA level or the protein level.

Further, the product comprises a reagent for detecting the mRNA level by a polymerase chain reaction, a real-time fluorescent quantitative reverse transcription polymerase chain reaction, a competitive polymerase chain reaction, a nuclease protection assay, an in situ hybridization method, a nucleic acid microarray, an RNA blot or a DNA chip.

Further, the product comprises reagents for detecting protein levels by immunoblotting, enzyme-linked immunosorbent assay, radioimmunoassay, radioimmunodiffusion, immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, complement fixation assay, fluorescence-activated cell sorting, mass analysis, or protein microarray.

The invention provides application of biomarkers comprising CLEC2L, SPNS3 and/or FAM86B1 in constructing a calculation model for predicting pulmonary arterial hypertension.

The present invention provides an apparatus for predicting pulmonary arterial hypertension, the apparatus comprising:

a processor;

an input module for inputting the level of a biomarker in a biological sample, the biomarker selected from CLEC2L, SPNS3, and/or FAM86B 1.

A computer-readable medium containing instructions that, when executed by the processor, perform an algorithm on the input levels of the biomarkers; and

an output module that indicates whether the subject has or is at risk of having pulmonary hypertension.

The invention has the beneficial effects that:

according to the invention, by detecting the expression levels of CLEC2L, SPNS3 and/or FAM86B1, the early diagnosis of pulmonary hypertension can be realized, the detection sensitivity is increased, the detection capability and efficiency are improved, intervention measures are actively taken, the PH progress can be delayed, the disability and death rate is reduced, and even the effect of early cure can be achieved.

Drawings

FIG. 1 shows the CLEC2L gene expression profile;

FIG. 2 shows the SPNS3 gene expression profile;

FIG. 3 shows FAM86B1 gene expression profiles;

FIG. 4 shows ROC plot of CLEC2L gene for diagnosing pulmonary hypertension;

FIG. 5 shows ROC plots of SPNS3 gene for diagnosing pulmonary hypertension;

FIG. 6 shows ROC plots of FAM86B1 gene in diagnosing pulmonary hypertension;

FIG. 7 shows ROC plot of the CLEC2L + SPNS3 gene for diagnosing pulmonary hypertension;

FIG. 8 shows ROC plot of the CLEC2L + FAM86B1 gene for diagnosing pulmonary hypertension;

FIG. 9 shows ROC plots of diagnosis of pulmonary hypertension by the SPNS3+ FAM86B1 gene;

FIG. 10 shows ROC plot of CLEC2L + SPNS3+ FAM86B1 combined diagnosis of pulmonary hypertension.

Detailed Description

The invention will be described in further detail below with the understanding that the terminology is intended to be in the nature of words of description rather than of limitation.

The term "and/or" means and includes any and all possible combinations of one or more of the associated listed items, as well as the lack of combinations when interpreted in the alternative (or).

The term "specimen" or "test specimen" refers to a biological specimen obtained or derived from an individual of interest, the source of which may be a fresh, frozen and/or preserved organ or tissue sample or solid tissue resulting from a biopsy or primer; blood or any blood component. The term "sample" or "test sample" includes a biological sample that has been manipulated in any manner after it has been obtained, such as by reagent treatment, stabilization, or enrichment for certain components (e.g., proteins or polynucleotides), or embedding in a semi-solid or solid matrix for sectioning purposes. In one embodiment of the invention, tissue components are used as the sample.

The term "biomarker" broadly refers to any detectable compound present in or derived from a sample, such as a protein, peptide, proteoglycan, glycoprotein, lipoprotein, carbohydrate, lipid, nucleic acid (e.g., DNA, such as cDNA or amplified DNA, or RNA, such as mRNA), organic or inorganic chemical, natural or synthetic polymer, small molecule (e.g., metabolite), or a discriminating molecule or fragment of any of the above. As used in this paragraph, "derived from" refers to a compound that, when detected, is indicative of a particular molecule present in a sample. For example, detection of a particular cDNA can indicate the presence of a particular RNA transcript in the sample. As another example, detection of or binding to a particular antibody can indicate the presence of a particular antigen (e.g., protein) in a sample. Herein, a discriminating molecule or fragment is a molecule or fragment that, upon detection, indicates the presence or abundance of a compound identified above. Biomarkers can be isolated from a sample, measured directly in a sample, or detected or determined in a sample, for example. The biomarker may be functional, partially functional or non-functional, for example.

In the present invention, the biomarkers include CLEC2L, SPNS3 and/or FAM86B 1. Biomarkers such as CLEC2L (C-type peptide family 2 member L, gene ID: 154790), SPNS3 (sphingolipid transporter 3, gene ID: 201305), FAM86B1 (family with sequence similarity 86 member B1, gene ID: 85002); including genes and their encoded proteins and homologs, mutations, and isoforms. The term encompasses full-length, unprocessed biomarkers, as well as any form of biomarker that results from processing in a cell. The term encompasses naturally occurring variants (e.g., splice variants or allelic variants) of the biomarkers. The gene ID is available at https:// www.ncbi.nlm.nih.gov/gene/.

The term "primer" refers to a short nucleic acid sequence, having a short free 3 hydroxyl nucleic acid sequence, capable of forming a base pair with a complementary template, which serves as an origin for replication of the template strand. The primers can induce DNA synthesis in the presence of reagents for the polymerization reaction (i.e., DNA polymerase or reverse transcriptase) and different 4 nucleoside triphosphates in the appropriate buffer and temperature.

The term "probe" refers to a nucleic acid fragment corresponding to several bases to several hundred bases capable of specifically binding to mRNA, such as RNA or DNA, and the like. Because of the labeling, the presence or absence of a specific mRNA can be confirmed. The probe can be produced in the form of an oligonucleotide probe, a single-stranded DNA probe, a double-stranded DNA probe, an RNA probe, or the like. In the present invention, hybridization is performed using a probe complementary to the CLEC2L, SPNS3, and/or FAM86B1 genes, and the expression level of the above genes can be diagnosed by whether or not hybridization is performed. The selection of an appropriate probe and hybridization conditions may be changed based on techniques known in the art, and there is no particular limitation in the present invention.

The primer or probe of the present invention can be chemically synthesized by using a phosphoramidite solid phase support method or other known methods. Such nucleic acid sequences may be modified by a variety of means well known in the art. Non-limiting examples of such variations include methylation, encapsulation, substitution of more than one homolog of the natural nucleotide, and variations between nucleotides, for example, variations to uncharged linkers (e.g., methyl phosphonates, phosphotriesters, phosphoramidates, carbamates, etc.) or charged linkers (e.g., phosphorothioates, phosphorodithioates, etc.).

In the present invention, suitable conditions for hybridizing a probe to a cDNA molecule can be determined in a series of processes by optimization steps. This step is performed by one of ordinary skill in the art through a series of procedures to establish a protocol for use in a research facility. For example, the conditions such as temperature, component concentration, hybridization and washing time, buffer components and their pH, and ionic strength depend on various factors such as the length of the probe, GC amount, and target nucleotide sequence.

The terms "level of expression" or "expression level" are generally used interchangeably and generally refer to the amount of a polynucleotide or amino acid product or protein in a biological sample. "expression" generally refers to the process by which information encoded by a gene is converted into structures that are present and operational in a cell. Thus, "expression" of a gene as used herein refers to transcription into a polynucleotide, translation into a protein, or even post-translational modification of a protein. Transcribed polynucleotides, translated proteins, or fragments of post-translationally modified proteins are also considered to be expressed, whether they are derived from transcripts produced or degraded by alternative splicing, or from post-translational processing of proteins (e.g., by proteolysis). "expressed genes" include those that are transcribed into a polynucleotide (e.g., mRNA) and then translated into a protein, as well as those that are transcribed into RNA but not translated into a protein (e.g., transfer RNA and ribosomal RNA).

The term "diagnosis" is used herein to refer to the identification or classification of a molecular or pathological state, disease or disorder. For example, "diagnosing" can refer to identifying a risk of developing pulmonary hypertension, either by the involved tissue/organ (e.g., pulmonary hypertension), or by a molecular characteristic (e.g., expression characterized by a particular gene or one or a combination of the proteins encoded by the gene).

"aiding diagnosis" refers to a method of aiding in making a clinical decision as to the presence or nature of a particular type of symptom or condition. For example, a method of aiding diagnosis of pulmonary hypertension may include measuring the expression of certain genes in a biological sample from an individual.

The term "antibody" is used herein in the broadest sense and includes monoclonal antibodies (e.g., full length or intact monoclonal antibodies), polyclonal antibodies, multivalent antibodies, multispecific antibodies (e.g., bispecific antibodies, so long as they exhibit the desired biological activity), and may also include certain antibody fragments (as described in more detail herein). The antibody may be a human, humanized and/or affinity matured antibody.

An "antibody fragment" comprises only a portion of an intact antibody, wherein the portion preferably retains at least one, preferably most or all, of the functions normally associated with the portion when present in an intact antibody. In one embodiment, the antibody fragment comprises the antigen-binding site of an intact antibody, thereby retaining the ability to bind antigen. In another embodiment, an antibody fragment (e.g., an antibody fragment comprising an Fc region) retains at least one of the biological functions normally associated with the Fc region when present in an intact antibody, such as FcRn binding, ADCC function, and complement binding. In one embodiment, the antibody fragment is a monovalent antibody having an in vivo half-life substantially similar to that of an intact antibody. For example, such an antibody fragment may comprise an antigen-binding arm linked to an Fc sequence capable of conferring in vivo stability to the fragment.

The term "monoclonal antibody" as used herein refers to an antibody obtained from a substantially homogeneous population of antibodies, i.e., the individual antibodies comprising the population are identical except for possible naturally occurring mutations that may be present in minor amounts. Monoclonal antibodies are highly specific, being directed against a single antigen. Furthermore, unlike polyclonal antibody preparations which typically include different antibodies directed against different determinants (epitopes), each monoclonal antibody is directed against a single determinant on the antigen.

Monoclonal antibodies herein specifically include "chimeric" antibodies in which a portion of the heavy and/or light chain is identical with or homologous to corresponding sequences in antibodies derived from a particular species or belonging to a particular antibody class or subclass, and the remainder of one or more chains is identical with or homologous to corresponding sequences in antibodies derived from another species or belonging to another antibody class or subclass, as well as fragments of such antibodies, so long as they exhibit the desired biological activity.

The term "diabodies" refers to small antibody fragments having two antigen-binding sites, which fragments comprise a variable heavy domain (VH) linked to a variable light domain (VL) in the same polypeptide chain (VH-VL). By using a linker that is too short to allow pairing between the two domains on the same chain, the domains are forced to pair with complementary domains on the other chain and two antigen binding sites are created.

The detection of the gene expression level described herein can employ assay methods known in the art, including, but not limited to, methods that detect the amount of an RNA transcript of the biomarker or the amount of a polypeptide encoded by the biomarker.

The RNA transcript of the biomarker may be converted to cDNA complementary thereto by methods known in the art, and the amount of the RNA transcript may be obtained by determining the amount of complementary cDNA. The amount of RNA transcript of a biomarker, or cDNA complementary thereto, can be normalized to the amount of total RNA or total cDNA in a sample, or to the amount of RNA transcript of a panel of housekeeping genes, or cDNA complementary thereto.

In this context, RNA transcripts can be detected and quantified by methods such as hybridization, amplification, sequencing, including, but not limited to, methods of hybridizing RNA transcripts to probes or primers, methods of detecting the amount of RNA transcripts or their corresponding cDNA products by various quantitative PCR techniques or sequencing techniques based on the Polymerase Chain Reaction (PCR). The quantitative PCR techniques include, but are not limited to, fluorescent quantitative PCR, real-time PCR, or semi-quantitative PCR techniques. Such sequencing techniques include, but are not limited to, Sanger sequencing, second-generation sequencing, third-generation sequencing, single cell sequencing, and the like. Preferably, the sequencing technique is next generation sequencing, more preferably a targeted RNA-seq technique.

Herein, the amount of polypeptide can be detected by, for example, proteomics or reagents. Preferably, the agent is an antibody, an antibody fragment or an affinity protein. Any suitable protein quantification method may be used in the methods provided herein. In certain embodiments, an antibody-based method is used. Exemplary methods that can be used include, but are not limited to, immunoblotting (western blot), enzyme-linked immunosorbent assay (ELISA), immunohistochemistry, flow cytometry bead arrays, and mass spectrometry. Some types of ELISA are commonly used, including direct ELISA, indirect ELISA, and sandwich ELISA.

Applications of

The invention relates to the use of reagents for determining biomarkers in a sample, including CLEC2L, SPNS3 and/or FAM86B1, for the preparation of a diagnostic product for pulmonary hypertension.

Preferably, the diagnostic product comprises reagents for detecting the expression level of CLEC2L, SPNS3 and/or FAM86B1 in a sample.

As an alternative embodiment, the reagent comprises:

a probe that specifically recognizes CLEC2L, SPNS3, or FAM86B1 gene;

primers for specifically amplifying CLEC2L, SPNS3 or FAM86B1 genes; or

A binding agent that specifically binds to a protein encoded by CLEC2L, SPNS3, or FAM86B 1.

As alternative embodiments, binding agents for proteins include, but are not limited to, peptides, peptide mimetics, aptamers, spiegelmers, dappin, ankyrin repeat proteins, Kunitz-type domains, antibodies, single domain antibodies, and monovalent antibody fragments.

As a preferred embodiment, the binding agent for the protein is an antibody.

As an alternative embodiment, the sample comprises plasma, serum or blood extract, brush, biopsy or surgically excised tissue or fluid sample from the subject.

(diagnostic) product

The invention relates to a product for diagnosing pulmonary arterial hypertension, which comprises a reagent for detecting biomarkers CLEC2L, SPNS3 and/or FAM86B 1.

In one embodiment, the agent is an agent that detects the level of expression of the biomarker.

In one embodiment, the diagnostic product is in the form of an in vitro diagnostic product.

In a specific embodiment, the diagnostic product is a diagnostic kit.

In one embodiment, the reagent is a reagent that detects the amount of RNA, particularly mRNA, transcribed from the biomarker. In yet another embodiment, the reagent is a reagent that detects the amount of cDNA complementary to the mRNA.

In a preferred embodiment, the diagnostic product further comprises a total RNA extraction reagent, a reverse transcription reagent and/or a secondary sequencing reagent.

The total RNA extraction reagent can be a total RNA extraction reagent which is conventional in the field.

The reverse transcription reagent may be a reverse transcription reagent conventional in the art, and preferably includes a dNTP solution and/or an RNA reverse transcriptase.

The second-generation sequencing reagent may be a reagent conventionally used in the art as long as it can satisfy the requirement of second-generation sequencing of the resulting sequence. The second generation sequencing reagents may be commercially available products, examples of which include, but are not limited to, Illumina MIseq. Reagent Kit v3 (150 cycles) (MS-102. sup. 3001), TruSeq. Targeted RNA Index KitA-96 Inds (384 Samples) (RT-402. sup. 1001). Secondary sequencing is a technique conventional in the art, such as targeted RNA-seq technology. Thus, the second generation sequencing reagents may also include reagents that can be tailored for constructing a library Illumina targeting RNA-seq, such as the Targeted RNA Custom Panel Kit (96 Samples) (RT-102-1001).

In a preferred embodiment, the agent is a probe or primer.

In alternative embodiments, the reagent is a reagent that detects the amount of the polypeptide encoded by the biomarker.

In particular embodiments, the agent is an antibody, antibody fragment, or affinity protein.

A "kit" is an article of manufacture (e.g., a package or container) containing probes for specifically detecting the biomarker genes or proteins of the present invention. In certain embodiments, the article of manufacture is marketed, distributed, or sold as a unit for performing the methods of the present invention.

Such kits may comprise carrier means compartmentalized to receive, in close confinement, one or more container means (e.g., vials, tubes, etc.), each container means comprising one of the separate components to be used in the method. For example, one of the container means may comprise a probe that carries or can carry a detectable label. Such probes may be polynucleotides specific for polynucleotides of one or more genes comprising gene expression characteristics. Where the kit utilizes nucleic acid hybridization to detect a target nucleic acid, the kit can also have a container containing one or more nucleic acids for amplifying the target nucleic acid sequence and/or a container containing a reporter means, such as a biotin-binding protein, such as avidin or streptavidin, bound to a reporter molecule, such as an enzymatic, fluorescent, or radioisotope label.

A kit will generally comprise the above-described container and one or more additional containers containing commercially and user-desired materials, including buffers, diluents, filters, needles, syringes, and package inserts containing instructions for use. A label may be present on the container to indicate that the composition is for a particular therapeutic or non-therapeutic application, and may also indicate the direction of in vivo or in vitro use, such as those described above. Other optional components of the kit include one or more buffers (e.g., blocking buffer, wash buffer, substrate buffer, etc.), other reagents (e.g., substrate chemically altered by enzymatic labeling), epitope retrieval solutions, control samples (positive and/or negative controls), control sections, and the like.

Calculation model

The invention provides application of gene markers in constructing a calculation model for predicting pulmonary arterial hypertension, wherein the gene markers comprise CLEC2L, SPNS3 and/or FAM86B 1.

As the skilled artisan will appreciate, the step of associating a marker level with a certain likelihood or risk may be implemented and realized in different ways. Preferably, the measured concentrations of the protein and one or more other markers are mathematically combined and the combined value is correlated with the underlying diagnostic problem. The determination of marker values may be combined by any suitable prior art mathematical method.

The logarithmic function used to correlate marker combinations with disease preferably employs algorithms developed and obtained by applying statistical methods. For example, suitable statistical methods are Discriminant Analysis (DA) (i.e., linear, quadratic, regular DA), Kernel methods (i.e., SVM), nonparametric methods (i.e., k-nearest neighbor classifiers), PLS (partial least squares), tree-based methods (i.e., logistic regression, CART, random forest methods, boosting/bagging methods), generalized linear models (i.e., logistic regression), principal component-based methods (i.e., SIMCA), generalized additive models, fuzzy logic-based methods, neural network-and genetic algorithm-based methods. The skilled person will not have problems in selecting a suitable statistical method to evaluate the marker combinations of the invention and thereby obtain a suitable mathematical algorithm. In one embodiment, the statistical method used to obtain the mathematical algorithm used in assessing pulmonary hypertension is selected from DA (i.e., linear, quadratic, regular discriminant analysis), Kernel method (i.e., SVM), non-parametric method (i.e., k-nearest neighbor classifier), PLS (partial least squares), tree-based methods (i.e., logistic regression, CART, random forest method, boosting method), or generalized linear model (i.e., logarithmic regression).

The area under the receiver operating curve (= AUC) is an indicator of the performance or accuracy of the diagnostic procedure. The accuracy of a diagnostic method is best described by its Receiver Operating Characteristics (ROC). ROC plots are line graphs of all sensitivity/specificity pairs derived from continuously varying decision thresholds across the entire data range observed.

The clinical performance of a laboratory test depends on its diagnostic accuracy, or the ability to correctly classify a subject into a clinically relevant subgroup. Diagnostic accuracy measures the ability to correctly discriminate between two different conditions of the subject under investigation. Such conditions are, for example, health and disease or disease progression versus no disease progression.

In each case, the ROC line graph depicts the overlap between the two distributions by plotting sensitivity versus 1-specificity for the entire range of decision thresholds. On the y-axis is the sensitivity, or true positive score [ defined as (number of true positive test results)/(number of true positives + number of false negative test results) ]. This is also referred to as a positive for the presence of a disease or condition. It is calculated from the affected subgroups only. On the x-axis is the false positive score, or 1-specificity [ defined as (number of false positive results)/(number of true negatives + number of false positive results) ]. It is an indicator of specificity and is calculated entirely from unaffected subgroups. Because the true and false positive scores are calculated completely separately using test results from two different subgroups, the ROC line graph is independent of the prevalence of disease in the sample. Each point on the ROC line graph represents a sensitivity/1-specificity pair corresponding to a particular decision threshold. One test with perfect discrimination (no overlap of the two result distributions) has a ROC line graph that passes through the upper left corner where the true positive score is 1.0, or 100% (perfect sensitivity), and the false positive score is 0 (perfect specificity). A theoretical line graph for an undifferentiated test (the results of the two groups are equally distributed) is a 45 ° diagonal from the lower left to the upper right. Most line graphs fall between these two extremes. (if the ROC line graph falls well below the 45 ° diagonal, this is easily corrected by reversing the criteria for "positive" from "greater to" less than "or vice versa.) qualitatively, the closer the line graph is to the upper left corner, the higher the overall accuracy of the test.

One convenient goal to quantify the diagnostic accuracy of a laboratory test is to express its performance by a single numerical value. The most common global metric is the area under the ROC curve (AUC). Conventionally, this area is always ≧ 0.5 (if not, the decision rule can be reversed to do so). The range of values was between 1.0 (test values that perfectly separated the two groups) and 0.5 (no significant distribution difference between the test values of the two groups). The area depends not only on a particular part of the line graph, such as the point closest to the diagonal or the sensitivity at 90% specificity, but also on the entire line graph. This is a quantitative, descriptive representation of how the ROC plot is close to perfect (area = 1.0).

Device for measuring the position of a moving object

The present invention provides an apparatus for diagnosing/predicting pulmonary hypertension, the apparatus comprising:

a processor;

an input module for inputting the level of a biomarker in a biological sample, the biomarker selected from CLEC2L, SPNS3, and/or FAM86B 1;

a computer-readable medium containing instructions that, when executed by the processor, perform an algorithm on the input levels of the biomarkers; and

an output module that indicates whether the subject has or is at risk of having pulmonary hypertension.

An apparatus as applied herein shall at least comprise the above-mentioned modules. The modules of the device are operatively connected to each other. How the modules are operatively linked will depend on the type of module contained in the device.

The processor may execute a series of machine-readable instructions, which may be embodied in a program or software. The instructions may be stored in a memory location, such as a memory. Instructions may be directed to a processor that may then program or otherwise configure the processor to implement the present disclosure. Examples of operations performed by a processor may include read, decode, execute, and write-back.

The present invention will be described in further detail with reference to the accompanying drawings and examples. The following examples are intended to illustrate the invention only and are not intended to limit the scope of the invention. The experimental procedures, in which specific conditions are not specified in the examples, are generally carried out under conventional conditions or conditions recommended by the manufacturers.

Example 1 detection of biomarkers associated with pulmonary hypertension

1. Sample collection

Blood samples of 7 chronic thromboembolic pulmonary hypertension (CTEPH) patients and 5 healthy population control groups were collected, and basic information including age, sex, BMI and the like of the patients and the healthy control groups were recorded in detail at the time of collecting the samples, wherein the disease groups and the healthy groups had no statistical difference in age, sex, BMI and the like.

Disease groups were included as criteria: CTEPH is diagnosed by right heart catheterization, pulmonary ventilation perfusion scan, or CT pulmonary angiography (CTPA). The CTEPH diagnosis needs to satisfy the following 3 items at the same time: effective anticoagulation treatment is carried out for at least 3 months to eliminate subacute PTE; V/Q imaging scanning shows that at least 1 lung segment perfusion defect, or the specific signs of CTEPH, such as annular stenosis, grid sign, gap and artery occlusion, are found by examination of multi-layer helical CT pulmonary artery imaging (CTPA), MRI or direct pulmonary angiography, and the like; and the pulmonary circulation hemodynamic index measured by the right heart catheter meets the diagnosis standard of pulmonary hypertension [ the average pulmonary artery pressure is more than or equal to 25mm Hg (1 mm Hg =0.133 k Pa), and the pulmonary arteriolar wedge pressure is less than or equal to 15 mm Hg ].

Disease group exclusion criteria: there are circulatory diseases, such as malignant tumor, hypertension, diabetes, coronary heart disease or cerebrovascular disease.

Health group inclusion criteria: including age, gender matched healthy controls and normothermic/urinalysis/biochemical test/carcinoembryonic antigen (CEA)/alpha-fetoprotein (AFP)/blood sedimentation (ESR)/chest X for the CTEPH group.

Healthy group exclusion criteria: excluding the people with the past history of the disease, head trauma and operation history, cardiac operation history or nervous system disease.

2. Experimental methods

2.1 extraction of total RNA from blood

Total RNA in Blood was extracted using PAXgene Blood RNA Kit (produced by BD Co.) and the procedures were performed as described in the specification.

2.2 sample detection

Total RNA concentration, RIN value, 28S/18S and fragment size were measured using an Agilent 2100 Bioanalyzer (Agilent RNA 6000 Nano Kit).

2.3 construction of the library and transcriptome sequencing

1) DNase digestion to remove DNA: digesting DNA fragments existing in a Total RNA sample by using DNase I, purifying and recovering reaction products by using magnetic beads, and finally dissolving the reaction products in DEPC water;

2) removing rRNA: taking a digested Total RNA sample, removing rRNA by using a kit, carrying out Agilent 2100 detection after the rRNA is removed, and verifying the rRNA removal effect;

3) RNA disruption: taking the sample in the previous step, adding a breaking Buffer, and placing the sample in a PCR instrument for thermal breaking to 130-;

4) reverse transcription one-strand synthesis: adding a proper amount of primers into the broken sample, fully and uniformly mixing, reacting for a certain time at a proper temperature of a Thermomixer to open a secondary structure and combine with the primers, adding a one-chain synthesis reaction system Mix prepared in advance, and synthesizing one-chain cDNA on a PCR instrument according to a corresponding procedure;

5) synthesis of reverse transcription duplex: preparing a double-chain synthesis reaction system, reacting on a Thermomixer at a proper temperature for a certain time to synthesize double-chain cDNA, and purifying and recovering reaction products by using magnetic beads. Purifying and recovering the product by using magnetic beads;

6) and (3) repairing the tail end: preparing a terminal repair reaction system, reacting in a Thermomixer at a proper temperature for a certain time, and repairing the cohesive terminal of the cDNA double-chain obtained by reverse transcription under the action of enzyme. Purifying and recovering the end repairing product by using magnetic beads, and finally dissolving a sample in EB Solution;

7) the cDNA ends were added with "A": preparing an A reaction system, reacting in a Thermomixer at a proper temperature for a certain time, and adding A basic groups to the 3' end of a product cDNA with repaired end under the action of enzyme;

8) ligation of cDNA adapter: preparing a joint connection reaction system, reacting in a Thermomixer at a proper temperature for a certain time, connecting a joint with the A base under the action of enzyme, and purifying and recovering a product by using magnetic beads;

9) PCR reaction and product recovery: preparing a PCR reaction system, selecting a proper PCR reaction program, and amplifying the product obtained in the previous step. And (5) carrying out magnetic bead purification and recovery on the PCR product. The recovered product was dissolved in EB solution. Labeling, and preparing the library to finish the preparation;

10) and (3) detecting the quality of the library: the size and concentration of fragments of the library were measured using an Agilent 2100 Bioanalyzer (Agilent DNA 1000 Reagents);

11) cyclization of PCR products: after the PCR product is denatured into single chains, preparing a cyclization reaction system, fully mixing the single chains and the cyclization reaction system uniformly, reacting at a proper temperature for a certain time to obtain single-chain cyclic products, and digesting non-cyclized linear DNA molecules to obtain a final library;

12) and (3) machine sequencing: the single-stranded circular DNA molecule replicates through rolling circles to form a DNA Nanosphere (DNB) containing more than 200 copies. The obtained DNBs are added into the mesh pores on the chip by adopting a high-density DNA nano chip technology. The sequencing read length of 50bp/100bp is obtained by a sequencing-by-synthesis method.

2.4 sequencing data quality control

Filtering the raw sequencing data to obtain high-quality sequencing data (clean data), comprising the following steps: removing the adapter sequence in reads; removing bases containing non-AGCT at the 5' end before shearing; pruning ends of reads with lower sequencing quality (sequencing quality value less than Q20); removing reads with the N content of 10%; discarding small fragments with length less than 25bp after removing the adapter and mass pruning.

2.5 alignment with reference genome

The price sequencing data was aligned to the reference genome using hisat2 analytical software. The reference genome was from the Ensembl database, genome version GRCh38, with gene annotation information Ensemble 92.

2.6 Gene expression level analysis

The expression level of the gene was calculated by aligning the number of sequences (clean reads) to the reference genomic region. The FPKM value of each gene/transcript in the sample was calculated using Stringtie according to the alignment of Hisat2 software, and this value was used as the expression level of the gene/transcript in the sample.

2.7 differential mRNA expression analysis

The expression difference of mRNA of the control group and the disease group is compared by using DESeq2, and the difference analysis steps are as follows: firstly, standardizing (normalization) the original read count, mainly correcting the sequencing depth; carrying out hypothesis test probability (P-value) calculation through a statistical model, carrying out multiple hypothesis test correction (BH) to obtain a padj value (false discovery rate), wherein the screening standard of the differential expression genes is as follows: pvalue<0.05 and | log₂foldchange|>1。

3. Results and analysis

3.1 data volume statistics is carried out on the sequence after data quality control, and the result is shown in Table 1.

TABLE 1 statistical Table of sequencing data

(1) Sample ID: sample information; (2) total _ reads: counting the number of the original sequence data; (3) total _ bases: multiplying the number of Raw reads by the length, and converting into a unit of G; (4) Q20, Q30: respectively calculating the percentage of the base with the Phred value more than 20 and 30 to the total base; (5) GC content: the sum of the numbers of bases G and C was calculated as a percentage of the total number of bases.

3.2 differential expression Gene analysis

The disease group and healthy control were subjected to high throughput sequencing analysis on all samples, and there were 437 genes with significant differences compared to healthy controls, 233 genes with up-regulation in expression and 204 genes with down-regulation in expression.

The expression of FAM86B1 and CLEC2L in the pulmonary hypertension patients is remarkably up-regulated, and the expression of SPNS3 in the pulmonary hypertension patients is remarkably down-regulated, wherein the specific expression condition is shown in Table 2.

TABLE 2 differential expression of genes

Example 2 validation and diagnostic Performance testing of differential genes

1. Data and preprocessing

Downloading gene expression data of a data set GSE33463 of pulmonary arterial hypertension and pulmonary arterial hypertension comparison from a GEO database, annotating the gene expression data by using an annotation file, taking an average value of a plurality of probes corresponding to the same gene as an expression quantity of the gene expression data, and then obtaining a gene expression matrix file.

2. Differential expression analysis

Differential gene expression analysis was performed using the "limma" package in the R software.

The analysis results show that the expression of FAM86B1 and CLEC2L in the pulmonary hypertension patients is remarkably up-regulated, and the expression of SPNS3 in the pulmonary hypertension patients is remarkably down-regulated, and the expression is shown in figures 1-3, wherein: p < 0.05; **: p < 0.01; ***: p < 0.001.

3. Diagnostic efficacy analysis

The AUC value, sensitivity and specificity of the differentially expressed gene as a detection variable are analyzed by using an R package 'pROC' ROC curve, and the diagnostic efficacy is judged. When the diagnostic efficacy of each gene was judged, the expression level of the gene was directly used for analysis. Calling a pROC package, reading in an expression quantity matrix constructed by a target gene, and running a command for drawing an ROC curve, wherein the command simultaneously relates to a command for adding AUC, thres (threshold value) and smooth (fitting curve). When the diagnosis efficiency of gene combination is judged, firstly, glmnet is used for conducting Logistic regression on genes, the established Logistic regression model is utilized, the influence of a certain prediction variable on the result probability at each level is observed by using a prediction function, the prediction probability is calculated, and an ROC curve of the prediction result is drawn.

As shown in table 3 and fig. 4-10, it can be seen that CLEC2L, SPNS3, FAM86B1 and their combinations have high accuracy in diagnosing pulmonary hypertension, especially their combinations, which have high accuracy, sensitivity and specificity.

TABLE 3 differential expression Gene diagnostic potency analysis

The preferred embodiments of the present application have been described in detail with reference to the accompanying drawings, however, the present application is not limited to the details of the above embodiments, and various simple modifications can be made to the technical solution of the present application within the technical idea of the present application, and these simple modifications are all within the protection scope of the present application.

It should be noted that, in the foregoing embodiments, various features described in the above embodiments may be combined in any suitable manner, and in order to avoid unnecessary repetition, various possible combinations are not described in the present application.

In addition, any combination of the various embodiments of the present application is also possible, and the same should be considered as disclosed in the present application as long as it does not depart from the idea of the present application.

Claims (8)

1. The application of a reagent for detecting the biomarkers in a sample in preparing a product for diagnosing pulmonary hypertension is characterized in that the biomarkers are the combination of CLEC2L, SPNS3 and FAM86B 1.

2. The use according to claim 1, wherein the expression level of CLEC2L, FAM86B1 is up-regulated in pulmonary arterial hypertension patients and the expression level of SPNS3 is down-regulated in pulmonary arterial hypertension patients, compared to normal controls.

3. The use according to claim 1, wherein the agent comprises:

probes specifically recognizing CLEC2L, SPNS3 and FAM86B1 genes; primers for specifically amplifying CLEC2L, SPNS3 and FAM86B1 genes; or a binding agent that specifically binds to a protein encoded by CLEC2L, SPNS3, and FAM86B 1.

4. The use according to any one of claims 1 to 3, wherein the sample is selected from blood.

5. The use according to claim 1, wherein the reagents comprise reagents for detecting the expression levels of the biomarkers CLEC2L, SPNS3 and FAM86B1 at the mRNA level or at the protein level.

6. The use of claim 5, wherein the product comprises reagents for detecting mRNA levels by polymerase chain reaction, real-time fluorescent quantitation reverse transcriptase polymerase chain reaction, competitive polymerase chain reaction, nuclease protection assay, in situ hybridization, nucleic acid microarray, northern blot, or DNA chip methods.

7. The use of claim 5, wherein the product comprises reagents for detecting protein levels by immunoblotting, enzyme-linked immunosorbent assay, radioimmunoassay, radioimmunodiffusion, immunoelectrophoresis, tissue immunostaining, immunoprecipitation assay, complement fixation assay, fluorescence activated cell sorting, mass analysis, or protein microarray.

8. Use of a biomarker for constructing a computational model for predicting pulmonary arterial hypertension, wherein the biomarker is a combination of CLEC2L, SPNS3 and FAM86B 1.

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