WO2020189821A1 - Blood marker for diagnosing major blindness-causing eye diseases, and diagnostic method using same - Google Patents

Abstract

The present invention relates to a blood marker for diagnosing major blindness-causing eye diseases, and a diagnostic method using same, and, more specifically, to: a marker for diagnosing at least one blindness-causing eye disease selected from a group consisting of age-related macular degeneration (AMD), diabetic retinopathy, cataract, and glaucoma; a composition and a kit for diagnosing blindness-causing eye diseases by using same; and a method for diagnosing blindness-causing eye diseases. A marker for diagnosing blindness-causing eye diseases, a diagnostic composition, a diagnostic kit, or a method for providing information required for diagnosis, of the present invention, are novel immunological diagnostic tools using the plasma of patients, have excellent sensitivity and enable convenient analysis of plasma without using a biopsy, and have been confirmed to show a high diagnostic ability when protein quantitative values of the diagnostic markers and basic clinical information are combined and analyzed, thereby being effectively usable for the diagnosis of blindness-causing eye diseases.

Description

Blood markers for diagnosis of major eye diseases causing blindness and diagnostic methods using the same

The present invention relates to a blood marker for diagnosing major eye diseases causing blindness and a diagnostic method using the same, and more particularly, to age related macular degeneration (AMD), diabetic retinopathy, cataract, and It relates to a marker for diagnosing one or more blindness-causing eye diseases selected from the group consisting of glaucoma, and a composition, kit, and a method for diagnosing blindness-causing eye diseases using the same.

Vision is the most important sense in our body. As chronic diseases such as obesity, diabetes, and hypertension increase with the recent aging, the number of patients with eye diseases that can cause blindness, such as macular degeneration, diabetic retinopathy, glaucoma, and cataract, is increasing. In particular, the elderly with visual impairments are at increased risk of death due to traffic accidents or falls, and may experience emotional problems as it is difficult to live independently.

Among the eye diseases that cause blindness, age-related macular degeneration (AMD) is a representative eye disease caused by various changes in the macular, the central part of the retina, which occurs mainly in adults over 50 years of age. It is the leading cause of blindness in adults and the incidence rate increases with age. Looking at the prevalence of age-related macular degeneration in Korea based on the National Health and Nutrition Survey, 11.7% of the population aged 60 to 69 and 18% of the population aged 70 or older in Korea are affected by age-related macular degeneration. The macula refers to the central part of the nervous tissue called the retina, and it is responsible for central vision because photoreceptor cells that respond to light stimuli are concentrated. Age-related macular degeneration is a disease that causes visual impairment due to loss of photoreceptor cells in the macular region with age. AMD is a degenerative disease affecting the retina, retinal pigment epithelium (RPE), Bruch's membrane, and choroid.

AMD can be divided into a dry or non-exudative (dry) form and a wet or exudative (exudative) form. The non-exudative form refers to a lesion in the retina, such as drusen or atrophy of the retinal pigment epithelium. It usually does not cause severe vision loss, but it can develop into a wet form. The exudative form is when choroidal neovascularization grows under the retina. These new blood vessels cause exudate and bleeding in the macula, damaging the photoreceptors, thereby lowering central vision, and most of them lead to legal blindness of 0.1 or less if not treated. The exudative form of macular degeneration is very rapid, and vision often deteriorates rapidly within a few weeks. Early detection of age-related macular degeneration is very important because, in general, once vision impairment begins, previous vision cannot be restored in many cases. Early detection is possible through regular ophthalmological examinations by an ophthalmologist.If age-related macular degeneration is suspected by ophthalmic examination including fundus examination, detailed ophthalmic examinations such as fluorescein angiography and optical coherence tomography should be performed to confirm the diagnosis. I can.

Diabetic retinopathy (DR or DMR) is a typical complication of diabetes that occurs when microvessels in the retina are damaged.According to the Health Insurance Review and Assessment Service, the number of diabetic patients increased from about 2 million in 2012 to about 2.45 million in 2016. Compared to an increase of about 21%, the number of diabetic retinopathy patients increased from about 260,000 in 2012 to 336,000 in 2016, which increased to 38%, which is a larger increase than diabetes.

As blood sugar rises due to diabetes, the microcirculation of retinal blood vessels is disturbed due to continuous high blood sugar, and the blood vessels supplying nutrients to the retina in the second half of the eye are narrowed or blocked, causing waste products to accumulate and bleeding. Diabetic retinopathy occurs because abnormally new blood vessels are formed in this area, causing bleeding without normal blood vessel function.

Diabetic retinopathy is classified into non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR) according to its severity. In addition, NPDR is classified into mild, moderative and severe NPDR depending on the degree. Nonproliferative diabetic retinopathy shows retinal bleeding, microvascular perfusion, and cotton patches, but maintains good vision until late. In proliferative diabetic retinopathy, new blood vessels are formed in the retina, and if these blood vessels rupture, it causes severe bleeding in the vitreous cavity. It is absorbed over time, but becomes a fibrous tissue, which in turn causes tractional retinal detachment and rebleeding. Leads to blindness.

Diabetic retinopathy is difficult to diagnose early because there are few initial symptoms, and when symptoms (vision loss, loss of focus, glare) are in progress, the disease has already progressed, and despite treatment (laser, vitreous surgery), it leads to blindness. There are many patients. However, the need for early detection and suppression of diabetic retinopathy and early treatment for high-risk groups is emerging, since it is possible to maintain visual acuity if appropriate treatment is received at the beginning of the onset and blood sugar management is thorough.

Cataract is a disease in which a structure called a transparent lens becomes cloudy in the eye, and the light cannot pass properly, and the overall vision becomes hazy as if it was fogged. The main cause is aging, and cataracts develop as the lens becomes less transparent with age. Patients with early or intermediate cataracts may take medication or use eye drops to slow the progression. If the cataract has progressed a lot, surgery is performed to remove the lens and insert an artificial lens.

Glaucoma is a disease that occurs when the optic nerve is depressed due to increased pressure in the eye or the blood supply is impaired and damage to the optic nerve progresses over time. 5.1% of adults over the age of 40 in Korea suffer from glaucoma, and even if the intraocular pressure is slightly high, they do not feel any abnormalities, but the optic nerve continues to deteriorate and the field of view becomes narrow. Once damaged, the optic nerve is difficult to recover, so it is very important to detect and treat glaucoma early.

However, biomarkers that determine the occurrence or progression of blindness-causing eye diseases such as age-related macular degeneration, diabetic retinopathy, cataracts or glaucoma are very limited, and continuous research is required.

Accordingly, the present inventors have tried to improve the early diagnosis ability of blindness-causing eye diseases such as age-related macular degeneration, diabetic retinopathy, cataracts or glaucoma, etc., by discovering blood protein markers with high sensitivity and specificity, and using them in combination. ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2), LGALS3BP (galectin-3-binding protein), MBL2 ( mannose-binding protein C), pancreatic triacylglycerol lipase (PNLIP), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14), and ZG16B (Zymogen granule protein 16 homolog B). It was confirmed that the markers of more than species have excellent diagnostic efficiency for blindness-causing eye diseases such as age-related macular degeneration, diabetic retinopathy, cataracts, or glaucoma, and the present invention was completed.

It is an object of the present invention to provide a composition for diagnosing blindness-causing eye diseases.

Another object of the present invention is to provide a diagnostic kit for blindness-induced eye disease using the marker for diagnosing blindness-induced eye disease.

Another object of the present invention is to provide a method of providing information necessary for diagnosing blindness-causing eye diseases using the marker for diagnosing blindness-induced eye disease.

Another object of the present invention is to provide a method for screening a substance for treating blindness-causing eye diseases.

To achieve the above object,

The present invention is ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2), LGALS3BP (galectin-3-binding protein) , MBL2 (mannose-binding protein C), PNLIP (pancreatic triacylglycerol lipase), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14) and ZG16B (Zymogen granule protein 16 homolog B) It provides a marker for diagnosing at least one selected type of blindness-causing eye disease.

In a preferred embodiment of the present invention, the blindness-causing eye disease may be selected from the group consisting of age-related macular degeneration, diabetic retinopathy, cataracts, and glaucoma.

In addition, the present invention is ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2), LGALS3BP (galectin-3-binding) protein), MBL2 (mannose-binding protein C), PNLIP (pancreatic triacylglycerol lipase), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14) and ZG16B (Zymogen granule protein 16 homolog B). It provides a composition for diagnosing blindness-causing eye disease, comprising a substance for measuring the protein level or mRNA level of at least one marker for diagnosis of blindness-causing eye disease selected from the group

In a preferred embodiment of the present invention, the blindness-causing eye disease may be selected from the group consisting of age-related macular degeneration, diabetic retinopathy, cataracts, and glaucoma.

In another preferred embodiment of the present invention, the agent for measuring the mRNA level of the complex marker may be a primer pair, a probe, or an antisense nucleotide that specifically binds to the gene of the marker.

In another preferred embodiment of the present invention, the agent for measuring the protein level of the complex marker is an antibody, interacting protein, ligand, nanoparticles or aptamer that specifically binds to the protein or peptide fragment. (aptamer) may be included.

In addition, the present invention provides a kit for diagnosing blindness-causing eye diseases including the composition for diagnosing blindness-causing eye diseases.

In a preferred embodiment of the present invention, the kit is a reverse transcription polymerase chain reaction (RT-PCR) kit, a DNA chip kit, an ELISA (Enzymelinked immunosorbent assay) kit, a protein chip kit, a rapid kit, or a MRM (Multiple reaction monitoring) kit.

In addition, the present invention (a) ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2) from a biological sample of a patient , LGALS3BP (galectin-3-binding protein), MBL2 (mannose-binding protein C), PNLIP (pancreatic triacylglycerol lipase), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14) and ZG16B (Zymogen granule protein 16 homolog B) measuring the mRNA or protein level of at least one marker for diagnosis of blindness-causing eye disease selected from the group consisting of; And

(b) comparing the mRNA or protein expression level with a control sample; provides a method of providing information for diagnosing blindness-causing eye disease.

In a preferred embodiment of the present invention, the blindness-causing eye disease may be selected from the group consisting of age-related macular degeneration, diabetic retinopathy, cataracts, and glaucoma.

In another preferred embodiment of the present invention, the method of providing information for diagnosing blindness-causing eye diseases is the age of the patient, hypertension, hyperlipidemia, smoking, diabetes, insulin treatment, BMI (body mass index). m Hb1AC test results and at least one clinical information selected from the group consisting of cardiovascular disease can be additionally included and compared with the control group.

In another preferred embodiment of the present invention, the mRNA expression level is measured using reverse transcriptase polymerase reaction, competitive reverse transcriptase polymerase reaction, real-time reverse transcriptase polymerase reaction, RNase protection assay, Northern blotting or DNA chip. You can do it.

In another preferred embodiment of the present invention, the measurement of the protein expression level is performed by using an antibody, interacting protein, ligand, nanoparticles, or aptamer that specifically binds to a protein or peptide fragment. Can be done.

In another preferred embodiment of the present invention, the protein expression level measurement is protein chip analysis, immunoassay, ligand binding assay, MALDI-TOF (Matrix Desorption/Ionization Time of Flight Mass Spectrometry) analysis, SELDITOF (Sulface Enhanced). Laser Desorption/Ionization Time of Flight Mass Spectrometry) analysis, radioimmunoassay, radioactive immunity diffusion method, octeroni immunity diffusion method, rocket immunoelectrophoresis, tissue immunostaining, complement fixation analysis method, 2D electrophoresis analysis, liquid chromatography- Liquid chromatography-Mass Spectrometry (LC-MS), liquid chromatography-Mass Spectrometry/ Mass Spectrometry (LCMS/MS), Western blot, enzyme linked immunosorbent assay (ELISA), multiple reaction monitoring (MRM), Parallel reaction monitoring (PRM), sequential windowed data independent acquisition of the total high-resolution (SWATH), selected reaction monitoring (SRM), or immune multiple reaction monitoring (iMRM) It can be done using.

In another preferred embodiment of the present invention, the method of providing information for diagnosing blindness-causing eye disease further comprises determining that the gene expression level or protein expression level of the marker is increased compared to the control group as a blindness-causing eye disease. Can include.

In another preferred embodiment of the present invention, step (b) may be performed by a statistical analysis method.

In another preferred embodiment of the present invention, the statistical analysis method may include a linear or nonlinear regression analysis method, a linear or nonlinear classification analysis method, a logistic regression method, and an Analysis of Variance; ANOVA), neural network analysis method, genetic analysis method, support vector machine analysis method, hierarchical analysis or clustering analysis method, hierarchical algorithm using decision tree or kernel principal component analysis method, Markov Blanket analysis method , Recursive feature elimination or entropy-basic regression feature elimination analysis method, forward floating search or rear floating search analysis method, and a combination thereof. .

Further, the present invention is (a) ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2), LGALS3BP (galectin- 3-binding protein), MBL2 (mannose-binding protein C), PNLIP (pancreatic triacylglycerol lipase), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14) and ZG16B (Zymogen granule protein 16 homolog B) ) Treating a candidate therapeutic agent in a cell sample in which the mRNA or protein expression level for one or more markers selected from the group consisting of increased compared to the control group;

It provides a method for screening a substance for treating blindness-causing eye diseases, comprising: (b) checking whether the mRNA or protein expression level of the marker is decreased after treatment with the candidate substance.

In a preferred embodiment of the present invention, the blindness-causing eye disease may be selected from the group consisting of age-related macular degeneration, diabetic retinopathy, cataracts, and glaucoma.

The method for diagnosing blindness-causing eye disease of the present invention, a diagnostic composition, a diagnostic kit, or a method for providing information necessary for diagnosis is a new immunological diagnostic tool using plasma of a patient, and has excellent sensitivity and plasma without using a biopsy. In addition to being able to easily analyze the target, it was confirmed that high diagnostic ability was shown by combining the quantitative value of the protein and basic clinical information of the diagnostic marker, and thus it can be usefully used for diagnosis of blindness-causing eye diseases.

FIG. 1 is a result of statistically processing 11 protein quantitative values and clinical information measured using the LC-MRM method in plasma of a normal person and plasma of a macular degeneration patient using a logistic regression model (Non AMD: non-macular degeneration Patient, AMD: macular degeneration).

2 is a result of statistically processing five protein quantitative values and clinical information measured using the LC-MRM method in the plasma of a normal person and plasma of a diabetic retinopathy patient using a logistic regression model (Non DMR: non-diabetic Retinopathy, DMR: diabetic retinopathy).

As a result of trying to improve the early diagnosis ability of blindness-causing eye diseases such as age-related macular degeneration, diabetic retinopathy, cataracts, or glaucoma, the present inventors have discovered and used in combination with high sensitivity and specific blood protein markers, ADAMTSL2 ( ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2), LGALS3BP (galectin-3-binding protein), MBL2 (mannose- binding protein C), PNLIP (pancreatic triacylglycerol lipase), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14), and ZG16B (Zymogen granule protein 16 homolog B). It was confirmed that the marker is excellent in the diagnostic efficiency of blindness-causing eye diseases such as age-related macular degeneration, diabetic retinopathy, cataracts or glaucoma, and the present invention was completed.

Hereinafter, the present invention will be described in detail.

In a consistent aspect, the present invention is ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2), LGALS3BP (galectin-3). -binding protein), MBL2 (mannose-binding protein C), PNLIP (pancreatic triacylglycerol lipase), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14) and ZG16B (Zymogen granule protein 16 homolog B) It relates to a marker for diagnosis of one or more blindness-causing eye diseases selected from the group consisting of.

The term "diagnosis" as used in the present invention means identifying the presence or characteristics of a pathological condition. For the purposes of the present invention, the diagnosis is to determine whether the onset of age-related macular degeneration or diabetic retinopathy.

The term "diagnostic marker" used in the present invention refers to a polypeptide showing a significant increase or decrease in gene expression level or protein expression level in an individual with blindness-causing eye disease compared to a normal control group (individuals other than blindness-causing eye disease) or It includes organic biomolecules such as nucleic acids (eg, mRNA), lipids, glycolipids, glycoproteins, sugars (monosaccharides, disaccharides, oligosaccharides, etc.).

In the present invention, the blindness-causing eye disease may be characterized in that it is selected from the group consisting of age-related macular degeneration, diabetic retinopathy, cataracts, and glaucoma.

According to the degree of progression, macular degeneration is classified into early AMD and late AMD. Since early macular degeneration does not develop blood vessels, and late macular degeneration is different in its mechanisms, such as blood vessel development, even a marker known as a late macular degeneration diagnostic marker cannot necessarily be used as an early macular degeneration diagnostic marker. The markers of the present invention can specifically diagnose both early and late macular degeneration.

Diabetic retinopathy is classified into early nonproliferative diabetic retinopathy (NPDR) and late proliferative diabetic retinopathy (PDR) according to the degree of progression. Nonproliferative diabetic retinopathy is characterized by no blood vessel development, and proliferative diabetic retinopathy differs in its mechanism, such as blood vessel development, and nonproliferative diabetic retinopathy does not necessarily progress to proliferative diabetic retinopathy. Then, even a marker known as a diagnostic marker for proliferative diabetic retinopathy cannot necessarily be used as a diagnostic marker for non-proliferative diabetic retinopathy. The marker of the present invention can specifically diagnose both non-proliferative diabetic retinopathy and proliferative diabetic retinopathy, and in particular, can diagnose an early stage of non-proliferative diabetic retinopathy.

Among the markers for diagnosis of blindness-causing eye diseases, ADAMTSL2 (ADAMTS-like protein 2) is a member of a disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS)-like protein subfamily, and is a glycoprotein that binds the cell surface and the extracellular matrix. ADAMTSL2 interacts with LTBP1 (latent transforming growth factor beta binding protein 1), and LTBP1 protein is involved in the storage of TGF-β1, an important growth factor that regulates cell growth and division, so ADAMTSL2 has the possibility of using TGF-β1. Adjust. In the marker of the present invention, ADAMTSL2 may preferably include the amino acid sequence of SEQ ID NO: 1, but the amino acid sequence of SEQ ID NO: 1 and 90% or more, 93% or more, 95% or more, 96% or more, 97% or more, 98% It may include a sequence that is more than or equal to 99% or more.

Cp (Ceruloplasmin) is the main protein that carries copper in the blood and plays an important role in iron metabolism. More than 95% of copper is present in the plasma of healthy people in the form of ceruloplasmin. In the marker of the present invention, Cp may preferably include the amino acid sequence of SEQ ID NO: 2, but 90% or more, 93% or more, 95% or more, 96% or more, 97% or more, 98% of the amino acid sequence of SEQ ID NO: 2 It may include a sequence that is more than or equal to 99% or more.

DDI2 (Protein DDI1 homolog2) is an internal peptide cleavage enzyme that activates nuclear respiratory factor 1 (Nrf1), which is involved in regulating cell growth and DNA replication, and compensates for protein degradation caused by proteasome abnormalities. In the marker of the present invention, DDI2 may preferably include the amino acid sequence of SEQ ID NO: 3, but 90% or more, 93% or more, 95% or more, 96% or more, 97% or more, 98% of the amino acid sequence of SEQ ID NO: 3 It may include a sequence that is more than or equal to 99% or more.

FCN2 (Ficolin 2) is a type of oligolectin and is composed of a short N-terminal partial-collagen-like domain and a fibrinogen-like domain. It is mainly expressed in the liver and is known to play an important role in the lectin pathway of the complement system by binding to N-acetylglucosamin in the bacterial cell wall and acting as an opsonin like a mannose binding protein. In the marker of the present invention, FCN2 may preferably include the amino acid sequence of SEQ ID NO: 4, but 90% or more, 93% or more, 95% or more, 96% or more, 97% or more, 98% of the amino acid sequence of SEQ ID NO: 4 It may include a sequence that is more than or equal to 99% or more.

IGFBP2 (insulin like growth factor binding protein 2) binds to insulin like growth factor (IGF) and regulates various processes in cells, thereby regulating angiogenesis. It is also known to promote the growth of cancer cells in various cancers (such as prostate and breast cancer). In the marker of the present invention, IGFBP2 may preferably include the amino acid sequence of SEQ ID NO: 5, but 90% or more, 93% or more, 95% or more, 96% or more, 97% or more, 98% of the amino acid sequence of SEQ ID NO: 5 It may include a sequence that is more than or equal to 99% or more.

LGALS3BP (galectin-3-binding protein) specifically binds to Mac-2 (human macrophage-associated lectin) and galactin 1 (galectin 1). LGALS3BP is known to be elevated in the serum of cancer patients and HIV-infected patients. It is involved in the immune response associated with the toxicity of natural killer (NK) cells and lymphokine-activated killer (LAK) cells. In the marker of the present invention, LGALS3BP may preferably include the amino acid sequence of SEQ ID NO: 6, but the amino acid sequence of SEQ ID NO: 6 and 90% or more, 93% or more, 95% or more, 96% or more, 97% or more, 98% It may include a sequence that is more than or equal to 99% or more.

Mannose-binding protein C (MBL2) is also referred to as mannose-binding lectin (MBL) or mannan-binding protein (MBP). MBL2 has an oligomer structure (400-700 kDa) and is composed of subunits containing three identical peptide chains consisting of approximately 30 kDa. It is produced by the liver in response to infection and is part of a number of other factors called acute stage proteins. MBL2 in the marker of the present invention may preferably include the amino acid sequence of SEQ ID NO: 17, but 90% or more, 93% or more, 95% or more, 96% or more, 97% or more, 98% of the amino acid sequence of SEQ ID NO: 7 It may include a sequence that is more than or equal to 99% or more.

PNLIP (pancreatic triacylglycerol lipase) is a group of lipolytic enzymes that hydrolyze the ester bond of triglycerides, is an enzyme secreted from the pancreas, and is known to be capable of diagnosing acute pancreatitis by measuring PNLIP serum concentration. PNLIP in the marker of the present invention may preferably include the amino acid sequence of SEQ ID NO: 8, but 90% or more, 93% or more, 95% or more, 96% or more, 97% or more, 98% of the amino acid sequence of SEQ ID NO: 8 It may include a sequence that is more than or equal to 99% or more.

SELE (E-selectin) is known as CD62E (CD62 antigen-like family member E), (endothelial-leukocyte adhesion molecule 1) or LECAM2 (leukocyte-endothelial cell adhesion molecule 2), and is used in interleukin 1β tumor necrosis factor, lipopolysaccharide. It is a cell adhesion molecule that is transiently expressed and induced in the vascular endothelial cells activated by 4-12 hours as the peak. SELE is strongly expressed in vascular endothelial cells in inflammatory tissues and promotes invasion of these cells into the inflammatory site by mediating the phenomenon that neutrophils and monocytes roll over vascular endothelial cells. It is known to be involved in adhesion of cancer cells to vascular endothelial cells. SELE in the marker of the present invention may preferably include the amino acid sequence of SEQ ID NO: 9, but 90% or more, 93% or more, 95% or more, 96% or more, 97% or more, 98% of the amino acid sequence of SEQ ID NO: 9 It may include a sequence that is more than or equal to 99% or more.

SIGLEC14 (Sialic acid-binding Ig-like lectin 14) is one of the subfamily of SIGLEC (Sialic acid-binding immunoglobulin-type lectins), and SIGLEC is a cell surface protein that binds to sialic acid and is mainly expressed on the surface of immune cells. The protein interaction between SIGLEC and sialic acid acts as a switch to turn on and off the immune system, and cancer cells are also known to acquire resistance to the immune response by using the SIGLEC-sialic acid reaction. SIGLEC14 in the marker of the present invention may preferably include the amino acid sequence of SEQ ID NO: 10, but 90% or more, 93% or more, 95% or more, 96% or more, 97% or more, 98% of the amino acid sequence of SEQ ID NO: 10 It may include a sequence that is more than or equal to 99% or more.

ZG16B (Zymogen granule protein 16 homolog B) is known as a pancreatic adenocarcinoma upregulated factor (PAUF) and is known to bind to carbohydrates and activate internal epithelial cells, angiogenesis, and permeability. In the marker of the present invention, ZG16B may preferably include the amino acid sequence of SEQ ID NO: 11, but 90% or more, 93% or more, 95% or more, 96% or more, 97% or more, 98% of the amino acid sequence of SEQ ID NO: 11 It may include a sequence that is more than or equal to 99% or more.

However, there is no known prior art that discloses that the markers can be used to diagnose blindness-causing eye diseases such as age-related macular degeneration, diabetic retinopathy, cataract or glaucoma.

In another aspect, the present invention is ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2), LGALS3BP (galectin-3). -binding protein), MBL2 (mannose-binding protein C), PNLIP (pancreatic triacylglycerol lipase), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14) and ZG16B (Zymogen granule protein 16 homolog B) It relates to a composition for diagnosing blindness-causing eye diseases comprising a substance for measuring the protein expression level or mRNA expression level of at least one marker for diagnosis of blindness-induced eye disease selected from the group consisting of.

In the present invention, the blindness-causing eye disease may be characterized in that it is selected from the group consisting of age-related macular degeneration, diabetic retinopathy, cataracts, and glaucoma.

The term "measurement of mRNA expression level" used in the present invention is a process of confirming the presence and expression of mRNA of genes for diagnosis of blindness-causing eye disease in a biological sample isolated from a patient suspected of blindness-causing eye disease in order to diagnose blindness-causing eye disease Measure the amount of mRNA. Analysis methods for this include reverse transcription polymerase reaction (RT-PCR), competitive reverse transcription polymerase reaction (Competitive RT-PCR), real-time reverse transcription polymerase reaction (Real-time RT-PCR), and RNase protection assay (RPA; RNaseprotection assay). ), Northern blotting, DNA chip, etc., but are not limited thereto.

The substance for measuring the mRNA level of the marker is characterized in that it is a primer pair, probe or antisense nucleotide that specifically binds to the gene of the marker, and the nucleic acid information of the genes is known in GeneBank, etc. These primer pairs, probes or antisense nucleotides can be designed.

The term "primer" as used in the present invention is a fragment that recognizes a target gene sequence, and includes forward and reverse primer pairs, preferably, a primer pair that provides an analysis result having specificity and sensitivity. When the nucleic acid sequence of the primer is a sequence that is inconsistent with the non-target sequence present in the sample, a primer that amplifies only the target gene sequence containing the complementary primer binding site and does not induce non-specific amplification can give high specificity. .

The term "probe" used in the present invention refers to a substance capable of specifically binding to a target substance to be detected in a sample, and refers to a substance capable of specifically confirming the presence of a target substance in a sample through the binding. do. The type of probe is a material commonly used in the art and is not limited, but preferably PNA (peptide nucleic acid), LNA (locked nucleic acid), peptide, polypeptide, protein, RNA or DNA, and most preferred Hagi is PNA. More specifically, the probe is a biomaterial that includes an organism-derived or similar thing or a thing produced in vitro, for example, enzymes, proteins, antibodies, microorganisms, animal and plant cells and organs, neurons, DNA, and It may be RNA, DNA includes cDNA, genomic DNA, oligonucleotide, RNA includes genomic RNA, mRNA, oligonucleotide, and examples of proteins include antibodies, antigens, enzymes, peptides, and the like.

The term "antisense", as used herein, refers to a nucleotide base in which an antisense oligomer is hybridized with a target sequence in RNA by Watson-Crick base pairing, typically allowing the formation of an mRNA and RNA: oligomeric heterodimer within the target sequence. It means an oligomer having a sequence of and a backbone between subunits. Oligomers may have exact sequence complementarity or approximate complementarity to the target sequence.

The term "protein expression level measurement" used in the present invention is a process of determining the presence and expression of a protein expressed from a gene of a marker for diagnosis of blindness-causing eye disease in a biological sample in order to diagnose blindness-causing eye disease. The protein expression level measurement or comparative analysis methods include protein chip analysis, immunoassay, ligand binding assay, MALDI-TOF (Matrix Desorption/Ionization Time of Flight Mass Spectrometry) analysis, SELDI-TOF (Sulface Enhanced Laser Desorption/Ionization Time). of Flight Mass Spectrometry) analysis, radioimmunoassay, radioactive immunodiffusion method, octeroni immune diffusion method, rocket immunoelectrophoresis, tissue immunostaining, complement fixation method, two-dimensional electrophoresis analysis, liquid chromatography-liquid chromatography -Mass Spectrometry, LC-MS), LC-MS/MS (liquid chromatography-Mass Spectrometry/ Mass Spectrometry), Western blot, and ELISA (enzyme linked immunosorbent assay), multiple reaction monitoring (MRM), parallel reaction Monitoring (parallel reaction monitoring: PRM), sequential windowed data independent acquisition of the total high-resolution (SWATH), selected reaction monitoring (SRM), or immune multiple reaction monitoring (iMRM). It is not limited to this.

The substance for measuring the protein level of the marker may be characterized in that it is an antibody, an interacting protein, a ligand, nanoparticles, or aptamer that specifically binds to the protein or peptide fragment.

As used herein, the term "antibody" refers to a substance that specifically binds to an antigen and causes an antigen-antibody reaction. For the purposes of the present invention, an antibody refers to an antibody that specifically binds to the marker for diagnosis of blindness-causing eye disease of the present invention. The antibodies of the present invention include all of polyclonal antibodies, monoclonal antibodies and recombinant antibodies. The antibody can be easily prepared using techniques well known in the art. For example, the polyclonal antibody can be produced by a method well known in the art including the process of injecting the antibody with a marker protein antigen for diagnosis of blindness-causing eye disease into an animal and collecting blood from the animal to obtain serum containing the antibody. have. Such polyclonal antibodies can be prepared from any animal such as goat, rabbit, sheep, monkey, horse, pig, cow, dog. In addition, the monoclonal antibody is a hybridoma method well known in the art (hybridoma method; see Kohler and Milstein (1976) European Journal of Immunology 6:511-519), or phage antibody library technology (Clackson et al, Nature, 352 :624-628, 1991; Marks et al, J. Mol. Biol., 222:58, 1-597, 1991). The antibody prepared by the above method may be separated and purified using a method such as gel electrophoresis, dialysis, salt precipitation, ion exchange chromatography, and affinity chromatography. In addition, the antibody of the present invention includes a complete form having two full-length light chains and two full-length heavy chains, as well as functional fragments of antibody molecules. The functional fragment of an antibody molecule means a fragment that has at least an antigen-binding function, and includes Fab, F(ab'), F(ab') ₂ and Fv. In addition, the antibody of the present invention may be obtained commercially.

The term "PNA (Peptide Nucleic Acid)" as used herein refers to an artificially synthesized, DNA or RNA-like polymer. While DNA has a phosphate-ribose sugar backbone, PNA has a repeated N-(2-aminoethyl)-glycine backbone linked by a peptide bond, which greatly increases the binding power and stability to DNA or RNA, resulting in molecular biology. , Diagnostic analysis and antisense therapy. PNA is described in Nielsen PE, Egholm M, Berg RH, Buchardt O (December 1991). "Sequence-selective recognition of DNA by strand displacement with a thymine-substituted polyamide". Science 254(5037): 1497-500.

In the present invention, "aptamer" is an oligonucleotide or a peptide molecule, and general information of the aptamer is described in Bock LC et al. , Nature 355(6360):5646(1992); Hoppe-Seyler F, Butz K "Peptide aptamers: powerful new tools for molecular medicine". J Mol Med. 78(8):42630(2000); Cohen BA, Colas P, Brent R. "An artificial cell-cycle inhibitor isolated from a combinatorial library". Proc Natl Acad Sci USA. 95(24): 142727(1998)].

In another aspect, the present invention relates to a kit for diagnosing blindness-induced eye diseases, including the composition for diagnosing blindness-induced eye diseases.

The kit can be prepared by a conventional manufacturing method known in the art. The kit may include, for example, an antibody in a freeze-dried form, a buffer, a stabilizer, an inactive protein, and the like.

The kit may further include a detectable label. The term "detectable label" refers to an atom or molecule that specifically detects a molecule containing a label among molecules of the same type without a label. The detectable label may be attached to an antibody, interacting protein, ligand, nanoparticle, or aptamer that specifically binds to the protein or fragment thereof. The detectable label may include a radionuclide, a fluorophore, or an enzyme.

The kit can be used according to various immunoassays or immunostaining methods known in the art. The immunoassay or immunostaining method may include radioimmunoassay, radioimmunoprecipitation, immunoprecipitation, ELISA, capture-ELISA, inhibition or competition analysis, sandwich analysis, flow cytometry, immunofluorescence staining, and immunoaffinity purification. Preferably, the kit may be a reverse transcription polymerase chain reaction (RT-PCR) kit, a DNA chip kit, an enzyme linked immunosorbent assay (ELISA) kit, a protein chip kit, a rapid kit, or a multiple reaction monitoring (MRM) kit. have.

In addition, the kit can be used for mass spectrometry. In this case, the specific amino acid residues of the protein are myristoylation, isoprenylation, prenylation, glypiation, lipoylation, acylation, alkylation, methylation, demethylation, amidation, It may have modifications such as ubiquitination, phosphorylation, deamidation, glycosylation, oxidation, or acetylation.

In another aspect of the present invention, (a) ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding) from a biological sample of a patient. protein 2), LGALS3BP (galectin-3-binding protein), MBL2 (mannose-binding protein C), PNLIP (pancreatic triacylglycerol lipase), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14) and Measuring the mRNA or protein level of at least one marker for diagnosis of blindness-causing eye disease selected from the group consisting of ZG16B (Zymogen granule protein 16 homolog B); And

It relates to a method for providing information for diagnosing blindness-causing eye diseases, including; (b) comparing the mRNA or protein expression level with a control sample.

In the present invention, the blindness-causing eye disease may be characterized in that it is selected from the group consisting of age-related macular degeneration, diabetic retinopathy, cataracts, and glaucoma.

In the above method, a "biological sample" refers to a tissue, cell, blood, serum, plasma, saliva, cerebrospinal fluid, or urine with a difference in protein expression level or gene expression level due to the onset of blindness-causing eye disease. Means, and preferably means blood, plasma, and serum.

The method of providing information for diagnosis of blindness-causing eye disease is selected from the group consisting of age, hypertension, hyperlipidemia, smoking, diabetes, insulin treatment, body mass index (BMI) m Hb1AC test results, and cardiovascular disease. One or more clinical information may be additionally included.

In addition, the method of providing information for diagnosing blindness-causing eye disease may further include determining that it is a blindness-causing eye disease if the gene expression level or protein expression level of the marker increases/decreases compared to the control group.

The measurement of the mRNA expression level in step (a) is the measurement or comparison of the mRNA expression level: reverse transcriptase polymerase reaction, competitive reverse transcriptase polymerase reaction, real-time reverse transcriptase polymerase reaction, RNase protection assay, Northern blotting or DNA chip, etc. Can be used, but the present invention is not limited thereto. Through the above measurement methods, the mRNA expression level in the normal control group and the mRNA expression level in age-related macular degeneration patients can be confirmed, and the onset of age-related macular degeneration can be diagnosed or predicted by comparing the levels of these expression levels.

The measurement of the protein expression level in step (a) may be measured and compared using antibodies, interacting proteins, ligands, nanoparticles, or aptamers that specifically bind to proteins or peptide fragments. Preferably, the protein expression level measurement or comparison analysis method includes protein chip analysis, immunoassay, ligand binding assay, MALDI-TOF (Matrix Desorption/Ionization Time of Flight Mass Spectrometry) analysis, SELDITOF (Sulface Enhanced Laser Desorption/ Ionization Time of Flight Mass Spectrometry) analysis, radioimmunoassay, radioactive immunodiffusion method, octeroni immunodiffusion method, rocket immunoelectrophoresis, tissue immunostaining, complement fixation method, two-dimensional electrophoresis analysis, liquid chromatography-mass spectrometry ( Liquid chromatography-Mass Spectrometry, LC-MS), LCMS/MS (liquid chromatography-Mass Spectrometry/ Mass Spectrometry), Western blot, and ELISA (enzyme linked immunosorbentassay), but are not limited thereto.

More preferably, in the present invention, multiple reaction monitoring (MRM), parallel reaction monitoring (PRM), sequential windowed data independent acquisition of the total high-resolution (SWATH), and selected reaction monitoring (selected reaction monitoring) monitoring: SRM) or immune multiple reaction monitoring (iMRM).

MRM is a method of determining an exact fragment of a substance, breaking it in a mass spectrometer, selecting a specific ion from the broken ions once more, and obtaining the number using a detector connected in series. In the case of using the MRM method, the protein or fragment thereof can be quantified using a mass spectrometer in blood samples of normal individuals and individuals suspected of age-related macular degeneration.

The comparison of the mRNA or protein expression level in step (b) can be analyzed using a statistical method or an algorithm to improve the accuracy of diagnosis, and a linear or nonlinear regression analysis method, an advance or nonlinear classification analysis method, and logistic Logistic regression, Analysis of Variance (ANOVA), neural network analysis method, genetic analysis method, support vector machine analysis method, hierarchical analysis or clustering analysis method, hierarchical algorithm or kernel principal component using decision trees ( Kernel principal component analysis method, Markov Blanket analysis method, recursive feature elimination or entropy-basic regression feature elimination analysis method, forward floating search or rear floating search analysis An analysis method selected from the group consisting of a method, and a combination thereof may be used. In the present invention, preferably, the statistical method uses a logistic regression analysis method, but is not limited thereto.

In a specific embodiment of the present invention, 102 plasma samples were analyzed for quantitative verification of biomarkers for diagnosis of age-related macular degeneration among plasma proteins (Table 1), and quantitative verification of biomarkers for diagnosis of diabetic retinopathy was performed. For this, 81 plasma samples were analyzed (Table 2). ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2), LGALS3BP (galectin-3-binding protein), MBL2 ( 11 target markers consisting of mannose-binding protein C), pancreatic triacylglycerol lipase (PNLIP), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14), and ZG16B (Zymogen granule protein 16 homolog B) Was analyzed using multiple reaction monitoring (MRM). As shown in Table 3, for quantitative analysis, peptides for each marker were selected and MRM-MS analysis was performed using SIS.

In another specific embodiment of the present invention, when a single biomarker quantitative result and clinical information are combined, the biomarker expression level conversion information and the clinical information conversion degree are input using a logistic regression model to confirm the diagnostic ability improvement effect. Thus, the probability of classification as age-related macular degeneration or diabetic retinopathy was estimated. As a result, as shown in Table 4, it was confirmed that the age-related macular degeneration diagnostic ability (AUC) for each single marker was 0.66 or higher, and as shown in Table 5, diabetic retinopathy diagnostic ability for each single marker ( AUC) was all confirmed to be 0.73 or more.

In another aspect of the present invention, (a) ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2), LGALS3BP (galectin-3-binding protein), MBL2 (mannose-binding protein C), PNLIP (pancreatic triacylglycerol lipase), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14) and ZG16B (Zymogen granule protein) 16 homolog B) treating a candidate therapeutic agent in a cell sample in which the expression level of mRNA or protein for one or more markers selected from the group is increased compared to the control group;

(b) checking whether the mRNA or protein expression level of the marker is decreased after treatment with the candidate substance;

It relates to a method for screening a substance for treating blindness-induced eye disease comprising a.

In the present invention, the blindness-causing eye disease may be characterized in that it is selected from the group consisting of age related macular degeneration (AMD), diabetic retinopathy, cataract and glaucoma.

The control group may be cells derived from an individual who does not have blindness-causing eye disease.

Hereinafter, the present invention will be described in more detail through examples.

These examples are for illustrative purposes only, and it will be apparent to those of ordinary skill in the art that the scope of the present invention is not construed as being limited by these examples.

Example 1. Blindness-causing eye disease patient selection and plasma collection

1-1: Age-related macular degeneration patient selection and plasma collection

Plasma samples from patients with age-related macular degeneration were collected with the approval of the Institutional Review Board of Seoul National University Bundang Hospital. A total of 102 plasma samples were analyzed for the quantitative detection of biomarkers using plasma proteins, and the clinical characteristics of the analyzed normal group (Non AMD) and age-related macular degeneration (AMD) disease group are shown in Table 1 below.

Sample clinical information

	Sample (n=102)
	Non AMD (n=30)	AMD (n=72)	Early AMD (n=29)	Late AMD (n=25)
age	59.8±6.6	71.7±8.1	71.8±6.5	71.6±9.2
Gender (Female/Male)	14/16	34/38	23/6	11/32
Systemic risk factors
smoking	11 (36.7)	34 (47.2)	8 (27.6)	26 (60.5)
diabetes	2 (6.7)	12 (16.7)	2 (6.9)	10 (23.3)
High blood pressure(%)	10 (33.3)	32 (44.4)	9 (31.0)	23 (53.5)
Hyperlipidemia (%)	7 (23.3)	23 (31.9)	12 (41.4)	11 (25.6)
Cardiovascular disease (%)	3 (10.0)	7 (9.7)	2 (6.9)	5 (11.6)

1-2: Diabetic retinopathy patient selection and plasma collection

Plasma samples from diabetic retinopathy patients were collected with the approval of the Institutional Review Board of Seoul National University Bundang Hospital. A total of 81 plasma samples were analyzed for quantitative detection of biomarkers using plasma proteins, and the clinical characteristics of the analyzed normal group (Non DMR) and diabetic retinopathy (DMR) disease group are shown in Table 2 below.

Sample clinical information

	Sample (n=81)
	Non DMR(n=25)	DMR (n=56)		NPDR (n=31)			PDR (n=25)
				Mild(n=14)	Moderate(n=8)	Severe(n=9)
age	60.88±12.5	59.4±8.7		62.6±7.7	60.3±6.8	57.3±8.6	57.6±9.6
Gender (Female/Male)	22/3	13/43		11/3	1/7	0/9	1/24
Hb1Ac	7.49±1.34	7.75±1.42		7.43±0.90	8.13±1.37	7.58±1.68	7.87±1.60
Insulin treatment (%)	21 (84.0)	55 (98.2)		14 (100.0)	8 (100.0)	9 (100.0)	24 (96.0)
BMI (%)
that	0 (0.0)		2 (3.6)	0 (0)	0 (0)	1 (11.1)	1 (4.0)
normal	18 (72.0)		32 (57.1)	6 (42.9)	5 (62.5)	5 (66.7)	15 (60.0)
Hardness	7 (28.0)		14 (25.0)	7 (50.0)	0 (0)	2 (22.2)	5 (20.0)
Altitude	0 (0)		8 (14.3)	1 (7.1)	3 (37.5)	0 (0)	4 (16.0)
High blood pressure(%)	11 (52.0)		26 (46.4)	5 (35.7)	2 (25.0)	4 (44.4)	15 (60.0)
Hyperlipidemia (%)	18 (72.0)		26 (46.4)	9 (64.3)	2 (25.0)	5 (55.6)	10 (40.0)
Cardiovascular disease (%)	3 (12.0)		7 (12.5)	1 (7.1)	1 (12.5)	2 (22.2)	3 (12.0)

Example 2. Peptide Selection and Peptide Analysis Using MRM-MS

2-1: Peptide selection and synthetic peptide design

In the present invention, as biomarkers for diagnosing blindness-causing eye diseases, MBL2 (mannose-binding protein C), PNLIP (pancreatic triacylglycerol lipase), LGALS3BP (galectin-3-binding protein), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14), ADAMTSL2 (ADAMTS-like protein 2), IGFBP2 (insulin like growth factor binding protein 2), DDI2 (Protein DDI1 homolog2), ZG16B (Zymogen granule protein 16 homolog B), Cp (Ceruloplasmin ) And 11 of FCN2 (Ficolin 2) were selected.

In order to perform MRM analysis on the biomarkers, a representative peptide having a specific charge-to-mass ratio (m/z) for the proteins of 11 biomarkers is selected (Q1), and the peptide is broken by electric shock. Among the fragmentation ions, the ion (Q3) having the highest strength was selected.

At least one peptide with high sensitivity per protein was measured and injected into a mass spectrometer based on this to obtain an optimal value of fragmentation energy per transition, and three or more upper fragmented ions were selected based on the intensity (Table 3).

Top fragmentation ions for 11 biomarkers

Gene name	Trypsin fragment	Target ion	Target m/z
ADAMTSL2	NFNIAGTVVK (SEQ ID NO: 12)	2y8	531.8007/801.4829
Cp	AEVGDTIR (SEQ ID NO: 13)	2y6	430.7272/660.3675
DDI2	DGDVVILR (SEQ ID NO: 14)	2y4	443.7533/500.3555
FCN2	LQAADTCPEVK (SEQ ID NO: 15)	2y9	616.303/990.4561
IGFBP2	LIQGAPTIR (SEQ ID NO: 16)	2y7	484.798/742.4206
LGALS3BP	SDLAVPSELALLK (SEQ ID NO: 17)	2y8	678.3927/870.5295
MBL2	WLTFSLGK (SEQ ID NO: 18)	2y6	476.2686/652.3665
PNLIP	TGYTQASQNIR (SEQ ID NO: 19)	2y5	619.8098/617.3365
SELE	NWAPGEPNNR (SEQ ID NO: 20)	2y8	577.7705/854.4115
SIGLEC14	EGGEFTCR (SEQ ID NO: 21)	2y3	478.2005/436.1973
ZG16B	YFSTTEDYDHEITGLR (SEQ ID NO: 22)	3y14+2	649.6304/818.8761

To confirm the quantification, SIS (Stable-isotope labeled standard) peptides corresponding to 11 proteins were used, and the spiked heavy peptide concentration was determined using an experiment to confirm linearity through calibration. The SIS peptide is a peptide obtained by substituting 13C and 15N for 12C and 14N in the lysine (Lys, K) or arginine (Arg, R) amino acids at the C-terminus of the peptide. Although the mass value is different from the endogenous peptide present in the blood, since the peptide has the same sequence, the peptide hydrophobicity is the same, so it is eluted at the same retention time (RT) on the chromatogram.

2-2: Plasma sample pretreatment and MRM-MS analysis

14 kinds of proteins (Albumin, IgG, Antitrypsin, IgA, Transferrin, Haptoglobin, Fibrinogen, Alpha2-Macroglobulin, Alpha1-Acid glycoprotein, IgM, Apolipoprotein AI) present in high abundant amounts in each plasma obtained in Example 1, Apolipoprotein AII, Complement C3, Transthyretin) was removed. For the depletion, 14 kinds of proteins were removed using a MARS (Multiple affinity removal system, Agilent, USA) column according to the manufacturer's method, and the remaining proteins were eluted and used for analysis. After adding urea to a concentration of 8 M to the eluted depleted sample, 2-carboxylethyltrisphosphine (Tris(2-carboxyethyl)-phosphine, TECP) to be 80 mM, and 2-chloro to be 320 mM. Acetamide (2-chloroacetamide) was added and reacted at 25° C. for 1 hour to reduce and alkylate disulfide bonds. Rice seed enzyme was added so that the mass ratio of plasma protein to rice seed (wako) enzyme was 100:1, and reacted at room temperature for 4 hours. After that, dilute 10 times with 50 mM Tris (Tris, pH 8.0) solution and add sequencing trypsin (Promega) so that the mass ratio of protein and trypsin becomes 50:1, and react at 37°C for 12 hours or more. And digested into peptide fragments. Formic acid (formic acid) solution was added to a concentration of 0.3%, acidified to a pH of 2.0 or less, and the trypsin reaction was stopped.

Here, desalination was performed and a heavy-labeled peptide was added (spiking) as an internal standard material (SIS peptide) determined in Example 2-1 to perform MRM analysis. Nano ultra 2D plus (Eksigent), a triple quadrupole mass spectrometer, QTarp 5500 (SCIEX) was used to monitor the transition of each selected protein in a scheduled MRM mode.

Specifically, an ion voltage of 5500 volts was used, and the resolution at Q1 (Quadruple 1) and Q3 (Quadruple 3) was set as a unit. The total cycle time for the transition was set to be 1.5 seconds. 20 units of nebulizing gas were used and the heater temperature was set to 350°C. Internal standards were spiked into each sample and monitored simultaneously to correct for variations between batches.

2-3: data analysis

The peak area of the transition was calculated by processing raw data using Skyline (Mccoss lab, University of Washington, USA). Relative concentrations were compared for the endogenous/heavy labeled peptide using the peak area. Using the measured result values, T-test and AUROC (Area under the receiver operating characteristic) values were generated to measure the predictive ability of each protein peptide. In order to confirm the predictive power combined with the information, a logistic regression model was used to input the expression level conversion information and the clinical record conversion degree to estimate a probability value classified as age-related macular degeneration or diabetic retinopathy. All statistical analyzes were performed using MedCal ver 17.1 (MedCalc).

Example 3. Confirmation of diagnostic ability according to the result of analysis of markers for diagnosis of eye disease causing blindness and combination of clinical information

3-1: Confirmation of age-related macular degeneration diagnostic ability

In the present invention, when the discovered blood marker results and clinical information are combined, a probability value classified as age-related macular degeneration by inputting biomarker expression level conversion information and clinical information conversion degree using a logistic regression model to confirm diagnostic ability Was estimated.

Age-related macular degeneration single marker diagnostic ability

	ADAMTSL2	CP	DDI2	FCN2	LGALS3BP	MBL2	PNLIP	SELE	SIGLEC14	ZG16B
AUC	0.753	0.679	0.665	0.659	0.699	0.682	0.684	0.679	0.66	0.706
P-value	<0.001	0.003	0.009	0.017	0.001	0.003	0.005	0.003	0.009	0.001

As shown in Table 4, it was confirmed that the diagnostic ability (AUC) of age-related macular degeneration for each single marker was 0.66 or higher. 1 is an independent t-test result for the difference between 10 protein quantification values and clinical information. All 10 proteins showed a p value of less than 0.05, showing a statistically significant difference.

3-2: Diabetic retinopathy diagnosis ability check

In the present invention, when the discovered blood marker results and clinical information are combined, the biomarker expression level conversion information and the clinical information conversion level are input using a logistic regression model to confirm the diagnostic ability to determine the probability value classified as diabetic retinopathy. Estimated.

Diabetic retinopathy single marker diagnostic ability

	ADAMTSL2	LGALS3BP	PNLIP	SELE	SIGLEC14
AUC	0.734	0.756	0.795	0.74	0.756
P-value	<0.001	<0.001	<0.001	<0.001	<0.001

As shown in Table 5, it was confirmed that all diabetic retinopathy diagnostic ability (AUC) for each single marker was 0.73 or higher. 2 is an independent t-test result for the difference between five protein quantification values and clinical information. All five proteins showed a statistically significant difference as the p value was less than 0.05.

The method for diagnosing blindness-causing eye diseases provided by the present invention, a diagnostic composition, a diagnostic kit, or a method for providing information necessary for diagnosis is a new immunological diagnostic tool using plasma of a patient, and has excellent sensitivity and does not use a biopsy. In addition to being able to conveniently analyze plasma as a target, it has been confirmed that high diagnostic ability is shown by combining the quantitative value of the protein and basic clinical information of the diagnostic marker, and thus it can be usefully used for diagnosis of blindness-causing eye diseases.

Claims (17)

1. ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2), LGALS3BP (galectin-3-binding protein), MBL2 ( mannose-binding protein C), pancreatic triacylglycerol lipase (PNLIP), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14), and ZG16B (Zymogen granule protein 16 homolog B). A marker for diagnosing eye diseases that cause blindness.
2. The marker for diagnosing blindness-induced eye disease according to claim 1, wherein the blindness-induced eye disease is selected from the group consisting of age-related macular degeneration, diabetic retinopathy, cataracts, and glaucoma.
3. ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2), LGALS3BP (galectin-3-binding protein), MBL2 ( mannose-binding protein C), pancreatic triacylglycerol lipase (PNLIP), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14), and ZG16B (Zymogen granule protein 16 homolog B). A composition for diagnosing blindness-causing eye disease, comprising a substance for measuring the protein level of the above-described blindness-causing eye disease diagnostic marker or its mRNA level.
4. The composition for diagnosing blindness-induced eye diseases according to claim 3, wherein the blindness-causing eye disease is selected from the group consisting of age-related macular degeneration, diabetic retinopathy, cataracts, and glaucoma.
5. The composition for diagnosing blindness-induced eye disease according to claim 3, wherein the substance for measuring the mRNA level of the complex marker is a primer pair, a probe, or an antisense nucleotide that specifically binds to the gene of the marker.
6. The method of claim 3, wherein the substance measuring the protein level of the complex marker is an antibody, interacting protein, ligand, nanoparticles, or aptamer that specifically binds to the protein or peptide fragment of the marker. A composition for diagnosing blindness-induced eye diseases, characterized in that.
7. A kit for diagnosing blindness-induced eye disease, comprising the composition for diagnosing blindness-induced eye disease according to any one of claims 3 to 6.
8. The method of claim 7, wherein the kit is RT-PCR (Reverse transcription polymerase chain reaction) kit, DNA chip kit, ELISA (Enzymelinked immunosorbent assay) kit, protein chip kit, rapid kit, or MRM (Multiple reaction monitoring) kit. A kit for diagnosing blindness-induced eye diseases, characterized in that.
9. (a) ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2), LGALS3BP (galectin- 3-binding protein), MBL2 (mannose-binding protein C), PNLIP (pancreatic triacylglycerol lipase), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14) and ZG16B (Zymogen granule protein 16 homolog B) ) Measuring the mRNA or protein level of at least one marker for diagnosis of blindness-causing eye disease selected from the group consisting of; And

   (b) comparing the mRNA or protein expression level with a control sample;

   Information providing method for diagnosing blindness-causing eye disease comprising a.
10. The method of claim 9, wherein the blindness-causing eye disease is selected from the group consisting of age-related macular degeneration, diabetic retinopathy, cataracts, and glaucoma.
11. The method of claim 9, wherein the method of providing information for diagnosing blindness-causing eye disease is in the group consisting of patient's age, body mass index (BMI), Hb1Ac test result, insulin treatment, hypertension, hyperlipidemia, and cardiovascular disease. Information providing method for diagnosing blindness-causing eye diseases, characterized in that providing additionally selected one or more kinds of clinical information.
12. The method of claim 9, wherein the mRNA expression level is measured using reverse transcriptase polymerase reaction, competitive reverse transcriptase polymerase reaction, real-time reverse transcriptase polymerase reaction, RNase protection assay, Northern blotting or DNA chip. How to provide information for diagnosing eye diseases.
13. The method of claim 9, wherein the protein expression level measurement is a protein chip analysis, immunoassay, ligand binding assay, MALDI-TOF (Matrix Desorption/Ionization Time of Flight Mass Spectrometry) analysis, SELDITOF (Sulface Enhanced Laser Desorption/Ionization Time of Flight Mass Spectrometry) analysis, radioimmunoassay, radioactive immunodiffusion method, octeroni immunodiffusion method, rocket immunoelectrophoresis, tissue immunostaining, complement fixation method, two-dimensional electrophoresis analysis, liquid chromatography-liquid chromatography- Mass Spectrometry, LC-MS), LCMS/MS (liquid chromatography-Mass Spectrometry/ Mass Spectrometry), Western Blot, ELISA (enzyme linked immunosorbent assay), multiple reaction monitoring (MRM), parallel reaction monitoring (parallel reaction) monitoring: PRM), sequential windowed data independent acquisition of the total high-resolution (SWATH), selected reaction monitoring (SRM), or immune multiple reaction monitoring (iMRM) Information provision method for diagnosis of induced eye disease.
14. The method of claim 9, wherein the step (b) is performed by a statistical analysis method.
15. The method of claim 14, wherein the statistical analysis method is a linear or nonlinear regression analysis method, a preceding or nonlinear classification analysis method, a logistic regression method, an Analysis of Variance (ANOVA), and a neural network analysis method. , Genetic analysis method, support vector machine analysis method, hierarchical analysis or clustering analysis method, hierarchical algorithm using decision tree or kernel principal component analysis method, Markov Blanket analysis method, recursive feature cancellation (recursive) lower blindness-causing eye disease, characterized by being selected from the group consisting of feature elimination) or entropy-basic regression feature elimination analysis method, forward floating search or rear floating search analysis method, and combinations thereof How to provide information for diagnosis.
16. (a) ADAMTSL2 (ADAMTS-like protein 2), Cp (Ceruloplasmin), DDI2 (Protein DDI1 homolog2), FCN2 (Ficolin 2), IGFBP2 (insulin like growth factor binding protein 2), LGALS3BP (galectin-3-binding protein) , MBL2 (mannose-binding protein C), PNLIP (pancreatic triacylglycerol lipase), SELE (E-selectin), SIGLEC14 (Sialic acid-binding Ig-like lectin 14) and ZG16B (Zymogen granule protein 16 homolog B) Treating a candidate therapeutic agent in a cell sample in which the mRNA or protein expression level for the selected one or more markers is increased compared to the control;

    (b) checking whether the mRNA or protein expression level of the marker is decreased after treatment with the candidate substance;

    Screening method of a substance for treating blindness-induced eye diseases comprising a.
17. The method of claim 16, wherein the blindness-causing eye disease is selected from the group consisting of age-related macular degeneration, diabetic retinopathy, cataracts, and glaucoma.

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