KR20240035686A - Composition for diagnosing diabetic retinopathy using biomarkers, method for providing information for diagnosing diabetic retinopathy, and screening method for substances for treatment of diabetic retinopathy - Google Patents

Abstract

The present invention provides a composition for diagnosing diabetic retinopathy using a biomarker, a method for providing information for diagnosing diabetic retinopathy, and a method for screening a substance for treating diabetic retinopathy, and the biomarkers are described in detail in the specification.

Description

Composition for diagnosing diabetic retinopathy using biomarkers, method for providing information for diagnosing diabetic retinopathy, and method for screening substances for treating diabetic retinopathy FOR SUBSTANCES FOR TREATMENT OF DIABETIC RETINOPATHY}

The present invention relates to a composition for diagnosing diabetic retinopathy using a biomarker, a method for providing information for diagnosing diabetic retinopathy, and a method for screening a substance for treating diabetic retinopathy.

Diabetic retinopathy (DR) is a metabolic disease that involves inflammation and changes in mitochondria, and is the leading cause of blindness in adults worldwide. Diabetic retinopathy is a complication of diabetes, and is mainly diagnosed by pathological changes in microcirculation, with mechanisms including abnormal vascular leakage in the retina, development of new and fragile blood vessels, hemorrhage, fluid leakage, inflammation, and retinal cell death.

The early stages of diabetic retinopathy include synaptic protein changes, neurodegeneration, retinal pigment epithelium (RPE) cell death and thinning of the inner nuclear layer, mitochondrial dysfunction, increased oxidative stress, increased advanced glycation end products, and apoptosis of photoreceptor cells. Includes the phenomenon of Additionally, the pathogenesis of diabetic retinopathy involves activation of the polyol pathway, excessive production of reactive oxygen species, VEGF activation, neovascularization and blood-retinal barrier (BRB) damage, mitochondrial dysfunction, and metabolites, including insulin-PI3K. Includes interactions between protein bodies. However, detecting these changes is difficult, and the molecular mechanisms involved are not fully understood.

The present inventor identified the mechanism of diabetic retinopathy at the molecular level through proteomic analysis, such as extracting and analyzing proteomes and metabolites and creating a metabolite map, for a diabetic retinopathy model, and identified diabetic retina. The present invention was completed by discovering a biomarker that can be used for diagnosis of diseases or screening for treatments.

Hyo Jung Gye, et al., New Modalities for the Diagnosis and Treatment of Diabetic Retinopathy, The Korean Journal of Medicine: Vol. 89, no. 3, 2015

Accordingly, the problem to be solved by the present invention is to provide a composition and method that can effectively diagnose diabetic retinopathy and a method that can screen substances for the treatment of diabetic retinopathy.

The problems of the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the description below.

In order to solve the above problem, the present invention provides a composition for diagnosing diabetic retinopathy (DR) according to one embodiment.

A composition for diagnosing diabetic retinopathy includes an agent that measures the level of a biomarker related to diabetic retinopathy, and the biomarker includes one or more of the biomarkers shown in Table 1 below.

division type change first biomarker Protein of SEQ ID NO: 1 (CAC2PBS) increase Protein of SEQ ID NO: 2 (VIMIII) increase Protein of SEQ ID NO: 3 (FAM81B) increase Protein of SEQ ID NO: 4 (ADAM18) increase Adenylate cyclase 4 (ADCY4) increase Myogenic regulatory factor 2 (MRF2) increase Vinculin (VCL) increase Toll-like Receptor 7 (TLR7) increase SH3 domain-binding protein 1 (SH3BP1) increase Thioredoxin domain containing protein 17 (TXNDC17) increase Microtubule-actin cross linking factor 1 (MACF1) increase Dynamin-1 like protein (DNM1L) increase Regulator of G-protein signaling 3 (RGS3) increase Activated protein C (APC) increase Ras-related C3 botulinum toxin substrate 1 (RAC1/2) increase RhoA (Ras homolog family member A) increase Calcium/calmodulin-dependent protein kinase II alpha, CAMK2A increase Complement 3 (C3) increase Disintegrin and metalloproteinase domain-containing protein 17 (ADAM17) increase Vascular cell adhesion molecule 1 (VCAM1) increase Estrogen receptor 1 (ESR1) (Estrogen receptor alpha) increase SOS1 (Son of Sevenless homolog 1) increase Second biomarker Prohibitin (PHB) decrease T-cell receptor beta (TCRB) decrease Insulin like growth factor 2 receptor A (IGF2R) decrease Junction plakoglobin (JUP) decrease E3 ubiquitin-protein ligase (RNF135) decrease Prohibitin 2 (PHB2) decrease

In Table 1, the CAC2PBS protein, VIMIII protein, FAM81B protein, and ADAM18 protein have 80% or more, 85% or more, 90% or more, 95% or more, and 96 independently of the amino acid sequences of SEQ ID NOs: 1, 2, 3, and 4, respectively. It may be a protein having sequence homology of at least %, at least 97%, at least 98%, or at least 99%. Alternatively, the CAC2PBS protein, VIMIII protein, FAM81B protein, and ADAM18 protein may be proteins having the amino acid sequences of SEQ ID NOs: 1, 2, 3, and 4, respectively. In this specification, a protein having an amino acid sequence of a specific sequence number also includes its functional equivalent. The “functional equivalent” refers to an amino acid sequence that is at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98% of the amino acid sequence of the specific sequence number, as a result of addition, substitution or deletion of amino acids. % or more, or 99% or more sequence homology, meaning that it has substantially the same physiological activity as the protein having the amino acid sequence of the specific sequence number. For example, the protein having the sequence homology is In a protein having an amino acid sequence of a specific sequence number, one or more amino acids, two or more amino acids, three or more amino acids, four or more amino acids, or five or more amino acids may be substituted.

The “substantially homogeneous physiological activity” refers to the prevention or treatment activity of diabetic retinopathy due to the structural and functional homology of the protein. Additionally, the protein may or may not have physicochemical properties as a result of addition, substitution, or deletion of amino acids. In exemplary embodiments, the amino acid substitutions may improve the thermal stability of the protein, change the substrate specificity, or change the optimal pH. However, it is not limited to this.

The N or C-terminus of a protein having an amino acid sequence of a specific sequence number may be bound to a specific functional group. The stability of the protein can be improved by the modification. The above stability is a concept that includes not only in vivo stability but also storage stability. The protecting group can protect the protein from attack by protein-cleaving enzymes in vivo.

Measuring the level of a biomarker may mean measuring the amount of the biomarker, such as its content or concentration, or measuring the expression level of mRNA or protein of a gene that directly expresses the biomarker or is involved in the increase of the biomarker. It may be possible. A gene involved in the increase of a biomarker may mean that a substance such as a protein produced through expression of the gene increases the abundance of the biomarker.

An agent for measuring the level of a biomarker as shown in Table 1, and when measuring the mRNA expression level of a gene related to the biomarker, it contains at least one of a primer pair, a probe, and an antisense nucleotide that specifically binds to the gene. can do. Since the nucleic acid information of at least one of the genes is known in GeneBank, etc., a person skilled in the art can design primer pairs, probes, or antisense nucleotides based on the sequences.

The probe refers to a substance that can confirm the presence of a target substance by specifically binding to the target substance to be detected in a sample, such as PNA (peptide nucleic acid), LNA (locked nucleic acid), peptide, polypeptide, protein, RNA. Alternatively, it may be DNA, but is not limited thereto.

Methods for measuring mRNA expression levels 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). RNase protection assay), Northern blotting, DNA chip, etc., but are not limited thereto.

Alternatively, it may include one or more of antibodies, interacting proteins, ligands, nanoparticles, and aptamers that specifically bind to the biomarker.

The antibodies may include polyclonal antibodies, monoclonal antibodies, and recombinant antibodies.

In order to solve the above other problems, the present invention provides a kit for diagnosing diabetic retinopathy according to one embodiment. The kit for diagnosing diabetic retinopathy includes the composition for diagnosing diabetic retinopathy as described above. Kits for diagnosing diabetic retinopathy may be RT-PCR (reverse transcription polymerase chain reaction) kits, DNA chip kits, ELISA (Enzyme linked immunosorbent assay) kits, protein chip kits, rapid kits, or MRM (multiple reaction monitoring) kits. there is.

Additionally, the kit can be used for mass spectrometry. In this case, specific amino acid residues of the protein may be myristoylated, isoprenylated, prenylated, glypiated, lipoylated, acylated, alkylated, methylated, demethylated, amidated, It may have modifications such as ubiquitination, phosphorylation, deamidation, glycosylation, oxidation, or acetylation.

A kit for diagnosing diabetic retinopathy can be manufactured by methods known to those skilled in the art. A kit for diagnosing diabetic retinopathy may include, for example, a freeze-dried antibody, a buffer solution, a stabilizer, an inactive protein, etc. The antibody may be labeled with radionuclides, fluoresces, enzymes, etc.

In order to solve the above problem, the present invention provides a method of providing information for diagnosing diabetic retinopathy according to an embodiment. A method of providing information for diagnosing diabetic retinopathy includes (a) measuring the level of a biomarker related to diabetic retinopathy in a biological sample of a subject; (b) comparing the measured level to a control sample; and (c) diagnosing the possibility of diabetic retinopathy if the measured level increases or decreases compared to the control sample. A biomarker related to diabetic retinopathy is one or more of the biomarkers in Table 1 above.

Specifically, the first biomarker among the biomarkers in Table 1 has the characteristic of increased (or greater) mRNA (or protein) expression level or abundance in cells or patients with diabetic retinopathy compared to the normal control group. Accordingly, if the level of the first biomarker increases (or exceeds) compared to the control sample, the subject may be diagnosed as having the possibility of having diabetic retinopathy. In other words, it can be diagnosed (or determined, determined) that the subject is likely to have or develop diabetic retinopathy.

Conversely, the second biomarker among the biomarkers in Table 1 has the characteristic that the mRNA (or protein) expression level or abundance is reduced (or less) in cells or patients with diabetic retinopathy compared to the normal control group. Accordingly, if the level of the second biomarker is reduced (or less) compared to the control sample, the subject may be diagnosed as having the possibility of having diabetic retinopathy. In other words, it can be diagnosed (or determined, determined) that the subject is likely to have or develop diabetic retinopathy.

Additionally, the more types of first biomarkers are measured to be increased (or the more types of second biomarkers are measured to be decreased), the higher the possibility of disease prevalence may be diagnosed.

The biological sample may be derived from a vascular region or a non-vascular region of the subject.

The vascular region is a tissue containing the blood vessels of the target, and a biological sample derived from the vascular region may be, for example, a sample containing blood, plasma, and/or vascular tissue (vascular endothelium, vascular mesothelium, vascular envelope, etc.). . More specifically, a biological sample derived from a vascular region may be one derived from a vascular region within a tissue related to the disease to be diagnosed. For example, in the case of diagnosing diabetic retinopathy, the sample may be the retina, macula, retinal nerve, or retina. It may be blood, plasma, and/or vascular tissue collected from pigment epithelium, etc.

The non-vascular area is tissue that does not contain blood vessels of interest, and a biological sample derived from the non-vascular area may be a sample containing tissue of extravascular cells. More specifically, a biological sample derived from a non-vascular area may be an extravascular tissue related to the disease to be diagnosed. For example, in the case of diagnosing diabetic retinopathy, the retina, macula, retinal nerve, and retinal pigment may be used. It may be tissue from an extravascular area collected from epithelium, etc.

As a more specific example, in the case of retinal blood vessels, entire retinal cells can be collected to analyze biomarkers related to diabetic retinopathy. In the case of diabetes, adipose tissue of brown adipose tissue or white adipose tissue can be separated and analyzed. However, embodiments of the present invention are not limited thereto.

In some embodiments, in the method of providing information for diagnosing diabetic retinopathy of the present invention, step (a) may be a step of measuring the level of one or more of the first biomarker and one or more of the second biomarker in the biological sample of the subject. You can. By measuring and comparing the first and second biomarkers together, the accuracy of diagnosing diabetic retinopathy can be further improved. In this case, it can be diagnosed that the likelihood of prevalence is higher when the first biomarker increases and the second biomarker decreases than when only the first biomarker is evidenced or only the second biomarker is decreased.

Measurement and comparison of the level of the biomarker can be performed using the diagnostic composition or kit described above.

To analyze the levels of the biomarkers, SDS-PAGE (sodium dodecyl sulfate-polyacrylamide gel electrophoresis), MALDI-TOF (Matrix-assisted laser desorption/ionization), GC-MS (Gas chromatography-mass spectrometry) analysis, and LC-MS (Liquid chromatography-mass spectrometry) analysis, cholesterol oxidase analysis, lipid panel analysis, etc. may be used alone or additionally, but embodiments of the present invention are not limited thereto.

In addition, the analysis in steps (a) to (c) can be analyzed using statistical methods or algorithms to improve the accuracy of diagnosis, such as linear or non-linear regression analysis methods, a priori or non-linear classification analysis methods, 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 using decision tree or kernel principal component ( Kernel principal component) analysis method, Markov Blanket analysis method, recursive feature elimination or entropy-basic regression feature elimination analysis method, and forward floating search or backward floating search analysis. One or more analysis methods selected from the group consisting of methods may be used.

In order to solve the above problem, the present invention, according to another embodiment, includes the step (d) of administering a therapeutic agent capable of reducing (or increasing) the biomarker level measured in step (a). Provides a treatment method for diabetic retinopathy that further includes. In other words, if a specific biomarker increases through steps (a) to (c) and it is determined that there is a possibility of the disease, by administering a therapeutic agent that can act by directly or indirectly inhibiting the relevant biomarker. Can heal the target. Meanwhile, if the biomarker measuring the level is a first biomarker, a therapeutic agent capable of reducing it is administered, and if the level is a second biomarker, a therapeutic agent capable of increasing it is administered.

The therapeutic preparation may be administered in the form of a pharmaceutical composition. The therapeutic preparation is mixed with a pharmaceutically acceptable carrier, excipient, diluent, etc. by a method known in the pharmaceutical field to form a dosage form such as an injection. It can be manufactured and administered by intravenous injection.

The method for treating diabetic retinopathy of the present invention may further include (e) measuring the level of the biomarker again after administration of the pharmaceutical agent in step (d).

In order to solve the above problem, the present invention provides a screening method for a substance for treating diabetic retinopathy according to an embodiment. A screening method for a substance for treating diabetic retinopathy includes (a) treating a candidate substance in an experimental model; (b) measuring the level of one or more of the above-described biomarkers in the treated experimental model; and (c) comparing the measured level with the control model to determine whether the biomarker has decreased or increased.

The biomarker of the present invention is a substance that increases (first biomarker) or decreases (second biomarker) compared to the normal control group, so the biomarker decreases (first biomarker) or increases (second biomarker) by treating a specific candidate material. marker), the candidate substance can be judged as a substance with the potential to treat diabetic retinopathy and used to conduct next-stage experiments such as preclinical and clinical trials.

The step of processing the candidate material may be performed in one or more of the following ways: in vitro, in vivo, ex vitro, ex vivo, and in silico, and the experimental model may be a cell, animal model, human, or a cell isolated or derived from an animal or human. It may be a cell or tissue, and may be a vascular area or a non-vascular area.

The experimental model may be a cell model or animal model in which diabetic retinopathy is induced, or a cell, animal, or human having diabetic retinopathy, or a cell or tissue isolated or derived from an animal or human.

Specific details of other embodiments are included in the detailed description.

According to embodiments of the present invention, diabetic retinopathy can be effectively diagnosed by using specific biomarkers related to diabetic retinopathy, and substances for treating diabetic retinopathy can be screened.

Effects according to embodiments of the present invention are not limited to the contents exemplified above, and further various effects are included in the present specification.

Figure 1 is a graph confirming that mitochondrial prohibitin (PHB) decreases in high blood sugar through an experimental example of the present invention.

The advantages and features of the present invention and methods for achieving them will become clear with reference to the embodiments described in detail below. However, the present invention is not limited to the embodiments disclosed below and will be implemented in various different forms, and only the embodiments serve to ensure that the disclosure of the present invention is complete, and those skilled in the art It is provided to fully inform the person of the scope of the invention, and the present invention is only defined by the scope of the claims.

The terminology used herein is for describing embodiments and is not intended to limit the invention. As used herein, 'and/or' includes each and every combination of one or more of the mentioned items. Additionally, the singular form also includes the plural form unless specifically stated in the phrase. As used in the specification, 'comprises' and/or 'comprising' do not exclude the presence or addition of one or more other components in addition to the mentioned components. The numerical range indicated using '-' or 'to' indicates a numerical range that includes the values written before and after it as the lower and upper limits, respectively, unless otherwise specified. ‘About’ or ‘approximately’ means a value or numerical range within 20% of the value or numerical range stated thereafter.

Additionally, when describing the components of an embodiment of the present invention, terms such as first, second, A, B, (a), and (b) may be used. These terms are only used to distinguish the component from other components, and the nature, sequence, or order of the component is not limited by the term.

Unless otherwise defined, all terms (including technical and scientific terms) used in this specification may be used with meanings that can be commonly understood by those skilled in the art to which the present invention pertains. Additionally, terms defined in commonly used dictionaries are not interpreted ideally or excessively unless clearly specifically defined.

Also, in describing embodiments of the present invention, if detailed descriptions of related known configurations or functions are judged to impede understanding of the embodiments of the present invention, the detailed descriptions will be omitted.

In this specification, 'prevention' means suppressing or delaying the occurrence of symptoms or diseases in an individual who does not yet have symptoms or diseases but may develop such symptoms or diseases.

As used herein, ‘treatment’ refers to any action that improves or beneficially changes symptoms in an individual, such as (a) suppressing the development (worsening) of a symptom or disease, (b) alleviating or improving a symptom or disease. , or (c) means elimination of symptoms or disease.

In this specification, 'individual' or 'subject' means a cell, tissue, animal, or human for which a specific disease or condition is to be diagnosed, prevented, or treated using the present invention.

In this specification, 'diagnosis' refers to the act of determining whether or not a specific disease or condition has developed or the risk of developing it using the composition or kit of the present invention, as well as providing information related to the disease or condition, such as confirming the characteristics of the pathological state. It means all actions that can be done.

In this specification, 'possibility of disease' means both the possibility of developing a specific disease or disease and the possibility of developing it.

In this specification, 'biological sample' refers to the subject's blood, plasma, serum, cells, tissues, body fluids, saliva, urine, aqueous humor, anterior chamber fluid, etc.

In this specification, 'derived from' may mean not only separation from a specific object or part, but also the object or part itself.

As used herein, 'biomarker' refers to a peptide, polypeptide, nucleic acid, or protein that shows a significant increase or decrease in the expression level of a gene or protein in an individual with a specific disease or condition compared to a normal control group (an individual without a specific disease or condition). Includes organic biomolecules such as lipids, glycolipids, glycoproteins, and sugars (monosaccharides, disaccharides, oligosaccharides, etc.).

In this specification, 'control group' refers to normal cells or patients that do not have or are not caused by a specific disease or disease.

In this specification, 'level' may mean the mRNA or protein expression level of a specific factor, including a biomarker, or may also mean a content, concentration, etc. that can be confirmed by measuring or analyzing the abundance of a specific factor.

In this specification, general rules for naming amino acid sequences may be based on three-letter or one-letter amino acid codes unless there are specifically indicated exceptions. For example, the center of the amino acid structure is indicated by a three-letter code (e.g., Ala, Lys), and the D-stereotype (e.g., D-Ala, D-Lys) is specified by writing “D-” in front of the three-letter code. Unless otherwise indicated, the L-stereotype can be assumed. The amino acid residues that make up a protein or peptide may be natural or non-natural amino acid residues.

Hereinafter, embodiments of the present invention will be described in detail through manufacturing examples and experimental examples, but it is obvious that the effect of the present invention is not limited by the following experimental examples.

Experimental example: Biomarker analysis using Diabetic Retinopathy (DR) model

Experimental method

1) Cell model production and proteomic and metabolite analysis

Retinal pigment epithelial cells (ARPE-19) were obtained from ATCC (Manassas, VA). Retinal progenitor cells were donated by Professor Harold J. Sheeldo of the University of North Texas.

Cells were cultured in 100 mm dishes (Nalge Nunc International, Naperville, IL) at 37°C in a 5% CO ₂ incubator using Dulbecco's modified Eagle's medium (DMEM) with fetal bovine serum (10%) and penicillin/streptomycin (1%). and trypsinized (5-7 minutes at 37°C). Cells were subjected to oxidative stress under H ₂ O ₂ (200 μM) and intense light (7,000-10,000 lx, 1-24 hours) or constant light (700 lx, 48 hours) for 2-4 days, resulting in proteome and metabolite changes. observed.

Cells were disrupted by periodic sonication (3 x 5) using PBS and IP lysis buffer (25 mM Tris, 150 mM NaCl, 1 mM EDTA, 1% NP-40, 5% glycerol, and protease inhibitors) at 0 °C. , pH 7.4, 5 min) and centrifuged (10 min, 13,000 x g). The isolated proteins were separated by SDS-PAGE using Laemmli sample buffer (5X, 5% β-mercaptoethanol) and visualized (Coomassie blue (Pierce, IL) or silver staining).

2) Animal model preparation and proteome analysis

Male Wistar rats (250-350 g/rat, 8 weeks old, Charles River Laboratories) were randomly assigned to control or diabetic groups. All procedures followed Directive 2010/63/EU, NIH Directive, and ARVO Directive. Mice were induced to develop diabetes by injecting streptozotocin (STZ in 10 mM sodium citrate, 65 mg/kg, pH 4.5, Sigma, St. Louis, MO, USA), and blood glucose levels exceeding 250 mg/dl were considered hyperglycemia. was considered. It was confirmed through known literature that STZ administration is a proven model manufacturing method for inducing diabetic retinopathy (Chen-Yuan Gong et al, Streptozotocin induced diabetic retinopathy in rat and the expression of vascular endothelial growth factor and its receptor, Int J Ophthalomol, Vol. 6, No. 5, Oct.18, 2013, etc.). Two days after STZ injection, blood sugar was checked with a glucometer (Elite, Bayer, Portugal), blood was collected for glucose analysis, and animals were prepared as weight- and age-matched control and diabetic rats. Afterwards, protein and metabolite analysis was performed as described below.

3) Extraction and analysis of retinal proteins from donor eyes of diabetic retinopathy patients

Utah Eye Hospital and Georgia Eye Hospital donated eyes from patients with diabetic retinopathy. Diabetic patients and age-matched control eyes were enucleated and retinal proteins were extracted.

Retinas were dissected using phosphate-buffered saline (2.7mM KCl, 10mM Na ₂ HPO ₄ , 1.8mM KH _{2PO 4} , 137mM NaCl, pH 7.4, 4°C) and incubated in RIPA buffer (0.1% SDS, 1mM DTT, 50 mM Tris-HCl, 150 mM NaCl, 1 _{% Triton} Proteins in the supernatant were collected by sonicating and centrifuging (10 min, 16,000 Retinal proteins were analyzed.

Proteins separated on SDS-PAGE gels (8-16%) were transferred to PVDF membranes (Millipore, Billerica, MA, USA), and non-specific proteins were blocked using low-fat milk (5%) in Tris-buffered saline (TBS- T, 20mM Tris-HCl, 137mM NaCl, 0.1% Tween-20, pH 7.6, 1 hour, 25°C). The membrane was reacted with primary antibody (rabbit polyclonal, Genemed Synthesis, San Antonio, TX) at 4°C for 16 hours at room temperature, and after membrane washing (TBS-T, 0.5% low-fat milk, 1 hour), anti-mouse or anti-goat alkali. Incubation with phosphatase-conjugated IgG secondary antibody (1:10,000, GE Healthcare, Buckinghamshire, UK or 1:10,000 dilution, anti-rabbit, Agrisera, Vannas, Sweden) in TBS-T (1% low-fat milk, 1 hour, 25°C) The membrane was washed (TBS-T, 0.5% low-fat milk, 1 hour). Retinal proteins were imaged using chemifluorescence (ECF, GE) (Typhoon FLA 9000, GE Healthcare, Image Quant 5.0 software Molecular Dynamics, Inc., Sunnyvale, CA, USA). As comparison groups, β-actin (1:5,000, Sigma), β-III tubulin (1:5,000, Covance), and HRP-conjugated secondary antibody (1:7,000, anti-mouse, Santa Cruz Biotechnology, Santa Cruz, CA) were used. Quantitative analysis was performed using

Immunohistochemistry and immunocytochemistry techniques were used to analyze intracellular proteins. Cells were reacted with primary antibody (2 hours, 25°C), washed (PBS), and secondary antibody (1 hour, 25°C). Cell nuclei were analyzed using DAPI staining (1:5,000), and mitochondria were analyzed using Mito Tracker Red (250 nM). Coverslips were mounted on glass slides using Dako fluorescence mounting (Dako, Denmark), and cells were analyzed using a laser. Quantitative analysis was performed using a scanning confocal microscope LSM 710 META (Zeiss, Germany) and ImageJ.

4) Proteome and metabolome analysis methods

Pieces (1 mm ² cubes) cut from protein bands/spots (1D/2D) were used and incubated in Coomassie destaining buffer (200 μL of 50% MeCN in 25 mM NH ₄ HCO ₃ , pH 8.0, 20 min, 25 °C) or 30 °C. A silver decolorizing buffer containing 100 mM potassium ferricyanide (50%) and 100 mM sodium thiosulfate (50%) solution was used. The gel was dehydrated using acetonitrile (200 μL).

Diabetic retinopathy-related proteins were reduced (100 mM NH ₄ HCO ₃ , 10 mM DTT, 56 ℃, 30 minutes) and alkylated (100 mM NH ₄ HCO ₃ , 55 mM iodoacetamide, 20 minutes, 25 ℃, dark color). and trypsin reaction (13 ng/μL sequencing grade trypsin, Promega, 10 mM NH ₄ HCO ₃ , 10% MeCN, 37°C, 12 hours). Peptides were extracted with buffer (50 μL MeCN in 50% NH ₄ HCO ₃ , 5% formic acid, 20 min, 37 °C), dried, and dissolved in mass spectrometry sample buffer (5–10 μL, 5% in NH ₄ HCO _{3 ).} 75% MeCN, 1% trifluoroacetic acid). Organic matrix (alpha-cyano-4-hydroxycinnamic acid, 5 mg/mL, MW 189.04, Sigma-Aldrich, St. Louis, MO) buffer (50% MeCN, 50% NH4HCO3, 1% trifluoroacetic acid). and after centrifugation (13,000 Germany) 70-75% laser intensity and 100-300 shots were used. All spectra were analyzed using Flex analysis software for tryptic peptides (842.5099, 2211.105 Da).

Mascot software (Matrix Science) and proteins were searched using NCBI/SwissProt. A database was used according to the following criteria: 50 ppm mass tolerance, zero missing cleavages, carbamidomethyl cysteine, methionine oxidation, and a minimum peptide match of four. Protein identification was verified based on protein sequence coverage, using the number of matching peptides, MOWSE score, and tandem mass amino acid sequence, and the MOWSE score was expressed as a probability value to calculate -10logP.

More than 1,000 proteins were analyzed in the retina of normal eyes and donor eyes with diabetic retinopathy.

Search SwissProt (http://www.expasy.ch/spot/), HPRD (http://hprd.org) and Gene Ontology (GO) databases (http://www.geneontology.org), TargetP (cbs. Gene fusion using software such as dtu.dk/service/TargetP/), Psort (http://psort.ims.utokyo.ac.jp/), and STRING 11 (http://string-db.org/). (red), co-occurrence (dark blue), co-expression (black), binding experiment (purple), database (blue), text mining (lime) and homology (turquoise). .uth.edu/retnet/; RPGeNet 2.0; RD5000 DB; Retino Base) was used.

Diabetic retinopathy metabolites were analyzed with OmicsNet.ca software using KEGG (Kyoto Encyclopedia of Genes and Genomes) and PubChem accessions (https://pubchem.ncbi.nlm.nih.gov/rest/pug). To discover hidden interactions in diabetic retinopathy, we analyzed the degree of binding between proteins and metabolites.

Statistical values were expressed as the average of three independent experiments, and two-group comparisons were performed using a 2-tailed t-test. Multiple comparisons were assessed by ANOVA and P < 0.05 was considered statistically significant using the Tukey or Dunnet test where appropriate.

Experiment result

Figure 1 is a graph confirming that mitochondrial prohibitin (PHB) decreases in high blood sugar through experimental examples of cell models, animal models, and donor eyes of diabetic retinopathy patients.

It was confirmed that actin, tubulin βIII, and vimentin were changed in diabetic retinopathy. Tubulin βIII was significantly decreased in the GCL, INL, and RPE layers, and these changes indicate that mitochondria in diabetic retinopathy cells may be altered by actin, tubulin, and vimentin polymers.

As a result of comparative analysis of more than 1,000 retinal proteins in the proteome of diabetic retinopathy donor eyes with that of normal eyes, changes in PI3K-AKT, WNT protein, p53, VEGF, and HIF-1 proteins were confirmed in retinal cells of diabetic retinopathy. did. These changes in the proteome confirmed an increase in complement proteins related to rhodopsin/retinoid reproduction, mitochondrial structure, and insulin resistance.

The diabetic retinopathy-related biomarkers discovered in this experimental example and the changes in diabetic retinopathy for each biomarker are shown in Table 2 below.

No. Protein Gene MW pi change One Prohibitin PHB 29820 5.57 decrease 2 New protein A (CAC2PBS) CAC2 27756 5.37 increase 3 New protein B (VIMIII) VIMIII 47488 5.09 increase 4 New protein C (FAM81B) FAM81B 48781 6.78 increase 5 New protein D (ADAM18) ADAM18 135097 8.91 increase 6 Adenylate cyclase 4 ADCY4 118799 8.15 increase 7 Myogenic regulatory factor 2 MRF2 12630 9.75 increase 8 Vinculin VCL 116615 5.83 increase 9 T cell receptor beta TCRB 35227 8.78 decrease 10 Toll-like Receptor 7 TLR7 121299 6.38 increase 11 SH3 domain-binding protein 1 SH3BP1 74852 6.16 increase 12 Thioredoxin doamin containing protein 17 TXNDC17 14092 4.85 increase 13 Insulin like growth factor 2 receptor A IGF2R 174358 5.45 decrease 14 Junction plakoglobin JUP 81801 5.75 decrease 15 Microtubule-actin cross linking factor 1 MACF1 830743 5.29 increase 16 Dynamin-1like protein DNM1L 83908 6.64 increase 17 E3 ubiquitin-protein ligase RNF135 RNF135 46012 5.53 decrease 18 Regulator of G-protein signaling 3 CRA_d RGS3 68401 8.54 increase 19 Prohibitin 2 PHB2 33296 9.21 decrease 20 Activated protein C APC 56200 4.40 increase 21 Ras-related C3 botulinum toxin substrate 1 RAC1/2 21450 8.77 increase 22 RhoA RHOA 21768 5.83 increase 23 calcium/calmodulin-dependent protein kinase II alpha CAMK2A 54088 6.61 increase 24 Complement 3 C3 187148 5.75 increase 25 Disintegrin and metalloproteinase domain-containing protein 17 ADAM17 93021 5.6 increase 26 vascular cell adhesion molecule 1 VCAM1 81276 5.14 increase 27 Estrogen receptor alpha ESR1 66216 8.30 increase 28 Son of Sevenless homolog 1 SOS1 152464 6.38 increase

The four novel proteins were further analyzed using bioinformatics tools. New protein 1 was named CAC2PBS. New protein 2 was named disintegrin and metalloproteinase (ADAM18), new protein 3 was named vimentin variant (VIMIII), and new protein 4 was named FAM81B. Figures 2 to 5 show the amino acid sequences of new proteins A to D, respectively. In addition to these new proteins, prohibitin (PHB) and vinculin are new biomarkers for diagnosis and/or treatment of diabetic retinopathy. , VCL), tubulin beta III (TUBB3), E3 ubiquitin-protein ligase (RNF135), microtubule-actin cross-linking factor 1 (MACF1), TCRB protein (TCRB), tolllike receptor 7 precursor (TLR7), Insulin-like growth factor 2 receptor (IGF2R) and myogenic regulatory factor 2 (MRF2) were discovered.

In other words, the new biomarkers for diagnosis and/or treatment of diabetic retinopathy identified in this experiment are ADAM18, FAM81B, PHB, TXNDC17, ADCY4, VCL, DNM1L, RNF135, CAC2PBS, SH3BP1, MRF2, TLR7, TCRB, MACF1, JUP and IGF2, etc. These biomarkers of diabetic retinopathy show that mitochondrial protein trafficking, crystalline aggregation, ubiquitin-based protein degradation, and complement inflammatory response may correspond to the pathogenesis mechanisms of diabetic retinopathy.

In addition, the four new proteins discovered through this experimental example were confirmed to have the following functions, but it is not assumed that they are limited thereto.

ADAM18 regulates phosphorylation signals including EGFR, PI3K, and APC, regulates RAC1/2 and RHO through TGFA interactions, and regulates calcium signaling kinase IIα/β (CAMK2A/B) and calcium channels (CACNG2) through calcium/calmodulin. appears to be involved in one or more of the following: It appears to be indirectly involved in regulating estrogen receptor (ESR1) phosphorylation through the PI3K catalytic subunit (PIK3CA, p110) and regulatory subunit (PIK3R1, p85), and regulating RAC1, CDC42, and RHOA molecules through EGFR. In addition, it appears to be able to regulate CAMK and MYO through DLG1 and regulate ubiquitin concentration through ADAM18-UBE3A binding and ubiquitin ligase (E3A).

Additionally, the ADAM18 protein complex appears to be able to have bidirectional signaling depending on ADAM18 phosphorylation, the first being the RHO kinase pathway through ADAM18-TGFA-EGFR-RHOA and the second being the ADAM18-ESR1-PI3K pathway. -It is a PI3K-AKT signaling system leading to the RAC1-CDC42-RAC2 pathway.

The CCAC2PBS protein has a calcium-binding C2 domain and a phospholipid-binding switch, and appears to be involved in Ca ²⁺ concentration-induced phospholipid proteome formation.

VIMIII proteins appear to be able to build a cytoskeleton containing mitochondria along with actin microfilaments and intermediate filaments with microtubules. This protein is involved in neurogenesis and cholesterol transport and can regulate retinal cell adhesion, migration, and phosphorylation.

The FAM81B protein appears to be able to bind DNA.

The mechanisms of diabetic retinopathy confirmed through changes in the entire proteome of this experimental example as described above include changes in energy metabolism and tubulin phosphorylation, rhodopsin cycle changes and reduced retinoid concentration, mitochondrial death, angiogenesis reaction, apoptosis, and cholesterol changes. It can be seen as being related to at least one of the changes in lipid metabolism, turning on the retinal cell death switch, and increasing inflammation-producing markers.

Although the description has been made above with a focus on embodiments of the present invention, this is merely an example and does not limit the present invention, and those skilled in the art will be able to understand the present invention without departing from the essential characteristics of the embodiments of the present invention. It will be apparent that various modifications and applications not illustrated above are possible. For example, each component specifically shown in the embodiments of the present invention can be modified and implemented. And these variations and differences in application should be construed as being included in the scope of the present invention as defined in the appended claims.

Claims (5)

Includes an agent that measures the level of biomarkers related to Diabetic Retinopathy (DR),
The biomarkers include Activated protein C, Ras-related C3 botulinum toxin substrate 1, RhoA (Ras homolog family member A), and calcium/calmodulin-dependent protein kinase II. Containing at least one selected from the group consisting of alpha (calcium/calmodulin-dependent protein kinase II alpha), Complement 3, and vascular cell adhesion molecule 1.
Composition for diagnosing diabetic retinopathy. In claim 1,
The biomarker includes activated protein C.
Composition for diagnosing diabetic retinopathy. (a) measuring the level of a biomarker in a biological sample isolated from a subject;
(b) comparing the measured level to a control sample; and
(c) including the step of diagnosing the possibility of diabetic retinopathy if the measured level increases compared to the control sample,
The biomarkers include Activated protein C, Ras-related C3 botulinum toxin substrate 1, RhoA (Ras homolog family member A), and calcium/calmodulin-dependent protein kinase II. Containing at least one selected from the group consisting of alpha (calcium/calmodulin-dependent protein kinase II alpha), Complement 3, and vascular cell adhesion molecule 1.
Method of providing information for diagnosing diabetic retinopathy. In claim 3,
The biomarker includes activated protein C.
Method of providing information for diagnosing diabetic retinopathy. (a) processing the candidate material in the experimental model;
(b) measuring the level of biomarkers in the treated experimental model; and
(c) Comparing the measured level with a control model to determine whether the biomarker has decreased,
The biomarkers include Activated protein C, Ras-related C3 botulinum toxin substrate 1, RhoA (Ras homolog family member A), and calcium/calmodulin-dependent protein kinase II. Containing at least one selected from the group consisting of alpha (calcium/calmodulin-dependent protein kinase II alpha), Complement 3, and vascular cell adhesion molecule 1.
Screening method for substances for treating diabetic retinopathy.