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CN-122017104-A - Myopia risk detection method based on tear protein analysis

CN122017104ACN 122017104 ACN122017104 ACN 122017104ACN-122017104-A

Abstract

The application relates to a myopia risk detection method based on tear protein analysis. The method comprises the steps of detecting concentration values of target proteins in tears to be detected, giving discrete scores to each target protein according to concentration intervals in which the concentration values are located, accumulating the discrete scores of each target protein to obtain a total myopia risk score corresponding to tears to be detected, wherein the target proteins are determined through a tandem mass label technology and are differentially expressed according to different myopia degrees by combining a liquid chromatography-tandem mass spectrometry technology, the target proteins comprise one or more of tumor necrosis factor related apoptosis inducing ligands, chemokine ligands 21 ‌ and epidermal growth factors, the myopia risk grade represented by the concentration intervals is positively correlated with the discrete scores, and the total myopia risk score is positively correlated with myopia risks. According to the scheme provided by the application, the biological proteins with different expression aiming at different myopia degrees can be utilized to detect the myopia risk of the individual corresponding to the tears to be detected.

Inventors

  • YANG XIAO
  • XU CHENGSONG
  • Han Mengya

Assignees

  • 中山大学中山眼科中心

Dates

Publication Date
20260512
Application Date
20260130

Claims (10)

  1. 1. A method for detecting myopia risk based on tear protein analysis, comprising: Detecting the concentration value of target protein in tears to be detected; Assigning a discrete score to each target protein according to the concentration interval in which the concentration value is located; accumulating the discrete scores of each target protein to obtain a total myopia risk score corresponding to the tears to be detected; The target protein is determined by combining a tandem mass label technology with a liquid chromatography-tandem mass spectrometry technology and has differential expression for different myopia degrees, the target protein comprises one or more of tumor necrosis factor related apoptosis-inducing ligand, chemokine ligand 21 ‌ and epidermal growth factor, the myopia risk level represented in the concentration interval is positively correlated with discrete scores, and the myopia risk total score is positively correlated with myopia risks.
  2. 2. The method of claim 1, wherein the target protein further comprises one or more of ribosomal proteins, lysosomal associated proteins, and lipid metabolism associated proteins.
  3. 3. The myopia risk detection method according to claim 1, further comprising, before assigning a discrete score to each target protein according to the concentration interval in which the concentration value is located: A tear sample group and a myopia risk grading model are constructed, wherein the tear sample group comprises tear samples of a high myopia population, tear samples of a moderate myopia population, tear samples of a mild myopia population and tear samples of a normal refraction state population, and the number of the tear samples is greater than or equal to 50; determining a plurality of concentration intervals corresponding to each target protein by using the tear sample set and the myopia risk classification model, wherein different concentration intervals correspond to different myopia risk grades; The expression of the myopia risk classification model is as follows: ; Wherein, the Indicating the total score of myopia risks, wherein the total score of myopia risks of tear samples of high-myopia people, tear samples of moderate-myopia people, tear samples of mild-myopia people and tear samples of normal refractive state people is decreased, A weight coefficient indicating a target protein numbered i in the tear sample, Concentration data representing the target protein numbered i in the tear sample, Representing an intercept term.
  4. 4. A method of detecting myopia according to claim 3, wherein determining a plurality of concentration intervals for each target protein using the tear sample set and the myopia risk classification model comprises: Collecting concentration data of target proteins in a tear sample group; training the myopia risk classification model by using the concentration data to obtain a weight coefficient and an intercept term in the myopia risk classification model; Generating a subject work profile based on the intercept term; And determining an optimal cut-off point on the working characteristic curve of the subject according to the about dengue index so as to obtain a demarcation value of a plurality of concentration intervals corresponding to each target protein.
  5. 5. The method of claim 4, wherein collecting concentration data of the target protein in the tear sample set comprises: Quantitatively detecting a tear sample group to obtain a target protein concentration value; Generating a target protein concentration vector based on the target protein concentration value; And carrying out standardization treatment on the target protein concentration vector by using a reference mean value and a standard deviation of a tear reference group to obtain target protein concentration data of standardized expression, wherein the tear reference group is a tear sample group of a crowd in a normal refraction state.
  6. 6. The method according to claim 4, wherein determining the optimal cutoff point on the subject's working characteristic curve according to the about-log index to obtain the demarcation values of the plurality of concentration intervals corresponding to each target protein comprises: Determining an optimal cutoff point on a working characteristic curve of the subject according to the about log index to generate a first threshold value and a second threshold value corresponding to each target protein; The first threshold is a demarcation value for distinguishing a low myopia risk concentration interval from a medium myopia risk concentration interval, and the second threshold is a demarcation value for distinguishing a medium myopia risk concentration interval from a high myopia risk concentration interval.
  7. 7. The method for detecting myopia according to any of claims 1-6, wherein, Aiming at the tumor necrosis factor related apoptosis-inducing ligand, the concentration interval corresponding to low myopia risk is [0-0.50 ] mug/L, the concentration interval corresponding to medium myopia risk is [ 0.50-1.50) mug/L, and the concentration interval corresponding to high myopia risk is [1.50 ] )μg/L; Aiming at chemokine ligand 21 ‌, the concentration interval corresponding to low myopia risk is [0-0.20 ] mug/L, the concentration interval corresponding to medium myopia risk is [ 0.20-0.60) mug/L, and the concentration interval corresponding to high myopia risk is [0.60 ] )μg/L; Aiming at the epidermal growth factor, the concentration interval corresponding to low myopia risk is [0-0.30 ] mug/L, the concentration interval corresponding to medium myopia risk is [ 0.30-1.00) mug/L, and the concentration interval corresponding to high myopia risk is [1.00 ] )μg/L。
  8. 8. The method for detecting myopia risk according to claim 1, further comprising, prior to detecting the concentration value of the target protein in the tear fluid to be detected: And screening target proteins from a plurality of biological proteins contained in tears by utilizing a tandem mass label technology and a liquid chromatography-tandem mass spectrometry technology, wherein the target proteins are differentially expressed according to different myopia degrees.
  9. 9. The method of claim 8, wherein the screening target proteins from a plurality of biological proteins contained in tears comprises: Constructing a tear sample group, wherein the tear sample group comprises tear samples of a high myopia population, tear samples of a moderate myopia population, tear samples of a mild myopia population and tear samples of a population with normal refraction state; preprocessing tear samples in a tear sample group to obtain a sample peptide solution; mixing ‌ tandem mass spectrum tag 16 re-labeling reagent with the sample peptide solution, and placing the mixture in a preset environment for reaction for a preset period of time to obtain a labeling solution; Adding a stopping solution into the marking solution to stop the reaction, so as to obtain a solution to be separated; Performing tandem mass spectrum tag fractionation operation ‌ on the solution to be separated to obtain a separation sample; Performing mass spectrometry on the separated sample by a liquid chromatography-tandem mass spectrometry technique; and determining the target protein according to mass spectrum comparison results of tear samples with different myopia degrees.
  10. 10. The myopia risk detection method according to claim 9, wherein the preprocessing comprises: Carrying out high-pressure assisted reduction and alkylation treatment on the tear sample to obtain a first sample; carrying out enzymolysis on the first sample by adopting a double-enzyme collaborative digestion strategy to obtain a second sample; And sequentially carrying out desalting operation, centrifugal concentration operation and redissolution operation on the second sample to obtain a sample peptide fragment solution containing a plurality of small molecule peptide fragments.

Description

Myopia risk detection method based on tear protein analysis Technical Field The application relates to the technical field of myopia risk detection, in particular to a myopia risk detection method based on tear protein analysis. Background Myopia is a worldwide high-rise ophthalmic disease and presents a rapid rise in the childhood and adolescent population, and has become a major public health problem affecting public eye health. The pathogenesis of myopia in the eyes is not completely understood in the childhood and adolescent population. In current risk assessment techniques for myopia, the diagnostic method to determine whether a patient is myopic is more dependent on measurements of diopter and eye axis length. At present, although the method for managing myopia by relying on structural indexes such as diopter, eye axis length and the like is simple and convenient clinically, the method is essentially passive record of formed lesions, molecular dynamics cannot be reflected before morphological change, and individual progression risk is difficult to predict. In other words, structural indicators such as diopter, eye axis length, and the like are neither early biomarkers for myopia progression nor provide a dynamic means of monitoring disease progression clinically. Therefore, the development of biomarker detection systems that can identify risk early, monitor progress dynamically, and reveal mechanisms has become an urgent need for ophthalmic precision medicine. Tears, which are non-invasively obtained ocular surface secretions, are rich in proteins associated with ocular health, whose component changes can directly reflect the local microenvironment state, and protein mass spectra in tears may be closely related to the progression of myopia, are a very potential marker source. However, studies on tear proteomics and myopia are not sufficient at present, and a need exists for the search for new biomarkers. Traditional protein analysis techniques, such as enzyme-linked immunosorbent assay (ELISA, enzyme Linked Immunosorbent Assay), although widely used in biomarker detection, show significant drawbacks in terms of sensitivity and sample size requirements. At present, the enzyme-linked immunosorbent assay is widely used for the quantification of specific proteins due to the standardized operation, and the detection is realized by a double-antibody sandwich structure and an enzymatic chromogenic reaction based on the principle of antigen-antibody specific binding. Although the method is used for detecting certain conventional inflammatory factors such as lactoferrin in tears, the limitation is remarkable when the method is applied to myopia-related low-abundance protein screening, the contradiction is mainly that firstly, the sensitivity is usually in the order of picograms to nanograms per milliliter, the extremely low-concentration regulatory protein in tears is difficult to capture effectively, secondly, tens of microliter samples are needed for single detection, the acquired quantity of tears of children is often less than ten microliter, the sample quantity becomes a hard bottleneck, thirdly, the tear components are complex, the stability of solid-phase coated antibodies is easy to interfere, the nonspecific binding or signal attenuation is caused, fourthly, the antibody reagent is easy to inactivate, the shelf life is short, and the requirement of large-scale application on stability is difficult to meet. In short, ELISA methods generally have low detection sensitivity and high sample size requirements, which limit their effectiveness in low concentration biomarker detection in practical applications. Furthermore, ELISA methods mostly rely on antigen-antibody binding reactions, usually performed on solid phase surfaces. Although relatively simple and economical to operate, the accuracy of detection by this method is limited by the stability of the reagents and platform. The stability problem of the kit, especially the transience of the shelf life, is a bottleneck restricting the popularization and clinical application of ELISA technology. For a kit needing long-term storage, the defects of stability and anti-interference capability of the reagent often lead to the performance reduction of the kit, and influence the accuracy and reliability of a detection result. In order to solve the problems, the invention adopts a novel technology of combining a tandem mass label technology (TMT, tandem Mass Tag) with a liquid chromatography-tandem mass spectrometry technology (LC-MS/MS) to carry out comprehensive proteomics analysis on tear samples of children and teenager groups, and provides a novel technical approach for early diagnosis of myopia and disease monitoring. The method can obtain more accurate and efficient detection results under lower sample size, and has higher clinical application value. Compared with the traditional ELISA method, the TMT technology has higher sensitivity and wider application r