Genetic locus marker combination for diagnosis or prognosis evaluation of keloid susceptible population as well as detection method and application of genetic locus marker combination

Abstract

The invention discloses a genetic locus marker combination for diagnosis or prognosis evaluation of keloid susceptible population as well as a detection method and application of the genetic locus marker combination, and belongs to the field of detection, and genetic loci comprise the following loci: rs873549, rs1442440, rs2271289, rs17431184 and rs2299939. According to the invention, the genetic susceptibility of Keloid keloid in North China can be comprehensively predicted according to genotype detection results of the selected five gene loci. Therefore, targeted treatment on the patient is achieved, and the curing possibility of the patient is improved.

Description

Technical Field

[0001] This invention relates to the field of biological detection, and more particularly to a combination of genetic locus markers for the diagnosis or prognostic assessment of keloid-prone populations, as well as their detection methods and applications. Background Technology

[0002] Keloids are benign fibroproliferative skin tumors. During wound healing, functional impairment causes fibrous growth of the skin, resulting in keloids that can grow larger than the original wound and persist for years. Genetic factors are considered an important cause of keloids, and individuals with a predisposition to keloid formation have a certain familial tendency to develop them.

[0003] Studies have found that rs2299939 and rs17431184 in the PTEN gene are significantly associated with keloids.

[0004] PTEN, located on chromosome 10q23.3, consists of 9 exons and encodes a 403-amino acid protein with phosphatase activity. PTEN protein can inhibit tumor development and progression by antagonizing the activity of phosphorylases such as tyrosine kinase. In a study of 400 keloid cases, individuals with the A allele in the rs2299939 genotype had a lower risk of keloids than those without the A allele. The CC genotype of rs2299939 was a risk factor for keloids, and these patients had a lower incidence of the AC / TC haplotype. Individuals with the C allele in the rs17431184 genotype had a lower risk of keloid scarring (KD) than those without the C allele.

[0005] In another genome-wide association study (GWAS), based on the results of 714 patients (Han Chinese) and 2944 healthy controls, three SNPs were found to be significantly associated with keloids in the Han Chinese population: 1q41 (rs873549, rs1442440), 15q21.3 (rs2271289). rs2271289 is located on the NEDD4 gene. NEDD4 negatively regulates TGF-β signaling through ubiquitin-mediated SMAD4 degradation, and TGF-β promotes type I collagen synthesis and inhibits collagenase transcription. Therefore, abnormalities in these signaling pathways may lead to pathological wound healing.

[0006] Current research has explored the linkage between disease susceptibility genes and the 15q22.31-q23 and 18q21.1 regions in a keloid pedigree from a specific region in China. Other studies have shown that susceptibility loci in a particular region abroad are located in the 2q23 region, while some studies have found them in the 7pl1 region. This indicates that keloids exhibit genetic heterogeneity, and disease susceptibility loci may differ across races, ethnicities, and regions. There is currently a research gap regarding genetic markers for keloids in North China.

[0007] Currently, cosmetic procedures such as laser treatment, injectable fillers, and surgical excision can all be contributing factors to keloid formation. For susceptible individuals, even minor skin trauma can trigger abnormal scarring reactions, significantly diminishing cosmetic results and even causing severe psychological distress. There is a lack of reliable biomarkers or clinical scoring systems to accurately predict an individual's risk of developing keloids. Existing assessments largely rely on empirical judgment and lack objective quantitative indicators. Emerging technologies such as genomics and proteomics have not yet been translated into clinically usable predictive tools. Most clinical studies focus on Caucasians, lacking differentiated research on the skin biology characteristics of different races, leading to some treatment regimens being ineffective in Asian or African populations. Summary of the Invention

[0008] Purpose of the invention

[0009] To overcome the above shortcomings, the present invention aims to provide a combination of genetic locus markers for the diagnosis or prognostic assessment of keloid-prone populations in North China, along with their detection methods and applications. Five loci—rs2299939, rs17431184, rs873549, rs1442440, and rs2271289—are selected as Keloid SNP detection loci. Keloid SNPs specific to North China are screened to construct a predictive model for susceptible populations. A comprehensive prediction algorithm is established to facilitate the interpretation of detection results, thereby enabling targeted treatment of patients and improving the likelihood of a cure.

[0010] Solution

[0011] To achieve the objectives of this invention, the technical solution adopted is as follows:

[0012] In a first aspect, the present invention provides a combination of genetic locus markers for diagnosing or prognostically assessing keloid-prone individuals, the genetic loci including the following loci: rs873549, rs1442440, rs2271289, rs17431184, and rs2299939.

[0013] Furthermore, the genotypic expression at each point is as follows:

[0014] The risk factor for rs873549 is expressed as allele C;

[0015] The risk factor for rs1442440 is expressed as allele T;

[0016] The risk factor for rs2271289 is expressed as allele T;

[0017] The risk factor for rs17431184 is expressed as allele T;

[0018] The risk factor for rs2299939 is expressed as allele C;

[0019] Optionally, the sample for detecting the genetic locus is blood.

[0020] In a second aspect, a primer combination for detecting genotyping of individuals susceptible to keloids is provided, including specific primer pairs for detecting rs873549, rs1442440, rs2271289, rs17431184, and rs2299939 loci, respectively; optionally, it includes combinations of primers as shown in SEQ ID NO:1 to 10, respectively.

[0021] Thirdly, a primer combination for detecting keloid-related gene typing in blood is provided, including specific primer pairs for detecting rs873549, rs1442440, rs2271289, rs17431184, and rs2299939 loci, respectively; optionally, it includes combinations of primers as shown in SEQ ID NO:1 to 10, respectively.

[0022] Fourthly, this invention provides the application of genotyping of genetic locus markers in susceptible populations in the preparation of kits or analytical systems for the diagnosis or prognostic assessment of keloid-susceptible populations; wherein the combination of genetic locus markers includes rs873549, rs1442440, rs2271289, rs17431184, and rs2299939.

[0023] Optionally, the test subject can be genotyped by detecting rs873549, rs1442440, rs2271289, rs17431184, and rs2299939 related genes.

[0024] Fifthly, a non-diagnostic detection method is provided for a combination of genetic locus markers in keloid-prone populations. The combination of genetic locus markers includes rs873549, rs1442440, rs2271289, rs17431184, and rs2299939. The primer combination described in the second aspect is used to detect the relevant genotypes at each locus.

[0025] Sixthly, an analytical system is provided for diagnosing or assessing the prognosis of keloid-prone populations in North China. This system includes a data analysis module, which collects genotyping data related to genetic loci of the keloid-prone population to be predicted, using genotype as input features. The system also calculates a predicted value based on the genotyping data to determine whether the target individual is keloid-prone.

[0026] Optionally, the genotype assignment method includes allele scoring methods, with risk factors assigned a score of 1 and protective factors assigned a score of 0, wherein:

[0027] The risk factor for rs873549 is allele C, and the protective factor is allele T.

[0028] The risk factor for rs1442440 is allele T, and the protective factor is allele C.

[0029] The risk factor for rs2271289 is allele T, and the protective factor is allele C.

[0030] The risk factor for rs17431184 is allele T, and the protective factor is allele C.

[0031] The risk factor for rs2299939 is allele C, and the protective factor is allele T.

[0032] Seventhly, a predictive system for diagnosing or assessing susceptibility to keloids is provided. Using the genotype of the target individual as input features, the system calculates a predicted value indicating whether the target individual is susceptible to keloids. The model prediction formula is as follows:

[0033] glm(formula=shaixuanhou_data$group~0.5911*rs873549+0.9331*rs1442440-0.1447*rs2271289+16.1030*rs17431184+(-15.9701)*rs2299939, family=binomial, data=shaixuanhou_data);

[0034] Among them, rs873549, rs1442440, rs2271289, rs17431184, and rs2299939 are the relevant genotypes of each indicator in the blood of the target subject to be predicted;

[0035] Optionally, individuals are considered susceptible to keloids if the predicted value is greater than 0.437; otherwise, they are not.

[0036] Furthermore, the genotypes of rs873549, rs1442440, rs2271289, rs17431184, and rs2299939 were analyzed. Genotyping and allele assignment methods included [methods not specified in the original text]. Risk factors were assigned a score of 1, and protective factors were assigned a score of 0.

[0037] The risk factor for rs873549 is allele C, and the protective factor is allele T.

[0038] The risk factor for rs1442440 is allele T, and the protective factor is allele C.

[0039] The risk factor for rs2271289 is allele T, and the protective factor is allele C.

[0040] The risk factor for rs17431184 is allele T, and the protective factor is allele C.

[0041] The risk factor for rs2299939 is allele C, and the protective factor is allele T.

[0042] Optionally, the sample for detecting the genetic locus is blood.

[0043] Eighthly, a kit is provided for the diagnosis, efficacy or prognosis assessment, or related drug evaluation in keloid-prone populations, said kit comprising a combination of genetic locus markers and / or their detection reagents as described in the first aspect.

[0044] This invention involves extracting nucleic acids from collected blood samples using a specific method, followed by multiplex PCR amplification and Sanger sequencing. With the aid of primers, multiplex PCR amplifies all target gene loci in a single reaction well. Sanger sequencing is then used to sequence the amplified sequences, obtaining the specific bases at each locus. The gene detection results are then input into a Keloid algorithm model, which serves as a sequencing score prediction model. The Keloid sequencing prediction analysis software is a Keloid keloid prediction software developed using machine learning algorithms to comprehensively analyze and model five scar-related gene loci indicators from 100 Keloid keloid patients and a control group. This software can comprehensively predict the genetic susceptibility to Keloid keloids based on genotype detection results, thereby enabling targeted treatment and increasing the likelihood of a cure.

[0045] Beneficial effects

[0046] (1) This invention establishes a detection kit and method for keloid-prone populations in North my country, specifically targeting relevant gene loci. Furthermore, it categorizes the clinical significance of different genotypes based on clinical diagnostic results, including susceptibility factors and protective factors. By constructing a comprehensive scoring system, integrated analysis can be performed based on the detected genotypes, which is of great significance for assisting in the detection and treatment of keloids. This solves the current difficulties in clinical diagnosis of keloid-prone populations and fills a gap in this clinical testing field in North China. The scoring system of this invention resolves the difficulties in clinical interpretation caused by inconsistent individual results, enabling multi-gene locus risk prediction for keloids and contributing to personalized prevention and treatment.

[0047] (2) In this invention, one reaction well can perform PCR reactions targeting five sites: rs2299939, rs17431184, rs873549, rs1442440, and rs2271289. The operation is simple and cost-effective. The primer design of this invention includes specific primer segments and universal primer segments. Universal primers ensure consistent amplification efficiency of the detection system, while specific primers ensure the specificity of the detection results, greatly improving the accuracy of the detection results. Attached Figure Description

[0048] One or more embodiments are illustrated by way of example with reference to the accompanying drawings, and these illustrative examples are not intended to limit the embodiments. The term "illustrative" as used herein means "serving as an example, embodiment, or illustration." Any embodiment illustrated herein as "illustrative" is not necessarily to be construed as superior to or better than other embodiments.

[0049] Figure 1A keloid susceptibility scoring model was established based on five gene loci highly associated with keloid-prone populations and clinical diagnostic data from this invention.

[0050] Figure 2 The present invention uses the combined prediction of rs873549, rs1442440, rs2271289, rs17431184, and rs2299939 at each point to predict the predicted ROC curve in keloids. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] Furthermore, to better illustrate the present invention, numerous specific details are provided in the following detailed embodiments. Those skilled in the art should understand that the present invention can be practiced without certain specific details. In some embodiments, materials, elements, methods, and means well known to those skilled in the art are not described in detail in order to highlight the spirit of the invention.

[0053] Unless otherwise expressly stated, throughout the specification and claims, the term "comprising" or its variations such as "including" or "comprises" shall be understood to include the stated elements or components without excluding other elements or other components.

[0054] All raw materials used in this invention are commercially available. Primers were synthesized by a biotechnology company.

[0055] This invention involved exome sequencing of eight individuals from a typical keloid family, including three patients and five carriers. Reference libraries included the 1000 Genomes SNV database, the Known Tumor Mutation Database (COSMIC), the Gene Variation and Clinical Phenotype Database (ClinVar), the Variance Database (esp6500), the ExAC_ALL database, the dbSNP147 database, and the GWAS Catalog, allowing for multi-level combined screening of variant results. Furthermore, the gene structures of the variant sites were annotated using the ENCODE database, targetScanS, and wgRNA, with gene types primarily including mRNA, microRNA, and snoRNA. Analysis revealed that in the exon region, 50.30% of SNVs were synonymous mutations, which do not affect the function of the corresponding gene product; 46.87% of SNVs were nonsynonymous mutations, which will affect the function of the gene product; other SNVs will lead to the emergence of new terminators (stopgain) or the disappearance of the original terminator (stoploss), which also have a certain impact on the function of the gene product.

[0056] This invention performed differential analysis on SNVs obtained from samples of keloid families to screen for specific SNV loci. Ultimately, 27 functional loci were identified, corresponding to 23 potential genes associated with keloids. Further validation was conducted in other families and sporadic cases, ultimately selecting rs873549, rs1442440, rs2271289, rs17431184, and rs2299939 as a combination of keloid-specific genetic locus markers.

[0057] This invention, through a retrospective analysis of hundreds of Keloid keloid samples from Beijing Jishuitan Hospital, screened for keloid-related gene loci polymorphism genotypes specific to North my country and analyzed the odds ratio (OR) for different genotypes. An OR value greater than 1 indicates a risk factor; an OR value less than 1 indicates a protective factor; and an OR value equal to 1 indicates that the factor has no effect on the development of the disease.

[0058] Calculate the OR value:

[0059]

[0060] Table 1. OR values ​​for each point

[0061] Based on the genotyping characteristics of different loci (rs2299939, rs17431184, rs873549, rs1442440 and rs2271289) in Table 1, the present invention designed and screened the following primers, as shown in Table 2.

[0062] Table 2. Primer pairs for amplification and sequencing of polymorphisms at different sites.

[0063]

[0064] The working solution concentration of each primer in Table 2 is 200 nM, but other concentrations are also possible, such as those in the range of 50–400 nM.

[0065] The composition of the PCR and sequencing kits of the present invention is shown in Table 3. The kit specifications are 50 doses / box.

[0066] Table 3. Components of PCR and Sequencing Kits

[0067]

[0068] This invention uses human genomic DNA as a template, prepares an amplification reaction system for PCR amplification to obtain PCR products, performs Sanger sequencing on the PCR products, analyzes the Sanger sequencing results, and assigns values ​​to the sequencing results of 5 loci to determine whether they are risk factors or protective factors. After assignment, the results are imported into predictive analysis software for integration, yielding a comprehensive and instructive result. Some operational methods are as follows:

[0069] The PCR amplification system includes: sample DNA, amplification reaction solution, and working primer solution (primer pairs for rs2299939, rs17431184, rs873549, rs1442440, and rs2271289 sites). The PCR amplification reaction system can be: 2 μL working primer solution (10 μM), 12.5 μL amplification reaction solution, and 5.5 μL purified water, for a total volume of 20 μL.

[0070] The amplification procedure is as follows:

[0071]

[0072] Add 20 μL of the prepared PCR amplification reaction solution to 5 μL of extracted human genomic DNA (20 ng / μL) and perform PCR amplification.

[0073] Product purification: After PCR amplification, take 5 μL of the PCR product and perform 1-2% agarose gel electrophoresis to observe whether the target band is amplified (target band size is 500 bp). If the target band is observed, purify the PCR product promptly. For detailed instructions, refer to the PCR product purification kit manual (FastPure Gel DNA Extraction MiniKit, catalog number: DC301-01). Identify and determine the concentration of the purified PCR product using electrophoresis (PCR product concentration range is...).

[0074] 10-50 ng), can be used immediately for sequencing PCR or stored at -20±2℃ for later use (storage time should not exceed 2 days).

[0075] Sequencing PCR: Prepare the sequencing PCR system according to the table below using the PCR products identified and determined by electrophoresis.

[0076] reagents Dosage PCR products XμL (approximately 3-10ng) BigDye 2μL BigDye Sequencing Buffer 3μL Sequencing primers 1μL RNase-Free ddH2O 14-XμL Total volume 20μL .

[0077] The qualitative PCR reaction conditions are shown in the table below:

[0078] Sequencing preparation:

[0079] (1) Take the PCR reaction tubes after the sequencing PCR reaction is completed, and add 2 μL of 125 mmol / L EDTA and 2 μL of 3 mol / L sodium acetate (pH 5.2) to the bottom of each PCR reaction tube.

[0080] (2) Add 50 μL of 100% anhydrous ethanol, tighten the cap, shake briefly, and let stand at room temperature away from light for 15 minutes.

[0081] (3) Centrifuge at 12000rpm for 30 minutes at 4℃, and carefully remove the supernatant immediately (if you cannot do it immediately, please centrifuge again for 3 minutes before operation).

[0082] (4) Add 150 μL of pre-cooled 70% ethanol to each tube, centrifuge at 12000 rpm for 10 minutes at 4°C, and carefully remove the supernatant immediately (try to remove the 70% ethanol from the bottom of the tube as much as possible. If you cannot operate immediately, centrifuge again for 3 minutes before operation). This step can be repeated once.

[0083] (5) Place at room temperature away from light for 15-30 minutes (observe the liquid at the bottom of the tube to ensure that 70% ethanol evaporates completely). The product from this step can be sealed and stored at -20±2℃ for 5 days away from light.

[0084] (6) Add 10 μL Hi-Di Formamide, shake briefly to dissolve DNA, and centrifuge briefly to remove all liquid from the tube wall to the bottom of the tube.

[0085] (7) After dissolving, the sample is denatured at 95°C for 5 minutes on a qualitative PCR instrument, then quickly placed on ice to cool for 4 minutes before being loaded for electrophoresis.

[0086] Gene sequencing analyzer:

[0087] (1) Sample loading: Add the denatured sequencing products to a 96-well plate compatible with the gene analyzer, close the plate, and edit the sample list according to the loading order. Select either Seq_std_BDTV3.1_ASSYXL_POP7 or Seq_std_BDTV3.1_ASSY_POP7 with the IVD label for sequencing, depending on the sequencer model.

[0088] (2) When using the ABI gene analyzer, use ABI's Data Collection and Sequencing Analysis software for data collection and analysis. For further information on the Data Collection and Sequencing Analysis software, please refer to the Data Collection and Analysis Software User Manual. Sequencing results are automatically saved in a preset location. After the reaction is complete, open the sequencing results for analysis to obtain files in .ab1 and .phd.1 formats.

[0089] Results analysis:

[0090] (1) Run the SeqScanner program and import the sequencing results.

[0091] (2) Sequencing results. Use software to compare the wild-type sequence base by base to find mutation points and record the type of mutated base.

[0092] (3) After assigning values ​​to the gene detection results at each locus, the results are imported into the sequencing prediction and analysis model. Then, the software comprehensively predicts and evaluates the genetic susceptibility of Keloid scars based on the genotype detection results.

[0093] Example 1: Reagent Kit Performance Validation

[0094] The performance of this method was validated using the "Reference Product for Detection of Polymorphisms at rs2299939, rs17431184, rs873549, rs1442440, and rs2271289 Loci". All samples underwent nucleic acid extraction using the MGI Bio-Column Method Universal DNA Extraction Kit (product number: IVD3018). The obtained DNA samples were diluted to 20 ng / μL and stored at 2–8℃; if samples are not intended for long-term use, they can be stored at -20℃.

[0095] Sequence information for "Reference Samples for Polymorphism Detection of rs2299939, rs17431184, rs873549, rs1442440, and rs2271289 Loci":

[0096] rs2299939: Polymorphic site at position 38955 in NCBI accession number NG_007466.2

[0097] rs17431184: A polymorphic site at position 102056 in NCBI accession number NG_007466.2.

[0098] rs873549:NC_000001.11:g.222098425

[0099] rs1442440:NC_000001.11:g.222066192

[0100] rs2271289: Polymorphic site at position 74152 in NCBI accession number NG_051072.1

[0101] Table 4. Reference Material Information

[0102]

[0103] The above reference samples were tested according to the PCR and sequencing methods described above, where P1-P15 are accuracy reference samples; P16 is a specificity reference sample; DP1-DP5 are sensitivity reference samples; and C1-C5 are precision reference samples (5 tests per sample).

[0104] The test results are shown in Table 5.

[0105] Table 5. Test results of reference samples

[0106]

[0107] The results in Table 5 show that the kit of the present invention can detect mutation sites at various points and has high sensitivity, specificity, accuracy and repeatability.

[0108] Establish a predictive analysis system for keloid-prone populations:

[0109] This invention is based on a multivariate logistic regression algorithm, which calculates binary classification probabilities to establish a scoring model for predicting keloid-prone populations.

[0110] First, prepare the data matrix to be analyzed. Use the ggcorrplot and pheatmap tools in R to calculate the correlation coefficients (i.e., the pairwise correlation between various indicators of keloids) using the cor() function. Then, use the corrplot package for visualization (e.g., ...). Figure 1 Intergroup correlation analysis.

[0111] Secondly, the data was preprocessed to check its integrity. Using the allele results of five keloid loci as input and disease status as the dependent variable, the raw data was correctly coded and initially screened. Data in the control group with a difference greater than 0.55 between predicted and actual values ​​were removed as outliers. Stratified sampling was then used to divide the dataset into training and test sets in an 8:2 ratio. A multivariate logistic regression model was then constructed and trained. The trained model was used to calculate the probability of each sample belonging to the case group on the test set. Subsequently, the model performance was evaluated using different performance metrics, including the AUC value (area under the ROC curve). An AUC value between 0.5 and 1 indicates that the predictive model performs better than random guessing; the closer the AUC is to 1, the better. The model's prediction for each sample is a probability value. An optimal cutoff point was obtained from the ROC curve as the desired cutoff value. The found cutoff value indicates that the model has at least one threshold that can accurately separate data above and below the threshold.

[0112] 2. Results Analysis

[0113] By conducting genetic locus detection of keloids in North China on blood samples from 49 keloid patients who visited Beijing Jishuitan Hospital in 2022 and 50 healthy volunteers (all subjects were from North China), the detection method, assignment method and predictive scoring method described in this invention have high predictive value for the disease.

[0114] The formula for the multivariate logistic regression model obtained by this invention is as follows:

[0115] pre=0.5911*rs873549+0.9331*rs1442440-0.1447*rs2271289+16.1030*rs17431184+-15.9701*rs2299939

[0116] A score >0.437 indicates a predisposition to keloid formation; otherwise, it indicates no risk.

[0117] Using the genotypes of each locus (rs873549, rs1442440, rs2271289, rs17431184, rs2299939) as input variables, the presence or absence of keloids as the dependent variable, and the predicted probability of keloid formation as the output, a logistic multivariate regression analysis was performed to obtain a model for predicting keloid formation. The data distribution and model performance were calculated, and the AUC value of the model was tested. The ROC curve results are shown below. Figure 2 .

[0118] Modeling based on nearly 100 samples and Figure 2 The results show that the keloid risk gene detection method and scoring method described in this invention, with 0.437 as the optimal threshold (specificity 0.625, sensitivity 0.725), can effectively indicate the risk level of keloid patients (AUC value 0.743).

[0119] Existing research has shown that rs2299939 and rs17431184 in the PTEN gene are significantly associated with keloids. Another genome-wide association study (GWAS) suggests that 1q41 (rs873549, rs1442440) and 15q21.3...

[0120] (rs2271289) was significantly associated with keloids. Therefore, the indicators mentioned in the literature were validated using the above-mentioned 99 clinical samples (49 case group and 50 control group samples).

[0121] The results showed that the AUC of the combined detection of rs17431184 and rs2299939 was 0.517. The AUC of the combined detection of rs873549, rs1442440, and rs2271289 was 0.729, with 0.471 as the optimal threshold (specificity 0.675, sensitivity 0.650). Although the combined diagnosis of the three loci has some predictive value for keloid susceptibility, its sensitivity and diagnostic efficacy are relatively low, far lower than the AUC (0.743), sensitivity, and specificity of the combined diagnosis of the five genetic locus markers (rs17431184, rs2299939, rs873549, rs1442440, and rs2271289) proposed in this application.

[0122] Real sample testing

[0123] Ten samples were selected from both the case group and the control group. Using the allele detection method proposed in this invention and the data processing and analysis methods described herein, the detection results are shown in Table 6.

[0124] Table 6. Detection values ​​and analysis results of samples from 10 keloid patients and 10 healthy volunteers.

[0125]

[0126] In the aforementioned 20 samples (10 keloid patients and 10 healthy volunteers), the detection results of this kit showed 100% coverage compared to next-generation sequencing results. Using the scoring system of this invention, a comprehensive assessment of five loci can be effectively performed, improving patient consultation efficiency and effectively assisting clinical practice in predicting the risk of keloid-prone populations, thus possessing significant clinical value.

[0127] The detection time of the kit of this invention is 24 hours (detection cycle 3 working days), while the detection time of next-generation sequencing is 96 hours (detection cycle 15 working days). The kit of this invention has a significant advantage in saving time and costs. The detection cost of the kit of this invention is 80 yuan, while the detection cost of next-generation sequencing is 2000 yuan. The kit of this invention has a significant advantage in saving economic costs (as shown in the table below).

[0128] Table 7. Comparison of the detection kit of the present invention with other methods

[0129] Detection methods Detection sites Testing cycle Testing costs Operational complexity Quick rating analysis NGS method comprehensive Slow, 15 working days High, 2000 yuan complex none This invention Related sites Quickly, within 3 business days Low, 80 yuan Simple Clinical evidence .

[0130] In summary, this invention provides an economical, convenient, and effective means for detecting and assessing the risk of keloid formation, which has certain clinical significance and solves the problem that the current market cannot comprehensively assess keloid risk genes.

[0131] The advantages and positive effects of this invention are as follows:

[0132] 1. Establishing a multivariate keloid prediction model with clinical significance and unique characteristics in North my country, enabling multi-gene locus risk assessment: This invention establishes a comprehensive scoring system based on the detection results of five gene loci and clinical analysis, predicting the probability of keloid formation through a comprehensive score. This scoring system resolves the difficulties in clinical interpretation caused by inconsistent individual results, enabling multi-gene locus risk assessment of keloids and facilitating personalized prevention and treatment.

[0133] 2. Filling a Clinical Gaps: Currently, the medical device market lacks products for detecting keloid-related gene polymorphisms. This invention establishes a method for detecting keloid-related gene loci specific to North my country, and uses clinical diagnostic results to differentiate the allele risk at different loci, indicating protective and risk factors. Based on integrated analysis of clinical results, a predictive model with North China characteristics is established, which is of great significance for assisting in the detection and treatment of keloids. It solves the current difficulties in the clinical diagnosis of keloids, fills a gap in this clinical testing field, and forms a closed-loop chain of "prevention-diagnosis-intervention".

[0134] 3. Diverse Application Scenarios, Breaking Boundaries of Clinical Diagnosis and Treatment: This predictive model is not only applicable to risk assessment and individualized treatment in medical institutions, but can also be widely applied in the medical aesthetics industry, health management, and skincare fields. Before minimally invasive procedures, laser treatments, and surgical procedures, susceptibility screening can significantly reduce the risk of postoperative scar complications, improving consumer safety and satisfaction; at the same time, it provides scientific decision-making basis for beauty institutions, reducing the risk of medical disputes.

[0135] 4. Simple operation: One reaction well of this invention can perform PCR reactions targeting 5 sites: rs2299939, rs17431184, rs873549, rs1442440, and rs2271289. The operation process is simplified (completed in 3 working days, compared to 15 working days for NGS), which greatly reduces the testing threshold for medical aesthetic institutions and health check centers. The cost per sample is only 80 yuan (compared to 2,000 yuan for NGS), which has the advantage of large-scale promotion.

[0136] 5. Accurate detection results: The primer design of this invention includes specific primer segments and universal primer segments. Universal primers ensure consistent amplification efficiency of the detection system, while specific primers ensure the specificity of the detection results, greatly improving the accuracy of the detection results.

[0137] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A combination of genetic locus markers for diagnosing or prognostically assessing keloid-prone populations in North China, characterized in that, The genetic loci include the following loci: rs873549, rs1442440, rs2271289, rs17431184, and rs2299939.

2. The combination of genetic locus markers according to claim 1, characterized in that, Allele expression at each locus is as follows: The risk factor for rs873549 is expressed as allele C; The risk factor for rs1442440 is expressed as allele T; The risk factor for rs2271289 is expressed as allele T; The risk factor for rs17431184 is expressed as allele T; The risk factor for rs2299939 is expressed as allele C; And / or, the sample for detecting the genetic locus is blood.

3. A primer combination for detecting relevant gene typing in individuals susceptible to keloid scarring, characterized in that, This includes specific primer pairs for detecting the rs873549, rs1442440, rs2271289, rs17431184, and rs2299939 loci, respectively. Alternatively, it may include combinations of primers as shown in SEQ ID NO:1 to 10, respectively.

4. A primer combination for detecting genotyping of blood-related genes in individuals susceptible to keloid scarring, characterized in that... This includes specific primer pairs for detecting the rs873549, rs1442440, rs2271289, rs17431184, and rs2299939 loci, respectively. Alternatively, it may include combinations of primers as shown in SEQ ID NO:1 to 10, respectively.

5. Application of genotyping of genetic locus markers in susceptible populations in the preparation of kits or analytical systems for the diagnosis or prognostic assessment of keloid-susceptible populations in North China; among which, The combination of genetic locus markers in blood includes rs873549, rs1442440, rs2271289, rs17431184, and rs22999390; Alternatively, it can be done by detecting the rs873549, rs1442440, rs2271289, rs17431184, and rs2299939 related genotypes in the test subjects.

6. A non-diagnostic detection method for a combination of genetic locus markers in keloid-prone populations in North China, characterized in that, The combination of genetic locus markers in blood includes rs873549, rs1442440, rs2271289, rs17431184, and rs2299939. The primer combination described in claim 3 or 4 is used to detect the relevant genotypes at each locus.

7. A predictive system for diagnosing or prognostically assessing keloid-prone populations in North China, characterized in that, The system includes a data analysis module, which is used to collect genotyping data related to genetic loci of keloid-prone individuals in the target population to be predicted, using their genotypes as input features. It is also used to calculate a predicted value based on the genotyping data related to genetic loci of keloid-prone individuals to determine whether the target population is susceptible to keloids. The input feature is a genotype related to the combination of genetic locus markers as described in claim 5 or 6. Methods for assigning genotypes include: The value of rs873549 is 1 when the genotype is C and 0 when the genotype is T. The value of rs1442440 is 1 when the genotype is T and 0 when the genotype is C. The value of rs2271289 is 1 when the genotype is T and 0 when the genotype is C. The genotype of rs17431184 is assigned a value of 1 when it is allele T and 0 when it is allele C. The value of rs2299939 is assigned as 1 when the genotype is C and 0 when the genotype is T.

8. An analytical system for diagnosing or prognostically assessing keloid-prone populations in North China, characterized in that, Using the genotype in the blood of the target individual as input features, the model calculates the predicted value of whether the target individual is susceptible to keloids. The prediction formula is as follows: glm(formula=shaixuanhou_data$group~0.5911*rs873549+0.9331*rs1442440-0.1447*rs2271289+16.1030*rs17431184+(-15.9701)*rs2299939, family=binomial, data = shaixuanhou_data); Among them, rs873549, rs1442440, rs2271289, rs17431184, and rs22999390 are the relevant genotypes of each indicator in the target object to be predicted; Among them, a predicted value > 0.437 indicates a susceptible population for keloids, otherwise it is not considered a susceptible population.

9. The prediction system according to claim 7 or 8, characterized in that, Genotyping of rs873549, rs1442440, rs2271289, rs17431184, and rs22999390 was performed. Allele assignment methods included assigning a score of 1 to risk factors and a score of 0 to protective factors. The risk factor for rs873549 is allele C, and the protective factor is allele T. The risk factor for rs1442440 is allele T, and the protective factor is allele C. The risk factor for rs2271289 is allele T, and the protective factor is allele C. The risk factor for rs17431184 is allele T, and the protective factor is allele C. The risk factor for rs2299939 is allele C, and the protective factor is allele T. The genetic locus was detected using blood as the sample.

10. A kit for diagnosis or prognostic assessment, or evaluation of related drugs, in populations susceptible to keloids, characterized in that, The kit includes the combination of genetic locus markers and / or their detection reagents as described in claim 1 or 2.

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