Application of methylation site CG06087988 in the detection of type 2 diabetes

Abstract

This application relates to the field of gene detection technology, and in particular to the application, kit, and method of DNA methylation site in the diagnosis of type 2 diabetes. This application demonstrates through clinical testing that the methylation site cg06087988 shows significant differences between patients with type 2 diabetes and those without, and can be used for the diagnosis / prediction of type 2 diabetes.

Description

Technical Field

[0001] This application relates to the field of gene detection technology, specifically to the application, products, and methods of the methylation site CG06087988 in the diagnosis / prediction of type 2 diabetes. Background Technology

[0002] Type 2 diabetes is the most common subtype of diabetes, accounting for approximately 90% of all diabetes patients worldwide. The main symptom of type 2 diabetes is elevated blood glucose levels. Its pathogenesis involves a relative deficiency in insulin synthesis and secretion by the pancreas, leading to decreased insulin sensitivity in the blood and insulin resistance in peripheral organs. The long-term compensatory work of pancreatic beta cells eventually results in functional failure and loss of insulin secretion capacity. Type 2 diabetes can cause serious damage to blood vessels, eyes, kidneys, and nerves, triggering a series of complications and seriously endangering public health. Early and accurate prediction and diagnosis of type 2 diabetes are of great significance for early prevention and treatment of patients with this condition.

[0003] DNA methylation refers to the covalent bonding of a methyl group to the 5' carbon atom of cytosine in a cytosine-phosphate-guanine (CpG) dinucleotide in the genome, under the action of DNA methyltransferases. DNA methylation is an important epigenetic modification. More than 98% of CpG dinucleotides in the human genome are located in transcription-dependent transposable repetitive sequences. As a novel biomarker, DNA methylation shows great potential for applications in risk prediction, diagnosis, and prognostic assessment of human diseases. DNA methylation is in a dynamic state throughout human life, recording the influence of environmental factors like tree rings. Furthermore, methylation site detection can be used to study important issues such as epigenetic regulation, gene expression regulation, and the impact of environmental factors on the genome. For example, Chinese invention patent CN105861644A proposes DNA methylation biomarkers for predicting the risk of lung cancer, as well as their detection methods and kits; Chinese invention patent CN110982907B proposes DNA methylation biomarkers related to thyroid nodules and their applications.

[0004] Existing research indicates a close correlation between DNA methylation levels and type 2 diabetes. For example, Ling et al. found that the methylation level of the PPARGC1A gene promoter region in the pancreatic islet tissue of patients with type 2 diabetes was significantly lower than that in healthy individuals. Barres et al. further found that the methylation level of the PPARGC1A gene promoter region in the skeletal muscle of patients with type 2 diabetes was significantly lower than that in healthy individuals. In peripheral blood, several DNA methylation biomarkers have also been found to differ significantly between patients with type 2 diabetes and healthy individuals. For example, in peripheral blood, DNA methylation sites on the ABCG1, LOXL2, TXNIP, SLC1A5, and SREBF1 genes were found to differ significantly between patients with type 2 diabetes and healthy individuals. Therefore, monitoring peripheral blood DNA methylation levels holds promise for providing earlier and more accurate prediction and diagnosis of type 2 diabetes. Currently, there are few reports on studies based on peripheral blood DNA methylation levels in the Chinese population with type 2 diabetes. Based on this, this application is submitted. Summary of the Invention

[0005] To address the aforementioned technical issues, this application recruited two case-control populations of type 2 diabetes patients from multiple hospitals in Guangzhou (Population 1: recruited from January to December 2022; Population 2: recruited from January to December 2023). Samples from Population 1 were analyzed using Illumina's Infinium Methylation EPIC BeadChip (850k chip) to detect 850,000 DNA methylation sites across the entire genome. Samples from Population 2 were validated using methylation-specific PCR (MSP) to verify candidate DNA methylation sites. Clinical case studies revealed that the peripheral blood of type 2 diabetes patients showed highly methylated methylation site cg06087988. Based on the above research, this application includes at least the following two objectives:

[0006] The primary objective of this application is to seek a novel method for the diagnosis or prediction of type 2 diabetes;

[0007] The second objective of this application is to seek a new methylation biomarker for the detection of type 2 diabetes and a corresponding detection kit.

[0008] To achieve the above objectives, this application provides the following technical solution:

[0009] This application first provides a DNA methylation biomarker for type 2 diabetes, wherein the DNA methylation biomarker is a single DNA methylation site, specifically cg06087988; where cg represents the site's number in Illumina's CpG locus database. This biomarker is suitable for diagnosing type 2 diabetes; the degree or level of methylation at this DNA methylation site is used to diagnose or predict type 2 diabetes, providing a basis for its diagnosis.

[0010] Furthermore, the diagnosis or prediction includes early prediction, screening (including early screening), auxiliary diagnosis, diagnosis (determining whether a disease exists), determining the severity of the disease, assessing disease activity, and monitoring treatment; preferably, the diagnosis or prediction described in this application includes early screening, auxiliary diagnosis or diagnosis, etc.

[0011] This application also provides an application of a detection reagent for obtaining the level of methylation site CG06087988 in a sample in the preparation of products for the diagnosis or prediction of type 2 diabetes.

[0012] This application also provides an application of a detection reagent for obtaining the level of methylation site CG06087988 in a sample in the diagnosis or prediction of type 2 diabetes.

[0013] This application also provides the application of the methylation site CG06087988 as a diagnostic biomarker for type 2 diabetes.

[0014] Furthermore, in the aforementioned applications, the diagnosis or prediction includes early prediction, screening (including early screening), assisted diagnosis, diagnosis (determining whether a disease exists), determining the severity of the disease, assessing disease activity, and monitoring treatment; preferably, it includes early prediction, early screening, or diagnosis.

[0015] Furthermore, in the aforementioned applications, the detection reagent performs detection at the nucleic acid level;

[0016] In some methods, the detection reagent is used to perform any of the following methods: polymerase chain reaction, denaturing gradient gel electrophoresis, nucleic acid sequencing, nucleic acid typing chip detection, denaturing high performance liquid chromatography, in situ hybridization, biomass spectrometry, and HRM.

[0017] In some specific embodiments, the detection reagent performs a polymerase chain reaction;

[0018] Preferably, the polymerase chain reaction uses the following specific primers:

[0019] For detection primer pairs that have not undergone methylation:

[0020] F:TAGTTGGGTTGGGGAGTTTAC (SEQ ID NO: 1);

[0021] R:AAAAAAAAACAACAAATTCGAT(SEQ ID NO:2);

[0022] For the detection primer pair that results in methylation:

[0023] F: TTTAGTTGGGTTGGGGAGTTTAT (SEQ ID NO: 3);

[0024] R:AAAAAAAAACAACAAATTCAAT (SEQ ID NO:4).

[0025] The primer pairs described herein can be used to efficiently detect the methylation level or degree of the DNA methylation markers described herein using methylation-specific PCR methods.

[0026] Furthermore, in the aforementioned applications, the sample may be selected from at least one of blood, serum, plasma, tissue or tissue lysate, urine or saliva;

[0027] In some preferred embodiments, the sample is selected from blood, serum, or plasma.

[0028] This application also provides a product for the diagnosis or prediction of type 2 diabetes, the product comprising a reagent for detecting the level of methylation site CG06087988;

[0029] In some embodiments, the product is in the form of a reagent kit.

[0030] In some specific embodiments, the kit may contain the primer pairs described above.

[0031] Furthermore, the kit may also contain reagents for detecting other known biomarkers that can be used for the diagnosis of type 2 diabetes, thereby improving diagnostic or predictive performance through combined detection of multiple biomarkers.

[0032] This application also provides a method for diagnosing or predicting type 2 diabetes, the method comprising the step of detecting the level of methylation site cg10364040 in a sample.

[0033] Furthermore, the method may include the following steps:

[0034] (i) Obtain the level of methylation site cg10364040 in the test samples;

[0035] (ii) Comparison with a control sample; wherein a significant difference in cg10364040 levels between the subject sample and the control sample is a possible indicator of the subject having type 2 diabetes in the future, or an indicator of having type 2 diabetes, or,

[0036] (ii) Compare with a set absolute threshold; wherein, a subject sample level higher than the absolute threshold is a possible indicator of the subject having type 2 diabetes in the future, or an indicator of having type 2 diabetes.

[0037] This application also provides a method for detecting biomarkers in subjects who have or are suspected of having type 2 diabetes in vivo or in vitro, the method comprising determining or detecting the level of methylation site cg10364040 from a subject sample.

[0038] This application also provides a method for evaluating or screening diagnostic biomarkers for type 2 diabetes, comprising the step of performing correlation or consistency analysis between a potential biomarker and the methylation site CG06087988. It is understood that, based on the conviction that CG06087988 can serve as a diagnostic biomarker for type 2 diabetes, those skilled in the art can use this to evaluate or screen other potential diagnostic biomarkers for type 2 diabetes. Typically, a correlation evaluation is performed between the potential biomarker and CG06087988; when a positive correlation is found, the diagnostic value of the potential biomarker can be demonstrated. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0040] Figure 1 Box plots showing the methylation rates of the cg06087988 site in the type 2 diabetes patient group and the control group in Example 1. The case group consisted of 223 individuals, and the control group consisted of 204 individuals. The difference in DNA methylation levels between the case and control groups was analyzed using multiple linear regression, adjusted for sex, age, and body mass index.

[0041] Figure 2 Box plots showing the methylation rates of the cg06087988 site in the type 2 diabetes patient group and the control group in Example 2. The case group consisted of 252 individuals, and the control group consisted of 236 individuals. The difference in DNA methylation levels between the case and control groups was analyzed using multiple linear regression, adjusted for sex, age, and body mass index.

[0042] Figure 3 Evaluation results of predictive performance of clinical samples. Detailed Implementation

[0043] The embodiments of this application will be described in detail below with reference to examples. However, those skilled in the art will understand that the following examples are for illustrative purposes only and should not be considered as limiting the scope of this application. Unless otherwise specified in the examples, conventional conditions or conditions recommended by the manufacturer shall apply.

[0044] The following basic terms or definitions are provided merely to aid in understanding this application. These definitions should not be construed as having a scope less than that understood by those skilled in the art. Unless otherwise defined below, all technical and scientific terms used in the specific embodiments of this application are intended to have the same meaning as commonly understood by those skilled in the art. While it is believed that the following terms will be well understood by those skilled in the art, the following definitions are still set forth to better explain this application.

[0045] As used in this application, the terms “comprising,” “including,” “having,” “containing,” or “involving” are inclusive or open-ended and do not exclude other unlisted elements or method steps. The term “consisting of” is considered a preferred embodiment of the term “comprising.” If a group is defined below as comprising at least a certain number of embodiments, this should also be understood to disclose a group that preferably consists only of those embodiments.

[0046] When referring to a singular noun, the indefinite or definite article used, such as "a" or "a kind of," "the," includes the plural form of the noun.

[0047] The terms "approximately" and "generally" in this application refer to an accuracy range that, as would be understood by those skilled in the art, still guarantees the technical effects of the mentioned features. This term typically indicates a deviation from the indicated value of ±10%, preferably ±5%.

[0048] Furthermore, the terms first, second, third, (a), (b), (c), and similar terms used in the specification and claims are for distinguishing similar elements and are not necessary for the order of description or chronological sequence. It should be understood that such terms are interchangeable in appropriate contexts, and the embodiments described herein can be implemented in a different order than that described or illustrated herein.

[0049] Reference will now be made to detailed embodiments of this application, one or more of which are described below. Each example is provided for explanation and not for limitation. It will be apparent to those skilled in the art that various modifications and variations can be made to this application without departing from its scope or spirit. For example, features described or illustrated as part of one embodiment may be used in another embodiment to produce further embodiments. Therefore, this application is intended to cover such modifications and variations falling within the scope of the appended claims and their equivalents. Other objects, features, and aspects of this application are disclosed in or will be apparent from the following detailed description. Those skilled in the art will understand that this discussion is merely a description of exemplary embodiments and is not intended to limit the broader aspects of this application.

[0050] This application includes at least the following details:

[0051] 1. Application

[0052] The embodiments of this application describe the following: nucleic acid samples were extracted from clinical type 2 diabetes case samples collected in 2022. Through DNA methylation sequencing and statistical testing, the methylation level of the methylation site cg10364040 was identified as having diagnostic potential for type 2 diabetes. Subsequently, type 2 diabetes cases were collected again the following year, and these samples were used as an independent population to verify whether there was a significant difference in cg06087988 between cases and controls. The applicant used PCR to detect the methylation level of the cg06087988 site. Using multiple linear regression to adjust for sex, age, and body mass index, it was found that the DNA methylation level of this site was significantly higher in the case group than in the control group. The average methylation level of this site was 75.4% in the control group and 80.1% in the case group. Therefore, it can be confirmed that cg06087988 is a methylation biomarker for type 2 diabetes.

[0053] Therefore, this application provides at least the following applications:

[0054] 1) Application of methylation site CG06087988 as a diagnostic marker for type 2 diabetes;

[0055] 2) Application of methylation site CG06087988 in the diagnosis of type 2 diabetes;

[0056] 3) Application of a detection agent for obtaining the level of methylation site CG06087988 in subject samples in the diagnosis of type 2 diabetes;

[0057] 4) Application of a detection reagent for obtaining the level of methylation site CG06087988 in subject samples in the preparation of diagnostic products for type 2 diabetes.

[0058] The terms "type 2 diabetes," "type 2 diabetes," and "type II diabetes" used in this article are interchangeable and have the same meaning: a chronic disease caused by insufficient insulin use or reduced insulin efficiency, commonly seen in adults, also known as adult-onset diabetes. This disease is caused by a combination of genetic and environmental factors, such as lifestyle, overnutrition, and insufficient physical activity.

[0059] As used herein, the term "diagnosis" refers to the process of identifying a medical condition or disease (such as type 2 diabetes) through its signs, symptoms, and especially the results of various diagnostic procedures (including detecting the level of cg06087988 in biological samples (such as serum) obtained from an individual). Furthermore, the term "diagnosis" as used herein includes early prediction of disease, screening (including early screening), auxiliary diagnosis, definitive diagnosis (determining the presence of a disease), assessment of disease severity, evaluation of disease activity, monitoring treatment (e.g., monitoring disease progression or recurrence during treatment), evaluation of treatment efficacy, and selection of a given treatment regimen. Without limitation, in some specific embodiments, this application has sufficiently demonstrated that cg06087988 levels can be used to determine the presence or absence of type 2 diabetes in a subject, and thus can be used for screening (early screening), auxiliary diagnosis, or definitive diagnosis.

[0060] The terms “individual,” “object,” “subject,” and “patient” are used interchangeably in this document and refer to any mammalian object, particularly a human, that requires diagnosis, treatment, or therapy.

[0061] As used herein, the terms “sample,” “sample,” “test sample,” “subject sample,” and “subject sample,” etc., encompass a wide range of sample types obtained from patients, individuals, or subjects and that may be used for diagnostic or monitoring assays. Patient samples may be obtained from healthy subjects, patients with the disease, or patients with symptoms associated with type 2 diabetes. Furthermore, samples obtained from patients may be aliquoted, and only a portion may be used for diagnostic purposes. Additionally, samples, or portions thereof, may be stored under conditions that allow for subsequent analysis. This definition specifically includes blood and other liquid samples of biological origin (including, but not limited to, tissues, cells (e.g., PMBC cells, T cells, etc.), body fluids, serum, plasma, whole blood, urine, semen, saliva, pleural effusion, ascites, cerebrospinal fluid, feces, and synovial fluid, etc.). In one specific embodiment, the sample includes blood samples. This definition also includes samples that have been manipulated in any way after acquisition, such as by centrifugation, filtration, precipitation, dialysis, chromatography, reagent treatment, washing, or enrichment of certain cell populations. These terms also include clinical samples and further include cells in cultures, cell supernatants, tissue samples, organs, etc.

[0062] In some embodiments of this application, the detection agent performs detection at the nucleic acid level. It is understood that the nucleic acid level can include the DNA level. There are various methods for DNA level detection in the art, including but not limited to sequencing technology, nucleic acid amplification technology, nucleic acid hybridization technology, electrophoresis technology, biomolecular mass spectrometry, or chromatography technology. These technologies can all be used in this application, such as but not limited to any of the following specific methods: gene sequencing, polymerase chain reaction, isothermal amplification reaction, gene chip method, probe hybridization, gel electrophoresis, RNA blotting, nucleic acid mass spectrometry, or liquid chromatography.

[0063] In some specific methods of this application, gene sequencing is used, specifically employing Illumina's methylation array; in other specific methods, polymerase chain reaction (PCR) is used, specifically employing primers F: TAGTTGGGTTGGGGAGTTTAC (SEQ ID NO:1), R: AAAAAAAACAACAAATTCGAT (SEQ ID NO:2), F: TTTAGTTGGGTTGGGGAGTTTAT (SEQ ID NO:3), and R: AAAAAAAACAACAAATTCAAT (SEQ ID NO:4). The specific sequencing method or primer sequences used are not limited here; conventional choices are generally acceptable in the art.

[0064] Furthermore, according to the experimental data of this application, the methylation site CG06087988 can be used as an independent indicator for the diagnosis of type 2 diabetes, and the effective diagnosis of type 2 diabetes can be achieved solely based on the level or degree of CG06087988.

[0065] It is also understandable that, in order to further enhance the diagnostic efficacy for type 2 diabetes, the detected biomarkers can also be other biological materials known to those skilled in the art as having diagnostic value, such as nucleic acid fragments, proteins, and metabolites. This allows for the combined use of multiple biomarkers, working synergistically to achieve better diagnostic results for patients with type 2 diabetes, thus achieving a more effective diagnostic assessment. Therefore, CG10364040, in addition to serving as an independent indicator for the diagnosis of type 2 diabetes, can also be used in conjunction with other existing known diagnostic markers to improve diagnostic efficacy.

[0066] 2. Products

[0067] As can be seen from the core diagnostic purpose of this application, the procedure for detecting the level of the methylation site cg10364040 can be configured into a corresponding product form for the diagnosis or prediction of type 2 diabetes. This product includes reagents for detecting the level of the methylation site cg10364040. It is understood that such product forms are diverse, including but not limited to kit forms.

[0068] reagent kit form

[0069] In some embodiments of this application, kits for detecting or analyzing the level of the methylation site cg10364040 to achieve the diagnosis or prediction of type 2 diabetes are also disclosed. Such kits may include reagents for detecting the level of the methylation site cg10364040 and instructions for predicting the disease based on the detected level.

[0070] As mentioned above, when the detection reagent is used for nucleic acid detection, it is understood that there are various nucleic acid detection methods in the art, including but not limited to sequencing technology, nucleic acid amplification technology, nucleic acid hybridization technology, electrophoresis technology, biomolecular mass spectrometry technology, or chromatography technology. All of these technologies can be used in this application. In some specific embodiments of this application, it includes, but is not limited to, any of the following specific methods: gene sequencing, polymerase chain reaction (PCR), isothermal amplification reaction, gene chip method, probe hybridization, gel electrophoresis, RNA blotting, nucleic acid mass spectrometry, or liquid chromatography. Therefore, the corresponding reagents or detection reagents can be primers for polymerase chain reaction, or various sequencing methods or panels, etc., without limitation.

[0071] 3. Diagnostic methods

[0072] Methods for the diagnosis or prediction of type 2 diabetes

[0073] The core of the diagnostic or predictive method in this application includes a step that detects the methylation level at the cg10364040 site in a sample.

[0074] In some embodiments, the method specifically includes the step of detecting the level of methylation site cg10364040 in a sample;

[0075] Furthermore, the method may include the following steps:

[0076] (i) Obtain the level of methylation site cg10364040 in the test samples;

[0077] (ii) Comparison with a control sample; wherein a significant difference in cg10364040 levels between the subject sample and the control sample is a possible indicator of the subject having type 2 diabetes in the future, or an indicator of having type 2 diabetes, or,

[0078] (ii) Compare with a set absolute threshold; wherein, a subject sample level higher than the absolute threshold is a possible indicator of the subject having type 2 diabetes in the future, or an indicator of having type 2 diabetes.

[0079] In some embodiments, the diagnosis includes early prediction, screening, assisted diagnosis, diagnosis (determining the presence of a disease), assessment of disease severity, evaluation of disease activity, and monitoring of treatment; in some preferred embodiments, the diagnosis includes early prediction, early screening, and diagnosis.

[0080] It is understandable that the control sample can be selected according to actual needs. For example, in early disease screening or diagnosis, the control sample is a normal population sample; while when used for prognostic assessment, it can be a control sample with different prognostic conditions.

[0081] In some specific implementations, for example, subjects with higher levels of cg06087988 methylation typically have a higher risk of developing type 2 diabetes. Another implementation may provide a set value for the cg10364040 methylation level. This set value can be determined based on the cg10364040 methylation levels of normal individuals and / or non-cancer normal samples. For example, the average cg10364040 methylation levels of a suitable number of normal samples can be selected, or a reasonable multiple of this average value can be set, such as 0.9, 0.8, 0.7, 0.6, or 0.5 times. When a subject's cg10364040 methylation level is higher than this set value, they are diagnosed with type 2 diabetes. It is understood that the set value determined based on the average value, or a multiple of the average value, needs to have good classification significance. Common statistical tests can be used to examine known samples based on the classification of this set value. When the results are statistically significant, it indicates that the set value can be used as a judgment criterion.

[0082] The implementation scheme of this application will be described in detail below with reference to the embodiments.

[0083] Example 1: Collection of clinical samples to screen for methylation biomarkers in type 2 diabetes.

[0084] 1. Materials and Methods

[0085] 1.1 Research Subjects

[0086] This study included 223 cases of type 2 diabetes and 204 controls from multiple hospitals in Guangzhou. These individuals were recruited between January and December 2022.

[0087] The diagnostic criteria for recruited type 2 diabetes cases were: fasting blood glucose level higher than 7.0 mmol / L; or blood glucose level measured at any time of day higher than 11.1 mmol / L and accompanied by typical diabetic symptoms. Controls were healthy individuals with normal blood glucose levels. Information on the population used in this study can be found in Table 1 below. There were no significant differences in gender and age between the case and control groups. Peripheral blood was collected from the individuals listed above, and DNA was extracted.

[0088] Table 1. Population information used in genome-wide association studies

[0089] Classification Cases (n=223) Control group (n=204) Age, year Mean (Standard Deviation) 57.2(13.2) 56.8(12.9) <60，n(％) 118(52.9) 109(53.4) ≥60，n(％) 105(47.1) 95(46.5) Gender, n (%) male 115(51.6) 101(49.5) female 108(48.4) 103(50.5)

[0090] 1.2 DNA methylation detection and quality control

[0091] The Infinium MethylationEPIC BeadChip (850k chip) from Illumina was used to detect 850,000 DNA methylation sites across the entire genome.

[0092] Quality control is divided into sample quality control and methylation site quality control.

[0093] Sample quality control was performed as follows: Initial quality control of sample data was conducted using GenomeStudio software, methylation module (version 1.9.0), to determine staining, extension, hybridization, target removal, bisulfite conversion, specificity, non-polymorphism, and negative controls (without background correction or normalization). Samples with a detection rate exceeding 95% were subsequently retained.

[0094] The quality control of methylation sites was as follows: First, DNA methylation sites with signal values ​​below 3 in at least 5% of the samples were excluded. Then, using the wateRmelon R package, CpG sites with a detection p-value > 0.05 were removed if they accounted for more than 1% of the total samples. To avoid the influence of single nucleotide polymorphisms (SNPs) on DNA methylation measurements and gender bias, if SNPs were present both within the probe and at CpG sites, those CpG sites were removed. In addition, probes at non-CpG sites and sex chromosome probes were also removed.

[0095] 1.3 Statistical Tests

[0096] The difference in DNA methylation levels between the case group and the control group was analyzed using multiple linear regression, adjusted for sex, age, and body mass index. P-values ​​were expressed as 1×10⁻⁶. -4 As a significance threshold across the entire genome.

[0097] 2. Results Statistics

[0098] After screening using the above process, 733,252 CpG sites were retained. Using multiple linear regression to adjust for sex, age, and body mass index, a series of DNA methylation sites significantly associated with type 2 diabetes were identified (P < 1 × 10⁻⁶). -4 Among them, cg06087988 is noteworthy, as this DNA methylation site was significantly higher in the case group than in the control group (P = 1.4 × 10⁻⁶). -5 See appendix for details. Figure 1 The average methylation level at this site was 77.6% in the control group and 83.0% in the case group, a difference of >5%.

[0099] The above results suggest that cg06087988 is a candidate peripheral blood DNA methylation marker associated with type 2 diabetes.

[0100] Example 2: Collection of clinical samples to validate methylation biomarkers in type 2 diabetes

[0101] 1. Materials and Methods

[0102] 1.1 Research Subjects

[0103] The validation study included 252 cases of type 2 diabetes and 236 controls recruited and collected from Guangzhou Municipal Hospital. These cases were recruited between January and December 2023.

[0104] The corresponding diagnostic criteria for cases were: fasting blood glucose level higher than 7.0 mmol / L; or blood glucose level measured at any time of day higher than 11.1 mmol / L and accompanied by typical symptoms of diabetes. Controls were healthy individuals with normal blood glucose levels. Population information used in this study can be found in Table 2. Peripheral blood was collected from the above individuals, and DNA was extracted. These samples served as an independent population to verify whether cg06087988 showed a significant difference between cases and controls.

[0105] Table 2. Population Information Table Used in the Validation Phase

[0106] Classification Cases (n=252) Comparison (n=236) Age, year Mean (Standard Deviation) 55.6(9.6) 56.6(11.1) <60，n(％) 141(56.0) 127(53.8) ≥60，n(％) 111(44.0) 109(46.2) Gender, n (%) male 128(50.8) 121(51.3) female 124(49.2) 115(48.7)

[0107] 1.2 DNA methylation detection

[0108] During the verification process, the applicant used methylation-specific PCR to detect the methylation level at the cg06087988 site.

[0109] First, the DNA was treated with sodium sulfite for desulfurization and purification using a reaction column. The purified DNA was then used for subsequent PCR reactions. Methylated and unmethylated primers were designed targeting the cg06087988 site. The unmethylated primer pair was TAGTTGGGTTGGGGAGTTTAC (SEQ ID NO:1) and AAAAAAAACAACAAATTCGAT (SEQ ID NO:2). SEQ ID NO:1 is the forward primer, and SEQ ID NO:2 is the backward primer. The methylated primer pair was TTTAGTTGGGTTGGGGAGTTTAT (SEQ ID NO:3) and AAAAAAAACAACAAATTCAAT (SEQ ID NO:4). SEQ ID NO:3 is the forward primer, and SEQ ID NO:4 is the backward primer. Finally, the PCR reaction was performed.

[0110] 1.3 Statistical Tests

[0111] The difference in DNA methylation levels between the case group and the control group was analyzed using multiple linear regression, adjusted for sex, age, and body mass index. A p-value of 0.05 was used as the significance threshold.

[0112] 2. Experimental Results

[0113] To verify whether there was a significant difference in cg06087988 between diabetic cases and controls, the applicant used methylation-specific PCR to detect the methylation level of the cg06087988 site. Statistical results showed that this DNA methylation site was significantly higher in the case group than in the control group (P = 2.7 × 10⁻⁶). -4 See appendix Figure 2 The average methylation level at this site was 75.4% in the control group and 80.1% in the case group. The validation results were statistically significant, confirming that cg06087988 is a peripheral blood DNA methylation marker associated with type 2 diabetes and can be used to differentiate between patients with and without type 2 diabetes.

[0114] Example 3: Evaluation of predictive performance using combined clinical samples

[0115] 1. Materials and Methods

[0116] 1.1 Research Subjects

[0117] A total of 915 samples were included in Examples 1 and 2, of which 475 were in the type 2 diabetes case group and 440 were in the control group. For detailed information on the study subjects, please refer to the descriptions in Examples 1 and 2.

[0118] 1.2 Statistical Tests

[0119] Use the "pROC" package in R to plot the receiver operating characteristic curve (ROC curve) and calculate the area under the curve (AUC).

[0120] 2. Experimental Results

[0121] The methylation status of cg06087988 was detected in all samples from the study subjects, and the methylation level was characterized using β values. To investigate the performance of cg06087988 methylation level in predicting type 2 diabetes, the applicant plotted ROC curves and calculated AUC.

[0122] It can be seen (see appendix) Figure 3 For all samples, cg06087988 was used to predict type 2 diabetes, with an AUC value of 0.631, indicating that the cg06087988 methylation level used in this study can be used to predict type 2 diabetes (while currently few studies can effectively predict type 2 diabetes based on a single methylation site). Furthermore, to determine the optimal diagnostic cutoff value, the applicant also used the "pROC" package to calculate the optimal cutoff value, which was 0.752. This suggests that selecting a cutoff value of 0.752 can more effectively identify positive samples and avoid misclassifying negative samples as positive.

[0123] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application 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 or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. Application of a detection reagent for obtaining the DNA methylation level of methylation site cg06087988 in a sample in the preparation of diagnostic or predictive products for type 2 diabetes.

2. The application according to claim 1, characterized in that, The detection reagent is used to perform any of the following methods: nucleic acid sequencing, polymerase chain reaction, denaturing gradient gel electrophoresis, nucleic acid typing chip detection, denaturing high performance liquid chromatography, in situ hybridization, biomass spectrometry, and HRM.

3. The application according to any one of claims 1-2, characterized in that, The sample is selected from blood, serum, or plasma.

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