Application of biomarker in diagnosis, treatment or prevention of diabetes mellitus

Abstract

The invention discloses an application of a biomarker in diagnosis, treatment or prevention of diabetes mellitus, provides an application of a reagent for detecting the biomarker in preparation of a product for diagnosing diabetes mellitus, the biomarker is RAB11FIP3, and provides an application of the reagent for detecting the biomarker in preparation of a product for diagnosing hyperglycemia. The specific value of the RAB11FIP3 full-length transcript to the RAB11FIP3 sixth exon deletion transcript is used for determining whether a subject suffers from diabetes mellitus / hyperglycemia or has the disease risk or not. The invention provides a related product, system, equipment and a computer readable storage medium.

Description

Technical Field

[0001] The present invention belongs to the field of biotechnology and relates to the application of biomarkers in diagnosing, treating or preventing diabetes. Background Art

[0002] Diabetes is a chronic disease characterized by dysregulation of blood sugar. Diabetic foot ulcers (DFUs) are one of the most serious complications of diabetes, affecting 15-25% of diabetic patients. About 50-60% of foot ulcers will become infected, and about 20% of moderate to severe infections will lead to lower limb amputation. A large number of studies have shown that the damage caused by elevated blood sugar may persist even after blood sugar levels return to normal, a phenomenon known as metabolic memory (MM). The MM phenomenon associated with hyperglycemia is closely associated with an increased risk of several diabetic complications, including cardiovascular disease, kidney disease, retinopathy, and diabetic foot ulcers. This means that transient high blood sugar can cause lasting damage to vascular endothelial cells.

[0003] Alternative splicing (AS) plays a crucial role in the development and progression of human diseases. AS is an important contributor to the high complexity of the transcriptome of multicellular eukaryotes. Most multi-exon human genes undergo AS, resulting in the production of multiple different mature mRNAs from one gene, thereby expanding the protein coding repertoire of the cell. Summary of the invention

[0004] In order to make up for the deficiencies of the prior art, the present invention provides the following technical solutions:

[0005] The present invention provides use of a reagent for detecting a biomarker in preparing a product for diagnosing diabetes, wherein the biomarker is RAB11FIP3.

[0006] Furthermore, the product determines whether a subject has diabetes or is at risk of the disease by measuring the ratio of the RAB11FIP3 full-length transcript to the RAB11FIP3 exon 6 deletion transcript in the sample, wherein the RAB11FIP3 full-length transcript is referred to as RAB11FIP3-FL, and the RAB11FIP3 exon 6 deletion transcript is referred to as RAB11FIP3-Δ6;

[0007] Furthermore, the ratio of RAB11FIP3-FL to RAB11FIP3-Δ6 is significantly overexpressed in diabetic patients;

[0008] Further, the diabetes includes diabetic foot ulcers and metabolic memory of diabetes;

[0009] Furthermore, the sample is from a human or non-human mammal;

[0010] Further, the sample includes tissue, blood, plasma, serum, saliva, urine, colon excretion, cerebrospinal fluid, sputum, sweat, breast milk, tears, bile, gastric juice, interstitial fluid, oral or nasal swab, aqueous humor, amniotic fluid, pleural fluid;

[0011] Further, the sample includes tissue, blood, plasma, serum, and interstitial fluid;

[0012] Furthermore, the reagents include primers, probes, antisense oligonucleotides, aptamers or antibodies specific for detecting RAB11FIP3-FL and RAB11FIP3-Δ6.

[0013] In some embodiments, the RAB11FIP3 full-length transcript and the RAB11FIP3 exon 6 deletion transcript are referred to as RAB11FIP3-FL and RAB11FIP3-Δ6, and the ratio of the two is referred to as FL / Δ6.

[0014] The term "sample" as used in the present invention refers to a composition obtained or derived from a subject (e.g., an individual of interest) that contains cells and / or other molecular entities to be characterized and / or identified based on, for example, physical, biochemical, chemical and / or physiological characteristics.

[0015] In some embodiments, the sample is taken directly from the subject without further processing, for example, blood can be obtained from the subject's peripheral circulatory system (e.g., via a blood collection needle). The sample may include, for example, blood, urine, feces, saliva, cerebrospinal fluid, and sweat. Non-limiting examples of such samples include blood (or components of blood - e.g., white blood cells, red blood cells, platelets) obtained from any anatomical location of a subject (e.g., tissue, circulatory system, bone marrow), cells obtained from any anatomical location of a subject, skin, heart, lung, kidney, exhaled breath, bone marrow, stool, semen, vaginal fluid, tissue fluid from tumor tissue, breast, pancreas, cerebrospinal fluid, tissue, throat swab, biopsy, placental fluid, amniotic fluid, liver, muscle, smooth muscle, bladder, gallbladder, colon, intestine, brain, cavity fluid, sputum, pus, microbiota, meconium, breast milk, prostate, esophagus, thyroid, serum, saliva, urine, gastric and digestive fluids, tears, ocular fluids, sweat, mucus, earwax, oils, glandular secretions, cerebrospinal fluid, hair, nails, skin cells, plasma, nasal swab or nasopharyngeal wash, cerebrospinal fluid, umbilical cord blood, lymphatic fluid and / or other excreta or body tissues.

[0016] Furthermore, the reagents include reagents for detecting the presence, absence and / or amount of genes, fragments and proteins of RAB11FIP3-FL and RAB11FIP3-Δ6 in a sample by PCR reaction, RT-PCR derivatization reaction, 3SR amplification, LCR, SDA, NASBA, TMA, SYBR Green, TaqMan probe, molecular beacon, double hybridization probe, composite probe, ISH, microarray, Southern blot, Northern blot, multi-analyte spectrum test, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay, immunofluorescence assay, enzyme immunoassay, immunoprecipitation assay, chemiluminescence assay, immunohistochemistry assay, dot blot assay or slot blot assay.

[0017] The present invention provides the use of a reagent for detecting a biomarker in the preparation of a product for diagnosing hyperglycemia, wherein the biomarker is RAB11FIP3;

[0018] Furthermore, the product determines whether the subject suffers from hyperglycemia or is at risk of the disease by measuring the ratio of RAB11FIP3-FL to RAB11FIP3-Δ6 in the sample;

[0019] Furthermore, the ratio of RAB11FIP3-FL to RAB11FIP3-Δ6 was significantly overexpressed in patients with hyperglycemia.

[0020] The term "level of expression" or "expression level" as used herein generally refers to the amount of a biomarker in a biological sample. "Expression" generally refers to the process by which information (e.g., genetic coding and / or epigenetic information) is converted into structures that exist and function in a cell. Therefore, as used herein, "expression" may refer to transcription into polynucleotides, translation into polypeptides, or even polynucleotide and / or polypeptide modifications (e.g., post-translational modifications of polypeptides). Fragments of transcribed polynucleotides, translated polypeptides, or polynucleotide and / or polypeptide modifications (e.g., post-translational modifications of polypeptides) should also be considered expressed, whether they are derived from transcripts generated by alternative splicing or degraded transcripts, or from post-translational processing of polypeptides (e.g., by proteolysis).

[0021] The present invention provides a system for predicting diabetes / hyperglycemia using biomarkers, comprising:

[0022] A data acquisition unit, used to obtain data of biomarkers of a target subject, wherein the biomarkers include expression levels of RAB11FIP3-FL and RAB11FIP3-Δ6;

[0023] A data processing unit, used for calculating the ratio of the expression levels of RAB11FIP3-FL and RAB11FIP3-Δ6 according to the obtained data to obtain a calculated value;

[0024] a result output unit, for comparing the calculated value obtained by the data processing unit with the control value of the control group; if the calculated value is higher than the control value of the control group, the computer determines that the target subject suffers from diabetes / hyperglycemia or has a high risk of suffering from diabetes / hyperglycemia; if the calculated value is lower than or equal to the control value of the control group, the computer determines that the target subject does not suffer from diabetes / hyperglycemia or has a low risk of suffering from diabetes / hyperglycemia;

[0025] Furthermore, the control value of the control group is a detection value obtained by pre-detecting the expression levels of RAB11FIP3-FL and RAB11FIP3-Δ6 of normal subjects and calculating the ratio;

[0026] Furthermore, the diabetes includes diabetic foot ulcers and metabolic memory of diabetes.

[0027] In some embodiments, if the calculated value is higher than the control value of the control group, the computer determines that the target subject suffers from diabetes / hyperglycemia or has a high risk of suffering from diabetes / hyperglycemia, wherein higher than generally means showing a significant difference, usually referring to a p value less than 0.05, which is a significant difference result.

[0028] In the context of the present invention, the term "subject" used is equivalent to "object", "patient", and refers to any animal, including humans and non-human animals. Non-human animals include all vertebrates, for example, mammals, such as non-human primates (especially higher primates), sheep, dogs, rodents (such as mice or rats), guinea pigs, goats, pigs, cats, rabbits, cattle, and any livestock or pets; and non-mammals, such as amphibians, reptiles, etc. In a preferred embodiment, the subject is a human.

[0029] The present invention provides a product for diagnosing diabetes / hyperglycemia, the product comprising a reagent for detecting the biomarker RAB11FIP3;

[0030] Further, the biomarker RAB11FIP3 includes detecting RAB11FIP3-FL and RAB11FIP3-Δ6;

[0031] Furthermore, the product uses the ratio of the expression levels of RAB11FIP3-FL and RAB11FIP3-Δ6 to determine whether the subject has diabetes / hyperglycemia or is at risk of the disease.

[0032] Furthermore, the reagents include specific primers, probes, antisense oligonucleotides, aptamers or antibodies for detecting the biomarkers.

[0033] The term "agent" used in the present invention should not be interpreted narrowly, but should be extended to small molecules, protein molecules such as peptides, polypeptides and proteins, and compositions comprising them, as well as genetic molecules such as RNA, DNA and their mimetics and chemical analogs and cellular agents.

[0034] The present invention provides the use of an inhibitor of RAB11FIP3-FL in the preparation of a pharmaceutical composition for treating and preventing diabetes / hyperglycemia;

[0035] Further, the inhibitors include inhibitors of RAB11FIP3-FL, RAB11FIP3-Δ6, and HNRNPL;

[0036] Furthermore, the diabetes includes diabetic foot ulcers and metabolic memory of diabetes.

[0037] In some embodiments, the hyperglycemia also includes decreased vascular proliferation, migration and lumen formation ability caused by hyperglycemia. In some embodiments, the inhibitor of HNRNPL can inhibit HNRNPL, thereby enhancing the proliferation ability, migration ability and vascular lumen formation ability of vascular endothelial cells.

[0038] The term "pharmaceutical composition" used in the present invention refers to any composition comprising at least one bioactive agent. When used herein, the term "pharmaceutical composition" also refers to a composition comprising an active pharmaceutical ingredient to be delivered to a subject, such as to achieve a therapeutic, preventive, diagnostic, preventive or prognostic effect. When used herein, the term "pharmaceutical composition" also refers to any composition comprising a medium or carrier that maintains cells in a viable state. In certain embodiments, the pharmaceutical composition comprises an active pharmaceutical ingredient and a pharmaceutically acceptable carrier. When used herein, the term "pharmaceutically acceptable carrier" includes any and all solvents, dispersion media, coatings, antibacterial and antifungal agents, isotonic and absorption delaying agents, etc. that are physiologically compatible. Examples of pharmaceutically acceptable carriers include one or more of water, saline, phosphate buffered saline, dextrose, glycerol, ethanol, etc., and combinations thereof.

[0039] The terms "treatment", "treat" and "treating" used in the present invention refer to reversing, alleviating, reducing the possibility of a disease or disorder or one or more of their symptoms, or inhibiting the progression of a disease or disorder or one or more of their symptoms. In some embodiments, treatment may be administered after one or more symptoms have occurred, i.e., therapeutic treatment. In other embodiments, treatment may be administered in the absence of symptoms. For example, treatment may be administered to susceptible individuals before the onset of symptoms (e.g., according to a history of symptoms and / or according to genetic or other susceptibility factors), i.e., preventive treatment. Treatment may also be continued after the symptoms subside, for example, to reduce the possibility of recurrence or to delay its recurrence.

[0040] The present invention provides the use of an enhancer of RAB11FIP3-FL and an inhibitor of RAB11FIP3-Δ6 in the preparation of a product for regulating HIF-1α ubiquitination and degradation;

[0041] Furthermore, the enhancers include enhancers of RAB11FIP3-FL, RAB11FIP3-Δ6, and HNRNPL.

[0042] The present invention provides a computer-aided prediction device, comprising:

[0043] A memory and a processor, wherein the memory is used to store program instructions, and the processor is used to call the program instructions. When the program instructions are executed, the unit functions of the system for predicting diabetes / hyperglycemia using biomarkers as described above are implemented.

[0044] The term "device" as used in the present invention refers to any suitable computing or processing device, or other device constructed or modified to store data or information. Examples of devices suitable for use with embodiments of the present invention include stand-alone computing devices; networks, including local area networks (LANs), wide area networks (WANs), the Internet, corporate intranets, and extranets; electronic devices such as personal digital assistants (PDAs), cell phones, page managers, etc.; and local and distributed processing systems.

[0045] The present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the unit functions of the system for predicting diabetes / hyperglycemia using biomarkers described above are implemented.

[0046] In some embodiments, a linear regression algorithm, a support vector machine algorithm, a nearest neighbor / k-nearest neighbor algorithm, a logistic regression algorithm, a decision tree algorithm, a k-means algorithm, a random forest algorithm, a naive Bayes algorithm, a dimensionality reduction algorithm, or a gradient boosting algorithm are used to train and learn a computer device or a computer program.

[0047] In some embodiments, the present invention can be used in a variety of general or special computing system environments, such as personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like.

[0048] The term "diagnosis" as used in the present invention refers to making a medical judgment about the health status of an individual.

[0049] The term "prognosis" used in the present invention refers to a prediction or projection of the future course or outcome of a disease or condition. The term also refers to a prediction of the likelihood of clinical benefit from treatment. In some embodiments, a statistical algorithm is used to provide a prognosis of a disease for an individual.

[0050] Markers used in the present invention such as RAB11FIP3 (Gene ID: 9727) include genes and proteins encoded therein and homologs thereof, mutations, and isoforms. The term encompasses full-length, unprocessed biomarkers, as well as any form of biomarkers derived from processing in cells. The term encompasses naturally occurring variants (e.g., splice variants or allelic variants) of biomarkers.

[0051] The term "ROC curve" used in the present invention is a receiver operating characteristic curve, which is a coordinate diagram composed of a false positive probability (1-specificity) as the horizontal axis and a true positive probability (sensitivity) as the vertical axis, and a curve drawn by different results obtained by the subject under specific stimulation conditions due to different judgment criteria. Select the best diagnostic limit value. The closer the ROC curve is to the upper left corner, the higher the accuracy of the test. The point of the ROC curve closest to the upper left corner is the best threshold with the least error, and its total number of false positives and false negatives is the least. Comparison of disease recognition ability of two or more different diagnostic tests. When comparing two or more diagnostic methods for the same disease, the ROC curves of each test can be drawn into the same coordinate to intuitively distinguish the pros and cons. The subject represented by the ROC curve close to the upper left corner works most accurately. It can also be compared by calculating the area under the ROC curve (AUC) of each test respectively. Which test has the largest AUC, then which test has the best diagnostic value.

[0052] Advantages and beneficial effects of the present invention:

[0053] In this study, we found that the ratio of RAB11FIP3 (FL / Δ6) was highly expressed in patients with hyperglycemia, MM, and DFUs. In addition, we found that the splicing factor HNRNPL is an upstream regulator of RAB11FIP3. More importantly, our study showed that RAB11FIP3-FL promoted the ubiquitination and degradation of HIF-1 by NEDD4L, and this effect persisted even in the absence of VHL. Our results suggest that an imbalance in the ratio of RAB11FIP3 (FL / Δ6) may lead to persistent damage to vascular endothelial cells. This study is the first to explore the relationship between diabetic foot and AS, providing new insights into the mechanism of prognosis of diabetic wounds. This also provides a new perspective for the treatment of diabetic wounds. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a graph showing the cell damage and gene expression results of HUVEC in a high-glucose environment.

[0055] Figure 2 This is a graph showing the effect of MM on AS events in vascular endothelial cells;

[0056] Figure 3 This is a graph showing the results of the Transwell and wound healing experiments of vascular endothelial cells using RAB11FIP3-FL;

[0057] Figure 4 This is the result graph of the effect of RAB11FIP3-FL overexpression on the cell proliferation ability, cell migration ability and lumen formation ability of vascular endothelial cells;

[0058] Figure 5 It is the RBPmap prediction result of RAB11FIP3-Δ6 and the interaction result diagram between RAB11FIP3-Δ6 and HNRNPL;

[0059] Figure 6 This is a graph showing the expression results of HNRNPL in MM environment and the effect of knocking out HNRNPL on RAB11FIP3-Δ6;

[0060] Figure 7 This is a result diagram showing the effect of HNRNPL overexpression on the proliferation, migration and tube formation of HUVECs;

[0061] Figure 8 This is the result diagram showing that knocking down RAB11FIP3-FL alleviates the harmful effects caused by HNRNPL overexpression;

[0062] Fig. 9 This is the result diagram of the effect of RAB11FIP3-FL expression on HIF-1α expression;

[0063] Fig.10 This is a diagram showing the result of RAB11FIP3-FL binding to NEDD4L to promote HIF-1α ubiquitination and degradation;

[0064] Fig.11 This is a graph showing the effects of antisense oligonucleotides of different RAB11FIP3 transcripts on diabetic wound healing in mice;

[0065] Fig.12 This is the ROC result diagram of the high diagnostic efficiency of the RAB11FIP3-FL / RAB11FIP3-Δ6 ratio as a potential biomarker for early diagnosis and intervention of diabetes;

[0066] Fig.13 It is the design of RAB11FIP3 transcript and the expression results of RAB11FIP3-FL and RAB11FIP3-Δ6. DETAILED DESCRIPTION

[0067] The invention will be further described below in conjunction with specific examples. It should be understood that the specific embodiments described herein are presented by way of example and are not intended to limit the invention. The main features of the invention may be used in a variety of embodiments without departing from the scope of the invention.

[0068] Example

[0069] 1. Experimental methods

[0070] 1.1 Cell culture and treatment

[0071] HUVECs were purchased from the Cell Bank of the Chinese Academy of Sciences (Shanghai). Before the experiment, HUVECs were cultured in DMEM (KeyGen Biotech, Jiangsu, China) (Clark Bioscience, Houston, USA) containing 10% fetal bovine serum and cultured in an incubator with 37°C, 5% carbon dioxide and humidity. We used a 25mM glucose concentration as an in vitro experiment to simulate a high-sugar environment. Cells from passages 3-5 were used and incubated in a medium containing 25mM HG or 5mM NG and 25mM mannitol as an osmotic pressure control. Human umbilical vein endothelial cells were first cultured in high glucose (HG) for 24h and then cultured in normal glucose (NG) for 2d (MM) to simulate a transient high-sugar environment in vitro. Plasmids were purchased from Grep Technology (Shanghai, China). According to the product instructions, plasmid transfection was performed using Lipofectamine 2000 (Life Technologies, Carlsbad, CA, USA).

[0072] 1.2 Tissue samples

[0073] The human tissue study of the present invention was approved by the Ethics Committee of the Affiliated Hospital of Xuzhou Medical University, China, and was conducted in accordance with the Declaration of Helsinki. 12 samples were taken from diabetic wounds in the amputation group, and 12 samples were taken from debridement patients with normal blood sugar levels in the normal group. All samples were from the Affiliated Hospital of Xuzhou Medical University.

[0074] 1.3RT-PCR and RT-qPCR

[0075] Cell samples were lysed using TRIzol reagent (Invitrogen). Tissue samples were ground into fine powder in liquid nitrogen and lysed using TRIzol reagent (Invitrogen). Total RNA was extracted according to the manufacturer's protocol. Reverse transcription into cDNA was performed using a reverse transcription polymerase chain reaction kit (Vazyme). qRT-PCR was performed on a Roche LightCycler 480 instrument using SYBR Green (Vazyme). qRT-PCR detected the mRNA levels of human genes and mouse genes. Each qRT-PCR reaction was repeated at least 3 times independently to ensure reproducibility. 2 -ΔΔCT Methods Data analysis was performed. Primers for RT-qPCR and RT-PCR were designed by an online tool Sigma (Table 1).

[0076] Table 1

[0077]

[0078]

[0079] 1.4WB Analysis

[0080] The cell extract was separated by 6-15% precast gel SDS-PAGE, and then the protein was transferred to a nitrocellulose membrane and incubated with the primary antibody (1:1000 dilution) at 4°C overnight, and then incubated with the secondary antibody (1:2000 dilution) at room temperature for 1.5 hours. The immune response bands were identified using a Tanon scanning device (Tanon Science & Technology). Antibody information is shown in Table 2.

[0081] Table 2

[0082]

[0083]

[0084] 1.5 Cell migration, wound healing and tube formation assays

[0085] Transwell chamber (24-well culture plate, 8 μm pore size) was used to detect the migration ability of HUVECs. The cell concentration was adjusted to 2.5×105 cells / ml, and then add 200μl of cell suspension to the upper chamber of the migration well. 600μl of complete culture medium was loaded at the bottom. After 24h, the cells on the upper layer of the Transwell chamber were removed with a cotton swab, fixed with 4% paraformaldehyde for 30min, and stained with crystal violet for 20min. The number of migrated or invaded cells was counted in 5 fields under an Olympus IX83 optical microscope. Each experiment was repeated and analyzed 3 times. Wound healing and tube formation assays were routine detection methods.

[0086] 1.6EdU

[0087] EdU detection was performed according to the instructions of the Cell-Light EdUApollo567 in vitro kit (RiboBio, Guangzhou, China) to evaluate the proliferation ability of cells. Cells were seeded in 24-well culture plates and incubated for 24 h. 10 μM EdU solution was added in a cell culture incubator for 2 h. Then, they were fixed with 4% paraformaldehyde for 30 min, permeabilized with 0.3% Triton for 10 min, stained with Apollo mixture for 30 min, and finally stained with Hoechst33342 for 10 min. Representative images were obtained on an Olympus IX83 optical microscope (Olympus, Center Valley, USA). The cell proliferation rate was calculated by the ratio of EdU-positive cells (red) to Hoechst-positive cells (blue).

[0088] 1.7 EMSA

[0089] MSA detection was performed using a chemiluminescent EMSA Detection Kit (Chemiluminescent EMSA Detection Kit). Briefly, biotin-labeled in vitro cyclized 5 primers (2 nM) were incubated with HNRNPL protein. Unlabeled 5 primers (10 mM) were used as competitors. PAGE reactions were performed using native gels, and after transfer to nylon membranes, biotin-labeled RNA was detected using streptavidin-HRP conjugates and ECL.

[0090] 1.8 Co-immunoprecipitation

[0091] The cells were dissolved in 500 ml of immunoprecipitation buffer, centrifuged at 12000 g for 30 min, incubated with the corresponding antibodies, washed overnight at 4 °C in immunoprecipitation buffer, and then added to SDS loading buffer to detect the interaction between proteins. Western blot analysis.

[0092] 1.9 Analysis of alternative splicing events

[0093] We used SUPPA2 v2.3 to calculate seven alternative splicing events (ASEs) through RNA-seq annotation, including A3 / A5 (alternative 3′ and alternative 5′ splice sites), AF / AL (alternative first and last exons), SE (skipped exon), RI (retained intron), and MX (mutually exclusive exons). Specifically, we used the generateEvent command in SUPPA2 with the -i option on the GTF file downloaded from the GENCODE database. Then, the PSI (percent spliced-in) level of each ASE was calculated using the psiPerEvent command based on the transcript-level expression matrix generated by StringTie and the ioe file generated by generateEvent. ASEs were further filtered to generate high-confidence events by retaining events with an average PSI value ≥ 0.05 in ≥ 75% of the samples. To detect differential splicing events, T-test was used to detect differential splicing events. DEAS events with p-value ≤ 0.05 and |ΔPSI| ≥ 0.1 were considered statistically significant.

[0094] 1.10 Establishment of diabetic nude mouse wound model

[0095] Five-week-old male nude mice were purchased from GemPharmatech (Nanjing, China) and housed under certain sterile conditions. All animal studies were approved by the Animal Care and Ethics Committee of Xuzhou Medical University (Project No.: 202311T024). After fasting for 12 h, STZ (65 mg / kg; Sigma, Missouri, USA) dissolved in pH 4.5 citrate buffer was injected intraperitoneally. Blood glucose was measured once every 7 days, and mice with blood glucose ≥16.7 mmol / l for 4 consecutive weeks were considered diabetic mice. After sodium pentobarbital anesthesia, full-thickness skin wounds with a diameter of 1.0 cm were made on the back of the mice.

[0096] 1.11 Wound closure assessment

[0097] Thirty-two diabetic nude mice and eight normal nude mice were divided into five groups, with eight mice in each group. They were blank group (normal mouse wound healing model), control group (diabetic mice injected with PBS), ASO-NC group (injected with ASO-NC), ASO-RAB11FIP3-FL group and ASO-RAB11FIP3-Δ6 group. The wounds were photographed and analyzed using Image J software on the 0th and 14th days after injury. Three mice were randomly selected for data measurement. The wound healing rate was determined as follows: Wound healing index (%) = (1-unhealed wound area / original wound area) 100%.

[0098] 1.12 H&E and Masson staining

[0099] The paraffin sections were dewaxed, stained with hematoxylin water for 3 to 5 minutes, rinsed with pure water, and placed in 85 and 95% graded alcohol for 5 minutes. Finally, we placed them in eosin staining solution for 5 minutes. We placed the dehydrated paraffin sections in Masson staining solution, washed with tap water, and finally observed under a microscope.

[0100] 1.13 Statistical analysis

[0101] SPSS 22.0 was used for statistical analysis, and GraphPad Prism 9 was used to visualize all the results. The results are expressed as mean ± standard deviation (SD). Student's t test or one-way analysis of variance was used for statistical analysis. P < 0.05 was considered statistically significant.

[0102] 2. Experimental results

[0103] 2.1 Identification of AS events caused by transient hyperglycemia

[0104] We incubated HUVECs in high glucose (HG) medium for 24 h and then in normal glucose (NG) medium for different time periods: 3 days (MM) to establish high glucose-induced in vitro metabolic memory conditions. We found that high glucose caused damage to human umbilical vein endothelial cells (HUVECs), which could not be reversed even after restoration of normal glucose (NG), indicating that transient high glucose caused persistent damage to vascular endothelial cells, resulting in decreased proliferation, migration and tube formation abilities of vascular endothelial cells ( Figure 1 AD). To explore the effects of MM on vascular endothelial cells, we identified a series of abnormal splicing isoforms by RAN sequencing. We identified a total of 114,621 AS events, of which ES events accounted for the majority ( Figure 2 A). Differential analysis of SE events between NC, HG, and MM ultimately identified 869,814 differentially expressed SE (DEAS) events with p-value < 0.05 and |ΔPSI| > 0.1 ( Figure 2 B). In the confirmed DEAS events, the PSI value of RAB11FIP3 (ENSG00000090565) and the ratio of RAB11FIP3 (FL / Δ6) were significantly increased in HG and MM ( Figure 2 C and Figure 1 J). Analysis based on PSI ratios showed that 3 genes were upregulated in both HG and MM (SAT1, SAT1, TMEM234), and 4 genes were downregulated in both MM and NC (TMEM40, MORF4L2, RAB11FIP3, SNX1) ( Figure 2D). Next, we cultured HUVECs in MM and HG environments and performed RT-PCR experiments to verify the results, and finally identified RAB11FIP3-FL and RAB11FIP3-Δ6 ( Figure 2 I and Figure 1 H). To verify the RAB11FIP3-FL and RAB11FIP3-Δ6 transcripts, we designed three pairs of primers, of which Primer 1 covered the fragment from exon 5 to exon 7 ( Figure 2 G). In addition, we designed primer 2 covering the exon 5 / exon 6 and exon 6 / exon 7 junctions to quantify RAB11FIP3-FL transcripts. Primer 3 covering the exon 5 / exon 7 junction was used to quantify RAB11FIP3-Δ6 transcripts. Sanger sequencing results confirmed the presence of RAB11FIP3-Δ6 isoforms in HUVECs ( Figure 2 H). Next, qRT-PCR results showed that the expression level of RAB11FIP3-FL was significantly upregulated in HUVECs, while the expression level of RAB11FIP3-Δ6 did not change significantly ( Figure 2 E, F). Further analysis showed that high sugar significantly enriched the ratio of RAB11FIP3 at the RNA and protein levels (FL / Δ6) ( Figure 2 I). At the same time, we also found the same expression pattern in clinical diabetic foot ulcer samples. Compared with normal subjects, the ratio of RAB11FIP3 (FL / Δ6) was significantly increased in DFUs tissues ( Figure 2 K,J). These data suggest that there is an imbalance in alternative splicing of RAB11FIP3 exon 6 in DFUs.

[0105] 2.2RAB11FIP3-FL inhibits endothelial cell migration and diabetic wound healing

[0106] Considering that RAB11FIP3-FL is highly expressed in both HG and MM environments, it is also highly expressed in clinical samples. We speculated that RAB11FIP3-FL may be a pathogenic subtype of the MM phenomenon. In addition, we were curious about the role of RAB11FIP3-Δ6. To verify our hypothesis, we performed Transwell and wound healing experiments and found that si-RAB11FIP3-FL significantly promoted the cell migration ability of HUVECs ( Figure 3 AD). In addition, si-RAB11FIP3-FL significantly promoted the proliferation and lumen formation ability of vascular endothelial cells. ( Figure 3 EH). Similarly, our results showed that RAB11FIP3-FL overexpression significantly inhibited the cell proliferation, cell migration and lumen formation abilities of endothelial cells ( Figure 4Interestingly, expression of RAB11FIP3-Δ6 had no significant effect on cell proliferation, migration, and angiogenesis ( Figure 3 AH and Figure 4 AJ). In summary, our experiments showed that RAB11FIP3-FL inhibited the proliferation, migration and tube formation of HUVECs under MM conditions.

[0107] 2.3HNRNPL regulates alternative splicing events of RAB11FIP3

[0108] Splicing factors play an important role in regulating the occurrence of AS events. To gain a deeper understanding of how splicing factors regulate the inclusion of RAB11FIP3 exon 6, we used RBPmap (http: / / rbpmap.technion.ac.il / ) to predict potential binding partners of RAB11FIP3 pre-mRNA. The results showed that the inclusion or exclusion of RAB11FIP3 exon 6 may be regulated by three splicing factors (ESRP, HNRNPH1, HNRNPL) ( Figure 5 A). These analyses identified candidate splicing factors that could affect exon 6 inclusion or exclusion. We then silenced each splicing factor individually in HUVECs and assessed the ratio of RAB11FIP3 (FL / Δ6) by RT-PCR. Our results showed that knockdown of HNRNPL significantly enhanced RAB11FIP3 exon 6 exclusion, whereas knockdown of ESRP or HNRNPH1 had no significant effect on its expression ( Figure 6 AF). Based on the prediction of HNRNPL binding sites to RAB11FIP3 pre-mRNA, we designed five primers targeting the HNRNPL binding motif ACACCA, which is significantly enriched near the intron-exon and exon-intron boundaries of exon 6 ( Figure 5 B). We then performed RIP-qPCR assay using anti-HNRNPL antibody to determine whether HNRNPL directly binds to HNRNPL mRNA. The results showed that anti-HNRNPL directly binds to RAB11FIP3 pre-mRNA, while IgG does not bind to RAB11FIP3 pre-mRNA, especially in the region of primer set 3 ( Figure 5 C). At the same time, we found that HNRNPL has many binding sites with RAB11FIP3-pre mRNA ( Figure 6 H). Further analysis showed that HNRNPL knockdown significantly reduced the expression ratio of RAB11FIP3-FL / RAB11FIP3-Δ6 at the RNA and protein levels ( Figure 5D, F). This suggests that HNRNPL, as a splicing factor, can increase the expression of RAB11FIP3-FL mRNA and protein levels by promoting the inclusion of exon 6. Next, following the 5 pairs of primers mentioned above, we developed 5 pairs of RNA probes, each labeled with biotin (Table 1). We confirmed through EMSA experiments that Probe 3 binds to HNRNPL, and the binding strength increases with the increase of probe concentration. The presence of cold probe can effectively inhibit this interaction ( Figure 5 F, G). We then changed the ACACACA motif to AGAGAAC using an online random mutagenesis tool (http: / / www.detaibio.com / sms2 / mutate_dna.html), and we observed that the binding between probe 3 and HNRNPL was disrupted ( Figure 5 H). This finding highlights the key role of the ACACCA motif in regulating the interaction between HNRNPL and its target RNA sequences. Altogether, these results suggest that HNRNPL promotes inclusion of exon 6 of RAB11FIP3.

[0109] 2.4HNRNPL inhibits the proliferation, migration and tube formation of HUVEC in vitro

[0110] HNRNPL is an RNA binding protein mainly located in the cell nucleus and is an important member of the HNRNP family. Studies have shown that HNRNPL is highly expressed in a variety of tumors and plays a key role in tumor progression. We found that HNRNPL is highly expressed in the MM environment ( Figure 6 H). Subsequent experiments showed that HNRNPL knockdown significantly enhanced the cell proliferation, migration and tube formation of HUVECs under MM conditions ( Figure 7 AH). In contrast, HNRNPL overexpression significantly inhibited the cell proliferation, migration and tube formation of HUVECs ( Figure 7 Furthermore, interestingly, the deleterious effects caused by HNRNPL overexpression could be alleviated by knockdown of RAB11FIP3-FL ( Figure 8 AE). Taken together, these findings suggest that HNRNPL causes endothelial injury by promoting inclusion of exon 6 of the RAB11FIP3 gene and expression of RAB11FIP3-FL. However, the exact effects of RAB11FIP3-FL on cell proliferation and migration ability remain unclear.

[0111] 2.5RAB11FIP3-FL enhances ubiquitination-mediated HIF-1α degradation

[0112] Numerous studies have highlighted the important role of HIF-1α in the wound healing process in diabetes. Therefore, our study aimed to explore the potential effects of RAB11FIP3-FL on endothelial function under the HIF-1α signaling pathway. Next, our Western blot analysis showed that silencing RAB11FIP3-FL significantly increased the expression of HIF-1α at the protein level ( Fig. 9 A), while overexpression of RAB11FIP3-FL significantly reduced the protein expression of HIF-1α ( Fig. 9 B). Interestingly, our data showed that no significant changes in HIF-1α mRNA expression were observed in either knockdown or overexpression of RAB11FIP3-FL ( Fig. 9 C, D). Exogenous co-immunoprecipitation (co-IP) showed that HIF-1α was co-precipitated by RAB11FIP3-FL, indicating an interaction between the two proteins ( Fig. 9 E, F). In addition, RAB11FIP3-FL-mediated HIF-1α / VEGFA downregulation could be rescued by the proteasome inhibitor MG132 ( Fig. 9 G), suggesting that proteasome / ubiquitin-mediated degradation is involved. RAB11FIP3-FL increased the turnover rate of HIF-1α, while RAB11FIP3-FL decreased the turnover rate of HIF-1α upon treatment with cycloheximide (CHX), which blocks de novo protein synthesis ( Fig. 9 H, I). VHL-dependent ubiquitin-proteasome degradation is the main regulatory mechanism of HIF-1α stability. To investigate whether RAB11FIP3-FL affects the ubiquitination and proteasomal degradation of HIF-1α through VHL, Flag-RAB11FIP3-FL was transfected into HUVECs. Our results showed that even when VHL was knocked out, RAB11FIP3-FL promoted the ubiquitination of HIF-1α ( Fig. 9 M). In addition, even when VHL was knocked out, RAB11FIP3-FL could inhibit the steady-state expression of HIF-1α ( Fig. 9 K). In addition, overexpression of RAB11FIP-FL can synergize with VHL to promote the degradation of HIF-1α ( Fig. 9 L). Taken together, all these data indicate that RAB11FIP3-FL stabilizes HIF-1α through ubiquitination and proteasomal degradation even when VHL is knocked out.

[0113] 2.6RAB11FIP3-FL binds to NEDD4L to promote HIF-1α ubiquitination and degradation

[0114] Therefore, RAB11FIP3-FL may promote the ubiquitination of HIF-1α through an E3 ligase different from VHL. To identify the E3 ligase, we performed IP / MS analysis ( Fig.10 A). Of the 564 proteins identified by immunoprecipitation, we carefully compared them with known E3 ligases and identified NEDD4L as the most promising candidate due to its strong binding to RAB11FIP3-FL ( Fig.10 B and Figure 8 F). Co-IP experiments showed that NEDD4L specifically bound to RAB11FIP3-FL but not RAB11FIP3-Δ6 ( Fig.10 C). These results suggest that NEDD4L may function as an E3 ligase for HIF-1α. Interestingly, domain mapping revealed that NEDD4L strongly bound to both the full-length and truncated forms of RAB11FIP3-FL (amino acid residues 1-588), but not to the truncated form (1-422) ( Fig.10 E, F). This suggests that aberrant splicing of exon 6 leads to defective synthesis of the RAB11FIP3 ABD domain. Therefore, this impairment may underlie the disruption of the interaction between RAB11FIP3-Δ6 and NEDD4L. Furthermore, NEDD4L-mediated downregulation of HIF-1α can be antagonized by the proteasome inhibitor MG132 ( Fig.11 D). Endogenous and exogenous co-IP experiments showed that HIF-1α and NEDD4L were co-immunoprecipitated, suggesting that there is an interaction between the two proteins ( Fig.10 G,H). To investigate whether the E3 ligase NEDD4L is involved in RAB11FIP3-FL-mediated HIF-1α inhibition, we co-transfected HA-NEDD4L, FLAG-RAB11FIP3-FL, and His-HIF-1α into HEK293T cells. Co-IP experiments showed that RAB11FIP3-FL promoted the binding of HIF-1α to NEDD4L ( Fig.10 I). By administering CHX, we found that NEDD4L decreased the turnover rate of HIF-1α, while knockdown of NEDD4L increased the turnover rate of HIF-1α ( Fig.10 J, K). We consistently found that NEDD4L overexpression enhanced the ubiquitination of HIF-1α in a dose-dependent manner ( Fig.10L), indicating that NEDD4L is a specific E3 ligase for HIF-1α. These findings together demonstrate that NEDD4L is a specific E3 ligase for HIF-1α. In summary, although VHL is considered to be the E3 ligase of HIF-1α, NEDD4L also significantly promotes the ubiquitination regulation of HIF-1α. In addition, RAB11FIP3-FL can promote the binding of NEDD4L and HIF-1α and subsequent ubiquitin-mediated degradation. The reason why RAB11FIP3-Δ6 cannot interact with NEDD4L may be due to the deletion of exon 6, which is essential for the formation of the ABD domain.

[0115] 2.7ASO-RAB11FIP3-FL promotes diabetic wound healing

[0116] To explore the role of different RAB11FIP3 transcripts in wound healing in vivo, we designed antisense oligonucleotides (ASOs) targeting the degradation of RAB11FIP3-FL and RAB11FIP3-Δ6 (Table 3), and injected ASOs around the wound to observe the wound healing rate. Our study found that the wound healing rate of mice injected with ASO-RAB11FIP3-FL was significantly accelerated, while the wound edge of mice injected with ASO-RAB11FIP3-Δ6 showed no significant changes compared with the control group ( Fig.11 A, B). Re-epithelialization is essential for wound healing. We found that ASO-RAB11FIP3-FL also improved re-epithelialization and reduced excessive inflammatory cell infiltration and collagen deposition ( Fig.11 C, D). Histological analysis of Masson-stained sections showed that at 14 days after injury, the collagen fibers in the diabetic wounds treated with ASO-RAB11FIP3-FL were thicker and more regular than those in the control group ( Fig.11 E). In addition, there was no statistical difference between ASO-RAB11FIP3-Δ6 and the control group. In addition, the results of immunofluorescence detection showed that the expression levels of CD31 and α-SMA in the ASO-RAB11FIP3-Δ6 group were higher than those in the control group ( Fig.11 F, G). In addition, we excised and homogenized the mouse skin to analyze the secretion of VEGF in the wound. Mice injected with ASO-RAB11FIP3-FL can stimulate the secretion of VEGF ( Fig.11 H). In summary, our experiments showed that RAB11FIP3-FL knockout enhanced the proliferation, migration and tube formation ability of vascular endothelial cells. In addition, RAB11FIP3-FL knockout promoted the expression of VEGF, thereby promoting wound angiogenesis and accelerating the healing process of diabetic wounds.

[0117] Table 3

[0118]

[0119]

[0120] 2.8 Using normal tissues and diabetic chronic wound tissues from clinical samples to measure the ratio of long and short transcripts by RT-PCR and perform ROC analysis

[0121] The RAB11FIP3-FL / RAB11FIP3-Δ6 ratio has important diagnostic value in distinguishing diabetic patients from healthy people ( Fig.12 ), the AUC of this ratio was 0.8033, which can be used as a potential biomarker for early detection of diabetes. The differential expression of RAB11FIP3 variant transcripts may be related to the key pathophysiological processes of diabetes. This ratio can also be used to monitor disease progression and guide therapeutic interventions.

Claims

1. Use of a reagent for detecting biomarkers in the preparation of a product for diagnosing diabetes, characterized in that: The biomarker is RAB11FIP3.

2. The use according to claim 1, characterized in that: The product determines whether the subject has diabetes or is at risk of the disease by measuring the ratio of the RAB11FIP3 full-length transcript to the RAB11FIP3 exon 6 deletion transcript in the sample, wherein the RAB11FIP3 full-length transcript is referred to as RAB11FIP3-FL, and the RAB11FIP3 exon 6 deletion transcript is referred to as RAB11FIP3-Δ6; Preferably, the ratio of RAB11FIP3-FL to RAB11FIP3-Δ6 is significantly overexpressed in diabetic patients; Preferably, the diabetes includes diabetic foot ulcers and metabolic memory of diabetes; Preferably, the sample is from a human or non-human mammal; Preferably, the sample comprises tissue, blood, plasma, serum, saliva, urine, colon excretion, cerebrospinal fluid, sputum, sweat, breast milk, tears, bile, gastric juice, interstitial fluid, oral or nasal swab, aqueous humor, amniotic fluid, pleural fluid; Preferably, the reagents include primers, probes, antisense oligonucleotides, aptamers or antibodies specific for detecting RAB11FIP3-FL and RAB11FIP3-Δ6.

3. Use of a reagent for detecting a biomarker in the preparation of a product for diagnosing hyperglycemia, characterized in that: The biomarker is RAB11FIP3; Preferably, the product determines whether the subject suffers from hyperglycemia or is at risk of the disease by measuring the ratio of RAB11FIP3-FL to RAB11FIP3-Δ6 in the sample; Preferably, the ratio of RAB11FIP3-FL to RAB11FIP3-Δ6 is significantly overexpressed in patients with hyperglycemia.

4. A system for predicting diabetes / hyperglycemia using biomarkers, characterized in that: include: A data acquisition unit, used to obtain data of biomarkers of a target subject, wherein the biomarkers include expression levels of RAB11FIP3-FL and RAB11FIP3-Δ6; A data processing unit, used for calculating the ratio of the expression levels of RAB11FIP3-FL and RAB11FIP3-Δ6 according to the obtained data to obtain a calculated value; a result output unit, for comparing the calculated value obtained by the data processing unit with the control value of the control group; if the calculated value is higher than the control value of the control group, the computer determines that the target subject suffers from diabetes / hyperglycemia or has a high risk of suffering from diabetes / hyperglycemia; if the calculated value is lower than or equal to the control value of the control group, the computer determines that the target subject does not suffer from diabetes / hyperglycemia or has a low risk of suffering from diabetes / hyperglycemia; Preferably, the control value of the control group is a detection value obtained by pre-detecting the expression levels of RAB11FIP3-FL and RAB11FIP3-Δ6 of normal subjects and calculating the ratio; Preferably, the diabetes includes diabetic foot ulcer and metabolic memory of diabetes.

5. A product for diagnosing diabetes / hyperglycemia, characterized in that: The product includes a reagent for detecting the biomarker RAB11FIP3; Preferably, the biomarker RAB11FIP3 includes detecting RAB11FIP3-FL and RAB11FIP3-Δ6; Preferably, the product uses the ratio of the expression levels of RAB11FIP3-FL and RAB11FIP3-Δ6 to determine whether a subject has diabetes / hyperglycemia or is at risk of developing the disease.

6. The product according to claim 5, characterized in that The reagents include specific primers, probes, antisense oligonucleotides, aptamers or antibodies for detecting the biomarkers.

7. Use of RAB11FIP3-FL inhibitors in the preparation of pharmaceutical compositions for the treatment and prevention of diabetes / hyperglycemia; Preferably, the inhibitor includes inhibitors of RAB11FIP3-FL, RAB11FIP3-Δ6, and HNRNPL; Preferably, the diabetes includes diabetic foot ulcer and metabolic memory of diabetes.

8. Use of enhancers of RAB11FIP3-FL and inhibitors of RAB11FIP3-Δ6 in the preparation of products regulating HIF-1α ubiquitination and degradation; Preferably, the enhancer includes enhancers of RAB11FIP3-FL, RAB11FIP3-Δ6, and HNRNPL.

9. A computer-aided prediction device, characterized in that: include: A memory and a processor, wherein the memory is used to store program instructions, and the processor is used to call the program instructions. When the program instructions are executed, the unit functions of the system for predicting diabetes / hyperglycemia using biomarkers as described in claim 4 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the unit functions of the system for predicting diabetes / hyperglycemia using biomarkers according to claim 4.

Images