Application of circular RNA hsa_circ_0083215 in the prognosis of bariatric surgery

Abstract

This invention provides the application of circular RNA hsa_circ_0083215 in the prognosis of bariatric surgery, belonging to the field of biomedical technology. This circular RNA is stably detectable in intraoperative visceral adipose tissue, and its expression level is significantly correlated with postoperative weight loss success, exhibiting good independent predictive ability. This invention directly solves the problem of clinically being unable to assess individualized weight loss effects before surgery by detecting specific molecular markers preoperatively, enabling doctors to predict surgical efficacy in advance and optimize treatment plans accordingly. The method is based on routinely obtained tissue samples during surgery, is simple to operate, and easy to promote clinically, providing a reliable foundation for the development of standardized preoperative predictive kits and contributing to the advancement of precision medicine practices in obesity treatment.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, and in particular to the application of circular RNA hsa_circ_0083215 in the prognosis of bariatric surgery. Background Technology

[0002] Obesity is a globally prevalent chronic metabolic disease characterized by significant weight gain and abnormal accumulation of body fat, often accompanied by metabolic syndrome manifestations such as insulin resistance, hyperlipidemia, and hypertension. According to data from the World Health Organization (WHO), the global obesity rate continues to rise, and obesity has become a significant risk factor for chronic diseases such as type 2 diabetes, cardiovascular disease, and certain cancers. Bariatric surgery (such as sleeve gastrectomy and Roux-en-Y gastric bypass) is one of the most effective treatments for moderate to severe obesity and is widely used in clinical practice. Bariatric surgery not only significantly reduces weight but also improves insulin sensitivity, regulates appetite-related hormones, and achieves diabetes remission in many patients.

[0003] However, in actual clinical follow-up, it was found that despite relatively consistent surgical methods and postoperative interventions, there were significant individual differences in weight loss outcomes among patients. Some patients did not reach their ideal weight loss goals (%EWL>60%) within one or even two years after surgery, and some even experienced weight rebound. At present, the assessment of surgical efficacy mainly relies on postoperative indicators, such as total weight loss percentage (TWL%), changes in body mass index (BMI), or excess weight loss percentage (%EWL). These indicators can only be obtained after a long period of time after surgery, making it impossible to predict preoperative risks and providing a basis for preoperative stratification and individualized treatment planning.

[0004] To address this issue, researchers have recently attempted to identify detectable molecular biomarkers before surgery. Existing studies have shown that the expression levels of certain mRNAs, miRNAs, and lncRNAs in adipose tissue are associated with obesity, metabolic syndrome, and insulin resistance. For example, LINC00278 and circSAMD4A are considered to potentially participate in energy metabolism regulation and adipose tissue function. However, most of these studies focus on mechanistic exploration, have limited sample sizes, lack postoperative efficacy verification, and have not yet developed standardized methods for clinical prediction. Summary of the Invention

[0005] The purpose of this invention is to provide the application of circular RNA hsa_circ_0083215 in the prognosis of bariatric surgery, which can accurately predict the weight loss effect one year after surgery based on visceral adipose tissue samples using %EWL.

[0006] To achieve the above-mentioned objectives, the present invention provides the following technical solution:

[0007] This invention provides an application of a predictive biomarker in the preparation of products for the prognosis or effect evaluation of weight loss surgery, wherein the predictive biomarker contains a circular RNA hsa_circ_0083215.

[0008] The present invention also provides an application of a kit in the preparation of products for the prognosis or effect evaluation of weight loss surgery, the kit comprising reagents for detecting the expression level of hsa_circ_0083215.

[0009] Preferably, the reagent used to detect the expression level of hsa_circ_0083215 includes primer pairs that specifically amplify hsa_circ_0083215.

[0010] The present invention also provides an application of a kit in the preparation of products for the prognosis or effect evaluation of weight loss surgery, the kit comprising primer pairs for specific amplification of hsa_circ_0083215 and quantitative PCR reaction reagents.

[0011] Preferably, the primer pair includes:

[0012] The nucleotide sequence is as shown in the forward primer of SEQ ID NO.1;

[0013] The nucleotide sequence is shown in the reverse primer of SEQ ID NO.2.

[0014] Preferably, the nucleotide sequence of the amplification product of the primer pair is shown in SEQ ID NO.3.

[0015] Preferably, the prognosis or effect assessment of the weight loss surgery is reflected by the percentage of excess weight loss one year after surgery. A percentage of excess weight loss greater than 60% one year after surgery is considered to have a better prognosis or better effect.

[0016] Conversely, it is recorded as a poor prognosis or poor outcome.

[0017] This invention also provides the application of circular RNA hsa_circ_0083215 as a target in the preparation of diagnostic reagents for the prognosis of bariatric surgery.

[0018] The present invention also provides a prognostic assessment system for bariatric surgery, the system including a computing device for judging the effect of bariatric surgery based on the expression level of circular RNA hsa_circ_0083215.

[0019] Preferably, the system further includes any one or more of the following components:

[0020] A detection device for detecting the expression level of the circular RNA hsa_circ_0083215;

[0021] A reference device is used to receive the expression level output by the detection device and compare it based on known grouping information of the successful weight loss group and the unsuccessful weight loss group;

[0022] The analysis device is used to compare the expression level of the circular RNA hsa_circ_0083215 of the subjects with known group information and output the prognostic assessment results.

[0023] The beneficial effects of this invention are:

[0024] This invention is the first to propose using the circular RNA hsa_circ_0083215 as a molecular biomarker for preoperative prediction of the efficacy of bariatric surgery (based on EWL% one year postoperatively). This circular RNA is stably detectable in intraoperative visceral adipose tissue, and its expression level is significantly correlated with postoperative weight loss success, demonstrating good independent predictive ability. This invention directly addresses the challenge of preoperative assessment of individualized weight loss outcomes by detecting a specific molecular biomarker, enabling physicians to predict surgical efficacy in advance and optimize treatment plans accordingly. The method is based on routinely obtained intraoperative tissue samples, is simple to operate, and easily promoted clinically, providing a reliable foundation for the development of standardized preoperative predictive kits and contributing to the advancement of precision medicine practices in obesity treatment. Ultimately, by improving patient management and the targeting of intervention strategies, it can effectively improve the success rate of surgical treatment and the long-term health benefits for patients. Attached Figure Description

[0025] Figure 1 The graph shows the differential expression levels of hsa_circ_0083215 between the successful and unsuccessful weight loss groups.

[0026] Figure 2 ROC curves representing the expression level prediction performance of hsa_circ_0083215 in the training set;

[0027] Figure 3 ROC curves characterizing the expression level prediction performance of hsa_circ_0083215 in the validation set;

[0028] Figure 4 The effect of hsa_circ_0083215 knockdown on key genes of lipid metabolism in primary mesenchymal stem cells, as shown in Western Blot. Detailed Implementation

[0029] The technical solutions provided by the present invention will be described in detail below with reference to the embodiments, but they should not be construed as limiting the scope of protection of the present invention.

[0030] Example

[0031] This invention provides a method for predicting the prognosis of weight loss surgery based on the expression level of circular RNA hsa_circ_0083215 in visceral adipose tissue collected intraoperatively. This method uses quantitative PCR to detect circRNA expression levels and preoperatively assesses whether the patient has achieved the target weight loss one year postoperatively, using an excess weight loss percentage (%EWL) > 60% as the criterion for successful weight loss.

[0032] The specific information of the circular RNA is as follows: ID (hsa_circ_0083215), location (chr7:158554186-158590767), and Genomic length (36581).

[0033] (1) Surgical procedure selection and tissue sample acquisition

[0034] This study included obese patients who underwent laparoscopic sleeve gastrectomy at the Third People's Hospital of Chengdu. All patients signed informed consent before surgery, and the procedure was approved and registered by the ethics committee. During the surgery, visceral adipose tissue samples were harvested from the greater omentum region under laparoscopic guidance. These samples were immediately cryopreserved in liquid nitrogen and then transferred to a -80°C freezer for subsequent RNA analysis.

[0035] (2) Total RNA extraction

[0036] Total RNA was extracted from frozen adipose tissue using the following steps:

[0037] 1. Use a pre-cooled grinding rod or liquid nitrogen grinder to thoroughly grind the adipose tissue;

[0038] 2. Add 1 ml of TRIzol reagent (Invitrogen) to the ground tissue and homogenize thoroughly;

[0039] 3. Let stand for 5 minutes to lyse the cells;

[0040] 4. Add 200 μl of chloroform, shake vigorously for 15 seconds, and let stand at room temperature for 10 minutes;

[0041] Centrifuge at 14,000 rpm for 15 minutes (4°C) and collect the supernatant;

[0042] 6. Add an equal volume of isopropanol to the collected supernatant, mix gently, and let stand for at least 10 minutes;

[0043] Centrifuge at 14,000 rpm for 10 minutes (4°C), then discard the supernatant;

[0044] 8. Wash with freshly prepared 75% ethanol, centrifuge at 7500 rpm for 5 minutes (4℃), and discard the supernatant;

[0045] 9. Repeat step 8 twice;

[0046] 10. Air dry the RNA precipitate and dissolve it in RNase-free water;

[0047] 11. Use NanoDrop to determine RNA concentration and purity.

[0048] (3) Reverse transcription reaction (cDNA synthesis)

[0049] Reverse transcription was performed using PrimeScript RT Master Mix (RR036A, TaKaRa). The 10 μl reaction mixture is shown in Table 1. The reaction conditions were as follows: 37℃ for 15 minutes; 85℃ for 5 seconds; after the reaction, the mixture was immediately stored at 4℃ or -20℃.

[0050] Table 1 Reverse transcription reaction system

[0051] reagents Usage Final concentration 5X PrimeScript RT Master Mix (Perfect Real Time) 2 μl 1X Total RNA extracted from adipose tissue * <![CDATA[RNase Free dH2O]]> Up to 10 μl

[0052] * The reaction system can be scaled up as needed; a 10 μl reaction system can use up to 500 ng of total RNA.

[0053] (4) Real-time quantitative PCR (qPCR)

[0054] qPCR amplification was performed using the following 20 μl reaction mixture (see Table 2):

[0055] Table 2 Real-Time PCR Reaction System

[0056] Components 20μl system Final concentration SYBR Green qPCR Mix 10μl 1X Forward primer (10 μM) 0.4~0.8 μl 0.2~0.4 μM Reverse primer (10 μM) 0.4~0.8 μl 0.2~0.4 μM cDNA template * <![CDATA[RNase-Free ddH2O]]> Up to 20 μl

[0057] * The reaction system can be scaled up as needed; a 10 μl reaction system can use up to 500 ng of total RNA.

[0058] Primer sequences:

[0059] hsa_circ_0083215 forward primer (5'→3'): TGAAGACCCAGACAAGGATGA, as shown in SEQ ID NO.1;

[0060] hsa_circ_0083215 reverse primer (3'→5'): CGCACGGCTGGTTCTATAGTT, as shown in SEQ ID NO.2;

[0061] The length of the amplified product of hsa_circ_0083215 is 126bp, and the specific sequence is: CTTTTTAGGAAGTCTTATGATTGACCTCATTGAAGTTGAAAAGGAGCGCCTTTTAGATGAAACTGTAAAACACATGTGGCCTTTCATTTGCCAATTTATAGAGAAGTTGTTTCGAGA, as shown in SEQ ID NO.3.

[0062] hGAPDH (internal reference) forward primer (5'→3'): GAAAGCCTGCCGGTGACTAA, as shown in SEQ ID NO.4;

[0063] hGAPDH (internal reference) reverse primer (3'→5'): GCCAATACGACCAAATCAGAG, as shown in SEQ ID NO.5, PCR product length 150bp.

[0064] A two-step PCR reaction program was used. First, pre-denaturation was performed at 95°C for 5 min, cycle number 1. Then, denaturation and annealing extension data were collected, with 40 cycles at 95°C for 10 sec followed by 60°C for 30 sec. Finally, melting curve analysis was performed according to the instrument's recommended settings. Each sample was tested in triplicate, and the relative expression level was calculated using the ΔΔCt method.

[0065] (5) Patient information and outcome grouping

[0066] A total of 87 obese patients were included, with the first 54 serving as the training set for building the predictive model and the latter 33 serving as the independent validation set. All patients completed a one-year follow-up after surgery, and %EWL was calculated. The calculation formula is: %EWL = (preoperative weight - postoperative weight) / (preoperative weight - ideal weight) × 100%. Ideal weight (kg) is calculated as height (cm) - 105 for men and height (cm) - 100 for women. %EWL > 60% was considered "successful weight loss," and ≤ 60% was considered "failed weight loss." Table 3 shows the basic information of the participants in the training set, and Table 4 shows the basic information of the participants in the validation set.

[0067] Table 3. Basic Information of Participants in the Training Set

[0068] serial number gender Age (years) Preoperative weight (kg) Height (cm) Postoperative weight (kg) 1 year later relative expression level of hsa_circ_0083215 Ideal weight (kg) Excess weight loss percentage (%EWL) Was the weight loss surgery successful? 1 female 35 80.5 165 92.9 1.208 65 -0.800 no 2 female 22 80.0 162 72 14.305 62 0.444 no 3 female 31 75.5 153 64 1 53 0.511 no 4 female 29 89.0 160 74 15.345 60 0.517 no 5 female 28 110.0 160 84 15.419 60 0.520 no 6 female 26 120.0 168 92.3 7.351 68 0.533 no 7 female 39 71.0 147 58 16.205 47 0.542 no 8 male 22 120.0 180 95 16.367 75 0.556 no 9 female 37 70.0 156 62 8.05 56 0.571 no 10 male 30 123.0 179 95 16.646 74 0.571 no 11 female 23 104.0 162 80 16.934 62 0.571 no 12 male 33 130.0 188 103 17.087 83 0.574 no 13 female 29 96.5 160 75 17.266 60 0.589 no 14 female 43 84.0 157 68 3.619 57 0.593 no 15 female 22 105.0 163 80 17.604 63 0.595 no 16 female 33 92.0 162 74 3.772 62 0.600 no 17 female 30 84.0 164 72 18.013 64 0.600 no 18 female 23 87.0 162 72 21.891 62 0.600 no 19 male 23 121.0 175 90 7.672 70 0.608 yes 20 female 31 69.0 153 59 1.428 53 0.625 yes 21 female 24 101.0 174 84 23.238 74 0.630 yes 22 male 34 97.3 167 75 6.403 62 0.632 yes 23 female 28 75.0 158 64 8.614 58 0.647 yes 24 female 30 72.0 155 61 26.692 55 0.647 yes 25 female 28 95.0 161 72.7 1.553 61 0.656 yes 26 female 21 105.0 168 80.7 1.569 68 0.657 yes 27 female 28 114.0 178 90 8.903 78 0.667 yes 28 female 26 95.0 163 73 3.982 63 0.688 yes 29 female 33 100.0 162 73.7 6.958 62 0.692 yes 30 male 25 135.0 193 102 4.533 88 0.702 yes 31 female 28 74.0 157 62 1.601 57 0.706 yes 32 female 26 79.0 159 64.8 1.767 59 0.710 yes 33 female 32 91.0 155 65 1.815 55 0.722 yes 34 female 24 72.5 155 59.7 38.396 55 0.731 yes 35 female 44 73.0 158 62 1.857 58 0.733 yes 36 male 28 129.0 172 77.5 9.445 67 0.831 yes 37 female 23 115.0 160 67.9 2.188 60 0.856 yes 38 male 19 130.0 171 75 2.572 66 0.859 yes 39 female 24 123.0 164 72.2 10.438 64 0.861 yes 40 female 31 89.0 154 58 5.045 54 0.886 yes 41 male 31 120.0 174 71.4 11.243 69 0.953 yes 42 female 19 103.0 164 65 7.875 64 0.974 yes 43 female 37 117.0 164 65 2.723 64 0.981 yes 44 male 28 103.0 165 60 2.78 60 1.000 yes 45 male 36 141.5 180 75 6.962 75 1.000 yes 46 female 27 118.5 162 60 11.693 62 1.035 yes 47 male 28 100.0 167 58.8 3.256 62 1.084 yes 48 female 34 100.0 163 59.1 5.396 63 1.105 yes 49 female 24 111.0 165 60 12.348 65 1.109 yes 50 female 20 93.0 159 55 5.483 59 1.118 yes 51 female 35 94.0 160 55 12.636 60 1.147 yes 52 female 24 110.0 170 62 6.083 70 1.200 yes 53 female 22 118.5 162 50 3.379 62 1.212 yes 54 female 27 108.0 163 52.5 6.097 63 1.233 yes

[0069] Table 4. Basic Information of Participants in the Validation Set

[0070] serial number gender Age (years) Preoperative weight (kg) Height (cm) Postoperative weight (kg) 1 year later relative expression level of hsa_circ_0083215 Ideal weight (kg) Excess weight loss percentage (%EWL) Was the weight loss surgery successful? 1 female 32 105.9 162.5 89 11.165 62.5 0.389 no 2 male 30 102.0 173 88 5.166 68 0.412 no 3 female 31 116.7 171 96 15.067 71 0.453 no 4 female 40 105.3 159.1 83 16.826 59.1 0.483 no 5 female 44 92.2 164.9 78 26.956 64.9 0.520 no 6 male 41 121.1 174.1 93 13.243 69.1 0.540 no 7 female 52 92.0 149.3 68 9.812 49.3 0.562 no 8 female 31 114.5 164 85 10.925 64 0.584 no 9 female 37 129.0 162.6 90 9.809 62.6 0.587 no 10 male 43 102.7 169.5 80 4.205 64.5 0.594 no 11 male 33 161.2 176.1 106 2.473 71.1 0.613 yes 12 male 35 79.3 169.3 70 1.341 64.3 0.620 yes 13 female 38 83.3 157.6 65 5.423 57.6 0.712 yes 14 female 37 84.9 161.1 67.8 1.679 61.1 0.718 yes 15 female 34 94.0 163.4 72 7.756 63.4 0.719 yes 16 female 38 81.9 155.2 61.8 6.509 55.2 0.753 yes 17 female 39 98.5 156.2 66 4.151 56.2 0.768 yes 18 female 46 102.8 172.5 77.8 3.964 72.5 0.825 yes 19 female 38 86.4 161.7 66 6.624 61.7 0.826 yes 20 male 29 95.7 170.4 70 5.44 65.4 0.848 yes 21 female 35 112.8 162.9 70 10.2 62.9 0.858 yes 22 female 44 89.8 158.6 63 21.537 58.6 0.859 yes 23 female 26 95.9 159.7 64 3.192 59.7 0.881 yes 24 male 29 117.8 169.4 70 10.76 64.4 0.895 yes 25 male 35 133.3 178.2 78 8.523 73.2 0.920 yes 26 female 33 82.9 153 55 3.815 53 0.933 yes 27 male 30 120.0 174 68 4.309 69 1.020 yes 28 female 31 93.0 166.4 65 9.744 66.4 1.053 yes 29 female 57 85.9 164 62 12.827 64 1.091 yes 30 female 32 71.3 148.5 45 2.29 48.5 1.154 yes 31 female 28 73.6 160 57 7.135 60 1.221 yes 32 male 41 81.7 171.1 62 4.349 66.1 1.263 yes 33 female 48 79.4 165.6 56 5.974 65.6 1.696 yes

[0071] (6) Expression Analysis and Results

[0072] The study found that the expression level of hsa_circ_0083215 was significantly higher in patients who failed to lose weight during the training session (n = 18) than in those who succeeded (n = 36). Figure 1 As shown ( P = 0.021), and see Table 5 for comparison of clinical baseline data.

[0073] Table 5. Clinical baseline data of patients who successfully lost weight one year after intensive weight-loss surgery and the control group.

[0074] variable Patients who failed to lose weight (n = 18) Patients who successfully lost weight (n = 36) value Age (years) 29.72 ± 6.20 27.83 ± 5.48 0.259 Gender (Male / Female) 3 / 15 9 / 27 0.487 Preoperative weight (kg) 95.64 ± 18.83 102.56 ± 19.17 0.214 Postoperative weight (kg) 1 year later 78.51 ± 12.76 67.72 ± 11.47 0.003 Height (cm) 163.78 ± 9.88 164.72 ± 8.40 0.715 relative expression level of hsa_circ_0083215 12.67 ± 6.57 7.63 ± 7.71 0.021 Excess weight loss percentage (%EWL) 48.27 ± 32.27 85.83 ± 20.17 <0.001

[0075] (7) Predictive capability assessment (ROC analysis)

[0076] ROC curves were plotted using the expression levels of hsa_circ_0083215 in the training set to evaluate its predictive ability for the success of weight loss in patients undergoing bariatric surgery one year post-surgery. Figure 2 As shown. First, considering only the expression level of hsa_circ_0083215, a one-way model is constructed, such as... Figure 2 The blue line represents the predictive performance. The area under the curve (AUC) is 0.725, with a 95% CI of 0.561–0.890. P = 0.007, cut-off = 13.4705, sensitivity = 0.917, specificity = 0.667. This indicates that the expression level of hsa_circ_0083215 has significant and good predictive power for the success of weight loss in patients undergoing bariatric surgery one year post-surgery. When using a multivariate model (hsa_circ_0083215 expression level + sex + age + preoperative weight + height), AUC = 0.804, 95% CI: 0.684–0.924, P <0.001, such as Figure 2 As shown by the red line. The Z-test compares the difference in predictive performance between the two models: Z = 1.099. P = 0.272, the difference is not significant. This indicates that hsa_circ_0083215 alone possesses good predictive performance in this invention.

[0077] To further validate the predictive ability of this biomarker, the expression level of hsa_circ_0083215 was analyzed using the same ROC method in a newly added independent validation set of 33 cases. Figure 3 In the validation set, the univariate model using only hsa_circ_0083215 expression levels had an AUC of 0.813 (95% CI: 0.649–0.977). P= 0.005), cut-off value 9.7765, sensitivity 0.800, specificity 0.826. The multivariate model (hsa_circ_0083215 expression level + sex + age + preoperative weight + height) had an AUC of 0.820 (95% CI: 0.721–0.984). P = 0.002), sensitivity was 0.900, and specificity was 0.696. To assess the difference in predictive ability between the two models in the validation set, a Z-test was performed, with a result of Z = -0.705. P = 0.481, indicating no significant difference in predictive performance between the two. This further demonstrates that hsa_circ_0083215 can serve as an effective indicator for predicting postoperative efficacy on its own, and it still exhibits robust predictive ability in independent samples, supporting its potential application as an intraoperative biomarker in clinical practice.

[0078] (8) Effects of hsa_circ_0083215 knockdown on key genes in lipid metabolism

[0079] Figure 4 This study demonstrates the effect of hsa_circ_0083215 knockdown (Circ_0083215-KD) on the expression of adipogenesis-related genes (C / EBP-α and PPAR-γ) in primary mesenchymal stem cells (MSCs) extracted from human visceral adipose tissue. Proteins were extracted from these cells at various time points during adipogenic differentiation induction (days 0, 3, 6, 9, and 12) and processed using Western blotting. The time points were chosen to observe the effect of hsa_circ_0083215 knockdown on primary MSCs at different differentiation stages. The results showed that the expression of C / EBP-α (38 kD) and PPAR-γ (58 kD) was significantly lower in the Circ_0083215-KD group than in the Scramble group. This suggests that hsa_circ_0083215 may influence adipogenic differentiation and adipogenesis in MSCs by regulating these key transcription factors. GAPDH (36 kD) was used as an internal reference gene, exhibiting stable expression, and was employed to correct experimental results. These results not only support the role of hsa_circ_0083215 in lipid metabolism but also provide molecular-level evidence for its use as a preoperative biomarker for predicting the efficacy of bariatric surgery.

[0080] As can be seen from the above embodiments, this invention is the first to propose using the circular RNA hsa_circ_0083215 as a molecular biomarker for preoperative prediction of the efficacy of bariatric surgery (based on EWL% one year postoperatively). This circular RNA can be stably detected in visceral adipose tissue during surgery, and its expression level is significantly correlated with the success of postoperative weight loss, demonstrating good independent predictive ability. This invention utilizes intraoperative omental visceral adipose tissue as a sample source. The tissue acquisition method conforms to actual clinical procedures, requiring no additional sampling and facilitating widespread adoption and standardization. Specific qRT-PCR primers are used to detect hsa_circ_0083215 expression, with the amplified fragment crossing splicing sites to avoid linear mRNA interference and ensure detection specificity. A ROC prediction model based on hsa_circ_0083215 expression was constructed, achieving an AUC value of 0.725, demonstrating high sensitivity (0.917) and specificity (0.667). The AUC increased to 0.804 after incorporating factors such as age, sex, height, and preoperative weight. The experimental methods utilize existing mature RNA extraction, reverse transcription, and qPCR detection platforms (such as TRIzol, TaKaRa RR036A, SYBR Green, and Roche LightCycler 480), ensuring reproducibility and clinical translation feasibility. This detection method is suitable for preoperative risk stratification and individualized intervention guidance, and can be extended to postoperative management, long-term efficacy prediction, or multifactorial modeling. This invention also covers the development of preoperative molecular diagnostic reagent compositions targeting hsa_circ_0083215, including their specific primer pairs, probes and adapted reaction systems.

[0081] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. The application of a predictive biomarker in the preparation of products for assessing the prognosis or effectiveness of weight-loss surgery, characterized in that, The predictive biomarker is the circular RNA hsa_circ_0083215; The weight loss surgery prognosis product or effect evaluation product is used to predict the weight loss effect 1 year after sleeve gastrectomy. The prognosis or effect assessment of the weight loss surgery is reflected by the percentage of excess weight loss one year after the surgery. The formula for calculating the percentage of excess weight loss is as follows: Excess weight loss percentage = (preoperative weight - postoperative weight) / (preoperative weight - ideal weight) × 100%; When the predicted gender is male, the formula for calculating the ideal weight is: height - 105; When the predicted gender is female, the formula for calculating the ideal weight is: height - 100; The unit for the height is cm; The unit for the ideal body weight is kg; The postoperative weight mentioned refers to the weight one year after the surgery.

2. The application of a reagent kit in the preparation of products for assessing the prognosis or efficacy of weight-loss surgery, characterized in that, The kit includes reagents for detecting the expression level of hsa_circ_0083215; The weight loss surgery prognosis product or effect evaluation product is used to predict the weight loss effect 1 year after sleeve gastrectomy. The prognosis or effect assessment of the weight loss surgery is reflected by the percentage of excess weight loss one year after the surgery. The formula for calculating the percentage of excess weight loss is as follows: Excess weight loss percentage = (preoperative weight - postoperative weight) / (preoperative weight - ideal weight) × 100%; When the predicted gender is male, the formula for calculating the ideal weight is: height - 105; When the predicted gender is female, the formula for calculating the ideal weight is: height - 100; The unit for the height is cm; The unit for the ideal body weight is kg; The postoperative weight mentioned refers to the weight one year after the surgery.

3. The application according to claim 2, characterized in that, The reagents used to detect the expression level of hsa_circ_0083215 include primer pairs that specifically amplify hsa_circ_0083215.

4. The application of a reagent kit in the preparation of products for assessing the prognosis or effectiveness of weight-loss surgery, characterized in that, The kit includes primer pairs for specific amplification of hsa_circ_0083215 and quantitative PCR reaction reagents; The weight loss surgery prognosis product or effect evaluation product is used to predict the weight loss effect 1 year after sleeve gastrectomy. The prognosis or effect assessment of the weight loss surgery is reflected by the percentage of excess weight loss one year after the surgery. The formula for calculating the percentage of excess weight loss is as follows: Excess weight loss percentage = (preoperative weight - postoperative weight) / (preoperative weight - ideal weight) × 100%; When the predicted gender is male, the formula for calculating the ideal weight is: height - 105; When the predicted gender is female, the formula for calculating the ideal weight is: height - 100; The unit for the height is cm; The unit for the ideal body weight is kg; The postoperative weight mentioned refers to the weight one year after the surgery.

5. The application according to claim 4, characterized in that, The primer pair includes: The nucleotide sequence is as shown in the forward primer of SEQ ID NO.1; The nucleotide sequence is shown in the reverse primer of SEQ ID NO.

2.

6. The application according to claim 5, characterized in that, The nucleotide sequence of the amplification product of the primer pair is shown in SEQ ID NO.

3.

7. The application according to any one of claims 1 to 6, characterized in that, The prognosis or effect assessment of the weight loss surgery is reflected by the percentage of excess weight loss one year after surgery. A percentage of excess weight loss greater than 60% one year after surgery is considered to have a better prognosis or better effect. Conversely, it is recorded as a poor prognosis or poor outcome.

8. A prognostic assessment system for bariatric surgery, characterized in that, The system includes a computing device for determining the effectiveness of weight loss surgery based on the expression level of circular RNA hsa_circ_0083215; The calculation device for judging the effect of weight loss surgery is used to predict the weight loss effect 1 year after sleeve gastrectomy. The effectiveness of the weight loss surgery is assessed by the percentage of excess weight loss one year after the surgery. The formula for calculating the percentage of excess weight loss is as follows: Excess weight loss percentage = (preoperative weight - postoperative weight) / (preoperative weight - ideal weight) × 100%; When the predicted gender is male, the formula for calculating the ideal weight is: height - 105; When the predicted gender is female, the formula for calculating the ideal weight is: height - 100; The unit for the height is cm; The unit for the ideal body weight is kg; The postoperative weight mentioned refers to the weight one year after the surgery.

9. The system according to claim 8, characterized in that, The system also includes one or more of the following components: A detection device for detecting the expression level of the circular RNA hsa_circ_0083215; A reference device is used to receive the expression level output by the detection device and compare it based on known grouping information of the successful weight loss group and the unsuccessful weight loss group; The analysis device is used to compare the expression level of the circular RNA hsa_circ_0083215 of the subjects with known group information and output the prognostic assessment results.

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