Application of miRNAs and downstream target gene in detection and treatment of obesity and related diseases of Chinese and original population

Abstract

The invention belongs to the technical field of biological pharmacy and application of MiRNAs in detection and prediction of obesity and related diseases thereof, and particularly relates to an application of hsa-miR-199b-5p, hsa-miR-548av-5phsa-miR-548k, hsa-miR-362-5p, hsa-miR-181c-3p, hsa-miR-664b-5p, hsa-miR-148a-5p, hsa-miR-885-5p, hsa-miR-18a-3p, hsa-miR-590-3p, hsa-miR-450b-5p, hsa-miR-26b-3p, hsa-miR-450b-3p, hsa-miR-654-5p, the invention further discloses application of the hsa-miR-196b-5p, the hsa-miR-141-3p, downstream key regulation molecules of the hsa-miR-196b-5p and the hsa-miR-141-3p and the like in comprehensive detection and comprehensive treatment of obesity and related diseases.

Description

Technical Field

[0001] The present invention belongs to the technical field of application of miRNAs in the detection and prediction of obesity and related diseases, and specifically relates to hsa-miR-199b-5p, hsa-miR-548av-5p, hsa-miR-548k, hsa-miR-362-5p, hsa-miR-181c-3p, hsa-miR-664b-5p, hsa-miR-148a-5p, hsa-miR-885-5p, hsa-miR-18a-3p, hsa-miR-590-3p, hsa-miR-45 0b-5p, hsa-miR-26b-3p, hsa-miR-143-3p, hsa-miR-145-5p, hsa-miR-760, hsa-miR-205-5p, hsa-miR-654-5p, hsa-miR-1306-3p, hsa-miR-5010-5p, hsa-miR-655-3p, hsa-miR-196b-5p and hsa-miR-141-3p and their downstream key regulatory molecules in the comprehensive detection and treatment of obesity and related diseases. Background Art

[0002] In recent years, the increase in the number of overweight and obese people has become a major health problem around the world. Since 1998, obesity has been recognized by the World Health Organization (WHO) as a global epidemic in developed countries, and several nutritional chronic diseases and obesity related to it have become public health issues that need to be addressed urgently. Therefore, overweight and obesity and chronic non-communicable diseases have been included in the 2025 global reduction plan by the World Health Organization. Overweight and obesity are major problems in today's society, and in most countries in the world, the number of overweight people exceeds the number of underweight people. Overweight and obesity are major risk factors for a variety of diseases, including the development of cardiovascular disease, type 2 diabetes, musculoskeletal diseases, stroke, and various cancers, which account for more than 70% of the total deaths in people aged 30-70 years. Obesity tends to cluster in specific families because they share related genes and similar eating and exercise behaviors, such as unhealthy diet, liquid calorie intake, and lack of exercise. Furthermore, energy imbalance between calories consumed and calories expended is a major cause of overweight and obesity worldwide, including increased intake of energy-dense foods high in fat and sugar, and reduced physical activity due to the increasingly sedentary nature of many forms of work, changes in transportation modes, and increasing urbanization. The main reasons for dietary changes and changes in physical activity patterns are development-related environmental and social changes and lack of supportive policies in sectors such as health, agriculture, transportation, urban planning, environment, food processing, distribution, marketing, and education. To further understand the molecular network regulatory systems of overweight and obesity, we performed a joint microRNA-omics and proteomics analysis of peripheral blood samples from 1027 Chinese Central Plains population.

[0003] Body mass index (BMI) is a weight-to-height ratio used to determine whether a person is overweight or obese. BMI is calculated by dividing weight in kilograms by height in meters squared (kg / m 2 ). In China, obesity is defined as a body mass index of 28 or higher, while overweight is defined as a body mass index of 24 or higher. BMI values ​​are the most reliable indicator of the prevalence of overweight and obesity in people of all ages. Both overweight and obesity are used to refer to people who are at risk of health problems due to excess fat. If the overweight state is not treated in time, it can quickly develop into obesity.

[0004] miRNA is a short noncoding RNA that regulates the expression of its target genes at the post-transcriptional level. In addition, miRNA has been used as a prognostic, diagnostic and therapeutic marker for a variety of diseases. miRNAs are often clustered in different locations or intronic regions within the gene sequence of the human genome, and they may affect the expression of about 30% of the genes in the entire mammalian genome. Recently, miRNAs have been shown to affect insulin resistance, adipogenesis, cardiovascular disease and endothelial dysfunction in overweight and obese individuals. Chromosomal regions associated with obesity contain approximately 79 differentially expressed miRNAs. MiRNAomics is used to study the complex signaling network regulated by miRNAs mediated by NO in response to cold and nitric oxide.

[0005] Mass spectrometry-based proteomics is a technique used to identify and measure proteins at the expression level. Proteomics has been used to study the whole proteome, drug screening, biomarker discovery, target validation, and post-translational modifications. Currently, the associations of various microRNAs and their protein targets with obesity and obesity-related diseases in the Chinese population are unclear, and the molecular regulatory processes behind these associations are not fully understood. Multi-omic analysis of obesity in the Central Plains population has not been studied. In this study, we used miRNA sequencing and proteomics to analyze peripheral blood samples of 1027 Central Plains Han adults in order to address the following questions: (1) analyze the obesity status of the population and explore the molecular risk factors for obesity; (2) identify miRNA signals associated with obesity; (3) identify miRNA targets and proteins associated with obesity; and (4) analyze miRNA and / or protein signals to predict the risk of overweight and obesity. Our study provides potential new mechanisms and biomarkers for the future prediction and prevention of obesity-related diseases.

[0006] Currently, there are no studies reporting the application of miRNAs and downstream key signaling molecules in the comprehensive detection and treatment of obesity and related diseases. Summary of the invention

[0007] In order to solve the shortcomings and deficiencies of the prior art, the purpose of the present invention is to provide an application of miRNAs and downstream key signaling molecules in the development of a comprehensive detection kit for obesity and related diseases and a comprehensive therapeutic drug.

[0008] The purpose of the present invention is achieved through the following technical solutions:

[0009] Application of miRNAs and downstream key signaling molecules in the development of comprehensive detection kits for obesity and related diseases and comprehensive therapeutic drugs. The hsa-miR-199b-5p, hsa-miR-548av-5p|hsa-miR-548k, hsa-miR-362-5p, hsa-miR-181c-3p, hsa-miR-664b-5p, hsa-miR-148a-5p, hsa-miR-885-5p, hsa-miR-18a-3p, hsa-miR-590-3p, hsa-miR-450b-5p, hsa-miR-26b- 3p, hsa-miR-143-3p, hsa-miR-145-5p, hsa-miR-760, hsa-miR-205-5p, hsa-miR-654-5p, hsa-miR-1306-3p, hsa-miR-5010-5p, hsa-miR-655-3p, hsa-miR-196b-5p and hsa-miR-141-3p and their downstream key regulatory molecules in the comprehensive detection and treatment of obesity and related diseases.

[0010] The above hsa-miR-199b-5p, hsa-miR-548av-5p|hsa-miR-548k, hsa-miR-362-5p, hsa-miR-181c-3p, hsa-miR-664b-5p, hsa-m iR-148a-5p,hsa-miR-885-5p,hsa-miR-18a-3p,hsa-miR-590-3p,hsa-miR-450b-5p,hsa-miR-26b-3p,hsa-miR-143-3 The application of hsa-miR-145-5p, hsa-miR-760, hsa-miR-205-5p, hsa-miR-654-5p, hsa-miR-1306-3p, hsa-miR-5010-5p, hsa-miR-655-3p, hsa-miR-196b-5p and hsa-miR-141-3p and their downstream key regulatory molecules in the comprehensive detection and comprehensive treatment of obesity and related diseases includes the preparation of comprehensive detection kits for detecting obesity and related diseases and comprehensive therapeutic drugs.

[0011] The application of the present invention has the following advantages and beneficial effects:

[0012] The combined use of miRNAs and downstream key signaling molecules can accurately predict the occurrence of obesity and related diseases. This indicates that miRNAs and downstream key signaling molecules can be used as a marker gene or therapeutic target for obesity and related diseases, providing guidance for the detection or treatment of obesity and related diseases. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a risk factor for obesity in Chinese Han adults.

[0014] Figure 2 Identification of differentially expressed miRNAs in normal and overweight / obese Chinese Han subjects.

[0015] Figure 3 Giving a relative score to differences in miRNA levels in response to obesity is a reasonable approach to measure different degrees of obesity.

[0016] Figure 4 These are differentially expressed proteins between normal and overweight / obese people of the Han Chinese population.

[0017] Figure 5 In the obese phenotype, the miRNA-protein regulatory network is remodeled.

[0018] Figure 6 The combination of several miRNAs and proteins has good predictive value for overweight / obese Han Chinese population, and has the function of predicting blood sugar and blood pressure. DETAILED DESCRIPTION

[0019] The present invention is further described in detail below in conjunction with embodiments and drawings, but the embodiments of the present invention are not limited thereto.

[0020] Embodiment 1:

[0021] Body mass index (BMI) is the most commonly used obesity indicator in clinical practice. In this study, 1027 Chinese Han adults were divided into underweight group (BMI < 18.5), normal group (18.5 ≤ BMI < 25), overweight group (25 ≤ BMI < 30) and obese group (BMI ≥ 30) according to the World Health Organization's adult BMI classification standard. The analysis results showed that among Chinese Han adults in 2017, the majority of them were normal and overweight ( Figure 1 A), and this overweight trend was similar in the follow-up survey results in 2020 ( Figure 1 B). Importantly, we followed up 596 volunteers and further compared changes in BMI levels approximately 3 years later ( Figure 1 C). We also found that men's BMI tends to stabilize in adulthood, while women's BMI continues to increase before the age of 56, especially between the ages of 40 and 50 ( Figure 1D) These results show the obesity status and living conditions associated with BMI in the Chinese population.

[0022] Embodiment 2:

[0023] In this study, we analyzed whether specific miRNA expression levels are associated with overweight and obesity. We performed RNA sequencing on all 1027 plasma samples and analyzed the results to assess differential miRNA expression levels in the cohort. For subsequent analysis, samples from 966 subjects were divided into normal and overweight / obese groups based on BMI. After quality control and normalization of the raw count data, we were able to obtain miRNA expression levels for 639 subjects in the normal and obese groups. Our volcano plot analysis showed that hsa-miR-199b-5p was the most highly expressed miRNA in the overweight / obese group, while hsa-miR-141-3p was the least expressed miRNA ( Figure 2 A). Heat map analysis further showed that 11 miRNAs were significantly lower in overweight / obese samples than in controls, including hsa-miR-26b-3p, hsa-miR-143-3p, hsa-miR-145-5p, hsa-miR-760, hsa-miR-205-5p, hsa-miR-654-5p, hsa-miR-1306-3p, hsa-miR-5010-5p, hsa-miR-655-3p, hsa-miR-196b-5p, and hsa-miR-141-3p. The reported data confirmed our results that miR-143, miR-760, miR-26b, miR-145, miR-196b-5p, miR-141-3p, and miR-205-5p levels were associated with obesity. In contrast, the expression levels of hsa-miR-199b-5p, hsa-miR-548av-5p|hsa-miR-548k, hsa-miR-362-5p, hsa-miR-181c-3p, hsa-miR-664b-5p, hsa-miR-148a-5p, hsa-miR-885-5p, hsa-miR-18a-3p, hsa-miR-590-3p, and hsa-miR-450b-5p in the overweight / obese group were significantly higher than those in the normal group ( Figure 2 B). Similarly, previous studies have shown that miR-885-5p, miR-199b, miR-181c, miR-18a, miR-590, miR-548av / miR-548k, and miR-148a levels are strongly correlated with obesity phenotypes.

[0024] To investigate whether these differentially expressed miRNAs are associated with obesity-related metabolic pathways, we performed gene set enrichment analysis (GSEA) on miRNAs using the web-based miRNA analysis application miEAA. We found that these differentially expressed miRNAs were associated with TGF-β signaling pathways, lipid metabolism, and insulin-related pathways ( Figure 2 C). We further analyzed the expression levels of miR-143-5p and miR-885-5p in plasma samples of 10 normal and 10 obese Chinese Han adults using a different set of samples. The results confirmed that the expression level of miR-143-5p was significantly lower than that of the normal group, while the expression level of miR-885-5p in obese samples was higher than that of the normal group, which further verified our predicted results of the association between differences in miRNA levels and obesity ( Figure 2 D). In summary, we found that the levels of some circulating miRNAs were dysregulated in overweight and obese Chinese subjects, and these miRNAs were mainly involved in regulating TGF-β signaling and insulin pathways.

[0025] Embodiment 3:

[0026] We found that 21 miRNAs were significantly differently expressed between the normal group and the overweight / obese group, and further classified them using Log2FoldChange. To investigate the relationship between the 21 differentially expressed miRNAs and the degree of obesity, we first established a scoring procedure to assess the degree of obesity in all 996 samples using the 21 differentially expressed miRNAs. The specific grading scale is as follows: (1) The specific miRNA in the sample is most highly expressed in the overweight / obese group. If the expression level of a sample is lower than the median of all samples, the score of the sample is -1, and if the expression level is higher than the median, the value increases by 1. (2) The miRNA in the sample belongs to the low-expressed miRNA in the obese group. If its expression level in a sample is lower than the median of all samples, the score of the sample increases by 1, and vice versa. (3) We summed the scores of the 21 miRNAs in all samples to determine the final score for each sample ( Figure 3 A). Based on the relative scores and results, we found that as the scores increased, the BMI level gradually increased, especially when the score was greater than 1, the overall BMI was higher ( Figure 3 B). We then defined samples with scores less than 0 as the low group and samples with scores greater than 0 as the high group. We then further compared the BMI and obesity-related clinical index levels of the two groups. The statistical test results showed that the BMI, cholesterol, triglyceride, low-density lipoprotein, and glucose levels of the high-score group were significantly increased, while the high-density lipoprotein level of the high-score group was significantly reduced ( Figure 4C). The above results indicate that the 21 differentially expressed miRNAs are strongly correlated with obesity and obesity-related hyperlipidemia and hyperglycemia.

[0027] Embodiment 4:

[0028] To further explore the mechanism by which abnormal miRNAs lead to metabolic disorders in the Chinese Han population, we performed proteomic analysis on more than 996 samples and collected protein data from 895 subjects. First, we compared the protein expression levels of the normal group and the overweight / obese group. The volcano plot results showed that there were significant differences in the expression of 230 proteins between the two groups ( Figure 4 A). The heat map showed that 128 proteins were significantly overexpressed and 102 proteins were significantly underexpressed in the overweight / obese group ( Figure 4 B). After classifying the 230 differentially expressed proteins by Log2FoldChange (Log2FC), we found that LLGL Scribble Cell Polarity Complex Component 1 (LLGL1) was the most highly expressed protein, and GWAS analysis showed that it was associated with systolic blood pressure (rs7221807) and BMI-adjusted waist-to-hip ratio (rs2245737, rs36058389, rs62072500, rs720856). Dehydrogenase / Reductase 1 (DHRS1) was the lowest expressed protein in the overweight / obese group, and according to the search results on the genecards website, DHRS1 was also associated with BMI-adjusted waist circumference (rs36226649) ( Figure 4 C). Further, pathway enrichment analysis of these differentially expressed proteins showed that these proteins were mainly enriched in the RNA decomposition and metabolism process, which means that these proteins may cause dysregulation of intracellular signaling pathways by affecting RNA processes ( Figure 4 D). To find the main proteins that affect the RNA decomposition process, we further analyzed the pathway enrichment results and visualized them using Chord plots, which showed that SNW1, EXOSC3, SNRPA, CIRBP, PSMO4, HNRNPU, GEMIN5, PNN, SMNDC1, and SERBP1 proteins were involved in multiple pathways ( Figure 4 E). It is noteworthy that previous studies have shown that SNRPA, HNRNPU, PNN, and SERBP1 are associated with the obese state. In these analyses, we found a series of novel proteins that are highly associated with obesity.

[0029] Embodiment 5:

[0030] To further investigate the miRNA-protein regulatory network, we used three computational methods (TargetScan, miRWalk 2.0, and miRDB) to identify the targets of 21 differentially expressed miRNAs. We then identified the clustered 5400 miRNA targets and 230 differentially expressed proteins and found that 54 different proteins overlapped ( Figure 5 A). Using the web-based program metscape to enrich these overlapping proteins, we found that the two most important enriched pathways were mRNA surveillance and receptor-mediated endocytosis regulation ( Figure 5 B). In order to clarify the regulatory relationship between miRNAs and proteins, we used the network visualization tool Cytoscape to construct a miRNA-protein-biological function regulatory network and revealed several key regulatory pathways, such as hsa-miR-548av-5p and miR-548k, which regulate PNN to affect the mRNA surveillance pathway. Regulation of PLCG2 affects the positive regulatory process of receptor-mediated endocytosis and AGE-RAGE signaling pathway in diabetic complications, and regulation of STK39 affects the negative regulatory process of glycogen biosynthesis. hsa-miR-199b-5p regulates HIP1 to affect the positive receptor-mediated endocytosis process, and EXOSC3 affects the RNA phosphodiester bond hydrolysis process ( Figure 5 C). In conclusion, we discovered a novel regulatory network of miRNA-protein changes in overweight / obese Han Chinese individuals.

[0031] Embodiment 6:

[0032] Obesity is a cause of many diseases, including hypertension and diabetes. Then, whether there is a relationship between obesity-related miRNAs and proteins and blood pressure and blood glucose levels was determined separately in the Chinese Han population. To analyze the potential relationship between differentially expressed miRNAs and hypertension, we analyzed these differential miRNAs from obesity to evaluate the potential of miRNAs as markers of hypertension risk. In addition, by combining differential protein and miRNA dysregulation from proteomics, we may find an effective method to predict hypertension. Therefore, we first performed correlation analysis on 21 obesity-related miRNAs with the average values ​​of three systolic and diastolic blood pressures, and found that the levels of hsa-miR-143-3p, hsa-miR-205-5p, hsa-miR-145-5p, hsa-miR-141-3p, has-miR-760, and hsa-miR-885-5p were correlated with both systolic and diastolic blood pressure ( Figure 6 A). Levels of obesity-related proteins: NEGR1, CACNA2D2, PYGB, CUL4A, and CNTN3 were associated with both systolic and diastolic blood pressure ( Figure 6B). A recent report validated the value of CACNA2D2 levels as predictive data for independently predicting the risk of progression of hypertension in a family based on a longitudinal study of 403 Japanese subjects; a mouse model showed that Cul4a was associated with systolic blood pressure and cardiac function. In addition, we evaluated the efficacy of blood pressure-related miRNAs and proteins in identifying hypertensive subjects from healthy participants. We characterized the hypertensive group as having two systolic blood pressures of at least 140 mmHg and / or diastolic blood pressures of at least 90 mmHg. In addition, we included 295 hypertensive patients. ROC curve analysis showed that hsa-miR-143-3p, hsa-miR-205-5p, hsa-miR-145-5p, hsa-miR-141-3p, has-miR-760, and hsa-miR-885-5p levels had an ROC value (0.597) for distinguishing hypertensive from healthy subjects ( Figure 6 C). The combined ROC value of miRNA and hypertension-related proteins was 0.63 ( Figure 6 D). Our results suggest that the combination of miRNAs and proteins can accurately predict hypertension. Similarly, the correlation between obesity-related miRNAs and fasting blood glucose was investigated. The expression levels of hsa-miR-143-3p, hsa-miR-141-3p, hsa-miR-654-5p, hsa-miR-655-3p, hsa-miR-5010-5p, hsa-miR-196-5p, and hsa-miR-885-5p were significantly different ( Figure 6 E). In the analysis of obesity-related proteins, only CNTN3 levels were correlated with blood glucose ( Figure 6 F), and a previous genome-wide association study based on T2D patients in Taiwan, China found that CNTN3 single nucleotide polymorphisms were associated with response to hypoglycemic drug treatment. We studied the effectiveness of blood glucose-related miRNAs and proteins in distinguishing hyperglycemic individuals from healthy individuals. We identified 62 hyperglycemic subjects with fasting blood glucose levels exceeding 7.0 mmol / L. ROC curve analysis showed that the ROC value of blood glucose-related miRNAs in distinguishing hyperglycemia from healthy controls was 0.546 ( Figure 6 G). The ROC value of the combination of miRNA and the level of hyperglycemia-related protein CNTN3 was 0.601 ( Figure 6 H). The results also suggest that the combination of miRNA and protein may contribute to the prediction of hyperglycemia. Together, these findings suggest that the combination of obesity-related miRNA and protein could serve as a potential biomarker for predicting disease status (hypertension and hyperglycemia) in the Chinese Han population.

[0033] The above describes in detail the preferred implementation of this patent, but this patent is not limited to the above implementation. Various changes can be made within the knowledge scope of ordinary technicians in this field without departing from the purpose of this patent.

Claims

1. Utilize a group of upregulated expression levels of hsa-miR-199b-5p, hsa-miR-548av-5p|hsa-miR-548k, hsa-miR-362-5p, hsa-miR-181c-3p, hsa-miR-664b-5p, hsa-miR-148a-5p, hsa-miR-885-5p, hsa-miR-18a-3p, hsa-miR-590-3p and hsa-miR-450b-5p in the development of comprehensive detection kits and comprehensive therapeutic drugs for obesity and related diseases.

2. Utilize a group of downregulated expression levels of hsa-miR-26b-3p, hsa-miR-143-3p, hsa-miR-145-5p, hsa-miR-760, hsa-miR-205-5p, hsa-miR-654-5p, hsa-miR-1306-3p, hsa-miR-5010-5p, hsa-miR-655-3p, hsa-miR-196b-5p and hsa-miR-141-3p in the development of comprehensive detection kits and comprehensive therapeutic drugs for obesity and related diseases.

3. Utilize a group of upregulated expression levels of hsa-miR-199b-5p, hsa-miR-548av-5p|hsa-miR-548k, hsa-miR-362-5p, hsa-miR-181c-3p, hsa-miR-664b-5p, hsa-miR-148a-5p, hsa-miR-885-5p, hsa-miR-18a-3p, hsa-miR-590-3p and hsa-miR-450b-5p and their downstream key regulatory molecules in the development of comprehensive detection kits and comprehensive therapeutic drugs for obesity and related diseases.

4. Utilize a group of hsa-miR-26b-3p, hsa-miR-143-3p, hsa-miR-145-5p, hsa-miR-760, hsa-miR-205-5p, hsa-miR-654-5p, hsa-miR-1306-3p, hsa-miR-5010-5p, hsa-miR-655-3p, hsa-miR-196b-5p and hsa-miR-141-3p with downregulated expression levels and their downstream key regulatory molecules in the development of comprehensive detection kits and comprehensive therapeutic drugs for obesity and related diseases. 5.Use hsa-miR-199b-5p, hsa-miR-548av-5p|hsa-miR-548k, hsa-miR-362-5p, hsa-miR-181c-3p, hsa-miR-66 4b-5p,hsa-miR-148a-5p,hsa-miR-885-5p,hsa-miR-18a-3p,hsa-miR-590-3p,hsa-miR-450b-5p,hsa-miR-2 6b-3p, hsa-miR-143-3p, hsa-miR-145-5p, hsa-miR-760, hsa-miR-205-5p, hsa-miR-654-5p, hsa-miR-1306-3p, hsa-miR-5010-5p, hsa-miR-655-3p, hsa-miR-196b-5p and hsa-miR-141-3p are used in the development of comprehensive detection kits and comprehensive therapeutic drugs for obesity and related diseases. 6.Use hsa-miR-199b-5p,hsa-miR-548av-5p|hsa-miR-548k,hsa-miR-362-5p,hsa-miR-181c-3p,hsa-miR-664b- 5p,hsa-miR-148a-5p,hsa-miR-885-5p,hsa-miR-18a-3p,hsa-miR-590-3p,hsa-miR-450b-5p,hsa-miR-26b-3p , hsa-miR-143-3p, hsa-miR-145-5p, hsa-miR-760, hsa-miR-205-5p, hsa-miR-654-5p, hsa-miR-1306-3p, hsa-miR-5010-5p, hsa-miR-655-3p, hsa-miR-196b-5p and hsa-miR-141-3p and their downstream key regulatory molecules are used in the development of comprehensive detection kits and comprehensive therapeutic drugs for obesity and related diseases.

Images