Real-time PCR-specific primers in the diagnosis of obesity

Abstract

The invention relates to PPARy and Lnc-LOC105377284 genes, which are among the targets of obesity treatment. It is the first study to reveal the expression difference of the PPARy gene between the obesity classes and the relationship of the LncRNA (Lnc-U90926) gene with both the human orthologist LOC105377284 gene with obesity and PPARy based on the studies in the literature. Thanks to the genes subject to the invention, the relationship of the expression of the PPARy and Lnc-LOC105377284 genes in the obesity classification is shown. In fact, the aim was to use obesity as a model and to look at the correlation of a gene (PPARy), which has been proven in the literature, with LncRNA, which is considered as a candidate, and to investigate whether there may be a new target, especially in treatment-resistant obese. According to the results of the research, these data revealed that there is a relationship between the PPARy and LOC105377284 genes and that this relationship may be effective in obesity.

Description

[0001] REAL-TIME PCR-SPECIFIC PRIMERS IN THE DIAGNOSIS OF OBESITY

[0002] Technical Field

[0003] The invention relates to genes targeting the PPARy gene, which is among the targets of obesity treatment. The gene of the invention shows the relationship of the expression of the Lnc-LOC105377284 gene in the PPARy gene target in the obesity classification.

[0004] State of the Art

[0005] Obesity is a complex, multifactorial disease characterized by excessive weight gain and under-calorie burn-off, which increases the likelihood of morbidity and mortality with the accumulation of excess fat tissue. In general, obesity is defined based on body mass index, weight in kilograms divided by height in square meters. A Body Mass Index (BMI) greater than 30 kg / m2 is defined as obesity.

[0006] More than 140 gene regions related to obesity have been identified in human genome studies. Although there is obesity in some of those who live in the same environment and receive energy and have a sedentary lifestyle, the fact that there is no obesity in some of them may explain the genetic relationship with obesity.

[0007] Obesity results from an epigenetic relationship. It changes the phenotypic expression of obesity genetic factors and allows recognition of different clinical symptoms of obesity.

[0008] Obesity increases the likelihood of various diseases associated with increased mortality. These include type-2 diabetes, cardiovascular diseases, metabolic syndrome, chronic kidney diseases, hyperlipidemia, hypertension, non-alcoholic fatty liver disease, some types of cancer, obstructive sleep apnea, osteoarthritis, and depression.

[0009] The regulation of food cravings in the brains of obese individuals, the regulation of appetite and satiety in the hypothalamus of intestinal hormones, adipose tissue, or intestinal microbiota, as well as the roles of intestinal dysbiosis in the formation of obesity and the dysfunction of glucose are increasingly better understood. In addition, it is known that genetic factors play an important role in determining the individual's predisposition to weight gain.

[0010] Recent research on the development of adipose suggests that a significant number of long non-coding RNAs (LncRNAs) participate in regulatory networks of adipogenesis and play a key role in regulating adipogenic adherence and differentiation. Long non-coding RNAs are a newly discovered class of regulatory RNAs involved in various cellular activities. Evidence from both studies of function gain and loss of function strongly suggests that LncRNAs are involved in the regulation of adipogenesis and play a key role in the development and function of both white and brown / beige adipose tissue. Long non-coding RNAs function as important contributors to the complex regulatory network of fat cell development, and further studies are required to elucidate their detailed mechanisms for regulating fat accumulation. Identification of LncRNA molecules with adipogenic activity may open new possibilities for potential therapeutic targets and strategies to combat human obesity.

[0011] Long non-coding RNAs are a type of RNA whose transcripts exceed 200 nucleotides that are not translated into proteins. They can regulate the expression of target genes by both transcriptional and post-transcriptional mechanisms.

[0012] They are involved in various biological processes such as epigenetic modulation of chromatin, promoter-specific gene modulation, and transcript stability. Non-coding RNAs associated with obesity mainly modulate metabolic pathways and inflammatory responses. Non-coding RNAs regulate several pathways related to adipogenesis, so they are considered new therapeutic targets for the management of metabolic disorders such as obesity.

[0013] The PPARy gene is a nine-exon gene with more than 100 kb on chromosome 3 at the 3p25-24 position. PPARy is mainly expressed in adipose tissue, where it regulates lipid storage in white adipose tissue and energy distribution in brown adipose tissue. However, PPARy is also detected in the human skeleton and heart muscle, liver, kidney, small intestine, bladder, and spleen. PPARy is a nuclear receptor that regulates adipocyte development and glucose homeostasis. PPARy activation has been shown to be beneficial in the fat microenvironment, reducing adipose tissue inflammation and moving fat from the intraabdominal to the subcutaneous stores.

[0014] PPARy participates in the metabolism of free fatty acids (FFAs) in adipocytes by regulating the expression of genes encoding proteins responsible for the release of FFAs from lipoproteins and their transport into the cell. PPARy also increases the efficiency of the synthesis of TGs from FFAs and glycerol in adipocytes. The PPARy receptor is directly involved in the transport of glucose into the adipocyte by regulating the expression of genes involved in the lipid-carbohydrate metabolism process.

[0015] Considering the wide range of effects on glucose, lipid metabolism and cell proliferation / apoptosis, PPARs and their modulators are recommended for the treatment of metabolic disorders such as hyperglycemia, dyslipidemia, and atherosclerosis. For the prevention and treatment of both lipid and glucose profile disorders, the potency and affinity of PPARs and their potential carcinogenic effects should be considered.

[0016] Although precise molecular processes involving obesity-related LncRNAs are still unclear, LncRNAs are now considered to be intermediates contributing to obesity and inflammation. It will be important to distinguish between LncRNAs, which are effective in increasing fat with obesity, and those that play a role in mediating chronic low-grade obesity. The increase in the volume and number of adipocytes, which play a role as the main factor of obesity, is defined as adipocyte differentiation. Adipogenesis, on the other hand, is a process that involves the transformation of precursor adipocytes into mature adipocytes and constitutes the process of increase and differentiation of precursor adipocytes, intracellular lipid storage and change in the expression of related genes. Adipogenesis appears to be a process characterized by a complex network in which many transcription factors and LncRNA are involved as regulators of gene expression. The study of LncRNAs in adipogenesis and related diseases, together with therapeutic approaches, may pave the way for developing new strategies to combat obesity and related metabolic diseases.

[0017] With the invention, it is aimed to investigate the effect of LncRNAs targeting the PPARy gene, which is especially among the targets of obesity treatment. Thus, it is aimed to show the relationship between PPARy and the expression of the genes subject to the invention in the obesity classification.

[0018] Descriptions of the Figures

[0019] Figure 1. PPARy mRNA levels in the blood

[0020] Figure 2. LOC105377284 mRNA levels in the blood

[0021] Figure 3. An image of expression levels of PPARy and LOC105377284 genes in the control group (BMI<25 kg / m2)

[0022] Figure 4. An image of expression levels of PPARy and LOC105377284 genes in the BMI: 25- 30 kg / m2group

[0023] Figure 5. An image of expression levels of PPARy and LOC105377284 genes in the BMI: 30- 40 kg / m2group

[0024] Figure 6. An image of expression levels of PPARy and LOC105377284 genes in the BMI>40 kg / m2group

[0025] Figure 7. Correlation levels of PPARy and LOC105377284 genes with BMI Figure 8. Correlation levels of PPARy and LOC105377284 genes with Total Cholesterol Figure 9. Correlation levels of PPARy and LOC105377284 genes with HDL-K Figure 10. Correlation levels of PPARy and LOC105377284 genes with LDL-K Figure 11. Correlation levels of PPARy and LOC105377284 genes with Triglyceride Figure 12. Correlation levels of PPARy and LOC105377284 genes with Vitamin D Figure 13. Correlation levels of PPARy and LOC105377284 genes with Vitamin B-12 Figure 14. Correlation level of LOC105377284 gene with Ferritin Figure 15. Correlation level of PPARy gene with Eosinophil

[0026] Figure 16. Correlation levels of PPARy and LOC105377284 genes with Fasting Blood Sugar

[0027] Brief Description of the Invention

[0028] The sequence of the Lnc-LOC105377284 gene in humans, which is the orthologist of the Lnc-U90926 gene in mice, which is known to regulate the regulation of the PPARG gene, known to be associated with the metabolic syndrome, was taken and its primer design was made in NCBI.

[0029] The primer sequences we use in our invention:

[0030] SEQ 1 : Forward Primer Sequence; ACCTCTCTGTGCCTCAACTTC

[0031] SEQ 2: Reverse Primer Sequence; GAAGACGATGGCAGAGAGCA

[0032] Obesity is a multifactorial disease affected by environmental and genetic factors. With the introduction of genome sequencing technologies in the clinic in recent years, it has been determined that there are no significant mutations in obesity. This has increased the importance of epigenetic mechanisms in elucidating the molecular basis of diseases. Precise molecular processes involving obesity-related LncRNAs are still unclear. Long non-coding RNAs are considered to be intermediates that contribute to gene regulation in a number of diseases. Thanks to the invention, the effect of LncRNAs in the PPARy gene, which is among the targets of obesity treatment, could be examined. Among the obese, the relationship between the peroxisome proliferator activated receptor gamma (PPARy) gene and the expression of LncRNAs in the obesity classification was evaluated. The relationship of the genes subject to the invention with both obesity and PPARy has been studied.

[0033] Detailed Description of the Invention

[0034] Analysis of blood samples taken from individuals who applied to Erciyes University Faculty of Medicine Endocrinology Polyclinic was performed at Betiil-Ziya Eren Genome and Stem Cell Center. Individuals were divided into 4 groups according to their BMI. According to BMIs over 18 years of age, there are 4 different groups: normal (18.5-24.9 kg / m2, 17 people), overweight (25-29.9 kg / m2, 16 people), obese (30-39.9 kg / m2, 20 people), and morbidly obese (>40 kg / m2, 14 people). PPARy and LOC105377284 gene expression levels were analyzed from blood samples taken from subjects.

[0035] Total RNA Isolation from Blood Samples

[0036] Total RNA isolation was performed with the Trizol method from blood samples taken from patients. cDNA Acquisition

[0037] For cDNA synthesis, cDNA synthesis was performed from RNA samples using the iScript cDNA synthesis kit (Bio-Rad, Cat No: 1708891).

[0038] Determination of mRNA Expression Levels

[0039] Using the Real-Time PCR method, mRNA expression levels were investigated using primers of PPARy and LncRNA-LOC105377284 genes in cDNA samples with the Roche LightCycler LC480 device. In order to determine the expression levels, the SYBR Green 1 Master Mix (Bio-Rad, Cat No: 1725271) kit was used.

[0040] GAPDH was used as a House-Keeping gene.

[0041] Table 1. Primer Sequences

[0042] For normalization; Ct (cycle hold) values of the target genes and the House-Keeping gene taken from the device were calculated by 2-AA CT.

[0043] Statistical Analyses

[0044] After the PCR results were obtained, comparisons were made between the experimental groups. The data were analyzed with two different statistical analysis software. Graphs and gene expression analyses were evaluated with Graphpad Prism 8.4.3 software. The relationship between gene expression levels between the groups was evaluated by One Way ANOVA test. The relationships between the genes and the analysis results determined by the blood test of the groups were evaluated by applying the linear regression test in the SPSS 16 software. p<0.05 was considered statistically significant.

[0045] Using blood samples from people with different BMIs, the transcript levels of PPARy, which is involved in lipid and glucose metabolism, and Lnc-LOC 105377284, which is a transcriptional modulator responsible for regulating gene expression, were determined.

[0046] (ns: p>0.05, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001).

[0047] PPARy gene expression levels were evaluated according to BMI<25 kg / m2group. It was found that the expression level of the PPARy gene increased statistically significantly between the groups compared to the BMI<25 kg / m2group, which was the control group.

[0048] (ns: p>0.05, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001).

[0049] LOC105377284 gene expression levels were evaluated according to the BMI<25 kg / m2group, which was accepted as control. According to these values, gene expression of the BMI: 25-30 kg / m2group was not statistically significant compared to the control group. It was found that there was a significant difference between BMI 30-40 kg / m2and BMI>40 kg / m2groups compared to the control and LOC105377284 level increased. It was found that gene expression level increased between the BMI: 25-30 kg / m2group and the BMI>40 kg / m2group and between the BMI: 30-40 kg / m2 group and the BMI>40 kg / m2 group.

[0050] As a result of the regression analysis, BMI is 77% effective on the expression of PPARy and 46% on the expression of Lnc-LOC105377284. The increase in BMI affects PPARy by 77 units and Lnc-LOC105377284 by 300 units. According to the results of the regression analysis, it was found that there was a positive correlation between BMI and PPARy and LOC105377284. The correlation coefficient is r=0.21. However, this correlation is not statistically significant.

[0051] According to the results of the analysis, total cholesterol has an effect of 81% and 46% on the expression of PPARy and LOC105377284 genes, respectively. According to this statistically significant result, total cholesterol had an effect of 11.9 and 231.7 units on PPARy and LOC105377284 genes. According to the results of the regression analysis, while there was a negative correlation (r=-0.071) between total cholesterol and PPARy, a positive correlation (r =0.07) was found between total cholesterol and LOC105377284, and this correlation was found to be statistically insignificant. While the increase in total cholesterol level causes a decrease in PPARy gene expression level, LOC105377284 causes an increase in gene expression level.

[0052] According to the results of the analysis, HDL-K has an effect of 2% and 15% on the expression levels of PPARy and LOC105377284 genes, respectively (p<0.001, p<0.01). HDL-K has an effect of 22 and 250 units on PPARy and LOC105377284 genes, respectively. According to the results of the regression analysis, a negative correlation was found between HDL-C and PPARy, and a positive correlation was found between HDL-C and LOC105377284. The correlation coefficients are r=-0.1440 and 0.1792, respectively. This correlation is statistically insignificant.

[0053] According to the results of the regression analysis, LDL-K has an effect of 2% and 14.5% on the expression levels of PPARy and LOC105377284 genes, respectively. LDL-K has an effect of 9 and 162 units on PPARy and LOC105377284 genes, respectively, and is statistically significant. According to the results of the regression analysis, a statistically insignificant negative correlation (r=-0.01254 and -0.02473) was found between LDL-C and PPARy and LDL-C and LOC105377284.

[0054] According to the results of the analysis, triglyceride has an effect of 5% and 18% on the expression levels of PPARy and LOC105377284 genes, respectively. According to this statistically significant result, triglyceride has an effect of 7.6 and 154 units on PPARy and LOC105377284 genes, respectively. According to the results of the regression analysis, a statistically significant negative correlation (r=-0.3207 and -0.19) was found between Triglyceride and PPARy.

[0055] According to the results of the analysis, Vitamin D has an effect of 17.6% and 2% on the expression levels of PPARy and LOC105377284 genes, respectively. According to this statistically significant result, Vitamin D has an effect of 83.5 and 344 units on PPARy and LOC105377284 genes, respectively (p<0.001). According to the regression analysis results, a statistically insignificant negative correlation was found between Vitamin D and PPARy, and a statistically significant negative correlation (r=-0.20 and -0.36) was found between Vitamin D and LOC105377284 (p<0.05).

[0056] According to the results of the analysis, Vitamin B12 has an effect of 44% and 11% on the expression levels of PPARy and LOC105377284 genes, respectively. According to this statistically significant result, Vitamin B12 has an effect of 3 and 7 units on PPARy and LOC105377284 genes, respectively (p<0.001). According to the results of the regression analysis, a statistically insignificant, positive correlation (r=0.11 and 0.17) was found between Vitamin B12 and PPARy and Vitamin B12 and LOC105377284.

[0057] According to the results of the analysis, Ferritin has an effect of 1% on the expression level of the LOC105377284 gene. According to this statistically significant result, Ferritin has an effect of 51 units on the LOC105377284 gene (p<0.05). According to the results of the regression analysis, a statistically insignificant, positive correlation (r=0.12) was found between Ferritin and LOC 105377284.

[0058] According to the results of the analysis, Eosinophil has an effect of 25% on the expression level of the PPARy gene. According to this statistically significant result, Eosinophil has an effect of 331 units on the PPARy gene. According to the results of the regression analysis, a statistically significant, negative correlation (r=-0.547) was found between Eosinophil and PPARy (p<0.001).

[0059] According to the results of the analysis, FBG (Fasting Blood Sugar) has an effect of 5% and 2% on the expression levels of PPARy and LOC105377284 genes, respectively (p<0.001). It is statistically significant. According to the results of the regression analysis, there is no statistical correlation between FBG and PPARy and LOC105377284 genes.

[0060] Table 4. Parameters examined in the study groups

[0061] BMI <25 kg / m2group is a healthy control group. Since the gene expression levels of the BMI: 25- 29.9 kg / m2, BMI: 30-39.9 kg / m2and BMI>40 kg / m2groups were calculated according to the control group, the average values of the PPARy and LOC105377284 genes for the BMI <25 kg / m2group are not seen.

[0062] With the invention, a negative relationship was found between PPARy and total cholesterol. A negative correlation was found between HDL-C and PPARy, and a positive correlation was found between HDL-C and total cholesterol and LOC105377284. There is a negative correlation between LDL-C and PPARy and LDL-C and LOC105377284. A negative correlation is observed between Triglyceride and PPARy and Triglyceride and LOC105377284. When total cholesterol, HDL-K, LDL-K, and triglyceride are high, PPARy gene expression level decreases. The increase in HDL-C and total cholesterol level also causes an increase in the LOC105377284 gene. The increase in LDL-K and triglyceride level causes a decrease in the LOC105377284 gene. A positive correlation was found between the human orthologist LOC105377284 gene of Lnc-U90926 and vitamin B12 and ferritin. In addition, a positive correlation was found between the PPARy gene and Vitamin B12. The increase in vitamin B12 and ferritin values causes an increase in the expression levels of the PPARy and LOC105377284 genes.

[0063] There is no linear relationship between the eosinophil and the LOC105377284 gene. However, a negative relationship was found between the PPARy gene and eosinophil. In other words, the increase in the eosinophil value causes a decrease in the expression levels of the PPARy gene.

[0064] Neutrophil was found to have a statistically significant effect of 8% on the PPARy gene. In addition, although not statistically significant, there is a positive correlation between them. No linear relationship was found between the neutrophil and the LOC105377284 gene. Any change in the neutrophil does not affect the LOC105377284 gene.

[0065] It is aimed to investigate the effect of the PPARy gene, which is one of the main regulators of adipogenesis, and the Lnc-U90926 gene, which is defined in the mouse, which is known to play a role in adipogenesis, and the LOC105377284 gene, which is the human orthologist, in obesity in individuals exposed to overweight with both genetic and environmental effects. The obtained data revealed that there is a relationship between the PPARy and LOC105377284 genes and this relationship may be effective in obesity. An increase was found in the expression levels of the PPARy and LOC105377284 genes in the other 3 groups compared to the control group, the BMI: 18.5-24.9 kg / m2group. In addition, changes in lipid, cholesterol, micronutrient metabolism, and macrophage cell physiology have been found to affect obesity.

Claims

CLAIMS1. A primer for the real-time polymerase chain reaction, characterized in comprising the following sequences:Forward Primer Sequence ACCTCTCTGTGCCTCAACTTC (SEQ 1) or Reverse Primer Sequence GAAGACGATGGCAGAGAGCA (SEQ 2).

2. The primer according to claim 1, characterized in that it comprises the following sequence:Forward Primer Sequence ACCTCTCTTGTGCCTCAACTTC (SEQ 1).

3. The primer according to claim 1, characterized in that it comprises the following sequence:Reverse Primer Sequence GAAGACGATGGCAGAGAGCA (SEQ 2).

4. Method for use in the diagnosis of obesity, characterized in that the Forward Primer Sequence ACCTCTCTGTGCCTCAACTTC (SEQ 1) is used in the real-time polymerase chain reaction.

5. Method for use in the diagnosis of obesity, characterized in that the primer of the Reverse Primer Sequence GAAGACGATGGCAGAGAGCA (SEQ 2) is used in the real-time polymerase chain reaction.

6. Real-time polymerase chain reaction kit for use in the diagnosis of obesity, characterized in that it comprises Forward Primer Sequence ACCTCTCTGTGCCTCAACTTC (SEQ1) primer.

7. Real-time polymerase chain reaction kit for use in the diagnosis of obesity, characterized in that it comprises Reverse Primer Sequence GAAGACGATGGCAGAGAGCA (SEQ2) primer.

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