A set of biomarkers for diagnosing parkinson's disease with rapid eye movement sleep behavior disorder and applications thereof

Abstract

The application discloses a set of biomarkers for diagnosing Parkinson disease with rapid eye movement sleep behavior disorder and application thereof, and belongs to the technical field of biomarkers. The application studies changes in plasma metabolite levels of patients with Parkinson disease with rapid eye movement sleep behavior disorder (PD+RBD) and changes in inflammation-related proteins based on metabolomics and protein analysis methods, finds potential biomarkers, and can be applied to the diagnosis of PD+RBD, solves the current problem of diagnosing Parkinson disease with rapid eye movement sleep behavior disorder in the clinic, helps to establish a scientific treatment plan as early as possible, relieves the pain of patients, and has a very good application prospect.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of biomarkers, and particularly relates to a group of biomarkers for diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder and application thereof. BACKGROUND

[0002] Parkinson's disease (PD) is a neurodegenerative disease that mainly occurs in the elderly, and is also the most common severe movement disorder disease in the world. According to statistics, the incidence of PD in people over 60 years old is about 1%, and increases with age. With the acceleration of population aging, PD has become a major disease that endangers the health of the elderly in China. PD has insidious onset, unknown etiology, and currently there is no effective cure.

[0003] Recent studies have found that PD is not a single disease, and there are significant differences in clinical features, progression rate and prognosis, suggesting that PD has high heterogeneity. The main clinical features of PD include motor symptoms such as bradykinesia, resting tremor, muscle rigidity and postural imbalance, as well as non-motor symptoms such as hyposmia, autonomic dysfunction, sleep disorders, depression and cognitive impairment. Sleep disorders are the most common non-motor symptoms of PD, among which rapid eye movement sleep behavior disorder (RBD) is the main form of sleep disorder in PD patients and is considered to be the most likely biomarker in the prodromal stage of PD. Studies have shown that there is a strong correlation between RBD and the typical pathological feature of PD, alpha-synuclein. Early studies have found that PD patients with RBD (PD+RBD) have more severe PD motor symptoms, autonomic dysfunction and cognitive impairment than PD patients without RBD (PD-RBD), and have poorer effects of levodopa drug treatment and deep brain stimulation surgery, higher mortality and other clinical characteristics. At present, RBD is proposed as a subtype of PD in clinical practice, and PD with RBD may have specific pathophysiological mechanisms. Therefore, elucidating the specific pathogenesis of PD+RBD is of great significance for the timely detection and diagnosis of PD+RBD patients and individualized treatment, and for improving the prognosis of patients and improving the quality of life of patients. At present, the assessment of PD+RBD mainly relies on clinical manifestations and artificial evaluation (such as scales), which requires a lot of time and effort for both doctors and patients, and the evaluation results will be affected by the fluctuation of patient symptoms and the personal subjectivity of the doctor. Therefore, finding a simple, fast and accurate new method for identifying PD+RBD is crucial for better understanding the heterogeneity of PD+RBD, monitoring disease progression and developing individualized treatment plans.

[0004] Normal physiological sleep needs homeostatic system and biological rhythm system to maintain together. The generation of circadian rhythm depends on the biological clock system of the organism and the complex regulation network of clock gene composition. Studies have shown that there is a close relationship between biological clock system and metabolism, and the two are connected through a series of metabolic receptors such as redox receptors, energy metabolism receptors, hormone synthesis and secretion, bile acid receptors and sugar and lipid metabolism receptors. Researchers use imaging technology to study the brain function of PD patients with and without RBD, and find that PD patients with RBD have extensive cortical and subcortical cerebral blood perfusion abnormalities and metabolic changes. However, the pathogenesis of PD+RBD is still unclear. With the development of high-throughput technology, especially high-resolution mass spectrometry technology, the emergence of metabolomics and proteomics technology provides a new concept and method for elucidating the biological mechanism of complex diseases. Metabolomics can accurately and sensitively detect subtle changes in disease state, which helps to reveal the potential mechanism of disease pathology and find stable and reliable biomarkers. The joint analysis of metabolomics and proteomics can help to comprehensively display the whole picture of disease occurrence and development from multiple levels and multiple dimensions. However, so far, there is no effective biomarker for the diagnosis of PD+RBD. SUMMARY

[0005] In view of the defects of the prior art, the purpose of the present application is to provide a group of biomarkers for diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder and application thereof. The present application studies the changes of plasma metabolites and inflammation-related proteins in PD+RBD patients based on metabolomics and protein analysis methods, and finds potential biomarkers that can be applied to the diagnosis of PD+RBD, solving the current clinical diagnosis problem of Parkinson's disease with rapid eye movement sleep behavior disorder, helping to establish a scientific treatment plan earlier, relieving the pain of patients, and having a very good application prospect.

[0006] To achieve the above purpose, the present application provides the following technical solutions:

[0007] In a first aspect, the present application provides a group of biomarkers for diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder, which includes 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, heptadecanoic acid, p-cresol sulfate, p-cresol glucuronide, toll-like receptor 3 (TLR3), copper-dependent amine oxidase (AOC1) and 2'-deoxynucleoside 5-monophosphate N-glycosidase (DNPH1).

[0008] As a preferred embodiment of the present application, the relative concentrations of 3-hydroxycinnamic acid, 5-hydroxyproline, p-cresol sulfate, p-cresol glucuronide, AOC1 and DNPH1 are significantly increased in the plasma of patients with Parkinson's disease with rapid eye movement sleep behavior disorder (PD+RBD), while the relative concentrations of 5-hydroxyindoleacetic acid, heptadecanoic acid and TLR3 are significantly reduced.

[0009] In a second aspect, the present application provides the use of the above-mentioned biomarkers in the preparation of a reagent / kit for diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder.

[0010] As a preferred embodiment of the present application, the use is to diagnose whether it belongs to Parkinson's disease with rapid eye movement sleep behavior disorder by combining 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, heptadecanoic acid, p-cresol sulfate, p-cresol glucuronide, toll-like receptor 3 (TLR3), copper-dependent amine oxidase (AOC1) and 2'-deoxynucleoside 5-monophosphate N-glycosidase (DNPH1).

[0011] In a third aspect, the present application provides a kit, which comprises reagents for detecting the above-mentioned biomarkers for diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder and instructions, wherein the detection reagents comprise reagents for detecting 3-hydroxycinnamic acid, reagents for detecting 5-hydroxyindoleacetic acid, reagents for detecting 5-hydroxyproline, reagents for detecting heptadecanoic acid, reagents for detecting p-cresol sulfate, reagents for detecting p-cresol glucuronide, reagents for detecting TLR3, reagents for detecting AOC1 and reagents for detecting DNPH1, and the instructions record a method for detecting the above-mentioned biomarkers in a subject; the kit is used to diagnose whether the subject is Parkinson's disease with rapid eye movement sleep behavior disorder.

[0012] As a preferred embodiment of the present application, the instructions record the following method:

[0013] The levels or contents of the above-mentioned biomarkers in the plasma from the subject are detected using the kit, and the contents of 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, heptadecanoic acid, p-cresol sulfate, p-cresol glucuronide, TLR3, AOC1 and DNPH1 (the contents of TLR3, AOC1 and DNPH1 are the contents after logarithmic conversion Log2) are respectively denoted as A, B, C, D, E, F, G, H and I;

[0014] In the differentiation of PD+RBD and Ctrl, according to the following formula:

[0015] X1 = 20.673*A - 719.096*B - 5.713*C - 1.417*D + 3.339*E + 3.577*F - 0.832*G + 0.700*H + 0.925*I + 2.025;

[0016] Pi(PD+RBD) = 1 / (1+e -X1 );

[0017] Pi(PD+RBD) = 1 / (1+e -X2 );

[0018] Pi(PD+RBD) = 1 / (1+e -X2 );

[0019] X2 = 10.862*A - 393.439*B - 368.522*C - 1.423*D + 11.742*E - 22.868*F - 2.24*G + 1.295*H + 2.314*I + 2.053;

[0020] Pi(PD+RBD) = 1 / (1+e -X2 );

[0021] Pi(PD+RBD) = 1 / (1+e -X2 );

[0022] As a preferred embodiment of the present application, the detection of the above biomarkers is carried out by liquid chromatography-mass spectrometry.

[0023] As a preferred embodiment of the present application, the mass spectrometry is in positive ion mode, the liquid chromatography uses an ACQUITY UPLC BEH C8 (2.1 mm x 50 mm, 1.7 μm) chromatographic column, the mobile phase A is 0.1% formic acid aqueous solution, the mobile phase B is 0.1% formic acid acetonitrile solution, the elution gradient is 5% B for 0-0.5 min, linearly changes to 40% B for 0.5 min-2 min, linearly changes to 100% B phase for 2 min-8 min, maintains for 2 min, linearly changes to 5% B phase for 10 min-10.1 min and balances for 1.9 min, and the flow rate of the mobile phase is 0.40 mL / min.

[0024] As a preferred embodiment of the present application, the mass spectrometer is a triple TOF 5600 plus system, and the parameters are set as follows: GS1, GS2 and CUR are 50 psi, 50 psi and 35 psi respectively; the ion source temperature is 500 DEG C; and the ion source voltages in positive and negative ion modes are 5500 V and -4500 V respectively.

[0025] As a preferred embodiment of the present application, the mass spectrometer is a triple TOF 5600 plus system, and the parameters are set as follows: GS1, GS2 and CUR are 50 psi, 50 psi and 35 psi respectively; the ion source temperature is 500 DEG C; and the ion source voltages in positive and negative ion modes are 5500 V and -4500 V respectively.

[0026] The present application has the following beneficial effects relative to the prior art:

[0027] 1. The present application provides a new biomarker 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, heptadecanoic acid, p-cresol sulfate, p-cresol glucuronide, TLR3, AOC1 and DNPH1 and a model for discriminating Parkinson's disease with rapid eye movement sleep behavior disorder, which can identify Parkinson's disease with rapid eye movement sleep behavior disorder, and thus be applied to the preparation of products related to the diagnosis and efficacy evaluation of Parkinson's disease with rapid eye movement sleep behavior disorder. The biomarker has high accuracy, fast detection speed, low cost, small trauma and is easy to be accepted by patients, and thus provides a scientific and effective diagnosis scheme for Parkinson's disease with rapid eye movement sleep behavior disorder.

[0028] 2. The present application can form a kit by detecting 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, heptadecanoic acid, p-cresol sulfate, p-cresol glucuronide, TLR3, AOC1 and DNPH1, which can effectively solve the current clinical diagnosis problem of Parkinson's disease with rapid eye movement sleep behavior disorder, help to establish a scientific treatment scheme earlier, relieve the pain of patients, and have a good application prospect. BRIEF DESCRIPTION OF DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present application, the drawings involved in the embodiments will be briefly introduced as follows.

[0030] Figure 1is the ROC analysis graph of the biomarker panel distinguishing PD+RBD from Ctrl, wherein A is the ROC analysis graph of the biomarker panel and each metabolite or protein distinguishing PD+RBD from Ctrl; B is the statistical graph of Pi(PD+RBD) of the biomarker panel for the prediction of PD+RBD and Ctrl, Pi(PD+RBD) greater than 0.500 is PD+RBD, and less than 0.500 is Ctrl; C is the accuracy graph of the biomarker panel for identifying PD+RBD and Ctrl.

[0031] Figure 2 is the ROC analysis graph of the biomarker panel distinguishing PD+RBD from PD-RBD, wherein A is the ROC analysis graph of the biomarker panel and each metabolite or protein distinguishing PD+RBD from PD-RBD; B is the statistical graph of Pi(PD+RBD) of the biomarker panel for the prediction of PD+RBD and PD-RBD, Pi(PD+RBD) greater than 0.500 is PD+RBD, and less than 0.500 is PD-RBD; C is the accuracy graph of the biomarker panel for identifying PD+RBD and PD-RBD. DETAILED DESCRIPTION

[0032] The application will be described in detail below with reference to the embodiments. However, the embodiments of the application are not limited thereto, and it is obvious that the embodiments described below are only some of the embodiments of the application, and other similar embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0033] Example 1

[0034] 1. Model establishment sample group 316 people

[0035] 1.1 PD group patient enrollment criteria

[0036] The enrolled patients met the Chinese PD diagnostic criteria (Chinese Parkinson's Disease Treatment Guidelines (second edition)) formulated on the basis of the PD diagnostic criteria in the UK brain bank, and were independently diagnosed by two neurologists. The following cases were excluded: patients with severe diabetes, severe hypertension, obvious cerebrovascular disease and other nervous system disease history, obvious brain trauma and nervous system operation history; patients with tumor diseases; patients with various infections in the near future (4 weeks); patients with serious bad living habits.

[0037] 1.2 Diagnosis criteria of RBD

[0038] According to the International Classification of Sleep Disorders, Third Edition (ICSD-3) revised by the American Sleep Medicine Society, if the polysomnogram (PSG) of the patient shows that there is a skeletal muscle weakness phenomenon (RWA) in the REM sleep period, that is, the persistent muscle tension is increased and the explosive muscle activity is increased, and the clinical symptoms have clear dream behavior interpretation (DEB), it can be diagnosed as RBD patient. For patients who have not undergone PSG detection, if the RBD questionnaire-Hong Kong version (RBD questionnaire-Hong Kong, RBDQ-HK) scale score is higher than 18 points, and the clinical manifestations are consistent with DEB, it is determined as a clinically possible RBD patient.

[0039] 1.3 Ctrl group entry criteria

[0040] The enrolled population meets the diagnostic criteria of healthy people and is excluded from the following cases: patients with a history of nervous system diseases or mental diseases, patients with various infections in the near future (4 weeks), and patients with serious adverse lifestyle habits.

[0041] In this embodiment, 105 cases of PD+RBD patients, the male to female ratio is about 1:1, the age range is 46-82, and the average age is 68 years old. 106 cases of PD-RBD patients, the male to female ratio is about 1:1, the age range is 50-84, and the average age is 67 years old. 105 cases of Ctrl group, the male to female ratio is about 1:1, the age range is 47-86, and the average age is 68 years old. The age and gender composition of the three groups are statistically different.

[0042] 2. Method

[0043] 2.1 Collection and pretreatment of plasma samples

[0044] Fasting blood was collected in an EDTA anticoagulant tube and stood for 30 minutes, centrifuged at 3000 rpm / min for 5 minutes, and the plasma was taken and stored in a -80°C refrigerator for standby. The plasma was thawed at room temperature, 50 μL of plasma was taken in a 1.5 mL centrifuge tube, 200 μL of extraction solution containing internal standard (methanol) was added (the specific concentration is shown in Table 1), vortexed for 2 min, and then centrifuged using a high-speed centrifuge for 15 min (15000g, 6°C); 200 μL of supernatant was vacuum centrifuged to powder, and stored in a -80°C refrigerator. Before sampling, the sample was reconstituted with 60 μL of methanol / water=1 / 4 (v / v) solution; vortex for 2 min, then centrifuge at 15000g, 10°C for 15 min, and take the supernatant to the sample bottle containing the inner liner for ultra-high performance liquid chromatography-mass spectrometry analysis.

[0045] Table 1. Internal standard concentration in extraction solution

[0046] Isotopic internal standard compounds Concentration (pg / mL) D3-acetylcarnitine 0.40 D3-palmitoylcarnitine 0.15 D5-propylphenylalanine 3.00 D5-tryptophan 4.00 D4-cholic acid 0.50 D4-chenodeoxycholic acid 0.80 D3-palmitic acid 2.50 lysophosphatidylcholine LPC 19:0 00.20 tridecanoic acid 3.00

[0047] 2.2 Ultra-high performance liquid chromatography-mass spectrometry analysis

[0048] (1) Liquid chromatography conditions: Waters ACQUITY UPLC HSS T3 (2.1 mm x 50 mm, 1.8 μιη) column (Waters, Ireland) was used with a mass spectrometer in positive mode. Mobile phase A was 0.1% formic acid in water and mobile phase B was 0.1% formic acid in acetonitrile. The elution gradient was 5% B for 0-0.5 min, linear change to 40% B for 0.5-2 min, linear change to 100% B for 2-8 min, hold for 2 min, linear change to 5% B for 10-10.1 min and equilibrate for 1.9 min. The flow rate was 0.40 mL / min.

[0049] Mass spectrometer in negative mode, ACQUITY UPLC HSS T3 (2.1 mm x 50 mm, 1.8 μιη) column (Waters, Ireland) was used. Mobile phase C was 6.5 mM ammonium bicarbonate in water and mobile phase D was 6.5 mM ammonium bicarbonate in methanol / water (methanol:water = 95:5, v / v). The elution gradient was 2% D for 0-0.5 min, linear change to 40% D for 0.5-2 min, linear change to 100% D for 2-8 min, hold for 2 min, linear change to 2% D for 0.1 min and equilibrate for 1.9 min. The temperature of the autosampler was 6 °C and the column temperature was 60 °C. The injection volume was 5 μί.

[0050] (2) Mass spectrometer conditions: triple TOF™ 5600 plus (Applied Biosystems, Foster City, CA) system was used. The parameters were set as follows: GS1, GS2 and CUR were 50 psi, 50 psi and 35 psi, respectively; ion source temperature, 500 °C; ion source voltage was 5500 V and -4500 V in positive and negative mode, respectively.

[0051] 2.3 Protein analysis

[0052] The expression levels of TLR3, AOC1 and DNPH1 in the plasma were analyzed by PEA (Proximity Extension Assay) technology. This technology is a method for recognizing and quantifying specific proteins in the plasma by using antibody and DNA oligonucleotide markers. A unique sequence of DNA barcode is generated through hybridization and extension of DNA, and then amplified and quantified by quantitative PCR. Finally, the data is standardized as the quantitative result of the protein. In short, the antibody with a designed oligonucleotide sequence is connected with the target protein, and the two oligonucleotide sequences connected to the protein are complementary to each other, and then extended under the action of DNA polymerase. The amplified PCR sequence is detected by high-throughput sequencing.

[0053] 3. Result analysis

[0054] The quantitative results of the metabolites were obtained according to the above method. According to the internal standard, the concentrations of 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, heptadecanoic acid, p-cresol sulfate and p-cresol glucuronide were calculated (see Table 2). The calculation formula is as follows:

[0055] Concentration 3-羟基肉桂酸 = Peak area 3-羟基肉桂酸 / Peak area D3-乙酰基肉碱 * 0.40 μg / mL;

[0056] Concentration 5-羟基吲哚乙酸 = Peak area 5-羟基吲哚乙酸 / Peak area D4-鹅脱氧胆酸 * 0.80 μg / mL;

[0057] Concentration 5-羟脯氨酸 = Peak area 5-羟脯氨酸 / Peak area D4-胆酸 * 0.50 μg / mL;

[0058] Concentration 十七烷酸 = Peak area 十七烷酸 / Peak area D5-色氨酸 * 4.00 μg / mL;

[0059] Concentration 对甲酚硫酸 = Peak area 对甲酚硫酸 / Peak area D4-鹅脱氧胆酸 * 0.80 μg / mL;

[0060] Concentration 对甲酚葡糖苷酸 = Peak area 对甲酚葡糖苷酸 / Peak area D5-色氨酸 * 4.00 μg / mL.

[0061] Table 2. Contents of six metabolites in three groups of samples

[0062]

[0063]

[0064] In addition, the normalized protein expression value (NPX value) obtained by logarithmic conversion (Log2) of the high-throughput sequencing result counts value was used as the relative quantitative unit of protein. The average NPX value of TLR3, AOC1 and DNPH1 in the three groups is shown in Table 3.

[0065] Table 3. Relative content of three proteins in three groups of samples

[0066] protein Ctrl (pg / mL) PD-RBD (pg / mL) PD+RBD (pg / mL) TLR3 -1.9301 -0.04193 -0.37942 AOC1 -0.7825 -0.04976 0.50225 DNPH1 1.0955 -0.0176 0.322891

[0067] Compared with Ctrl and PD-RBD patients, the concentrations of 3-hydroxy cinnamic acid, 5-hydroxy proline, p-cresol sulfate, p-cresol glucuronide, AOC1 and DNPH1 were significantly increased in PD+RBD patients, while the concentrations of 5-hydroxy indole acetic acid, heptadecanoic acid and TLR3 were significantly decreased. Subsequently, the above single indicators were further evaluated for their overall diagnostic and predictive effects by calculating the Youden index. The area under the curve (AUC), sensitivity and specificity of individual metabolites or proteins in predicting Parkinson's disease with rapid eye movement sleep behavior disorder are shown in Table 4.

[0068] Table 4. Youden index analysis of single indicators related to PD+RBD

[0069]

[0070] The AUC, sensitivity and specificity of individual metabolites or proteins in predicting Parkinson's disease with rapid eye movement sleep behavior disorder are listed in Table 4. The relevant parameters show that the use of any of the above indicators alone to distinguish PD+RBD from Ctrl or to distinguish PD+RBD from PD-RBD is not ideal. However, the sensitivity and specificity of the above indicators show good complementarity in identifying PD+RBD.

[0071] 4. Auxiliary diagnosis

[0072] To improve the diagnostic effect, we further used the concentration values of the above six metabolites and three proteins in each clinical sample to establish a diagnostic model to find the optimal combination of variables. It was found that when the above six metabolites and three proteins were combined to establish a combined marker model, the resulting model was the best. The parameters of this model, including AUC, sensitivity and specificity, are shown in Table 5. Among them, the contents of 3-hydroxy cinnamic acid, 5-hydroxy indole acetic acid, 5-hydroxy proline, heptadecanoic acid, p-cresol sulfate, p-cresol glucuronide, TLR3, AOC1 and DNPH1 are denoted as A, B, C, D, E, F, G, H and I, respectively.

[0073] Table 5. Youden's index analysis of combined marker models

[0074]

[0075] The results show that the above combined marker models all have good discrimination effect in distinguishing PD+RBD from Ctrl, with AUC all greater than 0.920. However, in distinguishing PD+RBD from PD-RBD, only when the above six metabolites and three proteins are combined to establish a combined marker model, the resulting model is the best, with AUC reaching more than 0.910. Therefore, we finally choose the combination of the above nine indicators as the discrimination model of PD+RBD.

[0076] Based on the above established logistic regression model, in distinguishing PD+RBD from Ctrl, regression equation 1 is:

[0077] X1 = 20.673*A - 719.096*B - 5.713*C - 1.417*D + 3.339*E + 3.577*F - 0.832*G + 0.700*H + 0.925*I + 2.025;

[0078] Pi(PD+RBD) = 1 / (1+e -X1 );

[0079] In distinguishing PD+RBD from Ctrl, regression equation 2 is:

[0080] X2 = 10.862*A - 393.439*B - 368.522*C - 1.423*D + 11.742*E - 22.868*F - 2.24*G + 1.295*H + 2.314*I + 2.053;

[0081] Pi(PD+RBD) = 1 / (1+e -X2 );

[0082] Where e is Euler's number, which is the base of natural logarithm.

[0083] Bringing into binary logistic regression equation, the variable Pi(PD+RBD) is higher in PD+RBD patients than in Ctrl and PD-RBD patients. When the variable Pi(PD+RBD) uses the cut-off value 0.500, the discrimination effect on PD+RBD is as shown in the figure. Figure 1-2 The established combined marker model has an AUC value of 0.946 in distinguishing PD+RBD patients from Ctrl, a sensitivity of 82.8%, a specificity of 96.6%, and a discrimination accuracy of more than 86% for PD+RBD and Ctrl (see Figure 1 ). In addition, the combined marker model has an AUC value of 0.917 in distinguishing PD+RBD patients from PD-RBD, a sensitivity of 84.5%, a specificity of 89.8%, and a discrimination accuracy of more than 84% for PD+RBD and PD-RBD (see Figure 2 ). The above results show that the combined marker established by us has very good discrimination effect in distinguishing normal people from PD+RBD patients and PD-RBD from PD+RBD patients.

[0084] Example 2

[0085] We additionally collected 93 plasma samples as an external validation set to verify the logistic regression model established in Example 1. Among them, 31 PD+RBD patients, the male to female ratio was about 1:1, the age range was 52-81, and the average age was 66. 31 PD-RBD patients, the male to female ratio was about 1:1, the age range was 55-82, and the average age was 68. 31 Ctrl, the male to female ratio was about 1:1, the age range was 56-85, and the average age was 67. The age and gender composition of the three groups were statistically different.

[0086] According to the detection method in Example 1, the contents of A, B, C, D, E, F, G, H and I were obtained, and the accuracy of the model in Example 1 was verified. The results show that the above combined marker model has an AUC value of 0.921 in distinguishing PD+RBD patients from Ctrl, a sensitivity of 86.8%, and a specificity of 83.6%. The combined marker model has an AUC value of 0.882 in distinguishing PD+RBD patients from PD-RBD, a sensitivity of 88.1%, and a specificity of 82.8%. The above results show that the combined marker model established by the present application has the potential to be applied to the clinical diagnosis of PD+RBD.

[0087] The application has the characteristics of rapidness, high sensitivity, low cost and high stability. Meanwhile, the application can be applied to the clinical diagnosis of auxiliary PD+RBD and has high development and application value. The application can form a reagent kit by detecting 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, heptadecanoic acid, p-cresol sulfate, p-cresol glucuronide, TLR3, AOC1 and DNPH1, which can effectively solve the current clinical diagnosis problem of Parkinson's disease with rapid eye movement sleep behavior disorder, help to establish a scientific treatment plan earlier, relieve the pain of patients and have good application prospect.

[0088] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the application, and not to limit them; although the application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the application.

Claims

1. A set of biomarkers for diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder, characterized in that: The biomarkers consist of 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, heptadecanoic acid, p-cresol sulfate, p-cresol glucuronide, toll-like receptor 3 (TLR3), copper-dependent amine oxidase (AOC1), and 2'-deoxynucleoside 5-monophosphate N-glycosidase (DNPH1).

2. Use of the biomarker according to claim 1 in the preparation of a reagent / kit for diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder.

3. The use according to claim 2, characterized in that The application is to combine 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, heptadecanoic acid, p-cresol sulfate, p-cresol glucuronide, toll-like receptor 3 (TLR3), copper-dependent amine oxidase (AOC1) and 2'-deoxynucleoside 5-monophosphate N-glycosidase (DNPH1) to diagnose whether it is Parkinson's disease with rapid eye movement sleep behavior disorder.

4. A kit, characterized in that The kit comprises reagents and instructions for detecting the biomarkers according to claim 1, wherein the reagents include reagents for detecting 3-hydroxycinnamic acid, reagents for detecting 5-hydroxyindoleacetic acid, reagents for detecting 5-hydroxyproline, reagents for detecting heptadecanoic acid, reagents for detecting p-cresol sulfate, reagents for detecting p-cresol glucuronide, reagents for detecting TLR3, reagents for detecting AOC1, and reagents for detecting DNPH1, and the instructions describe a method for detecting the above-mentioned biomarkers in a subject; the kit is used to diagnose whether a subject has Parkinson's disease with rapid eye movement sleep behavior disorder.

5. The kit according to claim 4, characterized in that The instructions describe the following method: The levels or contents of the above biomarkers in the plasma of the subjects were detected using a kit. The contents of 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, heptadecanoic acid, p-cresol sulfate, p-cresol glucuronide, TLR3, AOC1, and DNPH1 were denoted as A, B, C, D, E, F, G, H, and I, respectively. The contents of TLR3, AOC1, and DNPH1 were logarithmically transformed (Log2). When distinguishing PD+RBD from Ctrl, the following formula is used: X1=20.673*A-719.096*B-5.713*C-1.417*D+3.339*E+3.577*F-0.832*G+0.700*H+0.925*I+2.025; Pi(PD+RBD)=1 / (1+e -X1 ); Where e is the Euler number. The Pi (PD + RBD) value is calculated. The cutoff value of the variable Pi (PD + RBD) is set to 0.

500. When the Pi (PD + RBD) value is greater than 0.500, it is determined to be a PD + RBD patient, otherwise it is a non-PD + RBD patient; When distinguishing PD+RBD from PD-RBD, the following formula is used: X2=10.862*A-393.439*B-368.522*C-1.423*D+11.742*E-22.868*F-2.24*G+1.295*H+2.314*I+2.053; Pi(PD+RBD)=1 / (1+e -X2 ); The Pi (PD+RBD) value was calculated, and the cutoff value of the variable Pi (PD+RBD) was set to 0.

500. When the Pi (PD+RBD) value was greater than 0.500, the patient was judged to be a PD+RBD patient, otherwise he was judged to be a non-PD+RBD patient.

6. The kit according to claim 5, wherein The biomarkers are detected by liquid chromatography-mass spectrometry.

7. The kit according to claim 6, wherein Mass spectrometry was performed in positive ion mode, and liquid chromatography was performed on an ACQUITY UPLC BEH C8 column, 2.1 mm × 50 mm, 1.7 µm. Mobile phase A was 0.1% formic acid in water, and mobile phase B was 0.1% formic acid in acetonitrile. The elution gradient was as follows: 5% B from 0 to 0.5 min, linearly changing to 40% B from 0.5 min to 2 min, linearly changing to 100% B from 2 min to 8 min, holding for 2 min, linearly changing to 5% B from 10 min to 10.1 min, and equilibrating for 1.9 min. The mobile phase flow rate was 0.40 mL / min.

8. The kit according to claim 6, wherein The mass spectrometer was operated in negative ion mode using an ACQUITY UPLCHSS T3 column (2.1 mm × 50 mm, 1.8 µm). The mobile phase C was a 6.5 mM ammonium bicarbonate aqueous solution, and the mobile phase D was a 6.5 mM ammonium bicarbonate / methanol / water solution with a volume ratio of 95:

5. The elution gradient was as follows: 2% D from 0 to 0.5 min, linearly changing to 40% D from 0.5 min to 2 min, linearly changing to 100% D from 2 min to 8 min, holding for 2 min, and then linearly changing to 2% D within 0.1 min and equilibrating for 1.9 min.

9. The kit according to claim 7 or 8, characterized in that The mass spectrometer was a tripleTOFTM5600plus system with the following parameter settings: GS1, GS2, and CUR were 50 psi, 50 psi, and 35 psi, respectively; the ion source temperature was 500°C; and the ion source voltages were 5500 V and -4500 V in the positive and negative ion modes, respectively.

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