Biomarkers for diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder and application thereof

Abstract

The invention discloses a group of biomarkers for diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder and application thereof, and belongs to the technical field of biomarkers. According to the invention, on the basis of metabonomics and a protein analysis method, the change of plasma metabolite level and the change of inflammation-related protein of patients with Parkinson's disease with rapid eye movement sleep behavior disorder (PD + RBD) are studied, and a potential biomarker is found and can be applied to the diagnosis of PD + RBD; the problem of diagnosis of clinical Parkinson's disease with rapid eye movement sleep behavior disorder at present is solved, a scientific treatment scheme can be determined earlier, the pain of a patient is relieved, and the method has a very good application prospect.

Description

Technical Field

[0001] The present invention 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 their applications. Background Art

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

[0003] In recent years, studies have found that PD is not a single disease, and there are significant differences in its clinical characteristics, progression speed, prognosis, etc., indicating that PD has high heterogeneity. The main clinical characteristics of PD include motor symptoms mainly manifested as bradykinesia, resting tremor, muscle rigidity, and postural balance disorder, as well as non-motor symptoms such as hyposmia, autonomic dysfunction, sleep disorder, depression, and cognitive impairment. Sleep disorder is the most common non-motor symptom in PD. Among them, rapid eye movement sleep behavior disorder (RBD) is the main form of sleep disorder in PD patients and is considered the biomarker with the largest likelihood ratio in the prodromal stage of PD. And studies have shown that there is a strong correlation between RBD and the typical pathological feature α-synuclein in PD. Early studies found that PD patients with RBD (PD+RBD) have more severe PD motor symptoms, autonomic dysfunction, and cognitive impairment compared with PD patients without RBD (PD-RBD), and have worse effects in the treatment with levodopa drugs and deep brain stimulation surgery, and higher mortality and other clinical characteristics. Currently, it is clinically proposed that RBD is a subtype of PD, and PD with RBD may have specific pathophysiological mechanisms. Therefore, clarifying the specific pathogenesis of PD+RBD is of great significance for the timely detection and diagnosis of PD+RBD patients and personalized treatment, and for improving the prognosis of patients and enhancing the quality of life of patients. Currently, the evaluation of PD+RBD mainly relies on clinical manifestations and manual evaluations (such as scales), which requires a large amount of time and energy from both physicians and patients, and the evaluation results are affected by the fluctuations of patients' symptoms and the subjectivity of physicians. 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 formulating individualized treatment plans.

[0004] Normal physiological sleep requires the joint maintenance of the homeostatic system and the circadian rhythm system. The generation of the circadian rhythm depends on the organism's own biological clock system and the complex regulatory network formed by clock-controlled genes. Existing studies have shown that there is a close connection between the biological clock system and metabolism, and the two are connected through a series of metabolic sensors such as redox sensors, energy metabolism sensors, hormone synthesis and secretion, bile acid sensors, and glycolipid metabolism sensors. Researchers used imaging techniques to study the brain function of PD patients with and without RBD and found that PD patients with RBD had widespread cortical and subcortical cerebral blood perfusion abnormalities and metabolic changes. However, currently, the pathogenesis of PD+RBD is still unclear. With the development of high-throughput technologies, especially high-resolution mass spectrometry technology, the emergence of technologies such as metabolomics and proteomics has provided new ideas and methods for clarifying the biological mechanisms of complex diseases. Metabolomics can accurately and sensitively detect subtle changes in disease states, helping to reveal the potential mechanisms of disease pathology and discover stable and reliable biomarkers. The combined analysis of metabolomics and proteomics helps to comprehensively display the whole picture of the occurrence and development of diseases from multiple levels and dimensions. However, so far, no effective biomarkers for the diagnosis of PD+RBD have been found. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the purpose of the present invention is to provide a group of biomarkers for diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder and their applications. The present invention studied the changes in plasma metabolite levels and the alterations of inflammation-related proteins in PD+RBD patients based on metabolomics and protein analysis methods, discovered potential biomarkers, which can be applied to the diagnosis of PD+RBD, solve the current clinical problem of diagnosing 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 very good application prospects.

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

[0007] In the first aspect, the present invention provides a group of biomarkers for diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder, and the biomarkers include 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 invention, 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 decreased.

[0009] In a second aspect, the present invention 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 invention, 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 belongs to Parkinson's disease with rapid eye movement sleep behavior disorder.

[0011] In a third aspect, the present invention provides a kit, which includes reagents for detecting the above-mentioned biomarkers for diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder and an instruction manual. Among them, the detection 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. The instruction manual describes the method for detecting the above-mentioned biomarkers of the subject; the kit is used to diagnose whether the subject has Parkinson's disease with rapid eye movement sleep behavior disorder.

[0012] As a preferred embodiment of the present invention, the instruction manual describes the following method:

[0013] Use the kit to detect the levels or contents of the above-mentioned biomarkers in the plasma from the subject. 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 transformation Log2) are respectively denoted as A, B, C, D, E, F, G, H, and I;

[0014] When differentiating PD+RBD from 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] where e is the Euler number, i.e., the base of the natural logarithm. Calculate the value of Pi(PD + RBD), and this variable value can be used to assist in the determination of PD + RBD; based on the clinical samples involved in this experiment, according to the principle of the best diagnostic sensitivity and specificity, the cut-off value of the variable Pi(PD + RBD) is set to 0.500, that is, when the value of Pi(PD + RBD) is greater than 0.500, it is determined as a patient with PD + RBD, otherwise it is a non-PD + RBD patient;

[0018] When differentiating PD + RBD from PD - RBD, according to the following formula:

[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] Calculate the value of Pi(PD + RBD). Based on the clinical samples involved in this experiment, according to the principle of the best diagnostic sensitivity and specificity, the cut-off value of the variable Pi(PD + RBD) is set to 0.500, that is, when the value of Pi(PD + RBD) is greater than 0.500, it is determined as a patient with PD + RBD, otherwise it is a non-PD + RBD patient.

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

[0023] As a preferred embodiment of the present invention, in the positive ion mode of mass spectrometry, the liquid chromatography uses an ACQUITY UPLC BEH C8 (2.1 mm x 50 mm, 1.7 μm) chromatographic column. Mobile phase A is an aqueous solution of 0.1% formic acid, and mobile phase B is an acetonitrile solution of 0.1% formic acid. The elution gradient: 0 - 0.5 min is 5% B, linearly changes to 40% B from 0.5 min to 2 min, linearly changes to 100% B phase from 2 min to 8 min, holds for 2 min, linearly changes to 5% B phase from 10 min to 10.1 min and equilibrates 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 invention, in the negative ion mode of the mass spectrometry, an ACQUITY UPLC HSST3 (2.1 mm x 50 mm, 1.8 μm) chromatographic column is used. Mobile phase C is an aqueous solution of 6.5 mM ammonium bicarbonate, and mobile phase D is a methanol / water solution of 6.5 mM ammonium bicarbonate with a volume ratio of 95:5. The elution gradient is 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. After maintaining for 2 min, it linearly changes to 2% D within 0.1 min and equilibrates for 1.9 min.

[0025] As a preferred embodiment of the present invention, the mass spectrometer is a tripleTOFTM5600plus system, and the parameter settings are as follows: GS1, GS2, and CUR are 50 psi, 50 psi, and 35 psi respectively; the ion source temperature is 500 °C; the ion source voltages in positive and negative ion modes are 5500 V and -4500 V respectively.

[0026] The beneficial effects of the present invention compared with the prior art are as follows:

[0027] 1. The present invention provides new biomarkers 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, heptadecanoic acid, p-cresol sulfate, p-cresol glucuronide, TLR3, AOC1, and DNPH1, as well as 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 can be applied to the preparation of related products for the diagnosis and efficacy evaluation of Parkinson's disease with rapid eye movement sleep behavior disorder. The biomarkers of the present invention have high accuracy, fast detection speed, low cost, little trauma, and are easy for patients to accept, providing a scientific and effective diagnosis scheme for Parkinson's disease with rapid eye movement sleep behavior disorder.

[0028] 2. The present invention can form a kit with reagents for detecting 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, heptadecanoic acid, p-cresol sulfate, p-cresol glucuronide, TLR3, AOC1, and DNPH1. This kit will effectively solve the current clinical problem of diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder, help establish a scientific treatment plan earlier, relieve the pain of patients, and has good application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention, the drawings related to the embodiments will be briefly introduced below.

[0030] Figure 1It is the receiver operating characteristic (ROC) analysis chart of the biomarker panel for differentiating PD+RBD from Ctrl. Among them, A is the ROC analysis chart of the biomarker panel and each metabolite or protein for differentiating PD+RBD from Ctrl; B is the statistical chart of the prediction of Pi(PD+RBD) of the biomarker panel for PD+RBD and Ctrl. When Pi(PD+RBD) is greater than 0.500, it is PD+RBD, and when it is less than 0.500, it is Ctrl; C is the accuracy chart of the biomarker panel for identifying PD+RBD and Ctrl.

[0031] Figure 2 It is the receiver operating characteristic (ROC) analysis chart of the biomarker panel for differentiating PD+RBD from PD-RBD. Among them, A is the ROC analysis chart of the biomarker panel and each metabolite or protein for differentiating PD+RBD from PD-RBD; B is the statistical chart of the prediction of Pi(PD+RBD) of the biomarker panel for PD+RBD and PD-RBD. When Pi(PD+RBD) is greater than 0.500, it is PD+RBD, and when it is less than 0.500, it is PD-RBD; C is the accuracy chart of the biomarker panel for identifying PD+RBD and PD-RBD. Detailed implementation manners

[0032] The present invention will be described in detail below in conjunction with embodiments. However, the implementation manners of the present invention are not limited thereto. Obviously, the embodiments described below are only partial embodiments of the present invention. For those skilled in the art, without creative efforts, obtaining other similar embodiments will fall within the protection scope of the present invention.

[0033] Example 1

[0034] 1. The sample group for model establishment is 316 people

[0035] 1.1 Inclusion criteria for patients in the PD group

[0036] The included patients meet the Chinese PD diagnostic criteria (the Second Edition of the Chinese Parkinson's Disease Treatment Guidelines) formulated on the basis of the UK Brain Bank PD diagnostic criteria, and are independently diagnosed by two neurologists respectively. Exclude the following situations: patients with a history of severe diabetes, severe hypertension, obvious cerebrovascular diseases and other neurological diseases, obvious brain trauma and neurological surgery history; patients with concurrent tumor diseases; patients with various infections in the recent period (4 weeks); patients with severe bad living habits.

[0037] 1.2 Diagnostic criteria for RBD

[0038] According to the International Classification of Sleep Disorders, 3rd Edition, Revised (ICSD-3) by the American Academy of Sleep Medicine, if a patient shows rapid eye movement (REM) sleep without atonia (RWA) during polysomnography (PSG) testing, that is, persistent muscle tone increase and burst electromyogram activity, and at the same time has clear dream enactment behavior (DEB) in clinical symptoms, the patient can be diagnosed as an RBD patient. For patients who have not undergone PSG testing, if the score on the RBD questionnaire - Hong Kong version (RBDQ-HK) scale is higher than 18 points and the clinical manifestations are consistent with DEB, they are determined to be clinically probable RBD patients.

[0039] 1.3 Inclusion criteria for the Ctrl group

[0040] The enrolled population all met the diagnostic criteria for healthy individuals and excluded the following conditions: those with a history of neurological or mental diseases, those with various infections in the recent period (4 weeks), and those with serious bad living habits.

[0041] In this example, there were 105 PD+RBD patients, with a male-to-female ratio of approximately 1:1, an age range of 46 - 82, and an average age of 68 years. There were 106 PD-RBD patients, with a male-to-female ratio of approximately 1:1, an age range of 50 - 84, and an average age of 67 years. There were 105 Ctrl group individuals, with a male-to-female ratio of approximately 1:1, an age range of 47 - 86, and an average age of 68 years. There were no statistical differences in the age and gender compositions among the three groups.

[0042] 2. Methods

[0043] 2.1 Plasma sample collection and pretreatment

[0044] Collect fasting blood in an EDTA anticoagulant tube and let it stand for 30 minutes. Centrifuge at 3000 rpm / min for 5 minutes, take the plasma, and store it in a -80°C refrigerator for later use. Thaw the plasma at room temperature. Take 50 μL of plasma in a 1.5 mL centrifuge tube, add 200 μL of extraction solution (methanol) containing an internal standard (specific concentration see Table 1), vortex for 2 minutes, and then centrifuge using a high-speed centrifuge for 15 minutes (15000 g, 6°C); take 200 μL of the supernatant and vacuum centrifuge it to powder, and store it in a -80°C refrigerator. Before injection, the sample is reconstituted with 60 μL of methanol / water = 1 / 4 (v / v) solution; vortex for 2 minutes, and then centrifuge at 15000 g and 10°C for 15 minutes. Take the supernatant and place it in an injection vial with a liner for ultra-high performance liquid chromatography - mass spectrometry analysis.

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

[0046] Isotope internal standard compound Concentration (μg / mL) D3-Acetylcarnitine 0.40 D3-Palmitoylcarnitine 0.15 D5-Phenylalanine 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 phase conditions: The chromatograph is a Waters ACQUITY ultra-high performance liquid chromatograph. In the positive ion mode of the mass spectrometry, an ACQUITY UPLC BEH C8 (2.1 mm x 50 mm, 1.7 μm) chromatographic column (Waters, Ireland) is used. Mobile phase A is an aqueous solution of 0.1% formic acid, and mobile phase B is an acetonitrile solution of 0.1% formic acid. Elution gradient: 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 phase from 2 min to 8 min, holding for 2 min, linearly changing to 5% B phase in 0.1 min from 10 min to 10.1 min and equilibrating for 1.9 min. The flow rate of the mobile phase is 0.40 mL / min.

[0049] In the negative ion mode of the mass spectrometry, an ACQUITY UPLC HSS T3 (2.1 mm x 50 mm, 1.8 μm) chromatographic column (Waters, Ireland) is used. Mobile phase C is an aqueous solution of 6.5 mM ammonium bicarbonate, and mobile phase D is a methanol / aqueous solution of 6.5 mM ammonium bicarbonate (methanol: water = 95:5, v / v). Elution gradient: 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 in 0.1 min and equilibrating for 1.9 min. In both positive and negative ion modes, the injection chamber temperature is 6°C, the column temperature is 60°C, and the injection volume is 5 μL.

[0050] (2) Mass spectrometry conditions: The mass spectrometer is a tripleTOFTM5600plus (Applied Biosystems, Foster City, CA) system. The parameter settings are as follows: GS1, GS2, and CUR are 50 psi, 50 psi, and 35 psi respectively; the ion source temperature is 500°C; the ion source voltages in positive and negative ion modes are 5500 V and -4500 V respectively.

[0051] 2.3 Protein analysis

[0052] The expression levels of TLR3, AOC1, and DNPH1 in plasma were analyzed using the PEA (Proximity Extension Assay) technique. This technique is a method for identifying and quantifying specific proteins in plasma by using antibody and DNA oligonucleotide labeling. It generates unique-sequence DNA barcodes through DNA hybridization and extension, which are then amplified and quantified by quantitative PCR. Finally, the data are normalized as the quantitative results of the proteins. Briefly, the antibody carrying the designed oligonucleotide sequence is immunologically linked to the target protein. After the two oligonucleotide sequences linked to the protein undergo base complementary pairing, extension occurs under the action of DNA polymerase, and the amplified PCR sequences are detected by high-throughput sequencing.

[0053] 3. Result Analysis

[0054] The quantitative results of the metabolites were obtained according to the above method. Based on 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 / m;

[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 (Normalized Protein eXpression, i.e., NPX value) obtained by logarithmic transformation (Log2) of the counts value of high-throughput sequencing results was used as the relative quantification unit of proteins. Among them, the average NPX values of TLR3, AOC1, and DNPH1 in the three groups are shown in Table 3.

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

[0066] Protein Ctrl (μg / mL) PD-RBD (μg / mL) PD+RBD (μg / 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-hydroxycinnamic acid, 5-hydroxyproline, p-cresol sulfate, p-cresol glucuronide, AOC1, and DNPH1 were significantly increased in PD+RBD patients, while the concentrations of 5-hydroxyindoleacetic acid, heptadecanoic acid, and TLR3 were significantly decreased. Subsequently, by calculating the Youden index, the diagnostic and predictive effects of the above single indicators on the whole were further evaluated. The area under the curve (AUC), sensitivity, and specificity results of a single metabolite or protein predicting the diagnosis of Parkinson's disease with rapid eye movement sleep behavior disorder are shown in Table 4.

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

[0069]

[0070] Table 4 lists the AUC, sensitivity, and specificity of a single metabolite or protein predicting Parkinson's disease with rapid eye movement sleep behavior disorder. The relevant parameters show that the effect of using any of the above indicators alone to distinguish PD+RBD from Ctrl or to distinguish PB+RBD from PD-RBD is not ideal. However, when identifying PD+RBD, the sensitivity and specificity of the above indicators show good complementarity.

[0071] 4. Auxiliary diagnosis

[0072] To improve the diagnostic efficacy, we further established a diagnostic model using the concentration values of the above six metabolites and three proteins in each clinical sample to discover the optimal variable combination. The results showed that when a combined biomarker model was established by combining the above six metabolites and three proteins, the resulting model was the most superior. The parameters of this model and three other combined models, including AUC, sensitivity, and specificity results, are shown in Table 5. Among them, the contents of 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, 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 index analysis of the combined biomarker model

[0074]

[0075] The results showed that when differentiating PD+RBD from Ctrl, the above combined biomarker models had good differentiation effects, and the AUCs were all greater than 0.920. However, when differentiating PD+RBD from PD-RBD, only when a combined biomarker model was established by combining the above six metabolites and three proteins, the resulting model was the most superior, and the AUC could reach above 0.910. Therefore, we finally selected the combination of the above nine indicators as the discriminant model for PD+RBD.

[0076] Based on the above-established logistic regression model, when differentiating PD+RBD from Ctrl, the 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] When differentiating PD+RBD from Ctrl, the 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] Among them, e is the Euler number, that is, the base of the natural logarithm.

[0083] Substituting into the binary logistic regression equation, compared with Ctrl and PD-RBD patients, the obtained variable Pi(PD+RBD) is increased in PD+RBD patients. When the variable Pi(PD+RBD) uses the cut-off value of 0.500, the discriminant effect on PD+RBD is as follows Figure 1-2 shown. When the established combined biomarker model was used to distinguish PD+RBD patients from Ctrl, the AUC value was 0.946, the sensitivity was 82.8%, the specificity was 96.6%, and the discriminant accuracy rates for PD+RBD and Ctrl were both greater than 86% (see Figure 1 ). In addition, when the combined biomarker model was used to distinguish PD+RBD patients from PD-RBD, the area under the curve was 0.917, the sensitivity was 84.5%, the specificity was 89.8%, and the discriminant accuracy rates for PD+RBD and PD-RBD were both greater than 84% (see Figure 2 ). The above results show that the combined biomarker established by us has a very good discriminant effect on 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 validate the logistic regression model established in Example 1. Among them, there were 31 PD+RBD patients, with a male to female ratio of approximately 1:1, an age range of 52 - 81, and an average age of 66 years. There were 31 PD-RBD patients, with a male to female ratio of approximately 1:1, an age range of 55 - 82, and an average age of 68 years. There were 31 Ctrl subjects, with a male to female ratio of approximately 1:1, an age range of 56 - 85, and an average age of 67 years. There were no statistical differences in age and gender composition among the three groups.

[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 showed that when the above combined biomarker model was used to distinguish PD+RBD patients from Ctrl, the AUC value was 0.921, the sensitivity was 86.8%, and the specificity was 83.6%. When the combined biomarker model was used to distinguish PD+RBD patients from PD-RBD, the AUC value was 0.882, the sensitivity was 88.1%, and the specificity was 82.8%. The above results indicate that the combined biomarker model established by the present invention has the potential for clinical diagnosis of PD+RBD.

[0087] The present invention features rapidity, high sensitivity, low cost, and high stability. Meanwhile, the present invention can be applied to assist in the clinical diagnosis of PD+RBD, and has high development and application value. The present invention can form a kit with reagents for detecting 3-hydroxycinnamic acid, 5-hydroxyindoleacetic acid, 5-hydroxyproline, heptadecanoic acid, p-cresol sulfate, p-cresol glucuronide, TLR3, AOC1, and DNPH1. This kit will effectively solve the current problem of clinical diagnosis of Parkinson's disease with rapid eye movement sleep behavior disorder, contribute to establishing a scientific treatment plan earlier, relieve the pain of patients, and has good application prospects.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A set of biomarkers for diagnosing Parkinson's disease with rapid eye movement sleep behavior disorder, characterized in that: The biomarkers include 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 record 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, 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 transformation Log2) were recorded as A, B, C, D, E, F, G, H and I, respectively; 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 ); Wherein, e is the Euler number, and 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 a non-PD+RBD patient.

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

7. The kit according to claim 6, characterized in that The mass spectrometer was in positive ion mode, and the liquid chromatography used an ACQUITY UPLC BEH C8 column, 2.1 mm x 50 mm, 1.7 μm. The mobile phase A was an aqueous solution of 0.1% formic acid, and the mobile phase B was an acetonitrile solution of 0.1% formic acid. The elution gradient was: 5% B from 0 to 0.5 min, linearly changed to 40% B from 0.5 min to 2 min, linearly changed to 100% B phase from 2 min to 8 min, maintained for 2 min, linearly changed to 5% B phase from 10 min to 10.1 min and balanced for 1.9 min, and the mobile phase flow rate was 0.40 mL / min.

8. The kit according to claim 6, characterized in that The mass spectrometer was in negative ion mode, using an ACQUITY UPLCHSS T3 column, 2.1 mm x 50 mm, 1.8 μm, with mobile phase C being an aqueous solution of 6.5 mM ammonium bicarbonate, and mobile phase D being a methanol / water solution of 6.5 mM ammonium bicarbonate in a volume ratio of 95:5, with an elution gradient of 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, and after holding for 2 min, 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; ion source temperature was 500 °C; ion source voltages were 5500 V and -4500 V in positive and negative ion modes respectively.

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