Application of aromatic amino acid decarboxylase as a biomarker in detection products for hepatic encephalopathy

Abstract

The present application discloses the use of aromatic amino acid decarboxylase as a biomarker in a detection product for hepatic encephalopathy. It is confirmed that the abundance of the aromatic amino acid decarboxylase gene encoded by the intestinal flora and the aromatic amino acid decarboxylase product phenethylamine increase in patients with hepatic encephalopathy. Moreover, compared with blood ammonia, phenethylamine can more accurately diagnose hepatic encephalopathy, indicating that it is possible to quickly confirm whether hepatic encephalopathy has occurred and the degree of disease development by detecting the feces and serum of patients, thus meeting the clinical detection needs of hepatic encephalopathy. The present application also confirms that the baseline serum phenethylamine level can effectively predict the incidence of hepatic encephalopathy three months after Tips surgery, providing a detection means for early warning of hepatic encephalopathy.

Description

Technical Field

[0001] The present application relates to the field of biological detection technologies, and particularly to the application of aromatic amino acid decarboxylase as a biomarker in detection products for hepatic encephalopathy. Background Art

[0002] Hepatic encephalopathy (HE) is a severe complication of end-stage liver diseases, the main cause for hospitalization of end-stage liver disease patients, with an extremely high fatality rate and extremely poor short-term prognosis. Timely prediction and diagnosis of hepatic encephalopathy can help with preventive or early medication, which is an effective measure to reduce the hospitalization rate and mortality of liver disease patients.

[0003] Currently, the commonly used neuropsychological scoring scales in clinical practice are complex to operate and highly subjective, unable to meet the requirements of early warning; although blood ammonia detection is widely used in clinical practice, there is no significant correlation between it and the occurrence, severity, and prognosis of hepatic encephalopathy, and it is not the best choice as an early warning biomarker. If new and more accurate early warning biomarkers for hepatic encephalopathy can be discovered, it will help with early warning and reasonable prevention of high-risk patients with hepatic encephalopathy, which is of great value for reducing the hospitalization rate and mortality of cirrhotic patients and has a major clinical need. Summary of the Invention

[0004] The object of the present application is to provide the use of a detection method targeting bacterial aromatic L-amino acid decarboxylase (AADC) and its product phenethylamine as an early warning and diagnostic biomarker for hepatic encephalopathy, and to provide the application of aromatic amino acid decarboxylase as a biomarker in detection products for hepatic encephalopathy.

[0005] To achieve the above technical objectives, the technical solution adopted in the present application is as follows:

[0006] The application of aromatic amino acid decarboxylase as a biomarker in detection products for hepatic encephalopathy.

[0007] Optionally, as the biomarker, the detection items include at least one of the following:

[0008] Detecting the abundance of the gene encoding aromatic amino acid decarboxylase in the test sample;

[0009] Detecting the microbial species producing aromatic amino acid decarboxylase in the test sample and the corresponding abundance;

[0010] Detecting the concentration of the metabolite of aromatic amino acid decarboxylase in the test sample.

[0011] Optionally, the sample is derived from feces and / or serum.

[0012] Specifically, the process of processing the sample derived from feces is as follows:

[0013] Extract genomic DNA from the sample and detect the concentration and purity of the genomic DNA;

[0014] Prepare a DNA library based on the extracted genomic DNA;

[0015] Use the DNA library to quantitatively analyze the abundance of the gene encoding aromatic amino acid decarboxylase;

[0016] Use the DNA library to quantitatively analyze the abundance of the microorganisms producing aromatic amino acid decarboxylase;

[0017] Use the DNA library to identify the species of the microorganisms producing aromatic amino acid decarboxylase.

[0018] Furthermore, compared with the control sample, the abundance of the gene encoding aromatic amino acid decarboxylase in the test sample increases.

[0019] Even further, compared with the control sample, the microorganism with the highest abundance of aromatic amino acid decarboxylase in the test sample is Ruminococcus gnavus .

[0020] More specifically, the process of processing the sample derived from serum is as follows:

[0021] Purify the target substance in the serum sample;

[0022] Use a mass spectrometry-chromatography system to confirm the concentration of the target substance;

[0023] The target substance is a metabolite of aromatic amino acid decarboxylase.

[0024] Specifically, the target substance is phenethylamine.

[0025] Furthermore, compared with the control sample, the concentration of the target substance in the test sample increases.

[0026] Even further, the abundance of the gene encoding aromatic amino acid decarboxylase, the species and corresponding abundance of the microorganisms producing aromatic amino acid decarboxylase in the sample are significantly positively correlated with the concentration of the metabolite of aromatic amino acid decarboxylase.

[0027] Optionally, the concentration difference of the metabolite of aromatic amino acid decarboxylase is used to distinguish between cirrhotic patients with hepatic encephalopathy and those without hepatic encephalopathy.

[0028] Compared with the prior art, the present application has the following advantages:

[0029] This application confirms that the abundance of the AADC gene encoded by the gut microbiota and the AADC product phenethylamine increase in patients with hepatic encephalopathy, and that phenethylamine can diagnose hepatic encephalopathy more accurately than blood ammonia, suggesting that it is possible to quickly confirm whether hepatic encephalopathy has occurred and the degree of disease development by detecting the feces and serum of patients, thus meeting the clinical detection needs of hepatic encephalopathy.

[0030] This application also confirms that the baseline serum phenethylamine level can effectively predict the incidence of hepatic encephalopathy 3 months after TIPS surgery, providing a detection method for early warning of hepatic encephalopathy. Brief Description of the Drawings

[0031] Figure 1 Results of metagenomic analysis of fecal samples using this application.

[0032] Figure 2 Results of metabolomic analysis of serum samples using this application.

[0033] Figure 3 ROC curves of serum monoamines and ammonia using this application.

[0034] Figure 4 Comparison of serum phenethylamine concentrations between patients with hepatic encephalopathy and those without hepatic encephalopathy after TIPS surgery using this application.

[0035] Figure 5 ROC curve for predicting the occurrence of hepatic encephalopathy after surgery using the baseline serum phenethylamine level of this application. Detailed Description of the Invention

[0036] The following further describes this application in detail in conjunction with the drawings and specific embodiments.

[0037] The definitions of relevant technical terms in this application are as follows:

[0038] Hepatic encephalopathy: Hepatic encephalopathy (HE), also known as hepatic coma, is a syndrome of central nervous system dysfunction based on metabolic disorders caused by severe liver disease, and its main clinical manifestations are disorders of consciousness, abnormal behavior, and coma.

[0039] Gene abundance: In metagenomic analysis, the ratio of a specific gene or a specific type of gene to all genes of gut bacteria.

[0040] Monoaminergic neurotransmitter: A neurotransmitter and neuromodulator containing an amino group, connected to an aromatic ring by a double carbon chain (such as -CH2-CH2-), including serotonin, phenethylamine, etc.

[0041] Phenethylamine, with the following molecular formula:

[0042]

[0043] This application first included 122 cases of horizontally comparable samples: cirrhosis without hepatic encephalopathy, n = 41; cirrhosis with hepatic encephalopathy, n = 37; healthy controls, n = 44. The specific inclusion and exclusion criteria are as follows. The inclusion criteria for cirrhosis are as follows: 1) Patients diagnosed with cirrhosis based on clinicopathological features - including liver history, endoscopic examination, or radiological examination results (the clinical diagnosis of cirrhosis was determined by two independent hepatologists in a blinded manner; both experts must agree on the clinical diagnosis of cirrhosis before inclusion); 2) Patients with at least 6 months of clinical evidence of chronic liver disease, and the etiologies can include - alcoholic liver disease (drinking history: more than 2 ounces of ethanol per day for men, or 1 ounce of ethanol per day for women (for more than 10 years) and no other causes of liver disease were found), non-alcoholic fatty liver, viral hepatitis B or C (detected by measuring HCV RNA or HBV DNA), or autoimmune liver disease (based on international autoimmune scoring criteria). Hepatic encephalopathy was carefully evaluated by two independent hepatologists, and the specific criteria were: excluding sudden changes in mental status caused by other reasons. The inclusion criteria for healthy subjects are as follows: 1) Subjects from a physical examination center, with age and gender matched to those of cirrhosis patients; 2) No clinically diagnosed chronic diseases. The exclusion criteria include: 1) Receiving antibiotic, probiotic, or proton pump inhibitor treatment within 1 month before sample collection; 2) Undergoing gastrointestinal surgery or colonoscopy within 6 months before sample collection; 3) Existing infections.

[0044] Fecal (cirrhosis without hepatic encephalopathy, n = 26; cirrhosis with hepatic encephalopathy, n = 21; healthy controls, n = 10) and serum (cirrhosis without hepatic encephalopathy, n = 41; cirrhosis with hepatic encephalopathy, n = 37; healthy controls, n = 44) specimens of the above subjects were collected and subjected to metagenomic and metabolomic assays respectively.

[0045] The methods for metagenomic detection and analysis of fecal samples are as follows:

[0046] 1) Extraction of genomic DNA, and then detection of DNA integrity and purity on 1% agarose gel. At the same time, Qubit 3.0 (Thermo Fisher Scientific, Waltham, USA) and Nanodrop One (Thermo Fisher Scientific, Waltham, USA) were used to measure DNA concentration and purity.

[0047] 2) DNA library preparation and sequencing: The sequencing library was generated using the ALFA-SEQ DNA Library Prep Kit according to the instructions, and index codes were added. The library quality was evaluated on a Qubit 4.0 fluorometer (Life Technologies, Grand Island, NY) and a Qsep400 high-throughput nucleic acid and protein analysis system (Houze Biological Technology Co, Hangzhou, China). Finally, the library was sequenced on an Illumina NovaSeq 6000 platform to generate 150 bp paired-end reads.

[0048] 3) Data quality control and analysis: Kneaddata was used to remove low-quality bases, remove host DNA (human DNA), and remove qPCR duplicates; FastQC was used to view the sequence quality; ShortBred (version 0.9.5) was used to quantify the AADC gene abundance: First, the AADC sequences were clustered with 95% similarity, and then the UniRef90 database was used to identify short marker sequences. Finally, these marker sequences were quantified in metagenomic samples, and the quantitative data were normalized by RPKM (Reads Per Kilobase per Million mapped reads). At the same time, MetaPhlAn2 (version 2.7.7) was used to quantify the species abundance.

[0049] Furthermore, targeted metabolomics analysis was performed on serum samples, and the target substance was phenethylamine, a metabolite of aromatic amino acid decarboxylase. The sample processing and detection methods are as follows: The serum sample was diluted in methanol (1:4) and vortexed for 10 minutes. Then the sample was centrifuged to collect the supernatant (14,000 rpm, 10 minutes, 4°C) and filtered through a 0.22 μm pore size filter. Before measuring the monoamine level by HPLC-MS / MS, the mobile phase was placed at -80°C overnight. The above steps were used to purify the target substance. Next, the target substance was detected using a mass spectrometry-chromatography system. Specifically, 100 μl of the sample was separated at 40 ºC on a Waters Acquity UPLC HSS T3 chromatographic column (2.1 × 100 mm, 1.8 μm) on a Prelude SPLC system. The following mobile phases were used: (A) 1 mM ammonium formate and 0.1% formic acid aqueous solution, (B) 0.1% formic acid acetonitrile solution, with a gradient of 0 minutes (5% B), 1 minute (85% B), 5 minutes (95% B), 5.5 minutes (95% B), 6 minutes (5% B), and a flow rate of 0.3 ml / min. MS analysis was performed using the multiple reaction monitoring scan mode (TSQ Quantiva triple quadrupole mass spectrometer). The H-ESI source in positive mode was used. The parameters are as follows: ion pair (122.152 m / z, 77.04 m / z) 28.55 V, ion pair (138.152 m / z, 77.04 m / z) 27.494 V, ion pair 10.253 V (161.152 m / z, 144.11 m / z), 10 V for ion pair (177.152 m / z, 160.054 m / z). Thermo Xcalibur software was used to visualize peak detection. The peaks and corresponding concentrations of phenethylamine in each serum sample were confirmed.

[0050] The results in Figure 1 showed that the abundances of the AADC gene and bacteria expressing AADC increased in patients with hepatic encephalopathy and were correlated with serum phenylethylamine levels. Among them, (A) α-diversity of fecal microbiota in the control group (n = 10), liver cirrhosis (n = 26), and patients with hepatic encephalopathy (n = 21). α-Diversity was measured by the Shannon index. (B) β-diversity (Bray Curtis distance) in the control group (n = 10), liver cirrhosis (n = 26), and patients with hepatic encephalopathy (n = 21), and group differences were tested by pairwise PERMANOVA. (C) LEfSe linear discriminant analysis plot of the gut microbiota in control subjects (n = 10), compensated liver cirrhosis patients (n = 26), and patients with hepatic encephalopathy (n = 21). (D-E) Gene abundances of AADC (C) or total AADC (D) from Ruminococcus gnavus the source of Ruminococcus (C) or total AADC (D) in healthy controls (n = 10), compensated liver cirrhosis patients (n = 26), or patients with hepatic encephalopathy (n = 21). (F) Clinical and microbiota factors associated with serum phenylethylamine levels (only the top 5 species are shown). This association was analyzed using Spearman correlation analysis. * p <0.05; ** p <0.01.

[0051] Metagenomic analysis results found that the gut microbiota of healthy subjects, non-hepatic encephalopathy liver cirrhosis, and patients with hepatic encephalopathy were significantly different in terms of α-diversity and β-diversity ( Figure 1 A-B); the species Ruminococcus gnavus (Ruminococcus gnavus) that mainly encodes the AADC gene was significantly enriched in patients with hepatic encephalopathy ( Figure 1 C); the AADC gene from the microbiota and Ruminococcus gnavus the AADC gene from the source of Ruminococcus gnavus gradually increased in healthy subjects, non-hepatic encephalopathy liver cirrhosis, and patients with hepatic encephalopathy ( Figure 1 D-E). Importantly, Ruminococcus gnavus species abundance and AADC gene abundance were significantly positively correlated with serum phenylethylamine ( Figure 1 F), suggesting that the serum phenylethylamine concentration can reflect the occurrence and progression of hepatic encephalopathy.

[0052] The results in Figures 2 and 3 show that phenylethylamine in the serum of patients with hepatic encephalopathy increases. Among them, (A - F) Quantification of phenylethylamine (A), tryptamine (B), tyramine (C), 5 - hydroxytryptamine (D), octopamine (E) and ammonia (F) in the serum of healthy control group (n = 44), patients with liver cirrhosis (n = 37) or patients with hepatic encephalopathy (n = 41). ( Figure 3 , G) The accuracy of ROC curves of serum monoamines and ammonia in differentiating hepatic encephalopathy and liver cirrhosis. ** p <0.01, *** p <0.001.

[0053] Table 1 Demographic and clinical parameters of patients with liver disease

[0054] (Demographic and clinical parameters of patients with liver disease)

[0055]

[0056] Metabolomics result analysis found that compared with other monoamines, the serum phenylethylamine level in HE patients was significantly higher than that in the healthy control group and cirrhotic patients without hepatic encephalopathy (Figure 2A - F, Table 1). Although the blood ammonia level in patients with hepatic encephalopathy was also elevated, receiver operating characteristic (ROC) curve analysis showed that phenylethylamine was superior to blood ammonia in differentiating hepatic encephalopathy and cirrhotic patients without hepatic encephalopathy (AUC: 0.681 vs 0.743) ( Figure 3 , Table 1).

[0057] To further verify the predictive ability of serum phenylethylamine for the risk of hepatic encephalopathy, this application also conducted a longitudinal comparison, including 84 cirrhotic patients who underwent transjugular intrahepatic portosystemic shunt (TIPS) surgery (hepatic encephalopathy is the most common complication after TIPS). Detailed clinical information and peripheral blood specimens were collected before the surgery. The patients were followed up for 3 months after the surgery, and the occurrence of hepatic encephalopathy was observed and recorded. Using the above metabolomics detection method, the serum phenylethylamine concentration was detected. The results showed that within 3 months after the surgery, a total of 27 patients developed hepatic encephalopathy. The serum phenylethylamine concentration at baseline in the patients who developed hepatic encephalopathy was significantly higher than that in the patients who did not develop hepatic encephalopathy ( Figure 4 ); and using the serum phenylethylamine level at baseline to diagnose hepatic encephalopathy, the area under the ROC curve could reach 0.70 ( Figure 5 ), which was significantly better than other clinical indicators.

[0058] In summary, the application of the aromatic amino acid decarboxylase of the present application as a biomarker in the detection product for hepatic encephalopathy has confirmed that the abundance of the AADC gene encoded by the gut microbiota and the AADC product phenethylamine increase in patients with hepatic encephalopathy, and that phenethylamine can diagnose hepatic encephalopathy more accurately than blood ammonia. This indicates that it is possible to quickly confirm whether hepatic encephalopathy has occurred and the degree of disease development by detecting the feces and serum of patients, thus meeting the clinical detection requirements for hepatic encephalopathy. The present application has also confirmed that the baseline serum phenethylamine level can effectively predict the incidence of hepatic encephalopathy three months after Tips surgery, providing a detection method for early warning of hepatic encephalopathy.

[0059] The above embodiments are preferred embodiments of the present application, but are not limited thereto. Any other changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present application shall be equivalent replacement methods and are all included in the protection scope of the present application.

Claims

1. The use of phenylethylamine as a marker in the preparation of a detection product for hepatic encephalopathy, characterized in that: The test samples were derived from serum.

2. The use according to claim 1, characterized in that The sample processing process derived from serum is as follows: Purify the target substances in serum samples; The concentration of phenylethylamine was confirmed by mass spectrometry-chromatography system.

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