An intestinal microorganism associated with Huntington's disease and its application

Abstract

The present disclosure relates to an intestinal microorganism related to Huntington's disease and its application, wherein the application includes: the use of a product for detecting intestinal microorganisms in preparing a reagent or kit for assisting in diagnosing the occurrence of Huntington's disease in patients; the use of intestinal microorganisms in preparing a drug or kit for treating Huntington's disease; and the use of a product for detecting intestinal microorganisms in preparing a reagent or kit for evaluating the therapeutic effect of Huntington's disease. The present invention screens out intestinal microorganisms related to Huntington's disease, especially intestinal microorganisms related to the treatment of Huntington's disease, thereby opening up a new way to treat Huntington's disease.

Description

Technical Field

[0001] The invention belongs to the field of biotechnology, and specifically relates to an intestinal microorganism associated with Huntington's disease and an application thereof. Background Art

[0002] Huntington's disease (HD) is a monogenic dominant progressive neurodegenerative disease with complex and variable clinical symptoms. The patient's condition progressively worsens and usually dies 15 to 20 years after onset. The disease has an insidious onset and progresses slowly. The main features of the disease are chorea-like movements accompanied by progressive cognitive and mental dysfunction and eventually dementia. The cause is the incorrect expression of the polynucleotide repeat sequence on the Huntington gene.

[0003] HD is caused by a CAG trinucleotide repeat expansion in exon 1 of the huntingtin (HTT) gene on chromosome 4, affecting different molecular pathways, ultimately leading to neurological dysfunction and degeneration. The HTT gene is widely expressed in the brain and peripheral tissues such as skeletal muscle and intestine. Mutant huntingtin (mHTT) expressed in the gastrointestinal (GI) tract leads to gastrointestinal dysfunction, including impaired intestinal motility, diarrhea, and food absorption disorders. In HD patients and several HD transgenic mouse models, malabsorption is associated with the amount of weight loss that is a hallmark of HD. A recent study suggests that intestinal dysbiosis may play a role in regulating the age of onset and progression of HD symptoms. In addition, mHTT is expressed in peripheral myeloid cells, including monocytes and macrophages. Monocytes in the blood of HD patients produce higher levels of cytokines in vitro when stimulated.

[0004] The gut microbiota may play a key role in the bidirectional gut-brain axis that influences brain activity under both physiological and pathological conditions. An increasing number of studies have shown that the gut microbiota exhibits physiological functions related to neurodevelopment, brain function, and behavior. Maladaptive changes in the composition of the gut microbiota, known as gut dysbiosis, have been associated with many gastrointestinal and metabolic diseases, including inflammatory bowel disease (IBD), obesity, and diabetes. In addition, gut dysbiosis has been associated with various neurological and psychiatric diseases, such as autism spectrum disorder (ASD), major depression, amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), and Alzheimer's disease (AD). In addition, R6 / 1 transgenic HD mice exhibit weight loss and gut dysbiosis, the latter of which has been confirmed by 16S ribosomal RNA (rRNA) gene sequencing. Notably, changes in circulating metabolites associated with the gut microbiota in HD patients and transgenic animals suggest that changes in the gut microbiota may occur before the onset of HD.

[0005] However, no study has reported the composition of the intestinal flora and the associated host cytokine responses in HD patients. Finding an effective and inexpensive drug to treat Huntington's disease is an urgent problem to be solved. Summary of the invention

[0006] In order to address the deficiencies of the prior art, the purpose of the present invention is to screen out intestinal microorganisms associated with Huntington's disease, especially intestinal microorganisms associated with the treatment of Huntington's disease, thereby opening up a new way to treat Huntington's disease.

[0007] Specifically, the present invention proposes the following technical solutions:

[0008] In one aspect, the present invention provides the use of a product for detecting intestinal microorganisms in the preparation of a reagent or a kit for assisting in the diagnosis of the occurrence of Huntington's disease in patients or evaluating the therapeutic effect of Huntington's disease.

[0009] In one aspect, the present invention provides use of intestinal microorganisms in preparing a medicament or a kit for treating Huntington's disease.

[0010] The intestinal microorganisms used in the disclosed method can restore the intestinal microecology, restore the immune response between the intestinal flora and the body, and alleviate the patient's total functional status (TFC). The oral treatment method is simple, non-invasive, and basically does not cause additional harm to the patient's body. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 Differences in fecal microbiota between HD patients and healthy controls were detected by LEfSe analysis. (A) LEfSe analysis showed significant differences in bacteria in the fecal microbiota between HD patients and healthy controls. Species with significant differences in abundance between the two groups with LDA scores (log10) > 2 and p < 0.05 are shown. (B) Cladogram of the taxonomic structure and relative abundance of the identified taxa. The size of each point is proportional to the relative abundance of each taxon (p, phylum; c, class; o, order; f, family; g, genus).

[0012] Figure 2The matrix of HD patients' basic information, clinical information, plasma biomarkers and fecal flora information is shown. SPSS dimension deduction-factor analysis is used for statistical analysis, and the comprehensive factor number is analyzed by Spearman correlation. Among them, the plasma cell inflammatory factor matrix includes INF-γ = interferon-γ; IL-1β = interleukin-1β; IL-2 = interleukin-2; IL-4 = interleukin-4; IL-6 = interleukin-6; IL-8 = interleukin-8; IL-10 = interleukin-10; IL-12p70 = interleukin-12p70, IL-13 = interleukin-13; TNF-α = tumor necrosis factor-α.

[0013] Figure 3 This is a flow chart for the processing of donor fecal bacteria. DETAILED DESCRIPTION

[0014] Unless otherwise defined, the meaning of all scientific and technical terms used herein is the same as that generally understood by those of ordinary skill in the art to which the present invention belongs. Although any method and material similar or equivalent to the method and material described herein can be used in the practice or testing of the present invention, preferred methods and materials are described. For purposes of the present invention, the following terms are defined as follows.

[0015] I. Definitions

[0016] As used in the present disclosure, the term "Unified Huntington's Disease Rating Scale (UHDRS)" consists of four subscales, including motor (0-124), MMSE (0-30), mental (0-176) and functional domain (1-13). The scores of the four subscales are added together to calculate the total score. The higher the motor and psychiatric scores, the worse the prognosis, but the higher the MMSE scores and functional scores, the better the prognosis. The motor section of UHDRS (UHDRS-M) refers to the assessment of the motor symptoms of Huntington's disease patients, and the higher the score, the more severe the motor symptoms.

[0017] As used in this disclosure, the term “Functional Assessment Scale (FAS)” is a more detailed functional ability assessment test consisting of 25 questions about specific functional abilities. The FAS examines occupation-related tasks (e.g., customary work, volunteer work), finances (e.g., cash transactions, financial management), activities of daily living (e.g., driving, hygiene), housework (e.g., home maintenance, laundry), care level (e.g., home or supervised care), and physical abilities (e.g., walking, getting out of bed, falls). FAS scores range from 0 to 25, with higher scores indicating better function (33).

[0018] As used in this disclosure, the term "Total Functional Capacity (TFC)" is a broad functional capacity assessment consisting of five total items, including work ability, financial management, housework ability, daily living ability, and required care level. The score range for each item is from 0 to 2 or 3. The total score of TFC is 0-13 points, and the higher the score, the better the function.

[0019] As used in this disclosure, the term "Category Fluency Test (CFT)" refers to a test in which a subject is asked to name as many animals as possible within one minute.

[0020] As used in this disclosure, the term "Symbol Digit Modalities Test (SDMT)" refers to a test in which a subject makes as many symbol-digit associations as possible within 90 seconds.

[0021] As used in this disclosure, the term "Stroop Interference Test (SIT)" is a component of the Stroop test, which is a measure of the patient's executive function, including cognitive flexibility and the ability to resist interference. The score of the test is the correct number of colors read in 45 seconds. The higher the score, the better the patient's executive function.

[0022] As used in this disclosure, the term "Mini-Mental State Examination (MMSE)" is a measure of a patient's general cognitive function.

[0023] As used in this disclosure, the term "Beck Depression Inventory II (Beck Depression Inventory II, BDI-II)" is used to assess the intensity of depression in clinically depressed or non-depressed patients. Each item is scored on a 4-point scale, from 0 to 3, with higher scores indicating more severe depression.

[0024] As used in this disclosure, the term "fecal microbiota transplantation" (FMT) refers to transplanting the flora of normal people into the gastrointestinal tract of patients to rebuild new intestinal flora and achieve the treatment of intestinal and extra-intestinal diseases. It is also called Fecal transplantation, Fecal bacteriotherapy, Feacalmicrobiota transplanation and Intestinal microbiota transplantation by a few people, which can be translated as "fecal transplantation", "fecal microbiota therapy", "intestinal microbiota transplantation" or "intestinal microecological transplantation" respectively.

[0025] Fecal microbiota transplantation:

[0026] 1. Fresh fecal enema: Freshly prepared fecal bacteria from the donor, after the recipient has washed the intestine, the fecal bacteria are evenly sprayed onto the intestinal wall using a colonoscope. Fecal transplantation is performed once, and the evaluation period is: 1 day, 3 days, 7 days, 1 month, and 2 months after a fecal transplant.

[0027] 2. Oral therapy of "Enterobacterial Capsules":

[0028] 2.1 Preparation of "Enterobacterial Capsules": Weigh 100g of normal human feces, add 500mL of physiological saline, and stir with a stirrer. Pour the stirred liquid into 0.4mm, 0.2mm, and 0.1mm sieves and filter layer by layer. The filtered liquid is divided into centrifuge bottles and centrifuged (3000r / min, 15min). Prepare 6% trehalose, pour out the supernatant after centrifugation, and then pour the prepared trehalose into the centrifuge bottle and stir with a magnetic stirrer. Finally, pour the liquid into a centrifuge tube, seal it, and freeze it at -80℃. After 2h, take out the frozen bacterial liquid from the -80℃ refrigerator and put it into a vacuum freeze dryer for freeze drying. Finally, put the freeze-dried powder into capsules and store the capsules in a -80℃ refrigerator.

[0029] 2.2 How to take "Enterobacterial Capsules" and concomitant medication: The entire FMT course is 3 weeks. In the first 3 weeks, FMT is performed once a week, that is, 16 "Enterobacterial Capsules" are taken with warm water on an empty stomach every morning (equivalent to the amount of bacteria in 50g of stool), and meals are required to be taken at intervals of more than 1 hour, for a total of 3 times. Evaluation period: 1-8 weeks after enrollment, follow-up is conducted once after FMT every week, for a total of 8 times.

[0030] The therapeutic intestinal microorganisms described in the present disclosure, together with one or more excipients such as adjuvants, carriers or diluents, can be placed in the form of pharmaceutical compositions, unit dosages or dosage forms. The pharmaceutical compositions can be solid dosage forms (such as powders, granules, pellets, coated or uncoated tablets or filled capsules) or liquid dosage forms (such as solutions, suspensions, emulsions or capsules filled therein) or semisolid dosage forms (such as gels, creams and ointments). The dissolution and release characteristics of one or more active ingredients of the pharmaceutical dosage form can vary in the range of seconds to months.

[0031] The "medicament" or "pharmaceutical composition" is designed for use in animals and humans and can be administered via all routes of administration. Preferred routes of administration are oral, pulmonary, nasal, rectal, parenteral.

[0032] The medicaments or pharmaceutical compositions of the present disclosure can be administered orally, topically, parenterally or mucosally (e.g., buccally, by inhalation or rectally) in dosage unit formulations containing conventional non-toxic pharmaceutically acceptable carriers. It is generally desirable to use the oral route. The active agent can be administered orally in the form of capsules, tablets, etc. (see Remington: The Science and Practice of Pharmacy, 20th Edition).

[0033] For oral administration in the form of tablets or capsules, the active drug component can be mixed with non-toxic, pharmaceutically acceptable excipients such as binders (e.g., pregelatinized corn starch, polyvinyl pyrrolidone or hydroxypropyl methylcellulose); fillers (e.g., lactose, sucrose, glucose, mannitol, sorbitol and other reducing and non-reducing sugars, microcrystalline cellulose, calcium sulfate or dibasic calcium phosphate); lubricants (e.g., magnesium stearate, talc or silica, stearic acid, sodium stearyl fumarate, glyceryl behenate, calcium stearate, etc.); disintegrants (e.g., potato starch or sodium starch glycolate); or wetting agents (e.g., sodium lauryl sulfate), coloring and flavoring agents, gelatin, sweeteners, natural and synthetic gums (such as acacia, tragacanth or alginates), buffer salts, carboxymethylcellulose, polyethylene glycol, waxes, and the like. For oral administration in liquid form, the drug component can be combined with a non-toxic, pharmaceutically acceptable inert carrier (e.g., ethanol, glycerol, water), an anti-settling agent (e.g., sorbitol syrup, cellulose derivatives or hydrogenated edible fats), an emulsifier (e.g., lecithin or gum arabic), a non-aqueous carrier (e.g., almond oil, oily esters, ethanol or fractionated vegetable oils), a preservative (e.g., methyl or propyl p-hydroxybenzoate or sorbic acid), etc. Stabilizers such as antioxidants (BHA, BHT, propyl citric acid, sodium ascorbate, citric acid) can also be added to stabilize the dosage form.

[0034] The medicaments or pharmaceutical compositions of the present disclosure may also be formulated for rectal administration, for example, as suppositories or retention enemas (eg, containing conventional suppository bases such as cocoa butter or other glycerides).

[0035] The present disclosure provides a therapy for treating Huntington's disease using a drug made from intestinal microorganisms as described in the present disclosure in combination with other drugs. The term "combination therapy" as used in the present disclosure includes administering these agents (e.g., drugs made from intestinal microorganisms described in the present disclosure and other drugs) in a sequential manner, i.e., wherein each therapeutic agent is administered at a different time, and administering these therapeutic agents, or at least two agents, substantially simultaneously. The order of each agent, or substantially simultaneous administration, can be affected by any appropriate route, including, but not limited to, oral routes. The agents can be administered by the same route or by different routes.

[0036] The terms "subject", "individual" and "patient" are used interchangeably in this disclosure and refer to a mammal being evaluated for treatment and / or being treated. The subject can be a human, but also includes other mammals, particularly those that can be used as laboratory models of human disease, e.g., mice, rats, rabbits, dogs, etc.

[0037] As used in the present disclosure, "effective amount" refers to the amount of each active agent (e.g., a drug made by the intestinal microorganisms of the present disclosure) required to impart a therapeutic effect to an individual, whether administered alone or in combination with one or more other active agents. In some embodiments, the therapeutic effect is inhibition of cancer cell growth and / or reduction of tumor burden. In some embodiments, the amount of the drug made by the intestinal microorganisms of the present disclosure is effective for treating Huntington's disease.

[0038] As used in this disclosure, the term "treatment" refers to the application or administration of a composition comprising one or more active agents to an individual suffering from a target disease or condition, symptoms of a disease / condition, or a predisposition to the disease / condition, with the purpose of curing, treating, alleviating, alleviating, altering, remedying, improving, enhancing, or affecting the disease, disease symptoms, or predisposition to the disease or condition.

[0039] Alleviating the target disease / disorder includes delaying the development or progression of the disease, or reducing the severity of the disease. Alleviating disease symptoms does not necessarily require curing the disease. As used therein, "delaying" the development of the target disease or disorder means delaying, preventing, slowing, hindering, stabilizing, and / or delaying the progression of the disease. Such a delay can be a different length of time, depending on the history of the disease and / or the individual being treated. A method of "delaying" or alleviating disease development, or delaying the onset of a disease, is a method for reducing the likelihood of developing one or more disease symptoms within a given time frame, and / or reducing the degree of symptoms within a given time frame, compared with those who do not use the method. This comparison is usually based on clinical studies, using multiple individuals sufficient to give statistically significant results.

[0040] "Development" or "progression" of a disease refers to the initial manifestation of the disease and / or the subsequent progression. The development of a disease can be detected and assessed using standard clinical techniques well known in the art. However, development also refers to progression that may not be detected. For purposes of the present invention, development or progression refers to the biological course of the symptom. "Development" includes occurrence, recurrence, and onset. As used in this disclosure, "onset" or "occurrence" of a target disease or condition includes initial onset and / or recurrence.

[0041] Conventional methods known to those of ordinary skill in the medical field can be used to administer the pharmaceutical composition to an individual depending on the type of disease to be treated or the site of the disease. The composition can also be administered by other conventional routes, for example, orally, topically, rectally, or via implanted reservoirs, oral fecal capsules, direct spraying under gastroscopy, nasogastric or nasointestinal tube infusion, colonoscopy spraying, infusion after endoscopic intestinal catheterization, etc.

[0042] Whether by oral, rectal or even topical routes in some cases, the intestinal microorganisms described in the present disclosure can be prepared or administered with one or more pharmaceutically acceptable excipients, carriers or diluents, particularly and preferably in the form of their pharmaceutical compositions, in an effective amount to a subject in need thereof, such as a living animal (including a human body), for the treatment, alleviation or improvement, relief or elimination of indications or conditions to which it is sensitive or indications or conditions described elsewhere in this application.

[0043] II. Specific implementation methods

[0044] The present disclosure is further explained below with reference to examples. The description of specific exemplary embodiments of the present disclosure is for the purpose of illustration and demonstration. These descriptions are not intended to limit the present disclosure to the precise form disclosed, and it is clear that many changes and variations can be made according to the teachings of this application specification. The purpose of selecting and describing exemplary embodiments is to explain the specific principles of the present disclosure and its practical application, so that those skilled in the art can realize and utilize various different exemplary embodiments of the present disclosure and various different selections and changes.

[0045] One object of the present disclosure is to provide a use of a product for detecting intestinal microorganisms in the preparation of a reagent or a kit for assisting in the diagnosis of the occurrence of Huntington's disease in patients, wherein the patients carry a mutant Htt gene.

[0046] In a preferred embodiment, the intestinal microorganisms include Dialister bacteria.

[0047] In a preferred embodiment, when the relative abundance of Bacteroides bacteria is greater than or equal to 0.016, the patient suffers from Huntington's disease.

[0048] In a preferred embodiment, the intestinal microorganisms further include Bifidobacterium bacteria.

[0049] In a preferred embodiment, the intestinal microorganisms further include Actinomyces bacteria.

[0050] In a preferred embodiment, the intestinal microorganisms further include bacteria of the genus Intestinimonas.

[0051] In a preferred embodiment, the auxiliary diagnosis stage is to use Dialister and Bifidobacterium to jointly assist in the diagnosis of Huntington's disease, and the steps are as follows:

[0052] Step 1: Calculate Logit(P) according to the following formula (1):

[0053] Logit(P)=-0.813+69.211*Bifidobacterium relative abundance+22.667*Dialister relative abundance(1)

[0054] Step 2: Calculate the predicted value P of each subject suffering from Huntington's disease according to the following formula (2):

[0055]

[0056] If the predicted value of a stool sample is P ≥ 0.479859, it is Huntington's disease.

[0057] In a preferred embodiment, the auxiliary diagnosis stage is to use Dialister + Bifidobacterium + Actinomyces + Intestinimonas to jointly assist in the diagnosis of Huntington's disease, and the steps are as follows:

[0058] Step 1: Calculate Logit(P) according to the following formula (3):

[0059] Logit(P)=-2.937+48.077*Bifidobacterium relative abundance+29.557*Dialister relative abundance+7114.032*Actinnomyces relative abundance+118687.850*Intestinimonas relative abundance(3)

[0060] Then, the predicted value of each subject suffering from HD was calculated according to the following formula (2):

[0061]

[0062] If the predicted value of a stool sample is P ≥ 0.3819259, the patient suffers from Huntington's disease and the patient has not yet developed the disease or has developed the disease for less than 1 year.

[0063] An object of the present disclosure is also to provide use of intestinal microorganisms in preparing a drug or a kit for treating Huntington's disease.

[0064] In a preferred embodiment, the treatment is treatment using fecal microbiota transplantation.

[0065] In a preferred embodiment, the treatment further comprises treatment with one or more other drugs for treating Huntington's disease.

[0066] In a preferred embodiment, the other drugs for treating Huntington's disease are selected from deuterated tetrafenazine, tetrafenazine, sulpiride, haloperidol, sertraline, citalopram and the like.

[0067] In a preferred embodiment, the intestinal microorganisms used for fecal microbiota transplantation are in the form of enema preparations or oral preparations, preferably one or more of suspensions, capsules, lyophilized powders, tablets, and solutions.

[0068] In a preferred embodiment, the intestinal microorganism and the other drug for treating Huntington's disease can be used simultaneously or at different times.

[0069] An object of the present disclosure is also to provide use of a product for detecting intestinal microorganisms in preparing a reagent or a kit for evaluating the therapeutic effect of Huntington's disease.

[0070] In a preferred embodiment, the treatment is treatment using fecal microbiota transplantation.

[0071] In a preferred embodiment, the treatment is oral treatment after probiotic transplantation or capsule preparation; preferably, the probiotic is selected from Intestinimonas and / or Actinomyces.

[0072] In a preferred embodiment, the evaluation indicators include (1) whether clinical indicators are improved and (2) whether the relative abundance of harmful microorganisms in the Huntington's disease intestine is reduced compared with before treatment.

[0073] In a preferred embodiment, the clinical indicator is selected from one or more of BMI, UHDRS-M, FAS, TFC, SDMT, CFT, STROOP, BDI-II, MMSE, and PSQI.

[0074] In a preferred embodiment, the harmful microorganisms are bacteria of the genus Lactobacillus and / or Lactococcus.

[0075] The present disclosure also analyzed the relationship between fecal microbiota and clinical characteristics of Huntington's disease patients, and found that the relative abundance of Intestinimonas and Actinomyces was positively correlated with TFC and MMSE scores, respectively; while the abundance of Lactobacillus was negatively correlated with MMSE scores; the relative abundance of Lactococcus was negatively correlated with the movement and overall function of HD, etc.

[0076] After treatment, the patients were evaluated, and the clinical evaluation indicators were selected from one or more of BMI, UHDRS-M, FAS, TFC, SDMT, CFT, STROOP, BDI-II, MMSE, and PSQI.

[0077] After treatment, the patient's clinical improvement indicators are selected from one or more of BMI, UHDRS-M, FAS, TFC, and MMSE.

[0078] In a diagnostic embodiment, a stool sample has a predictive value (P) ≥ 0.479859 for diagnosis of HD, and the test has an AUC = 0.719, a sensitivity of 60.6%, and a specificity of 81.8%.

[0079] In a specific embodiment of the diagnosis, when the predicted value P of a stool sample is ≥ 0.3819259, it can be judged as HD-0, and the AUC of the test is 0.806, the sensitivity is 70.0%, and the specificity is 93%. If the Dialister genus is used alone for evaluation, the relative abundance of Dialister genus ≥ 0.016 is HD-0, and the AUC of the test is 0.735, the sensitivity is 60%, and the specificity is 78.8%.

[0080] The method of the present invention can make the diagnosis of Huntington's disease more convenient and easy, so that patients can know the disease risk in the early stage of the disease, especially for large-scale screening of Huntington's disease and provide a simple and effective auxiliary means for drug screening, efficacy evaluation and targeted treatment.

[0081] Example

[0082] Example 1: Screening of intestinal microorganisms associated with Huntington's disease

[0083] 1. Research Objects and Methods

[0084] 1. Subject population

[0085] 1.1 Early stage recruitment

[0086] This study was approved by the Ethics Committee of Beijing Tiantan Hospital, Capital Medical University. From May to October 2019, 33 HD patients and 33 healthy controls were recruited at the National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, with full informed consent.

[0087] 1.1.1 Inclusion criteria

[0088] The diagnosis of HD was made based on a confirmed family history, positive genetic testing, and movement disorders confirmed by the diagnostic confidence score of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score. Patients with a confirmed diagnosis of HD were included in this study.

[0089] 1.1.2 Exclusion criteria

[0090] (1) Combination with other serious chronic diseases, such as diabetes, heart failure, cirrhosis, malignant tumors, hematological / autoimmune diseases, etc.;

[0091] (2) Suffering from other movement disorders, such as Wilson's disease and chorea acanthocytosis;

[0092] (3) Those who have taken antibiotics within the past month;

[0093] (4) Those who have taken prebiotics or probiotics within the past month;

[0094] (5) Subjects with irritable bowel syndrome (IBS) affected by intestinal microbiota as determined by the Rome III criteria.

[0095] 2. Clinical data collection

[0096] 2.1 Clinical data collection

[0097] The age, gender, and education level of the subjects were recorded. The weight and height of each subject were measured. The clinical characteristics collected from HD patients included disease duration, CAG repeat number, motor section of the Unified Huntington's Disease Rating Scale (UHDRS-M), functional assessment (FAS), total functional capacity (TFC), category fluency test (CFT), symbol digit modalities test (SDMT), Stroop interference test (SIT), Mini-Mental State Examination (MMSE), and Beck Depression Inventory II (BDI-II). The clinical characteristics collected in the control group included categorization fluency test (CFT), digit symbol transformation test (SDMT), Stroop interference test (SIT), mini-mental state examination (MMSE), Beck Depression Inventory-II (BDI-II), and Pittsburgh sleep quality index (PSQI).

[0098] 2.2 Collection of peripheral blood

[0099] Before the above-mentioned scale assessment, fasting blood was collected from the subjects to detect cytokines in the blood, including IFN-γ, IL-10, IL-12p70, IL-13, IL-1β, IL-2, IL-4, IL-6, IL-8 and TNF-α.

[0100] 3. Intestinal flora detection

[0101] 3.1 Collection of stool specimens

[0102] Prepare a stool tube (Faeces Tube, LOT10381 l 1300) containing fecal preservation solution and give it to the subject. The subject will collect fecal specimens at home. Before collecting fecal specimens, empty your bladder first, put on a mask and gloves, prepare a disposable bedpan covered with a clean plastic bag, defecate into it, pick up a spoonful of soybean-sized feces (about 1g) inside the feces, and place the spoon vertically in the tube to ensure that the fecal preservation solution does not cover the fecal specimen. Collect two tubes in the same way. After taking, mark the subject information (name, sample number, sampling time), and place it vertically at room temperature (15-30℃) for at least 1 hour. And freeze in a -80℃ low-temperature refrigerator within 1 week.

[0103] 3.2 Fecal DNA extraction

[0104] use Fast DNA Stool Mini Kit (Cat. No. 51604) was used to extract fecal microbial genomic DNA.

[0105] 3.3 Sample DNA quality inspection

[0106] 3.3.1 Nanodrop detection of extracted DNA concentration

[0107] (1) Wash the detection well of nanodrop twice with ddH2O and use elution buffer (Buffer ATE) as a blank control for white balance until it reaches 0.0 ng / μl;

[0108] (2) Input the sample number and test the sample concentration;

[0109] If OD260 / 280=1.8-2.0, the DNA purity is relatively good. If it is too high, it may be RNA contamination, and if it is too low, it may be protein contamination. If OD260 / 230>2, the DNA purity is relatively good. If it is too low, it may be contaminated by humic acid, etc.

[0110] (3) After the test is completed, clean the detection hole of nanodrop three times with ddH2O and output the test data.

[0111] 3.3.2 DNA electrophoresis detection

[0112] (1) Glue preparation: Add 1 g of glue powder to 100 ml of 1×TAE solution and boil in a microwave oven until the glue powder is completely fused. After cooling, add 3 μl of EB solution, mix well, and introduce into a glue making tank (with a small comb inserted). Let it stand for 30 min and set aside.

[0113] (2) The loading volume of DNA electrophoresis is 400 ng. The loading volume of each sample is determined based on the concentration detected by nanodrop. If the concentration of the sample is too high, the sample can be appropriately diluted by mixing 400 ng DNA with 6× loading buffer. If the concentration of the sample is too low, the loading volume of the sample can be appropriately increased.

[0114] (3) Add the samples to the gel wells in order and turn on the power supply, 150V, 30min.

[0115] (4) The imaging system takes pictures, saves them, and observes the integrity of the extracted DNA.

[0116] 3.4 16S library construction (PCR amplification)

[0117] Specific primers with barcodes were synthesized according to the designated sequencing region, and the KAPA HiFi Hotstart ReadyMix PCR Kit was used for the formal PCR test.

[0118] 3.5 PCR amplification product recovery

[0119] After successful amplification, the PCR product was detected by 2% agarose gel and recovered by gel excision using Axy Prep DNA Gel Recovery Kit.

[0120] 3.6 Library concentration and size detection

[0121] 3.6.1Nanodrop detection of library concentration

[0122] (1) Wash the detection well of nanodrop twice with ddH2O, and use elution buffer (kit eluent or deionized water) as a blank control for white balance until it reaches 0.0 ng / μl;

[0123] (2) Enter the library number and test the concentration;

[0124] (3) After the test is completed, clean the detection hole of nanodrop three times with ddH2O and output the test data.

[0125] 3.6.2 Library electrophoresis detection

[0126] (1) Glue preparation: Add 1 g of glue powder to 100 ml of 1×TAE solution and boil in a microwave oven until the glue powder is completely fused. After cooling, add 3 μl of EB solution, mix well, and introduce into a glue making tank (with a small comb inserted). Let it stand for 30 min and set aside.

[0127] (2) The loading volume of DNA electrophoresis is about 100 ng. Determine the loading volume of each library based on the concentration detected by nanodrop. If the concentration of the library is too high, dilute the sample appropriately and mix 100 ng of DNA with 6× loading buffer (the final concentration of the loading buffer is 1×). If the concentration of the library is too low, directly take 5 μl as the loading volume.

[0128] (3) Add the library to the gel wells in order and turn on the power supply, 150V, 30min.

[0129] (4) The imaging system takes pictures, saves them, and observes whether the DNA bands are qualified.

[0130] 3.7 Library pooling detection and sequencing

[0131] The qualified libraries are mixed into the pre-sequencing library in the corresponding proportion according to the sequencing amount requirements of each sample. The dsDNA HS Assay Kit was used to quantify the predicted sequence library, and the predicted sequence library was mixed in the corresponding proportion according to the Qubit test results. Then, it was sequenced on the Illumina NovaSeq PE250 platform.

[0132] 3.8 Calculation of relative abundance of intestinal microbial species

[0133] The relative abundance of intestinal microbial flora species = the number of clean reads contained in all OTUs mapped to the species / the total number of clean reads in the sample.

[0134] OTU (Operational Taxonomic Units) is a unified mark set for a certain taxonomic unit (strain, genus, species, group, etc.) in phylogenetic or population genetics research for the convenience of analysis. Sequences are divided into many groups according to their similarity (usually 97%), and each group is an OTU.

[0135] 3.9 Significant difference analysis

[0136] 3.9.1 Analysis of LEfSe differences among species

[0137] LDA EffectSize (LEfSe analysis): LEfSe uses linear discriminant analysis (LDA) to estimate the size of the effect of each component (species) abundance on the difference effect, and find out the communities or species that have a significant difference in sample partitioning. LEfSe analysis emphasizes statistical significance and biological relevance.

[0138] 3.9.2 Inter-group rank sum test analysis

[0139] The rank sum test method was used to analyze the significant differences between different groups to find out the species that had a significant difference in the division between groups. The wilcox.test function of the R language stats package was used for the difference analysis between two groups, and the kruskal.test function of the R language stats package was used for the difference analysis between more than two groups.

[0140] 3.9.3 Spearman correlation analysis between clinical characteristics, cellular inflammatory factors and relative abundance of fecal microbial species

[0141] The relative abundance of species at the genus level, basic clinical characteristics, detected clinical characteristics and plasma cellular inflammatory factor levels were used to calculate the correlation between intestinal microbial species and basic disease characteristics, clinical characteristics and cellular inflammatory factors. The reduction factor analysis of SPSS software combined with Spearman correlation analysis revealed the important relationship between intestinal microbial species and clinical characteristics.

[0142] 4. Detection of plasma inflammatory factors

[0143] According to the instructions of the kit (The V-PLEX proinflammatory Panel 1human kit (Meso Scale Discovery, MSD, K15049D-1), the patient's plasma cell inflammatory factors were detected. The specific experimental steps are as follows:

[0144] (1) The plasma sample was diluted 2-fold and centrifuged at 3000 g for 5 min.

[0145] (2) Prepare standards: Shake the standards thoroughly and place them at room temperature for 15-20 min. Use this as the highest concentration point and make 4-fold dilutions in sequence, 7 standards + 1 blank.

[0146] (3) Prepare the detection antibody diluent: Pipette 60 μl of the detection antibody and add the diluent to make up to 3 ml. Prepare the cleaning solution: Prepare 1* PBS (0.05% Tween-20) for later use. Prepare the plate reading solution: Prepare 2* plate reading solution.

[0147] (4) Wash the MSD plate three times, using 150 μl of washing solution each time.

[0148] (5) Add 50 μl of sample and standard to each well, seal with sealing film, and shake at room temperature for 2 hours.

[0149] (6) Wash the MSD plate three times, using 150 μl of washing solution each time.

[0150] (7) Add 25 μl of the prepared detection antibody to each well, seal with sealing film, and shake at room temperature for 2 hours.

[0151] (8) Wash the MSD plate three times, using 150 μl of washing solution each time.

[0152] (9) Add 150 μl of the prepared plate reader to each well and perform the assay on the plate reader.

[0153] 2. Research Results

[0154] 1. Clinical data of subjects

[0155] Table 1 Demographic and clinical characteristics of HD patients and healthy controls

[0156]

[0157]

[0158] *Unpaired t test; data are presented as mean (SD) a or median (IQR) b =HD = Huntington's disease; NA = not applicable; SD = standard deviation; IQR = interquartile range; M:F = male:female; y = year; y / o = year / year; BMI = body mass index; UHDRS-M = unified Huntington's disease rating scale-motor component; FAS = functional assessment scale; TFC = global competence; SIT = Stroop interference test; SDMT = digit symbol transfer test; CFT = categorization fluency test; BDI-II = Beck Depression Inventory-Second Edition; MMSE = Mini-Mental State Examination.

[0159] Table 1-1 Correlation analysis of clinical phenotypes of HD patients

[0160]

[0161] Spearman correlation study of clinical indicators, p≤0.01 was considered significant

[0162] The results showed that BMI (body mass index) was closely related to TFC (total capacity), suggesting that nutrition, diet, daily activities and intestinal microorganisms are closely related to HD.

[0163] 2. Analysis of significant differences in intestinal flora

[0164] 2.1LEfSe difference analysis

[0165] In order to estimate the influence of each component (species) abundance on the differential effect and find out the communities or species that have a significant difference in sample division, LEfSe analysis was used. Specifically, the non-parametric factorial Kruskal-Wallis (KW) sum-rank test was first used to detect the characteristics with significant abundance differences, and then the groups with significant differences in abundance were found. Finally, LEfSe used linear discriminant analysis (LDA) to estimate the influence of each component (species) abundance on the differential effect. Figure 1 A shows that the abundance of 14 species was significantly different between the two groups, of which 13 species were significantly enriched in the HD group and 1 species was enriched in the normal control group. Among them, the 13 species significantly enriched in the HD group were: Actinobacteria, Deltaproteobacteria, Actinobacteria, Desulfovibrionales, Oxalobacteraceae, Lactobacillaceae, Desulfovibrionaceae, g__Intestinimonas, Bilophila, Lactobacillus, Oscillibacter, Gemmiger, Dialister, which were highly abundant in the HD group. g__Clostridium XVIII was highly abundant in the normal control group. LefSe analysis of evolutionary branch diagram ( Figure 1 In B), the circles from inside to outside represent different classification levels, namely, phylum, class, order, family, and genus. The small circles on different classifications are a classification at that level, and the size of the small circles indicates the abundance. Among them, blue represents the HD group, and red represents the healthy control group.

[0166] The results showed that there were significant differences in intestinal microorganisms between HD and normal people.

[0167] 2.2 Differences in the overall intestinal microbiota between normal and HD patients

[0168] 2.2.1 Analysis of species differences in intestinal flora at all levels between the HD group and the healthy control group

[0169] SPSS-ANOVA-BOOTSTRAP difference analysis was applied to find specific bacterial genera with significant differences between the HD and normal groups, with p ≤ 0.01 as the threshold. The results are shown in Table 2:

[0170] Table 2 Differences in species at all levels of intestinal flora between HD group and healthy control group

[0171]

[0172] The threshold for significance screening was p ≤ 0.01.

[0173] The results in Table 2 show that Dialister is the main bacterial genus that differs between HD and normal subjects.

[0174] To further increase the ability to distinguish HD from normal people, HD and control were used as dependent variables, and Bayesian regression analysis was applied with multiple bacteria as independent variables to obtain bacterial genera that can synergistically diagnose HD ( Table 3 ).

[0175] Table 3 Bayesian regression analysis showed that the two bacteria can synergistically identify HD and normal subjects (p = 0.006)

[0176]

[0177] The results in Table 3 show that the relative abundance of Dialister and Bifidobacterium in feces can distinguish HD from normal people.

[0178] Using ROC curve analysis, the AUC (area under the ROC curve) of Dialister for distinguishing HD was 0.672 (p=0.016), and the AUC of Bifidobacterium for distinguishing HD was 0.626 (p=0.078). The AUC of the combined diagnosis of HD was 0.719 (p=0.002), and AUC>0.7, indicating that the combined diagnosis of the two bacteria can further improve the accuracy of HD diagnosis (Table 4).

[0179] Table 4 Area under the curve (AUC) values ​​for differentiation of HD from normal using Bifidobacterium, Dialister and both

[0180]

[0181]

[0182] According to the maximum Youden's index, when Dialister was used alone as the identification index, the relative abundance of Dialister was ≥0.022, and the sensitivity of the detection was 45.5% and the specificity was 69.7%. When Dialister and Bifidobacterium were used together as the predictive index for HD, the prediction coefficients B of the two bacteria were obtained according to the binary regression equation (Table 5).

[0183] Table 5 Binary regression method to detect the synergistic effect of Dialister and Bifidobacterium

[0184]

[0185] According to the following formula, the predicted value P of each sample is obtained:

[0186] First, Logit(P) is calculated according to the following formula (1):

[0187] Logit(P)=-0.813+69.211*Bifidobacterium relative abundance+22.667*Dialister relative abundance(1)

[0188] Then, the predicted value P of each subject suffering from HD was calculated according to the following formula (2):

[0189]

[0190] If a stool sample had a predicted value ≥ 0.479859, it was HD, and the test had a sensitivity of 60.6% and a specificity of 81.8%.

[0191] 2.2.2 Analysis of species differences in intestinal flora at all levels between the HD-0 subgroup and the healthy control group

[0192] The most valuable intestinal microbiota microorganisms for the identification of HD and controls are Htt gene carriers who have not developed HD or have developed HD for less than 1 year (herein referred to as the HD-0 subgroup). Therefore, the same method as above was used to discover the microbiota markers of HD-0.

[0193] Table 6 Differences in species at all levels of intestinal flora between the HD-0 group and the healthy control group

[0194]

[0195] *The values ​​shown are 10% of the original values 5 The threshold for significance screening was p ≤ 0.01.

[0196] The results showed that the fecal Actinomyces, Bifidobacterium, Dialister, and Intestinimonas genera were significantly higher in the HD-0 group than in normal subjects.

[0197] To further increase the ability to distinguish HD-0 from normal people, HD-0 and controls were used as dependent variables, and Bayesian regression analysis was applied with the above four bacterial genera as independent variables, thus obtaining a trend of collaborative diagnosis of HD-0.

[0198] Table 7 Bayesian regression analysis showed that these four bacteria can synergistically identify HD preclinical patients and normal subjects (p = 0.000)

[0199]

[0200] The results showed that fecal bacteria (Actinomyces, Bifidobacterium, Dialister, Intestinimonas) have the ability to distinguish HD-0 from normal people.

[0201] Using ROC curve analysis, the AUC (area under the ROC curve) of Dialister for identifying HD-0 was 0.735 (p=0.025), the AUC of Bifidobacterium for identifying HD-0 was 0.574 (p=0.124), the AUC of Actinomyces for identifying HD-0 was 0.691 (p=0.107), and the AUC of Intestinimonas for identifying HD-0 was 0.650 (p=0.112). The AUC of the combined diagnosis of HD by the four was 0.806 (p=0.004), and AUC>0.8, indicating that it has a good diagnostic predictive value (Table 8).

[0202]

[0203]

[0204] According to the maximum Youden's index, when Dialister was used alone as the identification index, the relative abundance of Dialister was ≥0.016, and the sensitivity of the detection was 60.0% and the specificity was 78.2%. When the four bacteria were used together as the prediction index for HD-0, the prediction coefficients B of the four bacteria were obtained according to the binary regression equation (Table 9).

[0205] Table 9 Binary regression method detects the synergistic effect of Dialister, Bifidobacterium, Actinomyces and Intestinimonas as diagnostic biomarkers for HD-0.

[0206]

[0207] According to the following formula, the predicted value P of each sample is obtained:

[0208] First, Logit(P) is calculated according to the following formula (3):

[0209] Logit(P)=-2.937+48.077*Bifidobacterium relative abundance+29.557*Dialister relative abundance+7114.032*Actinnomyces relative abundance+118687.850*Intestinimonas relative abundance(3)

[0210] Then, the predicted value of each subject suffering from HD was calculated according to the following formula (2):

[0211]

[0212] If the predicted value of a stool sample is greater than 0.3819259, it is HD-0, the AUC of the test is 0.806, the sensitivity of the test is 70.0%, and the specificity is 93%. If the Dialister genus is used alone for evaluation, the relative abundance of Dialister genus ≥ 0.016 is HD-0, the AUC of the test is 0.735, the sensitivity is 60%, and the specificity is 78.8%.

[0213] 2.3 Correlation analysis between differential bacteria and clinical indicators

[0214] At the genus level, the abundance of intestinal flora was analyzed by spearman correlation with the clinical characteristics of HD patients, including disease course, BDI-II score, UHDRS-M score, FAS score, CAG repeat number, CFT score, MMSE score, SDMT score, SIT score, and TFC score. Four genera of bacteria were found to be associated with the clinical characteristics of HD. The abundance of Intestinimonas was positively correlated with the TFC score. The abundance of Lactobacillus was negatively correlated with the MMSE score, while the relative abundance of Actinomyces was positively correlated with MMSE. Lactococcus was positively correlated with movement and overall dysfunction in HD. See Table 10 for details.

[0215] Table 10 Nonparametric two-sided correlation analysis between clinical characteristics and intestinal bacterial genus abundance in HD patients

[0216]

[0217] BMI = body mass index; UHDRS-M = unified Huntington's disease rating scale motor part; FAS = functional assessment scale; TFC = global competence; SDMT = symbol-digit conversion test; MMSE = Mini-mental state examination. / : Results with p values ​​greater than 0.05 are not shown, and those with no correlation between enterobacteria and cognitive function are not shown. In Table 4, N = 33;

[0218] The results in Table 10 show that a variety of intestinal microorganisms affect the clinical manifestations of HD stages. Clinically, BMI, UHDRS-M, FAS, TFC, SDMT and MMSE can be used as clinical measurement indicators for fecal microbiota transplantation treatment.

[0219] 2.4 Analysis of the mechanism of action of intestinal flora in improving clinical symptoms: direct action or regulation by plasma cytokines

[0220] Using factor analysis, basic information, clinical information, plasma cytokine level information and intestinal flora information were classified into categories ( Figure 2 ), and then Spearman correlation analysis was performed. The results showed that the intestinal flora directly played a role in improving the clinical phenotype of HD patients (p = 0.035), and there might be a relationship between intestinal microorganisms and the overall plasma cytokine levels (p = 0.053) (Table 11).

[0221] Table 11 Correlation study between intestinal flora and basic clinical information, clinical information and plasma cytokine levels

[0222]

[0223] The results showed that based on the comprehensive analysis at the overall level, intestinal flora microorganisms directly improved the clinical manifestations of HD and may be related to cellular inflammatory factors.

[0224] Example 2 Treatment of Huntington's disease by intestinal microorganisms

[0225] In this example, one normal person was selected as a donor and three HD patients were enrolled for clinical experimental treatment.

[0226] Donor selection: 1. Healthy adults under 50 years old with good eating habits and lifestyle; 2. No known infectious diseases; 3. No use of antibiotics or other drugs that cause intestinal microecological disorders in the past 3 months; 4. No digestive diseases such as gastrointestinal tumors and polyps; 5. No history of immune system diseases; 6. No use of any immunosuppressants; 7. No history of IBD, chronic constipation and IBS; 8. No history of malignant tumors; 9. No travel to local epidemic diarrhea areas in the past 6 months; 10. No current digestive system symptoms and no other relevant risk factors, such as intravenous drug abuse (drug abuse), high-risk sexual behavior and criminal history; 11. All clinical observation indicators are evaluated as normal.

[0227] Recipient selection: Fecal flora analysis is rich in HD-specific intestinal strains, with no infectious or immune diseases and no recent history of antibiotic use.

[0228] Basic information of HD patients enrolled in the study was collected: name, gender, ID number, BMI, dietary information, personal smoking and drinking history, CAG repeat number of the Htt gene, whether the disease occurred and medical history, and age.

[0229] Clinical indicators evaluated at baseline before fecal microbiota transplantation: UHDRS-M, FAS, TFC, SDMT, CFT, STROOP, BDI-II, MMSE, and PSQI.

[0230] Clinical observation indicators of patients after fecal microbiota transplantation: UHDRS-M, FAS, TFC, SDMT, CFT, STROOP, BDI-II, MMSE, PSQI.

[0231] The clinical improvement indicators of patients after fecal microbiota transplantation: BMI, UHDRS-M, FAS, TFC, and MMSE were significantly improved compared with before transplantation.

[0232] Assessment of the patient's microbiome composition: 16S ribosomal RNA (rRNA) gene sequencing method was used. For details, see Section 3.4 of Study Subjects and Methods in Example 1 (as above).

[0233] Referring to the demonstration diagram of the method for collecting and processing intestinal microorganisms from donors (see Nicco C. et al. From Donor to Patient: Collection, Preparation and Cryopreservation of Fecal Samples for Fecal Microbiota Transplantation. Diseases, 2020, Diseases 2020, 8, 9; doi: 10.3390 / diseases8020009), the processing flow of the fecal bacteria from donors in this embodiment was designed, as follows: Figure 3 shown.

[0234] Fecal microbiota transplantation:

[0235] Fresh fecal enema: freshly prepared fecal bacteria from donors (such as Figure 3 ), after the recipient washes the intestine, the above fecal bacteria are evenly sprayed onto the intestinal wall with a colonoscope. Fecal microbiota transplantation was performed once, and the evaluation period was: 1 day, 3 days, 7 days, 1 month, and 2 months after the first fecal microbiota transplantation.

[0236] The above experimental results show that transplanting normal people's intestinal microorganisms into HD recipients can improve the clinical manifestations of HD recipients. Intestinal flora transplantation will be of great significance for delaying the occurrence and treatment of Huntington's disease.

Claims

1. Use of a product for detecting intestinal microorganisms in the preparation of a reagent or kit for assisting in the diagnosis of the occurrence of Huntington's disease in patients, wherein: The patient carries a Htt mutant gene, and the intestinal microorganisms include bacteria of the genera Dialister, Bifidobacterium, Actinomyces, and Intestinimonas.

2. The use according to claim 1, wherein The auxiliary diagnosis stage is to use Dialister + Bifidobacterium + Actinomyces + Intestinimonas to jointly assist in the diagnosis of Huntington's disease, and the steps are as follows: Step 1: Calculate Logit(P) according to the following formula (1): Logit (P) = -2.937 + 48.077 × Bifidobacterium relative abundance + 29.557 × Dialister relative abundance + 7114.032 × Actinnomyces relative abundance + 118687.850 × Intestinimonas relative abundance (1) Then, the predicted value of each subject suffering from HD was calculated according to the following formula (2): If the predicted value of a stool sample is P ≥ 0.3819259, the patient suffers from Huntington's disease and the patient has not yet developed the disease or has developed the disease for less than 1 year.

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