RU2791665C1 - Method for treatment of alzheimer's disease by t-cell inhibition of amino acid uptake - Google Patents

Abstract

FIELD: medicine.

SUBSTANCE: it is proposed to use an agent for inhibiting the uptake of amino acids by naive T-cells in the peripheral blood of a mammal for the production of a drug for the treatment of Alzheimer's disease in an individual, where the amino acid is one or more selected from the following: 4-OH proline, acetylornithine, alanine, alpha-aminoadipic acid, asparagine, aspartic acid, asymmetric dimethylarginine, beta-alanine, carnosine, citrulline, creatinine, GABA, glutamic acid, glutamine, glycine, histidine, hypotaurine, isoleucine, kynurenine, leucine, lysine, methionine, methionine sulfoxide, ornithine, phenylalanine, pipecolic acid, proline, putrescine, pyroglutamic acid, serine, serotonin, taurine, threonine, tryptophan, tyrosine and valine. Also provided are methods of treating Alzheimer's disease, comprising administering an agent for inhibiting amino acid uptake by naive T cells in the peripheral blood of a mammal to a patient.

EFFECT: treatment of Alzheimer's disease by inhibiting neuroinflammation.

9 cl, 23 dwg, 4 tbl, 4 ex

Description

FIELD OF TECHNOLOGY

The present invention relates to the treatment of Alzheimer's disease (AD). More specifically, the present invention relates to the use of the brain-gut association to inhibit the progression of Alzheimer's disease.

BACKGROUND OF THE INVENTION

Alzheimer's disease (AD) is a progressive neurodegenerative disease with gradual development. Clinically, it is characterized by generalized dementia such as memory impairment, aphasia, apraxia, agnosia, impairment of visuospatial skills, impaired ability to purposeful activities, and changes in personality and behavior. Two pathological features of Alzheimer's disease are extracellular deposits of β-amyloid (senile plaques) and intracellular neurofibrillary tangles (paired helical filament). β-amyloid deposits and neurofibrillary tangles lead to loss of synapses and neurons, which leads to severe atrophy of damaged areas of the brain, usually starting in the temporal lobe. The mechanism of this damage caused by β-amyloid peptides and neurofibrillary tangles is not fully understood.

Developed by a research team led by Geng Meiyu, a researcher at the Institute of Pharmaceutical Innovation of the Chinese Academy of Sciences/Shanghai Institute of Materia Medica, mannuronic acid oligosaccharides is a new oral Alzheimer's disease (AD) innovation drug with independent intellectual property rights . On July 17, 2018, the results of the Disclosed Phase III Clinical Trial demonstrated that mannuronic acid oligosaccharides achieved the expected results in terms of key performance indicators for improving cognitive function, which is of extremely significant statistical and clinical significance. In addition, the incidence of adverse events is comparable to the incidence of adverse events in the placebo group, and they have good safety and are suitable for long-term use. Mannuronic acid oligosaccharides became the first drug in the global field of AD treatment to be successful in a phase III clinical trial over a period of 16 years.

As for mannuronic acid oligosaccharides, many related Chinese patents have been issued. CN2017114675966 describes the composition of mannuronic diacid. CN2016100697039 describes a process for the production of oligomannuronic diacid. CN2018107134113 describes the use of a mannuronic diacid composition for the treatment of Parkinson's disease. CN2015104243401 describes the use of mannuronic acid oligosaccharides with a carboxyl group at position 1 from the reducing end and their derivatives for the treatment of Parkinson's disease. These patents are incorporated herein by reference in their entirety.

(mannuronic acid oligosaccharides)

The field needs more drugs that can be used to treat Alzheimer's disease.

SUMMARY OF THE INVENTION

In the present description, the inventors describe a causal relationship between intestinal microbiota dysbiosis and neuroinflammation in the progression of AD. In particular, changes in the composition of the gut microbiota can lead to peripheral accumulation of flora metabolites such as phenylalanine and isoleucine. They promote the proliferation and differentiation of peripheral pro-inflammatory T-helper type 1 (Th1) cells during the progression of AD. Peripheral immune cells infiltrate the brain and increase neuroinflammation. Importantly, increased levels of metabolites such as phenylalanine and isoleucine in peripheral blood have been confirmed in two independent samples of patients with moderate cognitive impairment (MCI) caused by AD. The inventors also demonstrated that mannuronic acid oligosaccharides, which showed a consistent and stable improvement in cognitive function in phase III clinical trials in China, alter the balance of the intestinal flora, reduce the accumulation of amino acid metabolites of the flora in the blood, and inhibit neuroinflammation. Mainly, the inventors' data highlight the role of gut dysbiosis-induced neuroinflammation in the progression of AD and propose a novel strategy for the treatment of AD by intervening in the brain-gut axis.

In one aspect, the present invention relates to the use of an agent for inhibiting amino acid uptake by naive T cells in the peripheral blood of a mammal for the manufacture of a medicament for the treatment of Alzheimer's disease in an individual.

In another aspect, the present invention provides a pharmaceutical composition for the treatment of Alzheimer's disease in a subject, comprising an effective amount of an agent for inhibiting amino acid uptake by naive T cells in the peripheral blood of a mammal.

In another aspect, the present invention relates to a method for screening a drug candidate that can be used to treat Alzheimer's disease, comprising:

a) administering the test agent to in vivo or in vivo models with the SLC7A5 transporter, and

b) selecting a test agent that inhibits the SLC7A5 transporter as a drug candidate that can be used to treat Alzheimer's disease.

In another aspect, the present invention relates to a method of treating a patient having Alzheimer's disease, comprising:

administering to a patient an agent for inhibiting amino acid uptake by naive T cells in the peripheral blood of a mammal so that the proportion of pro-inflammatory Th1 cells in the patient's CD4+ T cells is regulated to be close to or equal to the corresponding proportion of pro-inflammatory Th1 cells in CD4+ T cells -cells in the corresponding normal sample.

In another aspect, the present invention relates to a method of treating a patient having Alzheimer's disease, comprising:

administering an agent for inhibiting amino acid uptake by naive T cells in the peripheral blood of a mammal to a patient such that the relative level of amino acid uptake by naive T cells in the patient is adjusted to be close to or equal to the corresponding relative level of amino acid uptake by naive T cells in the corresponding normal sample.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig.1. Gut dysbiosis and immune cell changes during disease progression in 5XFAD transgenic (Tg) mice.

(a) Changes in relative levels of synaptophysin RNA expression in the hippocampus of transgenic (Tg) 5XFAD mice at 2, 3, 5, 7 and 9 months and in wild-type (WT) mice at 2 months (n = 5-12). Data are presented as the mean ± standard error of the mean (mean ± sem) relative to actin expression level. *P < 0.05, **P < 0.01 via one-way ANOVA (F(5, 43) = 2.952).

(b) Changes in time relative to 10 ⁴ s taken to achieve 80% success (see methods) in the discrimination learning test in 5XFAD transgenic (Tg) mice at 2, 3, 5, 7 and 9 months and in wild-type (WT) mice at 2 months (n=4-8). Data are presented as mean ± standard error of the mean (mean ± sem). *P < 0.05 by Student's t-test. S, seconds.

(c) Principal component analysis (PCA) for gut microbiome composition in WT and 5XFAD transgenic (Tg) mice at the operational taxonomic unit (OTU) level at different time points (n = 4-10). The shapes and colors of the dots indicate samples from each individual and in different months. Colored ovals indicate confidence interval (CI) ranges corresponding to 0.95 in each test group. M, months.

(d) Relative changes in operational taxonomic unit (OTU) content in the total gut microbiome population of 5XFAD transgenic (Tg) mice over different months, shaded at the type level in the flowplot (n = 4-10). The two most common types, Bacteroidetes and Firmicutes , are labeled on the graph. Colors indicate different types of gut microbiota.

(e) Changes in the positive density of IBA1 immunofluorescent staining reflecting the activation of microglial cells in the hippocampus of transgenic (Tg) 5XFAD mice at 2, 3, 5, 7, and 9 months relative to values in wild-type (WT) mice at 2 months of age (n = 2 -7). Data are presented as mean ± standard error of the mean (mean ± sem); the lines are approximated by a cubic spline. The Y-axis IBA1 value is the relative amount of fluorescent staining in a transgenic animal at each time point relative to the amount of fluorescent staining in a wild-type animal at the same time point.

(f) Changes in activated microglial type M1 and M2 detected in whole brain homogenates of 5XFAD transgenic (Tg) mice at 2, 3, 5, 7 and 9 months (n = 4-8). Type M1 microglia (CD45 ^low CD11b ⁺ CX3CR1 ⁺ Siglec-H ⁺ F4/80 ⁺ CD86 ⁺ ) and M2 microglia (CD45 ^low CD11b ⁺ CX3CR1 ⁺ Siglec-H ⁺ F4/80 ⁺ CD206 ⁺ ) were detected by flow cytometry, and the numbers of these cells are presented relative to the frequency of CD45 ^low CD11b ⁺ cells. Red dots and lines: M1 microglia. Green dots and lines: M2 microglia. Data are presented as mean ± standard error of the mean (mean ± sem); the lines are approximated using the cubic spline algorithm.

(g) Changes in infiltrating cells (CD45 ^high ) detected in whole brain homogenates of transgenic (Tg) 5XFAD mice (red dots and lines) and WT mice (black dots and lines) at different time points as determined by flow cytometry (Tg mice: 2 months, n=5; 3 months, n=4; 5 months, n=4; 7 months, n=7; 9 months, n=3. WT mice: n=6.). Cell numbers are presented relative to the frequency of CD45 ⁺ cells, and they have the format of the mean ± standard error of the mean (mean ± sem). The lines are approximated using the cubic spline algorithm.

(h) Changes in CD45 ^high cells in 5XFAD transgenic (Tg) mice at different time points (n=4-8). In the bar graph, cell numbers are presented relative to the frequency of CD45 ^high cells. Colors indicate different subtypes of CD45 ^high cells: Neu, neutrophils; DC, dendritic cells; NK, natural killers; Mo/Mϕː monocytes and macrophages; B, B cells; other, unclassified cells.

(i) Changes in infiltrating CD4 T cells (CD45 ^high CD4 ⁺ ) detected in whole brain homogenates of 5XFAD transgenic (Tg) mice (red dots and lines) at 2, 3, 5, 7, and 9 months as determined by flow cytometry ( n = 4-8). Cell numbers are presented relative to the frequency of CD45 ^high cells and are formatted as mean ± standard error of the mean (mean ± sem). The lines are approximated by cubic splines.

(j) Changes in infiltrating peripheral Th1 and Th2 cells detected in whole brain homogenates of 5XFAD transgenic (Tg) mice at 2, 3, 5, 7, and 9 months ( n = 4-8). Th1 cells (CD45 ^high CD4 ⁺ CXCR3 ⁺ CCR6 ^- ) and Th2 cells (CD45 ^high CD4 ⁺ CXCR3 ⁺ CCR6 ^- CCR4 ⁺ ) were detected by flow cytometry and the results are presented relative to the frequency of CD45 ^high CD4 ⁺ T cells. Red dots and lines: Th1 cells. Green dots and lines: Th2 cells. Data are presented as mean ± standard error of the mean (mean ± sem). The lines are approximated by cubic splines.

(k) Correlation of brain lymphocytes and gut microbiota reflected at the genus level during the Th2/M2-associated stage and the Th1/M1-associated stage at the early (2-3 months) and late phase (7-9 months), respectively. (left panels, n =4-8). All bacteria that significantly correlated with lymphocyte counts in the brain of 5XFAD mice are shown in the right panel. Red (positive correlation) or blue (negative correlation) boxes with a yellow asterisk (*) indicate significant correlations with P values < 0.05 determined by Pearson's parametric correlation test.

Figure 2 Gut microbiota is required for immune cell infiltration and microglia activation.

(a) Effects of antibiotic gavage administration for three months on the relative abundance of microorganisms in the gut of 7-month-old 5XFAD transgenic (Tg) mice (n = 6-7). ABX, a mixed antibiotic cocktail consisting of ampicillin (0.1 mg/ml), streptomycin (0.5 mg/ml) and colistin (0.1 mg/ml). Different genera of intestinal micro-organisms are colored differently, and their relative content changes are presented in a bar graph.

(bc) Effects of administration of antibiotics by gastric tube for three months on the frequency of Th1 cells (b) and M1-type microglial cells (c) in the brain homogenate of transgenic (Tg) 5XFAD mice at 7 months of age. The numbers of Th1 cells (CD45 ^high CD4 ⁺ CXCR3 ⁺ CCR6 ^- ) are presented relative to the frequency of CD45 ^high CD4 ⁺ cells ( b ), while the numbers of M1-type microglial cells (CD45 ^low CD11b ⁺ CX3CR1 ⁺ Siglec-H ⁺ F4/80 ⁺ CD86 ⁺ ) are shown relative to the frequency of CD45 ^low CD11b ⁺ cells ( c ). In both cases, detection was performed by flow cytometry. Data are presented as mean ± standard error of the mean (mean ± sem).

(d) Relative genus-level intestinal abundances in WT mice, co-housed WT mice, and 5XFAD transgenic (Tg) mice ( n = 6-7). All three groups of mice were 7 months old. Different colors correspond to different genders. Co-housed WT: WT mice housed with Tg mice.

(ef) Changes in frequency of Th1 cells ( e ) and M1 type microglia ( f ) in brain homogenates of co-housed WT, WT and 5XFAD transgenic (Tg) mice at 7 months of age ( n = 6-7). Th1 cells (CD45 ^high CD4 ⁺ CXCR3 ⁺ CCR6 ^- ) are presented relative to the frequency of CD45 ^high CD4 ⁺ cells ( e ), while the frequency of M1-type microglial cells (CD45 ^low CD11b ⁺ CX3CR1 ⁺ Siglec-H ⁺ F4/80 ⁺ CD86 ⁺ ) is shown relative to the frequency of CD45 ^low CD11b ⁺ cells ( f ). In both cases, detection was performed by flow cytometry. Data are presented as mean ± standard error of the mean (mean ± sem). * P < 0.05, ** P < 0.01 according to Student's t-test.

(g) Levels of cytokine proteins in brain homogenates of WT mice, co-housed WT mice and transgenic (Tg) 5XFAD mice at 7 months of age as detected using a cytokine antibody array (n = 6-7). In all three groups, the mice were 7 months old. Colors on the heat map indicate relative levels of cytokines normalized by a rough Z-score; red indicates cytokines that are elevated, and blue indicates cytokines that are declining.

Figure 3. Effects of OM1 on behavioral changes in APP/PS1 mouse models.

(a) Structure of OM1. OM1 is a mixture of acidic linear oligosaccharides with degrees of polymerization ranging from dimers to decamers with an average molecular weight of approximately 1 kDa.

(b) Results for Morris Water Maze (MWM) escape latency as an indicator of spatial learning and memory in APP/PS1 mice. Nine month old APP/PS1 mice were treated with 50 mg/kg and 100 mg/kg OM1 for 3 months until 12 months of age. The MWM test was then performed on spatial learning ability and memory for 6 additional days. During the test, OM1 was injected continuously. The latency of the start of rescue (seconds) was determined as one of the final results of the test (see methods). Higher latency indicates that these mice take longer to reach a goal, indicating more severely impaired spatial learning and memory (n = 11-14). Data are presented as mean ± standard error of the mean (mean ± sem). Black asterisks indicate comparison between WT and APP/PS1 groups. The blue asterisk indicates the comparison between the OM1 (100 mg/kg) administration group and the APP/PS1 administration group. *P < 0.05, ***P < 0.001 according to two-way ANOVA.

(c) The number of intersections of the platform areas in the MWM test as an indicator of spatial learning and memory in APP/PS1 mice. Nine month old APP/PS1 mice were treated with 50 mg/kg and 100 mg/kg OM1 for 3 months until 12 months of age. The MWM test for spatial learning ability and memory was then performed for 6 additional days. During the test, OM1 was constantly injected. The number of intersections of the platform areas was determined as another test result (see methods). Higher platform region crossing counts indicate less severely reduced spatial learning and memory capacity (n = 11-17). *P < 0.05, ***P < 0.001 according to one-way ANOVA (F(3, 55) = 6.542).

(d) Accuracy of spatial working memory when tested using a Y-maze in APP/PS1 mice. Nine month old APP/PS1 mice were treated with 50 mg/kg and 100 mg/kg OM1 for 3 months at 12 month old doses. Then a test was performed in the Y-maze. During the test, OM1 was constantly administered. The accuracy of the Y-maze was the ratio between the correct alternation and the total alternation (see "Materials and methods"). Higher precision indicates less impaired working memory capacity (n = 17-20). Data are presented as mean ± standard error of the mean (mean ± sem). **P < 0.01, ***P < 0.001 according to one-way ANOVA (F(3, 71) = 12.39).

Figure 4. OM1 alleviates neuroinflammation by reorganizing the gut microbiota.

(a) Principal coordinate analysis (PCoA) for gut microbiome composition at the operational taxonomic unit (OTU) level based on Bray-Curtis distance for 5XFAD (Tg) and OM1-treated Tg mice at 7 months of age (n = 7) . The shapes and colors of the dots indicate patterns from each individual. The colored ovals indicate the confidence interval (CI) ranges corresponding to 0.95 in each group tested. PC, main component.

(b) Heatmap of significant gut microbiota changes presented at the genus level between 5XFAD (Tg) mice and OM1-treated Tg mice at 7 months of age ( n =17). The colors on the color map indicate the relative content of the gut microbiota; red indicates bacteria that are rising, and blue indicates bacteria that are declining.

(c) Changes in correlations between gut microbiome (indicated by numbers near blue circles) and brain lymphocytes (solid circles) before (left) and after (right) OM1 gavage in 5XFAD (Tg) mice at 7 months of age. On the right side is the name of each gut microbiome.

(d) Effect of OM1 administration on the frequency of Th1 cells in the brain of 5XFAD (Tg) mice at 7 months of age ( n = 5-7). Th1 cell counts (CD45 ^high CD4 ⁺ CXCR3 ⁺ CCR6 ^- ) are relative to CD45 ^high CD4 ⁺ T cell counts as determined by flow cytometry. Data are presented as mean ± standard error of the mean (mean ± sem). * P < 0.05, *** P < 0.001, according to Student's t-test.

(e) Effect of OM1 injection on positive signal density in IBA1 immunofluorescence staining performed on hippocampal sections of 5XFAD (Tg) mice at 7 months of age, reflecting microglial cell activation ( n = 4-6). Data are presented as mean ± standard error of the mean (mean ± sem). * P < 0.05, according to one-way ANOVA (F(2, 15) = 21.94).

(f) Effect of OM1 administration on cytokine protein levels in brain homogenates of 7-month-old 5XFAD (Tg) mice as detected by anti-cytokine antibody array ( n = 5-6). Colors on the heat map indicate relative levels of cytokines normalized by a rough Z-score; red indicates cytokines that are elevated, and blue indicates cytokines that are declining.

(gh) Effect of OM1 on Aβ-positive region (g) and tau-positive region ( h ) in the hippocampus of 7-month-old 5XFAD (Tg) mice assessed in brain sections ( n = 4-7). Data are presented as mean ± standard error of the mean (mean ± sem). For Aβ analysis: * P < 0.05, ** P < 0.01 (F(2, 14) = 22.78). For tau analysis: * P < 0.05, *** P < 0.001 (F(2, 15) = 13.06) according to one-way ANOVA.

(i) Effects of OM1 on time relative to 10 ⁴ seconds (s) taken to achieve 80% success (see methods) in the discrimination learning test in 5XFAD mice at 7 months of age (n=10-13). Time means the time to reach the 80% efficiency level (seconds); the more time it takes, the more severe the violation (see methods). * P < 0.05, *** P < 0.001 according to one-way ANOVA (F(2.31) = 9.751).

Figure 5. OM1 inhibits neuroinflammation by taking control of amino acid metabolism.

(a) Signaling pathway enrichment analysis for 31 types of faecal metabolites from 5XFAD (Tg) mice at 7 months of age with or without OM1 administration and using MBROLE ( n = 6-8). Enrichment results are listed with KEGG modules and KEGG enzyme interactions screened using a P value < 0.05 test.

(b) Blood amino acid lists between WT (n=30) and Tg (n=26) that could be distinguished during disease progression using a random forest model (number of trees: 500; number of predictors: 7; randomness: included ; see method).

(c) Changes in the levels of histidine, phenylalanine and isoleucine in the faeces of WT mice, Tg mice and Tg mice injected with OM1 (n = 6-11). Red, increased level; blue, reduced level.

(d) Changes in blood levels of histidine, phenylalanine and isoleucine in WT, Tg mice and OM1 treated Tg mice (n = 6-7). Red, increased level; blue, reduced level.

(e) Effects of OM1 on differentiation of naive CD4 ⁺ T cells (Th0 cells) into Th1 cells induced by phenylalanine and isoleucine. Naive CD4 ⁺ T cells were cultured for 3 days with/without OM1 in the presence of phenylalanine (1 mm) or isoleucine (1 mm). The frequency of Th1 cells (CD4 ⁺ IFN-γ ⁺ ) was tested by flow cytometry. Data are presented as mean ± standard error of the mean (mean ± sem); n = 3 reps per group. Left, * P < 0.05, ** P < 0.01 according to one-way ANOVA (F(2, 6) = 15.64). Right, * P < 0.05, ** P < 0.01 according to one-way ANOVA (F(2, 6) = 10.35).

(f) Effects of OM1 on Th1 cell proliferation induced by phenylalanine and isoleucine. Naive CD4 ⁺ T cells were stained with CellTrace and cultured for 3 days with/without OM1 in the presence of phenylalanine (1 mm) and isoleucine (1 mm). CellTrace fluorescence density in Th1 (CD4 ⁺ IFN-γ ⁺ ) cells was tested by flow cytometry (see methods). Data are presented as mean ± standard error of the mean (mean ± sem), n = 3. * P < 0.05, *** P < 0.001 according to one-way ANOVA (F(4, 9) = 28, 34).

(g) Changes in blood Th1 cells after intraperitoneal (ip) injection for 4 days of phenylalanine and isoleucine ( n = 6). *** P < 0.001 according to one-way ANOVA (F(2, 21) = 101.8).

(h) Classification based on random trees of amino acid changes in healthy controls (HC) and in patients with mild cognitive impairment (MCI) due to AD (first group, n =9 for MCI due to AD, n =18 for HC).

(i) The frequency of Th1 cells in the blood of healthy controls (HC) and patients with mild cognitive impairment (MCI) due to AD (first group, n = 8 for MCI due to AD, n = 9 for HC). * P < 0.05 by Student's t-test. The vertical axis shows the percentage of Th1 cells/CD4 ⁺ T cells.

(j) Blood levels of phenylalanine and isoleucine in healthy controls (HC) and patients with mild cognitive impairment (MCI) due to AD (second group, n = 22 for both groups). * P < 0.05 according to Student's t-test.

Figure 6. Schematic diagram of neuroinflammation in AD progression and intervention strategy

Changes in the gut microbiota during the progression of AD cause alterations in amino acid metabolism. It promotes the differentiation of naïve CD4 T cells into Th1 cells in the blood. Meanwhile, amino acids and Th1 cells can infiltrate the brain through blood circulation. Infiltration of peripheral immune cells and activation of microglia lead to pathological neuroinflammation in the brain, leading to cognitive decline. Oral administration of OM1 can restore the gut microbiota, inhibit abnormal amino acid production and reduce brain peripheral immune cell infiltration, and ultimately reverse neuroinflammation.

Figure 7

(a-b) Changes in Aβ-positive regions (a) and phosphorylated tau (p-tau) positive regions (b) in hippocampal sections of 5XFAD transgenic (Tg) mice (aged 2, 3, 5, 7 and 9 months) versus mice wild-type at 2 months of age (WT) (n=2-7). Representative fluorescent images are shown; the scale mark corresponds to 100 µm. The line plots summarize the results for all individual points relative to WT mice and are presented as mean ± standard error of the mean (mean ± sem). The lines are approximated using the cubic spline algorithm. M, months.

(c) Principal component (PC) 1 from principal component analysis (PCA) for gut microbiome composition at the operating taxonomic unit (OTU) level in WT mice and 5XFAD transgenic (Tg) mice (aged 2, 3, 5, 7, and 9 months) (n=4-10). Red dots and lines, Tg mice; blue dots and lines, WT mice. Natural line connection without approximation. Using two-tailed Wilcoxon rank sum test (rank sum); * indicates a significant difference from 2 months of age in the same group. *P<0.05, **P<0.01. # indicates a significant difference compared to age-matched WT mice. #P<0.05; ##P<0.01; ###P<0.001.

(d) Change in the relative abundance of microorganisms in the intestine at the family level in transgenic (Tg) mice 5XFAD (aged 2, 3, 5, 7 and 9 months) (n=4-10). Different colors correspond to different families.

(e) Linear discriminant effect size (LEfSe) analysis cladogram for gut microbiome composition in 5XFAD transgenic (Tg) mice (2, 3, 5, 7, and 9 months of age) (n=4-10). Bacteria with the highest discriminatory ability are indicated on the graph for each month. Colors indicate taxa of bacteria that were enriched every month. Circles from inner to outer indicate different taxonomic levels (from inner to outer: phylum, class, order, family, and genus). M, months. Verrucomicrobia ; AlphaProteobacteria ; Bacteroidetes ; Prevotellaceae ; Erysipelotrichia ; Firmicutes ; Lachnoclostridium .

(f) PCA analysis for gut microbiome at OTU level in APP/PS1 transgenic mice at 3, 6, 8, 9, 12, and 14 months of age (n=4-12). Colors and shapes indicate data for different months. Colored ovals indicate confidence interval (CI) ranges corresponding to 0.95 in each test group. PC, main component.

(g) Changes in relative gut microbial content at the type level in APP/PS1 transgenic mice at 3, 6, 8, 9, 12 and 14 months of age (n=4-12). Colors correspond to different types. M, months.

(h) Representative fluorescent images of changes in IBA1-positive regions in hippocampal sections of 5XFAD transgenic (Tg) mice (at 2, 3, 5, 7, and 9 months of age) vs. wild-type mice at 2 months of age (WT) (n=2- 7). The scale mark corresponds to 500 µm in a small frame (top), 250 µm in a large frame (bottom). M, months.

(i) Changes in the frequency of infiltrating cells (CD45 ^high ) found in whole brain homogenates of APP/PS1 mice at 3, 6, 9 and 14 months of age as detected by flow cytometry (n=5-8). Cell numbers are presented relative to the frequency of CD45 ⁺ cells, and they have the format of mean ± standard error of the mean (mean ± sem). The lines are approximated using the cubic spline algorithm.

(j) Changes in the frequency of infiltrating peripheral Th1 cells in whole brain homogenates of APP/PS1 mice at 3, 6, 9 and 14 months of age as detected by flow cytometry (n=3-8). Th1 cells (CD45 ^high CD4 ⁺ CXCR3 ⁺ CCR6 ^- ) are presented relative to the frequency of CD45 ^high CD4 ⁺ T cells. Data are presented as mean ± standard error of the mean (mean ± sem). The lines are approximated using the cubic spline algorithm.

Figure 8. Changes in the hallmarks of AD in five animal models and wild-type (WT) mice at 2, 4, 8 and 18 months of age from the Mouseac database.

(a) Change in relative density of Aβ plaques or neurofibrillary tangles (n=4 for each group). Data are presented as mean ± standard error of the mean (mean ± sem). Colors indicate different models; the lines are approximated using a polynomial algorithm.

(b) Changes in log ₂ normalized synaptophysin expression levels (n=4 for each group). Data are presented as mean ± standard error of the mean (mean ± sem). Colors indicate different models; the lines are approximated using a polynomial algorithm.

(cd) Changes in log ₂ normalized CD86 and ARG1 expression levels corresponding to changes in M1 and M2 cell numbers (n=4 for each group). Data are presented as mean ± standard error of the mean (mean ± sem). Colors indicate different models; the lines are approximated using a polynomial algorithm.

(eh) Changes in log ₂ -normalized expression levels of TIPM, CCL3, GATA-3 and MIF, corresponding to changes in the amounts of Th1 and Th2 (n=4 for each group). Data are presented as mean ± standard error of the mean (mean ± sem). Colors indicate different models; the lines are approximated using a polynomial algorithm.

Figure 9

(a) Effects of co-housing on time out of 10 ⁴ seconds spent to achieve 80% success in a pattern recognition learning ability test in WT mice, co-housing WT and 5XFAD transgenic (Tg) mice at 7 months of age (n= 5-8). The elapsed time means the time to reach the 80% efficiency level (seconds); the longer it takes, the more severe the cognitive impairment (see methods).

(b) Effects of fecal microbiota transplantation (FMT) on immune cell counts in the brain (Th1 and Th2) of recipient WT mice injected with Aβ (see Methods) using faeces from either WT mice or transgenic (Tg) 5XFAD mice. Th1 cells (CD45 ^high CD4 ⁺ CXCR3 ⁺ CCR6 ^- ) and Th2 cells (CD45 ^high CD4 ⁺ CXCR3 ^- CCR6 ^- CCR4 ⁺ ) are presented relative to CD45 ^high CD4 ⁺ T cells (n=6-8); data are presented as mean ± standard error of the mean (mean ± sem). *P<0.05, Student's t-test.

(c) Effects of FMT from 2 month old WT mice on Th1 cells in the brain of 5XFAD transgenic (Tg) mice (n=6-7). Data are presented as mean ± standard error of the mean (mean ± sem). *P<0.05, Student's t-test.

Figure 10

(a) Linear discriminant effect size (LEfSe) analysis cladogram for gut microbiome composition of 7-month-old 5XFAD transgenic (Tg) mice administered orally with OM1 (n=5-7). Bacteria with the highest discriminating ability at the type level are indicated on the graph. Blue, increased bacteria in Tg mice at 7 months of age. Red, upregulated bacteria in 7-month-old Tg mice injected with OM1. Circles from inner to outer indicate different taxonomic levels (from inner to outer: phylum, class, order, family, and genus). M, months

(b-c) Correlation between microbiota having increased and decreased levels of microorganisms induced by OM1 and frequency of immune cell subtypes in the brains of 7-month-old 5XFAD transgenic (Tg) mice. Red (positive correlation) or blue (negative correlation) squares with a yellow asterisk (*) have a P value < 0.05 determined by Pearson's parametric correlation test, the net in each square represents the correlation coefficient.

(d) Representative images of IBA1 staining, Aβ deposition and tau phosphorylation in the brain hippocampus of WT mice, Tg mice and Tg mice injected with OM1. The scale mark corresponds to 250 µm. A positive signal was visualized using 3,3'-diaminobenzidine (DAB) substrate, shown in dark brown.

(e) Effects of FMT from WT, Tg and OM1 injected Tg mice on Th1 brain cells in C57 recipient mice injected with Aβ into the hippocampus (n=4-5). Data are presented as mean ± standard error of the mean (mean ± sem).

(f) Effects of antibiotic administration (ampicillin (0.1 mg/mL), streptomycin (0.5 mg/mL) and colistin (0.1 mg/mL) on relative abundance of gut microbiota at the genus level in the APP transgenic mouse model /PS1 at 6 months of age treated with OM1 orally (n=6-8) Colors indicate different genera.

(g) Effects of OM1 on Th1 cell frequency in the brains of 6 month old APP/PS1 mice treated with antibiotics (see Methods). Th1 cells (CD45 ^high CD4 ⁺ CXCR3 ⁺ CCR6 ^- ) are plotted against CD45 ^high CD4 ⁺ T cells (n=6-8) and data are presented as mean ± standard error of the mean (mean ± sem). Left to right: *P<0.05, Student's t-test. NS, no significant differences.

(h) Effects of OM1 on the relative density of IBA1 positive immunofluorescent staining detected in hippocampal sections of 6 month old APP/PS1 mice treated with antibiotics (n=4-6, see methods). The IBA1-positive region reflects the activation of microglial cells. Data are presented as mean ± standard error of the mean (mean ± sem). ***P < 0.0001 according to Student's t-test. NS, no significant differences.

(i) Representative immunofluorescent staining of IBA1 in the brains of APP/PS1 mice and APP/PS1 mice treated with OM1 with or without antibiotics. IBA1 was visualized using a FITC-conjugated secondary antibody, as shown in green. The nucleus was stained with DAPI as shown in blue. The scale mark corresponds to 250 µm.

(j) Effects of OM1 on cytokine levels in brain homogenates of APP/PS1 mice at 7 months of age as determined by anti-cytokine antibody array (n=5-6). Colors on the heat map indicate relative levels of cytokines normalized by a rough Z-score; red indicates cytokines that are elevated, and blue indicates cytokines that are declining.

Figure 11

(a) Effect of OM1 on the differentiation of naive CD4 ⁺ T cells treated with bacterial supernatant into Th1 and Th2 cells. Naive CD4 T cells were cultured and supernatant from 5XFAD mouse microbiota was added in the presence/absence of OM1 for 3 days. Gating of Th1 (CD4 ⁺ IFN-γ ⁺ ) and Th2 (CD4 ⁺ IL-4 ⁺ ) cells was performed by flow cytometry. Data are presented as mean ± standard error of the mean (mean ± sem); n=3 repetitions per group.

(bc) Vulcan plot shows the distribution of metabolites from raw gut fecal metabolomics data from 7-month-old WT and 5XFAD (Tg) mice (n=6-8) (b) and 7-month-old Tg mice treated with or not treated with OM1 (n=6) (c). Red dots indicate significant changes in metabolites. Significance is defined as P value < 0.05 according to Student's t-test and fold change (FC) < 0.83 or > 1.2 between (T) and wild type (WT). The x-axis represents log ₂ FC and the y-axis represents -log ₁₀ P.

(d-e) Heat map for seven hundred and eighty-six metabolites that were differentially regulated between Tg and WT mice (d), as well as 149 metabolites between Tg mice treated with OM1 and not treated with OM1 (e) (n=6-8). These metabolites were identified and annotated by matching the molecular weight (m/z) data of the significant peaks to the METLIN online database.

(f) Venn plot shows intestinal faecal metabolites that often decrease in levels when comparing Tg and WT mice (T_W) and Tg mice treated with or without OM1 (Ttreat_T) (n=6-8). One hundred and twenty-four metabolites had pattern reversal among the two comparisons, ie. metabolites that are either both high for T_W and low for Ttreat_T, or both low for T_W and high for Ttreat_T.

(g) The heat map shows 31 identified differentially regulated metabolites among the WT, Tg and Tg groups with OM1 administration (n=6-8) that can be compared to all three databases (Human Metabolites Database (HMDB), METLIN, Kyoto Encyclopedia of Genes and Genomes (KEGG)). Red, level up; blue, level down.

(h) Receiver operating characteristics (ROC) and area under the curve (AUC) for all amino acids during disease progression are calculated using a random forest algorithm.

(i) Effects of fecal microbiome transplantation (FMT) on blood levels of phenylalanine and isoleucine. Feces from 2 month old WT mice were transplanted into 7 month old Tg mice (n=6-7). For phenylalanine ***P < 0.001((F(2, 17)=26.59)). For isoleucine, **P<0.01 (Tg vs. WT), **P<0.01 (Tg+FMT vs. Tg) according to one-way ANOVA (F(2, 17)=8.181).

(j) Amino acid levels in blood samples from WT mice co-housed with WT and Tg at different months (M) of age. Red, increased level; blue, reduced level.

(k) Phenylalanine uptake by naive CD4 T cells. Naive CD4 T cells were cultured with/without ¹³ C-labeled phenylalanine for 0.5 h. Mass spectrometry of phenylalanine-related compounds was performed. ¹³ C-Phenylalanine was administered at a concentration of 5 mmol/L and is taken up by the L-type amino acid transporter.

Figure 12. JPH203, 50 mg/kg, effectively inhibits a portion of Th1 cells in the brain.

Figure 13. Trend in OTU levels in enterobacteria after OM1 administration compared to control - PCoA analysis of the effect of phenylalanine-degrading bacteria on fecal phenylalanine content 1 week after transplantation.

Figure 14. Tendency to change the relative content of enterobacteria after the introduction of OM1 compared with the control. Effect of phenylalanine-degrading bacteria on the proportion of Th1 cells in the blood one week after transplantation.

Figure 15. Change in the trend of the content of cytokines in the brain compared with the control after the introduction of OM1.

Figure 16. Change in the distribution of intestinal microbes before and after the use of agents used to regulate the relative content of microorganisms in the intestine: OM1 or fecal bacteria (complex of intestinal microorganisms).

Figure 17. Differences between type level and gender level for AD and HC, partially detailed. AD: patients with AD; HC: healthy controls.

Figure 18. Part of the significantly altered flora in AD and HC (genus and species level). AD: patients with AD; HC: healthy controls.

Figure 19. List of amino acids associated with AD. A multivariate exploratory analysis (Explorer) based on the ROC curve was used to analyze amino acids in the blood of wild-type and 5XFAD mice at different numbers of months of age and searched for potential combinations of amino acids as markers to distinguish wild-type mice from 5XFAD mice. Below is a list of the first 15 amino acids sorted by frequency of selection and all types.

Figure 20. 5XFAD mice at 6.5 months of age following 100 mg/kg OM1 administration for 1 month have blood amino acid levels that tend to recover to amino acid levels in wild-type mice.

Figure 21. 5XFAD mice at 6.5 months of age after administration of 100 mg/kg OM1 for 1 month have fecal amino acid levels that tend to recover to amino acid levels in wild-type mice.

Figure 22. List of cytokines, the levels of which were restored after the introduction of OM1. 5XFAD mice aged 6.5 were injected with 100 mg/kg OM1 for 1 month and had cytokines in the brain that tend to recover to cytokine levels in wild-type mice.

Figure 23. Trend in brain M1 cells in APP/PS1 mice at different months of age.

DETAILED DESCRIPTION OF THE INVENTION

Certain illustrative embodiments are described below to provide a thorough understanding of the principles of structure, function, preparation, and use of the products, methods, and uses described herein. One or more examples of these implementations are illustrated below. Those skilled in the art will appreciate that the products, methods, and uses specifically described herein and specifically illustrated in the accompanying drawings are non-limiting illustrative embodiments, and the scope of the present invention is limited only by the claims. Features illustrated or described together in one illustrative embodiment may be combined with features in other embodiments. Such modifications and changes are intended to be included within the scope of the present invention. All cited publications, patents and patent applications are incorporated herein by reference in their entirety.

In the context of the description of the present invention (especially in the context of the following claims), unless otherwise indicated in the present description, or unless the context clearly contradicts it, terms in the singular form should be interpreted as covering both the singular and the plural. Unless otherwise indicated, the terms "comprising", "having", "including", and "covering" are to be interpreted as open terms (i.e., "including but not limited to"), however, they also include partially closed or closed terms. "essentially consisting of" and "consisting of". Unless otherwise indicated in this specification, the description of a numerical range in this specification is intended to be used only as an abbreviation for independently referring to each individual value within a given range, and each individual value is included in this specification as if it were independently given in the present description. Unless otherwise indicated in the present description, or unless the context clearly contradicts it, all methods described in the present description may be performed in any suitable order. Unless otherwise indicated, the use of any and all examples or illustrative language (eg, "such as") given in the present description is only intended to better illustrate the present invention and does not limit the scope of the present invention. Nothing in the present description should be construed as indicating that any element not claimed in the claims is necessary for the practice of the present invention. All percentages are weight percentages and all weight percentages are based on the total weight of the composition (with any optional concentration and/or dilution). The expression "one or more" includes "two or more" and "three or more", and the like.

Preferred embodiments of the present invention are described in the present description. Upon reading the above description, modifications to the preferred embodiments may become apparent to those skilled in the art. The inventor believes that those skilled in the art will make proper use of such changes, and the inventor contemplates that the present invention will be carried out in a manner other than that specifically indicated herein. Thus, the present invention includes all modifications and equivalents of the subject matter described in the appended claims, permitted by applicable law. Moreover, unless otherwise indicated in the present description, or unless the context clearly contradicts it, the present invention covers any combination of all possible variants of the above elements.

When a sequence of values is given in this application, it should be understood that any given value may represent an upper or lower limit of a numerical range. It should also be understood that the present invention covers all such numerical ranges, i. a range having a combination of an upper limit and a lower limit, where the respective values of the upper limit and the lower limit may be any of the numerical values given herein. It should be understood that the range given in the present description. includes all values in the range. For example, 1-10 should be understood to include all of the values 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10, and include fractional values where appropriate. A range expressed by "up to" a certain value (e.g., up to 5) should be understood as all values (including the upper limit of the range) such as 0, 1, 2, 3, 4, and 5, and it includes fractional values in the respective cases. It should be understood that "not more than one week" or "within a week" includes 0.5, 1, 2, 3, 4, 5, 6 or 7 days. Likewise, the range defined by "at least" is to be understood to include lower values listed and all higher values.

Unless otherwise indicated, all percentages are weight/weight percentages.

As used in the context of the present invention, by "approximately/approximately" is meant to be within three standard deviations of the mean, or within a standard tolerance range in a particular area. In certain embodiments, "about" should be understood to mean a deviation of no more than 0.5. "Approximately/approximately" modifies all listed values after them. For example, "about 1, 2, 3" means "about 1", "about 2", "about 3".

Unless the context clearly indicates otherwise, the term "or" is used in the inclusive sense in the present description, meaning the term "and/or", and they can be used in the present description interchangeably.

The term "such as/for example/for example" is used herein to refer to the expression "such as/for example/for example, but not limited to", and they can be used interchangeably herein.

Those skilled in the art will appreciate that the technical features described in the various embodiments above may be used alone or in combination with the technical solutions of various aspects of the present invention.

The inventors used the 5XFAD transgenic (Tg) mouse model widely used in AD research due to its severe and accelerated cognitive decline. By analyzing the enterotype of Tg mice and WT mice at different stages of AD progression, it was found that the gut microbiota of Tg mice is highly dynamic (Fig. 1d). At 2–3 months of age, Bacteroidetes , Firmicutes , and Verrucomicrobia are the three most common bacterial types (46.8%, 32.3%, and 12.6%, respectively), while at 7–9 months of age, Firmicutes become the predominant bacteria. , while the content of Bacteroidetes and Verrucomicrobia is significantly reduced. This is in stark contrast to the gut microbiota of WT mice.

The inventors also analyzed peripheral immune cells Th1 and Th1 and microglial cells M1 and M2 and found that the two main subtypes of CD4+ cells (infiltrating Th1 and Th2 cells) showed similar dynamics with the two main subtypes of microglial cells (microglial cells M1 and M2) (fig. 1f and fig. 1j). In the early stage they are mainly Th2 cells and neuroprotective M2 microglial cells, and in the late stage they are mainly Th1 cells and pro-inflammatory M1 microglial cells. The inventors believe that as gut microbiota patterns change, the immune cell population tends to achieve Th1 and M1 predominance status.

The inventors also analyzed the correlation between gut microbiota content and brain cells in Tg mice, and also noted that the bacterial composition at an early stage (2-3 months) was highly correlated with the numbers of M2 and Th2 cells in the brain (Fig. 1k , top), while at the late stage (7-9 months), changes in the bacterial pattern are highly correlated with M1 and Th1 cells (Fig. 1k, bottom). Overall, these results indicate that during the progression of AD, gut bacteria are associated with peripheral immune cell infiltration and neuroinflammation.

Moreover, the inventors found that gut microbiota dysbiosis is required for the infiltration of various peripheral immune cells (including CD4+ and CD8+ T cells, B cells, natural killer (NK), neutrophils, dendritic cells (DC) and monocytes) into the brain. . Among them, Th1 cells are particularly notable because they are closely associated with the activation of M1 microglial cells during the progression of AD. In view of the generally recognized functional relationship between Th1 and M1 microglial cells in the brain, the inventors hypothesized that gut dysbiosis promotes Th1 cell infiltration by providing local interaction with M1 microglia, thereby triggering microglial differentiation into a pro-inflammatory state. Through a series of discoveries made during this study, understanding of this mechanism has increased. First, dynamic changes in the composition of the gut microbiota during the progression of AD are significantly associated with increased infiltration of Th1 cells. Second, reduction of the gut microbiota by administration of antibiotics blocked Th1 cell infiltration and subsequent activation of M1 microglia in AD mice (FIGS. 2a-c). Third, long-term exposure to fecal bacteria (co-housing experiment) and transplantation of fecal microbiota from AD mice significantly increased both Th1 cell infiltration (Fig. 2e) and M1 microglia activation, in WT mice, while transplantation of fecal microbiota WT mice to Tg mice reduced levels of Th1 cells in recipient Tg mice (Fig. 9c). The results of the inventor's study generally indicate that the gut microbiota is a trigger factor contributing to Th1/M1 microglia-induced neuroinflammation in the progression of AD.

The causal relationship between gut microbiota dysbiosis and neuroinflammation in AD is still unclear. In this study, the inventors found that over 100 metabolites were significantly altered in AD mice compared to WT mice. Among them, the most pronounced changes occurred among the amino acids, especially the amino acids in the phenylalanine-related cascade. The inventors were able to confirm that phenylalanine and isoleucine were elevated in the feces and blood of AD mice relative to WT mice. Functional evaluation, both in vitro and in vivo, demonstrated the role of phenylalanine and isoleucine in promoting the differentiation and proliferation of peripheral inflammatory Th1 cells. The use of antibiotics to reduce the gut microbiota resulted in simultaneous decreases in blood levels of phenylalanine and isoleucine, infiltration of Th1 cells, and activation of M1 cells. These data highlight the role of abnormal phenylalanine and isoleucine production in the gut microbiota in stimulating Th1-mediated neuroinflammation. In accordance with this view, the inventors found that the concentration of phenylalanine/isoleucine and the number of Th1 cells in the blood of patients with MCI caused by AD, are higher than in the group of healthy controls.

New emerging data show that polysaccharides or oligosaccharides have the advantage of regulating the gut microbiota. Mannuronic acid oligosaccharides are carbohydrate-based anti-AD drugs. In a phase III clinical trial recently completed in China, they have been shown to improve cognition in patients with mild to moderate AD. mannuronic acid oligosaccharides are well tolerated and have similar safety to placebo controls. In this trial, the inventors found that OM1 was effective in restoring the gut microbiota (FIGS. 4a-b; FIG. 10a), reducing fecal and blood phenylalanine and isoleucine (FIGS. 5c-d), and reducing Th1-mediated neuroinflammation (FIGS. 4g-i). It should be noted that Tg feces injected with OM1 can largely mimic the therapeutic effect of OM1 treatment itself, and antibiotic treatment eliminates their therapeutic effect. These data provide important evidence that the therapeutic effect of OM1 is mainly mediated by restoration of the gut microbiota. Thus, OM1 may provide an attractive approach for microbiota-focused AD treatment strategies that merit further investigation.

All these data allow the inventors to propose a conceptual breakthrough in understanding the pathogenesis of AD. AD is not only a local Aβ-mediated disease of the brain, but its development also requires systemic interactions between the gut, brain, and intermediate inflammatory factors (FIG. 6). In the case of Aβ deposition, the altered composition of the gut microbiota during the progression of AD causes an abnormal increase in amino acid levels (especially phenylalanine and isoleucine). These amino acids promote the infiltration of peripheral Th1 cells into the brain through the bloodstream. Infiltrating peripheral Th1 cells can locally interact with M1 microglia in the brain, leading to pathological neuroinflammation and cognitive decline. These data on the pathogenesis of AD can be used to restore the gut microbiota to promote an anti-inflammatory response and provide new therapeutic solutions.

The results of the research of the inventor can be revolutionary for the diagnosis and treatment of AD. A composition of specific bacteria (eg, Th1/M1 associated bacteria), amino acids (eg, phenylalanine and isoleucine), and brain-infiltrating immune cells (eg, Th1 cell predominance), or a combination of one or more of these, can be used as early diagnostic biomarkers for patients with MCI caused by AD, and this deserves further confirmation in a large sample of patients with AD.

More importantly, the established microbiota-focused anti-AD effect of OM1 will open up new therapeutic approaches for the treatment of AD by reorganizing the gut microbiota, and will guide the development of effective therapies in the future by exploring the highly unexplored sugar chemistry.

Each of the numerous characteristic gut microorganisms, amino acids, immune cells, and cytokines associated with the brain-gut axis, identified by the inventors, constitutes a gut microbial profile, an amino acid profile, an immune cell profile, and a cytokine profile. One or more of these profiles (such as the gut microbial profile) show differences between normal and diseased individuals. The present invention aims to detect or regulate the condition of an individual by detecting or regulating one or more of these profiles (such as the gut microbial profile). In some embodiments, for diagnostic purposes, a profile (e.g., gut microbial profile) of an individual may be determined for comparison with a profile (e.g., gut microbial profile) with normal characteristics of a corresponding normal individual and/or a profile (e.g., gut microbial profile) with disease characteristics. of the corresponding diseased individual to determine whether the individual's condition is normal or diseased, thereby diagnosing the individual. In some embodiments, for therapeutic purposes, the profile of an individual with disease characteristics can be adjusted to that of a corresponding normal individual, such that the disease state of the individual can be adjusted to a normal state, thereby treating the individual.

Thus, in one aspect, the present invention relates to the use of an agent for inhibiting amino acid uptake by naive T cells in the peripheral blood of a mammal for the manufacture of a medicament for the treatment of Alzheimer's disease in an individual.

In another aspect, the present invention provides a pharmaceutical composition for the treatment of Alzheimer's disease in a subject, comprising an effective amount of an agent for inhibiting amino acid uptake by naive T cells in the peripheral blood of a mammal.

In some embodiments, the amino acid is one or more amino acids selected from the following: 4-OH proline, acetylornithine, alanine, alpha-aminoadipic acid, asparagine, aspartic acid, asymmetric dimethylarginine, beta-alanine, carnosine, citrulline, creatinine, GABA, glutamic acid, glutamine, glycine, histidine, hypotaurine, isoleucine, kynurenine, leucine, lysine, methionine, methionine sulfoxide, ornithine, phenylalanine, pipecolic acid, proline, putrescine, pyroglutamic acid, serine, serotonine, taurine, threonine, tryptophan, tyrosine and valine; preferably one or more selected from phenylalanine, isoleucine, serotonin, histidine and acetylornithine; more preferably phenylalanine and/or isoleucine; most preferably phenylalanine.

In some embodiments, the agent inhibits amino acid uptake by naive T cells by inhibiting amino acid transport into the naive T cell by a transporter.

In some embodiments, the carrier is SLC7A5.

In some embodiments, the agent includes one or more selected from JPH 203, BCH, and KMH-233.

In some embodiments, the agent reduces the proportion of pro-inflammatory Th1 cells among CD4+ T cells in a sample from an individual by about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100% or more; and/or makes the proportion of pro-inflammatory Th1 cells in CD4+ T cells close to or equal to the corresponding proportion of pro-inflammatory Th1 cells in CD4+ T cells of the corresponding normal individual.

In some embodiments, the agent reduces the relative uptake of amino acids by naïve T cells by approximately 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, 200, 205, 210, 215, 220, 225, 230, 235, 240, 245, 250, 255, 260, 265, 270, 275, 280, 285, 290, 295, 300 or more; and/or makes the relative level of amino acid uptake by naive T cells close to or equal to the corresponding relative level of amino acid uptake by naive T cells of the corresponding normal individual.

In another aspect, the present invention relates to a method for screening a drug candidate that can be used to treat Alzheimer's disease, comprising:

a) administering the test agent in in vivo or in vitro models with the SLC7A5 transporter, and

b) selecting a test agent that inhibits the SLC7A5 transporter as a drug candidate that can be used to treat Alzheimer's disease.

In some embodiments, the method further comprises administering JPH 203 as a positive control in an in vivo or in vitro model with the SLC7A5 transporter, preferably selecting a test agent that inhibits the SLC7A5 transporter substantially comparable to JPH 203.

In some embodiments, the model is an in vivo model.

In some embodiments, the method further comprises administering the selected test agent to the SLC7A5 transporter in vivo model to confirm where the selected test agent reduces the proportion of pro-inflammatory Th1 cells among CD4+ T cells in the sample from the in vivo model by approximately 1, 2, 3, 4 , 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29 , 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54 , 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79 , 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100% or more; and/or makes the proportion of pro-inflammatory Th1 cells among CD4+ T cells close to or equal to the corresponding proportion of pro-inflammatory Th1 cells among CD4+ T cells in a corresponding normal in vivo model.

In some embodiments, the method further comprises administering the selected test substance in an in vivo or in vitro model with the SLC7A5 transporter to confirm where the selected test substance reduces the relative level of amino acid uptake by naïve T cells by approximately 5, 10, 15, 20, 25, 30 , 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155 , 160, 165, 170, 175, 180, 185, 190, 195, 200, 205, 210, 215, 220, 225, 230, 235, 240, 245, 250, 255, 260, 265, 270, 275, 280 , 285, 290, 295, 300 or more; and/or makes the relative level of amino acid uptake by naive T cells close to or equal to the corresponding relative level of amino acid uptake by naive T cells in a corresponding normal in vivo or in vitro model.

In some embodiments, the amino acid is one or more selected from the following: 4-OH proline, acetylornithine, alanine, alpha-aminoadipic acid, asparagine, aspartic acid, asymmetric dimethylarginine, beta-alanine, carnosine, citrulline, creatinine, GABA, glutamic acid, glutamine, glycine, histidine, hypotaurine, isoleucine, kynurenine, leucine, lysine, methionine, methionine sulfoxide, ornithine, phenylalanine, pipecolic acid, proline, putrescine, pyroglutamic acid, serine, serotonine, taurine, threonine, tryptophan, tyrosine and valine ; preferably one or more selected from phenylalanine, isoleucine, serotonin, histidine and acetylornithine; more preferably phenylalanine and/or isoleucine; most preferably, phenylalanine.

In another aspect, the present invention relates to a method of treating a patient having Alzheimer's disease, comprising:

administering an agent for inhibiting amino acid uptake by naive T cells in the peripheral blood of a mammal to a patient such that the proportion of pro-inflammatory Th1 cells among the CD4+ T cells in the patient is regulated to be close to or equal to the proportion of pro-inflammatory Th1 cells among the CD4+ T cells -cells in the corresponding normal sample.

In a further aspect, the present invention relates to a method of treating a patient having Alzheimer's disease, comprising:

administering to a patient an agent for inhibiting amino acid uptake by naive T cells in the peripheral blood of a mammal, so that the relative level of amino acid uptake of naive T cells in the patient is adjusted to be close to or equal to the corresponding relative level of amino acid uptake by naive T cells in the corresponding normal sample.

In some embodiments, the carbohydrate drug is OM1.

In some embodiments, the carbohydrate drug is not OM1.

In some embodiments, the mannuronic acid oligosaccharide is OM1.

In some embodiments, the mannuronic acid oligosaccharide is not OM1.

The structure and method of obtaining mannuronic acid oligosaccharides are described in many prior art documents. The prior art patent CN2016100697039 describes a method for producing oligomannuronic acid, the prior art patent CN2017107964853 describes a method for determining the weight average molecular weight and amount of mannuronic acids, the prior art patent CN2017114675966 describes the composition of mannuronic acid and its preparation, all of which are incorporated herein by reference. in full. OM1 as used herein is composition A according to CN2018107213276 ("alginic acid oligosaccharide composition"), which is incorporated herein by reference.

Microbiota

The present description describes methods and compositions that include altering the microbiota of the intestinal tract of an individual. The term "microbiota" is used to refer to one or more bacterial communities that can be found or exist (colonize) in the intestinal tract of an organism. It can be used interchangeably with "microbes/microorganisms" or "intestinal microbes/microorganisms" in the present specification. When referring to more than one microbiota, the microbiota may be of the same type (strain) or may be a mixture of groups such as Bacteroidetes, Proteobacteria and/or Firmicutes or subgroups thereof (class, order, family, genus, species). The microbiota may be a mixture of microorganisms at one level, such as Bacteroidetes , Proteobacteria , and/or Firmicutes ; it may also be a mixture of different levels of microorganisms such as Bacteroidetes and Proteobacteria .

In some embodiments, the gut microbes are selected from one or more selected from the phylum, class, order, family of genus or species listed in Table 1, or combinations thereof.

In some embodiments, the gut microbes are selected from one or more selected from the phylum, class, order, family, genus, or species listed in Table 2, or a combination thereof.

In some embodiments, the gut microbes are selected from one or more selected from Firmicutes , Bacteroidetes , Proteobacteria , Actinobacteria , Fusobacteria , Cyanobacteria , Verrucomicrobia , or combinations thereof.

In some embodiments, the gut microbes are one or more selected from the type shown in the table below, or a combination thereof:

type Firmicutes type Bacteroidetes type Proteobacteria type Actinobacteria type Fusobacteria type cyanobacteria type Verrucomicrobia

In some embodiments, the gut microbes are one or more selected from the classes shown in the following table, or combinations thereof:

Class bacteroidia Class Clostridia Class Gamma Proteobacteria Class Bacilli Class Negativicutes Class Actinobacteria Class Fusobacteria Class Beta Proteobacteria Class Alpha Proteobacteria

In some embodiments, the gut microbes are one or more selected from the orders in the table below, or combinations thereof:

order Bacteroidales order Clostridiales order Enterobacterials order Selenomonadales order Lactobacillales order Bifidobacterials order Fusobacterials order Burkholderiales order Bacillales

In some embodiments, the gut microorganism is one or more selected from the families shown in the table below, or combinations thereof:

family Rikenellaceae family Ktedonobacteraceae family Nannocystaceae

In some embodiments, the gut microbes are one or more selected from the genera listed in the table below, or combinations thereof:

genus Lachnospiraceae_NK4A136_group genus Alistipes genus Ruminococcus_1 genus Ruminococcaceae_UCG-002 genus Ruminococcaceae_UCG-005 genus Coprococcus_2 genus Tyzzerella_4 genus Lachnospiraceae_UCG-001 genus Anaerotruncus genus Cloacibacterium genus norank_f__Ktedonobacteraceae genus Nannocystis genus norank_f__Hydrogenophilaceae

In some embodiments, the gut microbes are one or more selected from the following, or combinations thereof:

view unclassified_g__Subdoligranulum View unclassified_g__Alistipes View uncultured_organism_g__Parasutterella View unclassified_g__Tyzzerella_4 View uncultured_organism_g__Ruminococcaceae_UCG-005 View uncultured_organism_g__Anaerotruncus View uncultured_Alistipes_sp._g__Alistipes View Lachnospiraceae_bacterium_TF01-11 View unclassified_g__Anaerotruncus View unclassified_g__norank_o__Mollicutes_RF9 View uncultured_bacterium_g__Family_XIII_AD3011_group View uncultured_bacterium_g__norank_f__Christensenellaceae View uncultured_bacterium_g__Cloacibacterium View uncultured_organism_g__Peptococcus View Mycobacterium_celatum_g__Mycobacterium View unclassified_g__Oceanobacillus View Alistipes_putredinis_DSM_17216 View Prevotella_loescheii View uncultured_bacterium_g__norank_o__MBA03 View Eubacterium_brachy View uncultured_bacterium_adhufec108 View uncultured_Clostridiales_bacterium_g__norank_f__Ktedonobacteraceae View Nannocystis_pusilla View bacterium_2013Ark19i View Auxenochlorella_protothecoides_g__norank View uncultured_ Bacteroidetes _bacterium_g__Dinghuibacter

The inventors have found that a variety of gut microbes are involved in the brain-gut axis in accordance with the present invention. As shown in the examples, between WT mice and TG mice, the levels of some gut microbes were altered and after administration of, for example, OM1, the levels of these gut microbes were restored to levels in WT mice. Such gut microbes constitute the profile of gut microbes. As mentioned earlier, such a profile can be used for diagnostic and/or therapeutic purposes.

In some embodiments, a change (e.g., increase or decrease) in the level of one or more (i.e., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 , 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 , 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65 , 66 or 67) of the gut microbes selected from the above table in an individual relative to the level of the corresponding gut microbes in the corresponding normal individual indicates that the individual is at risk of AD or has AD. In one embodiment, a change (e.g., increase or decrease) in level 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 , 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44 , 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69 , 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94 , 95, 96, 97, 98, 99, or 100% of gut microbes in a gut microbial profile consisting of gut microbes of the type, class, order, family, genus, and species listed in the table above in an individual relative to the level of the respective gut microbes in the respective normal individual indicates that the individual is at risk for AD or has AD.

In some embodiments, a change (e.g., increase or decrease) in the level of one or more (i.e., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 , 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40 , 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65 , 66 or 67) of gut microbes selected from the type, class, order, family, genus and species from the above table in an individual with AD to the level of the corresponding gut microbes in the corresponding normal individual relative to the level of the corresponding intestinal microbes in the corresponding normal individual indicates that that the individual is receiving appropriate treatment. In one embodiment, a change (e.g., increase or decrease) in level 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 , 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44 , 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69 , 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94 , 95, 96, 97, 98, 99, or 100% of gut microbes in a gut microbial profile consisting of gut microbes of the type, class, order, family, genus, and species listed in the table above in an individual with AD to the level of the corresponding gut microbes in a corresponding normal individual relative to the level of corresponding intestinal microbes in a corresponding normal individual indicates that the individual is receiving appropriate treatment.

The relative content of gut microbes can be changed using the composition or method of the present invention as follows: administering a composition containing the appropriate microbiota or administering a composition containing one or more compounds that significantly increase and/or reduce the relative content of the relevant intestinal microbes.

Bacteroidetes include three major classes of bacteria: Bacteroidia , Flavobacteri a, and Sphingobacteria . They are common in the environment, including soil, silt, sea water, and the intestines and skin of animals.

Proteobacteria are the largest type of bacteria. These organisms exhibit extremely high metabolic diversity and reflect the medical, industrial and agricultural importance of most of the known bacteria. This is important from an evolutionary, geological and ecological point of view. All Proteobacteria are gram-negative and their outer wall is composed of lipopolysaccharide. Many of them have gas vesicles, flagella, or can move by sliding; they may have stalks, other processes, or have the ability to form multicellular fruiting bodies. Most are facultative or obligate anaerobic, autotrophic and heterotrophic, but there are exceptions. Some species are capable of photosynthesis, while others store sulfur inside or outside the cell.

Firmicutes are a type of mostly Gram-positive bacteria. However, some have porous pseudoouter membranes which make them Gram-negative. Scientists once classified Firmicutes as including Gram-positive bacteria, but have recently identified them as a major group with a related form called the low-G+C form. They are mostly round cells called cocci (single cocci) or are rod-shaped (bacilli). Many Firmicutes produce endospores that are desiccation tolerant and can survive in extreme environments, allowing them to survive in a variety of environmental conditions.

The method for modifying the microbiota may also include measuring the relative abundance of one or more gut microorganisms in a sample from an individual. During last generation sequencing, multiple sequences are determined for each sample. After pre-processing, sequence clustering algorithms are used to combine sequences with more than 97% similarity to obtain an OTU. The OTU_table can then be obtained, which is a matrix that indicates how many reads each OTU contains in each sample, i.e. each pattern corresponds to the number of sequence reads in each OTU. The relative content corresponds to 100% for each sample (each row), and calculate the percentage of the number of readings in each OTU relative to the number of all readings in the sample. Thus, relative abundance refers to the relative percentage of the number of sequences of each microorganism in a sample. The relative abundance can be detected by the method described herein, or by a method known in the art that can be used to detect it, such as 16S rRNA gene detection.

The relative content of intestinal microbes can be determined by obtaining samples from the individual. The sample may be saliva, feces, and contents of the stomach, intestines, and/or rectum; tissue samples from the digestive tract (such as tissue from the mouth, esophagus, stomach, small intestine, ileum, caecum, colon, and/or rectum); ascitic fluid in the gastrointestinal tissues; and any other samples that may be used by individuals familiar with microbiota analysis.

The relative content of one or more types of intestinal microbes can be compared with the normal relative content of the corresponding intestinal microbes. The normal relative content may be that of one or more individuals of similar age, sex, race, and the like. The normal relative content may be the content in healthy individuals of similar age, sex, race, etc., who have responded to or demonstrated favorable results of treatment or therapeutic intervention. In a specific embodiment, the normal relative content is the relative content of intestinal microbes in healthy individuals.

The methods and compositions of the invention may involve changing the relative content of one or more intestinal microbes. Exemplary embodiments may involve methods or compositions for changing the relative abundance of gut microbes by administering the gut microbes to an individual. Depending on the desired outcome (e.g., reduced metabolite levels, reduced lymphocytic infiltration in the brain, reduced microglial activation, reduced neuroinflammation, improved cognitive function, and alleviated symptoms of Alzheimer's disease) and specific individuals, the relative content of gut microbes can be adjusted by 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99-100% or more, or to a range consisting of the end points of the above values or any values in between, such as from about 7% to about 28%, etc., or by about 7%, 14%, 21%, 28%, etc. .; and/or it is possible to provide the relative content of intestinal microbes in the individual, close to or reaching the relative content of the corresponding intestinal microbes in the corresponding normal individual.

As described herein, the present invention is directed to regulating a score that differs from a corresponding score in a corresponding normal individual towards a corresponding score in a corresponding normal individual, so that the score after regulation is close to or reaches the corresponding score in a corresponding normal individual. This regulation is applicable to various indicators to be regulated or regulated, as described in the present description. Obviously, it is ideal to achieve the corresponding indicator in the corresponding normal individual, however, it is also desirable to approximate the corresponding indicator in the corresponding normal individual. Thus, the present invention is directed to obtaining one or more indicators in an individual in which one or more indicators are intended to be adjusted so that they are close to or achieve the corresponding indicators in corresponding normal individuals. As used in the context of the invention, the term "close to or reaches" means that the difference between the score before regulation and the corresponding score in the corresponding normal individual is reduced by an amount greater than or equal to about 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 100%, or a range consisting of the end points of the above values or any values in between, such as from about 7% to about 28%, and the like. regarding the difference after regulation. When the difference between the score before regulation and the corresponding score in the corresponding normal individual is reduced by about 100% relative to the difference after regulation, the adjustable score reaches the corresponding score in the corresponding normal individual. Those skilled in the art will appreciate that the exact amount of difference depends on, for example, the object of regulation, the type of indicator, the method of measurement, and the like.

An agent capable of regulating one or more parameters in an individual so that they are close to or achieve the corresponding parameters in the corresponding normal individual is therapeutically desirable. The choice of such agents may be based, for example, on agents (such as OM1) that serve as a positive control. Preferably, a test substance is selected that regulates the respective parameter substantially comparable to the agent used as a positive control (eg, OM1).

On the other hand, one or more scores of an individual in whom regulation of one or more scores is required is substantially comparable to a reference score (e.g., benchmark for diagnosing Alzheimer's disease or identifying carbohydrate drug-responsive patients in Alzheimer's disease patients) that may indicate that the individual is at risk for Alzheimer's disease or has Alzheimer's disease.

As used herein, the term "substantially the same" refers to the standardization of a test score relative to a reference score (i.e., the benchmark is taken as 100%), the difference between the test score and the reference score is less than or equal to about 0.1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100% , consisting of the end points of the above values or any values in between, for example, from about 7% to about 28%, etc., or about 7%, 14%, 21%, 28%, etc. Those skilled in the art will appreciate that the exact amount of the difference will depend on, for example, the object to be controlled, the type of indicator, the method of measurement, and the like.

In some embodiments, the agent for regulating the relative content of intestinal microbes comprises a complex of intestinal microbes. In some embodiments, the gut microbial complex includes microorganisms derived from fecal material or a bacterial library. In some embodiments, the implementation of the fecal material comes from a normal individual or patient with Alzheimer's disease.

Bacterial Library Definition: To obtain information on the species classification corresponding to each OTU, the Bayesian RDP classification algorithm is used to perform a taxonomic analysis at the similarity level of 97% representative OTU sequences and the community composition for each sample is calculated at each classification level (domain, kingdom, phylum, class, order, family, genus, species). The taxonomic comparison database of species used for the analysis of 16S bacterial flora is silva132/16S:silva132/16S (http://www.arb-silva.de).

Involved metabolites

The inventor has found that certain gut microbial metabolites, such as amino acids, are involved in the AD brain-gut axis investigated in the present invention. These amino acids may be, for example, one or more selected from the following table; preferably one or more selected from phenylalanine, isoleucine, serotonin, histidine and acetylornithine; more preferably phenylalanine and/or isoleucine; most preferably phenylalanine.

4-OH proline Acetylornithine Alanine Alpha-aminoadipic acid Asparagine Aspartic acid Asymmetric dimethylarginine beta alanine Carnosine citrulline Creatinine GABA Glutamic acid Glutamine Glycine Histidine hypotaurine Isoleucine Kynurenine Leucine Lysine Methionine Methionine sulfoxide Ornithine Phenylalanine pipecolic acid Proline Putrescine Pyroglutamic acid Serene Serotonin Taurine Threonine tryptophan Tyrosine Valine

The inventors have found that various amino acids are involved in the brain-gut axis according to the present invention. As shown in the examples, between WT mice and TG mice, the levels of some amino acids were altered and after administration of, for example, OM1, the levels of these amino acids recovered in the direction of the levels in WT mice. Such amino acids constitute the amino acid profile. As mentioned earlier, such a profile can be used for diagnostic and/or therapeutic purposes. In some embodiments, a change (e.g., increase or decrease) in the level of one or more (i.e., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 , 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35 or 36) amino acids selected from the above table , in an individual relative to the level of the corresponding amino acids in a corresponding normal individual indicates that the individual is at risk of AD or has AD. In one embodiment, a change (e.g., increase or decrease) in level 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 , 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44 , 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69 , 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94 , 95, 96, 97, 98, 99 or 100% amino acids in the amino acid profile of the amino acids in the above table in an individual relative to the level of the corresponding amino acid in the corresponding normal individual indicates that the individual is at risk of having AD or has AD.

In some embodiments, a change (e.g., increase or decrease) in the level of one or more (i.e., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 , 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35 or 36) amino acids selected from the above table , in an individual having AD, relative to the level of the corresponding amino acid in the corresponding normal individual in the direction of the level of the corresponding amino acid in the corresponding normal individual indicates that the individual is being treated appropriately. In one embodiment, a change (e.g., increase or decrease) in level 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 , 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44 , 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69 , 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94 , 95, 96, 97, 98, 99 or 100% amino acids in the amino acid profile consisting of the amino acids in the above table in an individual with AD, relative to the level of the corresponding amino acids in the corresponding normal individual, in the direction of the level of the corresponding amino acids in the corresponding normal individual , indicates that the individual is being treated appropriately.

The inventors have found that the level of one or more amino acids in the above table in an individual does not correspond to the corresponding amino acid level in a corresponding normal individual, which may be due to the disease state of the individual. When an individual's amino acid level is lower than the corresponding amino acid level of a corresponding normal individual, the amino acid level is considered to be upregulated. When an individual's amino acid level is higher than the corresponding amino acid level in a corresponding normal individual, the amino acid level is considered to be downregulated.

In some embodiments, the level of one or more amino acids in the table above is lower than the corresponding amino acid level in a corresponding normal individual. In some embodiments, the level of one or more amino acids in the above table is higher than the corresponding amino acid level in the corresponding normal individual. In some embodiments, the level of one or more amino acids in the above table is lower than the corresponding amino acid level in the corresponding normal individual, while the level of another one or more amino acids is higher than the corresponding amino acid level in the corresponding normal individual. Upregulation or downregulation may depend on, for example, the object to be regulated, the type of indicator, the method of measurement, and the like.

In some embodiments, the implementation of the level of glutamine is lower than the corresponding level of this amino acid in the corresponding normal individual. In some embodiments, the level of methionine is lower than the corresponding level of that amino acid in a corresponding normal individual. In some embodiments, the levels of both glutamine and methionine are lower than the corresponding levels of these amino acids in a corresponding normal individual.

In some embodiments, the implementation of the level of glutamine is higher than the corresponding level of this amino acid in the corresponding normal individual. In some embodiments, the level of methionine is higher than the corresponding level of that amino acid in a corresponding normal individual. In some embodiments, the levels of both glutamine and methionine are higher than the corresponding levels of these amino acids in a corresponding normal individual.

In some embodiments, the level of one, two, three, four, or five of phenylalanine, isoleucine, serotonin, histidine, and acetylornithine is higher than the corresponding level of these amino acids in a corresponding normal individual. In some embodiments, the level of phenylalanine and/or isoleucine is higher than the corresponding level of these amino acids in a corresponding normal individual. In some embodiments, the level of phenylalanine is higher than the corresponding level of that amino acid in a corresponding normal individual.

In some embodiments, the levels of both glutamine and methionine are lower than the corresponding levels of these amino acids in a corresponding normal individual, while the level of one or more of 4-OH proline, acetylornithine, alanine, alpha-aminoadipate, asparagine, aspartic acid, asymmetric dimethylarginine, beta-alanine, carnosine, citrulline, creatinine, GABA, glutamic acid, glycine, histidine, hypotaurine, isoleucine, kynurenine, leucine, lysine, methionine sulfoxide, ornithine, phenylalanine, pipecolic acid, proline, putrescine, pyroglutamic acid acid, serine, serotonin, taurine, threonine, tryptophan, tyrosine and valine is higher than the corresponding level of these amino acids in the corresponding normal individual.

In some embodiments, the level of one or more of 4-OH proline, acetylornithine, alanine, alpha-aminoadipate, asparagine, aspartic acid, asymmetric dimethylarginine, beta-alanine, carnosine, citrulline, creatinine, GABA, glutamic acid, glutamine, glycine, histidine , hypotaurine, isoleucine, kynurenine, leucine, lysine, methionine, methionine sulfoxide, ornithine, phenylalanine, pipecolic acid, proline, putrescine, pyroglutamic acid, serine, serotonine, taurine, threonine, tryptophan, tyrosine and valine is higher than the corresponding level these amino acids in the corresponding normal individual.

In some embodiments, the level of one or more amino acids from the table above is increased. In some embodiments, the level of one or more amino acids from the above table is reduced. In some embodiments, the level of one or more amino acids from the table above is increased while the level of another one or more amino acids is decreased. In some cases, the increase or decrease in the level may depend on, for example, the subject being regulated, the type of indicator, the method of measurement, and the like.

In some embodiments, the implementation of the level of glutamine is increased. In some embodiments, the level of methionine is increased. In some embodiments, both glutamine and methionine levels are increased.

In some embodiments, the implementation of the level of glutamine is reduced. In some embodiments, the level of methionine is reduced. In some embodiments, both glutamine and methionine levels are reduced.

In some embodiments, the level of one, two, three, four, or five of phenylalanine, isoleucine, serotonin, histidine, and acetylornithine is reduced. In some embodiments, the level of phenylalanine and/or isoleucine is reduced. In some embodiments, the level of phenylalanine is reduced.

In some embodiments, both glutamine and methionine are elevated while one or more of their 4-OH proline, acetylornithine, alanine, alpha-aminoadipate, asparagine, aspartic acid, asymmetric dimethylarginine, beta-alanine, carnosine, citrulline, creatinine, GABA, glutamic acid, glycine, histidine, hypotaurine, isoleucine, kynurenine, leucine, lysine, methionine sulfoxide, ornithine, phenylalanine, pipecolic acid, proline, putrescine, pyroglutamic acid, serine, serotonine, taurine, threonine, tryptophan, tyrosine and valine is reduced.

In some embodiments, the level of one or more of 4-OH proline, acetylornithine, alanine, alpha-aminoadipate, asparagine, aspartic acid, asymmetric dimethylarginine, beta-alanine, carnosine, citrulline, creatinine, GABA, glutamic acid, glutamine, glycine, histidine , hypotaurine, isoleucine, kynurenine, leucine, lysine, methionine, methionine sulfoxide, ornithine, phenylalanine, pipecolic acid, proline, putrescine, pyroglutamic acid, serine, serotonine, taurine, threonine, tryptophan, tyrosine and valine is reduced. The inventor has found that immune cells, such as naïve T cells or undifferentiated T cells, take up amino acids (as exemplified by phenylalanine and isoleucine) in some cases, and, for example, differentiate into certain types of T cells, such as Th1 cells , via certain transporters such as SLC7A5 as an example. The inventors have found that preventing differentiation into Th1 cells, which results in a Th1-dominant state, can treat Th1-dominated diseases in various ways. Such measures include, but are not limited to, reducing the level of the respective amino acids, preventing immune cells from taking up the respective amino acids, and the like.

SLC7A5 is referred to as L-type amino acid transporter 1 (LAT1) and belongs to the APC superfamily. It forms a heterodimeric amino acid transporter that interacts with the CD98 (SLC3A2) glycoprotein via conserved disulfide bonds. CD98 (4F2hc, SLC3A2) is a type II glycoprotein that acts as a chaperone protein for LAT1, stabilizing and promoting its translocation to the plasma membrane. This complex is responsible for the uptake of essential amino acids in key areas of the body such as the placenta and the blood-brain barrier. The substrate includes a series of large neutral amino acids such as tyrosine, leucine, isoleucine, valine and phenylalanine, as well as drugs including L-DOPA and gabapentin.

Various agents (such as enzymes) can be used to degrade amino acids to reduce the levels of the corresponding amino acids, thereby reducing the differentiation of naïve T cells into Th1 cells. The enzymes shown in the table below can be used to degrade the corresponding amino acids such as phenylalanine and isoleucine. Present enzymes can be delivered to the appropriate areas in the individual in various ways, for example, in the intestine or peripheral circulation (such as peripheral blood), for the degradation of amino acids. For example, the enzyme can be delivered to an appropriate area by delivering an enzyme-expressing microorganism (eg, Escherichia coli ) to an appropriate area to express the enzyme in the corresponding area. The microorganism may express one or more of these enzymes. Those of skill in the art will appreciate that any microorganism that can be delivered to the area of interest by a variety of routes (eg, orally) can be used to deliver the enzyme without losing the ability to express the enzyme in the area. For example, Escherichia coli engineered to express an enzyme to degrade phenylalanine was used as a phenylalanine-degrading bacterium that was orally administered to mice to reduce phenylalanine in mice (as shown by fecal phenylalanine) and reduce the proportion of Th1 cells (as shown by detecting the proportion of Th1 cells in peripheral blood).

Enzymes that can be used to degrade phenylalanine

Convertible Products metabolic enzymes 1 Tyrosine Phenylalanine-4-hydroxylase, PAH，preferred 2 2-phenylacetamide Phenylalanine-2-monooxygenase, PAO Catalase-peroxidase, katG 3 Phenylacetaldehyde Phenylacetaldehyde synthase, PAAS 4 Phenylethylamine Aromatic L-Amino Acid/L-Tryptophan Decarboxylase, DDC，Preferred Phenylalanine decarboxylase, AADC 5 N-acetyl-L-phenylalanine Phenylalanine-N-acetyltransferase 6 Phenylpyruvate Aspartate aminotransferase, AST，preferred Tyrosine aminotransferase, TAT，preferred L-amino acid oxidase, IL4I1，preferred Phenylalanine dehydrogenase Aromatic amino acid transaminase Histidinol phosphate aminotransferase Aromatic amino acid aminotransferase II, AR09 7 D-phenylalanine Phenylalanine racemase 8 Trans-cinnamate Phenylalanine ammonia lyase, PAL Phenylalanine/tyrosine ammonia lyase, PTAL

Enzymes that can be used to degrade isoleucine

Convertible Products metabolic enzymes 1 (S)-3-methyl-2-oxopentanoate Branched chain amino acid aminotransferase L-amino acid oxidase, IL4I1

Transporter inhibitors can be used to prevent immune cells from taking up appropriate amino acids by inhibiting naive T cell uptake of the corresponding amino acid by inhibiting the transporter (e.g., the common transporter SLC7A5 for phenylalanine and isoleucine), thereby reducing the differentiation of naive T cells into Th1 cells. Inhibitors that can be used to inhibit the SLC7A5 transporter include, but are not limited to, JPH 203, BCH, and KMH-233 known in the art. For example, as shown in Example 4, administration of the SLC7A5 inhibitor JPH 203 to mice significantly reduces the proportion of Th1 cells in the mouse brain.

JPH203 is a chemically synthesized small molecule compound available from J-Pharma of Japan (http://www.j-pharma.com/b3_e.html) that selectively inhibits LAT1, with CAS number 1037592-40-7 (https:/ /www.medkoo.com/products/9544).

BCH is a known LAT1 inhibitor with CAS number 20448-79-7 (https://www.tocris.com/cn/products/bch_5027).

KMH-233 is a known LAT1 inhibitor with CAS number 1941174-13-5 (https://www.medkoo.com/products/9545).

Those skilled in the art will recognize that methods that can be used to prevent naïve T cells from differentiating into Th1 cells are not limited to this. Any methods that can be used to prevent the influence of gut microbes and/or their metabolites on the differentiation of naive T cells into Th1 cells can be used to reduce the proportion of Th1, and alleviate or reverse the Th1-dominant state, as described in the present description.

The inventors have found that various cytokines are involved in the brain-gut axis in accordance with the present invention. As shown in the examples, between WT mice and TG mice, the levels of some cytokines changed and after administration of, for example, OM1, the levels of these cytokines were restored to levels in WT mice. Such cytokines constitute a cytokine profile. As mentioned earlier, such a profile can be used for diagnostic and/or therapeutic purposes.

In some embodiments, a change (e.g., increase or decrease) in the level of one or more (i.e., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 , 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 or 31) cytokines selected from the following: OPG, resistin, TARC, VEGF, chemerin, IL -9, MMP-2, VEGF-D, TCA-3, gp130, MMP-10, 6Ckine, VEGF-B, IL-22, IL-1a, IFNg R1, granzyme B, LIX, CT-1, CD27L, endoglin , TRANCE, MCSF, 4-1BB, leptin R, CD36, TremL 1, VEGF R2, TGFb1, IL-3 Rb, H60 in an individual relative to the level of the corresponding cytokine in the corresponding normal individual indicates that the individual is at risk of AD or has AD . In one embodiment, a change (e.g., increase or decrease) in level 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 , 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44 , 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69 , 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94 , 95, 96, 97, 98, 99 or 100% cytokines in a cytokine profile consisting of cytokines selected from the following: OPG, resistin, TARC, VEGF, chemerin, IL-9, MMP-2, VEGF-D, TCA- 3, gp130, MMP-10, 6Ckine, VEGF-B, IL-22, IL-1a, IFNg R1, granzyme B, LIX, CT-1, CD27L, endoglin, TRANCE, MCSF, 4-1BB, leptin R, CD36 , TremL 1, VEGF R2, TGFb1, IL-3 Rb, H60 in an individual relative to the level of the corresponding cytokine in the corresponding normal individual indicates that the individual is at risk of AD or has AD.

In some embodiments, a change (e.g., increase or decrease) in the level of one or more (i.e., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 , 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30 or 31) cytokines selected from the following: OPG, resistin, TARC, VEGF, chemerin, IL -9, MMP-2, VEGF-D, TCA-3, gp130, MMP-10, 6Ckine, VEGF-B, IL-22, IL-1a, IFNg R1, granzyme B, LIX, CT-1, CD27L, endoglin , TRANCE, MCSF, 4-1BB, leptin R, CD36, TremL 1, VEGF R2, TGFb1, IL-3 Rb, H60 in an individual with AD to the level of the corresponding cytokines in the corresponding normal individual relative to the level of the corresponding cytokines in the corresponding normal individual indicates that the individual is receiving appropriate treatment. In one embodiment, a change (e.g., increase or decrease) in level 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 , 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44 , 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69 , 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94 , 95, 96, 97, 98, 99, or 100% cytokines in a gut microbial profile composed of cytokines selected from the following: OPG, resistin, TARC, VEGF, chemerin, IL-9, MMP-2, VEGF-D, TCA -3, gp130, MMP-10, 6Ckine, VEGF-B, IL-22, IL-1a, IFNg R1, granzyme B, LIX, CT-1, CD27L, endoglin, TRANCE, MCSF, 4-1BB, leptin R, CD36, TremL 1, VEGF R2, TGFb1, IL-3 Rb, H60 in an individual with AD to the level of the corresponding intestinal microbes in the corresponding normal individual indicates that the individual is receiving appropriate treatment.

The present invention relates to a composition that can directly or indirectly change the relative content of intestinal microbes to a given level (such as a therapeutic level) for a given period of time (for example, until the application of the next dose). Target levels can be obtained by measuring the relative microbiota content that resulted in a therapeutic response (e.g., reduced metabolite levels, decreased lymphocyte infiltration into the brain, decreased microglial activation, decreased neuroinflammation, improved cognition, improved symptoms of Alzheimer's disease).

In some embodiments of the method, the agent or composition of the present invention may contain sufficiently purified or enriched intestinal microbes such that the agent or composition may contain at least about 5 wt.%, 10 wt.%, 20 wt.%, 30 wt. %, 40 wt.%, 50 wt.%, 60 wt.%, 70 wt.%, 80 wt.%, 85 wt.%, 90 wt.%, 95 wt.%, 99 wt.% or more desired intestinal microbes based on the weight of the agent or composition, and/or less than about 40 wt.%, 30 wt.%, 20 wt.%, 15 wt.%, 14 wt.%, 13 wt.%, 12 wt.%, 11 wt.%, 10 wt.%, 9 wt.%, 8 wt.%, 7 wt.%, 6 wt.%, 5 wt.%, 4 wt.%, 3 wt.%, 2 wt.%, 1 wt.% or less unwanted intestinal microbes, based on the weight of the tool or composition.

Agents and compositions that regulate the relative content of intestinal microbes in accordance with the present invention can lead to changes in metabolic functions. For example, altered metabolic function may include regulation of amino acid levels among microbial metabolites.

In some embodiments, when performing detection in a sample of the peripheral blood of an individual, the methods, tools and compositions of the present invention can adjust the level of amino acids by approximately 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60 , 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185 , 190, 195, 200, 205, 210, 215, 220, 225, 230, 235, 240, 245, 250, 255, 260, 265, 270, 275, 280, 285, 290, 295, 300 μM or more, or by the range defined by the endpoints of the aforementioned values, or by any value in between; and/or make the amino acid level close to or achieve an appropriate amino acid level in an appropriate normal individual.

In some embodiments, when performing detection in a faecal sample of an individual, the methods, agents and compositions of the present invention can adjust the level of amino acids by approximately 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1100, 1200, 1300, 1400, 1500, 1600, 1700, 1800, 1900, 2000, 2100, 2200, 2300, 2400, 2500, 2600, 2700, 2800, 2900, 3000 µmol/g µM or more, or over the range determined by the endpoints the aforementioned values, or any value in between; and/or make the amino acid level close to or achieve an appropriate amino acid level in an appropriate normal individual.

In some embodiments, the methods, agents, and compositions of the present invention may cause altered infiltration by immune cells in the brain. For example, the proportion of pro-inflammatory Th1 cells among CD4+ T cells is reduced. In some embodiments, the agents and compositions of the present invention may reduce the proportion of pro-inflammatory Th1 cells relative to CD4+ T cells in an individual's sample by about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 , 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37 , 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62 , 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87 , 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100% or more; and/or make the proportion of pro-inflammatory Th1 cells relative to CD4+ T cells close to or equal to the proportion of corresponding pro-inflammatory Th1 cells relative to CD4+ T cells in a corresponding normal individual.

In some embodiments, the methods, agents, and compositions of the present invention may decrease the relative uptake of amino acids by naive T cells. In some embodiments, the agents and compositions of the present invention may reduce the relative uptake of amino acids by naïve T cells by approximately 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75 , 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, 200 , 205, 210, 215, 220, 225, 230, 235, 240, 245, 250, 255, 260, 265, 270, 275, 280, 285, 290, 295, 300 or more; and/or make the relative level of amino acid uptake by the naive T cells close to or equal to the relative level of amino acid uptake by the corresponding naive T cells in the corresponding normal individual.

In some embodiments, the methods, agents, and compositions of the present invention may result in altered activation of microglia in the brain. For example, altered activation of microglia in the brain may include an increase or decrease in the activation of microglia in the brain. Microglia activation in the brain can increase or decrease by about 1-100%, for example, by about 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70% , 75%, 80%, 85%, 90%, 95% or 99% or 100%, or any range, defined by the end points of the above values, or any value in between, for example, by about 7% to about 28%, etc., or by about 7%, 14%, 21%, 28%, etc.

In some embodiments, the methods, agents, and compositions of the invention may result in altered levels of IBA1. For example, changing the level of IBA1 may include increasing or decreasing the level of IBA1. The level of IBA1 can be increased or decreased by from about 0 to about 3000 relative levels, for example, by a relative level of about 0, 50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600 , 650, 700, 750, 800, 850, 900, 950, 1000, 1050, 1100, 1150, 1200, 1250, 1300, 1350, 1400, 1450, 1500, 1550, 1600, 1650, 170.00 relative levels by the range defined by the endpoints of the above values, or by any value in between, such as from about 500 to about 3000, or about 500, 1000, 1500, and the like.

Lineups

The agent or pharmaceutical composition of the present invention may contain intestinal microbes, which can regulate the relative content of intestinal microbes in an individual. Gut microbes can be viable (live), dormant, dormant, or dead bacteria. The agent or pharmaceutical composition of the present invention may contain a compound or agent that can regulate the relative content of intestinal microbes in an individual. One or more compounds can be used to alter the microbiota in an individual. Such compounds or agents may include, but are not limited to, antibiotics and/or antibacterial agents, prebiotics such as bacterial cell wall components, bacterial nucleic acids (such as DNA and RNA), bacterial membrane components, and bacterial structural components (such as proteins). , carbohydrates, lipids and combinations thereof such as lipoproteins, sugar esters and glycoproteins), organic acids, inorganic acids, alkalis, proteins and peptides, enzymes and coenzymes, amino acids and nucleic acids, sugars, lipids, glycoproteins, lipoproteins, esters sugars, vitamins, biologically active compounds, metabolites containing inorganic components, small molecular weight compounds such as nitrogen-containing molecules or molecules containing sulfurous acid, resistant starch, potato starch or starch with a high amylose content, modified starch (including carboxylated starch, acetylated starch , propionirov this starch and butylated starch), non-digestible oligosaccharides such as fructooligosaccharide, oligodextrose, xylooligosaccharide, galactooligosaccharide, arabinoxylan, arabinogalactan, galactomannan polysaccharides, polydextrose, oligofructose, inulin and their derivatives, but other oligosaccharides, other soluble fibers, and a combination thereof that may play a prebiotic role are not excluded. The sugar may be selected from monosaccharides, disaccharides, oligosaccharides, polysaccharides or derivatives thereof, combinations thereof and/or derivatives thereof; preferably oligosaccharides and polysaccharides; more preferably mannuronic acid oligosaccharides.

The agent or pharmaceutical composition of the present invention may also include, for example, amino acids, amino sugars, sugar alcohols, proteins, carbohydrates, monosaccharides, disaccharides, oligosaccharides, polysaccharides, nucleic acids, buffers, surfactants, lipids, liposomes, other excipients and their mixtures. Other useful ingredients may include steroids, anti-inflammatory drugs, non-steroidal anti-inflammatory drugs, painkillers, cells, anti-inflammatory drugs, growth factors, growth factor fragments, small molecule wound healing promoters, hormones, cytokines, peptides, antibodies, enzymes, isolated cells, platelets, immunosuppressants , nucleic acids, cell types, viruses, viral particles, essential nutrients, minerals, metals or vitamins, and combinations thereof. In addition, the agents and compositions of the present invention may include diluents such as water, saline or buffer.

The agent or pharmaceutical composition of the present invention may be formulated as a pharmaceutical composition comprising a pharmaceutically acceptable carrier. As used herein, a "pharmaceutically acceptable carrier" includes any and all physiologically compatible diluents, dispersants, coatings, antibacterial and antifungal agents, isotonic agents, absorption delay agents, and the like. In one embodiment, the agent or pharmaceutical composition of the invention may be included in a pharmaceutical composition suitable for delivery to an individual. The pharmaceutical composition may also include a pharmaceutically acceptable carrier. As used herein, a "pharmaceutically acceptable carrier" includes any and all physiologically compatible solvents, dispersion media, coatings, antibacterial and antifungal agents, isotonic agents, absorption delay agents, and the like. Examples of pharmaceutically acceptable carriers include one or more of the following: water, saline, phosphate buffered saline, glucose, glycerol, ethanol, etc., and combinations thereof. In many cases it is preferable to include isotonicity agents such as sugars, polyhydric alcohols such as mannitol, sorbitol or sodium chloride in the compositions.

The pharmaceutical composition may be formulated in various forms. They include, for example, liquid, semi-solid and solid form preparations such as liquid solutions (such as injectable and infusion solutions), dispersions or suspensions, tablets, pills, powders, liposomes, suppositories and other formulations. The pharmaceutical composition may be formulated for a high drug concentration. The pharmaceutical composition may also be sterile and stable under the conditions of manufacture and storage. Sterile injectable solutions can be obtained by including one of the ingredients listed above, or a combination of them (if necessary) in a suitable solvent in the required amount, followed by filtration and sterilization.

The exemplary form of the pharmaceutical composition may depend on the intended mode of delivery and therapeutic application. In one embodiment, the pharmaceutical composition is formulated for oral delivery. Some compositions may be in a pill-based delivery form (as described in US Patent Application No. 12/976,648 titled "pill catchers" filed Oct. 22, 2010) and have extended release. In one embodiment, pill-based delivery may be part of a system that allows delivery to a specific location in the intestinal tract. In another embodiment, the pharmaceutical composition may be formulated as a sustained release formulation. In another embodiment, the pharmaceutical composition may be enclosed in a coating that does not begin to degrade until it leaves the stomach. In another embodiment, the pharmaceutical composition may be formulated with a carrier that protects the composition from rapid release, such as in the case of a sustained or controlled release formulation, including implants, transdermal patches, and microencapsulated delivery systems. Biodegradable biocompatible polymers such as ethylene vinyl acetate, polyanhydrides, polyglycolic acid, collagen, polyorthoesters and polylactic acid can be used. Many methods for preparing such formulations have been granted patent rights or are well known to those skilled in the art. See, for example, Sustained and Controlled Release Drug Delivery Systems, J.R. Robinson, ed., Marcel Dekker, Inc., New York, 1978. "Sustained release" refers to the release of a composition or active compound thereof over an extended period of time relative to the release achieved by delivery of a conventional composition formulation.

Another type of pharmaceutical composition includes an activated form, such as formulation with the microbiota in a dormant or inactive state (eg, in a lyophilized state). In the combined composition, the microbiota may be present in a dormant or inactive state, or the compound or agent in which the microbiota is cultured may be inactive. In one exemplary embodiment, the pharmaceutical composition may be formulated to include at least one type of resting or inactive microbiota and an inactive compound or substance that cultivates the microbiota.

The described pharmaceutical compositions and combination pharmaceutical compositions can also be formulated as foodstuffs, beverages, nutritional supplements and/or additional substances. Such compositions are compositions suitable for human and/or animal consumption. Those skilled in the art may be well aware of specific microbiota formulations that can be used in oral or ingestible formulations and are considered suitable for human and/or animal administration. Many compositions are used for the production of food or nutritional supplements/additional substances; thus, another important aspect is to provide a human or animal with food or nutritional supplements/supplements that include microbiota for the regulation of gut microbes in an individual.

A consumable composition may be formulated to include sweeteners, stabilizers or binders, humectants, and/or natural and/or artificial flavors. The composition may also include natural and/or artificial colors and preservatives. In one embodiment, the composition may include monosaccharides, disaccharides, and polysaccharides such as, but not limited to, sucrose (sugar), dextrose, maltose, dextrin, xylose, ribose, glucose, mannose, galactose, sucromalt, fructose (levose), inverted Sugar, Corn Syrup, Maltodextrin, Oligofructose Syrup, Partially Hydrolysed Starch, Dry Corn Syrup, Polydextrose, Soluble Fiber, Insoluble Fiber, Natural Cane Juice, Gelatin, Citric Acid, Lactic Acid, Natural Colors, Natural Flavors, Fractionated Coconut Oil, carnauba wax or a combination.

Dosage

The agent or composition of the present invention may contain a "therapeutically effective amount" or "effective amount" of the ingredients. "Therapeutically effective amount" refers to an amount that is effective to achieve the desired therapeutic result at the required dose and for a certain period of time. The therapeutically effective amount of the agent or pharmaceutical composition may vary depending on various factors such as the disease state of the individual, age, sex and brain state, and the ability of the composition to elicit the desired response in the individual. A therapeutically effective amount is also the amount in which the therapeutically beneficial effects of the agent or pharmaceutical composition outweigh the toxic or deleterious effects of the agent or pharmaceutical composition. In an exemplary embodiment, a therapeutically effective amount of an agent or pharmaceutical composition is an amount in which the relative content of one or more intestinal microbes is increased. For example, a therapeutically effective amount of an agent for regulating the relative abundance of intestinal microbes increases the relative abundance of one or more intestinal microbes in an individual.

As used within the scope of the invention, the term "treatment" mainly refers to the achievement of the desired pharmacological and/or physiological effect. The effect may be prophylactic in terms of total or partial prevention of the disease or its symptoms; and/or it may be therapeutic in terms of partial or complete stabilization or treatment of the disease and/or side effects of the disease. "Treatment", as used herein, encompasses any treatment of a disease in a patient, including: (a) prevention of diseases or symptoms that occur in patients who are predisposed to diseases or symptoms but who have not yet been diagnosed with a disease; (b) inhibiting the symptoms of the disease, for example, inhibiting the progression of the disease and preventing the development of the disease; or (c) alleviating the symptoms of the disease, i. e. ensuring the extinction of the disease or symptoms.

Indications

Through research within the scope of the present invention, the inventors found that an abnormal intestinal microbial pattern caused naive T cells to overdifferentiate into Th1 cells, and the level of Th1 cells in the peripheral blood increased in an abnormal manner. Elevated levels of peripheral Th1 cells cause more Th1 cells to infiltrate into the brain, causing diseases such as Alzheimer's disease. By restoring the gut microbiota, differentiation of naïve T cells into Th1 cells can be reduced, and abnormally elevated levels of Th1 cells in peripheral blood can be reduced, thereby curing the disease. Thus, the present invention relates to a method of treating diseases associated with high levels of Th1 cells in the peripheral blood of an individual, and the method includes regulating the relative content of intestinal microbes in the individual, as described in the present description, reducing the level of amino acids in the peripheral blood, as described in the present description, or inhibition of uptake by naive T cells of an amino acid in peripheral blood, as described in the present description.

The terms "Th1 dominance" and "Th1 cell dominance" are used interchangeably herein. In some cases, Th1 dominance may be represented by high levels of Th1 cells in the peripheral blood. A high level of Th1 cells in the peripheral blood can refer to the level of Th1 cells in the peripheral blood of an individual, at 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20%, 25%, 30% , 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%, 150%, 200%, 250 %, 300%, 350%, 400%, 450%, 500%, 550%, 600%, 650%, 700%, 750%, 800%, 850%, 900%, 950%, 1000% or above a suitable control (for example, a normal control, such as a sample of healthy people), or a range defined by the end points of the above values, or any value in between, for example, from about 7% to about 28%, etc., or by about 7%, 14%, 21%, 28%, etc. Such diseases include, but are not limited to, multiple sclerosis, Crohn's disease, type 1 diabetes, rheumatoid arthritis, Hashimoto's thyroiditis, vitiligo, Sjögren's syndrome, polycystic ovaries (PCOS), celiac disease, and Graves' disease.

As used herein, the term "individual" refers to any living organism, including, but not limited to, humans, non-human primates such as chimpanzees and other great apes and marmosets, farm animals such as cows, sheep, pigs. , goats and horses, domestic mammals such as dogs and cats, laboratory animals including rodents such as mice, rats, rabbits, guinea pigs, and the like. The term does not indicate a specific age or gender. In one embodiment, the individual is a human. In the context of the present invention, the terms "subject", "individual" and "patient" are used interchangeably.

In one embodiment, the relative content of one or more intestinal microorganisms in an individual exceeds their relative content in a healthy individual. In one embodiment, the relative content of one or more intestinal microorganisms in an individual is lower than in a healthy individual. In one embodiment, the relative content of one or more intestinal microorganisms in an individual exceeds their content in a healthy individual, and the relative content of the other one or more microorganisms is lower than that of a healthy individual.

The dosage may depend on the type of microbiota present in the agent or pharmaceutical composition of the invention. The dosage may also be determined based on the relative content of one or more types of microbiota present in the individual.

In one embodiment, the agent or pharmaceutical composition of the present invention can effectively change the relative content of one or more types of microbiota. In another embodiment, the agent or pharmaceutical composition can effectively increase or decrease the relative microbiota content of an individual. In one embodiment, the agent or pharmaceutical composition can increase or decrease the relative abundance of specific microbiota microorganisms in an individual and decrease the relative abundance of other specific microbiota microorganisms in an individual.

In another embodiment, the agent or pharmaceutical composition of the present invention can also effectively alter the microbiota in an individual such that, upon administration of the agent or pharmaceutical composition, the individual's microbiota mimics the microbiota present in an individual responding to an Alzheimer's disease treatment process. The agent or pharmaceutical composition can effectively alter the microbiota to mimic the microbiota of normal and healthy individuals with similar brain conditions, age, sex, race, and the like.

The dosage regimen can be adjusted to provide the most appropriate desired response (such as a therapeutic response or a prophylactic response). For example, a single bolus may be delivered, multiple divided doses may be delivered over time, or the dose may be reduced or increased in proportion to the need of the treatment situation. It is particularly advantageous to formulate parenteral compositions in unit dosage form for ease of delivery and dosage uniformity. A unit dosage form, as used herein, refers to a physically discrete unit suitable as a single dose for a mammal to be treated; each unit contains a predetermined amount of the active compound, calculated to achieve the desired therapeutic effect, in combination with the required pharmaceutical carrier. The characteristics of the unit dosage form used in the present invention are determined by or directly dependent on the following: (a) the unique properties of the active compound and the particular therapeutic or prophylactic effect to be achieved; and (b) the limitations inherent in the field of combination of this active compound for individual therapy.

When used for the methods contemplated by the present invention, an exemplary dosage range for the agent or pharmaceutical composition of the present invention may be from about 0.001 to about 100 mg/kg of body weight per day, from about 0.01 to about 50 mg/kg of body weight body per day, such as from about 0.05 to about 10 mg/kg of body weight per day, delivered in one or more doses, for example, 1-3 doses. The exact dosage depends on the frequency and method of delivery, sex, age, body weight and general condition of the individual being treated, the nature and severity of the condition being treated, any comorbidities to be treated, and other factors known to those skilled in the art.

In one embodiment, the agent or pharmaceutical composition of the present invention contains a microbiota, such as Verrucomicrobia , having a total concentration ranging from about 0.001 mg/kg to about 100 mg/kg. In another embodiment, the agent or pharmaceutical composition contains a microbiota, such as Verrucomicrobia , having a total concentration in the range of about 0.1 mg/kg to about 50 mg/kg. In a further embodiment, the agent or pharmaceutical composition comprises a microbiota, such as Verrucomicrobia , having a total concentration in the range of about 1 mg/kg to about 10 mg/kg.

In some aspects, the agents, compositions, or kits described herein are administered in doses based on the individual's body weight. In some embodiments, the agents, compositions or kits described herein contain one or more of the agents mentioned herein in an amount based on the body weight of the individual.

In some embodiments, the amount of one or more of the agents mentioned herein in the agents, compositions, or kits described herein ranges from about 1.0 to about 50.0 mg/kg or more, preferably from about 5 0 to 40.0 mg/kg, more preferably from about 10.0 to 30.0 mg/kg, based on the body weight of the individual. In some embodiments, the amount of one or more agents mentioned herein in the agents, compositions, or kits described herein is approximately 1.0, 1.5, 2.0, 2.5, 3.0, 3 .5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 8.5, 9.0, 9.5 , 10.0, 10.5, 11.0, 11.5, 12.0, 12.5, 13.0, 13.5, 14.0, 14.5, 15.0, 15.5, 16 .0, 16.5, 17.0, 17.5, 18.0, 18.5, 19.0, 19.5, 20.0, 20.5, 21.0, 21.5, 22.0 , 22.5, 23.0, 23.5, 24.0, 24.5, 25.0, 25.5, 26.0, 26.5, 27.0, 27.5, 28.0, 28 .5, 29.0, 29.5, 30.0, 30.5, 31.0, 31.5, 32.0, 32.5, 33.0, 33.5, 34.0, 34.5 , 35.0, 35.5, 36.0, 36.5, 37.0, 37.5, 38.0, 38.5, 39.0, 39.5, 40.0, 40.5, 41 .0, 41.5, 42.0, 42.5, 43.0, 43.5, 44.0, 44.5, 45.0, 45.5, 46.0, 46.5, 47.0 , 47.5, 48.0, 48.5, 49.0, 49.5, 50.0 mg/kg or more, or any range defined by the endpoints of the above values, or any value in between, such as, about 1.1 to 1.4 mg/kg, etc., or about 1.1, 1.2, 1.3, 1.4 mg/kg etc. based on the body weight of the individual.

In other aspects, the agents, compositions or kits described herein are administered in fixed doses. In some embodiments, the agents, compositions, or kits described herein contain a fixed amount of one or more of the agents mentioned herein.

In some embodiments, the amount of one or more of the agents mentioned herein in the agents, compositions, or kits described herein is independently 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 at each occurrence. , 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35 , 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100 , 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, 200 mg or more, or endpoint range of the above values, or any value in between, for example, from about 1.1 to 1.4 mg, and the like. or about 1.1, 1.2, 1.3, 1.4, or the like.

In other aspects, some of the components of the agents, compositions or kits described herein are administered at individual weight doses as described above, while other components are administered at fixed doses as described above. In some embodiments, the amounts of some of the components in the agents, compositions, or kits described herein. are amounts based on the weight of the individual, as described above, and the other components are fixed amounts, as described above.

Delivery

The agent or pharmaceutical composition of the present invention can be delivered or administered by various methods known in the art. The terms "delivery", "deliver", "administer", and "apply" are used interchangeably herein. As will be understood by those skilled in the art, the route and/or method of delivery varies depending on the desired result. In one embodiment, the agent or pharmaceutical composition of the invention is delivered orally. In another embodiment, the agent or pharmaceutical composition of the invention is delivered orally. In another embodiment, the agent or pharmaceutical composition of the invention is delivered by the nasal route. Another delivery method may include methods and combinations for delivery to the intestine.

The agent or pharmaceutical composition of the present invention can be delivered to a given area and/or structure in an individual. The region that can be targeted in the intestine may include, but is not limited to, the stomach, the biliary-pancreatic branch (segment), the Roux branch, the common branch, the ileum, the caecum, or the colon. They can be targeted to a structure that constitutes an individualized environment with a specific pH range, temperature, humidity, and metabolite content. Diseases or conditions associated with altered microbiota genealogy may show the presence of new microorganisms, the absence of normal microorganisms, or a change in the ratio of microorganisms.

Delivery of the agent or pharmaceutical composition of the present invention may be targeted to one or more areas in an individual. The area may include, but is not limited to, the area in the intestine. In an exemplary embodiment, delivery is targeted to the oral cavity, stomach, biliary-pancreatic branch, Roux branch, common branch, small intestine, ileum, cecum, colon, or colon in the intestine. Delivery can also be targeted to one or more tissues of an individual. The tissue may include any tissue in the intestine, such as that of the stomach, biliary-pancreatic ramus, roux, common ramus, small intestine, ileum, caecum, colon, or colon.

The components of the agent or pharmaceutical composition of the present invention may be formulated separately, or some of them may be formulated together. In one embodiment, the agent or pharmaceutical composition of the present invention may be formulated as an agent or pharmaceutical composition suitable for single or multiple administration.

The components of the agent or pharmaceutical composition of the present invention may be administered separately, or some or all of them may be administered together. The agents or components of the pharmaceutical composition of the present invention may be administered at substantially different times, or some or all of them may be administered at substantially the same time.

Each of the agents or components of the pharmaceutical composition of the present invention may be independently administered by a variety of suitable routes, including, but not limited to, oral or parenteral (intravenous, intramuscular, topical, or subcutaneous routes). In some embodiments, each of the components of the agents or pharmaceutical composition of the present invention may be independently administered orally or by injection, for example, by intravenous injection or intraperitoneal injection.

Each of the components of the agent or pharmaceutical composition of the present invention may independently be a suitable dosage form, including, but not limited to, dosage forms of tablets, lozenges, pills, capsules (e.g., hard capsules, soft capsules, enteric-coated capsules, microcapsules), elixirs, granules, syrups, injectables (intramuscular, intravenous, intraperitoneal), granules, emulsions, suspensions, solutions, dispersions and sustained release preparations for oral or parenteral administration.

Each of the agents or components of the pharmaceutical composition of the present invention may independently contain a pharmaceutically acceptable carrier and/or excipient.

The agents of the present invention or components of the pharmaceutical composition can be administered independently every 1 day, every 2 days, every 3 days, every 4 days, every 5 days, every 6 days, every week, every 2 weeks, every 3 weeks, or every month or from lower frequency.

The agents of the present invention or components in the pharmaceutical composition can be administered independently 1 time, 2 times, 3 times, 4 times, 5 times, 6 times, 7 times, 8 times, 9 times or 10 times or more per day.

The agents of the present invention or components of the pharmaceutical composition can be administered independently within 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 , 20, 21, 22, 23, 24, 25, 26, 27, 28, 29 or 30 consecutive days or more.

One of the components of the agent or pharmaceutical composition of the present invention may be administered 1, 2, 3, 4, 5, 6, 7, 8, 9 or 10 or more days before or after the administration of the other component. For example, in one embodiment, the agent or component 1 of the pharmaceutical composition of the present invention is administered on day 1, and the agent or component 2 of the pharmaceutical composition of the present invention is administered after 2 days (i.e., on day 3), and the agent or component 1 of the pharmaceutical composition the compositions of the present invention are administered after another three days (ie on day 6).

The delivery of the agent or pharmaceutical composition of the present invention can also be repeated one or more times. Re-delivery of the agent or pharmaceutical composition of the present invention may be carried out one or more times before and/or after the treatment of the disease. Re-delivery can be made in the same way as the original delivery.

The agent or pharmaceutical composition of the present invention may also be administered with an agent, which may include a therapeutic, prophylactic, or diagnostic agent. The therapeutic, prophylactic or diagnostic agent is selected from small molecule compounds, nucleic acids, proteins such as polypeptide prebiotics, including bacterial components (such as bacterial cell wall components (such as peptidoglycan), bacterial nucleic acid (such as DNA and RNA), bacterial components membranes and structural components of bacteria (such as proteins, carbohydrates, lipids and combinations thereof such as lipoproteins, sugar esters and glycoprotein)), bacterial metabolites, organic acids, inorganic acids, bases, proteins and peptides, enzymes and coenzymes, amino acids and nucleic acids, carbohydrates, lipids, glycoproteins, lipoproteins, sugar esters, vitamins, biologically active compounds, metabolites containing inorganic components, small molecular weight compounds (for example, nitrogen-containing molecules or molecules containing sulfurous acid), resistant starch, potato starch or starch with high amylose, modified starch (including carboxylated starch, acetylated starch, propionated starch and butylated starch), digestible oligosaccharides such as fructooligosaccharides, dextrose, xylooligosaccharide, galactooligosaccharide, arabinoxylan, arabinogalactan, galactomannan polysaccharides, polydextran, oligofructose, inulin and their derivatives ( however, other oligosaccharides that may act as prebiotics are not excluded), other soluble fibers, and a combination thereof. In one embodiment, the delivered agent is a delivered small molecule compound that has low oral bioavailability and acts on a microbial site in the host's gut. Low bioavailability is generally undesirable in medicine since intestinal absorption is the target of most oral treatments.

The agent or pharmaceutical composition of the present invention can also be administered in the same composition as the aforementioned agent, or they can be administered separately from the agent administered before, simultaneously and/or after the agent or pharmaceutical composition of the present invention. The agent or pharmaceutical composition of the present invention may be administered at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 or more days prior to drug administration. The agent or pharmaceutical composition of the present invention can also be administered at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18 , 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 or more days after administration of the agent.

The agent or pharmaceutical composition of the invention can also be delivered via an at least partially implantable system. The implantable system may be any system known and used in the art. The system may include programmable pumps (such as pumps often used to deliver insulin to diabetic patients). One or more of these components may be modular or connected to a transdermal delivery system, which may include holes, needles, patches, and the like. In an exemplary embodiment, the implantable system includes a reservoir and an orifice. The reservoir may include a refillable or refillable container to contain the composition. In another embodiment, the system may include a catheter. In another embodiment, the implantable system is a transluminal catheter. The system may also be arranged to deliver the composition at a prescribed dose and/or at a prescribed interval. The dose to be administered and/or the interval to be administered can be determined by those skilled in the art.

Some embodiments of the invention are illustrated in the following non-limiting examples.

EXAMPLE

Materials and methods

Animals. Tg mice and co-housed WT mice (corresponding to WT mice obtained by crossing Tg mice and C57 mice) were kept in the same cage after birth. WT mice (C57) were housed in separate cages to avoid cross-transfer of microbiota. All mice were kept indoors at 23° C. with a 12 hour (h) light/dark cycle. Mice were randomly assigned to different groups before treatment. Throughout the assay, Tg mice, male and female Tg mice were sacrificed at 2, 3, 5, 7 and 9 months of age. The brain was removed and stained for immune cell analysis and cytokine analysis. Before sacrificing mice, faeces were collected for microbiota analysis. For OM1 administration at 6.5 months of age on a 450 mg bid (twice daily) basis in the phase III trial, Tg mice were administered 100 mg/kg OM1 via oral administration once daily for one month. Behavioral tests were performed to monitor cognitive activity after the last administration. The brains and faeces of the mice were then used for various analyses. For behavioral testing, Tg mice and WT mice at different months and treated mice were tested by discrimination training as described previously. All mouse movements that occurred in the Phenotyper (HomeCage) were recorded by a computerized tracking system that calculates the time and number of entries required to reach the 80% efficiency standard (Noldus, Ethovision). For intraperitoneal injection of phenylalanine and isoleucine, 4-month-old C57 mice were injected with 50 mg/kg of phenylalanine or isoleucine for 4 days. For hippocampal injection of phenylalanine and isoleucine, 4-month-old C57 mice were injected with 3 μl of phenylalanine or isoleucine at a dose of 120 ml/l. After 10 days, these mice were subjected to blood sample analysis and behavioral testing using FACS.

For analysis of APP/PS1 mice at different time points, mice and age-matched wild-type mice were sacrificed at 3, 9 and 14 months of age. The brain and blood of mice were collected for various analyses. Before sacrifice, mice faeces were collected for microbiota analysis. To administer APP/PS1 mice, 6-month-old mice were administered with or without antibiotics for 3 months at 50 mg/kg OM1 by gavage once daily. Behavioral tests were performed to monitor cognitive activity after the last administration. The animal experiment has been approved by the ethical committee of Shanghai SIPPR-Bk Lab Animal Co., Ltd (No.: 2016002).

Extraction of DNA from a faecal sample and amplification by PCR . All faecal samples were frozen at -80°C prior to DNA extraction and analysis. Microbial DNA was extracted from fecal samples using the EZNA® Soil DNA Kit (Omega Bio-Tek, Norcross, GA, US) according to the manufacturer's protocols. The final concentration and purity of the DNA was determined using a NanoDrop 2000 UV-Visible spectrophotometer (Thermo Scientific, Wilmington, USA) and DNA quality was checked by 1% agarose gel electrophoresis. Hypervariable regions V3-V4 of the bacterial 16S rRNA gene were amplified using primers 338 F (5'-ACTCCTACGGGAGGCAGCAG-3') and 806 R (5'-GGACTACHVGGGTWTCTAAT-3') using a PCR thermal cycler system (GeneAmp 9700, ABI, USA). PCR reactions were performed using the following program: 3 minutes (min) denaturation at 95°C, 27 cycles of 30 seconds (s) at 95°C, anneal for 30 s at 55°C, and elongation for 45 s at 72 °C, and final elongation at 72°C for 10 min. PCR reactions were run in triplicate in a 20 µl mixture containing 4 µl 5× FastPfu buffer, 2 µl 2.5 mmol/L dNTP, 0.8 µl each primer (5 µmol/L), 0.4 µl FastPfu polymerase, and 10 ng template DNA. The obtained PCR products were extracted from 2% agarose gel and further purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) and quantified using QuantiFluor™-ST (Promega, USA) according to the manufacturer's protocol . A degenerate primer refers to a mixture of different sequences that reflect all the different base possibilities for encoding a single amino acid. To improve specificity, a codon usage table can be consulted to reduce degeneracy according to base usage preferences in different organisms. In addition to the normal four base designations A, T, G, and C, other letters such as R, Y, M, K, etc. are present in the nucleotide chain where R=A/G, Y=C/T , M=A/C, K=G/T, S=C/G, W= A/T, H= A/C/T, B= C/G /T, V=A/C/G, D =A/G/T, N=A/C/G/T.

Sequencing using Illumina MiSeq . According to the standard protocol of Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China), purified amplicons were pooled in equimolar amounts and subjected to sequencing of paired ends (2×300) on the Illumina MiSeq platform (Illumina, San Diego, USA).

Processing of sequencing data. Fastq source files were demultiplexed, quality filtered by Trimmomatic, and merged by FLASH based on the following criteria: (i) Reads were truncated in any region that received an average quality score of < 20 over a 50 bp glide window. (ii) Primers were fine-tuned, allowing for a 2 nucleotide mismatch, and reads containing ambiguous bases were deleted. (iii) Sequences with more than 10 bp overlap. were combined according to their overlap sequence. Operational Taxonomic Units (OTUs) were clustered with a 97% similarity threshold using UPARSE (version 7.1 http://drive5.com/uparse/) and chimeric sequences were identified and deleted using UCHIME. The taxonomy of each 16S rRNA gene sequence was analyzed by the RDP Classifier algorithm (http://rdp.cme.msu.edu/) against the Silva 16S rRNA database (SSU123) using a confidence threshold of 70%.

Obtaining metabolite samples. Samples stored at -80°C were taken and thawed at room temperature. The experiment used samples weighing 50 mg and also added 400 μl of a mixture of methanol-water (4:1, v/v) to homogenize the sample using a homogenizer for 10 seconds. The solution was subjected to ultrasonic extraction on ice for 10 min and stored at -20°C for 30 min, then centrifuged for 15 min at 13,000 rpm at 4°C. For LC-MS analysis, 200 μl of the supernatant was used.

LC/MS Analysis Parameters . LC-MS was performed on an AB Sciex TripleTOF 5600TM mass spectrometric system (AB SCIEX, USA). LC Conditions: Column: Acquity BEH C18 (100 mm x 2.1 mm id, 1.7 µm; Waters, Milford, USA). Solvent: column was maintained at 40°C and separation was achieved using the following gradient: 5% B-30% B over 0-3 min, 30% B-95% B over 3-9 min, 95% B-95% B for 9-13.0 min; 95% B-5% B over 13.0-13.1 min, and hold for 13.1-16 min at 5% B; the flow rate is 0.40 ml/min, where B is acetonitrile:isopropanol 1:1 (0.1% (v/v) formic acid) and A is an aqueous solution of formic acid (0.1% (v/v) ./vol.) formic acid). The injection volume was 20 µl. Mass spectrometry data were obtained using an AB Sciex TripleTOF 5600TM mass spectrometry system equipped with an electrospray ionization (ESI) source operating in either positive ion or negative ion mode, capillary voltage 1.0 kV, sampling cone, 40 V, collision energy 6 eV. The source temperature was set to 120°C, with a desolvation gas flow of 45 l/h. Centroid data were acquired at 50 to 1000 m/z with a resolution of 30,000.

Obtaining a sample of QC metabolites . A QC sample was prepared by mixing aliquots of all samples to form a pooled sample and then analyzed using the same method with the analytical samples. QC was injected at regular intervals (every 10 samples) throughout the analytical series to obtain a set of data from which repeatability can be estimated.

In vitro differentiation of naïve CD4 into Th1 and Th2 induced by mouse faecal supernatant. Naïve CD4 ⁺ T cells were separated from splenocytes from female C57BL/6 mice at 8 months of age using a naïve CD4 ⁺ T cell isolation kit (Stem Cell, #19765). As described above, the supernatant of faeces from mice at the age of 7 months was obtained. A total of 0.5×10 ⁶ cells/well in 0.5 ml of RPMI-1640 medium were plated in 48-well plates coated with anti-CD3 antibody and anti-CD28 antibody, and the culture medium was supplemented with cytokines and blocking antibodies. Th0: 20 ng/ml mIL-2; Th1: 20 ng/ml mIL-2, 10 µl supernatant, 5000 ng/ml 11B11; Th2: 20 ng/ml mIL-2, 10 µl supernatant, 5000 ng/ml XMG1.2. OM1 was added to the designated wells to a final concentration of 100 μg/ml. After incubation at 37° C. in 5% CO ₂ for 5 days, cells were obtained on a BD Aria III cytometer and data was analyzed using FlowJo software.

Immunohistochemistry . For 3,30-diaminobenzidine (DAB) development staining, sections were immunostained using a Leica BOND-RX Autostainer (Leica Microsystems) and Coverslipper CV5030 (Leica Microsystems) according to the manufacturer's IHC protocol. Briefly, sections were subjected to heat-induced epitope unmasking with using Epitope Retrieval solution 2 (ER2, AR9640, Leica Biosystems) for 20 minutes Endogenous peroxidase activity was blocked with 3%-4% (v/v) hydrogen peroxide (part of DS9800, Leica Biosystems) for 10 minutes Then sections were incubated with blocking buffer (10% NGS in PBS with 0.3% Triton x-100) for 60 minutes Finally, staining was performed using the Bond Polymer Refine Detection System (DS9800, Leica Biosystems) according to the manufacturer's protocol. The incubation time with the primary antibody was 30 minutes Sections were stained for activated microglia using rabbit antibodies against IBA1 (1:1000, cat. no. 019-19741, Wako), amyloid deposits using mouse anti-Aβ42 antibody (1:1000; 803003, Biolegend) and phosphorylation of tau using the mouse anti-PHF-Tau & tangles-Thr231 antibody (1:300, catalog no. MN1040, Thermo Fisher). Stained sections were automatically scanned with a high performance brightfield scanner (NanoZoomer 2.0HT, Hamamatsu) and images were acquired using NDP.scan 3.2 software (Hamamatsu). For fluorescent staining, slides were blocked with blocking buffer (10% NGS in PBS with 0.3% Triton x-100) at rt. for 1 h, and then incubated in a solution of the primary antibody (Iba-1 1:1000, Aβ42 1:1000, tau 1:300) overnight at 4°C. After washing, the slides were incubated with a fluorescent anti-rabbit or anti-mouse secondary antibody (1:1000, Invitrogen) for 60 min at RT. and then washed 3 times in PBS. Finally, slides were counterstained with DAPI (1:10,000 in PBS, Sigma) for 5 min at RT, washed, sealed and stored at 4°C for imaging. Representative fluorescence images were obtained with a Zmager-m2 (Zeiss, Germany) upright fluorescence microscope under a 10x objective using Zen software (Zeiss).

Neurotoxicity test . SH-SY5Y cells (ATCC, USA) were seeded in a white polystyrene 96-well plate (Corning Inc., USA) at a density of 5000 cells/well and cultured in a humidified incubator at 37℃ and 5% CO ₂ in Dulbecco's modified Eagle's medium (DMEM) (Corning Inc., USA) supplemented with 10% fetal bovine serum (FBS), 100 units/ml penicillin and 100 µg/ml streptomycin. After 24 hours, cells were treated with L-phenylalanine or L-isoleucine (Sigma) at final concentrations of 10 mM, 1 mM and 0.1 mM, respectively. Cell viability was detected after 24 hours using CellTiter-Glo (Promega Inc., USA). The luminescent signal was recorded using a Cytation5 device (BioTek).

Amino acid detection . A set of solutions of standard mixtures of amino acids was obtained in the concentration range of 100-2000 µmol/l. A 10 μl portion of each standard mix solution or plasma sample was pipetted into the bottom of the tube, and then 70 μl of sodium borate buffer (200 mmol/l at pH 8.8) was added. 20 µl of 6-aminoquinolyl-N-hydroxysuccinimidylcarbamate (AQC) (4 mg/ml in acetonitrile) was added, the tube was capped and heated for 10 min at 55°C to obtain the AQC-amino acid. The solution was then cooled to room temperature and a 2 μl portion of each solution was injected into the UPLC-ESI-MS system for amino acid analysis without further purification.

People

Blood was collected from patients with MCI due to AD and healthy controls in a pilot trial. MCI due to AD was determined according to the NIA-AA 2011 clinical and scientific diagnostic criteria for MCI due to AD. Patients with MCI due to AD in this trial must meet the following criteria. The first factor is the change in cognitive function. The second is the disruption of one or more cognitive domains. The third is to preserve the independence of functional abilities. The fourth is the absence of dementia (NIA-AA 2011 clinical criteria for the diagnosis of MCI due to AD). All participants underwent a screening process that included their medical history, physical and neurological examination, laboratory tests, and MRI images. Clinical assessment of mild cognitive impairment or dementia included neuropsychological tests, as well as behavioral and psychiatric interviews conducted by attending physicians. Patients with AD scored < 4 on the Khachinsky Ischemia Scale and had no history of significant systemic or psychiatric conditions or traumatic brain injury that could impair brain function. All participants underwent a clinical assessment of dementia (CDR) and a Montreal Cognitive Assessment (MoCA). Based on this assessment, the inventors retained individuals with MCI due to AD and excluded others, such as individuals who had a non-memory single domain disorder (non-memory single domain MCI subtype) and individuals who had a non-memory single domain disorder. two or more domains (multiple domains, MCI subtype with mild impairment). Normal control individuals had no history of cognitive decline, neurological impairment, or uncontrolled systemic medical disorders. All individuals included in this trial had ischemia of no more than two lacunae (< 1 cm in diameter) as determined by fluid suppression inversion recovery (FLAIR) MRI sequence.

The sample size for the first group (Fig. 5h, i) is 9 patients with MCI due to AD and 18 healthy individuals. The sample size for the second group (FIG. 5j) is 22 patients with MCI due to AD and 22 healthy individuals. The diagnosis of MCI was based on the following criteria, which were adapted from the Petersen diagnostic criteria for MCI: (1) memory complaints, preferably confirmed by a spouse or relative; (2) objective memory impairment; (3) normal general cognitive function; (4) intact daily activities; and (5) no dementia. The Ethics Committee of the Shanghai Mental Health Center Institutional Review Board approved the trial (number: 2016-22R1). Informed consent was obtained from all individuals and guardians of individuals. Information about age and gender, etc. below.

First group:

Type Sample ID Age Floor Healthy HC-01 75 AND Healthy HC-02 71 AND Healthy HC-04 69 AND Healthy HC-05 73 AND Healthy HC-08 63 M Healthy HC-09 62 M Healthy HC-10 68 M Healthy HC-11 61 M Healthy HC-12 68 M Healthy HC-13 75 AND Healthy HC-14 70 AND Healthy HC-15 68 M Healthy HC-16 62 M Healthy HC-17 75 M Healthy HC-18 65 AND Healthy HC-19 64 AND Healthy HC-20 64 AND Healthy HC-22 63 AND MCI due to AD MCI-02 61 AND MCI due to AD MCI-03 79 M MCI due to AD MCI-04 71 AND MCI due to AD MCI-05 72 AND MCI due to AD MCI-06 80 AND MCI due to AD MCI-07 65 M MCI due to AD MCI-09 61 M MCI due to AD MCI-10 69 M MCI due to AD MCI-14 77 M

Second group:

Type Sample ID Age Floor Healthy HC-0149 73 M Healthy HC-0150 70 AND Healthy HC-0153 63 AND Healthy HC-0156 67 M Healthy HC-0158 71 AND Healthy HC-0165 61 AND Healthy HC-0168 62 AND Healthy HC-0172 70 AND Healthy HC-0176 71 AND Healthy HC-0187 73 AND Healthy HC-0191 65 M Healthy HC-0013 70 AND Healthy HC-0043 81 M Healthy HC-0050 64 AND Healthy HC-0051 66 M Healthy HC-0056 75 M Healthy HC-0068 67 AND Healthy HC-0074 57 AND Healthy HC-0076 60 AND Healthy HC-0081 71 AND Healthy HC-0089 57 AND Healthy HC-0090 76 AND MCI due to AD MCI-0169 65 AND MCI due to AD MCI-0175 61 AND MCI due to AD MCI-0211 69 M MCI due to AD MCI-0229 65 M MCI due to AD MCI-0240 59 AND MCI due to AD MCI-0244 64 AND MCI due to AD MCI-0257 61 AND MCI due to AD MCI-0260 60 AND MCI due to AD MCI-0282 66 AND MCI due to AD MCI-0284 64 AND MCI due to AD MCI-0287 75 AND MCI due to AD MCI-0303 62 AND MCI due to AD MCI-0319 63 AND MCI due to AD MCI-0332 67 AND MCI due to AD MCI-0374 61 M MCI due to AD MCI-0385 68 AND MCI due to AD MCI-0401 57 AND MCI due to AD MCI-0414 64 AND MCI due to AD MCI-0001 75 M MCI due to AD MCI-0043 55 AND MCI due to AD MCI-0061 63 AND MCI due to AD MCI-0091 78 AND

Differentiation and proliferation in vitro, induced by phenylalanine and isoleucine. Naive CD4⁺ T cells were separated from splenocytes from female C57BL/6 mice at 8 months of age using a naïve CD4 isolation kit.⁺ T cells (Stem Cell, #19765) and cells were stained with CellTrace (Thermo Fisher, #C34557). Total 1×10⁵ cells/well in 0.2 ml of RPMI-1640 medium were seeded into 96-well plates and the culture medium was supplemented with cytokines or blocking antibodies. Th0: 10 ng/ml mIL-2; Th1: 10 ng/ml mIL-2, 5000 ng/ml 11B11. To these wells were added phenylalanine (final concentration, 2 mmol/l), isoleucine (final concentration, 2 mmol/l) and OM1 (final concentration, 100 μg/ml), respectively. After incubation at 37°C in 5% CO₂ within 5 days, cells were obtained on a BD Fortessa cytometer and data was analyzed using FlowJo software.

Phenylalanine uptake . Naïve CD4 ⁺ T cells were separated from splenocytes from 8-month-old female C57BL/6 mice using a naïve CD4 ⁺ T cell isolation kit (Stem Cell, cat. no. 19765) and induced to differentiate into Th1 with 20 ng/mL IL- 12. After 3 days, a total of 5×10 ⁵ Th1 cells and Th0 cells/well in 0.5 ml of RPMI-1640 medium were seeded into 48-well plates. ¹³ C-labeled phenylalanine and 5 mM amino acid transport inhibitor BCH were added to these wells. After 0.5 h, the cells were harvested and washed twice with ice-cold D-PBS. Added 50 μl of deionized water and cells were lysed by freezing and thawing twice at -80°C. The cell lysate was centrifuged at 12,000×g for 10 min and ^{the 13} C-labeled phenylalanine in the supernatant was analyzed by mass spectrometry.

Antibiotic treatment . Mice were administered by adding to sterile drinking water an antibiotic solution (ATB) containing ampicillin (0.1 mg/ml, final concentration in drinking water), streptomycin (0.5 mg/ml, final concentration in drinking water) and colistin ( 0.1 mg/ml, final concentration in drinking water) (Sigma-Aldrich). Solutions and bottles were replaced 3 times and once a week, respectively. Antibiotic activity was confirmed by sequencing the 16S rRNA gene. Bacterial types with a relative content of less than 0.01 were removed for the Tg group. The duration of administration of ABX varied somewhat, based on the conditions of the experiment. In the context of the fecal microbiota transplantation experiments, mice were treated with ATB for 3 days before undergoing fecal microbiota transplantation the next day via gavage using animal feeding needles.

Fecal Microbiota Transplant (FMT) Experiments . FMT was performed by thawing fecal material. Then 200 μl of the suspension was transferred by means of a gastric tube to each of the recipients who were administered ATB. FMT was performed 3 times in 5 days. Twelve month old C57 mice were first treated with an antibiotic cocktail in drinking water for 3 days, and then 40 mg of mixed stool suspended in PBS was administered by gavage to each mouse 3 times with 2 days between doses. After 3 days, 4.2 μg of Aβ 1-40 oligomer was injected into both sides of the hippocampus. Mice were sacrificed after 3 days and used for various assays.

Bioinformatic Analysis . Signaling pathway analysis and biological function enrichment analysis were performed using the Kyoto Encyclopedia of Gene Genotype (KEGG). Data enrichment was performed using the R package "DOSE", "GO.db", "GSEABase" and "ClusterProfiler". Only cascades with a p-value adjusted for false positive rate (FDR) < 0.05 were displayed. The R-package "ggcorrplot" was used to analyze correlations. The R package "igraph" was used to construct pie charts of correlations. The R packages "ggalluvial" and "networkD3" were used to generate block diagrams for bacteria and Sankey diagrams. R-package "Mfuzz" was used for cluster trend analysis. Other bioinformatics analysis methods were performed using the Majorbio I-Sanger Cloud online platform (www.i-sanger.com). ROC biomarker analysis and random forest classification were performed using MetaboAnalyst 4.0 (https://www.metaboanalyst.ca/).

Sample acquisition for flow cytometry and analysis . Mice were anesthetized, blood samples were taken into tubes containing EDTA, and erythrocytes were removed using 1x erythrocyte lysis buffer. Before tissue harvesting, the brain was perfused with ice-cold PBS to avoid circulating immune blood cells, and the brain was removed, cut into fragments, and dissected according to the instructions for the Adult Brain Dissociation Kit (Miltenyi, cat. no. 130-107-677 ) using gentleMACS dissociator (Miltenyi Biotec). The brain homogenate was filtered through a 70 μm cell sieve and centrifuged at 300×g for 5 min at 4°C. The cell pellet was resuspended in cold PBS buffer and centrifuged again at 300×g for 5 min at 4°C. All samples were counted and adjusted to a density of 2-3×10 ⁶ /100 μl, labeled using the Live/Dead Kit for 30 min, and then centrifuged at 500×g for 3 min at 4°C. Cells were resuspended in 100 µl of PBS buffer, blocked with anti-CD16/32 antibody (Biolegend, cat. no. 101320) for 10 min, and incubated with antibody according to manufacturer's protocols at 4°C for 30 min. The following antibodies were used for FACS analysis: CD45（30-F11）-APC-Cy7（103116，Biolegend），CD11b（M1/70）-FITC（101205，Biolegend），CX3CR1（SA011F11）-PE-Dazzle 5901（4 Biolegend），F4/80（BM8）-BV421（123132，Biolegend），CD86（IT2.2）-PE（305438，Biolegend），CD206（15-2）-APC（321110，Biolegend（206） ）-BV785（321142，Biolegend），CD11c（N418）-PE-Cy7（117318，Biolegend），CD8（53-6.7）-Percp-Cy5.5（100734，Biolegend（H1.4，Ly-6C ）-PE-Dazzle 594（128044，Biolegend），Gr-1（RB6-8C5）-Percp-Cy5.5（108428，Biolegend），B220（RA3-6B2）-BV421（103240，9，Biolegend） -PE（115508，Biolegend），CD49b（DX5）-PE-Cy7（108922，Biolegend），CD4（GK1.5）-PE-Cy7（100422，Biolegend），CD4（GK1.5）-FITC，100Bioend6 ） ， Cxcr3 （cxcr3-173） -bv421 （126522 ， biolegend） ccr4 （l291h4 ）pe-q7 （359410 ， biolegend） ， ccr6 （-sapp） 129814 ， biolegend） biolegend） biolegend） biolegend） biolegend） biolegend） biolegend） biolegend （351304，Biolegend），CD25（3C7）-Percp-Cy5.5（101912，Biolegend），Live/Dead（423104，Biolegend）. Cells were added to 500 μl of PBS buffer, centrifuged at 500×g for 3 min at 4°C and resuspended in 200 μl of running buffer. The respective negative control, Fluorescence Minus One (FMO) control, and each fluorescence compensation sample were used to correct for fluorescence compensation and identify populations of interest. Cells were processed on a BD Aria III cytometer and data analyzed using FlowJo software.

Chip with antibodies . Brain homogenates (from 20 mg of tissue) were analyzed using a cytokine antibody microslide chip containing 200 proteins (RayBiotech, GSM-CAA-4000-1). 100 µl sample diluent was added to each well and incubated at room temperature for 30 minutes. The buffer was then replaced with another 100 µl of sample and incubated at room temperature for 2 h. Samples were removed and washed 5 times (5 min each time) using 150 µl of 1×wash buffer I and 2 times (5 min each time) with using 150 µl of 1x wash buffer II at room temperature with gentle rocking. 80 µl detection antibody cocktail was added to each well and incubated at room temperature for 2 h. each time) with 150 µl of 1x wash buffer II at room temperature with gentle rocking. Eighty microliters of streptavidin conjugated with an equivalent Cy3 dye was added to each well and incubated at room temperature for 1 hour. After 5 washes (5 minutes each time), the signal was visualized with a laser scanner. The data was then visualized with a heat map chart (www.metaboanalyst.ca).

Getting slices of the brain . Mice were transcardially perfused with 0.9% NaCl after deep anesthesia with pentobarbital (100 mg/kg, ip). Brain tissues were quickly removed, frozen and stored at -70°C. Serial frontal brain sections (12 μm thick) were obtained using a slicing freezing microtome (Leica Microsystems), placed on glass slides, and dried overnight in air at room temperature. Tissue sections were stored at -70°C used immediately.

Laser microdissection and analysis using q-PCR . Frozen mouse brain samples were cut into sections and collected on slides with a PEN membrane (Leica, 11600288). The hippocampus was removed by laser dissection microscopy (Leica Microsystems, LMD6). RNA was extracted using the RNeasy Micro Kit (Qiagen, 74004) and reverse transcribed into cDNA (Takara, PrimeScript RT Master Mix, RR036A). Q-PCR was performed using the ABI 7500 system by the SYBR method (Takara, SYBR Premix Ex Taq II). The following primers were used: synaptophysin-direct: CAGTTCCGGGTGGTCAAGG; synaptophysin-reverse: ACTCTCCGTCTTGTTGGCAC; actin direct: GCTCTTTTCCAGCCTTCCTT; actin-reverse: AGGTCTTTACGGAT GTCAACG.

Statistical Analysis . In the behavioral test, the animals were randomly assigned to different groups. An unpaired two-tailed Student's t-test was used to compare the two groups. To compare more than two groups, one-way ANOVA or two-way ANOVA followed by Dunnett's test was performed. All data with error bars are presented as mean ± sem. P < 0.05 was considered statistically significant. Most of the data was analyzed in GraphPad Prism. For imaging quantification, Iba-1 positive, Aβ42 positive, and phosphorylated tau positive cells were analyzed by ImageJ v1.8.0 with "area" recording.

Behavioral tests . Conducted the following behavioral tests: Morris water maze (Morris water maze, MWM), Y-maze and elevated plus maze (EPM). All movements were recorded using a camera and software (Jiliang) was used to calculate the corresponding parameters.

The MWM test is used to determine spatial learning and memory according to a previously published protocol. Briefly, mice were subjected to data acquisition experiments for 6 days, and 3 trials were performed for each mouse each day. Animals were released into the water in the desired starting position and the platform search latency was determined. On day 7, the platform was removed and the mice were allowed to swim for 60 seconds. The trajectory and the number of intersections of the platform areas were recorded using a video camera.

Working memory was assessed using a Y-maze according to the literature with some modifications. Y-consisted of three identical links (A, B, C) with different keys. Mice were placed in the starting link (A) and recorded the sequence of the investigated links (such as ABCBA). The total number of link entries and behavioral changes were recorded using a video camera. The accuracy in the Y-maze was the ratio between correct alternation and total alternation.

The EPM test is widely used to assess anxiety in animals and consists of two open links (30 cm x 6 cm), two closed links (30 cm x 6 cm x 22 cm), and a central region (6 cm x 6 cm). Each mouse was placed in the center of the maze towards the closed link and allowed to explore the maze for 5 minutes. The trajectory was recorded and the frequency of visits to the open link was calculated, which was negatively correlated with anxiety in mice.

Examples

Example 1 AD Progression Associated with Gut Microbiota Change and Immune Cell Infiltration

To assess the role of gut microbiota alteration in the pathogenesis of AD, the inventors used the 5XFAD transgenic (Tg) mouse model, which is widely used in AD research due to its rapid onset and plausible reproduction of many AD-associated pathological features and clinical phenotypes. She shows memory impairment at 4 months after birth, behavioral changes at 7 months, and neuronal loss at 9 months. Age-matched wild-type (WT) mice from the same strain grown under the same conditions were used as controls. In accordance with prior reports, the inventors have identified changes in Aβ plaque deposition, tau phosphorylation, synaptophysin expression, behavior, and the like. In particular, the deposition of Aβ plaques in the cortex and hippocampus rapidly accumulates starting from the 3rd month after birth (Fig. 7a). Tau phosphorylation in the brain of Tg mice was first detected at 5 months and gradually increased with age (Fig. 7b); the expression level of synaptophysin in the hippocampus decreased significantly from the 7th to the 9th month, indicating synaptic degeneration (Fig. 1a). A behavioral test in Tg mice demonstrated a significant impairment in discrimination learning at 9 months of age (FIG. 1b). It should be noted that early (2-3 months) and late (7-9 months) stages in Tg mice in the context of the present invention do not follow the same principle as late stages of human clinical AD. Late stage in Tg mice is symptomatically comparable to mild cognitive impairment (MCI) due to human AD. Thus, within the scope of the present invention, patients with MCI due to AD are used as subjects for human studies.

A marked shift in gut microbiota composition during the progression of AD in Tg mice was identified by further principal component analysis (PCA) for a series of time points, while virtually no change was observed in WT mice over time (Fig. 1c; Fig. 7c ).

Using OTU to track the dynamics of different bacterial types in Tg mice, the inventors found two characteristic changes in gut microbiota profiles in Tg mice during disease progression. At 2-3 months of age, Bacteroidetes, Firmicutes , and Verrucomicrobia were three of the most common bacterial types (46.8%, 32.3%, and 12.6%, respectively). At the age of 7-9 months, Firmicutes became the predominant bacteria, while the content of Bacteroidetes and Verrucomicrobia decreased significantly, indicating a change in bacterial types (Fig. 1d). The inventors further examined representative bacteria from Tg mice at each time point (Fig. 7d, Fig. 7e). These results indicated that the gut microbiota of Tg mice was highly dynamic, which is quite different from WT mice. Similar results were also obtained in the APP/PS1 doubly transgenic mouse model, another widely used model for the study of AD (Fig. 7f, Fig. 7g).

The inventors suggested that the observed change in the intestinal microbiota during the progression of AD may be associated with neuroinflammation. To test this hypothesis, the inventors assessed the inflammatory status in Tg mice. Immunostaining for IBA1, a hallmark of microglial activation, in brain sections of AD mice showed two distinct stages of microglial activation, at 3 months and 7-9 months, respectively (FIG. 1e). Given that microglial activation can be classified into two opposite types, the pro-inflammatory M1 subtype and the neuroprotective M2 subtype, the inventors also carefully characterized the M1 and M2 phenotypes. At an early stage at the age of 2-3 months, there was an increase in the level of both M1 cells and M2 microglial cells. In the following months, the level of M1 subtype cells continued to increase and peaked at 7-9 months, while the level of M2 microglial cells decreased from 3 to 5 months and remained at a low level thereafter (Fig. 1f). It can be seen that, as AD of Tg mice progressed over time, the pro-inflammatory M1 microglia subtype in the brain changed from comparable to the neuroprotective M2 microglia subtype (Fig. 1f, 2-3 months) to predominant in microglia (Fig. 1f, 5- 9 months) and there was an increase in overall microglial activation (Fig. 1e, 5-9 months).

In addition to microglia activation, AD-associated neuroinflammation is known to involve infiltration of peripheral immune cells. Thus, the inventors also analyzed the infiltration of peripheral immune cells into the brain during the progression of AD. It was found that the level of CD45 ^high cells in the brain was significantly higher in Tg mice than in WT mice, similar to the result of IBA1 staining (Fig. 1g). The subtypes of CD45 ^high cells over a series of time points were further analyzed during the progression of AD, which demonstrated the change in CD4 ⁺ T cells, since the main part of CD45 ^high cells has a similar trend to change with IBA1 (Fig.1h-i). Over the time period studied by the inventors, infiltrating Th1 and Th2 cells, the two major subtypes of CD4 ⁺ cells, showed similar dynamics to M1 and M2 microglial cells (FIG. 1j). It can be seen that as AD progressed in mice, Tg changed over time from being comparable to Th2 (Fig. 1j, 2-3 months) to predominant in CD4 ⁺ T cells (Fig. 1j, 5-9 months) and there was a general increased levels of CD4 ⁺ T cells (fig.1i, 5-9 months).

Thus, the inventors realized that as the gut microbial pattern changed, the immune cell population tended to change to a Th1- and M1-predominant state, the significance of these changes over time being particularly striking (FIGS. 1d-j). Similar results were also found in the APP/PS1 mouse model (Fig. 8, Fig. 7i, Fig. 7j, Fig. 23). It should be noted that the APP/PS1 mouse model and the 5XFAD transgenic (Tg) mouse model differ with respect to the progression of AD over time. Tg mice have obvious Aβ deposits at 5 months of age (FIG. 7a), while APP/PS1 mice have no obvious Aβ deposits at 5 months of age (FIG. 8a). Changes in gut microbes in these two models over time (fig. 1d, fig. 7g) are not completely robust, reflecting the intraspecies and inter-individual progression of AD and differences in gut microbes, however, they all show a correlation between changes in gut microbial patterns and changes in immune cells. over time.

The inventors also analyzed the correlation between gut microbiota content and the frequency of immune cells in the brain, and noted that early (2-3 months) bacterial composition is highly correlated with the numbers of M2 and Th2 cells in the brain (Fig. 1k, top) , however, changes in bacterial pattern were highly correlated with M1 and Th1 cells (Fig. 1k, bottom). Bacteria that were highly correlated with immune cells are shown in the right panel of Figure 1k, reaffirming the correlation between gut microbiota pattern and immune cells, especially Th1 and M1.

Overall, these results indicate that gut bacteria are associated with peripheral immune cell infiltration and neuroinflammation during the progression of AD, a study of which is described below.

Example 2: Changes in the Gut Microbiota Lead to Excessive Th1 Cell Infiltration and Excessive Activation of M1 Microglial Cells in the Brain

To determine whether a change in the gut microbiota is required to trigger peripheral immune cell infiltration and in turn neuroinflammation in the progression of AD, the inventors used an antibiotic cocktail containing ampicillin (0.1 mg/mL), streptomycin (0.5 mg/mL) and colistin (0.1  mg/mL) in late stage Tg mice (at 7 months of age) to reduce gut microbiota. Administration of the antibiotic to Tg mice at a late stage (at 7 months of age) resulted in a marked reduction in both microbial diversity and intestinal abundance (FIG. 2a).

Together with this change, the inventors found a decrease in the level of both infiltrating pro-inflammatory Th1 cells (Fig. 2b) and M1 cells (Fig. 2c) in the brain. This preliminary shows that by inhibiting the distribution of gut microbes in AD mice, the predominant state of Th1 and M1 in mice with advanced AD can be altered, indicating a causal relationship between changes in gut microbes and changes in immune cells.

In addition, these data were confirmed through a joint content experiment. WT mice were co-housed with Tg mice of the same age for 7 months from birth. Co-housed WT mice showed a reduction in discrimination learning comparable to Tg mice (FIG. 9a). To establish the reasons for this, analysis of the change in gut microbiota in these mice at 7 months of age showed that the composition of the gut microbiota was fairly similar between co-housed WT mice and Tg mice at the late stage (at 7 months of age), but significantly different from WT mice at that time. of the same age, kept separately (Fig. 2d), indicating that long-term exposure of WT mice to Tg bacteria (i.e., a gut microbial model in AD in Tg mice) caused a shift in the composition of the gut microbiota in WT mice towards Tg mice. , and at the same time caused a decrease in cognitive functions. This allows us to propose a strategy for creating an AD model that differs from the generally accepted scheme, i.e. by regulating the pattern of the WT model gut microbiota to change to the AD model microbiota.

Moreover, the levels of infiltrating Th1 cells between co-housed WT and Tg mice were also comparable, in both cases significantly higher than the levels in solitary WT mice (FIG. 2e). Meanwhile, M1 cell levels increased in co-housed WT mice (FIG. 2f). Simultaneously with the change in immune cells, the expression of cytokines in the brain showed a marked similarity between co-housed WT and Tg mice, but differed from their expression in WT mice (Fig. 2g).

Thus, the above description confirmed that by changing the gut microbiota of WT mice to the gut microbiota of Tg mice, Th1 and M1 cells of WT mice were transformed into a state similar to that of Tg mice, resulting in similar cognitive decline, and also confirming causation. -investigative relationship between changes in the intestinal microbiota and changes in immune cells, as well as cognitive function.

Moreover, the inventors used C57BL/6WT mice to create a model to demonstrate the therapeutic value of the method described above. The inventors conducted fecal microbiota transplantation (FMT) experiments using C57BL/6 WT mice and the results are shown in columns 6-10 of FIG.

C57BL/6WT mice were treated with antibiotics to provide an initial environment for subsequent fecal microbiota transplantation. Aggregated Aβ was injected into their hippocampus and then fecal bacteria from 7 to 9 month old Tg mice ("Receptor_C57_Receiving TG Fecal Bacteria") or fecal bacteria from WT mice ("Receptor_C57_Receive WT Fecal Bacteria") were orally administered as controls . This resulted in a significant increase in the level of Th1 cells and a significant decrease in the level of Th2 in the brain compared to the control (Fig.9b), which was consistent with the changes in Tg mice described above. This proved that Tg faecal transplantation can lead to a change in the pattern of intestinal microorganisms in WT mice, which also leads to a change in the pattern of immune cells.

Conversely, faecal transplantation from WT mice with a normal intestinal microorganism distribution pattern reduced the level of Th1 cells in the brains of recipient Tg mice (Fig. 9c). This showed that the gut microbial pattern of Tg mice changes relative to the gut microbial pattern of WT mice, and the immune cell pattern also changes.

These results re-confirm a causal relationship between changes in the gut microbiota and changes in brain immune cells (especially Th1/M1) and cognitive function in the progression of AD. For the treatment of AD, a strategy using the brain-gut axis has been proposed and validated.

Taken together, these data indicate that changes in the gut microbiota trigger peripheral immune cell infiltration and neuroinflammatory activation during AD progression. By administering agents (e.g., WT faeces with normal gut microbial distribution patterns or OM1, illustrated below) that regulate the relative abundance of gut microbes to Tg mice whose gut microbial distribution exhibits a disease-associated pattern, the gut microbial distribution of Tg mice was reorganized in the direction early and normal distribution of intestinal microorganisms. This effectively reversed the Th1/M1-dominated immune cell pattern in Tg mice, thereby improving cognitive function and treating AD. This provides a sound basis and strong evidence for further improving cognition and treating AD by reorganizing the distribution of gut micro-organisms in human AD patients (eg, the strategy of using agents to regulate the relative content of gut micro-organisms) to reverse the immune cell pattern; as well as to use the distribution of intestinal microorganisms and/or immune cell status (eg, Th1 status (eg, proportion in the population), M1 status (eg, proportion in the population)) as markers of AD progression.

Example 3 OM1 Facilitates Neuroinflammation Through Gut Microbiota Regulation

The indispensable role of the gut microbiota in the progression of AD, shown in the present description, may point to therapeutic implications of interfering with the gut microbiota. To confirm this again, the inventors used OM1, which is a clinically approved anti-AD drug extracted from brown algae. OM1 is a mixture of acidic linear oligosaccharides with a degree of polymerization ranging from dimer to decamer with an average molecular weight of approximately 1 kDa (FIG. 3a).

In late stage AD APP/PS1 model mice aged 9 months to 12 months, administered with OM1 for 3 months, OM1 showed a pronounced effect of attenuating cognitive decline as shown by enhanced spatial learning and memory performance in APP/PS1 mice in both the training trial (FIG. 3b) and the trial trial (FIG. 3c) in the Morris Water Maze (MWM) task. OM1 also significantly improved the performance of mice in the Y-maze (Fig. 3d). Recently, OM1 showed a therapeutic effect on reversal of impairment in AD patients in a 36-week, multicenter, randomized, double-blind, placebo-controlled phase 3 clinical trial (trial code: CTR20140274) in China. The inventors were interested in understanding whether OM1 demonstrates the effect of improving cognitive function by influencing the microbiota of patients with AD.

Interestingly, oral administration of OM1 for one month to late stage Tg mice, starting at 7 months of age, altered the gut microbiota composition (FIGS. 4a-b; FIG. 10a), restoring it in the direction of the WT pattern (FIGS. 13-14; Fig.16).

Along with altering the gut microbiota, administration of OM1 to Tg mice disrupted the correlation between brain lymphocyte counts and gut bacteria alteration (Fig. 4c; Fig. 10b and c), decreased levels of Th1 cells in the brain (Fig. 4d), significantly reduced activation of microglia to levels similar to WT mice (Fig. 4e) and reduced cytokine levels in the brain (Fig. 4f), restoring them in the direction of the WT pattern (Fig. 15). In parallel, OM1 administration significantly reduced Aβ plaque deposition, tau phosphorylation, and reduced discrimination learning observed in Tg mice (Fig. 4g-i). This again validated a strategy to restore the distribution of gut microbes, for example, using agents to regulate the relative abundance of gut microbes, to reverse the pattern of immune cells, thereby improving conditions and treating AD.

Further, the inventors performed fecal microflora transplantation (FMT) by transplanting the faeces of Tg mice injected with OM1 into recipient C57BL/6 WT mice that had received intraventricular injection of aggregated Aβ. The faeces of Tg mice injected with OM1 resulted in a decrease in the level of Th1 brain cells of the recipient mice compared to Tg mice without OM1 administration (FIG. 10e). It can be seen that the faeces of Tg mice injected with OM1 and the faeces of WT mice tested in Example 2 have a similar effect on restoring the distribution of gut microbes and reducing Th1, confirming the effect of restoring OM1 on the gut microbes of Tg mice. Consistently, administration of antibiotics reduced the effect of OM1 on Th1 cells, IBA1 levels, and cytokine expression in the APP/PS1 mouse model (FIGS. 10f-j). All of these data indicate that OM1 can alleviate neuroinflammation and cognitive decline through modulation of gut dysbiosis.

In general, the above in vivo mouse experiments have fully confirmed gut microbial changes and their tendency to regulate and reverse Th1/M1 immune cell predominance and reversal in cognitive impairments such as AD and their amelioration for brain-gut axis regulation cascades. in AD and interventional therapies. In addition, such regulatory cascades and interventions are consistently demonstrated in various mouse models (transgenic (Tg) 5XFAD model, APP/PS1 mouse model, C57BL/6 mouse model), although there are certain intraspecies and interindividual differences in initial state and transition process for gut microbes among these mice. Thus, the commonality of such regulatory cascades and interventions in different individuals is fully confirmed. Thus, a strategy is proposed to improve cognitive function and treat AD through the regulation of gut microbes to restore gut microbes to a normal and healthy state in order to reverse the state of immune cell-mediated disease.

The inventors used data from AD patients and healthy controls to compare and analyze AD brain-gut axis-associated microorganisms that differ between the two models, as summarized in Tables 1-2 and as illustrated in Figures 17-18. as a target for regulation. When applying the aforementioned treatment strategy aimed at the brain-gut axis in AD for humans, in addition to the interspecies differences in gut microbes between mice tested as rodents and humans as primates tested in the framework of the present invention, intraspecies and inter-individual differences in gut microorganisms between AD patients should also be fully considered. Thus, the mouse gut microbial types specifically shown in the above experiments are instructive only, and should not be rigidly and mechanically applied to human AD patients.

Example 4 OM1 Inhibits Neuroinflammation Through Regulation of Amino Acid Metabolism

Within the framework of the present invention, an intermediate relationship between alteration of the intestinal microbiota and alteration of immune cells or interference with it has also been investigated.

Causal relationship between gut microbial metabolites and Th1/Th2 naïve T-cell differentiation and intervention

To test for possible involvement of metabolites in immune modulation, in vitro cultured faecal supernatant from 7-month-old Tg mice was added to a culture of naive CD4 ⁺ T cells, which stimulated the differentiation of naive CD4 ⁺ T cells into Th1 and Th2 cells. In contrast, the faecal supernatant of OM1 injected Tg mice promoted differentiation to Th2 and inhibited differentiation to Th1 (Figure 11a), indicating that gut microbial metabolites influence the differentiation of naive T cells into Th1 and Th2 cells.

Causal relationship between amino acids in gut microbial metabolites and Th1/Th2 naïve T cell differentiation and intervention

The inventors further used a non-targeted metabolomics method to characterize the fecal metabolome. A total of 11289 metabolites were identified in faecal samples from WT, Tg mice and Tg mice injected with OM1 (Fig. 11b-c). Among these metabolites, 124 metabolites annotated in the METLIN database were significantly altered, decreased, or increased in Tg mice relative to WT mice, indicating that they are associated with AD. Strikingly, all of these metabolite changes can be largely reversed by OM1 treatment (FIGS. 11d-f), indicating that AD treatment restored the abnormal state of these AD-related metabolites. These altered metabolites were further annotated using the Human Metabolome Database (HMDB) and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) to yield a total of 31 metabolites that were differentially upregulated in WT, Tg and OM1 injected Tg mice, which could be compared to all three databases (HMDB, METLIN, KEGG). Analysis of the enrichment cascades for these metabolites using MBROLE or MetaboAnalyst further demonstrated significant changes in amino acid-related metabolic cascades and enzymes, especially phenylalanine-related cascades (FIG. 5a).

Thus, the inventors decided to focus on amino acids for further testing. Plasma concentrations of a total of 36 amino acids were screened (Table 3) in both WT and Tg mice. A random forest algorithm was used to classify these amino acids, and some of them were sorted as shown in Figure 19 and presented in Table 4. Phenylalanine was ranked as the highest, followed by isoleucine, serotonin, histidine, and acetylornithine. Multivariate exploratory analysis of these five amino acids revealed significant differences between WT and Tg mice according to the receiver operating characteristics (ROC) curve (Fig. 5b; Fig. 11h), indicating that they are closely associated with disease progression. The inventors then examined the concentration of selected amino acids in faecal and blood samples in Tg mice treated with OM1 or not and compared it with WT mice. Referring to FIG. 20 and FIG. 21, the inventors found that OM1 affected various amino acids and they recovered from the Tg pattern to the wild type pattern. In particular, the concentrations of phenylalanine and isoleucine were significantly higher in the feces of Tg mice than in the faeces of WT mice, and administration of OM1 significantly reduced their concentrations to a level comparable to that of WT mice (Fig. 5c). Similar changes in the content of phenylalanine and isoleucine were found in the blood (fig.5d). Of note, phenylalanine and isoleucine are typical gut microbial metabolites that change with disease progression and are reversed by OM1. In addition, the inventors also found that after administration of OM1, mouse cytokines tend to recover to the wild-type pattern (FIG. 22). This corresponds to the cytokine status in WT mice tending to change to a pattern in Tg mice as shown in FIG. 2g when co-habitated with Tg mice.

To test whether the increase in these amino acids was the result of an alteration in the gut microbiota, thereby allowing interference with amino acids by obstructing the gut microbiota, the inventors examined the concentration of amino acids in the FMT study. Feces from 2-month-old WT mice could significantly reduce phenylalanine and isoleucine levels in Tg mice (FIG. 11i). Similarly, co-housed WT mice described in FIG. 2, blood concentrations of phenylalanine and isoleucine also increased, which was comparable to Tg mice (FIG. 11j). Thus, it could be determined that when WT mice were co-housed with Tg mice to convert their own WT gut microbial pattern into a Tg pattern, abnormal production of phenylalanine and isoleucine occurred and levels of phenylalanine and isoleucine increased. In contrast, transplantation of faeces from WT mice containing normal WT gut microbiota into Tg mice caused the gut microbiota of Tg mice to shift towards the WT pattern, resulting in the restoration of abnormal phenylalanine and isoleucine production, and phenylalanine and isoleucine levels decreased. This confirmed that levels of the gut microbial metabolites phenylalanine and isoleucine could be restored by restoring the gut microbiota of Tg mice.

Confirmation that phenylalanine and isoleucine influence and interfere with naive T-cell differentiation into Th1/Th2

To assess the effects of phenylalanine and isoleucine on cells, these two compounds were added directly to a culture of naive CD4 ⁺ T cells. There was an increase in both differentiation of Th0 cells into Th1 cells (Fig. 5e) and proliferation of Th1 cells (Fig. 5f). In contrast, administration of OM1 can inhibit phenylalanine and isoleucine-induced Th1 differentiation and stimulation of Th1 cell proliferation, indicating that OM1 not only affects gut microbes, but also directly affects their amino acid metabolite itself. In addition, the inventors gave WT mice an intraperitoneal injection of phenylalanine and isoleucine and found that the number of Th1 cells in the blood increased significantly (Fig. 5g), confirming that amino acids promote differentiation of Th0 into Th1 in vivo . These results indicate that the accumulation of phenylalanine and isoleucine can increase the number of Th1 cells in the blood.

Interfering with naive T cell differentiation by interfering with amino acid uptake by naive T cells

Amino acids can be taken up by immune cells through specialized transporters. The inventors further examined the expression levels of SLC7A5, the transporter of phenylalanine and isoleucine, in naive CD4 ⁺ T cells and found that SLC7A5 was expressed in CD4 ⁺ T cells. Incubation of CD4 ⁺ T cells with ¹³ C-labeled phenylalanine demonstrated uptake of phenylalanine by CD4 ⁺ T cells, which could be blocked by the pharmacological inhibitor of SLC7A5, JPH 203 (Fig. 11k), indicating that it is able to inhibit amino acid uptake by immune cells through inhibition carriers of amino acids. The inventors further tested the resulting change in the ratio of Th1 cells. 5XFAD mice aged 6 months were injected with 50 mg/kg JPH 203 or vehicle control via intraperitoneal injection every day. One month after administration, mice were sacrificed, and the proportion of pro-inflammatory Th1 cells in the brain of mice in the control group and the JPH 203 administration group was analyzed by flow cytometry. This was representative, reflecting neuroinflammation in the brain. The results are presented in Fig.13. Compared with the vehicle control group, administration of JPH203 for one month significantly reduced the proportion of pro-inflammatory Th1 cells in the mouse brain, demonstrating that through inhibition of the amino acid transporter, amino acid uptake by immune cells is inhibited, thereby preventing amino acids from promoting immune cell differentiation and reducing neuroinflammation in the brain.

Confirmation of abnormal levels of phenylalanine and isoleucine in people with AD

Finally, the inventor confirms this in humans by investigating whether the above data can be replicated in patients with MCI due to AD (see the method used in this study for the definition of MCI used in this study). Indeed, the concentrations of phenylalanine and isoleucine, as well as the number of Th1 cells in the blood of individuals with MCI due to AD (n=9) were significantly higher than in age-matched healthy individuals (n=18) (Fig.5h, i). Elevated blood levels of both phenylalanine and isoleucine were also confirmed in another small group with MCI due to AD (FIG. 5j), thus allowing planning strategies for human diagnosis and treatment based on this.

In general, the inventors have found that several gut microbial metabolites are involved in the subsequent transition of immune cells to a Th1-dominated state. The inventors specifically investigated amino acids in metabolites, especially phenylalanine and isoleucine, and confirmed a causal relationship between changes in gut microbiota composition, abnormal production of phenylalanine and isoleucine, and overdifferentiation into Th1 naïve T cells. Through the administration of WT and OM1 faecal bacteria, which were confirmed above to restore the abnormal microbiota of Tg mice towards normal WT intestinal microbiota, abnormally high levels of phenylalanine and isoleucine were reduced and restored to normal levels. Moreover, differentiation of Th0 cells into Th1 cells was inhibited, reversing the Th1-dominated disease state, suggesting that gut microbial metabolites are a bridge between abnormal gut microbiota composition and abnormal immune cell status, and they are part of the brain-gut axis interconnections. with AD. The inventors have also tested other ways of interfering with metabolites, such as reducing the level of metabolites or preventing the uptake of metabolites by immune cells, to interfere with the subsequent abnormal state of immune cells via gut microbial metabolites, and thus the cognitive state.

Although the principle of the present invention has been described above in relation to the preferred embodiments, it should be well understood that the description is given by way of example only and not by way of limitation on the scope of the present invention.

Table 1 List of altered flora in AD patients or mice

Classification Name in English Appropriate name Type Actinobacteria p__Actinobacteria Type Bacteroidetes p__ Bacteroidetes Type Firmicutes p__ Firmicutes Type Proteobacteria p__Proteobacteria Type Tenericutes p__Tenericutes Class Beta Proteobacteria c__Beta Proteobacteria Order Burkholderiales o__Burkholderiales Family Bacteroidaceae f__Bacteroidaceae Family Bifidobacteriaceae f__Bifidobacteriaceae Family Burkholderiaceae f__Burkholderiaceae Family Clostridiaceae f_Clostridiaceae Family Desulfovibrionaceae f__Desulfovibrionaceae Family Erysipelotrichaceae f__Erysipelotrichaceae Family Fusobacteria ceae f__ Fusobacteria ceae Family Gemellaceae f_Gemellaceae Family Helicobacteriaceae f__Helicobacteraceae Family Lachnospiraceae f__Lachnospiraceae Family Mogibacteriaceae f__Mogibacteriaceae Family norank_Bacteroidales_S24-7_group f__Bacteroidales_S24-7_group Family Peptostreptococcaceae f__Peptostreptococcaceae Family Prevotellaceae f__Prevotellaceae Family Rikenellaceae f__Rikenellaceae Family Ruminococcaceae f__Ruminococcaceae Family Staphylococcusaceae f__Staphylococcaceae Family Turicibacteraceae f__ Turicibacteraceae Family Turicibacteriaceae f__turicibacteriaceae Genus Actinobacillus_actinomycetemcomitans g__Actinobacillus_actinomycetemcomitans Genus Actinobacteria g__Actinobacteria Genus Adlercreutzia g__Adlercreutzia Genus Alistipes g__Alistipes Genus Alternaria g__Alternaria Genus Bacteroides g__Bacteroides Genus Bifidobacteria g__Bifidobacteria Genus Bifidobacterium g__Bifidobacterium Genus Bilophila g__Bilophila Genus Blautia g__Blautia Genus Botrytis g__Botrytis Genus Candida g__Candida Genus cc115 g__cc115 Genus Clostridium g__Clostridium Genus dialer g__Dialister Genus E_coli_K99 g__E_coli_K99 Genus Escherichia g__Escherichia Genus Eubacterium_rectale g__[Eubacterium]_rectale Genus Fusarium g__Fusarium Genus Gemella g__Gemella Genus Lactobacilli g__Lactobacilli Genus Malassezia g__Malassezia Genus Phascolarctobacterium g__Phascolarctobacterium Genus Shigella g__Shigella Genus SMB53 g__SMB53 Genus Sutterella g__Sutterella Genus Tannerella_forsythia g__Tannerella_forsythia Genus Turicibacter g__turicibacter Genus g__Escherichia-Shigella

Table 2. List of flora with significant differences in the relative content of intestinal bacteria between patients with AD and healthy controls (HC)

Classification generic name AD -mean value (%) HC - average value (%) fold change in AD versus HC Upregulation or downregulation in AD versus HC Type p__ Firmicutes 39.41 44.07 0.8942591 Downregulation Type p__ Bacteroidetes 38.03 39.9 0.9531328 Downregulation Type p__Proteobacteria 12.85 8.086 1.5891665 Upregulation Type p__Actinobacteria 5.065 3.522 1.4381034 Upregulation Type p__ Fusobacteria 2.028 1.001 2.025974 Upregulation Type p__ Cyanobacteria 0.7771 1.227 0.6333333 Downregulation Type p__ Verrucomicrobia 0.2726 0.7585 0.3593935 Downregulation Class c__Bacteroidia 37.38 39.51 0.9460896 Downregulation Class c_Clostridia 25.5 32.33 0.7887411 Downregulation Class c__Gamma Proteobacteria 10.19 4,734 2.1525137 Upregulation Class c__Bacilli 5.575 6.606 0.8439298 Downregulation Class c__Negativicutes 6.319 4.507 1.4020413 Upregulation Class c__Actinobacteria 5.791 3.522 1.6442362 Upregulation Class c__Fusobacteriia 2.379 1.001 2.3766234 Upregulation Class c__Beta Proteobacteria 1.298 1.438 0.9026426 Downregulation Class c__Alpha Proteobacteria 1.104 1.349 0.818384 Downregulation Order o__Bacteroidales 37.38 39.51 0.9460896 Downregulation Order o__Clostridiales 25.43 32.24 0.7887717 Downregulation Order o__Enterobacteriales 8.983 3.453 2.6015059 Upregulation Order o__Selenomonadales 6.319 4.507 1.4020413 Upregulation Order o__Lactobacillales 4,803 5.774 0.8318324 Downregulation Order o__Bifidobacteriales 3.887 1.304 2.9808282 Upregulation Order o__ Fusobacteriales 2.379 1.001 2.3766234 Upregulation Order o__Burkholderiales 1.012 1.158 0.8739206 Downregulation Order o_Bacillales 0.7707 0.8287 0.9300109 Downregulation Family f__Rikenellaceae 0.5028 1.018 0.4939096 Downregulation Family f__Ktedonobacteraceae 0.000187 0.001769 0.1057094 Downregulation Family f__Nannocystaceae 0 0.001947 0 Downregulation Genus g__Lachnospiraceae_NK4A136_group 0.5582 1.478 0.3776725 Downregulation Genus g__Alistipes 0.4237 0.9265 0.4573125 Downregulation Genus g__Ruminococcus_1 0.2783 0.9167 0.303589 Downregulation Genus g__Ruminococcaceae_UCG-002 0.4232 0.6621 0.6391784 Downregulation Genus g__Ruminococcaceae_UCG-005 0.2549 0.5889 0.4328409 Downregulation Genus g__Coprococcus_2 0.1136 0.6677 0.1701363 Downregulation Genus g__Tyzzerella_4 0.4165 0.08026 5.1893845 Upregulation Genus g__Lachnospiraceae_UCG-001 0.04241 0.1747 0.242759 Downregulation Genus g__Anaerotruncus 0.08045 0.1342 0.5994784 Downregulation Genus g__Cloacibacterium 0.005284 0.001851 2.8546731 Upregulation Genus g__norank_f__Ktedonobacteraceae 0.000187 0.001769 0.1057094 Downregulation Genus g__Nannocystis 0 0.001947 0 Downregulation Genus g__norank_f__Hydrogenophilaceae 0.001435 0.0002894 4.9585349 Upregulation View s__unclassified_g__Subdoligranulum 0.1108 0.7963 0.1391435 Downregulation View s__unclassified_g__Alistipes 0.2412 0.6416 0.3759352 Downregulation View s__uncultured_organism_g__Parasutterella 0.09518 0.4442 0.2142729 Downregulation View s__unclassified_g__Tyzzerella_4 0.4165 0.08026 5.1893845 Upregulation View s__uncultured_organism_g__ Ruminococcaceae_UCG-005 0.1649 0.1728 0.9542824 Downregulation View s__uncultured_organism_g__Anaerotruncus 0.02364 0.05794 0.4080083 Downregulation View s__uncultured_Alistipes_sp._g__Alistipes 0.02727 0.04977 0.5479204 Downregulation View s__Lachnospiraceae_bacterium_TF01-11 0.009628 0.05391 0.178594 Downregulation View s__unclassified_g__Anaerotruncus 0.01064 0.01785 0.5960784 Downregulation View s__unclassified_g__norank_o__Mollicutes_RF9 0.003794 0.01637 0.2317654 Downregulation View s__uncultured_bacterium_g__Family_XIII_AD3011_group 0.008094 0.007951 1.0179852 Upregulation View s__uncultured_bacterium_g__norank_f__Christensenellaceae 0.007214 0.007841 0.9200357 Downregulation View s__uncultured_bacterium_g__Cloacibacterium 0.005284 0.001851 2.8546731 Upregulation View s__uncultured_organism_g__Peptococcus 0 0.006374 0 Downregulation View s__Mycobacterium_celatum_g__Mycobacterium 0.00115 0.005163 0.2227387 Downregulation View s__unclassified_g__Oceanobacillus 0.004827 0.001018 4.7416503 Upregulation View s__Alistipes_putredinis_DSM_17216 0.000187 0.003568 0.0524103 Downregulation View s__Prevotella_loescheii 0.002635 0.0004672 5.6399829 Upregulation View s__uncultured_bacterium_g__norank_o__MBA03 0.002428 0.0004532 5.3574581 Upregulation View s__Eubacterium_brachy 0.002443 0.0001614 15.136307 Upregulation View s__uncultured_bacterium_adhufec108 0 0.002173 0 Downregulation View s__uncultured_Clostridiales_bacterium_g__norank_f__Ktedonobacteraceae 0.000187 0.001769 0.1057094 Downregulation View s__Nannocystis_pusilla 0 0.001947 0 Downregulation View s__bacterium_2013Ark19i 0.001435 0.0002894 4.9585349 Upregulation View s__Auxenochlorella_protothecoides_g__norank 0.001463 0.0001447 10.110574 Upregulation View s__uncultured_ Bacteroidetes _bacterium_g__Dinghuibacter 0 0.0009268 0 Downregulation

Table 3. The list below gives the name of the amino acids identified in the blood of WT (2-9 months) and Tg (2-9 months) mice. Associated with Fig.5b.

[01] Name of amino acids glycine alanine serine valine 4-OH proline asparagine glutamine tyrosine hypotaurine methionine sulfoxide beta alanine threonine leucine ornithine aspartic acid methionine histidine phenylalanine arginine proline taurine isoleucine glutamic acid citrulline tryptophan kynurenine GABA lysine pyroglutamic acid acetylornithine asymmetric dimethylarginine alpha-aminoadipic acid carnosine creatinine putrescine serotonin

Table 4. ROC analysis of all amino acid markers in the blood of WT mice and Tg mice in order of frequency of selection

Amino acid Rank Frequency wt Tg phenylalanine 0.42 short high isoleucine 0.4 short high Serotonin 0.36 short high histidine 0.34 short high acetylornithine 0.32 high short Kynurenine 0.32 short high tryptophan 0.28 short high leucine 0.28 short high glutamic acid 0.26 short high pyroglutamic acid 0.22 short high valine 0.2 short high glutamine 0.2 short high beta alanine 0.2 short high hypotaurine 0.18 short high tyrosine 0.12 short high asymmetric dimethylarginine 0.12 high short glycine 0.1 short high Carnosine 0.08 short high 4-OH proline 0.08 short high aspartic acid 0.06 high short threonine 0.06 short high alpha-aminoadipic acid 0.04 short high ornithine 0.04 short high Creatinine 0.04 short high alanine 0.04 short high GABA 0.02 short high methionine sulfoxide 0.02 short high proline 0.02 short high

Claims (14)

1. The use of an agent for inhibiting the uptake of amino acids by naive T cells in the peripheral blood of a mammal for the manufacture of a medicament for the treatment of Alzheimer's disease in an individual, where the amino acid is one or more selected from the following: 4-OH proline, acetylornithine, alanine, alpha- aminoadipic acid, asparagine, aspartic acid, asymmetric dimethylarginine, beta-alanine, carnosine, citrulline, creatinine, GABA, glutamic acid, glutamine, glycine, histidine, hypotaurine, isoleucine, kynurenine, leucine, lysine, methionine, methionine sulfoxide, ornithine, phenylalanine , pipecolic acid, proline, putrescine, pyroglutamic acid, serine, serotonin, taurine, threonine, tryptophan, tyrosine and valine. 2. Use according to claim 1, where the amino acid is one or more selected from phenylalanine, isoleucine, serotonin, histidine and acetylornithine; more preferably phenylalanine and/or isoleucine; most preferably phenylalanine. 3. Use according to claim 1, wherein the agent inhibits amino acid uptake by naive T cells by inhibiting the transport of amino acids into the naive T cell via a transporter. 4. Use according to claim 3, where the carrier is SLC7A5. 5. Use according to claim 4, wherein the agent comprises one or more selected from JPH 203, BCH and KMH-233. 6. Use according to claim 1, wherein the agent reduces the proportion of pro-inflammatory Th1 cells among CD4+ T cells in a sample from an individual by about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 , 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37 , 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62 , 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87 , 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100% or more; and/or makes the proportion of pro-inflammatory Th1 cells in CD4+ T cells close to or equal to the corresponding proportion of pro-inflammatory Th1 cells in CD4+ T cells of the corresponding normal individual, where close to means that the difference between the index before adjustment and the corresponding index of the corresponding normal subject decreases by more than or exactly 10%. 7. Use according to claim 1, wherein the agent reduces the relative level of amino acid uptake by naive T cells by approximately 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75 , 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, 200 , 205, 210, 215, 220, 225, 230, 235, 240, 245, 250, 255, 260, 265, 270, 275, 280, 285, 290, 295, 300 or more; and/or makes the relative level of amino acid uptake by naive T cells close to or equal to the corresponding relative level of amino acid uptake by naive T cells of the corresponding normal individual, where close to means that the difference between the index before adjustment and the corresponding index of the corresponding normal subject decreases by more than or even on 10%. 8. A method for treating a patient with Alzheimer's disease, comprising: administering an agent for inhibiting amino acid uptake by naive T cells in the peripheral blood of a mammal to a patient such that the proportion of pro-inflammatory Th1 cells among the CD4+ T cells in the patient is regulated to be close to or equal to the proportion of pro-inflammatory Th1 cells among the CD4+ T cells -cells in the corresponding normal sample, where close to means that the difference between the index before adjustment and the corresponding index of the corresponding normal subject decreases by more than or exactly 10%, where the amino acid is one or more selected from the following: 4-OH proline, acetylornithine, alanine, alpha-aminoadipic acid, asparagine, aspartic acid, asymmetric dimethylarginine, beta-alanine, carnosine, citrulline, creatinine, GABA, glutamic acid, glutamine , glycine, histidine, hypotaurine, isoleucine, kynurenine, leucine, lysine, methionine, methionine sulfoxide, ornithine, phenylalanine, pipecolic acid, proline, putrescine, pyroglutamic acid, serine, serotonine, taurine, threonine, tryptophan, tyrosine, and valine. 9. A method for treating a patient with Alzheimer's disease, comprising: administering to a patient an agent for inhibiting amino acid uptake by naive T cells in the peripheral blood of a mammal, so that the relative level of amino acid uptake of naive T cells in the patient is adjusted to be close to or equal to the corresponding relative level of amino acid uptake by naive T cells in the corresponding normal sample, where close to means that the difference between the index before adjustment and the corresponding index of the corresponding normal subject decreases by more than or exactly 10%, where the amino acid is one or more selected from the following: 4-OH proline, acetylornithine, alanine, alpha-aminoadipic acid, asparagine, aspartic acid, asymmetric dimethylarginine, beta-alanine, carnosine, citrulline, creatinine, GABA, glutamic acid, glutamine , glycine, histidine, hypotaurine, isoleucine, kynurenine, leucine, lysine, methionine, methionine sulfoxide, ornithine, phenylalanine, pipecolic acid, proline, putrescine, pyroglutamic acid, serine, serotonine, taurine, threonine, tryptophan, tyrosine and valine.

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