Application of isovaleryl carnitine in prevention and treatment of progress of salt-sensitive hypertension state

Abstract

The invention provides an application of isovaleryl carnitine in preventing and treating the progress of a salt-sensitive hypertension state. The invention provides application of isovaleryl carnitine in a sample from an individual as a target spot in screening and / or preparing a reagent and / or a medicine for preventing and treating salt-sensitive hypertension. The invention also provides application of the isovaleryl carnitine or a reagent for detecting the isovaleryl carnitine in a sample from an individual in preparation of a product for evaluating the progress of the blood pressure state of the individual, and also provides application of the isovaleryl carnitine in preparation of a product for improving, preventing and / or treating salt-sensitive hypertension. The invention finds that isovaleryl carnitine is significantly related to hypertension attack and blood pressure state progress, and is expected to become a potential dietary supplement or intervention target for preventing and treating hypertension.

Description

TECHNICAL FIELD

[0001] The present application relates to a salt-sensitive hypertension diagnosis and treatment technology, in particular to the use of isovaleryl carnitine as a marker in the preparation of a dietary supplement and / or a drug for preventing and / or treating the progression of salt-sensitive hypertension. BACKGROUND

[0002] Global Burden of Disease Study shows that high-salt diet is the leading dietary risk factor for cardiovascular disease mortality. The effect of high-salt diet on the cardiovascular system is mainly related to sodium-induced blood pressure elevation. Studies have shown that the blood pressure of people with high-salt diet is significantly higher than that of people with low-salt diet. However, the response of blood pressure to sodium varies among populations, which is known as blood pressure salt sensitivity. The blood pressure of some individuals changes significantly with changes in sodium intake, which is called salt-sensitive; the blood pressure of some individuals is less responsive to sodium, which is called salt-insensitive or salt-resistant. High blood pressure caused by high-salt diet is called salt-sensitive hypertension. Compared with non-salt-sensitive individuals, salt-sensitive individuals have a higher risk of developing hypertension and cardiovascular disease. Previous studies have extensively explored the genetic and environmental factors associated with blood pressure salt sensitivity. For example, the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) study identified a series of genetic susceptibility loci associated with blood pressure salt sensitivity. However, the biological mechanisms from high-salt diet to salt-sensitive hypertension are not fully understood, and whether different blood pressure salt sensitivity populations have different molecular characteristics remains to be revealed.

[0003] With the rise of multi-omics technology, more and more studies use proteomics, metabolomics, gut microbiome technology to reveal the mechanism of disease development and to explore potential therapeutic and intervention targets. The gut is the first and largest site of sodium salt digestion and absorption, so the gut microbiota may play a certain role in regulating the response of blood pressure to sodium. Previous studies have also shown that high-salt diet can also affect the concentration of plasma metabolites. Therefore, it can be reasonably inferred that there may be some relationship between high-salt diet, gut microbiota, plasma metabolome, and salt-sensitive hypertension. Revealing the effects of high-salt diet on gut microbiota and metabolites can provide new insights into the biological mechanisms of salt-sensitive hypertension. Describing the gut microbiota and metabolome characteristics of different blood pressure salt sensitivity populations can further clarify the causes of blood pressure salt sensitivity and provide some basis for individualized precision prevention. SUMMARY

[0004] One object of the present application is to provide a blood pressure salt sensitivity-related marker.

[0005] Another object of the present invention is to provide the application of blood pressure salt sensitivity-related biomarkers.

[0006] The inventors of this invention investigated the effects of a high-sodium diet on gut microbiota and plasma metabolites, depicting the differences in gut microbiota and metabolome characteristics among individuals with varying blood pressure salt sensitivity, and identifying potential intervention targets for the prevention of salt-sensitive hypertension. Specifically, this invention explored the association between blood pressure salt sensitivity and the response of gut microbiota and metabolites to salt, finding significant differences in the responses of 22 gut microbiota species and 9 metabolites across different blood pressure salt sensitivity groups. Furthermore, it constructed a gut microbiota-metabolite regulatory network influencing blood pressure salt sensitivity, and correlation analysis revealed that the gut-acylcarnitine axis may be a key pathway leading to differences in blood pressure salt sensitivity among individuals. This invention also found that isovalerylcarnitine is significantly associated with the risk of hypertension and the progression of blood pressure status, and can serve as a potential dietary supplement or intervention target for the prevention and treatment of hypertension.

[0007] On the one hand, the present invention provides the use of isovalerylcarnitine as a target in samples from individuals for screening and / or preparation of reagents and / or drugs for the prevention and treatment of salt-sensitive hypertension.

[0008] On the other hand, the present invention provides the use of isovalerylcarnitine or a reagent for detecting isovalerylcarnitine in a sample from an individual in the preparation of products for assessing an individual's risk of developing hypertension and / or the progression of blood pressure status.

[0009] According to a specific embodiment of the present invention, the sample may be blood or plasma. The concentration of isovalerylcarnitine in the sample from an individual can be detected using any feasible reagent or method in the prior art.

[0010] According to a specific embodiment of the present invention, the individual is of East Asian race, preferably Chinese.

[0011] According to a specific embodiment of the present invention, the level of isovalerylcarnitine in samples from individuals is significantly negatively correlated with the progression of blood pressure status.

[0012] According to a specific embodiment of the present invention, the level of isovalerylcarnitine in samples from individuals is significantly negatively correlated with the risk of developing hypertension.

[0013] According to a more specific embodiment of the invention, for every SD increase in the logarithmic concentration of isovalerylcarnitine in an individual's sample, the individual's risk of progressing from ideal blood pressure to prehypertension or hypertension is reduced by 19% (HR=0.81, 95% CI: 0.70, 0.93), and the risk of progressing from normal blood pressure to hypertension is reduced by 17% (HR=0.83, 95% CI: 0.73, 0.95).

[0014] According to a specific embodiment of the present invention, the isovalerylcarnitine may be used independently for the application (as a target in screening and / or preparing reagents and / or drugs for preventing and treating blood pressure salt sensitivity, or isovalerylcarnitine or a reagent for detecting isovalerylcarnitine in samples from individuals for assessing an individual's risk of developing hypertension and / or progression of blood pressure status), or in combination with other salt sensitivity markers for the application.

[0015] According to a specific embodiment of the present invention, the other salt-sensitive markers include one or more of salt-sensitive gut bacteria and salt-sensitive metabolites.

[0016] According to some specific embodiments of the present invention, the salt-sensitive intestinal bacteria include *Alistipes ihumii*, *Anaerotruncus colihominis*, *Clostridiales bacterium* 42_27, *Clostridiales bacterium* 52_15, *Clostridium sp. CAG:389*, *Clostridium sp. CAG:413*, *Clostridium sp. CAG:780*, *Dialister sp. CAG:357*, *Eubacterium sp. CAG:180*, *Firmicutes bacterium* CAG:124*, *Firmicutes bacterium* CAG:129_59_24*, *Firmicutes bacterium* CAG:137*, *Firmicutes bacterium* CAG:170*, *Firmicutes bacterium* CAG:176*, *Firmicutes bacterium* CAG:24053_14*, and *Firmicutes bacterium*. One or more of the following: CAG:555, Firmicutes bacterium CAG:83, Intestinimonas butyriciproducens, Oscillibacter sp. CAG:241, Oscillibacters sp. ER4, Pseudoflavonifractor capillosus, and Ruminococcus sp. CAG:177.

[0017] According to some specific embodiments of the present invention, the salt-sensitive metabolite includes one or more of methylcysteine, histidine, phenylpyruvic acid, L-carnitine, valerate, 2-hydroxybutyric acid, α-hydroxyisobutyric acid, and 3-hydroxyisovalerate.

[0018] According to some preferred embodiments of the present invention, the other salt-sensitive markers include one or more of L-carnitine and valerate.

[0019] On the other hand, the present invention also provides the use of isovalerylcarnitine in the preparation of products for improving, preventing and / or treating salt-sensitive hypertension.

[0020] According to some specific embodiments of the present invention, for individuals with salt-sensitive hypertension or at risk of salt-sensitive hypertension, the dosage of isovalerylcarnitine may be 0.15-0.22 mg / kg body weight / day.

[0021] According to some specific embodiments of the present invention, the isovalerylcarnitine is an active ingredient for reducing systolic and / or diastolic blood pressure in patients with salt-sensitive hypertension.

[0022] According to some specific embodiments of the present invention, the products for improving, preventing, and / or treating salt-sensitive hypertension are dietary supplements or medicines. More specifically, the products for improving salt-sensitive hypertension are typically dietary supplements, and the products for preventing and / or treating salt-sensitive hypertension are typically medicines.

[0023] According to a specific embodiment of the present invention, this invention identifies key biomarkers based on the MetaSalt dietary salt intervention trial. This trial, conducted in 2019, enrolled 528 participants and included a 23-day intervention period, comprising 3 days of baseline observation, 10 days of low-salt intervention (3 g salt / day), and 10 days of high-salt intervention (18 g salt / day). Based on the response of mean arterial pressure to sodium intervention, the population was divided into salt-resistant, moderately salt-sensitive, and extremely salt-sensitive groups. Further, based on a prospective Chinese cohort population (n=3907) with a median follow-up of 5.5 years, the association between key biomarkers and the prevalence, onset, and progression of hypertension was explored. This invention uses shotgun metagenomic sequencing for fecal gut microbiota detection and ultra-high performance liquid chromatography-tandem mass spectrometry for plasma targeted metabolomics detection. Results showed that 85 (16%) gut microbiota species were identified in the MetaSalt population (P<9.42×10⁻⁶). -5 ) and 71 kinds (31.98%) of metabolites (P<2.25×10) -4The effects of high sodium intake intervention were observed. From these salt-related biomarkers, changes in 22 gut microbiota and 9 metabolites were further identified as significantly correlated with blood pressure salt sensitivity (P<0.05). Correlation analysis suggested that the gut-acylcarnitine axis is a key pathway affecting blood pressure salt sensitivity, with valerylcarnitine, isovalerylcarnitine, and 3-hydroxyisovaleric acid as core metabolites. Further focusing on isovalerylcarnitine revealed a significant negative correlation between it and the risk of hypertension and the progression of blood pressure status (P<0.05). For example, for every standard deviation increase in the logarithmic concentration of isovalerylcarnitine, the risk of progressing from ideal blood pressure to prehypertension or hypertension decreased by 19% (hazard ratio = 0.81, 95% confidence interval: 0.70, 0.93). Further research in this invention found that isovalerylcarnitine significantly reduced high-salt-induced blood pressure elevation in Dahl salt-sensitive rats.

[0024] In summary, this invention is the first to explore the effects of a high-sodium diet on the gut microbiota and plasma metabolome of the Chinese population: based on dietary salt intervention trials, metagenomic sequencing and plasma targeted metabolomics technologies were used to discover that a high-sodium diet can significantly affect the levels of many gut microbiota species and plasma metabolites. This invention further characterizes the gut microbiota and plasma metabolome of blood pressure salt sensitivity in the Chinese population: for the first time, the association between blood pressure salt sensitivity and the response of gut microbiota and metabolites to salt was explored, revealing significant differences in the responses of 22 gut microbiota species and 9 metabolites across different blood pressure salt sensitivity groups, indicating that gut microbiota and metabolomics can partially explain population-specific differences in blood pressure salt sensitivity, providing clues for precise population-based prevention. This invention also constructs a gut microbiota-metabolite regulatory network affecting blood pressure salt sensitivity: through correlation analysis, it was found that the gut-acylcarnitine axis may be a key pathway leading to population-specific differences in blood pressure salt sensitivity. This invention discovers that isovalerylcarnitine holds promise as an intervention target for preventing salt-sensitive hypertension: further focusing on isovalerylcarnitine, it was found to be significantly associated with the risk of hypertension and the progression of blood pressure status, potentially making it a potential dietary supplement or intervention target for the prevention and treatment of hypertension. This invention reveals the "black box" of high-sodium diets leading to salt-sensitive hypertension, providing new insights into the biological mechanisms of salt-sensitive hypertension and offering new intervention targets for the prevention and treatment of hypertension. Attached Figure Description

[0025] Figure 1 The mean arterial pressure (MAP) response trajectory is plotted for different blood pressure salt sensitivity groups. The differences between the MAP and the baseline mean MAP on days 2, 8, 9, and 10 of the low-salt phase and the mean MAP of the low-salt phase (the last three days) are calculated for all subjects. The average MAP change at each time point is calculated for each salt sensitivity group, and then the trajectory is plotted. MAP: Mean Arterial Pressure.

[0026] Figure 2A and Figure 2B Volcano plot for salt-related biomarkers. A linear mixture model was used to compare the differences in the relative abundance of gut microbiota and plasma levels of metabolites between the low-salt and high-pressure phases. Species and metabolites that reached Bonferroni significance were defined as salt-related species and salt-related metabolites.

[0027] Figure 3 This section displays the adjusted mean change in salt-sensitive gut microbiota across different blood pressure salt sensitivity groups. The changes in salt-associated gut microbiota from low to high salt levels were calculated, and a linear mixed model was used to analyze the association between these changes and blood pressure salt sensitivity. The adjusted mean change for each salt sensitivity group was then estimated.

[0028] Figure 4 This displays the adjusted mean changes in salt-sensitive metabolites across different blood pressure salt sensitivity groups. Changes in salt-related metabolites were calculated from low to high salt levels, and a linear mixed model was used to analyze the association between these changes and blood pressure salt sensitivity. The adjusted mean changes for each salt sensitivity group were then estimated.

[0029] Figure 5 Displaying a salt-sensitive gut microbiota-metabolite correlation network.

[0030] Figure 6 This study demonstrates the association between isovalerylcarnitine and the prevalence, incidence, and progression of hypertension. Logistic regression and Cox proportional hazards models were used to analyze the association between isovalerylcarnitine and the prevalence, incidence, and progression of hypertension, estimating the odds ratio (OR) and risk ratio (HR) for each standard deviation increase in the logarithmic concentration of isovalerylcarnitine, along with their corresponding confidence intervals (CIs). CI: confidence interval; HR: hazard ratio; OR: odds ratio.

[0031] Figure 7 The results of validation in Dahl salt-sensitive rats are shown. Repeated measures ANOVA was used to compare blood pressure differences among groups throughout the intervention period, and t-tests were used to compare blood pressure differences between the high-salt administration group and the high-salt control group on day 28. A, B, and C represent the low-salt control group, the high-salt control group, and the high-salt administration group, respectively. BP: Blood pressure; DBP: Diastolic blood pressure; HSD: High-salt diet; LSD: Low-salt diet; SBP: Systolic blood pressure.

[0032] Figure 8 This study demonstrates the effect of dietary salt on isovalerylcarnitine.

[0033] Figures 9A to 9C , Figures 10A to 10E This shows the experimental results of the Dahl salt sensitivity test to verify the role of key metabolites.

[0034] Figure 11A , Figure 11BThis shows the results of the antibiotic intervention experiment on the abundance of gut microbiota and the concentration of isovalerylcarnitine. Detailed Implementation

[0035] Before further describing specific embodiments of the present invention, it should be understood that the scope of protection of the present invention is not limited to the specific embodiments described below; it should also be understood that the terminology used in the embodiments of the present invention is for describing specific embodiments and not for limiting the scope of protection of the present invention.

[0036] When numerical ranges are given in the embodiments, it should be understood that, unless otherwise stated in the present invention, both endpoints of each numerical range and any value between the two endpoints may be selected. Unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. In addition to the specific methods, equipment, and reagents used in the embodiments, based on the knowledge of the prior art possessed by one of ordinary skill in the art and the description of this invention, any prior art methods, equipment, and materials similar to or equivalent to those described in the embodiments of this invention may be used to implement this invention.

[0037] Unless otherwise stated, the experimental methods, detection methods and preparation methods disclosed in this invention all adopt conventional techniques in this technical field.

[0038] Example 1. Screening and identification of salt-related biomarkers in gut microbiota and metabolites

[0039] I. Experimental Methods

[0040] 1. Study population and study design

[0041] 1.1 MetaSalt Research

[0042] This invention's study on the effects of dietary salt on gut microbiota and metabolism (Metabolome, Microbiome, and Dietary-Salt Intervention, MetaSalt) aims to explore the responses of gut microbiota and metabolites to a high-sodium diet and their impact on blood pressure and blood pressure salt sensitivity. In 2019, the study enrolled 528 participants from four rural areas in northern China and conducted a 23-day trial, including 3 days of baseline observation (no sodium intake control), 10 days of low-salt intervention (3 grams of salt or 51.3 mmol of sodium per day), and 10 days of high-salt intervention (18 grams of salt or 307.8 mmol of sodium per day). Ultimately, 512 participants (96.97%) completed the low-salt intervention, and 503 participants (95.27%) completed the entire trial.

[0043] During the baseline phase, a standard questionnaire was used to collect data on general demographic characteristics, medical history, medication history, dietary factors, and lifestyle of all participants. Blood pressure was measured three times on days 1-3 of baseline, and on days 2, 8, 9, and 10 of the low-salt and high-salt phases. The mean blood pressure for each phase was the average blood pressure over the last three days of that phase. Participants with a baseline systolic blood pressure (SBP) ≥140 mmHg and / or a baseline diastolic blood pressure (DBP) ≥90 mmHg were defined as hypertensive patients. Fasting blood samples were collected from participants on day 1 of baseline and day 9 of the low-salt and high-salt intervention phases for biochemical markers and plasma targeted metabolomics analysis. One stool sample was collected from each participant within three days of baseline and within the last two days of each intervention phase for metagenomic analysis. Three urine samples were collected from participants within the last three days of each phase, and 24-hour urinary sodium and potassium levels were measured and estimated.

[0044] This invention refers to the definition of blood pressure salt sensitivity in previous literature to classify salt-sensitive individuals and salt-resistant individuals. First, the difference in mean arterial pressure (MAP) before and after the intervention was calculated for 503 participants who completed the entire trial; that is, MAP during the low-salt phase minus MAP at baseline (ΔMAP). L-B ) and the decrease in MAP during the high-salt phase and the decrease in MAP during the low-salt phase (ΔMAP) H-L Next, the study subjects were divided into three groups according to a certain threshold: extreme salt sensitivity individuals (ΔMAP). L-B ≥-10mmHg or ΔMAP H-L ≥10 mmHg; Moderately salt-sensitive individuals: ΔMAP L-B -5 to -10 mmHg or ΔMAP H-L Salt resistance: 5~10 mmHg; Salt resistant individuals: the remaining subjects of the study.

[0045] 1.2 Forward-looking cohort

[0046] This invention explores the association between key metabolites and the prevalence, incidence, and progression of hypertension in an independent prospective cohort population. The study population consisted of participants from the International Collaborative Study of Cardiovascular Disease in Asia (InterASIA) cohort and the China Multi-Center Collaborative Study of Cardiovascular Epidemiology 1998 (China MUCA 1998) cohort. The China MUCA 1998 cohort, conducted in 1998, included 11,480 participants; the InterASIA cohort, conducted from 2000 to 2001, included 15,540 participants. Both cohorts underwent their first follow-up in 2007–2008 and their second follow-up in 2012–2015. Blood pressure and antihypertensive medication use were collected at baseline and at each follow-up stage. Hypertensive patients were defined as those with SBP ≥ 140 mmHg and / or DBP ≥ 90 mmHg and / or those taking antihypertensive medication in the past two weeks. In individuals not taking antihypertensive medication, ideal blood pressure was defined as SBP <120 mmHg and DBP <80 mmHg; prehypertension was defined as SBP between 120 and 139 mmHg and / or DBP between 80 and 89 mmHg; and normal blood pressure was defined as both ideal and prehypertension. Progression in blood pressure status was defined as an increase of at least one grade in blood pressure status during the follow-up period compared to the previous phase (e.g., from ideal blood pressure to prehypertension, from stage 1 hypertension to stage 2 hypertension, etc.).

[0047] This invention uses a survey conducted in 2007-2008 as a baseline, randomly selecting 3907 participants with blood samples for plasma targeted metabolomics analysis to explore the association between metabolites and the prevalence of hypertension, as well as the onset and progression of hypertension during the follow-up period from 2012 to 2015. First, the association between metabolites and the prevalence of hypertension was analyzed in all participants. Then, participants with missing blood pressure information during the 2012-2015 follow-up period (n=1181) were removed, leaving 2726 participants for analysis of the association between metabolites and the progression of hypertension. Finally, participants with hypertension during the 2007-2008 survey period (n=1404) were removed, leaving 1322 participants for analysis of the association between metabolites and prehypertension or the onset of hypertension.

[0048] 1.3 Dahl salt-sensitive rat model

[0049] An intervention study was conducted using 7-week-old Dahl salt-sensitive male rats to verify the role of key metabolites. Rats were randomly assigned to three groups: Group A maintained a low-salt diet (LSD, n=7); Groups B and C received 8% sodium chloride-induced hypertension, with Group B serving as the high-salt control group (HSD, n=11) and Group C as the high-salt treatment group (HSD + isovalerylcarnitine, n=11). Blood pressure was monitored using wireless telemetry (HD-X10, Data Sciences International). Catheters were implanted into the femoral arteries of the rats, and each rat was housed individually post-operatively for at least 3 days before blood pressure collection. SBP and DBP were continuously recorded from 22:00 to 1:00 on the day of monitoring using Ponemah v6.50 software, and analyzed using mean blood pressure. Before the intervention, all rats were given a low-salt diet containing 0.45% sodium chloride, and baseline blood pressure monitoring began 3 days after surgery. After baseline blood pressure measurement, the diet was changed according to group assignments, and drug intervention was administered. For group C, a microosmotic pump (Alzet Model 2004) containing isovalerylcarnitine (MedChemExpress, Cat#139144-12-0, dose 200ug / kg / d) was implanted subcutaneously in rats. For groups A and B, Alzet osmotic pumps containing physiological saline were implanted as controls. All rats were housed in a specific pathogen-free environment with free access to food and water during a 12-hour light / dark cycle. All animal experiments were approved by the Laboratory Animal Management and Use Committee of Fuwai Hospital, Chinese Academy of Medical Sciences.

[0050] 2. Metagenomic Detection

[0051] This invention utilizes shotgun metagenomic sequencing technology to detect gut microbiota in fecal samples from three phases of the MetaSalt study population. First, DNA was extracted from fecal samples using a Tiangen Magnetic Bead Kit (Tiangen Biotech Co., Ltd., Beijing). Then, the purity and integrity of the DNA were analyzed using 1% agarose gel electrophoresis. Finally, the DNA concentration was precisely quantified using a Qubit® double-stranded DNA fluorescence quantitative detection kit (Life Technologies, CA, USA). One μg of genomic DNA was taken from each sample and analyzed using NEBNext® Ultra... TMDNA library preparation kit (NEB, USA) was used to construct sequence libraries. After library construction, the effective concentration of the library was accurately quantified using real-time quantitative PCR, and then the indexed samples were clustered using the cBot clustering generation system. After clustering, sequencing was performed on the Illumina HiSeq platform to generate paired end reads. The raw data obtained from the Illumina HiSeq platform was quality controlled to generate valid data for subsequent analysis. The specific steps included: (1) removing reads containing low-quality bases; (2) removing reads with N-terminal bases reaching 10 bp; (3) removing reads that overlapped with adapter sequences by more than 15 bp. Next, Bowtie2 software (version 2.2.4) was used for genome alignment to exclude host DNA. Metagenome assembly was performed using SOAPdenova software (version 2.04). Open reading frames were predicted using MetaGeneMark software (version 2.10). Redundancy was removed and a unique initial gene catalog was obtained using CD-HIT software (version 4.5.8). Bowtie2 was used to map the valid data of each sample to an initial gene catalog, obtaining the absolute abundance of the mapped genes (unigenes) in each sample. Microbial sequences were extracted from the MicroNR database (January 2, 2018) and compared with the sample microbial unigenes using DIAMOND software (version 0.9.9). The alignment results were applied to MEGAN software for systematic classification. Finally, a table of gene quantity and absolute abundance information for each sample at each taxonomic level (kingdom, phylum, class, order, family, genus, species) was obtained. A relative abundance table was calculated based on the absolute abundance.

[0052] Ultimately, a total of 14,533 gut microbiota species were detected in fecal samples from the MetaSalt study population. This invention retains 531 species with a minimum relative abundance of 0.01% in at least 10% of the samples for subsequent analysis. For observations with a relative abundance of 0, a minimum value (1 × 10⁻⁶) was used. -11 The data was then filled in. Subsequently, a rank-based inverse normal transformation was performed on the relative abundance of all bacterial species.

[0053] 3. Plasma targeted metabolomics detection

[0054] Plasma samples from three phases of the MetaSalt population and baseline plasma samples from a prospective cohort were subjected to targeted metabolomics analysis. The assays used were the Q300 kit and the trimethylamine N-oxide (TMAO) kit, both provided by MetaBio (Shanghai). The Q300 kit can detect approximately 300 metabolites, encompassing 12 major metabolite classes. The TMAO kit can detect seven TMAO-related metabolites: TMAO, trimethylamine, choline, L-carnitine, betaine, creatinine, and imidazole propionic acid. The two kits together detect 13 major metabolite classes. Plasma samples were thawed in an ice bath and prepared by adding internal standards and stock solutions. Metabolite determination was performed using ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS / MS) (ACQUITY UPLCXevo TQ-S, Waters Corp., Milford, MA, 570 USA). For the Q300 kit, an ACQUITY UPLC BEH C18 (1.7 μM, 2.1 × 100 mm) column was used; for the TMAO kit, an ACQUITY UPLC HILIC (1.7 μM, 2.1 × 100 mm) column was used. Internal standards were used during the assay to monitor analytical biases in sample processing and analysis. Mixed biological samples were used as quality control samples, inserted into the injection sequence at intervals of 10 samples to objectively evaluate intra-batch repeatability and correct for inter-batch errors. Raw data generated by UPLC-MS / MS were imported into the analytical system for peak integration, calibration, and quantification. A linear relationship between the analytical signal and concentration was constructed using standards of different concentrations. The concentration of the analyte metabolite was calculated by substituting its analytical signal into the formula.

[0055] The MetaSalt cohort and prospective cohort populations detected 294 and 288 metabolites, respectively. After removing metabolites with a detection rate below 80%, 222 and 214 metabolites remained in the two populations, respectively. The K-nearest neighbor algorithm was used to select the five observations with the closest Euclidean distance to the missing observations, and their mean was used to fill in the missing values ​​of the metabolites. A rank-based inverse normal transformation was applied to the metabolites in the MetaSalt cohort population, while a logarithmic transformation and standardization were performed on the metabolites in the prospective cohort population.

[0056] 4. Statistical Analysis Methods

[0057] A linear mixed model was used to compare differences in gut microbiota and metabolites between the low-salt and high-salt phases in the MetaSalt population to identify salt-related biomarkers. The model adjusted for household and individual random effects. Because a self-controlled pre- and post-intervention design was used, comparisons were made across different intervention phases for individuals, eliminating the need for additional adjustment of other covariates. Gut microbiota and metabolites with Bonferroni significance (P < 9.42 × 10⁻⁶) were defined as salt-related microbiota. -5 =0.05 / 531) and salt-related metabolites (P<2.25×10 -4 =0.05 / 222).

[0058] The association between gut microbiota or metabolite responses and blood pressure salt sensitivity was analyzed. First, the changes in microbiota and metabolites from the low-salt stage to the high-salt stage were calculated, i.e., the marker levels in the high-salt stage decreased the marker levels in the low-salt stage. Next, blood pressure salt sensitivity was used as an ordinal variable, and a linear mixed model was used to analyze the association between blood pressure salt sensitivity and marker changes. The model was adjusted for random effects of age, sex, body mass index (BMI), study location, total cholesterol, hypertension, smoking, and family. Gut microbiota and metabolites were defined as salt-sensitive microbiota or salt-sensitive metabolites if they met the following conditions: (1) the association between marker changes and blood pressure salt sensitivity was P < 0.05; (2) the association between marker changes and blood pressure salt sensitivity was in the same direction as the effect of high salt on the marker. Furthermore, blood pressure salt sensitivity was used as a categorical variable for trend testing, and the least squares estimation method was used to obtain the adjusted average changes in salt sensitivity markers in salt-resistant, moderately salt-sensitive, and extremely salt-sensitive individuals. Pearson partial correlation analysis was performed on salt-sensitive bacterial species and metabolites, adjusting for age, sex, BMI, study location, total cholesterol, hypertension, and smoking. Associations with P < 0.05 were retained, and a correlation network was constructed using Cytoscape (version 3.8.2) to identify the gut microbiota-metabolite regulatory network associated with blood pressure salt sensitivity.

[0059] The association between salt-sensitive metabolites and hypertension and the progression of hypertension was analyzed in a prospective cohort population. Logistic regression was used to analyze the association between salt-sensitive metabolites and the prevalence of hypertension, while Cox proportional hazards models were used to analyze the association between salt-sensitive metabolites and the progression of hypertension and the onset of hypertension. The odds ratio (OR) and hazard ratio (HR) for each standard deviation (SD) increase in the logarithmic value of the metabolite concentration, along with their corresponding 95% confidence intervals (CI), were estimated. All models were adjusted for age, sex, BMI, work-related physical activity, urban / rural location, north / south orientation, smoking, alcohol consumption, education level, dietary score, dyslipidemia, diabetes, and L-carnitine levels.

[0060] Repeated measures ANOVA was used to compare blood pressure differences among Dahl salt-sensitive rats throughout the intervention trial, and t-tests were used to compare blood pressure differences between the high-salt control group and the high-salt administration group on day 28.

[0061] II. Experimental Results

[0062] 1. General characteristics of MetaSalt users

[0063] Among the 503 participants who completed the entire trial, the mean age was 48.11 ± 9.26 years, and the mean BMI was 26.30 ± 3.52 kg / m². 2 Of the participants, 317 (63.02%) were women. At baseline, the mean SBP and DBP of these participants were 129.32 ± 13.64 mmHg and 80.23 ± 9.75 mmHg, respectively, and 139 (27.63%) had hypertension. The mean 24-hour urinary sodium and potassium levels at baseline were 204.70 ± 50.24 mmol and 37.01 ± 9.02 mmol, respectively. Based on the MAP response to low- or high-salt interventions, the 503 participants were divided into three groups: 247 salt-resistant (49.10%), 168 moderately salt-sensitive (33.40%), and 88 extremely salt-sensitive (17.50%). The mean MAP response of the three groups showed three different trajectories throughout the study period. Figure 1 ).

[0064] 2. Salt-related markers

[0065] This invention found that, compared with the low-salt phase, the relative abundance of 85 (16.00%) gut microbiota species changed significantly after high-salt intervention (P<9.42×10⁻⁶). -5These bacterial species were defined as salt-associated. Among them, the relative abundance of 79 species significantly decreased after high-salt intervention, while only 6 showed a significant increase. For example, compared to the low-salt stage, the standardized relative abundance of *Anaerotruncus colihominis* decreased by 0.13 after high-salt intervention (95% CI: 0.07, 0.20, P = 6.48 × 10⁻⁶). -5 () Figure 2A (See Table 1). These strains mainly come from five major phyla, of which 60 belong to Firmicutes (Table 1).

[0066] Table 1. Salt-associated gut microbiota

[0067]

[0068]

[0069] A linear mixed model was used to compare the differences in relative abundance of gut microbiota during the low-salt and high-salt phases, retaining P < 9.42 × 10⁻⁶. -5 Species with a value of (0.05 / 531) are defined as salt-associated species. CI: confidence interval.

[0070] Compared with the low-salt phase, the plasma levels of 71 metabolites (31.98%) changed significantly after the high-salt intervention (P<2.25×10⁻⁶). -4 These metabolites were defined as salt-related metabolites. Of these, 66 metabolites significantly decreased after high-salt intervention, while only 5 metabolites significantly increased (serine, methylcysteine, arginine, glutamine, and maltotriose). For example, compared to the low-salt phase, the standardized concentration of valerate carnitine decreased by 0.20 in the high-salt phase (95% CI: 0.12, 0.28, P = 9.10 × 10⁻⁶). -7 The standardized concentration of methylcysteine ​​increased by 0.82 (95% CI: 0.74, 0.90, P = 3.71 × 10⁻⁶). -68 () Figure 2B (See Table 2). These salt-related metabolites come from 13 major categories, including 17 amino acids, 15 fatty acids, 8 carbohydrates, 7 organic acids, 7 carnitines, and others such as benzene ring compounds, indoles, and bile acids (Table 2).

[0071] Table 2. Salt-related metabolites

[0072]

[0073]

[0074] A linear mixed model was used to compare the differences in plasma metabolite levels between the low-salt and high-salt phases, retaining P < 2.25 × 10⁻⁶. -4 Metabolites with a value of (0.05 / 222) are defined as salt-related metabolites. CI: confidence interval.

[0075] 3. Salt-sensitive markers

[0076] This invention further analyzes the correlation between changes in metabolites from low-salt to high-salt phases and blood pressure salt sensitivity. From 85 salt-associated bacterial species, 22 salt-sensitive species were identified. The changes in these species were all significantly negatively correlated with blood pressure salt sensitivity (P<0.05), of which 21 belonged to Firmicutes (…). Figure 3 (and Table 3). For example, the mean changes in Anaerotruncus colihominis in the salt-resistant, moderately salt-sensitive, and extremely salt-sensitive groups were -0.03 (95% CI: -0.15, 0.09), -0.15 (95% CI: -0.27, -0.03), and -0.23 (95% CI: -0.40, 0.06), respectively (P < 0.09). 趋势 =0.0322).

[0077] Table 3. Salt-sensitive gut microbiota

[0078]

[0079] A linear mixed model was used to analyze the association between changes in gut microbiota and blood pressure salt sensitivity. Bacteria with P < 0.05 and an association direction consistent with the direction of the effect of high salt were defined as salt-sensitive bacteria. CI: confidence interval.

[0080] Of the 71 salt-related metabolites, this invention identified 9 metabolites whose changes were significantly correlated with blood pressure salt sensitivity (P<0.05), including methylcysteine, 2-hydroxybutyric acid, carnitine, phenylpyruvic acid, isovalerylcarnitine, 3-hydroxyisovaleric acid, valerylcarnitine, histidine, and α-hydroxyisobutyric acid. Figure 4 (See Table 4). Among these, only changes in methylcysteine ​​were positively correlated with blood pressure and salt sensitivity. For example, the mean differences in isovalerylcarnitine between the salt-resistant group, the moderately salt-sensitive group, and the extremely salt-sensitive group were -0.16 (95% CI: -0.28, -0.04), -0.19 (95% CI: -0.31, -0.06), and -0.46 (95% CI: -0.63, -0.29), respectively (P < 0.04). 趋势 =0.0105).

[0081] Table 4. Salt-sensitive metabolites

[0082]

[0083] A linear mixed model was used to analyze the association between changes in metabolites and blood pressure salt sensitivity. Metabolites with P < 0.05 and an association direction consistent with the direction of the effect of high salt on blood pressure were defined as salt-sensitive metabolites. CI: confidence interval.

[0084] Correlation analysis was performed on 22 salt-sensitive bacterial species and 9 salt-sensitive metabolites, revealing 52 pairs of relationships with P < 0.05, including 5 metabolites and 20 bacterial species (Table 5). By constructing a correlation network, this invention identified a gut-acylcarnitine axis (…). Figure 5 Among these, valerylcarnitine, isovalerylcarnitine, and 3-hydroxyisovaleric acid (acylcarnitine-related precursor metabolites) play a central role, with changes in these three metabolites significantly correlated with changes in at least 10 bacterial strains. Many of these strains are known short-chain fatty acid producers, such as *Pseudoflavonifractor capillosus*, *Intestinimonasbutyriciproducens*, and *Anaerotruncus colihominis*.

[0085] Table 5. Correlation between salt-sensitive bacterial species and salt-sensitive metabolites

[0086]

[0087] Pearson partial correlation analysis was used to calculate the correlation between salt-sensitive bacterial species and salt-sensitive metabolites.

[0088] 4. The association between acylcarnitine and the onset and progression of hypertension.

[0089] This invention further investigates the association between isovalerylcarnitine and the prevalence, onset, and progression of hypertension in a prospective cohort population (n=3907). The baseline (2007–2008) mean age of this population was 57.01 ± 8.80 years, including 2036 women (52.11%), with mean SBP and DBP of 136.46 ± 21.07 mmHg and 82.91 ± 11.84 mmHg, respectively.

[0090] This invention observed no significant association between isovalerylcarnitine and the risk of hypertension. After a median follow-up of 5.5 years, blood pressure was measured in 2726 participants, of whom 733 experienced progression of hypertension. Isovalerylcarnitine (HR=0.86, 95% CI: 0.79, 0.94) was significantly negatively correlated with progression of hypertension. Among 1322 participants without baseline hypertension, 286 progressed from ideal blood pressure to prehypertension or hypertension, 269 progressed from prehypertension to hypertension, and 345 progressed from normotensive blood pressure to hypertension. For every SD increase in the logarithmic concentration of isovalerylcarnitine, the risk of progression from ideal blood pressure to prehypertension or hypertension decreased by 19% (HR=0.81, 95% CI: 0.70, 0.93), and the risk of progression from normotensive blood pressure to hypertension decreased by 17% (HR=0.83, 95% CI: 0.73, 0.95). Figure 6 ).

[0091] 5. Results of intervention in Dahl salt-sensitive rats

[0092] In rats subjected to high-salt intervention, SBP and DBP were significantly reduced in the high-salt treatment group compared to the high-salt control group. On day 28 of monitoring, administration of isovalerylcarnitine significantly reduced SBP by 14.20 mmHg (P = 0.0009) and DBP by 8.81 mmHg (P = 0.0059). Figure 7 ).

[0093] Based on the above animal experiments, this invention hypothesizes that administering 13.2 mg of isovalerylcarnitine daily (4.4 mg three times a day) to individuals with a high-salt diet and blood pressure greater than 120 / 80 mmHg could achieve a similar significant reduction in SBP and DBP.

[0094] Example 2. Effect of dietary salt on isovalerylcarnitine

[0095] This embodiment verifies the effect of dietary salt on isovalerylcarnitine.

[0096] An intervention trial was conducted in rats. Four-week-old male Wistar rats were randomly assigned to a high-salt diet group (containing 8% sodium chloride, n = 15) and a normal-salt control group (containing 0.45% sodium chloride, n = 15). All rats were fed the control diet for one week prior to the intervention. The intervention then lasted four weeks. Blood pressure was monitored in each rat using the tail-clamp method during the daytime at the end of each week. Blood samples were collected from all rats at the end of the fourth week, and plasma isovalerylcarnitine levels were measured.

[0097] The experimental results showed that, compared with the low-salt control group, the plasma isovalerylcarnitine concentration in the high-salt intervention group was significantly lower (0.111 ± 0.028 μmol / L vs. 0.079 ± 0.023 μmol / L, P = 0.0017). Figure 8 ).

[0098] Example 3. Dahl salt sensitivity test to verify the role of key metabolites

[0099] In this study, 7-week-old Dahl salt-sensitive male rats were used to conduct an intervention experiment to verify the role of key metabolites. Rats were randomly divided into three groups: Group A maintained a low-salt diet (low-salt control group, n=7); Groups B and C received 8% sodium chloride-induced hypertension, with Group B serving as the high-salt control group (n=11) and Group C as the high-salt + isovalerylcarnitine intervention group (n=11). Blood pressure was monitored using wireless telemetry (HD-X10, Data Sciences International). Catheters were implanted into the femoral artery of the rats. Each rat was housed individually post-surgery and allowed at least 3 days of recovery before blood pressure collection. SBP and DBP were continuously recorded from 22:00 to 1:00 on the day of monitoring using Ponemah v6.50 software, and analyzed using mean blood pressure. Before the intervention, all rats were given a low-salt diet containing 0.45% sodium chloride, and baseline blood pressure monitoring began 3 days after surgery. After baseline blood pressure measurement, the diet was changed according to grouping, and drug intervention was administered. For group C, a microosmotic pump (Alzet Model 2004) containing isovalerylcarnitine (MedChemExpress, Cat#139144-12-0, dose 200ug / kg / d) was implanted subcutaneously in rats. For groups A and B, Alzet osmotic pumps containing physiological saline were implanted as controls. All rats underwent continuous intervention for 28 days, and blood pressure was monitored and recorded on days 3, 7, 14, 21, and 28. After the intervention, samples and tissues from the rats, including blood, aorta, mesenteric artery, and kidneys, were collected. Figure 9A ).

[0100] Vasodilatory function assessment: The rat mesenteric artery was rapidly dissected, cut into 2 mm segments, fixed between a microscope and a pressure sensor, and cultured in an organ bath containing Krebs buffer while tension was recorded. Maximum reference tension was determined using high-potassium Krebs buffer. Vasoconstriction to 80% of maximum vasoconstriction was induced with norepinephrine, followed by assessment of endothelium-dependent or non-endothelium-dependent vasodilation using incremental concentrations of acetylcholine or sodium nitroprusside, respectively.

[0101] Histological analysis: After euthanizing the animals, the descending aorta and kidneys were harvested, fixed in 4% paraformaldehyde, embedded in paraffin, and cut into 4 μm sections. Immunofluorescence staining was used to assess the expression level of endothelial-dependent nitric oxide synthase (eNOS) in the kidneys of different groups of rats. The degree of fibrosis in the aorta and kidneys was assessed using H&E staining (morphological observation), Masson's trichrome staining (quantification of thoracic aortic media collagen), and Sirius red staining (detection of renal cortical collagen).

[0102] All rats were housed in a specific pathogen-free environment with free access to food and water during a 12-hour light / dark cycle. All animal experiments were approved by the Laboratory Animal Management and Use Committee of Fuwai Hospital, Chinese Academy of Medical Sciences.

[0103] The experimental results showed that blood pressure was significantly higher in the high-salt control group and the high-salt + isovalerylcarnitine intervention group compared with the low-salt control group. In the two groups of rats receiving high-salt intervention, SBP and DBP were significantly lower in the high-salt + isovalerylcarnitine intervention group compared with the high-salt control group. On day 28 of monitoring, administration of isovalerylcarnitine significantly reduced SBP by 14.20 mmHg (P=0.0009) and DBP by 8.81 mmHg (P = 0.0059). Figure 9B ).

[0104] The results of vasodilatory function assessment showed that, compared with the high-salt control group, the mesenteric artery endothelium-dependent vasodilation function was improved in the high-salt + isovalerylcarnitine intervention group (P = 0.0132). Figure 9C Immunofluorescence staining of the kidneys showed that, compared with the low-salt control group, the eNOS expression level in the high-salt control group was decreased (P = 0.0014), while the eNOS expression level in the high-salt + isovalerylcarnitine intervention group recovered to the level of the low-salt control group (P = 0.9039). Figure 10A , Figure 10B The above results indicate that isovalerylcarnitine can improve endothelial diastolic dysfunction caused by a high-salt diet.

[0105] Masson staining showed that, compared with the low-salt control group, the high-salt control group had a significantly increased intramural collagen deposition in the aorta (P = 6.29 × 10⁻⁶). -5 In the high-salt + isovalerylcarnitine group, the collagen fraction was slightly reduced. Figure 10C , Figure 10D Sirius red staining showed that, compared with the high-salt control group, the high-salt + isovalerylcarnitine group had significantly reduced renal interstitial fibrosis (P = 0.0192). Figure 10C , Figure 10E These findings suggest that isovalerylcarnitine has a protective effect against salt-induced tissue remodeling.

[0106] Example 4. Antibiotic Intervention Experiment

[0107] To verify whether isovalerylcarnitine can be produced by gut microbiota, this study conducted a 28-day gut microbiota inhibition and fecal microbiota transplantation (FMT) experiment in 21 six-week-old Sprague-Dawley rats. These rats were randomly assigned to three groups: a control group (no intervention, n = 7), an antibiotic intervention group (n = 7), and a FMT group after antibiotic intervention (n = 7). The antibiotic mixture included ampicillin (1 g / L), vancomycin (0.5 g / L), metronidazole (1 g / L), and gentamicin (1 g / L). Rats in both the antibiotic intervention and FMT groups received antibiotics via drinking water to reduce gut bacterial load. During FMT, fecal samples were collected from the control group rats, suspended in phosphate-buffered saline (PBS, 1 g feces / 5 mL PBS), and filtered through a 70-micron filter. Rats in the FMT group after antibiotic intervention received 1 mL of the filtrate via gavage for 7 consecutive days following ACT treatment. One rat in the fecal microbiota transplantation group died during the gavage procedure after antibiotic intervention. Blood and fecal samples were collected from all rats at the end of the experiment, and metabolites and gut microbiota were detected by UPLC-MS / MS and 16S amplicon sequencing, respectively.

[0108] The experimental results showed that, compared with the control group, the gut microbiota richness of the antibiotic intervention group was significantly decreased (P = 4.67 × 10⁻⁶). -9 Compared with the antibiotic intervention group, the gut microbiota of the fecal microbiota transplantation group recovered after antibiotic intervention (P = 2.53 × 10⁻⁶). -5 () Figure 11A Similarly, compared with the control group (0.090 ± 0.023 μmol / L), the plasma isovalerylcarnitine concentration in the antibiotic intervention group (0.047 ± 0.024 μmol / L) was significantly decreased (P = 0.0043), while the isovalerylcarnitine concentration in the fecal microbiota transplantation group (0.084 ± 0.016 μmol / L) recovered somewhat after antibiotic intervention (P = 0.5648). Figure 11B This result indicates that isovalerylcarnitine can be considered an intestinal metabolite.

[0109] The above embodiments are only used to illustrate the present invention and are not intended to limit the present invention. Those skilled in the art can make various changes and modifications without departing from the essence and scope of the present invention. Therefore, all equivalent technical solutions also fall within the protection scope of the present invention.

Claims

1. Use of isovalerylcarnitine in a sample from an individual as a target point in screening and / or preparing an agent and / or a drug for preventing and / or treating salt-sensitive hypertension.

2. Use of isovalerylcarnitine or an agent for detecting isovalerylcarnitine in a sample from an individual in preparing a product for evaluating the risk of developing hypertension and / or the progression of blood pressure status of an individual.

3. Use according to claim 1 or 2, wherein, The sample is blood or plasma.

4. The use according to claim 1 or 2, wherein, The individual is of East Asian ethnicity, preferably Chinese.

5. The use according to claim 1 or 2, wherein: the level of isovalerylcarnitine in a sample from an individual is significantly negatively correlated with the progression of blood pressure status; and / or the level of isovalerylcarnitine in a sample from an individual is significantly negatively correlated with the risk of developing hypertension; Preferably, for each SD increase in the log concentration of isovalerylcarnitine in a sample from an individual, the risk of an individual progressing from ideal blood pressure to prehypertension or hypertension is reduced by 19% (HR = 0.81, 95% CI: 0.70, 0.93) and the risk of progressing from normal blood pressure to hypertension is reduced by 17% (HR = 0.83, 95% CI: 0.73, 0.95).

6. The use according to any one of claims 1 to 5, wherein, The isovalerylcarnitine is used independently or in combination with other salt-sensitive markers for the use; Preferably, the other salt-sensitive markers include one or more of salt-sensitive gut bacteria, salt-sensitive metabolites. More preferably, the salt-sensitive gut species include one or more of Alistipes ihumii, Anaerotruncus colihominis, Clostridiales bacterium 42_27, Clostridiales bacterium 52_15, Clostridium sp. CAG:389, Clostridium sp. CAG:413, Clostridium sp. CAG:780, Dialister sp. CAG:357, Eubacterium sp. CAG:180, Firmicutes bacterium CAG:124, Firmicutes bacterium CAG:129_59_24, Firmicutes bacterium CAG:137, Firmicutes bacterium CAG:170, Firmicutes bacterium CAG:176, Firmicutes bacterium CAG:24053_14, Firmicutes bacterium CAG:555, Firmicutes bacterium CAG:83, Intestinimonas butyriciproducens, Oscillibacter sp. CAG:241, Oscillibacter sp. ER4, Pseudoflavonifractor capillosus, Ruminococcus sp. CAG:177; More preferably, the salt-sensitive metabolite includes one or more of methylcysteine, histidine, phenylpyruvic acid, L-carnitine, valproline, 2-hydroxybutyric acid, a-hydroxyisobutyric acid, 3-hydroxyisovaleric acid; More preferably, the other salt-sensitive marker includes one or more of L-carnitine, valproline.

7. Use of valproline in the preparation of a product for improving, preventing and / or treating salt-sensitive hypertension.

8. Use according to claim 7, wherein, The dosage of valproline is 0.15-0.22 mg / kg body weight / day.

9. Use according to claim 7, wherein, The valproline is used as an active ingredient for reducing systolic pressure and / or diastolic pressure of a patient with salt-sensitive hypertension.

10. The use according to any one of claims 7 to 9, wherein, The product for improving, preventing and / or treating salt-sensitive hypertension is a dietary supplement or a drug. The product for improving, preventing and / or treating salt-sensitive hypertension is a dietary supplement or a drug.

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