Characteristic Gut Microbial Species Associated with Salt Sensitivity in Hypertensive and Normotensive Tibetan Individuals

doi:10.21203/rs.3.rs-4885429/v1

Backgroud: The study examined the diversity of gut microbiome in Tibetans residing in Gannan Prefecture, China, across varying levels of blood pressure in order to investigate the potential relationship between blood pressure, salt sensitivity, and gut microorganisms for the development of strategies aimed at preventing hypertension.

Methods: Utilizing data obtained from the National Natural Science Foundation of China project (No. 81960614), a cohort of 152 individuals was selected from a population of 1459 Tibetans following a seven-year period of surveillance in Lintan and Zhoni counties. These participants underwent comprehensive evaluations encompassing questionnaires, physical examinations, blood pressure measurements, and assessments of salt sensitivity. Subsequently, the individuals were categorized into distinct groups based on their salt sensitivity and hypertensive status, including Salt-Sensitive Hypertensive (SSHS), Non-Salt-Sensitive Hypertensive (NSSHS), Salt-Sensitive Normotensive (SSNHS), and Non-Salt-Sensitive Normotensive (NSSNHS).

Results: Significant differences in gut microbial β-diversity were observed between salt-sensitive and non-salt-sensitive groups. Among hypertensives, Fusobacterium spp, Prevotella spp_NK3B31_group, and Megalococcus spp. were more abundant in SSHS. In normotensives, Mycobacterium spp. and others were more prevalent in SSNHS. LEfSe analyses revealed a greater variety of characteristic species in the salt-sensitive groups. Specific taxa like CAG_352 and Acetanaerobacterium were enriched in hypertensive salt-sensitive subjects, whereas Brautobacteria spp., Klebsiella spp., Pseudomonas spp., and Moraxaceae were enriched in the non-salt-sensitive hypertensive group. In normotensives, Mycobacterium, Actinobacteria, and Bifidobacterium spp. were enriched in SSNHS, and Clostridium spp._UCG_014 in NSSNHS. Analysis of KEGG and COG pathways revealed distinct functional differences between hypertensive and normotensive groups.

Conclusion: Gut bacteria composition may affect salt sensitivity, with the salt-sensitive group showing more characteristic species than the non-salt-sensitive group. CAG_352 and Acetanaerobacterium could be potential biomarkers for salt sensitivity in those with hypertension, while the presence of Anabaenaerobacterium phylum may indicate salt sensitivity in those with normal blood pressure.

Health sciences/Cardiology

Health sciences/Medical research

Salt sensitivity

Blood pressure

Gut Microbiome

Tibetan

Hypertension

The escalating prevalence and mortality rates of cardiovascular diseases (CVDs) in China can be attributed to the country's socio-economic advancements and evolving lifestyle patterns. Recent data indicates that nearly 290 million people in China suffer from CVDs in 2018, with a mortality rate of more than 260 per 100,000 populations, and still rising.¹ Hypertension, a prominent risk factor for cardiovascular events, is linked to approximately 50% of strokes and coronary heart disease cases.² The prevalence of hypertension in the Chinese population is also high (30.54%) and significantly increased after applying the 2017 American College of Cardiology/American Heart Association Updated Hypertension Guidelines³, with notably higher rates observed in less developed regions such as Gannan in western Gansu Province⁴. Consequently, the prioritization of hypertension prevention and management is imperative.

Hypertension is a multifaceted condition influenced by both genetic and environmental components⁵. Among these factors, excessive consumption of dietary salt stands out as a significant contributor to the development of hypertension, as evidenced by various studies linking high-salt diets to elevated blood pressure^6–9. The concept of salt-sensitive blood pressure (SSBP), denoting varying responses to salt intake or restriction among individuals, is recognized as an autonomous predictor of mortality due to cardiovascular disease¹⁰.The variability in the detection rate of blood pressure salt sensitivity across diverse populations is influenced by factors such as gender, age, and ethnicity^11–13. Two primary mechanisms associated with blood pressure salt sensitivity are the renal dysfunction theory and the vascular dysfunction theory^14–16. This phenomenon is closely associated with environmental factors including lifestyle choices, hydration status, obesity, and metabolic syndrome¹⁷.

Gut microorganisms (GM) refer to the genetic composition of microorganisms residing in the human gastrointestinal tract, playing a crucial role in various metabolic processes essential for maintaining physiological homeostasis^{18, 19}. Studies have demonstrated a correlation between dysbiosis of gut flora, levels of intestinal metabolites, and the incidence of hypertension and associated cardiovascular disorders^20–23. Furthermore, these microorganisms are implicated in the pathogenesis of hypertension via immunoinflammatory, neuroinflammatory, and metabolite-mediated mechanisms^{24, 25}. Recently, researchers have identified substantial correlations between gut microbiota, blood pressure, and salt consumption, underscoring their pivotal role in the pathogenesis of salt-sensitive blood pressure.

The Gannan Tibetan Autonomous Prefecture, situated in the southwestern region of Gansu Province, exhibits a distinctive high-salt and high-fat dietary pattern that potentially contributes to the heightened prevalence of hypertension within the local population²⁶. Prior research has indicated a notably elevated occurrence of hypertension and salt sensitivity in blood pressure among individuals of Tibetan descent in Gannan, surpassing rates observed in other geographic areas²⁷. Consequently, a comprehensive examination of the correlation between gut microbiota and salt sensitivity in various blood pressure conditions within the Gannan Tibetan population is crucial for the formulation of specific preventive and management measures.

This study seeks to investigate the potential correlation between gut microorganisms and salt sensitivity of blood pressure in the Gannan Tibetan population, utilizing demographic data, blood pressure and salt sensitivity assessments, and analysis of gut microbial diversity within the population cohort established by the National Nature Project. The findings of this research aim to contribute to the development of evidence-based prevention and control strategies in the future.

Study subject

This research is part of the "7-year follow-up study of blood pressure salt sensitivity in the Gannan Tibetan population and its correlation with intestinal microorganisms" (NO.81960614), funded by the National Natural Science Foundation of China (NSFC). It builds on the earlier project "Role of kinin releasing enzyme-kinin system (KKS) genes in blood pressure salt sensitivity in the Gannan Tibetan population" (NO.81260444), also supported by NSFC, utilizing an established cohort from the same population. Initially, 1,459 individuals from seven villages in Lintan and Zhoni counties, Gannan Tibetan Autonomous Region, were selected using a multistage sampling method. Participants were categorized into cases with diagnosed essential hypertension and controls with normal blood pressure²⁷. After 7 years, 408 individuals were excluded due to non-participation reasons like coronary heart disease, stroke, relocation, or loss of contact, leaving 1,032 participants. Data collection was conducted on-site by trained investigators who obtained informed consent. Based on questionnaire responses and blood pressure salt sensitivity tests, participants were divided into four groups: 408 with salt-sensitive hypertension, 204 with non-salt-sensitive hypertension, 178 with salt-sensitive normal blood pressure, and 242 with non-salt-sensitive normal blood pressure. The final analysis included 152 participants after screening with 16S criteria. The study was approved by the Ethics Committee of the Gansu University of Chinese of Chinese Medicine (Lanzhou, China) (2019-05) and all patients in the study provided informed consent prior to the commencement of the investigation (Appendix S1). Simultaneously, all methodologies employed in our study were conducted in strict adherence to the MINSEQE standard regulations.

Inclusive criteria of baseline

1) Age ≥ 18 years;

2) Individuals with a previous diagnosis of secondary hypertension, diabetes mellitus, stroke, severe coronary artery disease, clinical cardiovascular disease, myocardial infarction, abnormal thyroid function, renal disease, hepatic disease, malignancy, and pregnant women were excluded;

3) Tibetan (at least three generations of paternal lineage);

3) Excluding those who are not easy to co-operate (with obvious impairment of intelligence, hearing, physical activity) and individuals who do not want to join this study;

4) Those who have not taken antibiotics or probiotics in the last 2 weeks;

Data collection

Trained health workers conducted one-on-one interviews using standardized questionnaires to gather socio-demographic data (such as age, sex, occupation, education, and monthly income), lifestyle habits (including physical activity, smoking, and alcohol consumption), and clinical information (like past medical history of coronary heart disease, hypertension, diabetes, and stroke, medication use, and family history of hypertension). Blood pressure was measured three times over three consecutive days using an automated sphygmomanometer (Microlife 3BTO-A), after a five-minute rest, sitting down. The average of these measurements was used for analysis, with re-measurement required if readings varied by more than 4 mmHg. Participants were classified as hypertensive if their average systolic blood pressure was ≥ 140 mm Hg or diastolic ≥ 90 mm Hg. Physical measurements such as weight and height were also recorded. Stool samples were collected using sterile techniques, with a 3–5 g sample taken from the first stool of the day, stored in a sterile bag, and refrigerated within 5 minutes of collection.

Blood pressure salt sensitivity test

Our study utilized a modified acute salt loading test²⁸ for assessing blood pressure salt sensitivity. Initially, participants measured their blood pressure three times to establish a baseline. They then ingested 1L of saline (155mmol NaCl) within 30 minutes, with subsequent blood pressure measurements taken 2 hours later. A diuretic contraction test followed, involving oral administration of 40mg furosemide, with blood pressure measured at 0.5, 1, and 2 hours afterward. Participants were required to abstain from antihypertensive drugs for 14 days prior to testing. Salt sensitivity was determined using the Sullivan criteria, defined by an increase in mean arterial pressure of ≥ 5 mmHg post-salt loading or a decrease of ≥ 10 mmHg after furosemide.

16s diversity detection

The MagPure SoilDNALQKit (Maga) kit was utilized for DNA extraction, with subsequent assessment of DNA sample concentration and purity conducted using NanoDrop 2000 (Thermo Fisher Scientific, USA) and agarose gel electrophoresis, respectively. PCR amplification of the variable region V3-V4 (or V4-V5) of the eligible 16SrRNA genes was performed using primers 343F (5’-TACGGRAGGCAGCAG-3’) and 798R (5’-AGGGTATCTAATCCT-3’) or 515F (5’-GTGCCAGCMGCCGCGG-3’) and 907R (5’-CCGTCAATTCMTTTRAGTTT-3’). The specificity of PCR products was confirmed via agarose gel electrophoresis, and purified PCR products were sequenced using the Illumina NovaSeq 600 sequencer (Illumina, USA) for bipartite 250 bp sequencing.

Bioinformatic analysis

Raw sequencing data were in FASTQ format. Paired-end reads were then preprocessed using cutadapt software to detect and cut off the adapter. After trimming, paired-end reads were filtering low quality sequences, denoised, merged and detect and cut off the chimera reads using DADA2²⁹ with the defalt parameters of QIIME2³⁰(2020.11). At last, the software output the representative reads and the ASV abundance table. The representative read of each ASV was selected using QIIME2 package. All representative reads were annotated and blasted against Silva database Version 138 (or Unite)(16s rDNA) using q2-feature-classifier with the default parameters. The microbial diversity in Caecal content samples was estimated using the alpha diversity that include Chao1³¹ index and Shannon³² index. The Unifrac distance matrix performed by QIIME software was used for unweighted Unifrac Principal coordinates analysis(PCoA) and phylogenetic tree construction. The 16S rRNA gene amplicon sequencing and analysis were conducted by OE Biotech Co., Ltd.(Shanghai, China).

Statistical analyses

The data were subjected to statistical analysis using SPSS 25.0. Shapiro-Wilk test method was used for normality test (P > 0.05 was considered normal). Normally distributed data were presented as mean ± standard deviation and compared between two groups using a t-test, while non-normally distributed data were presented as median (interquartile range) and differences were assessed using the Mann-Whitney U test. The count data were examined for variations in rates or component ratios through the use of the χ² test. Analysis of gut flora composition and diversity was conducted utilizing QIIME 2 and R software, encompassing assessments of alpha diversity (e.g. Chao1, Shannon, Simpson, Coverage, and PD_whole_tree diversity indices) and beta diversity (e.g. through the implementation of unweighted Unifrac and weighted Unifrac Principal Coordinate Analysis (PCoA)). The R package was utilized to analyze species abundance differences between salt-sensitive and non-salt-sensitive groups using the Wilcoxon statistical algorithm and LEfSe. A significance level of α = 0.05 was employed to determine significant differences in gut microbes.

This study examined 152 individuals for 16s gut microbiota diversity, distributed as follows: 30 in the salt-sensitive hypertensive group, 36 in the salt-sensitive non-hypertensive group, 43 in the non-salt-sensitive hypertensive group, and 43 in the non-salt-sensitive non-hypertensive group. The average age of hypertensive participants was 65.18±10.28 years, with the salt-sensitive and non-salt-sensitive hypertensive groups averaging 63.83±9.91 years and 66.12±10.55 years, respectively, showing no significant age differences (P>0.05).

In normotensive individuals, females were more prevalent than males (60.8% vs 39.2%), with similar proportions in both salt-sensitive and non-salt-sensitive subgroups, though these differences were not statistically significant (P>0.05). Educational levels were mostly elementary or below, with most participants being married and working in agriculture, forestry, animal husbandry, or fisheries. No significant differences were found in these demographics across groups (P>0.05). Income levels mostly ranged from 1000–3000 yuan/month, with smaller proportions earning 3000–5000 yuan/month or less than 1000 yuan/month. While income differences among hypertensive groups were not significant (P>0.05), a significant difference was noted among normotensive individuals (P<0.05), Table 1.

Alpha diversity analysis

The study measured Alpha diversity in populations with hypertension and normal blood pressure using seven indices (observed species, ACE, Chao1, Shannon, Simpson, goods_coverage, and PD_whole_tree) regarding species richness and evenness. No significant differences were found between the salt-sensitive and non-salt-sensitive groups in each population, (all P>0.05) (fig. 1, fig. 2).

Beta diversity analysis

Beta diversity analysis was performed on the gut microbiota of hypertensive individuals, comparing those who are salt-sensitive to those who are not. The analysis using unweighted UniFrac PCoA indicated that the primary two components accounted for 13.05% and 6.39% of the variability, respectively. Although no clear separation was observed in the PCoA plot, PERMANOVA confirmed a significant difference in beta diversity (P<0.05). Conversely, weighted UniFrac PCoA revealed that these components explained 31.56% and 16.12% of the differences, respectively. However, PERMANOVA showed no significant difference in species abundance (all P>0.05) (Fig. 3, A and B).

In normotensive individuals, significant differences in gut microbiota beta diversity were observed, as confirmed by PERMANOVA (P<0.05). Unweighted UniFrac PCoA analysis showed that the first and second principal components accounted for 13.42% and 5.46% of the variation, respectively. Weighted UniFrac PCoA indicated contributions of 32.86% and 13.55% by the first two components. However, no clear separation was visible on the plot, and PERMANOVA indicated no significant differences in species abundance between the groups (all P>0.05) (Fig. 3, C and D).

Species composition analysis

In hypertensive individuals, the predominant bacterial classes include Clostridia, Bacteroidia, Gammaproteobacteria, and Actinobacteria. The main orders are Oscillospirales, Bacteroidales, Lachnospirales, and Enterobacterales, with dominant families being Lachnospiraceae, Ruminococcaceae, Prevotellaceae, and Enterobacteriaceae. The leading genera are Prevotella, Faecalibacterium, Bacteroides, Bifidobacterium, and Escherichia-Shigella (Table 2, Fig. 4, A-E).

In normotensive individuals, the primary bacterial phyla are Firmicutes, Bacteroidota, Proteobacteria, and Actinobacteriota, just like in hypertensive individuals. The chief classes are Clostridia, Bacteroidia, Gammaproteobacteria, and Actinobacteria. Among salt-sensitive individuals, the principal orders are Oscillospirales, Lachnospirales, Bacteroidales, and Bifidobacteriales, while in non-salt-sensitive individuals, they are Oscillospirales, Lachnospirales, Bacteroidales, and Enterobacterales. The dominant families in salt-sensitive individuals are Lachnospiraceae, Ruminococcaceae, Bacteroidaceae, and Prevotellaceae, whereas in non-salt-sensitive individuals, they are Lachnospiraceae, Ruminococcaceae, Enterobacteriaceae, and Prevotellaceae. The leading genera in both groups are Prevotella, Faecalibacterium, Bacteroides, Bifidobacterium, and Escherichia-Shigella (Table 2, Fig. 5, A-E).

Wilcoxon characteristic differential species

In hypertensive populations, the genera Blautia, CAG-352, Klebsiella, Anaerostipes, Acinetobacter, Enterococcus, Prevotellaceae_NK3B31_group, Megasphaera, Dubosiella, and Fenollaria showed significant differences between salt-sensitive and non-salt-sensitive individuals (all P<0.05), with Acinetobacter, Prevotellaceae_NK3B31_group, and Megasphaera being more abundant in the salt-sensitive group (Fig 6A).

In normotensive populations, significant variances were observed in the phyla Bacteroidota, Campilobacterota, Acidobacteriota, Nitrospirota, and Spirochaetota between salt-sensitive and non-salt-sensitive groups (all P<0.05), with the former showing higher levels. At the genus level, Bifidobacterium, Clostridia_UCG_014, Lachnospira, Eubacterium_ruminantium_group, Succinivibrio, Lachnospiraceae_UCG_010, Lachnospiraceae_UCG_004, UCG-003, RF39, and Eubacterium_siraeum_group also differed, with higher abundances in the salt-sensitive group noted ( Fig. 6, B and C).

LEfSe analysis

To further analyze the differences in gut bacteria between the phylum and genus levels in SSHS and SSNHS in the hypertensive population, key microbiome elements were conducted using linear discriminant analysis efficacy values (LEfSe) to find species that differed significantly in abundance between species (i.e., biomarkers). The LEfSe method emphasizes both statistical significance and biological relevance. The LDA threshold was set to 3.0 to identify the marker species corresponding to each group. The number of biomarkers at different genus levels differed significantly between the hypertensive population and the normotensive population. The biomarkers for the hypertensive population, including CAG_352 and Acetanaerobacterium, were enriched in the SSHS, while Blautia, Klebsiella, Pseudomonadales, and Moraxellaceae were enriched in the SSNHS (Fig. 7A). Meanwhile, the biomarkers for the normotensive population were Bacteroidota, Bacteroidia, Actinobacteria, Bifidobacteriaceae, Bifidobacteriales, and Bifidobacterium were enriched in the NSSHS, whereas Clostridia_UCG_014 was enriched in the NSSNHS (Fig. 7B).

Functional predictions

The COG function terms and KEGG pathways were compared between hypertensive and normotensive populations. The hypertensive population exhibited 4 significantly different KEGG function terms (Fig. 8C), while the normotensive population showed 6 significantly different KEGG function terms (Fig. 8D). The analysis of the COG pathway revealed 6 significantly distinct metabolic pathways in the hypertensive population (Fig. 8A). Meanwhile, the COG pathway analysis identified 6 significantly different metabolic pathways in the normotensive population (Fig. 8B).

This study identified the predominant phyla present in salt-sensitive and non-salt-sensitive individuals within hypertensive and normotensive populations, including Thick-walled Bacteria, Anaplasma, Aspergillus, and Actinobacteria. These findings align with a previous study conducted on a healthy Tibetan population³³. Additionally, the major phyla observed were Prevotella, E. faecalis, Bacteroides, Bifidobacterium, and Escherichia coli-Shigella, with the first three being consistent with the predominant phyla in healthy Tibetan populations³⁴. A study has identified variations in the predominant genera across different racial groups. For instance, Prevotella spp. have been found to be more prevalent in Tibetan populations compared to Han Chinese individuals³⁵. Prevotella spp. is considered a core genus among Tibetans, as it produces short-chain fatty acids that aid in acclimatization to high-altitude environments^{35, 36}. Anaplasma spp. primarily participate in the breakdown of animal proteins and fats, with their abundance potentially influenced by dietary habits; sustained consumption of proteins and animal fats may elevate Anaplasma spp. levels, whereas a prolonged carbohydrate-based diet may promote the proliferation of Prevotella spp. in the gut microbiota. Shigella spp. and Escherichia coli spp. are both members of the Enterobacteriaceae family and exhibit significant genetic similarities in numerous isolates. Furthermore, the prevalence of E. coli spp. is elevated in individuals with atherosclerosis³⁷, whereas Shigella spp. is recognized as a significant bacterial pathogen causing dysentery worldwide³⁸. This study revealed a heightened relative abundance of Escherichia coli-Shigella spp. across all participant groups, underscoring the necessity for a more refined assay to accurately distinguish the predominant genera within the Gannan Tibetan population and to delve deeper into their potential correlation with disease.

Meanwhile, we conducted an analysis of the distinctive differential species present in the Gannan Tibetan population using Wilcoxon analysis. Our findings revealed that Fusobacterium spp, Prevotella spp_NK3B31_group, and Megalococcus spp. were elevated in the salt-sensitive group of individuals with hypertension. A study documented the isolation of Fusobacterium spp. strains from milk and milk derivative samples, suggesting that these microorganisms may possess conditional pathogenicity and multidrug resistance³⁹. Additionally, Fusobacterium spp. were identified in raw milk and raw beef³⁷. Air-dried yak meat and yak milk as unique raw food items consumed by Tibetan residents. The higher consumption of dairy products in the salt-sensitive group, as opposed to the non-salt-sensitive group, may account for the increased relative abundance of Fusobacterium sp. in the former group. Moreover, the Prevotella family has been implicated in the formation of trimethylamine-N-oxide (TMAO)⁴⁰, a metabolite originating in the intestine that is linked to vascular dysfunction and hypertension. This metabolite has been shown to disrupt bile acid metabolism and inhibit FXR, potentially indicating that TMAO indirectly influences salt sensitivity through bile acid metabolism disturbances⁴¹. This could explain the higher prevalence of Prevotella species in the salt-sensitive group.

Additionally, the prevalence of various bacterial and fungal phyla and species, including Anaplasma, Campylobacter, Acidobacter, Nitrospira, Spirochaetes, Bifidobacterium, Trichoderma, and various Trichoderma species, was found to be higher in salt-sensitive individuals within a normotensive population. Significant variations in salt-sensitive hypertension have been observed in Dahl salt-sensitive rats when comparing an animal diet to a grain diet, with a higher prevalence of the Mycobacterium anisopliae phylum S24-7 in Dahl salt-sensitive rats compared to non-salt-sensitive rats⁴². Additionally, a high salt diet was found to elevate the prevalence of Trichoderma sp^{43, 44}. These findings collectively indicate that the increased prevalence of Mycobacterium spp. and Trichosporon spp. in the salt-sensitive group may be linked to the dietary patterns of the Northwest region. The potential mechanism at play may involve the dysregulation of bile acid signaling induced by high-fat and high-salt diets, leading to impaired inhibition of NLRP3 inflammatory vesicle activation through the TGR5-cAMP-PKA axis. This process may contribute to the progression of elevated blood pressure and exacerbation of systemic inflammation, ultimately leading to salt-sensitive hypertension. Moreover, Campylobacter, a prominent pathogen responsible for diarrheal illnesses globally, primarily spreads through foodborne routes such as consumption of undercooked meat and raw milk⁴⁵. Gannan Tibetans' dietary habits may contribute to higher levels of Campylobacter in those who are sensitive to salt.

Further analysis using LEfSe revealed a higher number of characteristic species in salt-sensitive individuals compared to non-salt-sensitive individuals within the hypertensive population. Setting the LDA threshold to 3.0 identified CAG_352 and Acetanaerobacterium as enriched in the salt-sensitive group. Limited research exists on CAG_352 and Acetanaerobacterium in relation to human health, with Acetanaerobacterium being identified as a pro-inflammatory taxon and a characteristic microbiota of infarcts in the basal ganglia region⁴⁶. Increased levels of CAG_352 and Acetanaerobacterium in individuals sensitive to salt could indicate a potential link between gut bacteria and salt sensitivity. In the normal blood pressure population, the salt-sensitive subgroup demonstrated a greater abundance of characteristic species in comparison to the non-salt-sensitive subgroup. Actinobacterium spp. were found to be more prominent in the salt-sensitive subgroup. Research suggests a significant correlation between Actinobacteria and high-fat diets⁴⁷. The higher intake of red meat and dairy products in the salt-sensitive subgroup may account for these observations, consistent with the outcomes of the Wilcoxon characteristic differential species analysis.

Functional analysis utilizing the KEGG revealed that the normotensive cohort exhibited a greater abundance of genes involved in numerous metabolic pathways compared to the hypertensive cohort. Specifically, the gut microbiota of normotensive individuals demonstrated enrichment in genes associated with metabolic functions. The gut bacteria composition of normotensive individuals exhibited an enrichment of genes associated with metabolic functions, particularly in processes related to Carbon fixation in photosynthetic organisms, Photosynthesis, Zeatin biosynthesis, Phenazine biosynthesis, N-Glycan biosynthesis. Conversely, the gut bacteria composition of hypertensive individuals showed an enrichment of genes involved in metabolic functions such as Degradation of aromatic compounds, Xylene degradation, Atrazine degradation, Fluorobenzoate degradation. The result of the COG enrichment analysis revealed significant differences in 6 COG functional classifications between the hypertensive and normotensive population. Notably, the normotensive population exhibited the most significant differences in Site-specific recombinase XerD, Glycosyltransferase involved in cell wall bisynthesis, Predicted ATPase, AAA + superfamily, Cytidylate kinase, Acyl carrier protein and Sugar transferase involved in LPS biosynthesis (colanic, teichoic acid). Conversely, the hypertensive population displayed the most significant differences occurred in ABC-type sugar transport system, Ribose/xylose/arabinose/galactoside ABC-type transport system, permease component, Sugar (pentulose or hexulose) kinase, Ribulose-5-phosphate 4-epimerase/Fuculose-1-phosphate aldolase, Succinate dehydrogenase/fumarate reductase, flavoprotein subunit, ABC-type sugar transport system, ATPase component.

The research indicates a potential association between gut microbiota and salt sensitivity in blood pressure across various blood pressure categories, although it is important to acknowledge the study's limitations. Firstly, these include a restricted sample size due to constraints in data availability and the collection of a small number of fecal samples. Secondly, the study predominantly focused on rural Tibetan individuals residing in Gannan, Northwest China, but there are differences in dietary patterns and lifestyles between rural and urban populations, as well as among various ethnic groups. Hence, the generalizability of our findings for replication in other populations may be limited. To enhance the objectivity and generalizability of the study, it is recommended that the sample size be increased and urban samples be included in subsequent studies to encompass a broader range of populations. This will allow for a more comprehensive evaluation of blood pressure, salt sensitivity, and intestinal microbiology in the Northwest population.

This study identified notable variations in the relative abundance, diversity, and community structure of gut microbiota between salt-sensitive and non-salt-sensitive groups across various blood pressure conditions within the Gannan Tibetan population. The findings suggest that salt sensitivity may influence the composition of gut microbiota. The salt-sensitive group exhibited a greater abundance of characteristic species compared to the non-salt-sensitive group, with CAG_352 and Acetanaerobacterium potentially serving as biomarkers for salt sensitivity in individuals with hypertension, while Bacteroidetes and other species may serve as biomarkers for salt sensitivity in individuals with normal blood pressure.

Funding Information

The work was funded by the National Natural Science Foundation of China (No. 81960614); Key Research and Development Program of International Science and Technology Cooperation in Gansu Province (No. 20YF3WA020); General project of Gansu Provincial Joint Scientific Research Fund (No. 222301794304).

Conflicts of interests

All authors of this research paper have no conflicts of interest to declare.

Funding Information

The work was funded by the National Natural Science Foundation of China (No. 81960614); Key Research and Development Program of International Science and Technology Cooperation in Gansu Province (No. 20YF3WA020); General project of Gansu Provincial Joint Scientific Research Fund (No. 222301794304).

Author Contribution

All authors have read and approved the final manuscript and have no conflicts of interests to disclose. The corresponding author of this manuscript is Ji-hong Hu, and contribution of the authors as mentioned below with their responsibility in the research. All authors of this research paper have directly participated in the planning, execution, or analysis and interpretation of data and have read and approved the final version submitted. The contribution of each author is as follows: conceptualization, Li Wang; data curation, Zhidong Zhang; formal analysis, Liangjia Cao; methodology, Ke-ye Ru and Wen-juan Xu; writing-original draft, Li Wang; designed the research and revised, Li Wang. All authors discussed the results and contributed to the final manuscript.

Acknowledgement

All authors have read and approved the final manuscript and have no conflicts of interests to disclose. The corresponding author of this manuscript is Ji-hong Hu, and contribution of the authors as mentioned below with their responsibility in the research. All authors of this research paper have directly participated in the planning, execution, or analysis and interpretation of data and have read and approved the final version submitted. The contribution of each author is as follows: conceptualization, Li Wang; data curation, Zhidong Zhang; formal analysis, Liangjia Cao; methodology, Ke-ye Ru and Wen-juan Xu; writing-original draft, Li Wang; designed the research and revised, Li Wang. All authors discussed the results and contributed to the final manuscript.

Data Availability

The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable.

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Table 1Comparing baseline characteristics between salt-sensitive and non-salt-sensitive groups in various blood pressure statuses [Mean±SD,n(%)]

Characteristics	High blood pressure（n=73）		P	Normal blood pressure(n=79)		P
Characteristics	SSHS(n=30)	SSNHS(n=43)	P	NSSHS(n=36)	NSSNHS(n=43)	P
Age (year)	63.83±9.91	66.12±10.55	0.35	56.58±13.21	59.58±11.58	0.29
Sex (F/M)	18/12	19/24	0.18	21/15	27/16	0.69
SBP (Hg/mm)	156.22±16.61	152.50±11.49	0.26	113.38±13.85	121.94±11.11	<0.01
DBP (Hg/mm)	87.93±13.25	85.13±9.05	0.29	69.11±8.44	75.97±6.60	<0.01
SSBP (Hg/mm)	154.48±16.09	150.01±12.54	0.19	121.29±14.01	121.04±11.32	0.93
SDBP(Hg/mm)	92.50±13.17	82.87±8.96	<0.01	76.24±9.75	75.97±5.97	0.74
Height (cm)	160.35±7.98	158.80±7.81	0.42	160.00±7.29	158.00±7.81	0.31
Weight (cm)	66.38±11.24	61.08±9.49	0.04	60.75±11.68	60.53±10.76	0.93
BMI(kg/m²)	25.74±3.35	24.21±3.20	0.05	23.78±4.63	24.18±3.36	0.66
Waist (cm)	84.63±9.32	80.46±9.49	0.07	77.61±11.08	78.53±11.31	0.72
Primary and lower, %(n)	30(100.0%)	43(100.0%)	0.40	36(100.0%)	42(97.7%)	0.36
Married state, %(n)	30(100.0%)	42(97.7%)	0.34	36(100.0%)	42(97.7%)	0.36
Occupational conditions, %(n)			0.64			0.50
Public Officials	10(33.3%)	16(37.2%)		0(0.0%)	2(4.7%)
Works	18(60.0%)	26(60.5%)		36(100.0%)	40(93.0%)
Unemployed/Job Loss	2(6.7%)	1(2.3%)		0(0.0%)	1(2.3%)
Household Income, n(%)			0.34			0.043
<1000 RMB	4(13.3%)	2(4.7%)		2(5.6%)	0(0.0%)
1000-3000 RMB	23(76.7%)	34(79.1%)		26(72.2%)	24(55.8%)
≥3000 RMB	3(10.0%)	7(16.3%)		8(22.2%)	19(44.2%)
Current smokers, %(n)	7(23.3%)	10(23.3%)	0.94	14(38.9%)	13(30.2%)	0.42
Current drinker, %(n)	3(10.0%)	5(11.6%)	0.83	8(22.2%)	6(14.0%)	0.34

Note: SBP, Systolic Blood Pressure; SD, standard deviance; DBP, Diastolic Blood Pressure; SSBP, Salt Sensitivity of Systolic Blood Pressure; SDBP, Salt Sensitivity of Diastolic Blood Pressure;

Table 2 Dominant gut microbiota in SSHS, SSNHS, NSSHS, NSSHS, NSSNHS

Gut microbiota	High blood pressure		Normal blood pressure
	SSHS(n=30)	SSNHS(n=43)	NSSHS(n=36)	NSSNHS(n=43)
Phylum	Firmicutes, Bacteroidota, Proteobacteria, Actinobacteriota		Firmicutes, Bacteroidota, Proteobacteria, Actinobacteriota
Class	Clostridia, Bacteroidia, Gammaproteobacteria, Actinobacteria		Clostridia, Bacteroidia, Gammaproteobacteria, Actinobacteria
Order	Oscillospirales, Bacteroidales, Lachnospirales, Enterobacterales		Oscillospirales, Lachnospirales, Bacteroidales, Bifidobacteriales	Lachnospiraceae, Ruminococcaceae, Enterobacteriaceae, Prevotellaceae
Family	Lachnospiraceae, Ruminococcaceae, Prevotellaceae, Enterobacteriaceae		Lachnospiraceae, Ruminococcaceae, Bacteroidaceae, Prevotellaceae	Lachnospiraceae, Ruminococcaceae, Enterobacteriaceae, Prevotellaceae
Genus	Prevotella, Faecalibacterium, Bacteroides, Bifidobacterium, Escherichia-Shigella		Prevotella, Faecalibacterium, Bacteroides, Bifidobacterium, Escherichia-Shigella

No competing interests reported.

AppendixS1.pdf

Characteristic Gut Microbial Species Associated with Salt Sensitivity in Hypertensive and Normotensive Tibetan Individuals

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Abstract

Figures

Introduction

Materials and Methods

Study subject

Data collection

Blood pressure salt sensitivity test

16s diversity detection

Bioinformatic analysis

Statistical analyses

Result

Discussion

Conclusion

Declarations

Funding Information

Conflicts of interests

Funding Information

Author Contribution

Acknowledgement

Data Availability

References

Tables

Additional Declarations

Supplementary Files

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