Characteristic Gut Bacteria in High Barley Consuming Japanese Individuals without Hypertension

Abstract

Background: Barley, a grain rich in soluble dietary fiber β-glucan, is expected to lower blood pressure. Conversely, individual differences in its effects on the host might be an issue, and gut bacterial composition may be a determinant. Methods: Using data from a cross-sectional study, we examined whether the gut bacterial composition could explain the classification of a population with hypertension risks despite their high barley consumption. Participants with high barley intake and no occurrence of hypertension were defined as “responders” (n = 26), whereas participants with high barley intake and hypertension risks were defined as “non-responders” (n = 39). Results: 16S rRNA gene sequencing revealed that feces from the responders presented higher levels of Faecalibacterium, Ruminococcaceae UCG-013, Lachnospira, and Subdoligranulum and lower levels of Lachnoclostridium and Prevotella 9 than that from non-responders. We further created a machine-learning responder classification model using random forest based on gut bacteria with an area under the curve value of 0.75 for estimating the effect of barley on the development of hypertension. Conclusions: Our findings establish a link between the gut bacteria characteristics and the predicted control of blood pressure provided by barley intake, thereby providing a framework for the future development of personalized dietary strategies.

Gut microbiota’s causative relationship with peripheral artery disease: a Mendelian randomization study

“…Elevated levels of TMAO can inhibit reverse cholesterol transport and bile acid metabolism, amplifying vascular inflammation and cellular apoptosis, leading to atherosclerosis ( Chen et al, 2023 ). Moreover, other studies have shown the links of Lachnoclostridium with conditions like obesity ( Guo et al, 2023 ), hypertension ( Maruyama et al, 2023 ), and diabetes ( Zang et al, 2023 ). Our findings, suggesting an association between Lachnoclostridium and PAD, further underscore the role of this bacterial genus in vascular diseases.…”

The differential effect of two cereal foods on gut environment: a randomized, controlled, double-blind, parallel-group study

“…These variations can influence individual responses, categorizing some as “responders” who exhibit the anticipated effects, while others as “non-responders.” For instance, in a study involving mice fed barley, an elevation in Prevotella was detected among responders, where improved glucose tolerance was noted. This change was attributed to the production of succinic acid by Prevotella , resulting from the decomposition of β-glucan present in barley, which subsequently modulated glucose metabolism in the liver ( 38 ). To further elucidate the characteristics of the intestinal environment in subjects with heightened IgA and to discern potential similarities or differences between the CF and FG cohorts, we undertook a correlation analysis linking fecal IgA levels with the intestinal milieu.…”

Diversity of the Japanese Gut Microbiome Analysis: Relative Approach Using Principal Component Analysis

“…Principal component analysis (PCA) and multidimensional scaling (MDS or principal coordinates analysis/PCoA) are often used for gut microbiome analyses [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. PCA and PCoA are types of unsupervised machine learning.…”

“…Gut microbiome analysis is a field of information engineering. Moreover, in recent years, bacteriological studies have sometimes been conducted using the results from the gut microbiome analysis [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. However, misinformation is pervasive in the human microbiome literature [6].…”

“…Many recent microbiome analyses have compared the proportions of compositional data. Many studies apply mathematical incorrect methods (multidimensional scaling, correlation coefficient and arithmetic means) for analyzing the gut microbiome [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. Misinformation on microbiota analysis can cause great harm to bacteriology professionals.…”