The Gut Microbiota Genus Blautia is Associated with Skeletal Muscle Mass Reduction in Community-Dwelling Older Japanese Adults: The Wakayama Study

doi:10.21203/rs.3.rs-4930379/v1

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The Gut Microbiota Genus Blautia is Associated with Skeletal Muscle Mass Reduction in Community-Dwelling Older Japanese Adults: The Wakayama Study

https://doi.org/10.21203/rs.3.rs-4930379/v1

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Purpose: This cross-sectional study examined the gut microbiota species associated with skeletal muscle mass reduction in a community-based sample of older Japanese adults.

Methods: The study included 744 participants aged 65–89 years (mean age, 73 years) with no history of treatment for colorectal, chronic kidney, or liver diseases. Bioelectrical impedance analysis was performed to estimate the appendicular skeletal muscle mass (ASM) of each participant. The gut microbiota composition was assessed using next-generation sequencing targeting the V3-V4 regions of the prokaryotic 16S rRNA genes. A self-administered questionnaire was used to evaluate daily living habits, including food intake associated with maintaining the gut microbiota.

Results: Among the participants, those with reduced muscle mass (defined as an ASM index of less than 4.4 kg/m² for men and 3.7 kg/m² for women) had significantly higher levels of the genus Blautia when compared with those with normal muscle mass (P=0.009). Logistic regression analysis revealed that the association between the genus Blautia and skeletal muscle mass remained significant even after adjusting for multiple confounding factors (P=0.012). Additionally, an increase in the genus Blautia was positively associated with excessive alcohol consumption (≥ 20 g/day, β=0.125, P=0.002) and negatively associated with regular yogurt intake (≥ 1 time/week, β=-0.101, P=0.010), independent of other lifestyle and dietary factors.

Conclusion: Elevated levels of the genus Blautia were associated with reduced skeletal muscle mass in older Japanese adults, suggesting that improving the gut microbiota may be a potential approach to preserving muscle mass among this population.

gut microbiota

sarcopenia

skeletal muscle mass

alcohol consumption

yogurt intake

general population

Aim: To investigate the gut microbiota associated with skeletal muscle mass reduction in a community-based sample of older Japanese adults.

Findings: An increase in the genus Blautia was significantly and independently associated with decreased skeletal muscle mass. Excessive alcohol consumption and regular yogurt intake were found to influence changes in the abundance of the genus Blautia.

Message: Improving the gut microbiota, particularly by managing alcohol and yogurt intake, could be a potential approach to preserving skeletal muscle mass in older adults.

With the aging population, the prevention of frailty in older adults has become a major public health concern. Sarcopenia, a syndrome that combines loss of muscle mass with poor muscle strength, often worsens with age and increases the risk of falls, fractures, and difficulties in performing daily activities [1]. Well-known factors contributing to sarcopenia include aging, lack of physical activity, and poor nutrition [2]. Other factors, such as visceral functions related to nutrient digestion and absorption, may also be associated with sarcopenia [3]; however, their roles remain poorly clarified.

Recent studies have demonstrated that changes in the gut microbiota can influence various health conditions, including obesity [4], diabetes [5], and atherosclerosis [6]. There is also growing evidence suggesting a link between gut microbiota and sarcopenia. Animal studies have shown that dysbiosis, which is characterized by a decrease in short-chain fatty acid-producing bacteria, can lead to increased levels of inflammatory cytokines, which accelerate muscle cell catabolism and reduce muscle mass [7]. According to epidemiological studies, certain gut microbiota, including Oscillospira, Ruminococcus, Blautia, Subdoligranulum, and Lachnospira, are associated with fluctuations in skeletal muscle mass in older adults [8, 9]. However, the results of these studies have been inconsistent results owing to the inclusion of specific groups, such as institutionalized or hospitalized patients, or small sample sizes, even within the general population. Additionally, because the gut environment can be influenced by regional dietary culture [10], the microbiota associated with skeletal muscle mass may vary across countries. However, research on this topic in Japan is still lacking when compared with other countries.

Therefore, in the present study, we investigated the gut microbiota associated with skeletal muscle mass in a population-based sample of older Japanese adults and examined factors that may influence changes in the gut microbiota contributing to muscle mass reduction.

Study Participants

The study participants were part of the general population enrolled in the Wakayama Health Promotion Study (Wakayama Study). The Wakayama Study is a community-based prospective cohort study that began in 2011 and recruited residents of rural districts in Wakayama Prefecture, western Japan [11]. We used the most recent dataset of individuals who participated in multiple examinations. Of the 2358 participants from 2018 to 2021, 804 individuals aged 65–89 years who completed all assessments were initially included. Of these, participants who did not meet the inclusion criteria were excluded: 44 participants with a diagnosis of colorectal disease (n = 26), severe glucose intolerance (n = 8), chronic kidney disease or severe renal dysfunction (n = 9), or liver dysfunction (n = 1); and 16 participants with extreme obesity (body mass index, BMI ≥ 30 kg/m²). Consequently, a total of 744 older adults (320 men, 424 women) were selected for data analysis.

Written informed consent and permission to use the examination data were obtained from the participants after explaining the objectives and experimental procedures of the study. This study was approved by the Ethics Committee of the Wakayama Medical University (approval no. G92) and was conducted in accordance with the 1964 Declaration of Helsinki and its subsequent amendments or equivalent ethical standards.

General procedure

We conducted general health examinations, including anthropometric, physiological, and blood biochemical measurements. All measurements were performed in the morning after overnight fasting. The participants were instructed to refrain from performing vigorous physical activities, smoking, and drinking beverages containing caffeine prior to the examinations. Patients who are taking medications were advised not to take them until the end of the examination period.

Height and weight were measured with participants wearing lightweight clothes without shoes. The BMI was calculated as weight (kg) divided by height in meters squared (m²). Waist circumference was measured in the upright position at the end of normal expiration at the ribs in the midaxillary line using a standard non-stretchable flexible measuring tape. Blood samples were obtained from the antecubital vein using standard techniques to measure the concentrations of triglycerides, glycated hemoglobin (HbA1c), aspartate aminotransferase (AST), alanine amino transferase (ALT), albumin, and total protein. The risk profiles of the individuals were determined based on the following criteria: obesity, BMI ≥ 25 kg/m²; abdominal obesity, waist circumference ≥ 85 cm in men and ≥ 90 cm in women (according to the Japan Society for the Study of Obesity Guidelines 2022 [12]); diabetes mellitus, HbA1c ≥ 6.5%; liver dysfunction, AST ≥ 40 IU/L and AST ≥ 40 IU/L; and hypoalbuminemia, albumin < 4.0 g/dL.

A self-administered questionnaire was used to collect data on participants’ medical history, medication use, and daily habits, including smoking, alcohol consumption, sleep, and physical activity. Smoking behavior was assessed based on the responses to current and past smoking experiences. Participants were considered current smokers if they had smoked for ≥ 6 months and continued smoking until the last month. Daily alcohol consumption was determined based on the type of alcohol consumed, drinking frequency, and the amount consumed per day. Alcohol consumption ≥ 20 g/day was defined as excessive according to the recommendations by the Ministry of Health, Labor and Welfare of Japan [13]. Regular exercise was defined as light-to-moderate exercise (< 6.0 metabolic equivalents) for ≥ 30 min, performed at least twice weekly for one year. The average sleep hours per night were determined from the reported bedtime and wake-up times over the previous month.

Dietary habits were assessed using a brief-type self-administered diet history questionnaire (BDHQ) [14], which collected information on habitual food frequency and dietary practices over the past year. An ad hoc computer algorithm based on the Japanese Standard Tables of Food Composition developed for the BDHQ was used to calculate the intakes of protein, fat, carbohydrates, total dietary fiber, and salt. Additionally, participants were asked to report their weekly frequency dairy product consumption, including milk and yogurt.

Skeletal muscle mass

Bioelectrical impedance analysis (Physion MD, Physion Co., Ltd, Kyoto, Japan) was performed to estimate the whole and regional body compositions [15]. Measurements were performed with the participants in a comfortable supine position. The electrodes were placed at 12 locations on the left and right upper and lower limbs. The device measured the impedance and muscle mass of each body segment, including the upper arm, forearm, thigh, lower leg, and trunk. Muscle mass values obtained using this device highly correlated with those obtained using magnetic resonance imaging (MRI) [16]. Appendicular skeletal muscle mass (ASM) was determined as the sum of the muscle mass in the arms and legs. The ASM value was converted to the ASM index by dividing it by the squared height (kg/m²). The sex-specific lowest quintile of the ASM index (< 4.4 kg/m² for men and < 3.7 kg/m² for women) in the general population aged ≥ 65 years, as reported in our previous study, was used to define muscle mass reduction [17].

Gut microbiota

Fecal samples were collected within three days prior to the health examination using a commercial tube kit (Techno Suruga Laboratory Co., Ltd., Shizuoka, Japan). Samples from each participant were stored at 4°C until DNA extraction [18, 19]. The composition of the gut microbiota was determined using next-generation sequencing analysis targeting the V3-V4 region of the prokaryotic 16S rRNA genes, as described previously [20]. The relative abundance of each gut microbiota genus was calculated by dividing the read count for each genus by the total read count. Detailed descriptions of gut microbiota measurements are available elsewhere [21]. In this study, 380 genera were detected, and 11 genera with a relative abundance greater than 1.0% were included in the analysis. The Shannon index was used to assess the diversity of gut microbiota.

Statistical analysis

Descriptive statistics are presented as mean ± standard deviation and median (interquartile range) for continuous variables and as percentages for categorical variables, unless otherwise specified. The normality of the distribution of all analyzed variables was assessed. If a variable was non-normally distributed, it was transformed into an approximately normal distribution before the statistical analysis.

To investigate the gut microbiota associated with skeletal muscle mass, participants were divided into subgroups with and without muscle mass reduction based on the aforementioned sex-specific ASM index cutoffs. Gut microbial diversity (Shannon index) and relative abundance at the phylum and genus levels between the groups were compared using the Mann-Whitney U test. In addition, logistic regression analyses were performed with muscle mass reduction as the dependent variable (1 = present, 0 = absent) and certain gut microbiota species as independent variables. The following three models were constructed for the analyses: Model 1 was unadjusted (crude); Model 2 was adjusted for age and sex; and Model 3 was further adjusted for smoking, alcohol consumption, regular exercise, diabetes mellitus, liver dysfunction, and hypoalbuminemia. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for 1 unit increment for continuous variables and presence versus absence for binary (yes/no) variables.

We conducted additional linear regression analyses to investigate the associations between the selected gut microbiota species and clinical and demographic data, as well as lifestyle and dietary factors, including smoking, alcohol consumption, sleeping habits, regular exercise, and intake of protein, fat, carbohydrates, total dietary fiber, salt, milk, and yogurt. In the models, each factor was included separately as an independent variable with adjustments for age and sex. We also performed multiple regression analyses to assess the strength and independence of the effects of certain factors on the selected gut microbiota species. In the multivariate analyses, along with alcohol consumption and yogurt intake, Models 1 and 2 included age, sex, smoking, regular exercise, sleeping habits, fat intake, carbohydrate intake, dietary fiber intake, salt intake, and milk intake as covariates. Model 3 included alcohol consumption and yogurt intake simultaneously, with adjustments for other lifestyle and dietary factors.

All statistical analyses were conducted using IBM SPSS Statistics for Windows version 28 (IBM Corp., Armonk, NY, USA). The null hypothesis was rejected at a significance level of P < 0.05.

The demographic and clinical characteristics of the study participants are summarized in Table 1. The mean age was 72.6 years, with 34.9% of participants aged ≥ 75 years. The prevalence of obesity, defined as BMI ≥ 25 kg/m², was 25.0%. The mean ASM index was 4.4 ± 0.6 kg/m² (4.8 ± 0.5 kg/m² in men and 4.1 ± 0.5 kg/m² in women), and 22.7% of participants were classified as having low muscle mass based on sex-specific ASM index cutoffs (< 4.4 kg/m² for men and < 3.7 kg/m² for women). The participants had diabetes mellitus (10.3%), liver dysfunction (3.0%), and hypoalbuminemia (4.0%). The proportions of participants who were habitual smokers and those who consumed ≥ 20 g/day of alcohol were 13.1 and 16.1%, respectively.

Table 1

Clinical characteristics in the study participants
Variables	Mean ± s.d, %
Sex, men/ women	320 / 424
Age (years)	72.6 ± 5.5
Anthropometry measures
Body mass index (kg/m²)	22.9 ± 2.9
Waist circumference (cm)	86.1 ± 8.7
Obesity ^a (%)	25.0
Abdominal obesity ^a (%)	44.1
Skeletal muscle mass
Arms (kg)	2.1 ± 0.6
Legs (kg)	9.0 ± 1.9
ASM (kg)	11.1 ± 2.5
ASM-index (kg/m²)	4.4 ± 0.6
Low muscle mass ^a (%)	22.7
Biochemical data
Triglycerides (mg/dL)	112.6 ± 76.9
Hemoglobin A1c (%)	5.9 ± 0.6
AST (IU/L)	24.4 ± 8.5
ALT (IU/L)	20.3 ± 10.1
Albumin (g/dL)	4.4 ± 0.3
Diabetes mellites ^b (%)	10.3
Liver dysfunction ^b (%)	3.0
Hypoalbuminemia ^b (%)	4.0
Dietary and lifestyle variables
Protein intake (g/d)	75.7 ± 27.9
Fat intake (g/d)	54.5 ± 21.3
Carbohydrate intake (g/d)	254.3 ± 87.2
Total dietary fiber intake (g/d)	12.0 ± 4.8
Salt intake (g/d)	11.2 ± 3.9
Milk intake, ≥ 1d/wk ^c (%)	72.0
Yogurt intake, ≥ 1d/wk ^c (%)	67.8
Smoking ^c (%)	13.1
Alcohol consumption, ≥ 20g/d (%)	16.1
Regular exercise ^c (%)	52.7
Sleeping hours, <6h/d (%)	6.0
s.d, standard deviation; ASM, appendicular skeletal muscle mass. ^a Obesity, BMI ≥ 25.0 kg/m²; abdominal obesity, waist circumference ≥ 85 cm for men and ≥ 90 cm for women; low muscle mass, ASM-index < 4.4 kg/m² for men and < 3.7 kg/m² for women. ^b Diabetes mellites, hemoglobin A1c ≥ 6.5%; liver dysfunction, AST ≥ 40 IU/L and AST ≥ 40 IU/L; hypoalbuminemia, albumin < 4.0 g/dL. Patients taking medication are also included. ^c Smoking, smoked for ≥ 6 months and had been smoking until the last month; regular exercise, mild-to-moderate exercise for ≥ 30 minutes at least twice a week for one year.

The Shannon index, a measure of gut microbiota diversity, was compared between groups divided according to the presence or absence of muscle mass reduction (Fig. 1). The median Shannon index was 2.50 and 2.55 for participants with low and normal muscle mass, respectively. No significant difference was observed between the groups (P = 0.129).

Comparisons of the relative abundances of the gut microbiota at the phylum and genus levels between the groups are presented in Table 2. At the phylum level, Firmicutes and Bacteroidetes comprised approximately 70% of the total species, with no significant differences observed between the participants with low and normal muscle mass. However, at the genus level, significant differences were observed between the abundance of Blautia (P = 0.009) and Subdoligranulum (P = 0.023). Logistic regression analysis was performed to examine the strength and independence of the effects of the two genera on muscle mass reduction (Table 3). The genus Blautia was significantly associated with reduced muscle mass in the model adjusted for age and sex (Model 2). However, this association was not observed for the genus Subdoligranulum. Additionally, the genus Blautia remained an independent predictor of reduced muscle mass after further adjustments for smoking, alcohol consumption, regular exercise, diabetes mellitus, liver dysfunction, and hypoalbuminemia (adjusted OR: 1.37; 95% CI: 1.07–1.74; P = 0.012) (Model 3).

Table 2

The relative abundances of the gut microbiota at the phylum and genus levels in groups with low and normal skeletal muscle mass
	Low muscle mass M: < 4.4 kg/m² W: < 3.7 kg/m² (n = 169)	Normal muscle mass M: ≥ 4.4 kg/m² W: ≥ 3.7 kg/m² (n = 575)
Variables	Median [IQR]	Median [IQR]	P ^a
Phylum
Firmicutes	42.48 [34.11–47.80]	41.39 [34.18–47.93]	0.938
Bacteroidetes	26.51 [19.30–34.94]	27.66 [20.62–35.65]	0.215
Actinobacteria	6.41 [3.22–11.12]	6.63 [3.37–12.49]	0.567
Proteobacteria	1.87 [1.08–4.33]	2.10 [1.15–4.18]	0.610
Genus
Bacteroides	19.41 [11.67–27.82]	19.13 [10.94–26.99]	0.548
Blautia	8.08 [5.66–12.40]	7.30 [5.04–10.52]	0.009
Faecalibacterium	4.90 [2.00–7.75]	4.79 [2.17–7.41]	0.842
Bifidobacterium	3.70 [1.20–8.29]	3.99 [1.31–9.20]	0.652
Eubacterium	3.26 [1.44–5.44]	3.10 [1.51–4.95]	0.538
Ruminococcus	2.56 [0.34–5.10]	2.93 [0.76–5.65]	0.216
Collinsella	1.79 [0.50–3.26]	1.93 [0.69–3.32]	0.163
Parabacteroides	1.72 [0.90–3.13]	1.66 [0.98–2.73]	0.804
Fusicatenibacter	1.55 [0.44–3.17]	1.51 [0.57–2.75]	0.779
Subdoligranulum	1.51 [0.17–2.86]	1.12 [0.09–2.27]	0.023
Sterptcoccus	1.16 [0.38–4.51]	0.99 [0.32–3.71]	0.150
M, men; W, women; IQR, interquartile range ^a Significant difference was tested by Mann-Whiteny U test.

Table 3

Logistic regression analysis of the association between skeletal muscle mass and gut microbiota of the genera Blautia and Subdoligranulum
	Low muscle mass (M: <4.4 kg/m², W: <3.7 kg/m²)
	Blautia ^a			Subdoligranulum ^a
	OR	(95%CI)	P	OR	(95%CI)	P
Model 1 ^b	1.34	(1.06, 1.69)	0.014	1.85	(0.94, 3.64)	0.077
Model 2 ^b	1.30	(1.03, 1.65)	0.027	1.70	(0.86, 3.38)	0.127
Model 3 ^b	1.37	(1.07, 1.74)	0.012	1.56	(0.78, 3.11)	0.210
M, men; W, women; OR, odds ratio; 95%CI, 95% confidence interval. ^a The values were transformed into an approximately normal distribution before the statistical analysis. ^b Model 1 was unadjusted (crude), model 2 was adjusted for age and sex, and model 3 was adjusted for model 2 plus smoking, alcohol consumption, regular exercise, diabetes mellitus, liver dysfunction, and hypoalbuminemia.

Associations between the relative abundance of the genus Blautia and various demographic, clinical, lifestyle, and dietary variables were analyzed using a linear regression model (Table 4). After adjusting for age and sex, significant negative correlations were detected between Blautia and BMI and HbA1c levels, whereas AST showed a positive association. Among lifestyle and dietary factors, excessive alcohol consumption (≥ 20 g/day) positively correlated with the genus Blautia, whereas regular yogurt intake (≥ 1 time/week) exhibited a negative correlation.

Table 4

Factors associated with the relative abundance of the genus Blautia
	Blautia ^a
Variables	β ^b	P
Demographic and clinical data
Age (years)	–0.101	0.006
Sex, men ^c	–0.094	0.010
Body mass index (kg/m²)	–0.099	0.007
Waist circumference (cm)	–0.060	0.104
Triglycerides (mg/dL) ^a	0.055	0.133
Hemoglobin A1c (%)	–0.144	< 0.001
AST (IU/L)	0.095	0.009
ALT (IU/L)	0.023	0.525
Albumin (g/dL)	0.071	0.057
Dietary and lifestyle variables
Protein intake (g/d)	0.018	0.619
Fat intake (g/d)	0.033	0.376
Carbohydrate intake (g/d)	–0.018	0.638
Total dietary fiber intake (g/d)	–0.009	0.810
Salt intake (g/d)	0.009	0.805
Milk intake, ≥ 1d/wk ^c	–0.035	0.340
Yogurt intake, ≥ 1d/wk ^c	–0.105	0.005
Smoking ^c	–0.025	0.507
Alcohol consumption, ≥ 20g/d ^c	0.134	< 0.001
Regular exercise ^c	–0.047	0.198
Sleeping hours, < 6 h/d ^c	–0.017	0.641
s.d, standard deviation; β, standardized partial regression coefficient. ^a The value was transformed into an approximately normal distribution before the statistical analysis. ^b Adjusted for age and sex for variables other than age and sex. ^c Sex, milk intake, yogurt intake, smoking, alcohol consumption, regular exercise, sleeping hours were entered into the model as binary (presence/absence) variables.

Furthermore, the independent predictive influence of both alcohol consumption and yogurt intake on the relative abundance of Blautia was tested using multiple linear regression models (Table 5). The significant correlations between Blautia and alcohol consumption and yogurt intake persisted after adjusting for potential confounders, including age, sex, smoking, regular exercise, sleeping habits, fat intake, carbohydrate intake, dietary fiber intake, salt intake, and milk intake (Models 1 and 2). These associations remained significant even when alcohol consumption (β = 0.125, P = 0.002) and yogurt intake (β = -0.101, P = 0.101) were simultaneously included in a single regression model (Model 3).

Table 5

Multivariate regression analysis of association between the relative abundance of the genus Blautia and alcohol consumption and yogurt intake
	Blautia ^a
	Model 1 ^b		Model 2 ^b		Model 3 ^b
	β	P	β	P	β	P
Alcohol consumption, ≥ 20g/d ^c	0.135	< 0.001			0.125	0.002
Yogurt intake, ≥ 1 d/wk ^c			-0.112	0.004	-0.101	0.010
β, standardized partial regression coefficient. ^a The value was transformed into an approximately normal distribution before the statistical analysis. ^b Model 1 and 2 were adjusted for age, sex, fat intake, carbohydrate intake, dietary fiber intake, salt intake, mile intake, smoking, regular exercise, sleeping hours. Mode1 3 included alcohol consumption and yogurt intake simultaneously in addition to the variables in model 1 and 2. ^c Alcohol consumption and yogurt intake were entered into the models as binary (presence/absence) variables.

In this cross-sectional study of community-dwelling older participants, we found that higher levels of Blautia in the gut microbiota were associated with reduced skeletal muscle mass. Furthermore, the relative abundance of the genus Blautia was influenced by excessive alcohol consumption and regular yogurt intake. These findings suggest that elevated levels of the genus Blautia may contribute to muscle mass reduction in older Japanese adults and that improving the gut microbiota, particularly through controlled alcohol consumption and habitual yogurt intake, may serve as a possible approach for maintaining skeletal muscle mass among this population.

We observed that higher levels of the genus Blautia were significantly associated with reduced muscle mass. Recently, certain gut bacterial species have been suggested to be associated with the loss of muscle mass or sarcopenia. A study on older adults (n = 35) in an Italian community found that increased levels of Oscillospira and Ruminococcus, along with decreased levels of Barnesiellaceae and Christensenellaceae, are associated with lower muscle mass [8]. Another study on Chinese outpatients (n = 60) reported that patients with sarcopenia had lower levels of Blautia, Subdoligranulum, and Lachnospira than the control group [9]. However, the mean age differed substantially between patients with sarcopenia (91 years) and the control group (71 years), which may have influenced the results because Blautia levels are known to decrease with age [22]. Although studies involving Japanese participants are limited, a study on community-dwelling older adults (n = 96) found a positive association between lower limb muscle strength and Bacteroides but did not detect an association between muscle mass and gut microbiota composition [23]. In addition, a population-based study (n = 318) found that a decrease in Lachnospiraceae, a family of 36 genera, was associated with sarcopenia. However, this association was identified in a collective group of 32 genera from this family, excluding prominent genera such as Blautia and Roseburia, and no specific association with any particular bacterial species was detected [24]. As observed in these studies, inconsistent results have often been reported, which may be attributed to the inclusion of specific groups, such as institutionalized or hospitalized patients, or small sample sizes, even within the general population. However, this study included a relatively large population-based sample of older adults, and notable associations between the genus Blautia and skeletal muscle mass were confirmed after adjusting for potential confounding factors such as age, sex, and various clinical and lifestyle variables.

Although the underlying mechanism linking higher Blautia levels to reduced muscle mass in not clearly understood, research from animal models revealed that Blautia coccoides induces responses to inflammatory cytokines such as tumor necrosis factor-α, interleukin-10, and interleukin-8 [25]. Increased levels of these inflammatory cytokines in the circulation can disrupt muscle metabolism and impair anabolic stimulation [26]. Another study reported a positive correlation between the relative abundance of Blautia and C-reactive protein levels in patients with hypertension [27]. Therefore, an elevated abundance of Blautia may lead to increased levels of inflammatory cytokines, contributing to a reduction in muscle mass. Furthermore, a deficiency in leucine, an essential amino acid, can result in an increase in Blautia coccoides [28]. Given that leucine plays a crucial role in inhibiting muscle cell degradation and promoting muscle protein synthesis [29], its deficiency may have substantial implications for maintaining skeletal muscle mass in older adults.

In older adults, the gut environment is influenced by dietary patterns, aging, and nutritional status. Japanese dietary habits range between the meat-based diets typical of the U.S. and the grain-based diets commonly found in Asian and Latin American countries. Previous studies on older Japanese adults detected relatively higher proportions of Bifidobacterium and Blautia [30]. Consistent with these findings, the gut microbiota of the participants in the present study was abundant in Bacteroides, Blautia, Bifidobacterium, and Ruminococcus, indicating that the gut microbiota composition of the study participants was similar to that of the older Japanese population.

The composition of the gut microbiota is influenced by nutrient and food intakes. In this study, the relative abundance of Blautia was not significantly associated with the intake of carbohydrates, proteins, lipids, dietary fiber, or salt. Consistent with our findings, a population-based study of Japanese adults aged 20–76 years did not detect a clear association between Blautia and these key nutrients and foods [31]. Conversely, alcohol and yogurt consumption were associated with the relative abundance of the genus Blautia, with excessive alcohol intake increasing Blautia levels and regular yogurt consumption decreasing them. Previous studies have indicated that koji found in sake, malt, and barley, which are ingredients of beer, can increase Blautia levels [32, 33]. Another study reported that when regular red wine was compared with red wine without alcohol, both increased Blautia levels, with a more pronounced effect observed following intake of regular red wine containing alcohol [34]. These findings suggest that excessive consumption of alcohol and its ingredients in alcoholic beverages may contribute to increased Blautia levels.

Yogurt is known to balance the gut microflora and is widely recognized as a probiotic food owing to its beneficial effects on various health disorders by promoting Bifidobacterium [35]. However, limited research has been conducted on the genus Blautia. Studies in animal models have demonstrated that yogurt intake in obese mice reduced the Lachnospiraceae family, including Blautia [36]. Additionally, a subgroup-analysis of an intervention study assessing the impact of continuous yogurt intake (5 weeks) on the gut microbiota in healthy adults revealed a decrease in Blautia levels among women with abnormal lipid metabolism [37]. Despite these findings, few studies have examinined the association between yogurt intake and Blautia. Further investigations are warranted becasue Blautia is a relatively abundant bacterium that may be linked to several health-related indicators.

Regression analysis exploring factors associated with the genus Blautia revealed a negative correlation between age and the relative abundance of Blautia. This finding supports previous studies that reported a decline in Blautia levels with advancing age [22]. BMI was negatively associated with the relative abundance of the genus Blautia in a model adjusted for age and sex. Given that BMI reflects body size through the ratio of height to weight, it likely incorporates muscle mass, particularly in individuals with lower body weight. Conversely, in obese individuals, BMI is influenced not only by muscle mass but also by body fat mass. Therefore, when interpreting the association between BMI and Blautia in all participants, including those with obesity, it is important to consier the impact of fat accumulation on Blautia levels. In a study comparing obese and non-obese individuals, those with greater visceral fat accumulation tended to have lower levels of Blautia [21]. This suggests that obese individuals with a higher BMI may have increased muscle mass along with higher body fat, potentially explaining the observed negative correlation between BMI and Blautia. Furthermore, HbA1c was negatively correlated with Blautia, whereas AST was positively correlated. Previous studies reported a decrease in the relative abundance of Blautia in patients with diabetes mellitus [5]. Because liver dysfunction has been shown to affect Blautia levels [38], the observed increase in Blautia levels among excessive drinkers in our study may explain the notable positive correlation between AST levels and Blautia.

Several potential limitations of this study should be acknowledged. The participants were relatively selective, consisting of residents from rural areas who had undergone community health screening examinations. In addition, almost all participants were able to perform daily activities independently, indicating that this sample may be healthier than the general population. Another limitation is that we did not directly measure skeletal muscle mass. However, the muscle mass values obtained with the device used in this study were highly correlated with direct MRI measurements [16]. In addition to a lack of physical activity and poor nutrition, various conditions, such as organ disorders, malignant tumors, inflammatory conditions, and endocrine disorders, can contribute to a reduction in skeletal muscle mass. Although the participants in this study did not include individuals with severe organ disorders or advanced malignant tumors, we could not entirely rule out the presence of these conditions, including in less severe cases. Additionally, it has been noted that medications like proton pump inhibitors can impact the gut microbiota [39]. However, this study did not collect information on the use of medications that may influence the gut environment. Furthermore, owing to the cross-sectional study design, causality could not be inferred for any of the reported associations. Although substantial associations were detected between the increased abundance of genus Blautia and decreased muscle mass after adjusting for various factors, it was difficult to eliminate all effects, and other potential confounding factors may not have been considered.

Our study revealed that an increase in genus Blautia was significantly and independently associated with reduced skeletal muscle mass in older Japanese adults. These findings support growing evidence that maintaining a balanced gut microbiota plays a role in preserving skeletal muscle mass. Additionally, our results indicated that excessive alcohol consumption and regular yogurt intake can influence the abundance of the genus Blautia. Therefore, interventions aimed at improving gut microbiota are could help prevent the loss of skeletal muscle mass in this population.

Author contributions

MS and NM conceived and designed the study, collected and analyzed the data, interpreted the results, drafted the manuscript, and made the final revisions. YZ and YS contributed to the data collection. KT and TT contributed to the data collection and manuscript revision. MA contributed to the study design, data collection, interpretation of the results, and manuscript revision.

Funding

The Wakayama Health Promotion Study (the Wakayama Study) was supported by the Japan Society for the Promotion of Science Grant-in-Aid for Scientific Research (JSPS KAKENHI): grant numbers (C) 25350894, (C) 21K11116, (C) 21K11703, (C) 19K10581, (C) 17K01861, (C) 16K09104, and by the Japan Science and Technology Agency: grant numbers JPMJCE1302, JPMJCE 2201 and JPMJPF2210. The authors independently designed and analyzed this study.

Data availability

The datasets used and/or analyzed in this study are available from the corresponding author upon reasonable request.

Declarations

Conflict of interest

The authors declare no potential conflicts of interest with respect to the research, authorship, or publication of this article.

Ethical approval

This study was conducted in accordance with the 1964 Declaration of Helsinki and its amendments or equivalent ethical standards. This study was approved by the Ethics Committee of the Wakayama Medical University (approval no. G92).

Informed consent

All participants signed an informed consent form after the study objectives and experimental procedures were explained.

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Editorial decision: Minor revisions
01 Oct, 2024
Reviewers agreed at journal
02 Sep, 2024
Reviewers invited by journal
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Editor assigned by journal
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The Gut Microbiota Genus Blautia is Associated with Skeletal Muscle Mass Reduction in Community-Dwelling Older Japanese Adults: The Wakayama Study

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Abstract

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Key summary points

Introduction

Methods

Study Participants

General procedure

Skeletal muscle mass

Gut microbiota

Statistical analysis

Results

Discussion

Conclusion

Declarations

References

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Version 1