Microbial Dysbiosis Linked to Metabolic Dysfunction-Associated Fatty Liver Disease in Asians: Prevotella copri Promotes Lipopolysaccharide Biosynthesis and Network Instability in the Prevotella Enterotype.

Metabolic dysfunction-associated fatty liver disease (MAFLD), formerly known as non-alcoholic fatty liver disease (NAFLD), is characterized by hepatic fat accumulation by metabolic dysfunction. The rising prevalence of MAFLD, especially among Asians, may be associated with changes in gut microbiota. We investigated gut microbiota characteristics and potential mechanisms leading to MAFLD development according to enterotypes. Case-control studies examining the gut microbiota composition between MAFLD and non-MAFLD participants were searched in public databases until July 2023. Gut microbiota was categorized into two enterotypes by principal component analysis. According to the enterotypes, LEfSe, ALDEx2, XGBoost, and DCiPatho were utilized to identify differential abundances and pathogenic microbes in the gut between the MAFLD and non-MAFLD groups. We analyzed microbial community networks with the SprCC module and predicted microbial functions. In the Prevotella enterotype (ET-P), 98.6% of Asians and 65.1% of Caucasians were associated with MAFLD (p = 0.049). MAFLD incidence was correlated with enterotype, age, obesity, and ethnicity (p < 0.05). Asian MAFLD patients exhibited decreased Firmicutes and Akkermansia muciniphila and increased Bacteroidetes and P. copri. The pathogenicity scores were 0.006 for A. muciniphila and 0.868 for P. copri. The Asian MAFLD group showed decreased stability and complexity in the gut microbiota network. Metagenome function analysis revealed higher fructose metabolism and lipopolysaccharide (LPS) biosynthesis and lower animal proteins and α-linolenic acid metabolism in Asians with MAFLD compared with the non-MAFLD group. LPS biosynthesis was positively correlated with P. copri (p < 0.05). In conclusion, P. copri emerged as a potential microbial biomarker for MAFLD. These findings enhance our understanding of the pathological mechanisms of MAFLD mediated through the gut microbiota, providing insights for future interventions.

A Prediction Model for Osteoporosis Risk Using a Machine-Learning Approach and Its Validation in a Large Cohort.

BACKGROUND: Osteoporosis develops in the elderly due to decreased bone mineral density (BMD), potentially increasing bone fracture risk. However, the BMD is not regularly measured in a clinical setting. This study aimed to develop a good prediction model for the osteoporosis risk using a machine learning (ML) approach in adults over 40 years in the Ansan/Anseong cohort and the association of predicted osteoporosis risk with a fracture in the Health Examinees (HEXA) cohort. METHODS: The 109 demographic, anthropometric, biochemical, genetic, nutrient, and lifestyle variables of 8,842 participants were manually selected in an Ansan/Anseong cohort and included in the ML algorithm. The polygenic risk score (PRS) of osteoporosis was generated with a genome-wide association study and added for the genetic impact of osteoporosis. Osteoporosis was defined with < -2.5 T scores of the tibia or radius compared to people in their 20s-30s. They were divided randomly into the training (n = 7,074) and test (n = 1,768) sets-Pearson's correlation between the predicted osteoporosis risk and fracture in the HEXA cohort. RESULTS: XGBoost, deep neural network, and random forest generated the prediction model with a high area under the curve (AUC, 0.86) of the receiver operating characteristic (ROC) with 10, 15, and 20 features; the prediction model by XGBoost had the highest AUC of ROC, high accuracy and k-fold values (> 0.85) in 15 features among seven ML approaches. The model included the genetic factor, genders, number of children and breastfed children, age, residence area, education, seasons to measure, height, smoking status, hormone replacement therapy, serum albumin, hip circumferences, vitamin B6 intake, and body weight. The prediction models for women alone were similar to those for both genders, with lower accuracy. When the prediction model was applied to the HEXA study, the correlation between the fracture incidence and predicted osteoporosis risk was significant but weak (r = 0.173, P < 0.001). CONCLUSION: The prediction model for osteoporosis risk generated by XGBoost can be applied to estimate osteoporosis risk. The biomarkers can be considered for enhancing the prevention, detection, and early therapy of osteoporosis risk in Asians.

Gut Microbiota Alterations and Their Functional Differences in Depression According to Enterotypes in Asian Individuals.

This study aimed to investigate alterations in the gut microbiota of patients with depression compared to those in the gut microbiota of healthy individuals based on enterotypes as a classification framework. Fecal bacteria FASTA/Q samples from 333 Chinese participants, including 107 healthy individuals (Healthy group) and 226 individuals suffering from depression (DP group), were analyzed. The participants were classified into three enterotypes: Bacteroidaceae (ET-B), Lachnospiraceae (ET-L), and Prevotellaceae (ET-P). An α-diversity analysis revealed no significant differences in microbial diversity between the Healthy and DP groups across all enterotypes. However, there were substantial differences in the gut microbial composition for ß-diversity, particularly within ET-L and ET-B. The DP group within ET-B exhibited a higher abundance of Proteobacteria, while a linear discriminant analysis (LDA) of the DP group showed an increased relative abundance of specific genera, such as Mediterraneibacter, Blautia, Bifidobacterium, and Clostridium. Within ET-L, Bifidobacterium, Blautia, Clostridium, Collinsella, and Corynebacterium were significantly higher in the DP group in the LDA and ANOVA-like differential expression-2 (ALDEx2) analyses. At the species level of ET-L, Blautia luti, Blautia provencensis, Blautia glucerasea, Clostridium innocuum, Clostridium porci, and Clostridium leptum were the primary bacteria in the DP group identified using the machine learning approach. A network analysis revealed a more tightly interconnected microbial community within ET-L than within ET-B. This suggests a potentially stronger functional relationship among the gut microbiota in ET-L. The metabolic pathways related to glucose metabolism, tryptophan and tyrosine metabolism, neurotransmitter metabolism, and immune-related functions showed strong negative associations with depression, particularly within ET-L. These findings provide insights into the gut-brain axis and its role in the pathogenesis of depression, thus contributing to our understanding of the underlying mechanisms in Asian individuals. Further research is warranted to explain the mechanistic links between gut microbiota and depression and to explore their potential for use in precision medicine interventions.

Isolation and identification of mucin-degrading bacteria originated from human faeces and their potential probiotic efficacy according to host-microbiome enterotype.

AIM: Mucin-degrading bacteria are known to be beneficial for gut health. We aimed to isolate human-derived mucin-degrading bacteria and identify potential probiotic characteristics and their effects on the bacterial community and short-chain fatty acid (SCFA) production according to three different enterotypes of the host. METHODS AND RESULTS: Bacteria with mucin decomposition ability from human faeces were isolated and identified by 16S rRNA sequencing and MALDI-TOF. Heat resistance, acid resistance, antibiotic resistance, and antibacterial activity were analysed in the selected bacteria. Their adhesion capability to the Caco-2 cell was determined by scanning electron microscopy. Their ability to alter the bacterial community and SCFA production of the isolated bacteria was investigated in three enterotypes. The three isolated strains were Bifidobacterium(Bif.) animalis SPM01 (CP001606.1, 99%), Bif. longum SPM02 (NR_043437.1, 99%), and Limosilactobacillus(L.) reuteri SPM03 (CP000705.1, 99%) deposited in Korean Collection for Type Culture (KCTC-18958P). Among them, Bif. animalis exhibited the highest mucin degrading ability. They exhibited strong resistance to acidic conditions, moderate resistance to heat, and the ability to adhere tightly to Caco-2 cells. Three isolated mucin-degrading bacteria incubation increased Lactobacillus in the faecal bacteria from Bacteroides and Prevotella enterotypes. However, only L. reuteri elevated Lactobacillus in the faecal bacteria from the Ruminococcus enterotype. B. longum and B. animalis increased the α-diversity in the Ruminococcus enterotype, while their incubation with other intestinal types decreased the α-diversity. Bifidobacterium animalis and L. reuteri increased the butyric acid level in faecal bacteria from the Prevotella enterotype, and L. reuteri elevated the acetic acid level in those from the Ruminococcus enterotype. However, the overall SCFA changes were minimal. CONCLUSIONS: The isolated mucin-degrading bacteria act as probiotics and modulate gut microbiota and SCFA production differently according to the host's enterotypes. SIGNIFICANCE AND IMPACT OF STUDY: Probiotics need to be personalized according to the enterotypes in clinical application.

Modulation of the Gut Microbiota in Memory Impairment and Alzheimer's Disease via the Inhibition of the Parasympathetic Nervous System.

The gut microbiota has been demonstrated to play a critical role in maintaining cognitive function via the gut-brain axis, which may be related to the parasympathetic nervous system (PNS). However, the exact mechanism remains to be determined. We investigated that patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) could exhibit an altered gut microbiota through the suppression of the PNS, compared to the healthy individuals, using the combined gut microbiota data from previous human studies. The hypothesis was validated in rats to suppress the PNS by scopolamine injections. The human fecal bacterial FASTA/Q files were selected and combined from four different AD studies (n = 410). All rats had a high-fat diet and treatments for six weeks. The MD rats had memory impairment by scopolamine injection (2 mg/kg body weight; MD, Control) or no memory impairment by saline injection. The scopolamine-injected rats had a donepezil intake as the positive group. In the optimal model generated from the XGboost analysis, Blautia luti, Pseudomonas mucidoiens, Escherichia marmotae, and Gemmiger formicillis showed a positive correlation with MCI while Escherichia fergusonii, Mycobacterium neglectum, and Lawsonibacter asaccharolyticus were positively correlated with AD in the participants with enterotype Bacteroides (ET-B, n = 369). The predominant bacteria in the AD group were negatively associated in the networking analysis with the bacteria in the healthy group of ET-B participants. From the animal study, the relative abundance of Bacteroides and Bilophilia was lower, and that of Escherichia, Blautia, and Clostridium was higher in the scopolamine-induced memory deficit (MD) group than in the normal group. These results suggest that MCI was associated with the PNS suppression and could progress to AD by exacerbating the gut dysbiosis. MCI increased Clostridium and Blautia, and its progression to AD elevated Escherichia and Pseudomonas. Therefore, the modulation of the PNS might be linked to an altered gut microbiota and brain function, potentially through the gut-brain axis.

Effects of Bile Acid Modulation by Dietary Fat, Cholecystectomy, and Bile Acid Sequestrant on Energy, Glucose, and Lipid Metabolism and Gut Microbiota in Mice.

Bile acid metabolism, involved with the digestion and absorption of nutrients in the gut, is linked to the gut microbiota community, greatly impacting the host's metabolism. We examined the hypothesis that the modulation of bile acid metabolism by dietary fat contents, gallbladder removal (GBX; cholecystectomy), and bile acid sequestrant (BAS; cholestyramine) treatment could alter energy, glucose, and lipid metabolism through the changes in the gut microbiota. Mice were randomly assigned to the following six groups: (1) Sham GBX surgery (Sham) + low fat/high carbohydrate diet (LFD), (2) Sham + high fat diet (HFD), (3) Sham + HFD + BAS, (4) GBX + LFD, (5) GBX + HFD, and (6) GBX + HFD + BAS. BAS groups received 2% cholestyramine. After an 8-week intervention, energy, glucose, and lipid metabolism, and the gut microbiota community were measured. HFD groups exhibited higher body weight gain than LFD, and GBX increased the weight gain comped to Sham groups regardless of BAS in HFD (p < 0.05). Homeostatic model assessment for insulin resistance (HOMA-IR) was higher in HFD than LFD, and GBX increased it regardless of BAS. Serum lipid profiles were worsened in GBX + HFD compared to Sham + LFD, whereas BAS alleviated them, except for serum HDL cholesterol. Hepatic tumor-necrosis-factor-α (TNF-α) mRNA expression and lipid peroxide contents increased with GBX and BAS treatment compared to Sham and no BAS treatment (p < 0.05). Hepatic mRNA expression of sterol regulatory element-binding transcription factor 1c (SREBP1c) and peroxisome proliferator-activated receptor gamma (PPAR-γ) exhibited the same trend as that of tumor necrosis factor-α (TNF-α). The α-diversity of gut bacteria decreased in GBX + HFD and increased in GBX + HFD + BAS. Akkermentia, Dehalobacterium, SMB53, and Megamonas were high in the Sham + LFD, and Veillonella and Streptococcus were rich in the Sham + HFD, while Oscillospira and Olsenella were high in Sham + HFD + BAS (p < 0.05). GBX + LFD increased Lactobacillus and Sutterella while GBX + HFD + BAS elevated Clostridium, Alistipes, Blautia, Eubacterium, and Coprobacillus (p < 0.05). In conclusion, the modulation of bile acid metabolism influences energy, glucose, and lipid metabolisms, and it might be linked to changes in the gut microbiota by bile acid metabolism modulation.

Beneficial Effect of Gastrodia elata Blume and Poria cocos Wolf Administration on Acute UVB Irradiation by Alleviating Inflammation through Promoting the Gut-Skin Axis.

Bioactive compounds in some herbs can, directly and indirectly, protect against photoaging. We evaluated the effects of Gastrodia elata Blume (GE) and Poria cocos Wolf (PC) water extracts on ultraviolet (UV) B-induced skin lesions by acute UVB exposure in ICR mice and explored their mechanism of action. After removing the hair on the back of the mice, UVB (280-310 nm) was exposed to the back for 30 min to induce skin damage. Four UVB exposure groups were divided into the following according to the local application (1,3-butanediol extract) on the dorsal skin and oral intake (0.3 g water extract/kg body weight/day): 1,3-butanediol and cellulose(control; UV-Con), retinoic acid (positive-control; UV-Positive), PC extracts (UV-PC), and GE extracts (UV-GE). The fifth group had no UVB exposure with the same treatment as the UV-Con (Normal-control). The erythema, burns, erosion, and wounds of the UV-PC and UV-PC groups were alleviated, and the most significant improvements occurred in the UV-PC group. PC and GE reduced the thickness of the dorsal skin tissue, the penetration of mast cells, and malondialdehyde contents. The mRNA expression of TNF-α, IL-13, and IL-4, inflammatory factors, were also reduced significantly in the dorsal skin of the UV-PC and UV-GE groups. UV-PC, UV-GE, and UV-Positive showed improvements in UV-induced intestinal tissue inflammation. UV-Con deteriorated the intestinal morphology, and PC and GE alleviated it. The α-diversity of the fecal microbiota decreased in the UV-control, and UV-PC and UV-GE prevented the decrease. Fecal metagenome analysis revealed increased propionate biosynthesis in the UV-PC group but decreased lipopolysaccharide biosynthesis in the UV-PC and UV-GE groups compared to UV-Con. In conclusion, the local application and intake of PC and GE had significant therapeutic effects on acute UV-induced skin damage by reducing oxidative stress and proinflammatory cytokines, potentially promoting the gut-microbiota-gut-skin axis.

Long-Term Effect of Porcine Brain Enzyme Hydrolysate Intake on Scopolamine-Induced Memory Impairment in Rats.

No study has revealed the effect of porcine brain enzyme hydrolysate (PBEH) on memory impairment. We aimed to examine the hypothesis that PBEH intake modulates memory deficits and cognitive behavior in scopolamine (SC)-induced amnesia rats, and its mechanism, including gut microbiota changes, was determined. Sprague-Dawley male rats had intraperitoneal injections of SC (2 mg/kg body weight/day) at 30 min after daily feeding of casein (MD-control), PBEH (7 mg total nitrogen/mL) at 0.053 mL (Low-PBEH), 0.159 mL (Medium-PBEH), 0.478 mL (High-PBEH), or 10 mg donepezil (Positive-control) per kilogram body weight per day through a feeding needle for six weeks. The Normal-control rats had casein feeding without SC injection. PBEH dose-dependently protected against memory deficits determined by passive avoidance test, Y-maze, water-maze, and novel object recognition test in SC-induced rats compared to the MD-control. The High-PBEH group had a similar memory function to the Positive-control group. Systemic insulin resistance determined by HOMA-IR was lower in the PBEH groups than in the Normal-control but not the Positive-control. In parallel with systemic insulin resistance, decreased cholesterol and increased glycogen contents in the hippocampus in the Medium-PBEH and High-PBEH represented reduced brain insulin resistance. PBEH intake prevented the increment of serum TNF-α and IL-1ß concentrations in the SC-injected rats. Hippocampal lipid peroxide and TNF-α contents and mRNA TNF-α and IL-1ß expression were dose-dependently reduced in PBEH and Positive-control. PBEH decreased the hippocampal acetylcholinesterase activity compared to the MD-control, but not as much as the Positive-control. PBEH intake increased the α-diversity of the gut microbiota compared to the MD-control, and the gut microbiota community was separated from MD-control. In metagenome function analysis, PBEH increased the energy metabolism-related pathways of the gut microbiota, including citric acid cycle, oxidative phosphorylation, glycolysis, and amino acid metabolism, which were lower in the MD-control than the Normal-control. In conclusion, alleviated memory deficit by PBEH was associated potentially with not only reducing acetylcholinesterase activity but also improving brain insulin resistance and neuroinflammation potentially through modulating gut microbiota. PBEH intake (1.5-4.5 mL of 7 mg total nitrogen/mL for human equivalent) can be a potential therapeutic agent for improving memory impairment.

Chitosan alleviated menopausal symptoms and modulated the gut microbiota in estrogen-deficient rats.

PURPOSE: Menopause disturbs energy, glucose, and lipid metabolisms and changes the composition of the gut microbiota, but dietary fibers without phytoestrogens may ameliorate menopausal metabolic disorders. The objective of the present study was to assess whether consuming the prebiotics chitosan and citrus pectin can improve postmenopausal symptoms, possibly by modulating the gut microbiota in ovariectomized (OVX) rats, and the mechanism of action was examined. METHODS: The OVX rats were given 4.5% cellulose (OVX-Control), chitosan (OVX-Chitosan), or citrus pectin (OVX-Pectin) in a 43% fat diet and the sham rats were given the same diet as the OVX-Control for 12 weeks. Sham-operated rats had the same diet as OVX-Control (Normal-Control). Body-weight, visceral fat mass, tail skin temperature, serum 17ß-estradiol, glucose intolerance, and insulin tolerance were determined. Gut microbiota in the fecal samples was measured by NGS and analyzed with PICRUSt2. Short-chain fatty acids (SCFA) and metabolomic characteristics of serum were also measured with UPLC-mass spectrometry. RESULTS: Chitosan and citrus pectin were selected because the incubation of rat feces with these two prebiotics in vitro had shown increased butyrate production. OVX-Chitosan reduced the weight, visceral fat content, and tail skin temperature, and OVX-Chitosan and OVX-Pectin improved glucose tolerance, compared to the OVX-Control. Both alleviated dyslipidemia, compared to the OVX-Control. OVX-Chitosan and OVX-Pectin elevated serum propionate and butyrate concentrations but only OVX-Chitosan lowered serum acetate concentrations. In PICRUSt2, chitosan upregulated the functional genes of gut microbiota involved in valine, leucine, and isoleucine biosynthesis, whereas the OVX-Control exhibited significantly upregulated lipopolysaccharide biosynthesis. OVX-Pectin exhibited increased α-diversity in the fecal bacteria. Metabolomic analysis revealed higher serum urate concentrations in the OVX-Control group than the other groups, and serum arginine and leucine concentrations were higher in the OVX-Chitosan group (P < 0.05). CONCLUSION: Chitosan and citrus pectin consumptions improved menopausal symptoms by improving the diversity and composition of the gut microbiota, and serum metabolites and SCFA originating from fecal bacteria. Chitosan was more effective for improving menopausal symptoms than citrus pectin.

Ketone production by ketogenic diet and by intermittent fasting has different effects on the gut microbiota and disease progression in an Alzheimer's disease rat model.

The benefits of ketone production regimens remain controversial. Here, we hypothesized that the ketone-producing regimens modulated cognitive impairment, glucose metabolism, and inflammation while altering the gut microbiome. The hypothesis and the mechanism were explored in amyloid-ß infused rats. Rats that received an amyloid-ß(25-35) infusion into the hippocampus had either ketogenic diet (AD-KD), intermittent fasting (AD-IMF), 30 energy percent fat diet (AD-CON), or high carbohydrate (starch) diet (AD-CHO) for 8 weeks. AD-IMF and AD-CHO, but not AD-KD, lowered the hippocampal amyloid-ß deposition compared to the AD-CON despite serum ketone concentrations being elevated in both AD-KD and AD-IMF. AD-IMF and AD-CHO, but not AD-KD, improved memory function in passive avoidance, Y maze, and water maze tests compared to the AD-CON. Hippocampal insulin signaling (pAkt→pGSK-3ß) was potentiated and pTau was attenuated in AD-IMF and AD-CHO much more than AD-CON. AD-IMF and AD-CON had similar glucose tolerance results during OGTT, but AD-KD and AD-IMF exhibited glucose intolerance. AD-KD exacerbated gut dysbiosis by increasing Proteobacteria, and AD-CHO improved it by elevating Bacteriodetes. In conclusion, ketone production itself might not improve memory function, insulin resistance, neuroinflammation or the gut microbiome when induced by ketone-producing remedies. Intermittent fasting and a high carbohydrate diet containing high starch may be beneficial for people with dementia.

The impact of gut microbiome enterotypes on ulcerative colitis: identifying key bacterial species and revealing species co-occurrence networks using machine learning.

Ulcerative colitis (UC) is a chronic inflammatory intestinal disease affecting the colon and rectum, with its pathogenesis attributed to genetic background, environmental factors, and gut microbes. This study aimed to investigate the role of enterotypes in UC by conducting a hierarchical analysis, determining differential bacteria using machine learning, and performing Species Co-occurrence Network (SCN) analysis. Fecal bacterial data were collected from UC patients, and a 16S rRNA metagenomic analysis was performed using the QIIME2 bioinformatics pipeline. Enterotype clustering was conducted at the family level, and deep neural network (DNN) classification models were trained for UC and healthy controls (HC) in each enterotype. Results from eleven 16S rRNA gut microbiome datasets revealed three enterotypes: Bacteroidaceae (ET-B), Lachnospiraceae (ET-L), and Clostridiaceae (ET-C). Ruminococcus (R. gnavus) abundance was significantly higher in UC subjects with ET-B and ET-C than in those with ET-L. R. gnavus also showed a positive correlation with Clostridia in UC SCN for ET-B and ET-C subjects, with a higher correlation in ET-C subjects. Conversely, Odoribacter (O.) splanchnicus and Bacteroides (B.) uniformis exhibited a positive correlation with tryptophan metabolism and AMP-activated protein kinase (AMPK) signaling pathways, while R. gnavus showed a negative correlation. In vitro co-culture experiments with Clostridium (C.) difficile demonstrated that fecal microbiota from ET-B subjects had a higher abundance of C. difficile than ET-L subjects. In conclusion, the ET-B enterotype predisposes individuals to UC, with R. gnavus as a potential risk factor and O. splanchnicus and B. uniformis as protective bacteria, and those with UC may have ultimately become ET-C.

Improvement of Estrogen Deficiency Symptoms by the Intake of Long-Term Fermented Soybeans (Doenjang) Rich in Bacillus Species through Modulating Gut Microbiota in Estrogen-Deficient Rats.

Traditionally made doenjang (TMD) produced by the long-term fermentation of soybeans with salt may improve symptoms of estrogen deficiency. We aimed to evaluate the effects of four TMD types, containing low and high amounts of Bacillus species and biogenic amines (HBHA, HBLA, LBHA, and LBLA), on energy, glucose, and lipid metabolism, by altering the gut microbiota in estrogen-deficient ovariectomized (OVX) rats. Their mechanisms were also examined. The OVX rats were divided into the control, cooked soybean (CSB), HBHA, LBHA, HBLA, and LBLA groups. Sham-operated rats were the normal control group. Serum 17ß-estradiol concentrations were similar among all OVX groups. Tail skin temperatures, which are indicative of hot flashes, were higher in the control than the HBHA and HBLA groups and were similar to the normal control group. Weight gain and visceral fat mass were lower in the TMD and CSB intake groups but not as low as in the normal control group. Lean body mass showed a trend opposite to that of visceral fat in the respective groups. The hepatic triglyceride content decreased with the TMD intake compared to the control and CSB groups. mRNA expressions of the peroxisome proliferator-activated receptor-γ (PPAR-γ) and carnitine palmitoyltransferase-1 in the TMD and CSB groups were as high as in the normal control group, and the PPAR-γ mRNA expression was more elevated in the HBLA group than in the normal control group. The morphology of the intestines improved in the TMD groups compared to the control, and the HBHA and HBLA groups showed an enhanced improvement compared to the CSB group. The HBHA, HBLA, and LBHA groups increased the α-diversity of the cecal microbiota compared to the control. Akkermenia and Lactobacillus were higher in the HBLA and LBLA groups compared to the control. The expression of the estrogen, forkhead box proteins of the class-O subgroup, and insulin-signaling pathways were lower in the control group, and HBHA and HBLA prevented their decrement. In conclusion, long-term treatment with TMD containing high amounts of Bacillus potentially improves estrogen deficiency symptoms more than unfermented soybeans.

Protective Effect of Long-Term Fermented Soybeans with Abundant Bacillus subtilis on Glucose and Bone Metabolism and Memory Function in Ovariectomized Rats: Modulation of the Gut Microbiota.

We investigated the effects of different types of long-term fermented soybeans (traditionally made doenjang; TMD) on glucose and bone metabolism and memory function in ovariectomized (OVX) rats. The rats were categorized into six groups: Control, cooked unfermented soybeans (CSB), and four TMDs based on Bacillus subtilis (B. subtilis) and biogenic amine contents analyzed previously: high B. subtilis (HS) and high biogenic amines (HA; HSHA), low B. subtilis (LS) and HA (LSHA), HS and low biogenic amines (LA; HSLA), and LS and LA (LSLA). The rats in the CSB and TMD groups fed orally had a 4% high-fat diet for 12 weeks. Rats in the Control (OVX rats) and Normal-control (Sham-operated rats) groups did not consume CSB or TMD, although macronutrient contents were the same in all groups. Uterine weight and serum 17ß-estradiol concentrations were much lower in the Control than the Normal-control group, but CSB and TMD intake did not alter them regardless of B. subtilis and biogenic amine contents. HOMA-IR, a measure of insulin resistance, decreased with TMD with high B. subtilis (HSLA and HSHA) compared to the Control group. In OGTT and IPGTT, serum glucose concentrations at each time point were higher in the Control than in the Normal-control, and HSLA and HSHA lowered them. Memory function was preserved with HSHA and HSLA administration. Bone mineral density decline measured by DEXA analysis was prevented in the HSHA and HSLA groups. Bone metabolism changes were associated with decreased osteoclastic activity, parathyroid hormone levels, and osteoclastic activity-related parameters. Micro-CT results demonstrated that TMD, especially HSLA and HSHA, preserved bone structure in OVX rats. TMD also modulated the fecal bacterial community, increasing Lactobacillus, Ligalactobacillus, and Bacillus. In conclusion, through gut microbiota modulation, TMD, particularly with high B. subtilis content, acts as a synbiotic to benefit glucose, bone, and memory function in OVX rats. Further research is needed to make specific recommendations for B. subtilis-rich TMD for menopausal women.

Fecal Bacterial Community and Metagenome Function in Asians with Type 2 Diabetes, According to Enterotypes.

The role of gut microbes has been suggested in type 2 diabetes (T2DM) risk. However, their results remain controversial. We hypothesized that Asians with T2DM had different fecal bacterial compositions, co-abundance networks, and metagenome functions compared to healthy individuals, according to enterotypes. This hypothesis was examined using the combined gut microbiota data from human fecal samples from previous studies. The human fecal bacterial FASTA/Q files from 36 different T2DM studies in Asians were combined (healthy, n = 3378; T2DM, n = 551), and operational taxonomic units (OTUs) and their counts were obtained using qiime2 tools. In the machine learning approaches, fecal bacteria rich in T2DM were found. They were separated into two enterotypes, Lachnospiraceae (ET-L) and Prevotellaceae (ET-P). The Shannon and Chao1 indices, representing α-diversity, were significantly lower in the T2DM group compared to the healthy group in ET-L (p < 0.05) but not in ET-P. In the Shapley additive explanations analysis of ET-L, Escherichia fergusonii, Collinsella aerofaciens, Streptococcus vestibularis, and Bifidobacterium longum were higher (p < 0.001), while Phocaeicola vulgatus, Bacteroides uniformis, and Faecalibacterium prausnitzii were lower in the T2DM group than in the healthy group (p < 0.00005). In ET-P, Escherichia fergusonii, Megasphaera elsdenii, and Oscillibacter valericigenes were higher, and Bacteroides koreensis and Faecalibacterium prausnitzii were lower in the T2DM group than in the healthy group. In ET-L and ET-P, bacteria in the healthy and T2DM groups positively interacted with each other within each group (p < 0.0001) but negatively interacted between the T2DM and healthy groups in the network analysis (p < 0.0001). In the metagenome functions of the fecal bacteria, the gluconeogenesis, glycolysis, and amino acid metabolism pathways were higher, whereas insulin signaling and adenosine 5' monophosphate-activated protein kinase (AMPK) signaling pathways were lower in the T2DM group than in the healthy group for both enterotypes (p < 0.00005). In conclusion, Asians with T2DM exhibited gut dysbiosis, potentially linked to intestinal permeability and the enteric vagus nervous system.

Development and Validation of an Insulin Resistance Predicting Model Using a Machine-Learning Approach in a Population-Based Cohort in Korea.

BACKGROUND: Insulin resistance is a common etiology of metabolic syndrome, but receiver operating characteristic (ROC) curve analysis shows a weak association in Koreans. Using a machine learning (ML) approach, we aimed to generate the best model for predicting insulin resistance in Korean adults aged > 40 of the Ansan/Ansung cohort using a machine learning (ML) approach. METHODS: The demographic, anthropometric, biochemical, genetic, nutrient, and lifestyle variables of 8842 participants were included. The polygenetic risk scores (PRS) generated by a genome-wide association study were added to represent the genetic impact of insulin resistance. They were divided randomly into the training (n = 7037) and test (n = 1769) sets. Potentially important features were selected in the highest area under the curve (AUC) of the ROC curve from 99 features using seven different ML algorithms. The AUC target was ≥0.85 for the best prediction of insulin resistance with the lowest number of features. RESULTS: The cutoff of insulin resistance defined with HOMA-IR was 2.31 using logistic regression before conducting ML. XGBoost and logistic regression algorithms generated the highest AUC (0.86) of the prediction models using 99 features, while the random forest algorithm generated a model with 0.82 AUC. These models showed high accuracy and k-fold values (>0.85). The prediction model containing 15 features had the highest AUC of the ROC curve in XGBoost and random forest algorithms. PRS was one of 15 features. The final prediction models for insulin resistance were generated with the same nine features in the XGBoost (AUC = 0.86), random forest (AUC = 0.84), and artificial neural network (AUC = 0.86) algorithms. The model included the fasting serum glucose, ALT, total bilirubin, HDL concentrations, waist circumference, body fat, pulse, season to enroll in the study, and gender. CONCLUSION: The liver function, regular pulse checking, and seasonal variation in addition to metabolic syndrome components should be considered to predict insulin resistance in Koreans aged over 40 years.

Mitigation of Memory Impairment with Fermented Fucoidan and λ-Carrageenan Supplementation through Modulating the Gut Microbiota and Their Metagenome Function in Hippocampal Amyloid-ß Infused Rats.

Attenuating acetylcholinesterase and insulin/insulin-like growth factor-1 signaling in the hippocampus is associated with Alzheimer's disease (AD) development. Fucoidan and carrageenan are brown and red algae, respectively, with potent antibacterial, anti-inflammatory, antioxidant and antiviral activities. This study examined how low-molecular-weight (MW) and high-MW fucoidan and λ-carrageenan would improve memory impairment in Alzheimer's disease-induced rats caused by an infusion of toxic amyloid-ß(Aß). Fucoidan and λ-carrageenan were dissected into low-MW by Luteolibacter algae and Pseudoalteromonas carrageenovora. Rats receiving an Aß(25-35) infusion in the CA1 region of the hippocampus were fed dextrin (AD-Con), 1% high-MW fucoidan (AD-F-H), 1% low-MW fucoidan (AD-F-L), 1% high-MW λ-carrageenan (AD-C-H), and 1% low-MW λ-carrageenan (AD-C-L) for six weeks. Rats to receive saline infusion (Normal-Con) had an AD-Con diet. The AD-F-L group showed an improved memory function, which manifested as an enhanced Y-maze spontaneous alternation test, water maze, and passive avoidance tests, similar to the Normal-Con group. AD-F-L also potentiated hippocampal insulin signaling and increased the expression of ciliary neurotrophic factor (CNTF) and brain-derived neurotrophic factor (BDNF) in the hippocampus. AD-C-L improved the memory function mainly by increasing the BDNF content. AD-F-H and AD-C-H did not improve the memory function. Compared to AD-Con, the ascending order of AD-C-H, AD-F-H, AD-C-L, and AD-F-L increased insulin signaling by enhancing the pSTAT3®pAkt®pGSK-3ß pathway. AD-F-L improved glucose tolerance the most. Compared to AD-CON, the AD-F-L treatment increased the serum acetate concentrations and compensated for the defect of cerebral glucose metabolism. AD-Con increased Clostridium, Terrisporobacter and Sporofaciens compared to Normal-Con, and AD-F-L and AD-C-L increased Akkermentia. In conclusion, AD-F-L and AD-C-L alleviated the memory function in the rats with induced AD symptoms by modulating.

Beneficial Effects of a Low-Glycemic Diet on Serum Metabolites and Gut Microbiota in Obese Women With Prevotella and Bacteriodes Enterotypes: A Randomized Clinical Trial.

Generalized healthy eating patterns may not benefit everyone due to different genetics and enterotypes. We aimed to compare the effects of a low-glycemic diet representing the Korean traditional balanced diet (Low-GID) and westernized diet as a control diet (CD) on anthropometry, serum metabolites, and fecal bacteria in a randomized clinical trial according to enterotypes. We recruited 52 obese women aged 30-50 years, and they consumed Low-GID and CD meals for 1 month, with a 1-month washout period, in a crossover randomized clinical trial. The Low-GID was mainly composed of whole grains with fish, vegetables, seaweeds, and perilla oil, whereas CD contained refined rice, bread, noodles, meats, and processed foods. Serum lipid profiles, metabolomics, serum short-chain fatty acids, and fecal bacteria were analyzed. The important variables influenced by Low-GID and CD were determined by SHAP value in the XGBoost algorithm according to Bacteroides (ET-B) and Prevotella (ET-P). Low-GID and CD interventions did not change the enterotypes, but they modified serum metabolites and some fecal bacterial species differently according to enterotypes. The 10-fold cross-validation of the XGBoost classifier in the ET-P and ET-B clusters was 0.91 ± 0.04 and 0.8 ± 0.07, respectively. In the ET-P cluster, serum L-homocysteine, glutamate, leucine concentrations, and muscle mass were higher in the CD group than in the Low-GID group, whereas serum 3-hydroxybutyric acid concentration was significantly higher in the Low-GID group than in the CD group (p < 0.05). In fecal bacteria, Gemmiger formicilis, Collinsella aerofaciens, and Escherichia coli were higher in the CD group than in the Low-GID group. In the ET-B cohort, serum tryptophan and total cholesterol concentrations were higher in the CD group than in the Low-GID group, whereas serum glutathione and 3-hydroxybutyric acid concentrations were significantly higher in the Low-GID group than in the CD group (p < 0.05). However, Bifidobacterium longum was higher in CD than Low-GID in the ET-B cluster, but serum butyric acid levels were higher in the Low-GID than in the CD group. In conclusion, Low-GID can be recommended in obese women with both ET-P and ET-B enterotypes, although its efficacy was more effective in ET-P. Clinical Trial Registration: [https://cris.nih.go.kr/cris/search/detailSearch.do/17398], identifier [KCT0005340].

Alleviation of Metabolic Disturbance by Substituting Kanjang High in Bacillus for Salt through Modulation of Gut Microbiota in Estrogen-Deficient Rats.

A high salt intake may exacerbate menopausal symptoms and substituting for different types of traditionally made kanjang (TMK; soy sauce) may prevent it. This study examined whether substituting salt with lyophilized TMK containing low and high Bacillus and biogenic amines in a high-fat diet might modulate the menopausal symptoms and the energy, glucose, and lipid metabolism in ovariectomized (OVX) rats. They were categorized into salt (Control), TMK with high Bacillus and low biogenic amines (HBLB), TMK with high Bacillus and high biogenic amines (HBHB), TMK with low Bacillus and low biogenic amines (LBLB), and TMK with low Bacillus and high biogenic amines (LBHB). Sham-operated rats consumed the same diet as the Control. HBLB, HBHB, and LBHB prevented increased tail skin temperature compared to the Control. HBHB and HBLB partially inhibited the increased weight gain and abdominal fat mass by reducing the food efficiency without changing the serum 17ß-estradiol concentrations. Serum glucose and insulin concentrations and the insulin resistance index by the homeostatic model assessment for insulin resistance showed a positive association for weight gain. HBLB and HBHB decreased the serum malondialdehyde and tumor-necrosis factor-α levels. Hepatic triglyceride storage was lower in all TMK groups than in the Control, while hepatic glycogen accumulation was higher in the HBLB, HBHB, and LBHB groups than in the Control and LBLB groups. Accordingly, the mRNA expression of peroxisome proliferator-activated receptors-γ(PPAR-γ) was higher in the HBLB and HBHB groups compared to the Control, and that of fatty acid synthase was opposite to PPAR-γ expression. However, HBLB and HBHB improved dyslipidemia and insulin resistance compared to the Control, but their improvement did not reach that of the Normal-control. The acetic acid concentrations in the portal vein were lower in the LBLB than in the Control, while the butyric acid contents were higher in the LBHB and HBLB groups than in the Control. HBHB, HBLB, and LBHB elevated Akkermansia and Lactobacillus, and HBLB and LBLB increased Bacteroides and Ruminococcus compared to the Control. Polycyclic aromatic hydrocarbon degradation, bile acid synthesis, and unsaturated fatty acid biosynthesis were significantly higher in the HBLB group than in the Control group. In conclusion, substituting salts to TMK with a high Bacillus content regardless of the bioamine contents partially improved the menopausal symptoms and metabolic disturbance in estrogen-deficient animals.

Alleviation of Cognitive and Physical Fatigue with Enzymatic Porcine Placenta Hydrolysate Intake through Reducing Oxidative Stress and Inflammation in Intensely Exercised Rats.

Intense exercise is reported to induce physical and cognitive fatigue, but few studies have focused on treatments to alleviate fatigue. We hypothesized that the oral supplementation of enzymatic porcine placenta hydrolysate (EPPH) prepared using protease enzymes could alleviate exercise-induced fatigue in an animal model. The objectives of the study were to examine the hypothesis and the action mechanism of EPPH in relieving physical and cognitive fatigue. Fifty male Sprague−Dawley rats aged 8 weeks (body weight: 201 g) were classified into five groups, and rats in each group were given oral distilled water, EPPH (5 mg nitrogen/mL) at doses of 0.08, 0.16, or 0.31 mL/kg body weight (BW)/day, or glutathione (100 mg/kg BW/day) by a feeding needle for 5 weeks, which were named as the control, L-EPPH, M-EPPH, H-EPPH, or positive-control groups, respectively. Ten additional rats had no intense exercise with water administration and were designated as the no-exercise group. After 2 weeks, the rats were subjected to intense exercise and forced swimming trial for 30 min once per week for an additional 4 weeks. At 5 min after the intense exercise, lactate concentrations and lactate dehydrogenase (LDH) activity in the serum and the gastrocnemius muscle were higher in the control group, whereas M-EPPH and H-EPPH treatments suppressed the increase better than in the positive-control (p < 0.05). Intense exercise decreased glycogen content in the liver and gastrocnemius muscle, and M-EPPH and H-EPPH inhibited the decrement (p < 0.05). Moreover, lipid peroxide contents in the gastrocnemius muscle and liver were higher in the control group than in the M-EPPH, H-EPPH, positive-control, and no-exercise groups (p < 0.05). However, antioxidant enzyme activities such as superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) were opposite to the lipid peroxide contents. Hypothalamic corticosterone and hippocampal mRNA expressions of tumor necrosis factor (TNF)-α and IL-1ß were higher. However, hippocampal brain-derived neurotrophic factor (BDNF) mRNA expression and protein contents were lower in the control group than in the positive-control group. M-EPPH, H-EPPH, and positive-control suppressed the changes via activating hippocampal cAMP response element-binding protein phosphorylation, and H-EPPH showed better activity than in the positive-control (p < 0.05). In conclusion, EPPH (0.16−0.31 mL/kg BW) intake reduced exercise-induced physical and cognitive fatigue in rats and could potentially be developed as a therapeutic agent for relieving fatigue in humans.

An Inverse Relation between Hyperglycemia and Skeletal Muscle Mass Predicted by Using a Machine Learning Approach in Middle-Aged and Older Adults in Large Cohorts.

BACKGROUND: Skeletal muscle mass (SMM) and fat mass (FM) are essentially required for health and quality of life in older adults. OBJECTIVE: To generate the best SMM and FM prediction models using machine learning models incorporating socioeconomic, lifestyle, and biochemical parameters and the urban hospital-based Ansan/Ansung cohort, and to determine relations between SMM and FM and metabolic syndrome and its components in this cohort. METHODS: SMM and FM data measured using an Inbody 4.0 unit in 90% of Ansan/Ansung cohort participants were used to train seven machine learning algorithms. The ten most essential predictors from 1411 variables were selected by: (1) Manually filtering out 48 variables, (2) generating best models by random grid mode in a training set, and (3) comparing the accuracy of the models in a test set. The seven trained models' accuracy was evaluated using mean-square errors (MSE), mean absolute errors (MAE), and R² values in 10% of the test set. SMM and FM of the 31,025 participants in the Ansan/Ansung cohort were predicted using the best prediction models (XGBoost for SMM and artificial neural network for FM). Metabolic syndrome and its components were compared between four groups categorized by 50 percentiles of predicted SMM and FM values in the cohort. RESULTS: The best prediction models for SMM and FM were constructed using XGBoost (R2 = 0.82) and artificial neural network (ANN; R2 = 0.89) algorithms, respectively; both models had a low MSE. Serum platelet concentrations and GFR were identified as new biomarkers of SMM, and serum platelet and bilirubin concentrations were found to predict FM. Predicted SMM and FM values were significantly and positively correlated with grip strength (r = 0.726) and BMI (r = 0.915, p < 0.05), respectively. Grip strengths in the high-SMM groups of both genders were significantly higher than in low-SMM groups (p < 0.05), and blood glucose and hemoglobin A1c in high-FM groups were higher than in low-FM groups for both genders (p < 0.05). CONCLUSION: The models generated by XGBoost and ANN algorithms exhibited good accuracy for estimating SMM and FM, respectively. The prediction models take into account the actual clinical use since they included a small number of required features, and the features can be obtained in outpatients. SMM and FM predicted using the two models well represented the risk of low SMM and high fat in a clinical setting.