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Yang W, Wu Y, Chen Y, Chen S, Gao X, Wu S, Sun L. Different levels of physical activity and risk of developing type 2 diabetes among adults with prediabetes: a population-based cohort study. Nutr J 2024; 23:107. [PMID: 39289701 PMCID: PMC11406853 DOI: 10.1186/s12937-024-01013-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2024] [Accepted: 09/10/2024] [Indexed: 09/19/2024] Open
Abstract
OBJECTIVES This study aimed to evaluate the association between different levels of physical activity and risk of developing type 2 diabetes (T2D) mellitus among adults with prediabetes in Chinese population. METHODS This prospective population-based cohort study included 12,424 participants (mean [SD] age, 52.8 [16.8] years; 82.2% men) with prediabetes at 2014 survey of the Kailuan study. Physical activity information was collected through the International Physical Activity Questionnaire-Short Form and categorized by metabolic equivalent (MET) of task as low, moderate, and high. Cox regression models were built to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between physical activity levels and incident T2D. RESULTS During a median follow-up of 3.6 years, 2,207 (17.8%) participants developed T2D. The incident rate of T2D were 55.83/1000, 35.14/1000, and 39.61/1000 person-years in the low, moderate, and high physical activity level group, respectively. Both moderate (HR 0.57, 95% CI 0.49 to 0.67) and high (HR 0.76, 95% CI 0.66 to 0.89) physical activity levels were associated with lower risks of developing T2D compared to low physical activity level (P for trend < 0.001). The association between high physical activity level and T2D was primarily observed in participants without metabolic syndrome (P for interaction < 0.001). Moreover, participants with moderate or high levels of physical activity had significantly decreased fasting blood glucose levels during follow-up when compared to those with low level (P group*time < 0.001). CONCLUSION This study suggested that individuals with prediabetes might benefit from moderate and high levels of physical activity.
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Affiliation(s)
- Wenchang Yang
- Department of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Clinical Research Unit, Institute of Clinical Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yuntao Wu
- Department of Cardiology, Kailuan General Hospital, 57 Xinhua East Rd, Tangshan, 063000, Hebei Province, China
| | - Yue Chen
- Department of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Clinical Research Unit, Institute of Clinical Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Shuohua Chen
- Department of Cardiology, Kailuan General Hospital, 57 Xinhua East Rd, Tangshan, 063000, Hebei Province, China
| | - Xiang Gao
- Department of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Clinical Research Unit, Institute of Clinical Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Shouling Wu
- Department of Cardiology, Kailuan General Hospital, 57 Xinhua East Rd, Tangshan, 063000, Hebei Province, China.
| | - Liang Sun
- Department of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Clinical Research Unit, Institute of Clinical Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
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2
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Shi Y, Kan J, Wang W, Cao Y, Wu Y, Chen X, Zheng W, Yang F, Du J, He W, Zhu S. Nut consumption, gut microbiota, and body fat distribution: results of a large, community-based population study. Obesity (Silver Spring) 2024; 32:1778-1788. [PMID: 39041418 DOI: 10.1002/oby.24099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 05/25/2024] [Accepted: 05/27/2024] [Indexed: 07/24/2024]
Abstract
OBJECTIVE We aimed to investigate the relationships among nut consumption, gut microbiota, and body fat distribution. METHODS We studied 2255 Chinese adults in the Lanxi Cohort living in urban areas in Lanxi City, China. Fat distribution was assessed by dual-energy x-ray absorptiometry, and nut consumption was assessed using food frequency questionnaires. 16S ribosomal RNA (rRNA) sequencing was performed on stool samples from 1724 participants. Linear regression and Spearman correlation were used in all analyses. A validation study was performed using 1274 participants in the Lanxi Cohort living in rural areas. RESULTS Nut consumption was beneficially associated with regional fat accumulation. Gut microbial analysis suggested that a high intake of nuts was associated with greater microbial α diversity. Six genera were found to be associated with nut consumption, and the abundance of genera Anaerobutyricum, Anaerotaenia, and Fusobacterium was significantly associated with fat distribution. Favorable relationships between α diversity and fat distribution were also observed. Similar relationships between gut microbiota and fat distribution were obtained in the validation analysis. CONCLUSIONS We have shown that nut consumption is beneficially associated with body fat distribution and gut microbiota diversity and taxonomy. Furthermore, the microbial features related to high nut intake are associated with a favorable pattern of fat distribution.
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Affiliation(s)
- Yuwei Shi
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, Zhejiang, China
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Zhejiang, China
| | - Juntao Kan
- Nutrilite Health Institute, Shanghai, China
| | - Wenjie Wang
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, Zhejiang, China
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Zhejiang, China
| | - Yiyang Cao
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, Zhejiang, China
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Zhejiang, China
| | - Yimian Wu
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, Zhejiang, China
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Zhejiang, China
| | - Xinyu Chen
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, Zhejiang, China
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Zhejiang, China
| | - Weifang Zheng
- Lanxi Hospital of Traditional Chinese Medicine, Zhejiang, China
| | - Fei Yang
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, Zhejiang, China
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Zhejiang, China
| | - Jun Du
- Nutrilite Health Institute, Shanghai, China
| | - Wei He
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, Zhejiang, China
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Zhejiang, China
| | - Shankuan Zhu
- Chronic Disease Research Institute, The Children's Hospital, and National Clinical Research Center for Child Health, School of Public Health, School of Medicine, Zhejiang University, Zhejiang, China
- Department of Nutrition and Food Hygiene, School of Public Health, Zhejiang University, Zhejiang, China
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3
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Maukonen M, Koponen KK, Havulinna AS, Kaartinen NE, Niiranen T, Méric G, Pajari AM, Knight R, Salomaa V, Männistö S. Associations of plant-based foods, red and processed meat, and dairy with gut microbiome in Finnish adults. Eur J Nutr 2024; 63:2247-2260. [PMID: 38753173 PMCID: PMC11377619 DOI: 10.1007/s00394-024-03406-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 04/16/2024] [Indexed: 09/06/2024]
Abstract
PURPOSE Population-based studies on the associations of plant-based foods, red meat or dairy with gut microbiome are scarce. We examined whether the consumption of plant-based foods (vegetables, potatoes, fruits, cereals), red and processed meat (RPM) or dairy (fermented milk, cheese, other dairy products) are related to gut microbiome in Finnish adults. METHODS We utilized data from the National FINRISK/FINDIET 2002 Study (n = 1273, aged 25-64 years, 55% women). Diet was assessed with 48-hour dietary recalls. Gut microbiome was analyzed using shallow shotgun sequencing. We applied multivariate analyses with linear models and permutational ANOVAs adjusted for relevant confounders. RESULTS Fruit consumption was positively (beta = 0.03, SE = 0.01, P = 0.04), while a dairy subgroup including milk, cream and ice-creams was inversely associated (beta=-0.03, SE 0.01, P = 0.02) with intra-individual gut microbiome diversity (alpha-diversity). Plant-based foods (R2 = 0.001, P = 0.03) and dairy (R2 = 0.002, P = 0.01) but not RPM (R2 = 0.001, P = 0.38) contributed to the compositional differences in gut microbiome (beta-diversity). Plant-based foods were associated with several butyrate producers/cellulolytic species including Roseburia hominis. RPM associations included an inverse association with R. hominis. Dairy was positively associated with several lactic producing/probiotic species including Lactobacillus delbrueckii and potentially opportunistic pathogens including Citrobacter freundii. Dairy, fermented milk, vegetables, and cereals were associated with specific microbial functions. CONCLUSION Our results suggest a potential association between plant-based foods and dairy or their subgroups with microbial diversity measures. Furthermore, our findings indicated that all the food groups were associated with distinct overall microbial community compositions. Plant-based food consumption particularly was associated with a larger number of putative beneficial species.
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Affiliation(s)
- Mirkka Maukonen
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland.
| | - Kari K Koponen
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Aki S Havulinna
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
- Institute for Molecular Medicine Finland, FIMM-HiLIFE, Helsinki, Finland
| | | | - Teemu Niiranen
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Guillaume Méric
- Baker Heart and Diabetes Institute, Melbourne, Australia
- University of Melbourne, Melbourne, Australia
- Monash University, Melbourne, Australia
- La Trobe University, Melbourne, Australia
| | | | - Rob Knight
- University of California San Diego, La Jolla, CA, USA
| | - Veikko Salomaa
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
| | - Satu Männistö
- Finnish Institute for Health and Welfare (THL), Helsinki, Finland
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Faienza MF, Cognetti E, Farella I, Antonioli A, Tini S, Antoniotti V, Prodam F. Dietary fructose: from uric acid to a metabolic switch in pediatric metabolic dysfunction-associated steatotic liver disease. Crit Rev Food Sci Nutr 2024:1-16. [PMID: 39157959 DOI: 10.1080/10408398.2024.2392150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/20/2024]
Abstract
Fructose consumption in pediatric subjects is rising, as the prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH). Despite increasing evidence supporting the detrimental effects of fructose in the development of Metabolic Syndrome (MetS) and its related comorbidities, the association between fructose intake and liver disease remains unclear, mainly in youths. The current narrative review aims to illustrate the correlation between fructose metabolism and liver functions besides its impact on obesity and MASLD in pediatrics. Fructose metabolism is involved in the liver through the classical lipogenic pathway via de novo lipogenesis (DNL) or in the alternative pathway via uric acid accumulation. Hyperuricemia is one of the main features of MALSD patients, underlining how uric acid is growing interest as a new marker of disease. Observational and interventional studies conducted in children and adolescents, who consumed large amounts of fructose and glucose in their diet, were included. Most of these studies emphasized the association between high fructose intake and weight gain, dyslipidemia, insulin resistance, and MASLD/MASH, even in normal-weight children. Conversely, reducing fructose intake ameliorates liver fat accumulation, lipid profile, and weight. In conclusion, fructose seems a potent inducer of both insulin resistance and hepatic fat accumulation.
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Affiliation(s)
- Maria Felicia Faienza
- Pediatric Unit, Department of Precision and Regenerative Medicine and Ionian Area, University of Bari "Aldo Moro", Bari, Italy
| | - Eleonora Cognetti
- Pediatric Unit, Department of Precision and Regenerative Medicine and Ionian Area, University of Bari "Aldo Moro", Bari, Italy
| | - Ilaria Farella
- Department of Precision and Regenerative Medicine and Ionian Area, Clinica Medica "A. Murri", University of Bari "Aldo Moro", Bari, Italy
| | | | - Sabrina Tini
- Department of Health Science, University of Piemonte Orientale, Novara, Italy
| | | | - Flavia Prodam
- Department of Health Science, University of Piemonte Orientale, Novara, Italy
- Unit of Endocrinology, Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy
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5
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Guan J, Liu T, Yang K, Chen H. Dried fruit intake and lower risk of type 2 diabetes: a two-sample mendelian randomization study. Nutr Metab (Lond) 2024; 21:46. [PMID: 38987806 PMCID: PMC11234600 DOI: 10.1186/s12986-024-00813-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2024] [Accepted: 06/18/2024] [Indexed: 07/12/2024] Open
Abstract
BACKGROUND Previous studies have shown controversy about whether dried fruit intake is associated with type 2 diabetes. This study aimed to examine the potential causal effect of dried fruit intake on type 2 diabetes by conducting a two-sample Mendelian randomization study. METHODS We used genome-wide association study (GWAS) summary statistics for MR analysis to explore the causal association of dried fruit intake with T2D. The inverse-variance weighted (IVW) method was used as the main analytical method for MR analysis. In addition, the MR-Egger method and the weighted median method were applied to supplement the IVW method. Furthermore, Cochrane's Q test, MR-Egger intercept test, and leave-one-out analysis were used to perform sensitivity analysis. The funnel plot was used to assess publication bias. RESULTS The results from the IVW analysis indicated that dried fruit intake could reduce the risk of T2D [odds ratio (OR) = 0.392, 95% confidence interval (CI): 0.241-0.636, p-value = 0.0001]. In addition, the result of additional method Weighted median is parallel to the effects estimated by IVW. Furthermore, the sensitivity analysis illustrates that our MR analysis was unaffected by heterogeneity and horizontal pleiotropy. Finally, the results of the leave-one-out method showed the robustness of our MR results. And the funnel plot shows a symmetrical distribution. CONCLUSION Our study provides evidence for the benefits of dried fruit intake on T2D. Therefore, a reasonable consumption of dried fruit may provide primary prevention.
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Affiliation(s)
- Jianbin Guan
- Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shannxi, 710054, China
| | - Tao Liu
- Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shannxi, 710054, China
| | - Kaitan Yang
- Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shannxi, 710054, China.
- Truma Rehabilitation Department, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shannxi, 710054, China.
| | - Hao Chen
- Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shannxi, 710054, China.
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6
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Ma X, Li P, Liu Y, Liu L, Xu J, Wang X, Zhou S, Ren X, Wang Y, Yuan L. Suboptimal diet quality is associated with the incidence of type 2 diabetes mellitus in middle-aged and older populations in China: evidence from a population-based cross-sectional study. Nutr Res 2024; 127:123-132. [PMID: 38943730 DOI: 10.1016/j.nutres.2024.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 05/29/2024] [Accepted: 05/30/2024] [Indexed: 07/01/2024]
Abstract
The association between dietary quality and type 2 diabetes mellitus (T2DM) based on the Chinese Dietary Balance Index (DBI-16) is seldom reported. We hypothesized that poor dietary quality might increase the risk of T2DM in the middle-aged and older populations. A total of 1816 individuals (≥50 years) were included in the study. Demographic characteristics and dietary intake data were collected. Logistic regression and restricted cubic spline (RCS) analyses were conducted to explore the association between DBI-16 indexes and the risk of T2DM. The insufficient intake of vegetables and dairy might decrease the risk of T2DM (ORVegetable = 0.77, 95% CI = 0.60-0.97; ORDairy = 0.58, 95% CI = 0.35-0.96), but the individuals with insufficient intake of fruit were more likely to have a higher risk of T2DM (ORfruit = 2.26, 95% CI = 1.69-3.06). Compared with the subjects with the lowest quartile of Low Bound Score (LBS) or Diet Quality Distance (DQD), the individuals with Q2 and Q3 level of LBS (ORQ2 = 1.40, 95% CI = 1.03-1.90, P = .033; ORQ3 = 1.52, 95% CI = 1.11-2.08, P < .01) or DQD (ORQ2 = 1.45, 95% CI = 1.06-1.99, P = .021; ORQ3 = 1.64, 95% CI = 1.20-2.24, P < .01) showed increased risk of T2DM with a nonlinear association observed by RCS analysis. We concluded that imbalanced dietary intake, especially insufficient daily fruit intake, might predict an increased risk of T2DM in the middle-aged and elderly Chinese.
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Affiliation(s)
- Xiaojun Ma
- School of Public Health, Capital Medical Universiyt, Beijing China; China-British Joint Laboratory of Nutrition Prevention and Control of Chronic Diseases
| | - Pengfei Li
- School of Public Health, Capital Medical Universiyt, Beijing China; China-British Joint Laboratory of Nutrition Prevention and Control of Chronic Diseases
| | - Yu Liu
- School of Public Health, Capital Medical Universiyt, Beijing China; China-British Joint Laboratory of Nutrition Prevention and Control of Chronic Diseases
| | - Lu Liu
- School of Public Health, Capital Medical Universiyt, Beijing China; China-British Joint Laboratory of Nutrition Prevention and Control of Chronic Diseases
| | - Jingjing Xu
- School of Public Health, Capital Medical Universiyt, Beijing China; China-British Joint Laboratory of Nutrition Prevention and Control of Chronic Diseases
| | - Xixiang Wang
- School of Public Health, Capital Medical Universiyt, Beijing China; China-British Joint Laboratory of Nutrition Prevention and Control of Chronic Diseases
| | - Shaobo Zhou
- School of Science, Faculty of Engineering and Science, University of Greenwich, Chatham, UK
| | - Xiuwen Ren
- School of Public Health, Capital Medical Universiyt, Beijing China; China-British Joint Laboratory of Nutrition Prevention and Control of Chronic Diseases
| | - Ying Wang
- Suzhou Research Center of Medical School, Suzhou Hospital, Affiliated Hospital of Medical School, Nanjing University, Suzhou, China
| | - Linhong Yuan
- School of Public Health, Capital Medical Universiyt, Beijing China; China-British Joint Laboratory of Nutrition Prevention and Control of Chronic Diseases.
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Li X, Yang J, Zhou X, Dai C, Kong M, Xie L, Liu C, Liu Y, Li D, Ma X, Dai Y, Sun Y, Jian Z, Guo X, Lin X, Li Y, Sun L, Liu X, Jin L, Tang H, Zheng Y, Hong S. Ketogenic diet-induced bile acids protect against obesity through reduced calorie absorption. Nat Metab 2024; 6:1397-1414. [PMID: 38937659 DOI: 10.1038/s42255-024-01072-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Accepted: 05/24/2024] [Indexed: 06/29/2024]
Abstract
The low-carbohydrate ketogenic diet (KD) has long been practiced for weight loss, but the underlying mechanisms remain elusive. Gut microbiota and metabolites have been suggested to mediate the metabolic changes caused by KD consumption, although the particular gut microbes or metabolites involved are unclear. Here, we show that KD consumption enhances serum levels of taurodeoxycholic acid (TDCA) and tauroursodeoxycholic acid (TUDCA) in mice to decrease body weight and fasting glucose levels. Mechanistically, KD feeding decreases the abundance of a bile salt hydrolase (BSH)-coding gut bacterium, Lactobacillus murinus ASF361. The reduction of L. murinus ASF361 or inhibition of BSH activity increases the circulating levels of TDCA and TUDCA, thereby reducing energy absorption by inhibiting intestinal carbonic anhydrase 1 expression, which leads to weight loss. TDCA and TUDCA treatments have been found to protect against obesity and its complications in multiple mouse models. Additionally, the associations among the abovementioned bile acids, microbial BSH and metabolic traits were consistently observed both in an observational study of healthy human participants (n = 416) and in a low-carbohydrate KD interventional study of participants who were either overweight or with obesity (n = 25). In summary, we uncover a unique host-gut microbiota metabolic interaction mechanism for KD consumption to decrease body weight and fasting glucose levels. Our findings support TDCA and TUDCA as two promising drug candidates for obesity and its complications in addition to a KD.
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Affiliation(s)
- Xiao Li
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China
| | - Jie Yang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China
| | - Xiaofeng Zhou
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China
| | - Chen Dai
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China
| | - Mengmeng Kong
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China
| | - Linshan Xie
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China
| | - Chenglin Liu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China
- Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Precision Cancer Medicine Center, Fudan University Shanghai Cancer Center, Shanghai, P.R. China
| | - Yilian Liu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China
| | - Dandan Li
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China
| | - Xiaonan Ma
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China
| | - Yuxiang Dai
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Disease, Shanghai, P.R. China
| | - Yan Sun
- Masonic Medical Research Institute, Utica, NY, USA
| | - Zhijie Jian
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, P.R. China
| | - Xiaohuan Guo
- Institute for Immunology, Tsinghua University, Beijing, P.R. China
| | - Xu Lin
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, P.R. China
- Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou, P.R. China
| | - Yixue Li
- Bio-Med Big Data Center, Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, P.R. China
- Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, P.R. China
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Liang Sun
- Department of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Fudan University, Shanghai, P.R. China
| | - Xin Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Global Health Institute, Xi'an Jiaotong University Health Science Center, Xi'an, P.R. China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China
| | - Huiru Tang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China
| | - Yan Zheng
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China.
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Disease, Shanghai, P.R. China.
- Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Institute of Nutrition, Fudan University, Shanghai, P.R. China.
| | - Shangyu Hong
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Fudan University, Shanghai, P.R. China.
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Sprague KL, Rajakaruna S, Bandow B, Burchat N, Bottomley M, Sampath H, Paliy O. Gut Microbiota Fermentation of Digested Almond-Psyllium-Flax Seed-Based Artisan Bread Promotes Mediterranean Diet-Resembling Microbial Community. Microorganisms 2024; 12:1189. [PMID: 38930571 PMCID: PMC11205402 DOI: 10.3390/microorganisms12061189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Revised: 06/06/2024] [Accepted: 06/07/2024] [Indexed: 06/28/2024] Open
Abstract
Different modifications of the standard bread recipe have been proposed to improve its nutritional and health benefits. Here, we utilized the in vitro Human Gut Simulator (HGS) to assess the fermentation of one such artisan bread by human gut microbiota. Dried and milled bread, composed of almond flour, psyllium husks, and flax seeds as its three main ingredients, was first subjected to an in vitro protocol designed to mimic human oro-gastro-intestinal digestion. The bread digest was then supplied to complex human gut microbial communities, replacing the typical Western diet-based medium (WM) of the GHS system. Switching the medium from WM to bread digest resulted in statistically significant alterations in the community structure, encoded functions, produced short-chain fatty acids, and available antioxidants. The abundances of dietary fiber degraders Enterocloster, Mitsuokella, and Prevotella increased; levels of Gemmiger, Faecalibacterium, and Blautia decreased. These community alterations resembled the previously revealed differences in the distal gut microbiota of healthy human subjects consuming typical Mediterranean vs. Western-pattern diets. Therefore, the consumption of bread high in dietary fiber and unsaturated fatty acids might recapitulate the beneficial effects of the Mediterranean diet on the gut microbiota.
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Affiliation(s)
- Kourtney L. Sprague
- Department of Biochemistry and Molecular Biology, Boonshoft School of Medicine, Wright State University, Dayton, OH 45435, USA
| | - Sumudu Rajakaruna
- Department of Biochemistry and Molecular Biology, Boonshoft School of Medicine, Wright State University, Dayton, OH 45435, USA
| | - Brant Bandow
- Department of Biochemistry and Molecular Biology, Boonshoft School of Medicine, Wright State University, Dayton, OH 45435, USA
| | - Natalie Burchat
- New Jersey Institute for Food, Nutrition, and Health, Rutgers University, New Brunswick, NJ 08901, USA
| | - Michael Bottomley
- Statistical Consulting Center, Wright State University, Dayton, OH 45435, USA
| | - Harini Sampath
- New Jersey Institute for Food, Nutrition, and Health, Rutgers University, New Brunswick, NJ 08901, USA
- Department of Nutritional Sciences, Rutgers University, New Brunswick, NJ 08901, USA
| | - Oleg Paliy
- Department of Biochemistry and Molecular Biology, Boonshoft School of Medicine, Wright State University, Dayton, OH 45435, USA
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9
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Ling CW, Zhong H, Zeng FF, Chen G, Fu Y, Wang C, Zhang ZQ, Cao WT, Sun TY, Ding D, Liu YH, Dong HL, Jing LP, Ling W, Zheng JS, Chen YM. Cohort Profile: Guangzhou Nutrition and Health Study (GNHS): A Population-based Multi-omics Study. J Epidemiol 2024; 34:301-306. [PMID: 37813622 PMCID: PMC11078596 DOI: 10.2188/jea.je20230108] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/11/2023] Open
Abstract
BACKGROUND The Guangzhou Nutrition and Health Study (GNHS) aims to assess the determinants of metabolic disease in nutritional aspects, as well as other environmental and genetic factors, and explore possible biomarkers and mechanisms with multi-omics integration. METHODS The population-based sample of adults in Guangzhou, China (baseline: 40-83 years old; n = 5,118) was followed up about every 3 years. All are tracked via on-site follow-up and health information systems. We assessed detailed information on lifestyle factors, physical activities, dietary assessments, psychological health, cognitive function, body measurements, and muscle function. Instrument tests included dual-energy X-ray absorptiometry scanning, carotid artery and liver ultrasonography evaluations, vascular endothelial function evaluation, upper-abdomen and brain magnetic resonance imaging, and 14-day real-time continuous glucose monitoring tests. We also measured multi-omics, including host genome-wide genotyping, serum metabolome and proteome, gut microbiome (16S rRNA sequencing, metagenome, and internal transcribed spacer 2 sequencing), and fecal metabolome and proteome. RESULTS The baseline surveys were conducted from 2008 to 2015. Now, we have completed 3 waves. The 3rd and 4th follow-ups have started but have yet to end. A total of 5,118 participants aged 40-83 took part in the study. The median age at baseline was approximately 59.0 years and the proportion of female participants was about 69.4%. Among all the participants, 3,628 (71%) completed at least one on-site follow-up, with a median duration of 9.48 years. CONCLUSION The cohort will provide data that will be influential in establishing the role of nutrition in metabolic diseases with multi-omics.
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Affiliation(s)
- Chu-Wen Ling
- Department of Epidemiology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University
| | - Haili Zhong
- Department of Epidemiology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University
| | - Fang-Fang Zeng
- Department of Epidemiology, School of Medicine, Jinan University
| | - Gengdong Chen
- Department of Obstetrics, Foshan Institute of Fetal Medicine, Southern Medical University Affiliated Maternal & Child Health Hospital of Foshan
| | - Yuanqing Fu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University
| | - Cheng Wang
- Department of Clinical Nutrition, Sun Yat-sen Memorial Hospital
| | - Zhe-Qing Zhang
- Department of Nutrition and Food Hygiene, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University
| | - Wen-Ting Cao
- International School of Public Health and One Health, Hainan Medical University
| | - Ting-Yu Sun
- Department of Epidemiology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University
| | - Ding Ding
- Global Health Research Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences
| | - Yan-Hua Liu
- Department of Nutrition, the First Affiliated Hospital of Zhengzhou University
| | - Hong-Li Dong
- Scientific Education Section and Department of Child Healthcare, Affiliated Maternity & Child Health Care Hospital of Nantong University
| | - Li-Peng Jing
- Department of Epidemiology, School of Public Health, Lanzhou University
| | - Wenhua Ling
- Department of Nutrition, School of Public Health, Sun Yat-sen University
| | - Ju-Sheng Zheng
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University
| | - Yu-Ming Chen
- Department of Epidemiology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University
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Dobroslavska P, Silva ML, Vicente F, Pereira P. Mediterranean Dietary Pattern for Healthy and Active Aging: A Narrative Review of an Integrative and Sustainable Approach. Nutrients 2024; 16:1725. [PMID: 38892658 PMCID: PMC11174674 DOI: 10.3390/nu16111725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 05/27/2024] [Accepted: 05/29/2024] [Indexed: 06/21/2024] Open
Abstract
The global population is on a trajectory of continuous growth, with estimates projecting an increase from 7.7 billion in 2019 to approximately 9.7 billion by 2050. Longevity is also expected to rise rapidly, with advancements in healthcare contributing to increased life expectancies and an increase in the maximum lifespan. The aging process is accompanied by different changes, often leading to a decline in daily life activities and an increased susceptibility to disease. Age-related changes can cause cellular damage and subsequent cellular death. Oxidative stress and inflammation play significant roles in this process contributing to molecular damage and mitochondrial dysfunction. Active aging has been associated with improved quality of life and a reduced risk of morbidity and premature mortality. In this context, the Mediterranean diet has emerged as a promising approach to promoting healthy aging and sustainability. The phytochemical compounds within the Mediterranean diet have been linked to a lower risk of developing cardiovascular disease, type 2 diabetes, obesity, cancer and neurodegenerative diseases. The findings of peer-reviewed articles regarding the use of the Mediterranean diet as a healthy and sustainable dietary pattern written in Portuguese, Spanish or English were included in this narrative literature review. This dietary pattern's emphasis on the consumption of fresh and local food aligns with both health and environmental sustainability goals. This work provides a comprehensive review of the benefits of the Mediterranean diet and its components in a healthy aging process and highlights the importance of this dietary pattern as a sustainable approach.
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Affiliation(s)
| | - Maria Leonor Silva
- Applied Nutrition Research Group (GENA), Nutrition Lab, Egas Moniz Center for Interdisciplinary Research (CiiEM), Egas Moniz School of Health & Science, Monte de Caparica, 2829-511 Almada, Portugal; (P.D.); (F.V.); (P.P.)
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11
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Li J, Li Y, Zhang S, Wang C, Mao Z, Huo W, Yang T, Li Y, Xing W, Li L. Association of the short-chain fatty acid levels and dietary quality with type 2 diabetes: a case-control study based on Henan Rural Cohort. Br J Nutr 2024; 131:1668-1677. [PMID: 38343180 DOI: 10.1017/s0007114524000400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2024]
Abstract
Evidence of the relationship between fecal short-chain fatty acids (SCFA) levels, dietary quality and type 2 diabetes mellitus (T2DM) in rural populations is limited. Here, we aimed to investigate the association between fecal SCFA levels and T2DM and the combined effects of dietar quality on T2DM in rural China. In total, 100 adults were included in the case-control study. Dietary quality was assessed by the Alternate Healthy Eating Index 2010 (AHEI-2010), and SCFA levels were analysed using the GC-MS system. Generalised linear regression was conducted to calculate the OR and 95 % CI to evaluate the effect of SCFA level and dietary quality on the risk of T2DM. Finally, an interaction was used to study the combined effect of SCFA levels and AHEI-2010 scores on T2DM. T2DM participants had lower levels of acetic and butyric acid. Generalised linear regression analysis revealed that the OR (95 % CI) of the highest acetic and butyric acid levels were 0·099 (0·022, 0·441) and 0·210 (0·057, 0·774), respectively, compared with the subjects with the lowest tertile of level. We also observed a significantly lower risk of T2DM with acetic acid levels > 1330·106 μg/g or butyric acid levels > 585·031 μg/g. Moreover, the risks of higher acetic and butyric acid levels of T2DM were 0·007 (95 % CI: 0·001, 0·148), 0·005 (95 % CI: 0·001, 0·120) compared with participants with lower AHEI-2010 scores (all P < 0·05). Acetate and butyrate levels may be important modifiable beneficial factors affecting T2DM in rural China. Improving dietary quality for body metabolism balance should be encouraged to promote good health.
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Affiliation(s)
- Jia Li
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan450001, People's Republic of China
| | - Yuqian Li
- Department of Clinical Pharmacology, School of Pharmaceutical Science, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Shuhua Zhang
- Comprehensive Laboratory, Puyang Quality and Technical Supervision, Inspection and Testing Center, Puyang, Henan, People's Republic of China
| | - Chongjian Wang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan450001, People's Republic of China
| | - Zhenxing Mao
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan450001, People's Republic of China
| | - Wenqian Huo
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan450001, People's Republic of China
| | - Tianyu Yang
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan450001, People's Republic of China
| | - Yan Li
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan450001, People's Republic of China
| | - Wenguo Xing
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan450001, People's Republic of China
| | - Linlin Li
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan450001, People's Republic of China
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12
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Zheng G, Zhang Y, Ou F, Chang Q, Ji C, Yang H, Chen L, Xia Y, Zhao Y. Sugar types, genetic predictors of the gut microbiome, and the risk of chronic kidney disease: a prospective cohort study. Food Funct 2024; 15:4925-4935. [PMID: 38601989 DOI: 10.1039/d4fo00724g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/12/2024]
Abstract
Background: Emerging studies suggest that focusing on the intake of specific types or sources of sugars may yield greater benefits in preventing chronic kidney disease (CKD). Objective: We aimed to investigate the associations between free and non-free sugar intakes and CKD risk as well as the potential sugar type-gut microbiome interactions. Methods: A total of 138 064 participants from the UK Biobank were included in this prospective study. The free and non-free sugar intakes were assessed using repeated web-based 24-hour dietary recalls. A cause-specific competing risk model was used to estimate hazard ratios (HRs) and the corresponding confidence intervals (CIs) of incident CKD, treating deaths before incident CKD as competing events. Results: During a median follow-up of 10.5 years, 2,923 participants (2.1%) developed CKD. The free sugar intake was positively associated with the risk of CKD (HRquartile 4 vs. quartile 1 = 1.32, 95% CI = 1.18, 1.47), with a nonlinear relationship (P for nonlinearity = 0.01, the risk increased rapidly after free sugars made up 10% of the total energy). The non-free sugar intake was inversely associated with CKD risk (HRquartile 4 vs. quartile 1 = 0.68, 95% CI = 0.60, 0.77), with an L-shaped nonlinear curve (p for nonlinearity = 0.01, the turning point was at 13.5% of the total energy). We found that the associations between free sugar and non-free sugar intakes and CKD risk were more pronounced in participants with high genetically predicted gut microbial abundance. Furthermore, a significant interaction was observed between the genetically predicted gut microbial abundance and non-free sugar intake (P for interaction = 0.04). Conclusion: A higher intake of free sugars was associated with an elevated risk of CKD, whereas a higher intake of non-free sugars was associated with a reduced risk of CKD. The impact of free sugar intake and non-free sugar intake may be modified by the gut microbial abundance.
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Affiliation(s)
- Gang Zheng
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, China Medical, University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China.
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China
| | - Yixiao Zhang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, China Medical, University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China.
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China
- Department of Urology Surgery, Shengjing Hospital of China Medical University, China Medical University, Shenyang, China
| | - Fengrong Ou
- School of Public Health, China Medical University, Shenyang, China
| | - Qing Chang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, China Medical, University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China.
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China
| | - Chao Ji
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, China Medical, University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China.
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China
| | - Honghao Yang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, China Medical, University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China.
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China
| | - Liangkai Chen
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yang Xia
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, China Medical, University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China.
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China
| | - Yuhong Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, China Medical, University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China.
- Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China
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13
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Kase BE, Liese AD, Zhang J, Murphy EA, Zhao L, Steck SE. The Development and Evaluation of a Literature-Based Dietary Index for Gut Microbiota. Nutrients 2024; 16:1045. [PMID: 38613077 PMCID: PMC11013161 DOI: 10.3390/nu16071045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 03/26/2024] [Accepted: 03/29/2024] [Indexed: 04/14/2024] Open
Abstract
The aim of the study was to develop and evaluate a novel dietary index for gut microbiota (DI-GM) that captures dietary composition related to gut microbiota profiles. We conducted a literature review of longitudinal studies on the association of diet with gut microbiota in adult populations and extracted those dietary components with evidence of beneficial or unfavorable effects. Dietary recall data from the National Health and Nutrition Examination Survey (NHANES, 2005-2010, n = 3812) were used to compute the DI-GM, and associations with biomarkers of gut microbiota diversity (urinary enterodiol and enterolactone) were examined using linear regression. From a review of 106 articles, 14 foods or nutrients were identified as components of the DI-GM, including fermented dairy, chickpeas, soybean, whole grains, fiber, cranberries, avocados, broccoli, coffee, and green tea as beneficial components, and red meat, processed meat, refined grains, and high-fat diet (≥40% of energy from fat) as unfavorable components. Each component was scored 0 or 1 based on sex-specific median intakes, and scores were summed to develop the overall DI-GM score. In the NHANES, DI-GM scores ranged from 0-13 with a mean of 4.8 (SE = 0.04). Positive associations between DI-GM and urinary enterodiol and enterolactone were observed. The association of the novel DI-GM with markers of gut microbiota diversity demonstrates the potential utility of this index for gut health-related studies.
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Affiliation(s)
- Bezawit E. Kase
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Discovery 1, 915 Greene Street, Columbia, SC 29208, USA; (B.E.K.)
| | - Angela D. Liese
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Discovery 1, 915 Greene Street, Columbia, SC 29208, USA; (B.E.K.)
| | - Jiajia Zhang
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Discovery 1, 915 Greene Street, Columbia, SC 29208, USA; (B.E.K.)
| | - Elizabeth Angela Murphy
- Department of Pathology, Microbiology and Immunology, School of Medicine Columbia, University of South Carolina, Columbia, SC 29208, USA
| | - Longgang Zhao
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Discovery 1, 915 Greene Street, Columbia, SC 29208, USA; (B.E.K.)
| | - Susan E. Steck
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Discovery 1, 915 Greene Street, Columbia, SC 29208, USA; (B.E.K.)
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14
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Farahbod K, Slouha E, Gerts A, Rezazadah A, Clunes LA, Kollias TF. The Effects of Diet Intervention on the Gut Microbiota in Type 2 Diabetes Mellitus: A Systematic Review. Cureus 2024; 16:e56737. [PMID: 38646363 PMCID: PMC11033091 DOI: 10.7759/cureus.56737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/22/2024] [Indexed: 04/23/2024] Open
Abstract
The GI tract hosts a dynamic community known as the gut microbiota, which encompasses thriving bacteria that actively contribute to the physiological functions of the human body. The intricacies of its composition are profoundly influenced by dietary preferences, where the quality, quantity, and frequency of food consumption play a pivotal role in either fostering or impeding specific bacterial strains. Type 2 diabetes mellitus (T2DM) is a prevalent and deleterious condition that originates from excessive hyperglycemia. Do lifestyle interventions targeting dietary adjustments, nutritional supplements, physical activity, and weight management programs exhibit a significant relationship in altering the composition of the gut microbiome and managing T2DM? This paper aims to evaluate the effects of lifestyle interventions on patients with T2DM and the implications of these changes on disease outcomes and progression. Lifestyle interventions can significantly impact the management of T2DM, especially those targeting dietary adjustments, nutritional supplements, physical activity, and weight management programs. The adoption of a high-fiber diet and increased fruit consumption have shown positive impacts on both insulin sensitivity and the composition of the gut microbiota. Additionally, promising outcomes emerge from supplementing with Omega-3 fatty acids, Vitamin K2 (MK-7), and transglucosidase, which influence insulin levels, glycemic control, and gut microbiota composition. Personalized diet interventions and the transformative effects of the Mediterranean diet present positive outcomes in metabolic control. The intensity of exercise plays a pivotal role in shaping the composition of the gut microbiota, with moderate-intensity continuous exercise displaying positive effects on anti-inflammatory microbes. Chronic exercise showcases favorable impacts on glycemic control and systemic inflammation. Emphasizing the intricate relationship between dietary habits, gut microbiota, and the risk of T2DM underscores the potential of the gut microbiota as a universal biomarker for assessing diabetes risk. Nutritional supplements and exercise interventions provide potential avenues for the management of T2DM, emphasizing the necessity for tailored strategies. Further research is encouraged to delve into the long-term effects and intricate interplay between lifestyle factors and the gut microbiome, enhancing our understanding of T2DM pathophysiology for targeted therapeutic approaches.
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Affiliation(s)
- Kiana Farahbod
- Department of Pharmacology, St. George's University School of Medicine, St. George's, GRD
| | - Ethan Slouha
- Department of Pharmacology, St. George's University School of Medicine, St. George's, GRD
| | - Andrew Gerts
- Department of Pharmacology, St. George's University School of Medicine, St. George's, GRD
| | - Atbeen Rezazadah
- Department of Pharmacology, St. George's University School of Medicine, St. George's, GRD
| | - Lucy A Clunes
- Department of Pharmacology, St. George's University School of Medicine, St. George's, GRD
| | - Theofanis F Kollias
- Department Microbiology, Immunology, and Pharmacology, St. George's University School of Medicine, St. George's, GRD
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15
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Cheng J, Li J, Xiong RG, Wu SX, Xu XY, Tang GY, Huang SY, Zhou DD, Li HB, Feng Y, Gan RY. Effects and mechanisms of anti-diabetic dietary natural products: an updated review. Food Funct 2024; 15:1758-1778. [PMID: 38240135 DOI: 10.1039/d3fo04505f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Diabetes is a global public health issue, characterized by an abnormal level of blood glucose. It can be classified into type 1, type 2, gestational, and other rare diabetes. Recent studies have reported that many dietary natural products exhibit anti-diabetic activity. In this narrative review, the effects and underlying mechanisms of dietary natural products on diabetes are summarized based on the results from epidemiological, experimental, and clinical studies. Some fruits (e.g., grape, blueberry, and cherry), vegetables (e.g., bitter melon and Lycium barbarum leaves), grains (e.g., oat, rye, and brown rice), legumes (e.g., soybean and black bean), spices (e.g., cinnamon and turmeric) and medicinal herbs (e.g., Aloe vera leaf and Nigella sativa), and vitamin C and carotenoids could play important roles in the prevention and management of diabetes. Their underlying mechanisms include exerting antioxidant, anti-inflammatory, and anti-glycation effects, inhibiting carbohydrate-hydrolyzing enzymes, enhancing insulin action, alleviating insulin resistance, modulating the gut microbiota, and so on. This review can provide people with a comprehensive knowledge of anti-diabetic dietary natural products, and support their further development into functional food to prevent and manage diabetes.
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Affiliation(s)
- Jin Cheng
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
| | - Jiahui Li
- School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong 999077, China.
| | - Ruo-Gu Xiong
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
| | - Si-Xia Wu
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
| | - Xiao-Yu Xu
- School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong 999077, China.
| | - Guo-Yi Tang
- School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong 999077, China.
| | - Si-Yu Huang
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
| | - Dan-Dan Zhou
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
| | - Hua-Bin Li
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Nutrition, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
| | - Yibin Feng
- School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong 999077, China.
| | - Ren-You Gan
- Singapore Institute of Food and Biotechnology Innovation (SIFBI), Agency for Science, Technology and Research (A*STAR), 31 Biopolis Way, Singapore 138669, Singapore.
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16
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Ferreira G, Vieira P, Alves A, Nunes S, Preguiça I, Martins-Marques T, Ribeiro T, Girão H, Figueirinha A, Salgueiro L, Pintado M, Gomes P, Viana S, Reis F. Effect of Blueberry Supplementation on a Diet-Induced Rat Model of Prediabetes-Focus on Hepatic Lipid Deposition, Endoplasmic Stress Response and Autophagy. Nutrients 2024; 16:513. [PMID: 38398840 PMCID: PMC10892331 DOI: 10.3390/nu16040513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Revised: 02/06/2024] [Accepted: 02/09/2024] [Indexed: 02/25/2024] Open
Abstract
Blueberries, red fruits enriched in polyphenols and fibers, are envisaged as a promising nutraceutical intervention in a plethora of metabolic diseases. Prediabetes, an intermediate state between normal glucose tolerance and type 2 diabetes, fuels the development of complications, including hepatic steatosis. In previous work, we have demonstrated that blueberry juice (BJ) supplementation benefits glycemic control and lipid profile, which was accompanied by an amelioration of hepatic mitochondrial bioenergetics. The purpose of this study is to clarify the impact of long-term BJ nutraceutical intervention on cellular mechanisms that govern hepatic lipid homeostasis, namely autophagy and endoplasmic reticulum (ER) stress, in a rat model of prediabetes. Two groups of male Wistar rats, 8-weeks old, were fed a prediabetes-inducing high-fat diet (HFD) and one group was fed a control diet (CD). From the timepoint where the prediabetic phenotype was achieved (week 16) until the end of the study (week 24), one of the HFD-fed groups was daily orally supplemented with 25 g/kg body weight (BW) of BJ (HFD + BJ). BW, caloric intake, glucose tolerance and insulin sensitivity were monitored throughout the study. The serum and hepatic lipid contents were quantified. Liver and interscapular brown and epidydimal white adipose tissue depots (iBAT and eWAT) were collected for histological analysis and to assess thermogenesis, ER stress and autophagy markers. The gut microbiota composition and the short-chain fatty acids (SCFAs) content were determined in colon fecal samples. BJ supplementation positively impacted glycemic control but was unable to prevent obesity and adiposity. BJ-treated animals presented a reduction in fecal SCFAs, increased markers of arrested iBAT thermogenesis and energy expenditure, together with an aggravation of HFD-induced lipotoxicity and hepatic steatosis, which were accompanied by the inhibition of autophagy and ER stress responses in the liver. In conclusion, despite the improvement of glucose tolerance, BJ supplementation promoted a major impact on lipid management mechanisms at liver and AT levels in prediabetic animals, which might affect disease course.
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Affiliation(s)
- Gonçalo Ferreira
- Institute of Pharmacology & Experimental Therapeutics & Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal; (G.F.); (P.V.); (A.A.); (S.N.); (I.P.); (T.M.-M.); (H.G.); (P.G.); (S.V.)
- CIBB—Center for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004–504 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3004-531 Coimbra, Portugal
| | - Pedro Vieira
- Institute of Pharmacology & Experimental Therapeutics & Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal; (G.F.); (P.V.); (A.A.); (S.N.); (I.P.); (T.M.-M.); (H.G.); (P.G.); (S.V.)
- CIBB—Center for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004–504 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3004-531 Coimbra, Portugal
- Polytechnic Institute of Coimbra, ESTESC-Coimbra Health School, Pharmacy, 3045-043 Coimbra, Portugal
| | - André Alves
- Institute of Pharmacology & Experimental Therapeutics & Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal; (G.F.); (P.V.); (A.A.); (S.N.); (I.P.); (T.M.-M.); (H.G.); (P.G.); (S.V.)
- CIBB—Center for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004–504 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3004-531 Coimbra, Portugal
| | - Sara Nunes
- Institute of Pharmacology & Experimental Therapeutics & Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal; (G.F.); (P.V.); (A.A.); (S.N.); (I.P.); (T.M.-M.); (H.G.); (P.G.); (S.V.)
- CIBB—Center for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004–504 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3004-531 Coimbra, Portugal
- Polytechnic Institute of Coimbra, ESTESC-Coimbra Health School, Pharmacy, 3045-043 Coimbra, Portugal
| | - Inês Preguiça
- Institute of Pharmacology & Experimental Therapeutics & Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal; (G.F.); (P.V.); (A.A.); (S.N.); (I.P.); (T.M.-M.); (H.G.); (P.G.); (S.V.)
- CIBB—Center for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004–504 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3004-531 Coimbra, Portugal
| | - Tânia Martins-Marques
- Institute of Pharmacology & Experimental Therapeutics & Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal; (G.F.); (P.V.); (A.A.); (S.N.); (I.P.); (T.M.-M.); (H.G.); (P.G.); (S.V.)
- CIBB—Center for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004–504 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3004-531 Coimbra, Portugal
| | - Tânia Ribeiro
- CBQF—Centro de Biotecnologia e Química Fina—Laboratório Associado, Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Rua Diogo Botelho 1327, 4169-005 Porto, Portugal; (T.R.); (M.P.)
| | - Henrique Girão
- Institute of Pharmacology & Experimental Therapeutics & Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal; (G.F.); (P.V.); (A.A.); (S.N.); (I.P.); (T.M.-M.); (H.G.); (P.G.); (S.V.)
- CIBB—Center for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004–504 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3004-531 Coimbra, Portugal
| | - Artur Figueirinha
- Faculty of Pharmacy, University of Coimbra, 3000-548 Coimbra, Portugal; (A.F.); (L.S.)
- LAQV, REQUIMTE, Faculty of Pharmacy, University of Coimbra, 3000-548 Coimbra, Portugal
| | - Lígia Salgueiro
- Faculty of Pharmacy, University of Coimbra, 3000-548 Coimbra, Portugal; (A.F.); (L.S.)
- CERES, Chemical Engineering and Renewable Resources for Sustainability, Department of Chemical Engineering, University of Coimbra, 3030-790 Coimbra, Portugal
| | - Manuela Pintado
- CBQF—Centro de Biotecnologia e Química Fina—Laboratório Associado, Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Rua Diogo Botelho 1327, 4169-005 Porto, Portugal; (T.R.); (M.P.)
| | - Pedro Gomes
- Institute of Pharmacology & Experimental Therapeutics & Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal; (G.F.); (P.V.); (A.A.); (S.N.); (I.P.); (T.M.-M.); (H.G.); (P.G.); (S.V.)
- CIBB—Center for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004–504 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3004-531 Coimbra, Portugal
- Department of Biomedicine, Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal
| | - Sofia Viana
- Institute of Pharmacology & Experimental Therapeutics & Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal; (G.F.); (P.V.); (A.A.); (S.N.); (I.P.); (T.M.-M.); (H.G.); (P.G.); (S.V.)
- CIBB—Center for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004–504 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3004-531 Coimbra, Portugal
- Polytechnic Institute of Coimbra, ESTESC-Coimbra Health School, Pharmacy, 3045-043 Coimbra, Portugal
| | - Flávio Reis
- Institute of Pharmacology & Experimental Therapeutics & Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal; (G.F.); (P.V.); (A.A.); (S.N.); (I.P.); (T.M.-M.); (H.G.); (P.G.); (S.V.)
- CIBB—Center for Innovative Biomedicine and Biotechnology, University of Coimbra, 3004–504 Coimbra, Portugal
- Clinical Academic Center of Coimbra (CACC), 3004-531 Coimbra, Portugal
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17
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Liu C, Du MX, Xie LS, Wang WZ, Chen BS, Yun CY, Sun XW, Luo X, Jiang Y, Wang K, Jiang MZ, Qiao SS, Sun M, Cui BJ, Huang HJ, Qu SP, Li CK, Wu D, Wang LS, Jiang C, Liu HW, Liu SJ. Gut commensal Christensenella minuta modulates host metabolism via acylated secondary bile acids. Nat Microbiol 2024; 9:434-450. [PMID: 38233647 DOI: 10.1038/s41564-023-01570-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 11/29/2023] [Indexed: 01/19/2024]
Abstract
A strong correlation between gut microbes and host health has been observed in numerous gut metagenomic cohort studies. However, the underlying mechanisms governing host-microbe interactions in the gut remain largely unknown. Here we report that the gut commensal Christensenella minuta modulates host metabolism by generating a previously undescribed class of secondary bile acids with 3-O-acylation substitution that inhibit the intestinal farnesoid X receptor. Administration of C. minuta alleviated features of metabolic disease in high fat diet-induced obese mice associated with a significant increase in these acylated bile acids, which we refer to as 3-O-acyl-cholic acids. Specific knockout of intestinal farnesoid X receptor in mice counteracted the beneficial effects observed in their wild-type counterparts. Finally, we showed that 3-O-acyl-CAs were prevalent in healthy humans but significantly depleted in patients with type 2 diabetes. Our findings indicate a role for C. minuta and acylated bile acids in metabolic diseases.
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Affiliation(s)
- Chang Liu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Meng-Xuan Du
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Li-Sheng Xie
- College of Life Science, Hebei University, Baoding, P. R. China
| | - Wen-Zhao Wang
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Bao-Song Chen
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Chu-Yu Yun
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, P. R. China
| | - Xin-Wei Sun
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Xi Luo
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, P. R. China
| | - Yu Jiang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Kai Wang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, P. R. China
| | - Min-Zhi Jiang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Shan-Shan Qiao
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Min Sun
- The Second Hospital of Shandong University, Jinan, P. R. China
| | - Bao-Juan Cui
- The Second Hospital of Shandong University, Jinan, P. R. China
| | - Hao-Jie Huang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | | | | | - Dalei Wu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Lu-Shan Wang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Changtao Jiang
- Department of Physiology and Pathophysiology, School of Basic Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, P. R. China.
- Center of Basic Medical Research, Institute of Medical Innovation and Research, Third Hospital, Peking University, Beijing, P. R. China.
| | - Hong-Wei Liu
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China.
| | - Shuang-Jiang Liu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China.
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China.
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18
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Gul F, Herrema H, Davids M, Keating C, Nasir A, Ijaz UZ, Javed S. Gut microbial ecology and exposome of a healthy Pakistani cohort. Gut Pathog 2024; 16:5. [PMID: 38254227 PMCID: PMC10801943 DOI: 10.1186/s13099-024-00596-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 01/02/2024] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND Pakistan is a multi-ethnic society where there is a disparity between dietary habits, genetic composition, and environmental exposures. The microbial ecology of healthy Pakistani gut in the context of anthropometric, sociodemographic, and dietary patterns holds interest by virtue of it being one of the most populous countries, and also being a Lower Middle Income Country (LMIC). METHODS 16S rRNA profiling of healthy gut microbiome of normo-weight healthy Pakistani individuals from different regions of residence is performed with additional meta-data collected through filled questionnaires. The current health status is then linked to dietary patterns through [Formula: see text] test of independence and Generalized Linear Latent Variable Model (GLLVM) where distribution of individual microbes is regressed against all recorded sources of variability. To identify the core microbiome signature, a dynamic approach is used that considers into account species occupancy as well as consistency across assumed grouping of samples including organization by gender and province of residence. Fitting neutral modeling then revealed core microbiome that is selected by the environment. RESULTS A strong determinant of disparity is by province of residence. It is also established that the male microbiome is better adapted to the local niche than the female microbiome, and that there is microbial taxonomic and functional diversity in different ethnicities, dietary patterns and lifestyle habits. Some microbial genera, such as, Megamonas, Porphyromonas, Haemophilus, Klebsiella and Finegoldia showed significant associations with consumption of pickle, fresh fruits, rice, and cheese. Our analyses suggest current health status being associated with the diet, sleeping patterns, employment status, and the medical history. CONCLUSIONS This study provides a snapshot of the healthy core Pakistani gut microbiome by focusing on the most populous provinces and ethnic groups residing in predominantly urban areas. The study serves a reference dataset for exploring variations in disease status and designing personalized dietary and lifestyle interventions to promote gut health, particularly in LMICs settings.
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Affiliation(s)
- Farzana Gul
- Department of Biosciences, COMSATS University Islamabad, Islamabad, 45550, Pakistan
| | - Hilde Herrema
- Department of Experimental Vascular Medicine, Amsterdam University Medical Centers, Location AMC, Amsterdam, The Netherlands
| | - Mark Davids
- Department of Experimental Vascular Medicine, Amsterdam University Medical Centers, Location AMC, Amsterdam, The Netherlands
| | - Ciara Keating
- School of Biodiversity, One Health & Veterinary Medicine, Graham Kerr Building, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Arshan Nasir
- Department of Biosciences, COMSATS University Islamabad, Islamabad, 45550, Pakistan
- Moderna, Inc., Cambridge, MA, USA
| | - Umer Zeeshan Ijaz
- Water & Environment Research Group, Mazumdar-Shaw Advanced Research Centre, University of Glasgow, Glasgow, G11 6EW, UK.
- Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, L69 7BE, UK.
- National University of Ireland, Galway, University Road, Galway, H91 TK33, Ireland.
| | - Sundus Javed
- Department of Biosciences, COMSATS University Islamabad, Islamabad, 45550, Pakistan.
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Hamamah S, Iatcu OC, Covasa M. Nutrition at the Intersection between Gut Microbiota Eubiosis and Effective Management of Type 2 Diabetes. Nutrients 2024; 16:269. [PMID: 38257161 PMCID: PMC10820857 DOI: 10.3390/nu16020269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 01/15/2024] [Accepted: 01/15/2024] [Indexed: 01/24/2024] Open
Abstract
Nutrition is one of the most influential environmental factors in both taxonomical shifts in gut microbiota as well as in the development of type 2 diabetes mellitus (T2DM). Emerging evidence has shown that the effects of nutrition on both these parameters is not mutually exclusive and that changes in gut microbiota and related metabolites such as short-chain fatty acids (SCFAs) and branched-chain amino acids (BCAAs) may influence systemic inflammation and signaling pathways that contribute to pathophysiological processes associated with T2DM. With this background, our review highlights the effects of macronutrients, carbohydrates, proteins, and lipids, as well as micronutrients, vitamins, and minerals, on T2DM, specifically through their alterations in gut microbiota and the metabolites they produce. Additionally, we describe the influences of common food groups, which incorporate varying combinations of these macronutrients and micronutrients, on both microbiota and metabolic parameters in the context of diabetes mellitus. Overall, nutrition is one of the first line modifiable therapies in the management of T2DM and a better understanding of the mechanisms by which gut microbiota influence its pathophysiology provides opportunities for optimizing dietary interventions.
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Affiliation(s)
- Sevag Hamamah
- Department of Basic Medical Sciences, College of Osteopathic Medicine, Western University of Health Sciences, Pomona, CA 91766, USA;
| | - Oana C. Iatcu
- Department of Biomedical Sciences, College of Medicine and Biological Science, University of Suceava, 720229 Suceava, Romania
| | - Mihai Covasa
- Department of Basic Medical Sciences, College of Osteopathic Medicine, Western University of Health Sciences, Pomona, CA 91766, USA;
- Department of Biomedical Sciences, College of Medicine and Biological Science, University of Suceava, 720229 Suceava, Romania
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20
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Basu A, Richardson LA, Carlos A, Abubakr NH, Weltman RL, Ebersole JL. The Associations of Cardiometabolic and Dietary Variables with Clinical Periodontitis in Adults with and without Type 2 Diabetes: A Cross-Sectional Study. Nutrients 2023; 16:81. [PMID: 38201914 PMCID: PMC10780717 DOI: 10.3390/nu16010081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 12/19/2023] [Accepted: 12/20/2023] [Indexed: 01/12/2024] Open
Abstract
Periodontitis is a commonly occurring inflammatory oral disease affecting a large proportion of global and US adults and is characterized by the destruction of the tooth-supporting apparatus. Its etiology is multifactorial, and type 2 diabetes and diet play critical roles in its remission and progression. However, few studies have addressed nutritional and serum vitamin D status in adults with periodontitis in the presence of diabetes. A cross-sectional study (n = 78), and a sub-set of age- and BMI-matched case-control studies (n = 50), were conducted to examine differences in dietary and cardiometabolic variables, and serum vitamin D in adults with periodontitis with or without diabetes. Participants provided fasting blood samples and 24-h diet recalls on at least two different days. Data on health history, body weight, height, nutritional habits, and clinical features of periodontitis were also collected. The Mann-Whitney U Test (with exact p-value estimation by Monte Carlo simulation) was used to examine differences by diabetes status in continuous and ordinal variables. Results revealed significantly lower serum vitamin D, and dietary intake of fruits, vegetables, dairy, vitamins A and C in adults with periodontitis with vs. without diabetes in the sub-study (all p < 0.05). In the overall sample, adults with diabetes presented with higher caries risk measures and lower numbers of teeth than those without diabetes; plaque and bleeding scores did not differ by diabetes status. Finally, a significant associations of food habits was observed, especially consuming protein-rich foods twice a day with a lower bleeding score, and daily consumption of fried or fast foods with a fewer number of teeth present (all p < 0.05). The present findings show significant dietary and serum vitamin D inadequacies among adults with periodontitis, and diabetes further aggravates the observed malnourishment and oral health.
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Affiliation(s)
- Arpita Basu
- Department of Kinesiology and Nutrition Sciences, School of Integrated Health Sciences, University of Nevada at Las Vegas, Las Vegas, NV 89154, USA;
| | - Leigh Ann Richardson
- Department of Kinesiology and Nutrition Sciences, School of Integrated Health Sciences, University of Nevada at Las Vegas, Las Vegas, NV 89154, USA;
| | - Alicia Carlos
- Department of Biomedical Sciences, School of Dental Medicine, University of Nevada at Las Vegas, Las Vegas, NV 89154, USA; (A.C.); (N.H.A.); (J.L.E.)
| | - Neamat Hassan Abubakr
- Department of Biomedical Sciences, School of Dental Medicine, University of Nevada at Las Vegas, Las Vegas, NV 89154, USA; (A.C.); (N.H.A.); (J.L.E.)
| | - Robin L. Weltman
- Department of Clinical Sciences, School of Dental Medicine, University of Nevada at Las Vegas, Las Vegas, NV 89154, USA;
| | - Jeffrey L. Ebersole
- Department of Biomedical Sciences, School of Dental Medicine, University of Nevada at Las Vegas, Las Vegas, NV 89154, USA; (A.C.); (N.H.A.); (J.L.E.)
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21
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Feng X, Deng M, Zhang L, Pan Q. Impact of gut microbiota and associated mechanisms on postprandial glucose levels in patients with diabetes. J Transl Int Med 2023; 11:363-371. [PMID: 38130636 PMCID: PMC10732577 DOI: 10.2478/jtim-2023-0116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023] Open
Abstract
Diabetes and its complications are serious medical and global burdens, often manifesting as postprandial hyperglycemia. In recent years, considerable research attention has focused on relationships between the gut microbiota and circulating postprandial glucose (PPG). Different population studies have suggested that PPG is closely related to the gut microbiota which may impact PPG via short-chain fatty acids (SCFAs), bile acids (BAs) and trimethylamine N-oxide (TMAO). Studies now show that gut microbiota models can predict PPG, with individualized nutrition intervention strategies used to regulate gut microbiota and improve glucose metabolism to facilitate the precision treatment of diabetes. However, few studies have been conducted in patients with diabetes. Therefore, little is known about the relationships between the gut microbiota and PPG in this cohort. Thus, more research is required to identify key gut microbiota and associated metabolites and pathways impacting PPG to provide potential therapeutic targets for PPG.
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Affiliation(s)
- Xinyuan Feng
- Department of Endocrinology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Beijing100730 ,China
- Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing100730, China
| | - Mingqun Deng
- Department of Endocrinology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Beijing100730 ,China
| | - Lina Zhang
- Department of Endocrinology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Beijing100730 ,China
| | - Qi Pan
- Department of Endocrinology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Beijing100730 ,China
- Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing100730, China
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22
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Lin F, He R, Ling B, Wang L, Jiang T, Yu B. Dorzagliatin for Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis of Randomized Phase II/III Trials. Clin Ther 2023; 45:1277-1283. [PMID: 37777375 DOI: 10.1016/j.clinthera.2023.09.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/27/2023] [Accepted: 09/13/2023] [Indexed: 10/02/2023]
Abstract
PURPOSE Dorzagliatin is a glucokinase agonist with effects on type 2 diabetes mellitus (T2DM). This study included a meta-analysis on the efficacy and safety of dorzagliatin in the treatment of T2DM. METHODS The Cochrane Central Registry of Controlled Trials, PubMed, and Embase were searched from inception to July 25, 2022. A total of 3 studies including 1333 patients were identified in this meta-analysis. FINDINGS Overall, the meta-analysis showed that dorzagliatin remarkably reduced glycated hemoglobin levels versus placebo by 0.66%. The results of the meta-analysis showed a significant reduction in fasting plasma glucose of 6.77 mg/dL between dorzagliatin and placebo. In addition, dorzagliatin reduced 2-hour postprandial glucose (2h-PPG) by 43.87 mg/dL compared with placebo. Furthermore, the meta-analysis of available data revealed a significant reduction in the Homeostasis Model Assessment of Insulin Resistance of 0.07 between dorzagliatin and placebo. The risk of adverse events was slightly higher with dorzagliatin than with placebo. IMPLICATIONS Dorzagliatin significantly reduced glycated hemoglobin levels, fasting plasma glucose levels, 2h-PPG, and homeostasis model assessment 2 of insulin resistance in patients with T2DM. It was well tolerated and had good liver and kidney safety profiles.
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Affiliation(s)
- Fei Lin
- Department of Pharmacy, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China; Clinical Medical College, Chengdu Medical College, Chengdu, Sichuan, China
| | - Rong He
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China; Clinical Medical College, Chengdu Medical College, Chengdu, Sichuan, China
| | - Baodong Ling
- School of Pharmacy, Chengdu Medical College, Chengdu, China
| | - Lin Wang
- Department of Pharmacy, Sichuan Mianyang 404 Hospital, Mianyang, Sichuan, China
| | - Ting Jiang
- Department of Pharmacy, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China; Clinical Medical College, Chengdu Medical College, Chengdu, Sichuan, China
| | - Bin Yu
- Department of Pharmacy, Mianyang Central Hospital, Mianyang, China; School of Medicine, University of Electronic Science and Technology of China, Mianyang, Sichuan, China.
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23
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Chen S, Lin X, Ma J, Li M, Chen Y, Fang AP, Zhu HL. Dietary protein intake and changes in muscle mass measurements in community-dwelling middle-aged and older adults: A prospective cohort study. Clin Nutr 2023; 42:2503-2511. [PMID: 37922694 DOI: 10.1016/j.clnu.2023.10.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 10/12/2023] [Accepted: 10/20/2023] [Indexed: 11/07/2023]
Abstract
BACKGROUND & AIMS Increasing dietary protein intake can be an efficient strategy to prevent sarcopenia. Nevertheless, due to the discrepancy in the population and their dietary pattern, evidence suggested the effects of dietary protein amount or source on sarcopenia prevention varies. This prospective cohort study investigated the correlation between dietary protein intakes or sources and changes in muscle mass measurements. Additionally, the study explored the link between dietary protein and the prevalence of sarcopenia. METHODS Participants aged 40 to 75 were from Guangzhou Nutrition and Health Study (GNHS) 2011-2013 and returned in 2014-2017. Validated 79-item food frequency questionnaires were applied to calculate the amount of total, animal, and plant protein intakes and animal-to-plant protein ratio (APR). The body composition was examined by dual-energy x-ray absorptiometry (DXA) to calculate the appendicular lean mass (ALM) and its index (ASMI). Sarcopenia was diagnosed based on the 2019 Asia Working Group of Sarcopenia's criteria. ANCOVA was utilized to compare the differences of Δ ALM and Δ ASMI across the quartiles of the dietary protein, and linear regression was employed to examine dose-response associations. Multilinear mixed-effect models were employed to evaluate whether protein intake relates to annual changes in ALM and ASMI. Multivariable logistic regressions were performed to analyze the associations between dietary protein and sarcopenia. RESULTS In total, 2709 participants during the 3.2-year follow-up period were considered eligible for analysis. Higher dietary protein intakes (total, animal, plant) in both sexes could preserve more ALM and ASMI in a dose-response manner (all P-trend < 0.05). The annual estimated preservations of ASMI were greater in the highest dietary protein intakes (total, animal, plant) quartile than the lowest (0.05-0.13 kg/m2/y, all P < 0.05). In women, the risk of sarcopenia was reduced by 35%-50 % in the highest protein intake (total, animal, plant) quartile than the lowest. The APR did not display any significant associations. CONCLUSIONS Higher dietary protein intake, regardless of animal or plant sources, is associated with less muscle loss and a lower prevalence of sarcopenia in middle-aged and older Chinese, particularly women. CLINICALTRIALS GOV IDENTIFIER NCT03179657.
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Affiliation(s)
- Si Chen
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xinlei Lin
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Jingfei Ma
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Mengchu Li
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Yuming Chen
- Department of Epidemiology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Ai-Ping Fang
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - Hui-Lian Zhu
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
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24
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Song S, Shon J, Yang WR, Kang HB, Kim KH, Park JY, Lee S, Baik SY, Lee KR, Park YJ. Short-Term Effects of Weight-Loss Meal Replacement Programs with Various Macronutrient Distributions on Gut Microbiome and Metabolic Parameters: A Pilot Study. Nutrients 2023; 15:4744. [PMID: 38004139 PMCID: PMC10675061 DOI: 10.3390/nu15224744] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 10/21/2023] [Accepted: 10/31/2023] [Indexed: 11/26/2023] Open
Abstract
It has emerged the gut microbiome is crucially linked to metabolic health and obesity. Macronutrient distribution has been discussed as a key parameter in weight-loss programs, but little is known about its impact on the gut microbiome. We investigated the effects of weight-loss meal replacement programs with different macronutrient ratios on the gut microbiota and metabolic parameters in subjects with overweight and obesity. Three low-calorie meal replacement programs with different ratios of carbohydrates, proteins, and lipids were designed: a balanced diet (Group B, 60:15:30), a high-lipid-low-carbohydrate diet (Group F, 35:20:55), and a protein-enriched diet (Group P, 40:25:35). Sixty overweight or obese participants were provided with the meals twice daily for 3 weeks. In all groups, diet intervention resulted in reduced body weight and BMI. The relative abundance of Bacteroidetes and Firmicutes phyla decreased and increased, respectively, which increased the Firmicutes/Bacteroidetes (F/B) ratio in all subjects, particularly in Groups B and P. Alpha- and beta-diversity were augmented at the phylum level in Group P. In conclusion, short-term interventions with weight-loss meal replacement programs increased butyrate-producing bacteria and the F/B ratio. Moreover, the protein-enriched diet significantly increased alpha- and beta-diversity compared to the balanced diet and the high-lipid-low-carbohydrate diet.
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Affiliation(s)
- Seungmin Song
- Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul 03760, Republic of Korea
- Department of Nutritional Science and Food Management, Ewha Womans University, Seoul 03760, Republic of Korea
| | - Jinyoung Shon
- Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul 03760, Republic of Korea
- Department of Nutritional Science and Food Management, Ewha Womans University, Seoul 03760, Republic of Korea
| | - Woo-ri Yang
- Hyundai Greenfood Greating Laboratory, Yongin-si 16827, Republic of Korea
| | - Han-Bit Kang
- Hyundai Greenfood Greating Laboratory, Yongin-si 16827, Republic of Korea
| | - Keun-Ha Kim
- Hyundai Greenfood Greating Laboratory, Yongin-si 16827, Republic of Korea
| | - Ju-Yeon Park
- Hyundai Greenfood Greating Laboratory, Yongin-si 16827, Republic of Korea
| | - Sanghoo Lee
- SCL Healthcare Inc., Yongin-si 16954, Republic of Korea
| | - Sae Yun Baik
- Hanaro Medical Foundation, Seoul 03159, Republic of Korea
| | - Kyoung-Ryul Lee
- SCL Healthcare Inc., Yongin-si 16954, Republic of Korea
- Hanaro Medical Foundation, Seoul 03159, Republic of Korea
| | - Yoon Jung Park
- Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul 03760, Republic of Korea
- Department of Nutritional Science and Food Management, Ewha Womans University, Seoul 03760, Republic of Korea
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Gou W, Miao Z, Deng K, Zheng JS. Nutri-microbiome epidemiology, an emerging field to disentangle the interplay between nutrition and microbiome for human health. Protein Cell 2023; 14:787-806. [PMID: 37099800 PMCID: PMC10636640 DOI: 10.1093/procel/pwad023] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 04/02/2023] [Indexed: 04/28/2023] Open
Abstract
Diet and nutrition have a substantial impact on the human microbiome, and interact with the microbiome, especially gut microbiome, to modulate various diseases and health status. Microbiome research has also guided the nutrition field to a more integrative direction, becoming an essential component of the rising area of precision nutrition. In this review, we provide a broad insight into the interplay among diet, nutrition, microbiome, and microbial metabolites for their roles in the human health. Among the microbiome epidemiological studies regarding the associations of diet and nutrition with microbiome and its derived metabolites, we summarize those most reliable findings and highlight evidence for the relationships between diet and disease-associated microbiome and its functional readout. Then, the latest advances of the microbiome-based precision nutrition research and multidisciplinary integration are described. Finally, we discuss several outstanding challenges and opportunities in the field of nutri-microbiome epidemiology.
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Affiliation(s)
- Wanglong Gou
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- Research Center for Industries of the Future, Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310030, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, China
| | - Zelei Miao
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- Research Center for Industries of the Future, Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310030, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, China
| | - Kui Deng
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- Research Center for Industries of the Future, Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310030, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, China
| | - Ju-Sheng Zheng
- Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China
- Research Center for Industries of the Future, Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310030, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, China
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26
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Zhang S, Chen S, He K, Liu J, Su X, Li W, Ma J, Cheng C, Ouyang R, Mu Y, Zheng L, Cai J, Feng Y, Zeng F, Peng L, Ye Y. The Interaction of Dietary Patterns and Genetic Variants on the Risk of Cardiovascular Diseases in Chinese Patients with Type 2 Diabetes. Mol Nutr Food Res 2023; 67:e2300332. [PMID: 37712112 DOI: 10.1002/mnfr.202300332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 08/09/2023] [Indexed: 09/16/2023]
Abstract
SCOPE Diabetes is an important risk factor for cardiovascular disease (CVD), which in turn is the most common and serious complication of diabetes. This study analyzes dietary patterns and single nucleotide polymorphisms (SNPs) in 543 diabetes patients with new-onset cardiovascular events and 461 diabetic patients without. METHODS AND RESULTS SNPs are determined and analyzed using real time PCR and gene chip method. Factor analysis and logistic regression are used to determine dietary patterns and evaluate the level of associations and interaction effects, respectively. The legumes and edible fungi pattern and vegetable pattern show a significant negative correlation with complication risk. ADIPOQ rs37563 and legumes and edible fungi pattern have a significant interactive effect on disease, and patients with a high score of C polymorphism genotype (GC + CC) have a lower risk of disease. 5-10-Methylenetetrahydrofolate reductase (MTHFR) rs1801131 and vegetable pattern have a borderline interaction effect on disease, and those patients with TT genotype have a lower risk of disease. CONCLUSION These findings provide new insights into the role of the interactive protection of dietary patterns and SNPs. And participants with specific alleles show a lower risk of cardiovascular complications.
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Affiliation(s)
- Shiwen Zhang
- Department of Clinical Nutrition, The First Affiliated Hospital of Jinan University, No. 613 Huangpu Road West, Guangzhou, 510630, China
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, China
| | - Shiyun Chen
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, China
| | - Kaiyin He
- Department of Clinical Nutrition, The First Affiliated Hospital of Jinan University, No. 613 Huangpu Road West, Guangzhou, 510630, China
| | - Jiazi Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, China
| | - Xin Su
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, China
| | - Wanlin Li
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, China
| | - Junrong Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, China
| | - Chen Cheng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, China
| | - RuiQing Ouyang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, China
| | - Yingjun Mu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, China
| | - Lu Zheng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, China
| | - Jun Cai
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, China
| | - Yonghui Feng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, China
| | - Fangfang Zeng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, China
| | - Longyun Peng
- Department of Cardiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, China
| | - Yanbin Ye
- Department of Clinical Nutrition, The First Affiliated Hospital of Jinan University, No. 613 Huangpu Road West, Guangzhou, 510630, China
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Lambert K, Rinninella E, Biruete A, Sumida K, Stanford J, Raoul P, Mele MC, Wang AYM, Mafra D. Targeting the Gut Microbiota in Kidney Disease: The Future in Renal Nutrition and Metabolism. J Ren Nutr 2023; 33:S30-S39. [PMID: 37632511 PMCID: PMC10872791 DOI: 10.1053/j.jrn.2022.12.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/05/2022] [Accepted: 12/10/2022] [Indexed: 08/28/2023] Open
Abstract
There is increasing interest in the therapeutic potential of manipulating the gut microbiome of patients with chronic kidney disease (CKD). This is because there is a substantial deviation from a balanced gut microbiota profile in CKD, with many deleterious downstream effects. Nutritional interventions such as plant-based diets with reduced animal protein intake and the use of probiotics, prebiotics, and synbiotics may alter the microbiome. This article aims to briefly describe what is known about the gut microbiome in patients with CKD, factors contributing to gut dysbiosis, and outline important evidence gaps. Future potential therapies, including restoring the microbiota with food and microbiota-based and metabolomic-based therapies, are also discussed.
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Affiliation(s)
- Kelly Lambert
- School of Medical, Indigenous, and Health Sciences, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, New South Wales, Australia.
| | - Emanuele Rinninella
- Clinical Nutrition Unit, Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy; Department of Translational Medicine and Surgery, Catholic University of the Sacred Heart, Rome, Italy
| | - Annabel Biruete
- Department of Nutrition Science, Purdue University, West Lafayette, Indiana, USA, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Keiichi Sumida
- Division of Nephrology, Department of Medicine, University of Tennessee Health Science Center, Tennessee
| | - Jordan Stanford
- School of Medical, Indigenous, and Health Sciences, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, New South Wales, Australia
| | - Pauline Raoul
- Clinical Nutrition Unit, Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Maria Cristina Mele
- Clinical Nutrition Unit, Department of Medical and Surgical Sciences, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Angela Yee-Moon Wang
- Department of Medicine, Queen Mary Hospital, The University of Hong Kong, Hong Kong SAR, China
| | - Denise Mafra
- Professor, Graduate Program in Nutrition Sciences, Fluminense Federal University, Niterói, Rio de Janeiro, Brazil
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28
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Cai X, Xue Z, Zeng FF, Tang J, Yue L, Wang B, Ge W, Xie Y, Miao Z, Gou W, Fu Y, Li S, Gao J, Shuai M, Zhang K, Xu F, Tian Y, Xiang N, Zhou Y, Shan PF, Zhu Y, Chen YM, Zheng JS, Guo T. Population serum proteomics uncovers a prognostic protein classifier for metabolic syndrome. Cell Rep Med 2023; 4:101172. [PMID: 37652016 PMCID: PMC10518601 DOI: 10.1016/j.xcrm.2023.101172] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 07/31/2023] [Accepted: 08/03/2023] [Indexed: 09/02/2023]
Abstract
Metabolic syndrome (MetS) is a complex metabolic disorder with a global prevalence of 20%-25%. Early identification and intervention would help minimize the global burden on healthcare systems. Here, we measured over 400 proteins from ∼20,000 proteomes using data-independent acquisition mass spectrometry for 7,890 serum samples from a longitudinal cohort of 3,840 participants with two follow-up time points over 10 years. We then built a machine-learning model for predicting the risk of developing MetS within 10 years. Our model, composed of 11 proteins and the age of the individuals, achieved an area under the curve of 0.774 in the validation cohort (n = 242). Using linear mixed models, we found that apolipoproteins, immune-related proteins, and coagulation-related proteins best correlated with MetS development. This population-scale proteomics study broadens our understanding of MetS and may guide the development of prevention and targeted therapies for MetS.
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Affiliation(s)
- Xue Cai
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Zhangzhi Xue
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China
| | - Fang-Fang Zeng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510080, China
| | - Jun Tang
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Liang Yue
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
| | - Bo Wang
- Westlake Omics (Hangzhou) Biotechnology Co., Ltd., No. 1 Yunmeng Road, Cloud Town, Xihu District, Hangzhou, Zhejiang 310024, China
| | - Weigang Ge
- Westlake Omics (Hangzhou) Biotechnology Co., Ltd., No. 1 Yunmeng Road, Cloud Town, Xihu District, Hangzhou, Zhejiang 310024, China
| | - Yuting Xie
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
| | - Zelei Miao
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Wanglong Gou
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Yuanqing Fu
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Sainan Li
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
| | - Jinlong Gao
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
| | - Menglei Shuai
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Ke Zhang
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Fengzhe Xu
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Yunyi Tian
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China
| | - Nan Xiang
- Westlake Omics (Hangzhou) Biotechnology Co., Ltd., No. 1 Yunmeng Road, Cloud Town, Xihu District, Hangzhou, Zhejiang 310024, China
| | - Yan Zhou
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China
| | - Peng-Fei Shan
- Department of Endocrinology, the Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, Zhejiang 310009, China
| | - Yi Zhu
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China.
| | - Yu-Ming Chen
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - Ju-Sheng Zheng
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China.
| | - Tiannan Guo
- Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China; School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China; Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang 310024, China; Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310024, China.
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Lima MDC, do Nascimento HMA, da Silva JYP, de Brito Alves JL, de Souza EL. Evidence for the Beneficial Effects of Brazilian Native Fruits and Their By-Products on Human Intestinal Microbiota and Repercussions on Non-Communicable Chronic Diseases-A Review. Foods 2023; 12:3491. [PMID: 37761200 PMCID: PMC10527964 DOI: 10.3390/foods12183491] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/14/2023] [Accepted: 09/18/2023] [Indexed: 09/29/2023] Open
Abstract
Non-communicable chronic diseases (NCDs) are the most widespread cause of mortality worldwide. Intestinal microbiota balance can be altered by changes in the abundance and/or diversity of intestinal microbiota, indicating a role of intestinal microbiota in NCD development. This review discusses the findings of in vitro studies, pre-clinical studies and clinical trials on the effects of Brazilian native fruits, their by-products, as well as their bioactive compounds on human intestinal microbiota and NCD. The major bioactive compounds in Brazilian native fruits and their by-products, and the impacts of their administration on outcomes linked to intestinal microbiota modulation are discussed. Mechanisms of intestinal microbiota affecting NCD could be linked to the modulation of absorption and energy balance, immune and endocrine systems, and inflammatory response. Brazilian native fruits, such as acerola, açaí, baru, buriti, guava, jabuticaba, juçara, and passion fruit, have several bioactive compounds, soluble and insoluble fibers, and a variety of phenolic compounds, which are capable of changing these key mechanisms. Brazilian native fruits and their by-products can help to promote positive intestinal and systemic health benefits by driving alterations in the composition of the human intestinal microbiota, and increasing the production of distinct short-chain fatty acids and phenolic metabolites, thereby enhancing intestinal integrity and homeostasis. Evidence from available literature shows that the modulatory impacts of Brazilian native fruits and their by-products on the composition and metabolic activity of the intestinal microbiota could improve several clinical repercussions associated with NCD, reinforcing the influence of intestinal microbiota in extra-intestinal outcomes.
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Affiliation(s)
| | | | | | | | - Evandro Leite de Souza
- Department of Nutrition, Health Science Center, Federal University of Paraíba, João Pessoa 58051-900, PB, Brazil; (M.d.C.L.); (H.M.A.d.N.); (J.Y.P.d.S.); (J.L.d.B.A.)
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Aljuraiban GS, Algabsani SS, Sabico S, AlShammari S, Aljazairy EA, AL-Musharaf S. Types of fiber and gut microbiota composition and diversity among arab females. Saudi J Biol Sci 2023; 30:103767. [PMID: 37609544 PMCID: PMC10440561 DOI: 10.1016/j.sjbs.2023.103767] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 07/27/2023] [Accepted: 07/29/2023] [Indexed: 08/24/2023] Open
Abstract
Objectives Dietary fiber is recognized as an important nutrient for gut health. However, research on the relations of different types of fibers (soluble and insoluble) to the human microbiota health is limited. This study aimed to identify whether higher habitual intake of soluble and/or insoluble fiber have a different influence on the composition, diversity, and abundance of microbiota. Methods We examined the fecal microbial composition of 92 healthy females aged 18 and above using the novel shotgun metagenomics sequencing technique. The habitual fiber intake was determined using the Saudi food frequency questionnaire. Pearson's correlation was used for the correlations between total, soluble, and insoluble fiber and gut microbiota. α- and β-diversities were applied to acquire the distinctions in the relative abundances of bacterial taxa. Results Our findings show that higher dietary fiber, particularly insoluble fiber, was significantly correlated with the abundances of Bacteroides_u_s, Bacteroides uniformis, and Lactobacillus acidophilus (r = 0.26, 0.29, 0.26, p-value < 0.05, respectively). Non-significant difference was noted in the microbial α-diversity and β-diversity in low and high soluble/insoluble dietary fiber. Conclusions Current findings suggest that insoluble dietary-fiber intake is favorably correlated with the health of the human gut microbiota. However, further investigations are necessary to identify the effect of types of fiber on the specific species identified in this study.
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Affiliation(s)
- Ghadeer S. Aljuraiban
- Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11362, Saudi Arabia
| | - Sarah S. Algabsani
- Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11362, Saudi Arabia
| | - Shaun Sabico
- Chair for Biomarkers of Chronic Diseases, Biochemistry Department, College of Science, King Saud University, 11451 Riyadh, Saudi Arabia
| | - Salem AlShammari
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11362, Saudi Arabia
| | - Esra'a A. Aljazairy
- Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11362, Saudi Arabia
| | - Sara AL-Musharaf
- Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11362, Saudi Arabia
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Pan S, Lin Z, Yao T, Guo X, Xu T, Sheng X, Song X, Chen Z, Wei W, Yan Y, Hu Y. Global burden of non-communicable chronic diseases associated with a diet low in fruits from 1990 to 2019. Front Nutr 2023; 10:1202763. [PMID: 37693247 PMCID: PMC10491017 DOI: 10.3389/fnut.2023.1202763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Accepted: 08/10/2023] [Indexed: 09/12/2023] Open
Abstract
Background The aim of this study was to assess the global burden of disease from non-communicable chronic diseases (NCD) due to diet low in fruits from 1990 to 2019. Methods Based on data from the Global Burden of Disease (GBD) 2019, the global burden of disease due to diet low in fruits was analyzed for each country or region, disaggregated by disease type, age, sex, and year. The number of deaths and disability-adjusted life years (DALYs), population attributable fraction (PAF), age-standardized mortality rate (ASMR) and age-standardized DALY rate (ASDR) were calculated, and the average annual percentage change (AAPC) was calculated to describe trends in ASMR and ASDR from 1990 to 2019. Results From 1990 to 2019, the number of deaths and DALYs due to diet low in fruits increased by 31.5 and 27.4%, respectively. Among the tertiary diseases, ischemic heart disease, stroke, and diabetes and kidney disease were the top three contributors to the global increase in deaths and DALYs. However, both ASMR and ASDR showed a decreasing trend. The fastest decline in ASMR and ASDR was in stroke, with AAPC of -2.13 (95% CI: -2.22, -2.05, p < 0.05) and -0.56 (95% CI: -0.62, -0.51, p < 0.05), respectively. For GBD regions, high PAF occurred mainly in South Asia, Oceania, and sub-Saharan Africa. Age-specific PAF for stroke and ischemic heart disease death attributable to diet low in fruits was significantly negatively associated with age. Diet low in fruits related ASMR and ASDR showed an M-shaped relationship with the socio-demographic index (SDI), but with an overall decreasing trend. Conclusion The number of deaths and DALYs due to diet low in fruits continues to increase. Therefore, early nutritional interventions should be implemented by the relevant authorities to reduce the burden of diseases caused by diet low in fruits.
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Affiliation(s)
- Shijie Pan
- Department of Stomatology, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Zhihan Lin
- Department of Stomatology, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Teng Yao
- Department of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Xiaoli Guo
- Department of Stomatology, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Tongtong Xu
- Department of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Xinyan Sheng
- Department of Stomatology, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Xi Song
- Department of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Zuhai Chen
- Department of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Wanting Wei
- Department of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Yizhong Yan
- Department of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
- Key Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, Shihezi, Xinjiang, China
- Key Laboratory of Xinjiang Endemic and Ethnic Diseases (Ministry of Education), School of Medicine, Shihezi University, Shihezi, Xinjiang, China
- Key Laboratory of Preventive Medicine, Shihezi University, Shihezi, Xinjiang, China
| | - Yunhua Hu
- Department of Preventive Medicine, School of Medicine, Shihezi University, Shihezi, Xinjiang, China
- Key Laboratory for Prevention and Control of Emerging Infectious Diseases and Public Health Security, The Xinjiang Production and Construction Corps, Shihezi, Xinjiang, China
- Key Laboratory of Xinjiang Endemic and Ethnic Diseases (Ministry of Education), School of Medicine, Shihezi University, Shihezi, Xinjiang, China
- Key Laboratory of Preventive Medicine, Shihezi University, Shihezi, Xinjiang, China
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Farag HFM, Elrewany E, Abdel-Aziz BF, Sultan EA. Prevalence and predictors of undiagnosed type 2 diabetes and pre-diabetes among adult Egyptians: a community-based survey. BMC Public Health 2023; 23:949. [PMID: 37231362 DOI: 10.1186/s12889-023-15819-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 05/05/2023] [Indexed: 05/27/2023] Open
Abstract
BACKGROUND The global prevalence of abnormal glycemic level comprising diabetes mellitus (DM) and pre-diabetes (PDM) is rapidly increasing with special concern for the entity silent or undiagnosed diabetes; those unaware of their condition. Identification of people at risk became much easier with the use of risk charts than the traditional methods. The current study aimed to conduct a community-based screening for T2DM to estimate the prevalence of undiagnosed DM and to assess the AUSDRISK Arabic version as a predictive tool in an Egyptian context. METHODS A cross-sectional study was conducted among 719 Adults aging 18 years or more and not known to be diabetics through a population-based household survey. Each participant was interviewed to fill demographic and medical data as well as the AUSDRISK Arabic version risk score and undergo testing for fasting plasma glucose (FPG) and oral glucose tolerance test (OGTT). RESULTS The prevalence of DM and PDM were 5% and 21.7% respectively. The multivariate analysis revealed that age, being physically inactive, history of previous abnormal glycemic level and waist circumference were the predictors for having abnormal glycemic level among the studied participants. At cut off points ≥ 13 and ≥ 9, the AUSDRISK respectively discriminated DM [sensitivity (86.11%), specificity (73.35%), and area under the curve (AUC): 0.887, 95% CI: 0.824-0.950] and abnormal glycemic level [sensitivity (80.73%), specificity (58.06%), and AUC: 0.767, 95% CI: 0.727-0.807], p < 0.001. CONCLUSIONS Overt DM just occupies the top of an iceberg, its unseen big population have undiagnosed DM, PDM or been at risk of T2DM because of sustained exposure to the influential risk factors. The AUSDRISK Arabic version was proved to be sensitive and specific tool to be used among Egyptians as a screening tool for the detection of DM or abnormal glycemic level. A prominent association has been demonstrated between AUSDRISK Arabic version score and the diabetic status.
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Affiliation(s)
- Hassan Farag Mohamed Farag
- Department of Tropical Health, High Institute of Public Health, Alexandria University, Alexandria, Egypt
| | - Ehab Elrewany
- Department of Tropical Health, High Institute of Public Health, Alexandria University, Alexandria, Egypt
| | - Basem Farouk Abdel-Aziz
- Department of Health Administration and Behavioral Sciences, High Institute of Public Health, Alexandria University, Alexandria, Egypt
| | - Eman Anwar Sultan
- Department of Community Medicine, Faculty of Medicine, Alexandria University, Alexandria, Egypt.
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33
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Liu Y, Wang M, Li W, Gao Y, Li H, Cao N, Hao W, Zhao L. Differences in gut microbiota and its metabolic function among different fasting plasma glucose groups in Mongolian population of China. BMC Microbiol 2023; 23:102. [PMID: 37060052 PMCID: PMC10105465 DOI: 10.1186/s12866-023-02852-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 04/05/2023] [Indexed: 04/16/2023] Open
Abstract
BACKGROUND Many studies reported the association between gut microbiota and type 2 diabetes mellitus (T2D), but it is still unclear which bacterial genus plays a key role and how the metabolic function of gut microbiota changes in the occurrence and development of T2D. Besides, there is a high diabetic prevalence in Mongolian population, which may be partly affected by their high calorie diet. This study identified the main bacterial genus influencing T2D in Mongolian population, and analyzed the changes of metabolic function of gut microbiome. The association between dietary factors and the relative abundance of main bacterial genus and its metabolic function was also studied. METHODS Dietary surveys and gut microbiota test were performed on 24 Mongolian volunteers that were divided into T2D (6 cases), PRET2D (6 cases) and Control group (12 cases) according to fasting plasma glucose (FPG) values. The relative abundance and metabolic function of gut microbiome from their fecal samples were measured by metagenomic analysis. Statistic method was used to evaluate the association between dietary factors and the relative abundance of the main bacterial genus or its metabolic function. RESULTS This study found that the Clostridium genus may be one of the key bacterial genera affecting the process of T2D. First, the relative abundance of Clostridium genus was significantly different among the three groups. Second, there was a higher relative abundance of metabolic enzymes of gut bacteria in PRET2D and T2D group than that in Control group. Third, a strong correlation between Clostridium genus and many metabolic enzymes was uncovered, many of which may be produced by the Clostridium. Last, carotene intake daily was negatively correlated with the Clostridium but positively correlated with tagaturonate reductase catalyzing interconversions of pentose and glucuronate. CONCLUSIONS The gut Clostridium genus may play an important role in the development of T2D and it could be a potential biomarker for T2D in Mongolian population. Meanwhile, the metabolic function of gut bacteria has changed during the early stage of T2D and the changes in carbohydrate, amino acid, lipid or energy metabolism of Clostridium genus may play a critical role. In addition, the carotene intake may affect reproduction and metabolic function of Clostridium genus.
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Affiliation(s)
- Yanchao Liu
- Department of Epidemiology, School of Public Health, Inner Mongolia Medical University, Inner Mongolia Autonomous Region, Hohhot, 010110, China
- Laboratory for Molecular Epidemiology in Chronic Diseases, Inner Mongolia Medical University, Inner Mongolia Autonomous Region, Hohhot, 010110, China
| | - Mingxiao Wang
- Cspc Zhongqi Pharmaceutical Technology (Shijiazhuang) Co., Ltd, Shijiazhuang, Hebei Province, 050035, China
| | - Wuyuntana Li
- Laboratory for Molecular Epidemiology in Chronic Diseases, Inner Mongolia Medical University, Inner Mongolia Autonomous Region, Hohhot, 010110, China
| | - Yumin Gao
- Department of Epidemiology, School of Public Health, Inner Mongolia Medical University, Inner Mongolia Autonomous Region, Hohhot, 010110, China
| | - Hailing Li
- Department of Epidemiology, School of Public Health, Inner Mongolia Medical University, Inner Mongolia Autonomous Region, Hohhot, 010110, China
| | - Ning Cao
- Department of Epidemiology, School of Public Health, Inner Mongolia Medical University, Inner Mongolia Autonomous Region, Hohhot, 010110, China
| | - Wenli Hao
- Laboratory for Molecular Epidemiology in Chronic Diseases, Inner Mongolia Medical University, Inner Mongolia Autonomous Region, Hohhot, 010110, China
| | - Lingyan Zhao
- Department of Epidemiology, School of Public Health, Inner Mongolia Medical University, Inner Mongolia Autonomous Region, Hohhot, 010110, China.
- Laboratory for Molecular Epidemiology in Chronic Diseases, Inner Mongolia Medical University, Inner Mongolia Autonomous Region, Hohhot, 010110, China.
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34
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Zhang Y, Wang Y, Zhang S, Zhang Y, Zhang Q. Complex Association Among Diet Styles, Sleep Patterns, and Obesity in Patients with Diabetes. Diabetes Metab Syndr Obes 2023; 16:749-767. [PMID: 36936444 PMCID: PMC10015945 DOI: 10.2147/dmso.s390101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 12/24/2022] [Indexed: 03/13/2023] Open
Abstract
Background Health risk factors (HRFs), including the adjustment of disturbed sleep patterns (including disorders and duration) and improvement of dietary intake, have become relatively novel and critical strategies to prevent the development of diabesity and treat diabetic complications. Objective We aimed to explore 1) whether there was an association between diet styles (including healthy and unhealthy diets) and diabesity; 2) whether sleep patterns could moderate this relationship; and 3) whether there was a complex interaction association between sleep patterns, diet styles, and diabesity. Methods The study was based on a national survey conducted by the China National Diabetic Chronic Complications Study Group, this study extracted data from some cities in Anhui Province and obtained basic and lifestyle information using a detailed questionnaire for analysis. The primary exposure was diet styles, and the outcomes were body mass index (BMI) and waist circumference (WC), while HbA1c and FBG and sleep patterns were moderators. Data were pooled using logistic regression and moderation analysis. Results The overall response rate was 92.0%. This study ultimately included 1765 participants. The mean age was 57.10 ± 10.0 years. Sociographically, participants with lower educational levels were more likely to have lower levels of WC (χ 2 = 2.73) and BMI (χ 2 = 3.47), were female (t=6.54), were more likely to have lower educational levels (F=13.78) and were older (F=23.75), were more likely to have higher detection rates of sleep disorders and were more likely to have other HRFs (walking, SSBs, HbA1c and TG). Additionally, diet styles were also significantly associated with BMI and WC. In the moderation analysis, SES (socioeconomic status) also affected the correlation between healthy diet style, sleep disorders and WC (β=0.20), neither in BMI nor unhealthy diet style in BMI and WC; the combination effect between diet styles, sleep patterns and HbA1c was associated with WC and BMI. Conclusion Complex associations and interactions were found between diet styles, sleep patterns, HbA1c, and diabesity. Therefore, it is necessary to understand the dietary pattern and other HRFS that cause diabesity, so as to strengthen further preventive measures. These results can provide some theoretical basis for the treatment of diabesity in the public health field.
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Affiliation(s)
- Yi Zhang
- Department of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, People’s Republic of China
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, People’s Republic of China
| | - Yanlei Wang
- Department of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, People’s Republic of China
| | - Shengwu Zhang
- Department of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, People’s Republic of China
| | - Yulin Zhang
- The Second Clinical Medical College, Anhui Medical University, Hefei, Anhui, 230032, People’s Republic of China
| | - Qiu Zhang
- Department of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, People’s Republic of China
| | - On behalf of the China National Diabetic Chronic Complications Study Group
- Department of Endocrinology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, People’s Republic of China
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, People’s Republic of China
- The Second Clinical Medical College, Anhui Medical University, Hefei, Anhui, 230032, People’s Republic of China
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35
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Dogra SK, Dardinier A, Mainardi F, Siegwald L, Bartova S, Le Roy C, Chou CJ. Application of Computational Data Modeling to a Large-Scale Population Cohort Assists the Discovery of Inositol as a Strain-Specific Substrate for Faecalibacterium prausnitzii. Nutrients 2023; 15:nu15061311. [PMID: 36986043 PMCID: PMC10051675 DOI: 10.3390/nu15061311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/24/2023] [Accepted: 03/01/2023] [Indexed: 03/30/2023] Open
Abstract
Faecalibacterium prausnitzii (F. prausnitzii) is a bacterial taxon in the human gut with anti-inflammatory properties, and this may contribute to the beneficial effects of healthy eating habits. However, little is known about the nutrients that enhance the growth of F. prausnitzii other than simple sugars and fibers. Here, we combined dietary and microbiome data from the American Gut Project (AGP) to identify nutrients that may be linked to the relative abundance of F. prausnitzii. Using a machine learning approach in combination with univariate analyses, we identified that sugar alcohols, carbocyclic sugar, and vitamins may contribute to F. prausnitzii growth. We next explored the effects of these nutrients on the growth of two F. prausnitzii strains in vitro and observed robust and strain-dependent growth patterns on sorbitol and inositol, respectively. In the context of a complex community using in vitro fermentation, neither inositol alone nor in combinations with vitamin B exerted a significant growth-promoting effect on F. prausnitzii, partly due to high variability among the fecal microbiota community from four healthy donors. However, the fecal communities that showed an increase in F. prausnitzii on inulin also responded with at least 60% more F. prausnitzii on any of inositol containing media than control. Future nutritional studies aiming to increase the relative abundance of F. prausnitzii should explore a personalized approach accounting for strain-level genetic variations and community-level microbiome composition.
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Affiliation(s)
- Shaillay Kumar Dogra
- Department of Gastrointestinal Health, Nestlé Institute of Health Sciences, Nestlé Research, CH-1000 Lausanne, Switzerland
| | - Adrien Dardinier
- Department of Gastrointestinal Health, Nestlé Institute of Health Sciences, Nestlé Research, CH-1000 Lausanne, Switzerland
| | - Fabio Mainardi
- Department of Data Sciences and Precision Nutrition, Nestlé Institute of Health Sciences, Nestlé Research, CH-1000 Lausanne, Switzerland
| | - Léa Siegwald
- Department of Data Sciences and Precision Nutrition, Nestlé Institute of Health Sciences, Nestlé Research, CH-1000 Lausanne, Switzerland
| | - Simona Bartova
- Department of Bioanalytics, Nestlé Institute of Food Safety and Analytical Sciences, Nestlé Research, CH-1000 Lausanne, Switzerland
| | - Caroline Le Roy
- Department of Gastrointestinal Health, Nestlé Institute of Health Sciences, Nestlé Research, CH-1000 Lausanne, Switzerland
| | - Chieh Jason Chou
- Department of Gastrointestinal Health, Nestlé Institute of Health Sciences, Nestlé Research, CH-1000 Lausanne, Switzerland
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36
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Li H, Xiao C, Wang F, Guo X, Zhou Z, Jiang Y. Blueberry-Mulberry Extract Alleviates Cognitive Impairment, Regulates Gut Metabolites, and Inhibits Inflammation in Aged Mice. Foods 2023; 12:foods12040860. [PMID: 36832936 PMCID: PMC9956669 DOI: 10.3390/foods12040860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 01/24/2023] [Accepted: 01/28/2023] [Indexed: 02/22/2023] Open
Abstract
Cognitive impairment is associated with aging; however, the underlying mechanism remains unclear. Our previous study found that polyphenol-rich blueberry-mulberry extract (BME) had an antioxidant capability and effectively alleviated cognitive impairment in a mouse model of Alzheimer's disease. Thus, we hypothesized that BME would improve cognitive performance in naturally aging mice and assessed its effects on related signaling pathways. Eighteen-month-old C57BL/6J mice were gavaged with 300 mg/kg/d of BME for 6 weeks. Behavioral phenotypes, cytokine levels, tight junction protein levels, and the histopathology of the brain were assessed, and 16S ribosomal RNA sequencing and targeted metabolome analyses were used for gut microbiota and metabolite measurements. Our results showed that the cognitive performance of aged mice in the Morris water maze test was improved after BME treatment, neuronal loss was reduced, IL-6 and TNF-α levels in the brain and intestine were decreased, and the levels of intestinal tight junction proteins (ZO-1 and occludin) were increased. Further, 16S sequencing showed that BME significantly increased the relative abundance of Lactobacillus, Streptococcus, and Lactococcus and decreased the relative abundance of Blautia, Lachnoclostridium, and Roseburia in the gut. A targeted metabolomic analysis showed that BME significantly increased the levels of 21 metabolites, including α-linolenic acid, vanillic acid, and N-acetylserotonin. In conclusion, BME alters the gut microbiota and regulates gut metabolites in aged mice, which may contribute to the alleviation of cognitive impairment and to inflammation inhibition in both the brain and the gut. Our results provide a basis for future research on natural antioxidant intervention as a treatment strategy for aging-related cognitive impairment.
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Affiliation(s)
- Hui Li
- Institute of Environmental and Operational Medicine, Tianjin 300050, China
| | - Changhao Xiao
- Institute of Environmental and Operational Medicine, Tianjin 300050, China
- Key Laboratory of Food Nutrition and Safety, Ministry of Education, Tianjin University of Science and Technology, Tianjin 300457, China
| | - Feng Wang
- Institute of Environmental and Operational Medicine, Tianjin 300050, China
| | - Xuqi Guo
- Institute of Environmental and Operational Medicine, Tianjin 300050, China
| | - Zhongkai Zhou
- Key Laboratory of Food Nutrition and Safety, Ministry of Education, Tianjin University of Science and Technology, Tianjin 300457, China
| | - Yugang Jiang
- Institute of Environmental and Operational Medicine, Tianjin 300050, China
- Correspondence: ; Tel.: +86-139-2077-0716
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37
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Li L, Yang HY, Ma Y, Liang XH, Xu M, Zhang J, Huang ZX, Meng LH, Zhou J, Xian J, Suo YJ, Huang S, Cai JW, Meng BH, Zhao ZY, Lu JL, Xu Y, Wang TG, Li M, Chen YH, Wang WQ, Bi YF, Ning G, Shen FX, Hu RY, Chen G, Chen L, Chen LL, Deng HC, Gao ZN, Huo YN, Li Q, Liu C, Mu YM, Qin GJ, Shi LX, Su Q, Wan Q, Wang GX, Wang SY, Wang YM, Wu SL, Xu YP, Yan L, Yang T, Ye Z, Yu XF, Zhang YF, Zhao JJ, Zeng TS, Tang XL, Qin YF, Luo ZJ. Whole fresh fruit intake and risk of incident diabetes in different glycemic stages: a nationwide prospective cohort investigation. Eur J Nutr 2023; 62:771-782. [PMID: 36261730 PMCID: PMC9941276 DOI: 10.1007/s00394-022-02998-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 08/31/2022] [Indexed: 11/04/2022]
Abstract
PURPOSE Fruit intake is beneficial to several chronic diseases, but controversial in diabetes. We aimed to investigate prospectively the associations of whole fresh fruit intake with risk of incident type 2 diabetes (T2D) in subjects with different glucose regulation capacities. METHODS The present study included 79,922 non-diabetic participants aged ≥ 40 years from an ongoing nationwide prospective cohort in China. Baseline fruit intake information was collected by a validated food frequency questionnaire. Plasma HbA1c, fasting and 2 h post-loading glucose levels were measured at both baseline and follow-up examinations. Cox proportional hazards models were used to calculate hazard ratio (HR) and 95% confidence intervals (CI) for incident diabetes among participants with normal glucose tolerance (NGT) and prediabetes, after adjusted for multiple confounders. Restricted cubic spline analysis was applied for dose-response relation. RESULTS During a median 3.8-year follow-up, 5886 (7.36%) participants developed diabetes. Overall, we identified a linear and dose-dependent inverse association between dietary whole fresh fruit intake and risk of incident T2D. Each 100 g/d higher fruit intake was associated with 2.8% lower risk of diabetes (HR 0.972, 95%CI [0.949-0.996], P = 0.0217), majorly benefiting NGT subjects with 15.2% lower risk (HR 0.848, 95%CI [0.766-0.940], P = 0.0017), while not significant in prediabetes (HR 0.981, 95%CI 0.957-4.005, P = 0.1268). Similarly, the inverse association was present in normoglycemia individuals with a 48.6% lower risk of diabetes when consuming fruits > 7 times/week comparing to those < 1 time/week (HR 0.514, 95% CI [0.368-0.948]), but not in prediabetes (HR 0.883, 95% CI [0.762-1.023]). CONCLUSION These findings suggest that higher frequency and amount of fresh fruit intake may protect against incident T2D, especially in NGT, but not in prediabetes, highlighting the dietary recommendation of higher fresh fruit consumption to prevent T2D in normoglycemia population.
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Affiliation(s)
- Li Li
- grid.412594.f0000 0004 1757 2961Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021 Guangxi China
| | - Hai-Yan Yang
- grid.412594.f0000 0004 1757 2961Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021 Guangxi China
| | - Yan Ma
- grid.412594.f0000 0004 1757 2961Department of Ultrasonography, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Xing-Huan Liang
- grid.412594.f0000 0004 1757 2961Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021 Guangxi China
| | - Min Xu
- grid.16821.3c0000 0004 0368 8293Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China ,Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Jie Zhang
- grid.412594.f0000 0004 1757 2961Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021 Guangxi China
| | - Zhen-Xing Huang
- grid.412594.f0000 0004 1757 2961Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021 Guangxi China
| | - Li-Heng Meng
- grid.412594.f0000 0004 1757 2961Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021 Guangxi China
| | - Jia Zhou
- grid.412594.f0000 0004 1757 2961Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021 Guangxi China
| | - Jing Xian
- grid.412594.f0000 0004 1757 2961Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021 Guangxi China
| | - Ying-Jun Suo
- grid.412594.f0000 0004 1757 2961Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021 Guangxi China
| | - Song Huang
- grid.412594.f0000 0004 1757 2961Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021 Guangxi China
| | - Jin-Wei Cai
- grid.412594.f0000 0004 1757 2961Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021 Guangxi China
| | - Bi-Hui Meng
- grid.412594.f0000 0004 1757 2961Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021 Guangxi China
| | - Zhi-Yun Zhao
- grid.16821.3c0000 0004 0368 8293Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China ,Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Jie-Li Lu
- grid.16821.3c0000 0004 0368 8293Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China ,Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Yu Xu
- grid.16821.3c0000 0004 0368 8293Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China ,Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Tian-Ge Wang
- grid.16821.3c0000 0004 0368 8293Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China ,Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Mian Li
- grid.16821.3c0000 0004 0368 8293Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China ,Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Yu-Hong Chen
- grid.16821.3c0000 0004 0368 8293Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China ,Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Wei-Qing Wang
- grid.16821.3c0000 0004 0368 8293Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China ,Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Yu-Fang Bi
- grid.16821.3c0000 0004 0368 8293Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China ,Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Guang Ning
- grid.16821.3c0000 0004 0368 8293Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China ,Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - Fei-Xia Shen
- grid.414906.e0000 0004 1808 0918The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Ru-Ying Hu
- grid.433871.aZhejiang Provincial Center for Disease Control and Prevention, Zhejiang, China
| | - Gang Chen
- grid.256112.30000 0004 1797 9307Fujian Provincial Hospital, Fujian Medical University, Fuzhou, China
| | - Li Chen
- grid.452402.50000 0004 1808 3430Qilu Hospital of Shandong University, Jinan, China
| | - Lu-Lu Chen
- grid.33199.310000 0004 0368 7223Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hua-Cong Deng
- grid.452206.70000 0004 1758 417XThe First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Zheng-Nan Gao
- grid.452337.40000 0004 0644 5246Dalian Municipal Central Hospital, Dalian, China
| | - Ya-Nan Huo
- grid.415002.20000 0004 1757 8108Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, China
| | - Qiang Li
- grid.412463.60000 0004 1762 6325The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Chao Liu
- grid.412676.00000 0004 1799 0784Jiangsu Province Hospital on Integration of Chinese and Western Medicine, Nanjing, China
| | - Yi-Ming Mu
- grid.414252.40000 0004 1761 8894Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Gui-Jun Qin
- grid.412633.10000 0004 1799 0733The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Li-Xin Shi
- grid.452244.1Affiliated Hospital of Guiyang Medical College, Guiyang, China
| | - Qing Su
- grid.412987.10000 0004 0630 1330Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qin Wan
- grid.488387.8The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Gui-Xia Wang
- grid.430605.40000 0004 1758 4110The First Hospital of Jilin University, Changchun, China
| | - Shuang-Yuan Wang
- grid.16821.3c0000 0004 0368 8293Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China ,Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Shanghai, China
| | - You-Min Wang
- grid.412679.f0000 0004 1771 3402The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Sheng-Li Wu
- Karamay Municipal People’s Hospital, Xinjiang, China
| | - Yi-Ping Xu
- grid.16821.3c0000 0004 0368 8293Clinical Trials Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Li Yan
- grid.12981.330000 0001 2360 039XSun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Tao Yang
- grid.412676.00000 0004 1799 0784The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zhen Ye
- grid.433871.aZhejiang Provincial Center for Disease Control and Prevention, Zhejiang, China
| | - Xue-Feng Yu
- grid.33199.310000 0004 0368 7223Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yin-Fei Zhang
- grid.459667.fCentral Hospital of Shanghai Jiading District, Shanghai, China
| | - Jia-Jun Zhao
- grid.460018.b0000 0004 1769 9639Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China
| | - Tian-Shu Zeng
- grid.33199.310000 0004 0368 7223Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xu-Lei Tang
- grid.412643.60000 0004 1757 2902The First Hospital of Lanzhou University, Lanzhou, China
| | - Ying-Fen Qin
- Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021, Guangxi, China.
| | - Zuo-Jie Luo
- Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, No. 6 of Shuangyong Road, Nanning, 530021, Guangxi, China.
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Magro DO, Rossoni C, Saad-Hossne R, Santos A. INTERACTION BETWEEN FOOD PYRAMID AND GUT MICROBIOTA. A NEW NUTRITIONAL APPROACH. ARQUIVOS DE GASTROENTEROLOGIA 2023; 60:132-136. [PMID: 37194771 DOI: 10.1590/s0004-2803.202301000-15] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 12/08/2022] [Indexed: 05/18/2023]
Abstract
The food pyramid is a pre-established nutritional education tool. The integration between the intestinal microbiome, food groups, and SCFA-producing bacteria, which benefit from the ingestion of these foods, has the potential to further improve and innovate healthy eating. The diet-microbiome interaction needs to be incorporated into nutrition science, and the food pyramid might assist in this interaction and nutritional learning. Against this context, this brief communication proposes through the food pyramid, the interactions between the intestinal microbiota, food groups, and SCFAs-producing bacteria.
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Affiliation(s)
- Daniela O Magro
- Universidade Estadual de Campinas, Faculdade de Ciências Médicas, Campinas, SP, Brasil
| | - Carina Rossoni
- Instituto of Environmental Health, Faculty of Medicine (ISAMB), Universidade de Lisboa, Lisbon, Portugal
| | - Rogerio Saad-Hossne
- Universidade Estadual Paulista, Faculdade de Medicina, Departamento de Cirurgia, Botucatu, SP, Brasil
| | - Andrey Santos
- Universidade Estadual de Campinas, Faculdade de Ciências Médicas, Campinas, SP, Brasil
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Zhou YD, Liang FX, Tian HR, Luo D, Wang YY, Yang SR. Mechanisms of gut microbiota-immune-host interaction on glucose regulation in type 2 diabetes. Front Microbiol 2023; 14:1121695. [PMID: 36891383 PMCID: PMC9986296 DOI: 10.3389/fmicb.2023.1121695] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 01/31/2023] [Indexed: 02/22/2023] Open
Abstract
Intestinal absorption of food is one of the sources of glucose. Insulin resistance and impaired glucose tolerance caused by lifestyle and diet are the precursors of type 2 diabetes. Patients with type 2 diabetes have trouble controlling their blood sugar levels. For long-term health, strict glycemic management is necessary. Although it is thought to be well correlated with metabolic diseases like obesity, insulin resistance, and diabetes, its molecular mechanism is still not completely understood. Disturbed microbiota triggers the gut immune response to reshape the gut homeostasis. This interaction not only maintains the dynamic changes of intestinal flora, but also preserves the integrity of the intestinal barrier. Meanwhile, the microbiota establishes a systemic multiorgan dialog on the gut-brain and gut-liver axes, intestinal absorption of a high-fat diet affects the host's feeding preference and systemic metabolism. Intervention in the gut microbiota can combat the decreased glucose tolerance and insulin sensitivity linked to metabolic diseases both centrally and peripherally. Moreover, the pharmacokinetics of oral hypoglycemic medications are also influenced by gut microbiota. The accumulation of drugs in the gut microbiota not only affects the drug efficacy, but also changes the composition and function of them, thus may help to explain individual therapeutic variances in pharmacological efficacy. Regulating gut microbiota through healthy dietary patterns or supplementing pro/prebiotics can provide guidance for lifestyle interventions in people with poor glycemic control. Traditional Chinese medicine can also be used as complementary medicine to effectively regulate intestinal homeostasis. Intestinal microbiota is becoming a new target against metabolic diseases, so more evidence is needed to elucidate the intricate microbiota-immune-host relationship, and explore the therapeutic potential of targeting intestinal microbiota.
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Affiliation(s)
- Yu-Dian Zhou
- College of Acupuncture and Orthopedics, Hubei University of Chinese Medicine, Wuhan, Hebei, China
| | - Feng-Xia Liang
- College of Acupuncture and Orthopedics, Hubei University of Chinese Medicine, Wuhan, Hebei, China
| | - Hao-Ran Tian
- College of Acupuncture and Orthopedics, Hubei University of Chinese Medicine, Wuhan, Hebei, China
| | - Dan Luo
- Department of Respiratory Wuhan No.1 Hospital, Wuhan, Hebei, China
| | - Ya-Yuan Wang
- College of Acupuncture and Orthopedics, Hubei University of Chinese Medicine, Wuhan, Hebei, China
| | - Shu-Rui Yang
- College of Acupuncture and Orthopedics, Hubei University of Chinese Medicine, Wuhan, Hebei, China
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40
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Hajam TA, H S. Phytochemistry, biological activities, industrial and traditional uses of fig (Ficus carica): A review. Chem Biol Interact 2022; 368:110237. [DOI: 10.1016/j.cbi.2022.110237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 09/24/2022] [Accepted: 10/21/2022] [Indexed: 11/03/2022]
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Li R, Cai M, Qian ZM, Wang X, Zhang Z, Wang C, Wang Y, Arnold LD, Howard SW, Li H, Lin H. Ambient air pollution, lifestyle, and genetic predisposition associated with type 2 diabetes: findings from a national prospective cohort study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 849:157838. [PMID: 35934032 DOI: 10.1016/j.scitotenv.2022.157838] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 07/26/2022] [Accepted: 08/01/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND The combined effects of ambient air pollution, lifestyle, and genetic predisposition on incident Type 2 Diabetes (T2D) have not been well documented. METHODS A total of 263,733 participants without T2D at baseline were identified from the UK Biobank. Annual concentrations of five air pollutants were estimated using Land Use Regression, while a healthy lifestyle score (HLS) was constructed using 7 major lifestyle factors, and polygenic risk score (PRS) was generated using 73 genetic variants. Cox regression was used to determine the association between air pollution and incident T2D for different HLS/PRS categories. Potential HLS/PRS interactions and population attributable fraction (PAF) were also examined. RESULTS During a median follow-up of 11.94 years, 7827 (2.97 %) incident T2D cases were identified. Association between air pollution and incident T2D was stronger among those with higher HLS/PRS in a dose-response fashion. In addition, synergistic interactions between lifestyles and air pollution were observed. Lifestyle was the leading risk factor of T2D with a weighted PAF of 25.54 % (95 % CI: 19.22 %, 27.77 %) for intermediate HLS and 24.24 % (18.24 %, 26.36 %) due to unhealthy HLS. Overall, we estimated that about 25 % of T2D cases could be attributable to air pollution and associated interactions. CONCLUSIONS Associations between air pollution and T2D were stronger among individuals with unhealthier lifestyle on an additive interaction scale. Public health interventions that address both reduction of exposure to high levels of air pollution in addition to lifestyle changes may have more benefit on reducing T2D risk than focusing on lifestyle changes alone.
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Affiliation(s)
- Rui Li
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | - Miao Cai
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | - Zhengmin Min Qian
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, United States.
| | - Xiaojie Wang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | - Zilong Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
| | - Yuqin Wang
- Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou 510180, China.
| | - Lauren D Arnold
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, United States.
| | - Steven W Howard
- Department of Health Management and Policy, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, United States.
| | - Haitao Li
- Department of Social Medicine and Health Service Management, Health Science Center, Shenzhen University, Shenzhen, China.
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
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Liu T, Xiao W, Chen M, Mao R, San X, Peng Q, Zhao Z, Wang Q, Xie H, Deng Z, Li J. Aberrant amino acid metabolism promotes neurovascular reactivity in rosacea. JCI Insight 2022; 7:161870. [PMID: 36219476 DOI: 10.1172/jci.insight.161870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 10/05/2022] [Indexed: 12/15/2022] Open
Abstract
Rosacea is a chronic skin disorder characterized by abnormal neurovascular and inflammatory conditions on the central face. Despite increasing evidence suggesting that rosacea is associated with metabolic disorders, the role of metabolism in rosacea pathogenesis remains unknown. Here, via a targeted metabolomics approach, we characterized significantly altered metabolic signatures in patients with rosacea, especially for amino acid-related metabolic pathways. Among these, glutamic acid and aspartic acid were highlighted and positively correlated with the disease severity in patients with rosacea. We further demonstrated that glutamic acid and aspartic acid can facilitate the development of erythema and telangiectasia, typical features of rosacea, in the skin of mice. Mechanistically, glutamic acid and aspartic acid stimulated the production of vasodilation-related neuropeptides from peripheral neurons and keratinocytes and induced the release of nitric oxide from endothelial cells and keratinocytes. Interestingly, we provided evidence showing that doxycycline can improve the symptoms of patients with rosacea possibly by targeting the amino acid metabolic pathway. These findings reveal that abnormal amino acid metabolism promotes neurovascular reactivity in rosacea and raise the possibility of targeting dysregulated metabolism as a promising strategy for clinical treatment.
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Affiliation(s)
- Tangxiele Liu
- Department of Dermatology.,Hunan Key Laboratory of Aging Biology, and.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Wenqin Xiao
- Department of Dermatology.,Hunan Key Laboratory of Aging Biology, and.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Mengting Chen
- Department of Dermatology.,Hunan Key Laboratory of Aging Biology, and.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Rui Mao
- Department of Dermatology.,Hunan Key Laboratory of Aging Biology, and.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Xu San
- Department of Dermatology.,Hunan Key Laboratory of Aging Biology, and.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Qinqin Peng
- Department of Dermatology.,Hunan Key Laboratory of Aging Biology, and.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Zhixiang Zhao
- Department of Dermatology.,Hunan Key Laboratory of Aging Biology, and.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Qian Wang
- Hunan Binsis Biotechnology Co., Ltd, Changsha, China
| | - Hongfu Xie
- Department of Dermatology.,Hunan Key Laboratory of Aging Biology, and.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Zhili Deng
- Department of Dermatology.,Hunan Key Laboratory of Aging Biology, and.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Ji Li
- Department of Dermatology.,Hunan Key Laboratory of Aging Biology, and.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
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Brandão TO, Veiga ECDA, Levy RF, Damaso EL, Sandrim VC, Cavalli RC. Assessment by ABPM verified the presence of hypertension in patients with self-reported hypertension, pregnant women, as well as differences between ethnicities in women aged 39–39 years in the Ribeirão Preto cohort. Front Pharmacol 2022; 13:992595. [DOI: 10.3389/fphar.2022.992595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 10/20/2022] [Indexed: 11/10/2022] Open
Abstract
Introduction: Arterial hypertension is a global health problem and one of the main risk factors for cardiovascular diseases (CVD), and therefore for morbidity and mortality among adult men and women. Factors related to obstetric history, family history, sociodemographic characteristics, and lifestyle habits are known determinants of arterial hypertension.Methods: Case-control study of women belonging to the 1978/79 birth cohort conducted in the city of Ribeirão Preto/SP. Sociodemographic data, presence of comorbidities, maternal comorbidities, paternal comorbidities, comorbidities during pregnancy, and biometric and biophysical markers associated with blood pressure measured by 24-h ambulatory blood pressure monitoring (ABPM) were assessed in women aged 38–39 years. We want to study which variables of the previous sentence are related to the presence of hypertension measured by ABPM.Results: Data from 281 women were analyzed. Our results showed that ethnicity, a history of hypertension, and gestational hypertension reported by the women were significantly associated with the presence of hypertension measured by ABPM. Other factors such as marital status, educational level, comorbidities of the woman, paternal or maternal comorbidities, anthropometric measurements or serum levels of cardiovascular markers were not associated with the presence of hypertension measured by ABPM.Conclusion: We conclude that ethnicity, self-reported hypertension, and gestational hypertension are associated with arterial hypertension measured by ABPM.
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Efficacy and safety of dulaglutide compared with the first-line hypoglycemic drugs in Asian patients with type 2 diabetes: a systematic review and meta-analysis. Sci Rep 2022; 12:18281. [PMID: 36316432 PMCID: PMC9622886 DOI: 10.1038/s41598-022-22263-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 10/12/2022] [Indexed: 11/13/2022] Open
Abstract
To assess the efficacy and safety of dulaglutide in the treatment of Asian type 2 diabetes mellitus (T2DM), along with first-line hypoglycemic drugs. Systematic review and meta-analysis. Cochrane Library, Pubmed, Embase, and www.clinicaltrials.gov databases were searched from inception to September 27, 2022. The studies evaluating adults (≥ 18 years) undergoing dulaglutide (0.75 mg and 1.5 mg) and first-line hypoglycemic drugs were considered. There were only English languages. We used Stata 12.0 software to detect the risk of bias. 4 randomized controlled trials (RCTs), and 1 observational study. Both dulaglutide 0.75 mg dose group and 1.5 mg dose group could significantly reduce HbA1c [Dulaglutide 0.75 mg: WMD = - 0.20, 95% CI (- 0.28, - 0.11), P < 0.0001; Dulaglutide 1.5 mg: WMD = - 0.49, 95% CI (- 0.67, - 0.30), P < 0.0001] in Asian T2DM patients. In reducing fasting blood glucose (FBG) level, there was no significant difference observed in 2 dose groups. The body weight of patients in both dulaglutide dose groups was significantly reduced. In safety, the incidence of adverse events in the dulaglutide 0.75 mg dose group was slightly higher than that in the first-line drug group, but there was no statistically significant difference in the incidence of adverse events between the 1.5 mg dose group and the first-line drug group. Furthermore, the incidences of hypoglycemic events in both groups were higher than that in the first-line drug group. Two doses of dulaglutide showed better efficacy for Asian T2DM patients, but patients should be vigilant about the occurrence of hypoglycemia and gastrointestinal discomfort. However, more number and better quality of RCTs are suggested to confirm long-term safety and efficacy.
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Dhakal S, Dey M. Resistant starch type-4 intake alters circulating bile acids in human subjects. Front Nutr 2022; 9:930414. [PMID: 36337613 PMCID: PMC9631925 DOI: 10.3389/fnut.2022.930414] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 09/27/2022] [Indexed: 09/30/2023] Open
Abstract
Background Resistant starch (RS) type 4 (RS4) is a type of RS, a class of non-digestible prebiotic dietary fibers with a range of demonstrated metabolic health benefits to the host. On the other hand, bile acids (BA) have recently emerged as an important class of metabolic function mediators that involve host-microbiota interactions. RS consumption alters fecal and cecal BA in humans and rodents, respectively. The effect of RS intake on circulating BA concentrations remains unexplored in humans. Methods and results Using available plasma and stool samples from our previously reported double-blind, controlled, 2-arm crossover nutrition intervention trial (Clinicaltrials.gov: NCT01887964), a liquid-chromatography/mass-spectrometry-based targeted multiple reaction monitoring, and absolute quantifications, we assessed BA changes after 12 weeks of an average 12 g/day RS4-intake. Stool BA concentrations were lower post RS4 compared to the control, the two groups consuming similar macronutrients (n = 14/group). Partial least squares-discriminant analysis revealed distinct BA signatures in stool and plasma post interventions. The increased circulating BA concentrations were further investigated using linear mixed-effect modeling that controlled for potential confounders. A higher plasma abundance of several BA species post RS4 was observed (fold increase compared to control in parenthesis): taurocholic acid (1.92), taurodeoxycholic acid (1.60), glycochenodeoxycholic acid (1.58), glycodeoxycholic acid (1.79), and deoxycholic acid (1.77) (all, p < 0.05). Distinct microbiome ortholog-signatures were observed between RS4 and control groups (95% CI), derived using the Piphillin function-prediction algorithm and principal component analysis (PCA) of pre-existing 16S rRNA gene sequences. Association of Bifidobacterium adolescentis with secondary BA such as, deoxycholic acid (rho = 0.55, p = 0.05), glycodeoxycholic acid (rho = 0.65, p = 0.02), and taurodeoxycholic acid (rho = 0.56, p = 0.04) were observed in the RS4-group, but not in the control group (all, p > 0.05). Conclusion Our observations indicate a previously unknown in humans- RS4-associated systemic alteration of microbiota-derived secondary BA. Follow-up investigations of BA biosynthesis in the context of RS4 may provide molecular targets to understand and manipulate microbiome-host interactions.
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Affiliation(s)
| | - Moul Dey
- School of Health and Consumer Sciences, South Dakota State University, Brookings, SD, United States
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Wang Y, Xie W, Tian T, Zhang J, Zhu Q, Pan D, Xu D, Lu Y, Sun G, Dai Y. The Relationship between Dietary Patterns and High Blood Glucose among Adults Based on Structural Equation Modelling. Nutrients 2022; 14:nu14194111. [PMID: 36235763 PMCID: PMC9570980 DOI: 10.3390/nu14194111] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 09/23/2022] [Accepted: 09/29/2022] [Indexed: 11/06/2022] Open
Abstract
The aim of this study was to examine the association between dietary patterns and high blood glucose in Jiangsu province of China by using structural equation modelling (SEqM). Methods: Participants in this cross-sectional study were recruited through the 2015 Chinese Adult Chronic Disease and Nutrition Surveillance Program in Jiangsu province using a multistage stratified cluster random sampling method. Dietary patterns were defined by exploratory factor analysis (EFA). Confirmatory factor analysis (CFA) was used to test the fitness of EFA. SEqM was used to investigate the association between dietary patterns and high blood glucose. Results: After exclusion, 3137 participants with complete information were analysed for this study. The prevalence of high blood glucose was 9.3% and 8.1% in males and females, respectively. Two dietary patterns: the modern dietary pattern (i.e., high in red meats and its products, vegetables, seafood, condiments, fungi and algae, main grains and poultry; low in other grains, tubers and preserves), and the fruit−milk dietary pattern (i.e., high in milk and its products, fruits, eggs, nuts and seeds and pastry snacks, but low in vegetable oils) were established. Modern dietary pattern was found to be positively associated with high blood glucose in adults in Jiangsu province (multivariate logistic regression: OR = 1.561, 95% CI: 1.025~2.379; SEqM: β = 0.127, p < 0.05). Conclusion: The modern dietary pattern—high intake of red meats—was significantly associated with high blood glucose among adults in Jiangsu province of China, while the fruit−milk dietary pattern was not significantly associated with high blood glucose.
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Affiliation(s)
- Yuanyuan Wang
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, Nanjing 210009, China
| | - Wei Xie
- Institute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Ting Tian
- Institute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Jingxian Zhang
- Institute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Qianrang Zhu
- Institute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Da Pan
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, Nanjing 210009, China
| | - Dengfeng Xu
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, Nanjing 210009, China
| | - Yifei Lu
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, Nanjing 210009, China
| | - Guiju Sun
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, Nanjing 210009, China
| | - Yue Dai
- Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, Nanjing 210009, China
- Institute of Food Safety and Assessment, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
- Correspondence: ; Tel./Fax: +86-25-83759341
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Wu Y, He X, Zhou J, Wang Y, Yu L, Li X, Liu T, Luo J. Impact of healthy lifestyle on the risk of type 2 diabetes mellitus in southwest China: A prospective cohort study. J Diabetes Investig 2022; 13:2091-2100. [PMID: 36121185 DOI: 10.1111/jdi.13909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 08/18/2022] [Accepted: 09/05/2022] [Indexed: 11/30/2022] Open
Abstract
AIMS To explore the influence of nine healthy lifestyle factors on the risk of type 2 diabetes mellitus in adults in Guizhou, China. METHODS Data were obtained from a large population-based prospective cohort study in Guizhou Province, China. A total of 7,319 participants aged ≥18 years without diabetes at baseline were included in this study and were followed up from 2016 to 2020. A healthy lifestyle score was calculated based on the number of healthy lifestyle factors. RESULTS During an average of 7.1 person-years of follow-up, 764 participants were diagnosed with type 2 diabetes mellitus. Compared with those of participants who scored 0-3 for a healthy lifestyle, the hazard ratios (95% confidence intervals) of those who scored 4, 5, 6, and ≥7 were 0.676 (0.523-0.874), 0.599 (0.464-0.773), 0.512 (0.390-0.673), and 0.393 (0.282-0.550), respectively, showing a gradual downward trend (P for trend <0.01). More importantly, they had lower fasting and 2 h post-load plasma glucose levels and fewer changes in plasma glucose levels during follow-up. If ≥7 healthy lifestyle factors were maintained, 33.8% of incident diabetes cases could have been prevented. Never smoking was the strongest protective factor against type 2 diabetes mellitus. CONCLUSIONS A healthy lifestyle can effectively decrease plasma glucose levels and reduce the incidence of type 2 diabetes mellitus in adults in Guizhou, China. In addition, not smoking may be an effective way to prevent type 2 diabetes mellitus.
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Affiliation(s)
- Yanli Wu
- Guizhou Center for Disease Control and Prevention, Guiyang, China
| | - Xi He
- Department of Endocrinology and Metabolism, Guizhou Provincial People's Hospital, Guiyang, China
| | - Jie Zhou
- Guizhou Center for Disease Control and Prevention, Guiyang, China
| | - Yiying Wang
- Guizhou Center for Disease Control and Prevention, Guiyang, China
| | - Lisha Yu
- Guizhou Center for Disease Control and Prevention, Guiyang, China
| | - Xuejiao Li
- Guizhou Center for Disease Control and Prevention, Guiyang, China
| | - Tao Liu
- Guizhou Center for Disease Control and Prevention, Guiyang, China
| | - Jianhua Luo
- Department of Endocrinology and Metabolism, Guizhou Provincial People's Hospital, Guiyang, China
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Xiao C, Wang JT, Su C, Miao Z, Tang J, Ouyang Y, Yan Y, Jiang Z, Fu Y, Shuai M, Gou W, Xu F, Yu EYW, Liang Y, Liang X, Tian Y, Wang J, Huang F, Zhang B, Wang H, Chen YM, Zheng JS. Associations of dietary diversity with the gut microbiome, fecal metabolites, and host metabolism: results from 2 prospective Chinese cohorts. Am J Clin Nutr 2022; 116:1049-1058. [PMID: 36100971 PMCID: PMC9535526 DOI: 10.1093/ajcn/nqac178] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 05/28/2022] [Accepted: 06/21/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Dietary diversity is essential for human health. The gut ecosystem provides a potential link between dietary diversity, host metabolism, and health, yet this mechanism is poorly understood. OBJECTIVES Here, we aimed to investigate the relation between dietary diversity and the gut environment as well as host metabolism from a multiomics perspective. METHODS Two independent longitudinal Chinese cohorts (a discovery and a validation cohort) were included in the present study. Dietary diversity was evaluated with FFQs. In the discovery cohort (n = 1916), we performed shotgun metagenomic and 16S ribosomal ribonucleic acid (rRNA) sequencing to profile the gut microbiome. We used targeted metabolomics to quantify fecal and serum metabolites. The associations between dietary diversity and the microbial composition were replicated in the validation cohort (n = 1320). RESULTS Dietary diversity was positively associated with α diversity of the gut microbiota. We identified dietary diversity-related gut environment features, including the microbial structure (β diversity), 68 microbial genera, 18 microbial species, 8 functional pathways, and 13 fecal metabolites. We further found 332 associations of dietary diversity and related gut environment features with circulating metabolites. Both the dietary diversity and diversity-related features were inversely correlated with 4 circulating secondary bile acids. Moreover, 16 mediation associations were observed among dietary diversity, diversity-related features, and the 4 secondary bile acids. CONCLUSIONS These results suggest that high dietary diversity is associated with the gut microbial environment. The identified key microbes and metabolites may serve as hypotheses to test for preventing metabolic diseases.
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Affiliation(s)
- Congmei Xiao
- College of Life Sciences, Zhejiang University, Hangzhou, China,Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China
| | - Jia-ting Wang
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health; Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Chang Su
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China,Key Laboratory of Trace Element Nutrition, National Health Commission, Beijing, China
| | - Zelei Miao
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Jun Tang
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Yifei Ouyang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China,Key Laboratory of Trace Element Nutrition, National Health Commission, Beijing, China
| | - Yan Yan
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health; Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Zengliang Jiang
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Yuanqing Fu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Menglei Shuai
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Wanglong Gou
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Fengzhe Xu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Evan Y-W Yu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Key Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology & Biostatistics, School of Public Health, Southeast University, Nanjing, China,CAPHRI Care and Public Health Research Institute, School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands
| | - Yuhui Liang
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Xinxiu Liang
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Yunyi Tian
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Jiali Wang
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Feifei Huang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China,Key Laboratory of Trace Element Nutrition, National Health Commission, Beijing, China
| | - Bing Zhang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China,Key Laboratory of Trace Element Nutrition, National Health Commission, Beijing, China
| | - Huijun Wang
- Chinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China,Key Laboratory of Trace Element Nutrition, National Health Commission, Beijing, China
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Dietary fibre intake and risk of prediabetes in China: results from the Tianjin Chronic Low-grade Systemic Inflammation and Health (TCLSIH) Cohort Study. Br J Nutr 2022; 128:753-761. [PMID: 34544523 DOI: 10.1017/s0007114521003779] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
High dietary fibre intake has been associated with a lower risk of diabetes, but the association of dietary fibre with prediabetes is only speculative, especially in China, where the supportive data from prospective studies are lacking. This study aimed to examine the association between dietary fibre intake and risk of incident prediabetes among Chinese adults. We performed a prospective analysis in 18 085 participants of the Tianjin Chronic Low-grade Systemic Inflammation and Health cohort study who were free of diabetes, prediabetes, cancer and CVD at baseline. Dietary data were collected using a validated 100-item FFQ. Prediabetes was defined based on the American Diabetes Association diagnostic criteria. Cox proportional hazard models were used to estimate hazard ratios (HR) and 95 % CI. During 63 175 person-years of follow-up, 4139 cases of incident prediabetes occurred. The multivariable HR of prediabetes for the highest v. lowest quartiles were 0·85 (95 % CI 0·75, 0·98) (P for trend = 0·02) for total dietary fibre, 0·84 (95 % CI 0·74, 0·95) (P for trend < 0·01) for soluble fibre and 1·05 (95 % CI 0·93, 1·19) (P for trend = 0·38) for insoluble fibre. Fibre from fruits but not from cereals, beans and vegetables was inversely associated with prediabetes. Our results indicate that intakes of total dietary fibre, soluble fibre and fibre derived from fruit sources were associated with a lower risk of prediabetes.
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50
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Chen G, Su M, Chu X, Wei Y, Chen S, Zhou Y, Liu Z, Zhang Z. Plant-based diets and body composition in Chinese omnivorous children aged 6-9 years old: A cross-sectional study. Front Nutr 2022; 9:918944. [PMID: 35967769 PMCID: PMC9372333 DOI: 10.3389/fnut.2022.918944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 07/08/2022] [Indexed: 11/24/2022] Open
Abstract
Evidence suggests that plant-based diets are beneficial for alleviating metabolic diseases. Childhood is a crucial period for body growth and development. However, it is unknown whether adherence to a plant-based diet is related to a healthy body composition in children. We aimed to assess the relationship between a plant-based diet and body composition in children. A total of 452 Chinese children aged 6–9 years old participated in this cross-sectional study. Lean mass (LM), fat mass, and fat mass percentage (FMP) were assessed via dual-energy X-ray absorptiometry. An age- and sex-specific abdominal FMP ≥85th percentile was defined as abdominal obesity. Handgrip strength was measured using a hydraulic hand dynamometer. A validated 79-item food frequency questionnaire was used to collect dietary information. Overall plant-based diet index (PDI), healthful plant-based diet index (hPDI), and unhealthful plant-based diet index (uPDI) scores were calculated. After adjusting for potential covariates, a higher hPDI score (per 10-score increment) was associated with a higher LM in the android area (0.038 kg, 3.2%), gynoid area (0.048 kg, 1.9%), and trunk (0.102 kg, 1.2%) and with a lower FMP (1.18%) in the android area. In contrast, a higher uPDI score (per 10-score increment) was associated with a lower LM in the trunk (0.091 kg, 1.1%) and android area (0.023 kg, 1.9%) and with a higher FMP (0.74%) in the android area. No significant associations were observed between the overall PDI and body composition or abdominal obesity. After stratifying by sex, higher (vs. lower) hPDI scores was associated with lower abdominal obesity risk in girls and higher handgrip strength in boys. In conclusion, in this cross-sectional study, we found that stronger adherence to a healthful plant-based diet, and less adherence to an unhealthful plant-based diet was associated with better body composition in Chinese omnivorous children aged 6–9 years old. Our results highlight the need to distinguish between healthy and unhealthy plant foods within investigating how to obtain a healthy body composition in children.
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Affiliation(s)
- Gengdong Chen
- Department of Obstetrics, Foshan Institute of Fetal Medicine, Southern Medical University Affiliated Maternal & Child Health Hospital of Foshan, Foshan, China
| | - Mengyang Su
- Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Nutrition and Food Hygiene, School of Public Health, Southern Medical University, Guangzhou, China
| | - Xinwei Chu
- Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Nutrition and Food Hygiene, School of Public Health, Southern Medical University, Guangzhou, China
| | - Yuanhuan Wei
- Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Nutrition and Food Hygiene, School of Public Health, Southern Medical University, Guangzhou, China
| | - Shanshan Chen
- Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Nutrition and Food Hygiene, School of Public Health, Southern Medical University, Guangzhou, China
| | - Yingyu Zhou
- Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Nutrition and Food Hygiene, School of Public Health, Southern Medical University, Guangzhou, China
| | - Zhengping Liu
- Department of Obstetrics, Foshan Institute of Fetal Medicine, Southern Medical University Affiliated Maternal & Child Health Hospital of Foshan, Foshan, China
| | - Zheqing Zhang
- Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Nutrition and Food Hygiene, School of Public Health, Southern Medical University, Guangzhou, China
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