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Vanderpeet CL, Dorey ES, Neal ES, Mullins T, McIntyre DH, Callaway LK, Barrett HL, Dekker Nitert M, Cuffe JSM. Dietary Fibre Modulates Gut Microbiota in Late Pregnancy Without Altering SCFA Levels, and Propionate Treatement Has No Effect on Placental Explant Function. Nutrients 2025; 17:1234. [PMID: 40218992 PMCID: PMC11990268 DOI: 10.3390/nu17071234] [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: 02/28/2025] [Revised: 03/26/2025] [Accepted: 03/28/2025] [Indexed: 04/14/2025] Open
Abstract
Background/Objectives: Dietary fibre promotes health, partly by mediating gut microbiota and short-chain fatty acid (SCFA) production. Pregnancy alters the relationship between dietary composition and the gut microbiota, and it is unclear if fibre intake during late pregnancy alters the abundance of SCFA bacteria and circulating SFCA concentrations. The aim of this study was to determine the impact of dietary fibre on faecal microbiome composition and circulating concentrations of SCFA acetate, butyrate, and propionate in late pregnancy. We also aimed to assess the impact of propionate treatment on placental function using cultured placental explants. Methods: 16S rRNA gene amplicon sequencing was performed on faecal DNA collected at 28 weeks of gestation from participants enrolled in the SPRING cohort study consuming a low or adequate fibre diet. Circualting SCFA were assessed. Placental explants were treated with sodium propionate. Results: Fibre intake did not impact microbial diversity or richness but did impact the abundance of specific bacterial genera. Pregnant participants with low-fibre diets had a greater abundance of Bacteroides and Sutterella, and dietary fibre intake (mg/day) negatively correlated with genera, including Sutterella, Bilophila, and Bacteroides. SCFA concentrations did not differ between groups but circulating concentrations of acetate, propionate, and butyrate did correlate with the abundance of key bacterial genera. Propionate treatment of placental explants did not alter mRNA expression of fatty acid receptors, antioxidants, or markers of apoptosis, nor did it impact pAMPK levels. Conclusions: This study demonstrates that the impact of dietary fibre on SCFA concentrations in pregnant women is modest, although this relationship may be difficult to discern given that other dietary factors differed between groups. Furthermore, this study demonstrates that propionate does not impact key pathways in placental tissue, suggesting that previous associations between this SCFA and placental dysfunction may be due to other maternal factors.
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Affiliation(s)
- Chelsea L. Vanderpeet
- School of Biomedical Sciences, The University of Queensland, Brisbane, QLD 4072, Australia; (C.L.V.); (E.S.N.); (T.M.)
| | - Emily S. Dorey
- Mater Research Institute, The University of Queensland, South Brisbane, QLD 4101, Australia; (E.S.D.); (D.H.M.); (H.L.B.)
- Mater Hospital Brisbane, South Brisbane, QLD 4101, Australia
| | - Elliott S. Neal
- School of Biomedical Sciences, The University of Queensland, Brisbane, QLD 4072, Australia; (C.L.V.); (E.S.N.); (T.M.)
| | - Thomas Mullins
- School of Biomedical Sciences, The University of Queensland, Brisbane, QLD 4072, Australia; (C.L.V.); (E.S.N.); (T.M.)
| | - David H. McIntyre
- Mater Research Institute, The University of Queensland, South Brisbane, QLD 4101, Australia; (E.S.D.); (D.H.M.); (H.L.B.)
- Mater Hospital Brisbane, South Brisbane, QLD 4101, Australia
| | - Leonie K. Callaway
- Department of Obstetric Medicine, Royal Brisbane and Women’s Hospital, Herston, QLD 4059, Australia;
| | - Helen L. Barrett
- Mater Research Institute, The University of Queensland, South Brisbane, QLD 4101, Australia; (E.S.D.); (D.H.M.); (H.L.B.)
- Mater Hospital Brisbane, South Brisbane, QLD 4101, Australia
- Royal Hospital for Women, Randwick, NSW 2031, Australia
- Faculty of Medicine, University of New South Wales, Sydney, NSW 2033, Australia
| | - Marloes Dekker Nitert
- School of Chemistry & Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia;
| | - James S. M. Cuffe
- School of Biomedical Sciences, The University of Queensland, Brisbane, QLD 4072, Australia; (C.L.V.); (E.S.N.); (T.M.)
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Ruebel ML, Gilley SP, Yeruva L, Tang M, Frank DN, Garcés A, Figueroa L, Lan RS, Assress HA, Kemp JF, Westcott JLE, Hambidge KM, Shankar K, Krebs NF. Associations between maternal microbiome, metabolome and incidence of low-birth weight in Guatemalan participants from the Women First Trial. Front Microbiol 2024; 15:1456087. [PMID: 39473842 PMCID: PMC11518777 DOI: 10.3389/fmicb.2024.1456087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Accepted: 09/13/2024] [Indexed: 04/05/2025] Open
Abstract
Background Low birth weight (LBW; <2,500 g) affects approximately 15 to 20 percent of global births annually and is associated with suboptimal child development. Recent studies suggest a link between the maternal gut microbiome and poor obstetric and perinatal outcomes. The goal of this study was to examine relationships between maternal microbial taxa, fecal metabolites, and maternal anthropometry on incidence of LBW in resource-limited settings. Methods This was a secondary analysis of the Women First trial conducted in a semi-rural region of Guatemala. Maternal weight was measured at 12 and 34 weeks (wk) of gestation. Infant anthropometry measures were collected within 48 h of delivery. Maternal fecal samples at 12 and 34 weeks were used for microbiome (16S rRNA gene amplicon sequencing) and metabolomics analysis (34 wk). Linear mixed models using the MaAslin2 package were utilized to assess changes in microbiome associated with LBW. Predictive models using gradient boosted machines (XGBoost) were developed using the H2o.ai engine. Results No differences in β-diversity were observed at either time point between mothers with LBW infants relative to normal weight (NW) infants. Simpson diversity at 12 and 34 weeks was lower in mothers with LBW infants. Notable differences in genus-level abundance between LBW and NW mothers (p < 0.05) were observed at 12 weeks with increasing abundances of Barnesiella, Faecalibacterium, Sutterella, and Bacterioides. At 34 weeks, there were lower abundances of Magasphaera, Phascolarctobacterium, and Turicibacter and higher abundances of Bacteriodes, and Fusobacterium in mothers with LBW infants. Fecal metabolites related to bile acids, tryptophan metabolism and fatty acid related metabolites changed in mothers with LBW infants. Classification models to predict LBW based on maternal anthropometry and predicted microbial functions showed moderate performance. Conclusion Collectively, the findings indicate that alterations in the maternal microbiome and metabolome were associated with LBW. Future research should target functional and predictive roles of the maternal gut microbiome in infant birth outcomes including birthweight.
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Affiliation(s)
- Meghan L. Ruebel
- Microbiome and Metabolism Research Unit, USDA-ARS, Southeast Area USDA-ARS, Little Rock, AR, United States
- Arkansas Children's Nutrition Center, Little Rock, AR, United States
| | - Stephanie P. Gilley
- Department of Pediatrics, Section of Nutrition, University of Colorado School of Medicine, Aurora, CO, United States
| | - Laxmi Yeruva
- Microbiome and Metabolism Research Unit, USDA-ARS, Southeast Area USDA-ARS, Little Rock, AR, United States
- Arkansas Children's Nutrition Center, Little Rock, AR, United States
| | - Minghua Tang
- Department of Pediatrics, Section of Nutrition, University of Colorado School of Medicine, Aurora, CO, United States
| | - Daniel N. Frank
- Department of Medicine, Division of Infectious Disease, University of Colorado School of Medicine, Aurora, CO, United States
| | - Ana Garcés
- Maternal Infant Health Center, Instituto de Nutrición de Centro América y Panamá (INCAP), Guatemala City, Guatemala
| | - Lester Figueroa
- Maternal Infant Health Center, Instituto de Nutrición de Centro América y Panamá (INCAP), Guatemala City, Guatemala
| | - Renny S. Lan
- Arkansas Children's Nutrition Center, Little Rock, AR, United States
- Department of Pediatrics, Section of Developmental Nutrition, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Hailemariam Abrha Assress
- Arkansas Children's Nutrition Center, Little Rock, AR, United States
- Department of Pediatrics, Section of Developmental Nutrition, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Jennifer F. Kemp
- Department of Pediatrics, Section of Nutrition, University of Colorado School of Medicine, Aurora, CO, United States
| | - Jamie L. E. Westcott
- Department of Pediatrics, Section of Nutrition, University of Colorado School of Medicine, Aurora, CO, United States
| | - K. Michael Hambidge
- Department of Pediatrics, Section of Nutrition, University of Colorado School of Medicine, Aurora, CO, United States
| | - Kartik Shankar
- Department of Pediatrics, Section of Nutrition, University of Colorado School of Medicine, Aurora, CO, United States
| | - Nancy F. Krebs
- Department of Pediatrics, Section of Nutrition, University of Colorado School of Medicine, Aurora, CO, United States
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Iatcu OC, Hamamah S, Covasa M. Harnessing Prebiotics to Improve Type 2 Diabetes Outcomes. Nutrients 2024; 16:3447. [PMID: 39458444 PMCID: PMC11510484 DOI: 10.3390/nu16203447] [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: 09/18/2024] [Revised: 10/08/2024] [Accepted: 10/09/2024] [Indexed: 10/28/2024] Open
Abstract
The gut microbiota, a complex ecosystem of microorganisms in the human gastrointestinal tract (GI), plays a crucial role in maintaining metabolic health and influencing disease susceptibility. Dysbiosis, or an imbalance in gut microbiota, has been linked to the development of type 2 diabetes mellitus (T2DM) through mechanisms such as reduced glucose tolerance and increased insulin resistance. A balanced gut microbiota, or eubiosis, is associated with improved glucose metabolism and insulin sensitivity, potentially reducing the risk of diabetes-related complications. Various strategies, including the use of prebiotics like inulin, fructooligosaccharides, galactooligosaccharides, resistant starch, pectic oligosaccharides, polyphenols, β-glucan, and Dendrobium officinale have been shown to improve gut microbial composition and support glycemic control in T2DM patients. These prebiotics can directly impact blood sugar levels while promoting the growth of beneficial bacteria, thus enhancing glycemic control. Studies have shown that T2DM patients often exhibit a decrease in beneficial butyrate-producing bacteria, like Roseburia and Faecalibacterium, and an increase in harmful bacteria, such as Escherichia and Prevotella. This review aims to explore the effects of different prebiotics on T2DM, their impact on gut microbiota composition, and the potential for personalized dietary interventions to optimize diabetes management and improve overall health outcomes.
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Affiliation(s)
- Oana C. Iatcu
- Department of Biomedical Sciences, College of Medicine and Biological Science, University of Suceava, 720229 Suceava, Romania;
| | - Sevag Hamamah
- Department of Basic Medical Sciences, College of Osteopathic Medicine, Western University of Health Sciences, Pomona, CA 91766, USA;
- Department of Internal Medicine, Scripps Mercy Hospital, San Diego, CA 92103, USA
| | - Mihai Covasa
- Department of Biomedical Sciences, College of Medicine and Biological Science, University of Suceava, 720229 Suceava, Romania;
- Department of Basic Medical Sciences, College of Osteopathic Medicine, Western University of Health Sciences, Pomona, CA 91766, USA;
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Rong Q, Chen H, Chen Y, Xu M, Chen R, Li C. Potential mechanisms of gut microbiota influence on different types of vertigo: a bidirectional Mendelian randomization and mediation analysis. BMC Neurol 2024; 24:297. [PMID: 39192194 DOI: 10.1186/s12883-024-03805-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: 08/11/2023] [Accepted: 08/14/2024] [Indexed: 08/29/2024] Open
Abstract
BACKGROUND The relationship between gut microbiota and vertigo, specifically Benign Paroxysmal Vertigo (BPV) and Vertigo of Central (VC), remains underexplored. AIM AND HYPOTHESES This study aims to investigate the causal relationships between gut microbiota and two types of vertigo, BPV and VC. Additionally, the study seeks to explore the mediation effects of metabolic, inflammatory, and psychological factors on these relationships. We hypothesize that specific taxa of gut microbiota have a causal effect on the risk of developing BPV and VC. The mediation effects of HbA1c, obesity, major depression, and interleukin-18 levels significantly influence the relationships between gut microbiota and vertigo. METHOD Utilizing a bidirectional two-sample Mendelian randomization approach, this study investigated causal associations between gut microbiota and the two types of vertigo. A network MR assessed mediation effects of HbA1c, major depression, obesity, and interleukin-18 levels, with data sourced from several consortia, including MiBioGen. RESULTS Distinct gut microbiota displayed varying influences on BPV and VC risks. A total of ten taxa affect BPV. Among these, two taxa have an odds ratio (OR) greater than 1, including one class, one order. Conversely, eight taxa have an OR less than 1, encompassing four families, three genera, and one order. The OR for these taxa ranges from 0.693 to 0.930, with p-values between 0.006 and 0.048. For VC, eight taxa were found to have an impact. Five of these taxa exhibit an OR greater than 1, including four genera and one phylum. The OR for these taxa ranges from 1.229 to 2.179, with p-values from 0.000 to 0.046. The remaining three taxa have an OR less than 1, comprising one family and two genera, with an OR range of 0.445 to 0.792 and p-values ranging from 0.013 to 0.050. The mediation analysis for BPV shows that major depression, obesity, and HbA1c are key mediators between specific taxa and BPV. Major depression mediates 28.77% of the effect of family Rhodospirillaceae on BPV. Obesity mediates 13.90% of the effect of class Lentisphaeria/order Victivallales. HbA1c mediates 11.79% of the effect of genus Bifidobacterium, 11.36% of family Bifidobacteriaceae/order Bifidobacteriales. For VC, interleukin-18 levels and major depression are significant mediators. Interleukin-18 levels mediate 6.56% of the effect of phylum Actinobacteria. Major depression mediates 6.51% of the effect of genus Alloprevotella. CONCLUSION The study highlights potential causal links between gut microbiota and vertigo, emphasizing metabolic and psychological mediators. These insights underscore the therapeutic potential of targeting gut health in vertigo management.
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Affiliation(s)
- Qiongwen Rong
- Department of Neurology, The First Affiliated Hospital of Hainan Medical University, 31 Longhua Road Haikou, Haikou, 570201, Hainan, China
| | - Hao Chen
- Department of Neurology, The First Affiliated Hospital of Hainan Medical University, 31 Longhua Road Haikou, Haikou, 570201, Hainan, China
| | - Yibin Chen
- Department of Neurology, The First Affiliated Hospital of Hainan Medical University, 31 Longhua Road Haikou, Haikou, 570201, Hainan, China
| | - Minghui Xu
- Regenerative Medicine Institute, School of Medicine, National University of Ireland (NUI), Galway, Ireland
| | - Ruixue Chen
- Regenerative Medicine Institute, School of Medicine, National University of Ireland (NUI), Galway, Ireland
| | - Changxuan Li
- Department of Neurology, The First Affiliated Hospital of Hainan Medical University, 31 Longhua Road Haikou, Haikou, 570201, Hainan, China.
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Li F, Ming J. Mulberry polyphenols restored both small and large intestinal microflora in db/ db mice, potentially alleviating type 2 diabetes. Food Funct 2024; 15:8521-8543. [PMID: 39058305 DOI: 10.1039/d4fo01291g] [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: 07/28/2024]
Abstract
Polyphenols in mulberry fruit have potential anti-diabetic effects by targeting the gut microbiota. This study investigated how mulberry polyphenols (MPs) influence the microbiota of the small and large intestines and their effects on type 2 diabetes symptoms. The results showed lower microbiota densities in the small intestine. MP treatments improved microbiota richness and diversity in both intestines, similar to metformin. In particular, at a 400 mg kg-1 dose, mulberry polyphenols decreased Firmicutes, Lactobacillus, and Bacilli, while increasing Bacteroidetes, leading to elevated propionate and butyrate levels. Less abundant small intestinal microbiota, like Enterobacterales, Mycoplasmatales, Enterobacteriaceae, and Ureaplasma, were involved in regulating blood glucose and insulin levels. Functional analysis suggested that mulberry polyphenols reshaped the small intestinal microbiota to influence blood glucose balance via unknown pathways, while in the large intestine, they primarily affected blood glucose through carbohydrate transport and metabolism. Based on their ability to regulate the composition of intestinal flora, MPs likely improved glucose homeostasis by enhancing glucose utilization, supporting pancreatic tissue health, and increasing serum antioxidant capacity. However, the specific mechanisms underlying this potential are yet to be fully explored. This study provides new insights into the influence of MPs on remodeling the microbiota residing in both the small and large intestines, which thereby may contribute to the improvement of the pathophysiology of type 2 diabetes.
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Affiliation(s)
- Fuhua Li
- College of Food Science, Southwest University, Chongqing 400715, People's Republic of China.
- Research Center of Food Storage & Logistics, Southwest University, Chongqing 400715, People's Republic of China
- Chongqing Key Laboratory of Speciality Food Co-Built by Sichuan and Chongqing, Chongqing 400715, People's Republic of China
| | - Jian Ming
- College of Food Science, Southwest University, Chongqing 400715, People's Republic of China.
- Research Center of Food Storage & Logistics, Southwest University, Chongqing 400715, People's Republic of China
- Chongqing Key Laboratory of Speciality Food Co-Built by Sichuan and Chongqing, Chongqing 400715, People's Republic of China
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Li J, Wang M, Ma S, Jin Z, Yin H, Yang S. Association of gastrointestinal microbiome and obesity with gestational diabetes mellitus-an updated globally based review of the high-quality literatures. Nutr Diabetes 2024; 14:31. [PMID: 38773069 PMCID: PMC11109140 DOI: 10.1038/s41387-024-00291-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Revised: 04/27/2024] [Accepted: 05/03/2024] [Indexed: 05/23/2024] Open
Abstract
OBJECTIVES The purpose of this review is to investigate the relationship between gastrointestinal microbiome, obesity, and gestational diabetes mellitus (GDM) in an objective manner. METHODS We conducted a thorough and comprehensive search of the English language literatures published in PubMed, Web of Science, and the Cochrane Library from the establishment of the library until 12 December 2023. Our search strategy included both keywords and free words searches, and we strictly applied inclusion and exclusion criteria. Meta-analyses and systematic reviews were prepared. RESULTS Six high-quality literature sources were identified for meta-analysis. However, after detailed study and analysis, a certain degree of heterogeneity was found, and the credibility of the combined analysis results was limited. Therefore, descriptive analyses were conducted. The dysbiosis of intestinal microbiome, specifically the ratio of Firmicutes/Bacteroides, is a significant factor in the development of metabolic diseases such as obesity and gestational diabetes. Patients with intestinal dysbiosis and obesity are at a higher risk of developing GDM. CONCLUSIONS During pregnancy, gastrointestinal microbiome disorders and obesity may contribute to the development of GDM, with all three factors influencing each other. This finding could aid in the diagnosis and management of patients with GDM through further research on their gastrointestinal microbiome.
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Affiliation(s)
- Jiahui Li
- Department of Gynecology and Obstetrics, The Second Hospital of Jilin University, Changchun, 130000, Jilin, China
| | - Min Wang
- Department of Gynecology and Obstetrics, The Second Hospital of Jilin University, Changchun, 130000, Jilin, China
| | - Shuai Ma
- Department of Gynecology and Obstetrics, The Second Hospital of Jilin University, Changchun, 130000, Jilin, China
| | - Zhong Jin
- Department of Gynecology and Obstetrics, The Second Hospital of Jilin University, Changchun, 130000, Jilin, China
| | - Haonan Yin
- Department of Gynecology and Obstetrics, The Second Hospital of Jilin University, Changchun, 130000, Jilin, China
| | - Shuli Yang
- Department of Gynecology and Obstetrics, The Second Hospital of Jilin University, Changchun, 130000, Jilin, China.
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Shi G, Zhu B, Wu Q, Dai J, Sheng N. Prenatal exposure to hexafluoropropylene oxide trimer acid (HFPO-TA) disrupts the maternal gut microbiome and fecal metabolome homeostasis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169330. [PMID: 38135079 DOI: 10.1016/j.scitotenv.2023.169330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 12/09/2023] [Accepted: 12/11/2023] [Indexed: 12/24/2023]
Abstract
Initially considered a "safe" substitute for perfluorooctanoic acid (PFOA), hexafluoropropylene oxide trimer acid (HFPO-TA) has been extensively used in the production of fluoropolymers for several years, leading to its environmental ubiquity and subsequent discovery of its significant bio-accumulative properties and toxicological effects. However, the specific impact of HFPO-TA on females, particularly those who are pregnant, remains unclear. In the present study, pregnant mice were exposed to 0.63 mg/kg/day HFPO-TA from gestational day (GD) 2 to GD 18. We then determined the potential effects of exposure on gut microbiota and fecal metabolites at GD 12 (mid-pregnancy) and GD 18 (late pregnancy). Our results revealed that, in addition to liver damage, HFPO-TA exposure during the specified window altered the structure and function of cecal gut microbiota. Notably, these changes showed the opposite trends at GD 12 and GD 18. Specifically, at GD 12, HFPO-TA exposure primarily resulted in the down-regulation of relative abundances within genera from the Bacteroidetes and Proteobacteria phyla, as well as associated Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. With extended exposure time, the down-regulated genera within Proteobacteria became significantly up-regulated, accompanied by corresponding up-regulation of human disease- and inflammation-associated pathways, suggesting that HFPO-TA exposure can induce intestinal inflammation and elevate the risk of infection during late pregnancy. Pearson correlation analysis revealed that disturbances in the gut microbiota were accompanied by abnormal fecal metabolite. Additionally, alterations in hormones related to the steroid hormone biosynthesis pathway at both sacrifice time indicated that HFPO-TA exposure might change the steroid hormone level of pregnant mice, but need further study. In conclusion, this study provides new insights into the mechanisms underlying HFPO-TA-induced adverse effects and increases awareness of potential persistent health risks to pregnant females.
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Affiliation(s)
- Guohui Shi
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Bao Zhu
- State Environmental Protection Key Laboratory of Environmental Health Impact Assessment of Emerging Contaminants, School of Environmental Sciences and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Qi Wu
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Jiayin Dai
- State Environmental Protection Key Laboratory of Environmental Health Impact Assessment of Emerging Contaminants, School of Environmental Sciences and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Nan Sheng
- State Environmental Protection Key Laboratory of Environmental Health Impact Assessment of Emerging Contaminants, School of Environmental Sciences and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
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Wu N, Sun Y, Qiu T, Liu J, Cao Y, Zang T, Fan X, Bai J, Huang J, Liu Y. Associations of nighttime light exposure during pregnancy with maternal and neonatal gut microbiota: A cohort study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 908:168292. [PMID: 37924882 DOI: 10.1016/j.scitotenv.2023.168292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Revised: 10/27/2023] [Accepted: 10/31/2023] [Indexed: 11/06/2023]
Abstract
BACKGROUND Nighttime light (NTL) pollution has been reported as a risk factor for human health. However, the relationship between NTL and gut microbiota has not been reported in pregnant women and neonates. This study was conducted to investigate the relationship between NTL and gut microbial diversity and composition in mothers and their neonates. METHODS This study analyzed 44 mothers and 28 newborns. The composition of gut microbiota was evaluated using 16S rRNA V3-V4 sequencing. The monthly mean NTL exposure during pregnancy was respectively calculated based on each participant's residential address (NTLpoint) and a concentric 1 km radius buffer zone around their address (NTL1000m). The relationships between NTL exposure and gut microbiota of mothers and newborns were assessed using generalized linear models. RESULTS NTL exposure during pregnancy was not associated with alpha diversity of mothers or neonates. For mothers, results revealed that after adjusting for covariates, NTLpoint was negatively correlated with Prevotella_2 (p = 0.004, FDR-adjusted p = 0.030) and norank_o__Gastranaerophilales (p = 0.018, FDR-adjusted p = 0.049) at the genus level. In addition, Lachnospira (p = 0.036, FDR-adjusted p = 0.052) and Coprococcus_3 (p = 0.025, FDR-adjusted p = 0.052) were positively correlated with NTLpoint. The association between Coprococcus_3 (p = 0.01, FDR-adjusted p = 0.046) and NTLpoint persisted even after controlling for covariates. For neonates, Thauera was positively associated with NTLpoint (p = 0.015) and NTL1000m (p = 0.028), however, after adjusting for covariates and FDR correction, Thauera was not significantly associated with NTLpoint and NTL1000m. CONCLUSIONS This study found that NTL exposure was associated with maternal gut microbiota composition. Our findings provide a foundation for the potential impact of NTL exposure on maternal gut microbiota from a microbiological perspective. More population-based validation of the effects of NTL exposure on human gut microbiota is needed in future.
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Affiliation(s)
- Ni Wu
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China
| | - Yu Sun
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China
| | - Tianlai Qiu
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China.
| | - Jun Liu
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China.
| | - Yanan Cao
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China.
| | - Tianzi Zang
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China.
| | - Xiaoxiao Fan
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China.
| | - Jinbing Bai
- Emory University Nell Hodgson Woodruff School of Nursing, 1520 Clifton Road, Atlanta, GA 30322, USA.
| | - Jing Huang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing 100191, China.
| | - Yanqun Liu
- Center for Women's and Children's Health, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China; Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan 430062, China.
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Lan Y, Pan S, Chen B, Zhou F, Yang F, Chao S, Hua Y, Liu H. The relationship between gut microbiota, short-chain fatty acids, and glucolipid metabolism in pregnant women with large for gestational age infants. J Appl Microbiol 2023; 134:lxad240. [PMID: 37883533 DOI: 10.1093/jambio/lxad240] [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: 03/07/2023] [Revised: 10/02/2023] [Accepted: 10/21/2023] [Indexed: 10/28/2023]
Abstract
AIM To elucidate the association between gut microbiota, short-chain fatty acids (SCFAs), and glucolipid metabolism in women with large for gestational age (LGA) infants. METHODS AND RESULTS A single-center, observational prospective cohort study was performed at a tertiary hospital in Wenzhou, China. Normal pregnant women were divided into LGA group and appropriate for gestational age (AGA) group according to the neonatal birth weight. Fecal samples were collected from each subject before delivery for the analysis of gut microbiota composition (GMC) and SCFAs. Blood samples were obtained at 24-28 weeks of gestation age to measure fasting blood glucose and fasting insulin levels, as well as just before delivery to assess serum triglycerides, total cholesterol, high-density lipoprotein (HDL), and low-density lipoprotein. The GMC exhibited differences at various taxonomic levels. Within the Firmicutes phylum, genus Lactobacillus, genus Clostridium, species Lactobacillus agil, and species Lactobacillus salivarius were enriched in the LGA group. Microbispora at genus level, Microbispora rosea at species level belonging to the Actinobacteria phylum, Neisseriales at order level, Bartonellaceae at family level, Paracoccus aminovorans, and Methylobacterium at genus level from the Proteobacteria phylum were more abundant in the LGA group. In contrast, within the Bacteroidetes phylum, Prevotella at genus level and Parabacteroides distasonis at species level were enriched in the AGA group. Although there were few differences observed in SCFA levels and most glucolipid metabolism indicators between the two groups, the serum HDL level was significantly lower in the LGA group compared to the AGA group. No significant relevance among GMC, SCFAs, and glucolipid metabolism indicators was found in the LGA group or in the AGA group. CONCLUSIONS Multiple different taxa, especially phylum Firmicutes, genus Prevotella, and genus Clostridium, might play an important role in excessive fetal growth, and LGA might be associated with the lower serum HDL level.
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Affiliation(s)
- Yehui Lan
- Department of Obstetrics and Gynecology and General Surgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Shuangjia Pan
- Department of Obstetrics and Gynecology and General Surgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Baoyi Chen
- Department of Obstetrics and Gynecology and General Surgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Feifei Zhou
- Department of Obstetrics and Gynecology, The Wenzhou Third Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou 325027, China
| | - Fan Yang
- Key Laboratory of Cell Engineering in Guizhou Province, Affiliated Hospital of Zunyi Medical University, Zunyi 563000,China
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, China
- Research Center for Lin He Academician New Medicine, Institutes for Shanghai Pudong Decoding Life, Shanghai 2000240, China
| | - Shan Chao
- Research Center for Lin He Academician New Medicine, Institutes for Shanghai Pudong Decoding Life, Shanghai 2000240, China
| | - Ying Hua
- Department of Obstetrics and Gynecology and General Surgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Haibin Liu
- Department of Obstetrics and Gynecology and General Surgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou 325027, China
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Li H, Li C. Causal relationship between gut microbiota and type 2 diabetes: a two-sample Mendelian randomization study. Front Microbiol 2023; 14:1184734. [PMID: 37692402 PMCID: PMC10483233 DOI: 10.3389/fmicb.2023.1184734] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 08/01/2023] [Indexed: 09/12/2023] Open
Abstract
Background Studies showed that development of gut microbial dysbiosis has a close association with type 2 diabetes (T2D). It is not yet clear if there is a causal relationship between gut microbiota and T2D. Methods The data collected from the published genome-wide association studies (GWASs) on gut microbiota and T2D were analyzed. Two-sample Mendelian randomization (MR) analyses were performed to identify causal relationship between bacterial taxa and T2D. Significant bacterial taxa were further analyzed. To confirm the findings' robustness, we performed sensitivity, heterogeneity, and pleiotropy analyses. A reverse MR analysis was also performed to check for potential reverse causation. Results By combining the findings of all the MR steps, we identified six causal bacterial taxa, namely, Lachnoclostridium, Oscillospira, Roseburia, Ruminococcaceae UCG003, Ruminococcaceae UCG010 and Streptococcus. The risk of T2D might be positively associated with a high relative abundance of Lachnoclostridium, Roseburia and Streptococcus but negatively associated with Oscillospira, Ruminococcaceae UCG003 and Ruminococcaceae UCG010. The results of MR analyses revealed that there were causal relationships between the six different genera and T2D. And the reverse MR analysis did not reveal any evidence of a reverse causality. Conclusion This study implied that Lachnoclostridium, Roseburia and Streptococcus might have anti-protective effect on T2D, whereas Oscillospira, Ruminococcaceae UCG003 and Ruminococcaceae UCG010 genera might have protective effect on T2D. Our study revealed that there was a causal relationship between specific gut microbiota genera and T2D.
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Affiliation(s)
- Hanjing Li
- College of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
- Research Base of Traditional Chinese Medicine Syndrome, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
| | - Candong Li
- College of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
- Research Base of Traditional Chinese Medicine Syndrome, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
- Key Laboratory of Traditional Chinese Medicine Health Status Identification, Fuzhou, Fujian, China
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11
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Zhang X, Wang W, Cao Z, Yang H, Wang Y, Li S. Effects of altitude on the gut microbiome and metabolomics of Sanhe heifers. Front Microbiol 2023; 14:1076011. [PMID: 36910192 PMCID: PMC10002979 DOI: 10.3389/fmicb.2023.1076011] [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: 10/21/2022] [Accepted: 01/31/2023] [Indexed: 03/14/2023] Open
Abstract
Introduction Extreme environments at high altitudes pose a significant physiological challenge to animals. We evaluated the gut microbiome and fecal metabolism in Sanhe heifers from different altitudes. Methods Twenty Sanhe heifers (body weight: 334.82 ± 13.22 kg, 15-month-old) selected from two regions of China: the Xiertala Cattle Breeding Farm in Hulunbeier, Inner Mongolia [119°57' E, 47°17' N; approximately 700 m altitude, low altitude (LA)] and Zhizhao Dairy Cow Farm in Lhasa, Tibet [91°06' E, 29°36' N; approximately 3,650 m altitude, high altitude (HA)], were used in this study. Fecal samples were collected and differences in the gut microbiota and metabolomics of Sanhe heifers were determined using 16S rRNA gene sequencing and metabolome analysis. Results and discussion The results showed that altitude did not significantly affect the concentrations of fecal volatile fatty acids, including acetate, propionate, butyrate, and total volatile fatty acids (p > 0.05). However, 16S rRNA gene sequencing showed that altitude significantly affected gut microbial composition. Principal coordinate analysis based on Bray-Curtis dissimilarity analysis revealed a significant difference between the two groups (p = 0.001). At the family level, the relative abundances of Peptostreptococcaceae, Christensenellaceae, Erysipelotrichaceae, and Family_XIII were significantly lower (p < 0.05) in LA heifers than in HA heifers. In addition, the relative abundances of Lachnospiraceae, Domibacillus, Bacteroidales_S24-7_group, Bacteroidales_RF16_group, Porphyromonadaceae, and Spirochaetaceae were significantly higher in HA heifers than in LA heifers (p < 0.05). Metabolomic analysis revealed the enrichment of 10 metabolic pathways, including organismal systems, metabolism, environmental information processing, genetic information processing, and disease induction. The genera Romboutsia, Paeniclostridium, and g_unclassified_f_Lachnospiraceae were strongly associated with the 28 differential metabolites. This study is the first to analyze the differences in the gut microbiome and metabolome of Sanhe heifers reared at different altitudes and provides insights into the adaptation mechanism of Sanhe heifers to high-altitude areas.
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Affiliation(s)
- Xinyu Zhang
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Wei Wang
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Zhijun Cao
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Hongjian Yang
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Yajing Wang
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Shengli Li
- State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing, China
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Ionescu RF, Enache RM, Cretoiu SM, Gaspar BS. Gut Microbiome Changes in Gestational Diabetes. Int J Mol Sci 2022; 23:12839. [PMID: 36361626 PMCID: PMC9654708 DOI: 10.3390/ijms232112839] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 10/20/2022] [Accepted: 10/21/2022] [Indexed: 08/27/2023] Open
Abstract
Gestational diabetes mellitus (GDM), one of the most common endocrine pathologies during pregnancy, is defined as any degree of glucose intolerance with onset or first discovery in the perinatal period. Physiological changes that occur in pregnant women can lead to inflammation, which promotes insulin resistance. In the general context of worldwide increasing obesity in young females of reproductive age, GDM follows the same ascending trend. Changes in the intestinal microbiome play a decisive role in obesity and the development of insulin resistance and chronic inflammation, especially in patients with type 2 diabetes mellitus (T2D). To date, various studies have also associated intestinal dysbiosis with metabolic changes in women with GDM. Although host metabolism in women with GDM has not been fully elucidated, it is of particular importance to analyze the available data and to discuss the actual knowledge regarding microbiome changes with potential impact on the health of pregnant women and newborns. We analyzed peer-reviewed journal articles available in online databases in order to summarize the most recent findings regarding how variations in diet and metabolic status of GDM patients can contribute to alteration of the gut microbiome, in the same way that changes of the gut microbiota can lead to GDM. The most frequently observed alteration in the microbiome of patients with GDM was either an increase of the Firmicutes phylum, respectively, or a decrease of the Bacteroidetes and Actinobacteria phyla. Gut dysbiosis was still present postpartum and can impact the development of the newborn, as shown in several studies. In the evolution of GDM, probiotic supplementation and regular physical activity have the strongest evidence of proper blood glucose control, favoring fetal development and a healthy outcome for the postpartum period. The current review aims to summarize and discuss the most recent findings regarding the correlation between GDM and dysbiosis, and current and future methods for prevention and treatment (lifestyle changes, pre- and probiotics administration). To conclude, by highlighting the role of the gut microbiota, one can change perspectives about the development and progression of GDM and open up new avenues for the development of innovative therapeutic targets in this disease.
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Affiliation(s)
- Ruxandra Florentina Ionescu
- Department of Cardiology I, Central Military Emergency Hospital “Dr Carol Davila”, 030167 Bucharest, Romania
- Department of Morphological Sciences, Cell and Molecular Biology and Histology, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania
| | - Robert Mihai Enache
- Department of Radiology and Medical Imaging, Fundeni Clinical Institute, 022328 Bucharest, Romania
| | - Sanda Maria Cretoiu
- Department of Morphological Sciences, Cell and Molecular Biology and Histology, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania
| | - Bogdan Severus Gaspar
- Surgery Department, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Surgery Clinic, Bucharest Emergency Clinical Hospital, 014461 Bucharest, Romania
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Helichrysum italicum (Roth) G. Don and Helichrysum arenarium (L.) Moench Infusion Consumption Affects the Inflammatory Status and the Composition of Human Gut Microbiota in Patients with Traits of Metabolic Syndrome: A Randomized Comparative Study. Foods 2022. [PMCID: PMC9601527 DOI: 10.3390/foods11203277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Helichrysum italicum (Roth) G. Don (HI) and Helichrysum arenarium (L.) Moench (HA) are rich in polyphenols and their infusions have beneficial effects for patients with metabolic syndrome. To investigate whether these effects are mediated by the gut microbiota, we analysed the effects of daily consumption of HI or HA infusion on the composition of gut microbiota, inflammatory status, and zonulin, a marker of gut barrier permeability. The study was a randomized, double-blind comparative trial. Thirty participants were randomly assigned to two groups and received either HA or HI tea filter bags, each containing 1 g of dried plant material, for daily consumption lasting 4 weeks. The results show that consumption of both infusions resulted in a reduction of some genera belonging to Firmicutes and in a slight but significant reduction in Shannon diversity index. Consumption of HI infusion significantly reduced serum levels of proinflammatory markers and zonulin alongside with the observed trend of Proteobacteria reduction. It can therefore be concluded that the HI and HA infusions could act as prebiotics and thus improve the intestinal environment. In addition, HI infusion has a positive impact on microbial dysbiosis and gut barrier dysfunction that occur in obesity and metabolic syndrome.
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Xue C, Xie Q, Zhang C, Hu Y, Song X, Jia Y, Shi X, Chen Y, Liu Y, Zhao L, Huang F, Yuan H. Vertical transmission of the gut microbiota influences glucose metabolism in offspring of mice with hyperglycaemia in pregnancy. MICROBIOME 2022; 10:122. [PMID: 35941695 PMCID: PMC9361546 DOI: 10.1186/s40168-022-01318-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 06/30/2022] [Indexed: 05/21/2023]
Abstract
BACKGROUND Hyperglycaemia in pregnancy (HIP) is a common metabolic disorder that not only poses risks to maternal health but also associates with an increased risk of diabetes among offspring. Vertical transmission of microbiota may influence the offspring microbiome and subsequent glucose metabolism. However, the mechanism by which maternal gut microbiota may influence glucose metabolism of the offspring remains unclear and whether intervening microbiota vertical transmission could be used as a strategy to prevent diabetes in the offspring of mothers with HIP has not been investigated. So we blocked vertical transmission to investigate its effect on glucose metabolism in the offspring. RESULTS We established a murine HIP model with a high-fat diet (HFD) and investigated the importance of vertical transmission of gut microbiota on the glucose metabolism of offspring via birth and nursing by blocking these events through caesarean section (C-section) and cross-fostering. After weaning, all offspring were fed a normal diet. Based on multi-omics analysis, biochemical and transcriptional assays, we found that the glucometabolic deficits in the mothers were subsequently 'transmitted' to the offspring. Meanwhile, the partial change in mothers' gut microbial community induced by HIP could be transmitted to offspring, supported by the closed clustering of the microbial structure and composition between the offspring and their mothers. Further study showed that the microbiota vertical transmission was blocked by C-section and cross-fostering, which resulted in improved insulin sensitivity and islet function of the offspring of the mothers with HIP. These effects were correlated with changes in the relative abundances of specific bacteria and their metabolites, such as increased relative abundances of Bifidobacterium and short-chain fatty acids. In particular, gut microbial communities of offspring were closely related to those of their foster mothers but not their biological mothers, and the effect of cross-fostering on the offspring's gut microbiota was more profound than that of C-section. CONCLUSION Our study demonstrates that the gut microbiota transmitted via birth and nursing are important contributors to the glucose metabolism phenotype in offspring. Video Abstract.
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Affiliation(s)
- Cunxi Xue
- Department of Endocrinology of Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Intestinal Microecology and Diabetes Control, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Qinyuan Xie
- Department of Endocrinology of Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Intestinal Microecology and Diabetes Control, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Chenhong Zhang
- State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Yimeng Hu
- Department of Endocrinology of Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Intestinal Microecology and Diabetes Control, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Xiaoting Song
- Department of Endocrinology of Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Intestinal Microecology and Diabetes Control, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yifan Jia
- Department of Endocrinology of Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Intestinal Microecology and Diabetes Control, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Xiaoyang Shi
- Department of Endocrinology of Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Intestinal Microecology and Diabetes Control, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yiqi Chen
- Department of Endocrinology of Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Intestinal Microecology and Diabetes Control, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yalei Liu
- Department of Endocrinology of Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Intestinal Microecology and Diabetes Control, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Lingyun Zhao
- Department of Endocrinology of Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Intestinal Microecology and Diabetes Control, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Fenglian Huang
- Department of Endocrinology of Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Intestinal Microecology and Diabetes Control, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Huijuan Yuan
- Department of Endocrinology of Henan Provincial People's Hospital, Henan Provincial Key Laboratory of Intestinal Microecology and Diabetes Control, People's Hospital of Zhengzhou University, Zhengzhou, Henan, China.
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Lin H, Ma X, Yang X, Chen Q, Wen Z, Yang M, Fu J, Yin T, Lu G, Qi J, Han H, Yang Y. Natural shikonin and acetyl-shikonin improve intestinal microbial and protein composition to alleviate colitis-associated colorectal cancer. Int Immunopharmacol 2022; 111:109097. [PMID: 35952517 DOI: 10.1016/j.intimp.2022.109097] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 06/24/2022] [Accepted: 07/24/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND Colorectal cancer (CRC) and inflammatory bowel disease (IBD) are the most common diseases of human digestive system. Nowadays, the influence of the inflammatory microenvironment on tumorigenesis has become a new direction, and the exploration of relative molecular mechanism will facilitate the discovery and identification of novel potential anti-cancer molecules. METHODS Natural shikonin (SK) and acetyl-shikonin (acetyl-SK) was administered to azoxymethane (AOM)/dextran sodium sulphate (DSS)-induced colitis-associated colorectal cancer (CAC) mice model by gavage to investigate their therapeutic effects. Moreover, fresh feces and colon tissues were collected for determining the function of SK and acetyl-SK on the gut microbes and protein expression, respectively. RESULTS Both SK and acetyl-SK decreased AOM/DSS-induced CAC, and regulated the intestinal flora structure in CAC mouse model. They, especially SK, improved species richness, evenness and diversity of intestinal flora, recovered the upregulated ratio of Firmicutes to Bacteroidota (F/B ratio) which symbolizes gut microbiota dysbiosis. SK and its derivative increased the beneficial bacteria g__norank_f__Muribaculaceae, Lactobacillus, Lachnospiraceae_NK4A136_Group, and reduced those harmful ones including Ileibacterium and Coriobacteriaceae UCG-002. Notably, AOM/DSS caused significant increase in the abundance of Ileibaterium valens and g__norank_f__norank_o__Clostridia_UCG-014, which were not previously reported in studies of colonic inflammation or cancer, and the disorder was reversed by 20 mg/kg of SK. In our current study, the action of SK and acetyl-SK is dose-dependent, and 20 mg/kg SK exhibited the most effective functions, even better than the positive drug mesalazine. Moreover, differential proteomics and ELISA results showed that SK could recover the increase of pro-inflammatory cytokines (including IL-1β, IL-6 and TNF-α), the upregulation of pyruvate kinase isozyme type M2 (PKM2) and some other proteins (mainly concentrated in transcriptional mis-regulation in cancer and IL-17 signaling pathways), and the downregulation of Aldh1b1-Acc3-Maoa and Μgt2b34-Aldh1a1-Aldh1a7 involved in Wnt/β-catenin signaling pathway. CONCLUSION Our study identified SK and acetyl-SK, especially SK, as potential preventive agents for CAC through regulating both gut microbes and pathways involved in inflammation and cancer such as Wnt/β-catenin signaling pathway.
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Affiliation(s)
- Hongyan Lin
- State Key Laboratory of Pharmaceutical Biotechnology, Institute of Plant Molecular Biology, School of Life Sciences, Nanjing University, Nanjing 210023, China; School of Pharmacy, Changzhou University, Changzhou 213164, China
| | - Xiaopeng Ma
- State Key Laboratory of Pharmaceutical Biotechnology, Institute of Plant Molecular Biology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Xiaorong Yang
- School of Biology and Geography Science, Yili Normal University, Yining 835000, China
| | - Qingqing Chen
- State Key Laboratory of Pharmaceutical Biotechnology, Institute of Plant Molecular Biology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Zhongling Wen
- State Key Laboratory of Pharmaceutical Biotechnology, Institute of Plant Molecular Biology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Minkai Yang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute of Plant Molecular Biology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Jiangyan Fu
- State Key Laboratory of Pharmaceutical Biotechnology, Institute of Plant Molecular Biology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Tongming Yin
- Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
| | - Guihua Lu
- State Key Laboratory of Pharmaceutical Biotechnology, Institute of Plant Molecular Biology, School of Life Sciences, Nanjing University, Nanjing 210023, China; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
| | - Jinliang Qi
- State Key Laboratory of Pharmaceutical Biotechnology, Institute of Plant Molecular Biology, School of Life Sciences, Nanjing University, Nanjing 210023, China; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
| | - Hongwei Han
- State Key Laboratory of Pharmaceutical Biotechnology, Institute of Plant Molecular Biology, School of Life Sciences, Nanjing University, Nanjing 210023, China; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China.
| | - Yonghua Yang
- State Key Laboratory of Pharmaceutical Biotechnology, Institute of Plant Molecular Biology, School of Life Sciences, Nanjing University, Nanjing 210023, China; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China.
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Tang M, Weaver NE, Frank DN, Ir D, Robertson CE, Kemp JF, Westcott J, Shankar K, Garces AL, Figueroa L, Tshefu AK, Lokangaka AL, Goudar SS, Somannavar M, Aziz S, Saleem S, McClure EM, Hambidge KM, Hendricks AE, Krebs NF. Longitudinal Reduction in Diversity of Maternal Gut Microbiota During Pregnancy Is Observed in Multiple Low-Resource Settings: Results From the Women First Trial. Front Microbiol 2022; 13:823757. [PMID: 35979501 PMCID: PMC9376441 DOI: 10.3389/fmicb.2022.823757] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 06/15/2022] [Indexed: 11/13/2022] Open
Abstract
Objective To characterize the changes in gut microbiota during pregnancy and determine the effects of nutritional intervention on gut microbiota in women from sub-Saharan Africa (the Democratic Republic of the Congo, DRC), South Asia (India and Pakistan), and Central America (Guatemala). Methods Pregnant women in the Women First (WF) Preconception Maternal Nutrition Trial were included in this analysis. Participants were randomized to receive a lipid-based micronutrient supplement either ≥3 months before pregnancy (Arm 1); started the same intervention late in the first trimester (Arm 2); or received no nutrition supplements besides those self-administered or prescribed through local health services (Arm 3). Stool and blood samples were collected during the first and third trimesters. Findings presented here include fecal 16S rRNA gene-based profiling and systemic and intestinal inflammatory biomarkers, including alpha (1)-acid glycoprotein (AGP), C-reactive protein (CRP), fecal myeloperoxidase (MPO), and calprotectin. Results Stool samples were collected from 640 women (DRC, n = 157; India, n = 102; Guatemala, n = 276; and Pakistan, n = 105). Gut microbial community structure did not differ by intervention arm but changed significantly during pregnancy. Richness, a measure of alpha-diversity, decreased over pregnancy. Community composition (beta-diversity) also showed a significant change from first to third trimester in all four sites. Of the top 10 most abundant genera, unclassified Lachnospiraceae significantly decreased in Guatemala and unclassified Ruminococcaceae significantly decreased in Guatemala and DRC. The change in the overall community structure at the genus level was associated with a decrease in the abundances of certain genera with low heterogeneity among the four sites. Intervention arms were not significantly associated with inflammatory biomarkers at 12 or 34 weeks. AGP significantly decreased from 12 to 34 weeks of pregnancy, whereas CRP, MPO, and calprotectin did not significantly change over time. None of these biomarkers were significantly associated with the gut microbiota diversity. Conclusion The longitudinal reduction of individual genera (both commensals and potential pathogens) and alpha-diversity among all sites were consistent and suggested that the effect of pregnancy on the maternal microbiota overrides other influencing factors, such as nutrition intervention, geographical location, diet, race, and other demographical variables.
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Affiliation(s)
- Minghua Tang
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Nicholas E. Weaver
- Department of Mathematical and Statistical Sciences, University of Colorado, Denver, Denver, CO, United States
| | - Daniel N. Frank
- Department of Infectious Disease, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Diana Ir
- Department of Infectious Disease, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Charles E. Robertson
- Department of Infectious Disease, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Jennifer F. Kemp
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Jamie Westcott
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Kartik Shankar
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Ana L. Garces
- Institute of Nutrition in Central America and Panama (INCAP), Guatemala City, Guatemala
| | - Lester Figueroa
- Institute of Nutrition in Central America and Panama (INCAP), Guatemala City, Guatemala
| | - Antoinette K. Tshefu
- Institute of Nutrition in Central America and Panama (INCAP), Guatemala City, Guatemala
| | - Adrien L. Lokangaka
- Institute of Nutrition in Central America and Panama (INCAP), Guatemala City, Guatemala
| | - Shivaprasad S. Goudar
- KLE Academy of Higher Education and Research (Deemed-to-be-University), Jawaharlal Nehru Medical College, Belagavi, India
| | - Manjunath Somannavar
- KLE Academy of Higher Education and Research (Deemed-to-be-University), Jawaharlal Nehru Medical College, Belagavi, India
| | - Sumera Aziz
- Department of Community Health Sciences, Aga Khan University, Karachi, Pakistan
| | - Sarah Saleem
- Department of Community Health Sciences, Aga Khan University, Karachi, Pakistan
| | | | - K. Michael Hambidge
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Audrey E. Hendricks
- Department of Mathematical and Statistical Sciences, University of Colorado, Denver, Denver, CO, United States
| | - Nancy F. Krebs
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
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Tang R, Yi J, Lu S, Chen B, Liu B. Therapeutic Effect of Buyang Huanwu Decoction on the Gut Microbiota and Hippocampal Metabolism in a Rat Model of Cerebral Ischemia. Front Cell Infect Microbiol 2022; 12:873096. [PMID: 35774407 PMCID: PMC9237419 DOI: 10.3389/fcimb.2022.873096] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 05/11/2022] [Indexed: 12/04/2022] Open
Abstract
Buyang Huanwu decoction (BHD) is a well-known Chinese herbal prescription. It has been widely used in the clinical treatment of cerebral ischemia (CI) in China. However, the mechanism underlying the treatment of CI with BHD remains to be elucidated. In this study, we combined microbiomic and metabolomic strategies to explore the therapeutic effects of BHD on middle cerebral artery occlusion (MCAO) in rats. Our results showed that BHD could effectively improve neurological severity scores and alleviate neuronal damage in rats with MCAO. BHD could also reduce the level of peripheral proinflammatory cytokines and inhibit neuroinflammation. 16S rRNA sequencing showed that BHD could increase the relative abundances of the genera Lactobacillus, Faecalibacterium, Ruminococcaceae_UCG-002, etc., while decreasing the relative abundances of the genera Escherichia-Shigella, Klebsiella, Streptococcus, Coprococcus_2, Enterococcus, etc. Untargeted metabolomic analysis of hippocampal samples showed that 17 significantly differentially abundant metabolites and 9 enriched metabolic pathways were linked with BHD treatment. We also found that the regulatory effects of BHD on metabolites were correlated with the differentially abundant microbial taxa. The predicted function of the gut microbiota and the metabolic pathway enrichment results showed that purine metabolism, glutamatergic synapses, arginine and proline metabolism, and alanine, aspartic acid and glutamate metabolism were involved in the effects of BHD. These pathways may be related to pathological processes such as excitotoxicity, neuroinflammation, and energy metabolism disorder in CI. In summary, these findings suggest that regulation of hippocampal metabolism and of the composition and function of the gut microbiota may be important mechanisms underlying the effect of BHD in the treatment of CI.
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Affiliation(s)
- Rongmei Tang
- The First Affiliated Hospital, Hunan University of Chinese Medicine, Changsha, China
| | - Jian Yi
- The First Affiliated Hospital, Hunan University of Chinese Medicine, Changsha, China
| | - Shuangying Lu
- The First Affiliated Hospital, Hunan University of Chinese Medicine, Changsha, China
| | - Bowei Chen
- The First Affiliated Hospital, Hunan University of Chinese Medicine, Changsha, China
| | - Baiyan Liu
- College of Integrated Traditional Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha, China
- *Correspondence: Baiyan Liu,
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Dreisbach C, Morgan H, Cochran C, Gyamfi A, Henderson WA, Prescott S. Metabolic and Microbial Changes Associated With Diet and Obesity During Pregnancy: What Can We Learn From Animal Studies? Front Cell Infect Microbiol 2022; 11:795924. [PMID: 35118010 PMCID: PMC8804207 DOI: 10.3389/fcimb.2021.795924] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 12/13/2021] [Indexed: 12/22/2022] Open
Abstract
The intestinal microbiota changes throughout pregnancy and influences maternal metabolic adaptations to support fetal growth. Obesity induces alterations to the microbiota that include decreased microbial diversity and shifts in microbial composition, though specific species changes are inconsistent between published studies. In animal models, probiotics and exercise moderate maternal weight gain and partially correct the maternal microbiota. Supplemental Escherichia coli, however, exacerbate maternal obesity during the perinatal period, lending weight to the theory that inflammation-induced gut epithelial barrier leak influences metabolic dysregulation. Although birth weight is not always altered when offspring are exposed to an obesogenic diet during gestation, insulin resistance and lipid metabolism are impacted through adulthood in association with this exposure and can lead to increased body weight in adulthood. Postnatal offspring growth is accelerated in response to maternal overnutrition during lactation. Offspring microbiota, metabolism, and behavior are altered in response to early exposure to high fat and high sucrose diets. Consequences to this exposure include impaired glucose and insulin homeostasis, fatty liver, and neurobehavioral deficits that can be ameliorated by improving the microbial environment. In this mini review, we provide an overview of the use of translational animal models to understand the mechanisms associated with changes to the gastrointestinal microbiota due to maternal obesity and the microbial impact on the metabolic changes of pregnancy.
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Affiliation(s)
- Caitlin Dreisbach
- Data Science Institute, Columbia University, New York, NY, United States
| | - Hailey Morgan
- College of Nursing, University of South Florida, Tampa, FL, United States
| | - Caroline Cochran
- School of Nursing, Columbia University, New York, NY, United States
| | - Adwoa Gyamfi
- School of Medicine, University of Connecticut, Farmington, CT, United States
| | - Wendy Ann Henderson
- School of Medicine, University of Connecticut, Farmington, CT, United States
- School of Nursing, University of Connecticut, Storrs, CT, United States
| | - Stephanie Prescott
- College of Nursing, University of South Florida, Tampa, FL, United States
- *Correspondence: Stephanie Prescott,
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Chen Y, Wang M. New Insights of Anti-Hyperglycemic Agents and Traditional Chinese Medicine on Gut Microbiota in Type 2 Diabetes. Drug Des Devel Ther 2021; 15:4849-4863. [PMID: 34876807 PMCID: PMC8643148 DOI: 10.2147/dddt.s334325] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Accepted: 11/19/2021] [Indexed: 12/11/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is a widespread metabolic disease characterized by chronic hyperglycemia. Human microbiota, which is regarded as a “hidden organ”, plays an important role in the initiation and development of T2DM. In addition, anti-hyperglycemic agents and traditional Chinese medicine may affect the composition of gut microbiota and consequently improve glucose metabolism. However, the relationship between gut microbiota, T2DM and anti-hyperglycemic agents or traditional Chinese medicine is poorly understood. In this review, we summarized pre-clinical and clinical studies to elucidate the possible underlying mechanism. Some anti-hyperglycemic agents and traditional Chinese medicine may partly exert hypoglycemic effects by altering the gut microbiota composition in ways that reduce metabolic endotoxemia, maintain the integrity of intestinal mucosal barrier, promote the production of short-chain fatty acids (SCFAs), decrease trimethylamine-N-oxide (TMAO) and regulate bile acid metabolism. In conclusion, gut microbiota may provide some new therapeutic targets for treatment of patients with diabetes mellitus.
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Affiliation(s)
- Yanxia Chen
- Department of Endocrinology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050051, People's Republic of China
| | - Mian Wang
- Department of Endocrinology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050051, People's Republic of China
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20
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Sawicka-Smiarowska E, Bondarczuk K, Bauer W, Niemira M, Szalkowska A, Raczkowska J, Kwasniewski M, Tarasiuk E, Dubatowka M, Lapinska M, Szpakowicz M, Stachurska Z, Szpakowicz A, Sowa P, Raczkowski A, Kondraciuk M, Gierej M, Motyka J, Jamiolkowski J, Bondarczuk M, Chlabicz M, Bucko J, Kozuch M, Dobrzycki S, Bychowski J, Musial WJ, Godlewski A, Ciborowski M, Gyenesei A, Kretowski A, Kaminski KA. Gut Microbiome in Chronic Coronary Syndrome Patients. J Clin Med 2021; 10:jcm10215074. [PMID: 34768594 PMCID: PMC8584954 DOI: 10.3390/jcm10215074] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 10/26/2021] [Accepted: 10/27/2021] [Indexed: 02/07/2023] Open
Abstract
Despite knowledge of classical coronary artery disease (CAD) risk factors, the morbidity and mortality associated with this disease remain high. Therefore, new factors that may affect the development of CAD, such as the gut microbiome, are extensively investigated. This study aimed to evaluate gut microbiome composition in CAD patients in relation to the control group. We examined 169 CAD patients and 166 people in the control group, without CAD, matched in terms of age and sex to the study group. Both populations underwent a detailed health assessment. The microbiome analysis was based on the V3-V4 region of the 16S rRNA gene (NGS method). Among 4074 identified taxonomic units in the whole population, 1070 differed between study groups. The most common bacterial types were Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria. Furthermore, a higher Firmicutes/Bacteroidetes ratio in the CAD group compared with the control was demonstrated. Firmicutes/Bacteroidetes ratio, independent of age, sex, CAD status, LDL cholesterol concentration, and statins treatment, was related to altered phosphatidylcholine concentrations obtained in targeted metabolomics. Altered alpha-biodiversity (Kruskal-Wallis test, p = 0.001) and beta-biodiversity (Bray-Curtis metric, p < 0.001) in the CAD group were observed. Moreover, a predicted functional analysis revealed some taxonomic units, metabolic pathways, and proteins that might be characteristic of the CAD patients' microbiome, such as increased expressions of 6-phospho-β-glucosidase and protein-N(pi)-phosphohistidine-sugar phosphotransferase and decreased expressions of DNA topoisomerase, oxaloacetate decarboxylase, and 6-beta-glucosidase. In summary, CAD is associated with altered gut microbiome composition and function.
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Affiliation(s)
- Emilia Sawicka-Smiarowska
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
- Department of Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.T.); (A.S.); (W.J.M.)
| | - Kinga Bondarczuk
- Centre for Bioinformatics and Data Analysis, Medical University of Bialystok, 15-269 Bialystok, Poland; (K.B.); (M.K.); (M.B.)
| | - Witold Bauer
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Magdalena Niemira
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Anna Szalkowska
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Justyna Raczkowska
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Miroslaw Kwasniewski
- Centre for Bioinformatics and Data Analysis, Medical University of Bialystok, 15-269 Bialystok, Poland; (K.B.); (M.K.); (M.B.)
| | - Ewa Tarasiuk
- Department of Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.T.); (A.S.); (W.J.M.)
| | - Marlena Dubatowka
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Magda Lapinska
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Malgorzata Szpakowicz
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Zofia Stachurska
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Anna Szpakowicz
- Department of Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.T.); (A.S.); (W.J.M.)
| | - Pawel Sowa
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Andrzej Raczkowski
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Marcin Kondraciuk
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Magdalena Gierej
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Joanna Motyka
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Jacek Jamiolkowski
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
| | - Mateusz Bondarczuk
- Centre for Bioinformatics and Data Analysis, Medical University of Bialystok, 15-269 Bialystok, Poland; (K.B.); (M.K.); (M.B.)
| | - Malgorzata Chlabicz
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
- Department of Invasive Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (M.K.); (S.D.)
| | - Jolanta Bucko
- Department of Cardiology, Bialystok Regional Hospital, 15-950 Bialystok, Poland; (J.B.); (J.B.)
| | - Marcin Kozuch
- Department of Invasive Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (M.K.); (S.D.)
| | - Slawomir Dobrzycki
- Department of Invasive Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (M.K.); (S.D.)
| | - Jerzy Bychowski
- Department of Cardiology, Bialystok Regional Hospital, 15-950 Bialystok, Poland; (J.B.); (J.B.)
| | - Wlodzimierz Jerzy Musial
- Department of Cardiology, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.T.); (A.S.); (W.J.M.)
| | - Adrian Godlewski
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Michal Ciborowski
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Attila Gyenesei
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Adam Kretowski
- Clinical Research Centre, Medical University of Bialystok, 15-269 Bialystok, Poland; (W.B.); (M.N.); (A.S.); (J.R.); (A.G.); (M.C.); (A.G.); (A.K.)
| | - Karol Adam Kaminski
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, 15-269 Bialystok, Poland; (E.S.-S.); (M.D.); (M.L.); (M.S.); (Z.S.); (P.S.); (A.R.); (M.K.); (M.G.); (J.M.); (J.J.); (M.C.)
- Correspondence: ; Tel.: +48-85-8318-656
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21
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Kunasegaran T, Balasubramaniam VRMT, Arasoo VJT, Palanisamy UD, Ramadas A. The Modulation of Gut Microbiota Composition in the Pathophysiology of Gestational Diabetes Mellitus: A Systematic Review. BIOLOGY 2021; 10:biology10101027. [PMID: 34681126 PMCID: PMC8533096 DOI: 10.3390/biology10101027] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 10/08/2021] [Accepted: 10/08/2021] [Indexed: 02/08/2023]
Abstract
Simple Summary Recent studies have placed a great deal of emphasis on the importance of the microbiome, especially the link between the alteration of gut microbiota and multiple associated diseases. Gut microbiota changes in pregnancy have a significant impact on metabolic function and may contribute to gestational diabetes mellitus (GDM). Although GDM carries long-term health risks that affect women, there are also significant short- and severe long-term consequences for the offspring. Regardless, there is a notable lack of research focusing on the impact of prominent microorganisms involved in the development of GDM. A comprehensive review was conducted to gather relevant data on the types of microorganisms that have been associated with GDM. The review found that certain microorganisms impact the onset and progression of GDM during pregnancy. Several bacterial strains associated with GDM are influenced by a diet high in fat and low in fiber. Therefore, integrating the idea of a microbiome-based individualized dietary intervention into gestational diabetes management may be incredibly beneficial. Abstract General gut microbial dysbiosis in diabetes mellitus, including gestational diabetes mellitus (GDM), has been reported in a large body of literature. However, evidence investigating the association between specific taxonomic classes and GDM is lacking. Thus, we performed a systematic review of peer-reviewed observational studies and trials conducted among women with GDM within the last ten years using standard methodology. The National Institutes of Health (NIH) quality assessment tools were used to assess the quality of the included studies. Fourteen studies investigating microbial interactions with GDM were found to be relevant and included in this review. The synthesis of literature findings demonstrates that Bacteroidetes, Proteobacteria, Firmicutes, and Actinobacteria phyla, such as Desulfovibrio, Ruminococcaceae, P. distasonis, Enterobacteriaceae, Collinsella, and Prevotella, were positively associated with GDM. In contrast, Bifidobacterium and Faecalibacterium, which produce butyrate, are negatively associated with GDM. These bacteria were associated with inflammation, adiposity, and glucose intolerance in women with GDM. Lack of good diet management demonstrated the alteration of gut microbiota and its impact on GDM glucose homeostasis. The majority of the studies were of good quality. Therefore, there is great potential to incorporate personalized medicine targeting microbiome modulation through dietary intervention in the management of GDM.
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22
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Hu P, Chen X, Chu X, Fan M, Ye Y, Wang Y, Han M, Yang X, Yuan J, Zha L, Zhao B, Yang CX, Qi XR, Ning K, Debelius J, Ye W, Xiong B, Pan XF, Pan A. Association of Gut Microbiota during Early Pregnancy with Risk of Incident Gestational Diabetes Mellitus. J Clin Endocrinol Metab 2021; 106:e4128-e4141. [PMID: 34015117 DOI: 10.1210/clinem/dgab346] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Indexed: 01/02/2023]
Abstract
AIMS We aimed to assess the association between gut bacterial biomarkers during early pregnancy and subsequent risk of gestational diabetes mellitus (GDM) in Chinese pregnant women. METHODS Within the Tongji-Shuangliu Birth Cohort study, we conducted a nested case-control study among 201 incident GDM cases and 201 matched controls. Fecal samples were collected during early pregnancy (at 6-15 weeks), and GDM was diagnosed at 24 to 28 weeks of pregnancy. Community DNA isolated from fecal samples and V3-V4 region of 16S rRNA gene amplicon libraries were sequenced. RESULTS In GDM cases versus controls, Rothia, Actinomyces, Bifidobacterium, Adlercreutzia, and Coriobacteriaceae and Lachnospiraceae spp. were significantly reduced, while Enterobacteriaceae, Ruminococcaceae spp., and Veillonellaceae were overrepresented. In addition, the abundance of Staphylococcus relative to Clostridium, Roseburia, and Coriobacteriaceae as reference microorganisms were positively correlated with fasting blood glucose, 1-hour and 2-hour postprandial glucose levels. Adding microbial taxa to the base GDM prediction model with conventional risk factors increased the C-statistic significantly (P < 0.001) from 0.69 to 0.75. CONCLUSIONS Gut microbiota during early pregnancy was associated with subsequent risk of GDM. Several beneficial and commensal gut microorganisms showed inverse relations with incident GDM, while opportunistic pathogenic members were related to higher risk of incident GDM and positively correlated with glucose levels on OGTT.
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Affiliation(s)
- Ping Hu
- Key Laboratory of Environment & Health (Huazhong University of Science and Technology), Ministry of Education, Wuhan 430030, China
| | - Xiuyi Chen
- Key Laboratory of Environment & Health (Huazhong University of Science and Technology), Ministry of Education, Wuhan 430030, China
| | - Xufeng Chu
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Mengran Fan
- Key Laboratory of Environment & Health (Huazhong University of Science and Technology), Ministry of Education, Wuhan 430030, China
| | - Yi Ye
- Key Laboratory of Environment & Health (Huazhong University of Science and Technology), Ministry of Education, Wuhan 430030, China
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yi Wang
- Key Laboratory of Environment & Health (Huazhong University of Science and Technology), Ministry of Education, Wuhan 430030, China
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Maozhen Han
- Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xue Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Jiaying Yuan
- Department of Science and Education, Shuangliu Maternal and Child Health Hospital, Chengdu 610200, China
| | - Li Zha
- Department of Obstetrics and Gynecology, Shuangliu Maternal and Child Health Hospital, Chengdu 610200, China
| | - Bin Zhao
- Antenatal Care Clinics, Shuangliu Maternal and Child Health Hospital, Chengdu 610200, China
| | - Chun-Xia Yang
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Xiao-Rong Qi
- Department of Gynecology and Obstetrics, West China Second Hospital, State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610041, China
| | - Kang Ning
- Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Justin Debelius
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Weimin Ye
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Bo Xiong
- Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xiong-Fei Pan
- Key Laboratory of Environment & Health (Huazhong University of Science and Technology), Ministry of Education, Wuhan 430030, China
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - An Pan
- Key Laboratory of Environment & Health (Huazhong University of Science and Technology), Ministry of Education, Wuhan 430030, China
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
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Kong XJ, Liu J, Liu K, Koh M, Sherman H, Liu S, Tian R, Sukijthamapan P, Wang J, Fong M, Xu L, Clairmont C, Jeong MS, Li A, Lopes M, Hagan V, Dutton T, Chan ST(P, Lee H, Kendall A, Kwong K, Song Y. Probiotic and Oxytocin Combination Therapy in Patients with Autism Spectrum Disorder: A Randomized, Double-Blinded, Placebo-Controlled Pilot Trial. Nutrients 2021; 13:1552. [PMID: 34062986 PMCID: PMC8147925 DOI: 10.3390/nu13051552] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 05/01/2021] [Accepted: 05/02/2021] [Indexed: 12/14/2022] Open
Abstract
Autism spectrum disorder (ASD) is a rapidly growing neurodevelopmental disorder. Both probiotics and oxytocin were reported to have therapeutic potential; however, the combination therapy has not yet been studied. We conducted a randomized, double-blinded, placebo-controlled, 2-stage pilot trial in 35 individuals with ASD aged 3-20 years (median = 10.30 years). Subjects were randomly assigned to receive daily Lactobacillus plantarum PS128 probiotic (6 × 1010 CFUs) or a placebo for 28 weeks; starting on week 16, both groups received oxytocin. The primary outcomes measure socio-behavioral severity using the Social Responsiveness Scale (SRS) and Aberrant Behavior Checklist (ABC). The secondary outcomes include measures of the Clinical Global Impression (CGI) scale, fecal microbiome, blood serum inflammatory markers, and oxytocin. All outcomes were compared between the two groups at baseline, 16 weeks, and 28 weeks into treatment. We observed improvements in ABC and SRS scores and significant improvements in CGI-improvement between those receiving probiotics and oxytocin combination therapy compared to those receiving placebo (p < 0.05). A significant number of favorable gut microbiome network hubs were also identified after combination therapy (p < 0.05). The favorable social cognition response of the combination regimen is highly correlated with the abundance of the Eubacterium hallii group. Our findings suggest synergic effects between probiotics PS128 and oxytocin in ASD patients, although further investigation is warranted.
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Affiliation(s)
- Xue-Jun Kong
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Jun Liu
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
- Harvard Medical School, Boston, MA 02115, USA; (P.S.); (L.X.); (H.L.)
| | - Kevin Liu
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Madelyn Koh
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Hannah Sherman
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Siyu Liu
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Ruiyi Tian
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | | | - Jiuju Wang
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Michelle Fong
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Lei Xu
- Harvard Medical School, Boston, MA 02115, USA; (P.S.); (L.X.); (H.L.)
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Cullen Clairmont
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Min-Seo Jeong
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Alice Li
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Maria Lopes
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Veronica Hagan
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Tess Dutton
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Suk-Tak (Phoebe) Chan
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Hang Lee
- Harvard Medical School, Boston, MA 02115, USA; (P.S.); (L.X.); (H.L.)
- MGH Biostatistics Center, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Amy Kendall
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Kenneth Kwong
- Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA 02129, USA; (J.L.); (K.L.); (M.K.); (H.S.); (S.L.); (R.T.); (J.W.); (M.F.); (C.C.); (M.-S.J.); (A.L.); (M.L.); (V.H.); (T.D.); (S.-T.C.); (A.K.); (K.K.)
| | - Yiqing Song
- Department of Epidemiology, Indiana University, Richard M. Fairbanks School of Public Health, Indianapolis, IN 46202, USA;
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