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Li XM, Lv Q, Chen YJ, Yan LB, Xiong X. Association between childhood obesity and gut microbiota: 16S rRNA gene sequencing-based cohort study. World J Gastroenterol 2024; 30:2249-2257. [PMID: 38690025 PMCID: PMC11056921 DOI: 10.3748/wjg.v30.i16.2249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 02/18/2024] [Accepted: 03/22/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND This study aimed to identify characteristic gut genera in obese and normal-weight children (8-12 years old) using 16S rDNA sequencing. The research aimed to provide insights for mechanistic studies and prevention strategies for childhood obesity. Thirty normal-weight and thirty age- and sex-matched obese children were included. Questionnaires and body measurements were collected, and fecal samples underwent 16S rDNA sequencing. Significant differences in body mass index (BMI) and body-fat percentage were observed between the groups. Analysis of gut microbiota diversity revealed lower α-diversity in obese children. Di-fferences in gut microbiota composition were found between the two groups. Prevotella and Firmicutes were more abundant in the obese group, while Bacteroides and Sanguibacteroides were more prevalent in the control group. AIM To identify the characteristic gut genera in obese and normal-weight children (8-12-year-old) using 16S rDNA sequencing, and provide a basis for subsequent mechanistic studies and prevention strategies for childhood obesity. METHODS Thirty each normal-weight, 1:1 matched for age and sex, and obese children, with an obese status from 2020 to 2022, were included in the control and obese groups, respectively. Basic information was collected through questionnaires and body measurements were obtained from both obese and normal-weight children. Fecal samples were collected from both groups and subjected to 16S rDNA sequencing using an Illumina MiSeq sequencing platform for gut microbiota diversity analysis. RESULTS Significant differences in BMI and body-fat percentage were observed between the two groups. The Ace and Chao1 indices were significantly lower in the obese group than those in the control group, whereas differences were not significant in the Shannon and Simpson indices. Kruskal-Wallis tests indicated significant differences in unweighted and weighted UniFrac distances between the gut microbiota of normal-weight and obese children (P < 0.01), suggesting substantial disparities in both the species and quantity of gut microbiota between the two groups. Prevotella, Firmicutes, Bacteroides, and Sanguibacteroides were more abundant in the obese and control groups, respectively. Heatmap results demonstrated significant differences in the gut microbiota composition between obese and normal-weight children. CONCLUSION Obese children exhibited lower α-diversity in their gut microbiota than did the normal-weight children. Significant differences were observed in the composition of gut microbiota between obese and normal-weight children.
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Affiliation(s)
- Xu-Ming Li
- Laboratory Department, Nanjing Medical University Affiliated Obstetrics and Gynecology Hospital (Nanjing Maternal and Child Health Hospital), Nanjing 210004, Jiangsu Province, China
| | - Qing Lv
- Department of Pediatrics, Shenzhen University General Hospital, Shenzhen 518055, Guangdong Province, China
| | - Ya-Jun Chen
- Department of Inspection Division, Women’s Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing 210004, Jiangsu Province, China
| | - Lu-Biao Yan
- Department of Pediatrics, Women’s Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing 210004, Jiangsu Province, China
| | - Xin Xiong
- Department of Neonatology, Chenzhou First People’s Hospital, Chenzhou 423000, Hunan Province, China
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Yang Y, Yan J, Li S, Liu M, Han R, Wang Y, Wang Z, Wang D. Efficacy of fecal microbiota transplantation in type 2 diabetes mellitus: a systematic review and meta-analysis. Endocrine 2024; 84:48-62. [PMID: 38001323 DOI: 10.1007/s12020-023-03606-1] [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: 05/28/2023] [Accepted: 10/29/2023] [Indexed: 11/26/2023]
Abstract
OBJECTIVE Type 2 diabetes mellitus (T2DM) is one of the common metabolic diseases worldwide, and studies have found significant differences in the composition and ratio of intestinal flora between patients with T2DM and normal glucose tolerance, and fecal microbiota transplantation (FMT) may modulate the composition of the intestinal microbiota thereby alleviating the hyperglycemic state. We conducted a meta-analysis and systematic review of existing randomized controlled trials (RCTs) to assess the efficacy of FMT in T2DM. METHODS We conducted a computer search of PubMed, Embase, The Cochrane Library, and Web of Science to screen randomized controlled trials studies on FMT treatment for T2DM and extracted data from studies that met inclusion criteria. RevMan 5.4 software and Stata 11 software was used for meta-analysis. The indexes of Hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), postprandial blood glucose (PBG), homeostasis model assessment of insulin resistance (HOMA-IR), triglycerides (TG), cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), body mass index (BMI), Aspartate Aminotransferase (AST), Alanine Transaminase (ALT), Systolic blood pressure (SBP) and Diastolic blood pressure (DBP) were mainly evaluated after FMT treatment of T2DM patients, and the changes of intestinal flora were evaluated. RESULTS Four RCTs met the inclusion criteria and were included in the meta-analysis. Results of the meta-analysis showed that compared with the non-FMT group, FMT combined treatment could significantly reduce the PBG level in patients with type 2 diabetes (MD = -0.51, 95% CI: -1.42-0.40, P = 0.27). Compared with single FMT treatment, FMT combined treatment could reduce TG levels in patients with type 2 diabetes (MD = -0.60, 95% CI: -1.12~-0.07, P = 0.03). The levels of TG (MD = -0.26, 95% CI: -0.51~-0.02, P = 0.03), HOMA-IR (MD = -2.73, 95% CI: -4.71~0.75, P = 0.007) and HDL (MD = -0.06,95% CI: -0.10~-0.02, P = 0.003) were significantly decreased after treatment in the single FMT group. The level of TC (MD = -0.65, 95% CI: -1.00~-0.31, P = 0.0002) was significantly decreased after FMT combined treatment. Compared with before treatment, ALT (MD = -2.52, 95% CI: -3.86~-1.17, P = 0.0002) and DBP (MD = -2, 95% CI: -3.32~0.68, P = 0.003) levels decreased after treatment in the single FMT group and the FMT combined group. FPG (MD = -0.94, 95% CI: -1.86~-0.02, P = 0.04), TG (MD = -0.73, 95% CI: -1.42~-0.04, P = 0.04) and TC (MD = -0.94, 95% CI: -1.45~-0.43, P = 0.0003) were significantly decreased after combined drug and diet therapy. Secondly, FMT can promote the colonization and growth of donor-related flora in patients with type 2 diabetes. CONCLUSION In patients with type 2 diabetes mellitus, FMT treatment can reduce the levels of PBG, TG, HOMA-IR, TC, ALT, and DBP, especially in the combined treatment regimen. In addition, FMT can reshape the intestinal flora and establish the balance of dominant flora.
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Affiliation(s)
- Yan Yang
- Clinical Medical College of Hebei University of Engineering, Handan, Hebei, 056000, China
| | - Jingjing Yan
- Clinical Medical College of Hebei University of Engineering, Handan, Hebei, 056000, China
| | - Shuo Li
- Clinical Medical College of Hebei University of Engineering, Handan, Hebei, 056000, China
| | - Mengru Liu
- Clinical Medical College of Hebei University of Engineering, Handan, Hebei, 056000, China
| | - Ruimin Han
- Clinical Medical College of Hebei University of Engineering, Handan, Hebei, 056000, China
| | - Yinping Wang
- Clinical Medical College of Hebei University of Engineering, Handan, Hebei, 056000, China
| | - Zhen Wang
- Clinical Medical College of Hebei University of Engineering, Handan, Hebei, 056000, China.
| | - Defeng Wang
- Endocrinology Department of Affiliated Hospital of Hebei University of Engineering, Handan, Hebei, 056000, China.
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Tang LT, Feng L, Cao HY, Shi R, Luo BB, Zhang YB, Liu YM, Zhang J, Li SY. Investigation of the causal relationship between inflammatory bowel disease and type 2 diabetes mellitus: a Mendelian randomization study. Front Genet 2024; 15:1325401. [PMID: 38435063 PMCID: PMC10904574 DOI: 10.3389/fgene.2024.1325401] [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: 10/21/2023] [Accepted: 01/31/2024] [Indexed: 03/05/2024] Open
Abstract
Background: Type 2 diabetes mellitus (T2DM) and inflammatory bowel disease (IBD) have been associated, according to various epidemiological research. This study uses Mendelian randomization (MR) to investigate the causal link between T2DM and IBD. Methods: To investigate the causal relationship between IBD and T2DM risk using European population data from the genome-wide association study (GWAS) summary datasets, we constructed a two-sample MR study to evaluate the genetically predicted impacts of liability towards IBD outcomes on T2DM risk. As instrumental variables (IVs), we chose 26 single nucleotide polymorphisms (SNPs) associated with IBD exposure data. The European T2DM GWAS data was obtained from the IEU OpenGWAS Project database, which contains 298,957 cases as the outcome data. The causal relationship between T2DM and IBD using a reverse MR analysis was also performed. Results: The two-sample MR analysis, with the Bonferroni adjustment for multiple testing, revealed that T2DM risk in Europeans is unaffected by their IBD liability (odds ratio (OR): 0.950-1.066, 95% confidence interval (CI): 0.885-1.019, p = 0.152-0.926). The effects of liability to T2DM on IBD were not supported by the reverse MR analysis either (OR: 0.739-1.131, 95% confidence interval (CI): 0.651-1.100, p = 0.058-0.832). MR analysis of IBS on T2DM also have no significant causal relationship (OR: 0.003-1.007, 95% confidence interval (CI): 1.013-5.791, p = 0.069-0.790). FUMA precisely mapped 22 protein-coding genes utilizing significant SNPs of T2DM acquired from GWAS. Conclusion: The MR study showed that the existing evidence did not support the significant causal effect of IBD on T2DM, nor did it support the causal impact of T2DM on IBD.
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Affiliation(s)
- Ling-tong Tang
- Department of Clinical Laboratory, Yan’an Hospital Affiliated to Kunming Medical University, Kunming, Yunnan, China
| | - Lei Feng
- Department of Clinical Laboratory, Yan’an Hospital Affiliated to Kunming Medical University, Kunming, Yunnan, China
| | - Hui-ying Cao
- Department of Clinical Laboratory, Yan’an Hospital Affiliated to Kunming Medical University, Kunming, Yunnan, China
| | - Rui Shi
- Department of Clinical Laboratory, Sixth Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Bei-bei Luo
- Department of Clinical Laboratory, Sixth Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Yan-bi Zhang
- Department of Clinical Laboratory, Sixth Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Yan-mei Liu
- Department of Clinical Laboratory, Yan’an Hospital Affiliated to Kunming Medical University, Kunming, Yunnan, China
| | - Jian Zhang
- Department of Clinical Laboratory, Yan’an Hospital Affiliated to Kunming Medical University, Kunming, Yunnan, China
| | - Shuang-yue Li
- Department of Clinical Laboratory, Yan’an Hospital Affiliated to Kunming Medical University, Kunming, Yunnan, China
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Portincasa P, Khalil M, Graziani A, Frühbeck G, Baffy G, Garruti G, Di Ciaula A, Bonfrate L. Gut microbes in metabolic disturbances. Promising role for therapeutic manipulations? Eur J Intern Med 2024; 119:13-30. [PMID: 37802720 DOI: 10.1016/j.ejim.2023.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 08/30/2023] [Accepted: 10/02/2023] [Indexed: 10/08/2023]
Abstract
The prevalence of overweight, obesity, type 2 diabetes, metabolic syndrome and steatotic liver disease is rapidly increasing worldwide with a huge economic burden in terms of morbidity and mortality. Several genetic and environmental factors are involved in the onset and development of metabolic disorders and related complications. A critical role also exists for the gut microbiota, a complex polymicrobial ecology at the interface of the internal and external environment. The gut microbiota contributes to food digestion and transformation, caloric intake, and immune response of the host, keeping the homeostatic control in health. Mechanisms of disease include enhanced energy extraction from the non-digestible dietary carbohydrates, increased gut permeability and translocation of bacterial metabolites which activate a chronic low-grade systemic inflammation and insulin resistance, as precursors of tangible metabolic disorders involving glucose and lipid homeostasis. The ultimate causative role of gut microbiota in this respect remains to be elucidated, as well as the therapeutic value of manipulating the gut microbiota by diet, pre- and pro- synbiotics, or fecal microbial transplantation.
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Affiliation(s)
- Piero Portincasa
- Clinica Medica "A. Murri", Department of Precision and Regenerative Medicine and Ionian Area (DiMePre-J), University of Bari "Aldo Moro" Medical School, Policlinico Hospital, Piazza G. Cesare 11, Bari 70124, Italy.
| | - Mohamad Khalil
- Clinica Medica "A. Murri", Department of Precision and Regenerative Medicine and Ionian Area (DiMePre-J), University of Bari "Aldo Moro" Medical School, Policlinico Hospital, Piazza G. Cesare 11, Bari 70124, Italy
| | - Annarita Graziani
- Institut AllergoSan Pharmazeutische Produkte Forschungs- und Vertriebs GmbH, Graz, Austria
| | - Gema Frühbeck
- Metabolic Research Laboratory, Clínica Universidad de Navarra, Pamplona, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), ISCIII, Pamplona, Spain; Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain; Department of Endocrinology & Nutrition, Clínica Universidad de Navarra, Pamplona, Spain
| | - Gyorgy Baffy
- Department of Medicine, VA Boston Healthcare System and Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02130, USA
| | - Gabriella Garruti
- Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, Department of Precision and Regenerative Medicine and Ionian Area (DiMePre-J), University of Bari Medical School, Bari 70124, Italy
| | - Agostino Di Ciaula
- Clinica Medica "A. Murri", Department of Precision and Regenerative Medicine and Ionian Area (DiMePre-J), University of Bari "Aldo Moro" Medical School, Policlinico Hospital, Piazza G. Cesare 11, Bari 70124, Italy.
| | - Leonilde Bonfrate
- Clinica Medica "A. Murri", Department of Precision and Regenerative Medicine and Ionian Area (DiMePre-J), University of Bari "Aldo Moro" Medical School, Policlinico Hospital, Piazza G. Cesare 11, Bari 70124, Italy
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Xie X, Wu C, Hao Y, Wang T, Yang Y, Cai P, Zhang Y, Huang J, Deng K, Yan D, Lin H. Benefits and risks of drug combination therapy for diabetes mellitus and its complications: a comprehensive review. Front Endocrinol (Lausanne) 2023; 14:1301093. [PMID: 38179301 PMCID: PMC10766371 DOI: 10.3389/fendo.2023.1301093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 11/27/2023] [Indexed: 01/06/2024] Open
Abstract
Diabetes is a chronic metabolic disease, and its therapeutic goals focus on the effective management of blood glucose and various complications. Drug combination therapy has emerged as a comprehensive treatment approach for diabetes. An increasing number of studies have shown that, compared with monotherapy, combination therapy can bring significant clinical benefits while controlling blood glucose, weight, and blood pressure, as well as mitigating damage from certain complications and delaying their progression in diabetes, including both type 1 diabetes (T1D), type 2 diabetes (T2D) and related complications. This evidence provides strong support for the recommendation of combination therapy for diabetes and highlights the importance of combined treatment. In this review, we first provided a brief overview of the phenotype and pathogenesis of diabetes and discussed several conventional anti-diabetic medications currently used for the treatment of diabetes. We then reviewed several clinical trials and pre-clinical animal experiments on T1D, T2D, and their common complications to evaluate the efficacy and safety of different classes of drug combinations. In general, combination therapy plays a pivotal role in the management of diabetes. Integrating the effectiveness of multiple drugs enables more comprehensive and effective control of blood glucose without increasing the risk of hypoglycemia or other serious adverse events. However, specific treatment regimens should be tailored to individual patients and implemented under the guidance of healthcare professionals.
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Affiliation(s)
- Xueqin Xie
- Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Changchun Wu
- Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuduo Hao
- Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Tianyu Wang
- Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuhe Yang
- Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Peiling Cai
- School of Basic Medical Sciences, Chengdu University, Chengdu, China
| | - Yang Zhang
- Innovative Institute of Chinese Medicine and Pharmacy, Academy for Interdiscipline, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Jian Huang
- Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Kejun Deng
- Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Dan Yan
- Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Hao Lin
- Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
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