Influence of gut-brain axis interaction on disease condition and prognosis of patients with obesity and type 2 diabetes mellitus after bariatric and metabolic surgery
-
摘要:目的
探讨肠-脑轴交互效应对肥胖合并2型糖尿病(T2DM)患者减重代谢手术后病情及预后的影响。
方法选取50例接受减重代谢手术治疗的肥胖合并T2DM患者作为研究对象，比较患者治疗前后血清胃肠肽类激素[胰岛素(Ins)、瘦素(Lep)、胰高血糖素样肽-1(GLP-1)、饥饿素(Ghr)]、糖化血红蛋白(HbA1c)水平和体质量指数(BMI)，并对患者的粪便样本进行16S rRNA扩增子测序，明确肠道菌群的组成与丰度。采用Pearson直线相关分析、Spearman相关分析法评估血清胃肠肽类激素、肠道菌群丰度指标与BMI、HbA1c的相关性。随访1年，记录患者不良终点事件发生情况，采用多元Logistic回归分析探讨肥胖合并T2DM患者减重代谢手术后1年预后的影响因素。
结果与治疗前比较，治疗后患者的BMI和血清HbA1c、Ghr水平降低，血清Ins、Lep、GLP-1水平升高，差异有统计学意义(P < 0.05); 与治疗前比较，治疗后患者肠道菌群丰度指标Shannon指数、Simpson指数升高，差异有统计学意义(P < 0.05); 治疗后，肠道菌群中的厚壁菌门、拟杆菌门占比低于治疗前，变形菌门占比高于治疗前，差异有统计学意义(P < 0.05)。相关性分析结果显示，血清Ins、Lep、GLP-1水平均分别与BMI、HbA1c呈负相关(P < 0.05), 血清Ghr水平分别与BMI、HbA1c呈正相关(P < 0.05), Shannon指数、Simpson指数均分别与BMI、HbA1c呈负相关(P < 0.05)。多元Logistic回归分析结果显示，血清Lep、血清GLP-1、Simpson指数是肥胖合并T2DM患者减重代谢手术后预后的保护性因素(OR=0.523、0.417、0.613, P=0.020、0.015、0.026), 血清HbA1c是肥胖合并T2DM患者减重代谢手术后预后的危险性因素(OR=2.913, P=0.029)。
结论减重代谢手术能够调节肥胖合并T2DM患者的肠道菌群结构和胃肠肽类激素水平，通过影响肠-脑轴交互效应，改善患者的病情和预后。
Abstract:ObjectiveTo investigate the impact of gut-brain axis interaction on disease condition and prognosis in patients with obesity and type 2 diabetes mellitus (T2DM) following bariatric and metabolic surgery.
MethodsFifty patients with obesity and T2DM who underwent bariatric and metabolic surgery were recruited as study subjects. Serum levels of gastrointestinal peptide hormones[insulin (Ins), leptin (Lep), glucagon-like peptide-1 (GLP-1), ghrelin (Ghr)], glycated hemoglobin (HbA1c), and body mass index (BMI) were compared before and after treatment. Additionally, 16S rRNA amplicon sequencing of fecal samples was performed to determine the composition and abundance of gut microbiota. Pearson's correlation analysis and Spearman rank correlation analysis were used to assess the correlations of serum gastrointestinal peptide hormones, gut microbiota abundance indices with BMI and HbA1c. Patients were followed up for one year, and the occurrence of adverse outcomes was recorded. Multivariate logistic regression analysis was employed to explore influencing factors of the prognosis of patients with obesity and T2DM one year after bariatric and metabolic surgery.
ResultsCompared with pre-treatment levels, post-treatment BMI, serum HbA1c, and Ghr levels decreased, while serum Ins, Lep, and GLP-1 levels increased (P < 0.05). Post-treatment, gutmicrobiota abundanceindices, including Shannon and Simpson indices, increased significantly compared to pre-treatment levels (P < 0.05). After treatment, the proportions of Firmicutes, Bacteroidetes in the gut microbiota were lower than pre-treatment, but the proportion of Proteobacteria was higher than pre-treatment (P < 0.05). Correlation analysis revealed that serum Ins, Lep, and GLP-1 levels were separately negatively correlated with BMI and HbA1c (P < 0.05), while serum Ghr level was separately positively correlated with BMI and HbA1c (P < 0.05). Both Shannon and Simpson indices were negatively correlated with BMI and HbA1c (P < 0.05). Multivariate Logistic regression analysis showed that serum Lep, serum GLP-1, and Simpson index were protective factors for prognosis in patients with obesity and T2DM after bariatricand metabolic surgery (OR=0.523, 0.417, 0.613, P=0.020, 0.015, 0.026), while serum HbA1c was a risk factor (OR=2.913, P=0.029).
ConclusionBariatric and metabolicsurgery can regulate gut microbiota composition and gastrointestinal peptide hormone levels in patients with obesity and T2DM, thereby improving disease condition and prognosis through gut-brain axis interaction.
-
-
表 1 50例患者治疗前后血清指标及体质量指数比较(x±s)
时点 BMI/(kg/m2) HbA1c/% Ins/(pg/mL) Lep/(pg/mL) GLP-1/(pg/mL) Ghr/(pg/mL) 治疗前 32.8±2.4 8.1±1.2 260.8±23.2 5.8±0.9 82.8±9.4 272.8±20.6 治疗后 26.1±1.8* 5.7±0.5* 311.2±42.8* 7.2±1.4* 98.2±11.3* 223.2±14.8* BMI: 体质量指数; HbA1c: 糖化血红蛋白; Ins: 胰岛素; Lep: 瘦素; GLP-1: 胰高血糖素样肽-1; Ghr: 饥饿素。与治疗前比较, * P < 0.05。 
下载: 导出CSV
表 2 50例患者治疗前后肠道菌群丰度指标比较(x±s)
时点 OTU丰度 ACE指数 Chao指数 Shannon指数 Simpson指数 治疗前 128.2±10.1 168.1±23.6 208.3±9.7 2.84±0.22 0.18±0.04 治疗后 125.3±9.4 175.7±33.2 211.5±13.0 3.02±0.43* 0.22±0.06* OTU: 操作分类单元。与治疗前比较, * P < 0.05。
下载: 导出CSV
表 3 50例患者治疗前后肠道菌群组成情况比较(x±s)
% 时点 厚壁菌门 拟杆菌门 变形菌门 治疗前 49.32±8.26 30.53±5.67 11.65±4.98 治疗后 44.22±6.67* 21.23±4.72* 19.92±6.24* 与治疗前比较, * P < 0.05。
下载: 导出CSV
表 4 各项临床指标的相关性分析
指标 BMI HbA1c r P r P 血清Ins -0.779 0.026 -0.859 0.013 血清Lep -0.791 0.030 -0.725 0.040 血清GLP-1 -0.689 0.047 -0.708 0.042 血清Ghr 0.702 0.043 0.731 0.039 Shannon指数 -0.812 0.021 -0.866 0.011 Simpson指数 -0.802 0.023 -0.828 0.019
下载: 导出CSV
表 5 患者预后影响因素的多元Logistic回归分析
变量 β S. E. Wald系数 OR P 95%CI 年龄 0.218 0.177 1.521 1.244 0.088 0.896~1.504 BMI 0.439 0.283 2.405 1.551 0.071 0.927~2.038 血清HbA1c 1.069 0.462 5.356 2.913 0.029 2.462~3.423 血清Ins 0.886 0.512 2.996 2.426 0.058 1.589~3.261 血清Lep -0.648 0.257 6.361 0.523 0.020 0.316~0.865 血清GLP-1 -0.875 0.322 7.379 0.417 0.015 2.295~3.512 血清Ghr 0.758 0.435 3.040 2.135 0.055 1.867~2.460 OTU丰度 0.704 0.408 2.974 2.031 0.059 1.725~2.386 ACE指数 0.229 0.316 0.528 1.258 0.128 0.677~2.337 Chao指数 0.709 0.422 2.819 2.031 0.062 1.214~2.925 Shannon指数 -0.322 0.294 1.196 0.725 0.095 0.407~1.290 Simpson指数 -0.489 0.203 5.812 0.613 0.026 0.412~0.913
下载: 导出CSV
-
[1] YANPING W, GAO X F, CHENG Y Z, et al. The interaction between obesity and visceral hypersensitivity[J]. J Gastroenterol Hepatol, 2023, 38(3): 370-377.
[2] CABOU C, BURCELIN R. GLP-1, the gut-brain, and brain-periphery axes[J]. Rev Diabet Stud, 2011, 8(3): 418-431.
[3] CHEN G M, DONAHOO W T, CARDEL M I, et al. Variation by race/ethnicity in the utilization and weight loss following metabolic bariatric surgery[J]. Surg Obes Relat Dis, 2023, 19(12): 1391-1404.
[4] KÖHLER C A, MAES M, SLYEPCHENKO A, et al. The gut-brain axis, including the microbiome, leaky gut and bacterial translocation: mechanisms and pathophysiological role in Alzheimer's disease[J]. Curr Pharm Des, 2016, 22(40): 6152-6166.
[5] LONGO S, RIZZA S, FEDERICI M. Microbiota-gut-brain axis: relationships among the vagus nerve, gut microbiota, obesity, and diabetes[J]. Acta Diabetol, 2023, 60(8): 1007-1017.
[6] ZHANG Q, JIN K Y, CHEN B, et al. Overnutrition induced cognitive impairment: insulin resistance, gut-brain axis, and neuroinflammation[J]. Front Neurosci, 2022, 16: 884579.
[7] FERNÁNDEZ REAL J M, MORENO-NAVARRETE J M, MANCO M. Iron influences on the Gut-Brain axis and development of type 2 diabetes[J]. Crit Rev Food Sci Nutr, 2019, 59(3): 443-449.
[8] 张成岗, 巩文静, 李志慧, 等. 双脑模型假说—由肠道菌群微生态构建的"菌脑" 可能是人体对物质记忆的"第二大脑"[J]. 实用临床医药杂志, 2019, 23(6): 1-6. doi: 10.7619/jcmp.201906001 [9] ZHAO Q H, CHEN J L, WU M J, et al. Microbiota from healthy mice alleviates cognitive decline via reshaping the gut-brain metabolic axis in diabetic mice[J]. Chem Biol Interact, 2023, 382: 110638.
[10] CARACCIOLO B, XU W L, COLLINS S, et al. Cognitive decline, dietary factors and gut-brain interactions[J]. Mech Ageing Dev, 2014, 136/137: 59-69.
[11] CHEN S M, ZENG F S, FU W W, et al. White hyacinth bean polysaccharide ameliorates diabetes via microbiota-gut-brain axis in type 2 diabetes mellitus rats[J]. Int J Biol Macromol, 2023, 253(Pt 6): 127307.
[12] YIN M S, WANG Y, HAN M Y, et al. Mechanisms of bariatric surgery for weight loss and diabetes remission[J]. J Diabetes, 2023, 15(9): 736-752.
[13] SANTOS-MARCOS J A, MORA-ORTIZ M, TENA-SEMPERE M, et al. Interaction between gut microbiota and sex hormones and their relation to sexual dimorphism in metabolic diseases[J]. Biol Sex Differ, 2023, 14(1): 4.
[14] DOMÍNGUEZ ALVARADO G A, GARCÍA MURILLO J S, ZAMBRANO SILVA L P, et al. Comment on: insulin resistance levels predicted metabolic improvement and weight loss after metabolic surgery in Chinese patients with type 2 diabetes[J]. Surg Obes Relat Dis, 2024, 20(2): 213-214.
[15] AGAGVNDVZ D, ICER M A, YESILDEMIR O, et al. The roles of dietary lipids and lipidomics in gut-brain axis in type 2 diabetes mellitus[J]. J Transl Med, 2023, 21(1): 240.
[16] LEE S J, SEO W J, PARK S, et al. Comparative analysis of various weight loss success criteria models after bariatric metabolic surgery in Korean morbid obese patients[J]. J Metab Bariatr Surg, 2023, 12(2): 67-75.
[17] THAKER V V, KWEE L C, CHEN H Y, et al. Metabolite signature of diabetes remission in individuals with obesity undergoing weight loss interventions[J]. Obesity, 2024, 32(2): 304-314.
[18] CHAIYASOOT K, SAKAI N S, ZAKERI R, et al. Weight-loss Independent Clinical and Metabolic Biomarkers Associated with Type 2 Diabetes Remission Post-bariatric/metabolic Surgery[J]. Obes Surg, 2023, 33(12): 3988-3998.
[19] FLANAGAN E W, SPANN R, BERRY S E, et al. New insights in the mechanisms of weight-loss maintenance: summary from a Pennington symposium[J]. Obesity, 2023, 31(12): 2895-2908.
[20] SHAH A, LIANG N E, BRUZONI M, et al. Outcomes after metabolic and bariatric surgery in preteens versus teens using the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program database and center-specific data[J]. Obesity, 2024, 32(1): 150-155.
-
期刊类型引用(3)
1. 赵秀芬，杨名钫，程思思，曾超男，胡秋兰，杨丽珠. E-Coach慢病管理模式在根治性前列腺切除术患者中的应用. 卫生职业教育. 2024(19): 152-156 . 
百度学术
2. 汤爱玲，许方蕾. 腹腔镜前列腺癌根治术患者出院准备度预警模型的构建. 实用临床医药杂志. 2023(20): 16-20+25 . 本站查看
3. 张笑，孙健，丁锡奇. 腹腔镜前列腺癌根治术治疗早期前列腺癌对雄激素水平及术后尿失禁发生率的影响. 国际医药卫生导报. 2022(18): 2583-2586 . 百度学术
其他类型引用(0)
计量
- 文章访问数: 138
- HTML全文浏览量: 20
- PDF下载量: 11
- 被引次数: 3
苏公网安备 32100302010246号
