老年维持性血液透析患者肠道菌群分布与营养状态研究

Relationship between gut microbiota distribution and nutritional status in elderly patients with maintenance hemodialysis

【摘要】目的 探讨老年维持性血液透析(MHD)患者肠道菌群分布与营养状态和生活质量的相关性。方法 选取2021年2月至2023年2月于重庆医科大学附属大足医院接受规律MHD治疗的156例慢性肾功能衰竭患者为研究对象。采集患者新鲜粪便标本,根据肠道菌群涂片检查结果将其分为菌群正常组(n=53)和菌群失衡组(n=103)。经16S rDNA实时荧光定量聚合酶链式反应法检测并比较两组患者粪便双歧杆菌、乳酸杆菌、大肠杆菌以及肠球菌定量分析结果。收集患者营养状况指标,包括体质量指数(BMI)、血红蛋白、白蛋白(Alb)以及微型营养评价量表(MNA)评分。采用肾脏疾病生存质量简表1.3评估患者生存质量。采用Pearson相关性分析评估MHD患者肠道菌群定量检测结果与营养状态和生活质量的相关性。结果 156例MHD患者中肠道菌群正常者53例(33.97%),Ⅰ度菌群失衡者67例(42.95%),Ⅱ度菌群失衡者31例(19.87%),Ⅲ度菌群失衡者5例(3.21%)。菌群失衡组双歧杆菌[(6.73±1.09)和(9.45±1.26)lg CFU/g]及乳酸杆菌数量[(7.14±0.86)和(9.92±1.03)lg CFU/g]显著低于正常组,大肠杆菌[(8.75±1.12)和(8.06±0.94)lg CFU/g]及肠球菌数量[(9.68±1.05)和(9.13±1.27)lg CFU/g]显著高于正常组,差异均有统计学意义(均P<0.05)。菌群失衡组BMI[(20.34±3.51)和(21.68±3.27)kg/m²]、ALB[(28.53±4.29)和(31.47±4.05)g/L]、MNA评分[(21.36±4.27)和(25.14±3.98)分]及36条目简明健康状况调查问卷(SF-36)评分[(52.64±9.13)和(58.71±9.48)分]显著低于正常组,差异均有统计学意义(均P<0.05)。Pearson相关性分析显示,BMI、Alb、MNA评分和SF-36评分与肠道双歧杆菌(r=0.417,0.309,0.461,0.382；P<0.05)和乳酸杆菌(r=0.463,0.357,0.507,0.417；P<0.001)数量均呈正相关,与肠道大肠杆菌(r=-0.389,-0.426,-0.435,-0.354；P<0.001)和肠球菌(r=-0.326,-0.512,-0.548,-0.496；P<0.001)数量均呈负相关。结论 老年MHD患者营养状态和生活质量较差,且两者均与肠道菌群数量存在密切联系。

基金项目:重庆市科技局科研基金(2022L027)；重庆市科技计划项目(DZKJ2021ACC1025)

【Abstract】Objective To explore the relationship between gut microbiota distribution and the nutritional status and quality of life in elderly patients undergoing maintenance hemodialysis (MHD). Methods From February 2021 to February 2023,156 chronic renal failure patients who received regular MHD in the Affiliated Dazu′s Hospital of Chongqing Medical University were selected as the study subjects. Fresh fecal samples were collected, and the patients were divided into a normal group (n=53) and a dysbiosis group (n=103) according to the results of gut microbiota smear examination. The real-time fluorescence quantitative polymerase chain reaction (PCR) of the bacterial 16S rDNA gen was performed, and the two groups were compared in the quantitative results of fecal Bifidobacterum, Lactobacillus, Escherichia coli, and Enterococcus. The nutritional status indicators, including body mass index (BMI), hemoglobin (Hb), albumin (Alb), and scores on mini-nutritional assessment (MNA), were collected for both groups. The quality of life was evaluated using kidney disease quality of life short form (KDQOL-SF)1.3. Pearson correlation analysis was conducted to analyze the correlation between quantitative findings of gut microbiota and the nutritional status and quality of life in MHD patients. ResultsAmong 156 MHD patients, 53 (33.97%) were of normal gut microbiota, 67 (42.95%) of Degree Ⅰ gut microbiota dysbiosis, 31 (19.87%) of Degree Ⅱ gut microbiota dysbiosis, and 5 (3.21%) of Degree Ⅲ gut microbiota dysbiosis. The Bifidobacterium count [(6.73±1.09) vs (9.45±1.26) lg CFU/g] and Lactobacillus count [(7.14±0.86) vs (9.92±1.03) lg CFU/g] in the dysbiosis group were lower, while the Escherichia coli count [(8.75±1.12) vs (8.06±0.94) lg CFU/g] and Enterococcus count [(9.68±1.05) vs (9.13±1.27) lg CFU/g] were higher than those in the normal group, with all differences being statistically significant (P<0.05 for all). The BMI [(20.34±3.51) vs (21.68±3.27) kg/m²], Alb [(28.53±4.29) vs (31.47±4.05) g/L], MNA score [(21.36±4.27) vs (25.14±3.98) points] and 36-item short-form (SF-36) score [(52.64±9.13) vs (58.71±9.48) points] in the dysbiosis group were lower than those in the normal group, with all differences being statistically significant (P<0.05 for all). Pearson product-moment coefficient analysis showed that BMI, Alb, MNA score and SF-36 score were positively correlated with intestinal Bifidobacterium count (r=0.417,0.309,0.461,0.382; P<0.05) and Lactobacillus count (r=0.463,0.357,0.507,0.417; P<0.001), and were negatively correlated with intestinal Escherichia coli count (r=-0.389, -0.426, -0.435, -0.354; P<0.001) and Enterococcus count (r=-0.326, -0.512,-0.548, -0.496; P<0.001). Conclusion The nutritional status and quality of life in elderly MHD patients are poor, and both are closely related to the gut microbiota count.

This work was supported by Research Fund of Chongqing Science and Technology Bureau (2022L027) and Chongqing Science and Technology Project (DZKJ2021ACC1025).