脓毒症休克患者肠道菌群结构差异性表达与预后的关系

doi:10.3969/j.issn.1673-8640.2025.05.007

摘要/Abstract

摘要：

目的探讨脓毒症休克患者肠道菌群结构差异性表达与预后的关系。方法招募2020年1月—2022年1月衡水市人民医院直接入住或从其他病房转入重症监护病房（ICU）的81例重症患者，其中脓毒症休克患者34例（脓毒症休克组），其余47例患者纳入非脓毒症休克组。采集患者直肠拭子，对16S rRNA基因的V3-V4高变区进行测序，评估患者肠道微生物群构成。分析Beta多样性、操作分类单位（OTU），以及肠道微生物群与相关变量的相互作用。通过线性混合模型筛选与脓毒症特别相关的OTU。结果与非脓毒症休克评估组比较，脓毒症休克组年龄、C反应蛋白（CRP）水平、序贯器官衰竭评估（SOFA）评分、急性生理与慢性健康评分Ⅱ（APACHEⅡ）和ICU停留时间均增加（P<0.05）。脓毒症休克患者肠道菌群多样性较低（香农指数P=0.006，辛普森倒数P<0.001）。脓毒症休克组和非脓毒症休克组Beta多样性差异有统计学意义（伪F值=1.19，P=0.038）。通过线性混合模型检索到24个与脓毒症休克相关的OTU，关联最强的4个OTU中，Parabacteroides distasonis、Bilophila spp在脓毒症休克患者样本中的比例高于非脓毒症休克患者，Ezakiella、Megasphaera则相反。结论脓毒症休克患者肠道有益菌属丰度较低，病原体丰度较高，特定的肠道菌群特征或可预测ICU患者脓毒症发展。

关键词: 肠道菌群, 脓毒症休克, 重症监护病房

Abstract:

Objective To investigate the relationship between the differential expression of gut microbiota structure and prognosis in patients with septic shock. Methods Totally，81 critically sick patients were enrolled，including 34 cases of septic shock，who were either directly admitted to the intensive care unit（ICU）or transferred to the ICU from wards from January 2020 to January 2022. Perirectal swabs were collected from the patients during ICU admission. The gut microbiota was assessed by sequencing the V3-V4 hypervariable region of the 16S rRNA gene. Beta diversity，operational taxonomic units（OTU）and interactions of gut microbiota with the variables in the study were analyzed. OTU specifically associated with sepsis were researched in linear mixed models. Results Compared with non-septic shock group，age，C-reactive protein（CRP）level，sequential organ failure assessment（SOFA）score，acute physiology and chronic health evaluationⅡ（APACHEⅡ）score and ICU stay time were increased in septic shock group（P<0.05）. The diversity of gut microbiota was lower in the patients with septic shock（P=0.006 for Shannon's index，P<0.001 for Simpson's reciprocal）. There was a significant difference in Beta diversity between septic shock group and non-septic shock group（pseudo F=1.19，P=0.038）. After performing a linear mixed model analysis，24 OTU associated with septic shock could be retrieved，with Parabacteroides distasonis，Bilophila spp. being significantly higher in septic shock patient samples than in non-septic shock patient samples. In septic shock patients，Ezakiella and Megasphaera decreased. Conclusions Lower presence of beneficial genera and higher abundance of pathogens are observed in septic shock patients. Therefore，specific gut microbiota characteristics could predict sepsis development in ICU patients.

Key words: Gut microbiota, Septic shock, Intensive care unit

中图分类号:

R446.5

孟会敏, 杨俊礼, 韩永燕. 脓毒症休克患者肠道菌群结构差异性表达与预后的关系[J]. 检验医学, 2025, 40(5): 455-459.

MENG Huimin, YANG Junli, HAN Yongyan. Relationship between differential expression of gut microbiota structure and prognosis in patients with septic shock[J]. Laboratory Medicine, 2025, 40(5): 455-459.

图/表 5

参考文献 15

[1]	肖玲, 肖凤仙, 文海燕, 等. 危重症患者肠道微生态失衡与血浆Fib、APTT、D-D水平的关系及其对预后的影响[J]. 山东医药, 2021, 61(11):77-81.
[2]	LIU W, CHENG M, LI J, et al. Classification of the gut microbiota of patients in intensive care units during development of sepsis and septic shock[J]. Genomics Proteomics Bioinformatics, 2020, 18(6):696-707.
[3]	CHERNEVSKAYA E, BELOBORODOVA N, KLIMENKO N, et al. Serum and fecal profiles of aromatic microbial metabolites reflect gut microbiota disruption in critically ill patients:a prospective observational pilot study[J]. Crit Care, 2020, 24(1):312.
[4]	AGUDELO-OCHOA G M, VALDÉS-DUQUE B E, GIRALDO-GIRALDO N A, et al. Gut microbiota profiles in critically ill patients,potential biomarkers and risk variables for sepsis[J]. Gut Microbes, 2020, 12(1):1707610.
[5]	SINGER M, DEUTSCHMAN C S, SEYMOUR C W, et al. The third international consensus definitions for sepsis and septic shock(Sepsis-3)[J]. JAMA, 2016, 315(8):801-810.
[6]	KIM H, KIM S, JUNG S. Instruction of microbiome taxonomic profiling based on 16S rRNA sequencing[J]. J Microbiol, 2020, 58(3):193-205. DOI PMID
[7]	ZHAN L, PU J, ZHENG J, et al. Tetrastigma hemsleyanum Diels et Gilg ameliorates lipopolysaccharide induced sepsis via repairing the intestinal mucosal barrier[J]. Biomed Pharmacother, 2022, 148:112741.
[8]	HAAK B W, ARGELAGUET R, KINSELLA C M, et al. Integrative transkingdom analysis of the gut microbiome in antibiotic perturbation and critical illness[J]. mSystems, 2021, 6(2):e01148.
[9]	SALAZAR N, ARBOLEYA S, FERNÁNDEZ-NAVARRO T, et al. Age-associated changes in gut microbiota and dietary components related with the immune system in adulthood and old age:a cross-sectional study[J]. Nutrients, 2019, 11(8):1765.
[10]	COMAN V, VODNAR D C. Gut microbiota and old age:modulating factors and interventions for healthy longevity[J]. Exp Gerontol, 2020, 141:111095.
[11]	KORF J M, GANESH B P, MCCULLOUGH L D. Gut dysbiosis and age-related neurological diseases in females[J]. Neurobiol Dis, 2022, 168:105695.
[12]	EZEJI J C, SARIKONDA D K, HOPPERTON A, et al. Parabacteroides distasonis:intriguing aerotolerant gut anaerobe with emerging antimicrobial resistance and pathogenic and probiotic roles in human health[J]. Gut Microbes, 2021, 13(1):1922241.
[13]	KJØLBÆK L, BENÍTEZ-PÁEZ A, GÓMEZ DEL PULGAR E M, et al. Arabinoxylan oligosaccharides and polyunsaturated fatty acid effects on gut microbiota and metabolic markers in overweight individuals with signs of metabolic syndrome:a randomized cross-over trial[J]. Clin Nutr, 2020, 39(1):67-79.
[14]	WAN Y D, ZHU R X, WU Z Q, et al. Gut microbiota disruption in septic shock patients:a pilot study[J]. Med Sci Monit, 2018, 24:8639-8646.
[15]	JIANG P, WU S, LUO Q, et al. Metagenomic analysis of common intestinal diseases reveals relationships among microbial signatures and powers multidisease diagnostic models[J]. mSystems, 2021, 6(3):e00112.

组别	例数	系统发育多样性指数	Chao指数	香农指数	辛普森倒数
非脓毒症休克组	47	25.57±4.83	251.06±18.68	3.97±0.66	38.26±8.19
脓毒症休克组	34	26.58±5.21	248.26±23.06	4.76±0.52	54.12±12.07
统计值		0.899	0.603	5.795	7.048
P值		0.372	0.548	<0.001	<0.001

组别	例数	系统发育多样性指数	Chao指数	香农指数	辛普森倒数
非脓毒症休克组	47	25.57±4.83	251.06±18.68	3.97±0.66	38.26±8.19
脓毒症休克组	34	26.58±5.21	248.26±23.06	4.76±0.52	54.12±12.07
统计值		0.899	0.603	5.795	7.048
P值		0.372	0.548	<0.001	<0.001

变量	分组	关联的OTU数	关联最强的OTU	P值①
年龄	≤60岁/>60岁	45	埃希氏菌属	0.002（1.28）
			卟啉单胞菌属	<0.001（-1.76）
性别	男性/女性	43	斯尼思氏梭杆菌属	<0.001（0.48）
			戴阿利斯特杆菌属	<0.001（-0.51）
脓毒症休克	否 /是	27	狄氏副拟杆菌种	<0.001（0.44）
			巨球型菌属	0.008（-0.44）
SOFA评分		25	狄氏副拟杆菌种	<0.001（0.67）
			巨球型菌属	0.002（-0.54）
APACHEⅡ评分		21	埃希氏菌属	0.005（0.87）
			Ezakiella属	0.007（-0.99）
ICU时间	短/长	8	克里斯滕森菌科	0.007（0.36）
			戴阿利斯特杆菌属	<0.001（-0.57）
CRP		5	肠道小杆菌属	0.007（0.17）
			毛螺菌科	<0.001（-0.47）
出院条件	存活/死亡	4	小单胞菌属	0.007（-0.35）

变量	分组	关联的OTU数	关联最强的OTU	P值①
年龄	≤60岁/>60岁	45	埃希氏菌属	0.002（1.28）
			卟啉单胞菌属	<0.001（-1.76）
性别	男性/女性	43	斯尼思氏梭杆菌属	<0.001（0.48）
			戴阿利斯特杆菌属	<0.001（-0.51）
脓毒症休克	否 /是	27	狄氏副拟杆菌种	<0.001（0.44）
			巨球型菌属	0.008（-0.44）
SOFA评分		25	狄氏副拟杆菌种	<0.001（0.67）
			巨球型菌属	0.002（-0.54）
APACHEⅡ评分		21	埃希氏菌属	0.005（0.87）
			Ezakiella属	0.007（-0.99）
ICU时间	短/长	8	克里斯滕森菌科	0.007（0.36）
			戴阿利斯特杆菌属	<0.001（-0.57）
CRP		5	肠道小杆菌属	0.007（0.17）
			毛螺菌科	<0.001（-0.47）
出院条件	存活/死亡	4	小单胞菌属	0.007（-0.35）