AbstractThe gut microbiome has been implicated in various human diseases, though findings across studies have shown considerable variability. In this study, we reanalyzed 6314 publicly available fecal metagenomes from 36 case-control studies on different diseases to investigate microbial diversity and disease-shared signatures.

摘要肠道微生物组与各种人类疾病有关，尽管各项研究的结果显示出相当大的差异。在这项研究中，我们重新分析了来自36个不同疾病病例对照研究的6314个公开可用的粪便宏基因组，以调查微生物多样性和疾病共享特征。

Using a unified analysis pipeline, we observed reduced microbial diversity in many diseases, while some exhibited increased diversity. Significant alterations in microbial communities were detected across most diseases. A meta-analysis identified 277 disease-associated gut species, including numerous opportunistic pathogens enriched in patients and a depletion of beneficial microbes.

使用统一的分析流程，我们观察到许多疾病的微生物多样性降低，而一些疾病的多样性增加。在大多数疾病中检测到微生物群落的显着变化。一项荟萃分析确定了277种与疾病相关的肠道物种，包括许多富含患者的机会性病原体和有益微生物的消耗。

A random forest classifier based on these signatures achieved high accuracy in distinguishing diseased individuals from controls (AUC = 0.776) and high-risk patients from controls (AUC = 0.825), and it also performed well in external cohorts. These results offer insights into the gut microbiome’s role in common diseases in the Chinese population and will guide personalized disease management strategies..

基于这些特征的随机森林分类器在区分患病个体与对照（AUC=0.776）和高危患者与对照（AUC=0.825）方面取得了很高的准确性，并且在外部队列中也表现良好。这些结果提供了对肠道微生物组在中国人群常见疾病中的作用的见解，并将指导个性化疾病管理策略。。

IntroductionThe gut microbiota is currently considered a key factor contributing to the regulation of host health1,2. Generally, the overall structure of the gut microbiota is relatively stable despite acute perturbations because of its plasticity, which allows it to quickly return to its initial composition3.

引言肠道微生物群目前被认为是调节宿主健康的关键因素1,2。一般来说，肠道微生物群的整体结构相对稳定，尽管由于其可塑性而受到严重干扰，这使得它能够迅速恢复到其初始组成3。

However, when hosts are continuously exposed to various pollutants, stresses and diseases, the composition of the gut microbiota might change (dysbiosis), promoting the selection of more virulent microorganisms and potentially harming host health3. With the advancement of amplification-based and whole-metagenomic sequencing technologies, gut microbiota dysbiosis has been widely reported in many common diseases, including autoimmune disorders4,5,6, cardiometabolic conditions7,8, infectious diseases9, psychiatric disorders10,11, and cancers12,13,14.

然而，当宿主持续暴露于各种污染物，压力和疾病时，肠道微生物群的组成可能会改变（生态失调），促进选择更具毒性的微生物，并可能损害宿主健康3。随着基于扩增和全宏基因组测序技术的进步，肠道微生物群生态失调已在许多常见疾病中得到广泛报道，包括自身免疫性疾病4,5,6，心脏代谢状况7,8，传染病9，精神疾病10,11和癌症12,13,14。

The altered microbiome likely plays a crucial role in these diseases. The varying microbial changes across different diseases emphasize the diverse roles of the microbiota in health and disease states15,16,17,18. However, due to the lack of unified reference databases, the low accuracy of bacterial species annotation and quantification in high-throughput sequencing datasets, and the highly variable experimental and analytical methods used, the signatures of the gut microbiota in different disease states are often incomparable.

改变的微生物组可能在这些疾病中起着至关重要的作用。不同疾病的不同微生物变化强调了微生物群在健康和疾病状态中的不同作用15,16,17,18。然而，由于缺乏统一的参考数据库，高通量测序数据集中细菌物种注释和定量的准确性低，以及使用的高度可变的实验和分析方法，不同疾病状态下肠道微生物群的特征通常是不可比的。

Additionally, the precise cause of microbial dysfunction in these diseases is not completely understood. Therefore, uniform methods to characterize the gut microbiota in multiple diseases, especially using publicly available datasets, are necessary to identify the overall pattern of disease-associated microbiota shifts.Meta-analysis, which combines data from multiple studies, can help avoid biases .

此外，这些疾病中微生物功能障碍的确切原因尚不完全清楚。因此，有必要采用统一的方法来表征多种疾病中的肠道微生物群，特别是使用公开可用的数据集，以确定疾病相关微生物群变化的总体模式。荟萃分析结合了多项研究的数据，可以帮助避免偏见。

Data availability

数据可用性

The metadata, gut microbial profiles of all analyzed samples, and statistical scripts are available on the GitHub website (https://github.com/yexianingyue/GM_common_diseases). The authors declare that all other data supporting the findings of the study are available in the paper and supplementary materials or from the corresponding authors upon request..

所有分析样品的元数据、肠道微生物谱和统计脚本都可以在GitHub网站上找到(https://github.com/yexianingyue/GM_common_diseases)。作者声明，支持研究结果的所有其他数据均可在论文和补充材料中获得，或应要求从通讯作者处获得。。

ReferencesEhrlich, S. D. The human gut microbiome impacts health and disease. C. R. Biol. 339, 319–323 (2016).Article

参考文献Sehrlich，S.D。人类肠道微生物组影响健康和疾病。C、 R.生物。339319-323（2016）。文章

PubMed

PubMed

Google Scholar

谷歌学者

de Vos, W. M., Tilg, H., Van Hul, M. & Cani, P. D. Gut microbiome and health: mechanistic insights. Gut 71, 1020–1032 (2022).Article

de Vos，W.M.，Tilg，H.，Van Hul，M。＆Cani，P.D。肠道微生物组与健康：机理见解。肠道711020-1032（2022）。文章

PubMed

PubMed

Google Scholar

谷歌学者

Candela, M., Biagi, E., Maccaferri, S., Turroni, S. & Brigidi, P. Intestinal microbiota is a plastic factor responding to environmental changes. Trends Microbiol. 20, 385–391 (2012).Article

Candela，M.，Biagi，E.，Maccaferri，S.，Turroni，S。＆Brigidi，P。肠道微生物群是响应环境变化的塑性因素。趋势微生物。20385-391（2012）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

De Luca, F. & Shoenfeld, Y. The microbiome in autoimmune diseases. Clin. Exp. Immunol. 195, 74–85 (2019).Article

De Luca，F。＆Shoenfeld，Y。自身免疫性疾病中的微生物组。。实验免疫。195,74-85（2019）。文章

PubMed

PubMed

Google Scholar

谷歌学者

Chen, C. et al. Characterizations of the gut bacteriome, mycobiome, and virome in patients with osteoarthritis. Microbiol. Spectr. 11, e01711–e01722 (2023).PubMed

Chen，C.等人。骨关节炎患者肠道细菌组、真菌组和病毒组的特征。微生物。光谱。11，e01711–e01722（2023）。PubMed出版社

Google Scholar

谷歌学者

Chen, C. et al. Characterizations of the multi-kingdom gut microbiota in Chinese patients with gouty arthritis. BMC Microbiol. 23, 363 (2023).Article

Chen，C.等人。中国痛风性关节炎患者多王国肠道微生物群的特征。BMC微生物。23363（2023）。文章

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Witkowski, M., Weeks, T. L. & Hazen, S. L. Gut microbiota and cardiovascular disease. Circ. Res. 127, 553–570 (2020).Article

Witkowski，M.，Weeks，T.L。和Hazen，S.L。肠道微生物群和心血管疾病。保监会。第127553-570号决议（2020年）。文章

CAS

中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Fan, Y. & Pedersen, O. Gut microbiota in human metabolic health and disease. Nat. Rev. Microbiol 19, 55–71 (2021).Article

。《自然评论微生物学》19,55-71（2021）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Dhar, D. & Mohanty, A. Gut microbiota and Covid-19- possible link and implications. Virus Res. 285, 198018 (2020).Article

Dhar，D。＆Mohanty，A。肠道微生物群和Covid-19-可能的联系和影响。Virus Res.285198018（2020）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Jarbrink-Sehgal, E. & Andreasson, A. The gut microbiota and mental health in adults. Curr. Opin. Neurobiol. 62, 102–114 (2020).Article

Jarbrink-Sehgal，E。和Andreasson，A。成人的肠道微生物群和心理健康。货币。奥平。神经生物学。。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Nikolova, V. L. et al. Perturbations in gut microbiota composition in psychiatric disorders: a review and meta-analysis. JAMA Psychiatry 78, 1343–1354 (2021).Article

Nikolova，V.L.等人。精神疾病中肠道微生物群组成的扰动：综述和荟萃分析。JAMA精神病学781343-1354（2021）。文章

PubMed

PubMed

Google Scholar

谷歌学者

Zhu, J. et al. Breast cancer in postmenopausal women is associated with an altered gut metagenome. Microbiome 6, 136 (2018).Article

Zhu，J.等人。绝经后女性乳腺癌与肠道宏基因组改变有关。微生物组6136（2018）。文章

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Vivarelli, S. et al. Gut microbiota and cancer: from pathogenesis to therapy. Cancers 11, 38 (2019).Article

Vivarelli，S。等。肠道微生物群与癌症：从发病机制到治疗。癌症11,38（2019）。文章

CAS

中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Yachida, S. et al. Metagenomic and metabolomic analyses reveal distinct stage-specific phenotypes of the gut microbiota in colorectal cancer. Nat. Med. 25, 968–976 (2019).Article

Yachida，S。等人。宏基因组学和代谢组学分析揭示了结直肠癌肠道微生物群的不同阶段特异性表型。《自然医学》25968-976（2019）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Duvallet, C., Gibbons, S. M., Gurry, T., Irizarry, R. A. & Alm, E. J. Meta-analysis of gut microbiome studies identifies disease-specific and shared responses. Nat. Commun. 8, 1784 (2017).Article

Duvallet，C.，Gibbons，S.M.，Gurry，T.，Irizarry，R.A。＆Alm，E.J。肠道微生物组研究的荟萃分析确定了疾病特异性和共享反应。国家公社。81784（2017）。文章

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Mancabelli, L. et al. Identification of universal gut microbial biomarkers of common human intestinal diseases by meta-analysis. FEMS Microbiol. Ecol. https://doi.org/10.1093/femsec/fix153 (2017).Armour, C. R., Nayfach, S., Pollard, K. S. & Sharpton, T. J. A metagenomic meta-analysis reveals functional signatures of health and disease in the human gut microbiome.

Mancabelli，L.等人。通过荟萃分析鉴定常见人类肠道疾病的通用肠道微生物生物标志物。FEMS微生物。Ecol公司。https://doi.org/10.1093/femsec/fix153（2017年）。Armour，C.R.，Nayfach，S.，Pollard，K.S。＆Sharpton，T.J。宏基因组荟萃分析揭示了人类肠道微生物组中健康和疾病的功能特征。

MSystems 4, e00332–00318 (2019).Article .

MSystems 4，e00332–00318（2019）。第条。

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Yan, Q. et al. A genomic compendium of cultivated human gut fungi characterizes the gut mycobiome and its relevance to common diseases. Cell 187, 2969–2989.e2924 (2024).Article

Yan，Q.等人，《培养的人类肠道真菌基因组纲要》描述了肠道菌群及其与常见疾病的相关性。细胞1872969–2989.e2924（2024）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Pasolli, E., Truong, D. T., Malik, F., Waldron, L. & Segata, N. Machine learning meta-analysis of large metagenomic datasets: tools and biological insights. PLoS Comput. Biol. 12, e1004977 (2016).Article

Pasolli，E.，Truong，D.T.，Malik，F.，Waldron，L。＆Segata，N。大型宏基因组数据集的机器学习荟萃分析：工具和生物学见解。PLoS计算机。生物学12，e1004977（2016）。文章

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Gurevitch, J., Koricheva, J., Nakagawa, S. & Stewart, G. Meta-analysis and the science of research synthesis. Nature 555, 175–182 (2018).Article

。自然555175-182（2018）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Ho, N. T. et al. Meta-analysis of effects of exclusive breastfeeding on infant gut microbiota across populations. Nat. Commun. 9, 4169 (2018).Article

Ho，N.T.等人。纯母乳喂养对不同人群婴儿肠道微生物群影响的荟萃分析。国家公社。94169（2018）。文章

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Jiang, P., Wu, S., Luo, Q., Zhao, X. M. & Chen, W. H. Metagenomic analysis of common intestinal diseases reveals relationships among microbial signatures and powers multidisease diagnostic models. mSystems 6, e00112–21 (2021).Wu, Q., Badu, S., So, S. Y., Treangen, T. J. & Savidge, T.

Jiang，P.，Wu，S.，Luo，Q.，Zhao，X.M。＆Chen，W.H。常见肠道疾病的宏基因组分析揭示了微生物特征与多种疾病诊断模型之间的关系。mSystems 6，e00112–21（2021）。Wu，Q.，Badu，S.，So，S.Y.，Treangen，T.J。和Savidge，T。

C. The pan-microbiome profiling system Taxa4Meta identifies clinical dysbiotic features and classifies diarrheal disease. J. Clin. Invest. 134, e170859 (2024).Su, Q. et al. Faecal microbiome-based machine learning for multi-class disease diagnosis. Nat. Commun. 13, 6818 (2022).Article .

C、 泛微生物组分析系统Taxa4Meta识别临床益生菌特征并对腹泻疾病进行分类。J、 临床。投资。134，e170859（2024）。Su，Q。等人。基于粪便微生物组的机器学习用于多类疾病诊断。国家公社。136818（2022年）。文章。

CAS

中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Tierney, B. T. et al. Systematically assessing microbiome-disease associations identifies drivers of inconsistency in metagenomic research. PLoS Biol. 20, e3001556 (2022).Article

Tierney，B.T.等人系统地评估微生物组与疾病的关联，确定了宏基因组研究中不一致的驱动因素。《公共科学图书馆·生物学》。20，e3001556（2022）。文章

CAS

中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Blanco-Míguez, A. et al. Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4. Nat. Biotechnol. 41, 1633–1644 (2023).Suzuki, T. A. & Worobey, M. Geographical variation of human gut microbial composition. Biol. Lett. 10, 20131037 (2014).Article .

Blanco-Míguez，A.等人。使用MetaPhlAn 4扩展和改进未表征物种的宏基因组分类学分析。美国国家生物技术公司。411633-1644（2023）。Suzuki，T.A。和Worobey，M。人类肠道微生物组成的地理变异。生物学Lett。1020131037（2014）。文章。

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Wagner Mackenzie, B., Waite, D. W. & Taylor, M. W. Evaluating variation in human gut microbiota profiles due to DNA extraction method and inter-subject differences. Front Microbiol. 6, 130 (2015).Article

Wagner-Mackenzie，B.，Waite，D.W。＆Taylor，M.W。评估由于DNA提取方法和受试者间差异导致的人类肠道微生物群谱的变化。前微生物。6130（2015）。文章

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Arumugam, M. et al. Enterotypes of the human gut microbiome. Nature 473, 174–180 (2011).Article

Arumugam，M。等人。人类肠道微生物组的肠道类型。自然473174-180（2011）。文章

CAS

中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Costea, P. I. et al. Enterotypes in the landscape of gut microbial community composition. Nat. Microbiol. 3, 8–16 (2018).Article

Costea，P.I.等人。肠道微生物群落组成景观中的肠道类型。自然微生物。3,8-16（2018）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Machiels, K. et al. A decrease of the butyrate-producing species roseburia hominis and faecalibacterium prausnitzii defines dysbiosis in patients with ulcerative colitis. Gut 63, 1275–1283 (2014).Article

Machiels，K。等人。产生丁酸盐的物种roseburia hominis和faecalibacterium prausnitzii的减少定义了溃疡性结肠炎患者的生态失调。肠道631275-1283（2014）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Morrison, D. J. & Preston, T. Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism. Gut Microbes 7, 189–200 (2016).Article

Morrison，D.J。＆Preston，T。肠道微生物群形成短链脂肪酸及其对人体代谢的影响。肠道微生物7189-200（2016）。文章

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Koh, A., De Vadder, F., Kovatcheva-Datchary, P. & Backhed, F. From dietary fiber to host physiology: short-chain fatty acids as key bacterial metabolites. Cell 165, 1332–1345 (2016).Article

Koh，A.，De Vadder，F.，Kovatcheva-Datchary，P。＆Backhed，F。从膳食纤维到宿主生理学：短链脂肪酸作为关键的细菌代谢物。细胞1651332-1345（2016）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Martin-Gallausiaux, C., Marinelli, L., Blottiere, H. M., Larraufie, P. & Lapaque, N. SCFA: mechanisms and functional importance in the gut. Proc. Nutr. Soc. 80, 37–49 (2021).Article

。程序。。Soc.80，37-49（2021）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Wirbel, J. et al. Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer. Nat. Med. 25, 679–689 (2019).Article

粪便宏基因组的荟萃分析揭示了结直肠癌特有的全球微生物特征。《自然医学》25679-689（2019）。文章

CAS

中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Xia, X. et al. Bacteria pathogens drive host colonic epithelial cell promoter hypermethylation of tumor suppressor genes in colorectal cancer. Microbiome 8, 1–13 (2020).Article

Xia，X。等人。细菌病原体驱动大肠癌中肿瘤抑制基因的宿主结肠上皮细胞启动子高甲基化。微生物组8,1-13（2020）。文章

CAS

中科院

Google Scholar

谷歌学者

Wang, X. et al. Aberrant gut microbiota alters host metabolome and impacts renal failure in humans and rodents. Gut 69, 2131–2142 (2020).Article

Wang，X。等人。异常的肠道微生物群改变宿主代谢组并影响人类和啮齿动物的肾衰竭。肠道692131-2142（2020）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Wang, Q. et al. A metagenome-wide association study of gut microbiota in asthma in UK adults. BMC Microbiol. 18, 114 (2018).Article

Wang，Q。等人。英国成年人哮喘肠道微生物群的宏基因组关联研究。BMC微生物。18114（2018）。文章

CAS

中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Cekanaviciute, E. et al. Gut bacteria from multiple sclerosis patients modulate human T cells and exacerbate symptoms in mouse models. Proc. Natl Acad. Sci. USA 114, 10713–10718 (2017).Article

Cekanaviciute，E。等人。来自多发性硬化症患者的肠道细菌调节人类T细胞并加剧小鼠模型中的症状。程序。国家科学院。科学。美国11410713-10718（2017）。文章

CAS

中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Gupta, A. et al. Association of flavonifractor plautii, a flavonoid-degrading bacterium, with the gut microbiome of colorectal cancer patients in India. mSystems 4, e00438-19 (2019).Li, Z. et al. Multi-omics analyses of serum metabolome, gut microbiome and brain function reveal dysregulated microbiota-gut-brain axis in bipolar depression.

Gupta，A。等人。类黄酮降解细菌黄酮分形菌（flavonifractor plautii）与印度结直肠癌患者肠道微生物组的关联。mSystems 4，e00438-19（2019）。Li，Z。等人。血清代谢组学，肠道微生物组学和脑功能的多组学分析揭示了双相抑郁症中微生物群-肠-脑轴失调。

Mol. Psychiatry 27, 4123–4135 (2022).Article .

摩尔精神病学274123-4135（2022）。文章。

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Chen, F. et al. Meta-analysis of fecal viromes demonstrates high diagnostic potential of the gut viral signatures for colorectal cancer and adenoma risk assessment. J. Adv. Res. 49, 103–114 (2022).Article

Chen，F。等人。粪便病毒组的荟萃分析表明，肠道病毒特征对结直肠癌和腺瘤风险评估具有很高的诊断潜力。J、 Adv.Res.49103–114（2022年）。文章

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Zhang, P. et al. Metagenome-wide analysis uncovers gut microbial signatures and implicates taxon-specific functions in end-stage renal disease. Genome Biol. 24, 226 (2023).Article

Zhang，P。等人。全基因组分析揭示了肠道微生物特征，并暗示了终末期肾病的分类群特异性功能。基因组生物学。24226（2023年）。文章

CAS

中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Carding, S., Verbeke, K., Vipond, D. T., Corfe, B. M. & Owen, L. J. Dysbiosis of the gut microbiota in disease. Micro. Ecol. Health Dis. 26, 26191 (2015).

Carding，S.，Verbeke，K.，Vipond，D.T.，Corfe，B.M。＆Owen，L.J。疾病中肠道微生物群的生态失调。微型。Ecol公司。健康Dis。2626191（2015）。

Google Scholar

谷歌学者

Wang, J. & Jia, H. Metagenome-wide association studies: fine-mining the microbiome. Nat. Rev. Microbiol. 14, 508–522 (2016).Article

Wang，J。＆Jia，H。宏基因组关联研究：精细挖掘微生物组。自然修订版微生物学。14508-522（2016）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Young, V. B. The role of the microbiome in human health and disease: an introduction for clinicians. BMJ 356, j831 (2017).Article

Young，V.B。微生物组在人类健康和疾病中的作用：临床医生简介。BMJ 356，j831（2017）。文章

PubMed

PubMed

Google Scholar

谷歌学者

Hills, R. D., Jr. et al. Gut microbiome: profound implications for diet and disease. Nutrients 11, 1613 (2019).Magne, F. et al. The firmicutes/bacteroidetes ratio: a relevant marker of gut dysbiosis in obese patients? Nutrients 12, 1474 (2020).Mosca, A., Leclerc, M. & Hugot, J. P. Gut microbiota diversity and human diseases: should we reintroduce key predators in our ecosystem? Front.

Hills，R.D.，Jr.等人，《肠道微生物组：对饮食和疾病的深远影响》。营养素111613（2019）。Magne，F。等人。厚壁菌门/拟杆菌比率：肥胖患者肠道生态失调的相关标志物？营养素121474（2020）。Mosca，A.，Leclerc，M。＆Hugot，J.P。肠道微生物群多样性和人类疾病：我们应该在我们的生态系统中重新引入关键的捕食者吗？正面。

Microbiol. 7, 455 (2016).Article .

微生物。7455（2016）。文章。

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Kriss, M., Hazleton, K. Z., Nusbacher, N. M., Martin, C. G. & Lozupone, C. A. Low diversity gut microbiota dysbiosis: drivers, functional implications and recovery. Curr. Opin. Microbiol 44, 34–40 (2018).Article

Kriss，M.，Hazleton，K.Z.，Nusbacher，N.M.，Martin，C.G。＆Lozupone，C.A。低多样性肠道微生物群生态失调：驱动因素，功能影响和恢复。货币。奥平。微生物44,34-40（2018）。文章

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Manor, O. et al. Health and disease markers correlate with gut microbiome composition across thousands of people. Nat. Commun. 11, 1–12 (2020).Article

Manor，O。等人。健康和疾病标志物与数千人的肠道微生物组成相关。国家公社。11，1-12（2020）。文章

Google Scholar

谷歌学者

Qiu, P. et al. The gut microbiota in inflammatory bowel disease. Front Cell Infect. Microbiol. 12, 733992 (2022).Article

邱，P。等。炎症性肠病中的肠道微生物群。前细胞感染。微生物。12733992（2022）。文章

CAS

中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Chu, W. et al. Metagenomic analysis identified microbiome alterations and pathological association between intestinal microbiota and polycystic ovary syndrome. Fertil. Steril. 113, 1286–1298.e1284 (2020).Article

宏基因组分析确定了肠道微生物群与多囊卵巢综合征之间的微生物组改变和病理关联。费尔蒂尔。空间1131286-1298.e1284（2020）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Zhou, L. et al. Characteristic gut microbiota and predicted metabolic functions in women with PCOS. Endocr. Connect 9, 63–73 (2020).Article

Zhou，L.等。多囊卵巢综合征（PCOS）患者肠道微生物群特征及代谢功能预测。内分泌。连接9，63–73（2020）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Yeoh, Y. K. et al. Gut microbiota composition reflects disease severity and dysfunctional immune responses in patients with COVID-19. Gut 70, 698–706 (2021).Article

Yeoh，Y.K.等人。肠道微生物群组成反映了新型冠状病毒肺炎患者的疾病严重程度和功能失调的免疫反应。肠道70698-706（2021）。文章

CAS

中科院

PubMed

PubMed

Google Scholar

谷歌学者

Hu, Y. et al. Gut microbiota associated with pulmonary tuberculosis and dysbiosis caused by anti-tuberculosis drugs. J. Infect. 78, 317–322 (2019).Article

Hu，Y.等人。与肺结核和抗结核药物引起的生态失调相关的肠道微生物群。J、 感染。78317-322（2019）。文章

PubMed

PubMed

Google Scholar

谷歌学者

Jackson, M. A. et al. Gut microbiota associations with common diseases and prescription medications in a population-based cohort. Nat. Commun. 9, 2655 (2018).Article

Jackson，M.A.等人在基于人群的队列中，肠道微生物群与常见疾病和处方药的关联。国家公社。92655（2018）。文章

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Aringer, M. et al. 2019 European league against rheumatism/American college of rheumatology classification criteria for systemic lupus erythematosus. Arthritis Rheumatol. 71, 1400–1412 (2019).Article

Aringer，M.等人，2019年欧洲风湿病联盟/美国风湿病学会系统性红斑狼疮分类标准。风湿性关节炎。711400-1412（2019）。文章

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018).Article

Chen，S.，Zhou，Y.，Chen，Y。＆Gu，J。fastp：一种超快速的一体化FASTQ预处理器。。文章

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).Article

Langmead，B。＆Salzberg，S.L。与Bowtie 2快速间隙读取对齐。《自然方法》9357-359（2012）。文章

CAS

中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B (Methodol.) 57, 289–300 (1995).Article

Benjamini，Y。＆Hochberg，Y。控制错误发现率：一种实用而强大的多重测试方法。J、 R.统计社会服务。B（方法。）57289-300（1995）。文章

Google Scholar

谷歌学者

Mallick, H. et al. Multivariable association discovery in population-scale meta-omics studies. PLoS Comput. Biol. 17, e1009442 (2021).Article

Mallick，H.等人。人口规模元组学研究中的多变量关联发现。PLoS计算机。生物学17，e1009442（2021）。文章

CAS

中科院

PubMed

PubMed

PubMed Central

公共医学中心

Google Scholar

谷歌学者

Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. lmerTest package: tests in linear mixed effects models. J. Stat. Softw. 82, 1–26 (2017).Article

Kuznetsova，A.，Brockhoff，P.B。＆Christensen，R.H.lmerTest软件包：线性混合效应模型中的测试。J、 统计软件。82,1-26（2017）。文章

Google Scholar

谷歌学者

Dixon, P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 14, 927–930 (2003).Article

Dixon，P。VEGAN，社区生态学的R功能包。J、 蔬菜。科学。14927-930（2003）。文章

Google Scholar

谷歌学者

Download referencesAcknowledgementsThis work was supported by grants from the National Natural Science Foundation of China (81902037, 81503455, and 82370563), and Beijing University of Chinese Medicine (NO.5050071720001 and NO.2180072120049).Author informationAuthor notesThese authors contributed equally: Wen Sun, Yue Zhang, Ruochun Guo, Shanshan Sha, Changming Chen.Authors and AffiliationsCentre for Translational Medicine, Shenzhen Bao’an Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, 518000, ChinaWen SunKey Laboratory of Health Cultivation of the Ministry of Education, Beijing University of Chinese Medicine, Beijing, 100029, ChinaWen SunSchool of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100700, ChinaWen Sun & Jie MaPuensum Genetech Institute, Wuhan, 430076, ChinaYue Zhang, Ruochun Guo, Jinxin Meng, Qingbo Lv & Shenghui LiDepartment of Microbiology, Department of Biochemistry and Molecular Biology, College of Basic Medical Sciences, Dalian Medical University, Dalian, 116044, ChinaShanshan Sha, Hayan Ullah, Lin Cheng, Shao Fan, Rui Li & Qiulong YanDepartment of Rheumatology and Immunology, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang, 550001, ChinaChangming ChenDepartment of Traditional Chinese Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, ChinaYan ZhangDepartment of Acupuncture and Moxibustion, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, 100010, ChinaWei YouDepartment Orthopedics, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, 100700, ChinaXiaohong MuSchool of Chemistry, Chemical Engineering and Life Science, Hubei Key Laboratory of .

下载参考文献致谢这项工作得到了国家自然科学基金（819020378150345和82370563）和北京中医药大学（NO.5050071720001和NO.2180072120049）的资助。作者信息作者注意到这些作者做出了同样的贡献：孙文，张悦，郭若春，沙珊珊，陈昌明。作者和附属机构广州中医药大学深圳宝安中医医院转化医学中心，深圳，518000，北京中医药大学教育部健康培育国家重点实验室，北京，100029，北京中医药大学中医学院，北京，100700，武汉，430076，张跃跃，郭若春，孟金新，吕庆波和盛辉，大连医科大学基础医学院生物化学与分子生物学系，微生物学系，大连，116044，中国上海，海山贵州中医药大学第二附属医院风湿免疫科，贵阳，550001，中国陈昌明北京友谊医院中医科，首都医科大学，北京，100050，中国张燕首都医科大学北京中医院针灸科，北京，100010，中国北京中医药大学东直门医院骨科，北京，100700，中国小红化学化工与生命科学学院，湖北省重点实验室。

PubMed Google ScholarYue ZhangView author publicationsYou can also search for this author in

PubMed Google ScholarYue ZhangView作者出版物您也可以在

PubMed Google ScholarRuochun GuoView author publicationsYou can also search for this author in

PubMed Google ScholarShanshan ShaView author publicationsYou can also search for this author in

PubMed Google Scholarshan ShaView作者出版物您也可以在

PubMed Google ScholarChangming ChenView author publicationsYou can also search for this author in

PubMed Google ScholarChangming ChenView作者出版物您也可以在

PubMed Google ScholarHayan UllahView author publicationsYou can also search for this author in

PubMed Google ScholarHayan UllahView作者出版物您也可以在

PubMed Google ScholarYan ZhangView author publicationsYou can also search for this author in

PubMed Google ScholarYan ZhangView作者出版物您也可以在

PubMed Google ScholarJie MaView author publicationsYou can also search for this author in

PubMed Google ScholarJie MaView作者出版物您也可以在

PubMed Google ScholarWei YouView author publicationsYou can also search for this author in

PubMed Google ScholarWei YouView作者出版物您也可以在

PubMed Google ScholarJinxin MengView author publicationsYou can also search for this author in

PubMed谷歌学者Jinxin MengView作者出版物您也可以在

PubMed Google ScholarQingbo LvView author publicationsYou can also search for this author in

PubMed Google ScholarQingbo LvView作者出版物您也可以在

PubMed Google ScholarLin ChengView author publicationsYou can also search for this author in

PubMed Google ScholarLin ChengView作者出版物您也可以在

PubMed Google ScholarShao FanView author publicationsYou can also search for this author in

PubMed Google ScholarShao FanView作者出版物您也可以在

PubMed Google ScholarRui LiView author publicationsYou can also search for this author in

PubMed Google ScholarRui LiView作者出版物您也可以在

PubMed Google ScholarXiaohong MuView author publicationsYou can also search for this author in

PubMed Google ScholarXiaohong MuView作者出版物您也可以在

PubMed Google ScholarShenghui LiView author publicationsYou can also search for this author in

PubMed Google ScholarShenghui LiView作者出版物您也可以在

PubMed Google ScholarQiulong YanView author publicationsYou can also search for this author in

PubMed Google ScholarQiulong YanView作者出版物您也可以在

PubMed Google ScholarContributionsS.L., Q.Y., Yue Z., R.G., X.M., and W.S. contributed to the conception and design of the study. Yue Z., L.C., S.F., and R.L. downloaded and processed the publicly available datasets. Yue Z., Yan Z., S.L., R.G., S.S., J.M., H.U. and Q.L. performed the bioinformatics analyses.

PubMed谷歌学术贡献。五十、 ，Q.Y.，Yue Z.，R.G.，X.M。和W.S.为研究的概念和设计做出了贡献。Yue Z.，L.C.，S.F。和R.L.下载并处理了公开可用的数据集。Yue Z.，Yan Z.，S.L.，R.G.，S.S.，J.M.，H.U.和Q.L.进行了生物信息学分析。

S.L., S.S., and C.C. wrote the manuscript. S.L. and W.S. helped to draft the manuscript. J.M. and W.Y. contributed meaningful discussions. All authors were involved in preparing the manuscript and contributed to manuscript revision, reading, and approving the submitted version.Corresponding authorsCorrespondence to.

S、 L.，S.S。和C.C.撰写了手稿。S、 L.和W.S.帮助起草了手稿。J、 M.和W.Y.进行了有意义的讨论。所有作者都参与了稿件的准备，并为稿件的修订，阅读和批准提交的版本做出了贡献。通讯作者通讯。

Xiaohong Mu, Shenghui Li or Qiulong Yan.Ethics declarations

穆晓红、李盛辉或严秋龙。道德宣言

Competing interests

The authors declare no competing interests.

作者声明没有利益冲突。

Additional informationPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary informationSupplementary Figures and TablesRights and permissions

Additional informationPublisher的注释Springer Nature在已发布的地图和机构隶属关系中的管辖权主张方面保持中立。补充信息补充数字和表格权利和权限

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material.

开放获取本文是根据知识共享署名非商业性NoDerivatives 4.0国际许可证授权的，该许可证允许以任何媒介或格式进行任何非商业性使用，共享，分发和复制，只要您对原始作者和来源给予适当的信任，提供知识共享许可证的链接，并指出您是否修改了许可材料。

You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

根据本许可证，您无权共享源自本文或其部分的改编材料。本文中的图像或其他第三方材料包含在文章的知识共享许可证中，除非该材料的信用额度中另有说明。如果材料未包含在文章的知识共享许可中，并且您的预期用途不受法律法规的许可或超出许可用途，则您需要直接获得版权所有者的许可。

To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/..

要查看此许可证的副本，请访问http://creativecommons.org/licenses/by-nc-nd/4.0/..

Reprints and permissionsAbout this articleCite this articleSun, W., Zhang, Y., Guo, R. et al. A population-scale analysis of 36 gut microbiome studies reveals universal species signatures for common diseases.

转载和许可本文引用本文Sun，W.，Zhang，Y.，Guo，R。等人。对36个肠道微生物组研究的人口规模分析揭示了常见疾病的普遍物种特征。

npj Biofilms Microbiomes 10, 96 (2024). https://doi.org/10.1038/s41522-024-00567-9Download citationReceived: 21 March 2024Accepted: 15 September 2024Published: 01 October 2024DOI: https://doi.org/10.1038/s41522-024-00567-9Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard.

npj生物膜微生物组10,96（2024）。https://doi.org/10.1038/s41522-024-00567-9Download引文接收日期：2024年3月21日接受日期：2024年9月15日发布日期：2024年10月1日OI：https://doi.org/10.1038/s41522-024-00567-9Share本文与您共享以下链接的任何人都可以阅读此内容：获取可共享链接对不起，本文目前没有可共享的链接。复制到剪贴板。

Provided by the Springer Nature SharedIt content-sharing initiative

由Springer Nature SharedIt内容共享计划提供

CommentsBy submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

评论通过提交评论，您同意遵守我们的条款和社区指南。如果您发现有虐待行为或不符合我们的条款或准则，请将其标记为不合适。