非哺乳期乳腺炎(non-puerperal mastitis,NPM)是一种慢性、非特异性的乳房炎症性疾病,常发生于非妊娠期、非哺乳期的中青年女性[1]。近二十年来国内病例数显著增高,其临床表现以乳房部炎症性肿块形成,局部红、肿、疼痛为特点,病程慢性迁延、反复难愈,在炎性结块基础上可形成瘘管、窦道、溃疡。保守治疗无效者需行乳房区段切除,原发病灶与手术瘢痕严重破坏乳房外形,使患者承受长期的精神压力与经济负担,影响生活质量[2]。NPM病因尚不明确,一定程度上阻碍其诊疗技术的发展,已有研究认为其发病可能与乳腺导管不畅、吸烟、肥胖、病原菌感染、免疫反应等因素有关[3-5]。研究显示,在NPM疾病进程中存在免疫应答类型的转化[6-7],且多种免疫性疾病经研究发现与肠道菌群结构的改变有关[8-10]。肠道菌群的代谢活动被认为相当于机体的“虚拟器官”[11-12],肠道中的微生物及其代谢产物是促进和发展宿主免疫系统的基础,可对宿主的免疫、代谢调节及大脑功能等产生影响[13-15]。肠道免疫与共生菌失调可导致慢性炎症以及自身免疫性疾病的发生[14, 16-17]。目前,国内外对于乳腺炎症性疾病的肠道微生态特点研究十分有限。Ma等[18]通过动物实验发现患哺乳期乳腺炎的奶牛乳汁和粪便中菌群变化具有一致性,另一项实验将哺乳期乳腺炎奶牛的粪菌移植到无菌健康小鼠,结果显示无菌小鼠也产生了乳腺炎症状以及血液、脾脏、结肠的炎症[19],说明肠道菌群失调或结构改变可能与乳腺炎症性疾病的发生有关。本研究将通过高通量测序技术首次从肠道微生态层面分析NPM的病理特征,探讨NPM患者肠道菌群的结构特点。
资料和方法研究对象 本研究纳入来自上海中医药大学附属龙华医院门诊或住院治疗的NPM患者以及自社会招募的健康受试者。NPM患者符合临床症状,经病理诊断为NPM。所有患者及健康受试者年龄为18~60岁。排除标准:(1)合并肝、肾、造血系统、内分泌系统等严重原发疾病;(2)受试前3个月内服用过抗生素或微生物制剂;(3)正在使用对胃肠功能可能有影响的药物;(4)既往有良、恶性肿瘤病史;(5)确定或怀疑有酒精或药物滥用史;(6)精神病患者。本研究经上海中医药大学附属龙华医院医学伦理委员会批准(批准号:2021LCSY047),从2020年8月至2022年3月共纳入NPM组患者40例、健康对照(healthy controls,HC)组受试者30例,所有患者及受试者均签署知情同意书。
标本采集方法 向受试者详细讲解粪便标本采集方法:嘱受试者排便前排空尿液,避免污染;以无菌勺采集新鲜粪便内与空气和地面没有接触的部分,约黄豆大小(2~3 g),置入无菌管中,随后交由研究者转运至-80 ℃冰箱冻存以备检测。
高通量测序方法 应用E.Z.N.A.® soil DNA kit (美国Omega Bio-tek公司)进行微生物群落总DNA抽提,1%的琼脂糖凝胶电泳检测DNA的提取质量,NanoDrop2000测定DNA浓度和纯度;使用338F(5’-ACTCCTACGGGAGGCAG CAG-3’)和806R (5’-GGACTACHVGGGTWTC TAAT-3’) 对16S rRNA基因V3-V4可变区进行PCR扩增,扩增程序如下:95℃预变性3 min,27个循环(95 ℃变性30 s,55 ℃退火30 s,72 ℃延伸45 s),然后72 ℃稳定延伸10 min,最后在10 ℃进行保存(PCR仪:ABI GeneAmp®9700型)。使用2%琼脂糖凝胶回收PCR产物,利用AxyPrep DNA Gel Extraction Kit(美国Axygen Biosciences公司)进行回收产物纯化,2%琼脂糖凝胶电泳检测,并应用Quantus™ Fluorometer (美国Promega公司)对回收产物进行检测定量。使用NEXTFLEX® Rapid DNA-Seq Kit建库。应用Miseq PE300/NovaSeq PE250平台(美国Illumina公司)进行测序。
生物信息分析方法 应用fastp[20]软件FLASH[21]软件对原始测序序列进行质控和拼接:(1)过滤reads尾部质量值20以下的碱基,过滤质控后50 bp以下的reads;(2)将成对reads拼接(merge),最小overlap长度为10 bp,错配率不超过0.2;(3)根据序列首尾两端的barcode和引物区分样品,调整序列方向,barcode错配数为0,最大引物错配数为2。根据97%[22-23]相似度,应用UPARSE[22]软件进行操作分类单元(operational taxonomic unit,OUT)聚类并剔除嵌合体。利用RDP classifier[24]对每条序列进行物种分类注释,比对Silva 16S rRNA数据库(v138),将对比阈值设置为70%。
统计学方法 应用R语言软件(V.3.3.1)进行数据分析。若两组计量资料满足正态分布且方差齐,采用两独立样本t检验,若方差不齐,采用校正t检验;若不满足正态分布,采用秩和检验。计数资料采用χ2检验。P < 0.05为差异有统计学意义。
结果样本基本信息 2020年8月至2022年3月期间共采集粪便标本70例。其中NPM组40例,HC组30例,年龄范围21~45岁。两组平均年龄、身高、体重及BMI差异无统计学意义,具有可比性(表 1)。
(x±s) | |||||||||||||||||||||||||||||
Clinical indicators | NPM | HC | t | P | |||||||||||||||||||||||||
Age (y) | 31.63±4.67 | 29.20±5.38 | 2.02 | 0.05 | |||||||||||||||||||||||||
Weight (kg) | 60.10±8.35 | 58.35±9.30 | 0.83 | 0.41 | |||||||||||||||||||||||||
Height (cm) | 160.73±4.39 | 162.53±4.34 | -1.71 | 0.09 | |||||||||||||||||||||||||
BMI (kg/m2) | 23.24±2.88 | 22.02±2.82 | 1.77 | 0.08 | |||||||||||||||||||||||||
NPM:Non-puerperal mastitis;HC:Healthy controls. |
对70例粪便样本进行Illumina MiSeq测序,获得3 496 238条有效序列,包含1 435 357 507个碱基,序列长度集中在401~440 bp,序列平均长度为410 bp。应用Uparse软件,以97%的相似性对所有序列进行OTU聚类,按最小样本序列数抽平,结果显示共检出1 062个OTU,NPM组和HC组分别检出968个和965个OTU,两组共有的OTU 850个(图 1A)。应用R语言软件绘制稀释曲线,包括sobs、shannon和coverage曲线,分别代表物种丰富度、多样性和覆盖度,以评估测序深度。由图 1B可见,随着测序数据量逐渐增大,Sobs曲线趋向平缓,提示数据测序量合理;由图 1C、图 1D可见,随着测序数据量增多,shannon曲线、coverage曲线平缓,提示测序量足够大,可以反映样本中绝大部分微生物的多样性信息,提示当前样本量相对充足。
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A: Analysis of species Venn diagram of NPM group and HC group; B: Sobs curve of NPM group and HC group; C: Shannon curve of NPM group and HC group; D: Coverage curve of NPM group and HC group. 图 1 NPM组与HC组Venn图分析及稀释曲线分析 Fig 1 Analysis of species Venn diagram and rarefaction curve of NPM group and HC group |
Alpha多样性分析 Alpha多样性指数差异检验结果显示,NPM组sobs(t=2.70,P < 0.05)、ace(t=2.37,P < 0.05)、chao(t=2.38,P < 0.05)、shannon(t=2.56,P < 0.05)指数显著低于健康对照组,差异有统计学意义;组间coverage(t=-0.02,P > 0.05)指数差异无统计学意义(表 2)。
(x±s) | |||||||||||||||||||||||||||||
Index Type | NPM group | HC group | t | P | |||||||||||||||||||||||||
sobs | 255.82±61.28 | 299.93±75.34 | 2.70 | 0.01 | |||||||||||||||||||||||||
ace | 303.86±69.99 | 348.19±86.71 | 2.37 | 0.02 | |||||||||||||||||||||||||
chao | 307.58±71.80 | 353.68±90.59 | 2.38 | 0.02 | |||||||||||||||||||||||||
shannon | 3.33±0.41 | 3.58±0.42 | 2.56 | 0.01 | |||||||||||||||||||||||||
coverage | 1.00±0.000 5 | 1.00±0.0005 | -0.02 | 0.99 |
偏最小二乘法判别分析 偏最小二乘法判别分析(partial least squares discriminant analysis,PLS-DA)结果显示,在OTU水平,NPM组和HC组样本明显区分并聚成两个类群,各样本在图中位置的离散情况也说明了个体之间肠道菌群组成的差异程度(图 2)。
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图 2 NPM组与HC组肠道菌群偏最小二乘法分析 Fig 2 Partial least squares discriminant analysis of gut microbiota in NPM group and HC group |
NPM组与HC组肠道菌群组成与差异分析 70例受试者的粪便共检出15个菌门、22个菌纲、55个菌目、105个菌科、288个菌属。NPM组与HC组有4个优势菌门,分别为Firmicutes(72.78% vs. 72.39%,z=3.62,P=0.995 3)、Bacteroidota(13.39% vs.14.29%,z=3.41,P=0.656 3)、Actinobacteriota(8.23% vs. 9.18%,z=3.17,P=0.351 5)、Proteobacteria (5.12% vs.2.99%,z=4.41,P=0.113 1)(图 3)。NPM组与HC组相比,1个纲、5个目、14个科、28个属存在显著差异。纲水平,NPM组Bacilli(z=2.65,P < 0.05)平均相对丰度显著低于HC组;目水平,NPM组患者Lactobacillales(z=2.29)、Christensenellales(z=2.48)、RF39(z=2.75)、Peptococcales(z=2.68)、Corynebacteriales (z=2.59)平均相对丰度显著低于HC组,差异均有统计学意义;科水平,NPM组Streptococcaceae(z=2.37)、Oscillospiraceae(z=2.61)、Rikenellaceae(z=2.51)、Christensenellaceae(z=2.48)、Marinifilaceae(z=2.50)、norank_o_RF39(z=2.75)、UCG-010(z=2.42)、Peptococcaceae(z=2.68)、unclassified_o_Coriobacteriales(z=2.35)、Defluviitaleaceae(z=2.84)、Corynebacteriaceae(z=2.59)、Neisseriaceae(z=3.28)平均相对丰度显著低于HC组,Coriobacteriales_Incertae_Sedis(z=2.55)、Aerococcaceae(z=4.56)平均相对丰度显著高于HC组,差异均有统计学意义;属水平,NPM组Anaerostipes(z=2.13)、Streptococcus(z=2.36)、Ruminococcus_torques_group(z=2.47)、Alistipes(z=2.45)、Christensenellaceae_R-7_group(z=2.50)、UCG-002(z=2.65)、Eubacterium_ventriosum_group(z=2.58)、Ruminococcus_gauvreauii_group(z=2.40)、NK4A214_group(z=2.28)、norank_f_norank_o_RF39(z=2.75)、Butyricimonas(z=2.43)、UCG-003(z=2.67)、norank_f_UCG-010(z=2.42)、Family_XIII_UCG-001(z=2.25)、Christensenella(z=2.48)、Anaerotruncus(z=2.68)、norank_f_Peptococcaceae(z=2.63)、unclassified_o_Coriobacteriales(z=2.35)、norank_f_Christensenellaceae(z=2.25)、Defluviitaleaceae_UCG-011(z=2.84)、Corynebacterium(z=2.61)、Neisseria(z=3.28)平均相对丰度显著低于HC组,Faecalibacterium(z=4.72)、Escherichia-Shigella(z=4.61)、TM7x(z=4.60)、Peptoniphilus(z=4.44)、Abiotrophia(z=4.56)平均相对丰度显著高于HC组,差异均有统计学意义。
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图 3 NPM组与HC组门水平肠道菌群结构 Fig 3 Structure of gut microbiota at phylum level in NPM group and HC group |
采用线性判别分析估算两组间的差异性菌群丰度对差异效果影响的大小,LDA值越大说明其对组间差异影响越大(LDA值> 3,P < 0.05)。结果显示(图 4,表 3),属水平Faecalibacterium、Escherichia-Shigella在NPM组富集对组间差异影响显著;属水平Anaerostipes、Streptococcus、Neisseria、Christensenellaceae_R-7_group、Alistipes、UCG-002、Ruminococcus_torques_group、Corynebacterium在HC组富集,科水平Streptococcaceae、Oscillospiraceae、Christensenellaceae、Neisseriaceae、Rikenellaceae在HC组富集,目水平Lactobacillales、Christensenellales在HC组富集,纲水平Bacilli在HC组富集,对组间差异影响显著。
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图 4 NPM组与HC组肠道菌群进化分支图 Fig 4 Cladogram of gut microbiota in NPM group and HC group |
Group | Categorize | Species | LDA value | P |
NPM | Genus | g_Faecalibacterium | 4.42 | < 0.05 |
g_Escherichia-Shigella | 4.07 | < 0.05 | ||
HC | Class | c_Bacilli | 3.81 | < 0.05 |
Order | o_Lactobacillales | 3.83 | < 0.05 | |
o_Christensenellales | 3.48 | < 0.05 | ||
Family | f_Streptococcaceae | 3.90 | < 0.05 | |
f_Oscillospiraceae | 3.52 | < 0.05 | ||
f_Christensenellaceae | 3.48 | < 0.05 | ||
f_Neisseriaceae | 3.47 | < 0.05 | ||
f_Rikenellaceae | 3.36 | < 0.05 | ||
Genus | g_Anaerostipes | 4.17 | < 0.01 | |
g_Streptococcus | 3.90 | < 0.05 | ||
g_Neisseria | 3.56 | < 0.05 | ||
g_Christensenellaceae_R-7_group | 3.47 | < 0.05 | ||
g_Alistipes | 3.37 | < 0.05 | ||
g_UCG-002 | 3.37 | < 0.05 | ||
g_Ruminococcus_torques_group | 3.26 | < 0.05 | ||
g_Corynebacterium | 3.09 | < 0.05 |
针对LDA值> 3的10个属水平差异物种构建ROC曲线以进一步筛选生物标志物,结果显示该菌群组AUC为0.73(图 5),具有较高诊断意义。对本菌群组中的物种逐个分析,其中9个物种的AUC > 0.5,具有诊断意义(图 6),其中Anaerostipes、Ruminococcus_torques_group的AUC值较高,分别为0.72(95%CI:0.6~0.84)、0.70(95%CI:0.57~0.83);其余物种按AUC值从高到低分别为Streptococcus(AUC=0.69,95%CI:0.56~0.81)、Alistipes(AUC=0.68,95%CI:0.55~0.81)、Corynebacterium(AUC=0.66,95%CI:0.54~0.78)、Christensenellaceae_R-7_group(AUC=0.66,95%CI:0.53~0.79)、UCG-002(AUC=0.65,95%CI:0.52~0.78)、Faecalibacterium(AUC=0.63,95%CI:0.49~0.76)、Escherichia-Shigella(AUC=0.63,95%CI:0.49~0.76)。Neisseria的AUC值较低(AUC=0.45,95%CI:0.4~0.5),不具有诊断意义。
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图 5 NPM组与HC组属水平差异物种菌群组(LDA > 3)ROC曲线分析 Fig 5 ROC curve analysis of different species at genus level(LDA > 3)between NPM group and HC group |
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图 6 NPM组与HC组差异物种ROC曲线分析 Fig 6 ROC curve analysis of different species between NPM group and HC group |
NPM是一种病因不明的非特异性炎症性疾病,对病理标本及外周血检测的研究显示,其病程中存在免疫类型转化及免疫调节失衡,如由Th1型辅助细胞向Th2型转化以及Th17辅助细胞/调节性T细胞失衡[6-7],专家共识多认为其发病与自身免疫因素相关[1-2]。肠道菌群结构的改变可通过内分泌细胞影响屏障通透性,导致细菌及其代谢产物进入循环,进而影响宿主机能[25]。肠道菌群失调诱发的促炎因子表达、分子模拟机制启动、肠道代谢产物紊乱被认为与肠内外自身免疫性疾病的发生有关[26-28]。另一方面,肠道共生菌可协助机体进行营养物质代谢、药物代谢、构建消化道免疫屏障以及促进肠道淋巴组织、T细胞、B细胞等免疫结构发育[16, 29]。为探索NPM肠道微生态层面的发病机制,本研究收集了40例NPM患者以及30例健康受试者的粪便样本进行高通量测序分析。
在疾病与健康人肠道菌群差异结果中,Alpha多样性分析的sobs、ace、chao、shannon指数在健康人群中显著较高,说明在NPM的疾病状态下,肠道菌群的丰富度和多样性均显著降低。PLS-DA结果显示,在OTU水平,NPM组和HC组样本分区并聚成两个类群,说明可通过肠道菌群结构的差异对NPM患者与健康人群进行区别。本研究采用LDA分析发现16个物种在HC组富集并对组间差异形成贡献较大(LDA值> 3,P < 0.5),以属水平的10个物种作为菌群组进行ROC曲线构建,得到AUC值为0.73,提示对疾病组与健康组肠道菌群差异有一定诊断意义,该菌群组可作为潜在的生物标志物。其中,Anaerostipes、Ruminococcus_torques_group的AUC≥0.7,就单个物种而言具有较高诊断价值。Anaerostipes为严格厌氧菌,可将葡萄糖代谢为短链脂肪酸(short chain fatty acids,SCFA),如丁酸盐、醋酸盐[30]。研究显示,Anaerostipes在非酒精性脂肪性肝病合并2型糖尿病患者、肠易激综合征、Graves’病等患者肠道菌群中丰度相对较低[31-33]。Ruminococcus_torques_group亦属于厚壁菌门,有限报道显示其在Graves’病、溃疡性结肠炎患者肠道菌群中丰度相对减低[33-34]。另有6个在HC组富集的物种AUC值在0.5~0.7内,亦具有一定诊断意义。其中Streptococcus为厚壁菌门下菌属,其在肠道中的终末代谢产物为醋酸盐、乳酸盐、甲酸盐等[35],被报道在特质焦虑患者、强直性脊柱炎、过敏性紫癜肾等患者的肠道菌群中丰度富集[36-38]。Alistipes属于拟杆菌门、Rikenellaceae科,为严格厌氧的革兰阴性菌属[39],其代谢产物包括醋酸盐、丙酸盐等[35],其丰度相对减少,可见于肝硬化患者、自闭症患者以及肥胖或非酒精性脂肪性肝炎的儿童、青少年[40-42]。Christensenellaceae_R-7_group、Christensenellaceae科、Christensenellales目属于厚壁菌门下同一分类树支。一项荟萃分析显示,肠道疾病患者的肠道菌群中Christensenellaceae_R-7_group、Ruminococcaceae UCG-005、Alistipes等物种相对丰度显著较低[43]。Christensenellaceae是一类革兰氏阴性、厌氧菌[44],其丰度减低可见于非特异性炎症性肠病患者[45]。Christensenellaceae科下第一个分离物为Christensella minuta,其特点为严格厌氧,可将糖类代谢为醋酸盐和丁酸盐[44]。UCG-002属于Oscillospiraceae科,为厚壁菌门的梭菌纲所属,Oscillospiraceae亦为丁酸盐产生菌[46],其下菌属Oscillospira被报道在儿童非酒精性脂肪性肝炎、非特异性炎症性肠病、强迫症患者肠道菌群中丰度减低[47-48]。在NPM组显著富集的菌属中,Faecalibacterium、Escherichia-Shigella对组间差异影响显著(LDA > 3,P < 0.05),AUC值均为0.63,提示诊断意义有限。Faecalibacterium属于Ruminococcaceae科、Oscillospirales目,其下菌种被发现在肥胖儿童、结肠腺瘤患者、克罗恩病患者等肠道菌群中丰度相对较高[49-51],也有研究显示其下属菌种在非特异性炎症性肠病患者、非酒精性脂肪性肝炎患者肠道菌群中丰度减低[52-53]。Escherichia-Shigella属于Proteobacteria门,研究显示其与局部促炎症因子的产生和释放有关[54],例如Escherichia coli在诱导发热过程中,IL-6等促炎因子发挥了重要作用[55]。Escherichia coli亦被认为在非特异性炎症性肠病及结直肠癌进程中影响宿主细胞周期、引起DNA损伤[56-58]。
肠道微生物及其代谢产物可在机体局部和全身发挥作用,并与机体的疾病、健康状态相关[35]。在本研究结果中,Anaerostipes、Oscillospiraceae、Christensenellales、Alistipes、Streptococcus等物种在NPM组相对丰度较低,对组间差异形成影响显著,研究也报道与SCFA产生有关,即NPM组肠道菌群中多种SCFA产生菌相对丰度减少。SCFA是肠道菌群的代谢产物之一,为1-6碳原子组成的挥发性脂肪酸,是肠上皮细胞能量的来源,作用包括促进肠上皮细胞氧消耗、影响缺氧诱导因子调节氧代谢等,可调节肠上皮细胞的能量代谢、参与肠上皮屏障功能维持[59-61],主要包括醋酸盐、丙酸盐和丁酸盐[62]。SCFA对宿主的调节途径包括抑制组蛋白脱乙酰酶以及激活G蛋白偶联受体[63],可抑制趋化因子及黏附分子表达[64],既可直接作用于肠道细胞,也可以通过信号转导激活作用于肠外组织[65]。丁酸盐是肠道黏膜的首选能量来源,其作用方式包括影响跨上皮离子转运、影响细胞生长与分化、抗炎、抗氧化等,被认为与结肠炎、结肠恶性肿瘤的预防有关[66-67]。相关临床及实验研究显示,肠道中短链脂肪酸产生菌及短链脂肪酸的水平升高与代谢性疾病的恢复[68]以及肠息肉的改善有关[69]。
本研究具有一定局限性,当前研究结果呈现出患病者与健康人群肠道菌群结构的差异,但这种结构差异与疾病发生的因果关系以及潜在生物标志物的实用性,需在日后的临床及动物研究中进一步验证。
基于本研究当前所纳入的样本分析显示,NPM患者与健康人肠道菌群结构具有显著差异,患疾者肠道菌群的丰富度、多样性均明显较低。ROC曲线构建结果显示,LDA > 3的属水平差异物种菌群组以及单个物种Anaerostipes、Ruminococcus_torques_group可以作为NPM这一疾病和健康人肠道菌群的区分的潜在生物标志物。肠道菌群结构和其代谢产物水平对NPM发生、发展的影响机制尚缺乏报道,本文初步分析了NPM患者肠道微生态层面病理特点,对潜在生物标志物进行筛选,为NPM的病因学研究及临床诊疗提供新思路。
作者贡献声明 代秋颖 研究设计,标本收集,文献整理,论文撰写。周悦,程一凡,马丽娜,范奕伟 标本收集,文献整理。胡升芳,叶媚娜 可行性分析。吴晶晶,孟畑,殷玉莲论文修订。陈红风 研究设计,论文审校。
利益冲突声明 所有作者均声明不存在利益冲突。
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