基于唾液皮质醇、IL-1β、系统免疫炎症指数及牙周状况对类风湿性关节炎与口腔健康相关性的研究
A Study on the Correlation between Rheumatoid Arthritis and Oral Health Based on Salivary Cortisol, IL-1β, Systemic Immune-Inflammation Index and Periodontal Condition
摘要: 目的:探讨唾液皮质醇(CS)、白介素-1β (IL-1β)、系统免疫炎症指数(SII)及牙周状况在类风湿性关节炎(RA)与口腔健康的相关性。方法:选取2024年11月至2025年2月于安徽医科大学第四附属医院风湿免疫科及口腔科就诊的116例患者作为研究对象(初次确诊为类风湿性关节炎或近6个月内应用过抗风湿药物、糖皮质激素类药物或其他可能干扰机体免疫状态的药物),依据疾病类型分为慢性牙周炎组(CP组,37例)、类风湿性关节炎组(RA组,34例)、类风湿性关节炎合并慢性牙周炎组(RA + CP组,45例);另选取同期在该院体检中心进行健康体检的42例健康人群作为健康对照组(HC组)。所有研究对象均完成一般情况调查表及口腔健康影响程度量表(OHIP-14)填写,同时收集实验室检测数据并开展牙周检查;采用酶联免疫吸附试验(ELISA)检测唾液中CS与IL-1β的含量,运用χ2检验、单因素方差分析(ANOVA)、Mann-Whitney U检验、Kruskal-Wallis H检验及Spearman相关分析等统计学方法对数据进行分析。结果:① RA + CP组与CP组的CP分期显著高于HC组,差异具有统计学意义(P < 0.05);② RA + CP组、RA组、CP组的唾液CS浓度、IL-1β水平、SII值及OHIP-14得分均高于HC组,差异均有统计学意义(P < 0.05);③ 唾液CS与IL-1β水平均与CP分期呈正相关(P < 0.05);④ SII与CP分期无显著相关性(P > 0.05)。结论:① 皮质醇(CS)、白细胞介素-1β (IL-1β)及系统免疫炎症指数(SII)可作为评估类风湿关节炎(RA)与慢性牙周炎(CP)患者下丘脑–垂体–肾上腺轴(HPAA)功能失调及全身炎症负荷加重的重要生物标志物;② 唾液样本具有无创、易获取的优势,与基于常规血常规检测、兼具稳定性与低成本特点的SII指标相结合,在RA与CP的大规模人群筛查及疾病进展动态监测中展现出显著的应用价值。
Abstract: Objective: To explore the correlation among salivary cortisol (CS), interleukin-1β (IL-1β), systemic immune-inflammation index (SII), and periodontal status in rheumatoid arthritis (RA) and oral health. Methods: A total of 116 patients (first diagnosed with rheumatoid arthritis, or has used anti-rheumatic drugs, glucocorticoid drugs, or other drugs that may interfere with the body’s immune status within the past 6 months) who visited the Department of Rheumatology and Immunology and the Department of Stomatology at the Fourth Affiliated Hospital of Anhui Medical University from November 2024 to February 2025 were selected as research subjects and divided into chronic periodontitis group (CP group, 37 cases), rheumatoid arthritis group (RA group, 34 cases), and rheumatoid arthritis combined with chronic periodontitis group (RA + CP group, 45 cases) based on disease type. Another 42 healthy individuals undergoing physical examination at the same period in the hospital’s health examination center were selected as the healthy control group (HC group). All study subjects completed a general information survey form and the Oral Health Impact Profile (OHIP-14), while laboratory test data and periodontal examinations were also collected. Salivary CS and IL-1β levels were measured using enzyme-linked immunosorbent assay (ELISA), and statistical analyses were performed using chi-square test, one-way ANOVA, Mann-Whitney U test, Kruskal-Wallis H test, and Spearman correlation analysis. Results: 1) The CP stage in the RA + CP group and CP group was significantly higher than that in the HC group (P < 0.05); 2) Salivary CS concentration, IL-1β level, SII value, and OHIP-14 score in the RA + CP group, RA group, and CP group were all higher than those in the HC group (P < 0.05); 3) Salivary CS and IL-1β levels were positively correlated with the CP stage (P < 0.05); 4) SII was not significantly correlated with the CP stage (P > 0.05). Conclusion: 1) CS, IL-1β, and SII can serve as important biomarkers for assessing hypothalamic-pituitary-adrenal axis dysfunction and increased systemic inflammatory load in RA and CP patients; 2) Saliva samples, which are non-invasive and easy to obtain, combined with the SII index, which is stable and cost-effective, show significant application value in large-scale population screening and dynamic monitoring of disease progression in RA and CP.
文章引用:李豪杰, 谢一瑾, 丁红忠. 基于唾液皮质醇、IL-1β、系统免疫炎症指数及牙周状况对类风湿性关节炎与口腔健康相关性的研究[J]. 临床医学进展, 2026, 16(2): 679-689. https://doi.org/10.12677/acm.2026.162439

1. 引言

慢性牙周炎(Chronic Periodontitis, CP)是以口腔细菌感染为起始诱因、宿主复杂炎症反应为核心发病机制的多因素慢性疾病,也是导致成年人牙齿缺失的首要原因之一。近年来,大量流行病学与基础研究证实,CP并非局限于口腔局部的病变,其与类风湿关节炎(Rheumatoid Arthritis, RA)、心血管疾病、糖尿病及产科并发症等多种全身性疾病存在密切的双向关联,其中CP与RA的关联性研究已成为领域内的热点方向[1]-[3]

类风湿关节炎(RA)是一种以对称性多关节受累为主要特征的全身性慢性自身免疫性疾病,尤其好发于手足小关节。该疾病可导致进行性关节强直、骨质破坏、关节畸形乃至功能残疾,目前已成为我国劳动力丧失及人群残疾的重要致病因素之一[4] [5]。在CP与众多全身性疾病的关联中,其与RA的密切关系已得到多项研究的明确证实[1] [6] [7]。基于此,本研究拟以唾液中的皮质醇(CS)、白细胞介素-1β (IL-1β)及系统免疫炎症指数(systemic immune inflammation index, SII)为核心观测指标,深入探讨RA与CP之间的关联机制,旨在为临床中RA与CP的病情评估、诊疗效果监测提供全新的理论依据与实践思路。

2. 资料与方法

2.1. 一般资料

本研究的研究对象选取于2024年11月至2025年2月期间在安徽医科大学第四附属医院风湿免疫科及口腔科就诊的患者,共116例。根据患者所患疾病类型,将其分为三组:类风湿关节炎合并慢性牙周炎组(RA + CP组,45例)、单纯类风湿关节炎组(RA组,34例)及单纯慢性牙周炎组(CP组,37例);同时,选取同期在本院体检中心进行健康体检的42例健康人群作为健康对照组(HC组)。统计学分析结果显示,上述4组研究对象在性别、年龄等一般资料的比较上,差异均无统计学意义(P > 0.05),组间具有可比性,具体数据详见表1。本研究方案已通过安徽医科大学第四附属医院伦理委员会的审批(KYXM-202510-005),所有研究对象均已充分知晓本研究的目的、方法及潜在风险,在自愿参与的前提下签署了知情同意书。

Table 1. Comparison of general data among the 4 patient groups [n (%) or x ¯ ±s ]

1. 4组患者一般资料比较[n (%)或 x ¯ ±s ]

组别

n

性别

年龄

RA + CP

45

14 (31.1)

31 (68.9)

55.40 ± 6.81

RA

34

11 (32.4)

23 (67.6)

55.33 ± 7.51

CP

37

18 (48.6)

19 (51.4)

54.44 ± 4.25

HC

42

19 (45.2)

23 (54.8)

52.59 ± 4.84

χ2/F

3.931

1.498

P

0.269

0.219

2.2. 纳入及排除标准

1) 纳入标准:① 牙周炎患者符合慢性牙周炎诊断标准[8];② 经我院风湿免疫科确诊为类风湿关节炎患者(符合2010年美国风湿病协会(ACR)分类标准[9]);③ 告知患者及其家属研究意义,经过患者及其家属同意;年龄18~75岁。

2) 排除标准:① 近6个月内应用过抗风湿药物、糖皮质激素类药物或其他可能干扰机体免疫状态的药物;② 6个月内曾接受系统性牙周干预治疗;③ 存在咬合创伤或活动性牙龈出血;④ 合并内分泌系统疾病、心血管疾病、精神类疾病、其余自身免疫性疾病等可能影响自身免疫状态的慢性病;⑤ 有吸烟、酗酒史;⑥ 处于妊娠期、哺乳期或月经周期的女性受试者;⑦ 罹患口腔黏膜病变、涎腺疾病或其他口腔活动性病变;⑧ 体质量指数(BMI) > 28 kg/m2 (提示肥胖)或存在饮食紊乱史;⑨ 因过敏反应、严重不良反应主动退出试验,或无法配合研究流程者。

2.3. 临床数据采集

2.3.1. 收集调查量表

所有研究对象均需填写调查量表,包括一般情况调查表与口腔健康影响程度量表(OHIP-14)。其中,一般情况调查表涵盖姓名、性别、年龄、手术治疗史、外伤史、输血史、吸烟史及用药史等信息;OHIP-14含14个条目,采用0~56分计分法,由研究对象依据自身实际情况填写,得分越高提示口腔健康对日常生活的影响越显著,以此评估其口腔健康状况。

2.3.2. 牙周检查

对所有研究对象行牙周检查:依据社区牙周指数(CPI),选取16、11、26、36、31、46为指数牙,缺失时以相邻牙替代。使用牙周探针检测指数牙的牙龈出血指数、探诊深度(PD)及临床附着丧失(CAL),记录每颗牙近颊、正中颊、远颊、近舌、正中舌、远舌6个位点的PD与CAL,计算各位点3次检查的平均值。根据检查结果将CP分为0期(无)、I期(初始期)、II期(中度)、III期(重度)、IV期(进展期)。所有检查及分期评估均由同一名牙周科副主任医师完成,并已通过牙周检查一致性检验。

2.3.3. 计算SII

所有研究对象禁食禁水8小时后,次日采集空腹静脉血,检测由安徽医科大学第四附属医院检验科完成。收集相关实验室指标并计算系统免疫炎症指数(SII),计算公式为:SII = 血小板计数 × 中性粒细胞计数/淋巴细胞计数[10]

2.3.4. 唾液CS、白介素1β (IL-1β)含量检测

所有研究对象禁食禁水8小时,且睡前刷牙后至采集前不再刷牙,于次日清晨7:00~8:00采集唾液样本。采集前受试者用清水漱口,等待5分钟后丢弃前2分钟唾液;随后舌下含棉卷5分钟刺激分泌,用唾液收集器采集2 ml唾液并转移至离心管,以3000 r/min离心15分钟,取2 ml上清液置于−80℃冻存管保存备检。检测前将样本室温解冻1小时,再次离心后取上清液,采用酶联免疫吸附试验(ELISA) (厂家:江苏精美生物科技有限公司)定量检测唾液中皮质醇及IL-1β的含量。

2.4. 统计学处理

采用SPSS26.0软件进行数据统计分析。计数资料以例数或百分率(%)表示,组间比较用χ2检验;计量资料中,符合正态分布者以 x ¯ ±s 表示,两组比较采用独立样本t检验,多组比较采用单因素方差分析,两两比较用Dunnett’s T3检验;不符合正态分布者以M (P25, P75)表示,两组比较采用Mann-Whitney U检验,多组比较采用Kruskal-Wallis H检验,两两比较用Nemenyi检验。采用Spearman相关分析唾液CS、IL-1β及SII与CP分期的相关性。以P < 0.05为差异具有统计学意义。

3. 结果

3.1. CP分期分析

非参数Mann-Whitney U检验秩和检验认为两组间CP分期差异存在统计学意义(P < 0.05)。见表2

Table 2. Comparison of CP stages (n%)

2. CP分期比较(n%)

组别

n

I期

II期

III期

Z

P

RA + CP

45

18 (40.0)

17 (37.8)

10 (22.2)

2.045

<0.05

CP

37

23 (62.2)

10 (27.0)

4 (10.8)

3.2. 4组唾液皮质醇含量分析

ANOVA认为4组间唾液CS含量差异存在统计学意义(P < 0.05);之后进行Dunnett’s T3法两两比较,P均 < 0.05,两两比较唾液CS存在统计学差异。见图1(a)表3

Table 3. Analysis of salivary cortisol levels in 4 groups ( x ¯ ±s )

3. 4组唾液皮质醇含量分析( x ¯ ±s )

组别

RA + CP

RA

CP

HC

F

P

n

45

34

37

42

69.03

<0.05

唾液皮质醇(nmol/L)

38.79 ± 4.46

34.64 ± 6.24

25.86 ± 6.70

21.86 ± 1.70

3.3. 4组唾液IL-1β含量分析

非参数Kruskal-Wallis H检验认为4组间唾液IL-1β含量差异存在统计学意义(P < 0.05)。两两比较结果显示,RA组和CP组比较,P > 0.05,认为RA组与CP组唾液IL-1β不存在统计学差异,其余组间比较,P均 < 0.05,认为其余组间比较存在统计学意义。见图1(b)表4

Table 4. Analysis of IL-1β content in saliva from 4 groups [M (P25, P75)]

4. 4组唾液IL-1β含量分析[M (P25, P75)]

组别

RA + CP

RA

CP

HC

H

P

n

45

34

37

42

71.65

<0.05

IL-1β (pg/ml)

76.38 (70.56, 93.04)

64.76 (53.29, 81.06)

57.46 (51.88, 66.73)

45.14 (39.80, 49.52)

3.4. 4组SII水平分析

Table 5. Analysis of SII levels in 4 groups [M (P25, P75)]

5. 4组SII水平分析[M (P25, P75)]

组别

RA + CP

RA

CP

HC

H

P

n

45

34

37

42

38.07

<0.05

SII (109/L)

659.91 (461.82, 851.26)

483.99 (377.28, 633.66)

501.40 (391.18, 728.56)

282.07 (228.04, 403.78)

非参数Kruskal-Wallis H检验认为4组间SII差异存在统计学意义(P < 0.05)。两两比较结果显示,RA + CP组、RA组与CP组比较,P > 0.05,不存在统计学差异,余组间比较,P均 < 0.05,存在统计学差异。见图1(c)表5

3.5. 4组OHIP-14得分比较

ANOVA认为4组OHIP-14得分差异存在统计学意义(P < 0.05)。之后进行Dunnett’s T3法两两比较,发现RA + CP组与CP组比较,P > 0.05,认为RA + CP与CP组OHIP-14得分不存在统计学差异。其余组间比较,P均 < 0.05,两两比较OHIP-14得分存在统计学差异。见图1(d)表6

Table 6. Comparison of OHIP-14 scores in the 4 groups ( x ¯ ±s )

6. 4组OHIP-14得分比较( x ¯ ±s )

组别

RA + CP

RA

CP

HC

F

P

n

45

34

37

42

136.87

<0.05

OHIP-14

15.34 ± 3.07

9.50 ± 3.05

16 ± 3.38

3.53 ± 1.34

(a) 4组唾液CS浓度比较 (b) 4组唾液IL-1β浓度比较

(c) 4组SII值比较 (d) 4组OHIP-14得分比较

Figure 1. Violin plots comparing various indicators among the four groups

1. 4组间各项指标比较小提琴图

3.6. 唾液CS及、IL-1β及SII与CP分期相关性分析

唾液CS,IL-1β与CP分期呈正相关(P < 0.05);SII与CP分期无显著相关性(P > 0.05)。见图2(a)图2(b)表7

Table 7. Correlation analysis of salivary cortisol, IL-1β, and SII with CP staging

7. 唾液皮质醇、IL-1β及SII与CP分期相关性分析

组别

CS

IL-1β

SII

r

P

r

P

r

P

RA + CP组

0.493

0.003

0.391

0.008

0.225

0.194

CP组

0.492

0.009

0.461

0.004

0.210

0.293

(a) 唾液CS与CP分期的相关性 (b) 唾液IL-1β与CP分期的相关性

Figure 2. Correlation between salivary indicators and CP staging

2. 唾液指标与CP分期的相关性

4. 讨论

已有研究[1] [11] [12]表明,牙龈卟啉单胞菌(Porphyromonas gingicalis, Pg)在RA与CP的关联中发挥关键作用。作为CP的核心致病菌,Pg是目前已知唯一可产生肽基精氨酸脱亚胺酶(PAD)的细菌;PAD可诱导人体自身抗原瓜氨酸化,进而刺激抗瓜氨酸化蛋白抗体(ACPA)产生,而ACPA会破坏关节内瓜氨酸肽及宿主瓜氨酸蛋白的免疫耐受,最终触发自身免疫反应。Tan等[13]发现,RA合并CP患者的探诊深度(PD)、附着丧失(AL)等牙周指标水平更高,提示其牙周状况更差,且RA疾病活动度与CP分期呈高度关联。本研究结果显示,RA + CP组的CP分期显著高于单纯CP组(P < 0.05),这与既往研究结论一致[14]。Kobayashi等[15]指出,RA疾病活动度与血清IL-6、TNF-α、CRP水平相关,而CP与RA患者均存在TNF-α、IL-1β、IL-6等促炎细胞因子失衡。其中,TNF-α作为RA的核心促炎因子,可通过激活TNFR1受体介导的核因子-κB (NF-κB)通路,诱导IL-6、IL-1β等细胞因子及ICAM-1、VCAM-1等黏附分子表达,促进炎症细胞向滑膜迁移,并刺激成纤维样滑膜细胞(FLS)分泌RANKL、释放基质金属蛋白酶(MMPs),最终导致关节与牙周组织破坏[6] [7] [16],本研究中各组唾液IL-1β的差异与上述结论相符。

口腔健康影响程度量表(OHIP-14)是评估口腔疾病对患者生理、心理及社会功能影响的常用工具[17],尤其在牙周炎研究中应用广泛[18]。本研究中,单纯CP组的OHIP-14得分高于RA + CP组,但差异无统计学意义(P > 0.05)。Han等[19]对此的解释为:两组患者就医动机存在差异——RA作为高负担疾病更易引起患者重视,而CP起病隐匿,RA + CP患者往往忽视其牙周问题,因此评分较低。这提示临床医师在接诊RA患者时,应主动提醒其关注牙周健康。

系统免疫炎症指数(SII)是一种基于血小板、中性粒细胞及淋巴细胞计数的新型炎症标志物,具有常规检测、低成本、稳定性强的优势[10] [20] [21]。相较于中性粒细胞/淋巴细胞比值(NLR)、单核细胞/淋巴细胞比值(MLR)、血小板/淋巴细胞比值(PLR),SII能更精准地反映宿主炎症与免疫状态的平衡[22] [23]。多项研究证实,在评估RA疾病活动度及预后时,SII的敏感度与特异度优于CRP、ESR等常规炎症指标[23]-[25];在识别重度CP方面,其敏感性与准确性亦高于NLR、PLR,特异性优于PLR [22] [26]。本研究发现,RA与CP患者的全身炎症负荷均显著加重,与既往研究[24] [26]一致,但未观察到SII与CP分期存在显著相关性(P > 0.05)。这与Guo等[22]的结论相符——其研究指出SII > 978 × 109/L仅能预测50岁以上人群的牙周炎风险,无法区分CP分期。研究表明[27] [28],SII作为全身炎症指标,其反应系统免疫炎症状态,受年龄、系统性疾病和生活方式等全身因素调控,但无法特异性地对应牙周组织的局部破坏,表明SII与CP的关联缺乏局部特异性,揭示了局部病变与全身反应的差异。从机制上看,RA与CP患者长期处于慢性炎症状态,会破坏中性粒细胞、淋巴细胞及血小板的平衡与功能[2] [29]-[31],CP患者多形核中性粒细胞增多、淋巴细胞减少,直接导致SII升高[26] [32] [33];而RA患者免疫系统异常激活,会引起B淋巴细胞过度增殖,间接影响上述血细胞水平,最终导致SII异常。虽有研究[24]证实SII可预测RA预后,但利用其评估非手术牙周治疗效果仍需进一步探索。

唾液因具有无创、易采集、患者接受度高的特点,且能反映口腔整体炎症状态,已被广泛用于牙周炎生物标志物的筛选与监测[34] [35]。本研究以唾液皮质醇(CS)、IL-1β为切入点,探究CP与RA及口腔健康的关联。现有研究[36]已明确唾液IL-1β是CP分期的关键标志物。在CP中,IL-1β主要由巨噬细胞、树突状细胞分泌,牙龈成纤维细胞、牙周膜细胞及成骨细胞亦参与其合成,其在牙周组织、龈沟液及唾液中的水平升高是牙周病进展的重要驱动因素[37];而在RA中,Sung等[38]发现成纤维细胞生长因子23 (FGF23)可通过激活PI3K/Akt及NF-κB通路增强IL-1β表达,促进成纤维细胞合成IL-1β

对于唾液CS而言,由于血清白蛋白与CS结合球蛋白无法通过唾液细胞膜,唾液CS水平可直接反映生物活性游离CS的浓度[39]。研究[40]-[42]证实,情绪压力、吸烟与CP密切相关——情绪压力可促进CS分泌,而高CS水平会增强Th2细胞反应,加速牙周组织破坏;同时,CP患者唾液与血清中CS浓度升高,还会通过影响龈下菌群繁殖诱发或加重CP [43]。此外,RA的发病与下丘脑–垂体–肾上腺轴(HPAA)功能失调密切相关[44]:CS作为抗炎激素本可抑制炎症发展,但早期未接受激素治疗的RA患者,虽ACTH及CS分泌的昼夜节律正常,但其血清IL-6浓度显著升高,提示炎症状态下ACTH、CS分泌已相对不足,HPAA功能缺陷可能是RA发病的重要基础。

本研究结果显示,RA + CP组、RA组、CP组的唾液CS及IL-1β浓度均显著高于健康对照组(HC组,P < 0.05),且二者与CP分期均呈正相关(P < 0.05),这与既往研究[36] [45]-[47]结论一致。从相互作用机制看,CS可调控IL-1β、IL-6等促炎因子的表达,而IL-1β会促进MMPs合成,导致关节软骨与牙周组织破坏[48],加剧RA与CP病情;反之,RA患者自身的HPAA功能紊乱及CP引发的全身炎症负荷,又会影响CS的合成与释放[40],形成“炎症加重–组织破坏–炎症加剧”的恶性循环。因此,唾液CS、IL-1β检测作为无创、便捷的方法,可快速评估RA与CP的疾病进展及治疗效果。

综上所述:本研究通过分析唾液皮质醇(CS)、白细胞介素-1β (IL-1β)及全身免疫炎症指数(SII),进一步证实了类风湿性关节炎(RA)与慢性牙周炎(CP)之间的双向关联,并尝试从HPA轴功能(皮质醇)和局部免疫反应(IL-1β)的角度揭示其病理机制。唾液CS与IL-1β的无创、便捷优势,与SII的稳定性、经济性及易检性相结合,为RA与CP的疾病进展监测与预后评估提供了一套便捷、实用的工具系列,符合精准医疗和舒适化医疗的发展趋势。本研究受限于单中心设计和有限的样本量,后续需通过多中心合作与扩大样本量以进一步验证结论。

NOTES

*通讯作者。

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