血清sTWEAK与新冠肺炎患者严重程度及预后的关联：一项前瞻性队列研究
Association between Serum sTWEAK and Severity and Prognosis of Patients with COVID-19’s Disease: A Prospective Cohort Study
DOI: 10.12677/acm.2026.163860, PDF, HTML, XML,   
作者: 李 泺, 赵 卉*：安徽医科大学第二附属医院呼吸与危重症医学科，安徽 合肥
关键词: sTWEAK；新冠肺炎；严重程度；预后；队列研究；sTWEAK； COVID-19； Severity； Prognosis； Cohort Study
摘要: 背景：可溶性肿瘤坏死因子样弱凋亡诱导因子(sTWEAK)是一种具有生物活性的细胞因子，广泛存在于多种组织和细胞中，参与刺激细胞生长、诱导炎性细胞因子和刺激细胞凋亡，已有研究证明sTWEAK水平升高与肺动脉高压、哮喘和慢性阻塞性肺疾病等呼吸系统疾病的发病机制相关。然而，sTWEAK在新冠肺炎中的作用尚未阐明。本课题旨在探讨血清sTWEAK水平与新冠肺炎患者病情严重程度和预后的关系。方法：本研究是一项前瞻性队列研究，入组了343例符合标准的新冠肺炎患者，系统收集了人口统计学数据和临床特征。采用酶联免疫吸附试验测定血清sTWEAK浓度。结果：在这项队列研究中，我们观察到新冠肺炎患者血清sTWEAK浓度随疾病严重程度评分呈协同性升高。线性回归与逻辑回归模型均发现血清sTWEAK水平与新冠肺炎严重程度评分存在显著正相关关系。经混杂因素调整后，入院时血清sTWEAK水平升高被证实会显著增加机械通气及入住重症监护室风险。与传统肺炎严重程度评分系统相比，受试者工作特征曲线下面积显示，在COVID-19患者中，血清sTWEAK水平对预后恶化的预测能力与传统严重程度评分相当。结论：血清sTWEAK水平升高不仅与新冠肺炎严重程度呈正相关，还可预测新冠肺炎患者的不良临床结局。血清sTWEAK可作为评估新冠肺炎严重程度和预测不良预后的新型生物标志物，有望在临床应用中为新冠肺炎患者提供更精准有效的治疗策略。
Abstract: Background: Soluble tumor necrosis factor-like weak inducer of apoptosis (sTWEAK) is a biologically active cytokine widely distributed in various tissues and cells. It participates in stimulating cell growth, inducing inflammatory cytokines, and stimulating apoptosis. Previous studies have demonstrated that elevated sTWEAK levels are associated with the pathogenesis of respiratory diseases such as pulmonary hypertension, asthma, and chronic obstructive pulmonary disease. However, the role of sTWEAK in COVID-19 remains unclear. This study aims to investigate the relationship between serum sTWEAK levels and the severity and prognosis of COVID-19 patients. Methods: This prospective cohort study enrolled 343 eligible COVID-19 patients, and demographic and clinical characteristics were systematically collected. Serum sTWEAK concentration was measured using an enzyme-linked immunosorbent assay (ELISA). Results: In this cohort study, we observed a synergistic increase in serum sTWEAK concentration with disease severity scores in COVID-19 patients. Both linear and logistic regression models revealed a significant positive correlation between serum sTWEAK levels and COVID-19 severity scores. After adjusting for confounding factors, elevated serum sTWEAK levels at admission significantly increased the risk of mechanical ventilation and admission to the intensive care unit. Compared with the traditional pneumonia severity scoring system, the area under the receiver operating characteristic (AUC) curve showed that serum sTWEAK levels had comparable predictive power for prognostic deterioration in COVID-19 patients. Conclusion: Elevated serum sTWEAK levels are not only positively correlated with COVID-19 severity but can also predict adverse clinical outcomes in COVID-19 patients. Serum sTWEAK can serve as a novel biomarker for assessing COVID-19 severity and predicting adverse prognosis, and is expected to provide more precise and effective treatment strategies for COVID-19 patients in clinical applications.
文章引用：李泺, 赵卉. 血清sTWEAK与新冠肺炎患者严重程度及预后的关联：一项前瞻性队列研究[J]. 临床医学进展, 2026, 16(3): 893-902. https://doi.org/10.12677/acm.2026.163860

1. 背景

新冠肺炎(Corona virus disease 2019, COVID-19)是由一种新型冠状病毒(现称为严重急性呼吸综合征冠状病毒2型，SARS-CoV-2)引发的急性呼吸道感染，主要通过呼吸道飞沫传播[1]。新冠肺炎的体征和症状因患者而异，最常见的临床症状包括发热、乏力、咳嗽、咳痰、咳痰等[2]，截至2025年5月25日，全球已报告超过7.779亿例确诊病例和超过700万例死亡病例，对人类生命健康造成巨大损失，对全球经济、就业和社会生活造成了严重冲击[3]。尽管新冠病毒疫苗和口服抗病毒药物已取得研究进展并在临床中使用，但控制新冠肺炎的进展和死亡率尚未在临床上实现[4] [5]，这对新冠肺炎的防治仍具有重大意义[6]。

尽管已经有一些严重程度评分用于识别高风险新冠肺炎住院患者，但基于大量参数和合并症的复杂预后评分对住院新冠肺炎患者的生存结局没有实现更好的预后特性[7]，发现新的生物标志物对于理解病毒致病机制以及器官和细胞损伤至关重要。

可溶性肿瘤坏死因子样弱凋亡诱导因子(Soluble tumor necrosis factor-like weak inducer of apoptosis, sTWEAK)是一种具有弱凋亡活性的生长调节蛋白，属于肿瘤坏死因子-α家族，由肿瘤坏死因子样凋亡诱导微弱诱导剂(Tumor necrosis factor-like weak inducer of apoptosis, TWEAK)通过特异性蛋白酶水解作用转化而来[8]。sTWEAK由单核细胞和内皮细胞持续表达，可与成纤维细胞生长因子诱导的14号受体(Fn14)结合，从而激活信号传导通路并释放促炎分子[9]。一项动物研究表明，脂多糖诱导急性肺损伤的小鼠其肺组织中Fn14表达水平升高；体外实验显示，TWEAK可激活原代小鼠巨噬细胞中的NLRP3炎症小体，从而加剧小鼠的肺损伤[10]。此外，TWEAK通过Fn14在人支气管上皮细胞中刺激炎症因子白细胞介素-8 (IL-8)和粒细胞–巨噬细胞集落刺激因子(GM-CSF)的产生，并促进炎症性肺病的发生发展[11]。因此，我们推测sTWEAK可能在新冠肺炎的病理生理学过程中发挥重要作用，进行了这项前瞻性队列研究，以探讨新冠肺炎患者血清sTWEAK浓度与疾病严重程度和预后的关系。

2. 材料和方法

2.1. 研究对象

我们对2022年12月1日至2023年6月30日在安徽医科大学第二附属医院呼吸与危重症医学科住院时确诊为新冠肺炎的成人进行了前瞻性研究。所有入组的新冠肺炎患者均符合以下入选标准：(1) 年龄 ≥ 18岁；(2) 经RT-PCR检测新确诊感染SARS-CoV-2，具有新冠肺炎相关临床表现及肺部影像学特征，且发病时间不足48小时；(3) 临床资料完整者，愿意接受抽取外周血、参与后期的随访。排除标准如下：(1) 发病前曾在医疗场所居住超过两周或3月内因病住院；(2) 近一周使用静脉抗生素、抗病毒、糖皮质激素治疗；(3) 合并慢阻肺、支扩、肺恶性肿瘤等其他肺部疾病；(4) 人免疫缺陷病毒(HIV)感染者、粒细胞缺乏者、血液系统肿瘤及实体肿瘤放化疗者、器官移植者等免疫缺陷人群。

2.2. 人口统计学数据、临床特征和随访

研究人群的人口统计学和临床特征是在新冠肺炎患者入院期间从医疗工作站获得。根据血清sTWEAK水平的三分位数将新冠肺炎患者分为三组：T1组，<1.20 ng/mL；T2组，1.20~2.16 ng/mL；T3组，>2.16 ng/mL。住院期间使用公认的肺炎严重程度评分评估新冠肺炎的严重程度，包括SMART-COP评分、CURB-65评分、CURXO评分、PSI评分、A-DROP评分、4C死亡率评分、COVID-GRAM 评分和MuLBSTA评分[12]-[15]。

2.3. 酶联反应吸附实验(ELISA)

在入院后24小时内通过静脉穿刺将外周血抽入凝血管[16]，通过在3500 rpm下离心10分钟获得上层血清，并储存在−80℃冰箱中用于后续检测[17]。血清sTWEAK浓度(ng/mL)采用酶联免疫吸附试验法测定，使用试剂盒按厂商说明书进行定量检测。ELISA试剂盒(CSB-E16492h)由中国武汉科生源生物科技有限公司(https://www.cusabio.com/)提供。

2.4. 数据的统计分析

人口统计学特征和实验室参数以均值 ± 标准误(SEM)或中位数及四分位间距表示。分类变量用频率和百分比表示。不同亚组之间的特征差异用方差分析及卡方检验进行估计。此外，血清sTWEAK和新冠肺炎严重程度评分之间的关联通过线性和逻辑回归模型进行估计，采用逻辑回归模型探讨血清sTWEAK水平与临床结局的关系。通过受试者工作特征(ROC)曲线评估血清sTWEAK水平及传统肺炎严重程度评分系统对预后不良的预测能力。

3. 结果

3.1. 人口统计学和临床特征

本研究共纳入了343例入院时患有新冠肺炎的患者(表1)。如表1所示，所有受试者的平均年龄约为70岁，其中191例为男性(55.7%)。共有49名(14.3%)患者报告有吸烟史。在三个亚组中，高水平sTWEAK组(T3)糖尿病患病率显著更高(P < 0.05)。三个亚组之间在肌酸激酶同工酶(CK-MB)、D-二聚体(D-dimer)两项检验结果存在差异，T3组这两项指标显著升高，可能反映sTWEAK与心肌损伤、血栓形成风险相关。三个亚组在C反应蛋白(CRP)、白介素-6 (IL-6)、降钙素原(PCT)等其他检验指标方面无差异。

Table 1. Demographic characteristics of participators at baseline

表1. 参与者基线人口统计学特征

Characteristic

Tertile of serum sTWEAK

P

T1 (<1.20 ng/mL)

T2 (1.20~2.16 ng/mL)

T3 (>2.16 ng/mL)

N

108

107

108

Age, years

68.5 ± 1.58

71.6 ± 1.33

71.1 ± 1.30

0.238

Male, n (%)

68 (63.0)

58 (54.2)

65 (60.2)

0.408

BMI

24.5 ± 0.41

22.3 ± 0.41

24.5 ± 0.52

0.952

Smoker, n (%)

16 (14.8)

12 (11.2)

21 (19.4)

0.254

Systolic pressure (mmHg)

133.2 ± 2.04

137.1 ± 1.92

133.0 ± 2.07

0.275

Diastolic pressure (mmHg)

78.0 ± 1.24

80.2 ± 1.17

79.7 ± 1.19

0.376

Hypertension, n (%)

49 (45.4)

48 (44.9)

57 (52.8)

0.347

Diabetes mellitus, n (%)

20 (18.5)

17 (15.9)

36 (36.1)

0.012

Coronary heart diseases, n (%)

23 (21.3)

16 (15.0)

25 (23.1)

0.296

Other chronic heart disease, n (%)

20 (18.5)

9 (8.4)

13 (12.0)

0.093

Cerebrovascular diseases, n (%)

21 (19.4)

19 (17.8)

31 (28.7)

0.122

Chronic liver diseases, n (%)

3 (2.8)

5 (4.7)

3 (2.8)

0.748

Hepatitis B, n (%)

2 (1.9)

3 (2.8)

2 (1.9)

0.901

Chronic kidney diseases, n (%)

10 (9.3)

8 (7.5)

10 (9.3)

0.909

Bronchiectasis, n (%)

1 (0.9)

2 (1.9)

4 (3.7)

0.269

Corticosteroids therapy, n (%)

87 (80.6)

88 (82.2)

89 (82.4)

0.950

Antibiotics therapy, n (%)

106 (98.1)

100 (93.5)

106 (98.1)

0.101

Antiviral therapy, n (%)

45 (41.7)

47 (43.9)

55 (50.9)

0.373

Anticoagulant therapy, n (%)

56 (51.9)

63 (58.9)

66 (61.1)

0.368

PaO2 (mm Hg)

92.4 ± 3.91

87.5 ± 3.11

83.1 ± 2.87

0.142

PaCO2 (mm Hg)

35.6 ± 0.97

37.1 ± 0.98

36.7 ± 0.80

0.520

SpO2 (%)

93.6 ± 0.74

94.5 ± 0.51

93.6 ± 0.61

0.459

PaO2/FiO2 (%)

303.7 ± 14.10

294.4 ± 10.18

279.9 ± 13.18

0.407

WBC (109/L)

7.6 ± 0.37

7.7 ± 0.35

8.3 ± 0.35

0.378

Neutrophil (109/L)

6.0 ± 0.35

6.1 ± 0.34

6.4 ± 0.33

0.594

Lymphocyte (109/L)

1.1 ± 0.08

1.1 ± 0.06

1.2 ± 0.13

0.565

Monocyte (109/L)

0.5 ± 0.03

0.5 ± 0.02

0.6 ± 0.05

0.257

Eosinophil (109/L)

0.05 ± 0.01

0.05 ± 0.01

0.08 ± 0.02

0.296

ALT (U/L)

31.8 ± 2.12

34.0 ± 2.56

31.4 ± 3.05

0.737

AST (U/L)

33.0 ± 2.24

36.0 ± 3.32

35.6 ± 3.19

0.733

Uric acid (μmol/L)

269.7 ± 12.19

267.8 ± 13.84

268.5 ± 10.64

0.933

Urea nitrogen (mmol/L)

8.7 ± 0.93

8.1 ± 0.70

9.3 ± 0.92

0.641

Creatinine (μmol/L)

111.1 ± 18.06

98.3 ± 13.19

103.7 ± 14.78

0.842

CK (U/L)

53.0 (30.0, 90.0)

53.0 (30.0, 79.0)

57.0 (37.0, 123.0)

0.127

CK-MB (U/L)

14.0 (7.5, 18.5)

10.0 (7.0, 16.0)

14.5 (7.8, 24.3)

0.028

Myoglobin (ng/mL)

85.2 (40.1, 256.5)

54.1 (28.7, 185.7)

64.8 (32.6, 110.4)

0.250

LDH (U/L)

274.2 ± 10.53

270.8 ± 12.19

310.2 ± 19.37

0.614

D-dimer (ng/mL)

1.3 ± 0.15

2.6 ± 0.90

2.7 ± 0.59

0.039

CRP (mg/L)

22.5 (5.6, 71.0)

26.0 (5.8, 72.4)

27.2 (9.5, 86.9)

0.539

IL-6 (pg/mL)

20.8 (7.3, 91.2)

13.5 (5.4, 50.0)

23.0 (8.0, 74.2)

0.117

PCT (ng/mL)

0.05 (0.03, 0.17)

0.06 (0.03, 0.15)

0.06 (0.02, 0.33)

0.761

3.2. 不同严重程度新冠肺炎患者血清sTWEAK水平的研究

Figure 1. The levels of circulatory sTWEAK in COVID-19 patients with different severity

图1. 不同严重程度的新冠肺炎患者血液中sTWEAK的水平

采用ELISA法检测新冠肺炎患者血清中sTWEAK水平，比较不同严重程度新冠肺炎患者血清中sTWEAK水平的变化。如图1所示，根据SMART-COP评分，7~8分组的血清sTWEAK水平高于0~2分组、3~4分组和5~6分组(图1(A))；根据4C死亡率(4C mortality)评分，极高风险组的血清sTWEAK水平显著高于高风险组，亦高于低风险组和中风险组(图1(B))；根据A-DROP评分，极高风险组的血清sTWEAK水平高于其他组别，且高风险组的血清sTWEAK水平显著高于低风险组和中风险组(图1(D))；根据DTPNCP评分，极高风险组的血清sTWEAK水平显著高于高风险组，且高于低风险组和中风险组(图1(E))；根据PSI评分，PSIⅤ级的COVID-19患者显著高于其他级别(图1(G))。根据CURB-65评分，3~5分组的血清sTWEAK水平高于0~1分组和2分组(图1(H))；根据CURXO、MuLBSTA、COVID-GRAM评分,非重症与重症新冠肺炎组的sTWEAK水平无明显差异(图1(C)、图1(F)、图1(I))。

3.3. 血清sTWEAK水平与新冠肺炎患者疾病严重程度的关联

构建多元回归模型分析血清sTWEAK水平与疾病严重程度评分之间的关联，同时调整混杂变量(表2)。多元线性回归分析显示：sTWEAK水平每增加1个单位，SMART-COP评分增加0.333 (95%CI: 0.179~0.488)，CURB-65评分增加0.120分(95% CI: 0.039~0.202)，COVID-GRAM评分增加7.244分(95% CI: 2.764~11.725)，A-DROP评分增加0.125分(95%CI: 0.037~0.213)，4C死亡率评分增加0.343分(95%CI: 0.104~0.582)。CURXO、MuLBSTA、PSI和DTPNCP评分与sTWEAK水平之间均未发现显著线性关联。此外，还分析了各亚组间的差异。A-DROP评分存在显著差异，T3组评分较T1组高出2.390倍(95%CI: 1.168~2.892)，P值为0.015。T3组的4C死亡率评分是T1组的2.010倍(95%CI: 1.123~4.378)，P值为0.025，表明sTWEAK水平随死亡风险评分升高而呈现显著上升趋势。

Table 2. Associations between serum sTWEAK and severity in COVID-19 patients

表2. 新冠肺炎患者血清sTWEAK水平与疾病严重程度的相关性

Variables

Estimated changes by continues sTWEAK

Estimated changes (95% CI) by tertiles of sTWEAK

P trend

T1 (<1.20 ng/mL)

T2 (1.20~2.16 ng/mL)

T3 (>2.16 ng/mL)

N

323

108

107

108

SMART-COP

0.333 (0.179, 0.488)

1.0 (Ref)

0.779 (0.361, 1.682)

1.512 (0.732, 3.121)

0.359

CURB-65

0.120 (0.039, 0.202)

1.0 (Ref)

0.627 (0.317, 1.242)

0.933 (0.477, 1.825)

0.332

CURXO (Severe)

0.003 (−0.038, 0.043)

1.0 (Ref)

1.462 (0.759, 2.818)

1.109 (0.578, 2.128)

0.285

COVID-GRAM

7.244 (2.764, 11.725)

1.0 (Ref)

1.006 (0.492, 2.058)

1.397 (0.704, 2.772)

0.457

MuLBSTA

0.150 (−0.226, 0.526)

1.0 (Ref)

0.809 (0.396, 1.654)

1.054 (0.532, 2.088)

0.258

A-DROP

0.125 (0.037, 0.213)

1.0 (Ref)

1.162 (0.550, 2.454)

2.390 (1.168, 2.892)

0.015

PSI

3.042 (−0.401, 6.486)

1.0 (Ref)

0.657 (0.305, 1.417)

1.340 (0.654, 2.747)

0.203

4C Mortality

0.343 (0.104, 0.582)

1.0 (Ref)

0.716 (0.318, 1.614)

2.010 (1.123, 4.378)

0.025

DTPNCP

0.052 (−0.025, 0.130)

1.0 (Ref)

0.632 (0.333, 1.202)

0.944 (0.507, 1.759)

0.335

模型已根据年龄、高血压、糖尿病、冠心病、脑血管疾病、慢性肝病、乙型肝炎、慢性肾病及支气管扩张症进行调整。

3.4. 血清sTWEAK水平与新冠肺炎患者预后之间的关联

从表3可知，T3组中需要机械通气、使用血管活性药物、入住ICU、住院时间延长或死亡的新冠肺炎患者数量均高于T1组和T2组。在未调整混杂因素的情况下，T3组的机械通气和入住ICU相对风险(RR)最高。经混杂因素校正后，T3组机械通气(RR = 3.572)和ICU收治(RR = 3.867)的风险仍显著高于其他组别。

Table 3. Associations between serum sTWEAK and prognostic outcomes in COVID-19 patients

表3. 新冠肺炎患者血清sTWEAK与预后结果的相关性

Variables

Serum sTWEAK

Ptrend

T1 (<1.20 ng/mL)

T2 (1.20~2.16 ng/mL)

T3 (>2.16 ng/mL)

N

108

107

108

Mechanical ventilation

N, (%)

4 (3.7)

2 (1.9)

14 (13.0)

0.003

Unadjusted RR (95% CI)

Ref (1.0)

0.495 (0.089, 2.763)

3.872 (1.231, 12.177)

0.005

Adjusted RR (95% CI)

Ref (1.0)

0.424 (0.071, 2.525)

3.572 (0.984, 12.971)

0.030

Vasoactive agent

N, (%)

4 (3.7)

4 (3.7)

12 (11.1)

0.055

Unadjusted RR (95% CI)

Ref (1.0)

3.250 (1.014, 10.420)

1.010 (0.246, 4.146)

0.054

Adjusted RR (95% CI)

Ref (1.0)

0.778 (0.163, 3.707)

1.809 (0.463, 7.067)

0.216

ICU admission

N, (%)

4 (3.7)

5 (4.7)

17 (15.7)

0.002

Unadjusted RR (95% CI)

Ref (1.0)

1.275 (0.333, 4.881)

4.857 (1.577, 14.960)

0.001

Adjusted RR (95% CI)

Ref (1.0)

1.089 (0.245, 4.840)

3.867 (1.107, 13.509)

0.015

Death

N, (%)

6 (5.6)

4 (3.7)

13 (12.0)

0.060

Unadjusted RR (95% CI)

Ref (1.0)

0.660 (0.181, 2.409)

2.326 (1.050, 6.367)

0.064

Adjusted RR (95% CI)

Ref (1.0)

0.743 (0.177, 3.124)

2.795 (1.818, 9.547)

0.256

Longer hospital stays

N, (%)

20 (18.5)

17 (15.9)

28 (25.9)

0.288

Unadjusted RR (95% CI)

Ref (1.0)

0.840 (0.413, 1.710)

1.559 (0.815, 2.985)

0.165

Adjusted RR (95% CI)

Ref (1.0)

0.809 (0.371, 1.763)

1.277 (0.612, 2.663)

0.578

3.5. 血清sTWEAK水平对新冠肺炎患者疾病严重程度及死亡风险的预测能力

Figure 2. The predictive capacities of circulatory sTWEAK for severity and death among COVID-19 patients

图2. 循环sTWEAK对新冠肺炎患者病情严重程度及死亡风险的预测能力

通过ROC曲线下面积评估血清sTWEAK及多种严重程度评分对不良预后的预测能力。对机械通气的预测能力如下为DTPNCP：0.857；CURB-65：0.922；A-DROP：0.861；SMART-COP：0.797；MuLBSTA：0.758；PSI：0.897；COVID-GRAM：0.796；4C死亡率：0.933；CURXO：0.681；血清sTWEAK：0.862 (图2(A))。血清sTWEAK水平的临界浓度为2.38 ng/mL，其敏感性为73.1%，特异性为74.3%。此外，还评估了各评分系统对入住ICU的预测能力，如图2(B)所示，DTPNCP：0.859；CURB-65：0.912；A-DROP：0.859；SMART-COP：0.862；MuLBSTA：0.692；PSI：0.822；COVID-GRAM：0.788；4C死亡率：0.923；CURXO：0.749；血清sTWEAK：0.767。血清sTWEAK的临界浓度为2.39 ng/mL，其敏感性为90.0%，特异性为74.5%。

4. 讨论

本研究为探讨血清sTWEAK水平与新冠肺炎重症程度及预后之间的关联提供了证据。研究表明，入院时血清sTWEAK水平与新冠肺炎重症评分呈显著正相关。此外，研究结果显示入院时sTWEAK水平升高与机械通气风险增加及重症监护室收治风险升高存在显著关联。血清sTWEAK在预测不良预后方面的效能与多种肺炎严重程度评分相当。这些发现表明，入院时血清sTWEAK水平在评估新冠肺炎严重程度及预测不良预后方面具有临床实用价值。

sTWEAK是一种炎症性细胞因子，具有多种生物学功能，参与包括增殖、分化、炎症、组织修复、细胞凋亡和血管生成在内的病理生理过程[18]。大量证据表明，sTWEAK在多种疾病中发挥着重要作用，例如桥本甲状腺炎、神经血管疾病、心血管疾病和炎症性肠病[19]-[23]。此外，sTWEAK水平升高与呼吸系统疾病的发病机制相关，例如肺动脉高压、哮喘和慢性阻塞性肺病[24]。因此，我们检测了不同严重程度新冠肺炎患者体内的循环sTWEAK水平。研究发现，血清sTWEAK水平随严重程度评分升高而增加，证实了新冠肺炎患者sTWEAK水平与其病情严重程度呈正相关。并探讨了sTWEAK水平与多种临床指标的关系，结果显示血清sTWEAK水平升高与肌酸激酶同工酶(CK-MB)和D-二聚体水平呈正相关，表明sTWEAK升高可能参与新冠肺炎的病理生理过程。

此外，大量证据表明sTWEAK浓度与多种疾病的预后结果存在显著关联。sTWEAK水平在预测扩张型心肌病患者死亡率方面具有潜在价值[25]。测定sTWEAK水平对于评估住院慢性心力衰竭患者发生肺部感染时的病情及预后具有重要价值[26]。因此，我们分析了血清sTWEAK水平与预后的相关性。研究发现血清sTWEAK水平升高的新冠肺炎患者出现机械通气和重症监护室收治的风险显著增加。此外，我们评估了血清sTWEAK与不同肺炎严重程度评分系统预测预后的能力，结果表明血清sTWEAK水平预测不良预后的能力与某些传统评分系统相当，且血清sTWEAK可作为新冠肺炎的新型生物标志物。

本研究主要揭示了新冠肺炎患者入院时血清sTWEAK水平与疾病严重程度及不良预后呈正相关，但研究仍存在一些局限性：第一，由于所有受试者均来自单一研究机构，样本量相对较小；第二，本研究仅检测了血清样本中的sTWEAK水平，而支气管肺泡灌洗液及肺组织中的sTWEAK浓度尚不明确；第三，本研究属于基于人群的流行病学调查，sTWEAK升高的潜在机制仍有待阐明。

5. 结论

这项前瞻性队列研究主要分析了血清sTWEAK水平与新冠肺炎严重程度及预后的关联性。研究结果表明，新冠肺炎患者血清sTWEAK水平升高与疾病严重程度增加及预后不良风险升高相关。血清sTWEAK可作为评估新冠肺炎严重程度和预后的有效生物标志物，该发现有望为改善新冠肺炎的监测和治疗提供有益信息。

致 谢

向所有参与者致以诚挚的谢意，感谢他们为这项研究做出的宝贵贡献。

伦理与知情同意说明

本研究已获得安徽医科大学第二附属医院伦理委员会正式批准与支持(批准号：YJ-YX2021-147)。所有参与者均自愿参与并签署知情同意书。

NOTES

*通讯作者。

参考文献

[1] Baloch, S., Baloch, M.A., Zheng, T. and Pei, X. (2020) The Coronavirus Disease 2019 (COVID-19) Pandemic. The Tohoku Journal of Experimental Medicine, 250, 271-278. [Google Scholar] [CrossRef] [PubMed]
[2] Ochani, R., Asad, A., Yasmin, F., et al. (2021) COVID-19 Pandemic: From Origins to Outcomes. A Comprehensive Review of Viral Pathogenesis, Clinical Manifestations, Diagnostic Evaluation, and Management. Infezione Medica, 29, 20-36.
[3] World Health Organization (2025) WHO COVID-19 Dashboard.
https://data.who.int/dashboards/covid19/cases?n=c
[4] Li, M., Wang, H., Tian, L., Pang, Z., Yang, Q., Huang, T., et al. (2022) COVID-19 Vaccine Development: Milestones, Lessons and Prospects. Signal Transduction and Targeted Therapy, 7, Article No. 146. [Google Scholar] [CrossRef] [PubMed]
[5] Schilling, W.H.K., Jittamala, P., Watson, J.A., Boyd, S., Luvira, V., Siripoon, T., et al. (2024) Antiviral Efficacy of Molnupiravir versus Ritonavir-Boosted Nirmatrelvir in Patients with Early Symptomatic COVID-19 (PLATCOV): An Open-Label, Phase 2, Randomised, Controlled, Adaptive Trial. The Lancet Infectious Diseases, 24, 36-45. [Google Scholar] [CrossRef] [PubMed]
[6] Saxena, S.K., Kumar, S., Ansari, S., Paweska, J.T., Maurya, V.K., Tripathi, A.K., et al. (2022) Characterization of the Novel SARS‐CoV‐2 Omicron (B.1.1.529) Variant of Concern and Its Global Perspective. Journal of Medical Virology, 94, 1738-1744. [Google Scholar] [CrossRef] [PubMed]
[7] Lucijanić, M., Živković, N.P., Režić, T., Durlen, I., Stojić, J., Jurin, I., et al. (2023) The Performance of the WHO COVID-19 Severity Classification, COVID-GRAM, VACO Index, 4C Mortality, and CURB-65 Prognostic Scores in Hospitalized COVID-19 Patients: Data on 4014 Patients from a Tertiary Center Registry. Croatian Medical Journal, 64, 13-20. [Google Scholar] [CrossRef] [PubMed]
[8] Comertpay, E., Vural, S., Eroğlu, O., Dindar Badem, N., Bilgili, Y. and Coskun, F. (2020) The Diagnostic Value of Stweak in Acute Ischemic Stroke. Balkan Medical Journal, 37, 336-340. [Google Scholar] [CrossRef] [PubMed]
[9] da Silva-Candal, A., López-Dequidt, I., Rodriguez-Yañez, M., Ávila-Gómez, P., Pumar, J.M., Castillo, J., et al. (2021) Stweak Is a Marker of Early Haematoma Growth and Leukoaraiosis in Intracerebral Haemorrhage. Stroke and Vascular Neurology, 6, 528-535. [Google Scholar] [CrossRef] [PubMed]
[10] Guan, X., Yang, H., Zhong, W., Duan, J., Zhang, C., Jiang, H., et al. (2022) Fn14 Exacerbates Acute Lung Injury by Activating the NLRP3 Inflammasome in Mice. Molecular Medicine, 28, Article No. 85. [Google Scholar] [CrossRef] [PubMed]
[11] Xu, H., Okamoto, A., Ichikawa, J., Ando, T., Tasaka, K., Masuyama, K., et al. (2004) Tweak/Fn14 Interaction Stimulates Human Bronchial Epithelial Cells to Produce IL-8 and Gm-CSF. Biochemical and Biophysical Research Communications, 318, 422-427. [Google Scholar] [CrossRef] [PubMed]
[12] Xu, Z., Wang, X., Cao, P., Zhang, C., Feng, C., Zheng, L., et al. (2022) Serum IL-27 Predicts the Severity and Prognosis in Patients with Community-Acquired Pneumonia: A Prospective Cohort Study. International Journal of Medical Sciences, 19, 74-81. [Google Scholar] [CrossRef] [PubMed]
[13] Abu Elhassan, U.E., Alqahtani, S.M.A., Al Saglan, N.S., Hawan, A., Alqahtani, F.S., Almtheeb, R.S., et al. (2023) Utility of the 4C ISARIC Mortality Score in Hospitalized COVID-19 Patients at a Large Tertiary Saudi Arabian Center. Multidisciplinary Respiratory Medicine, 18, Article No. 917. [Google Scholar] [CrossRef] [PubMed]
[14] Armiñanzas, C., Arnaiz de las Revillas, F., Gutiérrez Cuadra, M., Arnaiz, A., Fernández Sampedro, M., González-Rico, C., et al. (2021) Usefulness of the COVID-GRAM and CURB-65 Scores for Predicting Severity in Patients with Covid-19. International Journal of Infectious Diseases, 108, 282-288. [Google Scholar] [CrossRef] [PubMed]
[15] Iijima, Y., Okamoto, T., Shirai, T., Mitsumura, T., Sakakibara, R., Honda, T., et al. (2021) Mulbsta Score Is a Useful Tool for Predicting COVID-19 Disease Behavior. Journal of Infection and Chemotherapy, 27, 284-290. [Google Scholar] [CrossRef] [PubMed]
[16] Feng, C., Cheng, J., Xu, Z., Liu, H., Xu, D., Fu, L., et al. (2021) Associations of Serum Resistin with the Severity and Prognosis in Patients with Community-Acquired Pneumonia. Frontiers in Immunology, 12, Article ID: 703515. [Google Scholar] [CrossRef] [PubMed]
[17] Zheng, L., Fei, J., Feng, C., Xu, Z., Fu, L. and Zhao, H. (2021) Serum 8-Iso-PGF2α Predicts the Severity and Prognosis in Patients with Community-Acquired Pneumonia: A Retrospective Cohort Study. Frontiers in Medicine, 8, Article ID: 633442. [Google Scholar] [CrossRef] [PubMed]
[18] Burkly, L.C., Michaelson, J.S., Hahm, K., Jakubowski, A. and Zheng, T.S. (2007) Tweaking Tissue Remodeling by a Multifunctional Cytokine: Role of Tweak/Fn14 Pathway in Health and Disease. Cytokine, 40, 1-16. [Google Scholar] [CrossRef] [PubMed]
[19] Altay, M., Ateş, İ., Yılmaz, F.M., Topçuoğlu, C. and Kaplan, M. (2016) Rola krążącego sTWEAK w patogenezie choroby Hashimoto—Badanie pilotażowe. Endokrynologia Polska, 67, 562-566. [Google Scholar] [CrossRef] [PubMed]
[20] da Silva‐Candal, A., Custodia, A., López‐Dequidt, I., Rodríguez‐Yáñez, M., Alonso‐Alonso, M.L., Ávila‐Gómez, P., et al. (2022) Stweak Is a Leukoaraiosis Biomarker Associated with Neurovascular Angiopathy. Annals of Clinical and Translational Neurology, 9, 171-180. [Google Scholar] [CrossRef] [PubMed]
[21] Ptaszynska-Kopczynska, K., Marcinkiewicz-Siemion, M., Lisowska, A., Waszkiewicz, E., Witkowski, M., Jasiewicz, M., et al. (2016) Alterations of Soluble TWEAK and CD163 Concentrations in Patients with Chronic Heart Failure. Cytokine, 80, 7-12. [Google Scholar] [CrossRef] [PubMed]
[22] Rusu, C.C., Racasan, S., Kacso, I.M., Ghervan, L., Moldovan, D., Potra, A., et al. (2015) The Association of High sCD163/STWEAK Ratio with Cardiovascular Disease in Hemodialysis Patients. International Urology and Nephrology, 47, 2023-2030. [Google Scholar] [CrossRef] [PubMed]
[23] Kaplan, M., Yuksel, M., Ates, I., Yaln Kilic, Z.M., Kilic, H., Ates, H., et al. (2016) Are Stweak and IL-17A Levels in Inflammatory Bowel Disease Associated with Disease Activity and Etiopathogenesis? Inflammatory Bowel Diseases, 22, 615-622. [Google Scholar] [CrossRef] [PubMed]
[24] Wang, M., Xie, Z., Xu, J. and Feng, Z. (2020) Tweak/Fn14 Axis in Respiratory Diseases. Clinica Chimica Acta, 509, 139-148. [Google Scholar] [CrossRef] [PubMed]
[25] Richter, B., Rychli, K., Hohensinner, P.J., Berger, R., Mörtl, D., Neuhold, S., et al. (2010) Differences in the Predictive Value of Tumor Necrosis Factor-Like Weak Inducer of Apoptosis (TWEAK) in Advanced Ischemic and Non-Ischemic Heart Failure. Atherosclerosis, 213, 545-548. [Google Scholar] [CrossRef] [PubMed]
[26] Zheng, F. (2022) Pathogenic Characteristics of Pulmonary Infection in Hospitalized Patients with Chronic Heart Failure and Diagnostic Value of sTREM-1, sCD163, and Stweak. Pakistan Journal of Medical Sciences, 38, 536-541. [Google Scholar] [CrossRef] [PubMed]

为你推荐