Correlation between NRS-2002 scores and PD-1/CTLA-4 expression levels in patients with community-acquired pneumonia

Abstract

This study aimed to investigate the association between nutritional status, T cell-mediated immunosuppression involving PD-1 and CTLA-4, and the prognosis of patients with community-acquired pneumonia (CAP). Following the enrollment protocol, 60 participants were recruited, and their medical records were collected. Blood samples were obtained to assess the expression of PD-1 and CTLA-4 across different T-cell subsets. Logistic regression analysis revealed no significant association between PD-1/CTLA-4 expression and severe CAP (SCAP) or 28-day mortality. However, elevated levels of PD-1 and CTLA-4 on CD4 + T cells correlated with higher Pneumonia Severity Index (PSI) scores. Patients identified as being at malnutrition risk (Nutritional Risk Screening [NRS-2002] score ≥ 3) exhibited a higher proportion of SCAP and experienced prolonged hospital stays compared to those without nutritional risk. Furthermore, higher expression levels of PD-1 and CTLA-4 were observed in the malnutrition risk group. Malnutrition was associated with longer hospitalization and an increased risk of severe CAP. Elevated PD-1 and CTLA-4 expression on CD4 + T cells was linked to higher PSI scores. These findings suggest that nutritional status may influence the development of immunosuppression, potentially through pathways involving PD-1 and CTLA-4.

Introduction

Nutritional status exerts a significant influence on overall health, particularly in individuals with comorbidities, critical illnesses, or advanced age, and is closely correlated with disease prognosis and mortality^1–3. In Asia, the prevalence of malnutrition risk among the elderly population is as high as 73%⁴. The increasing rates of hospitalization and mortality associated with community-acquired pneumonia (CAP) have become a growing concern in the post-coronavirus disease 2019 (COVID-19) era, with some studies reporting in-hospital mortality rates of approximately 40% and a sharp rise in associated healthcare costs⁵.

Nutritional status plays a critical role in immune competence. Malnutrition can impair immune function by hindering antibody production, exacerbating oxidative stress, and disrupting inflammatory responses. Specifically, hypoproteinemia reduces the production of key antibodies, including functional immunoglobulins and those associated with gut-associated lymphoid tissue, thereby increasing the risk of infection. When pathogens invade, lymphocytes respond by secreting cytokines and chemokines, which orchestrate the subsequent inflammatory response^6,7. To assess nutritional status, the Nutritional Risk Screening-2002 (NRS-2002) is widely used as a classic, validated, and rapid tool, categorizing patients into malnutrition risk (score ≥ 3) and no-risk (score < 3) groups. The clinical relevance of this tool is underscored by research from Iddir M and Sümer A, which demonstrated that an NRS-2002 score ≥ 3 is associated with a 5.6-fold increased risk of severe COVID-19⁸. Despite this evidence, the specific relationship between nutritional status and CAP has not yet been clearly defined.

T-cell subsets, including CD4 + T cells (CD4+), CD8 + T cells (CD8+), and regulatory T cells (Tregs), play pivotal roles in the immune response to infections. Programmed cell death protein 1 (PD-1) is an inhibitory receptor expressed on activated T lymphocytes that regulates T-cell activation. Upon binding to its ligands on antigen-presenting cells (APCs), PD-1 can induce immune tolerance, leading to T lymphocyte dysfunction, apoptosis, and impaired cytokine production. Cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) is another immunosuppressive molecule expressed on activated T lymphocytes. It generates inhibitory signals that prevent T-cell activation by competitively inhibiting CD28 binding to APCs^9–11. The inhibitory molecules PD-1 and CTLA-4, which are expressed on activated T cells, are upregulated in the context of pneumonia and sepsis, suggesting their involvement in infection-induced immunosuppression. Given that the expression of PD-1 and CTLA-4 is elevated in patients with pneumonia or sepsis compared to healthy controls, we hypothesize that the early stage of infection is characterized by a state of immunosuppression mediated by the upregulation of these inhibitory receptors on CD4+, CD8+, and Treg cells^9–12.

Nutritional status is known to modulate immune function, and malnutrition is recognized as a cause of immune deficiency and impaired immune responses. While most studies have focused on the impact of nutritional status on infection outcomes (e.g., pneumonia), limited research has addressed the reciprocal relationship between infection and nutritional status. To determine whether malnutrition promotes T-cell-mediated immunosuppression, we conducted this study to explore the relationship between nutritional status and the expression of PD-1 and CTLA-4 in patients with CAP.

Materials and methods

Definitions

This study adhered to established clinical guidelines for defining and assessing CAP. Following the American Thoracic Society (ATS) and Infectious Diseases Society of America (IDSA) CAP guidelines, CAP was defined as pneumonia acquired outside of hospital settings^13–16. Severe CAP (SCAP) was diagnosed according to the IDSA/ATS severity criteria, and the Pneumonia Severity Index (PSI) was employed as a recommended clinical predictor for CAP prognosis^13–16.

Nutritional status was assessed using the Nutritional Risk Screening-2002 (NRS-2002), in accordance with the European Society for Clinical Nutrition and Metabolism (ESPEN) guidelines. This validated tool categorizes participants into a malnutrition risk group (score ≥ 3) and a no-risk group (score < 3)^17,18.

PD-1 and CTLA-4, expressed on the surface of CD4+, CD8+, and regulatory T cells (Tregs), are considered indicators of immunosuppression that regulate T-cell function. Tregs were identified as the CD3+CD4+CD25+CD127-/low population within the lymphocyte gate.

Study design

Enrollment strategy

Inclusion Criteria: Eligible participants were adults aged ≥ 18 years with a primary diagnosis of CAP. Enrollment required complete demographic data, medical history, laboratory results, and clinical records. All participants provided informed consent after receiving a thorough explanation of the study’s purpose and procedures, and were capable of cooperating with the research protocol.

Exclusion Criteria: Exclusion criteria included age < 18 years, pregnancy, incomplete clinical records, a history of immune-related diseases (e.g., HIV/AIDS, primary immunodeficiency), or use of immunosuppressive medications within the preceding three months. Patients with COVID-19 or hospital-acquired pneumonia were also excluded. Additionally, individuals whose primary diagnosis was not CAP (e.g., heart failure with pneumonia, postprocedural pneumonia) were ineligible. Patients with severe comorbidities, including chronic kidney disease (CKD stage ≥ 2) or chronic heart failure (NYHA class ≥ 2), were excluded from participation.

Data collection

This prospective, cross-sectional study was approved by the Ethics Committee of Beijing Tsinghua Changgung Hospital (BTCH) (Ethics number: 18190-0-02; Date: September 7, 2021) and was conducted collaboratively by the Department of Emergency and the Infectious Disease Center at BTCH. All participants provided written informed consent prior to enrollment, and blood samples were collected for analysis.

From September 2021 to September 2022, 103 patients were initially screened, of whom 64 met the inclusion criteria and were enrolled. Participants were stratified into two groups based on NRS-2002 scores: a malnutrition risk group (score ≥ 3) and a no-risk group (score < 3). During follow-up, four participants were excluded due to hospital transfer or treatment withdrawal, leaving 60 participants for final analysis. The malnutrition risk group comprised 38 individuals (63.33%), while the no-risk group included 22 individuals (36.67%). Demographic data, comorbidities, laboratory findings, PSI scores, and NRS-2002 scores were obtained from the BTCH hospital information system (HIS) (Fig. 1).

Fig. 1.

Research enrollment strategy.

Laboratory methods

After obtaining informed consent, 10mL of venous blood was collected from each participant within 24 h of admission. Blood samples were placed in anticoagulant tubes containing dipotassium ethylenediaminetetraacetate (EDTA-K2) and transported at 4℃ for processing within 2 h of collection.

Peripheral blood mononuclear cells (PBMCs) were isolated via density gradient centrifugation. Briefly, 3 mL of lymphocyte separation medium was added to a centrifuge tube. Heparin-anticoagulated blood was mixed with an equal volume of phosphate-buffered saline (PBS) (10 mL total), and the mixture was gently layered onto the separation medium. Following centrifugation at 400 × g for 30 min at 20 °C, the liquid separated into three distinct layers. The mononuclear cell layer (buffy coat) was carefully transferred to a new tube, and at least three volumes of PBS were added. The suspension was centrifuged at 1500 rpm for 6 min at 4 °C, and the supernatant was discarded.

The cell pellet was resuspended in 100 µL of cold PBS, and fluorochrome-conjugated antibodies against cell surface molecules (anti-CD3, anti-CD4, anti-CD8, anti-CD25, anti-CD127, anti-PD-1(eBioscience 61-2799-42), and anti-CTLA-4(eBioscience-46-1529-42)) were added. The samples were vortexed gently and incubated at 4 °C for 30 min in the dark. Following incubation, excess unbound antibodies were removed by adding 3 mL of cold PBS, centrifuging at 1500 rpm for 5 min, and discarding the supernatant. This washing step was repeated once. Stained cells were resuspended in an appropriate volume of PBS and analyzed using a FACS Canto II flow cytometer (BD Biosciences). Data were analyzed with FCS Express 4 software (De Novo Software) (Fig. 2).

Fig. 2.

Laboratory methods.

Outcomes

SCAP occurrence and mortality were compared across the different groups. SCAP was diagnosed according to the standards of the IDSA/ATS CAP severity criteria: (1) Major criteria (requiring Intensive Care Unit (ICU) admission if ≥ 1 is present): invasive mechanical ventilation (IMV) is needed. Septic shock with vasopressors is needed (systolic Blood Pressure(SBP) < 90 mmHg after fluid resuscitation). (2) Minor criteria (≥ 3 minor criteria suggest severe CAP and ICU consideration): respiratory rate ≥ 30 breaths/min, PaO₂/FiO₂ ratio ≤ 250 (hypoxemia requiring high oxygen support), multilobar infiltrates on chest imaging (≥ 2 lobes involved), confusion/disorientation (altered mental status), blood urea nitrogen (BUN) ≥ 20 mg/dL (or elevated creatinine, indicating renal dysfunction), leukopenia (white blood cell(WBC) < 4,000 cells/mm³) due to infection, thrombocytopenia (platelets < 100,000 cells/mm³), hypothermia (core temperature < 36 °C), and hypotension requiring aggressive fluid resuscitation.

Mortality was assessed as death from any cause within 28 days following enrollment. Participants were categorized into a malnutrition risk group (NRS-2002 score ≥ 3) and a no-risk group (NRS-2002 score < 3) to evaluate the association between nutritional status and clinical outcomes. The primary objective was to determine whether nutritional risk screening results correlated with SCAP occurrence and 28-day mortality. Furthermore, we examined the relationship between PD-1/CTLA-4 expression and these outcomes, and explored whether BMI and serum albumin (ALB) levels—as additional nutritional indicators—influenced the expression of these immune checkpoint molecules.

Statistical analysis

Statistical analyses were performed using SPSS software (version 30.0) and GraphPad Prism (version 10). Continuous variables were tested for normality using appropriate methods. Normally distributed data are presented as mean ± standard deviation (x̄± s), and comparisons between two groups were conducted using the independent samples t-test. Non-normally distributed data are expressed as median with interquartile range [M (P₂₅, P₇₅)], and group comparisons were performed using the Mann-Whitney U test (rank sum test). Categorical variables are presented as frequencies and percentages (n, %), and comparisons among groups were analyzed using the chi-square test.

The correlation between PD-1/CTLA-4 expression and clinical variables was assessed using Pearson correlation analysis for normally distributed data; a positive correlation coefficient indicated a positive association, while a negative coefficient indicated a negative association. Survival analysis was performed to evaluate the relationship between relevant variables and 28-day patient survival. All statistical tests were two-tailed, and a P-value < 0.05 was considered statistically significant.

Results

Correlations between PD-1/CTLA-4 expression and Pneumonia severity

Logistic regression analysis was performed to evaluate the associations between PD-1 and CTLA-4 expression on different T-cell subsets and clinical outcomes. As shown in Table 1, no significant associations were found between the expression of PD-1 or CTLA-4 on CD4 + T cells, CD8 + T cells, or regulatory T cells (Tregs) and the occurrence of severe CAP (SCAP) (CD4 + PD-1: P = 0.46; CD4 + CTLA-4: P = 0.30; CD8 + PD-1: P = 0.25; CD8 + CTLA-4: P = 0.10; Tregs PD-1: P = 0.89; Tregs CTLA-4: P = 0.57) or 28-day mortality (CD4 + PD-1: P = 0.44; CD4 + CTLA-4: P = 0.75; CD8 + PD-1: P = 0.36; CD8 + CTLA-4: P = 0.31; Tregs PD-1: P = 0.10; Tregs CTLA-4: P = 0.60).

Table 1.

Correlation of PD-1/CTLA-4 expression with SCAP and mortality.

	SCAP				Death
	Wald	P	OR	95% CI	Wald	P	OR	95% CI
NRS-2002 score	3.98	0.04	4.18	1.02–17.04	2.54	0.11	0.12	0.01–1.63
BMI(kg/m2)1	0.72	0.40	1.91	0.79–1.78	0.07	0.80	1.07	0.65–1.77
ALB(g/L)2	1.21	0.27	0.78	0.50–1.21	3.09	0.08	0.57	0.31–1.07
CD4+PD1	0.54	0.46	1.15	0.80–1.65	0.60	0.44	1.19	0.79–1.83
CD4+CTLA4	1.07	0.30	1.37	0.75–2.49	0.11	0.75	1.09	0.66–1.78
CD8+PD1	1.32	0.25	1.15	0.91–1.45	0.83	0.36	0.89	0.70–1.13
CD8+CTLA4	2.72	0.10	0.74	0.52–1.06	1.02	0.31	1.20	0.84–1.70
Treg-PD1	0.02	0.89	1.02	0.75–1.39	2.66	0.10	1.28	0.95–1.71
Treg-CTLA4	0.32	0.57	0.89	0.59–1.34	0.27	0.60	0.91	0.64–1.63

(1) BMI=body mass index, (2) ALB=Albumin.

When stratified by gender, no significant differences were observed in the expression levels of PD-1 or CTLA-4 on CD4 + T cells, CD8 + T cells, or Tregs between male and female patients (CD4+: t=-0.38, P = 0.71 for PD-1; t=-0.37, P = 0.71 for CTLA-4; CD8+: t = 1.37, P = 0.17 for PD-1; t = 0.48, P = 0.63 for CTLA-4; Tregs: t=-0.95, P = 0.35 for PD-1; t=-1.31, P = 0.19 for CTLA-4).

Correlation analysis between immune checkpoint expression and PSI scores revealed that only PD-1 and CTLA-4 expression on CD4 + T cells showed a significant positive correlation with PSI scores (PD-1: P = 0.01; CTLA-4: P < 0.01). No significant correlations were found between PSI scores and PD-1 or CTLA-4 expression on CD8 + T cells or Tregs (Table 2).

Table 2.

Correlation of PD-1 and CTLA-4 Expression with PSI Score, Albumin Level, BMI, and NRS-2002 Score.

	PSI score		ALB		BMI		NRS-2002 score
	Correlation coefficient	P	Correlation coefficient	P	Correlation coefficient	P	Correlation coefficient	P
CD4+ PD1	0.32	0.01	-0.67	< 0.01	0.05	0.72	0.86	< 0.01
CD4+CTLA4	0.38	< 0.01	-0.67	< 0.01	-0.01	0.98	0.80	< 0.01
CD8+ PD1	0.11	0.42	-0.34	0.01	0.18	0.17	0.36	< 0.01
CD8+CTLA4	0.19	0.14	-0.28	0.03	0.18	0.17	0.29	0.02
Treg-PD1	0.19	0.14	-0.36	0.01	0.02	0.89	0.47	< 0.01
Treg-CTLA4	0.21	0.12	-0.37	< 0.01	-0.05	0.72	0.48	< 0.01

Impact of nutritional status on community-acquired Pneumonia

Based on the inclusion criteria, 60 participants were enrolled and stratified into a malnutrition risk group (NRS-2002 score ≥ 3; n = 38) and a no-risk group (NRS-2002 score < 3; n = 22). The mean NRS-2002 score was 4.02 ± 1.21 in the malnutrition risk group and 1.54 ± 0.50 in the no-risk group. No significant differences were observed between the two groups regarding sex, age, or comorbidities at baseline, indicating successful group matching.

As shown in Table 3, in-hospital mortality was higher in the malnutrition risk group compared to the no-risk group (23.7% vs. 4.5%). The no-risk group also demonstrated better outcomes in terms of hospital-free days and a lower occurrence of severe SCAP. Although 28-day mortality was elevated in the high nutritional risk group (23.7% vs. 4.5%), this difference did not reach statistical significance (P = 0.06).

Table 3.

Comparison of clinical outcomes between nutritional risk groups.

	No-risk group	Malnutrition risk group	Value	P
Number	22	38	-	-
Age(years)	63.40 ± 19.19	69.57 ± 19.18	1.20	0.23
Male	10(45.5)	20(52.6)	0.29	0.59
Heart disease	6(27.3)	11(28.9)	0.02	0.89
Diabetes	7(31.8)	15(39.5)	0.35	0.55
CKD1	2(9.0)	8(21.1)	1.43	0.23
Mental disorder	4(18.1)	10(26.3)	0.51	0.47
NRS-2002 score	1.54 ± 0.50	4.02 ± 1.21	9.07	< 0.01
CRP(mg/L)2	47.60(13.92,104.50)	33.00(11.00,88.00)	367.50	0.44
PCT(ng/mL)3	2.80(1.22,4.32)	8.80(3.20,18.92)	662	< 0.01
PSI score	3.50(2.00,4.00)	3.00(2.22,4.00)	408.50	0.88
Length of hospitalization(days)	11(8.00,16.50)	15.00(13.50,20.50)	450	< 0.01
SCAP	1(4.5)	13(34.2)	10.6	< 0.01
Death	1(4.5)	9(23.7)	3.67	0.06

(1) CKD=chronic kidney disease; (2) CRP = C-reactive protein; (3) PCT=Procalcitonin.

Logistic regression models were constructed to assess the associations between nutritional parameters and clinical outcomes. After incorporating NRS-2002 score, body mass index (BMI), and serum albumin (ALB) concentration into the models, the NRS-2002 score was found to be significantly associated with the occurrence of SCAP. However, none of these nutritional factors was significantly related to the risk of 28-day mortality (Table 1).

Distribution of PD-1/CTLA-4 expression in patients with different nutritional statuses

The expression levels of PD-1 and CTLA-4 on various T-cell subsets were compared between the malnutrition risk group and the no-risk group. As shown in Fig. 3, the malnutrition risk group (Group B) exhibited significantly higher levels of PD-1 and CTLA-4 on CD4 + T cells, CD8 + T cells, and regulatory T cells (Tregs) compared to the no-risk group (Group A).(Fig. 3).

Fig. 3.

PD-1 and CTLA-4 expression in different nutritional status groups. (A) Gating strategy for Tregs identification. (B) Comparison of PD-1 and CTLA-4 expression between the no-risk group (A) and malnutrition risk group (B). A = no-risk group; B=malnutrition risk group.

Regarding nutritional parameters, PD-1 and CTLA-4 expression across all three T-cell subsets (CD4+, CD8+, and Tregs) demonstrated consistent associations: they were negatively correlated with serum albumin levels and positively correlated with NRS-2002 scores. However, no significant correlations were found between immune checkpoint expression and body mass index (BMI) for any of the T-cell subsets examined. (Table 2)

Discussion

Given the established association between nutritional status and the prognosis and mortality of various diseases, including cardiovascular disease and cancer, an increasing number of studies have emphasized the importance of nutritional status screening in clinical practice^1–3,19,20. Yanagita et al.²¹ utilized the Geriatric Nutritional Risk Index (GNRI) to investigate the relationship between nutritional status and the risk of aspiration pneumonia, reporting that GNRI scores were significantly higher in the survivor group than in the non-survivor group. In the present study, we employed the NRS-2002 score to assess nutritional status in patients with CAP and obtained comparable findings.Our results demonstrated that patients in the no-risk group had significantly more hospital-free days (t = 450, P < 0.01) and a lower incidence of SCAP (χ²=10.6, P < 0.01) compared to those in the malnutrition risk group. Furthermore, logistic regression analysis identified nutritional status, as indicated by the NRS-2002 score, as an independent risk factor for SCAP development. These findings collectively support the conclusion that the NRS-2002 score is a valuable predictor of prognosis in patients with CAP.

Although both Iddir et al. and Yanagita et al. emphasized the prognostic value of ALB levels in pneumonia patients, we did not observe significant differences in ALB concentration or BMI between the two nutritional risk groups in our study. This discrepancy may be attributed to differences in study populations or the specific nutritional assessment tools employed. Nevertheless, numerous studies have consistently demonstrated that ALB concentration is associated with infectious disease risk^22–24. Although we did not clarify whether SCAP itself could exacerbate nutritional status, accumulating evidence suggests that severe infections may lead to malnutrition through increased consumption of carbohydrates, fats, and proteins^22–24. Further studies are warranted to elucidate this bidirectional relationship.

In the context of sepsis, studies have demonstrated that CD4 + and CD8 + T cells and Tregs are decreased, while PD-1 and CTLA-4 expression is upregulated^9–11. Gong et al.¹² investigated PD-1 and CTLA-4 expression specifically in patients with CAP and reported that the percentages of Tregs expressing PD-1 and CTLA-4 were significantly higher than those in healthy controls. However, no significant differences were observed between CAP patients and healthy individuals for CD4 + or CD8 + T cells¹². In the present study, logistic regression analysis revealed no significant independent associations between PD-1 or CTLA-4 expression on CD4 + T cells, CD8 + T cells, or Tregs and the presence of SCAP or 28-day mortality. However, correlation analysis demonstrated that PD-1 and CTLA-4 expression on CD4 + T cells was modestly but significantly correlated with higher PSI scores, suggesting a potential link between immune checkpoint expression on this specific T-cell subset and disease severity.It is important to note that we did not adjust for multiple comparisons in our exploratory analyses. Therefore, the significant findings—particularly the correlations with PSI scores—should be considered hypothesis-generating and warrant validation in a larger, independent cohort.

Although malnutrition is known to impair immune function, few studies have elucidated the underlying molecular mechanisms. In the present study, we investigated this process in patients with CAP and demonstrated that PD-1 and CTLA-4 expression on T cells was significantly higher in the malnutrition risk group compared to the no-risk group. Furthermore, the percentages of PD-1 and CTLA-4-expressing cells were positively correlated with NRS-2002 scores, indicating that poorer nutritional status is associated with elevated expression of these immune checkpoint molecules. In our study, albumin levels were inversely correlated with PD-1 and CTLA-4 expression, whereas no significant correlation was observed with BMI. Patients with higher NRS-2002 scores or lower albumin levels exhibited elevated PD-1 and CTLA-4 expression. These findings suggest that CAP patients with malnutrition or hypoalbuminemia may have an increased risk of immunosuppression mediated by immune checkpoint pathways.Consistent with our observations, Tang et al.²⁵ reported that the NRS-2002 score can predict the efficacy and prognosis of immunotherapy in patients with solid tumors receiving immune checkpoint inhibitor therapy. Given the difficulty of assessing immunosuppression status using precise and efficient methods in clinical practice, our findings propose that the NRS-2002 score may serve as a practical indicator of immunosuppression risk in patients with CAP. This simple screening tool could help clinicians promptly identify patients at risk for immune dysfunction and may provide new insights for developing immunosuppression-targeted therapies in severe pneumonia.

This study has several limitations. First, its single-center, exploratory design and small sample size may have introduced sampling bias; moreover, the absence of adjustment for multiple comparisons necessitates cautious interpretation and external validation. Second, the cross-sectional design prevented long-term follow-up, limiting insights into dynamic changes in PD-1/CTLA-4 expression. Third, we did not investigate anti-PD-1/CTLA-4 therapy or whether nutritional improvement affects immune checkpoint levels.

Conclusion

In conclusion, this study suggests that malnutrition which was assessed by the NRS-2002, is associated with longer hospital stay, higher incidence of SCAP, and increased expression of PD-1 and CTLA-4. Higher levels of expression of PD-1 and CTLA-4 on CD4 + T cells appeared to correlate with higher PSI scores. These findings indicate that nutritional status influences the development of immunosuppression via pathways involving PD-1 and CTLA-4, which are also associated with length of hospital stay and incidence of SCAP in patients with CAP.

Author contributions

Chenguang Zhang was responsible for data collection, literature review, and drafting the manuscript. Mingqiang Zhang and Xiangdong Mu performed the experiments and measured the expression levels of PD-1 and CTLA-4 on various T-cell subsets. Sheng Wu and Xuyan Chen contributed to manuscript writing and critical revision. Hao Yang and He Yin participated in data collection and figure generation. Jingjing Li was involved in the collection, preservation, and transportation of blood samples. All authors reviewed and approved the final manuscript.

Funding

This research was supported by the Special Program for Major Epidemic Prevention and Control in Beijing (XKB2022B101), the National Natural Science Foundation of China (Grant No. 81900021).

Data availability

The datasets generated and/or analyzed during the current study are not publicly available due to their intended use in ongoing and future research. However, they may be made available by the corresponding author upon reasonable request.

Declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

This study was conducted in accordance with the International Ethical Guidelines for Biomedical Research Involving Human Subjects (2002) and the Declaration of Helsinki (2013). The research protocol was approved by the Ethics Committee of Beijing Tsinghua Changgung Hospital (Approval No. 18190-0-02; Date: September 7, 2021). All patients provided written informed consent prior to participation and agreed to the use of their samples and data for research purposes.