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Research Article

Cytokines and Inflammatory Gene Polymorphisms Associated With Nosocomial Pulmonary Infection After Spontaneous Intracerebral Hemorrhage

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DOI:

10.3791/70761

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August 4th, 2026

In This Article

Summary

This retrospective study presents a reproducible workflow for early post-admission blood collection, measurement of serum cytokines and Toll-like receptors, genotyping of inflammatory gene polymorphisms, and infection-risk assessment in patients with spontaneous intracerebral hemorrhage.

Abstract

Nosocomial pulmonary infection is a frequent complication after spontaneous intracerebral hemorrhage and may worsen neurological recovery, prolong hospitalization, and increase clinical burden. This retrospective clinical-laboratory study presents a reproducible workflow for evaluating inflammatory biomarker and host immune-genetic profiles associated with nosocomial pulmonary infection after primary spontaneous intracerebral hemorrhage. Patients are classified according to whether nosocomial pulmonary infection occurs after admission. Peripheral venous blood is collected in the early post-admission period under standardized pre-analytical conditions. Serum is separated, aliquoted, and stored for enzyme-linked immunosorbent assay measurement of IL-1β, IL-6, IL-10, IL-17, IFN-γ, TNF-α, TLR2, TLR4, and TLR9. In parallel, genomic DNA is extracted from anticoagulated whole blood and used for polymerase chain reaction-restriction fragment length polymorphism genotyping of selected cytokine- and Toll-like receptor-related loci. The workflow also includes quality-control procedures for sample handling, duplicate ELISA measurements, DNA purity assessment, genotype calling, and repeat genotyping. Statistical analysis includes between-group comparison of clinical characteristics and biomarker levels, Hardy-Weinberg equilibrium testing, logistic regression analysis for genotype and allele associations, adjustment for relevant clinical covariates, and false-discovery-rate correction for multiple genetic comparisons. This combined clinical, inflammatory, and immune-genetic workflow may help characterize infection-risk profiles after spontaneous intracerebral hemorrhage, although prospective multicenter validation is still required before routine clinical application.

Introduction

Spontaneous intracerebral hemorrhage (ICH) is a severe subtype of stroke caused by non-traumatic rupture of cerebral vessels and remains a major source of neurological death and disability. Clinically, ICH is commonly classified as primary or secondary. Primary ICH accounts for most cases and is mainly related to hypertensive arteriopathy or cerebral amyloid angiopathy1. By contrast, secondary ICH is associated with structural or hematologic causes, including aneurysms, arteriovenous malformations, Moyamoya disease, and coagulation disorders. Although ICH accounts for a smaller proportion of all stroke events than ischemic stroke, it carries disproportionately high short-term mortality and long-term functional burden2,3,4,5.

Among the major in-hospital complications after ICH, nosocomial pulmonary infection is particularly frequent and clinically consequential. Previous studies have shown that pulmonary infection can occur in a substantial proportion of hospitalized patients after stroke or intracerebral hemorrhage and is associated with longer hospitalization, greater medical burden, poorer neurological recovery, and increased mortality6,7,8. The clinical importance of this complication extends beyond respiratory management alone. Reduced consciousness, impaired swallowing and cough reflexes, immobilization, mechanical airway support, and invasive drainage procedures may all increase the risk of infection during the acute phase after ICH. At the same time, pulmonary infection may further worsen systemic inflammation, impair oxygen delivery, and complicate neurocritical care, thereby amplifying secondary injury processes.

This relationship is biologically plausible because ICH is not only a focal cerebrovascular event but also a trigger of systemic immune dysregulation. Acute cerebral hemorrhage can activate inflammatory cascades, alter innate immune signaling, and disrupt the balance between neuroinflammation and peripheral host defense. In this context, some patients may become more susceptible to hospital-acquired infections even under similar clinical management. Therefore, pulmonary infection after ICH should not be viewed solely as a consequence of bedside exposure or supportive care; it may also reflect differences in host inflammatory activation and immune responsiveness.

Despite the clinical relevance of this complication, practical approaches for early risk stratification remain limited9. Existing clinical risk-stratification approaches for post-ICH pulmonary infection generally rely on bedside and admission-related variables, such as neurological severity, age, swallowing impairment, comorbidities, invasive procedures, and length of device exposure. These tools are clinically useful because they can be applied rapidly in emergency, intensive care, or neurocritical care settings. However, clinical variables alone may not fully explain why patients with comparable neurological severity and similar care exposure show different infection outcomes. Inflammatory biomarkers and host immune-genetic factors may therefore provide additional information about biological susceptibility, especially during the early post-admission period when preventive surveillance and respiratory management decisions are being made.

Cytokines are central mediators of immune and inflammatory responses, and Toll-like receptor (TLR) pathways play key roles in pathogen recognition and innate immune activation. Serum cytokine and TLR protein measurements can provide a snapshot of early systemic inflammatory activation, whereas selected immune-gene polymorphisms may reflect more stable host differences in cytokine production, receptor signaling, or inflammatory regulation. Compared with clinical assessment alone, a combined biomarker and polymorphism workflow can capture both the current inflammatory state and each patient's underlying immune response. This approach is not intended to replace bedside clinical assessment, but to complement it by adding laboratory and host-genetic information that may help identify patients who warrant closer infection surveillance after spontaneous ICH.

On this basis, we hypothesized that patients with spontaneous ICH who develop nosocomial pulmonary infection would exhibit a distinct inflammatory profile together with a different distribution of selected immune-related genetic polymorphisms compared with patients who remain free of infection. To test this hypothesis, the present retrospective clinical-laboratory study analyzed early post-admission serum cytokines, serum protein levels of TLR2, TLR4, and TLR9, and selected inflammatory gene polymorphisms in patients with primary spontaneous ICH. The workflow uses peripheral blood collected during acute hospitalization, ELISA-based protein quantification, PCR-RFLP-based genotyping, and statistical comparison between patients with and without nosocomial pulmonary infection. The aim was to provide a reproducible framework for characterizing inflammatory and host-genetic profiles associated with infection risk, thereby supporting earlier recognition of high-risk patients in the acute hospital setting.

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Protocol

This study was approved by the Ethics Committee of the Affiliated Hospital of Jiaxing University, The First Hospital of Jiaxing, Jiaxing, Zhejiang, China (Approval No. 2025-LP-599). All procedures involving human participants were conducted in accordance with institutional requirements and the principles of the Declaration of Helsinki. Written informed consent for blood collection and data use was obtained from all participants and/or their legally authorized representatives before sample collection.

All commercial kits, reagents, consumables, instruments, software, manufacturers, catalog numbers, and key operating specifications used in this workflow are listed in the Table of Materials.

Study scope, eligibility, and patient grouping

This study was conducted as a single-center retrospective clinical-laboratory cohort analysis of patients with primary spontaneous intracerebral hemorrhage (ICH) admitted to the Emergency and Critical Care Center or Intensive Care Unit of the Affiliated Hospital of Jiaxing University, The First Hospital of Jiaxing, Jiaxing, Zhejiang, China, between May 2019 and September 2024. The diagnosis of ICH was confirmed by cranial computed tomography or magnetic resonance imaging in accordance with the Chinese Guidelines for Diagnosis and Treatment of Cerebral Hemorrhage (2019)10.

Patients were eligible if they had imaging-confirmed primary spontaneous ICH, were admitted within 3 days of symptom onset, and had complete key clinical variables, along with available peripheral blood samples for measurement of inflammatory biomarkers and genetic analysis. Patients were excluded if they had traumatic intracranial hemorrhage, secondary ICH, pulmonary infection present before admission or within 48 h after admission, discharge against medical advice, or death within 48 h after admission, a history of malignancy or autoimmune disease, or incomplete key clinical, laboratory, or genotyping records. After screening, 360 patients met the eligibility criteria and were included in the final analysis. Among them, 180 patients developed nosocomial pulmonary infection during hospitalization, and 180 patients did not. Patients were assigned to the pulmonary infection group or the no pulmonary infection group based on whether a nosocomial pulmonary infection occurred after admission.

Before final grouping, imaging diagnosis, admission time, infection timing, blood-sample availability, and completeness of clinical and laboratory records were checked. This step was used to reduce misclassification and ensure that all included cases had complete data for clinical comparison, measurement of inflammatory biomarkers, and genotyping.

Definition of nosocomial pulmonary infection

Nosocomial pulmonary infection was defined on the basis of radiologic evidence combined with clinical criteria11. Radiologic confirmation required a new or progressive infiltrative, consolidative, or ground-glass lesion on chest radiography or computed tomography. In addition, at least two of the following criteria had to be present: body temperature > 38 °C, purulent respiratory secretions, or abnormal peripheral white blood cell count with WBC < 4 × 109/L or > 10 × 109/L.

Pulmonary infection present before admission or diagnosed within the first 48 h after admission was not classified as nosocomial pulmonary infection. Infection classification was verified using radiologic reports, body temperature records, documentation of respiratory secretions, peripheral blood count results, and clinical diagnosis records.

Biosafety and waste disposal

Human blood, serum, and blood-derived DNA were handled under standard biosafety level 2 precautions. Laboratory personnel wore gloves, laboratory coats, masks, and protective eyewear during blood handling, serum aliquoting, ELISA testing, DNA extraction, PCR preparation, gel electrophoresis, restriction digestion, and UV visualization. Blood tubes were checked for leakage or breakage before processing. Centrifugation was performed using capped tubes or, where available, sealed centrifuge buckets.

Sharps were discarded immediately into approved sharps containers. Blood-contaminated tubes, pipette tips, gloves, ELISA plates, and other disposable consumables were discarded as biological laboratory waste. Liquid biological waste was disinfected in accordance with institutional procedures before disposal. Agarose gels, polyacrylamide gels, staining reagents, and electrophoresis-related materials were discarded in accordance with institutional chemical and laboratory waste requirements.

PCR reagent preparation, DNA template addition, amplified product handling, restriction digestion, and gel electrophoresis were separated as far as possible to reduce contamination. Aerosol-resistant pipette tips were used for PCR and DNA handling. UV visualization was performed only with a protective shield or gel documentation system, and direct eye or skin exposure to UV light was avoided.

Peripheral blood collection and sample processing

To reduce pre-analytical variation, 10 mL of peripheral venous blood was collected at 08:00 on the morning after admission, after an overnight fast of at least 12 h. 5 mL of blood was drawn into a plain vacuum tube for serum preparation, and the remaining 5 mL was drawn into a heparinized tube for genomic DNA extraction.

Before processing, each tube was checked for patient identifier, collection time, tube type, blood volume, leakage, visible clotting, and gross hemolysis. Samples with incorrect labeling, insufficient blood volume, tube leakage, or visible clotting in the anticoagulated tube were excluded from downstream analysis. Blood in the plain tube was allowed to clot at room temperature for 60 min, then centrifuged at 1,500 × g for 10 min at 4 °C. The serum supernatant was transferred into sterile low-protein-binding polypropylene tubes without disturbing the cell layer, aliquoted into 0.5 mL fractions, and stored at −80 °C until analysis.

Samples showing visible moderate or severe hemolysis were excluded from ELISA-based quantification. Mildly hemolyzed samples were recorded and were not used for the primary cytokine analysis. Samples with visible turbidity, obvious lipemia, insufficient residual volume, or repeated freeze-thaw exposure were flagged before testing. No serum aliquot underwent more than one freeze-thaw cycle before analysis.

Cytokine quantification by ELISA

Serum concentrations of IL-1β, IL-6, IL-10, IL-17, IFN-γ, and TNF-α were measured using commercially available human sandwich ELISA kits validated for serum samples. Serum aliquots were thawed, gently mixed, and inspected for hemolysis, turbidity, lipemia, insufficient volume, and freeze-thaw history before loading.

Standards, blank wells, and serum samples were loaded in duplicate. Standard curves were generated on each plate using serial dilutions of standard concentrations and a blank control, according to the kit instructions. Optical density was measured at 450 nm, with a reference correction at 570 nm, using a calibrated microplate reader. Concentrations were calculated by four-parameter logistic curve fitting.

Assay results were accepted only when the standard curve showed an appropriate concentration-response pattern, blank wells showed low background, and the duplicate sample coefficient of variation was ≤ 10%. Samples with duplicate CV > 10% were re-assayed from the original serum aliquot when sufficient volume was available. Samples outside the reliable standard-curve range were diluted or repeated according to the kit instructions. Plates showing inconsistent standards, excessive background, or obvious edge effects were repeated.

The lower analytical detection limits used for data acceptance were 2.0 pg/mL for IL-1β, 1.5 pg/mL for IL-6, 2.0 pg/mL for IL-10, 3.0 pg/mL for IL-17, 4.0 pg/mL for IFN-γ, and 2.5 pg/mL for TNF-α. Final cytokine values were checked against sample identifiers, plate maps, duplicate-readout records, and sample-quality notes before statistical analysis.

Quantification of serum TLR2, TLR4, and TLR9 by ELISA

Serum TLR2, TLR4, and TLR9 protein levels were measured using commercially available human ELISA kits validated for serum specimens. Serum samples were thawed, mixed gently, and inspected using the same sample-quality criteria applied to cytokine measurement.

Standards, blank wells, and serum samples were analyzed in duplicate. Plates were read at 450 nm with reference correction at 570 nm, and concentrations were calculated using four-parameter logistic regression. Results were accepted when the standard curve was valid, blank wells were within the expected background range, and the duplicate CV was ≤ 10%. Samples exceeding this duplicate CV threshold were retested when sufficient samples remained.

The lower analytical detection limits used for result acceptance were 0.10 ng/mL for TLR2, 0.12 ng/mL for TLR4, and 0.15 ng/mL for TLR9. Final TLR2, TLR4, and TLR9 values were checked against sample identifiers, plate maps, duplicate-readout records, and sample-quality notes before statistical analysis.

Genomic DNA extraction

Genomic DNA was extracted from heparin-anticoagulated whole blood using a silica column-based blood genomic DNA extraction kit. Before extraction, anticoagulated blood samples were checked for correct labeling, sufficient volume, visible clotting, leakage, and storage condition.

DNA purity and concentration were assessed by spectrophotometry. Only samples with an A260/A280 ratio between 1.80 and 2.00 were accepted for downstream PCR amplification. Samples outside this range were remeasured after gentle mixing. If the abnormal purity ratio persisted, DNA extraction was repeated when sufficient whole blood remained.

DNA was diluted with nuclease-free water to a working concentration of 50 ng/µL and stored at -20 °C until PCR amplification. Before PCR setup, each DNA sample was checked for concentration, purity, sample identifier, and freeze-thaw history.

PCR-RFLP genotyping and genotype calling

Genotyping was performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) for IL-1B +3954 C/T, IL-10-1082 G/A, IL-10-819 T/C, TNF-α-308 G/A, TLR2-196 to-174 ins/del, TLR4 Asp299Gly, TLR4 Thr399Ile, TLR9 rs187084, IFN-γ +874 A/T, and IFN-γ +2108 A/G. Locus-specific primer sequences, expected amplicon sizes, restriction enzymes, and genotype-specific digestion patterns are provided in Supplementary Table 1.

PCR amplification was carried out in a final reaction volume of 25 µL containing 2.5 µL of 10 × buffer, 2.0 µL of dNTP mixture at 2.5 mM each, 1.0 µL of forward primer at 10 µM, 1.0 µL of reverse primer at 10 µM, 0.25 µL of Taq DNA polymerase at 5 U/µL, 2.0 µL of genomic DNA at 50 ng/µL, and 16.25 µL of nuclease-free water. PCR master mix was prepared in a clean pre-PCR area, and the DNA template was added last. A no-template negative control was included in each PCR run.

The thermal profile consisted of an initial denaturation at 95 °C for 5 min, followed by 35 cycles of denaturation at 95 °C for 30 s, annealing at 58–62 °C for 30 s depending on the primer pair, and extension at 72 °C for 30 s, with a final extension at 72 °C for 7 min. PCR products were first confirmed on 1.5% agarose gel before restriction digestion.

PCR amplification was accepted only when the expected amplicon band was visible, and the no-template control showed no amplification. Reactions showing weak bands, nonspecific amplification, primer-dimer interference, or contamination in the negative control were repeated from the original DNA template.

PCR products were digested with the corresponding restriction endonuclease at 37 °C for 3 h in a total digestion volume of 15 µL according to the manufacturer's instructions. Digested fragments were resolved on 2.5% agarose gel for most loci. The TLR2-196 to -174 ins/del locus was resolved on 8% polyacrylamide gel to improve fragment discrimination.

Restriction digestion was accepted only when fragment patterns matched the expected genotype-specific digestion profile. Reactions showing incomplete digestion, smeared bands, unexpected fragment sizes, or unclear separation were repeated. Bands were visualized under ultraviolet illumination after nucleic-acid staining. Gel images were saved with the sample identifier, locus name, run date, and gel number.

Genotype assignment was performed independently by two blinded laboratory investigators. Discordant or ambiguous genotype calls were reviewed using the original gel image and repeated from PCR amplification when necessary. Ten percent of randomly selected samples were re-genotyped for quality control, and the concordance rate was 99.2%. Final genotype data were entered into the analysis dataset only after sample identifiers, locus names, genotype calls, and quality-control records had been checked.

Statistical analysis

Statistical analyses were performed using an appropriate statistical analysis software. The clinical, ELISA, and genotype datasets were merged using de-identified patient codes. Patient codes were checked for duplication, mismatch, and missing values before analysis. A complete-case strategy was used because all included patients had available key clinical, inflammatory, and genotyping data.

In an appropriate statistical analysis software, pulmonary infection status was coded as the grouping variable, with the no pulmonary infection group used as the reference category. Continuous variables were first tested for normality using the Shapiro-Wilk test. Normally distributed continuous variables were expressed as mean ± standard deviation and compared using the independent-samples Student's t test. Non-normally distributed continuous variables were reported as medians with interquartile ranges and compared using the Mann-Whitney U test. Categorical variables were expressed as counts and percentages and compared using the chi-square test or Fisher's exact test, as appropriate.

Genotype distributions in the no pulmonary infection group were evaluated for Hardy-Weinberg equilibrium before association analysis. Genotype and allele frequencies were summarized as n (%). Odds ratios and 95% confidence intervals for pulmonary infection risk were estimated using multivariable logistic regression models. Pulmonary infection status was entered as the dependent variable. Genotype, allele, or biomarker variables were entered as independent variables, as specified for each analysis.

Age and sex were entered into the primary model a priori. BMI, chronic obstructive pulmonary disease, cardiac disease, cerebrospinal fluid leakage, indwelling time of the drain, and admission Glasgow Coma Scale category were entered simultaneously into the fully adjusted model because these variables were clinically relevant or showed baseline imbalance between groups. Multicollinearity was assessed using variance inflation factors (VIFs), and VIFs <5.0 were considered acceptable.

Because multiple polymorphisms were tested, Benjamini-Hochberg false discovery rate correction was applied to the genetic association analyses12. P values from the genetic association tests were ranked from smallest to largest, and corrected significance was determined according to the Benjamini-Hochberg procedure. All tests were two-sided, and P <0.05 was considered statistically significant unless otherwise specified after multiple-comparison adjustment.

Final outputs were checked against the source dataset, ELISA quality-control records, genotype-calling records, and table values before manuscript preparation. Results were interpreted as associations rather than causal effects because the study used a retrospective observational design.

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Results

Clinical indicators

Baseline clinical characteristics are summarized in Table 1. A total of 360 patients with spontaneous intracerebral hemorrhage were included in the final analysis, comprising 180 patients who developed nosocomial pulmonary infection during hospitalization and 180 patients who did not. There were no significant between-group differences in age (62.4 years ± 6.8 years vs 63.6 years ± 7.0 years, P > 0.05), sex distribution (142/180...

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Discussion

Spontaneous intracerebral hemorrhage (ICH) remains one of the most severe stroke subtypes and continues to impose substantial early mortality and long-term disability burdens13. In clinical practice, patients with ICH are especially vulnerable to in-hospital complications because neurological injury can weaken airway protection, reduce cough effectiveness, restrict mobility, and increase exposure to invasive supportive procedures. Among these complications, nosocomial pulmonary infection is partic...

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Disclosures

The authors declare that they have no competing financial interests or other conflicts of interest related to this work.

Acknowledgements

The authors thank the clinical staff involved in patient care and the individuals who assisted with literature retrieval and data organization. This study was supported by the Jiaxing City Health Science and Technology Planning Project (Grant No. JWKJ-25005).

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Materials

List of materials used in this article
NameCompanyCatalog NumberComments
Human TNF-α ELISA KitInvitrogen / Thermo Fisher ScientificKHC3011ELISA kit for quantitative measurement of human TNF-α in serum.
Human TLR2 / Toll-like Receptor 2 ELISA KitSigma-Aldrich / MerckRAB0744-1KT96-well ELISA kit for measurement of human TLR2 in serum or plasma samples.
Human TLR4 ELISA Kit, colorimetricNovus Biologicals / Bio-TechneNBP3-11807Colorimetric sandwich ELISA kit for measurement of human TLR4 in serum, plasma, or other biological fluids.
Human TLR9 ELISA Kit, colorimetricNovus Biologicals / Bio-TechneNBP2-76574Colorimetric ELISA kit for measurement of human TLR9 in serum samples.
Absorbance microplate readerAgilent BioTek800 TSMicroplate reader for ELISA optical-density measurement at 450 nm with reference correction at 570 nm.
QIAamp DNA Blood Mini KitQIAGEN51104Silica membrane-based kit for genomic DNA extraction from anticoagulated whole blood.
NanoDrop One Microvolume UV-Vis SpectrophotometerThermo ScientificND-ONE-WMicrovolume spectrophotometer for DNA concentration and A260/A280 purity assessment.
SimpliAmp Thermal CyclerApplied Biosystems / Thermo Fisher ScientificA24811Thermal cycler used for endpoint PCR amplification in PCR-RFLP genotyping.
PCR Master Mix, 2XThermo ScientificK0171Premixed PCR reagent containing Taq DNA polymerase, dNTPs, MgCl2, and reaction buffer; used for conventional PCR amplification.
Recombinant Taq DNA PolymeraseThermo ScientificEP0401Alternative enzyme source for locus-specific PCR reactions when separate PCR components are used instead of 2X master mix.
Nuclease-free waterThermo ScientificR0581Molecular-biology-grade water used for PCR setup, DNA dilution, and no-template controls.
Custom DNA primersSangon BiotechCustom synthesisLocus-specific primers for PCR-RFLP genotyping; primer sequences are listed in Supplementary Table S1.
Restriction endonucleases for PCR-RFLPThermo Scientific / New England BiolabsLocus-specific enzymes listed in Supplementary Table S1Restriction enzymes used for genotype-specific digestion of PCR products. The enzyme selected for each locus should match the digestion pattern listed in Supplementary Table S1.
Agarose I, molecular biology gradeThermo Scientific17850Agarose for preparation of 1.5% and 2.5% gels used to confirm PCR products and resolve most RFLP fragments.
GeneRuler 50 bp DNA LadderThermo ScientificSM0371DNA size marker for PCR amplicons and RFLP fragment-size estimation.
SYBR Safe DNA Gel StainInvitrogen / Thermo Fisher ScientificS33102Nucleic-acid gel stain for visualization of DNA in agarose or acrylamide gels; used as a reduced-hazard alternative to ethidium bromide.
Horizontal agarose gel electrophoresis systemBio-RadMini-Sub Cell GT system / 1704360 baseElectrophoresis system for agarose gel separation of PCR and RFLP products.
Vertical PAGE electrophoresis systemBio-RadMini-PROTEAN Tetra Cell / 1658001Vertical electrophoresis system for 8% polyacrylamide gel separation when higher-resolution fragment discrimination is required.
Gel documentation system with UV or blue-light transilluminationBio-Rad / equivalent laboratory systemGel Doc XR+ or equivalentImaging system for documenting stained DNA bands after gel electrophoresis. Use UV shielding or blue-light mode where available.
Refrigerated centrifugeEppendorf / equivalent laboratory centrifuge5424 R or equivalentRefrigerated centrifuge used for serum separation at 1,500 × g and 4 °C.
−80 °C ultra-low temperature freezerThermo Scientific / equivalent laboratory freezerForma 900 Series or equivalentStorage of serum aliquots before ELISA analysis.
IBM SPSS StatisticsIBMVersion 25.0Statistical software used for descriptive statistics, normality testing, group comparisons, logistic regression, and model-output export.
Spreadsheet softwareMicrosoftExcel for Microsoft 365Used for data checking, plate-map organization, duplicate-value review, and preparation of merged analysis files before SPSS analysis.

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Cytokine BiomarkersToll-Like ReceptorsELISA MeasurementGenotype AssociationDNA ExtractionLogistic RegressionImmune Genetic Profiles