Association of rs1544410, rs1800796, and rs3917924 Polymorphisms with Malnutrition and Surgical Site Infection Susceptibility in Patients Undergoing Gastrointestinal Surgery

Abstract

Genetic variations play a pivotal role in modulating an individual’s susceptibility to complex conditions such as malnutrition and surgical site infection (SSI) in patients undergoing gastrointestinal surgery. This study aimed to investigate the association of three single nucleotide polymorphisms (SNPs)—rs1544410 (C/T), rs1800796 (C/G), and rs3917924 (G/A)—with malnutrition and SSI status after gastrointestinal surgery, and to verify their conformity to the Hardy-Weinberg equilibrium (HWE). A total of 169 participants were stratified into malnutrition (n = 26) vs. non-malnutrition (n = 143) groups and infection (n = 52) vs. non-infection (n = 117) groups. Genotyping was performed using Kompetitive Allele-Specific Polymerase Chain Reaction (KASP). HWE tests, univariate analysis, and multivariate logistic regression were employed to evaluate genotype/allele distributions and their associations with the studied conditions. In the malnutrition analysis, the rs1800796 SNP showed a significant difference in genotype distribution between groups (χ² = 8.179, P = 0.017). However, this nominal statistical significance was lost following Bonferroni correction. For SSI susceptibility, the rs1544410 SNP demonstrated a significant association with genotype distribution (χ² = 6.242, P = 0.012) and allele frequency (χ² = 5.590, P = 0.018), with the C allele conferring a higher infection risk (odds ratio [OR] = 3.426, 95% confidence interval [CI]: 1.162–10.06), but rs1544410 did not reach statistical significance after Bonferroni correction. In exploratory multivariate analyses, the CC genotype of rs1544410 retained preliminary predictive value for SSI after adjustment (OR = 3.241, 95% CI: 1.050–10.000, P = 0.041). All SNPs complied with HWE except for rs1800796 in the non-malnutrition group (P < 0.001) and both rs1800796 in infection (P = 0.019) and non-infection (P = 0.019) groups. Our exploratory multivariate logistic regression suggested that the CC genotype of rs1544410 might correlate with postoperative SSI risk after adjusting for clinical confounders, although this SNP lost statistical significance after Bonferroni multiple testing correction, and further research is required to validate the correlation between rs1800796 and malnutrition risk.

Keywords

single nucleotide polymorphism / malnutrition / surgical site infection / gastrointestinal surgery / susceptibility

Introduction

Malnutrition and infection represent major global health challenges, particularly in patients undergoing gastrointestinal surgery, as these complications arise from intertwined environmental and genetic risk factors[1,2]. Both malnutrition and surgical site infection (SSI) contribute to impaired wound recovery, surgical failure and even mortality, and their onset is modulated by genetic backgrounds[3,4]. Single nucleotide polymorphisms (SNPs), the most common form of genetic variation in the human genome, have been shown to influence disease susceptibility by altering gene expression, protein function, or signaling pathways[5,6]. To date, there are few studies that have explored the association of SNPs with malnutrition and SSI in patients undergoing gastrointestinal surgery. Understanding the genetic determinants of malnutrition and SSI after gastrointestinal surgery could facilitate the development of targeted prevention and intervention strategies.

Three genes —Vitamin D Receptor (VDR), Granulocyte Colony-Stimulating Factor (GCSF), and Interleukin 6 (IL-6)—have been previously implicated in pathways related to immune function, metabolism, and nutrient absorption, making them promising candidates for association studies[7–9]. For instance, VDR rs1544410 is located in a gene involved in ion transport, related to the development of several inflammatory disorders[10]. IL-6 rs1800796 is associated with genes regulating inflammatory responses whose C allele has been associated with an increased IL-6 synthetic response[11]. GCSF rs3917924 has been linked to metabolic enzymes that influence energy metabolism and nutrient utilization[12]. Given the necessity to understand the importance of these genes for malnutrition and SSI to inform preventive interventions, these three SNPs have been considered together.

The lack of nutrition absorption impairs the immune function in gastrointestinal surgery. Meanwhile, surgical trauma itself elevates the risk of both malnutrition and postoperative infectious complications[13]. Statistically, SSI and malnutrition were usually responsible for the deaths after gastrointestinal surgery[14]. In addition, routine parenteral nutrition yields limited efficacy in lowering SSI rates for gastrointestinal surgical patients, and immunonutrition confers no additional protective benefits[15,16]. Thus, novel and unconventional approaches are needed to explore and effectively manage these two complications. SSI prevention has been most effective when multiple risk factors are addressed, including gene characteristics and comprehensive treatment, because malnutrition may also be contributed by SSI[17,18]. SSI and malnutrition reciprocally worsen clinical outcomes of patients after gastrointestinal surgery, and complicate each other. However, few studies have investigated whether SNPs exert effects on both SSI and malnutrition.

Hardy-Weinberg equilibrium (HWE) is a fundamental principle in population genetics, dictating that genotype frequencies remain stable in the absence of evolutionary pressures[19]. Deviations from HWE may indicate population stratification, selection bias, or genotyping errors, and thus must be evaluated to validate study results[20]. Kompetitive Allele-Specific Polymerase Chain Reaction (KASP) is a robust and cost-effective genotyping method widely used in genetic association studies, offering high accuracy and reproducibility[21].

In this study, we hypothesized that rs1544410, rs1800796, and rs3917924 polymorphisms are associated with malnutrition and SSI susceptibility. We aimed to: (1) genotype these SNPs in a study population using KASP; (2) assess their conformity to HWE; (3) analyze genotype and allele frequency distributions between malnutrition/non-malnutrition and SSI/non-SSI groups; and (4) perform multivariate logistic regression adjusted for clinical confounders to identify whether SNPs act as independent preliminary signal for malnutrition and SSI, respectively. The results of this study will contribute to the growing body of evidence on genetic factors influencing malnutrition and SSI, potentially informing personalized health care approaches. All genetic association findings in this study will be reported in accordance with the STrengthening the REporting of Genetic Association Studies (STREGA) statement guidelines.

Materials and methods

The study was first approved by the Ethics Committee of the First Affiliated Hospital of Xinjiang Medical University (approval ID: K202310-09, date: 10 August 2023). In accordance with the Declaration of Helsinki, patients aged over 18 years who were scheduled to undergo gastrointestinal surgery at the First Affiliated Hospital of Xinjiang Medical University were recruited from February 2024 to November 2024. All participants gave informed consent after a full explanation of the study objectives and procedures. Patients after laparoscopic surgery without gastrointestinal perforation were included (small abdominal operations, such as open appendectomies were excluded) in the Department of Gastrointestinal (Oncology) Surgery[2]. Patients observed for less than 1 month after surgery were also excluded. Participants’ clinical history was obtained from their medical files and records.

Diagnosis

A total of 169 participants were recruited for this study and underwent clinical assessment for malnutrition and SSI. The cohort was divided into two pairs of groups based on clinical assessments: (1) malnutrition (n = 26) and non-malnutrition (n = 143) groups, defined by standardized nutritional status evaluation criteria from the Global Leadership Initiative on Malnutrition (GLIM)[22]; (2) infection (n = 52) and non-infection (n = 117) groups, confirmed by Centers for Disease Control and Prevention Guideline for the Prevention of Surgical Site Infection[23]. Participants with genetic disorders, or recent use of immunosuppressive drugs, were excluded, and we excluded patients with inherited genetic diseases or recent administration of immunosuppressive agents to avoid diagnostic bias.

DNA extraction and quality control

Peripheral blood samples (3–5 mL) were collected in EDTA anticoagulant tubes. Genomic DNA was extracted using a commercial DNA extraction kit (Junode DNA Extraction Kit, Wuhan, China) following the manufacturer’s instructions. DNA concentration and purity were quantified using a Nano-100 spectrophotometer (Ao Sheng, Hangzhou, China), with A260/A280 ratios between 1.8 and 2.0 considered acceptable.

DNA integrity was verified by 1.0% agarose gel electrophoresis (120 V, 30 min) stained with nucleic dye (Sangon Biotech, Shanghai, China), and visualized using a Tanon-2500 gel imaging system (Tanon Science & Technology, Shanghai, China). Qualified DNA samples (concentration ≥ 50 ng/μL, no degradation) were stored at −20 °C until genotyping.

Genotyping

KASP is based on a competitive, allele-specific PCR genotyping technique with a homogenous fluorescent based reporting system[24]. Genotyping of rs1544410, rs1800796, and rs3917924 was performed using the KASP assay (LGC Genomics, Hoddesdon, UK) at Xinjiang OE Biotech Co., Ltd. The KASP reaction mixture (5.07 μL) contained 2.5 μL of KASP Master Mix, 0.07 μL of KASP Assay Mix (including allele-specific primers and a common primer), and 2.5 μL DNA (10 ng/μl). The thermal cycling protocol was as follows: initial activation at 94 °C for 14 min; 48 cycles of denaturation at 94 °C for 20 s and annealing/elongation at 57 °C for 60 s; and a final hold at 4 °C. Fluorescence signals were detected using an ABI Q6 Real-Time PCR System (Thermo Fisher Scientific, Waltham, MA, USA), and genotype calls were made using LGC Kraken software. Negative controls (no template DNA) were included in each run to ensure the absence of contamination, and sequences of primers for KASP are listed in Table S1. Samples were randomly selected for duplicate genotyping to confirm accuracy using Sanger sequencing, and no inconsistencies in genotype assignment were found.

Statistical analysis

All statistical analyses were performed using SPSS 26.0 software (IBM Corp., Armonk, NY, USA) and SNP Stats online tool. HWE was tested using the chi-square test for each SNP in each group, with P > 0.05 considered in equilibrium.

Genotype and allele frequencies between groups were compared using the chi-square test or Fisher’s exact test (when expected frequencies < 5). Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to assess the strength of association. All multiple comparisons across three SNPs were corrected by Bonferroni adjustment. The adjusted significance cutoff was calculated as α = 0.05 divided by the total number of comparative tests performed. Statistical significance was re-evaluated based on corrected P values. A two-tailed P < 0.05 was considered statistically significant.

Quality control for ensuring the reliability of HWE tests

All study subjects were consecutively enrolled patients admitted to the Department of Gastrointestinal (Oncology) Surgery, the First Affiliated Hospital of Xinjiang Medical University between February and November 2024 in this single-center study, with no mixed populations recruited from multiple centers. Subjects were screened in strict accordance with the unified pre-established inclusion and exclusion criteria of this study. Double quality control filtering was implemented during the genotyping stage. A quality control procedure of independent HWE testing stratified by subgroups was also adopted.

Results

The results of the quality checks ensured confidence in the construction of genotyping and were detailed in Figure S1 and Table S2. Quality check of 169 samples was acceptable based on DNA electrophoresis and integrity analysis. Genotyping quality control criteria were strictly implemented to exclude unqualified samples with insufficient fluorescence signals, and genotyping failure was observed in a small number of samples due to low fluorescent signal intensity, which was a common technical limitation of the KASP assay. Specifically, valid genotyping data were obtained for 164 samples for rs1544410 (5 failures), 169 samples for rs1800796 (0 failures), and 167 samples for rs3917924 (2 failures). Samples regenotyped were in good quality based on DNA electrophoresis (Figure S2), and the genotype of each SNP in the duplicate samples was consistent with the results obtained by KASP genotyping (concordance rate = 100.0%), as shown in Table S3.

HWE test

HWE tests were performed for each SNP in the malnutrition/non-malnutrition and SSI/non-SSI groups using their respective valid genotyping sample sizes (rs1544410: n = 164; rs1800796: n = 169; rs3917924: n = 167), and the results are summarized in Table 1. In the malnutrition group, all SNPs complied with HWE (rs1544410: P = 0.506; rs1800796: P = 0.225; rs3917924: P = 0.588). In the non-malnutrition group, rs1544410 (P = 0.242) and rs3917924 (P = 0.316) complied with HWE, while rs1800796 deviated from HWE (P < 0.001).

For the infection group, rs1544410 (P = 0.773) and rs3917924 (P = 0.829) conformed to HWE, but rs1800796 did not (P = 0.019). In the non-infection group, rs1544410 (P = 0.147) and rs3917924 (P = 0.393) complied with HWE, whereas rs1800796 showed deviation (P = 0.019).

Genotype and allele distributions in malnutrition vs. non-malnutrition groups

The genotype and allele frequencies of the three SNPs in the malnutrition and non-malnutrition groups are presented in Table 2 and Table 3 (valid genotyping sample sizes: rs1544410 = 164, rs1800796 = 169, rs3917924 = 167).

For rs1544410 (C/T), the genotype frequencies were 76.9% (CC), 23.1% (CT), and 0.0% (TT) in the malnutrition group, and 81.9% (CC), 18.1% (CT), and 0.0% (TT) in the non-malnutrition group. No significant difference was observed in the genotype (P = 0.362) or allele (P = 0.575) frequencies between the two groups.

For rs1800796 (C/G), the genotype frequencies were 23.1% (CC), 61.5% (CG), and 15.4% (GG) in the malnutrition group, and 42.0% (CC), 32.2% (CG), and 25.9% (GG) in the non-malnutrition group. There was a significant difference in genotype distribution between the two groups (χ² = 8.179, P = 0.017). However, after Bonferroni correction for multiple SNP tests, the statistical significance of rs1800796 disappeared, indicating no significant association between rs1800796 and nutritional status.

For rs3917924 (G/A), the genotype frequencies were 80.8% (GG), 19.2% (GA), and 0.0% (AA) in the malnutrition group, and 72.3% (GG), 24.1% (GA), and 3.5% (AA) in the non-malnutrition group. No significant associations were detected for genotype (P = 0.686) or allele (P = 0.262) frequencies.

Comparison of general clinical data between malnutrition and non-malnutrition groups

Univariate analysis indicated that rs1800796 and body mass index (BMI) differed significantly between patients with malnutrition and those without malnutrition (P < 0.05) as shown in Table 4.

Genotype and allele distributions in infection vs. non-infection groups

The genotype and allele frequencies of the three SNPs in the infection and non-infection groups are shown in Tables 4 and 5 (valid genotyping sample sizes: rs1544410 = 164, rs1800796 = 169, rs3917924 = 167).

For rs1544410 (C/T), the genotype frequencies were 92.3% (CC), 7.7% (CT), and 0.0% (TT) in the infection group, and 75.9% (CC), 24.1% (CT), and 0.0% (TT) in the non-infection group. A significant difference was observed in the genotype distribution between the two groups (χ² = 6.242, P = 0.012). Regarding allele frequencies, the C allele was more common in the infection group (96.2%) than in the non-infection group (87.9%), with a significant association (χ² = 5.590, P = 0.018; OR = 3.426, 95% CI: 1.162–10.06) (Tables 5, 6).

For rs1800796 (C/G), the genotype frequencies were 42.3% (CC), 32.7% (CG), and 25.0% (GG) in the infection group, and 37.6% (CC), 38.5% (CG), and 23.9% (GG) in the non-infection group. No significant difference was found in the genotype (P = 0.761) or allele (P = 0.755) frequencies (Tables 5, 6).

For rs3917924 (G/A), the genotype frequencies were 76.5% (GG), 21.6% (GA), and 2.0% (AA) in the infection group, and 72.4% (GG), 24.1% (GA), and 3.4% (AA) in the non-infection group. No significant associations were detected for the genotype (P = 0.944) or allele (P = 0.510) frequencies (Tables 5, 6).

Univariate analysis and multivariate logistic regression of general clinical data between infection and non-infection groups

Variables with significant differences in univariate analysis (gender and rs1544410) were entered into multivariate logistic regression, and both were found to be statistically significant (P < 0.05) as shown in Table 7. Male gender (β = 0.949, OR = 2.583, P = 0.017) and the CC genotype of rs1544410 (β = 1.176, OR = 3.241, P = 0.041) were potential risk factors for infection and detailed in Table 8.

Discussion

Malnutrition and SSI are common issues and the two conditions exacerbate one another to drive poor clinical outcomes. Accordingly, determining the association of genetic polymorphism with the risk of malnutrition and SSI can provide useful information for public health officials to design interventions for patients, aligning with the concept of Precision Medicine in early recognition and rehabilitation[25]. Nominal univariate genotype differences were observed for rs1800796 between malnutrition and non-malnutrition groups, and an exploratory multivariate regression suggested a potential correlation between rs1544410 CC genotype and SSI. However, both nominal positive signals disappeared after Bonferroni correction, and rs1800796 deviated from HWE in multiple subgroups and lost statistical independence after adjusting for clinical covariates. All observed nominal differences should be interpreted with extreme caution.

Deviations from HWE were observed for rs1800796 in the non-malnutrition, infection, and non-infection groups. Such deviations may be attributed to several factors, including population stratification, natural selection, and other evolutionary pressures[26]. Nevertheless, the genotyping method (KASP) used in this study was highly reliable, and negative controls confirmed the absence of contamination, suggesting that genotyping errors were unlikely. Single-center enrollment, limited sample size (only 26 malnourished patients), and clinical selection bias of surgical inpatients could be a potential explanation, as the study population may have included individuals from different regions with varying genotype frequencies. The procedures of DNA Extraction were screened strictly, and all quality control measures were performed consistently (including fluorescence signal filtering, Sanger sequencing validation, and removal of low-quality samples) to rule out genotyping errors as a cause of HWE deviation. Alternatively, it was reported that rs1800796 may be under selection pressure leading to altered genotype frequencies[27]. For malnutrition susceptibility, rs1800796 showed a significant difference in genotype distribution between the malnutrition and non-malnutrition groups. This is consistent with the present study, in which the rs1800796 polymorphism was associated with nutritional status, and inflammatory processes may indirectly contribute to physical weakness through the endocrine and musculoskeletal systems, leading to nutritional imbalances[28,29]. Rs1800796 is located in a gene involved in inflammatory signaling, which plays a critical role in nutrient metabolism and immune response[11]. The C allele of rs1800796 has been reported to correlate with higher High-Density Lipoprotein Cholesterol and lower total cholesterol levels, which may indicate inadequate lipid storage. Such lipid-related effects of this variant have been reported in previous literature, but the present study could not confirm an independent association between rs1800796 and malnutrition after adjusting for clinical covariates[30]. Among them are probable reasons that may explain why the C/G genotype of rs1800796 is more prevalent in malnourished patients. In this vein, inflammatory marker such as IL-6 appear to be useful laboratory markers for assessing malnutrition and sarcopenia[31]. Improving nutritional status and mitigating systemic inflammation effectively improves patients’ postoperative quality of life[32]. However, rs1800796 only showed univariate intergroup differences and lost independent significance after covariate adjustment. Furthermore, potential multicollinearity existed between rs1800796 and BMI, which limited the stability of multivariate regression outputs. Thus, we hold a reserved attitude toward conclusions regarding the correlation between rs1800796 and malnutrition. As a result, further research is warranted to explore whether rs1800796 exhibits genotype-specific (rather than allele-specific) associations with malnutrition.

In the infection analysis, rs1544410 demonstrated a significant association with both genotype and allele frequencies. However, rs1544410 did not reach statistical significance after Bonferroni correction. To explore the potential association between these genetic variants and surgical site infection, clinical variables with P < 0.0083 in univariate analysis (gender) together with rs1544410 were incorporated into multivariate logistic regression for exploratory analysis. The C allele of rs1544410 was more common in the infection group, with an OR of 3.426, but it must be interpreted with extreme caution and cannot be regarded as reliable genetic evidence. Located at chr12:47846052 (GRCh38.p14), rs1544410 may affect gene expression and differential biological response to vitamin D[33]. Similarly, a recent study observed that the CT genotype was more frequent in healthy controls (12.9% vs. 7.9%), with a borderline significant association in the heterozygous model (OR = 0.610, 95% CI: 0.371–1.002, P = 0.049). Rs1544410 lost statistical significance after Bonferroni correction, and a multivariate model was constructed for exploratory purposes. Rs1544410 exhibited significantly elevated odds of adverse postoperative outcomes (OR = 3.241, 95% CI: 1.050–10.000, P < 0.05). Collectively, prior research on other infectious diseases reported protective effects of the CT genotype of rs1544410, but such findings cannot be directly generalized to postoperative SSI in gastrointestinal patients[10]. Rs1544410 involved in the pathogenesis of SSI may achieve partly via its influence on vitamin D level, and sufficient levels of vitamin D stimulate the innate immune system through the toll-like receptors (TLRs) in the immune cells. The stimulation of TLRs in the immune cell stimulates the generation of anti-microbial peptides such as reactive oxygen species, and cathelicidin that further eliminate the intracellular microorganism[34]. Since the C allele of the rs1544410 polymorphism may contribute to the development of infectious diseases[10,33,34], and considering that SSI has been found to be associated with a higher level of vitamin D[35], it would be reasonable to consider that rs1544410 could also be involved in the development of SSI in patients undergoing gastrointestinal surgery. In fact, CT genotype of rs1544410, as underlying protective factor, CC genotype of rs1544410 along with low vitamin D levels may increase the risk of infection[36–38]. Previously, allelic differences in the rs1544410 polymorphism may affect gene expression through regulation of mRNA stability, leading to infection[37], and vitamin D supplementation could be useful to reverse this effect[38,39]. Pointing to the role of vitamin D in innate and adaptive immunity, simultaneous measurement of serum vitamin D level and rs1544410 polymorphisms in patients is recommended[40].

Fever, pain, and poor wound healing, 30.7% patients exhibited SSI in the present study[41,42]. In particular, an early way to manage SSI occurrence is crucial, since it seems to be the most important to identify the characteristics of patients and implement early prevention[43]. Only nominal univariate differences and exploratory multivariate correlation were observed for rs1544410, and no robust significant association remained after multiple testing correction. Large multi-center cohorts are needed to verify its potential link with postoperative SSI[44], large-scale multi-center cohorts are required for exploration in patients undergoing gastrointestinal surgery.

However, Bonferroni correction was used to control type I error for six tested SNPs, and no genetic variants remained significant after adjustment, implying that the nominal positive findings in univariate analysis may reflect false positives caused by multiple testing. We further performed exploratory multivariate logistic regression including SNPs with nominal P < 0.05 in univariate analysis. Although rs1544410 showed an association in this exploratory model, the result should be interpreted cautiously. The Bonferroni method is overly conservative and reduces statistical power, and the limited sample size may restrict the reliability of genetic association results. Further large-sample cohorts are required to validate these preliminary findings.

As one of the main SNPs of the VDR, it is believed that individuals carrying the C allele of rs1544410 have a higher risk of infection[45]. The VDR gene is a trans-acting transcription factor that mediates the innate immune response by enhancing the expression of several antimicrobial peptides, and VDRs are expressed on various immune cells including activated CD4+ and CD8+ T cells, B cells, neutrophils, macrophages, and dendritic cells[45,46]. In complex with 1,25‑dihydroxyvitamin D3, VDR regulates the expression of more than 900 genes[47]. This could explain why the C allele of rs1544410 is associated with higher infection risk. To the best of the authors’ knowledge, this is the first study to investigate the potential correlation between the rs1544410 SNP and the presence of SSI in patients undergoing gastrointestinal surgery. Notably, all observed associations were not robust after Bonferroni correction and were only derived from exploratory regression analysis.

Emergency granulopoiesis and neutrophil mobilization that can be triggered through the receptor of GCSF are essential for antibacterial innate defense[48]. The genotype of the GCSF gene at the rs3917924 locus is associated with the risk of surgical infection, due to insufficient secretion of GCSF in individuals, frequently resulting in decreased immune function of phagocytes and T lymphocytes, which impairs the ability to control the progression of the inflammatory response[49,50]. However, rs3917924 showed no significant associations with either malnutrition or infection in this study. Its role in malnutrition and infection may be minor or dependent on other genetic or environmental factors. The lack of association could also be due to the small sample size, which may have limited statistical power to detect weak associations in patients undergoing gastrointestinal surgery. In contrast, GCSF was thought to be a potential biomarker of infection-related sepsis induced by cecal ligation and puncture surgery, and GCSF targeting may be a safe therapeutic strategy for arthritis and other inflammatory conditions[51,52]. Moreover, a specific diet increases GCSF expression, resulting in metabolic disorder[53]. It has so far not yet been confirmed in rs3917924, and larger scale and detecting the expression of GCSF are recommended. The results did not reveal an overall association; however, such knowledge may provide fundamental insight for other researchers.

This study has several limitations. First, a formal pre-study power analysis was not performed before participant enrollment, and the sample size was relatively small, particularly for the malnutrition group, which may have affected the statistical power to detect associations. Moreover, low-frequency genotypes increased risks of Type I and Type II errors. Second, differences in SSI pathogens and heterogeneous scopes of gastrointestinal surgery introduced inter-group heterogeneity. Third, rs1800796 deviated from HWE, and its association lost statistical significance after Bonferroni correction, which limits the reliability of relevant results. Fourth: Genotyping failure occurred in a small number of samples (5 for rs1544410, 2 for rs3917924) due to technical limitations of the KASP assay. Fifth, sensitivity analysis excluding SNPs with HWE deviation was not performed. Future studies should address these limitations by recruiting larger and more diverse populations, adjusting for confounding factors, and conducting functional experiments to validate these findings.

Conclusions

Univariate comparisons revealed intergroup genotype distribution differences of rs1800796 between malnourished and non-malnourished patients, yet this variant deviated from HWE across multiple subgroups and showed no independent correlation after Bonferroni correction. We maintain a reserved stance on its correlation with malnutrition. Failed to reach the threshold of statistical significance after Bonferroni correction, CC genotype rs1544410 showed a nominally significant correlation with SSI in exploratory analysis. After adjusting for age, sex, BMI, smoking status, cancer diagnosis, and lesion location, the CC genotype of rs1544410 remained an independent risk factor for postoperative SSI. The findings from this single-center small-sample study only generate preliminary hypotheses and cannot serve as definitive genetic predictive indicators. Additional large-scale, multi-center cohorts and functional experiments are required to replicate these associations and clarify the underlying biological mechanisms.

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