Genetic Evidence of Obesity-Induced Chronic Wounds Mediated by Inflammatory Biomarkers

Abstract

Background: Obese patients are increasingly recognized as being at higher risk for skin diseases, particularly chronic wounds. While the exact mechanisms remain unclear, obesity is suspected to influence the development of chronic injuries via inflammatory biomarkers. Single nucleotide polymorphisms (SNPs) may further influence gene expression, protein function, and levels of inflammatory biomarkers through various mechanisms, thereby modulating inflammatory responses that contribute to wound pathogenesis. Methods: A two-sample two-step Mendelian Randomization (MR) was employed to explore the causal relationship between obesity and chronic wounds, focusing on the mediating role of inflammatory biomarkers. SNPs were used as instrumental variables (IVs) to infer causality. Obesity-related genetic data were sourced from the UK Biobank and GIANT consortium. Genome-wide association studies provided data on 92 inflammatory biomarkers, involving 14,824 and 575,531 individuals. Pressure injuries, lower limb venous ulcers, and diabetic foot ulcer data were obtained from FinnGen R10 and the Pan-UK Biobank. Results: Obesity significantly increased the risk of pressure injuries, lower limb venous ulcers, and diabetic foot ulcers. CCL19, hGDNF, IL-12B, and TNFRSF9 were identified as mediators in obesity-induced lower limb venous ulcers. Conclusion: This study provides genetic evidence that obesity leads to lower limb venous ulcers via inflammatory biomarkers, suggesting potential therapeutic targets for intervention.

Keywords

obesity inflammatory biomarkers inflammation chronic wounds pressure injuries leg ulcer venous ulcer diabetic foot mendelian randomization analysis

Introduction

Chronic wounds are wounds that do not heal within the expected timeframe for a conventional wound, typically considered to be three months (Graves et al., 2022). In the United States, approximately 4.5 million people suffer from chronic wounds (Frykberg & Banks, 2015). The National Health Service (NHS) in the United Kingdom spends between £230 million and £310 million annually on the direct care of patients with chronic wounds, which represents about 3% of total healthcare expenditures (Phillips et al., 2016). These wounds have a prolonged non-healing nature, significantly impacting patients’ quality of life and leading to substantial healthcare costs, creating a significant economic burden on patients. The majority of chronic wounds can be categorized into three main types: pressure injuries, diabetic foot ulcers, and lower limb venous ulcers, which may occur even in the absence of overt signs of venous stasis disease (Mustoe, 2004). These wounds deviate from the typical healing process and, instead, remain in a prolonged inflammatory state, despite receiving appropriate wound care. Chronic wounds are distinguished by persistent and severe inflammation, marked by significant neutrophil infiltration, along with the presence of reactive oxygen species (ROS) and destructive enzymes that perpetuate the inflammatory cycle (Butin-Israeli et al., 2019). Nevertheless, by addressing the primary causative factors, it is possible to effectively promote the healing of chronic wounds (Goldman, 2004). In addition to inflammation, chronic wounds may also result from underlying factors such as deformities (bone, bursa, and cicatrix; Bibbo et al., 2020), deep infections (e.g., osteomyelitis; Uberoi et al., 2024; Yammine et al., 2024), and/or ischemia-hypoxia (Rivers & Meininger, 2023), which further complicate the healing process.

In recent years, obesity has emerged as a growing public health concern globally. The World Health Organization (WHO) reports that 43% of adults worldwide are overweight (BMI ≥25), with 16% classified as obese (BMI ≥30; Obesity and Overweight, 2024). Obesity not only affects the quality of life for individuals but also has strong correlations with an increased prevalence of diverse skin issues. Research has shown a notably higher frequency of skin injuries in obese individuals compared to those who are not obese, potentially because of the inflammatory state and diminished cell-mediated immune response linked to obesity (Hirt et al., 2019), even though the exact mechanisms remain unclear. Obesity can trigger chronic low-grade inflammation in the body (Chen et al., 2024). Excessive obesity and dysfunction of adipocytes lead to abnormal secretion of inflammatory biomarkers from adipose tissue (Cao et al., 2017; Martinerie et al., 2016; Sacerdoti et al., 2018), such as IL-6, IL-1β, and TNF-α (Miggitsch et al., 2019; Zatterale et al., 2019).

Based on the background provided, we propose that inflammatory biomarkers might play a role in mediating the connection between obesity and the development of chronic wounds. SNPs are variations at specific positions in the genome, where a single nucleotide (A, T, C, or G) differs, resulting in sequence diversity (Kim & Misra, 2007). SNPs can significantly affect gene expression and protein function, thereby modulating biological processes involved in inflammatory responses. These variations exert their influence on cellular signaling pathways, gene regulation, and immune responses through a variety of mechanisms, ultimately leading to changes in the levels of inflammatory biomarkers. For example, SNPs can regulate the expression of IL-6 by modifying the binding affinity of transcription factors to the promoter region of the IL-6 gene (Xin et al., 2018). Additionally, they can modulate the NF-κB signaling pathway, affecting the expression of IL-6 and high-sensitivity C-reactive protein (hsCRP), thereby influencing the overall inflammatory response (Saratzis et al., 2015). Our research begins with a two-sample MR analysis to investigate the link between obesity and chronic wounds. By leveraging the ability of MR to minimize confounding, this approach effectively controls for potential confounders, including diabetes (Klein et al., 2022), cardiovascular disease (Drozdová et al., 2016), cerebrovascular disease (Dutta et al., 2024), and metabolic disorders (Vorobeľová et al., 2021), all of which are closely associated with both obesity and the development of chronic wounds. Subsequently, we conduct a comprehensive two-step MR analysis involving 92 inflammatory biomarkers to elucidate the potential mechanisms by which obesity impacts the likelihood of chronic wounds. This methodology is designed to assist healthcare professionals in identifying novel targets for the treatment and prevention of chronic wounds, thus deepening our understanding of the inflammatory pathways through which obesity contributes to their formation. By utilizing MR, we aim to mitigate the impact of these critical confounders, thereby providing more robust evidence for the causal relationships between obesity, inflammation, and the development of chronic wounds. Ultimately, the aim of this study is to investigate whether obesity contributes to the formation of chronic wounds through the mediation of inflammatory biomarkers. By understanding this relationship, we hope to advance clinical care strategies for more effective management of these complex conditions.

Methods

Exposure and Outcome

The IVs for BMI were carefully selected in a multi-step process. Initially, a meta-analysis was conducted using data from the UK Biobank and the Genetic Investigation of Anthropometric Traits (GIANT) consortium, which included 681,275 individuals of European ancestry (Yengo et al., 2018). Subsequently, independent SNPs were selected through Linkage Disequilibrium (LD) clumping. LD refers to the non-random association of alleles at different loci, which can result in high correlation between SNPs and lead to false-positive associations. To address this, a stringent threshold of r² < 0.001 was applied during LD clumping to retain only low-correlation SNPs, thereby minimizing redundancy. Within each 10,000 kb window, the SNPs with the smallest p-value was retained as the representative SNPs, while those in high LD with it were pruned, resulting in a total of 521 independent SNPs with p < 5 × 10^−8. The selected SNPs were subsequently used in the MR analysis, ensuring that they were independent of each other to avoid bias arising from collinearity. Additionally, the F-statistic for each SNPs was calculated to evaluate its strength as an IV. The F-statistic serves as a crucial measure to confirm that the SNPs are sufficiently strong to minimize the risk of weak instrument bias, which could otherwise distort causal estimates in IVs analysis. Consistent with established guidelines, SNPs with an F-statistic greater than 10 were considered strong instruments, thereby supporting the validity of the causal inferences. Chronic wounds, such as pressure injuries, lower limb venous ulcers, and diabetic foot ulcers, were the focus of our literature review. Data on pressure injuries and lower limb venous ulcers were gathered from FinnGen (FINN), specifically from FinnGen R10, with 1621 cases of pressure injuries and 385,509 control cases, as well as 4101 cases of lower limb venous ulcers and 385,509 control cases (Kurki et al., 2023). For diabetic foot ulcers, data were sourced from the 2020 PAN-UK BIOBANK initiative, using genetic summary data from 420,473 individuals of European ancestry from PAN-UK BIOBANK (Karczewski et al., 2024), with 130 diabetic foot ulcers cases and 420,343 controls. Diagnoses were established through assessments conducted by trained nurses and self-reports (Supplemental Table S1).

Genetic Instruments for Inflammatory Biomarkers

Inflammatory biomarker data were sourced from Zhao et al.'s study (Zhao et al., 2023). However, this study did not cover C-reactive protein (CRP), a commonly used marker for inflammation. Therefore, we utilized summarized genetic data on CRP-related genetic variations from Dehghan et al., which focused on individuals of European descent (Said et al., 2022), involving 575,531 individuals. We focused on analyzing genetic variants that showed independent associations (LD r² < 0.001 within a 10,000 kb range). To secure a sufficient quantity of SNPs for every inflammatory biomarker—ensuring that there are more than five—we employed a genome-wide p-value threshold set at p < 5 × 10⁻⁶ to pinpoint pertinent SNPs. In addressing weak instrument bias in IV analysis, we assessed the F-statistic for the chosen SNPs, considering values above 10 as strong instruments.

Two Sample MR

Figure 1 illustrates the research design of this study, which utilized a two-sample MR approach to assess the causal relationships between obesity and three types of chronic wounds: pressure injuries, diabetic foot ulcers, and lower limb venous ulcers. This method leverages summary statistics gathered from publicly available databases. In observational studies, estimating causal effects is often hindered by confounding factors, which can bias the association between the exposure (obesity) and the outcomes (the chronic wounds). Confounders are variables that influence both the exposure and outcome, leading to potential misinterpretations of causality. To mitigate this bias, the two-sample MR approach uses genetic variants as IVs. An IVs is a variable that is associated with the exposure (obesity), but not with the confounders, thereby isolating the causal effect on the outcomes. As depicted in Figure 1, the genetic variants serve as IVs to address the confounding that is typically present in observational studies. This approach strengthens the causal inference by ensuring that the associations between obesity and the chronic wounds are not driven by unmeasured confounders. The MR analysis was carried out based on three key assumptions: (1) the IVs selected must have a strong association with BMI; (2) the IVs should not be correlated with any potential confounders; (3) the IVs should only affect chronic wounds through BMI, without influencing other pathways. In this study, SNPs were employed as IVs. SNPs are genetic variants that are strongly associated with BMI but are independent of other confounders that might influence the outcome. Confounding factors are variables that can affect both the exposure (BMI) and the outcome (chronic wounds), thereby introducing potential bias. By using SNPs as IVs, the MR approach effectively mitigates the influence of these confounders, enabling a more precise estimation of the causal relationship. Utilizing SNPs as IVs, MR is an analytical method used to explore potential causal links between exposure and outcomes in observational data. By mimicking the methodological rigor of random assignment in randomized controlled trials, this design approach leverages the random assortment of alleles during gametogenesis. In the initial analysis, the data were used for MR analysis using the inverse-variance weighted (IVW) method to estimate the causal impact of BMI on chronic wounds. Furthermore, four supplementary methods were employed: the weighted median method, the weighted mode method, the simple mode, and MR Egger. This article followed the STROBE-MR guidelines for reporting observational studies in epidemiology (Skrivankova et al., 2021).

Mediation MR/Two-Step MR Analysis

The mediation analysis used a two-step MR approach to evaluate the indirect effect of each mediator. Initially, IVs for BMI were employed to estimate the causal impact of BMI on inflammatory biomarkers. This method facilitates the examination of the relationship between BMI and inflammation, assessing how changes in BMI may influence inflammatory responses within the body. By leveraging genetic variants as IVs, this approach helps to minimize confounding factors and establish a clearer cause-and-effect relationship. This initial step is crucial for understanding the underlying mechanisms through which BMI may affect inflammation and subsequent health outcomes. Subsequently, the causal effect of the mediator variables on chronic wounds was determined. The proportion mediated for all mediators was calculated by dividing the indirect effect by the total effect, and confidence intervals (CI) were estimated using the delta method.

Statistical Analysis

The IVW method is typically used as the primary analysis when multiple SNPs are available for constructing IVs, as it provides more precise and robust estimates. In this study, bidirectional MR analysis was conducted to investigate the relationship between BMI and chronic wounds. Additionally, a two-step MR analysis was performed to assess the mediating role of inflammatory biomarkers in this relationship. First, the effect of BMI on 92 inflammatory biomarkers was evaluated using univariate MR methods (beta 1). Subsequently, significant inflammatory biomarkers associated with BMI were selected, and their effect on chronic wounds (beta 2) was estimated. The mediation proportion of each inflammatory biomarker in the association between BMI and chronic wounds was calculated as the product of beta 1 and beta 2, divided by the total effect of BMI on chronic wounds. The 95% CI for the mediated effects were calculated using the delta method (MacKinnon et al., 2002).

Sensitivity analyses were conducted using various methods including MR Egger, MR-PRESSO, weighted median, simple mode, and weighted mode. The MR Egger method was employed to test for horizontal pleiotropy, with a non-zero intercept indicating potential bias in the IVW estimates due to horizontal pleiotropy (Bowden et al., 2015). Furthermore, the MR-PRESSO method was utilized to identify outliers and recalculate estimates after their removal, thereby assessing the presence of horizontal pleiotropy (Verbanck et al., 2018). The weighted median method is commonly used in conducting MR studies to estimate causal relationships between exposures and outcomes. This method assumes that genetic instruments are valid IVs, meeting three key MR assumptions. These assumptions include that the genetic instrument is associated with the exposure of interest, not associated with any confounders of the exposure-outcome relationship, and only affects the outcome through the exposure. It is important to note that the weighted median method can provide unbiased causal estimates even if only half of the genetic instruments meet the MR assumptions. This means that as long as at least 50% of the genetic instruments are valid, the estimates obtained through the weighted median method will be reliable and unbiased. This highlights the robustness of this method in dealing with potential violations of the MR assumptions. In conclusion, the weighted median method is a valuable tool in MR studies for estimating causal relationships between exposures and outcomes. It can provide unbiased estimates even in situations where not all genetic instruments meet the necessary assumptions (Bowden et al., 2016). The simple mode method utilizes a mode-based approach to cluster causal effect estimates from individual SNPs, selecting the largest SNPs cluster for causal effect estimation (Hartwig et al., 2017). In the same manner, the method of weighted mode also goes through a comparable procedure but gives weights to each individual nucleotide polymorphism. All MR analyses were carried out using the ‘Two Sample Mendelian Randomization,’ ‘Mendelian Randomization,’ and ‘MRPRESSO’ packages in R software (version 4.4.0).

Cochrane’s Q test was employed as a comprehensive measure for heterogeneity within IVW to assess variations among genetic tools. If p < .05, a random-effects model was employed to calculate IVW. In MR studies, multiple hypothesis testing can increase the risk of false positives. To control the false discovery rate (FDR), we applied the Benjamini-Hochberg procedure, which offers greater flexibility than Bonferroni correction, especially in large-scale analyses. This method adjusts p-values to balance controlling FDR while preserving statistical power. The resulting q-values allow us to identify true significant associations, ensuring robust and reliable findings. This approach adheres to current guidelines for managing multiple testing in MR studies.

Results

Obesity as a Risk Factor for Chronic Wounds

For the three types of chronic wounds—pressure injuries, lower limb venous ulcers, and diabetic foot ulcers—493, 493, and 452 independent SNPs were selected as genetic instruments for BMI, respectively. All SNPs had an F-statistics greater than 10. A significant association was observed between BMI and pressure injuries (1.55 [1.24–1.94], p = .0001), by conducting sensitivity analysis with MR-PRESSO to support these results. No heterogeneity was detected among the genetic tools (Q = 483.6405, p = .5974) and no signs of horizontal pleiotropy was detected (Egger intercept = 0.0003, p = .9480). Similarly, a significant association was found between BMI and diabetic foot ulcers (5.88 [2.53–13.67], p < .0001), with MR-PRESSO sensitivity analysis supporting these results. Once again, no heterogeneity among genetic instruments was detected (Q = 492.6961, p = .0854) and no horizontal pleiotropy was observed (Egger intercept = 0.0221, p = .2518). The association between BMI and lower limb venous ulcers was confirmed using the MR Egger method (3.07 [1.98–4.75], p < .0001) (Table 1).

Table 1.

Bidirectional Mendelian Randomization Analysis of Obesity and Chronic Wounds.

Exposure	Outcome	Method	Number of SNPs	Or (95%CI)	p value
BMI	Pressure ulcer	Inverse variance weighted	493	1.55 (1.24–1.94)	<0.01
BMI	Lower limb venous ulcer	MR egger	493	3.07 (1.98–4.75)	<0.01
BMI	Diabetic foot ulcer	Inverse variance weighted	452	5.88 (2.53–13.67)	<0.01
Pressure injuries	BMI	Inverse variance weighted	2	1.01 (0.98–1.05)	0.54
Lower limb venous ulcer	BMI	Inverse variance weighted	7	1.01 (0.99–1.03)	0.18
Diabetic foot ulcer	BMI	Inverse variance weighted	3	1.00 (0.99–1.01)	0.80

Note. Exposure: The variable or risk factor under investigation to determine its potential causal effect on the outcome. Outcome: The clinical condition or trait that is being assessed for a possible association with the exposure. Method: The specific statistical or analytical approach applied to evaluate the causal relationship between the exposure and outcome.

Obesity Induces Elevated Inflammatory Biomarkers

Our research focused on analyzing how BMI affects 92 circulating inflammatory biomarkers. The results showed noteworthy links with 36 of these biomarkers (Table 2, Supplemental Table S2). Specifically, we noted that BMI was associated with elevated levels of CCL19 (OR = 1.19 [95% CI 1.11–1.29], p = .0000, FDR-corrected p = .0000), hGDNF (OR = 1.10 [95% CI 1.02–1.19], p = .0152, FDR-corrected p = .0177), IL-12B (OR = 1.10 [95% CI 1.01–1.20], p = .0213, FDR-corrected p = .0241), and TNFRSF9 (OR = 1.17 [95% CI 1.08–1.28], p = .0001, FDR-corrected p = .0004).

Table 2.

Impact of Obesity on Inflammatory Biomarkers.

Variants	OR (95%CI)	p value	FDR adjusted p value
4EBP1	1.09 (1.01–1.17)	0.0331	0.0351
CCL19	1.19 (1.11–1.29)	0.0000	0.0000
CCL20	1.14 (1.06–1.22)	0.0006	0.0013
CCL28	0.91 (0.84–0.98)	0.0143	0.0173
CD5	1.13 (1.05–1.23)	0.0023	0.0037
CD6	1.11 (1.03–1.2)	0.0065	0.0090
CSF-1	1.25 (1.16–1.35)	0.0000	0.0000
DNER	0.84 (0.77–0.92)	0.0002	0.0005
EN-RAGE	1.09 (1.01–1.17)	0.0306	0.0335
FGF-19	0.89 (0.83–0.97)	0.0043	0.0063
FGF-21	1.16 (1.07–1.27)	0.0004	0.0009
FGF-23	1.16 (1.08–1.25)	0.0000	0.0001
HGDNF	1.1 (1.02–1.19)	0.0152	0.0177
HGF	1.32 (1.23–1.42)	0.0000	0.0000
IL10	1.08 (1.0–1.17)	0.0422	0.0434
IL10RB	1.18 (1.1–1.27)	0.0000	0.0000
IL12 B	1.1 (1.01–1.2)	0.0213	0.0241
IL15RA	1.11 (1.03–1.21)	0.0108	0.0139
IL18	1.13 (1.04–1.22)	0.0022	0.0037
IL18R1	1.29 (1.2–1.39)	0.0000	0.0000
IL-6	1.28 (1.19–1.38)	0.0000	0.0000
IL-8	1.15 (1.07–1.24)	0.0002	0.0004
LAP TGF-beta-1	1.08 (1.0–1.16)	0.0429	0.0429
CCL2	1.13 (1.05–1.22)	0.002	0.0036
CCL7	1.14 (1.05–1.25)	0.0018	0.0034
MIP-1 alpha	1.17 (1.08–1.26)	0.0000	0.0002
OPG	1.1 (1.02–1.19)	0.0117	0.0146
OSM	1.14 (1.05–1.23)	0.0011	0.0022
SCF	0.84 (0.78–0.91)	0.0000	0.0001
SLAMF1	1.13 (1.04–1.22)	0.0037	0.0056
TGF-alpha	1.13 (1.05–1.21)	0.0013	0.0026
TNFRSF9	1.17 (1.08–1.28)	0.0001	0.0004
TNFSF14	1.12 (1.03–1.21)	0.0095	0.0127
TRAIL	1.15 (1.07–1.24)	0.0002	0.0005
VEGF_A	1.18 (1.09–1.26)	0.0000	0.0001

Note. Variants: Refers to the genetic variants or markers used in the study to explore the association between genes and traits or diseases. FDR Adjusted p value: The p-value adjusted for the FDR, which helps to control the proportion of false positives when conducting multiple comparisons.

Inflammatory Biomarkers Induce Chronic Wounds

Among the 36 inflammatory biomarkers associated with BMI, we found that two were significantly associated with pressure injuries: CSF-1 was positively associated with pressure injuries (OR 1.3054 [95% CI 1.0211–1.6688], p = .0335, corrected p = .0335), and CRP was positively associated with pressure injuries (OR 1.1992 [95% CI 1.0483–1.3719], p = .0081, corrected p = .0162).

Five biomarkers were significantly associated with lower limb venous ulcers: TNFRSF9 (OR 1.2356 [95% CI 1.0581–1.4430], p = .0075, corrected p = .0188), CRP (OR 1.1992 [95% CI 1.0483–1.3719], p = .0081, corrected p = .01,351), hGDNF (OR 1.1951 [95% CI 1.0177–1.4033], p = .0297, corrected p = .0297), IL-12B (OR 1.1524 [95% CI 1.0452–1.2706], p = .0044, corrected p = .0220), and CCL19 (OR 1.1492 [95% CI 1.0214–1.2930], p = .0208, corrected p = .0260).

Four biomarkers were significantly associated with diabetic foot ulcers: DNER (OR 3.0845 [95% CI 1.1020–8.6335], p = .0320, corrected p = .0399), IL-15RA (OR 2.1272 [95% CI 1.2517–3.6153], p = .0052, corrected p = .0132), SCF (OR 2.1090 [95% CI 1.1567–3.8452], p = .0149, corrected p = .0248), IL-8 was negatively associated with diabetic foot ulcers (OR 0.2581 [95% CI 0.0729–0.9136], p = .0357, corrected p = .0357), and CCL19 was negatively associated with diabetic foot ulcers (OR 0.1532 [95% CI 0.0647–0.3625], p < .0001, corrected p < .0001) (Figure 2, Supplemental Table S3).

Inflammatory Biomarkers Mediate Obesity-Induced Lower Limb Venous Ulcers

In our study, we found that while many inflammatory biomarkers were linked to pressure injuries, lower limb venous ulcers, and diabetic foot ulcers, only four inflammatory biomarkers—CCL19, hGDNF, IL-12B, and TNFRSF9—showed mediation effects specifically in relation to lower limb venous ulcers. The total effect of BMI on lower limb venous ulcers was calculated to be OR 3.07 [95% CI 1.98–4.75], p < .001. We determined that 2.18% (95% CI [0.30%–4.06%], p = .0244) of the effect of BMI on lower limb venous ulcers was mediated through CCL19, 1.56% (95% CI [-1.09%–4.21%], p = .0175) through hGDNF, 1.25% (95% CI [-0.19%–2.69%], p = .014) through IL-12B, and 3.04% (95% CI [-0.12%–6.2%], p = .0341) through TNFRSF9 (Figure 3, Supplemental Table S4).

Discussion

In this study, we employed univariate and two-step MR mediation analyses to examine the connections among obesity, inflammatory biomarkers, and chronic wounds. Our results suggest that BMI impacts the development of lower limb venous ulcers through four specific inflammatory biomarkers (CCL19, hGDNF, IL-12B, TNFRSF9), explaining approximately 1%–3% of the risk linked to obesity and lower limb venous ulcers. However, the mediation effects on pressure injuries and diabetic foot ulcers did not reach statistical significance (p < .05).

Previous clinical trials and observational studies have established a causal relationship between obesity and low-grade chronic inflammation (Gregor & Hotamisligil, 2011). Inflammation induced by obesity is characterized by metabolic inflammation, the release of inflammatory biomarker, immune cell infiltration, and chronic persistence. Unlike classical inflammation, which presents symptoms like redness, swelling, heat, and pain, the inflammation caused by metabolic excess is distinct. Classical inflammation is linked to an elevated basal metabolic rate and signifies the immune system’s quick and focused reaction to injury or infection, resolving once the damage is resolved or neutralized. White adipose tissue serves as the primary fat storage depot in the body and functions as the largest endocrine organ responsible for secreting adipokines and cytokines (Kawai et al., 2021). The process of weight gain and obesity triggers a phenotypic shift in white adipose tissue, marked by the presence of inflamed, dysfunctional adipocytes and the infiltration of immune cells into the stromal vascular fraction (Hotamisligil, 2017b). These inflamed adipocytes release pro-inflammatory cytokines such as IL-6, IL-1β, and CCL2 (Engin, 2024), both locally and systemically, disrupting the normal functions of adipose tissue and impacting distant organs (Hotamisligil, 2017a). This perspective views adipose tissue as an immune and secretory organ, with obesity being classified as an inflammatory immune disease. The inflammatory response in expanding white adipose tissue is characterized by a prolonged and intense duration, leading to persistent low-grade inflammation that does not resolve. This chronic low-grade inflammation, associated with obesity and subsequent metabolic changes, is referred to as ‘metaflammation' (Hotamisligil, 2017b). Furthermore, obesity causes an increase in macrophages within adipose tissue. M1 (classically activated) macrophages are triggered by pro-inflammatory stimuli such as LPS, TNFα, and IFNγ, contributing to TH1 immune responses by releasing pro-inflammatory cytokines, on the other hand, M2 (alternatively activated) macrophages are activated by TH2 cytokines like IL-4 and IL-13, releasing TH2 cytokines (Orecchioni et al., 2019). These inflammatory responses and immune cell infiltrations progress gradually and persist over the long term, leading to a state of chronic low-grade inflammation in individuals with obesity.

Lower limb venous ulcers are a prevalent type of chronic wounds, particularly in individuals over the age of 60 in Shanghai, China (Sun et al., 2017). Obesity plays a significant role in the development of lower limb venous ulcers, as it is closely linked to obesity-induced venous hypertension (Davies et al., 2016; Jockenhöfer et al., 2016). Weight gain exerts pressure on the lower limb veins, impairing venous return. This venous hypertension results in blood pooling in the lower limbs, further increasing vascular wall pressure and permeability. Prolonged blood pooling in the lower limbs can lead to tissue edema and hypoxia, worsening the local metabolic environment.

In patients with venous insufficiency, the failure of venous valves to close effectively can worsen blood reflux, leading to increased venous hypertension. This sustained rise in venous pressure can put added strain on vascular walls, potentially causing structural damage (Xie et al., 2018). Additionally, obese patients may face challenges in wound healing, with issues like larger wound sizes and extended healing times (Alavi et al., 2016).

Damage to the venous walls triggers a cascade of inflammatory responses that worsen venous hypertension and weaken the integrity of the vascular walls, increasing their vulnerability to damage and ulceration. In obese individuals, the expression of CCL19 is notably higher compared to lean individuals and is positively associated with BMI (Kochumon et al., 2019). CCL19, a chemokine closely linked to inflammation, plays a key role in orchestrating the positioning of various cells, including immune cells, in the body. It promotes pro-inflammatory effects by interacting with its receptor CCR7, leading to the production of interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α; Bosè et al., 2013; Marsland et al., 2005). Through its binding to CCR7, CCL19 attracts dendritic cells (DCs), T cells, and B cells to lymph nodes and sites of inflammation, facilitating the accumulation and activation of immune cells, thereby bolstering the immune response (Hong et al., 2022). IL-12 B is a crucial pro-inflammatory cytokine that plays a significant role in driving the differentiation of T cells into Th1 cells. Additionally, it stimulates activated T cells and natural killer (NK) cells to produce other important cytokines such as interferon-γ and TNF-α (Ullrich et al., 2020). In obese individuals, elevated levels of IL-12 may boost the activity of T cells and NK cells, leading to systemic and local inflammatory responses that can accelerate damage to venous walls and ulcer formation. TNFRSF9, a receptor involved in immune regulation, supports the activation, proliferation, and cytokine production in CD8⁺ T cells (Fröhlich et al., 2020), including interleukin-2 (IL-2) and interferon-γ. In the context of chronic inflammation related to obesity, TNFRSF9 may intensify immune responses, contributing to local inflammation and tissue damage. On the other hand, hGDNF is recognized for its neuroprotective role, potentially achieved through regulating neuro-immune interactions and influencing the local inflammatory environment.

While inflammatory responses typically involve increased blood flow, characterized by erythema (rubor) and warmth (calor), venous hypertension can impair this process. Specifically, the increased blood flow may be insufficient or poorly distributed due to compromised venous return, ultimately resulting in inadequate tissue perfusion and localized hypoxia. In this hypoxic environment, cellular metabolism becomes abnormal, diminishing tissue repair capabilities and ultimately resulting in tissue necrosis and ulcer formation. The combination of blood stasis and tissue hypoxia, caused by lower limb venous hypertension, triggers a persistent chronic inflammatory response. Inflammatory cells continuously release inflammatory mediators, leading to tissue damage and repair responses. The presence of inflammatory biomarkers further exacerbates local tissue damage and inflammation, ultimately delaying the healing process of ulcers. Our study suggests that the chronic low-grade inflammation induced by obesity provides a potential target for anti-inflammatory interventions in the treatment of lower limb venous ulcers.

Chronic wounds, as complex skin conditions, can be effectively prevented through proactive measures. Obesity, a significant risk factor for various diseases, notably impacts chronic wounds. Early education and interventions focused on weight reduction can be advantageous for high-risk obese patients. Throughout treatment, specific attention should be given to inflammatory biomarkers like CCL19, hGDNF, IL12 B, and TNFRSF9. Timely diagnosis and risk assessment for identifying high-risk patients are essential. The use of anti-inflammatory medications such as corticosteroids or biologics can aid in inflammation control and lower the risk of lower limb venous ulcers. While NSAIDs are effective in managing acute inflammatory responses, their efficacy in addressing chronic low-grade inflammation associated with obesity may be limited due to the complex metabolic and immune pathways involved. In contrast, corticosteroids and biologics are more suited for the treatment of chronic inflammatory conditions. Therefore, in the context of obesity-related chronic low-grade inflammation, exploring targeted anti-inflammatory therapies, including biologics or metabolic regulators, may prove more beneficial than relying solely on traditional NSAIDs. Further research could investigate targeted therapies against these biomarkers to establish novel treatment strategies for lower limb venous ulcers.

Nursing Implications for Inflammation in Obesity-Related Wounds

Nurses can assess the susceptibility of obese patients to developing chronic wounds by monitoring inflammatory markers and providing crucial clinical guidance for wound management. The dynamic changes in inflammatory markers, such as CRP and interleukins, are closely linked to the complex mechanisms of wound healing. Through the monitoring of these markers, nurses can effectively predict the risk of wound deterioration and adjust care strategies in a timely manner. MR, as a genetic research method, serves as a supplementary tool in evidence-based nursing by validating the causal relationships between inflammatory markers and wound healing, thus offering robust scientific support for the development of personalized nursing care plans.

By integrating findings from MR studies with evidence-based nursing practices, biomarker monitoring technology provides essential support for the dynamic adjustment of nursing interventions. Currently, relevant studies have monitored and tracked biomarkers to assess and determine the onset of conditions like hypertension and cancer (Kasimovskaya et al., 2024; Yule et al., 2024). We can further extend this approach to enhance patient care in various medical contexts. Regular monitoring of inflammatory biomarkers in obese patients allows nurses to accurately evaluate the progression of inflammation and make corresponding adjustments to care plans. For instance, when inflammatory marker levels increase, nurses can intensify local wound care, replace dressings more frequently, or escalate the use of anti-inflammatory treatments to prevent wound deterioration. This dynamic approach enables the effective evaluation of nursing interventions, preventing both overtreatment and undertreatment, ultimately optimizing the overall quality of care.

Furthermore, with the ongoing advancements in artificial intelligence and big data technologies (Romero-Tapiador et al., 2023), remote care platforms can be used by nurses to implement personalized care decisions and enhance patient self-management. These platforms enable real-time access to patients’ physiological data and wound healing progress, facilitating timely adjustments to care strategies and ensuring precision in personalized interventions. Leveraging big data from comparable patients, while ensuring privacy, further optimizes care plans and aids in identifying potential issues early, preventing wound deterioration. In addition, remote care technologies offer patients scientific guidance for self-management by analyzing data collected from smart devices (Christopoulou, 2024). For example, nurses can help patients adjust their lifestyles and improve self-management behaviors by interpreting data related to weight, diet, and physical activity. The combination of personalized care decisions and enhanced patient self-management improves care outcomes and adherence, empowering obese patients to take a more active role in managing their health while reducing dependence on healthcare resources.

MR provides critical insights for nursing practice, particularly in optimizing inflammatory marker monitoring, validating causal relationships, and designing personalized care strategies. By utilizing genetic evidence from MR, nurses can make more precise care decisions, thereby enhancing the scientific rigor and clinical efficacy of evidence-based nursing practices.

Strengths and Limitations of the Study

This study is the first to utilize MR to examine the connections between obesity, inflammatory biomarkers, and chronic wounds. Although the study has notable strengths, there are several limitations to consider. Initially, though genetic variations that imitate pressure injuries, diabetes-related foot ulcer, and venous ulcers on the lower limbs could offer understanding into immediate consequences, the sizes of the impacts may not precisely mirror long-standing exposure. Consequently, utilizing MR methodology is better suited for evaluating the orientation of potential causal connections as opposed to measuring the magnitudes of effects. Despite this, the anticipated direction of effect can provide insight for further exploration of therapeutic impacts in clinical trials. Additionally, the research was conducted using data from individuals of European lineage, therefore, extending these results to different populations requires further investigation. Our study encompassed a wide array of inflammatory proteins; However, some inflammatory biomarkers were not considered, emphasizing the necessity of an extensive pQTL repository to reveal more potential candidates. Furthermore, the specific mechanisms by which certain inflammatory biomarkers, like hGDNF, impact wound formation remain elusive and warrant further basic experimental investigation. Notably, the mediation effects observed for pressure injuries and diabetic foot ulcers were negative, suggesting that obesity may not influence their development through inflammatory biomarkers. Pressure injuries primarily result from local ischemia and tissue necrosis due to prolonged pressure, with inflammation playing a secondary role in mechanical pressure and blood flow obstruction. On the other hand, diabetic foot ulcers involve a complex interplay of neuropathy, vasculopathy, and infection, where inflammation is significant but factors like poor blood glucose control, peripheral neuropathy, and microcirculatory disturbances may have a more substantial impact. Despite examining 35 obesity-related inflammatory biomarkers, markers such as CRP, IL-8, and CSF-1 were found to be linked to pressure injuries and diabetic foot ulcers. Additionally, other factors such as underlying deformities, neuropathies, and occult injuries should also be considered in the context of chronic wound development. Skeletal abnormalities, for instance, can lead to uneven pressure distribution, thereby increasing the risk of tissue damage (Bibbo et al., 2020). Neuropathies, commonly observed in conditions such as diabetes, can result in loss of sensation, reducing awareness of injuries or pressure injuries, which in turn exacerbates wound formation (Mohsin et al., 2024). Occult injuries, which may not be immediately apparent, contribute significantly to the development of chronic wounds by gradually causing tissue damage through persistent stress or impaired blood flow. This highlights the importance of conducting single-sample MR studies to identify risk factors and determine appropriate interventions to reduce the occurrence of chronic wounds.

Conclusion

This study presents genetic evidence that supports the connection between obesity, inflammatory biomarkers, and chronic wounds. More specifically, CCL19, hGDNF, IL-12B, and TNFRSF9 are identified as potential mediators of the impact of obesity on lower limb venous ulcers.

Supplemental Material

Supplemental Material - Genetic Evidence of Obesity-Induced Chronic Wounds Mediated by Inflammatory Biomarkers

Supplemental Material for Genetic Evidence of Obesity-Induced Chronic Wounds Mediated by Inflammatory Biomarkers by Hai Xu, Sheyuan Ding, Yu Tong, and Qiong Zhang in Biological Research For Nursing

Footnotes

Acknowledgments

We appreciate all the participants involved in the genome-wide association studys used for this study and extend our gratitude to the investigators who made these genome-wide association study data accessible to the public.

Author Contributions

Concept and design: Hai Xu and Yu Tong. Acquisition, analysis, or interpretation of data: Hai Xu, Sheyuan Ding and Yu Tong. Drafting of the manuscript: Hai Xu. Critical review of the manuscript for important intellectual content: All authors. Statistical analysis: Hai Xu. Supervision: Qiong Zhang.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the 2024 National Administration of Traditional Chinese Medicine Science and Technology Department - Zhejiang Provincial Administration of Traditional Chinese Medicine Joint Construction of Science and Technology Plan Key Project. grant numbers [2024035416]; 2023 Ministry of Education Higher Education Department Industry-Academia Cooperation and Collaborative Talent Cultivation Project. grant number [22077043292135]; and 2023 Zhejiang Province Medical and Health Science and Technology Plan Project grant number [2023KY045].

ORCID iD

Hai Xu

Supplemental Material

Supplemental material for this article is available online.

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