Mesenteric Adipose Tissue Volume Predicts Response to Antitumor Necrosis Factor Therapy in Biological-Naïve Patients With Crohn's Disease

Abstract

INTRODUCTION:

Crohn's disease is associated with varying degrees of mesenteric adipose tissue (MAT) hypertrophy. The study aimed to evaluate whether MAT hypertrophy, measured by MAT volume, is associated with worse response to anti-tumor necrosis factor alpha (TNF-α) therapy in biologic-naïve patients with Crohn's disease (CD).

METHODS:

A cohort of consecutive patients with CD who underwent computed tomography or MRI before the start of the anti-TNF-α therapy was included. Total MAT volume, excluding large vessels, was estimated. Primary outcomes—dose intensification, surgery, and withdrawal of anti-TNF-α therapy—were evaluated at 3 and 12 months after the initiation of treatment. We performed a multivariate logistic regression model to identify MAT volume as an independent risk factor of poor response to anti-TNF-α.

RESULTS:

Fifty biologic-naïve, consecutive patients with CD were included. The median MAT volume was 559.5 cm³ (IQR: 410.3–891.9). MAT volume was positively correlated with weight (ρ = 0.66, P < 0.001) and age (ρ = 0.5, P < 0.001). Multivariate regression model showed that higher MAT volume independently predicted a poor response to anti-TNF-α treatment, as indicated by a greater need for dose intensification of anti-TNF-α agents within 12 months (adjusted odds ratio [OR^a]: 1.36; 95% CI: 1.08–1.81; P = 0.016) and an increased risk of CD surgery within 3 months (OR^a: 1.65; 95% CI: 1.08–3.05; P = 0.048).

DISCUSSION:

MAT volume predicted an increased need for anti-TNF-α dose intensification and surgery in patients with biological-naïve Crohn's disease. MAT volume could be a valuable measure for identifying patients at risk of a poor anti-TNF-α response.

INTRODUCTION

The mesentery is a continuous organ that plays a central role in maintaining intestinal homeostasis (1). In addition to its function of suspending abdominal organs, the mesentery has a crucial immunological role: it promotes both tolerogenic and inflammatory processes to suppress antigen-specific immune responses or clear pathogens, thereby maintaining intestinal balance (2–5). In this context, its role becomes even more significant considering that the mesentery has recently emerged as a key player in the pathogenesis and progression of Crohn's disease (CD) (6); however, the precise mechanisms involved in this mesentery—gut crosstalk remains unraveled. It has been proposed that the mesentery behaves as a source of inflammatory mediators, indicating that this organ may contribute to a proinflammatory state. This is supported early on by the obesity model, which suggests that the mesentery acts as both a local and systemic producer of adipokines and proinflammatory cytokines, such as tumor necrosis factor alpha (TNF-α), interleukin (IL)-6, and IL-8 (7–9). These mediators have been implicated in the development of metabolic syndrome and coronary artery disease (10,11).

Crohn, Ginzburg, and Oppenheimer initially documented the involvement of the mesentery in CD in 1932 (12). The common features described are hypertrophy and wrapping of the mesentery around the inflamed segment of the bowel, known as a creeping fat (13). The mesentery contains the main depot of visceral adipose tissue (VAT). Specifically, various studies have used the mesenteric adipose tissue (MAT) measurements as a surrogate indicator of mesentery hypertrophy. In addition, several studies have associated a higher MAT with a more complicated phenotype (14–20) and poor outcomes, including increased clinical disease activity, a greater risk of flare, a higher likelihood of surgery, hospitalizations, and endoscopic recurrence (14,15,18,21–27).

Despite the availability of multiple therapeutic options, a significant proportion of patients with CD fail to achieve sustained remission. This has prompted ongoing efforts to better understand disease mechanisms and identify novel predictive factors for treatment response. Exploring the association between MAT and responses to biologic treatments may enhance our comprehension of nonresponse mechanisms and support optimized strategies for dosing and therapeutic positioning of biologics.

To date, only 2 studies have evaluated MAT quantified as volume using computed tomography (CT) to predict response to anti-TNF-α therapy (28,29). The first study (28) involved a nonbiologic-naïve population with a high prevalence of obesity, which may limit its generalizability. The second study focused on radiomic analysis and developed a model to predict a high risk of primary nonresponse to infliximab therapy, without providing longer term outcome data (29). Owing to this limited evidence, the role of the fat mesentery in influencing treatment response remains poorly understood.

We hypothesized that increased MAT, measured by volume, may contribute to worse response to biologic therapy and a higher risk of CD surgery. Accordingly, we aimed to analyze the impact of mesentery volume on treatment response to anti-tumor necrosis factor-alpha (TNF-α) therapy in a well-defined cohort of biologic-naïve patients with CD.

MATERIALS AND METHODS

We conducted a retrospective study at Gregorio Marañón Hospital, a tertiary referral center for inflammatory bowel disease (IBD) in Madrid, Spain. We included consecutive patients with active Crohn's disease (CD) who underwent a CT scan or MRI at our center within 6 months before the initiation of anti-TNF-α therapy. The patients were enrolled between 2012 and 2021, and none had received biologic therapy before this study. All patients had luminal active disease based on biochemical, endoscopic, or radiologic findings. We excluded patients who had previous bowel resection, those with a follow-up period shorter than 12 months unless they underwent surgery or withdrawal of biologic agents due to drug failure or a diagnosis of cancer. For recruitment, we used a prospective registry from the Pharmacy Department of our institution, which precisely identified patients who received biologic therapies during the study period. The study was approved by the local Clinical Research Ethics Committee of the Hospital General Universitario Gregorio Marañón and waived the requirement for informed consent to participate.

Clinical variables at baseline

We obtained demographic data, along with main anthropometric measurements, including weight (Kilograms, Kg) and height (meters, m), from a review of medical records at the time of the baseline radiologic images. In addition, we reviewed phenotypic characteristics according to Montreal's Classification (30) and noted the occurrence of extraintestinal manifestations. We collected whether concomitant steroid treatment was necessary. The anti-TNF-α agents included were infliximab or adalimumab. The standard doses for infliximab induction therapy were 5 mg/kg at weeks 0, 2, and 6, followed by a maintenance phase with infusions every 8 weeks. For adalimumab, the standard induction regimen included 160 mg at week 0 and 80 mg at week 2, followed by a maintenance dose of 40 mg every 2 weeks.

Acquisition of MAT volume and other radiographic parameters

The image readings were analyzed by the same radiologist expert in IBD, who was blinded to the clinical data. Mesenteric volume measurement was performed using a multidetector CT or MRI scan. Complete abdominal and pelvic region images were acquired after intravenous contrast administration in the portal phase for each patient included in the analysis.

All images were processed using the IntelliSpace Portal software (Philips) and its 3D Volume application. Tissues with a standard attenuation threshold between −50 and −150 Hounsfield units were selected to identify MAT. Subsequently, the entire intrabdominal mesenteric fat was manually delineated, excluding subcutaneous adipose tissue, preperitoneal fat, and retroperitoneal fat. The mesenteric fat volume was then calculated. The results (mean with SD) were expressed in cubic centimeters (cm³). The same method was applied to images acquired with a 1.5T MRI in the T2 phase, calculating the volume in absolute values to minimize post-processing errors. MAT can be accurately assessed using CT or MRI (31,32). To exclude discrepancies of mesenteric volume quantification across imaging modalities in our cohort, a sensitivity analysis was conducted in 10 individuals who underwent both CT and MRI within a short interval. MAT volume estimates obtained from both modalities demonstrated high concordance. Figure 1 illustrates an example of MAT volume quantification.

Figure 1.

Evaluation of the absolute mesenteric adipose tissue volume using computerized tomography scan. Blue represents mesenteric adipose tissue. AV, average value; HU, Hounsfield units; WL, window level; WW, window width.

In addition, the radiologist reviewed specific findings described in the Consensus Recommendations for patients with small bowel CD (33). These findings included the presence of strictures, ulcerations, perienteric edema, fistulizing disease (excluding perianal disease), vascular engorgement, segmental mural hyperenhancement, wall thickening, inflammatory mass, and abscess. We also reviewed the development of fibrofatty proliferation of the mesentery which was defined by identifying an affected loop separated from other structures by surrounding fatty tissue. In addition to the previous findings, we calculated the thickness of the subcutaneous tissue (mm) measured at the umbilical level section.

Outcomes

The primary outcomes were evaluated at 3 and 12 months after the initiation of anti-TNF-α therapy. The defined end points included dose intensification, surgery, and withdrawal of anti-TNF-α treatment. Anti-TNF-α dose intensification was defined as either shortening the time interval between anti-TNF-α doses, increasing the anti-TNF-α dose, or using both approaches. Reasons for treatment withdrawal were reviewed and classified as due to inefficacy or adverse events.

Secondary outcomes included clinical and biochemical variables related to the response to therapy. Secondary outcomes were also evaluated at 3 and 12 months. Clinical response was defined as a reduction of 3 or more points in the Harvey‐Bradshaw index from baseline; clinical remission was identified as an Harvey‐Bradshaw index of 4 or less. We also evaluated whether MAT volume was associated with biochemical markers of inflammation, such as hemoglobin, platelets, leukocytes, fibrinogen, C-reactive protein, and fecal calprotectin. The laboratory parameters were recorded at baseline (at the time of CT or MRI imaging), at 3 months, and at 12 months after the initiation of biologic therapy.

Statistical analysis

Continuous variables were expressed as medians with interquartile ranges (IQR). Categorical variables were presented as the number of cases and percentages. We used the Mann-Whitney U test or the Kruskal-Wallis test for continuous variables, and the χ² test or the Fisher exact test for categorical variables, as appropriate. Measures of MAT volume and anthropometric and demographic variables were compared using Spearman correlation analysis, and a significant correlation was considered if the P-value was less than or equal to 0.05.

A multivariable logistic regression model was performed for each outcome to identify MAT volume as an independent risk factor of worse response to anti-TNF-α therapy. MAT volume was analyzed as a continuous variable, and odds ratios were expressed per 100 cm³ increase to improve clinical interpretability. Odds ratios were adjusted (OR^a) for age and body weight (kg). Body weight was selected instead of body mass index (BMI) to avoid collinearity and because MAT volume showed no correlation with height, supporting its role as a regional visceral adiposity measure rather than a surrogate of overall body size. The variance inflation factor (VIF) of the variables was examined, and a value lower than 5 was used to exclude the presence of statistical multicollinearity.

Subsequently, we developed a predictive model. Both predictive models were developed using multivariable logistic regression. For each outcome, the variable selection was based on a combination of clinical assessment and a stepwise forward selection approach using the lower Akaike information criterion to determine which factor best explained the outcome. Then, we designed a receiver operating characteristic curve to assess the appropriate score of sensibility and specificity. To determine the optimal threshold for classification, the Youden index was applied. A P-value less than or equal to 0.05 was considered statistically significant. All data analysis was performed using R statistical software (Version 2023.12.1)

RESULTS

Baseline characteristics

The cohort consisted of 50 patients diagnosed with CD who were not exposed to biologic agents. Figure 2 displays the study flow chart. The median age of the cohort was 35.70 (IQR: 26.72–44.74), with a predominance of male patients (64%). Regarding anthropometric measures, the median weight was 63 kg (56–72). Most of the patients had a normal BMI level (23.31, IQR: 20.07–25.48). Twelve patients (26.7%) were classified as overweight (BMI 25–29.9 kg/m²), whereas only 2 patients (4.4%) met criteria for obesity. According to the Montreal Classification, half of the patients exhibited ileal involvement (L1). The baseline characteristics of the patients are shown in Table 1. We also compared MAT volume based on baseline characteristics. We found that the ileal phenotype had significantly higher MAT volume compared with the other disease localizations (L2 and L3) (Table 2 and Figure 3).

Figure 2.

Study flowchart. CT, computerized tomography.

Table 1.

Baseline characteristics of the cohort of patients diagnosed with Crohn's disease

Patient´s characteristics	Total cohort
	N = 50
Sex, male	32 (64)
Age, yr	35.70 (26.72–44.74)
Min-Max	14–81
Weight, Kg	63 (56–72)
Min-Max	44–100
Height, cm	168.0 (163.0–175.0)
Min-Max	155.0–191.0
BMI, kg/m2	23.31 (20.07–25.48)
BMI categories
Underweight, <18.5 kg/m2	6 (13.33)
Normal weight, 18.5–24 kg/m2	25 (55.56)
Overweight, 25–29.9 kg/m2	12 (26.67)
Obesity, ≥30 kg/m2	2 (4.44)
Smoking habit
Nonsmoker	23 (46)
Former smoker	16 (32)
Active smoker	11 (22)
Family history of IBD	9 (18)
Diabetes mellitus	2 (4)
Hypertension	10 (20)
Appendicectomy	5 (10)
PSC	1 (2)
Disease duration, yr	0.34 (0.00–4.08)
Montreal classification
Age, yr
A1 (≤16)	2 (4)
A2 (17–40)	41 (82)
A3 (>40)	7 (14)
Location
L1 (ileal)	25 (50)
L2 (colonic)	8 (16)
L3 (ileocolonic)	17 (34)
+L4 (upper GI)	8 (16)
Behavior
B1 (inflammatory)	16 (32)
B2 (stenosing)	9 (18)
B3 (fistulizing)	25 (50)
+p (perianal)	18 (36)
EIMs	17 (34)
Musculoskeletal	8 (16)
Ocular	4 (8)
Mucocutaneous	9 (18)
Previous corticosteroid therapy	46 (92)
Concomitant corticosteroid therapy	31 (62)

Continuous variables were expressed as medians with their interquartile range (IQR). Categorical variables were presented as a number of cases and percentages (%).

BMI, body mass index; EIMs, extraintestinal manifestations; IBD, inflammatory bowel disease; GI, gastrointestinal; PSC, primary sclerosing cholangitis.

Table 2.

Baseline clinical characteristics by MAT volume

Total cohort (n = 50)	MAT volume (cm3)	P-value
Variable	Median (IQR)
Sex
Male	557.49 (416.60–1,162.78)
Female	601.56 (396.15–816.48)	0.596
Montreal classification
Localization
L1 (ileal)
L2 (colonic)	804.15 (483.29–1,203.59)
L3 (ileocolonic)	503.80 (394.90–1,150.66)
+L4 (upper GI)	461.95 (335.60–559.58)
Behavior	784.87 (445.50–1,174.88)
B1 (inflammatory)	510.67 (426.48–1,042.75)	0.022
B2 (stenosing)	758.97 (483.81–1,345.27)	0.458
B3 (fistulizing)	555.40 (396.15–804.15)	0.644
+p (perianal)	491.07 (425.10–1,296.83)	0.818
Smoking habit
Nonsmoker	643.72 (416.60–965.99)
Former smoker	637.62 (393.90–784.87)
Active smoker	483.29 (410.62–1,054.60)	0.948
Diabetes mellitus, yes	730.50 (555.40; 905.60)	0.620
Hypertension, yes	802.02 (559.39; 1,004.50)	0.158
EIMs	731.59 (452.20; 850.98)	0.440

Values are presented as median (IQR) for MAT volume in cubic centimeters (cm³). P-values were calculated using the Mann-Whitney U test for binary variables and the Kruskal-Wallis test for categorical variables with more than 2 levels.

EIMs, extraintestinal manifestations; MAT, mesenteric adipose tissue.

Figure 3.

Boxplot of MAT volume stratified by disease phenotype (L1: Ileal, L2–L3: Colonic or ileocolonic). Patients with isolated ileal involvement showed significantly higher MAT volume compared with those with colonic or ileocolonic involvement (P = 0.011, Mann-Whitney test). Black dots represent group means. Boxes indicate IQRs; whiskers denote 1.5× IQR. MAT, mesenteric adipose tissue.

A review of the radiologic findings and MAT volume calculations was conducted on 37 CT scans and 13 MRIs. As previously mentioned, a sensitivity analysis was performed in 10 individuals who underwent both CT and MRI to assess the concordance of mesenteric volume quantification. In the subgroup of patients who underwent both CT and MRI, MAT volume measurements showed good concordance between imaging modalities (see Supplementary Figure S1, Supplementary Digital Content, http://links.lww.com/CTG/B471).

The median MAT volume was 559.5 cm³ (IQR: 410.3–891.9). The recorded minimum volume was 47.3 cm³, whereas the maximum reached 2086.1 cm³. PFM, defined as which was defined by identifying an affected loop separated from other structures by surrounding fatty tissue. It was observed in 27 patients (55.10%). In addition, deep ulcers were identified in 32.65% of cases. Table 3 illustrates the radiologic findings of the cohort.

Table 3.

Radiological characteristics of the cohort of patients diagnosed with Crohn's disease

Patient´s characteristics	Total cohort
	N = 50
Imaging modality
MRI	13 (26)
CT	37 (74)
MAT volume, cm3	559.5 (410.3–891.9)
Min-max	47.3–2086.1
Stenosis	15 (30.61)
Ulcers	16 (32.65)
Perienteric edema	25 (51.02)
Engorged vasa recta	25 (51.02)
Fistulizing disease	25 (50)/19 (38.77551)
Mural thickening, mm	6 (5–9)
Mural enhancement after i.v. contrast	34 (69.39)
Inflammatory mass (Flegmon)	10 (20.41)
Abscess	9 (18.37)
Fibrofatty proliferation	27 (55.10)

Continuous variables were expressed as medians with their interquartile range (IQR). Categorical variables were presented as a number of cases and percentages (%).

CT, computed axial tomography; i.v: intravenous; MAT: mesenteric adipose tissue.

MAT volume correlated with body weight and age in patients with CD

Spearman correlation analysis revealed a significant relationship between MAT volume and body weight (Figure 4c), as well as between MAT volume and BMI (Figure 4b). Similarly, MAT volume was correlated with age (Figure 4a). We also found a positive correlation between MAT and subcutaneous thickness (R = 0.66, P < 0.001). However, no correlation was found between MAT volume and height (Figure 4d) or disease duration (data not shown). Furthermore, we did not observe a significant correlation between body weight and patient age (P = 0.391) (data not shown).

Figure 4.

Scatter plot illustrating the Spearman correlation between MAT volume and (a) age, (b) BMI, (c) body weight and (d) height, in patients with Crohn's disease. A significant positive association was found (R = 0.66; P < 0.001), indicating that an increase in body weight was associated with an increase in MAT volume. Body weight was measured in kilograms (Kg), and MAT volume was measured in cubic centimeters (cm³). R represents the Spearman correlation coefficient; p denotes the P-value of statistical significance, and the continuous grey line shows the linear regression. BMI, body mass index; MAT, mesenteric adipose tissue.

MAT volume was associated with poor response to anti-TNF-α treatment

All 50 patients received anti-TNF-α therapy as first advanced therapy: 28 (56%) were treated with infliximab and 22 (44%) with adalimumab. Concomitant corticosteroid use was reported in 62% of patients, and 92% had a previous history of corticosteroid exposure before starting anti-TNF-α agents.

At 3 months, 8 patients required dose escalation, whereas this number rose to 42 patients by month 12. The multivariable logistic regression model indicated that elevated MAT volume was also associated with a higher rate of anti-TNF-α dose escalation at 12 months (OR^a: 1.36; 95% CI: 1.08–1.81; P = 0.016; Table 4 and Figure 5).

Table 4.

Regression logistic analysis: MAT as an independent risk factor for poor response to anti-tumor necrosis factor-α treatment

Independent variable	Dependent variables (primary outcomes)	ORa (CI 95%)	P-value
MAT volume, 100 cm3	Surgery at 3 months	1.65 (1.08–3.05)	0.048
	Dose intensification therapy at 3 mo	1.26 (0.94–1.73)	0.127
	Withdrawal treatment at 3 mo	0.91 (0.39–1.62)	0.782
	Surgery at 12 mo	1.33 (1.00–1.85)	0.061
	Dose intensification therapy at 12 mo	1.36 (1.08–1.81)	0.016
	Withdrawal treatment at 12 mo	1.21 (0.98–1.53)	0.087

Primary outcomes for treatment response based on MAT volume were evaluated at 3 and 12 months. Primary outcomes were surgery, disease intensification therapy, and withdrawal treatment.

OR^a are reported per 100 cm³ increase in MAT volume.

MAT, mesenteric adipose tissue; OR^a, odds ratio adjusted for both age and body weight.

Figure 5.

Regression logistic analysis: MAT as an independent risk factor for poor response to anti-tumor necrosis factor-α treatment. Primary outcomes for treatment response based on MAT volume were evaluated at 3 and 12 months. Primary outcomes were surgery, disease intensification therapy, and withdrawal treatment. Red dots represent odds ratio adjusted (OR^a) for both age and body weight, and error bars indicate 95% CIs; MAT, mesenteric adipose tissue.

Surgical intervention was undergone in 5 patients within the first 3 months, rising to 9 patients (18%) at 12 months of starting anti-TNF-α therapy. In addition, 16 patients discontinued anti–TNF-α therapy within the first year of treatment, of whom only 1 discontinued treatment due to an adverse event, whereas all remaining discontinuations were related to treatment inefficacy. Given the very low number of adverse-event-related discontinuations, withdrawal outcomes were analyzed as a composite end point. A higher MAT volume was independently associated with an increased risk of surgery at 3 months (OR^a: 1.65; 95% CI: 1.08–3.05; P = 0.048; Table 4 and Figure 5). At 12 months, a trend toward a similar association was observed (OR^a: 1.33; 95% CI: 1.00–1.85; P = 0.061; Table 4 and Figure 5). Furthermore, we calculated the VIF to assess collinearity among the variables, and all VIF values were less than 2, indicating no significant multicollinearity.

Additional multivariable logistic regression analyses were performed using body weight and BMI as independent predictors of treatment outcomes at 3 and 12 months. Neither body weight nor BMI independently predicted surgery, dose intensification therapy, or treatment withdrawal (see Supplementary Tables S2A and S2B, Supplementary Digital Content, http://links.lww.com/CTG/B471). By contrast, MAT volume remained significantly associated with poor treatment response.

As secondary outcomes, no association was observed between MAT volume and clinical response or remission, as measured by the Harvey-Bradshaw Index, at either 3 or 12 months (Table 5). Likewise, no correlation was found between MAT volume and laboratory parameters at baseline, 3, and 12 months.

Table 5.

Regression logistic analysis: MAT as an independent risk factor for poor response to anti-tumor necrosis factor-α treatment

Independent variable	Dependent variables (secondary outcomes)	ORa (CI 95%)	P-value
MAT volume, 100 cm3	Clinical remission at 3 mo	0.86 (0.69–1.05)	0.167
	Clinical response at 3 mo	0.95 (0.77–1.15)	0.583
	Clinical remission at 12 mo	0.99 (0.80–1.24)	0.915
	Clinical response at 12 mo	1.01 (0.83–1.25)	0.906

OR^a are reported per 100 cm³ increase in MAT volume.

Secondary outcomes for treatment response based on MAT volume were evaluated at 3 and 12 months.

MAT, mesenteric adipose tissue; OR^a, odds ratios adjusted for both age and body weight.

MAT volume predicted the risk of dose intensification of anti-TNF-α treatment and the risk of surgery at 12 months.

We developed 2 predictive models to assess the response to biologic therapy at 12 months in a cohort of biologic-naïve patients with CD. The first model was designed to predict dose intensification of anti-TNF-α therapy, whereas the second aimed to estimate the risk of surgical intervention within the first year of anti-TNF-α treatment.

The first prediction model was constructed using multivariable logistic regression analysis (Figure 6), incorporating both clinical and radiological variables, including MAT volume and the presence of perienteric edema. Variable selection was performed using a forward stepwise selection approach. The model demonstrated robust discriminative capacity, with an area under the curve of 0.83 (95% CI: 0.70–0.96). Using the optimal classification threshold determined by the Youden index, the model achieved a sensitivity of 95% and a specificity of 71% for predicting dose intensification within the first year of therapy.

Figure 6.

Predictive model of treatment intensification within the first year of anti-tumor necrosis factor-α therapy. (a) ROC curve of the predictive model. The diagonal dotted black line represents the performance of a diagnostic test with no discriminatory ability, equivalent to random chance, yielding an area under the curve of 0.5. Red dot indicated the Youden index. (b) The ROC curve was built from the logistic regression analysis. MAT, mesenteric adipose tissue; ROC, receiver operating characteristic; OR, odds ratio.

The second predictive model assessed the need for surgery within the first year after initiating biologic therapy. The model included both clinical and radiological variables, and the forward stepwise method was used for variable selection. We estimated an area under the curve of 0.89 (95% CI: 0.71–0.1) on the receiver operating characteristic curve, enabling discrimination between patients who required surgical intervention and those who did not. By determining an optimal classification threshold using the Youden index, the model achieved a sensitivity of 88.89% and a specificity of 76.92% in predicting the need for surgery 1 year after initiating biologic treatment (Figure 7).

Figure 7.

Predictive model of surgery within the first year of anti-tumor necrosis factor-α therapy. (a) ROC curve of the predictive model. The diagonal dotted black line represents the performance of a diagnostic test with no discriminatory ability, equivalent to random chance, yielding an area under the curve of 0.5. Red dot indicated the Youden index. (b) The ROC curve was built from the logistic regression analysis. MAT, mesenteric adipose tissue; OR, odds ratio; ROC, receiver operating characteristic.

DISCUSSION

The present study demonstrates that higher absolute MAT volume independently predicted a poor response to anti-TNF-α treatment in a well-defined bio-naïve patient cohort. Our results showed that MAT volume was associated with a greater need for dose intensification of anti-TNF-α agents within 12 months and a higher risk of CD surgery—i.e., primary nonresponse—within 3 months. In addition, we developed 2 predictive models to estimate the risk of dose intensification of anti-TNF-α therapy and CD surgery after 12 months of initiating anti-TNF-α therapy. These models should be interpreted as exploratory and hypothesis-generating, given the limited sample size, and are not intended for immediate clinical implementation.

MAT is proposed to be actively implicated in CD (6). Investigating MAT remains challenging, primarily because its direct assessment relies on invasive methods involving surgical specimens. As a result, noninvasive imaging techniques have emerged as valuable tools for assessing MAT. Despite increasing attention, MAT metrics have not been thoroughly studied in this field.

We examined clinical variables associated with MAT volume in patients with CD at the time of imaging. Our findings showed that absolute MAT volume presented a direct correlation with the BMI. These results align with observations in patients with CD, where MAT measured as area has also been shown to be positively correlated with BMI (34,35). Our results are also consistent with studies that measured MAT as a volume, in which higher values were associated with higher BMI (18,28,36). In our study, the association between MAT and BMI seems to be mainly attributable to body weight, as MAT volume was correlated with body weight but not with height. BMI is a simple clinical tool, but may not accurately reflect visceral fat accumulation, because it does not distinguish between adipose tissue and lean body mass (37). Furthermore, weight loss due to malnutrition is commonly observed in individuals with CD (38). BMI does not appear to be a reliable predictor of postoperative outcomes (39) nor anti-TNF-α treatment response. A large, pooled analysis using data from 4 clinical trials of infliximab in IBD (ACCENT-I, SONIC, ACT-1, and -2) found no significant differences in treatment response based on BMI (40). Importantly, MAT volume should not be considered interchangeable with BMI. Consistently, in additional multivariable analyses, neither body weight nor BMI independently predicted treatment outcomes, whereas MAT volume remained significantly associated with poor response to anti–TNF-α therapy. Although BMI reflects global body mass, it does not distinguish between lean mass and fat mass nor capture regional fat distribution. By contrast, MAT represents a specific visceral adipose compartment closely linked to intestinal inflammation and may therefore provide biologically and clinically distinct information.

Beyond its association with BMI and body weight, we also investigated whether MAT volume correlates with age, given that it is commonly linked to a progressive accumulation of abdominal fat throughout the adult lifespan in healthy subjects (41). In a chronic inflammation state, our analysis revealed a significant positive correlation between MAT volume and age, in agreement with previously published studies (18,28,36).

Recent evidence has yielded conflicting results regarding the impact of MAT on treatment outcomes. Although some literature has suggested that increased MAT may not be a consistent predictor of response to biologic therapy (42), others have identified it as a risk factor for worse treatment outcomes (21,28,29,35,43,44). The published studies are heterogeneous, making direct comparisons challenging. This limitation may reflect differences in study design, patient populations, and methods used to quantify MAT. The study populations vary significantly between studies, some included patients with both types of inflammatory bowel diseases, including ulcerative colitis and CD, or individuals previously exposed to biologic therapy. It is also important to note that in some studies, the terms VAT and MAT have been used interchangeably, despite referring to distinct anatomical entities. By definition, VAT includes all intra-abdominal fat depots, whereas MAT is a specific component of VAT that consists of the fat attached to and surrounding the intestines, and is actually the largest fraction of the VAT compartment (45). In addition, most studies assess MAT area rather than MAT volume. Quantifying mesenteric volume provides a more comprehensive and physiologically relevant assessment of mesenteric fat involvement. Although area measurements offer a two-dimensional approximation, they may not estimate well the extent of adipose tissue, especially in cases where fat accumulation is irregular or distributed across multiple planes. By contrast, volume measurement captures the three-dimensional axis of mesenteric fat, allowing for a more accurate evaluation. So, most of the previous studies had assessed MAT using cross-sectional area measurements, only 2 publications had quantified volume using imaging. In the first study, absolute MAT volume was associated with TNF-α antagonist response in a non-dose-response manner, with patients exhibiting moderate MAT volumes achieving higher clinical response rates compared with those with low or high volumes (28). The second study performed a radiomic analysis of MAT to predict primary non-response to infliximab, although long-term outcomes were not evaluated (29). Notably, the Constellation study extended the scope beyond infliximab, demonstrating that an increased intra-abdominal MAT burden was significantly associated with non-response to infliximab, vedolizumab, and ustekinumab (43). However, MAT was measured by Dual-energy x-ray absorptiometry.

Such evidence highlights the need to better understand the role of the mesentery in modulating chronic intestinal inflammation. There is still controversy about whether the mesentery functions as an organ that limits or promotes the inflammatory process (4,46). Our findings support the hypothesis that the mesentery contributes to a proinflammatory state, which may hinder the therapeutic efficacy of anti-TNF-α agents. We speculate that fat accumulation reflects the degree of systemic inflammation. MAT functions as a source of proinflammatory mediators (7,8). Higher MAT accumulation might denote a more aggressive disease and could partly explain the suboptimal response observed in certain patients undergoing anti-TNF-α therapy. In addition, high MAT accumulation is likely to lead to an unfavorable pharmacokinetic profile for anti-TNF-α response. Excess adipose tissue may increase drug clearance through mechanisms such as accelerating proteolytic degradation (47) and the ‘TNF sink’ phenomenon, where the sequestration of anti-TNF agents by excess adipose-derived TNF leads to lower circulating drug concentrations (48).

In our study, we found that patients with higher MAT volume were more likely to require anti-TNF-α dose intensification within 12 months. Supporting this, 2 retrospective studies have shown that infliximab trough levels are inversely correlated with MAT area (35,44). A similar negative correlation has been observed with MAT metric volume and infliximab trough levels, but not with adalimumab (28). However, the ability to draw firm conclusions is restricted by the reactive therapeutic drug monitoring strategy. Because not all individuals underwent systematic monitoring; this selective testing may introduce measurement bias and limit the generalizability of the results. There is literature suggesting that individuals with increased visceral fat accumulation may require higher infliximab concentrations to achieve remission (49).

Besides the need for dose intensification, our analysis revealed that a higher MAT volume was associated with an increased risk of undergoing surgery within the 3 months—indicating, presumably, an anti-TNF primary non-response—and trended toward 6 months after anti-TNF-α initiation. Our findings are consistent with previous retrospective studies, which have shown that MAT is a factor associated with a higher risk of surgery in IBD cohorts (15,18). MAT has also been associated with a more complicated phenotype (structuring or fistulizing behavior) (14–18). We did not observe these findings, which may be explained, at least in part, by an insufficient sample size. However, we identified that ileal involvement had higher MAT volume compared with ileocolonic or colonic involvement. In earlier studies, different outcomes were reported based on localization, with the ileal phenotype showing poor efficacy of infliximab therapy (44).

We also examined the relationship between MAT and the disease activity index after the start of anti-TNF-α treatment; however, the results were not statistically significant. Previous literature has presented conflicting results: some studies have indicated a relationship between MAT and clinical disease activity (14,21), whereas other studies have not (20,50). Discrepancies with earlier literature may reflect differences in patient selection and the use of varying disease activity indices, as well as the aforementioned insufficient sample size.

The strengths of the study include the measurement of MAT using volume instead of area, as this approach better captures the heterogeneity of fat distribution in patients with CD. We specifically focused on MAT rather than total VAT, as it offers a more accurate evaluation of mesenteric fat due to its close association with gut inflammation and disease. Another key strength is that all included patients had CD and were bio-naïve, which minimizes the change in MAT composition from other biologics. Commonly, the studies included populations with a high rate of obese patients, making it difficult to generalize to other patients. In our cohort, only 2 patients met criteria for obesity.

This study has several limitations. Its retrospective design and small sample size limited the availability of objective disease activity measures, requiring the use of surrogate outcomes. Nevertheless, all mesenteric volumetric assessments were performed by experienced radiologists blinded to clinical outcomes, ensuring unbiased image analysis, although inter-rater reliability could not be assessed as measurements were performed by a single expert reader. In addition, trough levels of infliximab and adalimumab were not available for most patients, precluding correlations between MAT volume and drug concentrations; however, empirical dose intensification, a commonly strategy to regain response (50), was used as an accepted surrogate variable of loss of response. A comprehensive body composition assessment was not feasible, including evaluation of skeletal muscle mass and alternative adiposity measures such as waist circumference or longitudinal weight trends. Future prospective studies incorporating detailed body composition analyses are warranted to further clarify the relationship between MAT and treatment response. Finally, the proposed predictive models require external validation in larger, independent cohorts before any potential clinical application.

In summary, our study identified increased MAT volume as an independent predictor of poor response to anti-TNF-α agents in a biologic-naïve CD population. After adjusting for anthropometric and demographic variables, MAT volume was associated with an increased risk of requiring dose intensification of anti-TNF-α therapy and the risk of undergoing CD surgery. These findings suggest that quantification of visceral adiposity may serve as a clinically relevant marker for identifying CD at risk of suboptimal response to anti-TNF-α therapy. In addition, our results further underline the relevance of the mesentery in CD pathophysiology.

CONFLICTS OF INTEREST

Guarantor of the article: Luis Menchén, MD, PhD.

Specific author contributions: H.M.-L.: data collection, data analysis, writing up of the first draft of the paper. J.M.-O.: MAT volume analysis. C.I.: data collection. J.M.-B.: data collection. M.P.: data analysis. I.M.-J.: data collection. E.R.: study design, MAT volume analysis. L.M.: study design, data analysis, writing up of the final manuscript.

Financial support: This project was supported by Fondo de Investigación Sanitaria, Instituto de Salud Carlos III (PI19/01746).

Potential competing interests: H.M.-L. has received support for congress and conference attendance, from, Abbvie, Johnsson&Johnsson, Alfa-sigma, Tillotts, Takeda, Pfizer and Ferring. J.M.-O., C.I., J.C.G.-B. declare no conflicts of interest. J.M.-B. has received support for congress and conference attendance, from Abbvie, Johnsson&Johnsson, Takeda, Pfizer and Ferring. I.M.-J. has served as a speaker, consultant or advisory member for or has received unrestricted grants from MSD, Abbvie, Takeda, Johnsson&Johnsson, Pfizer, Biogen, Alfa-sigma, Kern Pharma, Lilly, Adacyte, Ferring and Dr Falk Pharma. M.P. has received support for congress attendance from Pfizer. I.B. has served as a speaker, consultant or advisory member for Novo Nordisk, Lilly, Boeringher, Nutricia, Nestlé, Persan, Vegenat, Abbott. E.R. declares no conflict of interest. L.M. has served as a speaker, consultant or advisory member for or has received unrestricted grants from MSD, Abbvie, Takeda, Johnsson&Johnsson, Pfizer, Biogen, Alfa-sigma, Kern Pharma, Lilly, Adacyte, Tillotts, Dr Falk Pharma, Ferring, Medtronic and General Electric.

Data availability statement: The data underlying this article will be shared on reasonable request to the corresponding author.

Study Highlights.

WHAT IS KNOWN

• ✓ Mesentery is as a source of inflammatory mediators in Crohn's disease.

• ✓ Mesentery hypertrophy in Crohn's disease is associated with a more complicated phenotype.

WHAT IS NEW HERE

• ✓ Mesenteric adipose tissue (MAT) volume is associated with a higher rate of anti-TNF-α dose escalation at 12 months.

• ✓ MAT volume is also associated with an increased risk of surgery at 3 months after anti-TNF-α start.

• ✓ Prediction models including MAT volume accurately predict dose intensification and need for surgery within the first year of anti-TNF-α therapy in Crohn's disease.

Supplementary Material

ct9-17-e00993-s001.pdf ^{(245.2KB, pdf)}

ABBREVIATIONS:

CD

Crohn's disease

MAT

mesenteric adipose tissue

TNF-α

tumor necrosis factor alpha

VAT

visceral adipose tissue

VIF

variance inflation factor