Abstract
Preserving gut integrity is essential to preventing the development of chronic diseases. Several factors are associated with gut integrity and inflammation in adults. However, there is limited evidence in healthy children. This study evaluated the factors associated with gut integrity and inflammation in healthy children participating in the MetA Bone trial. We hypothesized that age, sex, race/ethnicity, diet, vitamin D and body composition will be associated with gut integrity and inflammation. Socio-demographic variables were collected with a questionnaire. Measures included markers of gut integrity (Intestinal Fatty Acid Binding Protein; I-FABP), and inflammation (IL-17 and calprotectin) determined by ELISA in 24-h urine and serum; serum 25(OH)D levels (commercial lab), BMI percentile, and diet (24-hr recalls). Analyses included descriptive statistics, chi-square, and adjusted logistic regressions. Participants (n=138) median age was 12.4 [11.1–13.3], 53.6% were male, 9.4% were Black/African American, and 71.1% were Hispanic/Latino. Children with suboptimal vitamin D status were 3.35 times more likely to present gut integrity damage (elevated I-FABP) than those with optimal status (P=0.005). Overweight/obesity and fructose intake were associated with inflammation (elevated calprotectin) (P<0.05). Those with lower gut integrity damage had lower odds of having higher inflammation (P=0.021). Other factors were not associated with inflammation. Suboptimal vitamin D status, overweight/obesity and inflammation may compromise the gut integrity in healthy children, suggesting an impairment on the intestinal barrier repair system. More research with a longitudinal design is needed to gain a deeper understanding of the role of additional factors linked to gut integrity and inflammation in healthy children.
Keywords: vitamin D, overweight/obesity, gut integrity, inflammation, children
1. Introduction
The gut barrier is an anatomical structure that divides the intestinal lumen from the internal host to shield against pathogenic microorganism invasion and maintain mucosal immunity [1–4]. The architecture of this structure is mainly supported by protein complexes called tight junctions located in the apical surface of the adjacent intestinal epithelial cells [5]. Tight junctions prevent the passage of large molecules into the systemic circulation playing an essential role in gut permeability [5]. Disruption of the gut integrity and increased intestinal permeability are directly associated with health, since barrier dysfunction promotes inflammation and the pathogenesis of chronic diseases [6,7].
Several factors seem to influence gut integrity and permeability in adults including genetic predisposition, diet, changes in gut microbiome composition, certain drugs, alcohol, environmental factors, among others [8]. One of the most noticeable factors influencing gut integrity and permeability is the gut microbiome. The gut microbiome is a community of microorganisms that impacts the physiology and functioning in the gastrointestinal tract [9]. Changes in the composition of the gut microbiome directly affect the tight junctions, increasing gut permeability, promoting inflammation, and therefore the development of metabolic diseases [2,10,11]. There is vast evidence showing the associations between gut microbiome composition, gut permeability and the development of chronic diseases in adults [12]. In children, the gut microbiome composition has been linked to several conditions, including undernutrition, obesity, gastrointestinal disorders, cardiovascular disease, allergies, and autism, among others [13]. However, evidence on the factors that affect gut integrity and permeability in healthy children and adolescents is limited. Recently, a study found that race and ethnicity significantly contribute to the gut microbiome composition after three months of age and continue through childhood potentially affecting the gut integrity [14]. Given the context of health disparities, it is believed that race and ethnicity are key factors that pose inequitable exposure to social and environmental determinants of children’s health that affects dietary patterns and gut integrity [14]. Since the evidence on factors other than the gut microbiome are associated with gut integrity and inflammation in children is scarce, it is important to investigate these factors as a preventive approach to avoid the development of metabolic disorders in adulthood. Therefore, this study aimed to evaluate the association of factors, other than the gut microbiome, affecting gut integrity and inflammation in minority children and adolescents. We hypothesized that age, sex, race/ethnicity, diet, vitamin D status and body composition will be associated with gut integrity and inflammation. To test this hypothesis, we conducted a cross-sectional study to evaluate the associations between physiological and lifestyle factors, gut integrity and inflammation in children and adolescents.
2. Methods and Materials
2.1. Study design.
This cross-sectional analysis evaluated the association of factors affecting gut integrity and inflammation in minority children and adolescents participating in the MetA Bone trial (grant # 5R01HD098589–03). MetA Bone is a randomized double-blinded placebo-controlled trial evaluating the effects of soluble corn fiber supplementation for one year on bone metabolism in healthy children and adolescents [15]. The primary outcome measures in the parent grant are changes in total and spine bone mineral content between baseline and six months and between baseline and 12 months.
2.2. Study population.
The data for this analysis was taken from the baseline visit of the MetA-Bone Trial. Inclusion criteria for children and adolescents participating in the parent grant were age 9–14 years, low calcium intake (2 or fewer servings of dairy products/day), and serum 25(OH)D ≥20 ng/ml. Exclusion criteria were having chronic illnesses requiring medication use, or use of regular calcium (>200 mg/d) or vitamin D supplements (>400 IU/d). Children and adolescents were recruited through letters, emails, community events, after-school programs, social media platforms, and clinics in South Florida. Parents interested completed a pre-screening questionnaire to assess the eligibility of the child. If eligible, parents were asked to review and sign the consent forms if they were interested in participating. Children and adolescents were asked to review and sign the assent form along with parents if they agree to participate. Once enrolled in the study, participants completed a baseline visit to collect information on measurements including family health history, socio-demographic, sleep, stress, anthropometrics, diet, physical activity, a DEXA scan and blood draw. Participants were instructed to collect urine over a 24-hour period and a fecal sample before randomization.
2.3. Data collection.
This analysis used the following data collected at baseline from the parent grant: socio-demographic, health, anthropometrics, diet, vitamin D status, and gut integrity and inflammatory biomarkers (measured from urine and blood samples). The use of this data was approved by the Institutional Review Board of Florida International University (IRB-23–0044).
2.4. Measures
2.4.1. Socio-demographic data.
Participants completed a socio-demographic and health questionnaire to gather data on age, sex, Tanner stages (a classification system used to track the development of secondary sex characteristics of children during puberty) [16], race, and ethnicity.
2.4.2. Anthropometric measurements.
Weight and height were obtained by trained research staff. Participants wore light clothing, utilizing a standardized scale and a wall-mounted stadiometer. Body Mass Index (BMI) (kg/m2) was calculated. BMI percentiles for sex and age were calculated using the CDC standardized growth charts for children ages 2–20 years. Overweight/obesity status was defined as BMI percentile >85th [17].
2.4.3. Diet.
At baseline, participants were asked to complete three 24-h dietary recalls; the first one was completed in-person during the baseline visit, and the two others were completed in the next few days to represent 2 weekdays and 1 weekend day. The research staff reviewed the participant’s food description with the participant to ensure completeness and correctness. The 24-h dietary recalls were analyzed by a Registered Dietitian using the dietary computer-based analysis software application ‘Nutrition Data System for Research (NDSR)’ developed at the University of Minnesota Nutrition Coordinating Center (NCC). The average of the three 24-h recalls was calculated to estimate dietary intake of energy, total carbohydrates, total fructose, total protein, total fat, total saturated fat, total monosaturated fat, total polyunsaturated fat, omega-3 and omega-6 fatty acids, total fiber and vitamin D.
2.4.4. Gut integrity.
Intestinal Fatty Acid Binding Protein (I-FABP), a marker of gut integrity was used in the analysis and measured in 24-h urine samples. Participants were instructed to collect urine for 24 hours beginning with the second urine void of the day and ending with the first urine of the morning next day. I-FABP was detected using the Human FABP2/I-FABP Quantikine ELISA Kit by R&D Systems (Catalog # DFBP20, Minneapolis, MN, US). For this analysis, we used undiluted urine samples (50 μl) in duplicates according to manufacturer’s instructions. I-FABP is considered a specific biomarker to assess the degree of gut integrity damage because it reflects intestinal injury and translocation that affects the innate barrier function [5,18]. Although I-FABP is preferred to be measured in blood, we measured it in urine as this study was conducted in children with limited blood sample collection as per NIH guidelines. However, urine has been shown to be a valid marker for I-FABP, as this molecule is released when the intestinal mucosa is disrupted, and it is filtered via glomerulus because of its low molecular weight [19,20]. In addition, urinary I-FABP had similar sensitivity and specificity to plasma I-FABP in patients with gastrointestinal diseases [20–22].
2.4.5. Inflammation.
This was assessed in two ways, by measuring IL-17 from 24-hr urine samples as described above and by measuring calprotectin from fasting blood samples. A trained phlebotomist collected fasting blood samples from venipuncture during baseline visit and centrifuged to obtain serum. IL-17 was analyzed using the Human IL-17 ELISA kit by Sigma-Aldrich (Catalog # RAB0262, St. Louis, MO, US). For this analysis, we used undiluted urine samples in duplicates (100 μl) according to manufacturer’s instructions. Although IL-17 is preferred to be assessed in blood, we measured it in urine as this study was conducted in children with limited blood sample collection as per NIH guidelines. However, it has been suggested that urine is also a reliable marker to measure IL-17 and that it correlates well with serum levels in various conditions [23]
Calprotectin was analyzed using the Human Calprotectin ELISA Kit by Hycult Biotech (Catalog # HK379 Wayne, PA, US). For this analysis, fasting blood samples were collected in red top vacutainer tube and centrifugated for 15 minutes at 3000 RPM within one hour of collection to obtain serum samples. We used serum samples with a 20-fold dilution in duplicates (100 μl) according to the manufacturer’s instructions. Studies have suggested that serum calprotectin is considered a good marker to assess inflammation in patients with inflammatory bowel disease as it correlates well with other methods to assess inflammation, and it has a good specificity [24–27].
2.4.6. Vitamin D.
Fasting blood samples were collected in yellow top vacutainer tubes and centrifugated for 15 minutes at 2200 RPM within one hour of collection to obtain serum samples. Serum samples (2ml) were sent to a commercial laboratory (Quest Diagnostics, test code 17306) for total 25(OH)D determination using an immunoassay procedure. Although vitamin D status has been defined by the Institute of Medicine as suboptimal if serum levels are <20 ng/ml for bone health outcomes [28], other organizations have traditionally used <30 ng/ml as suboptimal when associating this to other health outcomes [29,30]. Also, in the present study, we only had a few participants with a level <20 ng/ml. Therefore, in the present analyses, we only used 2 categories for vitamin D status: Suboptimal (if serum levels 0–29.9 ng/ml) and Optimal (if serum levels ≥30 ng/ml).
2.5. Statistical analysis.
Data was examined for outliers and normality. Descriptive statistics, including median, interquartile range, and percentages, were used to describe the data. Gut integrity damage was assessed as high I-FABP (≥ median) and inflammation was assessed as high IL-17 and calprotectin (≥ median). Mann Whitney test was used to assess the median of continuous variables for low and high values (< median ≥) of I-FABP, IL-17 and calprotectin. Chi-square test (X2) was used to compare the proportion of participants with low and high values (< median ≥) of I-FABP, IL-17 and calprotectin and categorical variables. Logistic regressions models were implemented to evaluate factors associated with gut integrity damage and inflammation. In the logistic regression model assessing factors associated with gut integrity damage (I-FABP ≥ median) the following covariates were included age, sex, race, ethnicity and total fiber intake. In the logistic regression models assessing the factors associated with inflammation the following covariates were included age, sex, race, ethnicity, vitamin D levels, total dietary fiber intake, and I-FABP levels. All statistical analyses were performed using SPSS software, version 29.
3. Results
A total of 213 participants were recruited in the parent grant. However, only 138 had collected all the samples needed for this analysis. The median age was 12.4 [11.1–13.3] years and the median Tanner stage was 3.00 [1.25–4.00]. A total of 53.6% were male, 9.4% were Black or African American, 71.1% were Hispanic or Latino, 25.7% had overweight/obesity, and 68.1% had suboptimal vitamin D status (0–29.9 ng/ml) (Table 1). Participants had an inadequate intake of total fiber (12.8 [9.51–17.0] g/d) and vitamin D (3.90 [2.99–6.22] mcg) based on the Recommended Dietary Allowances and Dietary Reference Intake for fiber and vitamin D intake [28,31]. In addition, about half of participants exhibited higher gut integrity damage (I-FABP ≥ median) and higher inflammation (IL-17 and calprotectin ≥ median).
Table 1.
Participant characteristics
| Variable | Total (n=138) |
|---|---|
| Age (years) | 12.4 [11.1–13.3] |
| Sex | |
| Male | 53.6 (74) |
| Race/Ethnicity | |
| American Indian or Alaska Native | 2.9 (4) |
| Asian | 3.6 (5) |
| Black or African American | 9.4 (13) |
| White | 40.6 (56) |
| More than one race | 3.6 (5) |
| No reported Race | 39.9 (55) |
| Hispanic or Latino (yes) | 71.7 (99) |
| Tanner stage | 3.00 [1.25–4.00] |
| Weight category | |
| Normal weight | 74.3 (101) |
| Overweight/obesity | 25.7 (35) |
| Vitamin D status | |
| Optimal (≥30 ng/ml) | 31.9 (44) |
| Suboptimal (0–29.9 ng/ml) | 68.1 (94) |
| Dietary Intake | |
| Energy (kcal) | 1776 [1424–2157] |
| Total Fat (g) | 73.2 [52.7–90.3] |
| Saturated Fat (g) | 23.1 [17.4–34.4] |
| Monosaturated Fat (g) | 23.3 [17.4–29/5] |
| Polysaturated Fat (g) | 15.1 [11.1–20.5] |
| Omega-3 fatty acids (g) | 1.57 [1.12–2.04] |
| Omega-6 fatty acids (g) | 12.8 [9.20–17.4] |
| Total Carbohydrate (g) | 217 [168–254] |
| Fructose (g) | 14.7 [8.42–23.9] |
| Total Protein (g) | 65.5 [53.4–85.2] |
| Total Dietary Fiber (g) | 12.8 [9.51–17.0] |
| Vitamin D (calciferol) (mcg) | 3.90 [2.99–6.22] |
| I-FABP (pg/mL) n=138 | 25.6 [13.0–50.5] |
| Above the median (≥25.6) | 50.0 (69) |
| IL-17 (pg/ml) n=125 | 35.7 [15.0–87.5] |
| Above the median (≥35.7) | 50.4 (63) |
| Calprotectin (ng/ml) n=83 | 493.3 [341.5–711.7] |
| Above the median (≥493) | 50.6 (42) |
Data are summarized as median [Interquartile Range] for continuous variables and % (n) for categorical variables. Intestinal Fatty Acid Binding Protein (I-FABP)
3.1. Factors associated with Gut Integrity
There was a greater proportion of participants with I-FABP ≥ median (56.4%) with low serum vitamin D (<30 ng/ml) when compared to participants with I-FABP < median (43.6%, P=0.044). Other factors including age, sex, race, ethnicity, overweight/obesity, diet, IL-17 and calprotectin were not associated with I-FABP ≥median (P>0.05) (Table 2). In the logistic regression analyses (Table 3), participants with suboptimal vitamin D status (0–29.9 ng/ml) were 3.35 times more likely to present gut integrity damage (I-FABP ≥ median 25.6 pg/ml) than those with optimal vitamin D (OR: 3.35, 95%CI: 1.42, 7.86; P=0.005) after controlling for age, sex, race, ethnicity and total dietary fiber intake.
Table 2.
Comparison of different factors by gut integrity and inflammatory biomarkers categories (< or ≥ the median) in healthy children and adolescents
| Factors | I-FABP (n=138) | IL-17 (n=125) | Calprotectin (n=83) | |||
|---|---|---|---|---|---|---|
| < median | ≥ median | < median | ≥ median | < median | ≥ median | |
| Age (years) | 12.5 [11.0–13.3] | 12.4 [11.5–13.4] | 12.5 [11.2–13.4] | 12.4 [11.1–13.4] | 12.4 [11.5–13.2] | 12.5 [11.0–13.6] |
| Sex | ||||||
| Male | 44.6 (33) | 55.4 (41) | 51.4 (36) | 48.6 (34) | 53.5 (23) | 46.5 (20) |
| Female | 56.3 (36) | 43.8 (28) | 47.3 (26) | 52.7 (29) | 45.0 (18) | 55.0 (22) |
| Race | ||||||
| American Indian Alaska Native | 0 (0) | 100 (4) | 50.0 (2) | 50.0 (2) | 33.3 (1) | 66.7 (2) |
| Asian | 60.0 (3) | 40.0 (2) | 40.0 (2) | 60.0 (3) | 75.0 (3) | 25.0 (1) |
| Black or African American | 38.5 (5) | 61.5 (8) | 61.5 (8) | 38.5 (5) | 71.4 (5) | 28.6 (2) |
| White | 46.4 (26) | 53.6 (30) | 58.3 (28) | 41.7 (20) | 51.5 (19) | 48.6 (18) |
| More than 1 race | 60.0 (3) | 40.0 (2) | 0 (0) | 100 (3) | 100 (2) | 0 (0) |
| Ethnicity (Hispanic or Latino) | 49.5 (49) | 50.5 (50) | 52.8 (47) | 47.2 (21) | 49.4 (41) | 50.6 (42) |
| BMI percentile | 68.6 [35.1–89.2] | 65.9 [38.9–83.9] | 66.6 [29.6–93.7] | 69.7 [32.9–84.2] | 58.8 [35.1–80.2] | 65.4 [39.4–86.8] |
| Overweight/obesity | 57.1 (20) | 42.9 (15) | 51.6 (16) | 48.6 (46) | 36.8 (7) | 63.2 (12)** |
| Diet | ||||||
| Energy intake (kcal/d) | 1852 [1568–2187] | 1773 [1369–2114] | 1716 [1305–2089] | 1920 [1670–2201] | 1772 [1476–2329] | 1846 [1490–2111] |
| Total protein intake (g/d) | 63.7 [52.3–83.5] | 73.8 [56.5–92.6] | 62.8 [52.8–86.8] | 74.4 [57.6–84.2] | 70.8 [55.3–92.8] | 64.7 [52.9–80.0] |
| Total carbohydrate intake (g/d) | 232 [186–254] | 208 [172–280] | 194 [165–250] | 243 [200–275] | 212 [177–270] | 232 [171–255] |
| Fructose (g/d) | 15.6 [7.35–23.8] | 14.2 [8.44–20.0] | 15.5 [7.35–23.7] | 14.2 [8.44–20.0] | 14.4 [8.41–22.3] | 14.8 [8.20–23.8]* |
| Total fat intake (g/d) | 74.7 [54.1–91.1] | 70.0 [53.1–83.7] | 69.6 [51.0–81.6] | 75.5 55.4–100] | 70.9 [53.2–99.9] | 74.8 [53.8–84.5] |
| Saturated fat (g/d) | 21.6 [17.0–32.4] | 24.3 [16.2–37.9] | 22.3 [15.8–33.3] | 24.2 [17.5–35.6] | 25.5 [19.2–36.2] | 21.3 [16.5–27.8] |
| Monosaturated fat (g/d) | 22.5 [15.2–26.8] | 24.1 [17.7–31.3] | 23.0 [17.2–27.9] | 23.4 [15.4–29.7] | 22.5 [17.5–28.8] | 22.3 [12.9–26.2] |
| Polysaturated fat (g/d) | 14.1 [10.3–17.6] | 15.7 [11.1–20.4] | 14.8 [11.1–17.0] | 14.7 [10.7–20.6] | 15.0 [10.1–18.7] | 14.8 [10.5–18.3] |
| Omega-3 fatty acids (g/d) | 1.52 [1.00–1.90] | 1.75 [1.14–2.13] | 1.57 [1.12–1.92] | 1.54 [0.97–1.97] | 1.54 [1.02–2.01] | 1.66 [1.26–2.11] |
| Omega-6 fatty acids (g/d) | 12.1 [8.46–15.0] | 13.1 [9.26–17.5] | 12.2 [8.89–14.1] | 12.8 [8.48–10.8] | 12.8 [8.56–16.0] | 12.5 [8.23–15.5] |
| Total Fiber intake (g/d) | 13.3 [9.58–17.1] | 12.5 [10.0–16.3] | 11.7 [8.86–14.4] | 14.4 [10.5–18.6] | 13.1 [10.0–17.9] | 12.4 [9.46–16.3] |
| Vitamin D intake (mcg/d) | 3.31 [2.28–5.37] | 5.21 [1.93–7.27] | 4.63 [2.07–7.08] | 4.06 [2.26–5.86] | 5.07 [2.60–7.25] | 3.73 [1.93–5.52] |
| Vitamin D (25OH)D | 27 [21.0–32.0] | 24 [20.0–28.0] | 26.0 [19.5–32.0] | 25.0 [21.0–31.0] | 26.0 [21.0–32.0] | 25.0 [19.0–31.0] |
| Low vitamin D levels (<30 ng/ml) | 43.6 (41) | 56.4 (53)* | 47.7 (41) | 52.3 (45) | 44.4 (24) | 55.6 (30) |
| I-FABP (pg/ml) | - | - | 30.9 [19.0–57.4] | 18.2 [6.12–47.1] | 39.3 [24.4–59.9] | 15.9 [6.12–30.9] |
| IL-17 (pg/ml) | 61.5 [23.5–114.6] | 31.4 [0.44–71.4] | - | - | 31.4 [26.5–78.9] | 30.4 [1.58–98.6] |
| Calprotectin (ng/ml) | 600 [484–757] | 398 [301–579] | 488 [354–706] | 526 [318–767] | - | - |
For continuous variables median [Interquartile Range], differences were assessed by Mann Whitney and for categorical variables % (n), differences were assessed by chi-square (X2)
P<0.05;
P=0.06. Intestinal Fatty Acid Binding Protein (I-FABP)
Table 3.
Factors associated with gut integrity damage and inflammation in healthy children and adolescents
| I-FABP ≥ median* | IL-17 ≥ median** | Calprotectin ≥ median*** | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Variable | OR | 95% CI | P-value | OR | 95% CI | P-value | OR | 95% CI | P-value |
| Vitamin D suboptimal | 3.35 | 1.42, 7.86 | 0.005 | 1.99 | 0.65, 6.09 | 0.223 | 5.40 | 0.95, 30.6 | 0.057 |
| Overweight/obesity | 1.26 | 0.40, 3.95 | 0.684 | 0.61 | 0.15, 2.39 | 0.481 | 7.61 | 1.13, 51.2 | 0.037 |
| Hispanic or Latino | 1.03 | 0.41, 2.61 | 0.941 | 0.48 | 0.16, 1.40 | 0.181 | 3.53 | 0.99, 12.6 | 0.052 |
| Gut integrity damage (I-FABP ≥ 25.6 pg/ml) |
- | - | - | 0.26 | 0.08, 0.81 | 0.021 | 0.27 | 0.08, 0.94 | 0.240 |
Bold means statistical significance P<0.05. Intestinal Fatty Acid Binding Protein (I-FABP)
Analysis adjusted by age, sex, race, ethnicity and total dietary fiber
Analysis adjusted by age, sex, race, ethnicity and vitamin D levels and total dietary fiber
Analysis adjusted by age, sex, race, I-FABP levels and total dietary fiber
3.2. Factors associated with Inflammation
Age, sex, race, ethnicity, overweight/obesity, vitamin D status were not associated with inflammation (IL-17 and calprotectin ≥median) (P>0.05). However, there was a trend between the proportion of participants with overweight/obesity and calprotectin ≥median (P=0.06) (Table 2). Among the dietary factors, fructose intake was greater (median 14.8 [8.20–23.8] vs. 14.5 [8.41–22.3], P<0.05) in participants with calprotectin levels ≥median when compared with those with calprotectin < median.
In the logistic regression analyses (Table 3), participants with overweight/obesity were 7.61 times more likely to present higher inflammation (calprotectin ≥ median 493 ng/ml) than those with a healthy weight (OR: 7.61, 95%CI: 1.13, 51.2; P=0.037) after controlling for age, sex, race, I-FABP and total dietary fiber intake. In addition, we found that participants with lower gut integrity damage (I-FABP < median) had lower odds of having inflammation (IL-17 ≥ median 35.7 pg/ml) (P=0.021) after controlling for age, sex, race, ethnicity, serum vitamin D and total dietary fiber intake.
Hispanic or Latino participants were 3.53 times more likely to present higher inflammation (calprotectin ≥ median 493 ng/ml) compared with non-Hispanic or Latino participants (OR: 3.53, 95%CI: 0.99, 12.6; P=0.052) after controlling for age, sex, race, I-FABP and total dietary fiber intake (Table 3).
4. Discussion
The present analysis evaluated factors associated with gut integrity and inflammation in healthy minority children and adolescents. Our data showed that half of our participants exhibited gut integrity damage and inflammation. This is a surprising finding since children participating in our trial did not report gastrointestinal symptoms or conditions that may have impacted gut integrity or inflammation. Gut integrity damage was higher among participants with low serum vitamin D. However, age, sex, race, ethnicity, and vitamin D status were not associated with high levels of inflammation. Nonetheless, overweight/obesity and dietary fructose intake were associated with inflammation. Lastly, we showed that low gut integrity damage was associated with low inflammation. Our hypothesis was accepted for vitamin D status and body composition but rejected for other factors including age, sex, race and ethnicity.
Our findings suggest that vitamin D status may play a key role in the preservation of gut integrity and permeability. Animal studies exploring the mechanism behind the role of vitamin D and gut integrity demonstrated that vitamin D receptors are found in the intestine and adequate vitamin D levels help to maintain the expression of the tight junctions, particularly claudin-2, preserving the integrity of the epithelial barrier [32–34]. Our finding is of great importance since our participants did not report gastrointestinal symptoms or conditions that may have compromised the gut epithelial barrier. This suggests that alterations in vitamin D status are a novel and contributing factor affecting gut integrity and permeability in healthy children and adolescents.
Overweight/obesity was also associated with greater inflammation. Similar to our finding, studies have reported that children with obesity present inflammation, and that inflammation worsens with the degree of obesity [35–38]. It has been recognized that people with obesity may have a compromised gut integrity due to a suboptimal diet, specifically low in fiber, which decreases the expression of intestinal tight junctions activating the intestinal inflammatory response cascade and subsequent systemic inflammation [39]. In addition, children with obesity may exhibit metabolic complications including non-alcoholic fatty liver disease (NAFLD) [40], which in turn may impair vitamin D status. Dietary and nutritional interventions are effective in the clinical management of NAFLD among children, in particular vitamin D supplementation [41], posing the importance of lifestyle modification in this population.
We observed that participants had inadequate fiber intake, although unrelated to inflammation in this cross-sectional analysis. Nevertheless, our study showed that fructose intake was associated with high inflammation levels which corroborates findings from other studies suggesting that fructose consumption may promote intestinal inflammation and alter the gut microbiome [42,43].
Hispanic or Latino children also exhibited a trend towards a higher odd of inflammation. Current evidence on assessing race and ethnicity with inflammation in healthy children and adolescents is scarce. However, a study reported that race and ethnicity influence the gut microbiome composition after three months of age and continue through childhood [14], indicating that changes in the gut microbiome composition may disrupt the gut integrity, causing microbial translocation and promoting local (intestinal) and systemic inflammation [44]. These changes in gut microbiome among minority groups in the US are likely due to interaction between social and environmental factors, including socioeconomic differences, dietary patterns, food insecurity, culture, access to healthcare, and education, among others [45–47]. These factors constitute important environmental and social determinants of health that profoundly influence gut microbiome composition, gut integrity damage and subsequent intestinal inflammation [48,49]. Future studies should aim to evaluate the gut microbiome in Hispanic children, and how this is associated with gut integrity and inflammation.
Our results also suggested that low gut integrity damage was associated with low inflammation which corroborates the interconnexion between these elements to preserve gut health during youth. Damage to the gut integrity promotes the disruption of the tight junctions allowing the passage of microbial products from the gut microbiome (microbial translocation) into the lamina propia, leading to activation of the local immune response and the release of pro-inflammatory cytokines, including IL-17 and tumor necrosis factor (TNF-α), that eventually enhance the systemic inflammation [49–52].These results are similar to studies reporting the relationship between gut integrity and inflammation in adults [39,53–56] and children [57–59] with chronic diseases.
Our study has potential limitations. The cross-sectional nature of the analysis does not allow us to establish causation. Our sample size was relatively small. Measure of I-FABP does not reflect a direct measure of intestinal injury since it was detected in urine. However, urine samples have been used to detect this biomarker in children with gastrointestinal diseases involving intestinal injury [20,60–64]. The inflammatory biomarkers included in this study, IL-17, and calprotectin, were performed in a subset of the sample (IL-17 n=125 and calprotectin n=83) which could have potentially influenced the results for inflammation. In addition, measurement of IL-17 was done in urine samples which does not reflect a direct measure of inflammation commonly found in serum or plasma. Calprotectin was measured in serum which does not reflect a direct measure of inflammation in the context of intestinal injury. However, serum calprotectin has been used to assess inflammation in adult and pediatric population with inflammatory bowel diseases [24–27]. Self-identification for race and ethnicity is complex and poses limitations in research; in fact, many of the Hispanic or Latino participants did not report race. Importantly, metabolic conditions, including underlying hepatic steatosis, that play a critical role in vitamin D status were not investigated in this study. Future studies addressing NAFLD and vitamin D status in children are needed. However, this study provides preliminary data with a unique perspective on how factors, such as vitamin D levels, overweight/obesity and dietary (fructose) intake, are associated with gut integrity and inflammation in minority healthy children and adolescents.
5. Conclusion
Suboptimal vitamin D status and inflammation may compromise the gut integrity in this sample of mostly Hispanic healthy children and adolescents, suggesting an impairment on the intestinal barrier repair system. Also, there was greater inflammation in participants with overweight/obesity and in those with greater fructose intake, which may also affect gut integrity, although longitudinal studies are needed to understand how all these factors are associated. This study provides an important insight to lay the foundation for the development of effective dietary approaches focused on improving diet quality, vitamin D-rich foods and supplements, and anti-inflammatory foods to target overweight/obesity, suboptimal vitamin D status, and inflammation in children and adolescents.
Acknowledgment.
The authors have no acknowledgments to declare.
Sources of Support.
This work was supported by the National Institutes of Health (Eunice Kennedy Shriver National Institute of Child Health and Human Development, NICHD) under Parent Grant #5R01HD098589-03 and Diversity Supplement #1R01HD098589 for Cristina Palacios.
List of Abbreviations
- BMI
Body Mass Index
- I-FABP
Intestinal Fatty Acid Binding Protein
Footnotes
Author Declarations. The authors have no conflicts to declare.
Contributor Information
Jacqueline Hernandez, Department of Dietetics and Nutrition, Robert Stempel College of Public Health & Social Work, Florida International University, 11200 SW 8th Street AHC5, Miami, FL 33199..
Jose Bastida Rodriguez, Department of Dietetics and Nutrition, Robert Stempel College of Public Health & Social Work, Florida International University, 11200 SW 8th Street AHC5, Miami, FL 33199..
Maria Angelica Trak-Fellermeier, Department of Dietetics and Nutrition, Robert Stempel College of Public Health & Social Work, Florida International University, 11200 SW 8th Street AHC5, Miami, FL 33199..
Rodolfo Galvan, Department of Dietetics and Nutrition, Robert Stempel College of Public Health & Social Work, Florida International University, 11200 SW 8th Street, AHC5, Miami, FL 33199..
Alison Macchi, Department of Dietetics and Nutrition, Robert Stempel College of Public Health & Social Work, Florida International University, 11200 SW 8th Street, AHC5, Miami, FL 33199..
Preciosa Martinez-Motta, Department of Dietetics and Nutrition, Robert Stempel College of Public Health & Social Work, Florida International University, 11200 SW 8th Street, AHC5, Miami, FL 33199..
Cristina Palacios, Department of Dietetics and Nutrition, Robert Stempel College of Public Health & Social Work, Florida International University, 11200 SW 8th Street AHC5, Miami, FL 33199..
References
- [1].Cummings JH, Antoine JM, Azpiroz F, Bourdet-Sicard R, Brandtzaeg P, Calder PC, et al. PASSCLAIM - Gut health and immunity. Eur J Nutr 2004;43:II/118–II/173. 10.1007/s00394-004-1205-4. [DOI] [PubMed] [Google Scholar]
- [2].Bischoff SC, Barbara G, Buurman W, Ockhuizen T, Schulzke JD, Serino M, et al. Intestinal permeability - a new target for disease prevention and therapy. BMC Gastroenterol 2014;14:189. 10.1186/s12876-014-0189-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [3].Brandtzaeg P The gut as communicator between environment and host: Immunological consequences. Eur J Pharmacol, vol. 668, 2011. 10.1016/j.ejphar.2011.07.006. [DOI] [PubMed] [Google Scholar]
- [4].Otani S, Coopersmith CM. Gut integrity in critical illness. J Intensive Care 2019. 10.1186/s40560-019-0372-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [5].Wells JM, Brummer RJ, Derrien M, MacDonald TT, Troost F, Cani PD, et al. Homeostasis of the gut barrier and potential biomarkers. Am J Physiol Gastrointest Liver Physiol 2017;312. 10.1152/ajpgi.00048.2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [6].Burcelin R Gut microbiota and immune crosstalk in metabolic disease. Mol Metab 2016;5. 10.1016/j.molmet.2016.05.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7].Shemtov SJ, Emani R, Bielska O, Covarrubias AJ, Verdin E, Andersen JK, et al. The intestinal immune system and gut barrier function in obesity and ageing. FEBS Journal 2023;290. 10.1111/febs.16558. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [8].Di Tommaso N, Gasbarrini A, Ponziani FR. Intestinal barrier in human health and disease. Int J Environ Res Public Health 2021;18. 10.3390/ijerph182312836. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [9].Shreiner AB, Kao JY, Young VB. The gut microbiome in health and in disease. Curr Opin Gastroenterol 2015;31. 10.1097/MOG.0000000000000139. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [10].Chakaroun RM, Massier L, Kovacs P. Gut microbiome, intestinal permeability, and tissue bacteria in metabolic disease: Perpetrators or bystanders? Nutrients 2020;12. 10.3390/nu12041082. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [11].Inczefi O, Bacsur P, Resál T, Keresztes C, Molnár T. The Influence of Nutrition on Intestinal Permeability and the Microbiome in Health and Disease. Front Nutr 2022;9. 10.3389/fnut.2022.718710. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [12].Mishra SP, Wang B, Jain S, Ding J, Rejeski J, Furdui CM, et al. A mechanism by which gut microbiota elevates permeability and inflammation in obese/diabetic mice and human gut. Gut 2023;72. 10.1136/gutjnl-2022-327365. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [13].Saeed NK, Al-Beltagi M, Bediwy AS, El-Sawaf Y, Toema O. Gut microbiota in various childhood disorders: Implication and indications. World J Gastroenterol 2022;28. 10.3748/wjg.v28.i18.1875. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [14].Mallott EK, Sitarik AR, Leve LD, Cioffi C, Camargo CA, Hasegawa K, et al. Human microbiome variation associated with race and ethnicity emerges as early as 3 months of age. PLoS Biol 2023;21. 10.1371/journal.pbio.3002230. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [15].Palacios C, Trak-Fellermeier MA, Pérez CM, Huffman F, Hernandez Suarez Y, Bursac Z, et al. Effect of soluble corn fiber supplementation for 1 year on bone metabolism in children, the MetA-bone trial: Rationale and design. Contemp Clin Trials 2020;95. 10.1016/j.cct.2020.106061. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [16].Emmanuel M, Bokor B. Tanner Stages. StatPearls, https://www.ncbi.nlm.nih.gov/books/NBK470280/; 2022. [accessed September 19, 2024]. [Google Scholar]
- [17].Centers for Disease Control and Prevention. CDC Growth Charts, https://www.cdc.gov/growthcharts/cdc-growth-charts.htm; 2017. [accessed September 19, 2024]. [Google Scholar]
- [18].Seethaler B, Basrai M, Neyrinck AM, Nazare JA, Walter J, Delzenne NM, et al. Biomarkers for assessment of intestinal permeability in clinical practice. Am J Physiol Gastrointest Liver Physiol 2021;321. 10.1152/AJPGI.00113.2021. [DOI] [PubMed] [Google Scholar]
- [19].Derikx JPM, Evennett NJ, Degraeuwe PLJ, Mulder TL, Van Bijnen AA, Van Heurn LWE, et al. Urine based detection of intestinal mucosal cell damage in neonates with suspected necrotising enterocolitis. Gut 2007;56. 10.1136/gut.2007.128934. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [20].Cronk DR, Houseworth TP, Cuadrado DG, Herbert GS, McNutt PM, Azarow KS. Intestinal Fatty Acid Binding Protein (I-FABP) for the Detection of Strangulated Mechanical Small Bowel Obstruction. Curr Surg 2006;63. 10.1016/j.cursur.2006.05.006. [DOI] [PubMed] [Google Scholar]
- [21].Coufal S, Kokesova A, Tlaskalova-Hogenova H, Snajdauf J, Rygl M, Kverka M. Urinary intestinal fatty acid-binding protein can distinguish necrotizing enterocolitis from sepsis in early stage of the disease. J Immunol Res 2016;2016. 10.1155/2016/5727312. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [22].Schurink M, Kooi EMW, Hulzebos CV., Kox RG, Groen H, Heineman E, et al. Intestinal fatty acid-binding protein as a diagnostic marker for complicated and uncomplicated necrotizing enterocolitis: A prospective cohort study. PLoS One 2015;10. 10.1371/journal.pone.0121336. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [23].Mousa FA, Jasim HA, Shakir F. A Prognostic Impact of Interleukin 17 (IL-17) as an Immune-Marker in Patients with Bladder Cancer. Arch Razi Inst 2022;77. 10.22092/ARI.2022.357801.2098. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [24].Ferrer CS, Barno MA, Arranz EM, Jochems A, Ramírez LG, Cordón JP, et al. The use of serum calprotectin as a biomarker for inflammatory activity in inflammatory bowel disease. Revista Espanola de Enfermedades Digestivas 2019;111. 10.17235/REED.2019.5797/2018. [DOI] [PubMed] [Google Scholar]
- [25].Carlsen K, Malham M, Hansen LF, Petersen JJH, Paerregaard A, Houen G, et al. Serum calprotectin in adolescents with inflammatory bowel disease-A pilot investigation. J Pediatr Gastroenterol Nutr 2019;68. 10.1097/MPG.0000000000002244. [DOI] [PubMed] [Google Scholar]
- [26].Malham M, Carlsen K, Riis L, Paerregaard A, Vind I, Fenger M, et al. Plasma calprotectin is superior to serum calprotectin as a biomarker of intestinal inflammation in ulcerative Colitis. Scand J Gastroenterol 2019;54. 10.1080/00365521.2019.1665097. [DOI] [PubMed] [Google Scholar]
- [27].Leach ST, Yang Z, Messina I, Song C, Geczy CL, Cunningham AM, et al. Serum and mucosal S100 proteins, calprotectin (S100A8/S100A9) and S100A12, are elevated at diagnosis in children with inflammatory bowel disease. Scand J Gastroenterol 2007;42. 10.1080/00365520701416709. [DOI] [PubMed] [Google Scholar]
- [28].Institute of Medicine (IOM). Dietary reference intakes for calcium and vitamin D. Washington DC: The National Academies Press; 2011. Pediatrics 2012;130:e1424. 10.1542/peds.2012-2590. [DOI] [PubMed] [Google Scholar]
- [29].Holick MF. Vitamin D Status: Measurement, Interpretation, and Clinical Application. Ann Epidemiol 2009;19:73–8. 10.1016/j.annepidem.2007.12.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [30].Bresson J, Burlingame B, Dean T, Fairweather-Tait S, Heinonen M, Hirsch-Ernst K, et al. Scientific Opinion on Dietary Reference Values for vitamin D EFSA Panel on Dietetic Products, Nutrition, and Allergies (NDA). EFSA Journal 2016;14:4547, 145pp. doi: 10.2903/j.efsa.2016.4547. [DOI] [Google Scholar]
- [31].Trumbo P, Schlicker S, Yates AA, Poos M. Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein and amino acids. J Am Diet Assoc 2002;102. 10.1016/S0002-8223(02)90346-9. [DOI] [PubMed] [Google Scholar]
- [32].Yeung CY, Chiang Chiau JS, Cheng ML, Chan WT, Jiang C Bin, Chang SW, et al. Effects of Vitamin D-Deficient Diet on Intestinal Epithelial Integrity and Zonulin Expression in a C57BL/6 Mouse Model. Front Med (Lausanne) 2021;8. 10.3389/fmed.2021.649818. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [33].Assa A, Vong L, Pinnell LJ, Avitzur N, Johnson-Henry KC, Sherman PM. Vitamin D deficiency promotes epithelial barrier dysfunction and intestinal inflammation. J Infect Dis 2014;210:1296–305. 10.1093/infdis/jiu235. [DOI] [PubMed] [Google Scholar]
- [34].Zhang YG, Wu S, Lu R, Zhou D, Zhou J, Carmeliet G, et al. Tight junction CLDN2 gene is a direct target of the Vitamin D receptor. Sci Rep 2015;5. 10.1038/srep10642. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [35].Spagnuolo MI, Cicalese MP, Caiazzo MA, Franzese A, Squeglia V, Assante LR, et al. Relationship between severe obesity and gut inflammation in children: what’s next? Ital J Pediatr 2010;36. 10.1186/1824-7288-36-66. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [36].Calcaterra V, De Amici M, Leonard MM, De Silvestri A, Pelizzo G, Buttari N, et al. Serum Calprotectin Level in Children: Marker of Obesity and its Metabolic Complications. Ann Nutr Metab 2018;73. 10.1159/000492579. [DOI] [PubMed] [Google Scholar]
- [37].Nier A, Engstler AJ, Maier IB, Bergheim I. Markers of intestinal permeability are already altered in early stages of non-alcoholic fatty liver disease: Studies in children. PLoS One 2017;12. 10.1371/journal.pone.0183282. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [38].Grand A, Rochette E, Dutheil F, Gozal D, Calcaterra V, Canani RB, et al. Body mass index and calprotectin blood level correlation in healthy children: An individual patient data meta-analysis. J Clin Med 2020;9. 10.3390/jcm9030857. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [39].Scheithauer TPM, Rampanelli E, Nieuwdorp M, Vallance BA, Verchere CB, van Raalte DH, et al. Gut Microbiota as a Trigger for Metabolic Inflammation in Obesity and Type 2 Diabetes. Front Immunol 2020;11. 10.3389/fimmu.2020.571731. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [40].Li J, Ha A, Rui F, Zou B, Yang H, Xue Q, et al. Meta-analysis: global prevalence, trend and forecasting of non-alcoholic fatty liver disease in children and adolescents, 2000–2021. Aliment Pharmacol Ther 2022;56. 10.1111/apt.17096. [DOI] [PubMed] [Google Scholar]
- [41].Farías C, Cisternas C, Gana JC, Alberti G, Echeverría F, Videla LA, et al. Dietary and Nutritional Interventions in Nonalcoholic Fatty Liver Disease in Pediatrics. Nutrients 2023;15. 10.3390/nu15224829. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [42].Montrose DC, Nishiguchi R, Basu S, Staab HA, Zhou XK, Wang H, et al. Dietary Fructose Alters the Composition, Localization, and Metabolism of Gut Microbiota in Association With Worsening Colitis. CMGH 2021;11. 10.1016/j.jcmgh.2020.09.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [43].Jung S, Bae H, Song WS, Jang C. Dietary Fructose and Fructose-Induced Pathologies. Annu Rev Nutr 2022;42:45–66. 10.1146/annurev-nutr-062220-025831. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [44].Di Vincenzo F, Del Gaudio A, Petito V, Lopetuso LR, Scaldaferri F. Gut microbiota, intestinal permeability, and systemic inflammation: a narrative review. Intern Emerg Med 2024;19. 10.1007/s11739-023-03374-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [45].Byrd DA, Carson TL, Williams F, Vogtmann E. Elucidating the role of the gastrointestinal microbiota in racial and ethnic health disparities. Genome Biol 2020;21. 10.1186/s13059-020-02117-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [46].Findley K, Williams DR, Grice EA, Bonham VL. Health Disparities and the Microbiome. Trends Microbiol 2016;24. 10.1016/j.tim.2016.08.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [47].Williams DR, Lawrence JA, Davis BA. Racism and Health: Evidence and Needed Research. Annu Rev Public Health 2019;40. 10.1146/annurev-publhealth-040218-043750. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [48].Williams DR, Sternthal M. Understanding Racial-ethnic Disparities in Health: Sociological Contributions. J Health Soc Behav 2010;51. 10.1177/0022146510383838. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [49].Andrews C, McLean MH, Durum SK. Cytokine tuning of intestinal epithelial function. Front Immunol 2018;9. 10.3389/fimmu.2018.01270. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [50].Buckley A, Turner JR. Cell biology of tight junction barrier regulation and mucosal disease. Cold Spring Harb Perspect Biol 2018;10. 10.1101/cshperspect.a029314. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [51].Abraham C, Abreu MT, Turner JR. Pattern Recognition Receptor Signaling and Cytokine Networks in Microbial Defenses and Regulation of Intestinal Barriers: Implications for Inflammatory Bowel Disease. Gastroenterology 2022;162. 10.1053/j.gastro.2021.12.288. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [52].Fasano A All disease begins in the (leaky) gut: Role of zonulin-mediated gut permeability in the pathogenesis of some chronic inflammatory diseases. F1000Res 2020;9. 10.12688/f1000research.20510.1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [53].Mokkala K, Röytiö H, Munukka E, Pietilä S, Ekblad U, Rönnemaa T, et al. Gut microbiota richness and composition and dietary intake of overweight pregnant women are related to serum zonulin concentration, A marker for intestinal permeability. Journal of Nutrition 2016;146. 10.3945/jn.116.235358. [DOI] [PubMed] [Google Scholar]
- [54].Gil-Cardoso K, Ginés I, Pinent M, Ardévol A, Blay M, Terra X. Effects of flavonoids on intestinal inflammation, barrier integrity and changes in gut microbiota during diet-induced obesity. Nutr Res Rev 2016;29. 10.1017/S0954422416000159. [DOI] [PubMed] [Google Scholar]
- [55].Kuzma JN, Hagman DK, Cromer G, Breymeyer KL, Roth CL, Foster-Schubert KE, et al. Intraindividual variation in markers of intestinal permeability and adipose tissue inflammation in healthy normal-weight to obese adults. Cancer Epidemiology Biomarkers and Prevention 2019;28. 10.1158/1055-9965.EPI-18-0641. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [56].Jayashree B, Bibin YS, Prabhu D, Shanthirani CS, Gokulakrishnan K, Lakshmi BS, et al. Increased circulatory levels of lipopolysaccharide (LPS) and zonulin signify novel biomarkers of proinflammation in patients with type 2 diabetes. Mol Cell Biochem 2014;388. 10.1007/s11010-013-1911-4. [DOI] [PubMed] [Google Scholar]
- [57].Küme T, Acar S, Tuhan H, Çatlı G, Anık A, Gürsoy Çalan Ö, et al. The relationship between serum zonulin level and clinical and laboratory parameters of childhood obesity. JCRPE Journal of Clinical Research in Pediatric Endocrinology 2017;9. 10.4274/jcrpe.3682. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [58].Kim JH, Heo JS, Baek KS, Kim SY, Kim JH, Baek KH, et al. Zonulin level, a marker of intestinal permeability, is increased in association with liver enzymes in young adolescents. Clinica Chimica Acta 2018;481. 10.1016/j.cca.2018.03.005. [DOI] [PubMed] [Google Scholar]
- [59].Kortekangas E, Fan YM, Chaima D, Lehto KM, Malamba-Banda C, Matchado A, et al. Associations between Gut Microbiota and Intestinal Inflammation, Permeability and Damage in Young Malawian Children. J Trop Pediatr 2022;68. 10.1093/tropej/fmac012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [60].Kokesova A, Coufal S, Frybova B, Kverka M, Rygl M. The intestinal fatty acid-binding protein as a marker for intestinal damage in gastroschisis. PLoS One 2019;14. 10.1371/journal.pone.0210797. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [61].Evennett NJ, Hall NJ, Pierro A, Eaton S. Urinary intestinal fatty acid-binding protein concentration predicts extent of disease in necrotizing enterocolitis. J Pediatr Surg 2010;45. 10.1016/j.jpedsurg.2009.09.024. [DOI] [PubMed] [Google Scholar]
- [62].Coufal S, Kokesova A, Tlaskalova-Hogenova H, Frybova B, Snajdauf J, Rygl M, et al. Urinary I-FABP, L-FABP, TFF-3, and SAA Can Diagnose and Predict the Disease Course in Necrotizing Enterocolitis at the Early Stage of Disease. J Immunol Res 2020;2020. 10.1155/2020/3074313. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [63].Jung YH, Kim EK, Shin SH, Lee JA, Kim HS, Kim B Il. The physiologic significance of early urinary intestinal fatty acid binding protein levels in preterm infants: A prospective cohort study. Children 2021;8. 10.3390/children8100842. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [64].Thuijls G, Van Wijck K, Grootjans J, Derikx JPM, Van Bijnen AA, Heineman E, et al. Early diagnosis of intestinal ischemia using urinary and plasma fatty acid binding proteins. Ann Surg 2011;253. 10.1097/SLA.0b013e318207a767. [DOI] [PubMed] [Google Scholar]
