Zinc as a Biomarker of Nutritional Status and Clinical Burden in Recessive Dystrophic Epidermolysis Bullosa: Implications for Preventive Monitoring

Abstract

Background/Objectives: Recessive dystrophic epidermolysis bullosa (RDEB) is a severe congenital genodermatosis characterized by skin and mucosa fragility, chronic inflammation, recurrent infections and high nutritional demands due to increased metabolism and epithelial barrier-related losses, placing patients at risk of zinc deficiency. We aimed to investigate the clinical relevance and biochemical determinants of zinc deficiency as a potentially modifiable contributor to disease burden in RDEB. Methods: In this cross-sectional study (n = 84), serum zinc levels were analyzed in association with sex, age, disease severity, percentage of body surface area (BSA) affected, inflammatory markers, infection burden, and common clinical complications including anemia and growth impairment. Results: Zinc deficiency, defined as levels below 670 µg/L, was identified in 35% of patients and became more frequent after age 5 and during adulthood, particularly among those with more severe disease. Deficiency was strongly associated with anemia, inflammation, infection burden, growth impairment, and extensive skin involvement. A revised cutoff of 780 µg/L is proposed, showing improved diagnostic performance for identifying patients at risk of systemic complications, and offering a more suitable threshold for starting preventive supplementation. Multivariate logistic modeling confirmed that low serum zinc independently predicted anemia risk, alongside transferrin saturation and C- reactive protein levels. Serum albumin was identified as the strongest determinant of zinc levels, partially mediating the effects of inflammation and skin involvement. Conclusions: These findings identify serum zinc as a clinically relevant marker of nutritional status and complication burden in RDEB. While no causal or therapeutic effects can be inferred from this cross-sectional study, the strong and biologically plausible associations observed suggest a rationale for systematic monitoring and correction of zinc deficiency as part of comprehensive supportive care, and warrant prospective studies to assess clinical benefit.

Keywords: albumin; anemia; inflammation; recessive dystrophic epidermolysis bullosa; serum zinc levels; skin fragility; zinc deficiency.

Figure 1

Zinc status in the RDEB cohort. Serum zinc levels are shown according to sex (a); across age as a continuous variable (b); by age group (preschool children <5 years, children and adolescents 5–<18 years, and adults ≥18 years) (c); by EBDASI severity categories (mild <43 points, moderate 43–106 points, and severe ≥107 points) (d). Panel (e) shows the relationship between serum zinc levels and the EBDASI score as a continuous variable, also stratified by age group. Statistical analyses include an unpaired t-test for panel (a), the Kruskal–Wallis test followed by Dunn’s multiple comparison test for panels (c,d), and Spearman’s rank-order correlation coefficient (ρ) for panels (b,e). NS indicates non-significant results (p > 0.05). Error bars represent the median and interquartile range, and dashed lines denote the normal zinc reference range (red) and EBDASI severity thresholds (blue). Panel (f) shows the comparison of age (Mann–Whitney test) and EBDASI severity scores (unpaired t-test) in children and adolescents with severe disease, stratified by zinc status (with or without zinc deficiency, n = 12 per group) with error bars representing the median and interquartile range. Gray shading indicates zinc deficiency.

Figure 2

Association of zinc deficiency with growth impairment in RDEB. Correlation between serum zinc levels and anthropometric parameters was assessed using Z-scores for weight and height by age, calculated from contemporary Spanish reference charts [31]. Statistical analyses include Pearson’s correlation coefficient (r) and Spearman’s rank-order correlation coefficient (ρ), with corresponding p-values. Red dashed lines indicate the normal zinc reference range (vertical) and the 3rd and 97th percentile thresholds for Z-scores (horizontal). Gray shading indicates zinc deficiency. Blue diagonal shading highlights patients with Z-scores below the 3rd percentile.

Figure 3

Lower serum zinc levels in patients presenting with the most frequent complications in RDEB. Zinc levels, analyzed as a continuous variable (µg/L), are compared between patients with (“Yes”, open squares) or without (“No”, solid circles) specific clinical outcomes: cutaneous and oral complications (a), inflammatory and infectious burden (b), psychological symptoms (c), and anemia (d). Statistical analysis (p-value) was performed using an unpaired t test. Dashed lines indicate the normal zinc range (red) and the proposed threshold for preventive supplementation (780 µg/L; blue). %BSA = percentage of body surface area affected; CRP = C-reactive protein; ACI = active cutaneous infection; HCI = history of cutaneous infection; HHI = history of hospitalization due to serious infection (nonresponsive to oral antibiotics or sepsis). Gray shading indicates zinc deficiency.

Figure 4

Zinc levels as a predictor of anemia risk in RDEB. (a) Correlation of serum zinc levels (µg/L) with hemoglobin (Hb, g/dL; n = 84) and serum iron (µg/dL; n = 83) in patients with RDEB. Spearman’s rank-order correlation coefficient (ρ) and corresponding p-values are shown; linear regression lines (solid red lines) with 95% confidence intervals (dotted red lines) are displayed. Vertical dashed lines indicate the normal zinc range (in red) and the proposed threshold for preventive supplementation (780 µg/L; blue) Gray shading indicates zinc deficiency. (b) Comparison of logistic regression models with different predictor sets and (c) summary of the final selected model (Model 4), including 5-fold cross-validation results. Blue shading highlights the selected model. CRP = C-reactive protein; BSA = Body surface area; TSAT = transferrin saturation; AIC = Akaike Information Criterion; R² (McFadden) = pseudo-R²; AUC = area under the receiver operating characteristic curve. β = represent log-odds from the logistic regression model predicting anemia risk (1 = anemic, 0 = non-anemic); SE = Standard error of the β coefficient; OR = odds ratio (e^β); p-value = statistical significance of each predictor; 95% CI (OR): confidence interval for OR estimates, reported as [lower, upper] SD = Standard deviation.

Figure 5

Factors influencing blood zinc levels in RDEB. (a) Scatterplots showing the association between blood zinc levels (µg/L) and potential predictors, including percentage of body surface area affected (BSA; %, n = 84), serum C-reactive protein (CRP; mg/L, n = 84), interleukin-6 (IL6; pg/mL, n = 79), and albumin (g/dL, n = 84), with fitted linear regression lines (dashed black) and 95% confidence intervals (dotted). Horizontal dashed lines indicate the normal zinc reference range. Gray shading indicates zinc deficiency. Dashed vertical red lines indicate the normal range for CRP (5 mg/L) and the 95th percentile of healthy controls used as the cut-off for IL-6 (77 pg/mL; [3]). (b) Statistical output of the corresponding univariable linear regression models predicting blood zinc levels. (c) Comparison of logistic regression models including different predictor sets (with or without albumin, IL6 and CRP × BSA interaction; n = 79). (d) Summary of the final selected model (Model D), including 5-fold cross-validation results. Blue shading highlights the selected model. β = unstandardized regression coefficient; SE = standard error of the regression coefficient β; p-val= p-value for testing β ≠ 0; R² = coefficient of determination; Adj R² = Adjusted R²; F stat = Fisher’s F-test result; F- p val = Fisher’s F-test p value; AIC = Akaike Information Criterion; t = T-statistic (β/SE); 95% CI = confidence interval; VIF = Variance Inflation Factors; MSE = mean squared error; RMSE = root mean squared error in the original units of zinc. MAE = mean absolute error; SD = standard deviation.