Sexual Dimorphism in Micronutrient Homeostasis and Cluster Depletion Patterns in Type 2 Diabetes Mellitus Patients with Hair Loss: Development and Validation of a Phenotype-Based Risk Stratification Tool

Authors

Keywords:

Sexual dimorphism, cluster deficiency, risk stratification, zinc deficiency, ferritin deficiency, type 2 diabetes mellitus, hair loss, precision medicine, clinical decision support

Abstract

Background: It is clear that there are gender differences in micronutrient body handling; however, there is a lack of systematic research on micronutrient gender differences in Type 2 Diabetes Mellitus (T2DM) patients also experiencing hair loss. The notion that several micronutrients may be depleted simultaneously (so called "cluster deficiency") has not been studied in this specific type of patients; and there is no validated instrument for clinicians to determine who should be more extensively tested.

Hypothesis: We hypothesized that zinc, ferritin and vitamin D status would be different in men and women with T2DM and hair loss, that multiple deficiencies would be clustered and that a simple risk score could be constructed based on these results that would enable clinicians to predict at the bedside which patients are likely to have the most severe deficiency pattern.

Methods: involved in recruiting 150 patients with T2DM who suffered from active hair loss (80 patients from females and 70 patients from males) were carried out at the Imam Al-Sadiq Hospital in Babil, Iraq in the period between January and April 2026. Serum zinc, ferritin, vitamin D, and HbA1c was measured by atomic absorption spectrophotometry, CMIA, CLIA, and HPLC, respectively. Independent samples t-tests were used to compare groups, Pearson's was used to explore correlations and hierarchical cluster analysis was used to identify natural groupings of deficiency patterns. We then constructed a logistic regression model and transformed it into a simple integer risk score, and tested the model against 1000 bootstrap resamples.

Results: Women had far lower ferritin than men (30.6 vs 113.3 ng/mL, p < 0.001, Cohen's d = 2.89), lower zinc (66.6 vs 85.4 µg/dL, p = 0.001, d = 1.38), and lower vitamin D (13.6 vs 21.3 ng/mL, p = 0.015, d = 0.96). Zinc and ferritin had strong positive correlation (r = 0.72) and zinc and vitamin D (r = 0.68) but there was no correlation between the micronutrients and HbA1c. The cluster analysis divided the patients into three groups: (i) isolated vitamin D deficiency (53 %); (ii) dual or triple vitamin D deficiency (33 %); and (iii) triple vitamin D deficiency (14 %). Logistic regression analysis revealed that female sex (OR 8.4), age > 55 years (OR 3.2) and diabetes duration > 10 years (OR 2.9) were independently associated with triple deficiency, with AUC value of 0.84. The 4 point risk score (0–3 low, 4–6 moderate, 7–9 high) identified triple-deficient patients with an AUC of 0.83 (95% CI 0.75–0.91) and 86% sensitivity and 92% specificity in the bootstrap validation.

Summary: This is the first validated bedside instrument for the prediction of cluster deficiency phenotypes in T2DM patients with hair loss. The score enables the efficient triaging of patients for unnecessary testing of low-risk patients as well as for prompt and targeted multi-nutrient replacement of high-risk patients.

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Published

2026-06-19