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Updated: May 21, 2026

Standardized Data Acquisition for Neuromelanin-Sensitive Magnetic Resonance Imaging of the Substantia Nigra
Published on: September 8, 2021
Sex-specific alterations of niacin flush pathway biomarkers in schizophrenia
Kuang-Yu Hsieh1, Chi-Wei Chiu2, Jin-Jia Lin3
1Department of Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Abstract:
Attenuated niacin flush has been associated with schizophrenia (SZ), and six biomarkers within the niacin flush pathway have been identified as potential biomarkers for SZ, including niacin flush response, G-protein-coupled receptor 109 A (GPR109A), prostaglandin E2 (PGE2), prostaglandin D2 receptor 1 (DP1), and PGE2 receptors (EP2 and EP4). However, sex differences may influence the discriminative performance of biomarker-based models. To examine this hypothesis, we recruited 182 patients with SZ and 111 healthy controls (HC) and constructed sex-specific classification models to evaluate the impact of sex on the predictive utility of these biomarkers. Additionally, the expression levels of two other PGE2 receptors, EP1 and EP3, were also measured, but neither showed statistically significant differences between SZ and HC. In females, PGE2 demonstrated promising discriminative ability, with a nested 10-fold cross-validated AUC of 0.92 and a Brier score of 0.10. In contrast, the contribution of PGE2 in males was negligible, resulting in lower model performance compared with that in females. In terms of AUC performance, EP4 also showed a similar but weaker effect to PGE2. Feature analysis indicated PGE2 contributed prominently to the discriminative model in females but had minimal impact in males. Decision curve analysis revealed a higher clinical benefit for the female-specific model, suggesting superior utility. These findings suggest the presence of sex-specific differences in inflammatory signaling associated with the niacin flush pathway in SZ. Incorporating sex-specific profiles may therefore help refine niacin flush pathway biomarkers into more robust tools for the personalized prediction of SZ.
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