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Assessing Niacin Flush Pathway Markers for Resilience Classification in Schizophrenia (101927)

Session Information:

Tuesday, 24 March 2026 16:00
Session: Poster Session 3
Room: Orion Hall (5F)
Presentation Type: Poster Presentation

All presentation times are UTC + 9 (Asia/Tokyo)

Background: Psychological resilience supports better outcomes and recovery in schizophrenia. These patients often show a blunted niacin flush, associated with dysregulated phospholipid metabolism and downstream signaling. Chronic stress and depressive symptoms lower polyunsaturated fatty acids, increase oxidative stress, activate phospholipase A2, and reduce flush response. This study aims to identify key niacin flush pathway biomarkers that distinguish schizophrenia patients with low resilience.
Methods: A total of 108 schizophrenia patients were recruited from the hospitals in southern Taiwan. Resilience was assessed with the Connor-Davidson Resilience Scale, and cluster analysis categorized them into high- and low-resilience groups. The niacin skin flush test evaluated flush responses, and blood samples were analyzed for niacin receptor, prostaglandins, and their specific receptors. We utilized different machine learning algorithms and a SuperLearner ensemble model to construct predictive models for identifying low resilience in schizophrenia patients.
Results: The findings demonstrated that a panel of six biomarkers related to the niacin flushing pathway yielded area under the curve (AUC) values between 0.71 and 0.78 across various machine learning algorithms. Notably, when predictions from four individual algorithms were combined using the SuperLearner ensemble approach, the model achieved an improved AUC of 0.80. Furthermore, 10-fold cross-validation showed that the SuperLearner ensemble model maintained a robust discriminative performance in identifying patients with schizophrenia characterized by low psychological resilience, yielding an AUC of 0.70.
Conclusions: This study identified biomarkers within the niacin flush pathway associated with low psychological resilience in schizophrenia. The risk models may facilitate early identification and inform targeted clinical interventions.

Authors:
Sheng-Hsiang Lin, National Cheng Kung University, Taiwan
Chih-Wei Lin, National Cheng Kung University, Taiwan
Wan-Lin Cheng, Chi Mei Medical Center, Taiwan
Huai-Hsuan Tseng, National Cheng Kung University Hospital, Taiwan
Chih-Chun Huang, National Cheng Kung University Hospital, Taiwan
Shulan Hsieh, National Cheng Kung University, Taiwan


About the Presenter(s)
Dr. Sheng-Hsiang Lin is currently a Professor of Institute of Clinical Medicine, National Cheng Kung University, Taiwan.

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Posted by James Alexander Gordon

Last updated: 2023-02-23 23:45:00