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Objective <p>Individual variations in depressive disorder (DD) treatment responses highlight the need for early efficacy prediction to optimize regimens. The niacin skin flushing response (NSFR) is a potential DD biomarker, and elevated inflammatory cytokines are linked to DD. This study explored the association between blunted NSFR and DD symptom severity, and evaluated the predictive value of NSFR and inflammatory cytokines for early antidepressant efficacy.</p> Methods <p>Fifty DD patients were grouped as responders (≥ 50% Hamilton Depression Rating Scale reduction at week 2) or non-responders. Intergroup differences in NSFR index and inflammatory cytokines (Phospholipase A2 [PLA2], Cyclooxygenase-2 [COX-2]) were compared. Spearman’s correlation, binary logistic regression, and receiver operating characteristic (ROC) curves analyzed associations and predictive performance.</p> Results <p>(1) Baseline NSFR index was significantly negatively correlated with baseline HAMD score (<i>r</i> = -0.736, <i>p</i> &lt; 0.001), indicating that the degree of NSFR attenuation reflects depression severity. (2) Both baseline NSFR index (AUC = 0.615) and COX-2 level (AUC = 0.725) independently predicted early treatment efficacy, with patients exhibiting lower baseline NSFR index or higher baseline COX-2 levels showing superior early efficacy. (3) The combined predictive model incorporating baseline NSFR index, COX-2, and PLA2 demonstrated optimal predictive performance (AUC = 0.786).</p> Conclusion <p>This study confirms that greater NSFR attenuation is associated with more severe depressive symptoms. Baseline NSFR and COX-2 hold promise as potential predictive biomarkers. Furthermore, the combined model based on NSFR and inflammatory cytokines exhibits superior predictive value, providing a potential basis for optimizing individualized DD treatment strategies and exploring anti-inflammatory therapeutic targets.</p>

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The predictive value of niacin skin flushing response and inflammatory factors for the antidepressant efficacy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月26日

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  • Meiyue Yang,
  • Lan Wang,
  • Mei Song,
  • Jing Yang,
  • Xueqi Wang,
  • Yuke Zheng,
  • Ziyi Hou,
  • Ran Wang,
  • Cuixia An

摘要

Objective

Individual variations in depressive disorder (DD) treatment responses highlight the need for early efficacy prediction to optimize regimens. The niacin skin flushing response (NSFR) is a potential DD biomarker, and elevated inflammatory cytokines are linked to DD. This study explored the association between blunted NSFR and DD symptom severity, and evaluated the predictive value of NSFR and inflammatory cytokines for early antidepressant efficacy.

Methods

Fifty DD patients were grouped as responders (≥ 50% Hamilton Depression Rating Scale reduction at week 2) or non-responders. Intergroup differences in NSFR index and inflammatory cytokines (Phospholipase A2 [PLA2], Cyclooxygenase-2 [COX-2]) were compared. Spearman’s correlation, binary logistic regression, and receiver operating characteristic (ROC) curves analyzed associations and predictive performance.

Results

(1) Baseline NSFR index was significantly negatively correlated with baseline HAMD score (r = -0.736, p < 0.001), indicating that the degree of NSFR attenuation reflects depression severity. (2) Both baseline NSFR index (AUC = 0.615) and COX-2 level (AUC = 0.725) independently predicted early treatment efficacy, with patients exhibiting lower baseline NSFR index or higher baseline COX-2 levels showing superior early efficacy. (3) The combined predictive model incorporating baseline NSFR index, COX-2, and PLA2 demonstrated optimal predictive performance (AUC = 0.786).

Conclusion

This study confirms that greater NSFR attenuation is associated with more severe depressive symptoms. Baseline NSFR and COX-2 hold promise as potential predictive biomarkers. Furthermore, the combined model based on NSFR and inflammatory cytokines exhibits superior predictive value, providing a potential basis for optimizing individualized DD treatment strategies and exploring anti-inflammatory therapeutic targets.