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Purpose <p>Hair cortisol concentration (HCC) represents a promising biomarker for long-term hypothalamic–pituitary–adrenal (HPA) axis activity. However, its routine clinical application is currently limited by the lack of well-established reference ranges. We aimed to establish population-based reference intervals for HCC in healthy adults from Northern Italy, using a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method following the Clinical and Laboratory Standards Institute (CLSI) EP28-A3c guidelines.</p> Methods <p>Hair samples were collected from 256 healthy volunteers selected using strict inclusion and exclusion criteria. Cortisol quantification was performed by LC-MS/MS using a deuterated internal standard, guaranteeing high sensitivity and specificity. The method was validated for linearity, limit of detection, extraction efficiency, matrix effect, robustness across different sample weights, and inter-batch reproducibility using an internal quality control sample. Reference intervals were defined nonparametrically (2.5th–97.5th percentiles). Associations with demographic, clinical, and lifestyle variables were assessed.</p> Results <p>The established reference interval was 0.84 to 8.07 pg/mg, with a median of 2.41 pg/mg. HCC was significantly associated with body mass index (ρ = 0.160, <i>p</i> = 0.010) and weakly correlated with perceived stress (ρ = 0.137, <i>p</i> = 0.028). However, no significant associations were observed with sex, age, smoking status, alcohol consumption, physical activity, hair dyeing, or hair washing frequency.</p> Conclusion <p>This study provides, for the first time, a population-based reference interval for hair cortisol concentrations using LC-MS/MS in healthy adults. These findings offer a benchmark for future research, supporting the use of HCC as a biomarker in epidemiological and translational research contexts.</p>

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Establishment of a reference range for hair cortisol using a HPLC-MS/MS method in a Northern Italian population

  • 期刊论文

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  • 发表日期：

    2026年5月26日

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  • Federico Fortuna,
  • Alessia Lanno,
  • Davide Magrin,
  • Amelia Locatelli,
  • Diego Gonzalez,
  • Dario Jacobsen,
  • Juan Jamardo,
  • Bibiana Fabre,
  • Alice Passoni,
  • Renzo Bagnati

摘要

Purpose

Hair cortisol concentration (HCC) represents a promising biomarker for long-term hypothalamic–pituitary–adrenal (HPA) axis activity. However, its routine clinical application is currently limited by the lack of well-established reference ranges. We aimed to establish population-based reference intervals for HCC in healthy adults from Northern Italy, using a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method following the Clinical and Laboratory Standards Institute (CLSI) EP28-A3c guidelines.

Methods

Hair samples were collected from 256 healthy volunteers selected using strict inclusion and exclusion criteria. Cortisol quantification was performed by LC-MS/MS using a deuterated internal standard, guaranteeing high sensitivity and specificity. The method was validated for linearity, limit of detection, extraction efficiency, matrix effect, robustness across different sample weights, and inter-batch reproducibility using an internal quality control sample. Reference intervals were defined nonparametrically (2.5th–97.5th percentiles). Associations with demographic, clinical, and lifestyle variables were assessed.

Results

The established reference interval was 0.84 to 8.07 pg/mg, with a median of 2.41 pg/mg. HCC was significantly associated with body mass index (ρ = 0.160, p = 0.010) and weakly correlated with perceived stress (ρ = 0.137, p = 0.028). However, no significant associations were observed with sex, age, smoking status, alcohol consumption, physical activity, hair dyeing, or hair washing frequency.

Conclusion

This study provides, for the first time, a population-based reference interval for hair cortisol concentrations using LC-MS/MS in healthy adults. These findings offer a benchmark for future research, supporting the use of HCC as a biomarker in epidemiological and translational research contexts.