MULTIVARIATE DEPENDENCE IN HORMONAL AND IMMUNE RESPONSES: EFFECT ESTIMATION AND PHYSIOLOGICAL VARIATION
DOI:
https://doi.org/10.69980/az668g76Keywords:
Hormonal biomarkers, Immune response, Cytokines, Physiological variation, Multivariate analysisAbstract
This study examined multivariate dependence between hormonal biomarkers and immune responses, emphasizing effect estimation and physiological variation. Participant-level data from healthy adults were analyzed using progesterone, testosterone, 25-hydroxy vitamin D3, and lipopolysaccharide-stimulated IFN-gamma, IL-1beta, IL-6, and TNF-alpha responses. Descriptive statistics, Spearman correlation, false-discovery-rate adjustment, Mann-Whitney U tests, and multivariable linear regression with heteroskedasticity-robust standard errors were applied. Regression models adjusted for age, sex, body mass index, smoking status, and the remaining hormonal variables. Testosterone showed significant positive unadjusted correlations with all four cytokines, whereas progesterone showed minimal associations and vitamin D3 demonstrated a modest inverse relationship with IL-6. However, none of the hormonal coefficients remained statistically significant after multivariable adjustment and correction for multiple testing. Pronounced sex-related physiological variation was observed, with males exhibiting markedly higher testosterone concentrations and stronger IFN-gamma, IL-1beta, IL-6, and TNF-alpha responses, while females showed higher vitamin D3 concentrations. These findings indicate that apparent hormone-immune relationships are strongly influenced by underlying physiological heterogeneity and may attenuate substantially after adjustment for major covariates. Overall, multivariate analytical approaches provide a more comprehensive framework for evaluating endocrine-immune interactions and distinguishing direct biomarker relationships from broader physiological variation.
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