Intranasal oxytocin increases heart-rate variability in men at clinical high risk for psychosis: a proof-of-concept study

Abstract

Autonomic nervous system (ANS) dysfunction (i.e., increased sympathetic and/or decreased parasympathetic activity) has been proposed to contribute to psychosis vulnerability. Yet, we still lack directed therapeutic strategies that improve ANS regulation in psychosis or at-risk states. The oxytocin system constitutes a potential therapeutic target, given its role in ANS regulation. However, whether intranasal oxytocin ameliorates autonomic regulation during emerging psychosis is currently unknown. We pooled together two datasets, one of 30 men at clinical high risk for psychosis (CHR-P), and another of 17 healthy men, who had participated in two double-blinded, placebo-controlled, randomised, crossover MRI studies with similar protocols. All participants self-administered 40 IU of intranasal oxytocin or placebo using a nasal spray. We recorded pulse plethysmography during a period of 8 min at about 1 h post dosing and estimated heart rate (HR) and high-frequency HR variability (HF-HRV), an index of cardio-parasympathetic activity. CHR-P and healthy men did not differ at resting HR or HF-HRV under placebo. We found a significant condition × treatment effect for HF-HRV, showing that intranasal oxytocin, compared with placebo, increased HF-HRV in CHR-P but not in healthy men. The main effects of treatment and condition were not significant. In this proof-of-concept study, we show that intranasal oxytocin increases cardio-parasympathetic activity in CHR-P men, highlighting its therapeutic potential to improve autonomic regulation in this clinical group. Our findings support the need for further research on the preventive and therapeutic potential of intranasal oxytocin during emerging psychosis, where we lack effective treatments.

Fig. 1. Condition, treatment, and condition × treatment effects on heart rate (a) and high-frequency heart-rate variability (b).

Heart rate (HR) (a) and high-frequency heart-rate variability (HF-HRV) (b) descriptive for each treatment level within each group. Violin plots represent the smoothed distribution of the data. Box plots represent the distribution of the HR/HF-HRV values for each treatment level in each condition (median is indicated by the black central line; upper and lower whiskers denote the highest and the lowest datum within 1.5 interquartile range of the upper and lower quartiles). We tested for the main effects of condition, treatment, and the condition × treatment interaction on HR and HF-HRV using two separate linear mixed models. Statistical significance was set to *p < 0.05. Abbreviations: HC healthy controls, CHR-P clinical high-risk for psychosis, OT intranasal oxytocin, PL placebo.

Fig. 2. Association between heart rate (a), high-frequency heart-rate variability (b), and attenuated positive symptoms in men at clinical high risk for psychosis.

Scatter plots showing the absence of correlation between heart rate (a) or high-frequency heart-rate variability (b) in the placebo session and attenuated positive symptoms (as assessed by the Comprehensive Assessment of At-risk Mental States (CAARMS)) in men at clinical high risk for psychosis. The blue line represents the fitting of a linear regression and the shadow the respective 95% confidence interval. The histograms on the top of each axis show the density distribution of each variable.

Fig. 3. Association between high-frequency heart-rate variability response to intranasal oxytocin and attenuated positive symptoms in clinical high risk for psychosis men.

Scatterplot showing the absence of correlation between the response of the high-frequency heart-rate variability (HF-HRV) to intranasal oxytocin and attenuated positive symptoms (as assessed by the Comprehensive Assessment of At-risk Mental States (CAARMS)) in men at clinical high risk for psychosis. ΔHF-HRV corresponds to the difference between the HF-HRV values of the oxytocin and placebo sessions (oxytocin–placebo). The blue line represents the fitting of a linear regression and the shadow the respective 95% confidence interval. The histograms on the top of each axis show the density distribution of each variable.