Despite the promise of intranasal oxytocin (OT) for modulating social behavior, recent work has provided mixed results. This may relate to suboptimal drug deposition achieved with conventional nasal sprays, inter-individual differences in nasal physiology and a poor understanding of how intranasal OT is delivered to the brain in humans. Delivering OT using a novel ‘Breath Powered' nasal device previously shown to enhance deposition in intranasal sites targeted for nose-to-brain transport, we evaluated dose-dependent effects on social cognition, compared response with intravenous (IV) administration of OT, and assessed nasal cavity dimensions using acoustic rhinometry. We adopted a randomized, double-blind, double-dummy, crossover design, with 16 healthy male adults completing four single-dose treatments (intranasal 8 IU (international units) or 24 IU OT, 1 IU OT IV and placebo). The primary outcome was social cognition measured by emotional ratings of facial images. Secondary outcomes included the pharmacokinetics of OT, vasopressin and cortisol in blood and the association between nasal cavity dimensions and emotional ratings. Despite the fact that all the treatments produced similar plasma OT increases compared with placebo, there was a main effect of treatment on anger ratings of emotionally ambiguous faces. Pairwise comparisons revealed decreased ratings after 8 IU OT in comparison to both placebo and 24 IU OT. In addition, there was an inverse relationship between nasal valve dimensions and anger ratings of ambiguous faces after 8-IU OT treatment. These findings provide support for a direct nose-to-brain effect, independent of blood absorption, of low-dose OT delivered from a Breath Powered device.

The deviation between chronological age and age predicted using brain MRI is a putative marker of overall brain health. Age prediction based on structural MRI data shows high accuracy in common brain disorders. However, brain aging is complex and heterogenous, both in terms of individual differences and the underlying biological processes. Here, we implemented a multimodal model to estimate brain age using different combinations of cortical area, thickness and sub‐cortical volumes, cortical and subcortical T1/T2‐weighted ratios, and cerebral blood flow (CBF) based on arterial spin labeling. For each of the 11 models we assessed the age prediction accuracy in healthy controls (HC, n = 750) and compared the obtained brain age gaps (BAGs) between age‐matched subsets of HC and patients with Alzheimer's disease (AD, n = 54), mild (MCI, n = 90) and subjective (SCI, n = 56) cognitive impairment, schizophrenia spectrum (SZ, n = 159) and bipolar disorder (BD, n = 135). We found highest age prediction accuracy in HC when integrating all modalities. Furthermore, two‐group case–control classifications revealed highest accuracy for AD using global T1‐weighted BAG, while MCI, SCI, BD and SZ showed strongest effects in CBF‐based BAGs. Combining multiple MRI modalities improves brain age prediction and reveals distinct deviations in patients with psychiatric and neurological disorders. The multimodal BAG was most accurate in predicting age in HC, while group differences between patients and HC were often larger for BAGs based on single modalities. These findings indicate that multidimensional neuroimaging of patients may provide a brain‐based mapping of overlapping and distinct pathophysiology in common disorders.

Background: Individuals suffering from schizophrenia have a reduced life expectancy with cardiovascular disease (CVD) as a major contributor. Low educational attainment is associated with schizophrenia, as well as with all-cause and CVD mortality. However, it is unknown to what extent low educational attainment can explain the increased mortality in individuals with schizophrenia. Aim: Here, we quantify associations between educational attainment and allcause and CVD mortality in individuals with schizophrenia, and compare them with the corresponding associations in the general population.