Oxytocin and the stress buffering effect of social company: A genetic study in daily life

Social relationships are a crucial determinant of both mental and physical health. This effect is partly due to social buffering of stress. Animal studies suggest that social buffering is mediated via the oxytocin system, while studies in humans are sparse and limited by the low ecological validity of laboratory settings. In the present study, participants (N = 326) completed smartphone questionnaires four times a day over 4 to 5 days, measuring stressors, negative affect, and social context to assess social buffering. We found that under stress, participants reported a higher need for social company. Further, the impact of prior stressful events on momentary negative affect was attenuated by the perceived pleasantness of current social company. This social buffering effect was moderated by haplotypes of the oxytocin receptor gene, based on two well-described single nucleotide polymorphisms (rs2268498, rs53576). Effects were robust when controlling for gender and age, applying different data quality criteria, and even apparent in genotype-based analyses. Our findings demonstrate that social buffering and its modulation by oxytocin system characteristics have implications for life as lived outside the laboratory

Open and reproducible science practices in psychoneuroendocrinology: Opportunities to foster scientific progress

This perspective article was written by invitation of the editors in chief as a summary and extension of the symposium entitled Psychoneuroendocrine Research in the Era of the Replication Crisis which was held at the virtual meeting of the International Society of Psychoneuroendocrinology 2021. It highlights the opportunities presented by the application of open and reproducible scientific practices in psychoneuroendocrinology (PNE), an interdisciplinary field at the intersection of psychology, endocrinology, immunology, neurology, and psychiatry. It conveys an introduction to the topics preregistration, registered reports, quantifying the impact of equally-well justifiable analysis decisions, and open data and scripts, while emphasizing ‘selfish’ reasons to adopt such practices as individual researcher. Complementary to the call for adoption of open science practices, we highlight the need for methodological best practice guidelines in the field of PNE, which could further contribute to enhancing replicability of results. We propose concrete steps for future actions and provide links to additional resources for those interested in adopting open and reproducible science practices in future studies

The DNA methylation landscape of the human oxytocin receptor gene (OXTR): data-driven clusters and their relation to gene expression and childhood adversity

The oxytocin receptor gene (OXTR) is of interest when investigating the effects of early adversity on DNA methylation. However, there is heterogeneity regarding the selection of the most promising CpG sites to target for analyses. The goal of this study was to determine functionally relevant clusters of CpG sites within the OXTR CpG island in 113 mother-infant dyads, with 58 of the mothers reporting childhood maltreatment (CM). OXTR DNA methylation was analyzed in peripheral/umbilical blood mononuclear cells. Different complexity reduction approaches were used to reduce the 188 CpG sites into clusters of co-methylated sites. Furthermore, associations between OXTR DNA methylation (cluster- and site-specific level) and OXTR gene expression and CM were investigated in mothers. Results showed that, first, CpG sections differed strongly regarding their statistical utility for research of individual differences in DNA methylation. Second, cluster analyses and Partial Least Squares (PLS) suggested two clusters consisting of intron1/exon2 and the protein-coding region of exon3, respectively, as most strongly associated with outcome measures. Third, cross-validated PLS regression explained 7% of variance in CM, with low cross-validated variance explained for the prediction of gene expression. Fourth, substantial mother-child correspondence was observed in correlation patterns within the identified clusters, but only modest correspondence outside these clusters. This study makes an important contribution to the mapping of the DNA methylation landscape of the OXTR CpG island by highlighting clusters of CpG sites that show desirable statistical properties and predictive value. We provide a Companion Web Application to facilitate the choice of CpG sites

The DNA methylation landscape of the human oxytocin receptor gene (OXTR): data-driven clusters and their relation to gene expression and childhood adversity.

The oxytocin receptor gene (OXTR) is of interest when investigating the effects of early adversity on DNA methylation. However, there is heterogeneity regarding the selection of the most promising CpG sites to target for analyses. The goal of this study was to determine functionally relevant clusters of CpG sites within the OXTR CpG island in 113 mother-infant dyads, with 58 of the mothers reporting childhood maltreatment (CM). OXTR DNA methylation was analyzed in peripheral/umbilical blood mononuclear cells. Different complexity reduction approaches were used to reduce the 188 CpG sites into clusters of co-methylated sites. Furthermore, associations between OXTR DNA methylation (cluster- and site-specific level) and OXTR gene expression and CM were investigated in mothers. Results showed that, first, CpG sections differed strongly regarding their statistical utility for research of individual differences in DNA methylation. Second, cluster analyses and Partial Least Squares (PLS) suggested two clusters consisting of intron1/exon2 and the protein-coding region of exon3, respectively, as most strongly associated with outcome measures. Third, cross-validated PLS regression explained 7% of variance in CM, with low cross-validated variance explained for the prediction of gene expression. Fourth, substantial mother-child correspondence was observed in correlation patterns within the identified clusters, but only modest correspondence outside these clusters. This study makes an important contribution to the mapping of the DNA methylation landscape of the OXTR CpG island by highlighting clusters of CpG sites that show desirable statistical properties and predictive value. We provide a Companion Web Application to facilitate the choice of CpG sites

Neuroimaging-based classification of PTSD using data-driven computational approaches: a multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.Stress-related psychiatric disorders across the life spa

A new era for understanding amyloid structures and disease

The aggregation of proteins into amyloid fibrils and their deposition into plaques and intracellular inclusions is the hallmark of amyloid disease. The accumulation and deposition of amyloid fibrils, collectively known as amyloidosis, is associated with many pathological conditions that can be associated with ageing, such as Alzheimer disease, Parkinson disease, type II diabetes and dialysis-related amyloidosis. However, elucidation of the atomic structure of amyloid fibrils formed from their intact protein precursors and how fibril formation relates to disease has remained elusive. Recent advances in structural biology techniques, including cryo-electron microscopy and solid-state NMR spectroscopy, have finally broken this impasse. The first near-atomic-resolution structures of amyloid fibrils formed in vitro, seeded from plaque material and analysed directly ex vivo are now available. The results reveal cross-β structures that are far more intricate than anticipated. Here, we describe these structures, highlighting their similarities and differences, and the basis for their toxicity. We discuss how amyloid structure may affect the ability of fibrils to spread to different sites in the cell and between organisms in a prion-like manner, along with their roles in disease. These molecular insights will aid in understanding the development and spread of amyloid diseases and are inspiring new strategies for therapeutic intervention

Oxytocin and the stress buffering effect of social company: A genetic study in daily life

Social relationships are a crucial determinant of both mental and physical health. This effect is partly due to social buffering of stress. Animal studies suggest that social buffering is mediated via the oxytocin system, while studies in humans are sparse and limited by the low ecological validity of laboratory settings. In the present study, participants (N = 326) completed smartphone questionnaires four times a day over 4 to 5 days, measuring stressors, negative affect, and social context to assess social buffering. We found that under stress, participants reported a higher need for social company. Further, the impact of prior stressful events on momentary negative affect was attenuated by the perceived pleasantness of current social company. This social buffering effect was moderated by haplotypes of the oxytocin receptor gene, based on two well-described single nucleotide polymorphisms (rs2268498, rs53576). Effects were robust when controlling for gender and age, applying different data quality criteria, and even apparent in genotype-based analyses. Our findings demonstrate that social buffering and its modulation by oxytocin system characteristics have implications for life as lived outside the laboratory