Multi-omics data integration methods and their applications in psychiatric disorders.

To study mental illness and health, in the past researchers have often broken down their complexity into individual subsystems (e.g., genomics, transcriptomics, proteomics, clinical data) and explored the components independently. Technological advancements and decreasing costs of high throughput sequencing has led to an unprecedented increase in data generation. Furthermore, over the years it has become increasingly clear that these subsystems do not act in isolation but instead interact with each other to drive mental illness and health. Consequently, individual subsystems are now analysed jointly to promote a holistic understanding of the underlying biological complexity of health and disease. Complementing the increasing data availability, current research is geared towards developing novel methods that can efficiently combine the information rich multi-omics data to discover biologically meaningful biomarkers for diagnosis, treatment, and prognosis. However, clinical translation of the research is still challenging. In this review, we summarise conventional and state-of-the-art statistical and machine learning approaches for discovery of biomarker, diagnosis, as well as outcome and treatment response prediction through integrating multi-omics and clinical data. In addition, we describe the role of biological model systems and in silico multi-omics model designs in clinical translation of psychiatric research from bench to bedside. Finally, we discuss the current challenges and explore the application of multi-omics integration in future psychiatric research. The review provides a structured overview and latest updates in the field of multi-omics in psychiatry.

Usability Design in Medical Informatics: A Prospective Research Project.

This short paper aims to raise awareness of good usability design in medical computer sciences. We present a research plan about developing usability design guidelines for web application development in medical informatics. Following a nimble creation process we shall create a guideline tailored for software developers, that aims to improve communication between the developer and the medical professional. Results are therefore expected to impact the way applications are being developed within the medical sector.

Psychological Network Analysis of General Self-Efficacy in High vs. Low Resilient Functioning Healthy Adults.

Resilience to stress has gained increasing interest by researchers from the field of mental health and illness and some recent studies have investigated resilience from a network perspective. General self-efficacy constitutes an important resilience factor. High levels of self-efficacy have shown to promote resilience by serving as a stress buffer. However, little is known about the role of network connectivity of self-efficacy in the context of stress resilience. The present study aims at filling this gap by using psychological network analysis to study self-efficacy and resilience. Based on individual resilient functioning scores, we divided a sample of 875 mentally healthy adults into a high and low resilient functioning group. To compute these scores, we applied a novel approach based on Partial Least Squares Regression on self-reported stress and mental health measures. Separately for both groups, we then estimated regularized partial correlation networks of a ten-item self-efficacy questionnaire. We compared three different global connectivity measures-strength, expected influence, and shortest path length-as well as absolute levels of self-efficacy between the groups. Our results supported our hypothesis that stronger network connectivity of self-efficacy would be present in the highly resilient functioning group compared to the low resilient functioning group. In addition, the former showed higher absolute levels of general self-efficacy. Future research could consider using partial least squares regression to quantify resilient functioning to stress and to study the association between network connectivity and resilient functioning in other resilience factors.

RAISE study protocol: a cross-sectional, multilevel, neurobiological study of resilience after individual stress exposure.

INTRODUCTION: This paper describes the protocol for an ongoing project funded by the Royal Society, the Resilience After Individual Stress Exposure (RAISE) study; which aims to examine the factors and mechanisms that facilitate resilient functioning after childhood adversity (CA). METHODS AND ANALYSIS: We aim to recruit up to 200 participants. We will use dimension reduction techniques (principal component analysis) on standard-normally transformed individual parameters of mental health, social functioning and CA to calculate a composite measure of adaptive (ie, 'resilient') psychosocial functioning. To examine the neuroimmune responses to stress and their relationship with the brain and social environment, we will use a well validated functional MRI task; the Montreal imaging stress task and venepuncture. We will run group or dimensional comparisons in multiple levels of biological and psychological outcomes, as well as mediation and moderation analyses to study how key biological systems (ie, the hypothalamic-pituitary-adrenal axis and the immune system) interrelate and interact with brain function and social influences in order to facilitate resilient functioning after CA. We hypothesise that resilient functioning will be facilitated by reduced morning cortisol and cytokine levels before and after the stressor and improved neural responses to such stress, as well as increased gray matter volume in the hippocampus and prefrontal cortex, enhanced inhibitory control and emotion regulation, and more friendship and family support. ETHICS AND DISSEMINATION: This study has been reviewed and given favourable opinion by the National Research Ethics Service, NRES Committee East of England-Cambridge Central and external reviewers from the Royal Society (RGF\R1\180064 and RGF\EA\180029). The results of the RAISE study will be disseminated through (1) publications in scientific peer reviewed journals, (2) presentations on relevant scientific conferences and meetings, (3) publications and presentations for the general public and (4) through social media.

A Medical Report Feature for OSSE Rare Disease Registries.

Web-based patient registries support clinicians by providing a way to effectively store and process data. Here, we present a new feature for the open-source registry software OSSE: medical reports generated with R Markdown. As part of a rare disease research project, we describe the process from requirements assessment to the current state of technical implementation. The feature offers clinicians the possibility to download customised as well as generic reports from an OSSE rare disease registry.

The Resilient Emotional Brain: A Scoping Review of the Medial Prefrontal Cortex and Limbic Structure and Function in Resilient Adults With a History of Childhood Maltreatment.

Childhood maltreatment (CM) is one of the strongest predictors of adult mental illness, although not all adults with CM develop psychopathology. Here, we describe the structure and function of the emotional brain regions that may contribute to resilient functioning after CM. We review studies that report medial prefrontal cortex, amygdala, and hippocampus (limbic regions) structure, function, and/or connections in resilient adults (i.e., those reporting CM without psychopathology) versus vulnerable adults (i.e., those reporting CM with psychopathology) or healthy adults (those without CM and with no psychopathology). We find that resilient adults have larger hippocampal gray and white matter volume and greater connectivity between the central executive network and the limbic regions. In addition, resilient adults have improved ability to regulate emotions through medial prefrontal cortex-limbic downregulation, lower hippocampal activation to emotional faces, and increased amygdala habituation to stress. We highlight the need for longitudinal designs that examine resilient functioning across domains and consider gender, type, timing, and nature of CM assessments and further stressors to further improve our understanding of the role of the emotional brain in resilient functioning after CM.