Imaging the spontaneous flow of thought: Distinct periods of cognition contribute to dynamic functional connectivity during rest

Available online 25 August 2019.This research was possible thanks to the support of the National Institute of Mental Health Intramural Research Program. Portions of this study used the high-performance computational capabilities of the Biowulf Linux cluster at the National Institutes of Health, Bethesda, MD (biowulf.nih.gov). This study is part of NIH clinical protocol number NCT00001360, annual report ZIAMH002783, and protocol ID 93-M- 0170. CCG was supported by the Spanish Ministry of Economy and Competitiveness through the Juan de la Cierva Fellowship (IJCI-2014- 20821), Ramon y Cajal Fellowship (RYC-2017-21845), and the “Severlo Ochoa” Programme for Centres/Units of Excellence in R& D (SEV-2015- 490). Resting-state data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University

Blood epigenome-wide association studies of suicide attempt in adults with bipolar disorder

Abstract Suicide attempt (SA) risk is elevated in individuals with bipolar disorder (BD), and DNA methylation patterns may serve as possible biomarkers of SA. We conducted epigenome-wide association studies (EWAS) of blood DNA methylation associated with BD and SA. DNA methylation was measured at >700,000 positions in a discovery cohort of n = 84 adults with BD with a history of SA (BD/SA), n = 79 adults with BD without history of SA (BD/non-SA), and n = 76 non-psychiatric controls (CON). EWAS revealed six differentially methylated positions (DMPs) and seven differentially methylated regions (DMRs) between BD/SA and BD/non-SA, with multiple immune-related genes implicated. There were no epigenome-wide significant differences when BD/SA and BD/non-SA were each compared to CON, and patterns suggested that epigenetics differentiating BD/SA from BD/non-SA do not differentiate BD/non-SA from CON. Weighted gene co-methylation network analysis and trait enrichment analysis of the BD/SA vs. BD/non-SA contrast further corroborated immune system involvement, while gene ontology analysis implicated calcium signalling. In an independent replication cohort of n = 48 BD/SA and n = 47 BD/non-SA, fold changes at the discovery cohort’s significant sites showed moderate correlation across cohorts and agreement on direction. In both cohorts, classification accuracy for SA history among individuals with BD was highest when methylation at the significant CpG sites as well as information from clinical interviews were combined, with an AUC of 88.8% (CI = 83.8–93.8%) and 82.1% (CI = 73.6–90.5%) for the combined epigenetic-clinical classifier in the discovery and replication cohorts, respectively. Our results provide novel insight to the role of immune system functioning in SA and BD and also suggest that integrating information from multiple levels of analysis holds promise to improve risk assessment for SA in adults with BD