Giovanna Punzi1, Gianluca Ursini1, Qiang Chen1, Eugenia Radulescu1, Ran Tao1, Louise A Huuki1, Pasquale Di Carlo1, Leonardo Collado-Torres1, Joo Heon Shin1, Roberto Catanesi1, Andrew E Jaffe1, Thomas M Hyde1, Joel E Kleinman1, Trudy F C Mackay1, Daniel R Weinberger1. 1. Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore (Punzi, Ursini, Chen, Radulescu, Tao, Huuki, Di Carlo, Collado-Torres, Shin, Jaffe, Hyde, Kleinman, Weinberger); Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore (Ursini, Hyde, Kleinman, Weinberger); Section of Forensic Psychiatry and Criminology, Institute of Legal Medicine, D.I.M., University of Bari "Aldo Moro," Bari, Italy (Catanesi); Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore (Jaffe); Department of Neurology, Johns Hopkins School of Medicine, Baltimore (Hyde, Weinberger); Department of Genetics and Biochemistry and Center for Human Genetics, Clemson University, Greenwood, S.C. (Mackay); Departments of Neuroscience and Genetic Medicine, Johns Hopkins School of Medicine, Baltimore (Weinberger).
Abstract
OBJECTIVE: The authors sought to study the transcriptomic and genomic features of completed suicide by parsing the method chosen, to capture molecular correlates of the distinctive frame of mind of individuals who die by suicide, while reducing heterogeneity. METHODS: The authors analyzed gene expression (RNA sequencing) from postmortem dorsolateral prefrontal cortex of patients who died by suicide with violent compared with nonviolent means, nonsuicide patients with the same psychiatric disorders, and a neurotypical group (total N=329). They then examined genomic risk scores (GRSs) for each psychiatric disorder included, and GRSs for cognition (IQ) and for suicide attempt, testing how they predict diagnosis or traits (total N=888). RESULTS: Patients who died by suicide by violent means showed a transcriptomic pattern remarkably divergent from each of the other patient groups but less from the neurotypical group; consistently, their genomic profile of risk was relatively low for their diagnosed illness as well as for suicide attempt, and relatively high for IQ: they were more similar to the neurotypical group than to other patients. Differentially expressed genes (DEGs) associated with patients who died by suicide by violent means pointed to purinergic signaling in microglia, showing similarities to a genome-wide association study of Drosophila aggression. Weighted gene coexpression network analysis revealed that these DEGs were coexpressed in a context of mitochondrial metabolic activation unique to suicide by violent means. CONCLUSIONS: These findings suggest that patients who die by suicide by violent means are in part biologically separable from other patients with the same diagnoses, and their behavioral outcome may be less dependent on genetic risk for conventional psychiatric disorders and be associated with an alteration of purinergic signaling and mitochondrial metabolism.
OBJECTIVE: The authors sought to study the transcriptomic and genomic features of completed suicide by parsing the method chosen, to capture molecular correlates of the distinctive frame of mind of individuals who die by suicide, while reducing heterogeneity. METHODS: The authors analyzed gene expression (RNA sequencing) from postmortem dorsolateral prefrontal cortex of patients who died by suicide with violent compared with nonviolent means, nonsuicide patients with the same psychiatric disorders, and a neurotypical group (total N=329). They then examined genomic risk scores (GRSs) for each psychiatric disorder included, and GRSs for cognition (IQ) and for suicide attempt, testing how they predict diagnosis or traits (total N=888). RESULTS: Patients who died by suicide by violent means showed a transcriptomic pattern remarkably divergent from each of the other patient groups but less from the neurotypical group; consistently, their genomic profile of risk was relatively low for their diagnosed illness as well as for suicide attempt, and relatively high for IQ: they were more similar to the neurotypical group than to other patients. Differentially expressed genes (DEGs) associated with patients who died by suicide by violent means pointed to purinergic signaling in microglia, showing similarities to a genome-wide association study of Drosophila aggression. Weighted gene coexpression network analysis revealed that these DEGs were coexpressed in a context of mitochondrial metabolic activation unique to suicide by violent means. CONCLUSIONS: These findings suggest that patients who die by suicide by violent means are in part biologically separable from other patients with the same diagnoses, and their behavioral outcome may be less dependent on genetic risk for conventional psychiatric disorders and be associated with an alteration of purinergic signaling and mitochondrial metabolism.
Authors: Andrew E Jaffe; Ran Tao; Alexis L Norris; Marc Kealhofer; Abhinav Nellore; Joo Heon Shin; Dewey Kim; Yankai Jia; Thomas M Hyde; Joel E Kleinman; Richard E Straub; Jeffrey T Leek; Daniel R Weinberger Journal: Proc Natl Acad Sci U S A Date: 2017-06-20 Impact factor: 11.205
Authors: Ye Zhang; Kenian Chen; Steven A Sloan; Mariko L Bennett; Anja R Scholze; Sean O'Keeffe; Hemali P Phatnani; Paolo Guarnieri; Christine Caneda; Nadine Ruderisch; Shuyun Deng; Shane A Liddelow; Chaolin Zhang; Richard Daneman; Tom Maniatis; Ben A Barres; Jian Qian Wu Journal: J Neurosci Date: 2014-09-03 Impact factor: 6.167
Authors: Andrew E Jaffe; Richard E Straub; Joo Heon Shin; Ran Tao; Yuan Gao; Leonardo Collado-Torres; Tony Kam-Thong; Hualin S Xi; Jie Quan; Qiang Chen; Carlo Colantuoni; William S Ulrich; Brady J Maher; Amy Deep-Soboslay; Alan J Cross; Nicholas J Brandon; Jeffrey T Leek; Thomas M Hyde; Joel E Kleinman; Daniel R Weinberger Journal: Nat Neurosci Date: 2018-07-26 Impact factor: 24.884
Authors: Mario Merlini; Victoria A Rafalski; Keran Ma; Keun-Young Kim; Eric A Bushong; Pamela E Rios Coronado; Zhaoqi Yan; Andrew S Mendiola; Elif G Sozmen; Jae Kyu Ryu; Matthias G Haberl; Matthew Madany; Daniel Naranjo Sampson; Mark A Petersen; Sophia Bardehle; Reshmi Tognatta; Terry Dean; Rosa Meza Acevedo; Belinda Cabriga; Reuben Thomas; Shaun R Coughlin; Mark H Ellisman; Jorge J Palop; Katerina Akassoglou Journal: Nat Neurosci Date: 2020-12-14 Impact factor: 24.884
Authors: Jonathan L Hess; Daniel S Tylee; Manuel Mattheisen; Anders D Børglum; Thomas D Als; Jakob Grove; Thomas Werge; Preben Bo Mortensen; Ole Mors; Merete Nordentoft; David M Hougaard; Jonas Byberg-Grauholm; Marie Bækvad-Hansen; Tiffany A Greenwood; Ming T Tsuang; David Curtis; Stacy Steinberg; Engilbert Sigurdsson; Hreinn Stefánsson; Kári Stefánsson; Howard J Edenberg; Peter Holmans; Stephen V Faraone; Stephen J Glatt Journal: Mol Psychiatry Date: 2019-09-06 Impact factor: 15.992