Literature DB >> 30207258

Linking genes, circuits, and behavior: network connectivity as a novel endophenotype of externalizing.

Naomi Sadeh1, Jeffrey M Spielberg1, Mark W Logue2, Jasmeet P Hayes2, Erika J Wolf2, Regina E McGlinchey3, William P Milberg3, Steven A Schichman4, Annjanette Stone4, Mark W Miller2.   

Abstract

BACKGROUND: Externalizing disorders are known to be partly heritable, but the biological pathways linking genetic risk to the manifestation of these costly behaviors remain under investigation. This study sought to identify neural phenotypes associated with genomic vulnerability for externalizing disorders.
METHODS: One-hundred fifty-five White, non-Hispanic veterans were genotyped using a genome-wide array and underwent resting-state functional magnetic resonance imaging. Genetic susceptibility was assessed using an independently developed polygenic score (PS) for externalizing, and functional neural networks were identified using graph theory based network analysis. Tasks of inhibitory control and psychiatric diagnosis (alcohol/substance use disorders) were used to measure externalizing phenotypes.
RESULTS: A polygenic externalizing disorder score (PS) predicted connectivity in a brain circuit (10 nodes, nine links) centered on left amygdala that included several cortical [bilateral inferior frontal gyrus (IFG) pars triangularis, left rostral anterior cingulate cortex (rACC)] and subcortical (bilateral amygdala, hippocampus, and striatum) regions. Directional analyses revealed that bilateral amygdala influenced left prefrontal cortex (IFG) in participants scoring higher on the externalizing PS, whereas the opposite direction of influence was observed for those scoring lower on the PS. Polygenic variation was also associated with higher Participation Coefficient for bilateral amygdala and left rACC, suggesting that genes related to externalizing modulated the extent to which these nodes functioned as communication hubs.
CONCLUSIONS: Findings suggest that externalizing polygenic risk is associated with disrupted connectivity in a neural network implicated in emotion regulation, impulse control, and reinforcement learning. Results provide evidence that this network represents a genetically associated neurobiological vulnerability for externalizing disorders.

Entities:  

Keywords:  Alcohol use; disinhibition; neural circuits; polygenic risk score; substance use

Mesh:

Year:  2018        PMID: 30207258      PMCID: PMC6414280          DOI: 10.1017/S0033291718002672

Source DB:  PubMed          Journal:  Psychol Med        ISSN: 0033-2917            Impact factor:   7.723


  57 in total

1.  Principal components analysis corrects for stratification in genome-wide association studies.

Authors:  Alkes L Price; Nick J Patterson; Robert M Plenge; Michael E Weinblatt; Nancy A Shadick; David Reich
Journal:  Nat Genet       Date:  2006-07-23       Impact factor: 38.330

2.  Heritability of "small-world" networks in the brain: a graph theoretical analysis of resting-state EEG functional connectivity.

Authors:  Dirk J A Smit; Cornelis J Stam; Danielle Posthuma; Dorret I Boomsma; Eco J C de Geus
Journal:  Hum Brain Mapp       Date:  2008-12       Impact factor: 5.038

3.  Interference resolution: insights from a meta-analysis of neuroimaging tasks.

Authors:  Derek Evan Nee; Tor D Wager; John Jonides
Journal:  Cogn Affect Behav Neurosci       Date:  2007-03       Impact factor: 3.282

4.  PLINK: a tool set for whole-genome association and population-based linkage analyses.

Authors:  Shaun Purcell; Benjamin Neale; Kathe Todd-Brown; Lori Thomas; Manuel A R Ferreira; David Bender; Julian Maller; Pamela Sklar; Paul I W de Bakker; Mark J Daly; Pak C Sham
Journal:  Am J Hum Genet       Date:  2007-07-25       Impact factor: 11.025

Review 5.  The influence of gene-environment interactions on the development of alcoholism and drug dependence.

Authors:  Mary-Anne Enoch
Journal:  Curr Psychiatry Rep       Date:  2012-04       Impact factor: 5.285

Review 6.  Substance use disorders: a theory-driven approach to the integration of genetics and neuroimaging.

Authors:  Hollis C Karoly; Nicole Harlaar; Kent E Hutchison
Journal:  Ann N Y Acad Sci       Date:  2013-03-07       Impact factor: 5.691

7.  Higher serum cholesterol is associated with intensified age-related neural network decoupling and cognitive decline in early- to mid-life.

Authors:  Jeffrey M Spielberg; Naomi Sadeh; Elizabeth C Leritz; Regina E McGlinchey; William P Milberg; Jasmeet P Hayes; David H Salat
Journal:  Hum Brain Mapp       Date:  2017-03-31       Impact factor: 5.038

8.  Genetic control over the resting brain.

Authors:  D C Glahn; A M Winkler; P Kochunov; L Almasy; R Duggirala; M A Carless; J C Curran; R L Olvera; A R Laird; S M Smith; C F Beckmann; P T Fox; J Blangero
Journal:  Proc Natl Acad Sci U S A       Date:  2010-01-19       Impact factor: 11.205

9.  Brain network disturbance related to posttraumatic stress and traumatic brain injury in veterans.

Authors:  Jeffrey M Spielberg; Regina E McGlinchey; William P Milberg; David H Salat
Journal:  Biol Psychiatry       Date:  2015-02-18       Impact factor: 13.382

Review 10.  Connectomics: a new paradigm for understanding brain disease.

Authors:  Alex Fornito; Edward T Bullmore
Journal:  Eur Neuropsychopharmacol       Date:  2014-03-05       Impact factor: 4.600

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.