Electrophysiological Endophenotypes in Rodent Models of Schizophrenia and Psychosis

Rosen, Andrew M.; Spellman, Timothy; Gordon, Joshua A.

doi:10.1016/j.biopsych.2015.03.021

Cited by 35 publications

(27 citation statements)

References 133 publications

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“…Some mouse models showing behavioral phenotypes relevant to schizophrenia have shown altered gamma oscillation, supporting that alterations in gamma oscillation may be one of common features in the schizophrenia pathophysiological changes that may be caused by diverse pathogenic pathways (Table 5, and see review Rosen et al, 2015). For example, mice with altered Nrg1 or Erbb4 showed alterations in interneuron positioning and gamma oscillation (Del Pino et al, 2013; Fisahn et al, 2009; Yang et al, 2013).…”

Section: Neurobiological Basis For Cognitive Impairments In Schizomentioning

confidence: 88%

Converging models of schizophrenia – Network alterations of prefrontal cortex underlying cognitive impairments

Sakurai

Gamo

Hikida

et al. 2015

Progress in Neurobiology

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The prefrontal cortex (PFC) and its connections with other brain areas are crucial for cognitive function. Cognitive impairments are one of the core symptoms associated with schizophrenia, and manifest even before the onset of the disorder. Altered neural networks involving PFC contribute to cognitive impairments in schizophrenia. Both genetic and environmental risk factors affect the development of the local circuitry within PFC as well as development of broader brain networks, and make the system vulnerable to further insults during adolescence, leading to the onset of the disorder in young adulthood. Since spared cognitive functions correlate with functional outcome and prognosis, a better understanding of the mechanisms underlying cognitive impairments will have important implications for novel therapeutics for schizophrenia focusing on cognitive functions. Multidisciplinary approaches, from basic neuroscience to clinical studies, are required to link molecules, circuitry, networks, and behavioral phenotypes. Close interactions among such fields by sharing a common language on connectomes, behavioral readouts, and other concepts are crucial for this goal.

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Section: Neurobiological Basis For Cognitive Impairments In Schizomentioning

confidence: 88%

Converging models of schizophrenia – Network alterations of prefrontal cortex underlying cognitive impairments

Sakurai

Gamo

Hikida

et al. 2015

Progress in Neurobiology

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“…In addition to the fact that animal studies offer control over confounds that complicate human research, and thus may simplify the task of identifying relevant brain systems, they also facilitate study of gene function related to these systems (e.g., Rosen et al, 2015). Animal research that yields a gene finding for an analog endophenotype that involves a genetic homolog in humans has obvious merit: It can be used to generate a human candidate gene study that adopts a hypothesis backed by high biological plausibility.…”

Section: 0 Endophenotype Construct Validationmentioning

confidence: 99%

“…Many thoughtful endophenotype articles populate the literature (for recent examples, see Anokhin, 2014; Beauchaine, 2009; Burton et al, 2015; Campanella, Pogarell, & Boutros, 2014; Euser et al, 2012; Faraone, Bonvicini, & Scassellati, 2014; Ferrarelli, 2013; Glahn et al, 2014; Goldstein & Klein, 2014; W. G. Iacono & Malone, 2011; Lenzenweger, 2013; Loo, Lenartowicz, & Makeig, 2015; Manoach & Agam, 2013; Miller & Rockstroh, 2013; Moses-Kolko, Horner, Phillips, Hipwell, & Swain, 2014; Owens, Bachman, Glahn, & Bearden, 2016; Pearlson, 2015; Rosen, Spellman, & Gordon, 2015; Rubenstein, Wiggins, & Lee, 2015; Salvatore, Gottesman, & Dick, 2015; Swerdlow, Gur, & Braff, 2015), and many of these share a conviction that endophenotypes are valuable for identifying genetic liability . However, despite their introduction to psychiatry by Gottesman and Shields (I.…”

Section: 0 Introductionmentioning

confidence: 99%

Endophenotype best practices

Iacono

Malone

Vrieze

2017

International Journal of Psychophysiology

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This review examines the current state of electrophysiological endophenotype research and recommends best practices that are based on knowledge gleaned from the last decade of molecular genetic research with complex traits. Endophenotype research is being oversold for its potential to help discover psychopathology relevant genes using the types of small samples feasible for electrophysiological research. This is largely because the genetic architecture of endophenotypes appears to be very much like that of behavioral traits and disorders: they are complex, influenced by many variants (e.g., tens of thousands) within many genes, each contributing a very small effect. Out of over 40 electrophysiological endophenotypes covered by our review, only resting heart, a measure that has received scant advocacy as an endophenotype, emerges as an electrophysiological variable with verified associations with molecular genetic variants. To move the field forward, investigations designed to discover novel variants associated with endophenotypes will need extremely large samples best obtained by forming consortia and sharing data obtained from genome wide arrays. In addition, endophenotype research can benefit from successful molecular genetic studies of psychopathology by examining the degree to which these verified psychopathology-relevant variants are also associated with an endophenotype, and by using knowledge about the functional significance of these variants to generate new endophenotypes. Even without molecular genetic associations, endophenotypes still have value in studying the development of disorders in unaffected individuals at high genetic risk, constructing animal models, and gaining insight into neural mechanisms that are relevant to clinical disorder.

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“…Overall, studies show evidence that resting 215,216 and pre-stimulus baseline gamma activity is elevated, 217,218 while task-driven gamma-band responses are reduced in schizophrenia, 205,219,220 suggesting deficits in signal-to-noise ratio between neural network states. 28 …”

Section: Gammamentioning

confidence: 99%

“…26,27 Furthermore, electrophysiological endophenotypes have high translational value, as they can also be effectively modeled in animals. 28-31 .…”

Section: Introductionmentioning

confidence: 99%

Electrophysiological Endophenotypes for Schizophrenia

Owens

Bachman

Glahn

et al. 2016

Harvard Review of Psychiatry

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Endophenotypes are quantitative, heritable traits that may help to elucidate the pathophysiologic mechanisms underlying complex disease syndromes, such as schizophrenia. They can be assessed at numerous levels of analysis; here, we review electrophysiological endophenotypes that have shown promise in helping us understand schizophrenia from a more mechanistic point of view. For each endophenotype, we describe typical experimental procedures, reliability, heritability, and reported gene and neurobiological associations. We discuss recent findings regarding the genetic architecture of specific electrophysiological endophenotypes, as well as converging evidence from EEG studies implicating disrupted balance of glutamatergic signaling and GABA-ergic inhibition in the pathophysiology of schizophrenia. We conclude that refining the measurement of electrophysiological endophenotypes, expanding genetic association studies, and integrating datasets are important next steps for understanding the mechanisms that connect identified genetic risk loci for schizophrenia to the disease phenotype.

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Electrophysiological Endophenotypes in Rodent Models of Schizophrenia and Psychosis

Cited by 35 publications

References 133 publications

Converging models of schizophrenia – Network alterations of prefrontal cortex underlying cognitive impairments

Converging models of schizophrenia – Network alterations of prefrontal cortex underlying cognitive impairments

Endophenotype best practices

Electrophysiological Endophenotypes for Schizophrenia

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