Associations between psychosis endophenotypes across brain functional, structural, and cognitive domains

Blakey, Robert; Ranlund, Siri; Zartaloudi, Eirini; Cahn, Wiepke; Colizzi, Marco; Crespo‐Facorro, Benedicto; Daniel, Christina; Díez, Álvaro; Forti, Marta Di; Iyegbe, Conrad; Jablensky, Assen; Jones, Rebecca; Hall, M-H; Kahn, R.S.; Kalaydjieva, Luba; Kravariti, Eugenia; Lin, Kuang; McDonald, Colm; McIntosh, Andrew M.; Picchioni, Marco; Powell, John; Presman, Amelia; Rujescu, Dan; Schulze, Katja; Shaikh, Madiha; Thygesen, Johan Hilge; Toulopoulou, Timothea; Haren, N Van; Os, Jim van; Walshe, Muriel; Murray, Robin M.; Bramon, Elvira

doi:10.1017/s0033291717002860

Cited by 14 publications

(16 citation statements)

References 175 publications

(243 reference statements)

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“…Taken together, these findings align with previous research showing reduced NoGo P3 amplitude in antisocial samples (38)(39)(40)(41) and, to some extent, individuals with schizophrenia (86). In addition, the estimated median effect sizes in the current study were larger than previous metaanalytic research showing reduced P3 amplitudes (d = 0.25) and delayed P3 latencies (d = 0.13) in antisocial samples (37) Since the NoGo P3 component is thought to reflect outcome monitoring or outcome evaluation after successful inhibitions (31)(32)(33), with amplitude reflecting the amount of cognitive resources used and latency serving as an index of neural efficiency (22,23), it is possible that MDOs have deficits both in the allocation of cognitive resources during monitoring or evaluation of their behavior, as well as in the efficiency of such allocation (88). If monitoring and evaluation capabilities are reduced, it may be difficult to correctly interpret the environment and evaluate possible consequences of one's behavior.…”

Section: Discussioncontrasting

confidence: 51%

“…Going beyond P3 amplitude reduction, research suggests that the amplitude and latency of the P3 ERP may represent distinct endophenotypes. Whereas amplitude is thought to reflect the amount of cognitive resources or "neural power" being used, latency, often defined as the time point where the waveform peaks, may serve as an index of neural processing speed or "neural efficiency" (22,23). Studies investigating P3 latency are limited, especially in antisocial populations, and results have been mixed.…”

Section: Introductionmentioning

confidence: 99%

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Trait Disinhibition and NoGo Event-Related Potentials in Violent Mentally Disordered Offenders and Healthy Controls

et al. 2020

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Trait disinhibition may function as a dispositional liability toward maladaptive behaviors relevant in the treatment of mentally disordered offenders (MDOs). Reduced amplitude and prolonged latency of the NoGo N2 and P3 event-related potentials have emerged as promising candidates for transdiagnostic, biobehavioral markers of trait disinhibition, yet no study has specifically investigated these two components in violent, inpatient MDOs. Here, we examined self-reported trait disinhibition, experimentally assessed response inhibition, and NoGo N2 and P3 amplitude and latency in male, violent MDOs (N = 27) and healthy controls (N = 20). MDOs had a higher degree of trait disinhibition, reduced NoGo P3 amplitude, and delayed NoGo P3 latency compared to controls. The reduced NoGo P3 amplitude and delayed NoGo P3 latency in MDOs may stem from deficits during monitoring or evaluation of behavior. NoGo P3 latency was associated with increased trait disinhibition in the whole sample, suggesting that trait disinhibition may be associated with reduced neural efficiency during later stages of outcome monitoring or evaluation. Findings for NoGo N2 amplitude and latency were small and non-robust. With several limitations in mind, this is the first study to demonstrate attenuated NoGo P3 amplitude and delayed NoGo P3 latency in violent, inpatient MDOs compared to healthy controls.

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Section: Discussioncontrasting

confidence: 51%

Section: Introductionmentioning

confidence: 99%

Trait Disinhibition and NoGo Event-Related Potentials in Violent Mentally Disordered Offenders and Healthy Controls

et al. 2020

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“…In the past decade, the endophenotype approach has been applied to psychiatric disorders such as depression 122,123 , obsessive-compulsive disorder [124][125][126] , and schizophrenia [127][128][129][130] , revealing alterations in brain structure and function in patients and their unaffected relatives. Thereby, these studies provide initial insight into the genetic vulnerability to these disorders, as they show that the changes are not just a manifestation of the disease state (as the alterations were present in unaffected family members as well) and are likely heritable because the characteristics were present in both patients and relatives (cf.…”

Section: Endophenotype Research On Social Anxiety Disordermentioning

confidence: 99%

Imaging the socially-anxious brain: recent advances and future prospects

Bas-Hoogendam

Westenberg

2020

F1000Res

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Social anxiety disorder (SAD) is serious psychiatric condition with a genetic background. Insight into the neurobiological alterations underlying the disorder is essential to develop effective interventions that could relieve SAD-related suffering. In this expert review, we consider recent neuroimaging work on SAD. First, we focus on new results from magnetic resonance imaging studies dedicated to outlining biomarkers of SAD, including encouraging findings with respect to structural and functional brain alterations associated with the disorder. Furthermore, we highlight innovative studies in the field of neuroprediction and studies that established the effects of treatment on brain characteristics. Next, we describe novel work aimed to delineate endophenotypes of SAD, providing insight into the genetic susceptibility to develop the disorder. Finally, we outline outstanding questions and point out directions for future research.

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“…Assessment of early information processing as measured with electrophysiological paradigms has also indicated impairments in schizophrenia patients, and also these disturbances are generally considered unaffected by disease stage and severity of symptoms (Koychev et al ., 2012; Thibaut et al ., 2015; Blakey et al ., 2018). Commonly used electrophysiological paradigms comprise P50 suppression (Adler et al ., 1982), pre-pulse inhibition of the startle response (PPI) (Braff and Geyer, 1990), and mismatch negativity (MMN) (Shelley et al ., 1991).…”

Section: Introductionmentioning

confidence: 99%

Accuracy of diagnostic classification algorithms using cognitive-, electrophysiological-, and neuroanatomical data in antipsychotic-naïve schizophrenia patients

et al. 2018

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BackgroundA wealth of clinical studies have identified objective biomarkers, which separate schizophrenia patients from healthy controls on a group level, but current diagnostic systems solely include clinical symptoms. In this study, we investigate if machine learning algorithms on multimodal data can serve as a framework for clinical translation.MethodsForty-six antipsychotic-naïve, first-episode schizophrenia patients and 58 controls underwent neurocognitive tests, electrophysiology, and magnetic resonance imaging (MRI). Patients underwent clinical assessments before and after 6 weeks of antipsychotic monotherapy with amisulpride. Nine configurations of different supervised machine learning algorithms were applied to first estimate the unimodal diagnostic accuracy, and next to estimate the multimodal diagnostic accuracy. Finally, we explored the predictability of symptom remission.ResultsCognitive data significantly classified patients from controls (accuracies = 60–69%; p values = 0.0001–0.009). Accuracies of electrophysiology, structural MRI, and diffusion tensor imaging did not exceed chance level. Multimodal analyses with cognition plus any combination of one or more of the remaining three modalities did not outperform cognition alone. None of the modalities predicted symptom remission.ConclusionsIn this multivariate and multimodal study in antipsychotic-naïve patients, only cognition significantly discriminated patients from controls, and no modality appeared to predict short-term symptom remission. Overall, these findings add to the increasing call for cognition to be included in the definition of schizophrenia. To bring about the full potential of machine learning algorithms in first-episode, antipsychotic-naïve schizophrenia patients, careful a priori variable selection based on independent data as well as inclusion of other modalities may be required.

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Associations between psychosis endophenotypes across brain functional, structural, and cognitive domains

Cited by 14 publications

References 175 publications

Trait Disinhibition and NoGo Event-Related Potentials in Violent Mentally Disordered Offenders and Healthy Controls

Trait Disinhibition and NoGo Event-Related Potentials in Violent Mentally Disordered Offenders and Healthy Controls

Imaging the socially-anxious brain: recent advances and future prospects

Accuracy of diagnostic classification algorithms using cognitive-, electrophysiological-, and neuroanatomical data in antipsychotic-naïve schizophrenia patients

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