Strategies for Advancing Disease Definition Using Biomarkers and Genetics: The Bipolar and Schizophrenia Network for Intermediate Phenotypes

Tamminga, Carol A.; Pearlson, Godfrey D.; Stan, Ana D.; Gibbons, Robert D.; Padmanabhan, Jaya; Keshavan, Matcheri S.; Clementz, Brett A.

doi:10.1016/j.bpsc.2016.07.005

Cited by 44 publications

(34 citation statements)

References 40 publications

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“…As a result of this emphasis, many studies and some multisite consortia are currently recruiting participants across various psychotic disorders, not schizophrenia alone, to address key scientific questions. For example, the Bipolar and Schizophrenia Network for Intermediate Phenotypes Consortium has proposed cognitive‐based biotypes that can be compared in terms of their external validity with existing diagnostic classifications. Similarly, the Consortium on the Genetics of Endophenotypes in Schizophrenia has closely examined the genetic influences on a wide range of cognitive endophenotypes for schizophrenia, thereby providing a way to identify genetic subgroups of patients or to parse the genetic architecture of the disorder.…”

Section: Discussionmentioning

confidence: 99%

Nonsocial and social cognition in schizophrenia: current evidence and future directions

2019

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Cognitive impairment in schizophrenia involves a broad array of nonsocial and social cognitive domains. It is a core feature of the illness, and one with substantial implications for treatment and prognosis. Our understanding of the causes, consequences and interventions for cognitive impairment in schizophrenia has grown substantially in recent years. Here we review a range of topics, including: a) the types of nonsocial cognitive, social cognitive, and perceptual deficits in schizophrenia; b) how deficits in schizophrenia are similar or different from those in other disorders; c) cognitive impairments in the prodromal period and over the lifespan in schizophrenia; d) neuroimaging of the neural substrates of nonsocial and social cognition, and e) relationships of nonsocial and social cognition to functional outcome. The paper also reviews the considerable efforts that have been directed to improve cognitive impairments in schizophrenia through novel psychopharmacology, cognitive remediation, social cognitive training, and alternative approaches. In the final section, we consider areas that are emerging and have the potential to provide future insights, including the interface of motivation and cognition, the influence of childhood adversity, metacognition, the role of neuroinflammation, computational modelling, the application of remote digital technology, and novel methods to evaluate brain network organization. The study of cognitive impairment has provided a way to approach, examine and comprehend a wide range of features of schizophrenia, and it may ultimately affect how we define and diagnose this complex disorder.

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Section: Discussionmentioning

confidence: 99%

Nonsocial and social cognition in schizophrenia: current evidence and future directions

2019

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“…2 Clinical practice requests guidance of some objective, quantitative and specific biomarker reflecting its neurobiological substrates for diagnosis and treatment selection. 3 Functional magnetic resonance imaging (fMRI) studies have accumulated increasing evidence for neuroimaging basis of SZ, [4][5][6] raising the possibility to understand the pathophysiology of this debilitating mental illness. Our previous studies have shown the dysconnectivity pattern of SZ patients by means of functional connectivity, 7,8 effective connectivity, 9,10 voxel-mirrored homotopic connectivity, 11 and resting-state networks analyses.…”

Section: Introductionmentioning

confidence: 99%

Disease Definition for Schizophrenia by Functional Connectivity Using Radiomics Strategy

Cui

Liu

Wang

et al. 2018

Schizophrenia Bulletin

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Specific biomarker reflecting neurobiological substrates of schizophrenia (SZ) is required for its diagnosis and treatment selection of SZ. Evidence from neuroimaging has implicated disrupted functional connectivity in the pathophysiology. We aimed to develop and validate a method of disease definition for SZ by resting-state functional connectivity using radiomics strategy. This study included 2 data sets collected with different scanners. A total of 108 first-episode SZ patients and 121 healthy controls (HCs) participated in the current study, among which 80% patients and HCs (n = 183) and 20% (n = 46) were selected for training and testing in intra-data set validation and 1 of the 2 data sets was selected for training and the other for testing in inter-data set validation, respectively. Functional connectivity was calculated for both groups, features were selected by Least Absolute Shrinkage and Selection Operator (LASSO) method, and the clinical utility of its features and the generalizability of effects across samples were assessed using machine learning by training and validating multivariate classifiers in the independent samples. We found that the accuracy of intra-data set training was 87.09% for diagnosing SZ patients by applying functional connectivity features, with a validation in the independent replication data set (accuracy = 82.61%). The inter-data set validation further confirmed the disease definition by functional connectivity features (accuracy = 83.15% for training and 80.07% for testing). Our findings demonstrate a valid radiomics approach by functional connectivity to diagnose SZ, which is helpful to facilitate objective SZ individualized diagnosis using quantitative and specific functional connectivity biomarker.

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“…One such approach is “reverse nosology,” which suggests redefining diagnostic categories based on their molecular, cellular, and circuit basis. 42 In this approach, patients that display a similar neurobiology (eg, similar brain activation patterns) are grouped in the same diagnostic category, although the self-reported symptoms or observable psychopathology may be fundamentally different. Thus, clinical practitioners would be no longer able to diagnose based on their clinical impression and self-report.…”

Section: New Approaches In Diagnostic Classificationmentioning

confidence: 99%

Changes from ICD-10 to ICD-11 and future directionsin psychiatric classification

Gäebel

Stricker

Kerst

2020

Dialogues in Clinical Neuroscience

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This article provides a brief overview of the changes from ICD-10 to ICD-11 regarding the classification of mental, behavioral, or neurodevelopmental disorders. These changes include a new chapter structure, new diagnostic categories, changes in diagnostic criteria, and steps towards dimensionality. Additionally, we review evaluative field studies of ICD-11, which provide preliminary evidence for higher reliability and clinical utility of ICD-11 compared with ICD-10. Despite the extensive revision process, changes from ICD-10 to ICD-11 were relatively modest in that both systems are categorical, classifying mental phenomena based on self-reported or clinically observable symptoms. Other recent approaches to psychiatric nosology and classification (eg, neurobiology-based or hierarchical) are discussed. To meet the needs of different user groups, we propose expanding the stepwise approach to diagnosis introduced for some diagnostic categories in ICD-11, which includes categorical and dimensional elements.

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Strategies for Advancing Disease Definition Using Biomarkers and Genetics: The Bipolar and Schizophrenia Network for Intermediate Phenotypes

Cited by 44 publications

References 40 publications

Nonsocial and social cognition in schizophrenia: current evidence and future directions

Nonsocial and social cognition in schizophrenia: current evidence and future directions

Disease Definition for Schizophrenia by Functional Connectivity Using Radiomics Strategy

Changes from ICD-10 to ICD-11 and future directionsin psychiatric classification

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