Literature DB >> 18812206

An integrated psychobiological predictive model of emergent psychopathology among young relatives at risk for schizophrenia.

Shaun M Eack1, Konasale M R Prasad, Debra M Montrose, Dhruman D Goradia, Diana Dworakowski, Jean Miewald, Matcheri S Keshavan.   

Abstract

OBJECTIVE: Studies of young relatives at elevated risk for schizophrenia have pointed to the importance of a variety of neurobiological, cognitive, and clinical risk factors for the disorder; yet few have employed integrated models to estimate the joint contribution of these factors to heightened schizophrenic risk. We tested the predictive power of an integrated psychobiological model of schizophrenia risk to subsequent psychopathology development among young relatives at risk for the disorder.
METHODS: Young first (n=66) and second (n=20) degree relatives of schizophrenia probands were followed for an average of 3 (SD=1.13) years to examine their trajectories toward psychopathology development. Neurobiologic, cognitive, and clinical measures were employed in an integrated structural equation model to estimate their contribution to the prospective emergence of psychopathology.
RESULTS: Results indicated that neurobiological, neurocognitive, and psychosis proneness factors at baseline were all uniquely predictive of subsequent psychopathology development, and that an integrated model of psychopathology development that took into account these factors provided an excellent fit to the observed data. Subsequent classification analyses of model accuracy using likelihood ratios adjusting for the base-rate of psychopathology development in this sample revealed that individuals identified by this model had a 71% chance of developing psychopathology in the future.
CONCLUSIONS: An integrated model of biobehavioral risk factors may provide a powerful method for predicting psychopathology and schizophrenia risk in at-risk samples. If validated, this model may be useful for early detection and intervention programs. Future research will need to focus particularly on predicting schizophrenia development and refining models to further enhance sensitivity.

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Year:  2008        PMID: 18812206      PMCID: PMC2649961          DOI: 10.1016/j.pnpbp.2008.08.024

Source DB:  PubMed          Journal:  Prog Neuropsychopharmacol Biol Psychiatry        ISSN: 0278-5846            Impact factor:   5.067


  25 in total

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6.  Prefrontal membrane phospholipid metabolism of child and adolescent offspring at risk for schizophrenia or schizoaffective disorder: an in vivo 31P MRS study.

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8.  Neuroanatomical abnormalities before and after onset of psychosis: a cross-sectional and longitudinal MRI comparison.

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  11 in total

Review 1.  Predicting the risk of psychosis onset: advances and prospects.

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Review 2.  Psychosis prediction and clinical utility in familial high-risk studies: selective review, synthesis, and implications for early detection and intervention.

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3.  One-year durability of the effects of cognitive enhancement therapy on functional outcome in early schizophrenia.

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4.  Grey matter and cognitive deficits in young relatives of schizophrenia patients.

Authors:  Tejas S Bhojraj; Alan N Francis; Debra M Montrose; Matcheri S Keshavan
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5.  Longitudinal alterations of executive function in non-psychotic adolescents at familial risk for schizophrenia.

Authors:  Tejas S Bhojraj; Vaibhav A Diwadkar; John A Sweeney; Konasale M Prasad; Shaun M Eack; Debra M Montrose; Matcheri S Keshavan
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6.  Multivariate prediction of emerging psychosis in adolescents at high risk for schizophrenia.

Authors:  Jai Shah; Shaun M Eack; Debra M Montrose; Neeraj Tandon; Jean M Miewald; Konasale M Prasad; Matcheri S Keshavan
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7.  Cortical surface characteristics among offspring of schizophrenia subjects.

Authors:  Konasale M Prasad; Dhruman Goradia; Shaun Eack; Malolan Rajagopalan; Jeffrey Nutche; Tara Magge; Rajaprabhakaran Rajarethinam; Matcheri S Keshavan
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8.  Premorbid cognitive deficits in young relatives of schizophrenia patients.

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