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      Improving risk assessment and familial aggregation of age at onset in schizophrenia using minor physical anomalies and craniofacial measures

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          Abstract

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          Abstract

          Age at onset is the most important feature of schizophrenia that could indicate its origin. Minor physical anomalies (MPAs) characterize potential marker indices of disturbances in early neurodevelopment. However, the association between MPAs and age at onset of schizophrenia is still unclear. We aimed to compare risk assessment and familial aggregation in patients with early-onset schizophrenia (EOS) and adult-onset schizophrenia (AOS) with MPAs and craniofacial measures.

          We estimated the risk assessment of MPAs among patients with EOS (n = 68), patients with AOS (n = 183), nonpsychotic relatives (n = 147), and healthy controls (n = 241) using 3 data-mining algorithms. In addition, we assessed the magnitude of familial aggregation of MPAs with respect to the age at onset of schizophrenia.

          The performance of EOS was superior to that of AOS, with discrimination accuracies of 89% and 76%, respectively. Combined MPA scores as the risk assessment were significantly higher in all schizophrenia subgroups and the nonpsychotic relatives of EOS patients than in the healthy controls. The recurrence risk ratio for familial aggregation of the MPA scores of EOS families (odds ratio 9.27) was substantially higher than that of AOS families (odds ratio 2.47).

          The results highlight that EOS improves risk assessment and has a severe magnitude of familial aggregation of MPAs. These findings indicate that EOS might result from a stronger genetic susceptibility to neurodevelopmental deficits.

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          Most cited references52

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          Mapping adolescent brain change reveals dynamic wave of accelerated gray matter loss in very early-onset schizophrenia.

          Neurodevelopmental models for the pathology of schizophrenia propose both polygenetic and environmental risks, as well as early (pre/perinatal) and late (usually adolescent) developmental brain abnormalities. With the use of brain mapping algorithms, we detected striking anatomical profiles of accelerated gray matter loss in very early-onset schizophrenia; surprisingly, deficits moved in a dynamic pattern, enveloping increasing amounts of cortex throughout adolescence. Early-onset patients were rescanned prospectively with MRI, at 2-year intervals at three time points, to uncover the dynamics and timing of disease progression during adolescence. The earliest deficits were found in parietal brain regions, supporting visuospatial and associative thinking, where adult deficits are known to be mediated by environmental (nongenetic) factors. Over 5 years, these deficits progressed anteriorly into temporal lobes, engulfing sensorimotor and dorsolateral prefrontal cortices, and frontal eye fields. These emerging patterns correlated with psychotic symptom severity and mirrored the neuromotor, auditory, visual search, and frontal executive impairments in the disease. In temporal regions, gray matter loss was completely absent early in the disease but became pervasive later. Only the latest changes included dorsolateral prefrontal cortex and superior temporal gyri, deficit regions found consistently in adult studies. These emerging dynamic patterns were (i) controlled for medication and IQ effects, (ii) replicated in independent groups of males and females, and (iii) charted in individuals and groups. The resulting mapping strategy reveals a shifting pattern of tissue loss in schizophrenia. Aspects of the anatomy and dynamics of disease are uncovered, in a changing profile that implicates genetic and nongenetic patterns of deficits.
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            Linkage strategies for genetically complex traits. I. Multilocus models.

            N Risch (1990)
            In order to investigate linkage detection strategies for genetically complex traits, multilocus models of inheritance need to be specified. Here, two types of multilocus model are described: (1) a multiplicative model, representing epistasis (interaction) among loci, and (2) an additive model, which is shown to closely approximate genetic heterogeneity, which is characterized by no interlocus interaction. A ratio lambda R of risk for type R relatives that is compared with population prevalence is defined. For a single-locus model, lambda R - 1 decreases by a factor of two with each degree of relationship. The same holds true for an additive multilocus model. For a multiplicative (epistasis) model, lambda R - 1 decreases more rapidly than by a factor of two with degree of relationship. Examination of lambda R values for various classes of relatives can potentially suggest the presence of multiple loci and epistasis. For example, data for schizophrenia suggest multiple loci in interaction. It is shown in the second paper of this series that lambda R is the critical parameter in determining power to detect linkage by using affected relative pairs.
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              Cognitive training in mental disorders: update and future directions.

              This article reviews the conceptual basis, definitions, and evolution of cognitive training approaches for the treatment of mental disorders.
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                Author and article information

                Journal
                Medicine (Baltimore)
                Medicine (Baltimore)
                MEDI
                Medicine
                Wolters Kluwer Health
                0025-7974
                1536-5964
                July 2016
                29 July 2016
                : 95
                : 30
                : e4406
                Affiliations
                [a ]Institute of Clinical Medicine, College of Medicine, National Cheng Kung University
                [b ]Department of Psychiatry, Chimei Medical Center
                [c ]Department of Health, Jianan Mental Hospital
                [d ]Department of Applied Life Science and Health, Chia Nan University of Pharmacy and Science
                [e ]Department of Psychiatry, Kaohsiung Veterans General Hospital Tainan Branch
                [f ]Department of Acupressure Technology, Chung Hwa University of Medical Technology
                [g ]Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University
                [h ]Biostatistics Consulting Center, National Cheng Kung University Hospital, Tainan, Taiwan.
                Author notes
                []Correspondence: Sheng-Hsiang Lin, Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, 138, Shengli Road, Tainan, Taiwan (e-mail: shlin922@ 123456mail.ncku.edu.tw ).
                Article
                04406
                10.1097/MD.0000000000004406
                5265874
                27472737
                93e32881-7c90-42e8-8948-0ce1606ad6fd
                Copyright © 2016 the Author(s). Published by Wolters Kluwer Health, Inc. All rights reserved.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially. http://creativecommons.org/licenses/by-nc/4.0

                History
                : 1 February 2016
                : 5 July 2016
                : 6 July 2016
                Categories
                5000
                Research Article
                Observational Study
                Custom metadata
                TRUE

                endophenotype,familial aggregation,minor physical anomalies,neurodevelopmental markers,recurrence risk ratio,schizophrenia

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