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      In Vivo Amygdala Nuclei Volumes in Schizophrenia and Bipolar Disorders

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          Abstract

          Abnormalities in amygdala volume are well-established in schizophrenia and commonly reported in bipolar disorders. However, the specificity of volumetric differences in individual amygdala nuclei is largely unknown. Patients with schizophrenia disorders (SCZ, N = 452, mean age 30.7 ± 9.2 [SD] years, females 44.4%), bipolar disorders (BP, N = 316, 33.7 ± 11.4, 58.5%), and healthy controls ( N = 753, 34.1 ± 9.1, 40.9%) underwent T1-weighted magnetic resonance imaging. Total amygdala, nuclei, and intracranial volume (ICV) were estimated with Freesurfer (v6.0.0). Analysis of covariance and multiple linear regression models, adjusting for age, age 2, ICV, and sex, were fitted to examine diagnostic group and subgroup differences in volume, respectively. Bilateral total amygdala and all nuclei volumes, except the medial and central nuclei, were significantly smaller in patients relative to controls. The largest effect sizes were found for the basal nucleus, accessory basal nucleus, and cortico-amygdaloid transition area (partial η 2 > 0.02). The diagnostic subgroup analysis showed that reductions in amygdala nuclei volume were most widespread in schizophrenia, with the lateral, cortical, paralaminar, and central nuclei being solely reduced in this disorder. The right accessory basal nucleus was marginally smaller in SCZ relative to BP ( t = 2.32, P = .05). Our study is the first to demonstrate distinct patterns of amygdala nuclei volume reductions in a well-powered sample of patients with schizophrenia and bipolar disorders. Volume differences in the basolateral complex (lateral, basal, and accessory basal nuclei), an integral part of the threat processing circuitry, were most prominent in schizophrenia.

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          The variable results of positive-negative research with schizophrenics underscore the importance of well-characterized, standardized measurement techniques. We report on the development and initial standardization of the Positive and Negative Syndrome Scale (PANSS) for typological and dimensional assessment. Based on two established psychiatric rating systems, the 30-item PANSS was conceived as an operationalized, drug-sensitive instrument that provides balanced representation of positive and negative symptoms and gauges their relationship to one another and to global psychopathology. It thus constitutes four scales measuring positive and negative syndromes, their differential, and general severity of illness. Study of 101 schizophrenics found the four scales to be normally distributed and supported their reliability and stability. Positive and negative scores were inversely correlated once their common association with general psychopathology was extracted, suggesting that they represent mutually exclusive constructs. Review of five studies involving the PANSS provided evidence of its criterion-related validity with antecedent, genealogical, and concurrent measures, its predictive validity, its drug sensitivity, and its utility for both typological and dimensional assessment.
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            Adjusting batch effects in microarray expression data using empirical Bayes methods.

            Non-biological experimental variation or "batch effects" are commonly observed across multiple batches of microarray experiments, often rendering the task of combining data from these batches difficult. The ability to combine microarray data sets is advantageous to researchers to increase statistical power to detect biological phenomena from studies where logistical considerations restrict sample size or in studies that require the sequential hybridization of arrays. In general, it is inappropriate to combine data sets without adjusting for batch effects. Methods have been proposed to filter batch effects from data, but these are often complicated and require large batch sizes ( > 25) to implement. Because the majority of microarray studies are conducted using much smaller sample sizes, existing methods are not sufficient. We propose parametric and non-parametric empirical Bayes frameworks for adjusting data for batch effects that is robust to outliers in small sample sizes and performs comparable to existing methods for large samples. We illustrate our methods using two example data sets and show that our methods are justifiable, easy to apply, and useful in practice. Software for our method is freely available at: http://biosun1.harvard.edu/complab/batch/.
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              An eleven item clinician-administered Mania Rating Scale (MRS) is introduced, and its reliability, validity and sensitivity are examined. There was a high correlation between the scores of two independent clinicians on both the total score (0.93) and the individual item scores (0.66 to 0.92). The MRS score correlated highly with an independent global rating, and with scores of two other mania rating scales administered concurrently. The score also correlated with the number of days of subsequent stay in hospital. It was able to differentiate statistically patients before and after two weeks of treatment and to distinguish levels of severity based on the global rating.
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                Author and article information

                Journal
                Schizophr Bull
                Schizophr Bull
                schbul
                Schizophrenia Bulletin
                Oxford University Press (US )
                0586-7614
                1745-1701
                September 2021
                22 January 2021
                22 January 2021
                : 47
                : 5
                : 1431-1441
                Affiliations
                [1 ]Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo , Section Vinderen, Oslo, Norway
                [2 ]Department of Psychiatric Research, Diakonhjemmet Hospital , Oslo, Norway
                [3 ]Department of Psychiatry, University of Oxford , Oxford, UK
                [4 ]Department of Psychology, University of Oslo , Oslo, Norway
                [5 ]Norwegian Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital , Oslo, Norway
                [6 ]Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm County Council , Stockholm, Sweden
                Author notes
                To whom correspondence should be addressed; tel: +47 22 02 99 67, fax: +47 22 02 99 01, e-mail: claudia.barth@ 123456medisin.uio.no
                Author information
                https://orcid.org/0000-0001-6544-0945
                Article
                sbaa192
                10.1093/schbul/sbaa192
                8379533
                33479754
                c38643c7-d852-4f72-9834-56cf61d1c5e8
                © The Author(s) 2021. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                Page count
                Pages: 11
                Funding
                Funded by: Research Council of Norway, DOI 10.13039/501100005416;
                Award ID: 223273
                Award ID: 250358
                Award ID: 286838
                Funded by: K. G. Jebsen Foundation;
                Award ID: SKGJ-MED-008
                Categories
                Regular Articles
                AcademicSubjects/MED00810

                Neurology
                amygdala,neuroimaging,schizophrenia,bipolar disorder,schizoaffective disorder,other psychotic disorders

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