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      Structural and Functional Neuroimaging of Polygenic Risk for Schizophrenia: A Recall-by-Genotype–Based Approach

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          Abstract

          Risk profile scores (RPS) derived from genome-wide association studies (GWAS) explain a considerable amount of susceptibility for schizophrenia (SCZ). However, little is known about how common genetic risk factors for SCZ influence the structure and function of the human brain, largely due to the constraints of imaging sample sizes. In the current study, we use a novel recall-by-genotype (RbG) methodological approach, where we sample young adults from a population cohort (Avon Longitudinal Study of Parents and Children: N genotyped = 8365) based on their SCZ-RPS. We compared 197 healthy individuals at extremes of low ( N = 99) or high ( N = 98) SCZ-RPS with behavioral tests, and structural and functional magnetic resonance imaging (fMRI). We first provide methodological details that will inform the design of future RbG studies for common SCZ genetic risk. We further provide an between group analysis of the RbG individuals (low vs high SCZ-RPS) who underwent structural neuroimaging data (T1—weighted scans) and fMRI data during a reversal learning task. While we found little evidence for morphometric differences between the low and high SCZ-RPS groups, we observed an impact of SCZ-RPS on blood oxygen level-dependent (BOLD) signal during reward processing in the ventral striatum ( P FWE-VS-CORRECTED = .037), a previously investigated broader reward-related network ( P FWE-ROIS-CORRECTED = .008), and across the whole brain ( P FWE-WHOLE-BRAIN-CORRECTED = .013). We also describe the study strategy and discuss specific challenges of RbG for SCZ risk (such as SCZ-RPS related homoscedasticity). This study will help to elucidate the behavioral and imaging phenotypes that are associated with SCZ genetic risk.

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          Statistical improvements in functional magnetic resonance imaging analyses produced by censoring high-motion data points.

          Subject motion degrades the quality of task functional magnetic resonance imaging (fMRI) data. Here, we test two classes of methods to counteract the effects of motion in task fMRI data: (1) a variety of motion regressions and (2) motion censoring ("motion scrubbing"). In motion regression, various regressors based on realignment estimates were included as nuisance regressors in general linear model (GLM) estimation. In motion censoring, volumes in which head motion exceeded a threshold were withheld from GLM estimation. The effects of each method were explored in several task fMRI data sets and compared using indicators of data quality and signal-to-noise ratio. Motion censoring decreased variance in parameter estimates within- and across-subjects, reduced residual error in GLM estimation, and increased the magnitude of statistical effects. Motion censoring performed better than all forms of motion regression and also performed well across a variety of parameter spaces, in GLMs with assumed or unassumed response shapes. We conclude that motion censoring improves the quality of task fMRI data and can be a valuable processing step in studies involving populations with even mild amounts of head movement. Copyright © 2013 Wiley Periodicals, Inc.
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            Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N=112 151)

            People's differences in cognitive functions are partly heritable and are associated with important life outcomes. Previous genome-wide association (GWA) studies of cognitive functions have found evidence for polygenic effects yet, to date, there are few replicated genetic associations. Here we use data from the UK Biobank sample to investigate the genetic contributions to variation in tests of three cognitive functions and in educational attainment. GWA analyses were performed for verbal–numerical reasoning (N=36 035), memory (N=112 067), reaction time (N=111 483) and for the attainment of a college or a university degree (N=111 114). We report genome-wide significant single-nucleotide polymorphism (SNP)-based associations in 20 genomic regions, and significant gene-based findings in 46 regions. These include findings in the ATXN2, CYP2DG, APBA1 and CADM2 genes. We report replication of these hits in published GWA studies of cognitive function, educational attainment and childhood intelligence. There is also replication, in UK Biobank, of SNP hits reported previously in GWA studies of educational attainment and cognitive function. GCTA-GREML analyses, using common SNPs (minor allele frequency>0.01), indicated significant SNP-based heritabilities of 31% (s.e.m.=1.8%) for verbal–numerical reasoning, 5% (s.e.m.=0.6%) for memory, 11% (s.e.m.=0.6%) for reaction time and 21% (s.e.m.=0.6%) for educational attainment. Polygenic score analyses indicate that up to 5% of the variance in cognitive test scores can be predicted in an independent cohort. The genomic regions identified include several novel loci, some of which have been associated with intracranial volume, neurodegeneration, Alzheimer's disease and schizophrenia.
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              Ventral-striatal responsiveness during reward anticipation in ADHD and its relation to trait impulsivity in the healthy population: a meta-analytic review of the fMRI literature.

              A review of the existing functional magnetic resonance imaging (fMRI) studies on reward anticipation in patients with attention-deficit/hyperactivity disorder (ADHD) is provided. Meta-analysis showed a significant medium effect size (Cohen's d=0.48-0.58) in terms of ventral-striatal (VS)-hyporesponsiveness in ADHD. Studies on VS-responsiveness and trait impulsivity in the healthy population demonstrate the opposite relationship, i.e. impulsivity-scores positively correlated with VS activation during reward processing. Against the background that ADHD may represent an extreme on a continuum of normal variability, the question arises as to how these contrasting findings can be integrated. We discuss three theoretical approaches, each of which integrates the opposing findings: (1) an inverted-u-shape model; (2) a (genetic) moderator model; and (3) the "unrelated model". We conclude that at the present stage the number of existing studies in the healthy population as well as in ADHD groups is too small for a final answer. Therefore, our presented integrative approaches should be understood as an attempt to frame future research directions by generating testable hypotheses and giving practical suggestions for future studies. Copyright © 2013 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Schizophr Bull
                Schizophr Bull
                schbul
                Schizophrenia Bulletin
                Oxford University Press (US )
                0586-7614
                1745-1701
                March 2019
                28 March 2018
                28 March 2018
                : 45
                : 2
                : 405-414
                Affiliations
                [1 ]Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
                [2 ]Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
                [3 ]MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Cardiff, UK
                [4 ]MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
                [5 ]School of Psychology, Durham University, Durham, UK
                [6 ]Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
                Author notes
                To whom correspondence should be addressed; Cardiff University Brain Research Imaging Centre, Maindy Road, Cardiff CF244HQ, UK; tel: +44(0)29 2087 0365, e-mail: lancastertm@ 123456cardiff.ac.uk
                Article
                sby037
                10.1093/schbul/sby037
                6403064
                29608775
                b51bd132-df8d-4d69-b4fd-2ce91e27ec01
                © The Author(s) 2018. 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 License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Pages: 10
                Funding
                Funded by: Medical Research Council 10.13039/501100000265
                Funded by: MRC Centre for Neuropsychiatric Genetics and Genomics
                Award ID: G0800509
                Categories
                Regular Articles

                Neurology
                schizophrenia,polygenic,recall-by-genotype,reward processing,imaging genetics
                Neurology
                schizophrenia, polygenic, recall-by-genotype, reward processing, imaging genetics

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