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      Genome-wide association study of emotional empathy in children

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          Abstract

          The genetic contribution to different aspects of empathy is now established, although the exact loci are unknown. We undertook a genome-wide association study of emotional empathy (EE) as measured by emotion recognition skills in 4,780 8-year old children from the ALSPAC cohort who were genotyped and imputed to Phase 1 version 3 of the 1000 Genomes Project. We failed to find any genome-wide significant signal in either our unstratified analysis or analysis stratified according to sex. A gene-based association analysis similarly failed to find any significant loci. In contrast, our transcriptome-wide association study (TWAS) with a whole blood reference panel identified two significant loci in the unstratified analysis, residualised for the effects of age, sex and IQ. One signal was for CD93 on chromosome 20; this gene is not strongly expressed in the brain, however. The other signal was for AL118508, a non-protein coding pseudogene, which completely lies within CD93’s genomic coordinates, thereby explaining its signal. Neither are obvious candidates for involvement in the brain processes that underlie emotion recognition and its developmental pathways.

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          The social brain in psychiatric and neurological disorders.

          Daniel Kennedy, Ralph Adolphs (2012)
          Psychiatric and neurological disorders have historically provided key insights into the structure-function relationships that subserve human social cognition and behavior, informing the concept of the 'social brain'. In this review, we take stock of the current status of this concept, retaining a focus on disorders that impact social behavior. We discuss how the social brain, social cognition, and social behavior are interdependent, and emphasize the important role of development and compensation. We suggest that the social brain, and its dysfunction and recovery, must be understood not in terms of specific structures, but rather in terms of their interaction in large-scale networks. Copyright © 2012 Elsevier Ltd. All rights reserved.
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            Revealing the complex genetic architecture of obsessive–compulsive disorder using meta-analysis

            Michael Wagner, Kathleen D. Askland, Cristina Barlassina … (2017)
            Two obsessive-compulsive disorder (OCD) genome-wide association studies (GWASs) have been published by independent OCD consortia, the International Obsessive-Compulsive Disorder Foundation Genetics Collaborative (IOCDF-GC) and the OCD Collaborative Genetics Association Study (OCGAS), but many of the top-ranked signals were supported in only one study. We therefore conducted a meta-analysis from the two consortia, investigating a total of 2688 individuals of European ancestry with OCD and 7037 genomically matched controls. No single-nucleotide polymorphisms (SNPs) reached genome-wide significance. However, in comparison with the two individual GWASs, the distribution of P-values shifted toward significance. The top haplotypic blocks were tagged with rs4733767 (P=7.1 × 10-7; odds ratio (OR)=1.21; confidence interval (CI): 1.12-1.31, CASC8/CASC11), rs1030757 (P=1.1 × 10-6; OR=1.18; CI: 1.10-1.26, GRID2) and rs12504244 (P=1.6 × 10-6; OR=1.18; CI: 1.11-1.27, KIT). Variants located in or near the genes ASB13, RSPO4, DLGAP1, PTPRD, GRIK2, FAIM2 and CDH20, identified in linkage peaks and the original GWASs, were among the top signals. Polygenic risk scores for each individual study predicted case-control status in the other by explaining 0.9% (P=0.003) and 0.3% (P=0.0009) of the phenotypic variance in OCGAS and the European IOCDF-GC target samples, respectively. The common SNP heritability in the combined OCGAS and IOCDF-GC sample was estimated to be 0.28 (s.e.=0.04). Strikingly, ∼65% of the SNP-based heritability in the OCGAS sample was accounted for by SNPs with minor allele frequencies of ⩾40%. This joint analysis constituting the largest single OCD genome-wide study to date represents a major integrative step in elucidating the genetic causes of OCD.
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              Tuning the developing brain to social signals of emotions.

              Andrew Nelson, Jukka M Leppänen (2008)
              Humans in different cultures develop a similar capacity to recognize the emotional signals of diverse facial expressions. This capacity is mediated by a brain network that involves emotion-related brain circuits and higher-level visual-representation areas. Recent studies suggest that the key components of this network begin to emerge early in life. The studies also suggest that initial biases in emotion-related brain circuits and the early coupling of these circuits and cortical perceptual areas provide a foundation for a rapid acquisition of representations of those facial features that denote specific emotions.
              Article 0 comments Cited 125 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                M. R. Woodbury-Smith:
                ORCID: http://orcid.org/0000-0002-0593-8917
                marc.woodbury-smith@newcastle.ac.uk
                Journal
                Journal ID (nlm-ta): Sci Rep
                Journal ID (iso-abbrev): Sci Rep
                Title: Scientific Reports
                Publisher: Nature Publishing Group UK (London )
                ISSN (Electronic): 2045-2322
                Publication date (Electronic): 4 May 2020
                Publication date PMC-release: 4 May 2020
                Publication date Collection: 2020
                Volume: 10
                Electronic Location Identifier: 7469
                Affiliations
                [1 ]ISNI 0000 0001 0462 7212, GRID grid.1006.7, Translational and Clinical Research Institute, Newcastle University, ; Newcastle upon Tyne, UK
                [2 ]ISNI 0000 0004 0473 9646, GRID grid.42327.30, The Centre for Applied Genomics, The Hospital for Sick Children, ; Toronto, ON Canada
                [3 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Division of Epidemiology and Biostatistics, Dalla Lana School of Public Health, University of Toronto, ; Toronto, ON Canada
                [4 ]ISNI 0000 0000 8793 5925, GRID grid.155956.b, Centre for Addiction and Mental Health, The Hospital for Sick Children & University of Toronto, ; Toronto, ON Canada
                [5 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, McLaughlin Centre and Department of Molecular Genetics, University of Toronto, ; Toronto, ON Canada
                Author information
                http://orcid.org/0000-0002-0593-8917
                http://orcid.org/0000-0002-8326-1999
                Article
                Publisher ID: 62693
                DOI: 10.1038/s41598-020-62693-6
                PMC ID: 7198552
                PubMed ID: 32366958
                SO-VID: c98880fb-1368-45e2-b195-bcaf4b69f471
                Copyright © © The Author(s) 2020
                License:

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                Date received : 13 August 2019
                Date accepted : 13 March 2020
                Categories
                Subject: Article
                Custom metadata
                issue-copyright-statement © The Author(s) 2020

                ScienceOpen disciplines: Uncategorized
                Keywords: quantitative trait,prefrontal cortex
                Data availability:
                ScienceOpen disciplines: Uncategorized
                Keywords: quantitative trait, prefrontal cortex

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