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Dalmaz C, Barth B, Pokhvisneva I, Wang Z, Patel S, Quillfeldt JA, Mendonça Filho EJ, de Lima RMS, Arcego DM, Sassi RB, Hall GBC, Kobor MS, Meaney MJ, Silveira PP. Prefrontal cortex VAMP1 gene network moderates the effect of the early environment on cognitive flexibility in children. Neurobiol Learn Mem 2021; 185:107509. [PMID: 34454100 DOI: 10.1016/j.nlm.2021.107509] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 08/10/2021] [Accepted: 08/20/2021] [Indexed: 01/07/2023]
Abstract
During development, genetic and environmental factors interact to modify specific phenotypes. Both in humans and in animal models, early adversities influence cognitive flexibility, an important brain function related to behavioral adaptation to variations in the environment. Abnormalities in cognitive functions are related to changes in synaptic connectivity in the prefrontal cortex (PFC), and altered levels of synaptic proteins. We investigated if individual variations in the expression of a network of genes co-expressed with the synaptic protein VAMP1 in the prefrontal cortex moderate the effect of early environmental quality on the performance of children in cognitive flexibility tasks. Genes overexpressed in early childhood and co-expressed with the VAMP1 gene in the PFC were selected for study. SNPs from these genes (post-clumping) were compiled in an expression-based polygenic score (PFC-ePRS-VAMP1). We evaluated cognitive performance of the 4 years-old children in two cohorts using similar cognitive flexibility tasks. In the first cohort (MAVAN) we utilized two CANTAB tasks: (a) the Intra-/Extra-dimensional Set Shift (IED) task, and (b) the Spatial Working Memory (SWM) task. In the second cohort, GUSTO, we used the Dimensional Change Card Sort (DCCS) task. The results show that in 4 years-old children, the PFC-ePRS-VAMP1 network moderates responsiveness to the effects of early adversities on the performance in attentional flexibility tests. The same result was observed for a spatial working memory task. Compared to attentional flexibility, reversal learning showed opposite effects of the environment, as moderated by the ePRS. A parallel ICA analysis was performed to identify relationships between whole-brain voxel based gray matter density and SNPs that comprise the PFC-ePRS-VAMP1. The early environment predicts differences in gray matter content in regions such as prefrontal and temporal cortices, significantly associated with a genetic component related to Wnt signaling pathways. Our data suggest that a network of genes co-expressed with VAMP1 in the PFC moderates the influence of early environment on cognitive function in children.
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Affiliation(s)
- Carla Dalmaz
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada; Depto Bioquimica e PPG CB Bioquimica, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; PPG Neurociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
| | - Barbara Barth
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada; Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Irina Pokhvisneva
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
| | - Zihan Wang
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
| | - Sachin Patel
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
| | - Jorge A Quillfeldt
- PPG Neurociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; Depto Biofisica, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Euclides J Mendonça Filho
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
| | - Randriely Merscher Sobreira de Lima
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada; PPG Neurociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Danusa M Arcego
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada; Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Roberto Britto Sassi
- Mood Disorders Program, Department of Psychiatry & Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Geoffrey B C Hall
- Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, ON, Canada
| | - Michael S Kobor
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, Department of Medical Genetics, The University of British Columbia, 938 West 28th Avenue, Vancouver, BC V5Z 4H4, Canada
| | - Michael J Meaney
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada; Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada; Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR), Singapore
| | - Patrícia P Silveira
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada; Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada; PPG Neurociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
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Menezes IG, Duran VR, Mendonça Filho EJ, Veloso TJ, Sarmento SMS, Paget CL, Ruggeri K. Policy Implications of Achievement Testing Using Multilevel Models: The Case of Brazilian Elementary Schools. Front Psychol 2016; 7:1727. [PMID: 27933004 PMCID: PMC5120133 DOI: 10.3389/fpsyg.2016.01727] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 10/19/2016] [Indexed: 11/13/2022] Open
Abstract
Large-scale educational assessment has been established as source of descriptive, evaluative and interpretative information that influence educational policies worldwide throughout the last third of the twentieth century. In the 1990s the Brazilian Ministry of Education developed the National Basic Education Assessment System (SAEB) that regularly measures management, resource and contextual school features and academic achievement in public and private institutions. In 2005, after significant piloting and review of the SAEB, a new sampling strategy was taken and Prova Brasil became the new instrument used by the Ministry to assess skills in Portuguese (reading comprehension) and Mathematics (problem solving), as well as collecting contextual information concerning the school, principal, teacher, and the students. This study aims to identify which variables are predictors of academic achievement of fifth grade students on Prova Brasil. Across a large sample of students, multilevel models tested a large number of variables relevant to student achievement. This approach uncovered critical variables not commonly seen as significant in light of other achievement determinants, including student habits, teacher ethnicity, and school technological resources. As such, this approach demonstrates the value of MLM to appropriately nuanced educational policies that reflect critical influences on student achievement. Its implications for wider application for psychology studies that may have relevant impacts for policy are also discussed.
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Affiliation(s)
- Igor G Menezes
- Laboratory of Quantitative, Methods for Predictive Psychometrics, Psychology Institute, Federal University of BahiaSalvador, Brazil; Judge Business School, University of CambridgeCambridge, UK
| | - Victor R Duran
- Laboratory of Quantitative, Methods for Predictive Psychometrics, Psychology Institute, Federal University of Bahia Salvador, Brazil
| | - Euclides J Mendonça Filho
- Laboratory of Quantitative, Methods for Predictive Psychometrics, Psychology Institute, Federal University of Bahia Salvador, Brazil
| | - Tainã J Veloso
- Laboratory of Quantitative, Methods for Predictive Psychometrics, Psychology Institute, Federal University of Bahia Salvador, Brazil
| | - Stella M S Sarmento
- Laboratory of Quantitative, Methods for Predictive Psychometrics, Psychology Institute, Federal University of Bahia Salvador, Brazil
| | | | - Kai Ruggeri
- Policy Research Group, Department of Psychology, University of Cambridge Cambridge, UK
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