Gene-environment interactions in the influence of maternal education on adolescent neurodevelopment using ABCD study

Runye Shi¹, Xiao Chang^{2

3

4

5}, Tobias Banaschewski⁶, Gareth J Barker⁷, Arun L W Bokde⁸, Sylvane Desrivières⁹, Herta Flor^{10

11}, Antoine Grigis¹², Hugh Garavan¹³, Penny Gowland¹⁴, Andreas Heinz¹⁵, Rüdiger Brühl¹⁶, Jean-Luc Martinot¹⁷, Marie-Laure Paillère Martinot¹⁸, Eric Artiges^{17

19}, Frauke Nees^{6

10

20}, Dimitri Papadopoulos Orfanos¹², Luise Poustka²¹, Sarah Hohmann^{6

22}, Nathalie Holz⁶, Michael N Smolka²³, Nilakshi Vaidya²⁴, Henrik Walter¹⁵, Robert Whelan²⁵, Gunter Schumann^{24

26}, Xiaolei Lin¹, Jianfeng Feng^{1

2

3

4

5

27}; IMAGEN Consortium

Affiliations

¹ School of Data Science, Fudan University, Shanghai, China.
² Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
³ Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
⁴ MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
⁵ Zhangjiang Fudan International Innovation Center, Shanghai, China.
⁶ Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany.
⁷ Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
⁸ Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.
⁹ Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
¹⁰ Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany.
¹¹ Department of Psychology, School of Social Sciences, University of Mannheim, 68131 Mannheim, Germany.
¹² NeuroSpin, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France.
¹³ Departments of Psychiatry and Psychology, University of Vermont, 05405 Burlington, VT, USA.
¹⁴ Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK.
¹⁵ Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin, Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
¹⁶ Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany.
¹⁷ Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie", Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France.
¹⁸ AP-HP, Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France.
¹⁹ Psychiatry Department, EPS Barthélémy Durand, Etampes, France.
²⁰ Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein Kiel University, Kiel, Germany.
²¹ Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075 Göttingen, Germany.
²² Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
²³ Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
²⁴ Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Germany.
²⁵ School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland.
²⁶ Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China.
²⁷ Department of Computer Science, University of Warwick, Coventry, UK.

PMID: 39546599
PMCID: PMC11567010
DOI: 10.1126/sciadv.adp3751

Gene-environment interactions in the influence of maternal education on adolescent neurodevelopment using ABCD study

Runye Shi et al. Sci Adv. 2024.

. 2024 Nov 15;10(46):eadp3751.

doi: 10.1126/sciadv.adp3751. Epub 2024 Nov 15.

Authors

Affiliations

¹ School of Data Science, Fudan University, Shanghai, China.
² Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
³ Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
⁴ MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
⁵ Zhangjiang Fudan International Innovation Center, Shanghai, China.
⁶ Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany.
⁷ Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
⁸ Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.
⁹ Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
¹⁰ Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany.
¹¹ Department of Psychology, School of Social Sciences, University of Mannheim, 68131 Mannheim, Germany.
¹² NeuroSpin, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France.
¹³ Departments of Psychiatry and Psychology, University of Vermont, 05405 Burlington, VT, USA.
¹⁴ Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK.
¹⁵ Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin, Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
¹⁶ Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany.
¹⁷ Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie", Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France.
¹⁸ AP-HP, Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France.
¹⁹ Psychiatry Department, EPS Barthélémy Durand, Etampes, France.
²⁰ Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein Kiel University, Kiel, Germany.
²¹ Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075 Göttingen, Germany.
²² Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
²³ Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
²⁴ Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Germany.
²⁵ School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland.
²⁶ Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China.
²⁷ Department of Computer Science, University of Warwick, Coventry, UK.

PMID: 39546599
PMCID: PMC11567010
DOI: 10.1126/sciadv.adp3751

Abstract

Maternal education was strongly correlated with adolescent brain morphology, cognitive performances, and mental health. However, the molecular basis for the effects of maternal education on the structural neurodevelopment remains unknown. Here, we conducted gene-environment-wide interaction study using the Adolescent Brain Cognitive Development cohort. Seven genomic loci with significant gene-environment interactions (G×E) on regional gray matter volumes were identified, with enriched biological functions related to metabolic process, inflammatory process, and synaptic plasticity. Additionally, genetic overlapping results with behavioral and disease-related phenotypes indicated shared biological mechanism between maternal education modified neurodevelopment and related behavioral traits. Finally, by decomposing the multidimensional components of maternal education, we found that socioeconomic status, rather than family environment, played a more important role in modifying the genetic effects on neurodevelopment. In summary, our study provided analytical evidence for G×E effects regarding adolescent neurodevelopment and explored potential biological mechanisms as well as social mechanisms through which maternal education could modify the genetic effects on regional brain development.

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Figures

**Fig. 1.. The influence of ME on regional GMVs.**
(A) Spearman correlations between ME and regional GMVs, adjusting for age, site, handedness, sex, and estimated intracranial volume. Regions in gray indicate nonsignificant correlations after BH-FDR correction. (B) Longitudinal effects of ME on cortical (left) and subcortical brain GMVs. Both GMVs (top) and GMV change rate (bottom) for participants with high, medium, and low levels of ME are estimated. The bands indicate 95% confidence intervals for predicted GMV at the top and relative regression coefficients at the bottom.

**Fig. 2.. Genomic loci with genome-wide significant main and interaction effects with ME on regional brain GMVs.**
SNPs in red indicate interaction effects only, while those in purple indicate both main and interaction effects. These SNPs are then mapped to functional genes using position, molecular phenotype quantitative trait loci, chromatin interaction, and in silico functional prediction mapping methods. Genes involved in synaptic plasticity, inflammatory process, and metabolic process are highlighted in purple, brown, and green, respectively. Plot created using PhenoGram (http://visualization.ritchielab.org).

**Fig. 3.. Validation of G×ME and the interpretation of the influence of ME on neurodevelopment.**
(A) Validation of significant GEWIS results obtained from ABCD using the leave-out samples as an internal validation (top) and independent adolescent study IMAGEN as an external validation (bottom). (B) Genetic overlap between SNPs showing G×ME effects on regional brain GMVs and those showing strong associations with multiple diseases and related traits. * indicates a significant overlap after BY-FDR correction. BMI, body mass index; WCadjBMI, waist circumference–adjusted BMI; IBD, inflammatory bowel disease; MS, multiple sclerosis; RA, rheumatoid arthritis; ADHD, attention-deficit/hyperactivity disorder; ASD, autism; Dep, depression; SCZ, schizophrenia; BIP, bipolar disorder; AD, Alzheimer’s disease; PD, Parkinson’s disease. (C) Significant G×ME effects after adjusting for family or social environmental factors. * indicates remained genome-wide significant G×ME effects. FCS, family conflict score; PMS, parenting monitoring score; ADI, area deprivation index; HI, household income.

See this image and copyright information in PMC

References

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Gene-environment interactions in the influence of maternal education on adolescent neurodevelopment using ABCD study

Affiliations

Gene-environment interactions in the influence of maternal education on adolescent neurodevelopment using ABCD study

Authors

Affiliations

Abstract

Figures

References

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources