| Literature DB >> 31828294 |
Tristram A Lett1,2, Bob O Vogel1, Stephan Ripke1,3,4, Carolin Wackerhagen1, Susanne Erk1, Swapnil Awasthi1,4, Vassily Trubetskoy1,4, Eva J Brandl1, Sebastian Mohnke1, Ilya M Veer1, Markus M Nöthen5,6, Marcella Rietschel7, Franziska Degenhardt5,6, Nina Romanczuk-Seiferth1, Stephanie H Witt7, Tobias Banaschewski8, Arun L W Bokde9, Christian Büchel10, Erin B Quinlan11, Sylvane Desrivières11, Herta Flor12,13, Vincent Frouin14, Hugh Garavan15, Penny Gowland16, Bernd Ittermann17, Jean-Luc Martinot18, Marie-Laure Paillère Martinot19, Frauke Nees8,12, Dimitri Papadopoulos-Orfanos14, Tomáš Paus20, Luise Poustka21, Juliane H Fröhner22, Michael N Smolka22, Robert Whelan23, Gunter Schumann11, Heike Tost7, Andreas Meyer-Lindenberg7, Andreas Heinz1, Henrik Walter1.
Abstract
Recent large-scale, genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with general intelligence. The cumulative influence of these loci on brain structure is unknown. We examined if cortical morphology mediates the relationship between GWAS-derived polygenic scores for intelligence (PSi) and g-factor. Using the effect sizes from one of the largest GWAS meta-analysis on general intelligence to date, PSi were calculated among 10 P value thresholds. PSi were assessed for the association with g-factor performance, cortical thickness (CT), and surface area (SA) in two large imaging-genetics samples (IMAGEN N = 1651; IntegraMooDS N = 742). PSi explained up to 5.1% of the variance of g-factor in IMAGEN (F1,1640 = 12.2-94.3; P < 0.005), and up to 3.0% in IntegraMooDS (F1,725 = 10.0-21.0; P < 0.005). The association between polygenic scores and g-factor was partially mediated by SA and CT in prefrontal, anterior cingulate, insula, and medial temporal cortices in both samples (PFWER-corrected < 0.005). The variance explained by mediation was up to 0.75% in IMAGEN and 0.77% in IntegraMooDS. Our results provide evidence that cumulative genetic load influences g-factor via cortical structure. The consistency of our results across samples suggests that cortex morphology could be a novel potential biomarker for neurocognitive dysfunction that is among the most intractable psychiatric symptoms.Entities:
Keywords: cortical thickness; genetics; intelligence; mediation; surface area
Mesh:
Year: 2020 PMID: 31828294 PMCID: PMC7175009 DOI: 10.1093/cercor/bhz270
Source DB: PubMed Journal: Cereb Cortex ISSN: 1047-3211 Impact factor: 4.861