| Literature DB >> 32047264 |
Aldo Córdova-Palomera1, Dennis van der Meer2,3, Tobias Kaufmann2, Francesco Bettella2, Yunpeng Wang2,4, Dag Alnæs2, Nhat Trung Doan2, Ingrid Agartz5,6,7, Alessandro Bertolino8,9, Jan K Buitelaar10,11, David Coynel12,13, Srdjan Djurovic14,15, Erlend S Dørum2,16,17, Thomas Espeseth16, Leonardo Fazio9, Barbara Franke18, Oleksandr Frei2, Asta Håberg19,20, Stephanie Le Hellard14, Erik G Jönsson2,6, Knut K Kolskår2,16,17, Martina J Lund2, Torgeir Moberget2,16, Jan E Nordvik21, Lars Nyberg22, Andreas Papassotiropoulos12,23,24, Giulio Pergola9, Dominique de Quervain12,13, Antonio Rampino9, Genevieve Richard2,16,17, Jaroslav Rokicki2,16, Anne-Marthe Sanders2,16,17, Emanuel Schwarz25, Olav B Smeland2, Vidar M Steen14,26, Jostein Starrfelt27, Ida E Sønderby2,15, Kristine M Ulrichsen2,16,17, Ole A Andreassen2, Lars T Westlye28,29.
Abstract
Sensitivity to external demands is essential for adaptation to dynamic environments, but comes at the cost of increased risk of adverse outcomes when facing poor environmental conditions. Here, we apply a novel methodology to perform genome-wide association analysis of mean and variance in ten key brain features (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, intracranial volume, cortical surface area, and cortical thickness), integrating genetic and neuroanatomical data from a large lifespan sample (n = 25,575 individuals; 8-89 years, mean age 51.9 years). We identify genetic loci associated with phenotypic variability in thalamus volume and cortical thickness. The variance-controlling loci involved genes with a documented role in brain and mental health and were not associated with the mean anatomical volumes. This proof-of-principle of the hypothesis of a genetic regulation of brain volume variability contributes to establishing the genetic basis of phenotypic variance (i.e., heritability), allows identifying different degrees of brain robustness across individuals, and opens new research avenues in the search for mechanisms controlling brain and mental health.Entities:
Mesh:
Year: 2020 PMID: 32047264 DOI: 10.1038/s41380-020-0664-1
Source DB: PubMed Journal: Mol Psychiatry ISSN: 1359-4184 Impact factor: 15.992