Genetic and environmental influences on neuroimaging phenotypes: A meta-analytical perspective on twin imaging studies

Blokland, G. A. M., de Zubicaray, Greig I., McMahon, K. L., & Wright, M. J. (2012) Genetic and environmental influences on neuroimaging phenotypes: A meta-analytical perspective on twin imaging studies. Twin Research and Human Genetics, 15(3), pp. 351-371.

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Because brain structure and function are affected in neurological and psychiatric disorders, it is important to disentangle the sources of variation in these phenotypes. Over the past 15 years, twin studies have found evidence for both genetic and environmental influences on neuroimaging phenotypes, but considerable variation across studies makes it difficult to draw clear conclusions about the relative magnitude of these influences. Here we performed the first meta-analysis of structural MRI data from 48 studies on >1,250 twin pairs, and diffusion tensor imaging data from 10 studies on 444 twin pairs. The proportion of total variance accounted for by genes (A), shared environment (C), and unshared environment (E), was calculated by averaging A, C, and E estimates across studies from independent twin cohorts and weighting by sample size. The results indicated that additive genetic estimates were significantly different from zero for all metaanalyzed phenotypes, with the exception of fractional anisotropy (FA) of the callosal splenium, and cortical thickness (CT) of the uncus, left parahippocampal gyrus, and insula. For many phenotypes there was also a significant influence of C. We now have good estimates of heritability for many regional and lobar CT measures, in addition to the global volumes. Confidence intervals are wide and number of individuals small for many of the other phenotypes. In conclusion, while our meta-analysis shows that imaging measures are strongly influenced by genes, and that novel phenotypes such as CT measures, FA measures, and brain activation measures look especially promising, replication across independent samples and demographic groups is necessary.

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72 citations in Web of Science®
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ID Code: 85681
Item Type: Journal Article
Refereed: Yes
Keywords: Heritability, Magnetic resonance imaging, Meta-analysis, Neuroimaging genetics, Review, Twin study
DOI: 10.1017/thg.2012.11
ISSN: 1839-2628
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Copyright Owner: Copright 2012 The Authors
Deposited On: 07 Sep 2015 07:01
Last Modified: 25 Jun 2017 04:01

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