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Transl Psychiatry. 2017 Aug 1;7(8):e1188. doi: 10.1038/tp.2017.159.

Genome-wide association analysis identifies common variants influencing infant brain volumes.

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Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.
Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA.
Curriculum in Neurobiology, University of North Carolina, Chapel Hill, NC, USA.
Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.
Department of Biostatistics, MD Andersen Cancer Center, University of Texas, Houston, TX, USA.
Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, USC Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.
Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.


Genome-wide association studies (GWAS) of adolescents and adults are transforming our understanding of how genetic variants impact brain structure and psychiatric risk, but cannot address the reality that psychiatric disorders are unfolding developmental processes with origins in fetal life. To investigate how genetic variation impacts prenatal brain development, we conducted a GWAS of global brain tissue volumes in 561 infants. An intronic single-nucleotide polymorphism (SNP) in IGFBP7 (rs114518130) achieved genome-wide significance for gray matter volume (P=4.15 × 10-10). An intronic SNP in WWOX (rs10514437) neared genome-wide significance for white matter volume (P=1.56 × 10-8). Additional loci with small P-values included psychiatric GWAS associations and transcription factors expressed in developing brain. Genetic predisposition scores for schizophrenia and ASD, and the number of genes impacted by rare copy number variants (CNV burden) did not predict global brain tissue volumes. Integration of these results with large-scale neuroimaging GWAS in adolescents (PNC) and adults (ENIGMA2) suggests minimal overlap between common variants impacting brain volumes at different ages. Ultimately, by identifying genes contributing to adverse developmental phenotypes, it may be possible to adjust adverse trajectories, preventing or ameliorating psychiatric and developmental disorders.

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