| Title |
Genome-wide association analysis identifies common variants influencing infant brain volumes
|
|---|---|
| Published in |
Translational Psychiatry, August 2017
|
| DOI | 10.1038/tp.2017.159 |
| Pubmed ID | |
| Authors |
K Xia, J Zhang, M Ahn, S Jha, J J Crowley, J Szatkiewicz, T Li, F Zou, H Zhu, D Hibar, P Thompson, P F Sullivan, M Styner, J H Gilmore, R C Knickmeyer |
| Abstract |
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. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 84 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 15% |
| Student > Master | 11 | 13% |
| Student > Ph. D. Student | 9 | 11% |
| Student > Bachelor | 8 | 10% |
| Student > Doctoral Student | 7 | 8% |
| Other | 10 | 12% |
| Unknown | 26 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 16 | 19% |
| Medicine and Dentistry | 9 | 11% |
| Psychology | 8 | 10% |
| Biochemistry, Genetics and Molecular Biology | 8 | 10% |
| Agricultural and Biological Sciences | 6 | 7% |
| Other | 5 | 6% |
| Unknown | 32 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 August 2017.
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#17,910,703
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Outputs from Translational Psychiatry
#2,760
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Outputs of similar age from Translational Psychiatry
#69
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