| Title: | The genetic architecture of the corpus callosum and its genetic overlap with common neuropsychiatric diseases |
| Journal: | Journal of Affective Disorders |
| Published: | 8 May 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37164063/ |
| DOI: | https://doi.org/10.1016/j.jad.2023.05.002 |
| Citations: | 6 (6 in last 2 years) as of 8 Aug 2024 |
Publication 11417
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Abstract
BACKGROUND: The corpus callosum (CC) is the main structure transferring information between the cerebral hemispheres. Although previous large-scale genome-wide association study (GWAS) has illustrated the genetic architecture of white matter integrity of CC, CC volume is less stressed.</p>
METHODS: Using MRI data from 33,861 individuals in UK Biobank, we conducted univariate and multivariate GWAS for CC fractional anisotropy (FA) and volume with PLINK 2.0 and MOSTest. All discovered SNPs in the multivariate framework were functionally annotated in FUMA v1.3.8. In the meanwhile, a series of gene property analyses was conducted simultaneously. In addition, we estimated genetic relationship between CC metrics and other neuropsychiatric traits and diseases.</p>
RESULTS: We identified a total of 36 and 82 significant genomic loci for CC FA and volume (P < 5 × 10-8). And 53 and 27 genes were respectively mapped by four mapping strategies. For CC volume, gene-set analysis revealed pathways mainly relating to cell migration; cell-type analysis found the top enrichment in neuroglia while for CC FA in GABAergic neurons. Furthermore, we found a lot of genetic overlap and shared loci between CC FA and volume and common neuropsychiatric diseases.</p>
DISCUSSION: Collectively, this study helps to better understand the genetic architecture of whole CC and CC subregions. However, the way to divide CC FA and volume in our study restricts the interpretations of our results. Future work will be needed to pay attention to the genetic structure of white matter volume, and an appropriate division of CC may help to better understand CC structure.</p>
9 Authors
- Si-Jia Chen
- Bang-Sheng Wu
- Yi-Jun Ge
- Shi-Dong Chen
- Ya-Nan Ou
- Qiang Dong
- Jianfeng Feng
- Wei Cheng
- Jin-Tai Yu
1 Application
| Application ID | Title |
|---|---|
| 19542 | Identifying multi-level biomarkers and disease mechanisms for major mental disorders |
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