Twin studies have been critical in determining the contributions of genetic and environmental factors to normal brain structure and for understanding abnormalities of brain development that underlie neurodevelopmental and neuropsychiatric disorders. In adults and older children, twin studies indicate that genes play a significant role in the variability of global brain volumes, including total brain, total gray and total white matter volumes. Other than this current study, there have been no studies of twin brain development in early childhood, the period of brain development implicated in the pathogenesis of many psychiatric disorders. In the first funding cycle of this grant, we used prenatal ultrasound and neonatal MRI to study discordance of early brain development, and to determine genetic and environmental contributions to neonatal brain structure. We have and have developed a unique and valuable cohort of twins, having recruited and scanned over 100 twin pairs. We found that discordance of prenatal brain size in MZ twins is similar to that in DZ twins, but that by 1 month after birth, discordance of overall brain volume in MZ twins is already less than in DZ twins. Statistical modeling of neonatal MRI brain volumes in our twin cohort indicates that global tissue volumes are highly heritable, similar to that observed in older children and adults, though gray matter heritability may is somewhat less. Therefore, it appears that genetic programs act very early in postnatal brain development to determine global tissue volumes. Interestingly, preliminary longitudinal mapping of correlations in gray matter density indicate correlations decrease in the first year of life, perhaps as the result of rapid brain growth in the first years of life. We also found that while global white matter volumes are highly heritable, diffusion tensor properties of specific white matter tracts are not. In the next funding cycle, we propose to continue enlarging this unique cohort and to follow them through age 6 years with structural MRI, diffusion tensor imaging (DTI), and developmental assessments to determine how genetic and environmental factors contribute to brain development in the first years of life.
Twins studies play an important role in understanding the contributions of genes and environment to brain development and risk for psychiatric disease. While there have been twin studies of brain structure adults and older children, ours is the only twin study of brain development in the first years of life. We propose to continue our study of early childhood brain development in twins, using structural MRI, diffusion tensor imaging, and cognitive assessments.
|Sadeghi, Neda; Gilmore, John H; Gerig, Guido (2017) Twin-singleton developmental study of brain white matter anatomy. Hum Brain Mapp 38:1009-1024|
|Noel, Jean; Prieto, Juan C; Styner, Martin (2017) FADTTSter: Accelerating Hypothesis Testing With Functional Analysis of Diffusion Tensor Tract Statistics. Proc SPIE Int Soc Opt Eng 10137:|
|Wang, Yan; Ma, Guangkai; An, Le et al. (2017) Semisupervised Tripled Dictionary Learning for Standard-Dose PET Image Prediction Using Low-Dose PET and Multimodal MRI. IEEE Trans Biomed Eng 64:569-579|
|Xia, K; Zhang, J; Ahn, M et al. (2017) Genome-wide association analysis identifies common variants influencing infant brain volumes. Transl Psychiatry 7:e1188|
|Wei, Lifang; Cao, Xiaohuan; Wang, Zhensong et al. (2017) Learning-based deformable registration for infant MRI by integrating random forest with auto-context model. Med Phys 44:6289-6303|
|Lee, Seung Jae; Steiner, Rachel J; Yu, Yang et al. (2017) Common and heritable components of white matter microstructure predict cognitive function at 1 and 2 y. Proc Natl Acad Sci U S A 114:148-153|
|Hu, Shunbo; Wei, Lifang; Gao, Yaozong et al. (2017) Learning-based deformable image registration for infant MR images in the first year of life. Med Phys 44:158-170|
|Rekik, Islem; Li, Gang; Yap, Pew-Thian et al. (2017) Joint prediction of longitudinal development of cortical surfaces and white matter fibers from neonatal MRI. Neuroimage 152:411-424|
|Chen, Haiwei; Budin, Francois; Noel, Jean et al. (2017) White Matter Fiber-based Analysis of T1w/T2w Ratio Map. Proc SPIE Int Soc Opt Eng 10133:|
|Deng, Minghui; Yu, Renping; Wang, Li et al. (2016) Learning-based 3T brain MRI segmentation with guidance from 7T MRI labeling. Med Phys 43:6588|
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