Mapping genetic influences on ventricular structure in twins.

Area of Science:

• Neuroimaging
• Quantitative Genetics
• Human Brain Anatomy

Background:

• Understanding the genetic and environmental influences on human brain structure variability is crucial.
• Existing methods for measuring these effects in large neuroimaging datasets are limited.

Purpose of the Study:

• To develop and apply an automated system for visualizing genetic and environmental effects on brain structure using MRI data.
• To quantify the contributions of genetic and environmental factors to lateral ventricular volume variation in twins.

Main Methods:

• Utilized a multi-template segmentation approach called "Multi-Atlas Fluid Image Alignment" on 3D MRI scans of monozygotic (MZ) and dizygotic (DZ) twins.
• Applied quantitative genetic models to approximately 30,000 surface points to assess variance attributable to additive genetics (A), common environment (C), and unique environment (E).
• Generated surface-based statistical maps to visualize spatial patterns of heritability and gene-environment interactions.

Main Results:

• The 'ACE' model indicated that unique environmental influences (E=53.8%) were the largest contributors to lateral ventricular volume variation, followed by common environment (C=38.9%) and genetic factors (A=7.3%).
• Revealed spatially varying profiles of genetic versus environmental influences across the lateral ventricles.
• Suggested that earlier-maturing brain regions, like the occipital horns, might be more genetically influenced than later-maturing regions.

Conclusions:

• The developed automated system effectively visualizes gene-environment effects on brain structure in large MRI databases.
• Lateral ventricular volume is primarily influenced by unique environmental factors, with significant contributions from shared environment and genetics.
• The findings highlight the complex interplay of genetic and environmental factors in shaping human brain anatomy.