iScienceNeurosciencePeer-reviewed journal article
Parent-offspring brain similarity: Specificities and commonalities across gender combinations - the Transmit Radiant Individuality to Offspring (TRIO) study
Abstract
Research suggests that parent-offspring brain similarities may underlie intergenerational transmission of psychopathology. However, most studies have focused on mothers and offspring, with few including fathers. This study aimed to extend understanding of parent-offspring neural similarities by examining parent-offspring trios. The study included 152 Japanese biological parent-offspring trios who participated in the Transmit Radiant Individuality to Offspring (TRIO) study. We analyzed the parent-offspring similarities in brain structural features (cortical thickness, surface area, local gyrification index, and subcortical volume) across different parent-offspring gender combinations (father-son, father-daughter, mother-son, and mother-daughter). Additionally, we investigated the relationship between brain similarities and similarities in intelligence and personality traits in parents and offspring. Our findings confirmed that correlations in brain structural features between father-offspring or mother-offspring dyads were significantly stronger than those between unrelated individuals. Notably, both sons and daughters exhibited brain regions similar to their fathers only, mothers only, both parents, or neither parent. Furthermore, a significant association was observed between similarities in general intelligence and the surface area of auditory regions in both father-offspring and mother-offspring dyads. These results provide valuable insights into the genetic and environmental factors influencing brain development and aging across generations. This study is expected to contribute to future research elucidating the mechanisms underlying the intergenerational transmission of psychiatric disorders.
- organism: human
- assay: imaging
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 3
- FWCI
- 1.76
- Field percentile
- top 16%
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