A strong relationship has been found between the shape of the cerebral cortex – the brain’s outer layer of neural tissue – and genetic ancestry.
A research team at the University of California in San Diego used genetics data – the Pediatric Imaging, Neurocognition and Genetics study (PING) – and analysis of the geometry of the cerebral cortex and managed to predict genetic ancestry.
“The geometry of the brain’s cortical surface contains rich information about ancestry. Even in the modern contemporary US population, with its melting pot of different cultures, it was still possible to correlate brain cortex structure to ancestral background,” said research associate Chun Chieh Fan.
In the study, published in Current Biology, the team used a subset of the PING data including neuroimaging and genotyping data from 562 children aged 12 years and older. The scientists determined the different ancestral lineages in each child and mapped the shape of the children’s cerebral cortex.
By comparing genetic data, the researchers managed to predict with a relatively high degree of accuracy an individual’s genetic ancestry based on the geometry of their cerebral cortex. They found that the differences in cortex shapes between the various ancestries are subtle, but systematic.
“We looked to see how well we could predict how much genetic ancestry they had from Africa, Europe and so forth. There were various systematic differences, particularly in the folding and gyrification patterns of the cortex. Those patterns were quite strongly reflective of genetic ancestry,” said research associate Professor Terry Jernigan.
The team discovered that the cortical patterns variation accounted for 47-66% among individuals in their genetic ancestry, depending on the ancestral lineage. They believe that understanding the differences in the brain structure will be important in refining future brain studies.
“In order to understand what might be abnormal for a particular individual, it is very important to control for the differences in brain structure that are simply reflective of genetic ancestry. We need to develop better genetically informed analysis for detecting abnormalities in the brain and for measuring differences in the brain that might account for disease symptoms. This study is a step in the right direction and has implications for how people conduct brain research going forward,” said Professor Jernigan.