Fri, Mar 24, 2017 | updated 09:51 AM IST

Study helps finding genetic blueprint of human brain

Updated: Sep 07, 2016 17:57 IST
Washington D.C. [USA], Sept. 7 (ANI): A study of healthy twins, 65 years of age or older, has unlocked important clues about how genes

influence the development of key grey matter structures, paving the way for a genetic blueprint of the human brain.

The objective was to map the genetic relatedness (or heritability) of cortical and subcortical structures in their brains.

These structures are responsible for functions ranging from memory and visual processing, to motor control.

Lead researcher Professor Wei Wen said, "We know that genes strongly underpin brain development. But we still don't understand which

specific genes are implicated, or how they contribute to different brain structures."

"In order to identify these genes, we need to first know whether they are shared by different parts of the brain, or unique to a single

structure. This is the first attempt to examine genetic correlations between all of the brain's structures, using the twin design," he

added.

The team analysed MRI scans of 93 sets of identical twins and 68 sets of fraternal twins.

These participants were all Caucasian men and women without dementia, with an average age of 70, living in the Eastern states of Australia.

The scientists measured the volume of their brain structures (12 in total) and, using statistical and genetic modelling, determined the

heritability for each. Heritability is the extent to which genes contribute to phenotypic, or physical, differences.

Some of the major key findings were that the volume of cortical and subcortical brain structures have moderate to strong genetic

contributions (between 40 and 80percent). The subcortical hippocampus, which play a key role in memory processes, has a genetic contribution

greater than 70% in older people.

The study found cortical structures, including the frontal lobe (movement, memory and motivation) and occipital lobe (visual processing), have genetic contributions greater than 70 percent.

And finally, the data suggests that there are three genetically correlated clusters within the brain. These are regions where the same

sets of genes seem to be influencing multiple structures.

One cluster involves the four cortical lobe structures, while the other two involve clusters of subcortical structures.

Professor Perminder Sachdev said, "The presence of these three genetically correlated clusters is the most significant result, and is where the novelty of the work lies."

"It gives us a blueprint for forming a new model of the brain, subdivided into genetically linked structures. This we can apply to the analysis of big data, and use to more effectively hunt for the specific genes involved in brain development," he added.

Sachdev said the classical twin design is an important tool for understanding whether physical or behavioural traits have a genetic determinant.

Twin studies compare the similarity of a given trait (or characteristic) between monozygotic (identical) twins, who share 100

percent of their DNA, and dizygotic (fraternal) twins, who share 50 percent of their DNA.

In these studies, if a physical trait is considerably more similar for identical twins than fraternal twins, this suggests a strong genetic

contribution.

Despite finding strong genetic contributions across all structures examined, Sachdev said he was surprised by the low genetic correlation

between cortical and subcortical structures.

These structures tended to have unique genetic determinants, and were only weakly related.

"It's a reminder that the brain is an incredibly complex organ, which cannot be treated as a homogenous structure for genetic purposes," he

said.

The researchers are hopeful that their results will lead to progress in the field and a better understanding of the genetic blueprint of the human brain.

"This is one of the crucial first steps that needed to be taken," said Sachdev.

Adding, "It's a long way away, but if we can understand the genetic basis for variability in human brains, we can begin to understand the

mechanisms that cause these differences, and that also underpin the development of diseases in future."

The study was published in Scientific Reports journal.(ANI)

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