Using DNA To Predict Intelligence
Someone’s DNA could be used to predict their IQ for the first time, according to a new study. The research was the largest investigation into the link between intelligence and genetics ever, and was carried out by a collaboration of researchers at the University of Edinburgh, UK and Harvard University, USA. The work, which was published across two papers in Molecular Psychiatry, identified a total of 538 genes that are thought to be linked to intelligence.
The factors that affect a person’s intelligence have never been clearly understood. Previous research has suggested that anywhere between 50% and 75% of a person’s IQ is inherited from their parents, with the rest resulting from environmental factors like education and upbringing. This idea was developed during by observing differences in the IQ of identical twins, instead of studying the genes themselves; as a result, no one had identified any intelligence-linked genes.
To make up for this, the team examined genomic data from 24,090 participants in the Generation Scotland: Scottish Family Health Study in one study, and 248,482 individuals in the other. The first study compared the genomic data of closely related family members to determine more clearly what percentage of intelligence could be attributed to genetics. Their results demonstrated that genetics can account for up to 80% of the intelligence observed.
The second paper was focused specifically on identifying intelligence-linked genes through SNP-based and gene-based genome-wide association studies. Their analysis revealed 187 independent genetic loci that were associated with IQ, implicating 538 genes in variations in the phenotype.
“This paper exploited the high genetic correlations found between intelligence and education, increased the statistical power of a GWAS on intelligence, and attempted to find the loci and biological mechanisms that help explain intelligence differences, and the health differences with which they are associated,” the authors wrote. “Through the use of summary statistics drawn from a large GWAS on intelligence and education, and the latest release of the UK Biobank genetic data used in conjunction with a recently-developed method, MTAG, we were able to assemble the sample sizes required to achieve the high levels of statistical power needed to detect loci of small effect that explain differences in intelligence.”
Not only does this research help us to better understand the factors that can influence a person’s intelligence, it may enable us to develop an IQ DNA test. Such a test could be highly useful for clinicians when diagnosing cognitive disorders at a younger age.
The results could also have implications in other areas of healthcare.
“People with a higher level of cognitive function have been observed to have better physical and mental health, and to have longer lives,” the paper reads. “This paper exploited the high genetic correlations found between intelligence and education, increased the statistical power of a GWAS on intelligence, and attempted to find the loci and biological mechanisms that help explain intelligence differences, and the health differences with which they are associated.”
While previous research has demonstrated that a higher intelligence correlates to greater longevity, it was believed that the link was due to differences in lifestyle, such as higher paying jobs and a better standard of living. These new studies imply that this is not the case; instead, it would appear that people with higher intelligence also benefit from improved physical health.
“Future work using large GWAS that are exclusively based on established tests of intelligence will provide valuable samples in which to attempt replication of these findings,” the authors concluded. “The strength of the MTAG approach used here, drawing power from related phenotypes, lies in the accumulation of additional power to detect loci, make more accurate predictions based on SNP data, and the ability to identify the biological significance behind the polygenic signal in such data sets.”