A genome-wide association study (GWAS) has identified 15 new genomic loci and 40 new genes for intelligence. Some of the newly identified genes also appear to influence several neuropsychiatric and metabolic disorders. Finally, there appear to be correlations between some of the genes and traits sometimes attributed to lifestyle choices—smoking, for example, and educational attainment. These findings, which are based on a meta-analysis of nearly 80,000 individuals, not only shed light on the genetic foundations of intelligence, they also suggest that genetics may help explain the associations between intelligence and many socioeconomic and health-related outcomes.
The new findings appeared May 22 in the journal Nature Genetics, in an article entitled, “Genome-Wide Association Meta-Analysis of 78,308 Individuals Identifies New Loci and Genes Influencing Human Intelligence.” The article, the work of an international research team headed by scientists of Vrije Universiteit Amsterdam, emphasizes that the identified genes are predominantly expressed in brain tissue. The article also asserts that pathway analysis implicates the genes in the regulation of cell development.
“We identify 336 associated SNPs in 18 genomic loci, of which 15 are new,” the article’s authors wrote. “Around half of the SNPs are located inside a gene, implicating 22 genes, of which 11 are new findings. Gene-based analyses identified an additional 30 genes, of which all but one had not been implicated previously.”
The authors added that despite the well-known difference in twin-based heritability for intelligence in childhood (0.45) and adulthood (0.80), the new findings are consistent with substantial genetic correlation.
“These results are very exciting as they provide very robust associations with intelligence,” said Danielle Posthuma, Ph.D., principal investigator of the study. “The genes we detect are involved in the regulation of cell development, and are specifically important in synapse formation, axon guidance, and neuronal differentiation. These findings for the first time provide clear clues toward the underlying biological mechanisms of intelligence.”
Although intelligence is one of the most investigated traits in humans, only a handful of genes had previously been associated with intelligence, and for most of these genes the findings were not reliable.
The article’s authors also describe how they used whole-genome LD (linkage disequilibrium) score regression to calculate genetic correlations with 32 traits. Significant genetic correlations, the authors indicated, were observed with 14 traits: “The strongest, positive genetic correlation was with educational attainment. Moderate, positive genetic correlations were observed with smoking cessation, intracranial volume, head circumference in infancy, autism spectrum disorder, and height. Moderate negative genetic correlations were observed with Alzheimer's disease, depressive symptoms, having ever smoked, schizophrenia, neuroticism, waist-to-hip ratio, body mass index, and waist circumference.”
“These genetic correlations shed light on common biological pathways for intelligence and other traits,” noted Suzanne Sniekers, Ph.D., the study’s first author and a researcher in Dr. Posthuma’s laboratory. “Seven genes for intelligence are also associated with schizophrenia; nine genes also with body mass index, and four genes were also associated with obesity. These three traits show a negative correlation with intelligence. So, a variant of gene with a positive effect on intelligence has a negative effect on schizophrenia, body mass index, or obesity.”
Future studies will need to clarify the exact role of these genes in intelligence in order to obtain a more complete picture of how genetic differences lead to differences in intelligence. “The current genetic results explain up to 5% of the total variance in intelligence. Although this is quite a large amount of variance for a trait as intelligence, there is still a long road to go: Given the high heritability of intelligence, many more genetic effects are expected to be important, and these can only be detected in even larger samples,” concluded Dr. Posthuma.