Genome-wide association meta-analysis of more than 75,000 individuals identifies new loci and genes influencing human intelligence

As these GEITP emails have often described, genome-wide association studies, GWAS (most of which began to be published in 2oo6 and more recently) are studies to attempt to find a genotype (DNA genes or genetic loci) that is statistically significantly STRONGLY associated (P < 5.0 x 10–8, also designated as P < 5.0e–08) with a phenotype, (multifactorial trait). This trait (or phenotype) can be schizophrenia, coronary heart disease, bipolar disorder, type-2 diabetes, obesity, height, weight, serum uric acid levels, etc. It has become increasingly clear that –– the larger the cohort –– the more variance it is that can be explained. [Variance explained (R2) is "that proportion of phenotypic variance (the dependent variable) explained by genetic factors and/or environmental factors (the predictor).] Increasingly commplicated phenotypes can now be tackled. For example, "Intelligence" is associated with important economic and health-related life outcomes. Despite Intelligence having substantial heritability (h2 = 0.54) and a confirmed polygenic nature, initial genetic studies have mostly been underpowered. Authors [see attached paper] report a meta-analysis for intelligence of 78,308 individuals. They identified 336 associated single-nucleotide polymmorphism (SNP) DNA variants (METAL P < 5 × 10–8) in 18 genomic loci, of which 15 are new. About half of the SNPs are located inside a gene –– implicating 22 genes, of which 11 are novel findings. [For an explanation of METAL statistical analysis, please see: "METAL: fast and efficient meta-analysis of genomewide association scans" Bioinformatics 2o1o; 26: 2190–2191.] Gene-based analyses identified an additional 30 genes (MAGMA P < 2.73 × 10–6) –– of which all but one had not been implicated previously. [For an explanation of MAGMA statistical analysis, please see "MAGMA: generalized gene-set analysis of GWAS data" PloS Comput Biol 2o15; 11: e1004219.] Authors show that the identified genes are predominantly expressed in brain tissue, and pathway analysis indicates the involvement of genes regulating cell development (MAGMA competitive P = 3.5 × 10–6). Despite the well-known difference in twin-based heritability for intelligence in childhood (h2 =0.45) and adulthood (h2 =0.80), authors show substantial genetic correlation (rg = 0.89; LD score regression P = 5.4 × 10–29). These intriguing findings provide new insight into the genetic architecture of intelligence. Nature Genet July 2017; 49: 1107–111