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The intelligence gene hunters have been stepping up their activities, and keep coming back with more trophies. Danielle Posthuma and colleagues are at it again, studying very large samples and finding further novel genes which load on brain tissues. I hope someone somewhere is keeping track of the overall picture, perhaps in a control room with multiple screens, like the NASA control centre of old, tracking the orbit of each SNP as it hoves into sight.
This is all very good, but it makes life difficult for mere commentators. When starting to write my comments I chose the working title “More genes for intelligence”. When trying to save it my Word program told me, somewhat severely, that I already had a document of that name. So, perhaps this note will have to read “Even more genes for intelligence.
This was the position in May: http://www.nature.com/ng/journal/v49/n7/full/ng.3869.html
Briefly, in a study of 78,308 individuals Sniekers et al. said:
We identify 336 associated SNPs (METAL P < 5 × 10−8) in 18 genomic loci, of which 15 are new. 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 (MAGMA P < 2.73 × 10−6), of which all but one had not been implicated previously. We 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 (0.45) and adulthood (0.80), we show substantial genetic correlation (rg = 0.89, LD score regression P = 5.4 × 10−29). These findings provide new insight into the genetic architecture of intelligence.
So, where are we in September?
GWAS meta-analysis (N=279,930) identifies new genes and functional links to intelligence. Savage et al. say:
Intelligence is highly heritable and a major determinant of human health and well-being. Recent genome-wide meta-analyses have identified 24 genomic loci linked to intelligence, but much about its genetic underpinnings remains to be discovered. Here, we present the largest genetic association study of intelligence to date (N=279,930), identifying 206 genomic loci (191 novel) and implicating 1,041 genes (963 novel) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and identify 89 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain and specifically in striatal medium spiny neurons and cortical and hippocampal pyramidal neurons. Gene-set analyses implicate pathways related to neurogenesis, neuron differentiation and synaptic structure. We confirm previous strong genetic correlations with several neuropsychiatric disorders, and Mendelian Randomization results suggest protective effects of intelligence for Alzheimer’s dementia and ADHD, and bidirectional causation with strong pleiotropy for schizophrenia. These results are a major step forward in understanding the neurobiology of intelligence as well as genetically associated neuro-psychiatric traits.
What is all this about?
As you know, I try to understand these procedures by analogy with code breaking. The actual DNA code comes all wrapped up, so it needs to be broken apart, shattered into pieces and then assembled again to reveal its underlying sequence. This involves some assumptions, but the mapping of the code is all about finding where everything is located, ideally precisely where it is in the sequence of base pairs. However, this approach loses the packaging information, so researchers pay attention to genetic linkage, the tendency of DNA sequences that are close together on a chromosome to be inherited together. Call this the packaging information. Guilt by association. Of course, this code is very complicated, but at least it has been road tested for millennia. This may account for many sections being conserved, on the sensible basis one does not tamper with the instructions on which life depends, even though some of those instruction may be redundant.
There are many techniques being used, and this paper describes the results of each in supplementary sections. Positional mapping means that genetic variants are linked to a gene when they are physically located inside that gene. Expression quantitative trait locus mapping (eQTL) links a genetic variant to a gene when that variant changes the expression of that gene. The variant is not necessarily located inside the gene. Chromatin interaction mapping links genetic variants to genes by looking at the 3D organization of chromosomes, which may allow remote genetic variants to influence a gene when they become close through DNA folding. Exonic variants are the parts which code for proteins, whereas introns do not. (Consider introns to be intervening sequences and exons to be expressed sequences). One day someone will write a user’s manual for all this research, though it will have to be updated every few months.
In gene-set analysis using the GWGAS results, six Gene Ontology gene-sets were significantly associated with intelligence: neurogenesis (Beta=0.153), neuron differentiation (Beta=0.178), central nervous system neuron differentiation (Beta=0.398), regulation of nervous system development (Beta=0.187), positive regulation of nervous system development (Beta=0.242), and regulation of synapse structure or activity(Beta=0.153). Conditional analysis indicated that there were three independent associations, for the neurogenesis, central nervous system neuron differentiation, and regulation of synapse structure or activity processes, which together accounted for the associations of the other three sets. Linking gene-based P-values to tissue-specific gene-sets, we observed strong associations across various brain areas (as shown in the figure), most strongly with the cortex (P=5.12×10-9), and specifically frontal cortex (P=4.94×10-9). In brain single-cell expression gene-set analyses, we found significant associations of striatal medium spiny neurons (P=1.47×10-13) and pyramidal neurons in the CA1 hippocampal (P=4×10-11) and cortical somatosensory regions (P=3×10-9).
Using polygenic score prediction we show that the current results explain up to 5.4% of the variance in four independent samples.
Our results also suggested a protective effect of intelligence on ADHD (OR=0.46) and Alzheimer’s disease (OR=0.66). In line with a positive genetic correlation, we observed that intelligence was associated with higher risk of autism (OR=1.47). There was evidence of a bidirectional association between intelligence and schizophrenia including a strong protective effect of intelligence on schizophrenia (OR=0.58), and a relatively smaller reverse effect (bxy= −0.195), with additional evidence for pleiotropy.
Once more the gene hunters are finding features of the genetic code which appear to be the building blocks of what makes brains intelligent. As has been found in most previous studies, these aspects are also related to important psychiatric disorders, opening up new lines of research. Despite the very healthy sample size, such association studies can only capture part of the variance, in my view because so much remains to be understood as to how the code leads to the proteins which lead to the tissues and their functions and capabilities.
Once the association studies get to the Hsu boundary (1 million) as will shortly be reported on by James Lee, we will be able to see how far association studies can get, given that we do not have any secret code book available for capture.
Finally, to follow my analogy, the code-breakers can now report:
After taking down lots of their messages, we can read about 5% of the enemy code. They are sending resources to the brain. This boosts their intelligence and protects them from attention deficit and dementing disorders, and also gives them some protection against schizophrenia, but leaves them with a liability to autism. We will crack the rest of the code in due course. However, if you could capture their code book, it would speed things up.