Your IQ in 13 Genes (Or About 29% of It)

I have already said that I favour the gene hunters over the gene saboteurs. That said, I keep a bleary and cynical eye open when gene hunters find something, lest I be led up the garden path by false positives.

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And yet, and yet, if one manages to put together a very large sample, and checks the findings against those obtained from other large samples, it ought to be possible to run one’s fingertips across the face of reality. Gene hunters tend to lead the pack when it comes to sample size.

With this in mind it is a rare pleasure to report the findings of a team who have found something. {snip}

Published the day before yesterday, in Molecular Psychiatry, advance online publication, 3 February 2015; doi:10.1038/mp.2014.188, this multi-author paper merits the breathless categorization of an “Immediate Communication”. In short, they have made a major advance in tracking down some genes which are very likely to be involved in intelligence. Here is the abstract:

General cognitive function is substantially heritable across the human life course from adolescence to old age. We investigated the genetic contribution to variation in this important, health- and well-being-related trait in middle-aged and older adults. We conducted a meta-analysis of genome-wide association studies of 31 cohorts (N = 53 949) in which the participants had undertaken multiple, diverse cognitive tests. A general cognitive function phenotype was tested for, and created in each cohort by principal component analysis. We report 13 genome-wide significant single-nucleotide polymorphism (SNP) associations in three genomic regions, 6q16.1, 14q12 and 19q13.32 (best SNP and closest gene, respectively: rs10457441, P = 3.93 × 10− 9, MIR2113; rs17522122, P = 2.55 × 10− 8, AKAP6; rs10119, P = 5.67 × 10 − 9, APOE/TOMM40). We report one gene-based significant association with the HMGN1 gene located on chromosome 21 (P=1×10− 6). These genes have previously been associated with neuropsychiatric phenotypes.

Meta-analysis results are consistent with a polygenic model of inheritance. To estimate SNP-based heritability, the genome-wide complex trait analysis procedure was applied to two large cohorts, the Atherosclerosis Risk in Communities Study (N = 6617) and the Health and Retirement Study (N = 5976). The proportion of phenotypic variation accounted for by all genotyped common SNPs was 29% (s.e. = 5%) and 28% (s.e. = 7%), respectively. Using polygenic prediction analysis, ~ 1.2% of the variance in general cognitive function was predicted in the Generation Scotland cohort (N = 5487; P = 1.5 × 10− 17). In hypothesis-driven tests, there was significant association between general cognitive function and four genes previously associated with Alzheimer’s disease: TOMM40, APOE, ABCG1 and MEF2C.

https://drive.google.com/file/d/0B3c4TxciNeJZUjdEVHF4dkVtaTQ/view?usp=sharing

The paper has a particularly good introductory section, which is worth reading in its own right as a starting point in understanding intelligence and ageing.

Participants were individuals from 31 population-based cohorts of European ancestry aged 45 years or older excluding dementia and clinical stroke (including self-reported stroke). The total sample size was 53 949 individuals (N men = 23 030, N women = 30 919).  Intelligence was estimated by extracting a principal components factor from a range of heterogenous mental tasks, and this factor accounted for 34% to 62% of the variance. Therefore, large populations given the same mental tasks might provide even higher g estimates, though the procedure seems to work well with disparate measures.

However, if one moves from the samples of discovery to a sample of replication then only 1.2% of the variance in that new sample can be explained by the patterns detected in the samples of discovery. Nonetheless, to be able to explain so much variance in a human behaviour on the basis of so few genes is intriguing, particularly when these genes are linked in other studies with cognitive ageing.

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Now the race is on to confirm, disconfirm and extend these findings.