Heritability 2.0

Current best estimates of the heritability of g come from twin and adoption studies. The table below, from the recent paper: Molecular Psychiatry (2010) 15, 1112, gives you an idea of the general consistency of results from a number of twins studies with large statistics.



But now that we have inexpensive genotyping, we can study heritability of a quantitative trait by looking at unrelated (or only distantly related) individuals, and asking to what extent similarity in genotype is correlated with similarity in phenotype. A simple way to think about this is to imagine that we have a sample of N people for whom both phenotype (measured g score) and genotype (e.g., SNP profile) are known. Form all possible pairs and plot magnitude of difference in g score against genetic distance between the individuals in the pair. The g score difference should (on average) decrease as the genetic distance goes to zero (at which point the pair are MZ twins; but we avoid the confound of shared prenatal environment). Even if we have no identical twins in the sample, and even if none of the people in the sample are closely related to each other, we can extrapolate to zero genetic distance to obtain an estimate of heritability. An analysis along these lines (more technically, a global fit across all SNPs of total heritability) for height yields a result which is consistent with the narrow sense heritability estimate from twin and adoption studies. The results for g have not yet been published, but rumor has it that they also support earlier estimates such as those given above.

With this new technique one can average over a much larger range of environments. (As we know, heritability is only defined with respect to a specific range of environments.) One can form the sample from individuals who grew up in very deprived or very privileged families. One can even compare cohorts born in very different eras -- as long as DNA samples are available. For example, we can compare people born 80 years ago (i.e., who are still living and whose early adult IQs are known from military or school records) to each other, or even to people born as little as 15 or 20 years ago (assuming raw scores or cross norms are available). This kind of analysis may reveal something interesting about the Flynn Effect.

Update: The paper I referred to is out. It yields a lower bound on narrow sense heritability which is consistent with the earlier twin and adoption studies.

Genome-wide association studies establish that human intelligence is highly heritable and polygenic.

Abstract
General intelligence is an important human quantitative trait that accounts for much of the variation in diverse cognitive abilities. Individual differences in intelligence are strongly associated with many important life outcomes, including educational and occupational attainments, income, health and lifespan. Data from twin and family studies are consistent with a high heritability of intelligence, but this inference has been controversial. We conducted a genome-wide analysis of 3511 unrelated adults with data on 549,692 single nucleotide polymorphisms (SNPs) and detailed phenotypes on cognitive traits. We estimate that 40% of the variation in crystallized-type intelligence and 51% of the variation in fluid-type intelligence between individuals is accounted for by linkage disequilibrium between genotyped common SNP markers and unknown causal variants. These estimates provide lower bounds for the narrow-sense heritability of the traits. We partitioned genetic variation on individual chromosomes and found that, on average, longer chromosomes explain more variation. Finally, using just SNP data we predicted ∼1% of the variance of crystallized and fluid cognitive phenotypes in an independent sample (P=0.009 and 0.028, respectively). Our results unequivocally confirm that a substantial proportion of individual differences in human intelligence is due to genetic variation, and are consistent with many genes of small effects underlying the additive genetic influences on intelligence.