Predicting human height by Victorian and genomic methods

Abstract

In the Victorian era, Sir Francis Galton showed that 'when dealing with the transmission of stature from parents to children, the average height of the two parents, y is all we need care to know about them' (1886). One hundred and twenty-two years after Galton's work was published, 54 loci showing strong statistical evidence for association to human height were described, providing us with potential genomic means of human height prediction. In a population-based study of 5748 people, we find that a 54-loci genomic profile explained 4-6% of the sex-and age-adjusted height variance, and had limited ability to discriminate tall/short people, as characterized by the area under the receiver-operating characteristic curve (AUC). In a family-based study of 550 people, with both parents having height measurements, we find that the Galtonian mid-parental prediction method explained 40% of the sex-and age-adjusted height variance, and showed high discriminative accuracy. We have also explored how much variance a genomic profile should explain to reach certain AUC values. For highly heritable traits such as height, we conclude that in applications in which parental phenotypic information is available (eg, medicine), the Victorian Galton's method will long stay unsurpassed, in terms of both discriminative accuracy and costs. For less heritable traits, and in situations in which parental information is not available (eg, forensics), genomic methods may provide an alternative, given that the variants determining an essential proportion of the trait's variation can be identified.

Predicting quantitative traits from genome and phenome with near perfect accuracy

“…There is almost no missing narrow-or broad-sense heritability, proving that very accurate genome-aided predictions can be obtained in practice, in contrast to relatively poor genomic prediction performance for human cohorts, for example, R 2 o0.16 using unrelated individuals, and o0.37 for ARTICLE close relatives 9 . Our predictions outperformed the traditional mid-parent approach that is limited to narrow-sense heritability, but has been predicted to remain unsurpassed in accuracy for humans 30 .…”

Seeing the forest through the gene‐trees

“…But we can gain a better understanding of genetic causation in a different way, taking a hint from the observation that criteria such as parental trait values-Francis Galton's original criteria for the heritable effects of quantitative traits-currently yield better predictions of offspring trait values than do genes identified by conventional GWAS. 56 This is easy to understand. Correlations among relatives aggregate all genetic effects without the need for them to be enumerated.…”

Is Life Law-Like?

“…Individuals are connected by the genomic flux from parent to offspring or horizontally by infection. Flux involves individual molecules but life is an aggregate phenomenon, and this is why heritability may be in some ways as useful as enumerative genomic prediction (Aulchenko et al 2009).…”