Many of the non-significant results likely reflect limited statistical power rather than a true lack of heritability. Accounting for effective sample size (\(N_{eff}\)) [3] as a rough measure of statistical power, 56% of phenotypes with \(N_{eff}\) > 10,000, and an impressive 89.9% of phenotypes with \(N_{eff}\) > 100,000, have significant heritability estimates. To understand why negative estimates of heritability occur, please see the FAQ on the ldsc Github.

This widespread heritability across many traits shouldn’t be a surprise. Countless twin studies have shown a wide variety of traits are heritable, to the point the Eric Turkheimer famously proposed the first law of behavioral genetics: “all human behavioral traits are heritable”. But it’s encouraging to see molecular genetics evidence continue to support the same conclusion as previous methods that almost all human traits, not just behavior, have a heritable component.

Anthropometric measures are really heritable, but so is behavior

If you browse the heritability results (either in a table or in graphical form), one of the most obvious trends is that the top heritability results are often for anthropometric measures (i.e. physical measures of the human body).

Defining a “most heritable” phenotype depends a bit your choice of metric (e.g. highest \(h^2\) estimate, most significant \(h^2\) estimate, highest \(h^2\) conditional on significance level, etc), but height stands out from the crowd (\(h^2\)=.46, p=7.5e-109). This perhaps isn’t surprising, given that height was one of the first traits studied to formalize the concept of heritability in humans, has among the highest twin and family heritability estimates, and mapping specific genetic loci associated with height has been extremely successful over the past decade. Many less commonly studied anthropometric measures show similarly strong results (e.g. percentage of fat in each arm and leg, bone mineral density, impedance measures, waist circumference).

Many behavioral outcomes also show strong heritability though. Having a college degree appears near the top of the heritability results (\(h^2\)=.28, p=6.6e-195), consistent with previous work on the genetics of educational attainment. Multiple phenotypes related to alcohol consumption and cigarette smoking also show significant heritability, as do personality features (e.g. neuroticism, restlessness, mood swings). Even something as simple as the amount of time someone spends watching TV appears to be at least a little bit heritable (\(h^2\)=.096, p=2.8e-114).

The heritability of a trait is heavily influenced by the quality of the measurement of the trait. Heritability is a proportion of variation of the trait, meaning that increasing the measurement error will decrease the heritability. For anthropometric traits, many of these measures show extremely low variability in repeated measurement studies.

If anything, it’s more difficult to find phenotypes with strong evidence for a complete lack of heritability. At large effective sample sizes even very low heritability estimates around .01 for phenotypes, such as the amount of time employed at one’s current job or the death of a close relative in the last 2 years, have nominal statistical evidence for non-zero heritability. This may be evidence of some statistical artifact of LDSR at large sample sizes, or may reflect indirect influences of genetics on general health for example.

There’s still some inflation or model misspecification

In addition to heritability, LDSR also estimates an intercept term that aims to gauge the amount of confounding in each analysis (indeed, this was the original goal of LDSR). This confounding could be population stratification, subtle familial relatedness, or other model misspecification in the LDSR model.