Rare genetic variants explain missing heritability in smoking

Abstract

Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.

Figure 1.

SNP-based heritability estimates in the European ancestry sample for each of the six MAF/LD bins, and sums across bins. Error bars represent standard errors. The “Rare” bin is the sum of the MAF 0.1–1% and MAF 0.01–0.1%. “Common” is the sum of the other MAF bins. “Total” is the sum of “Rare” and “Common”. HI and LO each indicate high and low LD. All estimates were adjusted for by demographic variables and 20 PCs (half of them from rare variants) as fixed effects along with random effect of cohort except for CigDay which was adjusted for 5 common PCs to allow model convergence.

Figure 2.

SNP-based heritability estimates in the European ancestry sample from sensitivity analyses Error bars represent standard errors. The figure shows SNP-based heritability estimates from different sensitivity conditions. Heritability was estimated after adjusting for 20 common and 20 rare variant PCs (“40 PCs”), 50 common and 50 rare variant PCs (“100 PCs”), after removing individuals who share IBD segments more than 2.5% of the total genome length (“long IBD”), after adjusting for the top 20 PCs from the IBD-based GRM matrix (“IBD PCs”), and after adjusting for recruitment site as a random effect (“Site”).

Figure 3.

Comparison of heritability estimates between current and published studies. The figure shows SNP heritability estimates across different studies. Error bars denote standard errors. “Pedigree” and “Pedigree-FHS” refer to ${{\widehat{h}}^2}_{\mathrm{p}\mathrm{e}\mathrm{d}}$ from whole TOPMed pedigree samples and FHS only. “WGS_EUR” and “WGS_AFR” refer to WGS-based SNP heritability estimates in individuals of European and African ancestries. Note that WGS_AFR is based on common variants only for all phenotypes except for SmkInit which includes the contribution from MAF 0.1–1% variants additionally. “Evans_imputed” and “Liu_LDSC” each refer to SNP heritability estimates from Evans et al. (MAF:1–50%, relatedness threshold=.02⁷⁹) and LDSC analysis from a recent meta-analysis of tobacco use. The red dotted line indicates the heritability estimate of smoking from a recent large meta-analysis of twin studies.