Missing heritability: is the gap closing? An analysis of 32 complex traits in the Lifelines Cohort Study

Abstract

Despite the recent explosive rise in number of genetic markers for complex disease traits identified in genome-wide association studies, there is still a large gap between the known heritability of these traits and the part explained by these markers. To gauge whether this 'heritability gap' is closing, we first identified genome-wide significant SNPs from the literature and performed replication analyses for 32 highly relevant traits from five broad disease areas in 13 436 subjects of the Lifelines Cohort. Next, we calculated the variance explained by multi-SNP genetic risk scores (GRSs) for each trait, and compared it to their broad-and narrow-sense heritabilities captured by all common SNPs. The majority of all previously-associated SNPs (median = 75%) were significantly associated with their respective traits. All GRSs were significant, with unweighted GRSs generally explaining less phenotypic variance than weighted GRSs, for which the explained variance was highest for height (15.5%) and varied between 0.02 and 6.7% for the other traits. Broad-sense common-SNP heritability estimates were significant for all traits, with the additive effect of common SNPs explaining 48.9% of the variance for height and between 5.6 and 39.2% for the other traits. Dominance effects were uniformly small (0-1.5%) and not significant. On average, the variance explained by the weighted GRSs accounted for only 10.7% of the common-SNP heritability of the 32 traits. These results indicate that GRSs may not yet be ready for accurate personalized prediction of complex disease traits limiting widespread adoption in clinical practice.

Efficient estimation and applications of cross-validated genetic predictions

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“…Polygenic risk scores (PRS), aggregate the contributions of multiple genetic variants to a phenotype [Torkamani et al (2018)]. These scores can be calculated using routinely recorded genotypes [Torkamani et al (2018); Nolte et al (2017)], are strongly associated with heritable traits [Nolte et al (2017)], and are independent of environmental exposures or other factors that are uncorrelated with germ line genetic variants. These properties have motivated a rapidly expanding list of applications from basic science (e.g.…”

Full genetic analysis for genome-wide association study of Fangji: a powerful approach for effectively dissecting the molecular architecture of personalized traditional Chinese medicine

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Assessing genetic risk of hypertension at an early age: future research directions

“…Although much more gene finding is still needed to bridge the heritability gap of complex traits like BP [33], the most recent encouraging findings from BP GWAS in adults have moved us one step closer to more accurate prediction of hypertension in early life. A concerted effort to integrate genomics and epigenomics of both hypertension and its underlying risk factors in combination with much larger GWAS efforts in longitudinal cohorts of children with much more detailed phenotypes as well as accurate recording of relevant environmental exposures will be key to advancing this research field in the near future.…”