Results

VU - Vrije Universiteit Amsterdam

08/19/2019 | News release | Distributed by Public on 08/20/2019 02:24

Huge genetic study provides insight into how genes influence hundreds of human traits

The study is published in Nature Genetics and all results are available through a novel central database gwasATLAS_anchor_1.

A decade of genome-wide association studies (GWAS) has provided a wealth of genetic associations for hundreds of human traits. In this new study, the team of Posthuma systematically analyzed the results of virtually all published GWAS results. 'Our study provides insight into fundamental questions on the extent of pleiotropy across the genome, the nature of risk variants and the genetic architecture of complex traits', says Kyoko Watanabe, a PhD student in the group of Posthuma and the first author on the study.

Many genes influence multiple traits
'Pleiotropy' refers to the observation that one gene can influence multiple traits. 'Many traits are known to be influenced by hundreds of genes, and given that we have a finite number of genes in our genome, it has been hypothesized that pleiotropy is ubiquitous in our genome. In the current study we quantified this, by analyzing the results of well-powered GWAS studies for more than 500 different traits', explains Posthuma.

More than half the genome was found to be associated with at least one trait, and 66% of 17.5k tested genes were associated with at least one trait. Of these associated genes, 81% were associated with multiple traits.
'These results show that pleiotropy is the rule rather than the exception, and that one gene can be involved in hundreds of different traits. Thus, variations in one gene may for example be associated with a slight increase in risk of being bald, a tiny decrease in the risk of being neurotic, and may add 0.02 cm to a person's height', says Watanabe.

The finding that the majority of genes are influencing multiple traits suggests that strategies such as gene-editing for complex traits based on GWAS results can be risky. 'One problem is that GWAS results do not provide causal variants, but provide a range of variants that might include the causal variant. A second problem is that to influence one trait via gene-editing, one would need to edit hundreds of variants in hundreds of genes, and since these genes may not only influence the targeted trait, unintended effects on hundreds of other traits may occur', says Posthuma.

The study also found several genes which were specific to one disease or trait. 'These genes are highly informative for that particular trait, and therefore the most interesting targets for functional follow-up studies and drug developments', says Posthuma.