In the largest genome study to date, a team led by scientists at the University of Queensland (UQ) has analyzed genetic data of nearly 5.4 million people from 281 genome-wide association studies (GWAS) to identify 12,111 common variations in the genome associated with differences in height. The study, published in the journal Nature, will enable better assessments of growth in children and more accurate predictions of height. The findings could also aid the prediction of height from a suspect’s DNA sample during forensic investigations.

Senior author of the study, Loïc Yengo Dimbou, PhD, is a statistical geneticist and group leader of the Statistical Genomics Laboratory at the University of Queensland.

“Eighty percent of height differences between people are determined by genetic factors,” said Loïc Yengo Dimbou, PhD, a statistical geneticist and group leader of the Statistical Genomics Laboratory at UQ and a senior author of the study. “The 12,000 variants that we found explain 40% of height differences, meaning we’ve opened the door for DNA to be used to predict height more accurately than ever before. Currently, a child’s height is best predicted using the average height of their two biological parents, but using this genomic data, pediatricians will be able to get a better estimate. It will put parents’ minds at ease if children are growing as their genes predict, or it will trigger further medical investigation and help pick up potential issues sooner.”

Dimbou and co-senior author, Peter Visscher, PhD, professor and chair of quantitative genetics at UQ’s Institute for Molecular Bioscience worked with 600 researchers for the completion of this study, including Joel Hirschhorn, PhD, a professor at Boston Children’s Hospital and Harvard Medical School, Andrew Wood, PhD, senior lecturer at the University of Exeter, Yukinori Okada, PhD, a professor at Osaka University, as well as other colleagues in the GIANT consortium. The large sample size analyzed in the study overcomes the limitations of scattered data from smaller studies conducted earlier and is the first to identify height-associated variant clusters near genes involved in skeletal growth disorders.

“This feat marks a milestone in our understanding of the contribution of genetics to complex traits,” noted Karoline Kuchenbaecker, PhD, a professor of genetic epidemiology at the University College of London in an independent perspective article on the study published in the same issue of Nature. “It also highlights the essential work still to be done to close the diversity gap in existing genetic data.”

Height in adults is a heritable and easily measurable parameter that provides a model complex trait for assessing the relationship between genotype (the genetic variations present at a given location in the genome) and phenotype (an observable characteristic in an individual). While Dimbou confirmed that the GWAS study included at least a million individuals of non-European ancestry, which was higher than usual, he admitted that the data was still skewed toward people of European ancestry (75.8%) and poses a problem. “There is a growing number of worldwide initiatives to collect more diverse genetic data because it is critical to widen the benefit of genetic studies to all populations,” said Dimbou.

Identification of the remaining genetic factors for height will be a more formidable task as these are expected to have subtler effects on height. This may require an even larger sample size, said Dimbou. Nevertheless, the current study establishes that sufficiently large sample sizes can yield saturated maps of regions in the genome that contribute to variations in a complex trait.

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