ESPE Yearbook of Paediatric Endocrinology

J Bone Miner Res 36, 2300–2308. (2021)Abstract: https://pubmed-ncbi-nlm-nih-gov.proxy.kib.ki.se/34346115/

In brief: The genetic basis of human body height is only partly understood. This study combined genome-wide association study (GWAS) data with expression data from specific chondrocyte populations to identify genes responsible for skeletal growth. They found strong associations of height variability and genes expressed in early differentiation stages.

Commentary: Research on the genetic regulation of human height is a complex area: lack of human growth plate material, numerous involved regulatory pathways and species-specifc features of the growth plate are among the main burdens of a better understanding of the genetics of body height variability.

Renthal et al. used GWAS data from 700,000 individuals (from the GIANT consortium) and correlated height-associated loci with expression data of specific chondrocyte differentiation stages, derived from both micro dissected murine growth plates and from a mesenchymal cell line.

As a proof of concept, the authors could show an association with height in the GWAS data with a set of 287 genes associated with skeletal disorders. By linking the expression profiles of differential stages of growth plate chondrocytes with GWAS data, the authors could for the first time prove that height is predominantly associated with variants in genes enriched in the reserve zone (stated as the ‘round layer’). Further, they confirmed the association of height with genes specific for early differential stages by using RNAseq data from an immortalized mesenchymal cell line. Interestingly, this association was only in part driven by genes linked to monogenic skeletal disorders. Thus, the data emphasizes the importance of general progenitor chondrocytes physiology in the variability of human linear growth. The identified genes revealed enrichment in several expression pathways including Wnt signalling, PTHrP, TGFb and matrix proteins as major superfamilies.

This study impressively illustrates the potential of large GWAS datasets in combination with gene expression data from tissues of interest, in particular in separate differentiation stages as demonstrated with growth plate chondrocytes. Although the different approaches using expression data from growth plates and from a cell line do not show perfect overlaps, high levels of association of early differentiation stage-specific genes with height-associated loci in the GWAS data could be identified. With the increasing availability of GWAS datasets, similar approaches could spur future efforts to identify critical regulatory genes and potential treatment targets.