ISSN 1662-4009 (online)

ESPE Yearbook of Paediatric Endocrinology (2021) 18 4.11 | DOI: 10.1530/ey.18.4.11

Division of Endocrinology, Nemours Alfred I. duPont Hospital for Children, Wilmington, Delaware. USA.

J Clin Endocrinol Metab. 2020 Jun 1;105(6):dgaa131. doi: 10.1210/clinem/dgaa131. PMID: 32170311

Genetic control of height has been widely explored using genome-wide association studies (GWAS) in multi-ethnic populations (1-4). Although familial short stature (FSS) is the most common type of short stature, its genetic profile and impact on bone metabolism remains to be investigated. This GWAS study identifies 10 novel common genetic variants associated with FSS in 1163 Han Chinese subjects with FSS.

The selection criteria for FSS was (a) height less than the 3rd percentile, (b) father and/or mother height less than the 3rd percentile, (c) bone age appropriate for chronologic age, (d) normal onset of puberty, (e) normal annual growth rate, and (f) normal results of clinical and biochemistry evaluation. The control group consisted of 4168 individuals from the Taiwan Biobank and type 2 diabetes cohorts. For both participants and control subjects, genotyping by GWAS method was performed and a genetic predisposition score was calculated.

Ten novel genetic single nucleotide polymorphisms (SNPs) were identified. These 10 novel SNPs within the 5 closest genes were rs202128628 and rs116988614 in COL6A5; rs2375843 in LOC105374144 (a non-coding ribonucleic acid gene); rs525537 and rs367599822 in UGT2B17; rs7659854 in IQCM; and rs13183322, rs117002249, rs7033295, and rs199690933 in PGM5P2. Furthermore, based on SNPs related to adult height reported by previous GWAS studies (1-6), the associations between these known human height-related SNPs and FSS risk was evaluated and 9 reported GWAS human height-related SNPs were identified for FSS risk. A risk prediction model was performed by ROC curves based on the 10 novel SNPs analyzed. These 10 novel SNPs served as a polygenic risk predisposition score for FSS risk prediction (area under the curve: 0.940 in the testing group). There was no significant increase in the predictive value with the combined 10 novel and 9 reported SNPs when compared with the 10 novel SNPs alone. An association of the 10 novel and 9 reported genetic SNPs with height reduction in the general population emerged from the analysis.

Interestingly, two SNPs mapped to COL65A, which encodes a member of the supramolecular assembly of collagen VI (ColVI). ColVI is involved in the formation of the extracellular matrix of articular cartilage and fetal bone. ColVI is responsible for the survival and proliferation of chondrocytes and mutations of this gene have been described in different disorders of bone and cartilage. Another interesting gene among the 10 novel SNPs is UGT2B17, which encodes for the uridine 5’-diphosphoglucuronosyltransferase [UDP]-2B17 protein, involved in testosterone metabolism. Homozygous deletions of UGT2B17 are associated with higher concentrations of total serum testosterone and estradiol. Given the known role of sex hormones in regulating bone and chondrocytes metabolism, UGT2B17 may affect human height by modulating serum levels of sex hormones.

Reference: 1. Gudbjartsson, D.F., et al., Many sequence variants affecting diversity of adult human height. Nat Genet, 2008. 40(5): p. 609–15.2. Lango Allen, H., et al., Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature, 2010. 467(7317): p. 832–8.3. Weedon, M.N., et al., Genome-wide association analysis identifies 20 loci that influence adult height. Nat Genet, 2008. 40(5): p. 575–83.4. Wood, A.R., et al., Defining the role of common variation in the genomic and biological architecture of adult human height. Nat Genet, 2014. 46(11): p. 1173–86.5. Lettre, G., et al., Identification of ten loci associated with height highlights new biological pathways in human growth. Nat Genet, 2008. 40(5): p. 584–91.6. Yang, J., et al., Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat Genet, 2012. 44(4): p. 369–75, S1–3.

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