Association of human height-related genetic variants with familial short stature in Han Chinese in Taiwan

Abstract

Human height can be described as a classical and inherited trait model. Genome-wide association studies (GWAS) have revealed susceptible loci and provided insights into the polygenic nature of human height. Familial short stature (FSS) represents a suitable trait for investigating short stature genetics because disease associations with short stature have been ruled out in this case. In addition, FSS is caused only by genetically inherited factors. In this study, we explored the correlations of FSS risk with the genetic loci associated with human height in previous GWAS, alone and cumulatively. We systematically evaluated 34 known human height single nucleotide polymorphisms (SNPs) in relation to FSS in the additive model (p < 0.00005). A cumulative effect was observed: the odds ratios gradually increased with increasing genetic risk score quartiles (p < 0.001; Cochran-Armitage trend test). Six affected genes-ZBTB38, ZNF638, LCORL, CABLES1, CDK10, and TSEN15-are located in the nucleus and have been implicated in embryonic, organismal, and tissue development. In conclusion, our study suggests that 13 human height GWAS-identified SNPs are associated with FSS risk both alone and cumulatively.Human height can be described as a classical, inherited, and polygenic trait model. The ultimate phenotype represents the outcome of genetics and developmental biology, including the enlargement of bone length and the sizes of tissues and organ sizes. Undoubtedly, the developmental processes may be affected by environmental factors, including nutrition 1 , exercise 2 , diseases 3-5 , and infections 6, 7 . However, ~80% of the variance in height among individuals can also be explained by genetic variation [8][9][10] . Modern high-density genotyping platforms have now made it possible to identify candidate genes across the whole genome in relation to complex traits and diseases [11][12][13] .Genetic factors that contribute to the genetic architecture of human height are widely identified by means of genome-wide screening methods [14][15][16][17][18][19][20][21][22][23][24] . Human height-related susceptibility loci related to the protein tyrosine phosphatase family, insulin-like growth factor, and skeletal growth have been reported in Asian populations 18,19,21,22,25 . In addition, predisposing loci determining height have also been discovered in European populations in genes related to skeletal development, mitosis, fibroblast growth factors, the WNT/β-catenin pathway, chondroitin sulfate-related genes, mammalian target of rampamycin, osteoglycin, binding of hyaluronic acid, Hedgehog

A genome-wide association analysis identifies 16 novel susceptibility loci for carpal tunnel syndrome

“…EFEMP1 is a gene that encodes protein fibulin-3, an extracellular matrix glycoprotein associated with basement membranes, elastic fibres and matrix components 52 . EFEMP1 is implicated in extracellular matrix architecture 36 as well as in bone- and cartilage-development pathways (hence its potential role in contributing to the observed enrichments between CTS and height, osteoblasts and lumbar spine bone mineral density). Variants at the EFEMP1 locus have been associated with adult height 36 , inguinal hernia 53 , and various cancers 54 ; EFEMP1 knockout mice demonstrated disruption or reduction in elastic fibres in their connective tissues 55 .…”

A QTL on chromosome 3q23 influences processing speed in humans

“…Variation in ZBTB38 has been associated with prostate cancer . It has also been associated consistently with stature in both cattle and humans . This gene has not been previously associated with either processing speed or general cognitive ability.…”

Gene-gene interaction analysis for quantitative trait using cluster-based multifactor dimensionality reduction method

“…In the 1st-order analysis of height, the proposed CL-MDR detected rs7632381 as the best model. The rs7632381 was found from previous studies as a marker associated with human height (Duncan, 2012;Kim et al, 2010;Lin et al, 2017). The QMDR and GMDR chose the same SNP, rs11184316, as the best model; the best model selected by the MDR was rs4679115.…”