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Predictive value of single-nucleotide polymorphisms in curve progression of adolescent idiopathic scoliosis
Authors:Wang  Wengang  Chen  Tailong  Liu  Yibin  Wang  Songsong  Yang  Ningning  Luo  Ming
Affiliation:1.Department of Orthopedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, Henan, People’s Republic of China
;2.Department of Emergency, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, Henan, People’s Republic of China
;3.Department of Orthopedics, Zhongnan Hospital of Wuhan University, Wuhan, 430071, Hubei, People’s Republic of China
;
Abstract:
Purpose

Genetic diagnosis is a promising approach because several single-nucleotide polymorphisms (SNPs) associated with adolescent idiopathic scoliosis (AIS) progression have been reported. We review the predictive value of SNPs in curve progression of adolescent idiopathic scoliosis.

Methods

We reviewed DNA-based prognostic testing to predict curve progression. Then, the multiple polymorphisms in loci related to AIS progression were also reviewed, and we elucidated the predictive value of SNPs from four functional perspectives, including endocrine metabolism, neuromuscular system, cartilage and extracellular matrix, enzymes, and cytokines.

Results

The ScoliScores were less successful predictors than expected, and the weak power of predictive SNPs might account for its failure. Susceptibility loci in ESR1, ESR2, GPER, and IGF1, which related to endocrine metabolism, have been reported to predict AIS progression. Neuromuscular imbalance might be a potential mechanism of scoliosis, and SNPs in LBX1, NTF3, and SOCS3 have been reported to predict the curve progression of AIS. Susceptibility loci in SOX9, MATN1, AJAP1, MMP9, and TIMP2, which are related to cartilage and extracellular matrix, are also potentially related to AIS progression. Enzymes and cytokines play essential roles in regulating bone metabolism and embryonic development. SNPs in BNC2, SLC39A8, TGFB1, IL-6, IL-17RC, and CHD7 were suggested as predictive loci for AIS curve progression.

Conclusions

Many promising SNPs have been identified to predict the curve progression of AIS. However, conflicting results from replication studies and different ethnic groups hamper their reliability. Convincing SNPs from multiethnic populations and functional verification are needed.

Keywords:
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