Genome-wide association study identifies GAK and KLF12 associated with curve severity of adolescent idiopathic scoliosis.

BACKGROUND

Genetic factors have been increasingly recognized as important contributors to the development and progression of adolescent idiopathic scoliosis (AIS). However, the genetic basis underlying AIS curve severity remains largely unclear. The objective of this study is to identify novel genetic variants associated with curve severity in AIS through a genome-wide association study (GWAS).

METHODS

In the discovery stage, 620 female AIS patients were enrolled, including 323 with severe curves (> 40°) and 297 with mild curves (< 30°). Top single nucleotide polymorphisms (SNPs) from each locus were selected for replication in an independent cohort of 634 severe and 546 mild cases. Associations between gene expression and Cobb angle were evaluated using Spearman correlation, while correlations with myofiber-related genes were analyzed using Pearson correlation.

RESULTS

Fifteen novel SNPs showed potential association with AIS curve severity in the discovery stage (P < 1 × 10-4). Six lead SNPs were selected for replication, including rs2061846 (GAK), rs12200301 (DST), rs10820637 (SMC2/NIPSNAP3A), rs7330031 (KLF12), rs2469472 (ST8SIA5-DT), and rs738650 (SEZ6L). Among these, rs2061846 and rs7330031 were successfully replicated. For rs2061846 in GAK, the frequency of the G allele was significantly higher in the severe group (P = 0.001; OR = 1.32). For rs7330031 in KLF12, the C allele was significantly more frequent in the severe group than in the mild group (P = 0.001; OR = 1.46). Moreover, KLF12 mRNA expression in the paraspinal muscle of AIS patients was negatively correlated with Cobb angle and associated with muscle fiber-specific gene expression.

CONCLUSIONS

This study identified GAK and KLF12 as novel susceptibility genes associated with AIS curve severity, providing new insights into the genetic basis of curve progression. These findings may contribute to improved risk stratification and personalized management in AIS.