Core planar cell polarity genes VANGL1 and VANGL2 in predisposition to congenital vertebral malformations.

Congenital scoliosis (CS), affecting approximately 0.5 to 1 in 1,000 live births, is commonly caused by congenital vertebral malformations (CVMs) arising from aberrant somitogenesis or somite differentiation. While Wnt/ß-catenin signaling has been implicated in somite development, the function of Wnt/planar cell polarity (Wnt/PCP) signaling in this process remains unclear. Here, we investigated the role of Vangl1 and Vangl2 in vertebral development and found that their deletion causes vertebral anomalies resembling human CVMs. Analysis of exome sequencing data from multiethnic CS patients revealed a number of rare and deleterious variants in VANGL1 and VANGL2, many of which exhibited loss-of-function and dominant-negative effects. Zebrafish models confirmed the pathogenicity of these variants. Furthermore, we found that Vangl1 knock-in (p.R258H) mice exhibited vertebral malformations in a Vangl gene dose- and environment-dependent manner. Our findings highlight critical roles for PCP signaling in vertebral development and predisposition to CVMs in CS patients, providing insights into the molecular mechanisms underlying this disorder.

Rare variant association analyses reveal the significant contribution of carbohydrate metabolic disturbance in severe adolescent idiopathic scoliosis.

BACKGROUND: Adolescent idiopathic scoliosis (AIS), the predominant genetic-influenced scoliosis, results in spinal deformities without vertebral malformations. However, the molecular aetiology of AIS remains unclear. METHODS: Using genome/exome sequencing, we studied 368 patients with severe AIS (Cobb angle >40°) and 3794 controls from a Han Chinese cohort. We performed gene-based and pathway-based weighted rare variant association tests to assess the mutational burden of genes and established biological pathways. Differential expression analysis of muscle tissues from 14 patients with AIS and 15 controls was served for validation. RESULTS: SLC16A8, a lactate transporter linked to retinal glucose metabolism, was identified as a novel severe AIS-associated gene (p=3.08E-06, false discovery rate=0.009). Most AIS cases with deleterious SLC16A8 variants demonstrated early onset high myopia preceding scoliosis. Pathway-based burden test also revealed a significant enrichment in multiple carbohydrate metabolism pathways, especially galactose metabolism. Patients with deleterious variants in these genes demonstrated a significantly larger spinal curve. Genes related to catabolic processes and nutrient response showed divergent expression between AIS cases and controls, reinforcing our genomic findings. CONCLUSION: This study uncovers the pivotal role of genetic variants in carbohydrate metabolism in the development of AIS, unveiling new insights into its aetiology and potential treatment.

SIGMA leverages protein structural information to predict the pathogenicity of missense variants.

Leveraging protein structural information to evaluate pathogenicity has been hindered by the scarcity of experimentally determined 3D protein. With the aid of AlphaFold2 predictions, we developed the structure-informed genetic missense mutation assessor (SIGMA) to predict missense variant pathogenicity. In comparison with existing predictors across labeled variant datasets and experimental datasets, SIGMA demonstrates superior performance in predicting missense variant pathogenicity (AUC = 0.933). We found that the relative solvent accessibility of the mutated residue contributed greatly to the predictive ability of SIGMA. We further explored combining SIGMA with other top-tier predictors to create SIGMA+, proving highly effective for variant pathogenicity prediction (AUC = 0.966). To facilitate the application of SIGMA, we pre-computed SIGMA scores for over 48 million possible missense variants across 3,454 disease-associated genes and developed an interactive online platform (https://www.sigma-pred.org/). Overall, by leveraging protein structure information, SIGMA offers an accurate structure-based approach to evaluating the pathogenicity of missense variants.

Unraveling the genetic architecture of congenital vertebral malformation with reference to the developing spine.

Congenital vertebral malformation, affecting 0.13-0.50 per 1000 live births, has an immense locus heterogeneity and complex genetic architecture. In this study, we analyze exome/genome sequencing data from 873 probands with congenital vertebral malformation and 3794 control individuals. Clinical interpretation identifies Mendelian etiologies in 12.0% of the probands and reveals a muscle-related disease mechanism. Gene-based burden test of ultra-rare variants identifies risk genes with large effect sizes (ITPR2, TBX6, TPO, H6PD, and SEC24B). To further investigate the biological relevance of the genetic association signals, we perform single-nucleus RNAseq on human embryonic spines. The burden test signals are enriched in the notochord at early developmental stages and myoblast/myocytes at late stages, highlighting their critical roles in the developing spine. Our work provides insights into the developmental biology of the human spine and the pathogenesis of spine malformation.