Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal deformity. Several AIS susceptibility loci have been identified; however, they could explain only a small proportion of AIS heritability. To identify additional AIS susceptibility loci, we conduct a meta-analysis of the three genome-wide association studies consisting of 79,211 Japanese individuals. We identify 20 loci significantly associated with AIS, including 14 previously not reported loci. These loci explain 4.6% of the phenotypic variance of AIS. We find 21
cis
-expression quantitative trait loci-associated genes in seven of the fourteen loci. By a female meta-analysis, we identify additional three significant loci. We also find significant genetic correlations of AIS with body mass index and uric acid. The cell-type specificity analyses show the significant heritability enrichment for AIS in multiple cell-type groups, suggesting the heterogeneity of etiology and pathogenesis of AIS. Our findings provide insights into etiology and pathogenesis of AIS.
ObjectiveAnkylosing spondylitis (AS) is a form of chronic inflammatory spondyloarthritis (SpA) that causes pain and stiffness in spines or joints. Human leukocyte antigen B27 (HLA-B27) and B60 (HLA-B60) have been reported as major genetic risk factors of AS. In addition, rs13202464, located on major histocompatibility complex (MHC) region, showed high sensitivity (98.7%) and specificity (98.0%) for HLA-B27.DesignThe aim of our study is to test whether the interaction between HLA-B60 and HLA-B27 (rs13202464) can serve as a better predictor of AS. We have genotyped HLA-B60 and rs13202464 among 471 patients with AS and 557 healthy subjects. Combined risk factors were investigated to test the biological interaction.ResultsOur results indicated that the relative risk (RR) for HLA-B27+/HLA-B60− was 152 (95% CI 91 to 255) and it increased to 201 (95% CI 85 to 475) in HLA-B27+/HLA-B60+ patients (with HLA-B27−/HLA-B60− as reference). Combinational analysis of two risk factors (HLA-B27+/HLA-B60+) showed a relative excess risk due to interaction (RERI) of 46.79 (95% CI: -117.58 to 211.16), attributable proportion (AP) of 0.23 (95% CI: -0.41 to 0.88) and a synergy index (S) of 1.31 (95% CI: 0.56 to 3.04).ConclusionIn conclusion, genetic interaction analysis revealed that the interaction between HLA-B60 and HLA-B27 is a better marker for the risk of AS susceptibility in a Taiwanese population.
Surgery is the most effective treatment for breast cancer patients. However, some patients developed recurrence and distant metastasis after surgery. Adjuvant therapy is considered for high-risk patients depending on several prognostic markers, and lymphovascular invasion has become one of such prognostic markers that help physicians to identify the risk for distant metastasis and recurrence. However, the mechanism of lymphovascular invasion in breast cancer remains unknown. This study aims to unveil the genes and pathways that may involve in lymphovascular invasion in breast cancer. In total, 108 breast cancer samples were collected during surgery and microarray analysis was performed. Significance analysis of the microarrays and limma package for R were used to examine differentially expressed genes between lymphovascular invasion-positive and lymphovascular invasion-negative cases. Network and pathway analyses were mapped using the Ingenuity Pathway Analysis and the Database for Annotation, Visualization and Integrated Discovery. In total, 86 differentially expressed genes, including 37 downregulated genes and 49 upregulated genes were identified in lymphovascular invasion-positive patients. Among these genes, TNFSF11, IL6ST, and EPAS1 play important roles in cytokine-receptor interaction, which is the most enriched pathway related to lymphovascular invasion. Moreover, the results also suggested that an imbalance between extracellular matrix components and tumor micro-environment could induce lymphovascular invasion. Our study evaluated the underlying mechanisms of lymphovascular invasion, which may further help to assess the risk of breast cancer progression and identify potential targets of adjuvant treatment.
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