Dataset Information

Evaluation of IRX Genes and Conserved Noncoding Elements in a Region on 5p13.3 Linked to Families with Familial Idiopathic Scoliosis and Kyphosis.

ABSTRACT: Because of genetic heterogeneity present in idiopathic scoliosis, we previously defined clinical subsets (a priori) from a sample of families with idiopathic scoliosis to find genes involved with spinal curvature. Previous genome-wide linkage analysis of seven families with at least two individuals with kyphoscoliosis found linkage (P-value = 0.002) in a 3.5-Mb region on 5p13.3 containing only three known genes, IRX1, IRX2, and IRX4 In this study, the exons of IRX1, IRX2, and IRX4, the conserved noncoding elements in the region, and the exons of a nonprotein coding RNA, LOC285577, were sequenced. No functional sequence variants were identified. An intrafamilial test of association found several associated noncoding single nucleotide variants. The strongest association was with rs12517904 (P = 0.00004), located 6.5 kb downstream from IRX1 In one family, the genotypes of nine variants differed from the reference allele in all individuals with kyphoscoliosis, and two of three individuals with scoliosis, but did not differ from the reference allele in all other genotyped individuals. One of these variants, rs117273909, was located in a conserved noncoding region that functions as an enhancer in mice. To test whether the variant allele at rs117273909 had an effect on enhancer activity, zebrafish transgenesis was performed with overlapping fragments of 198 and 687 bp containing either the wild type or the variant allele. Our data suggests that this region acts as a regulatory element; however, its size and target gene(s) need to be identified to determine its role in idiopathic scoliosis.

SUBMITTER: Justice CM

PROVIDER: S-EPMC4889666 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Evaluation of IRX Genes and Conserved Noncoding Elements in a Region on 5p13.3 Linked to Families with Familial Idiopathic Scoliosis and Kyphosis.

Justice Cristina M CM Bishop Kevin K Carrington Blake B Mullikin Jim C JC Swindle Kandice K Marosy Beth B Sood Raman R Miller Nancy H NH Wilson Alexander F AF

G3 (Bethesda, Md.) 20160601 6

Because of genetic heterogeneity present in idiopathic scoliosis, we previously defined clinical subsets (a priori) from a sample of families with idiopathic scoliosis to find genes involved with spinal curvature. Previous genome-wide linkage analysis of seven families with at least two individuals with kyphoscoliosis found linkage (P-value = 0.002) in a 3.5-Mb region on 5p13.3 containing only three known genes, IRX1, IRX2, and IRX4 In this study, the exons of IRX1, IRX2, and IRX4, the conserved ...[more]

PMID: 27172222

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Project description:ObjectiveTo build a model for proximal junctional kyphosis (PJK) prognostication in Lenke 5 adolescent idiopathic scoliosis (AIS) patients undergoing long posterior instrumentation and fusion surgery by machine learning and analyze the risk factors for PJK.Materials and methodsIn total, 44 AIS patients (female/male: 34/10; PJK/non-PJK: 34/10) who met the inclusion criteria between January 2013 and December 2018 were retrospectively recruited from West China Hospital. Thirty-seven clinical and radiological features were acquired by two independent investigators. Univariate analyses between PJK and non-PJK groups were carried out. Twelve models were built by using four types of machine learning algorithms in conjunction with two oversampling methods [the synthetic minority technique (SMOTE) and random oversampling]. Area under the receiver operating characteristic curve (AUC) was used for model discrimination, and the clinical utility was evaluated by using F1 score and accuracy. The risk factors were simultaneously analyzed by a Cox regression and machine learning.ResultsStatistical differences between PJK and non-PJK groups were as follows: gender (p = 0.001), preoperative factors [thoracic kyphosis (p = 0.03), T1 slope angle (T1S, p = 0.078)], and postoperative factors [T1S (p = 0.097), proximal junctional angle (p = 0.003), upper instrumented vertebra (UIV) - UIV + 1 (p = 0.001)]. Random forest using SMOTE achieved the best prediction performance with AUC = 0.944, accuracy = 0.909, and F1 score = 0.667 on independent testing dataset. Cox model revealed that male gender and larger preoperative T1S were independent prognostic factors of PJK (odds ratio = 10.701 and 57.074, respectively). Gender was also at the first place in the importance ranking of the model with best performance.ConclusionThe random forest using SMOTE model has the great value for predicting the individual risk of developing PJK after long instrumentation and fusion surgery in Lenke 5 AIS patients. Moreover, the combination of the outcomes of a Cox model and the feature ranking extracted by machine learning is more valuable than any one alone, especially in the interpretation of risk factors.

Dataset Information

Evaluation of IRX Genes and Conserved Noncoding Elements in a Region on 5p13.3 Linked to Families with Familial Idiopathic Scoliosis and Kyphosis.

Publications

Evaluation of IRX Genes and Conserved Noncoding Elements in a Region on 5p13.3 Linked to Families with Familial Idiopathic Scoliosis and Kyphosis.

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