Institute of Computer Science, Division of Biomedical Computer Systems, University of Silesia, Katowice, Poland.
Biomed Eng Online. 2013 Jan 4;12:1. doi: 10.1186/1475-925X-12-1.
Importance of hereditary factors in the etiology of Idiopathic Scoliosis is widely accepted. In clinical practice some of the IS patients present with positive familial history of the deformity and some do not. Traditionally about 90% of patients have been considered as sporadic cases without familial recurrence. However the exact proportion of Familial and Sporadic Idiopathic Scoliosis is still unknown. Housekeeping genes encode proteins that are usually essential for the maintenance of basic cellular functions. ACTB and GAPDH are two housekeeping genes encoding respectively a cytoskeletal protein β-actin, and glyceraldehyde-3-phosphate dehydrogenase, an enzyme of glycolysis. Although their expression levels can fluctuate between different tissues and persons, human housekeeping genes seem to exhibit a preserved tissue-wide expression ranking order. It was hypothesized that expression ranking order of two representative housekeeping genes ACTB and GAPDH might be disturbed in the tissues of patients with Familial Idiopathic Scoliosis (with positive family history of idiopathic scoliosis) opposed to the patients with no family members affected (Sporadic Idiopathic Scoliosis). An artificial neural network (ANN) was developed that could serve to differentiate between familial and sporadic cases of idiopathic scoliosis based on the expression levels of ACTB and GAPDH in different tissues of scoliotic patients. The aim of the study was to investigate whether the expression levels of ACTB and GAPDH in different tissues of idiopathic scoliosis patients could be used as a source of data for specially developed artificial neural network in order to predict the positive family history of index patient.
The comparison of developed models showed, that the most satisfactory classification accuracy was achieved for ANN model with 18 nodes in the first hidden layer and 16 nodes in the second hidden layer. The classification accuracy for positive Idiopathic Scoliosis anamnesis only with the expression measurements of ACTB and GAPDH with the use of ANN based on 6-18-16-1 architecture was 8 of 9 (88%). Only in one case the prediction was ambiguous.
Specially designed artificial neural network model proved possible association between expression level of ACTB, GAPDH and positive familial history of Idiopathic Scoliosis.
遗传性因素在特发性脊柱侧凸的发病机制中很重要，这一观点已被广泛接受。在临床实践中，一些特发性脊柱侧凸患者存在阳性家族史，而另一些患者则没有。传统上，约 90%的患者被认为是没有家族复发的散发性病例。然而，特发性家族性脊柱侧凸和特发性散发性脊柱侧凸的确切比例仍不清楚。管家基因编码的蛋白质通常对维持基本细胞功能至关重要。ACTB 和 GAPDH 是两种管家基因，分别编码细胞骨架蛋白 β-肌动蛋白和糖酵解酶甘油醛-3-磷酸脱氢酶。尽管它们的表达水平在不同的组织和个体之间可能会波动，但人类管家基因似乎表现出一种保守的组织-wide 表达排序。假设在特发性脊柱侧凸（有特发性脊柱侧凸阳性家族史）患者的组织中，两种代表性管家基因 ACTB 和 GAPDH 的表达排序可能会受到干扰，而在没有家族成员受影响的患者（特发性散发性脊柱侧凸）中则不会受到干扰。开发了一种人工神经网络（ANN），可以根据特发性脊柱侧凸患者不同组织中 ACTB 和 GAPDH 的表达水平，将特发性脊柱侧凸的家族性和散发性病例区分开来。本研究的目的是探讨特发性脊柱侧凸患者不同组织中 ACTB 和 GAPDH 的表达水平是否可以作为专门开发的人工神经网络的数据源，以便预测指数患者的阳性家族史。
对所开发模型的比较表明，对于具有 18 个节点的第一层隐藏层和 16 个节点的第二层隐藏层的 ANN 模型，达到了最令人满意的分类精度。仅使用 ANN 基于 6-18-16-1 架构的 ACTB 和 GAPDH 表达测量对阳性特发性脊柱侧凸病史的分类准确率为 8 例 9 例（88%）。仅在一个病例中预测结果不明确。
专门设计的人工神经网络模型证明了 ACTB、GAPDH 的表达水平与特发性脊柱侧凸阳性家族史之间可能存在关联。
