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  • 學位論文

適用於產前帶因篩檢的體染色體隱性遺傳疾病變異分析系統

A Variation Analysis System of Autosomal Recessive Genetic Disorders for Prenatal Carrier Screening

指導教授 : 賴飛羆

摘要


在台灣,由政府公告的罕見疾病種類共有236種,依照國民健康署的罕見疾病通報個案統計表顯示,截至今年四月止,國內罹患罕見疾病的人數為19,029人。罕見疾病多以遺傳的方式發生,因此及早的檢驗並預防至關重要。隨著次世代基因定序技術在這些年來的迅速發展,基於其之上的全外顯子組定序數據在生物及醫學領域中的應用也越來越廣泛,基因檢測也越來越普及,這對那些患有遺傳性疾病或是家中有遺傳病史的病人無疑是一大福音。若是能在產前就得知夫妻雙方是否有人為某一遺傳疾病的帶因者,那麼就可以盡最大可能避免疾病隨著血緣關係遺傳下去,帶因篩檢因此誕生。帶因篩檢是用來偵測臨床上沒有症狀,但事實上為特定隱性遺傳疾病帶因者的健康人。由於這些帶因者有較高的風險會生下患病的小孩,所以帶因篩檢的結果可以讓備孕的夫妻更了解自己後代的患病風險也可以對日後的醫療或人生管理做更全面的規劃。 本研究的目的旨在開發出一個線上的帶因篩檢系統,供醫師或研究人員分析病患的全外顯子組定序數據,找到那些與體染色體隱性遺傳疾病高度相關的變異。該系統囊括了與體染色體隱性遺傳疾病相關的415個基因,除了能夠篩查出序列中可疑的致病基因變異,同時也會對基因變異的致病嚴重性進行排序,並計算出後代患有遺傳疾病的機率。系統生成的報告結果不僅能提供為夫妻的產前準備提供參考,亦能用於進一步研究。 在實驗中,我們利用台大醫院中111組後代患有罕見遺傳性疾病的夫妻及其後代的全外顯子定序資料作為測試資料,並以之前已檢驗出的導致後代致病的變異為答案,對系統的變異檢出成效進行分析。對於其中已確定發生的變異位於系統可檢測的415個基因中的測試資料,系統的檢出率為100%。而對於其它答案中的致病基因並不位於囊括的基因中的測試資料,系統也檢測出了在臨床上可能被忽略的在415個基因中的致病變異。使用此系統可協助分析全外顯子組定序數據中與體染色體隱性遺傳疾病相關的基因變異,縮減判讀基因變異的時間,更好地進行帶因篩檢,幫助備孕夫妻規避後代患病風險。

並列摘要


In Taiwan, there are 236 types of rare diseases declared by the government. And the number of people suffering from rare diseases was 19,029 as of April this year, according to the Statistical Report of Rare Disease Confirmed Cases from Health Promotion Administration, Ministry of Health and Welfare. Rare diseases occur in a genetic manner, so early detection and prevention is crucial. With the rapid development of next-generation sequencing (NGS) technology in recent years, the application of whole-exome sequencing (WES) data based on it in the biological and medical field is becoming more and more extensive, and gene testing is becoming more and more popular, which is undoubtedly a great boon for those patients suffering from genetic diseases or family history of genetic diseases. Knowing prenatally whether a partner is the carrier of a genetic disease can prevent the disease from being passed down through blood ties as much as possible, and this demand leads to carrier screening. Carrier screening is used to detect healthy individuals who are clinically asymptomatic but are in fact the carrier of a specific recessive genetic disease. Since these patients are at higher risk of having a child with the disease, the results of screening can help couples better understand their offspring's risk and make more comprehensive plans for future medical and life management. The aim of this study was to develop an online variant analysis system that allows physicians or researchers to analyze whole-exome sequencing data of patients to find mutations highly associated with autosomal recessive genetic disorders. The system, which includes 415 genes related to recessive genetic diseases on autosomes, can not only screen for suspected disease-causing gene variations in the sequence, but also rank the severity of the genetic variations and calculate the risk that offspring will have inherited diseases. The report results generated by the system can not only provide a reference for the prenatal preparation of couples, but also be used for further research In this study, we used the whole-exome sequencing data of 111 groups of couples whose offspring suffered from rare genetic diseases in National Taiwan University Hospital as testing data, and analyzed the results of the system's variant detection based on the previously detected mutations that caused disease in the offspring. The detection rate of the variants in 415 genes detected by the system is 100%. For other testing data, the disease-causing genes in answer are not in the included genes, but the system also detects variants that might have been clinically overlooked in the 415 genes. This system can assist in analyzing variants related to recessive genetic diseases in whole-exome sequencing data, shorten the time of variants interpretation, better carry out screening for carriers, and help pregnant couples avoid the risk of developing disease in their offspring.

參考文獻


[1] K. A. Beauchamp, D. Muzzey, K. K. Wong, G. J. Hogan, K. Karimi, S. I. Candille, N. Mehta, R. Mar-Heyming, K. E. Kaseniit, H. P. Kang, E. A. Evans, J. D. Goldberg, G. A. Lazarin, and I. S. Haque, “Systematic design and comparison of expanded carrier screening panels,” Genet Med, vol. 20, no. 1, pp. 55-63, Jan, 2018.
[2] A. V. Kiseleva, M. V. Klimushina, E. A. Sotnikova, M. G. Divashuk, A. I. Ershova, O. P. Skirko, O. V. Kurilova, A. A. Zharikova, E. Y. Khlebus, I. A. Efimova, M. S. Pokrovskaya, P. A. Slominsky, S. A. Shalnova, A. N. Meshkov, and O. M. Drapkina, “A Data-Driven Approach to Carrier Screening for Common Recessive Diseases,” J Pers Med, vol. 10, no. 3, Sep 22, 2020.
[3] C. Hsu, “An Integrated Genetic Variation Analysis System for Gene Diagnostics in Precision Medicine,” National Taiwan University, 2018.
[4] Y.-S. Huang, “Prioritization of Disease-Causing Variants of Exome Data by Machine Learning,” National Taiwan University, 2020.
[5] J. D. Hintzsche, W. A. Robinson, and A. C. Tan, “A Survey of Computational Tools to Analyze and Interpret Whole Exome Sequencing Data,” Int J Genomics, vol. 2016, pp. 7983236, 2016.

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