淡江大學機構典藏:Item 987654321/118662
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    Title: Genetic Architecture Associated With Familial Short Stature
    Authors: Ying-Ju Lin;Chi-Fung Cheng;Chung-Hsing Wang;Wen-Miin Liang;Chih-Hsin Tang;Li-Ping Tsai;Chien-Hsiun Chen;Jer-Yuarn Wu;Ai-Ru Hsieh;Ming Ta Michael Lee;Ting-Hsu Lin;Chiu-Chu Liao;Shao-Mei Huang;Yanfei Zhang;Chang-Hai Tsai;Fuu-Jen Tsai
    Keywords: GWAS;Han Chinese ancestry;familial short stature;human height;polygenic trait
    Date: 2020-06
    Issue Date: 2020-06-01 12:11:55 (UTC+8)
    Abstract: Context: Human height is an inheritable, polygenic trait under complex and multilocus genetic regulation. Familial short stature (FSS; also called genetic short stature) is the most common type of short stature and is insufficiently known.

    Objective: To investigate the FSS genetic profile and develop a polygenic risk predisposition score for FSS risk prediction.

    Design and setting: The FSS participant group of Han Chinese ancestry was diagnosed by pediatric endocrinologists in Taiwan.

    Patients and interventions: The genetic profiles of 1163 participants with FSS were identified by using a bootstrapping subsampling and genome-wide association studies (GWAS) method.

    Main outcome measures: Genetic profile, polygenic risk predisposition score for risk prediction.

    Results: Ten novel genetic single nucleotide polymorphisms (SNPs) and 9 reported GWAS human height-related SNPs were identified for FSS risk. These 10 novel SNPs served as a polygenic risk predisposition score for FSS risk prediction (area under the curve: 0.940 in the testing group). This FSS polygenic risk predisposition score was also associated with the height reduction regression tendency in the general population.

    Conclusion: A polygenic risk predisposition score composed of 10 genetic SNPs is useful for FSS risk prediction and the height reduction tendency. Thus, it might contribute to FSS risk in the Han Chinese population from Taiwan.
    Relation: The Journal of Clinical Endocrinology & Metabolism 105(6), p.1801-1813
    DOI: 10.1210/clinem/dgaa131
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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