Estimating the Genetic Risk of First-Degree Relatives for Chronic Diseases Using the Short Tandem Repeat Score as Model of Polygenic Inheritance.

IF 2.1 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Xia Qi, Anwar Ullah, Weijian Yu, Xiaojun Jin, Hui Liu
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引用次数: 0

Abstract

This study aims to establish a genetic risk assessment model based on a score of short tandem repeats (STRs) of polygenic inheritance. A total of 396 children and their biological parents were collected for STR genotyping. The numbers of tandem repeats of two alleles in one STR locus were assumed to be a quantitative genetic strength for disease incidence. The sums of 19 STR loci were considered a quantitative genetic strength per individual. Various thresholds of the STRs between paternal, maternal, and childhood data were recorded. As an exemplar, for thresholds of 25%, the first quarter = 1. All other samples = 0. The consistency rate for heredity (CH) was calculated from the difference in the morbidity of children between parents with and without disease groups. The ratio of observed CH to expected CH was defined as the heredity index (HI). Actual Pedigree data (finger-crossing test) confirmed the accuracy of the STR score. The genetic risk of first-degree relatives could be estimated using easily acquired data (incidence in an unrelated population). Our findings can provide a polygenic genetic model for estimating the incidence and genetic risk of chronic disease in first-degree relatives.

用短串联重复序列评分作为多基因遗传模型估计慢性病一级亲属遗传风险。
本研究旨在建立基于多基因遗传短串联重复序列(STRs)评分的遗传风险评估模型。收集396名儿童及其亲生父母进行STR基因分型。一个STR基因座上两个等位基因的串联重复次数被认为是疾病发病率的定量遗传强度。19个STR位点的总和被认为是每个个体的数量遗传强度。记录了父亲、母亲和儿童数据之间str的不同阈值。作为示例,对于25%的阈值,第一季度= 1。所有其他样本= 0。遗传一致性率(CH)是根据有疾病组和无疾病组父母之间儿童发病率的差异计算的。将观察到的CH与期望CH的比值定义为遗传指数(HI)。实际系谱数据(交叉指检)证实了STR评分的准确性。一级亲属的遗传风险可以用容易获得的数据(无亲缘关系人群的发病率)来估计。我们的研究结果可以为估计一级亲属中慢性病的发病率和遗传风险提供一个多基因遗传模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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