Estimating Uterine Fibroid SNP-Based Heritability in European American Women with Imaging-Confirmed Fibroids.

IF 1.1 4区 生物学 Q4 GENETICS & HEREDITY
Human Heredity Pub Date : 2019-01-01 DOI:10.1159/000501335
Michael J Bray, Lea K Davis, Eric S Torstenson, Sarah H Jones, Todd L Edwards, Digna R Velez Edwards
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引用次数: 6

Abstract

Background: Heritability estimates (including twin and single nucleotide polymorphism [SNP]-based heritability studies) for fibroids have been inconsistent across prior studies ranging between 9 and 69%. These inconsistencies are due to variations in study design and included populations. A major design issue has been lack of imaging confirmation to identify controls, where asymptomatic women without imaging confirmation may be misclassified as controls leading to an attenuation of heritability estimates. To reconcile the differences in prior heritability estimates and the impact of misclassification of controls on heritability, we determined SNP-based heritability and characterized the genetic architecture of pelvic image-confirmed fibroid cases and controls.

Methods: Analyses were performed among women of European American descent using genome-wide SNP data from BioVU, a clinical database composed of DNA linked to de-identified electronic health records. We estimated the genetic variance explained by all SNPs using Genome-Wide Complex Trait Analysis on imputed data. Fibroid cases and controls were identified using a previously reported phenotyping algorithm that required pelvic imaging confirmation.

Results: In total, we used 1,067 image-confirmed fibroid cases and 1,042 image-confirmed fibroid controls. The SNP-based heritability estimate for fibroid risk was h2 = 0.33 ± 0.18 (p = 0.040). We investigated the relationship between heritability per chromosome and chromosome length (r2 < 1%), with chromosome 8 explaining the highest proportion of variance for fibroid risk. There was no enrichment for intergenic or genic SNPs for the fibroid SNP-based heritability. Excluding loci previously associated with fibroid risk from genome-wide association study did not attenuate fibroid heritability suggesting that loci associating with fibroid risk are yet to be discovered.

Conclusions: We observed that fibroid SNP-based heritability was higher than the previous estimate using genome-wide SNP data that relied on self-reported outcomes, but within the range of prior twin pair studies. Furthermore, these data support that imprecise phenotyping can significantly affect the ability to estimate heritability using genotype data.

Abstract Image

Abstract Image

在影像学证实的欧美女性中估计基于snp的子宫肌瘤遗传率。
背景:肌瘤的遗传率估计(包括基于双胞胎和单核苷酸多态性[SNP]的遗传率研究)在先前的研究中不一致,范围在9%到69%之间。这些不一致是由于研究设计和纳入人群的差异。一个主要的设计问题是缺乏影像学确认来识别对照,没有影像学确认的无症状妇女可能被错误地分类为对照,导致遗传力估计的衰减。为了调和先前遗传力估计的差异和对照组错误分类对遗传力的影响,我们确定了基于snp的遗传力,并对盆腔图像证实的纤维瘤病例和对照组的遗传结构进行了表征。方法:使用来自BioVU的全基因组SNP数据对欧洲裔女性进行分析,BioVU是一个由与去识别电子健康记录相关的DNA组成的临床数据库。我们使用全基因组复杂性状分析对输入数据估计了所有snp解释的遗传方差。肌瘤病例和对照组使用先前报道的表型算法进行鉴定,该算法需要盆腔成像确认。结果:我们总共使用了1067例图像证实的肌瘤病例和1042例图像证实的肌瘤对照。基于snp的子宫肌瘤风险遗传率估计为h2 = 0.33±0.18 (p = 0.040)。我们研究了每条染色体的遗传率与染色体长度之间的关系(r2 < 1%),其中第8号染色体解释了子宫肌瘤风险的最高变异比例。子宫肌瘤的遗传力没有基因间或基因snp的富集。从全基因组关联研究中排除先前与肌瘤风险相关的基因座并没有减弱肌瘤的遗传性,这表明与肌瘤风险相关的基因座尚未被发现。结论:我们观察到肌瘤单核苷酸多态性遗传率高于先前使用依赖于自我报告结果的全基因组单核苷酸多态性数据估计的遗传率,但在先前双胞胎研究的范围内。此外,这些数据支持不精确的表型可以显著影响使用基因型数据估计遗传力的能力。
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来源期刊
Human Heredity
Human Heredity 生物-遗传学
CiteScore
2.50
自引率
0.00%
发文量
12
审稿时长
>12 weeks
期刊介绍: Gathering original research reports and short communications from all over the world, ''Human Heredity'' is devoted to methodological and applied research on the genetics of human populations, association and linkage analysis, genetic mechanisms of disease, and new methods for statistical genetics, for example, analysis of rare variants and results from next generation sequencing. The value of this information to many branches of medicine is shown by the number of citations the journal receives in fields ranging from immunology and hematology to epidemiology and public health planning, and the fact that at least 50% of all ''Human Heredity'' papers are still cited more than 8 years after publication (according to ISI Journal Citation Reports). Special issues on methodological topics (such as ‘Consanguinity and Genomics’ in 2014; ‘Analyzing Rare Variants in Complex Diseases’ in 2012) or reviews of advances in particular fields (‘Genetic Diversity in European Populations: Evolutionary Evidence and Medical Implications’ in 2014; ‘Genes and the Environment in Obesity’ in 2013) are published every year. Renowned experts in the field are invited to contribute to these special issues.
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