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COA1 与髌腱炎的关联:全基因组关联分析。

Association of COA1 with Patellar Tendonitis: A Genome-wide Association Analysis.

机构信息

Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA.

Kaiser Permanente Northern California, Division of Research, Oakland, CA.

出版信息

Med Sci Sports Exerc. 2021 Nov 1;53(11):2419-2424. doi: 10.1249/MSS.0000000000002710.

DOI:10.1249/MSS.0000000000002710
PMID:34081057
Abstract

PURPOSE

It is unknown why some athletes develop patellar tendinopathy and others do not, even when accounting for similar workloads between individuals. Genetic differences between these two populations may be a contributing factor. The purpose of this work was to screen the entire genome for genetic markers associated with patellar tendinopathy.

METHODS

Genome-wide association (GWA) analyses were performed utilizing data from the Kaiser Permanente Research Board (KPRB) and the UK Biobank. Patellar tendinopathy cases were identified based on electronic health records from KPRB and UK Biobank. GWA analyses from both cohorts were tested for patellar tendinopathy using a logistic regression model adjusting for sex, height, weight, age, and race/ethnicity using allele counts for single nucleotide polymorphisms. The data from the two GWA studies (KPRB and UK Biobank) were combined in a meta-analysis.

RESULTS

There were a total of 1670 cases of patellar tendinopathy and 293,866 controls within the two cohorts. Two single nucleotide polymorphisms located in the intron of the cytochrome c oxidase assembly factor 1 (COA1) gene showed a genome-wide significant association in the meta-analysis.

CONCLUSIONS

Genetic markers in COA1 seem to be associated with patellar tendinopathy and are potential risk factors for patellar tendinopathy that deserve further validation regarding molecular mechanisms.

摘要

目的

目前尚不清楚为什么有些运动员会出现髌腱病,而有些运动员则不会,即使考虑到个体之间相似的工作量也是如此。这两个人群之间的遗传差异可能是一个促成因素。这项工作的目的是筛选与髌腱病相关的全基因组遗传标记。

方法

利用 Kaiser Permanente 研究委员会(KPRB)和英国生物银行的数据进行全基因组关联(GWA)分析。根据 KPRB 和英国生物银行的电子健康记录确定髌腱病病例。使用 logistic 回归模型对两个队列的 GWA 分析进行髌腱病检测,该模型通过单核苷酸多态性的等位基因计数调整性别、身高、体重、年龄和种族/民族。对来自两个 GWA 研究(KPRB 和英国生物银行)的数据进行荟萃分析。

结果

两个队列中共有 1670 例髌腱病病例和 293866 例对照。两个位于细胞色素 c 氧化酶组装因子 1(COA1)基因内含子中的单核苷酸多态性在荟萃分析中显示出全基因组显著关联。

结论

COA1 中的遗传标记似乎与髌腱病有关,是髌腱病的潜在危险因素,值得进一步验证其分子机制。

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