LA-GEM: imputation of gene expression with incorporation of Local Ancestry
LA-GEM: imputation of gene expression with incorporation of Local Ancestry
复制标题
LA-GEM:结合当地祖先的基因表达估算
DOI:
--
复制
发表时间:
2023
影响因子:
--
通讯作者:
M. Perera
中科院分区:
文献类型:
--
作者:
Mrinal Mishra;Layan Nahlawi;Yizhen Zhong;T. De;Guang Yang;Cristina Alarcon;M. Perera
Gene imputation and TWAS have become a staple in the genomics medicine discovery space; helping to identify genes whose regulation effects may contribute to disease susceptibility. However, the cohorts on which these methods are built are overwhelmingly of European Ancestry. This means that the unique regulatory variation that exist in non-European populations, specifically African Ancestry populations, may not be included in the current models. Moreover, African Americans are an admixed population, with a mix of European and African segments within their genome. No gene imputation model thus far has incorporated the effect of local ancestry (LA) on gene expression imputation. As such, we created LA-GEM which was trained and tested on a cohort of 60 African American hepatocyte primary cultures. Uniquely, LA-GEM include local ancestry inference in its prediction of gene expression. We compared the performance of LA-GEM to PrediXcan trained the same dataset (with no inclusion of local ancestry) We were able to reliably predict the expression of 2559 genes (1326 in LA-GEM and 1236 in PrediXcan). Of these, 546 genes were unique to LA-GEM, including the CYP3A5 gene which is critical to drug metabolism. We conducted TWAS analysis on two African American clinical cohorts with pharmacogenomics phenotypic information to identity novel gene associations. In our IWPC warfarin cohort, we identified 17 transcriptome-wide significant hits. No gene reached are prespecified significance level in the clopidogrel cohort. We did see suggestive association with RAS3A to P2RY12 Reactivity Units (PRU), a clinical measure of response to anti-platelet therapy. This method demonstrated the need for the incorporation of LA into study in admixed populations.
登录
查看更多内容
影响因子:
9.8
作者:
Mancuso, Nicholas;Shi, Huwenbo;Pasaniuc, Bogdan
通讯作者:
Pasaniuc, Bogdan
DOI:
10.1038/nrc2960
发表时间:
2010-12
期刊:
Nature reviews. Cancer
影响因子:
--
作者:
通讯作者:
--
影响因子:
4.6
作者:
Zhang Y;Parmigiani G;Johnson WE
通讯作者:
Johnson WE
影响因子:
15.9
作者:
Stefanini, Lucia;Paul, David S.;Bergmeier, Wolfgang
通讯作者:
Bergmeier, Wolfgang
影响因子:
9.8
作者:
Maples, Brian K.;Gravel, Simon;Bustamante, Carlos D.
通讯作者:
Bustamante, Carlos D.