| Autor: |
Xuan Wang, Isabelle-Emmanuella Nogues, Molei Liu, Tony Chen, Xin Xiong, Clara-Lea Bonzel, Harrison Zhang, Chuan Hong, Kumar Dahal, Lauren Costa, J. Michael Gaziano, Seoyoung C. Kim, Yuk-Lam Ho, Kelly Cho, Tianxi Cai, Katherine P. Liao |
| Rok vydání: |
2022 |
| DOI: |
10.1101/2022.09.24.22280325 |
| Popis: |
Genomic data are increasingly incorporated into high-throughput approaches such as the Phenome-Wide Association Study (PheWAS) to query potential effects of targeted therapies. Genetic variants, such as the interleukin-6 receptor (IL6R) genetic variant rs2228145 (Asp358Ala), have been identified with a downstream effect similar to the drug, e.g., tocilizumab which targets IL6R, and can be used to screen for potential protective or harmful signal across a broad range of traits in large biobanks with linked genomic and clinical data. To date, there are limited approaches to determine whether these effects may differ across diverse populations to inform potential differential drug effects especially in populations under-represented in clinical trials. In this study, we developed and applied an approach to detect heterogeneous associations, using the IL6R variant as an example, in African vs European ancestry. We identified a total of 29 traits with a differential association between the IL6R variant, with notable differences including a lower risk of type 2 diabetes in AFR vs EUR, and a higher white blood cell count. With the increasing use of targeted blockade of the IL6 pathway in conditions ranging from rheumatologic to cardiovascular conditions, the findings from this study can inform ongoing studies targeting IL6; general approach to test for heterogeneity of associations can be applied broadly to any PheWAS. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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