Heterogeneous associations between interleukin-6 receptor variants and phenotypes across ancestries and implications for therapy

Xuan Wang, Molei Liu, Isabelle Emmanuella Nogues, Tony Chen, Xin Xiong, Clara Lea Bonzel, Harrison Zhang, Chuan Hong, Yin Xia, Kumar Dahal, Lauren Costa, Jing Cui, J. Michael Gaziano, Seoyoung C. Kim, Yuk Lam Ho, Kelly Cho, Tianxi Cai, Katherine P. Liao, Sumitra Muralidhar, Jennifer MoserJennifer E. Deen, Philip S. Tsao, Sumitra Muralidhar, J. Michael Gaziano, Elizabeth Hauser, Amy Kilbourne, Shiuh Wen Luoh, Michael Matheny, Dave Oslin, J. Michael Gaziano, Philip S. Tsao, Lori Churby, Stacey B. Whitbourne, Jessica V. Brewer, Shahpoor Shayan, Luis E. Selva, Saiju Pyarajan, Kelly Cho, Scott L. DuVall, Mary T. Brophy, J. Michael Gaziano, Philip S. Tsao, Brady Stephens, Todd Connor, Themistocles L. Assimes, Adriana Hung, Henry Kranzler, Samuel Aguayo, Sunil Ahuja, Kathrina Alexander, Xiao M. Androulakis, Prakash Balasubramanian, Zuhair Ballas, Jean Beckham, Sujata Bhushan, Edward Boyko, David Cohen, Louis Dellitalia, L. Christine Faulk, Joseph Fayad, Daryl Fujii, Saib Gappy, Frank Gesek, Jennifer Greco, Michael Godschalk, Todd W. Gress, Samir Gupta, Salvador Gutierrez, John Harley, Kimberly Hammer, Mark Hamner, Adriana Hung, Robin Hurley, Pran Iruvanti, Frank Jacono, Darshana Jhala, Scott Kinlay, Jon Klein, Michael Landry, Peter Liang, Suthat Liangpunsakul, Jack Lichy, C. Scott Mahan, Ronnie Marrache, Stephen Mastorides, Elisabeth Mates, Kristin Mattocks, Paul Meyer, Jonathan Moorman, Timothy Morgan, Maureen Murdoch, James Norton, Olaoluwa Okusaga, Kris Ann Oursler, Ana Palacio, Samuel Poon, Emily Potter, Michael Rauchman, Richard Servatius, Satish Sharma, River Smith, Peruvemba Sriram, Patrick Strollo, Neeraj Tandon, Philip Tsao, Gerardo Villareal, Agnes Wallbom, Jessica Walsh, John Wells, Jeffrey Whittle, Mary Whooley, Allison E. Williams, Peter Wilson, Junzhe Xu, Shing Shing Yeh

Research output: Contribution to journalArticlepeer-review

Abstract

The Phenome-Wide Association Study (PheWAS) is increasingly used to broadly screen for potential treatment effects, e.g., IL6R variant as a proxy for IL6R antagonists. This approach offers an opportunity to address the limited power in clinical trials to study differential treatment effects across patient subgroups. However, limited methods exist to efficiently test for differences across subgroups in the thousands of multiple comparisons generated as part of a PheWAS. In this study, we developed an approach that maximizes the power to test for heterogeneous genotype–phenotype associations and applied this approach to an IL6R PheWAS among individuals of African (AFR) and European (EUR) ancestries. We identified 29 traits with differences in IL6R variant-phenotype associations, including a lower risk of type 2 diabetes in AFR (OR 0.96) vs EUR (OR 1.0, p-value for heterogeneity = 8.5 × 10–3), and higher white blood cell count (p-value for heterogeneity = 8.5 × 10–131). These data suggest a more salutary effect of IL6R blockade for T2D among individuals of AFR vs EUR ancestry and provide data to inform ongoing clinical trials targeting IL6 for an expanding number of conditions. Moreover, the method to test for heterogeneity of associations can be applied broadly to other large-scale genotype–phenotype screens in diverse populations.

Original languageEnglish
Article number8021
JournalScientific Reports
Volume14
Issue number1
DOIs
StatePublished - Dec 2024
Externally publishedYes

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