. 2024 Apr 5;14(1):8021.

doi: 10.1038/s41598-024-54063-3.

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

Xuan Wang^#¹, Molei Liu^#², Isabelle-Emmanuella Nogues^#³, Tony Chen³, Xin Xiong³, Clara-Lea Bonzel^{3

4}, Harrison Zhang^{4

5}, Chuan Hong⁶, Yin Xia⁷, Kumar Dahal⁶, Lauren Costa⁸, Jing Cui⁶; VA Million Veteran Program; J Michael Gaziano^{8

9}, Seoyoung C Kim¹⁰, Yuk-Lam Ho⁸, Kelly Cho^{8

9}, Tianxi Cai^#^{11

12}, Katherine P Liao^#^{13

14

15

16}

Collaborators, Affiliations

Collaborators

VA Million Veteran Program:
Sumitra Muralidhar, Jennifer Moser, Jennifer 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 Jr, 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

Affiliations

¹ Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA.
² Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA.
³ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
⁴ Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
⁵ Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA.
⁶ Department of Biostatistics, Duke University, Durham, NC, USA.
⁷ Department of Statistics and Data Science, Fudan University, Shanghai, China.
⁸ Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, USA.
⁹ Division of Aging, Brigham and Women's Hospital, Boston, MA, USA.
¹⁰ Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital, Boston, MA, USA.
¹¹ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA. tcai@hsph.harvard.edu.
¹² Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. tcai@hsph.harvard.edu.
¹³ Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. kliao@bwh.harvard.edu.
¹⁴ Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA. kliao@bwh.harvard.edu.
¹⁵ Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, USA. kliao@bwh.harvard.edu.
¹⁶ Rheumatology Section, VA Boston Healthcare System, Boston, USA. kliao@bwh.harvard.edu.

^# Contributed equally.

PMID: 38580710
PMCID: PMC10997791
DOI: 10.1038/s41598-024-54063-3

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

Xuan Wang et al. Sci Rep. 2024.

. 2024 Apr 5;14(1):8021.

doi: 10.1038/s41598-024-54063-3.

Authors

Collaborators

VA Million Veteran Program:
Sumitra Muralidhar, Jennifer Moser, Jennifer 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 Jr, 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

Affiliations

¹ Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA.
² Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA.
³ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
⁴ Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
⁵ Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA.
⁶ Department of Biostatistics, Duke University, Durham, NC, USA.
⁷ Department of Statistics and Data Science, Fudan University, Shanghai, China.
⁸ Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, USA.
⁹ Division of Aging, Brigham and Women's Hospital, Boston, MA, USA.
¹⁰ Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital, Boston, MA, USA.
¹¹ Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA. tcai@hsph.harvard.edu.
¹² Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. tcai@hsph.harvard.edu.
¹³ Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. kliao@bwh.harvard.edu.
¹⁴ Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA. kliao@bwh.harvard.edu.
¹⁵ Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System, Boston, MA, USA. kliao@bwh.harvard.edu.
¹⁶ Rheumatology Section, VA Boston Healthcare System, Boston, USA. kliao@bwh.harvard.edu.

^# Contributed equally.

PMID: 38580710
PMCID: PMC10997791
DOI: 10.1038/s41598-024-54063-3

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.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

**Figure 1**
Phenotypes (phecodes) significantly associated with the *IL6R* variant in AFR or EUR (BH adjusted p value ≤ 0.1).

**Figure 2**
Laboratory measurements significantly associated with the *IL6R* variant in AFR or EUR (BH adjusted p value ≤ 0.1).

**Figure 3**
Odds ratios for phenotypes with significant differential associations in AFR vs EUR ancestries (BH adjusted p value ≤ 0.1), see also Supplementary Table S2.

**Figure 4**
Comparison of standardized coefficients for associations between *IL6R* with laboratory values in AFR vs EUR (BH adjusted p value ≤ 0.1), see also Supplementary Table S3.

See this image and copyright information in PMC

References

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

Collaborators

Affiliations

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

Authors

Collaborators

Affiliations

Abstract

Conflict of interest statement

Figures

References

MeSH terms

Substances

Grants and funding

LinkOut - more resources

Full Text Sources

Medical

Research Materials