Association of Interleukin 6 Receptor Variant With Cardiovascular Disease Effects of Interleukin 6 Receptor Blocking Therapy

Cai, Tianxi; Zhang, Yichi; Ho, Yuk Lam; Link, Nicholas; Sun, Jiehuan; Huang, Jie; Damrauer, Scott M.; Ahuja, Yuri; Honerlaw, Jacqueline; Costa, Lauren; Schubert, Petra; Hong, Chuan; Gagnon, David; Sun, Yan V.; Gaziano, J. Michael; Wilson, Peter W.F.; Cho, Kelly; O’Donnell, Christopher J.; Liao, Katherine P.; Gaziano, Michael; Ramoni, Rachel; Breeling, Jim; Chang, Kyong Mi; Huang, Grant D.; Muralidhar, Sumitra; Tsao, Philip S.; Moser, Jennifer; Whitbourne, Stacey B.; Brewer, Jessica; Concato, John; Warren, Stuart; Argyres, Dean P.; Stephens, Brady; Brophy, Mary; Humphries, Donald E.; Do, Nhan; Shayan, Shahpoor; Nguyen, Xuan Mai T.; Pyarajan, Saiju; Hauser, Elizabeth R.; Zhao, Hongyu; McArdle, Rachel; Dell’Italia, Louis J.; Harley, John B.; Whittle, Jeff; Beckham, Jean C.; Wells, John A.; Gutierrez, Salvador; Gibson, Gretchen; Kaminsky, Laurence S.; Villareal, Gerardo; Xu, Junzhe; Hamner, Mark B.; Haddock, Kathlyn Sue; Bhushan, Sujata; Iruvanti, Pran; Godschalk, Michael; Ballas, Zuhair K.; Buford, Malcolm; Mastorides, Stephen; Klein, Jon; Ratcliffe, Nora R.; Flórez, Hermes; Swann, Alan C.; Murdoch, Maureen; Sriram, Peruvemba; Kinlay, Scott; Yeh, Shing Shing; Washburn, Ronald G.; Jhala, Darshana; Aguayo, Samuel M.; Cohen, David; Sharma, Satish C.; Callaghan, John T.; Oursler, Kris Ann; Whooley, Mary A.; Ahuja, Sunil K.; Gutierrez, Amparo; Schifman, Ron B.; Greco, Jennifer J.; Rauchman, Michael; Servatius, Richard J.; Oehlert, Mary E.; Wallbom, Agnes; Fernando, Ronald; Morgan, Timothy R.; Stapley, Todd; Sherman, Scott E.; Anderson, Gwenevere; Sonel, Elif; Boyko, Edward J.; Meyer, Laurence; Gupta, Samir; Fayad, Joseph; Hung, Adriana M.; Lichy, Jack H.; Hurley, Robin A.; Robey, R. Brooks; Striker, Rob

doi:10.1001/jamacardio.2018.2287

Cited by 87 publications

(101 citation statements)

References 68 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Large-scale biobank datasets provide an unparalleled opportunity to undertake hypothesis-free causal inference. Such efforts can help identify evidence supporting established causal relationships, as well as potentially implicating novel ones 12,37 . We have illustrated this type of approach in our study by evaluating the results of a phenome-wide association study of schizophrenia genetic liability.…”

Section: Discussionmentioning

confidence: 99%

An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome

Richardson

Harrison

Hemani

et al. 2018

Preprint

View full text Add to dashboard Cite

The age of large-scale genome-wide association studies (GWAS) has provided us with an unprecedented opportunity to evaluate the genetic liability of complex disease using polygenic risk scores (PRS). In this study, we have analysed 162 PRS (P<5×l0 05) derived from GWAS and 551 heritable traits from the UK Biobank study (N=334,398). Findings can be investigated using a web application (http://mrcieu.mrsoftware.org/PRS_atlas/), which we envisage will help uncover both known and novel mechanisms which contribute towards disease susceptibility.To demonstrate this, we have investigated the results from a phenome-wide evaluation of schizophrenia genetic liability. Amongst findings were inverse associations with measures of cognitive function which extensive follow-up analyses using Mendelian randomization (MR) provided evidence of a causal relationship. We have also investigated the effect of multiple risk factors on disease using mediation and multivariable MR frameworks. Our atlas provides a resource for future endeavours seeking to unravel the causal determinants of complex disease.

show abstract

Section: Discussionmentioning

confidence: 99%

An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome

Richardson

Harrison

Hemani

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Small studies of targeted interleukin-6 inhibition have been completed and provide early biomarker evidence suggesting clinical benefit [45]. One phenome-wide association study has recently linked IL-6 receptor variants with increased risks of aortic aneurysm and myocardial infarction [46], data providing further support for this approach.…”

Section: Il-6 Hscrpmentioning

confidence: 99%

Anti‐inflammatory therapy for atherosclerosis: interpreting divergent results from the CANTOS and CIRT clinical trials

Ridker

2018

J Intern Med

View full text Add to dashboard Cite

show abstract

“…Individuals with the IL6R variant have profiles similar to individuals on IL6R antagonists, tocilizumab and sarilumab; both have been indicated for the treatment of rheumatoid arthritis (RA), and tocilizumab for giant cell arteritis (GCA). A recently published standard PheWAS based on ICD codes using MVP data found 22 phenotypes significantly associated with IL6R at the false discovery rate of 0.05 [33]. While this SNP was found to be associated with vascular and cardiac diseases, its associations with RA and GCA were not statistically significant.…”

Section: (Iii) Map For Phewasmentioning

confidence: 92%

High-throughput Multimodal Automated Phenotyping (MAP) with Application to PheWAS

Liao

Sun

Cai

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Objective: Electronic health records (EHR) linked with biorepositories are a powerful platform for translational studies. A major bottleneck exists in the ability to phenotype patients accurately and efficiently. The objective of this study was to develop an automated high-throughput phenotyping method integrating International Classification of Diseases (ICD) codes and narrative data extracted using natural language processing (NLP). Method:We developed a mapping method for automatically identifying relevant ICD and NLP concepts for a specific phenotype leveraging the UMLS. Aggregated ICD and NLP counts along with healthcare utilization were jointly analyzed by fitting an ensemble of latent mixture models. The MAP algorithm yields a predicted probability of phenotype for each patient and a threshold for classifying subjects with phenotype yes/no. The algorithm was validated using labeled data for 16 phenotypes from a biorepository and further tested in an independent cohort PheWAS for two SNPs with known associations. Results:The MAP algorithm achieved higher or similar AUC and F-scores compared to the ICD code across all 16 phenotypes. The features assembled via the automated approach had comparable accuracy to those assembled via manual curation (AUCMAP 0.943, AUCmanual 0.941). The PheWAS results suggest that the MAP approach detected previously validated associations with higher power when compared to the standard PheWAS method based on ICD codes. Conclusion:The MAP approach increased the accuracy of phenotype definition while maintaining scalability, facilitating use in studies requiring large scale phenotyping, such as PheWAS.

show abstract

Association of Interleukin 6 Receptor Variant With Cardiovascular Disease Effects of Interleukin 6 Receptor Blocking Therapy

Cited by 87 publications

References 68 publications

An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome

An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome

Anti‐inflammatory therapy for atherosclerosis: interpreting divergent results from the CANTOS and CIRT clinical trials

High-throughput Multimodal Automated Phenotyping (MAP) with Application to PheWAS

Contact Info

Product

Resources

About