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4. Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis

Author

Ishigaki, Kazuyoshi, Sakaue, Saori, Terao, Chikashi, Luo, Yang, Sonehara, Kyuto, Yamaguchi, Kensuke, Amariuta, Tiffany, Too, Chun Lai, Laufer, Vincent A., Scott, Ian C., Viatte, Sebastien, Takahashi, Meiko, Ohmura, Koichiro, Murasawa, Akira, Hashimoto, Motomu, Ito, Hiromu, Hammoudeh, Mohammed, Emadi, Samar Al, Masri, Basel K., Halabi, Hussein, Badsha, Humeira, Uthman, Imad W., Wu, Xin, Lin, Li, Li, Ting, Plant, Darren, Barton, Anne, Orozco, Gisela, Verstappen, Suzanne M. M., Bowes, John, MacGregor, Alexander J., Honda, Suguru, Koido, Masaru, Tomizuka, Kohei, Kamatani, Yoichiro, Tanaka, Hiroaki, Tanaka, Eiichi, Suzuki, Akari, Maeda, Yuichi, Yamamoto, Kenichi, Miyawaki, Satoru, Xie, Gang, Zhang, Jinyi, Amos, Christopher I., Keystone, Edward, Wolbink, Gertjan, van der Horst-Bruinsma, Irene, Cui, Jing, Liao, Katherine P., Carroll, Robert J., Lee, Hye-Soon, Bang, So-Young, Siminovitch, Katherine A., de Vries, Niek, Alfredsson, Lars, Rantapää-Dahlqvist, Solbritt, Karlson, Elizabeth W., Bae, Sang-Cheol, Kimberly, Robert P., Edberg, Jeffrey C., Mariette, Xavier, Huizinga, Tom, Dieudé, Philippe, Schneider, Matthias, Kerick, Martin, Denny, Joshua C., Matsuda, Koichi, Matsuo, Keitaro, Mimori, Tsuneyo, Matsuda, Fumihiko, Fujio, Keishi, Tanaka, Yoshiya, Kumanogoh, Atsushi, Traylor, Matthew, Lewis, Cathryn M., Eyre, Stephen, Xu, Huji, Saxena, Richa, Arayssi, Thurayya, Kochi, Yuta, Ikari, Katsunori, Harigai, Masayoshi, Gregersen, Peter K., Yamamoto, Kazuhiko, Louis Bridges, Jr, S., Padyukov, Leonid, Martin, Javier, Klareskog, Lars, Okada, Yukinori, and Raychaudhuri, Soumya

Published
2022
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5. Distinct transcriptome architectures underlying lupus establishment and exacerbation

Author

Nakano, Masahiro, Ota, Mineto, Takeshima, Yusuke, Iwasaki, Yukiko, Hatano, Hiroaki, Nagafuchi, Yasuo, Itamiya, Takahiro, Maeda, Junko, Yoshida, Ryochi, Yamada, Saeko, Nishiwaki, Aya, Takahashi, Haruka, Takahashi, Hideyuki, Akutsu, Yuko, Kusuda, Takeshi, Suetsugu, Hiroyuki, Liu, Lu, Kim, Kwangwoo, Yin, Xianyong, Bang, So-Young, Cui, Yong, Lee, Hye-Soon, Shoda, Hirofumi, Zhang, Xuejun, Bae, Sang-Cheol, Terao, Chikashi, Yamamoto, Kazuhiko, Okamura, Tomohisa, Ishigaki, Kazuyoshi, and Fujio, Keishi

Published
2022
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7. A missense variant in NCF1 is associated with susceptibility to multiple autoimmune diseases

Author

Zhao, Jian, Ma, Jianyang, Deng, Yun, Kelly, Jennifer A, Kim, Kwangwoo, Bang, So-Young, Lee, Hye-Soon, Li, Quan-Zhen, Wakeland, Edward K, Qiu, Rong, Liu, Mengru, Guo, Jianping, Li, Zhanguo, Tan, Wenfeng, Rasmussen, Astrid, Lessard, Christopher J, Sivils, Kathy L, Hahn, Bevra H, Grossman, Jennifer M, Kamen, Diane L, Gilkeson, Gary S, Bae, Sang-Cheol, Gaffney, Patrick M, Shen, Nan, and Tsao, Betty P

Subjects
Biological Sciences, Genetics, Autoimmune Disease, 2.1 Biological and endogenous factors, Black or African American, Asian People, Autoimmune Diseases, Case-Control Studies, Female, Genetic Predisposition to Disease, Humans, Lupus Erythematosus, Systemic, Male, NADPH Oxidases, Polymorphism, Single Nucleotide, Reactive Oxygen Species, Sjogren's Syndrome, White People, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease with a strong genetic component characterized by autoantibody production and a type I interferon signature. Here we report a missense variant (g.74779296G>A; p.Arg90His) in NCF1, encoding the p47phox subunit of the phagocyte NADPH oxidase (NOX2), as the putative underlying causal variant that drives a strong SLE-associated signal detected by the Immunochip in the GTF2IRD1-GTF2I region at 7q11.23 with a complex genomic structure. We show that the p.Arg90His substitution, which is reported to cause reduced reactive oxygen species (ROS) production, predisposes to SLE (odds ratio (OR) = 3.47 in Asians (Pmeta = 3.1 × 10-104), OR = 2.61 in European Americans, OR = 2.02 in African Americans) and other autoimmune diseases, including primary Sjögren's syndrome (OR = 2.45 in Chinese, OR = 2.35 in European Americans) and rheumatoid arthritis (OR = 1.65 in Koreans). Additionally, decreased and increased copy numbers of NCF1 predispose to and protect against SLE, respectively. Our data highlight the pathogenic role of reduced NOX2-derived ROS levels in autoimmune diseases.

Published
2017

8. Two Functional Lupus-Associated BLK Promoter Variants Control Cell-Type- and Developmental-Stage-Specific Transcription

Author

Guthridge, Joel M, Lu, Rufei, Sun, Harry, Sun, Celi, Wiley, Graham B, Dominguez, Nicolas, Macwana, Susan R, Lessard, Christopher J, Kim-Howard, Xana, Cobb, Beth L, Kaufman, Kenneth M, Kelly, Jennifer A, Langefeld, Carl D, Adler, Adam J, Harley, Isaac TW, Merrill, Joan T, Gilkeson, Gary S, Kamen, Diane L, Niewold, Timothy B, Brown, Elizabeth E, Edberg, Jeffery C, Petri, Michelle A, Ramsey-Goldman, Rosalind, Reveille, John D, Vilá, Luis M, Kimberly, Robert P, Freedman, Barry I, Stevens, Anne M, Boackle, Susan A, Criswell, Lindsey A, Vyse, Tim J, Behrens, Timothy W, Jacob, Chaim O, Alarcón-Riquelme, Marta E, Sivils, Kathy L, Choi, Jiyoung, Bin Joo, Young, Bang, So-Young, Lee, Hye-Soon, Bae, Sang-Cheol, Shen, Nan, Qian, Xiaoxia, Tsao, Betty P, Scofield, R Hal, Harley, John B, Webb, Carol F, Wakeland, Edward K, James, Judith A, Nath, Swapan K, Graham, Robert R, and Gaffney, Patrick M

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Autoimmune Disease, Stem Cell Research, Women's Health, Lupus, 2.1 Biological and endogenous factors, Inflammatory and immune system, Alleles, Chromosomes, Human, Pair 8, Electrophoretic Mobility Shift Assay, Female, Genetic Predisposition to Disease, Haplotypes, Humans, Lupus Erythematosus, Systemic, Male, Polymorphism, Single Nucleotide, Promoter Regions, Genetic, Transcription, Genetic, src-Family Kinases, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Efforts to identify lupus-associated causal variants in the FAM167A/BLK locus on 8p21 are hampered by highly associated noncausal variants. In this report, we used a trans-population mapping and sequencing strategy to identify a common variant (rs922483) in the proximal BLK promoter and a tri-allelic variant (rs1382568) in the upstream alternative BLK promoter as putative causal variants for association with systemic lupus erythematosus. The risk allele (T) at rs922483 reduced proximal promoter activity and modulated alternative promoter usage. Allelic differences at rs1382568 resulted in altered promoter activity in B progenitor cell lines. Thus, our results demonstrated that both lupus-associated functional variants contribute to the autoimmune disease association by modulating transcription of BLK in B cells and thus potentially altering immune responses.

Published
2014

9. Associations of upper respiratory mucosa microbiota with Rheumatoid arthritis, autoantibodies, and disease activity.

Author

Joo, Young Bin, Lee, Juho, Park, Yune-Jung, Bang, So-Young, Kim, Kwangwoo, and Lee, Hye-Soon

Subjects
RESPIRATORY mucosa, PEPTIDES, BIOMARKERS, MICROBIAL diversity, RHEUMATOID arthritis
Abstract

The lung is recognized as a site for initiating the formation of self-antigen and autoimmune responses in rheumatoid arthritis (RA). We aimed to investigate the association of upper respiratory microbiota with RA, autoantibody production, and disease activity. Forty-six patients with RA and 17 controls were examined. Nasopharyngeal swab samples were sequenced for microbiome profiling using the V3–V4 region of the 16S rRNA gene. The microbial diversity and relative abundance were compared between RA patients and controls. Correlation analyses were conducted to evaluate the relationship between microbial abundance and clinical markers such as autoantibodies and disease activity. Microbial diversity analysis revealed no major differences between RA patients and healthy controls. However, beta diversity analysis indicated a subtle distinction in microbial composition (unweighted UniFrac distance) between the two groups (P = 0.03), hinting at a minor subset of microbiota associated with disease status. Differential abundance analysis uncovered specific taxa at various taxonomic levels, including Saccharibacteria (TM7) [O-1] (PFDR = 2.53 × 10−2), TM7 [F-1] (PFDR = 5.20 × 10−3), Microbacterium (PFDR = 3.37 × 10−4), and Stenotrophomonas (PFDR = 2.57 × 10−3). The relative abundance of ten genera correlated significantly with anti-cyclic citrullinated peptide (anti-CCP) antibody levels (PFDR < 0.05) and 11 genera were significantly associated with disease activity markers, including ESR, CRP, DAS28-ESR, and DAS-CRP (PFDR < 0.05). In particular, Saccharibacteria TM7 [G-3] and Peptostreptococcaceae [XI] [G-1] were correlated with all disease activity biomarkers. Dysbiosis in the upper respiratory mucosa is associated with RA, anti-CCP antibody levels, and disease activity. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Genetics of rheumatoid arthritis contributes to biology and drug discovery.

Author

Okada, Yukinori, Wu, Di, Trynka, Gosia, Raj, Towfique, Terao, Chikashi, Ikari, Katsunori, Kochi, Yuta, Ohmura, Koichiro, Suzuki, Akari, Yoshida, Shinji, Graham, Robert, Manoharan, Arun, Ortmann, Ward, Bhangale, Tushar, Denny, Joshua, Carroll, Robert, Eyler, Anne, Greenberg, Jeffrey, Kremer, Joel, Pappas, Dimitrios, Jiang, Lei, Yin, Jian, Ye, Lingying, Su, Ding-Feng, Yang, Jian, Xie, Gang, Keystone, Ed, Westra, Harm-Jan, Esko, Tõnu, Metspalu, Andres, Zhou, Xuezhong, Gupta, Namrata, Mirel, Daniel, Stahl, Eli, Diogo, Dorothée, Cui, Jing, Liao, Katherine, Guo, Michael, Myouzen, Keiko, Kawaguchi, Takahisa, Coenen, Marieke, van Riel, Piet, van de Laar, Mart, Guchelaar, Henk-Jan, Huizinga, Tom, Dieudé, Philippe, Mariette, Xavier, Bridges, S, Zhernakova, Alexandra, Toes, Rene, Tak, Paul, Miceli-Richard, Corinne, Bang, So-Young, Lee, Hye-Soon, Martin, Javier, Gonzalez-Gay, Miguel, Rodriguez-Rodriguez, Luis, Rantapää-Dahlqvist, Solbritt, Arlestig, Lisbeth, Choi, Hyon, Kamatani, Yoichiro, Galan, Pilar, Lathrop, Mark, Eyre, Steve, Bowes, John, Barton, Anne, de Vries, Niek, Moreland, Larry, Karlson, Elizabeth, Taniguchi, Atsuo, Yamada, Ryo, Kubo, Michiaki, Liu, Jun, Bae, Sang-Cheol, Worthington, Jane, Padyukov, Leonid, Klareskog, Lars, Gregersen, Peter, Raychaudhuri, Soumya, Stranger, Barbara, De Jager, Philip, Franke, Lude, Visscher, Peter, Brown, Matthew, Yamanaka, Hisashi, Mimori, Tsuneyo, Takahashi, Atsushi, Xu, Huji, Behrens, Timothy, Siminovitch, Katherine, Momohara, Shigeki, Matsuda, Fumihiko, Yamamoto, Kazuhiko, Plenge, Robert, and Criswell, Lindsey

Subjects
Alleles, Animals, Arthritis, Rheumatoid, Asian People, Case-Control Studies, Computational Biology, Drug Discovery, Drug Repositioning, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Hematologic Neoplasms, Humans, Male, Mice, Mice, Knockout, Molecular Targeted Therapy, Polymorphism, Single Nucleotide, White People
Abstract

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA). Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ∼10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2 - 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation, cis-acting expression quantitative trait loci and pathway analyses--as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes--to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

Published
2014

12. Transcriptomic network analysis reveals key drivers of response to anti-TNF biologics in patients with rheumatoid arthritis.

Author

Yu, Chae-Yeon, Lee, Hye-Soon, Joo, Young Bin, Cho, Soo-Kyung, Choi, Chan-Bum, Sung, Yoon-Kyoung, Kim, Tae-Hwan, Jun, Jae-Bum, Yoo, Dae Hyun, Bae, Sang-Cheol, Kim, Kwangwoo, and Bang, So-Young

Subjects
*ANTI-inflammatory agents, *KILLER cells, *RESEARCH funding, *RHEUMATOID arthritis, *DESCRIPTIVE statistics, *LYMPHOCYTES, *BIOLOGICAL products, *BIOTHERAPY, *BIOINFORMATICS, *LONGITUDINAL method, *RNA, *GENE expression profiling, *STATISTICS, *BIOMARKERS, *SEQUENCE analysis, *B cells
Abstract

Objective Anti-TNF biologics have been widely used to ameliorate disease activity in patients with RA. However, a large fraction of patients show a poor response to these agents. Moreover, no clinically applicable predictive biomarkers have been established. This study aimed to identify response-associated biomarkers using longitudinal transcriptomic data in two independent RA cohorts. Methods RNA sequencing data from peripheral blood cell samples of Korean and Caucasian RA cohorts before and after initial treatment with anti-TNF biologics were analysed to assess treatment-induced expression changes that differed between highly reliable excellent responders and null responders. Weighted correlation network, immune cell composition, and key driver analyses were performed to understand response-associated transcriptomic networks and cell types and their correlation with disease activity indices. Results In total, 305 response-associated genes showed significantly different treatment-induced expression changes between excellent and null responders. Co-expression network construction and subsequent key driver analysis revealed that 41 response-associated genes played a crucial role as key drivers of transcriptomic alteration in four response-associated networks involved in various immune pathways: type I IFN signalling, myeloid leucocyte activation, B cell activation, and NK cell/lymphocyte–mediated cytotoxicity. Transcriptomic response scores that we developed to estimate the individual-level degree of expression changes in the response-associated key driver genes were significantly correlated with the changes in clinical indices in independent patients with moderate or ambiguous response outcomes. Conclusion This study provides response-specific treatment-induced transcriptomic signatures by comparing the transcriptomic landscape between patients with excellent and null responses to anti-TNF drugs at both gene and network levels. [ABSTRACT FROM AUTHOR]

Published
2024
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13. Transcriptomic network analysis reveals key drivers of response to anti-TNF biologics in patients with rheumatoid arthritis

Author

Yu, Chae-Yeon, primary, Lee, Hye-Soon, additional, Joo, Young Bin, additional, Cho, Soo-Kyung, additional, Choi, Chan-Bum, additional, Sung, Yoon-Kyoung, additional, Kim, Tae-Hwan, additional, Jun, Jae-Bum, additional, Yoo, Dae Hyun, additional, Bae, Sang-Cheol, additional, Kim, Kwangwoo, additional, and Bang, So-Young, additional

Published
2023
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15. Comparative effectiveness of JAK inhibitors and biologic disease-modifying antirheumatic drugs in patients with rheumatoid arthritis

Author

Cho, Soo-Kyung, primary, Kim, Hyoungyoung, additional, Song, Yeo-Jin, additional, Kim, Hye Won, additional, Nam, Eunwoo, additional, Lee, Shin-Seok, additional, Lee, Hye-Soon, additional, Park, Sung-Hoon, additional, Lee, Yeon-Ah, additional, Park, Min-Chan, additional, Chang, Sung Hae, additional, Kim, Hyoun-Ah, additional, Kwok, Seung-Ki, additional, Kim, Hae-Rim, additional, Kim, Hyun-Sook, additional, Yoon, Bo Young, additional, Uhm, Wan-Sik, additional, Kim, Yong-Gil, additional, Kim, Jae Hoon, additional, Lee, Jisoo, additional, Choi, Jeongim, additional, and Sung, Yoon-Kyoung, additional

Published
2023
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19. LSO-079 Dynamic changes of immune cells in systemic lupus erythematosus with nephritis using longitudinal peripheral blood single-cell RNA-seq

Author

Paek, Seung-Jun, primary, Lee, Hye-Soon, additional, Lee, Ye Ji, additional, Bang, So-Young, additional, Kang, Bo-Kyeong, additional, Park, Dae Jin, additional, Joo, Young Bin, additional, Kim, Mimi, additional, Kim, Hyunsung, additional, Park, Sung Yul, additional, Park, Woong-Yang, additional, Kim, Kyu-Tae, additional, and Bae, Sang-Cheol, additional

Published
2023
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20. LSO-072 Comparison of COVID-19 vaccination with influenza vaccination in Korean patients with systemic lupus erythematosus: perception, adverse events, and flares from the CIVIL study

Author

Park, Seonghoon, primary, Shim, Seung Cheol, additional, Lee, Ji Soo, additional, Lee, Young Ho, additional, Kwok, Seung-Ki, additional, Kim, Yong-Gil, additional, Park, Yong-Beom, additional, Park, Sung-Hwan, additional, Bae, Sang-Cheol, additional, Suh, Chang Hee, additional, Sung, Yoon-Kyung, additional, Lee, Shin-Seok, additional, Lee, Chang-Keun, additional, Lee, Hye-Soon, additional, Jung, Seung Min, additional, and Cha, Hoon-Suk, additional

Published
2023
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22. LP-116 To get, or not to get: risk and benefit of COVID-19 vaccine in Korean patients with systemic lupus erythematosus

Author

Park, Seonghoon, primary, Lee, Ji Soo, additional, Lee, Young Ho, additional, Kwok, Seung-Ki, additional, Kim, Yong-Gil, additional, Park, Yong-Beom, additional, Park, Sung-Hwan, additional, Bae, Sang-Cheol, additional, Suh, Chang Hee, additional, Sung, Yoon-Kyung, additional, Lee, Shin-Seok, additional, Lee, Chang-Keun, additional, Lee, Hye-Soon, additional, Jung, Seung Min, additional, Cha, Hoon-Suk, additional, and Shim, Seung Cheol, additional

Published
2023
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24. LO-042 High genetic risk load for systemic lupus erythematosus in antinuclear antibody-positive individuals at the preclinical stage

Author

Chun, Sehwan, primary, Bang, So-Young, additional, Kwon, Young-Chang, additional, Cho, Soo-Kyung, additional, Choi, Chan-Bum, additional, Sung, Yoon-Kyoung, additional, Han, Ji-Young, additional, Kim, Tae-Hwan, additional, Jun, Jae-Bum, additional, Yoo, Dae Hyun, additional, Lee, Hye-Soon, additional, Kim, Kwangwoo, additional, and Bae, Sang-Cheol, additional

Published
2023
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26. Higher Genetic Risk Loads Confer More Diverse Manifestations and Higher Risk of Lupus Nephritis in Systemic Lupus Erythematosus

Author

Kwon, Young‐Chang, primary, Ha, Eunji, additional, Kwon, Hyuk‐Hee, additional, Park, Dae Jin, additional, Shin, Jung‐Min, additional, Joo, Young Bin, additional, Chung, Won Tae, additional, Yoo, Dae‐Hyun, additional, Lee, Hye‐Soon, additional, Kim, Kwangwoo, additional, Bae, Sang‐Cheol, additional, and Bang, So‐Young, additional

Published
2023
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29. Comparative effectiveness of treatment options after conventional DMARDs failure in rheumatoid arthritis

Author

Sung, Yoon-Kyoung, Cho, Soo-Kyung, Kim, Dam, Choi, Chan-Bum, Won, Soyoung, Bang, So-Young, Cha, Hoon-Suk, Choe, Jung-Yoon, Chung, Won Tae, Hong, Seung-Jae, Jun, Jae-Bum, Kim, Hyoun Ah, Kim, Jinseok, Kim, Seong-Kyu, Kim, Tae-Hwan, Lee, Hye-Soon, Lee, Jaejoon, Lee, Jisoo, Lee, Shin-Seok, Lee, Sung Won, Lee, Yeon-Ah, Nah, Seong-Su, Suh, Chang-Hee, Yoo, Dae-Hyun, Yoon, Bo Young, Bae, Sang Cheol, and For the BIOPSY and KORONA investigators

Published
2017
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32. MUC5Bpromoter variant rs35705950, rare but significant susceptibility locus in rheumatoid arthritis-interstitial lung disease with usual interstitial pneumonia in Asian populations

Author

Joo, Young Bin, primary, Ahn, Soo Min, additional, Bang, So-Young, additional, Park, Youngho, additional, Hong, Su Jin, additional, Lee, Youkyung, additional, Cho, Soo-Kyung, additional, Choi, Chan-Bum, additional, Sung, Yoon-Kyoung, additional, Kim, Tae-Hwan, additional, Jun, Jae-Bum, additional, Yoo, Dae Hyun, additional, Bae, Sang-Cheol, additional, and Lee, Hye-Soon, additional

Published
2022
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35. Mapping health assessment questionnaire disability index (HAQ-DI) score, pain visual analog scale (VAS), and disease activity score in 28 joints (DAS28) onto the EuroQol-5D (EQ-5D) utility score with the KORean Observational study Network for Arthritis (KORONA) registry data

Author

Kim, Hye-Lin, Kim, Dam, Jang, Eun Jin, Lee, Min-Young, Song, Hyun Jin, Park, Sun-Young, Cho, Soo-Kyung, Sung, Yoon-Kyoung, Choi, Chan-Bum, Won, Soyoung, Bang, So-Young, Cha, Hoon-Suk, Choe, Jung-Yoon, Chung, Won Tae, Hong, Seung-Jae, Jun, Jae-Bum, Kim, Jinseok, Kim, Seong-Kyu, Kim, Tae-Hwan, Kim, Tae-Jong, Koh, Eunmi, Lee, Hwajeong, Lee, Hye-Soon, Lee, Jisoo, Lee, Shin-Seok, Lee, Sung Won, Park, Sung-Hoon, Shim, Seung-Cheol, Yoo, Dae-Hyun, Yoon, Bo Young, Bae, Sang-Cheol, and Lee, Eui-Kyung

Published
2016
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37. Confirmation of five novel susceptibility loci for systemic lupus erythematosus (SLE) and integrated network analysis of 82 SLE susceptibility loci

Author

Molineros, Julio E., Yang, Wanling, Zhou, Xu-jie, Sun, Celi, Okada, Yukinori, Zhang, Huoru, Heng Chua, Kek, Lau, Yu-Lung, Kochi, Yuta, Suzuki, Akari, Yamamoto, Kazuhiko, Ma, Jianyang, Bang, So-Young, Lee, Hye-Soon, Kim, Kwangwoo, Bae, Sang-Cheol, Zhang, Hong, Shen, Nan, Looger, Loren L., and Nath, Swapan K.

Published
2017
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38. Rheumatoid arthritis patients fulfilling Korean National Health Insurance reimbursement guidelines for anti-tumor necrosis factor-α treatment and comparison to other guidelines

Author

Hur, Jin-Wuk, Choe, Jung-Yoon, Kim, Dong-Wook, Kim, Hyun Ah, Kim, Sang-Hyon, Kim, Wan-Uk, Kim, Yun Sung, Lee, Hye-Soon, Lee, Sang-Heon, Park, Sung-Hwan, Park, Won, Park, Yong-Beom, Suh, Chang-Hee, Shim, Seung-Cheol, Song, Yeong-Wook, Yoon, Bo Young, Yu, Dae Young, and Yoo, Dae Hyun

Published
2015
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42. Korean Observational Study Network for Arthritis (KORONA): Establishment of a Prospective Multicenter Cohort for Rheumatoid Arthritis in South Korea

Author

Sung, Yoon-Kyoung, Cho, Soo-Kyung, Choi, Chan-Bum, Park, So-Yeon, Shim, Jeeseon, Ahn, Joong Kyong, Bang, So-Young, Cha, Hoon-Suk, Choe, Jung-Yoon, Chung, Won Tae, Her, Minyoung, Hong, Seung-Jae, Hong, Yun Kyung, Joung, Chung-Il, Jun, Jae-Bum, Jung, Young Ok, Kang, Young Mo, Kim, Dong-Yook, Kim, Hae-Rim, Kim, Hyoun Ah, Kim, Jinseok, Kim, Seong-Kyu, Kim, Sung-Il, Kim, Tae-Hwan, Kim, Tae-Jong, Koh, Eunmi, Lee, Choong Ki, Lee, Hye-Soon, Lee, Jisoo, Lee, Sang-Heon, Lee, Sang-Hoon, Lee, Shin-Seok, Lee, Sung Won, Lee, Yeon-Ah, Nah, Seong-Su, Park, Sung-Hoon, Sheen, Dong Hyuk, Shim, Seung-Cheol, Gyu Song, Gwan, Suh, Chang-Hee, Uhm, Wan-Sik, Yoo, Dae-Hyun, Yoo, Wan-Hee, Yoon, Bo Young, and Bae, Sang-Cheol

Published
2012
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44. Biological insights into systemic lupus erythematosus through an immune cell-specific transcriptome-wide association study

Author

Yin, Xianyong, Kim, Kwangwoo, Suetsugu, Hiroyuki, Bang, So-Young, Wen, Leilei, Koido, Masaru, Ha, Eunji, Liu, Lu, Sakamoto, Yuma, Jo, Sungsin, Leng, Rui-Xue, Otomo, Nao, Kwon, Young-Chang, Sheng, Yujun, Sugano, Nobuhiko, Hwang, Mi Yeong, Li, Weiran, Mukai, Masaya, Yoon, Kyungheon, Cai, Minglong, Ishigaki, Kazuyoshi, Chung, Won Tae, Huang, He, Takahashi, Daisuke, Lee, Shin-Seok, Wang, Mengwei, Karino, Kohei, Shim, Seung-Cheol, Zheng, Xiaodong, Miyamura, Tomoya, Kang, Young Mo, Ye, Dongqing, Nakamura, Junichi, Suh, Chang-Hee, Tang, Yuanjia, Motomura, Goro, Park, Yong-Beom, Ding, Huihua, Kuroda, Takeshi, Choe, Jung-Yoon, Li, Chengxu, Niiro, Hiroaki, Park, Youngho, Shen, Changbing, Miyamoto, Takeshi, Ahn, Ga-Young, Fei, Wenmin, Takeuchi, Tsutomu, Shin, Jung-Min, Li, Keke, Kawaguchi, Yasushi, Lee, Yeon-Kyung, Wang, Yong-Fei, Amano, Koichi, Park, Dae Jin, Yang, Wanling, Tada, Yoshifumi, Lau, Yu Lung, Yamaji, Ken, Zhu, Zhengwei, Shimizu, Masato, Atsumi, Takashi, Suzuki, Akari, Sumida, Takayuki, Okada, Yukinori, Matsuda, Koichi, Matsuo, Keitaro, Kochi, Yuta, Yamamoto, Kazuhiko, Ohmura, Koichiro, Kim, Tae-Hwan, Yang, Sen, Yamamoto, Takuaki, Kim, Bong-Jo, Shen, Nan, Ikegawa, Shiro, Lee, Hye-Soon, Zhang, Xuejun, Terao, Chikashi, Cui, Yong, Bae, Sang-Cheol, Japanese Research Committee on Idiopathic Osteonecrosis of the Femoral Head, Yin, Xianyong, Kim, Kwangwoo, Suetsugu, Hiroyuki, Bang, So-Young, Wen, Leilei, Koido, Masaru, Ha, Eunji, Liu, Lu, Sakamoto, Yuma, Jo, Sungsin, Leng, Rui-Xue, Otomo, Nao, Kwon, Young-Chang, Sheng, Yujun, Sugano, Nobuhiko, Hwang, Mi Yeong, Li, Weiran, Mukai, Masaya, Yoon, Kyungheon, Cai, Minglong, Ishigaki, Kazuyoshi, Chung, Won Tae, Huang, He, Takahashi, Daisuke, Lee, Shin-Seok, Wang, Mengwei, Karino, Kohei, Shim, Seung-Cheol, Zheng, Xiaodong, Miyamura, Tomoya, Kang, Young Mo, Ye, Dongqing, Nakamura, Junichi, Suh, Chang-Hee, Tang, Yuanjia, Motomura, Goro, Park, Yong-Beom, Ding, Huihua, Kuroda, Takeshi, Choe, Jung-Yoon, Li, Chengxu, Niiro, Hiroaki, Park, Youngho, Shen, Changbing, Miyamoto, Takeshi, Ahn, Ga-Young, Fei, Wenmin, Takeuchi, Tsutomu, Shin, Jung-Min, Li, Keke, Kawaguchi, Yasushi, Lee, Yeon-Kyung, Wang, Yong-Fei, Amano, Koichi, Park, Dae Jin, Yang, Wanling, Tada, Yoshifumi, Lau, Yu Lung, Yamaji, Ken, Zhu, Zhengwei, Shimizu, Masato, Atsumi, Takashi, Suzuki, Akari, Sumida, Takayuki, Okada, Yukinori, Matsuda, Koichi, Matsuo, Keitaro, Kochi, Yuta, Yamamoto, Kazuhiko, Ohmura, Koichiro, Kim, Tae-Hwan, Yang, Sen, Yamamoto, Takuaki, Kim, Bong-Jo, Shen, Nan, Ikegawa, Shiro, Lee, Hye-Soon, Zhang, Xuejun, Terao, Chikashi, Cui, Yong, Bae, Sang-Cheol, and Japanese Research Committee on Idiopathic Osteonecrosis of the Femoral Head

Abstract

Objective Genome-wide association studies (GWAS) have identified >100 risk loci for systemic lupus erythematosus (SLE), but the disease genes at most loci remain unclear, hampering translation of these genetic discoveries. We aimed to prioritise genes underlying the 110 SLE loci that were identified in the latest East Asian GWAS meta-analysis. Methods We built gene expression predictive models in blood B cells, CD4(+) and CD8(+) T cells, monocytes, natural killer cells and peripheral blood cells of 105 Japanese individuals. We performed a transcriptome-wide association study (TWAS) using data from the latest genome-wide association meta-analysis of 208 370 East Asians and searched for candidate genes using TWAS and three data-driven computational approaches. Results TWAS identified 171 genes for SLE (p<1.0x10(-5)); 114 (66.7%) showed significance only in a single cell type; 127 (74.3%) were in SLE GWAS loci. TWAS identified a strong association between CD83 and SLE (p<7.7x10(-8)). Meta-analysis of genetic associations in the existing 208 370 East Asian and additional 1498 cases and 3330 controls found a novel single-variant association at rs72836542 (OR=1.11, p=4.5x10(-9)) around CD83. For the 110 SLE loci, we identified 276 gene candidates, including 104 genes at recently-identified SLE novel loci. We demonstrated in vitro that putative causal variant rs61759532 exhibited an allele-specific regulatory effect on ACAP1, and that presence of the SLE risk allele decreased ACAP1 expression. Conclusions Cell-level TWAS in six types of immune cells complemented SLE gene discovery and guided the identification of novel genetic associations. The gene findings shed biological insights into SLE genetic associations.

Published
2022

50. Identification of a Systemic Lupus Erythematosus Risk Locus Spanning ATG16L2, FCHSD2, and P2RY2 in Koreans

Author

Lessard, Christopher J., Sajuthi, Satria, Zhao, Jian, Kim, Kwangwoo, Ice, John A., Li, He, Ainsworth, Hannah, Rasmussen, Astrid, Kelly, Jennifer A., Marion, Miranda, Bang, So-Young, Joo, Young Bin, Choi, Jeongim, Lee, Hye-Soon, Kang, Young Mo, Suh, Chang-Hee, Chung, Won Tae, Lee, Soo-Kon, Choe, Jung-Yoon, Shim, Seung Cheol, Oh, Ji Hee, Kim, Young Jin, Han, Bok-Ghee, Shen, Nan, Howe, Hwee Siew, Wakeland, Edward K., Li, Quan-Zhen, Song, Yeong Wook, Gaffney, Patrick M., Alarcón-Riquelme, Marta E., Criswell, Lindsey A., Jacob, Chaim O., Kimberly, Robert P., Vyse, Timothy J., Harley, John B., Sivils, Kathy L., Bae, Sang-Cheol, Langefeld, Carl D., and Tsao, Betty P.

Published
2016
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