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311 results on '"Ishigaki, Kazuyoshi"'

3. Immunosuppression causes dynamic changes in expression QTLs in psoriatic skin.

Author

Xiao, Qian, Mears, Joseph, Nathan, Aparna, Ishigaki, Kazuyoshi, Baglaenko, Yuriy, Lim, Noha, Cooney, Laura, Harris, Kristina, Anderson, Mark, Fox, David, Smilek, Dawn, Krueger, James, and Raychaudhuri, Soumya

Abstract

Psoriasis is a chronic, systemic inflammatory condition primarily affecting skin. While the role of the immune compartment (e.g., T cells) is well established, the changes in the skin compartment are more poorly understood. Using longitudinal skin biopsies (n = 375) from the Psoriasis Treatment with Abatacept and Ustekinumab: A Study of Efficacy(PAUSE) clinical trial (n = 101), we report 953 expression quantitative trait loci (eQTLs). Of those, 116 eQTLs have effect sizes that were modulated by local skin inflammation (eQTL interactions). By examining these eQTL genes (eGenes), we find that most are expressed in the skin tissue compartment, and a subset overlap with the NRF2 pathway. Indeed, the strongest eQTL interaction signal - rs1491377616-LCE3C - links a psoriasis risk locus with a gene specifically expressed in the epidermis. This eQTL study highlights the potential to use biospecimens from clinical trials to discover in vivo eQTL interactions with therapeutically relevant environmental variables.

Published
2023

4. High incidence of proliferative and membranous nephritis in SLE patients with low proteinuria in the Accelerating Medicines Partnership.

Author

Carlucci, Philip M, Li, Jessica, Fava, Andrea, Deonaraine, Kristina K, Wofsy, David, James, Judith A, Putterman, Chaim, Diamond, Betty, Davidson, Anne, Fine, Derek M, Monroy-Trujillo, Jose, Atta, Mohamed G, DeJager, Wade, Guthridge, Joel M, Haag, Kristin, Rao, Deepak A, Brenner, Michael B, Lederer, James A, Apruzzese, William, Belmont, H Michael, Izmirly, Peter M, Zaminski, Devyn, Wu, Ming, Connery, Sean, Payan-Schober, Fernanda, Furie, Richard, Dall’Era, Maria, Cho, Kerry, Kamen, Diane, Kalunian, Kenneth, Anolik, Jennifer, Barnas, Jennifer, Ishimori, Mariko, Weisman, Michael H, Goff, Jennifer, Dunn, Patrick J, Raychaudhuri, Soumya, Zhang, Fan, Korsunsky, Ilya, Nathan, Aparna, Mears, Joseph, Ishigaki, Kazuyoshi, Xiao, Qian, Millard, Nghia, Weinand, Kathryn, Sakaue, Saori, Utz, PJ, Mao, Rong, Robinson, Bill, Maecker, Holden, Macwana, Susan, Bridges, S Louis, Bykerk, Vivian, Donlin, Laura, Goodman, Susan, DiCarlo, Edward, Smith, Melanie, Lakhanpal, Amit, Sherman, Heather, Singaraju, Anvita, Shakib, Lorien, Ritchlin, Christopher, Boyce, Brendan, Tabechian, Darren, McDavid, Andrew, Rangel-Moreno, Javier, Meednu, Nida, Albrecht, Jen, Wei, Kevin, Helena Jonsson, A, Simmons, Daimon, Keras, Gregory, Keegan, Joshua, Watts, Gerald, Li Zhu, Yuhong, Chicoine, Adam, Jian Li, Zhihan, Gravallese, Ellen M, Howard, Kaitlyn, McGeachy, Mandy, Firestein, Gary S, Boyle, David L, Ceponis, Arnold, Gregersen, Peter K, Horowitz, Diane, Perlman, Harris, Dominguez, Salina, Cuda, Carla M, Mandolin, Arthur M, Thakrar, Anjali, Bathon, Joan M, Hughes, Laura, Michael Holers, V, Seifert, Jennifer, Deane, Kevin, Moreland, Larry W, Filer, Andrew, Raza, Karim, Sahbudin, Ilfita, and Pitzalis, Costantino

Subjects
Clinical Research, Kidney Disease, Lupus, Autoimmune Disease, Humans, Lupus Nephritis, Prospective Studies, Incidence, Proteinuria, Kidney Function Tests, Kidney, systemic lupus erythematosus, lupus nephritis, diagnosis, Accelerating Medicines Partnership (AMP) RA/SLE Network, Clinical Sciences, Immunology, Public Health and Health Services, Arthritis & Rheumatology
Abstract

ObjectiveDelayed detection of LN associates with worse outcomes. There are conflicting recommendations regarding a threshold level of proteinuria at which biopsy will likely yield actionable management. This study addressed the association of urine protein:creatinine ratios (UPCR) with clinical characteristics and investigated the incidence of proliferative and membranous histology in patients with a UPCR between 0.5 and 1.MethodsA total of 275 SLE patients (113 first biopsy, 162 repeat) were enrolled in the multicentre multi-ethnic/racial Accelerating Medicines Partnership across 15 US sites at the time of a clinically indicated renal biopsy. Patients were followed for 1 year.ResultsAt biopsy, 54 patients had UPCR

Published
2022

5. Quantification of escape from X chromosome inactivation with single-cell omics data reveals heterogeneity across cell types and tissues

Author

Charoensawan, Varodom, Hon, Chung-Chau, Majumder, Partha P., Matangkasombut, Ponpan, Park, Woong-Yang, Prabhakar, Shyam, Shin, Jay W., Carninci, Piero, Chambers, John C., Loh, Marie, Pithukpakorn, Manop, Suktitipat, Bhoom, Yamamoto, Kazuhiko, Rajagopalan, Deepa, Rayan, Nirmala Arul, Sankaran, Shvetha, Chantaraamporn, Juthamard, Chatterjee, Ankita, Ghosh, Supratim, Han, Kyung Yeon, Jevapatarakul, Damita, Nguantad, Sarintip, Sarkar, Sumanta, Thungsatianpun, Narita, Abe, Mai, Furukawa, Seiko, Inoue, Gyo, Myouzen, Keiko, Oh, Jin-Mi, Suzuki, Akari, Ando, Yoshinari, Kojima, Miki, Kouno, Tsukasa, Lim, Jinyeong, Maitra, Arindam, Tan, Le Min, Venkatesh, Prasanna Nori, Choi, Murim, Park, Jong-Eun, Buyamin, Eliora Violain, Kock, Kian Hong, Xuan Lin, Quy Xiao, Moody, Jonathan, Sonthalia, Radhika, Ishigaki, Kazuyoshi, Nakano, Masahiro, Okada, Yukinori, Tomofuji, Yoshihiko, Ho Namkoong, Edahiro, Ryuya, Takano, Tomomi, Nishihara, Hiroshi, Shirai, Yuya, Sonehara, Kyuto, Tanaka, Hiromu, Azekawa, Shuhei, Mikami, Yohei, Lee, Ho, Hasegawa, Takanori, Okudela, Koji, Okuzaki, Daisuke, Motooka, Daisuke, Kanai, Masahiro, Naito, Tatsuhiko, Yamamoto, Kenichi, Wang, Qingbo S., Saiki, Ryunosuke, Ishihara, Rino, Matsubara, Yuta, Hamamoto, Junko, Hayashi, Hiroyuki, Yoshimura, Yukihiro, Tachikawa, Natsuo, Yanagita, Emmy, Hyugaji, Takayoshi, Shimizu, Eigo, Katayama, Kotoe, Kato, Yasuhiro, Morita, Takayoshi, Takahashi, Kazuhisa, Harada, Norihiro, Naito, Toshio, Hiki, Makoto, Matsushita, Yasushi, Takagi, Haruhi, Aoki, Ryousuke, Nakamura, Ai, Harada, Sonoko, Sasano, Hitoshi, Kabata, Hiroki, Masaki, Katsunori, Kamata, Hirofumi, Ikemura, Shinnosuke, Chubachi, Shotaro, Okamori, Satoshi, Terai, Hideki, Morita, Atsuho, Asakura, Takanori, Sasaki, Junichi, Morisaki, Hiroshi, Uwamino, Yoshifumi, Nanki, Kosaku, Uchida, Sho, Uno, Shunsuke, Nishimura, Tomoyasu, Ishiguro, Takashi, Isono, Taisuke, Shibata, Shun, Matsui, Yuma, Hosoda, Chiaki, Takano, Kenji, Nishida, Takashi, Kobayashi, Yoichi, Takaku, Yotaro, Takayanagi, Noboru, Ueda, Soichiro, Tada, Ai, Miyawaki, Masayoshi, Yamamoto, Masaomi, Yoshida, Eriko, Hayashi, Reina, Nagasaka, Tomoki, Arai, Sawako, Kaneko, Yutaro, Sasaki, Kana, Tagaya, Etsuko, Kawana, Masatoshi, Arimura, Ken, Takahashi, Kunihiko, Anzai, Tatsuhiko, Ito, Satoshi, Endo, Akifumi, Uchimura, Yuji, Miyazaki, Yasunari, Honda, Takayuki, Tateishi, Tomoya, Tohda, Shuji, Ichimura, Naoya, Sonobe, Kazunari, Sassa, Chihiro Tani, Nakajima, Jun, Nakano, Yasushi, Nakajima, Yukiko, Anan, Ryusuke, Arai, Ryosuke, Kurihara, Yuko, Harada, Yuko, Nishio, Kazumi, Ueda, Tetsuya, Azuma, Masanori, Saito, Ryuichi, Sado, Toshikatsu, Miyazaki, Yoshimune, Sato, Ryuichi, Haruta, Yuki, Nagasaki, Tadao, Yasui, Yoshinori, Hasegawa, Yoshinori, Mutoh, Yoshikazu, Kimura, Tomoki, Sato, Tomonori, Takei, Reoto, Hagimoto, Satoshi, Noguchi, Yoichiro, Yamano, Yasuhiko, Sasano, Hajime, Ota, Sho, Nakamori, Yasushi, Yoshiya, Kazuhisa, Saito, Fukuki, Yoshihara, Tomoyuki, Wada, Daiki, Iwamura, Hiromu, Kanayama, Syuji, Maruyama, Shuhei, Yoshiyama, Takashi, Ohta, Ken, Kokuto, Hiroyuki, Ogata, Hideo, Tanaka, Yoshiaki, Arakawa, Kenichi, Shimoda, Masafumi, Osawa, Takeshi, Tateno, Hiroki, Hase, Isano, Yoshida, Shuichi, Suzuki, Shoji, Kawada, Miki, Horinouchi, Hirohisa, Saito, Fumitake, Mitamura, Keiko, Hagihara, Masao, Ochi, Junichi, Uchida, Tomoyuki, Baba, Rie, Arai, Daisuke, Ogura, Takayuki, Takahashi, Hidenori, Hagiwara, Shigehiro, Nagao, Genta, Konishi, Shunichiro, Nakachi, Ichiro, Murakami, Koji, Yamada, Mitsuhiro, Sugiura, Hisatoshi, Sano, Hirohito, Matsumoto, Shuichiro, Kimura, Nozomu, Ono, Yoshinao, Baba, Hiroaki, Suzuki, Yusuke, Nakayama, Sohei, Masuzawa, Keita, Namba, Shinichi, Suzuki, Ken, Naito, Yoko, Liu, Yu-Chen, Takuwa, Ayako, Sugihara, Fuminori, Wing, James B., Sakakibara, Shuhei, Hizawa, Nobuyuki, Shiroyama, Takayuki, Miyawaki, Satoru, Kawamura, Yusuke, Nakayama, Akiyoshi, Matsuo, Hirotaka, Yuichi, Maeda, Nii, Takuro, Noda, Yoshimi, Niitsu, Takayuki, Adachi, Yuichi, Enomoto, Takatoshi, Amiya, Saori, Hara, Reina, Yamaguchi, Yuta, Murakami, Teruaki, Kuge, Tomoki, Matsumoto, Kinnosuke, Yamamoto, Yuji, Yamamoto, Makoto, Yoneda, Midori, Kishikawa, Toshihiro, Yamada, Shuhei, Kawabata, Shuhei, Kijima, Noriyuki, Takagaki, Masatoshi, Sasa, Noah, Ueno, Yuya, Suzuki, Motoyuki, Takemoto, Norihiko, Eguchi, Hirotaka, Fukusumi, Takahito, Imai, Takao, Fukushima, Munehisa, Kishima, Haruhiko, Inohara, Hidenori, Tomono, Kazunori, Kato, Kazuto, Takahashi, Meiko, Matsuda, Fumihiko, Hirata, Haruhiko, Takeda, Yoshito, Koh, Hidefumi, Manabe, Tadashi, Funatsu, Yohei, Ito, Fumimaro, Fukui, Takahiro, Shinozuka, Keisuke, Kohashi, Sumiko, Miyazaki, Masatoshi, Shoko, Tomohisa, Kojima, Mitsuaki, Adachi, Tomohiro, Ishikawa, Motonao, Takahashi, Kenichiro, Inoue, Takashi, Hirano, Toshiyuki, Kobayashi, Keigo, Takaoka, Hatsuyo, Watanabe, Kazuyoshi, Miyazawa, Naoki, Kimura, Yasuhiro, Sado, Reiko, Sugimoto, Hideyasu, Kamiya, Akane, Kuwahara, Naota, Fujiwara, Akiko, Matsunaga, Tomohiro, Sato, Yoko, Okada, Takenori, Hirai, Yoshihiro, Kawashima, Hidetoshi, Narita, Atsuya, Niwa, Kazuki, Sekikawa, Yoshiyuki, Nishi, Koichi, Nishitsuji, Masaru, Tani, Mayuko, Suzuki, Junya, Nakatsumi, Hiroki, Ogura, Takashi, Kitamura, Hideya, Hagiwara, Eri, Murohashi, Kota, Okabayashi, Hiroko, Mochimaru, Takao, Nukaga, Shigenari, Satomi, Ryosuke, Oyamada, Yoshitaka, Mori, Nobuaki, Baba, Tomoya, Fukui, Yasutaka, Odate, Mitsuru, Mashimo, Shuko, Makino, Yasushi, Yagi, Kazuma, Hashiguchi, Mizuha, Kagyo, Junko, Shiomi, Tetsuya, Fuke, Satoshi, Saito, Hiroshi, Tsuchida, Tomoya, Fujitani, Shigeki, Takita, Mumon, Morikawa, Daiki, Yoshida, Toru, Izumo, Takehiro, Inomata, Minoru, Kuse, Naoyuki, Awano, Nobuyasu, Tone, Mari, Ito, Akihiro, Nakamura, Yoshihiko, Hoshino, Kota, Maruyama, Junichi, Ishikura, Hiroyasu, Takata, Tohru, Odani, Toshio, Amishima, Masaru, Hattori, Takeshi, Shichinohe, Yasuo, Kagaya, Takashi, Kita, Toshiyuki, Ohta, Kazuhide, Sakagami, Satoru, Koshida, Kiyoshi, Hayashi, Kentaro, Shimizu, Tetsuo, Kozu, Yutaka, Hiranuma, Hisato, Gon, Yasuhiro, Izumi, Namiki, Nagata, Kaoru, Ueda, Ken, Taki, Reiko, Hanada, Satoko, Kawamura, Kodai, Ichikado, Kazuya, Nishiyama, Kenta, Muranaka, Hiroyuki, Nakamura, Kazunori, Hashimoto, Naozumi, Wakahara, Keiko, Koji, Sakamoto, Omote, Norihito, Ando, Akira, Kodama, Nobuhiro, Kaneyama, Yasunari, Shunsuke, Maeda, Kuraki, Takashige, Matsumoto, Takemasa, Yokote, Koutaro, Nakada, Taka-Aki, Abe, Ryuzo, Oshima, Taku, Shimada, Tadanaga, Harada, Masahiro, Takahashi, Takeshi, Ono, Hiroshi, Sakurai, Toshihiro, Shibusawa, Takayuki, Kimizuka, Yoshifumi, Kawana, Akihiko, Sano, Tomoya, Watanabe, Chie, Suematsu, Ryohei, Sageshima, Hisako, Yoshifuji, Ayumi, Ito, Kazuto, Takahashi, Saeko, Ishioka, Kota, Nakamura, Morio, Masuda, Makoto, Wakabayashi, Aya, Watanabe, Hiroki, Ueda, Suguru, Nishikawa, Masanori, Chihara, Yusuke, Takeuchi, Mayumi, Onoi, Keisuke, Shinozuka, Jun, Sueyoshi, Atsushi, Nagasaki, Yoji, Okamoto, Masaki, Ishihara, Sayoko, Shimo, Masatoshi, Tokunaga, Yoshihisa, Kusaka, Yu, Ohba, Takehiko, Isogai, Susumu, Ogawa, Aki, Inoue, Takuya, Fukuyama, Satoru, Eriguchi, Yoshihiro, Yonekawa, Akiko, Kan-o, Keiko, Matsumoto, Koichiro, Kanaoka, Kensuke, Ihara, Shoichi, Komuta, Kiyoshi, Inoue, Yoshiaki, Chiba, Shigeru, Yamagata, Kunihiro, Hiramatsu, Yuji, Kai, Hirayasu, Asano, Koichiro, Oguma, Tsuyoshi, Ito, Yoko, Hashimoto, Satoru, Yamasaki, Masaki, Kasamatsu, Yu, Komase, Yuko, Hida, Naoya, Tsuburai, Takahiro, Oyama, Baku, Takada, Minoru, Kanda, Hidenori, Kitagawa, Yuichiro, Fukuta, Tetsuya, Miyake, Takahito, Yoshida, Shozo, Ogura, Shinji, Abe, Shinji, Kono, Yuta, Togashi, Yuki, Takoi, Hiroyuki, Kikuchi, Ryota, Ogawa, Shinichi, Ogata, Tomouki, Ishihara, Shoichiro, Kanehiro, Arihiko, Ozaki, Shinji, Fuchimoto, Yasuko, Wada, Sae, Fujimoto, Nobukazu, Nishiyama, Kei, Terashima, Mariko, Beppu, Satoru, Yoshida, Kosuke, Narumoto, Osamu, Nagai, Hideaki, Ooshima, Nobuharu, Motegi, Mitsuru, Umeda, Akira, Miyagawa, Kazuya, Shimada, Hisato, Endo, Mayu, Ohira, Yoshiyuki, Watanabe, Masafumi, Inoue, Sumito, Igarashi, Akira, Sato, Masamichi, Sagara, Hironori, Tanaka, Akihiko, Ohta, Shin, Kimura, Tomoyuki, Shibata, Yoko, Tanino, Yoshinori, Nikaido, Takefumi, Minemura, Hiroyuki, Sato, Yuki, Yamada, Yuichiro, Hashino, Takuya, Shinoki, Masato, Iwagoe, Hajime, Takahashi, Hiroshi, Fujii, Kazuhiko, Kishi, Hiroto, Kanai, Masayuki, Imamura, Tomonori, Yamashita, Tatsuya, Yatomi, Masakiyo, Maeno, Toshitaka, Hayashi, Shinichi, Takahashi, Mai, Kuramochi, Mizuki, Kamimaki, Isamu, Tominaga, Yoshiteru, Ishii, Tomoo, Utsugi, Mitsuyoshi, Ono, Akihiro, Tanaka, Toru, Kashiwada, Takeru, Fujita, Kazue, Saito, Yoshinobu, Seike, Masahiro, Watanabe, Hiroko, Matsuse, Hiroto, Kodaka, Norio, Nakano, Chihiro, Oshio, Takeshi, Hirouchi, Takatomo, Makino, Shohei, Egi, Moritoki, Omae, Yosuke, Nannya, Yasuhito, Ueno, Takafumi, Katayama, Kazuhiko, Ai, Masumi, Fukui, Yoshinori, Kumanogoh, Atsushi, Sato, Toshiro, Hasegawa, Naoki, Tokunaga, Katsushi, Ishii, Makoto, Koike, Ryuji, Kitagawa, Yuko, Kimura, Akinori, Imoto, Seiya, Miyano, Satoru, Ogawa, Seishi, Kanai, Takanori, Fukunaga, Koichi, Takeshima, Yusuke, Tanaka, Kentaro, Koichi Matsuda, Yamanashi, Yuji, Furukawa, Yoichi, Morisaki, Takayuki, Murakami, Yoshinori, Kamatani, Yoichiro, Muto, Kaori, Nagai, Akiko, Nakamura, Yusuke, Obara, Wataru, Yamaji, Ken, Asai, Satoshi, Takahashi, Yasuo, Higashiue, Shinichi, Kobayashi, Shuzo, Yamaguchi, Hiroki, Nagata, Yasunobu, Wakita, Satoshi, Nito, Chikako, Iwasaki, Yu-ki, Murayama, Shigeo, Yoshimori, Kozo, Miki, Yoshio, Obata, Daisuke, Higashiyama, Masahiko, Masumoto, Akihide, Koga, Yoshinobu, Koretsune, Yukihiro, Yata, Tomohiro, Ogawa, Kotaro, Namkoong, Ho, Okuno, Tatsusada, Liu, Boxiang, Matsuda, Koichi, and Mochizuki, Hideki

Published
2024
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9. Mobile element variation contributes to population-specific genome diversification, gene regulation and disease risk

Author

Kojima, Shohei, Koyama, Satoshi, Ka, Mirei, Saito, Yuka, Parrish, Erica H., Endo, Mikiko, Takata, Sadaaki, Mizukoshi, Misaki, Hikino, Keiko, Takeda, Atsushi, Gelinas, Asami F., Heaton, Steven M., Koide, Rie, Kamada, Anselmo J., Noguchi, Michiya, Hamada, Michiaki, Kamatani, Yoichiro, Murakawa, Yasuhiro, Ishigaki, Kazuyoshi, Nakamura, Yukio, Ito, Kaoru, Terao, Chikashi, Momozawa, Yukihide, and Parrish, Nicholas F.

Published
2023
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11. Safety of procuring research tissue during a clinically indicated kidney biopsy from patients with lupus: data from the Accelerating Medicines Partnership RA/SLE Network

Author

Deonaraine, Kristina K, Carlucci, Philip M, Fava, Andrea, Li, Jessica, Wofsy, David, James, Judith A, Putterman, Chaim, Diamond, Betty, Davidson, Anne, Fine, Derek M, Monroy-Trujillo, Jose, Atta, Mohamed G, Haag, Kristin, Rao, Deepak A, Apruzzese, William, Belmont, H Michael, Izmirly, Peter M, Wu, Ming, Connery, Sean, Payan-Schober, Fernanda, Furie, Richard A, Berthier, Celine C, Dall'Era, Maria, Cho, Kerry, Kamen, Diane L, Kalunian, Kenneth, Anolik, Jennifer, Ishimori, Mariko, Weisman, Michael H, Petri, Michelle A, Buyon, Jill P, Goff, Jennifer, Dunn, Patrick, Raychaudhuri, Soumya, Zhang, Fan, Korsunsky, Ilya, Nathan, Aparna, Mears, Joseph, Ishigaki, Kazuyoshi, Xiao, Qian, Millard, Nghia, Weinand, Kathryn, Sakaue, Saori, Utz, PJ, Mao, Rong, Robinson, Bill, Maecker, Holden, Guthridge, Joel, DeJager, Wade, Macwana, Susan, Bridges, Louis, Bykerk, Vivian, Donlin, Laura, Goodman, Susan, DiCarlo, Edward, Smith, Melanie, Lakhanpal, Amit, Sherman, Heather, Singaraju, Anvita, Shakib, Lorien, Ritchlin, Christopher, Boyce, Brendan, Tabechian, Darren, McDavid, Andrew, Rangel-Moreno, Javier, Meednu, Nida, Albrecht, Jen, Brenner, Michael, Lederer, James, Wei, Kevin, Jonsson, A Helena, Simmons, Daimon, Keras, Gregory, Keegan, Joshua, Watts, Gerald, Li, Yuhong, Zhu, Zhu, Chicoine, Adam, Li, Zhihan Jian, McGeachy, Mandy, Firestein, Gary, Boyle, David, Ceponis, Arnold, Gregersen, Peter, Horowitz, Diane, Perlman, Harris, Dominguez, Salina, Cuda, Carla, Mandelin, Arthur, Thakrar, Anjali, Bathon, Joan, Hughes, Laura, Holers, Mike, Seifert, Jennifer, Deane, Kevin, Moreland, Larry, Filer, Andrew, Raza, Karim, Sahbudin, Ilfita, and Pitzalis, Constanino

Subjects
Autoimmune Disease, Patient Safety, Kidney Disease, Lupus, Clinical Research, Renal and urogenital, Arteriovenous Fistula, Biopsy, Hematoma, Humans, Kidney, Lupus Nephritis, United States, lupus nephritis, lupus erythematosus, systemic, autoimmunity, Accelerating Medicines Partnership RA/SLE network
Abstract

In lupus nephritis the pathological diagnosis from tissue retrieved during kidney biopsy drives treatment and management. Despite recent approval of new drugs, complete remission rates remain well under aspirational levels, necessitating identification of new therapeutic targets by greater dissection of the pathways to tissue inflammation and injury. This study assessed the safety of kidney biopsies in patients with SLE enrolled in the Accelerating Medicines Partnership, a consortium formed to molecularly deconstruct nephritis. 475 patients with SLE across 15 clinical sites in the USA consented to obtain tissue for research purposes during a clinically indicated kidney biopsy. Adverse events (AEs) were documented for 30 days following the procedure and were determined to be related or unrelated by all site investigators. Serious AEs were defined according to the National Institutes of Health reporting guidelines. 34 patients (7.2%) experienced a procedure-related AE: 30 with haematoma, 2 with jets, 1 with pain and 1 with an arteriovenous fistula. Eighteen (3.8%) experienced a serious AE requiring hospitalisation; four patients (0.8%) required a blood transfusion related to the kidney biopsy. At one site where the number of cores retrieved during the biopsy was recorded, the mean was 3.4 for those who experienced a related AE (n=9) and 3.07 for those who did not experience any AE (n=140). All related AEs resolved. Procurement of research tissue should be considered feasible, accompanied by a complication risk likely no greater than that incurred for standard clinical purposes. In the quest for targeted treatments personalised based on molecular findings, enhanced diagnostics beyond histology will likely be required.

Published
2021

12. Multimodally profiling memory T cells from a tuberculosis cohort identifies cell state associations with demographics, environment and disease

Author

Nathan, Aparna, Beynor, Jessica I, Baglaenko, Yuriy, Suliman, Sara, Ishigaki, Kazuyoshi, Asgari, Samira, Huang, Chuan-Chin, Luo, Yang, Zhang, Zibiao, Lopez, Kattya, Lindestam Arlehamn, Cecilia S, Ernst, Joel D, Jimenez, Judith, Calderón, Roger I, Lecca, Leonid, Van Rhijn, Ildiko, Moody, D Branch, Murray, Megan B, and Raychaudhuri, Soumya

Subjects
Genetics, Prevention, Tuberculosis, Biodefense, Emerging Infectious Diseases, Rare Diseases, Vaccine Related, Infectious Diseases, Clinical Research, Lung, 2.1 Biological and endogenous factors, Aetiology, Infection, Good Health and Well Being, Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Case-Control Studies, Child, Disease Progression, Female, Follow-Up Studies, Genetic Predisposition to Disease, Genotyping Techniques, Humans, Immunologic Memory, Male, Middle Aged, Mycobacterium tuberculosis, Peru, RNA-Seq, Sex Factors, Single-Cell Analysis, Socioeconomic Factors, Th17 Cells, Tuberculosis, Pulmonary, Young Adult, Immunology
Abstract

Multimodal T cell profiling can enable more precise characterization of elusive cell states underlying disease. Here, we integrated single-cell RNA and surface protein data from 500,089 memory T cells to define 31 cell states from 259 individuals in a Peruvian tuberculosis (TB) progression cohort. At immune steady state >4 years after infection and disease resolution, we found that, after accounting for significant effects of age, sex, season and genetic ancestry on T cell composition, a polyfunctional type 17 helper T (TH17) cell-like effector state was reduced in abundance and function in individuals who previously progressed from Mycobacterium tuberculosis (M.tb) infection to active TB disease. These cells are capable of responding to M.tb peptides. Deconvoluting this state-uniquely identifiable with multimodal analysis-from public data demonstrated that its depletion may precede and persist beyond active disease. Our study demonstrates the power of integrative multimodal single-cell profiling to define cell states relevant to disease and other traits.

Published
2021

13. Identification of a regulatory pathway governing TRAF1 via an arthritis-associated non-coding variant

Author

Wang, Qiang, Martínez-Bonet, Marta, Kim, Taehyeung, Sparks, Jeffrey A., Ishigaki, Kazuyoshi, Chen, Xiaoting, Sudman, Marc, Aguiar, Vitor, Sim, Sangwan, Hernandez, Marcos Chiñas, Chiu, Darren J., Wactor, Alexandra, Wauford, Brian, Marion, Miranda C., Gutierrez-Arcelus, Maria, Bowes, John, Eyre, Stephen, Nordal, Ellen, Prahalad, Sampath, Rygg, Marite, Videm, Vibeke, Raychaudhuri, Soumya, Weirauch, Matthew T., Langefeld, Carl D., Thompson, Susan D., and Nigrovic, Peter A.

Published
2023
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14. Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants

Author

Aragam, Krishna G., Jiang, Tao, Goel, Anuj, Kanoni, Stavroula, Wolford, Brooke N., Atri, Deepak S., Weeks, Elle M., Wang, Minxian, Hindy, George, Zhou, Wei, Grace, Christopher, Roselli, Carolina, Marston, Nicholas A., Kamanu, Frederick K., Surakka, Ida, Venegas, Loreto Muñoz, Sherliker, Paul, Koyama, Satoshi, Ishigaki, Kazuyoshi, Åsvold, Bjørn O., Brown, Michael R., Brumpton, Ben, de Vries, Paul S., Giannakopoulou, Olga, Giardoglou, Panagiota, Gudbjartsson, Daniel F., Güldener, Ulrich, Haider, Syed M. Ijlal, Helgadottir, Anna, Ibrahim, Maysson, Kastrati, Adnan, Kessler, Thorsten, Kyriakou, Theodosios, Konopka, Tomasz, Li, Ling, Ma, Lijiang, Meitinger, Thomas, Mucha, Sören, Munz, Matthias, Murgia, Federico, Nielsen, Jonas B., Nöthen, Markus M., Pang, Shichao, Reinberger, Tobias, Schnitzler, Gavin, Smedley, Damian, Thorleifsson, Gudmar, von Scheidt, Moritz, Ulirsch, Jacob C., Arnar, David O., Burtt, Noël P., Costanzo, Maria C., Flannick, Jason, Ito, Kaoru, Jang, Dong-Keun, Kamatani, Yoichiro, Khera, Amit V., Komuro, Issei, Kullo, Iftikhar J., Lotta, Luca A., Nelson, Christopher P., Roberts, Robert, Thorgeirsson, Gudmundur, Thorsteinsdottir, Unnur, Webb, Thomas R., Baras, Aris, Björkegren, Johan L. M., Boerwinkle, Eric, Dedoussis, George, Holm, Hilma, Hveem, Kristian, Melander, Olle, Morrison, Alanna C., Orho-Melander, Marju, Rallidis, Loukianos S., Ruusalepp, Arno, Sabatine, Marc S., Stefansson, Kari, Zalloua, Pierre, Ellinor, Patrick T., Farrall, Martin, Danesh, John, Ruff, Christian T., Finucane, Hilary K., Hopewell, Jemma C., Clarke, Robert, Gupta, Rajat M., Erdmann, Jeanette, Samani, Nilesh J., Schunkert, Heribert, Watkins, Hugh, Willer, Cristen J., Deloukas, Panos, Kathiresan, Sekar, and Butterworth, Adam S.

Published
2022
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15. 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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16. Large-scale genome-wide association study of coronary artery disease in genetically diverse populations

Author

Tcheandjieu, Catherine, Zhu, Xiang, Hilliard, Austin T., Clarke, Shoa L., Napolioni, Valerio, Ma, Shining, Lee, Kyung Min, Fang, Huaying, Chen, Fei, Lu, Yingchang, Tsao, Noah L., Raghavan, Sridharan, Koyama, Satoshi, Gorman, Bryan R., Vujkovic, Marijana, Klarin, Derek, Levin, Michael G., Sinnott-Armstrong, Nasa, Wojcik, Genevieve L., Plomondon, Mary E., Maddox, Thomas M., Waldo, Stephen W., Bick, Alexander G., Pyarajan, Saiju, Huang, Jie, Song, Rebecca, Ho, Yuk-Lam, Buyske, Steven, Kooperberg, Charles, Haessler, Jeffrey, Loos, Ruth J. F., Do, Ron, Verbanck, Marie, Chaudhary, Kumardeep, North, Kari E., Avery, Christy L., Graff, Mariaelisa, Haiman, Christopher A., Le Marchand, Loïc, Wilkens, Lynne R., Bis, Joshua C., Leonard, Hampton, Shen, Botong, Lange, Leslie A., Giri, Ayush, Dikilitas, Ozan, Kullo, Iftikhar J., Stanaway, Ian B., Jarvik, Gail P., Gordon, Adam S., Hebbring, Scott, Namjou, Bahram, Kaufman, Kenneth M., Ito, Kaoru, Ishigaki, Kazuyoshi, Kamatani, Yoichiro, Verma, Shefali S., Ritchie, Marylyn D., Kember, Rachel L., Baras, Aris, Lotta, Luca A., Kathiresan, Sekar, Hauser, Elizabeth R., Miller, Donald R., Lee, Jennifer S., Saleheen, Danish, Reaven, Peter D., Cho, Kelly, Gaziano, J. Michael, Natarajan, Pradeep, Huffman, Jennifer E., Voight, Benjamin F., Rader, Daniel J., Chang, Kyong-Mi, Lynch, Julie A., Damrauer, Scott M., Wilson, Peter W. F., Tang, Hua, Sun, Yan V., Tsao, Philip S., O’Donnell, Christopher J., and Assimes, Themistocles L.

Published
2022
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17. Early progression to active tuberculosis is a highly heritable trait driven by 3q23 in Peruvians

Author

Luo, Yang, Suliman, Sara, Asgari, Samira, Amariuta, Tiffany, Baglaenko, Yuriy, Martínez-Bonet, Marta, Ishigaki, Kazuyoshi, Gutierrez-Arcelus, Maria, Calderon, Roger, Lecca, Leonid, León, Segundo R, Jimenez, Judith, Yataco, Rosa, Contreras, Carmen, Galea, Jerome T, Becerra, Mercedes, Nejentsev, Sergey, Nigrovic, Peter A, Moody, D Branch, Murray, Megan B, and Raychaudhuri, Soumya

Subjects
Biological Sciences, Genetics, Prevention, Orphan Drug, Lung, Infectious Diseases, Rare Diseases, Tuberculosis, Vaccine Related, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Infection, Good Health and Well Being, Adult, Disease Progression, Female, Gene Expression, Genetic Loci, Genome-Wide Association Study, Genotype, Humans, Male, Monocytes, Mycobacterium tuberculosis, Peru, Sodium-Potassium-Exchanging ATPase
Abstract

Of the 1.8 billion people worldwide infected with Mycobacterium tuberculosis, 5-15% will develop active tuberculosis (TB). Approximately half will progress to active TB within the first 18 months after infection, presumably because they fail to mount an effective initial immune response. Here, in a genome-wide genetic study of early TB progression, we genotype 4002 active TB cases and their household contacts in Peru. We quantify genetic heritability ([Formula: see text]) of early TB progression to be 21.2% (standard error 0.08). This suggests TB progression has a strong genetic basis, and is comparable to traits with well-established genetic bases. We identify a novel association between early TB progression and variants located in a putative enhancer region on chromosome 3q23 (rs73226617, OR = 1.18; P = 3.93 × 10-8). With in silico and in vitro analyses we identify rs73226617 or rs148722713 as the likely functional variant and ATP1B3 as a potential causal target gene with monocyte specific function.

Published
2019

23. A genome-wide association study identified PTPN2 as a population-specific susceptibility gene locus for primary biliary cholangitis

Author

Hitomi, Yuki, primary, Ueno, Kazuko, additional, Aiba, Yoshihiro, additional, Nishida, Nao, additional, Kono, Michihiro, additional, Sugihara, Mitsuki, additional, Kawai, Yosuke, additional, Kawashima, Minae, additional, Khor, Seik-Soon, additional, Sugi, Kazuhiro, additional, Kouno, Hirotaka, additional, Kouno, Hiroshi, additional, Naganuma, Atsushi, additional, Iwamoto, Satoru, additional, Katsushima, Shinji, additional, Furuta, Kiyoshi, additional, Nikami, Toshiki, additional, Mannami, Tomohiko, additional, Yamashita, Tsutomu, additional, Ario, Keisuke, additional, Komatsu, Tatsuji, additional, Makita, Fujio, additional, Shimada, Masaaki, additional, Hirashima, Noboru, additional, Yokohama, Shiro, additional, Nishimura, Hideo, additional, Sugimoto, Rie, additional, Komura, Takuya, additional, Ota, Hajime, additional, Kojima, Motoyuki, additional, Nakamuta, Makoto, additional, Fujimori, Naoyuki, additional, Yoshizawa, Kaname, additional, Mano, Yutaka, additional, Takahashi, Hironao, additional, Hirooka, Kana, additional, Tsuruta, Satoru, additional, Sato, Takeaki, additional, Yamasaki, Kazumi, additional, Kugiyama, Yuki, additional, Motoyoshi, Yasuhide, additional, Suehiro, Tomoyuki, additional, Saeki, Akira, additional, Matsumoto, Kosuke, additional, Nagaoka, Shinya, additional, Abiru, Seigo, additional, Yatsuhashi, Hiroshi, additional, Ito, Masahiro, additional, Kawata, Kazuhito, additional, Takaki, Akinobu, additional, Arai, Kuniaki, additional, Arinaga, Teruko, additional, Abe, Masanori, additional, Harada, Masaru, additional, Taniai, Makiko, additional, Zeniya, Mikio, additional, Ohira, Hiromasa, additional, Shimoda, Shinji, additional, Komori, Atsumasa, additional, Tanaka, Atsushi, additional, Ishigaki, Kazuyoshi, additional, Nagasaki, Masao, additional, Tokunaga, Katsushi, additional, and Nakamura, Minoru, additional

Published
2024
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24. Long-read sequencing for 29 immune cell subsets reveals disease-linked isoforms

Author

30439244, Inamo, Jun, Suzuki, Akari, Ueda, Mahoko Takahashi, Yamaguchi, Kensuke, Nishida, Hiroshi, Suzuki, Katsuya, Kaneko, Yuko, Takeuchi, Tsutomu, Hatano, Hiroaki, Ishigaki, Kazuyoshi, Ishihama, Yasushi, Yamamoto, Kazuhiko, Kochi, Yuta, 30439244, Inamo, Jun, Suzuki, Akari, Ueda, Mahoko Takahashi, Yamaguchi, Kensuke, Nishida, Hiroshi, Suzuki, Katsuya, Kaneko, Yuko, Takeuchi, Tsutomu, Hatano, Hiroaki, Ishigaki, Kazuyoshi, Ishihama, Yasushi, Yamamoto, Kazuhiko, and Kochi, Yuta

Abstract

Alternative splicing events are a major causal mechanism for complex traits, but they have been understudied due to the limitation of short-read sequencing. Here, we generate a full-length isoform annotation of human immune cells from an individual by long-read sequencing for 29 cell subsets. This contains a number of unannotated transcripts and isoforms such as a read-through transcript of TOMM40-APOE in the Alzheimer’s disease locus. We profile characteristics of isoforms and show that repetitive elements significantly explain the diversity of unannotated isoforms, providing insight into the human genome evolution. In addition, some of the isoforms are expressed in a cell-type specific manner, whose alternative 3’-UTRs usage contributes to their specificity. Further, we identify disease-associated isoforms by isoform switch analysis and by integration of several quantitative trait loci analyses with genome-wide association study data. Our findings will promote the elucidation of the mechanism of complex diseases via alternative splicing.

Published
2024

25. Identification of telomere maintenance gene variations related to lung adenocarcinoma risk by genome‐wide association and whole genome sequencing analyses

Author

Shiraishi, Kouya, Takahashi, Atsushi, Momozawa, Yukihide, Daigo, Yataro, Kaneko, Syuzo, Kawaguchi, Takahisa, Kunitoh, Hideo, Matsumoto, Shingo, Horinouchi, Hidehito, Goto, Akiteru, Honda, Takayuki, Shimizu, Kimihiro, Torasawa, Masahiro, Takayanagi, Daisuke, Saito, Motonobu, Saito, Akira, Ohe, Yuichiro, Watanabe, Shun-ichi, Goto, Koichi, Tsuboi, Masahiro, Tsuchihara, Katsuya, Takata, Sadaaki, Aoi, Tomomi, Takano, Atsushi, Kobayashi, Masashi, Miyagi, Yohei, Tanaka, Kazumi, Suzuki, Hiroyuki, Maeda, Daichi, Yamaura, Takumi, Matsuda, Maiko, Shimada, Yoko, Mizuno, Takaaki, Sakamoto, Hiromi, Yoshida, Teruhiko, Goto, Yasushi, Yoshida, Tatsuya, Yamaji, Taiki, Sonobe, Makoto, Toyooka, Shinichi, Yoneda, Kazue, Masago, Katsuhiro, Tanaka, Fumihiro, Hara, Megumi, Fuse, Nobuo, Nishizuka, Satoshi S., Motoi, Noriko, Sawada, Norie, Nishida, Yuichiro, Kumada, Kazuki, Takeuchi, Kenji, Tanno, Kozo, Yatabe, Yasushi, Sunami, Kuniko, Hishida, Tomoyuki, Miyazaki, Yasunari, Ito, Hidemi, Amemiya, Mitsuhiro, Totsuka, Hirohiko, Nakayama, Haruhiko, Yokose, Tomoyuki, Ishigaki, Kazuyoshi, Nagashima, Toshiteru, Ohtaki, Yoichi, Imai, Kazuhiro, Takasawa, Ken, Minamiya, Yoshihiro, Kobayashi, Kazuma, Okubo, Kenichi, Wakai, Kenji, Shimizu, Atsushi, Yamamoto, Masayuki, Iwasaki, Motoki, Matsuda, Koichi, Inazawa, Johji, Shiraishi, Yuichi, Nishikawa, Hiroyoshi, Murakami, Yoshinori, Kubo, Michiaki, Matsuda, Fumihiko, Kamatani, Yoichiro, Hamamoto, Ryuji, Matsuo, Keitaro, Kohno, Takashi, Shiraishi, Kouya, Takahashi, Atsushi, Momozawa, Yukihide, Daigo, Yataro, Kaneko, Syuzo, Kawaguchi, Takahisa, Kunitoh, Hideo, Matsumoto, Shingo, Horinouchi, Hidehito, Goto, Akiteru, Honda, Takayuki, Shimizu, Kimihiro, Torasawa, Masahiro, Takayanagi, Daisuke, Saito, Motonobu, Saito, Akira, Ohe, Yuichiro, Watanabe, Shun-ichi, Goto, Koichi, Tsuboi, Masahiro, Tsuchihara, Katsuya, Takata, Sadaaki, Aoi, Tomomi, Takano, Atsushi, Kobayashi, Masashi, Miyagi, Yohei, Tanaka, Kazumi, Suzuki, Hiroyuki, Maeda, Daichi, Yamaura, Takumi, Matsuda, Maiko, Shimada, Yoko, Mizuno, Takaaki, Sakamoto, Hiromi, Yoshida, Teruhiko, Goto, Yasushi, Yoshida, Tatsuya, Yamaji, Taiki, Sonobe, Makoto, Toyooka, Shinichi, Yoneda, Kazue, Masago, Katsuhiro, Tanaka, Fumihiro, Hara, Megumi, Fuse, Nobuo, Nishizuka, Satoshi S., Motoi, Noriko, Sawada, Norie, Nishida, Yuichiro, Kumada, Kazuki, Takeuchi, Kenji, Tanno, Kozo, Yatabe, Yasushi, Sunami, Kuniko, Hishida, Tomoyuki, Miyazaki, Yasunari, Ito, Hidemi, Amemiya, Mitsuhiro, Totsuka, Hirohiko, Nakayama, Haruhiko, Yokose, Tomoyuki, Ishigaki, Kazuyoshi, Nagashima, Toshiteru, Ohtaki, Yoichi, Imai, Kazuhiro, Takasawa, Ken, Minamiya, Yoshihiro, Kobayashi, Kazuma, Okubo, Kenichi, Wakai, Kenji, Shimizu, Atsushi, Yamamoto, Masayuki, Iwasaki, Motoki, Matsuda, Koichi, Inazawa, Johji, Shiraishi, Yuichi, Nishikawa, Hiroyoshi, Murakami, Yoshinori, Kubo, Michiaki, Matsuda, Fumihiko, Kamatani, Yoichiro, Hamamoto, Ryuji, Matsuo, Keitaro, and Kohno, Takashi

Published
2024

27. Age-associated CD4 + T cells with B cell–promoting functions are regulated by ZEB2 in autoimmunity

Author

Goto, Manaka, primary, Takahashi, Hideyuki, additional, Yoshida, Ryochi, additional, Itamiya, Takahiro, additional, Nakano, Masahiro, additional, Nagafuchi, Yasuo, additional, Harada, Hiroaki, additional, Shimizu, Toshiaki, additional, Maeda, Meiko, additional, Kubota, Akatsuki, additional, Toda, Tatsushi, additional, Hatano, Hiroaki, additional, Sugimori, Yusuke, additional, Kawahata, Kimito, additional, Yamamoto, Kazuhiko, additional, Shoda, Hirofumi, additional, Ishigaki, Kazuyoshi, additional, Ota, Mineto, additional, Okamura, Tomohisa, additional, and Fujio, Keishi, additional

Published
2024
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30. Large-scale genome-wide association study in a Japanese population identifies novel susceptibility loci across different diseases

Author

Ishigaki, Kazuyoshi, Akiyama, Masato, Kanai, Masahiro, Takahashi, Atsushi, Kawakami, Eiryo, Sugishita, Hiroki, Sakaue, Saori, Matoba, Nana, Low, Siew-Kee, Okada, Yukinori, Terao, Chikashi, Amariuta, Tiffany, Gazal, Steven, Kochi, Yuta, Horikoshi, Momoko, Suzuki, Ken, Ito, Kaoru, Koyama, Satoshi, Ozaki, Kouichi, Niida, Shumpei, Sakata, Yasushi, Sakata, Yasuhiko, Kohno, Takashi, Shiraishi, Kouya, Momozawa, Yukihide, Hirata, Makoto, Matsuda, Koichi, Ikeda, Masashi, Iwata, Nakao, Ikegawa, Shiro, Kou, Ikuyo, Tanaka, Toshihiro, Nakagawa, Hidewaki, Suzuki, Akari, Hirota, Tomomitsu, Tamari, Mayumi, Chayama, Kazuaki, Miki, Daiki, Mori, Masaki, Nagayama, Satoshi, Daigo, Yataro, Miki, Yoshio, Katagiri, Toyomasa, Ogawa, Osamu, Obara, Wataru, Ito, Hidemi, Yoshida, Teruhiko, Imoto, Issei, Takahashi, Takashi, Tanikawa, Chizu, Suzuki, Takao, Sinozaki, Nobuaki, Minami, Shiro, Yamaguchi, Hiroki, Asai, Satoshi, Takahashi, Yasuo, Yamaji, Ken, Takahashi, Kazuhisa, Fujioka, Tomoaki, Takata, Ryo, Yanai, Hideki, Masumoto, Akihide, Koretsune, Yukihiro, Kutsumi, Hiromu, Higashiyama, Masahiko, Murayama, Shigeo, Minegishi, Naoko, Suzuki, Kichiya, Tanno, Kozo, Shimizu, Atsushi, Yamaji, Taiki, Iwasaki, Motoki, Sawada, Norie, Uemura, Hirokazu, Tanaka, Keitaro, Naito, Mariko, Sasaki, Makoto, Wakai, Kenji, Tsugane, Shoichiro, Yamamoto, Masayuki, Yamamoto, Kazuhiko, Murakami, Yoshinori, Nakamura, Yusuke, Raychaudhuri, Soumya, Inazawa, Johji, Yamauchi, Toshimasa, Kadowaki, Takashi, Kubo, Michiaki, and Kamatani, Yoichiro

Published
2020
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36. Identification of 28 new susceptibility loci for type 2 diabetes in the Japanese population

Author

Suzuki, Ken, Akiyama, Masato, Ishigaki, Kazuyoshi, Kanai, Masahiro, Hosoe, Jun, Shojima, Nobuhiro, Hozawa, Atsushi, Kadota, Aya, Kuriki, Kiyonori, Naito, Mariko, Tanno, Kozo, Ishigaki, Yasushi, Hirata, Makoto, Matsuda, Koichi, Iwata, Nakao, Ikeda, Masashi, Sawada, Norie, Yamaji, Taiki, Iwasaki, Motoki, Ikegawa, Shiro, Maeda, Shiro, Murakami, Yoshinori, Wakai, Kenji, Tsugane, Shoichiro, Sasaki, Makoto, Yamamoto, Masayuki, Okada, Yukinori, Kubo, Michiaki, Kamatani, Yoichiro, Horikoshi, Momoko, Yamauchi, Toshimasa, and Kadowaki, Takashi

Published
2019
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37. Population-specific reference panel improves imputation quality and enhances locus discovery and fine-mapping

Author

Terao, Chikashi, primary, Flanagan, Jack, additional, Tomizuka, Kohei, additional, Liu, Xiaoxi, additional, Ortega-Reyes, David, additional, Matoba, Nana, additional, Akiyama, Masato, additional, Ishigaki, Kazuyoshi, additional, Ashikawa, Kyota, additional, Takata, Sadaaki, additional, Aoi, Tomomi, additional, Momozawa, Yukihide, additional, Ito, Kaoru, additional, Murakami, Yoshinori, additional, Matsuda, Koichi, additional, Kamatami, Yoichiro, additional, Morris, Andrew, additional, and Horikoshi, Momoko, additional

Published
2023
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38. Multimodal repertoire analysis unveils B cell biology in immune-mediated diseases

Author

Ota, Mineto, primary, Nakano, Masahiro, additional, Nagafuchi, Yasuo, additional, Kobayashi, Satomi, additional, Hatano, Hiroaki, additional, Yoshida, Ryochi, additional, Akutsu, Yuko, additional, Itamiya, Takahiro, additional, Ban, Nobuhiro, additional, Tsuchida, Yumi, additional, Shoda, Hirofumi, additional, Yamamoto, Kazuhiko, additional, Ishigaki, Kazuyoshi, additional, Okamura, Tomohisa, additional, and Fujio, Keishi, additional

Published
2023
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39. Genome-wide association meta-analysis identifies GP2 gene risk variants for pancreatic cancer

Author

Lin, Yingsong, Nakatochi, Masahiro, Hosono, Yasuyuki, Ito, Hidemi, Kamatani, Yoichiro, Inoko, Akihito, Sakamoto, Hiromi, Kinoshita, Fumie, Kobayashi, Yumiko, Ishii, Hiroshi, Ozaka, Masato, Sasaki, Takashi, Matsuyama, Masato, Sasahira, Naoki, Morimoto, Manabu, Kobayashi, Satoshi, Fukushima, Taito, Ueno, Makoto, Ohkawa, Shinichi, Egawa, Naoto, Kuruma, Sawako, Mori, Mitsuru, Nakao, Haruhisa, Adachi, Yasushi, Okuda, Masumi, Osaki, Takako, Kamiya, Shigeru, Wang, Chaochen, Hara, Kazuo, Shimizu, Yasuhiro, Miyamoto, Tatsuo, Hayashi, Yuko, Ebi, Hiromichi, Kohmoto, Tomohiro, Imoto, Issei, Kasugai, Yumiko, Murakami, Yoshinori, Akiyama, Masato, Ishigaki, Kazuyoshi, Matsuda, Koichi, Hirata, Makoto, Shimada, Kazuaki, Okusaka, Takuji, Kawaguchi, Takahisa, Takahashi, Meiko, Watanabe, Yoshiyuki, Kuriki, Kiyonori, Kadota, Aya, Okada, Rieko, Mikami, Haruo, Takezaki, Toshiro, Suzuki, Sadao, Yamaji, Taiki, Iwasaki, Motoki, Sawada, Norie, Goto, Atsushi, Kinoshita, Kengo, Fuse, Nobuo, Katsuoka, Fumiki, Shimizu, Atsushi, Nishizuka, Satoshi S., Tanno, Kozo, Suzuki, Ken, Okada, Yukinori, Horikoshi, Momoko, Yamauchi, Toshimasa, Kadowaki, Takashi, Yu, Herbert, Zhong, Jun, Amundadottir, Laufey T., Doki, Yuichiro, Ishii, Hideshi, Eguchi, Hidetoshi, Bogumil, David, Haiman, Christopher A., Le Marchand, Loic, Mori, Masaki, Risch, Harvey, Setiawan, Veronica W., Tsugane, Shoichiro, Wakai, Kenji, Yoshida, Teruhiko, Matsuda, Fumihiko, Kubo, Michiaki, Kikuchi, Shogo, and Matsuo, Keitaro

Published
2020
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40. Author Correction: Characterizing rare and low-frequency height-associated variants in the Japanese population

Author

Akiyama, Masato, Ishigaki, Kazuyoshi, Sakaue, Saori, Momozawa, Yukihide, Horikoshi, Momoko, Hirata, Makoto, Matsuda, Koichi, Ikegawa, Shiro, Takahashi, Atsushi, Kanai, Masahiro, Suzuki, Sadao, Matsui, Daisuke, Naito, Mariko, Yamaji, Taiki, Iwasaki, Motoki, Sawada, Norie, Tanno, Kozo, Sasaki, Makoto, Hozawa, Atsushi, Minegishi, Naoko, Wakai, Kenji, Tsugane, Shoichiro, Shimizu, Atsushi, Yamamoto, Masayuki, Okada, Yukinori, Murakami, Yoshinori, Kubo, Michiaki, and Kamatani, Yoichiro

Published
2020
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41. Age-associated CD4+ T cells with B cell–promoting functions are regulated by ZEB2 in autoimmunity.

Author

Goto, Manaka, Takahashi, Hideyuki, Yoshida, Ryochi, Itamiya, Takahiro, Nakano, Masahiro, Nagafuchi, Yasuo, Harada, Hiroaki, Shimizu, Toshiaki, Maeda, Meiko, Kubota, Akatsuki, Toda, Tatsushi, Hatano, Hiroaki, Sugimori, Yusuke, Kawahata, Kimito, Yamamoto, Kazuhiko, Shoda, Hirofumi, Ishigaki, Kazuyoshi, Ota, Mineto, Okamura, Tomohisa, and Fujio, Keishi

Subjects
T cells, B cells, SYSTEMIC lupus erythematosus, IMMUNOLOGIC memory, AUTOIMMUNITY
Abstract

Aging is a significant risk factor for autoimmunity, and many autoimmune diseases tend to onset during adulthood. We conducted an extensive analysis of CD4+ T cell subsets from 354 patients with autoimmune disease and healthy controls via flow cytometry and bulk RNA sequencing. As a result, we identified a distinct CXCR3midCD4+ effector memory T cell subset that expands with age, which we designated "age-associated T helper (THA) cells." THA cells exhibited both a cytotoxic phenotype and B cell helper functions, and these features were regulated by the transcription factor ZEB2. Consistent with the highly skewed T cell receptor usage of THA cells, gene expression in THA cells from patients with systemic lupus erythematosus reflected disease activity and was affected by treatment with a calcineurin inhibitor. Moreover, analysis of single-cell RNA sequencing data revealed that THA cells infiltrate damaged organs in patients with autoimmune diseases. Together, our characterization of THA cells may facilitate improved understanding of the relationship between aging and autoimmune diseases. Editor's summary: Pathological CD4+ T cell responses contribute to the development of autoimmunity, but whether their age-related changes affect autoimmune disease susceptibility remains unclear. By analyzing a cohort of 354 patients with autoimmune disease, Goto et al. identified a population of peripheral blood CXCR3midCD4+ T cells that is expanded during aging and conditions such as systemic lupus erythematosus (SLE) and rheumatoid arthritis. These age-associated helper T (THA) cells promoted antibody production by B cells and were regulated by the transcription factor ZEB2. THA cell gene signatures correlated with SLE disease activity and were observed in target organs, indicating that THA cells may represent a therapeutic target for autoimmune diseases. —Claire Olingy [ABSTRACT FROM AUTHOR]

Published
2024
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42. Identification of a regulatory pathway governing TRAF1 via an arthritis-associated non-coding variant

Author

Wang, Qiang, Martínez-Bonet, Marta, Kim, Taehyeung, Sparks, Jeffrey A., Ishigaki, Kazuyoshi, Chen, Xiaoting, Sudman, Marc, Aguiar, Vitor, Sim, Sangwan, Hernandez, Marcos Chiñas, Chiu, Darren J., Wactor, Alexandra, Wauford, Brian, Marion, Miranda C., Gutierrez-Arcelus, Maria, Bowes, John, Eyre, Stephen, Nordal, Ellen, Prahalad, Sampath, Rygg, Marite, Videm, Vibeke, Raychaudhuri, Soumya, Weirauch, Matthew T., Langefeld, Carl D., Thompson, Susan D., and Nigrovic, Peter A.

Published
2024
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43. Self antigen-driven, undifferentiated memory-phenotype CD4 T lymphocytes can induce mild and systemic inflammation by differentiating into effector and regulatory T cells

Author

Kawajiri, Akihisa, primary, Li, Jing, additional, Yang, Ziying, additional, Koinuma, Keita, additional, Yoon, Hye Jin, additional, Ishii, Minami, additional, Tayama, Shunichi, additional, Sato, Kosuke, additional, Okuyama, Yuko, additional, Harigae, Hideo, additional, Ishii, Naoto, additional, Ishigaki, Kazuyoshi, additional, Zhu, Jinfang (Jeff), additional, Kim, Kwang Soon, additional, and Kawabe, Takeshi, additional

Published
2023
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44. Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants

Author

Aragam, Krishna G, Jiang, Tao, Goel, Anuj, Kanoni, Stavroula, Wolford, Brooke N, Atri, Deepak S, Weeks, Elle M, Wang, Minxian, Hindy, George, Zhou, Wei, Grace, Christopher, Roselli, Carolina, Marston, Nicholas A, Kamanu, Frederick K, Surakka, Ida, Venegas, Loreto Muñoz, Sherliker, Paul, Koyama, Satoshi, Ishigaki, Kazuyoshi, Åsvold, Bjørn O, Brown, Michael R, Brumpton, Ben, De Vries, Paul S, Giannakopoulou, Olga, Giardoglou, Panagiota, Gudbjartsson, Daniel F, Güldener, Ulrich, Haider, Syed M Ijlal, Helgadottir, Anna, Ibrahim, Maysson, Kastrati, Adnan, Kessler, Thorsten, Kyriakou, Theodosios, Konopka, Tomasz, Li, Ling, Ma, Lijiang, Meitinger, Thomas, Mucha, Sören, Munz, Matthias, Murgia, Federico, Nielsen, Jonas B, Nöthen, Markus M, Pang, Shichao, Reinberger, Tobias, Schnitzler, Gavin, Smedley, Damian, Thorleifsson, Gudmar, Von Scheidt, Moritz, Ulirsch, Jacob C, Danesh, John, Arnar, David O, Burtt, Noël P, Costanzo, Maria C, Flannick, Jason, Ito, Kaoru, Jang, Dong-Keun, Kamatani, Yoichiro, Khera, Amit V, Komuro, Issei, Kullo, Iftikhar J, Lotta, Luca A, Nelson, Christopher P, Roberts, Robert, Thorgeirsson, Gudmundur, Thorsteinsdottir, Unnur, Webb, Thomas R, Baras, Aris, Björkegren, Johan LM, Boerwinkle, Eric, Dedoussis, George, Holm, Hilma, Hveem, Kristian, Melander, Olle, Morrison, Alanna C, Orho-Melander, Marju, Rallidis, Loukianos S, Ruusalepp, Arno, Sabatine, Marc S, Stefansson, Kari, Zalloua, Pierre, Ellinor, Patrick T, Farrall, Martin, Ruff, Christian T, Finucane, Hilary K, Hopewell, Jemma C, Clarke, Robert, Gupta, Rajat M, Erdmann, Jeanette, Samani, Nilesh J, Schunkert, Heribert, Watkins, Hugh, Willer, Cristen J, Deloukas, Panos, Kathiresan, Sekar, Butterworth, Adam S, Aragam, Krishna G [0000-0003-3223-9131], Goel, Anuj [0000-0003-2307-4021], Kanoni, Stavroula [0000-0002-1691-9615], Wolford, Brooke N [0000-0003-3153-1552], Atri, Deepak S [0000-0001-8139-5419], Weeks, Elle M [0000-0002-4317-4444], Wang, Minxian [0000-0002-3753-508X], Zhou, Wei [0000-0001-7719-0859], Roselli, Carolina [0000-0001-5267-6756], Kamanu, Frederick K [0000-0001-7208-1047], Koyama, Satoshi [0000-0002-9286-0360], Ishigaki, Kazuyoshi [0000-0003-2881-0657], Åsvold, Bjørn O [0000-0003-3837-2101], Brumpton, Ben [0000-0002-3058-1059], Gudbjartsson, Daniel F [0000-0002-5222-9857], Güldener, Ulrich [0000-0001-5052-8610], Helgadottir, Anna [0000-0002-1806-2467], Kessler, Thorsten [0000-0003-3326-1621], Li, Ling [0000-0002-3280-9475], Mucha, Sören [0000-0002-1647-2526], Munz, Matthias [0000-0002-4728-3357], Murgia, Federico [0000-0002-3608-845X], Pang, Shichao [0000-0002-4111-2864], Smedley, Damian [0000-0002-5836-9850], Thorleifsson, Gudmar [0000-0003-4623-9087], von Scheidt, Moritz [0000-0001-7159-8271], Ulirsch, Jacob C [0000-0002-7947-0827], Costanzo, Maria C [0000-0001-9043-693X], Flannick, Jason [0000-0002-3618-795X], Ito, Kaoru [0000-0003-1843-773X], Khera, Amit V [0000-0001-6535-5839], Komuro, Issei [0000-0002-0714-7182], Kullo, Iftikhar J [0000-0002-6524-3471], Roberts, Robert [0000-0002-6792-4633], Webb, Thomas R [0000-0001-5998-8226], Baras, Aris [0000-0002-6830-3396], Björkegren, Johan LM [0000-0003-1945-7425], Holm, Hilma [0000-0002-9517-6636], Morrison, Alanna C [0000-0001-6381-4296], Orho-Melander, Marju [0000-0002-3578-2503], Stefansson, Kari [0000-0003-1676-864X], Farrall, Martin [0000-0003-4564-2165], Finucane, Hilary K [0000-0003-3864-9828], Clarke, Robert [0000-0002-9802-8241], Erdmann, Jeanette [0000-0002-4486-6231], Samani, Nilesh J [0000-0002-3286-8133], Schunkert, Heribert [0000-0001-6428-3001], Watkins, Hugh [0000-0002-5287-9016], Willer, Cristen J [0000-0001-5645-4966], Kathiresan, Sekar [0000-0002-3711-7101], Butterworth, Adam S [0000-0002-6915-9015], and Apollo - University of Cambridge Repository

Subjects
692/699/75/2, 631/208/205/2138, article, Humans, Coronary Artery Disease, Genome-Wide Association Study
Abstract

Funder: K.G.A. has received support from the American Heart Association Institute for Precision Cardiovascular Medicine (17IFUNP3384001), a KL2/Catalyst Medical Research Investigator Training (CMeRIT) award from the Harvard Catalyst (KL2 TR002542), and the NIH (1K08HL153937)., Funder: B.N.W is supported by the National Science Foundation Graduate Research Program (DGE 1256260)., Funder: I.S. is supported by a Precision Health Scholars Award from the University of Michigan Medical School., Funder: I.K., S.Ko., and K.It. are funded by the Japan Agency for Medical Research and Development, AMED, under Grant Numbers JP16ek0109070h0003, JP18kk0205008h0003, JP18kk0205001s0703, JP20km0405209, and JP20ek0109487. The BioBank Japan is supported by AMED under Grant Number JP20km0605001., Funder: J.L.M.B. acknowledges research support from NIH R01HL125863, American Heart Association (A14SFRN20840000), the Swedish Research Council (2018-02529) and Heart Lung Foundation (20170265) and the Foundation Leducq (PlaqueOmics: Novel Roles of Smooth Muscle and Other Matrix Producing Cells in Atherosclerotic Plaque Stability and Rupture, 18CVD02., Funder: P.S.dV was supported by American Heart Association grant number 18CDA34110116 and National Heart, Lung, and Blood Institute grant R01HL146860. The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services (contract numbers HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I and HHSN268201700005I), R01HL087641, R01HL059367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research., Funder: O.G. has received funding from the British Heart Foundation (BHF) (FS/14/66/3129)., Funder: T.K. is supported by the Corona-Foundation (Junior Research Group Translational Cardiovascular Genomics) and the German Research Foundation (DFG) as part of the Sonderforschungsbereich SFB 1123 (B02)., Funder: D.S.A. has received support from a training grant from the NIH (T32HL007604)., Funder: N.P.B., M.C.C., J.F., and D.-K.J. have been funded by the National Institute of Diabetes and Digestive and Kidney Diseases (2UM1DK105554)., Funder: A.V.K. has been funded by 1K08HG010155 from the National Human Genome Research Institute., Funder: C.P.N. and T.R.W received funding from the British Heart Foundation (SP/16/4/32697)., Funder: The Trøndelag Health Study (The HUNT Study) is a collaboration between HUNT Research Centre (Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology), Trøndelag County Council, Central Norway Regional Health Authority, and the Norwegian Institute of Public Health. The K.G. Jebsen Center for Genetic Epidemiology is financed by Stiftelsen Kristian Gerhard Jebsen; Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology; and Central Norway Regional Health Authority. Whole genome sequencing for the HUNT study was funded by HL109946., Funder: O.M. was funded by the Swedish Heart- and Lung Foundation, the Swedish Research Council, the European Research Council ERC-AdG-2019-885003 and Lund University Infrastructure grant ”Malmö population-based cohorts” (STYR 2019/2046)., Funder: This work was supported by the European Commission (HEALTH-F2–2013-601456) and the TriPartite Immunometabolism Consortium [TrIC]- NovoNordisk Foundation (NNF15CC0018486), VIAgenomics (SP/19/2/344612), the British Heart Foundation, a Wellcome Trust core award (M.F., H.W., 203141/Z/16/Z) and support from the NIHR Oxford Biomedical Research Centre. M.F. and H.W. are members of the Oxford BHF Centre of Research Excellence (RE/13/1/30181). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health., Funder: J.D. is a British Heart Foundation Professor, European Research Council Senior Investigator, and National Institute for Health Research (NIHR) Senior Investigator., Funder: J.C.H. acknowledges personal funding from the British Heart Foundation (FS/14/55/30806) and is a member of the Oxford BHF Centre of Research Excellence (RE/13/1/30181)., Funder: R.C. has received funding from the British Heart Foundation and British Heart Foundation Centre of Research Excellence., Funder: This research was supported by BHF (SP/13/2/30111) and conducted using the UK Biobank Resource (application number 9922)., Funder: The GerMIFs gratefully acknowledge the support of the Bavarian State Ministry of Health and Care, furthermore founded this work within its framework of DigiMed Bayern (grant No: DMB-1805-0001), the German Federal Ministry of Education and Research (BMBF) within the framework of ERA-NET on Cardiovascular Disease (Druggable-MI-genes: 01KL1802), within the scheme of target validation (BlockCAD: 16GW0198K), within the framework of the e:Med research and funding concept (AbCD-Net: 01ZX1706C), the British Heart Foundation (BHF)/German Centre of Cardiovascular Research (DZHK)-collaboration (VIAgenomics) and the German Research Foundation (DFG) as part of the Sonderforschungsbereich SFB 1123 (B02) and the Sonderforschungsbereich SFB TRR 267 (B05)., Funder: C.J.W. is funded by NIH grant R35-HL135824., Funder: This work was supported by the British Heart Foundation (BHF) grant RG/14/5/30893 (P.D.) and forms part of the research themes contributing to the translational research portfolios of the Barts Biomedical Research Centre funded by the UK National Institute for Health Research (NIHR)., The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR–Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.

Published
2022
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46. Characterizing rare and low-frequency height-associated variants in the Japanese population

Author

Akiyama, Masato, Ishigaki, Kazuyoshi, Sakaue, Saori, Momozawa, Yukihide, Horikoshi, Momoko, Hirata, Makoto, Matsuda, Koichi, Ikegawa, Shiro, Takahashi, Atsushi, Kanai, Masahiro, Suzuki, Sadao, Matsui, Daisuke, Naito, Mariko, Yamaji, Taiki, Iwasaki, Motoki, Sawada, Norie, Tanno, Kozo, Sasaki, Makoto, Hozawa, Atsushi, Minegishi, Naoko, Wakai, Kenji, Tsugane, Shoichiro, Shimizu, Atsushi, Yamamoto, Masayuki, Okada, Yukinori, Murakami, Yoshinori, Kubo, Michiaki, and Kamatani, Yoichiro

Published
2019
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47. Immunomics analysis of rheumatoid arthritis identified precursor dendritic cells as a key cell subset of treatment resistance

Author

Yamada, Saeko, primary, Nagafuchi, Yasuo, additional, Wang, Min, additional, Ota, Mineto, additional, Hatano, Hiroaki, additional, Takeshima, Yusuke, additional, Okubo, Mai, additional, Kobayashi, Satomi, additional, Sugimori, Yusuke, additional, Masahiro, Nakano, additional, Yoshida, Ryochi, additional, Hanata, Norio, additional, Suwa, Yuichi, additional, Tsuchida, Yumi, additional, Iwasaki, Yukiko, additional, Sumitomo, Shuji, additional, Kubo, Kanae, additional, Shimane, Kenichi, additional, Setoguchi, Keigo, additional, Azuma, Takanori, additional, Kanda, Hiroko, additional, Shoda, Hirofumi, additional, Zhang, Xuan, additional, Yamamoto, Kazuhiko, additional, Ishigaki, Kazuyoshi, additional, Okamura, Tomohisa, additional, and Fujio, Keishi, additional

Published
2023
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49. Immunomics analysis of rheumatoid arthritis identified precursor dendritic cells as a key cell subset of treatment resistance

Author

Yamada, Saeko, primary, Nagafuchi, Yasuo, additional, Wang, Min, additional, Ota, Mineto, additional, Hatano, Hiroaki, additional, Takeshima, Yusuke, additional, Okubo, Mai, additional, Kobayashi, Satomi, additional, Sugimori, Yusuke, additional, Nakano, Masahiro, additional, Yoshida, Ryochi, additional, Hanata, Norio, additional, Suwa, Yuichi, additional, Tsuchida, Yumi, additional, Iwasaki, Yukiko, additional, Sumitomo, Shuji, additional, Kubo, Kanae, additional, Shimane, Kenichi, additional, Setoguchi, Keigo, additional, Azuma, Takanori, additional, Kanda, Hiroko, additional, Shoda, Hirofumi, additional, Zhang, Xuan, additional, Yamamoto, Kazuhiko, additional, Ishigaki, Kazuyoshi, additional, Okamura, Tomohisa, additional, and Fujio, Keishi, additional

Published
2022
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50. Identification of a regulatory pathway governing TRAF1 via an arthritis-associated non-coding variant

Author

Wang, Qiang, primary, Martínez-Bonet, Marta, additional, Kim, Taehyeung, additional, Sparks, Jeffrey A., additional, Ishigaki, Kazuyoshi, additional, Chen, Xiaoting, additional, Sudman, Marc, additional, Aguiar, Vitor, additional, Hernandez, Marcos Chiñas, additional, Wactor, Alexandra, additional, Wauford, Brian, additional, Marion, Miranda C., additional, Gutierrez-Arcelus, Maria, additional, Bowes, John, additional, Eyre, Stephen, additional, Nordal, Ellen, additional, Prahalad, Sampath, additional, Rygg, Marite, additional, Videm, Vibeke, additional, Raychaudhuri, Soumya, additional, Weirauch, Matthew T., additional, Langefeld, Carl D., additional, Thompson, Susan D., additional, and Nigrovic, Peter A., additional

Published
2022
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