Supplementary Material - ars.els-cdn.com€¦ · 20. Department of Pediatrics, Wakayama Medical University, Wakayama, Japan. 21. A list of members and affiliations appears in the

1

Supplementary Material

Common risk variants in NPHS1 and TNFSF15 are associated

with childhood steroid-sensitive nephrotic syndrome

Xiaoyuan Jia, MD, PhD1, 2, 33, Tomohiko Yamamura, MD, PhD3, 33, Rasheed Gbadegesin,

MD4, 33, Michelle T. McNulty, MS5, 6, 33, Kyuyong Song, PhD7, China Nagano, MD3 , Yuki

Hitomi, PhD1, 8, Dongwon Lee, PhD5, 9, 6, Yoshihiro Aiba, PhD10, Seik-Soon Khor, PhD1,2,

Kazuko Ueno, MS1,2, Yosuke Kawai, PhD1,2, Masao Nagasaki, PhD11, 12, Eisei Noiri, MD,

PhD13, 2, Tomoko Horinouchi, MD, PhD3, Hiroshi Kaito, MD, PhD3, 14, Riku Hamada, MD15,

Takayuki Okamoto, MD, PhD16, Koichi Kamei, MD, PhD17, Yoshitsugu Kaku, MD, PhD18,

Rika Fujimaru, MD19, Ryojiro Tanaka, MD, PhD14, Yuko Shima, MD, PhD20, The Research

Consortium on Genetics of Childhood Idiopathic Nephrotic Syndrome in Japan21, Jiwon

Baek, MS7, Hee Gyung Kang, MD, PhD22, Il-Soo Ha, MD, PhD 22, Kyoung Hee Han, MD,

PhD23, Eun Mi Yang, MD, PhD24, Korean Consortium of Hereditary Renal Diseases in

Children21, Asiri Abeyagunawardena, MBBS4, Brandon Lane, PhD4, Megan Chryst-Stangl,

MS4, Christopher Esezobor, MBBS25, Adaobi Solarin, MBBS26, Midwest Pediatric

Nephrology Consortium (Genetics of nephrotic syndrome study group)21, Claire Dossier,

MD21, 27, Georges Deschênes, MD, PhD21, 27, 28, NEPHROVIR21, Marina Vivarelli, MD29,

Hanna Debiec, PhD30, Kenji Ishikura, MD, PhD17, 31, Masafumi Matsuo, MD, PhD32, Kandai

Nozu, MD, PhD3, Pierre Ronco, MD, PhD30, Hae Il Cheong, MD, PhD 22, Matthew G.

Sampson, MD, MSCE5, 9, 6, Katsushi Tokunaga, PhD1, 2*, Kazumoto Iijima, MD, PhD3*

1. Department of Human Genetics, Graduate School of Medicine, The University of

Tokyo, Tokyo, Japan. 2. Present address: Genome Medical Science Project (Toyama), National Center for

Global Health and Medicine (NCGM), Tokyo, Japan. 3. Department of Pediatrics, Kobe University Graduate School of Medicine, Kobe, Japan. 4. Division of Nephrology, Departments of Pediatrics, Duke University Medical Center,

Durham, NC, USA. 5. Department of Medicine-Nephrology, Boston Children’s Hospital, Boston, MA, USA. 6. Broad Institute, Cambridge, MA, USA. 7. Department of Biochemistry and Molecular Biology, University of Ulsan College of

Medicine, Seoul, Korea. 8. Present address: Department of Microbiology, Hoshi University School of Pharmacy

and Pharmaceutical Sciences, Tokyo, Japan. 9. Harvard Medical School, Boston, MA, USA 10. Clinical Research Center, National Hospital Organization Nagasaki Medical Center,

Omura, Japan.

2

11. Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.

12. Present address: Human Biosciences Unit for the Top Global Course, Center for the Promotion of Interdisciplinary Education and Research (CPIER), Kyoto University, Kyoto, Japan.

13. Department of Hemodialysis and Apheresis, The University of Tokyo Hospital, Tokyo, Japan.

14. Department of Nephrology, Hyogo Prefectural Kobe Children’s Hospital, Kobe, Japan. 15. Department of Nephrology, Tokyo Metropolitan Children’s Medical Center, Tokyo,

Japan. 16. Department of Pediatrics, Hokkaido University Hospital, Sapporo, Japan. 17. Division of Nephrology and Rheumatology, National Center for Child Health and

Development, Tokyo, Japan. 18. Department of Nephrology, Fukuoka Children’s Hospital, Fukuoka, Japan. 19. Department of Pediatrics, Osaka City General Hospital, Osaka, Japan. 20. Department of Pediatrics, Wakayama Medical University, Wakayama, Japan. 21. A list of members and affiliations appears in the Supplementary Note. 22. Department of Pediatrics, Seoul National University Children’s Hospital, Seoul, Korea. 23. Department of Pediatrics, Jeju National University School of Medicine, Jeju, Korea. 24. Department of Pediatrics, Chonnam National University Children’s Hospital, Gwangju,

Korea. 25. Department of Paediatrics, College of Medicine University of Lagos, Lagos, Nigeria. 26. Department of Pediatrics, Lagos State University Teaching Hospital, Ikeja, Nigeria. 27. Department of Paediatric Nephrology, Assistance Publique Hôpitaux de Paris, Hôpital

Robert-Debré, Paris, France. 28. Center of Research on Inflammation, Institut National de la Santé et de la Recherche

Médicale UMR 1149, University Sorbonne-Paris, Paris, France. 29. Division of Nephrology and Dialysis, Bambino Gesù Children’s Hospital and Research

Institute, Rome, Italy. 30. Sorbonne University, INSERM UMR_S1155, and Nephrology and Dialysis Department,

Hopital Tenon, Paris France. 31. Present address: Department of Pediatrics, Kitasato University, Kanagawa, Japan. 32. Research Center for Locomotion Biology, Kobe Gakuin University, Kobe, Japan; KNC

Department of Nucleic Acid Drug Discovery, Faculty of Rehabilitation, Kobe Gakuin University, Kobe, Japan.

33. These authors contributed equally. *Address for correspondence: Kazumoto Iijima, MD, PhD Professor and Chairman Department of Pediatrics, Kobe University Graduate School of Medicine, 5-1 Kusunoki-cho 7 chome, Chuo-ku, Kobe 650-0017, Japan. TEL: +81-78-382-6080, FAX: +81-78-382-6098 e-mail: [email protected] Or Katsushi Tokunaga, PhD Director Genome Medical Science Project (Toyama), National Center for Global Health and Medicine (NCGM), 1-21-1-Toyama, Shinjuku-ku, Tokyo 162-8655, Japan. TEL: 03-3202-7181 (Ext. 2273) e-mail: [email protected]

mailto:[email protected]

mailto:[email protected]

3

Table of contents

1. Supplementary Notes -------------------------------------------------- 4

2. Step-wise conditional analyses in HLA region and HLA fine-

mapping ------------------------------------------------------------------ 10

3. Supplementary Methods ---------------------------------------------- 11

4. Supplementary Tables & Figures* ---------------------------------- 21

(Supplementary Tables S3-S5, S7, S8, S12-S15, S17and S18: See Excel files)

4

Supplementary Notes

The Research Consortium on Genetics of Childhood Idiopathic Nephrotic

Syndrome in Japan

Yoshinori Araki1, Yoshinobu Nagaoka1, Takayuki Okamoto2, Yasuyuki Sato2, Asako

Hayashi2, Toshiyuki Takahashi2, Hayato Aoyagi3, Michihiko Ueno4, Masanori Nakanishi5,

Nariaki Toita6, Kimiaki Uetake7, Norio Kobayashi8, Shoji Fujita9, Kazushi Tsuruga10,

Naonori Kumagai11, 12, Hiroki Kudo11, Eriko Tanaka13, 14, Tae Omori15, Mari Okada16,

Yoshiho Hatai17, Tomohiro Udagawa18, 19, Yaeko Motoyoshi20, Kenji Ishikura21, 62, Koichi

Kamei21, Masao Ogura21, Mai Sato21, Yuji Kano21, 22, Motoshi Hattori23, Kenichiro Miura23,

Yutaka Harita24, Shoichiro Kanda24, Emi Sawanobori25, Anna Kobayashi25, Manabu

Kojika26, Yoko Ohwada27, 28, Kunimasa Yan29, Hiroshi Hataya30, Riku Hamada30, Chikako

Terano30, Ryoko Harada30, Yuko Hamasaki31, Junya Hashimoto31, Shuichi Ito32, Hiroyuki

Machida32, Aya Inaba32, Takeshi Matsuyama33, Miwa Goto34, Masaki Shimizu35, Kazuhide

Ohta36, Yohei Ikezumi37, 38, Takeshi Yamada37, Toshiaki Suzuki39, Soichi Tamamura40,

Yukiko Mori40, Yoshihiko Hidaka41, Daisuke Matsuoka41, Tatsuya Kinoshita42, Shunsuke

Noda43, Masashi Kitahara44, Naoya Fujita45, Satoshi Hibino45, Kazumoto Iijima46, Kandai

Nozu 46, Hiroshi Kaito46, 50, Shogo Minamikawa46, 47, Tomohiko Yamamura46, China

Nagano46, Tomoko Horinouchi46, Keita Nakanishi46, 48, Junya Fujimura46, 49, Nana

Sakakibara46, Yuya Aoto46, Shinya Ishiko46, Ryojiro Tanaka50, Kyoko Kanda50, 51, Yosuke

Inaguma50, Yuya Hashimura52, Shingo Ishimori53, 54, Naohiro Kamiyoshi55, Takayuki

Shibano56, Yasuhiro Takeshima56, Rika Fujimaru57, Hiroaki Ueda57, Akira Ashida58, Hideki

Matsumura58, Takuo Kubota59, Taichi Kitaoka59, 60, Yusuke Okuda61, 62, Toshihiro Sawai61,

Tomoyuki Sakai61, Yuko Shima63, Taketsugu Hama63, Mikiya Fujieda64, Masayuki

Ishihara64, Shigeru Itoh65, Takuma Iwaki66, Maki Shimizu67, Koji Nagatani68, Shoji

Kagami69, Maki Urushihara69, Yoshitsugu Kaku70, Manao Nishimura70, Miwa Yoshino70,

Ken Hatae71, Maiko Hinokiyama71, Rie Kuroki71, Yasufumi Ohtsuka72, Masafumi Oka72,

Shinji Nishimura73, Tadashi Sato74, Seiji Tanaka75, Ayuko Zaitsu75, Hitoshi Nakazato76,

Hiroshi Tamura76, Koichi Nakanishi77

1. Department of Pediatrics, National Hospital Organization Hokkaido Medical Center, Sapporo, Japan

2. Department of Pediatrics, Hokkaido University Hospital, Sapporo, Japan 3. Department of Pediatrics, Obihiro Kyokai Hospital, Obihiro, Japan 4. Department of Pediatrics, Nikko Memorial Hospital, Muroran, Japan 5. Department of Pediatrics, Kushiro Red Cross Hospital, Kushiro, Japan 6. Department of Pediatrics, Sapporo Kosei Hospital, Sapporo, Japan 7. Department of Pediatrics, Obihiro Kosei Hospital, Obihiro, Japan 8. Department of Pediatrics, Oji General Hospital, Tomakomai, Japan 9. Department of Pediatrics, Hakodate Goryoukaku Hospital, Hakodate, Japan

5

10. Department of Pediatrics, Hirosaki University Hospital, Hirosaki, Japan 11. Department of Pediatrics, Tohoku University Graduate School of Medicine, Sendai,

Japan 12. Present address: Department of Pediatrics, Fujita Health University, Toyoake, Japan 13. Department of Pediatrics and Developmental biology, Tokyo Medical and Dental

University, Tokyo, Japan 14. Present address: Department of Pediatrics, Kyorin University Hospital, Tokyo, Japan 15. Department of Peditrics, Tokyo Metropolitan Bokutoh Hospital, Tokyo, Japan 16. Musashino Red Cross Hospital, Musashino, Japan 17. Tokyo Bay Urayasu-Ichikawa Medical Center, Urayasu, Japan 18. Tsuchiura Kyodo General Hospital, Tsuchiura, Japan 19. Present address: Department of Pediatrics and Developmental biology, Tokyo

Medical and Dental University, Tokyo, Japan 20. Department of Pediatrics, Tokyo Kita Medical Center, Tokyo, Japan 21. Division of Nephrology and Rheumatology, National Center for Child Health and

Development, Tokyo, Japan 22. Present address: Department of Pediatrics, Dokkyo Medical University School of

Medicine, Mibu, Japan 23. Department of Pediatric Nephrology,Tokyo Women's Medical University, Tokyo,

Japan 24. Department of Pediatrics, The University of Tokyo Hospital, Tokyo, Japan 25. Department of Pediatrics, Faculty of Medicine, University of Yamanashi, Chuo, Japan 26. Department of Pediatrics, Fujiyoshida Manucipal Hospital, Fujiyoshida, Japan 27. Department of Pediatrics, Dokkyo Medical University School of Medicine, Mibu, Japan 28. Department of Pediatrics,Tochigi Medical Center Shimostuga, Tochigi, Japan 29. Department of Pediatrics, Kyorin University Hospital, Tokyo, Japan 30. Department of Nephrology, Tokyo Metropolitan Children’s Medical Center, Tokyo,

Japan 31. Department of Nephrology, Toho University Faculty of Medicine, Tokyo, Japan 32. Department of Peditrics, Yokohama City University, Yokohama, Japan 33. Department of Pediatrics, Fussa Hospital, Tokyo, Japan 34. Department of Pediatrics, National Hospital Organization Kofu National Hospital,

Kofu, Japan 35. Department of Pediatrics, Kanazawa University Hospital, Kanazawa, Japan 36. Department of Pediatrics, Kanazawa Medical Center, Kanazawa, Japan 37. Department of Pediatrics, Niigata University Medical & Dental Hospital, Niigata,

Japan 38. Present address: Department of Pediatrics, Fujita Health University, Toyoake, Japan 39. Department of Pediatrics, National Hospital Organization Niigata National Hospital,

Niigata 40. Department of Pediatrics, Japanese Red Cross Fukui Hospital, Fukui, Japan 41. Department of Pediatrics, Shinshu University Hospital, Matsumoto, Japan 42. Department of Pediatrics, Ina Central Hospital, Ina, Japan 43. Department of Pediatrics, Nagano Red Cross Hospital, Nagano, Japan 44. Department of Pediatrics, Matsumoto Medical Center, Matsumoto, Japan 45. Department of Pediatric Nephrology, Aichi Children's Health And Medical Center,

Obu, Japan 46. Department of Pediatrics, Kobe University Graduate School of Medicine, Kobe, Japan 47. Present address: Department of General Medicine, Hyogo Prefectural Kobe Children's

Hospital, Kobe, Japan 48. Present address: Department of Pediatrics, Saiseikai Hyogoken Hospital, Kobe, Japan 49. Present address: Department of Pediatrics, Kakogawa Central City Hospital,

Kakogawa, Japan 50. Department of Nephrology, Hyogo Prefectural Kobe Children's Hospital, Kobe, Japan

6

51. Department of Pediatrics, National Hospital Organization Kobe Medical Center 52. Department of Pediatrics, Takatsuki General Hospital, Takatsuki, Japan 53. Department of Pediatrics, Kakogawa Central City Hospital, Kakogawa, Japan 54. Present address: Department of Pediatrics, Takatsuki General Hospital, Takatsuki,

Japan 55. Department of Pediatrics, Himeji Red Cross Hospital, Himeji, Japan 56. Department of Pediatrics, Hyogo College of Medicine, Nishinomiya, Japan 57. Department of Pediatrics, Osaka City General Hospital, Osaka, Japan 58. Department of Pediatrics, Osaka Medical College, Takatsuki, Japan 59. Department of Pediatrics, Osaka Univeristy Graduate School of Medicine, Suita, Japan 60. Present address: Department of Pediatrics, Yodogawa Children Hospital, Osaka,

Japan 61. Department of Pediatrics, Shiga University of Medical Science, Otsu, Japan 62. Present address: Department of Pediatrics, Kitasato Univeristy School of Medicine,

Sagamihara, Japan 63. Department of Pediatrics, Wakayama Medical University, Wakayama, Japan 64. Department of Pediatrics, Kochi Medical School, Kochi University, Nankoku, Japan 65. Department of Pediatrics, Kagawa Prefecture Central Hospital, Takamatsu, Japan 66. Department of Pediatrics, Faculty of Medicine, Kagawa University, Kagawa, Japan 67. Department of Pediatrics, Faculty of Medicine, Kagawa University, Kagawa, Japan 68. Department of Pediatrics, Uwajima City Hospital, Uwajima, Japan 69. Department of Pediatrics, Institute of Biomedical Sciences, Tokushima University

Graduate School, Tokushima, Japan 70. Department of Nephrology, Fukuoka Children’s Hospital, Fukuoka, Japan 71. Department of Pediatrics, Japanese Red Cross Fukuoka Hospital, Fukuoka, Japan 72. Department of Pediatrics, Faculty of Medicine, Saga University, Saga, Japan 73. Department of Pediatrics, Saga-ken Medical Centre Koseikan, Saga, Japan 74. Department of Pediatrics, National Hospital Organization Ureshino Medical Center,

Ureshino, Japan 75. Department of Pediatrics and Child Health, Kurume University School of Medicine,

Kurume, Japan 76. Department of Pediatrics, Faculty of Life Sciences, Kumamoto University, Kumamoto,

Japan 77. Department of Child Health and Welfare (Pediatrics), Graduate School of Medicine,

University of the Ryukyus, Nishihara, Japan

Korean Consortium of Hereditary Renal Diseases in Children

Min Hyun Cho1, Tae-Sun Ha2, Hae Il Cheong3, Hee Gyung Kang3, Il-Soo Ha3, Ji Hyun Kim3,

Peong Gang Park3, Myung Hyun Cho3, Kyoung Hee Han4, Eun Mi Yang5

1. Department of Pediatrics, Kyungpook National University, School of Medicine, Daegu, Korea

2. Department of Pediatrics, Chungbuk National University College of Medicine, Cheongju, Korea

3. Department of Pediatrics, Seoul National University Children’s Hospital, Seoul, Korea 4. Department of Pediatrics, Jeju National University School of Medicine, Jeju, Korea 5. Department of Pediatrics, Chonnam National University Children’s Hospital, Gwangju,

Korea

7

Midwest Pediatric Nephrology Consortium (Genetics of Nephrotic Syndrome study

group)

Alejandro Quiroga1, Asha Moudgil2, Blanche Chavers3, Charles Kwon4, Corinna Bowers5,

Deb Gipson6, Deepa Chand7, Donald Jack Weaver8, Elizabeth Abraham9, Halima Janjua10,

Jen-Jar Lin11, Larry Greenbaum12, Mahmoud Kallash5, Michelle Rheault3, Nilka De Jeus

Gonzalez13, Patrick Brophy14, Rasheed Gbadegesin15, Shashi Nagaraj15, Susan Massengill8,

Tarak Srivastava16, Tray Hunley17, Yi Cai1, Abiodun Omoloja18, Cynthia Silva19,

Adebowale Adeyemo20, Shenal Thalgahagoda21, Jameela A. Kari22, Sherif El Desoky22

1. Division of Nephrology, Helen DeVos Children's Hospital, Grand Rapids, MI, USA 2. Division of Nephrology, Children's National Medical Center, DC, USA 3. Division of Nephrology, Department of Pediatrics, University of Minnesota, MN, USA 4. Division of Nephrology, Department of Pediatrics, Cleveland Clinic, Cleveland, OH,

USA 5. Division of Nephrology, Department of Pediatrics, Nationwide Children's Hospital,

Columbus, OH, USA 6. Division of Nephrology, Department of Pediatrics, University of Michigan Children's

Hospital, Ann Arbor, MI, USA 7. Division of Nephrology, Department of Pediatrics, Akron Children's Hospital, OH, USA 8. Division of Nephrology, Department of Pediatrics, Carolinas Health Care / Levine

Children's Hospital, Charlotte, NC, USA 9. Division of Nephrology, Department of Pediatrics, Saint Louis University / Cardinal

Glennon Children's Medical Center, St Louis, MO, USA 10. Division of Nephrology, Department of Pediatrics, Cleveland Clinic, OH, USA 11. Division of Nephrology, Department of Pediatrics, Wake Forest University, Winston

Salem, NC, USA 12. Division of Nephrology, Department of Pediatrics, Emory University, Atlanta, GA, USA 13. Division of Nephrology, Department of Pediatrics, University of Puerto Rico, San Juan,

Puerto Rico 14. Division of Nephrology, Department of Pediatrics, University of Iowa, IA, USA 15. Division of Nephrology, Department of Pediatrics, Duke University Medical Center,

Durham, NC, USA 16. Division of Nephrology, Department of Pediatrics, Mercy Children's Hospital, Kansas,

MO, USA 17. Division of Nephrology, Department of Pediatrics, Vanderbilt University, Nashville,

TN, USA 18. Division of Nephrology, Department of Pediatrics, Dayton Children's Hospital, OH,

USA 19. Division of Nephrology, Department of Pediatrics, Connecticut Children's Hospital,

New Haven, CT, USA 20. Center for Research on Genomics and Global Health, National Human Genome

Research Institute, National Institutes of Health, Bethesda, MD, USA 21. Department of Paediatrics, University of Peradeniya, Peradeniya, Sri Lanka 22. Pediatric Nephrology center of excellence, Department of Pediatrics, King Abdulaziz

University, Jeddah, Saudi Arabia

8

NEPHROVIR

Mohammed Abdelhadi1, Rachida Akil2, Sonia Azib3, Romain Basmaci4, Gregoire Benoist5,

Philippe Bensaid6, Philippe Blanc7, Olivia Boyer8, Julie Bucher9, Anne Chace10, Arnaud

Chalvon11, Marion Cheminee12, Sandrine Chendjou13, Patrick Daoud14, Georges

Deschênes15, 16, Claire Dossier15, Ossam Elias17, Chantal Gagliadone18, Vincent Gajdos19,

Aurélien Galerne20, Evelyne Jacqz Aigrain21, Lydie Joly Sanchez22, Mohamed Khaled23,

Fatima Khelfaoui24, Yacine Laoudi25, Anis Larakeb26, Tarek Limani27, Fouad Mahdi28,

Alexis Mandelcwaijg29, Stephanie Muller30, Kacem Nacer31, Sylvie Nathanson32, Béatrice

Pellegrino33, Isabelle Pharaon34, Véronica Roudault35, Sébastien Rouget36, Marc Saf37,

Tabassom Simon38, Cedric Tahiri39, Tim Ulinski40, Férielle Zenkhri41

1. Service de Pédiatrie, Centre Hospitalier Léon Binet, Provins, france 2. Service de Pédiatrie, Centre Hospitalier Rives de Seine, Neuilly-sur-Seine, France 3. Service de Pédiatrie, Centre Hospitalier René-Dubos, Pontoire, France 4. Service de Pédiatrie, APHP Louis-Mourier - Université de Paris, Colombes, France 5. Service de Pédiatrie, APHP Ambroise-Paré, Boulonge-Billancourt, France 6. Service de Pédiatrie, Centre Hospitalier Victor Dupouy, Argenteuil, France 7. Service de Pédiatrie, Centre Hospitalier Poissy Saint Germain, Poissy, France 8. Service de Néphrologie Pédiatrique, APHP Necker-Enfants-Malades - Université de

Paris, Paris, France 9. Service de Pédiatrie, Groupe Hospitalier Nord Essonne, Longjumeau, France 10. Service de Pédiatrie, Centre Hospitalier Intercommunal de Villeneuve Saint-Georges,

Villeneuve Saint-Georges, France 11. Service de Pédiatrie, Grand Hôpital de l'Est Francilien, Jossigny, France 12. Service de Pédiatrie, Groupe Hospitalier Nord Essonne, Orsay, France 13. Service de Pédiatrie, Centre Hospitalier des Portes de l’Oise, Beaumont sur Oise,

France 14. Service de Pédiatrie, Centre Hospitalier Intercommunal André-Grégoire, Montreuil,

France 15. Department of Paediatric Nephrology, Assistance Publique Hôpitaux de Paris, Hôpital

Robert-Debré, Paris, France 16. Center of Research on Inflammation, Institut National de la Santé et de la Recherche

Médicale UMR 1149, University Sorbonne-Paris, Paris, France 17. Service de Pédiatrie, Centre Hospitalier de Gonesse, Gonesse, France 18. Service de Pédiatrie, Centre Hospitalier Franco-Britannique, Levallois, France 19. Service de Pédiatrie, APHP Antoine-Béclère, Université Paris Sud, Clamart, France 20. Service de Pédiatrie, APHP Jean-Verdier - Université Paris XIII, Bondy, France 21. Laboratoire de Pharmacogénétique, APHP Robert-Debré, France 22. Service de Pédiatrie, Centre Hospitalier Marc Jacquet, Melun, France 23. Service de Pédiatrie, Groupe Hospitalier Intercommunal Le Raincy Montfermeil,

Montfermeil, France 24. Service de Pédiatrie, Centre Hospitalier Saint-Camille, Bry-sur-Marne, France 25. Service de Pédiatrie, Centre Hospitalier Intercommunal Robert-Ballanger, Aulnay-

Sous-Bois, France 26. Service de Pédiatrie, Grand Hôpital de l'Est Francilien, Meaux, France 27. Service de Pédiatrie, Centre Hospitalier Sud Seine-et-Marne, Montereau-Fault-Yonne,

France 28. Service de Pédiatrie, Centre Hospitalier Intercommunal de Creteil, Creteil, France

9

29. Service de Pédiatrie, Centre Hospitalier Delafontaine, Saint-Denis, France 30. Service de Pédiatrie, Centre Hospitalier de Rambouillet, Rambouillet, France 31. Service de Pédiatrie, Grand Hôpital de l'Est Francilien , Coulommiers, France 32. Service de Pédiatrie, Centre Hospitalier André Mignot, Le Chesnay, France 33. Service de Pédiatrie, Centre Hospitalier François- Quesnay, Mantes-la-Jolie, France 34. Service de Pédiatrie, Centre Hospitalier d'Eaubonne Montmorency, Montmorency,

France 35. Service de Pédiatrie, Centre Hospitalier Sud Seine-et-Marne, Fontainebleau, France 36. Service de Pédiatrie, Centre Hospitalier Sud Francilien, Corbeil, France 37. Service de Pédiatrie, Centre Hospitalier d'Arpajon, Arpajon, France 38. Unité de Recherche Clinique de l'Est Parisien, APHP Saint-Antoine, Paris, France 39. Service de Pédiatrie, Centre Hospitalier Sud Essonne, Dourdan, France 40. Service de Néphrologie Pédiatrique, APHP Armand-Trousseau - Sorbonne Université,

Paris, France 41. Service de Pédiatrie, APHP Bicêtre, Le Kremlin-Bicêtre, France

10

Step-wise conditional analyses in HLA region and HLA fine-mapping

Step-wise conditional analyses were conducted including 21,912 SNVs/INDELs

within the HLA region (Hg19: chr6: 29,640,147–33,115,544 bp). The HLA class II region

exhibited the most significant association and the HLA class I region showed

independent but moderate significance after conditioning on top SNPs (Supplementary

Figure S9A-G, Supplementary Table S9).

HLA fine-mapping was performed in the discovery sample set by imputing

classical HLA genes (HLA-A, -C, -B, -DRB1, -DQB1, -DPA1 and -DPB1). Overall, 870 cases

and 2,903 controls passed the post-imputation QC (call threshold >0.4).

Significantly associated HLA alleles were identified in six HLA genes except for

HLA-DPA1 (Supplementary Tables S11-S13). HLA haplotypes were generated and

association analyses were conducted (Supplementary Table S10, Supplementary Tables

S14–S19). As we emphasized in our previous workS1, HLA-DRB1*08:02-DQB1*03:02 was

the most significant susceptibility haplotype (Pc=1.16E-22, OR=3.38), with a more

significant and stronger association than HLA-DRB1*08:02 (Pc=2.60E-22, OR=2.66) or

HLA-DQB1*03:02 (Pc=2.59E-10, OR=1.71) alone. HLA-DRB1*13:02-DQB1*06:04 was the

most significant protective haplotype (Pc=1.63E-16, OR=0.18). One individual in the

case group (1/870=0.11%) and 15 healthy controls (15/2,903=0.52%) were

heterozygotes for HLA-DRB1*08:02-DQB1*03:02 and HLA-DRB1*13:02-DQB1*06:04,

suggesting a dominant effect of the protective haplotype over the susceptibility

haplotype although the difference was not statistically significant (P=0.14,

Supplementary Table S20).

Reference

S1. Jia X, Horinouchi T, Hitomi Y, et al. Strong Association of the HLA-DR/DQ Locus with

Childhood Steroid-Sensitive Nephrotic Syndrome in the Japanese Population. J Am

Soc Nephrol. 2018;29:2189-2199. doi: 10.1681/ASN.2017080859.

11

Supplementary Methods

Samples and clinical data

In the discovery stage, 1,018 Japanese patients diagnosed as childhood SSNS

were recruited from 67 hospitals throughout Japan. Clinical data for the patients were

collected using a simple questionnaire. Genomic DNA was extracted from peripheral

blood following a standard protocol.

Overall, 3,331 Japanese healthy adults (>18 years) who passed childhood

without disease onset were recruited as controls; 419 healthy adults were collected

from Tokyo, Japan (Tokyo Healthy Control, THC), referred by the Department of Human

Genetics, Graduate School of Medicine, The University of Tokyo; 1,857 Japanese adults

were provided by Tohoku Medical Megabank Project (TMM)S2; 384 healthy controls

were provided by PharmaSNP Consortium, Japan; and 671 controls were provided by

Nagasaki Medical Center, Japan.

This study was approved by the Research Ethics Committees of Kobe

University Graduate School of Medicine and the Graduate School of Medicine, The

University of Tokyo, and all collaborating universities and hospitals. All participants

provided written informed consent for participation in this study.

Genotyping and whole-genome imputation in the discovery stage

In the discovery stage, 1,018 patients with childhood SSNS and 3,331 healthy

adult controls were genotyped using the Affymetrix ‘Japonica Array’S3, which was

specially designed for the Japanese population based on the whole-genome sequencing

data of 1,070 healthy Japanese individuals. The 384 controls samples from

PharmaSNPConsortium were genotyped by Japonica Array V2, while the rest of the

samples were genotyped by Japonica Array V1. Genotyping was performed for each SNP

array using Affymetrix Power Tools version 1.17.0 (Thermo Fisher Inc.) according to the

manufacturer’s instructions. All genotyped samples passed the recommended sample

12

QC metric for the AXIOM arrays (dish QC >0.82). We conducted the genotyping of QC

markers as recommend by the manufacturer’s instructions. Nineteen samples (16 and

three samples from Japonica Array V1 and V2, respectively) with an overall call rate

<97% were excluded in this step. The genotyping of all SNPs was then conducted for the

remaining samples and all the samples had an overall call rate ≥97%. Nine controls with

ambiguous sex were excluded. The genotype data were then merged into a single file by

extracting the overlapping SNPs between both SNP arrays. Because most of the SNP

probes designed on Japonica Array V1 and V2 were identical, 6,632,490 SNPs remained

after this process.

For imputation, the clustering plots were classified by the Ps classification

function in the SNPolisher package (Affymetrix Power Tools version 1.17.0 and Axiom

Analysis Suite 4.0). SNPs that were assigned “recommended” by Ps classification were

retained. SNPs with a call rate <99.0%, a MAF <0.5%, non-autosomal SNPs or with an

HWE test result of P<0.0001 in controls were excluded. Prephasing was conducted first

with the SNPs which passed the filtering step with EAGLE (ver. 2.3.2); the options were

–burn 10, –prune 10, and –main 25. Genotype imputation was performed on the phased

genotypes with IMPUTE4S4 (ver. 2.3.1) using a phased reference panel of 2,036 healthy

Japanese individuals (2KJPN panel). For IMPUTE4, the applied options were –Ne 2000, –

k hap 1000, –k 120, –burnin 15, and –iter 50.

After whole-genome imputation, there were 22,049,786 autosomal SNVs and

short INDELs with an info score >0.5. QC was conducted using the following threshold:

individual missing rate <3% (one case and one control were excluded), SNV/INDEL call

rate ≥97% (661,512 SNVs/INDELs were excluded), MAF ≥0.5% (14,598,443

SNVs/INDELs were excluded), and HWE P-value ≥0.0001 in healthy controls (491

SNPs/INDELs were excluded). Identical-by-Descent test was performed and 101

individuals were excluded using a threshold of Pi-hat >0.1875. PCA was performed using

GCTA (Version 1.26.0)S5 for cases, controls, and HapMap Phase III data (113 CEU, 113

13

YRI, 84 CHB, and 86 JPT). Twenty-five individuals were identified as outliers and

excluded (Supplementary Figure S1A-E).

Genome-wide association analyses in the discovery stage

Association analyses were conducted using logistic regression, adjusting for sex

and the first four principal components (PC1 to PC4) by PLINK 1.9. All cluster plots of

genotyped SNPs with P<1E-05 were checked by visual inspection. Regional plots were

checked for each candidate region with suggestive significance (P<1E-05).

Gene-based test and gene-set analysis

Gene-based test and gene-set analysis were performed using GWAS summary

statistics by MAGMA v1.6S6 (implemented through FUMAS7). For gene analysis, a gene-

based P-value was computed for protein-coding genes obtained from Ensembl build 85

by mapping SNPs to genes if SNPs were located within the genes. For the gene set

analysis, the gene set P-value was computed using the gene-based P-value for 4,728

curated gene sets (including canonical pathways) and 6,166 GO terms obtained from

MsigDB v5.2. The Genotype-Tissue Expression (GTEx) databaseS8 and the NephVS eQTL

Browser (NephQTL)S9 were utilized to find eQTLs affecting the expression of various

genes in various tissues and kidney-specific tissues. Variants in the candidate region on

chromosome 19 (Hg19: chr19: 36.2-36.6Mb) with P-values <0.05 were checked.

Validation and replication of candidate SNPs

For technical validation, rs56117924, rs412175, rs2285450, rs404299,

rs34213471 and rs8086340 were genotyped in 224 cases in the discovery sample set

while rs2073901 was genotyped in 96 healthy controls in the discovery sample set by

Taqman assay. Candidate variants were genotyped successfully with a mean

concordance rate of 99.3% (96.8%–100%).

14

An international collaboration was carried out to replicate the detected signals

in multiple populations. Participants in the Korean dataset were recruited from the

South Korea. The MWPNC (Midwest Pediatric Nephrology Consortium) cohort included

181 patients of South Asian ancestry recruited from the USA and Sri Lanka, 158 patients

of African ancestry recruited from the USA and Nigeria, and 63 European and 27

Hispanic patients recruited from the USA. The NEPHROVIR (Children Cohort Nephrosis

and Virus) cohort included 132 European, 56 African and 85 Maghrebian children with

SSNS, which were recruited in the Paris area (Ile-de-France), 2000 European controls

from 3 Cités, and 454 controls from the 1000G African cohort and 261 Moroccan

controls were used as population-matched controls, respectively. The ItSpa (Italian and

Spanish) cohort comprised 112 European patients from Italy and Spain and 552 controls

from the 1000G European cohortS10.

In the Korean dataset, 249 patients were included. Seven of the nine SNPs

(rs56117924, rs2073901, rs412175, rs2285450, rs404299, rs34213471 and

rs8086340) were genotyped by Taqman assay, while the genotypes of rs6478109 and

rs4979462 in the same 249 patients were extracted from existing genotype data by

Axiom Genome-Wide ASI Array. Five candidate SNPs on chromosome 19 (rs56117924,

rs2073901, rs412175, rs2285450 and rs404299) were genotyped in 380 Korean

healthy adult controls, two candidates SNPs on chromosome 18 (rs34213471 and

rs8086340) were genotyped in 665 Korean controls, and individual genotype data of

rs6478109 and rs4979462, which were genotyped in 3,805 Korean controls in a

previous study10, were utilized here. The MWPNC cohort included 181 patients of South

Asian ancestry, 158 patients of African ancestry, 63 European and 27 Hispanic patients.

For the MWPNC cohort, nine candidate SNPs were genotyped by Taqman assay. The

allele counts of candidate variants for South Asians, Europeans, Africans and Hispanics

were obtained from the public databases of Genome Aggregation Database (genomAD,

http://gnomad.broadinstitute.org), ExAC database by Exome Aggregation Consortium

http://gnomad.broadinstitute.org/

15

(http://exac.broadinstitute.org) or “The South Asian Genome” dataset from South Asian

Genomes&Exomes (http://clingen.igib.res.in/sage/) as population-matched controls.

Information of candidate SNPs from the NEPHROVIR (Children Cohort Nephrosis and

Virus) and ItSpa (Italian and Spanish) cohorts in reported trans-ethnic GWAS9 was

utilized as independent replication sample sets.

Whole Genome Sequencing

Whole genome sequencing (WGS, 30x) was performed on 625 samples from

the Nephrotic Syndrome Study Network Consortium (NEPTUNES12) using the Illumina

HiSeq system. Alignment and variant calling was performed using default settings of

GotCloud with the GrCh37 reference of the human genomeS13. We then removed rare

variants (MAF < 0.0001), variants with quality score less than 20, variants with greater

than 10% missing and indels from the resulting VCFs. Finally, we used McCarthy Tools

to remove variants missing or with greater than 0.5 allele frequency difference from the

1,000 Genomes Phase 3 reference panelS14. A total of 531,420 variants on chromosome

19 were phased with Eagle v2.4.1S15 on the Michigan Imputation ServerS16using the

1,000 Genomes Phase 3 reference panelS14. Due to a high recombination hotspot within

NPHS1, we found inconsistent phasing of rs2071347 (NPHS1, exon 26) when comparing

different reference panels and methods, and thus removed it from downstream

analyses. Samples harboring all five chromosome 19 risk alleles (rs56117924,

rs2073901, rs412175, rs2285450 and rs404299) were identified.

RNA-seq

Total RNA from 269 NEPTUNE glomerular biopsies was extracted, and libraries

were prepared using the Clontech SMARTSeq v4 kit. Samples underwent sequencing

using Illumina HiSeq 2500, resulting in 150 bp unstranded, paired-end reads. Reads

found in fastq files underwent quality control filtering and trimming using fastQC,

http://exac.broadinstitute.org/

http://clingen.igib.res.in/sage/

16

fastQScreen, and picardtools (REFs ). Trimmed reads were then aligned to the human

genome (GRCh37) with STAR 2.6.0aS17. Gene quantification (Log2CPM) was calculated

with the edgeR TMM-normalization methodS18. The bam files were subset to NPHS1 and

the surrounding 1KB intergenic region (chr19: 36,315,274-36,343,895). The bam files

were subset to NPHS1 and the surrounding intergenic region (chr19:36,304,201-

36,358,048). Sashimi plots were visually inspected for exon skipping using IGV version

2.7.2S19, S20.

Allele-specific expression (ASE)

The NPHS1 bam files and phased WGS for 241 matched WGS-RNAseq samples

were input into phASERS21 to perform haplotype phasing. Only uniquely mapped

variants with a minimum base quality score of 10 were used. We used phASER to

calculate haplotype-specific expression by summing RNA-seq counts across all

heterozygous SNPs. Samples with less than 20 total reads across NPHS1 were removed.

For the 187 remaining samples, we calculated ASE as |0.5 – (reference reads / total

reads)|. We then compared ASE for samples with and without the risk haplotype with a

Wilcoxon rank-sum test in R. The total reads and number of supporting heterozygous

SNPs varied across samples. Samples with lower power to detect ASE, less than three

heterozygous SNPs or in the bottom 10% of total reads, were nonetheless included for

completeness and are indicated as gray points in corresponding figures.

HLA imputation and HLA genotyping

In the discovery stage, HLA imputation was performed in 987 cases and 3,206

controls to clarify the genome-wide associated signals identified in the HLA region. We

conducted 2-field HLA genotype imputation for seven classical HLA genes in HLA class I

(HLA-A, -C and -B) and class II (HLA-DRB1, -DQB1, -DPA1 and -DPB1) loci using the

“HIBAG” R package. After SNP QC (SNP call rate ≥97%, MAF ≥5%, and HWE P-value

17

≥0.0001 in healthy controls), SNP data for individuals were extracted from an extended

major histocompatibility complex (MHC) region, ranging from 25,759,242 to 33,534,827

bp based on the hg19 position. Our in-house Japanese imputation reference was used for

HLA genotype imputation. We applied post-imputation QC using a call threshold

(CT) >0.4 for each geneS22. Individuals were excluded from subsequent analyses if have

one or more than one gene failed in the post-imputation QC. Overall, 870 cases and

2,903 healthy controls in the discovery stage passed the post-imputation QC and were

kept in association analyses. HLA haplotypes were estimated using BIGDAWG (Bridging

ImmunoGenomic Data-Analysis Workflow Gaps) software version 2S23. HLA

allele/haplotype frequencies were compared between cases and controls. P-values were

calculated using Pearson’s chi-square test or Fisher’s exact test in the presence vs

absence of each HLA allele/haplotype. P-values were corrected for the number of

alleles/haplotypes tested in each analysis (shown as P-corrected). We considered an

association significant when the P-value was <0.05 after correction for multiple

comparisons. Rare HLA alleles/haplotypes with the total counts in cases and controls

<10 were excluded before performing association analyses. HLA alleles/haplotypes with

frequencies <0.5% in cases or controls were excluded from multiple corrections. As

validation, HLA genotyping was performed in 418 controls. The accuracy rate of HLA-

imputation with post-QC (CT>0.4) for the seven imputed genes was 99.2% (96.2%–

100%).

Heritability estimates

We used GCTAS5, S24 (GCTA-LDMS method) to estimate the heritability of

childhood SSNS explained by genome-wide variants, assuming a disease prevalence of

0.016% in the Japanese population. After whole-genome imputation, all variants passed

QC procedure were utilized in the analysis. We calculated segment-based LD scores

using a segment length of 200 kb (with 100 kb overlap between two adjacent segments).

18

To stratify the variants for genetic relationship matrixes (GRMs), we used two LD score

bins (≤ median LD score and > median LD score) and two MAF bins (common variants:

MAFs ≥ 0.05 and uncommon variants: 0.005 ≤ MAFs < 0.05). We then estimated the

GRMs using variants stratified into each group separately. Lastly, we performed

restricted maximum likelihood (REML) analysis using the multiple GRMs. Considering

the established strong association of the HLA region, heritability was calculated without

variants on chromosome 6 using the same criteria. GCTA uses disease prevalence to

transform the estimated heritability from the observed scale to the liability scale;

therefore, we assumed a population prevalence of 0.016% for childhood SSNS.

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21

Supplementary Tables & Figures

(Supplementary Tables S3-S5, S7, S8, S12-S15, S17 and S18: See Excel files)

22

Supplementary Table S1. Definitions of NS.

Nephrotic syndrome Urine protein to creatinine ratio ≥2.0 and serum albumin ≤2.5 g/dl

Complete remission Negative protein on urine dipstick test or urine protein to creatinine ratio 0.2 for 3 consecutive days

Relapse Protein ≥3+ on urine dipstick test for 3 consecutive days

Steroid-sensitive nephrotic syndrome (SSNS) Complete remission within 4-6 weeks after starting 60 mg/m² oral prednisolone per day

Steroid-resistant nephrotic syndrome (SRNS) Persistent proteinuria after 60 mg/m² oral prednisolone per day for 4-6 weeks

Steroid-dependent nephrotic syndrome (SDNS) Two relapses of nephrotic syndrome during the reduction of steroid treatment or within 2 weeks of discontinuation of steroid treatment

Frequently-relapsing nephrotic syndrome (FRNS) ≥2 relapses of nephrotic syndrome within 6 months after initial remission, or ≥4 relapses within any 12-month period

23

Supplementary Table S2. Clinical information of patients in the discovery GWAS and international replication study.

GINS-J: The Research Consortium on Genetics of Childhood Idiopathic Nephrotic Syndrome in Japan. KCHRD: Korean Consortium of Hereditary Renal Diseases in Children. MWPNC: Midwest Pediatric Nephrology Consortium. NEPHROVIR: Children Cohort Nephrosis and Virus. ItSpa: Italian and Spanish cohort.

Study Discovery GWAS

Consortium GINS-J KCHRD ItSpa

Population Japanese Korean South Asian African European Hispanic European Maghrebian African European

N of samples 987 249 181 158 63 27 132 85 56 112

Male 710 198 110 108 35 19 75 62 39 75

Female 277 51 69 50 28 8 57 23 17 37

Unknown 0 0 2 0 0 0 0 0 0 0

Sex ratio, Male/Female 2.6:1 3.9:1 1.6:1 2.1:1 1.3:1 2.4:1 1.31:1 2.69:1 2.29:1 2.0:1

Onset age 4.0 4.0 3.0 4.9 4.5 4.0 4.2 3.9 4.5 3.4

(median, range, yr) (0.4-17.9) (0.8-17.2) (1.0-19.0) (1.0-17.2) (1.0-16.0) (1.5-14.0) (1.1-15.0) (1.4-15.2) (1.6-13.7) (2.5-5.0)

Replication

MWPNC NEPHROVIR

24

Supplementary Table S6. Significant gene sets with P-values < 0.05 after Bonferroni correction in gene-set analysis by MAGMA.

Gene Set Number of genes Beta Standard error P P-Bonferroni

GO_cc: go MHC class II protein complex 14 1.50 0.29 1.14E-07 1.22E-03

GO_mf: go MHC class II receptor activity 10 1.61 0.33 5.78E-07 6.17E-03

GO_cc: go luminal side of membrane 28 0.75 0.16 1.85E-06 1.97E-02

GO_bp: go innate immune response 544 0.17 0.04 1.85E-06 1.97E-02

25

Supplementary Table S9. Step-wise conditional analyses in HLA region.

Analysis Top SNP BP OR P

Logistic regression: sex, PC1-4 adjusted rs6901541 32442261 2.49 2.80E-33

Round 1 Condition on rs6901541 rs9275103 32649386 0.42 1.17E-21

Round 2 Condition on rs6901541 and rs9275103 rs436845 32197736 1.50 1.14E-08

Round 3 Condition on rs6901541, rs9275103 and

rs436845 rs145590657 32426634 2.08 2.22E-07

Round 4 Condition on rs6901541, rs9275103, rs436845

and rs145590657 rs3097670 33046752 0.43 7.26E-07

Round 5 Condition on rs6901541, rs9275103, rs436845,

rs145590657 and rs3097670 rs77806421 31234462 0.61 1.98E-06

Round 6 Condition on rs6901541, rs9275103, rs436845,

rs145590657, rs3097670 and rs77806421 rs3093561 31547474 0.48 1.71E-05 (NS)

SNP: Single nucleotide polymorphism. BP: Physical position (base-pair) according to Hg19. OR: Odds ratio. NS: Not significant. Significant threshold was considered when P<0.05/21,912=2.28E-06.

26

Supplementary Table S10. HLA haplotypes significantly associated with Japanese childhood SSNS in the discovery stage using HLA-imputation data.

HLA haplotypesa Cases (2N=1740) Controls (2N=5806) Chi-squared test

No. % No. % OR (95% CI) P-correctedb

A-B

A*02:06-B*40:06 49 2.8 87 1.5 1.90 (1.31-2.75) 1.13E-02

A*31:01-B*51:01 80 4.6 160 2.8 1.70 (1.28-2.25) 4.79E-03

A*33:03-B*44:03 42 2.4 353 6.1 0.38 (0.27-0.53) 6.69E-08

A-C-B

A*02:06-C*08:01-B*40:06 46 2.6 76 1.3 2.05 (1.38-3.00) 3.67E-03

A*31:01-C*14:02-B*51:01 74 4.3 137 2.4 1.84 (1.36-2.47) 9.00E-04

A*33:03-C*14:03-B*44:03 42 2.4 353 6.1 0.38 (0.27-0.53) 5.83E-08

DRB1-DQB1

DRB1*01:01-DQB1*05:01 68 3.9 352 6.1 0.63 (0.48-0.82) 1.23E-02

DRB1*04:05-DQB1*04:01 251 14.4 667 11.5 1.30 (1.11-1.52) 2.12E-02

DRB1*08:02-DQB1*03:02 127 7.3 132 2.3 3.38 (2.61-4.38) 1.16E-22

DRB1*08:02-DQB1*04:02 59 3.4 116 2.0 1.72 (1.23-2.39) 1.49E-02

DRB1*09:01-DQB1*03:03 330 19.0 906 15.6 1.27 (1.10-1.46) 1.87E-02

DRB1*13:02-DQB1*06:04 22 1.3 380 6.5 0.18 (0.11-0.28) 1.63E-16

DRB1*15:01-DQB1*06:02 52 3.0 478 8.2 0.34 (0.25-0.46) 1.25E-12

DRB1-DQB1-DPB1

DRB1*04:05-DQB1*04:01-DPB1*05:01 181 10.4 405 7.0 1.55 (1.28-1.87) 8.96E-05

DRB1*08:02-DQB1*03:02-DPB1*05:01 75 4.3 110 1.9 2.33 (1.71-3.17) 3.50E-07

DRB1*09:01-DQB1*03:03-DPB1*02:01 139 8.0 314 5.4 1.52 (1.22-1.88) 2.26E-03

DRB1*13:02-DQB1*06:04-DPB1*04:01 13 0.7 251 4.3 0.17 (0.09-0.29) 3.43E-11

DRB1*15:01-DQB1*06:02-DPB1*02:01 16 0.9 230 4.0 0.22 (0.13-0.37) 1.18E-08

DRB1-DQB1-DPA1-DPB1

DRB1*04:05-DQB1*04:01-DPA1*02:02-DPB1*05:01 153 8.8 368 6.3 1.42 (1.16-1.74) 1.23E-02

DRB1*08:02-DQB1*03:02-DPA1*02:02-DPB1*05:01 87 5.0 108 1.9 2.78 (2.06-3.74) 1.38E-11

DRB1*09:01-DQB1*03:03-DPA1*01:03-DPB1*02:01 129 7.4 295 5.1 1.50 (1.20-1.86) 6.51E-03

DRB1*13:02-DQB1*06:04-DPA1*01:03-DPB1*04:01 13 0.7 251 4.3 0.17 (0.09-0.29) 3.32E-11

DRB1*15:01-DQB1*06:02-DPA1*01:03-DPB1*02:01 13 0.7 171 2.9 0.25 (0.13-0.44) 5.71E-06

A-C-B-DRB1-DQB1-DPA1-DPB1

A*24:02-C*12:02-B*52:01-DRB1*15:02-DQB1*06:01-DPA1*02:01-DPB1*09:01

155 8.9 397 6.8 1.33 (1.09-1.62) 3.99E-02

A*33:03-C*14:03-B*44:03-DRB1*13:02-DQB1*06:04-DPA1*01:03-DPB1*04:01

10 0.6 204 3.5 0.16 (0.07-0.30) 1.02E-09

N: Counts of subjects in the case group and control group. 2N: Counts of HLA haplotypes. aHLA Haplotypes: HLA haplotypes where total counts in cases and controls <10 were omitted. Rare HLA haplotypes with frequencies <0.5% in cases or controls were excluded from multiple correction. bP-corrected: P-values for haplotype frequency comparisons between cases and controls using Pearson’s chi-square test and then corrected for multiplicity of testing based on the number of comparisons.

27

Supplementary Table S11. HLA alleles significantly associated with Japanese childhood SSNS in the discovery stage using HLA-imputation data.

HLA allelesa Cases (2N=1740) Controls (2N=5806) Chi-squared test

No. % No. % OR (95% CI) P-correctedb

HLA-A

A*02:06 215 12.4 553 9.5 1.34 (1.13-1.59) 5.50E-03

A*33:03 75 4.3 441 7.6 0.55 (0.42-0.71) 1.72E-05

HLA-C

C*03:04 276 15.9 739 12.7 1.29 (1.11-1.50) 9.33E-03

C*07:02 180 10.3 761 13.1 0.76 (0.64-0.91) 2.66E-02

C*14:02 176 10.1 335 5.8 1.84 (1.51-2.23) 2.99E-09

C*14:03 51 2.9 411 7.1 0.40 (0.29-0.53) 2.93E-09

HLA-B

B*40:02 199 11.4 513 8.8 1.33 (1.11-1.59) 2.26E-02

B*40:06 135 7.8 285 4.9 1.63 (1.31-2.02) 1.08E-04

B*44:03 50 2.9 411 7.1 0.39 (0.28-0.52) 2.64E-09

B*46:01 55 3.2 293 5.0 0.61 (0.45-0.83) 2.01E-02

B*51:01 203 11.7 462 8.0 1.53 (1.28-1.82) 3.37E-05

HLA-DRB1

DRB1*01:01 68 3.9 352 6.1 0.63 (0.48-0.82) 1.11E-02

DRB1*04:05 254 14.6 678 11.7 1.29 (1.10-1.51) 2.21E-02

DRB1*08:02 186 10.7 250 4.3 2.66 (2.17-3.26) 2.60E-22

DRB1*09:01 333 19.1 917 15.8 1.26 (1.09-1.45) 1.90E-02

DRB1*13:02 33 1.9 402 6.9 0.26 (0.18-0.37) 5.64E-14

DRB1*14:54 17 1.0 188 3.2 0.29 (0.17-0.49) 6.84E-06

DRB1*15:01 70 4.0 498 8.6 0.45 (0.34-0.58) 5.09E-09

HLA-DQB1

DQB1*03:01 247 14.2 650 11.2 1.31 (1.12-1.54) 7.64E-03

DQB1*03:02 263 15.1 549 9.5 1.71 (1.45-2.00) 2.59E-10

DQB1*03:03 346 19.9 965 16.6 1.25 (1.08-1.43) 1.78E-02

DQB1*04:01 255 14.7 684 11.8 1.29 (1.10-1.50) 1.59E-02

DQB1*05:01 71 4.1 387 6.7 0.60 (0.45-0.77) 8.20E-04

DQB1*05:03 27 1.6 234 4.0 0.38 (0.24-0.56) 7.64E-06

DQB1*06:02 52 3.0 479 8.3 0.34 (0.25-0.46) 5.71E-13

DQB1*06:04 22 1.3 380 6.5 0.18 (0.11-0.28) 8.51E-17

HLA-DPB1

DPB1*03:01 47 2.7 310 5.3 0.49 (0.35-0.67) 4.90E-05

DPB1*04:01 28 1.6 308 5.3 0.29 (0.19-0.43) 4.98E-10

DPB1*05:01 784 45.1 2295 39.5 1.25 (1.12-1.40) 3.46E-04

DPB1*09:01 208 12.0 540 9.3 1.32 (1.11-1.57) 1.04E-02

N: Counts of subjects in the case group and control group. 2N: Counts of HLA alleles. aHLA alleles: HLA alleles where total counts in cases and controls <10 were omitted. Rare HLA alleles with frequencies <0.5% in cases or controls were excluded from multiple correction. bP-corrected: P-values for allele frequency comparisons between cases and controls using Pearson’s chi-square test and then corrected for multiplicity of testing based on the number of comparisons.

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Supplementary Table S16. Association analysis of HLA-DRB1-DQB1 haplotypes with childhood SSNS in the discovery stage using HLA-imputation data.

HLA haplotypesa Cases (2N=1740) Controls (2N=5806) Chi-square test

No. % No. % OR (95% CI) P-valueb P-correctedc

DRB1*01:01-DQB1*05:01 68 3.9 352 6.1 0.63 (0.48-0.82) 5.84E-04 1.23E-02

DRB1*04:01-DQB1*03:01 12 0.7 58 1.0 0.69 (0.34-1.30) NS -

DRB1*04:03-DQB1*03:02 65 3.7 174 3.0 1.26 (0.92-1.69) NS -

DRB1*04:05-DQB1*04:01 251 14.4 667 11.5 1.30 (1.11-1.52) 1.01E-03 2.12E-02

DRB1*04:06-DQB1*03:02 62 3.6 213 3.7 0.97 (0.72-1.30) NS -

DRB1*08:02-DQB1*03:02 127 7.3 132 2.3 3.38 (2.61-4.38) 5.54E-24 1.16E-22

DRB1*08:02-DQB1*04:02 59 3.4 116 2.0 1.72 (1.23-2.39) 7.09E-04 1.49E-02

DRB1*08:03-DQB1*06:01 135 7.8 479 8.3 0.94 (0.76-1.14) NS -

DRB1*09:01-DQB1*03:03 330 19.0 906 15.6 1.27 (1.10-1.46) 8.91E-04 1.87E-02

DRB1*11:01-DQB1*03:01 54 3.1 135 2.3 1.35 (0.96-1.87) NS -

DRB1*12:01-DQB1*03:01 60 3.4 136 2.3 1.49 (1.07-2.04) 1.10E-02 2.30E-01 (NS)

DRB1*12:01-DQB1*03:03 15 0.9 53 0.9 0.94 (0.49-1.70) NS -

DRB1*12:02-DQB1*03:01 11 0.6 88 1.5 0.41 (0.20-0.78) 4.50E-03 9.45E-02 (NS)

DRB1*13:02-DQB1*06:04 22 1.3 380 6.5 0.18 (0.11-0.28) 7.74E-18 1.63E-16

DRB1*14:03-DQB1*03:01 48 2.8 102 1.8 1.59 (1.10-2.27) 8.64E-03 1.81E-01 (NS)

DRB1*14:05-DQB1*05:03 19 1.1 127 2.2 0.49 (0.29-0.81) 3.62E-03 7.59E-02 (NS)

DRB1*14:06-DQB1*03:01 43 2.5 97 1.7 1.49 (1.01-2.17) 2.99E-02 6.29E-01 (NS)

DRB1*14:54-DQB1*05:02 9 0.5 81 1.4 0.37 (0.16-0.73) 3.09E-03 6.48E-02 (NS)

DRB1*15:01-DQB1*06:02 52 3.0 478 8.2 0.34 (0.25-0.46) 5.96E-14 1.25E-12

DRB1*15:02-DQB1*06:01 220 12.6 590 10.2 1.28 (1.08-1.51) 3.35E-03 7.04E-02 (NS)

DRB1*16:02-DQB1*05:02 12 0.7 49 0.8 0.82 (0.39-1.56) NS -

OR: Odds ratio. CI: Confidence interval. aHLA haplotypes: Rare HLA haplotypes with frequencies <0.5% in cases or controls were excluded from multiple correction. N: Counts of subjects in case group and control group. 2N: Counts of HLA haplotypes. bP-values: P-values for haplotype frequency comparisons between cases and controls using Pearson’s chi-square test or Fisher’s exact test. cP-corrected: P-values were corrected for multiplicity of testing based on the number of comparisons in each haplotype. NS: not significant (P≥0.05). -: The P-value before multiple corrections was not significant (P≥0.05); P-corrected was omitted

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Supplementary Table S19. Association analysis of HLA-A-C-B-DRB1-DQB1-DPA1-DPB1 haplotypes with childhood SSNS in the discovery stage using HLA-imputation data.

HLA haplotypesa

Cases (2N=1740)

Controls (2N=5806)

Chi-square test

No. % No. % OR (95% CI) P-valueb P-correctedc

A*02:07-C*01:02-B*46:01-DRB1*08:03-DQB1*06:01-DPA1*02:02-DPB1*05:01 14 0.8 57 1.0 0.82 (0.42-1.49) NS -




A*24:02-C*07:02-B*07:02-DRB1*01:01-DQB1*05:01-DPA1*01:03-DPB1*04:02 38 2.2 179 3.1 0.70 (0.48-1.01) 4.90E-02 5.39E-01 (NS)



A*24:02-C*12:02-B*52:01-DRB1*15:02-DQB1*06:01-DPA1*02:01-DPB1*09:01 155 8.9 397 6.8 1.33 (1.09-1.62) 3.62E-03 3.99E-02



A*33:03-C*14:03-B*44:03-DRB1*13:02-DQB1*06:04-DPA1*01:03-DPB1*04:01 10 0.6 204 3.5 0.16 (0.07-0.30) 9.30E-11 1.02E-09

OR: Odds ratio. CI: Confidence interval. aHLA haplotypes: Rare HLA haplotypes with frequencies <0.5% in cases or controls were excluded from multiple corrections. N: Counts of subjects in the case group and control group. 2N: Counts of HLA haplotypes. bP-values: P-values for haplotype frequency comparisons between cases and controls using Pearson’s chi-square test or Fisher’s exact test. cP-corrected: P-values were corrected for multiplicity of testing based on the number of comparisons in each haplotype. NS: not significant (P≥0.05). -: The P-value before multiple corrections was not significant (P≥0.05); P-corrected was omitted.

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Supplementary Table S20. Homozygotes of HLA-DRB1*08:02-DQB1*03:02, HLA-DRB1*13:02-DQB1*06:04, and heterozygotes of HLA-DRB1*08:02-DQB1*03:02, HLA-DRB1*13:02-DQB1*06:04 in the discovery stage by HLA-imputation.

Haplotype Cases (N, %) Controls (N/ %) P

DRB1*08:02-DQB1*03:02/DRB1*08:02-DQB1*03:02 1 (0.11%) 3 (0.10%) 1 (NS)

DRB1*08:02-DQB1*03:02/DRB1*13:02-DQB1*06:04 1 (0.11%) 15 (0.52%) 0.14 (NS)

DRB1*13:02-DQB1*06:04/DRB1*13:02-DQB1*06:04 1 (0.11%) 8 (0.28%) 0.42 (NS)

NS: Not significant.

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Supplementary Table S21. Heritability estimation using autosomal variants in discovery Japanese sample set.

Variants Heritability (SE) Common variant (MAF >0.05) Uncommon variant (0.005 < MAF ≤ 0.05)

All variants (observed-scale) 0.411±0.140 0.370 (90%) 0.041 (10%)

All variants (liability-scale) 0.148±0.050 0.133 (90%) 0.015 (10%)

Chromosome 6 excluded (observed-scale) 0.316±0.136 0.279 (88%) 0.037 (12%)

Chromosome 6 excluded (liability-scale) 0.114±0.049 0.100 (88%) 0.014(12%)

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Supplementary Figure S1. Principal component analysis in the discovery GWAS using HapMap Phase III samples as a reference (113 Utah residents with ancestry from northern and western Europe [CEU], 113 Yoruba in Ibadan [YRI], 84 Han Chinese in Beijing [CHB] and 86 Japanese in Tokyo [JPT]).

(A) All samples in the discovery stage with global reference data (CEU, YRI and JPT+CHB): eight outliers were detected.

(B) Remaining samples in the discovery stage with global reference data (CEU, YRI and JPT+CHB): eight outliers were excluded.

(C) Remaining samples in the discovery stage with Asian reference data (JPT and CHB): 17 outliers were detected.

(D) Remaining samples in the discovery stage with Asian reference data (JPT and CHB): 17 outliers were excluded.

(E) 988 cases and 3,207 controls after the removal of 25 outliers based on the results of PCA. (A) (B)

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(C) (D)

(E)

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Supplementary Figure S2. Power of the discovery GWAS. The power of the discovery GWAS (987 cases and 3,206 controls) exceeded 80% to detect uncommon variants (minor allele frequency [MAF] >0.5%) with genotypic relative risk (RR)>6.20, or common alleles (MAF ≥5%) with RR >2.05, or variants with an allele frequency >50% conferring RR >1.48 at a significant P-value threshold of 5E-08 under the additive model.

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Supplementary Figure S3. Quantile-quantile (Q-Q) plot of P-values for SNPs calculated using logistic regression with an adjustment for sex and PC1-4 (987 cases with childhood SSNS and 3,206 healthy controls). The inflation factor, λ, was estimated as 1.048 (A), and decreased to 1.043 when the HLA region (Hg19: chr6: 29,691,116–33,054,976bp) was excluded (B). (A) (B)

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Supplementary Figure S4. Conditional analysis in the candidate locus on chromosome 19. (A) Regional plot of the candidate locus on chromosome 19 (top SNP: rs56117924, P=4.94E-20,

OR=1.90). (B) Regional plot of the same candidate locus, after conditioning on rs56117924 (significant

threshold was considered when P<0.05/890=5.62E-05; no secondary signal was detected in this candidate region).

(A) Regional plot: associations in the discovery stage.

(B) Conditioning on the top SNP rs56117924 (rs117331539, P-condition=7.35E-04).

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OR=0.72). (B) Regional plot of the same candidate locus, after conditioning on rs6478109 (significant threshold

was considered when P<0.05/493=1E-04; no secondary signal was detected in this candidate region).


(B) Conditioning on the top SNP rs6478109 (rs79151619, P-condition=4.83E-03).

0

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rs64781090.2

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117.5 117.55 117.6 117.65 117.7

Position on chr9 (Mb)

Plotted SNPs

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OR=1.38). (B) Regional plot of the same candidate locus, after conditioning on rs34213471 (significant

threshold was considered when P<0.05/1,096=4.56E-05, no secondary signal was detected in this candidate region).


(B) Conditioning on the top SNP rs34213471 (rs80041808, P-codition=7.29E-03)

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Supplementary Figure S7. The location and annotation of 5 SNPs selected for replication in the NPHS1-KIRREL2 region (A). LD structures of the NPHS1-KIRREL2 region in the Japanese population (B) and European population (C). LD structure plots were generated by LDlink, JPT (Japanese in Tokyo) and EUR (European) was used as the LD reference, separately. The SNPs selected for replication were shown in blue boxes.

(A) The location and annotation of 5 SNPs selected for replication in the NPHS1-KIRREL2

region

SNP Position (hg19) Gene Exon/Intron Annotation

rs56117924 19:36334182 NPHS1 Intron 17 Intron variant

rs2073901 19:36334485 NPHS1 Exon 17 Synonymous variant (p.Thr741Thr)

rs412175 19:36342103NPHS1

KIRREL2

Intron 3

Upstream

Intron variant

Upstream variant

rs2285450 19:36342267NPHS1

KIRREL2

Exon 3

Upstream

Synonymous variant (p.Ile98Ile)

Upstream variant

rs404299 19:36349752 KIRREL2 Exon 4 Missense variant (p.Ala170Thr)

rs404299rs412175 rs2285450rs2073901rs56117924

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(B) Japanese (1000 Genome Project, JPT)

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(C) European (1000 Genome Project, CEU)

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Supplementary Figure S8. Manhattan plot of the gene-based test by MAGMA. Overall, 6,834,340 autosomal variants were mapped to 18,644 protein-coding genes and 71 genes achieved genome-wide significance (P<0.05/18,644=2.68E-06).

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Supplementary Figure S9. Stepwise conditional analyses in the HLA region. (A) Logistic regression (B) Conditional analysis: Round 1

(C) Conditional analysis: Round 2 (D) Conditional analysis: Round 3

(E) Conditional analysis: Round 4 (F) Conditional analysis: Round 5

(G) Conditional analysis: Round 6

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Supplementary Figure S10. Estimation of SNP-based heritability in the Japanese population.

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Supplementary Figure S11. Schematic Diagram of Allele-Specific Expression of NPHS1 Both risk and non-risk samples show the same total reads. However, samples harboring the NPHS1 risk haplotype show decreased NPHS1 expression transcribed from the risk haplotype and increased NPHS1 expression transcribed from the wildtype haplotype.

NPHS1

NPHS1 Risk Hap

NPHS1

NPHS1

1/2

1/2

3/10

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10 reads

10 reads

Documents

Supplementary Material - ars.els-cdn.com€¦ · 20. Department of Pediatrics, Wakayama Medical University, Wakayama, Japan. 21. A list of members and affiliations appears in the