Multi-population genome-wide association study implicates immune and non-immune factors in pediatric steroid-sensitive nephrotic syndrome

Alexandra Barry, Michelle T. McNulty, Xiaoyuan Jia, Yask Gupta, Hanna Debiec, Yang Luo, China Nagano, Tomoko Horinouchi, Seulgi Jung, Manuela Colucci, Dina F. Ahram, Adele Mitrotti, Aditi Sinha, Nynke Teeninga, Gina Jin, Shirlee Shril, Gianluca Caridi, Monica Bodria, Tze Y. Lim, Rik WestlandFrancesca Zanoni, Maddalena Marasa, Daniel Turudic, Mario Giordano, Loreto Gesualdo, Riccardo Magistroni, Isabella Pisani, Enrico Fiaccadori, Jana Reiterova, Silvio Maringhini, William Morello, Giovanni Montini, Patricia L. Weng, Francesco Scolari, Marijan Saraga, Velibor Tasic, Domenica Santoro, Joanna A. E. van Wijk, Danko Milošević, Yosuke Kawai, Krzysztof Kiryluk, Martin R. Pollak, Ali Gharavi, Fangmin Lin, Ana Cristina Simœs e Silva, Ruth J. F. Loos, Eimear E. Kenny, Michiel F. Schreuder, Aleksandra Zurowska, Claire Dossier, Gema Ariceta, Magdalena Drozynska-Duklas, Julien Hogan, Augustina Jankauskiene, Friedhelm Hildebrandt, Larisa Prikhodina, Kyuyoung Song, Arvind Bagga, Hae Cheong, Gian Marco Ghiggeri, Prayong Vachvanichsanong, Kandai Nozu, Dongwon Lee, Marina Vivarelli, Soumya Raychaudhuri, Katsushi Tokunaga, Simone Sanna-Cherchi, Pierre Ronco, Kazumoto Iijima, Matthew G. Sampson

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7 Citations (Scopus)


Pediatric steroid-sensitive nephrotic syndrome (pSSNS) is the most common childhood glomerular disease. Previous genome-wide association studies (GWAS) identified a risk locus in the HLA Class II region and three additional independent risk loci. But the genetic architecture of pSSNS, and its genetically driven pathobiology, is largely unknown. Here, we conduct a multi-population GWAS meta-analysis in 38,463 participants (2440 cases). We then conduct conditional analyses and population specific GWAS. We discover twelve significant associations—eight from the multi-population meta-analysis (four novel), two from the multi-population conditional analysis (one novel), and two additional novel loci from the European meta-analysis. Fine-mapping implicates specific amino acid haplotypes in HLA-DQA1 and HLA-DQB1 driving the HLA Class II risk locus. Non-HLA loci colocalize with eQTLs of monocytes and numerous T-cell subsets in independent datasets. Colocalization with kidney eQTLs is lacking but overlap with kidney cell open chromatin suggests an uncharacterized disease mechanism in kidney cells. A polygenic risk score (PRS) associates with earlier disease onset. Altogether, these discoveries expand our knowledge of pSSNS genetic architecture across populations and provide cell-specific insights into its molecular drivers. Evaluating these associations in additional cohorts will refine our understanding of population specificity, heterogeneity, and clinical and molecular associations.
Original languageEnglish
Article number2481
JournalNature communications
Issue number1
Publication statusPublished - 1 Dec 2023

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