BACKGROUND AND OBJECTIVES: At least 20 susceptibility loci of IgA nephropathy have been identified by genome-wide association studies to date. Whether these loci were associated with disease progression is unclear. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We enrolled 613 adult patients with IgA nephropathy for a follow-up of ≥12 months. All 20 IgA nephropathy susceptibility loci were selected and their tag single nucleotide polymorphisms (SNPs) were genotyped. After strict quality control, 16 SNPs and 517 patients with IgA nephropathy were eligible for subsequent analysis. Progression was defined as ESKD or 50% decrease in eGFR. A stepwise Cox regression analysis of all SNPs on Akaike information criterion was performed to select the best model. RESULTS: A four-SNP model, rs11150612 (ITGAM-ITGAX), rs7634389 (ST6GAL1), rs2412971 (HORMAD2), and rs2856717 (HLA-DQ/DR), was selected as the best predictive model. The genetic risk score calculated on the basis of the four SNPs was independently associated with disease progression before (hazard ratio [HR], 1.65; 95% confidence interval [95% CI], 1.29 to 2.12) and after adjustment by a recently reported clinical model (HR, 1.29; 95% CI, 1.03 to 1.62) or clinical-pathologic model (HR, 1.35; 95% CI, 1.03 to 1.77). Compared with low genetic risk, patients with middle genetic risk had a 2.12-fold (95% CI, 1.33 to 3.40) increase of progression risk, whereas patients with high genetic risk had 3.61-fold (95% CI, 2.00 to 6.52) progression risk increase. In addition, incorporation of genetic risk score could potentially increase discrimination of the clinical model (c-statistic increase from 0.83 to 0.86) or the clinical-pathologic model (c-statistic increase from 0.82 to 0.85) in predicting 5-year progression risk. CONCLUSIONS: The four-SNP genetic risk score was independently associated with IgA nephropathy progression and could enhance the performance of clinical and clinical-pathologic risk models.
BACKGROUND AND OBJECTIVES: At least 20 susceptibility loci of IgA nephropathy have been identified by genome-wide association studies to date. Whether these loci were associated with disease progression is unclear. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We enrolled 613 adult patients with IgA nephropathy for a follow-up of ≥12 months. All 20 IgA nephropathy susceptibility loci were selected and their tag single nucleotide polymorphisms (SNPs) were genotyped. After strict quality control, 16 SNPs and 517 patients with IgA nephropathy were eligible for subsequent analysis. Progression was defined as ESKD or 50% decrease in eGFR. A stepwise Cox regression analysis of all SNPs on Akaike information criterion was performed to select the best model. RESULTS: A four-SNP model, rs11150612 (ITGAM-ITGAX), rs7634389 (ST6GAL1), rs2412971 (HORMAD2), and rs2856717 (HLA-DQ/DR), was selected as the best predictive model. The genetic risk score calculated on the basis of the four SNPs was independently associated with disease progression before (hazard ratio [HR], 1.65; 95% confidence interval [95% CI], 1.29 to 2.12) and after adjustment by a recently reported clinical model (HR, 1.29; 95% CI, 1.03 to 1.62) or clinical-pathologic model (HR, 1.35; 95% CI, 1.03 to 1.77). Compared with low genetic risk, patients with middle genetic risk had a 2.12-fold (95% CI, 1.33 to 3.40) increase of progression risk, whereas patients with high genetic risk had 3.61-fold (95% CI, 2.00 to 6.52) progression risk increase. In addition, incorporation of genetic risk score could potentially increase discrimination of the clinical model (c-statistic increase from 0.83 to 0.86) or the clinical-pathologic model (c-statistic increase from 0.82 to 0.85) in predicting 5-year progression risk. CONCLUSIONS: The four-SNP genetic risk score was independently associated with IgA nephropathy progression and could enhance the performance of clinical and clinical-pathologic risk models.
Authors: Andrew D Johnson; Robert E Handsaker; Sara L Pulit; Marcia M Nizzari; Christopher J O'Donnell; Paul I W de Bakker Journal: Bioinformatics Date: 2008-10-30 Impact factor: 6.937
Authors: Sean J Barbour; Gabriela Espino-Hernandez; Heather N Reich; Rosanna Coppo; Ian S D Roberts; John Feehally; Andrew M Herzenberg; Daniel C Cattran Journal: Kidney Int Date: 2016-01 Impact factor: 10.612
Authors: T E Hunley; B A Julian; J A Phillips; M L Summar; H Yoshida; R G Horn; N J Brown; A Fogo; I Ichikawa; V Kon Journal: Kidney Int Date: 1996-02 Impact factor: 10.612
Authors: Ian S D Roberts; H Terence Cook; Stéphan Troyanov; Charles E Alpers; Alessandro Amore; Jonathan Barratt; Francois Berthoux; Stephen Bonsib; Jan A Bruijn; Daniel C Cattran; Rosanna Coppo; Vivette D'Agati; Giuseppe D'Amico; Steven Emancipator; Francesco Emma; John Feehally; Franco Ferrario; Fernando C Fervenza; Sandrine Florquin; Agnes Fogo; Colin C Geddes; Hermann-Josef Groene; Mark Haas; Andrew M Herzenberg; Prue A Hill; Ronald J Hogg; Stephen I Hsu; J Charles Jennette; Kensuke Joh; Bruce A Julian; Tetsuya Kawamura; Fernand M Lai; Lei-Shi Li; Philip K T Li; Zhi-Hong Liu; Bruce Mackinnon; Sergio Mezzano; F Paolo Schena; Yasuhiko Tomino; Patrick D Walker; Haiyan Wang; Jan J Weening; Nori Yoshikawa; Hong Zhang Journal: Kidney Int Date: 2009-07-01 Impact factor: 10.612
Authors: Lukasz Wojtasz; Katrin Daniel; Ignasi Roig; Ewelina Bolcun-Filas; Huiling Xu; Verawan Boonsanay; Christian R Eckmann; Howard J Cooke; Maria Jasin; Scott Keeney; Michael J McKay; Attila Toth Journal: PLoS Genet Date: 2009-10-23 Impact factor: 5.917