BACKGROUND: Recent genome-wide association studies have identified multiple genetic loci that increase the risk of chronic kidney disease (CKD) in the general population. We hypothesized that knowledge of these loci might permit improved CKD risk prediction beyond that provided by traditional phenotypic risk factors. STUDY DESIGN: Observational cohort study. SETTING & PARTICIPANTS: Participants who attended the 15th (1977-1979) and 24th (1995-1998) examination cycles of the original cohort or the 6th (1995-1998) and 8th cycles (2005-2008) of the offspring cohort of the Framingham Heart Study (n = 2,489). PREDICTORS: Single-nucleotide polymorphisms at 16 stage 3 CKD loci were genotyped and used to construct a genetic risk score. Standard clinical predictors of incident stage 3 CKD also were used. OUTCOMES & MEASUREMENTS: Incident stage 3 CKD was defined as estimated glomerular filtration rate <60 mL/min/1.73 m(2) at follow-up. Participants with baseline stage 3 CKD were excluded. Logistic regression was used to generate C statistics, which measured the power of the genetic risk score to discriminate risk of incident CKD stage 3 with and without traditional risk factors. RESULTS: There were 270 new stage 3 CKD cases during an average of 10.8 years of follow-up. Mean genetic risk score was 17.5 ± 2.8 (SD) for those who developed stage 3 CKD and 17.3 ± 2.6 for those who did not (P for genotype score difference = 0.2). The OR for stage 3 CKD was 1.06 (95% CI, 1.01-1.11; P = 0.03) per additional risk allele, adjusting for age and sex. In the age- and sex-adjusted model, the C statistic was 0.748 without the genotype score and 0.751 with the score (P difference = 0.3). The risk score was not statistically significant in a multivariable model adjusted for standard stage 3 CKD risk factors (P = 0.07). LIMITATIONS: All participants were of European ancestry; the genotype score may not be valid in different ancestral groups. CONCLUSIONS: A genetic score generated from 16 known CKD risk alleles did not predict new cases of stage 3 CKD in the community beyond knowledge of common clinical risk factors alone. Published by Elsevier Inc.
BACKGROUND: Recent genome-wide association studies have identified multiple genetic loci that increase the risk of chronic kidney disease (CKD) in the general population. We hypothesized that knowledge of these loci might permit improved CKD risk prediction beyond that provided by traditional phenotypic risk factors. STUDY DESIGN: Observational cohort study. SETTING & PARTICIPANTS: Participants who attended the 15th (1977-1979) and 24th (1995-1998) examination cycles of the original cohort or the 6th (1995-1998) and 8th cycles (2005-2008) of the offspring cohort of the Framingham Heart Study (n = 2,489). PREDICTORS: Single-nucleotide polymorphisms at 16 stage 3 CKD loci were genotyped and used to construct a genetic risk score. Standard clinical predictors of incident stage 3 CKD also were used. OUTCOMES & MEASUREMENTS: Incident stage 3 CKD was defined as estimated glomerular filtration rate <60 mL/min/1.73 m(2) at follow-up. Participants with baseline stage 3 CKD were excluded. Logistic regression was used to generate C statistics, which measured the power of the genetic risk score to discriminate risk of incident CKD stage 3 with and without traditional risk factors. RESULTS: There were 270 new stage 3 CKD cases during an average of 10.8 years of follow-up. Mean genetic risk score was 17.5 ± 2.8 (SD) for those who developed stage 3 CKD and 17.3 ± 2.6 for those who did not (P for genotype score difference = 0.2). The OR for stage 3 CKD was 1.06 (95% CI, 1.01-1.11; P = 0.03) per additional risk allele, adjusting for age and sex. In the age- and sex-adjusted model, the C statistic was 0.748 without the genotype score and 0.751 with the score (P difference = 0.3). The risk score was not statistically significant in a multivariable model adjusted for standard stage 3 CKD risk factors (P = 0.07). LIMITATIONS: All participants were of European ancestry; the genotype score may not be valid in different ancestral groups. CONCLUSIONS: A genetic score generated from 16 known CKD risk alleles did not predict new cases of stage 3 CKD in the community beyond knowledge of common clinical risk factors alone. Published by Elsevier Inc.
Authors: Nina P Paynter; Daniel I Chasman; Guillaume Paré; Julie E Buring; Nancy R Cook; Joseph P Miletich; Paul M Ridker Journal: JAMA Date: 2010-02-17 Impact factor: 56.272
Authors: Josef Coresh; Elizabeth Selvin; Lesley A Stevens; Jane Manzi; John W Kusek; Paul Eggers; Frederick Van Lente; Andrew S Levey Journal: JAMA Date: 2007-11-07 Impact factor: 56.272
Authors: Abhijit V Kshirsagar; Heejung Bang; Andrew S Bomback; Suma Vupputuri; David A Shoham; Lisa M Kern; Philip J Klemmer; Madhu Mazumdar; Phyllis A August Journal: Arch Intern Med Date: 2008-12-08
Authors: Andrew S Levey; Lesley A Stevens; Christopher H Schmid; Yaping Lucy Zhang; Alejandro F Castro; Harold I Feldman; John W Kusek; Paul Eggers; Frederick Van Lente; Tom Greene; Josef Coresh Journal: Ann Intern Med Date: 2009-05-05 Impact factor: 25.391
Authors: James B Meigs; Peter Shrader; Lisa M Sullivan; Jarred B McAteer; Caroline S Fox; Josée Dupuis; Alisa K Manning; Jose C Florez; Peter W F Wilson; Ralph B D'Agostino; L Adrienne Cupples Journal: N Engl J Med Date: 2008-11-20 Impact factor: 91.245
Authors: Philippa J Talmud; Aroon D Hingorani; Jackie A Cooper; Michael G Marmot; Eric J Brunner; Meena Kumari; Mika Kivimäki; Steve E Humphries Journal: BMJ Date: 2010-01-14
Authors: Conall M O'Seaghdha; Adrienne Tin; Qiong Yang; Ronit Katz; Yongmei Liu; Tamara Harris; Brad Astor; Josef Coresh; Caroline S Fox; W H Linda Kao; Michael G Shlipak Journal: Am J Kidney Dis Date: 2013-08-07 Impact factor: 8.860
Authors: Paolo Fraccaro; Sabine van der Veer; Benjamin Brown; Mattia Prosperi; Donal O'Donoghue; Gary S Collins; Iain Buchan; Niels Peek Journal: BMC Med Date: 2016-07-12 Impact factor: 8.775