Schulz Christina-Alexandra, Engström Gunnar, Christensson Anders, Nilsson Peter M, Melander Olle, Orho-Melander Marju
Department of Clinical Sciences, Lund University, Malmö, Sweden.
Department of Nephrology, Lund University, Malmo, Sweden.
Kidney Int Rep. 2019 May 16;4(8):1143-1151. doi: 10.1016/j.ekir.2019.05.003. eCollection 2019 Aug.
Genome-wide association studies (GWAS) have identified >50 single nucleotide polymorphisms (SNP) in association with estimated glomerular filtration rate (eGFR) and chronic kidney disease (CKD) but little is known about whether the combination of these SNPs may aid in prediction of future incidence of CKD in the population.
We included 2301 participants with baseline eGFR ≥60 mL/min per 1.73 m from the Malmö Diet and Cancer Study-Cardiovascular Cohort. The eGFR was estimated during baseline (1991-1996) and after a mean follow-up of 16.6 years using the CKD-Epidemiology Collaboration 2009 creatinine equation. We combined 53 SNPs into a genetic risk score weighted by the effect size (wGRS), and examined its association with incidence of CKD stage 3A (eGFR ≤60 mL/min per 1.73 m).
At follow-up, 453 study participants were defined as having CKD stage 3A. We observed a strong association between wGRS and eGFR at baseline = 6.5 × 10) and at the follow-up reexamination ( = 5.0 × 10). The odds ratio (OR) for incidence of CKD stage 3A was 1.25 per 1 SD increment in the wGRS (95% confidence interval [CI]: 1.12-1.39) adjusting for potential confounders (sex, age, body mass index [BMI], baseline eGFR, fasting glucose, systolic blood pressure (SBP), antihypertensive treatment, smoking, follow-up time). Adding wGRS on the top of traditional risk factors did not improve the C-statistics ( = 0.12), but the Net Reclassification-Improvement-Index was significantly improved (cNRI = 21.3%; 95% CI: 21.2-21.4; < 0.0001).
wGRS was associated with a 25% increased incidence of CKD per 1 SD increment. Although the wGRS did not improve the prediction model beyond clinical risk factors , the information of genetic predisposition may aid in reclassification of individuals into correct risk direction.
全基因组关联研究（GWAS）已确定超过50个单核苷酸多态性（SNP）与估计肾小球滤过率（eGFR）和慢性肾脏病（CKD）相关，但对于这些SNP的组合是否有助于预测人群中CKD的未来发病率知之甚少。
我们纳入了马尔默饮食与癌症研究-心血管队列中2301名基线eGFR≥60ml/（min·1.73m²）的参与者。在基线期（1991 - 1996年）以及平均随访16.6年后，使用慢性肾脏病流行病学协作组2009年的肌酐方程估算eGFR。我们将53个SNP组合成一个按效应大小加权的遗传风险评分（wGRS），并研究其与3A期CKD（eGFR≤60ml/（min·1.73m²））发病率的关联。
随访时，453名研究参与者被定义为患有3A期CKD。我们观察到基线时wGRS与eGFR之间存在强关联（=6.5×10），随访复查时也存在强关联（=5.0×10）。在调整潜在混杂因素（性别、年龄、体重指数[BMI]、基线eGFR、空腹血糖、收缩压[SBP]、降压治疗、吸烟、随访时间）后，wGRS每增加1个标准差，3A期CKD发病的比值比（OR）为1.25（95%置信区间[CI]：1.12 - 1.39）。在传统危险因素基础上增加wGRS并未改善C统计量（=0.12），但净重新分类改善指数显著提高（cNRI = 21.3%；95%CI：21.2 - 21.4；<0.0001）。
wGRS每增加1个标准差，CKD发病率增加25%。尽管wGRS在临床危险因素之外并未改善预测模型，但遗传易感性信息可能有助于将个体重新分类到正确的风险方向。
