Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong; CUHK-SJTU Joint Research Centre in Diabetes Genomics and Precision Medicine, Shatin, New Territories, Hong Kong.
Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.
Kidney Int. 2019 Jan;95(1):178-187. doi: 10.1016/j.kint.2018.08.026. Epub 2018 Nov 8.
Diabetes is a major cause of end stage renal disease (ESRD), yet the natural history of diabetic kidney disease is not well understood. We aimed to identify patterns of estimated GFR (eGFR) trajectory and to determine the clinical and genetic factors and their associations of these different patterns with all-cause mortality in patients with type 2 diabetes. Among 6330 patients with baseline eGFR >60 ml/min per 1.73 m in the Hong Kong Diabetes Register, a total of 456 patients (7.2%) developed Stage 5 chronic kidney disease or ESRD over a median follow-up of 13 years (incidence rate 5.6 per 1000 person-years). Joint latent class modeling was used to identify different patterns of eGFR trajectory. Four distinct and non-linear trajectories of eGFR were identified: slow decline (84.3% of patients), curvilinear decline (6.5%), progressive decline (6.1%) and accelerated decline (3.1%). Microalbuminuria and retinopathy were associated with accelerated eGFR decline, which was itself associated with all-cause mortality (odds ratio [OR] 6.9; 95% confidence interval [CI]: 5.6-8.4 for comparison with slow eGFR decline). Of 68 candidate genetic loci evaluated, the inclusion of five loci (rs11803049, rs911119, rs1933182, rs11123170, and rs889472) improved the prediction of eGFR trajectories (net reclassification improvement 0.232; 95% CI: 0.057--0.406). Our study highlights substantial heterogeneity in the patterns of eGFR decline among patients with diabetic kidney disease, and identifies associated clinical and genetic factors that may help to identify those who are more likely to experience an accelerated decline in kidney function.
糖尿病是终末期肾病(ESRD)的主要原因,但糖尿病肾病的自然史尚不清楚。我们旨在确定估算肾小球滤过率(eGFR)轨迹的模式,并确定这些不同模式与 2 型糖尿病患者全因死亡率的临床和遗传因素及其相关性。在香港糖尿病登记处的基线 eGFR>60 ml/min/1.73 m 的 6330 名患者中,共有 456 名患者(7.2%)在中位随访 13 年后发展为 5 期慢性肾脏病或 ESRD(发病率为 5.6/1000 人年)。联合潜在类别建模用于识别 eGFR 轨迹的不同模式。确定了 4 种不同的非直线 eGFR 轨迹:缓慢下降(84.3%的患者)、曲线下降(6.5%)、进行性下降(6.1%)和加速下降(3.1%)。微量白蛋白尿和视网膜病变与加速的 eGFR 下降相关,而 eGFR 下降本身与全因死亡率相关(与缓慢 eGFR 下降相比,比值比[OR]为 6.9;95%置信区间[CI]为 5.6-8.4)。在评估的 68 个候选遗传位点中,包含 5 个位点(rs11803049、rs911119、rs1933182、rs11123170 和 rs889472)可改善 eGFR 轨迹的预测(净重新分类改善 0.232;95%CI:0.057-0.406)。我们的研究强调了糖尿病肾病患者中 eGFR 下降模式的显著异质性,并确定了相关的临床和遗传因素,这些因素可能有助于识别那些肾功能更有可能加速下降的患者。