根據(jù)3月的《糖尿病治療》（Diabetes Care 2007;30:638-643.）雜志上的一項(xiàng)報(bào)告,，尿蛋白組譜可預(yù)測(cè)正常蛋白尿2型糖尿病患者的糖尿病性腎病,。
美國(guó)麻薩諸塞州總醫(yī)院和哈佛醫(yī)學(xué)院的Ravi Thadhani博士及其同事比較了有2型糖尿病和正常尿白蛋白排泄的62例美國(guó)Pima印地安人的尿蛋白組譜,，這些患者被隨訪10年，觀察糖尿病性腎病的發(fā)生,。
作者確定了12峰預(yù)測(cè)標(biāo)記，其預(yù)測(cè)糖尿病性腎病發(fā)生的敏感性為93%，特異性為86%,，準(zhǔn)確性為93%。將標(biāo)記在驗(yàn)證系列的所有樣本（17例樣本和17例匹配對(duì)照）進(jìn)行檢測(cè)時(shí),，總體準(zhǔn)確性為74%,，敏感性為71%,，特異性為76%。在調(diào)整了基線血紅蛋白A1c的多變量尿logistic回歸模型中,，12峰標(biāo)記是糖尿病性腎病的獨(dú)立預(yù)測(cè)因素,，而血紅蛋白A1c不再與以后的糖尿病性腎病顯著相關(guān)。
Thadhani博士說(shuō),，雖然這些發(fā)現(xiàn)需要大量的工作確定和檢測(cè)這些標(biāo)志物的穩(wěn)定性，但是它們?yōu)榕R床醫(yī)生在1天內(nèi)確定糖尿病患者是否將發(fā)生腎功能衰竭提供了可能,，因此,，為防止這種疾病發(fā)生的早期干預(yù)提供了希望。
部分英文原文：
Diabetes Care 30:638-643, 2007
Pathophysiology/Complications
Original Article
Prediction of Diabetic Nephropathy Using Urine Proteomic Profiling 10 Years Prior to Development of Nephropathy
Hasan H. Otu, PHD1,2, Handan Can, PHD1,2, Dimitrios Spentzos, MD1, Robert G. Nelson, MD, PHD3, Robert L. Hanson, MD, MPH3, Helen C. Looker, MBBS3, William C. Knowler, MD, DRPH3, Manuel Monroy, MD4, Towia A. Libermann, PHD1, S. Ananth Karumanchi, MD5 and Ravi Thadhani, MD, MPH4
1 Genomics Center and DF/HCC Cancer Proteomics Core, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
2 Department of Genetics and Bioengineering, Yeditepe University, Istanbul, Turkey
3 Diabetes Epidemiology and Clinical Research Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona
4 Department of Medicine and Renal Unit, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
5 Division of Nephrology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts
Address correspondence and reprint requests to Ravi Thadhani, MD, MPH, Bullfinch 127, 55 Fruit St., Massachusetts General Hospital, Boston, MA 02114. E-mail: [email protected]
OBJECTIVE—We examined whether proteomic technologies identify novel urine proteins associated with subsequent development of diabetic nephropathy in subjects with type 2 diabetes before evidence of microalbuminuria.
RESEACH DESIGN AND METHODS—In a nested case-control study of Pima Indians with type 2 diabetes, baseline (serum creatinine <1.2 mg/dl and urine albumin excretion <30 mg/g) and 10-year urine samples were examined. Case subjects (n = 31) developed diabetic nephropathy (urinary albumin–to–creatinine ratio >300 mg/g) over 10 years. Control subjects (n = 31) were matched to case subjects (1:1) according to diabetes duration, age, sex, and BMI but remained normoalbuminuric (albumin–to–creatinine ratio <30 mg/g) over the same 10 years. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) was performed on baseline urine samples, and training (14 cases:14 controls) and validation (17:17) sets were tested.
RESULTS—At baseline, A1C levels differed between case and control subjects. SELDI-TOF MS detected 714 unique urine protein peaks. Of these, a 12-peak proteomic signature correctly predicted 89% of cases of diabetic nepropathy (93% sensitivity, 86% specificity) in the training set. Applying this same signature to the independent validation set yielded an accuracy rate of 74% (71% sensitivity, 76% specificity). In multivariate analyses, the 12-peak signature was independently associated with subsequent diabetic nephropathy when applied to the validation set (odds ratio [OR] 7.9 [95% CI 1.5–43.5], P = 0.017) and the entire dataset (14.5 [3.7–55.6], P = 0.001), and A1C levels were no longer significant.
CONCLUSIONS—Urine proteomic profiling identifies normoalbuminuric subjects with type 2 diabetes who subsequently develop diabetic nephropathy. Further studies are needed to characterize the specific proteins involved in this early prediction.
Abbreviations: SELDI-TOF MS, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry
