蛋白尿
医学
肾功能
糖尿病
比例危险模型
肌酐
内科学
肾脏疾病
2型糖尿病
2型糖尿病
微量白蛋白尿
内分泌学
作者
Laura Pyle,Ye Ji Choi,Phoom Narongkiatikhun,Kumar Sharma,Sushrut S. Waikar,Anita T. Layton,Kalie L. Tommerdahl,Ian H. de Boer,Tim Vigers,Robert G. Nelson,Jane Lynch,Frank C. Brosius,Pierre‐Jean Saulnier,Jesse A. Goodrich,Jeanie B. Tryggestad,Elvira Isganaitis,Fida Bacha,Kristen J. Nadeau,Daniël H. van Raalte,Matthias Kretzler
标识
DOI:10.2215/cjn.0000000000000559
摘要
Background: The onset of diabetic kidney disease (DKD) in youth with type 2 diabetes mellitus often occurs early, leading to complications in young adulthood. Risk biomarkers associated with the early onset of DKD are urgently needed in youth with type 2 diabetes. Methods: We conducted an in-depth analysis of 6596 proteins (SomaScan 7K) in 374 baseline plasma samples from the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study to identify multi-protein signatures associated with the onset of albuminuria (urine albumin-to-creatinine ratio [UACR] ≥30 mg/g), a rapid decline in estimated glomerular filtration rate (eGFR) [annual eGFR decline >3 mL/min/1.73m 2 and/or ≥3.3% at two consecutive visits], and hyperfiltration (≥135 mL/min/1.73m 2 at two consecutive visits). Elastic net Cox regression with 10-fold cross-validation was applied to the top 100 proteins (ranked by p -value) to identify multi-protein signatures of time to development of DKD outcomes. Results: Participants in the TODAY study (14±2 years old, 63% female, 7±6 months diabetes duration) experienced high rates of early DKD: 43% developed albuminuria, 48% hyperfiltration, and 16% rapid eGFR decline. Increased levels of seven and three proteins were predictive of shorter time to develop albuminuria and rapid eGFR decline, respectively; 118 proteins predicted time to development of hyperfiltration. Elastic net Cox proportional hazards model identified multi-protein signatures of time to incident early DKD with concordance for models with clinical covariates and selected proteins between 0.81 and 0.96, while the concordance for models with clinical covariates only was between 0.56 and 0.63. Conclusions: Our research sheds new light on proteomic changes early in the course of youth-onset type 2 diabetes that associate with DKD. Proteomic analyses identified promising risk factors that predict DKD risk in youth with type 2 diabetes and could deepen our understanding of DKD mechanisms and potential interventions.
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