Lipidomic Predictors of Diabetic Kidney Disease Progression in Patients with Type-1 Diabetes
1 型糖尿病患者糖尿病肾病进展的脂质组学预测因素
基本信息
- 批准号:9804708
- 负责人:
- 金额:$ 8.79万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-07-01 至 2021-06-30
- 项目状态:已结题
- 来源:
- 关键词:18 year oldAgeAlbuminsBiological MarkersCholesterolChronic Kidney FailureClassificationClinicalClinical DataClinical ResearchClinical assessmentsColoradoComplications of Diabetes MellitusControl GroupsCreatinineCross-Sectional StudiesDataDiabetes MellitusDiabetic NephropathyDiseaseDisease ProgressionEarly identificationEnd stage renal failureEpidemiologyExclusion CriteriaExcretory functionFrequenciesGlycerolipid Metabolism PathwayGrantHumanIndividualInformation SystemsInsulin-Dependent Diabetes MellitusInterventionKidneyKidney DiseasesLipidsLipoproteinsLogistic RegressionsMasksMass Spectrum AnalysisMeasurementMeasuresMethodsModelingMonitorNative AmericansNatureNon-Insulin-Dependent Diabetes MellitusNonesterified Fatty AcidsOutcomePatient CarePatientsPhenotypePlasmaPrevalenceProteinuriaRaceRenal functionResearchRisk stratificationSamplingSampling StudiesTechnologyTestingTimeTrainingTranslationsTriglyceridesUnited StatesUrineValidationVisitacylcarnitinebasecase controlclinical applicationclinical careclinical practicecohortcoronary artery calcificationdata reductionfollow-uphigh riskinclusion criteriainterestkidney preservationmass spectrometermitochondrial dysfunctionmultiple reaction monitoringnovelpatient orientedpatient populationpredictive markerpredictive testpreservationprognosticprognostic valuesexstatisticsurinary
项目摘要
ABSTRACT
Diabetes is the leading cause of end stage kidney disease in the United States. Currently there is no biomarker
to identify patients at high risk of progression of diabetic kidney disease (DKD) when GFR is preserved (>90
mL/min) and urine albumin excretion is within normal limit. In this study we aim to test the predictive power of
C16-C24 free fatty acids (FFA)s and C40-C46 triacylglycerols (TAG)s in plasma to predict progression of DKD
at early stage when estimated GFR (eGFR) is greater than 90 mL/min and urine albumin-creatinine ratio (ACR)
is less than 30 mg/g. This study will be a case control observation in which the case group is defined as
progression of DKD in longitudinal follow up visits. Patient population is the patients with type-1 diabetes. Study
samples are selected from 4 established cohorts of patients with type-1 diabetes including the Steno Diabetes
Center Copenhagen, the Finnish Diabetic Nephropathy (FinnDiane), the Colorado Coronary Artery Calcification
in Type 1 diabetes (CACT1), and the Pittsburgh Epidemiology of Diabetic Complications (EDC). Sampling is
based on the application of the inclusion and exclusion criteria. The inclusion criteria are age of 18 years or older
at the time of sample selection, eGFR ≥90 ml/min, ≥3 longitudinal measure of eGFR, and follow up of more than
4 years. Exclusion criterion is age<18 years. Case group is defined as patients with type-1 diabetes who had >3
ml/min/year loss in eGFR during follow up. Control group is defined as patients with type-1 diabetes who had no
or less than 1 mL/min/year loss in eGFR during follow up, frequency matched by age, sex, race, and eGFR at
baseline with the case group. Overall, 350 patients including non-progressors and progressors with a 2:1 ratio
are selected. After selection, patients will be randomly split to the training (57 progressors and 117 non-
progressors) and validation cohorts. Outcome is progression of DKD defined as >3 mL/min/year loss in eGFR
during follow up visits. Clinical data and plasma samples at baseline visit (corresponding date of matching cases
and controls) are available. Targeted lipidomic studies (based on our preliminary data) will be applied to quantify
the proposed lipids in multiple reaction monitoring (MRM) mode using an AB Sciex Triple Quadrupole/QTRAP
6500+ mass spectrometer. For analysis, we will apply t-test with false discovery rate correction for multiple
comparisons using a compound by compound comparison for ability to predict DKD progression. Additionally,
we will use principal component for data reduction, and will incorporate the significant lipids as well as the
principal components separately in adjusted logistic regression models to test the independent prediction of
proposed markers on DKD progression. We will calculate c-statistics and compare it to that of eGFR and ACR
to assess the improvement of classification power. We will replicate the analysis in the validation subset
consisting of 175 patients including non-progressors and progressors with 2:1 ratio. Collectively, we anticipate
identifying a quantitative prognostic lipid panel that accurately predicts early DKD progression.
摘要
糖尿病是美国终末期肾病的主要原因。目前没有生物标志物
当GFR保持(>90)时,识别糖尿病肾病(DKD)进展的高风险患者
mL/min),尿白蛋白排泄量在正常范围内。在这项研究中,我们的目的是测试的预测能力,
血浆中C16-C24游离脂肪酸(FFA)和C40-C46三酰甘油(TAG)预测DKD进展
在早期,当估计的GFR(eGFR)大于90 mL/min和尿白蛋白-肌酐比值(ACR)时
小于30 mg/g。本研究将是一项病例对照观察,其中病例组定义为
纵向随访访视中DKD的进展。患者人群为1型糖尿病患者。研究
样本选自4个已建立的1型糖尿病患者队列,包括Steno Diabetes
哥本哈根中心,芬兰糖尿病肾病(FinnDiane),科罗拉多冠状动脉钙化
1型糖尿病(CACT 1)和匹兹堡糖尿病并发症流行病学(EDC)。采样
根据入选和排除标准的应用。入选标准为18岁或以上
样本选择时,eGFR ≥90 ml/min,eGFR纵向测量≥3次,随访超过
4年排除标准为3岁<18 years. Case group is defined as patients with type-1 diabetes who had >
随访期间eGFR损失ml/min/年。对照组定义为1型糖尿病患者,
或随访期间eGFR损失小于1 mL/min/年,按年龄、性别、种族和eGFR匹配的频率
与病例组基线比较。总体而言,350例患者包括非进展者和进展者,比例为2:1
被选中。在选择之后,患者将被随机分成训练组(57名进展者和117名非进展者)。
进展者)和验证群组。结局为DKD进展,定义为eGFR损失>3 mL/min/年
在后续访问中。基线访视时的临床数据和血浆样本(匹配病例的相应日期
和控制)可用。靶向脂质组学研究(基于我们的初步数据)将用于量化
使用AB Sciex Triple Quadrupole/QTRAP,在多反应监测(MRM)模式下,
6500+质谱仪。为了进行分析,我们将对多个样本应用t检验和错误发现率校正。
使用化合物与化合物之间的比较来预测DKD进展的能力。此外,本发明还
我们将使用主成分进行数据简化,并将纳入重要的脂质以及
主成分分别在调整后的逻辑回归模型,以测试的独立预测
建议的DKD进展标志物。我们将计算c统计量,并将其与eGFR和ACR进行比较
以评估分类能力的改善。我们将在验证子集中重复分析
由175名患者组成,包括2:1比例的非进展者和进展者。总体而言,我们预计
确定可准确预测早期DKD进展的定量预后脂质组。
项目成果
期刊论文数量(0)
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Farsad Afshinnia其他文献
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