Metabolomic Markers of Kidney Function Decline in Patients With Diabetes: Evidence From the Chronic Renal Insufficiency Cohort (CRIC) Study

Kwan, Brian; Fuhrer, Tobias; Zhang, Jing; Darshi, Manjula; Espen, Benjamin Van; Montemayor, Daniel; Boer, Ian H. de; Dobre, Mirela; Hsu, Chi‐yuan; Kelly, Tanika N.; Raj, Dominic S.; Rao, Panduranga S.; Saraf, Santosh L.; Scialla, Julia J.; Waikar, Sushrut S.; Sharma, Kumar; Natarajan, Loki; Appel, Lawrence J.; Feldman, Harold I.; Go, Alan S.; He, Jiang; Lash, James P.; Rahman, Mahboob; Townsend, Raymond R.

doi:10.1053/j.ajkd.2020.01.019

Cited by 53 publications

(63 citation statements)

References 39 publications

(47 reference statements)

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“…13 metabolites predicted CKD progression in the CRIC cohort [76]. A panel of 21 metabolites was shown to predict the proteinuric response to ARBs [112].…”

Section: Classifiersmentioning

confidence: 98%

“…In further risk prediction models, CKD273 was also able to reclassify about 30% of patients compared with the standard equation that considers eGFR and albuminuria, for the risk of CKD progression [75]. The CRIC investigators described, in a recent manuscript, the association between a panel of 13 urine metabolites and CKD progression [76]. Results of this analysis are encouraging since the levels of four metabolites, namely, 3-hydroxyisobutyrate (3-HIBA), 3-methylcrotonyglycine, citric acid, and aconitic acid, were associated with eGFR decline, with 3-HIBA and aconitic acid levels also significantly associated with the hard endpoint ESKD.…”

Section: Prognostic Role Of Proteomics Metabolomics and Genomicsmentioning

confidence: 99%

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Contribution of Predictive and Prognostic Biomarkers to Clinical Research on Chronic Kidney Disease

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Chiodini

et al. 2020

IJMS

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Chronic kidney disease (CKD), defined as the presence of albuminuria and/or reduction in estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73m2, is considered a growing public health problem, with its prevalence and incidence having almost doubled in the past three decades. The implementation of novel biomarkers in clinical practice is crucial, since it could allow earlier diagnosis and lead to an improvement in CKD outcomes. Nevertheless, a clear guidance on how to develop biomarkers in the setting of CKD is not yet available. The aim of this review is to report the framework for implementing biomarkers in observational and intervention studies. Biomarkers are classified as either prognostic or predictive; the first type is used to identify the likelihood of a patient to develop an endpoint regardless of treatment, whereas the second type is used to determine whether the patient is likely to benefit from a specific treatment. Many single assays and complex biomarkers were shown to improve the prediction of cardiovascular and kidney outcomes in CKD patients on top of the traditional risk factors. Biomarkers were also shown to improve clinical trial designs. Understanding the correct ways to validate and implement novel biomarkers in CKD will help to mitigate the global burden of CKD and to improve the individual prognosis of these high-risk patients.

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“…13 metabolites predicted CKD progression in the CRIC cohort [76]. A panel of 21 metabolites was shown to predict the proteinuric response to ARBs [112].…”

Section: Classifiersmentioning

confidence: 98%

Section: Prognostic Role Of Proteomics Metabolomics and Genomicsmentioning

confidence: 99%

Contribution of Predictive and Prognostic Biomarkers to Clinical Research on Chronic Kidney Disease

Provenzano

Rotundo

Chiodini

et al. 2020

IJMS

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“…There has been increasing interest in the association of biomarkers with eGFR decline in DKD [38, 39]. Our panel of 13 urine metabolites was recently found to correlate with eGFR slope in 1,001 subjects with T2D in the Chronic Renal Insufficiency Cohort Study [40]. Notably, this panel was responsive to therapy with dapagliflozin and atrasentan, suggesting potential as a surrogate indicator for mitochondrial dysfunction in T2D [41, 42].…”

Section: Discussion/conclusionmentioning

confidence: 99%

A Targeted Multiomics Approach to Identify Biomarkers Associated with Rapid eGFR Decline in Type 1 Diabetes

et al. 2020

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Background: Individuals with type 1 diabetes (T1D) demonstrate varied trajectories of estimated glomerular filtration rate (eGFR) decline. The molecular pathways underlying rapid eGFR decline in T1D are poorly understood, and individual-level risk of rapid eGFR decline is difficult to predict. Methods: We designed a case-control study with multiple exposure measurements nested within 4 well-characterized T1D cohorts (FinnDiane, Steno, EDC, and CACTI) to identify biomarkers associated with rapid eGFR decline. Here, we report the rationale for and design of these studies as well as results of models testing associations of clinical characteristics with rapid eGFR decline in the study population, upon which “omics” studies will be built. Cases (n = 535) and controls (n = 895) were defined as having an annual eGFR decline of ≥3 and <1 mL/min/1.73 m2, respectively. Associations of demographic and clinical variables with rapid eGFR decline were tested using logistic regression, and prediction was evaluated using area under the curve (AUC) statistics. Targeted metabolomics, lipidomics, and proteomics are being performed using high-resolution mass-spectrometry techniques. Results: At baseline, the mean age was 43 years, diabetes duration was 27 years, eGFR was 94 mL/min/1.73 m2, and 62% of participants were normoalbuminuric. Over 7.6-year median follow-up, the mean annual change in eGFR in cases and controls was −5.7 and 0.6 mL/min/1.73 m2, respectively. Younger age, longer diabetes duration, and higher baseline HbA1c, urine albumin-creatinine ratio, and eGFR were significantly associated with rapid eGFR decline. The cross-validated AUC for the predictive model incorporating these variables plus sex and mean arterial blood pressure was 0.74 (95% CI: 0.68–0.79; p < 0.001). Conclusion: Known risk factors provide moderate discrimination of rapid eGFR decline. Identification of blood and urine biomarkers associated with rapid eGFR decline in T1D using targeted omics strategies may provide insight into disease mechanisms and improve upon clinical predictive models using traditional risk factors.

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“…An inherent problem with mtDNA in the urine or plasma as biomarkers is that its source is unclear and it is unlikely to be a tissue specific biomarker. While there is not a definitive conclusion on the utility of mtDNA as biomarker at this time, metabolomic and proteomic approaches to identify suitable biomarkers still hold promise (87)(88)(89).…”

Section: Mitochondria As Biomarkers Of Dn Progressionmentioning

confidence: 99%

Shaping Up Mitochondria in Diabetic Nephropathy

2020

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Mitochondrial medicine has experienced significant progress in recent years and is expected to grow significantly in the near future, yielding many opportunities to translate novel bench discoveries into clinical medicine. Multiple lines of evidence have linked mitochondrial dysfunction to a variety of metabolic diseases, including diabetic nephropathy (DN). Mitochondrial dysfunction presumably precedes the emergence of key histologic and biochemical features of DN, which provides the rationale to explore mitochondrial fitness as a novel therapeutic target in patients with DN. Ultimately, the success of mitochondrial medicine is dependent on a better understanding of the underlying biology of mitochondrial fitness and function. To this end, recent advances in mitochondrial biology have led to new understandings of the potential effect of mitochondrial dysfunction in a myriad of human pathologies. We have proposed that molecular mechanisms that modulate mitochondrial dynamics contribute to the alterations of mitochondrial fitness and progression of DN. In this comprehensive review, we highlight the possible effects of mitochondrial dysfunction in DN, with the hope that targeting specific mitochondrial signaling pathways may lead to the development of new drugs that mitigate DN progression. We will outline potential tools to improve mitochondrial fitness in DN as a novel therapeutic strategy. These emerging views suggest that the modulation of mitochondrial fitness could serve as a key target in ameliorating progression of kidney disease in patients with diabetes.

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Metabolomic Markers of Kidney Function Decline in Patients With Diabetes: Evidence From the Chronic Renal Insufficiency Cohort (CRIC) Study

Cited by 53 publications

References 39 publications

Contribution of Predictive and Prognostic Biomarkers to Clinical Research on Chronic Kidney Disease

Contribution of Predictive and Prognostic Biomarkers to Clinical Research on Chronic Kidney Disease

A Targeted Multiomics Approach to Identify Biomarkers Associated with Rapid eGFR Decline in Type 1 Diabetes

Shaping Up Mitochondria in Diabetic Nephropathy

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