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Lipidomic Signature of Progression of Chronic Kidney Disease in the Chronic Renal
Insufficiency Cohort
#MMPMID28451650
Afshinnia F
; Rajendiran TM
; Karnovsky A
; Soni T
; Wang X
; Xie D
; Yang W
; Shafi T
; Weir MR
; He J
; Brecklin CS
; Rhee EP
; Schelling JR
; Ojo A
; Feldman H
; Michailidis G
; Pennathur S
Kidney Int Rep
2016[Nov]; 1
(4
): 256-268
PMID28451650
show ga
INTRODUCTION: Human studies report conflicting results on the predictive power of
serum lipids on progression of chronic kidney disease (CKD). We aimed to
systematically identify the lipids that predict progression to end-stage kidney
disease. METHODS: From the Chronic Renal Insufficiency Cohort, 79 patients with
CKD stage 2 to 3 who progressed to ESKD over 6 years of follow up were selected
and frequency-matched by age, sex, race, and diabetes with 121 non-progressors
with less than 25% decline in estimated glomerular filtration rate (eGFR) during
the follow up. The patients were randomly divided into Training and Test sets. We
applied liquid chromatography-mass spectrometry-based lipidomics on visit year 1
samples. RESULTS: We identified 510 lipids, of which the top 10 coincided with
false discovery threshold of 0.058 in the Training set. From the top 10 lipids,
the abundance of diacylglycerols (DAGs) and cholesteryl esters was lower, but
that of phosphatidic acid 44:4 and monoacylglycerol (MAG) 16:0 was significantly
higher in progressors. Using logistic regression models a multi-marker panel
consisting of DAGs, and MAG independently predicted progression. The c-statistic
of the multimarker panel added to the base model consisting of eGFR and urine
protein-creatinine ratio (UPCR) as compared to that of the base model was 0.92
(95% Confidence Interval [CI]: 0.88-0.97), and 0.83 (95% CI: 0.76-0.90, P<0.01),
respectively; an observation which was validated in the Test subset. CONCLUSION:
We conclude that a distinct panel of lipids may improve prediction of progression
of CKD beyond eGFR and UPCR when added to the base model.
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