Markers e diagnosi precoce di danno renale acuto
L. Gesualdo Università di Bari
I pazienti ! Il numero dei pazienti con Insufficienza Renale Acuta (IRA) è in continuo aumento e, sempre più frequentemente, si riscontrano:
" Pazienti affetti da patologie per le quali in passato si registrava un’elevata m o r t a l i t à p r e c o c e e c h e o g g i sopravvivono sviluppando IRA.
" Un numero sempre più elevato di anziani e cardiopatici, che sono tra i soggetti a maggior rischio di sviluppare una IRA.
" Pazienti affetti da gravi traumi (incidenti d’auto, sul lavoro, ecc).
IRA in TERAPIA INTENSIVA Principali caratteristiche
Incidenza: 2.5 (non in TI) – 25% (in TI) (Guerin C, 2000; de Mendonça A, 2000)
Mortalità complessiva estremamente elevata: 25-80% (Kellum , 2004)
Meccanismi patogenetici: prevalentemente ischemici o tossici o ischemici + tossici (Metha RL, 2004)
Influenza diretta sulla mortalità (Chertow JM, 1998; Metnitz PG, 2002)
IRA severa in forma isolata: rara
Più frequente il coinvolgimento multiorgano: IRA in MOFS: disfunzione respiratoria, circolatoria, epatica (de Mendonça A, 2000; Chen YC, 2001)
Pazienti presenti in Unità di TERAPIA INTENSIVA (TI)
USARE UN LINGUAGGIO COMUNE! Inquadrare clinicamente il paziente
The Acute Dialysis Quality Initiative (RIFLE) and Acute Kidney Injury Network (AKIN) classification systems for
AKI
Ostermann M and Chang RW Crit Care Med 35:1837-1843, 2007 Bagshaw SM et al Nephrol Dial Transplant 23:1569-1574, 2008
Acute Renal Failure Pathophysiology
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Acute renal failure
Pre-renal Renal Post-renal
Ischemia (reperfusion)
50%
Toxins 35%
Others 15%
ARF - Renal causes a) Drug-induced acute interstitial nephritis
1) Diuretics 2) Analgesics 3) Allopurinol
b) Rapidly progressive glomerulonephritis (crescentic disease, 39%)
c) Acute tubular necrosis mediated by ischemia and/or nephrotoxicity 1) Radio-contrast media 2) Aminoglycosides 3) Rhabdomyolysis 4) Cardiac surgery
d) Cholesterol emboli
Necrosi tubulari acute
Nefriti interstiziali acute
Anti-Kappa
Mieloma Kidney
Microembolismo colesterinico
LIMITI della BR in corso di IRA
Elevata tendenza al sanguinamento post bioptico per la frequente presenza, in corso di IRA, di anomalie della coagulazione, anemia ed ipertensione arteriosa
Disfunzioni piastriniche e/o trombocitopenia conseguenti all’uso di eparina e all’interazione del sangue con le superfici artificiali del circuito di dialisi
Eventuale scarsa collaborazione del paziente per la difficoltà a mantenere la posizione prona per le possibili difficoltà respiratorie
Diagnosis of AKI: the Achilles Heel
Early diagnosis has been the ‘Achilles heel’ of acute kidney injury (AKI) that has prevented successful implementation of treatment strategies
To date, pharmacological intervention has been largely unsuccessful or equivocal, and morbidity and mortality associated with AKI have remained unacceptably high
Despite their well-known limitations, the most widely used biomarkers for the early diagnosis of AKI are serum creatinine, blood urea nitrogen and urine output
Development of new biomarkers is imperative!
AKI and Biomarkers
Neuro-imaging
TAC
Electric Signals
ECG Gene Expression
Microarray
Proteins
Troponin I Proteomic Pattern
Urine Proteome SELDI-TOF
What is a Biomarkers?
A characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention
2000s 1990s 1980s 1970s 1960s Period
Troponin I
Multiple Therapies 50% ! Mortality
Troponin T
CK-MB
CPK, myoglobin
LDH
Acute Myocardial Infarction
Serum creatinine
Supportive Care High Mortality
Serum creatinine
Serum creatinine
Serum creatinine
Serum creatinine
Acute Kidney Injury
Biomarkers: AMI versus AKI
Diagnosis of AKI is often delayed!
Conventional biomarkers for AKI diagnosis and for differential diagnosis
are imperfect
• sCreat, BUN • Urinary Na/K ratio • FENa • Urinary output • Urine sediment • Tubular proteins • Enzymuria
function
injury
Relazione tra SCr e GFR
Which Role for Biomarkers in AKI?
# Early prediction and diagnosis of AKI (before increase in serum creatinine)
# Identify the primary location of injury (proximal tubule, distal tubule, interstitium, vasculature)
# Pick out the duration (Prerenal, AKI, CKD) and severity # Identify the etiology of AKI (ischemic, septic, toxic, combination)
# Differentiate from other types of kidney disease (UTI, GN, IN) # Predict the outcome (need for RRT, length of hospitalization,
mortality)
# Monitor response to intervention and treatment # Expedite the drug development process
Normal Increased Risk !GFR Injury Kidney
Failure Death
Risk Stratification Surveillance Diagnosis Prognosis/Outcome
Clinical stages of AKI and phases of biomarker utility
Modified from Molitoris BA et al, Nat Clin Pract Nephrol 2008
–
NGAL IL-18
NGAL IL-18
Reactive oxygen species? FGF23? C-reactive protein? Pentraxins?
Inflammatory
KIM-1
KIM-1 NHE3 NAG GST
NAG NHE3 Proteinuria? Structural
GFR
Cystatin C Fractional excretion: Na GFR Fractional excretion: urea
GFR Renal blood flow
! Serum creatinine " GFR " Renal blood flow
Functional
Renal replacement therapy Urine output " Blood pressure "Urine output
Congestive heart failure Liver disease Diabetes mellitus CKD Sepsis
Clinical
Prognosis Diagnosis Surveillance Risk Identification Class of Biomarker
Ideal Biomarker in AKI assessment at bedside
1. Noninvasive and easy to perform at the bedside or in a standard clinical laboratory, using easily accessible samples such as blood or urine
2. Rapidly and rel iably measurable using a standardized assay platform (i.e. ELISA)
3. Highly sensitive to facilitate early detection with a wide dynamic range and cut-off values (risk stratification)
Phase Terminology Action Steps Phase 1 Preclinical Discovery • Discover biomarkers in tissues or body fluids
• Confirm and prioritize promising candidates
Phase 2 Assay Development • Develop and optimize clinically useful assay • Test on existing samples of established disease
Phase 3 Retrospective Study • Test biomarker in completed clinical trial • Test if biomarker detects the disease early • Evaluate sensitivity, specificity, ROC
Phase 4 Prospective Screening • Use biomarker to screen population • Identify extent and characteristics of disease • Identify false referral rate
Phase 5 Disease Control • Determine impact of screening on reducing disease burden
Biomarkers: From Bench To Bedside
Modified from Pepe MS et al, J Natl Cancer Inst 2001
“Storici” Biomarker Urinari di Danno Renale
Netti GS et al, G Ital Nefrol 2008
Biomarkers for AKI (injury) • NGAL (serum and urine) • KIM-1 • L-FABP • Netrin-1 • IL-18 • Etc.
The generally accepted measure of performance (discrimination) is the receiver operating characteristic (ROC) curve, which compares test sensitivity to test 1-specificity for all possible cutoff values The area under the ROC curve (also known as the C statistic) is the proportion of pairs for which the model assigns greater probability to subjects who will experience the event than to individuals who will not Appropriate interpretation of a biomarker requires a Bayesian approach in which pre-test probability of disease is integrated with biomarker test results to estimate the post-test probability of disease. This combination yelds a predictive values of positive or negative test (PPV, NPV).
Biomarker performance evaluation
NGAL • Neutrophil Gelatinase-Associated Lipocalin
• First identified as a neutrophil granule protein
• Normally very small amounts in kidney tubules
• The most upregulated gene in the kidney by gene chip analysis, very early after ischemic or nephrotoxic AKI in animals
NGAL/PCNA
Mishra J et al, J Am Soc Nephrol. 2003; Mishra J et al, J Am Soc Nephrol. 2004
• Mouse Ischemia (30 min) • S creat " 24 h • Kidney NGAL " 3 h • Colocalize with PCNA
(proliferating cell nuclear antigen)
NGAL before… …and after 30min ischemia…
Plasma NGAL • The kidney itself does not appear to be a major source • AKI results in a dramatically increased NGAL mRNA expression in
distant organ, especially the liver and lung, and the overexrpressed NGAL protein relased into the circulation may constitute a distinct systemic pool
• Additional contributions to the systemic pool in AKI may derive from the fact that NGAL is an acute phase reactant and may be released from neutrophils, macrophages and other immune cells
• Any decrease in glomerular filtration rate resulting from AKI would be expected to decrease the renal clearance of NGAL, with subsequent accumulation in the systemic circulation
• The relative contribution of these mechanisms to the rise in plasma NGAL after AKI remains to be determined
Devarajan P, Nephrol Dial Transplant 2008; 23:3737-3743
Urinary NGAL • Plasma NGAL freely filtered by the glomerulus • Largely reabsorbed in the proximal tubules by efficient
megalin-dependent endocytosis • Rapid and massive (1000-fold) upregulation of NGAL
RNA in the TAL and CD following IRI. • The resultant synthesis of NGAL protein in the distal
nephron and secretion in the urine appears to comprise the major fraction of urinary NGAL
Devarajan P, Nephrol Dial Transplant 2008; 23:3737-3743
NGAL acts as an acute phase protein which is rapidly released upon kidney injury
• Human adults in ICUs with ARF (sepsis, ischemia, or nephrotoxins) displayed >10-fold increase in plasma NGAL and >100-fold increase in urine NGAL, when compared with normal controls (Intense cortical tubular NGAL staining)
Mori K et al, J Clin Invest. 2005
• NGAL is a biomarker for AKI after cardiac surgery in children
Mishra J et al, Lancet 2005
• In a cohort of adults who developed AKI after cardiac surgery, urinary NGAL was significantly elevated by 1-3 hrs after the operation
Wegener G et al, Anesthesiology 2006
• NGAL levels in biopsies specimens and in urine after kidney transplantation clearly predict Delayed Graft Function onset and requirement of RRT
Mishra J et al, Pediatr Nephrol. 2006; Parikh CR et al, Am J Transpl. 2006
# ARF # without ARF
Urin
e N
GA
L (µ
g/L)
2-6 h
ROC area 0.998 2-hr urine NGAL
ROC area 0.91 2-hr serum NGAL
Point-of-Care: Near Patient Testing
• Glucometers • Arterial Blood Gas Analyzers • Cardiac Analyzer® (NT-
proBNP, Troponin T, Myoglobin, D-Dimers)
• … …
# Tests for Cardiac Markers # Adapted for NGAL testing # 15 min results (whole blood) # Compact, portable, simple, easy to use # Undergoing clinical testing
Triage® NGAL KIT
Prediction of AKI Cut-off value=100 ng/ml
Sensitivity 100% Specificity 75% PPV 100% NPV 75% ROC AUC 0.96
Am J Kidney Dis 2009; 54:1012-1024
Better accuracy in pediatric populations and when timing of kidney injury is known (AUC-ROC > 0.9 in pediatric cardiac surgery, < 0.7
adult cardiac surgery)
Am J Kidney Dis 2009; 54:1012-1024
Haase M et al. Am J Kidney Dis 2009; 54:1012-1024
NGAL as a predictor of AKI
Haase M et al. Am J Kidney Dis 2009; 54:1012-1024
NGAL as a predictor of RRT start in AKI
Haase M et al. Am J Kidney Dis 2009; 54:1012-1024
NGAL as a predictor of mortality in AKI
Interleukin-18 • Proinflammatory cytokine induced and cleaved in the proximal tubule
after AKI. The active form of IL-18 exits the cell and may enter the urine after being activated in proximal tubules.
• In mice, urinary IL-18 concentration was increased in ischemic AKI compared with sham-surgery controls.
Melnikov VY et al, J Clin Invest 2001
• Urine IL-18 levels were markedly increased in pts with established AKI but not in subjects with UTI, CKD, nephritic syndrome, or prerenal failure (ROC AUC of 95% for the diagnosis of established AKI)
Parikh CR et al, Am J Kid Dis 2004
IL-18 seems to be an excellent tool to differentiate ATN from other types of acute renal diseases
IL-18 may predict development of AKI, requirement of RRT and mortality
• In acute respiratory distress syndrome (ARDS) urine IL-18 levels of >100 pg/mg predicted the development of AKI 24 hrs before the serum creatinine (OR 6.5; ROC AUC 0,73). Urine IL-18 predicted also mortality in ARDS
Parikh CR et al, J Am Soc Nephrol 2005
• In 137 critically ill pediatric pts, urine IL-18 rose 48h before SCr in non-septic critically ill children, predicted severity of AKI and was an independent predictor of mortality Washburn KK et al. Nephrol Dial Trasplant 2007
• Urine IL-18 levels at the day of transplant clearly identified cadaveric kidney
recipients who subsequently developed DGF and dialysis requirement Parikh CR et al, Am J Kid Dis 2004; Parikh CR et al, Am J Transplant 2006
• In children pts after cardiac surgery, urine IL-18 levels increased ~6h and peaked at >25-fold at 12h. IL-18 was associated with duration of AKI.
Parikh CR, Mishra J et al, Kidney Int. 2006
AKI
Controls
Not expressed in normal kidney Epithelial adhesion molecule upregulated following injury in dedifferentiating and regenerating tubule epithelial cells following ischemic and nephrotoxic injury May play a role in the restoration of morphological integrity of the tubule Expressed on the proximal tubule epithelial cells in human kidney biopsy sections from pts with ATN
Immunohistochemistry
Normal human kidney Acute tubular necrosis
Tissue KIM-1 expression: Undetectable in normal kidneys Increased in ischemic ATN (or toxic injury - KI 2007)
ELISA Western blot Urinary KIM-1 excretion
met
allo
prot
eina
ses
Han WK et al, Kidney Int. 2002
KIM-1: acute tubule injury marker
KIM-1 is specific to ischemic or nephrotoxic injury, but is a bad early biomarker
• Urinary KIM-1 level elevation predicted AKI in adults undergoing cardiopulmonary bypass and in pediatric patients undergoing cardiac surgery
Han WK et al, Kidney Int. 2007
• In hospitalized patients, urinary KIM-1 level possessed an AUC of 0.61 for the prediction of the composite end point (dialysis or death)
Liangos O et al, J Am Soc Nephrol. 2007
More specific to ischemic or nephrotoxic injury and not significantly affected by CKD or UTI Limited use as an early biomarker: uKIM-1 increases 12-24h after the insult
RenaStick (POC)
15 minutes
Semiquantitative
Immunochromatografic method
- 25-75 Kd laminin-like protein - Chemotropic and cell survival factor in nervous system development - Excreted in the urine as early as 1 h after injury, 30- to 40-fold increase by 3 h, peak by 6 h after the insult
Clin J Am Soc Nephrol 2010 in press Urinary Netrin-1 Is an Early Predictive Biomarker of Acute Kidney Injury after Cardiac Surgery. Ramesh G, Krawczeski CD, Woo JG, Wang Y, Devarajan P. Pennsylvania State University College of Medicine, Hershey, PennsylvaniaB BACKGROUND AND OBJECTIVES: Netrin-1, a laminin-related axon guidance molecule, is highly induced and excreted in the urine after acute kidney injury (AKI) in animals. Here, we determined the utility of urinary netrin-1 levels to predict AKI in humans undergoing cardiopulmonary bypass (CPB). DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Serial urine samples were analyzed by enzyme-linked immunosorbent assay for netrin-1 in 26 patients who developed AKI (defined as a 50% or greater increase in serum creatinine after CPB) and 34 controls (patients who did not develop AKI after CPB). RESULTS: Using serum creatinine, AKI was detected on average only 48 hours after CPB. In contrast, urine netrin-1 increased at 2 hours after CPB, peaked at 6 hours (2462 +/- 370 pg/mg creatinine), and remained elevated up to 48 hours after CPB. The predictive power of netrin-1 as demonstrated by area under the receiver-operating characteristics curve for diagnosis of AKI at 2, 6, and 12 hours after CPB was 0.74, 0.86, and 0.89, respectively. The 6-hour urine netrin-1 measurement strongly correlated with duration and severity of AKI, as well as length of hospital stay (all P < 0.05). Adjusting for CPB time, the 6-hour netrin-1 remained a powerful independent predictor of AKI, with an odds ratio of 1.20 (95% confidence interval: 1.08 to 1.41; P = 0.006). CONCLUSION: Our results suggest that netrin-1 is an early, predictive biomarker of AKI after CPB and may allow for the reliable early diagnosis and prognosis of AKI after CPB, before the rise in serum creatinine.
Urinary Panel for Early Diagnosis of AKI after temporally defined events
(in analogy with serum cardiac markers)
Netrin-1 (Myoglobin)
NGAL (CPK-MB)
IL-18, KIM-1 (Troponin)
0 10 20 30 40 50 60 70 80 90
100
0 6 12 18 24 30 36 42 48 h Urin
e (P
lasm
a) B
iom
arke
rs (f
old
incr
ease
)
Time after injury onset (hours)
Plasma Panel for Early Diagnosis of AKI after temporally defined events
(in analogy with serum cardiac markers)
??? (Myoglobin)
NGAL (CPK-MB)
Cystatin C (Troponin)
0
1
2
3
4
5
6
7
8
0 6 12 18 24 30 36 42 48 h Time after injury onset (hours)
Plas
ma
Bio
mar
kers
(fol
d in
crea
se)
The role of a combination (panel) of Biomarkers for AKI diagnosis
Methodological problems with biomarkers for AKI
• Timing of measurements when timing of renal injury is not known
• Accuracy changes in different populations • Most of the available studies conducted in a single center,
with relatively few events (death or RRT) • Accuracy decreased when baseline GFR < 60 ml/min • Specificity of biomarkers in critically ill patients • The problem of “imperfect” gold standard (serum
creatinine) • Accuracy changes according to criteria utilized for AKI
diagnosis • Standardization of reporting • Potential for publication bias
Neutrophil Gelatinase-Associated Lipocalin and Acute Kidney Injury after Cardiac Surgery: The Effect of Baseline Renal Function on Diagnostic Performance David R. McIlroy, Gebhard Wagener, and H. Thomas Lee Department of Anesthesiology, College of Physicians and Surgeons of Columbia University, New York, New York Background and objectives: Neutrophil Gelatinase-Associated Lipocalin (NGAL) is rapidly released by renal tubules after injury, potentially allowing early identification of acute kidney injury (AKI) after cardiac surgery. However, the diagnostic performance of NGAL has varied widely in clinical studies, and it remains unknown what factors modify the relationship between NGAL and AKI. We hypothesized the relationship between urinary NGAL and AKI would vary with baseline renal function, allowing a stratified analysis to improve diagnostic performance of this novel biomarker. Design, setting, participants, & measurements: We performed a prospective observational study in 426 adult cardiac surgical patients. Urinary NGAL was serially determined, commencing preoperatively and continuing 24 hours postoperatively. AKI was defined as increase in serum creatinine from baseline by either >50% or >0.3 mg/dl within 48 hours postoperatively. Patients were stratified by baseline estimated GFR (eGFR). NGAL levels were compared between patients with and without AKI and diagnostic characteristics determined according to baseline eGFR. Results: In patients with baseline eGFR 60 ml/min, urinary NGAL was higher at all postoperative time points in patients who developed AKI compared with those who did not. In patients with baseline eGFR <60 ml/min, urinary NGAL did not differ at any time between those who did and those who did not develop AKI. Postoperative NGAL best identified AKI in patients with baseline eGFR 90 to 120 ml/min. Conclusions: The relationship between urinary NGAL and AKI after cardiac surgery varies with baseline renal function, with optimal discriminatory performance in patients with normal preoperative function.
Clin J Am Soc Nephrol 5: 211-219, 2010
New biomarkers: risks with abuse
• Costs • “NGALitis” epidemic • Risk of “enthusiastic” overtreatment on the
basis of a “biomarker-guided” approach
Conclusion • Promising novel biomarkers with potentially high sensitivity and specificity are
available, however they have been tested only in small studies and in a limited number of clinical situations
• The lure of their novelty does not remove the need for a clear and guarded appraisal of their potential: thus, their sensitivity and specificity must be validated in clinical samples from large cohorts and from multiple clinical situations
• At the present time no one biomarker fulfils all the desirable features of early detection of active renal damage, of rapid reflection of changes in renal fucntion, of risk stratification, or of differential diagnosis; it is likely that different panels of biomarkers will be required to meet different needs
• Several areas in the biostatistical approach to biomarker studies need to be more fully investigated, and economic issues to be carefully analyzed
• At the present time not enough data for “biomarker-guided” therapy
Grazie per l’attenzione!