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!