Transcript Slides for HRW from RB - Pediatric Continuous Renal Replacement

Genomics of Septic Shock-Associated Kidney Injury
Rajit K. Basu, MD
Assistant Professor, Division of Critical Care
Center for Acute Care Nephrology
Cincinnati Children’s Hospital Medical Center
1st International Symposium on AKI in Children
7th International Conference
Pediatric Continuous Renal Replacement Therapy
September 2012
Disclosures
• Speaker is partially funded by the Gambro
Renal Products for the TAKING-FOCUS
clinical research study
The problem of sepsis and AKI
• Sepsis1
– Leading cause of death in critically ill adults (1/4)
• Mortality of severe sepsis is 35%2, costs > $15 billion/yr
– 42,000 pediatric cases/yr of septic shock in US2
• Mortality ~ 9%, ~ 4,400 deaths / yr, >$2 billion/yr
• Acute kidney injury (AKI)
– ~ 6% of all adult ICU patients (RIFLE)3
– ~2.5-10% of all pediatric ICU patients (pRIFLE)4
• Sepsis associated AKI (SA-AKI)
– Most frequent etiology of AKI in adults (~ 33-50%)5
– Most frequent etiology of AKI in children (~25-50%)6
– Combined mortality ~50% (PICARD 2011)
1 – Angus, CCM 2001; 2 – Levy, CCM 2010; 3 – Watson, AJRCC 2003; 4 – Uchino, JAMA 2005;
5 – Schneider, CCM 2010; 6 – Bagshaw, CC 2008; 7 – Duzova, Peds Neph 2010
Detection  Improved outcomes?
The cardiac angina paradigm
Acute Myocardial Infarction (AMI)
Biomarkers
Classic Risk Factors
Clinical Signs/Symptoms
Early Recognition
Ancillary Tests
Early Treatment
(Thrombolytics, PCI)
Early Recovery
Identifying the renal troponin for SSAKI?
Biomarkers
Classic Risk Factors
Clinical Signs/Symptoms
Early Recognition
Ancillary Tests
Early Treatment
(Thrombolytics, PCI)
Early Recovery
Markers of kidney function in SSAKI
• No troponin-I for SSAKI currently exists
• Common indices of kidney “function” inadequate for diagnosis and
classification
– Both urine and serum studies of “function” with marginal identification,
prognosis, predictive power
• Where could a potential SSAKI biomarker come from (that matches
the diverse pathophysiology?)
– Where do putative SSAKI biomarkers come from?
• Majority developed in models of non-septic AKI
• Ischemic AKI (including cardiopulmonary bypass)
• Nephrotoxic AKI
• Pathophysiology of SA-AKI is multifactorial
– Combination of ischemic, inflammatory, nephrotoxic, apoptotic AKI
– Studies of AKI biomarkers not stratified purely by “sepsis” etiology
Biomarkers + Severe Sepsis Associated AKI (SSAKI)
“Incidental” SSAKI biomarker studies
• PROWESS
– Study of drotrecogin-alfa (Activated Protein C) for sepsis
– Biomarkers for sepsis also with notable performance for prediction of AKI (IL-6,
APACHE-II score) (Chawla, CJASN 2007)
• NORASEPT
– Study of murine monoclonal Ab to tumor necrosis factor for treatment of
sepsis
– Association of TNF-a and inflammation with ↑rate of SSAKI (Iglesias, AJKD
2003)
• PICARD
– Prospective study examining the history, treatment, outcomes of ARF
– ARF patients had higher pro-inflammatory markers (Simmons, KI 2004)
Biomarkers + Severe Sepsis Associated AKI (SSAKI)
• Where are the dedicated SSAKI biomarker studies?
– Few and far between
• Sepsis studies  highly heterogeneous given severity of illness differences (SOI)
between patients
– Barrier to proper study of biomarkers and therapy for sepsis
– Complicates any study of SSAKI
• NIDDK workshop regarding SSAKI trials (Molitoris, CJASN 2012)
– Homogeneity of patients paramount
– Classification/stratification of cohorts by SOI score
• “Standard biomarkers”
– “pNGAL is raised in patients with SIRS, severe sepsis, and septic shock and should be
used with caution as a marker of AKI in ICU patients with septic shock” (Martensson, Intens
Care Med 2010)
– “The inflammatory response induced by sepsis has no impact on the levels of cystatin C in
plasma during the first week in the ICU” – (Martensson, Neph Dial Trans 2012)
Biomarkers + Severe Sepsis Associated AKI (SSAKI)
• Human “models”
– Association of SSAKI and ↑inflammatory phenotype
– HLA genotype associated with “severe AKI” (Payen, PLoS One 2012)
– TGF-b, TNF-a, IL-6, KC, MIP-1a, MCP-1 all linked to ↑rates of AKI
• Animal models
– Initial ischemic models led to identification of prominent biomarkers
(Devarajan, Mol Med 2003)
– Models of sepsis in animals are JUST as heterogeneous as human patients
• Degree of sepsis variable
• “observed variability in susceptibility to septic AKI in our models replicates
that of human disease” – (Benes, Crit Care 2011)
• Rates of AKI after sepsis inconsistent
– Meprin – 1- a elevated (though AKI was variable) (Holly, KI 2006)
– Later reports indicate no correlation between Meprin -1 and AKI
Biomarkers + Severe Sepsis Associated AKI (SSAKI)
• There is a need to identify AKI biomarkersAKI = [Cr] > 2 mg/dl
– Specific to patients with SSAKI
– Especially in pediatrics
• Limited number of studies
= BUN > 100 mg/dl
= dialysis
NGAL performance:
Sens = 86%
Spec = 39%
PPV = 39%
NPV = 94%
ROC : 0.68 (0.56-0.79)
Wheeler (PCCM, 2008)
AKI Markers in SSAKI:
Poor Specificity
Poor Discrimination
Poor Precision
Microarray  biomarkers for SSAKI
METHODS:
– Inclusion:
• Age < 10, diagnosis of septic shock
• Controls – from ambulatory departments
– Whole blood derived RNA, 1st 24 hours of presentation
• Microarray using Human Genome U133 Plus 2.0 GeneChip
• Hybridization vs. 80,000 gene probes
• 53 normal controls used for normalization
– SSAKI
• Defined as > 2x creatinine persistent to 7 days (“resolved” creatinine elevations
not included)
• Patients with mortality before 7 days were included
– Outcomes
• SSAKI : Morbidity and mortality tracked to 28 days
Basu, Crit Care, 2011
Microarray  biomarkers for SSAKI
Basu, Crit Care, 2011
Microarray  biomarkers for SSAKI
Basu, Crit Care, 2011
Testing the prediction of each patient for
SSAKI or no SSAKI using gene expression
Leave-one-out cross validation
procedure for derivation cohort
(148 without SSAKI, 31 with SSAKI)
Basu, Crit Care, 2011
Microarray  biomarkers for SSAKI
Basu, Crit Care, 2011
Microarray  biomarkers for SSAKI
• Differentially regulated probes analyzed for readily
measurable products
• Protein expression readily measured in serum
– Matrix metalloproteinase-8 (MMP-8)
– Neutrophil elastase-2 (Ela-2)
• Tested serum MMP-8 and Ela-2 expression versus
development of SSAKI in derivation cohort
– 150 samples analyzed (84%)
• 132 no SSAKI (88%), 18 with SSAKI (12%)
Microarray  biomarkers for SSAKI
Basu, Crit Care, 2011
Microarray  biomarkers for SSAKI
Basu, Crit Care, 2011
Microarray  biomarkers for SSAKI
Basu, Crit Care, 2011
Microarray  biomarkers for SSAKI
NGAL
86%
39%
39%
94%
Basu, Crit Care, 2011
Genomics  SSAKI biomarkers
• 1st attempt to characterize biomarkers for SA-AKI (vs. all
cause-AKI)
– 1st 24 hours – expression of 21 gene probes demonstrate high
reliability for prediction of persistent AKI
– Protein products of two gene probes from list measured in serum
carry high sensitivity and negative predictive value
• Biological links of MMP-8 and Ela-2 to SSAKI are unclear
– MMP-8 association with sepsis being investigated (Solan, CCM 2012)
• Gene expression micro-array can be leveraged to identify
putative biomarkers of SSAKI
Conclusions
• Biomarkers for SSAKI will need to come from
select patients properly stratified
• Genomics offer a potential avenue for
biomarker identification
– Still in its infancy
• Will allow for
– Stratification of patients by severity of SSAKI
– Patient specific decision making
– Potential outcome variable
Acknowledgements
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Cincinnati Children’s Hospital
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Hector R. Wong
Stuart L. Goldstein
Prasad Devarajan
Center for Acute Care Nephrology
Division of Critical Care
Collaborators (Multiple Institutions)
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Stephen Standage
Natalie Cvijanovich
Geoffrey Allen
Neal Thomas
Robert Freishtat
Nick Anas
Keith Meyer
Paul Checchia
Richard Lin
Thomas Shanley
Mike Bigham