Genomics of Septic Shock-Associated Kidney Injury

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Genomics of Septic Shock-Associated Kidney Injury

• Rajit K. Basu, MD
• Assistant Professor, Division of Critical Care
• Center for Acute Care Nephrology
• Cincinnati Childrens Hospital Medical Center

1st International Symposium on AKI in
Children 7th International Conference Pediatric
Continuous Renal Replacement Therapy September
2012
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Disclosures

• Speaker is partially funded by the Gambro Renal
  Products for the TAKING-FOCUS clinical research
  study

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The problem of sepsis and AKI

• Sepsis1
• Leading cause of death in critically ill adults
  (1/4)
• Mortality of severe sepsis is 352, costs gt 15
  billion/yr
• 42,000 pediatric cases/yr of septic shock in US2
• Mortality 9, 4,400 deaths / yr, gt2
  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
4
The cardiac angina paradigm
Detection ? Improved outcomes?
Acute Myocardial Infarction (AMI)
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Identifying the renal troponin for SSAKI?
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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

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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)

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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)

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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

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Biomarkers Severe Sepsis Associated AKI (SSAKI)

• There is a need to identify AKI biomarkers
• Specific to patients with SSAKI
• Especially in pediatrics
• Limited number of studies

AKI Cr gt 2 mg/dl BUN gt 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
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Microarray ? biomarkers for SSAKI

• METHODS
• Inclusion
• Age lt 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 gt 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
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Microarray ? biomarkers for SSAKI
Basu, Crit Care, 2011
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Microarray ? biomarkers for SSAKI
Basu, Crit Care, 2011
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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
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Microarray ? biomarkers for SSAKI
Basu, Crit Care, 2011
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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)

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Microarray ? biomarkers for SSAKI
Basu, Crit Care, 2011
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Microarray ? biomarkers for SSAKI
Basu, Crit Care, 2011
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Microarray ? biomarkers for SSAKI
Basu, Crit Care, 2011
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Microarray ? biomarkers for SSAKI
NGAL
86
39
39
94
Basu, Crit Care, 2011
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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

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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

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Acknowledgements

• Cincinnati Childrens Hospital
• Hector R. Wong
• Stuart L. Goldstein
• Prasad Devarajan
• Center for Acute Care Nephrology
• Division of Critical Care
• Collaborators (Multiple Institutions)
• Stephen Standage
• Natalie Cvijanovich
• Geoffrey Allen
• Neal Thomas
• Robert Freishtat
• Nick Anas
• Keith Meyer
• Paul Checchia
• Richard Lin
• Thomas Shanley
• Mike Bigham