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 Children’s Hospital Medical Center. 1 st International Symposium on AKI in Children 7 th International Conference

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Genomics of Septic Shock-Associated Kidney Injury

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Genomics of septic shock associated kidney injury

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

Disclosures

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


The problem of sepsis and aki

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


The cardiac angina paradigm

The cardiac angina paradigm

Detection  Improved outcomes?

Acute Myocardial Infarction (AMI)

Clinical Signs/Symptoms

Ancillary Tests

Classic Risk Factors

Biomarkers

Early Treatment

(Thrombolytics, PCI)

Early Recognition

Early Recovery


Identifying the renal troponin for ssaki

Identifying the renal troponin for SSAKI?

Clinical Signs/Symptoms

Ancillary Tests

Classic Risk Factors

Biomarkers

Early Treatment

(Thrombolytics, PCI)

Early Recognition

Early Recovery


Markers of kidney function in ssaki

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

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 ssaki1

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 ssaki2

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 ssaki3

Biomarkers + Severe Sepsis Associated AKI (SSAKI)

AKI = [Cr] > 2 mg/dl

= 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)

  • There is a need to identify AKI biomarkers

    • Specific to patients with SSAKI

    • Especially in pediatrics

      • Limited number of studies

AKI Markers in SSAKI:

Poor Specificity

Poor Discrimination

Poor Precision


Microarray biomarkers for ssaki

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 ssaki1

Microarray  biomarkers for SSAKI

Basu, Crit Care, 2011


Genomics of septic shock associated kidney injury

  • Microarray  biomarkers for SSAKI

Basu, Crit Care, 2011


Genomics of septic shock associated kidney injury

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


Genomics of septic shock associated kidney injury

  • Microarray  biomarkers for SSAKI

Basu, Crit Care, 2011


Genomics of septic shock associated kidney injury

  • 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%)


Genomics of septic shock associated kidney injury

  • Microarray  biomarkers for SSAKI

Basu, Crit Care, 2011


Genomics of septic shock associated kidney injury

  • Microarray  biomarkers for SSAKI

Basu, Crit Care, 2011


Genomics of septic shock associated kidney injury

  • Microarray  biomarkers for SSAKI

Basu, Crit Care, 2011


Genomics of septic shock associated kidney injury

  • Microarray  biomarkers for SSAKI

Basu, Crit Care, 2011


Genomics ssaki biomarkers

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

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

Acknowledgements

  • Cincinnati Children’s 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


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