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microRNA Diagnostics and Therapeutics in Acute Kidney Injury
Christos Argyropoulos MD, MSc,PhDAssistant Professor of MedicineDivision of NephrologyUniversity of New Mexico School of Medicine
Department of Internal Medicine Medical Grand RoundsFebruary 12, 2015
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Overview
• A Brief overview of Acute Kidney Injury (AKI)
• Gene Regulation by microRNAs (miRNA)
• miRNAs and the kidney
• miRNAs in Acute Kidney Injury:
– Prognostic/diagnostic
– Therapeutic
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Bad things happen to good people when their kidneys fail acutely
• 65 y/o male admitted for an elective cardiac procedure (3V-CABG+MVR)
• SCr on admission 1.6 mg/dl
• Uncomplicated surgical procedure with “minimal hypotension” (30 mins from 145/88 to 125/60)
• POD1 SCr 2.2 mg/dl, POD3 SCr 4.5 mg/dl (anuric), CRRT initiated for volume overload on POD5
• Patient died in the ICU from sepsis in POD 27 while on dialysis
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AKI: the fast facts
• Complicates 5-7% of hospitalizations (300K/yr)• Incidence is increasing over time• Etiology:
– Prerenal (25-60%)– Renal (35-70%): 80-90% are ischemic/toxic– Post-renal: <5% (but 20% in community AKI)
• Treating AKI is expensive:– US (2005): $10B
• Costs of postsurgical AKI(2014): $42600 v.s $27600
– UK (2014): £1.02 (1% of NHS budget)
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AKI: the grim facts
• x 5.5-6.5 acute mortality risk
• x 1.36-1.59 long term mortality risk
• 20-75% will need acute dialytic support
• 10-50% of dialysis dependent-survivors requiring dialysis will develop ESRD (3% of all incident cases)
Nat. Rev. Nephrol. 10, 193–207, 2014
Hospital Mortality
Long Term Survival
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Pathophysiology of AKI
Compr Physiol. 2012 Apr; 2(2): 1303–1353.
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Regional Blood Flow is altered in AKI
Compr Physiol. 2012 Apr; 2(2): 1303–1353.
During ischemia During reperfusion
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Tubular and Vascular Injury During AKI extension
Compr Physiol. 2012 Apr; 2(2): 1303–1353.
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The continuum of cell damage in AKI
Compr Physiol. 2012 Apr; 2(2): 1303–1353.
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“Where” are the unknowns?
Cardiovascular
System• Angiogenesis
• Vascular inflammation
• Atherosclerosis
• LVH
• Vascular tone
• Endothelial dysfunction
• Hypoxia
• Endothelin
• Prostaglandins
Kidney• Tubuloglomerular
feedback
• Loss of renal filtration
• Cellular metabolism
• Cell death/apoptosis
• Water homestasis
• Osmoregulation
• Calcium sensing
• Sodium, potassium, acid base handling
• Renin-Angiotensinproduction
• Renal development
• Renal senescence
• EMT
• Collagen production
Inflammatory Response
• Leukocyte adhesion
• Neutrophil infiltration
• CD4+/Tregs
• Macrophages
• Dendritic cells
• Cytokine networks
• Native immunity (TLR)
• Complement system
• Reactive O2 production
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Understanding Biology By Understandingand Reverse Engineering The Control
Proc Natl Acad Sci U S A. Mar 22, 2005; 102(12): 4219–4220
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http://en.wikipedia.org/wiki/File:MiRNA.svg
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miRNAs• Short (21-23nt) non-coding RNAs
• First miRNA (lin-4) identified in 1993 as a regulator of larval development in C. elegans
• Second miRNA (let-7) isolated in 2000
• In 2014: 28645 miRNAs in animals, plants and some viruses (~1900 in humans)
• Function as negative, post-transcriptional, regulators of gene expression
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miRNA Generation
Nat. Rev. Drug. Discov. 13, 622-638,2014
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miRNA function
Nat. Rev. Drug. Discov. 13, 622-638,2014
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Principles of miRNA – mRNA interaction
Nature Reviews Genetics 9, 102-114,2008
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The “needle-in-a-haystack” statistics of miRNA- mRNA target interaction
miRNAs binding to each target mRNAs targeted by each miRNA
Number of miRs
De
nsity (
x 1
00
0)
0 50 100 150 200 250 300 350
01
23
45
67
89
11
13
15
17
Number of Targets
De
nsity (
x 1
00
0)
0 1000 2000 3000 4000 5000 6000
00
.10
.20
.30
.40
.50
.60
.70
.80
.91
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Control In Biological Systems Is Many-To-Many, Cooperative And Patterned
Feala JD, et al. PLoS ONE 7(1): e29374. (2012)Riba A et al PLoS Comput Biol 10(2): e1003490. (2014)
Bipartite Control Network Topologies miRNA – Transcription Factor circuits
Feed Forward Loop: master control layout in many natural and artificial control systems
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Statistics Of Biological Regulatory Networks
Feala JD, et al. PLoS ONE 7(1): e29374. (2012)
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How do we control things?
Predictably simple
Error Correcting
Model based
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Feed forward control
• Control element responds to a change in the environment in a predefined manner
• Based on prediction of plant (“what is being controlled”) behavior (requires model)
• Can react before error actually occurs (stabilizing the system)
• Benefits: reduced hysteresis, increased accuracy, cost-efficiency, lower “wear-tear”
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Practical implications
• miRNAs function as master controllers in FFLs
• miRNA profiling reveals the “plant” dynamics of complex biological processes (biology is intrisincly NOT model free)
• miRNA associations are causal
– “a priori plausible” biomarkers
– direct therapeutic implications
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miRNAinhibitionstrategies
Nat. Rev. Drug. Discov. 13, 622-638,2014
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MIRNAS AND THE KIDNEY
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Nephrons, Channels and miRNAs
Kidney International (2012) 81, 617–627
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miRNAs in renal (patho-)physiology
Loop of Henle
Distal Nephron
Int. J. Mol. Sci. 2013, 14, 13078-13092
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Many (?Most) Renal And “Extrarenal” microRNAs are handled by the kidneys
Gidlöf O et al Cardiology 2011;118:217–26. Thompson JD, et al. Nucleic Acid Ther 2012;22:255–64. Water FM van de et al Drug Metab Dispos 2006;34:1393–7.
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Circulating and Urine microRNA in Renal And Non Renal Diseases
G
P
Ker
D
eGFR
GFR G
P
Ker
eGFR
GFR
U
G
Ker
D eGFR
GFR
TA
IRG
U
G
Ker
eGFR
GFR
TA
IRG
A B
PKerGFR
G
UUFR
NR
UFR
GFRP
Multiple confounders arising from the physiological interconnections between the kidney and other organ systems in health and disease may affect the plasma/urine profiles of miRNAs
miRNAs involved in kidney disease
miRNAs not=involved in kidney disease
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Why bother with microRNAs?
• Ubiquity-conservation
• Breadth & width of regulation (>60% of genes)
• Context-specificity (“meta-controller”)
• Master Controllers in Feed Forward Loops
• miRNAs appear relevant in renal physiology and pathophysiology
• “Nice-to-have” biomarker features
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microRNAs as Biomarkers
Advantages of microRNAs
•More stable in circulation than mRNAs•High expression level and low complexity compared to mRNA•Tissue specific expression•Availability of analytical platforms
Keep getting cheaper over time•Sequence conservation
Allows translation of clinical associations to animal modelsAllows translation of animal models to clinical applications
Nat Rev Clin Oncol. Jun 7, 2011; 8(8): 467–477.
Circulating microRNAs
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Potential renal sources
of miRNAs
Clin
J A
m S
oc
Nep
hro
l. 2
01
2 ,7
(9):
15
28
-33
.
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miRNAs in DKD: an example
Stage I
•Hyperfiltration
•Normoalbuminuria
•Reversible/no structural damage
Stage II
•Normoalbuminuria
•Structural abnormalities evident in biopsy
Stage III
•Microalbuminuria
•Hypertension
•Declining (but still supernormal) renal function
Stage IV
•Overt nephropathy
•Macroalbuminuria (>300 mg/d)
•Impaired and worsening renal function
Stage V
•Renal function continues to worsen
•Patient approaches or is already on dialysis
http://en.wikipedia.org/wiki/File:Nodular_glomerulosclerosis.jpeg
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Monitoring the process by observing the controller
MA v.s. NA Overt vs NormalPathway P-value Fraction P-value FractionSignal Transduction
Signaling by SCF-KIT 0.006 18/76 0.001 41/76Signaling by Insulin receptor 0.009 23/109 <0.001 65/109Signaling by NGF 0.016 38/212 <0.001 119/212Signaling by Rho GTPases 0.024 24/125 <0.001 71/125Signaling by ERBB4 0.027 16/76 <0.001 45/76Signaling by ERBB2 0.035 19/97 <0.001 59/97Signaling by PDGF 0.040 22/118 <0.001 67/118Signaling by VEGF 0.041 4/11Signaling by EGFR 0.044 20/106 <0.001 64/106Dowstream signaling of activated FGFR 0.038 19/98 <0.001 61/98Signaling by BMP 0.001 16/23Signaling by TGFβ 0.004 11/15DAG and IP3 signaling 0.010 20/31PIP3 activates AKT signaling 0.020 15/26RAF/MAP kinase cascade 0.031 7/10Signaling by Notch 0.036 13/23Interaction of integrin α5β3 with fibrillin 0.044 2/3Interaction of integrin α5β3 with von Willbrand factor 0.044 2/3Integrin cell surface interactions 0.024 40/85
Cell-Cell Communication 0.009 57/122Cell Cycle
G0 and early G1 0.040 12/21
PLoS One. 2013;8(1):e54662
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MiRNAs as early predictors of microalbuminuria
Feature Expression LevelExpression Level And Target
Analysis
Intercept 2.725 3.313
hsa-miR-105-3p -0.125 -0.196
hsa-miR-122-3p 0.022
hsa-miR-124-3p 0.003
hsa-miR-126-3p 0.045
hsa-miR-1972 -0.003 -0.054
hsa-miR-28-5p -0.316 -0.682
hsa-miR-30b-5p -0.008
hsa-miR-363-3p -0.141 -0.009
hsa-miR-424-5p -0.069
hsa-miR-486-5p 0.083 0.212
hsa-miR-495 -0.045 -0.028
hsa-miR-548o-3p -0.055
hsa-miR-122-5p X Women¶ 0.007
hsa-miR-192-5p X Women¶ 0.033 0.03
hsa-miR-200c-3p X Women¶ 0.07
hsa-miR-548o-3p X Women¶ -0.296 -0.498
hsa-miR-720 X Women¶ 0.059 0.018
Mis-classification Rate 11.1% 7.4%
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MIRNAS IN ACUTE KIDNEY INJURY
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Selective Deletion of Dicer from the PT protects against ischemic AKI
JASN 2010 21(5): 756-761
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miRNA signatures of experimental ischemia reperfusion injury
TGF-b pri-miR-21
PN
AS
10
7(3
2):
14
33
9-4
4,2
01
0
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miRNAs in experimental toxic AKI
Kidney International (2014) 86, 943–953
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miRNA antagonism may affect the severity of experimental toxic AKI
Kidney International (2014) 86, 943–953
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miRNA 21 identifies patients at risk for developing AKI and AKI progression
AKI detection AKI progression
PLoS ONE 8(5): e63390
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miRNA 21 predicts clinical outcomes in post-CPB patients
PLoS ONE 8(5): e63390
Urine miR-21 Plasma miR-21
Outcomes AUC 95%CI OR(95%CI) P AUC 95%CI OR(95%CI) P
RRT 0.99 0.96–1.00 2.59(1.37–4.92) 0.003 0.97 0.90–1.00 1.20(1.06–1.36) 0.005
30 day mortality 0.93 0.85–1.00 1.68(1.25–2.27) <0.001 0.88 0.72–1.00 1.12(1.05–1.20) <0.001
AKIN 3 0.82 0.69–0.95 1.56(1.25–1.95) <0.001 0.81 0.69–0.93 1.10(1.04–1.15) <0.001
Prolonged hospital stay (>10 d) 0.73 0.63–0.84 1.40(1.15–1.70) <0.001 0.71 0.60–0.82 1.06(1.02–1.11) 0.007
Prolonged ICU stay (>4 d) 0.72 0.61–0.83 1.28(1.08–1.52) 0.004 0.67 0.55–0.79 1.05(1.01–1.10) 0.015
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AKI is associated with changes in circulating miRNAs
CJA
SN6
: 15
40
–15
46
, 2
01
1
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Circulating miR-210 predicts survival in clinical AKI
CJASN 6: 1540–1546, 2011
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miRNA profiling distinguishes between various forms of post-transplant AKI
Transplantation. 95(6): 835–841, 2013
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Altered molecular pathways in various forms of post-transplant AKI
Transplantation. 95(6): 835–841, 2013
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miR modulation may prevent experimental ischemia reperfusion injury
J Am Soc Nephrol. 2014, 25(12):2717-29Anesthesiology. 2013, 119(3):621-30
Anti-miR-24
Ischemic preconditioning
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miR-21 is a two sided sword in AKI
Anti-apoptotic in early AKI (PDCD-4/BCL-2)Protective role in the context of ischemic precondition (PDCD-4)Pro-inflammatory in late AKI (MyD88/IRAK1)Pro-fibrotic if excessively upregulated Protein Cell 2013, 4(11): 813–819
Kidney Int. 2012 Dec;82(11):1149-51
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Treating experimental AKI by the vessel-specific mR-126
J Am Soc Nephrol 25: 1710–1722, 2014
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Anti-p53 siRNA in ischemic & toxic AKI
J Am Soc Nephrol 20: 1754–1764, 2009
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Anti-p53 siRNA in ischemic & toxic AKI
J Am Soc Nephrol 20: 1754–1764, 2009
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Clinical Trial of QPI-1002 in renal transplantation
• RCT to assess whether anti-p53 siRNA impacts the outcomes in renal transplantation
• 322 pts (177 were “extended criteria” kidneys)
• DGF ↓: 15.1 % (overall) and 30.5% (ECD)
• ↑ time to first dialysis (p=0.04)
• ↓ duration of dialysis dependency (13.4 v.s. 25.3 days)
NCT00802347
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Why bother with miRNAs in AKI?
Cardiovascular
System• Angiogenesis
• Vascular inflammation
• Atherosclerosis
• LVH
• Vascular tone
• Endothelial dysfunction
• Hypoxia
• Endothelin
• Prostaglandins
Kidney
• Tubuloglomerularfeedback
• Loss of renal filtration
• Cellular metabolism
• Cell death/apoptosis
• Water homestasis
• Osmoregulation
• Calcium sensing
• Sodium, potassium, acid base handling
• Renin-Angiotensinproduction
• Renal development
• Renal senescence
• EMT
• Collagen production
Inflammatory Response
• Leukocyte adhesion
• Neutrophil infiltration
• CD4+/Tregs
• Macrophages
• Dendritic cells
• Cytokine networks
• Native immunity (TLR)
• Complement system
• Reactive O2 production
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Animal Models
Clinical Interventions
Clinical Associations
A microRNA driven discovery cycle
Biomarkers
Mechanistic Insights
Therapeutics
Clinical Science And Bioinformatics Driven “Reverse Translation”
Translational Science
Evidence Based Medicine
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Summary• miRNAs are important regulators of many
biological processes• They are particularly relevant for renal diseases
(acute and chronic)• miRNA based diagnostics are promising markers
of clinical outcomes in AKI• miRNA based therapies may meet the significant
unmet needs in nephrology• Informatics challenges have to be addressed to
facilitate the “reverse-translation” /“translation” discovery cycles for novel diagnostics and therapeutics in renal and non-renal diseases
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