micro rna diagnostics and therapeutics in acute kidney injury

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

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

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

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)

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

Pathophysiology of AKI

Compr Physiol. 2012 Apr; 2(2): 1303–1353.

Regional Blood Flow is altered in AKI


During ischemia During reperfusion

Tubular and Vascular Injury During AKI extension


The continuum of cell damage in AKI


“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

Understanding Biology By Understandingand Reverse Engineering The Control

Proc Natl Acad Sci U S A. Mar 22, 2005; 102(12): 4219–4220

http://en.wikipedia.org/wiki/File:MiRNA.svg

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

miRNA Generation

Nat. Rev. Drug. Discov. 13, 622-638,2014

miRNA function


Principles of miRNA – mRNA interaction

Nature Reviews Genetics 9, 102-114,2008

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

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

Statistics Of Biological Regulatory Networks

Feala JD, et al. PLoS ONE 7(1): e29374. (2012)

How do we control things?

Predictably simple

Error Correcting

Model based

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”

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

miRNAinhibitionstrategies


MIRNAS AND THE KIDNEY

Nephrons, Channels and miRNAs

Kidney International (2012) 81, 617–627

miRNAs in renal (patho-)physiology

Loop of Henle

Distal Nephron

Int. J. Mol. Sci. 2013, 14, 13078-13092

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.

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

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

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

Potential renal sources

of miRNAs

Clin

J A

m S

oc

Nep

hro

l. 2

01

2 ,7

(9):

15

28

-33

.

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

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

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%

MIRNAS IN ACUTE KIDNEY INJURY

Selective Deletion of Dicer from the PT protects against ischemic AKI

JASN 2010 21(5): 756-761

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

miRNAs in experimental toxic AKI


miRNA antagonism may affect the severity of experimental toxic AKI


miRNA 21 identifies patients at risk for developing AKI and AKI progression

AKI detection AKI progression

PLoS ONE 8(5): e63390

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

AKI is associated with changes in circulating miRNAs

CJA

SN6

: 15

40

–15

46

, 2

01

1

Circulating miR-210 predicts survival in clinical AKI

CJASN 6: 1540–1546, 2011

miRNA profiling distinguishes between various forms of post-transplant AKI

Transplantation. 95(6): 835–841, 2013

Altered molecular pathways in various forms of post-transplant AKI

Transplantation. 95(6): 835–841, 2013

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

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

Treating experimental AKI by the vessel-specific mR-126

J Am Soc Nephrol 25: 1710–1722, 2014

Anti-p53 siRNA in ischemic & toxic AKI

J Am Soc Nephrol 20: 1754–1764, 2009

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

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

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

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

micro rna diagnostics and therapeutics in acute kidney injury

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