Genomic

expression

profiling

of

human

inflammatory

cardiomyopathy

-LRB-

DCMi

-RRB-

suggests

novel

therapeutic

targets

The

clinical

phenotype

of

human

dilated

cardiomyopathy

-LRB-

DCM

-RRB-

encompasses

a

broad

spectrum

of

etiologically

distinct

disorders

As

targeting

of

etiology-related

pathogenic

pathways

may

be

more

efficient

than

current

standard

heart

failure

treatment

we

obtained

the

genomic

expression

profile

of

a

DCM

subtype

characterized

by

cardiac

inflammation

to

identify

possible

new

therapeutic

targets

in

humans

In

this

inflammatory

cardiomyopathy

-LRB-

DCMi

-RRB-

a

distinctive

cardiac

expression

pattern

not

described

in

any

previous

study

of

cardiac

disorders

was

observed

Two

significantly

altered

gene

networks

of

particular

interest

and

possible

interdependence

centered

around

the

cysteine-rich

angiogenic

inducer

-LRB-

-RRB-

and

adiponectin

-LRB-

APN

-RRB-

gene

overexpression

as

in

human

DCMi

hearts

in

situ

was

similarly

induced

by

inflammatory

cytokines

in

vascular

endothelial

cells

in

vitro

APN

was

strongly

downregulated

in

DCMi

hearts

and

completely

abolished

cytokine-dependent

induction

in

vitro

Dysbalance

between

the

and

APN

networks

may

play

a

pathogenic

role

in

DCMi

and

contain

novel

therapeutic

targets

Multiple

immune

cell-associated

genes

were

also

deregulated

-LRB-

e.g.

chemokine

ligand

nuclear

factors

of

activated

T

cells

-RRB-

In

contrast

to

previous

investigations

in

patients

with

advanced

or

end-stage

DCM

where

etiology-related

pathomechanisms

are

overwhelmed

by

unspecific

processes

the

deregulations

detected

in

this

study

occurred

at

a

far

less

severe

and

most

probably

fully

reversible

disease

stage

Introduction

The

term

dilated

cardiomyopathy

-LRB-

DCM

-RRB-

describes

a

cardiac

phenotype

characterized

by

dilation

and

dysfunction

of

the

ventricles

From

an

etiologic

perspective

DCM

encompasses

a

spectrum

of

disease

entities

some

of

which

are

due

to

monogenic

defects

in

cardiac

expressed

genes

-LSB-

-RSB-

others

triggered

by

exogenous

factors

including

cardiotropic

viruses

-LSB-

-RSB-

Targeting

of

etiology-related

pathogenic

pathways

in

etiologically

distinct

DCM

subtypes

may

be

more

efficient

than

current

standard

treatment

protocols

employed

in

heart

failure

of

any

origin

One

important

DCM

subtype

characterized

by

cardiac

inflammation

is

designated

as

inflammatory

cardiomyopathy

-LRB-

DCMi

-RRB-

often

found

in

conjunction

with

cardiac

viral

infections

Spontaneous

elimination

of

cardiac

viruses

was

associated

with

significant

hemodynamic

improvement

for

various

viruses

-LSB-

-RSB-

and

interferon-β

-LRB-

IFN-β

-RRB-

therapy

was

useful

to

promote

virus

elimination

and

improve

cardiac

function

and

clinical

status

-LSB-

-RSB-

A

search

for

new

therapeutic

targets

in

DCMi

seems

worthwhile

due

to

the

high

prevalence

of

this

condition

and

its

still

unsatisfactory

long-term

outcome

The

current

study

combined

in

vivo

and

in

vitro

methods

to

identify

possible

DCMi-related

gene

regulatory

networks

that

might

be

exploited

to

expand

the

therapeutic

repertoire

beyond

the

standard

heart

failure

drugs

currently

used

The

study

does

not

address

individual

gene

deregulations

but

searches

for

disturbances

of

regulatory

gene

networks

reflected

by

anomalous

cardiac

expression

patterns

Genomic

screening

strategies

require

precise

phenotyping

of

the

study

groups

as

this

will

minimize

interindividual

differences

and

increase

the

likelihood

of

revealing

distinctive

pathomechanisms

Because

in

advanced

stages

of

DCM

such

processes

are

most

likely

overwhelmed

by

unspecific

reactions

of

the

failing

heart

long

after

the

initiating

process

has

burnt

out

we

investigated

patients

with

moderately

severe

disease

in

contrast

to

most

previous

microarray

work

in

the

field

-LSB-

-RSB-

The

standard

clinical

characterization

was

refined

by

endomyocardial

biopsy

-LRB-

EMB

-RRB-

based

immunohistological

and

molecular

virological

analyses

In

contrast

to

multiple

fields

of

cancer

research

restrictive

disease

phenotyping

of

this

kind

is

rarely

employed

in

cardiovascular

research

mostly

due

to

the

difficult

access

to

affected

cardiovascular

tissues

in

humans

in

vivo

The

microarray

part

of

our

study

was

entirely

based

on

RNA

isolated

from

EMBs

thus

providing

an

approach

suitable

for

follow-up

investigations

of

clinical

courses

in

relation

to

cardiac

expression

profiles

We

report

on

a

distinctive

cardiac

expression

pattern

in

DCMi

and

two

significantly

altered

gene

networks

centered

around

the

cysteine-rich

angiogenic

inducer

-LRB-

-RRB-

and

adiponectin

-LRB-

APN

-RRB-

gene

Patients

and

methods

Characterization

of

study

groups

The

patients

investigated

by

microarray

analysis

of

cardiac

gene

expression

displayed

the

distinct

DCM

subtype

of

DCMi

as

defined

by

the

World

Health

Organization

and

characterized

by

its

association

with

cardiac

inflammation

The

DCMi

group

of

this

study

was

derived

from

a

large

series

of

patients

initially

submitted

to

our

clinic

with

symptoms

and

signs

of

DCM

in

all

of

whom

EMBs

from

the

right

ventricular

septum

were

obtained

by

standard

procedure

for

histological

immunohistological

and

molecular

virological

analyses

All

patients

had

given

written

informed

consent

After

standard

clinical

morphological

and

functional

patient

characterization

their

EMBs

were

assessed

for

myocardial

inflammation

by

histological

and

immunohistological

methods

Their

cardiac

virological

status

was

assessed

by

polymerase

chain

reaction

-LRB-

PCR

-RRB-

real-time

polymerase

chain

reaction

-LRB-

RT-PCR

-RRB-

for

the

following

viral

genomes

enteroviruses

adenoviruses

-LRB-

ADV

-RRB-

Epstein

Barr

virus

human

herpesvirus

-LRB-

-RRB-

and

parvovirus

-LRB-

-RRB-

Eight

DCMi

patients

with

cardiac

inflammation

in

association

with

cardiac

were

selected

for

the

microarray

study

-LRB-

DCMi

group

Table

-RRB-

This

group

was

compared

to

a

control

group

of

four

individuals

submitted

to

our

clinic

and

diagnosed

to

clarify

a

clinically

suspected

cardiomyopathy

in

whom

the

full

differential

diagnostic

workup

finally

revealed

that

their

complaints

were

noncardiac

in

origin

-LRB-

Cont

group

Table

-RRB-

They

had

normal

cardiac

morphology

and

function

were

negative

for

cardiac

inflammation

or

viral

genomes

and

were

subjected

to

microarray

analysis

too

The

DCMi

group

patients

were

on

standard

heart

failure

medication

and

in

New

York

Heart

Association

functional

class

II

-LRB-

Table

-RRB-

Table

of

study

groupsCodeGroupAge

-LRB-

years

-RRB-

EF

-LRB-

-RRB-

LVEDD

-LRB-

mm

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

EF

ejection

fraction

LVEDD

left

ventricular

end-diastolic

diameter

INFLAM

cardiac

inflammation

parvovirus

EV

enterovirus

AdV

adenovirus

human

herpesvirus

EBV

Epstein

Barr

virus

High

density

microarray

studies

of

human

cardiac

biopsies

cDNA

was

synthesized

from

ng

of

total

RNA

isolated

from

EMBs

The

minimal

amount

of

total

RNA

routinely

available

from

human

EMBs

was

ng

cRNA

targets

were

generated

using

the

small

sample

protocol

of

Affymetrix

Briefly

in

vitro

transcribed

unlabeled

cRNA

from

the

first

round

of

amplification

was

subjected

to

a

second

round

of

amplification

cRNA

was

transcribed

into

cDNA

using

random

primers

After

RNAse

H-mediated

removal

of

surplus

cRNA

a

second

strand

was

synthesized

using

a

primer

cRNA

amount

was

determined

by

ultraviolet

spectroscopy

and

distribution

of

cRNA

fragment

sizes

of

both

cRNA

and

fragmentation

products

was

checked

on

a

BioAnalyzer

Each

cRNA

sample

was

hybridized

for

h

at

°C

to

an

Affymetrix

Human

Genome

Plus

GeneChip

Array

Chips

were

washed

and

stained

with

streptavidin

phycoerythrin

using

a

fluidics

station

according

to

Affymetrix

protocols

Probe

arrays

were

scanned

at

resolution

using

the

Affymetrix

GeneChip

System

Confocal

Scanner

Raw

data

were

analyzed

with

Affymetrix

GeneChip

Operating

Software

The

detection

p

value

of

a

transcript

determines

the

detection

call

indicating

if

the

transcript

is

reliably

detected

-LRB-

p

present

-RRB-

or

not

detected

-LRB-

absent

-RRB-

To

enable

the

comparison

between

chips

data

were

normalized

to

a

global

intensity

of

The

expression

data

can

be

obtained

from

the

Gene

Expression

Omnibus

-LRB-

GEO

-RRB-

website

GEO

experimental

series

number

For

TaqMan

experiments

to

verify

candidate

genes

see

next

chapter

Quantitative

real-time

PCR

analysis

of

human

cardiac

biopsies

Total

RNA

was

extracted

using

TRIzol

reagent

-LRB-

Invitrogen

-RRB-

Quality

and

quantity

was

checked

on

a

Agilent

Bioanalyzer

A

minimal

amount

of

only

ng

of

total

RNA

was

routinely

available

from

human

EMBs

for

cDNA

synthesis

to

become

reverse

transcribed

using

the

High

Capacity

cDNA

Archive

Kit

-LRB-

Applied

-RRB-

according

to

the

manufacturers

instructions

For

determination

of

gene

expression

quantitative

PCR

assays

were

performed

on

an

ABI

PRISM

Sequence

Detector

-LRB-

Applied

-RRB-

with

TaqMan

Universal

PCR

Master

Mix

and

TaqMan

Gene

expression

assays

-LRB-

Applied

-RRB-

consisting

of

a

FAM

dye-labeled

TaqMan

MGB

probe

and

two

PCR

primers

The

following

oligonucleotide

sets

purchased

from

Applied

Biosystems

were

used

human

genes

encoding

APN

-LRB-

-RRB-

-LRB-

-RRB-

chemokine

ligand

-LRB-

-RRB-

Ras-responsive

element

protein

-LRB-

-RRB-

GTP

binding

protein

overexpressed

in

skeletal

muscle

-LRB-

GEM

-RRB-

membrane

protein

palmitoylated

-LRB-

-RRB-

dehydrogenase

-LRB-

GAPDH

-RRB-

and

hypoxanthine

phosphoribosyltransferase

-LRB-

-RRB-

Quantitative

RT-PCR

reactions

were

performed

using

standard

cycle

parameters

determined

by

the

company

Normalization

and

fold

change

were

calculated

with

the

ΔΔCt

method

with

GAPDH

and

as

reference

mRNA

species

according

to

ABI

Prism

manufacturer

's

instructions

-LSB-

-RSB-

The

values

given

in

Supplementary

Fig.

are

the

means

SEM

of

two

independent

quantitative

TaqMan

PCRs

performed

on

RNA

isolated

from

the

same

EMB

that

was

also

used

for

the

microarray

analysis

Cardiovascular

cell

cultures

Primary

culture

of

neonatal

rat

cardiomyocytes

-LRB-

NRCMC

-RRB-

Cells

were

prepared

from

ventricular

tissue

of

to

Wistar

rat

pups

-LRB-

Charles

River

-RRB-

as

described

previously

-LSB-

-RSB-

Briefly

the

removed

ventricles

of

animals

were

placed

into

ice-cold

calcium

ion-free

phosphate-buffered

cell

isolation

medium

-LRB-

CIM

-RRB-

containing

mM

NaCl

mM

KCl

mM

mM

mM

and

mM

glucose

pH

as

well

as

mg/ml

streptomycin

and

IE/ml

penicillin

G

-LRB-

Biochrom

-RRB-

Ventricular

tissue

was

transferred

to

a

Petri

dish

and

minced

into

pieces

of

approximately

in

size

using

two

sterile

scalpels

Stepwise

disaggregation

for

min

each

of

tissue

pieces

into

single

cells

was

performed

at

°C

under

continuous

mixing

with

a

magnetic

stirrer

at

rpm

in

a

ml

Erlenmeyer

flask

containing

CIM

supplemented

with

porcine

trypsin

-LRB-

Belger

-RRB-

The

first

tissue

digest

was

discarded

The

following

three

to

eight

supernatants

obtained

after

each

digestion

period

were

poured

into

single

sterile

glass

centrifuge

tubes

each

containing

ml

of

ice-cold

heat-inactivated

fetal

calf

serum

-LRB-

FCS

Biochrom

-RRB-

Cells

were

gently

sedimented

at

g

for

min

The

sedimented

cells

were

resuspended

in

cell

growth

medium

CMRL

-LRB-

CMRL-ATM

Connaught

Medical

Research

Laboratories-atmospheric

-RRB-

that

was

supplemented

with

FCS

horse

serum

-LRB-

HS

-RRB-

and

mg/ml

gentamicin

-LRB-

all

from

Biochrom

-RRB-

and

adjusted

to

pH

using

N

NaOH

For

enrichment

of

cardiomyocytes

ml

of

this

suspension

containing

approximately

cardiac

cells

were

incubated

in

plastic

dishes

Corning

culture

flask

in

a

water-saturated

atmosphere

for

min

at

°C

During

this

incubation

most

of

the

nonmuscle

cells

comprising

of

total

cell

number

attached

to

the

bottom

surface

of

the

culture

flask

The

cardiomyocyte-enriched

supernatant

was

carefully

removed

and

pooled

in

an

Erlenmeyer

flask

The

number

of

cells

was

counted

using

a

light

microscope

and

a

hemocytometer

The

cell

density

was

adjusted

with

additional

growth

medium

to

cells/ml

and

the

cells

seeded

to

Nunc

culture

plates

and

incubated

in

a

water-saturated

atmosphere

at

°C

After

h

of

incubation

the

FCS/HS-supplemented

growth

medium

was

replaced

either

by

a

FCS-supplemented

CMRL

or

serum-free

hormone-supplemented

CMRL

medium

containing

fluorodeoxfyuridine

-LRB-

Sigma

-RRB-

for

inhibition

of

proliferation

of

contaminating

nonmuscle

cells

Vascular

endothelial

cell

line

The

endothelial

cell

line

-LRB-

a

hybrid

line

derived

from

human

umbilical

vein

endothelial

cells

and

cells

-RRB-

was

cultured

in

Dulbecco

's

modified

Eagle

's

medium

supplemented

with

hypoxanthine

aminopterin

thymidine

FCS

and

penicillin

and

streptomycin

Quantitative

real-time

PCR

analysis

of

activated

cell

cultures

To

study

regulatory

factors

of

and

APN

in

cultured

cardiovascular

cells

-LRB-

Fig.

b

-RRB-

NRCMCs

were

grown

in

and

cells

in

dishes

for

h.

Thereafter

they

were

incubated

for

h

with

the

following

cytokines

-LRB-

concentrations

-RRB-

-LRB-

ng/ml

-RRB-

-LRB-

ng/ml

-RRB-

IFN-γ

-LRB-

ng/ml

-RRB-

-LRB-

ng/ml

-RRB-

-LRB-

ng/ml

-RRB-

tumor

necrosis

factor

-LRB-

TNF

-RRB-

α

-LRB-

ng/ml

-RRB-

and

TNF-β

-LRB-

ng/ml

-RRB-

In

some

experiments

-LRB-

Fig.

-RRB-

cells

were

preincubated

for

h

with

APN

-LRB-

μg/ml

-RRB-

before

the

addition

of

the

above

cytokines

This

APN

concentration

was

chosen

because

the

APN

plasma

range

in

humans

is

μg/ml

Cells

were

harvested

h

after

cytokine

addition

Of

the

total

RNA

to

μg

were

isolated

from

cell

cultures

to

become

reverse

transcribed

using

the

High

Capacity

cDNA

Archive

Kit

and

TaqMan

PCRs

were

then

carried

out

employing

the

following

primer

systems

-LRB-

Applied

-RRB-

for

the

rat

genes

encoding

APN

-LRB-

Acdc

-RRB-

-LRB-

-RRB-

and

GAPD

-LRB-

-RRB-

mRNA

amounts

were

standardized

against

the

housekeeping

gene

GAPDH

The

values

given

in

Fig.

b

are

the

means

SEM

of

two

independent

experiments

each

performed

in

triplicate

Network

analysis

The

networks

shown

in

Fig.

c

e

were

derived

by

the

Ingenuity

Pathways

Analysis

-LRB-

IPA

-RRB-

software

The

microarray

dataset

containing

gene

identifiers

and

corresponding

expression

values

was

uploaded

as

an

Excel

spreadsheet

using

the

template

provided

in

the

application

Each

gene

identifier

was

mapped

to

its

corresponding

gene

object

in

the

Ingenuity

Pathways

Knowledge

Base

-LRB-

IPKB

-RRB-

A

cutoff

of

fold

change

was

set

to

identify

genes

whose

expression

was

significantly

differentially

regulated

these

were

then

used

as

the

starting

point

for

generating

regulatory

networks

Biological

functions

were

assigned

to

each

network

or

the

overall

analysis

respectively

by

using

the

findings

that

have

been

extracted

from

the

scientific

literature

and

stored

in

the

IPKB

The

biological

functions

assigned

to

each

network

or

the

overall

analysis

respectively

are

ranked

according

to

the

significance

of

that

biological

function

to

the

network

or

the

overall

analysis

respectively

A

Fischer

's

exact

test

is

used

to

calculate

a

p

value

determining

the

probability

that

the

biological

function

assigned

to

that

network

is

explained

by

chance

alone

The

networks

are

displayed

graphically

as

nodes

-LRB-

genes/gene

products

-RRB-

and

edges

-LRB-

the

biological

relationships

between

the

nodes

-RRB-

Human

mouse

and

rat

orthologs

of

a

gene

are

stored

as

separate

objects

in

the

knowledge

base

but

are

represented

as

a

single

node

in

the

network

The

intensity

of

the

node

color

indicates

the

degree

of

up

-LRB-

red

-RRB-

or

down

-LRB-

green

-RRB-

regulation

Nodes

are

displayed

using

various

shapes

that

represent

the

functional

class

of

the

gene

product

Edges

are

displayed

with

various

labels

that

describe

the

nature

of

the

relationship

between

the

nodes

-LRB-

e.g.

B

for

binding

T

for

transcription

-RRB-

Fig.

gene

expression

profile

and

regulatory

networks

in

DCMi

a

c

e

The

networks

altered

in

DCMi

are

displayed

graphically

as

nodes

-LRB-

genes/gene

products

-RRB-

and

edges

-LRB-

biological

relationships

between

the

nodes

-RRB-

Human

mouse

and

rat

orthologs

of

a

gene

are

stored

as

separate

objects

in

the

knowledge

base

but

are

represented

as

a

single

node

in

the

network

The

intensity

of

the

node

color

indicates

the

degree

of

up

-LRB-

red

-RRB-

or

down

-LRB-

green

-RRB-

regulation

Nodes

are

displayed

using

various

shapes

that

represent

the

functional

class

of

the

gene

product

Continuous

edge

lines

indicate

protein

protein

interactions

broken

edge

lines

changes

at

the

transcriptional

level

The

software

further

displays

various

labels

that

describe

the

nature

of

the

relationship

between

the

nodes

-LRB-

e.g.

B

for

binding

T

for

transcription

-RRB-

b

d

f

Show

cluster

analyses

of

the

genes

within

the

networks

in

-LRB-

a

-RRB-

-LRB-

c

-RRB-

-LRB-

e

-RRB-

respectively

Here

analogous

to

the

networks

red

color

denotes

upregulation

green

color

denotes

downregulation

of

a

gene

whereas

the

brightness

of

the

color

indicates

the

extent

of

deregulation

Statistical

analysis

For

statistical

analysis

of

microarray

data

we

used

the

significance

analysis

of

microarrays

-LRB-

SAM

-RRB-

SAM

statistics

identifies

significant

changes

in

gene

expression

by

performing

a

set

of

gene-specific

t-tests

For

each

gene

a

score

is

calculated

on

the

basis

of

its

change

of

expression

relative

to

the

standard

deviation

of

repeated

measurements

for

that

gene

Genes

with

scores

greater

than

a

given

threshold

Δ

are

defined

as

significantly

deregulated

Manual

adjustment

of

this

threshold

Δ

allows

the

identification

of

smaller

or

larger

cohorts

of

genes

In

addition

a

false

discovery

rate

can

be

estimated

based

on

random

permutations

of

all

measurements

With

respect

to

quantitative

TaqMan

PCRs

Student

's

t-test

was

applied

to

demonstrate

statistical

significance

A

value

of

p

was

considered

statistically

significant

Results

Because

in

advanced

or

end-stage

DCM

any

etiology-related

pathomechanisms

are

most

likely

overwhelmed

by

unspecific

reactions

of

the

terminally

failing

myocardium

long

after

the

initiating

process

has

burnt

out

we

studied

patients

with

moderately

severe

disease

-LRB-

Table

-RRB-

The

standard

clinical

characterization

was

refined

by

EMB-based

immunohistological

-LRB-

Supplementary

Fig.

-RRB-

and

molecular

virological

analyses

The

DCMi

group

was

characterized

by

myocardial

inflammation

in

association

with

A

distinctive

expression

profile

was

detected

in

the

DCMi

group

by

microarray

analysis

of

the

EMBs

The

complete

dataset

is

available

from

the

website

Genes

significantly

-LRB-

q

value

-RRB-

and

deregulated

are

listed

in

Supplementary

Table

Subsequently

a

network

analysis

of

the

complete

dataset

with

genes

down

and

genes

up-regulated

was

performed

as

shown

in

Fig.

f.

Several

of

these

genes

were

validated

by

quantitative

TaqMan

PCR

-LRB-

Table

Supplementary

Fig.

-RRB-

Whereas

confirmatory

PCR

analysis

was

desirable

for

a

major

number

of

DCMi-associated

genes

the

limited

mRNA

quantity

available

from

human

EMBs

confined

the

number

of

such

analyses

The

minimal

amount

of

total

RNA

available

from

EMBs

for

both

microarrays

and

confirmatory

PCR

was

only

ng

The

genes

selected

for

confirmatory

PCRs

are

shown

in

Supplementary

Fig.

They

include

APN

and

GEM

as

novel

deregulated

genes

associated

with

DCMi

natriuretic

peptide

precursor

A

-LRB-

NPPA

-RRB-

and

natriuretic

peptide

precursor

B

-LRB-

NPPB

-RRB-

as

standard

heart

failure-associated

genes

and

confirmed

the

microarray

data

in

all

cases

The

microarray

q

values

for

each

of

the

genes

in

Supplementary

Fig.

the

corresponding

p

values

in

the

confirmatory

TaqMan

PCRs

and

similar

regulatory

factors

are

proof

of

deregulation

of

these

genes

of

particular

interest

Table

cardiac

gene

expression

profile

of

human

DCMi

-LRB-

further

data

at

and

in

Supplementary

Table

-RRB-

NetworkSymbolRegulationFactorq

valueGene

Chemokine

-LRB-

C

X

C

motif

-RRB-

ligand

144.4AKTTDGF1Down4.70.605Teratocarcinoma-derived

growth

factor

growth

factor

-LRB-

PDGF

-RRB-

α

Son

of

sevenless

homolog

-LRB-

Drosophila

-RRB-

CYRTMSB10Down2.60.371Thymosin-β10APNINSRDown2.50

Insulin

Epidermal

growth

factor

-LRB-

EGF

-RRB-

regulatory

subunit

-LRB-

-RRB-

Laminin

-LRB-

LIM

-RRB-

domain

only

Heparan

sulfate

proteoglycan

Sex

determining

region

Y

-LRB-

SRY

-RRB-

box

Leukemia

inhibitory

factor

-LRB-

LIF

-RRB-

Tenascin

receptor

III

-LRB-

betaglycan

-RRB-

Eukaryotic

translation

initiation

factor

binding

protein

Slit

homolog

-LRB-

Drosophila

-RRB-

growth

factor

binding

protein

angiogenic

inducer

Thrombospondin

Signal

transducer

and

activator

of

transcription

Ankyrin

repeat

domain

-LRB-

cardiac

muscle

-RRB-

Integrin

β1

β-subunit

of

fibronectin

receptor

-LRB-

-RRB-

neurotrophic

Matrin

Janus

kinase

Solute

carrier

family

member

EGF-like

growth

factorCYRCD47Up2.14.108Integrin-associated

signal

Fibroblast

growth

factor

-LRB-

basic

-RRB-

EPH

receptor

Syntaxin

Platelet

derived

growth

factor

Protein

tyrosine

kinase

Protein

tyrosine

phosphatase

non-receptor

type

Golgi

SNAP

receptor

complex

member

Nuclear

factor

of

activated

T

cells

Baculoviral

IAP

repeat-containing

XIAP

associated

Protein

phosphatase

regulatory

subunit

A

SWI/SNF

related

matrix

associated

regulator

of

chromatin

Midline

Lipoprotein

lipaseCYRLAMA2Up1.81.994Laminin-α2AKTGSK3BUp1.80

Glycogen

synthase

kinase

Protein

phosphatase

regulatory

subunit

B

Synaptotagmin

binding

RNA

interacting

Protein

phosphatase

regulatory

subunit

B

regulator

of

nonsense

transcripts

A

Adiponectin

receptor

Tissue

factor

pathway

Sorting

nexin

Sorting

nexin

Retinoblastoma

binding

protein

protein

Vacuolar

protein

sorting

Nuclear

factor

of

activated

T

cells

Nuclear

factor

of

activated

T

cells

Janus

kinase

transcription

binding

protein

Syntaxin

Proline

arginine-rich

end

leucine-rich

repeat

simian

leukemia

viral

oncogene

homolog

Fibroblast

growth

factor

Transforming

growth

factor-β

receptor

Fused

toes

murine

thymoma

viral

oncogene

homolog

Protein

phosphatase

catalytic

subunit

αAll

factors

of

deregulations

are

derived

from

the

Affymetrix

microarray

analysis

For

certain

genes

additional

TaqMan

analyses

were

conducted

which

are

then

given

in

italics

below

the

respective

Affymetrix

values

-LRB-

see

also

Supplementary

Fig.

-RRB-

aPlease

note

the

synonyma

APN

ADIPOQ

The

network

analysis

of

the

microarray

data

-LSB-

-RSB-

was

conducted

by

the

IPA

software

employing

the

genes

significantly

-LRB-

q

value

-RRB-

and

deregulated

IPA

is

based

on

modeled

biological

networks

derived

from

information

of

peer-reviewed

scientific

publications

Analysis

of

our

data

revealed

several

strongly

altered

regulatory

networks

The

gene

networks

shown

in

Fig.

c

e

have

not

been

previously

described

in

former

microarray

studies

of

DCM

-LRB-

details

in

discussion

-RRB-

One

of

these

networks

centered

around

the

or

gene

-LRB-

Fig.

b

-RRB-

another

one

around

the

APN

gene

-LRB-

Fig.

d

-RRB-

These

networks

are

related

to

cell-to-cell

signaling

and

cellular

compromise

Another

network

around

the

gene

-LRB-

Fig.

f

-RRB-

also

deserves

consideration

because

is

involved

in

the

regulation

of

both

-LSB-

-RSB-

and

APN

-LSB-

-RSB-

and

because

APN

strongly

influences

expression

in

vitro

-LRB-

Fig.

-RRB-

Table

summarizes

all

member

genes

of

these

three

networks

with

full

gene

names

q

values

and

fold

changes

Those

two

genes

-LRB-

APN

-RRB-

that

were

among

the

most

strongly

deregulated

and

at

the

same

time

key

components

of

complex

deregulated

networks

were

further

investigated

in

cardiovascular

cell

cultures

in

vitro

-LRB-

Fig.

b

-RRB-

Fig.

regulating

of

APN

and

in

cardiovascular

cells

We

searched

for

possible

triggers

of

cardiac

APN

and

deregulation

in

DCMi

in

both

endothelial

cells

and

cardiomyocytes

a

b

Summarize

real-time

quantitative

TaqMan

PCR

data

on

the

regulatory

potential

of

inflammatory

cytokines

in

these

cell

cultures

investigated

as

first

approximation

to

the

far

more

complex

in

vivo

situation

with

multiple

resident

and

infiltrating

cell

types

-LRB-

compare

Fig.

-RRB-

a

Endothelial

cells

expressed

and

both

APN

receptors

but

no

detectable

amount

of

APN

mRNA

-LRB-

data

not

shown

-RRB-

The

inflammatory

cytokines

TNF-α

and

IFN-β

induced

expression

in

these

cells

whereas

others

showed

no

effect

-LRB-

IFN-γ

-RRB-

or

even

reduced

-LRB-

TNF-β

-RRB-

To

reveal

possible

interactions

between

the

APN

and

regulatory

networks

induction

experiments

were

conducted

in

the

presence

-LRB-

asterisksin

shaded

bars

-RRB-

vs

the

absence

of

APN

The

effect

of

APN

on

induction

by

cytokines

was

unexpectedly

strong

induction

of

by

TNF-α

or

IFN-β

was

not

only

abolished

but

reverted

resulting

in

a

net

reduction

of

expression

below

that

in

untreated

controls

The

APN

concentration

at

which

effect

was

observed

is

in

the

range

μg/ml

as

observed

in

human

plasma

-LSB-

-RSB-

Error

bars

indicate

the

SEM

from

two

independent

experiments

each

performed

in

triplicate

b

In

contrast

to

endothelial

cells

cardiomyocytes

expressed

APN

and

its

receptors

as

well

as

Several

inflammatory

cytokines

-LRB-

TNF-α

IFN-β

γ

-RRB-

significantly

reduced

APN

expression

in

cardiomyocytes

whereas

expression

was

not

significantly

altered

in

this

cell

type

-LRB-

not

shown

-RRB-

Error

bars

as

in

panel

-LRB-

a

-RRB-

The

APN

regulatory

network

contains

significantly

deregulated

-LRB-

q

value

change

-RRB-

genes

not

previously

reported

in

microarray

studies

of

DCM

-LRB-

full

gene

names

in

Table

-RRB-

up

up

HBEGF

up

up

up

LPL

up

up

up

APN

down

INSR

down

down

LIFR

down

TNXB

down

and

down

Three

genes

encoding

the

nuclear

factors

of

activated

T

cells

-LRB-

NFAT

-RRB-

-LRB-

up

-RRB-

-LRB-

up

-RRB-

-LRB-

up

-RRB-

are

also

linked

to

the

APN

network

as

negative

regulators

of

APN

expression

-LSB-

-RSB-

Similarly

the

gene

-LRB-

up

-RRB-

encoding

the

APN

receptor

gene

is

part

of

the

APN

signal

transduction

system

A

second

regulatory

network

around

contains

further

deregulated

genes

with

q

value

and

change

-LRB-

full

gene

names

in

Table

-RRB-

up

up

up

up

up

NES

up

PDGFC

up

up

up

up

up

TFPI

up

down

PDGFA

down

down

EGFR

down

down

down

TNXB

and

down

A

recent

publication

also

links

to

Wnt

signaling

pathways

-LSB-

-RSB-

and

several

Wnt

signal

pathway

genes

were

deregulated

in

DCMi

up

GCLM

up

up

up

up

INSR

down

down

and

down

In

addition

to

the

multifunctional

and

APN

genes

several

other

deregulated

genes

are

known

to

be

involved

in

immunological

and

inflammatory

processes

The

gene

was

and

the

neurturin

-LRB-

NRTN

-RRB-

gene

downregulated

in

DCMi

The

-LRB-

-RRB-

gene

a

member

of

to

F

gene

family

was

induced

serum

levels

were

elevated

in

DCMi

patients

-LRB-

not

shown

-RRB-

Altered

intracardiac

immune

regulation

is

further

suggested

by

upregulation

of

the

immediate

early

response

-LRB-

-RRB-

and

-LRB-

-RRB-

genes

ubiquitin-specific

protease

-LRB-

-RRB-

phospholipase

protein

-LRB-

PLAA

-RRB-

and

IFN-related

developmental

regulator

-LRB-

-RRB-

Induction

of

the

neural

cell

adhesion

molecule

-LRB-

-RRB-

gene

-LSB-

-RSB-

and

the

coxsackie

virus

ADV-receptor

-LRB-

CXADR

-RRB-

gene

-LSB-

-RSB-

already

known

from

immunohistochemical

studies

of

DCMi

hearts

were

recognized

by

the

microarrays

too

As

a

first

step

to

elucidate

the

molecular

mechanisms

that

deregulate

and

APN

expression

in

human

DCMi

cell

culture

studies

were

conducted

Both

genes

were

significantly

deregulated

in

DCMi

as

components

of

complex

gene

networks

Figure

shows

that

certain

inflammatory

cytokines

induced

expression

in

vascular

endothelial

cell

cultures

similarly

as

observed

in

the

DCMi

hearts

This

induction

by

TNF-α

and

IFN-β

was

completely

abolished

in

the

presence

of

APN

-LRB-

Fig.

-RRB-

The

APN

plasma

range

in

humans

is

μg/ml

-LSB-

-RSB-

and

the

concentration

therefore

chosen

for

the

cell

culture

investigations

was

μg/ml

At

this

concentration

APN

generally

suppressed

the

expression

level

in

this

cell

type

In

cardiomyocytes

TNF-α

IFN-β

IFN-γ

and

all

significantly

reduced

the

expression

of

APN

-LRB-

Fig.

-RRB-

whereas

expression

was

not

affected

by

these

cytokines

in

this

cell

type

Several

other

deregulated

genes

of

interest

known

to

be

involved

in

immunological

and

inflammatory

processes

were

neither

expressed

in

endothelial

cells

nor

in

cardiomyocytes

and

therefore

could

not

be

studied

in

these

cell

biological

models

Discussion

Identification

of

DCM

subtypes

DCM

is

the

term

used

to

describe

any

clinical

phenotype

characterized

by

dilation

and

dysfunction

of

the

cardiac

ventricles

From

an

etiologic

perspective

however

DCM

encompasses

a

diverse

spectrum

of

disease

entities

some

of

which

are

due

to

monogenic

defects

in

cardiac

expressed

genes

-LSB-

-RSB-

others

triggered

by

exogenous

factors

including

cardiotropic

viruses

-LSB-

-RSB-

Therapies

directed

at

etiology-related

pathogenic

pathways

in

these

etiologically

distinct

DCM

subtypes

may

be

more

efficient

than

current

standard

treatment

protocols

employed

in

heart

failure

of

any

origin

However

etiology-related

early

pathogenic

pathways

must

be

assumed

to

prevail

only

in

the

beginnings

of

the

respective

DCM

subtype

whereas

common

unspecific

molecular

pathomechanisms

will

predominate

in

advanced

heart

failure

irrespective

of

etiology

One

important

DCM

subtype

as

defined

by

cardiac

inflammation

was

investigated

in

the

current

study

to

further

define

it

at

the

molecular

level

Whereas

previous

studies

focused

on

advanced

or

end-stage

DCM

-LSB-

-RSB-

where

specific

pathomechanisms

are

overwhelmed

by

unspecific

processes

we

probed

an

earlier

and

restrictively

defined

phenotype

-LRB-

DCMi

-RRB-

to

identify

early

and

etiology-related

disease

processes

Importantly

our

patients

were

not

terminally

ill

nor

on

maximum

supportive

therapy

as

in

previous

studies

of

advanced

DCM

Similarly

controls

had

no

severe

underlying

condition

as

e.g.

heart

transplantation

donor

hearts

often

used

as

controls

for

expression

profiles

but

were

free

of

cardiac

disease

after

comprehensive

exclusion

of

multiple

cardiac

differential

diagnoses

Further

any

search

for

etiology-related

pathomechanisms

is

more

likely

successful

if

the

study

groups

are

highly

homogenous

An

excellent

previous

study

has

also

defined

its

patient

groups

by

clinical

morphological

and

hemodynamic

phenotyping

-LSB-

-RSB-

and

derived

interesting

data

on

common

expression

profiles

in

disorders

linked

by

common

hemodynamic

anomalies

We

likewise

defined

a

highly

homogeneous

study

group

by

sequential

stratification

of

a

large

DCM

patient

cohort

first

by

standard

clinical

morphological

and

hemodynamic

criteria

second

by

biopsy-based

detection

of

cardiac

inflammation

in

conjunction

with

a

cardiotropic

virus

Cardiac

inflammation

in

our

patients

was

associated

with

the

presence

of

genomes

in

the

myocardium

We

think

however

that

the

observed

anomalous

expression

pattern

probably

reflects

a

general

inflammatory

pathomechanism

that

may

be

triggered

by

diverse

proinflammatory

stimuli

After

the

current

pilot

study

all

the

key

genes

of

this

anomalous

pattern

need

to

be

further

investigated

in

major

patient

groups

with

varying

degrees

of

cardiac

inflammation

and

hemodynamic

impairment

to

address

issues

of

specificity

and

dynamic

In

vivo

biopsies

on

which

the

current

study

was

entirely

based

further

provide

the

perspective

for

follow-up

studies

of

the

clinical

courses

that

would

then

add

a

third

stratification

criterion

for

patient

selection

to

be

used

in

the

future

Cardiac

expression

profile

of

DCMi

The

anomalous

cardiac

expression

pattern

observed

for

human

DCMi

was

not

described

in

previous

studies

of

human

cardiac

diseases

or

heart

failure

of

any

origin

-LSB-

-RSB-

Most

network

genes

listed

in

Table

and

in

particular

and

APN

have

to

our

knowledge

not

been

found

to

be

deregulated

in

human

microarray

studies

and

also

not

in

animal

models

of

DCM

A

comprehensive

recent

review

-LSB-

-RSB-

summarizes

that

the

major

molecular

pathway

changes

in

human

DCM

and

other

human

cardiomyopathies

encompass

sarcomeric

cytoskeletal

extracellular

matrix

homeostasis

apoptosis

and

energy

metabolism

genes

Major

deregulations

of

inflammation

and

immune

system-associated

genes

as

in

DCMi

were

not

included

Because

we

investigated

a

DCM

subtype

associated

with

intracardiac

inflammation

a

recent

microarray

study

of

two

giant

cell

myocarditis

patients

-LSB-

-RSB-

is

of

specific

interest

for

comparison

That

study

addressed

an

immunohistologically

defined

inflammatory

cardiac

phenotype

clearly

different

from

that

in

our

study

and

found

deregulated

T

cell

activation

genes

including

receptor-α

chemokine

receptor

and

chemokine

ligands

and

Remarkably

of

the

latter

genes

was

deregulated

in

DCMi

but

only

Conversely

and

gene

upregulations

and

APN

gene

downregulation

as

observed

in

DCMi

were

not

observed

in

the

giant

cell

myocarditis

study

This

appears

to

reflect

distinct

immunological

pathomechanisms

The

gene

and

its

associated

network

showed

particularly

strong

deregulation

in

DCMi

is

a

member

of

the

CCN

gene

family

-LSB-

-RSB-

-LRB-

also

including

connective

tissue

growth

factor

-LSB-

CTGF

-RSB-

-RRB-

and

has

already

attracted

attention

as

a

multifunctional

secreted

protein

able

to

modulate

multiple

cell

functions

It

induces

apoptosis

in

fibroblasts

-LSB-

-RSB-

and

mediates

cell

death

in

neurons

-LSB-

-RSB-

and

in

virus-infected

cells

-LSB-

-RSB-

From

a

therapeutic

perspective

it

is

interesting

that

RNA

interference-mediated

silencing

of

the

gene

protected

cells

against

cell

death

whereas

overexpression

enhanced

it

-LSB-

-RSB-

Moreover

coordinates

genes

that

control

inflammation

-LRB-

-RRB-

extracellular

matrix

remodeling

-LRB-

e.g.

-RRB-

cell

extracellular

matrix

interactions

and

angiogenesis

-LSB-

-RSB-

acts

in

a

cell

type

and

context-dependent

manner

through

direct

binding

to

at

least

five

distinct

integrins

including

α6β1

and

heparan

sulfate

proteoglycans

as

co-receptors

-LSB-

-RSB-

integrins

αvβ3

and

αvβ5

-LSB-

-RSB-

and

integrin

αMβ2

on

blood

monocytes

-LSB-

-RSB-

is

involved

in

integrin-linked

kinase-mediated

AKT

and

β-catenin-T

cell

factor/Lef

signaling

-LSB-

-RSB-

It

is

also

regulated

by

canonical

Wnt

signaling

and

involved

in

mesenchymal

stem

cell

differentiation

-LSB-

-RSB-

In

contrast

to

this

wealth

of

data

on

in

vitro

actions

of

data

on

its

physiological

functions

and

pathogenic

potential

in

humans

are

sparse

upregulation

has

only

recently

been

described

in

end-stage

ischemic

cardiomyopathy

-LSB-

-RSB-

The

current

work

shows

for

the

first

time

induction

in

an

inflammatory

cardiac

disorder

with

far

less

severe

clinical

phenotype

where

most

likely

no

irreversible

cardiac

damage

has

yet

occurred

Cardiac

expression

is

apparently

induced

by

multiple

stimuli

-LSB-

-RSB-

including

inflammation

in

vivo

and

inflammatory

cytokines

in

vitro

-LRB-

this

study

-RRB-

Whereas

transient

induction

may

be

a

temporarily

beneficial

response

of

the

heart

to

various

stress

factors

chronic

stimulation

of

the

auto/paracrine

signaling

pathways

activated

by

may

be

maladaptive

and

pathogenic

in

itself

by

e.g.

sustaining

exuberant

tissue

inflammatory

and

remodeling

processes

-LSB-

-RSB-

Our

observation

of

overexpression

in

DCMi

suggests

to

investigate

further

if

modulation

of

auto/paracrine

pathways

might

have

therapeutic

potential

in

cardiac

diseases

associated

with

local

inflammation

In

the

current

study

we

show

for

the

first

time

that

APN

is

synthesized

by

human

hearts

in

situ

not

only

by

adipose

tissues

as

previously

assumed

and

that

this

local

synthesis

is

strongly

downregulated

in

a

human

cardiac

disease

Cultured

cardiomyocytes

were

already

known

to

express

APN

and

both

of

its

receptors

and

secrete

APN

-LSB-

-RSB-

APN

has

encountered

high

interest

in

the

cardiovascular

field

due

to

pioneering

work

in

APN

knockout

mice

proving

important

functions

of

APN

in

the

heart

-LSB-

-RSB-

These

studies

assumed

however

that

cardioprotective

effects

were

exerted

by

APN

synthesized

by

adipose

tissue

and

acting

via

the

circulation

APN

inhibits

apoptosis

and

TNF-α

production

in

cardiomyocytes

modulates

hypertrophic

signals

in

the

heart

-LSB-

-RSB-

and

protects

it

from

ischemic

injury

in

a

mouse

model

-LSB-

-RSB-

APN

regulation

has

not

been

previously

investigated

in

human

hearts

in

situ

Previous

studies

-LSB-

-RSB-

and

the

present

work

suggest

that

cardiac

APN

is

influenced

by

multiple

factors

acting

on

components

of

the

APN

gene

network

is

involved

in

the

regulation

of

both

-LSB-

-RSB-

and

APN

-LSB-

-RSB-

Interestingly

APN

abolished

induction

by

inflammatory

cytokines

in

endothelial

cells

-LRB-

Fig.

-RRB-

Because

multiple

other

endothelial

activation

markers

are

induced

in

DCMi

-LSB-

-RSB-

it

is

of

interest

to

know

the

whole

spectrum

controlled

by

APN

but

this

is

beyond

the

scope

of

the

current

study

In

synopsis

with

a

previous

report

that

APN

inhibits

synthesis

by

endothelial

cells

-LSB-

-RSB-

these

data

suggest

that

local

cardiac

APN

synthesis

is

required

for

adequate

control

of

local

inflammatory

processes

If

so

depression

of

cardiac

APN

synthesis

by

various

mechanism

may

render

the

heart

vulnerable

to

inflammatory

challenges

such

as

imposed

by

infiltrating

immune

cells

in

DCMi

or

under

other

conditions

associated

with

enhanced

cardiac

inflammatory

cytokine

production

-LSB-

-RSB-

Modulation

of

the

local

cardiac

APN

system

may

therefore

have

therapeutic

potential

under

certain

conditions

Due

to

the

complexities

of

the

biological

functions

of

both

and

APN

it

is

impossible

to

predict

the

effects

of

their

modulation

in

vivo

Synopsis

of

previous

work

and

the

current

study

suggests

to

investigate

however

if

modulation

of

the

balance

between

the

and

APN

networks

may

have

therapeutic

potential

in

cardiac

diseases

associated

with

local

inflammation

One

obvious

approach

would

be

cardiac

APN

gene

therapy

another

one

RNA

interference-mediated

suppression

by

cardiac

shRNA

expression

In

addition

to

the

multifunctional

and

APN

proteins

and

interacting

gene

products

such

as

the

NFATs

several

other

deregulated

genes

are

also

directly

involved

in

immunological

and

inflammatory

processes

Two

genes

encoding

proteins

described

as

endothelial

activation

markers

in

DCMi

-LSB-

-RSB-

were

upregulated

-LRB-

-RRB-

and

CXADR

-LRB-

a

component

of

the

network

-RRB-

belongs

to

a

family

of

dendritic

cell

and

monocyte-attracting

chemokine-like

proteins

-LSB-

-RSB-

Loss

of

in

tumors

was

associated

with

low

infiltration

by

dendritic

cells

whereas

its

restoration

caused

dendritic

cell

attraction

in

vitro

and

in

vivo

-LSB-

-RSB-

The

downregulated

NRTN

gene

belongs

to

the

same

family

as

glial

cell

line-derived

neurotrophic

factor

-LRB-

GDNF

-RRB-

GDNF

and

NRTN

signaling

is

mediated

by

a

two-component

receptor

the

signal-transducing

component

RET

shared

by

both

ligands

and

the

ligand-specific

binding

components

-LRB-

GDNF

-RRB-

or

-LRB-

NRTN

-RRB-

Human

T

and

B

cells

and

monocytes

produce

RET

and

NRTN

and

are

transcribed

in

all

immune

cell

subsets

with

being

the

dominant

ligand-binding

chain

in

T

cells

B

cells

and

monocytes

-LSB-

-RSB-

Therefore

NRTN

downregulation

may

alter

immune

cell

communication

whereas

little

is

known

about

its

functions

in

other

cell

types

belongs

to

a

family

of

secreted

proteins

that

play

an

active

role

in

inflammatory

and

autoimmune

diseases

-LSB-

-RSB-

Because

stimulates

production

of

and

granulocyte/macrophage

colony-stimulating

factor

-LRB-

GM-CSF

-RRB-

in

human

endothelial

cells

-LSB-

-RSB-

its

upregulation

may

enhance

the

activation

of

the

endothelium

the

primary

attachment

site

for

migrating

immune

cells

functionally

cooperates

with

TNF-α

-LSB-

-RSB-

enhances

growth

of

vascular

endothelial

cells

-LSB-

-RSB-

and

stimulates

matrix

expression

-LSB-

-RSB-

The

upregulated

PLAA

activates

mammalian

involved

in

inflammatory

responses

-LSB-

-RSB-

Thus

is

upregulated

during

inflammation

stimulates

production

via

extracellular

signal-regulated

kinase

-LRB-

ERK

-RRB-

and

nuclear

factor-κB

in

neutrophils

and

modulates

inflammatory

responses

via

the

receptor

-LSB-

-RSB-

Working

model

of

local

cardiac

inflammation

control

A

working

model

of

a

novel

inflammation-associated

cardiac

pathomechanism

is

outlined

in

Fig.

The

model

proposes

the

existence

and

pathogenic

relevance

of

a

local

inflammation

control

system

in

human

hearts

acting

by

local

synthesis

of

anti-inflammatory

proteins

a

representative

of

which

is

APN

If

local

cardiac

APN

synthesis

by

cardiomyocytes

is

absent

as

in

knockout

mice

-LSB-

-RSB-

or

suppressed

as

in

DCMi

patients

inflammatory

challenges

such

as

imposed

by

cardiac

immune

cell

infiltrations

-LRB-

Supplementary

Fig.

-RRB-

may

result

in

grave

damage

to

vascular

endothelia

and

myocardium

The

model

assumes

that

cardiac

inflammation

control

is

predominantly

mediated

by

auto/paracrine

actions

of

locally

synthesized

APN

whereas

in

the

context

of

cardiac

ischemic

injury

in

APN

knockout

mice

a

complementary

systemic

model

of

APN

action

has

been

proposed

in

which

APN

secreted

by

adipose

tissue

acts

hormone-like

to

protect

the

heart

-LSB-

-RSB-

and

the

endothelia

via

the

circulation

-LSB-

-RSB-

APN

acts

directly

upon

immune

cells

such

as

natural

killer

-LRB-

NK

-RRB-

cells

-LSB-

-RSB-

and

on

nonimmune

cells

such

as

vascular

endothelia

-LSB-

-RSB-

One

new

target

controlled

by

APN

is

that

is

locally

upregulated

in

DCMi

hearts

in

situ

and

whose

endothelial

induction

by

cytokines

is

abolished

by

APN

-LRB-

Fig.

-RRB-

Although

induces

transient

local

inflammation

and

matrix

remodeling

during

healing

processes

-LSB-

-RSB-

its

activity

needs

to

be

controlled

so

that

it

does

not

cause

chronic

tissue

damage

In

addition

to

such

direct

anti-inflammatory

actions

of

APN

upon

non-immune

targets

-LRB-

endothelial

cells

cardiomyocytes

-RRB-

a

recent

study

-LSB-

-RSB-

shows

that

APN

is

also

a

potent

negative

regulator

of

NK

cell

activation

IFN-γ

production

was

suppressed

by

APN

accompanied

by

downregulation

of

the

IFN-γ-inducible

TNF-related

apoptosis

inducing

ligand

and

Fas

ligands

APN

and

cellular

immunity

are

further

linked

by

the

fact

that

NFAT

transcription

factors

are

key

regulators

of

T

cell

function

-LSB-

-RSB-

and

also

negative

regulators

of

APN

expression

-LSB-

-RSB-

All

local

cardiac

functions

of

APN

and

other

factors

in

the

model

are

thought

to

be

mediated

via

auto/paracrine

loops

unrelated

to

the

respective

circulating

plasma

levels

-LRB-

μg/ml

for

APN

in

humans

unknown

for

-RRB-

Fig.

model

of

local

cardiac

inflammation

control

The

model

proposes

the

existence

of

a

inflammation

control

system

in

human

hearts

acting

by

local

synthesis

of

anti-inflammatory

proteins

a

representative

of

which

is

APN

If

local

cardiac

APN

synthesis

by

cardiomyocytes

is

genetically

absent

-LSB-

-RSB-

or

suppressed

-LRB-

this

study

-RRB-

inflammatory

challenges

may

result

in

aggravated

damage

to

endothelia

and

myocardium

This

local

model

assumes

that

inflammation

control

and

other

regulatory

functions

are

mediated

by

auto/paracrine

actions

of

APN

synthesized

locally

by

cardiomyocytes

whereas

in

the

context

of

APN

knockout

mice

-LSB-

-RSB-

a

complementary

systemic

model

of

APN

action

was

proposed

in

which

APN

secreted

by

adipose

tissue

acts

hormone-like

to

protect

heart

and

endothelia

via

the

circulation

APN

-LRB-

downregulated

in

DCMi

-RRB-

acts

directly

upon

immune

cells

-LSB-

-RSB-

-LRB-

right

side

of

figure

-RRB-

and

also

on

nonimmune

cells

such

as

vascular

endothelia

-LSB-

-RSB-

-LRB-

left

side

-RRB-

One

new

target

for

control

by

APN

is

that

is

locally

upregulated

in

DCMi

-LRB-

center

-RRB-

and

whose

endothelial

induction

by

cytokines

is

suppressed

by

APN

-LRB-

see

Fig.

-RRB-

In

addition

to

such

direct

anti-inflammatory

action

of

APN

on

vascular

endothelia

-LRB-

left

side

-RRB-

APN

is

a

potent

negative

regulator

of

NK

cell

activation

-LRB-

right

side

-RRB-

-LSB-

-RSB-

APN

and

cellular

immunity

are

further

linked

by

NFATs

-LRB-

upregulated

in

DCMi

-RRB-

which

are

key

regulators

of

T

cell

function

-LSB-

-RSB-

and

negative

regulators

of

APN

expression

-LSB-

-RSB-

The

functions

of

APN

and

other

factors

deregulated

in

DCMi

in

this

local

model

are

thought

to

be

mediated

via

auto/paracrine

loops

unrelated

to

the

respective

circulating

plasma

levels

downregulation

in

DCMi

-LRB-

right

side

-RRB-

may

alter

immune

cell

attraction

to

the

heart

induction

in

DCMi

-LRB-

left

side

-RRB-

may

stimulate

and

GM-CSF

production

by

endothelial

cells

and

thus

activation

of

the

endothelium

the

primary

attachment

site

for

migrating

immune

cells

Limitations

and

perspective

of

the

study

Gain/loss-of-function

experiments

are

required

to

clarify

which

of

the

gene

deregulations

in

DCMi

are

primary

and

causative

or

secondary

and

maladaptive

Conventional

gain/loss-of-function

experiments

in

cell

cultures

may

contribute

to

solve

these

questions

but

are

rather

artificial

as

compared

to

the

complex

physiological

situation

in

intact

tissues

composed

of

multiple

interacting

cell

types

Cardiac

overexpression

of

deregulated

genes

and

silencing

of

these

genes

by

shRNA-mediated

RNA

interference

in

vivo

has

recently

become

feasible

however

by

intravenous

injection

of

cardiotropic

and

vectors

in

mice

-LSB-

-RSB-

These

systems

have

considerable

potential

for

gene

therapy

-LSB-

-RSB-

Beyond

the

classical

knockout

technologies

this

novel

approach

may

also

help

to

clarify

pathogenic

cause

effect

relationships

arising

from

genomic

and

proteomic

screening

studies

in

humans

such

as

the

current

one

based

on

EMBs

of

human

hearts

in

situ

Conclusions

Genomic

expression

profiling

evolves

as

a

useful

tool

to

identify

novel

pathomechanisms

in

human

cardiac

disorders

-LSB-

-RSB-

because

most

animal

models

if

available

at

all

display

multiple

crucial

differences

to

the

respective

human

disease

Restrictive

disease

phenotyping

significantly

improves

the

chance

of

genomic

approaches

to

identify

such

mechanisms

and

therapeutic

targets

even

in

complex

human

disorders

The

current

work

shows

for

the

first

time

local

APN

expression

in

human

hearts

in

situ

and

its

downregulation

in

a

human

cardiac

disease

It

further

demonstrates

that

APN

efficiently

inhibits

the

endothelial

expression

of

that

is

strongly

induced

in

DCMi

Synopsis

of

previous

work

and

these

data

suggests

to

investigate

further

if

modulation

of

the

balance

between

the

and

APN

network

may

have

therapeutic

potential

in

cardiac

diseases

associated

with

inflammation

Electronic

Supplementary

Material

Below

is

the

link

to

the

electronic

supplementary

material

Fig

The

disease

phenotyping

of

the

DCMi

patient

group

-LRB-

Table

and

Patients

and

methods

-RRB-

that

were

investigated

by

genomewide

Affymetrix

microarray

expression

profiling

included

-LRB-

in

addition

to

clinical

and

molecular

virological

characterization

-RRB-

an

immunohistochemical

characterization

of

cardiac

immune

cell

infiltration

and

vascular

endothelial

activation

The

immunohistochemical

studies

were

done

on

EMBs

obtained

by

the

same

standard

procedure

as

those

used

for

the

Affymetrix

microarray

expression

profiling

and

for

the

TaqMan

quantitative

RT-PCRs

-LRB-

KB

-RRB-

-LRB-

KB

-RRB-

-LRB-

KB

-RRB-

Fig

Real-time

quantitative

TaqMan

PCR

data

on

shifts

in

gene

expression

in

the

DCMi

patients

versus

the

control

group

TaqMan

data

on

the

above

novel

DCMi-associated

genes

were

obtained

by

analysis

of

residual

RNA

extracted

from

the

same

EMB

as

already

used

for

the

genomic

Affymetrix

microarrays

and

confirmed

the

respective

data

from

the

microarray

study

reported

in

detail

in

Table

Fig.

-LRB-

panels

a

f

-RRB-

and

in

all

cases

Sharp

sign

denotes

p

between

the

study

groups

In

addition

to

these

new

genes

the

standard

heart

failure-associated

genes

NPPA

and

NPPB

were

significantly

-LRB-

p

-RRB-

upregulated

-LRB-

and

respectively

-RRB-

in

the

DCMi

group

as

assessed

by

TaqMan

PCR

confirming

a

trend

observed

in

the

microarrays

-LRB-

at

q

and

at

q

-LRB-

PDF

kb

-RRB-

Table

Extension

of

Table

with

all

shifts

in

cardiac

gene

expression

down

to

change

for

DCMi

patient

group

vs

Cont

control

group

as

assessed

by

Affymetrix

microarray

analysis

of

RNA

extracted

from

EMB

For

further

details

of

the

DCMi

and

Cont

groups

see

Table

and

Patients

and

methods

The

complete

Affymetrix

dataset

is

available

from

the

GEO

website

projects/geo

GEO

experimental

series

number

was

assigned

as

-LRB-

PDF

mb

-RRB-

B I I O B I I O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

human inflammatory cardiomyopathy
genomic expression profiling
molecular pathomechanisms
dilated cardiomyopathy
heart failure