Complement Activating anti-HLA DSA and Solid Organ ... · Meta-Analysis: Clinical Significance of...

ADV/15/0002/EUj January

2015

Paris Translational Research Center

for Organ Transplantation

Complement Activating anti-HLA DSA and Solid Organ

Transplant Survival

Olivier Aubert (MD, PhD)

INSERM U970, Equipe 12

Hôpital Necker, Service de Transplantation Rénale

www.paristransplantgroup.org

THE PREVALENT ORGAN TRANSPLANT UNIVERSE

1,000,000(700,000 kidneys)

80,000 new kidney transplants per year

About 15% have DSA: 150,000

About half have ABMR: 75,000

NATUREL HISTORY OF DSA MEDIATED KIDNEY ALLOGRAFT

INJURY

Loupy, Hill & Jordan, Nat reviews 2012

NATUREL HISTORY OF DSA MEDIATED KIDNEY ALLOGRAFT

INJURY

Loupy, Hill & Jordan, Nat reviews 2012

NATUREL HISTORY OF DSA MEDIATED KIDNEY ALLOGRAFT

INJURY

Loupy, Hill & Jordan, Nat reviews 2012

NATUREL HISTORY OF DSA MEDIATED KIDNEY ALLOGRAFT

INJURY

Loupy, Hill & Jordan, Nat reviews 2012

NATUREL HISTORY OF DSA MEDIATED KIDNEY ALLOGRAFT

INJURY

Loupy, Hill & Jordan, Nat reviews 2012

NATUREL HISTORY OF DSA MEDIATED KIDNEY ALLOGRAFT

INJURY

Loupy, Hill & Jordan, Nat reviews 2012

ABMR IS THE MAIN CAUSE OF LATE ALLOGRAFT LOSS

Loheac C & Aubert O et al. Unpublished data

WHAT NEED TO BE ACHIEVED

Treatment

Risk stratification

Diagnosis – Activity – Stage

Washington, Sept 28th 2015

✓ ABMR = current outstanding matter of

concern

✓ Reponse to therapy in ABMR is unknown

✓ PHENOTYPES ARE MANDATORY

✓ Precision composite end point is needed

Lefaucheur & Loupy, JASN, 2010

Lefaucheur, AJT, 2008

Presence/absence of anti-HLA antibody is not enough

Thresholds of HLA-DSA

ARE DSA EQUAL?

Miss C.3rd graft

DSA DQ2

MFI 2460

ARE DSA EQUAL?

Mr D1st graft

DSA DR 7

MFI 3800

WHAT NEED TO BE ACHIEVEDPresence/absence of anti-HLA Ab:Not enough

Thresholds of HLA-DSA:Not enough

➢ Affinity/Avidity of Anti-HLA antibodies➢ Complement activation: C1q➢ Subclasses: IgG1-4➢ Pre-existing vs. de novo DSA

We need new tools for risk stratification !

Graft failures

Disease progression

Risk prediction

Validation

• Tyan et al; Human Immunol 2011

• Sicard et al; JASN 2014

• Taupin et al; JASN 2015

• Viglietti et al: JASN 2015

• Akalin et al; KI 2015

• Canër et al; Transplantation 2015

• Aubert O et al, JASN 2017

Integrative and multiplex assessment of DSA

C1q

binding

Preformed

De novo

Affinity

Strengh

MFI

levels

Class

Eplets

IgG

Subclass

Anti-HLA DSA characteristics associated with

risk of allograft loss

• Complement binding capacity

• IgG subclass composition

Meta-Analysis: Clinical Significance of Complement Activating Anti-HLA DSA in

Kidney TransplantationSc

ree

nin

gEl

igib

ility

Incl

ud

ed

Records identified through databases (Mayo clinic research) (n=5,513)

Full-text articles assessed for eligibilityperformed by 2 blinded reviewers (n=62)

(n patients=10,510)

Articles selected on abstracts: duplicates were removed, no related abstracts

performed by 2 blinded reviewers (n=286)

Exclusion criteria- Methodology articles - No data on primary or

secondary outcomes

Studies included in quantitative synthesis(n=36, 7,547 patients)

Kappa 0.9941

Inclusion criteria-NOS ≥ 6-HR available

Iden

tifi

cati

on

Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009)

Loheac C, Aubert O et al PLOS MEDICINE IN PRESS

Meta-Analysis: Clinical Significance of Complement Activating Anti-HLA DSA in

Kidney Transplantation

3.05

C’ activating Ab: multiorgan relevance

C’ activating Ab: Timing of Ab detection

C’ activating Ab: type of test

Factors influencing complement fixing

(CF) HLA-Ab in vitro (C1q reactivity)

1. Presence of complement fixing (CF) IgG subtypes

(IgG1/IgG3)

2. Level of IgG subtypes (weak /strong MFI)

3. Mixture of CF and non CF (NCF) (C1q reactivity)

4. Impact of antibody removal therapy:

Loss of C1q reactivity – diminished IgG subtype reactivity-

NOT Switch of IgG subtype

DSA IgG subclass distribution

0

0

54%

1411%

1310%

97%

0

0

3125%

86% 0 17

14%

22%

32%

22%

IgG1N=94

75%

IgG4N=33

26%

IgG2N=55

44%

IgG3N=35

28%

IgG1 N=94 75%

IgG2 N=55 44%

IgG3 N=35 28%

IgG4 N=33 26%

DSA IgG SUBCLASS COMPOSITION ACCORDING TO C1q STATUS

IgG subclass compositionAll patients C1q- DSA C1q+ DSA

N=157 N=113 N=44

None 24 (15) 24 (21) 0

1 28 (18) 21 (19) 7 (16)

2 6 (4) 6 (5) 0

3 6 (4) 4 (4) 2 (5)

4 5 (3) 5 (4) 0

1+2 24 (15) 21 (19) 3 (7)

1+3 28 (18) 13 (12) 15 (34)

1+4 5 (3) 3 (3) 2 (5)

2+4 4 (3) 4 (4) 0

1+2+3 8 (5) 2 (2) 6 (14)

1+2+4 17 (11) 10 (9) 7 (16)

1+2+3+4 2 (1) 0 2 (5)

All C1q-binding DSAs were positive for IgG1 and/or IgG3 subtypes

C1q negative DSA does not indicate absence of IgG1 or IgG3

1) IgG1-4, C1q and pan-IgG MFI segregate presence/absence of ABMR

2) IgG3 and IgG4 segragate ABMR phenotype

Identification of distinct patterns of injury according

to DSA characteristics

Lefaucheur C, JASN, 2015

DSA: N=157

C1q DSA: N=44

OR 95%CI P

MFI level 1 [1.00-1.00] <0.001

IgG1

No 1

Yes 5.59 [0.90-34.60] 0.064

IgG3

No 1

Yes 3.66 [1.40-9.54] 0.008

IMMUNOLOGIC DETERMINANTS OF C1q POSITIVITY: MULTIVARIATE

MODEL

Univariate analysis considered: MFI level, HLA class, IgG1, IgG2, IgG3 and IgG4 subclasses

Systematic monitoring and characterization of DSA

could add to the predictive value for allograft loss of

the conventional approach based on their detection

and strength

STUDY DESIGN

TX 01/2016

Clinical indication 1 & 2 years

screening

Graft loss

2008

- 2010

Day-0 DSA• HLA class, specificity, MFI

• C1q-binding

• IgG1-4 subclasses

Graft Biopsy

GFR

Prot U

Prospective DSA monitoring strategy

Post-Tx DSA• HLA class, specificity, MFI

• C1q-binding

• IgG1-4 subclasses

DYNAMIC MODELING TO ASSESS IMPROVEMENT IN RISK PREDICTION ACCORDING

TO DSA MONITORING AND CHARACTERIZATION

Donor

characteristics

Model 1

Reference

Model

Recipient

characteristics

Transplant

characteristics

Immunological

Anti-HLA DSA

characteristics

Model 2

= Reference Model

+

DSA detection

Post transplant

Kid

ney a

llogra

ft s

urv

ivalModel 3

= Model 2

+

DSA characteristic 1

Post transplant

Model 4

= Model 2

+

DSA characteristic 2

Post transplant

Day 0 Year 2Year 1

Post-TX prospective anti-HLA DSA monitoring strategy

IgG1

MFI

IgG4

IgG2

C1q-binding

IgG3

Relative Variable Importance

0.0 0.2 0.4 0.6 0.8 1.0

HLA class

01000

2000

3000

4000

5000

Number of trees

Out-

of-

bag

err

or

rate

Preformed

0.15

0.20

0.25

IgG1

MFI

IgG2

IgG4

C1q-binding

IgG3

Relative Variable Importance

0.0 0.2 0.4 0.6 0.8 1.0

HLA class 01000

2000

3000

4000

5000

0.25

Number of trees

0.16

0.18

0.20

0.22

Out-

of-

ba

g e

rro

r ra

te

DSA CHARACTERISTICS AND ABILITY TO CLASSIFY ALLOGRAFT LOSS

Day-0 (N=110) Post-Tx (N=186)

Hierarchical ranking by multivariate survival random forest modeling

Viglietti D, JASN, 2016

0.5

0.6

0.7

0.8

1.0

0.0

0.9

Pre-transplant Post-transplant

Day-0

Reference

Model

Day-0

Reference

Model

+

C1q

Day-0

Reference

Model

+

IgG3

Post-Tx

DSA

Model

Post-Tx

DSA

Model

+

C1q

Post-Tx

DSA

Model

+

IgG3

*

*

* *

*

C-s

tati

sti

c

* 95%CI for mean difference in C-statistics

between two models does not include zero

PREDICTIVE VALUE OF DSA MONITORING AND CHARACTERIZATION

Overall population

N=851

0.00

0.25

0.50

0.75

1.00

Pts without graft loss (N=89) Pts with graft loss (N=21)

Day-0

MFI

Day-0

MFI

+

IgG3

Day-0

MFI

Day-0

MFI

+

IgG3

Pts without graft loss (N=89) Pts with graft loss (N=21)

Day-0

MFI

Day-0

MFI

+

C1q

Day-0

MFI

Day-0

MFI

+

C1q

Pre

dic

ted

pro

ba

bil

ity o

f g

raft

lo

ss

0.00

0.25

0.50

0.75

1.00

Pre

dic

ted

pro

bab

ilit

y o

f g

raft

lo

ss

80%

67%

RISK RECLASSIFICATION BY IgG3 AND C1q BEYOND MFI

NRI=1.326, P<0.001 NRI=0.948, P<0.001

In patients with Day-0 DSA

84%

81%

RISK RECLASSIFICATION BY IgG3 AND C1q BEYOND MFI

Pts without graft loss (N=149) Pts with graft loss (N=37)

0.00

0.25

0.50

0.75

1.00

Pre

dic

ted

pro

ba

bil

ity o

f g

raft

lo

ss

Post-Tx

MFI

Post-Tx

MFI

+

IgG3

Post-Tx

MFI

Post-Tx

MFI

+

IgG3

0.00

0.25

0.50

0.75

1.00

Pre

dic

ted

pro

ba

bilit

y o

f g

raft

lo

ss

Post-Tx

MFI

Post-Tx

MFI

+

C1q

Post-Tx

MFI

Post-Tx

MFI

+

C1q

Pts without graft loss (N=149) Pts with graft loss (N=37)

62%

NRI=1.326, P<0.001 NRI=0.948, P<0.001

In patients with Post-Tx DSA

85%91%

76%

CONCLUSION

• Prospective, systematic monitoring of DSA improved risk stratification for allograft loss

beyond traditional determinants

• IgG3 positivity and C1q-binding capacity were the most informative DSA characteristics

for classifying patients according to their risk of allograft loss

• IgG3 positivity or C1q-binding capacity improved risk stratification at the population level

and also in patients with DSA beyond MFI level

• Further studies are needed to determine the most cost efficient DSA screening policies

Anti-HLA DSA characteristics induce distinct injuries in

kidney allografts

• Complement binding capacity

• IgG subclass composition

INTRAGRAFT GENE EXPRESSION ACCORDING TO

DSA C1q STATUS

10-310-210-11000.0

0.5

1.0

1.5

2.0

2.5

Association with C1q binding DSA (adjusted p value)

Fo

ld c

han

ge

(C1q

+ v

s C

1q-)

NK genes

NK genes with CD16 engagement

Interferon gamma genes

Macrophages genes

Endothelial genes

CXCL11

CXCL11

CXCL11FCGR3A

LILRB2

CD163

FCGR3A/3B

MS4A6A

MS4A7

C1QB

PTPRC

FYB

GBP5CCL4

CCL4

C1QC

FCGR1A

CD84

C1QA

CTLA4C3AR1

CD86

Effector T cell

CD72

MS4A6AMS4A7

9954 IQR-filtered genes

0 5 10 15 200

10

20

30

40

50

60

70

80

90

100

Rank of Feature

Re

lati

ve

Im

po

rta

nc

e f

or

C1

q+

DS

A (

%)

CXCL11

CCL4

MS4A6A

CTLA4CTSS

CYBBC1QB

MS4A7

GBP5CD86

FCGR3A

GBP1

LST1

ITKC1QAKLRC1

CRTAMPTPRCFYBHISTOLOGY

RELATIVE IMPORTANCE OF C1q SELECTIVE GENES AND HISTOLOGY

IN DETERMINING DSA C1q STATUS

Hierarchical ranking (random forest)

Histology: g+ptc+v+i+t+C4d Banff scores

Top genes Biological association

CXCL11 ENDOTHELIAL IFNG RESPONSE

CCL4

NK CELL CD16-

ENGAGEMENT/MACROPHAGE

IFNG RESPONSE

MS4A6A MONOCYTE/MACROPHAGE

MS4A7 MONOCYTE/MACROPHAGE

FCGR3A NK CELL

BIOLOGICAL RELEVANCE OF C1q DSA TRANSCRIPTS

Human rejection effector cells culture

CCL4

CXCL11

FCGR3A

MS4A6AMS4A7

Anti-HLA DSA characteristics & gene expression to

identify responders to Eculizumab therapy

THERAPEUTIC STUDY: EFFECT OF COMPLEMENT INHIBITION

TX Complement C5 INH (N=52)

2011

- 2014

Allograft BiopsyHistology

Gene expression

Multi-center, international study in HLA incompatible kidney recipients

11 centers in the US and Europe: NCT01567085 & NCT01399593

DSAC1q status

FCM+

Standard of care (N=64)

Day 0 Day 14 Day 90

Incidence of

biopsy-proven

AMR

Standard of care: PE and IVIG according to local centers’ protocol

C5 INH: Eculizumab 1200 mg at Tx, 900 mg/week x4 and 1200 mg at week 5, 7, 9

gptc v i t

cgC4d

0.0

0.5

1.0

1.5

2.0

2.5

NS

NS

* *

NS

NS

* *

NSNS

NS

NS

SOC/C1q+ (N=32)

Eculizumab/C1q+ (N=37)

SOC/C1q- (N=32)

Eculizumab/C1q- (N=15)

* P<0.01

Ba

nff

sc

ore

EFFECT OF COMPLEMENT INHIBITION ON HISTOLOGY

Eculizumab specifically decreased acute injury in C1q+DSA patients (Day 14

allograft biopsy)

C1q+ DSAC1q- DSA

CXC

L11

CCL4

MS4A

6A

MS4A

7

FCG

R3A

0

5

10 *

NS

* *

*

*

NS

NS

NSNS

SOC/C1q+ (N=32)

Eculizumab/C1q+ (N=37)

SOC/C1q- (N=32)

Eculizumab/C1q- (N=15)

* P<0.001O

pti

ca

l d

en

sit

y (

log

2)

EFFECT OF COMPLEMENT INHIBITION ON THE C1q DSA GENE SET

Eculizumab specifically decreased the C1q gene set expression

C1q+ DSAC1q- DSA

IMPACT OF A THERAPEUTIC STRATEGY BASED ON DSA C1q STATUS

vs. DSA DETECTION

Response rate to complement inhibition improved when characterizing DSA C1q

status at transplantation

CONCLUSION

C’-binding HLA DSA as a biomarker in the era of new technologies

Prognosis

Risk stratification

Enrichment of trials

Diagnosis

Rejection heterogeneity

Precision diagnosis

Gene expression

- NEJM 2013

- Meta-analysis (Plos Med

in press)

Therapy

efficacy

Response to complement INH

Personalized medicine

JASN 2018

CONCLUSION

Lee S & Aubert O et al. JASN in press

CONCLUSION

Kaplan-Meier curves of kidney allograft survival by donor type Kaplan-Meier curves of kidney allograft survival by donor type and the presence of DSA

Aubert O et al. BMJ 2015

88%

80%

90%

85%

73%

44%

ECD/DSA-

ECD/DSA+

paristransplantgroup.org

@ParisTxGroup

Acknowledgments