Immune monitoring in the blood bank setting: Can the ...€¦ · Immune monitoring in the blood...

Immune monitoring in the blood bank setting: Can the effects of transfusion be detected?

Philip Norris, M.D.

BSRI

Array of up to 100 Luminex beads

Luminex flow cell detection

Cytokine levels in acute HIV HIV 6246

0

2

4

6

8

10

12

14

16

18

-49

-35

-28

-21

-14 -7 0 7 14 23 30

Days after VL>100

pg/m

l or l

og(V

L)

0

500

1000

1500

2000

2500

3000

pg/m

l

Viral lo ad

IL -‐1b

IL -‐2

IL 4

IL -‐5

IL -‐6

IL -‐7

IL -‐8

IL -‐12p70

IL -‐13

IF N -‐g

GM-‐C S F

T NF -‐a

IL -‐15

IL -‐10

IF N -‐α

IL -‐18

IP -‐10

MC P -‐1

Early Elevation of Pro and Anti-Inflammatory Cytokines in Response to Trauma

Jackman et al., Transfusion 2012

Early Anti-Inflammatory Response

ln c

once

ntra

tion

(pg/

mL)

0 1wk 2wk 3wk 4wk 1-3mo 1yr

Pro-Inflammatory Anti-Inflammatory IL-6


Late Wound Healing/Homeostasis

ln c

once

ntra

tion

(pg/

mL)

0 1wk 2wk 3wk 4wk 1-3mo 1yr

Wound Healing Activated Endothelial Homeostasis


Can a mouse model shed light on the human data?


Se=ng up a mouse model Transfusion versus blood loss

Context of loss & transfusion Stress Wound type

Innate immune activators

Product transfused

Minimal requirements for establishment of microchimerism

Tracking of transferred cells

Mouse model results: Trauma drives, fluids rescue


Mouse model results: Trauma drives, fluids don’t rescue


Mouse model results: Transfusion drives


Human Mouse Protein Trauma Tx Mechanism: Trauma or Tx IL-6 á áC á trauma drives, fluids rescue IL-10 á á trauma drives, fluids rescue MMP-9 á áC á trauma drives, fluids rescue INF-γ á trauma drives, fluids rescue IL-8/KC áB á trauma drives IL-13 á trauma drives MCP-1 á á á both trauma and tx but not NaCl drive, highest with both IL-1α â â requires both trauma and fluids IL-5 áB á both trauma and fluids drive, highest levels with tx IL-15 áB á tx drives sE-Selectin áB â á tx drives TNFα áB Eotaxin áB IP-10 áB sICAM-1 áB sVCAM-1 áB tPAI-1 áB â IL-7 â IL-17 â MIP-1α â

1

Concordance of mouse and human data


Conclusions

•  Trauma and transfusion are associated with marked modulation of the cytokine environment.

•  An early anti-inflammatory response is followed by factors associated with wound healing

•  Chemokine responses are variable

•  These relative contribution of trauma vs. transfusion is difficult to assess in humans.

16

BSRI / UCSF Rachael Jackman John Heitman Jacqueline Law Nelly Gefter Leslie Tobler Li Wen Daniel Chafets Lani Montalvo Tzong-Hae Lee Michael Busch

UC Davis Garth Utter Ryan Rivers BloodSource Don Fipps Pat Kopko Anne Igbokwe Kathy Castillo

Acknowledgments

Do patient immune parameters change after

transfusion of aged blood?

ABLE Hypotheses •  Stored blood will lead to greater immune modulation in transfused recipients (and

that greater immune perturbation will be associated with poor outcome)

–  Transfusion with stored RBCs will tilt the balance of T cell responses to an anti-inflammatory state (immune suppression), with increased frequencies of Treg cells and decreased frequencies of Th17 & effector cells

–  We expect that patients transfused w/ older RBCs will have increased pro-inflammatory concentrations of cytokines that will be followed in time (3-7 days from first transfusion) by a hypercoagulable and immune deficient state.

•  RBC storage will increase the number of MPs in RBC units

à These hypotheses would help explain how transfusion can be associated with innate activation (e.g. acute lung injury) and immune suppression (e.g. increased rate of infection and impaired tumor rejection)

storage -80o C

Flow Cytometer

Whole blood in citrate tubes

1500g 10 min

EVs in suspension

RBC pellet discarded

Platelet Poor Plasma (PPP)

Platelet pellet discarded

13,000g 10 min

Thaw, Stain w/ PRE-

FILTERED Abs, 30min

Transfer to centrifugal

filter

850g 3 min

Resuspend top in PBS

Refined Protocol

1.  FiltraEon of Abs prior to staining to remove Ab aggregates

2.  Post-‐stain filtraEon to wash PPP & remove unbound stain

3.  Lyse samples to idenEfy non-‐vesicle-‐related posiEve signal

1)  Run each sample for exactly 60 sec

2)  Lyse w/ 1% NP-40, Re-run for 60sec

ABLE PRELIMINARY DATA

EV ConcentraEons using Trucount Beads


GROUP 1 VS. GROUP 2: PLATELET MARKERS


GROUP 1 VS. GROUP 2 : RBC MARKERS


GROUP 1 VS. GROUP 2; GRANULOCYTE MARKERS


Correlation Matrix of #pos MP difference (D2-‐D0)Correlation Coeffficients

CD3 CD14 CD16 CD19 CD28 CD152 CD41a CD62L+ CD108a CD235a CD11b CD15 CD62p CD66 AnnexinV CD3 0.22802 -0.0491 0.39496 0.79739 0.11111 -0.0709 0.09633 0.37419 0.37566 0.26684 0.47587 -0.02615 0.0265 -0.02860452CD14 0.22802 -0.0406 0.38922 -0.1457 0.57452 -0.0196 0.01687 0.51222 0.3237 0.03274 0.11925 -0.0313 -0.08907 -0.00946498CD16 -0.0491 -0.0406 0.04378 -0.0431 -0.0164 -0.1445 -0.1822 0.018 0.05239 0.07768 0.18485 -0.12815 0.235146 -0.04174524CD19 0.39496 0.38922 0.04378 0.22467 0.41465 -0.0907 0.03139 0.05179 0.04232 0.35192 0.081713 -0.05062 0.035589 -0.06053526CD28 0.79739 -0.1457 -0.0431 0.22467 -0.4205 -0.0025 0.11243 0.32288 0.33989 0.24433 0.453776 0.053154 0.090637 -0.01868686CD152 0.11111 0.57452 -0.0164 0.41465 -0.4205 -0.001 -0.0079 0.01922 0.00988 -0.0496 -0.06902 -0.03983 -0.10769 -0.06095381CD41a -0.0709 -0.0196 -0.1445 -0.0907 -0.0025 -0.001 0.62537 0.07718 0.07773 0.0976 0.057293 0.964878 0.145636 0.877234

CD62L+ 0.09633 0.01687 -0.1822 0.03139 0.11243 -0.0079 0.62537 0.07815 0.08999 0.11529 0.080549 0.715948 0.11199 0.4582827CD108a 0.37419 0.51222 0.018 0.05179 0.32288 0.01922 0.07718 0.07815 0.92141 0.12977 0.373131 0.09514 0.073339 -0.03828306CD235a 0.37566 0.3237 0.05239 0.04232 0.33989 0.00988 0.07773 0.08999 0.92141 0.1896 0.341872 0.104689 0.081216 -0.01951654CD11b 0.26684 0.03274 0.07768 0.35192 0.24433 -0.0496 0.0976 0.11529 0.12977 0.1896 0.47812 0.158067 0.434607 0.04698643CD15 0.47587 0.11925 0.18485 0.08171 0.45378 -0.069 0.05729 0.08055 0.37313 0.34187 0.47812 0.084933 0.386143 -0.1169258

CD62p -0.0261 -0.0313 -0.1282 -0.0506 0.05315 -0.0398 0.96488 0.71595 0.09514 0.10469 0.15807 0.084933 0.164065 0.7622687CD66 0.0265 -0.0891 0.23515 0.03559 0.09064 -0.1077 0.14564 0.11199 0.07334 0.08122 0.43461 0.386143 0.164065 0.01552139

AnnexinV -0.0286 -0.0095 -0.0417 -0.0605 -0.0187 -0.061 0.87723 0.45828 -0.0383 -0.0195 0.04699 -0.11693 0.762269 0.015521

•  Red = positive correlation •  Blue = negative correlation •  Outlined boxes indicate value is significant (p<0.01)




CD62L+ 0.09633 0.01687 -0.1822 0.03139 0.11243 -0.0079 0.62537 0.07815 0.08999 0.11529 0.080549 0.715948 0.11199 0.4582827CD108a 0.37419 0.51222 0.018 0.05179 0.32288 0.01922 0.07718 0.07815 0.92141 0.12977 0.373131 0.09514 0.073339 -0.03828306CD235a 0.37566 0.3237 0.05239 0.04232 0.33989 0.00988 0.07773 0.08999 0.92141 0.1896 0.341872 0.104689 0.081216 -0.01951654CD11b 0.26684 0.03274 0.07768 0.35192 0.24433 -0.0496 0.0976 0.11529 0.12977 0.1896 0.47812 0.158067 0.434607 0.04698643CD15 0.47587 0.11925 0.18485 0.08171 0.45378 -0.069 0.05729 0.08055 0.37313 0.34187 0.47812 0.084933 0.386143 -0.1169258

CD62p -0.0261 -0.0313 -0.1282 -0.0506 0.05315 -0.0398 0.96488 0.71595 0.09514 0.10469 0.15807 0.084933 0.164065 0.7622687CD66 0.0265 -0.0891 0.23515 0.03559 0.09064 -0.1077 0.14564 0.11199 0.07334 0.08122 0.43461 0.386143 0.164065 0.01552139

AnnexinV -0.0286 -0.0095 -0.0417 -0.0605 -0.0187 -0.061 0.87723 0.45828 -0.0383 -0.0195 0.04699 -0.11693 0.762269 0.015521

CD235a correlates with CD108a. Both are RBC markers known to coexist on EVs




CD62L+ 0.09633 0.01687 -0.1822 0.03139 0.11243 -0.0079 0.62537 0.07815 0.08999 0.11529 0.080549 0.715948 0.11199 0.4582827CD108a 0.37419 0.51222 0.018 0.05179 0.32288 0.01922 0.07718 0.07815 0.92141 0.12977 0.373131 0.09514 0.073339 -0.03828306CD235a 0.37566 0.3237 0.05239 0.04232 0.33989 0.00988 0.07773 0.08999 0.92141 0.1896 0.341872 0.104689 0.081216 -0.01951654CD11b 0.26684 0.03274 0.07768 0.35192 0.24433 -0.0496 0.0976 0.11529 0.12977 0.1896 0.47812 0.158067 0.434607 0.04698643CD15 0.47587 0.11925 0.18485 0.08171 0.45378 -0.069 0.05729 0.08055 0.37313 0.34187 0.47812 0.084933 0.386143 -0.1169258

CD62p -0.0261 -0.0313 -0.1282 -0.0506 0.05315 -0.0398 0.96488 0.71595 0.09514 0.10469 0.15807 0.084933 0.164065 0.7622687CD66 0.0265 -0.0891 0.23515 0.03559 0.09064 -0.1077 0.14564 0.11199 0.07334 0.08122 0.43461 0.386143 0.164065 0.01552139

AnnexinV -0.0286 -0.0095 -0.0417 -0.0605 -0.0187 -0.061 0.87723 0.45828 -0.0383 -0.0195 0.04699 -0.11693 0.762269 0.015521

CD41a correlates with CD62p, CD62L, and Annexin V. All are known to coexist on Platelet-derived EVs




CD62L+ 0.09633 0.01687 -0.1822 0.03139 0.11243 -0.0079 0.62537 0.07815 0.08999 0.11529 0.080549 0.715948 0.11199 0.4582827CD108a 0.37419 0.51222 0.018 0.05179 0.32288 0.01922 0.07718 0.07815 0.92141 0.12977 0.373131 0.09514 0.073339 -0.03828306CD235a 0.37566 0.3237 0.05239 0.04232 0.33989 0.00988 0.07773 0.08999 0.92141 0.1896 0.341872 0.104689 0.081216 -0.01951654CD11b 0.26684 0.03274 0.07768 0.35192 0.24433 -0.0496 0.0976 0.11529 0.12977 0.1896 0.47812 0.158067 0.434607 0.04698643CD15 0.47587 0.11925 0.18485 0.08171 0.45378 -0.069 0.05729 0.08055 0.37313 0.34187 0.47812 0.084933 0.386143 -0.1169258

CD62p -0.0261 -0.0313 -0.1282 -0.0506 0.05315 -0.0398 0.96488 0.71595 0.09514 0.10469 0.15807 0.084933 0.164065 0.7622687CD66 0.0265 -0.0891 0.23515 0.03559 0.09064 -0.1077 0.14564 0.11199 0.07334 0.08122 0.43461 0.386143 0.164065 0.01552139

AnnexinV -0.0286 -0.0095 -0.0417 -0.0605 -0.0187 -0.061 0.87723 0.45828 -0.0383 -0.0195 0.04699 -0.11693 0.762269 0.015521

•  Significant negative correlation observed between CD152 (CTLA-4) and CD28 •  CD152 and CD28 are known to have inverse relationship

Modest changes in cytokine levels

Gro

u p 1 D

a y 0

Gro

u p 2 D

a y 0

Gro

u p 1 D

a y 2

Gro

u p 2 D

a y 2

Gro

u p 1 D

a y 6

Gro

u p 2 D

a y 6

Gro

u p 1 D

a y 28

Gro

u p 2 D

a y 2 80 .1

1

1 0

1 0 0

1 0 0 0

1 0 0 0 0

IL -6

Co

nc

en

tra

tio

n(p

g/m

L)

Gro

u p 1 D

a y 0

Gro

u p 2 D

a y 0

Gro

u p 1 D

a y 2

Gro

u p 2 D

a y 2

Gro

u p 1 D

a y 6

Gro

u p 2 D

a y 6

Gro

u p 1 D

a y 28

Gro

u p 2 D

a y 2 80 .0 1

0 .1

1

1 0

1 0 0

1 0 0 0

IF N -g

Co

nc

en

tra

tio

n(p

g/m

L)

p = 0 .0 1

Gro

u p 1 D

a y 0

Gro

u p 2 D

a y 0

Gro

u p 1 D

a y 2

Gro

u p 2 D

a y 2

Gro

u p 1 D

a y 6

Gro

u p 2 D

a y 6

Gro

u p 1 D

a y 28

Gro

u p 2 D

a y 2 80 .0 1

0 .1

1

1 0

1 0 0

1 0 0 0

IL -2

Co

nc

en

tra

tio

n(p

g/m

L) p = 0 .0 3

T cell assay: IL-17

•  Increase in IL-17 in Group 1 post-transfusion

D 0 D 6D 2 8

D 1 8 00 .0

0 .2

0 .4

0 .6

0 .8

1 .0

C D 4 + IL 1 7 +

% P

os

itiv

e

G ro u p 1

G ro u p 2

N D

H e a lth y D o n o rs

*

T cell assay: IFN-γ

•  Increase in IFN-γ post-transfusion •  Sustained increase in Group 2 only

D 0 D 6D 2 8

D 1 8 03 0

4 0

5 0

6 0

C D 8 + IF N g +

% P

os

itiv

e

G ro u p 1

G ro u p 2

N D


D 0 D 6D 2 8

D 1 8 00

5

1 0

1 5

C D 4 + IF N g +

% P

os

itiv

e

G ro u p 1

G ro u p 2

N D


*

Treg assay

•  No significant changes observed in Treg assay

D 0 D 6 D 2 8 D 1 8 00

1

2

3

4

5

T r e g G 1 v s G 2

% P

os

itiv

eG 1

G 2

D0D6D28D180

G1Mean SEM N

2.8142193.5195352.6921432.817778

0.2822830.3677150.2953540.364804

32432818

G2Mean SEM N

3.4560003.0788572.8165522.608000

0.3859780.3346430.3440410.401106

34352920

N D


D 0 D 6 D 2 8 D 1 8 00

5

1 0

1 5

T r e g /T H 1 7 G 1 v s G 2

% P

os

itiv

e

G1

G2

D0D6D28D180

G1Mean SEM N

9.2099875.6500287.3680306.965416

1.7386960.7393731.3746621.605430

18351916

G2Mean SEM N

10.2942707.2360836.21956210.121020

1.8955981.4402521.2771022.596938

25272416

ND

The Treg:Th17 Ratio •  Hypothesized to be low immediately post-

transfusion, as cells are in pro-inflammatory state with elevated Th17 levels.

•  Over time (3-7 days post-transfusion) expect to see this ratio increase, in immune deficient state

Conclusions ABLE prelim MP data Significant correlations among several of the markers tested, particularly:

Significant differences between the ND and patient samples, including:

1.  CD41a -- CD62p – Annexin V 2.  CD11b – CD15 – CD66b 3.  CD108a – CD235a

1.  CD41a and CD62p are lower in ABLE patients, compared to ND 2.  CD108a and CD235a are higher in ABLE patients, compared to ND 3.  CD66b is lower in ABLE patients, compared to ND

Conclusions

ABLE cell-based assays: •  Significant increase in %IL-17+ cells from D0-D6 in Group 1

•  Significant increase in %IFNγ+ from D0 to D6 in Group 1(increase observed in both groups but significant only in Group 1)

•  Drop in %IFNγ + cells after D6, which remained significantly lower in Group 1 vs Group 2 from D6-D180

•  No significant difference in Treg+ cells

Acknowledgments Washington University, St. Louis •  Phil Spinella BSRI/UCSF •  Ali Danesh •  John Heitman •  Dale Hirschkorn •  Avani Shah •  Heather Inglis •  Tzong-Hae Lee

Ottawa General Hospital •  Irene Watpool •  Claude Gaudert •  Amanda van Beinum

Laval Quebec •  Marie-Claude Ferland

University of Montreal •  Lucy Clayton •  Jacques Lacroix

Immune monitoring in the blood bank setting: Can the ...€¦ · Immune monitoring in the blood...

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