Acute
HIV
infec-on
and
Prospects
for
Op-mizing
the
Immune
Response
with
Quan-ta-ve
Modeling


Eric
Rosenberg,
MD
Associate
Professor
of
Medicine


MassachuseDs
General
Hospital


Harvard
Medical
School


47
year
old
male



Present
to
MGH
ED
with
an
8
day
history
of
:
Fever
to
102.5
Headache
Photophobia
Myalgias
and
arthralgias
Nausea
and
vomi-ng


3rd
visit

to
health
care
system


47
year
old
male



Addi-onal
history:
MSM


Recent
unprotected
sex
with
an
HIV
infected
partner


PMH:
prior
history
of
syphilis


Exam:
Fever


Cervical
lymphadenopathy

Rash
(started
on
torso
spread
to
limbs
and
scalp)


Diagnosis


Acute
HIV
Infec-on


Viral
Infec-ons
and
Immunity


• Three
outcomes
of
a
viral
infec-on
– Death
– Eradica-on
– Chronic
infec-on
Latency
 
 
Viral
ac-vity


Chronic Infection: Viral Latency and Replication

Immune
Response


VZV,
HSV,
EBV,
CMV


HIV


HIV infection

J. Coffin, XI International Conf. on AIDS, Vancouver, 1996

Acute
HIV
Infec-on


Acute
HIV
Infec-on
Early
events
and
Diagnosis


CTL


The
level
of
HIV
in
the
blood
stream
following
seroconversion
predicts
disease
progression


HIV

Vira

l Loa

d

One year

Rapid Progression

Slow Progression

28, 240

59, 987

11,843

Interquartileranges

Lyles et al, 2000

Par-al
Control


Why
can’t
the
immune
system
more
effec-vely
control
HIV
replica-on?


Viral factors

Host immune responses

Host genetic factors

New virus assembly

Neutralizing Antibodies

B cell

• Viral
debris
• Rapid
evolu-on
and
diversifica-on
• Inadequate
T
cell
“help”


Why
do
neutralizing
an-bodies
fail?


New virus assembly

2-3 Days

CTL


Solublefactors

If
CTL
are
present,
why
is
the
immune
response
not
more
effec-ve
in
HIV
infec-on?


An-gen
Presen-ng


Cell


Class
II


CD4+
Th
Cell


CD4


HIV‐Specific
T
Helper
Cells
are
impaired
in
all
stages
of
disease


TCR


1.

Ac-va-on
 2. Clonal

expansion


3.

Cytokine
secre-on


Cri-cal
rela-onship
between
CD4
and
CD8


What
happens
to
HIV‐specific
T
helper
cells?


Acute
HIV
infec-on


Acute
HIV
Infec-on
Early
events
and
Diagnosis


CTL


Treatment


Should
individuals
with
Acute
HIV‐1
infec-on
be
treated
with
an-retroviral
therapy?


Advantages

 Disadvantages

Preserva-on
of
HIV‐specific
cellular
immune
responses



Toxici-es
and
unknown
long‐term
risks



Opportunity
for
structured
treatment
interrup-on



Short‐
and
long‐term
clinical
benefits
are
not
well‐defined



Lowering
of
HIV‐1
set
point

 Resistance
acquisi-on



Limita-on
of
viral
evolu-on
and
diversity



Limita-on
of
future
an-retroviral
therapy
op-ons



Decreased
transmission

 Quality
of
life
impact



Mi-ga-on
of
acute
retroviral
symptoms



Cost



Kassutto et al, Clinical Infectious Diseases 2006

HIV‐Specific
T
helper
cells


Can
treatment
ini-ated
during
acute
HIV
infec-on
preserve
HIV‐specific
T


helper
cells?


What
happens
to
HIV‐specific
T
helper
cells?


Pathogenesis
hypothesis:
•  HIV‐specific
T
helper
cell
responses
are
generated
and
subsequently
lost
during
acute
infec-on



Treatment
hypothesis: 
 



•  Treatment
with
ARV
during
acute
infec-on
will
protect
these
responses
from
being
lost


Ac-va-on







&


Expansion


Impairment
Infec-on
CD4
cells


Class
II


CD4


TCR


Ac-va-on







&


Expansion


An-retroviral
therapy


CD4
cells


Class
II


CD4


TCR


Characteristic Acute Early total n Median age (years)

[IQR] 35

[31,39] 37

[34,43] 102

Male gender (%) 94 94 102 HIV Risk Factor

MSM (%) 82 81 94

White race (%) 77 78 102

Mean baseline VL (copies/mL)

(range)

5.61 million

(11,000-95 million)

382,000 (2800-2.95

million) 75

Mean baseline CD4 (cells/mm3)

(range)

445 (42-1093)

567 (170-981) 100

Kassutto et al, CID 2006

control chronic acute acute LTNP 1

10

100

1000

Rx No
Rx

S0mula0

on
inde

x

Rosenberg et al, Science 1997

Elite controllers

Clinical
Point


•  Immune
damage
occurs
in
the
earliest
stages
of
acute
HIV
infec-on:
there
appears
to
be
a
“window
of
opportunity”
to
reverse
this
damage
with
treatment


•  Highly
drug
resistant
virus
can
be
transmiDed
during
acute
infec-on:
viral
genotyping
is
recommended
if
treatment
is
ini-ated


Treatment
Interrup-on


If
treatment
during
acute
infec-on
restores
immune
responses
similar
to
the
elite
controller
phenotype…


Can
treatment
ini-ated
during
acute
HIV
infec-on
be
discon-nued?


Lessons from Berlin Lisziewicz et al, NEJM 340 (21), 1999

Augment
HIV‐specific
immunity
Hypothesis


Can
therapy
be
discon-nued?


• Will
HIV‐1‐specific
immune
responses
generated
and
maintained
during
acute
infec-on
be
enough
to
control
viremia?


• Can
a
“snap‐shot”
of
autologous
virus
further
boost
the
immune
system?


Mul-ple
Treatment
Interrup-ons


36

Can
therapy
be
discon-nued?


“STI”
Structured
treatment
interrup-on


Several
paDerns
have
emerged
– Failure
– Transient
control
of
viremia
with
sudden
loss
of
containment


– Control
(
durability?)
• This
strategy
works
50%
of
the
-me…
Are
we
doing
it
correctly?


Rosenberg et al, Nature 2000 Kaufmann et al, PLoS Med 2004

Treatment
Interrup-on
Strategies


Terminal
Treatment
Discon-nua-on


39

40

Terminal
Treatment
Discon-nua-on


•  ACTG
5187
•  Four
gene
DNA
vaccine
•  20
subjects
treated
during
acute
HIV
infec-on
•  Randomized
to
DNA
vaccine
versus
placebo
•  Amer
4th
vaccina-on
(week
30),
ARV
was
discon-nued


Rosenberg,
et
al:
PLoSOne,
2010


1. Median viral load in placebo group (3.7 log10) 5,012 copies/ml

2. This is markedly different from expected VL based on MAC’s data (28,000 copies)

3. CD4 counts remained stable during treatment interruption

HIV
RNA

Terminal
Treatment
Interrup-on


Rosenberg,
et
al:
PLoSOne,
2010


Future
Direc-ons:
Sor-ng
it
all
out


• More
ques-ons
then
answers…
•  Is
treatment
interrup-on
a
viable
clinical
strategy?


•  Should
individuals
with
acute
infec-on
be
treated
at
all?


•  Can
we
rely
on
clinical
trials
to
sort
it
all
out?


Future
Direc-ons
:Modeling
Biomedical
Problems


• Mul-disciplinary
collabora-on
is
essen-al

 
 
 
MGH‐NCSU


•  Physician‐Scien-sts
do
not
understand
math!
•  Be
prepared
for
skep-cism
•  Be
the
“science
behind
the
science”


Smarter
Trial
Design


•  In
the
absence
of
clinical
data,
physicians
rely
on
“experience”,
“expert
opinion”
and
“educated
guessing”


• Can
sophis-cated
mathema-cal
and
sta-s-cal
models
of
Acute
HIV
infec-on
more
effec-vely
design
clinical
trials?


Popula-on
Based
Simula-on
100
“virtual”
pa-ents



Conclusions…
•  The
early
events
in
acute
HIV
infec-on
may
represent
a
unique
“window
of
opportunity”
for
treatment


•  It
is
not
known
whether
treatment
during
acute
infec-on
is
the
correct
thing
to
do


•  STI
may
have
a
role
in
management
of
treated
during
acute
infec-on
but
op-mal
approach
not
known.


•  Can
Quan-ta-ve
modeling
be
used
to
op-mize
the
design
and
conduct
of
clinical
trials?


Acknowledgements


•  The
MGH
Team
–  Marcus
Alpeld
–  Todd
Allen
–  Jenna
Rychert
–  Daniel
Kaufmann
–  Bruce
Walker
–  Suzanne
Bazner
–  Lindsay
Jones


•  
The
NCSU
Team
–  H.
T.
Banks
–  Marie
Davidian
–  Shuhua
Hu


Solid
Organ
Transplanta-on


Solid
Organ
Transplanta-on
•  Every
transplant
requires
a
Donor
and
a
Recipient


•  Unless
the
donor
and
recipient
are
a
perfect
gene-c
match,
the
recipient
immune
system
will
reject
the
transplanted
organ


•  Rejec-on
ul-mately
results
in
failure
of
the
transplanted
organ


•  Every
transplant
recipient
must
take
immunosuppressive
therapy
to
prevent
rejec-on


•  



Solid
Organ
Transplanta-on
•  Every
transplant
recipient
must
take
immunosuppressive
therapy
to
prevent
rejec-on


•  
Transplant
recipients
are
pharmacologically
immunosuppressed
and
therefore
much
more
suscep-ble
to
serious
infec-on


•  A
major
problem
in
immunosuppressed
pa-ents
is
the
reac-va-on
of
latent
viruses
such
as
CMV,
VZV,
HSV
and
EBV


The Balance of Immunosuppression

Infec-on


Rejec-on


Latency vs re-activation: a delicate balance

Immune pressure

May result in rejection

Viral replication

Viral latency

Latency vs re-activation: a delicate balance

Immune pressure

Viral replication

Intermittent periods of viremia and control

Can
modeling
be
used
to
inform
and
op-mize


immunosuppression
strategies?


What is measurable? – Donor and Recipient tissue type/

genetics – Serologic status – Pre-transplantation immune responses – Post-transplantation immune responses – Drug-level of immunosuppression* – Levels of viremia over time – Graft function –  Tissue activity (via biopsy) – Activity of other viruses