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========================================================
ISIS Press Release 03/04/07
Beyond the HIV-Causes-AIDS Model
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Dr. Mae-Wan Ho follows the trail of how a bad mathematical
model has misled AIDS policies with disastrous consequences,
and recent attempts to find a better model
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“A model lacking in predictive and explanatory power” “More
than 20 years into the AIDS era, it has become increasingly
clear that the current single-virus causation model is
lacking in predictive and explanatory power.” This is how
Rebecca Culshaw, assistant professor of mathematics at the
University of Texas, Tyler, USA, begins her most recent
paper published in the winter 2006 issue of the Journal of
American Physicians and Surgeons [1].
Culshaw has announced why she “quit HIV” in March 2006 [2]
(On Quitting HIV, this series), and this had lured me onto
the fascinating trail of how a bad mathematical model has
misguided AIDS policies for so many years worldwide, and
more importantly, alerted me to recent attempts to find
alternative, more realistic models.
Perhaps quitting HIV is not the same as quitting AIDS, as
the world is desperately in need of a good model, to save
lives and end human suffering on a gigantic scale.
AIDS disease is generally characterised by a decline in CD4+
T lymphocytes circulating in the blood, which are
responsible for cell-mediated immunity. As a result, the
patient becomes susceptible to opportunistic infections
(those affecting weakened immune systems) such as
tuberculosis, pneumonia, meningitis, and other diseases
caused by parasites, bacteria and viruses that can enter and
multiply in the cells of the body.
But models that assume the human immunodeficiency
virus (HIV) plays a central role in disease
progression run into considerable difficulties.
If the decline in CD4+ cells is due to HIV
killing the cells, then there should be a
correlation between the ‘viral load’, which
estimates the amount of virus in the body, and
the CD4+ cell count. But that is not the case.
CD4+ cell count is not a reliable indicator of
disease progression at all, nor for that matter
is viral load [3] (Chapter 2,
<http://www.i-sis.org.uk/unravelingAIDS.php>Unraveling
AIDS, ISIS Report), and they bear little
relationship to each another. This has been
confirmed in a recent study on untreated HIV+ individuals [4].
Although higher viral loads are associated with
greater CD4+ cell decline, only a very small
proportion of CD4+ cell loss, about 4 – 6
percent, is influenced by viral load. The authors
reporting the new study called for future efforts
[4] “to delineate the relative contribution of
other mechanisms.” In short, as Culshaw states
[1]: “It has been extremely difficult to
construct a realistic theoretical model of immune
suppression that is entirely mediated by HIV.”
Why is it important to have a realistic model of
the disease? A realistic model not only can
predict how the disease will progress, it can
also help in developing effective treatment and
prevention. Since the discovery of HIV,
mathematical models have been constructed
precisely for those purposes: to determine the
rates of progression to AIDS, to define optimal
drug regimens for therapy, to develop vaccines,
and as a desperate last resort, microbicide
vaginal gels [5]
(<http://www.i-sis.org.uk/HIVsexualTransmission.php>Concentrating
Exclusively on Sexual Transmission of HIV is
Misplaced, this series). However, the vast
majority of the models lack predictive power
because the mechanisms of disease and the
fundamental nature of the immune system are both
poorly understood. Meanwhile, the consequences of
models based on a wrong hypothesis are all too
clear, as Culshaw has starkly stated [2].
The toxicity of HAART treatment is now widely
accepted [3]
(<http://www.i-sis.org.uk/unravelingAIDS.php>Unraveling
AIDS, Chapter 7). The scandal of toxic drugs
being tested on defenceless foster children in
New York City and mothers and babies in Uganda
[6-8] (<http://www.i-sis.org.uk/USFCUADT.php>US
Foster Children Used in AIDS Drugs Tests;
<http://www.i-sis.org.uk/GPKADT.php>Guinea Pig
Kids in AIDS Drugs Trials ;
<http://www.i-sis.org.uk/NSADTMB.php>NIH-Sponsored
AIDS Drugs Tests on Mothers and Babies ; SiS 27)
was widely publicised more recently in Harper’s
Magazine [9]. This has reopened the acrimonious
debate [10] between AIDS ‘dissidents’ and the
orthodox community of researchers and activists
led by Robert Gallo, the controversial
co-discoverer of HIV. The litany of vaccine
failures has reached epic, controversial
proportions [3]
(<http://www.i-sis.org.uk/unravelingAIDS.php>Unraveling
AIDS, Chapters 9-13); and the third large-scale
clinical trials of anti-HIV gels has just been
terminated because it was not only ineffective,
but actually increased the risk of HIV infection
[5]. There are many compelling reasons to confront the bad model itself.
The Ho/Shaw model on why “hit hard hit early”
The model of HIV causes AIDS disease that has
come to dominate global policies on AIDS, from
diagnosis to therapy and prevention, is barely 12
years old. It was created in two high profile
papers published in the 12 January 1995 issue of
the journal Nature [11, 12]. Two research teams,
led respectively by David Ho of the Aaron Diamond
AIDS Research Centre NYU School of Medicine, New
York, and George Shaw of the University of
Alabama at Birmingham, used experimental
antiretroviral drugs to follow how HIV viral load
and CD4+ cell counts change after drug
administration. From the changes, they estimated
the rates of viral replication and elimination
from the body as well as the rates at which CD4+
cells are killed and replaced by cell proliferation.
The results were astonishing; they were touted as
giving a radically new understanding of HIV
infection, one in which the immune system is in a
constant battle with HIV from the moment of
initial infection. As the distinguished late
mathematician Serge Lang, a prominent AIDS
dissident wrote [13]: “These papers largely
provided the justification for the new phase of
protease inhibitor and cocktail treatments, as
well as for the expanded use of surrogate markers
such as “viral load” and CD4 counts for AIDS
disease. Each of these represented a significant
departure in terms of HIV/AIDS diagnosis,
maintenance, treatment, and epidemiological reporting.”
In the Ho study [11], a protease inhibitor code
named ABT-538 was given at 600 to 1 200 mg per
day to 20 HIV+ individuals whose pre-treatment
CD4+ lymphocyte counts ranged from 36 to 490 per
mm3 and viral load, measured by a new
quantitative branch polymerase chain reaction
from 15 – 554 x 103 virus particles per ml.
Following treatment, every patient had a rapid
and dramatic decline in plasma viral load over
the first two weeks, between 11 and 275-fold
reduction, with a mean of 66-fold, i.e., a 98.5
percent drop. The initial decline was assumed to
be exponential, allowing the half time of viral
decay (time it takes for half of the virus
particles to disappear) to be estimated as 2.1 +
0.4 days. That showed HIV-replication must be
“highly productive”, the authors claimed; and the
virus particles were cleared as fast as they were
produced. In other words, a steady state standoff
was established in the body, so that the viral
load measured at any time remained roughly the
same. The estimated minimum production rate – the
same as the minimum clearance rate - averaged
0.68 + 0.13 x 109 virus particles per day, which
is really quite modest, considering that each
infected cell can produce a hundred virus particles.
The paper was heavily criticised. The estimates
depended on the assumption that drug treatment
does not affect viral clearance, and that there
was a pre-existing steady state between viral
production and viral clearance, regardless of the
amount of virus in circulation. Curiously, the
estimated viral clearance/production rate bore no
relationship to the initial viral load or to the
CD4+ lymphocyte count, which was difficult to
reconcile with the idea that the virus was
killing the CD4+ cells by invading the cells to
replicate and burst the cells. In that case, the
more virus particles and the more cells, the
higher should be the production/clearance rate.
After ABT-538 treatment, CD4+ lymphocyte counts
rose in each of 18 patients that could be
evaluated. Some increases were dramatic and
others quite modest. From the slope of the line
depicting the rise in CD4+ lymphocyte counts
assuming an exponential increase, a doubling time
of about 15 days was estimated during the
(assumed) pre-treatment steady state. The slopes
were inversely correlated with baseline CD4+ cell
counts, however, which too was difficult to
explain. In patients with lower initial CD4 cell
counts, more prominent rises were obtained.
Nevertheless, the authors claimed: “This
demonstrates convincingly that the CD4+
lymphocyte depletion seen in AIDS is primarily a
consequence of the destruction of these cells
induced by HIV-1, not a lack of their
production.” They explained that such an inverse
correlation would be expected if T-cell
proliferation were governed by some kind of
homeostatic mechanism. From the inverse
correlation, it was estimated that the minimum
number of CD4+ cells in blood produced or
destroyed each day ranged from 4.3 x 106 to 109 x
106, with a mean of 35.1 x 106. As the blood
lymphocyte pool is about 2 percent of the total
population, the overall CD4+ lymphocytes turnover
in the patients was calculated to vary from 0.2 x
109 to 5.4 x 109 cells per day, with a mean of
1.8 x109 cells per day. This number of cells was
about the same as the number of putative viruses
produced (and cleared) each day, far too many
cells killed for the number of viruses produced. Things didn’t add up.
The increase in CD4+ lymphocyte counts following
ABT-538 administration was also modelled
linearly, and using the same arguments as for the
decline in viral load, the minimum estimates of
total CD4+ lymphocytes production or destruction
rates at baseline were determined to vary between
0.1 x 109 to 7.8 x 109 cells per day with a mean
of 2.6 x 109 cells per day, sufficiently close to the estimate above.
The authors commented that the CD4+ lymphocyte
depletion seen in advanced HIV-1 infection “may
be likened to a sink containing a low water
level, with the tap and drain both equally wide
open.” As the regenerative capacity of the immune
system is not infinite, it is not difficult to
see why the sink eventually empties (when CD4+ cells are all depleted).
Now comes the crucial conclusion that has
justified the “hit hard, hit early” [14] strategy
of HAART that has gone so disastrously wrong for
otherwise healthy HIV+ individuals: “It is also
evident from this analogy that our primary
strategy to reverse the immunodeficiency ought to
be to target virally mediated destruction (plug
the drain) rather than to emphasize lymphocyte
reconstitution (put in a second tap).”
And: “We believe our new kinetic data have
important implications for HIV-1 therapy and
pathogenesis. It is self evident that, with rapid
turnover of HIV-1, generation of viral diversity
and the attendant increased opportunities for
viral escape from therapeutic agents are
unavoidable sequelae. Treatment strategies, if
they are to have a dramatic clinical impact, must
therefore be initiated as early in the infection
course as possible, perhaps seen during seroconversion…”
The Shaw study [12] used the protease inhibitors
ABT-538, L-735.524, or the non-nucleoside reverse
transcriptase inhibitor Nevirepine on a total of
22 patients, as part of a phase I/IIA clinical
trial, and came to the same conclusions. In
addition, it found drug resistant mutant viruses
in all subjects soon after treatment started. The
lowest point of viral load was at two weeks in
all subjects after treatment started, when the
CD4+ cell count rose to a peak. Thereafter, viral
load increased rapidly, despite increased drug
dosage, and by week four, 100 percent of the
virus in blood was drug resistant. The CD4+ cell
counts dropped more slowly, and were back to baseline within 6-20 weeks.
Critics faulted the Shaw study for the same
unwarranted assumptions that underlie the Ho
study. Neither study included a control group.
The clinical outcomes of the drugs on the
patients were not reported, so it was impossible
to tell whether the patients benefited from the
transient reduction in viral load or the
transient increase in CD4+ cells. The
mathematical model had no contact with the
observations other than dubious fitting of a
straight line through two or three data points [15].
The Ho/Shaw model began to unravel almost as soon
as it was proposed, but the “hit hard hit early”
HAART approach continued at least until 2001 when
the US government’s expert panel on anti-HIV
therapy finally recommended restricting the
prescription of anti-HIV drugs for as long as
possible for people without symptoms, on account
of the serious side effects [3]
(<http://www.i-sis.org.uk/unravelingAIDS.php>Unraveling AIDS, Chapter 7).
“The final nails in the coffin” of Ho/Shaw models
Mario Rodoerer at Stanford University Beckman
Center, writing in News and Views of the February
1998 issue of Nature Medicine commented [15] that
two papers published in the same issue [16,
17] “provide the final nails in the coffin for
models of T cell dynamics in which a major reason
for changes in T cell numbers is the death of
HIV-infected cells [i.e., the Ho/Shaw models].”
The papers presented extensive data on the
remodelling of the T cell compartment in
HIV-infected individuals after treatment with
HAART. Throughout the early stages of HIV
infection, CD4+ cells decline, whereas the total
CD8+ cells expand. However, the application of
flow cytometry techniques that accurately
identified subsets of T cells showed that this
increase in CD8+ cells is made up entirely of
memory and activated T cells, while naïve T cells
(precursor of memory and activated T cells)
declined at the same rate as naïve CD4+ cells
(precursor of memory and activated CD4+ cells).
Activated T cells are found only in peripheral
tissues - the spleen and lymph nodes – and their
expansion in the blood in HIV-infected
individuals indicated an active immune response
even during the later stages of disease.
Within weeks after starting HAART, there were
significant increases in the number of B cells,
and of CD4+ and CD8+ cell in the blood, but these
were only memory cells that can maintain
long-term residence in lymph nodes, and not naïve
T cells, which do not dwell in lymph nodes and do
not immediately respond to HAART.
Essentially, the studies provided evidence for
the ‘redistribution hypothesis’: the increase in
CD4+ cell counts observed shortly after the start
of HAART are T lymphocytes redistributed from the
lymph nodes, and not produced by cell
proliferation. During active viral replication
and the concomitant cellular immune response, a
large number of B and T cells may be trapped in
peripheral sites (for example, by antigen,
cytokine or chemokine signals). After initiation
of HAART, when HIV is effectively removed from
the system, the immune response begins to resolve
and cells pour out of the inflamed lymph nodes back into the blood.
The first study [17] suggested that the degree of
T lymphocyte trapping increases as disease
progresses. That would explain why the response
to HAART tends to be greater in individuals with lower CD4+ cell counts.
Functional recovery of the T cell compartment is
only complete when the repertoire of T cell
receptors is restored, so that potentially all
antigens can be recognized. The decrease in naïve
and memory T cell populations during disease
progression means that the repertoire becomes
increasingly restricted, finally resulting in immunodeficiency.
The second study [18] confirmed earlier findings
that the T cell receptor repertoire in
HIV-infected individuals is significantly
different from the normal distribution found in
healthy adults. This is due to a loss of unique T
cell clones and an expansion of antigen-specific
clones caused by an over-representation of certain receptor types.
In individuals responding to HAART, the number of
naïve T cells slowly increases over a six-month
period after initiation of HAART and a
reconstitution of the T cell repertoire can take
place (but see later). Notably, this
reconstitution occurs only in individuals who
show reductions in viral load in response to
HAART. It is also likely that failure of HAART,
which occurs in many patients over time, will
also be accompanied by a re-initiation of cell
losses and repertoire restriction.
AIDS and an over-stimulated and unbalanced immune system
The use of radioisotope labelling has enabled
researchers to identify different populations of
T lymphocytes in the human body [19]. There are
long-lived and short-lived cells, and the size of
the total T lymphocyte pool appears to be
regulated mainly at the level of the long-lived
cells. During the course of an antigen-driven
cell proliferation response, some T cells
differentiate into effector cells that clear the
antigens from the body, and typically have a
short life span. Others become memory T cells,
which, by contrast, are long-lived and serve as
reservoirs for subsequent activation by antigen
to proliferate and produce effector cells. Naïve
T cells also have a long life span. In advanced
HIV-1 infection, a much higher proportion of T
cells are short-lived, compared to healthy
controls, and effective HAART tends to restore
the values towards the normal. Advanced HIV-1
infection greatly reduces the percentage and
total number of CD4+ cells that are long-lived.
Because these cells represent the regenerative
source of newly formed CD4+ effector T cells,
their loss may underlie the immunodeficiency of
HIV-1 disease. These abnormalities may not be
present in early HIV-1 infection and may represent a marker of disease stage.
However, many questions remain unanswered
[20]. Why is HIV so uniquely powerful, among
chronic viruses, in inducing a chronic state of
immune activation? And why is the HIV- induced
immune activation is so disruptive of the proper
overall functioning of the immune system?
Of course, there remains the lingering doubt that
HIV is not actually causing the disease
A radical new model is needed
None of the models so far has taken into account
the role of nutrition in AIDS or AIDS-like
diseases, and the ability of good nutrition to
reverse or delay disease progression [3]
(<http://www.i-sis.org.uk/unravelingAIDS.php>Unraveling
AIDS, Chapters 15-17). In particular, AIDS is a
disease in which the immune system is out of
balance, not only in being chronically activated,
but also in the predominance of the humoural
(type 2) at the expense of cellular (type 1)
immunity [3]
(<http://www.i-sis.org.uk/unravelingAIDS.php>Unraveling AIDS, Chapter 12).
All HIV models so far have considered the CD4+
cells as a single entity. But it has been known
for some that the pool of CD4+ cells (commonly
known as T-helper or Th cells) contained two
different subsets: Th 1, responsible for
cell-mediated immunity and Th 2, responsible for
extracellular or humoural immunity. The majority
of the CD4+ Th 1 cells reside in the peripheral
blood and it is their depletion that occurs in
the progression to AIDS [1 and references
therein]. Th2 cells reside mainly in the bone
marrow and to a lesser extent in the lymph nodes,
and do not appear to become depleted in the
progression to AIDS. If anything they have been observed to increase [21].
As AIDS progresses there appears to be a gradual
shift from Th1- to Th2-dominance, which is why
patients experience mainly fungal and
mycobacterial infections, but very few
“classical” bacterial diseases. Furthermore,
elevated levels of antibodies, including
autoantibodies, are characteristic of all AIDS
patients, as consistent with an increase in Th2
subset. Contrary to what one might expect, HIV is
expressed primarily in Th0 (precursor of Th1 and
Th2) and Th2 cells and is scarcely
Expressed in the Th1 subset [22]. Yet it is the
Th1 cells that are depleted, whereas the cells in
which HIV prefers to reside do not decrease. So
what mediates the Th1 to Th2 shift, and how can
it be prevented or reversed so as to restore balance to the immune system?
Culshaw [1] suggests using bifurcation theory, a
branch of mathematics that deals with changes in
critical parameters that determines major or
abrupt changes, such as the commitment of Th0 to become either Th1, or Th2.
One crucial component in the Th1 to Th2 shift is
the release of nitrous oxide (NO) from the
cell-mediated arm of the immune system [23]. NO
can diffuse though cell membranes without the
help of receptors in cell-cell communication, and
nitrogen oxides are regulated by the oxidative
state of the immune cells. Excessive oxidation
negatively affects immune function through the
production of cytokines from the immune cells.
Oxidative processes are counterbalanced by
reduction, which is accomplished by
sulphur-containing molecules that serve as
electron donors, the main one is glutathione, a
tripeptide consisting of cysteine, glutamine and
glycine. Glutathione is found in both the reduced
(GSH) and the oxidized (GSSG) form. The ratio of
GSH:GSSG has been shown to be important in
regulating Th1/Th2 balance [24, 25]. If the
GSH:GSSH ratio declines, Th2 cells are
preferentially made from Th0, thus resulting in
Th2 dominating at the expense of Th1 cells.
HAART causes a transient increase in T-cell
counts in the peripheral blood because it damages
B-cells as they mature and disrupts antibody
production. Unable to make contact with
antibody-producing B-cells in the bone marrow,
the CD4+ Th2 cells return to the peripheral
blood. So, although CD4+ T cell count increases,
the cells are ineffective against opportunistic
infections. This gives rise to the phenomenon of
‘immune reconstitution syndrome’, in which
patients experience the “irony” of an increase in
opportunistic infections after initiating HAART therapy [26].
Culshaw sketches out an alternative mathematical
model based on the GSH:GSSG ratio and Th1/Th2
balance, which are crucial in the development of
AIDS, and proposes that HIV itself need not even
be included as a variable. The proposed model
tracks the Th0, Th1 and Th2 subsets of the T-cell
pool over time, with the ratio of GSH:GSSG as a
possible bifurcation parameter. As GSSG
increases, and the ratio declines, a greater
proportion of the Th0 cells mature into Th2 cells
and are diverted from the Th1 pool. Such a model
could enable researchers to determine the
critical ratio of GSH:GSSG below which a shift to Th2-dominance occurs.
There are several advantages to such a model.
First, it replaces viral load measurements, which
have not been shown to have good clinical
predictive value as a therapeutic endpoint.
Second, determining a critical ratio of GSH:GSSH
rather than a critical value gets around the
problem of variability among individual patients.
Finally, the model explicitly considers the
Th1/Th2 ratio, an important measure in the
progression to AIDS that has been largely neglected in theoretical modelling.
Circumstance evidence in favour of such a model
is that selenium and other antioxidants appear to
be effective in preventing and treating AIDS [3]
(<http://www.i-sis.org.uk/unravelingAIDS.php>Unraveling
AIDS, Chapter 17). Another advantage of Culshaw’s
new model is that it can make direct contact with
nutritional status, an important determinant in disease progression.
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http://www.i-sis.org.uk/beyondHIV-CausesAIDS.php
This is the second article in the current AIDS series
Previous articles in the series:
28/3/07 On Quitting HIV
http://www.i-sis.org.uk/OnQuittingHIV.php
The rest will be released over the next two weeks
Or read other articles in the Health & Disease
section of the Institute of Science in Society
Website
http://www.i-sis.org.uk/scihealth.php
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This article can be found on the I-SIS website at
http://www.i-sis.org.uk/beyondHIV-CausesAIDS.php
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