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SCIENCE-FOR-THE-PEOPLE  April 2007

SCIENCE-FOR-THE-PEOPLE April 2007

Subject:

Beyond the HIV-Causes-AIDS Model

From:

Mitchel Cohen <[log in to unmask]>

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Science for the People Discussion List <[log in to unmask]>

Date:

Tue, 3 Apr 2007 12:10:21 -0400

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This article can be found on the I-SIS website at
http://www.i-sis.org.uk/beyondHIV-CausesAIDS.php

========================================================
ISIS Press Release 03/04/07

Beyond the HIV-Causes-AIDS Model
##############################

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

An electronic version of this report, or any other ISIS
report, with full references, can be sent to you via e-mail
for a donation of £3.50. Please e-mail the title of the
report to: [log in to unmask]

Alternatively, order you copy of ISIS Report Unraveling AIDS
and get a free CD of all new articles and others on AIDS
from SiS archives to bring you right up to date
http://www.i-sis.org.uk/onlinestore/books.php#236

“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.

---------------------------------------------------------------------
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

========================================================
This article can be found on the I-SIS website at
http://www.i-sis.org.uk/beyondHIV-CausesAIDS.php

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