Beyond the HIV-Causes-AIDS Model


Richard Moore

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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 

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³A model lacking in predictive and explanatory power²

³More 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.² 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 ³quit HIV² 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 Œviral load¹, 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, 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] 
³to delineate the relative contribution of other mechanisms.² In short, as 
Culshaw states [1]: ³It has been extremely difficult to construct a realistic 
theoretical model of immune suppression that is entirely mediated by HIV.²

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] (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] (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] (US Foster 
Children Used in AIDS Drugs Tests; Guinea Pig Kids in AIDS Drugs Trials ; 
NIH-Sponsored AIDS Drugs Tests on Mothers and Babies ; SiS 27) was widely 
publicised more recently in Harper¹s Magazine [9]. This has reopened the 
acrimonious debate [10] between AIDS Œdissidents¹ 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] (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 ³hit hard hit early²

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]: ³These 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 ³viral load² and CD4 counts for AIDS disease. Each of these represented a 
significant departure in terms of HIV/AIDS diagnosis, maintenance, treatment, 
and epidemiological reporting.²

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 ³highly productive², 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: ³This 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.²  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 didn¹t 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 ³may be likened to a sink containing a low water level, with the tap 
and drain both equally wide open.² 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 ³hit hard, hit early² 
[14] strategy of HAART that has gone so disastrously wrong for otherwise healthy
HIV+ individuals: ³It 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).²

And: ³We 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 

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 
³hit hard hit early² HAART approach continued at least until 2001 when the US 
government¹s 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] (Unraveling AIDS, Chapter 

³The final nails in the coffin² 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]  ³provide 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].²

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 

Essentially, the studies provided evidence for the Œredistribution hypothesis¹: 
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 

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] (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] (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 ³classical² 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 Œimmune reconstitution syndrome¹, in which 
patients experience the ³irony² 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 

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] 
(Unraveling AIDS, Chapter 17). Another advantage of Culshaw¹s new model is that 
it can make direct contact with nutritional status, an important determinant in 
disease progression.

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