PAGE 2

J. Theor. Biol. 67: 625-635, 1977;
reprinted in Advances 1(3): 53-59, 1984.

A Theory of Diagnosis for Orthomolecular Medicine

5. Evolution of Disease (continued)

  Consider the following scenario, in which disease X is characterized by
abcde, disease Y by defgh, and disease Z by dhjkm. A patient possesses in-
herent anomalies dfm, and is seemingly healthy. After a period of stress and
poor diet, anomaly e develops. The patient now has a sufficiently large set
(defm) to experience vague constitutional symptoms such as fatigue and
headaches. He consults his physician, who is uneasily aware that most
patients' complaints do not resemble the textbook syndromes that he has
studied in the teaching hospital. The physician does not perform a battery
of tests, as the health insurance will not pay for them; the physician in any
event has not been properly trained to interpret the set defm. The physician
does make a provisional diagnosis of Y-or-Z, for he knows that both diseases
are often associated in their early stages with vague constitutional symptoms.
To clarify the diagnosis he tests for dgm. Finding dm, he assumes Z and
erroneously excludes Y, which has actually evolved most closely toward a
clinical-disease stage. He prescribes a drug that has the unfortunate side-
effect of activating c. Additional symptoms arise, of an ambiguous nature;
the patient is now chronically ill and the prolonged derangement in body
chemistry finally causes compensatory mechanism a to fail. The distraught
patient then consults a university medical school professor, who perceives
from the symptoms that the differential diagnosis lies between X and Y.
Testing for abcdefgh, and finding acdef, the professor concludes that X is
the correct diagnosis, Y is unlikely, and Z is erroneous. This ritual, repeated
endlessly in medical centers throughout the world, serves to affirm the natural
order of a universe in which professors of medicine possess more erudition
than their brethren in private practice. In fact Y (in a preclinical stage) has
been neglected, and Z (in a potential stage) ignored altogether. If by chance
a test for m should be performed, the professor may publish a clinical note
on the unusual occurrence of m in a case of X.

  The point of the preceding scenario is that diseases progress through
evolutionary stages, that several evolving diseases are likely to be present
simultaneously, that differential diagnosis is therefore a pointless exercise,
and that insufficient data lead to inadequate conclusions.

  It is presently exceptional for disease to be recognized in its preclinical
stages, and indeed no unifying scheme exists for classifying preclinical
diseases. A suitable scheme might be classification according to subsystem
(cardiovascular, adrenal, hepatic, etc.) and process (e.g. insufficiency,
imbalance, hyperfunction, congestion). Thus a hierarchy is established in
which constitutional abnormalities combine with acquired anomalies to
produce derangements of subsystems; interactions among abnormally
functioning subsystems result in clinically-apparent diseases. For example, a
patient with elevated excretion of metanephrines and pregnandiol, with low
17-ketosteroids and cortisol, may be said to have adrenal imbalance. Later,
when subsequent exhaustion of the adrenal glands leads to widespread
systemic disturbances, he can be diagnosed as having Addison's disease.
The clinically-apparent disease diabetes mellitus may be preceded by dys-
functional states of the pancreas, adrenals, pituitary, thyroid and peripheral
vasculature, as discussed by Loeb (1955) or by Medalie, Papier, Goldbourt
& Herman (1975). The latter authors used a multivariate analytical tech-
nique to demonstrate that serum uric acid and cholesterol, among other
parameters, are major factors in the development of diabetes.

 In practice, a patient will usually be found to have several preclinical
diseases at the same time. Examples of preclinical diseases with their com-
ponent anomalies are presented in Table 1. Such sets of anomalies would
be encountered fairly frequently were it not for inadequate laboratory
examinations that test for only a few disease elements among the many
within a set, an approach that is insufficiently multivariate. Unfortunately,
the selected elements are most often those that differentiate the hospitalized
population from the outpatients.


TABLE 1. Diagnostic profile of a 40-year-old male physician
who complained of chronic fatigue

.

  Hepatic insufficiency
  Hyperuricemia
  Hyperalbuminemia
  Low aldolase
  Low beta globulin
  Borderline hypobilirubinemia

  Malabsorption dysnutrition syndrome
  Hypovitaminosis B1
  Hypovitaminosis B3
  Deficient serum magnesium

  Adrenal hyperfunction
  High metanephrine excretion
  High catecholamine excretion
  High pregnandiol excretion

  Pancreatic dysfunction
  High lactic dehydrogenase (isoenzyme iii)
  Low amylase
  Abnormal glucose tolerance

  Hypogammaglobulinemia

  Reticulocytopenia

.

Diagnostic categorical headings are followed by a list of the component anomalies.
The final two diagnoses are isolated anomalies that do not yet form part of a larger set. The data were obtained by standard biochemical and cellular analyses of body fluids.


6. Therapeutic Implications

 Although a discussion of orthomolecular therapy (Pauling, 1974) is
beyond the scope of this paper, it is appropriate to mention that many of
the biochemical anomalies within a disease set are in theory reversible by
orthomolecular methods. Preclinical disease ought to be more easily reversible
than clinically-apparent disease, because preclinical-disease sets are smaller
than clinical-disease sets. For example, examination of an infant's urine
may reveal the diathesis phenylketonuria. Once recognized, the potential
disease can be treated by orthomolecular methods, thereby preventing the
clinically-apparent disease phenylpyruvic oligophrenia, of which phenyl-
ketonuria is a subset. As an additional example, I have observed a
68-year-old woman who was treated for multiple clinical and preclinical
diseases, including chronic hepatic dysfunction. The latter condition was
defined by high serum copper, high cholesterol esters, high isocitric de-
hydrogenase, low cholinesterase and low thermostable alkaline phosphatase
isoenzyme. The patient responded to orthomolecular therapy with a reversion
to normal of the anomalous esterified cholesterol, isocitric dehydrogenase
and cholinesterase. Presumably, if this patient were subsequently to be
stressed with a hepatotoxin, the now-latent anomalies would appear more
readily than would unrelated anomalies.

7. Conclusions

  The art of clinical diagnosis conventionally rests on the assumption that
signs, symptoms and anomalous laboratory findings follow from specific
diseases, each of which in turn follows from unique causes. By contrast, the
theory presented here holds that multiple non-specific causes give rise first
to biochemical aberrations, which then result in symptoms and signs, from
which a perceived disease state follows. The present theory thus constitutes
an inversion of the usual conceptual hierarchy.

  The present model is more deterministic than the conventional one, in
that a more central role is assigned to genetic influences. The model predicts
that unique sets of stable biochemical anomalies will be observable in each
individual, regardless of his stage of development. It predicts further that
some elements of such sets will become observable as components of the
diseases that an individual will develop with the passage of time. Additionally,
the model requires that disease states as conventionally defined be describable
as polythetic classes of biochemical anomalies.

  If the predictions of the theory are valid, the science of clinical diagnosis
should become a process of multifactorial biochemical analysis, followed by
assignment of biochemical anomalies (with probability weightings) to various
diagnostic categories. By this means it will be possible to identify evolving
diseases in early (preclinical) stages of development, or even as mere
genetically-determined predispositions. The diagnostic process would appear
to lend itself well to electronic data-processing techniques (cf. Pomeroy et al.,
1975). In the final analysis, most diseases are traceable to molecular causes,
whether inborn or acquired during life. Present-day clinical-laboratory
technology is sufficiently advanced to detect the proximate effects of many
molecular defects, and in some cases the defects themselves. Thus the
classification of disease along the lines elaborated above is presently feasible.
In time, refinements in laboratory technology will permit identification of a
sufficiently broad range of molecular defects to make possible a true
molecular-etiologic classification of disease.

  The theoretical analysis implies that laboratory tests should properly be
used to make a diagnosis before a patient becomes ill, not afterward. The
timely application of specific therapy can then prevent more serious disease.
Isolated biochemical defects can in principle be corrected with orthomolecular
methods, and a small number of defects should be more easily correctible
than a larger number. At present it is indifference, not technological im-
maturity, that offers the major obstacle to earlier disease detection and to
advanced preventive therapeutics.

I am profoundly grateful to the late Joseph D. Walters, M.D., for many dis-
cussions concerning the diagnostic interpretation of his clinical data. These pages
contain descriptions of clinical cases observed by Dr. Walters and myself. I also
acknowledge the helpful comments of Dr. Bernard Strehler and Dr. Leon Pomeroy
on earlier versions of this manuscript. I thank Damon Medical Laboratory, Sherman
Oaks, California, for donating the tests on which Table 1 is based.

REFERENCES

AMADOR, E. (1975). J. Am. med. Assoc. 232, 953.

CARTER, C. 0. (1967). Lancet i, 436.

CHERASKIN, E. & RINGSDORF, W. M. (1973). Predictive Medicine: A Study in Strategy
  p. 65. Mountain View: Pacific Press.

COPELAND, B. E. (1972). In Clinical Diagnosis by Laboratory Methods (I. Davidsohn &
  J. B. Henry, eds), p. 1. Philadelphia: W. B. Saunders.

COTLOVE, E., HARRIS, E. K. & WILLIAMS, G. Z. (1970). Clin. Chem., 16, 1028.

ELVEBACK, L. R., GUILLIER, C. L. & KEATING, F. R. (1970). J. Am. med. Assoc. 211, 69.

FILES, J. B., VAN PEENEN, H. J. & LINDBERG, D. A. B. (1968). J. Am. med. Assoc. 205, 94.

GERSHON, H. & GERSHON, D. (1973). Mech. Age. Dev., 2, 33.

HARRIS, H. (1966). Proc. R. Soc. B. 164, 298.

HUBBY, J. L. & LEWONTIN, R. C. (1966). Genetics, Princeton 54, 595. [excuse my typographical error]

HUEMER, R. P. (1972). J. appl. Nutr. 24, 34.

LOEB, R. F. (1955). In A textbook of Medicine (R. L. Cecil & R. F. Loeb, eds), p. 658.
Philadelphia: W. B. Saunders.

MEDALIE, J. H., PAPIER, C. M., GOLDBOURT, U. & HERMAN, J. B. (1975). Arch. intern.
 Med. 135, 811.

MULLER, H. J. (1950). Am. J. hum. Genet. 2, 111.

PATTON, D., HUEMER, R. P., HUSSMAN, T. A. & CAINES, K. L. (1963). Advanced Psycho-physiological Sensors for the PIAPACS Program. Los Angeles: Planning Research Corp. (Report R-449).

PAULING, L. (1968). Science, N. Y. 160, 265.

PAULING, L. (1974). J. int. Acad. prev. Med. 1, 1.

POMEROY, L., KEYES, J. & PATTERSON, J. (1975). J. int. Acad. prev. Med. 2, 53.

ROBINSON, A. B. & PAULING, L. (1974). Clin. Chem. 20, 961.

SOKAL, R. R. & SNEATH, P. H. A. (1963). Principles of Numerical Taxonomy, p. 14. San
Francisco: Freeman.

 

Website Design, Hosting and Maintenance by User-Friendly Computing
505 River Street, Santa Cruz, CA 95060  • Tel:  (831) 423-9653
Copyright (C) 2008.  All Rights Reserved.