Chronic Diseases with Delayed Onset After Vaccinations and Infections. A Complex Systems Approach to Pathology and Therapy

Abstract

Background: The medical community fails dramatically in the understanding of chronic diseases and development of causal therapies. Statistical associations between vaccinations or infections and autoimmune diseases or a multitude of chronic diseases remains without any scientific rational. The Gulf War illness, with an unexpected high health risk (34%) for military personnel after a manifold of vaccinations, points to the need of a scientific approach different from insufficient linear clonal selection concepts in immunology. Methods: Non-linear dynamics analyzed in time series, phase portraits, and mathematical models. Results: Three different types of chronic diseases, different from lasting acute diseases, are discriminated by Cerebrospinal fluid analysis and nonlinear dynamics. A nonlinear model for a virus-driven chronic disease explains the chronification of the infection, as one of the stable optional states between complete immunity and death. The model also helps create causal therapies and facilitating phase transitions to complete immunity based on individual connectivity in the immune network. Chronic diseases with a sudden change from stable health to a pathological but stable state are phase transitions based on metabolic fluctuations spontaneous or facilitated by external influences (via the immune, endocrine or nervous system). A reduced complexity in diseases is shown by the numerical analysis of time series (e.g., heart rate) or attractor phase portraits. In chronic diseases, with immune system associated pathology, vaccination or infection has to be regarded as a facilitator for a phase transition, like a catalyst, but not as the cause. With this causation we understand why no traces, like causative antigens, are found in Gulf War illness, chronic fatigue syndrome, post lyme syndrome, or the mild encephalitis in schizophrenia.Conclusions: The complexity approach shows why antiviral or antibiotic medications fail in chronic diseases. Disease as an emergent property should be investigated on the phenotype level. Nonlinear analysis of time series of the individual patient gives information not available from group statistics of molecular "multiscale" systems or systems biology. New research perspectives could base on the extended time of registry after vaccinations and should focus on causal therapies, which need financial support, independent from the medical-industrial complex, with its divergent interests.

Polyspecific antibodies without persisting antigen in multiple sclerosis, neurolupus and Guillain-Barré syndrome: immune network connectivity in chronic diseases

“…Another irritation in the research of chronic diseases comes from a clear statistical correlation between infections and autoimmune diseases, including MS 3 . This connection is supported by the association of vaccinations with a three-week to two-month delayed appearance of multi-symptom diseases, like Gulf war illness, chronic fatigue or Guillain-Barré syndrome 4,5,6 . This shows that there is a basic deficit in the understanding of the causation of chronic diseases; in fact, of the nature of chronic disease at all 4 …”

“…We obviously have to discriminate between an acute disease with long-lasting complications and an essentially chronic disease. There is a discontinuity between an infection or vaccination and the recognition of an autoimmune disease or multisymptom illnesses of a few weeks to two months 3,4,5,6 after the initiating event. In MS, as well, there is no development such as starting with an acute demyelinating meningoencephalitis and slowly becoming an MS 19,25 .…”

“…This is not a dose-effect relationship. The complex system for regulation of blood pressure has switched to a new attractor, the disease is a stable state 4,41,42,43,44 . The usual medical treatment suppresses only the symptoms but does not change the attractor 36 .…”

“…The set of data (< 70-80 uninterrupted serial time points) was too small for a reliable determination of the fractal dimension of the time series 33,34 . But the combined analysis of several time series according to the power law in double logarithmic diagrams allowed the exclusion of a statistical variation like a Gaussian error function 4,35,36 . This allows the conclusion that the time series of antibody concentrations in blood are a deterministic chaotic variation, different from noise.…”

“…There may be any trigger (infection or vaccination) that facilitates the phase transition between the healthy state and the pathological stable state 4,44 , as in case of a catalyst that is not a traceable part of the system. The nature of this change (due to amplified local metabolic fluctuations 43 ) also allows the possibility of a spontaneous change to a pathological state of lower complexity 41 without any external influence 4 .…”