Table of Contents

Th1 Spectrum Disorder

Th1 Spectrum Disorder refers to the group of chronic inflammatory diseases, which are hypothesized to be caused by the Th1 pathogens, a microbiota of bacteria which include L-form, biofilm, and intracellular bacterial forms. Although the exact species and forms of bacteria, as well as the location and extent of the infection, vary between one patient suffering from chronic disease and the next, the disease process is common: bacterial pathogens persist and reproduce by disabling the innate immune response.

Although patients who become infected with the Th1 pathogens are given a variety of diagnoses, there are often no clear cut distinctions between one disease and the next. Rather, symptoms frequently overlap creating a spectrum of illness in which diseases are more connected to one another than mutually exclusive disease states.

The evidence that chronic disease is ultimately a spectrum disorder caused by a common infectious cause includes:

Conflict in theories

Traditionally, diseases are understood to be discrete and have their own respective and distinct pathologies. This theory of disease has been advanced by researchers intent upon pinpointing the human genes which they theorize cause disease. The existence of a vast network of clinical specialists and sub-specialists only reinforces this idea.

According to the Marshall Pathogenesis, the range of chronic diseases is caused by a common etiology or disease process. Patients accumulate Th1 pathogens, which proliferate by disabling the Vitamin D Receptor and consequently weakening the</html> innate immune response.

Comorbidity of inflammatory diseases

One of the striking features of a variety of neuropsychiatric diseases (e.g., affective disorders) is their variance, with differences observed across individuals in terms of their susceptibility, in the combination of systems that are disturbed, and in the therapeutic and adverse responses to various medications…. The microbiome [may represent] a source of this observed variance.

A. Gonzalez et al.1

When the Th1 pathogens compromise the immune response, they make it easier for other types of bacteria in other locations to infect the body as well. This phenomenon is known as comorbidity. Although a comorbid condition is traditionally understood to be unrelated to the underlying condition, the sheer number of common comorbidities points to a common pathology.

Epidemiological research may have its share of liabilities, but one contribution it has made is in demonstrating the strong connections between seemingly disparate diseases as evidenced by the number of patients who share diagnoses with two or more “unrelated” disease processes.

The following wheel shows how truly related chronic diseases are. Each “spoke” represents a published study which has demonstrated a significant statistical relationship between patients suffering from one disease and the next.

The following paragraph contains links to all the studies alluded to in the above chart. Please note that some of the disease names are links to articles discussing those diseases in further detail.

allergies 2 alopecia areata 3 4 Alzheimer's disease & dementia 5 6 ankylosing spondylitis 7 8 9 anorexia nervosa 10 anxiety disorders 11 12 13 14 15 16 17 18 19 arthritis 20 21 22 23 24 25 26 asthma 27 28 29 30 31 32 33 34 35 36 37 38 bipolar disease 39 40 41 42 cancer 43 44 45 46 cardiac disease 47 48 49 50 51 52 53 54 55 56 cardiovascular disease 57 58 59 60 61 celiac disease 62 63 64 65 chronic fatigue syndrome 66 67 68 chronic obstructive pulmonary disease 69 depression 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 diabetes 87 88 89 90 91 92 93 diabetes, type1 94 95 96 diabetes, type2 97 fibromyalgia 98 99 Guillain-Barré syndrome 100 101 hypertension 102 103 inflammatory bowel disease (Crohn's disease and ulcerative colitis) 104 105 106 107 108 109 110 111 112 113 114 115 116 117 lupus 118 119 120 121 122 multiple chemical sensitivity 123 multiple sclerosis 124 125 126 127 128 129 130 myasthenia gravis 131 obesity 132 133 134 135 136 obsessive compulsive disorder 137 138 139 140 141 osteoporosis 142 143 144 145 Parkinson's disease 146 147 148 149 periodontal disease 150 151 pernicious anemia 152 psoriasis 153 154 155 156 157 rheumatoid arthritis 158 159 160 sarcoidosis 161 162 schizophrenia 163 164 165 scleroderma 166 Sjogren's syndrome 167 168 169 170 thyroiditis (Graves' disease and Hashimoto's thyroiditis) 171 172 173 174 175 176 177 uveitis 178 179 vitiligo 180

Infrequency with which patients suffer from only a single disease

25% of Americans have more than one chronic condition.

To control for confounding variables, researchers often exclude patients with more than one condition from research studies even though they represent the majority of patients. Jeste et al made this observation in patients with schizophrenia181 and there's no reason to think it's any different with other patient groups.

A recent survey of Marshall Protocol patients, discussed in Amy Proal's presentation at Congress on Autoimmunity, showed that of those with Hashimoto's thyroiditis, only 8% had been diagnosed with Hashimoto's alone.

The challenge of diagnosing diseases caused by bacteria

Many doctors are reluctant to say that chronic diseases are caused by bacterial pathogens and for a couple reasons.

No consistent symptom presentation

Medicine has difficulty diagnosing disorders where there is no consistently identified anatomic abnormality or documented metabolic/physiological dysfunction.182

Diagnoses are driven by perceived therapeutic options

What a clinician thinks causes many of the ill-defined chronic diseases may in fact be shaped by available treatment options for that disease.

Consider dentists. Most dentists will readily concede that bacteria cause plaque and tooth decay. The fact that a dentist can employ a therapy against plaque (in this case, manually removing plaque) clearly shapes their opinion about the etiology of the disease. That the intervention is at least temporarily effective also has something to do with it, but perhaps not as much as most people might imagine.

When it comes to lethargy or exercise intolerance or difficulty breathing or any number of other symptoms of disease, the explanation for the disease's etiology is often driven by the available mainstream treatment options, of which very few are effective. These options are themselves highly influenced by pharmaceutical companies which have a vested interest in selling a drug or treatment. In their drive to differentiate themselves and their product, these companies will overemphasize the distinctions among diseases when there may be no such fundamental differences.

False assurance of diagnostic compartmentalization

Another challenge relates to how diseases are segmented into categories even when the nature of the diseases themselves don't warrant such fine-graded distinctions.

One who pores through the articles of a medical textbook could easily form the impression that diseases are discrete, well-defined and mutually exclusive. The reality is that the nature of illness is such that diagnosis is often inexact. Over the past few decades, the sensitivity and specificity of diagnostic tests has, in many cases, increased dramatically. Yet, neither precision nor accuracy is useful when two test results for a patient suggest conflicting diagnoses.

To resolve this ambiguity, epidemiologists have developed a kind of stop-gap measure: rubrics - many of them “evidence-based” - for diagnosing disease. A rubric is a checklist of sorts. Doctors who diagnose according to a rubric look to see if a patient has at least a certain number of classical symptoms - say, eight of the twelve symptoms listed. Given that the vagaries of any one chronic disease are determined by patients' unique pea soup, that is, their particular mix of Th1 pathogens, the traditional methods for diagnosis leave a great deal to be desired.

Patients presenting with prototypical cases of a given disease tend to be the exception rather than the rule. They may have some of the classical symptoms of a given disease but not others. Also, patients may have symptoms that are unique to a different disease. Patients with symptoms of chronic disease could present five different doctors with the same set of symptoms and get five different diagnoses, and many have!

Excessive testing

In the face of uncertainty and ambiguity, a clinician's natural response might be to order a battery of tests. After all, the more information clinicians obtain, the more confidence they have in the validity of their diagnoses, even when such confidence may not be justified on the basis of the information obtained.

In his paper, “Our stubborn quest for diagnostic certainty: a cause of excessive testing,” JP Kassirer writes:

Absolute certainty in diagnosis is unattainable, no matter how much information we gather, how many observations we make, or how many tests we perform. Our task is not to attain certainty, but rather to reduce the level of diagnostic uncertainty enough to make optimal therapeutic decisions…. We continue to test excessively, partly because of our discomfort with uncertainty.

Jerome Kassirer, MD 183

A 2011 article in the Daily Beast shows how some common tests and procedures may do more harm than good.

A single diagnosis for chronic inflammatory disease

Given that all of the so-called autoimmune diseases and chronic infections are a variation of the Th1 inflammatory process, neither a specific diagnostic label or identification of specific pathogens is needed to begin the Marshall Protocol (MP). With the MP, patients identify Th1 inflammation with simple blood tests and then confirm the presence of occult microbes with a therapeutic probe. As treatment continues, the presence of the immune system reactions confirms the continuing efficacy of treatment. And finally, symptom resolution, absence of immune system reactions and normal blood work indicate recovery.

Where the MP is unique is that I set out to kill pathogens which have never been fully identified, whose exact nature is still largely unknown. I did this based on an understanding of the pathogens' biochemical effects on the body, and the consequent understanding of how they must therefore be exerting that effect…. We have focused on the commonalities, rather than the differences, between immune disease syndromes, and this tends to make it easier to distinguish the forest from the trees.

Trevor Marshall, PhD

A corollary of this principle is that attempts to compare one patient's disease with another's are futile. Certainly there is a great deal of variability in the location and severity of infection and the corresponding symptoms, but ultimately there is no fundamental difference between the state of patients' disease states and there is, therefore, no difference in their ultimate recovery trajectories.

Health and disease is a continuum

Related article: Th1 Spectrum Disorder

…because the women are all healthy when they enroll [then any disease can be detected as they continue sampling from that time].

Claire Fraser-Liggett, Director of the Institute for Genome Sciences at the University of Maryland, BBC Radio 4 program about the Human Microbiome

It is common practice to assign one group of patients participating in a controlled trial to be the “healthy control group.” While researchers are apt to make a hard distinction between health and disease, this dichotomy is contrary to what we know about successive infection.

The process of successive infection does not just occur in sick people or people who are symptomatic. In healthy subjects, subclinical infection is not the exception, but the rule. For example:

  • 30% of healthy people are carriers of the pathogen Staphylococcus aureus.184
  • A 2011 pyrosequencing study looked at 16S rDNA amplicons of eight culture-negative healthy female urine specimens.185 The study found a significant amount of sequences belonging to bacteria with a known pathogenic potential.

From even before birth, every human is constantly acquiring new microbes as demonstrated in several studies186 by Rob Knight and Jeffrey Gordon's team. After sequencing the microbiome of two individuals at four body sites over 396 timepoints, the group essentially concluded that the notion of a “core microbiome” is overblown.

We find that despite stable differences between body sites and individuals, there is pronounced variability in an individual's microbiota across months, weeks and even days. Additionally, only a small fraction of the total taxa found within a single body site appear to be present across all time points, suggesting that no core temporal microbiome exists at high abundance (although some microbes may be present but drop below the detection threshold). Many more taxa appear to be persistent but non-permanent community members.

J. Gregory Caporaso et al. 187

Clearly, the microbiota can be affected in any number of ways that are not picked up by the relatively crude tests that we use to measure “health.” Further, patients carry pathogenic elements of their microbiota but without the symptoms to show for it – at least initially.

The variability of patients' responses – both between control and experimental groups, and among an experimental group (some subjects get a side effect, some don't) – may ultimately be a testament to the unique nature of each person's microbiota.

Because everyone person's microbiota is unique, it may be overly simplistic, if not naive, to say there is such a thing as a person who is truly healthy.

Keywords:

Notes and comments

Should this article be chronic inflammatory spectrum disorder?

Studies to add:

Integrate into above sections how psychiatry's diagnoses are in a state of turmoil:

Links Between Hypertension, Bipolar Disorders Identified

http://www.sciencedaily.com/releases/2010/06/100610171716.htm

“There is a large clinical relevance to the finding hypertension could be linked to the severity of bipolar disorders,” he said. “There is some similarity to the pathology of the two conditions; they both can be triggered by stress and are tied to the excretion of norepinephrine, a hormone affecting how the brain reacts to stress.”

Arch Dermatol. 2009 Apr;145(4):379-82. Psoriasis and the risk of diabetes and hypertension: a prospective study of US female nurses.

Qureshi AA, Choi HK, Setty AR, Curhan GC. Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, 45 Francis St, 221L, Boston, MA 02115, USA. abrar.qureshi@channing.harvard.edu Comment in: Arch Dermatol. 2009 Apr;145(4):467-9. Abstract OBJECTIVE: To evaluate the independent association between psoriasis and risk of diabetes and hypertension. DESIGN: A prospective study of female nurses who were followed up from 1991 to 2005. SETTING: Nurses' Health Study II, a cohort of 116 671 US women aged 27 to 44 years in 1991. PARTICIPANTS: The study included 78 061 women who responded to a question about a lifetime history of physician-diagnosed psoriasis in 2005. Women who reported a diagnosis of diabetes or hypertension at baseline were excluded. Main Outcome Measure New diagnosis of diabetes or hypertension, obtained from biennial questionnaires. RESULTS: Of the 78 061 women, 1813 (2.3%) reported a diagnosis of psoriasis. During the 14 years of follow-up, a total of 1560 incident cases (2%) of diabetes and 15 724 incident cases (20%) of hypertension were documented. The multivariate-adjusted relative risk of diabetes in women with psoriasis compared with women without psoriasis was 1.63 (95% confidence interval, 1.25-2.12). Women with psoriasis were also at an increased risk for the development of hypertension (multivariate relative risk, 1.17; 95% confidence interval, 1.06-1.30). Age, body mass index, and smoking status did not significantly modify the association between psoriasis and risk of diabetes or hypertension (P values for interaction, > or =.07). CONCLUSIONS: In this prospective analysis, psoriasis was independently associated with an increased risk of diabetes and hypertension. Future studies are needed to find out whether psoriasis treatment will reduce the risk of diabetes and hypertension. PMID: 19380659

http://www.drugs.com/news/autoimmune-disorder-linked-stroke-heart-attack-women-20088.html

Lancet Neurol. 2009 Nov;8(11):998-1005. Epub 2009 Sep 25. Antiphospholipid antibodies and risk of myocardial infarction and ischaemic stroke in young women in the RATIO study: a case-control study.

Urbanus RT, Siegerink B, Roest M, Rosendaal FR, de Groot PG, Algra A. Department of Clinical Chemistry and Haematology, University Medical Centre Utrecht, Utrecht, Netherlands. Comment in: Womens Health (Lond Engl). 2010 Mar;6(2):179-82. Lancet Neurol. 2009 Nov;8(11):971-3. Abstract BACKGROUND: Arterial thrombosis is a major clinical manifestation of the antiphospholipid syndrome, which is an autoimmune disease found mostly in young women. Although the presence of circulating antiphospholipid antibodies in individuals who have a thrombotic event is a prerequisite for the diagnosis of the antiphospholipid syndrome, the risk of arterial thrombosis associated with antiphospholipid antibodies in the general population is unclear. METHODS: In RATIO (Risk of Arterial Thrombosis In relation to Oral contraceptives), a large multicentre population-based case-control study, we enrolled women aged under 50 years who were admitted to hospital at 16 centres with first ischaemic stroke or myocardial infarction between January, 1990, and October, 1995. An additional 59 women who presented with ischaemic stroke at the University Medical Centre Utrecht between 1996 and 2001 were also enrolled. Information on cardiovascular risk factors (such as oral contraceptive use, smoking, and hypertension) were assessed with a standard questionnaire. During the second phase (1998-2002), blood samples were taken to measure antiphospholipid antibody profiles (lupus anticoagulant, anticardiolipin IgG, anti-beta(2)-glycoprotein I IgG, and antiprothrombin IgG) and to determine genetic prothrombotic risk factors (factor V G1691A variant, prothrombin G20210A variant, and factor XIII 204Phe allele). FINDINGS: 175 patients with ischaemic stroke, 203 patients with myocardial infarction, and 628 healthy controls were included. Patients were frequency matched with controls for age, residence area, and index year. Lupus anticoagulant was found in 30 (17%) patients with ischaemic stroke, six (3%) patients with myocardial infarction, and four (0.7%) in the control group. The odds ratio for myocardial infarction was 5.3 (95% CI 1.4-20.8), which increased to 21.6 (1.9-242.0) in women who used oral contraceptives and 33.7 (6.0-189.0) in those who smoked. The odds ratio for ischaemic stroke was 43.1 (12.2-152.0), which increased to 201.0 (22.1-1828.0) in women who used oral contraceptives and 87.0 (14.5-523.0) in those who smoked. In women who had anti-beta(2)-glycoprotein I antibodies, the risk of ischaemic stroke was 2.3 (1.4-3.7), but the risk of myocardial infarction was not increased (0.9, 0.5-1.6). Neither anticardiolipin nor antiprothrombin antibodies affected the risk of myocardial infarction or ischaemic stroke. INTERPRETATION: Our results suggest that lupus anticoagulant is a major risk factor for arterial thrombotic events in young women, and the presence of other cardiovascular risk factors increases the risk even further. FUNDING: Netherlands Heart Foundation and Leducq Foundation. PMID: 19783216

Neuropsychiatric disorders more common in rheumatologic disease Concise summaries of recent journal articles chosen for clinical significance June 21, 2008 Sundquist K, Li X, Hemminki K, Sundquist J, Karolinska Institute, Huddinge, Sweden, and German Cancer Research Center, Heidelberg. Subsequent risk of hospitalization for neuropsychiatric disorders in patients with rheumatic diseases: a nationwide study from Sweden.Arch Gen Psychiatry. 2008;65:501-507. Neuropsychiatric disorders are more likely to develop in patients with a rheumatologic disease—rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), or ankylosing spondylitis (AS)—than in the general population. Some subgroups with rheumatologic disease seem to be more vulnerable than others. Sundquist and associates conducted a cohort study of hospitalizations in Sweden for RA, SLE, and AS and for subsequent affective, psychotic, neurotic, and personality disorders, as well as for dementia and delirium, for the entire Swedish population. Age-standardized incidence ratios (SIRs) were calculated for the whole follow-up period. In most age groups, rates of psychiatric disorders were higher in persons who had rheumatologic diseases than in the general population.The highest risks were found in men and women with SLE (significant SIRs, 2.38 and 2.16, respectively); those with AS also were at higher risk than those with RA. The risk of severe depression was increased in women with SLE and those with RA. There was an increased risk of dementia and delirium in persons with SLE. The authors noted that their study adds to the literature because it took a novel approach, studying an entire population to examine the association between rheumatologic diseases and neuropsychiatric disorders.

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