T Cell Receptor Variable Regions in Diabetes Bind to Each Other, to Insulin, Glucagon or Insulin Receptor, and to Their Antibodies

Abstract

Our objective is to elucidate the nature of the autoimmune disregulation in diabetes through the antigen specificity of the T-cell receptor (TCR) sequences generated by patients with type 1 diabetes mellitus (T1DM). Previously we demonstrated that TCR from T1DM patients and NOD mice mimic insulin, glucagon and their receptors. We hypothesize that these TCR will bind to each other (as insulin and glucagon do to their receptors) and also be targets of anti-insulin and anti-glucagon antibodies. The hypervariable regions of multiple TCR from three patients were synthesized and their binding specificities determined using UV spectroscopy. ELISA was used to determine whether these TCR were recognized by anti-insulin and anti-glucagon antibodies. Each patient produced TCR that recognized insulin, glucagon and the insulin receptor (IR). These TCR also recognized each other as complementary (possibly idiotype-antiidiotype) pairs. In addition, each TCR peptide was recognized with nanomolar affinity as an antigen by an antibody against insulin, glucagon, and/or IR. Finally, each of the antibodies against insulin, glucagon and IR formed a complementary antibody (or idiotype-antiidiotype) pair with another antibody involved in the disease, again at nanomolar affinities. Every possible expression of complementarity (or idiotype-antiidiotype cross-reactivity) involving TCRs and antibodies was manifested by each patient. Two interpretations of these observations are offered. One, following Marchelonis, is that TCR-antibody complementarity is a mechanism for down-regulating the autoimmune process to re-establish tolerance to self-antigens. A non-exclusive alternative is that the trigger for autoimmunity is antigenic complementarity, which results in the production of complementary TCR and antibodies that appear to have idiotype-antiidiotype relationships among themselves.

Possible Cross-Reactivity between SARS-CoV-2 Proteins, CRM197 and Proteins in Pneumococcal Vaccines May Protect Against Symptomatic SARS-CoV-2 Disease and Death

“…The LALIGN results were culled by applying the criterion that any sequence similarity reported must have an E value of less than either 0.1 ( Table 2 ) or 1.0 ( Table 3 ), a Waterman–Eggert score of more than 50, and a region containing at least six out of ten identities. These criteria are based on a number of experimental studies involving the average length of peptide recognized by major histocompatibility (MHC) receptors and T cell receptors (TCR), which is about 10 consecutive amino acids [ 13 , 14 , 15 ], and the degree of similarity between two antigens that is likely to induce cross-reactive immune responses, which generally consists of at least five consecutive identical amino acids or six identities distributed within a 10 amino acid sequence [ 14 , 16 , 17 , 18 , 19 , 20 ].In essence, setting the E value to 0.1 or 1.0 determines how many matches the BLAST program will yield. The lower the E value, the less matches BLAST will yield because a lower E value limits the matches to those with rare combinations of amino acids such as methionines, tryptophans, tyrosines, cysteines, etc., rather than ones made up of sequences of very common amino acids such as glycine, alanine, valine and leucine, which appear at high rates in almost all proteins.…”

“…Thus, limiting the Waterman–Eggert score to more than 50 provides reasonable assurance that any sequence that appears in the BLAST search will display a high proportion of amino acid identities and similarities. Experience shows [ 16 , 17 , 18 , 19 , 20 ] that the combination of low E value and high Waterman–Eggert score tends to yield reasonably short sequences of high similarity, which is emphasized by using BLOSUM80. Despite using these boundary conditions, however, experience shows that about half of the sequences that BLAST yields are unlikely to be antigenically cross-reactive.…”

<strong>A General Theory of Autoimmune Disease Causation: Integrating Innate and Adaptive Immunity, Altered Antigen Processing, Sex and Genetic Predispositions, and Microbiome Effects</strong>

“…A similar situation exists in type 1 diabetes mellitus (T1DM), in which antibodies to both insulin and its receptor (which are obviously complementary to each other) as well as to glucagon (which is complementary to insulin) are present, and the complementary pairs of antibodies precipitate each other (Root-Bernstein & Dobbelstein, 2001). Moreover, TCR in T1DM also express complementary sequences that mimic insulin, its receptor and glucagon; these TCR sequences bind to each other; and the TCR are targets for T1DM autoantibodies (Root- Bernstein & Podufaly, 2012). Such anti-idiotype T cells are known to exist, but have not, apparently, yet been documented in AD perivascular cuffs.…”

Unresolved issues in theories of autoimmune disease using myocarditis as a framework

“…ACT has been applied theoretically to understanding a number of autoimmune diseases including EAE [185, 186, 194–200], idiopathic thrombocytopenia purpura [201, 202], and autoimmune myocarditis [81]. …”

“…Another way to test for antigenic complementarity is to perform enzyme-linked immunoadsorption assays (ELISA) or Ouchterlony immunodiffiusion experiments to determine whether antibodies against one antigen or pathogen bind specifically to antibodies against another [81]. Alternatively, TCR sequences specific to the potential pathogen pairs can be synthesized and the ability to recognize each other determined [200]. None of these experiments should be successful according to other theories.…”