Аутоиммунные проблемы из-за ковида

chuka_lis — 20.02.2022 — Коронавирус У здоровых людей аутоантитела присутствуют на физиологических уровнях, регулирующих множество физиологических функций, которые необходимы для поддержания гомеостаза организма. Однако аномальные уровни аутоантител часто являются доклиническими предвестниками  аутоиммунных заболеваний, и также способствовать или усугублять воспалительные состояния, нарушения гомеостаза, метаболизма, приводя, в том числе, к гибели "своих" клеток. Так что повышение уровня аутоантител при ковиде и после него могут иметь клинические последствия.
Ковид, как и некоторыые другие вирусные инфекции, может поспособствовать появлению  опасной для жизни генерализованной потере толерантности к своим тканям, с возникновением таких болезней (синдромов) как антифосфолипидный синдром, синдром Жиллиана-Барре, краниальный полиневрит, диабет 1 типа, провоцировать аутоиммунную гемолитическую анемию, болезнь Грейвса, иммунную тромбоцитопеническую пурпуру, артрит, системную красную волчанку итд. Среди недавно найденных аутоантител при ковиде - это выработка изза ковида иммунитета на интерфероны 1 типа, цитокины, хемокины и их рецепторы, а также факторы системы комплемента, рецепторы, связанные с G-белком и ренин-ангиотензиновой системой.  С ковидом ассоциируются так же "классическая" группа аутоантител (антиядерные антитела, антитела к рибосомным P белкам, белкам хроматина и антитела на тиреоидные антигены) наблюдаемая при аутоиммунных заболеваниях, и эти антитела коррелирует с тяжестью ковида- тоже. Ассоциированы с тяжелым течением ковида и антифосфолипидные аутоантитела (считают, что они могут играть роль в утяжелении болезни, провоцируя нейтрофилы на выбросы ДНК-сетей и способствуя венозному тромбозу)
Так что при ковиде (и после него) зачастую повышаются уровни аутоантител, нацеленных на свои белки и липиды,  и в том числе и на иммуно-регуляторные медиаторы, такие как как цитокины и хемокины. Есть данные, что ковид можетс пособствовать возникновению (развитию) аутоиммунных заболеваний, но причины этого явления не особо изучены. Так же, не совсем ясно, на сколько широк спектр этого осложнения (аутоиммунности: на какие белки-ткани). Чтобы получить больше информации, израильтяне провели всестороннюю оценку аутоантител (которые связаны с различными аутоиммунными заболеваниями), наблюдаемыми у пациентов с COVID-19, в когорте из 248 человек, из которых 171 были ковидные (74 с легкой, 65 средней, и 32 с тяжелыой формой течения) и 77 были здоровыми (контроль). У всех проверяли наличие аутоантител на 52 "своих" антигена, и оценивали его количественно.
Оказалось, что у тех, кто болеет и переболел ковидом средне и тяжелее, в организме наблюдается дисрегуляция уровней аутоантител IgG и IgA в сыворотке (в основнм, их больше "нормы"). Повышенные уровни аутоантител коррелировали с титрами противокоронавирусных антител, с аносмией и возрастом. В том смысле, что у тех, у кого была аносмия,  кто болел ятжелее, или кто старше - у тех шансы  на то, что в крови будут аутоантила в повышенных концентрациях, после ковида- выше. Выше аутоантитела- выше шансы на аутоиммунное заболевание как следствие ковида. Потому, ковид может послужить триггером для дальнейших аутоиммунных "осложнений".
Данные работы свидетельствуют, что коронавирус SARS-CoV-2 вызывает более широкую потерю толерантности к своим антигенам, чем считалось ранее.
All collected sera were tested for IgG anti-SARS-CoV-2 antibody using the ZEUS SARS-CoV-2 ELISA Test System according to the manufacturer’s instructions (ZEUS Scientific, New Jersey, USA). This is an ELISA test that measures IgG antibodies to spike and nucleoprotein combined. Serum IgG autoantibodies against nuclear antigen (ANA), extractable nuclear antigen (ENA), double-stranded DNA (dsDNA), actin, mitochondrial M2, and rheumatoid factor (RF) were measured using commercial ELISA kits obtained from INOVA Diagnostics (San Diego, CA, USA). In addition, IgG and IgA antibodies against 52 different autoantigens50–58 100 were measured by in-house ELISA procedure at Immunosciences Lab., Inc. (Los Angeles, CA USA) in blinded fashion.
Here we investigated the serum levels of IgG and IgA autoantibodies targeting 58 and 52 self-antigens, respectively, that are linked to a variety of autoimmune diseases (Fig. 1).
Multi-study factor analysis (MSFA)   revealed a progressive dysregulation in the number of latent factors from mild COVID-19 patients to those with moderate and severe disease. The two latter groups presented fewer latent factors when compared with control and mild COVID-19 groups, indicating by this statistical inference approach that the perturbation of normal autoantibody levels mostly occurs in patients with moderated and severe COVID-19. We found significantly elevated levels of IgG (Supplementary Fig. 1) and IgA (Supplementary Fig. 2) autoantibodies targeting a total of 42 and 25 antigens, respectively, when comparing COVID-19 groups (mild, moderate, and severe) versus healthy controls.
In agreement with the results obtained by MSFA, we observed a progressive increase of the autoantibodies targeting autoantigens 182 such as those associated with Alzheimer's disease (rabaptin-5, tau protein), antiphospholipid syndrome (cardiolipin), multiple sclerosis and other neuroimmune disorders (myelin basic protein), celiac disease (transglutaminases, zonulin), neuropsychiatric and neurodegenerative disorders (NMDAR), gut motility disorders (enteric nerve), liver autoimmunity (liver microsomal antigen), immune thrombocytopenia (platelet glycoprotein),myasthenia gravis (acetylcholine receptor, somatotropin), neurodegenerative foliaceus (Desmoglein-E-Cadherin 1), neurological disorders (S100B), rheumatic heart disease (-myosin), rheumatoid arthritis (-enolase, fibulin), systemic lupus erythematosus (cardiolipin, dsDNA, rabaptin-5), type 1 diabetes (islet cell antigen), immune thrombotic thrombocytopenia (heparin), and vitiligo (tyrosinase) . In addition, we also identified reduced levels of IgG autoantibodies such as those against a-myosin, rabaptin-5, S100B, and cerebellar as well as IgA autoantibodies targeting the NMDA R and cerebellar.
Thus, indicating a broad breakdown of physiological autoantibody levels/self-tolerance in patients with COVID-19 that paralleled disease severity. Of note, the progressive perturbation of autoantibody levels was accompanied by increased serum concentration of anti-SARS-CoV-2 antibodies These results indicate that, among others, COVID-19 patients have dysregulated levels of autoantibodies affecting in neurological functions such as memory, learning, and cognition. Taken together, our data indicate that autoantibodies may also be involved with altered learning, memory and neuroplasticity68 recently reported during SARS CoV-2 infection, which promotes a systemic inflammation milieu that might be neurotoxic. Autoantibody generation correlates with severe SARS-CoV-2 infection and anosmia the model was considered adequate to classify the COVID-19 patients by severity according to IgA and IgG autoantibodies, showing areas under the ROC curve of 0.91%, 0.85%, and 0.90% for the healthy control, moderate, and severe COVID-19 groups for IgA (Supplementary Fig. 6j) and 0.98%. 0.96% and 0.99% for IgG (Supplementary Fig. 6i).
In this context, autoantibodies tracked with anti- SARS-CoV-2 antibodies and age as predictive factors for COVID-19 outcome. Among them are IgG autoantibodies targeting the NMDA R, insulin, PG, LSPC, human RO60, claudin, heparin, and S100B, as well as IgA autoantibodies targeting cardiolipin, the NMDA R, HEK, cerebellar, ICA, AbP, DEC, -synucleins, and tyrosinase.
Thus, IgA and IgG autoantibodies stratify COVID-19 according to disease severity. To better understand the stratification power of the autoantibody predictors of COVID-19 outcomes, we performed principal component analysis (PCA) with a spectral decomposition approach to analyze whether the top 10 ranked variables (IgA and IgG autoantibodies and age) as predictors of COVID-19 severity have stratification power. This approach indicated, in accordance with the random forest modeling, that the ranked autoantibodies stratify COVID-19 patients according to disease severity. While healthy controls and patients with mild COVID-19 presented with similar autoantibody patterns, moderate and severe COVID-19 groups clustered closely.
Together, these results indicate that the immune responses against SARS-CoV-2 not only are associated with an increase of serum autoantibody levels linked to autoimmune diseases, but also have predictive stratification values for COVID-19 patients. SARS-CoV-2 infection dysregulates autoantibody levels in an age-dependent manner. However, only elderly patients with severe COVID- 19 presented with significant differences in most of the top 10 IgG (Fig. 6b) and IgA  autoantibodies when compared with young patients with severe disease.
Of note, except for autoantibodies targeting -enolase, cardiolipin, CS, DEC, dsDNA, ENA, elderly patients with severe COVID-19 had significant differences in all other IgG autoantibodies.In turn, IgA autoantibodies against 10 antigens displayed significant differences. comparing young COVID-19 patients to severe COVID-19 patients.
No age-dependent differences were observed regarding the levels of anti-SARS-CoV-2 antibodies. Of note, there were only a few (IgG autoantibodies targeting heparin and LSPC; SARS CoV-2 antibodies; IgA autoantibodies targeting cardiolipin, DEC, ICA, and tyrosinase) age dependent significant differences in patients with anosmia versus no anosmia regarding the top 10 autoantibody predictors of COVID-19 severity (Supplementary Fig. 8).
Furthermore, we asked whether sex also impacts the levels of autoantibodies during SARS-Co-2 infections. IgG anti-cardiolipin-aab was elevated in males from all three disease groups (but only significantly in mild and moderate COVID-19 cohorts) when compared to females. Except for this, there were no significant sex differences in the levels of the top 10 IgG and IgA autoantibody predictors of COVID-19 severity .
This work sheds light on the immunopathogenesis of COVID-19 demonstrating the presence of increased levels of IgG and IgA autoantibodies linked to diverse number of autoimmune diseases. Among them, are autoantibodies not yet reported in COVID-19 patients such as those targeting neuronal antigens (e.g., -synuclein, acetylcholine receptor, myeloid- peptide, -catenin, brain-derived neurotrophic factor, cerebellar antigen, chondroitin sulphate, dopamine receptors [D1 and D2], enteric nerve, ganglioside, glutamic acid decarboxylase, myelin basic protein, myelin oligodendrocyte glycoprotein, neurofilament proteins, NMDA receptor, rabaptin-5, somatotropin, S100B, tau protein, and transglutaminases 6) and non294 neuronal antigens (e.g., -enolase, -myosin, claudin-5 and -7, collagen, desmoglein-E-cadherin 1, epithelial sodium channel , fibulin,  fibrinogen, human epidermal keratin, insulin receptor, islet cell antigen, occluding, platelet glycoprotein, transglutaminases 2 and 3, tyrosinase, and zonulin).
Importantly, autoantibodies correlate with clinical features of SARS-CoV-2 infection such as disease severity and anosmia. Besides expanding the spectrum of autoantibodies associated with COVID-19 (e.g., cardiolipin, dsDNA, epithelial cell antigen, heparin, human RO, liver microsomal antigen, lung surfactant protein C)76 , our data also indicate that both disease severity and anosmia disrupt the physiological IgG and IgA autoantibody signatures.
These findings are consistent with the notion that autoantibodies are natural components of human physiology and become dysregulated under pathological conditions . Further supporting the concept that COVID-19 disrupts antibody physiology, anti-SARS-CoV-2 antibody levels accompany the levels of autoantibodies. Those antibodies targeting self- and non-self-antigens, along with age, are predictors of disease severity as classified by random forest modeling.
Viral-induced autoimmune diseases are due to multiple mechanisms such as molecular mimicry, epitope spreading , and bystander activation, all of which could possibly be involved in SARS-CoV-2 induced autoimmunity. Indeed, evidence has been provided for strong, chronic inflammation promoting the release of self-antigens and high cytokine levels activating bystander T-cells, and for molecular mimicry, all of which have been associated with severe COVID-19.
Molecular mimicry has been explored by assessing the SARS-CoV-2 proteome, which revealed the existence of 21 viral peptides that show at least 90% homology with human proteins known to be involved in autoimmune diseases such as multiple sclerosis and rheumatoid arthritis. Furthermore, it has been shown that monoclonal antibodies generated against SARS-CoV-2 proteins reacted with 28 out of 55 tested autoantigens. These observations may explain why the multiple serum autoantibodies causative to autoimmune diseases dysregulate their levels, perturbing their physiologic function. These findings are in line with reports from ours20 and other groups demonstrating that changes in autoantibody signatures affect physiologic and pathologicl immune homeostasis.
Our finding that the highest levels of anti-SARS-CoV-2 antibodies are achieved by patients with severe COVID-19 is in agreement with previous reports demonstrating a similar pattern of humoral immune response in critically ill COVID-19 patients. In addition, it was shown that the levels of anti-SARS-CoV-2 antibodies accompany longitudinally with the dysregulation of autoantibody levels.
While we found no age effect on the levels of anti-SARS CoV-2 antibodies, severe SARS-CoV-2 infection induces higher autoantibody levels in elderly patients compared with young patients. Thus, our data point to novel mechanisms involved in the risk intersection of immunosenescence and COVID-19, suggesting that SARS-CoV-2 infection induces a broader loss of self-tolerance than previously thought, particularly in elderly patients. In this context, several age-associated factors such as chronic inflammation in ageing (inflammageing) might promote the production of autoantibodiesas well as the tendency to naturally progress to immune dysregulation of innate and adaptive immune cells. Therefore, our data support the idea that the induction of high levels of serum autoantibodies in elderly COVID-19 patients contribute to the increased risk for negative outcomes in older persons. For instance, while anti-cardiolipin antibodies were previously associated with the development of hyperinflammatory syndromes , the high levels of autoantibodies targeting neuronal-associated molecules could provide clues why the respiratory symptoms of COVID-19 patients are often accompanied by short- and long-term neuropsychiatric symptoms and brain sequelae . It has been convincingly shown that SARS-CoV-2 is able enter the brain by crossing the blood-brain barrier (BBB) because inflammatory cytokines induce BBB instability.
Our data indicate that the array of autoantibodies targeting neuronal molecules is an additional molecular layer that could contribute to the neurological manifestationsoccuring in COVID-19 patients.

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