The level of α7, β2 or β4 nAChR subunits in the brain sections of experimental mice studied by immunohistochemistry.

<p>Confocal microscopy images of the hippocampus CA1 and striatum of non-treated (Ctrl), α7(1–208)-immunized or LPS-injected mice stained with biotinylated α7-, β2- or β4-specific antibodies and developed with Extravidin-Cy3 (<i>red</i>). Cell nuclei are stained with DAPI (<i>blue</i>). Bar corresponds to 50μm, actual for each fragment of the panel.</p

Visualization of biotinylated antibody within the brain at different periods after injection.

<p>Confocal microscopy images of the striatum of mice injected with α7(1–208)-specific antibody (A-B) or non-specific IgG (C) in 15 min (A) or 3h (B-C) after injection. Antibodies were developed with Extravidin-Cy3 (<i>red</i>). Bar corresponds to 100μm, actual for each fragment of the panel. D—Antibody-specific ELISA signal of the primary brain supernatants and detergent lysates of mice either pre-treated or not with LPS; the brains were removed in 15 min or 3 h after the antibody injection. Each column corresponds to mean±SE of three repeats in ELISA; *—p<0.05; **—p<0.005 compared to the data of LPS non-treated mice.</p

The GFAP-positive astrocytes (A) and the number of nucleated cells (B) in the brain sections of experimental mice studied by immunohistochemistry.

<p><b>A</b>—Confocal microscopy images of the hippocampus CA1 (Hip), motor/somatosensory cortex (Crtx) or striatum (Str) of non-treated (Ctrl), α7(1–208)-immunized or LPS-injected mice stained with rabbit GFAP-specific antibody and developed with anti-rabbit Alexa 488 (<i>green</i>). Cell nuclei are stained with DAPI (<i>blue</i>). Bar corresponds to 50μm, actual for each fragment of the panel. <b>B</b>—The number of nucleated cells (DAPI-positive) in corresponding brain regions studied in all available sections (12 to 16 for each treatment for each region); *—p<0.05; **—p< 0.005.</p

The levels of different Aβ isoforms in the brain detergent lysates of experimental mice studied by Sandwich ELISA.

<p><b>A</b>—total Aβ₄₀ and Aβ₄₂, <b>B</b>—Aβ₄₀ and Aβ₄₂ bound to α7 nAChR in mice immunized with 7(1–208) (n = 8) or injected with LPS (n = 5) compared to non-treated animals (Ctrl, n = 9) and to those “immunized” with complete Freund’s adjuvant (CFA, n = 5). The columns correspond to M±SE (n = 5); *—p<0.05; **—p<0.005; ***—p<0.0005 compared to Ctrl.</p

The level of Aβ₄₀ and Aβ₄₂ in the brain sections of experimental mice studied by immunohistochemistry.

<p>Confocal microscopy images of the hippocampus CA1 or motor/somatosensory cortex of non-treated (Ctrl), α7(1–208)-immunized or LPS-injected mice stained with biotinylated Aβ₄₀- or Aβ₄₂-specific antibodies and developed with Extravidin-Cy3 (<i>red</i>) and with α7-specific antibody developed with anti-rabbit Alexa 488 (<i>green</i>). Bar corresponds to 50μm, actual for each fragment of the panel.</p

Episodic memory of experimental mice studied in the “Novel Object Recognition” test.

<p>Discrimination indexes calculated for mice immunized with 7(1–208) (n = 8) or injected with LPS (n = 5) compared to non-treated animals (n = 9) or those “immunized” with complete Freund’s adjuvant (CFA, n = 5). ***—p<0.0005 compared to non-treated mice (Ctrl).</p

The level of nAChR-specific antibodies in the blood and of nAChR subtypes in the brain of experimental mice studied by ELISA (A) or Sandwich ELISA (B).

<p><b>A</b>—7(1–208)-specific antibodies in the blood sera (1:50) of mice immunized with 7(1–208) (n = 8) or injected with LPS (n = 5) for 5 months compared to non-treated (Ctrl, n = 9) and adjuvant-“immunized” animals (CFA, n = 5). <b>B</b>—3, 4, 7, β2 and β4 nAChR subunits in the brain detergent lysates of the same groups of mice (4 mice from each group). <b>C</b>—Pearson coefficients (R) of correlation between the levels of nAChR subunits in the brain and those of 7(1–208)-specific antibodies in the blood. The columns correspond to M±SE, *—p<0.05; **—p<0.005; ***—p<0.0005 compared to Ctrl.</p

Additional file 1: Table S1. of Dental follicle mesenchymal stem cell administration ameliorates muscle weakness in MuSK-immunized mice

Clinical incidences, average clinical grades, and inverted screen hang times of MuSK-immunized mice treated with different mesenchymal stem cell (MSC) types and cell numbers during optimization studies. The values were obtained at termination (28 days after the third MuSK immunization) and each experiment was done with 10 mice per mouse group. Note that lowest experimental autoimmune myasthenia gravis (EAMG) clinical scores were obtained with administration of dental follicle MSCs and with 1 × 106 cells per injection (two injections in total). Immunization and MSC injection were done as described in the “Methods” section. (DOC 29 kb

Table_2_PheWAS and cross-disorder analysis reveal genetic architecture, pleiotropic loci and phenotypic correlations across 11 autoimmune disorders.xlsx

IntroductionAutoimmune disorders (ADs) are a group of about 80 disorders that occur when self-attacking autoantibodies are produced due to failure in the self-tolerance mechanisms. ADs are polygenic disorders and associations with genes both in the human leukocyte antigen (HLA) region and outside of it have been described. Previous studies have shown that they are highly comorbid with shared genetic risk factors, while epidemiological studies revealed associations between various lifestyle and health-related phenotypes and ADs.MethodsHere, for the first time, we performed a comparative polygenic risk score (PRS) - Phenome Wide Association Study (PheWAS) for 11 different ADs (Juvenile Idiopathic Arthritis, Primary Sclerosing Cholangitis, Celiac Disease, Multiple Sclerosis, Rheumatoid Arthritis, Psoriasis, Myasthenia Gravis, Type 1 Diabetes, Systemic Lupus Erythematosus, Vitiligo Late Onset, Vitiligo Early Onset) and 3,254 phenotypes available in the UK Biobank that include a wide range of socio-demographic, lifestyle and health-related outcomes. Additionally, we investigated the genetic relationships of the studied ADs, calculating their genetic correlation and conducting cross-disorder GWAS meta-analyses for the observed AD clusters.ResultsIn total, we identified 508 phenotypes significantly associated with at least one AD PRS. 272 phenotypes were significantly associated after excluding variants in the HLA region from the PRS estimation. Through genetic correlation and genetic factor analyses, we identified four genetic factors that run across studied ADs. Cross-trait meta-analyses within each factor revealed pleiotropic genome-wide significant loci.DiscussionOverall, our study confirms the association of different factors with genetic susceptibility for ADs and reveals novel observations that need to be further explored.</p

Table_1_PheWAS and cross-disorder analysis reveal genetic architecture, pleiotropic loci and phenotypic correlations across 11 autoimmune disorders.xlsx

IntroductionAutoimmune disorders (ADs) are a group of about 80 disorders that occur when self-attacking autoantibodies are produced due to failure in the self-tolerance mechanisms. ADs are polygenic disorders and associations with genes both in the human leukocyte antigen (HLA) region and outside of it have been described. Previous studies have shown that they are highly comorbid with shared genetic risk factors, while epidemiological studies revealed associations between various lifestyle and health-related phenotypes and ADs.MethodsHere, for the first time, we performed a comparative polygenic risk score (PRS) - Phenome Wide Association Study (PheWAS) for 11 different ADs (Juvenile Idiopathic Arthritis, Primary Sclerosing Cholangitis, Celiac Disease, Multiple Sclerosis, Rheumatoid Arthritis, Psoriasis, Myasthenia Gravis, Type 1 Diabetes, Systemic Lupus Erythematosus, Vitiligo Late Onset, Vitiligo Early Onset) and 3,254 phenotypes available in the UK Biobank that include a wide range of socio-demographic, lifestyle and health-related outcomes. Additionally, we investigated the genetic relationships of the studied ADs, calculating their genetic correlation and conducting cross-disorder GWAS meta-analyses for the observed AD clusters.ResultsIn total, we identified 508 phenotypes significantly associated with at least one AD PRS. 272 phenotypes were significantly associated after excluding variants in the HLA region from the PRS estimation. Through genetic correlation and genetic factor analyses, we identified four genetic factors that run across studied ADs. Cross-trait meta-analyses within each factor revealed pleiotropic genome-wide significant loci.DiscussionOverall, our study confirms the association of different factors with genetic susceptibility for ADs and reveals novel observations that need to be further explored.</p