ars.els-cdn.com · Web viewSputum Ig Isotyping (IgA, IgM, IgG, IgE): For detecting the total IgG, IgA and IgM quantity in each sputum sample, 96-well MaxiSorb (Nunc) plates were coated

Mukherjee et al., 2016

Online Methods:

All ELISAs for sputum and animal samples were developed in our laboratory using the reagents

from KPL Inc., (Gaithersburg, MA, USA), unless otherwise stated.

Sputum Ig Isotyping (IgA, IgM, IgG, IgE): For detecting the total IgG, IgA and IgM quantity in

each sputum sample, 96-well MaxiSorb (Nunc) plates were coated with the respective sputum

IP-Igs at a dilution of 1:50 (in PBS), separately for each subtype. ChromPure Human IgG, IgM

and IgA (Jackson ImmunoResearch Laboratories, PA, USA) were used for constructing the

standard curve. The Igs were allowed to attach at 37˚C for 1.5 hrs, followed by a thorough-wash

and 1 hr of blocking (1% BSA) at RT. Biotinylated secondary antibodies (BD Biosciences, ON,

Canada) against human IgG (1:2000 dilution), IgM (1:1000) and IgA (1:1000) were added to the

respective wells for 1 hr at RT, and subsequently the plates were developed and absorbance read

at 600 nm. A 4PL-standard curve was used to analyse the unknowns. In addition, since Protein

A/G does not bind IgE, the total IgE levels in all 79 sputum supernatants were tested with a

Human IgE SinglePlex kit (Eve Technologies, Calgary, Canada).

Immunostaining of eosinophils with Sputum Igs

Human peripheral blood eosinophils were isolated from the venous blood of atopic donors, as

previously described (E1). Cells were re-suspended in serum-free RPMI 1640 at 1 x 106/mL, and

coated onto glass coverslips for 15 min at 37°C, and fixed with 4% PFA for 20 min. Cells were

then permeabilized with 0.1% Triton X-100 in PBS for 3 min prior to blocking with 2% bovine

serum albumin and 2% goat serum in PBS to reduce nonspecific binding by antibodies. Sputum

Igs were diluted in blocking buffer and added to permeabilized eosinophils and incubated at RT

for 1 hr. For co-localization studies, mouse anti-EPX monoclonal antibody (clone MM25-

429.1.1) was used. Secondary antibody labelling was carried out with Alexa 488-conjugated

E1Supplementary material

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anti-human IgG and Cy3-conjugated anti-mouse IgG secondary antibodies (Life Technologies,

Inc.). Images were captured on a Deltavision OMX super resolution microscope using a 60X

objective, and fluorescence was quantified on a Leica SP5 confocal microscope. Image analysis

was carried out using Fiji by ImageJ to determine total cellular fluorescence values.

Mice models of airway degranulation

The double transgenic model of severe respiratory inflammation (I5/hE2) was created from a

cross of NJ.1638 mice (a transgenic line of mice generated by driving constitutive expression of

a cDNA/genomic fusion gene of mouse IL-5 using a CD3δ promoter/enhancer construct (E2, E3)

with another transgenic strain constitutively expressing the human eotaxin 2 gene in central

airway epithelial cells (i.e., Clara cells) using a rat secretory protein CC10 promoter (E4). These

individual transgenic lines were created on a C57BL/6J background and subsequent generations

of transgenic animals were the result of backcrosses (every 5th generation) onto inbred strain

C57BL/6J and have been in this breeding program for >35 generations. The studies described in

this report were performed exclusively with mice hemizygous for both transgenes. Transgene

negative littermates and/or C57BL/6J mice purchased from The Jackson Laboratory (Bar Harbor,

ME) were used as control animals. The mice were maintained in ventilated micro-isolator cages

housed in the specific pathogen-free animal facility at Mayo Clinic Arizona. The sentinel cages

within the animal colony surveyed negative for the presence of known mouse pathogens.

Protocols and studies involving animals were carried out in accordance with NIH and Mayo

Foundation institutional guidelines.

Bronchoalveolar lavage fluid cellularity, anti-EPX IgG detection and Immunohistochemical

detection of B-cell clusters


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BAL fluid was recovered following instillation of 1mL of 2% fetal calf serum (FCS) in

phosphate-buffered saline. The BAL fluid was initially centrifuged at low speed (10 min at

400xg, 4°C) for cell isolation. However, cell-free BAL fluid for assessment of Ig levels and the

presence of free eosinophil peroxidase (i.e., eosinophil degranulation) was prepared by a second

high speed centrifugation (10 minutes, 10,000xg) at 4°C, which was necessary to clear all

remaining cells from the fluid. For the anti-EPX reactivity in mice BAL and sera,

immunoprecipitated Igs were incubated overnight in EPX-coated (1µg/ml LEE Biosolutions,

MO, USA) Maxisorb plates and probed with biotinylated secondary antibodies against mouse

IgG. ,Mouse anti-EPX monoclonal (clone MM25-429.1.1) antibody was used for constructing

the standard curve, and values were normalised to the total protein content measured by Bio-rad

DC kit. Lung and lymph node infiltrating B220+ mononuclear cells (pan-B cell marker) was

identified via immunohistochemistry using a rat monoclonal antibody recognizing mouse B220

(BD Pharmingen, California) as per manufacturer’s instructions.

Statistical Analysis:

All experimental data were analysed with GraphPad Prism (Version 6.05, La Jolla, CA, USA).

Statistical comparison between the groups were performed by Analysis of Variance (ANOVA) /

Kruskal-Wallis non-parametric tests, and associations were determined by Spearman’s rank/

Pearson correlation test based on the distribution of the respective data-sets (D'Agostino &

Pearson omnibus normality tests). IBM® SPSS® Statistical software (version 23.0) was used for

multivariate regression analysis. P values ≤ 0.01 were considered to be significant, unless

otherwise stated.

Online Results:


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Development of local autoimmune responses in the airways of mice with heightened airway

degranulation

To reiterate the importance of airway degranulation we investigated the presence autoimmune

phenomenon in two unique murine models of eosinophilic asthma: (i) double transgenic mice

with severe respiratory inflammation (I5/hE2) and airway eosinophil degranulation (REF: E4),

showing detectable EPX exclusively in the bronchoalveolar lavage (BAL) (Figure E5, A) vs. (ii)

lung-specific IL-5 transgenic mice (l5) with no demonstrable airway degranulation (REF: E3).

We exploited this distinction and investigated the concurrent presence of anti-EPX

autoantibodies and B-cell clusters. Anti-EPX IgG was detectable in the BAL of l5/hE2 mice

otherwise undetectable in l5 and WT; and their respective matched sera (Figure E5, B-D). The

lung histology of the l5/hE2 mice exhibited large clusters of B220+ B-cells with surrounding

zones of cells resembling T cell morphology (Figure E5, E-L) and could be considered to be the

potential sites for in situ autoantibody generation. As mentioned earlier l5 mice with ectopic

expression of IL-5 showed organized iBALT in lungs (REF: E3), but the lack of an autoimmune

response in this model can be explained by the absence of airway degranulation in these mice

(Figure E5).

E-References:

E1. Lacy P, Latif DA, Steward M, Musat-Marcu S, Man SFP, Moqbel R. Divergence of

Mechanisms Regulating Respiratory Burst in Blood and Sputum Eosinophils and

Neutrophils from Atopic Subjects. The Journal of Immunology 2003; 170: 2670-2679.

E2. Lee NA, Loh DY, Lacy E. CD8 surface levels alter the fate of alpha/beta T cell receptor-

expressing thymocytes in transgenic mice. The Journal of Experimental Medicine 1992;

175: 1013-1025.


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E3. Lee JJ, McGarry MP, Farmer SC, Denzler KL, Larson KA, Carrigan PE, Brenneise IE,

Horton MA, Haczku A, Gelfand EW, Leikauf GD, Lee NA. Interleukin-5 Expression in

the Lung Epithelium of Transgenic Mice Leads to Pulmonary Changes Pathognomonic of

Asthma. The Journal of Experimental Medicine 1997; 185: 2143-2156.

E4. Ochkur SI, Jacobsen EA, Protheroe CA, Biechele TL, Pero RS, McGarry MP, Wang H,

O’Neill KR, Colbert DC, Colby TV, Shen H, Blackburn MR, Irvin CC, Lee JJ, Lee NA.

Coexpression of IL-5 and Eotaxin-2 in Mice Creates an Eosinophil-Dependent Model of

Respiratory Inflammation with Characteristics of Severe Asthma. The Journal of

Immunology 2007; 178: 7879-7889.

Supplementary figure legends:

Figure E1: Sputum IgGs from asthmatics show anti-eosinophil reactivity: Representative

image panels showing Immunostaining of eosinophils fixed and permeabilized on cover-slips,

and reacted with Igs isolated from a healthy volunteer with no anti-EPX IgG and ANA, along

with two patients positive for anti-EPX IgG and ANAs. The green channel represents the

reactivity of the sputum Igs counterstained by secondary antibodies to human IgG conjugated

with Alexa Fluor 488. The red channel represents EPX staining with Cy3-conjugated mouse

secondary antibodies. DAPI (blue) was used to stain the nuclei. Yellow regions in Overlay

images represent localisation, indicative of an anti-EPX specificity of sputum IgGs. Bars

represent 10 µM.

Figure E2: Sputum autoantibodies associated with indices of airway degranulation:

Association studies between anti-EPX reactivity (represented as closed red circles) and ANA

index (open black circles) within the diseased population (n = 64, excluding 15 healthy controls)

with respect to the documented (A) sputum eosinophil% (counted as intact eosinophils on


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stained cytospin slides) and markers of luminal eosinophil activity - (B) measured sputum EPX

content, (C) extent of free eosinophil granules, FEG, in the sputum. The respective Spearman’s

correlation coefficient (ρ) and the P values are presented next to their respective correlation

plots.

Figure E3: Sputum Igs from severe asthmatics cause eosinophil degranulation in vitro: (A)

LDH activity measured as a function of detected NADH (nmol) in the supernatants collected

from eosinophils incubated with immobilised sputum Igs from n = 5 asthmatics with anti-EPX

IgG and ANAs (2-way ANOVA, post Tukey multiple comparison test). Data presented as mean ±

SD (B) total IgG content between asthmatic and healthy sputum samples used for experiment

(Wilcoxon paired test, P = 0.125) (C) Representative images of immunostaining with anti-

histone monoclonal antibody (counterstained with anti-human IgG Alexa Fluor 488) on fixed,

non-permeabilized eosinophils stimulated with sputum Igs at different time-points and uncoated

negative control. 2 µM A23817 at t = 3 hr was used as positive control for eosinophil cytolysis.

Figure E4: Distribution of Immunoglobulin subtypes in sputum: Distribution of sputum (A)

IgA, (B) IgG, (C) IgM, (D) IgE in tested population. Kruskal-Wallis with Dunn multiple

comparison.

Figure E5: Mice with airway degranulation have anti-EPX autoantibodies and organised

B-cell clusters: (A) Double transgenic l5/hE2 mice show detectable EPX in the BAL, not serum,

indicative of eosinophil degranulation localised to the lungs. (B) Significant increase in anti-EPX

antibodies (IgG) detected in the BAL of l5/hE2 mice, otherwise undetectable in wild type (WT)

and negligible in l5 mice, normalised to the protein content. (C-D) the comparative anti-EPX

optical density (OD) values measured for three dilutions of BAL and serum.*indicates


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significant difference, P <0.05, two-way ANOVA, post Tukey test. Immunostaining lung tissue

sections with anti-B220 antibody showing no evident B cells in WT mice(E-F), with a few

positive B cells infiltrated into the airways with OVA challenge (G-H), and evidence of B220+ B

cell clusters in l5/hE2 mice lungs (I-J) indicated with arrows. 200x and 400x magnification (K,

L) shows organised B (designated as iB) and T cell zones (designated as T), indicative of

functional iBALTs.


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Supplementary Tables:

Table E1: Subject characteristics of the validation cohort

Groups Healthy Non-Eos Asthma

Eos Asthma

Subjects, n 6 4 10

Sputum Eos% 0.2 ± 0.4 0.15 ± 0.17

33 ± 28*

Sputum Neu % 28 ± 15 76 ± 24 47 ± 33

Sputum TCC (106/g)

5 ± 2 25 ± 26 10 ± 7

OCS (median) 0 7.5 11.225ICS (median) 0 1500 1350

Data presented as Mean ± SD; ICS - mcg daily equivalent dose of fluticasone propionate; OCS:

prednisone, mg/daily; *P < 0.01

Table E2: Non-parametric ranking of clinical parameters and inflammatory mediators

[A] Clinical Parameters

Independent Samples Mann-Whitney U TestSignificance (P values)

Anti-EPX signature ANA signatureAge 0.046 0.200Atopy 0.230 0.310Blood_Abs_Eosinophils 0.832 0.231Blood_Abs_Lymphocytes 0.273 0.583Blood_Abs_Monocytes 0.381 0.390Blood_Abs_neutrophils 0.885 0.095Blood_platelet 0.274 0.710BMI 0.004 0.025CRS 0.330 0.047FEG_index 0.000 0.000FEV1 (L) 0.001 0.021FEV1% 0.001 0.006FEV1/FVC ratio 0.011 0.007Hx_Lymphopenia 0.016 0.251ICS 0.000 0.001OCS 0.000 0.019Smoking_Hx 0.520 0.210Sp_Lymphocyte% 0.068 0.046


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Sputum_Eosinophil% 0.001 0.000Sputum_EPX_ng/ml 0.018 0.003Sputum_Neutrophil% 0.428 0.951Sputum_TCC 0.031 0.487

[B] Cytokines/ mediators

Independent Samples Mann-Whitney U TestSignificance P values

Anti-EPX signature ANA signature6CKine 0.386 0.932BAFF 0.000 0.000BCA-1 0.017 0.037CTACK 0.330 0.083EGF 0.122 0.197ENA-78 0.021 0.020Eotaxin-1 0.008 0.139Eotaxin-2 0.001 0.000Eotaxin-3 0.380 0.008FGF-2 0.012 0.226Flt-3L 0.254 0.179Fractalkine 0.148 0.575G-CSF 0.163 0.311GM-CSF 0.003 0.407GRO pan 0.451 0.572I-309 0.847 0.752IFNa2 0.179 0.519IFNy 0.137 0.558IL-10 0.966 0.828IL-12P40 0.789 0.594IL-12P70 0.327 0.171IL-13 0.000 0.000IL-15 0.120 0.089IL-16 0.001 0.007IL-17A 0.419 0.906IL-18 0.010 0.039IL-1a 0.979 0.528IL-1B 0.233 0.664IL-1RA 0.016 0.608IL-2 0.504 0.792IL-20 0.727 0.792IL-21 0.914 0.464IL-23 0.043 0.812IL-28A 0.090 0.947



IL-3 0.140 0.579IL-33 0.064 0.088IL-4 0.095 0.874IL-5 0.001 0.009IL-6 0.157 0.469IL-7 0.611 0.289IL-8 0.007 0.043IL-9 0.011 0.218IP-10 0.160 0.174LIF 0.638 0.485MCP-1 0.022 0.124MCP-2 0.542 0.457MCP-3 0.314 0.916MCP-4 0.632 0.693MDC 0.002 0.004MIP-1a 0.009 0.050MIP-1B 0.002 0.034MIP-1d 0.075 0.453PDGF-AA 0.024 0.013PDGF-BB 0.021 0.234RANTES 0.347 0.449sCD40L 0.251 0.678SCF 0.451 0.843SDF-1a+B 0.317 0.169TARC 0.003 0.002TGF-a 0.125 0.502TNFa 0.242 0.511TNFB 0.835 0.138TPO 0.592 0.995TRAIL 0.176 0.317TSLP 0.636 0.797VEGF-A 0.116 0.150

BMI- body mass index; TCC- total cell count; FEV1 – forced expiratory volume in 1 second; FVC- forced

vital capacity; ICS – inhaled corticosteroid; CRSwNP- chronic rhinosinusitis with nasal polyposis; Abs-

absolute; Hx – history; ; IL-interleukin; Chemokine (C-C motif); EGF- epithelial growth factor; FGF-

fibroblast growth factor; GM-CSF-Granulocyte macrophage colony-stimulating factor; IFN- interferon;

GRO pan comprises of CXCL1/2/3; MCP- Monocyte Chemoattractant Protein ; MDC- Macrophage-

derived chemokine ; TNF- Tumour Necrosis Factor ; VEGF- Vascular endothelial growth factor; TARC-


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Thymus- and activation-regulated chemokine (CCL17) ; LIF- Leukemia inhibitory factor ; TPO-

Thrombopoietin; SCF- Stem cell factor; TSLP- Thymic stromal lymphopoetin; TRAIL- TNF-related

apoptosis-inducing ligand; CTACK- Cutaneous T-cell-attracting chemokine; SDF- Stromal cell-derived

factor; ENA- epithelial-derived neutrophil-activating peptide; MIP- Macrophage inflammatory protein.


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Table E3: Model summary of regression analyses for assessing clinical predictors

A. Regression Model for Prediction of Anti-EPX signature:(Dependent Variable: Anti-EPX_sig: Cut-off threshold: Absorbance value 0.76)

ModelSum of

Squares dfMean

Square F Sig.Regression 3.146 2 1.573 7.992 .001b

Residual 10.236 52 .197Total 13.382 54

Model Unstandardized CoefficientsStandardized Coefficients

t Sig.B Std. Error Beta(Constant) .071 .106 .670 .506FEG index .943 .246 .493 3.833 .000Sputum_TCC .003 .001 .301 2.344 .023

Excluded Variables

Beta In t Sig.

Partial Correlatio

n

Collinearity Statistics

Tolerance VIFMinimum Tolerance

BMI .182b 1.466 .149 .201 .934 1.071 .842FEV1(L) -.039b -.300 .766 -.042 .897 1.115 .816FEV1 % -.041b -.319 .751 -.045 .926 1.080 .843FEV1/FVC .055b .452 .653 .063 .995 1.005 .887Sputum Eosinophil -.036b -.272 .786 -.038 .865 1.156 .819Sp EPX ng/ml -.136b -1.110 .272 -.154 .969 1.032 .864ICS .043b .329 .744 .046 .876 1.141 .795OCS .075b .577 .567 .080 .873 1.146 .780Hx_Lymphopenia -.036b -.277 .783 -.039 .885 1.130 .806

a. Dependent Variable: Anti-EPX_sigb. Predictors in the Model: (Constant), FEG index, Sputum_TCC

B. Regression Model for Prediction of ANA signature:(Dependent Variable: ANA sig : cut-off threshold ANA Index: 0.08)

ModelSum of

Squares dfMean

Square F Sig.Regression 1.381 1 1.381 6.070 .018b

Residual 10.236 45 .227Total 11.617 46

Coefficientsa


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Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.B Std. Error Beta(Constant) .377 .100 3.788 .000FEG index .630 .256 .345 2.464 .018

a. Dependent Variable: ANA_signature

Excluded Variablesa

Model Beta In t Sig.Partial

Correlation


Tolerance VIFMinimum Tolerance

BMI .014b .097 .923 .015 .980 1.021 .980FEV1(L) .039b .274 .785 .041 .991 1.009 .991FEV1 % .007b .050 .960 .008 .980 1.021 .980FEV1/FVC .045b .319 .751 .048 .999 1.001 .999Sputum_TCC .016b .105 .917 .016 .883 1.133 .883Sputum Eosinophil -.037b -.243 .809 -.037 .874 1.144 .874

Sp EPX ng/ml .102b .710 .481 .106 .969 1.032 .969ICS -.097b -.690 .494 -.103 1.000 1.000 1.000OCS -.132b -.901 .372 -.135 .914 1.094 .914Sp_Lymphocyte -.052b -.365 .717 -.055 .987 1.013 .987

a. Dependent Variable: ANA_signatureb. Predictors in the Model: (Constant), FEG index

Table E4: Correlation coefficient and non-parametric ranking for all sputum inflammatory mediator levels with autoantibody signature

Autoantibody signatureCorrelation

matrixMann

Whitney

r P PBAFF 0.457 0.000 0.000

BCA-1 0.312 0.003 0.015

CTACK 0.006 0.479 0.469

EGF 0.206 0.037 0.183

ENA-78 0.224 0.026 0.031

Eotaxin-1 0.149 0.099 0.065

Eotaxin-2 0.426 0.000 0.000

Eotaxin-3 0.153 0.093 0.231

FGF-2 0.201 0.041 0.065

Flt-3 Ligand 0.217 0.030 0.196

Fractalkine 0.154 0.092 0.460


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G-CSF 0.093 0.211 0.473

GM-CSF 0.171 0.070 0.012

GRO pan 0.035 0.383 0.771

I-309 0.043 0.357 0.751

IFNa2 0.158 0.087 0.444

IFNy 0.082 0.241 0.603

IL-10 -0.035 0.381 0.681

IL-12P40 -0.013 0.457 0.692

IL-12P70 -0.187 0.053 0.217

IL-13 0.444 0.000 0.000

IL-15 0.242 0.018 0.069

IL-16 0.207 0.036 0.002

IL-17A 0.010 0.465 0.525

IL-18 0.213 0.032 0.006

IL-1alpha -0.061 0.300 0.492

IL-1beta 0.124 0.143 0.571

IL-1RA 0.193 0.048 0.067

IL-2 -0.050 0.333 0.791

IL-20 -0.001 0.497 0.838

IL-21 -0.105 0.184 0.193

IL-23 0.109 0.174 0.398

IL-28A 0.107 0.178 0.386

IL-3 0.032 0.392 0.312

IL-33 0.146 0.104 0.269

IL-4 0.175 0.066 0.338

IL-5 0.292 0.005 0.002

IL-6 0.082 0.241 0.574

IL-7 0.118 0.155 0.320

IL-8 0.220 0.028 0.027

IL-9 0.224 0.026 0.053

IP-10 0.176 0.064 0.224

LIF -0.026 0.413 0.539

MCP-1 0.166 0.075 0.212

MCP-2 0.137 0.120 0.382

MCP-3 -0.007 0.477 0.542

MCP-4 -0.013 0.456 0.696

MDC 0.283 0.007 0.001

MIP-1a 0.098 0.201 0.056

MIP-1B 0.194 0.046 0.011

MIP-1d 0.069 0.278 0.293

PDGF-AA 0.135 0.123 0.035

PDGF-BB -0.016 0.446 0.093

RANTES -0.020 0.433 0.621



sCD40L 0.082 0.241 0.823

SCF 0.143 0.108 0.677

SDF-1a+B -0.122 0.148 0.126

TARC 0.387 0.000 0.003

TGF-alpha -0.106 0.180 0.614

TNFa 0.075 0.260 0.921

TNFB -0.080 0.245 0.799

TPO -0.069 0.276 0.758

TRAIL -0.169 0.072 0.720

TSLP 0.058 0.311 0.707

VEGF-A 0.071 0.272 0.168

*r - correlation coefficient, P < 0.01 is considered significant

Table E5: Model summary of regression analyses for assessing molecular predictors

A. Regression Model for Prediction of Anti-EPX signature: (Dependent Variable: Anti-EPX_sig: Cut-off threshold: Absorbance value 0.76)

ModelSum of

Squares dfMean

Square F Sig.Regressio

n 8.207 2 4.103 30.792 .000b

Residual 9.728 73 .133

Total 17.934 75

ModelUnstandardized

CoefficientsStandardized Coefficients

t Sig.BStd. Error Beta

(Constant) .058 .059 .977 .332

BAFF .001 .000 .465 5.341 .000

IL-13 .165 .033 .431 4.955 .000

Excluded Variables

Model Beta In t Sig.

Partial Correlatio

n


Tolerance VIF

Minimum Toleranc

eTARC 0.204 1.811 .074 .209 .566 1.768 .560

IL-16 0.128 1.391 .169 .162 .860 1.163 .851Eotaxin-

2 0.071 .635 .528 .075 .604 1.656 .600

MIP-1B 0.087 .900 .371 .105 .791 1.265 .775


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IL-5 0.168 1.408 .163 .164 .513 1.950 .503

MDC 0.034 .334 .740 .039 .719 1.391 .705

GM-CSF 0.056 .587 .559 .069 .832 1.203 .825

a. Dependent Variable: Anti-EPX_sigb. Predictors in the Model: (Constant), BAFF, IL-13

B. Regression Model for Prediction of ANA signature:(Dependent Variable: ANA sig: cut-off threshold ANA Index: 0.08)

ModelSum of

Squares dfMean

Square F Sig.2 Regression

4.785 2 2.393 13.048 .000b

Residual 11.369 62 .183Total 16.154 64

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.B Std. Error Beta(Constant)

.214 .074 2.902 .005

Eotaxin-2 .001 .000 .467 4.340 .000BAFF .001 .000 .223 2.071 .043

Excluded Variablesa

Model Beta In t Sig.

Partial Correlatio

n


Tolerance VIF

Minimum Toleranc

eTARC 0.106 .495 .622 .063 .249 4.013 .249

IL-5 0.065 .486 .629 .062 .638 1.568 .626

IL-13 0.174 1.237 .221 .156 .569 1.758 .568

MDC -0.128 -.800 .427 -.102 .447 2.237 .439Eotaxin-

3 -0.078 -.545 .588 -.070 .558 1.791 .549

IL-16 -0.002 -.020 .984 -.003 .959 1.042 .948PDGF-

AA -0.199 -1.451 .152 -.183 .594 1.684 .583

a. Dependent Variable: ANA_signatureb. Predictors in the Model: (Constant), Eotaxin-2 , BAFF


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ars.els-cdn.com · Web viewSputum Ig Isotyping (IgA, IgM, IgG, IgE): For detecting the total IgG, IgA and IgM quantity in each sputum sample, 96-well MaxiSorb (Nunc) plates were coated