Comment on 'AIRE-deficient patients harbor unique high-affinity disease-ameliorating autoantibodies'
- Karolinska University Hospital, Karolinska Institutet, Sweden
- Science for Life Laboratory, Uppsala University, Sweden
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, United States
- National Bioinformatics Infrastructure, Sweden
- Karolinska University Hospital, Sweden
- Lund University, Skåne University Hospital, Sweden
- Broad Institute of Harvard, Massachusetts Institute of Technology, United States
- Lund University, Sweden
- Science for Life Laboratory, Karolinska Institutet, Sweden
- Stanford University, United States
- University of California, San Francisco, United States
- University of Bergen, Norway
Figures
Figure 1 with 7 supplements
The statistical analysis used by Meyer et al. is biased towards overestimation of the number of autoantibody signals in the patient group.
(A) We used our previously published proteome array dataset for 51 APS1 patients and 21 healthy controls to reevaluate the autoantigen spectrum in APS1. (B) To first determine if our dataset and the …
Figure 1—figure supplement 1
Autoantibody signals for interferons in the protein array.
Z-scores were calculated based on the mean and standard deviation of the healthy controls. p=APS1 patients (n = 51), C = controls (n = 21).
Figure 1—figure supplement 2
Simulation where an elevated outlier value at saturation level (65 000 signal units) was introduced in either the APS1 patient group or the control group for the array protein serum albumin.
Z-scores were calculated based on the mean and standard deviation of the healthy controls. p=APS1 patients, C = controls.
Figure 1—figure supplement 3
Simulation where increasingly strong outliers (z-score 2, 3, …, 10) were introduced in random normal data for in total 51 ‘cases’ and 21 ‘controls’ respectively, illustrating how the cutoff is affected by elevated outliers in the control group but not by outliers in the case group.
Horizontal bars indicate 3, 4, and five standard deviations above the ‘control’ group mean.
Figure 1—figure supplement 4
Analyses in permuted data from healthy controls reveal skewing effects in the analysis used by Meyer et al.
To investigate whether there was an inherent skewing effect associated with the statistical method used by Meyer et al., analyses were performed using healthy blood donors randomly assigned to …
Figure 1—figure supplement 5
Random selection of 10 protein identified as autoantigens in APS1 using the criteria applied by Meyer et al.
(Z ≥ 3). Z-scores were calculated based on the mean and standard deviation of the healthy controls. p=APS1 patients (n = 51), C = controls (n = 21).
Figure 1—figure supplement 6
Targets identified using the analysis by Meyer et al. are low in signal and do not show enrichment for tissue-specific genes.
To further evaluate the relevance of the targets identified using the statistical analysis by Meyer et al., we compared them against the established autoantigens in APS1 with respect to the number …
Figure 1—figure supplement 7
No support for widespread autoantigen spectrum in APS1.
As the statistical analysis used by Meyer et al. had proved to be biased in the comparison between patients and controls, the question remained whether or not the APS1 patients showed autoantibody …
Figure 2
No association between neutralizing interferon autoantibodies and type 1 diabetes in APS1.
(A) Representative FACS plots showing IFNα-induced (blue), IFNω-induced (green), or IFNγ-induced (red) STAT1 phosphorylation in normal PBMC (gating on CD14 +monocytes) in the presence of 10% serum …
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Figure 2—source data 1
Neutralizing interferon autoantibodies in APS1 patients with and without type 1 diabetes.
- https://doi.org/10.7554/eLife.43578.011
Tables
Key resources table
| Reagent type (species) or resource | Designation | Source or reference | Identifiers | Additional information |
|---|---|---|---|---|
| Biological sample (Homo sapiens) | Serum samples from patients with APS1 from Sweden, Norway and Finland, and blood donor controls from Sweden | PMID: 26084804 and 26830021 | ||
| Biological sample (Homo sapiens) | Serum samples from patients with APS1 from USA | PMID: 27588307 | ||
| Biological sample (Homo sapiens) | Blood donor controls from NIH Blood Bank | |||
| Antibody | Fluorophore-conjugated goat polyclonal anti-human IgG | Thermo Fisher Scientific | Alexa Fluor 647 Goat Anti-Human IgG; Cat#A21445, | Concentration: 1:2000 |
| Antibody | Fluorophore-conjugated mouse monoclonal anti-pSTAT1 | BD Biosciences | Alexa Fluor 647 mouse anti-human Stat1 (pY701); Cat# 612597 | 5 uL/test |
| Antibody | Fluorophore-conjugated mouse monoclonal anti-CD14 | BD Biosciences | FITC mouse anti-human CD14; Cat# 555397 | 2 uL/test |
| Recombinant protein | Recombinant human interferon-alpha 2 | PBL Assay Science | Cat # 11101–2 | Concentration: 10 ng/mL |
| Recombinant protein | Recombinant human interferon-alpha | Peprotech | Cat# 300–02J | Concentration: 10 ng/mL |
| Recombinant protein | Recombinant human interferon-gamma 1b | ActImmune | NDC 42238-111-01 | Concentration: 400 U/mL |
| Commercial assay or kit | Protein microarray | Thermo Fisher Scientific | ProtoArray v5.0 (PAH0525020) | |
| Commercial assay or kit | Blocking buffer kit used in the protein array screening | Thermo Fisher Scientific | Blocking Buffer Kit (PA055) | |
| Software, algorithm | Software used for protein microarray scanning, alignment and data acquisition | GenePix Pro microarray (v6.1) | ||
| Software | FlowJo | FlowJo (v10.5.3) | ||
| Software | Prism | GraphPad Prism (v6.0) |
Additional files
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Transparent reporting form
- https://doi.org/10.7554/eLife.43578.012
