Supplemental Data R2 CLEAN VERSION...19Pediatric Rheumatology, Dell Children's Medical Center of...

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Supplemental Data

Distinct Interferon Signatures and Cytokine Patterns Define Additional

Systemic Autoinflammatory Diseases

Short title: IFN signature in undifferentiated immune-dysregulatory diseases Adriana A. de Jesus, M.D., Ph.D.1, Yangfeng Hou, M.D.2, Stephen Brooks, Ph.D.3, Louise Malle, B.S.4, Angelique Biancotto, Ph.D.5, Yan Huang, M.D., Ph.D.1, Katherine R. Calvo, M.D., Ph.D.6, Bernadette Marrero, Ph.D.7, Susan Moir, Ph.D.8, Andrew J. Oler, Ph.D.9, Zuoming Deng, Ph.D.3, Gina A. Montealegre Sanchez, M.D., M.S. 1, the Autoinflammatory Diseases Consortium (Amina Ahmed10, Eric Allenspach11, Bita Arabshahi12, Edward Behrens13, Susanne Benseler14, Liliana Bezrodnik15, Sharon Bout-Tabaku16, AnneMarie C. Brescia17, Diane Brown18, Jon M. Burnham13, Maria Soledad Caldirola15, Ruy Carrasco19, Alice Y. Chan20, Rolando Cimaz21, Paul Dancey22, Jason Dare23, Marietta DeGuzman24, Victoria Dimitriades25, Ian Ferguson26, Polly Ferguson27, Laura Finn28, Marco Gattorno29, Alexei A. Grom30, Eric P. Hanson31, Philip J. Hashkes32, Christian M. Hedrich33, Ronit Herzog34, Gerd Horneff35, Rita Jerath36, Elizabeth Kessler37, Hanna Kim38, Daniel J. Kingsbury39, Ronald M. Laxer40, Pui Y. Lee41, Min Ae Lee-Kirsch42, Laura Lewandowski43, Suzanne Li44, Vibke Lilleby45, Vafa Mammadova46, Lakshmi N. Moorthy47, Gulnara Nasrullayeva46, Kathleen M. O’Neill31, Karen Onel48, Seza Ozen49, Nancy Pan48, Pascal Pillet50, Daniela G.P. Piotto51, Marilynn G. Punaro52, Andreas Reiff53, Adam Reinhardt54, Lisa G. Rider55, Rafael Rivas-Chacon56, Tova Ronis57, Angela Rösen-Wolff42, Johannes Roth58, Natasha Mckerran Ruth59, Marite Rygg60, Heinrike Schmeling14, Grant Schulert30, Christiaan Scott61, Gisella Seminario15, Andrew Shulman62, Vidya Sivaraman63, Mary Beth Son64, Yuriy Stepanovskiy65, Elizabeth Stringer66, Sara Taber67, Maria Teresa Terreri51, Cynthia Tifft68, Troy Torgerson11, Laura Tosi69, Annet Van Royen-Kerkhof70, Theresa Wampler Muskardin71), Scott W. Canna, M.D.72, Raphaela Goldbach-Mansky1 M.D., M.H.S. 1Translational Autoinflammatory Diseases Section (TADS), NIAID/NIH, Bethesda, Maryland, United States 2Department of Rheumatology, Shandong Provincial Qianfoshan Hospital, Shandong University, Shandong, China 3Biomining and Discovery Section, NIAMS/NIH, Bethesda, Maryland, United States 4Icahn School of Medicine at Mount Sinai, New York, New York, United States 5Immunology & Inflammation Research Therapeutic Area, Sanofi, Boston, Massachusetts, United States 6Department of Laboratory Medicine (DLM), Clinical Center/NIH, Bethesda, Maryland, United States 7Computational Systems Biology Section, NIAID/NIH, Bethesda, Maryland, United States

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8Laboratory of Immunoregulation, NIAID/NIH, Bethesda, Maryland, United States 9Bioinformatics and Computational Biosciences Branch (BCBB), Office of Cyber Infrastructure and Computational Biology (OCICB), NIAID/NIH, Bethesda, Maryland, United States 10Levine Children’s Hospital, Charlotte, North Carolina, United States 11Divisions of Immunology & Rheumatology, Department of Pediatrics, University of Washington and Seattle Children’s Hospital, Seattle, Washington, United States 12Virginia Commonwealth University & Pediatric Specialists of Virginia, Fairfax, Virginia, United States 13Division of Rheumatology,Children's Hospital of Philadelphia and the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States 14Department of Pediatrics, Pediatric Rheumatology Section, Alberta Children's Hospital, University of Calgary, Calgary, Alberta, Canada 15Immunology Unit, Pediatric Hospital R. Gutierrez, Buenos Aires, Argentina 16Department of Pediatric Medicine, Sidra Medicine, Qatar Foundation, Doha, Qatar 17Nemours/Alfred I. DuPont Hospital for Children, Wilmington, Delaware, United States 18Division of Rheumatology, Children's Hospital Los Angeles & University of Southern California, Los Angeles, California, United States 19Pediatric Rheumatology, Dell Children's Medical Center of Central Texas, Austin, Texas, United States 20Divisions of Pediatric AIBMT & Rheumatology, University of California San Francisco, San Francisco, California, United States 21Department of Clinical Sciences and Community Health, University of Milano, Milan, Italy 22Division of Rheumatology, Janeway Children's Hospital & Rehabilitation Centre, Saint John's, Newfoundland and Labrador, Canada 23Division of Pediatric Rheumatology, University of Arkansas for Medical Sciences, Arkansas Children's Hospital, Little Rock, Arkansas, United States 24Department of Immunology, Allergy and Rheumatology, Baylor College of Medicine, Houston, Texas, United States 25Division of Pediatric Allergy, Immunology & Rheumatology, University of California Davis Health, Sacramento, CA, United States 26Department of Pediatrics/Pediatric Rheumatology, Yale University School of Medicine, New Haven, Connecticut, United States 27Pediatrics Department, University of Iowa Carver College of Medicine, Iowa City, Iowa, United States 28Pathology Department, University of Washington and Seattle Children’s Hospital, Seattle, Washington, United States 29Center for Autoinflammatory Diseases and Immunedeficiencies, IRCCS Giannina Gaslini, Genoa, Italy 30Division of Rheumatology, Children’s Hospital Medical Center, Cincinnati, Ohio, United States 31Department of Pediatrics Indiana University School of Medicine and Riley Hospital for Children, Indianapolis, Indiana, United States

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32Pediatric Rheumatology Unit, Shaare Zedek Medical Center, Jerusalem, Israel 33Department of Women's & Children's Health, Institute of Translational Medicine, University of Liverpool & Department of Paediatric Rheumatology, Alder Hey Children's NHS Foundation Trust Hospital, Liverpool, United Kingdom 34Department of Otolaryngology, Division of Allergy and ImmunologyNew York University, New York, New York, United States 35Asklepios Klinik Sankt, Augustin GmbH, St. Augustin, Germany and Department of Pediatric and Adolescents Medicine, University of Cologne, Cologne, Germany 36Augusta University Medical Center, Augusta, Georgia, United States 37Division of Rheumatology, Children's Mercy, Kansas City and University of Missouri, Kansas City, Missouri, United States 38Pediatric Translational Research Branch, NIAMS/NIH, Bethesda, Maryland, Unite States 39Randall Children's Hospital at Legacy Emanuel, Portland, Oregon, United States 40Division of Pediatric Rheumatology, University of Toronto and The Hospital for Sick Children, Toronto, Ontario, Canada 41Division of Allergy, Immunology and Rheumatology, Boston Children's Hospital, Boston, Massachusetts, United States 42Department of Pediatrics, Medizinische Fakultät Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany 43Systemic Autoimmunity Branch, NIAMS/NIH, Bethesda, Maryland, United States 44Hackensack University Medical Center; Hackensack Meridian School of Medicine at Seton Hall University, Hackensack, New Jersey, United States 45Department of Rheumatology, Pediatric Section, Oslo University Hospital, Oslo, Norway 46Azerbaijan Medical University, Baku, Azerbaijan 47Rutgers- Robert Wood Johnson Medical School, New Brunswick, New Jersey, United States 48Division of Pediatric Rheumatology Weill Cornell Medicine & Hospital for Special Surgery, New York, New York, United States 49Hacettepe University, Department of Pediatrics, Ankara, Turkey 50Children Hospital Pellegrin-Enfants, Bordeaux, France 51Department of Pediatric Rheumatology, Federal University of Sao Paulo, Sao Paulo, Brazil 52Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, Texas, United States 53Division of Rheumatology, Children's Hospital Los Angeles, Keck School of Medicine, USC, Los Angeles, California, United States 54University of Nebraska Medical Center/Children's Hospital and Medical Center, Omaha, Nebraska, United States 55Environmental Autoimmunity Group, NIEHS/NIH, Bethesda, Maryland, United States 56Department of Pediatric Rheumatology, Nicklaus Children‘s Hospital, Miami, Florida, United States 57Division of Pediatric Rheumatology, Children’s National Health System, Washington, District of Columbia, United States

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58Division of Pediatric Dermatology and Rheumatology, Children’s Hospital of Eastern Ontario, Ottawa, Canada 59Medical University of South Carolina, Charleston, South Carolina, United States 60Department of Clinical and Molecular Medicine, NTNU - Norwegian University of Science and Technology, and Department of Pediatrics, St. Olavs Hospital, Trondheim, Norway 61University of Cape Town, Red Cross War Memorial Children's Hospital, Cape Town, South Africa 62Pediatric Rheumatology, Children's Hospital of Orange County, University of California Irvine, Irvine, California, United States 63Section of Rheumatology, Nationwide Children’s Hospital, Columbus, Ohio, United States 64Division of Immunology, Boston Children's Hospital, Boston, Massachusetts, United States 65Department of Pediatric Infectious Diseases and Immunology, Shupyk National Medical Academy for Postgraduate Education, Kiev, Ukraine 66IWK Health Centre, Dalhousie University, Halifax, Nova Scotia, Canada 67Division of Pediatric Rheumatology, Department of Rheumatology, Hospital for Special Surgery, New York, New York, United States 68Undiagnosed Diseases Program, NHGRI/NIH, Bethesda, Maryland, United States 69Bone Health Program, Children’s National Health System, Washington, District of Columbia, United States 70Department of Pediatric Immunology and Rheumatology, Wilhelmina Children's Hospital Utrecht, Utrecht, Netherlands 71New York University School of Medicine, New York, New York, United States 72Children’s Hospital Pittsburgh, Pittsburgh, Pennsylvania, United States Trial registration: ClinicalTrials.gov NCT02974595

Funding: This research was supported by the Intramural Research Program of the NIH,

NIAID, NIAMS and the Clinical Center.

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CONTENTS I. Supplemental Methods

A. FEATURES AND CRITERIA FOR CLASSIFICATION OF PATIENTS WITH CANDLE, AGS

AND SAVI-LIKE DISEASES

B. CYTOKINE ANALYSIS

C. GENETIC ANALYSIS (WES AND WGS) AND POTENTIAL DISEASE-CAUSING GENES

VARIANT CALLS

D. CORRELATION OF NANOSTRING AND RNA-SEQ SCORES

E. STATISTICAL ANALYSES

II. Supplemental Figures

1. Supplemental Figures 1 A. Different cytokine profiles in patients with and without

elevated IFN scores. B. Cytokine profile and 12-cytokine-signature in patients assessed

2. Supplemental Figure 2. Example of 4 genes with the most common pattern of IFN

response gene expression across disease groups compared to 4 genes with a different

expression pattern (particularly in groups G1-G4).

3. Supplemental Figures 3 A. Plot of a 3-gene and 25-gene score by disease group

recapitulate differences in disease-specific expression patterns. B. STAT1 and NF-kB

transcription factor binding sites in genes in the 28-gene IFN score.

4. Supplemental Figure 4. High correlation of RNA-seq-derived and nanostring-derived

expression data is further confirmed by strong correlation of the 3-gene and 25-gene

Sub-scores obtained by RNA seq and nanostring in the same subjects.

5. Supplemental Figures 5. A. Correlation of 3-gene score (CXCL10, GBP1, SOCS1) with 11

NFKB-regulated genes (11-gene NFKB score) in HC and NOMID (negative controls) and

CANDLE and SAVI (interferonopathy controls) B. Correlation of the 3-gene score with

“11-gene NFkB score” in IL-18PAP-MAS (G1), LRBA deficiency (G2), NEMO-NDAS (G3)

and SAMD9L-SAAD (G4)

6. Supplemental Figure 6. A. Correlation of 28-gene IFN score with serum IL-18, IL-18BP

and CXCL9 levels B. Assessment of the ratio of IFNg-, and IFNa-regulated genes over

all genes in patients with IL-18PAP-MAS (G1)

7. Supplemental Figure 7. Comparison of 3/25 gene ratio in other IFNopathies and

diseases with presumed Type-I IFN contribution

III. Supplemental Tables

1. Supplemental Table 1: Demographic features of patients with and without elevated IFN

score

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2. Supplemental Table 2. Laboratory characteristics of patients with and without elevated

IFN score

3. Supplemental Table 3. Pulmonary alveolar proteinosis (PAP) and macrophage

activation syndrome (MAS), G1 (IL-18PAP-MAS)

4. Supplemental Table 4. Genetic data and immune phenotype of disease groups with B

cell cytopenia +/- low immunoglobulin levels, G2 (LRBA), G3 (NDAS) to G4 (SAAD)

5. Supplemental Table 5. Genetic data and clinical description of patients with AGS/AGS-

like disease (G5), aMDA5-pos JDM (G6) and CANDLE/CANDLE-like (G7) syndromes and

SAVI-like disease (G8).

6. Supplemental Table 6. Clinical features of patients with unclassifiable disease, group 9

(G9)

7. Supplemental Table 7. Clinical features of patients with normal IFN scores

8. Supplemental Table 8. Clinical and genetic features and treatment responses of

patients treated with JAK inhibitors

9. Supplemental Table 9. Proposed Disease Criteria for Patients in Both

Interferonopathies and Non-interferonopathies Groups

IV. Supplemental References

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I. Supplemental Methods:

A. Features and Criteria for Classification of patients with CANDLE, AGS and SAVI-like diseases:

1. CANDLE, CANDLE-like classification:

(A diagnosis of “definitive CANDLE” was made based on genetic testing, revealing 3 patients with features consistent with the below criteria (homozygous PSMB8: p.T75M; compound heterozygous PSMB8: p.Q55* and p.S118P; compound heterozygous PSMG2: p.Y223fs*2 and p.N225K) For “CANDLE-like” classification, patients have to have all the required features and could have at least 2 supportive features: Required: • Neutrophilic panniculitis • Systemic inflammation with disease flares • No interstitial lung disease • No white matter disease other than basal ganglia calcification Supportive: • Lipodystrophy • Patchy myositis • Transient lymphopenia with flares • Hepatic steatosis • Metabolic syndrome • Basal ganglia calcification • Soft tissue or vascular calcifications • Primary pulmonary hypertension 2. AGS, or AGS-like disease

(A diagnosis of definitive AGS5 was made on genetic testing of one patient who was positive for a deletion in SAMHD1, the patient had Moya-Moya like disease, a history of stroke at the age 7, panniculitis and superficial soft tissue calcifications) For “AGS-like” classification, patients have to have all the required features and could have at least 2 supportive features: Required: • Presence of white matter disease or Moya-Moya like disease • Presence of Chilblain-like lesions Supportive: • Neutrophilic panniculitis • Transient lymphopenia with flares • Basal ganglia calcifications • Soft tissue or vascular calcifications

3. SAVI-like disease:

For “SAVI-like” classification, patients have to have all the required features and could have at least 2 supportive features: Required: • Peripheral vasculitis and interstitial lung disease Supportive: • Livedo reticularis

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• Chilblain like-lesions • Cold sensitivity • Gangrene following vasculitic lesions • Raynaud’s disease

Determination of active disease:

For patients seen at the NIH: Active disease was defined at the respective NIH visit and included evidence of systemic inflammation (elevated ESR and CRP) and/or evidence of active organ inflammation (i.e. rashes, lung findings suggesting inflammation (i.e ground glass appearance, or sterile osteomyelitis), or presence of macrophage activation syndrome (MAS)-like features including elevated ferritin, LDH and cytopenias with disease flares.

For patients not seen at the NIH: Clinical information was obtained from the records and from the referring physicians focusing on the day of blood draw. B. Cytokine Analysis:

Serum was collected from patients and healthy controls. Cytokine concentrations were measured using the Bio-Plex system (Bio-Rad, Hercules, CA) in batches including patient control and healthy serum as previously reported (1). The samples were run in 2 batches, batch 1 included 45 patients, 20 with undifferentiated interferonopathies (UIFN) and 25 without UIFN, and 5 healthy controls and batch 2 included 8 patients with an UIFN. Statistical analysis was performed only in samples from batch 1. Since the inter-assay variability is high, to compare batch 1 and batch 2, we generated a ratio for each patient, the means of the normal control that were run with each batch were generated for each cytokine and for each patient and each analyte a ratio was generated of the patient value over the mean of the healthy control for that analyte. Twelve healthy controls were females and 6 were males and the age ranged between 7 months-old and 53 years-old (median 25.5 years-old). Cytokine assays. Serum from five of the healthy controls described above were used in the Luminex assays, three females and 2 males. Age ranged between 7 and 53 years-old (median 11 years-old). C. Genetic analysis (WES and WGS) and potential disease-causing genes variant calls:

Whole exome sequencing (WES) was performed in 19 trios, 1 duo and 4 singletons, whole genome sequencing (WGS) in 36 trios and 1 duo; 5 patients had Sanger sequencing of candidate genes performed only. Confirmatory targeted (Sanger) sequencing of candidate genes detected by WES or WGS was performed. Different sequencing companies were used for the 61 patients who had either WES (Otogenetics, Atlanta, GA, or BGI Genomics, Hong Kong) and WGS (The Broad Institute, Cambridge, MA) performed.

D. Validation of 3/25 gene ratio To test whether NF-kB activation might contribute to the expression of the 3 genes with NF-kB/STAT1” TFBS, we subdivided 28 genes in our IRG-S into the 25-gene with STAT1 TFBS only and calculated a “25-gene STAT1-only” score and the 3-gene with NF-kB and STAT1 TFBS (CXCL10, GBP1 and SOCS1) and calculated a “3-gene STAT1/NF-kB “ score. We selected 11-gene from IPA that harbor NF-kB1/2 TFBS, but no STAT1 TFBS and are expressed in blood and calculated an “11-gene NF-kB-only validation score” that we used for correlation studies.

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Step 1. Identification of upstream regulators of the 28 IRGs: To identify upstream regulators of the 28 IRGs and to determine whether the 3 genes that had a different expression pattern in disease groups G2 and G3 (genes: CXCL10, GBP1 and SOCS1) (Supplemental figure 2 and Supplemental figure 3A) have different upstream regulators we used the following resources: 1. Ingenuity Pathway Analysis (IPA) (QIAGEN Inc.,

https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis) 2. MotifMap (http://motifmap-rna.ics.uci.edu) (2, 3) 3. MATCH. Motif enrichment was performed using MATCH in the geneXplain TRANSFAC® +

PROTEOME™ platform (http://genexplain.com/). Promoter sequences (500bp upstream to 100bp downstream of transcription start site) for the 28-gene list were queried using only high-quality matrices from the “minSUM” vertebrate nonredundant set of transcription factor matrices, which has matrix-specific thresholds optimized to minimize the sum of false positive and false negative error rates.

Step 2. Identification of a validation set of genes with NF-kB1 and NF-kB2 transcription factor

binding sites and no STAT1, STAT2 or TYK1 binding sites that are expressed in peripheral blood

cells.

To determine whether the subset of 3 IRGs with NF-kB1 and NF-kB2 TFBS (see Step 1) correlate with genes that have NF-kB1 and NF-kB2 TFBS and no STAT1, STAT2 or TYK1 binding sites and are mainly driven by NFkB activating stimuli, we generated a validation set of target genes with NF-kB1 and NF-kB2 transcription factor binding sites that have no STAT1, STAT2 or TYK1 binding sites and were unlikely to respond to Type-I IFN stimulation. We used Ingenuity Pathway Analysis (IPA) (QIAGEN Inc., https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis). The validation was performed with RNA-seq data in various patients and controls as described below.

Identification of NFkB1 targets: IPA analysis revealed 166 NFkB1 targets, 127 of those had also a STAT1 binding site and were excluded from the validation set. Of the remaining 39 targets, 17 had very low expression in blood cells (RPKM<0.5) and were excluded. Of the remaining 22 targets, 13 were downregulated in most patients (average z-score within patients < zero) and were excluded. The remaining 9 targets were included in the validation set (AICDA, CCND2, EBI3, GZMB, IFNG, MSR1, SELP, TANK and TLR2). Identification of NFkB2 targets: IPA analysis revealed 36 targets, 26 of those had a STAT1 binding site and were excluded. Of the 10 remaining, 7 targets had low RNA expression in blood cells and were excluded. Of the remaining 3 targets, 2 were not downregulated (positive z-score) and were included (SELL and XIAP). The resulting validation set of 11 genes (AICDA, CCND2, EBI3, GZMB, IFNG, MSR1, TANK, TLR2, SELL, SELP and XIAIP) was used to develop an 11-gene “NF-kB gene validation score”. RNA-seq data were used to generate the 28-gene IFN score, a 3-gene (STAT1 and NFKB TFBS) subscore and a 25-gene (STAT1 only TFBS) subscore. The “11-gene NF-kB-only validation score” was correlated with the 3-gene and the 25-gene subscores respectively. Correlation of nanostring and RNA seq scores:

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Although all correlations were performed with the RNAseq data, we determined whether the gene scores that could be calculated on nanostring and RNA-seq correlated by using 21 samples that had both gene expression profiling analyses performed (including: 4 healthy controls, 8 patients with CANDLE, 4 with SAVI, 2 with IL-18PAP-MAS, 1 with LRBA deficiency and 2 with NEMO-NDAS). Pearson correlations between nanostring and RNA-seq were performed for the sum of the individual z-scores of 28 genes (28-gene IFN score) as previously calculated (4), the 3 gene score (CXCL10, GBP1 and SOCS1) and a 25-gene score (28-gene – 3-gene score). The correlations were r=0.961, r=0.958 and r=0.969, respectively (p<0.0001 for all 3 correlations, Supplemental Figure 4).

Step 3. Correlations of the “NF-kB-only validation score” (11 genes, AICDA, CCND2, EBI3, GZMB, IFNG, MSR1, TANK, TLR2, SELL, SELP and XIAP) and the 3-gene (sub-score (CXCL10, GBP1 and

SOCS1) in various disease groups

The correlations of the NF-kB score (11 genes) and the 3-gene sub-score were performed in RNA-seq data from whole blood. RNA seq on 19 healthy controls, 21 patients with NOMID, 12 patients with CANDLE, 5 with SAVI, 2 of the 7 patients with IL-18PAP-MAS, the 2 patients with LRBA deficiency, the 3 NEMO-NDAS patients and 3 of 6 patients with SAMD9L mutations were used for correlations between the 3-gene (z-score) or the 25-gene score with the 11-gene NF-kB score (Supplemental Figures 4B and 5)

II. Supplemental Figures

Supplemental Figure 1. A. Different cytokine profiles in patients with and without elevated IFN

scores. B. Cytokine profile and 12-cytokine-signature in patients assessed

A.

E

IP-10/CXCL10 GROa /CXCL1

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B.

A. Comparison between 20 patients who had serum levels assessed and had a high IFN score compared to 25 patients who had normal IFN scores and to 5 healthy controls. Mann-Whitney test was used with a p-value of <0.05. Patients with an interferon response gene (IRG) signature had higher levels of IP-10/CXCL10 (7,369 (404.1 – 25,884) vs. 622.1 (191.4 – 3,185) pg/ml, p<0.0001), GROa/CXCL1 (251.6 (74.9 – 1,696) vs. 161.7 (24.9 – 314.8) pg/ml, p=0.0043), MIG/CXCL9 (2,890 (441.9 – 43,205) vs. 737.5 (83.4 – 1,272) pg/ml, p=0.0001), TRAIL (94.8 (18.1 – 633.3) vs. 47.9 (10.7 – 290.0) pg/ml, p=0.0277) and SCF (38.9 (4.3 – 209.8) vs. 20.9 (3.5 – 107.2) pg/ml, p=0.0156). RANTES levels were significantly lower in patients with an IRG signature (28,337 (12,596 – 32,934) in comparison with healthy controls (31,132 (28,326 - 38,306), p=0.050) and with patients in the non-IFN group (29,431 (22,825 – 40,553), p=0.050). The 50 serum samples assessed were run in the same Luminex assay (Bio-Rad, Hercules, CA) batch (Batch 1).

B. 48 cytokines tested in 28 patients with an IRS and 25 patients without an IRS. Depicted in the heatmap is the ratio between patient (Pt) and healthy control (HC) concentration (pg/ml) for each analyte; red denotes row maximum and blue denotes row minimum. Different time points for the same patient are marked with a capital letter (A, B or C). Eight out of the 28 patients with an IRS had the cytokines measured in a different Luminex batch (Batch 2) and all 25 patients without an IRS had the cytokines measured in the same Luminex batch. The Pt:HC ratio was calculated using healthy controls ran in the same Luminex batch.

IL-18PAP-MAS Other IFN patients Non-IFN patients

A A B B B CC

Pt:HC ratio

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Supplemental Figure 2. Example of 4 genes with the most common pattern of IFN response gene

expression across disease groups pattern compared to 3 genes with a different expression

pattern particularly in groups G1-G4.

Different patterns of elevation of raw counts are found in the various diseases. IFI27 and USP18 belong to a pattern in which the Nanostring counts are highly elevated in CANDLE and SAVI patients but groups 1-4 patients have counts that were barely different from HC and NOMID patients. MX1 and ISG15 belong to a pattern of genes that are elevated in groups 1-4 patients compared to HC and NOMID, but significantly lower than in CANDLE and SAVI. Blue arrows indicate relatively lower counts in groups 1-4. CXCL10, GBP1 and SOCS1 are grouped in an expression pattern with counts that where significantly elevated in groups 2 and 3 (red arrows) compared to HC and NOMID and as high as in CANDLE and SAVI (CXCL10 for G1, G2 and G4) or even significantly higher than in CANDLE and SAVI patients (GBP1 and SOCS1 for G2 and G3 and CXCL10 for G3). Seven out of the 8 patients in group 1 are depicted in the graphs. The pattern analysis and graphs were generated with patient G3-P4 (red circle) still classified as CANDLE-like. She was later found to have a de novo NEMO splice variant and moved to G3-P4. Her expression pattern independently confirms that of the 3 NEMO-NDAS boys (G3-P1, -P2, -P3).

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(n=5)

Group 5

(n=4)

Group 6

(n=2)

Group 7

(n=7)

Group 8

(n=2)

Group 9

(n=5)

Non-IFN gro

up (n=2

7)0

1000

2000

3000

40004000

5000

6000

*

*

CXCL10

SOCS1

HC (n=1

8)

NOMID (n

=19)

CANDLE (n=9

)

SAVI (n=7

)

Group 1

(n=7)

Group 2

(n=2)

Group 3

(n=3)

Group 4

(n=5)

Group 5

(n=4)

Group 6

(n=2)

Group 7

(n=7)

Group 8

(n=2)

Group 9

(n=5)

Non-IFN gro

up (n=2

7)0

5000

10000

15000

20000

25000

30000

40000

50000 SOCS1GBP1

HC (n=1

8)

NOMID (n

=19)

CANDLE (n=9

)

SAVI (n=7

)

Group 1

(n=7)

Group 2

(n=2)

Group 3

(n=3)

Group 4

(n=5)

Group 5

(n=4)

Group 6

(n=2)

Group 7

(n=7)

Group 8

(n=2)

Group 9

(n=5)

Non-IFN gro

up (n=2

7)0

10000

20000

30000

40000

50000

60000

70000

80000 GBP1

Na

no

stri

ng c

ou

nts

no

rma

lize

d t

o H

K g

en

es

13

Supplemental Figures 3 A. Plot of a 3-gene and 25-gene score by disease group recapitulate

differences in disease-specific expression patterns. B. Transcription factor binding sites in genes

in the 28-gene IFN score

A

B

Y/N, present/not present; Y?, given the difference in expression pattern between OAS3 vs. CXCL10, GBP1 and SOCS1, further analyses of the functional impact on the putative NFKB1/2 site in OAS3 are needed; N?, SIGLEC1 was empirically selected for the 28-gene IFN score (Kim et al. J Interferon Cytokine Res. 2018) as it

Gene STAT1 TFBS present

NFKB1/2 TFBS present

Summary z-score calculation 3/25 gene ratio

DDX60 Y NEPSTI1 Y NHERC5 Y NHERC6 Y NIFI27 Y NIFI44 Y NIFI44L Y NIFI6 Y NIFIT1 Y NIFIT2 Y NIFIT3 Y NIFIT5 Y NISG15 Y NLAMP3 Y NLY6E Y NMX1 Y NOAS1 Y NOAS2 Y NOAS3 Y Y?OASL Y NRSAD2 Y NRTP4 Y NSIGLEC1 N? NSPATS2L Y NUSP18 Y NCXCL10 Y YGBP1 Y YSOCS1 Y Y

25 STAT1-only genes of 3/25-

gene ratio

3 STAT1/NF-kB genes of 3/25-

gene ratio

Used to generate the “3-gene

STAT1/NF-kB

Used to generate "25-gene STAT1-

only score"

14

is an IFN response gene (http://www.interferome.org/interferome/home.jspx), however a STAT1 TFBS could not identified in the databases screened.

A. The 3-gene subscore (CXCL10, GBP1 and SOCS1) was as high or higher in G1-G4 compared to HC and NOMID with patients in groups G1 (IL-18PAP-MAS) and G4 (SAMD9L-SAAD) having similar elevation as SAVI; but the 25-gene score was significantly lower in G1-G4 compared to CANDLE and SAVI. (This figure includes patient G3-P4, now correctly classified as NEMO-NDAS instead of CANDLE-like (G7). The 3-gene and 25-genes subscores were similar to CANDLE and SAVI in groups G5-G8. Groups G1 (IL-18PAP-MAS), G2 (LRBA def) and G3 (NEMO-NDAS), G4 (SAMD9L-SAAD), G5 (AGS, AGS-like), G6 (MDA5+JDM), G7 (CANDLE, CANDLE-like), G8 (SAVI-like), G9 (misc. other). B. List of the 28 interferon response genes (IRGs) and their respective STAT1 and NF-kB1/NF-kB2 transcription factor binding sites (TFBS). The genes with a disease-specific expression pattern (CXCL10, GBP1 and SOCS1) have NF-kB1 (GBP1 and SOCS1) or NF-kB1/NF-kB2 binding sites (CXCL10). Highlighted in orange are the STAT1 TFBS and highlighted in blue are the NF-kB1/NF-kB2 TFBS. TFBS, transcription factor binding site.

15

Supplemental Figure 4. High correlation of RNA-seq-derived and nanostring-derived expression

data is further confirmed by strong correlation of the 3-gene and 25-gene sub-scores obtained

by RNA-seq and nanostring in the same subjects

Gene expression excluding the 28 genes that were assessed on the nanostring assay, were only assessed by RNA-seq; this includes strictly NFKB regulated genes. To correlate the 3 genes with other genes we validated the RNA-seq data by correlating the expression of the 28 IRGs generated in both methods (the RNA seq data set and from the nanostring assay). In panel A, the same samples (n=21) were used to generate raw counts on the nanostring assay and RPKMs expression data by RNAseq. Raw counts and RPKMs correlated highly (r-values between 0.95 and 0.97). Next, we calculated z-scores from the Nanostring counts and correlated them with z-scores generated from the RNA seq RPKMs (see ref 20 for z-score calculation). The z-scores generated by both methods correlated highly (r-values between 0.95 and 0.97). Pearson correlation was used; and all p-values were p<0.001. The following samples were used for the correlation: healthy controls (n=4), patients with CANDLE (n=8), SAVI (n=4), IL-18PAP-MAS (n=2), LRBA deficiency (n=1), NDAS (n=2).

-500000 0 500000 1000000 1500000 2000000

10000

20000

30000

Sum Nanostring Counts

Sum

RN

A-s

eq C

ount

s (R

PKM

)

28 gene Counts Sum

0 500000 1000000 1500000 20000000

10000

20000

30000


Sum

RN

A-s

eq C

ount

s (R

PKM

)

24 gene NSvsRNA-seq

0 50000 100000 1500000

200

400

600

800

1000

4 gene NSvsRNA-seq


Sum

RN

A-s

eq C

ount

s (R

PKM

)

COUN

TS

r=0.9584

r=0.961

r=0.9532

-500 500 1000 1500 2000 2500-500

500

1000

1500

2000

2500

Sum Nanostring z-scores

Sum

RN

A-s

eq z

-sco

res

28 gene z-scores NSvsRNA-seq

-500 500 1000 1500 2000 2500-500

500

1000

1500

2000

2500


Sum

RN

A-s

eq z

-sco

res


-100 100 200 300 400-100

100

200

300

400


Sum

RN

A-s

eq z

-sco

res


r=0.9612

r=0.9697

r=0.9587

z-SCO

RES

A

25-gene score

28-gene score

3-gene score

25-gene score

28-gene score

3-gene score

16

Supplemental Figures 5. A. Correlation of 3-gene score (CXCL10, GBP1, SOCS1) with 11 NFKB-

regulated genes (11-gene NFKB score) in HC and NOMID (negative controls) and CANDLE and

SAVI (interferonopathy controls) B. Correlation of the 3-gene score with “11-gene NFkB score”

in IL-18PAP-MAS (G1), LRBA deficiency (G2), NEMO-NDAS (G3) and SAMD9L-SAAD (G4)

Red circles: 3-gene (CXCL10, GBP1, SOCS1) subscore

Blue squares: 25-gene IFN calculated gene subscore

HC

r= 0.19, p=ns r= 0.33, p=ns

CANDLE

r= 0.07, p=ns r= 0.49, p=ns

NOMID

r= 0.51, p=0.017 r= 0.42, p=0.06

SAVI

r= -0.10, p=ns r= 0.18, p=ns

11-gene NFkB Score

3-or

25-

gene

IFN

Scor

e

3-gene score25-gene score

-4 -2 2 4 6 8

-50

50

100

11 gene vs 3 vs 25 HC

-5 5 10 15-20

20

40

60

80

11 gene vs 3 vs 25 NOMID

-10 0 10 20 30

200

400

600

800

11 gene vs 3 vs 25 CANDLE

0 5 10 150

50

100

150

200

250

11 gene vs 3 vs 25 SAVI

-10 10 20 30-20

20

40

60

80

11 gene vs 3 vs 25 G2G1: IL-18PAP-MAS G2: LRBA-Def

G3: NEMO-NDAS G4: SAMD9L-SAAD

r= 0.37, p=ns r= 0.72, p=0.029

r= -0.62, p=ns r= 0.99, p=0.002

r= 0.39, p=ns r= -0.14, p=ns r= 0.53, p=ns

r= 0.82, p=0.023

11-gene NFkB Score

3-or

25-

gene

IFN

Scor

e

3-gene score25-gene score

12 14 16 18 20 22 240

50

100

150

11 gene vs 3 vs 25 G1

-10 10 20 30-50

50

100

150

200

250

-15 -10 -5 5 10 15

-50

50

100

150

11 gene vs 3 vs 25 G4

A

B

11 genes with NF-kB

binding sites but no

STAT1 binding sites:

AICDA

CCND2

EBI3

GZMB

IFNG

MSR1

SELL

TANK

TLR2

SELP XIAP

17

A. Correlation of the 3-gene subscore or the 25-gene subscore with a score generated from 11 NF-kB1/2 regulated genes that do not have STAT1 TF binding sites, in the IFN score negative control population (HC , n=19 and NOMID n=21) and the autoinflammatory interferonopathies (CANDLE (n=12) and SAVI (n=5)), shows a weak correlation between both the 3-gene score (red)(r=0.45) and the 25-gene score (blue)(r=0.51) in NOMID patients but no correlation was seen in CANDLE and SAVI patients, which both had much higher 25-gene than 3-gene subscores.

B. Correlation of RNA seq data scores generated from the 3-gene subscore (red circles and lines) or a 25-gene subscore (blue squares and lines) with the 11-gene NF-kB gene score showed a positive correlation between the 3-gene and the 11-gene scores in disease groups 2 (LRBA), 3 (NEMO-NDAS) and 4 (SAMD9L-SAAD). Patient G3-P4 was not included in the validation.

18

Supplemental Figure 6. A. Correlation of 28-gene IFN score with serum IL-18, IL-18BP and CXCL9

levels B. Assessment of ratio of IFNg and IFNa regulated genes over all genes in patients with

IL-18PAP-MAS

A. Correlation of the 28-gene IFN score (IRG-S) with serum levels of IL-18, IL-18BP and CXCL9 in 7 patients with IL-18PAP-MAS and 3 patients with NLRC4-MAS. Partial correlations to measures the strength of the linear relationship between two variables, while adjusting for the effect of other variables were performed using SAS. IL-18 or IL-18BP or CXCL9 serum levels were correlated with the 28 gene-IFN score. One -sided p-values to determine a presumed positive correlation were denoted. The correlation of IL-18 with the IFN score was weak and borderline significant.

B. Assessment of the ratio of IFNg-, and IFNa-regulated genes over all genes in patients with IL-18PAP-MAS patients (G1). Given the IFNg inducing function of IL-18, we defined IFNa and IFNg induced genes per ref. Liu SY et al, PNAS, 2012 (highlighted in yellow) and generated a ratio of 9 IFNa and IFNg- induced genes over all 28 genes. Two genes, CXCL10 and SOCS1 have IFNa, IFNg

-50 0 50 100 150 200 250 300

100000

200000

300000

400000

28-gene score

IL-1

8 (p

g/m

l)

-100 0 100 200 300

50000

100000

150000

All Score vs IL-18BP

28-gene scoreIL

-18B

P (

pg

/ml)

-50 0 50 100 150 200

5000

10000

15000

20000

25000

28-gene score

CX

CL

9 (p

g/m

L)

r=0.4913 r=-0.0768 r=0.5053r=0.28 p=0.06

r=0.07 p=0.34

r=0.16 p=0.26

B

19

and NFkB1/2-regulated TF binding sites, which also increased the ratio in the NEMO-NDAS and LRBA deficiency patients who have elevated NFkB activation (data not shown). When CXCL10 and SOCS1 removed from the ratio, the ratio was highest in IL-18PAP-MAS and indicated a significant difference from NEMO-NDAS and LRBA deficiency (data not shown). Nonparametric Mann-Whitney test was used to compare groups, p-values are <0.01 and >0.001.

Supplemental Figure 7. Comparison of 3/25 gene ratio in other IFNopathies and diseases with

presumed Type-I IFN contribution

A ratio between the nanostring normalized counts of 3 IFN response genes which correlated with the 11-gene NF-kB score in G2 (NDAS), G3 (LRBA) and G4 (SAAD) and the 25 IFN gene genes with no NF-kB binding sites that did not correlate with the 11-gene NF-kB score (referred to as: 3/25

ratio) was calculated. Depicted in the graph are the statistical significances (nonparametric Kruskal-Wallis test) from the comparisons of each group with CANDLE and SAVI patients combined: HC (healthy control) and NOMID combined p<0.0001, Group 2 (=LRBA deficiency) p=0.0005, Group 3 (=NEMO-NDAS) p<0.0001, Group 5 (=Aicardi Goutières Syndrome (AGS)) p=0.9102, childhood systemic lupus erythematosus (cSLE) p=0.5395, juvenile dermatomyositis (JDM) p=0.3275, Group 6 (=anti-MDA5 autoantibody positive JDM) p=0.5742, otulin-related autoinflammatory syndrome (ORAS), one patient no statistical analysis done and deficiency of ADA2 (DADA2) disease p=0.3117. ns: not significant. Red shade area indicates a high 3/25-gene ratio, blue shade area indicates low ratio and white area indicates normal ratio. All of the 3 cSLE and 3 JDM samples had high 28-gene IFN scores and 3 of the 5 DADA2 samples had high 28-gene IFN scores. The 2 DADA2 samples with low 3/25 gene ratio (<0.07, blue range), had elevated 28-gene IFN score (60.4 and 131). This figure correctly includes the female patient with NEMO-NDAS as G3-P4.

20

III. Supplemental Tables

Supplemental Table 1. Demographics and treatment information of patients with (n=41) and

without (n=25) an elevated IFN score

Demographic Characteristics

With IFN signature

(n=41)F

Without IFN signature

(n=25)

Age of disease onset (mean SD

(min - max)) - months 13.67 +/- 21.96 (0 - 84)A 35.52 +/- 38.40 (0 - 144)

Age group - no. (%) < 1 month 10 5

1 - 6 months 9 2

6 - 24 months 13 5 2-4 yrs 3 5

4-8 yrs 4 5

8-12 yrs 0 2 12-18 yrs 0 1

>18 yrs 2 0

Ethnicity (no. (%))

White 21 (51.2) 21 (84)

Black 2 (4.8) 0 (0) Hispanic 10 (24.4) 1 (25)

Asian 5 (12.2) 0 (0)

Other 3 (7.3) 3 (12)

DMARDs prior to baseline—

no. (%) 25 (78.1)B 6 (24)

≥2 DMARDs prior to baseline 12 (38.7)C 2 (8)

Mean use of DMARDS prior to

baseline 1.32 (0-5) 0.32 (0-2)

Biologics prior to baseline—

no. (%) 22 (68.7)B 11 (44)

≥2 biologics prior to baseline 14 (45.2)C 7 (28)

Mean use of biologics prior to

baseline 1.45 (0-3) 0.96 (0-5)

Oral corticosteroids— no. (%) 38 (95)D 17 (68)

Mean exposure to oral

corticosteroids (Mean (range))

- months

32.48 (0-192)E 8.48 (0-36)

21

A Two patients had disease onset above 18yrs and were excluded

B Information available for 32 patients

C Information available for 31 patients

D No information on steroid use for 1 patient

E Mean exposure to corticosteroids calculated for 27 patients

F Of 65 patients tested for IRG-S score elevation, 36 had elevated IFN response gene and 29 patients were negative. Four of the 29 patients with a normal IRG-S score at the time of testing were later included in one of the disease groups of patients with an elevated IRG-S score. An additional patient who did not have an IRG-S score testing done, had a post-mortem genetic diagnosis of SAAD and was added to the group of patients with an elevated IRG-S score. Therefore, the final number of subjects in the group of patients with a diagnosis related to a “positive” IRG-S score was 41, and 25 patients were listed with “negative IRG-S scores”.

22

Supplemental Table 2. Laboratory characteristics of patients with elevated IFN score

Laboratory

FindingsA

With IFN

signature

(affected/

no. patients

evaluated)

(%)

Without IFN

signature

(affected/

no. patients

evaluated)

(%)

Fisher exact

test p-value

Red blood cell

dyscrasia

Anemia 13 / 36 (36.1) 2 / 25 (8.0) 0.015

Leukocyte count

Leukocytosis 4 / 33 (12.1) 4 / 25 (16.0) ns

Neutrophilia 8 / 33 (24.2) 3 / 25 (12.0) ns

Lymphocytosis 2 / 33 (6.1) 6 / 25 (24.0) 0.064

Monocytosis 8 / 33 (24.2) 6 / 25 (24.0) ns

Leukopenia 6 / 33 (18.2) 3 / 25 (12.0) ns

Neutropenia 4 / 33 (12.1) 3 / 25 (12.0) ns

Lymphopenia 8 / 33 (24.2) 0 / 25 (0.0) 0.008

Monocytopenia 8 / 33 (24.2) 2 / 25 (8.0) ns

Platelet count Thrombocytosis 9 / 36 (25.0) 8 / 25 (32.0) ns

Thrombocytopenia 11 / 36 (30.6) 0 / 25 (0.0) 0.002

Lymphocyte

immunophenotyping

High CD19+ cell

numberB 14 / 34 (41.2) 16 / 25 (64.0) ns

Low CD19+ cell numberB 8 / 34 (23.5) 0 / 25 (0.0) 0.016

High CD3+ cell numberC 5 / 34 (14.7) 10 / 25 (40.0) 0.037

Low CD3+ cell

numberC 2 / 34 (5.9) 1 / 25 (4.0) ns

High CD4+ cell

number 5 / 33 (15.2) 6 / 25 (24.0) ns

Low CD4+ cell

number 2 / 33 (6.1) 0 / 25 (0.0) ns

High CD8+ cell

number 6 / 33 (18.2) 7 / 25 (28.0) ns

Low CD8+ cell

number 0 / 33 (0.0) 1 / 25 (4.0) ns

High CD56+ cell

number 2 / 33 (6.1) 4 / 25 (16.0) ns

Low CD56+ cell number 11 / 33 (33.3) 1 / 25 (4.0) 0.008

Autoantibodies

ANA 11 / 32 (33.3) 3 / 23 (11.5) ns

Anti-dsDNA 2 / 18 (11.1) 0 / 10 (0.0) ns

ACL IgG 5 / 30 (16.7) 4 / 22 (18.2) ns

ACL IgM 4 / 30 (13.3) 1 / 22 (4.5) ns

LAC 13 / 30 (43.3) 7 / 23 (30.4) ns

23

RF 1 / 20 (5.0) 1 / 13 (7.7) ns

Anti-PR3 1 / 14 (7.1) 0 / 5 (0.0) ns

Anti-MPO 1 / 14 (7.1) 0 / 5 (0.0) ns

Immunoglobulin

serum levels

High IgG 9 / 32 (28.1) 4 / 19 (21.0) ns

Low IgG 2 / 32 (6.3) 1 / 19 (5.3) ns

High IgA 7 / 32 (21.9) 2 / 19 (10.5) ns

Low IgA 3 / 32 (9.4) 0 / 19 (0.0) ns

High IgM 4 / 32 (12.5) 1 / 19 (5.3) ns

Low IgM 3 / 32 (9.4) 0 / 19 (0.0) ns

High IgE 9 / 31 (29.0) 2 / 19 (10.5) ns

CRPD elevated >5mg/L 15 / 32 (46.9) 4 / 25 (16.0) 0.023 elevated >15mg/L 12 / 32 (37.5) 4 / 25 (16.0) 0.085

ESR D elevated

>15mm/hr 18 / 32 (56.3) 8 / 25 (32.0)

ns

A Laboratory findings obtained at first NIH visit or first visit with local physician when available.

B One patient from group 2, 1 patient from group 3 and 1 patient from group 4 had high CD19# at the first NIH visit and developed progressive B-cell lymphopenia overtime. One patient from group 3 and 1 patient from group 5 had normal CD19 cell numbers at the first visit and developed progressive B cell lymphopenia overtime.

C One patient from group 2, 1 patient from group 4 and 1 patient from group 5 had normal CD3 cell numbers at the first NIH visit and developed progressive T-cell lymphopenia overtime.

D Assessed at the time of the NIH visit

A laboratory value was considered abnormal if the result was below or above the normal range for the age of each patient.

Limited laboratory information was available in 5 patients: 2 patients in G1, 1 patient in G4 and 2 patients in G8.

24

Supplemental Table 3. Pulmonary alveolar proteinosis (PAP) and macrophage activation syndrome (MAS), G1 (IL-18PAP-MAS)

Disease group Patients/Outcome

Potential genetic disease

associated mutations#

Disease onset Clinical Characteristics

IgE IU/mL at first

visit (min-max)

Immune signature: IL-18 serum level (min-max), IFN score (min-

max)

Past and current treatment responses

G1 Pt1/ alive candidate gene de novo mutation under investigation

6 mos PAP (biopsy confirmed), recurrent MAS, clubbing, elevated IgE

706-1342 IU/mL

27,498-351,441pg/mL/ 116.51-263.63

stable response to canakinumab and cyclosporine

G1 Pt2/ alive candidate gene compound heterozygous mutations under investigation

Dx at 15 mos with fever, rash, MAS. Noticed clubbing while systemic disease was quiet at about 2yrs, but lung disease not identified by CT until 3yrs.

recurrent MAS, clubbing, characteristic CT, never biopsied.

4.5 IU/mL 29,597-151,987pg/mL/ 144.56A

stable response to canakinumab, cyclosporine, tacrolimus, prophylactic trimethoprim-sulfamethoxazole, no response to tocilizumab

G1 Pt3/ deceased no obvious candidate

Born at 30ks, twin. sJIA onset at 10 mos with severe but transient arthritis. Began developing "recurrent pneumonia" around age 2yrs 6mos

PAP (biopsy confirmed) recurrent MAS, clubbing, elevated IgE

1804 IU/mL

53,697-141,069pg/mL/ -4.83-42.70

incomplete responses to anakinra/canakinumab, cyclosporine, IVIg, tocilizumab, prophylactic trimethoprim-sulfamethoxazole

G1 Pt4/ alive no obvious candidate

Presented at 15 mos with KD-like syndrome

recurrent MAS, clubbing, characteristic CT, elevated IgE

1506 IU/mL

76,114pg/mLA / 10.42-112.05

partial responses to anakinra and cyclosporine, no response to tocilizumab

25

G1 Pt5/ alive novel variant in NLRC4 (from maternal allele), candidate gene de novo mutation under investigation

Presented at 3yrs with sJIA/MAS, refractory course. Eventually well on treatment, but mild clubbing and subpleural blebs noted on CT. PAP developed over 6 months of difficult to control MAS.

PAP (biopsy confirmed) recurrent MAS, clubbing, elevated IgE

503 IU/mL

2,506-430,423pg/mL/ 13.77A

partial responses to canakinumab and cyclosporine, no response to tocilizumab

G1 Pt6/ alive S/P treatment for AMLB

candidate gene compound heterozygous mutations under investigation

5 weeks recurrent MAS, clubbing, characteristic CT. Patient developed AML at age 4.5yrs

ND ND/ 262.75A partial response to anakinra, improvement of MAS S/P treatment for AML

G1 Pt7/ alive no obvious candidate

sJIA dx at 13 mos of age, clubbing onset at 26 mos

PAP (biopsy confirmed) recurrent MAS, clubbing

4 IU/mL 42,383-117,345pg/mL/ -20.36-87.38

partial response to cyclosporine, tocilizumab, cyclophosphamide, prophylactic trimethoprim-sulfamethoxazole, currently on treatment with anakinra, tadekinig and tofacitinib with stable disease

G1 Pt8/ deceasedB no obvious candidate

sJIA dx at 7yrs. Lung disease incidentally noted about 1 year later

PAP (biopsy confirmed) recurrent MAS, clubbing

Normal 26,074-179,502pg/mL/ -22.78-200.38

NA

IL-18 normal range (100 - 500pg/ml); PAP: pulmonary alveolar proteinosis; Dx: diagnosis; AML: acute myeloid leukemia; MAS: macrophage activation syndrome; sJIA: systemic juvenile idiopathic arthritis; KD-like: Kawasaki disease-like; CT: computer tomography; IVIg: intravenous immunoglobulin;

A One measurement only, B Not seen at NIH (records reviewed only)

26

Supplemental Table 4. Genetic data and Immune phenotype of disease groups with B cell cytopenia +/- low immunoglobulin levels, G2 (LRBA), G3 (NDAS) and G4 (SAAD)

Disease group

Patients/Outcome

B -cell cytopenias

low IgG low IgM low IgA Other hematopoietic findings

Comorbidities Genetic mutation Past and current treatment responses

G2 Pt1 NIH age 2yrs 7mos/ alive

initially high B cell count, developed progressive B cell lymphopenia at 4yrs 8mos

low IgG (documented 4yrs 2mos)

low IgM (developed 6yrs 2mos)

low IgA (documented 4yrs 2mos)

BMB: normocellular with trilineage hematopoiesis, decreased B-cells, mild increase in T-cells, few hemophagocytic histiocytes; low IgE

granulomatous liver disease, HSM

LRBA: c.6010C>T/ p.H2004Y and c.6671G>A/ p.R2224Q autosomal recessive, compound heterozygous

minimal response to MMF, sirolimus and abatacept, currently on baricitinib and lower doses of prednisone

G2 Pt2 NIH age 4yrs 10mos/ alive S/P BMT (8yrs)

has high B cells since splenectomy at 4yrs 7mos

low IgG (documented 7yrs 1mo)

low IgM (documented 7yrs 1mo)

normal IgA BMB NA, low IgE suspicious of granulomatous lymphocytic ILD (GLILD) and autoimmune hepatitis, severe HSM S/P splenectomy (4yrs 8mos). On treatment with sirolimus and abatacept, patient developed cervical myelitis (C2-C5)(7yrs 6mos) and septic arthritis (7yrs 9mos)

LRBA: c.7648C>T/ p.Q2550* and c.1359+1G>A autosomal recessive, compound heterozygous

minimal response to MMF, sirolimus and abatacept, currently post-BMT

27

G3 Pt1 NIH age 20mos/ alive

low B cell count at 7yrs, progressive B cell lymphopenia

low IgG (documented 20mos)

low IgM (developed 5yrs)

fluctuating low IgA (documented 20mos)

no response to pneumococcal vaccine, no major infections, nl IgE

granulomatous uveitis, HSM, granulomatous hepatitis

IKBKG: c.597G>A/ p.V199V X-linked recessive, de novo

currently on adalimumab with partial response


low B cell count at 4yrs 8mos, progressive B cell lymphopenia


low IgM (developed 4yrs 8mos)

still low normal no major infections, IgE 250 IU/mL

Synechiae due to anterior uveitis, mild HSM

IKBKG: c.671+5G>A X-linked recessive, de novo

minimal response to MTX, MMF, tocilizumab, anakinra, etanercept and infliximab, currently on adalimumab with partial response

G3 Pt3 NIH age 2yrs 3 mos/ alive

low B cell count at 2yrs 3mos, progressive B cell lymphopenia


normal IgM low IgA (documented 2yrs 3mos)

on IVIG since age 2yrs 6 mos; h/o ITP (positive antiplatelet antibodies age 6yrs 6mos), no major infections, BMB: hypocellular marrow with trilineage hematopoiesis and markedly decreased to absent B-cells and B-cell precursors; nl IgE

mild HSM IKBKG: c.671+2T>G X-linked recessive, de novo

partial response to cyclosporine, tocilizumab, currently on adalimumab with moderate response

G3 Pt4A NIH age 14yrs/ alive

low B cell count at first NIH visit

normal IgG normal IgM elevated IgA anemia and lymphopenia, normal platelet count at first NIH visit

panniculitis, lipodystrophy, basal ganglia calcifications, myositis, anemia, lymphopenia

IKBKG: c.519-2A>G. X-linked dominant, de novo

partial response to MMF, no response to tofacitinib

28

G4 Pt1 NIH age 10mos/ alive

initially high B cell count, developed progressive B cell lymphopenia at 4yrs

normal IgG normal IgM elevated IgA (progressively since 4yrs)

anemia, initially thrombocytosis with progressive decrease in platelet counts, BMB: mildly hypercellular marrow with trilineage hematopoiesis, myeloid hyperplasia with mild left shift in myeloid maturation, lymphopenia with decreased B-cells and B-cell precursors; nl IgE

no ILD, mild HSM, subcortical white matter changes, neutrophilic panniculitis by biopsy. Viral infections: Coronavirus HKU1, RSV and Parainfluenza (3yrs8mos), adenovirus and rhinovirus (6yrs)

SAMD9L: c.2626delA/ p.I876Lfs*15 Autosomal dominant, de novo

partial/minimal response to corticosteroids and tocilizumab, currently on baricitinib with a partial response


B cell lymphopenia triggered by infections

elevated IgG normal IgM elevated IgA anemia, thrombocytopenia, BMB: markedly decreased B-cells; IgE 423 IU/mL

no ILD, HSM, neutrophilic panniculitis by biopsy. Viral infections: rhinovirus (3yrs2mos), RSV

SAMD9L: c.2633delA/ p.K878Sfs*13 Autosomal dominant, de novo

partial response to etanercept and IVIg

G4 Pt3 NIH age 12mos/ alive S/P BMT (21mos)

mild B cell lymphopenia pre BMT

normal IgG slightly low IgM (10mos)

normal IgA transfusion dependent anemia and leukocytosis (2mos), thrombocytopenia (6mos), progressive leukopenia (lymphopenia and neutropenia, 12mos), BMB with occasional hemophagocytosis

ILD (several admissions due to respiratory distress), mild HSM, basal ganglia calcifications and diffuse bilateral white matter disease, neutrophilic panniculitis by

SAMD9L: c.2658_2659delTT/ p.F886Lfs*11 Autosomal dominant, de novo

minimal response to cyclosporine, etanercept, adalimumab, anakinra, currently 10 years post-BMT

29

(6mos), normal IgE, CRP post BMT: 74-87 mg/L

biopsy. Viral infections: RSV (5mos), parainfluenza (6mos)

G4 Pt4B/ deceased (6yrs)

initially low (1mo) and then absent (12mos) B cell count

NR NR NR chronic thrombocytopenia (since birth), anemia with reticulocytosis (12mos), low NK cells. BMB (3 weeks of life): decreased CD20 (< 5%) and PAX5 (5-10%) B-cells

perinatal intracranial temporal lobe bleed (secondary to thrombocytopenia), basal ganglia calcifications, severe ILD, HSM with portal hypertension, neutrophilic panniculitis by biopsy, hypertension (since birth)


minimal response to anakinra, IVIg

G4 Pt5B/ deceased (2mos), post-mortem diagnosis

severe B cell aplasia (absent B cells)

NR NR NR anemia, progressive thrombocytopenia (perinatal), low NK cells, normal T cell number with decreased proliferation

basal ganglia calcifications, severe ILD, HSM, neutrophilic panniculitis by biopsy. Viral infections: chronic rhinovirus infection


IVIg

30

G4 Pt6B/ alive S/P BMT (9mos)

reported low B cell count (3mos)

hypo-gamma-globulinemia

NR NR Thrombocytopenia, normal T cell number, low NK cells, BMB NR

severe ILD, splenomegaly, neutrophilic panniculitis by biopsy, negative brain CT

SAMD9L: c.2666delT/ p.F889Sfs*2 Autosomal dominant, de novo

IVIg, currently 3 years post-BMT

A patient was reclassified from CANDLE-like to NEMO-NDAS while writing the manuscript and discovering the splice variant in IKBKG/NEMO in this patient. Her samples were therefore not included in the validation experiments for the NF-kB signaling but served as a confirmation.

B not seen at NIH.

C Patient has another potentially pathogenic mutation in LRP8: c.241T>C/ p.C81R, de novo

D Patient has another potentially pathogenic mutation in IRS1: c.3632T>G/ p.L1211R, de novo

NIH age: age first seen at NIH. None of the patients in these groups had autoantibodies to ANA, ACA and lupus anticoagulant.

BMT: bone marrow transplant; BMB: bone marrow biopsy; ILD: interstitial lung disease; HSM: hepatosplenomegaly; ITP: immune thrombocytopenic purpura; RSV: respiratory syncytial virus; MMF: mycophenolate mofetil; MTX: methotrexate; IVIg: intravenous immunoglobulin; nl: normal: NR: not reported

IgE upper limit of normal 90 IU/mL

31

Supplemental Table 5. Genetic Data and Clinical Description of Patients with AGS/AGS-like Disease (G5), aMDA5-pos JDM (G6) and CANDLE/CANDLE-like (G7) Syndromes and SAVI-like Disease (G8).

Disease group

Patients/Disease type Outcome Genetic

mutation Clinical Characteristics Past and current treatment responses

G5 Pt1 AGS5 alive SAMHD1, homozygous 9Kb deletion

stroke at age 7, Moya-Moya like disease, left-eye blindness due to retinal vasculitis, peripheral vasculopathy with livedo reticularis, S/P revascularization surgery, progressive fixed finger contractures

stable disease since on baricitinib over last 5 years

G5 Pt2 AGS/AGS-like

deceased candidate gene de novo large deletion under investigation

white matter disease, spastic quadriplegia, ulcerative vasculitis in predominantly cold exposed areas

no response to MTX and etanercept

G5 Pt3 AGS/AGS-like

alive no obvious candidate

white matter disease, spastic quadriplegia, ulcerative vasculitis in predominantly cold exposed areas, nodular regenerative hyperplasia with portal hypertension

partial response to IVIg, no response to azathioprine, no response to baricitinib

G5 Pt4 AGS/AGS-like


father of pt. 3 included due to basal ganglia calcifications and elevated IFN score

partial response to tofacitinib

32

G6 Pt1 anti-MDA5

autoantibody-positive JDM


ILD, myositis, Gottron's papules, heliotrope rash, calcinosis, transaminitis with mild portal inflammation and fibrosis

partial response to MTX and IVIg

G6 Pt2A anti-MDA5 autoantibody-positive JDM

deceased no obvious candidate

acute progressive ILD, Gottron's papules no response to cyclophosphamide and ruxolitinib

G7 Pt1 CANDLE-like

(sibling of Pt 2) alive candidate gene

homozygous mutation under investigation

lymphohistiocytic panniculitis with lipodystrophy, leukopenia and thrombocytopenia

hydroxychloroquine

G7 Pt2 CANDLE-like (sibling of Pt 1)

alive candidate gene homozygous mutation under investigation

presentation with MAS in early childhood, panniculitis with lipodystrophy, leukopenia and thrombocytopenia

treatment of MAS episode

G7 Pt3 CANDLE-like alive TREX1: de novo, somatic p.D255N

myositis, subcutaneous calcifications, skin rash with perivascular predominantly lymphocytic infiltrate

partial response to methotrexate, hydroxychloroquine and IVIg, complete response to baricitinib

33

G7 Pt4 CANDLE deceased due to complications from primary pulmonary hypertension

PSMB8: homozygous: p.T75M

neutrophilic panniculitis and lipodystrophy, patchy myositis, systemic inflammation, metabolic syndrome, severe primary pulmonary hypertension

partial response to cyclosporine and tofacitinib

G7 Pt5 CANDLE alive PSMB8: compound heterozygous: p.Q55* and p.S118P

neutrophilic panniculitis and lipodystrophy, patchy myositis, systemic inflammation, milder disease with normalization of acute phase reactants in between flares

no response to MTX, etanercept and infliximab, good response to tofacitinib

G7 Pt6A CANDLE alive PSMG2: p.Y223Sfs*2 and p.N225K

neutrophilic panniculitis and lipodystrophy, patchy myositis, systemic inflammation, metabolic syndrome

good response to ruxolitinib

G8 Pt1A SAVI-like alive no obvious

candidate skin vasculopathy N/A

G8 Pt2A SAVI-like alive no obvious candidate

skin vasculopathy N/A

A not seen at the NIH MTX: methotrexate; MMF: mycophenolate mofetil; IVIg: intravenous immunoglobulin; JDM: juvenile dermatomyositis; ILD: interstitial lung disease; MAS: macrophage activation syndrome

34

Supplemental Table 6. Clinical features of patients with unclassifiable disease, group 9 (G9)

Disease group

Patient/outcome Unique clinical features Other potentially pathogenic mutations

IRS and 3/25 ratio Past and current treatment responses

G9 P1/alive psoriasiform dermatitis with scarring and skin fibrosis predominantly between digits and periorally, severe recurrent scleritis, little systemic inflammation, ANA neg.

possible disease-causing compound heterozygous mutations in a candidate gene are under study

28-gene score: 146.79-266.95. 3/25 ratio: 0.25-0.33

partial response to MTX, etanercept and anakinra; no response to baricitinib

G9 P2/deceased Severe destructive erosive granulomatous dermatitis, severe growth retardation and bone maturation, severe systemic inflammation. Positive ANA

possible disease-causing mutation in a candidate gene are under study

28-gene score: 2224.72 3/25 ratio: 0.055

no response to MMF, MTX, infliximab and anakinra

G9 P3/alive recurrent SLE-like symptoms as adult with systemic inflammation and recurrent pericarditis and pleuritis, strongly positive ANA (>12), anti-Sm, anti-SSA and anti-SSB

X-linked rare variant in TREX2 (VUS)

28-gene score: 205.51 to 273.16 3/25 ratio: 0.021-0.051

partial response to HCQ, colchicine, MTX, azathioprine, anakinra and tofacitinib

G9 P4/alive dermatitis with elastin destruction and exuberant skin in severely affected skin/scar areas, fever and systemic inflammation very elevated ANA-IgA titers

rare compound heterozygous variants in DENND5A (VUS) and de novo in DENND6B (VUS)


partial response to MTX, MMF and tocilizumab

G9 P5/alive systemic inflammation with recurrent colitis and MAS

no obvious candidate 28-gene score: -7.47 to 218.60 3/25 ratio: 0.12-0.26

partial response to cyclosporine and tocilizumab

35

G9 P6/alive systemic inflammation with recurrent aseptic meningitis

rare compound heterozygous variants in DLL4 (VUS)


significant response to tocilizumab

G9 P7/alive systemic inflammation with recurrent pyoderma gangrenosum, pathergy, oral ulcers and colitis

rare compound heterozygous variants in DLG5 (VUS)


no response to anakinra, partial response to infliximab and adalimumab

MTX: methotrexate; MMF: mycophenolate mofetil; HCQ: hydroxychloroquine; MAS: macrophage activation syndrome; ANA: antinuclear antibody; SLE: systemic lupus erythematosus

36

Supplemental Table 7. Clinical features of patients with normal IFN scores

Disease group

Patients/ Outcome Unique clinical features Potentially pathogenic

mutationsA Treatment responses

GN1 P1/alive severe recurrent sterile osteomyelitis affecting femur, paronychia, sister of Pt4

No obvious candidate partial response to NSAIDs and etanercept

GN1 P2/alive TMJ and mandibular osteomyelitis No obvious candidate significant response to indomethacin, MTX and sulfasalazine

GN1 P3/alive recurrent osteomyelitis No obvious candidate significant response to indomethacin

GN1 P4/alive severe recurrent sterile osteomyelitis affecting knees and spine, sister of Pt1

No obvious candidate partial response to NSAIDs and IL-1 inhibition

GN1 P5/alive jaw osteomyelitis and hearing loss Compound heterozygous variants in EWSR1 (c.1408G>A, p.G470S, MAF: 0.008219; 2323 Hets, 13 HM and c.1016A>G, p.N339S, MAF: 0.0001239, 35 Hets, 0 HM)(VUS)

significant response to canakinumab

GN2 P1/alive recurrent headaches with increased ICP, arthralgia, recurrent fever, abdominal pain and painful urticarial rash (biopsy with superficial and periadnexal mixed inflammatory infiltrate), mild leukopenia and neutropenia

Het NLRP3 rare variant (c.578C>A, p.T193K) in patient and father (MAF: 0.00001416; 4 Hets, 0 HM) (VUS)


GN2 P2/alive recurrent fever and urticarial rash, mother with similar phenotype

Het NLRP3 rare variant (c.974G>A, p.R325Q) in patient and mother (MAF: 0.000014194; 4 Hets, 0 HM) (VUS)

partial response to NSAIDs and anakinra

37

GN2 P3/alive recurrent fever, headaches, arthralgia and abdominal pain

Het NLRP3 rare variant (c.1630G>A, p.V544I) in patient and father (MAF: 0.00005306; 13 Hets, 0 HM) (VUS)


GN2 P4/alive recurrent fever, mild erythematous and blistering rash, arthralgia, lymphadenopathy, recurrent otitis and mastoiditis (1x)

Het NLRP3 rare variant (c.1463G>A, p.R488K) in patient and father (MAF: 0.0006688; 188 Hets, 0 HM) (VUS)

Partial response to IL-1 inhibition (insufficient follow up data)

GN3 P1/alive neonatal onset maculopapular rash (bx with neutrophilic dermatosis, perivascular neutrophilic infiltrate), fever, systemic inflammation.

No obvious candidate no response to colchicine, partial response to anakinra/canakinumab

GN3 P2/alive recurrent fever, headaches, lymphadenopathy, leukopenia and neutropenia

No obvious candidate partial response to anakinra/canakinumab

GN3 P3/alive recurrent fever, rash, arthralgia, headaches, pineal cyst

No obvious candidate incomplete response to anakinra, canakinumab and tocilizumab

GN3 P4/alive recurrent fever, rash, superior sagittal sinus blockade, superior oblique palsy bilaterally, alopecia, abdominal pain, diarrhea, oral ulcers

No obvious candidate no response to NSAIDs, and colchicine, significant response to etanercept

GN3 P5/alive recurrent fever, headache, lymphadenopathy, alopecia areata, eosinophilia

No obvious candidate partial response to NSAIDs and MTX

GN3 P6/alive recurrent fever, maculopapular rash, hypotonia and motor developmental delay, recurrent sinopulmonary infections, adrenal insufficiency; sister with similar phenotype

Het AIRE rare variant (c.132+1G>C, MAF 0.000007103, 1 Het, 0 HM)

partial response to anakinra

38

GN4 P1/alive recurrent MAS episodes, fever, macular rash (bx with mild perivascular neutrophilic infiltrate), hepatosplenomegaly (normal liver biopsy), lymphadenopathy, periorbital cellulitis (1x), anemia and thrombocytopenia, high IL-18 serum levels (9,878.01 pg/mL)

Compound heterozygous variants in ATM (c.1229T>C, p.V410A, MAF: 0.002135, 603 Hets, 2 HM and c.4709T>C, p.V1570A, MAF: 0.0004144, 117 Hets, 0 HM)(VUS)

no response to MMF, partial response to anakinra

GN4 P2/alive recurrent MAS episodes, fever, macular rash, hepatosplenomegaly, lymphadenopathy, thrombocytopenia, high IL-18 serum levels (24,100.53 pg/mL)

Het NLRC4 rare variant (c.2357G>T, p.G786V) in patient and father (MAF: 0.002385, 660 Hets, 2 HM)(VUS)

partial response to etanercept, tocilizumab e anakinra

GN4 P3/alive recurrent fever, urticarial rash (bx with perivascular chronic inflammation with interstitial neutrophils), arthralgia, myalgia, leukopenia, high IL-18 serum levels (21,580.18 pg/mL)

No obvious candidate no response to MTX, etanercept, adalimumab, tocilizumab, significant response to anakinra and canakinumab

GN5 P1/alive pyoderma gangrenosum, aorta dilation and pulmonary stenosis, hypoplastic right kidney, ganglion cyst

No obvious candidate no response to cyclosporine, partial response to MTX, infliximab and IVIg

GN5 P2/alive pustular psoriasis-like Homozygous deletion under investigation

temporary response to anakinra, partial response to adalimumab

GN5 P3/alive systemic inflammation, recurrent capillaritis, hepatitis and liver cirrhosis

candidate gene under investigation

partial response to Src kinase inhibition and etanercept

GN5 P4/alive recurrent fever, hypocomplementemic vasculitis, stroke

Compound heterozygous variants in LRP2 (c.894A>C, p.E298D, MAF: 0.00001416, 4 Hets, 0 HM and c.13569C>A, p.N4523K, MAF: 0)(VUS)

partial response to rituximab and IVIg

39

GN5 P5/alive recurrent fever and interstitial lung disease (biopsy with focal perivascular eosinophilic infiltrate)

No obvious candidate partial response to IVIg

GN5 P6/alive recurrent fever, urticarial rash No obvious candidate no response to cyclosporine, MTX anakinra and omalizumab

GN5 P7/alive urticarial rash, chronic arthritis, anemia Het AIRE rare variants in patient and father (c.701G>A, p.R234Q, MAF: 0.002579; 552 Hets, 10 HM and c.1244A>G, p.H415R, MAF: 0.0001967; 45 Hets, 0 HM)

no response to infliximab and tocilizumab, partial response to MTX and anakinra

GN1 CRMO/CRMO-like

GN2 CAPS/CAPS-like GN3 Periodic fever syndrome

GN4 Still's like disease and MAS

GN5 Other

A Minor allele frequency (MAF) stated are from gnomAD (genome aggregation database)(https://gnomad.broadinstitute.org/)

IL-18 normal range (100 - 500pg/ml)

NSAIDs, nonsteroidal anti-inflammatory drugs; TMJ, temporo-mandibular joint; SAPHO, Synovitis, Acne, Pustulosis, Hyperostosis, and Osteomyelitis; MTX, methotrexate; Hets, heterozygotes; HM, homozygotes; VUS, variant of unknown significance; IVIg, intravenous immunoglobulin; CRMO, chronic recurrent multifocal osteomyelitis; CAPS, cryopyrin associated periodic syndrome; MAS, macrophage activation syndrome

40

Supplemental Table 8. Clinical and genetic features and treatment responses of patients treated with JAK inhibitors

Disease group Patient/Age/Outcome Genetic Mutation Clinical Characteristics Past and Current Treatment Responses

G1 Pt7/ NIH age 5yrs 8mos/ alive

no obvious candidate sJIA dx at 13 months of age, clubbing onset at 26 months of age; PAP (biopsy confirmed) recurrent MAS, clubbing

partial response to cyclosporine, tocilizumab, and cyclophosphamide; currently on treatment with anakinra, tadekinig and tofacitinib with stable disease

G2 Pt1A/ NIH age 2yrs 7mos/ alive

LRBA: c.6010C>T/p.H2004Y and c.6671G>A/p.R2224Q autosomal recessive, compound heterozygous

neutrophilic panniculitis, lipodystrophy, granulomatous liver disease, systemic inflammation, progressive B cell lymphopenia, hypogammaglobulinemia

partial response to MMF, sirolimus and abatacept; currently on baricitinib and lower doses of prednisone with recovery of blood counts and better clinical control

G3 Pt4/ NIH age 14yrs/ alive IKBKG: de novo, c.519-2 A>G

panniculitis, lipodystrophy, basal ganglia calcifications, myositis, anemia, lymphopenia

partial response to MMF, no response to tofacitinib

41

G4 Pt1A/ NIH age 10mos/ alive

SAMD9L: c.2626delA/p.I876Lfs*15 Autosomal dominant, de novo

neutrophilic panniculitis, mild HSM, systemic inflammation, anemia, mild B-cell lymphopenia subcortical white matter changes

partial/minimal response to corticosteroids and tocilizumab, currently on baricitinib with a partial response

G5 Pt1A/ NIH age 12yrs/ alive

SAMHD1, homozygous 9Kb deletion

stroke at age 7yrs, Moya-Moya like disease, left eye blindness due to retinal vasculitis, peripheral vasculopathy with livedo reticularis, S/P revascularization surgery, progressive fixed finger contractures

stable disease since on baricitinib (started in 2015) with gradual decrease in IFN scores

G5 Pt3A/ NIH age 10mos/ alive

no obvious candidate white matter disease, spastic quadriplegia, ulcerative vasculitis in predominantly cold exposed areas, nodular regenerative hyperplasia with portal hypertension

partial response to IVIg and corticosteroids, minimal or no response to azathioprine, no response to baricitinib

G5 Pt4/ NIH age 29yrs/ alive no obvious candidate father of Pt 3 included due to basal ganglia calcifications and elevated IFN score

partial response to tofacitinib

G6 Pt1/NIH age 5yrs/ alive no obvious candidate ILD, myositis, Gottron's papules, heliotrope rash, transaminitis with mild portal inflammation and fibrosis

partial response to MTX and IVIg, response to tofacitinib not clearly demonstrated at this point

G6 Pt2B/ deceased no obvious candidate acute rapidly progressive ILD, Gottron's papules

no response to cyclophosphamide and ruxolitinib which was initiated when patient was in ICU intubated

42

G7 Pt3/ NIH age 5yrs/ alive TREX1: de novo, somatic p.D255N

myositis, subcutaneous calcifications, skin rash with perivascular predominantly lymphocytic infiltrate

partial response to MTX, HCQ and IVIg, complete response to baricitinib

G7 Pt4/ NIH age 6yrs 7mos/ deceased

PSMB8: homozygous: p.T75M

neutrophilic panniculitis and lipodystrophy, patchy myositis, systemic inflammation, metabolic syndrome, severe primary pulmonary hypertension

partial response to cyclosporine and tofacitinib

G7 Pt5/ NIH age 12yrs/ alive PSMB8: compound heterozygous: p.Q55* and p.S118P

neutrophilic panniculitis and lipodystrophy, patchy myositis, systemic inflammation, milder disease with normalization of acute phase reactants in between flares

no response to MTX, etanercept and infliximab; significant response to tofacitinib

G7 Pt6B/ alive PSMG2: p.Y223Sfs*2 and p.N225K

neutrophilic panniculitis and lipodystrophy, patchy myositis, systemic inflammation, metabolic syndrome

significant response to ruxolitinib

G9 P1A/ NIH age 5yrs/ alive possible disease-causing compound heterozygous mutations in a candidate gene are under study

psoriasiform dermatitis with scarring and skin fibrosis predominantly between digits and periorally, severe recurrent scleritis, little systemic inflammation, negative ANA

partial response to MTX, etanercept and anakinra; no response to baricitinib

43

G9 P3/ NIH age 25yrs/ alive X-linked rare variant in TREX2 (VUS)

recurrent SLE-like symptoms as adult with systemic inflammation and recurrent pericarditis and pleuritis, strongly positive ANA (>12), positive anti-Sm, anti-SSA and anti-SSB

partial response to HCQ, colchicine, MTX, azathioprine and anakinra, partial response to tofacitinib

Apatients who received compassionate use baricitinib under NCT01724580, patients G2-P1, G4-P1, G5-P1, G5-P3 and G9-P1. Patients G4P1, G5-P1 and G9-P1 were reported in Montealegre Sanchez, JCI 2018

Bnot seen at the NIH

VUS, variant of unknown significance; MTX, methotrexate; MMF, mycophenolate mofetil; IVIg, intravenous immunoglobulin; HCQ, hydroxychloroquine; sJIA, systemic juvenile idiopathic arthritis; ILD, interstitial lung disease; ICU, intensive care unit; SLE, systemic lupus erythematosus; ANA, antinuclear antibody; MAS, macrophage activation syndrome; PAP, pulmonary alveolar proteinosis

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Supplemental Table 9. Proposed Disease Criteria for Patients in Both Interferonopathies and Non-interferonopathies Groups

Disease Group

Number Disease Name Disease Criteria to define a disease

group before genetic evaluation Current Disease Criteria after genetic and

immunologic Evaluation

IFNopathies

G1 IL-18PAP-MAS ILD, interferon signature Novel disease; No genetic diagnosis: high IL-18 levels, biopsy proven PAP or CT consistent with moist infiltrate, clubbing, normal to mildly elevated 28 IFN score and variable 3/25 gene ratio

G2 LRBA-deficiency neutrophilic/lymphocytic panniculitis and IFN signature (CANDLE-like)

Known disease, expanded phenotype; Genetic diagnosis: LRBA LOF mutations with CTLA4 recycling defect, IFN signature with high 3/25 gene ratio >0.15

G3 NEMO-NDAS neutrophilic/lymphocytic panniculitis and IFN signature (CANDLE-like)

Novel disease; Genetic diagnosis: NEMO D5 splice variant, IFN signature with high 3/25 gene ratio >0.15 and panniculitis

G4 SAMD9L-SAAD neutrophilic/lymphocytic panniculitis and IFN signature (CANDLE-like)

Novel disease; Genetic diagnosis: SAMD9L truncating GOF mutation, panniculitis, IFN signature with normal to mildly elevated 28 IFN score and variable 3/25 gene ratio

G5 AGS/AGS-like white matter disease and IFN signature No unifying genetic diagnosis for patients with no known AGS mutation: white matter disease and IFN signature (AGS with known disease-causing mutation)

G6 Myositis + positive anti-MDA5 autoantibody

ILD, Gottron's papules and IFN signature, diagnosed as anti-MDA5 positive JDM when anti-MDA5 antibody tests were positive

Clinical diagnosis; No genetic diagnosis: myositis, anti-MDA5 autoantibody positive JDM

45

G7 CANDLE/CANDLE like

neutrophilic panniculitis and IFN signature

Genetic diagnosis of CANDLE for 3 patients, novel CANDLE-causing gene, PSMG2. No unifying diagnosis for 3 CANDLE-like patients

G8 SAVI-like peripheral acral (chilblain like vasculopathy) in context of interstitial lung disease and IFN signature

No unifying genetic diagnosis: peripheral acral (chilblain like vasculopathy) in context of ILD and IFN signature

G9 Other positive IFN signature in blood and not fulfilling any criteria above, and no other patient had similar disease manifestations

No unifying clinical diagnoses. No genetic diagnoses: no change of diagnostic criteria from entry

Non-IFNopathies

GN1 CRMO-like presence of sterile osteomyelitis Clinical diagnosis; No unifying genetic diagnosis: no unifying pathogenic diagnosis

GN2 CAPS-like fever and urticarial rashes and inflammation and organ damage in a CAPS-like pattern (neutrophilic aseptic meningitis, hearing loss due to cochleitis)

Possible genetic hypothesis: rare variants in NLRP3, that are all inherited from a parent, may be low penetrance variants that modify/predispose to a CAPS-like clinical phenotype

GN3 Periodic fever syndrome

periodic fevers with episodes of remission in between attacks

No unifying clinical diagnoses. No genetic diagnoses: no change of diagnostic criteria from entry

GN4 sJIA-like disease with MAS

inflammatory flares associated with ferritin elevation, drop in platelets, increase in LFTs and LDH

Clinical diagnosis; No genetic diagnosis: Inflammatory flares associated with ferritin elevation, drop in platelets, increase in LFTs and LDH, all patients had elevated serum IL-18 levels and a IL-18/CXCL9 ratio for greater than 1 consistent with other patients who have high IL-18 states and a predisposition to MAS.

46

GN5 Other not fulfilling any criteria above and no other patient had similar disease manifestations

No unifying clinical diagnoses. No genetic diagnoses: cannot be classified with the above

ILD, interstitial lung disease; PAP, pulmonary alveolar proteinosis; CT, computed tomography; LOF, loss-of-function; GOF, gain-of-function; NDAS, NEMO deleted exon 5 associated autoinflammatory syndrome; MAS, macrophage activation syndrome; SAAD, SAMD9L-associated autoinflammatory disease; CANDLE, chronic atypical neutrophilic dermatosis with lipodystrophy and elevated temperature; AGS, Aicardi-Goutières syndrome; JDM, juvenile dermatomyositis; CAPS, cryopyrin-associated periodic syndrome; sJIA, systemic

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IV. Supplemental References

1. Sanchez GAM, Reinhardt A, Ramsey S, Wittkowski H, Hashkes PJ, Berkun Y, et al. JAK1/2 inhibition with baricitinib in the treatment of autoinflammatory interferonopathies. The Journal of clinical investigation. 2018;128(7):3041-3052.

2. Daily K, Patel VR, Rigor P, Xie X, and Baldi P. MotifMap: integrative genome-wide maps of regulatory motif sites for model species. BMC Bioinformatics. 2011;12:495.

3. Xie X, Rigor P, and Baldi P. MotifMap: a human genome-wide map of candidate regulatory motif sites. Bioinformatics. 2009;25(2):167-74.

4. Kim H, de Jesus AA, Brooks SR, Liu Y, Huang Y, VanTries R, et al. Development of a Validated Interferon Score Using NanoString Technology. Journal of interferon & cytokine research : the official journal of the International Society for Interferon and Cytokine Research. 2018;38(4):171-85.

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