Clinical and immunological impact of JAK inhibition in concurrent Down Syndrome and STAT1 gain of function

Background: Down syndrome (DS) and STAT1 gain-of-function (GOF) share clinical and molecular features, including persistent inflammation. We aim to investigate whether the coexistence of DS and a STAT1 GOF mutation in a patient synergistically enhance interferon (IFN) signaling and exacerbate inflammatory responses, posing additional management challenges. Methods: Two patients (P1 and P2) were studied: P1, with DS and a heterozygous p.P326S STAT1 variant, and P2, with the STAT1 p.P326S variant only. Individuals with isolated DS or STAT1 GOF served as controls. IFN receptor subunits (IFNγR1/R2 and IFNαR1/R2) and responses to IFNα/γ stimulation were analyzed using flow cytometry and RT-PCR. Whole blood type-I IFN signature and serum cytokines were evaluated using NanoString and Luminex assays, respectively. Results: P1 experienced recurrent infections, chronic mucocutaneous candidiasis, interstitial pneumonitis, and pulmonary hypertension. P2 presented with esophageal candidiasis, dysphagia, and stenosis. The p.P326S variant led to increased STAT1/pSTAT1 levels in response to IFNα/γ. Both patients showed significant clinical improvement with the Janus kinase (JAK) inhibitor ruxolitinib. However, in P1, key biomarkers (STAT1 levels, IFN signature, and cytokines such as TNFα and IL-6) remained altered, indicating persistent inflammation despite clinical improvement. Conclusion: This first report of a STAT1 GOF variant in DS provides a unique ”experiment of nature,” offering insights into the interplay between trisomy 21 and STAT1-mediated immune dysregulation. Although treatment with ruxolitinib demonstrated clinical benefits, the persistent inflammation observed in P1 highlights the need for further strategies to achieve complete immune resolution. These findings emphasize the importance of comprehensive genetic and immunologic assessments in individuals with DS, particularly when immune dysfunction is suspected. Clinical and immunological impact of JAK inhibition in concurrent Down Syndrome and STAT1 gain of function Pilar Blanco-Lobo 1,2, Paula Gilabert Prieto 3, Beatriz de Felipe 1, David Moreno-Fuentes 1, Paloma Guisado Hernández 1, Ana Ortiz-Ramírez 4,5, Anna Mensa-Vilaró 6,7, Juan I Aróstegui 6,7,, Natalia Palmou 8, Valle Velasco Gonzalez 9, Ángela Deyà Martinez 10,11,12, Jan Ramakers 13, José Ivorra-Cortés 14, Cristina Roca 15, Elisa Cordero 15,16,17, Inmaculada Guillen 18, Nicolás Valerdiz Menéndez 19, José Manuel Lucena 20, Mirella Gaboli 21, Peter Olbrich 1,2,#, Olaf Neth 1 1 Instituto de Biomedicina de Sevilla, Research Group: “Inborn Errors of Immunity”, IBiS/Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Pediatric Infectious Diseases, Rheumatology and Immunology Unit, Red de Investigación Traslacional en Infectología Pediátrica RITIP, Seville, Spain. 2 Departamento de Farmacología, Pediatría y Radiología. Facultad de Medicina, Universidad de Sevilla, Seville, Spain. 3 Instituto de Biomedicina de Sevilla, IBiS/Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain. 4 Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y digestivas (CIBEREHD), Instituto de Salud Carlos III (ISCIII), 28009 Madrid, Spain. 5 Departament de Bioquímica i Biomedicina molecular, Facultat de Biologia, Universitat de Barcelona, 08028 Barcelona, Spain. 6 Department of Immunology, CDB, Hospital Clínic Barcelona, Spain. 7 Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain 8 Department of Rheumatology and Pediatric Rheumatology, Immunology Group, Hospital Universitario Marques de Valdecilla, Santander, Cantabria, Spain. 9 Pediatric Pulmonology, Canary Islands University Teaching Hospital, Tenerife, Spain. Institut de Recerca Hospital Sant Joan de Déu, Universitat de Barcelona, Esplugues, Spain. 10 Study group for Immune dysfunction Diseases in children. Institut de recerca Sant Joan de Deu 11 Departament de cirurgia i especialitats medicoquirúrgiques, Universitat de Barcelona. 12 Clinical Immunology Unit Hospital Sant Joan de Deu-Hospitcal Clínic de Barcelona, Barcelona. 13 Department of Pediatrics. Hospital Universitari Son Espases, Palma, Spain; Multidisciplinary Group for Research in Pediatrics, Balearic Island Health Research Institute (IdISBa), Palma, Spain. 14 Servicio de Reumatología, Hospital Universitari I Politècnic La Fe, Valencia, Spain. 15 Clinical Unit of Infectious Diseases, Microbiology and Parasitology, Institute of Biomedicine of Seville (IBiS), Virgen del Rocio University Hospital/CSIC/University of Seville, 41013 Seville, Spain. 16 Departament of Medicine, Faculty of Medicine, Universidad de Sevilla, Spain. 17 Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain. 18 Pediatric Cardiology Unit, Hospital Universitario Virgen del Rocío, 41013 Seville, Spain. 19 UGC Anatomía patológica, Hospital Universitario Virgen del Rocío, 41013 Seville, Spain. 20 Immunology Unit. University Hospital Virgen del Rocío, Seville, Spain 21 Pediatric Pneumology Unit, Hospital Universitario Virgen del Rocío, 41013 Seville, Spain. # Corresponding author: Peter Olbrich, MD, PhD Pediatric Infectious Diseases, Rheumatology and Immunology Unit Hospital Infantil Virgen del Rocío, Instituto de Biomedicina de Sevilla, Research Group: “Inborn Errors of Immunity” Av. Manuel Siurot, s/n. 41013, Sevilla, Spain. Phone: +34 695600725; Fax: +34-955012991 Departamento de Farmacología, Pediatría y Radiología. Facultad de Medicina, Universidad de Sevilla, Seville, Spain e-mail: [email protected] Short title: JAK inhibition in trisomy 21 and STAT1 gain of function Word count; number of tables and figures: Word count 3501, 2 tables and 4 figures. Tables and Figure Legends are embedded in the main Document. Figures, Cover Letter and Supplementary Material have been uploaded separately. Contributors Statement Page Peter Olbrich and Olaf Neth contributed to the conception of the work and revision of the final manuscript. Pilar Blanco-Lobo supervised the experiment performance and wrote the manuscript. Paula Gilabert Prieto, Beatriz de Felipe, Paloma Guisado Hernández, Ana Ortiz-Ramírez and David Moreno-Fuentes performed the experiments included in the final manuscript. Beatriz de Felipe organized sample shipping and processed all samples. Nicolas Valerdiz Menendez performed immunohistochemistry tests. Anna Mensa-Vilaró and Juan I Aróstegui determined and analyzed the type I interferon signature. Natalia Palmou, Valle Velasco Gonzalez, Ángela Deyà Martinez, Jan Ramakers, José Ivorra Cortés, Elisa Cordero, Cristina Roca, Mirella Gaboli, Immaculada Guillen and José Manuel Lucena contributed to the diagnosis, monitoring and recruitment of patients included in the final work All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work Conflict of interest: The authors declare no competing interests. Financial support: This work was supported by Instituto de Salud Carlos III, Madrid (Spain) [Sara Borrell, CD20/00124 to P.B.L, Juan Rodés JR18/00042 to P.O, FIS PI19/01471 to O.N, FIS PI22/01254 to ON and PO], contract for the Intensification of Research Activity AISNS (INT23/00089) to ON and Jerome Lejeune Foundation (2023) to ON. PI19/01567 grant from Instituto de Salud Carlos III (ISCIII) co-funded by the European Union (AM-V).

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Down syndrome (DS) and STAT1 gain-of-function (GOF) share clinical and molecular features, including persistent inflammation. We aim to investigate whether the coexistence of DS and a STAT1 GOF mutation in a patient synergistically enhance interferon (IFN) signaling and exacerbate inflammatory responses, posing additional management challenges.

Two patients (P1 and P2) were studied: P1, with DS and a heterozygous p.P326S STAT1 variant, and P2, with the STAT1 p.P326S variant only. Individuals with isolated DS or STAT1 GOF served as controls. IFN receptor subunits (IFNγR1/R2 and IFNαR1/R2) and responses to IFNα/γ stimulation were analyzed using flow cytometry and RT-PCR. Whole blood type-I IFN signature and serum cytokines were evaluated using NanoString and Luminex assays, respectively.

P1 experienced recurrent infections, chronic mucocutaneous candidiasis, interstitial pneumonitis, and pulmonary hypertension. P2 presented with esophageal candidiasis, dysphagia, and stenosis. The p.P326S variant led to increased STAT1/pSTAT1 levels in response to IFNα/γ. Both patients showed significant clinical improvement with the Janus kinase (JAK) inhibitor ruxolitinib. However, in P1, key biomarkers (STAT1 levels, IFN signature, and cytokines such as TNFα and IL-6) remained altered, indicating persistent inflammation despite clinical improvement.

This first report of a STAT1 GOF variant in DS provides a unique ”experiment of nature,” offering insights into the interplay between trisomy 21 and STAT1-mediated immune dysregulation. Although treatment with ruxolitinib demonstrated clinical benefits, the persistent inflammation observed in P1 highlights the need for further strategies to achieve complete immune resolution. These findings emphasize the importance of comprehensive genetic and immunologic assessments in individuals with DS, particularly when immune dysfunction is suspected. Key Message This is the first report describing the coexistence of Down syndrome and a STAT1 gain-of-function mutation, revealing a synergistic amplification of interferon signaling and immune dysregulation. The study underscores the clinical benefit of JAK inhibition whilst highlighting its limitations in completely controling hyperinflammation. These findings are of particular interest to clinicians and researchers focused on interferonopathies and complex immune disorders, as they provide new insights into the molecular and therapeutic challenges associated with dual genetic immune dysregulation.

Down syndrome, Inborn Errors of Immunity, STAT1 Transcription Factor, STAT1 gain-of-function, interferon, JAK inhibitors, Ruxolitinib

Down syndrome (DS) is one of the most common genetic disorders resulting from a partial or complete third copy of chromosome 21 (1). It is associated with neurodevelopmental delay, hypotonia, congenital cardiac and gastrointestinal abnormalities, and an increased risk of leukemia and Alzheimer-like disease . Individuals with DS are prone to autoimmune and autoinflammatory diseases, including type 1 diabetes, hypothyroidism, arthritis and skin conditions (1, 2). While their susceptibility to viral infections is not inherently high, viral infection-associated morbidity and mortality are disproportionately elevated compared to the general population (3). DS has been recently recognized as an interferonopathy characterized by persistent interferon (IFN) hyperactivity contributing to chronic sterile inflammation (4, 5). This phenomena is partly attributed to gene dosage effect, as 4 out of 6 IFN receptors subunits are encoded on chromosome 21, leading to heightened Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling (6-11) (Supplementary Figure 1). Peripheral blood mononuclear cells (PBMCs) from DS exhibit increased levels of total and phosphorylated STAT1 (pSTAT1) compared to controls (4, 6, 12). A recent multiomic analysis revealed that DS individuals with stronger activity of IFN signaling pathway were more prone to major comorbidities such as congenital heart disease and hypothyroidism (13). Recently, encouraging outcomes with JAK inhibitors (JAKi) have been reported in DS-associated autoimmune conditions, including alopecia areata and psoriatic arthritis (13-18). Ongoing clinical trials (NCT04246372, NCT05662228) aim to assess the therapeutic potential of modulating IFN responses with JAK1/JAK3 inhibitor tofacitinib in DS. From a clinical perspective, there is an overlap between certain DS individuals and those patients harboring gain-of-function (GOF) variants in STAT1, including chronic mucocutaneous candidiasis (CMC), poor infection outcomes and autoimmunity (19). Non-immunological complications, such as aneurysms, neurological features, and cognitive disability, are also observed in in patients with STAT1 GOF variants at slightly higher rates (19). The molecular hallmark of STAT1 GOF is characterized by increased total STAT1 and pSTAT1 in response to stimulation with type I/II IFNs (20, 21) (Supplementary Figure 1). JAKi have been successfully used in both adult and pediatric patients with STAT1 GOF variants (22-24), though prospective studies are needed to evaluate long-term treatment outcomes and identify biomarkers for assessing therapeutic efficacy. Here, we describe for the first time, a child with DS with severe clinical manifestations that significantly impacted her quality of life (QoL) who also carry the previously unreported STAT1 GOF variant (p.P326S). Treatment with ruxolitinib led to sustained clinical improvement, although key inflammatory markers remained elevated, indicating persistent subclinical inflammation. Study participants Study was approved by the ethics committees of Hospital Universitario Virgen Macarena and Hospital Universitario Virgen del Rocío (PI19/01471, 0641-N-20). Written informed consent from patients, patient’s parents and controls were obtained. The study was conducted according to the ethical principles set forth in the Declaration of Helsinki. Genetic analysis Genes associated to mendelian susceptibility to mycobacterial disease ( IFNGR1, IFNGR2, IL12RB1, IL12B, IRF8, ISG15, STAT1, RORC and TYK2 ) were analyzed by using a Next-generation sequencing (NGS) approach, using an AmpliSeq strategy for the library preparation that was subsequently sequenced in the Ion Torrent PGM platform- Identified variant in the STAT1 gene was validated by using Sanger sequencing Lung Section Staining A lung fragment (1 cm) was formalin-fixed (10%), paraffin-embedded, sectioned (3–8 μm) and stained with hematoxylin-eosin, Grocott, PAS-Diastase, and Masson’s trichrome. Immunohistochemistry used Roche Diagnostics antibodies: CD3 (2GV6), CD4 (SP35), CD8 (SP57), CD20 (L26), CD68 (KP-1), Citomegalovirus (8B1.2, 1G5.2, 2D4.2), and Epstein Barr Virus (CS1-4). Intracellular staining for STAT1 and pSTAT1 Quantification was performed as previously described (25). Briefly, whole blood was stimulated (15 min, 37⁰C) with IFNγ (400 UI/mL) or IFNα (100ng/mL) with or without ruxolitinib (100, 500 or 1000 nM). After erythrocytes lysis and iced-cold methanol permeabilization cells were stained with human monoclonal antibodies against CD14 (FITC; clone M5E2, Becton Dickinson, BD), CD3 (APC-H7; clone SK7, BD), CD4 (BV711; clone SK3, BioLegend), CD8 (PE-Cy7;clone SK1, BioLegend), STAT1 (Alexa Fluor 647; clone 1/STAT1, BD) and pSTAT1 (pTyr701-PerCP-Cy5.5; clone 4A, BD). Data were collected using the BD LSR Fortessa™ and analysed with the FlowJo software package (Becton Dickinson). Dephosphorylation assay Whole blood samples were incubated with anti-human CD14-FITC (FITC; clone M5E2, Becton Dickinson, BD) and then stimulated with IFNγ for 15 min at 37⁰C. At that point, ruxolitinib 1000nM was added and samples were incubated for additional 15, 30, 60, 90 or 120 min before fixation and staining as previously described (21). Gene expression analysis Transcription levels of STAT1-dependent genes were evaluated as previously described (25). Briefly, peripheral blood mononuclear cells (PBMCs) from the STAT1 GOF patient (P2) and a healthy donor were stimulated with IFNγ (400 UI/mL) or IFNα (100ng/ml) with or without ruxolitinib (100, 500 or 1000 nM) for 4 h at 37⁰C. An unstimulated sample was included as a baseline reference. STAT1 mRNA levels were evaluated after normalization to beta actin as an internal control. Western blot STAT1 and pSTAT1 protein levels were quantified as described (25). PBMCs from P2 and a healthy donor were stimulated with IFNα (100 ng/mL) ± ruxolitinib (1 Μm; 30 min, 37°C). Proteins underwent sodium dodecyl sulfate-10% polyacrylamide gel electrophoresis, transfer to PVDF membranes and overnight inclubation (4°C) with STAT1(Cell Signaling 9172), pSTAT1 (Py701; Cell Signaling 9167) or β-actin (Cell Signaling 4967)antibodies, . Detection was performed using horseradish peroxidase-conjugated secondary antibody (1 hour, room temperature) and chemiluminescence detection . Type I Interferon signature To evaluate the type I IFN signature, whole blood specimens were collected into Blood RNA Tempus™ (Thermofisher) tubes following manufactures’ instructions. Quantification of a subset of IFN-response genes was performed using the nCounter Elements Technology System (nanoString), including 28 genes representative of type I IFN response (28-IRG) (26) and 2 additional genes (CXCL9 and STAT1) relevant to the IFN response though not exclusively to type I response. Z-score calculation for each gene was conducted using formula: Z-score = (counts of gene A - average count of gene A in healthy controls) / Standard Deviation of gene A in healthy controls. A Z-score exceeding 1.73 for the 28-IRG set and 1.96 for the 6-IRG ( IFI 27, IFI44L, IFIT1, ISG15, RSAD2, SIGLEC1 ) was defined as indicative of an upregulation of type-I IFN-response genes. Cytokines analysis Serum cytokines (IFNα, IFNγ, IL-1Ra, IL-6, IL-8, IL-7, IL-9, IL-10, IL-12p70, IL-17A, IL-18, IL-23, IP-10, TNFα and CXCL5) were quantified with Procarta-Pex TM panels, (Invitrogen) and Bio-Plex 200 System (Bio-Rad). Clinical assessment pre and during JAKi therapy using the Immune Deficiency and Dysregulation Activity (IDDA) Score This score was designed as a physician-reported outcome measure tool and is used to assess the severity of the involvement of 12 organ systems in immune dysregulation and two other clinical features (failure to thrive and severe infections). The proportion of hospitalization days, need for supportive therapies and care are included. Furthermore, “any other organ or immune dysfunction” and “any relevant chronic or recurring infestation or infection” are added to the score as previously described (27). Data analysis Flow cytometry data were analyzed in raw values of geometric mean of fluorescence intensity (gMFI). Graphs and statistics (Shapiro-Wilk, Wilcoxon, Kruskal-Wallis tests; significance p<0.05) were performed using the Prism software (version 8, GraphPad software) and IMB SPSS Statistics 26.

Clinical evaluation, genetic analysis and diagnosis A five-year-old girl (P1) with DS presented with a two- year history of recurrent bacterial infections in the upper respiratory tract, oral (Figure 1A) and vaginal Candida albicans infections, lymphadenopathies, progressive interstitial pneumonitis with bronchiectasis, and secondary pulmonary hypertension. She required antibiotic and antifungal prophylaxis (including sulfamethoxazole and trimethoprim (SMX-TMP), and fluconazole), intermittent nebulized and systemic steroid therapy, 24-hour oxygen supplementation, and pulmonary antihypertensive therapy with, sildenafil and iloprost (Table 1). Blood count and basic immunological workup revealed reduced memory B cells with normal immunoglobulin levels for age (supplementary Table 1). Histopathology showed bronchiolar submucosal fibrosis and alveolar septal widening, increased alveolar macrophages (CD68+) and T cells (CD3+; balanced CD4+/CD8+ ratio) but scarce B cells (CD20+). No vasculitis or thrombosis was detected, and screening for fungal, CMV and other microorganisms was negative (Figure 1B). NGS analysis identified the heterozygous c.976C>T transition in the STAT1 gene that leads to the amino acid exchange p.P326S in the DNA-binding domain of the protein (Figure 2A). Intrafamilial segregation analysis revealed that this variant was inherited from the patient’s mother (P2). At that time, she was 42-year-old and referred a lifelong CMC and esophageal candidiasis and stenosis during adolescence and adulthood. In silico tools classified this variant as deleterious (including Sift: 0.05; Polyphen 0.991) (Supplmentary Table 2). Functional assays using peripheral blood from P2 showed increased levels of STAT1 in monocytes and increased pSTAT1 upon IFNγ stimulation, with normal dephosphorylation kinetics (Figure 2B-C) . These findings confirmed P326S as a pathogenic STAT1 GOF variant. Ex vivo effects of ruxolitinib and long-term clinical benefits in STAT1 GOF syndrome We evaluated the ex vivo effect of ruxolitinib on IFNγ-induced pSTAT1 levels in P2’s monocytes. At 0.1-0.5 μM, ruxolitinib normalized pSTAT1 to control levels (Figure 2D) with a similar effect on relative STAT1 expression (Figure 2E). Similarly, PBMCs from P2 stimulated with IFNα displayed increased pSTAT1 levels, which were inhibited by 1 μM ruxolitinib (Figure 2F). Based on these findings, and prior positive clinical reports (28), ruxolitinib was initiated in P1 (age 6.5 years) at 3 mg/12h (0.4mg/kg/day; March 2018 ), increased to 5mg/12h (0.66mg/kg/day; May 2018) and to her current dose of 5mg/8h (0.66mg/kg/day; May 2024). P2 (age 43 years) with milder symptoms, started ruxolitinib at 5 mg/12h (February 2021), later increased to 7.5mg/12h- a regimen she continues to date. P1´s clinical response to ruxolitinib was remarkable and sustained (currently 7 years of therapy). CMC resolved (4-6 weeks), allowing withdrawal of antibiotic and antifungal prophylaxis. Steroids and oxygen supplementation were successfully weaned within 6 and 12 months, respectively. Pulmonary hypertension improved, enabling a 66% reduction of phosphodiesterase 5 (PDE5) inhibitors within 36 months (Table 1). Overall pulmonary function stabilized and partially improved (Figure 1C-D). She did not require any hospital admissions after initiating ruxolitinib, in contrast to the 30 non-elective hospitalizations recorded between diagnosis of STAT1 GOF in October 2016 and start of JAKi therapy in March 2018. Her exercise tolerance assessed by the 6- minute walk test, also significantly improved (Figure 1E) (29). Despite clinical benefits, progressive lymphopenia affecting T, B, and NK cells was observed (Supplementary Table 1). The IDDA Score decreased from 40 pre- ruxolitinib treatment to 8.1 at 40-months (27). Nutritional support could be discontinued after 20 months, and she continued to thrive along the 3 rd percentile (Figure 1F). Ruxolitinib modulates pSTAT1 activation in P1 but fails to normalize IFNAR and total STAT1 levels As a unique and challenging case combining two complex diseases associated to IFN signaling dysregulation (DS and STAT1 GOF), and based on the fact that individuals with DS exhibit elevated IFN receptor levels compared to healthy controls, we hypothesized a synergistic IFN hyperactivity in P1 exceeding that seen in isolated DS or STAT1 GOF cases. Baseline experimental tests could not be performed in P1 before ruxolitinib initiation. However, IFN receptor subunit analysis was performed 60 months post treatment. Despite clinical improvement (Table 1 and Figure 1), P1 exhibited persistently elevated IFNAR2 levels comparable to those of DS individuals (n = 8, DS1–DS6 and DS8–DS9; clinical characteristics in Supplementary Table 3), whereas the remaining subunits were similar to those of healthy controls and P2 who had been receiving ruxolitinib for 30 months (Supplementary Figure 2). Conditioned by sample availability, we analyzed P1’s IFN response at 18, 24, 36, 60, and 70 months post-treatment, comparing STAT1 and pSTAT1 levels to healthy controls, DS individuals, naïve STAT1 GOF patients (GOF1-4, P2 pre-treatment), and STAT1 GOF patients on ruxolitinib (P2 at 7 months, GOF5 at 60 months) (Figure 3, Supplementary Tables 3-4). Although ruxolitinib reduced STAT1 levels in P1 compared to naïve STAT1 GOF patients, they remained elevated relative to healthy controls (Figure 3A, Supplementary Figure 3A). However, pSTAT1 levels post-IFN stimulation were notably reduced in P1 (Figure 3B, Supplementary Figure 4). A similar pattern was observed in P2 and GOF5 during ruxolitinib: total STAT1 remained high, but pSTAT1 normalized upon IFNα and IFNγ stimulations (Figure 3, Supplementary Figure 3D, 5). Altogether, these findings indicate that while ruxolitinib effectively modulates pSTAT1 activation in an individual with concurrent DS and STAT1 GOF, it does not fully normalize IFNAR or total STAT1 levels. Persistent STAT1 elevation in P1, P2 and GOF5 despite ruxolitinib may suggest a broader limitation of JAKi in fully restoring STAT1 homeostasis. Limited efficacy of ruxolitinib in normalizing the atypical IFN signature in P1 We assessed the IFN signature in P1´s peripheral blood, comparing it to naïve individuals (DS, P2 before treatment) and STAT1 GOF patients on ruxolitinib (P2, GOF5; Table 2). At 36 months post treatment, P1 displayed a persistently positive IFN signature, similar to naïve P2 and DS-9. Specific STAT1 target genes, such as CXCL9 and CXCL10 were elevated in naïve P2, in 50 % of DS individuals, and in both P1 and GOF5. While ruxolitinib normalized most genes in P2 and GOF5, P1 exhibited elevated expression in 22 of 32 genes, including CXCL9, CXCL10, ISG15 and USP18 . Persistent inflammatory cytokine profile in P1 despite ruxolitinib therapy. To further evaluate P1´s inflammatory status, we analyzed cytokine levels in serum samples collected at 36- and 60-months post-treatment (Figure 4). DS individuals also exhibited elevated IL-6 levels, a finding absent in STAT1 GOF patients. Notably, despite ruxolitinib treatment, P1- unlike P2 and GOF5- maintained persistently increased TFN-α, IL-1Ra and IL-6 levels, suggesting an unresolved pro-inflammatory state that JAKi failed to fully control in this patient with concurrent DS and STAT1 GOF mutation.

Down syndrome (DS) is associated with an increased incidence of recurrent infections of respiratory tract (5, 30, 31). Additionally, pulmonary hypertension is also frequently observed in DS, often secondary to congenital heart disease (32). Here, we describe a 5 years-old patient with DS (P1) suffering from recurrent pneumonia, chronic mucocutaneous candidiasis (CMC) and secondary pulmonary hypertension. Validation of a novel STAT1 variant and response to ruxolitinib Since CMC is uncommon in DS and primarily linked to pathogenic variants in STAT1, STAT3, AIRE or IL17 genes (33), we first performed genetic analysis in P1 that revealed the novel heterozygous P326S variant in STAT1, which was inherited from her mother (P2). In silico prediction tools and functional assays of the variant suggested a gain-of-function (GOF) behavior, with elevated STAT1 and phosphorylated STAT1 (pSTAT1) levels upon IFNγ stimulation (34). While early studies attributed GOF variants in STAT1 to impaired dephosphorylation (20, 35), recent evidence suggests increased total STAT1 protein as an alternative mechanism (21). Ex-vivo experiments demonstrated that ruxolitinib effectively modulated IFN responses in P2’s cells at clinically relevant plasma concentrations (0.1–0.5 μM), achievable with oral 5–10 mg doses every 12 hours (20, 21, 36). Clinical response to ruxolitinib Ruxolitinib therapy (0.4 mg/kg/day) resolved fungal infections in P1 within three months. Remarkably, her lung pathology also improved, with a dramatic reduction in the frequency of pneumonias and associated complications. Before treatment, P1 had approximately 30 non-elective hospitalizations in two years (mostly due to respiratory infections). After seven years on ruxolitinib no further non-elective hospital admissions were recorded, indicating a profound clinical benefit. P2 showed similar improvement with ruxolitinib treatment, with CMC resolving within four months on 0.3 mg/kg/day. Both patients tolerated the JAKi treatment, with no significant adverse effects, consistent with prior data on JAKi in patients harboring in STAT1 GOF variants (22-24, 28). Notably, this is the first report documented case of ruxolitinib treatment in a patient with concurrent DS and STAT1 GOF. Interferon Signaling and Gene Expression Given the hyperactive IFN signaling in DS and STAT1 GOF, we hypothesized that their coexistence in a unique patient would exacerbate immune dysregulation when compared to isolated cases of each condition. We therefore included individuals with DS with infectious and/or autoimmune manifestations, untreated patients with STAT1 GOF variants, and a patient with a STAT1 GOF variant receiving ruxolitinib (GOF5). In DS, IFN hyperactivity is believed to be linked to the extra copies of IFN receptor genes, located in chromosome 21, increasing IFNAR/IFNAR2 expression (6, 7). However, P1, uniquely exhibited persistently elevated IFNAR2 but unchanged IFNAR1 expression, differing from DS individuals. IFNAR2 overexpression alone has been suggested as sufficient to enhance pSTAT1 levels following IFN-I stimulation (37). Despite ruxolitinib therapy, IFNAR2 levels in P1 remained elevated, consistent with findings from a previously reported DS case (13). The IFNAR2 overexpression in P1 compared to her mother may partly explain the differences in their clinical manifestations. To explore whether this IFNAR overexpression together with effects of the GOF mutation in STAT1 could lead to an extra-amplification of IFN response in P1, we interrogated the IFN-JAK-STAT pathway comparing to DS and STAT1 GOF patients. As expected, DS and treatment-naïve STAT1 GOF patients had elevated basal STAT1 and increased pSTAT1 levels upon IFNα and IFNγ .stimulations (6, 20, 21). While ruxolitinib normalized pSTAT1 responses in P1, P2, and GOF5, total STAT1 levels remained high. While IFN-I signaling normalization in P2 can be attributed to ruxolitinib, the case of P1 appears to be more complex. Prior studies suggest that individuals with DS exhibit baseline IFN-I pathway activation and elevated pSTAT1 levels, leading to a refractory state where cells become unresponsive to subsequent IFN-I stimulation (37). In our study, DS cells displayed normal basal pSTAT1 levels with elevations occurring only after IFNα stimulation. We assessed type I IFN signature scores, commonly used in the diagnostic evaluation, monitoring of disease activity, and assessment of treatment responses in patients suspected of having type I interferonopathies (26). Previous studies have shown that JAK inhibition reduces ISG expression in both DS and STAT1 GOF patients (13, 38). Accordingly, IFN signature was overall normal in P2 and GOF5 under ruxolitinib. However, complete normalization could not be confirmed due to the lack of pre-treatment samples for comparison and persistence of altered expression in certain IFN-related genes, such as CXCL10, CXCL9, and STAT1 . P1 exhibited elevated expression of 22 out of 32 analyzed ISGs, suggesting sustained IFN dysregulation. Notably, USP18, a negative IFNAR regulator was overexpressed, potentially reducing IFNα responsiveness (4, 37). However, this did not correlate with increased viral susceptibility in P1. A limitation inherent to IFN signature assessment is the potential influence of concurrent therapies, such as corticosteroids, which can suppress interferon-stimulated gene expression and thus may lead to false-negative results. Additionally, active infections at the time of sampling may transiently elevate the IFN signature, generating false-positive findings that complicate the accurate interpretation of disease activity. Despite these constraints, IFN signature assessment remains a valuable clinical tool for providing a general overview of the patient’s interferon status. Complex Immune Dysregulation and Therapeutic Considerations IFN hyperactivity has been linked to a proinflammatory profile, characterized by elevated IL-6 and TNFα in both DS (13, 39) and STAT1 GOF (40). As expected, P1 exhibited increased serum IL6 and TNFα levels. Since IL-6 can activate pSTAT1 independently of IFN signaling, IL-6 inhibitors may be a promising adjunct therapy (41, 42). A potential interplay between pSTAT1-mediated pathways and TNFα signaling has been described; however, further studies are required to determine whether direct TNFα inhibition could modulate STAT1 activation or vice versa (43). P1 also exhibited increased IL-10 and IL-1Ra, suggesting a compensatory anti-inflammatory response to STAT1 hyperactivation, an aspect not yet studied in the context of STAT1 GOF (44). Similarly, Malle et al . identified a subset of DS individuals with elevated IL-10, though its biological impact remains unclear (39). These findings underscore the complexity of immune dysregulation in this dual pathology and highlight the need for therapeutic strategies extend beyond JAKi.

of Ruxolitinib and Need for Additional Therapeutic Strategies While ruxolitinib effectively reduced clinical symptoms and pSTAT1 activation, its inability to fully normalize the IFN signature or resolve inflammation suggests the need for additional therapeutic strategies. Longitudinal assessments of P1 revealed progressive lymphopenia affecting all subsets, a known but poorly understood feature of STAT1 GOF (19, 45). Chronic inflammation, linked to immunosenescence (46), may contribute to long-term immune dysfunction and neurodegeneration (47) potentially accelerating Alzheimer-like disease, which is well described in DS (48). As in previous studies, biomarkers such as pSTAT1 and total STAT1 levels, IP-10 or IFN signature scores did not always correlate with clinical improvement, indicating the need for more reliable biomarkers to monitor disease progression and treatment response in the DS and STAT1 GOF settings (38, 45, 49). Despite the promising clinical outcomes, certain limitations of the study must be acknowledged. The lack of measurements plasma ruxolitinib level measurements limits insights into its pharmacokinetics and correlation with clinical responses. Additionally, the absence of baseline molecular data from P1 prior to treatment prevents a full evaluation of the effect of JAK inhibition in this particular patient.

Comprehensive immunologic evaluations are crucial in DS individuals with immune dysregulation. The coexistence of DS and STAT1 GOF amplifies IFN signaling abnormalities, further complicating disease management. While ruxolitinib effectively reduced pSTAT1 activation and prevented CMC and recurrent respiratory infections, it failed to fully normalize inflammation, indicating the need for additional therapies. Future studies should explore alternative treatments, refine biomarker-based monitoring, and optimize dosing strategies to improve patient outcomes in IFN-driven disorders. Table 1. Clinical course and treatment response | STAT1 GOF diagnosis | Start on ruxolitinib | 24-m ruxolitinib treatment | 36-m ruxolitinib treatment | 48-m ruxolitinib treatment | 60-m ruxolitinib treatment | | | SABA | On demand | On demand | On demand | On demand | On demand | On demand | | LABA/IC (mcg/day)* | 100/500 | 100/500 | |||| | LTRA | 4 mg | 4 mg | |||| | Short Acting anti-cholinergic | On demand | On demand | On demand | On demand | On demand | On demand | | Long Acting Anti-cholinergic | 5mcg/24 hours | 5mcg/24 hours | 5mcg/24 hours | 5mcg/24 hours | || | Antibiotic (prophylaxis) | SMX/TMP 100/20mg/day | SMX/TMP 100/20mg/day | SMX/TMP 200/40mg/day | SMX/TMP 200/40mg/day | SMX/TMP 200/40mg/day | SMX/TMP 200/40mg/day | | Immunoglobulin | 7,5gr/4-weeks i.v. $ | 7,5gr/4-weeks i.v. $ | 5gr/3-weeks s.c.” | 5gr/3-weeks s.c.” | 5gr/3-weeks s.c. ” | 5gr/3-weeks s.c.” | | Anti-fungal (prophylaxis) | Fluconazole 6mg/kg/day | Fluconazole 6mg/kg/day | Topical Nystatin | Topical Nystatin | Topical Nystatin | Topical Nystatin | | Ruxolitinib | 3mg/12 hours | 5 mg/12 hours | 5 mg/12 hours | 5 mg/12 hours | 5 mg/12 hours | | | Oxygen (hours/per day) | 24 | 24 | 0 | 0 | 0 | 0 | | Oxygen L/per min | 0,75-2 | 1-3 | 0 | 0 | 0 | 0 | | Gastro-esophagic reflex | PBI + | PBI + | Surgical treatment | ||| | PDE5 inhibitors a | 1mg/kg/8hours & | 1mg/kg/8hours & | 1mg/kg/8hours & | 1mg/kg/day & | 1mg/kg/day % | 1mg/kg/day % | | Iloprost | 2,5ng (x5 /day) | 2,5ng (x5 /day) | SABA: Short-Acting Beta Agonist; LABA: Long-Acting Beta-Agonist; IC: Inhaled Corticosteroid; LTRA: Leukotriene Receptor Antagonist; SMX/TMP: Sulfamethoxazole and Trimethoprim *salmeterol/fluticasone; + Proton Pump Inhibitors; “Subcutaneous immunoglobulin; $ Intravenous immunoglobulins; PDE5 inhibitors a aphosphodiesterase type 5 inhibitor, % Tadalafil; & Sildenafil , Table 2. Individual Z-scores from Interferon Signature analysis. | GENES | PATIENTS | ||||||||||| | W/O RUXOLITINIB TREATMENT | W/ RUXOLITINIB TREATMENT | ||||||||||| | DS-1 | DS-2 | DS-3 | DS-5 | DS-6 | DS-8 | DS-9 | DS-11 | P2 | P2 (1 m) | GOF5 (36 m) | P1 (36 m) | | | CXCL10 | 3,16 | 3,36 | 1,81 | 10,11 | 0,02 | 0,24 | 0,84 | 2,38 | 6,62 | 0,54 | 6,23 | 2,15 | | DDX60 | 0,17 | 0,04 | -0,41 | 0,66 | -0,12 | 0,94 | 6,21 | 1,09 | 2,87 | 0,52 | 0,4 | 3,85 | | EPSTI1 | 2,00 | 0,35 | 0,32 | 5,00 | 1,11 | 3,02 | 8,40 | 2,23 | 3,04 | 0,69 | 3,48 | 2,23 | | GBP1 | 0,47 | 0,46 | -0,27 | 4,15 | 0,17 | 4,32 | 1,30 | 1,22 | 6,92 | 2,06 | 8,77 | 2,30 | | HERC5 | -0,08 | -0,58 | -0,50 | 0,61 | -0,68 | 0,22 | 3,88 | 0,91 | 2,56 | 0,43 | -0,36 | 2,36 | | HERC6 | 0,91 | 0,42 | -0,30 | 0,14 | -0,32 | 0,72 | 5,49 | 2,18 | 1,74 | 0,37 | -0,68 | 2,73 | | IFI27 | 2,92 | 0,06 | 1,16 | 7,85 | 0,06 | 1,65 | 75,10 | 1,68 | 0,31 | -0,32 | 0,1 | 2,97 | | IFI44 | 0,44 | -0,12 | 0,23 | 1,54 | -0,14 | 0,73 | 6,74 | 1,25 | 3,12 | 0,75 | -0,1 | 3,43 | | IFI44L | 0,39 | -0,38 | -0,15 | 0,96 | -0,42 | 0,10 | 6,77 | 0,75 | 2,35 | 0,13 | -0,43 | 3,27 | | IFI6 | -0,16 | -0,32 | -0,25 | 1,37 | -0,71 | -0,08 | 2,34 | 0,18 | 2,47 | 0,18 | -0,74 | 1,63 | | IFIT1 | -0,04 | -0,35 | -0,11 | 1,46 | -0,50 | 0,34 | 5,39 | 0,54 | 3,01 | 0,63 | -0,35 | 1,80 | | IFIT2 | -0,28 | 0,02 | -1,00 | 2,03 | -0,83 | 2,40 | 9,64 | -0,26 | 4,58 | 1,56 | 1,16 | 2,87 | | IFIT3 | -0,37 | -0,36 | -0,56 | 1,30 | -0,86 | 0,59 | 3,84 | 0,15 | 3,32 | 0,66 | 0,34 | 1,67 | | IFIT5 | 0,53 | -0,2 | -0,44 | 2,14 | -0,64 | 1,00 | 6,06 | 1,55 | 5,11 | 2,20 | 1,43 | 4,12 | | ISG15 | -0,11 | -0,29 | -0,41 | 1,08 | -0,39 | -0,30 | 5,01 | 0,61 | 1,67 | -0,22 | -0,17 | 1,42 | | LAMP3 | 1,52 | 0,69 | -0,15 | -0,29 | -0,05 | 0,60 | 3,48 | 1,27 | 3,62 | 1,07 | 1,23 | 1,31 | | LY6E | 0,94 | -0,27 | 0,20 | 2,24 | -0,18 | -0,06 | 10,25 | 1,40 | 1,15 | -0,26 | -0,33 | 2,55 | | MX1 | 1,73 | 0 | 1,10 | 3,06 | 0,23 | 1,12 | 9,58 | 2,54 | 2,10 | 0,2 | -0,89 | 5,60 | | OAS1 | 0,54 | 0,24 | 0,05 | 3,50 | -0,81 | -0,69 | 8,79 | 1,05 | 3,29 | 0,39 | 0,85 | 4,71 | | OAS2 | 1,77 | 1,15 | -0,21 | 2,04 | -0,52 | -0,14 | 12,57 | 2,85 | 5,08 | 1,22 | 0,7 | 6,75 | | OAS3 | 0,55 | 0,31 | -0,04 | 2,47 | -0,20 | -0,01 | 7,97 | 1,08 | 3,05 | 0,12 | 0,24 | 4,52 | | OASL | -0,12 | -0,4 | -0,87 | 0,10 | -1,02 | -0,95 | 3,06 | 0,86 | 3,72 | 1,38 | -0,11 | 1,24 | | RSAD2 | 0,15 | -0,13 | -0,33 | 1,24 | -0,38 | 0,22 | 6,94 | 0,57 | 2,63 | 0,18 | -0,31 | 2,24 | | RTP4 | -0,32 | 0 | -0,35 | 0,28 | -1,10 | 0,55 | 2,74 | 0,26 | 0,90 | -0,83 | 0,92 | -0,33 | | SIGLEC1 | 0,84 | 0 | -0,05 | 2,49 | -0,14 | -0,22 | 13,47 | 1,11 | 1,43 | -0,18 | -0,6 | 5,98 | | SOCS1 | 0,23 | 0,37 | -0,51 | -0,52 | -0,86 | 0,65 | 0,38 | -1,39 | 1,36 | -1,92 | -1,06 | -0,56 | | SPATS2L | -0,24 | -0,37 | 3,30 | 0,58 | -0,68 | -0,61 | 3,20 | 2,07 | -0,05 | -1,31 | -1,22 | 2,05 | | USP18 | 1,97 | -0,18 | 0,28 | 1,14 | 0,26 | 0,12 | 7,61 | 1,84 | 1,41 | -0,04 | -0,63 | 2,55 | | CXCL9 | 4,44 | 1,25 | 1,15 | 17,00 | 2,35 | 1,12 | 1,23 | 2,51 | 3,36 | 0,39 | 10,21 | 2,48 | | STAT1 | -0,01 | -0,75 | -0,85 | 2,46 | -0,21 | 2,40 | 0,88 | -0,01 | 3,51 | 0,57 | 4,86 | 0,93 | | 28IRG* | 0,46 | -0,06 | -0,18 | 1,42 | -0,39 | 0,29 | 6,13 | 1,10 | 2,75 | 0,28 | -0,48 | 2,46 | | 6IRG* | 0,27 | -0,21 | -0,13 | 1,35 | -0,39 | 0,16 | 6,85 | 0,68 | 2,01 | -0,03 | -0,53 | 2,60 | | *Z-score exceeding 1.73 for the 28-IRG set and 1.96 for the 6-IRG indicates an upregulation of type-I IFN-response genes. | Figure 1. Clinical manifestations of P1. (A) Oral candidiasis at the age of 5 years old (2016). (B) Immuno-histological staining of lung tissue. Masson staining was performed for collagen fibers detection and differentiation between connective and lung tissues. Immune cell infiltration in lung tissue was assessed by immunochemistry targeting CD68+ alveolar macrophages, CD3+ cells, CD4+ T cells, CD8+ T cells and CD20+ B cells. (C) Pulmonary function over time. P1’s pulmonary function was measured through spirometry for 60 months after start of treatment with ruxolitinib. Results are shown as z-score based on forced vital capacity (FVC) and forced expiratory volume in 1s (FEV1). (D) Chest CT-scans. P1 presented lung involvement including bronchiectasis and ground-glass opacification due to continued inflammation and infection. P1’s lung structure was analyzed by chest CT-scans over time since start of treatment with ruxolitinib. (E) 6-minute walk test. Physical condition was measured through 6 minute walk tests for 60 months after start of treatment with ruxolitinib. (F) P1’s weight and height using 3rd-97th centile ranges using Growth Charts for Children with Down syndrome (50). Figure 2. P326S STAT1 variant identification and validation and the ex vivo effect of ruxolitinib. A) Schematic representation of the STAT1 protein domains including the mutation. B) Geometric mean fluorescence intensity (gMFI) of STAT1 in resting CD3 +, CD4 + and CD8 + T cells and CD14 + monocytes of healthy controls (white bars) and P2 (blue bars). C) Levels of pSTAT1 after IFNγ stimulation for 15 min and 15-120 min after reaching peak levels in the presence of ruxolitinib (1 μM) using monocytes of P2 (blue) and heathy controls (white). D) Dose-related effect of ruxolitinib (0.1, 0.5 and 1 μM) on pSTAT1 levels of monocytes from P2 (blue) healthy controls (white) after stimulation with IFNγ. Representative histograms of the gMFI obtained for STAT1 (APC) and pSTAT1 (PercP Cy5.5) are shown at right. E) Relative expression of STAT1 after 4h-stimulation of PBMCs with IFNα in presence of different concentrations of ruxolitinib (0.1 μM, 0.5 μM or 1 μM). Relative expression was calculated after normalization to unstimulated d sample of healthy control using the comparative 2- ΔΔct method. F) Immunoblot analysis of lysates of PBMCs from P2 and the healthy control. Cells were left unstimulated or stimulated with IFNα with or without presence of 1 μM ruxolitinib. Figure 3. STAT1 and pSTAT1 levels measured by flow cytometry. A) Geometric mean fluorescence intensity (gMFI) of STAT1 in resting CD3 +, CD4 + and CD8 + T cells and CD14 + monocytes of healthy controls (white circles), DS (grey squares), STAT1 GOF (black or blue squares) and P1 (red triangle). Standard or dotted background in bars indicate the naïve or under ruxolitinib status of individuals. Dotted line represents normalized healthy controls values. B) Levels of pSTAT1 in unstimulated (NS) or IFNγ/IFNα stimulated monocytes of healthy controls (white circles), DS (grey squares), STAT1 GOF (black or blue squares) and P1 (red triangle). Each grey and black square represent an individual DS or STAT1 GOF while red triangles represent different time-points of P1 [18 months (September 2019), 24 months (March 2020), 36 (March 2021), 60 (March 2023), 70 months (January 2024)]. Black lines associate the patients with their respective healthy controls. Median and interquartile ranges are represented. Dotted line represents normalized healthy controls values. Figure 4. Serum cytokine levels. Quantification of cytokines (pg/ml) found in healthy controls (white circles), DS (grey squares), STAT1 GOF (black or blue squares) and P1 (red triangle). Median and interquartile ranges are represented. Two time points after ruxolitinib initiation is included: 30 and 60 months post- ruxolitinib initiation. *p-values lower than 0.05 were considered statistically significant. Supplementary Figures Supplementary Figure 1. JAK/STAT signaling pathway and its modulation in STAT1 GOF and DS individuals and under ruxolitinib treatment. Type I IFN JAK/STAT signaling pathway: IFNα binds IFNAR, leading to STAT1 and STAT2 phosphorylation (p) by JAK1 and TYK2 respectively. Homodimers (pSTAT1/pSTAT1) and ISGF3 complexes (pSTAT1/pSTAT2/IRF9) translocate to nucleus to activate GAS and ISRE sites, inducing IFN-stimulated genes (ISGs) such as STAT1, CXCL10 or SOCS1. Finally, ISGs expression leads to the release of proinflammatory and anti-viral cytokines. This schematic representation also shows how key factors from JAK/STAT signaling pathway are modulated in STAT1 GOF, DS and STAT1 GOF+DS phenotypes, which are considered interferonopathies, compared to a healthy individual. Elements displaying positive red marks are up-regulated, while those displaying green negative marks are partially down-regulated after ruxolitinib’s JAK inhibition. In STAT1 GOF and DS individuals, JAK/STAT signaling pathway is altered due to the increased expression of IFNAR2, STAT1, pSTAT1, IGSs and proinflammatory cytokines. In the case of P1, we observed a synergistic effect where both DS and STAT1 GOF phenotypes contribute to an even bigger dysregulation of JAK/STAT signaling pathway. When we tried to modulate IFN response through JAK inhibition (ruxolitinib) we were able to normalize the expression in the majority of up-regulated elements of DS and STAT1 GOF individuals. However, despite ruxolitinib treatment P1 continued displaying a hyperactivated JAK/STAT signaling pathway and a proinflammatory profile. Supplementary Figure 2. IFN-R expression in monocytes. IFN-R expression was analyzed in monocytes from individuals with Down syndrome (DS; gray), patient 1 (P1; red; 60 months of ruxolitinib therapy), and patient 2 (P2; blue; 30 months of ruxolitinib therapy). Levels of IFNα and IFNγ receptor subunits were assessed by flow cytometry using peripheral blood mononuclear cells (PBMCs) from DS individuals, patients with STAT1 GOF mutations, and age-matched healthy controls. PBMCs (10⁶) were incubated for 30 minutes in the dark at 4°C with the LIVE/DEAD™ Fixable Aqua Dead Cell Stain Kit (Invitrogen) and washed twice with serum-free PBS. Cells were stained with the following antibody mix: CD14 (Brilliant Violet 750, BioLegend), IFNγR1 (FITC, Miltenyi Biotec), IFNγR2 (PE, BioLegend), IFNαR1 (Alexa Fluor 405, Miltenyi Biotec), and IFNαR2 (APC, R&D Systems). Data were collected on the LSRFortessa™ flow cytometer (Becton Dickinson) and analyzed using FlowJo software (v. 10.7.0, Treestar, Ashland, OR, USA). The geometric mean fluorescence intensity (gMFI) is shown. Both raw (A) and normalized (B) data are presented. The dotted black line represents the values of healthy controls. Representative histograms of gMFI for IFN receptor subunits IFN-αR1 and IFN-αR2 are displayed for DS (C; gray) and P1 (D; red). *P-values < 0.05 were considered statistically significant. Supplementary Figure 3. Total STAT1 levels in T cells and CD14 + monocytes from Patient 1 (P1), DS individuals and STAT1 GOF. Geometric mean fluorescence intensity (gMFI) of STAT1 in resting CD3 +, CD4 + and CD8 + T cells and CD14 + monocytes of P1 (A; red triangle), DS (B; grey squares), STAT1 GOF (C; black or blue squares) and their respective healthy control (white circles). Supplementary Figure 4. Phosphorylated STAT1 levels in T cells and CD14 + monocytes after IFN stimulation. 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