Chronic Pulmonary Aspergillosis: Genomic Variant Analysis and Protein Dysfunction Susceptibility in a Brazilian Cohort

Chronic Pulmonary Aspergillosis: Genomic Variant Analysis and Protein Dysfunction Susceptibility in a Brazilian Cohort | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Chronic Pulmonary Aspergillosis: Genomic Variant Analysis and Protein Dysfunction Susceptibility in a Brazilian Cohort Rafaela da Silva Mendes, Beatriz Martins Wolff, Mariana Ribeiro Costa Siemann, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6473313/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Chronic pulmonary aspergillosis (CPA) is a debilitating condition often affecting immunocompetent patients with underlying structural lung diseases, particularly pulmonary tuberculosis. This study investigates single nucleotide variants (SNVs) in immunogenetic-related genes among a Brazilian cohort with CPA. Twelve patients with confirmed CPA, based on ESCMID/ERS criteria, were sequenced using NGS technology. Variants were annotated, classified using ACMG guidelines, and analyzed for potential impact on protein interactions and immune pathways. A set of SNVs in CX3CR1, IL12B, IL4R, PTX3 , CCR5 and IFNG genes were classified as variants of uncertain significance (VUS), but protein–protein interaction analysis suggests a potential role in immune evasion and dysfunction. This is the first study to apply a custom multigenic panel for CPA susceptibility in a Brazilian cohort, contributing to future functional and clinical studies in fungal immunogenetics. Molecular Genetics CPA immune genes brazilian aspergillus Figures Figure 1 Figure 2 Introduction Chronic pulmonary aspergillosis (CPA) is a progressive and potentially fatal fungal infection primarily caused by Aspergillus spp ., an opportunistic fungus commonly found in the environment. Its clinical manifestation is influenced by both host immune status and the presence of pre-existing pulmonary sequelae( 1 – 3 ). Immunocompromised individuals—such as those undergoing solid organ or bone marrow transplantation—are particularly vulnerable to invasive aspergillosis( 4 ). However, CPA predominantly affects immunocompetent or non-neutropenic patients, especially those with chronic lung conditions such as tuberculosis sequelae( 5 , 6 ). CPA encompasses several clinical subtypes, including simple aspergilloma, chronic cavitary pulmonary aspergillosis, subacute invasive aspergillosis, Aspergillus nodules, and chronic fibrosing pulmonary aspergillosis. Diagnosis relies on a combination of radiological evidence, immunoprecipitation antibody titers, and clinical symptoms, which is especially critical in low-resource settings( 7 – 10 ). Despite treatment efforts, CPA is associated with significant morbidity and mortality, often progressing to pulmonary fibrosis and severely impacting quality of life( 11 , 12 ). Globally, an estimated 3 million individuals are affected by CPA annually, with Brazil reporting approximately 112,000–160,000 new cases per year and a 5-year mortality rate ranging from 38–85%( 13 ). Genetic predisposition may influence susceptibility to CPA. Single nucleotide polymorphisms (SNPs) are common in the general population and can result from evolutionary adaptation, spontaneous mutations, or environmental exposure( 14 , 15 ). While not all genetic mutations result in pathogenic protein alterations, certain SNPs may affect immune response pathways. Genome-wide association studies (GWAS) have identified variants in immune-related genes, such as PTX3, associated with impaired neutrophil function and increased susceptibility to fungal infections( 5 , 16 , 17 ). Given the limited literature on host–pathogen genetic interactions in fungal infections, this study aims to investigate genomic variants in Brazilian patients diagnosed with CPA. Using next-generation sequencing (NGS) and American College of Medical Genetics (ACMG) classification guidelines, we identified and evaluated genetic variants that may contribute to susceptibility to CPA. Materials and Methods Participants This study enrolled Brazilian patients receiving outpatient follow-up in the Infectious Diseases and Pulmonology departments at the Hospital das Clínicas, University of São Paulo (HC-FMUSP) during the period of 2023, with a confirmed diagnosis of chronic pulmonary aspergillosis (CPA). All patients with CPA had the following characteristics, in accordance with the ESCMID/ERS criteria( 18 ): ( 1 ) the computerized tomography scan of the chest findings suggestive of aspergillosis (one or more cavities with or without a fungal ball present or nodules); ( 2 ) microbiological evidence of Aspergillus infection [microscopy or culture from sputum, bronchoalveolar lavage (BAL) or, biopsy, histology, positive serum or BAL galactomannan] or serological evidence (serum immunodiffusion test and counterimmunoelectrophoresis); ( 3 ) All present for at least 3 months or at least a 1-month duration in SAIA; ( 4 ) Exclusion of alternative diagnoses, such as tuberculosis, malignancy, and other similar pathological conditions. A total of 12 patients (n = 12) were included, of whom 8 were male (66.7%) and 4 were female (33.3%). All patients presented post-tuberculosis pulmonary. The clinical subtypes observed in the cohort were: chronic cavitary pulmonary aspergillosis in 8 patients (66.7%), simple aspergilloma in 3 patients (25.0%), and chronic fibrosing pulmonary aspergillosis in 1 patient (8.3%). The exclusion criteria for the study were: immunosuppressive conditions (eg. HIV infection, malignancies, prolonged corticosteroid administration, diabetes mellitus, and cirrhosis) and confirmed genetic diseases. DNA Extraction Peripheral blood (4 mL) was collected in EDTA-containing tubes. All participants signed informed consent forms (CAAE: 76601023.1.0000.0068). DNA was extracted at the Cytogenomics Laboratory, Department of Pathology, Faculty of Medicine, University of São Paulo, using the QIAamp DNA Blood Mini Kit (Qiagen®, Hilden, Germany) , following the manufacturer’s protocol. A final volume of 30 µL was obtained for subsequent analyses, and DNA concentration and quality were measured using a Qubit fluorometer (Thermo Fisher Scientific®). Next-Generation Sequencing (NGS) Exome libraries were prepared using the Illumina® DNA Prep with Exome 2.0 Plus Enrichment kit , according to the manufacturer's instructions. Sequencing was performed using the NovaSeq 6000 System (Illumina®, 2025) . Raw data were generated in Variant Call Format (VCF) and annotated by comparison with the reference genome GRCh38/hg38 using bioinformatics tools. Variant Filtering and Classification A custom-designed virtual multigenic panel was developed including genes previously reported to be associated with susceptibility to fungal infections. The panel included: CCR5, CX3CR1, IFNG, IFNGR2, IL10, IL12A, IL12B, IL13, IL4, IL4R, CXCL8, CXCR1, CXCR2, MBL2, MIF, NOS3, PTX3 , and ARNT2 . VCF files from each participant were analyzed using the Franklin by Genoox® platform ( https://franklin.genoox.com ). Allele frequencies were obtained from the gnomAD v4.1.0 and ABraOM databases (Brazilian Online Archive of Mutations). Variants classified as single nucleotide variants (SNVs) were evaluated using the American College of Medical Genetics and Genomics (ACMG) guidelines, considering allele frequency, in silico prediction tools, and mutation type. The criteria PM2_SUPP and BP4 were applied, and most variants were categorized as variants of uncertain significance (VUS). Additional analyses included computational modeling of amino acid substitutions and chemical dissimilarity to assess potential protein dysfunction. Protein–protein interaction networks and immune pathway enrichment were evaluated for implicated genes. Results Variant Analysis and Classification Variant analysis was guided by the development of a virtual multigenic panel consisting of genes previously associated with susceptibility to fungal infections (Table 1 ). The selected genes were: CCR5, CX3CR1, IFNG, IFNGR2, IL10, IL12A, IL12B, IL13, IL4, IL4R, CXCL8, CXCR1, CXCR2, MBL2, MIF, NOS3, PTX3 , and ARNT2. VCF files containing the sequencing data of each participant were uploaded to the Franklin by Genoox® platform for variant annotation and classification. Global allele frequencies were obtained from gnomAD v4.1.0, while Brazilian-specific frequencies were retrieved from the ABraOM database. ACMG Guidelines Variants were evaluated using the ACMG criteria, including absence in population databases, in silico pathogenicity predictions, and variant type. Most SNVs were classified under the criteria PM2_SUPP + BP4 as variants of uncertain significance (VUS) (Table 2). Due to inconsistencies in in silico predictors, we further assessed the potential for structural and functional disruption by analyzing the chemical dissimilarity of substituted amino acids. This analysis supported the hypothesis of potential protein dysfunction. Additional evaluation using PPI networks revealed possible impacts on antifungal immune mechanisms. Table 1. Virtual Multigenic Panel Table 1 : Virtual multigenic panel. Column 1: name of genes. Column 2: Reference of literature. Column 3: SNP ID. Column 4: Related to infections. Table 2. Variant Classification According to ACMG Table 2 : Variant classification. Column 1: Name of gene. Column 2: SNP ID. Column 3: type of molecular alteration found. Column 4: Classification according ACMG. Column 5: Level of mutation damage. Column 6: rediction of the effect of substitutions between amino acids based on chemical properties. Protein–Protein Interaction and Pathway Enrichment PPI network analysis was performed using STRING v12.0, incorporating genes that showed VUS with potential immunological relevance (PTX3, CX3CR1, IL4R, IL12B, IFNG, CCR5). Significant enrichment was observed (PPI enrichment p-value < 0.05), suggesting interactions relevant to antifungal defense. Figure 1 . Biological processes identified included: cytokine-mediated signaling pathway (GO:0019221), macrophage activation in immune response (GO:0002281), response to fungal pathogens (GO:0009620), positive regulation of phagocytosis (GO:0050766), host modulation of symbiont processes (GO:0051851), and regulation of cytokine production (GO:0001817). Relevant KEGG pathways included: cytokine–cytokine receptor interaction (FDR: 1.26e-06), Th1 and Th2 cell differentiation (FDR: 0.00019), and the JAK-STAT signaling pathway (FDR: 0.00071). Discussion The primary clinical feature associated with progressive chronic Aspergillus infection is structural damage caused by previous pulmonary diseases, such as tuberculosis. Interestingly, most affected individuals do not present significant alterations in leukocyte or lymphocyte lineages, which raises questions about immune system functionality in immunocompetent hosts. Effective immune responses require adequate signaling pathways. Although humoral immunity is not yet fully understood in fungal infections, it is clear that the absence of humoral signaling compromises the recruitment of cellular immune mechanisms. Pathogen recognition is mediated by soluble molecules that participate in immune cascades, including opsonization, phagocytic activation, and direct pathogen neutralization. This immunological synergy—particularly against Aspergillus conidia—requires the coordinated action of pattern recognition molecules and cellular immunity. PTX3 is a soluble pattern recognition molecule that plays a vital role in recruiting macrophages and neutrophils to sites of inflammation. Its multifunctional nature includes modulating inflammation, tissue remodeling, and complement activation. Previous studies have shown that polymorphisms in PTX3 are associated with increased susceptibility to fungal infections in non-neutropenic patients due to impaired conidial opsonization. In our study, the variant rs138818541 in PTX3 was identified in one patient (8.3%). Although classified as a variant of uncertain significance (VUS) by ACMG guidelines, emerging evidence suggests a deleterious impact of such variants. Similarly, the rs555964469 variant in CX3CR1 was also found in one patient. This chemokine receptor is predominantly expressed in natural killer cells, cytotoxic CD8 + T cells, macrophages, and monocytes. As leukocytes are essential in fungal clearance, defects in receptor function may compromise host defense. Studies like that of Lupiañez et al. (2020) have shown that macrophages are key players in eliminating fungal pathogens, and alterations in their activation may contribute to CPA persistence. The pulmonary epithelium consists of alveolar epithelial cells type I and II (ATI and ATII). While ATII cells retain regenerative potential in adults, aging and chronic infections impair their functionality. The sustained recruitment of macrophages and inflammatory mediators, including profibrotic signals, can exacerbate CPA progression. Our cohort's average age of 48 years may reflect environmental and age-related impacts on epithelial repair. Interestingly, the most frequently observed variant in our study was located in the IL4R gene (75% of patients). Although this gene is widely studied in allergic bronchopulmonary aspergillosis (ABPA), its role in CPA is less established. IL-4 is essential for Th2 cell differentiation, and abnormal expression of IL4R is implicated in Th2-skewed diseases. However, given the high allele frequency of most IL4R variants in the Brazilian population (ABraOM > 0.5), they were excluded from ACMG classification—except for the rare rs780006435 variant (allele frequency < 0.01), which met classification criteria. The presence of these variants suggests a molecular mechanism underlying increased vulnerability to CPA. While some in silico predictors did not classify them as deleterious, additional analyses of amino acid property changes suggested structural and functional alterations in the encoded proteins. Our study is limited by its small sample size and the scarcity of published functional studies on host genetics in chronic fungal infections. Moreover, the Brazilian population's genetic diversity complicates variant interpretation due to limited genome databases. Although we used ABraOM as a reference, it remains underpowered compared to European datasets. Nevertheless, this is the first study to apply a custom multigenic panel to a Brazilian CPA cohort. Our findings underscore the need for further functional studies and biomarker development, including quantification of PTX3 and MBL2 in clinical settings. Ultimately, integrating genetic insights into CPA management may improve diagnostic accuracy and therapeutic outcomes. Conclusion This exploratory study highlights the potential role of rare genomic variants in immune-related genes among patients with chronic pulmonary aspergillosis. Although the variants identified were classified as VUS, structural and network analyses indicate possible impacts on protein function and antifungal immune responses. This research represents the first application of a multigenic panel in a Brazilian cohort with CPA and emphasizes the importance of integrating genomic data into the investigation of host susceptibility to fungal diseases. Future studies with larger cohorts and functional validation are essential to better understand the molecular basis of CPA and to advance personalized approaches for its diagnosis and treatment. Declarations Contributions R. S. Mendes, V. F. Oliveira, A. N. Costa and M. M. C. Magri were involved in writing—review and editing, formal analysis, methodology; B.M. Wolff, L.L. Vieira, M.R. Costa Siemann, Karina Marinho Nascimento and L. S. Rolim helped in methodology— Next Generation Sequencing, review; Y. Gasparini, and G.F.S. Carvalho, review; E. A. Moura helped in NGS analysis; L.D. Kulikowski took charge of project administration and funding acquisition. Ethics approval and consent to participate The ethics committee of the University of São Paulo approved this study (HC-FMUSP—CAPPesq 76601023.1.0000.0068. The patients or parents of the patients signed the consent form for participation in the study. Consent for publication All authors have agreed to have this article published. Competing interests The authors declare no competing interests. References Denning DW, Chakrabarti A (2017) Pulmonary and sinus fungal diseases in non-immunocompromised patients. Lancet Infect Dis 17(11):e357–e66 Gago S, Denning DW, Bowyer P (2019) Pathophysiological aspects of Aspergillus colonization in disease. Med Mycol 57(Supplement2):S219–S27 Griffiths JS, Orr SJ, Morton CO, Loeffler J, White PL (2022) The Use of Host Biomarkers for the Management of Invasive Fungal Disease. J Fungi (Basel). ;8(12) Lupiañez CB, Canet LM, Carvalho A, Alcazar-Fuoli L, Springer J, Lackner M et al (2015) Polymorphisms in Host Immunity-Modulating Genes and Risk of Invasive Aspergillosis: Results from the AspBIOmics Consortium. Infect Immun 84(3):643–657 He Q, Li H, Rui Y, Liu L, He B, Shi Y et al (2018) Pentraxin 3 Gene Polymorphisms and Pulmonary Aspergillosis in Chronic Obstructive Pulmonary Disease Patients. Clin Infect Dis 66(2):261–267 de Oliveira VF, Viana JA, Sawamura MVY, Magri ASGK, Benard G, Costa AN et al (2023) Challenges, Characteristics, and Outcomes of Chronic Pulmonary Aspergillosis: A 11-Year Experience in A Middle-Income Country. Mycopathologia 188(5):683–691 Hayes GE, Novak-Frazer L (2016) Chronic Pulmonary Aspergillosis-Where Are We? and Where Are We Going? J Fungi (Basel). ;2(2) Denning DW, Page ID, Chakaya J, Jabeen K, Jude CM, Cornet M et al (2018) Case Definition of Chronic Pulmonary Aspergillosis in Resource-Constrained Settings. Emerg Infect Dis. ;24(8) De Oliveira VF, Magri MMC (2023) Diagnosis of Chronic Pulmonary Aspergillosis: Challenges and Limitations Response to Diagnosis of Chronic Pulmonary Aspergillosis: Which Is the Best Investigation? and Diagnosis of Chronic Pulmonary Aspergillosis. Am J Trop Med Hyg 108(6):1302–1303 de Oliveira VF, Viana JA, Sawamura MVY, Magri ASGK, Nathan Costa A, Abdala E et al (2023) Sensitivity of Antigen, Serology, and Microbiology Assays for Diagnosis of the Subtypes of Chronic Pulmonary Aspergillosis at a Teaching Hospital in São Paulo, Brazil. Am J Trop Med Hyg 108(1):22–26 Im Y, Jhun BW, Kang ES, Koh WJ, Jeon K (2021) Impact of treatment duration on recurrence of chronic pulmonary aspergillosis. J Infect 83(4):490–495 Sengupta A, Ray A, Upadhyay AD, Izumikawa K, Tashiro M, Kimura Y et al (2025) Mortality in chronic pulmonary aspergillosis: a systematic review and individual patient data meta-analysis. Lancet Infect Dis 25(3):312–324 Volpe-Chaves CE, Venturini J, Castilho B, S O Fonseca S, Nunes SF, Cunha TT (2022) Prevalence of chronic pulmonary aspergillosis regarding time of tuberculosis diagnosis in Brazil. Mycoses 65(7):715–723 Soremekun OS, Soliman MES (2019) From genomic variation to protein aberration: Mutational analysis of single nucleotide polymorphism present in ULBP6 gene and implication in immune response. Comput Biol Med 111:103354 Zhang H, Zhan J, Jin J, Zhang J, Lu W, Zhao R et al (2023) A new method for multiancestry polygenic prediction improves performance across diverse populations. Nat Genet 55(10):1757–1768 Tang T, Dai Y, Zeng Q, Bu S, Huang B, Xiao Y et al (2020) Pentraxin-3 polymorphisms and pulmonary fungal disease in non-neutropenic patients. Ann Transl Med 8(18):1142 Kalkanci A, Tug E, Fidan I, Guzel Tunccan O, Ozkurt ZN, Yegin ZA et al (2020) Retrospective analysis of the association of the expression and single nucleotide polymorphisms (SNPs) of the TLR4, PTX3 and Dectin-1 (CLEC/A) genes with development of invasive aspergillosis among haematopoietic stem cell transplant recipients with oncohaematological disorders. Mycoses 63(8):832–839 Denning DW, Cadranel J, Beigelman-Aubry C, Ader F, Chakrabarti A, Blot S et al (2016) Chronic pulmonary aspergillosis: rationale and clinical guidelines for diagnosis and management. Eur Respir J 47(1):45–68 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6473313","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":444508067,"identity":"44c7976d-2301-4485-84b8-45f2158593e1","order_by":0,"name":"Rafaela da Silva Mendes","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYBAC+wbGBwwMBVAeDwODHIhmxqfF4ACzAZBEaDEmXUtiA0Etxw8zfvhgYMcgP+3wsQdvKurSN5w/e4C5cA8ev/QkM0vOMEhmMLidlm4458zh3A038hKYZzzDrcWOIf+ANI8BM4OBdI6ZNG/bAaAWIJfnAG4txvyPmX//MahnkJ+d/02a919dusH5M/i1GM5IZpNmMDjMwHA7h02at4E5weBADn4tBjces1n2GBznAfrFTHLOscOGM4F+OTwDn5bzycw3flRUy8nPTn4m8aamTp7v/NmDjwvwaIEBHhQ2ERpwax8Fo2AUjIJRwMAAAP3qUXdfuqnOAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-9607-8245","institution":"Cytogenomics Laboratory, Departament of Pahology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.","correspondingAuthor":true,"prefix":"","firstName":"Rafaela","middleName":"da Silva","lastName":"Mendes","suffix":""},{"id":444508068,"identity":"aa00f43b-2ec6-49d4-ae8d-4c48594b1453","order_by":1,"name":"Beatriz Martins Wolff","email":"","orcid":"https://orcid.org/0000-0002-3290-9652","institution":"Cytogenomics Laboratory, Departament of Pahology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Beatriz","middleName":"Martins","lastName":"Wolff","suffix":""},{"id":444508069,"identity":"f3665ee1-1d8d-448e-9916-fb38aecb3c15","order_by":2,"name":"Mariana Ribeiro Costa Siemann","email":"","orcid":"https://orcid.org/0000-0002-2761-3275","institution":"Cytogenomics Laboratory, Departament of Pahology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Mariana","middleName":"Ribeiro Costa","lastName":"Siemann","suffix":""},{"id":444508070,"identity":"2300bf92-77de-427b-a04c-7527c3a699a7","order_by":3,"name":"Yanca Gasparini Oliveira","email":"","orcid":"https://orcid.org/0000-0002-7035-7705","institution":"Cytogenomics Laboratory, Departament of Pahology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Yanca","middleName":"Gasparini","lastName":"Oliveira","suffix":""},{"id":444508071,"identity":"864566d8-ea58-4b67-b182-57d74d1e6d71","order_by":4,"name":"Gleyson Francisco da Silva Carvalho","email":"","orcid":"https://orcid.org/0000-0003-1505-7651","institution":"Cytogenomics Laboratory, Departament of Pahology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Gleyson","middleName":"Francisco da Silva","lastName":"Carvalho","suffix":""},{"id":444508072,"identity":"19dc2cc4-8fc7-4a74-9cf3-8e1f14e186cf","order_by":5,"name":"Lucas Liro Vieira","email":"","orcid":"","institution":"Cytogenomics Laboratory, Departament of Pahology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Lucas","middleName":"Liro","lastName":"Vieira","suffix":""},{"id":444508073,"identity":"8a5454d6-8864-43cd-85b4-0e9416b3c012","order_by":6,"name":"Eder Alencar Moura","email":"","orcid":"https://orcid.org/0000-0003-1507-2632","institution":"Cytogenomics Laboratory, Departament of Pahology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Eder","middleName":"Alencar","lastName":"Moura","suffix":""},{"id":444508074,"identity":"8dedce45-9a3f-4585-939a-0fe784f215a8","order_by":7,"name":"Karina Marinho Nascimento","email":"","orcid":"https://orcid.org/0009-0007-5939-4939","institution":"Cytogenomics Laboratory, Departament of Pahology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Karina","middleName":"Marinho","lastName":"Nascimento","suffix":""},{"id":444508075,"identity":"5fdc0b92-b994-4c11-b428-b84599c1853b","order_by":8,"name":"Lissandro de Sousa Rolim","email":"","orcid":"https://orcid.org/0009-0009-0109-5981","institution":"Cytogenomics Laboratory, Departament of Pahology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Lissandro","middleName":"de Sousa","lastName":"Rolim","suffix":""},{"id":444508076,"identity":"51bd4dbe-5988-411b-8168-bc9bc0077a6d","order_by":9,"name":"Andre Nathan Costa","email":"","orcid":"","institution":"Department of Pneumology, Hospital das Clínicas (HCFMUSP), University of São Paulo, São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Andre","middleName":"Nathan","lastName":"Costa","suffix":""},{"id":444508077,"identity":"73666146-9162-4882-af2a-a0e1d4d0238a","order_by":10,"name":"Marcello Mihailenko Chaves Magri","email":"","orcid":"","institution":"Department of Infectious and Parasitic Diseases, Hospital das Clínicas (HCFMUSP), University of São Paulo, São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Marcello","middleName":"Mihailenko Chaves","lastName":"Magri","suffix":""},{"id":444508078,"identity":"7d1e5a72-0147-4853-8b88-a9072d5c6fe5","order_by":11,"name":"Vítor Falcão de Oliveira","email":"","orcid":"","institution":"Department of Infectious and Parasitic Diseases, Hospital das Clínicas (HCFMUSP), University of São Paulo, São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Vítor","middleName":"Falcão","lastName":"de Oliveira","suffix":""},{"id":444508079,"identity":"d3eab110-05cd-4e2a-a655-1adcb37fc64d","order_by":12,"name":"Leslie Domenici Kulikowski","email":"","orcid":"","institution":"Cytogenomics Laboratory, Departament of Pahology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Leslie","middleName":"Domenici","lastName":"Kulikowski","suffix":""}],"badges":[],"createdAt":"2025-04-17 16:04:11","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6473313/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6473313/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81028819,"identity":"50a495d5-a76c-4e6d-aa8a-c5bddc598538","added_by":"auto","created_at":"2025-04-21 11:07:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":52348,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of nodes: 6 number of edges: 7 average node degree: 2.33 avg. local clustering coefficient: 0.867 expected number of edges: 1 PPI enrichment p-value: 6.27e-05 (0.0000627).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6473313/v1/9d887a4579a95e64eb112685.png"},{"id":81028818,"identity":"b4e91e00-efcc-4663-b926-ec5972ebc93f","added_by":"auto","created_at":"2025-04-21 11:07:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":32764,"visible":true,"origin":"","legend":"\u003cp\u003eUnnumbered image in the Results section.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6473313/v1/2315df3b9c6d4c32a52c7a44.png"},{"id":81031686,"identity":"81c2ffbd-3c25-4559-9820-09fe15c6d44e","added_by":"auto","created_at":"2025-04-21 11:23:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":812734,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6473313/v1/65f9475e-81ed-49bf-b0ab-99692cdd7c7b.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eChronic Pulmonary Aspergillosis: Genomic Variant Analysis and Protein Dysfunction Susceptibility in a Brazilian Cohort\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic pulmonary aspergillosis (CPA) is a progressive and potentially fatal fungal infection primarily caused by \u003cem\u003eAspergillus spp\u003c/em\u003e., an opportunistic fungus commonly found in the environment. Its clinical manifestation is influenced by both host immune status and the presence of pre-existing pulmonary sequelae(\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Immunocompromised individuals\u0026mdash;such as those undergoing solid organ or bone marrow transplantation\u0026mdash;are particularly vulnerable to invasive aspergillosis(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). However, CPA predominantly affects immunocompetent or non-neutropenic patients, especially those with chronic lung conditions such as tuberculosis sequelae(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCPA encompasses several clinical subtypes, including simple aspergilloma, chronic cavitary pulmonary aspergillosis, subacute invasive aspergillosis, \u003cem\u003eAspergillus\u003c/em\u003e nodules, and chronic fibrosing pulmonary aspergillosis. Diagnosis relies on a combination of radiological evidence, immunoprecipitation antibody titers, and clinical symptoms, which is especially critical in low-resource settings(\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite treatment efforts, CPA is associated with significant morbidity and mortality, often progressing to pulmonary fibrosis and severely impacting quality of life(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Globally, an estimated 3\u0026nbsp;million individuals are affected by CPA annually, with Brazil reporting approximately 112,000\u0026ndash;160,000 new cases per year and a 5-year mortality rate ranging from 38\u0026ndash;85%(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGenetic predisposition may influence susceptibility to CPA. Single nucleotide polymorphisms (SNPs) are common in the general population and can result from evolutionary adaptation, spontaneous mutations, or environmental exposure(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). While not all genetic mutations result in pathogenic protein alterations, certain SNPs may affect immune response pathways. Genome-wide association studies (GWAS) have identified variants in immune-related genes, such as PTX3, associated with impaired neutrophil function and increased susceptibility to fungal infections(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGiven the limited literature on host\u0026ndash;pathogen genetic interactions in fungal infections, this study aims to investigate genomic variants in Brazilian patients diagnosed with CPA. Using next-generation sequencing (NGS) and American College of Medical Genetics (ACMG) classification guidelines, we identified and evaluated genetic variants that may contribute to susceptibility to CPA.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThis study enrolled Brazilian patients receiving outpatient follow-up in the Infectious Diseases and Pulmonology departments at the Hospital das Cl\u0026iacute;nicas, University of S\u0026atilde;o Paulo (HC-FMUSP) during the period of 2023, with a confirmed diagnosis of chronic pulmonary aspergillosis (CPA). All patients with CPA had the following characteristics, in accordance with the ESCMID/ERS criteria(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e): (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) the computerized tomography scan of the chest findings suggestive of aspergillosis (one or more cavities with or without a fungal ball present or nodules); (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) microbiological evidence of \u003cem\u003eAspergillus\u003c/em\u003e infection [microscopy or culture from sputum, bronchoalveolar lavage (BAL) or, biopsy, histology, positive serum or BAL galactomannan] or serological evidence (serum immunodiffusion test and counterimmunoelectrophoresis); (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) All present for at least 3 months or at least a 1-month duration in SAIA; (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) Exclusion of alternative diagnoses, such as tuberculosis, malignancy, and other similar pathological conditions.\u003c/p\u003e \u003cp\u003eA total of 12 patients (n\u0026thinsp;=\u0026thinsp;12) were included, of whom 8 were male (66.7%) and 4 were female (33.3%). All patients presented post-tuberculosis pulmonary. The clinical subtypes observed in the cohort were: chronic cavitary pulmonary aspergillosis in 8 patients (66.7%), simple aspergilloma in 3 patients (25.0%), and chronic fibrosing pulmonary aspergillosis in 1 patient (8.3%). The exclusion criteria for the study were: immunosuppressive conditions (eg. HIV infection, malignancies, prolonged corticosteroid administration, diabetes mellitus, and cirrhosis) and confirmed genetic diseases.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDNA Extraction\u003c/h3\u003e\n\u003cp\u003ePeripheral blood (4 mL) was collected in EDTA-containing tubes. All participants signed informed consent forms (CAAE: 76601023.1.0000.0068). DNA was extracted at the Cytogenomics Laboratory, Department of Pathology, Faculty of Medicine, University of S\u0026atilde;o Paulo, using the \u003cem\u003eQIAamp DNA Blood Mini Kit (Qiagen\u0026reg;, Hilden, Germany)\u003c/em\u003e, following the manufacturer\u0026rsquo;s protocol. A final volume of 30 \u0026micro;L was obtained for subsequent analyses, and DNA concentration and quality were measured using a \u003cem\u003eQubit fluorometer (Thermo Fisher Scientific\u0026reg;).\u003c/em\u003e\u003c/p\u003e\n\u003ch3\u003eNext-Generation Sequencing (NGS)\u003c/h3\u003e\n\u003cp\u003eExome libraries were prepared using the \u003cem\u003eIllumina\u0026reg; DNA Prep with Exome 2.0 Plus Enrichment kit\u003c/em\u003e, according to the manufacturer's instructions. Sequencing was performed using the \u003cem\u003eNovaSeq 6000 System (Illumina\u0026reg;, 2025)\u003c/em\u003e. Raw data were generated in Variant Call Format (VCF) and annotated by comparison with the reference genome GRCh38/hg38 using bioinformatics tools.\u003c/p\u003e\n\u003ch3\u003eVariant Filtering and Classification\u003c/h3\u003e\n\u003cp\u003eA custom-designed virtual multigenic panel was developed including genes previously reported to be associated with susceptibility to fungal infections. The panel included: \u003cem\u003eCCR5, CX3CR1, IFNG, IFNGR2, IL10, IL12A, IL12B, IL13, IL4, IL4R, CXCL8, CXCR1, CXCR2, MBL2, MIF, NOS3, PTX3\u003c/em\u003e, and \u003cem\u003eARNT2\u003c/em\u003e. VCF files from each participant were analyzed using the \u003cem\u003eFranklin by Genoox\u0026reg; platform (\u003c/em\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://franklin.genoox.com\u003c/span\u003e\u003cspan address=\"https://franklin.genoox.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cem\u003e).\u003c/em\u003e Allele frequencies were obtained from the \u003cem\u003egnomAD v4.1.0\u003c/em\u003e and \u003cem\u003eABraOM\u003c/em\u003e databases (Brazilian Online Archive of Mutations).\u003c/p\u003e \u003cp\u003e Variants classified as single nucleotide variants (SNVs) were evaluated using the American College of Medical Genetics and Genomics (ACMG) guidelines, considering allele frequency, in silico prediction tools, and mutation type. The criteria PM2_SUPP and BP4 were applied, and most variants were categorized as variants of uncertain significance (VUS).\u003c/p\u003e \u003cp\u003eAdditional analyses included computational modeling of amino acid substitutions and chemical dissimilarity to assess potential protein dysfunction. Protein\u0026ndash;protein interaction networks and immune pathway enrichment were evaluated for implicated genes.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eVariant Analysis and Classification\u003c/h2\u003e\n \u003cp\u003eVariant analysis was guided by the development of a virtual multigenic panel consisting of genes previously associated with susceptibility to fungal infections (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The selected genes were: \u003cem\u003eCCR5, CX3CR1, IFNG, IFNGR2, IL10, IL12A, IL12B, IL13, IL4, IL4R, CXCL8, CXCR1, CXCR2, MBL2, MIF, NOS3, PTX3\u003c/em\u003e, and \u003cem\u003eARNT2.\u003c/em\u003e VCF files containing the sequencing data of each participant were uploaded to the Franklin by Genoox\u0026reg; platform for variant annotation and classification. Global allele frequencies were obtained from gnomAD v4.1.0, while Brazilian-specific frequencies were retrieved from the ABraOM database.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eACMG Guidelines\u003c/h3\u003e\n\u003cp\u003eVariants were evaluated using the ACMG criteria, including absence in population databases, in silico pathogenicity predictions, and variant type. Most SNVs were classified under the criteria PM2_SUPP\u0026thinsp;+\u0026thinsp;BP4 as variants of uncertain significance (VUS) (Table\u0026nbsp;2). Due to inconsistencies in in silico predictors, we further assessed the potential for structural and functional disruption by analyzing the chemical dissimilarity of substituted amino acids. This analysis supported the hypothesis of potential protein dysfunction. Additional evaluation using PPI networks revealed possible impacts on antifungal immune mechanisms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Virtual Multigenic Panel\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003cbr\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e: Virtual multigenic panel. Column 1: name of genes. Column 2: Reference of literature. Column 3: SNP ID. Column 4: Related to infections.\u003c/p\u003e\n\u003cp\u003eTable 2. Variant Classification According to ACMG\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;2\u003c/strong\u003e: Variant classification. Column 1: Name of gene. Column 2: SNP ID. Column 3: type of molecular alteration found. Column 4: Classification according ACMG. Column 5: Level of mutation damage. Column 6: rediction of the effect of substitutions between amino acids based on chemical properties.\u003c/p\u003e\n\u003ch3\u003eProtein\u0026ndash;Protein Interaction and Pathway Enrichment\u003c/h3\u003e\n\u003cp\u003ePPI network analysis was performed using STRING v12.0, incorporating genes that showed VUS with potential immunological relevance \u003cem\u003e(PTX3, CX3CR1, IL4R, IL12B, IFNG, CCR5).\u003c/em\u003e Significant enrichment was observed (PPI enrichment p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting interactions relevant to antifungal defense. Figure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eBiological processes identified included: cytokine-mediated signaling pathway (GO:0019221), macrophage activation in immune response (GO:0002281), response to fungal pathogens (GO:0009620), positive regulation of phagocytosis (GO:0050766), host modulation of symbiont processes (GO:0051851), and regulation of cytokine production (GO:0001817).\u003c/p\u003e\n\u003cp\u003eRelevant KEGG pathways included: cytokine\u0026ndash;cytokine receptor interaction (FDR: 1.26e-06), Th1 and Th2 cell differentiation (FDR: 0.00019), and the JAK-STAT signaling pathway (FDR: 0.00071).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe primary clinical feature associated with progressive chronic \u003cem\u003eAspergillus\u003c/em\u003e infection is structural damage caused by previous pulmonary diseases, such as tuberculosis. Interestingly, most affected individuals do not present significant alterations in leukocyte or lymphocyte lineages, which raises questions about immune system functionality in immunocompetent hosts.\u003c/p\u003e \u003cp\u003eEffective immune responses require adequate signaling pathways. Although humoral immunity is not yet fully understood in fungal infections, it is clear that the absence of humoral signaling compromises the recruitment of cellular immune mechanisms. Pathogen recognition is mediated by soluble molecules that participate in immune cascades, including opsonization, phagocytic activation, and direct pathogen neutralization. This immunological synergy\u0026mdash;particularly against \u003cem\u003eAspergillus\u003c/em\u003e conidia\u0026mdash;requires the coordinated action of pattern recognition molecules and cellular immunity.\u003c/p\u003e \u003cp\u003ePTX3 is a soluble pattern recognition molecule that plays a vital role in recruiting macrophages and neutrophils to sites of inflammation. Its multifunctional nature includes modulating inflammation, tissue remodeling, and complement activation. Previous studies have shown that polymorphisms in \u003cem\u003ePTX3\u003c/em\u003e are associated with increased susceptibility to fungal infections in non-neutropenic patients due to impaired conidial opsonization. In our study, the variant rs138818541 in \u003cem\u003ePTX3\u003c/em\u003e was identified in one patient (8.3%). Although classified as a variant of uncertain significance (VUS) by ACMG guidelines, emerging evidence suggests a deleterious impact of such variants.\u003c/p\u003e \u003cp\u003eSimilarly, the rs555964469 variant in \u003cem\u003eCX3CR1\u003c/em\u003e was also found in one patient. This chemokine receptor is predominantly expressed in natural killer cells, cytotoxic CD8\u0026thinsp;+\u0026thinsp;T cells, macrophages, and monocytes. As leukocytes are essential in fungal clearance, defects in receptor function may compromise host defense. Studies like that of Lupia\u0026ntilde;ez et al. (2020) have shown that macrophages are key players in eliminating fungal pathogens, and alterations in their activation may contribute to CPA persistence.\u003c/p\u003e \u003cp\u003eThe pulmonary epithelium consists of alveolar epithelial cells type I and II (ATI and ATII). While ATII cells retain regenerative potential in adults, aging and chronic infections impair their functionality. The sustained recruitment of macrophages and inflammatory mediators, including profibrotic signals, can exacerbate CPA progression. Our cohort's average age of 48 years may reflect environmental and age-related impacts on epithelial repair.\u003c/p\u003e \u003cp\u003eInterestingly, the most frequently observed variant in our study was located in the IL4R gene (75% of patients). Although this gene is widely studied in allergic bronchopulmonary aspergillosis (ABPA), its role in CPA is less established. IL-4 is essential for Th2 cell differentiation, and abnormal expression of IL4R is implicated in Th2-skewed diseases. However, given the high allele frequency of most IL4R variants in the Brazilian population (ABraOM\u0026thinsp;\u0026gt;\u0026thinsp;0.5), they were excluded from ACMG classification\u0026mdash;except for the rare rs780006435 variant (allele frequency\u0026thinsp;\u0026lt;\u0026thinsp;0.01), which met classification criteria.\u003c/p\u003e \u003cp\u003eThe presence of these variants suggests a molecular mechanism underlying increased vulnerability to CPA. While some in silico predictors did not classify them as deleterious, additional analyses of amino acid property changes suggested structural and functional alterations in the encoded proteins.\u003c/p\u003e \u003cp\u003eOur study is limited by its small sample size and the scarcity of published functional studies on host genetics in chronic fungal infections. Moreover, the Brazilian population's genetic diversity complicates variant interpretation due to limited genome databases. Although we used ABraOM as a reference, it remains underpowered compared to European datasets.\u003c/p\u003e \u003cp\u003eNevertheless, this is the first study to apply a custom multigenic panel to a Brazilian CPA cohort. Our findings underscore the need for further functional studies and biomarker development, including quantification of PTX3 and MBL2 in clinical settings. Ultimately, integrating genetic insights into CPA management may improve diagnostic accuracy and therapeutic outcomes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis exploratory study highlights the potential role of rare genomic variants in immune-related genes among patients with chronic pulmonary aspergillosis. Although the variants identified were classified as VUS, structural and network analyses indicate possible impacts on protein function and antifungal immune responses. This research represents the first application of a multigenic panel in a Brazilian cohort with CPA and emphasizes the importance of integrating genomic data into the investigation of host susceptibility to fungal diseases. Future studies with larger cohorts and functional validation are essential to better understand the molecular basis of CPA and to advance personalized approaches for its diagnosis and treatment.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eContributions\u003c/h2\u003e \u003cp\u003eR. S. Mendes, V. F. Oliveira, A. N. Costa and M. M. C. Magri were involved in writing\u0026mdash;review and editing, formal analysis, methodology; B.M. Wolff, L.L. Vieira, M.R. Costa Siemann, Karina Marinho Nascimento and L. S. Rolim helped in methodology\u0026mdash; Next Generation Sequencing, review; Y. Gasparini, and G.F.S. Carvalho, review; E. A. Moura helped in NGS analysis; L.D. Kulikowski took charge of project administration and funding acquisition.\u003c/p\u003e \u003c/div\u003e \n\u003ch3\u003eEthics approval and consent to participate\u003c/h3\u003e\n\u003cp\u003eThe ethics committee of the University of São Paulo approved this study (HC-FMUSP—CAPPesq\u0026nbsp;76601023.1.0000.0068.\u003c/p\u003e\n\u003cp\u003eThe patients or parents of the patients signed the consent form for participation in the study.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eAll authors have agreed to have this article published.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDenning DW, Chakrabarti A (2017) Pulmonary and sinus fungal diseases in non-immunocompromised patients. Lancet Infect Dis 17(11):e357\u0026ndash;e66\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGago S, Denning DW, Bowyer P (2019) Pathophysiological aspects of Aspergillus colonization in disease. Med Mycol 57(Supplement2):S219\u0026ndash;S27\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGriffiths JS, Orr SJ, Morton CO, Loeffler J, White PL (2022) The Use of Host Biomarkers for the Management of Invasive Fungal Disease. J Fungi (Basel). ;8(12)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLupia\u0026ntilde;ez CB, Canet LM, Carvalho A, Alcazar-Fuoli L, Springer J, Lackner M et al (2015) Polymorphisms in Host Immunity-Modulating Genes and Risk of Invasive Aspergillosis: Results from the AspBIOmics Consortium. Infect Immun 84(3):643\u0026ndash;657\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe Q, Li H, Rui Y, Liu L, He B, Shi Y et al (2018) Pentraxin 3 Gene Polymorphisms and Pulmonary Aspergillosis in Chronic Obstructive Pulmonary Disease Patients. Clin Infect Dis 66(2):261\u0026ndash;267\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Oliveira VF, Viana JA, Sawamura MVY, Magri ASGK, Benard G, Costa AN et al (2023) Challenges, Characteristics, and Outcomes of Chronic Pulmonary Aspergillosis: A 11-Year Experience in A Middle-Income Country. Mycopathologia 188(5):683\u0026ndash;691\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHayes GE, Novak-Frazer L (2016) Chronic Pulmonary Aspergillosis-Where Are We? and Where Are We Going? J Fungi (Basel). ;2(2)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDenning DW, Page ID, Chakaya J, Jabeen K, Jude CM, Cornet M et al (2018) Case Definition of Chronic Pulmonary Aspergillosis in Resource-Constrained Settings. Emerg Infect Dis. ;24(8)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Oliveira VF, Magri MMC (2023) Diagnosis of Chronic Pulmonary Aspergillosis: Challenges and Limitations Response to Diagnosis of Chronic Pulmonary Aspergillosis: Which Is the Best Investigation? and Diagnosis of Chronic Pulmonary Aspergillosis. Am J Trop Med Hyg 108(6):1302\u0026ndash;1303\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Oliveira VF, Viana JA, Sawamura MVY, Magri ASGK, Nathan Costa A, Abdala E et al (2023) Sensitivity of Antigen, Serology, and Microbiology Assays for Diagnosis of the Subtypes of Chronic Pulmonary Aspergillosis at a Teaching Hospital in S\u0026atilde;o Paulo, Brazil. Am J Trop Med Hyg 108(1):22\u0026ndash;26\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIm Y, Jhun BW, Kang ES, Koh WJ, Jeon K (2021) Impact of treatment duration on recurrence of chronic pulmonary aspergillosis. J Infect 83(4):490\u0026ndash;495\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSengupta A, Ray A, Upadhyay AD, Izumikawa K, Tashiro M, Kimura Y et al (2025) Mortality in chronic pulmonary aspergillosis: a systematic review and individual patient data meta-analysis. Lancet Infect Dis 25(3):312\u0026ndash;324\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVolpe-Chaves CE, Venturini J, Castilho B, S O Fonseca S, Nunes SF, Cunha TT (2022) Prevalence of chronic pulmonary aspergillosis regarding time of tuberculosis diagnosis in Brazil. Mycoses 65(7):715\u0026ndash;723\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoremekun OS, Soliman MES (2019) From genomic variation to protein aberration: Mutational analysis of single nucleotide polymorphism present in ULBP6 gene and implication in immune response. Comput Biol Med 111:103354\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang H, Zhan J, Jin J, Zhang J, Lu W, Zhao R et al (2023) A new method for multiancestry polygenic prediction improves performance across diverse populations. Nat Genet 55(10):1757\u0026ndash;1768\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang T, Dai Y, Zeng Q, Bu S, Huang B, Xiao Y et al (2020) Pentraxin-3 polymorphisms and pulmonary fungal disease in non-neutropenic patients. Ann Transl Med 8(18):1142\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKalkanci A, Tug E, Fidan I, Guzel Tunccan O, Ozkurt ZN, Yegin ZA et al (2020) Retrospective analysis of the association of the expression and single nucleotide polymorphisms (SNPs) of the TLR4, PTX3 and Dectin-1 (CLEC/A) genes with development of invasive aspergillosis among haematopoietic stem cell transplant recipients with oncohaematological disorders. Mycoses 63(8):832\u0026ndash;839\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDenning DW, Cadranel J, Beigelman-Aubry C, Ader F, Chakrabarti A, Blot S et al (2016) Chronic pulmonary aspergillosis: rationale and clinical guidelines for diagnosis and management. Eur Respir J 47(1):45\u0026ndash;68\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Cytogenomics Laboratory, Departament of Pahology, Faculty of Medicine, University of São Paulo, São Paulo, Brazil.","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"CPA, immune genes, brazilian, aspergillus","lastPublishedDoi":"10.21203/rs.3.rs-6473313/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6473313/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eChronic pulmonary aspergillosis (CPA) is a debilitating condition often affecting immunocompetent patients with underlying structural lung diseases, particularly pulmonary tuberculosis. This study investigates single nucleotide variants (SNVs) in immunogenetic-related genes among a Brazilian cohort with CPA. Twelve patients with confirmed CPA, based on ESCMID/ERS criteria, were sequenced using NGS technology. Variants were annotated, classified using ACMG guidelines, and analyzed for potential impact on protein interactions and immune pathways. A set of SNVs in \u003cem\u003eCX3CR1, IL12B, IL4R, PTX3\u003c/em\u003e, \u003cem\u003eCCR5\u003c/em\u003e and \u003cem\u003eIFNG \u003c/em\u003egenes were classified as variants of uncertain significance (VUS), but protein–protein interaction analysis suggests a potential role in immune evasion and dysfunction. This is the first study to apply a custom multigenic panel for CPA susceptibility in a Brazilian cohort, contributing to future functional and clinical studies in fungal immunogenetics.\u003c/p\u003e","manuscriptTitle":"Chronic Pulmonary Aspergillosis: Genomic Variant Analysis and Protein Dysfunction Susceptibility in a Brazilian Cohort","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-21 11:07:13","doi":"10.21203/rs.3.rs-6473313/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"90d3faf9-4325-4cb1-b029-fb7031e073da","owner":[],"postedDate":"April 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":47325850,"name":"Molecular Genetics"}],"tags":[],"updatedAt":"2025-04-21T11:07:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-21 11:07:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6473313","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6473313","identity":"rs-6473313","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}