Autoimmune manifestations among 461 patients with monogenic inborn errors of immunity

Azizi, Gholamreza; Tavakol, Marzieh; Yazdani, Reza; Delavari, Samaneh; Shad, Tannaz Moeini; Rasouli, Seyed Erfan; Jamee, Mahnaz; Pashangzadeh, Salar; Kalantari, Arash; Shariat, Mansoureh; Shafiei, Alireza; Mohammadi, Javad; Hassanpour, Gholamreza; Chavoshzadeh, Zahra; Mahdaviani, Seyed Alireza; Momen, Tooba; Behniafard, Nasrin; Nabavi, Mohammad; Bemanian, Mohammad Hassan; Arshi, Saba; Molatefi, Rasol; Sherkat, Roya; Shirkani, Afshin; Alyasin, Soheila; Jabbari‐Azad, Farahzad; Ghaffari, Javad; Mesdaghi, Mehrnaz; Ahanchian, Hamid; Khoshkhui, Maryam; Eslamian, Mohammad Hossein; Cheraghi, Taher; Dabbaghzadeh, Abbas; Kalmarzi, Rasoul Nasiri; Esmaeilzadeh, Hossein; Tafaroji, Javad; Khalili, Abbas; Sadeghi‐Shabestari, Mahnaz; Darougar, Sepideh; Moghtaderi, Mojgan; Ahmadiafshar, Akefeh; Shakerian, Behzad; Heidarzadeh, Marzieh; Ghalebaghi, Babak; Fathi, Seyed Mohammad; Darabi, Behzad; Fallahpour, Morteza; Mohsenzadeh, Azam; Ebrahimi, Sarehsadat; Sharafian, Samin; Vosughimotlagh, Ahmad; Tafakoridelbari, Mitra; Haji‐Abadi, Maziyar Rahimi; Ashournia, Parisa; Razaghian, Anahita; Rezaei, Arezou; Salami, Fereshte; Shirmast, Paniz; Bazargan, Nasrin; Mamishi, Setareh; Negahdari, Babak; Shokri, Sima; Nabavizadeh, Seyed Hesamedin; Bazregari, Saeed; Ghasemi, Ramin; Bayat, Shiva; Eshaghi, Hamid; Rezaei, Nima; Abolhassani, Hassan; Aghamohammadi, Asghar

doi:10.1111/pai.13510

Cited by 10 publications

(2 citation statements)

References 36 publications

(148 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our cohort, we have one patient with ICOS deficiency in 34 CVID patients (2.9%). Recent studies showed that pediatric CVID patients, especially who have autoimmune disorders, mostly mutated with autoimmune-associated genes like LRBA and AIRE [34]. Although 42% of our patients have at least one autoimmune disorder, we did not detect any pathogenic variant in autoimmune-related genes.…”

Section: Discussioncontrasting

confidence: 69%

Primary antibody deficiencies in Turkey: molecular and clinical aspects

Fırtına

et al. 2021

Immunol Res

View full text Add to dashboard Cite

Primary antibody deficiencies (PAD) are the most common subtype of primary immunodeficiencies, characterized by increased susceptibility to infections and autoimmunity, allergy, or malignancy predisposition. PAD syndromes comprise of immune system genes highlighted the key role of B cell activation, proliferation, migration, somatic hypermutation, or isotype switching have a wide spectrum from agammaglobulinemia to selective Ig deficiency. In this study, we describe the molecular and the clinical aspects of fifty-two PAD patients. The most common symptoms of our cohort were upper and lower respiratory infections, bronchiectasis, diarrhea, and recurrent fever. Almost all patients (98%) had at least one of the symptoms like autoimmunity, lymphoproliferation, allergy, or gastrointestinal disease. A custom-made next-generation sequencing (NGS) panel, which contains 24 genes, was designed to identify well-known disease-causing variants in our cohort. We identified eight variants (15.4%) among 52 PAD patients. The variants mapped to BTK (n = 4), CD40L (n = 1), ICOS (n = 1), IGHM (n = 1), and TCF3 (n = 1) genes. Three novel variants were described in the BTK (p.G414W), ICOS (p.G60*), and IGHM (p.S19*) genes. We performed Sanger sequencing to validate pathogenic variants and check for allelic segregation in the family. Targeted NGS panel sequencing can be beneficial as a suitable diagnostic modality for diagnosing well-known monogenic PAD diseases (only 2-10% of PADs); however, screening only the coding regions of the genome may not be adequately powered to solve the pathogenesis of PAD in all cases. Deciphering the regulatory regions of the genome and better understanding the epigenetic modifications will elucidate the molecular basis of complex PADs.

show abstract

Section: Discussioncontrasting

confidence: 69%

Primary antibody deficiencies in Turkey: molecular and clinical aspects

Fırtına

et al. 2021

Immunol Res

View full text Add to dashboard Cite

show abstract

“…S2G). Given that thyroid autoimmunities are among the most common endocrine autoimmune features in the clinic and enriched in IEIs with autoimmunity (33), our results indicate that the AutoCore is linked through the transcription machinery across various tissue types but most prominently in immune cell-related tissues. Together, these results demonstrate that the AutoCore represents major molecular, phenotypic, and therapeutic hallmarks of autoimmune/autoinflammatory diseases, suggesting that network-based methods can be further applied to identify disease subclusters and therapeutic options.…”

Section: Identification Of the Autocore A Dense Interactome Subnetwor...mentioning

confidence: 83%

AutoCore: A network-based definition of the core module of human autoimmunity and autoinflammation

Guthrie,

Köstel Bal,

Lombardo

et al. 2023

Sci. Adv.

View full text Add to dashboard Cite

Although research on rare autoimmune and autoinflammatory diseases has enabled definition of nonredundant regulators of homeostasis in human immunity, because of the single gene-single disease nature of many of these diseases, contributing factors were mostly unveiled in sequential and noncoordinated individual studies. We used a network-based approach for integrating a set of 186 inborn errors of immunity with predominant autoimmunity/autoinflammation into a comprehensive map of human immune dysregulation, which we termed “AutoCore.” The AutoCore is located centrally within the interactome of all protein-protein interactions, connecting and pinpointing multidisease markers for a range of common, polygenic autoimmune/autoinflammatory diseases. The AutoCore can be subdivided into 19 endotypes that correspond to molecularly and phenotypically cohesive disease subgroups, providing a molecular mechanism–based disease classification and rationale toward systematic targeting for therapeutic purposes. Our study provides a proof of concept for using network-based methods to systematically investigate the molecular relationships between individual rare diseases and address a range of conceptual, diagnostic, and therapeutic challenges.

show abstract