Associations between HLA class II alleles and IgE sensitization to allergens in the Qatar Biobank cohort

Background: Allergic disorders are the consequence of IgE sensitization to allergens. Population studies have shown that certain human leukocyte antigen (HLA) alleles are associated with increased or decreased risk of developing allergy. Objective: We aimed to characterize the relationship between HLA class II allelic diversity and IgE sensitization in an understudied Arab population. Methods: We explored associations between IgE sensitization to 7 allergen mixes and mesquite (comprising 41 food or aeroallergens) and 45 common classical HLA class II alleles in a well-defined cohort of 797 individuals representing the general adult population of Qatari nationals and long-term residents. To do so, we performed HLA calling from whole genome sequencing data at 2-field resolution using 2 independent algorithms. We then applied 3 different regression models to assess either each allergen mix independently, in the context of IgE sensitization to other allergens tested, or polysensitization. Results: More than half (n 5 447) of the study participants showed IgE sensitization to at least 1 allergen, most of them (n 5 400) to aeroallergens (Phadiatop). We identified statistically significant negative and positive associations with 24 HLA class II alleles. These have been reported to confer risk or protection from variety of diseases; however, only a few have previously been associated with allergy in other populations. Conclusions: Our study reveals several new risk and protective genetic markers for allergen-specific IgE sensitization. This is a first and essential step toward a better understanding of the origins of allergic diseases in this understudied population. (J Allergy Clin Immunol Global 2023;2:100117.

Harnessing large language models (LLMs) for candidate gene prioritization and selection.

BACKGROUND: Feature selection is a critical step for translating advances afforded by systems-scale molecular profiling into actionable clinical insights. While data-driven methods are commonly utilized for selecting candidate genes, knowledge-driven methods must contend with the challenge of efficiently sifting through extensive volumes of biomedical information. This work aimed to assess the utility of large language models (LLMs) for knowledge-driven gene prioritization and selection. METHODS: In this proof of concept, we focused on 11 blood transcriptional modules associated with an Erythroid cells signature. We evaluated four leading LLMs across multiple tasks. Next, we established a workflow leveraging LLMs. The steps consisted of: (1) Selecting one of the 11 modules; (2) Identifying functional convergences among constituent genes using the LLMs; (3) Scoring candidate genes across six criteria capturing the gene\u27s biological and clinical relevance; (4) Prioritizing candidate genes and summarizing justifications; (5) Fact-checking justifications and identifying supporting references; (6) Selecting a top candidate gene based on validated scoring justifications; and (7) Factoring in transcriptome profiling data to finalize the selection of the top candidate gene. RESULTS: Of the four LLMs evaluated, OpenAI\u27s GPT-4 and Anthropic\u27s Claude demonstrated the best performance and were chosen for the implementation of the candidate gene prioritization and selection workflow. This workflow was run in parallel for each of the 11 erythroid cell modules by participants in a data mining workshop. Module M9.2 served as an illustrative use case. The 30 candidate genes forming this module were assessed, and the top five scoring genes were identified as BCL2L1, ALAS2, SLC4A1, CA1, and FECH. Researchers carefully fact-checked the summarized scoring justifications, after which the LLMs were prompted to select a top candidate based on this information. GPT-4 initially chose BCL2L1, while Claude selected ALAS2. When transcriptional profiling data from three reference datasets were provided for additional context, GPT-4 revised its initial choice to ALAS2, whereas Claude reaffirmed its original selection for this module. CONCLUSIONS: Taken together, our findings highlight the ability of LLMs to prioritize candidate genes with minimal human intervention. This suggests the potential of this technology to boost productivity, especially for tasks that require leveraging extensive biomedical knowledge

Detection of Antinuclear Antibodies Targeting Intracellular Signal Transduction, Metabolism, Apoptotic Processes and Cell Death in Critical COVID-19 Patients

Background and Objectives: The heterogeneity of the coronavirus disease of 2019 (COVID-19) lies within its diverse symptoms and severity, ranging from mild to lethal. Acute respiratory distress syndrome (ARDS) is a leading cause of mortality in COVID-19 patients, characterized by a hyper cytokine storm. Autoimmunity is proposed to occur as a result of COVID-19, given the high similarity of the immune responses observed in COVID-19 and autoimmune diseases. Here, we investigate the level of autoimmune antibodies in COVID-19 patients with different severities. Results: Initial screening for antinuclear antibodies (ANA) IgG using ELISA revealed that 1.58% (2/126) and 4% (5/126) of intensive care unit (ICU) COVID-19 cases expressed strong and moderate ANA levels, respectively. An additional sample was positive with immunofluorescence assays (IFA) screening. However, all the non-ICU cases (n=273) were ANA negative using both assays. Samples positive for ANA were further confirmed with large-scale autoantibody screening by phage immunoprecipitation-sequencing (PhIP-Seq). The majority of the ANA-positive samples showed "speckled" ANA pattern by microscopy and revealed autoantibody specificities that targeted proteins involved in intracellular signal transduction, metabolism, apoptotic processes, and cell death by PhIP-Seq; further denoting reactivity to nuclear and cytoplasmic antigens. Conclusion: Our results further support the notion of routine screening for autoimmune responses in COVID-19 patients, which might help improve disease prognosis and patient management. Further, results provide compelling evidence that ANA-positive individuals should be excluded from being donors for convalescent plasma therapy in the context of COVID-19.This study was supported by funds from QNRF, grant # NPRP11S-1212-170092

Distinct antibody repertoires against endemic human coronaviruses in children and adults.

Four endemic human coronaviruses (HCoVs) are commonly associated with acute respiratory infection in humans. B cell responses to these "common cold" viruses remain incompletely understood. Here we report a comprehensive analysis of CoV-specific antibody repertoires in 231 children and 1168 adults using phage-immunoprecipitation sequencing. Seroprevalence of antibodies to endemic HCoVs ranged between ~4 and 27% depending on the species and cohort. We identified at least 136 novel linear B cell epitopes. Antibody repertoires against endemic HCoVs were qualitatively different between children and adults in that anti-HCoV IgG specificities more frequently found among children targeted functionally important and structurally conserved regions of the spike, nucleocapsid and matrix proteins. Moreover, antibody specificities targeting the highly conserved fusion peptide region and S2' cleavage site of the spike protein were broadly cross-reactive with peptides of epidemic human and non-human coronaviruses. In contrast, an acidic tandem repeat in the N-terminal region of the Nsp3 subdomain of the HCoV-HKU1 polyprotein was the predominant target of antibody responses in adult donors. Our findings shed light on the dominant species-specific and pan-CoV target sites of human antibody responses to coronavirus infection, thereby providing important insights for the development of prophylactic or therapeutic monoclonal antibodies and vaccine design.This work was supported in part by a grant from the Qatar National Research Fund (PPM1-1220-150017) and funds from Sidra Medicine. I Meyts is a Senior Clinical Investigator at the Research Foundation — Flanders and is supported by the CSL Behring Chair of Primary Immunodeficiencies; by the KU Leuven C1 grant C16/18/007; by a VIB GC PID grant; by FWO grants G0C8517N, G0B5120N, and G0E8420N; and by the Jeffrey Modell Foundation. The ULB Center of Human Genetics is supported by the Fonds Erasme

Human MCTS1-dependent translation of JAK2 is essential for IFN-γ immunity to mycobacteria.

Human inherited disorders of interferon-gamma (IFN-γ) immunity underlie severe mycobacterial diseases. We report X-linked recessive MCTS1 deficiency in men with mycobacterial disease from kindreds of different ancestries (from China, Finland, Iran, and Saudi Arabia). Complete deficiency of this translation re-initiation factor impairs the translation of a subset of proteins, including the kinase JAK2 in all cell types tested, including T lymphocytes and phagocytes. JAK2 expression is sufficiently low to impair cellular responses to interleukin-23 (IL-23) and partially IL-12, but not other JAK2-dependent cytokines. Defective responses to IL-23 preferentially impair the production of IFN-γ by innate-like adaptive mucosal-associated invariant T cells (MAIT) and γδ T lymphocytes upon mycobacterial challenge. Surprisingly, the lack of MCTS1-dependent translation re-initiation and ribosome recycling seems to be otherwise physiologically redundant in these patients. These findings suggest that X-linked recessive human MCTS1 deficiency underlies isolated mycobacterial disease by impairing JAK2 translation in innate-like adaptive T lymphocytes, thereby impairing the IL-23-dependent induction of IFN-γ

Inherited Human ITK Deficiency Impairs IFN-γ Immunity and Underlies Tuberculosis

Inborn errors of IFN-γ immunity can underlie tuberculosis (TB). We report three patients from two kindreds without EBV viremia or disease but with severe TB and inherited complete ITK deficiency, a condition associated with severe EBV disease that renders immunological studies challenging. They have CD4+ αβ T lymphocytopenia with a concomitant expansion of CD4-CD8- double-negative (DN) αβ and Vδ2- γδ T lymphocytes, both displaying a unique CD38+CD45RA+T-bet+EOMES- phenotype. Itk-deficient mice recapitulated an expansion of the γδ T and DN αβ T lymphocyte populations in the thymus and spleen, respectively. Moreover, the patients\u27 T lymphocytes secrete small amounts of IFN-γ in response to TCR crosslinking, mitogens, or forced synapse formation with autologous B lymphocytes. Finally, the patients\u27 total lymphocytes secrete small amounts of IFN-γ, and CD4+, CD8+, DN αβ T, Vδ2+ γδ T, and MAIT cells display impaired IFN-γ production in response to BCG. Inherited ITK deficiency undermines the development and function of various IFN-γ-producing T cell subsets, thereby underlying TB

Modularity in protein structures: study on all-alpha proteins

<div><p>Modularity is known as one of the most important features of protein’s robust and efficient design. The architecture and topology of proteins play a vital role by providing necessary robust scaffolds to support organism’s growth and survival in constant evolutionary pressure. These complex biomolecules can be represented by several layers of modular architecture, but it is pivotal to understand and explore the smallest biologically relevant structural component. In the present study, we have developed a component-based method, using protein’s secondary structures and their arrangements (i.e. patterns) in order to investigate its structural space. Our result on all-alpha protein shows that the known structural space is highly populated with limited set of structural patterns. We have also noticed that these frequently observed structural patterns are present as modules or “building blocks” in large proteins (i.e. higher secondary structure content). From structural descriptor analysis, observed patterns are found to be within similar deviation; however, frequent patterns are found to be distinctly occurring in diverse functions e.g. in enzymatic classes and reactions. In this study, we are introducing a simple approach to explore protein structural space using combinatorial- and graph-based geometry methods, which can be used to describe modularity in protein structures. Moreover, analysis indicates that protein function seems to be the driving force that shapes the known structure space.</p></div

Associations between HLA class II alleles and IgE sensitization to allergens in the Qatar Biobank cohort

Background: Allergic disorders are the consequence of IgE sensitization to allergens. Population studies have shown that certain human leukocyte antigen (HLA) alleles are associated with increased or decreased risk of developing allergy. Objective: We aimed to characterize the relationship between HLA class II allelic diversity and IgE sensitization in an understudied Arab population. Methods: We explored associations between IgE sensitization to 7 allergen mixes and mesquite (comprising 41 food or aeroallergens) and 45 common classical HLA class II alleles in a well-defined cohort of 797 individuals representing the general adult population of Qatari nationals and long-term residents. To do so, we performed HLA calling from whole genome sequencing data at 2-field resolution using 2 independent algorithms. We then applied 3 different regression models to assess either each allergen mix independently, in the context of IgE sensitization to other allergens tested, or polysensitization. Results: More than half (n = 447) of the study participants showed IgE sensitization to at least 1 allergen, most of them (n = 400) to aeroallergens (Phadiatop). We identified statistically significant negative and positive associations with 24 HLA class II alleles. These have been reported to confer risk or protection from variety of diseases; however, only a few have previously been associated with allergy in other populations. Conclusions: Our study reveals several new risk and protective genetic markers for allergen-specific IgE sensitization. This is a first and essential step toward a better understanding of the origins of allergic diseases in this understudied population

Virome-wide serological profiling reveals association of herpesviruses with obesity

The relationship between viral infection and obesity has been known for several decades but epidemiological data is limited to only a few viral pathogens. The association between obesity and a wide range of viruses was assessed using VirScan, a pan-viral serological profiling tool. Serum specimens from 457 Qatari adults (lean = 184; obese = 273) and 231 Qatari children (lean = 111; obese = 120) were analyzed by VirScan. Associations with obesity were determined by odds ratio (OR) and Fisher’s test (p values), and by multivariate regression analysis to adjust for age and gender. Although there was no association of viral infections with obesity in the pediatric population, a nominal association of obesity with seropositivity to members of the Herpesviridae family is observed for the adult population (OR = 1.5–3.3; p Other Information Published in: Scientific Reports License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1038/s41598-021-82213-4</p