Artificial Intelligence and Machine Learning for Inborn Errors of Immunity: Current State and Future Promise.

Artificial intelligence (AI) and machine learning (ML) research within medicine has exponentially increased over the last decade, with studies showcasing the potential of AI/ML algorithms to improve clinical practice and outcomes. Ongoing research and efforts to develop AI-based models have expanded to aid in the identification of inborn errors of immunity (IEI). The use of larger electronic health record data sets, coupled with advances in phenotyping precision and enhancements in ML techniques, has the potential to significantly improve the early recognition of IEI, thereby increasing access to equitable care.

Enhancing tumor-infiltrating T cells with an exclusive fuel source.

Solid tumors harbor immunosuppressive microenvironments that inhibit tumor infiltrating lymphocytes (TILs) through the voracious consumption of glucose. We sought to restore TIL function by providing them with an exclusive fuel source. The glucose disaccharide cellobiose, which is a building block of cellulose, contains a β-1,4-glycosidic bond that cannot be hydrolyzed by animals (or their tumors), but fungal and bacterial organisms have evolved enzymes to catabolize cellobiose and use the resulting glucose.

Electronic health record signatures identify undiagnosed patients with common variable immunodeficiency disease.

Human inborn errors of immunity include rare disorders entailing functional and quantitative antibody deficiencies due to impaired B cells called the common variable immunodeficiency (CVID) phenotype. Patients with CVID face delayed diagnoses and treatments for 5 to 15 years after symptom onset because the disorders are rare (prevalence of ~1/25,000), and there is extensive heterogeneity in CVID phenotypes, ranging from infections to autoimmunity to inflammatory conditions, overlapping with other more common disorders. The prolonged diagnostic odyssey drives excessive system-wide costs before diagnosis.

Harnessing Biomaterials to Amplify Immunity in Aged Mice through T Memory Stem Cells.

The durability of a protective immune response generated by a vaccine depends on its ability to induce long-term T cell immunity, which tends to decline in aging populations. The longest protection appears to arise from T memory stem cells (TMSCs) that confer high expandability and effector functions when challenged. Here we engineered artificial antigen presenting cells (aAPC) with optimized size, stiffness and activation signals to induce human and mouse CD8 TMSCs .

Proceedings from the inaugural Artificial Intelligence in Primary Immune Deficiencies (AIPID) conference.

Here, we summarize the proceedings of the inaugural Artificial Intelligence in Primary Immune Deficiencies conference, during which experts and advocates gathered to advance research into the applications of artificial intelligence (AI), machine learning, and other computational tools in the diagnosis and management of inborn errors of immunity (IEIs). The conference focused on the key themes of expediting IEI diagnoses, challenges in data collection, roles of natural language processing and large language models in interpreting electronic health records, and ethical considerations in implementation. Innovative AI-based tools trained on electronic health records and claims databases have discovered new patterns of warning signs for IEIs, facilitating faster diagnoses and enhancing patient outcomes.

A Clinicopathological Categorization System for Clinical Research in Coccidioidomycosis.

A wide array of clinical manifestations follow infection with or , ranging from asymptomatic infection to life-threatening pulmonary disease or extrapulmonary dissemination and meningitis. Epidemiological studies require consistent definitions of cases and their comparative clinical features. Understanding host and pathogen determinants of the severity of coccidioidomycosis also requires that specific clinical features (such as coccidioidal meningitis) and their overlap be precisely defined and quantified.

Whole blood transcriptomics identifies subclasses of pediatric septic shock.

Background: Sepsis is a highly heterogeneous syndrome, which has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies.

Whole Blood Transcriptomics Identifies Subclasses of Pediatric Septic Shock.

Background: Sepsis is a highly heterogeneous syndrome, that has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies.

Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19.

Background: We previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15-20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in ~ 80% of cases.

Methods: We report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia.

Systemic enhancement of antitumour immunity by peritumourally implanted immunomodulatory macroporous scaffolds.

A tumour microenvironment abundant in regulatory T (T) cells aids solid tumours to evade clearance by effector T cells. Systemic strategies to suppress T cells or to augment immunity can elicit autoimmune side effects, cytokine storms and other toxicities. Here we report the design, fabrication and therapeutic performance of a biodegradable macroporous scaffold, implanted peritumourally, that releases a small-molecule inhibitor of transforming growth factor β to suppress T cells, chemokines to attract effector T cells and antibodies to stimulate them.

Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19.

Background: We previously reported inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity in 1-5% of unvaccinated patients with life-threatening COVID-19, and auto-antibodies against type I IFN in another 15-20% of cases.

Methods: We report here a genome-wide rare variant burden association analysis in 3,269 unvaccinated patients with life-threatening COVID-19 (1,301 previously reported and 1,968 new patients), and 1,373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. A quarter of the patients tested had antibodies against type I IFN (234 of 928) and were excluded from the analysis.

Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative.

Background: Large medical centers in urban areas, like Los Angeles, care for a diverse patient population and offer the potential to study the interplay between genetic ancestry and social determinants of health. Here, we explore the implications of genetic ancestry within the University of California, Los Angeles (UCLA) ATLAS Community Health Initiative-an ancestrally diverse biobank of genomic data linked with de-identified electronic health records (EHRs) of UCLA Health patients (N=36,736).

Methods: We quantify the extensive continental and subcontinental genetic diversity within the ATLAS data through principal component analysis, identity-by-descent, and genetic admixture.

Tuning immunity through tissue mechanotransduction.

Immune responses are governed by signals from the tissue microenvironment, and in addition to biochemical signals, mechanical cues and forces arising from the tissue, its extracellular matrix and its constituent cells shape immune cell function. Indeed, changes in biophysical properties of tissue alter the mechanical signals experienced by cells in many disease conditions, in inflammatory states and in the context of ageing. These mechanical cues are converted into biochemical signals through the process of mechanotransduction, and multiple pathways of mechanotransduction have been identified in immune cells.

Partial RAG deficiency in humans induces dysregulated peripheral lymphocyte development and humoral tolerance defect with accumulation of T-bet B cells.

The recombination-activating genes (RAG) 1 and 2 are indispensable for diversifying the primary B cell receptor repertoire and pruning self-reactive clones via receptor editing in the bone marrow; however, the impact of RAG1/RAG2 on peripheral tolerance is unknown. Partial RAG deficiency (pRD) manifesting with late-onset immune dysregulation represents an 'experiment of nature' to explore this conundrum. By studying B cell development and subset-specific repertoires in pRD, we demonstrate that reduced RAG activity impinges on peripheral tolerance through the generation of a restricted primary B cell repertoire, persistent antigenic stimulation and an inflammatory milieu with elevated B cell-activating factor.

Immunomodulatory Microneedle Patch for Periodontal Tissue Regeneration.

Periodontal diseases are caused by microbial infection and the recruitment of destructive immune cells. Current therapies mainly deal with bacteria elimination, but the regeneration of periodontal tissues remains a challenge. Here we developed a modular microneedle (MN) patch that delivered both antibiotic and cytokines into the local gingival tissue to achieve immunomodulation and tissue regeneration.