The Immunobiology and Treatment of Food Allergy.

IgE-mediated food allergy (IgE-FA) occurs due to a breakdown in immune tolerance that leads to a detrimental type 2 helper T cell (TH2) adaptive immune response. While the processes governing this loss of tolerance are incompletely understood, several host-related and environmental factors impacting the risk of IgE-FA development have been identified. Mounting evidence supports the role of an impaired epithelial barrier in the development of IgE-FA, with exposure of allergens through damaged skin and gut epithelium leading to the aberrant production of alarmins and activation of TH2-type allergic inflammation. The treatment of IgE-FA has historically been avoidance with acute management of allergic reactions, but advances in allergen-specific immunotherapy and the development of biologics and other novel therapeutics are rapidly changing the landscape of food allergy treatment. Here, we discuss the pathogenesis and immunobiology of IgE-FA in addition to its diagnosis, prognosis, and treatment.

A trans-complementation system for SARS-CoV-2 recapitulates authentic viral replication without virulence.

The biosafety level 3 (BSL-3) requirement to culture severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a bottleneck for research. Here, we report a trans-complementation system that produces single-round infectious SARS-CoV-2 that recapitulates authentic viral replication. We demonstrate that the single-round infectious SARS-CoV-2 can be used at BSL-2 laboratories for high-throughput neutralization and antiviral testing. The trans-complementation system consists of two components: a genomic viral RNA containing ORF3 and envelope gene deletions, as well as mutated transcriptional regulator sequences, and a producer cell line expressing the two deleted genes. Trans-complementation of the two components generates virions that can infect naive cells for only one round but does not produce wild-type SARS-CoV-2. Hamsters and K18-hACE2 transgenic mice inoculated with the complementation-derived virions exhibited no detectable disease, even after intracranial inoculation with the highest possible dose. Thus, the trans-complementation platform can be safely used at BSL-2 laboratories for research and countermeasure development.

The next horizon in precision oncology: Proteogenomics to inform cancer diagnosis and treatment.

When it comes to precision oncology, proteogenomics may provide better prospects to the clinical characterization of tumors, help make a more accurate diagnosis of cancer, and improve treatment for patients with cancer. This perspective describes the significant contributions of The Cancer Genome Atlas and the Clinical Proteomic Tumor Analysis Consortium to precision oncology and makes the case that proteogenomics needs to be fully integrated into clinical trials and patient care in order for precision oncology to deliver the right cancer treatment to the right patient at the right dose and at the right time.

Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.

Screening for lung cancer: 2023 guideline update from the American Cancer Society.

Lung cancer is the leading cause of mortality and person-years of life lost from cancer among US men and women. Early detection has been shown to be associated with reduced lung cancer mortality. Our objective was to update the American Cancer Society (ACS) 2013 lung cancer screening (LCS) guideline for adults at high risk for lung cancer. The guideline is intended to provide guidance for screening to health care providers and their patients who are at high risk for lung cancer due to a history of smoking. The ACS Guideline Development Group (GDG) utilized a systematic review of the LCS literature commissioned for the US Preventive Services Task Force 2021 LCS recommendation update; a second systematic review of lung cancer risk associated with years since quitting smoking (YSQ); literature published since 2021; two Cancer Intervention and Surveillance Modeling Network-validated lung cancer models to assess the benefits and harms of screening; an epidemiologic and modeling analysis examining the effect of YSQ and aging on lung cancer risk; and an updated analysis of benefit-to-radiation-risk ratios from LCS and follow-up examinations. The GDG also examined disease burden data from the National Cancer Institute's Surveillance, Epidemiology, and End Results program. Formulation of recommendations was based on the quality of the evidence and judgment (incorporating values and preferences) about the balance of benefits and harms. The GDG judged that the overall evidence was moderate and sufficient to support a strong recommendation for screening individuals who meet the eligibility criteria. LCS in men and women aged 50-80 years is associated with a reduction in lung cancer deaths across a range of study designs, and inferential evidence supports LCS for men and women older than 80 years who are in good health. The ACS recommends annual LCS with low-dose computed tomography for asymptomatic individuals aged 50-80 years who currently smoke or formerly smoked and have a ≥20 pack-year smoking history (strong recommendation, moderate quality of evidence). Before the decision is made to initiate LCS, individuals should engage in a shared decision-making discussion with a qualified health professional. For individuals who formerly smoked, the number of YSQ is not an eligibility criterion to begin or to stop screening. Individuals who currently smoke should receive counseling to quit and be connected to cessation resources. Individuals with comorbid conditions that substantially limit life expectancy should not be screened. These recommendations should be considered by health care providers and adults at high risk for lung cancer in discussions about LCS. If fully implemented, these recommendations have a high likelihood of significantly reducing death and suffering from lung cancer in the United States.

Clinical insights into small cell lung cancer: Tumor heterogeneity, diagnosis, therapy, and future directions.

Small cell lung cancer (SCLC) is characterized by rapid growth and high metastatic capacity. It has strong epidemiologic and biologic links to tobacco carcinogens. Although the majority of SCLCs exhibit neuroendocrine features, an important subset of tumors lacks these properties. Genomic profiling of SCLC reveals genetic instability, almost universal inactivation of the tumor suppressor genes TP53 and RB1, and a high mutation burden. Because of early metastasis, only a small fraction of patients are amenable to curative-intent lung resection, and these individuals require adjuvant platinum-etoposide chemotherapy. Therefore, the vast majority of patients are currently being treated with chemoradiation with or without immunotherapy. In patients with disease confined to the chest, standard therapy includes thoracic radiotherapy and concurrent platinum-etoposide chemotherapy. Patients with metastatic (extensive-stage) disease are treated with a combination of platinum-etoposide chemotherapy plus immunotherapy with an anti-programmed death-ligand 1 monoclonal antibody. Although SCLC is initially very responsive to platinum-based chemotherapy, these responses are transient because of the development of drug resistance. In recent years, the authors have witnessed an accelerating pace of biologic insights into the disease, leading to the redefinition of the SCLC classification scheme. This emerging knowledge of SCLC molecular subtypes has the potential to define unique therapeutic vulnerabilities. Synthesizing these new discoveries with the current knowledge of SCLC biology and clinical management may lead to unprecedented advances in SCLC patient care. Here, the authors present an overview of multimodal clinical approaches in SCLC, with a special focus on illuminating how recent advancements in SCLC research could accelerate clinical development.

Severe combined immunodeficiency diagnosis and genetic defects.

Severe combined immunodeficiency (SCID) is a rare and life-threatening genetic disorder that severely impairs the immune system's ability to defend the body against infections. Often referred to as the "bubble boy" disease, SCID gained widespread recognition due to the case of David Vetter, a young boy who lived in a sterile plastic bubble to protect him from germs. SCID is typically present at birth, and it results from genetic mutations that affect the development and function of immune cells, particularly T cells and B cells. These immune cells are essential for identifying and fighting off infections caused by viruses, bacteria, and fungi. In SCID patients, the immune system is virtually non-existent, leaving them highly susceptible to recurrent, severe infections. There are several forms of SCID, with varying degrees of severity, but all share common features. Newborns with SCID often exhibit symptoms such as chronic diarrhea, thrush, skin rashes, and persistent infections that do not respond to standard treatments. Without prompt diagnosis and intervention, SCID can lead to life-threatening complications and a high risk of mortality. There are over 20 possible affected genes. Treatment options for SCID primarily involve immune reconstitution, with the most well-known approach being hematopoietic stem cell transplantation (HSCT). Alternatively, gene therapy is also available for some forms of SCID. Once treated successfully, SCID patients can lead relatively normal lives, but they may still require vigilant infection control measures and lifelong medical follow-up to manage potential complications. In conclusion, severe combined immunodeficiency is a rare but life-threatening genetic disorder that severely compromises the immune system's function, rendering affected individuals highly vulnerable to infections. Early diagnosis and appropriate treatment are fundamental. With this respect, newborn screening is progressively and dramatically improving the prognosis of SCID.

The role of exosomes in cancer-related programmed cell death.

Cancer arises from the growth and division of uncontrolled erroneous cells. Programmed cell death (PCD), or regulated cell death (RCD), includes natural processes that eliminate damaged or abnormal cells. Dysregulation of PCD is a hallmark of cancer, as cancer cells often evade cell death and continue to proliferate. Exosomes nanoscale extracellular vesicles secreted by different types of cells carrying a variety of molecules, including nucleic acids, proteins, and lipids, to have indispensable role in the communication between cells, and can influence various cellular processes, including PCD. Exosomes have been shown to modulate PCD in cancer cells by transferring pro- or antideath molecules to neighboring cells. Additionally, exosomes can facilitate the spread of PCD to surrounding cancer cells, making them promising in the treatment of various cancers. The exosomes' diagnostic potential in cancer is also an active area of research. Exosomes can be isolated from a wide range of bodily fluids and tissues, such as blood and urine, and can provide a noninvasive way to monitor cancer progression and treatment response. Furthermore, exosomes have also been employed as a delivery system for therapeutic agents. By engineering exosomes to carry drugs or other therapeutic molecules, they can be targeted specifically to cancer cells, reducing toxicity to healthy tissues. Here, we discussed exosomes in the diagnosis and prevention of cancers, tumor immunotherapy, and drug delivery, as well as in different types of PCD.

Extracellular vesicles as modifiers of epigenomic profiles.

Extracellular vesicles (EVs), emerging as novel mediators between intercellular communication, encapsulate distinct bioactive cargoes to modulate multiple biological events, such as epigenetic remodeling. In essence, EVs and epigenomic profiles are tightly linked and reciprocally regulated. Epigenetic factors, including histone and DNA modifications, noncoding RNAs, and protein post-translational modifications (PTMs) dynamically regulate EV biogenesis to contribute to EV heterogeneity. Alternatively, EVs actively modify DNA, RNA, and histone profiles in recipient cells by delivering RNA and protein cargoes for downstream epigenetic enzyme regulation. Moreover, EVs display great potential as diagnostic markers and drug-delivery vehicles for therapeutic applications. The combination of parental cell epigenomic modification with single EV characterization would be a promising strategy for EV engineering to enhance the epidrug loading efficacy and accuracy.

An interactive atlas of three-dimensional syndromic facial morphology.

Craniofacial phenotyping is critical for both syndrome delineation and diagnosis because craniofacial abnormalities occur in 30% of characterized genetic syndromes. Clinical reports, textbooks, and available software tools typically provide two-dimensional, static images and illustrations of the characteristic phenotypes of genetic syndromes. In this work, we provide an interactive web application that provides three-dimensional, dynamic visualizations for the characteristic craniofacial effects of 95 syndromes. Users can visualize syndrome facial appearance estimates quantified from data and easily compare craniofacial phenotypes of different syndromes. Our application also provides a map of morphological similarity between a target syndrome and other syndromes. Finally, users can upload 3D facial scans of individuals and compare them to our syndrome atlas estimates. In summary, we provide an interactive reference for the craniofacial phenotypes of syndromes that allows for precise, individual-specific comparisons of dysmorphology.

The clinical utility and diagnostic implementation of human subject cell transdifferentiation followed by RNA sequencing.

RNA sequencing (RNA-seq) has recently been used in translational research settings to facilitate diagnoses of Mendelian disorders. A significant obstacle for clinical laboratories in adopting RNA-seq is the low or absent expression of a significant number of disease-associated genes/transcripts in clinically accessible samples. As this is especially problematic in neurological diseases, we developed a clinical diagnostic approach that enhanced the detection and evaluation of tissue-specific genes/transcripts through fibroblast-to-neuron cell transdifferentiation. The approach is designed specifically to suit clinical implementation, emphasizing simplicity, cost effectiveness, turnaround time, and reproducibility. For clinical validation, we generated induced neurons (iNeurons) from 71 individuals with primary neurological phenotypes recruited to the Undiagnosed Diseases Network. The overall diagnostic yield was 25.4%. Over a quarter of the diagnostic findings benefited from transdifferentiation and could not be achieved by fibroblast RNA-seq alone. This iNeuron transcriptomic approach can be effectively integrated into diagnostic whole-transcriptome evaluation of individuals with genetic disorders.

Accurate estimation of biological age and its application in disease prediction using a multimodal image Transformer system.

Aging in an individual refers to the temporal change, mostly decline, in the body's ability to meet physiological demands. Biological age (BA) is a biomarker of chronological aging and can be used to stratify populations to predict certain age-related chronic diseases. BA can be predicted from biomedical features such as brain MRI, retinal, or facial images, but the inherent heterogeneity in the aging process limits the usefulness of BA predicted from individual body systems. In this paper, we developed a multimodal Transformer-based architecture with cross-attention which was able to combine facial, tongue, and retinal images to estimate BA. We trained our model using facial, tongue, and retinal images from 11,223 healthy subjects and demonstrated that using a fusion of the three image modalities achieved the most accurate BA predictions. We validated our approach on a test population of 2,840 individuals with six chronic diseases and obtained significant difference between chronological age and BA (AgeDiff) than that of healthy subjects. We showed that AgeDiff has the potential to be utilized as a standalone biomarker or conjunctively alongside other known factors for risk stratification and progression prediction of chronic diseases. Our results therefore highlight the feasibility of using multimodal images to estimate and interrogate the aging process.

Pan-cancer scRNA-seq analysis reveals immunological and diagnostic significance of the peripheral blood mononuclear cells.

Peripheral blood mononuclear cells (PBMCs) reflect systemic immune response during cancer progression. However, a comprehensive understanding of the composition and function of PBMCs in cancer patients is lacking, and the potential of these features to assist cancer diagnosis is also unclear. Here, the compositional and status differences between cancer patients and healthy donors in PBMCs were investigated by single-cell RNA sequencing (scRNA-seq), involving 262,025 PBMCs from 68 cancer samples and 14 healthy samples. We observed an enhanced activation and differentiation of most immune subsets in cancer patients, along with reduction of naïve T cells, expansion of macrophages, impairment of NK cells and myeloid cells, as well as tumor promotion and immunosuppression. Based on characteristics including differential cell type abundances and/or hub genes identified from weight gene co-expression network analysis (WGCNA) modules of each major cell type, we applied logistic regression to construct cancer diagnosis models. Furthermore, we found that the above models can distinguish cancer patients and healthy donors with high sensitivity. Our study provided new insights into using the features of PBMCs in non-invasive cancer diagnosis.

Comparative analysis of in-silico tools in identifying pathogenic variants in dominant inherited retinal diseases.

Inherited retinal diseases (IRDs) are a group of rare genetic eye conditions that cause blindness. Despite progress in identifying genes associated with IRDs, improvements are necessary for classifying rare autosomal dominant (AD) disorders. AD diseases are highly heterogenous, with causal variants being restricted to specific amino acid changes within certain protein domains, making AD conditions difficult to classify. Here, we aim to determine the top-performing in-silico tools for predicting the pathogenicity of AD IRD variants. We annotated variants from ClinVar and benchmarked 39 variant classifier tools on IRD genes, split by inheritance pattern. Using area-under-the-curve (AUC) analysis, we determined the top-performing tools and defined thresholds for variant pathogenicity. Top-performing tools were assessed using genome sequencing on a cohort of participants with IRDs of unknown etiology. MutScore achieved the highest accuracy within AD genes, yielding an AUC of 0.969. When filtering for AD gain-of-function and dominant negative variants, BayesDel had the highest accuracy with an AUC of 0.997. Five participants with variants in NR2E3, RHO, GUCA1A, and GUCY2D were confirmed to have dominantly inherited disease based on pedigree, phenotype, and segregation analysis. We identified two uncharacterized variants in GUCA1A (c.428T>A, p.Ile143Thr) and RHO (c.631C>G, p.His211Asp) in three participants. Our findings support using a multi-classifier approach comprised of new missense classifier tools to identify pathogenic variants in participants with AD IRDs. Our results provide a foundation for improved genetic diagnosis for people with IRDs.

DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data.

DECIPHER (Database of Genomic Variation and Phenotype in Humans Using Ensembl Resources) shares candidate diagnostic variants and phenotypic data from patients with genetic disorders to facilitate research and improve the diagnosis, management, and therapy of rare diseases. The platform sits at the boundary between genomic research and the clinical community. DECIPHER aims to ensure that the most up-to-date data are made rapidly available within its interpretation interfaces to improve clinical care. Newly integrated cardiac case-control data that provide evidence of gene-disease associations and inform variant interpretation exemplify this mission. New research resources are presented in a format optimized for use by a broad range of professionals supporting the delivery of genomic medicine. The interfaces within DECIPHER integrate and contextualize variant and phenotypic data, helping to determine a robust clinico-molecular diagnosis for rare-disease patients, which combines both variant classification and clinical fit. DECIPHER supports discovery research, connecting individuals within the rare-disease community to pursue hypothesis-driven research.

Contribution and therapeutic implications of retroelement insertions in ataxia telangiectasia.

Certain classes of genetic variation still escape detection in clinical sequencing analysis. One such class is retroelement insertion, which has been reported as a cause of Mendelian diseases and may offer unique therapeutic implications. Here, we conducted retroelement profiling on whole-genome sequencing data from a cohort of 237 individuals with ataxia telangiectasia (A-T). We found 15 individuals carrying retroelement insertions in ATM, all but one of which integrated in noncoding regions. Systematic functional characterization via RNA sequencing, RT-PCR, and/or minigene splicing assays showed that 12 out of 14 intronic insertions led or contributed to ATM loss of function by exon skipping or activating cryptic splice sites. We also present proof-of-concept antisense oligonucleotides that suppress cryptic exonization caused by a deep intronic retroelement insertion. These results provide an initial systematic estimate of the contribution of retroelements to the genetic architecture of recessive Mendelian disorders as ∼2.1%-5.5%. Our study highlights the importance of retroelement insertions as causal variants and therapeutic targets in genetic diseases.

Salt Sensitivity of Blood Pressure.

The year 2024 marks the centennial of the initiation of the American Heart Association. Over the past 100 years, the American Heart Association has led groundbreaking discoveries in cardiovascular disease including salt sensitivity of blood pressure, which has been studied since the mid-1900s. Salt sensitivity of blood pressure is an important risk factor for cardiovascular events, but the phenotype remains unclear because of insufficient understanding of the underlying mechanisms and lack of feasible diagnostic tools. In honor of this centennial, we commemorate the initial discovery of salt sensitivity of blood pressure and chronicle the subsequent scientific discoveries and efforts to mitigate salt-induced cardiovascular disease with American Heart Association leading the way. We also highlight determinants of the pathophysiology of salt sensitivity of blood pressure in humans and recent developments in diagnostic methods and future prospects.

Proteomics-Derived Biomarker Panel Facilitates Distinguishing Primary Lung Adenocarcinomas With Intestinal or Mucinous Differentiation From Lung Metastatic Colorectal Cancer.

The diagnosis of primary lung adenocarcinomas with intestinal or mucinous differentiation (PAIM) remains challenging due to the overlapping histomorphological, immunohistochemical (IHC), and genetic characteristics with lung metastatic colorectal cancer (lmCRC). This study aimed to explore the protein biomarkers that could distinguish between PAIM and lmCRC. To uncover differences between the two diseases, we used tandem mass tagging-based shotgun proteomics to characterize proteomes of formalin-fixed, paraffin-embedded tumor samples of PAIM (n = 22) and lmCRC (n = 17).Then three machine learning algorithms, namely support vector machine (SVM), random forest, and the Least Absolute Shrinkage and Selection Operator, were utilized to select protein features with diagnostic significance. These candidate proteins were further validated in an independent cohort (PAIM, n = 11; lmCRC, n = 19) by IHC to confirm their diagnostic performance. In total, 105 proteins out of 7871 proteins were significantly dysregulated between PAIM and lmCRC samples and well-separated two groups by Uniform Manifold Approximation and Projection. The upregulated proteins in PAIM were involved in actin cytoskeleton organization, platelet degranulation, and regulation of leukocyte chemotaxis, while downregulated ones were involved in mitochondrial transmembrane transport, vasculature development, and stem cell proliferation. A set of ten candidate proteins (high-level expression in lmCRC: CDH17, ATP1B3, GLB1, OXNAD1, LYST, FABP1; high-level expression in PAIM: CK7 (an established marker), NARR, MLPH, S100A14) was ultimately selected to distinguish PAIM from lmCRC by machine learning algorithms. We further confirmed using IHC that the five protein biomarkers including CDH17, CK7, MLPH, FABP1 and NARR were effective biomarkers for distinguishing PAIM from lmCRC. Our study depicts PAIM-specific proteomic characteristics and demonstrates the potential utility of new protein biomarkers for the differential diagnosis of PAIM and lmCRC. These findings may contribute to improving the diagnostic accuracy and guide appropriate treatments for these patients.

Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring.

Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.

An updated list of eumycetoma causative agents and their differences in grain formation and treatment response.

SUMMARYIn 2023, the World Health Organization designated eumycetoma causative agents as high-priority pathogens on its list of fungal priority pathogens. Despite this recognition, a comprehensive understanding of these causative agents is lacking, and potential variations in clinical manifestations or therapeutic responses remain unclear. In this review, 12,379 eumycetoma cases were reviewed. In total, 69 different fungal species were identified as causative agents. However, some were only identified once, and there was no supporting evidence that they were indeed present in the grain. Madurella mycetomatis was by far the most commonly reported fungal causative agent. In most studies, identification of the fungus at the species level was based on culture or histology, which was prone to misidentifications. The newly used molecular identification tools identified new causative agents. Clinically, no differences were reported in the appearance of the lesion, but variations in mycetoma grain formation and antifungal susceptibility were observed. Although attempts were made to explore the differences in clinical outcomes based on antifungal susceptibility, the lack of large clinical trials and the inclusion of surgery as standard treatment posed challenges in drawing definitive conclusions. Limited case series suggested that eumycetoma cases caused by Fusarium species were less responsive to treatment than those caused by Madurella mycetomatis. However, further research is imperative for a comprehensive understanding.