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At least 19 recordsLinked to original sources
PubMed2024

Neutralizing IFN-γ autoantibodies are rare and pathogenic in HLA-DRB1*15:02 or 16:02 individuals.

BACKGROUNDWeakly virulent environmental mycobacteria (EM) can cause severe disease in HLA-DRB1*15:02 or 16:02 adults harboring neutralizing anti-IFN-γ autoantibodies (nAIGAs). The overall prevalence of nAIGAs in the general population is unknown, as are the penetrance of nAIGAs in HLA-DRB1*15:02 or 16:02 individuals and the proportion of patients with unexplained, adult-onset EM infections carrying nAIGAs.METHODSThis study analyzed the detection and neutralization of anti-IFN-γ autoantibodies (auto-Abs) from 8,430 healthy individuals of the general population, 257 HLA-DRB1*15:02 or 16:02 carriers, 1,063 patients with autoimmune disease, and 497 patients with unexplained severe disease due to EM.RESULTSWe found that anti-IFN-γ auto-Abs detected in 4,148 of 8,430 healthy individuals (49.2%) from the general population of an unknown HLA-DRB1 genotype were not neutralizing. Moreover, we did not find nAIGAs in 257 individuals carrying HLA-DRB1* 15:02 or 16:02. Additionally, nAIGAs were absent in 1,063 patients with an autoimmune disease. Finally, 7 of 497 patients (1.4%) with unexplained severe disease due to EM harbored nAIGAs.CONCLUSIONThese findings suggest that nAIGAs are isolated and that their penetrance in HLA-DRB1*15:02 or 16:02 individuals is low, implying that they may be triggered by rare germline or somatic variants. In contrast, the risk of mycobacterial disease in patients with nAIGAs is high, confirming that these nAIGAs are the cause of EM disease.FUNDINGThe Laboratory of Human Genetics of Infectious Diseases is supported by the Howard Hughes Medical Institute, the Rockefeller University, the St. Giles Foundation, the National Institutes of Health (NIH) (R01AI095983 and U19AIN1625568), the National Center for Advancing Translational Sciences (NCATS), the NIH Clinical and Translational Science Award (CTSA) program (UL1 TR001866), the French National Research Agency (ANR) under the "Investments for the Future" program (ANR-10-IAHU-01), the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (ANR-10-LABX-62-IBEID), ANR-GENMSMD (ANR-16-CE17-0005-01), ANR-MAFMACRO (ANR-22-CE92-0008), ANRSECTZ170784, the French Foundation for Medical Research (FRM) (EQU201903007798), the ANRS-COV05, ANR GENVIR (ANR-20-CE93-003), and ANR AI2D (ANR-22-CE15-0046) projects, the ANR-RHU program (ANR-21-RHUS-08-COVIFERON), the European Union's Horizon 2020 research and innovation program under grant agreement no. 824110 (EASI-genomics), the Square Foundation, Grandir - Fonds de solidarité pour l'enfance, the Fondation du Souffle, the SCOR Corporate Foundation for Science, the Battersea & Bowery Advisory Group, William E. Ford, General Atlantic's Chairman and Chief Executive Officer, Gabriel Caillaux, General Atlantic's Co-President, Managing Director, and Head of business in EMEA, and the General Atlantic Foundation, Institut National de la Santé et de la Recherche Médicale (INSERM) and of Paris Cité University. JR was supported by the INSERM PhD program for doctors of pharmacy (poste d'accueil INSERM). JR and TLV were supported by the Bettencourt-Schueller Foundation and the MD-PhD program of the Imagine Institute. MO was supported by the David Rockefeller Graduate Program, the Funai Foundation for Information Technology (FFIT), the Honjo International Scholarship Foundation (HISF), and the New York Hideyo Noguchi Memorial Society (HNMS).

Adult↗
PubMed2026

The Subtle Crisis: Public Domain Genomes and the Ethics of Translational Infrastructure.

Public domain human genomic resources are infrastructure: tools researchers use to ask basic biological questions whose answers are then translated into products and care. Translational science now asks them to support an expanding set of tasks, including clinical variant interpretation for diverse populations, pharmacogenomic prescribing, polygenic risk prediction, and the training of clinical artificial intelligence. The corpus of public domain genomes, due in large part to upstream recruitment choices, is not fit for these purposes, and the gap between discovery and translation is widening. This essay argues that closing the gap requires treating public domain genomic infrastructure as a particular object of translational bioethics rather than a technical precondition for it. The limited number of genomes in the public domain relative to the broader genomic record, and the typology-friendliness of how that record represents human variation, are two faces of the same set of upstream choices. Reversing them is not a matter of more sampling under existing terms; it is a matter of building infrastructure of a particular kind; infrastructure made from people. That category, common in genomics but absent from the rest of science, demands an ethical apparatus the field has not yet built. Here we consider the commitments such an apparatus requires, and argue that where, how, and with whom we build genomic infrastructure is itself an ethics question the field has largely declined to ask.

Humans↗
PubMed2026

Research updates in cystic fibrosis related diabetes: Understanding pathophysiology, expanding animal and human islet models, and advancing clinical and translational research.

In 2024-2025, the Cystic Fibrosis Foundation (US) and Cystic Fibrosis Trust (UK) hosted an International CFRD Consortium round-table webinar series for basic science, translational, and clinical researchers with the goal of sharpening mechanistic understanding of CFRD pathogenesis and prioritizing therapeutic development. This review summarizes the research priorities identified in the International CFRD Consortium, including (i) further investigation into the role of pancreatic fibrosis, vascular abnormalities, and α-cell dysfunction in the development of CFRD; (ii) the creation and refinement of novel animal and human cell- and tissue-based models to understand the complex interplay of exocrine and endocrine cells in the CF pancreas; (iii) development and validation of circulating and imaging biomarkers, together with dynamic glucose testing to explore β-cell function and kinetics in people with CF across the dysglycemia spectrum; and (iv) prospective clinical studies to guide CFRD treatment options and investigate the changing landscape of aging, increasing prevalence of obesity and diabetes and their complications in the era of cystic fibrosis transmembrane conductance regulator (CFTR) modulators. Collectively, these priorities aim to accelerate transition from mechanism to intervention and expand evidence-based care for people with CF at risk of, or living with, CFRD.

Humans↗
PubMed2026

Cellular transcriptomic signatures underpinning the heterogeneity of depression in Alzheimer's disease.

INTRODUCTION: Late-onset Alzheimer's disease (LOAD) and major depressive disorder (MDD) share genetic etiologies. Here, we investigated brain transcriptomic landscapes to gain insights into shared and divergent molecular and biological etiologies across LOAD and MDD. METHODS: Brain single-nucleus RNA sequencing (snRNA-seq) datasets from cognitively normal older and young individuals and LOAD patients stratified by comorbid MDD were analyzed to identify differential expressed genes (DEGs). Using cell type-specific DEGs we performed biological pathway and intercellular-communication networks analyses. We investigated shared DEGs across MDD and LOAD cohorts and sex-specific DEGs. Results were validated by comparison with four transcriptomic and proteomic studies of MDD and depression. RESULTS: MDD-associated dysregulated genes and pathways were shared between LOAD and cognitive-normal individuals, including JUNB and DUSP1 in glutamatergic neurons, and PRAM1 and SNX9 in microglia. DEGs shared between the MDD and LOAD cohorts included HSPA1A and NDUFB7 in glutamatergic neurons. Sex interaction analysis identified numerous new DEGs in the MDD cohorts, whereas there were ≈5 to 10 times more DEGs in female than in male individuals. LOAD and MDD common microglial pathways included neuronal injury, stress, peroxisome proliferator-activated receptor (PPAR) signaling and interferon alpha/beta signaling. DISCUSSION: LOAD and MDD exhibited common molecular profiles, dysregulated pathways, and cellular communication changes. MDD develops earlier in life, thus, our findings provide a window into early molecular and biological processes preceding LOAD-onset.

Humans↗
PubMed2025

A Qualitative Study of the Roles and Responsibilities of Academic and Journalistic Publishing in Social and Behavioral Genomics.

The conduct and translation of scientific research is shaped by academic and journalistic publishing. Academic journals issue editorial guidelines and policies that inform how researchers shape and present their studies. Journalists select and report on academic studies for public audiences. Despite the potential importance of journal editors and journalists in the scientific process, little has been done to examine how these groups think about their roles and responsibilities-especially when it comes to ethically sensitive scientific domains like social and behavioral genomics (SBG): the study of whether and how genetic differences between individuals correlate with differences in behaviors such as aggression and outcomes such as educational attainment. To begin filling this gap, we conducted semi-structured interviews with editors working at academic journals that publish SBG research (n = 10) and journalists who have reported on SBG studies (n = 13). Journal editors largely saw themselves as mediators between authors and peer reviewers who help to shepherd along research. Journalists frequently described themselves as translators of science for wide audiences; at times they also saw themselves as interrogators of science. While both groups considered SBG especially ethically sensitive and prone to risks such as misinterpretation, many expressed that systematic ethical review processes and guidelines for SBG are lacking. Further, many deferred the ethical responsibility to minimize risks associated with SBG to others. Our findings highlight the need for more explicit frameworks in academic and journalistic publishing to support the ethically responsible conduct and communication of SBG.

ELSI↗
PubMed2024

Central conducting lymphatic anomaly: from bench to bedside.

Central conducting lymphatic anomaly (CCLA) is a complex lymphatic anomaly characterized by abnormalities of the central lymphatics and may present with nonimmune fetal hydrops, chylothorax, chylous ascites, or lymphedema. CCLA has historically been difficult to diagnose and treat; however, recent advances in imaging, such as dynamic contrast magnetic resonance lymphangiography, and in genomics, such as deep sequencing and utilization of cell-free DNA, have improved diagnosis and refined both genotype and phenotype. Furthermore, in vitro and in vivo models have confirmed genetic causes of CCLA, defined the underlying pathogenesis, and facilitated personalized medicine to improve outcomes. Basic, translational, and clinical science are essential for a bedside-to-bench and back approach for CCLA.

Cell-Free Nucleic Acids↗
PubMed2025

RBC-GEM: A genome-scale metabolic model for systems biology of the human red blood cell.

Advancements with cost-effective, high-throughput omics technologies have had a transformative effect on both fundamental and translational research in the medical sciences. These advancements have facilitated a departure from the traditional view of human red blood cells (RBCs) as mere carriers of hemoglobin, devoid of significant biological complexity. Over the past decade, proteomic analyses have identified a growing number of different proteins present within RBCs, enabling systems biology analysis of their physiological functions. Here, we introduce RBC-GEM, one of the most comprehensive, curated genome-scale metabolic reconstructions of a specific human cell type to-date. It was developed through meta-analysis of proteomic data from 29 studies published over the past two decades resulting in an RBC proteome composed of more than 4,600 distinct proteins. Through workflow-guided manual curation, we have compiled the metabolic reactions carried out by this proteome to form a genome-scale metabolic model (GEM) of the RBC. RBC-GEM is hosted on a version-controlled GitHub repository, ensuring adherence to the standardized protocols for metabolic reconstruction quality control and data stewardship principles. RBC-GEM represents a metabolic network is a consisting of 820 genes encoding proteins acting on 1,685 unique metabolites through 2,723 biochemical reactions: a 740% size expansion over its predecessor. We demonstrated the utility of RBC-GEM by creating context-specific proteome-constrained models derived from proteomic data of stored RBCs for 616 blood donors, and classified reactions based on their simulated abundance dependence. This reconstruction as an up-to-date curated GEM can be used for contextualization of data and for the construction of a computational whole-cell models of the human RBC.

Humans↗
PubMed2024

PoweREST: Statistical Power Estimation for Spatial Transcriptomics Experiments to Detect Differentially Expressed Genes Between Two Conditions.

Recent advancements in Spatial Transcriptomics (ST) have significantly enhanced biological research in various domains. However, the high cost of current ST data generation techniques restricts its application in large-scale population studies. Consequently, there is a pressing need to maximize the use of available resources to achieve robust statistical power. One fundamental question in ST analysis is to detect differentially expressed genes (DEGs) among different conditions using ST data. Such DEG analysis is often performed but the associated power calculation is rarely discussed in the literature. To address this gap, we introduce, PoweREST (https://github.com/lanshui98/PoweREST), a power estimation tool designed to support power calculation of DEG detection with 10X Genomics Visium data. PoweREST enables power estimation both before any ST experiments or after preliminary data are collected, making it suitable for a wide variety of power analyses in ST studies. We also provide a user-friendly, program-free web application (https://lanshui.shinyapps.io/PoweREST/), allowing users to interactively calculate and visualize the study power along with relevant the parameters.

Differentially expressed genes↗
PubMed2025

PoweREST: Statistical power estimation for spatial transcriptomics experiments to detect differentially expressed genes between two conditions.

Recent advancements in spatial transcriptomics (ST) have significantly enhanced biological research in various domains. However, the high cost for current ST data generation techniques restricts the large-scale application of ST. Consequently, maximization of the use of available resources to achieve robust statistical power for ST data is a pressing need. One fundamental question in ST analysis is detection of differentially expressed genes (DEGs) under different conditions using ST data. Such DEG analyses are performed frequently, but their power calculations are rarely discussed in the literature. To address this gap, we developed PoweREST, a power estimation tool designed to support the power calculation for DEG detection with 10X Genomics Visium data. PoweREST enables power estimation both before any ST experiments and after preliminary data are collected, making it suitable for a wide variety of power analyses in ST studies. We also provide a user-friendly, program-free web application that allows users to interactively calculate and visualize study power along with relevant parameters.

Gene Expression Profiling↗
PubMed2026

Trichoderma specialized metabolites in biocontrol: gene-metabolite links, ecological functions, and translational bottlenecks.

Trichoderma spp. produce a diverse repertoire of metabolites with specific activities that contribute to biocontrol through direct antagonism, ecological signalling, and modulation of plant responses. However, current knowledge remains uneven: many metabolites are chemically described, whereas fewer are supported by robust gene-metabolite associations, experimentally validated ecological functions, and realistic translational evidence. Progress in this field will depend less on expanding compound catalogues than on integrating mechanistic, ecological, and translational evidence. This review examines the specialized metabolism of Trichoderma with emphasis on biosynthetic gene clusters, regulatory networks, ecological roles, and biosafety constraints relevant to biocontrol. Major metabolite classes, including polyketides, terpenoids, peptaibols, siderophores, diketopiperazines, and volatile organic compounds, are discussed together with representative case studies for which genetic and functional evidence is available. We further propose a translational framework to distinguish metabolites with mainly descriptive support from those approaching application readiness, based on four criteria: gene-level validation, demonstrated ecological role, manageable biosafety profile, and feasible delivery/stability. This perspective helps explain why metabolite inventories continue to expand faster than field translation. Recent advances in genomics, transcriptomics, metabolomics, genome editing, and formulation science are reshaping how Trichoderma metabolites are prioritized for future development.

Biosafety↗
PubMed2026

Nourishing collaboration: interdisciplinary nutrition education for health care professionals.

Nutrition education remains insufficient in many health care professional training programs despite the central role of diet in the prevention and management of chronic disease. Contemporary nutrition science increasingly recognizes that dietary behaviors and health outcomes are shaped by complex interactions among biological, behavioral, environmental, and food system factors. This perspective proposes an interdisciplinary framework for nutrition education that integrates the complementary expertise of physicians, dietitians, chefs, and farmers. By bridging clinical care, nutrition science, culinary practice, and agricultural systems, such an approach may strengthen the translation of evidence into practice, improve nutrition-related competencies among health care professionals, and ultimately enhance population health outcomes.

Humans↗
PubMed2026

AISP position statement: Standardising biological sample collection and handling for advanced diagnostics and multi-omic analyses in pancreatic cancer.

The quality of biological samples is a major determinant of analytical reliability and translational relevance in patients with pancreatic ductal adenocarcinoma (PDAC). However, variability in specimen procurement, handling, transport, processing, and storage can substantially affect tissue integrity and the robustness of downstream analyses. This paper, promoted by the Pathology and Basic Science Task Force of the Italian Association for the Study of the Pancreas (AISP), brings together experts in pathology, molecular biology, translational research, medical oncology, and gastroenterology to provide practical recommendations for the collection, handling, and pre-analytical management of biological samples. Draft recommendations were discussed during dedicated working group meetings and approved by consensus among all authors, supported by key literature. The document identifies the biological specimen as the critical link between patient care, pathology, and research, and provides guidance for clinicians and professionals involved in sample procurement and processing. By addressing the requirements of different analytical platforms, including genomics, organoid generation, immunophenotyping, pharmacogenomics, and multiplex/spatial analyses, this paper aims to reduce pre-analytical variability, improve diagnostic accuracy, and enhance the clinical and translational value of molecular investigations in pancreatic cancer. Standardised procedures across centres may facilitate comparable data collection, support multicentre studies, and strengthen collaboration between clinicians, pathologists, and research laboratories.

Biobanking↗
PubMed2026

Clinical proteomics in inborn errors of metabolism: from biomarker discovery to implementation.

INTRODUCTION: Inborn errors of metabolism (IEMs) are rare, heterogeneous disorders traditionally diagnosed through genetic testing, enzyme assays, and metabolite measurements. However, these tools often do not fully explain phenotypic variability, organ involvement, disease progression, or treatment response. Clinical proteomics provides a complementary functional layer by capturing changes in protein abundance, proteoforms, post-translational modifications (PTM), and biological pathways, offering insights beyond genotype- and metabolite-based approaches. AREAS COVERED: This review examines the role of high-resolution mass spectrometry and computational proteomics in biomarker discovery and clinical decision-making for IEMs. It focuses on their contribution to diagnosis, variant interpretation, patient stratification, and treatment monitoring. Disease-specific applications are discussed, with the strongest evidence in lysosomal storage disorders, mitochondrial diseases, congenital disorders of glycosylation, and selected neurodegenerative or renal metabolic conditions. The literature search was performed in PubMed, Scopus, Web of Science, and Google Scholar, covering peer-reviewed articles available up to 2026, with emphasis on methodological advances and translational applications in clinical proteomics for IEMs. EXPERT OPINION: Proteomics will not replace established diagnostic tools, but it can help address clinically actionable questions in selected contexts. Translation into clinical practice will require standardized workflows, multicenter validation, clinically anchored endpoints, and integration with other omics approaches.

Humans↗
PubMed2025

Delivery of genome editors with engineered virus-like particles.

Genome editing technologies have revolutionized biomedical sciences and biotechnology. However, their delivery in vivo remains one of the major obstacles for clinical translation. Here, we introduce various emerging genome editing systems and review different delivery systems have been developed to realize the promise of in vivo gene editing therapies. In particular, we focus on virus-like particles (VLPs), an emerging delivery platform and provide in depth analysis on recent advancements to improve VLPs delivery potential and highlight opportunities for future improvements. To this end, we also provide detail workflows for engineered VLP (eVLP) selection, production, and purification, along with methods for characterization and validation.

Gene Editing↗
PubMed2025

CSGL: chemical synthesis graph learning for molecule representation.

MOTIVATION: Molecule representation learning (MRL) translates molecules into a real vector space, serving as input to downstream tasks in biology, chemistry, and computer science. This article introduces a chemical synthesis graph learning (CSGL) framework, which enhances MRL by considering both the atomic structures of molecules and their roles in chemical reactions through a hierarchical graph representation. Specifically, molecules are first modeled based on their molecular graphs, which capture atomic-level structural information. They are then further refined using a chemical synthesis graph, where nodes represent reactant and product molecule sets, and edges encode chemical transformations between reactants and products (e.g. changes in molecular structures). CSGL optimizes molecular embeddings of reactant and product nodes in a fashion that ensures the embeddings conform to a chemical balance constraint. RESULTS: Experimental results show that our method CSGL achieves strong performance on a variety of tasks, including product prediction, reaction classification, and molecular property prediction. AVAILABILITY AND IMPLEMENTATION: https://github.com/li-2023/CSGL.

Machine Learning↗
PubMed2025

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins.

A major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.

GENCODE↗
PubMed2026

Genomic science and the nurse educator's role: Promoting integration from curriculum to clinical practice.

BACKGROUND: Registered nurses and nurse educators play a critical role in preparing future clinicians to translate genomic discoveries into practice. However, emerging evidence suggests that both groups may lack sufficient knowledge and confidence in genomics, potentially limiting their ability to teach, mentor, and apply genomics in real-world settings. This gap is especially concerning in Aotearoa New Zealand, where the genomic literacy of nurse educators and clinicians remains underexplored. OBJECTIVE: This study aims to: (1) assess nurse educators' genomic literacy and confidence in teaching genomics; and (2) evaluate registered nurses' knowledge and confidence in applying and teaching genomics in clinical practice. DESIGN: Exploratory descriptive qualitative. SETTING: This study was conducted in the greater Auckland area. PARTICIPANTS: A total of 17 participants were recruited using purposive sampling to ensure a diverse range of perspectives across varying levels of teaching experience, disciplinary backgrounds, and exposure to genomic content. METHODS: Data were collected using semi-structured focus group interviews, a method well-suited for generating in-depth discussion and facilitating interaction among participants with shared professional interests. The collected data were analysed using thematic analysis methods. RESULTS: The findings offer insight into the preparedness of New Zealand's nursing workforce to engage with genomic-informed healthcare and inform strategies for integrating genomics into nursing curricula and continuing professional development. Given the interdisciplinary nature of genomic healthcare, these insights may also be relevant to other health professionals-including midwives, pharmacists, and allied health practitioners-who increasingly encounter genomic information in clinical practice and require foundational competencies to support patient care. CONCLUSION: Addressing this educational gap is critical to ensuring that nurses-key facilitators of patient care and public health-are equipped to deliver safe, equitable, and evidence-based genomic healthcare.

Humans↗
PubMed2026

Temporal mismatch in allogeneic iPSC therapies: biological risks and implications for clinical translation.

INTRODUCTION: The clinical translation of pluripotent stem cell-derived therapies has entered a new phase following conditional approval of first-in-class allogeneic induced pluripotent stem cell (iPSC)-derived products in Japan. These approvals highlight both the therapeutic promise of iPSC technologies and regulatory challenges associated with evaluating complex cell-based interventions. AREAS COVERED: This report examines the evidentiary basis supporting recent approvals and reviews key biological characteristics of allogeneic iPSC-derived therapies, including pluripotency-associated instability, immunological constraints, and manufacturing-related genomic variability. Drawing on recent clinical studies and relevant experimental literature, we analyze how these multilayered risks evolve over extended time horizons and assess their implications for the interpretation of early-phase clinical data and current regulatory frameworks. EXPERT OPINION: We argue that the central challenge extends beyond limited clinical evidence to a fundamental mismatch between the temporal dynamics of biological risk and the duration of conventional clinical evaluation. As a result, early clinical observations may systematically underestimate long-term risks. Conditional approval pathways should therefore incorporate safeguards aligned with this temporal uncertainty, including long-term follow-up, rigorous post-approval evaluation, and enhanced transparency in biological and manufacturing data. Aligning regulatory design with intrinsic properties of pluripotent stem cell-derived therapies will be essential for ensuring safe and responsible clinical translation.

Humans↗