Search results

Association of COVID-19 With Risk of Posttransplant Diabetes Mellitus

Background. Posttransplant diabetes mellitus (PTDM) is an important complication for solid organ transplant recipients (SOTRs). COVID-19 has been associated with an increased risk of incident diabetes in the general population. However, the association between COVID-19 and new-onset PTDM has not been explored. Methods. Using the National COVID Cohort Collaborative Enclave, we conducted a cohort study of adults without diabetes receiving a solid organ transplant (heart, lung, kidney, or liver) in the United States between April 1, 2020, and March 31, 2023, with and without a first diagnosis of COVID-19 (COVID+ versus COVID-) within 180 d of SOT. We propensity score matched a single COVID+ SOTR with a COVID- SOTR who was diabetes free at the same point posttransplant. Within this matched cohort, we used multivariable Cox proportional hazards models to examine the adjusted risk of PTDM associated with COVID+. Results. Among 1342 COVID+ SOTRs matched to 1342 COVID- SOTRs, the crude rate of newly diagnosed PTDM in the 2 y post-COVID was 17% in those with versus 13% in those without COVID-19 (P = 0.007). COVID-19 was significantly associated with new PTDM (adjusted hazard ratio, 1.37; 95% confidence interval, 1.12-1.68 at 2 y). Conclusions. Similar to other viral infections, COVID-19 is associated with an increased risk of PTDM in SOTRs.

Transcriptomic effects of methotrexate on natural killer cells in psoriatic arthritis

Navigating severe class imbalance in population cohort data

Class imbalance is a major challenge in predictive modelling for rare disease outcomes, particularly in large-scale population cohorts. Traditional machine learning models often struggle with imbalanced datasets, leading to biased performance metrics and poor generalisability. This study systematically evaluates multiple approaches to mitigate class imbalance in predicting Multiple myeloma using proteomic and clinical data from UK Biobank. We compare standard classification models (XGBoost and logistic regression) with synthetic resampling (SMOTE), anomaly detection techniques (isolation forests, local outlier factors, one-class SVM, and autoencoders), and a transformer-based foundation model (TabPFN), using standard classification performance metrics. Our results indicate that anomaly detection models generalise better than conventional classifiers (XGBoost and logistic regression), while SMOTE fails to improve, and may actively worsen, predictive performance. To address the precision-sensitivity trade-off, we introduce a sequential XGBoost ensemble classifier (SeqXGB) that prioritises high precision over sensitivity to minimise false positive predictions. Compared with a single XGBoost model, the SeqXGB approach successfully reduces false positives (420 vs 9), but significantly limits sensitivity (0.70 vs 0.15) in held-out test data. Our findings highlight that no single method is universally optimal for addressing class imbalance; rather, model selection should be guided by clinical application, balancing the risks of false positives and false negatives.

Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysis.

Single-cell multiomic analysis of the epigenome, transcriptome, and proteome allows for comprehensive characterization of the molecular circuitry that underpins cell identity and state. However, the holistic interpretation of such datasets presents a challenge given a paucity of approaches for systematic, joint evaluation of different modalities. Here, we present Panpipes, a set of computational workflows designed to automate multimodal single-cell and spatial transcriptomic analyses by incorporating widely-used Python-based tools to perform quality control, preprocessing, integration, clustering, and reference mapping at scale. Panpipes allows reliable and customizable analysis and evaluation of individual and integrated modalities, thereby empowering decision-making before downstream investigations.

Safe emergency general surgery-ASGBI statement.

Harnessing transcriptomic signals for amyotrophic lateral sclerosis to identify novel drugs and enhance risk prediction.

INTRODUCTION: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. This study integrates common genetic association results from the latest ALS genome-wide association study (GWAS) summary statistics with functional genomic annotations with the aim of providing mechanistic insights into ALS risk loci, inferring drug repurposing opportunities, and enhancing prediction of ALS risk and clinical characteristics. METHODS: Genes associated with ALS were identified using GWAS summary statistic methodology including SuSiE SNP-based fine-mapping, and transcriptome- and proteome-wide association study (TWAS/PWAS) analyses. Using several approaches, gene associations were integrated with the DrugTargetor drug-gene interaction database to identify drugs that could be repurposed for the treatment of ALS. Furthermore, ALS gene associations from TWAS were combined with observed blood expression in two external ALS case-control datasets to calculate polytranscriptomic scores and evaluate their utility for prediction of ALS risk and clinical characteristics, including site of onset, age at onset, and survival. RESULTS: SNP-based fine-mapping, TWAS and PWAS identified 118 genes associated with ALS, with TWAS and PWAS providing novel mechanistic insights. Drug repurposing analyses identified six drugs significantly enriched for interactions with ALS associated genes, though directionality could not be determined. Additionally, drug class enrichment analysis showed gene signatures linked to calcium channel blockers may reduce ALS risk, whereas antiepileptic drugs may increase ALS risk. Across the two observed expression target samples, ALS polytranscriptomic scores significantly predicted ALS risk (R 2 = 5.1 %; p-value = 3.2 × 10-27) and clinical characteristics. CONCLUSIONS: Functionally-informed analyses of ALS GWAS summary statistics identified novel mechanistic insights into ALS aetiology, highlighted several therapeutic research avenues, and enabled statistically significant prediction of ALS risk.

Fine needle aspiration of human lymph nodes reveals cell populations and soluble interactors pivotal to immunological priming.

Lymph node (LN) fine needle aspiration (LN FNA) represents a powerful technique for minimally invasive sampling of human LNs in vivo and has been used effectively to directly study aspects of the human germinal center response. However, systematic deep phenotyping of the cellular populations and cell-free proteins recovered by LN FNA has not been performed. Thus, we studied human cervical LN FNAs as a proof-of-concept and used single-cell RNA-sequencing and proteomic analysis to benchmark this compartment, define the purity of LN FNA material, and facilitate future studies in this immunologically pivotal environment. Our data provide evidence that LN FNAs contain bone-fide LN-resident innate immune populations, with minimal contamination of blood material. Examination of these populations reveals unique biology not predictable from equivalent blood-derived populations. LN FNA supernatants represent a specific source of lymph- and lymph node-derived proteins, and can, aided by transcriptomics, identify likely receptor-ligand interactions. This represents the first description of the types and abundance of immune cell populations and cell-free proteins that can be efficiently studied by LN FNA. These findings are of broad utility for understanding LN physiology in health and disease, including infectious or autoimmune perturbations, and in the case of cervical nodes, neuroscience.

Digital health interventions in primary care in low- and middle-income countries: a systematic scoping review protocol

Background The integration of digital health (eHealth) interventions into primary healthcare systems has gained recognition lately in Low-and Middle-Income Countries (LMICs) to enhance healthcare quality, accessibility, and efficiency. These interventions may offer effective strategies in mitigating the burden of chronic diseases by facilitating access to remote healthcare and optimising its processes. This scoping review aims to identify and assess eHealth interventions implemented in primary care settings in LMICs for further development and adaptation. Methods and analysis We will search two electronic databases, such as Scopus and Embase, to identify peer-reviewed studies reporting on eHealth interventions implemented in primary care settings within LMICs. This review will encompass evidence published in the English language without a time frame restriction. We will remove duplicates from the search, and two reviewers will independently assess all articles for eligibility by first screening the title and abstract, followed by a full-text review. Eligible articles will be extracted, and data will be charted according to types of intervention and settings using a standardised form. Ethics and dissemination There is no ethical review required for this scoping review. We plan to disseminate the findings by presentations at conferences and publishing in open-access journal.

Global estimates and determinants of antituberculosis drug pharmacokinetics in children and adolescents: a systematic review and individual patient data meta-analysis.

BACKGROUND: Suboptimal exposure to antituberculosis (anti-TB) drugs has been associated with unfavourable treatment outcomes. We aimed to investigate estimates and determinants of first-line anti-TB drug pharmacokinetics in children and adolescents at a global level. METHODS: We systematically searched MEDLINE, Embase and Web of Science (1990-2021) for pharmacokinetic studies of first-line anti-TB drugs in children and adolescents. Individual patient data were obtained from authors of eligible studies. Summary estimates of total/extrapolated area under the plasma concentration-time curve from 0 to 24 h post-dose (AUC0-24) and peak plasma concentration (C max) were assessed with random-effects models, normalised with current World Health Organization-recommended paediatric doses. Determinants of AUC0-24 and C max were assessed with linear mixed-effects models. RESULTS: Of 55 eligible studies, individual patient data were available for 39 (71%), including 1628 participants from 12 countries. Geometric means of steady-state AUC0-24 were summarised for isoniazid (18.7 (95% CI 15.5-22.6) h·mg·L-1), rifampicin (34.4 (95% CI 29.4-40.3) h·mg·L-1), pyrazinamide (375.0 (95% CI 339.9-413.7) h·mg·L-1) and ethambutol (8.0 (95% CI 6.4-10.0) h·mg·L-1). Our multivariate models indicated that younger age (especially <2 years) and HIV-positive status were associated with lower AUC0-24 for all first-line anti-TB drugs, while severe malnutrition was associated with lower AUC0-24 for isoniazid and pyrazinamide. N-acetyltransferase 2 rapid acetylators had lower isoniazid AUC0-24 and slow acetylators had higher isoniazid AUC0-24 than intermediate acetylators. Determinants of C max were generally similar to those for AUC0-24. CONCLUSIONS: This study provides the most comprehensive estimates of plasma exposures to first-line anti-TB drugs in children and adolescents. Key determinants of drug exposures were identified. These may be relevant for population-specific dose adjustment or individualised therapeutic drug monitoring.

Harnessing Transcriptomic Signals for Amyotrophic Lateral Sclerosis to Identify Novel Drugs and Enhance Risk Prediction.

INTRODUCTION: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. This study integrates the latest ALS genome-wide association study (GWAS) summary statistics with functional genomic annotations with the aim of providing mechanistic insights into ALS risk loci, inferring drug repurposing opportunities, and enhancing prediction of ALS risk and clinical characteristics. METHODS: Genes associated with ALS were identified using GWAS summary statistic methodology including SuSiE SNP-based fine-mapping, and transcriptome- and proteome-wide association study (TWAS/PWAS) analyses. Using several approaches, gene associations were integrated with the DrugTargetor drug-gene interaction database to identify drugs that could be repurposed for the treatment of ALS. Furthermore, ALS gene associations from TWAS were combined with observed blood expression in two external ALS case-control datasets to calculate polytranscriptomic scores and evaluate their utility for prediction of ALS risk and clinical characteristics, including site of onset, age at onset, and survival. RESULTS: SNP-based fine-mapping, TWAS and PWAS identified 117 genes associated with ALS, with TWAS and PWAS providing novel mechanistic insights. Drug repurposing analyses identified five drugs significantly enriched for interactions with ALS associated genes, with directional analyses highlighting α-glucosidase inhibitors may exacerbate ALS pathology. Additionally, drug class enrichment analysis showed calcium channel blockers may reduce ALS risk. Across the two observed expression target samples, ALS polytranscriptomic scores significantly predicted ALS risk (R2 = 4%; p-value = 2.1×10-21). CONCLUSIONS: Functionally-informed analyses of ALS GWAS summary statistics identified novel mechanistic insights into ALS aetiology, highlighted several therapeutic research avenues, and enabled statistically significant prediction of ALS risk.

Lipopolysaccharide distinctively alters human microglia transcriptomes to resemble microglia from Alzheimer's disease mouse models.

Alzheimer's disease (AD) is the most common form of dementia, and risk-influencing genetics implicates microglia and neuroimmunity in the pathogenesis of AD. Induced pluripotent stem cell (iPSC)-derived microglia (iPSC-microglia) are increasingly used as a model of AD, but the relevance of historical immune stimuli to model AD is unclear. We performed a detailed cross-comparison over time on the effects of combinatory stimulation of iPSC-microglia, and in particular their relevance to AD. We used single-cell RNA sequencing to measure the transcriptional response of iPSC-microglia after 24 h and 48 h of stimulation with prostaglandin E2 (PGE2) or lipopolysaccharide (LPS)+interferon gamma (IFN-γ), either alone or in combination with ATPγS. We observed a shared core transcriptional response of iPSC-microglia to ATPγS and to LPS+IFN-γ, suggestive of a convergent mechanism of action. Across all conditions, we observed a significant overlap, although directional inconsistency to genes that change their expression levels in human microglia from AD patients. Using a data-led approach, we identify a common axis of transcriptomic change across AD genetic mouse models of microglia and show that only LPS provokes a transcriptional response along this axis in mouse microglia and LPS+IFN-γ in human iPSC-microglia. This article has an associated First Person interview with the first author of the paper.

Gliotransmission of D-serine promotes thirst-directed behaviors in Drosophila.

Thirst emerges from a range of cellular changes that ultimately motivate an animal to consume water. Although thirst-responsive neuronal signals have been reported, the full complement of brain responses is unclear. Here, we identify molecular and cellular adaptations in the brain using single-cell sequencing of water-deprived Drosophila. Water deficiency primarily altered the glial transcriptome. Screening the regulated genes revealed astrocytic expression of the astray-encoded phosphoserine phosphatase to bi-directionally regulate water consumption. Astray synthesizes the gliotransmitter D-serine, and vesicular release from astrocytes is required for drinking. Moreover, dietary D-serine rescues aay-dependent drinking deficits while facilitating water consumption and expression of water-seeking memory. D-serine action requires binding to neuronal NMDA-type glutamate receptors. Fly astrocytes contribute processes to tripartite synapses, and the proportion of astrocytes that are themselves activated by glutamate increases with water deprivation. We propose that thirst elevates astrocytic D-serine release, which awakens quiescent glutamatergic circuits to enhance water procurement.

Fly Cell Atlas: A single-nucleus transcriptomic atlas of the adult fruit fly.

For more than 100 years, the fruit fly Drosophila melanogaster has been one of the most studied model organisms. Here, we present a single-cell atlas of the adult fly, Tabula Drosophilae, that includes 580,000 nuclei from 15 individually dissected sexed tissues as well as the entire head and body, annotated to >250 distinct cell types. We provide an in-depth analysis of cell type-related gene signatures and transcription factor markers, as well as sexual dimorphism, across the whole animal. Analysis of common cell types between tissues, such as blood and muscle cells, reveals rare cell types and tissue-specific subtypes. This atlas provides a valuable resource for the Drosophila community and serves as a reference to study genetic perturbations and disease models at single-cell resolution.

Integration of single-cell RNA-Seq and CyTOF data characterises heterogeneity of rare cell subpopulations

Background: The simultaneous measurement of cellular proteins and transcriptomes of single cell data has become an exciting new possibility with the advent of highly multiplexed multi-omics methodologies. However, mass cytometry (CyTOF) is a well-established, affordable technique for the analysis of proteomic data, which is well suited for the discovery and characterisation of very rare subpopulations of cells with a wealth of publicly available datasets. Methods: We present and evaluate the multimodal integration of single cell RNA-Seq and CyTOF datasets coming from both matched and unmatched samples, using two publicly available datasets. Results: We demonstrate that the integration of well annotated CyTOF data with single cell RNA sequencing can aid in the identification and annotation of cell populations with high accuracy. Furthermore, we show that the integration can provide imputed measurements of protein markers which are comparable to the current gold standard of antibody derived tags (ADT) from CITE-Seq for both matched and unmatched datasets. Using this methodology, we identify and transcriptionally characterise a rare subpopulation of CD11c positive B cells in high resolution using publicly available data and we unravel its heterogeneity in a single cell setting without the need to sort the cells in advance, in a manner which had not been previously possible. Conclusions: This approach provides the framework for using available proteomic and transcriptomic datasets in a unified and unbiased fashion to assist ongoing and future studies of cellular characterisation and biomarker identification.

The long-term sequelae of COVID-19: an international consensus on research priorities for patients with pre-existing and new-onset airways disease.

Persistent ill health after acute COVID-19-referred to as long COVID, the post-acute COVID-19 syndrome, or the post-COVID-19 condition-has emerged as a major concern. We undertook an international consensus exercise to identify research priorities with the aim of understanding the long-term effects of acute COVID-19, with a focus on people with pre-existing airways disease and the occurrence of new-onset airways disease and associated symptoms. 202 international experts were invited to submit a minimum of three research ideas. After a two-phase internal review process, a final list of 98 research topics was scored by 48 experts. Patients with pre-existing or post-COVID-19 airways disease contributed to the exercise by weighting selected criteria. The highest-ranked research idea focused on investigation of the relationship between prognostic scores at hospital admission and morbidity at 3 months and 12 months after hospital discharge in patients with and without pre-existing airways disease. High priority was also assigned to comparisons of the prevalence and severity of post-COVID-19 fatigue, sarcopenia, anxiety, depression, and risk of future cardiovascular complications in patients with and without pre-existing airways disease. Our approach has enabled development of a set of priorities that could inform future research studies and funding decisions. This prioritisation process could also be adapted to other, non-respiratory aspects of long COVID.

Phenotypic manifestation of α-synuclein strains derived from Parkinson's disease and multiple system atrophy in human dopaminergic neurons.

α-Synuclein is critical in the pathogenesis of Parkinson's disease and related disorders, yet it remains unclear how its aggregation causes degeneration of human dopaminergic neurons. In this study, we induced α-synuclein aggregation in human iPSC-derived dopaminergic neurons using fibrils generated de novo or amplified in the presence of brain homogenates from Parkinson's disease or multiple system atrophy. Increased α-synuclein monomer levels promote seeded aggregation in a dose and time-dependent manner, which is associated with a further increase in α-synuclein gene expression. Progressive neuronal death is observed with brain-amplified fibrils and reversed by reduction of intraneuronal α-synuclein abundance. We identified 56 proteins differentially interacting with aggregates triggered by brain-amplified fibrils, including evasion of Parkinson's disease-associated deglycase DJ-1. Knockout of DJ-1 in iPSC-derived dopaminergic neurons enhance fibril-induced aggregation and neuronal death. Taken together, our results show that the toxicity of α-synuclein strains depends on aggregate burden, which is determined by monomer levels and conformation which dictates differential interactomes. Our study demonstrates how Parkinson's disease-associated genes influence the phenotypic manifestation of strains in human neurons.

High-resolution transcriptional landscape of xeno-free human induced pluripotent stem cell-derived cerebellar organoids.

Current protocols for producing cerebellar neurons from human pluripotent stem cells (hPSCs) often rely on animal co-culture and mostly exist as monolayers, limiting their capability to recapitulate the complex processes in the developing cerebellum. Here, we employed a robust method, without the need for mouse co-culture to generate three-dimensional cerebellar organoids from hPSCs that display hallmarks of in vivo cerebellar development. Single-cell profiling followed by comparison to human and mouse cerebellar atlases revealed the presence and maturity of transcriptionally distinct populations encompassing major cerebellar cell types. Encapsulation with Matrigel aimed to provide more physiologically-relevant conditions through recapitulation of basement-membrane signalling, influenced both growth dynamics and cellular composition of the organoids, altering developmentally relevant gene expression programmes. We identified enrichment of cerebellar disease genes in distinct cell populations in the hPSC-derived cerebellar organoids. These findings ascertain xeno-free human cerebellar organoids as a unique model to gain insight into cerebellar development and its associated disorders.

Ductal variant prostate carcinoma is associated with a significantly shorter metastasis-free survival.

BACKGROUND: Ductal adenocarcinoma is an uncommon prostate cancer variant. Previous studies suggest that ductal variant histology may be associated with worse clinical outcomes, but these are difficult to interpret. To address this, we performed an international, multi-institutional study to describe the characteristics of ductal adenocarcinoma, particularly focussing on the effect of presence of ductal variant cancer on metastasis-free survival. METHODS: Patients with ductal variant histology from two institutional databases who underwent radical prostatectomies were identified and compared with an independent acinar adenocarcinoma cohort. After propensity score matching, the effect of the presence of ductal adenocarcinoma on time to biochemical recurrence, initiation of salvage therapy and the development of metastatic disease was determined. Deep whole-exome sequencing was performed for selected cases (n = 8). RESULTS: A total of 202 ductal adenocarcinoma and 2037 acinar adenocarcinoma cases were analysed. Survival analysis after matching demonstrated that patients with ductal variant histology had shorter salvage-free survival (8.1 versus 22.0 months, p = 0.03) and metastasis-free survival (6.7 versus 78.6 months, p 

Commissioning the H i Observing Mode of the Beam Former for the Cryogenically Cooled Focal L-band Array for the GBT (FLAG)

Abstract We present the results of commissioning observations for a new digital beam-forming back end for the Focal plane L-band Array for the Robert C. Byrd Green Bank Telescope (FLAG), a cryogenically cooled Phased Array Feed (PAF) with the lowest measured T sys/η of any PAF outfitted on a radio telescope to date. We describe the custom software used to apply beam-forming weights to the raw element covariances to create research-quality spectral-line images for the new fine-channel mode, study the stability of the beam weights over time, characterize FLAG’s sensitivity over a frequency range of 150 MHz, and compare the measured noise properties and observed distribution of neutral hydrogen emission from several extragalactic and Galactic sources with data obtained with the current single-pixel L-band receiver. These commissioning runs establish FLAG as the preeminent PAF receiver currently available for spectral-line observations on the world’s major radio telescopes.

Initial results from the ALFABURST survey

Here, we present initial results from the ALFABURST radio transient survey, which is currently running in a commensal mode with the ALFA receiver at the Arecibo telescope. We observed for a total of 1400 hours and have detected single pulses from known pulsars but did not detect any FRBs. The non-detection of FRBs is consistent with the current FRB sky rates.