bluuebunny/crossref_metadata_2025 huggingface dataset:
Bridging the gap: Enhancing the generalizability of epigenetic clocks through transfer learning
Authors: Luo Lan , Shang Lulu , Goodrich Jaclyn M. , Peterson Karen E. , Song Peter X-K
Published: February 2025

Changes in DNA methylation patterns exhibit a high correlation with chronological age. Epigenetic clocks, developed through statistical models that estimate epigenetic age using the methylation levels of cytosine-guanine dinucleotide (CpG) sites, have emerged as powerful tools in understanding aging and age-related diseases. Despite their popularity, the generalizability of these clocks across diverse populations remains a challenge. We find that some of the widely used epigenetic clocks, such as Horvath’s clock (Horvath, 2013) and PedBE clock (McEwen et al., 2020) do not perform well in our target cohort. This lack of representativeness raises concerns about applying these clocks to quantify biological age in distinct demographic and ethnic groups. In addition, the feature space between existing clocks and our target data is different: most existing clocks are trained with data from older platforms, such as the Illumina HumanMethylation450 BeadChip (450K). In contrast, our target data are profiled with a more recent Illumina HumanMethylationEPIC BeadChip (EPIC) array. To address these gaps, we propose a transfer learning framework to adapt existing epigenetic clocks to underrepresented populations, using shared knowledge from diverse datasets. Furthermore, we develop imputation- and DNN-based methods for feature adaptation between existing clocks and our target data. Using data collected from 593 blood samples from a cohort of children and adolescents in the ELEMENT study, we find that our proposed transfer learning methods greatly improve the prediction performance compared to applying existing clocks directly. Performance is further enhanced by using the CpG sites profiled on the EPIC array. Our methodology showcases the potential to bridge the gap between different DNAm datasets and different profiling platforms, thus improving the applicability of epigenetic clocks in diverse population groups and contributing to more accurate aging research.
Peripheral blood mononuclear cell transcriptomic trajectories reveal dynamic regulation of inflammatory actors in delirium
Authors: LaHue Sara C. , Takegami Naoki , Simmasalam Rubinee , Baqai Abiya , Munoz Elena , Sikri Anya , de Courson Thibault du Buisson , Singhal Nilika S. , Eckalbar Walter , Langelier Charles R. , Hendrickson Carolyn M. , Calfee Carolyn S. , Erle David J. , Krummel Matthew F. , Woodruff Prescott G. , Oskotsky Tomiko , Sirota Marina , Ferguson Adam , Douglas Vanja C. , Newman John C. , Pleasure Samuel J. , Wilson Michael R. ,   COMET consortium, Singhal Neel S.
Published: February 2025

Delirium is a neurologic syndrome characterized by inattention and cognitive impairment frequently encountered in the medically ill. Peripheral inflammation is a key trigger of delirium, but the patient-specific immune responses associated with delirium development and resolution are unknown. This retrospective cohort study of prospectively collected biospecimens examines RNA sequencing from peripheral blood mononuclear cells of adults hospitalized for COVID-19 to better understand patient-specific factors associated with delirium (n = 64). Longitudinal transcriptomic analyses highlight persistent immune dysregulation in delirium, marked by increasing expression trajectories of genes linked to innate immune pathways, including complement activation, cytokine production, and monocyte/macrophage recruitment. Genes involved adaptive immunity showed a declining trajectory over time in patients with delirium. Although corticosteroid treatment suppressed some aspects of immune hyperactivation, aberrant responses contributing to delirium were exacerbated. Delirium resolution was characterized by normalization of key transcripts such asCCL2and innate immune markers. Novel associations with delirium were found in genes related to stress granule assembly andDUSP2andKLF10, which mediate T-cell responses. These findings provide insights into the peripheral immune responses accompanying delirium and their modulation by corticosteroids. Future trials targeting aberrant inflammatory responses may mitigate the severe outcomes associated with delirium due to COVID19.
Applying Machine-Learning and Deep-Learning to Predict Depression from Brain MRI and Identify Depression-Related Brain Biology
Authors: Jiang Jiayue-Clara , Brianceau Camille , Delzant Elise , Colle Romain , Bottemanne Hugo , Corruble Emmanuelle , Wray Naomi R , Colliot Olivier , Shah Sonia , Couvy-Duchesne Baptiste
Published: February 2025

The accuracy of grey-matter predictors of depression has remained limited. In this study, brain-based predictors of major depressive disorder (MDD) were trained using machine-learning (Best Linear Unbiased Predictors [BLUP]) and deep-learning (ResNet3D) techniques applied to high-dimensional (voxel-wise) grey-matter structure extracted from T1-weighted structural MRI. The training sample comprised 987 MDD cases and 3,934 controls from the UK Biobank. Predictors were evaluated in an independent sub-cohort of 483 MDD cases and 1,939 controls from the UK Biobank and replicated in a clinical cohort (DEP-ARREST CLIN) of 64 cases and 32 controls. In the UK Biobank, logistic regression showed a significant association between the BLUP predictor and MDD status (AUC=0.57; OR=1.28 [1.15-1.43]; p-value=1.1×10−5), which was confirmed in both males and females. By partitioning the BLUP predictor by brain regions of interest (ROI), we found nominal significance supporting the contribution of previously identified MDD-related ROIs (e.g. hippocampus and amygdala). The BLUP predictor overlapped partially with a polygenic score (PGS) of major depression but also captured a signal that was not captured by the genetic score (combined AUC=0.66, p-value=0.024 when compared to PGS alone). No association passed multiple testing correction in the DEP-ARREST CLIN cohort, likely due to the small sample size. In contrast, the deep-learning predictor did not show a significant association with MDD after multiple testing corrections. Our novel application of the BLUP method shows promising predicting accuracy and suggests new leads to overcome the remaining challenges in predicting MDD from brain imaging.
LONGITUDINAL CHANGES IN WHITE MATTER MICROSTRUCTURAL STATUS FOLLOWING QUANTIFIED HEAD-BALL IMPACTS IN SOCCER: A PRELIMINARY, PROSPECTIVE STUDY
Authors: McCloskey Hugh , McNabb Carolyn Beth , Laguna Pedro Luque , Keenan Bethany , Evans John , Jones Derek K , Palombo Marco , Barnes-Wood Megan , Adams Rhosslyn , Connelly Sean , Theobald Peter
Published: February 2025

Repetitive, sub-concussive head impacts have been associated with increased chronic traumatic encephalopathy (CTE) incidence. CTE diagnosis traditionally relies on post-mortem examination, which limits precise correlation between cause- and-effect. This prospective study embraced innovative diffusion magnetic resonance imaging, which enables in vivo quantification of acute, sub-acute and chronic changes in brain tissue microstructure. This approach was used to evaluate changes in white matter microstructural status at intervals up to 180 days following a specified soccer heading protocol. This study was approved by the university ethics panel. Twelve males (21 – 23 years) were recruited to the study and gave signed, informed consent. Six Intervention participants were university-level soccer players, with 6 Control participants drawn from university-level non-contact sports. Multi-shell diffusion-weighted MRI data were acquired on a 3T Siemens Connectom (300mT/m) scanner using the HARDI protocols. Baseline measures of fractional anisotropy, mean diffusivity and mean kurtosis were acquired at day 0. The Intervention cohort then performed 10 soccer ‘headers’ in a laboratory, with acceleration-time data captured using an instrumented mouthguard and post-processed to report common metrics. The Intervention group was then re-scanned at day 1 (n = 6), day 90 (n = 5) and day 180 (n = 4). The Control group was re-scanned at day 1 (n = 6) and day 180 (n = 3). Many brain tracts were identified as having significant (p < 0.05) changes in white matter microstructural changes at day 90, which correlated strongly with the magnitude of head impact. A smaller number of tracts had changes at day 1 and day 180. These results indicate that, within this pilot population, the magnitude of repeated soccer headers appears to correlate with the magnitude of white matter microstructural change. Additional investigation is required to determine whether the effect of such an intervention influences long-term brain health risk.
A Multimodal Framework to Uncover Drug-Responsive Subpopulations in Triple-Negative Breast Cancer
Authors: Wang Yue , Haase Santiago , Whitman Austin , Beltran Adriana , Spanheimer Philip M. , Brunk Elizabeth
Published: February 2025

Understanding how individual cancer cells adapt to drug treatment is a fundamental challenge limiting precision medicine cancer therapy strategies. While single-cell technologies have advanced our understanding of cellular heterogeneity, efforts to connect the behavior of individual cells to broader tumor drug responses and uncover global trends across diverse systems remain limited. There is a growing availability of single-cell and bulk omics data, but a lack of centralized tools and repositories makes it difficult to study drug response globally, especially at the level of single-cell adaptation. To address this, we present a multimodal framework that integrates bulk and single-cell treated and untreated transcriptomics data to identify drug responsive cell populations in triple-negative breast cancer (TNBC). Our framework leverages population-scale bulk transcriptomics data from TNBC samples to define seven main “identities”, each representing unique combinations of biologically relevant genes. These identities are dynamic and trackable, allowing us to map them onto single cells and uncover global patterns of how cell populations respond to drug treatment. Unlike static classifications, this approach captures the evolving nature of cellular states, revealing that a select few identities dominate and drive population-level responses during treatment. Crucially, our ability to decode these trends through the inherent noise of single-cell data provides a clearer picture of how heterogeneous cell populations adapt to therapy. By identifying the dominant identities and their dynamics, we can better predict how entire tumors respond to treatment. This insight is essential for designing precise combination therapies tailored to the unique heterogeneity of patient tumors, addressing the single-cell variations that ultimately determine therapeutic outcomes.
Investigating Facial Expression Processing during Fast Periodic Visual Stimulation using Highly Variable Stimuli
Authors: Vandenheever David , Davidson Haleigh , Kemp Jennifer , Murphy Zack , Kujawa Autumn , Shi Catherine , Nadorff Michael , Bates-Brantley Kayla , Sidwell MacKenzie
Published: February 2025

Facial expression recognition is a fundamental aspect of human social interaction, enabling effective communication and emotional understanding. Fast Periodic Visual Stimulation (FPVS) paradigms have recently emerged as a powerful approach for studying facial expression processing. However, previous studies often utilized identical base stimuli, making it difficult to disentangle neural responses to low-level perceptual differences from those reflecting conceptual discrimination of emotion. By introducing variability in our stimuli, we aimed to overcome these limitations and investigate neural responses to facial expressions of anger, fear, happiness, and sadness. Using EEG, robust oddball responses were observed across participants at both individual and group levels, demonstrating the paradigm’s sensitivity even with brief recordings and limited post-processing. Significant neural responses were detected across key regions of interest, with the right occipito-temporal region showing the strongest activity, consistent with its role in high-level facial expression processing. This study highlights the effectiveness of the FPVS paradigm for examining emotional processing using naturalistic stimuli and provides a framework for future research into neural mechanisms underlying facial emotion recognition in diverse and pathological populations.
PDBCleanV2: A Python Library for Generating Consistent Structure Datasets
Authors: Pardo-Avila Fátima , Weiner Liv , Cabral Paulina , Corsepius Nicholas , Poitevin Frédéric , Levitt Michael
Published: February 2025

The number of structures in the Protein Data Bank has grown rapidly in recent years. Nonetheless, comparing structures of a specific system often proves challenging due to variant nomenclature, origins from different species, presence of various ligands, and missing atoms or chains. To address these issues, we have developed PDBCleanV2, a Python package that enables users to create consistent datasets of structures, simplifying comparison among structures. This library generates individual files for each molecule in a structure file, corrects labeling errors, and standardizes chain names and numbering. Our aim is to provide researchers with consistent datasets that streamline their analysis. The source code, installation instructions, and tutorials can be found in PDBCleanV2’s GitHub repository and Zenodo accessible athttps://github.com/fatipardo/PDBClean-0.0.2/andhttps://doi.org/10.5281/zenodo.14014241, respectively.
The tree labeling polytope: a unified approach to ancestral reconstruction problems
Authors: Schmidt Henri , Raphael Benjamin J.
Published: February 2025

Motivation

Reconstructing unobserved ancestral states of a phylogenetic tree provides insight into the history of evolving systems and is one of the fundamental problems in phylogenetics. For a fixed phylogenetic tree, the most parsimonious ancestral reconstruction – a solution to the small parsimony problem – can be efficiently found using the dynamic programming algorithms of Fitch-Hartigan and Sankoff. Ancestral reconstruction is important in many applications including inferring the routes of metastases in cancer, deriving the transmission history of viruses, determining the direction of cellular differentiation in organismal development, and detecting recombination and horizontal gene transfer in phylogenetic networks. However, most of these applications impose additionalglobalconstraints on the reconstructed ancestral states, which break the local structure required in the recurrences of Fitch-Hartigan and Sankoff.

Results

We introduce an alternative, polyhedral approach to ancestral reconstruction problems using thetree labeling polytope, a geometric object whose vertices represent the feasible ancestral labelings of a tree. This framework yields a polynomial-time linear programming algorithm for thesmall parsimony problem. More importantly, the tree labeling polytope facilitates the incorporation of additional constraints that arise in modern ancestral reconstruction problems. We demonstrate the utility of our approach by deriving mixed-integer programming algorithms with a small number of integer variables and strong linear relaxations for three such problems: the parsimonious migration history problem, the softwired small parsimony problem on phylogenetic networks, and the convex recoloring problem on trees. Our algorithms outperform existing state-of-the-art methods on both simulated and real datasets. For instance, our algorithm scales to trace routes of cancer metastases in trees with thousands of leaves, enabling the analysis of large trees generated by recent single-cell sequencing technologies. On a mouse model of metastatic lung adenocarcinoma, the tree labeling polytope allows us to infer simpler migration histories compared to previous results.

Availability

Python implementations of the algorithms provided in this work are available at:github.com/raphael-group/tree-labeling-polytope.
Learning Latent Trajectories in Developmental Time Series with Hidden-Markov Optimal Transport
Authors: Halmos Peter , Gold Julian , Liu Xinhao , Raphael Benjamin J.
Published: February 2025

Deriving the sequence of transitions between cell types, or differentiation events, that occur during organismal development is one of the fundamental challenges in developmental biology. Single-cell and spatial sequencing of samples from different developmental timepoints provide data to investigate differentiation but inferring a sequence of differentiation events requires: (1) finding trajectories, or ancestor:descendant relationships, between cells from consecutive timepoints; (2) coarse-graining these trajectories into adifferentiation map, or collection of transitions betweencell types, rather than individual cells. We introduce Hidden-Markov Optimal Transport (HM-OT), an algorithm that simultaneously groups cells into cell types and learns transitions between these cell types from developmental transcriptomics time series.HM-OTuses low-rank optimal transport to simultaneously align samples in a time series and learn a sequence of clusterings and a differentiation map with minimal total transport cost. We assume that the law governing cell-type trajectories is characterized by the joint law on consecutive time points, tantamount to a Markov assumption on these latent trajectories.HM-OTcan learn these clusterings in a fully unsupervised manner or can generate the least-cost cell type differentiation map consistent with a given set of cell type labels. We validate the unsupervised clusters and cell type differentiation map output byHM-OTon a Stereo-seq dataset of zebrafish development, and we demonstrate the scalability ofHM-OTto a massive Stereo-seq dataset of mouse embryonic development.

Code availability

Software is available athttps://github.com/raphael-group/HM-OT
3D finite element models reveal regional fatty infiltration modulates tibialis anterior force generating capacity in FSHD
Authors: McCrady Allison N. , Friedman Seth D. , Wang Leo , Shaw Dennis W , Tawil Rabi , Statland Jeffery M , Tapscott Stephen J. , Blemker Silvia S.
Published: February 2025

Facioscapulohumeral muscular dystrophy (FSHD) is a progressive neuromuscular disorder characterized by muscle damage, fibro-fatty infiltration, and ultimately weakness. The tibialis anterior (TA), very often involved relatively early in FSHD, is a primary dorsiflexor and important for ambulation. Recent work using magnetic resonance imaging to quantify fat infiltration in the TA volume observed a steep decline in force generation after fat reached ~20% in volume. Additional imaging studies have identified regional fat infiltration patterns that may contribute to the non-linear relationship between fat volume and muscle strength due to the distribution of fat within the muscle structure. The goals of this study were to 1) develop a pipeline for creating subject-specific models of the TA that include fat infiltration patterns measured from MRI and predict force generation, 2) compare models created using this pipeline with clinical measures of muscle strength, and 3) use the models to investigate the impact of regional fat distribution on muscle force generation. Twelve subject-specific models were created, and the model-predicted forces strongly correlate to clinical measures of strength in the same subjects (manual muscle testing (MMT): r=0.75, and quantitative muscle testing (QMT): r=0.54). The models showed fat amount accounts for 48% and muscle volume accounts for 74% of the variation in force. To investigate the impact of fat distribution, we developed eight pseudo maps to systematically vary fat location and amount in all subject-specific geometries. The models revealed that fat location modulates force generation, with the middle region involvement having the greatest impact in reducing force. This work highlights the need to characterize and understand the impact of intra-muscular fat distributions in neuromuscular diseases.
Clinical Progression on CDR-SB©: Progression Free Time at Each 0.5-unit Level in Dominantly Inherited and Sporadic Alzheimer’s Disease Populations
Authors: Wang Guoqiao , Li Yan , McDade Eric , Xiong Chengjie , Hartz Sarah M. , Bateman Randall J. , Morris John C. , Schneider Lon S.
Published: February 2025

INTRODUCTION

CDR-SB is a reliable and clinically meaningful composite for assessing treatment effects in Alzheimer’s disease (AD) clinical trials. Small CDR-SB differences at the end of a trial often lead to controversy in deriving clinically meaningful interpretations.

METHODS

We estimated progression-free time participants remained at each 0.5-unit CDR-SB increment in dominantly inherited AD (DIAD) and sporadic AD populations, evaluating its potential as an alternative measure of treatment effects.

RESULTS

Progression-free time is longer at CDR-SB ≤ 2.0 (1–2 years) and shorter at CDR-SB ≥ 5 (0.33 or less) in the ADNI cohort. The DIAD cohort showed similar but shorter times. Using progression-free time, continuous lecanemab treatment for three years is estimated to delay disease progression by 0.7 years in the sporadic population.

DISCUSSION

Progression-free time provides a benchmark for expressing clinical progression and treatment effects and can be applied particularly during open-label extensions and singlearm trials without placebo comparisons.
Changed epidemiology of influenza and RSV hospitalizations after the emergence of SARS-CoV-2 in Norway, 2017 - 2024
Authors: Bøås Håkon , Seppälä Elina , Veneti Lamprini , Stålcrantz Jeanette , Berild Jacob Dag , Dahl Jesper , Paulsen Trine Hessevik
Published: February 2025

Background

Many countries reported missing and atypical influenza and RSV seasons during the COVID-19 pandemic. Here we describe the incidence and seasonality of COVID-19, influenza, and RSV hospitalizations in Norway between 2017-2024, and the disease burden between 2022-2024.

Methods

Using nationwide data on ICD-10 discharge codes, procedure codes and laboratory results, we calculate the incidence of COVID-19, influenza, and RSV hospitalizations, by age group, week and season between January 2017 to April 2024, and report proportions receiving intensive care, proportion of deaths and length of stay between 2022-2024.

Results

The transmission of influenza and RSV was interrupted the first year of the COVID-19 pandemic and reemerged with epidemics outside of the normal seasonality in 2021/2022, after COVID-19 restrictions were removed. Between 2022-2024, COVID-19 was a greater contributor to hospitalizations than influenza and RSV, with higher mortality rate within two weeks of admission. The use of ventilatory support/intensive care admission was highest among patients hospitalized with RSV.

Conclusion

The transmission of influenza and RSV was interrupted during the first year of the COVID-19 pandemic, followed by an unusual seasonality. Although many hospitalizations are caused by RSV and influenza, COVID-19 was the largest contributor of these three to hospital burden in the first years with co-circulation.
A systems-level insight into PHB-driven metabolic adaptation orchestrated by the PHB-binding transcriptional regulator AniA (PhaR)
Authors: Lagares Antonio , Krol Elizaveta , Müller Tina , Glatter Timo , Becker Anke
Published: February 2025

Polyhydroxybutyrate (PHB) is a carbon and energy storage polymer, whose accumulation under nutrient imbalances with excess carbon is a widespread phenomenon in bacteria. PhaR is a conserved transcriptional regulator found to be associated to PHB granules in several species. Although its role in modulating PHB storage and metabolism has been extensively studied across the bacterial phylogeny, a comprehensive analysis of the PhaR regulon within the context of its dual role as a metabolic sensor and regulator remains missing. To bridge this gap, we integrated co-expression network analysis with proteome profiling across multiple mutant backgrounds (lack of PhaR (AniA) and/or PHB synthesis) in the free-living state of the PHB-accumulating alphaproteobacterial root nodule symbiontSinorhizobium meliloti. This analysis was enriched by identifying direct regulatory targets of PhaR through a regulon-centric computational multi-step search for DNA binding site motifs combined with PhaR-DNA binding and promoter-reporter assays. We confirmed that the model of accumulated PHB sequestering PhaR and thereby relieving phasin and PHB depolymerase gene repression to control cellular PHB levels also applies toS. meliloti, and showed that PhaR-mediated regulation also occurs the symbiotic state. A comprehensive picture of the impact of PHB-mediated PhaR titration on cellular functions revealed exopolysaccharide production as well as central carbon metabolism (pdhandbkd), gluconeogenesis (ppdKandpyc),entry into the TCA cycle (gltA), and the initial steps of the Entner-Doudoroff pathway (zwf, pgl and edd) as major regulatory targets, and beyond carbon metabolism several target genes of yet unknown function. Our findings highlight a pivotal role for PhaR in orchestrating carbon metabolism.
In a pathophysiologic state due to SARS-CoV-2, viscosity and cholesterol are two-edged swords
Authors: Udema Ikechukwu Iloh
Published: February 2025

Much attention has been paid to the genetic composition and molecular biology of viral particles, infection, and micro-anatomical impacts that culminate in fatalities; vaccines have been in continuous development and production; less attention is paid to the fundamental issues of thermodynamics and activation energy characterization of viral RNA replication and cell death. The study aimed at deriving equations that can be fitted to both theoretically and empirically derived data for the quantitation of other thermodynamic parameters and its cognate dimensionless equilibrium constant; some of the derived equations addressed the issue of viscosity and the concentration of cholesterol in particular as they affect translational velocity needed for the delivery of biomolecules to the site of need. The instantaneous velocities before terminal velocity are: ∼ 0.046674 m/s (cytosol); 0.141837 m/s (water). The terminal velocities were approximately equal to 3.548614 nm/s for the cytosol and 99.590626 nm/s for the water; these values were computed using literature values of translational diffusion coefficients (Di) of glucose in cytoplasm and in water. The value in water is higher than in the cytosol because of higher cytosolic viscosity than aqueous viscosity. These support the view that cholesterol and viscosity have a dual-edged effect on the pathophysiologic state orchestrated by SARS-CoV-2; higher viscosities in the membrane and in the cytoplasm enhance binding and infection and can diminish the progress of infection, respectively. Higher feasibility and rates were observed at lower thermodynamic temperatures than at higher ones, according to the outcome of the analysis of the viral binding free energy and activation energy, respectively. The dimensionless constant values were higher at the earlier time of the infection and decreased with time, exhibiting a power law relationship. It is advised, among others, that pharmaceuticals (including airborne surfactants) and drugs in solution be given at temperatures above body temperature. Swab testing should be performed on a regular basis to detect significant infections early. Future in vitro and in vivo studies on viral infection might focus on various time periods at different temperatures, above and below body temperature.

GRAPHICAL ABSTRACT

With vaccine and/or drug the viral infection can regress; without treatment there could be infection and progression into disease state; discontinuation of treatment can cause a reinfection.
Climate change and tuberculosis: an analytical framework
Authors: Saunders Matthew J , Boccia Delia , Khan Palwasha Y , Goscè Lara , Gasparrini Antonio , Clark Rebecca A , Pescarini Julia M , White Richard G , Houben Rein MGJ , Zignol Matteo , Gebreselassie Nebiat , Finn McQuaid C
Published: February 2025

Climate change is likely to exacerbate a range of determinants which drive tuberculosis, the world’s leading infectious disease killer. However, tuberculosis is often neglected in wider climate health discussions.

Commissioned by the World Health Organization, we developed an analytical framework outlining potential causal relationships between climate change and tuberculosis. We drew on existing knowledge of tuberculosis determinants, identified which are likely to be sensitive to the effects of climate change, and conceptualised the mechanistic pathways through which this might occur. We collated evidence for these pathways through literature reviews. Our reviews found no studies directly linking climate change and tuberculosis, warranting research to build evidence for action.

The available evidence supports the existence of plausible links between climate change and tuberculosis, and highlights the need to include tuberculosis in climate risk adaptation and mitigation programmes, and climate-resilient funding and response mechanisms. Further evidence is urgently needed to quantify the effects of climate change on tuberculosis.
Genome-wide association study on longitudinal and cross-sectional traits of child health and development in a Japanese population
Authors: Kumasaka Natsuhiko , Mezawa Hidetoshi , Sakamoto Kei , Isobe Tomohiko , Sato Miori , Saito-Abe Mayako , Yang Limin , Harama Daisuke , Miyaji Yumiko , Nishizato Minaho , Sekiyama Makiko , Iwai Miyuki , Kobayashi Yayoi , Takagi Mai , Tatsuta Nozomi , Taniguchi Yu , Matsumoto Kenji , Nakabayashi Kazuhiko , Kagami Masayo , Noguchi Emiko , Hata Akira , Hata Kenichiro , Okada Yukinori , Tajima Atsushi , Mingyang Shi , Koido Masaru , Kamatani Yoichiro , Matsuda Koichi ,   BioBank Japan, Kawai Yosuke , Tokunaga Katsushi ,   National Center Biobank Network, Kishi Reiko , Ota Chiharu , Hashimoto Koichi , Mori Chisato , Ito Shuich , Shinohara Ryoji , Inadera Hidekuni , Nakayama Takeo , Kawasaki Ryo , Takeshima Yasuhiro , Kageyama Seiji , Morita Akemi , Suganuma Narufumi , Ohga Shoichi , Katoh Takahiko , Kamijima Michihiro , Yamamoto-Hanada Kiwako , Umezawa Akihiro , Fukami Maki , Yamazaki Shin , Nakayama Shoji F. , Ohya Yukihiro
Published: February 2025

Understanding the influence of both genetics and environment on human health, especially early in life, is essential for shaping long-term health. Here, we utilize a nationwide prospective birth cohort, the Japan Environment and Children's Study (JECS), to conduct a large-scale population-based genetic study using biannual questionnaire surveys and biological and physical measurements collected from both parents and their children since the participant mothers were pregnant. Analyses of genome-wide genotyping for 80,638 child participants with parental consent and sufficient DNA from cord blood samples represent the genetic diversity of the general population in Japan. Systematic genome-wide association studies of 1,163 child health and developmental traits (including, e.g., food allergy, anthropometry measurements or ASQ-3 developmental screening) and parental environmental exposure traits (including, e.g., mercury or PFAS exposure) identify 4,985 common genomic loci (of which 1,885 loci passed the phenome-wide significant P=4.3 x 10^(-11)), of which 25% of loci represent novel associations not previously reported. Additional longitudinal GWAS of BMI using Gaussian process regression identified 66 novel dynamic genetic associations along child development. In addition, genetic correlation analysis suggested some evidence that maternal environmental exposures during pregnancy influence child traits at birth. Together with studies of environmental exposures and genetic risk factors, across time and multiple outcomes, these demonstrate the uniqueness and value of the JECS data.
Frequency and Predictors of Adolescent Worry for School Gun Violence In the United States: Findings from a Nationally Representative Study
Authors: Kirkland Danielle , Fu Tsung-chieh , Herbenick Debby , Hensel Devon J.
Published: February 2025

Purpose

While school gun violence (SGV) incidents in the United States (U.S.) have risen sharply over the past decade, limited research has examined adolescent worries about SGV. We examined the frequency and correlates of SGV worry in a U.S. nationally representative sample of adolescents.

Methods

Data were from adolescent participants (14–17 years; N = 1017) in the 2022 National Survey of Sexual Health and Behavior, a nationally representative study of sexual health experiences of people in the U.S. SGV worry was a single 5-point item (not at all worried – extremely worried). We used both weighted descriptive statistics to examine SGV frequency and random intercept mixed effects ordinal regression to examine demographic and background impact on SGV worry.

Results

Nearly 75% of adolescents reported some degree of SGV worry; of these, one in five were very or extremely worried. SGV worry was significantly higher for adolescents in younger grades and among racial/ethnic minority youth, as well as for cisgender female and gender minority teens. Adolescents in higher income homes were less worried about SGV. Both teens living in metropolitan locations and teens who reported higher anxiety in the past two weeks noted higher SGV worry.

Conclusions

U.S. adolescents have a substantial level of worry about school gun violence. Structural interventions are needed to reduce SGV itself. Moreover, because there are detrimental long-term impacts of prolonged worry, targeted interventions are important for reaching those who are at greatest worry risk, including lower income, race/ethnic minority and gender minority teens.

Implications and Conclusions

Three out of every four adolescents in the United States worry about being a victim of school gun violence. Structural interventions to both reduce SGV itself and to reach adolescents at greatest risk for SGV worry are warranted.
An integrated framework for early detection and transmissibility assessment of emerging variants in wastewater
Authors: Chen Xingwen , Phan Tin , Lee Wei Lin , Rhode Steven , Brozak Samantha , Pell Bruce , Palden Tsultrim , Leifels Mats , Gitter Anna , Kuang Yang , Wuertz Stefan , Thompson Janelle , Mena Kristina , Alm Eric , Wu Fuqing
Published: February 2025

Tracking the emergence of new SARS-CoV-2 variants is important for a comprehensive understanding of the pandemic's progression. However, it remains challenging due to the low variant prevalence in the early stage of an outbreak. Here, we present an integrated framework that combines three key components: early variant detection in wastewater, validation through clinical genome sequencing, and transmissibility assessment using mathematical modeling. Using the SARS-CoV-2 Omicron variant as a proof of concept, we developed a novel nested allele-specific RT-qPCR assay (NAS-PCR) for wastewater surveillance. Our framework detected Omicron in Greater Boston wastewater samples starting from September 2021, over two months before the first U.S. clinical case. We validated these findings by analyzing GISAID clinical sequence data, which revealed 172 previously unreported Omicron genomes predating its official identification in South Africa. To assess transmissibility, we developed a Susceptible-Infected-Viral load model using quantified wastewater concentrations, which estimated Omicron's basic reproduction number (R0) between 2.36 and 3.09, showing robust consistency across varying population sizes, data points, and viral shedding rates. This integrated approach unifies molecular diagnostics, wastewater epidemiology, and mathematical modeling for comprehensive variant surveillance. Our framework provides a systematic solution for early warning and risk assessment of emerging variants, which can strengthen public health preparedness for future viral threats.
Fibroblast growth factor 21 regulates neuromuscular junction innervation through HDAC4 in denervation-induced skeletal muscle atrophy
Authors: Zheng Lirong , Sasaki Takashi , Ni Liyang , Takahashi Yu , Yamauchi Yoshio , Shimizu Makoto , Ryuichiro Sato
Published: February 2025

Skeletal muscles undergo atrophy in response to denervation and neuromuscular diseases. Understanding the mechanisms by which denervation drives muscle atrophy is crucial for developing therapies against neurogenic muscle atrophy. Here, we identify muscle-secreted fibroblast growth factor 21 (FGF21) as a key inducer of atrophy following muscle denervation. In denervated skeletal muscles, FGF21 is uniquely upregulated among the FGF family members and acts in an autocrine/paracrine manner to promote muscle atrophy. Silencing FGF21 in muscle prevents denervation-induced muscle wasting by preserving neuromuscular junction (NMJ) innervation. Conversely, forced expression of FGF21 in muscle reduces NMJ innervation, leading to muscle atrophy. Mechanistically, TGFB1 released by denervated fibro-adipogenic progenitors (FAPs) upregulates FGF21 through the JNK/c-Jun axis, which in turn reduces the cytoplasmic level of histone deacetylase 4 (HDAC4), culminating in muscle atrophy. HDAC4 knockdown abolishes the atrophy-resistant effects observed in FGF21-deficient denervated muscles, resulting in muscle atrophy. Our findings reveal a novel role and heretofore unrecognized mechanism of FGF21 in skeletal muscle atrophy, suggesting that inhibiting muscular FGF21 could be a promising strategy for mitigating skeletal muscle atrophy.
Developing Interferon-β as a safe in-vivo experimental-medicine model of human inflammation
Authors: Periche-Tomas Eva , Maclver Claire , Underwood John , Leach Helena , Bone Claudia , Jones Simon , Szomolay Barbara , Triantafilou Kathy , Harrison Neil A.
Published: February 2025

Background

Inflammation is increasingly implicated in a wide range of neuropsychiatric disorders ranging from depression through age- and infection-related cognitive decline to dementia. Arguably, the most important evidence supporting an aetiological role for inflammation in these conditions in humans has come from studies of patients receiving IFN- α therapeutically or longitudinal follow-up of patients after naturalistic infections (e.g., hepatitis C). These experimental medicine-type approaches have identified a discrete set of brain regions e.g. amygdala-hippocampus-hypothalamus, insula and anterior cingulate as well as dopamine-rich subcortical structures that are particularly sensitive to systemic inflammation. Coupled with renewed interest in developing novel immune-targeted therapies for neuropsychiatric disorders as diverse as depression and neurodegenerative disorders, this has highlighted the urgent need for a safe, reliable in-vivo experimental medicine model of inflammation that can be used across the age range. To date, this need has been partially addressed by access to short-acting forms of Interferon-alpha or human (GMP) grade lipopolysaccharide (LPS). However, unpegylated IFN-α is no longer commercially available and the costs and cardiovascular monitoring requirements of low-dose (i.e. 0.8-1ng/Kg i.v. endotoxin) LPS are prohibitive and particularly challenging to use in older or more vulnerable populations.

Aim

Develop a new experimental model of human inflammation that elicits robust sickness responses within a few hours but with minimal cardiovascular effects, thus avoiding the need for continuous cardiac monitoring and ensuring applicability across diverse experimental contexts and participant groups from the young to the elderly.

Methods

Using a randomized, placebo-controlled, repeated measures cross-over design, physiological, behavioural, immune and transcriptomic responses were collected from 30 healthy volunteers (15 young [18-34] and 15 old [60-75]) following both IFN-β (EXTAVIA® [100 µg]) and saline (placebo) injections.

Results

IFN-β induced a robust systemic immune response, evidenced by significant increases in temperature, heart rate, immune cell activation (lymphocytes, monocytes and neutrophils) and levels of IFN-β, IL-10 and TNF-α cytokines. These physiological changes were accompanied by significant increases in negative mood, tiredness, tension and sickness symptoms aa well as by a decrease in vigour.

Conclusions

FN-β is a safe and robust new experimental model of mild acute inflammation, This minimally invasive and effective design can induce transient changes in systemic inflammation in healthy individuals from 18-75. A more refined, ecologically valid model similar to the mild inflammation typically reported in psychiatric disorders like depression or cognitive impairment.
Intracellular Trafficking SNARE Protein, Syntaxin-6, is a Modifier of Prion and Tau Pathogenesisin vivoand in Cellular Models
Authors: Hill Elizabeth , Patel Mitali , Ribes Juan M , Linehan Jacqueline , Zhang Fuquan , Farmer Michael , Jakubcova Tatiana , Hamdan Shyma , Tomlinson Andrew , Ercolani Tiziana , Schmidt Christian , Ahmed Parvin , Thirlway George , Purro Silvia , Argentina Fabio , Marinho Aline T , Jones Emma , Kaye Nicholas , Fitzhugh Craig , de Silva Rohan , Jackson Graham S , Brandner Sebastian , Kloehn Peter , Collinge John , Cunningham Thomas J , Mead Simon
Published: February 2025

Syntaxin-6, a SNARE protein involved in intracellular protein trafficking, is a proposed risk factor for sporadic prion disease, progressive supranuclear palsy and Alzheimer’s disease. However, no study has validated its functional role in these diseases, explored the disease stage at which it is acting nor its mechanism of action. Here, we show that syntaxin-6 acts at early stages of prion disease in experimental mice by increasing disease transmission risk following inoculation with low prion doses. Conversely, syntaxin-6 does not affect prion propagation kinetics or toxicity during established disease. Syntaxin-6 manipulation in cellular models profoundly alters the subcellular distribution and morphologies of disease-related PrP and modifies prion export. Furthermore, syntaxin-6 knockout in a transgenic tauopathy mouse model exerts protective effects on numerous physiological, behavioural and neuropathological outcome measures. Therefore, our studies firmly establish syntaxin-6 as a modifier of prion and tau pathogenesis, providing key insights into a fundamental mechanism of neurodegeneration.
Lysyl-phosphatidylglycerol promotes cell-to-cell interaction and biofilm formation ofStaphylococcus aureusas a biofilm matrix component
Authors: Sugimoto Shinya , Hara Keiichiro , Taketomi Yoshitaka , Nagasaki Yuki , Sato Chikara , Murakami Makoto , Kinjo Yuki
Published: February 2025

Biofilms formed byStaphylococcus aureuscontribute significantly to persistent infections and antibiotic resistance, driven by the unique composition of their extracellular matrix. While previous studies highlighted extracellular DNA, proteins, and polysaccharides as key components, the role of phospholipids in biofilm architecture remains underexplored. This study identifies extracellular phospholipids, including lysyl-phosphatidylglycerol (Lys-PG), phosphatidylglycerol, and cardiolipin (CL), as critical structural elements inS. aureusbiofilms. Bacterial phospholipase A1(PLA1) that cleaves the acyl ester bond at thesn-1 position of phospholipids effectively dispersed pre-formed biofilms and prevented new biofilm formation by hydrolyzing extracellular phospholipids, without affecting bacterial growth or exhibiting cytotoxicity. Microscopy analyses confirmed that PLA1disrupts membranous nanostructures, including extracellular vesicles and nanofilaments, integral to biofilm stability. Lipidomic analysis revealed an enrichment of Lys-PG and CL in the biofilm matrix. Lys-PG promotes bacterial aggregation by acting as a molecular glue, mediated through electrostatic and hydrophobic interactions. Deletion of themprFgene, responsible for Lys-PG synthesis, significantly impaired biofilm formation, confirming its essential role. These findings reveal a "moonlighting" function of phospholipids in biofilm architecture, providing insights into biofilm biology and presenting PLA1as a promising tool for biofilm control.

Significance

Biofilms, dense bacterial communities, pose significant challenges across medical, industrial, and daily life contexts. Understanding their formation mechanisms is crucial for developing effective strategies against them. We investigated biofilm matrix components inS. aureusbiofilms, focusing on phospholipids. Our study reveals the presence and significance of Lys-PG in the biofilm matrix, acting as a crucial factor in biofilm formation and maintenance. Through biochemical, lipidomic, and genetic analyses, we demonstrate the role of Lys-PG in facilitating cell-to-cell contacts, contributing to the robustness and thickness ofS. aureusbiofilms. These findings shed light on the physiological function of extracellular phospholipids in bacterial biofilms and suggest targeting Lys-PG and its synthetic mechanism as a promising strategy for biofilm control.
Drivers of avian genomic change revealed by evolutionary rate decomposition
Authors: Duchêne David A. , Chowdhury Al-Aabid , Yang Jingyi , Iglesias-Carrasco Maider , Stiller Josefin , Feng Shaohong , Gilbert M. Thomas P. , Zhang Guojie , Tobias Joseph A. , Ho Simon Y. W.
Published: February 2025

Modern bird diversity spans a striking array of forms, behaviours, and ecological roles. Analyses of molecular evolutionary rates can reveal the links between genomic and phenotypic change, but disentangling the drivers of rate variation has been difficult across large numbers of whole-genomes. Using comprehensive estimates of traits and evolutionary rates across a family-level phylogeny of birds, we show that clutch size, generation length, and beak shape are dominant predictors of genome-wide mutation rates. To identify the major axes of evolutionary rate variation, we employ covariance matrix eigendecomposition from rates estimated for branches of the avian phylogeny and across genomic loci. We find that the majority of rate variation occurs along the terminal branches of the phylogeny associated with extant families of birds. Additionally, we use principal components analyses to show that several axes of variation are linked with rapid evolution in microchromosomes immediately after the Cretaceous–Palaeogene transition. These apparent pulses of evolution are consistent with major changes in evolutionary rates in the machineries for meiosis, heart performance, and RNA splicing, surveillance, and translation. They also correlate with the diversification of ecological niches reflected in increased tarsus length. Collectively, our analyses paint a nuanced picture of avian evolutionary rates through time, revealing that the ancestors of the most diverse lineages of birds underwent major genomic changes related to mutation, gene usage, and niche expansion near the beginning of the Palaeogene period.