bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and external validation of prediction models for major osteoporotic fracture and hip fracture in people with intellectual disability
Authors: Smith Margaret , Roast Jan , Collins Gary S. , Holt Tim A. , Frighi Valeria 
Published: February 2025

SummaryPurposeCompared with the general population, people with intellectual disabilities (ID) have higher incidences of major osteoporotic fracture (MOF) and hip fracture (HF), and osteoporosis develops at a younger age. The rate of HF in those aged 50 years and over is two and four times higher than that in women and men, respectively, without ID. It is essential to identify people with ID at risk of such fractures so that a targeted fracture prevention strategy can be designed. However, current fracture prediction models are derived from the general population and may underestimate risk in the ID population.MethodsPrediction models (IDFracture) for the 10-year risk of HF and MOF were developed and validated in populations of people with ID aged 30-79 years. Models were developed in the CPRD GOLD database and temporally validated in the Aurum database. The predictors included those in current fracture prediction models and ID-specific predictors such as Down syndrome. All the predictors were included in the Cox regression models. Bootstrapping was used to adjust for overfitting.ResultsThe development cohort included 38,665 people with IDs, 1045 with MOFs and 360 with HFs within 10 years. The external validation cohort included 76,385 people, 2420 MOFs and 1001 HFs. Discrimination, as judged by the C statistic, was good: MOF 0.775, HF 0.839. The calibration was also good but tended to overpredict at the highest predicted risks.ConclusionIDFracture has potential as a screening tool in clinical practice to identify people with ID who are at increased risk of MOF and HF.Mini AbstractBrief rationalePeople with intellectual disability (ID) have a relatively high incidence of fracture, so current risk prediction models are not appropriate.Main resultA new prediction model for people with ID showed good calibration and discrimination in external validation.Significance of paperThis is the first such prediction model developed for people with ID.
Dissecting the genetic etiology of intestinal obstruction: mendelian randomization identifies potential therapeutic targets
Authors: Haodong Zhao , Baoping Cai , Jiongjiong Chen , Jia Chen , hui Liu , Yu Wang , bocheng Ding 
Published: February 2025

AbstractIntestinal obstruction, a prevalent and serious condition, necessitates deeper understanding of its genetic architecture. This study rigorously employed two-sample Mendelian randomization to dissect the causal influence of gene expression on intestinal obstruction risk, leveraging comprehensive summary-level data from eQTLGen and FinnGen GWAS. To enhance causal inference, Summary-data-based Mendelian Randomization was integrated, utilizing GTEx eQTL data to specifically assess tissue-relevant gene expression. Our multi-pronged analyses provide compelling genetic evidence supporting causal roles for genetically predicted expression ofCHRNB2andMIATin intestinal obstruction. Specifically, increased genetically proxiedCHRNB2expression was associated with a protective effect, while higher genetically proxiedMIATexpression suggested an elevated susceptibility to intestinal obstruction. Colocalization analysis, alongside HEIDI heterogeneity testing within the SMR framework, further bolstered the robustness of these findings by distinguishing causality from linkage disequilibrium. These convergent results offer novel mechanistic insights into intestinal obstruction pathogenesis, positioningCHRNB2andMIATas promising therapeutic targets for both prevention and treatment strategies. Future research is crucial to validate these findings across diverse ancestries and to fully elucidate the intricate biological mechanisms underpinning these gene-disease associations.
Risk Stratification for Endometrial Cancer Reveals Independent Contributions of Polygenic Risk and Body Mass Index
Authors: Wang Xuemin , Dossus Laure , Gunter Marc J. , Crosbie Emma J. , Ong Jue-Sheng , Glubb Dylan M. , O’Mara Tracy A. 
Published: February 2025

AbstractBackgroundObesity is a major risk factor for endometrial cancer, but it is unknown whether it impacts the association between genetic risk and endometrial cancer. We incorporated polygenic risk score and epidemiological risk factors in the prediction of and investigated associations of BMI and polygenic risk score with endometrial cancer riskMethodsWe generated polygenic risk score for endometrial cancer in 129,829 unrelated female participants of European ancestry (including 956 incident cases with endometrial cancer) in the UK Biobank and predicted endometrial cancer using endometrial cancer polygenic risk score and established epidemiological risk factors, including BMI. We evaluated the performance of endometrial cancer prediction models by odds ratios and area under the receiver operating characteristic curves (AUCs) to using logistic regression. Individual and joint associations of BMI and polygenic risk score with endometrial cancer were assessed using Cox proportional hazards models.ResultsAn integrated model incorporating both polygenic risk score and epidemiological risk factors achieved a modest, but statistically significant, improvement in predicting endometrial cancer status compared with the model that included epidemiologic risk factors alone (AUC = 0.74 versus 0.73;P= 3.98 × 10−5). Obese participants (BMI ≥ 30 kg/m2) in the top polygenic risk tertile had the highest endometrial cancer risk. We observed independent effects of genetic risk and BMI on endometrial cancer risk.ConclusionIntegrating polygenic risk score with epidemiological risk factors may offer insights into population stratification for endometrial cancer susceptibility. Higher endometrial cancer polygenic risk is associated with endometrial cancer, irrespective of BMI.
Discovering Signature Disease Trajectories in Pancreatic Cancer and Soft-tissue Sarcoma from Longitudinal Patient Records
Authors: Wang Liwei , Li Rui , Wen Andrew , Lu Qiuhao , Wang Jinlian , Ruan Xiaoyang , Gamboa Adriana , Malik Neha , Roland Christina L. , Katz Matthew H.G. , Lyu Heather , Liu Hongfang 
Published: February 2025

AbstractUnderstanding the disease trajectories of specific diseases can provide important clinical insights. In this paper, we aimed to discover signature disease trajectories of 3 rare cancer types: pancreatic cancer, soft tissue sarcoma (STS) of the trunk and extremity (STS-TE), and STS of the abdomen and retroperitoneum (STS-AR), leveraging IQVIA Oncology Electronic Medical Record. We identified significant diagnosis pairs in patients with these cancers through matched cohort sampling, statistical computation, right-tailed binomial hypothesis test, and visualized trajectories up to 3 progressions. Results included 266 significant diagnosis pairs for pancreatic cancer, 130 for STS-TE, and 118 for STS-AR. We further found 44 2-hop (i.e., 2- progression) and 136 3-hop trajectories before pancreatic cancer, 36 2-hop and 37 3-hop trajectories before STS-TE, and 17 2-hop and 5 3-hop trajectories before STS-AR. Meanwhile, we found 54 2-hop and 129 3-hop trajectories following pancreatic cancer, 11 2-hop and 17 3- hop trajectories following STS-TE, 5 2-hop and 0 3-hop trajectories following STS-AR. Systematic validation of discovered trajectories with the UTHealth Electronic Health Records confirmed the feasibility and reliability of our method. Our result suggested that some key clinical features can potentially serve as early markers of rare cancers. This approach is generalizable to other disease types and real-world longitudinal patient records.
Exploring Causal Association between Neuroticism Subclusters and Risk of Coronary Atherosclerosis: A Mendelian Randomization Analysis based on Genome-Wide Association Studies
Authors: Ming Jie , Li Rui-lin , Gao Yi-li , Huang Shu-ting , Yao Xiao-yan , Tan Qi , Zong Ming , Fan Lie-ying 
Published: February 2025

ABSTRACTBackgroundUnderstanding the risk factors associated with coronary atherosclerosis (CA)—an evident cardiovascular disease—is vital. This study aimed to explore the causal relationship between neuroticism subclusters and CA, focusing on lipids as mediators, using genome-wide association studies and Mendelian randomization (MR).Methods and ResultsInstrumental variables were selected based on their genetic associations with neuroticism subclusters and CA. Causal effects were primarily assessed using inverse variance-weighted (IVW) methods. Sensitivity analyses and colocalization analyses were conducted, and possible confounders were determined using multivariable MR analysis. IVW modeling revealed that neuroticism subclusters significantly affect CA risk (ebi-a-GCST006475odds ratio [OR]: 1.02, 95% confidence interval [95%CI]: 1.01–1.03,P= 1.52E-05;ebi-a-GCST006478OR: 1.01, 95%CI: 1.00–1.02,P= 0.026;ebi-a-GCST006950OR: 1.01, 95%CI: 1.00–1.02,P= 0.036). Cochran’s Q test demonstrated moderate heterogeneity (ebi-a-GCST006475,P< 0.05,I²= 28%). The Steiger test confirmed the correct causal direction (P< 0.05). Multivariable MR remained significant after adjusting for confounders (P< 0.05). Mediation analyses suggested that lipids partially mediated the neuroticism–CA effect.ConclusionsOverall, our findings indicated a causal link between neuroticism subclusters and CA, with lipids partially mediating this relationship, emphasizing the role of psychosocial factors in cardiovascular risk assessment and intervention strategies.
Neuronal development shapes activity-dependent gene expression in a stimulus-specific manner
Authors: Lukin Jeronimo , Beckel Maximiliano S , Pedroncini Olivia , Giusti Sebastian A , Linenberg Ivana Marcela , Patop Ines Lucia , Chernomoretz Ariel , Marin-Burgin Antonia , Kadener Sebastian , Refojo Damian 
Published: February 2025

ABSTRACTNeuronal activity-dependent gene expression is fundamental to a wide variety of brain functions. However, how development progress and stimulation modalities specifically affect neuron transcription is not fully understood. In this work, we first investigate the influence of development on neuronal firing and activity-driven transcription. We used an RNA sequencing approach over 7 daysin vitro(DIV) or mature 21 DIV neurons, comparing neuronal depolarization with potassium chloride (KCl) versus Biccuculine application, a synaptic modality to induce neuronal activity. To further investigate how different activity patterns influence gene transcription in mature neurons, we compared global gene expression in neurons treated with three different and extensively used activation protocols: KCl, Bicuculine (Bic), and TTX withdrawal (TTXw). Our results demonstrate a strong influence of development on activity-dependent gene expression, and showed that different patterns of neuronal activity induce different transcriptional profiles and exhibit distinct temporal dynamics for the same genes. These findings offer novel insights into the complex relationship between neuronal activity and gene expression, shedding light on the context-dependent nature of activity-dependent transcriptional responses.
Ciliated cell domains with locally coordinated ciliary motion generate a mosaic of microflows in the brain’s lateral ventricles
Authors: Mellanson Kennelia , Zhou Lei , Michurina Tatiana , Mikhailik Anatoly , Benveniste Helene , Samaras Dimitris , Enikolopov Grigori , Peunova Natalia 
Published: February 2025

AbstractCirculation of cerebrospinal fluid (CSF) through the brain’s ventricles is essential for maintaining brain homeostasis and supporting neurogenesis. CSF flow is supported by the structural polarization of multiciliated cells, which align with the flow direction. However, it remains unclear how the organization of tissue-wide polarity across the ciliary epithelium comprised of thousands of cells, determines the trajectory of the flow and efficient distribution of the CSF.Here, we used new approaches to analyze the organization of translational polarity across extensive areas of the lateral ventricular wall. We also used live imaging to examine cilia motion, flow trajectories, and ciliary beat frequency (CBF) in live preparations of ventricles. In addition to the primary flow running across the ventricular wall from the posterior area to the anterior (P-A), we found multiple local microflows with both direct and curved trajectories that deviate from the mainstream P-A direction.Our results suggest that the ciliated epithelium in the lateral ventricles varies in the alignment of ciliated cell translational polarity: whereas in the narrow dorsal area translational polarity is aligned with the direction of the mainstream flow, in the periphery of the mainstream it is organized into distinct cell clusters with locally aligned polarity vectors. We posit that the cluster organization of the multiciliated ependymal cells underpins the generation of a complex mosaic of flows, with the local microflows facilitating the wide spreading of the CSF across the ependyma. We demonstrate that nNOS is involved in the control of translational polarity, cluster organization, microflows, and CBF in the ependyma.SignificanceThe flow of cerebrospinal fluid (CSF) is crucial for brain homeostasis. This flow is driven by the coordinated beating of cilia on thousands of ciliated cells. Planar polarity vector of the ciliated cells is aligned with the flow direction in the areas of the ependyma underlying the mainstream flow (1). However, the overall alignment of planar cell polarity and flow across the whole tissue is unclear. Here we report a discovery of complex flow patterns over the ependyma, consisting of numerous microflows in the periphery of the mainstream flow. Using new approaches, we found that planar polarity of the ependymal ciliated cells on the periphery of the mainstream flow aligns only locally, indicating a clustered organization of the ependyma that supports various flow directions.
Characterization of neurite and soma organization in the brain and spinal cord with diffusion MRI
Authors: Schilling Kurt G , Palombo Marco , Witt Atlee A. , O’Grady Kristin P. , Pizzolato Marco , Landman Bennett A , Smith Seth A. 
Published: February 2025

AbstractThe central nervous system (CNS), comprised of both the brain and spinal cord, and is a complex network of white and gray matter responsible for sensory, motor, and cognitive functions. Advanced diffusion MRI (dMRI) techniques offer a promising mechanism to non-invasively characterize CNS architecture, however, most studies focus on the brain or spinal cord in isolation. Here, we implemented a clinically feasible dMRI protocol on a 3T scanner to simultaneously characterize neurite and soma microstructure of both the brain and spinal cord. The protocol enabled the use of Diffusion Tensor Imaging (DTI), Standard Model Imaging (SMI), and Soma and Neurite Density Imaging (SANDI), representing the first time SMI and SANDI have been evaluated in the cord, and in the cord and brain simultaneously. Our results demonstrate high image quality even at high diffusion weightings, reproducibility of SMI and SANDI derived metrics similar to those of DTI with few exceptions, and biologically feasible contrasts between and within white and gray matter regions. Reproducibility and contrasts were decreased in the cord compared to that of the brain, revealing challenges due to partial volume effects and image preprocessing. This study establishes a harmonized approach for brain and cord microstructural imaging, and the opportunity to study CNS pathologies and biomarkers of structural integrity across the neuroaxis.
Learning molecular traits of human pain disease via voltage-gated sodium channel structure renormalization
Authors: Xenakis Markos N. , Lampert Angelika 
Published: February 2025

AbstractMammalian neurophysiology vitally depends on the stable functioning of transmembrane, pore-forming voltage-sensing proteins known as voltage-gated sodium channels (NaVChs). Deciphering the principles of NaVCh spatial organization can illuminate fundamental structure-function aspects of pore-forming proteins and offer new opportunities for pharmacological treatment of associated diseases such as chronic pain. Here, we introduce a renormalization group flow paradigm permitting a formal investigation of NaVCh thermostability properties. Our procedures are solidified by deriving aq-deformed statistical mechanical entropy and validated over 121 experimentally resolved NaVCh structures of prokaryotic and eukaryotic origin. We uncover the universality of a critical inflection point regulating the thermostability of the pore domain relative to the voltage sensors, summarized in terms of a generalized Widom scaling law. A machine learning algorithm, rationalized in terms of the ‘loosening’ of inertia and conductivity channel constraints, identifies pain-disease-associated mutation hotspots in the human NaV1.7 channel. Our work illustrates how first-principles-based machine learning approaches can deliver accurate insights for human pain medicine and clinicians at a reduced computational cost, while clarifying the self-organized critical nature of NaVChs.
A Myosin Nanomotor Essential for Stereocilia Maintenance Expands the Etiology of Hereditary Hearing Loss DFNB3
Authors: Behnammanesh Ghazaleh , Dragich Abigail K. , Liao Xiayi , Hadi Shadan , Kim Mi-Jung , Perrin Benjamin , Someya Shinichi , Frolenkov Gregory I. , Bird Jonathan E. 
Published: February 2025

ABSTRACTCochlear hair cells transduce sound using stereocilia, and disruption to these delicate mechanosensors is a significant cause of hearing loss. Stereocilia architecture is dependent upon the nanomotor myosin 15. A short isoform (MYO15A-2) drives stereocilia development by delivering an elongation-promoting complex (EC) to stereocilia tips, and an alternatively spliced long isoform (MYO15A-1) tunes postnatal size in shorter stereocilia, which possess mechanosensitive ion channels. Disruption of these functions causes two distinct stereocilia pathologies, which underly human autosomal recessive non-syndromic hearing loss DFNB3. Here, we characterize a new isoform, MYO15A-3, that increases expression in postnatal hair cells as the developmental MYO15A-2 isoform wanes reciprocally. We show the critical EC complex is initially delivered by MYO15A-2, followed by a postnatal handover to MYO15A-3, which continues to deliver the EC. In aMyo15a-3mutant mouse, stereocilia develop normally with correct EC targeting, but lack the EC postnatally and do not maintain their adult architecture, leading to progressive hearing loss. We conclude MYO15A-3 delivers the EC in postnatal hair cells and that the EC and MYO15A-3 are both required to maintain stereocilia integrity. Our results add to the spectrum of stereocilia pathology underlying DFNB3 hearing loss and reveal new molecular mechanisms necessary for resilient hearing during adult life.
Reduced amino acid substitution matrices find traces of ancient coding alphabets in modern day proteins
Authors: Douglas Jordan , Bouckaert Remco , Carter Charles W. , Wills Peter R. 
Published: February 2025

AbstractAll known living systems make proteins from the same twenty canonically-coded amino acids, but this was not always the case. Early genetic coding systems likely operated with a restricted pool of amino acid types and limited means to distinguish between them. Despite this, amino acid substitution models like LG and WAG all assume a constant coding alphabet over time. That makes them especially inappropriate for the aminoacyl-tRNA synthetases (aaRS) - the enzymes that govern translation. To address this limitation, we created a class of substitution models that accounts for evolutionary changes in the coding alphabet size by defining the transition from nineteen states in a past epoch to twenty now. We use a Bayesian phylogenetic framework to improve phylogeny estimation and testing of this two-alphabet hypothesis. The hypothesis was strongly rejected by datasets composed exclusively of “young” eukaryotic proteins. It was generally supported by “old” (aaRS and non-aaRS) proteins whose origins date from before the last universal common ancestor. Standard methods overestimate the divergence ages of proteins that originated under reduced coding alphabets in both simulated and aaRS alignments. The new model reduces this bias substantially. Our findings support the late incorporation of tryptophan into the genetic code (relative to tyrosine) and suggest that isoleucine and valine were once coded interchangeably, forming protein quasispecies. This work provides a robust, seamless framework for reconstructing phylogenies from ancient protein datasets and offers further insights into the dawn of molecular biology.
De novo annotation of centromere with centroAnno
Authors: Qi Junhai , Ma Junchi , Han Renmin , Han Zheng , Yu Ting , Li Guojun 
Published: February 2025

AbstractAccurate centromere annotation is essential for elucidating chromosomal stability, gene regulation, and the complexities of genome architecture. However, existing methods are often constrained by their dependence on prior knowledge and their limited applicability across diverse genomic contexts. In this study, we present Centromere Annotator (centroAnno), a novel de novo algorithm tailored for the precise annotation of centromeres and tandem repeats directly within complex genomes, assemblies, centromeric sequences, or raw sequencing data. Through extensive evaluations on both simulated and real-world datasets, centroAnno consistently outperforms existing tools in annotation accuracy. Additionally, centroAnno significantly enhances efficiency, achieving annotation speeds 12 to 44 times faster than other methods when applied to human centromeric regions.
Fusion of magnet resonance imaging and electronic health records promotes the multimodal prediction of postoperative delirium
Authors: Giesa Niklas , Dell’Orco Andrea , Scheel Michael , Finke Carsten , Balzer Felix , Spies Claudia Doris , Sekutowicz Maria 
Published: February 2025

AbstractThe role of individual brain morphometry, derived from clinical imaging, for the analysis as well as the early prediction of postoperative delirium (POD), as a severe complication after a surgery, is currently under-explored. We extensively analyzed patient trajectories of magnet resonance imaging (MRI) and electronic health records (EHRs) for two POD definitions covering 557 and 201 patients. Age-adjusted correlations with linear mixed-effect models identified middle temporal and superior temporal cortical thickness as well as thalamus and brain stem volumes. We trained highly non-linear multi-layer perceptrons (MLPs) on EHRs, MRI measures, and the combination of both as multimodal fusions. MLP models achieved high performance metrics, as are under receiver operating characteristics (AUROC) values up to 86%, outperforming baselines. Multimodal fusion was especially beneficial for 645 less critically ill patients. MLP model weights for this cohort focused on cerebral atrophy measures of higher order cortical areas, such as the temporalpole -, superiofrontal gyrus-, and the insula. Our results pave the way for the far unrecognized potential of clinical MRI features for early multimodal predictions of POD.