bluuebunny/crossref_metadata_2025_split huggingface dataset:
Leveraging functional annotations to map rare variants associated with Alzheimer’s disease with gruyere
Authors: Das Anjali , Lakhani Chirag , Terwagne Chloé , Lin Jui-Shan T. , Naito Tatsuhiko , Raj Towfique , Knowles David A. 
Published: December 2024

AbstractThe increasing availability of whole-genome sequencing (WGS) has begun to elucidate the contribution of rare variants (RVs), both coding and non-coding, to complex disease. Multiple RV association tests are available to study the relationship between genotype and phenotype, but most are restricted to per-gene models and do not fully leverage the availability of variant-level functional annotations. We propose Genome-wide Rare Variant EnRichment Evaluation (gruyere), a Bayesian probabilistic model that complements existing methods by learning global, trait-specific weights for functional annotations to improve variant prioritization. We applygruyereto WGS data from the Alzheimer’s Disease (AD) Sequencing Project, consisting of 7,966 cases and 13,412 controls, to identify AD-associated genes and annotations. Growing evidence suggests that disruption of microglial regulation is a key contributor to AD risk, yet existing methods have not had sufficient power to examine rare non-coding effects that incorporate such cell-type specific information. To address this gap, we 1) use predicted enhancer and promoter regions in microglia and other potentially relevant cell types (oligodendrocytes, astrocytes, and neurons) to define per-gene non-coding RV test sets and 2) include cell-type specific variant effect predictions (VEPs) as functional annotations.gruyereidentifies 15 significant genetic associations not detected by other RV methods and finds deep learning-based VEPs for splicing, transcription factor binding, and chromatin state are highly predictive of functional non-coding RVs. Our study establishes a novel and robust framework incorporating functional annotations, coding RVs, and cell-type associated non-coding RVs, to perform genome-wide association tests, uncovering AD-relevant genes and annotations.
Reasoning Models for Text Mining in Oncology – a Comparison Between o1 Preview and GPT-4o
Authors: Windisch Paul , Dennstädt Fabio , Schröder Christina , Zwahlen Daniel R. , Förster Robert 
Published: December 2024

AbstractPurposeChain-of-thought prompting is a method to make a Large Language Model (LLM) generate intermediate reasoning steps when solving a complex problem to increase its performance. OpenAI’s o1 preview is an LLM that has been trained with reinforcement learning to create such a chain-of-thought internally, prior to giving a response and has been claimed to surpass various benchmarks requiring complex reasoning. The purpose of this study was to evaluate its performance for text mining in oncology.MethodsSix hundred trials from high-impact medical journals were classified depending on whether they allowed for the inclusion of patients with localized and/or metastatic disease.GPT–4o and o1 preview were instructed to do the same classification based on the publications’ abstracts.ResultsFor predicting whether patients with localized disease were enrolled, GPT-4o and o1 preview achieved F1 scores of 0.80 (0.76 - 0.83) and 0.91 (0.89 - 0.94), respectively. For predicting whether patients with metastatic disease were enrolled, GPT-4o and o1 preview achieved F1 scores of 0.97 (0.95 - 0.98) and 0.99 (0.99 - 1.00), respectively.Conclusiono1 preview outperformed GPT-4o for extracting if people with localized and or metastatic disease were eligible for a trial from its abstract. o1 previews’s performance was close to human annotation but could still be improved when dealing with cancer screening and prevention trials as well as by adhering to the desired output format. While research on additional tasks is necessary, it is likely that reasoning models could become the new state of the art for text mining in oncology and various other tasks in medicine.
Association of CD7⁺CXCR3⁺ CAR T cells with long-term remission in R/R DLBCL
Authors: Bartolini Robin , Trueb Lionel , Daoudlarian Douglas , Joo Victor , Noto Alessandra , Stadelmann Raphaël , Gentner Bernhard , Fenwick Craig , Perreau Matthieu , Coukos Georges , Pantaleo Giuseppe , Arber Caroline , Obeid Michel 
Published: December 2024

AbstractBackground.CAR T-cell therapy is the standard of care for R/R DLBCL, but more than half of patients fail to achieve long-term remission. Identification of cellular biomarkers in CAR T- cell infusion products (IPs) that predict complete remission beyond six months may guide the development of strategies to improve outcomes.Methods.IPs from 13 R/R DLBCL patients were analyzed using a 39-marker mass cytometry panel, comparing cell populations between long-term responders (R) and non-responders (NR). Both unsupervised and supervised analyses were performed. Longitudinal blood samples were analyzed for 30 days to track CAR T-cell subpopulation dynamics.Results.At a median follow-up of 13.5 months, median progression-free survival (PFS) was 13.3 months (95% CI: 9.7-24.3) in R (n=8) versus 3.5 months (95% CI: 0.5-5.4) in NR (n=5).The HR for PFS was 56.67 (95% CI: 7.3-439.3; P=0.0001). A subset of CD3+CXCR3+CD7+CAR T-cells found in both CD4+and CD8+populations was significantly enriched in R and expressed higher levels of perforin, granzyme B, and NKG2D (restricted to CD8+). NR had more CXCR3+CD7+LAG3+CAR T-cells. CD3, CD7, CXCR3, and NKG2D cell surface levels were higher in R, whereas LAG3, Ki67, and CD71 were elevated in NR. A predictive cut-off ratio of CD3+CXCR3+CD7+LAG3+CAR+T-cells <0.83 and CD3+CXCR3+CD7+NKG2D+CAR+T-cells >1.034 yielded a predictive accuracy of 0.92. Serum CXCL9 and CXCL10 levels were not different between groups.Conclusions.Increased frequency of CAR T-cells expressing CD7, CXCR3 and NKG2D in R versus LAG3 and CD71 in NR emerged as strong correlates of therapeutic outcome.
Leveraging DNA methylation to create Epigenetic Biomarker Proxies that inform clinical care: A new framework for Precision Medicine
Authors: Carreras-Gallo Natàlia , Chen Qingwen , Balagué-Dobón Laura , Aparicio Andrea , Giosan Ilinca M. , Dargham Rita , Phelps Daniel , Guo Tao , Mendez Kevin M. , Chen Yulu , Carangan Athena , Vempaty Srikar , Hassouneh Sayf , McGeachie Michael , Mendez Tavis , Comite Florence , Suhre Karsten , Smith Ryan , Dwaraka Varun B. , Lasky-Su Jessica A. 
Published: December 2024

ABSTRACTThe lack of accurate, cost-effective, and clinically relevant biomarkers remains a major barrier to incorporating omic data into clinical practice. Previous studies have shown that DNA methylation algorithms have utility as surrogate measures for selected proteins and metabolites. We expand upon this work by creating DNAm surrogates, termed epigenetic biomarker proxies (EBPs), across clinical laboratories, the metabolome, and the proteome. After screening >2,500 biomarkers, we trained and tested 1,694 EBP models and assessed their incident relationship with 12 chronic diseases and mortality, followed up to 15 years. We observe broad clinical relevance: 1) there are 1,292 and 4,863 FDR significant incident and prevalent associations, respectively; 2) most of these associations are replicated when looking at the lab-based counterpart, and > 62% of the shared associations have higher odds and hazard ratios to disease outcomes than their respective observed measurements; 3) EBPs of current clinical biochemistries detect deviations from normal with high sensitivity and specificity. Longitudinal EBPs also demonstrate significant changes corresponding to the changes observed in lab-based counterparts. Using two cohorts and > 30,000 individuals, we found that EBPs validate across healthy and sick populations. While further study is needed, these findings highlight the potential of implementing EBPs in a simple, low-cost, high-yield framework that benefits clinical medicine.
Computationally efficient meta-analysis of gene-based tests using summary statistics in large-scale genetic studies
Authors: Joseph Tyler , Mbatchou Joelle , Ghosh Arkopravo , Marcketta Anthony , Gillies Christopher , Tang Jing , Nakka Priyanka , Zhang Xinyuan , Kosmicki Jack , Sidore Carlo , Gurski Lauren ,   Regeneron Genetics Center, Ghoussaini Maya , Ferreira Manuel A.R. , Abecasis Gonçalo , Marchini Jonathan 
Published: December 2024

AbstractMeta-analysis of gene-based tests using single variant summary statistics is a powerful strategy for associating genes with disease. However, current approaches require sharing the covariance matrix between variants for each study and trait of interest. For large-scale studies with many phenotypes, these matrices can be cumbersome to calculate, store, and share. To address this challenge, we present REMETA, an efficient tool for meta-analysis of gene-based tests. REMETA uses a single sparse covariance reference file per study that is rescaled for each phenotype using single variant summary statistics. We develop methods to apply REMETA to binary traits with case-control imbalance, and estimate allele frequencies, genotype counts and effect sizes of burden tests. We demonstrate the performance and advantages of our approach via meta-analysis of 5 traits in 469,376 samples in UK Biobank. The open-source REMETA software tools and framework will facilitate meta-analysis across large scale exome sequencing studies from diverse studies that cannot easily be brought together.
Efficient multi-phenotype genome-wide analysis identifies genetic associations for unsupervised deep-learning-derived high-dimensional brain imaging phenotypes
Authors: Guo Bohong , Xie Ziqian , He Wei , Islam Sheikh Muhammad Saiful , Gottlieb Assaf , Chen Han , Zhi Degui 
Published: December 2024

AbstractBrain imaging is a high-content modality that offers dense insights into the structure and pathology of the brain. Existing genetic association studies of brain imaging, typically focusing on a number of individual image-derived phenotypes (IDPs), have successfully identified many genetic loci. Previously, we have created a 128-dimensional Unsupervised Deep learning derived Imaging Phenotypes (UDIPs), and identified multiple loci from single-phenotype genome-wide association studies (GWAS) for individual UDIP dimensions, using data from the UK Biobank (UKB). However, this approach may miss genetic associations where one single nucleotide polymorphism (SNP) is moderately associated with multiple UDIP dimensions. Here, we present Joint Analysis of multi-phenotype GWAS (JAGWAS), a new tool that can efficiently calculate multivariate association statistics using single-phenotype summary statistics for hundreds of phenotypes. When applied to UDIPs of T1 and T2 brain magnetic resonance imaging (MRI) on discovery and replication cohorts from the UKB, JAGWAS identified 195/168 independently replicated genomic loci for T1/T2, 6 times more than those from the single-phenotype GWAS. The replicated loci were mapped into 555/494 genes, and 217/188 genes overlapped with the expression quantitative trait loci (eQTL) of brain tissues. Gene enrichment analysis indicated that the genes mapped are closely related to neurobiological functions. Our results suggested that multi-phenotype GWAS is a powerful approach for genetic discovery using high-dimensional UDIPs.
Cost-utility analysis of COVID-19 vaccination strategies for endemic SARS-CoV-2 circulation in Canada
Authors: Miranda Rafael N. , Simmons Alison E. , Li Michael W.Z. , Gebretekle Gebremedhin B. , Xi Min , Salvadori Marina I. , Warshawsky Bryna , Wong Eva , Ximenes Raphael , Andrew Melissa K. , Sander Beate , Singh Davinder , Wilson Sarah , Tunis Matthew , Tuite Ashleigh R. 
Published: December 2024

ABSTRACTBackgroundWith shifting epidemiology and changes in the vaccine funding landscape, resource use considerations for ongoing COVID-19 vaccination programs are increasingly important. We assessed the cost-effectiveness of COVID-19 vaccination programs, where eligibility is defined by combinations of age and chronic medical conditions, including a strategy similar to current Canadian recommendations, from the health system and societal perspectives.MethodsWe used a static, individual-based probabilistic model simulating medically attended COVID-19 in a population of 1 million people followed over a 15-month time period to estimate costs in 2023 Canadian dollars, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs), discounted at 1.5%. COVID-19 epidemiology, vaccine characteristics, and costs were based on the most recently available data.ResultsAnnual vaccination for adults aged 65 years and older consistently emerged as a cost-effective intervention, with ICERs less than $50,000 per QALY compared to no vaccination for a range of model assumptions. Adding a second dose for adults aged 65 years and older or expanding programs to include vaccination for younger age groups, including those at higher risk of COVID-19 due to chronic medical conditions, generally resulted in ICERs of greater than $50,000 per QALY. Shifting timing of vaccination programs to better align with periods of high COVID-19 case occurrence could result in biannual vaccination for those aged 65 and older being a cost-effective strategy.ConclusionsCOVID-19 vaccination programs may be cost-effective when focused on groups at higher risk of disease. Optimal timing of vaccination could improve the cost-effectiveness of various strategies.
Differentiation of Mesenchymal Stem/ Stromal Cells into CD45+ Macrophage-like Cells: Expanding Insights into MSC Plasticity
Authors: Rusch Robert M. , Mabuchi Yo , Morikawa Satoru , Ogawa Yoko , Shimmura Shigeto 
Published: December 2024

ABSTRACTMesenchymal stem/stromal cells (MSCs) are notable for their differentiation potential and immunomodulatory properties. They share several features with macrophages that are also similar to those of fibrocytes. This study aimed to investigate the relationship between MSCs, fibrocytes, and macrophages, focusing on the hypothesis of a possible direct lineage. This study focuses on a freshly isolated murine MSC population known as PαSmMSCs (CD45−TER119−Sca-1+PDGFRα+). Transplanting PαSmMSCs from transgenic GFP mice into irradiated recipients produced GFP+cells expressing the macrophage markers CD45, CD68, and CD115, indicating a macrophage-like phenotype. Further analysis showed that PαSmMSCs cultured in macrophage differentiation media acquired characteristics of M2 macrophages (CD45, CD68, and CD206). These results were confirmed in two different mouse strains as well as in human MSCs (hMSCs). Single-cell RNA sequencing revealed macrophage-like and fibrocyte-like populations among the PαSmMSCs. These findings demonstrate the phenotypic plasticity of freshly isolated MSCs to transition into macrophage-like and/or fibrocyte-like states, which has not been reported, particularly in long-term cultured MSCs. This study provides new insights into MSC plasticity and its potential roles in immune regulation and tissue repair.
Iterative SCRaMbLE for Engineering Synthetic Genome Modules and Chromosomes
Authors: Lu Xinyu , Ciurkot Klaudia , Gowers Glen-Oliver F. , Shaw William M , Ellis Tom 
Published: December 2024

AbstractSynthetic biology offers the possibility of synthetic genomes with customised gene content and modular organisation. In eukaryotes, building whole custom genomes is still many years away, but work inSaccharomyces cerevisiaeyeast is closing-in on the first synthetic eukaryotic genome with genome-wide design changes. A key design change throughout the synthetic yeast genome is the introduction of LoxPsym site sequences. These enable inducible genomic rearrangementsin vivovia expression of Cre recombinase via SCRaMbLE (Synthetic Chromosome Recombination and Modification by LoxPsym-mediated Evolution). When paired with selection, SCRaMbLE can quickly generate strains with phenotype improvements by diversifying gene arrangement and content in LoxPsym-containing regions. Here, we demonstrate how iterative cycles of SCRaMbLE can be used to reorganise synthetic genome modules and synthetic chromosomes for improved functional performance under selection. To achieve this, we developed SCOUT (SCRaMbLEContinuousOutput andUniversalTracker), a reporter system that allows SCRaMbLEd cells to be sorted into a high diversity pool. When coupled with long-read sequencing, SCOUT enables high-throughput mapping of genotype abundance and correlation of gene content and arrangement with growth-related phenotypes. Iterative SCRaMbLE was applied here to yeast strains with a full synthetic chromosome, and to strains with synthetic genome modules encoding the gene set for histidine biosynthesis. Five synthetic designs forHISmodules were constructed and tested, and we investigated how SCRaMbLE reorganised the poorest performing design to give improved growth under selection. The results of iterative SCRaMbLE serve as a quick route to identify genome module designs with optimised function in a selected condition and offer a powerful tool to generate datasets that can inform the design of modular genomes in the future.
FAK activity exacerbates disturbed flow-mediated atherosclerosis via VEGFR2-Cbl-NF-κB signaling
Authors: Murphy James M. , Kieu Tran Duyen Thi , Jeong Kyuho , Nguyen Ly , Nguyen Mai Thi , Tambe Dhananjay , Jo Hanjoong , Ahn Eun-Young Erin , Lim Ssang-Taek Steve 
Published: December 2024

AbstractAtherosclerosis develops at predictable sites in the vasculature where branch points and curvatures create non-laminar disturbed flow. This disturbed flow causes vascular inflammation by increased endothelial cell (EC) barrier permeability and the expression of inflammatory genes such as vascular cell adhesion molecule-1 (VCAM-1). Vascular endothelial growth factor receptor 2 (VEGFR2) is important for flow-induced EC inflammation; however, there are still some gaps in the signaling pathway. Focal adhesion kinase (FAK) is a protein tyrosine kinase whose expression has been implicated in flow-mediated signaling in ECs. However, the link between FAK and VEGFR2 in flow-mediated inflammation signaling has remained unelucidated. Here we found that priming of VEGFR2 with VEGF was critical for flow-mediated activation of FAK and NF-kB. Mechanistically, FAK activation triggers tyrosine phosphorylation of Casitas B-lineage lymphoma (CBL; an E3 ubiquitin ligase) that interacts with VEGFR2 under flow conditions. Further,Apoe-/-mice fed a western diet (WD) exhibited increased FAK activity within the atheroprone disturbed flow region of the inner aortic arch compared to the outer arch. Disturbed flow-induced FAK activation is associated with elevated VEGFR2 on the surface of ECs of the inner aortic arch, but not in the outer arch. Taken together, these data suggest that suppression of augmented FAK activity under disturbed flow may prove beneficial in reducing pro-inflammatory signaling of the endothelial layer.
Epigenetic silencing and blockade of latency reversal by an HIV-1 encoded antisense transcript
Authors: Li Rui , Daneshvar Kaveh , Ji Xinjie , Pleet Michelle , Igbinosun Grace , Iqbal Mohd. Shameel , Kashanchi Fatah , Mullen Alan C. , Romerio Fabio 
Published: December 2024

AbstractThe mechanisms that regulate human immunodeficiency virus 1 (HIV-1) latency are not fully elucidated. We reported that an HIV-1 antisense transcript (AST) induces epigenetic modifications at the HIV-1 promoter causing a closed chromatin state that suppresses viral transcription. Here we show that ectopic expression of AST in CD4+ T-cells from people with HIV-1 under antiretroviral therapy blocks latency reversal in response to pharmacologic and T-cell receptor stimulation, enforcing transcriptional silencing. We define structural domains and sequence motifs of AST contributing to its latency-promoting functions. Finally, we report an unbiased proteomics screen of AST interactors that revealed an array of previously known and potential new HIV-1-suppressive factors. Our studies identify AST as a first-in-class biological molecule capable of enforcing HIV-1 latency and with actionable curative potential.
The primary mechanism for highly potent inhibition of HIV-1 maturation by lenacapavir
Authors: Huang Szu-Wei , Briganti Lorenzo , Annamalai Arun S. , Greenwood Juliet , Shkriabai Nikoloz , Haney Reed , Armstrong Michael L. , Wempe Michael F. , Singh Satya Prakash , Francis Ashwanth C. , Engelman Alan N. , Kvaratskhelia Mamuka 
Published: December 2024

AbstractLenacapavir (LEN) is a highly potent, long-acting antiretroviral medication for treating people infected with muti-drug-resistant HIV-1 phenotypes. The inhibitor targets multifaceted functions of the viral capsid protein (CA) during HIV-1 replication. Previous studies have mainly focused on elucidating LEN’s mode of action during viral ingress. Additionally, the inhibitor has been shown to interfere with mature capsid assembly during viral egress. However, the mechanism for how LEN affects HIV-1 maturation is unknown. Here, we show that pharmacologically relevant LEN concentrations do not impair proteolytic processing of Gag in virions. Instead, we have elucidated the primary mechanism for highly potent inhibition of HIV-1 maturation by sub-stoichiometric LEN:CA ratios. The inhibitor exerts opposing effects on formation of CA pentamers versus hexamers, the key capsomere intermediates in mature capsid assembly. LEN impairs formation of pentamers, whereas it induces assembly of hexameric lattices by imposing an opened CA conformation and stabilizing a dimeric form of CA. Consequently, LEN treatment results in morphologically atypical virus particles containing malformed, hyper-stable CA assemblies, which fail to infect target cells. Moreover, we have uncovered an inverse correlation between inhibitor potency and CA levels in cell culture assays, which accounts for LEN’s ability to potently (with pM EC50values) inhibit HIV-1 maturation at clinically relevant drug concentrations.Author SummaryLenacapavir (LEN) is the first-in-class HIV-1 capsid targeting antiretroviral that exhibits multimodal modality to inhibit both early and late steps of viral replication. Our studies here have elucidated previously undescribed structural and mechanistic bases for a highly potent antiviral activity of LEN during viral egress. These findings will inform clinical applications of LEN as a potent HIV-1 maturation inhibitor and aid the development of second-generation inhibitors targeting assembly of the mature viral capsid.
A CRISPRi Library Screen in Group BStreptococcusIdentifies Surface Immunogenic Protein (Sip) as a Mediator of Multiple Host Interactions
Authors: Firestone K , Gopalakrishna KP , Rogers LM , Peters A , Gaddy JA , Nichols C , Hall MH , Varela HN , Carlin SM , Hillebrand GH , Giacobe EJ , Aronoff DM , Hooven TA 
Published: December 2024

AbstractGroup BStreptococcus(GBS;Streptococcus agalactiae) is an important pathobiont capable of colonizing various host environments, contributing to severe perinatal infections. Surface proteins play critical roles in GBS-host interactions, yet comprehensive studies of these proteins’ functions have been limited by genetic manipulation challenges. This study leveraged a CRISPR interference (CRISPRi) library to target genes encoding surface-trafficked proteins in GBS, identifying their roles in modulating macrophage cytokine responses. Bioinformatic analysis of 654 GBS genomes revealed 66 conserved surface protein genes. Using a GBS strain expressing chromosomally integrated dCas9, we generated and validated CRISPRi strains targeting these genes. THP-1 macrophage-like cells were exposed to ethanol-killed GBS variants, and pro-inflammatory cytokines TNF-α and IL-1β were measured. Notably, knockdown of thesipgene, encoding the Surface Immunogenic Protein (Sip), significantly increased IL-1β secretion, implicating Sip in caspase-1-dependent regulation. Further, Δsipmutants demonstrated impaired biofilm formation, reduced adherence to human fetal membranes, and diminished uterine persistence in a mouse colonization model. These findings suggest Sip modulates GBS- host interactions critical for pathogenesis, underscoring its potential as a therapeutic target or vaccine component.