Publications by authors named "Raul Mendez Giraldez"

Triple-negative breast cancer (TNBC) is the most therapeutically recalcitrant form of breast cancer, which is due in part to the paucity of targeted therapies. A systematic analysis of regulatory elements that extend beyond protein-coding genes could uncover avenues for therapeutic intervention. To this end, we analyzed the regulatory mechanisms of TNBC-specific transcriptional enhancers together with their noncoding enhancer RNA (eRNA) transcripts.

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  • Blood-based small molecule metabolites can provide valuable insights into health and disease risk, especially in understanding heart failure (HF) through metabolite profiling in individuals who initially do not have HF.
  • The study used network analysis to reveal how metabolites interact and their roles in influencing HF risk, while controlling for confounding factors among metabolites.
  • Key findings indicate that certain metabolites, like glycine and asparagine, are linked to both dietary intake and genetic factors, highlighting their importance in predicting HF incidence and understanding complex health conditions.
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Annotation of the -regulatory elements that drive transcriptional dysregulation in cancer cells is critical to improving our understanding of tumor biology. Herein, we present a compendium of matched chromatin accessibility (scATAC-seq) and transcriptome (scRNA-seq) profiles at single-cell resolution from human breast tumors and healthy mammary tissues processed immediately following surgical resection. We identify the most likely cell-of-origin for luminal breast tumors and basal breast tumors and then introduce a novel methodology that implements linear mixed-effects models to systematically quantify associations between regions of chromatin accessibility (i.

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Vaccination reduces morbidity and mortality due to infections, but efficacy may be limited due to distinct immunogenicity at the extremes of age. This raises the possibility of employing adjuvants to enhance immunogenicity and protection. Early IFNγ production is a hallmark of effective vaccine immunogenicity in adults serving as a biomarker that may predict effective adjuvanticity.

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  • Monoclonal antibody therapies have improved cancer survival rates, but individual responses vary, necessitating the identification of cancer subtypes and biomarkers for effective treatment.* -
  • This study focused on colorectal cancer, combining genotype and RNA-seq data to find biomarkers linked to overall survival for patients treated with cetuximab or bevacizumab.* -
  • Notably, a gene found to be overexpressed in certain subtypes was linked to shorter survival for cetuximab patients, suggesting that specific subtypes may respond better to certain treatments.*
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  • This study focused on identifying gene interconnectivity, specifically in metastatic colorectal cancer (CRC), to improve patient treatment by linking gene networks to overall survival (OS) outcomes.
  • Researchers analyzed data from 1,165 patients in a clinical trial comparing treatments with cetuximab and bevacizumab, discovering gene signatures that predict patient survival based on specific treatments.
  • The identified gene signatures not only showed downregulation in CRC tumors compared to normal tissue but also highlighted proteins that interact functionally, indicating their potential as novel biomarkers for personalized cancer treatment.
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  • - The study analyzed metabolite profiles from individuals without heart failure to understand the connections between different metabolites and their potential role in heart failure incidence.
  • - Researchers identified specific metabolites, like glycine and asparagine, that are linked to heart failure risk, taking into account polygenic factors and the influence of dietary amino acids.
  • - The findings highlight how metabolites are interconnected and may help bridge genetic and lifestyle factors in heart failure development, contributing to a better mechanistic understanding of the condition.
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  • The increasing integration of biological data across multiple levels, like genomics and proteomics, aims to uncover new mechanisms in health and disease, with a focus on causal frameworks such as Mendelian randomization (MR).
  • Classical MR methods often target individual molecular components without addressing their interactions; in contrast, causal network models enhance the framework by considering these complex relationships.
  • This review explores the progression from classical MR to causal networks, highlighting methods for identifying these networks, conducting sensitivity analyses, and demonstrating their utility in integrating large-scale omic data for better biological insights.
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A major topic of debate in developmental biology centers on whether development is continuous, discontinuous, or a mixture of both. Pseudo-time trajectory models, optimal for visualizing cellular progression, model cell transitions as continuous state manifolds and do not explicitly model real-time, complex, heterogeneous systems and are challenging for benchmarking with temporal models. We present a data-driven framework that addresses these limitations with temporal single-cell data collected at discrete time points as inputs and a mixture of dependent minimum spanning trees (MSTs) as outputs, denoted as dynamic spanning forest mixtures (DSFMix).

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Deconvolution of regulatory mechanisms that drive transcriptional programs in cancer cells is key to understanding tumor biology. Herein, we present matched transcriptome (scRNA-seq) and chromatin accessibility (scATAC-seq) profiles at single-cell resolution from human ovarian and endometrial tumors processed immediately following surgical resection. This dataset reveals the complex cellular heterogeneity of these tumors and enabled us to quantitatively link variation in chromatin accessibility to gene expression.

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  • This study emphasizes the importance of understanding how multiple genes interact and regulate each other to uncover biological networks, especially in the context of complex traits like schizophrenia (SCZ).
  • Researchers combined transcriptomics, genotypes, and Hi-C data, using machine learning techniques to create a causal network that reveals differential regulatory patterns in SCZ cases compared to controls, identifying novel genes implicated in the disorder.
  • The findings suggest that gene transcription is affected by nearby genetic variants and distant regulatory factors, and studying these interactions provides deeper insights into gene behavior and potential therapeutic strategies, which wouldn't be achieved by analyzing individual genes alone.
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Background: The electrocardiographically quantified QRS duration measures ventricular depolarization and conduction. QRS prolongation has been associated with poor heart failure prognosis and cardiovascular mortality, including sudden death. While previous genome-wide association studies (GWAS) have identified 32 QRS SNPs across 26 loci among European, African, and Asian-descent populations, the genetics of QRS among Hispanics/Latinos has not been previously explored.

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Background: DNA methylation (DNAm) may contribute to processes that underlie associations between air pollution and poor health. Therefore, our objective was to evaluate associations between DNAm and ambient concentrations of particulate matter (PM) ≤2.5, ≤10, and 2.

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  • * Researchers used a Bayesian multi-trait approach to analyze 10 cardiac traits from a large group of individuals and found significant genetic variants linked to heart function.
  • * They identified three new variants in the genes RGS3, CHD3, and MRPL38 that affect various cardiac traits, with RGS3 showing a notable impact on multiple heart measurements and its role in inhibiting TGF-beta signaling related to heart issues.
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Eukaryotic genome replication depends on thousands of DNA replication origins (ORIs). A major challenge is to learn ORI biology in multicellular organisms in the context of growing organs to understand their developmental plasticity. We have identified a set of ORIs of and their chromatin landscape at two stages of post-embryonic development.

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The genetic basis of supraventricular and ventricular ectopy (SVE, VE) remains largely uncharacterized, despite established genetic mechanisms of arrhythmogenesis. To identify novel genetic variants associated with SVE/VE in ancestrally diverse human populations, we conducted a genome-wide association study of electrocardiographically identified SVE and VE in five cohorts including approximately 43,000 participants of African, European and Hispanic/Latino ancestry. In thirteen ancestry-stratified subgroups, we tested multivariable-adjusted associations of SVE and VE with single nucleotide polymorphism (SNP) dosage.

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QT interval prolongation is a heritable risk factor for ventricular arrhythmias and can predispose to sudden death. Most genome-wide association studies (GWAS) of QT were performed in European ancestral populations, leaving other groups uncharacterized. Herein we present the first QT GWAS of Hispanic/Latinos using data on 15,997 participants from four studies.

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Objective: PR interval (PR) is a heritable electrocardiographic measure of atrial and atrioventricular nodal conduction. Changes in PR duration may be associated with atrial fibrillation, heart failure and all-cause mortality. Hispanic/Latino populations have high burdens of cardiovascular morbidity and mortality, are highly admixed and represent exceptional opportunities for novel locus identification.

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Background: Ambient particulate matter (PM) air pollution exposure has been associated with increases in QT interval duration (QT). However, innate susceptibility to PM-associated QT prolongation has not been characterized.

Objective: To characterize genetic susceptibility to PM-associated QT prolongation in a multi-racial/ethnic, genome-wide association study (GWAS).

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Background: Although time-domain measures of heart rate variability (HRV) are used to estimate cardiac autonomic tone and disease risk in multiethnic populations, the genetic epidemiology of HRV in Hispanics/Latinos has not been characterized.

Objective: The purpose of this study was to conduct a genome-wide association study of heart rate (HR) and its variability in the Hispanic Community Health Study/Study of Latinos, Multi-Ethnic Study of Atherosclerosis, and Women's Health Initiative Hispanic SNP-Health Association Resource project (n = 13,767).

Methods: We estimated HR (bpm), standard deviation of normal-to-normal interbeat intervals (SDNN, ms), and root mean squared difference in successive, normal-to-normal interbeat intervals (RMSSD, ms) from resting, standard 12-lead ECGs.

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Background: Increased heart rate and a prolonged QT interval are important risk factors for cardiovascular morbidity and mortality, and can be influenced by the use of various medications, including tricyclic/tetracyclic antidepressants (TCAs). We aim to identify genetic loci that modify the association between TCA use and RR and QT intervals.

Methods And Results: We conducted race/ethnic-specific genome-wide interaction analyses (with HapMap phase II imputed reference panel imputation) of TCAs and resting RR and QT intervals in cohorts of European (n=45 706; n=1417 TCA users), African (n=10 235; n=296 TCA users) and Hispanic/Latino (n=13 808; n=147 TCA users) ancestry, adjusted for clinical covariates.

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Type 1 ryanodine receptors (RyR1s) release Ca(2+) from the sarcoplasmic reticulum to initiate skeletal muscle contraction. The role of RyR1-G4934 and -G4941 in the pore-lining helix in channel gating and ion permeation was probed by replacing them with amino acid residues of increasing side chain volume. RyR1-G4934A, -G4941A, and -G4941V mutant channels exhibited a caffeine-induced Ca(2+) release response in HEK293 cells and bound the RyR-specific ligand [(3)H]ryanodine.

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Chromatin is of major relevance for gene expression, cell division, and differentiation. Here, we determined the landscape of Arabidopsis thaliana chromatin states using 16 features, including DNA sequence, CG methylation, histone variants, and modifications. The combinatorial complexity of chromatin can be reduced to nine states that describe chromatin with high resolution and robustness.

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Here we perform a large-scale study of the structural properties and the expression of proteins that constitute the human Centrosome. Centrosomal proteins tend to be larger than generic human proteins (control set), since their genes contain in average more exons (20.3 versus 14.

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