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Mashup Score: 0Metabolic and inflammatory perturbation of diabetes associated gut dysbiosis in people living with and without HIV infection - Genome Medicine - 15 day(s) ago
Background Gut dysbiosis has been linked with both HIV infection and diabetes, but its interplay with metabolic and inflammatory responses in diabetes, particularly in the context of HIV infection, remains unclear. Methods We first conducted a cross-sectional association analysis to characterize the gut microbial, circulating metabolite, and immune/inflammatory protein features associated with diabetes in up to 493 women (~ 146 with prevalent diabetes with 69.9% HIV +) of the Women’s Interagency HIV Study. Prospective analyses were then conducted to determine associations of identified metabolites with incident diabetes over 12 years of follow-up in 694 participants (391 women from WIHS and 303 men from the Multicenter AIDS Cohort Study; 166 incident cases were recorded) with and without HIV infection. Mediation analyses were conducted to explore whether gut bacteria–diabetes associations are explained by altered metabolites and proteins. Results Seven gut bacterial genera were identif
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Mashup Score: 1PheSeq, a Bayesian deep learning model to enhance and interpret the gene-disease association studies - Genome Medicine - 17 day(s) ago
Despite the abundance of genotype-phenotype association studies, the resulting association outcomes often lack robustness and interpretations. To address these challenges, we introduce PheSeq, a Bayesian deep learning model that enhances and interprets association studies through the integration and perception of phenotype descriptions. By implementing the PheSeq model in three case studies on Alzheimer’s disease, breast cancer, and lung cancer, we identify 1024 priority genes for Alzheimer’s disease and 818 and 566 genes for breast cancer and lung cancer, respectively. Benefiting from data fusion, these findings represent moderate positive rates, high recall rates, and interpretation in gene-disease association studies.
Source: genomemedicine.biomedcentral.comCategories: General Medicine News, General HCPsTweet
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Mashup Score: 1
Background Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. Methods Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. Results scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved
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Mashup Score: 0Recent advances in polygenic scores: translation, equitability, methods and FAIR tools - Genome Medicine - 3 month(s) ago
Polygenic scores (PGS) can be used for risk stratification by quantifying individuals’ genetic predisposition to disease, and many potentially clinically useful applications have been proposed. Here, we review the latest potential benefits of PGS in the clinic and challenges to implementation. PGS could augment risk stratification through combined use with traditional risk factors (demographics, disease-specific risk factors, family history, etc.), to support diagnostic pathways, to predict groups with therapeutic benefits, and to increase the efficiency of clinical trials. However, there exist challenges to maximizing the clinical utility of PGS, including FAIR (Findable, Accessible, Interoperable, and Reusable) use and standardized sharing of the genomic data needed to develop and recalculate PGS, the equitable performance of PGS across populations and ancestries, the generation of robust and reproducible PGS calculations, and the responsible communication and interpretation of resul
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Mashup Score: 0Biological basis of extensive pleiotropy between blood traits and cancer risk - Genome Medicine - 3 month(s) ago
Background The immune system has a central role in preventing carcinogenesis. Alteration of systemic immune cell levels may increase cancer risk. However, the extent to which common genetic variation influences blood traits and cancer risk remains largely undetermined. Here, we identify pleiotropic variants and predict their underlying molecular and cellular alterations. Methods Multivariate Cox regression was used to evaluate associations between blood traits and cancer diagnosis in cases in the UK Biobank. Shared genetic variants were identified from the summary statistics of the genome-wide association studies of 27 blood traits and 27 cancer types and subtypes, applying the conditional/conjunctional false-discovery rate approach. Analysis of genomic positions, expression quantitative trait loci, enhancers, regulatory marks, functionally defined gene sets, and bulk- and single-cell expression profiles predicted the biological impact of pleiotropic variants. Plasma small RNAs were se
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Mashup Score: 2Rare copy-number variants as modulators of common disease susceptibility - Genome Medicine - 4 month(s) ago
Background Copy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described. Methods Assessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank. Results We identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare sing
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Mashup Score: 0Systematic analysis of Mendelian disease-associated gene variants reveals new classes of cancer-predisposing genes - Genome Medicine - 4 month(s) ago
Background Despite the acceleration of somatic driver gene discovery facilitated by recent large-scale tumor sequencing data, the contribution of inherited variants remains largely unexplored, primarily focusing on previously known cancer predisposition genes (CPGs) due to the low statistical power associated with detecting rare pathogenic variant-phenotype associations. Methods Here, we introduce a generalized log-regression model to measure the excess of pathogenic variants within genes in cancer patients compared to control samples. It aims to measure gene-level cancer risk enrichment by collapsing rare pathogenic variants after controlling the population differences across samples. Results In this study, we investigate whether pathogenic variants in Mendelian disease-associated genes (OMIM genes) are enriched in cancer patients compared to controls. Utilizing data from PCAWG and the 1,000 Genomes Project, we identify 103 OMIM genes demonstrating significant enrichment of pathogenic
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Mashup Score: 0Systematic analysis of Mendelian disease-associated gene variants reveals new classes of cancer-predisposing genes - Genome Medicine - 4 month(s) ago
Background Despite the acceleration of somatic driver gene discovery facilitated by recent large-scale tumor sequencing data, the contribution of inherited variants remains largely unexplored, primarily focusing on previously known cancer predisposition genes (CPGs) due to the low statistical power associated with detecting rare pathogenic variant-phenotype associations. Methods Here, we introduce a generalized log-regression model to measure the excess of pathogenic variants within genes in cancer patients compared to control samples. It aims to measure gene-level cancer risk enrichment by collapsing rare pathogenic variants after controlling the population differences across samples. Results In this study, we investigate whether pathogenic variants in Mendelian disease-associated genes (OMIM genes) are enriched in cancer patients compared to controls. Utilizing data from PCAWG and the 1,000 Genomes Project, we identify 103 OMIM genes demonstrating significant enrichment of pathogenic
Source: genomemedicine.biomedcentral.comCategories: General Medicine News, Hem/OncsTweet
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Mashup Score: 6Prenatal BRCA1 epimutations contribute significantly to triple-negative breast cancer development - Genome Medicine - 5 month(s) ago
Background Normal cell BRCA1 epimutations have been associated with increased risk of triple-negative breast cancer (TNBC). However, the fraction of TNBCs that may have BRCA1 epimutations as their underlying cause is unknown. Neither are the time of occurrence and the potential inheritance patterns of BRCA1 epimutations established. Methods To address these questions, we analyzed BRCA1 methylation status in breast cancer tissue and matched white blood cells (WBC) from 408 patients with 411 primary breast cancers, including 66 TNBCs, applying a highly sensitive sequencing assay, allowing allele-resolved methylation assessment. Furthermore, to assess the time of origin and the characteristics of normal cell BRCA1 methylation, we analyzed umbilical cord blood of 1260 newborn girls and 200 newborn boys. Finally, we assessed BRCA1 methylation status among 575 mothers and 531 fathers of girls with (n = 102) and without (n = 473) BRCA1 methylation. Results We found concordant tumor and mosaic
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Mashup Score: 1
Background Chronic limb-threatening ischemia (CLTI), a severe manifestation of peripheral arterial disease (PAD), is associated with a 1-year limb amputation rate of approximately 15–20% and substantial mortality. A key feature of CLTI is the compromised regenerative ability of skeletal muscle; however, the mechanisms responsible for this impairment are not yet fully understood. In this study, we aim to delineate pathological changes at both the cellular and transcriptomic levels, as well as in cell–cell signaling pathways, associated with compromised muscle regeneration in limb ischemia in both human tissue samples and murine models of CLTI. Methods We performed single-cell transcriptome analysis of ischemic and non-ischemic muscle from the same CLTI patients and from a murine model of CLTI. In both datasets, we analyzed gene expression changes in macrophage and muscle satellite cell (MuSC) populations as well as differential cell–cell signaling interactions and differentiation trajec
Source: genomemedicine.biomedcentral.comCategories: General Medicine News, General HCPsTweet
Among individuals with and without HIV, multiple gut bacterial genera, blood metabolites, and proinflammatory proteins are associated with diabetes, reports a study published in @GenomeMedicine. https://t.co/TpAq8cySnd