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| http://dx.doi.org/10.1165/rcmb.2017-0409LE | DOI Listing |
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Transcriptome-Wide Association Study of Metabolic Dysfunction-Associated Steatotic Liver Disease Identifies Relevant Gene Signatures.
Turk J Gastroenterol
December 2024
Department of Emergency Medicine, Shandong University, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Qingdao, China.
Metabolic dysfunction-associated steatotic liver disease (MASLD) is considered the most widespread chronic liver condition globally. Genome-wide association studies (GWAS) have pinpointed several genetic loci correlated to MASLD, yet the biological significance of these loci remains poorly understood. Initially, we applied Functional Mapping and Annotation (FUMA) to conduct a functional annotation of the MASLD GWAS summary statistics, which included data from 3242 cases and 707 631 controls.
View Article and Find Full Text PDFA genome-wide association study of high-sensitivity C-reactive protein in a large Korean population highlights its genetic relationship with cholesterol metabolism.
Sci Rep
January 2025
Department of Pharmacy, College of Pharmacy, Chungbuk National University, 194-21, Osongsaengmyeong-1 ro, Heungdeok-gu, Cheongju, 28160, Chungcheongbuk-do, Korea.
High-sensitivity C-reactive protein (hsCRP) is a representative biomarker of systemic inflammation and is associated with numerous chronic diseases. To explore the biological pathways and functions underlying chronic inflammation, we conducted a genome-wide association study (GWAS) and several post-GWAS analyses of the hsCRP levels. This study was performed on data from 71,019 Koreans and is one of the largest East Asian studies.
View Article and Find Full Text PDFAn integrative approach to identifying as a susceptibility gene for gestational diabetes mellitus.
J Matern Fetal Neonatal Med
December 2025
Department of Obstetrics and Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Objective: The objective of this study was to identify a novel gene and its potential mechanisms associated with susceptibility to gestational diabetes mellitus (GDM) through an integrative approach.
Methods: We analyzed data from genome-wide association studies (GWAS) of GDM in the FinnGen R11 dataset (16,802 GDM cases and 237,816 controls) and Genotype Tissue Expression v8 expression quantitative trait locus data. We used summary-data-based Mendelian randomization to determine associations between transcript levels and phenotypes, transcriptome-wide association studies to provide insights into gene-trait associations, multi-marker analysis of genomic annotation to perform gene-based analysis, genome-wide complex trait analysis-multivariate set-based association test-combo to determine gene prioritization, and polygenic priority scores to prioritize the causal genes to screen candidate genes.
Mapping the landscape of lineage-specific dynamic regulation of gene expression using single-cell transcriptomics and application to genetics of complex disease.
HGG Adv
December 2024
Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN; Clare Hall, University of Cambridge, Cambridge, England. Electronic address:
Single-cell transcriptome data can provide insights into how genetic variation influences biological processes involved in human biology and disease. However, the identification of gene-level associations in distinct cell types faces several challenges, including the limited reference resource from population scale studies, data sparsity in single-cell RNA sequencing, and the complex cell state pattern of expression within individual cell types. Here we develop genetic models of cell type specific and cell state adjusted gene expression in mid-brain neurons in the process of specializing from induced pluripotent stem cells.
View Article and Find Full Text PDFBackground: Considering that the treatment of gout is poor, we performed a Mendelian randomization (MR) study to identify candidate biomarkers and therapeutic targets for gout.
Methods: A drug-targeted MR study was performed for gout by integrating the gout genome-wide association studies (GWAS) summary data and cis expression quantitative trait loci of 2,633 druggable genes from multiple cohorts. Summary data-based Mendelian randomization (SMR) analyses based on transcript and protein levels were further implemented to validate the reliability of the identified potential therapeutic targets for gout.
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