Context: Our objective was to evaluate the effect of gene polymorphisms of apolipoprotein C3 (APOC3) on the development of non-alcoholic fatty liver disease (NAFLD) in different populations.
Evidence Acquisition: We performed a meta-analysis of all relevant studies published in the literature. A total of 115 clinical trials or reports were identified, but only seven trials met our inclusion criteria. A meta-analysis was performed according to the Cochrane Reviewers' Handbook recommendations.
Results: Five hospital-based and two population-based case-control studies were included in the final analysis. The overall frequency of APOC3 gene polymorphisms was 67.5% (1177/1745) in NAFLD and 68.8% (988/1437) in controls. The summary odds ratio for the association of gene polymorphisms of APOC3 and the risk of NAFLD was 1.03 (95% CI: 0.89-1.22),which was not statistically significant (P > 0.05).
Conclusions: Our meta-analysis, while not ruling out possible publication bias, showed no association between gene polymorphisms of APOC3 and the risk of NAFLD development in different populations in the world.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4250968 | PMC |
| http://dx.doi.org/10.5812/hepatmon.23100 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Interaction study of the effects of environmental exposure and gene polymorphisms of inflammatory and immune-active factors on chronic obstructive pulmonary disease.
Respir Res
January 2025
Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Center for Chronic Disease Prevention and Control, Harbin Medical University, Harbin, 150081, People's Republic of China.
Background: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease, influenced by both environmental and genetic factors. Single nucleotide polymorphism (SNP) in the human genome may influence the risk of developing COPD and the response to treatment. We assessed the effects of gene polymorphism of inflammatory and immune-active factors and gene-environment interaction on risk of COPD in middle-aged and older Chinese individuals.
View Article and Find Full Text PDFPre-breeding in alfalfa germplasm develops highly differentiated populations, as revealed by genome-wide microhaplotype markers.
Sci Rep
January 2025
Plant Science Research Unit, USDA-ARS, St. Paul, MN, USA.
Plant genebanks contain large numbers of germplasm accessions that likely harbor useful alleles or genes absent in commercial plant breeding programs. Broadening the genetic base of commercial alfalfa germplasm with these valuable genetic variations can be achieved by screening the extensive genetic diversity in germplasm collections and enabling maximal recombination among selected genotypes. In this study, we assessed the genetic diversity and differentiation of germplasm pools selected in northern U.
View Article and Find Full Text PDFSmall variant benchmark from a complete assembly of X and Y chromosomes.
Nat Commun
January 2025
Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr., Gaithersburg, MD, USA.
The sex chromosomes contain complex, important genes impacting medical phenotypes, but differ from the autosomes in their ploidy and large repetitive regions. To enable technology developers along with research and clinical laboratories to evaluate variant detection on male sex chromosomes X and Y, we create a small variant benchmark set with 111,725 variants for the Genome in a Bottle HG002 reference material. We develop an active evaluation approach to demonstrate the benchmark set reliably identifies errors in challenging genomic regions and across short and long read callsets.
View Article and Find Full Text PDFEnhancing genomic-based forward prediction accuracy in wheat by integrating UAV-derived hyperspectral and environmental data with machine learning under heat-stressed environments.
Plant Genome
March 2025
USDA-ARS Southeast Area, Plant Science Research, Raleigh, North Carolina, USA.
Integrating genomic, hyperspectral imaging (HSI), and environmental data enhances wheat yield predictions, with HSI providing detailed spectral insights for predicting complex grain yield (GY) traits. Incorporating HSI data with single nucleotide polymorphic markers (SNPs) resulted in a substantial improvement in predictive ability compared to the conventional genomic prediction models. Over the course of several years, the prediction ability varied due to diverse weather conditions.
View Article and Find Full Text PDFImprovement in genomic prediction of maize with prior gene ontology information depends on traits and environmental conditions.
Plant Genome
March 2025
INRAE, CNRS, AgroParisTech, GQE-Le Moulon, Université Paris-Saclay, Gif-sur-Yvette, France.
Classical genomic prediction approaches rely on statistical associations between traits and markers rather than their biological significance. Biologically informed selection of genomic regions can help prioritize polymorphisms by considering underlying biological processes, making prediction models robust and accurate. Gene ontology (GO) terms can be used for this purpose, and the information can be integrated into genomic prediction models through marker categorization.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!