scholarly journals Genome-wide analysis of long noncoding RNA expression profiles in patients with non-alcoholic fatty liver disease

IUBMB Life ◽  
2015 ◽  
Vol 67 (11) ◽  
pp. 847-852 ◽  
Author(s):  
Chuanzheng Sun ◽  
Xunyang Liu ◽  
Zhongjie Yi ◽  
Xuefei Xiao ◽  
Mingshi Yang ◽  
...  
Keyword(s):  
Liver Disease ◽  
Long Noncoding Rna ◽  
Fatty Liver Disease ◽  
Noncoding Rna ◽  
Expression Profiles ◽  
Rna Expression ◽  
Alcoholic Fatty Liver ◽  
Genome Wide Analysis ◽  
Genome Wide ◽  
Alcoholic Fatty Liver Disease

Genome-Wide Analysis of Long Noncoding RNA Expression Profiles in Human Xuanwei Lung Cancer

2015 ◽  
Vol 61 (10/2015) ◽  
Author(s):  
Qing Li ◽  
Chunyan Wu ◽  
Guibo Song ◽  
Hui Zhang ◽  
Bin Shan ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Expression Profiles ◽  
Rna Expression ◽  
Genome Wide Analysis ◽  
Genome Wide

scholarly journals Identifying potential biomarkers of nonalcoholic fatty liver disease via genome-wide analysis of copy number variation

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yang fan Li ◽  
Jing Zheng ◽  
He wei Peng ◽  
Xiao lin Cai ◽  
Xin ting Pan ◽  
...  
Keyword(s):  
Liver Disease ◽  
Copy Number Variation ◽  
Fatty Liver ◽  
Quantitative Pcr ◽  
Copy Number ◽  
Fatty Liver Disease ◽  
Alcoholic Fatty Liver ◽  
Genome Wide Analysis ◽  
Genome Wide ◽  
Number Variation

Abstract Background The prevalence of Non-alcoholic fatty liver disease (NAFLD) is increasing and emerging as a global health burden. In addition to environmental factors, numerous studies have shown that genetic factors play an important role in the development of NAFLD. Copy number variation (CNV) as a genetic variation plays an important role in the evaluation of disease susceptibility and genetic differences. The aim of the present study was to assess the contribution of CNV to the evaluation of NAFLD in a Chinese population. Methods Genome-wide analysis of CNV was performed using high-density comparative genomic hybridisation microarrays (ACGH). To validate the CNV regions, TaqMan real-time quantitative PCR (qPCR) was utilized. Results A total of 441 CNVs were identified, including 381 autosomal CNVs and 60 sex chromosome CNVs. By merging overlapping CNVs, a genomic CNV map of NAFLD patients was constructed. A total of 338 autosomal CNVRs were identified, including 275 CNVRs with consistent trends (197 losses and 78 gains) and 63 CNVRs with inconsistent trends. The length of the 338 CNVRs ranged from 5.7 kb to 2.23 Mb, with an average size of 117.44 kb. These CNVRs spanned 39.70 Mb of the genome and accounted for ~ 1.32% of the genome sequence. Through Gene Ontology and genetic pathway analysis, we found evidence that CNVs involving nine genes may be associated with the pathogenesis of NAFLD progression. One of the genes (NLRP4 gene) was selected and verified by quantitative PCR (qPCR) method with large sample size. We found the copy number deletion of NLRP4 was related to the risk of NAFLD. Conclusions This study indicate the copy number variation is associated with NAFLD. The copy number deletion of NLRP4 was related to the risk of NAFLD. These results could prove valuable for predicting patients at risk of developing NAFLD.

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