Association of LIPC -250G/A and -514C/T polymorphisms and hypertension: a systematic review and meta-analysis

Association of LIPC polymorphisms with stroke risk in the Chinese population

Background

Stroke is a common cerebrovascular disease. The purpose of this study was to explore the association between LIPC single nucleotide polymorphisms (SNPs) and the risk of stroke in the Chinese population.

Methods

This study recruited 710 stroke patients and 701 healthy controls. The four SNPs (rs690, rs6083, rs3829461, and rs6074) in LIPC were genotyped by the Agena MassARRAY. The correlation between LIPC polymorphisms and stroke risk was measured by odds ratio (OR) and 95% confidence interval (CI). In addition, multifactor dimensionality reduction (MDR) analysis was used to evaluate the impact of SNP-SNP interaction on stroke risk.

Results

Overall analysis showed that rs690 was associated with an increased risk of stroke (T vs. G: OR = 1.19, 95% CI: 1.01-1.40, p = 0.041; additive: OR = 1.20, 95% CI: 1.01-1.42, p = 0.036). The stratified analysis revealed that rs690 was associated with an increased risk of stroke in subjects aged ≤ 64 years, male patients, and smokers, and rs6074 was associated with an increased risk of stroke in subjects aged > 64 years, male patients, drinkers, and non-smokers (p < 0.05). The results of the MDR analysis suggested the four-locus model as the most favorable model for assessing the risk of stroke. The analysis of clinical parameters of stroke patients showed that rs690 was correlated with platelet distribution width (PDW) (p = 0.014) and hematocrit levels (p = 0.004), and rs6074 was correlated with low-density lipoprotein cholesterol (LDL-C) level (p = 0.033). Furthermore, bioinformatics analysis results demonstrated that the expression levels of LIPC and its related genes (APOB, CETP, PNPLA2, and LMF1) were significantly different between the control and stroke groups (p < 0.05), and LIPC-related proteins were mainly related to lipid metabolism.

Conclusion

This study indicated that rs690 and rs6074 in LIPC were significantly associated with increased risk of stroke in the Chinese population, possibly by regulating the levels of PDW, HCT, and LDL-C.

Downregulation of TUSC3 promotes EMT and hepatocellular carcinoma progression through LIPC/AKT axis

Background

Hepatocellular carcinoma (HCC) is one of the most common and malignant tumors in the digestive tract. Tumor Suppressor Candidate 3 (TUSC3) is one subunit of the endoplasmic reticulum Oligosaccharyl transferase (OST) complex, which plays an important role in N-glycosylation during the protein folding process. However, the role of TUSC3 in the initiation and progression of HCC has not been mentioned yet. In the present study, we aim to investigate the effects of TUSC3 on the initiation and progression of HCC.

Methods

Immunohistochemical assay and qRT-PCR were used to detect the expression of TUSC3 and lipase C hepatic type (LIPC) in HCC tissue and cells. Loss-of-function and gain-of-function were applied to detect the function of TUSC3 and LIPC in vivo and in vitro. Immunofluorescence assay and co-immunoprecipitation were used to detect the relationship between TUSC3 and LPC. Western blot was applied to detect the expression of epithelial–mesenchymal transition (EMT) markers and the Akt signaling pathway.

Results

TUSC3 was aberrantly decreased in hepatocellular carcinoma tissues compared to the matched adjacent normal tissues, which resulted in bigger size of tumor (P = 0.001, Table 2), worse differentiation (P = 0.006, Table 2) and an advanced BCLC stage. Down-regulation of TUSC3 led to the enhanced proliferation and migration of hepatocellular carcinoma cells in vivo and vitro, whereas the opposite effect could be observed in the TUSC3-overexpression group. The analysis of TUSC3 microarray showed that LIPC, a glycoprotein primarily synthesized and secreted by hepatocytes, was a downstream target of TUSC3, and it negatively modulated the development of HCC. The morphological changes in HCC cells indicated that TUSC3 regulated the epithelial-mesenchymal transition (EMT). Mechanistically, TUSC3 inhibited EMT progression through the LIPC/AKT axis.

Conclusion

Down-regulation of TUSC3 promotes EMT progression by activating AKT signaling via targeting LIPC in HCC, which is probably the possible mechanism driving TUSC3-deficient hepatocellular carcinoma cells toward a malignant phenotype.

Increased Expression of LIPC Is Associated with Aggressive Phenotype of Borrmann Type 4 Gastric Cancer

PURPOSE

To investigate lipase C hepatic type (LIPC) expression in Borrmann type 4 gastric cancer and its correlation with clinical outcome. The biological roles of LIPC in Borrmann type 4 gastric cancer progression were also investigated.

METHODS

We determined LIPC expression in 324 primary gastric cancer tissues and 178 matched adjacent non-tumor tissues by immunohistochemistry. We explored the role of LIPC in Borrmann type 4 gastric cancer cell (OCUM-1) migration, invasion, proliferation, cell cycle, and expression of epithelial-mesenchymal transition-related genes by knocking down LIPC expression.

RESULTS

LIPC expression was upregulated in Borrmann type 4 gastric cancer tissues compared with other types of gastric cancer and adjacent non-tumor tissues. High LIPC expression correlated with lymph node metastasis, advanced TNM stage, and poor overall survival in Borrmann type 4 gastric cancer patients. Multivariate analysis demonstrated that high LIPC expression was an independent prognostic factor in patients with Borrmann type 4 gastric cancer. By reducing LIPC expression, OCUM-1 cell invasion and migration were suppressed and Snail and MMP2 expression was downregulated, while E-cadherin expression was upregulated.

CONCLUSIONS

High LIPC expression correlates with poor clinical outcome and plays an important role in regulating cell migration and invasion in Borrmann type 4 gastric cancer.

Hepatic lipase (LIPC) sequencing in individuals with extremely high and low high-density lipoprotein cholesterol levels

Common variants in the hepatic lipase (LIPC) gene have been shown to be associated with plasma lipid levels; however, the distribution and functional features of rare and regulatory LIPC variants contributing to the extreme lipid phenotypes are not well known. This study was aimed to catalogue LIPC variants by resequencing the entire LIPC gene in 95 non-Hispanic Whites (NHWs) and 95 African blacks (ABs) with extreme HDL-C levels followed by in silico functional analyses. A total of 412 variants, including 43 novel variants were identified; 56 were unique to NHWs and 234 were unique to ABs. Seventy-eight variants in NHWs and 89 variants in ABs were present either in high HDL-C group or low HDL-C group. Two non-synonymous variants (p.S289F, p.T405M), found in NHWs with high HDL-C group were predicted to have damaging effect on LIPC protein by SIFT, MT2 and PP2. We also found several non-coding variants that possibly reside in the circRNA and lncRNA binding sites and may have regulatory potential, as identified in rSNPbase and RegulomeDB databases. Our results shed light on the regulatory nature of rare and non-coding LIPC variants as well as suggest their important contributions in affecting the extreme HDL-C phenotypes.

A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context

Genetic studies of metabolites have identified thousands of variants, many of which are associated with downstream metabolic and obesogenic disorders. However, these studies have relied on univariate analyses, reducing power and limiting context-specific understanding. Here we aim to provide an integrated perspective of the genetic basis of metabolites by leveraging the Finnish Metabolic Syndrome In Men (METSIM) cohort, a unique genetic resource which contains metabolic measurements, mostly lipids, across distinct time points as well as information on statin usage. We increase effective sample size by an average of two-fold by applying the Covariates for Multi-phenotype Studies (CMS) approach, identifying 588 significant SNP-metabolite associations, including 228 new associations. Our analysis pinpoints a small number of master metabolic regulator genes, balancing the relative proportion of dozens of metabolite levels. We further identify associations to changes in metabolic levels across time as well as genetic interactions with statin at both the master metabolic regulator and genome-wide level.