Association of hepatic lipase gene polymorphisms with hypertriglyceridemia and low high-density lipoprotein-cholesterol levels among South Indian subjects without diabetes

Understanding Hypertriglyceridemia: Integrating Genetic Insights

Hypertriglyceridemia is an exceptionally complex metabolic disorder characterized by elevated plasma triglycerides associated with an increased risk of acute pancreatitis and cardiovascular diseases such as coronary artery disease. Its phenotype expression is widely heterogeneous and heavily influenced by conditions as obesity, alcohol consumption, or metabolic syndromes. Looking into the genetic underpinnings of hypertriglyceridemia, this review focuses on the genetic variants in LPL, APOA5, APOC2, GPIHBP1 and LMF1 triglyceride-regulating genes reportedly associated with abnormal genetic transcription and the translation of proteins participating in triglyceride-rich lipoprotein metabolism. Hypertriglyceridemia resulting from such genetic abnormalities can be categorized as monogenic or polygenic. Monogenic hypertriglyceridemia, also known as familial chylomicronemia syndrome, is caused by homozygous or compound heterozygous pathogenic variants in the five canonical genes. Polygenic hypertriglyceridemia, also known as multifactorial chylomicronemia syndrome in extreme cases of hypertriglyceridemia, is caused by heterozygous pathogenic genetic variants with variable penetrance affecting the canonical genes, and a set of common non-pathogenic genetic variants (polymorphisms, using the former nomenclature) with well-established association with elevated triglyceride levels. We further address recent progress in triglyceride-lowering treatments. Understanding the genetic basis of hypertriglyceridemia opens new translational opportunities in the scope of genetic screening and the development of novel therapies.

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.

Determination of individual type 2 diabetes risk profile in the North East Indian population & its association with anthropometric parameters

Background & objectives:

Diabetes genomics research has illuminated single nucleotide polymorphism (SNP) in several genes including, fat mass and obesity associated (FTO) (rs9939609 and rs9926289), potassium voltage-gated channel subfamily J member 11 (rs5219), SLC30A8 (rs13266634) and peroxisome proliferator-activated receptor gamma 2 (rs1805192). The present study was conducted to investigate the involvement of these polymorphisms in conferring susceptibility to type 2 diabetes (T2D) in the North East Indian population, and also to establish their association with anthropometric parameters.

Methods:

DNA was extracted from blood samples of 155 patients with T2D and 100 controls. Genotyping was performed by polymerase chain reaction-restriction fragment length polymorphism and DNA sequencing. To confirm the association between the inheritance of SNP and T2D development, logistic regression analysis was performed.

Results:

For the rs9939609 variant (FTO), the dominant model AA/(AT+TT) revealed significant association with T2D [odds ratio (OR)=2.03, P=0.021], but was non-significant post correction for multiple testing (P=0.002). For the rs13266634 variant (SLC30A8), there was considerable but non-significant difference in the distribution pattern of genotypic polymorphisms between the patients and the controls (P=0.004). Significant association was observed in case of the recessive model (CC+CT)/TT (OR=4.56 P=0.001), after adjusting for age, gender and body mass index. In addition, a significant association (P=0.001) of low-density lipoprotein (mg/dl) could be established with the FTO (rs9926289) polymorphism assuming dominant model.

Interpretation & conclusions:

The current study demonstrated a modest but significant effect of SLC30A8 (rs13266634) polymorphisms on T2D predisposition. Considering the burgeoning prevalence of T2D in the Indian population, the contribution of these genetic variants studied, to the ever-increasing number of T2D cases, appears to be relatively low. This study may serve as a foundation for performing future genome-wide association studies (GWAS) involving larger populations.

A systems genetics approach to dyslipidemia in children and adolescents

Elevated triglycerides (TG) or low high density lipoprotein cholesterol (HDL-C) levels are common cardiometabolic risk factors in children. From a systems genetics standpoint, Visualization of Statistical Epistasis Networks (ViSEN) is a nonparametric entropy-based method that can characterize the global structure of interacting genetic factors. We identified a novel set of connected genetic and cardiometabolic risk factors with strong and significant interaction effects on two important dyslipidemia phenotypes (low HDL-C and high TG) in children and adolescents. Study participants were recruited from five schools in Istanbul, Turkey (n=360; 170 boys, 190 girls). Participants with TG levels≥75th and HDL-C levels≤25th percentile were defined as 'high TG' and 'low HDL-C', respectively. We genotyped participants for six single nucleotide polymorphisms (SNPs) in five genes with known associations to lipid levels (rs328 in LPL, rs708272 in CETP, rs1800588 in LIPC, rs1800977 in ABCA1, rs1799941 and rs6257 in SHBG gene). ViSEN was used to identify associations with dyslipidemia phenotypes. There were 71 (50 males, 21 females) and 93 (60 males and 33 females) subjects with low HDL-C and high TG, respectively. Biological variables including age, gender, and BMI were significantly associated with both phenotypes (p<0.001). Importantly, a single SNP, rs708272, was associated with low HDL-C (IG=2.24%, p=0.026). Pairwise and higher order interaction analyses in the full dataset for low HDL-C and high TG revealed the largest effects in the models containing rs1800977, rs708272, age (IG=6.20%, p=0.046) and rs1800588, age, BMI (IG, 3.06%, p=0.022), respectively. In conclusion, the present study brings us a step closer to a systems genetic approach in understanding lipid phenotypes in children. Further efforts can integrate population and laboratory-based studies, hence accelerate the preventive medicine efforts.

Epipolymorphisms within lipoprotein genes contribute independently to plasma lipid levels in familial hypercholesterolemia

Gene polymorphisms associated so far with plasma lipid concentrations explain only a fraction of their heritability, which can reach up to 60%. Recent studies suggest that epigenetic modifications (DNA methylation) could contribute to explain part of this missing heritability. We therefore assessed whether the DNA methylation of key lipoprotein metabolism genes is associated with high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and triglyceride levels in patients with familial hypercholesterolemia (FH). Untreated FH patients (61 men and 37 women) were recruited for the measurement of blood DNA methylation levels at the ABCG1, LIPC, PLTP and SCARB1 gene loci using bisulfite pyrosequencing. ABCG1, LIPC and PLTP DNA methylation was significantly associated with HDL-C, LDL-C and triglyceride levels in a sex-specific manner (all P<0.05). FH subjects with previous history of coronary artery disease (CAD) had higher LIPC DNA methylation levels compared with FH subjects without CAD (P = 0.02). Sex-specific multivariable linear regression models showed that new and previously reported epipolymorphisms (ABCG1-CpGC3, LIPC-CpGA2, mean PLTP-CpGC, LPL-CpGA3, CETP-CpGA2, and CETP-CpGB2) significantly contribute to variations in plasma lipid levels (all P<0.001 in men and P<0.02 in women), independently of traditional predictors such as age, waist circumference, blood pressure, fasting plasma lipids and glucose levels. These results suggest that epigenetic perturbations of key lipoprotein metabolism genes are associated with plasma lipid levels, contribute to the interindividual variability and might partially explain the missing heritability of plasma lipid levels, at least in FH.