Background
Insulin resistance (IR) is an insensitivity state of the peripheral tissue to the effects of insulin. IR and the consequence of compensatory hyperinsulinemia are fundamental pathogenic factors for various metabolic abnormalities [
1] that contribute to the development of diabetes mellitus and cardiovascular disease [
2,
3]. Hyperinsulinemic euglycemic pump remains the gold standard for measuring IR, whereas homeostatic model assessment for insulin resistance (HOMA-IR) index is more practically used for determining IR in clinical application. Recently, multiple predictors for IR have also been proposed. For example, the visceral adiposity index (VAI) is an indicator of adipose tissue dysfunction and a surrogate marker for IR, which is calculated on the basis of anthropometric body mass index (BMI), waist circumference (WC), and lipid traits [
4,
5]. The lipid accumulation product (LAP), a mathematical model based on a combination of serum triglyceride (TG) levels and WC, is a sensitive marker for visceral obesity that has the potential to estimate IR [
6,
7]. The product of TG and fasting plasma glucose (FPG) levels (the TyG index) and the TyG index-related parameters, including the TyG with adiposity status (TyG-BMI index) and the TyG-WC index (particularly the TyG-BMI), have been proposed as simple, efficient, and clinically useful surrogate markers for early identification of IR, which may further predict the occurrence of metabolic syndromes and diabetes mellitus [
8‐
11].
Hepatic lipase (HL, encoded by
LIPC) is a glycoprotein primarily synthesized and secreted by hepatocytes, and to a lesser extent, by macrophages and other tissues [
12]. HL is a member of the triacylglycerol lipase family and is a key enzyme responsible for the hydrolysis of TGs and phospholipids in nearly all lipoprotein subclasses, resulting in the generation of small and dense particles [
13]. HL also plays a role in the metabolism of high density lipoprotein (HDL) by converting large, TG-rich HDL
2 into small, dense HDL
3; moreover, it is a negative regulator of plasma HDL cholesterol (HDL-C) levels [
12]. In humans, HL overexpression considerably reduces HDL-C levels because of the increased catabolic rate, whereas HL deficiency increases the levels of large HDL
2 particles, enriches HDL with TG, and causes hyperalphalipoproteinemia because of slow apolipoprotein AI catabolism [
13]. Andrés-Blasco et al. [
14] also showed that HL-inactivation in mice fed with a high-fat, high cholesterol diet, exhibited augmented glucose levels for HL
−/− mice in feed state with similar serum insulin levels compared to wild type mice, suggesting glucose intolerance. In addition to its enzymatic functions, HL facilitates the uptake of chylomicron remnant-like particles by acting as a ligand for glycosaminoglycans on the surface of rat hepatocytes [
13]. Overall, HL is crucial for reverse cholesterol transport, and it affects the lipoprotein and possibly glucose metabolism [
14‐
16].
Recent studies have shown pleiotropic associations of
LIPC single nucleotide polymorphisms (SNPs), which included lipid profiles, hepatic lipase activity, serum insulin levels, insulin sensitivity, markers for oxidative stress, metabolic syndrome and atherosclerotic cardiovascular diseases [
17‐
26]. By contrast, controversial results have been reported on the association between
LIPC SNPs and obesity [
27‐
29]. The visceral adiposity indicators and TyG index-related parameters represent complex phenotypes with the combinations of adiposity status and metabolic traits. Therefore, in the present study, we aimed to investigate the association between
LIPC SNPs and adiposity status, visceral adiposity indicators and TyG index-related parameters and IR in term of HOMA-IR in the Taiwanese population.
Discussion
This study investigated the association between LIPC SNPs and adiposity status, visceral adiposity indicators, and TyG index-related parameters, and HOMA-IR in the Taiwanese population. Our data revealed at least a trend of significant association between two LIPC SNPs, rs2043085 and rs1532085, and BMI, WC, and adiposity status. In addition, these LIPC SNPs were associated with visceral adiposity indicators and TyG index-related parameters, either in continuous variables or in quartiles which were mediated by serum TG levels. The pleiotropic associations further support a complex interaction between LIPC SNPs and the risk of metabolic syndromes, diabetes mellitus and future atherosclerotic cardiovascular disease.
Previous studies have reported controversial results on the association between HL and obesity. For example, mice lacking HL were reported to be lean and protected against diet-induced obesity and hepatic steatosis in one study [
38]. The influence of
LIPC alleles on obesity was investigated through a reciprocal hemizygosity analysis [
39]. Additionally, several studies have revealed that
LIPC SNPs, mostly promoter SNPs, are not associated with BMI. However, one previous study [
29] demonstrated the association between
LIPC promoter SNPs and BMI. Mägi et al. [
40] reported that the rs2043085 SNP was the most significant SNP in the
LIPC locus associated with lipid traits and BMI through a reverse regression approach by using software for correlated phenotype analysis (SCOPA) and META-SCOPA software. Our data revealed that SNPs rs2043085 and rs1532085 were significantly associated with adiposity status. Differential associations between the studied SNPs in adiposity status are interesting. SNP rs1800588 is the promoter
LIPC SNP that has been most widely reported to be associated with various phenotypes [
17‐
21].
LIPC is expressed only in the liver, and both rs1532085 and rs1800588 were associated with the expression of
LIPC [
41].
LIPC SNP rs2043085 exhibited high linkage disequilibrium with rs1532085 and either of them has been shown to be the most significant SNP in the
LIPC locus associated with various phenotypes in several genome-wide association studies (GWASs) [
26,
42,
43]. Using a bivariate genome-wide approach for seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, Kraja et al. [
26] also showed variants in the
LIPC gene as one of the loci associated with metabolic syndrome. Our data suggested that the haplotype block, combining all the three studied SNPs, may be more crucial for future studies as a marker for atherosclerotic cardiovascular disease.
The combined associations of
LIPC SNPs with insulin surrogate markers that based on both metabolic and adiposity status are noteworthy. Shared common variants have similarly been reported between lipid genes and glucose metabolism, inflammation, BMI, cardiometabolic traits, and coronary artery disease [
20,
40,
44‐
46]. Pickrell et al. [
21] developed a method of detecting pairs of traits that exhibited an asymmetry in the effect sizes of associated variants, which is more consistent with a causal relationship between the traits and the authors indicated that an elevated BMI causally increases TG levels, but the reverse is not true. By contrast, we have previously demonstrated that
LIPC SNPs were associated with serum TG and HDL cholesterol levels independently of the BMI [
17]. These results suggest the independence of association between
LIPC SNPs and metabolic and adiposity status.
The genetic determinants of the visceral adiposity indicators and TyG index-related parameters have not been previously reported. These parameters are complex traits derived from simple phenotypes, including metabolic phenotypes with or without adiposity status, with the serum TG level as the most common component of all indices. Thus, a polymorphism associated with both adiposity status and serum TG levels may be associated with these parameters. Furthermore, the associations became nonsignificant after adjustment for serum TG levels. Because of the involvement of serum TG levels in each parameter, other genetic determinants of serum TG levels may also be the genetic determinants of these parameters; however, further research is required to confirm this phenomenon.
The term pleiotropy is used to describe the phenomenon by which genetic variation at a single locus exerts an effect on more than one phenotype. Pleiotropy observed in genetic association studies can provide insight into the shared biology underlying a spectrum of phenotypes. Pleiotropy may be caused by the third variable with mediational, interactive, reverse causal, or suppressive effect [
47‐
49]. By using the National Human Genome Research Institute’s catalog of a published GWAS, Sivakumaran et al. [
50] reported that 4.6% of the SNPs and 16.9% of the genes exhibited the cross-phenotype effect. However, with the growing number of GWASs, this effect is likely to be underestimated. Some chromosomal regions, including the gene loci near
LIPC, appear to be particular foci for association with multiple phenotypes [
20,
21]. Moreover, different
LIPC SNPs have been associated with levels of circulating malondialdehyde-modified low-density lipoprotein [
22]; phospholipids and sphingolipids [
51]; folate and vitamin E [
52]; BMI [
29,
39]; metabolic syndrome [
26]; and diseases such as advanced age-related macular degeneration [
43,
53,
54], coronary artery disease [
18], and myocardial infarction [
19]. Our data further revealed that the
LIPC SNPs are associated with adiposity status, visceral adiposity indicators, and TyG index-related parameters in the Taiwanese population. Visceral obesity has been shown to be associated with IR and a high risk of developing type 2 diabetes after myocardial infarction [
55]. Several human studies also indicate that these surrogated markers for IR may identify individuals at a high risk of developing cardiovascular events and mortality [
56‐
62]. Thus, our findings implicated that the genetic determinants of these parameters is crucial in providing a method for identifying high-risk populations of cardiovascular diseases for preventive medicine.
By contrast, IR is influenced by multiple factors, including lipid profiles, obesity and inflammation, in which LIPC SNPs are not associated with circulating inflammatory markers in our study population (data not shown). We also found no significant association between any the studied LIPC SNPs and IR in term of HOMA-IR.
The main limitation of this study is its medium sample size and relatively low number of genotyped participants. This limitation may be more marked because a complex trait was central to this analysis. Nevertheless, such associations may be attributed to the mediational effect of serum TG levels. Furthermore, only three LIPC SNPs were analyzed, which suggests an incomplete coverage of LIPC SNPs; hence, the study did not represent all genetic variations of LIPC.
Authors’ contributions
M-ST and SW prepared the DNA samples, participated in genotyping, performed statistical analysis and drafted the manuscript. L-KE and H-HC assisted in study design and contributed to the discussion. L-AH assisted in study design and performed and corrected statistical analysis. Y-LK designed the study, drafted and revised the manuscript. All authors read and approved the final manuscript.