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Diabetology & Metabolic Syndrome
Published in: Diabetology & Metabolic Syndrome 1/2018

Open Access 01-12-2018 | Research

LIPC variants as genetic determinants of adiposity status, visceral adiposity indicators, and triglyceride-glucose (TyG) index-related parameters mediated by serum triglyceride levels

Authors: Ming-Sheng Teng, Semon Wu, Leay-Kiaw Er, Lung-An Hsu, Hsin-Hua Chou, Yu-Lin Ko

Published in: Diabetology & Metabolic Syndrome | Issue 1/2018

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Abstract

Background

Visceral adiposity indicators and the product of triglyceride and fasting plasma glucose (TyG) index-related parameters are effective surrogate markers for insulin resistance (IR) and are predictors of metabolic syndrome and diabetes mellitus. However, their genetic determinants have not been previously reported. Pleiotropic associations of LIPC variants have been observed in lipid profiles and atherosclerotic cardiovascular diseases. We aimed to investigate LIPC polymorphisms as the genetic determinants of adiposity status, visceral adiposity indicators and TyG index-related parameters.

Methods

A total of 592 participants from Taiwan were genotyped for three LIPC single nucleotide polymorphisms (SNPs).

Results

The LIPC SNPs rs2043085 and rs1532085 were significantly associated with body mass index (BMI), waist circumference (WC), lipid accumulation product, visceral adiposity index, and TyG index-related parameters [including the TyG index, TyG with adiposity status (TyG-BMI), and TyG-WC index], whereas the rs1800588 SNP was only significantly associated with the TyG index. The associations became nonsignificant after further adjustment for serum TG levels. No significant association was observed between any the studied LIPC SNPs and IR status.

Conclusion

Our data revealed a pleiotropic association between the LIPC variants and visceral adiposity indicators and TyG index-related parameters, which are mediated by serum TG levels.
Appendix
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Literature
1.
Matthaei S, Stumvoll M, Kellerer M, Häring HU. Pathophysiology and pharmacological treatment of insulin resistance. Endocr Rev. 2000;21:585–618.PubMed
2.
Lillioja S, Mott DM, Spraul M, Ferraro R, Foley JE, Ravussin E, et al. Insulin resistance and insulin secretory dysfunction as precursors of non-insulin-dependent diabetes mellitus: prospective studies of Pima Indians. N Engl J Med. 1993;329:1988–92.CrossRef
3.
Rader DJ. Effect of insulin resistance, dyslipidemia, and intra-abdominal adiposity on the development of cardiovascular disease and diabetes mellitus. Am J Med. 2007;120:S12–8.CrossRef
4.
Amato MC, Giordano C, Galia M, Criscimanna A, Vitabile S, Midiri M, et al. Visceral adiposity index: a reliable indicator of visceral fat function associated with cardiometabolic risk. Diabetes Care. 2010;33:920–2.CrossRef
5.
Ciresi A, Amato MC, Pizzolanti G, Giordano Galluzzo C. Visceral adiposity index is associated with insulin sensitivity and adipocytokine levels in newly diagnosed acromegalic patients. J Clin Endocrinol Metab. 2012;97:2907–15.CrossRef
6.
Kahn HS. The lipid accumulation product is better than BMI for identifying diabetes: a population-based comparison. Diabetes Care. 2006;29:151–3.CrossRef
7.
Ioachimescu AG, Brennan DM, Hoar BM, Hoogwerf BJ. The lipid accumulation product and all-cause mortality in patients at high cardiovascular risk: a PreCIS database study. Obesity (Silver Spring). 2010;18:1836–44.CrossRef
8.
Du T, Yuan G, Zhang M, Zhou X, Sun X, Yu X. Clinical usefulness of lipid ratios, visceral adiposity indicators, and the triglycerides and glucose index as risk markers of insulin resistance. Cardiovasc Diabetol. 2014;13:146.CrossRef
9.
Lee SH, Han K, Yang HK, Kim MK, Yoon KH, Kwon HS, et al. Identifying subgroups of obesity using the product of triglycerides and glucose: the Korea national health and nutrition examination survey, 2008–2010. Clin Endocrinol (Oxf). 2015;82:213–20.CrossRef
10.
Er LK, Wu S, Chou HH, Hsu LA, Teng MS, Sun YC, et al. Triglyceride glucose-body mass index is a simple and clinically useful surrogate marker for insulin resistance in nondiabetic individuals. PLoS ONE. 2016;11:e0149731.CrossRef
11.
Zheng S, Shi S, Ren X, Han T, Li Y, Chen Y, et al. Triglyceride glucose-waist circumference, a novel and effective predictor of diabetes in first-degree relatives of type 2 diabetes patients: cross-sectional and prospective cohort study. J Transl Med. 2016;14:260.CrossRef
12.
Kobayashi J, Miyashita K, Nakajima K, Mabuchi H. Hepatic lipase: a comprehensive view of its role on plasma lipid and lipoprotein metabolism. J Atheroscler Thromb. 2015;22:1001–11.CrossRef
13.
Annema W, Tietge UJ. Role of hepatic lipase and endothelial lipase in high-density lipoprotein-mediated reverse cholesterol transport. Curr Atheroscler Rep. 2011;13:257–65.CrossRef
14.
Andrés-Blasco I, Herrero-Cervera A, Vinué Á, Martínez-Hervás S, Piqueras L, et al. Hepatic lipase deficiency produces glucose intolerance, inflammation and hepatic steatosis. J Endocrinol. 2015;227:179–91.CrossRef
15.
Cohen JC, Vega GL, Grundy SM. Hepatic lipase: new insights from genetic and metabolic studies. Curr Opin Lipidol. 1999;10:259–67.CrossRef
16.
Thuren T. Hepatic lipase and HDL metabolism. Curr Opin Lipidol. 2000;2000(11):277–83.CrossRef
17.
Ko YL, Hsu LA, Hsu KH, Ko YH, Lee YS. The interactive effects of hepatic lipase gene promoter polymorphisms with sex and obesity on high-density-lipoprotein cholesterol levels in Taiwanese–Chinese. Atherosclerosis. 2004;172:135–42.CrossRef
18.
Zhang C, Lopez-Ridaura R, Rimm EB, Li T, Hunter DJ, et al. Genetic variation in the hepatic lipase gene and the risk of coronary heart disease among US diabetic men: potential interaction with obesity. Diabetologia. 2006;49:1552–9.CrossRef
19.
Ahmad T, Chasman DI, Buring JE, Lee IM, Ridker PM, et al. Physical activity modifies the effect of LPL, LIPC, and CETP polymorphisms on HDL-C levels and the risk of myocardial infarction in women of European ancestry. Circ Cardiovasc Genet. 2011;4:74–80.CrossRef
20.
Price AL, Spencer CC, Donnelly P. Progress and promise in understanding the genetic basis of common diseases. Proc Biol Sci. 2015;282:20151684.CrossRef
21.
Pickrell JK, Berisa T, Liu JZ, Ségurel L, Tung JY, Hinds DA. Detection and interpretation of shared genetic influences on 42 human traits. Nat Genet. 2016;48:709–17.CrossRef
22.
Yamazaki K, Bujo H, Taira K, Itou N, Shibasaki M, Takahashi K, et al. Increased circulating malondialdehyde-modified LDL in the patients with familial combined hyperlipidemia and its relation with the hepatic lipase activity. Atherosclerosis. 2004;172:181–7.CrossRef
23.
Pihlajamäki J, Karjalainen L, Karhapää P, Vauhkonen I, Taskinen MR, et al. G-250A substitution in promoter of hepatic lipase gene is associated with dyslipidemia and insulin resistance in healthy control subjects and in members of families with familial combined hyperlipidemia. Arterioscler Thromb Vasc Biol. 2000;20:1789–95.CrossRef
24.
Waterworth DM, Jansen H, Nicaud V, Humphries SE, Talmud PJ, EARSII Study Group. Interaction between insulin (VNTR) and hepatic lipase (LIPC-514C>T) variants on the response to an oral glucose tolerance test in the EARSII group of young healthy men. Biochim Biophys Acta. 2005;1740:375–81.CrossRef
25.
Andrés-Blasco I, Vinué Á, Herrero-Cervera A, Martínez-Hervás S, Nuñez L, et al. Hepatic lipase inactivation decreases atherosclerosis in insulin resistance by reducing LIGHT/lymphotoxin β-receptor pathway. Thromb Haemost. 2016;116:379–93.CrossRef
26.
Kraja AT, Vaidya D, Pankow JS, Goodarzi MO, Assimes TL, Kullo IJ, et al. A bivariate genome-wide approach to metabolic syndrome: STAMPEED consortium. Diabetes. 2011;60:1329–39.CrossRef
27.
Murtomäki S, Tahvanainen E, Antikainen M, Tiret L, Nicaud V, Jansen H, et al. Hepatic lipase gene polymorphisms influence plasma HDL levels: results from Finnish EARS participants. European atherosclerosis research study. Arterioscler Thromb Vasc Biol. 1997;17:1879–84.CrossRef
28.
St-Pierre J, Miller-Felix I, Paradis ME, Bergeron J, Lamarche B, Després JP, et al. Visceral obesity attenuates the effect of the hepatic lipase −514C>T polymorphism on plasma HDL-cholesterol levels in French–Canadian men. Mol Genet Metab. 2003;78:31–6.CrossRef
29.
Wang H, Zhang D, Ling J, Lu W, Zhang S, Zhu Y, et al. Gender specific effect of LIPC C-514T polymorphism on obesity and relationship with plasma lipid levels in Chinese children. J Cell Mol Med. 2015;19:2296–306.CrossRef
30.
Tan CE, Ma S, Wai D, Chew SK, Tai ES. Can we apply the national cholesterol education program adult treatment panel definition of the metabolic syndrome to Asians? Diabetes Care. 2004;27:1182–6.CrossRef
31.
Lu X, Huang J, Mo Z, He J, Wang L, Yang X, et al. Genetic susceptibility to lipid levels and lipid change over time and risk of incident hyperlipidemia in Chinese populations. Circ Cardiovasc Genet. 2016;9:37–44.CrossRef
32.
Shohet RV, Vega GL, Bersot TP, Mahley RW, Grundy SM, Guerra R, et al. Sources of variability in genetic association studies: insights from the analysis of hepatic lipase (LIPC). Hum Mutat. 2002;19:536–42.CrossRef
33.
Bonora E, Targher G, Alberiche M, Bonadonna RC, Saggiani F, Zenere MB, et al. Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes Care. 2000;23:57–63.CrossRef
34.
Gayoso-Diz P, Otero-González A, Rodriguez-Alvarez MX, Gude F, García F, De Francisco A, Quintela AG. Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study. BMC Endocr Disord. 2013;13:47.CrossRef
35.
Gayoso-Diz P, Otero-Gonzalez A, Rodriguez-Alvarez MX, Gude F, Cadarso-Suarez C, García F, De Francisco A. Insulin resistance index (HOMA-IR) levels in a general adult population: curves percentile by gender and age. The EPIRCE study. Diabetes Res Clin Pract. 2011;94(1):146–55.CrossRef
36.
Simental-Mendia LE, Rodriguez-Moran M, Guerrero-Romero F. The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects. Metab Syndr Relat Disord. 2008;6:299–304.CrossRef
37.
Guerrero-Romero F, Simental-Mendia LE, Gonzalez-Ortiz M, Martinez-Abundis E, Ramos-Zavala MG, Hernandez-Gonzalez SO, et al. The product of triglycerides and glucose, a simple measure of insulin sensitivity. Comparison with the euglycemic hyperinsulinemic clamp. J Clin Endocrinol Metab. 2010;95:3347–51.CrossRef
38.
Chiu HK, Qian K, Ogimoto K, Morton GJ, Wisse BE, Agrawal N, et al. Mice lacking hepatic lipase are lean and protected against diet-induced obesity and hepatic steatosis. Endocrinology. 2010;151:993–1001.CrossRef
39.
Farahani P, Fisler JS, Wong H, Diament AL, Yi N, Warden CH. Reciprocal hemizygosity analysis of mouse hepatic lipase reveals influence on obesity. Obes Res. 2004;12:292–305.CrossRef
40.
Mägi R, Suleimanov YV, Clarke GM, Kaakinen M, Fischer K, Prokopenko I, et al. SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes. BMC Bioinform. 2017;11(18):25.CrossRef
41.
Folkersen L, van’t Hooft F, Chernogubova E, Agardh HE, Hansson GK, Hedin U, et al. Association of genetic risk variants with expression of proximal genes identifies novel susceptibility genes for cardiovascular disease. Circ Cardiovasc Genet. 2010;3:365–73.CrossRef
42.
Benner C, Spencer CC, Havulinna AS, Salomaa V, Ripatti S, Pirinen M. FINEMAP: efficient variable selection using summary data from genome-wide association studies. Bioinformatics. 2016;32:1493–501.CrossRef
43.
Fritsche LG, Igl W, Bailey JN, Grassmann F, Sengupta S, Bragg-Gresham JL, et al. A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants. Nat Genet. 2016;48:134–43.CrossRef
44.
Li N, van der Sijde MR, LifeLines Cohort Study Group, Bakker SJ, Dullaart RP, van der Harst P, Gansevoort RT, et al. Pleiotropic effects of lipid genes on plasma glucose, HbA1c, and HOMA-IR levels. Diabetes. 2014;63:3149–58.CrossRef
45.
Ligthart S, Vaez A, Hsu YH, Inflammation Working Group of the CHARGE Consortium, PMI-WG-XCP, LifeLines Cohort Study, Stolk R, Uitterlinden AG, et al. Bivariate genome-wide association study identifies novel pleiotropic loci for lipids and inflammation. BMC Genomics. 2016;10(17):443.CrossRef
46.
Kim YK, Hwang MY, Kim YJ, Moon S, Han S, Kim BJ. Evaluation of pleiotropic effects among common genetic loci identified for cardio-metabolic traits in a Korean population. Cardiovasc Diabetol. 2016;15:20.CrossRef
47.
MacKinnon D, Krull JL, Lockwood CM. Equivalence of the mediation, confounding and suppression effect. Prev Sci. 2000;1:173–81.CrossRef
48.
Solovieff N, Cotsapas C, Lee PH, Purcell SM, Smoller JW. Pleiotropy in complex traits: challenges and strategies. Nat Rev Genet. 2013;14:483–95.CrossRef
49.
Ko YL, Hsu LA, Wu S, Teng MS, Chou HH. CRP and SAA1 haplotypes are associated with both C-reactive protein and serum amyloid A levels: role of suppression effects. Mediat Inflamm. 2016;2016:5830361.
50.
Sivakumaran S, Agakov F, Theodoratou E, Prendergast JG, Zgaga L, Manolio T, et al. Abundant pleiotropy in human complex diseases and traits. Am J Hum Genet. 2011;89:607–18.CrossRef
51.
Demirkan A, van Duijn CM, Ugocsai P, Isaacs A, Pramstaller PP, Liebisch G, et al. Genome-wide association study identifies novel loci associated with circulating phospho- and sphingolipid concentrations. PLoS Genet. 2012;8:e1002490.CrossRef
52.
Hall MA, Verma A, Brown-Gentry KD, Goodloe R, Boston J, Wilson S, et al. Detection of pleiotropy through a phenome-wide association study (PheWAS) of epidemiologic data as part of the environmental architecture for genes linked to environment (EAGLE) study. PLoS Genet. 2014;10:e1004678.CrossRef
53.
Neale BM, Fagerness J, Reynolds R, Sobrin L, Parker M, Raychaudhuri S, et al. Genome-wide association study of advanced age-related macular degeneration identifies a role of the hepatic lipase gene (LIPC). Proc Natl Acad Sci USA. 2010;107:7395–400.CrossRef
54.
Seddon JM, Reynolds R, Rosner B. Associations of smoking, body mass index, dietary lutein, and the LIPC gene variant rs10468017 with advanced age-related macular degeneration. Mol Vis. 2010;16:2412–24.PubMedPubMedCentral
55.
Barbarash O, Gruzdeva O, Uchasova E, Dyleva Y, Belik E, Akbasheva O, et al. The role of adipose tissue and adipokines in the manifestation of type 2 diabetes in the long-term period following myocardial infarction. Diabetol Metab Syndr. 2016;8:24.CrossRef
56.
Sánchez-Íñigo L, Navarro-González D, Fernández-Montero A, Pastrana-Delgado J, Martínez JA. The TyG index may predict the development of cardiovascular events. Eur J Clin Invest. 2016;46(2):189–97.CrossRef
57.
Wang Y, He S, He J, Wang S, Liu K, Chen X. Predictive value of visceral adiposity index for type 2 diabetes mellitus: a 15-year prospective cohort study. Herz. 2015;40(Suppl 3):277–81.CrossRef
58.
Chen HY, Chiu YL, Chuang YF, Hsu SP, Pai MF, Yang JY, Peng YS. Visceral adiposity index and risks of cardiovascular events and mortality in prevalent hemodialysis patients. Cardiovasc Diabetol. 2014;4(13):136.CrossRef
59.
Lee SH, Kwon HS, Park YM, Ha HS, Jeong SH, Yang HK, Lee JH, Yim HW, Kang MI, Lee WC, Son HY, Yoon KH. Predicting the development of diabetes using the product of triglycerides and glucose: the Chungju metabolic disease cohort (CMC) study. PLoS ONE. 2014;9(2):e90430.CrossRef
60.
Wehr E, Pilz S, Boehm BO, März W, Obermayer-Pietsch B. The lipid accumulation product is associated with increased mortality in normal weight postmenopausal women. Obesity (Silver Spring). 2011;19(9):1873–80.CrossRef
61.
Ioachimescu AG, Brennan DM, Hoar BM, Hoogwerf BJ. The lipid accumulation product and all-cause mortality in patients at high cardiovascular risk: a PreCIS database study. Obesity (Silver Spring). 2010;18(9):1836–44.CrossRef
62.
Bozorgmanesh M, Hadaegh F, Azizi F. Predictive performances of lipid accumulation product vs. adiposity measures for cardiovascular diseases and all-cause mortality, 8.6-year follow-up: Tehran lipid and glucose study. Lipids Health Dis. 2010;9:100.CrossRef
63.
Nikpay M, Goel A, Won HH, Hall LM, Willenborg C, Kanoni S, et al. A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nat Genet. 2015;47:1121–30.CrossRef
Metadata
Title
LIPC variants as genetic determinants of adiposity status, visceral adiposity indicators, and triglyceride-glucose (TyG) index-related parameters mediated by serum triglyceride levels
Authors
Ming-Sheng Teng
Semon Wu
Leay-Kiaw Er
Lung-An Hsu
Hsin-Hua Chou
Yu-Lin Ko
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Diabetology & Metabolic Syndrome / Issue 1/2018
Electronic ISSN: 1758-5996
DOI
https://doi.org/10.1186/s13098-018-0383-9

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