Lipoprotein Lipase Variants D9N and N291S Are Associated With Increased Plasma Triglyceride and Lower High-Density Lipoprotein Cholesterol Concentrations
Studies in the Fasting and Postprandial States: The European Atherosclerosis Research Studies
Background Variations at the DNA level with moderate effects on biochemical variables may be important for the occurrence of disease at the population level, if they are common. Two mutations in the LPL gene, N9 and S291, are associated with variation in fasting plasma concentrations of HDL cholesterol (HDL-C) and triglycerides (TG). We investigated whether these mutants were more frequent in offspring of cases with premature coronary disease and analyzed the effects on fasting plasma lipids and postprandial TG.
Methods and Results Students with and without paternal history of myocardial infarction (cases and control subjects [controls]) were studied in the European Atherosclerosis Research Studies I and II (EARS-I and -II). Allelic frequencies for the N9 and S291 mutations did not differ between cases and control subjects. The N9 mutation was identified in 4.2% of all subjects in EARS-I, and carriers had higher fasting TG levels (P<.001) than noncarriers. In an oral fat tolerance test, there were no differences in postprandial TG between carriers and noncarriers of the N9 allele. The S291 mutation was identified in 3.1% of all subjects in EARS-I, and carriers had lower fasting HDL-C levels (P<.005) than noncarriers. There was a significant interaction between S291 genotype and body mass index on fasting TG levels (P<.01). In the cases, carriers of the S291 allele had higher TG levels 6 hours postprandially (P<.04) than did noncarriers.
Conclusions The two LPL mutations are common and may predispose to elevated TG and decreased HDL-C concentrations, even in young subjects. In the case of the S291 mutation, this effect appears to be mediated via delayed postprandial TG clearance. Moreover, even moderate obesity potentiates the TG-raising and HDL-lowering effects associated with the S291 allele.
Low concentrations of plasma HDL-C are inversely related to atherosclerosis and CHD.1 They are also inversely correlated with fasting TG2 and strongly associated with the activity of LPL, a key enzyme in the metabolism of TG-rich lipoproteins.3 A common lipid phenotype, characterized by both low HDL and high TG levels, substantially increases the risk of CHD.1 It is maintained across generations, suggesting a strong genetic component,2 4 with the LPL gene as an obvious candidate.
Variations at the DNA level in general have moderate-to-weak effects on biochemical variables.5 Nevertheless, they may be important for the occurrence of disease at the population level, if they are common.6 There are two common mutations in the LPL gene. One of these substitutes an asparagine for an aspartic acid at amino acid residue 9 (N9)7 in the mature protein, and the other mutant results in the replacement of asparagine by serine at residue 291 (S291).8
Fasting HDL-C and, to a lesser extent, fasting TG concentrations partially reflect postprandial lipoprotein metabolism.3 9 10 If fat absorption from the gut is normal, the postprandial lipoprotein pattern is largely determined by LPL, and the effects of genetic variation in the LPL gene might therefore be more evident on postprandial than on fasting lipoproteins. The effects of N9 and S291 mutations on postprandial plasma lipids are largely unknown,11 and one of the purposes of this study was to clarify them. We also wanted to test whether subjects with a priori higher risk of CHD had a higher frequency of the variant alleles and to study the effects of the two LPL mutations on fasting plasma lipids in young subjects.
A problem in the study of genetic determinants of risk of CHD is that the study variable (eg, biochemical trait) may itself be affected by the disease, age, environmental factors, and/or by treatment of the disease. A way to circumvent this problem is to study young offspring of patients with and without CHD (cases and control subjects [controls], respectively). The design of an offspring study makes data interpretation complex, and comparison of, for example, allele frequencies between cases and control subjects has less power and cannot be interpreted as in a classic case-control study.12
The EARS-I and -II are case-control offspring studies of European university students with and without a paternal history of myocardial infarction before the age of 55 years. In EARS-I, we screened a large number of subjects for the two LPL mutations and studied the effects on fasting lipids associated with the variant alleles. In EARS-II, we tested the stability of the effects observed in EARS-I and studied the impact of the two LPL mutations on postprandial TG responses.
EARS-I has been described previously.13 Briefly, male and female university students between 18 and 26 years with a paternal history of myocardial infarction before age 55 (cases) were recruited in 1990 from 14 university student populations from 11 European countries: Austria, Belgium, Denmark, Finland, France, Germany, Italy, Spain, Sweden, Switzerland, and the United Kingdom. Two age- and sex-matched control subjects per case were randomly selected from the same university populations. Details of lifestyle, medical history, and physiological measurements were established using standardized protocols. Venous blood was collected after a 14-hour fast.
EARS-II was carried out in 1993. Male students aged 18 to 28 years were recruited from 14 university student populations from 11 European countries: Estonia, Finland, Belgium, Denmark, Germany, Switzerland, the United Kingdom, Spain, Italy, Portugal, and Greece. Subjects were recruited and data were collected using the same protocol as described above with the exception that cases and control subjects were matched 1:1. EARS-II also included an OGTT and an OFTT.
OGTT and OFTT
Subjects were given a standard (75 g) OGTT. One week later, they were given an oral liquid lipid load containing 66 g fat (42 g saturated), 22 g protein, 56 g carbohydrate, and 417 mg cholesterol. The formula contained 6186 kJ. Blood was drawn at baseline and at 2, 3, 4, and 6 hours. Biochemical analyses were performed as previously described.14 15
DNA was extracted as previously described.7 LPL exon 2 was amplified by the polymerase chain reaction7 using DNA predried onto microtiter plates.16 Screening for the N9 allele was by allele-specific oligonucleotides. Oligonucleotides used for the allele-specific oligonucleotides had the following sequence: homologous to D9 sequence 5′-GAT TTT ATC GAC ATC G-3′ and homologous to N9 sequence 5′-GAT TTT ATC AAC ATC GA-3′. Positive samples were confirmed using a restriction enzyme cleavage assay.7 Screening for the S291 allele was performed as previously described17 using DNA predried onto microtiter plates.
The recruitment centers in EARS-I were grouped into five regions on the basis of published age-standardized mortality rates, geography, and language.14 In EARS-II, we defined the four regions of Baltic (Finland and Estonia), United Kingdom, Middle Europe (Denmark, Germany, Belgium, and Switzerland), and Southern Europe (Portugal, Italy, Spain, and Greece).
We excluded from analyses subjects with both mutations and subjects from whom measurements of TG, cholesterol, or HDL-C were not available. In analyses of N9 carriers, subjects with the S291 mutation were excluded from the noncarrier group and vice versa. Allele frequencies were compared between cases and control subjects with a Mantel-Haenszel test adjusted for region.
In analyses of lipid levels by genotype, means were compared with ANOVA (GLM procedure) after adjustment of matching and stratification criteria (age, region, sex, and case/control subject status) and covariates (oral contraception, tobacco and alcohol consumption, and physical activity assessed as one of three levels [minimal, moderate, and heavy]). TG and insulin levels were log-transformed for analyses, but arithmetic mean values are shown. The homogeneity of the genotype effect in cases and control subjects, in men and women, and by region was systematically tested by introducing the corresponding interaction term in all stages of the analyses. Further analyses were performed in center and gender tertiles of BMI, TG, and HDL-C.
The postprandial response studied in EARS-II was characterized by three different methods in which we adjusted for age, region, case/control subject status, and covariates: (1) two-way ANOVA for repeated measures to test the overall significance of postprandial measurements over time and between genotypes and the parallelism of the two curves (GLM procedure); (2) the AUC above the fasting concentration, calculated by the trapezoidal rule; and (3) the peak, calculated as the highest value minus the fasting value.
For technical reasons, DNA samples from Italy in EARS-I could not be analyzed. Because of a low yield of DNA from some other samples and exclusion due to missing data, final analysis was based on 84% and 74% of 1994 subjects for the N9 and S291 genotypes, respectively. In EARS-II, all data were obtained on 90% of 822 subjects for both genotypes.
The overall frequency of the N9 allele for pooled cases and control subjects was 2.1% in EARS-I (Table 1⇓) and 1.7% in EARS-II (legend to Table 3⇓). Allele frequencies varied statistically significantly between regions in EARS-I, and the EARS-II data suggested the same pattern. Allelic frequencies did not differ significantly between cases and control subjects in either of the studies. One subject was homozygous for the N9 allele, and three subjects (who were excluded from analysis) were heterozygous for both the N9 and S291 alleles. Plasma lipid and apolipoprotein concentrations as well as body mass indices were within the normal range for these four subjects (data not shown). There were more smokers in the N9 carrier group in EARS-I than in the noncarrier group (42% versus 26%, P=.003), whereas the proportion of smokers was the same in carriers and noncarriers in EARS-II (26% versus 23%).
Biochemical and anthropometric data for carriers and noncarriers of the N9 allele are given for all subjects (pooled regardless of gender or case/control subject status) in Table 2⇓ (EARS-I) and Table 3⇓ (EARS-II). Pooling of the data was justified by the homogeneity of the observed effects of the N9 allele on the variables (data not shown).
In EARS-I, carriers of the N9 allele had statistically significantly higher fasting TG concentrations than noncarriers (Table 2⇑), and a similar trend was found in EARS-II (Table 3⇑), although the difference in TG was smaller and not statistically significant. In EARS-I, HDL-C concentrations were lower in N9 carriers than in noncarriers (P=.05, Table 2⇑). No significant differences in BMI, waist-to-hip ratio, or other biochemical traits were observed between N9 carriers and noncarriers in either the subgroups (data not shown) or pooled groups (Tables 2⇑ and 3⇑) in either of the studies.
Possible interaction between N9 carrier status and BMI, as previously reported,7 was investigated. As shown in Fig 1a⇓, carriers of the N9 allele in EARS-I had a graded increase in plasma TG with increasing BMI. Although N9 carriers in the upper tertile showed a more marked increase in TG concentrations than did noncarriers, the test for interaction between BMI and N9 carrier status on TG was not statistically significant. The EARS-II data showed a similar pattern (data not shown).
N9 allele carriers and noncarriers in EARS-II did not differ in postprandial TG responses after the OFTT (Fig 2a⇓ and 2b⇓) before or after correction for baseline values. There were no differences in glucose or insulin responses after OFTT or OGTT in either cases or control subjects (data not shown).
The overall frequency of the S291 allele was 1.6% and 1.9% in EARS-I (Table 1⇑) and EARS-II (legend to Table 3⇑), respectively. There were no significant differences in allele frequencies between cases and control subjects in either of the studies. One female subject in EARS-I was homozygous for the S291 allele. She had a normal BMI and had lipid and apolipoprotein concentrations within the normal range (data not shown). There was the same proportion of smokers in carriers and noncarriers in both studies (data not shown).
In the pooled data in each of the studies, carriers of the S291 allele had statistically significantly lower HDL-C concentrations than did noncarriers (Tables 2⇑ and 3⇑), and this effect associated with the S291 allele was homogeneous in men and women and cases and control subjects in both populations (data not shown). In EARS-II the HDL-C–lowering effect associated with the S291 allele was stronger in cases than in control subjects. In cases mean HDL-C concentration±SEM was 0.93±0.06 and 1.17±0.02 mmol/L (P=.0001) for carriers and noncarriers, respectively, and in the control group, mean HDL-C concentration±SEM was 1.10±0.07 and 1.16±0.02 mmol/L (P=NS) in carriers and noncarriers, respectively. In the pooled data in each of the studies, carriers of the S291 allele had higher fasting TG concentrations than did noncarriers (Tables 2⇑ and 3⇑), and this effect associated with the S291 allele was homogeneous in men and women and cases and control subjects in both populations (data not shown). However, the differences were not statistically significant. No significant differences in BMI or other biochemical traits were observed between S291 carriers and noncarriers in either the pooled data (Tables 2⇑ and 3⇑) or in subgroups (data not shown) in either of the populations.
Possible interaction between S291 carrier status and BMI as previously reported17 was tested. As shown in Fig 1b⇑, S291 carriers in EARS-I showed a more marked increase in plasma TG with increasing BMI than noncarriers. The EARS-II data showed a similar pattern (data not shown), and the test for interaction between S291 carrier status and BMI on plasma TG concentrations was statistically significant in both studies (P<.01). Moreover, S291 carriers showed a more marked decrease in HDL-C concentrations with increasing BMI than did noncarriers (data not shown).
In the OFTT, plasma TG concentrations in cases were significantly higher in S291 carriers than noncarriers (P<.03) at baseline and 3, 4, and 6 hours (Fig 2⇑). The overall significance of carriers being above noncarriers was P=.007, and the test for parallelism of the two curves was of borderline statistical significance (P=.057). After correction for baseline value, the 6-hour TG concentration remained significantly higher in S291 carriers (P=.04). In control subjects, only baseline TG concentrations were higher in S291 carriers, although they did not reach statistical significance. There were no differences in other postprandial parameters between carriers and noncarriers in either cases or control subjects.
There were no differences in postprandial insulin responses in either cases or control subjects (data not shown) to either the OFTT or OGTT. In cases, S291 carriers had higher glucose at 2 hours after OFTT than noncarriers (data not shown; repeated-measures ANOVA, P=.03), whereas no differences in glucose responses after the OGTT were observed between S291 carriers and noncarriers in the control group (data not shown).
Patients at high risk of developing CHD benefit from lipid-lowering treatment, and early identification is therefore important. If an atherogenic biochemical phenotype is characterized at the DNA level, it is possible to identify cases before their clinical phenotype becomes evident. This approach has been used successfully in FH.18 However, with an occurrence of 0.1% to 0.2% in the general population, FH is a relatively rare disease,18 and variation in other genes involved in lipoprotein metabolism must be considered.19
In general, variations at the DNA level have moderate-to-weak effects on biochemical variables.5 Nevertheless, they may be important for the occurrence of disease at the population level, if they are common.6 This was recently demonstrated in a study showing that the LPL N9 variation was significantly associated with progression of coronary atherosclerosis, despite having only subtle effects on plasma lipids.20 Here, we report on two common mutations (variants) resulting in amino acid changes in the mature LPL protein (ie, N9 and S291) with effects on plasma lipids in two offspring studies, EARS-I and -II.
The N9 mutation was identified in 4.2% of all subjects in EARS-I, confirming that this mutation is common in Western populations.20 21 Carrier frequencies differed markedly between European regions, but the frequency of the N9 allele was not higher in subjects with a paternal history of MI (cases) than in control subjects. This accords with another study in which N9 carrier frequencies were insignificantly higher in myocardial infarction survivors than in control subjects.21 In contrast, Jukema et al20 found that the N9 allele was associated with a family history of CHD.
In accordance with previous studies,7 20 21 carriers of the N9 allele in EARS-I had higher plasma TG and lower HDL-C levels. To a lesser extent, these associations were also present in EARS-II. In vitro studies22 indicate that the N9 mutation reduces hydrolytic activity by reducing the amounts of LPL protein secreted by the cell LPL protein by 15% to 20%. We therefore expected the effects of the N9 mutant on fasting lipids to be evident in an OFTT, but there was no difference in postprandial TG responses between carriers and noncarriers. We propose the following: Inactive intracellular deposits of LPL are activated when TG-rich lipoproteins bind to the luminal surface of the endothelium.23 Before the OFTT, our study subjects had fasted for 14 hours, and maximal LPL deposition had therefore probably occurred. The partial catalytic defect in N9 carriers does not prevent activation of sufficient LPL protein from the intracellular deposits to meet the demand during the OFTT. Instead of a single OFTT, successive OFTTs might have unmasked the moderate decrease in catalytic capacity in N9 carriers.
It has been reported that obesity amplified the effect of the N9 allele on fasting TG concentrations.7 Although we observed the same trend, the effect did not reach statistical significance in these young men and women. It was suggested7 that carriers of the N9 mutation can maintain low plasma TG levels if they are lean, but if the partially impaired LPL function in N9 carriers is additionally strained by the increased VLDL lipoprotein production associated with even moderate obesity,24 the secretion of active LPL protein becomes relatively insufficient and hypertriglyceridemia develops.7 Compared with the subjects studied by Mailly et al,7 mean plasma TG concentrations and BMI ranges were considerably lower in our studies and perhaps within the limits in which N9 carriers can maintain TG homeostasis.
In contrast to N9, the S291 mutant was distributed homogeneously across Europe, with an overall frequency of 3.1% in EARS-I. Again, no differences in carrier frequencies between cases and control subjects were detected, and published case-control studies8 25 have not shown an association between the S291 allele and premature atherosclerosis. These studies did not include deceased cases, however, and offspring studies like the present ones have the power to detect only large effects of fairly common genetic variants on CHD risk12 because the gene pool under investigation is diluted. Currently available data therefore do not rule out an association of the S291 mutant with premature atherosclerosis.
In agreement with one8 but not another25 study, carriers of the S291 allele had significantly lower HDL-C concentrations. In vitro,22 the activity of the S291 mutation is reduced by 30% to 40%. As outlined by Patsch,10 an HDL particle exchanges cholesteryl esters for TG with numerous generations of TG-rich lipoproteins, and HDL can be regarded as “the memory box of TG metabolism.” Given the large intraindividual variability of plasma TG concentrations,26 the relatively low number of S291 carriers, and the low mean TG concentration, it was expected that the S291 mutant was associated with variation in HDL-C but not necessarily with fasting TG concentrations.17 The HDL-C–lowering effect of the S291 allele was more pronounced in cases than control subjects in EARS-II, and S291 carriers in the case group accordingly cleared TG more slowly than did noncarrier cases during the OFTT. This difference was not observed in the control group, suggesting that the S291 mutant interacts with one or more genetic or environmental factors present in cases but not in control subjects. Identification of these factors will be of great importance in better developing predictive tests for individuals at risk of becoming severely hypertriglyceridemic.
Despite the low mean TG concentration and narrow BMI range in these healthy young subjects, carriers of the S291 allele could not maintain low plasma TG with increased body weight. We also found that in S291 carriers, obesity amplified the HDL-C–lowering effect more than in noncarriers. These results are in accordance with the reduced catalytic activities of the two LPL mutant proteins (a 15% to 20% and 30% to 40% reduction for the N9 and S291 mutations, respectively) and in accordance with a previous study.17
The remarkable heterogeneity of the N9 carrier frequencies, ranging from 0.2% in Finnish/Baltic populations to 7.7% in British populations in EARS-I, could explain why we could not fully reproduce the results from EARS-I in EARS-II; the two populations were not from the exact same European regions. Although we controlled for environmental factors and region in the statistical analyses, the heterogeneity of the N9 carrier frequencies makes it possible that other region-specific factors might make the results biased. In contrast, data for the S291 mutant were concurrent in EARS-I and -II.
Other LPL gene mutations delay postprandial TG clearance,27 28 and recently published small studies of heterozygous carriers of the S291 allele showed that these subjects also had delayed postprandial TG clearance.11 29 Carriers of the G188E LPL mutation develop dyslipidemia only after the age of 40 years,30 whereas carriers of the P201L mutation have dyslipidemia at a younger age.31 Our subjects were young (mean age, ≈23 years), and we could not study gene×environment interaction over time. Our results are good estimates of the effects associated with specific genotypes per se, however, and increasing age is unlikely to diminish the effects of these two LPL mutants on plasma lipids. Because even moderate obesity amplified the atherogenic effects of both mutations on plasma lipids, carriers are likely to be at increased risk of CHD if certain other genetic and/or lifestyle factors are present.
Our results confirm that alleles coding for the two LPL mutations N9 and S291 are common in the general population, but they do not show that they are more frequent in subjects with higher a priori risk of CHD. Both mutants are associated with atherogenic changes in plasma TG and HDL-C concentrations in young subjects, and for the S291 mutation, this effect might be mediated by delayed postprandial TG clearance. Even moderate obesity seems to potentiate the effects of the two LPL mutants, making it likely that age aggravates the effects on plasma lipids. Our results suggest that the LPL gene is a strong candidate as a “high TG/low HDL gene.”2 4
Selected Abbreviations and Acronyms
|AUC||=||area under the curve|
|BMI||=||body mass index|
|CHD||=||coronary heart disease|
|EARS||=||European Atherosclerosis Research Study|
|OFTT||=||oral fat tolerance test|
|OGTT||=||oral glucose tolerance test|
The EARS-I project leader was J. Shepherd, Glasgow, UK, and the EARS-II project leader was D.StJ. O’Reilley, Glasgow, UK.
The EARS Group, Collaborating Centers, and Associated Investigators
Austria: H.J. Menzel, C. Sandholzer, C. Duba, H.G. Kraft (Institute for Medical Biology and Genetics, University of Innsbruck); Belgium: G. De Backer, S. De Henauw, D. De Bacquer, A. Bael (Department of Hygiene and Social Medicine, State University of Ghent); M. Rosseneu, N. Vinaimont (Department of Clinical Chemistry, University Hospital St Jan, Brügge); Denmark: C. Gerdes, O. Faergeman, I.C. Klausen, L.U. Gerdes (Department of Medicine and Cardiology, Aarhus Amtssygehus University Hospital); Estonia: M. Saava (Department of Nutrition and Metabolism, Institute of Cardiology, Tallin); Finland: C. Ehnholm (National Public Health Institute, Helsinki); A. Kesaniemi (Department of Internal Medicine, University of Oulu); France: F. Cambien, L. Tiret, R. Agher, V. Nicaud, R. Rakotovao (INSERM U 258, Hôpital Broussais, Paris); M.-M. Galteau, S.M. Visvikis (Centre de Medicine Preventive, Nancy); J.C. Fruchart, J. Dallongeville, J.M. Bard, P. Lebel (INSERM U235, Institut Pasteur, Lille); L. Bara (Laboratories de Trombose Expérimentale, Paris); C. Bady, J. Beylot, A. Lindoulsi (UFR de Sante Publique, Bordeaux); Greece: G. Tsitouris, N. Papageorgakis (Department of Medicine/Cardiology, Evangelismos Hospitals, Athens); Germany: U. Beisiegel, A. Jorge, M. Papanikolaou (Medizinische Klinik, Universitätskrankenhaus, Hamburg); Italy: E. Farinaro (Institute of Internal Medicine and Metabolic Disease, University of Naples); F. De Lorenzo, C. Cortese, M. Ligouri (Community Medicine, Institute of Hygiene and Preventive Medicine, University of Naples); The Netherlands: L.M. Havekes, P. de Knijff (IVVO-TNO Health Research, Gaubius Institute, Leiden); Portugal: M.J. Halpern (Instituto Superior de Ciencias da Saude, Lisbon); Spain: S. Sans, T. Puig, V. Moreno, M. Martin (Programma CRONICAT, Hospital Sant Pau, Barcelona); P.R. Turner, M. Masana, A. Altadill, M. Castro (Unitat Recerca Lipids, University Barcelona, Reus); Switzerland: F. Gutzwiller, B. Martin, M. Knobloch, P. Anliker (Institute of Social and Preventive Medicine, University of Zürich); United Kingdom: D. Stansbie, A. Day, S. Plumridge (Department of Chemical Pathology, Bristol); J. Shepherd, D. St O’Reilly, G.W. Tait, G.M. Hamilton (Institute of Biochemistry, Royal Infirmary, Glasgow); S. Humphries, P. Talmud, S. Ye, R.M. Fisher (University College London, School of Medicine, London); and A. Evans, F. Kee (Department of Epidemiology and Public Health, The Queens University of Belfast).
This work was supported by grants from the Danish Heart Foundation, Kirsten Anthonius’ Mindelegat, British Heart Foundation (grant RG16), and EC Concerted Action MRH-4 COMAC Epidemiology.
↵1 Members of the EARS Group are listed in the “Appendix.”
- Received February 6, 1997.
- Accepted March 2, 1997.
- Copyright © 1997 by American Heart Association
Gordon DJ, Probstfield JL, Garrison RJ, Neaton JD, Castelli WP, Knoke JD, Jacobs DR Jr, Bangdiwala S, Tyroler HA. High-density lipoprotein cholesterol and cardiovascular disease: four prospective American studies. Circulation. 1989;79:8-15.
Sprecher DL, Feigelson HS, Laskazewski PM. The low HDL cholesterol/high triglyceride trait. Arterioscler Thromb. 1993;13:495-504.
Patsch JR, Prasad S, Gotto AM Jr, Patsch W. High density lipoprotein2: relations of the plasma level of this lipoprotein species to its composition, to the magnitude of postprandial lipemia, and to activities of lipoprotein lipase and hepatic lipase. J Clin Invest. 1987;80:341-347.
Sprecher DL, Hein MJ, Laskarzewski PM. Conjoint high triglycerides and low HDL cholesterol across generations. Circulation. 1994;90:1177-1184.
Humphries SE. DNA polymorphisms of the apolipoprotein genes: their use in the investigation of the genetic component of hyper-lipidaemia and atherosclerosis. Atherosclerosis. 1988;72:89-108.
Gerdes C, Gerdes LU, Hansen PS, Faergeman O. Polymorphisms in the lipoprotein lipase gene and their associations with plasma lipid concentrations in 40-year-old Danish men. Circulation. 1995;92:1765-1769.
Mailly F, Tugrul Y, Reymer PWA, Bruin T, Seed M, Groenemeyer BF, Asplund-Carlson A, Vallance D, Winder AF, Miller GJ, Kastelein JJP, Hamsten A, Olivecrona G, Humphries SE, Talmud PJ. A common variant in the gene for lipoprotein lipase (Asp9–Asn). Arterioscler Thromb Vasc Biol. 1995;15:468-478.
Reymer PWA, Gagné E, Groenemeyer BE, Zhang H, Forsyth I, Jansen H, Seidell JC, Kromhout D, Lie KE, Kastelein JJ, Hayden MR. A lipoprotein lipase mutation (Asn291Ser) is associated with reduced HDL cholesterol levels in premature atherosclerosis. Nat Genet. 1995;10:28-34.
Patsch JR, Prasad S, Gotto AM Jr, Bengtsson-Olivecrona G. Postprandial lipemia: a key for the conversion of high density lipoproteins by hepatic lipase. J Clin Invest. 1984;74:2017-2023.
Patsch JR, Miesenböck G, Hopferwieser T, Muhlberger V, Knapp E, Dunn JK, Gotto AM Jr, Patsch W. Relation of triglyceride metabolism and coronary heart disease. Arterioscler Thromb. 1992;12:1336-1345.
Pimstone SN, Clee SM, Gagne SE, Miao L, Zhang HF, Stein EA, Hayden MR. A frequently occurring mutation in the lipoprotein lipase gene (Asn291Ser) results in altered postprandial chylomicron triglyceride and retinyl palmitate response in normolipidemic carriers. J Lipid Res. 1996;37:1675-1684.
Tiret L, Nicaud V, Ehnholm C, Havekes L, Menzel HJ, Ducimetière P, Cambien F. Inference of the strength of genotype-disease association from studies comparing offspring with and without parental history of disease. Ann Hum Genet. 1993;57:141-149.
The EARS Group. The European Atherosclerosis Research Study (EARS): design and objectives. Int J Epidemiol. 1994;23:465-471.
The EARS Group. The distribution of fasting plasma lipid concentrations in the offspring of men with premature coronary heart disease in Europe: the EARS Study. Int J Epidemiol. 1994;23:472-481.
Rosseneu M, Fruchart JC, Bard JM, Nicaud V, Vinaimont N, Cambien F, De Backer G. Plasma apolipoprotein concentrations in young adults with a parental history of premature coronary heart disease and in control subjects: the EARS Study. Circulation. 1994;89:167-173.
Whittall R, Gudnason V, Weavind GP, Day LB, Humphries SE, Day INM. Utilities for high throughput use of the single strand conformational polymorphism method: screening of 791 patients with familial hypercholesterolemia for mutations in exon 3 of the low density lipoprotein receptor gene. J Med Genet. 1995;32:509-515.
Fisher RM, Mailly F, Peacock RE, Hamsten A, Seed M, Yudkin JS, Beisiegel U, Feussner G, Miller G, Humphries SE, Talmud PJ. Interaction of the lipoprotein lipase asparagine 291–serine mutation with body mass index determines elevated plasma triacylglycerol concentrations: a study in hyperlipidemic subjects, myocardial infarction survivors, and healthy adults. J Lipid Res. 1995;36:2104-2112.
Packard CJ, Shepherd J. Current concepts in the treatment of familial hypercholesterolaemia. Curr Opin Lipidol. 1995;6:57-61.
Humphries SE. Life style, genetic factors and the risk of heart attack: the apolipoprotein B gene as an example. Biochem Soc Trans. 1993;21:569-582.
Jukema JW, Vanboven AJ, Groenemeijer B, Zwinderman AH, Reiber JHC, Bruschke AVG, Henneman JA, Molhoek GP, Bruin T, Jansen H, Gagne E, Hayden MR, Kastelein JJP. The Asp(9)Asn mutation in the lipoprotein lipase gene is associated with increased progression of coronary atherosclerosis. Circulation. 1996;94:1913-1918.
Mailly F, Fisher RM, Nicaud V, Luong L-A, Evans AE, Marques-Vidal P, Luc G, Arveiler D, Bard JM, Poirier O, Talmud PJ, Humphries SE. Association between the LPL-D9N mutation in the lipoprotein lipase gene and plasma lipid traits in myocardial infarction survivors from the ECTIM study. Atherosclerosis. 1996;122:21-28.
Zhang H, Henderson H, Gagne SE, Clee SM, Miao L, Liu G, Hayden MR. Common sequence variants of lipoprotein lipase: standardized studies of in vitro expression and catalytic function. Biochim Biophys Acta. 1996;130:159-166.
Ailhaud G. Cellular and secreted lipoprotein lipase revisited. Clin Biochem. 1990;23:343-347.
Laskarzewski PM, Morrison JA, Mellies MJ, Kelly K, Gartside PS, Khoury P, Glueck CJ. Relationships of measurements of body mass to plasma lipoproteins in school children and adults. Am J Epidemiol. 1980;111:395-407.
Jemaa R, Fumeron F, Poirer O, Lecerf L, Evans A, Arveiler D, Luc G, Cambou J-P, Bard J-M, Fruchart JC, Apfelbaum M, Cambien F, Tiret L. Lipoprotein lipase gene polymorphisms: associations with myocardial infarction and lipoprotein levels, the ECTIM study. J Lipid Res. 1995;36:2141-2146.
Patsch JR, Karlin JB, Scott LW, Smith LC, Gotto AM Jr. Inverse relationship between blood levels of high density lipoprotein subfraction 2 and magnitude of postprandial lipemia. Proc Natl Acad Sci U S A. 1983;80:1449-1453.
Sprecher DL, Knauer SL, Black DM, Kaplan LA, Akeson AA, Dusing M, Lattier D, Stein EA, Rymaszewski M, Wiginton DA. Chylomicron-retinyl palmitate clearance in type I hyperlipidemic families. J Clin Invest. 1991;88:985-994.
Miesenböck G, Holzl B, Foger B, Brandstatter E, Paulweber B, Sandhofer F, Patsch JR. Heterozygous lipoprotein lipase deficiency due to a missense mutation as the cause of impaired triglyceride tolerance with multiple lipoprotein abnormalities. J Clin Invest. 1993;91:448-455.
Humphries S, Fisher R, Mailly F, Peacock R, Talmud P, Karpe F, Hamsten A, Miller GJ. Gene-environment interaction in determining plasma lipids and dietary response: the effects of common mutations in the gene for lipoprotein lipase (D9N and N291S). In: Bray GA, Ryan DH, eds. Pennington Center Nutrition Series: Vol 6. Nutrition, Genetics and Heart Disease. Baton Rouge, La/London, UK: Louisiana State University Press; 1996:279-295.
Wilson DE, Emi M, Iverius PH, Hata A, Wu LL, Hillas E, Williams RR, Lalouel JM. Phenotypic expression of heterozygous lipoprotein lipase deficiency in the extended pedigree of a proband homozygous for a missense mutation. J Clin Invest. 1990;86:735-750.
Bijvoet S, Gagne SE, Moorjani S, Gagne C, Henderson HE, Fruchart JC, Dallongeville J, Alaupovic P, Prins M, Kastelein JJP, Hayden MR. Alterations in plasma lipoproteins and apolipoproteins before the age of 40 in heterozygotes for lipoprotein lipase deficiency. J Lipid Res. 1996;37:640-650.