Lp Variance Research Articles

Using Media to Influence Consumer Attitudes to Domestic Goods in Vietnam by Framing Public Interest: A Media Framing Effect Analysis

Recent research shows the importance of purchasing local products for development the local and national economy. In developing countries, consumption of domestic products is a rapidly growing trend as it contributes to the development of brands and images of local companies. Faced with a foreign product preference in Vietnam, the Vietnamese government has organized a campaign entitled “Vietnamese people prioritizing Vietnamese products” in which local companies are encouraged to enhance their product quality, and consumers are encouraged to buy locally manufactured products. This study seeks to investigate how the Vietnamese government has shaped consumer behavior for domestic goods by framing public interest in the campaign. An analysis of 274 news articles in popular newspapers showed four main frames: campaign’s policy framing (CP), benefit of using Vietnamese goods (VG), advanced role models (RM), and criticizing foreign product preference (CF). A survey with 526 Vietnamese consumers indicated that four frames significantly predicted consumer attitudes. Results of the linear regression model were significant, the R-squared ( R2) value was .25, indicating that approximately 25% of the variance in LP was explained by CP, VG, CF, and RM. RM, VG, and CP significantly predicted LP, but CF did not significantly predict LP. The findings suggest that further studies test the framing theory by using media coverage as a secondary source.

Genetic and Mechanistic Insights into the Modulation of Circulating Lipoprotein (a) Concentration by Apolipoprotein E Isoforms.

Lipoprotein (a) [Lp(a)] is a highly atherogenic lipoprotein species. A unique feature of Lp(a) is the strong genetic determination of its concentration. The LPA gene is responsible for up to 90% of the variance in Lp(a), but other genes also have an impact. Genome-wide associations studies indicate that the APOE gene, encoding apolipoprotein E (apoE), is the second most important locus modulating Lp(a) concentrations. Population studies clearly show that carriers of the apoE2 variant (ε2) display reduced Lp(a) levels, the lowest concentrations being observed in ε2/ε2 homozygotes. This genotype can lead predisposed adults to develop dysbetalipoproteinemia, a lipid disorder characterized by sharp elevations in cholesterol and triglycerides. However, dysbetalipoproteinemia does not significantly modulate circulating Lp(a). Mechanistically, apoE appears to impair the production but not the catabolism of Lp(a). These observations underline the complexity of Lp(a) metabolism and provide key insights into the pathways governing Lp(a) synthesis and secretion.

Variación temporal y espacial de la calidad de las aguas superficiales en la subcuenca del río Virilla (Costa Rica) entre 2006 y 2010

In this work, we considered data of 25 water quality variables collected between January 2006 to December 2010 at 64 monitoring sites along the Virilla River Subbasin in Costa Rica. Factor analysis identified two potential pollution sources that explained 80.9% of the total variance in LP, two potential pollution sources that explained 77.1% of the total variance in MP, and two potential pollution sources that explained 67.8% of the total variance in HP. Most water quality variables were influenced primarily by pollution due to industrial wastewater, agricultural activities and urban runoff.

Expectation Values and Variance Based on Lp-Norms

This analysis introduces a generalization of the basic statistical concepts of expectation values and variance for non-Euclidean metrics induced by Lp-norms. The non-Euclidean Lp means are defined by exploiting the fundamental property of minimizing the Lp deviations that compose the Lp variance. These Lp expectation values embody a generic formal scheme of means characterization. Having the p-norm as a free parameter, both the Lp-normed expectation values and their variance are flexible to analyze new phenomena that cannot be described under the notions of classical statistics based on Euclidean norms. The new statistical approach provides insights into regression theory and Statistical Physics. Several illuminating examples are examined.

Genetic Variation in LPAL2 , LPA , and PLG Predicts Plasma Lipoprotein(a) Level and Carotid Artery Disease Risk

lipoprotein(a) [Lp(a)] level is an established risk factor for coronary artery disease and has been implicated in carotid artery disease (CAAD). The relationship between genetic variation in the LPA gene region and CAAD risk remains unknown. we genotyped single nucleotide polymorphisms (SNPs) in the LPAL2, LPA, and PLG regions in 530 individuals with severe CAAD and 770 controls and kringle IV type 2 (KIV2) repeat length in a subset of 90 individuals. nine SNPs collectively accounted for 30% of the variance in Lp(a) level. Six SNPs were associated with Lp(a) level after accounting for KIV2 copy number, and the dominant KIV2 allele combined with these markers explained 60% of the variance in Lp(a) level. Five SNPs, including rs10455872, which had an odds ratio of 2.1 per minor allele and haplotypes formed by rs10455872, rs6919346, and rs3123629, were significant predictors of CAAD. After accounting for Lp(a) level, all evidence of CAAD-genotype association in the LPA region was eliminated. LPA region SNPs capture some but not all of the effect of KIV2 repeat length on Lp(a) level. There are associations between LPA region SNPs and CAAD that appear to be attributable to effects on Lp(a) level.

Spatial variation and source apportionment of water pollution in Qiantang River (China) using statistical techniques

Understanding the spatial distribution and apportioning the sources of water pollution are important in the study and efficient management of water resources. In this work, we considered data for 13 water quality variables collected during the year 2004 at 46 monitoring sites along the Qiantang River (China). Fuzzy comprehensive analysis categorized the data into three major pollution zones (low, moderate, and high) based on national quality standards for surface waters, China. Most sites classified as “low pollution zones” (LP) occurred in the main river channel, whereas those classified as “moderate and high pollution zones” (MP and HP, respectively) occurred in the tributaries. Factor analysis identified two potential pollution sources that explained 67% of the total variance in LP, two potential pollution sources that explained 73% of the total variance in MP, and three potential pollution sources that explained 80% of the total variance in HP. UNMIX was used to estimate contributions from identified pollution sources to each water quality variable and each monitoring site. Most water quality variables were influenced primarily by pollution due to industrial wastewater, agricultural activities and urban runoff. In LP, non-point source pollution such as agricultural runoff and urban runoff dominated; in MP and HP, mixed source pollution dominated. The pollution in the small tributaries was more serious than that in the main channel. These results provide information for developing better pollution control strategies for the Qiantang River.

LPA and PLG Sequence Variation and Kringle IV-2 Copy Number in Two Populations

Background/Aims: Lp(a) levels have long been recognized as a potential risk factor for coronary heart disease that is almost completely under genetic control. Much of the genetics impacting Lp(a) levels has been attributed to the highly polymorphic LPA kringle IV-2 copy number variant, and most of the variance in Lp(a) levels in populations of European-descent is inversely correlated with kringle IV copy number. However, less of the variance is explained in African-descent populations for the same structural variation. African-descent populations have, on average, higher levels of Lp(a), suggesting other genetic factors contribute to Lp(a) level variability across populations. Methods: To identify potential cis-acting factors, we re-sequenced the gene LPA for single nucleotide polymorphism (SNP) discovery in 23 European-Americans and 24 African-Americans. We also re- sequenced the neighboring gene plasminogen (PLG) and genotyped the kringle IV copy number variant in the same reference samples. Results: These data are the most comprehensive description of sequence variation in LPA and its relationship with the kringle IV copy number variant. With these data, we demonstrate that only a fraction of LPA sequence diversity has been previously documented. Also, we identify several high frequency SNPs present in the African-American sample but absent in the European-American sample. Finally, we show that SNPs within PLG are not in linkage disequilibrium with SNPs in LPA, and we show that kringle IV copy number variation is not in linkage disequilibrium with either LPA or PLG SNPs. Conclusions: Together, these data suggest that LPA SNPs could independently contribute to Lp(a) levels in the general population.

Factors contributing to variation in lipoprotein (a) in Melbourne Anglo-Celtic population.

The purpose of this report is to survey the factors contributing to variation in lipoprotein(a) (Lp(a)) in a population-based sample of Anglo-Celtic Melburnians. The plasma Lp(a) levels were highly skewed towards low levels in this population, with a median of 156 mg/l and a mean of 262 mg/l. Approximately 33% had plasma Lp(a) above the threshold value of 300 mg/l, while 35% had Lp(a) levels below 100 mg/l. The most commonly occurring phenotype was apo(a) S3. In this phenotype, Lp(a) concentrations ranged from 10 to 596 mg/l. Lp(a) was consistently associated with diastolic blood pressure, systolic blood pressure, total protein, albumin and nitrogen excretion in the 40-60 y age group. Multiple stepwise regression analyses, in non-dietary factors, were used to explain about 13% of the variance in Lp(a) (19% in men and 23% in women). Remarkably, in the <40 y age group, non-dietary factors may account for 86% of the variance in Lp(a) and dietary factors, analysed separately, 46%. Thus, although Lp(a) is mainly genetically determined, there are clearly other factors which contribute to variations in Lp(a) concentrations.

The effect of apolipoprotein(a)-, apolipoprotein E-, and apolipoprotein A4- polymorphisms on quantitative lipoprotein(a) concentrations.

The effects of apolipoprotein (a), apolipoprotein-E, and apolipoprotein-A4 isoforms on quantitative lipoprotein(a) [Lp(a)] levels were assessed in a sample of 142 Dutch families consisting of two parents and their adolescent twin offspring. A total heritability of 95% was estimated for plasma Lp(a) concentrations. The largest part of this heritability was due to the apo(a) locus which explained 61% of the total variance in Lp(a) levels. The pattern of familial correlations for the residual part of the Lp(a) variance that could not be attributed to the apo(a) isoforms, suggested genetic influences on the residual variance. We addressed the question whether this residual genetic variance could be ascribed to the apoE or the apoA4 locus. A simultaneous analysis of all three loci showed that both the apoE and the apoA4 polymorphism did not contribute significantly to Lp(a) variation.

The effect of apolipoprotein(a)-, apolipoprotein E-, and apolipoprotein A4- polymorphisms on quantitative lipoprotein(a) concentrations

AbstractThe effects of apolipoprotein (a), apolipoprotein-E, and apolipoprotein-A4 isoforms on quantitative lipoprotein(a) [Lp(a)] levels were assessed in a sample of 142 Dutch families consisting of two parents and their adolescent twin offspring. A total heritability of 95% was estimated for plasma Lp(a) concentrations. The largest part of this heritability was due to the apo(a) locus which explained 61% of the total variance in Lp(a) levels. The pattern of familial correlations for the residual part of the Lp(a) variance that could not be attributed to the apo(a) isoforms, suggested genetic influences on the residual variance. We addressed the question whether this residual genetic variance could be ascribed to the apoE or the apoA4 locus. A simultaneous analysis of all three loci showed that both the apoE and the apoA4 polymorphism did not contribute significantly to Lp(a) variation. Twin Research (2000) 3, 152–158.

LPA gene: interaction between the apolipoprotein(a) size ('kringle IV' repeat) polymorphism and a pentanucleotide repeat polymorphism influences Lp(a) lipoprotein level.

In order to search for factors influencing the Lp(a) lipoprotein level, we have examined the apolipoprotein(a) (apo(a)) size polymorphism as well as a pentanucleotide (TTTTA) repeat polymorphism in the 5' control region of the LPA gene. Lp(a) lipoprotein levels were compared between individuals with different genotypes as defined by pulsed field gel electrophoresis of DNA plugs, and PCR of DNA samples followed by polyacrylamide gel electrophoresis. DNA plugs and DNA were prepared from blood samples collected from blood donors. Twenty-seven different K IV repeat alleles were observed in the 71 women and 92 men from which apo(a) size polymorphism results were obtained. Alleles encoding 26-32 Kringle IV repeats were the most frequent. Alleles encoding seven to 11 TTTTA repeats were detected in the 84 women and 122 men included in the pentanucleotide polymorphism study, and homozygosity for eight TTTTA repeats was the most common genotype. The eight TTTTA repeat allele occurred with almost any apo(a) allele. An inverse relationship between number of K IV repeats and Lp(a) concentration was confirmed. The contributions of the apo(a) size polymorphism and the pentanucleotide repeat polymorphism to the interindividual variance of Lp(a) lipoprotein concentrations were 9.7 and 3.5%, respectively (type IV sum of squares). Nineteen per cent of the variance in Lp(a) lipoprotein level appeared to be the result of the multiplication product (interaction) between the apo(a) size polymorphism and the pentanucleotide repeat polymorphism. The contribution of the apo(a) size polymorphism alone to the variation in Lp(a) lipoprotein level was lower than previously reported. However, the multiplicative interaction effect between the K IV repeat polymorphism and the pentanucleotide repeat polymorphism may be an important factor explaining the variation in Lp(a) lipoprotein levels among the populations.

Evidence that multiple genes influence baseline concentrations and diet response of Lp(a) in baboons.

We investigated the response of lipoprotein(a) [Lp(a)] levels to dietary fat and cholesterol in 633 baboons fed a series of 3 diets: a basal diet low in cholesterol and fat, a high-fat diet, and a diet high in fat and cholesterol. Measurement of serum concentrations in samples taken while the baboons were sequentially fed the 3 diets allowed us to analyze 3 Lp(a) variables: Lp(a)(Basal), Lp(a)(RF) (response to increased dietary fat), and Lp(a)(RC) (response to increased dietary cholesterol in the high-fat environment). On average, Lp(a) concentrations significantly increased 6% and 28%, respectively, when dietary fat and cholesterol were increased (P<0.001). As expected, most of the variation in Lp(a)(Basal) was influenced by genes (h(2)=0.881). However, less than half of the variation in Lp(a)(RC) was influenced by genes (h(2)=0.347, P<0. 0001), whereas the increase due to dietary fat alone was not significantly heritable (h(2)=0.043, P=0.28). To determine whether Lp(a) phenotypic variation was due to variation in LPA, the locus encoding the apolipoprotein(a) [apo(a)] protein, we conducted linkage analyses by using LPA genotypes inferred from the apo(a) isoform phenotypes. All of the genetic variance in Lp(a)(Basal) concentration was linked to the LPA locus (log of the odds [LOD] score was 30.5). In contrast, linkage analyses revealed that genetic variance in Lp(a)(RC) was not linked to the LPA locus (LOD score was 0.036, P>0.5). To begin identifying the non-LPA genes that influence the Lp(a) response to dietary cholesterol, we tested, in bivariate quantitative genetic analyses, for correlation with low density lipoprotein cholesterol [LDLC; ie, non-high density lipoprotein cholesterol less the cholesterol contribution from Lp(a)]. LDLC(Basal) was weakly correlated with Lp(a)(Basal) (rho(P)=0.018). However, LDLC(RC) and Lp(a)(RC) were strongly correlated (rho(P)=0. 382), and partitioning the correlations revealed significant genetic and environmental correlations (rho(G)=0.587 and rho(E)=0.251, respectively). The results suggest that increasing both dietary fat and dietary cholesterol caused significant increases in Lp(a) concentrations and that the response to dietary cholesterol was mediated by a gene or suite of genes that appears to exert pleiotropic effects on LDLC levels as well. The gene(s) influencing Lp(a) response to dietary cholesterol is not linked to the LPA locus.

Sequence polymorphisms in the apolipoprotein(a) gene and their association with lipoprotein(a) levels and myocardial infarction. The ECTIM Study

Lp(a) concentrations are largely determined by apo(a) isoform size, but several studies have shown that apo(a) isoforms could not entirely explain the increase of Lp(a) levels observed in patients with coronary heart disease (CHD). Since up to 90% of the variance in Lp(a) levels has been suggested to be attributable to the apo(a) locus, the hypothesis that polymorphisms of the apo(a) gene other than size could contribute to the increase of Lp(a) levels in CHD patients must be considered. This hypothesis was tested in the ECTIM Study comparing 594 patients with myocardial infarction and 682 control subjects in Northern Ireland and France. In addition to apo(a) phenotyping, five previously described polymorphisms of the apo(a) gene were genotyped: a (TTTTA) n repeat at position −1400 from the ATG, a G/A at −914, a C/T at −49, a G/A at −21 and a Met/Thr affecting amino acid 4168. As reported earlier [Parra HJ, Evans AE, Cambou JP, Amouyel P, Bingham A, McMaster D, Schaffer P, Douste-Blazy P, Luc G, Richard JL, Ducimetiere P, Fruchart JC, Cambien F. A case-control study of lipoprotein particles in two populations at contrasting risk for coronary heart disease. The ECTIM study. Arterioscler Thromb 1992;12:701–707], mean Lp(a) levels were higher in cases than in controls (20.7 vs 14.6 mg/dl in Belfast, 17.2 vs 8.9 mg/dl in France, P<0.001 for case-control and population differences). In the present study, mean apo(a) isoform size differed significantly between cases and controls (25.7 vs 26.6 kr in Belfast, 25.9 vs 27.4 kr in France, P<0.001 for case-control and P=0.13 for population difference). After adjustment for apo(a) isoforms, Lp(a) levels remained significantly higher in cases than in controls (difference, 4.6 mg/dl; P<0.001). Genotype and allele frequencies did not differ significantly between cases and controls for any of the five polymorphisms studied. The five polymorphisms were in strong linkage disequilibrium and had a combined heterozygosity of 0.83. In multivariate regression analysis adjusted for apo(a) isoforms, only the (TTTTA) n polymorphism was significantly associated with Lp(a) levels; it explained 4.5% of Lp(a) variability in cases and 3.1% in controls. The Lp(a) case/control difference was not reduced after taking into account the (TTTTA) n effect. We conclude that the increase of Lp(a) levels observed in MI cases, and which was not directly attributable to apo(a) size variation, was not related to the five polymorphisms of the apo(a) gene considered.

Growth hormone increases and insulin-like growth factor-I decreases circulating lipoprotein(a)

Elevated serum lipoprotein(a) (Lp(a)) is a strong risk factor for coronary artery disease (CAD). Genetic factors appear to account for the major variance in Lp(a) levels but the contribution hormones make in modulating Lp(a) levels is not yet clear. In the present investigation we determined the effects of human growth hormone (hGH) and insulin-like growth factor-I (IGF-I) on circulating Lp(a). Four groups of patients were studied. Group a: adults with GH deficiency (n = 7) treated with hGH (0.05 U/kg/day, s.c.); group b: girls with Turner syndrome (n = 7) treated with hGH (0.1 U/kg/day, s.c.); group c: prepubertal boys with idiopathic short stature (n = 6) treated with the GH secretagogue (GHRP) hexarelin (60 micrograms t.i.d. intranasally); group d: Laron syndrome patients (n = 10) treated with IGF-I (100-200 micrograms/kg/day, s.c.). Following overnight fasting, serum was sampled before the initiation of treatment and during 6-9 months treatment. Serum IGF-I rose significantly in all the subjects in all four groups. In the first three groups in which IGF-I was elevated by exogenous or endogenous GH stimulation, serum Lp(a) increased significantly (119 +/- 35%, P < 0.01; 126 +/- 44%, P < 0.05; 102 +/- 29%, P < 0.01 for groups a, b, and c respectively). By contrast, serum Lp(a) levels decreased in group d to whom exogenous IGF-I was administered (-66 +/- 5%, P < 0.001). The differential effect of endogenous vs exogenous IGF-I on serum Lp(a) paralleled the behaviour of serum insulin. Insulin was significantly increased in all the subjects receiving hGH or GHRP (65.2 +/- 31%, P = 0.109; 93.7 +/- 53%, P = 0.062; 353.8 +/- 52.7%, P < 0.01 for groups a, b, and c respectively) whereas insulin levels were reduced following exogenous administration of IGF-I (-34.1 +/- 9.1%, P < 0.01). We conclude that long-term GH treatment increases and IGF-I decreases circulating levels of Lp(a). These findings may have clinical relevance in view of the increasing use of hGH in children and adults and the role of Lp(a) as a CAD risk factor.

Concentrations of Lp(a) in black and white young adults: Relations to risk factors for cardiovascular disease

The purpose of this report is to compare the distribution of total lipoprotein(a) [Lp(a)] mass in a population-based sample of blacks and whites, and to investigate the association of Lp(a) with other cardiovascular risk factors. A cross-sectional study design was used. Black and white men and women (n = 4125), aged 23-35 from the Coronary Artery Risk Development in Young Adults Study had the following data collected: Lp(a), lipids and lipoproteins, other metabolic parameters, anthropometry, physical activity, dietary intake, cigarette use, and alcohol use. Blacks had concentrations of Lp(a) approximately three-fold higher than whites. Medians were: black men 21.5 mg/dL, black women 23.9 mg/dL, white men 6.1 mg/dL, and white women 6.4 mg/dL. Lp(a) concentrations were higher in women than in men. Lp(a) was not consistently associated with smoking, alcohol consumption, physical activity, dietary fat, or obesity. In stepwise regression analyses in both blacks and whites, Lp(a) was consistently associated with low-density lipoprotein (LDL) cholesterol, fibrinogen, and apoB; regression models explained about 7% of the variance in Lp(a). In whites, Lp(a) tended to be higher in those with a positive family history of myocardial infarction. The large differences in Lp(a) between blacks and whites, and the absence of association with many other variables are consistent with previous suggestions that Lp(a) concentration is in large part genetically determined. The association of Lp(a) with LDL and fibrinogen, two strong risk factors for cardiovascular disease (CVD), could represent part of the mechanism of the CVD risk associated with Lp(a) in other studies. Longitudinal data are needed to determine the extent to which Lp(a) will independently predict disease, especially in diverse ethnic groups.

Lipoprotein(a): relation to other risk factors and genetic heritability. Results from a Dutch parent-twin study

We measured plasma levels of lipoprotein(a) (Lp(a)) in a sample of 152 Dutch adolescent mono- and dizygotic twin pairs and their parents. The distribution of Lp(a) levels was skewed, with the highest frequencies at low levels and was similar for adult men and women and their children. The relationship of Lp(a) concentrations with other lipoprotein and apolipoprotein risk factors for coronary heart disease and with lathosterol, an indicator of whole-body cholesterol synthesis, was studied dependent on sex and generation. In mothers and children there was a small positive correlation between Lp(a) levels and plasma cholesterol and apolipoprotein (apo) B. In mothers and daughters there also was a correlation between Lp(a)and LDL cholesterol levels. No correlation was found between Lp(a) levels and plasma lathosterol, suggesting that there is no relationship between Lp(a) levels and cholesterol synthesis. Associations among family members, i.e. between monozygotic and dizygotic twins and between parents and offspring were used to study familial transmission of Lp(a) levels. Results showed that almost all of the variance in Lp(a) concentrations was accounted for by genetic heritability. A small, but significant, sex difference in heritability was observed, but heritabilities were the same in parents and offspring. Heritability estimates were 93% for females and 98% for males. No evidence was found for assortative mating or for the influence of a shared family environment. These results indicate that nearly all variance in Lp(a) concentrations that is not accounted for by the apo(a) size polymorphism, is also under genetic control.

Influence of variety, row type and time of sowing on the morphology, chemical composition and in vitro digestibility of barley straw

SUMMARYLeaf proportions (LP) were determined in spring barley straws harvested at Cambridge in 1984 and 1985. Linear regression equations showed that a greater number of days to flowering increased LP whilst greater plant height decreased LP in spring barley straws. Plant height accounted for more than 70% of the variance in LP. By contrast, grain yield and stem diameter accounted for only a small percentage of the variance in LP. Straws from two-rowed winter barleys had slightly higher LP than six-rowed winter barleys but LP in winter and spring barleys were similar.Leaf blade and leaf sheath fractions of the straws had lower acid detergent fibre and lignin contents and were more digestible than the stem fractions. Linear regression equations of straw digestibility in spring barleys on LP, grain yields, days to flowering and plant heights showed that LP accounted for a higher percentage of the variance in digestibility in 1984 than the other characteristics. In 1985, when harvesting conditions were unusually wet, grain yield accounted for the highest percentage of the variance in straw digestibility.There were no differences in chemical composition and straw digestibility between two-rowed and six-rowed barleys, but winter barleys had higher straw digestibility than spring barleys. Date of sowing did not influence straw quality in two-rowed winter barleys.The ranking of two-rowed spring barleys for LP, chemical composition and digestibility suggested that varieties with consistently better straw quality could be identified.