Familial Combined Hyperlipidemia: metabolic features and new diagnostic criteria.

Contains fulltext : 59038.pdf (publisher's version ) (Open Access)Familial Combined Hyperlipidemia (FCH) is the most common inherited hyperlipidemia in humans with an increased risk of cardiovascular disease (CVD). Therefore, it is of great importance to identify and treat subjects with FCH appropriately. The exact pathophysiology of FCH is still unknown, also the genetic basis for FCH has remained obscure. The search for metabolic and genetic origin of this lipid disorder has some fundamental problems. Not all research groups use the same criteria to establish the diagnosis FCH, and the lipid phenotype can vary substantially within any individual. The main aim of this thesis was to evaluate this intra-individual variation in lipid phenotype over a period of 5 year and to come to more consistent and unequivocal diagnostic criteria for FCH which can be used in clinical practice. The diagnosis FCH based on plasma total cholesterol and triglycerides, both adjusted for age and gender was consistent in only 74% of the subjects over a 5-year period. It appeared that the combination of absolute apoB level, triglyceride concentration and total cholesterol concentration, both adjusted for age and gender most adequately predict FCH. To facilitate the implementation of these new diagnostic criteria in clinical practice we developed a nomogram to simply and accurately diagnose FCH. Furthermore, we investigated the contribution of other metabolic parameters and factors (like homocysteine, insulin resistance and leptin) in relation to FCH phenotype and the increased risk of CVD and presented a review about the pathogenesis of FCH with emphasis on the role of insulin resistance, adipose tissue metabolism and fatty acids.KUN Katholieke Universiteit Nijmegen, 8 december 2004Promotor : Stalenhoef, A.F.H. Co-promotor : Graaf, J. de165 p

A patient with swollen ears and ECG abnormalities.

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Nomogram to diagnose familial combined hyperlipidemia on the basis of results of a 5-year follow-up study.

Contains fulltext : 58813.pdf (publisher's version ) (Open Access)BACKGROUND: Familial combined hyperlipidemia (FCH) is traditionally diagnosed by total plasma cholesterol and/or triglyceride levels above the 90th percentile adjusted for age and gender. In a recent study, we showed that the diagnosis of FCH on the basis of these diagnostic criteria was inconsistent in 26% of the subjects over a 5-year period. This result emphasizes the need for reevaluation of the diagnostic criteria for FCH. METHODS AND RESULTS: A total of 32 families (299 subjects) were studied in 1994 and 1999. A subject was defined "truly" FCH when diagnosed FCH in 1994 and/or 1999 on the basis of traditional plasma lipid criteria. Additional lipid and lipoprotein parameters, including apolipoprotein B (apoB) and small, dense LDL, were measured at both time points. In total, 121 subjects (40%) were defined as truly FCH. Multivariate analysis revealed that absolute apoB values combined with triglyceride and total cholesterol levels adjusted for age and gender best predicted truly FCH. A nomogram including these parameters is provided to simply and accurately calculate the probability to be affected by FCH. Furthermore, it is shown that when percentiles of triglyceride and total cholesterol adjusted for age and gender are not available in a population, the definition of FCH can be established on the basis of hypertriglyceridemia (>1.5 mmol/L) and hyper-apoB (>1200 mg/L). CONCLUSIONS: The diagnosis of FCH is best predicted by absolute apoB levels combined with triglyceride and total cholesterol levels adjusted for age and gender and can accurately be calculated by a nomogram. This definition is also a good predictor of cardiovascular risk in FCH

Histochemical localization of heart-type fatty-acid binding protein in human and murine tissues

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Kengetal voor energiebalans

Op ID-DLO ging men op zoek naar een andere methode om de energiebalans in een kengetal te vatten: de verandering in het vetpercentage tijdens het begin van de lactatie blijkt een goede graadmeter. Een sterke daling van het vetgehalte duidt op een negatieve energiebalan

Role of insulin resistance in familial combined hyperlipidemia.

Contains fulltext : 48514.pdf (publisher's version ) (Closed access)OBJECTIVE: Insulin resistance is associated with increased triglyceride levels, low high-density lipoprotein cholesterol, small dense low-density lipoprotein (LDL), and increased apolipoprotein B (apoB) levels, all characteristics of familial combined hyperlipidemia (FCH). Therefore, we explored the role of insulin resistance in FCH lipid phenotype expression. METHODS AND RESULTS: FCH was defined by traditional diagnostic criteria including plasma total cholesterol or triglyceride levels >90th percentile. Insulin resistance was assessed by the Homeostasis Model Assessment (HOMA) index. In total, 132 subjects with FCH, 350 normolipidemic relatives, and 81 spouses who referenced as controls were studied. FCH subjects were significantly more insulin resistant compared with controls and normolipidemic relatives (HOMA index 2.9 [95% CI, 2.6 to 3.2], 2.2 [95% CI, 2.0 to 2.5], and 2.0 [95% CI, 1.9 to 2.2], respectively), even after correction for sex, age, and body mass index (BMI). The degree of insulin resistance was associated with the lipid phenotype expression, and a change in insulin-resistant state was associated with a change in lipid phenotype expression over 5 years. For any level of insulin resistance and degree of obesity, FCH subjects had increased levels of apoB and more small dense LDL compared with controls. CONCLUSIONS: Insulin resistance is a characteristic feature of FCH, which is not fully explained by their increased BMI and is associated with (change in) lipid phenotype expression. Furthermore, our results support the concept of genetic origin of high apoB and small dense LDL in FCH, which is modulated by insulin resistance and obesity

Estimation of genetic parameters for milk fat depression in dairy cattle

The objective of this study was to apply reaction norm models to milk recording data to investigate genetic variation in and environmental sensitivity of susceptibility to milk fat depression (MFD). Data comprised 556,276 test-day records of 80,493 heifers in 1043 herds. Breeding values and genetic variances for fat percentage and fat yield were estimated by applying random regression models to average herd-test-day fat percentage. Genetic and permanent environmental correlations between fat yield expressed in different environments ranged, respectively, from 0.83 to 1.00 and from 0.29 to 1.00. Genetic and permanent environmental correlations between fat percentage expressed in different environments ranged, respectively, from 0.87 to 1.00 and from ¿0.05 to 0.99. Two traits were defined for MFD. The first trait reflected variation of milk fat percentage of animals within lactation after correction for year-season, herd-test-day, age-at-calving, and stage-of-lactation. This trait had an estimated heritability of about 5% and a genetic correlation between the fifth and 95th percentile of the data of 0.50. The second trait reflected the deviation of an animal¿s fat percentage on a test-day from its expected fat percentage based on fat percentage on the first test-day. This trait had an estimated heritability of about 4% and a genetic correlation between the fifth and 95th percentile of the data of 0.43. The correlation between estimated breeding values of sires for the 2 MFD traits was ¿0.3. Our results suggest that genetic variation in susceptibility to MFD is present and that selection for reduced susceptibility to MFD is possibl

Predicted accuracy of and response to genomic selection for new traits in dairy cattle

Genomic selection relaxes the requirement of traditional selection tools to have phenotypic measurements on close relatives of all selection candidates. This opens up possibilities to select for traits that are difficult or expensive to measure. The objectives of this paper were to predict accuracy of and response to genomic selection for a new trait, considering that only a cow reference population of moderate size was available for the new trait, and that selection simultaneously targeted an index and this new trait. Accuracy for and response to selection were deterministically evaluated for three different breeding goals. Single trait selection for the new trait based only on a limited cow reference population of up to 10 000 cows, showed that maximum genetic responses of 0.20 and 0.28 genetic standard deviation (s.d.) per year can be achieved for traits with a heritability of 0.05 and 0.30, respectively. Adding information from the index based on a reference population of 5000 bulls, and assuming a genetic correlation of 0.5, increased genetic response for both heritability levels by up to 0.14 genetic s.d. per year. The scenario with simultaneous selection for the new trait and the index, yielded a substantially lower response for the new trait, especially when the genetic correlation with the index was negative. Despite the lower response for the index, whenever the new trait had considerable economic value, including the cow reference population considerably improved the genetic response for the new trait. For scenarios with a zero or negative genetic correlation with the index and equal economic value for the index and the new trait, a reference population of 2000 cows increased genetic response for the new trait with at least 0.10 and 0.20 genetic s.d. per year, for heritability levels of 0.05 and 0.30, respectively. We conclude that for new traits with a very small or positive genetic correlation with the index, and a high positive economic value, considerable genetic response can already be achieved based on a cow reference population with only 2000 records, even when the reliability of individual genomic breeding values is much lower than currently accepted in dairy cattle breeding programs. New traits may generally have a negative genetic correlation with the index and a small positive economic value. For such new traits, cow reference populations of at least 10 000 cows may be required to achieve acceptable levels of genetic response for the new trait and for the whole breeding goal