Guidelines were developed for data collection from medical records for use in retrospective analyses

Jansen, Angelique C.M.; Cohen, Emily; Hutten, Barbara A.; Büller, Harry R.; Kastelein, John J.P.; Prins, Martin H.

doi:10.1016/j.jclinepi.2004.07.006

Cited by 109 publications

(93 citation statements)

References 16 publications

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“…The second replication cohort consisted of Dutch clinically proven heterozygous FH patients who were recruited from 27 lipid clinics in the Netherlands between 1989 and 2002. 10,11 For the cases in this cohort, the same CHD definition was applied as described above for the MARCH sample. The controls had no manifest CHD.…”

Section: Description Of the Populationsmentioning

confidence: 99%

Identifying genetic risk variants for coronary heart disease in familial hypercholesterolemia: an extreme genetics approach

et al. 2014

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Mutations in the low-density lipoprotein receptor (LDLR) gene cause familial hypercholesterolemia (FH), a disorder characterized by coronary heart disease (CHD) at young age. We aimed to apply an extreme sampling method to enhance the statistical power to identify novel genetic risk variants for CHD in individuals with FH. We selected cases and controls with an extreme contrast in CHD risk from 17 000 FH patients from the Netherlands, whose functional LDLR mutation was unequivocally established. The genome-wide association (GWA) study was performed on 249 very young FH cases with CHD and 217 old FH controls without CHD (above 65 years for males and 70 years of age for females) using the Illumina HumanHap550K chip. In the next stage, two independent samples (one from the Netherlands and one from Italy, Norway, Spain, and the United Kingdom) of FH patients were used as replication samples. In the initial GWA analysis, we identified 29 independent single nucleotide polymorphisms (SNPs) with suggestive associations with premature CHD (Po1 Â 10 À4 ). We examined the association of these SNPs with CHD risk in the replication samples. After Bonferroni correction, none of the SNPs either replicated or reached genome-wide significance after combining the discovery and replication samples. Therefore, we conclude that the genetics of CHD risk in FH is complex and even applying an 'extreme genetics' approach we did not identify new genetic risk variants. Most likely, this method is not as effective in leveraging effect size as anticipated, and may, therefore, not lead to significant gains in statistical power.

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Section: Description Of the Populationsmentioning

confidence: 99%

Identifying genetic risk variants for coronary heart disease in familial hypercholesterolemia: an extreme genetics approach

et al. 2014

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“…A welltrained team of 13 data collectors reviewed medical records to establish extensive phenotypic data including CHD events. 19 Total cholesterol, high-density lipoprotein cholesterol, and triglyceride levels were measured by standard methods in fasting patients who had been withdrawn from lipid-lowering medication at least 6 weeks before blood collection. Low-density lipoprotein cholesterol concentration was calculated with the Friedewald formula.…”

Section: Fh Cohortmentioning

confidence: 99%

Apolipoprotein Isoform E4 Does Not Increase Coronary Heart Disease Risk in Carriers of Low-Density Lipoprotein Receptor Mutations

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Hoekstra

et al. 2011

Circ Cardiovasc Genet

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Background-In humans, the E4 allele of the apolipoprotein E gene is associated with increased coronary heart disease risk. Surprisingly, in rodents, apolipoprotein E4 only accelerates the atherosclerotic process when transgenic for the human low-density lipoprotein receptor (LDLR) protein. We therefore investigated whether the LDLR locus interacted with the apolipoprotein E gene genotype on coronary heart disease risk in patients clinically diagnosed with familial hypercholesterolemia with and without LDLR mutation. We investigated whether the presence of an LDLR mutation diminishing LDLR function was protective in E4/E4 carriers. Methods and Results-In a cohort of 2400 patients clinically diagnosed with familial hypercholesterolemia, we found an LDLR gene mutation in 1383 patients, whereas in 1013 patients, such mutation was not present. In 92 patients homozygous for the apolipoprotein E4, the presence of an LDLR mutation conferred lower coronary heart disease risk (hazard ratio, 0.16; 95% CI, 0.05-0.58; Pϭ0.005). Mirroring these results, the apolipoprotein E4/E4 genotype was also associated with lower coronary heart disease risk in patients with familial hypercholesterolemia with an LDLR mutation (hazard ratio, 0.26; hazard ratio, 0.08 -0.80; Pϭ0.02). Conclusions-LDLR function is key to the detrimental effects of apolipoprotein E4 in humans. Kinetic studies in humans are now required to study the consequences of our observation for prevention of both coronary heart disease and Alzheimer disease. (Circ Cardiovasc Genet. 2011;4:655-660.)Key Words: apolipoprotein E Ⅲ coronary heart disease Ⅲ familial hypercholesterolemia C omplications of atherosclerotic vascular disease are the most common causes of death and morbidity in the Western world with coronary heart disease (CHD) as its most prominent manifestation. 1 Hereditary predisposition plays an important role in the pathobiology of atherosclerosis. One of the genes best known for its association with CHD risk is the 1 coding for the low-density lipoprotein receptor (LDLR) protein. Mutations in this gene cause an autosomal-dominant disorder called familial hypercholesterolemia (FH), which is characterized by severe hypercholesterolemia and premature CHD. 2 Another important gene known to influence CHD risk is apolipoprotein E (APOE). 3 Mice completely lacking the ApoE protein are severely hypercholesterolemic and develop extensive atherosclerotic lesions, a process that is accelerated when they are fed a high-fat diet. 4,5 Homozygous deficiency of the APOE gene in humans is extremely rare and is also characterized by atherogenic lipid abnormalities and premature CHD. 6,7 Clinical Perspective on p 660In humans, 3 main haplotypes of the APOE gene have been identified: APOE2, APOE3, and APOE4. The encoded ApoE2, ApoE3, and ApoE4 proteins differ in their amino acid sequences at positions 112 and 158. Although these differences are not located in the LDLR binding domain, affinity to the LDLR differs between genotypes: ApoE2 has the lowest affinity for the LDLR, where...

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“…Details of the study design and the study population have been published previously. 8,9 In brief, lipid clinics in the Netherlands routinely submit DNA of suspected FH individuals to a central laboratory for lowdensity lipoprotein (LDL) receptor mutation analysis. A total of 2400 unrelated patients who fulfilled the internationally established FH diagnostic criteria 8 were randomly selected from this database.…”

Section: Study Populationmentioning

confidence: 99%

“…Data on CHD were collected from the medical records by using a standardized protocol. 9 CHD was defined as the presence of at least one of the following: (i) myocardial infarction, (ii) percutaneous coronary intervention or other invasive procedures, (iii) coronary artery bypass grafting, or (iv) angina pectoris. Forty-nine percent of the FH patients were men, and mean age at the last visit to the lipid clinic was 50 years (SD 13 years).…”

Section: Study Populationmentioning

confidence: 99%

Cox proportional hazards models have more statistical power than logistic regression models in cross-sectional genetic association studies

et al. 2008

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Cross-sectional genetic association studies can be analyzed using Cox proportional hazards models with age as time scale, if age at onset of disease is known for the cases and age at data collection is known for the controls. We assessed to what degree and under what conditions Cox proportional hazards models have more statistical power than logistic regression models in cross-sectional genetic association analyses. Analyses were conducted in an empirical study on the association of 65 polymorphisms and risk of coronary heart disease among 2400 familial hypercholesterolemia patients, and in a simulation study that considered various combinations of sample size, genotype frequency, and strength of association between the genotype and coronary heart disease. We applied Cox proportional hazards models and logistic regression models, and compared effect estimates (hazard ratios and odds ratios) and statistical power. In the empirical study, Cox proportional hazards models generally showed lower P-values for polymorphisms than logistic regression models. In the simulation study, Cox proportional hazards models had higher statistical power in all scenarios. Absolute differences in power did depend on the effect estimate, genotype frequency and sample size, and were most prominent for genotypes with minor effects. For example, when the genotype frequency was 30% in a sample with size n ¼ 2000 individuals, the absolute differences were the largest for effect estimates between 1.1 and 1.5. In conclusion, Cox proportional hazards models can increase statistical power in cross-sectional genetic association studies, especially in the range of effect estimates that are expected for genetic associations in common diseases.

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Guidelines were developed for data collection from medical records for use in retrospective analyses

Cited by 109 publications

References 16 publications

Identifying genetic risk variants for coronary heart disease in familial hypercholesterolemia: an extreme genetics approach

Identifying genetic risk variants for coronary heart disease in familial hypercholesterolemia: an extreme genetics approach

Apolipoprotein Isoform E4 Does Not Increase Coronary Heart Disease Risk in Carriers of Low-Density Lipoprotein Receptor Mutations

Cox proportional hazards models have more statistical power than logistic regression models in cross-sectional genetic association studies

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