Download Laboratory Analytical Methods

Material and Methods
Ascertainment of FCH Families
The 18 extended Dutch FCH families were ascertained through probands that were
recruited from the Lipid Clinic of the Utrecht Academic University Hospital, as previously
described16. The probands met the following criteria: (1) a primary combined hyperlipidemia
with varying phenotypic expression, including a fasting plasma cholesterol > 6.5 mmol/l, or >
90th percentile for age, defined according to tables from the Lipid Research Clinics, and fasting
plasma triglycerides >2.3 mmol/l; (2) at least one first degree relative with a different
hyperlipidemic phenotype; (3) a positive family history of premature CHD defined as
myocardial infarction or cardiovascular disease before 60 years of age. While plasma
apolipoprotein B (apoB) levels are also frequently elevated in FCH individuals and sometimes
used as another diagnostic feature, this latter criterion was not applied to the ascertainment of
these families. Exclusion criteria for the probands included diabetes, obesity (BMI > 30), tendon
xanthomas, or type III hyperlipidemia (apoE2/E2). Relatives were assigned the FCH phenotype
when they met the following criteria: fasting plasma cholesterol > 6.5 mmol/l, and/or fasting
plasma triglycerides > 2.3 mmol/l. Using these criteria, there were 158 affected individuals and
212 unaffected relatives. The spouses (n=173) represented a common, environment-, nutrition-,
and age-matched control group for the probands and their hyperlipidemic relatives. All subjects
gave informed consent, and the study protocol was approved by the Human Investigation Review
Committee of Utrecht University Hospital, the Netherlands.
SBP and DBP were measured twice with a mercury sphygmomanometer in a standardized
fashion with the subject in sitting position after 10 min of rest. Of the 240 individuals that were
genotyped for the genome scan, 24 were taking anti-hypertensive medication. The percentage of
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FCH relatives and spouses with hypertension (defined as SBP > 140 and/or DBP > 90 and/or
taking anti-hypertensive medication) is 44% and 28%, respectively. However, for the purposes
of this study, SBP and DBP were treated as continuous, quantitative traits.
Laboratory Analytical Methods
Venous blood was drawn after an overnight fast of 12-14h and plasma was prepared by
immediate centrifugation. Lipids, apolipoproteins, and measures of insulin/glucose were
quantified by methods as described elsewhere14,16. Probands or hyperlipidemic relatives who
used lipid-lowering drugs were studied after their lipid lowering treatment was withheld for 3
weeks. Only these lipid values and other quantitative measurements were used in this study.
Genotyping
For the genome scan, 399 microsatellite markers, spaced on average 10cM, were
genotyped in 240 individuals from the 18 FCH families using fluorescent-based methods, as
described elsewhere17. We previously conducted a genome scan for the discrete FCH trait in
these same families, and in the present study, the genotyping data was used to conduct a genome
scan for BP. The markers employed in construction of the linkage map comprised the Weber 6a
screening set, and the heterozygosity indices of the markers averaged 0.82 in the families
analyzed.
Genotypes for two polymorphisms in the -adducin gene were determined in those
individuals for whom DNA and phenotype data was available (n=496). Genotyping of a GT
substitution in exon 10 was performed according to previously described methods18. Genotyping
of a CG polymorphism in exon 1319 was determined by PCR amplification (forward primer:
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5’AAC CCC TTC ACC ACA CTC AC 3’ and reverse primer: 5’ CCA CAA AGA AGC TCC
CAG AG 3’) followed by digestion with the restriction enzyme BanII.
Genetic Statistical Analyses
Since BP is thought to be a genetically complex trait, nonparametric linkage methods,
which do not require assumptions regarding the mode of inheritance, were used20. For the
multipoint linkage analyses of the genome scan, the MAPMAKER/SIBS program was used to
estimate allele sharing at and between markers21. The test statistic for a correlation between
allele sharing and squared trait differences among sibpairs is reported as a LOD score20. Twopoint linkage with individual markers at the chromosome 4p locus was assessed using the
SIBPAL subprogram of the S.A.G.E. package22. SBP and plasma FFA levels were evaluated for
linkage with marker loci using the Haseman-Elston algorithm23 by regressing the squared trait
difference of sibling pairs (n=322) on the proportion of alleles shared identical-by-descent.
Because sibpairs in the same sibship may be nonindependent statistically, significance levels are
calculated using effective degrees of freedom (edf), which reflects the number of independent
sibling pairs in the analyses22.
Association analyses of the -adducin polymorphisms with SBP were assessed with an
ANOVA, using a measured genotype approach24. The Statview program (Ver. 5.0; The SAS
Institute) was used to conduct these analyses, and, to ensure that all observations in the data were
independent, only those marrying into the pedigrees, i.e. the spouse controls, were analyzed for
statistical significance.
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