Genome-wide linkage scan for genes affecting longitudinal trends in systolic blood pressure

Jacobs, Kevin B.; Gray‐McGuire, Courtney; Cartier, Kevin C.; Elston, Robert C.

doi:10.1186/1471-2156-4-s1-s82

Cited by 17 publications

(19 citation statements)

References 8 publications

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“…There was little agreement in the linkage analysis results based on SBP in the FHS. Significant results in the same region were found by two groups on chromosomes 1 (200-240 cM) [James et al, 2003;Wang et al, 2003] and 12 (66-78 cM) [James et al, 2003;Jacobs et al, 2003].…”

supporting

confidence: 76%

Modeling and dissection of longitudinal blood pressure and hypertension phenotypes in genetic epidemiological studies

et al. 2003

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We discuss analyses of the Genetic Analysis Workshop 13 data from the Framingham Heart Study and simulations based on this study. We summarize analyses that investigated measures of systolic blood pressure or hypertension as the main phenotype, with the main focus being the modeling of this complex longitudinal phenotype. The approaches include familial aggregation methods and one-stage and two-stage linkage methods. For one-stage linkage methods, phenotype modeling is carried out jointly with the linkage analysis or incorporated in the analysis design. For two-stage linkage methods, phenotypes are first modeled in order to develop summary measures that are then analyzed in a subsequent linkage analysis. Results depend on phenotype selection and on how analyses account for longitudinality, treatment effects, and heterodasticity.

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confidence: 76%

Modeling and dissection of longitudinal blood pressure and hypertension phenotypes in genetic epidemiological studies

et al. 2003

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“…In the Framingham Offspring Study, blood pressure slope and curvature over time during adulthood have been found to link to regions on chromosomes 7, 18, and 20. 12,13 In this study, we found a LOD peak at 28 cM from the p-terminal on chromosome 18 for the incremental AUC of diastolic blood pressure, a combination of linear slope and nonlinear curvature. Positive linkage has also been observed around this region for long-term blood pressure levels 10 and essential hypertension 36 in other studies.…”

Section: Chen Et Al Genetic Loci For Blood Pressure Since Childhood 957supporting

confidence: 49%

“…10,12,13 However, information on the genetic loci linking longitudinal changes in blood pressure from childhood to adulthood is still limited. Longitudinal observations from the Bogalusa Heart Study, a community-based epidemiologic study of early natural history of cardiovascular risk factors beginning in childhood, 14 provide an opportunity to examine the susceptibility loci influencing both between-person and within-person variability in blood pressure from childhood to young adulthood.…”

mentioning

confidence: 99%

Autosomal Genome Scan for Loci Linked to Blood Pressure Levels and Trends Since Childhood

Chen

Srinivasan

et al. 2005

Hypertension

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Abstract-Genetic loci influencing the long-term levels and trends of blood pressure over time were investigated using 775 white siblings, ages 13 to 43 years, enrolled in the Bogalusa Heart Study, and 357 microsatellite markers on the 22 autosomal chromosomes. Subjects had been examined serially 2 to 12 times with 4365 serial observations over an average of 22 years from childhood to adulthood. Total and incremental area under the curve was calculated based on a cubic growth curve and used as long-term levels and trends, respectively. After adjusting for age, sex, and body mass index, heritability estimates of total area were 0.66 for systolic and 0.68 for diastolic blood pressure. Heritability of incremental area was 0.38 for systolic and 0.46 for diastolic blood pressure. Significant linkage to the total area of diastolic blood pressure (peak logarithm of odds [LOD]ϭ3.9 at 73 cM) was observed on chromosome 2, with a region spanning from 44 cM to 103 cM showing supporting linkage evidence of LOD Ͼ3.0. In addition, suggestive linkage for total area of systolic (LODϭ1.6 at 182 cM) and diastolic blood pressure (LODϭ2.0 at 36 cM) on chromosome 4 and diastolic blood pressure incremental area (LODϭ2.2 at 28 cM) on chromosome 18 was noted. Several hypertension candidate genes such as ␣-adducin, ␤-adducin, sodium bicarbonate co-transporter, and G protein-coupled receptor kinase 4 are located in these regions. Linkage evidence found in this community-based study indicates that regions on these chromosomes harbor genetic loci that affect the propensity for development of hypertension from childhood. Key Words: blood pressure E ssential hypertension is a polygenic disorder that results from the interplay of multiple susceptibility genes and environmental factors. 1 Numerous genome-wide linkage studies to localize genes influencing blood pressure and hypertension status in a number of populations and ethnic groups have found linkage evidence in regions on multiple chromosomes. 2 However, most linkage studies on blood pressure and hypertension have thus far been cross-sectional in nature, representing between-person variability at a specific time point only.Blood pressure increases with age at different rates. 3,4 In addition to levels, genes may also affect the longitudinal trends of blood pressure that represent within-person variability. A substantial genetic contribution to the changes in blood pressure over time has been demonstrated in longitudinal twin and family studies. 5,6 A concept of "variability genes," whose expression depends on environmental exposure, is proposed to explain the within-person variability. 7 Further, using serial measurements of a trait at multiple time points dilutes the measurement errors and minimizes the short-term influences when the trait is subject to variation from time to time within the same individual. 8,9 This notion is supported by earlier findings from studies on genetics and epidemiology of blood pressure. 10,11 Therefore, measures of long-term levels and trend of blood pressure...

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“…Franke et al [2005] and Papanicolaou et al [2005] examined the issue of critical values. Franke et al [2005], using simulated data, examined a methodological issue concerning the family-wise weighting of H-E regression by marker informativity, as proposed by Jacobs et al [2003]. Specifically, they used a simplex weighting scheme to determine the applicability of designing asymptotically significant P-values.…”

Section: Genome-wide Scans: Methodological Issuesmentioning

confidence: 99%

Dissection of heterogeneous phenotypes for quantitative trait mapping

et al. 2005

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We discuss analyses of Genetic Analysis Workshop 14 data from the Collaborative Study on the Genetics of Alcoholism (COGA) as well as from a simulated complex disease, Kofendrerd personality disorder (KPD), with both genetic and phenotypic heterogeneity. Both data sets included numerous related phenotypes in addition to disease definitions. All analyses either chose from the given selection of phenotypes or defined new ones, including traits that may not have been related to alcoholism or KPD. Some contributors evaluated the genetic components of the trait. Many investigated genome-wide linkage and/or association, using microsatellites and/or single-nucleotide polymorphism (SNP) chip data. Here we will focus on methodological issues that the investigators faced. Their results depended on phenotype selection, whether continuous or discrete, the covariates included, and ethnicity of the study population. For SNP chip data, members of our group detected no difference in results for Affymetrix or Illumina chips, although higher marker density for association studies appeared to be advantageous. Overall, there were some observations that different chromosomal segments, i.e., physical locations on the p-arm, q-arm, or middle segment, might lead to possible differences in type I error rates. This finding and others highlight the importance of empirical determination of P-values to determine significance.

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Genome-wide linkage scan for genes affecting longitudinal trends in systolic blood pressure

Cited by 17 publications

References 8 publications

Modeling and dissection of longitudinal blood pressure and hypertension phenotypes in genetic epidemiological studies

Modeling and dissection of longitudinal blood pressure and hypertension phenotypes in genetic epidemiological studies

Autosomal Genome Scan for Loci Linked to Blood Pressure Levels and Trends Since Childhood

Dissection of heterogeneous phenotypes for quantitative trait mapping

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