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author:("Engelman, corine D ")
1.  The Association of Telomere Length with Colorectal Cancer Differs by the Age of Cancer Onset 
OBJECTIVES:
Telomeres are nucleoprotein structures that cap the end of chromosomes and shorten with sequential cell divisions in normal aging. Short telomeres are also implicated in the incidence of many cancers, but the evidence is not conclusive for colorectal cancer (CRC). Therefore, the aim of this study was to assess the association of CRC and telomere length.
METHODS:
In this case–control study, we measured relative telomere length from peripheral blood leukocytes (PBLs) DNA with quantitative PCR in 598 CRC patients and 2,212 healthy controls.
RESULTS:
Multivariate analysis indicated that telomere length was associated with risk for CRC, and this association varied in an age-related manner; younger individuals (≤50 years of age) with longer telomeres (80–99 percentiles) had a 2–6 times higher risk of CRC, while older individuals (>50 years of age) with shortened telomeres (1–10 percentiles) had 2–12 times the risk for CRC. The risk for CRC varies with extremes in telomere length in an age-associated manner.
CONCLUSIONS:
Younger individuals with longer telomeres or older individuals with shorter telomeres are at higher risk for CRC. These findings indicate that the association of PBL telomere length varies according to the age of cancer onset and that CRC is likely associated with at minimum two different mechanisms of telomere dynamics.
doi:10.1038/ctg.2014.3
PMCID: PMC3972691  PMID: 24598784
2.  Perceived neighborhood quality, sleep quality, and health status: Evidence from the Survey of the Health of Wisconsin 
Why does living in a disadvantaged neighborhood predict poorer mental and physical health? Recent research focusing on the Southwestern United States suggests that disadvantaged neighborhoods favor poor health, in part, because they undermine sleep quality. Building on previous research, we test whether this process extends to the Midwestern United States. Specifically, we use cross-sectional data from the Survey of the Health of Wisconsin (SHOW), a statewide probability sample of Wisconsin adults, to examine whether associations among perceived neighborhood quality (e.g., perceptions of crime, litter, and pleasantness in the neighborhood) and health status (overall self-rated health and depression) are mediated by overall sleep quality (measured as self-rated sleep quality and physician diagnosis of sleep apnea). We find that perceptions of low neighborhood quality are associated with poorer self-rated sleep quality, poorer self-rated health, and more depressive symptoms. We also observe that poorer self-rated sleep quality is associated with poorer self-rated health and more depressive symptoms. Our mediation analyses indicate that self-rated sleep quality partially mediates the link between perceived neighborhood quality and health status. Specifically, self-rated sleep quality explains approximately 20% of the association between neighborhood quality and self-rated health and nearly 19% of the association between neighborhood quality and depression. Taken together, these results confirm previous research and extend the generalizability of the indirect effect of perceived neighborhood context on health status through sleep quality.
doi:10.1016/j.socscimed.2012.07.021
PMCID: PMC3733364  PMID: 22901794
Sleep; Sleep quality; Neighborhood context; Neighborhood quality; Self-rated health; Depression; Wisconsin; USA
3.  Detecting Multiple Causal Rare Variants in Exome Sequence Data 
Genetic Epidemiology  2011;35(Suppl 1):S18-S21.
Recent advances in sequencing technology have presented both opportunities and challenges, with limited statistical power to detect a single causal rare variant with practical sample sizes. To overcome this, the contributors to Group 1 of Genetic Analysis Workshop 17 sought to develop methods to detect the combined signal of multiple causal rare variants in a biologically meaningful way. The contributors used genes, genome location proximity, or genetic pathways as the basic unit in combining the information from multiple variants. Weaknesses of the exome sequence data and the relative strengths and weaknesses of the five approaches are discussed.
doi:10.1002/gepi.20644
PMCID: PMC3271433  PMID: 22128053
Bayesian; pathways; simulated
4.  Interaction between two cholesterol metabolism genes influences memory: findings from the Wisconsin Registry for Alzheimer’s Prevention 
The strongest genetic factor for late-onset Alzheimer’s disease (AD) is APOE; nine additional susceptibility genes have recently been identified. The effect of these genes is often assumed to be additive and polygenic scores are formed as a summary measure of risk. However, interactions between these genes are likely to be important. We sought to examine the role of interactions between the nine recently identified AD susceptibility genes and APOE in cognitive function and decline in 1,153 participants from the Wisconsin Registry for Alzheimer’s Prevention, a longitudinal study of middle-aged adults enriched for a parental history of AD. Participants underwent extensive cognitive testing at baseline and up to two additional visits approximately 4 and 6 years later. The influence of the interaction between APOE and each of 14 single nucleotide polymorphisms (SNPs) in the nine recently identified genes on three cognitive factor scores (Verbal Learning and Memory, Working Memory, and Immediate Memory) was examined using linear mixed models adjusting for age, gender and ancestry. Interactions between the APOE ε4 allele and both of the genotyped ABCA7 SNPs, rs3764650 and rs3752246, were associated with all three cognitive factor scores (P-values ≤0.01). Both of these genes are in the cholesterol metabolism pathway leading to AD. This research supports the importance of considering non-additive effects of AD susceptibility genes.
doi:10.3233/JAD-130482
PMCID: PMC3759032  PMID: 23669301
gene-gene interaction; memory; cognition; Alzheimer’s disease; cholesterol
5.  Correlation of Chromosomal Instability, Telomere Length and Telomere Maintenance in Microsatellite Stable Rectal Cancer: A Molecular Subclass of Rectal Cancer 
PLoS ONE  2013;8(11):e80015.
Introduction
Colorectal cancer (CRC) tumor DNA is characterized by chromosomal damage termed chromosomal instability (CIN) and excessively shortened telomeres. Up to 80% of CRC is microsatellite stable (MSS) and is historically considered to be chromosomally unstable (CIN+). However, tumor phenotyping depicts some MSS CRC with little or no genetic changes, thus being chromosomally stable (CIN-). MSS CIN- tumors have not been assessed for telomere attrition.
Experimental Design
MSS rectal cancers from patients ≤50 years old with Stage II (B2 or higher) or Stage III disease were assessed for CIN, telomere length and telomere maintenance mechanism (telomerase activation [TA]; alternative lengthening of telomeres [ALT]). Relative telomere length was measured by qPCR in somatic epithelial and cancer DNA. TA was measured with the TRAPeze assay, and tumors were evaluated for the presence of C-circles indicative of ALT. p53 mutation status was assessed in all available samples. DNA copy number changes were evaluated with Spectral Genomics aCGH.
Results
Tumors were classified as chromosomally stable (CIN-) and chromosomally instable (CIN+) by degree of DNA copy number changes. CIN- tumors (35%; n=6) had fewer copy number changes (<17% of their clones with DNA copy number changes) than CIN+ tumors (65%; n=13) which had high levels of copy number changes in 20% to 49% of clones. Telomere lengths were longer in CIN- compared to CIN+ tumors (p=0.0066) and in those in which telomerase was not activated (p=0.004). Tumors exhibiting activation of telomerase had shorter tumor telomeres (p=0.0040); and tended to be CIN+ (p=0.0949).
Conclusions
MSS rectal cancer appears to represent a heterogeneous group of tumors that may be categorized both on the basis of CIN status and telomere maintenance mechanism. MSS CIN- rectal cancers appear to have longer telomeres than those of MSS CIN+ rectal cancers and to utilize ALT rather than activation of telomerase.
doi:10.1371/journal.pone.0080015
PMCID: PMC3836975  PMID: 24278232
6.  Genetic Determinants of Macular Pigments in Women of the Carotenoids in Age-Related Eye Disease Study 
Purpose.
To investigate genetic determinants of macular pigment optical density in women from the Carotenoids in Age-Related Eye Disease Study (CAREDS), an ancillary study of the Women's Health Initiative Observational Study.
Methods.
1585 of 2005 CAREDS participants had macular pigment optical density (MPOD) measured noninvasively using customized heterochromatic flicker photometry and blood samples genotyped for 440 single nucleotide polymorphisms (SNPs) in 26 candidate genes related to absorption, transport, binding, and cleavage of carotenoids directly, or via lipid transport. SNPs were individually tested for associations with MPOD using least-squares linear regression.
Results.
Twenty-one SNPs from 11 genes were associated with MPOD (P ≤ 0.05) after adjusting for dietary intake of lutein and zeaxanthin. This includes variants in or near genes related to zeaxanthin binding in the macula (GSTP1), carotenoid cleavage (BCMO1), cholesterol transport or uptake (SCARB1, ABCA1, ABCG5, and LIPC), long-chain omega-3 fatty acid status (ELOVL2, FADS1, and FADS2), and various maculopathies (ALDH3A2 and RPE65). The strongest association was for rs11645428 near BCMO1 (βA = 0.029, P = 2.2 × 10−4). Conditional modeling within genes and further adjustment for other predictors of MPOD, including waist circumference, diabetes, and dietary intake of fiber, resulted in 13 SNPs from 10 genes maintaining independent association with MPOD. Variation in these single gene polymorphisms accounted for 5% of the variability in MPOD (P = 3.5 × 10−11).
Conclusions.
Our results support that MPOD is a multi-factorial phenotype associated with variation in genes related to carotenoid transport, uptake, and metabolism, independent of known dietary and health influences on MPOD.
In 1585 postmenopausal women of the Carotenoids in Age-Related Eye Disease Study sample, common genetic variants in or near genes involved in carotenoid transport, uptake, and metabolism were associated with density of lutein and zeaxanthin in the macula, independent of other known predictors, including dietary intake of carotenoids.
doi:10.1167/iovs.12-10867
PMCID: PMC3626525  PMID: 23404124
7.  The Challenge of Detecting Epistasis (G×G Interactions): Genetic Analysis Workshop 16 
Genetic epidemiology  2009;33(0 1):S58-S67.
Interest is increasing in epistasis as a possible source of the unexplained variance missed by genome-wide association studies. The Genetic Analysis Workshop 16 Group 9 participants evaluated a wide variety of classical and novel analytical methods for detecting epistasis, in both the statistical and machine learning paradigms, applied to both real and simulated data. Because the magnitude of epistasis is clearly relative to scale of penetrance, and therefore to some extent, to the choice of model framework, it is not surprising that strong interactions under one model might be minimized or even disappear entirely under a different modeling framework.
doi:10.1002/gepi.20474
PMCID: PMC3692280  PMID: 19924703
generalized linear model; machine learning methods
8.  Duration of Physical Activity and Serum 25-hydroxyvitamin D Status of Postmenopausal Women 
Annals of epidemiology  2011;21(6):440-449.
Purpose
To investigate whether the association between physical activity and serum 25-hydroxyvitamin D (25(OH)D) concentrations is independent of sun exposure, body size, and other potential explanatory variables.
Methods
Using data from a sample of 1,343 postmenopausal women, from the Women’s Health Initiative, linear regression was used to examine the associations of duration (minutes/week) of recreational activity and of yard work with 25(OH)D concentrations (nmol/L).
Results
In age-adjusted analyses, positive associations were observed between 25(OH)D concentrations and both duration of recreational physical activity (β=0.71, SE(0.09), P<0.001) and yard work (β=0.36, SE(0.10), P=0.004). After further adjustment for vitamin D intake, self-reported sunlight exposure, waist circumference, and season of blood draw, 25(OH)D was significantly associated with recreational activity (β=0.21, SE(0.09), P=0.014) but not with yard work (β=0.18, SE(0.09), P=0.061). Interactions were observed between season and both recreational activity (Pinteraction=0.082) and yard work (Pinteraction=0.038) such that these activity-25(OH)D associations were greater during summer/fall compared to winter/spring. Self-reported sunlight exposure and measures of body size did not modify the associations.
Conclusion
The observed age-adjusted activity-25(OH)D associations were attenuated after adjusting for explanatory variables and were modified by season of blood draw. Adopting a lifestyle that incorporates outdoor physical activity during summer/fall, consuming recommended amounts of vitamin D, and maintaining a healthy weight may improve or maintain vitamin D status in postmenopausal women.
doi:10.1016/j.annepidem.2010.11.011
PMCID: PMC3090482  PMID: 21414803
25-hydroxyvitamin D; vitamin D; serum; sunlight exposure; physical activity; epidemiology; women
9.  Analysis of human mini-exome sequencing data from Genetic Analysis Workshop 17 using a Bayesian hierarchical mixture model 
BMC Proceedings  2011;5(Suppl 9):S93.
Next-generation sequencing technologies are rapidly changing the field of genetic epidemiology and enabling exploration of the full allele frequency spectrum underlying complex diseases. Although sequencing technologies have shifted our focus toward rare genetic variants, statistical methods traditionally used in genetic association studies are inadequate for estimating effects of low minor allele frequency variants. Four our study we use the Genetic Analysis Workshop 17 data from 697 unrelated individuals (genotypes for 24,487 autosomal variants from 3,205 genes). We apply a Bayesian hierarchical mixture model to identify genes associated with a simulated binary phenotype using a transformed genotype design matrix weighted by allele frequencies. A Metropolis Hasting algorithm is used to jointly sample each indicator variable and additive genetic effect pair from its conditional posterior distribution, and remaining parameters are sampled by Gibbs sampling. This method identified 58 genes with a posterior probability greater than 0.8 for being associated with the phenotype. One of these 58 genes, PIK3C2B was correctly identified as being associated with affected status based on the simulation process. This project demonstrates the utility of Bayesian hierarchical mixture models using a transformed genotype matrix to detect genes containing rare and common variants associated with a binary phenotype.
doi:10.1186/1753-6561-5-S9-S93
PMCID: PMC3287935  PMID: 22373180
10.  Genome-wide association study of vitamin D concentrations in Hispanic Americans: The IRAS Family Study 
Vitamin D deficiency is associated with many adverse health outcomes. There are several well established environmental predictors of vitamin D concentrations, yet studies of the genetic determinants of vitamin D concentrations are in their infancy. Our objective was to conduct a pilot genome-wide association (GWA) study of 25-hydroxyvitamin D (25[OH]D) and 1,25-dihydroxyvitamin D (1,25[OH]2D) concentrations in a subset of 229 Hispanic subjects, followed by replication genotyping of 50 single nucleotide polymorphisms (SNPs) in the entire sample of 1,190 Hispanics from San Antonio, Texas and San Luis Valley, Colorado. Of the 309,200 SNPs that met all quality control criteria, three SNPs in high linkage disequilibrium (LD) with each other were significantly associated with 1,25[OH]2D (rs6680429, rs9970802, and rs10889028) at a Bonferroni corrected P-value threshold of 1.62 × 10−7, however none met the threshold for 25[OH]D. Of the 50 SNPs selected for replication genotyping, five for 25[OH]D (rs2806508, rs10141935, rs4778359, rs1507023, and rs9937918) and eight for 1,25[OH]2D (rs6680429, rs1348864, rs4559029, rs12667374, rs7781309, rs10505337, rs2486443, and rs2154175) were replicated in the entire sample of Hispanics (P < 0.01). In conclusion, we identified several SNPs that were associated with vitamin D metabolite concentrations in Hispanics. These candidate polymorphisms merit further investigation in independent populations and other ethnicities.
doi:10.1016/j.jsbmb.2010.06.013
PMCID: PMC2949505  PMID: 20600896
Vitamin D; 25-hydroxyvitamin D; 1,25-dihydroxyvitamin D; genome-wide association study; Hispanic
11.  The Survey of the Health of Wisconsin (SHOW), a novel infrastructure for population health research: rationale and methods 
BMC Public Health  2010;10:785.
Background
Evidence-based public health requires the existence of reliable information systems for priority setting and evaluation of interventions. Existing data systems in the United States are either too crude (e.g., vital statistics), rely on administrative data (e.g., Medicare) or, because of their national scope (e.g., NHANES), lack the discriminatory power to assess specific needs and to evaluate community health activities at the state and local level. This manuscript describes the rationale and methods of the Survey of the Health of Wisconsin (SHOW), a novel infrastructure for population health research.
Methods/Design
The program consists of a series of independent annual surveys gathering health-related data on representative samples of state residents and communities. Two-stage cluster sampling is used to select households and recruit approximately 800-1,000 adult participants (21-74 years old) each year. Recruitment and initial interviews are done at the household; additional interviews and physical exams are conducted at permanent or mobile examination centers. Individual survey data include physical, mental, and oral health history, health literacy, demographics, behavioral, lifestyle, occupational, and household characteristics as well as health care access and utilization. The physical exam includes blood pressure, anthropometry, bioimpedance, spirometry, urine collection and blood draws. Serum, plasma, and buffy coats (for DNA extraction) are stored in a biorepository for future studies. Every household is geocoded for linkage with existing contextual data including community level measures of the social and physical environment; local neighborhood characteristics are also recorded using an audit tool. Participants are re-contacted bi-annually by phone for health history updates.
Discussion
SHOW generates data to assess health disparities across state communities as well as trends on prevalence of health outcomes and determinants. SHOW also serves as a platform for ancillary epidemiologic studies and for studies to evaluate the effect of community-specific interventions. It addresses key gaps in our current data resources and increases capacity for etiologic, applied and translational population health research. It is hoped that this program will serve as a model to better support evidence-based public health, facilitate intervention evaluation research, and ultimately help improve health throughout the state and nation.
doi:10.1186/1471-2458-10-785
PMCID: PMC3022857  PMID: 21182792
12.  Detecting Gene-Environment Interactions in Genome-Wide Association Data 
Genetic epidemiology  2009;33(Suppl 1):S68-S73.
Despite the importance of gene-environment (G×E) interactions in the etiology of common diseases, little work has been done to develop methods for detecting these types of interactions in genome-wide association study data. This was the focus of Genetic Analysis Workshop 16 Group 10 contributions, which introduced a variety of new methods for the detection of G×E interactions in both case-control and family-based data using both cross-sectional and longitudinal study designs. Many of these contributions detected significant G×E interactions. Although these interactions have not yet been confirmed, the results suggest the importance of testing for interactions. Issues of sample size, quantifying the environmental exposure, longitudinal data analysis, family-based analysis, selection of the most powerful analysis method, population stratification, and computational expense with respect to testing G×E interactions are discussed.
doi:10.1002/gepi.20475
PMCID: PMC2924567  PMID: 19924704
GAW; case-control; family-based; cross-sectional; longitudinal; rheumatoid arthritis; Framingham Heart Study
13.  Detecting gene-by-smoking interactions in a genome-wide association study of early-onset coronary heart disease using random forests 
BMC Proceedings  2009;3(Suppl 7):S88.
Background
Genome-wide association studies are often limited in their ability to attain their full potential due to the sheer volume of information created. We sought to use the random forest algorithm to identify single-nucleotide polymorphisms (SNPs) that may be involved in gene-by-smoking interactions related to the early-onset of coronary heart disease.
Methods
Using data from the Framingham Heart Study, our analysis used a case-only design in which the outcome of interest was age of onset of early coronary heart disease.
Results
Smoking status was dichotomized as ever versus never. The single SNP with the highest importance score assigned by random forests was rs2011345. This SNP was not associated with age alone in the control subjects. Using generalized estimating equations to adjust for sex and account for familial correlation, there was evidence of an interaction between rs2011345 and smoking status.
Conclusion
The results of this analysis suggest that random forests may be a useful tool for identifying SNPs taking part in gene-by-environment interactions in genome-wide association studies.
PMCID: PMC2795991  PMID: 20018084
14.  Classification tree for detection of single-nucleotide polymorphism (SNP)-by-SNP interactions related to heart disease: Framingham Heart Study 
BMC Proceedings  2009;3(Suppl 7):S83.
The aim of this study was to detect the effect of interactions between single-nucleotide polymorphisms (SNPs) on incidence of heart diseases. For this purpose, 2912 subjects with 350,160 SNPs from the Framingham Heart Study (FHS) were analyzed. PLINK was used to control quality and to select the 10,000 most significant SNPs. A classification tree algorithm, Generalized, Unbiased, Interaction Detection and Estimation (GUIDE), was employed to build a classification tree to detect SNP-by-SNP interactions for the selected 10 k SNPs. The classes generated by GUIDE were reexamined by a generalized estimating equations (GEE) model with the empirical variance after accounting for potential familial correlation. Overall, 17 classes were generated based on the splitting criteria in GUIDE. The prevalence of coronary heart disease (CHD) in class 16 (determined by SNPs rs1894035, rs7955732, rs2212596, and rs1417507) was the lowest (0.23%). Compared to class 16, all other classes except for class 288 (prevalence of 1.2%) had a significantly greater risk when analyzed using GEE model. This suggests the interactions of SNPs on these node paths are significant.
PMCID: PMC2795986  PMID: 20018079
15.  Detecting single-nucleotide polymorphism by single-nucleotide polymorphism interactions in rheumatoid arthritis using a two-step approach with machine learning and a Bayesian threshold least absolute shrinkage and selection operator (LASSO) model 
BMC Proceedings  2009;3(Suppl 7):S63.
The objective of this study was to detect interactions between relevant single-nucleotide polymorphisms (SNPs) associated with rheumatoid arthritis (RA). Data from Problem 1 of the Genetic Analysis Workshop 16 were used. These data consisted of 868 cases and 1,194 controls genotyped with the 500 k Illumina chip. First, machine learning methods were applied for preselecting SNPs. One hundred SNPs outside the HLA region and 1,500 SNPs in the HLA region were preselected using information-gain theory. The software weka was used to reduce colinearity and redundancy in the HLA region, resulting in a subset of 6 SNPs out of 1,500. In a second step, a parametric approach to account for interactions between SNPs in the HLA region, as well as HLA-nonHLA interactions was conducted using a Bayesian threshold least absolute shrinkage and selection operator (LASSO) model incorporating 2,560 covariates. This approach detected some main and interaction effects for SNPs in genes that have previously been associated with RA (e.g., rs2395175, rs660895, rs10484560, and rs2476601). Further, some other SNPs detected in this study may be considered in candidate gene studies.
PMCID: PMC2795964  PMID: 20018057
16.  Genome-wide association studies using single-nucleotide polymorphisms versus haplotypes: an empirical comparison with data from the North American Rheumatoid Arthritis Consortium 
BMC Proceedings  2009;3(Suppl 7):S35.
The high genomic density of the single-nucleotide polymorphism (SNP) sets that are typically surveyed in genome-wide association studies (GWAS) now allows the application of haplotype-based methods. Although the choice of haplotype-based vs. individual-SNP approaches is expected to affect the results of association studies, few empirical comparisons of method performance have been reported on the genome-wide scale in the same set of individuals. To measure the relative ability of the two strategies to detect associations, we used a large dataset from the North American Rheumatoid Arthritis Consortium to: 1) partition the genome into haplotype blocks, 2) associate haplotypes with disease, and 3) compare the results with individual-SNP association mapping. Although some associations were shared across methods, each approach uniquely identified several strong candidate regions. Our results suggest that the application of both haplotype-based and individual-SNP testing to GWAS should be adopted as a routine procedure.
PMCID: PMC2795933  PMID: 20018026
17.  Comparison between two analytic strategies to detect linkage to obesity with genetically determined age of onset: the Framingham Heart Study 
BMC Genetics  2003;4(Suppl 1):S90.
Background
Genes have been found to influence the age of onset of several diseases and traits. The occurrence of many chronic diseases, obesity included, appears to be strongly age-dependent. However, an analysis of potential age of onset genes for obesity has yet to be reported. There are at least two analytic methods for determining an age of onset gene. The first is to consider a person affected if they possess the trait before a certain age (an early age of onset phenotype). The second is to define the phenotype based on the residual from a survival analysis.
Results
No regions provided evidence for linkage at the more stringent level of p < 0.001. However, five regions showed consistent suggestive evidence for linkage (one marker with p < 0.01 and a second contiguous marker at p < 0.05). These regions were chromosome 1 (280–294 cM) and chromosome 16 (56–64 cM) for overweight using the survival analysis residual method and chromosome 13 (102–122 cM), chromosome 17 (127–138 cM), and chromosome 19 (23–47 cM) for obese before age 35.
Conclusion
Only one region (chromosome 19 at 23–47 cM) showed somewhat consistent results between the two analytic methods. Potential reasons for inconsistent results between the two methods, as well as their strengths and weaknesses, are discussed. The use of both methods together to explore the genetics of the age of onset of a trait may prove to be beneficial in determining a gene that is linked only to an early age of onset phenotype versus one that determines age of onset through all age groups.
doi:10.1186/1471-2156-4-S1-S90
PMCID: PMC1866531  PMID: 14975158
18.  Genome scan linkage results for longitudinal systolic blood pressure phenotypes in subjects from the Framingham Heart Study 
BMC Genetics  2003;4(Suppl 1):S83.
The relationship between elevated blood pressure and cardiovascular and cerebrovascular disease risk is well accepted. Both systolic and diastolic hypertension are associated with this risk increase, but systolic blood pressure appears to be a more important determinant of cardiovascular risk than diastolic blood pressure. Subjects for this study are derived from the Framingham Heart Study data set. Each subject had five records of clinical data of which systolic blood pressure, age, height, gender, weight, and hypertension treatment were selected to characterize the phenotype in this analysis.
We modeled systolic blood pressure as a function of age using a mixed modeling methodology that enabled us to characterize the phenotype for each individual as the individual's deviation from the population average rate of change in systolic blood pressure for each year of age while controlling for gender, body mass index, and hypertension treatment. Significant (p = 0.00002) evidence for linkage was found between this normalized phenotype and a region on chromosome 1. Similar linkage results were obtained when we estimated the phenotype while excluding values obtained during hypertension treatment. The use of linear mixed models to define phenotypes is a methodology that allows for the adjustment of the main factor by covariates. Future work should be done in the area of combining this phenotype estimation directly with the linkage analysis so that the error in estimating the phenotype can be properly incorporated into the genetic analysis, which, at present, assumes that the phenotype is measured (or estimated) without error.
doi:10.1186/1471-2156-4-S1-S83
PMCID: PMC1866523  PMID: 14975151
19.  Identifying rare variants from exome scans: the GAW17 experience 
BMC Proceedings  2011;5(Suppl 9):S1.
Genetic Analysis Workshop 17 (GAW17) provided a platform for evaluating existing statistical genetic methods and for developing novel methods to analyze rare variants that modulate complex traits. In this article, we present an overview of the 1000 Genomes Project exome data and simulated phenotype data that were distributed to GAW17 participants for analyses, the different issues addressed by the participants, and the process of preparation of manuscripts resulting from the discussions during the workshop.
doi:10.1186/1753-6561-5-S9-S1
PMCID: PMC3287821  PMID: 22373325
20.  Association of 25-hydroxyvitamin D with Blood Pressure in Predominantly 25-hydroxyvitamin D Deficient Hispanic and African Americans 
American journal of hypertension  2009;22(8):867-870.
Background
Several observational studies have recently suggested an inverse association of circulating levels of vitamin D with blood pressure. These findings have been based mainly on Caucasian populations; whether this association also exists among Hispanic and African Americans has yet to be definitively determined. This study investigates the association of 25-hydroxyvitamin D (25[OH]D) with blood pressure in Hispanic and African Americans.
Methods
The data source for this study is the Insulin Resistance Atherosclerosis Family Study (IRASFS), which consists of Hispanic- and African-American families from three U.S. recruitment centers (n=1334). A variance components model was used to analyze the association of plasma 25[OH]D levels with blood pressure.
Results
An inverse association was found between 25[OH]D and both systolic (β for 10 ng/mL difference= −2.05; p<0.01) and diastolic (β for 10 ng/mL difference= −1.35; p<0.001) blood pressure in all populations combined, after adjusting for age, sex, ethnicity and season of blood draw. Further adjustment for body mass index (BMI) weakened this association (β for 10 ng/mL difference= −0.94; p=0.14 and β for 10 ng/mL difference = −0.64; p=0.09, respectively).
Conclusions
25[OH]D levels are significantly inversely associated with blood pressure in Hispanic and African Americans from the IRASFS. However, this association was not significant after adjustment for BMI. Further research is needed to determine the role of BMI in this association. Large, well-designed prospective studies of the effect of vitamin D supplementation on blood pressure may be warranted.
doi:10.1038/ajh.2009.88
PMCID: PMC2865679  PMID: 19444222
Vitamin D; 25-hydroxyvitamin D; blood pressure; hypertension; race; ethnic groups; Hispanic; African American

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