Selected Abstracts from Approved DNA Committee Applications


Cardiovascular Risk in Relation to Adducin Polymorphisms in the Framingham Heart Study

PI: Giuseppe Bianchi

A recent longitudinal population study suggested a role of ADD1 Gly460Trp polymorphism alone or in association with the ACE I/D polymorphism as a predictor of cardiovascular risk. Aims: to study association of ADD1, ADD2 and ADD3 loci polymorphisms (Gly460Trp, C1797T, IVS10+386A>G respectively) and between ADD1 Gly460Trp and ACE polymorphism to cardiovascular events and blood pressure

Validation of 100K Genome-Wide Association Study Findings for Subclinical Atherosclerosis Measures in Multiple Vascular Beds-Carotid Intimal Medial Thickness, Coronary Artery and Abdominal Aortic Calcium Deposits, and Ankle Brachial Index

PI: L. Adrienne Cupples
Christopher J. O'Donnell

Atherosclerosis in the arterial wall of the aorta, carotid, and coronary arteries precedes the onset of clinically apparent cardiovascular disease by decades. A number of subclinical atherosclerosis measures have been obtained in the Framingham Heart Study, including measures of atherosclerotic disease in the carotid arteries using carotid ultrasonography, the coronary arteries and the abdominal aorta using multidetector computed tomography, and the lower extremities using ankle-brachial blood pressure measurements. All of these traits have been found to have moderate heritability. We previously conducted a study of association between 100K SNPs genotyped in Offspring families and these traits. In this project, we aim to seek independent evidence in unrelated subjects in the FHS for the significant associations detected in the family plates. In this way, we seek to identify "validated" subclinical atherosclerosis genotype-phenotype associations that may be carried forward for replication in other independent cohorts.

Genetic Polymorphisms Related to Metabolic Syndrome and Its Individual Components

PI: Joseph Devaney, PhD

Of the five sub-phenotypes defining metabolic syndrome, all are known to have strong genetic components (typically 50-80% of population variation). To identify these genetic components, we have studied 610 young adult volunteers (average age 24 yrs), and measured metabolic syndrome markers at baseline, as well as response of muscle, fat, and bone tissue volumes to a 12 week supervised resistance training intervention. Using this data, we have identified 37 SNPs in 10 genes (AKT1, AKT2, ANKRD6, BCL6, BMP2, INSIG2, MYLK, PGC-1a, PPARA, TPD52L1) that have shown associations with components of metabolic syndrome and subcutaneous fat. We hypothesize that these genetic variants will be associated with similar variables in the 1888 unrelated individuals in the Framingham study. Logistic regression models will be used for assessing SNP effects adjusted for multiple non-genetic covariates. The data generated from this study will be extremely useful in pinpointing some of the genetic causes of metabolic syndrome and may present targets for future drug therapies.

Structural Equation Modeling of Genotype by Environment Interaction in Coronary Heart Disease

PI: Kent M. Eskridge, Ph.D.

Coronary Heart Disease (CHD) is a complex disease involving multiple genetic and environmental risk factors. Genotype-by-environment interactions play an important role in the development of CHD. An understanding of GEI on the prevalence of CHD will provide insights into the development of new strategies for the diagnosis, prevention and treatment of CHD. The reported GEI variability may due to the pleiotropic and indirect effects. Structural equation modeling (SEM) is a multivariate approach that allows one to account for indirect effects and pleiotropy by simultaneously analyzing a system of equations where each equation describes a causal relationship among variables considered in the system. Also genetic studies have identified markers associated with major risk factors, but it is not known whether these marker genotypes have interaction with environmental risk factors. The objectives of this project are (1) to identify the gene, and gene by environment interactions in the development of CHD using a three-level structural equation modeling approach, (2) to improve the precision of estimates by adjusting for hierarchical nesting structures and repeated measures, and (3) to evaluate the advantages of the proposed model over the single equation approach in terms of interpretation and fit. The phenotypes to be studied are blood glucose (BG), systolic blood pressure (SBP), high density lipoprotein (HDL), and total cholesterol (TC). The real existing data at Framingham Heart Study will be used for analysis.

Evaluation of Genetic Factors Underlying AF in a Community-based Population

PI: Diane Fatkin, MD

Atrial fibrillation (AF) is the most common heart rhythm disorder and a major risk factor for heart failure and stroke. Recent data suggest that genetic factors can cause AF. In support of this, over the years several families in which AF is inherited have been reported and as a result, 5 genes and 4 genetic regions responsible for AF have been identified. We propose that genetic factors also underlie sporadic AF and that certain common genetic variations within the population predispose individuals to developing the disease when combined with environmental factors. In particular, high blood pressure may be a factor which together with a predisposing genetic variation may trigger AF. The Framingham Heart Study (FHS) is a multi-generational research study that has evaluated cardiovascular risk factors in a community-based population. The FHS dataset, including clinical data and genetic information derived from studies of genetic variations (single nucleotide polymorphisms or SNPs) represent an ideal resource for population-based association studies. We are seeking to gain access to this dataset to statistically evaluate the role of genetic and environmental factors in the development of sporadic or non-familial AF.

Relationship Between Heterozygosity, Cardiac Aging and Health

PI: Diddahally R. Govindaraju, PhD
Ramachandran S. Vasan, MD

We propose to study the relationship between heterozygosity as estimated from genome-wide single nucleotide polymorphisms and components of cardiac aging and health in Framingham Offspring Study cohort. Heterozygosity has been shown to play an important role in conferring disease resistance, increased fitness, and provide buffering capacity against environmental perturbations, termed genetic homeostasis, in many organisms. Heterozygosity, as measured by using novel classes of molecular markers such as microsatellites and SNPs, has been related to both Mendelian and complex diseases, and has been associated with dosage-sensitive gene regulation of phenotypic expression. Nonetheless, key questions remain unanswered on the potential advantage (or disadvantage) of the degree of heterozygosity at different levels of the genome organization in humans - entire genome, individual sections of the genome (e.g. HLA cluster) or specific sites. This exploratory study will help elucidate the role of heterozygosity in cardiac aging. Additionally, our investigation may shed light on several long standing questions such as the role of dominance on the maintenance of quantitative variation in humans, which in turn may offer evolutionary insights.

Genetics of Bone Structural Geometry in Framingham Cohorts

PI: David Karasik, Ph.D.

Bone geometry and muscular geometry (shape and size) are important predictors of skeletal fragility (osteoporotic fracture) and loss of muscle strength due to sarcopenia, respectively. In this competing renewal for the project "Genetics of Bone Structural Geometry: Framingham Cohorts", we propose to expand our current study of the genetics of bone geometry in several ways: by using state-of-the-art imaging of a spinal cross-sectional bone area and novel muscle area/muscle mass measurements at the spine and hip by quantitative computed tomography (QCT); by linkage and association study with genome-wide SNP data from the "Framingham Heart Study SNP Health Association Resource" (FHS SHARe Project); and by focusing on several specific pathways through which we expect genes to exert their action on the skeleton and muscle.

In our proposed work, we will apply a genome-wide dense SNP strategy to find genes that are linked or associated with both bone and muscle geometry as well as a biological candidate gene strategy, using data from three generations of the FHS (Original Cohort, Offspring Cohort, and Generation III). Identifying significant genetic variants underlying both bone and muscles measured with the novel state-of-art technology may lead to important potential targets for risk stratification and therapy of osteoporotic fractures and sarcopenia.

Validation in the Framingham Heart Study of Genetic Variants Associated with Metabolic Syndrome

PI: Jennifer K. Lowe, PhD

We are investigating the genetic basis of metabolic traits, including type 2 diabetes, obesity, dyslipidemia, and hypertension. To this end, over 3000 individuals from the island of Kosrae, in the Federated States of Micronesia, were ascertained and genotyped using the Affymetrix 100k assay. Increased linkage disequilibrium and decreased haplotype diversity in this population facilitate mapping variants that influence complex genetic traits. Using the Framingham Heart Study cohort, we propose to replicate genome-wide significant findings and validate the best 50 associations identified in Kosraens for type 2 diabetes, BMI, total cholesterol, LDL, HDL, systolic and diastolic blood pressure.

Associations of Genetic Variation at the Sex-Hormone Binding Globulin Locus with Sex-Hormone Binding Globulin Levels, Sex Hormones, Cardiovascular Risk Factors, and Bone Density

PI: Joanne Murabito, MD
Ramachandran S. Vasan, MD

We hypothesize that common genetic variation at the SHBG locus influences inter-individual variability in SHBG levels, endogenous sex hormones (testosterone and estradiol), body mass index and lean mass, metabolic traits, physical function, and bone density. We aim to test this hypothesis by studying the association of common SNPs at the SHBG locus with SHBG levels and related phenotypes. We will genotype 11 tag SNPs that cover the common sequence variation at SHBG. We will use multivariable linear regression to test the association between SNP genotype and phenotypes.

Functional Analysis of Longitudinal Data from Genetic Studies of Age-related Traits

PI: Yuanjia Wang

The goal of this project is to use functional data analysis techniques to develop new statistical methods for longitudinal genetic data measured from age-related quantitative traits. We first propose to incorporate family structure information into functional principal components analysis to examine polygenic heritability in longitudinal phenotypes before obtaining genetic markers. We then propose to use functional basis expansion to capture the time-varying genetic effect and estimate age-specific QTL heritability in variance components models. The flexibility of basis expansion allows for the identification of temporal patterns of genetic variation of any shape. Within this functional mapping framework, research questions such as when is a quantitative trait locus switched on to affect a trait and how long will the genetic effect last can be answered. We also investigate methods to include time-varying covariates. We will investigate our proposed methods through Genetic Analysis Workshop 13 (GAW13) data from the Framingham Heart Study. Results from this project will be compared to that in the literature.

Heritability and Linkage to Radiologic Measures of Adiposity: the Framingham Heart Study CT Sub-Study

PI: Caroline Fox, MD, MPH
Joel N. Hirschhorn MD, PhD

Goals: To test whether variants in genes that associate with obesity, DM, IFG and dyslipidemia also associate with fatty liver in the offspring and 3rd generation samples. We will be testing variants in the genes INSIG2, CETP, APOA5, LIPC, LPL, APOE, PCSK9, KCNJ11, PPARG, TCF7L2, APOB, NEIL1. In a separate proposal we would also like to test whether SNPs from the 500K also associate with fatty liver.

Phenotypes: Liver fat
Laboratory Methods: Variants in specific genes will be tested for association to fatty liver in the FHS offspring and 3rd generation samples.
Analytical Approach: Linear and longitudinal regression techniques with permutation or using generalized estimating equations (to account for relatedness) will be used for SNP association analyses.

Genetics of Vasorelaxation and Cardiovascular Responses

PI: Gordon Huggins, MD
David Housman, PhD

Common genetic contributors to high blood pressure are unknown. Genes that control blood vessel constriction critically regulate blood pressure, and can affect blood vessel thickness. We hypothesize that variants in genes that control blood vessel contraction are associated with hypertension and blood vessel thickness in humans. To test this hypothesis we studied the association of polymorphisms in the 100K FHS genome-wide study that are contained within genes important for blood vessel wall constriction with blood vessel phenotypes. From that analysis we identified markers associated with artery thickness and blood pressure. We now propose to extend these observations by testing the association of related markers with blood pressure and carotid artery thickness in the FHS offspring and family cohorts. In addition we will study the association of these markers with the requirement for blood pressure treatment and the timing of hypertension onset. For continuous variables, such as blood pressure, we will use analysis of variance while for a dichotomous variable logistic regression models will be used. Related individuals will be analyzed using family based association testing. In summary, we will determine if variants of genes important for blood vessel contraction and relaxation are associated with heart and blood vessel disorders, including blood pressure.

Genetics of Bone Density and Structural Geometry in Framingham Cohorts II

PI: Douglas P. Kiel, MD, MPH
David Karasik, PhD

This proposed study is an extension of R01 AR050066-01 "Genetics of Bone Structural Geometry: Framingham Cohorts" (to D. Karasik), with a primary aim to identify linkage of bone geometry indices with a set of autosomal microsatellite markers, and R01 AR/AG 41398 "Risk Factors for Aged Related Bone Loss" (to D. P. Kiel), which includes analysis of candidate genes for bone mineral density. Osteoporosis is a common, age-related disease with a strong genetic component. With increasing age of the population, Europe is facing a substantial increase in osteoporotic fractures, which account for considerable disease-burden and costs. Early identification and treatment of subjects at risk can help preventing this. Gene polymorphisms which predispose to osteoporosis are the most promising risk factors. The goal of this project is for the two grants above that fund the Framingham Osteoporosis Study to contribute data from the study of candidate genes that are genotyped by the Framingham Study Genetics Laboratory to planned meta-analyses from Europe's largest population studies on osteoporosis. Phenotypes to be studied include highly heritable bone mineral density, as well as geometric indices of the proximal femur derived from cross-sectional cortical measurements. All genotyping will be done by the Framingham Genetics Laboratory. These meta-analyses will be used to develop sufficient power to detect small, but clinically important risks that would otherwise not be possible using only Framingham Study data. The project will result in a collection of osteoporosis risk-alleles with quantified risks. Such genetic markers will improve clinical risk-assessment for osteoporosis.

FHS - HSPH Collaboration for the Development of New Statistical Tools for the Analysis of Genome-wide Association Studies

PI: Christoph Lange

We will develop new statistical analysis methods for genome-wide association studies and apply them to the 100k-scan in Framingham Family plate set (n=1400). We will report back interesting findings to the investigators of the Framingham Heart Study. The analysis will be published as part of our methodology papers. The methods will be implemented in our freely available software packages.

Effect of Mutations in Renal Ion Transport Pathways on Bone Density

PI: Richard P. Lifton, PhD

Hypertension is a complex multifactoral disease that affects over 20% of the adult population in the US known to be a major risk factor for morbidity and mortality. Mutations that alter renal salt handling underlie Mendelian forms of high and low blood pressure. Recessive loss-of-function mutations in many genes in this pathway cause reduced blood pressure. We estimate that loss of function mutations in each of these genes are present in 0.3 - 1% of the population, and that heterozygous mutations in genes of this pathway lower blood pressure and protect from development of hypertension; in addition, a number of these alter renal calcium reabsorption, and we hypothesize that these result in altered bone mineral density and susceptibility to osteoporosis. We will screen 3125 individuals from the offspring cohort of the Framingham Heart Study for mutations in these genes and analyze their impact on these quantitative traits.

Gene/Diet/Plasma Lipid Interactions: Characterization of Informative DNA Blocks.

PI: Jose M. Ordovas, PhD

Cardiovascular disease (CVD) is the result of complex interactions between genetic and environmental factors. During the last few decades, much attention has focused on plasma lipoproteins as CVD risk factors. The current evidence supports the concept that gene-environment interactions modulate plasma lipid concentrations and potentially CVD risk. The findings from studies examining gene-diet interactions and lipid metabolism have been highly promising. Several loci [i.e., APOA1, APOA4, APOA5, APOB, APOC3, APOE, CETP, LPL, LIPC, PPARA, PPARD, PPARG] are providing proof-of-concept for the potential application of genetics in the context of personalized nutritional recommendations for CVD prevention. However, the incorporation of these findings to the clinical environment is not ready for prime time. There is compelling need for replication using a higher level of scientific evidence. Moreover, we need to evolve from the simple scenarios examined nowadays (i.e., one single dietary component, SNP and risk factor) to more realistic situations involving more functional alleles, interactions among multiple genes, dietary components and risk factors. Therefore, we propose to carry out denser genotyping of a number of relevant candidate genes (those previously approved plus the newly requested PPARD and APOA2) in subjects for which dietary habits and plasma lipid levels are known in order to provide a more precise definition of nutrigenetics of plasma lipids and other variables related with the metabolic syndrome.

Association of Variation in Nuclear Receptor Co-activator 1 Gene and Microsatellites in Other Estrogen-Related Genes with Circulating Steroid Hormone Levels in the Framingham Heart Study

PI: Inga Peter, PhD

Strong biological evidence supports the beneficial effect of estrogen on the human body. Despite various studies suggesting substantial role of genes involved in estrogen metabolism in the development of complex traits, the molecular mechanisms underlying these associations are still unclear. Given that steroid hormones are heritable traits and that significant background genetic effects may modify their circulating levels, we hypothesize that variations in the estrogen receptor-a and ß, aromatase, and nuclear receptor coactivator 1 genes are associated with serum steroid levels. To test this hypothesis we propose to use existing genotypes and test their association with total testosterone, estradiol, and dehydroepiandrosterone sulfate levels measured in the Framingham Heart Study's (FHS) Offspring cohort of unrelated individuals at the 3rd and 4th examination cycles. Analysis of covariance will be employed to test the association between the steroid levels and genotypes for the 12 SNPs and 4 microsatellites under study adjusting for age, sex, body mass index, smoking, alcohol intake, and diabetes status.

Based on the associations between polymorphisms in these genes and cardiovascular endpoints in the FHS cohort detected by our previous studies, differences in steroid levels between carriers of various polymorphisms may help shed light on pathophysiology of cardiovascular disease.

Analysis of Framingham Reynolds Genes in Relation to Telomere Length

PI: Abraham Aviv, MD
Daniel Levy, MD

The investigators hypothesize that variability in leukocyte telomere length (LTL) can be explained by genetic variants in critical growth factor and inflammatory pathway genes. Gene variants of the insulin-like growth factor receptor 1 (IGF1R) will be analyzed for association with LTL in the Framingham Offspring cohort. The investigators also want to determine potential associations of LTL with other genes in the critical growth factor and inflammatory pathways.

The Genetics of Atrial Fibrillation: Identification of Common AF Variants Using a Whole Genome Association Study and Validated Myocardial Repolarization Variants

PI: Emelia Benjamin, MD, ScM
Patrick Ellinor, MD PhD

The investigators propose to identify the common genetic determinants of atrial fibrillation by validating the results a whole genome association study conducted on 100K SNP data from the Framingham Heart Study. The results of the association study revealed 50 SNPs that were determined to be significantly associated with atrial fibrillation; these results will be validating using the Framingham Original and Offspring Cohorts as well as the Massachusetts General Hospital AF Study participants. Certain existing genotypes will also be investigated for association with atrial fibrillation.

Genetics of Water Balance

PI: David Cohen, MD

The researchers propose to determine genetic components that result in abnormal water balance. The 100K SNP data and other clinical variables/phenotype data will be analyzed for significant associations with systemic water imbalance.

Investigation of Association and Replication of Variants in KIF6, KLOTHO, TCF2, and NPHS1 with Chronic Kidney Disease

PI: Josef Coresh, MD, PhD

The investigators seek to replicate the genetic findings of the ARIC Study. In this study, an association between genetic variation of the KIF6 gene and Chronic Kidney Disease were determined. The researchers also propose to investigate the association of common variants in candidate genes with kidney function measures in the Framingham Heart Study participants.

Assessment of Association between 100K SNP Data with Glycemic-Traits: Application of Alternation Method of Analysis

PI: Josee Dupuis, PhD

The investigators are exploring strategies for conducting association studies that produce informative results and are cost-effective. They have developed strategies based on multipoint identity-by-descent (IBD) sharing and/or quantitative variables, which they believe to fit both criteria. They now want to use diabetes-related quantitative traits and 100K SNP data to apply and validate their strategies.

Effects of Selected SNPs in the TCF7L2 Gene on Glycemic and Obesity Traits

PI: Jose Florez, MD, PhD

SNP rs7903146 in the gene TCF7L2 was found to be significantly associated with the prevalence of type 2 diabetes. However, the relationship between the presence of this polymorphism and BMI is intriguing as people who are carriers for this risk genotype have lower BMI. The objective of this proposal is to elucidate the relationship of the SNP to BMI measures by using data from the Framingham Heart Study cohorts.

Is There an Association between SNPs in the Multiple DM Pathways and Measures of Adiposity?

PI: Caroline Fox, MD, MPH

The investigators hypothesize that variants in genes associated with type 2 Diabetes Mellitus might also be associated with obesity-related traits. They propose to evaluate candidate genes for type 2 DM and genes in the endocannabinoid pathway to look for association with adiposity phenotypes. Phenotype data were requested in the application. The investigators had previously received and genotyped DNA received from Framingham.

Identification of Common DNA Sequence Variants Associated with ALT and AST a Genome-wide Association Scan

PI: Wolfram Goessling, MD, PhD

The investigators propose to identify genetic variants related to elevated levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST). ALT and AST are associated with the incidence of hepatitic manifestation of the metabolic syndrome (MetS) and Diabetes Mellitus (DM) as indicated by the results of a study conducted on the Framingham Offspring Cohort. The investigators wish to conduct a follow-up study on these initial results.

Age Related Structural Variations in the Framingham Heart Study Population

PI: Charles Lee, PhD
Diddahally R. Govindaraju, PhD

The investigators propose to study age related structural genomic variations among the Framingham Heart Study participants. The molecular approaches utilized in this research will help determine the frequencies of copy number variations in the Framingham population as well determine inheritance patterns and stability of these variations. Research results will be utilized to postulate mechanisms for the emergence of copy number variations.

Type 2 Diabetes Phenotype and Genotype Risk Prediction Models in the Framingham Heart Study

PI: James Meigs, MD, MPH

A phenotype and genotype diabetes risk prediction model will be developed and tested as part of this research proposal. A Phenotype Risk Score and a Genotype Risk Score will be developed. The investigators hypothesize that the risk of incident diabetes increases with the number of risk alleles present. They also posit that the Genotype Risk Score is instrumental in determining if one has a risk for developing diabetes as well as reclassifying risk status.

Estimation of Deleterious Mutations in Humans

PI: Shamil Sunyaev, PhD
George Church, PhD

The investigators seek to get accurate measurements of mutation rates in humans. All exons in the genome of 1300 Framingham subjects will be sequenced. The investigators seek to determine the level of natural selection in utero, to estimate the rate of deleterious mutations in populations similar to that of Framingham, and to conjecture on evolutionary mechanisms for these mutations.

Validation in the Framingham Heart Study of Genetic Variants Associated with Metabolic Syndrome

PI: Jennifer Lowe, PhD

The investigators seek to identify common genetic factors that influence one's susceptibility to developing Metabolic Syndrome. The investigators have genotyped 3000 individuals from the island of Kosrae in Micronesia using both the 100K and 500K mapping assays. They now want to incorporate the results of the 500K study into the original objectives of the application. To that end, they request permission to include several traits to be used in their analyses; these traits include fasting glucose and blood lipid measures. Framingham data will be used to replicate the Kosrae results.

Validation of 100K Genome-Wide Association Study Findings for Subclinical Atherosclerosis Measures in Multiple Vascular Beds - Carotid Intimal Medial Thickness, Coronary Artery and Abdominal Aortic Calcium Deposits, and Ankle Brachial Index

PI: L. Adrienne Cupples, PhD
Christopher O'Donnell, MD, MPH

In the original application, the investigators proposed to validate and replicate the initial findings of a 100K scan for subclinical atheroscelerosis phenotypes. They now seek permission to conduct follow-up genotyping on a larger number of SNPs than originally requested.

Fine-mapping of Novel QT Loci Identified through Genome-wide Association Analysis of QT Interval Duration in FHS Unrelated Plate, Related Plate, and Generation 3 Participants

PI: Christopher Newton-Cheh, PhD

The investigators have conducted a candidate gene and genome wide association study on continuous QT interval during using Framingham data. They have now identified 4 loci that influence this trait. Therefore, they seek permission to utilize these loci to finish the finemapping of associations. They also want to determine other variants at the loci as well as produce multi-SNP models that predict the incidence of the phenotype.

Validation of Polymorphic Gene Sequence Variants Contributing to Extremes of Blood Pressure in the Framingham Heart Study

PI: Christopher Newton-Cheh, PhD
Daniel Levy, MD

The investigators originally re-sequenced over 100 individuals with extreme blood pressure measurements. They now want to genotype SNPs identified through this re-sequencing effort.

Type 2 Deiodinase Thr92Ala Polymorphism and Risk for Development of Hypertension

PI: Ana Luiza Maia, MD, PhD
P. Reed Larsen, MD

The researchers hypothesize that the Thr92Ala polymorphism, a Type 2 deiodianse SNP A/G in humans might be associated with hypertension. This research extends upon prior research which evaluated the presence of an association between Thr92Ala with diabetes intermediate trait levels and Diabetes Mellitus 2 risk.

Investigation of Genes Previously Implicated in Stroke

PI: Philip A. Wolf, MD

In the original application, the investigators wanted to conduct association studies on stroke and stroke related phenotypes and genotype data from the Framingham Heart Study. They were interested in genotyping the ALOX5AP and PDE4D genes in particular. To this end, they had request custom plates to genotype all Framingham subjects with stroke events and brain MRI measures. With the advent of the 550K SHARe Initiative, a new 550K plate set has been created. Therefore, the researchers propose to conduct genotyping on this new plate set, instead of the custom plates originally requested.

Evaluation in the Framingham Heart Study of Polymorphisms Previously Reported to be Associated with Measures of Obesity

PI: Joel N. Hirschhorn MD, PhD

The original objective of this project was to test genes for association with BMI. 74 SNPs were initially proposed to be genotyped, of which 72 have been genotyped. The researchers want to use the results from the original study to assess association of SNPs to obesity for more genes. Permission to conduct this genotyping is requested; the researchers will utilize extant DNA for the genotyping.

Request to Follow-up 100K Results with Additional Genotyping

PI: Emelia Benjamin, MD, ScM
Juan-Pablo Casas, MD

The aims of the initial proposal were to investigate and identify the genetic and environmental determinants of systemic inflammation. The researchers now seek permission to collaborate with the CRP Coronary Disease Genetics Collaboration. The goal of this international initiative is to generate data on 3 variants of the C-reactive protein (CRP) gene to utilize in a case-control study.