Jeanne M. McCaffery, Ph.D. - US grants

DESCRIPTION (provided by applicant): It is now well established that depressive symptoms predict coronary artery disease (CAD), both in community samples with no known CAD and among patients who have already experienced a clinical event. Nonetheless, the mechanisms underlying this association remain unclear. Of the proposed common mechanisms, the potential for common genetic variants to contribute to both depression and cardiovascular disease has received little attention to date. Depression and CAD morbidity and mortality are each heritable in twin and family studies. In addition, the one twin study to address covariation of depression and CAD suggested that 43 percent of the common variance between depressive symptoms and CAD was attributable to common genetic effects. In this proposal, we aim to target genes coding for components of three plausible biological pathways, inflammation, serotonin-mediated platelet aggregation and omega-3 metabolism, as a first step in identifying candidate genes that may account for the association between depressive symptoms and CAD. Specifically, we will haplotype: 1) ICAM-1, IL6, and CRP within the inflammation pathway; 2) the genes that code for the serotonin2 receptor (5HT2) and the serotonin transporter (5HTT), mediating serotonin-induced platelet aggregation; and 3) the genes that code for delta-6 desaturase (FADS2) and delta-5 desaturase (FADS1), essential to omega-3 fatty acid metabolism. Participants will be 1074 individuals with established CAD and 462 age- and sex- matched controls. Depressive symptoms will be characterized from responses to the Beck Depression Inventory (BDI). Importantly, all participants are of French-Canadian descent (self-report of four grandparents of French-Canadian descent). French-Canadians are a homogeneous, founder population, indicating a simpler haplotype structure and reduced risk of population substructure or admixture, thereby, substantially improving the likelihood of detection of genetic association.

[unreadable] DESCRIPTION (provided by applicant): Cardiovascular disease (CVD) affects approximately 60,800,000 Americans each year, claiming the lives of nearly one million of these people (American Heart Association, 2001). CVD is likely to be complex in etiology, reflecting the combined effect of both genes and environment, as well as gene x gene and gene x environment interaction. Examination of environmental factors thought to affect CVD risk in the context of a genetically informative design can help elucidate the relative contribution of genetic and environmental factors and potentially aid in identifying environmental factors that may interact with genetic vulnerability in predicting CVD. Cardiovascular morbidity and mortality are over-represented among individuals in lower socioeconomic strata, as are behaviors that increase the likelihood of cardiovascular events, including smoking, heavy alcohol consumption and physical inactivity (Adler et al., 1994; Anderson & Armstead, 1995). Thus, it is commonly assumed that socioeconomic status (SES) serves as an important environmental influence on health and health behaviors. Twin studies partition genetic and environmental variance and detect gene x environment interaction and provide a unique opportunity to study the association between SES and health. The goal of this application is to further characterize the nature of the association between SES, health behaviors and early CVD in the Vietnam Era Twin (VET) Registry, a sample of over 4,000 twin pairs. Specifically, we plan to: 1) determine how strongly environmental factors contribute to individual differences in SES, health behaviors and CVD, relative to genetic factors; 2) examine whether measures of SES are associated with health behaviors and CVD mortality when controlling for concomitant genetic influences; and 3) investigate whether SES interacts with genetic vulnerabilities to predict health behaviors and CVD (gene x environment interaction). The primary method of analysis will be twin structural equation modeling. [unreadable] [unreadable]

DESCRIPTION (provided by applicant): Obesity is a major public health problem, with millions of Americans suffering from weight-related health complications, including Type 2 diabetes, coronary heart disease, hypertension, and osteoarthritis. Behavioral weight loss intervention has emerged as a key strategy in combating obesity and the associated health consequences. However, individuals differ in their degree of success in these programs and genetic factors are known to play a role. In this application, we propose to identify specific genes that predict individual differences in weight loss in response to behavioral intervention to help identify individuals who struggle with weight loss despite behavioral efforts. Specifically, we will determine whether obesity genes interact with lifestyle intervention in predicting weight loss at year 1 of the Look AHEAD trial (U01DK056992), an NIH-funded, multi-center randomized controlled trial with the primary goal of determining whether weight loss achieved through an intensive lifestyle intervention can reduce cardiovascular morbidity and mortality among persons with type 2 diabetes. At year 1, participants assigned to Intensive Lifestyle Intervention (ILI), focusing on changes in diet and physical activity, lost an average of 8.6% of their weight (N= 2,496;97.1% follow-up) relative to losses of 0.7% among individuals assigned to the Diabetes Support and Education (DSE) group (N= 2,463, 95.7% follow-up), who received diabetes support and education groups alone. Consent for genetic analyses was provided by 3,759 participants. Genotype data from the IBC chip, including over 4,000 markers within genes previously associated with obesity, will allow us to test our central hypothesis that genes that predispose to obesity interact with lifestyle treatment to influence weight loss following intensive lifestyle intervention. We conduct these aims with the explicit goal of bringing together a team with expertise in behavioral research, genetic epidemiology and molecular biology to create transdisciplinary researchers who are able to bridge across the disciplines and identify key gene x behavior interactions in the context of the Look AHEAD trial. PUBLIC HEALTH RELEVANCE: The interplay of genetic and behavioral factors is critical to understanding obesity and behavioral weight loss intervention has emerged as a key strategy in combating obesity. In this application, we propose to identify specific genes that predict individual differences in weight loss in response to behavioral intervention to help identify individuals that struggle with weight loss despite behavioral efforts.

DESCRIPTION (provided by applicant): At least 65% of individuals with diabetes die of some form of heart disease or stroke. This occurs despite effective treatments for certain cardiovascular risk factors, such as high low-density lipoprotein (LDL) cholesterol and hypertension. High-density lipoprotein (HDL) cholesterol is a major cardiovascular risk factor that is often low among individuals with type 2 diabetes. Behavioral interventions targeting weight and/or physical activity are well known to improve HDL. At the same time, however, genome-wide association studies (GWAS) have been successful in identifying markers associated with HDL and twin studies suggest that HDL response to behavioral intervention is heritable. In this application, we propose to determine whether well established genetic predictors of HDL also predict individual differences in HDL response to weight loss and physical activity intervention. These efforts will help identify individuals who may be resistant to HDL change in response to behavioral efforts and may lead to tailoring of interventions to optimize treatment for these individuals. Specifically, we will determine whether HDL genes (CETP, LPL, LIPC, ABCA1 and LIPG) interact with lifestyle intervention in predicting change in HDL at year 1 and 4 of the Look AHEAD trial, an NIH-funded, multi-center randomized controlled trial with the primary goal of determining whether weight loss achieved through an intensive lifestyle intervention can reduce cardiovascular morbidity and mortality among persons with type 2 diabetes (grant #DK056992). At year 1, participants assigned to Intensive Lifestyle Intervention (ILI), focusing on changes in diet and physical activity (N = 2,496;97.1% follow-up), lost significantly more weight and showed greater improvements in fitness than individuals assigned to the Diabetes Support and Education (DSE) group (N= 2,463, 95.7% follow-up), who received diabetes support and education groups alone. The weight loss and improved fitness in the ILI at year 1 produced a significantly greater increase in HDL (7.8%), relative to DSE (2.9%). Greater increases in HDL in ILI relative to DSE are also seen at year 4. Consent for genetic analyses was provided by 3,990 participants. Genotype data for HDL markers identified from genome-wide association studies and from the IBC chip, a genotyping platform including 50,000 SNPs from ~2,600 genes relevant to cardiovascular disease, lipid metabolism, diabetes and obesity, will allow us to test our central hypothesis that genes that contribute to variability in HDL will interact with lifestyle treatment to influence changes in HDL following intensive weight loss and physical activity intervention. PUBLIC HEALTH RELEVANCE: Project Narrative Individuals with type 2 diabetes remain at increased risk for cardiovascular disease and mortality, potentially due to low high density lipoprotein (HDL) levels. Behavioral intervention, involving weight loss and physical activity, is known increase HDL. However, individuals differ in their degree of success in these programs and genetic factors may play a role. In this application, we propose to identify specific genes that predict individual differences in HDL response to behavioral intervention to help identify individuals that struggle with improving HDL despite behavioral efforts.

? DESCRIPTION (provided by applicant): This grant application responds to PA-15-169: Secondary Analyses in Obesity, Diabetes and Digestive and Kidney Diseases (R21) with an exploratory/developmental application designed to determine whether a copy number variant in salivary amylase (AMY1), recently shown for the first time to be associated with body mass index (BMI), 1) associates with BMI, dietary intake, fasting insulin and glucose in European-, African- and Hispanic-Americans, and 2) predicts weight loss, weight loss maintenance, insulin resistance and/or diabetes outcomes in two large behavioral weight loss trials. Specifically, we propose to add de novo genotyping of three variants in the AMY1 region (AMY1 CNV, AMY2 CNV and a new AMY1 microsatellite), and conduct secondary data analyses leveraging existing data from two of the largest behavioral weight loss trials conducted to date. Look AHEAD (Action for Health and Diabetes) Study is a multi-center randomized controlled trial with the primary goal of determining whether weight loss achieved through an intensive lifestyle intervention (ILI) can improve health outcomes among persons with type 2 diabetes. The Diabetes Prevention Program (DPP), a randomized clinical trial testing whether lifestyle intervention or metformin prevents or delays type 2 diabetes in high-risk individuals, provides an excellent replication cohort due to similarity in lifestyle intervention and dietary measurement. DPP further tracked insulin resistance and incidence of diabetes, providing a unique opportunity to test whether AMY1 predicts diabetes incidence over time and whether behavioral weight loss treatment may mitigate this association. Given the successful weight loss, excellent retention, large samples sizes with genetic consent (>7,000 combined) and extensive data collection in both of these studies, they provide outstanding opportunities to cost-effectively explore the role of the AMY1 region in BMI and diet as well as treatment outcomes related to weight loss, weight loss maintenance, and incidence of type 2 diabetes. Overall, this proposal will expand the breadth of knowledge regarding the phenotypes predicted by AMY1 and test for the first time potential treatment implications, beginning to lay the groundwork for optimizing obesity treatment and diabetes prevention based on AMY1 copy number.