Approximately 20 million adults in the U.S. with diabetes are of low-income and minority populations. This population has an increased vulnerability to diabetes due living in high-stress environments, victimization from violent crimes, family history of domestic violence, personal histories of child physical and/or sexual abuse, and witnessing repetitive community violence. Common health disparities are often overlooked and access to appropriate medical care can be limited. Patient education for diabetes does not address how these previous traumatic experiences affect patients' ability to be compliant with their diabetes treatment plan.
While the effects of mental trauma on health disparities related to Type 2 Diabetes have focused largely on major depression, there is growing evidence that posttraumatic stress disorder (PTSD) is also associated with chronic disease and with poorer health outcomes. A potential contributing factor to the detrimental effects of PTSD and self-management for diabetes is an individual’s difficulty with regulating emotions and stress. Customized modifications of diabetes self-management could help increase patient engagement in both PTSD treatment and compliance with their own diabetes treatment plan. This study will be the first to examine effects of mental trauma as a contributor to the link between trauma exposure and diabetes self-care. The sample population consists of adults that are predominantly from ethnic minority groups (Latino and African American) and all are un-insured, lower socioeconomic families.
In this study, we will be able to look at electronic medical records of patients at two community clinics (Harvest Free Community Clinic and East Cooper Community Outreach (ECCO)) that are well-respected and trusted by this underserved and high needs population.
Individuals will be asked if they would be interested in participating in our survey study, which would involve completion of self report survey to gather information about each patient's emotion regulation, interpersonal violence and abuse history, PTSD symptoms, depression, daily diabetes self management activities, and positive/negative mood. Staff will also gather information from their electronic medical record (EMR) about their HbA1C, medications, other chronic conditions, BMI, and glucose levels. Most importantly, 10 of the participants will be asked to join in a group feedback session with the researchers to share from their perspective what their barriers are to managing their diabetes so that this information can be incorporated into appropriate health interventions.
While some studies may link the connection between PTSD and diabetes with biological changes in the stress regulating systems of the body (e.g., dysregulation of stress reacting hormones like cortisol), this study will determine whether the socio-emotional aspects related to health decision making behaviors may also lead to the development of type 2 diabetes and continue to contribute to poor management of diabetes.
Emotion regulation refers to how each individual handles intense emotions and/or stress (e.g., overeating, becoming more sedentary, impulsive poor choices, forgetfulness). By examining the role of emotion regulation in diabetes management, we can tailor diabetes self management to increase patient engagement in compliance with diabetes treatment plans as well as patient engagement in treatment for PTSD symptoms.
In addition to recruiting enough patients (100) to conduct analyses that are reliable and accurate, we are also relying on the input of patients from this victimized population, who can tell us first-hand what obstacles may be affecting their diabetes self management and can let us know what strategies will be most accepted in their community and how best to share this information with the community in need.
Results from the proposed study will provide pilot data for the NINR R21 application to develop proper modifications to PTSD treatment and/or customized diabetes self-care activities to prevent patient drop-out and/or noncompliance.
Late-onset Alzheimer’s disease (AD), the most common form of dementia, places a large economic and financial burden on families and society and can be emotionally devastating to loved ones. While we know several things can affect AD, it is an incredibly complex disease, and there are likely other risk factors of AD that we still don’t understand.
Over the past two decades cardiovascular disease (CVD) is being increasingly recognized as an important risk factor of AD. In this project, we are interested in seeing if there are specific changes to genes that are risk factors for CVD and risk factors for Alzheimer’s disease. If we can find genetic risk factors that overlap between CVD and AD, we could target these genes to prevent or delay the onset of Alzheimer’s disease.
One way to identify the genetic risk factors for CVD that are also risk factors in AD is through large-scale genome-wide association studies (GWAS). In GWAS, human genomes – typically ones without a disease and ones with a disease – are compared to see if there are specific changes (or ‘genetic variants’) in the genomes of individuals with a specific disease.
In this project, we plan to take GWAS a step further by using the genomes of patients with CVD to find new genetic risk factors for AD. By using this approach, we intend to identify a subset of genetic variants that are risk factors for dyslipidemia, inflammation (two CVD traits that can be treated and prevented) and AD. As a second step, to understand the role of these risk factors in AD, we will then investigate the relationship between each of these genes and known pathobiological markers of AD.
1) Identify and validate genetic variants associated with AD and CVD traits. We plan to use GWAS to identify genetic variants that are common to traits of CVD (dyslipidemia and inflammation) and AD.
2) Determine the effect that these common genetic variants have on clinical and neuropathological measures of AD. We will determine the relationship between AD/CVD genetic risk variants and the presence of markers known to be elevated in AD.
Late-onset Alzheimer’s disease (AD), the most common form of dementia, effects an estimated 30 million people worldwide, a number that is expected to quadruple in the next 40 years. In the brain (or ‘neuropathologically’), AD is characterized by the presence of amyloid-beta plaques and tau-associated neurofibrillary tangles. Since there are no current disease-modifying therapies and there has been an increasing awareness that symptoms of AD develop over many years, there is a strong need to develop effective strategies to prevent AD. If we could even delay the onset of dementia by a modest 2 years, we could potentially lower the worldwide prevalence of AD by more than 22 million cases over the next 40 years.
Although previous studies have examined the association between AD and CVD traits, no study to date has fully identified the genetic and molecular basis of how dyslipidemia and inflammation influence AD. This project will provide us with a clearer understanding of how CVD and AD are related.
Additionally, this study is the first step in research that is expected to lead to the development of novel strategies for preventing AD. Dyslipidemia and inflammation are effectively managed through current therapeutics; therefore, if we can identify an overlap between the genetic variants causing these CVD traits and AD, we could use drugs targeting dyslipidemia and inflammation to also treat, prevent, or delay AD.