A putatively functional polymorphism in the HTR2C gene is associated with depressive symptoms in white females reporting significant life stress.

In the early part of my career, my work generally focused on examining psychosocial determinants or correlates (e.g., emotion, personality, and socioeconomic status) of cardiovascular disease.  However, in the past several years, my work has also expanded to include examining how stressful emotional responses, combined with proposed genetic markers, influence metabolic functioning, cognitive decline, functional capacity and quality of live in the elderly, depressive symptomology, and major depressive disorder.  I also have an interest in statistical methodology. 

Since coming to Duke as an intern in 1994 I have collaborated as a biostatistician and co-investigator at Duke on numerous observational and experimental studies involving behavior, psychosocial factors, health, and disease. The substantive topics have ranged across questions concerning exercise and depression, hypertension, weight loss, the genetics of stress and heart disease, sickle cell disease, to name a few. I am particularly interested in the issue of improving reproducibility and transparency in data analysis.

My research aims to identify psychosocial factors that are involved in the pathogenesis and course of major medical disorders, to characterize the biobehavioral mechanisms whereby such factors influence disease, and to develop both behavioral and pharmacologic means of preventing or ameliorating the adverse impact of psychosocial factors on health and disease. Specific projects that are currently active include: 1) The influence of hostile personality, social isolation, depression and other psychosocial risk factors upon the development and course of cardiometabolic disease; 2) Biological and genetic mechanisms whereby psychosocial risk factors influence disease development and course; and 3) Behavioral and pharmacologic approaches to ameliorate impact of psychosocial risk factors on disease risk and course.

My training, expertise and research interests range from human integrative physiology and genetics to animal exercise models to cell culture models of skeletal muscle adaptation to mechanical stretch. I am trained clinically as an internist and preventive cardiologist, with particular expertise in preventive cardiology and cardiac rehabilitation.  My research training spans molecular biology and cell culture, molecular genetics, and integrative human exercise physiology and metabolism. I practice as a preventive cardiologist with a focus on cardiometabolic risk and exercise physiology for older athletes.  My research space has both a basic wet laboratory component and a human integrative physiology one.

One focus of our work is an integrative physiologic examination of exercise effects in human subjects in clinical studies of exercise training in normal individuals, in individuals at risk of disease (such as pre-diabetes and metabolic syndrome; STRRIDE), and in individuals with disease (such as coronary heart disease, congestive heart failure and cancer).

A second focus of my research group is exploration of genetic determinates of disease risk in human subjects.  We conduct studies of early onset cardiovascular disease (GENECARD; CATHGEN), congestive heart failure (HF-ACTION), peripheral arterial disease (AMNESTI), and metabolic syndrome.  We are exploring analytic models of predicting disease risk using established and innovative statistical methodology.

A third focus of my group’s work is to understand the cellular signaling mechanisms underlying the normal adaptive responses of skeletal muscle to physiologic stimuli, such as occur in exercise conditioning, and to understand the abnormal maladaptive responses that occur in response to pathophysiologic stimuli, such as occur in congestive heart failure, aging and prolonged exposure to microgravity.

Recently we have begun to investigate interactions of genes and lifestyle interventions on cardiometabolic outcomes.  We have experience with clinical lifestyle intervention studies, particularly the contributions of genetic variants to interventions responses.  We call this Lifestyle Medicopharmacogenetics.

KEY WORDS:

exercise, skeletal muscle, energy metabolism, cell signaling, gene expression, cell stretch, heart failure, aging, spaceflight, human genetics, early onset cardiovascular disease, lifestyle medicine

With a unique skill set resulting from outstanding training, my sole aim was to help improve human health through cutting-edge translational research. Specifically, I have been interested in illuminating the mechanisms responsible for the causes and progression of the leading public health conditions, which may help with the development and enhancement of precision medicine.  As part of this endeavor, I also became interested in studying the measurement of biobehavioral risk factors and environmental stressors and their interactions with genes that may influence cardiovascular disease (CVD) risk factors and endophenotypes, adversely affecting the CVD pathways.

I joined medical research with my early research training on computational biology, high-throughput genomics, next-gen DNA sequencing, genome-wide studies, and big data analytics, which resulted in some of prominent findings on human genome (PMID: 18048317, PMID: 20223737, PMID: 20598109, PMID: 21703177). These findings included a significant contribution to the scientific community’s understanding that I made during my postdoctoral fellowship with Dr. David Goldstein at Duke Center for Human Genome Variation that how well RNA-Seq can identify human coding variants just using a small fraction of genome (transcriptome) as compared to whole genome (PMID: 20598109). This work was important not only scientifically, but also in pragmatic terms, given the high cost of sequencing.

In relatively recent work I discovered a novel CVD risk gene EBF1, where  a common genetic variant contributed to inter-individual differences in human central obesity, fasting blood glucose, diabetes, and CVD risk factors in the presence of chronic psychosocial stress (PMID: 25271088). This work demonstrated the genetic variant-specific significant path from chronic psychosocial stress to common carotid intimal–media thickness (CCIMT), a surrogate marker for atherosclerosis, via central obesity and fasting glucose. I also developed an algorithm to create a synthetic measure of stress using the proxy indicators of its components (PMID: 26202568).  Other more recent work has elucidated the race, sex, and age related differences in the EBF1 gene-by-stress interaction (PMID: 33077726), which suggests the need for careful evaluation of environmental measures in different ethnicities in cross-ethnic gene-by-stress interaction studies.

More recently, I have expanded my research interest in studying the genetic architecture of Alzheimer’s disease (AD) and the role of psychosocial stress in modifying the effect of genetic variants on the disease risks.

Dr Georgiades research has focused on evaluating bio-behavioral risk-factors, in particular the role mental stress, in the development of diabetes and cardiovascular disease. She have written and co-authored over 45 papers in the area of behavioral medicine and have vast experience from designing experimental studies and evaluating epidemiological cohort studies. In addition, she has been co-investigator on intervention studies examining the effects of cognitive behavioral therapy, stress management and exercise programs in diabetic, hypertensive and cardiac patients.

For the past 10 years, her focus been to examine the role of stress and stress hormones in glucose regulation. Results from her recent studies suggest that increased stress hormone activity, manifested as elevated circulating epinephrine after a glucose challenge, interact with central adiposity in the prediction of increased glucose levels in obese individuals.

Dr Georgiades is presently a collaborator on a Program Project Grant (PPG) lead by Dr Redford Williams. The aim of her work within the PPG is to study the relationship between behavioral factors and various measures of glucose metabolism and identify genes/loci that account for the clustering of metabolic abnormalities with cardiovascular, neuroendocrine, platelet function and inflammatory markers.  The overall aim of the PPG is to increase understanding of the gene-environment interactions that contribute to pathogenic mechanisms whereby psychosocial and biobehavioral risk factors increase risk for cardiovascular disease.