Unearthing Clues to Help Understand and Manage Chronic Illness

Before she became a nurse, Elena Flowers was a research assistant at San Francisco General Hospital, where she worked on a study that examined how individual responses to common drugs for cardiovascular risk factors differed between African Americans and Caucasians.

During her time at San Francisco General, she observed up close the disproportionate burden that chronic conditions, like cardiovascular and metabolic disease, can have on vulnerable populations.

Something clicked.

“I got very interested in health disparities and how the things in our environment interact with genetic disposition to have an impact on our health,” says Flowers.

That interest eventually led her to the field of epigenetics, which examines how environment can change how a gene functions or expresses itself. Those changes, it’s believed, can predict and possibly influence both how disease develops in individuals and how they respond to therapy. Flowers is determined to deepen our understanding in this area, in the hope that it can speed the journey to more personalized and effective care.

Identifying Biomarkers for Cardiovascular Disease

After receiving her nursing credential in 2004, Flowers worked as a clinical nurse and went on to receive her master’s from UCSF School of Nursing. Keen to pursue a research career, she immediately entered the PhD program, receiving her doctorate in June 2012 and joining the faculty a few months later.

During her master’s studies, Flowers got the chance to participate in research that would set the stage for her current work. With mentor Brad Aouizerat, an associate professor in the Department of Physiological Nursing, and other investigators, Flowers conducted epidemiological studies that looked at overall metabolic and cardiovascular risk factors among South Asians living in the San Francisco Bay Area. South Asians are disproportionately at risk for cardiovascular disease compared with other ethnic groups, but the reasons aren’t totally clear.

“There is some evidence for both a genetic component and a lifestyle component,” says Flowers, “but there’s a lot of work to be done.”

In the South Asian population they studied, Flowers and her co-investigators identified a specific phenotype – observable characteristics – that appears to contribute to the group’s elevated risk for cardiovascular disease. A large proportion had atherogenic dyslipidemia, a condition that contains a combination of risk factors – low high-density lipoproteins (HDLs) and high triglycerides – that play a clear role in the development of cardiovascular disease. Moreover, they discovered that, contrary to previous assumptions, being overweight was not a prerequisite for the development of cardiovascular risk factors or insulin resistance in the studied population.

This suggested to Flowers that there might be differences in the way genes are expressed among people with cardiovascular and metabolic risk factors compared with those without them, and that these differences could be identified via the way microRNA, a genetic biomarker in the blood, is expressed.

For her dissertation, Flowers studied South Asian men: some with abnormal cholesterol and some without. She and her co-investigators screened their blood for 85 different epigenetic biomarkers and found that 15 microRNA types were expressed differently between the two groups.

Moving a Step Closer to Personalized Care

This was important because it indicated that differences in gene expression were associated with the specific risk factor of abnormal cholesterol. Flowers hopes that by characterizing these differences, scientists will eventually be able to predict individuals’ responses to specific interventions – moving us closer to personalized medicine, which uses genetic and other information to tailor health care to the individual patient.

While most people think of personalized medicine in terms of pharmacology, Flowers is equally interested in how people respond to nonpharmacological interventions, such as exercise, stress reduction and diet. Individual response to behavioral interventions is notoriously variable, not only because of compliance challenges, but also because of differing physiological response.

“We all know the anecdote of the person who does all the right things and still has high blood pressure, contrasted with the person who doesn’t seem to do anything that’s health promoting yet still remains very healthy,” says Flowers.

She hopes to tease out some of these physiological differences at the genetic level in a new study that will look at how gene expression differs between individuals with and without insulin resistance, which is a precursor to type 2 diabetes. Flowers and her co-investigators – Aouizerat; Yoshimi Fukuoka, an associate adjunct professor in the UCSF Institute for Health & Aging; and Stanford University School of Medicine Professor Emeritus Gerald Reaven – will also investigate whether gene expression can predict response to both a pharmacologic treatment and the type of behavioral treatment that emerged from the landmark Diabetes Prevention Program, a major multicenter clinical research study.

“We all have a certain genetic code that’s present in every cell, and there’s no changing it,” says Flowers. “But disease can stem from one pathway in one person and another in someone else. Epigenetic markers might give us information as to which pathway is relevant for which individual and, potentially, can change the way we look at health and address disease, especially common chronic problems like cardiovascular disease and type 2 diabetes.”