Blood vessel network (Image courtesy of Iruela-Arispe Lab)
Cardiovascular disease does not affect everyone the same way. An individual’s susceptibility to disease, response to treatment and likelihood of survival are partly inherited. Environmental factors (for instance, diet, exercise and whether or not the person smokes) have an impact, as well. Yet, treatment of cardiovascular disease is too often one-size-fits-all.
UCLA takes a different approach. We tailor research, care and recovery to match an individual’s unique genetics and lifestyle.
The first step toward individualized medicine is to make sure patients receive the treatment options that have already been developed and are available. UCLA has long been a leader in evidence-based medicine for cardiovascular care.
The key to success is to make sure patients are receiving the benefits of prior discoveries. Dr. Gregg C. Fonarow notes that without a system in place to make sure that happens, it can take 10 to 15 years from discovery until definitive proof that a therapy improves outcomes for patients.
Although this problem exists worldwide in health care systems, it may be most recognized in cardiology, given the number of very beneficial therapies that exist.
The spirit of precision medicine, says Dr. Yibin Wang, Chair of the Cardiovascular Research Theme, is to understand, diagnose and treat a disease much more powerfully and accurately than is possible now. This goes beyond genetics. It encompasses each person’s whole health.
It will not be possible, physicians explain, to treat every single patient uniquely. But the big difference from current practice is that patients will likely fit into categories of treatment.
Borrowing an analogy from his colleague Dr. James Weiss, chief of the Division of Cardiology, Dr. Tom Vondriska says it would be impossible to come up with more than 300 million unique pairs of shoes to perfectly fit everyone in the U.S. Offering only small, medium and large sizes wouldn’t work, either.
“If you had 10 sizes, you could make shoes that would be comfortable for probably about 99% of the population,” Vondriska says. “That is what we are trying to do with our approach to cardiovascular disease at UCLA: assign patients to the right group so that we can accurately diagnose and treat their conditions and thereby dramatically improve quality of life and survival. Our approach at UCLA is to leverage multiple so-called “omics technologies,” including genomics, epigenomics and proteomics, in models systems and human populations, to discover the molecular signatures of health and disease. We can then use this high resolution information to more effectively care for patients.”
Today, UCLA’s adult congenital heart disease clinic is one of the largest in the United States. The “UCLA difference” can be seen clearly when heart surgeon Dr. Jamil Aboulhosn operates on an adult with an inherited heart condition.
Each patient has unique anatomical and physiological problems. Dr. Aboulhosn and his colleagues address these patients’ individual situations by:
The goal is to understand how diseases arise from a combination of lifestyle and genetic factors. With this knowledge, our team of physicians, scientists, surgeons and engineers can better design strategies for preventing and curing cardiovascular disease on a patient-by-patient basis – providing truly individualized care.
Led by Dr. Fonarow, UCLA launched the UCLA Cardiovascular Hospitalization Atherosclerosis Management Program (CHAMP). CHAMP provided the first scientific evidence demonstrating that a hospital-based cardiovascular treatment system could reduce fatal and non-fatal cardiovascular events and improve cardiovascular care quality and outcomes.
CHAMP has demonstrated:
In fact, the scientific evidence provided by CHAMP resulted in changes in guidelines recommended by the National Heart, Lung and Blood Institute (NHLBI), American Heart Association (AHA) and American College of Cardiology (ACC).
The AHA even launched a nationwide program modeled after CHAMP, called “Get With The Guidelines” (GWTG), to apply this model of care at hospitals across the country. GWTG has:
UCLA aims to transform the understanding of cardiovascular disease risk and reveal new cures. To do this, we are developing one of the nation’s biggest collections of patient data – up to 500,000 records.
This data will result in the ability to view what can be described as a molecular EKG, according to Dr. Tom Vondriska, professor of anesthesiology, medicine and physiology at UCLA. For example, the electrical activity of the heart informs doctors about problems with the heart’s function.
Similarly, the molecular EKG – a combination of genes, proteins and other factors – will provide an objective measurement of cardiovascular risk. Combined with the doctor’s clinical decision-making skill and innovative big data tools, these molecular features will revolutionize cardiovascular care.
Soon, all patients who visit a UCLA clinic or hospital will have the chance for their genomes to be scanned for disease markers. Ultimately, the genome scan will:
UCLA was recently awarded $11 million to lead a National Institutes of Health (NIH) Center of Excellence for Big Data Computing (BD2K) that focuses on cardiovascular health.
Directed by principal investigator Dr. Peipei Ping, professor of physiology, medicine and bioinformatics in the David Geffen School of Medicine, the center will:
Dr. Peipei Ping
When integration is complete, users will be able to do a simple search to get the desired information, even from a patient with a chronic disease, who might have 150 pages of medical records.
The big data approach will be a boon to cardiovascular treatment, says Dr. Karol Watson, professor of medicine in the Division of Cardiology. Outcomes of this approach could include:
UCLA hosts one of the world’s longest-running congenital heart disease programs. Our physicians have treated more than 1,000 patients with inherited heart defects.
One example of a condition caused by genetic mutations that run in families is hypertrophic cardiomyopathy. This is the disorder often associated with sudden death in young athletes.
Left to right: Dr. Jesscia Wang, Jessica Rahman, and Dr. Adriana Huertas Vazquez
Dr. Jessica Wang, assistant professor of medicine in the Division of Cardiology, leads an effort to understand how variation in the DNA sequence causes disease.
Dr. Jessica Wang and her team have identified 35 genes in mice that make them susceptible to fibrosis, the stiffening of heart muscle that leads to heart failure, as well as other cardiac features associated with disease.
Of note, as with human populations, these animal studies reveal strongly heritable susceptibility to disease onset and progression. Researchers have been able to make mice destined to develop heart failure become more resilient. This suggests that investigators eventually may use similar approaches to mitigate the inherited components of cardiovascular disease in humans.
Dr. Wang is now comparing her genetic findings in mice to the human gene information contained in the growing Inherited Cardiovascular Disease Registry, which also contains exome sequencing of patients’ family members.
She believes there are a number of genes that work in concert to predestine some people to heart failure. “What we learn from the gracious cooperation of our patients and their families will likely shed light not only on inherited conditions but on the heart failure that affects many, many more people,” she says.
Big data is improving cardiovascular care at UCLA by examining the role of ethnicity and sex in cardiovascular disease across the diverse Southern California population. This real-world information is almost never uncovered in clinical trials.
Dr. Watson helps lead a large, NIH-funded study, the Multi-Ethnic Study of Atherosclerosis (MESA), which has enrolled 6,000 patients in six communities nationwide.
The MESA findings, as well as her own work – Dr. Watson is also director of the UCLA Barbra Streisand Women’s Heart Health Program at UCLA – have shown that heart disease in women is not the same as it is in men.
Among the differences: