Smartphone app calculates genetic risk for heart attack
Study showed that at-risk users who downloaded the app increased life-
saving statin use

Date:
March 14, 2022
Source:
Scripps Research Institute
Summary:
Researchers have developed a smartphone app that can calculate
users' genetic risk for coronary artery disease (CAD)--and found
that users at high risk sought out appropriate medication after
using the app.



FULL STORY ==========================================================================
A Scripps Research team developed a smartphone app that can calculate
users' genetic risk for coronary artery disease (CAD) -- and found that
users at high risk sought out appropriate medication after using the app.


==========================================================================
In the study, which appears in npj Digital Medicine in March 2022,
the researchers detailed how their app called MyGeneRank inputs
participating individuals' genetic information from the 23andMe genetic
testing company and outputs a CAD risk score based on the DNA data. Of
the 721 participants who provided complete information, those with
high-risk scores were much more likely to start using statins or other cholesterol-lowering therapies, compared to those with low-risk scores.

"We saw about twice the rate of statin initiation in the high genetic
risk group vs the low genetic risk group, which indicates that strategies
like this could make a big contribution to public health -- heart disease
being the largest cause of death globally," says study senior author Ali Torkamani, PhD, professor and director of Genomics and Genome Informatics
at the Scripps Research Translational Institute.

According to the U.S. Centers for Disease Control and Prevention,
about 18 million American adults have CAD, the most common form of heart disease, which features the hardening and narrowing of arteries feeding
the heart muscle. More than 300,000 Americans die of resulting heart
attacks every year.

Statins such as atorvastatin and simvastatin, as well as other, non-statin drugs that reduce bloodstream levels of cholesterol and other fat-related molecules called lipids, are now widely used, and have helped reduce the
annual death rate from CAD over the past two decades. But researchers
estimate that in the US nearly half of men and about 10 percent of women between 45 and 65 years old are at least at intermediate risk of CAD --
yet only about a third of these individuals take lipid-lowering drugs.

Calculating CAD risk scores and communicating that information via
smartphone apps is now being considered as a highly scalable method for
nudging more at- risk people to seek medical advice and get lipid-lowering medications when appropriate, thereby lowering the incidence of CAD
and heart-attacks.



==========================================================================
"We now have the opportunity to integrate a person's genetics into their cardiovascular health assessment to help them better understand their individualized risk and empower them to make the necessary modifications
- - including the addition of statin therapy -- to their risk factor optimization plans," says first author Evan Muse, MD, PhD, a cardiologist
and lead for cardiovascular genomics at the Scripps Research Translational Institute.

"Even if someone finds out they have low genetic risk for CAD, knowing
their score can help -- for example if they also know they have high risk overall, that may suggest other non-genetic factors like lifestyle are contributing to their risk and that they should consider making changes," Torkamani adds.

The team is pioneering this app-based approach. They developed a free
CAD-risk iPhone app, as well as an Android app. Users can link their
existing 23andMe data and fill out consent forms and health-related
surveys, including questions about the use of lipid-lowering drugs. The
app can then calculate and share with the respondent a risk score based on
the latest recognized genetic risk factors for CAD. The app then followed
up approximately a year later with questions on the respondent's current
use of lipid-lowering medications.

The researchers promoted the apps at scientific conferences, conducted an advertising campaign on Facebook, and ultimately enrolled 3,800 eligible respondents, of whom 721 provided enough initial and follow-up information
for the analysis.

The results were encouraging, according to the team. A key finding was
that respondents who were not taking lipid lowering medication at the
outset of the study, but were informed by the app that they had high
gene-based risk scores for CAD, initiated lipid lowering therapy at more
than twice the rate of those with low risk scores.

Overall, study respondents in the high-risk category, compared to the
low risk category, were, at follow-up, about 1.4 times more likely
to report use of a statin lipid-lowering drug, and about 4 times more
likely to report use of a non-statin lipid-lowering drug. Respondents in
the high-risk group also initiated lipid-lowering therapy much earlier,
at age 52 on average, compared to 65 for the low-risk group.

"On the whole it looks like a significant effect, especially considering
that we were giving respondents only appropriately contextualized
information about their gene-based risk scores -- we weren't directly
telling them to go out and start taking medications," Torkamani says.

He and his colleagues now plan to follow up this pilot study with
larger and longer-term studies of CAD risk-scoring apps -- studies
that will include clinicians and will objectively record differences in cardiovascular health outcomes such as heart attacks.

Funding was provided by the Stowers Family Foundation and the National Institutes of Health (UL1TR002550).


========================================================================== Story Source: Materials provided by Scripps_Research_Institute. Note:
Content may be edited for style and length.


========================================================================== Journal Reference:
1. Evan D. Muse, Shang-Fu Chen, Shuchen Liu, Brianna Fernandez, Brian
Schrader, Bhuvan Molparia, Andre' Nicola's Leo'n, Raymond Lee,
Neha Pubbi, Nolan Mejia, Christina Ren, Ahmed El-kalliny, Ernesto
Prado Montes de Oca, Hector Aguilar, Arjun Ghoshal, Raquel Dias,
Doug Evans, Kai-Yu Chen, Yunyue Zhang, Nathan E. Wineinger, Emily
G. Spencer, Eric J. Topol, Ali Torkamani. Impact of polygenic
risk communication: an observational mobile application-based
coronary artery disease study. npj Digital Medicine, 2022; 5 (1)
DOI: 10.1038/s41746-022-00578-w ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2022/03/220314142023.htm

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