Circulation July 24, 2018

Dr Carolyn Lam: Welcome to Circulation on the Run, your weekly
podcast summary and backstage pass to the journal and its
editors. I'm Dr Carolyn Lam, associate editor from the National
Heart Center and Duke National University of Singapore. Did you
know that despite being one of the wealthiest nations in the
world, the United States population has a shorter life expectancy
compared to almost all other high-income countries in the world?
Well, stay tuned to learn what Americans could do to narrow the
life expectancy gap between the United States and other
industrialized nations. Coming right up after these summaries.


                               
Are microRNAs involved in nitrate tolerance? Well, the first
original paper this week provides some answers. This is from
co-corresponding authors Dr Bai and Zhang from Central South
University in Changsha, China. Nitrate tolerance develops when
there's dysfunction of the prostaglandin I2 synthase and
prostaglandin I2 deficiency. These authors hypothesize that
prostaglandin I2 synthase gene expression may be regulated by a
microRNA-dependent mechanism in endothelial cells. They induce
nitrovasodilator resistance by nitroglycerin infusion in Apoe
deficient mice and studied endothelial function in both the mouse
models as well as human umbilical vein endothelial cells. They
found that nitric oxide donors induced atopic expression of
microRNA 199a/b in endothelial cells, which was required for the
nitrovasodilator resistance via repression of prostaglandin I2
synthase gene expression. Targeting this axis effectively
improved nitrate tolerance. Thus, the atopic expression of
microRNA 199 in endothelial cells induced by nitric oxide may
explain prostaglandin I2 synthase deficiency in the progression
of nitric tolerance. Thus, microRNA 199a/b may be a novel target
for the treatment of nitric tolerance.


                               
What are the long-term outcomes of childhood left ventricular
noncompaction cardiomyopathy? Well, the next paper presents
results from the National Population-Based Study in Australia.
First author, Dr Shi, corresponding author, Dr Weintraub, from
Royal Children's Hospital in Melbourne, looked at the National
Australian Childhood Cardiomyopathy Study, which includes all
children in Australia with primary cardiomyopathy diagnosed at
less than 10 years of age between 1987 and 1996. Outcomes for
left ventricular noncompaction patients with a dilated phenotype
will compare to those with a dilated cardiomyopathy.


                               
There were 29 patients with left ventricular noncompaction with a
mean annual incidence of newly diagnosed cases of 0.11 per
hundredth thousand at risks persons.


                               
Congestive heart failure was initial symptom in 83%, and 93% had
a dilated phenotype. The median age at diagnosis was 0.3 years of
age. Freedom from death or transplantation was 48% at 10 years
after diagnosis, and 45% at 15 years. Using propensity score
inverse probability of treatment-weighted Cox regression, the
authors found evidence that left ventricular noncompaction with a
dilated phenotype was associated with a more than two-fold
greater risk of death or transplantation.


                               
The next paper reports the first application of multiomics and
network medicine to calcific aortic valve disease. Co-first
authors Dr Schlotter and Halu, corresponding author Dr Aikawa
from Brigham and Woman's Hospital and Harvard Medical School in
Boston, and their colleagues examined 25 human stenotic aortic
valves obtained from valve replacement surgeries. They used
multiple modalities, including transcriptomics and global
unlabeled and label-based tandem-mass-tagged proteomics.


                               
Segmentation of valves into disease stage–specific samples was
guided by near-infrared molecular imaging. Anatomic-layer
specificity was facilitated by laser capture microdissection.
Side-specific cell cultures was subjected to multiple calcifying
stimuli, and the calcification potential and basil or stimulated
proteomics were evaluated. Furthermore, molecular interaction
networks were built, and their central proteins and disease
associations were identified.


                               
The authors found that global transcriptional and protein
expression signatures differed between the nondiseased, fibrotic,
and calcific stages of calcific aortic valve disease. Anatomical
aortic valve microlayers exhibited unique proteome profiles that
were maintained throughout disease progression and identified
glial fibrillary acidic protein as a specific marker of valvula
interstitial cells from the spongiosa layer. In vitro,
fibrosa-derived valvular interstitial cells demonstrated greater
calcification potential than those from the ventricularis.
Analysis of protein-protein interaction networks further found a
significant closeness to multiple inflammatory and fibrotic
diseases. This study is significant because it is the first
application of spatially and temporarily resolved multiomics and
network systems biology strategy to identify molecular regulatory
networks in calcific aortic valve disease. It provides network
medicine–based rational for putative utility of antifibrotic and
anti-inflammatory therapies in the treatment of calcific aortic
valve disease. It also sets a roadmap for the multiomic study of
complex cardiovascular diseases.


                               
The final paper tackles the controversy of antibiotic prophylaxis
for the prevention of infective endocarditis during invasive
dental procedures. This is from a population-based study in
Taiwan. First author, Dr Chen, corresponding author, Dr Tu from
Institute of Epidemiology and Preventive Medicine College of
Public Health in National Taiwan University aimed to estimate the
association between invasive dental treatments and infective
endocarditis using the health insurance database in Taiwan.


                               
They chose 2 case-only study designs. First a case-crossover, and
second, self-controlled case series. Both designs used
within-subject comparisons such that confounding factors were
implicitly adjusted for. They found that invasive dental
treatments did not appear to be associated with a larger risk of
infective endocarditis in the short period following invasive
dental treatment. Results were consistent from both study
designs. The authors also did not find any association between
invasive dental treatments and infective endocarditis even among
the high-risk patients, such as those with a history of rheumatic
disease or valve replacement.


                               
In summary, these authors found no evidence to support antibiotic
prophylaxis for the prevention of infective endocarditis before
invasive dental treatments in the Taiwanese population. Whether
antibiotic prophylaxis is necessary in other populations requires
further study.


                               
Alright, so that wraps it up for our summaries, now for our
feature discussion.


                               
The United States is one of the wealthiest nations worldwide, but
Americans have a shorter life expectancy compared with almost all
other high-income countries. In fact, the US ranks only 31st in
the world for life expectancy at birth in 2015. What are the
factors that contribute to premature mortality and life
expectancy in the US? Well, today's feature paper gives us some
answers. And I'm just delighted to have with us the corresponding
author, Dr Frank Hu from Harvard T.H. Chan School of Public
Health, as well as our dear associate editor, Dr Jarett Berry,
from UT Southwestern.


                               
Frank, could you begin by telling us a bit more about the
inspiration for looking at this, what you did, and what you
found?


Dr Frank Hu:       So, we look at
the impact of healthy lifestyle habits, life expectancy in the US
as a nation. As you just mentioned, Americans have a shorter life
expectancy compared with almost all other high-income countries,
so in this study we wanted to estimate what kind of impact of
lifestyle factors have, premeasured that and life expectancy in
the US population.


                               
What we did is to combine three datasets. One is our large
cohort, Nurses’ Health Study, and Health Professionals Follow-Up
Study. We use this large cohort to estimate the relationships
between lifestyle habits and mortality. And the second data set
we use is to get age and sex to specific mortality rates in the
US as a nation. This is the CDC WONDER dataset. And the third
dataset we used is the NHANES dataset, this is the National
Health and Nutrition Examination Survey. We used this dataset to
get the prevalence of healthy lifestyle factors in the general US
as a nation. So, we used the three datasets to create
age-specific, sex-specific life tables and estimated life
expectancies.


                               
At age 50, according to the number of healthy lifestyle habits
that people would follow, what we found is that following several
lifestyle factors can make a huge difference in life
expectancies.


                               
Here we talk about five basic lifestyle factors: not smoking,
maintaining a healthy weight, exercise regularly—at least a half
hour per day—and eating a healthy diet, and not drinking too much
alcohol. No more than one drink per day for a woman, no more than
two drinks per day for men. What we found is that, compared with
people who did not adapt any of those low-risk habits, we
estimated that the life expectancy at age 50 was 29 years for
woman and about 26 years for men. But for people who adapted all
five healthy lifestyle habits, life expectancy at age 50 was 43
years for women and 38 years for men. So, in other words, a woman
who maintains all 5 healthy habits gained, on average, 14 years
of life, and the men who did so gained 12 years life compared
with those who didn't maintain healthy lifestyle habits. So I
think this is a very important public health message. It means
that following several bases of healthy factors can add
substantial amount of life expectancy to the US population, and
this could help to reduce the gap in life expectancy between the
US population and other developed countries.


Dr Carolyn Lam: Thank you, Frank. You know that is such an
important public health message that I am going to repeat it.
Adhering to five lifestyle risk factors mainly, don't smoke,
maintain a healthy weight, have regular physical activity,
maintain a healthy diet, and have moderate alcohol consumption,
AND a woman could increase her life expectancy at age 50 by 14
years and a man could do that by 12 years more. That is
absolutely amazing.


                               
Okay so Frank, actually, I do have a question though. These are
remarkable datasets obviously, but they also go back to the
1980s. So did you see any chief risk factor that may have played
more predominant apart with time?


Dr Frank Hu:       We didn't
specifically look at the changes in risk factors life expectancy,
but among the five risk factors, not smoking is certainly the
most important factor in terms of improving life expectancy. The
good news is that prevalent smoking in the US has decreased
substantially in the past several decades. However, the
prevalence of other risk factors has actually increased. For
example, the prevalence of obesity has increased two- or
three-fold and the prevalence of regular exercise remained at a
very low level, and also the diet quality in the US population is
relatively poor. So, the combination of those risk factors have
contributed to relatively low life expectancies in the US
population.


Dr Carolyn Lam: Right. Obesity, not smoking, I hear you. I just
wanted to point out to all the listeners too, you have to take a
look at Figure 1 of this beautiful paper, it’s just so
beautifully illustrated in it.


                               
Jarett, you helped to manage and bring this paper through. What
are your thoughts?


Dr Jarett Berry: Yeah, I just want to echo your comments,
Carolyn, and Dr Hu. This is a fabulous paper, and a very
important contribution characterizing these important
associations in the US population. And I think, and the
discussion thus far has been really helpful in putting all of
this into context.


                               
I do want to ask you, just a couple of, I guess more,
philosophical questions about some of the observations in the
paper. And one of them is the prevalence of the low-risk factor,
those with a large number of low-risk factors, for example, in
both the Nurses Health and in the Health Professional Follow-Up
Study, you observed that the presence of five lifestyle factors
was less than 2%. And it's interesting you see this in a large
number of datasets and I think important, maybe for our readers
to realize that there's two sides to the coin here.


                               
One, the benefit of these low risk factors, but also,
unfortunately, the low prevalence of these collections of healthy
lifestyle factors that you've outlined.


                               
Could you comment a little bit on that, and what that means, both
maybe from a scientific point of view of perhaps, more
importantly, from a public health stand point?


Dr Frank Hu:       Yeah and this is
very important observation and the number of people or the
percentage of people who maintained all the five low-risk
lifestyle habits is quite low in our cohort, even the nurses and
health professionals, they are more health conscience in the
general population. They have much better access to health care
and also better access to healthy foods and have physical
activity facilities. Despite all this potential advantages, and
these more percentage of people who are able to maintain all five
lifestyle risk factors.


                               
On the other hand, about 10 to 15% of our participants did not
adopt any of the five low-risk lifestyle habits. So it means that
we still have a lot of work to do in terms of improving the
lifestyle habits that we discussed earlier. The five risk
lifestyle factors and in the general population, I think the
percentage of people who adapt all the five lifestyle factors,
probably even lower than 2%. And so that means that we have a
huge public health challenge in front of us and have to improving
the five lifestyle risk factors. One of the most important public
health challenges as mentioned earlier is obesity because
currently we have two-third of the US population is overweight or
obese. So that's something I think is major public health
challenges for us.


Dr Jarett Berry: Right, and it’s interesting looking at your
Table 1, and those individuals who have all five low risk
factors. It's interesting that the prevalence of physical
activity was incredibly high. I have a great interest of impact
of exercise on these types of outcomes and it's interesting that
in both cohorts, six or seven hours a week of exercise was the
mean physical activity level in those with five risk factors. So,
it's interesting and in some ways, these lifestyle factors, they
do tend to congregate or covary with one another such that those
individuals who do spend that kind of time, albeit unfortunately
more rare than we would like to see it, the increase in physical
activity does tend to have a positive impact, not only on the
weight, but also on healthy lifestyle or healthy diet choices.


Dr Frank Hu:       Right, yeah this
is a very good observation that what I do want to point out that
our definition of regular exercise is pretty cerebral to put it
in terms of the definition. So we define moderate to vigorous
physical activity in our cohorts. We included not just running,
playing sports, but it was also walking in a moderate intensity.
So it means that people can incorporate physical activity into
their daily life. For example, by walking from a train station
and with climbing stairs in their workplace and so on and so
forth. So here physical activity means both recreational activity
and also moderate intensity activities such as graceful walking.


Dr Carolyn Lam: Frank, I think both of us listening are breathing
a sigh of relief there and just for the listeners to understand
too. These factors were dichotomized, right, and so you were
describing the type of exercise and actually you used a three and
a half hour per week limit to define healthy or not.


                               
Similarly, just for reference the alcohol intake was 5 to 15g a
day for women, or 5 to 30g a day for men. And normal weight was
defined as a BMI of 18.5 to 24.9. I'm just thinking that if I
were listening I'd want to know those cutoffs.


                               
Now, can I ask a follow-up question, therefore to this dichotomy.
As far as I understand you counted each of these risk factors
equally, but did you try to do a weighted analysis by any chance?
Did any one of them play a bigger role than others?


Dr Frank Hu:       That's an
interesting mathematical question because it’s very difficult to
assign different weights to different risk factors because we
look at, not just total mortality but also cardiovascular
mortality and cancer mortality. So, you would have to use
different weights for different causes of mortality. That would
make the analysis much more complicated. But we did calculate a
different type of score using five categories of each risk factor
and then using that score, we were able to rank people in more
categories so for that score the range is from five to 25, and we
categorized people into quintiles or even more categories and the
contrast in life expectancy between the lowest and the highest
group is even greater. So, it means that, the higher number of
healthy lifestyle factors, the greater life expectancy. Also,
with each category, each lifestyle factors a high degree of
adherence to that factor, the greater health benefit people will
get. So, I think it's really accumulative fact of multiple risk
factors and also the degree of adherence to each of the factors.


Dr Carolyn Lam: Again, such an important public health message.


                               
Jarett, how do you think this is going to be received by the
public at large?


Dr Jarett Berry: Very well received. I mean this is a very
important observation demonstrating some of these disconcerting
observations about life expectancy in the United States and as we
think about strategies for improving the public health, I think
Dr Hu's group has really helped us outline, very clearly, what
other bodies such as the American Heart Association have been
saying for years now, that lifestyle factors are so important in
influencing cardiovascular risk, and in this case, life
expectancy. It really does put, once again, the right amount of
emphasis on the role these lifestyle factors of improving the
public health. I think it’s going to be very well received and
really helpful and important observation that all of us need to
hear.


Dr Carolyn Lam: Listeners, don't forget this important message
and tell your friends about it, please.


                               
Thanks for joining us today, don't forget to join us again next
week.