Genomics of Sudden Coronary Death: What Causes Atherosclerotic Plaques to Rupture - Shurjo Sen
Genomics of Sudden Coronary Death: What Causes Atherosclerotic Plaques to Rupture - Shurjo Sen
July 16, 2015 - Three-Minute Talk. Part of the 2015 plain language competition at NIH. More info: http://www.genome.gov/27562188
Content
8.519 -> Shurjo Sen:
In our lab, we study coronary artery disease,
10.809 -> or CAD, which is the single largest cause
of death worldwide.
14.57 -> Many of us don’t know that CAD begins in
our late teens, early 20s.
19.27 -> As a 35-year-old former smoker, I’m actually
a really good candidate myself.
24.7 -> But advanced CAD mainly manifests in people
55 years of age and older, and it takes two
30.5 -> very distinct forms.
32.43 -> In panel A, what you see is what we call stable
plaques.
36.14 -> And these are plaques where, although the
artery has become narrower, the plaque itself
41.09 -> is at lesser risk for rupturing and releasing
its contents into the lumen.
46.26 -> Contrasting with this is what we see in panel
B, which are much more dangerous, vulnerable
52.19 -> plaques.
53.19 -> And what distinguishes them from stable plaques
is the thin, fibrous cap, which you’ll see
58.421 -> right above the black arrow.
60.489 -> And so in a vulnerable cap, when that thin,
fibrous cap ruptures, what happens is what
65.74 -> we see in panel C, where the contents of the
necrotic core spill out into the lumen.
71.92 -> And these usually form a thrombus, which occludes
blood flow to the heart muscle, leading to
77.569 -> a myocardial infarction and unfortunately
most often a fatal myocardial infarction.
82.56 -> So one of the big, big unknowns of cardiology
is what exactly causes a vulnerable plaque
89.249 -> to go into the rupture state.
91.799 -> If we understand this, this helps us immensely
in managing advanced cardiovascular disease.
98.829 -> So my specialty is in applying RNA sequencing
to the study of cardiovascular phenotypes
103.67 -> such as plaque rupture, which is what we see
here.
106.99 -> And one of the things I’m doing to understand
this question is, I’m sequencing RNA from
112.669 -> subjects who died from sudden cardiac death.
115.719 -> And what sudden cardiac death is, is a person
doubles up symptoms -- usually chest pain
120.729 -> -- and then within the next hour, they’re
dead.
123.95 -> And during autopsy they’re found to have
a ruptured plaque like the ones we see here,
127.969 -> which caused the myocardial infarction that
led to their dying.
131.54 -> So we want to use RNA sequencing as a tool
for studying the changes leading up to this
137.78 -> event.
138.78 -> The experimental design we use for this project
is about half pathology and half sequencing.
144.47 -> First we collect hearts from the autopsy procedure.
148.77 -> And then we put these hearts through a pretty
detailed protocol to isolate the lesions,
153.57 -> characterize them, understand what caused
the death, and by getting the data from that
158.92 -> procedure, we have formed a matched set of
10 hearts, which had both vulnerable and ruptured
164.86 -> plaques.
165.86 -> And then from 10 other hearts, we have 10
stable plaques like the one in panel A, which
170.36 -> we use as controls.
172.24 -> So our next challenge is to sequence the RNA
from these plaques, and that is unfortunately
178.19 -> a little harder than it sounds because the
hearts were originally not for sequencing,
183.44 -> but for pathology procedures.
184.58 -> And the chemicals used for the histology staining
usually degrade the nucleic acids pretty badly.
191.15 -> So I’m, however, quite happy because we’ve
been able to recover substantial amounts of
197.18 -> RNA in a size range that, although it’s
not perfect, is still usable for sequencing.
202.68 -> So in panel D, what you see is relative to
the highly quality in near-perfect RNA on
209.8 -> the extreme right.
211.37 -> The other A samples, which are in the two
other boxes to the left, are the samples we
215.47 -> get from these autopsy hearts.
217.44 -> And as you can see, they’re pretty fragmented
compared to the control sample.
222.08 -> But the good news here is that if you look
at the box in the middle, which is RNA, those
225.93 -> 200 base pairs are greater in size.
228.3 -> We still have a substantial amount of RNA
in that size range, and that’s actually
233.11 -> want we need to use sequencing on these samples.
236.32 -> So I’m really, very optimistic that one
we have the results from sequencing these,
241.36 -> we’ll be in a pretty good position to understand
from the transcriptor [spelled phonetically]
244.83 -> point of view what went on that led a stable
plaque to go in the direction of becoming
249.97 -> vulnerable and, even more importantly, what
happened between the vulnerable plaque and
254.52 -> the rupture event that caused sudden cardiac
death.
257.739 -> If we understand that, that gives us a good
starting point to be able to manage this disease,
262.12 -> hopefully lower rates of cardiovascular mortality,
which, as I mentioned, are highest in the
266.58 -> world.
267.58 -> Thank you.
268.58 -> [end of transcript]
Source: https://www.youtube.com/watch?v=WaIhQGqBihw