2022-10-24 - Presentation Dr. David Sinclair - ARDD2022 - Great release of unpublished data from David Sinclair's Lab

• https://www.youtube.com/watch?v=mfeu3nTuNbc&ab_channel=ARDD

Transcript

0:00	[Music]
0:00	foreign
0:03	[Music]
0:06	we are on to our final speaker who is on
0:09	Zoom
0:10	David we are ready for your talk
0:12	whenever you are ready to share your
0:15	slides all right let's do it hi everyone
0:17	wish I could be there wish I was there
0:20	uh next year for sure next oh that's
0:23	great
0:24	I'll hold you up to that promise I've
0:26	got my uh my father visiting from
0:28	Australia he's 83 and
0:31	I think that took precedent but uh next
0:33	year I'll bring him with me that would
0:35	be amazing that would be amazing okay
0:37	well thanks for inviting me let me get
0:39	my
0:40	presentation up and running
0:43	perfect great and I'll set a timer so
0:47	that we're good
0:49	okay all right so um yeah it's it's uh
0:52	it's amazing to be here this conference
0:54	to your credit uh and the other
0:56	organizers um just it's growing to be
0:59	one of the Premier conferences in the
1:02	world in this topic so hats off to you
1:04	and I've really enjoyed the the talks
1:07	uh so just because I don't have much
1:08	time I'll get straight into it
1:10	uh so I've been doing this for a while
1:12	started at MIT working in little yeast
1:14	cells and we discovered that and by we I
1:16	mean a lot of other people as well uh
1:18	the team discovered that uh their
1:21	reaction to genomic instability uh
1:24	particularly repetitive regions uh leads
1:26	to the reorganization of Chromatin which
1:28	leads to changes in gene expression and
1:30	phenotypes of aging and what we work on
1:33	in the lab is that that process that we
1:36	worked on in Lenny grunty's lab in yeast
1:38	in the mid-1990s uh is also true for
1:41	mammals um and that there's a backup
1:44	copy of information to reset the
1:46	epigenome
1:48	uh so what I'll do today is I'll share a
1:50	fair bit of unpublished research it's uh
1:53	it's really a coming out moment here
1:55	um so this is how we think in my lab
1:57	um similar to many others we like to
1:59	understand why we get old
2:01	uh and we think that the Hallmarks are
2:04	part of a whole system and we think that
2:06	the loss of information in particular is
2:09	is very important and information comes
2:12	in two types in in biology mainly it's
2:14	the DNA and the epigenome control
2:16	systems and we have a a lot of evidence
2:20	in the field increasingly so that the
2:22	epigenetic noise as we call it and the
2:25	loss of differentiation is a major
2:28	driver of of the process we call aging
2:31	and illness
2:33	um so I'm going to talk about efforts in
2:36	many organisms including humans to slow
2:39	down aging by targeting epigenetic
2:42	modifiers
2:43	um which include the sirtuins which we
2:47	worked on and continued to do so
2:50	I'm going to talk about the ability to
2:52	reverse aspects of Aging including
2:55	epigenetic age
2:57	and I'm going to talk about what we
2:58	really have talked about a lot at this
3:00	conference and in my lab we are
3:02	fascinated with the
3:04	um the goal of having accurate clocks
3:07	that represent epigenetic aging if not
3:10	other aspects of Aging
3:12	um it's a bit of a complicated slide but
3:14	it does cover what we work on in my lab
3:17	this was from a review back in 2008 when
3:20	we published a paper that showed that
3:23	not just in yeast but in mammals
3:24	chromatin modifiers move around during
3:26	aging and that process can be
3:28	accelerated by extreme cellular damage
3:31	and what we used in this case was the
3:33	double-stranded DNA break or dsb and we
3:36	use an enzyme called people ppo1 to
3:39	accelerate what looked like aging and I
3:42	think you've heard probably me talk
3:44	about this before so I'll go quickly but
3:46	we've used this system to understand the
3:49	process of Aging in mammals and and how
3:52	to reverse it and just some some aspects
3:55	I want to point out
3:56	NAD is a cofactor co-substrate as you
3:59	know so Twins and we found that up
4:03	regulating cert one gene expression as
4:05	well as NAD levels in the cell can slow
4:08	down this reorganization of the
4:10	epigenome and prevent loss of gene
4:13	expression patterns and we did this in a
4:15	mouse back in 2008 in in neurons in the
4:18	brain but we've gone a long way since
4:20	then
4:21	come a long way oh we also I want to
4:24	report a little bit about mib626 which
4:26	is an NAD
4:27	precursor uh it's a polymorph of
4:30	nicotinamide mononucleotide that is GMP
4:35	pure it's been in humans and I'll update
4:37	you on that and how that seems to work
4:39	and our goal there is to have a drug
4:42	that will treat
4:44	um not just aging but diseases of aging
4:47	and they're about I think right now
4:49	we've got five clinical trials up and
4:52	running and I'll share some results of
4:54	that
4:55	um so what about the clocks uh we have a
4:58	paper that's up online it's not yet
5:00	published this is work by Patrick
5:02	Griffin and Jen Lee in my lab two
5:04	students who came up with the idea that
5:07	you can greatly reduce the the cost of
5:10	sequencing by uh transposon tagging DNA
5:14	samples and we can pull 500 or more
5:17	people or dogs or mice and we've built
5:21	some and Patrick and Jenna built some
5:23	really accurate clocks for Mouse tissues
5:26	and in humans you can see down below
5:28	wherever I can I give you directions to
5:31	go follow up on this news
5:34	um these are hot off the press human
5:36	clocks from Patrick they're really great
5:38	they've got um
5:40	all the attributes that you'd want this
5:42	is from human blood we have brought in
5:44	over a thousand human samples from
5:47	people a variety of Ages and you can see
5:49	that the the uh our values are really
5:52	great and uh the uh midday of 3.5 uses
5:57	it's not bad for a first start uh and
5:59	this is again just half the presses uh
6:01	the mouse ones look really good too I
6:04	would also phenotypic age clocks which
6:05	we've published on if you're interested
6:07	you could check that out
6:10	uh how about slowing aging well we've
6:12	worked on activators of sirtuins for a
6:15	long time Resveratrol was the one back
6:16	20 years ago we've developed some
6:19	synthetic ones and some NAD precursors
6:21	uh mib626 is as I mentioned an oral
6:25	formulation of a polymorph of mh66 that
6:28	stabilized crystalline and it's gone
6:30	through a lot of safety studies over the
6:32	last few years headed by this lab are
6:35	shally basin's group at Brigham and
6:37	Women's Hospital and David Livingston
6:40	runs the group at Metro biotech which is
6:42	a massachusetts-based company that's
6:44	been making NAD precursors both
6:46	synthetic and natural for the last
6:48	decade
6:49	uh and that and full disclosure this was
6:51	spun out of my lab and others including
6:54	Sheena Mai and Raj after
6:57	uh how do you measure uh what the effect
6:59	might be well one of the ways that
7:01	Shelley's lab did it was to look at
7:03	endurance and strength uh within an MRI
7:07	and so this is uh an example of the
7:10	machine that they built to insert the
7:11	patients into the machine and measure
7:14	their endurance strength and things like
7:16	uh ATP NAD oxygenation
7:20	um and some of the data that hasn't
7:21	probably been published yet but we're
7:22	starting to talk about it and this is
7:24	their group's data not mine uh is that
7:27	uh
7:27	a number of things happen when you take
7:29	uh 1 000 milligrams from roughly a month
7:33	of this uh substance orally
7:37	and you can see here an example of some
7:39	of the data uh the repetitions the
7:41	failure of that leg exercise uh
7:44	significantly greater after taking
7:45	mib636 this is similar or at least
7:48	reminiscent to the mouse data that we
7:50	published in 2018 on endurance in mice
7:53	due to increased vascularization of the
7:57	action on endothelial cells
8:00	um and others nice bit of data I would
8:03	admit it was a surprise a nice surprise
8:05	is that Shelley's group showed that um
8:08	lipids and cholesterol uh went in the
8:11	right direction for improved Health uh
8:13	as you can see here
8:16	uh HDL was not affected which was also
8:18	reassuring
8:21	uh what about acceleration of Aging now
8:23	we do this for two reasons one is to
8:25	understand why we age because if we can
8:27	cause it then we have some idea that
8:29	we're on the right track but we also
8:31	want to know if we can have a model of
8:35	Aging that's much quicker because
8:36	typical longevity experiment takes way
8:38	too long and in organoids organoids are
8:40	way too young when you build an organide
8:42	from a stem cell an ipsc they're age
8:45	zero which is not that useful and so
8:48	we've used this system which you may
8:50	know about it's close to getting
8:52	accepted we hope uh last last stages of
8:56	this uh 12-year Journey
8:59	um actually I started this project with
9:00	Philip oberdorf when I was 39 so I've
9:03	aged a little uh this project is uh the
9:06	combination of 20 labs around the world
9:10	to see if we can displace chromatin
9:13	modifiers in a way that mimics aging and
9:15	we've done that and that's this work
9:17	which we call the ice system and we have
9:19	cell based systems and mouse systems to
9:21	do that
9:22	and we'll use it in a minute I'll show
9:24	you later but we can drive aging
9:26	forwards as far as we can tell
9:27	epigenetically and the other Hallmarks
9:29	of Aging accelerate as well for the most
9:32	part
9:33	the reversal this is a very hot topic as
9:36	you all know we use uh typically we use
9:40	a combination of three of the yamanaka
9:42	factors rather than four we leave out
9:44	cmic and we're using other methods
9:46	chemicals now as well we published this
9:50	um in 2020 so I'm not going to repeat
9:53	that data but we did use it to
9:55	rejuvenate neurons in mice and restore
9:57	Vision in mice that had damaged or old
10:00	retinas by targeting the neurons
10:03	um and we find that we need all three of
10:05	those factors O S and K shown down here
10:08	in this Vector that we can control with
10:10	Doxycycline Teton and Ted off system if
10:12	you would like to try it this isn't uh
10:15	injections in the eye which was in the
10:17	the nature paper this one's the whole
10:19	brain and we're using a variety of aavs
10:21	now to infect different tissues and the
10:23	whole body in the in efforts to not just
10:26	accelerate aging but take those mice and
10:28	wild type and reverse them and see what
10:30	happens and this is work that I'm
10:32	showing you from Xiao Tian uh primarily
10:36	and jeun jeunyang and their goal is to
10:39	reverse the age of the brain and see
10:41	what happens
10:42	and uh well this was the paper I just
10:44	wanted to remind you and we had a lot of
10:47	help from people in the field some of
10:48	who are at this conference uh Morgan's
10:50	here uh that in was great help Steve
10:53	Horvath there's a long list you can see
10:55	here I couldn't have done any of this
10:57	without their Labs as well what was
10:59	amazing about this was that we showed
11:01	that there's a repository of youthful
11:04	information that can reset a cell's
11:06	epigenome we measure gene expression on
11:08	the right you can see it's nicely reset
11:10	proportionally to how this genes were
11:12	expressed when they were young this is
11:13	RNA and on the left I think even
11:16	just as impressive is the methylation
11:18	patterns were largely restored as well
11:21	um and the clock uh which uh Morgan and
11:24	Steve and that even helped us show uh
11:26	was as well and one of the
11:28	interesting things in this paper is we
11:29	found that damage to neurons accelerates
11:33	epigenetic aging as well so it's not
11:35	just DNA cutting
11:37	um or time it's extreme cell stress like
11:40	a nerve Crush that can do it as well
11:43	uh this has been commercialized or is
11:46	being commercialized by life biosciences
11:48	a boston-based company also spun out of
11:50	my lab you can check it out
11:53	um and you'll probably get the website
11:54	if you spell The Sciences correctly
11:57	there's an e in there
11:59	um Blackberry Sciences was started in
12:01	2017 uh Bruce Cassandra at Mass Eye and
12:04	Ear has done a lot of the pre-clinical
12:06	work and safety work we've now got a
12:08	fair amount of data and we're now in
12:10	non-human primates with a goal uh of
12:12	some time in uh the next whole to 24
12:15	months of uh starting uh work towards an
12:18	IND and getting into humans if all goes
12:20	well and our goal is to reverse
12:22	blindness in a variety of different
12:24	disorders in humans
12:26	but it is remarkable if you reverse the
12:28	age of neurons in the retina you can
12:30	restore vision and gene expression this
12:32	way
12:33	um of course I'm standing on the back of
12:34	some very big names uh in this field who
12:37	uh showed pointed the way uh this is new
12:41	data unpublished I was allowed to share
12:43	this from Bruce Cassandra's lab
12:45	uh he and I are infecting not the
12:47	neurons here but the retinal pigment and
12:49	pythelium cells rpe and these give rise
12:52	to uh the photoreceptors and these
12:54	degrade over time particularly in
12:56	macular degeneration and what Bruce has
12:58	found is that he can actually restore
13:00	the morphology and the function of these
13:02	cells and restore eyesight back to a
13:04	young State similar to what happens when
13:06	you rejuvenate neurons in the eye as
13:08	well
13:09	the system uh in the lab now that we're
13:11	doing is more human we have inducible
13:13	human neurons uh where we can
13:16	differentiate them both into flat
13:17	cultures and three-dimensional and we do
13:20	pro-aging with ice and reversal with osk
13:22	typically okay I'll give you some
13:25	examples of what we do
13:27	and this is work mainly by Xiao and Jay
13:29	in the lab we grow the nerves on these
13:31	little culture dishes that can sense
13:33	electrical signals uh when we have a
13:35	control induction of no osk there's not
13:40	very good electrical firing but when we
13:42	rejuvenate them
13:44	uh with uh the osk treatment uh just for
13:48	a short amount of time this just takes a
13:50	little over a week we see that there's a
13:54	great induction of function
13:57	um and it continues out the longer we go
13:59	this is day 50 that you're seeing on the
14:01	right so that's just neurons that's
14:03	human neurons we've got Alzheimer's
14:04	patient neurons as well we can make
14:07	these into little brain organoids you
14:09	can see here that we can turn on all of
14:11	the three yamanaka factors that we like
14:13	in these organoids which have a similar
14:15	brain structure to ours great models
14:19	um for human aging we can age these
14:21	forward and get them to take on
14:23	inflammatory and senescent signatures
14:26	which I think will be a useful model
14:28	in terms of reversal uh we've done this
14:30	in mice as well we can now deliver the
14:33	osk system into various places in the
14:37	brain whole brain or in this case on the
14:39	right the excitatory neurons and in both
14:43	cases we get an improvement in learning
14:45	in these old mice which is what I think
14:49	might have we might find out as a field
14:51	is that diseases of old age particularly
14:53	in the brain I'm thinking of like
14:55	Alzheimer's if you make the the brain
14:57	young then the diseases just go away
14:59	because most of these diseases of Aging
15:01	are caused by edging I mean it's obvious
15:03	to a lot of us but to the rest of the
15:05	world it's not
15:07	um so I want to thank the people who
15:09	made this possible uh there's a large
15:11	group The the clinical trial group is at
15:14	Brigham and Women's Hospital there are
15:16	four other clinical trials that are
15:18	ongoing there's one actually for
15:20	Alzheimer's disease that's starting to
15:21	recruit there's one um well I won't say
15:25	the whole lot but they're interesting
15:26	ones
15:28	um you can see that we've got
15:29	collaborators both for exercise
15:31	physiology the hormones and this is um
15:34	the mib636 group at Metro biotech
15:38	uh here we have uh the people in my lab
15:40	that helped or did major contributions I
15:43	want to point out the work of Jay who
15:45	did the Ice Mouse
15:47	um and matoshi I want to thank everyone
15:49	really but I want to focus on I
15:52	mentioned Xiao Jian
15:55	um for the osk work uh Yuan Chang Liu
15:58	who left the lab after he published
16:00	rightly so uh he's uh not listed but he
16:03	was the first author on that nature
16:05	paper and I also want to point out Chris
16:07	who's doing reversal of senescence uh
16:10	Gerald who's working on a lot of the
16:13	mouse projects I could go on I won't uh
16:15	do that but I do want to thank Patrick
16:17	who I probably didn't mention enough he
16:19	was the one that came up with this idea
16:21	to do the time seek clock
16:23	um so many collaborators it's impossible
16:25	to thank everybody these are the
16:26	highlights and I am so grateful for
16:29	their uh advice uh reagents and uh and
16:32	friendship over the years and the people
16:34	who uh supported the work financially
16:36	have been amazing too
16:38	um so I'll stop there and take any
16:39	questions thank you for having me
16:47	thank you so much David we have a
16:50	question here in the front from one of
16:52	our Inspire ambassadors
16:54	they're the high school students that
16:56	are involved in the erdd organization
17:00	hi my name is Andrea
17:02	um I was just wondering so you you said
17:05	that you used three of the Fourier
17:06	Monica factors when looking at eyesight
17:09	Rejuvenation have you tested any other
17:11	combinations of these yamanaka factors
17:15	we tested all combinations
17:18	um and
17:19	we needed three uh four uh worked as
17:23	well but we were concerned about the
17:26	loss of cellular identity so we left c
17:28	MC out and those three are necessary if
17:31	we just do one or two combinations uh it
17:34	did not work and if we gave them
17:36	individually in different viruses it
17:39	still didn't work so it seems like we
17:40	need to package them into the same AV
17:41	three of them put them in a polycystron
17:44	and get those in were there slight
17:46	changes maybe but the the big difference
17:49	was when when we put in all three now we
17:52	were trying for years different factors
17:53	so we tried nanog and that didn't work
17:55	very well it was pretty toxic
17:58	um and I think I mean it sounds like we
18:00	just tried something and it worked but
18:01	it was actually many years of one
18:03	Chang's efforts to find this particular
18:05	combination
18:08	great thank you so much uh it's quite
18:11	late here and we have we have a couple
18:13	questions Paul sorry it's late for me I
18:15	guess it's a couple of questions in the
18:17	back there
18:19	hi I was wondering if you also tested
18:21	the data that you showed in rpe cells in
18:24	pathological conditions either genetic
18:26	or chemical
18:29	oh uh yeah so it's been done in a uh a
18:32	mouse model of macular degeneration
18:37	um with the the iodide model if you're
18:39	familiar with it and it uh it works well
18:42	in that situation okay cool cool thanks
18:46	there's another one from Lawrence
18:48	hi David uh I don't know if you can see
18:50	me it's Lauren Zion from vitadel I am
18:53	wondering about the the time sake if you
18:55	can talk a bit about the implications
18:57	there uh how would it look like for the
19:00	consumer what does this enable what are
19:03	the uh downsides as well
19:07	uh yeah I don't know of any true
19:10	downsides uh
19:12	the cost is the main thing so what we do
19:14	is we we barcode each each person's
19:17	sample and we run them through the same
19:19	sequencing reaction there's also an
19:21	enrichment step that I didn't mention uh
19:23	and so it currently costs us
19:25	less than a you know basically a few
19:27	dollars less than five dollars per
19:29	sample and that's just on the bench here
19:30	not high throughput not optimized so we
19:33	think we can get the test down to really
19:35	low amounts and for the consumer that's
19:37	of course a benefit
19:40	um it this technology is licensed to a
19:42	company that next year will if all goes
19:45	well provide a product to Consumers
19:48	um to try this out but I wouldn't
19:50	release that until we've shown that it
19:52	works well we've done I think a couple
19:53	of thousand people so far we have 10 000
19:56	samples waiting to be tested and about
19:58	250 000 people on the waitlist so we
20:01	will use those numbers to aim to get a
20:03	really good clock and not put it out
20:04	there at all if it doesn't work I'm
20:07	assuming the costs doesn't include the
20:09	the logistics right so it would only
20:10	make sense in in batches with shipping
20:13	or something like that
20:14	yeah you know the shipping will be more
20:17	expensive than the cost of the test
20:18	eventually but yeah that that's just the
20:21	cost of the reagents and the the
20:23	sequencing yeah
20:25	great one more uh hello David uh so my
20:29	question is have you ever tried to uh
20:31	combine also fasting and color reduction
20:34	as a synergistic effect in your
20:36	reprogramming with the harmonica factors
20:38	uh we have not we have not we
20:42	have tried a few chemicals in
20:43	combination and we're still working on
20:45	that but no I think it's a good idea
20:48	um
20:49	it may be that some of the genes that I
20:52	talked about today could be involved
20:54	we'll try it
20:56	thank you
20:57	all right very cool thank you so much
20:59	David that was a fantastic and inspiring
21:02	talk we're looking forward
21:08	and we're living we're looking forward
21:10	to seeing you here next year so thank
21:13	you so much and everybody will
21:16	reconvene in 13 hours maybe we'll see
21:19	each other in the bar thank you so much
21:21	for today and see you later
21:29	[Applause]
21:33	[Music]