2022-10-24 - Presentation Dr. David Sinclair - ARDD2022 - Great release of unpublished data from David Sinclair's Lab: Difference between revisions
No edit summary |
m (Strimo moved page 24.10.2022 - Presentation Dr. David Sinclair - ARDD2022 - Great release of unpublished data from David Sinclair's Lab to 2022-10-24 - Presentation Dr. David Sinclair - ARDD2022 - Great release of unpublished data from David Sinclair's Lab without leaving a redirect) |
(No difference)
|
Latest revision as of 02:50, 15 September 2023
- Interviewee: Dr. David Sinclair
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] |