1 00:00:01,134 --> 00:00:05,793 This is a painting from the 16th century from Lucas Cranach the Elder. 2 00:00:06,160 --> 00:00:08,926 It shows the famous Fountain of Youth. 3 00:00:09,308 --> 00:00:15,034 If you drink its water or you bathe in it, you will get health and youth. 4 00:00:15,857 --> 00:00:21,406 Every culture, every civilization has dreamed of finding eternal youth. 5 00:00:22,044 --> 00:00:26,796 There are people like Alexander the Great or Ponce De León, the explorer, 6 00:00:26,820 --> 00:00:30,251 who spent much of their life chasing the Fountain of Youth. 7 00:00:30,726 --> 00:00:31,894 They didn't find it. 8 00:00:33,450 --> 00:00:36,050 But what if there was something to it? 9 00:00:36,074 --> 00:00:38,773 What if there was something to this Fountain of Youth? 10 00:00:39,284 --> 00:00:44,462 I will share an absolutely amazing development in aging research 11 00:00:44,486 --> 00:00:48,096 that could revolutionize the way we think about aging 12 00:00:48,120 --> 00:00:51,322 and how we may treat age-related diseases in the future. 13 00:00:52,145 --> 00:00:54,654 It started with experiments that showed, 14 00:00:54,678 --> 00:00:57,972 in a recent number of studies about growing, 15 00:00:57,996 --> 00:01:03,997 that animals -- old mice -- that share a blood supply with young mice 16 00:01:04,021 --> 00:01:05,625 can get rejuvenated. 17 00:01:06,148 --> 00:01:10,757 This is similar to what you might see in humans, in Siamese twins, 18 00:01:10,781 --> 00:01:12,869 and I know this sounds a bit creepy. 19 00:01:13,338 --> 00:01:19,285 But what Tom Rando, a stem-cell researcher, reported in 2007, 20 00:01:19,309 --> 00:01:22,809 was that old muscle from a mouse can be rejuvenated 21 00:01:22,833 --> 00:01:27,462 if it's exposed to young blood through common circulation. 22 00:01:27,903 --> 00:01:32,546 This was reproduced by Amy Wagers at Harvard a few years later, 23 00:01:32,570 --> 00:01:37,165 and others then showed that similar rejuvenating effects could be observed 24 00:01:37,189 --> 00:01:39,975 in the pancreas, the liver and the heart. 25 00:01:40,974 --> 00:01:45,071 But what I'm most excited about, and several other labs as well, 26 00:01:45,095 --> 00:01:47,514 is that this may even apply to the brain. 27 00:01:48,715 --> 00:01:54,046 So, what we found is that an old mouse exposed to a young environment 28 00:01:54,070 --> 00:01:57,083 in this model called parabiosis, 29 00:01:57,107 --> 00:01:58,899 shows a younger brain -- 30 00:01:58,923 --> 00:02:01,105 and a brain that functions better. 31 00:02:01,966 --> 00:02:03,556 And I repeat: 32 00:02:03,580 --> 00:02:09,793 an old mouse that gets young blood through shared circulation 33 00:02:09,817 --> 00:02:12,801 looks younger and functions younger in its brain. 34 00:02:13,998 --> 00:02:15,530 So when we get older -- 35 00:02:15,554 --> 00:02:18,226 we can look at different aspects of human cognition, 36 00:02:18,250 --> 00:02:20,003 and you can see on this slide here, 37 00:02:20,027 --> 00:02:23,410 we can look at reasoning, verbal ability and so forth. 38 00:02:23,899 --> 00:02:29,178 And up to around age 50 or 60, these functions are all intact, 39 00:02:29,202 --> 00:02:33,684 and as I look at the young audience here in the room, we're all still fine. 40 00:02:33,708 --> 00:02:34,716 (Laughter) 41 00:02:34,740 --> 00:02:38,547 But it's scary to see how all these curves go south. 42 00:02:38,571 --> 00:02:40,160 And as we get older, 43 00:02:40,184 --> 00:02:44,235 diseases such as Alzheimer's and others may develop. 44 00:02:45,004 --> 00:02:48,575 We know that with age, the connections between neurons -- 45 00:02:48,599 --> 00:02:53,250 the way neurons talk to each other, the synapses -- they start to deteriorate; 46 00:02:53,274 --> 00:02:56,580 neurons die, the brain starts to shrink, 47 00:02:56,604 --> 00:03:00,596 and there's an increased susceptibility for these neurodegenerative diseases. 48 00:03:01,573 --> 00:03:06,482 One big problem we have -- to try to understand how this really works 49 00:03:06,506 --> 00:03:09,102 at a very molecular mechanistic level -- 50 00:03:09,126 --> 00:03:13,176 is that we can't study the brains in detail, in living people. 51 00:03:14,033 --> 00:03:17,019 We can do cognitive tests, we can do imaging -- 52 00:03:17,043 --> 00:03:19,739 all kinds of sophisticated testing. 53 00:03:19,763 --> 00:03:23,381 But we usually have to wait until the person dies 54 00:03:23,405 --> 00:03:28,499 to get the brain and look at how it really changed through age or in a disease. 55 00:03:28,888 --> 00:03:31,952 This is what neuropathologists do, for example. 56 00:03:32,333 --> 00:03:38,000 So, how about we think of the brain as being part of the larger organism. 57 00:03:38,024 --> 00:03:40,501 Could we potentially understand more 58 00:03:40,525 --> 00:03:43,454 about what happens in the brain at the molecular level 59 00:03:43,478 --> 00:03:47,064 if we see the brain as part of the entire body? 60 00:03:47,088 --> 00:03:51,965 So if the body ages or gets sick, does that affect the brain? 61 00:03:51,989 --> 00:03:56,412 And vice versa: as the brain gets older, does that influence the rest of the body? 62 00:03:57,050 --> 00:04:00,541 And what connects all the different tissues in the body 63 00:04:00,565 --> 00:04:01,715 is blood. 64 00:04:02,366 --> 00:04:08,191 Blood is the tissue that not only carries cells that transport oxygen, for example, 65 00:04:08,215 --> 00:04:09,456 the red blood cells, 66 00:04:09,480 --> 00:04:11,680 or fights infectious diseases, 67 00:04:11,704 --> 00:04:15,975 but it also carries messenger molecules, 68 00:04:15,999 --> 00:04:19,911 hormone-like factors that transport information 69 00:04:19,935 --> 00:04:24,068 from one cell to another, from one tissue to another, 70 00:04:24,092 --> 00:04:25,549 including the brain. 71 00:04:25,573 --> 00:04:30,711 So if we look at how the blood changes in disease or age, 72 00:04:30,735 --> 00:04:33,098 can we learn something about the brain? 73 00:04:33,651 --> 00:04:38,487 We know that as we get older, the blood changes as well, 74 00:04:38,511 --> 00:04:41,470 so these hormone-like factors change as we get older. 75 00:04:41,494 --> 00:04:45,693 And by and large, factors that we know are required 76 00:04:45,717 --> 00:04:49,138 for the development of tissues, for the maintenance of tissues -- 77 00:04:49,162 --> 00:04:52,039 they start to decrease as we get older, 78 00:04:52,063 --> 00:04:56,766 while factors involved in repair, in injury and in inflammation -- 79 00:04:56,790 --> 00:04:58,740 they increase as we get older. 80 00:04:58,764 --> 00:05:03,806 So there's this unbalance of good and bad factors, if you will. 81 00:05:04,988 --> 00:05:07,981 And to illustrate what we can do potentially with that, 82 00:05:08,005 --> 00:05:10,657 I want to talk you through an experiment that we did. 83 00:05:10,681 --> 00:05:14,330 We had almost 300 blood samples from healthy human beings 84 00:05:14,354 --> 00:05:16,871 20 to 89 years of age, 85 00:05:16,895 --> 00:05:20,790 and we measured over 100 of these communication factors, 86 00:05:20,814 --> 00:05:24,908 these hormone-like proteins that transport information between tissues. 87 00:05:25,266 --> 00:05:26,942 And what we noticed first 88 00:05:26,966 --> 00:05:29,783 is that between the youngest and the oldest group, 89 00:05:29,807 --> 00:05:33,104 about half the factors changed significantly. 90 00:05:33,128 --> 00:05:36,263 So our body lives in a very different environment as we get older, 91 00:05:36,287 --> 00:05:38,038 when it comes to these factors. 92 00:05:38,062 --> 00:05:41,558 And using statistical or bioinformatics programs, 93 00:05:41,582 --> 00:05:46,276 we could try to discover those factors that best predict age -- 94 00:05:46,300 --> 00:05:49,943 in a way, back-calculate the relative age of a person. 95 00:05:50,337 --> 00:05:53,193 And the way this looks is shown in this graph. 96 00:05:53,618 --> 00:05:58,987 So, on the one axis you see the actual age a person lived, 97 00:05:59,011 --> 00:06:00,316 the chronological age. 98 00:06:00,340 --> 00:06:02,062 So, how many years they lived. 99 00:06:02,086 --> 00:06:04,794 And then we take these top factors that I showed you, 100 00:06:04,818 --> 00:06:09,662 and we calculate their relative age, their biological age. 101 00:06:10,708 --> 00:06:14,342 And what you see is that there is a pretty good correlation, 102 00:06:14,366 --> 00:06:17,681 so we can pretty well predict the relative age of a person. 103 00:06:17,705 --> 00:06:21,620 But what's really exciting are the outliers, 104 00:06:21,644 --> 00:06:23,448 as they so often are in life. 105 00:06:23,922 --> 00:06:28,490 You can see here, the person I highlighted with the green dot 106 00:06:28,514 --> 00:06:31,110 is about 70 years of age 107 00:06:31,134 --> 00:06:36,140 but seems to have a biological age, if what we're doing here is really true, 108 00:06:36,164 --> 00:06:38,207 of only about 45. 109 00:06:38,231 --> 00:06:41,715 So is this a person that actually looks much younger than their age? 110 00:06:42,183 --> 00:06:46,699 But more importantly: Is this a person who is maybe at a reduced risk 111 00:06:46,723 --> 00:06:50,047 to develop an age-related disease and will have a long life -- 112 00:06:50,071 --> 00:06:51,566 will live to 100 or more? 113 00:06:52,402 --> 00:06:56,963 On the other hand, the person here, highlighted with the red dot, 114 00:06:56,987 --> 00:07:01,893 is not even 40, but has a biological age of 65. 115 00:07:01,917 --> 00:07:06,315 Is this a person at an increased risk of developing an age-related disease? 116 00:07:06,339 --> 00:07:09,995 So in our lab, we're trying to understand these factors better, 117 00:07:10,019 --> 00:07:12,257 and many other groups are trying to understand, 118 00:07:12,281 --> 00:07:14,357 what are the true aging factors, 119 00:07:14,381 --> 00:07:19,354 and can we learn something about them to possibly predict age-related diseases? 120 00:07:20,281 --> 00:07:24,343 So what I've shown you so far is simply correlational, right? 121 00:07:24,367 --> 00:07:28,398 You can just say, "Well, these factors change with age," 122 00:07:28,422 --> 00:07:32,077 but you don't really know if they do something about aging. 123 00:07:33,031 --> 00:07:36,079 So what I'm going to show you now is very remarkable 124 00:07:36,103 --> 00:07:41,174 and it suggests that these factors can actually modulate the age of a tissue. 125 00:07:41,845 --> 00:07:45,143 And that's where we come back to this model called parabiosis. 126 00:07:45,167 --> 00:07:47,707 So, parabiosis is done in mice 127 00:07:47,731 --> 00:07:52,643 by surgically connecting the two mice together, 128 00:07:52,667 --> 00:07:55,000 and that leads then to a shared blood system, 129 00:07:55,024 --> 00:07:59,811 where we can now ask, "How does the old brain get influenced 130 00:07:59,835 --> 00:08:01,573 by exposure to the young blood?" 131 00:08:02,144 --> 00:08:04,348 And for this purpose, we use young mice 132 00:08:04,372 --> 00:08:07,825 that are an equivalency of 20-year-old people, 133 00:08:07,849 --> 00:08:12,185 and old mice that are roughly 65 years old in human years. 134 00:08:12,958 --> 00:08:15,784 What we found is quite remarkable. 135 00:08:15,808 --> 00:08:19,528 We find there are more neural stem cells that make new neurons 136 00:08:19,552 --> 00:08:20,884 in these old brains. 137 00:08:21,351 --> 00:08:23,933 There's an increased activity of the synapses, 138 00:08:23,957 --> 00:08:25,996 the connections between neurons. 139 00:08:26,020 --> 00:08:29,305 There are more genes expressed that are known to be involved 140 00:08:29,329 --> 00:08:31,076 in the formation of new memories. 141 00:08:31,659 --> 00:08:34,167 And there's less of this bad inflammation. 142 00:08:35,427 --> 00:08:41,923 But we observed that there are no cells entering the brains of these animals. 143 00:08:41,947 --> 00:08:43,333 So when we connect them, 144 00:08:43,357 --> 00:08:48,733 there are actually no cells going into the old brain, in this model. 145 00:08:49,379 --> 00:08:53,040 Instead, we've reasoned, then, that it must be the soluble factors, 146 00:08:53,064 --> 00:08:57,847 so we could collect simply the soluble fraction of blood which is called plasma, 147 00:08:57,871 --> 00:09:01,815 and inject either young plasma or old plasma into these mice, 148 00:09:01,839 --> 00:09:04,207 and we could reproduce these rejuvenating effects, 149 00:09:04,231 --> 00:09:05,945 but what we could also do now 150 00:09:05,969 --> 00:09:08,419 is we could do memory tests with mice. 151 00:09:08,443 --> 00:09:12,296 As mice get older, like us humans, they have memory problems. 152 00:09:12,818 --> 00:09:14,411 It's just harder to detect them, 153 00:09:14,435 --> 00:09:16,779 but I'll show you in a minute how we do that. 154 00:09:16,803 --> 00:09:19,498 But we wanted to take this one step further, 155 00:09:19,522 --> 00:09:23,562 one step closer to potentially being relevant to humans. 156 00:09:23,586 --> 00:09:26,783 What I'm showing you now are unpublished studies, 157 00:09:26,807 --> 00:09:31,340 where we used human plasma, young human plasma, 158 00:09:31,364 --> 00:09:33,213 and as a control, saline, 159 00:09:33,237 --> 00:09:35,113 and injected it into old mice, 160 00:09:35,137 --> 00:09:39,989 and asked, can we again rejuvenate these old mice? 161 00:09:40,013 --> 00:09:41,673 Can we make them smarter? 162 00:09:42,104 --> 00:09:45,393 And to do this, we used a test. It's called a Barnes maze. 163 00:09:45,417 --> 00:09:48,572 This is a big table that has lots of holes in it, 164 00:09:48,596 --> 00:09:52,079 and there are guide marks around it, 165 00:09:52,103 --> 00:09:54,709 and there's a bright light, as on this stage here. 166 00:09:54,733 --> 00:09:57,866 The mice hate this and they try to escape, 167 00:09:57,890 --> 00:10:02,146 and find the single hole that you see pointed at with an arrow, 168 00:10:02,170 --> 00:10:04,115 where a tube is mounted underneath 169 00:10:04,139 --> 00:10:07,332 where they can escape and feel comfortable in a dark hole. 170 00:10:07,977 --> 00:10:09,779 So we teach them, over several days, 171 00:10:09,803 --> 00:10:12,706 to find this space on these cues in the space, 172 00:10:12,730 --> 00:10:15,524 and you can compare this for humans, 173 00:10:15,548 --> 00:10:19,778 to finding your car in a parking lot after a busy day of shopping. 174 00:10:19,802 --> 00:10:20,803 (Laughter) 175 00:10:20,827 --> 00:10:24,578 Many of us have probably had some problems with that. 176 00:10:24,602 --> 00:10:26,620 So, let's look at an old mouse here. 177 00:10:26,954 --> 00:10:29,130 This is an old mouse that has memory problems, 178 00:10:29,154 --> 00:10:30,843 as you'll notice in a moment. 179 00:10:31,305 --> 00:10:36,029 It just looks into every hole, but it didn't form this spacial map 180 00:10:36,053 --> 00:10:41,300 that would remind it where it was in the previous trial or the last day. 181 00:10:41,873 --> 00:10:47,340 In stark contrast, this mouse here is a sibling of the same age, 182 00:10:47,364 --> 00:10:52,783 but it was treated with young human plasma for three weeks, 183 00:10:52,807 --> 00:10:55,340 with small injections every three days. 184 00:10:55,741 --> 00:10:59,964 And as you noticed, it almost looks around, "Where am I?" -- 185 00:10:59,988 --> 00:11:02,895 and then walks straight to that hole and escapes. 186 00:11:02,919 --> 00:11:05,783 So, it could remember where that hole was. 187 00:11:06,742 --> 00:11:10,430 So by all means, this old mouse seems to be rejuvenated -- 188 00:11:10,454 --> 00:11:12,833 it functions more like a younger mouse. 189 00:11:12,857 --> 00:11:15,563 And it also suggests that there is something 190 00:11:15,587 --> 00:11:20,578 not only in young mouse plasma, but in young human plasma 191 00:11:20,602 --> 00:11:24,262 that has the capacity to help this old brain. 192 00:11:24,834 --> 00:11:25,986 So to summarize, 193 00:11:26,010 --> 00:11:30,209 we find the old mouse, and its brain in particular, are malleable. 194 00:11:30,233 --> 00:11:33,684 They're not set in stone; we can actually change them. 195 00:11:33,708 --> 00:11:35,181 It can be rejuvenated. 196 00:11:35,680 --> 00:11:38,277 Young blood factors can reverse aging, 197 00:11:38,301 --> 00:11:40,013 and what I didn't show you -- 198 00:11:40,037 --> 00:11:45,259 in this model, the young mouse actually suffers from exposure to the old. 199 00:11:45,283 --> 00:11:48,663 So there are old-blood factors that can accelerate aging. 200 00:11:49,725 --> 00:11:54,042 And most importantly, humans may have similar factors, 201 00:11:54,066 --> 00:11:58,144 because we can take young human blood and have a similar effect. 202 00:11:58,592 --> 00:12:02,148 Old human blood, I didn't show you, does not have this effect; 203 00:12:02,172 --> 00:12:03,934 it does not make the mice younger. 204 00:12:05,071 --> 00:12:08,699 So, is this magic transferable to humans? 205 00:12:08,723 --> 00:12:12,352 We're running a small clinical study at Stanford, 206 00:12:12,376 --> 00:12:16,252 where we treat Alzheimer's patients with mild disease 207 00:12:16,276 --> 00:12:22,886 with a pint of plasma from young volunteers, 20-year-olds, 208 00:12:22,910 --> 00:12:25,505 and do this once a week for four weeks, 209 00:12:25,529 --> 00:12:28,692 and then we look at their brains with imaging. 210 00:12:29,050 --> 00:12:30,894 We test them cognitively, 211 00:12:30,918 --> 00:12:34,924 and we ask their caregivers for daily activities of living. 212 00:12:34,948 --> 00:12:38,867 What we hope is that there are some signs of improvement 213 00:12:38,891 --> 00:12:40,255 from this treatment. 214 00:12:40,758 --> 00:12:43,314 And if that's the case, that could give us hope 215 00:12:43,338 --> 00:12:45,758 that what I showed you works in mice 216 00:12:45,782 --> 00:12:47,560 might also work in humans. 217 00:12:48,478 --> 00:12:50,836 Now, I don't think we will live forever. 218 00:12:51,955 --> 00:12:54,292 But maybe we discovered 219 00:12:54,316 --> 00:12:57,403 that the Fountain of Youth is actually within us, 220 00:12:57,427 --> 00:12:59,165 and it has just dried out. 221 00:12:59,574 --> 00:13:02,402 And if we can turn it back on a little bit, 222 00:13:02,426 --> 00:13:07,053 maybe we can find the factors that are mediating these effects, 223 00:13:07,077 --> 00:13:09,664 we can produce these factors synthetically 224 00:13:09,688 --> 00:13:13,701 and we can treat diseases of aging, such as Alzheimer's disease 225 00:13:13,725 --> 00:13:14,955 or other dementias. 226 00:13:15,282 --> 00:13:16,433 Thank you very much. 227 00:13:16,457 --> 00:13:19,750 (Applause)