1 00:00:05,142 --> 00:00:05,743 WELCOME. 2 00:00:05,743 --> 00:00:07,378 IT'S MY PLEASURE TO INTRODUCE 3 00:00:07,378 --> 00:00:08,479 OUR SPEAKER TODAY. 4 00:00:08,479 --> 00:00:14,713 I'M RICHARD HODES, HAPPY TO BE 5 00:00:14,713 --> 00:00:16,915 WELCOMING YOU TO THE FLORENCE 6 00:00:16,915 --> 00:00:17,783 MAHONEY LECTURE, THE TITLE OF 7 00:00:17,783 --> 00:00:20,085 WHICH WILL BE TARGETING AGING, 8 00:00:20,085 --> 00:00:24,122 LONGEVITY AND REJUVENATION. 9 00:00:24,122 --> 00:00:28,193 VADIM GLADYSHEV IS THE SPEAKER. 10 00:00:28,193 --> 00:00:29,928 A COUPLE ITEMS OF HISTORY. 11 00:00:29,928 --> 00:00:32,130 ONE IS THE BACKGROUND BEHIND THE 12 00:00:32,130 --> 00:00:33,665 NAMED LECTURER, FLORENCE 13 00:00:33,665 --> 00:00:33,899 MAHONEY. 14 00:00:33,899 --> 00:00:35,734 SO I HAD THE PLEASURE OF KNOWING 15 00:00:35,734 --> 00:00:37,436 FLORENCE MAHONEY, SHE DIED IN 16 00:00:37,436 --> 00:00:39,338 2002 AT THE AGE OF 103, AND SHE 17 00:00:39,338 --> 00:00:43,475 WAS REALLY AN EXTRAORDINARY 18 00:00:43,475 --> 00:00:44,743 PERSON WHO WAS LARGELY 19 00:00:44,743 --> 00:00:45,777 RESPONSIBLE FOR THE FOUNDATION 20 00:00:45,777 --> 00:00:47,212 OF NIA, ALSO SOME OTHER 21 00:00:47,212 --> 00:00:48,313 INSTITUTES, SHE WAS GREAT 22 00:00:48,313 --> 00:00:51,383 POLITICIAN AND SHE WOULD HOLD 23 00:00:51,383 --> 00:00:52,684 COURT WITH INFLUENTIAL 24 00:00:52,684 --> 00:00:55,087 POLITICIANS IN HER HOME IN 25 00:00:55,087 --> 00:00:56,822 GEORGETOWN, WHERE A NUMBER OF 26 00:00:56,822 --> 00:00:58,590 MOVIES HAVE BEEN FILMED AS WELL. 27 00:00:58,590 --> 00:00:59,057 EXTRAORDINARY WOMAN. 28 00:00:59,057 --> 00:01:02,627 AND WE WOULD MEET BEFORE THE 29 00:01:02,627 --> 00:01:05,130 SELECTION OF A SPEAKER, SHE WAS 30 00:01:05,130 --> 00:01:07,232 INSISTENT ON HARD SCIENCE, SHE 31 00:01:07,232 --> 00:01:08,100 WANTED REAL HARD SCIENCE. 32 00:01:08,100 --> 00:01:12,270 UP TO THE AGE OF 103, SHE WAS 33 00:01:12,270 --> 00:01:13,805 SHARP ENOUGH TO BE DELIGHTED 34 00:01:13,805 --> 00:01:16,842 TODAY BY THE CHOICE OF OUR 35 00:01:16,842 --> 00:01:17,175 SPEAKER. 36 00:01:17,175 --> 00:01:20,479 BEFORE WE GET STARTED, WON'T BE 37 00:01:20,479 --> 00:01:21,880 ON SCREEN BUT THOSE INTERESTED 38 00:01:21,880 --> 00:01:26,318 IN CME CREDIT, THE CODE IS 39 00:01:26,318 --> 00:01:31,189 57682. 40 00:01:31,189 --> 00:01:32,491 ON GOOD DAYS, THAT WOULD BE 41 00:01:32,491 --> 00:01:34,059 DISPLAYED UP HERE, BUT I THINK 42 00:01:34,059 --> 00:01:35,761 IT'S GOOD FOR SOME TIME 43 00:01:35,761 --> 00:01:36,862 AFTERWARDS, IF YOU WANT TO COME 44 00:01:36,862 --> 00:01:38,964 UP AND GET IT FROM US LATER, WE 45 00:01:38,964 --> 00:01:40,032 CAN DO THAT. 46 00:01:40,032 --> 00:01:42,067 IN ADDITION, DURING -- THOSE WHO 47 00:01:42,067 --> 00:01:43,969 ARE JOINING BY VIDEOCAST, IF YOU 48 00:01:43,969 --> 00:01:45,504 HAD QUESTIONS, YOU CAN ENTER 49 00:01:45,504 --> 00:01:49,241 THEM UNDER THE LIVE FEEDBACK 50 00:01:49,241 --> 00:01:50,976 ICON AND WE'LL COLLECT THOSE AND 51 00:01:50,976 --> 00:01:52,878 THEY'LL BE READ OUT AND ANSWERED 52 00:01:52,878 --> 00:01:55,013 IN THE DISCUSSION PERIOD. 53 00:01:55,013 --> 00:01:56,348 FOR THOSE HERE IN PERSON, WE 54 00:01:56,348 --> 00:01:57,649 HAVE MICROPHONES TO DO THAT 55 00:01:57,649 --> 00:01:57,983 LIVE. 56 00:01:57,983 --> 00:02:00,185 IT'S ALSO GOING TO BE -- THERE'S 57 00:02:00,185 --> 00:02:01,420 ALSO GOING TO BE A RECEPTION 58 00:02:01,420 --> 00:02:02,554 AFTER THE LECTURE, WANT TO MAKE 59 00:02:02,554 --> 00:02:04,656 YOU ALL AWARE OF THAT WITH SOME 60 00:02:04,656 --> 00:02:08,593 REASONABLY HEALTHY AND BALANCED 61 00:02:08,593 --> 00:02:08,927 REFRESHMENTS. 62 00:02:08,927 --> 00:02:10,996 SO TO INTRODUCE OUR SPEAKER 63 00:02:10,996 --> 00:02:11,930 TODAY, VADIM GLADYSHEV IS 64 00:02:11,930 --> 00:02:14,066 PROFESSOR OF MEDICINE AT 65 00:02:14,066 --> 00:02:15,967 HARVARD, ALSO AN APPOINTMENT AT 66 00:02:15,967 --> 00:02:19,304 THE BROAD INSTITUTE AND HE'S 67 00:02:19,304 --> 00:02:20,939 BEEN A PIONEER IN THE AREA OF 68 00:02:20,939 --> 00:02:22,874 REDOX BIOLOGY AND I'LL ELABORATE 69 00:02:22,874 --> 00:02:23,909 ON THAT A BIT. 70 00:02:23,909 --> 00:02:25,911 HE GOT HIS UNDERGRADUATE DEGREES 71 00:02:25,911 --> 00:02:26,511 IN MOSCOW. 72 00:02:26,511 --> 00:02:28,480 THEN HE CAME FOR POSTDOCTORAL 73 00:02:28,480 --> 00:02:29,481 FELLOWSHIPS HERE ON CAMPUS. 74 00:02:29,481 --> 00:02:31,349 SO HE KNOWS THE PLACE. 75 00:02:31,349 --> 00:02:33,185 OR AT LEAST WHAT IT USED TO LOOK 76 00:02:33,185 --> 00:02:33,652 LIKE. 77 00:02:33,652 --> 00:02:35,821 THIS IS WITH NHLBI AND NCI, BUT 78 00:02:35,821 --> 00:02:38,457 MORE TO THE POINT, HOW MANY OF 79 00:02:38,457 --> 00:02:39,758 YOU NOTICED WHEN YOU WALK BY ALL 80 00:02:39,758 --> 00:02:40,759 THE TIME THE EXHIBIT THAT'S 81 00:02:40,759 --> 00:02:45,564 RIGHT UP THERE ON THE STADMAN 82 00:02:45,564 --> 00:02:46,498 PATH. 83 00:02:46,498 --> 00:02:49,234 EARL AND TERRY STADMAN, HIS 84 00:02:49,234 --> 00:02:50,402 FIRST POSTDOC WAS IN THE STADMAN 85 00:02:50,402 --> 00:02:50,702 LAB. 86 00:02:50,702 --> 00:02:52,237 IF YOU GO UP THERE AND A LOOK AT 87 00:02:52,237 --> 00:02:54,306 A FACE MASK ATTACHED TO A TANK, 88 00:02:54,306 --> 00:02:57,008 HE'S GOT THE RECORD SECOND IN 89 00:02:57,008 --> 00:02:58,009 PLACE FOR NUMBER OF HOURS SPENT 90 00:02:58,009 --> 00:02:58,577 IN THERE. 91 00:02:58,577 --> 00:03:01,079 THIS WAS TO BREATHE AIR IN A 92 00:03:01,079 --> 00:03:04,816 SEALED NITROGEN ENVIRONMENT TO 93 00:03:04,816 --> 00:03:05,584 LOOK AT MICROBES. 94 00:03:05,584 --> 00:03:06,785 THIS WHOLE STORY IN HISTORY 95 00:03:06,785 --> 00:03:08,086 COULDN'T BE MORE FITTING FOR OUR 96 00:03:08,086 --> 00:03:10,255 SPEAKER TODAY. 97 00:03:10,255 --> 00:03:14,426 HE'S TRANSFORMED THE FIELD, 98 00:03:14,426 --> 00:03:18,196 WIDELY RECOGNIZED WITH HIS 99 00:03:18,196 --> 00:03:19,464 CONTRIBUTIONS, NOW AN NIA 100 00:03:19,464 --> 00:03:23,101 GRANTEE, FULL PROFESSOR, EUREKA 101 00:03:23,101 --> 00:03:24,069 PIONEER AWARDS, HIS 102 00:03:24,069 --> 00:03:25,137 CONTRIBUTIONS HAVE BEEN MANY. 103 00:03:25,137 --> 00:03:28,640 SO WITHOUT FURTHER ADO WN AND WH 104 00:03:28,640 --> 00:03:30,308 THAT HISTORICAL INTRODUCTION, 105 00:03:30,308 --> 00:03:35,213 IT'S A GREAT PLEASURE TO WELCOME 106 00:03:35,213 --> 00:03:36,114 HIM TO SPEAK HERE TODAY. 107 00:03:36,114 --> 00:03:40,919 [APPLAUSE] 108 00:03:40,919 --> 00:03:42,654 >> THANK YOU, DR. HODES. 109 00:03:42,654 --> 00:03:44,189 IT'S A GREAT PLEASURE TO BE HERE 110 00:03:44,189 --> 00:03:45,590 GIVING THIS MAHONEY LECTURE TO 111 00:03:45,590 --> 00:03:46,791 YOU, AND THANK YOU, EVERYBODY, 112 00:03:46,791 --> 00:03:50,629 FOR COMING, COMING HERE. 113 00:03:50,629 --> 00:03:52,063 AS YOU MENTIONED I'VE BEEN HERE 114 00:03:52,063 --> 00:03:53,798 AT NIH AND I HAVE MANY GOOD 115 00:03:53,798 --> 00:03:54,566 MEMORIES ASSOCIATED WITH THIS 116 00:03:54,566 --> 00:03:55,333 PLACE. 117 00:03:55,333 --> 00:03:57,702 I'VE BEEN WORKING IN THE 90s 118 00:03:57,702 --> 00:03:59,371 AS A POSTDOC. 119 00:03:59,371 --> 00:04:06,044 AND I WAS WORKING WITH HATFIELD 120 00:04:06,044 --> 00:04:09,114 IN BUILDING 37, HE'S JUST A 121 00:04:09,114 --> 00:04:10,649 WONDERFUL HUMAN BEING, I JUST 122 00:04:10,649 --> 00:04:13,285 YESTERDAY HAD DINNER WITH HIM, 123 00:04:13,285 --> 00:04:15,654 HE IS LONG RETIRED BUT I HAVE 124 00:04:15,654 --> 00:04:19,724 125 PAPERS TOGETHER WITH HIM. 125 00:04:19,724 --> 00:04:21,660 AS DR. HODES MENTIONED, THERE IS 126 00:04:21,660 --> 00:04:24,329 A STADMAN WAY, I ENCOURAGE YOU 127 00:04:24,329 --> 00:04:25,564 AFTER THE LECTURE TO LOOK AT 128 00:04:25,564 --> 00:04:26,398 THIS BECAUSE THERE'S REALLY A 129 00:04:26,398 --> 00:04:30,235 LOT OF HISTORY IN THIS AMAZING 130 00:04:30,235 --> 00:04:31,970 PLACE. 131 00:04:31,970 --> 00:04:35,740 BUT RECENTLY, I'D BEEN -- 132 00:04:35,740 --> 00:04:39,177 ACTUALLY NOT RECENTLY, FOR MAYBE 133 00:04:39,177 --> 00:04:40,445 EIGHT YEARS I'VE BEEN WORK ON 134 00:04:40,445 --> 00:04:42,147 AGING AND OF COURSE I'M VERY 135 00:04:42,147 --> 00:04:43,882 GRATEFUL FOR NIA FOR ALL THE 136 00:04:43,882 --> 00:04:45,417 SUPPORT WHICH ALLOWED US TO 137 00:04:45,417 --> 00:04:45,984 STUDY THIS. 138 00:04:45,984 --> 00:04:47,886 BUT THE POINT IS ONCE YOU START 139 00:04:47,886 --> 00:04:49,254 STUDYING AGING, IT'S HARD TO 140 00:04:49,254 --> 00:04:50,155 STUDY ANYTHING ELSE. 141 00:04:50,155 --> 00:04:54,960 IT'S JUST -- THE PROBLEM IS SO 142 00:04:54,960 --> 00:04:55,827 IMPORTANT THAT NOTHING REALLY 143 00:04:55,827 --> 00:04:56,928 COMPARES TO IT I THINK IN 144 00:04:56,928 --> 00:04:58,230 BIOLOGY AND MEDICINE, BECAUSE 145 00:04:58,230 --> 00:05:00,198 THE IDEA IS THAT MOST DISEASES 146 00:05:00,198 --> 00:05:05,337 THAT MEDICINE STUDIES ARE AGING 147 00:05:05,337 --> 00:05:06,438 DISEASES, AND IF YOU CAN TARGET 148 00:05:06,438 --> 00:05:11,476 THE AGING PROCESS ITSELF, YOU 149 00:05:11,476 --> 00:05:12,777 SEE ALL THIS AT ONCE, THIS IS 150 00:05:12,777 --> 00:05:14,646 WHY IT'S SO APPEALING BUT ALSO 151 00:05:14,646 --> 00:05:18,016 IT'S INCREDIBLY DIFFICULT TO DO. 152 00:05:18,016 --> 00:05:19,017 THE FIRST QUESTION WE NEED TO 153 00:05:19,017 --> 00:05:21,086 ASK IS ACTUALLY WHAT ARE WE 154 00:05:21,086 --> 00:05:24,322 STUDYING ACTUALLY WHEN WE SAY 155 00:05:24,322 --> 00:05:25,257 NATIONAL INSTITUTE ON AGING, BUT 156 00:05:25,257 --> 00:05:27,092 WHAT IS AGING? 157 00:05:27,092 --> 00:05:28,426 APPARENTLY, IT'S NOT EASY TO 158 00:05:28,426 --> 00:05:29,728 DEFINE. 159 00:05:29,728 --> 00:05:32,364 AND THERE IS DIFFERENCE OF 160 00:05:32,364 --> 00:05:33,565 OPINION ON THAT TOPIC. 161 00:05:33,565 --> 00:05:37,402 SOME PEOPLE THINK THAT AGING IS 162 00:05:37,402 --> 00:05:39,471 LIKE INCREASED MORTALITY RATE, 163 00:05:39,471 --> 00:05:43,608 INCREASED CHANCE OF DYING WITH 164 00:05:43,608 --> 00:05:44,175 AGE. 165 00:05:44,175 --> 00:05:45,710 SOME PEOPLE THINK IT'S DECREASED 166 00:05:45,710 --> 00:05:47,012 LOSS OF FUNCTION OR SOME PEOPLE 167 00:05:47,012 --> 00:05:49,414 THINK IT'S A PROCESS AFTER 168 00:05:49,414 --> 00:05:50,849 DEVELOPMENT, OTHER PEOPLE THINK 169 00:05:50,849 --> 00:05:54,019 IN TERMS OF THE BIOLOGICAL AGE 170 00:05:54,019 --> 00:05:55,320 OR MAYBE DAMAGE ACCUMULATION. 171 00:05:55,320 --> 00:05:58,189 THERE'S NO DOMINANT IDEA, SO IT 172 00:05:58,189 --> 00:06:00,258 TURNS OUT THAT WHEN WE SAY 173 00:06:00,258 --> 00:06:02,227 AGING, WE USE THE SAME WORD TO 174 00:06:02,227 --> 00:06:04,729 MEAN DIFFERENT THINGS. 175 00:06:04,729 --> 00:06:06,931 BUT TO ME, IT'S THE MOST 176 00:06:06,931 --> 00:06:08,466 CRITICAL QUESTION I FEEL BECAUSE 177 00:06:08,466 --> 00:06:10,869 ALL OTHER -- ALL EXPERIMENTS, 178 00:06:10,869 --> 00:06:12,737 EXPERIMENTAL DESIGN IS BASED ON 179 00:06:12,737 --> 00:06:13,738 THIS CONCEPTUAL UNDERSTANDING. 180 00:06:13,738 --> 00:06:15,240 SO WE NEED TO THINK ABOUT THIS 181 00:06:15,240 --> 00:06:16,908 PROCESS FIRST, AND THEN DESIGN 182 00:06:16,908 --> 00:06:17,842 EXPERIMENTS. 183 00:06:17,842 --> 00:06:22,981 AND IT DOESN'T HAPPEN OFTEN. 184 00:06:22,981 --> 00:06:24,949 ANOTHER WAY TO ILLUSTRATE THIS, 185 00:06:24,949 --> 00:06:27,752 YOU CAN STUDY AGING AT THE LEVEL 186 00:06:27,752 --> 00:06:29,788 OF DYING, MORTALITY, BUT 187 00:06:29,788 --> 00:06:30,989 MORTALITY IS CAUSED BY DISEASES, 188 00:06:30,989 --> 00:06:35,794 WE CAN STUDY MORBIDITY, DISEASE 189 00:06:35,794 --> 00:06:37,662 INCIDENCE, BUT THIS IS TYPICALLY 190 00:06:37,662 --> 00:06:40,265 CAUSED BY FUNCTIONAL DECLINE. 191 00:06:40,265 --> 00:06:48,273 FUNCTION NAT DECLFUNCTIONAL DECY 192 00:06:48,273 --> 00:06:48,907 DAMAGE. 193 00:06:48,907 --> 00:06:51,309 THERE'S NO CONSENSUS IN THE 194 00:06:51,309 --> 00:06:53,611 FIELD THAT AGING STARTS HERE. 195 00:06:53,611 --> 00:06:58,316 THESE LEITMAN 'FESS TA LATE MANF 196 00:06:58,316 --> 00:06:58,983 THIS PROCESS. 197 00:06:58,983 --> 00:07:01,052 I WAS TRAINED AS A BIOCHEMIST 198 00:07:01,052 --> 00:07:04,989 AND I OFTEN THINK ABOUT EMG ENZS 199 00:07:04,989 --> 00:07:05,657 THIS WAY. 200 00:07:05,657 --> 00:07:07,392 SO LET'S CONSIDER AN ENZYME. 201 00:07:07,392 --> 00:07:10,261 THERE MUST BE A GENE FOR THAT 202 00:07:10,261 --> 00:07:13,865 ENZYME THAT CATALYZES THE 203 00:07:13,865 --> 00:07:15,600 PROTEIN, CATALYZES SOME KIND OF 204 00:07:15,600 --> 00:07:16,568 REACTION BUT THIS IS NOT 205 00:07:16,568 --> 00:07:17,335 PERFECT. 206 00:07:17,335 --> 00:07:19,003 IT'S COMPOSED OF ONLY 20 TYPES 207 00:07:19,003 --> 00:07:20,972 OF AMINO ACIDS AND HAS A 208 00:07:20,972 --> 00:07:22,507 FLEXIBLE STRUCTURE, SO THERE IS 209 00:07:22,507 --> 00:07:24,242 NON-ZERO LIKELIHOOD IT SHALL 210 00:07:24,242 --> 00:07:25,443 PRODUCE SOMETHING ELSE. 211 00:07:25,443 --> 00:07:26,211 LET'S CALL IT DAMAGE. 212 00:07:26,211 --> 00:07:30,382 SO AS A RESULT, WE HAVE A GENE 213 00:07:30,382 --> 00:07:31,349 WHICH POSITIVE FUNCTION BUT AS A 214 00:07:31,349 --> 00:07:32,550 RESULT OF THAT FUNCTION, WE HAVE 215 00:07:32,550 --> 00:07:33,418 A NEGATIVE CONSEQUENCE IN THE 216 00:07:33,418 --> 00:07:34,085 FORM OF DAMAGE. 217 00:07:34,085 --> 00:07:42,627 AND IT APPLIES TO AN ENZYME. 218 00:07:42,627 --> 00:07:43,595 NEGATIVE IS CUMULATIVE. 219 00:07:43,595 --> 00:07:45,797 SO IF YOU USE THAT ENZYME EARLY 220 00:07:45,797 --> 00:07:50,502 IN LIFE, UNAVOIDABLY YOU'LL HAVE 221 00:07:50,502 --> 00:07:52,237 LATE DELETERIOUS CONSEQUENCES. 222 00:07:52,237 --> 00:07:54,239 IF WE COULD EXTEND THIS CONCEPT 223 00:07:54,239 --> 00:07:57,842 TO OTHER TYPES OF BIOLOGICAL 224 00:07:57,842 --> 00:07:59,577 PROCESSES AND AS A RESULT DAMAGE 225 00:07:59,577 --> 00:08:01,780 COULD WOMAN IN FORM OF ALL KINDS 226 00:08:01,780 --> 00:08:07,018 OF ERRORS, IMBALANCE IN PROTEIN 227 00:08:07,018 --> 00:08:08,219 COMPLEX, CELL COMPOSITION OF 228 00:08:08,219 --> 00:08:09,654 ORGANS AND SO ON, ALL OTHER 229 00:08:09,654 --> 00:08:10,855 KNOWN AND UNKNOWN FORMS OF 230 00:08:10,855 --> 00:08:11,389 DAMAGE. 231 00:08:11,389 --> 00:08:16,194 BUT THE WORD DAMAGE IS SOMEWHAT 232 00:08:16,194 --> 00:08:17,562 LIMITING, BECAUSE PEOPLE 233 00:08:17,562 --> 00:08:18,830 TYPICALLY THINK OF DAMAGE AS 234 00:08:18,830 --> 00:08:23,101 LIKE MOLECULAR, SOME KIND OF 235 00:08:23,101 --> 00:08:25,170 DAMAGING CHANGES. 236 00:08:25,170 --> 00:08:29,340 BUT WE OFTEN USE THE WORD 237 00:08:29,340 --> 00:08:31,943 DELETERIOME, THIS ENCOMPASSES 238 00:08:31,943 --> 00:08:32,811 ALL NEGATIVE CHANGES AS A RESULT 239 00:08:32,811 --> 00:08:33,578 OF LIFE. 240 00:08:33,578 --> 00:08:36,014 YOU CAN THINK OF IN TERMS OF 241 00:08:36,014 --> 00:08:37,215 CHEMISTRY AS A CUMULATIVE DAMAGE 242 00:08:37,215 --> 00:08:38,983 AT ALL LEVELS OF BIOLOGICAL 243 00:08:38,983 --> 00:08:40,151 ORGANIZATION, OR YOU CAN THINK 244 00:08:40,151 --> 00:08:43,755 IN TERMS OF PHYSICS, LIKE 245 00:08:43,755 --> 00:08:44,656 ENTROPY OR DISORDER. 246 00:08:44,656 --> 00:08:46,491 SO IN THAT SENSE, TO ME, AGING 247 00:08:46,491 --> 00:08:48,359 HAS A PHYSICAL NATURE. 248 00:08:48,359 --> 00:08:54,466 IT COMES ULTIMATELY FROM 249 00:08:54,466 --> 00:08:56,501 PHYSICS. 250 00:08:56,501 --> 00:08:58,102 SO THEN A LIFE EVOLVED TO 251 00:08:58,102 --> 00:09:00,939 COUNTERACT THAT INCREASE IN 252 00:09:00,939 --> 00:09:03,541 ENTROPY AND THERE ARE VARIOUS 253 00:09:03,541 --> 00:09:04,442 STRATEGIES TO DO IT. 254 00:09:04,442 --> 00:09:06,511 ONE SIMPLY IS TO DILUTE THE 255 00:09:06,511 --> 00:09:07,178 DAMAGE. 256 00:09:07,178 --> 00:09:08,813 BECAUSE THERE ARE SO MANY 257 00:09:08,813 --> 00:09:09,781 VARIETY OF DAMAGE FORMS, THE 258 00:09:09,781 --> 00:09:10,982 MEANS OF PROTECTION ARE 259 00:09:10,982 --> 00:09:12,317 OBVIOUSLY LIMITING, BUT CELLS 260 00:09:12,317 --> 00:09:14,486 DON'T NEED TO KNOW THAT WHAT ARE 261 00:09:14,486 --> 00:09:15,720 THE SPECIFIC DAMAGE FORMS IF 262 00:09:15,720 --> 00:09:16,788 THEY CAN DILUTE IT? 263 00:09:16,788 --> 00:09:19,290 SO FOR EXAMPLE, IN HERE, THERE 264 00:09:19,290 --> 00:09:24,128 IS A CELL AND TWO BECOMES FOUR, 265 00:09:24,128 --> 00:09:27,065 IT DIVIDES TWO AGAIN AND SO ON. 266 00:09:27,065 --> 00:09:29,367 THAT'S ONE STRATEGY, TO DILUTE 267 00:09:29,367 --> 00:09:29,968 ENTROPY. 268 00:09:29,968 --> 00:09:31,936 ANOTHER STRATEGY IS GERMLINE, 269 00:09:31,936 --> 00:09:32,437 FOR EXAMPLE. 270 00:09:32,437 --> 00:09:34,506 SO WHEN THERE IS A SUCCESSION OF 271 00:09:34,506 --> 00:09:37,375 ORGANISMS THROUGH GENERATIONS, 272 00:09:37,375 --> 00:09:39,310 THAT'S ALSO A WAY TO DEAL WITH 273 00:09:39,310 --> 00:09:40,645 THIS INCREASED ENTROPY. 274 00:09:40,645 --> 00:09:41,946 AS A RESULT THE NATURE OF AGING 275 00:09:41,946 --> 00:09:44,682 IS PHYSICAL, BUT COUNTERACTED 276 00:09:44,682 --> 00:09:45,783 BIOLOGICALLY. 277 00:09:45,783 --> 00:09:47,752 THROUGH LIFE. 278 00:09:47,752 --> 00:09:49,921 AND SO WE HAVE THIS KIND OF 279 00:09:49,921 --> 00:09:53,825 CONCEPT IN ALL OF OUR RESEARCH 280 00:09:53,825 --> 00:09:55,293 AND THE ACTUAL RESEARCH IS 281 00:09:55,293 --> 00:09:55,827 ORGANIZED LIKE THIS. 282 00:09:55,827 --> 00:10:00,865 SO WE STUDY LONGEVITY, FOR 283 00:10:00,865 --> 00:10:02,200 EXAMPLE, CELL TYPES, ACROSS 284 00:10:02,200 --> 00:10:05,036 DIFFERENT MAMMALS, DIFFERENT 285 00:10:05,036 --> 00:10:06,771 SPECIES HAVE DIFFERENT 286 00:10:06,771 --> 00:10:08,740 LIFESPANS, IN FACT OVER 100 FOLD 287 00:10:08,740 --> 00:10:10,208 DIFFERENCE IN LIFESPAN ACROSS 288 00:10:10,208 --> 00:10:10,508 MAMMALS. 289 00:10:10,508 --> 00:10:12,577 THIS IS US IN SO CALLED 290 00:10:12,577 --> 00:10:13,678 SIGNATURES OF LONGEVITY, WHICH 291 00:10:13,678 --> 00:10:19,384 ARE OMICS PATTERNS, TYPICALLY 292 00:10:19,384 --> 00:10:20,451 OMICS, INDICATIVE OF THE SYSTEM 293 00:10:20,451 --> 00:10:21,653 TO LIVE LONG. 294 00:10:21,653 --> 00:10:27,325 THEY MAY NOT CHANGE WITH AGE B. 295 00:10:27,325 --> 00:10:29,527 WE ALSO STUDY AGING, CHANGES 296 00:10:29,527 --> 00:10:31,162 DURING AGING, AND HERE WE 297 00:10:31,162 --> 00:10:32,363 QUANTIFIED THE AGING PROCESS 298 00:10:32,363 --> 00:10:34,899 THROUGH BIOMARKERS OF AGING. 299 00:10:34,899 --> 00:10:39,270 THIS MAY BE EPIGENETIC CLOCKS, 300 00:10:39,270 --> 00:10:41,239 TRANSCRIPTOMIC CLOCKS, ORGANIZE 301 00:10:41,239 --> 00:10:42,440 BEGAN SPECIFIC CLOCKS AND SO ON. 302 00:10:42,440 --> 00:10:44,609 THESE ARE ACTIONABLE BIOMARKERS 303 00:10:44,609 --> 00:10:45,810 OF AGING. 304 00:10:45,810 --> 00:10:47,579 SO WE ACTUALLY NEED BOTH TO 305 00:10:47,579 --> 00:10:48,546 STUDY THE AGING PROCESS. 306 00:10:48,546 --> 00:10:50,415 AND THE THIRD COMPONENT IS 307 00:10:50,415 --> 00:10:50,848 REJUVENATION. 308 00:10:50,848 --> 00:10:52,717 THIS IS SOMETHING WE NEW IN THE 309 00:10:52,717 --> 00:10:55,353 FIELD WHERE WE FIND THAT CELLS 310 00:10:55,353 --> 00:10:57,755 OR SOMETIMES THE ENTIRE ORGANISM 311 00:10:57,755 --> 00:10:59,824 CAN GO TO THE LOWER BIOLOGICAL 312 00:10:59,824 --> 00:11:01,693 AGE, THE STATE OF LOWER 313 00:11:01,693 --> 00:11:02,226 BIOLOGICAL AGE. 314 00:11:02,226 --> 00:11:04,629 WE CALL IT REJUVENATION. 315 00:11:04,629 --> 00:11:05,630 TRANSITION FROM AN OLDER STATE 316 00:11:05,630 --> 00:11:06,831 TO A YOUNGER STATE. 317 00:11:06,831 --> 00:11:09,233 I WOULD SAY THAT THE AGING 318 00:11:09,233 --> 00:11:10,368 PROCESS ITSELF IS IRREVERSIBLE. 319 00:11:10,368 --> 00:11:13,171 THERE IS NO WAY WITH ALL OF 320 00:11:13,171 --> 00:11:14,138 THESE CHANGES THAT YOU COULD GO 321 00:11:14,138 --> 00:11:15,239 THAT SAME ROAD BACK. 322 00:11:15,239 --> 00:11:17,208 SO AGING IS IRREVERSIBLE, BUT 323 00:11:17,208 --> 00:11:18,843 YOU COULD STILL TARGET AN 324 00:11:18,843 --> 00:11:20,278 ORGANISM OR A CELL OR TISSUE 325 00:11:20,278 --> 00:11:23,281 WHERE IT COULD GO TO A SLIGHTLY 326 00:11:23,281 --> 00:11:29,354 LOWER BIOLOGICAL AGE. 327 00:11:29,354 --> 00:11:33,524 SO THIS STRATEGY ALLOWS US TO 328 00:11:33,524 --> 00:11:36,894 TARGET IN MOUSE MODELS PRIMARILY 329 00:11:36,894 --> 00:11:38,997 AND DIETARY PHARMACOLOGICAL 330 00:11:38,997 --> 00:11:39,964 GENETIC INTERVENTIONS. 331 00:11:39,964 --> 00:11:41,165 AND I'LL GIVE A FEW EXAMPLES OF 332 00:11:41,165 --> 00:11:45,436 HOW WE DO IT. 333 00:11:45,436 --> 00:11:46,971 SO WE START WITH THE GENOMES, WE 334 00:11:46,971 --> 00:11:50,041 ACTUALLY SEQUENCED MANY SPECIES. 335 00:11:50,041 --> 00:11:53,111 THE FIRST ONE WAS THIS ONE, THIS 336 00:11:53,111 --> 00:11:54,512 PAPER PUBLISHED ALREADY A LONG 337 00:11:54,512 --> 00:11:57,682 TIME AGO, BUT I THINK IT WAS THE 338 00:11:57,682 --> 00:11:58,750 FIRST PAPER WHERE GENOME WAS 339 00:11:58,750 --> 00:12:00,952 SEQUENCED WITH THE GOAL OF 340 00:12:00,952 --> 00:12:02,286 UNDERSTANDING LONGEVITY. 341 00:12:02,286 --> 00:12:07,091 ANOTHER ONE IS CALLED -- THIS IS 342 00:12:07,091 --> 00:12:08,726 ALSO A VERY AMAZING ANIMAL, ONE 343 00:12:08,726 --> 00:12:10,161 OF THE SMALLEST MAMMALS BUT 344 00:12:10,161 --> 00:12:11,129 LIVES MORE THAN 40 YEARS. 345 00:12:11,129 --> 00:12:14,432 AND THIS IS THE LONGEST LIVED 346 00:12:14,432 --> 00:12:17,068 MAMMAL CALLED BULLHEAD WHALE, 347 00:12:17,068 --> 00:12:18,036 LIVES MORE THAN 200 YEARS. 348 00:12:18,036 --> 00:12:20,638 WHAT WE FIND THROUGH THIS STUDY 349 00:12:20,638 --> 00:12:22,407 IS THAT VARIOUS SPECIES DEVELOP 350 00:12:22,407 --> 00:12:25,243 THEIR OWN WAY TO LIVE LONG. 351 00:12:25,243 --> 00:12:26,444 SO THE ADAPTATIONS THAT THEY 352 00:12:26,444 --> 00:12:27,545 DEVELOPED ARE NOT NECESSARILY 353 00:12:27,545 --> 00:12:29,614 THE SAME ACROSS THIS LONG LIVED 354 00:12:29,614 --> 00:12:30,181 SPECIES. 355 00:12:30,181 --> 00:12:31,916 SO FOR THESE REASONS, WE ALSO 356 00:12:31,916 --> 00:12:35,119 TRIED TO IDENTIFY COMMON CHANGES 357 00:12:35,119 --> 00:12:36,854 ACROSS VARIOUS GROUPS OF 358 00:12:36,854 --> 00:12:44,595 ANIMALS, AND OUR MAIN FOCUS IS 359 00:12:44,595 --> 00:12:46,230 MAMMALS, SO IN THIS STUDY 360 00:12:46,230 --> 00:12:47,331 PUBLISHED ALMOST TWO YEARS AGO 361 00:12:47,331 --> 00:12:49,200 NOW, WE ACTUALLY ANALYZED 40 362 00:12:49,200 --> 00:12:50,068 SPECIES OF MAMMALS. 363 00:12:50,068 --> 00:12:55,440 THEY ARE SHOAP HERE. 364 00:12:55,440 --> 00:12:56,974 IN THREE ORGANS LOOKING AT THE 365 00:12:56,974 --> 00:12:58,176 GENE EXPRESSION CHANGES. 366 00:12:58,176 --> 00:13:00,745 WE FIND SOME SHOW INCREASED OR 367 00:13:00,745 --> 00:13:02,213 DECREASED EXPRESSION WITH THE 368 00:13:02,213 --> 00:13:05,516 CHANGE IN LONGEVITY ACROSS 369 00:13:05,516 --> 00:13:06,250 SPECIES. 370 00:13:06,250 --> 00:13:09,120 WHAT'S INTERESTING, IF ONE GENE 371 00:13:09,120 --> 00:13:11,189 GOES UP, TYPICALLY IT ALSO GOES 372 00:13:11,189 --> 00:13:13,057 UP IN OTHER ORGANS. 373 00:13:13,057 --> 00:13:14,358 IF IT GOES DOWN TYPICALLY IT 374 00:13:14,358 --> 00:13:17,095 GOES DOWN TO OTHER ORGANS WHICH 375 00:13:17,095 --> 00:13:18,396 INITIALLY WAS COUNTERINTUITIVE 376 00:13:18,396 --> 00:13:18,830 ACTUALLY. 377 00:13:18,830 --> 00:13:20,698 WHY WOULD IT GO SIMILARLY IN 378 00:13:20,698 --> 00:13:24,202 DIFFERENT ORGANS? 379 00:13:24,202 --> 00:13:25,636 BUT THE POINT IS THAT IN EACH 380 00:13:25,636 --> 00:13:28,372 ORGAN, WE HAD ABOUT 500 GENES, 381 00:13:28,372 --> 00:13:30,007 MAYBE 500 TO 1,000 GENES THAT 382 00:13:30,007 --> 00:13:32,076 REPRESENT THESE LONGEVITY 383 00:13:32,076 --> 00:13:33,611 SIGNATURES, WHICH AGAIN IS A 384 00:13:33,611 --> 00:13:35,146 VERY USEFUL MEASURE FOR US, 385 00:13:35,146 --> 00:13:36,347 MEASURE OF POTENTIAL TO LIVE 386 00:13:36,347 --> 00:13:39,183 LONG. 387 00:13:39,183 --> 00:13:41,719 YOU ALSO STUDY LONGEVITY ACROSS 388 00:13:41,719 --> 00:13:42,487 INTERVENTIONS BECAUSE NOW WE 389 00:13:42,487 --> 00:13:44,856 KNOW MANY WAYS TO EXTEND 390 00:13:44,856 --> 00:13:46,591 LIFESPAN IN MODEL ORGANISMS. 391 00:13:46,591 --> 00:13:47,725 I SHOW THIS SLIDE FROM THIS 392 00:13:47,725 --> 00:13:49,260 PAPER PUBLISHED FIVE YEARS AGO, 393 00:13:49,260 --> 00:13:52,296 AND HERE WE STUDY INTERVENTIONS 394 00:13:52,296 --> 00:13:55,466 IN MICE THAT EXTEND LIFESPAN. 395 00:13:55,466 --> 00:13:59,537 AND THE DATA IN THE FORM OF -- 396 00:13:59,537 --> 00:14:01,372 MATRIX AND GENE EXPRESSION DATA. 397 00:14:01,372 --> 00:14:04,442 SO KIND OF RED MEANS THE GENE 398 00:14:04,442 --> 00:14:05,777 EXPRESSION CHANGES ARE SIMILARLY 399 00:14:05,777 --> 00:14:07,612 INDUCED BY DIFFERENT LONGEVITY 400 00:14:07,612 --> 00:14:08,713 INTERVENTIONS. 401 00:14:08,713 --> 00:14:10,782 AND BLUE IS KIND OF IN THE 402 00:14:10,782 --> 00:14:11,115 NEGATIVE WAY. 403 00:14:11,115 --> 00:14:15,052 SO YOU CAN SEE ONE CLUSTER, FOR 404 00:14:15,052 --> 00:14:17,021 EXAMPLE, WE CALL IT CALORIE 405 00:14:17,021 --> 00:14:18,356 RESTRICTION CLUSTER, SIMILAR TO 406 00:14:18,356 --> 00:14:20,858 SOMETHING LIKE GROWTH HORMONE 407 00:14:20,858 --> 00:14:25,329 RECEPTOR TO FG21 OR SOME GENETIC 408 00:14:25,329 --> 00:14:29,734 MODELS AND SO ON. 409 00:14:29,734 --> 00:14:32,570 BUT ANOTHER CLUSTER, ONE 410 00:14:32,570 --> 00:14:35,072 COMPOUND CALLED RAPAMYCIN IS 411 00:14:35,072 --> 00:14:36,707 WELL-KNOWN IT EXPANDS LIFESPAN 412 00:14:36,707 --> 00:14:38,810 BUT INTERESTINGLY, IT INDUCES 413 00:14:38,810 --> 00:14:39,744 CHANGES WHICH ARE QUITE 414 00:14:39,744 --> 00:14:40,545 DIFFERENT FROM THE CHANGES 415 00:14:40,545 --> 00:14:42,180 INDUCED BY CALORIE RESTRICTION 416 00:14:42,180 --> 00:14:42,914 CLUSTER. 417 00:14:42,914 --> 00:14:43,948 SO APPARENTLY THERE ARE MANY 418 00:14:43,948 --> 00:14:45,583 WAYS TO MODIFY THE ORGANISM SO 419 00:14:45,583 --> 00:14:50,822 THAT IT LIVES LONGER. 420 00:14:50,822 --> 00:14:52,356 WE DON'T KNOW YET WHICH OF THESE 421 00:14:52,356 --> 00:14:54,992 STRATEGIES MAY BE COMBINED AND 422 00:14:54,992 --> 00:14:56,627 THIS IS CURRENTLY BEING STUDIED 423 00:14:56,627 --> 00:14:57,261 ACTIVELY IN THE FIELD. 424 00:14:57,261 --> 00:14:59,130 NOW WE HAVE THIS LONGEVITY 425 00:14:59,130 --> 00:15:02,433 ACROSS SPECIES, LONGEVITY ACROSS 426 00:15:02,433 --> 00:15:03,401 INTERVENTIONS, AND WE ALSO CAN 427 00:15:03,401 --> 00:15:07,104 ADD ANOTHER DIMENSION WHICH IS 428 00:15:07,104 --> 00:15:08,339 AGING CHANGES, AGING ITSELF. 429 00:15:08,339 --> 00:15:10,508 NOW WE COULD ASK AT THE OMICS 430 00:15:10,508 --> 00:15:12,476 LEVEL, HOW ARE THESE THREE 431 00:15:12,476 --> 00:15:14,979 PATTERNS RELATED TO ONE ANOTHER? 432 00:15:14,979 --> 00:15:18,950 AND THIS DATA SHOW HERE FROM A 433 00:15:18,950 --> 00:15:22,420 PAPER THAT I HAVE -- REALLY 434 00:15:22,420 --> 00:15:24,088 AMAZING RESEARCHER IN THE LAB 435 00:15:24,088 --> 00:15:27,458 WHO DEVELOPED THIS STUDY. 436 00:15:27,458 --> 00:15:28,693 AND I WILL WALK YOU THROUGH THIS 437 00:15:28,693 --> 00:15:29,760 SLIDE. 438 00:15:29,760 --> 00:15:32,163 IN BLUE ARE LONGEVITY CROSS 439 00:15:32,163 --> 00:15:33,164 SPECIES, FOR EXAMPLE, BRAIN 440 00:15:33,164 --> 00:15:33,931 ACROSS MAMMALS. 441 00:15:33,931 --> 00:15:35,466 OR KIDNEY ACROSS MAMMALS AND SO 442 00:15:35,466 --> 00:15:36,100 ON. 443 00:15:36,100 --> 00:15:38,970 AND THE CHANGES CLUSTER WITH ONE 444 00:15:38,970 --> 00:15:41,806 ANOTHER, SO AGAIN, CHANGES IN 445 00:15:41,806 --> 00:15:43,674 DIFFERENT ORGANS ARE SIMILAR 446 00:15:43,674 --> 00:15:45,309 THAT LEAD TO LONGEVITY OF THE 447 00:15:45,309 --> 00:15:46,277 SPECIES. 448 00:15:46,277 --> 00:15:48,813 AND THIS CLUSTER IS AGING, LIKE 449 00:15:48,813 --> 00:15:50,014 AGING ACROSS MUSCLE OF MAMMALS, 450 00:15:50,014 --> 00:15:52,416 BRAIN OF MAMMALS, DIFFERENT 451 00:15:52,416 --> 00:15:54,685 TISSUES OF HUMAN, GLOBAL MEANS 452 00:15:54,685 --> 00:15:55,887 DIFFERENT TISSUES AND SPECIES 453 00:15:55,887 --> 00:15:56,520 AND SO ON. 454 00:15:56,520 --> 00:15:57,622 THEY ALSO CLUSTER WITH ONE 455 00:15:57,622 --> 00:15:57,989 ANOTHER. 456 00:15:57,989 --> 00:15:59,724 AND THIS IS LONGEVITY ACROSS 457 00:15:59,724 --> 00:16:00,291 INTERVENTIONS. 458 00:16:00,291 --> 00:16:02,894 AGAIN, GROWTH HORMONE RECEPTOR, 459 00:16:02,894 --> 00:16:05,496 CALORIE RESTRICTION, RAPAMYCIN, 460 00:16:05,496 --> 00:16:06,197 SO ON. 461 00:16:06,197 --> 00:16:07,698 THEY ALSO MOSTLY CLUSTER WITH 462 00:16:07,698 --> 00:16:09,233 ONE ANOTHER, BUT THEY FORM THREE 463 00:16:09,233 --> 00:16:11,602 DIFFERENT CLUSTERS, AND IF YOU 464 00:16:11,602 --> 00:16:12,737 COMPARE THE CLUSTERS WHAT YOU 465 00:16:12,737 --> 00:16:14,705 FIND IS QUITE STRIKING TO ME. 466 00:16:14,705 --> 00:16:17,475 FIRST THERE IS A SLIGHT POSITIVE 467 00:16:17,475 --> 00:16:18,442 CORRELATION BETWEEN LONGEVITY 468 00:16:18,442 --> 00:16:20,845 ACROSS SPECIES AND AGING. 469 00:16:20,845 --> 00:16:23,481 WHICH ON THE SURFACE MEANS THAT 470 00:16:23,481 --> 00:16:24,982 LONGER LIVED SPECIES ARE OLDER. 471 00:16:24,982 --> 00:16:26,417 THIS MAKES NO SENSE, WHY WOULD 472 00:16:26,417 --> 00:16:28,486 LONGER LIVED SPECIES LIKE HUMANS 473 00:16:28,486 --> 00:16:29,921 BE OLDER, FOR EXAMPLE, THAN 474 00:16:29,921 --> 00:16:32,223 MICE? 475 00:16:32,223 --> 00:16:33,858 BUT OUR INTERPRETATION IS 476 00:16:33,858 --> 00:16:34,859 ACTUALLY QUITE DIFFERENT. 477 00:16:34,859 --> 00:16:38,229 SO WHEN ORGANISMS AGE, THEY 478 00:16:38,229 --> 00:16:39,664 ACCUMULATE DAMAGE, BUT ALSO THIS 479 00:16:39,664 --> 00:16:41,632 DAMAGE INDUCES ACTIVATION OF 480 00:16:41,632 --> 00:16:43,000 PROTECTIVE SYSTEMS. 481 00:16:43,000 --> 00:16:45,670 AND APPARENTLY, THESE PROTECTIVE 482 00:16:45,670 --> 00:16:48,639 SYSTEMS ARE ALSO USED BY LONGER 483 00:16:48,639 --> 00:16:49,273 LIVED SPECIES. 484 00:16:49,273 --> 00:16:51,242 SO THEY ARE NOT OLDER, THEY'RE 485 00:16:51,242 --> 00:16:56,814 JUST BETTER PROTECTED. 486 00:16:56,814 --> 00:17:00,117 THERE IS NO CORRELATION BETWEEN 487 00:17:00,117 --> 00:17:01,319 LONGEVITY ACROSS SPECIES AND 488 00:17:01,319 --> 00:17:01,986 ACROSS INTERVENTIONS WE FIND IN 489 00:17:01,986 --> 00:17:02,620 THE LAB. 490 00:17:02,620 --> 00:17:07,758 SO WHATEVER WE DO IN THE LAB, 491 00:17:07,758 --> 00:17:09,527 DIETARY, PHARMACOLOGICAL, 492 00:17:09,527 --> 00:17:10,728 GENETIC INTERVENTIONS, THEY ARE 493 00:17:10,728 --> 00:17:12,897 QUITE DIFFERENT FROM HOW NATURE 494 00:17:12,897 --> 00:17:13,531 EXTENDS LIFESPAN. 495 00:17:13,531 --> 00:17:16,200 TO ME THIS REPRESENTS AN 496 00:17:16,200 --> 00:17:17,168 UNTAPPED POTENTIAL TO STUDY 497 00:17:17,168 --> 00:17:19,236 LONGEVITY. 498 00:17:19,236 --> 00:17:20,004 THE INFORMATION THAT WE COULD 499 00:17:20,004 --> 00:17:22,306 GAIN FROM ANALYZING LONGEVITY 500 00:17:22,306 --> 00:17:25,710 ACROSS SPECIES COULD BE USED 501 00:17:25,710 --> 00:17:27,611 MAYBE IN THE FUTURE FOR RADICAL 502 00:17:27,611 --> 00:17:28,446 CHANGES IN LIFESPAN, NOT 503 00:17:28,446 --> 00:17:29,747 SOMETHING THAT WE FIND IN THE 504 00:17:29,747 --> 00:17:34,218 LAB WHICH IS QUITE MARGINAL. 505 00:17:34,218 --> 00:17:35,219 TYPICAL INTERVENTION OF MICE ON 506 00:17:35,219 --> 00:17:39,590 ORDER OF 10 TO 20%. 507 00:17:39,590 --> 00:17:40,791 WE NOW CONTINUE ACTIVELY WORKING 508 00:17:40,791 --> 00:17:42,226 IN THIS DIRECTION TRYING TO 509 00:17:42,226 --> 00:17:43,294 UNDERSTAND THESE PRINCIPLES OF 510 00:17:43,294 --> 00:17:46,063 LIFESPAN CONTROL. 511 00:17:46,063 --> 00:17:48,466 NOW I WILL GO TO THE NECK TOPIC, 512 00:17:48,466 --> 00:17:50,434 BIOMARKERS OF AGING, AND TO ME, 513 00:17:50,434 --> 00:17:52,903 THIS IS A TRUE REVOLUTION IN THE 514 00:17:52,903 --> 00:17:53,270 FIELD. 515 00:17:53,270 --> 00:17:55,339 THIS IS SOMETHING THAT HAPPENED 516 00:17:55,339 --> 00:17:57,408 ABOUT 10 YEARS AGO AND THE FIRST 517 00:17:57,408 --> 00:18:04,749 PERSON IS STEVE HORWATH, HE 518 00:18:04,749 --> 00:18:05,850 CALLS IT AGING CLOCKS. 519 00:18:05,850 --> 00:18:07,051 WE FOLLOWED ON THAT AND 520 00:18:07,051 --> 00:18:07,918 DEVELOPED A MOUSE CLOCK. 521 00:18:07,918 --> 00:18:16,293 THIS WAS ALREADY YEARS AGO. 522 00:18:16,293 --> 00:18:20,564 WE SEQUENCE THE GENOME ABOUT 200 523 00:18:20,564 --> 00:18:21,799 MICE OF DIFFERENT AGES AND OUT 524 00:18:21,799 --> 00:18:23,968 OF MILLIONS OF CPG SITES, 525 00:18:23,968 --> 00:18:25,636 IDENTIFIED A FEW LIKE IN THIS 526 00:18:25,636 --> 00:18:28,272 PARTICULAR CASE, LIKE 90 CPG 527 00:18:28,272 --> 00:18:29,673 SITES THAT CONSISTENTLY CHANGE 528 00:18:29,673 --> 00:18:32,543 WITH AGE, INCREASE OR DECREASE 529 00:18:32,543 --> 00:18:34,478 METHYLATION, AND TOGETHER, THEY 530 00:18:34,478 --> 00:18:36,680 REPRESENT A MATHEMATICAL FORMULA 531 00:18:36,680 --> 00:18:38,082 WITH EACH SITE HAS A PARTICULAR 532 00:18:38,082 --> 00:18:39,984 WEIGHT IN THE MODEL WHERE YOU 533 00:18:39,984 --> 00:18:41,352 COULD ACCURATELY PREDICT THE AGE 534 00:18:41,352 --> 00:18:41,819 OF THE MICE. 535 00:18:41,819 --> 00:18:43,354 THIS IS THE ACTUAL AGE OF MICE 536 00:18:43,354 --> 00:18:46,323 IN MONTHS, AND THIS IS THE THE 537 00:18:46,323 --> 00:18:46,757 PREDICTIONED AGE. 538 00:18:46,757 --> 00:18:48,826 YOU CAN SEE THERE IS VERY GOOD 539 00:18:48,826 --> 00:18:50,361 CORRESPONDENCE SO WE CAN 540 00:18:50,361 --> 00:18:51,128 ACCURATELY PREDICT THE AGE OF 541 00:18:51,128 --> 00:18:51,896 THE MICE. 542 00:18:51,896 --> 00:18:52,763 THESE FOUR GROUPS OF MICE ARE 543 00:18:52,763 --> 00:18:55,166 MICE THAT HAVE BEEN SUBJECTED TO 544 00:18:55,166 --> 00:18:58,669 CALORIE RESTRICTION. 545 00:18:58,669 --> 00:19:00,438 AT ANY AGE THESE MICE ARE 546 00:19:00,438 --> 00:19:01,405 LITERALLY YOUNGER BASED ON THIS 547 00:19:01,405 --> 00:19:01,705 CLOCK. 548 00:19:01,705 --> 00:19:04,475 SO THIS CLOCK IS VERY USEFUL TO 549 00:19:04,475 --> 00:19:05,276 IDENTIFY INTERVENTIONS LIKE 550 00:19:05,276 --> 00:19:05,543 THIS. 551 00:19:05,543 --> 00:19:07,445 SO FOR EXAMPLE, IF YOU WOULD 552 00:19:07,445 --> 00:19:08,746 KNOW NOTHING ABOUT CALORIE 553 00:19:08,746 --> 00:19:10,481 RESTRICTION, WHEN THE MICE ARE 554 00:19:10,481 --> 00:19:11,682 10 MONTHS OLD, WE COULD MEASURE 555 00:19:11,682 --> 00:19:13,451 AND SAY THIS ARE YOUNGER, MAYBE 556 00:19:13,451 --> 00:19:15,186 THERE'S POTENTIAL TO EXTEND 557 00:19:15,186 --> 00:19:17,288 LIFESPAN AND WE DON'T NEED TO 558 00:19:17,288 --> 00:19:18,155 WAIT UNTIL MICE DIE. 559 00:19:18,155 --> 00:19:20,224 THIS IS THAT TRACTION OF THE 560 00:19:20,224 --> 00:19:21,692 BIOMARKERS IN HUMAN CLINICAL 561 00:19:21,692 --> 00:19:22,059 TRIALS. 562 00:19:22,059 --> 00:19:24,161 BECAUSE WE CAN LEARN OF THE 563 00:19:24,161 --> 00:19:25,896 POTENTIAL OF CERTAIN PREVENTIONS 564 00:19:25,896 --> 00:19:27,765 WITHOUT WAITING FOR LATE-LIFE 565 00:19:27,765 --> 00:19:29,400 OUTCOMES. 566 00:19:29,400 --> 00:19:31,068 AND ON THIS PART OF THE SLIDE, 567 00:19:31,068 --> 00:19:33,671 IT SHOWS THAT EVEN IF WE 568 00:19:33,671 --> 00:19:37,274 DEVELOPED A CLOCK BASED ON THE 569 00:19:37,274 --> 00:19:41,112 BLOOD OF MICE AND APPLY THIS TO 570 00:19:41,112 --> 00:19:42,746 CELLULAR PROGRAMMING WHERE WE 571 00:19:42,746 --> 00:19:45,049 CAN INDUCE PLURIPOTENT STEM 572 00:19:45,049 --> 00:19:46,250 CELLS, THE AGE ON THIS CLOCK 573 00:19:46,250 --> 00:19:47,218 GOES TO ZERO. 574 00:19:47,218 --> 00:19:49,753 SO OF COURSE EMBRYONIC CELLS 575 00:19:49,753 --> 00:19:51,622 SHOULD BE YOUNG CELLS, BUT IT'S 576 00:19:51,622 --> 00:19:53,257 REALLY NICE THAT EVEN SUCH A 577 00:19:53,257 --> 00:19:54,992 CLOCK, LIKE A BLOOD CLOCK, SHOWS 578 00:19:54,992 --> 00:19:56,293 THE AGE IS ZERO. 579 00:19:56,293 --> 00:19:57,962 SO AGAIN, IT EXTENDS THE 580 00:19:57,962 --> 00:19:58,929 APPLICATION OF THE CLOCKS. 581 00:19:58,929 --> 00:20:00,798 BUT THEN THE QUESTION IS, WHAT 582 00:20:00,798 --> 00:20:02,433 ARE THE BEST BIOMARKERS? 583 00:20:02,433 --> 00:20:04,902 BECAUSE THE FIRST BIOMARKER THAT 584 00:20:04,902 --> 00:20:07,238 WAS DEVELOPED WAS TRAINED ON 585 00:20:07,238 --> 00:20:08,038 CHRONOLOGICAL AGE BUT IN FACT 586 00:20:08,038 --> 00:20:09,106 YOU CAN MEASURE AGING IN 587 00:20:09,106 --> 00:20:09,773 DIFFERENT WAYS. 588 00:20:09,773 --> 00:20:11,175 YOU COULD, OF COURSE, MEASURE 589 00:20:11,175 --> 00:20:12,610 BASED ON CHRONOLOGICAL AGE, 590 00:20:12,610 --> 00:20:14,912 TRAIN THE MODEL CHRONOLOGICAL 591 00:20:14,912 --> 00:20:16,780 AGE, YOU CAN TRAIN A CLOCK BASED 592 00:20:16,780 --> 00:20:17,848 ON FUTURE MORTALITY AND THESE 593 00:20:17,848 --> 00:20:23,120 ARE SO CALLED SECOND -- YOU CAN 594 00:20:23,120 --> 00:20:24,421 TRAIN A CLOCK BASED ON THE RATE 595 00:20:24,421 --> 00:20:30,761 OF CHANGE, THAT'S ANOTHER CLOCK, 596 00:20:30,761 --> 00:20:32,196 YOU CAN BASICALLY MEASURE AGING 597 00:20:32,196 --> 00:20:33,063 IN VERY DIFFERENT WAYS. 598 00:20:33,063 --> 00:20:35,132 TO THIS DAY, IT'S STILL UNCLEAR 599 00:20:35,132 --> 00:20:36,333 WHAT'S THE BEST WAY TO MEASURE 600 00:20:36,333 --> 00:20:37,434 AND GOES BACK TO THE MAIN 601 00:20:37,434 --> 00:20:40,070 PROBLEM THAT I POSED EARLY IN MY 602 00:20:40,070 --> 00:20:41,372 TALK ON THE NATURE OF AGING. 603 00:20:41,372 --> 00:20:42,373 BECAUSE WE VIEW AGING IN 604 00:20:42,373 --> 00:20:43,674 DIFFERENT WAYS, AN THEREFORE, IT 605 00:20:43,674 --> 00:20:44,875 CAN BE QUANTIFIED IN DIFFERENT 606 00:20:44,875 --> 00:20:46,177 WAYS. 607 00:20:46,177 --> 00:20:50,681 SO FOR THIS REASON, OUR LAB AND 608 00:20:50,681 --> 00:20:53,184 MANY OTHER LABS STARTED A SO 609 00:20:53,184 --> 00:20:57,788 CALL WOULD BIOMARKER OF AGING 610 00:20:57,788 --> 00:21:00,191 CONSORTIUM, AND THIS IS AN 611 00:21:00,191 --> 00:21:01,125 INSTRUCTOR IN THE LAB WHO 612 00:21:01,125 --> 00:21:01,926 STARTED THIS WHOLE THING AND 613 00:21:01,926 --> 00:21:03,594 KIND OF BROUGHT TOGETHER THE 614 00:21:03,594 --> 00:21:07,431 COMMUNITY, AS WELL AS JC POGANIK 615 00:21:07,431 --> 00:21:07,698 ALSO. 616 00:21:07,698 --> 00:21:08,933 THIS IS THE FIRST PAPER OF THIS 617 00:21:08,933 --> 00:21:09,934 GROUP, KIND OF POSITIONAL PAPER 618 00:21:09,934 --> 00:21:11,569 WHERE WE DEFINED WHAT IS 619 00:21:11,569 --> 00:21:13,537 BIOLOGICAL AGE, WHAT IS AGING, 620 00:21:13,537 --> 00:21:15,072 WHAT'S THE INTERVENTION, YOU 621 00:21:15,072 --> 00:21:16,707 KNOW, WHAT'S THE APPROACHES TO 622 00:21:16,707 --> 00:21:18,142 ADDRESS THAT. 623 00:21:18,142 --> 00:21:19,543 AND BECOME -- THE FIELD BECOMES 624 00:21:19,543 --> 00:21:20,110 VERY POPULAR. 625 00:21:20,110 --> 00:21:22,613 FOR EXAMPLE, WE HAD A CONFERENCE 626 00:21:22,613 --> 00:21:25,015 LAST FALL AND THERE WAS 450 627 00:21:25,015 --> 00:21:29,920 ATTENDEES FROM 30 COUNTRIES. 628 00:21:29,920 --> 00:21:31,488 INITIALLY -- AND IT'S GROWING 629 00:21:31,488 --> 00:21:32,556 EXPONENTIALLY, IT'S REALLY 630 00:21:32,556 --> 00:21:33,324 AMAZING. 631 00:21:33,324 --> 00:21:36,060 SO MUCH TALENT, SO MANY YOUNG 632 00:21:36,060 --> 00:21:36,927 PEOPLE, PEOPLE ARE COMING FROM 633 00:21:36,927 --> 00:21:39,029 ALL KINDS OF DISCIPLINES. 634 00:21:39,029 --> 00:21:41,532 WE HAD A MEETING TOGETHER, A 635 00:21:41,532 --> 00:21:43,100 CHALLENGE, A BIOMARKER CHALLENGE 636 00:21:43,100 --> 00:21:47,972 WHERE ANYBODY COULD COMPETE, 637 00:21:47,972 --> 00:21:51,809 FOUR, 500 PEOPLE FROM MASS 638 00:21:51,809 --> 00:21:53,677 BRIGHAM GENERAL PATIENTS, GENE 639 00:21:53,677 --> 00:21:54,778 METHYLATION, AND ASKED ANYBODY, 640 00:21:54,778 --> 00:21:56,180 OKAY, TELL US WHAT'S THE AGE? 641 00:21:56,180 --> 00:21:57,481 TELL US HOW LONG ARE THEY GOING 642 00:21:57,481 --> 00:21:58,916 TO LIVE? 643 00:21:58,916 --> 00:22:01,118 BECAUSE ABOUT 16% OF THESE 644 00:22:01,118 --> 00:22:03,254 PEOPLE DIED, SAMPLES FROM 15 645 00:22:03,254 --> 00:22:05,256 YEARS AGO. 646 00:22:05,256 --> 00:22:07,224 THIS IS HOW IT WORKS. 647 00:22:07,224 --> 00:22:09,226 THESE ARE THE THREE WINNERS, 648 00:22:09,226 --> 00:22:10,961 THEY GO BY NICKNAMES. 649 00:22:10,961 --> 00:22:13,430 AND THIS IS THE ACTUAL AGE OF 650 00:22:13,430 --> 00:22:14,765 THE PATIENTS FROM OUR HOSPITAL 651 00:22:14,765 --> 00:22:17,635 AND THIS IS -- SEE HOW WELL THEY 652 00:22:17,635 --> 00:22:17,968 PREDICT? 653 00:22:17,968 --> 00:22:20,137 THIS IS THE KNOWN CLOCKS, AND 654 00:22:20,137 --> 00:22:21,572 IT'S ALL NEW CLOCKS FROM THAT 655 00:22:21,572 --> 00:22:22,006 COMPETITION. 656 00:22:22,006 --> 00:22:23,540 THEY ALL OUTCOMPETED THE 657 00:22:23,540 --> 00:22:24,174 EXISTING CLOCKS. 658 00:22:24,174 --> 00:22:27,044 IT'S REALLY AMAZING HOW, AGAIN, 659 00:22:27,044 --> 00:22:29,947 RAPIDLY THINGS DEVELOPED. 660 00:22:29,947 --> 00:22:32,483 , AND MEAN ABSOLUTE ERROR IS 661 00:22:32,483 --> 00:22:35,886 ALMOST TWO YEARS NOW, AGE CAN BE 662 00:22:35,886 --> 00:22:38,422 PREDICTED OF PEOPLE BASED ON THE 663 00:22:38,422 --> 00:22:39,823 BLOOD ANALYSIS. 664 00:22:39,823 --> 00:22:41,025 AND I WILL SHOW YOU A FEW 665 00:22:41,025 --> 00:22:43,427 EXAMPLES OF HOW WE USE THE 666 00:22:43,427 --> 00:22:45,062 CLOCKS CURRENTLY AND BIOMARKERS. 667 00:22:45,062 --> 00:22:46,497 SO FOR EXAMPLE, IN THIS STUDY, 668 00:22:46,497 --> 00:22:51,201 WHICH IS DONE BY JV POGANIK, 669 00:22:51,201 --> 00:22:52,303 ALSO AN INSTRUCTOR IN THE LAB 670 00:22:52,303 --> 00:22:59,176 AND ALSO HAS HIS OWN PROGRAM 671 00:22:59,176 --> 00:23:01,278 WHERE WE STUDY HOW BIOLOGICAL 672 00:23:01,278 --> 00:23:02,579 AGE CHANGES IN RESPONSE TO 673 00:23:02,579 --> 00:23:03,681 STRESS. 674 00:23:03,681 --> 00:23:06,817 AND HE DESCRIBED SEVERAL TYPES 675 00:23:06,817 --> 00:23:12,556 OF STRESS, LIKE MAJOR SURGERY, 676 00:23:12,556 --> 00:23:15,159 COVID-19, IN EACH SITUATION HE 677 00:23:15,159 --> 00:23:18,228 FOUND UNDER STRESS, BIOLOGICAL 678 00:23:18,228 --> 00:23:21,165 STRESS INCREASES, WE CANNOT SAY 679 00:23:21,165 --> 00:23:22,933 IT GOES EXACTLY TO NORMAL BUT AT 680 00:23:22,933 --> 00:23:24,668 LEAST IT'S DECREASED. 681 00:23:24,668 --> 00:23:28,038 SO FOR EXAMPLE IN PREGNANCY, WE 682 00:23:28,038 --> 00:23:29,373 FIND WOMEN ARE BIOLOGICALLY 683 00:23:29,373 --> 00:23:32,109 OLDER IN THE THIRD TRIMESTER, 684 00:23:32,109 --> 00:23:34,945 AND POSTPARTUM BIOLOGICAL AGE IS 685 00:23:34,945 --> 00:23:35,612 DECREASED. 686 00:23:35,612 --> 00:23:37,681 WHAT IS KNOWN ABOUT GESTATIONAL 687 00:23:37,681 --> 00:23:39,350 DIABETES, HEART DISEASE, 688 00:23:39,350 --> 00:23:40,417 MORTALITY CHANGE DURING THIS 689 00:23:40,417 --> 00:23:43,721 PERIOD, WHICH IS ALSO INCREASED. 690 00:23:43,721 --> 00:23:46,123 AND NOW WE HAVE MANY OTHER 691 00:23:46,123 --> 00:23:47,958 MODELS THAT KIND OF SHOW THIS 692 00:23:47,958 --> 00:23:49,827 CONSISTENT PATTERN. 693 00:23:49,827 --> 00:23:54,631 ANOTHER EXAMPLE I'D LIKE TO SNOW 694 00:23:54,631 --> 00:23:57,701 YOU LAST YEAR, THIS WAS LED BY 695 00:23:57,701 --> 00:24:00,003 ALBERT INN, GRADUATE STUDENT, 696 00:24:00,003 --> 00:24:03,841 DID HIS THESIS LAST WEEK, HE'S 697 00:24:03,841 --> 00:24:04,942 NOW DR. YING. 698 00:24:04,942 --> 00:24:06,343 HE DEVELOPED THE FIRST CAUSAL 699 00:24:06,343 --> 00:24:10,948 CLOCK OF AGING. 700 00:24:10,948 --> 00:24:12,583 WHEN AGING HAPPENS, THINGS 701 00:24:12,583 --> 00:24:14,885 CHANGE, RIGHT? 702 00:24:14,885 --> 00:24:16,420 AND DAMAGE IS ACCUMULATED BUT 703 00:24:16,420 --> 00:24:18,922 ALSO AS I MENTIONED, PROTECTION 704 00:24:18,922 --> 00:24:20,791 AGAINST DAMAGE ALSO CHANGES WITH 705 00:24:20,791 --> 00:24:22,326 AGE. 706 00:24:22,326 --> 00:24:25,696 AND WHEN WE BUILD CLOCKS, 707 00:24:25,696 --> 00:24:32,169 TRAINED FOR LOGICAL AGE -- THE 708 00:24:32,169 --> 00:24:35,105 RESPONSES ARE GOOD, BUT THEY 709 00:24:35,105 --> 00:24:36,640 ALSO BECOME PART OF THE CLOCK. 710 00:24:36,640 --> 00:24:38,842 AND IF YOU RANDOMLY BUILD A 711 00:24:38,842 --> 00:24:42,112 CLOCK AND IT HAPPENS TO BE BASED 712 00:24:42,112 --> 00:24:43,647 ON THESE ADAPTIVE CHANGES, THIS 713 00:24:43,647 --> 00:24:45,616 WILL BE VERY MISLEADING IF YOU 714 00:24:45,616 --> 00:24:50,421 APPLY INTERVENTIONS. 715 00:24:50,421 --> 00:24:51,955 -- DEVELOP CLOCK BASED ON 716 00:24:51,955 --> 00:24:53,090 DAMAGING CHANGES AND ADAPTIVE 717 00:24:53,090 --> 00:24:53,390 CHANGES. 718 00:24:53,390 --> 00:24:58,295 AND WE CALL THEM DAMAGE CLOCK 719 00:24:58,295 --> 00:24:58,862 AND ADAPTIVE CLOCK. 720 00:24:58,862 --> 00:25:00,931 BOTH OF THEM CAN PREDICT CHANGES 721 00:25:00,931 --> 00:25:03,233 WITH AGE, BUT WHEN WE APPLY 722 00:25:03,233 --> 00:25:04,568 THESE CLOCKS TO INTERVENTIONS, 723 00:25:04,568 --> 00:25:05,836 THEY SHOW RADICALLY DIFFERENT 724 00:25:05,836 --> 00:25:06,270 CHANGES. 725 00:25:06,270 --> 00:25:08,906 SO FOR EXAMPLE, HERE IS 726 00:25:08,906 --> 00:25:11,308 REPROGRAMMING FROM MY BRO BLAST 727 00:25:11,308 --> 00:25:13,410 CELLS AND DAMAGE CLOCK SHOWS 728 00:25:13,410 --> 00:25:16,246 REJUVENATION, BUT ADAPT AGE DOES 729 00:25:16,246 --> 00:25:17,781 NOT SHOW REJUVENATION, WHICH 730 00:25:17,781 --> 00:25:18,415 MAKES SENSE. 731 00:25:18,415 --> 00:25:19,950 WE TARGET ADAPTIVE CHANGES, THEY 732 00:25:19,950 --> 00:25:21,919 MAY OR MAY NOT BE REJUVENATED. 733 00:25:21,919 --> 00:25:24,555 SO AGAIN, IT SUGGESTS THAT 734 00:25:24,555 --> 00:25:27,491 FURTHER WORK IS NEEDED IN ORDER 735 00:25:27,491 --> 00:25:30,127 TO VERTICAL BIOMARKERS OF AGING. 736 00:25:30,127 --> 00:25:31,862 IT'S A REVOLUTION, IT'S REALLY 737 00:25:31,862 --> 00:25:33,096 AMAZING WHAT WE HAVE, BUT THE 738 00:25:33,096 --> 00:25:34,865 MANY THINGS ARE STILL UNKNOWN, 739 00:25:34,865 --> 00:25:36,366 AND WE NEED THE EFFORT OF THE 740 00:25:36,366 --> 00:25:44,675 ENTIRE COMMUNITY TO DO IT. 741 00:25:44,675 --> 00:25:48,612 ANOTHER EXAMPLE I'D LIKE TO 742 00:25:48,612 --> 00:25:49,546 GIVE, HERE WE STRIVE TO 743 00:25:49,546 --> 00:25:54,084 UNDERSTAND THE RELATIONSHIP OF 744 00:25:54,084 --> 00:25:55,385 COREGULATED CHANGES AND 745 00:25:55,385 --> 00:25:56,153 STOCHASTIC CHANGES. 746 00:25:56,153 --> 00:25:57,921 DURING AGE SOMETHING, THERE ARE 747 00:25:57,921 --> 00:25:59,323 STOCHASTIC CHANGES I EXPECTED. 748 00:25:59,323 --> 00:26:01,792 MUTATIONS HERE AND THERE, THE 749 00:26:01,792 --> 00:26:04,161 EPI MUTATION, SO ON, BY PRODUCT, 750 00:26:04,161 --> 00:26:06,563 BUT ALSO SOME CHANGES MAY BE 751 00:26:06,563 --> 00:26:09,166 KIND OF DETERM DETERMINISTIC. 752 00:26:09,166 --> 00:26:10,601 WE CALL THEM REGULATORY. 753 00:26:10,601 --> 00:26:12,569 AND HERE ASK A QUESTION, WHICH 754 00:26:12,569 --> 00:26:17,608 ONE ACTUALLY WINS? 755 00:26:17,608 --> 00:26:25,148 IF I LACK ATIF YOU LOOK AT THE L 756 00:26:25,148 --> 00:26:26,583 STATE -- STOCHASTIC CHANGES LIKE 757 00:26:26,583 --> 00:26:27,351 THIS, RANDOM CHANGES. 758 00:26:27,351 --> 00:26:28,652 HE FOUND MANY CHANGES ARE 759 00:26:28,652 --> 00:26:29,987 DETERMINISTIC. 760 00:26:29,987 --> 00:26:31,955 LIKE REGULATORY DURING AGING. 761 00:26:31,955 --> 00:26:33,957 BUT ALSO MANY ARE STOCHASTIC. 762 00:26:33,957 --> 00:26:35,893 SO AGAIN, WE HAVE THIS 763 00:26:35,893 --> 00:26:37,761 DEUMALITY, WHEN WE CAN TO THE 764 00:26:37,761 --> 00:26:43,233 CLEARLY SEPARATE THE STOCHASTIC 765 00:26:43,233 --> 00:26:44,735 NATURE. 766 00:26:44,735 --> 00:26:47,504 BY THE WAY, HE HAS DONE IT BY 767 00:26:47,504 --> 00:26:49,239 ANALYZING SINGLE CELL DNA 768 00:26:49,239 --> 00:26:51,441 METHYLATION VERSUS BULK DNA 769 00:26:51,441 --> 00:26:53,076 METHYLATION. 770 00:26:53,076 --> 00:26:55,913 NOW I'D LIKE TO SWITCH TO 771 00:26:55,913 --> 00:27:00,183 ANOTHER TYPE OF BY OWE MARKER, 772 00:27:00,183 --> 00:27:04,121 TRANSCRIPTOMIC CLOCK. 773 00:27:04,121 --> 00:27:06,056 AMAZING DATASET OF ALMOST 5,000 774 00:27:06,056 --> 00:27:07,190 SAMPLES IN MICE AND RATS AND 775 00:27:07,190 --> 00:27:11,762 LATER IN HUMANS AS WELL, THEY 776 00:27:11,762 --> 00:27:13,196 PRESENT VARIOUS MODELS OF 777 00:27:13,196 --> 00:27:15,065 SHORTER AND LONGER LIFE. 778 00:27:15,065 --> 00:27:18,001 LIKE GENETIC MANIPULATION, 779 00:27:18,001 --> 00:27:22,472 DIETARY, PHARMACOLOGICAL THAT 780 00:27:22,472 --> 00:27:24,107 INCREASE LIFESPAN. 781 00:27:24,107 --> 00:27:26,109 HE DEVELOPED A CLOCK, THIS IS A 782 00:27:26,109 --> 00:27:27,611 CHRONOLOGICAL CLOCK BASED ON THE 783 00:27:27,611 --> 00:27:28,512 TRANSCRIPTOME, AND YOU CAN SEE 784 00:27:28,512 --> 00:27:30,247 IN BLUE IS TRAINING SET, IN RED 785 00:27:30,247 --> 00:27:30,814 THE TEST SET. 786 00:27:30,814 --> 00:27:32,215 YOU CAN SEE IT WORKS PRETTY 787 00:27:32,215 --> 00:27:33,750 WELL. 788 00:27:33,750 --> 00:27:36,286 IN PREDICTING CHRONOLOGICAL AGE. 789 00:27:36,286 --> 00:27:37,888 IT'S A MULTI-TISSUE CLOCK BASED 790 00:27:37,888 --> 00:27:43,260 ON THE RNA SEQ, AND BECAUSE 791 00:27:43,260 --> 00:27:45,562 WE'VE HAD THIS LONGEVITY DATA, 792 00:27:45,562 --> 00:27:48,198 HE WAS ABLE TO PREDICT ALSO 793 00:27:48,198 --> 00:27:49,600 DEVELOPMENT OF A MORTALITY 794 00:27:49,600 --> 00:27:51,368 CLOCK, WHICH QUANTIFIES TIME 795 00:27:51,368 --> 00:27:52,235 UNTIL DEATH. 796 00:27:52,235 --> 00:27:54,538 AND THIS MORTALITY -- YOU SEE 797 00:27:54,538 --> 00:27:55,572 THERE'S VERY GOOD CORRESPONDENCE 798 00:27:55,572 --> 00:27:56,707 ABOUT ACTUAL AND PREDICTIVE 799 00:27:56,707 --> 00:27:57,274 MORTALITY. 800 00:27:57,274 --> 00:27:59,943 AND THIS IS HOW JUST ONE 801 00:27:59,943 --> 00:28:00,711 ILLUSTRATION OF THE USEFULNESS 802 00:28:00,711 --> 00:28:02,079 OF THIS CLOCK. 803 00:28:02,079 --> 00:28:04,147 WE APPLY THESE TO INTERVENTIONS 804 00:28:04,147 --> 00:28:05,816 WHICH ARE ALREADY KNOWN TO 805 00:28:05,816 --> 00:28:07,017 EXTEND LIFESPAN OR DECREASE 806 00:28:07,017 --> 00:28:08,418 LIFESPAN, AND THIS IS CONTROL 807 00:28:08,418 --> 00:28:10,821 AND THIS IS LIFESPAN EXTEND 808 00:28:10,821 --> 00:28:12,589 INTERVENTIONS, THIS IS LIFESPAN 809 00:28:12,589 --> 00:28:13,223 SHORTENING INTERVENTIONS. 810 00:28:13,223 --> 00:28:15,092 YOU CAN SEE THE CLOCK CAN BE 811 00:28:15,092 --> 00:28:16,960 USED TO DISTINGUISH THESE 812 00:28:16,960 --> 00:28:17,594 INTERVENTIONS NICELY. 813 00:28:17,594 --> 00:28:18,829 AND OF COURSE IN THE FUTURE, IT 814 00:28:18,829 --> 00:28:21,665 MAY BE USED, YOU KNOW, WITH 815 00:28:21,665 --> 00:28:22,866 OTHER INTERVENTIONS. 816 00:28:22,866 --> 00:28:25,268 THIS STUDY IS STILL UNPUBLISHED, 817 00:28:25,268 --> 00:28:26,470 CURRENTLY IN SUBMISSION, BUT WE 818 00:28:26,470 --> 00:28:27,771 ARE VERY EXCITED ABOUT THIS 819 00:28:27,771 --> 00:28:32,609 CLOCK AND WE KURNLY APPLY MANY 820 00:28:32,609 --> 00:28:34,077 MODELS, I MENTIONED THIS IN A 821 00:28:34,077 --> 00:28:35,445 FEW TALKS AND WE NOW HAVE 822 00:28:35,445 --> 00:28:36,747 SEVERAL DOZEN COOPERATIONS ON 823 00:28:36,747 --> 00:28:39,149 USING THIS CLOCK. 824 00:28:39,149 --> 00:28:40,050 COLLABORATIONS. 825 00:28:40,050 --> 00:28:43,220 THIS IS ILLUSTRATION OF THE 826 00:28:43,220 --> 00:28:45,922 APPLICATION OF THIS CLOCK. 827 00:28:45,922 --> 00:28:47,591 THESE ARE DISEASES IN MICE, LIKE 828 00:28:47,591 --> 00:28:48,558 ALZHEIMER'S DISEASE MODEL, LIKE 829 00:28:48,558 --> 00:28:51,194 A CHRONIC KIDNEY DISEASE, 830 00:28:51,194 --> 00:28:52,295 ISCHEMIC STROKE AND SO ON. 831 00:28:52,295 --> 00:28:54,931 BUT IN EACH CASE, WE FIND THAT 832 00:28:54,931 --> 00:28:58,101 THE DISEASED TISSUE IN MICE 833 00:28:58,101 --> 00:28:59,770 BASED ON THE TRANSCRIPTOMIC 834 00:28:59,770 --> 00:29:00,837 CLOCK IS OLDER THAN THE CONTROL 835 00:29:00,837 --> 00:29:01,471 SISH TEU. 836 00:29:01,471 --> 00:29:03,674 SO IT'S INTERESTING THAT THIS 837 00:29:03,674 --> 00:29:05,942 REALLY AMAZING RELATIONSHIP 838 00:29:05,942 --> 00:29:10,013 BETWEEN DISEASES IN AGING, WHERE 839 00:29:10,013 --> 00:29:13,083 LIKE DISEASE IS ASSOCIATED WITH 840 00:29:13,083 --> 00:29:14,418 INCREASED BIOLOGICAL AGE IN THAT 841 00:29:14,418 --> 00:29:17,354 PARTICULAR TISSUE. 842 00:29:17,354 --> 00:29:18,355 NOW I'D LIKE TO TELL YOU A 843 00:29:18,355 --> 00:29:19,790 LITTLE BIT ABOUT REJUVENATION. 844 00:29:19,790 --> 00:29:24,261 SO WHY WE DISCUSS AGING, IT'S 845 00:29:24,261 --> 00:29:25,228 REPRESENTED BY THIS WATER KIND 846 00:29:25,228 --> 00:29:26,763 OF GOING FROM THE PIPE, AGING IN 847 00:29:26,763 --> 00:29:28,732 THIS DIRECTION, AND IF YOU CAN 848 00:29:28,732 --> 00:29:31,368 SLOW DOWN THIS PROCESS BY 849 00:29:31,368 --> 00:29:33,770 INTERVENTIONS LIKE CALORIE 850 00:29:33,770 --> 00:29:35,105 RESTRICTION, RAPAMYCIN AND SO 851 00:29:35,105 --> 00:29:36,373 ON, BUT WHAT WE ALSO WOULD LIKE 852 00:29:36,373 --> 00:29:37,708 TO DO, WE WOULD LIKE TO TAKE 853 00:29:37,708 --> 00:29:39,009 WATER FROM HERE AND TAKE IT ALL 854 00:29:39,009 --> 00:29:41,211 THE WAY TO HERE, WHICH MEANS 855 00:29:41,211 --> 00:29:43,947 GOING FROM OLDEST STATE TO A 856 00:29:43,947 --> 00:29:44,314 YOUNGER STATE. 857 00:29:44,314 --> 00:29:45,482 IS THIS EVEN POSSIBLE? 858 00:29:45,482 --> 00:29:46,783 IT'S STILL DEBATED IN THE FIELD 859 00:29:46,783 --> 00:29:48,218 AND SOME PEOPLE THINK 860 00:29:48,218 --> 00:29:49,319 REJUVENATION IS SIMPLY NOT 861 00:29:49,319 --> 00:29:50,620 POSSIBLE. 862 00:29:50,620 --> 00:29:52,823 BUT I THINK BY NOW WE HAVE A FEW 863 00:29:52,823 --> 00:29:53,457 EXAMPLES. 864 00:29:53,457 --> 00:29:57,828 AND THE ONE CLEAR EXAMPLE IS IPS 865 00:29:57,828 --> 00:29:58,161 CELLS. 866 00:29:58,161 --> 00:30:00,897 SO WHEN WE CONVERT SOMATIC CELLS 867 00:30:00,897 --> 00:30:02,532 TO EMBRYONIC CELLS, LITERALLY WE 868 00:30:02,532 --> 00:30:04,501 CONVERT THEM FROM OLDER CELLS TO 869 00:30:04,501 --> 00:30:05,602 YOUNGER CELLS. 870 00:30:05,602 --> 00:30:07,804 THEY'RE EMBRYONIC CELLS, THEY'RE 871 00:30:07,804 --> 00:30:12,175 YOUNG CELLS. 872 00:30:12,175 --> 00:30:13,910 ANOTHER EXAMPLE IN THIS STUDY 873 00:30:13,910 --> 00:30:18,081 PUBLISHED IN AGING, NOW IS A 874 00:30:18,081 --> 00:30:20,584 POSTDOC IN THE LAB AND CLOSE 875 00:30:20,584 --> 00:30:24,521 COLLABORATION IS JEAN WYATT AT 876 00:30:24,521 --> 00:30:24,921 DUKE. 877 00:30:24,921 --> 00:30:33,263 WE USED A MODEL OF HETEROCHRONIC 878 00:30:33,263 --> 00:30:34,164 PARABIODOSIS, WE FOLLOW WHAT 879 00:30:34,164 --> 00:30:35,699 HAPPENS AFTER THREE MONTHS, THEN 880 00:30:35,699 --> 00:30:40,070 THEY SEPARATE AND FOLD OASM THEM 881 00:30:40,070 --> 00:30:41,171 NE THEY DIE. 882 00:30:41,171 --> 00:30:43,774 WHAT WE FIND IS THAT AFTER THIS 883 00:30:43,774 --> 00:30:46,510 PROCESS, THE OLD MOUSE IS 884 00:30:46,510 --> 00:30:48,478 REJUVENATED AND IT LIVES LONGER 885 00:30:48,478 --> 00:30:50,347 COMPARED TO CONTROL. 886 00:30:50,347 --> 00:30:52,449 AT THE LEVEL OF EPIGENETIC CLOCK 887 00:30:52,449 --> 00:30:53,750 SHOWN HERE, BUT ACTUALLY WE HAVE 888 00:30:53,750 --> 00:30:57,254 OTHER CLOCKS AS WELL, WE FIND 889 00:30:57,254 --> 00:30:59,222 THAT THESE MICE ARE LITERALLY 890 00:30:59,222 --> 00:30:59,556 REJUVENATED. 891 00:30:59,556 --> 00:31:01,825 THIS IS THE SITUATION THREE 892 00:31:01,825 --> 00:31:04,761 MONTHS AFTER THEY ARE CONNECTED, 893 00:31:04,761 --> 00:31:06,329 THIS SITUATION IS TWO MONTHS 894 00:31:06,329 --> 00:31:08,965 AFTER THEY'VE BEEN DISCONNECTED. 895 00:31:08,965 --> 00:31:09,833 IT REMAINS THERE. 896 00:31:09,833 --> 00:31:12,469 SO THEY'RE STILL YOUNGER THAN 897 00:31:12,469 --> 00:31:14,571 CONTROLS, AND OAFNTLY THEY LIVE 898 00:31:14,571 --> 00:31:15,539 LONGER. 899 00:31:15,539 --> 00:31:16,173 ALTHOUGH I SHOULD MENTION THAT 900 00:31:16,173 --> 00:31:17,841 THE CHANGE IN BIOLOGICAL AGE IS 901 00:31:17,841 --> 00:31:20,911 MUST STRONGER THAN THE EFFECT OF 902 00:31:20,911 --> 00:31:21,378 LONGEVITY. 903 00:31:21,378 --> 00:31:22,712 IT SEEMS LIKE THIS TIME THE 904 00:31:22,712 --> 00:31:23,647 EFFECT DIMINISHES. 905 00:31:23,647 --> 00:31:25,282 IT STILL REMAINS A LITTLE BIT IN 906 00:31:25,282 --> 00:31:28,118 THAT THEY STILL LIVE LONGER, BUT 907 00:31:28,118 --> 00:31:29,219 THE STRONGEST EFFECT IS REALLY 908 00:31:29,219 --> 00:31:30,620 AT THE TIME WHEN THEY ARE 909 00:31:30,620 --> 00:31:31,822 CONNECTED. 910 00:31:31,822 --> 00:31:33,490 AND OVER TIME, AGAIN, IT 911 00:31:33,490 --> 00:31:35,425 DECREASES. 912 00:31:35,425 --> 00:31:36,860 BUT ANYWAY, THIS REPRESENTS 913 00:31:36,860 --> 00:31:38,495 ANOTHER EXAMPLE OF REEF JEUF 914 00:31:38,495 --> 00:31:41,898 NATION AND WE ALSO STUDY THIS ME 915 00:31:41,898 --> 00:31:43,200 NAN NIS PARTICULARLY. 916 00:31:43,200 --> 00:31:43,967 THE THIRD EXAMPLE I'D LIKE TO 917 00:31:43,967 --> 00:31:48,138 SHOW IS ACTUALLY CURRENTLY THE 918 00:31:48,138 --> 00:31:50,207 ONLY NATURAL PROCESS OF 919 00:31:50,207 --> 00:31:50,640 REJUVENATION. 920 00:31:50,640 --> 00:31:51,842 WE COVERED THIS A FEW YEARS AGO. 921 00:31:51,842 --> 00:31:54,344 THIS WAS A CONCEPTUAL PAPER FOUR 922 00:31:54,344 --> 00:31:58,081 YEARS AGO AND THEN WE HAD A FEW 923 00:31:58,081 --> 00:31:59,282 EXPERIMENTAL PAPERS IN MICE 924 00:31:59,282 --> 00:32:00,483 ITSELF AND SO ON. 925 00:32:00,483 --> 00:32:09,693 AND THIS WAS DONE BY -- AND ALEX 926 00:32:09,693 --> 00:32:11,528 TRAPP, AND LEADS INFORMATICS AT 927 00:32:11,528 --> 00:32:12,863 A BIOTECH COMPANY. 928 00:32:12,863 --> 00:32:16,233 WHAT WE FIND IS THAT WHEN -- AT 929 00:32:16,233 --> 00:32:17,634 THE LEVEL OF THE ZYGOTE, WHICH 930 00:32:17,634 --> 00:32:19,636 IS A FERTILIZED EGG, BIOLOGICAL 931 00:32:19,636 --> 00:32:21,104 AGE IS VERY LOW, BUT IT'S NOT 932 00:32:21,104 --> 00:32:22,239 ZERO. 933 00:32:22,239 --> 00:32:24,207 AND INITIALLY, IT KIND OF STAYS 934 00:32:24,207 --> 00:32:27,410 THE SAME AND THEN ABOUT IN THE 935 00:32:27,410 --> 00:32:29,913 THIRD WEEK OF LIFE, IN HUMAN 936 00:32:29,913 --> 00:32:31,114 LIFE, AND IN MICE OF COURSE IT'S 937 00:32:31,114 --> 00:32:32,415 A LITTLE EARLIER, THERE IS A 938 00:32:32,415 --> 00:32:34,751 REDUCTION IN BU BIOLOGICAL AGE. 939 00:32:34,751 --> 00:32:37,153 THE LOWEST BIOLOGICAL AGE IS 940 00:32:37,153 --> 00:32:37,687 FOUND HERE. 941 00:32:37,687 --> 00:32:38,889 WE CALL IT GROUND ZERO. 942 00:32:38,889 --> 00:32:41,524 AND FROM HERE, FROM THIS POINT, 943 00:32:41,524 --> 00:32:43,159 WE COULD DETECT AN INCREASED 944 00:32:43,159 --> 00:32:43,727 BIOLOGICAL AGE. 945 00:32:43,727 --> 00:32:48,565 WE THINK AGING BEGINS RIGHT HERE 946 00:32:48,565 --> 00:32:51,735 AT THE GROUND ZERO LEVEL AND 947 00:32:51,735 --> 00:32:57,741 THIS IS IN DEVELOPMENT -- SO 948 00:32:57,741 --> 00:33:01,344 AGAIN, WE OBSERVED THIS IN 949 00:33:01,344 --> 00:33:04,180 MULTIPLE SITUATIONS, I MEAN, 950 00:33:04,180 --> 00:33:06,049 THEY SEE THIS AT LEVEL OF 951 00:33:06,049 --> 00:33:08,685 EPIGENETIC CLOCK, WE ALSO -- I 952 00:33:08,685 --> 00:33:09,886 DIDN'T INCLUDE HERE BUT ALEX 953 00:33:09,886 --> 00:33:11,621 ALSO DEVELOPED A SINGLE CELL 954 00:33:11,621 --> 00:33:13,823 EPIGENETIC CLOCK, AND THAT'S 955 00:33:13,823 --> 00:33:14,591 QUITE DIFFERENT. 956 00:33:14,591 --> 00:33:16,159 IT ALSO SHOWS REJEUF RANGE OF 957 00:33:16,159 --> 00:33:18,328 MOTION AND TRANSCRIPTOMIC -- 958 00:33:18,328 --> 00:33:21,898 EVEN CONCEPTUALLY W HE KNOW THAT 959 00:33:21,898 --> 00:33:23,566 THE SPERM FROM OLDER MAN IS 960 00:33:23,566 --> 00:33:26,403 OLDER THAN SPERM FROM YOUNGER 961 00:33:26,403 --> 00:33:26,937 MACHINE? 962 00:33:26,937 --> 00:33:29,139 SO THERE MUST BE A PROCESS OF 963 00:33:29,139 --> 00:33:30,006 REJUVENATION SOMEWHERE BUT IT 964 00:33:30,006 --> 00:33:31,207 WAS NOT KNOWN, BUT I THINK THIS 965 00:33:31,207 --> 00:33:32,409 HAPPENS HERE. 966 00:33:32,409 --> 00:33:33,176 MECHANISTICALLY, WE DON'T 967 00:33:33,176 --> 00:33:34,277 UNDERSTAND, BUT WE ARE VERY 968 00:33:34,277 --> 00:33:39,416 EXCITED ABOUT THIS FINDING, IT'S 969 00:33:39,416 --> 00:33:42,819 A NATURAL PROCESS OF 970 00:33:42,819 --> 00:33:43,687 REJUVENATION, APEESHES 971 00:33:43,687 --> 00:33:45,655 UNIVERSALLY ACROSS MAMMALS AND 972 00:33:45,655 --> 00:33:47,924 VERTEBRATES, AND IF YOU 973 00:33:47,924 --> 00:33:49,492 UNDERSTAND MECHANISTICALLY, 974 00:33:49,492 --> 00:33:51,227 PERHAPS IN THE FUTURE, YOU COULD 975 00:33:51,227 --> 00:33:53,296 APPLY TO OTHER SYSTEMS INCLUDING 976 00:33:53,296 --> 00:33:54,064 SOMATIC CELLS. 977 00:33:54,064 --> 00:33:55,165 I WILL SHOW YOU A COUPLE OF 978 00:33:55,165 --> 00:33:57,467 EXAMPLES OF HOW WE STUDY THIS. 979 00:33:57,467 --> 00:34:00,737 THIS IS STRAN SCRIP TOE MIBG 980 00:34:00,737 --> 00:34:01,271 CLOCK. 981 00:34:01,271 --> 00:34:05,442 WE APPLY THIS AT THE SINGLE 982 00:34:05,442 --> 00:34:09,379 LEVEL, SINT .5 -- YOU CAN SEE 983 00:34:09,379 --> 00:34:11,348 THERE'S A NICE REDUCTION IN 984 00:34:11,348 --> 00:34:12,115 BIOLOGICAL AGE. 985 00:34:12,115 --> 00:34:13,750 THE QUESTION IS, OF COURSE, AT 986 00:34:13,750 --> 00:34:14,851 THAT POINT THERE ARE MANY CELLS, 987 00:34:14,851 --> 00:34:16,353 SO WHICH CELLS ARE REJUVENATED 988 00:34:16,353 --> 00:34:17,387 AND WHICH ARE NOT? 989 00:34:17,387 --> 00:34:19,122 AND WE COULD APPLY OUR CLOCK AND 990 00:34:19,122 --> 00:34:20,890 YOU CAN SEE THAT ESSENTIALLY ALL 991 00:34:20,890 --> 00:34:24,828 CELL TYPES ARE REJUVENATED. 992 00:34:24,828 --> 00:34:25,996 THEY GO TO YOUNGER STATE AT THIS 993 00:34:25,996 --> 00:34:27,998 POINT WITH THE EXCEPTION OF 994 00:34:27,998 --> 00:34:29,299 EXTRA EMBRYONIC TISSUES. 995 00:34:29,299 --> 00:34:33,803 SO WE HAVE A FEW EXAMPLES OF 996 00:34:33,803 --> 00:34:35,572 CELLS WHICH LATER BECOME 997 00:34:35,572 --> 00:34:38,274 PLACENTA WHICH ARE NOT 998 00:34:38,274 --> 00:34:39,609 RECIPROCATED -- BUT NOT 999 00:34:39,609 --> 00:34:41,111 REJUVENATED AS LIKE CELLS THAT 1000 00:34:41,111 --> 00:34:44,514 BECOME AN EMBRYO IT SELF TO 1001 00:34:44,514 --> 00:34:49,386 BECOME REJUVENATED. 1002 00:34:49,386 --> 00:34:50,920 AND NOW I'D LIKE TO TELL YOU A 1003 00:34:50,920 --> 00:34:53,423 LITTLE BIT ABOUT AN OMICS LEVEL 1004 00:34:53,423 --> 00:34:55,392 TO QUANTIFY BIOLOGICAL AGE BASED 1005 00:34:55,392 --> 00:34:58,795 ON PROTEOMICS, DONE BY A VERY 1006 00:34:58,795 --> 00:35:00,630 TALENTED POSTDOCTORAL FELLOW IN 1007 00:35:00,630 --> 00:35:00,964 THE LAB. 1008 00:35:00,964 --> 00:35:03,299 HE DEVELOPED A CLOCK THAT 1009 00:35:03,299 --> 00:35:04,634 PREDICTS BIOLOGICAL AGE BASED ON 1010 00:35:04,634 --> 00:35:06,036 THE PLASMA PROTEOME. 1011 00:35:06,036 --> 00:35:08,204 THIS IS AN ACTUAL AGE AND 1012 00:35:08,204 --> 00:35:10,940 PREDICTIVE AGE IN COLORS. 1013 00:35:10,940 --> 00:35:13,343 THIS IS THE CLOCK TRAINED ON 1014 00:35:13,343 --> 00:35:14,677 CHRONOLOGICAL AGE AND THIS IS A 1015 00:35:14,677 --> 00:35:17,614 CLOCK TRAINED ON TIME TO -- ALSO 1016 00:35:17,614 --> 00:35:19,582 WORKS REALLY WELL. 1017 00:35:19,582 --> 00:35:24,287 BUT WE'VE BEEN THINKING THAT WE 1018 00:35:24,287 --> 00:35:25,622 ALWAYS DISCUSS BIOLOGICAL AGE OF 1019 00:35:25,622 --> 00:35:26,523 INDIVIDUALS, LIKE WHEN WE LOOK 1020 00:35:26,523 --> 00:35:28,024 AT THE PERSON AND SAY OH, HOW 1021 00:35:28,024 --> 00:35:29,125 OLD IS THIS PERSON? 1022 00:35:29,125 --> 00:35:35,698 MAYBE 50 OR 30 OR 90. 1023 00:35:35,698 --> 00:35:37,767 BUT PEOPLE ARE COMPLEX ORGANISMS 1024 00:35:37,767 --> 00:35:39,202 AND THEIR CELLS AND TISSUES 1025 00:35:39,202 --> 00:35:40,437 MIGHT AGE WITH SLIGHTLY 1026 00:35:40,437 --> 00:35:41,271 DIFFERENT RATES. 1027 00:35:41,271 --> 00:35:42,906 SO WHAT WE REALLY NEED TO THICK 1028 00:35:42,906 --> 00:35:44,674 IS NOT JUST A BIOLOGICAL AGE OF 1029 00:35:44,674 --> 00:35:47,544 A PERSON, BUT BIOLOGICAL AGE OF 1030 00:35:47,544 --> 00:35:52,315 DIFFERENT TISSUES AND CELLS. 1031 00:35:52,315 --> 00:35:53,550 THAT'S THE PAPER WE PUBLISHED ON 1032 00:35:53,550 --> 00:35:53,750 THAT. 1033 00:35:53,750 --> 00:35:58,988 I WOULD MENTION THAT IT WAS -- 1034 00:35:58,988 --> 00:36:02,592 ANOTHER POPE IF WE DEVELOP 1035 00:36:02,592 --> 00:36:05,228 THIS -- PIONEER THIS APPROACH 1036 00:36:05,228 --> 00:36:06,663 THE ORGAN-SPECIFIC AGING. 1037 00:36:06,663 --> 00:36:09,632 BASICALLY WHAT WE DID, THE STUDY 1038 00:36:09,632 --> 00:36:10,934 BIOBANK POPULATION, 40 TO 70 1039 00:36:10,934 --> 00:36:15,538 YEARS OLD, BUT 45,000 PEOPLE. 1040 00:36:15,538 --> 00:36:17,273 WE HAVE IDENTIFIED PROTEINS IN 1041 00:36:17,273 --> 00:36:18,608 PLASMA THAT COME FROM DIFFERENT 1042 00:36:18,608 --> 00:36:19,042 ORGANS. 1043 00:36:19,042 --> 00:36:21,211 LET'S SAY PROTEINS ARE MADE IN 1044 00:36:21,211 --> 00:36:24,948 THE BRAIN, BASED ON BE GENE 1045 00:36:24,948 --> 00:36:26,282 EXPRESSION AND WE DETECT THEM IN 1046 00:36:26,282 --> 00:36:26,583 PLASMA. 1047 00:36:26,583 --> 00:36:30,186 WE ENSURE THAT THESE ARE BRAIN 1048 00:36:30,186 --> 00:36:31,521 PROTEINS, AND IF YOU FOLLOW HOW 1049 00:36:31,521 --> 00:36:35,892 THEY CHANGE WITH AGE, WE COULD 1050 00:36:35,892 --> 00:36:37,227 BUILD A MODEL OF AGING OF THE 1051 00:36:37,227 --> 00:36:39,195 BRAIN AND BASED ON THESE PLASMA 1052 00:36:39,195 --> 00:36:42,332 PROTEINS, WHICH COULD BE EASILY 1053 00:36:42,332 --> 00:36:43,933 ACCESSIBLE BY -- WE CAN PREDICT 1054 00:36:43,933 --> 00:36:45,768 THE AGE OF THE BRAIN. 1055 00:36:45,768 --> 00:36:50,340 SO THIS WAY WE ARE ABLE TO 1056 00:36:50,340 --> 00:36:56,646 PREDICT THE -- BASED ON PROFILE. 1057 00:36:56,646 --> 00:36:58,148 THE CLOCK CHRONOLOGICAL AND ALSO 1058 00:36:58,148 --> 00:37:02,552 MORTALITY CLOCK, WE CAN ANALYZE 1059 00:37:02,552 --> 00:37:04,854 ORGAN -- YOU KNOW, USING THE 1060 00:37:04,854 --> 00:37:05,622 SAME INDIVIDUAL. 1061 00:37:05,622 --> 00:37:07,357 AND THESE ARE RESIDUALS WHICH 1062 00:37:07,357 --> 00:37:08,691 ARE SHOWN HERE FOR THIS OR GAB 1063 00:37:08,691 --> 00:37:10,260 AGING SO NOW WE HAVE CLOCK FOR 1064 00:37:10,260 --> 00:37:12,629 THE LIVER, BRAIN, ARTERY, 1065 00:37:12,629 --> 00:37:14,264 CONVENTIONAL -- YOU KNOW, 1066 00:37:14,264 --> 00:37:19,102 INTESTINAL CLOCK, KIDNEY CLOCK, 1067 00:37:19,102 --> 00:37:20,970 BASED ON THE PROFILE. 1068 00:37:20,970 --> 00:37:22,772 SO THEY'RE CORRELATED WITH ONE 1069 00:37:22,772 --> 00:37:27,877 ANOTHER, ALSO IN MORTALITY -- 1070 00:37:27,877 --> 00:37:30,813 WHO HAS -- SO IT'S EXPECTED. 1071 00:37:30,813 --> 00:37:32,248 ORGANS SHOW CORRELATION. 1072 00:37:32,248 --> 00:37:37,053 BUT ALSO, THERE ARE SIGNIFICANT 1073 00:37:37,053 --> 00:37:40,356 DEVIATIONS, AND MAYBE 2% OF 1074 00:37:40,356 --> 00:37:41,357 PEOPLE, MAYBE THEY ARE OLDER IN 1075 00:37:41,357 --> 00:37:44,861 THE KIDNEY AND 2% MIGHT BE OLDER 1076 00:37:44,861 --> 00:37:46,596 IN THE BRAIN OR IN THE CART AND 1077 00:37:46,596 --> 00:37:48,464 SO ON. 1078 00:37:48,464 --> 00:37:52,535 SO IN FACT, WHEN WE APPLY OUR 1079 00:37:52,535 --> 00:37:55,138 ORGAN-SPECIFIC ASIAN MODELS, WE 1080 00:37:55,138 --> 00:37:57,240 FIND REALLY AMAZING 1081 00:37:57,240 --> 00:37:57,574 OBSERVATIONS. 1082 00:37:57,574 --> 00:38:00,410 FOR EXAMPLE, IF YOU TAKE A -- 1083 00:38:00,410 --> 00:38:02,946 SPECIFIC MODEL, AND YOU LOOK AT 1084 00:38:02,946 --> 00:38:03,947 DISEASES, THE FIRST DISEASE 1085 00:38:03,947 --> 00:38:11,254 THAT'S PREDICTED BY THE LANT-YOU 1086 00:38:11,254 --> 00:38:18,494 SEE SOPD, OUR ORGAN-SPECIFIC 1087 00:38:18,494 --> 00:38:23,866 CLOCKS TRAINED ON MORTALITY PROO 1088 00:38:23,866 --> 00:38:26,269 PREDICT AGING-RELATED DISEASES 1089 00:38:26,269 --> 00:38:27,170 IN THESE PEOPLE. 1090 00:38:27,170 --> 00:38:32,742 NOW WE CAN RELATE THESE, PEOPLE 1091 00:38:32,742 --> 00:38:34,077 WITH NEN SHA. 1092 00:38:34,077 --> 00:38:36,045 BLUE IS YOUNG, RED IS OLD. 1093 00:38:36,045 --> 00:38:37,580 YOU CAN SEE IN MANY OF THE 1094 00:38:37,580 --> 00:38:39,215 TISSUES, THEY ARE QUITE YOUNG. 1095 00:38:39,215 --> 00:38:41,851 BUT THEY ARE OLD IN THE BRAIN. 1096 00:38:41,851 --> 00:38:43,386 LIKE PEOPLE WITH CPG, THEY'RE 1097 00:38:43,386 --> 00:38:44,821 OLD IN THE LUNG, AND SO ON. 1098 00:38:44,821 --> 00:38:47,557 AND WE ALSO HAVE THIS KIND OF 1099 00:38:47,557 --> 00:38:51,160 LARGE METABOLIC CLUSTER, WE 1100 00:38:51,160 --> 00:38:52,362 CANNOT -- THEY IB FLEUNS ONE 1101 00:38:52,362 --> 00:38:53,997 ANOTHER. 1102 00:38:53,997 --> 00:39:02,138 SO NOW THAT WE HAVE THESE ORGAN 1103 00:39:02,138 --> 00:39:03,773 SPECIFIC -- AGING IN THE ORGAN 1104 00:39:03,773 --> 00:39:06,075 RESULTS IN THE DISEASE IN THIS 1105 00:39:06,075 --> 00:39:06,376 ORGAN. 1106 00:39:06,376 --> 00:39:09,779 WE COULD INSTEAD OF LOOKING FOR 1107 00:39:09,779 --> 00:39:12,749 INTERVENTIONS, THAT EU UNIVERSAY 1108 00:39:12,749 --> 00:39:14,717 USED IN HUMANS, THAT TARGET 1109 00:39:14,717 --> 00:39:15,385 PARTICULAR ORGANS. 1110 00:39:15,385 --> 00:39:16,319 FOR EXAMPLE IF SOMEBODY IS OLD 1111 00:39:16,319 --> 00:39:18,988 IN THE BRAIN, MAYBE ALZHEIMER'S 1112 00:39:18,988 --> 00:39:19,789 DISEASE, FUTURE ALZHEIMER'S 1113 00:39:19,789 --> 00:39:23,926 DISEASE, WE NEED TO TARGET THE 1114 00:39:23,926 --> 00:39:28,398 BRAIN -- I THINK THERE WILL BE 1115 00:39:28,398 --> 00:39:31,334 NO -- NOTHING WORKS UNIVERSALLY 1116 00:39:31,334 --> 00:39:32,669 FOR EVERYBODY. 1117 00:39:32,669 --> 00:39:33,670 CALORIE RESTRICTION IS VERY 1118 00:39:33,670 --> 00:39:35,738 USEFUL BUT WE NEED TO KNOW WHO 1119 00:39:35,738 --> 00:39:41,344 CAN BENEFIT FROM IT, BECAUSE NOT 1120 00:39:41,344 --> 00:39:42,278 EVERYTHING -- LET'S LOOK AT THE 1121 00:39:42,278 --> 00:39:43,746 ASSOCIATION OF VARIOUS 1122 00:39:43,746 --> 00:39:44,747 ENVIRONMENTAL FACTORS. 1123 00:39:44,747 --> 00:39:46,482 THESE ORGAN-SPECIFIC AGING. 1124 00:39:46,482 --> 00:39:52,555 LIKE THIS ORGAN AGES AND -- BUT 1125 00:39:52,555 --> 00:39:53,956 WHICH ORGANS DO I AFFECT BY 1126 00:39:53,956 --> 00:39:54,857 SMOKING? 1127 00:39:54,857 --> 00:39:59,095 YOU FIND ACTUALLY MOST OF THE 1128 00:39:59,095 --> 00:40:00,229 ORGANS ARE AFFECTED. 1129 00:40:00,229 --> 00:40:02,732 LET'S LOOK AT DRINKING. 1130 00:40:02,732 --> 00:40:07,870 DRINKING IS LTION -- LYLE A 1131 00:40:07,870 --> 00:40:10,740 WHOA -- BUT THE EFFECT IS NOT AS 1132 00:40:10,740 --> 00:40:14,143 WITH THE CASE OF SMOKING. 1133 00:40:14,143 --> 00:40:15,678 KIDNEY, INTESTINAL AGE IS 1134 00:40:15,678 --> 00:40:17,647 INCREASED, ARTERIAL AGE IS NOT. 1135 00:40:17,647 --> 00:40:19,415 ACTUALLY IF ANYTHING, MIGHT BE 1136 00:40:19,415 --> 00:40:25,455 REJUVENATED BY ALCOHOL. 1137 00:40:25,455 --> 00:40:28,324 SO DEPENDING ON WHO AGES MORE IN 1138 00:40:28,324 --> 00:40:31,394 THE KIDNEY, INTESTINE, ARTERY, 1139 00:40:31,394 --> 00:40:32,695 ALCOHOL CONSUMPTION COULD HAVE 1140 00:40:32,695 --> 00:40:36,432 RADIALLY DIFFERENT EFFECT. 1141 00:40:36,432 --> 00:40:37,934 JUST ANOTHER EXAMPLE JUST TO 1142 00:40:37,934 --> 00:40:40,136 ILLUSTRATE THIS POINT. 1143 00:40:40,136 --> 00:40:41,904 LET'S CONSIDER ARTERIAL CLOCK. 1144 00:40:41,904 --> 00:40:45,508 AGAIN, PLASMA -- YOU TAKE 1145 00:40:45,508 --> 00:40:46,609 PROTEINS -- BY THE ARTERY AND WE 1146 00:40:46,609 --> 00:40:48,611 TELL THE AGE OF THE ARTERY PLACE 1147 00:40:48,611 --> 00:40:50,246 BACEED ON THE PLASMA PROTEOME. 1148 00:40:50,246 --> 00:40:52,648 WE LOOK AT ASSOCIATIONS, IN THIS 1149 00:40:52,648 --> 00:40:53,216 CASE, FOODS. 1150 00:40:53,216 --> 00:40:57,720 LIKE YOGURT AND WINE. 1151 00:40:57,720 --> 00:40:59,255 SO WINE FOR THE ARTERY SEEMS 1152 00:40:59,255 --> 00:41:00,356 GOOD. 1153 00:41:00,356 --> 00:41:02,658 YOE DPURT IS BAD. 1154 00:41:02,658 --> 00:41:03,326 YOGURT IS BAD. 1155 00:41:03,326 --> 00:41:05,328 BUT IF YOU LOOK AT INTESTINAL 1156 00:41:05,328 --> 00:41:08,398 AGING CLOCK, IT'S OPPOSITE. 1157 00:41:08,398 --> 00:41:11,334 SO NOW WINE IS BAD, YOGURT IS 1158 00:41:11,334 --> 00:41:12,101 GOOD. 1159 00:41:12,101 --> 00:41:16,172 SO TENDING ON AGE IS MORE IN ONE 1160 00:41:16,172 --> 00:41:17,540 ORGAN OR ANOTHER A DIFFERENT 1161 00:41:17,540 --> 00:41:18,674 INTERVENTION WOULD NEED TO BE 1162 00:41:18,674 --> 00:41:19,242 USED. 1163 00:41:19,242 --> 00:41:20,877 THE INTERVENTION NEEDS TO BE 1164 00:41:20,877 --> 00:41:22,779 PERSONALIZED. 1165 00:41:22,779 --> 00:41:26,916 SO WHAT CO DOES IT MEAN? 1166 00:41:26,916 --> 00:41:30,086 FIRST WE -- OF COURSE I TELL BUT 1167 00:41:30,086 --> 00:41:32,655 THE PROTEOMIC-BASED MEASURES, 1168 00:41:32,655 --> 00:41:34,357 BUT WE ARE TRYING TO DEVELOP 1169 00:41:34,357 --> 00:41:37,226 ADDITIONAL MEASURES OF 1170 00:41:37,226 --> 00:41:37,794 ORGAN-SPECIFIC AGING AND OF 1171 00:41:37,794 --> 00:41:41,364 COURSE NOT ONLY MY LAB BUT AN 1172 00:41:41,364 --> 00:41:42,698 EXCELLENT AREA OF RESEARCH. 1173 00:41:42,698 --> 00:41:46,302 WE NEED TO THINK OF TARGETING 1174 00:41:46,302 --> 00:41:47,103 ORGANIZE -- IF SOMEBODY AGES 1175 00:41:47,103 --> 00:41:48,838 MORE IN ONE PARTICULAR SYSTEM, 1176 00:41:48,838 --> 00:41:51,040 LET'S TART THAT BECAUSE THAT 1177 00:41:51,040 --> 00:41:53,009 SYSTEM WILL RESULT IN A DISEASE 1178 00:41:53,009 --> 00:41:54,310 ANTITHE PERSON WILL DIE FROM IT 1179 00:41:54,310 --> 00:41:55,645 MOST LIKELY. 1180 00:41:55,645 --> 00:41:57,380 NEED TO THINK OF PERSONALIZED 1181 00:41:57,380 --> 00:41:57,713 INTERVENTIONS. 1182 00:41:57,713 --> 00:42:01,250 THIS IS OUR MODEL. 1183 00:42:01,250 --> 00:42:02,685 LIFE AGAINS HERE, AGING BEGINS 1184 00:42:02,685 --> 00:42:04,654 HERE. 1185 00:42:04,654 --> 00:42:05,955 REMEMBER GROUND ZERO, THIRD WEEK 1186 00:42:05,955 --> 00:42:10,893 OF LIFE IN HUMANS? 1187 00:42:10,893 --> 00:42:12,328 THEN -- IN THIS PARTICULAR CASE, 1188 00:42:12,328 --> 00:42:14,897 JUST AN EXAMPLE, HEART AGES MORE 1189 00:42:14,897 --> 00:42:18,434 THAN OTHER ORGANS. 1190 00:42:18,434 --> 00:42:20,336 BUT THE HEART IS NOT SIMPLY 1191 00:42:20,336 --> 00:42:21,737 OLDER. 1192 00:42:21,737 --> 00:42:23,706 HEART INTERACTS WITH OTHER 1193 00:42:23,706 --> 00:42:24,140 ORGANS. 1194 00:42:24,140 --> 00:42:25,908 BECAUSE THERE IS A CROSSTALK. 1195 00:42:25,908 --> 00:42:27,777 SO OTHER ORGANS WHICH ARE 1196 00:42:27,777 --> 00:42:30,079 YOUNGER PULL IT BACK. 1197 00:42:30,079 --> 00:42:31,948 SO WITHOUT THESE ORGANS, IT WILL 1198 00:42:31,948 --> 00:42:34,350 BE EVEN OLDER, BUT NOW IT'S IN A 1199 00:42:34,350 --> 00:42:36,652 SLIGHTLY OLER BUT ALTERED STATE. 1200 00:42:36,652 --> 00:42:38,087 AND WE STILL DON'T KNOW EXACTLY 1201 00:42:38,087 --> 00:42:39,388 HOW TO DESCRIBE THAT KIND OF 1202 00:42:39,388 --> 00:42:41,491 SITUATION. 1203 00:42:41,491 --> 00:42:44,093 BUT WHAT I CAN TELL YOU IS THAT 1204 00:42:44,093 --> 00:42:51,133 TO US, BASICALLY WE THINK OF 1205 00:42:51,133 --> 00:42:59,208 DISEASES AS AGING. 1206 00:42:59,208 --> 00:43:01,444 SO TO ME THERE ARE NO DISEASE, 1207 00:43:01,444 --> 00:43:02,845 ALL WE HAVE IS AGING. 1208 00:43:02,845 --> 00:43:04,614 SO AGING HAPPENS, AND SOME 1209 00:43:04,614 --> 00:43:06,115 ORGANS, THEY ARE AGED MORE. 1210 00:43:06,115 --> 00:43:07,917 NOT NECESSARILY ORGANS OR 1211 00:43:07,917 --> 00:43:09,552 SYSTEMS, SOME PART OF THE ORGAN, 1212 00:43:09,552 --> 00:43:15,992 AND THAT STATE RECALL A DISEASE. 1213 00:43:15,992 --> 00:43:18,194 -- FROM THAT STATE, WE 1214 00:43:18,194 --> 00:43:20,730 CALL A DISEASE. 1215 00:43:20,730 --> 00:43:23,566 SO IT HIGHLIGHTS THE IMPORTANCE 1216 00:43:23,566 --> 00:43:25,001 OF THE AGING PROCESS IN ANY KIND 1217 00:43:25,001 --> 00:43:28,337 OF HEALTH-RELATED ISSUES. 1218 00:43:28,337 --> 00:43:29,639 SO I'D LIKE TO SUMMARIZE WHAT I 1219 00:43:29,639 --> 00:43:34,243 WAS TELLING YOU TODAY. 1220 00:43:34,243 --> 00:43:35,244 SO FIRST WE DISCUSSED A LITTLE 1221 00:43:35,244 --> 00:43:37,013 BIT ABOUT THE NATURE OF AGING, 1222 00:43:37,013 --> 00:43:43,786 AGING TO ME IS THE INCREASED 1223 00:43:43,786 --> 00:43:47,857 DELETERIOME, IT BEGINS AT 1224 00:43:47,857 --> 00:43:49,725 GASTRULATION, GROUND ZERO, NOT 1225 00:43:49,725 --> 00:43:50,159 ADAPTIVE. 1226 00:43:50,159 --> 00:43:52,895 IT HAS PHYSICAL INEVITABILITY, 1227 00:43:52,895 --> 00:43:55,197 MANIFESTS CHEMICALLY, MITIGATED 1228 00:43:55,197 --> 00:43:59,268 BIOLOGICALLY. 1229 00:43:59,268 --> 00:44:01,671 DISCUSSED ACROSS SPEES SHE 1230 00:44:01,671 --> 00:44:03,639 CELLS, DIFFERENCES BETWEEN 1231 00:44:03,639 --> 00:44:04,507 LONGEVITY AND KNOWN 1232 00:44:04,507 --> 00:44:06,175 INTERVENTIONS WHICH HIGHLIGHT, 1233 00:44:06,175 --> 00:44:09,679 AGAIN, INDICATES THE POTENTIAL 1234 00:44:09,679 --> 00:44:15,785 TO DEVELOP NEW CADICALLY LIFE 1235 00:44:15,785 --> 00:44:18,087 SAVING INTERVENTIONS, AND 1236 00:44:18,087 --> 00:44:19,555 GENOMES OF LONG LIVED SPECIES. 1237 00:44:19,555 --> 00:44:21,524 ALSO I DISCUSSED A LOT ABOUT 1238 00:44:21,524 --> 00:44:25,061 AGING BIOMARKERS AT THE LEVEL OF 1239 00:44:25,061 --> 00:44:33,135 BULK, SINGLE CELL, STOCHASTIC, 1240 00:44:33,135 --> 00:44:35,104 MULTI-TISSUE. ALSO I 1241 00:44:35,104 --> 00:44:35,871 HIGHLIGHTED REVERSIBLE CHANGES 1242 00:44:35,871 --> 00:44:37,974 IN THE PREDICTED BIOLOGICAL AGE 1243 00:44:37,974 --> 00:44:39,208 UPON SEVERE STRESS. 1244 00:44:39,208 --> 00:44:41,043 AND ALSO DISCUSSED BIOMARKER OF 1245 00:44:41,043 --> 00:44:42,645 AGING CONSORTIUM AND BIOMARKER 1246 00:44:42,645 --> 00:44:44,113 CHALLENGE, WHICH IS A COMMUNITY 1247 00:44:44,113 --> 00:44:48,517 EFFORT THAT WE SUPPORT. 1248 00:44:48,517 --> 00:44:51,253 ANOTHER TOPIC DISCUSSED WAS 1249 00:44:51,253 --> 00:44:52,922 REJUVENATION, AND EXAMPLE, 1250 00:44:52,922 --> 00:44:55,758 CELLULAR PROGRAMMING. 1251 00:44:55,758 --> 00:44:59,161 I DIDN'T MENTION CHEMICALS, BUT 1252 00:44:59,161 --> 00:45:01,697 LAST YEAR PUBLISHED A PAPER, 1253 00:45:01,697 --> 00:45:03,866 BEING ABLE TO REDUCE BIOLOGICAL 1254 00:45:03,866 --> 00:45:04,634 AGE. 1255 00:45:04,634 --> 00:45:07,303 ALSO THIS EXAMPLE OF YOU NATURE, 1256 00:45:07,303 --> 00:45:09,372 GROUND ZERO, AS WELL AS -- SOME 1257 00:45:09,372 --> 00:45:11,440 OF THE EXAMPLES WHERE BIOLOGICAL 1258 00:45:11,440 --> 00:45:13,909 AGE CAN BE REDUCED EVEN THOUGH 1259 00:45:13,909 --> 00:45:17,179 AGING -- THE AGING PROCESS IS 1260 00:45:17,179 --> 00:45:17,613 IRREVERSIBLE. 1261 00:45:17,613 --> 00:45:20,016 ALSO FINAL PART OF MY TALK WAS 1262 00:45:20,016 --> 00:45:22,385 ON ORGAN-SPECIFIC AGING. 1263 00:45:22,385 --> 00:45:24,787 I'VE TOLD BUT ORGAN AGING 1264 00:45:24,787 --> 00:45:26,322 MODELS, MORTALITY BASED MODELS 1265 00:45:26,322 --> 00:45:28,424 AND ASSOCIATION WITH DISEASES 1266 00:45:28,424 --> 00:45:30,593 AND DIETS, WHERE I THINK THAT 1267 00:45:30,593 --> 00:45:35,431 ACTUALLY RATED BIOLOGICAL AGE 1268 00:45:35,431 --> 00:45:39,502 SUBSYSTEM KIND OF -- AGING IS A 1269 00:45:39,502 --> 00:45:40,603 DISEASE, IS REPRESENTED BY 1270 00:45:40,603 --> 00:45:43,005 DISEASE AND, THEREFORE, 1271 00:45:43,005 --> 00:45:44,306 BIOLOGICAL AGE AS A MEASURE CAN 1272 00:45:44,306 --> 00:45:45,775 BE USED TO TARGET A PARTICULAR 1273 00:45:45,775 --> 00:45:47,643 PROCESS BEFORE IT HAPPENS, 1274 00:45:47,643 --> 00:45:48,878 PREEMPTIVELY. 1275 00:45:48,878 --> 00:45:51,213 SO DISEASES IN THAT CONTEXT CAN 1276 00:45:51,213 --> 00:45:57,787 BE VIEWED AS POCKETS OF 1277 00:45:57,787 --> 00:45:59,922 NON-AUTONOMOUS AGING. 1278 00:45:59,922 --> 00:46:01,957 ALL WE DO IS TRY TO UNDERSTAND 1279 00:46:01,957 --> 00:46:06,896 AGING, SO AGAIN THERE IS NO 1280 00:46:06,896 --> 00:46:08,664 CONSENSUS, BUT IT SUCH AN 1281 00:46:08,664 --> 00:46:10,966 IMPORTANT PROCESS BECAUSE IT 1282 00:46:10,966 --> 00:46:14,136 AFFECTS OUR HEALTH, LIKE IT 1283 00:46:14,136 --> 00:46:17,206 DEPENDS ON STUDYING AGING IN MY 1284 00:46:17,206 --> 00:46:17,740 MIND. 1285 00:46:17,740 --> 00:46:18,874 THAT'S THE MOST IMPORTANT 1286 00:46:18,874 --> 00:46:20,309 QUESTION. 1287 00:46:20,309 --> 00:46:23,813 AND THIS IS MY LAB. 1288 00:46:23,813 --> 00:46:25,047 THERE IS PEOPLE THAT HAVE BEEN 1289 00:46:25,047 --> 00:46:26,148 INVOLVED IN THIS WORK AS WELL AS 1290 00:46:26,148 --> 00:46:26,682 PREVIOUS MEMBERS. 1291 00:46:26,682 --> 00:46:28,117 WE HAVE MANY COLLABORATORS. 1292 00:46:28,117 --> 00:46:30,653 I WOULD LIKE PARTICULARLY TO 1293 00:46:30,653 --> 00:46:33,823 MENTION LUIGI FROM THE NIA, 1294 00:46:33,823 --> 00:46:35,291 WHO'S A GREAT COLLEAGUE, AND 1295 00:46:35,291 --> 00:46:36,092 WHAT HAPPENED YESTERDAY I HOPE 1296 00:46:36,092 --> 00:46:37,693 IS A MISTAKE. 1297 00:46:37,693 --> 00:46:40,429 AND OF COURSE OUR FUNDING, ALL 1298 00:46:40,429 --> 00:46:41,630 OF OUR FUNDING, MOST OF OUR 1299 00:46:41,630 --> 00:46:45,034 FUNDING IS FROM NIA, I AM 1300 00:46:45,034 --> 00:46:46,702 GRATEFUL FOR NIA AND NIH FOR 1301 00:46:46,702 --> 00:46:49,205 ALLOWING US TO DO THIS WORK. 1302 00:46:49,205 --> 00:46:50,873 WE ARE VERY PASSIONATE ABOUT IT, 1303 00:46:50,873 --> 00:46:53,509 HOPE TO CONTINUE MAKING PROGRESS 1304 00:46:53,509 --> 00:46:55,277 IN THE FIELD AS WELL AS OTHER 1305 00:46:55,277 --> 00:46:55,578 FUNDERS. 1306 00:46:55,578 --> 00:46:56,645 AND WITH THIS, I WOULD LIKE TO 1307 00:46:56,645 --> 00:46:58,347 YOTHANK YOU FOR YOUR ATTENTION. 1308 00:46:58,347 --> 00:47:08,524 [APPLAUSE] 1309 00:47:10,226 --> 00:47:12,161 >> THAT WAS A WONDERFUL TALK. 1310 00:47:12,161 --> 00:47:14,029 COULD YOU HAZARD A GUESS ON THAT 1311 00:47:14,029 --> 00:47:18,501 ORIGINAL SOURCE OF DAMAGE THAT 1312 00:47:18,501 --> 00:47:20,469 INITIATES THE AGING PROCESS? 1313 00:47:20,469 --> 00:47:25,975 WHAT DO YOU THINK ABOUT REACTIVE 1314 00:47:25,975 --> 00:47:29,044 OXYGEN SPECIES OR INFLAMMATION 1315 00:47:29,044 --> 00:47:30,579 AS UPSTREAM EVENT THAT DRIVES 1316 00:47:30,579 --> 00:47:34,016 ALL THIS -- ALL THE ORGANS? 1317 00:47:34,016 --> 00:47:37,153 >> MY OPINION IS THAT THERE IS 1318 00:47:37,153 --> 00:47:40,456 NO SINGLE CAUSE. 1319 00:47:40,456 --> 00:47:42,658 SO MUCH OF THE FIELD STUDIES OF 1320 00:47:42,658 --> 00:47:44,059 PARTICULAR DAMAGE TYPES, LIKE 1321 00:47:44,059 --> 00:47:47,363 YOU MENTIONED -- I COME FROM THE 1322 00:47:47,363 --> 00:47:50,966 REDOX BIOLOGY FIELD, THAT'S 1323 00:47:50,966 --> 00:47:52,735 MY -- 10 YEARS AGO I PUBLISHED A 1324 00:47:52,735 --> 00:47:58,007 PAPER WITH THE TITLE THE FREE 1325 00:47:58,007 --> 00:47:59,308 RADICAL -- WE SHOULD NOT LIMIT 1326 00:47:59,308 --> 00:48:00,409 OURSELVES TO INDIVIDUAL DAMAGE 1327 00:48:00,409 --> 00:48:00,776 TYPES. 1328 00:48:00,776 --> 00:48:02,511 SO THERE IS NO ONE MOST 1329 00:48:02,511 --> 00:48:04,146 IMPORTANT DAMAGE TYPE. 1330 00:48:04,146 --> 00:48:05,581 THE DAMAGE COMES FROM THE 1331 00:48:05,581 --> 00:48:10,319 TOTALITY OF BUY OJ THAT HAPP BIT 1332 00:48:10,319 --> 00:48:10,953 HAPPENS. 1333 00:48:10,953 --> 00:48:12,755 THE FUNCTION OF ITSELF, 1334 00:48:12,755 --> 00:48:13,956 GENETICALLY ENCODED TYPICALLY, 1335 00:48:13,956 --> 00:48:15,391 BUT ALSO NEGATIVE EFFECT WHICH 1336 00:48:15,391 --> 00:48:17,393 IS CUMULATIVE, AND IF YOU TRY TO 1337 00:48:17,393 --> 00:48:20,229 ISOLATE U ONE COMPONENT, IT WILL 1338 00:48:20,229 --> 00:48:21,764 BE MISLEADING. 1339 00:48:21,764 --> 00:48:23,766 SO IT'S A TOTALITY, THAT'S WHY 1340 00:48:23,766 --> 00:48:26,936 WE CALL IT THE DELETARIOME. 1341 00:48:26,936 --> 00:48:28,604 IT MAKES IT VERY DIFFICULT TO 1342 00:48:28,604 --> 00:48:34,610 STUDY BECAUSE WE TRAINED AS 1343 00:48:34,610 --> 00:48:35,711 REDUCTIONISTS, OTHERS FEATURED 1344 00:48:35,711 --> 00:48:37,046 ON THIS COMPONENT STUDY AND 1345 00:48:37,046 --> 00:48:38,047 EXPLAIN THE PROCESS BUT IT 1346 00:48:38,047 --> 00:48:39,615 DOESN'T WORK IN THE CASE OF 1347 00:48:39,615 --> 00:48:44,420 AGING, IN MY OPINION. 1348 00:48:44,420 --> 00:48:46,822 >> I HAVE TWO QUESTIONS. 1349 00:48:46,822 --> 00:48:48,023 THE FIRST, GOING BACK TO THE 1350 00:48:48,023 --> 00:48:51,861 BEGINNING OF YOUR TALK, WHAT'S 1351 00:48:51,861 --> 00:48:53,162 THE EVOLUTIONARY ADVANTAGE OF 1352 00:48:53,162 --> 00:48:54,096 LONG LIFE? 1353 00:48:54,096 --> 00:48:55,965 SO IF YOU WERE A SMALL RODENT, 1354 00:48:55,965 --> 00:48:57,700 LET'S SAY, THAT CAN MATE WHEN 1355 00:48:57,700 --> 00:48:59,368 YOU'RE A FEW WEEKS OR A FEW 1356 00:48:59,368 --> 00:49:00,903 MONTHS OLD, WHAT'S THE ADVANTAGE 1357 00:49:00,903 --> 00:49:03,539 OF LIVING TO THE AGE OF 40? 1358 00:49:03,539 --> 00:49:05,875 AND MY SECOND QUESTION HAS TO DO 1359 00:49:05,875 --> 00:49:08,611 WITH PARABIOSIS, SO I'VE BEEN 1360 00:49:08,611 --> 00:49:09,678 HEARING PEOPLE TALK ABOUT THIS 1361 00:49:09,678 --> 00:49:11,447 NOW FOR A NUMBER OF YEARS, SO 1362 00:49:11,447 --> 00:49:14,416 THERE MUST BE SOMETHING IN YOUNG 1363 00:49:14,416 --> 00:49:18,153 BLOOD THAT CAN BE USED TO 1364 00:49:18,153 --> 00:49:20,656 REVERSE AGING IN OLDER ANIMALS 1365 00:49:20,656 --> 00:49:25,294 OR OLDER PEOPLE, AND YET I 1366 00:49:25,294 --> 00:49:26,395 HAVEN'T HEARD ANYBODY TALK ABOUT 1367 00:49:26,395 --> 00:49:28,130 A SUBSTANCE, A CHEMICAL, A 1368 00:49:28,130 --> 00:49:31,467 PROTEIN, ANY YOUNG BLOOD THAT 1369 00:49:31,467 --> 00:49:32,368 HAS THAT EFFECT. 1370 00:49:32,368 --> 00:49:33,569 SO WHAT'S THE REASON FOR THAT? 1371 00:49:33,569 --> 00:49:34,870 >> OKAY, THANK YOU. 1372 00:49:34,870 --> 00:49:39,508 THAT'S GREAT QUESTIONS. 1373 00:49:39,508 --> 00:49:41,076 NOW I FORGOT THE FIRST QUESTION. 1374 00:49:41,076 --> 00:49:43,913 >> YES, THE EVOLUTIONARY -- 1375 00:49:43,913 --> 00:49:48,183 >> ANIMALS ADAPT TO THE 1376 00:49:48,183 --> 00:49:48,951 ENVIRONMENT OF THE NICHE. 1377 00:49:48,951 --> 00:49:50,686 SOMETIMES IT'S BENEFICIAL TO 1378 00:49:50,686 --> 00:49:51,620 REPRODUCE VERY RAPIDLY LIKE IN 1379 00:49:51,620 --> 00:49:54,123 THE CASE OF MICE AND RATS, AND 1380 00:49:54,123 --> 00:49:56,525 SOMETIMES JUST -- THERE IS 1381 00:49:56,525 --> 00:49:57,726 ADVANTAGE TO LIVE LONGER AND 1382 00:49:57,726 --> 00:49:59,795 INVEST MORE INTO LIKE A FEW 1383 00:49:59,795 --> 00:50:01,130 PROGENY BUT KIND OF PROTECT THEM 1384 00:50:01,130 --> 00:50:01,764 REALLY WELL. 1385 00:50:01,764 --> 00:50:06,435 IT'S REALLY -- IT'S AN ADAPTIVE 1386 00:50:06,435 --> 00:50:10,706 PROCESS, BUT THE ADAPTATION IS 1387 00:50:10,706 --> 00:50:14,343 FOR THE FITNESS IN THEIR -- 1388 00:50:14,343 --> 00:50:14,877 LONGEVITY COMES SEPARATE. 1389 00:50:14,877 --> 00:50:18,747 SO I'D LIKE TO MAKE THIS -- 1390 00:50:18,747 --> 00:50:19,515 DISTINGUISH AGING FROM 1391 00:50:19,515 --> 00:50:19,815 LONGEVITY. 1392 00:50:19,815 --> 00:50:20,916 AGAIN I ALREADY TRIED IT A 1393 00:50:20,916 --> 00:50:21,784 COUPLE OF TIMES. 1394 00:50:21,784 --> 00:50:25,354 AGING TO ME IS A WASTE, 1395 00:50:25,354 --> 00:50:28,424 LONGEVITY IS ADAPTIVE. 1396 00:50:28,424 --> 00:50:29,391 AND PARABIOSIS. 1397 00:50:29,391 --> 00:50:30,926 YOU'RE RIGHT, SO THERE HAVE BEEN 1398 00:50:30,926 --> 00:50:33,462 MANY STUDIES AND WE STILL DON'T 1399 00:50:33,462 --> 00:50:34,330 UNDERSTAND MECHANISTICALLY HOW 1400 00:50:34,330 --> 00:50:38,400 IT HAPPENS, BECAUSE IT'S A 1401 00:50:38,400 --> 00:50:38,901 COMPLEX MODEL. 1402 00:50:38,901 --> 00:50:40,869 SO WHEN WE CONNECT THE MICE, 1403 00:50:40,869 --> 00:50:42,604 IT'S NOT SIMPLY LIKE 1404 00:50:42,604 --> 00:50:43,505 REJUVENATING FACTORS IN THE 1405 00:50:43,505 --> 00:50:44,740 BLOOD THAT GO TO THE OLD 1406 00:50:44,740 --> 00:50:45,741 ANIMALS. 1407 00:50:45,741 --> 00:50:49,678 BUT ALSO OLDER ANIMALS HAVE 1408 00:50:49,678 --> 00:50:51,747 ACCESS TO THE YOUNGER ORGANS. 1409 00:50:51,747 --> 00:50:52,748 IT'S VERY DIFFICULT TO SEPARATE 1410 00:50:52,748 --> 00:50:53,182 THIS. 1411 00:50:53,182 --> 00:50:56,585 TO ME IT'S LOCALLY 1412 00:50:56,585 --> 00:51:00,122 MULTIFACTORIAL PROCESS WHERE 1413 00:51:00,122 --> 00:51:01,223 MAYBE DAMAGE DELUSION, REMOVAL 1414 00:51:01,223 --> 00:51:05,160 OF DAMAGE FL THROUGH YOUNGER 1415 00:51:05,160 --> 00:51:06,528 ORGANS, ONCE YOU TRY TO 1416 00:51:06,528 --> 00:51:08,597 SEPARATE, ISOLATE, YOU LOSE THE 1417 00:51:08,597 --> 00:51:10,032 EFFECT. 1418 00:51:10,032 --> 00:51:13,102 SO IN OUR HANDS, WE CANNOT 1419 00:51:13,102 --> 00:51:15,304 RECAPITULATE THIS EFFECT BY 1420 00:51:15,304 --> 00:51:19,375 YOUNG BLOOD CELLS, FOR EXAMPLE. 1421 00:51:19,375 --> 00:51:21,343 SO WE DON'T SEE REJUVENATION. 1422 00:51:21,343 --> 00:51:22,678 OF COURSE WE LOOK AT REJEUF 1423 00:51:22,678 --> 00:51:25,614 NEAREJUVENATION OF OTHER ORGANS. 1424 00:51:25,614 --> 00:51:27,216 IS LIVER REJUVENATED? 1425 00:51:27,216 --> 00:51:30,285 WE DON'T OBSERVE THIS EFFECT, 1426 00:51:30,285 --> 00:51:32,454 BUT ONCE WE GO INDIVIDUAL MODEL, 1427 00:51:32,454 --> 00:51:33,622 SOMEHOW WE LOSE THE EFFECT. 1428 00:51:33,622 --> 00:51:34,823 IT'S NOT AN EASY QUESTION. 1429 00:51:34,823 --> 00:51:39,528 >> OKAY, THANK YOU. 1430 00:51:39,528 --> 00:51:41,797 >> VADIM FIRST OF ALL THANK YOU 1431 00:51:41,797 --> 00:51:43,465 FOR A VERY STIMULATING LECTURE 1432 00:51:43,465 --> 00:51:45,000 AND IT'S LIKE THE MORE YOU KNOW, 1433 00:51:45,000 --> 00:51:46,869 YOU'RE OPENING A PANDORA BOX, SO 1434 00:51:46,869 --> 00:51:49,004 ALL KINDS OF INTERESTING THINGS 1435 00:51:49,004 --> 00:51:50,739 POP UP. 1436 00:51:50,739 --> 00:51:53,475 MY QUESTION IS VERY NARROW. 1437 00:51:53,475 --> 00:51:55,444 THERE HAS BEEN A LOT OF 1438 00:51:55,444 --> 00:52:00,215 ATTENTION IN THE LAST FEW YEARS 1439 00:52:00,215 --> 00:52:02,151 ON EXERCISE AS RESETTING 1440 00:52:02,151 --> 00:52:03,018 METABOLISM THAT COULD AFFECT 1441 00:52:03,018 --> 00:52:04,686 MANY O ORGANS. 1442 00:52:04,686 --> 00:52:05,821 HAVE YOU LOOKED AT SOME OF THE 1443 00:52:05,821 --> 00:52:07,689 EFFECTS OF EXERCISE IN YOUR 1444 00:52:07,689 --> 00:52:09,958 MODEL, AND IF IT RESETS SOME OF 1445 00:52:09,958 --> 00:52:12,327 THE AGING MECHANISM OF 1446 00:52:12,327 --> 00:52:13,862 INDIVIDUAL ORGANS WHICH WOULD BE 1447 00:52:13,862 --> 00:52:14,963 OF GREAT INTEREST? 1448 00:52:14,963 --> 00:52:16,131 >> YEAH, THAT'S A GREAT 1449 00:52:16,131 --> 00:52:17,466 QUESTION. 1450 00:52:17,466 --> 00:52:20,235 WE HAVEN'T STUDIED IT IN MY LAB, 1451 00:52:20,235 --> 00:52:22,204 EXERCISE, OF COURSE THERE ARE 1452 00:52:22,204 --> 00:52:23,672 MANY OTHER LABS WHO STUDY AND 1453 00:52:23,672 --> 00:52:25,207 THEY DO OBSERVE HEALTH BENEFITS 1454 00:52:25,207 --> 00:52:25,641 FROM EXERCISE. 1455 00:52:25,641 --> 00:52:28,310 OF COURSE IN HUMANS AND IN MICE. 1456 00:52:28,310 --> 00:52:32,147 I HAVEN'T SEEN ANYBODY LOOKING 1457 00:52:32,147 --> 00:52:33,449 AT ORGAN SPECIFIC. 1458 00:52:33,449 --> 00:52:34,750 ACTUALLY WE DID LOOK A LITTLE 1459 00:52:34,750 --> 00:52:37,986 BIT IN THE UK BIOBANK, WE CAN 1460 00:52:37,986 --> 00:52:41,924 ALSO PREDICT THE AGE BASED ON 1461 00:52:41,924 --> 00:52:43,692 LIKE IMAGING DATA, LIKE A DEXA 1462 00:52:43,692 --> 00:52:44,026 SCAN. 1463 00:52:44,026 --> 00:52:47,229 IN THIS PARTICULAR CASE, WE FIND 1464 00:52:47,229 --> 00:52:49,298 EXERCISE ACTUALLY -- AGING OF 1465 00:52:49,298 --> 00:52:51,266 THE BONE EVEN THOUGH IT 1466 00:52:51,266 --> 00:52:52,167 REJUVENATES -- HELPS TO SLOW 1467 00:52:52,167 --> 00:52:53,535 DOWN AGING OF INTERNAL ORGANS, 1468 00:52:53,535 --> 00:52:55,704 SO THERE IS A KIND OF 1469 00:52:55,704 --> 00:52:56,572 CONTRASTING -- BUT IT'S 1470 00:52:56,572 --> 00:52:58,574 PRELIMINARY DATA, IT'S NOT YET 1471 00:52:58,574 --> 00:52:58,841 PUBLISHED. 1472 00:52:58,841 --> 00:53:00,776 >> SO VADIM, TAKING OFF ON THIS 1473 00:53:00,776 --> 00:53:02,444 QUESTION, THERE ARE RESOURCES 1474 00:53:02,444 --> 00:53:04,480 AROUND, REAGENTS, SPECIMENS, FOR 1475 00:53:04,480 --> 00:53:05,848 EXAMPLE, FROM EXERCISE 1476 00:53:05,848 --> 00:53:08,617 INTERVENTIONS LIKE IN MOTRPAC. 1477 00:53:08,617 --> 00:53:09,852 WOULD THE ABILITY TO LOOK -- 1478 00:53:09,852 --> 00:53:13,455 EVEN IF IT'S JUST SERUM, AT, FOR 1479 00:53:13,455 --> 00:53:15,357 EXAMPLE, EXOSOMES OR PARTICLES 1480 00:53:15,357 --> 00:53:17,326 WHICH CAN BE ATTRIBUTED TO 1481 00:53:17,326 --> 00:53:19,394 VARIOUS ORGANS AND TISSUES, IS 1482 00:53:19,394 --> 00:53:20,462 THIS POTENTIALLY A RICH SOURCE 1483 00:53:20,462 --> 00:53:22,865 OF INFORMATION ABOUT ORGAN 1484 00:53:22,865 --> 00:53:23,866 SPECIFIC -- WITH INTERVENTION, 1485 00:53:23,866 --> 00:53:25,200 THAT'S THERE FOR THE ANALYSIS? 1486 00:53:25,200 --> 00:53:27,736 >> YEAH, DEFINITELY. 1487 00:53:27,736 --> 00:53:29,371 YOU'RE RIGHT. 1488 00:53:29,371 --> 00:53:31,206 SO THESE METHODS -- IT'S VERY 1489 00:53:31,206 --> 00:53:33,308 NEW, SO JUST PUBLISHED, AND 1490 00:53:33,308 --> 00:53:34,676 LIMITED TO SOME DATASET LIKE IN 1491 00:53:34,676 --> 00:53:40,249 OUR CASE, IT'S A PROTEOMICS 1492 00:53:40,249 --> 00:53:43,118 BASED -- BUT YOU'RE RIGHT, SO 1493 00:53:43,118 --> 00:53:44,219 THESE ADDITIONAL APPROACH, WE 1494 00:53:44,219 --> 00:53:46,088 SHOULD BE ABLE TO GO 1495 00:53:46,088 --> 00:53:47,055 ORGAN-SPECIFIC, IN 1496 00:53:47,055 --> 00:53:47,990 ORGAN-SPECIFIC MANNER AND STUDY 1497 00:53:47,990 --> 00:53:49,525 ALL OF THESE EFFECTS INCLUDING 1498 00:53:49,525 --> 00:53:49,791 EXERCISE. 1499 00:53:49,791 --> 00:53:52,161 YOU'RE RIGHT. 1500 00:53:52,161 --> 00:53:52,694 >> HI. 1501 00:53:52,694 --> 00:53:56,265 SO I THOUGHT IT WAS REALLY 1502 00:53:56,265 --> 00:54:00,202 INTERESTING HOW CERTAIN 1503 00:54:00,202 --> 00:54:02,271 INVENTION LIKE CALORIC 1504 00:54:02,271 --> 00:54:05,340 RESTRICTION OR SENOLYTICS HAD A 1505 00:54:05,340 --> 00:54:07,242 DIFFERENT AGING SIGNATURE LIKE 1506 00:54:07,242 --> 00:54:08,443 AGING REVERSE SAL RATHER THAN 1507 00:54:08,443 --> 00:54:10,412 HOW YOU AGE, AND I WAS WONDERING 1508 00:54:10,412 --> 00:54:14,616 IF YOU'VE LOOKED AT HOW 1509 00:54:14,616 --> 00:54:17,152 REPROGRAMMING OR THAT 1510 00:54:17,152 --> 00:54:19,922 REJUVENATION DURING -- HOW THOSE 1511 00:54:19,922 --> 00:54:21,456 ASPECTS OF REDUCING AGING MIGHT 1512 00:54:21,456 --> 00:54:23,892 LOOK IN THAT CONTEXT. 1513 00:54:23,892 --> 00:54:26,428 >> WE ACTUALLY STUDIED THIS, BUT 1514 00:54:26,428 --> 00:54:28,263 WE DON'T HAVE INSIGHTS YET 1515 00:54:28,263 --> 00:54:32,634 BECAUSE WE WANT TO BETTER DEFINE 1516 00:54:32,634 --> 00:54:37,406 THIS REJUVENATION STATES, AND 1517 00:54:37,406 --> 00:54:38,840 LIKE IF YOU NOTICED IN MY TALK 1518 00:54:38,840 --> 00:54:40,776 LIKE IN THE CASE WHEN I WAS 1519 00:54:40,776 --> 00:54:42,744 TALKING ABOUT REVERSIBILITY IN 1520 00:54:42,744 --> 00:54:44,112 BIOLOGICAL AGE, I DIDN'T USE THE 1521 00:54:44,112 --> 00:54:45,113 WORD REJUVENATION BECAUSE LIKE 1522 00:54:45,113 --> 00:54:46,949 IN THIS CASE, ACTUALLY WE DON'T 1523 00:54:46,949 --> 00:54:47,816 KNOW. 1524 00:54:47,816 --> 00:54:50,953 IF WE ARTIFICIALLY INCREASE IT 1525 00:54:50,953 --> 00:54:52,487 AND THEN TO THE NORMAL STATE, IS 1526 00:54:52,487 --> 00:54:53,255 THIS REJUVENATION OR NOT? 1527 00:54:53,255 --> 00:54:54,723 I WAS REFERRING TO REJUVENATION 1528 00:54:54,723 --> 00:54:56,024 WHEN WE GO FROM THE NORMAL STATE 1529 00:54:56,024 --> 00:54:58,460 TO LIKE YOUNGER STATE. 1530 00:54:58,460 --> 00:55:01,230 THEN WE SAY REJUVENATION, BUT 1531 00:55:01,230 --> 00:55:03,966 BIOLOGICAL AGE FLUCTUATES, LIKE 1532 00:55:03,966 --> 00:55:07,903 SEALLY THROUGH STRESS, WHATEVER, 1533 00:55:07,903 --> 00:55:10,138 AND WE NEED TO BETTER UNDERSTAND 1534 00:55:10,138 --> 00:55:13,308 THOSE SITUATIONS. 1535 00:55:13,308 --> 00:55:14,343 BUT IT'S AN EXCELLENT QUESTION 1536 00:55:14,343 --> 00:55:15,711 AND HOPEFULLY IN THE FUTURE 1537 00:55:15,711 --> 00:55:20,716 WE'LL KNOW MORE ABOUT IT. 1538 00:55:20,716 --> 00:55:22,017 >> HI. 1539 00:55:22,017 --> 00:55:25,520 SO I THOUGHT THE MENTION OF 1540 00:55:25,520 --> 00:55:26,622 ORGAN-SPECIFIC AGING WAS SUPER 1541 00:55:26,622 --> 00:55:32,728 INTERESTING. 1542 00:55:32,728 --> 00:55:34,396 SO I UNDERSTAND YOU'VE DONE SOME 1543 00:55:34,396 --> 00:55:38,033 WORK ON HOW ORGANS AGE 1544 00:55:38,033 --> 00:55:38,567 ASYNCHRONOUSLY. 1545 00:55:38,567 --> 00:55:44,106 I WAS WONDERING IF YOU'VE DONOR 1546 00:55:44,106 --> 00:55:44,740 CONCEPTUALIZED INTERACTIVE 1547 00:55:44,740 --> 00:55:46,041 STUDIES, SO KIND OF 1548 00:55:46,041 --> 00:55:48,510 UNDERSTANDING HOW AGING OF LIKE 1549 00:55:48,510 --> 00:55:51,146 THE LUNGS WOULD CORRELATE WITH 1550 00:55:51,146 --> 00:55:53,315 AGING OF THE BRAIN OR AGING OF 1551 00:55:53,315 --> 00:55:54,683 THE PANCREAS, CORRELATING WITH 1552 00:55:54,683 --> 00:55:55,550 AGING OF THE EYE OR SKIN WITH 1553 00:55:55,550 --> 00:55:58,153 THE LIVER, ET CETERA. 1554 00:55:58,153 --> 00:56:01,623 YA, AGAIN, SO THIS IS ALL VERY 1555 00:56:01,623 --> 00:56:04,026 NEW AND IN ONE SLIDE I SHOWED 1556 00:56:04,026 --> 00:56:07,529 THAT THERE IS A CORRELATION, IF 1557 00:56:07,529 --> 00:56:08,530 YOU LOOK AT THE POPULATION 1558 00:56:08,530 --> 00:56:10,899 LEVEL, THERE IS CORRELATION IN 1559 00:56:10,899 --> 00:56:15,170 ONE ORGAN AGING -- ONE ORGAN, 1560 00:56:15,170 --> 00:56:16,571 AGING OF ANOTHER ORGAN IN 1561 00:56:16,571 --> 00:56:17,939 GENERAL BUT THERE'S OUTLIERS. 1562 00:56:17,939 --> 00:56:21,443 SOMETIMES IT'S DIFFICULT TO 1563 00:56:21,443 --> 00:56:23,278 RELATE, LIKE, VARIOUS ORGANS. 1564 00:56:23,278 --> 00:56:26,848 LIKE FOR EXAMPLE, IN THE 1565 00:56:26,848 --> 00:56:28,016 PLASMA -- ORGAN SPECIFIC -- WE 1566 00:56:28,016 --> 00:56:29,418 HAVE ACCESS TO MAYBE EIGHT OR 1567 00:56:29,418 --> 00:56:31,887 NINE ORGANS IN TISSUES. 1568 00:56:31,887 --> 00:56:34,890 SO FOR OTHERS, JUST NOT ENOUGH 1569 00:56:34,890 --> 00:56:35,324 DATA. 1570 00:56:35,324 --> 00:56:36,758 WE NEED BETTER DATASET. 1571 00:56:36,758 --> 00:56:37,959 BUT LIKE EYE, FOR EXAMPLE, WOULD 1572 00:56:37,959 --> 00:56:39,461 NOT BE PART OF IT. 1573 00:56:39,461 --> 00:56:41,630 SO WE TRY TO LOOK AT THE EYE 1574 00:56:41,630 --> 00:56:44,566 THROUGH NOT DEX KA SCAN -- 1575 00:56:44,566 --> 00:56:46,601 IMAGING, AND ALSO -- BUT IT'S -- 1576 00:56:46,601 --> 00:56:48,470 AGAIN, SO WE'RE WORKING ON IT, 1577 00:56:48,470 --> 00:56:50,439 BUT WE ARE NOT ABLE TO RELATE 1578 00:56:50,439 --> 00:56:51,840 YET TO INTERNAL ORGANS. 1579 00:56:51,840 --> 00:56:53,575 >> THANK YOU. 1580 00:56:53,575 --> 00:56:53,975 >> HI. 1581 00:56:53,975 --> 00:56:55,844 SO I WAS CURIOUS ABOUT YOUR 1582 00:56:55,844 --> 00:56:58,347 MODELS ON ORGAN-SPECIFIC AGING 1583 00:56:58,347 --> 00:56:58,647 AS WELL. 1584 00:56:58,647 --> 00:57:00,282 WHAT DID THE DATA LOOK LIKE THAT 1585 00:57:00,282 --> 00:57:01,483 YOU BUILT THOSE MODELS ON? 1586 00:57:01,483 --> 00:57:03,018 FOR EXAMPLE, HOW WERE YOU ABLE 1587 00:57:03,018 --> 00:57:04,619 TO BUILD A MODEL THAT COULD 1588 00:57:04,619 --> 00:57:06,488 PREDICT, FOR EXAMPLE, HOW YOE 1589 00:57:06,488 --> 00:57:13,862 IMYOGURTAFFECTS INTESTINAL AGIN? 1590 00:57:13,862 --> 00:57:16,431 >> THIS DATASET IN UK BIOBANK, 1591 00:57:16,431 --> 00:57:19,334 IT'S 50,000 PEOPLE AND THE 1592 00:57:19,334 --> 00:57:21,570 DATASET HAS ABOUT 3,000 1593 00:57:21,570 --> 00:57:23,038 PROTEINS, QUANTIFICATION OF 1594 00:57:23,038 --> 00:57:25,807 3,000 PR PROTEINS. 1595 00:57:25,807 --> 00:57:27,442 WE LOOK AT ORGAN-SPECIFIC 1596 00:57:27,442 --> 00:57:28,844 EXPRESSION OF GENES BASED ON 1597 00:57:28,844 --> 00:57:30,011 GENE EXPRESSION, BECAUSE WE 1598 00:57:30,011 --> 00:57:31,446 CANNOT LOOK AT THE PROTEINS, 1599 00:57:31,446 --> 00:57:34,716 PROTEIN, IF THEY ARE LIKE IN THE 1600 00:57:34,716 --> 00:57:36,084 ORGAN -- IN PLASMA, IT WOULD 1601 00:57:36,084 --> 00:57:37,819 BE -- BUT GENE EXPRESSION, IF 1602 00:57:37,819 --> 00:57:39,654 IT'S ONLY EXPRESSED IN ONE 1603 00:57:39,654 --> 00:57:40,756 PARTICULAR ORGAN AND DETECTED IN 1604 00:57:40,756 --> 00:57:42,824 PLASMA, WE CAN SAY OKAY, PROTEIN 1605 00:57:42,824 --> 00:57:43,925 COMES FROM THAT ORGAN. 1606 00:57:43,925 --> 00:57:46,161 SO NOW WE FOCUS ON ONLY THAT 1607 00:57:46,161 --> 00:57:47,696 SUBSET FOR PARTICULAR ORGAN, AND 1608 00:57:47,696 --> 00:57:50,732 SOMETIMES IT COULD BE LIKE 20 OR 1609 00:57:50,732 --> 00:57:53,268 50 OR HUNDRED PROTEINS WHICH ARE 1610 00:57:53,268 --> 00:57:54,669 UNIQUE TO A PARTICULAR ORGAN. 1611 00:57:54,669 --> 00:57:57,272 AND WE BUILT AGING BIOMARKERS 1612 00:57:57,272 --> 00:57:58,140 BASED ON THAT. 1613 00:57:58,140 --> 00:57:59,541 NOW IN PLASMA, WE CAN TELL THE 1614 00:57:59,541 --> 00:58:01,209 AGE AND BECAUSE WE HAVE OTHER 1615 00:58:01,209 --> 00:58:02,344 PROTEINS FOR OTHER ORGANS FOR 1616 00:58:02,344 --> 00:58:03,545 THE SAME PERSON, WE CAN TELL AGE 1617 00:58:03,545 --> 00:58:05,414 OF THE BRAIN, LIVER, KIDNEY, SO 1618 00:58:05,414 --> 00:58:07,983 ON, INTESTINAL, ARTERY, SO ON. 1619 00:58:07,983 --> 00:58:09,418 NOW THERE'S INFORMATION ABOUT 1620 00:58:09,418 --> 00:58:10,619 DIET FOR THESE PEOPLE. 1621 00:58:10,619 --> 00:58:15,824 NOT ONLY DIETS, BUT DRUGS, LIKE 1622 00:58:15,824 --> 00:58:18,226 PROFESSIONS, LIKE LIFESTYLES, WE 1623 00:58:18,226 --> 00:58:20,862 DO THIS, ALL OF THIS, AND WE CAN 1624 00:58:20,862 --> 00:58:25,066 FIND ASSOCIATIONS OF THIS KIND 1625 00:58:25,066 --> 00:58:29,538 OF LIFESTYLE CHANGES, WITH ORGAN 1626 00:58:29,538 --> 00:58:29,871 AGING. 1627 00:58:29,871 --> 00:58:31,072 SO YOU SEE? 1628 00:58:31,072 --> 00:58:33,875 >> SO ALL THE LIKE SORT OF 1629 00:58:33,875 --> 00:58:35,343 DIETARY DATA WAS SELF-REPORTED? 1630 00:58:35,343 --> 00:58:37,379 >> IT'S -- IN THIS PARTICULAR 1631 00:58:37,379 --> 00:58:39,948 CASE, IT'S SELF-REPORTED. 1632 00:58:39,948 --> 00:58:42,784 ALSO WE COULD QUANTIFY -- WE 1633 00:58:42,784 --> 00:58:45,086 COULD DO VARIOUS WAYS, BUT 1634 00:58:45,086 --> 00:58:45,854 SELF-REPORTED BUT ALSO WE 1635 00:58:45,854 --> 00:58:46,788 QUANTIFY THE TOTAL AMOUNT OF 1636 00:58:46,788 --> 00:58:49,791 CERTAIN TYPES OF FOOD BASED ON 1637 00:58:49,791 --> 00:58:50,826 THE KNOWN -- WHEN PEOPLE SAY 1638 00:58:50,826 --> 00:58:53,195 WHAT THEY EAT, WE COULD QUANTIFY 1639 00:58:53,195 --> 00:58:54,062 BASED ON CALORIES AT COMPONENTS 1640 00:58:54,062 --> 00:58:54,496 OF THE FOOD. 1641 00:58:54,496 --> 00:58:56,598 >> GOT IT, THANK YOU. 1642 00:58:56,598 --> 00:58:57,365 >> HI. 1643 00:58:57,365 --> 00:58:58,633 VERY INTERESTING. 1644 00:58:58,633 --> 00:59:01,470 SO A QUESTION, SO WHEN YOU 1645 00:59:01,470 --> 00:59:03,972 TALKED ABOUT THE DIFFERENT 1646 00:59:03,972 --> 00:59:04,840 ORGANS, DIFFERENT SPEED, 1647 00:59:04,840 --> 00:59:06,541 DIFFERENT PEOPLE AND DIFFERENT 1648 00:59:06,541 --> 00:59:07,876 INTERVENTIONS LIKE FOODS HAVING 1649 00:59:07,876 --> 00:59:12,881 DIFFERENT EFFECT, DOES YOUR BODY 1650 00:59:12,881 --> 00:59:16,318 TELL YOU WHAT TO EAT DEPENDING 1651 00:59:16,318 --> 00:59:17,919 ON THE SIGNALS THAT YOU GET FROM 1652 00:59:17,919 --> 00:59:18,587 YOUR ORGANS? 1653 00:59:18,587 --> 00:59:22,524 FOR EXAMPLE, LIKE YOUR ARTERY IS 1654 00:59:22,524 --> 00:59:24,226 AGING FASTER AND YOU HAVE A 1655 00:59:24,226 --> 00:59:26,294 CRAVING FOR WHITE WINE, OR YOUR 1656 00:59:26,294 --> 00:59:27,929 INTESTINE AND THEN -- THAT'S WHY 1657 00:59:27,929 --> 00:59:30,732 YOU LIKE THE YOGURT DURING THESE 1658 00:59:30,732 --> 00:59:32,501 FEW YEARS FOR EXAMPLE AND THEN 1659 00:59:32,501 --> 00:59:33,935 DON'T ANYMORE. 1660 00:59:33,935 --> 00:59:35,637 >> IT MAY BE, IT MAY BE THE 1661 00:59:35,637 --> 00:59:36,538 CASE. 1662 00:59:36,538 --> 00:59:38,540 WE HAVEN'T STUDIES THIS. 1663 00:59:38,540 --> 00:59:40,075 IT WOULD BE VERY INTERESTING TO 1664 00:59:40,075 --> 00:59:41,076 TEST, I AGREE. 1665 00:59:41,076 --> 00:59:46,348 IT'S AN IMPORTANT QUESTION. 1666 00:59:46,348 --> 00:59:48,783 >> I THOUGHT IT WAS VERY 1667 00:59:48,783 --> 00:59:50,418 INTERESTING OF HOW YOU DESCRIBED 1668 00:59:50,418 --> 00:59:53,955 CELL DIVISION AS DELUSION OF DIF 1669 00:59:53,955 --> 00:59:54,189 DAMAGE. 1670 00:59:54,189 --> 00:59:57,259 DO YOU THINK THE SAME CONCEPT AT 1671 00:59:57,259 --> 01:00:00,562 A MACROSCOPIC LEVEL, WHERE IT'S 1672 01:00:00,562 --> 01:00:01,763 DILUTING DAMAGED PRODUCTS IN THE 1673 01:00:01,763 --> 01:00:02,998 BLOOD, AND THEN AS A FOLLOW-UP 1674 01:00:02,998 --> 01:00:04,366 TO THAT, DO YOU EVER TEST 1675 01:00:04,366 --> 01:00:06,401 WHETHER THE YOUNG MICE AFTER 1676 01:00:06,401 --> 01:00:07,402 PARABIOSIS LIVE FOR A SHORT 1677 01:00:07,402 --> 01:00:10,472 AMOUNT OF TIME? 1678 01:00:10,472 --> 01:00:13,408 >> SO MECHANISTICALLY WE DON'T 1679 01:00:13,408 --> 01:00:16,211 FULLY UNDERSTAND BUT I THINK 1680 01:00:16,211 --> 01:00:17,279 DAMAGE DILUTION IS DEFINITELY 1681 01:00:17,279 --> 01:00:20,582 ONE OF THE FACTORS IN CHANGING 1682 01:00:20,582 --> 01:00:21,449 THE BIOLOGICAL AGE. 1683 01:00:21,449 --> 01:00:23,251 IN TERMS OF THE OLD MICE, WE 1684 01:00:23,251 --> 01:00:26,121 ACTUALLY DO HAVE THE DATA, 1685 01:00:26,121 --> 01:00:27,222 PUBLISHED A PAPER ON THAT AND WE 1686 01:00:27,222 --> 01:00:29,224 FOUND THAT AFTER THREE MONTHS, 1687 01:00:29,224 --> 01:00:34,996 YOUNGER MICE, THEY DR. MATICALLY 1688 01:00:34,996 --> 01:00:38,033 INCREASE THEIR BIOLOGICAL AGE, 1689 01:00:38,033 --> 01:00:38,700 ALMOST DOUBLE. 1690 01:00:38,700 --> 01:00:40,902 TWO MONTHS LAY TE THE BIOLOGICAL 1691 01:00:40,902 --> 01:00:41,937 AGE GOES BACK TO ALMOST MORE 1692 01:00:41,937 --> 01:00:42,370 MALL. 1693 01:00:42,370 --> 01:00:43,471 SO IT SEEMS LIKE UNDER STRESS, 1694 01:00:43,471 --> 01:00:45,206 THEY ARE NOT ABLE TO DEAL WITH 1695 01:00:45,206 --> 01:00:46,341 ALL THIS DAMAGE THAT COMES FROM 1696 01:00:46,341 --> 01:00:48,677 THE OLDER MICE, BUT AFTER THE 1697 01:00:48,677 --> 01:00:50,345 MICE ARE SEPARATED, SLOWLY, THEY 1698 01:00:50,345 --> 01:00:52,447 ARE ABLE TO RECOVER AND KIND OF 1699 01:00:52,447 --> 01:00:54,115 REMOVE THAT DAMAGE. 1700 01:00:54,115 --> 01:00:56,284 AND THEREFORE BIOLOGICAL AGE IS 1701 01:00:56,284 --> 01:00:58,687 DECREASED. 1702 01:00:58,687 --> 01:01:02,924 THE ACCURACY OF THE CLOCKS IS 1703 01:01:02,924 --> 01:01:03,491 INSUFFICIENT WHETHER THEY'RE 1704 01:01:03,491 --> 01:01:05,327 EXACTLY THE SAME AS NORMAL OR 1705 01:01:05,327 --> 01:01:06,528 SLIGHTLY ABOVE, THIS, WE ARE NOT 1706 01:01:06,528 --> 01:01:10,632 SURE WITH YOU IT DEFI BUT IT DES 1707 01:01:10,632 --> 01:01:10,966 REVERSIBILITY. 1708 01:01:10,966 --> 01:01:11,299 >> THANK YOU. 1709 01:01:11,299 --> 01:01:14,436 >> THANK YOU FOR A FASCINATING 1710 01:01:14,436 --> 01:01:16,404 TALK. 1711 01:01:16,404 --> 01:01:17,038 TREMENDOUS BODY OF WORK. 1712 01:01:17,038 --> 01:01:17,372 >> THANK YOU. 1713 01:01:17,372 --> 01:01:19,174 >> MY QUESTION HAS TO DO WITH 1714 01:01:19,174 --> 01:01:22,043 PHYSIOLOGIC STRESS-RELATED 1715 01:01:22,043 --> 01:01:24,646 CHANGES. 1716 01:01:24,646 --> 01:01:25,080 IN AGING. 1717 01:01:25,080 --> 01:01:30,352 YOU MENTIONED AS AN EXAMPLE 1718 01:01:30,352 --> 01:01:31,720 PREGNANCY, THEN THERE'S A 1719 01:01:31,720 --> 01:01:32,787 REVERSAL IN THE POSTPARTUM 1720 01:01:32,787 --> 01:01:33,054 PERIOD. 1721 01:01:33,054 --> 01:01:40,095 AND MY QUESTION IS, IS IT AN 1722 01:01:40,095 --> 01:01:41,830 UNMECHANISTIC EXPLANATION FOR 1723 01:01:41,830 --> 01:01:43,765 THIS REVERSAL IN THE POSTPARTUM 1724 01:01:43,765 --> 01:01:44,699 PERIOD? 1725 01:01:44,699 --> 01:01:45,667 THE SECOND RELATED QUESTION IS 1726 01:01:45,667 --> 01:01:47,268 YOU MAP THE PATTERN OF AGING OF 1727 01:01:47,268 --> 01:01:49,704 DIFFERENT O ORGAN, AND MY QUESTN 1728 01:01:49,704 --> 01:01:52,474 IS WE HAVE AN ORGAN THAT HAS A 1729 01:01:52,474 --> 01:01:53,775 TIMETABLE THAT IS THE PLACENTA. 1730 01:01:53,775 --> 01:01:55,910 DO YOU KNOW IF THERE IS AGING OF 1731 01:01:55,910 --> 01:01:59,981 THE PLACENTA? 1732 01:01:59,981 --> 01:02:02,917 >> LET ME GO FIRST WITH THE 1733 01:02:02,917 --> 01:02:03,885 PLACENTA BECAUSE EVENTUALLY WE 1734 01:02:03,885 --> 01:02:05,320 DID TEST IT BECAUSE I WAS 1735 01:02:05,320 --> 01:02:06,655 THINKING PLACENTA EXACTLY AS YOU 1736 01:02:06,655 --> 01:02:09,324 SAY HAS A PARTICULAR TIME SPAN, 1737 01:02:09,324 --> 01:02:12,193 AND THEREFORE MIGHT BE OLDER. 1738 01:02:12,193 --> 01:02:14,763 BUT WHEN WE TESTED, WE STILL 1739 01:02:14,763 --> 01:02:16,097 FIND IT YOUNG. 1740 01:02:16,097 --> 01:02:19,334 SOMEHOW IT AGES BUT DOESN'T AGE 1741 01:02:19,334 --> 01:02:20,368 AS I THOUGHT IT WOULD AGE. 1742 01:02:20,368 --> 01:02:23,505 IT WOULD AGE MORE LIKE THAN THE 1743 01:02:23,505 --> 01:02:25,373 EMBRYO, BUT ITS AGE IS ABOUT THE 1744 01:02:25,373 --> 01:02:26,041 SAME FOR SOME REASON. 1745 01:02:26,041 --> 01:02:28,610 >> SO IT MAY BE THAT THERE IS A 1746 01:02:28,610 --> 01:02:31,246 PROCESS THAT IS NOT MEASURABLE 1747 01:02:31,246 --> 01:02:32,080 WITH THE TOOLS THAT WE HAVE. 1748 01:02:32,080 --> 01:02:32,881 >> IT'S POSSIBLE. 1749 01:02:32,881 --> 01:02:34,716 >> BUT PERHAPS IT'S THE WAY THE 1750 01:02:34,716 --> 01:02:37,218 QUESTION IS FRAMED. 1751 01:02:37,218 --> 01:02:39,487 THIS PHYSIOLOGIC PREGNANCY AND 1752 01:02:39,487 --> 01:02:40,355 COMPLICATED PREGNANCY AND IN THE 1753 01:02:40,355 --> 01:02:42,957 CONTEXT OF COMPLICATION, LET'S 1754 01:02:42,957 --> 01:02:44,693 SAY, PREMATURITY OR 1755 01:02:44,693 --> 01:02:47,328 PREECLAMPSIA, WOULD THAT 1756 01:02:47,328 --> 01:02:47,595 AFFECT -- 1757 01:02:47,595 --> 01:02:49,230 >> THIS PREMATURE KIND OF 1758 01:02:49,230 --> 01:02:51,332 PREGNANCY, WE HAVE A PROJECT ON 1759 01:02:51,332 --> 01:02:52,867 THAT, WE STUDY THIS, WE DON'T 1760 01:02:52,867 --> 01:02:54,235 HAVE DATA YET, BUT THAT'S 1761 01:02:54,235 --> 01:02:56,204 EXACTLY WHAT -- LIKE EARLY LIFE 1762 01:02:56,204 --> 01:02:57,539 ADVERSITY BASICALLY WE CALL 1763 01:02:57,539 --> 01:02:59,174 EARLY LIFE ADVERSITY, HOW IT 1764 01:02:59,174 --> 01:03:00,041 AFFECTS BIOLOGICAL AGE. 1765 01:03:00,041 --> 01:03:01,509 BUT IN TERMS OF REVERSIBLE 1766 01:03:01,509 --> 01:03:04,813 CHANGES DURING PREGNANCY, I 1767 01:03:04,813 --> 01:03:07,682 THINK DAMAGE DILUTION IS AN EASY 1768 01:03:07,682 --> 01:03:10,351 KIND OF WAY TO EXPLAIN IT, AND 1769 01:03:10,351 --> 01:03:16,357 THERE'S A HUGE STRESS IN 1770 01:03:16,357 --> 01:03:17,559 PREGNANCY ON WOMEN, THEY'RE NOT 1771 01:03:17,559 --> 01:03:18,727 ABLE TO DEAL WITH ALL OF THE 1772 01:03:18,727 --> 01:03:20,695 DAMAGE THAT IS GENERATED BUT 1773 01:03:20,695 --> 01:03:22,030 POSTPARTUM DAMAGE CAN BE SLOWLY 1774 01:03:22,030 --> 01:03:22,764 REMOVED. 1775 01:03:22,764 --> 01:03:25,700 BUT SOMETIMES I'M GETTING A 1776 01:03:25,700 --> 01:03:27,102 QUESTION WHETHER WHEN THEY 1777 01:03:27,102 --> 01:03:28,436 RECOVER, THE AGE WILL BE EVEN 1778 01:03:28,436 --> 01:03:30,939 LOWER THAN NORMAL. 1779 01:03:30,939 --> 01:03:32,674 AND THE REASON IS BECAUSE OF THE 1780 01:03:32,674 --> 01:03:36,811 PARABIOSIS WITH THE FETUS. 1781 01:03:36,811 --> 01:03:37,812 THAT'S ALSO A VERY INTERESTING 1782 01:03:37,812 --> 01:03:38,346 QUESTION. 1783 01:03:38,346 --> 01:03:40,081 AFTER WE PUBLISHED OUR PAPER 1784 01:03:40,081 --> 01:03:41,483 ABOUT A YEARING A, THERE WAS 1785 01:03:41,483 --> 01:03:42,817 ANOTHER PAPER PUBLISHED LATER 1786 01:03:42,817 --> 01:03:46,154 ALSO IN CELL METABOLISM, THEY 1787 01:03:46,154 --> 01:03:47,388 FOUND THAT THERE MIGHT BE A 1788 01:03:47,388 --> 01:03:51,192 REDUCTION EVEN MORE SIGNIFICANT, 1789 01:03:51,192 --> 01:03:52,527 OUR -- IN THEIR CASE IT WAS A 1790 01:03:52,527 --> 01:03:53,695 BETTER DATASET AND THEY FOUND 1791 01:03:53,695 --> 01:03:56,397 ALSO THAT WOMEN WHO BREAST-FED 1792 01:03:56,397 --> 01:03:57,732 THEIR BABIES, THEY ALSO 1793 01:03:57,732 --> 01:03:58,299 RECOVERED FASTER. 1794 01:03:58,299 --> 01:04:01,536 SO IT'S INTERESTING. 1795 01:04:01,536 --> 01:04:03,271 SO IT -- IT NEEDS TO BE 1796 01:04:03,271 --> 01:04:04,272 REPRODUCED BY OTHER LABS BUT IT 1797 01:04:04,272 --> 01:04:06,074 SEEMS LIKE AT LEAST IN THE CASE 1798 01:04:06,074 --> 01:04:08,042 OF REVERSAL OF CHANGES DURING 1799 01:04:08,042 --> 01:04:09,911 PREGNANCY, THE TWO LABS HAVE 1800 01:04:09,911 --> 01:04:11,346 SIMILAR DATA. 1801 01:04:11,346 --> 01:04:13,081 >> MAYBE ONE MORE, DR. HODES, 1802 01:04:13,081 --> 01:04:14,482 AND THEN WE'LL FINISH UP OVER 1803 01:04:14,482 --> 01:04:14,816 HERE. 1804 01:04:14,816 --> 01:04:16,684 SHE WAS THERE FIRST. 1805 01:04:16,684 --> 01:04:18,086 >> THANKS FOR THE TALK. 1806 01:04:18,086 --> 01:04:20,922 AND MY QUESTION IS, THE AGING 1807 01:04:20,922 --> 01:04:24,425 COMMUNITY SEEMS TO USE THAT 1808 01:04:24,425 --> 01:04:25,960 DEVIATION FROM TRUE PREDICTION 1809 01:04:25,960 --> 01:04:28,563 AS A MEASURE OF REJUVENATION, 1810 01:04:28,563 --> 01:04:30,398 LIKE, IF WE'RE PREDICTING WITH 1811 01:04:30,398 --> 01:04:31,533 LESS ACCURACY, PREDICTING 1812 01:04:31,533 --> 01:04:31,833 YOUNGER. 1813 01:04:31,833 --> 01:04:33,535 SO MY QUESTION, EVEN WITH -- IF 1814 01:04:33,535 --> 01:04:36,938 YOU HAVE A CAUSAL CLOCK AND YOU 1815 01:04:36,938 --> 01:04:38,840 INCORPORATE SMR, HOW DO YOU KNOW 1816 01:04:38,840 --> 01:04:41,509 IF THERE'S REALLY RELEVANT 1817 01:04:41,509 --> 01:04:42,744 BIOLOGICAL CONTEXT IN 1818 01:04:42,744 --> 01:04:43,077 REJUVENATION? 1819 01:04:43,077 --> 01:04:43,945 >> IT'S A VERY GOOD QUESTION. 1820 01:04:43,945 --> 01:04:45,880 SO THE CONCEPT OF BIOMARKERS OF 1821 01:04:45,880 --> 01:04:47,282 AGING IS VERY NEW, RIGHT? 1822 01:04:47,282 --> 01:04:49,818 AND IT'S POSSIBLE THAT IF YOU 1823 01:04:49,818 --> 01:04:51,553 JUST USE ONE INDIVIDUAL 1824 01:04:51,553 --> 01:04:52,954 BIOMARKER, IT MIGHT HAVE 1825 01:04:52,954 --> 01:04:53,388 MISLEADING EFFECT. 1826 01:04:53,388 --> 01:04:55,924 SO IN ANY OF THE STUDIES THAT 1827 01:04:55,924 --> 01:04:57,225 DEFINED, THERE IS ALL THIS -- WE 1828 01:04:57,225 --> 01:04:58,660 CANNOT BE 100% SURE, THAT'S 1829 01:04:58,660 --> 01:04:59,093 TRUE. 1830 01:04:59,093 --> 01:05:01,996 BUT FOR EXAMPLE, IN THE CASE OF 1831 01:05:01,996 --> 01:05:03,631 LIKE -- IN -- REJUVENATION, 1832 01:05:03,631 --> 01:05:05,700 THAT'S WHY I MENTIONED WE HAVE 1833 01:05:05,700 --> 01:05:06,901 DIFFERENT TYPES OF CLOCK, 1834 01:05:06,901 --> 01:05:11,039 COMPLETELY DIFFERENT, LIKE 1835 01:05:11,039 --> 01:05:12,473 TRANSCRIPTOMIC CLOCK -- THEY ALL 1836 01:05:12,473 --> 01:05:14,108 SHOW THE SAME. 1837 01:05:14,108 --> 01:05:15,310 AND CONCEPTUALLY WE EXPECT TO 1838 01:05:15,310 --> 01:05:16,277 SEE THAT AS WELL. 1839 01:05:16,277 --> 01:05:20,215 SO THEN WE SAY OKAY, I FEEL 1840 01:05:20,215 --> 01:05:21,516 QUITE CONFIDENT THERE IS 1841 01:05:21,516 --> 01:05:22,250 EMBRYONIC REJUVENATION. 1842 01:05:22,250 --> 01:05:24,352 ALSO FOR PARABIOSIS, WE USE ALL 1843 01:05:24,352 --> 01:05:27,589 KINDS OF BIOMARKERS, WE OBSERVE 1844 01:05:27,589 --> 01:05:29,123 CONSISTENT EFFECTS SO WE ARE 1845 01:05:29,123 --> 01:05:29,657 QUITE CONFIDENT. 1846 01:05:29,657 --> 01:05:32,393 IN MANY OTHER CASES, WE ARE 1847 01:05:32,393 --> 01:05:32,961 QUITE UNSURE. 1848 01:05:32,961 --> 01:05:36,998 IF YOU LOOK N IN THE LITERATURE, 1849 01:05:36,998 --> 01:05:38,700 IS IT REJUVENATION, SLOWING OF 1850 01:05:38,700 --> 01:05:40,235 AGING OR -- A PARTICULAR 1851 01:05:40,235 --> 01:05:40,501 BIOMARKER. 1852 01:05:40,501 --> 01:05:43,071 >> HOW DO I RECONCILE IN TERMS 1853 01:05:43,071 --> 01:05:45,139 OF SOME SENESCENT CELLS IN AGING 1854 01:05:45,139 --> 01:05:46,441 IN DISEASE AND CANCER, THEY 1855 01:05:46,441 --> 01:05:48,943 START TO HAVE THE STEMNESS 1856 01:05:48,943 --> 01:05:50,879 FACTOR AND IT SEEMS TO PREDICT 1857 01:05:50,879 --> 01:05:57,652 YOUNGER, BUT THEY ARE STILL 1858 01:05:57,652 --> 01:05:57,986 INCREASING -- 1859 01:05:57,986 --> 01:05:59,854 > INCREASING 1860 01:05:59,854 --> 01:06:00,788 EMBRYONIC STEM CELL MARKERS. 1861 01:06:00,788 --> 01:06:03,524 >> EMBRYONIC STEM CELL MARKERS 1862 01:06:03,524 --> 01:06:04,759 OF -- IN SENESCENT CELLS? 1863 01:06:04,759 --> 01:06:08,029 >> I MIGHT BE WRONG. 1864 01:06:08,029 --> 01:06:10,965 IN CANCER CELLS. 1865 01:06:10,965 --> 01:06:15,103 >> ON CANCER, I CANNOT BE SURE. 1866 01:06:15,103 --> 01:06:16,871 I JUST KNOW SOMETIMES IN THE 1867 01:06:16,871 --> 01:06:18,806 CANCERS, WE OBSERVE REDUCTION IN 1868 01:06:18,806 --> 01:06:20,341 BIOLOGICAL AGE, MAYBE BECAUSE 1869 01:06:20,341 --> 01:06:23,711 CELLS DIVIDE A LOT AND THEY DO 1870 01:06:23,711 --> 01:06:25,113 DAMAGE SOMETIMES, INCREASE 1871 01:06:25,113 --> 01:06:26,547 BIOLOGICAL AGE, SO THERE'S A LOT 1872 01:06:26,547 --> 01:06:28,483 OF HETEROGENEITY IN THE CANCER. 1873 01:06:28,483 --> 01:06:30,985 BUT I HAVEN'T SEEN DATA WHICH 1874 01:06:30,985 --> 01:06:32,287 WOULD SHOW THAT SENESCENT CELLS 1875 01:06:32,287 --> 01:06:33,154 ARE YOUNGER. 1876 01:06:33,154 --> 01:06:34,589 I JUST HAVEN'T SEEN IT. 1877 01:06:34,589 --> 01:06:36,224 I'VE SEEN THAT SENESCENT CELLS 1878 01:06:36,224 --> 01:06:37,959 ARE OLDER, BUT MAYBE I MISSED 1879 01:06:37,959 --> 01:06:38,426 SOMETHING. 1880 01:06:38,426 --> 01:06:46,167 >> THANK YOU. 1881 01:06:46,167 --> 01:06:48,469 >> THANK YOU FIRST FOR A 1882 01:06:48,469 --> 01:06:49,604 FANTASTIC LECTURE. 1883 01:06:49,604 --> 01:06:51,139 OVER TIME AND NO ONE'S LEAVING. 1884 01:06:51,139 --> 01:06:53,141 APOLOGIES TO THOSE WHO WERE 1885 01:06:53,141 --> 01:06:54,342 ONLINE AND HAVE THEIR QUESTIONS 1886 01:06:54,342 --> 01:06:55,743 WITHOUT TIME, WE'LL SEE WHAT WE 1887 01:06:55,743 --> 01:06:56,611 CAN DO ABOUT IT. 1888 01:06:56,611 --> 01:06:59,113 AND JUST FOR THOSE THAT DIDN'T 1889 01:06:59,113 --> 01:07:01,416 GET THE CME CODE BEFOREHAND, 1890 01:07:01,416 --> 01:07:04,752 THERE IT IS, 57682, STILL GOOD, 1891 01:07:04,752 --> 01:07:06,821 YOU CAN ENTER IT NOW, AND YES, 1892 01:07:06,821 --> 01:07:08,456 PLEASE JOIN US UP AT STADMAN WAY 1893 01:07:08,456 --> 01:07:09,757 FOR THE RECEPTION TO FOLLOW. 1894 01:07:09,757 --> 01:07:10,291 THANKS SO MUCH. 1895 01:07:10,291 --> 01:07:10,725 GREAT TALK. 1896 01:07:10,725 --> 01:07:11,659 >> THANK YOU VERY MUCH. 1897 01:07:11,659 --> 01:07:21,836 [APPLAUSE]