1 00:00:04,771 --> 00:00:06,373 >> GOOD AFTERNOON, EVERYBODY. 2 00:00:06,439 --> 00:00:08,274 MY NAME'S CAROLYN HUTTER, I'M 3 00:00:08,341 --> 00:00:09,442 DIVISION DIRECTOR FOR THE 4 00:00:09,509 --> 00:00:12,312 DIVISION OF GENOME SCIENCES AT 5 00:00:12,379 --> 00:00:14,080 NHGRI AND I WANT TO WELCOME 6 00:00:14,147 --> 00:00:15,382 EVERYBODY TO TODAY'S WALS 7 00:00:15,448 --> 00:00:15,749 LECTURE. 8 00:00:15,815 --> 00:00:17,717 FIRST A COUPLE OF HOUSEKEEPING 9 00:00:17,784 --> 00:00:17,984 NOTES. 10 00:00:18,051 --> 00:00:22,422 I WANT TO THANK THE WALS TEAM, 11 00:00:22,489 --> 00:00:24,758 PARTICULARLY DIANEA GOMEZ FOR 12 00:00:24,824 --> 00:00:25,558 ORGANIZING TODAY. 13 00:00:25,625 --> 00:00:27,060 IF YOU DIDN'T PICK IT UP ON YOUR 14 00:00:27,127 --> 00:00:29,796 WAY IN, ON YOUR WAY OUT YOU CAN 15 00:00:29,863 --> 00:00:32,332 PICK UP HANDOUTS ABOUT UPCOMING 16 00:00:32,399 --> 00:00:33,967 WALS SPEAKERS, IT'S A VERY 17 00:00:34,033 --> 00:00:34,667 IMPRESSIVE LINE UP. 18 00:00:34,734 --> 00:00:38,405 I ALSO WANT TO THANK MY 19 00:00:38,471 --> 00:00:40,573 COLLEAGUE LISA CHAD WICK WHO 20 00:00:40,640 --> 00:00:42,742 NOMINATED DR. COX TODAY TO COME. 21 00:00:42,809 --> 00:00:44,778 LISA IS A REMOTE WORKER SO SHE'S 22 00:00:44,844 --> 00:00:46,346 WATCHING REMOTELY BUT I WANTED 23 00:00:46,413 --> 00:00:48,548 TO THANK HER FOR HER WORK IN THE 24 00:00:48,615 --> 00:00:50,850 NOMINATION AND IN ORGANIZING THE 25 00:00:50,917 --> 00:00:51,017 DAY. 26 00:00:51,084 --> 00:00:56,623 IF YOU ARE WANTING CME, THE CME 27 00:00:56,689 --> 00:00:57,223 CODE IS 50111. 28 00:00:57,290 --> 00:01:00,026 UP HERE ON THE SCREEN. 29 00:01:00,093 --> 00:01:02,028 AND FOR WHEN WE GET TO THE Q&A, 30 00:01:02,095 --> 00:01:04,931 PEOPLE IN THE ROOM, I WILL 31 00:01:04,998 --> 00:01:06,666 ENCOURAGE TO USE 1 OF THE 2 32 00:01:06,733 --> 00:01:07,967 MICs BUT WE WILL ALSO HAVE A 33 00:01:08,034 --> 00:01:10,370 LARGE NUMBER OF PEOPLE 34 00:01:10,437 --> 00:01:11,571 PARTICIPATING ONLINE TODAY, SO 35 00:01:11,638 --> 00:01:12,739 ONLINE PEOPLE TO SUBMIT A 36 00:01:12,806 --> 00:01:16,242 QUESTION FOR THE SPEAKER USE THE 37 00:01:16,309 --> 00:01:17,410 SEND LIVE FEEDBACK BUTTON THAT 38 00:01:17,477 --> 00:01:18,745 YOU WILL FIEBD ON THE VIDEOCAST 39 00:01:18,812 --> 00:01:21,347 PAGE THAT YOU ARE WATCHING THIS 40 00:01:21,414 --> 00:01:23,283 ON. 41 00:01:23,349 --> 00:01:26,386 SO IN TERMS OF INTRODUCTION, 42 00:01:26,453 --> 00:01:27,387 DR. NANCY COX, A PROFESSOR OF 43 00:01:27,454 --> 00:01:29,756 MEDICINE AND DIRECTOR OF THE 44 00:01:29,823 --> 00:01:30,723 DIVISION OF GENETIC MEDICINE 45 00:01:30,790 --> 00:01:34,060 WITHIN THE DEPARTMENT OF 46 00:01:34,127 --> 00:01:34,861 MEDICINE AT VANDERBILT 47 00:01:34,928 --> 00:01:35,829 UNIVERSITY MEDICAL CENTER, A LOT 48 00:01:35,895 --> 00:01:38,898 OF MEDICINE IN THAT TIELTS AND 49 00:01:38,965 --> 00:01:42,268 FOUNDING DIRECTOR OF THE 50 00:01:42,335 --> 00:01:43,369 VANDERBILT GENETICS INSTITUTE. 51 00:01:43,436 --> 00:01:45,104 SHE HAD TRAINING AT YALE, 52 00:01:45,171 --> 00:01:47,574 WASHINGTON UNIVERSITY, AND THE 53 00:01:47,640 --> 00:01:48,208 UNIVERSITY OF PENNSYLVANIA, 54 00:01:48,274 --> 00:01:49,476 BEFORE ANYTHING TO THE 55 00:01:49,542 --> 00:01:51,711 UNIVERSITY OF CHICAGO WHERE SHE 56 00:01:51,778 --> 00:01:53,446 WAS A DISTINGUISHED FACULTY IN 57 00:01:53,513 --> 00:01:54,781 THE BIOLOGICAL SCIENCE PS 58 00:01:54,848 --> 00:01:57,350 KIVISION, AND THEN MOVING TO 59 00:01:57,417 --> 00:01:58,084 VANNEDDER BELT IN 2015. 60 00:01:58,151 --> 00:02:00,487 SHE HAS AN ACTIVE RESEARCH 61 00:02:00,553 --> 00:02:02,422 PROGRAM FOCUSED ON INTEGRATION 62 00:02:02,489 --> 00:02:03,923 OF FUNCTIONAL GENOMIC 63 00:02:03,990 --> 00:02:05,925 INFORMATION TOA AID AND 64 00:02:05,992 --> 00:02:06,659 DISCOVERY OF AND INTERPRETATION 65 00:02:06,726 --> 00:02:14,667 OF ASSOCIATIONS AND SHE'S DONE 66 00:02:14,734 --> 00:02:18,771 BI PIONEERING PROGRAMS BAYOUS OF 67 00:02:18,838 --> 00:02:20,373 THE VANDERBILT BIOBANK VENUE. 68 00:02:20,440 --> 00:02:22,742 I COULD GO ON FOR HOURS, BUT 69 00:02:22,809 --> 00:02:25,645 WILL CALL OUT THAT SHE'S THE 70 00:02:25,712 --> 00:02:28,648 2008 RESEARCH LAND RON CANCER 71 00:02:28,715 --> 00:02:31,384 RESEARCH AWARD, LEADER IN THE 72 00:02:31,451 --> 00:02:32,986 2021 EPIDEMIOLOGY AWARD AND 73 00:02:33,052 --> 00:02:34,687 RECENTLY THE 2023 HUMAN GENETICS 74 00:02:34,754 --> 00:02:37,023 LEADERSHIP ARK WARD IN AKIGZ TO 75 00:02:37,090 --> 00:02:38,124 HER RESEARCH, I JUST PERSONALLY 76 00:02:38,191 --> 00:02:40,293 WANT TO NOTE THAT SHE HAS A VERY 77 00:02:40,360 --> 00:02:42,262 STRONG FOCUS ON TRAINING, 78 00:02:42,328 --> 00:02:43,329 MENTORING AND WORKFORCE 79 00:02:43,396 --> 00:02:45,265 DEVELOPMENT, AND SHE'S BEEN AN 80 00:02:45,331 --> 00:02:48,801 INSPIRATION TO MANY EARLY CAREER 81 00:02:48,868 --> 00:02:50,370 GENETICISTS, PARTICULARLY WOMEN, 82 00:02:50,436 --> 00:02:51,204 SEEKING INCREASING LEADERSHIP 83 00:02:51,271 --> 00:02:53,239 ROLES IN THE FIELD SHE'S 84 00:02:53,306 --> 00:02:55,441 CERTAINLY BEEN AN INSPIRATION TO 85 00:02:55,508 --> 00:02:55,842 ME. 86 00:02:55,909 --> 00:02:57,744 IN ADDITION TO THAT SHE'S HAD 87 00:02:57,810 --> 00:02:59,245 MANY ACTIVE RESEARCH AND 88 00:02:59,312 --> 00:03:02,248 ADVISORY ROLES IN GENOMIC 89 00:03:02,315 --> 00:03:03,716 CONSORTIA, THAT'S WHERE I 90 00:03:03,783 --> 00:03:05,518 CURRENTLY ISHT ACT WITH HER THE 91 00:03:05,585 --> 00:03:06,486 MOST AND THIS INCLUDES HADDER 92 00:03:06,553 --> 00:03:10,990 BEING A MEMBER OF THE N HGRI FOR 93 00:03:11,057 --> 00:03:11,925 HUMAN GENOME RESEARCH. 94 00:03:11,991 --> 00:03:14,193 SO IT'S TRULY AN HONOR TO 95 00:03:14,260 --> 00:03:16,963 WELCOME NANCY COX TO GIVE 96 00:03:17,030 --> 00:03:18,965 TODAY'S WALS LECTURE ON 97 00:03:19,032 --> 00:03:20,767 PRIORITIZING GENETICS TO REDUCE 98 00:03:20,833 --> 00:03:23,536 EXISTING HEGHT DISPARITIES. 99 00:03:23,603 --> 00:03:23,736 NANCY? 100 00:03:23,803 --> 00:03:32,312 [ APPLAUSE ] 101 00:03:32,378 --> 00:03:33,846 NTHANKS SO MUCH FOR THAT 102 00:03:33,913 --> 00:03:34,614 GENEROUS INTRODUCTION AND IT'S 103 00:03:34,681 --> 00:03:36,316 SUCH A PLEASURE TO BE HERE AT 104 00:03:36,382 --> 00:03:40,620 NIH, SUCH A STORIED PLACE FOR 105 00:03:40,687 --> 00:03:41,654 RESEARCH IN THE UNITED STATES 106 00:03:41,721 --> 00:03:44,190 AND I WAS A FREQUENT VISITOR TO 107 00:03:44,257 --> 00:03:46,059 THE CAMPUS FOR MANY, MANY YEARS 108 00:03:46,125 --> 00:03:47,460 AND WE'VE KIND OF GOTTEN AWAY 109 00:03:47,527 --> 00:03:52,098 FROM THAT OVER TIME, AND THERE'S 110 00:03:52,165 --> 00:03:54,634 A LOT MORE CAMPUS NOW, MANY OF 111 00:03:54,701 --> 00:03:58,404 OUR NIH SPONSORED MEETINGS HERE 112 00:03:58,471 --> 00:04:02,108 IN THE BETHESDA AREA AND 113 00:04:02,175 --> 00:04:04,444 SATURDAY HOTELS AND SATURDAY NIH 114 00:04:04,510 --> 00:04:05,478 BUILDINGS FURTHER OUT, IT'S NICE 115 00:04:05,545 --> 00:04:07,146 TO BE ON CAMPUS IMEAN, I WAS 116 00:04:07,213 --> 00:04:10,149 HERE FOR MANY, MANY KINDS OF 117 00:04:10,216 --> 00:04:14,787 MEETINGS OVER MANY YEARS AND 118 00:04:14,854 --> 00:04:16,756 ALSO, YOU KNOW, KNOW MANY 119 00:04:16,823 --> 00:04:17,890 INTRAMURAL SCIENTISTS HERE SO 120 00:04:17,957 --> 00:04:19,626 IT'S BEEN A REAL PLEASURE TO 121 00:04:19,692 --> 00:04:22,095 CATCH UP ON ALL THE SCIENCE 122 00:04:22,161 --> 00:04:24,364 BEING DONE HERE THAT IS SO 123 00:04:24,430 --> 00:04:25,765 IMPORTANT AND WORKT WHILE, SO 124 00:04:25,832 --> 00:04:28,167 I'M REALLY HAPPY TO BE HERE 125 00:04:28,234 --> 00:04:30,903 TALKING ABOUT THIS TOPIC WHICH 126 00:04:30,970 --> 00:04:34,974 IS TAKEN OVER MY LIFE AND SO I'M 127 00:04:35,041 --> 00:04:40,980 REALLY GOING TO TALK ABOUT HOW 128 00:04:41,047 --> 00:04:44,717 MUCH MORE HERITABILITY LAB 129 00:04:44,784 --> 00:04:47,420 VALUES USED IN EVERY DAY 130 00:04:47,487 --> 00:04:48,321 MEDICINE AND PHYSICIANS REALIZE 131 00:04:48,388 --> 00:04:51,491 AND HOW THAT HAS LED TO REALLY 132 00:04:51,557 --> 00:04:51,991 INSTITUTIONALIZED HELT 133 00:04:52,058 --> 00:04:54,927 DISPARITIES THAT CAN'T BE FIXED 134 00:04:54,994 --> 00:04:56,663 WITHOUT GENETICS. 135 00:04:56,729 --> 00:04:59,999 AND IT'S--PART OF THIS IS THAT 136 00:05:00,066 --> 00:05:01,334 BRINGING GENETICS INTO MEDICINE 137 00:05:01,401 --> 00:05:03,136 IS CREATING NEW KINDS OF HEALTH 138 00:05:03,202 --> 00:05:10,777 DISPARITIES AND WE ALL KNOW 139 00:05:10,843 --> 00:05:11,744 THAT, IT'S--IT'S--THEY'RE 140 00:05:11,811 --> 00:05:14,013 IMPORTANT NEW HEALTH DISPARITIES 141 00:05:14,080 --> 00:05:16,315 IN BOTH THE COMMON VARIANT SPACE 142 00:05:16,382 --> 00:05:17,984 WITH THINGS LIKE POLYGENIC RISK 143 00:05:18,051 --> 00:05:19,952 SCORES FOR RISK PREDICTION AND 144 00:05:20,019 --> 00:05:21,754 ALSO IN THE RARE VARIANCE SPACE 145 00:05:21,821 --> 00:05:23,589 WITH HOW MUCH HARDER IT CAN BE 146 00:05:23,656 --> 00:05:29,495 TO INTERPRET THE IME NOAMS, 147 00:05:29,562 --> 00:05:31,497 FOR--GENOMES FOR ANYONE WHOSE 148 00:05:31,564 --> 00:05:35,268 GENETIC ANCESTRIES ARE REALLY 149 00:05:35,334 --> 00:05:37,437 OUTSIDE EUROPE. 150 00:05:37,503 --> 00:05:39,706 IN CONTRAST, A LOT OF THE 151 00:05:39,772 --> 00:05:42,842 LABORATORY VALUES WE USE IN 152 00:05:42,909 --> 00:05:46,512 EVERYDAY MEDICINE ARE TRYING TO 153 00:05:46,579 --> 00:05:49,082 CAPTURE PRIMARILY DYNAMIC 154 00:05:49,148 --> 00:05:54,020 CHANGES THAT HAPPEN AS WE DEPART 155 00:05:54,087 --> 00:05:55,354 FROM HEALTHY HOMEOSTASIS, INTO 156 00:05:55,421 --> 00:06:00,626 EITHER A DISEASE STATE OR THAT 157 00:06:00,693 --> 00:06:02,128 OUR MEDICATIONS ARE DRIVING US 158 00:06:02,195 --> 00:06:03,096 IN THE WRONG WAY TO HAVE, BUT 159 00:06:03,162 --> 00:06:05,898 THE PROBLEM IS THAT THESE 160 00:06:05,965 --> 00:06:09,268 LABORATORY VALUES ARE MORE 161 00:06:09,335 --> 00:06:10,203 HERITABLE THAN PHYSICIANS 162 00:06:10,269 --> 00:06:14,941 REALIZE AND ESPECIALLY THE 1S 163 00:06:15,007 --> 00:06:18,244 THAT ARE OLD AND MORE GENERAL 164 00:06:18,311 --> 00:06:20,646 INDICATORS OF HEALTH THAN 165 00:06:20,713 --> 00:06:26,352 SPECIFIC INDICATORS OF 166 00:06:26,419 --> 00:06:28,654 PARTICULAR DISEASE. 167 00:06:28,721 --> 00:06:31,557 THE GENETICS IS OFTEN COMPLETELY 168 00:06:31,624 --> 00:06:32,225 NONPREDICTIVE OF THE OUTCOMES 169 00:06:32,291 --> 00:06:34,026 WE'RE USING THE MEASUREMENTS 170 00:06:34,093 --> 00:06:35,461 FOR, AND SO WHEN THOSE 171 00:06:35,528 --> 00:06:37,096 LABORATORY MEASUREMENTS ARE 172 00:06:37,163 --> 00:06:38,631 HIGHLY HERITABLE, AND THAT 173 00:06:38,698 --> 00:06:41,067 GENETICS IS NOT PREDICTIVE OF 174 00:06:41,134 --> 00:06:44,070 THE OUTCOMES, THE GENETICS IS 175 00:06:44,137 --> 00:06:47,373 NOT JUST MISLEADING US BUT IT'S 176 00:06:47,440 --> 00:06:49,308 CREATING A BARRIER TO THE 177 00:06:49,375 --> 00:06:52,278 DYNAMIC PART OF THE MEASUREMENT 178 00:06:52,345 --> 00:06:53,613 TELLING US THE RIGHT THINGS 179 00:06:53,679 --> 00:06:56,449 ABOUT WHERE PEOPLE ARE IN THE 180 00:06:56,516 --> 00:06:57,150 DISTRIBUTION. 181 00:06:57,216 --> 00:07:00,686 THIS MAKE ITS AN OPPORTUNITY TO 182 00:07:00,753 --> 00:07:05,191 USE GENETICS TO IMPROVE HEALTH 183 00:07:05,258 --> 00:07:09,095 AND EQUITY, BOTH, NOT BY--NOT BY 184 00:07:09,162 --> 00:07:11,264 USING THE GENETICS, TO CHANGE 185 00:07:11,330 --> 00:07:13,065 THIS PREDICTION, BY REGRESSING 186 00:07:13,132 --> 00:07:18,604 OUT THE GENETICS OF PLACES WHERE 187 00:07:18,671 --> 00:07:19,038 IT'S MISLEADING US. 188 00:07:19,105 --> 00:07:22,842 SO ALL THIS WORK WAS DONE IN THE 189 00:07:22,909 --> 00:07:24,777 CONTEXT OF THE BIOBANK OF 190 00:07:24,844 --> 00:07:27,947 VANDERBILT UNIVERSITY WHERE WE 191 00:07:28,014 --> 00:07:30,850 HAVE EHR DATA AND GOING BACK AN 192 00:07:30,917 --> 00:07:34,854 AVERAGE OF 10-15 YEARS AND MORE 193 00:07:34,921 --> 00:07:36,055 THAN 30 YEARS IN SUBSUBJECTS. 194 00:07:36,122 --> 00:07:39,392 WE HAVE MORE THAN 300,000 195 00:07:39,458 --> 00:07:41,794 SAMPLES, DNA SAMPLES IN THE 196 00:07:41,861 --> 00:07:43,863 BIOBANK MAIL, AND HAVE GENOME 197 00:07:43,930 --> 00:07:44,997 INTERROGATION ON ABOUT HALF OF 198 00:07:45,064 --> 00:07:47,900 THOSE SUBJEKS IN VARIOUS WAYS, 199 00:07:47,967 --> 00:07:50,903 GWAS, EXOHM SEQUENCING AND WHOLE 200 00:07:50,970 --> 00:07:52,972 GENOME SEQUENCING BUT NOW 201 00:07:53,039 --> 00:07:55,308 THERE'S AN ALLIANCE THAT WILL BE 202 00:07:55,374 --> 00:07:57,577 SEQUENCING THE ENTIRE BIOBANK 203 00:07:57,643 --> 00:07:59,579 AND PHARMA IS SEQUENCING THE 204 00:07:59,645 --> 00:08:00,746 ENTIRE BIOBANK WHICH WILL REALLY 205 00:08:00,813 --> 00:08:03,282 ALLOW US TO DO A BETTER 206 00:08:03,349 --> 00:08:06,552 INTEGRATION OF THE COMMON AND 207 00:08:06,619 --> 00:08:09,622 RARE VARIANT SPACE BUT WE'VE 208 00:08:09,689 --> 00:08:13,226 ALWAYS ALSO USED THE GENOME 209 00:08:13,292 --> 00:08:18,431 VARIATION TO IMPUTE OTHER OMICS 210 00:08:18,497 --> 00:08:20,867 INTO THE DATA. 211 00:08:20,933 --> 00:08:23,202 I THOUGHT 10 YEARS AGO, AS WE 212 00:08:23,269 --> 00:08:27,206 WERE DOING MORE MULTIOMICS 213 00:08:27,273 --> 00:08:28,741 STUDIES, AND THESE--THESE ARE 214 00:08:28,808 --> 00:08:29,909 BIOMARKERS THAT ARE SO RICH, 215 00:08:29,976 --> 00:08:32,445 THAT ALL OF THE MULTIOMICS DATA 216 00:08:32,511 --> 00:08:34,780 IS VERY, VERY RICH FOR 217 00:08:34,847 --> 00:08:37,250 PREDICTING FUTURE HEALTH STATUS. 218 00:08:37,316 --> 00:08:42,655 THOSE THINGS WILL MAKE THEIR WAY 219 00:08:42,722 --> 00:08:47,293 INTO MEDICINE AS BIOMARKERS THAT 220 00:08:47,360 --> 00:08:49,362 WE WOULD USE COMMONLY IN 221 00:08:49,428 --> 00:08:52,064 THINKING ABOUT HEALTH AND 222 00:08:52,131 --> 00:08:53,466 DISEASE BUT EVERYTHING CHANGES 223 00:08:53,532 --> 00:08:59,205 VERY SLOWLY IN MEDICINE AND FOR 224 00:08:59,272 --> 00:08:59,805 SURE, TRANSCRIPT ORDER OF 225 00:08:59,872 --> 00:09:01,774 MICRONSS, METRICS TAB O LOAMS, 226 00:09:01,841 --> 00:09:03,976 PROTEOMES ARE NOT NEARLY AS 227 00:09:04,043 --> 00:09:05,611 HARDENED IN TERMS OF INTER 228 00:09:05,678 --> 00:09:08,915 IMAIGZ AS GENOMES HAVE BEEN AND 229 00:09:08,981 --> 00:09:10,416 WE MEDE--WE NEED TO MOVE IN THAT 230 00:09:10,483 --> 00:09:12,985 DIRECTION IN ORDER TO BE EVEN 231 00:09:13,052 --> 00:09:20,726 THINKING ABOUT USING THESE IN A 232 00:09:20,793 --> 00:09:21,861 CLINICAL CONTEXT. 233 00:09:21,928 --> 00:09:23,963 BUT THE BIOMARKERS THAT WE USE 234 00:09:24,030 --> 00:09:27,500 VERY ROUTINELY ARE OFTEN TELLING 235 00:09:27,566 --> 00:09:30,670 US MUCH, MUCH MORE ABOUT VERY 236 00:09:30,736 --> 00:09:32,538 LATE STAGE DEPARTURES FROM 237 00:09:32,605 --> 00:09:34,273 HEALTHY HOMEOSTASIS AND I THINK 238 00:09:34,340 --> 00:09:37,643 THE OPPORTUNITY MORE OF THE 239 00:09:37,710 --> 00:09:42,014 OMICS MEASURES IS TO BE CATCHING 240 00:09:42,081 --> 00:09:43,616 DEPARTURES FROM HEALTHY 241 00:09:43,683 --> 00:09:45,518 HOMEOSTASIS POTENTIALLY MUCH 242 00:09:45,584 --> 00:09:45,751 EARLIER. 243 00:09:45,818 --> 00:09:47,420 ONE OF THE THINGS I HADN'T 244 00:09:47,486 --> 00:09:49,021 APPRECIATED TILL I GOT TO 245 00:09:49,088 --> 00:09:50,289 VANDERBILT IS THAT WHILE THE 246 00:09:50,356 --> 00:09:53,492 PART OF THIS, THAT HAS THE 247 00:09:53,559 --> 00:09:56,929 GENOMIC INTERROGATION IS A 248 00:09:56,996 --> 00:09:57,596 FANTASTIC RESOURCE. 249 00:09:57,663 --> 00:10:02,201 THE PART THAT DOES HAVE ANYTIME 250 00:10:02,268 --> 00:10:02,735 GENOMIC INTERROGATION, THE 251 00:10:02,802 --> 00:10:05,338 2.8 MILLION OTHER PEOPLE WITH 252 00:10:05,404 --> 00:10:07,707 JUST 15-30 YEARS OF ELECTRONIC 253 00:10:07,773 --> 00:10:09,976 HEALTH RECORDS DATA IS A 254 00:10:10,042 --> 00:10:11,043 FANTASTIC ARK DITIONAL RESOURCE 255 00:10:11,110 --> 00:10:15,147 FOR ENRICHING WHAT WE LEARNED 256 00:10:15,214 --> 00:10:16,849 FROM THE GENETICS BUT ALSO FOR A 257 00:10:16,916 --> 00:10:18,417 BIG SAMPLE THAT CAN LEAD TO 258 00:10:18,484 --> 00:10:20,586 DISCOVERIES THAT WE ARE ABLE TO 259 00:10:20,653 --> 00:10:23,222 TAKE INTO GENETICS TO VALIDATE 260 00:10:23,289 --> 00:10:28,861 AND I THINK AS WE THINK MORE 261 00:10:28,928 --> 00:10:31,130 ABOUT USING GENETICS TO DO 262 00:10:31,197 --> 00:10:36,202 TARGET DEVELOPMENT FOR BETTER 263 00:10:36,268 --> 00:10:39,038 THERAPEUTICS, THE OTHER THINGS 264 00:10:39,105 --> 00:10:41,807 WE CAN DO WITH DATA LIKE THIS 265 00:10:41,874 --> 00:10:50,649 ARE THINKING ABOUT THE MRI O 266 00:10:50,716 --> 00:10:52,284 TROAPIC EFFECTS OF GENETIC 267 00:10:52,351 --> 00:10:54,286 FACTORS EARLIER IN LIFE, SO THAT 268 00:10:54,353 --> 00:10:56,889 WE USE BIOLOGICAL INFORMATION TO 269 00:10:56,956 --> 00:10:58,257 THINK ABOUT SURROGATE END POINTS 270 00:10:58,324 --> 00:10:59,992 THAT ARE NOT ALZHEIMERS BECAUSE 271 00:11:00,059 --> 00:11:01,861 IT'S SO LATE IN ONSET, BUT ABOUT 272 00:11:01,927 --> 00:11:04,363 SOME OF THE OTHER BIOLOGY DRIVEN 273 00:11:04,430 --> 00:11:07,566 BY THE SAME GENETIC FACTORS THAT 274 00:11:07,633 --> 00:11:10,870 ARE DRIVING AT LEAST PIECES OF 275 00:11:10,936 --> 00:11:11,637 THE ALZHEIMER'S GENETIC PUZZLE 276 00:11:11,704 --> 00:11:14,473 AND I THINK AS WE LEARN MORE AND 277 00:11:14,540 --> 00:11:17,743 MORE, THINK ABOUT THE BIG 278 00:11:17,810 --> 00:11:20,579 CONTRIBUTION THAT BIOLOGY 279 00:11:20,646 --> 00:11:21,847 ATTRIBUTABLE TO MICROGLIA WHICH 280 00:11:21,914 --> 00:11:29,355 ARE JUST MACROFAJS MIGHT BE 281 00:11:29,422 --> 00:11:30,523 TELLING US ABOUT MUCH EARLIER IN 282 00:11:30,589 --> 00:11:33,125 THE LIFE SPAN THAT WE COULD 283 00:11:33,192 --> 00:11:41,434 PROFITABLY USE IN THINKING ABOUT 284 00:11:41,500 --> 00:11:43,135 CLEVER DRUG DESIGNS TO WAIT 285 00:11:43,202 --> 00:11:44,370 UNTIL PEOPLE HAVE COGNITIVE 286 00:11:44,437 --> 00:11:46,539 DECLINE TO BE THINKING ABOUT 287 00:11:46,605 --> 00:11:47,873 THERAPY RATHER LOOKING AT THE 288 00:11:47,940 --> 00:11:50,476 SORT OF SAME KINDS OF FAILURES 289 00:11:50,543 --> 00:11:53,379 IN OTHER CLASSES OF MACROFAJS 290 00:11:53,446 --> 00:12:00,486 THAT MAY BE MANIFESTING EARLIER. 291 00:12:00,553 --> 00:12:02,755 BUT EVERYBODY FULLY UNDERSTANDS 292 00:12:02,822 --> 00:12:03,589 THAT INTRODUCING GENOMES INTO 293 00:12:03,656 --> 00:12:04,757 MEDICINE HAS LED AND IS 294 00:12:04,824 --> 00:12:06,625 CONTINUING TO LEAD TO NEW KINDS 295 00:12:06,692 --> 00:12:08,661 OF HEALTH DISPARITIES AND PART 296 00:12:08,727 --> 00:12:11,897 OF IT IS TOTALLY NOT IN OUR 297 00:12:11,964 --> 00:12:14,166 CONTROL EXCEPT AS CITIZEN TO DO 298 00:12:14,233 --> 00:12:17,236 ANYTHING ABOUT, THIS JUST SHOWS 299 00:12:17,303 --> 00:12:18,971 THE INCREASE IN INCOME AND 300 00:12:19,038 --> 00:12:24,276 EQUALITY IN THE U.S. IN FROM 301 00:12:24,343 --> 00:12:26,679 1967 TO 2014. 302 00:12:26,745 --> 00:12:29,915 AND THESE TRAJECTORIES GOT WORSE 303 00:12:29,982 --> 00:12:31,917 AND IT WAS REALLY ONLY OVER 304 00:12:31,984 --> 00:12:35,054 COVID WITH A DECREASE IN INEQUAT 305 00:12:35,121 --> 00:12:35,988 TO REFLECT INVESTMENTS THAT WERE 306 00:12:36,055 --> 00:12:37,723 MADE TO TRY TO KEEP PEOPLE 307 00:12:37,790 --> 00:12:39,325 HEALTHY AND SAFE DURING THE 308 00:12:39,391 --> 00:12:42,862 MIDST OF THE COVID OUTBREAKS. 309 00:12:42,928 --> 00:12:45,865 THAT INEQUALITY OF ACCESS IS 310 00:12:45,931 --> 00:12:51,403 THEN COUPLED TO HISTORICAL 311 00:12:51,470 --> 00:12:56,342 FAILURES TO HAVE THE RIGHT DATA 312 00:12:56,408 --> 00:12:58,410 FROM DIVERSE POPULATIONS TO 313 00:12:58,477 --> 00:13:03,382 INVEST IN WITH GENETIC STUDIES. 314 00:13:03,449 --> 00:13:06,051 IT MAKES SENSE TO USE CATATHAT 315 00:13:06,118 --> 00:13:09,021 ARE VERY RICH AND HAVE A LONG 316 00:13:09,088 --> 00:13:13,826 HISTORY OF INFORMATION, CLINICAL 317 00:13:13,893 --> 00:13:15,227 INFORMATION, AND MEDICATION 318 00:13:15,294 --> 00:13:17,229 INFORMATION TO USE IN INVESTING 319 00:13:17,296 --> 00:13:20,799 IN THE FIRST GENETIC STUDIES BUT 320 00:13:20,866 --> 00:13:22,768 BECAUSE THOSE STUDIES HAD MUCH 321 00:13:22,835 --> 00:13:24,537 LESS DIVERSE DATA, LESS DIVERSE 322 00:13:24,603 --> 00:13:26,605 WITH RESPECT TO REPRESENTATION 323 00:13:26,672 --> 00:13:29,141 BY GENDER, LESS DIVERSE WITH 324 00:13:29,208 --> 00:13:30,576 RESPECT TO REPRESENTATION OF THE 325 00:13:30,643 --> 00:13:36,649 DIVERSITY OF THE HUMAN 326 00:13:36,715 --> 00:13:39,652 POPULATION THAT WE--WE HAVE 327 00:13:39,718 --> 00:13:40,719 SUBSTANTIALLY OVERSAMPLED 328 00:13:40,786 --> 00:13:41,420 EUROPEAN GENOMES RELATIVE TO 329 00:13:41,487 --> 00:13:44,490 GENOMES IN THE REST OF THE WORLD 330 00:13:44,557 --> 00:13:47,326 AND THE PROBLEM IS THE VERY 331 00:13:47,393 --> 00:13:48,661 SUCCESS OF THE SCIENCE IN 332 00:13:48,727 --> 00:13:53,732 LEADING TO DISCOVERIES THAT HAVE 333 00:13:53,799 --> 00:13:57,102 SOME GOOD OPPORTUNITIES FOR 334 00:13:57,169 --> 00:13:58,170 CLINICAL TRANSLATION, MEANS THAT 335 00:13:58,237 --> 00:14:03,576 POPULATIONS THAT CAN AFFORD TO 336 00:14:03,642 --> 00:14:04,643 HAVE MORE GENETIC INFORMATION 337 00:14:04,710 --> 00:14:08,280 USED IN OUR HEALTHCARE CONTINUE 338 00:14:08,347 --> 00:14:08,881 TO DO THAT. 339 00:14:08,948 --> 00:14:11,116 SO EVEN THOUGH WE ARE NOW 340 00:14:11,183 --> 00:14:12,885 COLLECTING MUCH MORE IMENETTIC 341 00:14:12,952 --> 00:14:15,154 DATA ON DIVERSE POPULATIONS THAN 342 00:14:15,221 --> 00:14:17,957 WE EVER HAVE IT'S ACCUMULATING 343 00:14:18,023 --> 00:14:22,428 FASTER, IT'S AN IMPRESSIVE WORLD 344 00:14:22,494 --> 00:14:23,262 WIDE EFFORT. 345 00:14:23,329 --> 00:14:24,296 WE ARE STILL ACCUMULATING 346 00:14:24,363 --> 00:14:28,567 INFORMATION ON THE GENOMES OF 347 00:14:28,634 --> 00:14:29,268 EUROPEANS EVEN FASTER. 348 00:14:29,335 --> 00:14:32,905 I DON'T SEE A WAY TO CATCH UP 349 00:14:32,972 --> 00:14:35,174 UNTIL EVERYBODY HAS GENOMES DONE 350 00:14:35,241 --> 00:14:35,874 ROUTINELY FOR HEALTHCARE. 351 00:14:35,941 --> 00:14:37,810 I REALLY DON'T THINK WE WILL 352 00:14:37,876 --> 00:14:40,546 CATCH UP IN TERMS OF THE 353 00:14:40,613 --> 00:14:44,450 REPRESENTATION OF WORLD 354 00:14:44,516 --> 00:14:45,517 POPULATIONS IN INTERROGATED 355 00:14:45,584 --> 00:14:49,088 GENOMES UNTIL THAT HAPPENS 356 00:14:49,154 --> 00:14:52,291 BECAUSE EVEN WORLD WIDE, THERE 357 00:14:52,358 --> 00:14:53,892 IS--THERE IS INEQUALITY OF 358 00:14:53,959 --> 00:14:58,264 ACCESS TO INFORMATION AND 359 00:14:58,330 --> 00:14:59,531 INEQUALITY IN THE ABILITY TO 360 00:14:59,598 --> 00:15:02,067 INVEST IN THE RESEARCH 361 00:15:02,134 --> 00:15:04,103 ENTERPRISES TO CREATE ALL THE 362 00:15:04,169 --> 00:15:10,209 DATA THAT WOULD REALLY HAVE 363 00:15:10,276 --> 00:15:11,877 VALUE FOR INTERPRETING. 364 00:15:11,944 --> 00:15:15,047 SO WE KNOW THAT WE CAN'T MOVE 365 00:15:15,114 --> 00:15:16,749 FORWARD WITHOUT CREATING NEW 366 00:15:16,815 --> 00:15:19,084 KINDS OF HEALTH DISPARITIES, AND 367 00:15:19,151 --> 00:15:23,155 SO THIS MAKES THE CASE EVEN NOW 368 00:15:23,222 --> 00:15:25,491 THAT IN NOF 1 STUDIES IN 369 00:15:25,557 --> 00:15:27,126 CHILDREN AND ADULTS FROM DIVERSE 370 00:15:27,192 --> 00:15:29,328 POPULATIONS WERE LESS LIKELY TO 371 00:15:29,395 --> 00:15:30,929 GET AN UNEQUIVOCAL SOLVE, WERE 372 00:15:30,996 --> 00:15:32,164 MORE LIKELY TO BE DEALING WITH 373 00:15:32,231 --> 00:15:35,834 VALID AND RELIABLE YABTS OF 374 00:15:35,901 --> 00:15:36,869 UNKNOWN SIGNIFICANCE AND THAT 375 00:15:36,935 --> 00:15:43,008 WOULD BE THE CASE FOR SOMETIME 376 00:15:43,075 --> 00:15:43,275 YET. 377 00:15:43,342 --> 00:15:52,217 AND THIS IS NOT--THIS IS A WORLD 378 00:15:52,284 --> 00:15:53,852 WIDE PROBLEM AND WE--I MEAN 379 00:15:53,919 --> 00:15:55,621 EVERYBODY IS TRYING TO INVEST IN 380 00:15:55,688 --> 00:16:02,094 WAY TAC IMPROVE THOSE OUTCOMES 381 00:16:02,161 --> 00:16:04,229 BUT IT WILL TAKE TIME AND IT 382 00:16:04,296 --> 00:16:08,000 WILL BE HARD TO CATCH UP WITH 383 00:16:08,067 --> 00:16:09,034 THE QUALITY OF INFORMATION. 384 00:16:09,101 --> 00:16:12,037 IN THE COMMON VARIANT SPACE, 385 00:16:12,104 --> 00:16:13,339 POLYGENIC RISK SCORES ARE BEING 386 00:16:13,405 --> 00:16:14,707 DELIVERED TO DIVERSE POPULATIONS 387 00:16:14,773 --> 00:16:18,477 EVEN NOW, BUT THE TRUTH IS WHAT 388 00:16:18,544 --> 00:16:20,679 WE NEED TO LEARN FROM POLYGENIC 389 00:16:20,746 --> 00:16:24,416 RISK SCORES WHAT WE HAVE ANY 390 00:16:24,483 --> 00:16:26,118 OPPORTUNITY TO DELIVER INVOLVES 391 00:16:26,185 --> 00:16:29,421 A LOT OF TAIL PROPERTIES, LIKE 392 00:16:29,488 --> 00:16:34,960 MOST OF WHAT IS HAPPENING IN THE 393 00:16:35,027 --> 00:16:35,928 MITSD OF THIS DISTRIBUTION 394 00:16:35,994 --> 00:16:39,398 DOESN'T MATTER FOR UNDERSTANDING 395 00:16:39,465 --> 00:16:40,866 RISK, YOU'RE AT THE SAME GENERAL 396 00:16:40,933 --> 00:16:42,301 RISK AS THE GENERAL POPULATION. 397 00:16:42,368 --> 00:16:46,605 WHAT WE GENERALLY TRY TO DELIVER 398 00:16:46,672 --> 00:16:47,973 IS MORE INFORMATION FROM THE 399 00:16:48,040 --> 00:16:50,743 TAILS AND IT CAN BE WILL HIGH 400 00:16:50,809 --> 00:16:52,678 TALES OF RISK, WE NEED TO 401 00:16:52,745 --> 00:16:55,314 UNDERSTAND LOW RISK AS WELL, 402 00:16:55,381 --> 00:16:57,049 ESPECIALLY AS WE'RE ABLE TO 403 00:16:57,116 --> 00:16:58,317 BETTER COMBINE RARE AND COMMON 404 00:16:58,384 --> 00:17:02,121 VARIANTS IN A WAY THAT REALLY 405 00:17:02,187 --> 00:17:03,756 HELPS DEFINE ACCURATELY, LARGE 406 00:17:03,822 --> 00:17:07,960 SCALE GENETIC RISK TO DISEASE 407 00:17:08,026 --> 00:17:10,796 BUT TAIL PROPERTIES OF NORMAL 408 00:17:10,863 --> 00:17:12,431 DISTRIBUTIONS ARE THE LEAST 409 00:17:12,498 --> 00:17:18,237 TABLE PART, RIGHT? 410 00:17:18,303 --> 00:17:20,105 AND DIFFERENT WAYS OF 411 00:17:20,172 --> 00:17:21,039 CALCULATING POLYGENIC RISK 412 00:17:21,106 --> 00:17:22,941 SCORES HAVE THE MOST IMPACT IN 413 00:17:23,008 --> 00:17:24,576 THE TALES OF DISTRIBUTION. 414 00:17:24,643 --> 00:17:25,878 SO SMALL VARIATIONS IN HOW 415 00:17:25,944 --> 00:17:27,546 CALCULATIONS ARE DONE IN THE 416 00:17:27,613 --> 00:17:29,314 POPULATIONS IN WHICH THESE 417 00:17:29,381 --> 00:17:31,450 PREDICTIVE MODELS ARE TRAINED 418 00:17:31,517 --> 00:17:36,622 HAVE A BIG IMPACT IN WHO ENDS UP 419 00:17:36,688 --> 00:17:38,490 IN THE TALE THAT GETS NFGZ THAT 420 00:17:38,557 --> 00:17:41,460 THEY'RE AT HIGH RISK. 421 00:17:41,527 --> 00:17:52,037 THAT'S NOT ATTRACTIVE FROM THE 422 00:17:52,771 --> 00:17:54,807 STATISTICAL PERSPECTIVE BUT BOTH 423 00:17:54,873 --> 00:17:56,341 OUR METHODS FOR CALCULATING THE 424 00:17:56,408 --> 00:17:57,409 TRAINING OF THESE RISK SCORE 425 00:17:57,476 --> 00:18:03,949 PREDICS ABOUT YOU ALSO THE 426 00:18:04,016 --> 00:18:04,783 APPLICATION IGNORES THE REALITY 427 00:18:04,850 --> 00:18:09,121 THAT ABOUT HALF OF THE U.S. 428 00:18:09,188 --> 00:18:09,688 POPULATION IS 429 00:18:09,755 --> 00:18:11,156 CONTINENTALLYAD-MIXED IN RECENT 430 00:18:11,223 --> 00:18:13,025 GENERATION ANDS THAT THAT'S THE 431 00:18:13,091 --> 00:18:16,128 FASTEST GROWING PART OF OUR 432 00:18:16,195 --> 00:18:19,198 POPULATION, ALL OF WHICH IS 433 00:18:19,264 --> 00:18:24,336 IGNORED AT SOME RISK OF FAILING 434 00:18:24,403 --> 00:18:27,873 TO CAPTURE IMPORTANT ASPECTS OF 435 00:18:27,940 --> 00:18:31,510 POPULATION LEVEL RISK FULLY 436 00:18:31,577 --> 00:18:41,887 ACCURATELY. 437 00:18:41,954 --> 00:18:44,323 AND SO, WE LOOK AT THOSE THAT 438 00:18:44,389 --> 00:18:45,724 DEAL WITH THE LEVEL OF 439 00:18:45,791 --> 00:18:47,025 COMPLEXITY THAT WE NEED TO DEAL 440 00:18:47,092 --> 00:18:48,126 WITH IN TREATING POPULATIONS IN 441 00:18:48,193 --> 00:18:50,329 THE U.S. AND DELIVERYING 442 00:18:50,395 --> 00:18:52,064 IMENETTIC DATA TO POPULATIONS IN 443 00:18:52,130 --> 00:18:54,900 THE U.S., IS GOING TO HAUNT US 444 00:18:54,967 --> 00:18:58,637 FOR SOMETIME. 445 00:18:58,704 --> 00:19:00,138 WE NEED TO IMPROVE METHODS THAT 446 00:19:00,205 --> 00:19:03,642 ARE ALREADY BEING USED TO 447 00:19:03,709 --> 00:19:06,712 DELIVER RESULTS TO OUR 448 00:19:06,778 --> 00:19:08,313 POPULATIONS AND SO WE CAN HARDLY 449 00:19:08,380 --> 00:19:15,020 DO THIS FAST ENOUGH BECAUSE IT'S 450 00:19:15,087 --> 00:19:15,420 ALREADY HAPPENING. 451 00:19:15,487 --> 00:19:22,995 SO WE KNOW BY TRANSLATING 452 00:19:23,061 --> 00:19:23,896 GENOMIC DISCOVERIES, BUT WE HAVE 453 00:19:23,962 --> 00:19:27,766 AN OPPORTUNITY IN THE LAB TO 454 00:19:27,833 --> 00:19:30,202 SPACE THAT USE GENETICS IN A WAY 455 00:19:30,269 --> 00:19:32,004 THAT WILL IMPROVE HEALTH AND 456 00:19:32,070 --> 00:19:33,138 IMPROVE HEALTH EQUITY. 457 00:19:33,205 --> 00:19:39,411 AND WE USE LABORATORY TESTS 458 00:19:39,478 --> 00:19:40,579 EVERY DAY IN MEDICINE AND THE 459 00:19:40,646 --> 00:19:44,550 FAILURE TO HAVE FULLY 460 00:19:44,616 --> 00:19:46,151 APPRECIATED HOW DIVERSE HUMAN 461 00:19:46,218 --> 00:19:51,223 POPULATIONS ARE IN THESE 462 00:19:51,290 --> 00:19:52,157 MEASUREMENTS HAS CREATED A 463 00:19:52,224 --> 00:19:55,027 NUMBER OF REALLY IMPORTANT 464 00:19:55,093 --> 00:19:55,861 INSTITUTIONAL DISPARITIES WITHIN 465 00:19:55,928 --> 00:19:56,562 MEDICAL CENTERS WHICH REALLY 466 00:19:56,628 --> 00:20:03,201 HAVE TO BE ADDRESSED. 467 00:20:03,268 --> 00:20:07,606 SO IN OUR CENTER IN VANDERBILT 468 00:20:07,673 --> 00:20:11,443 GENETICS INNS TUITION, LEA DAVIS 469 00:20:11,510 --> 00:20:13,545 LED THE EFFORTS TO CLEAN THE 470 00:20:13,612 --> 00:20:14,813 LABORATORY VALUES IN A WAY THAT 471 00:20:14,880 --> 00:20:17,015 IT COULD BE SHOWN THAT WE WERE 472 00:20:17,082 --> 00:20:18,650 GETTING ESTIMATING WITH SAME 473 00:20:18,717 --> 00:20:20,185 LEVELS OF HERITABILITY, GETTING 474 00:20:20,252 --> 00:20:22,387 THE SAME GWAS SIGNALS AS STUDIES 475 00:20:22,454 --> 00:20:24,122 DONE ON THOSE LABORATORY 476 00:20:24,189 --> 00:20:29,127 MEASURES IN A RESEARCH CONTEXT. 477 00:20:29,194 --> 00:20:31,997 THE REASON IT TAKES SO LONG AND 478 00:20:32,064 --> 00:20:33,298 IT'S HARD TO CLAIM THESE VALUES 479 00:20:33,365 --> 00:20:35,834 IS THAT OVER TIME WE ANY TO 480 00:20:35,901 --> 00:20:37,402 DIFFERENT VENDORS FOR GETTING 481 00:20:37,469 --> 00:20:38,337 LABORATORY TESTS RUN, OVER TIME 482 00:20:38,403 --> 00:20:40,839 THEY CHANGE THE UNITS IN WHICH 483 00:20:40,906 --> 00:20:44,076 LABORATORY VALUES GET REPORTED, 484 00:20:44,142 --> 00:20:49,715 THERE'S MASSIVE BATCH EFFECTS 485 00:20:49,781 --> 00:20:51,116 THAT CAN VERY BY PLACES WHERE 486 00:20:51,183 --> 00:20:52,351 THE TESTS GET RUN AND ALL OF 487 00:20:52,417 --> 00:20:54,786 THAT, YOU KNOW YOU WANT TO TRY 488 00:20:54,853 --> 00:20:57,756 TO STANDARDIZE THAT WE CAPTURE 489 00:20:57,823 --> 00:21:00,158 THE ESSENCE OF GENETICS THAT ARE 490 00:21:00,225 --> 00:21:01,593 REALLY UNDERLYING THESE BY O 491 00:21:01,660 --> 00:21:04,630 MARKERS BUT THEY SUCK 492 00:21:04,696 --> 00:21:05,397 SEDENTARIED--SUCCEEDED IN THAT 493 00:21:05,464 --> 00:21:06,732 AND YOU COULD SHOW THAT AT THE 494 00:21:06,798 --> 00:21:08,367 END OF THIS PROCESS AND THAT 495 00:21:08,433 --> 00:21:09,801 THEY PUBLISHED AND CREATE THIS 496 00:21:09,868 --> 00:21:12,304 PIPELINE THAT'S USED BY LOTS OF 497 00:21:12,371 --> 00:21:14,873 MEDICAL CENTERS NOW TO CLEAN AND 498 00:21:14,940 --> 00:21:16,274 STANDARDIZE THEIR LABORATORY 499 00:21:16,341 --> 00:21:18,110 VALUES FOR FURTHER GENETIC 500 00:21:18,176 --> 00:21:25,150 STUDIES BUT YOU DO--YOU CAN GET 501 00:21:25,217 --> 00:21:26,918 THE SAME ESTIMATES OF GWAS 502 00:21:26,985 --> 00:21:27,386 SIGNALS. 503 00:21:27,452 --> 00:21:30,522 WE ARE CAPTURING THE HEART OF 504 00:21:30,589 --> 00:21:33,859 THE POLYGENIC ARCHITECTURE OF 505 00:21:33,925 --> 00:21:34,826 LABORATORY VALUES IN THE 506 00:21:34,893 --> 00:21:37,562 HOSPITAL SETTING IN THIS 507 00:21:37,629 --> 00:21:39,498 CLINICAL SETTING. 508 00:21:39,564 --> 00:21:41,233 SO WHAT PROPORTION OF THE THAT 509 00:21:41,299 --> 00:21:42,167 PHYSICIANS ORDER AND INTERPRET 510 00:21:42,234 --> 00:21:44,970 ON AT LEAST A MONTHLY BASIS AND 511 00:21:45,037 --> 00:21:46,538 WE MIGHT SAY EVEN THAT WE HAVE 512 00:21:46,605 --> 00:21:48,640 DAT ON AT LEAST A THOUSAND 513 00:21:48,707 --> 00:21:50,542 PEOPLE IN OUR BIOBANK FOR WHAT 514 00:21:50,609 --> 00:21:54,379 PROPORTION OF THOSE LAB VALUES 515 00:21:54,446 --> 00:22:02,220 DO YOU THINK ARE 10% HERITABLE? 516 00:22:02,287 --> 00:22:05,857 I ASK THESE QUESTIONS. 517 00:22:05,924 --> 00:22:07,526 SO IF I ASK OR EVEN WHAT 518 00:22:07,592 --> 00:22:09,961 PROPORTION OF LAB VALUES WOULD 519 00:22:10,028 --> 00:22:11,129 BE SIGNIFICANTLY HERITABLE IN 520 00:22:11,196 --> 00:22:13,765 THAT CONTEXT, IN A GROUP OF 521 00:22:13,832 --> 00:22:14,966 PHYSICIANS IN A GRAND ROUNDS, 522 00:22:15,033 --> 00:22:18,170 YOU KNOW IF I SAY HOW MANY 523 00:22:18,236 --> 00:22:20,505 PEOPLE SAY 10% OF LABS YOU ORDER 524 00:22:20,572 --> 00:22:21,673 WOULD BE SIGNIFICANTLY 525 00:22:21,740 --> 00:22:22,908 HERITABLE, A LOT OF PHYSICIANS 526 00:22:22,974 --> 00:22:24,743 WILL RAISE THEIR HAND AND 20% 527 00:22:24,810 --> 00:22:26,278 AND HALF THE HANDS GO DOWN, AND 528 00:22:26,344 --> 00:22:29,481 30% AND THEY'LL SAY, YEAH, IF MY 529 00:22:29,548 --> 00:22:31,116 HUSBAND'S IN THE AUDIENCE, HE'S 530 00:22:31,183 --> 00:22:35,053 THE ONLY 1 STILL RAISING HIS 531 00:22:35,120 --> 00:22:36,922 HAND BECAUSE HE WERES I'M A 532 00:22:36,988 --> 00:22:38,757 GENETICIST AND I WOULDN'T BE 533 00:22:38,824 --> 00:22:40,625 ASKING OTHERWISE, BUT IT'S 534 00:22:40,692 --> 00:22:42,394 2/3RDS OF LABORATORY VALUES 535 00:22:42,461 --> 00:22:43,862 TAKEN--THEY HAVE--THAT WE HAVE 536 00:22:43,929 --> 00:22:45,197 THAT MEAN PEOPLE ON THAT ARE 537 00:22:45,263 --> 00:22:47,065 ORDERED AT LEAST ONCE A MONTH 538 00:22:47,132 --> 00:22:51,937 ARE SIGNIFICANT LE HERITABLE IN 539 00:22:52,003 --> 00:22:54,806 THE EHR, A SUBSTANDIAL FRACTION 540 00:22:54,873 --> 00:22:56,942 OF THOSE, BETWEEN 30-40% OF 541 00:22:57,008 --> 00:22:58,677 LABORATORY VALUES ARE 542 00:22:58,744 --> 00:23:01,313 SIGNIFICANTLY HERITABLE, HAVE 543 00:23:01,379 --> 00:23:02,481 HERITABILITYS IN EXCESS OF 40% 544 00:23:02,547 --> 00:23:10,555 AND UP INTO THE 80, 90% RANGE. 545 00:23:10,622 --> 00:23:11,857 SO IS THIS A PROBLEM BECAUSE 546 00:23:11,923 --> 00:23:13,592 PHYSICIANS THINK OF THEM AS 547 00:23:13,658 --> 00:23:14,459 DYNAMIC MEASURES OF DISEASE, 548 00:23:14,526 --> 00:23:19,498 RISK AND PROGRESS AND THAT'S HOW 549 00:23:19,564 --> 00:23:22,067 THEY ARE USED AS PRIMARILY 550 00:23:22,134 --> 00:23:23,335 DYNAMIC MEASURES OF WHAT'S 551 00:23:23,401 --> 00:23:27,906 HAPPENING RIGHT NOW, IN THIS 552 00:23:27,973 --> 00:23:31,877 SYSTEM AND THE GENETIC SYSTEM 553 00:23:31,943 --> 00:23:32,110 STATIC. 554 00:23:32,177 --> 00:23:37,716 THE GENETICS IS HOLDING, 555 00:23:37,783 --> 00:23:39,518 ANCHORING PEOPLE AT SOME PART OF 556 00:23:39,584 --> 00:23:40,352 THAT DISTRIBUTION, TRYING AS 557 00:23:40,418 --> 00:23:45,223 HARD AS POSSIBLE TO KEEP THEM 558 00:23:45,290 --> 00:23:47,058 THERE, AND THAT'S WHERE IT'S 559 00:23:47,125 --> 00:23:50,562 ACTUALLY A DRUG --DRAG ON THE 560 00:23:50,629 --> 00:23:52,130 DYNAMIC PART OF THESE MEASURES. 561 00:23:52,197 --> 00:23:53,598 CERTAINLY THERE COULD BE SOME 562 00:23:53,665 --> 00:23:56,134 POSSIBILITY THAT ANY GENE BY 563 00:23:56,201 --> 00:23:56,701 ENVIRONMENT INTERACTION, ANY 564 00:23:56,768 --> 00:23:57,936 EXPOSURES THAT ARE CHANGING 565 00:23:58,003 --> 00:23:59,571 THESE VALUES COULD BE 566 00:23:59,638 --> 00:24:00,739 INTERACTING WITH THE GENETICS 567 00:24:00,806 --> 00:24:02,941 BUT FOR THE MOST PART THE 568 00:24:03,008 --> 00:24:07,212 GENETICS ARE STATIC AND 569 00:24:07,279 --> 00:24:08,947 THAT--BECAUSE THEY'RE MUCH MORE 570 00:24:09,014 --> 00:24:10,015 GENETIC THAN PHYSICIANS ARE 571 00:24:10,081 --> 00:24:14,319 OFTEN GIVING THEM CREDIT FOR, 572 00:24:14,386 --> 00:24:17,455 THAT MEANS THAT FIRST TIME 573 00:24:17,522 --> 00:24:19,191 SOMEBODY ORDERS A CREATINE THAT 574 00:24:19,257 --> 00:24:21,259 LOOKS LIKE IT'S PUTTING PEOPLE 575 00:24:21,326 --> 00:24:27,232 INTO TAIJ 2 KIDNEY DISEASE 576 00:24:27,299 --> 00:24:28,166 THEY'RE JUST WATCHING TO SEE 577 00:24:28,233 --> 00:24:29,801 THAT PROGRESS BECAUSE THEY THINK 578 00:24:29,868 --> 00:24:31,770 THAT PERSON IS IN STAGE 2 END 579 00:24:31,837 --> 00:24:34,206 KIDNEY DISEASE BUT THE GENETICS 580 00:24:34,272 --> 00:24:37,509 MAY BE PLACING THEM IN THE 581 00:24:37,576 --> 00:24:42,280 GRIEWKS, THEY MAY BE AT STAGE 4 582 00:24:42,347 --> 00:24:49,688 IN THE DISEASE, OR THEY MAY BE 583 00:24:49,754 --> 00:24:49,921 HEALTHY. 584 00:24:49,988 --> 00:24:51,156 I WILL SHOW YOU IN A MINUTE. 585 00:24:51,223 --> 00:24:54,893 SO THEN IF YOU THINK ABOUT THESE 586 00:24:54,960 --> 00:24:56,862 BEING HERITABLE AND MORE 587 00:24:56,928 --> 00:24:57,863 HERITABLE THAN PHYSICIANS 588 00:24:57,929 --> 00:25:00,432 REALIZE, WHAT PROPORTION OF THE 589 00:25:00,498 --> 00:25:02,667 HERITABLE LAB VALUES HAVE MEAN 590 00:25:02,734 --> 00:25:04,903 VALUES OR VARIANCES, THAT DIFFER 591 00:25:04,970 --> 00:25:11,243 SIGNIFICANTLY BY EHR REPORTED 592 00:25:11,309 --> 00:25:12,177 RACE ETHNICITY. 593 00:25:12,244 --> 00:25:14,512 TEN%, A QUARTER OF THEM, HALF OF 594 00:25:14,579 --> 00:25:15,981 THEM. 595 00:25:16,047 --> 00:25:18,416 HALF OF THEM HAVE SIGNIFICANT 596 00:25:18,483 --> 00:25:23,722 MEAN DIFFERENCES BY EHR REPORTED 597 00:25:23,788 --> 00:25:26,358 RACE ETHNICITY AND NOT 598 00:25:26,424 --> 00:25:27,425 INSUBSTANTIAL FRACTION DIFFERS 599 00:25:27,492 --> 00:25:31,296 SIGNIFICANTLY IN THE VARIANCES 600 00:25:31,363 --> 00:25:33,365 AND ESPECIALLY AMONG POPULATIONS 601 00:25:33,431 --> 00:25:36,001 OF RECENT AFRICAN GENETIC 602 00:25:36,067 --> 00:25:37,836 ANCESTRIES, THE FACT THAT 603 00:25:37,903 --> 00:25:40,238 THERE'S A MUCH LONGER POPULATION 604 00:25:40,305 --> 00:25:42,007 HISTORY LARGER AFFECTIVE 605 00:25:42,073 --> 00:25:43,041 POPULATION SIZE, AND THOSE 606 00:25:43,108 --> 00:25:44,910 POPULATIONS HAVE MUCH MORE 607 00:25:44,976 --> 00:25:47,279 GENETIC VARIATION, THEY HAVE 608 00:25:47,345 --> 00:25:49,748 MUCH MORE FUNCTIONAL VARIATION. 609 00:25:49,814 --> 00:25:54,219 IT IS NOT UNCOMMON TO 610 00:25:54,286 --> 00:25:56,221 OBSERVATION LABORATORY VALUES 611 00:25:56,288 --> 00:25:58,290 WITH SIGNIFICANT MEAN 612 00:25:58,356 --> 00:25:59,691 DIFFERENCES WHERE THE AFRICAN 613 00:25:59,758 --> 00:26:01,426 AMERICANS IN OUR BIOBANK ARE 614 00:26:01,493 --> 00:26:03,929 MORE LIKELY TO BE OUTSIDE 615 00:26:03,995 --> 00:26:05,997 REFERENCE RANGES, OF COURSE, IN 616 00:26:06,064 --> 00:26:09,167 THE DIRECTION WHERE THE MEAN HAS 617 00:26:09,234 --> 00:26:10,602 CHANGED BUT ACTUALLY ARE MORE 618 00:26:10,669 --> 00:26:13,138 LIKELY TO BE OUTSIDE REFERENCED 619 00:26:13,204 --> 00:26:15,140 RANGES ON BOTH ENDS OF THE 620 00:26:15,206 --> 00:26:16,841 GRIEWKS DESPITE THE FACT THAT 621 00:26:16,908 --> 00:26:24,049 THERE'S A BIG MEAN DIFFERENCE. 622 00:26:24,115 --> 00:26:26,551 IN SOME WAYS THIS IS A CRAZY 623 00:26:26,618 --> 00:26:30,488 THING BUT THE TRUTH IS, MANY OF 624 00:26:30,555 --> 00:26:32,257 THE REFERENCE RANGES WERE SET A 625 00:26:32,324 --> 00:26:34,192 VERY ALONG TIME AGO IN NOW WE 626 00:26:34,259 --> 00:26:36,861 WOULD NOW THINK OF RIDICULOUSLY 627 00:26:36,928 --> 00:26:38,363 SAMPLES OF OLD WHITE MEN, SOME 628 00:26:38,430 --> 00:26:41,333 OF THE LAB COMMONLY USED MEASURE 629 00:26:41,399 --> 00:26:43,401 AMS HAVE UNDERGONE CHANGES OVER 630 00:26:43,468 --> 00:26:46,004 TIME WITH RESPECT TO REFERENCE 631 00:26:46,071 --> 00:26:50,742 RANGES, MOST HAVE NOT, MOST OF 632 00:26:50,809 --> 00:26:52,544 THEM ARE NOT ADEQUATELY 633 00:26:52,610 --> 00:26:56,681 CORRECTED FOR SEX DIFFERENCES IN 634 00:26:56,748 --> 00:26:59,217 THE MEASURES OR FOR HOUR DIVERSE 635 00:26:59,284 --> 00:27:05,423 THESE LABORATORY VALUES ARE 636 00:27:05,490 --> 00:27:05,857 ACROSS POPULATIONS. 637 00:27:05,924 --> 00:27:07,692 SO I WILL GO THROUGH A FEW 638 00:27:07,759 --> 00:27:08,426 EXAMPLES OF STUDIES THAT HAVE 639 00:27:08,493 --> 00:27:11,629 BEEN DONE ON COMMONLY USED LAB 640 00:27:11,696 --> 00:27:13,732 VALUES, WHITE CELL COUNT, 641 00:27:13,798 --> 00:27:18,570 NUTRIFILL COUNTS, XONLY USED TO 642 00:27:18,636 --> 00:27:20,438 IN PEOPLE WHO TAKE DRUGS THAT 643 00:27:20,505 --> 00:27:25,276 MIGHT BE CYTOTOXIC IN TRYING TO 644 00:27:25,343 --> 00:27:30,281 IDENTIFY PEOPLE WHO MIGHT HAVE 645 00:27:30,348 --> 00:27:34,753 THE DISEASE, THE DUFFY MORPHISM 646 00:27:34,819 --> 00:27:38,723 IS A LOWER COMPOUND AND PEOPLE 647 00:27:38,790 --> 00:27:39,891 HOMOZYGOUS FOR THISPOLOGYY 648 00:27:39,958 --> 00:27:41,893 MORPHISM, MOST OF WHOM HAVE 649 00:27:41,960 --> 00:27:43,128 RECENT GENETIC ANCESTRY FROM 650 00:27:43,194 --> 00:27:46,297 AFRICA BECAUSE IT IS AN 651 00:27:46,364 --> 00:27:48,233 ADAPTATION TO HIGH MALARIA 652 00:27:48,299 --> 00:27:50,668 ENVIRONMENTS THAT IS EXTREMELY 653 00:27:50,735 --> 00:27:53,538 EFFECTIVE, ALLELE FREQUENCIES 654 00:27:53,605 --> 00:27:56,241 AND ENVIRONMENTS WHERE THE 655 00:27:56,307 --> 00:27:57,575 PARTICULAR, THIS PARTICULAR 656 00:27:57,642 --> 00:27:59,244 ADAPTATION IS EFFECTIVE. 657 00:27:59,310 --> 00:28:03,048 ALLELE FREQUENCIES ARE NEARLY 1 658 00:28:03,114 --> 00:28:04,783 FOR THIS--NEARLY EVERYONE IS 659 00:28:04,849 --> 00:28:07,052 HOMOZYGOUS FOR THIS VARIANT IN 660 00:28:07,118 --> 00:28:09,454 MOST PARTS OF AFRICA, SO ONA 661 00:28:09,521 --> 00:28:12,991 AVERAGE AFRICAN AMERICANS IN THE 662 00:28:13,058 --> 00:28:15,093 U.S. ARE--THE ALLELE FREQUENCY 663 00:28:15,160 --> 00:28:16,861 .8, THAT'S ABOUT THE PROPORTION 664 00:28:16,928 --> 00:28:21,332 YOU WOULD EXPECT GIVEN THE 665 00:28:21,399 --> 00:28:25,270 AVERAGE ADD MIXTURE OF EUROPEAN 666 00:28:25,336 --> 00:28:26,538 ALLELES IN AFRICAN--RECENT 667 00:28:26,604 --> 00:28:28,907 AFRICAN ANCESTRY GROUPS IN THE 668 00:28:28,973 --> 00:28:30,909 UNITED STATES, THAT MEANS 2/3RDS 669 00:28:30,975 --> 00:28:32,777 OF AFRICAN AMERICANS ARE 670 00:28:32,844 --> 00:28:34,079 HOMOZYGOUS FOR THIS ALLELE AND 671 00:28:34,145 --> 00:28:37,782 WHEN A BONE MARROW BIOPSY IS 672 00:28:37,849 --> 00:28:42,921 ORDERED IN A PATIENT HOMOZYGOUS 673 00:28:42,987 --> 00:28:44,789 FOR THE DOVE ARK LEGAL, AND THE 674 00:28:44,856 --> 00:28:47,559 ONLY REASON FOR THE BIOPSY IS 675 00:28:47,625 --> 00:28:49,360 THE BONE MARROW WHITE COUNT. 676 00:28:49,427 --> 00:28:51,129 IT'S NEVER POSITIVE, THERE'S NO 677 00:28:51,196 --> 00:28:53,264 RETURN IN THE INVESTMENT OF THAT 678 00:28:53,331 --> 00:28:54,566 BONE MARROW BIOPSY, IT IS NEVER 679 00:28:54,632 --> 00:28:56,134 POSITIVE AND THAT WAS SHOWN AT 680 00:28:56,201 --> 00:28:59,237 VANTER BUILT AND A GROUP OF 681 00:28:59,304 --> 00:29:01,439 OTHER BIOBANKS, SO THERE'S 682 00:29:01,506 --> 00:29:02,707 UNNECESSARY BONE MARROW 683 00:29:02,774 --> 00:29:03,741 BIOPSIES, STILL BEING DONE 684 00:29:03,808 --> 00:29:07,812 DESPITE THE FACT THAT THIS 685 00:29:07,879 --> 00:29:09,347 BENIGN ETHNIC NEWT PENIA IS 686 00:29:09,414 --> 00:29:11,349 SUPPOSED TO BE WELL KNOWN TO 687 00:29:11,416 --> 00:29:12,150 PHYSICIANS. 688 00:29:12,217 --> 00:29:14,552 BONE MARROW BIOPSIES ARE STILL 689 00:29:14,619 --> 00:29:17,288 BEING ORDERED, NOT UNCOMMONLY IN 690 00:29:17,355 --> 00:29:19,457 MEDICAL CENTERS, WHERE THE ONLY 691 00:29:19,524 --> 00:29:23,161 INICATION IS A LOW WHITE CELL 692 00:29:23,228 --> 00:29:23,628 COUNT. 693 00:29:23,695 --> 00:29:26,364 NO ADDITIONAL SYMPTOMS AND WHEN 694 00:29:26,431 --> 00:29:28,099 THOSE PEOPLE ARE DUFFY 695 00:29:28,166 --> 00:29:30,135 HOMOSWROIG OATS THERE'S NO 696 00:29:30,201 --> 00:29:33,338 RETURN ON THE BONE MARROW 697 00:29:33,404 --> 00:29:33,905 BIOPSY. 698 00:29:33,972 --> 00:29:38,877 THERE'S A LOT OF DRUGS THAT WE 699 00:29:38,943 --> 00:29:40,945 GIVE THAT ARE CYTOTOXIC, 700 00:29:41,012 --> 00:29:42,180 PHYSICIANS LOOK AT THE FIRST 701 00:29:42,247 --> 00:29:43,581 WHITE CELL COUNT THAT HAPPENS 702 00:29:43,648 --> 00:29:44,649 AFTER PATIENTS GET PUT ON THESE 703 00:29:44,716 --> 00:29:46,851 DRUGS AND THEY ARE TAKING 704 00:29:46,918 --> 00:29:49,888 PATIENTS WHO ARE DUFFY 705 00:29:49,954 --> 00:29:53,224 HOMOZYGOTES OFF FIRST LINE MEDS 706 00:29:53,291 --> 00:30:00,031 FOR AUTOIMMUNE CONDITIONS, FOR 707 00:30:00,098 --> 00:30:01,833 CANCER CHEMO THERAPIES, YOU KNOW 708 00:30:01,900 --> 00:30:04,669 DRUGS PEOPLE TAKE AFTER 709 00:30:04,736 --> 00:30:06,638 TRANSPLANTATION, THEY'RE TAKING 710 00:30:06,704 --> 00:30:09,474 DUFFY HOMOZYGOTES OFF THEIR 711 00:30:09,541 --> 00:30:14,679 MEDS, WHEN THEY DON'T NEED TO 712 00:30:14,746 --> 00:30:14,913 BE. 713 00:30:14,979 --> 00:30:22,153 AFRICAN AMERICANS WHO ARE DUFFY 714 00:30:22,220 --> 00:30:23,354 HOMOZYGOTES DON'T HAVE FEWER 715 00:30:23,421 --> 00:30:25,990 WHITE CELLS, THERE ARE FEWER IN 716 00:30:26,057 --> 00:30:27,058 CIRCULATION, THEY'RE HEANGING 717 00:30:27,125 --> 00:30:28,927 OUT IN PERIPHERAL TISSUES AND AS 718 00:30:28,993 --> 00:30:30,895 SOON AS THEIR'S AN INFEC, THEY 719 00:30:30,962 --> 00:30:36,467 COME OUT, FIGHT THAT INFECTION 720 00:30:36,534 --> 00:30:39,537 JUST FINE. 721 00:30:39,604 --> 00:30:41,606 THE LOW COUNTS OF WHITE CELL 722 00:30:41,673 --> 00:30:42,907 POPULATION ARE NOT INDICATIVE OF 723 00:30:42,974 --> 00:30:46,644 INCREASED RISK FOR INFECTION. 724 00:30:46,711 --> 00:30:48,246 SO, SO TAKING PEOPLE OFF THESE 725 00:30:48,313 --> 00:30:53,251 IMPORTANT FIRST LINE DRUGS IS 726 00:30:53,318 --> 00:30:54,419 DISADVANTAGING THEM IN THEIR 727 00:30:54,485 --> 00:30:59,958 HEALTHCARE AND AGAIN, YOU SEE 728 00:31:00,024 --> 00:31:02,160 THIS REALLY DRAMATICALLY FOR 729 00:31:02,227 --> 00:31:03,861 DRUG WITHDRAWALS FOR HEMOPOETIC 730 00:31:03,928 --> 00:31:07,699 TOXICITY BUT NOT FOR OTHER 731 00:31:07,765 --> 00:31:09,467 REASONS THAT HAD TO DO WITH THE 732 00:31:09,534 --> 00:31:11,669 INABILITY TO JUST TAKE THE DRUG, 733 00:31:11,736 --> 00:31:13,438 OTHER KINDS OF SIDE EFFECTS 734 00:31:13,504 --> 00:31:16,574 ENTIRELY, SO IT'S ALL ABOUT 735 00:31:16,641 --> 00:31:20,945 DUFFY AND PEOPLE TAKEN OFF THE 736 00:31:21,012 --> 00:31:22,013 DRUGS FOR TOXICITY AND ON 737 00:31:22,080 --> 00:31:24,148 AVERAGE THEY GET TO TAKE ABOUT 738 00:31:24,215 --> 00:31:27,285 20% OF THE FIRST LINE MEDS THAT 739 00:31:27,352 --> 00:31:28,953 OTHER AFRICAN AMERICANS TAKE 740 00:31:29,020 --> 00:31:32,290 WHEN THEY HAVE LUPUS AND WE'VE 741 00:31:32,357 --> 00:31:35,526 ALWAYS KNOWN THAT PEOPLE WHO 742 00:31:35,593 --> 00:31:38,496 HAVE LUPUS WITH RECENT AFRICAN 743 00:31:38,563 --> 00:31:44,302 ANCESTRY DO WORSE WITH LUPUS 744 00:31:44,369 --> 00:31:45,803 THAN WE SEE THIS OTHER 745 00:31:45,870 --> 00:31:49,907 POPULATIONS BUT HOW MUCH OF THAT 746 00:31:49,974 --> 00:31:52,910 IS TAKING A SUBSTANTIAL--2/3RDS 747 00:31:52,977 --> 00:31:54,279 OF ATRICK AN AMERICANS ARE AT 748 00:31:54,345 --> 00:31:57,015 RISK OF BEING TAKEN OFF THOSE 749 00:31:57,081 --> 00:32:01,185 FIRST LINE MEDS VERY EARLY. 750 00:32:01,252 --> 00:32:04,722 SO AS I DAY DUFFY IS A BENIGN 751 00:32:04,789 --> 00:32:09,027 POLYMORPHISM EXCEPT FOR HOW IT 752 00:32:09,093 --> 00:32:10,662 EXECUTES HEALTHCARE IN THE 753 00:32:10,728 --> 00:32:10,895 UCARIOT. 754 00:32:10,962 --> 00:32:13,831 SO IT IS NOT A GENETIC HEALTH 755 00:32:13,898 --> 00:32:14,832 DISPARITY, IT IS SOMETHING ELSE, 756 00:32:14,899 --> 00:32:16,834 IT SHOULD NEVER LEAD TO A HELT 757 00:32:16,901 --> 00:32:19,137 DISPARITY BUT IT LEADS TO A LOT 758 00:32:19,203 --> 00:32:22,173 OF REPEAT TESTING, UNNECESSARY 759 00:32:22,240 --> 00:32:23,675 BONE MARROW BIOPSIES, 760 00:32:23,741 --> 00:32:26,277 UNDERTREATMENT IN LUPUS, THAT I 761 00:32:26,344 --> 00:32:29,347 JUST SHOWED YOU, BUT UNDER THE 762 00:32:29,414 --> 00:32:32,283 HOOD, I MEAN THE THRESHOLD FOR 763 00:32:32,350 --> 00:32:34,852 WHITE CELL COUNT TO GET INTO 764 00:32:34,919 --> 00:32:36,821 CANCER THEME O THERAPY TRIALS 765 00:32:36,888 --> 00:32:41,125 WAS FOR MANY YEARS GOING TO KEEP 766 00:32:41,192 --> 00:32:45,029 HALF OF ALL AFRICAN AMERICANS 767 00:32:45,096 --> 00:32:47,365 OUT OF CLINICAL TRIALS BECAUSE 768 00:32:47,432 --> 00:32:51,035 2/3RDS OF THEM WHO ARE DUFFY 769 00:32:51,102 --> 00:32:52,804 HOMOZYGOTES END YOU FALLING 770 00:32:52,870 --> 00:32:56,874 BELOW THE THRESHOLDS ALL THE 771 00:32:56,941 --> 00:32:58,509 TIME AND THEY SET THOSE 772 00:32:58,576 --> 00:32:59,410 THRESHOLDS BECAUSE THEY DON'T 773 00:32:59,477 --> 00:33:01,045 WANT TO LOOSE PEOPLE IN THE 774 00:33:01,112 --> 00:33:06,084 WORSE OF CLINICAL TRIALS WHO ARE 775 00:33:06,150 --> 00:33:07,752 ALREADY STARTING TO HAVE 776 00:33:07,819 --> 00:33:08,786 CYTOTOXICITY FROM THE TREATMENTS 777 00:33:08,853 --> 00:33:14,525 THEY'VE HAD BUT OF COURSE, WITH 778 00:33:14,592 --> 00:33:16,427 HOMOZYGOTES THEY WILL BE LOWER, 779 00:33:16,494 --> 00:33:17,929 IT WAS AN INAPPROPRIATE 780 00:33:17,995 --> 00:33:20,164 THRESHOLD FOR AFRICAN AMERICANS 781 00:33:20,231 --> 00:33:25,503 AND I--WHILE THAT'S BEING 782 00:33:25,570 --> 00:33:26,704 CHANGED NOW, THAT'S PART OF THE 783 00:33:26,771 --> 00:33:28,606 REASON WHY IT'S SO 784 00:33:28,673 --> 00:33:29,207 UNDERREPRESENTED IN CHEMO 785 00:33:29,273 --> 00:33:34,545 THERAPY TRIALS FOR SO MANY 786 00:33:34,612 --> 00:33:34,779 YEARS. 787 00:33:34,846 --> 00:33:35,847 AND FOR TRANSPLANT, PEOPLE ARE 788 00:33:35,913 --> 00:33:37,815 LOOKING AT BUT IT'S NOT ANYTHING 789 00:33:37,882 --> 00:33:40,485 IMD, I CAN TELL THAT NOW. 790 00:33:40,551 --> 00:33:44,822 HOW BAD IT IS, WE ARE STILL 791 00:33:44,889 --> 00:33:47,258 LOOKING AT BUT YOU CAN SEE IT IN 792 00:33:47,325 --> 00:33:49,560 THE RATES AT WHICH AFRICAN 793 00:33:49,627 --> 00:33:53,498 AMERICANS ENDED UP HAVING BURST 794 00:33:53,564 --> 00:33:54,799 APPENDIXES BECAUSE MANY OF THE 795 00:33:54,866 --> 00:33:59,103 RUBRICS FOR WHEN YOU DO SURGERY, 796 00:33:59,170 --> 00:34:01,506 WHEN YOU SHOULD DO SURGERY, TO 797 00:34:01,572 --> 00:34:04,909 KEEP THE APPENDIX FROM BURSTING 798 00:34:04,976 --> 00:34:06,944 REQUIRED REACHING A CERTAIN HIGH 799 00:34:07,011 --> 00:34:09,380 WHITE CELL COUNT THAT PEOPLE 800 00:34:09,447 --> 00:34:11,749 WITH, WHO ARE DUFFY HOMOZYGOTES 801 00:34:11,816 --> 00:34:13,418 WILL NOT GET TO. 802 00:34:13,484 --> 00:34:16,754 THEY WILL BE--THEY WILL BE RIGHT 803 00:34:16,821 --> 00:34:18,122 AT OTHER POPULATIONS AFRAMMINGS 804 00:34:18,189 --> 00:34:20,124 WHEN THEY'RE WHITE CELL COUNTS 805 00:34:20,191 --> 00:34:30,701 HAVE REALLY GOTTEN DANGEROUSLY 806 00:34:32,170 --> 00:34:32,236 HIGH. 807 00:34:32,303 --> 00:34:34,205 AFRICAN AMERICANS HAVE JUST HAD 808 00:34:34,272 --> 00:34:37,208 MORE SERIOUS HEALTH DISPARITIES 809 00:34:37,275 --> 00:34:42,547 REFLECTING BURST APPENDIX. 810 00:34:42,613 --> 00:34:44,382 RISK BASED REF FERENCE RANGES 811 00:34:44,449 --> 00:34:49,420 CANNOT SOLVE THIS PROBLEM. 812 00:34:49,487 --> 00:34:51,088 ONE-THIRD OF AFRICAN AMERICANS 813 00:34:51,155 --> 00:34:52,957 ARE NOT DUFFY ZYGOTES, THEY ARE 814 00:34:53,024 --> 00:34:55,126 DISTRIBUTION OF THEIR WHITE CELL 815 00:34:55,193 --> 00:34:56,727 COUNTS LOOKS LIKE EVERYBODY'S 816 00:34:56,794 --> 00:34:58,129 EXPWRIEWKS OF WHITE CELL COUNTS, 817 00:34:58,196 --> 00:35:00,097 IT'S NOT ABOUT THE SOCIAL 818 00:35:00,164 --> 00:35:05,269 CONSTRUCT OF RACE, IT'S ABOUT 819 00:35:05,336 --> 00:35:08,439 WHAT ALLELES YOU HAVE AND COMMON 820 00:35:08,506 --> 00:35:14,078 ALLELES WITH BIG EFFECTS DRIVE 821 00:35:14,145 --> 00:35:15,279 HUGE HERITABILITYS. 822 00:35:15,346 --> 00:35:16,981 THE HERITABILITY OF WHITE CELL 823 00:35:17,048 --> 00:35:18,983 COUNTS IN POPULATIONS OF RECENT 824 00:35:19,050 --> 00:35:21,385 AFRICAN ANCESTRY IS MUCH HIGHER 825 00:35:21,452 --> 00:35:22,753 ABOUT THE HERITABILITY OF WHITE 826 00:35:22,820 --> 00:35:25,423 CELL COUNTS IN OTHER POPULATIONS 827 00:35:25,490 --> 00:35:29,026 BECAUSE IN PART OF THIS ALLELE 828 00:35:29,093 --> 00:35:32,363 IT HAS A BIG IMPACT ON AVERAGE 829 00:35:32,430 --> 00:35:34,398 CELL COUNT, AND IS VERY COMMON 830 00:35:34,465 --> 00:35:36,267 IN THAT POPULATION, MOST ALLELES 831 00:35:36,334 --> 00:35:38,469 THAT HAVE BIG EFFECT SIZES ARE 832 00:35:38,536 --> 00:35:42,073 RARE, THIS IS AN EXAMPLE OF HOW 833 00:35:42,139 --> 00:35:43,241 SELECTION HAS DRIVEN ALLELE, AN 834 00:35:43,307 --> 00:35:47,879 ALLELE TO VERY HIGH FREQUENCY 835 00:35:47,945 --> 00:35:50,147 THAT'S BENIGN FOR HEALTH BUT NOT 836 00:35:50,214 --> 00:35:59,624 BENIGN WHEN WE THINK OF HOW IT 837 00:35:59,690 --> 00:36:00,858 INFLUENCES HEALTHCARE. 838 00:36:00,925 --> 00:36:05,763 SO WHAT DO YOU EVEN CALL THIS 839 00:36:05,830 --> 00:36:06,130 DISPARITY? 840 00:36:06,197 --> 00:36:08,900 IT'S NOT REALLY A DISPARITY, 841 00:36:08,966 --> 00:36:10,368 IT'S AN IGNORANT DISPARITY. 842 00:36:10,434 --> 00:36:12,603 IT'S 1 THAT CAN BE FIXED WITH 843 00:36:12,670 --> 00:36:13,404 GENETIC COUNTS. 844 00:36:13,471 --> 00:36:15,339 WHILE CELL COUNTS ARE USEFUL 845 00:36:15,406 --> 00:36:17,708 MEASUREMENTS WE SHOULD BE 846 00:36:17,775 --> 00:36:19,143 RECOGNIZING AND YOU KNOW THESE 847 00:36:19,210 --> 00:36:22,246 ARE STUDIES THAT ARE ABOUT TO BE 848 00:36:22,313 --> 00:36:24,181 PUBLISHED, THE POLYGENIC 849 00:36:24,248 --> 00:36:26,284 BACKGROUND FOR WHITE CELL COUNTS 850 00:36:26,350 --> 00:36:29,220 IS NOT PREDICTIVE FOR ANY OF THE 851 00:36:29,287 --> 00:36:31,656 OUTCOMES THAT WE USE IT, IT'S 852 00:36:31,722 --> 00:36:37,028 NOT PREDICTIVE OF WHO WILL 853 00:36:37,094 --> 00:36:38,329 DEVELOP INFECTIONS WHEN THEY 854 00:36:38,396 --> 00:36:42,199 TAKE MEDICATIONS, JUST THE PURE 855 00:36:42,266 --> 00:36:44,402 POLYGENIC BACKGROUND, EVEN IN 856 00:36:44,468 --> 00:36:45,770 EUROPEAN POPULATIONS, WHAT'S 857 00:36:45,836 --> 00:36:47,838 VALUABLE ABOUT WHITE CELL 858 00:36:47,905 --> 00:36:48,773 COUNTS, NUTRIFILL COUNTS IN 859 00:36:48,839 --> 00:36:53,744 THESE CONTEXT IS THAT DYNAMIC 860 00:36:53,811 --> 00:36:54,679 NATURE. 861 00:36:54,745 --> 00:36:56,180 WILL WAY GENETIC INFLUENCE WHERE 862 00:36:56,247 --> 00:36:57,448 YOU ARE IN THE DISTRIBUTION IS 863 00:36:57,515 --> 00:36:58,416 NOISE FOR HOW WE USE THAT 864 00:36:58,482 --> 00:37:00,718 MEASURE AND THAT MEASURE WILL BE 865 00:37:00,785 --> 00:37:02,486 MORE INFORMATIVE, IF WE REGRESS 866 00:37:02,553 --> 00:37:03,654 ALL THE GENETICS OUT FOR 867 00:37:03,721 --> 00:37:06,757 EVERYBODY, IT WILL BE A BETTER 868 00:37:06,824 --> 00:37:08,159 MORE EFFECTIVE BIOMARKER FOR THE 869 00:37:08,225 --> 00:37:18,569 WAYS THAT WE USE IT. 870 00:37:21,238 --> 00:37:23,174 --HOW WELL THE CONTROL FOR BLOOD 871 00:37:23,240 --> 00:37:24,909 FLUICOSE LEVELS IS IN PEOPLE 872 00:37:24,976 --> 00:37:25,343 WITH DIABETES. 873 00:37:25,409 --> 00:37:28,012 IT IS NOW NOT INFREQUENTLY 874 00:37:28,079 --> 00:37:31,315 USEDDAs A WAY OF DIAGNOSE 875 00:37:31,382 --> 00:37:35,586 DIABETES IN HEALTHCARE SYSTEMS. 876 00:37:35,653 --> 00:37:41,726 BUT G6 PEOPLE WHO CARRY GSPD 877 00:37:41,792 --> 00:37:42,660 ALLELES, MUTATIONS, AGAIN THAT 878 00:37:42,727 --> 00:37:49,100 HAPPEN TO BE ADAPTATIONS TO 879 00:37:49,166 --> 00:37:50,801 MALARIA ENVIRONMENTS THIS IS A 880 00:37:50,868 --> 00:37:53,337 VERY COMMON ADAPTATION THAT HAS 881 00:37:53,404 --> 00:37:54,639 RISEN OVER AND OVER AGAIN 882 00:37:54,705 --> 00:37:56,941 INDEPENDENTLY AT DIFFERENT 883 00:37:57,008 --> 00:37:59,610 ALLELES AT G6 PD, WHICH IS ON 884 00:37:59,677 --> 00:38:01,479 THE X-CHROMOSOME, SO MALES ARE 885 00:38:01,545 --> 00:38:03,214 HOMOZYGOUS FOR THESE ALLELES, 886 00:38:03,280 --> 00:38:06,417 THESE ARK LEGALS HAVE ARISEN ALL 887 00:38:06,484 --> 00:38:08,386 OVER THE WORLD WHERE IT'S 888 00:38:08,452 --> 00:38:11,622 INDEMMIC AND THEY'RE NOT RARE IN 889 00:38:11,689 --> 00:38:12,657 POSE POPULATIONS, COLLECTIVELY 890 00:38:12,723 --> 00:38:19,063 G6 PD MUTATIONS THAT CAN HAVE 891 00:38:19,130 --> 00:38:21,599 THIS EFFECT ON HEMOGLOBIN 892 00:38:21,666 --> 00:38:28,339 IEE, AUDIENCE 1 C RANGE FROM 893 00:38:28,406 --> 00:38:29,306 25%, WE CARRY AROUND THOSE 894 00:38:29,373 --> 00:38:31,075 VARIANTS IF ARE A LONG TIME 895 00:38:31,142 --> 00:38:36,347 AFTER THE PATHOGENS ARE NO 896 00:38:36,414 --> 00:38:40,117 LONGER DRIVING THEM EMPLOY THE 897 00:38:40,184 --> 00:38:41,852 REASON THIS AFFECTS A1C LEVEL 898 00:38:41,919 --> 00:38:43,587 SYSTEM THAT THERE'S RED CELL 899 00:38:43,654 --> 00:38:45,322 HOMOLOGY SIS WHICH AFFECTS TD 900 00:38:45,389 --> 00:38:46,490 AVERAGE LIFE SPAN OF THE RED 901 00:38:46,557 --> 00:38:48,492 CELL WHA. WE'RE DOING IS 902 00:38:48,559 --> 00:38:51,729 MEASURING THE GLUE 903 00:38:51,796 --> 00:38:52,997 MARIOUSICATION OF HEMOGLOBIN ON 904 00:38:53,064 --> 00:38:56,634 RED CELLS AND IN PEOPLE WITHOUT 905 00:38:56,701 --> 00:38:59,537 G6 PD VARIANCE LEADING TO RED 906 00:38:59,603 --> 00:39:03,107 CELL HOMOLYSIS, WE ARE GETTING A 907 00:39:03,174 --> 00:39:05,543 SNAPSHOT OF THE AVERAGE 908 00:39:05,609 --> 00:39:07,278 CIRCULATING GLUCOSE LEVELS IN 909 00:39:07,344 --> 00:39:08,546 ABOUT THE PAST 3 MONTHS WHICH IS 910 00:39:08,612 --> 00:39:10,748 THE RATE OF RED CELL TURNOVER 911 00:39:10,815 --> 00:39:14,552 AND PEOPLE WITH G6 PD VARIANTS, 912 00:39:14,618 --> 00:39:15,886 THERE'S MORE RAPID TURNOVER, RED 913 00:39:15,953 --> 00:39:18,022 CELLS BECAUSE OF THE HOMOLYSIS 914 00:39:18,089 --> 00:39:19,023 AND YOU'RE LOOKING AT SOMETHING 915 00:39:19,090 --> 00:39:22,026 CLOSER TO A MONTH OR A MONTH AND 916 00:39:22,093 --> 00:39:26,997 A HALF OF LIFE OF THAT 917 00:39:27,064 --> 00:39:32,837 HEMOGLOBIN MOLECULE IN ITS GLUE 918 00:39:32,903 --> 00:39:33,904 MARIOUSICATION, THE 1 WHO YOU 919 00:39:33,971 --> 00:39:36,440 DON'T KNOW WHO'S A CARRIER AND 920 00:39:36,507 --> 00:39:38,509 WHO'S NOT YOU CAN'T TAKE THAT 921 00:39:38,576 --> 00:39:41,278 INTO ACCOUNT AND ON AVERAGE WITH 922 00:39:41,345 --> 00:39:42,813 DIABETES, THOSE CARRYING G6 PD 923 00:39:42,880 --> 00:39:46,484 ALLELES HAVE ABOUT A 1 POINT 924 00:39:46,550 --> 00:39:47,785 LOWER HEMODPLOABIN A1C LEVELS 925 00:39:47,852 --> 00:39:51,555 FOR MALES AND YOU CAN SEE THE 926 00:39:51,622 --> 00:39:53,758 PROGRESS IN FEMALES, EVEN THE 927 00:39:53,824 --> 00:39:56,527 HETEROZYGOTES HAVE A LOWER LEVEL 928 00:39:56,594 --> 00:39:58,195 AND HOMOZYGOTES MORE SIMILAR TO 929 00:39:58,262 --> 00:40:01,065 WHAT WE SEE IN THE MALE 930 00:40:01,132 --> 00:40:01,365 HOMOZYGOTES. 931 00:40:01,432 --> 00:40:03,467 SO WHAT HAPPENS AS A CONSEQUENCE 932 00:40:03,534 --> 00:40:03,834 OF THIS? 933 00:40:03,901 --> 00:40:05,269 CERTAINLY PEOPLE WITH DIABETES, 934 00:40:05,336 --> 00:40:07,004 SEEING THEIR PHYSICIANS ON A 935 00:40:07,071 --> 00:40:10,141 REGULAR BASIS, AND HAVING THIS 936 00:40:10,207 --> 00:40:12,009 MEASURED NOT BEING TREATED AS 937 00:40:12,076 --> 00:40:13,944 AGGRESSIVE LOAMACYY BECAUSE 938 00:40:14,011 --> 00:40:14,879 THEIR PHYSICIANS AND THEY 939 00:40:14,945 --> 00:40:18,282 THEMSELVES THINK THEY ARE DOING 940 00:40:18,349 --> 00:40:19,784 BETTER AT CONTROLLING THEIR 941 00:40:19,850 --> 00:40:22,186 BLOOD DPLUICOSE LEVELS THAN THEY 942 00:40:22,253 --> 00:40:23,854 ACTUALLY ARE, A FULL POINT LOWER 943 00:40:23,921 --> 00:40:27,091 ON AVERAGE IN MALES. 944 00:40:27,158 --> 00:40:30,528 THIS MEEPS IN OUR BIOBANK ON 945 00:40:30,594 --> 00:40:33,364 AVERAGE, CARRIERS OF G6 PD 946 00:40:33,430 --> 00:40:39,103 ALLELES HAVE A 1.2 FOLD DIABETIC 947 00:40:39,170 --> 00:40:40,371 RISK COMPLICATION IN ANY 948 00:40:40,437 --> 00:40:43,841 SITUATION EMPLOY IT IS SERIES 949 00:40:43,908 --> 00:40:45,109 FOR DIABETIC RETINAL LOCATIONIN 950 00:40:45,176 --> 00:40:46,744 OPEN MEETINGATHY, AND IT'S IN 951 00:40:46,811 --> 00:40:49,313 EARLY CLINICAL TRIALS TO 952 00:40:49,380 --> 00:40:51,148 UNDERSTAND HOW WELL, BLOOD 953 00:40:51,215 --> 00:40:53,684 GLUCOSE CONTROL WOULD REDUCE THE 954 00:40:53,751 --> 00:40:54,919 RISK OF COMPLICATIONS, DIABETIC 955 00:40:54,985 --> 00:40:55,986 RETINAL LOCATION NUMBER OF 956 00:40:56,053 --> 00:40:57,388 PATIENTSATHY WAS THE SENTINEL 1 957 00:40:57,454 --> 00:40:59,690 BECAUSE IT'S 1 OF THE FIRST 958 00:40:59,757 --> 00:41:02,359 COMPLICATIONS TO ARISE, SO 959 00:41:02,426 --> 00:41:03,594 HUGELY SIGNIFICANT EMPLOY 1.8 960 00:41:03,661 --> 00:41:06,430 FOLD INCREASED RISK IFA BETTIC 961 00:41:06,497 --> 00:41:10,768 RETINAL LOCATIONIN OPEN 962 00:41:10,835 --> 00:41:11,735 MEETINGATHY, HIGHLY SIGNIFICANT, 963 00:41:11,802 --> 00:41:13,037 BUT BIOBANKS ARE SEEING THIS 964 00:41:13,103 --> 00:41:13,804 TOO. 965 00:41:13,871 --> 00:41:15,906 WE ARE WORKING IN PRIMED IN A 966 00:41:15,973 --> 00:41:19,176 CONSORTIUM TO LOOK AT THIS IN A 967 00:41:19,243 --> 00:41:20,010 SERIOUS WAY. 968 00:41:20,077 --> 00:41:22,780 IT'S THE SAME EVERYWHERE, AND WE 969 00:41:22,847 --> 00:41:33,290 HAVE GOOD INFORMATION FROM 970 00:41:41,732 --> 00:41:43,567 SINGAPORE AND TAIWAN--AND STILL 971 00:41:43,634 --> 00:41:53,777 IS ENDEMIC IN SOUTHERN PARTS OF 972 00:41:53,844 --> 00:41:54,011 EUROPE. 973 00:41:54,078 --> 00:41:59,783 IT AFFECTS THIS MEASUREMENT OF 974 00:41:59,850 --> 00:42:00,384 GLUE MARIOUSICATED HEMOGLOBIN 975 00:42:00,451 --> 00:42:03,153 THAT IS A RELATIVELY INEXPENSIVE 976 00:42:03,220 --> 00:42:05,823 AND EFFECTIVE ASSAY. 977 00:42:05,890 --> 00:42:07,224 IN POPULATIONS THAT HAVE THE 978 00:42:07,291 --> 00:42:12,763 KIND OF HEALTHCARE SYSTEM WHERE 979 00:42:12,830 --> 00:42:16,000 HEMODPLOAGIN A1C IS TESTED EVERY 980 00:42:16,066 --> 00:42:18,836 WHY TO IDENTIFY DIABELTICS, IT'S 981 00:42:18,903 --> 00:42:22,573 AN AVERAGE 7 YEAR LATER 982 00:42:22,640 --> 00:42:25,442 DIAGNOSIS OF THE DIABETES IN THE 983 00:42:25,509 --> 00:42:26,010 G6 PD CARRIERS. 984 00:42:26,076 --> 00:42:27,978 SO IT'S NOT JUST THAT THEY'RE 985 00:42:28,045 --> 00:42:29,513 NOT BEING TREATED AGGRESSIVELY 986 00:42:29,580 --> 00:42:31,715 ENOUGH, BUT IF YOU USE 987 00:42:31,782 --> 00:42:32,783 HEMODPLOABIN A1C TO DIAGNOSE THE 988 00:42:32,850 --> 00:42:35,953 DIABETES, THEY WILL HAVE IT FOR 989 00:42:36,020 --> 00:42:41,592 MANYIERS BEFORE YOU RECOGNIZE 990 00:42:41,659 --> 00:42:42,293 AND TREAT IT. 991 00:42:42,359 --> 00:42:43,994 THE COST OF DIABETIC 992 00:42:44,061 --> 00:42:47,364 COMPLICATIONS IS 1 OF THE 993 00:42:47,431 --> 00:42:49,900 REASONS WHY THE NATIONAL 994 00:42:49,967 --> 00:42:51,168 INSTITUTES OF DIGESTIVE 995 00:42:51,235 --> 00:42:52,870 DISORDERS AND KIDNEY DISEASE 996 00:42:52,937 --> 00:42:53,437 EXIST. 997 00:42:53,504 --> 00:42:58,075 DIABETES IS A HUGE PUBLIC 998 00:42:58,142 --> 00:42:58,909 HEALTHCARE PROBLEM EXCLUSIVELY 999 00:42:58,976 --> 00:43:00,945 BECAUSE OF THE COMPLICATIONS 1000 00:43:01,011 --> 00:43:04,048 THAT IT CAUSES AND THE EXPANSE 1001 00:43:04,114 --> 00:43:07,117 AND DIFFICULTY OF TREATING THOSE 1002 00:43:07,184 --> 00:43:08,452 COMPLICATIONS AND THE MORBIDITY 1003 00:43:08,519 --> 00:43:13,257 AND MORTALITY THAT ARISE BECAUSE 1004 00:43:13,324 --> 00:43:14,058 OF THESE COMPLICATIONS. 1005 00:43:14,124 --> 00:43:15,926 WE HAVE ALWAYS RECOGNIZED THAT 1006 00:43:15,993 --> 00:43:19,396 MINORITY POPULATIONS HAVE MORE 1007 00:43:19,463 --> 00:43:20,030 DIABETIC COMPLICATIONS AND IT'S 1008 00:43:20,097 --> 00:43:22,366 EASY TO SAY, WELL, THEY CAN 1009 00:43:22,433 --> 00:43:23,834 ACCESS HEALTHCARE LESS, THEY 1010 00:43:23,901 --> 00:43:26,704 HAVE LESS ACCESS TO THINGS LIKE 1011 00:43:26,770 --> 00:43:29,206 FLUICOSE METERS THAT GIVE 1012 00:43:29,273 --> 00:43:32,876 CONTINUOUS FEEDBACK ON HOW WELL 1013 00:43:32,943 --> 00:43:34,178 THEY'RE DOING? 1014 00:43:34,244 --> 00:43:38,048 BUT PART OF IT ARE THESE KINDS 1015 00:43:38,115 --> 00:43:40,918 OF THINGS AND REMOVING THIS 1 1016 00:43:40,985 --> 00:43:43,454 HEALTH DISPARITY, USING GENETICS 1017 00:43:43,520 --> 00:43:46,390 WOULD PAY FOR THE GENETICS FOR 1018 00:43:46,457 --> 00:43:50,794 EVERYTHING ELSE. 1019 00:43:50,861 --> 00:43:52,663 IT'S HUGELY CONSEQUENTIAL IN 1020 00:43:52,730 --> 00:43:58,669 COST TO HAVE PEOPLE GO BLIND. 1021 00:43:58,736 --> 00:44:01,638 AND AS I SAY, THESE ALLELES ARE 1022 00:44:01,705 --> 00:44:03,374 NOT RARE IS ON THIS PARTICULAR 1023 00:44:03,440 --> 00:44:05,275 BIOMARKER THEY HAVE A BIG 1024 00:44:05,342 --> 00:44:05,609 EFFECT. 1025 00:44:05,676 --> 00:44:07,611 THEY HAVE EFFECTS ON OTHER 1026 00:44:07,678 --> 00:44:12,583 BIOMARKERS, TOO BECAUSE OF THE 1027 00:44:12,649 --> 00:44:14,618 RED CELL HOMOLYSIS. 1028 00:44:14,685 --> 00:44:21,525 BLOOD BORNE PATHOGENS, THE 1029 00:44:21,592 --> 00:44:22,626 ADAPTATIONS TO BLOOD BORNE 1030 00:44:22,693 --> 00:44:23,694 PATHOGENS WILL HAVE A LOT OF 1031 00:44:23,761 --> 00:44:25,529 EFFECTS ON THINGS WE MEASURE IN 1032 00:44:25,596 --> 00:44:26,230 BLOOD. 1033 00:44:26,296 --> 00:44:30,401 WE HAVE IGNORED THOSE THINGS IN 1034 00:44:30,467 --> 00:44:32,202 INTERPRETING LABORATORY VALUES 1035 00:44:32,269 --> 00:44:37,074 IN WAYS THAT ARE TRULY 1036 00:44:37,141 --> 00:44:39,943 DISADVANTAGING A LOT OF THE 1037 00:44:40,010 --> 00:44:44,281 WORLD'S POPULATIONS AND WE CAN 1038 00:44:44,348 --> 00:44:47,151 FIX THIS AND WE WOULD IMPROVE 1039 00:44:47,217 --> 00:44:48,218 HEALTHCARE IN GENERAL AND HEALTH 1040 00:44:48,285 --> 00:44:56,260 EQUITY IF WE DO. 1041 00:44:56,326 --> 00:44:57,928 I'M GOING TO GO FAST THRU A 1042 00:44:57,995 --> 00:44:59,496 KIDNEY STORY BECAUSE THIS IS 1043 00:44:59,563 --> 00:45:01,832 JUST A CRAZY WAY THAT 1044 00:45:01,899 --> 00:45:02,633 GENETICISTS AND NEPHROLOGIST 1045 00:45:02,699 --> 00:45:04,635 HAVE TALKED PAST EACH OTHER FOR 1046 00:45:04,701 --> 00:45:05,402 A LONG TIME. 1047 00:45:05,469 --> 00:45:07,471 YOU CAN MAKE DIRECT MEASURE AMS 1048 00:45:07,538 --> 00:45:10,140 OF KIDNEY FUNCTION THROUGH GLUE 1049 00:45:10,207 --> 00:45:14,178 MARRIAL FILTRATION, BUT IN 1050 00:45:14,244 --> 00:45:20,684 GENERAL WE ESTIMATE GLUE HERRIAL 1051 00:45:20,751 --> 00:45:23,220 FILTRATION THAT ARE FILTERED 1052 00:45:23,287 --> 00:45:24,888 THROUGH KIDNEYS, 1'S A 1053 00:45:24,955 --> 00:45:26,490 METABOLITE, 1'S A PROACTIVE TEEN 1054 00:45:26,557 --> 00:45:30,327 AND THE EQUATIONS FOR USING THIS 1055 00:45:30,394 --> 00:45:33,230 TO ESTIMATE GLUE MARULAR 1056 00:45:33,297 --> 00:45:34,965 FILTRATION REALLY TAKES SEX AND 1057 00:45:35,032 --> 00:45:36,967 AGE INTO ACCOUNT AS IF THE 1058 00:45:37,034 --> 00:45:38,335 CIRCULATING AND VARIABILITY OF 1059 00:45:38,402 --> 00:45:43,307 CIRCULATING LEVELS OF THESE 1060 00:45:43,373 --> 00:45:46,610 BIOMARKERS WAS ONLY ATTRIBUTABLE 1061 00:45:46,677 --> 00:45:49,046 TO KIDNEY FUNCTION. 1062 00:45:49,113 --> 00:45:50,080 THE HERITABILITY OF SIS AT THAT 1063 00:45:50,147 --> 00:45:52,516 TIMEIN C HAS BEEN ESTIMATED IN 1064 00:45:52,583 --> 00:45:55,185 THE RANGE OF 70-80% AND A HUGE 1065 00:45:55,252 --> 00:45:57,921 PROPORTION OF THAT HERITABILITY 1066 00:45:57,988 --> 00:46:00,357 IS ATTRIBUTE AUTOMOBILE TO THE 1067 00:46:00,424 --> 00:46:01,959 STRUCTURAL LOCUST VERSUS STATIN 1068 00:46:02,025 --> 00:46:05,863 C GENES WHERE THERE'S A HUGE 1069 00:46:05,929 --> 00:46:09,566 EFFECT OF QTLs, SO THERE'S A 1070 00:46:09,633 --> 00:46:10,367 BIG GENETIC INFLUENCE ON WHERE 1071 00:46:10,434 --> 00:46:15,672 PEOPLE ARE GOING TO SIT IN THAT 1072 00:46:15,739 --> 00:46:16,573 DISTRIBUTION FOR 1073 00:46:16,640 --> 00:46:17,040 [INDISCERNIBLE]. 1074 00:46:17,107 --> 00:46:18,575 CREATINE IS JUST POLYGENIC, IT'S 1075 00:46:18,642 --> 00:46:24,281 NOT BIG EFFECT ALLELES BUT IT'S 1076 00:46:24,348 --> 00:46:24,748 60% HERITABLE. 1077 00:46:24,815 --> 00:46:31,021 THE ONLY PART OF THE ACTUAL 1078 00:46:31,088 --> 00:46:32,990 GENETIC VARIATION IN THAT SPACE 1079 00:46:33,056 --> 00:46:34,158 THAT'S TELLING US ABOUT KIDNEY 1080 00:46:34,224 --> 00:46:35,659 FUNCTION IS THE PART THAT'S 1081 00:46:35,726 --> 00:46:38,428 SHARED BETWEEN THE 2 OF THESE. 1082 00:46:38,495 --> 00:46:40,030 THEY HAVE NOTHING INTRINSIC TO 1083 00:46:40,097 --> 00:46:41,665 DO WITH KIDNEY FUNCTION, THEY'RE 1084 00:46:41,732 --> 00:46:44,101 JUST CHEAP AND EASILY MEASURED 1085 00:46:44,168 --> 00:46:45,669 PROTEINS OR METABOLITES THAT GET 1086 00:46:45,736 --> 00:46:46,503 FILTERED THROUGH KIDNEYS AND 1087 00:46:46,570 --> 00:46:49,840 USING THEM AS IF THE ONLY THING 1088 00:46:49,907 --> 00:46:53,043 AFFECTING THEIR LEVELS IS KIDNEY 1089 00:46:53,110 --> 00:46:55,646 FUNCTION IS SELLING SHORT WHAT 1090 00:46:55,712 --> 00:46:57,481 THE BIOLOGY OF THESE THINGS 1091 00:46:57,548 --> 00:47:00,584 ACTUALLY IS, THEY HAVE THEIR OWN 1092 00:47:00,651 --> 00:47:06,423 GENETIC REASONS FOR BEING 1093 00:47:06,490 --> 00:47:08,025 PRESENT IN CIRCULATION AND 1094 00:47:08,091 --> 00:47:08,859 AFFECTING KIDNEY FUNCTION ISN'T 1095 00:47:08,926 --> 00:47:09,993 1 OF THEM. 1096 00:47:10,060 --> 00:47:11,828 THEY'RE JUST WAYS WE ASSAY 1097 00:47:11,895 --> 00:47:12,796 KIDNEY FUNCTION. 1098 00:47:12,863 --> 00:47:14,298 THE MAGNITUDE OF GENETIC 1099 00:47:14,364 --> 00:47:18,101 EFFECTS, SO THIS IS UK BIOBANK 1100 00:47:18,168 --> 00:47:19,736 DATA, SIS STATIN C LEVELS, HUGE 1101 00:47:19,803 --> 00:47:21,572 EFFECTS AND WE TOOK OUT THE 1102 00:47:21,638 --> 00:47:23,106 CHROMOSOME 20 REGION BECAUSE WE 1103 00:47:23,173 --> 00:47:27,277 WANT TO KEEP SIS STATIC C AND 1104 00:47:27,344 --> 00:47:29,012 CREATININE ON THE SCALE AND THE 1105 00:47:29,079 --> 00:47:31,682 VALUE FOR THE LOCUST IS LIKE 10 1106 00:47:31,748 --> 00:47:32,983 TO THE MINUS 5000, IT'S SUCH A 1107 00:47:33,050 --> 00:47:35,953 BIG EFFECT AND OF COURSE THEY'RE 1108 00:47:36,019 --> 00:47:38,789 IDEBTICAL WHETHER YOU USE RAW 1109 00:47:38,855 --> 00:47:42,359 SIS STATIN C OR KRAW 1110 00:47:42,426 --> 00:47:43,961 CREATEININE, SO THE GENETICS IS 1111 00:47:44,027 --> 00:47:47,631 THE SAME FOR THE RAW BIOMARKER 1112 00:47:47,698 --> 00:47:53,003 AS THE ESTIMATED TBLOR MARULAR 1113 00:47:53,070 --> 00:47:55,439 FILTRATION AND WHEN I TALK ABOUT 1114 00:47:55,505 --> 00:47:56,607 THIS WITH NEPHROLOGIST THE FIRST 1115 00:47:56,673 --> 00:47:58,742 THING THEY IS WELL, NO, WE ONLY 1116 00:47:58,809 --> 00:48:00,143 CARE ABOUT THE CHANGES, THAT'S 1117 00:48:00,210 --> 00:48:01,578 THE ONLY THING THAT MATTERS, 1118 00:48:01,645 --> 00:48:05,582 IT'S THE CHANGES THAT TELL US, 1119 00:48:05,649 --> 00:48:08,151 EXCEPT MANY PEOPLE WITH THEIR 1120 00:48:08,218 --> 00:48:09,286 FIRST CREATEININE LEVEL ARE IN 1121 00:48:09,353 --> 00:48:12,723 SOME STAGE OF KIDNEY FAILURE. 1122 00:48:12,789 --> 00:48:15,592 SO WE'RE USING ABSOLUTE VALUES, 1123 00:48:15,659 --> 00:48:17,561 NOT JUST CHANGES IN THE WAY WE 1124 00:48:17,628 --> 00:48:19,596 LABEL PEOPLE AND FOLLOW THEM. 1125 00:48:19,663 --> 00:48:22,266 AND SOMEBODY SAID TO BE AT STAGE 1126 00:48:22,332 --> 00:48:25,569 2 KIDNEY DISEASE, MAY BE 1127 00:48:25,636 --> 00:48:26,670 PERFECTLY HEALTHY OR MAYBE AT 1128 00:48:26,737 --> 00:48:29,706 STAIM 4 JUST FROM THE DISTANCE, 1129 00:48:29,773 --> 00:48:30,841 THE GENETICS THAT HAVE NOTHING 1130 00:48:30,907 --> 00:48:32,542 TO DO WITH KIDNEY FUNCTION TAKES 1131 00:48:32,609 --> 00:48:35,279 THEM, SO IT LEADS TO THE 1132 00:48:35,345 --> 00:48:37,114 HERITABILITY CAN LEAD TO 1133 00:48:37,180 --> 00:48:38,282 MISSTAGING, THIS CONTRIBUTES TO 1134 00:48:38,348 --> 00:48:42,152 WHAT WE SEE AS FAILURE TO 1135 00:48:42,219 --> 00:48:47,391 PROGRESS, BUT IT ALSO IS 1136 00:48:47,457 --> 00:48:48,692 SOMETHING THAT IS PROBABLY, I 1137 00:48:48,759 --> 00:48:52,462 MEAN BASED ON OUR DATA WOULD BE 1138 00:48:52,529 --> 00:48:53,530 SOMETIMES MISLABELINGED AS CUTE 1139 00:48:53,597 --> 00:48:59,503 KIDNEY INJURY THAT LEADS PEOPLE 1140 00:48:59,569 --> 00:49:01,204 TO EARLY DEATH. 1141 00:49:01,271 --> 00:49:02,372 THESE 2 BIOMARKERS HAVE NOTHING 1142 00:49:02,439 --> 00:49:05,208 IN COMMON EXCEPT FOR WHAT THEY 1143 00:49:05,275 --> 00:49:11,581 DO AND THEY'RE RECYCLED THROUGH 1144 00:49:11,648 --> 00:49:12,549 THE KIDNEYS. 1145 00:49:12,616 --> 00:49:15,419 SO KIDNEY FUNCTION IS IMPORTANT 1146 00:49:15,485 --> 00:49:19,723 FOR SHARED BIOLOGY, SO THE TOP 1147 00:49:19,790 --> 00:49:22,526 IS SERUM CREATEININE, THE 1148 00:49:22,592 --> 00:49:26,029 BOTTOM'S THE SIS STATIN C BUT 1149 00:49:26,096 --> 00:49:28,632 THEY ALSO HAVE, ABSOLUTELY 1150 00:49:28,699 --> 00:49:31,101 UNIQUE BIG EFFECTS AND OF COURSE 1151 00:49:31,168 --> 00:49:32,703 THIS IS STATIN C ON CHROMOSOME 1152 00:49:32,769 --> 00:49:36,173 20 IS A HUGE EFFECT IN SIS 1153 00:49:36,239 --> 00:49:39,376 STATIN C THAT'S NOT IN CREATINE, 1154 00:49:39,443 --> 00:49:41,978 WE COULD ESTIMATE GFR BETTER BY 1155 00:49:42,045 --> 00:49:43,613 REIMRESESSING OUT THE GENETIC 1156 00:49:43,680 --> 00:49:46,416 PARTS THAT ARE NOT ABOUT KIDNEY 1157 00:49:46,483 --> 00:49:46,683 FUNCTION. 1158 00:49:46,750 --> 00:49:48,385 WE WOULD HAVE A BETTER MEASURE 1159 00:49:48,452 --> 00:49:53,357 OF THE TRULY DYNAMIC PART OF 1160 00:49:53,423 --> 00:49:54,658 WHAT'S HAPPENING WHEN KIDNEYS 1161 00:49:54,725 --> 00:49:58,929 START TO FAIL, AND SO, YOU KNOW 1162 00:49:58,995 --> 00:50:01,064 YOU COULD DO A PRS THAT'S JUST 1163 00:50:01,131 --> 00:50:02,632 ABOUT THAT SHARED GENETIC 1164 00:50:02,699 --> 00:50:03,667 ARCHITECTURE THAT REALLY IS 1165 00:50:03,734 --> 00:50:05,936 TELLING BUT THE LIKELIHOOD OF 1166 00:50:06,002 --> 00:50:07,204 FUTURE KIDNEY FAILURE BUT YOU 1167 00:50:07,270 --> 00:50:11,975 COULD DO AN EGFR, ESTIMATED GLUE 1168 00:50:12,042 --> 00:50:13,610 MARRIAL FILTRATE VERSUS 1169 00:50:13,677 --> 00:50:15,846 STATINNING AND REMOVE EVERYTHING 1170 00:50:15,912 --> 00:50:17,848 THAT ISN'T SHARED WITH--ACROSS 1171 00:50:17,914 --> 00:50:21,952 THESE BIOMARKERS AND SO, YOU 1172 00:50:22,018 --> 00:50:23,887 KNOW YOU WOULD JUST REMOVE ALL 1173 00:50:23,954 --> 00:50:26,590 THE HERITABILITY AND USE THE 1174 00:50:26,656 --> 00:50:28,392 GENETICS AS GENETICS, OR YOU 1175 00:50:28,458 --> 00:50:30,293 COULD DO THESE OTHER KINDS OF 1176 00:50:30,360 --> 00:50:33,463 REGRESSIONS THAT FOCUS IN ON 1177 00:50:33,530 --> 00:50:37,567 JUST THE DYNAMIC PART THAT 1178 00:50:37,634 --> 00:50:38,034 MATTERS. 1179 00:50:38,101 --> 00:50:39,870 I'M GOING TO STOP TALKING ABOUT 1180 00:50:39,936 --> 00:50:41,571 THIS NOW, SO WE CAN HAVE 1181 00:50:41,638 --> 00:50:48,145 QUESTIONS, BUT SEX IS A PROBLEM, 1182 00:50:48,211 --> 00:50:48,912 TOO. 1183 00:50:48,979 --> 00:50:50,881 WOMEN HAVE BEEN DISADVANTAGED IN 1184 00:50:50,947 --> 00:50:52,182 LIVER TRANSPLANT FOR A LONG TIME 1185 00:50:52,249 --> 00:50:53,483 BECAUSE THE SEX DIFFERENCES IN 1186 00:50:53,550 --> 00:50:57,287 MEASURES OF LIVER FUNCTION WERE 1187 00:50:57,354 --> 00:50:59,256 NEVER TAKEN APPROPRIATELY INTO 1188 00:50:59,322 --> 00:50:59,623 ACCOUNT. 1189 00:50:59,689 --> 00:51:03,293 THERE ARE NO SIMPLE SOLUTIONS TO 1190 00:51:03,360 --> 00:51:04,161 COMPLEX PROBLEMS AND THE WHOLE 1191 00:51:04,227 --> 00:51:06,496 BUSINESS OF THE HERITABILITY OF 1192 00:51:06,563 --> 00:51:08,331 COMMONLY USED LABORATORY VALUES 1193 00:51:08,398 --> 00:51:13,437 IS A TIP OF THE ICEBERG PROBLEM. 1194 00:51:13,503 --> 00:51:19,042 AS I SAID, HALF OF THESE HAVE 1195 00:51:19,109 --> 00:51:20,477 POPULATION DIFFERENCES IN 1196 00:51:20,544 --> 00:51:23,447 ACHERAGE VALUES, HALF OF THE 1197 00:51:23,513 --> 00:51:24,481 HERITABLE MEASURES AND MOST OF 1198 00:51:24,548 --> 00:51:26,349 THE MEASURES ARE HERITABLE, IF 1199 00:51:26,416 --> 00:51:28,552 WE EVEN FOCUS ON IN ON THE 1200 00:51:28,618 --> 00:51:30,086 HIGHLY HERITABLE 1S THAT HAVE 1201 00:51:30,153 --> 00:51:31,755 DIFFERENT POPULATION DIFFERENCES 1202 00:51:31,822 --> 00:51:36,393 WE HAVE DOZENS MORE IMPORTANT 1203 00:51:36,460 --> 00:51:39,362 BIOMARKERS THAT THAT WE HAVE TO 1204 00:51:39,429 --> 00:51:40,764 ADDRESS AND AND YOU CAN'T--I 1205 00:51:40,831 --> 00:51:48,004 MEAN YOU JUSTICE CAN'T GO 1206 00:51:48,071 --> 00:51:49,105 FORWARDOT SAME PATH ONCE YOU 1207 00:51:49,172 --> 00:51:49,573 KNOW ABOUT THIS. 1208 00:51:49,639 --> 00:51:51,074 WHEN YOU KNOW ABOUT HARMS THAT 1209 00:51:51,141 --> 00:51:52,742 YOU ARE DOING EVERY DAY IN 1210 00:51:52,809 --> 00:51:55,011 MEDICINE, WE HAVE TO FIGURE OUT 1211 00:51:55,078 --> 00:52:02,953 HOW WE CAN FIX THESE AS FAST AS 1212 00:52:03,019 --> 00:52:04,921 POSSIBLE, AND SO WE'RE BECAUSE 1213 00:52:04,988 --> 00:52:06,456 WE'VE USED GENETICALLY PREDICTED 1214 00:52:06,523 --> 00:52:07,624 GENE EXPRESSION SO MUCH, WE'RE 1215 00:52:07,691 --> 00:52:09,125 REALLY USED TO THE IDEA OF 1216 00:52:09,192 --> 00:52:10,694 SEPARATING OUT THE GENETIC 1217 00:52:10,760 --> 00:52:13,129 COMPONENT FROM ALL OF THE OTHER 1218 00:52:13,196 --> 00:52:17,501 THINGS THAT INFLUENCE GENE 1219 00:52:17,567 --> 00:52:19,269 EXPRESSION. 1220 00:52:19,336 --> 00:52:21,938 AND I THINK AS IMENET CYSTS 1221 00:52:22,005 --> 00:52:23,740 WE'RE FOCUSED ON THE VASE VERY 1222 00:52:23,807 --> 00:52:25,442 HEAVILY BUT WE CAN USE THE 1223 00:52:25,509 --> 00:52:29,312 GENETICS TO SEE MUCH BETTER THE 1224 00:52:29,379 --> 00:52:30,714 CONSEQUENCES OF THINGS LIKE 1225 00:52:30,780 --> 00:52:32,549 ENVIRONMENTAL EXPOSURES AND 1226 00:52:32,616 --> 00:52:34,351 SOCIAL DETERMINANTS OF HEALTH 1227 00:52:34,417 --> 00:52:38,488 AND LEARN THAT BIOLOGY AND WHEN 1228 00:52:38,555 --> 00:52:40,790 THE GENETICS IS NOISE FOR HOW WE 1229 00:52:40,857 --> 00:52:43,727 USE A LABORATORY VALUE IN 1230 00:52:43,793 --> 00:52:45,495 MEDICINE, WE SHOULDN'T HESITATE 1231 00:52:45,562 --> 00:52:45,962 TO REMOVE IT. 1232 00:52:46,029 --> 00:52:51,535 WE DO A LOT OF THINGS WITH 1233 00:52:51,601 --> 00:52:52,602 LABORATORY VALUES UNDER THE HOOD 1234 00:52:52,669 --> 00:52:56,072 O WHAT COMES BACK FROM THE 1235 00:52:56,139 --> 00:52:57,073 LABORATORY THAT'S ORDERED OFTEN 1236 00:52:57,140 --> 00:52:58,475 GOES THROUGH SOME EQUATION 1237 00:52:58,542 --> 00:53:01,177 BEFORE THAT IS SUBMITTED TO THE 1238 00:53:01,244 --> 00:53:01,945 PHYSICIAN TO INTERPRET. 1239 00:53:02,012 --> 00:53:03,647 ALL WE WOULD BE DOING IS 1240 00:53:03,713 --> 00:53:05,382 REGRESSING OUT THE GENETICS THIS 1241 00:53:05,448 --> 00:53:10,887 THAT SAME KIND OF EQUATION. 1242 00:53:10,954 --> 00:53:17,694 SO YOU COULD THINK ABOUT THIS AS 1243 00:53:17,761 --> 00:53:18,194 INDIVIDUALIZING GENETIC 1244 00:53:18,261 --> 00:53:19,195 DIFFERENCES, CHANGES IN THE 1245 00:53:19,262 --> 00:53:20,263 INDIVIDUAL REFERENCE RANGES THAT 1246 00:53:20,330 --> 00:53:21,998 ARE PROVIDED TO PHYSICIANS AND 1247 00:53:22,065 --> 00:53:22,699 OUR PHYSICIAN SCIENTISTS THINK 1248 00:53:22,766 --> 00:53:24,568 THAT IS THE BEST WAY TO DO IT, 1249 00:53:24,634 --> 00:53:28,772 BECAUSE IT WOULD HELP PHYSICIANS 1250 00:53:28,838 --> 00:53:29,940 INTERNALIZE HOW DIVERSE THEIR 1251 00:53:30,006 --> 00:53:31,041 POP EULOGIES ACTUALLY ARE WITH 1252 00:53:31,107 --> 00:53:32,876 RESPECT TO THESE MEASURES, THEY 1253 00:53:32,943 --> 00:53:35,946 WOULD LEARN AND UNDERSTAND MORE 1254 00:53:36,012 --> 00:53:38,381 ABOUT GENETIC DIVERSITY IN 1255 00:53:38,448 --> 00:53:38,982 LABORATORY MEASUREMENTS BUT I 1256 00:53:39,049 --> 00:53:42,519 HAVE TO TELL YOU PHYSICIANS WHO 1257 00:53:42,586 --> 00:53:45,455 HAVE 9 OR 10 CLINICS A WEEK, 1258 00:53:45,522 --> 00:53:47,123 HEAR THAT AND THEY'RE LIKE, ARE 1259 00:53:47,190 --> 00:53:47,457 YOU NUTS? 1260 00:53:47,524 --> 00:53:49,826 I DON'T WANT TO SEE A MILLION 1261 00:53:49,893 --> 00:53:52,095 DIFFERENT REFERENCE RANGES FROM 1262 00:53:52,162 --> 00:53:53,463 MY PATIENTS, NO. 1263 00:53:53,530 --> 00:53:55,765 IF YOU THINK THIS IS DESTROYING 1264 00:53:55,832 --> 00:53:57,534 MY ABILITY TO INTERPRET 1265 00:53:57,601 --> 00:53:58,969 LABORATORY VALUES, TAKE THAT 1266 00:53:59,035 --> 00:53:59,836 GENETICS OUT, BLOW THE 1267 00:53:59,903 --> 00:54:01,304 DISTRIBUTION BACK UP TO WHAT I 1268 00:54:01,371 --> 00:54:02,839 EXPECT AND LET ME USE THE 1269 00:54:02,906 --> 00:54:04,240 REFERENCE RANGES THAT I'M 1270 00:54:04,307 --> 00:54:05,675 FAMILIAR WITH AND KNOW HOW TO 1271 00:54:05,742 --> 00:54:06,076 DEAL WITH. 1272 00:54:06,142 --> 00:54:07,911 SO I THINK WHAT WE NEED TO DO IS 1273 00:54:07,978 --> 00:54:12,682 STUDY TO REALLY LOOK AT 1274 00:54:12,749 --> 00:54:13,750 PHYSICIANS AND THINK ABOUT HOW 1275 00:54:13,817 --> 00:54:16,052 WE TRY TO FIX THIS BUT IT HAS TO 1276 00:54:16,119 --> 00:54:17,687 BE DONE UNDER THE HOOD, IT HAS 1277 00:54:17,754 --> 00:54:19,456 TO BE DONE IN A WAY THAT DOESN'T 1278 00:54:19,522 --> 00:54:21,391 REQUIRE PHYSICIANS TO KNOW AND 1279 00:54:21,458 --> 00:54:23,259 UNDERSTAND THE GENETICS OF DUFFY 1280 00:54:23,326 --> 00:54:25,662 IN ORDINANCE NUMBERER TO 1281 00:54:25,729 --> 00:54:27,163 INTERPRET A WHITE CELL COUNT. 1282 00:54:27,230 --> 00:54:30,033 AND HERE'S A RECEIPT PUBLICATION 1283 00:54:30,100 --> 00:54:31,568 THAT SHOWS THE DISTRIBUTION MUCH 1284 00:54:31,635 --> 00:54:33,770 WHITE CELL COUNTS IN DUFFY 1285 00:54:33,837 --> 00:54:34,604 HOMOZYGOTES RELATIVE TO THE 1286 00:54:34,671 --> 00:54:40,510 MEANS FOR THE POPULATION AT 1287 00:54:40,577 --> 00:54:41,177 LARNG.- 1288 00:54:41,244 --> 00:54:41,945 -LARGE. 1289 00:54:42,012 --> 00:54:43,580 SO IT'S A BIG EFFECT ON A SINGLE 1290 00:54:43,647 --> 00:54:46,416 ARK LEGAL ON A COMMONLY USED 1291 00:54:46,483 --> 00:54:46,783 BIOMARKER. 1292 00:54:46,850 --> 00:54:48,618 AND I DO WANT TO SHOUT OUT TO MY 1293 00:54:48,685 --> 00:54:49,686 COLLEAGUES IN THE HEALTH 1294 00:54:49,753 --> 00:54:51,121 DISPARITIES RESEARCH THAT WE DO, 1295 00:54:51,187 --> 00:54:55,091 I'VE BEEN WORKING WITH CONSWALA 1296 00:54:55,158 --> 00:54:57,560 WILKINS, SHE WAS THE FITTER 1297 00:54:57,627 --> 00:54:59,396 NONGENETICIST TO ASK ME TO 1298 00:54:59,462 --> 00:55:00,664 COLLABORATE ON STUDIES SHE WAS 1299 00:55:00,730 --> 00:55:02,132 DOING AND SHE ALWAYS TELLS THE 1300 00:55:02,198 --> 00:55:03,867 FUNNY STORY THAT SHE HAD TO WORK 1301 00:55:03,933 --> 00:55:06,269 UP THE COURAGE TO SAY TO ME 1302 00:55:06,336 --> 00:55:07,771 WHILE WE'RE PLANNING OUR FIRST 1303 00:55:07,837 --> 00:55:10,206 GRANT, NANCY, I DON'T REALLY 1304 00:55:10,273 --> 00:55:11,708 THINK GENETICS HAVE VERY MUCH TO 1305 00:55:11,775 --> 00:55:14,644 DO WITH HEALTH DISPARITIES, I 1306 00:55:14,711 --> 00:55:16,846 WAS LIKE OH YEAH, ME EITHER, BUT 1307 00:55:16,913 --> 00:55:17,681 THEY'RE MOSTLY ABOUT OTHER 1308 00:55:17,747 --> 00:55:21,251 THINGS ABOUT YOU WE DON'T WANT 1309 00:55:21,317 --> 00:55:22,786 TO LEAVE ON THE TABLE ANYTHING 1310 00:55:22,852 --> 00:55:26,289 THAT WE COULD FIX USING 1311 00:55:26,356 --> 00:55:26,856 GENETICS. 1312 00:55:26,923 --> 00:55:31,561 AND SO THAT'S BEEN OUR MANTRA 1313 00:55:31,628 --> 00:55:32,796 THROUGH--NOW 2 GENERATIONS OF 1314 00:55:32,862 --> 00:55:35,265 STUDIES AND THEN OUR EPIC PRS 1315 00:55:35,331 --> 00:55:37,133 GROUP THAT'S PART OF THE PRIMED 1316 00:55:37,200 --> 00:55:38,768 CONSORTIUM, WE WERE ALL OVER 1317 00:55:38,835 --> 00:55:40,970 THIS, IN THIS GRANT AND THEY 1318 00:55:41,037 --> 00:55:42,372 REALLY HAVE THOUGHT OF VERY 1319 00:55:42,439 --> 00:55:44,007 CLEVER WAYS OF TRYING TO GET AT 1320 00:55:44,074 --> 00:55:45,075 SOME OF THESE THINGS AND IT'S 1321 00:55:45,141 --> 00:55:47,243 BEEN A REAL PLEASURE TO WORK 1322 00:55:47,310 --> 00:55:51,548 BOTH IN THAT CONSORTIUM AND IN 1323 00:55:51,614 --> 00:55:52,716 THIS GROUP AND MY FUNDING AND 1324 00:55:52,782 --> 00:55:54,951 HAPPY TO TAKE QUESTIONS. 1325 00:55:55,018 --> 00:55:55,952 I THOUGHT I WOULD LEAVE MORE 1326 00:55:56,019 --> 00:55:58,588 TIME BUT DO I GET CARRIED AWAY 1327 00:55:58,655 --> 00:56:00,623 WITH THIS STUFF. 1328 00:56:00,690 --> 00:56:02,092 REALLY, APOLOGIZE, I SHOULD HAVE 1329 00:56:02,158 --> 00:56:04,461 LEFT MORE TIME FOR QUESTIONS. 1330 00:56:04,527 --> 00:56:12,669 [ APPLAUSE ] 1331 00:56:12,736 --> 00:56:14,437 >> SO WHILE WE'RE WAITING FOR 1332 00:56:14,504 --> 00:56:16,406 HER TO FIND QUESTIONS ONLINE, 1333 00:56:16,473 --> 00:56:17,474 ARE THERE QUESTIONS FROM THE 1334 00:56:17,540 --> 00:56:17,741 AUDIENCE. 1335 00:56:17,807 --> 00:56:19,709 >> I WAS GOING TO SAY, WE DO 1336 00:56:19,776 --> 00:56:22,245 HAVE A FEW MINUTES, PLEASE COME 1337 00:56:22,312 --> 00:56:23,847 TO THE MICROPHONE AND PEOPLE 1338 00:56:23,913 --> 00:56:25,648 HERE IN PERSON, THERE WILL BE A 1339 00:56:25,715 --> 00:56:26,916 RECEPTION RIGHT AFTER THIS, SO 1340 00:56:26,983 --> 00:56:29,719 JUST IF 5 MINUTES WE CAN DO 1341 00:56:29,786 --> 00:56:31,321 QUESTIONS THEN. 1342 00:56:31,387 --> 00:56:32,388 AND PEOPLE ONLINE, PLEASE FEEL 1343 00:56:32,455 --> 00:56:33,223 FREE TO SUBMIT YOUR QUESTIONS 1344 00:56:33,289 --> 00:56:35,258 AND WE WILL SEE WHAT WE CAN DO. 1345 00:56:35,325 --> 00:56:35,558 SO GO AHEAD. 1346 00:56:35,625 --> 00:56:38,895 NTHANK 1347 00:56:38,962 --> 00:56:39,162 -- 1348 00:56:39,229 --> 00:56:41,664 >> THANK YOU VERY MUCH, NANCY I 1349 00:56:41,731 --> 00:56:42,632 AM [INDISCERNIBLE] FROM NIMHD 1350 00:56:42,699 --> 00:56:45,602 AND I WOULD LIKE TO ASK YOU DO 1351 00:56:45,668 --> 00:56:48,605 YOU THINK THAT HAVING REFERENCE 1352 00:56:48,671 --> 00:56:54,410 VALUES FOR DIVERSE POPULATIONS 1353 00:56:54,477 --> 00:56:58,047 OR FOR LET'S SAY DIFFERENT 1354 00:56:58,114 --> 00:57:08,057 GENDERS AND DIFFERENT TIMES, 1355 00:57:08,124 --> 00:57:09,325 DIFFERENT AGES WILL DO AS 1356 00:57:09,392 --> 00:57:10,426 OPPOSED TO WHAT WE'RE USING 1357 00:57:10,493 --> 00:57:12,529 RIGHT NOW BEFORE WE HAVE TO GET 1358 00:57:12,595 --> 00:57:14,464 TO THE POINT THAT YOU'RE TALKING 1359 00:57:14,531 --> 00:57:17,100 ABOUT WHERE YOU HAVE-- 1360 00:57:17,167 --> 00:57:20,003 >> ACTUALLY NO. 1361 00:57:20,069 --> 00:57:29,112 SO I'M UNEASY THAT THAT'S 1362 00:57:29,179 --> 00:57:30,680 A--ONE-SIZE-FITS-ALL KIND OF 1363 00:57:30,747 --> 00:57:31,648 SOLUTION THAT WON'T FIT ANYBODY. 1364 00:57:31,714 --> 00:57:34,851 AND I MEAN THAT SINCERELY FOR 1365 00:57:34,918 --> 00:57:39,355 THE SUBSTANTIAL FRACTION OF 1366 00:57:39,422 --> 00:57:44,828 LABORATORY VALUES THAT ARE 1367 00:57:44,894 --> 00:57:46,462 HERITABLE, THE IDEA OF REFERENCE 1368 00:57:46,529 --> 00:57:49,532 RANGES THAT TRY TO USE JUST 1369 00:57:49,599 --> 00:57:52,135 POPULATION LEVEL INFORMATION, IS 1370 00:57:52,202 --> 00:57:55,438 GOING TO BE AT BEST MISLEADING 1371 00:57:55,505 --> 00:57:57,907 AND MOSTLY WRONG FOR EVERYBODY. 1372 00:57:57,974 --> 00:57:59,142 BUT IS IT GOING TO BE BETTER 1373 00:57:59,209 --> 00:58:04,681 THAN WHAT WE HAVE RIGHT NOW? 1374 00:58:04,747 --> 00:58:06,149 >> I DOUBT IT. 1375 00:58:06,216 --> 00:58:09,352 I MEAN BECAUSE I'LL SAY, WE USED 1376 00:58:09,419 --> 00:58:13,890 TO USE RACE IN THE CREATEININE 1377 00:58:13,957 --> 00:58:15,692 CALCULATION OF ESTIMATED 1378 00:58:15,758 --> 00:58:16,726 GLOMULAR MARULAR FILTRATION AND 1379 00:58:16,793 --> 00:58:22,832 THAT WAS NOT BETTER BECAUSE IT 1380 00:58:22,899 --> 00:58:25,935 WAS NOT ABOUT THE ACTUAL 1381 00:58:26,002 --> 00:58:26,870 BIOLOGY. 1382 00:58:26,936 --> 00:58:29,606 IT DISADVANTAGED POPULATIONS OF 1383 00:58:29,672 --> 00:58:32,342 RECENT AFRICAN ANCESTRIES, AND 1384 00:58:32,408 --> 00:58:35,011 REALLY PROMINENT WAYS THAT 1385 00:58:35,078 --> 00:58:37,313 ALMOST CERTAINLY KEPT PEOPLE WHO 1386 00:58:37,380 --> 00:58:40,216 NEEDED KIDNEY TRANSPLANTS FROM 1387 00:58:40,283 --> 00:58:40,850 GETTING THEM. 1388 00:58:40,917 --> 00:58:44,287 TAKING RACE OUT OF THAT 1389 00:58:44,354 --> 00:58:45,555 EQUATION, DOESN'T REMOVE THE BIG 1390 00:58:45,622 --> 00:58:49,626 MEAN DIFFERENCES THAT ARE THERE. 1391 00:58:49,692 --> 00:58:51,394 PEOPLE ARE STILL DISADVANTAGED 1392 00:58:51,461 --> 00:58:57,166 BY THE GENETICS BUT 1393 00:58:57,233 --> 00:58:58,835 THEY'RE--THEY'RE NOT 1394 00:58:58,902 --> 00:59:01,771 DISADVANTAGED IN A PARTICULAR 1395 00:59:01,838 --> 00:59:03,539 RACE BASED WAY, THEY'RE 1396 00:59:03,606 --> 00:59:05,408 DISADVANTAGED BY THE GENETICS 1397 00:59:05,475 --> 00:59:08,044 THAT WE FAIL TO ADEQUATELY 1398 00:59:08,111 --> 00:59:17,153 ACCOMMODATE IN THE WAY WE DO THE 1399 00:59:17,220 --> 00:59:17,487 CALCULATIONS. 1400 00:59:17,553 --> 00:59:19,055 I THINK THAT MORE INDIVIDUALIZED 1401 00:59:19,122 --> 00:59:20,657 REFERENCE RANGES FOR THINGS LIKE 1402 00:59:20,723 --> 00:59:24,160 SEX AND AGE, MAKE A LOT OF 1403 00:59:24,227 --> 00:59:27,297 SENSE. 1404 00:59:27,363 --> 00:59:30,466 BUT I'M UNEASY ABOUT POPULATION 1405 00:59:30,533 --> 00:59:36,172 BASED REFERENCE RANGES THAT 1406 00:59:36,239 --> 00:59:38,841 WOULD CAPITALIZE ON ALLELE 1407 00:59:38,908 --> 00:59:44,280 FREQUENCY DIFFERENCES AMONG 1408 00:59:44,347 --> 00:59:45,214 POPULATIONS BECAUSE THOSE REALLY 1409 00:59:45,281 --> 00:59:47,116 DON'T WORK FOR ANY INDIVIDUAL. 1410 00:59:47,183 --> 00:59:51,187 YOU HAVE TO KNOW THE ALLELES, 1411 00:59:51,254 --> 00:59:55,358 AND SO, I THINK, YEAH, WOULDN'T 1412 00:59:55,425 --> 00:59:56,859 THEY BE BETTER? 1413 00:59:56,926 --> 01:00:00,697 IN MOST CASES I'M SKEPTICAL THEY 1414 01:00:00,763 --> 01:00:01,631 WOULD BE BETTER. 1415 01:00:01,698 --> 01:00:02,765 MAYBE FOR THINGS LIKE AGE AND 1416 01:00:02,832 --> 01:00:08,004 SEX WHEN THOSE HAVE A PROMINENT 1417 01:00:08,071 --> 01:00:12,875 ROLE IN THE INTERPRETATION OF 1418 01:00:12,942 --> 01:00:14,177 THE BIOMARKER BUT, YOU KNOW IF 1419 01:00:14,243 --> 01:00:15,678 IT'S REALLY JUST ABOUT AGE AND 1420 01:00:15,745 --> 01:00:18,748 REALLY JUST ABOUT GENDER, YEAH, 1421 01:00:18,815 --> 01:00:21,217 WE SHOULD BE DOING THINGS LIKE 1422 01:00:21,284 --> 01:00:22,385 THAT. 1423 01:00:22,452 --> 01:00:23,386 >> OKAY, THANK YOU. 1424 01:00:23,453 --> 01:00:25,621 NSO WE HIT THE 3:00 MARK. 1425 01:00:25,688 --> 01:00:27,657 ARE YOU COMING DOWN FOR A 1426 01:00:27,724 --> 01:00:28,825 QUESTION? 1427 01:00:28,891 --> 01:00:29,659 SO WE'LL UNFORTUNATELY HAVE THIS 1428 01:00:29,726 --> 01:00:32,962 BE OUR LAST QUESTION, BUT AGAIN, 1429 01:00:33,029 --> 01:00:34,731 AVAILABILITY IN THE--FOR THE 1430 01:00:34,797 --> 01:00:37,500 RECEPTION OUTSIDE. 1431 01:00:37,567 --> 01:00:37,900 GO AHEAD. 1432 01:00:37,967 --> 01:00:40,703 >> I WANT TO THANK YOU FOR A 1433 01:00:40,770 --> 01:00:42,238 BEAUTIFUL TALK EMPLOY I'VE BEEN 1434 01:00:42,305 --> 01:00:47,643 TRYING HERE AT NIH THE PAST 2 1435 01:00:47,710 --> 01:00:54,617 YEARS TO GET PEOPLE HERE TO GET 1436 01:00:54,684 --> 01:00:56,919 THEMSELVES A WHOLE GENOME 1437 01:00:56,986 --> 01:00:59,689 SEQUENCE INCLUDING ALL THE RNA, 1438 01:00:59,756 --> 01:01:09,532 ET CETERA, AND EXPRESSION. 1439 01:01:09,599 --> 01:01:12,468 YOUR EXAMPLES, YOU'RE USING A 1440 01:01:12,535 --> 01:01:13,970 LOT OF EUPHEMISMS IN YOUR 1441 01:01:14,037 --> 01:01:15,972 EXAMPLES BUT BASICALLY IT COMES 1442 01:01:16,039 --> 01:01:20,977 DOWN TO YOU HAVE TO DIAGNOSE 1443 01:01:21,044 --> 01:01:23,413 FIRST, TREAT SECOND, NOT THE 1444 01:01:23,479 --> 01:01:24,714 OTHER WAY AROUND AND SO JUST 1445 01:01:24,781 --> 01:01:28,418 THANK YOU AGAIN FOR YOUR TALK. 1446 01:01:28,484 --> 01:01:28,985 >> THANK YOU. 1447 01:01:29,052 --> 01:01:31,788 >> SO HAPPY TO ANSWER QUESTIONS 1448 01:01:31,854 --> 01:01:34,457 USED AND IF ANYBODY LISTENING IN 1449 01:01:34,524 --> 01:01:35,725 HAS QUESTIONS THAT THEY DIDN'T 1450 01:01:35,792 --> 01:01:37,393 GET TO ASK OR THINK OF LATER, 1451 01:01:37,460 --> 01:01:40,563 I'M HAPPY FOR THEM TO E-MAIL AND 1452 01:01:40,630 --> 01:01:41,964 WE'LL DEFINITELY RESPOND. 1453 01:01:42,031 --> 01:01:43,066 >> SO WONDER. 1454 01:01:43,132 --> 01:01:44,834 SO LET'S THANK DR. COX AGAIN. 1455 01:01:44,901 --> 01:01:45,501 [ APPLAUSE ] 1456 01:01:45,568 --> 01:01:47,603 AND I WILL NOTE TO THE SIDE, 1457 01:01:47,670 --> 01:01:49,472 NANCY IF YOU CAN POINT FOR ME, 1458 01:01:49,539 --> 01:01:51,707 WE HAVE A WALS PLAQUE WHICH WE 1459 01:01:51,774 --> 01:01:53,509 WILL MAIL TO HER AND NOT MAKE 1460 01:01:53,576 --> 01:01:55,378 HER CARRY ON HER CARRY HOME, BUT 1461 01:01:55,445 --> 01:01:56,679 THANK YOU GANNA FOR EVERYONE WHO 1462 01:01:56,746 --> 01:01:58,848 CAME IN, PLEASE PICK UP THE LIST 1463 01:01:58,915 --> 01:02:00,383 OF UPCOMING WALS, I WAS LOOKING 1464 01:02:00,450 --> 01:02:01,784 AT IT, VERY IMPRESSIVE LINE UP 1465 01:02:01,851 --> 01:02:03,186 ON YOUR WAY OUT AND PLEASE YOIN 1466 01:02:03,252 --> 01:02:05,955 US FOR THE RECEPTION AND 1467 01:02:06,022 --> 01:02:06,589 EVERYBODY PARTICIPATING ONLINE, 1468 01:02:06,656 --> 01:02:07,390 WE APPRECIATE YOURCANDIDATES 1469 01:02:07,457 --> 01:02:08,891 JOINING US THIS AFTERNOON. 1470 01:02:08,958 THANK YOU.