1 00:00:01,040 --> 00:00:03,664 Some of my most wonderful memories of childhood 2 00:00:03,664 --> 00:00:06,968 are of spending time with my grandmother, Mamar [???], 3 00:00:06,968 --> 00:00:10,768 in our four-family home in Brooklyn, New York. 4 00:00:10,768 --> 00:00:13,720 Her apartment was an oasis. 5 00:00:13,720 --> 00:00:16,289 It was a place where I could sneak a cup of coffee, 6 00:00:16,289 --> 00:00:19,600 which was really warm milk with just a touch of caffeine. 7 00:00:19,600 --> 00:00:21,888 She loved life. 8 00:00:21,888 --> 00:00:24,798 And although she worked in a factory, 9 00:00:24,798 --> 00:00:27,970 she saved her pennies and she traveled to Europe. 10 00:00:27,970 --> 00:00:31,608 And I remember poring over those pictures with her 11 00:00:31,608 --> 00:00:34,935 and then dancing with her to her favorite music. 12 00:00:34,935 --> 00:00:39,864 And then, when I was eight and she was sixty, 13 00:00:39,864 --> 00:00:42,024 something changed. 14 00:00:42,024 --> 00:00:44,440 She no longer worked or traveled. 15 00:00:44,440 --> 00:00:46,408 She no longer danced. 16 00:00:46,408 --> 00:00:48,992 There were no more coffee times. 17 00:00:48,992 --> 00:00:51,408 My mother missed work and took her to doctors 18 00:00:51,408 --> 00:00:53,578 who couldn't make a diagnosis. 19 00:00:53,578 --> 00:00:58,976 And my father, who worked at night, would spend every afternoon with her -- 20 00:00:58,976 --> 00:01:02,008 just to make sure she ate. 21 00:01:02,008 --> 00:01:06,576 Her care became all-consuming for our family. 22 00:01:06,576 --> 00:01:08,840 And by the time a diagnosis was made, 23 00:01:08,840 --> 00:01:10,928 she was in a deep spiral. 24 00:01:10,928 --> 00:01:14,489 Now many of you will recognize her symptoms. 25 00:01:14,489 --> 00:01:17,352 My grandmother had depression. 26 00:01:17,352 --> 00:01:20,688 A deep, life-altering depression, 27 00:01:20,688 --> 00:01:23,456 from which she never recovered. 28 00:01:23,456 --> 00:01:27,592 And back then, so little was known about depression. 29 00:01:27,592 --> 00:01:30,136 But even today, 50 years later, 30 00:01:30,136 --> 00:01:33,656 there's still so much more to learn. 31 00:01:33,656 --> 00:01:38,840 Today, we know women are 70 percent more likely 32 00:01:38,840 --> 00:01:42,216 to experience depression over their lifetimes 33 00:01:42,216 --> 00:01:44,112 compared with men. 34 00:01:44,112 --> 00:01:47,168 And even with this high prevalence, 35 00:01:47,168 --> 00:01:53,024 women are misdiagnosed between 30 and 50 percent of the time. 36 00:01:53,024 --> 00:01:56,480 Now we know that women are more likely 37 00:01:56,480 --> 00:02:01,056 to experience the symptoms of fatigue, sleep disturbance, 38 00:02:01,056 --> 00:02:04,736 pain and anxiety compared with men. 39 00:02:04,736 --> 00:02:07,112 And these symptoms are often overlooked 40 00:02:07,112 --> 00:02:10,106 as symptoms of depression. 41 00:02:10,106 --> 00:02:14,032 And it isn't only depression in which these sex differences occur, 42 00:02:14,032 --> 00:02:18,090 but they occur across so many diseases. 43 00:02:18,090 --> 00:02:20,512 So it's my grandmother's struggles 44 00:02:20,512 --> 00:02:23,936 that have really led me on a lifelong quest. 45 00:02:23,936 --> 00:02:27,395 And today, I lead a center in which the mission 46 00:02:27,395 --> 00:02:31,128 is to discover why these sex differences occur 47 00:02:31,128 --> 00:02:33,106 and to use that knowledge 48 00:02:33,106 --> 00:02:36,112 to improve the health of women. 49 00:02:36,112 --> 00:02:40,168 Today, we know that every cell has a sex. 50 00:02:40,168 --> 00:02:44,136 Now, that's a term coined by the Institute of Medicine. 51 00:02:44,136 --> 00:02:47,728 And what it means is that men and women are different 52 00:02:47,728 --> 00:02:52,216 down to the cellular and molecular levels. 53 00:02:52,216 --> 00:02:57,264 It means that we're different across all of our organs. 54 00:02:57,264 --> 00:03:01,728 From our brains to our hearts, our lungs, our joints. 55 00:03:01,728 --> 00:03:07,184 Now, it was only 20 years ago that we 56 00:03:07,184 --> 00:03:10,424 hardly had any data on women's health 57 00:03:10,424 --> 00:03:13,383 beyond our reproductive functions. 58 00:03:13,383 --> 00:03:15,992 But then in 1993, 59 00:03:15,992 --> 00:03:20,712 the NIH Revitalization Act was signed into law. 60 00:03:20,712 --> 00:03:23,376 And what this law did was it mandated 61 00:03:23,376 --> 00:03:27,957 that women and minorities be included in clinical trials 62 00:03:27,957 --> 00:03:32,001 that were funded by the National Institutes of Health. 63 00:03:32,001 --> 00:03:34,904 And in many ways, the law has worked. 64 00:03:34,904 --> 00:03:38,420 Women are now routinely included in clinical studies, 65 00:03:38,420 --> 00:03:40,856 and we've learned that there are major differences 66 00:03:40,856 --> 00:03:42,841 in the ways that women and men 67 00:03:42,841 --> 00:03:45,162 experience disease. 68 00:03:45,162 --> 00:03:47,112 But remarkably, 69 00:03:47,112 --> 00:03:52,016 what we have learned about these differences is often overlooked. 70 00:03:52,016 --> 00:03:56,616 So, we have to ask ourselves the question: 71 00:03:56,616 --> 00:04:00,928 Why leave women's health to chance? 72 00:04:00,928 --> 00:04:03,787 And we're leaving it to chance in two ways. 73 00:04:03,787 --> 00:04:07,408 The first is that there is so much more to learn 74 00:04:07,408 --> 00:04:09,816 and we're not making the investment 75 00:04:09,816 --> 00:04:14,107 in fully understanding the extent of these sex differences. 76 00:04:14,107 --> 00:04:18,736 And the second is that we aren't taking what we have learned, 77 00:04:18,736 --> 00:04:22,256 and routinely applying it in clinical care. 78 00:04:22,256 --> 00:04:26,168 We are just not doing enough. 79 00:04:26,168 --> 00:04:28,488 So, I'm going to share with you three examples 80 00:04:28,488 --> 00:04:32,256 of where sex differences have impacted the health of women, 81 00:04:32,256 --> 00:04:34,572 and where we need to do more. 82 00:04:34,572 --> 00:04:37,008 Let's start with heart disease. 83 00:04:37,008 --> 00:04:41,957 It's the number one killer of women in the United States today. 84 00:04:41,957 --> 00:04:45,342 This is the face of heart disease. 85 00:04:45,344 --> 00:04:47,563 Linda is a middle-aged woman, 86 00:04:47,563 --> 00:04:49,979 who had a stent placed in one of the arteries 87 00:04:49,979 --> 00:04:52,088 going to her heart. 88 00:04:52,088 --> 00:04:55,330 When she had recurring symptoms she went back to her doctor. 89 00:04:55,330 --> 00:04:57,168 Her doctor did the gold-standard test -- 90 00:04:57,168 --> 00:05:00,424 a cardiac catheterization. 91 00:05:00,424 --> 00:05:02,688 It showed no blockages. 92 00:05:02,688 --> 00:05:04,944 Linda's symptoms continued. 93 00:05:04,944 --> 00:05:07,248 She had to stop working. 94 00:05:07,248 --> 00:05:10,080 And that's when she found us. 95 00:05:10,080 --> 00:05:14,240 When Lynda came to us, we did another cardiac catheterization 96 00:05:14,240 --> 00:05:17,488 and this time, we found clues. 97 00:05:17,488 --> 00:05:20,084 But we needed another test 98 00:05:20,084 --> 00:05:22,496 to make the diagnosis. 99 00:05:22,496 --> 00:05:27,136 So we did a test called an intracoronary ultrasound, 100 00:05:27,136 --> 00:05:29,904 where you use soundwaves to look at the artery 101 00:05:29,904 --> 00:05:32,480 from the inside out. 102 00:05:32,480 --> 00:05:34,479 And what we found 103 00:05:34,479 --> 00:05:36,776 was that Linda's disease didn't look like 104 00:05:36,776 --> 00:05:39,432 the typical male disease. 105 00:05:39,432 --> 00:05:43,015 The typical male disease looks like this. 106 00:05:43,015 --> 00:05:46,370 There's a discrete blockage or stenosis. 107 00:05:46,370 --> 00:05:50,578 Linda's disease, like the disease of so many women, 108 00:05:50,578 --> 00:05:52,899 looks like this. 109 00:05:52,899 --> 00:05:55,880 The plaque is laid down more evenly, more diffusely 110 00:05:55,880 --> 00:05:59,776 along the artery, and it's harder to see. 111 00:05:59,776 --> 00:06:03,104 So for Linda, and for so many women, 112 00:06:03,104 --> 00:06:06,904 the gold-standard test wasn't gold. 113 00:06:06,904 --> 00:06:09,953 Now, Lynda received the right treatment. 114 00:06:09,953 --> 00:06:11,792 She went back to her life and fortunately, today 115 00:06:11,792 --> 00:06:14,096 she is doing well. 116 00:06:14,096 --> 00:06:15,504 But Lynda was lucky. 117 00:06:15,504 --> 00:06:18,176 She found us, we found her disease. 118 00:06:18,176 --> 00:06:21,180 But for too many women, that's not the case. 119 00:06:21,180 --> 00:06:23,448 We have the tools. 120 00:06:23,448 --> 00:06:26,960 We have the technology to make the diagnosis. 121 00:06:26,960 --> 00:06:30,249 But it's all too often that these sex diffferences 122 00:06:30,249 --> 00:06:31,816 are overlooked. 123 00:06:31,816 --> 00:06:34,726 So what about treatment? 124 00:06:34,726 --> 00:06:37,544 A landmark study that was published two years ago 125 00:06:37,544 --> 00:06:40,120 asked the very important question: 126 00:06:40,120 --> 00:06:45,056 What are the most effective treatments for heart disease in women? 127 00:06:45,056 --> 00:06:48,665 The authors looked at papers written over a 10-year period, 128 00:06:48,665 --> 00:06:51,312 and hundreds had to be thrown out. 129 00:06:51,312 --> 00:06:55,578 And what they found out was that of those that were tossed out, 130 00:06:55,578 --> 00:06:59,432 65 percent were excluded 131 00:06:59,432 --> 00:07:04,072 because even though women were included in the studies, 132 00:07:04,072 --> 00:07:10,336 the analysis didn't differentiate between women and men. 133 00:07:10,336 --> 00:07:13,281 What a lost opportunity. 134 00:07:13,281 --> 00:07:15,665 The money had been spent 135 00:07:15,665 --> 00:07:17,904 and we didn't learn how women fared -- 136 00:07:17,904 --> 00:07:20,659 and these studies could not contribute one iota 137 00:07:20,659 --> 00:07:23,215 to the very, very important question: 138 00:07:23,215 --> 00:07:25,436 What are the most effective treatments 139 00:07:25,436 --> 00:07:28,608 for heart disease in women? 140 00:07:28,608 --> 00:07:33,408 I want to introduce you to Hortense [???], my godmother, 141 00:07:33,408 --> 00:07:37,312 Hung Way [???], a relative of a colleague, 142 00:07:37,312 --> 00:07:39,488 and somebody you may recognize -- 143 00:07:39,488 --> 00:07:43,120 Dana, Christopher Reeve's wife. 144 00:07:43,120 --> 00:07:47,480 All three women have something very important in common. 145 00:07:47,480 --> 00:07:51,224 All three were diagnosed with lung cancer, 146 00:07:51,224 --> 00:07:53,984 the number one cancer killer of women 147 00:07:53,984 --> 00:07:56,808 in the United States today. 148 00:07:56,808 --> 00:08:00,546 All three were non-smokers. 149 00:08:00,546 --> 00:08:05,048 Sadly, Dana and Hung Way [???] died of their disease. 150 00:08:05,048 --> 00:08:11,251 Today, what we know is that women who are non-smokers are three times more likely 151 00:08:11,251 --> 00:08:14,665 to be diagnosed with lung cancer than are men 152 00:08:14,665 --> 00:08:16,867 who are non-smokers. 153 00:08:16,867 --> 00:08:20,280 Now interestingly, when women are diagnosed with lung cancer, 154 00:08:20,280 --> 00:08:23,520 their survival tends to be better than that of men. 155 00:08:23,520 --> 00:08:25,272 Now here are some clues. 156 00:08:25,272 --> 00:08:27,656 Our investigators have found that there are 157 00:08:27,656 --> 00:08:32,128 certain genes in the lung tumor cells of both women and men. 158 00:08:32,128 --> 00:08:34,504 And these genes are activated 159 00:08:34,504 --> 00:08:36,872 mainly by estrogen. 160 00:08:36,872 --> 00:08:39,520 And when these genes are over-expressed, 161 00:08:39,520 --> 00:08:42,344 it's associated with improved survival 162 00:08:42,344 --> 00:08:44,903 only in young women. 163 00:08:44,903 --> 00:08:46,807 Now this is a very early finding 164 00:08:46,807 --> 00:08:50,082 and we don't yet know whether it has relevance 165 00:08:50,082 --> 00:08:52,600 to clinical care. 166 00:08:52,600 --> 00:08:56,104 But it's findings like this that may provide hope 167 00:08:56,104 --> 00:08:59,240 and may provide an opportunity to save lives 168 00:08:59,240 --> 00:09:01,526 of both women and men. 169 00:09:01,526 --> 00:09:03,568 Now let me share with you an example 170 00:09:03,568 --> 00:09:07,024 of when we do consider sex differences, it can drive the science. 171 00:09:07,024 --> 00:09:09,552 Several years ago a new lung cancer drug 172 00:09:09,552 --> 00:09:11,120 was being evaluated, 173 00:09:11,120 --> 00:09:15,400 and when the authors looked at whose tumors shrank, 174 00:09:15,400 --> 00:09:18,864 they found that 82 percent were women. 175 00:09:18,864 --> 00:09:21,904 This led them to ask the question: Well, why? 176 00:09:21,904 --> 00:09:23,336 And what they found 177 00:09:23,336 --> 00:09:26,847 was that the genetic mutations that the drug targeted 178 00:09:26,847 --> 00:09:29,512 were far more common in women. 179 00:09:29,512 --> 00:09:31,273 And what this has led to 180 00:09:31,273 --> 00:09:33,578 is a more personalized approach 181 00:09:33,578 --> 00:09:37,440 to the treatment of lung cancer that also includes sex. 182 00:09:37,440 --> 00:09:39,704 This is what we can accomplish 183 00:09:39,704 --> 00:09:43,668 when we don't leave women's health to chance. 184 00:09:43,668 --> 00:09:46,784 We know that when you invest in research, 185 00:09:46,784 --> 00:09:48,264 you get results. 186 00:09:48,264 --> 00:09:52,648 Take a look at the death rate from breast cancer over time. 187 00:09:52,648 --> 00:09:55,220 And now take a look at the death rates 188 00:09:55,220 --> 00:09:57,984 from lung cancer in women over time. 189 00:09:57,984 --> 00:10:01,824 Now let's look at the dollars invested in breast cancer -- 190 00:10:01,824 --> 00:10:04,192 these are the dollars invested per death -- 191 00:10:04,192 --> 00:10:08,544 and the dollars invested in lung cancer. 192 00:10:08,544 --> 00:10:13,757 Now it's clear that our investment in breast cancer 193 00:10:13,757 --> 00:10:15,653 has produced results. 194 00:10:15,653 --> 00:10:17,909 They may not be fast enough, 195 00:10:17,909 --> 00:10:20,181 but it has produced results. 196 00:10:20,181 --> 00:10:22,001 We can do the same 197 00:10:22,001 --> 00:10:26,685 for lung cancer and for every other disease. 198 00:10:26,685 --> 00:10:30,038 So let's go back to depression. 199 00:10:30,038 --> 00:10:32,474 Depression is the number-one cause 200 00:10:32,474 --> 00:10:37,189 of disability in women in the world today. 201 00:10:37,189 --> 00:10:39,309 Our investigators have found 202 00:10:39,309 --> 00:10:41,341 that there are differences in the brains 203 00:10:41,341 --> 00:10:42,709 of women and men 204 00:10:42,709 --> 00:10:45,813 in the areas that are connected with mood. 205 00:10:45,813 --> 00:10:47,717 And when you put men and women 206 00:10:47,717 --> 00:10:49,670 in a functional MRI scanner -- 207 00:10:49,670 --> 00:10:54,002 that's the kind of scanner that shows how the brain is functioning when it's activated -- 208 00:10:54,002 --> 00:10:58,168 so you put them in the scanner and you expose them to stress. 209 00:10:58,168 --> 00:11:02,007 You can actually see the difference. 210 00:11:02,007 --> 00:11:04,782 And it's findings like this 211 00:11:04,782 --> 00:11:08,149 that we believe holds some of the clues 212 00:11:08,149 --> 00:11:11,547 for why we see these very significant sex differences 213 00:11:11,547 --> 00:11:13,217 in depression. 214 00:11:13,217 --> 00:11:15,221 But even though we know 215 00:11:15,221 --> 00:11:17,597 that these differences occur, 216 00:11:17,597 --> 00:11:20,557 66 percent 217 00:11:20,557 --> 00:11:24,829 of the brain research that begins in animals 218 00:11:24,829 --> 00:11:27,109 is done in either male animals 219 00:11:27,109 --> 00:11:31,349 or animals in whom the sex is not identified. 220 00:11:31,349 --> 00:11:35,023 So, I think we have to ask again the question: 221 00:11:35,023 --> 00:11:39,555 Why leave women's health to chance? 222 00:11:39,555 --> 00:11:42,582 And this is a question that haunts those of us 223 00:11:42,582 --> 00:11:44,517 in science and medicine 224 00:11:44,517 --> 00:11:50,429 who believe that we are on the verge of being able to dramatically improve 225 00:11:50,429 --> 00:11:52,582 the health of women. 226 00:11:52,582 --> 00:11:55,053 We know that every cell has a sex. 227 00:11:55,053 --> 00:11:57,917 We know that these differences are often overlooked. 228 00:11:57,917 --> 00:12:02,093 And therefore we know that women are not getting the full benefit 229 00:12:02,093 --> 00:12:05,829 of modern science and medicine today. 230 00:12:05,829 --> 00:12:07,709 We have the tools 231 00:12:07,709 --> 00:12:11,653 but we lack the collective will and momentum. 232 00:12:11,653 --> 00:12:14,381 Women's health is an equal rights issue 233 00:12:14,381 --> 00:12:17,781 as important as equal pay. 234 00:12:17,781 --> 00:12:20,119 And it's an issue of the quality 235 00:12:20,119 --> 00:12:23,290 and the integrity of science and medicine. 236 00:12:23,290 --> 00:12:29,232 (Applause) 237 00:12:29,232 --> 00:12:35,405 So imagine the momentum we could achieve 238 00:12:35,405 --> 00:12:37,486 in advancing the health of women 239 00:12:37,486 --> 00:12:40,237 if we considered whether these sex differences were present 240 00:12:40,237 --> 00:12:43,903 at the very beginning of designing research. 241 00:12:43,903 --> 00:12:47,813 Or if we analyzed our data by sex. 242 00:12:47,813 --> 00:12:49,885 So, people often ask me: 243 00:12:49,885 --> 00:12:51,593 What can I do? 244 00:12:51,593 --> 00:12:53,850 And here's what I suggest: 245 00:12:53,850 --> 00:12:57,916 First, I suggest that you think about women's health 246 00:12:57,916 --> 00:12:59,597 in the same way 247 00:12:59,597 --> 00:13:05,381 that you think and care about other causes that are important to you. 248 00:13:05,381 --> 00:13:08,517 And second, and equally as important, 249 00:13:08,517 --> 00:13:10,837 that as a woman, 250 00:13:10,837 --> 00:13:13,908 you have to ask your doctor 251 00:13:13,908 --> 00:13:18,197 and the doctors who are caring for those who you love: 252 00:13:18,197 --> 00:13:22,966 Is this disease or treatment different in women? 253 00:13:22,966 --> 00:13:26,661 Now this is a profound question because the answer is likely yes -- 254 00:13:26,661 --> 00:13:30,512 but your doctor may not know the answer, at least not yet. 255 00:13:30,512 --> 00:13:34,519 But if you ask the question, your doctor will very likely 256 00:13:34,519 --> 00:13:37,037 go looking for the answer. 257 00:13:37,037 --> 00:13:39,414 And this is so important -- 258 00:13:39,414 --> 00:13:41,622 not only for ourselves, 259 00:13:41,622 --> 00:13:44,229 but for all of those whom we love. 260 00:13:44,229 --> 00:13:47,791 Whether it be a mother, a daughter, a sister, 261 00:13:47,791 --> 00:13:51,781 a friend or a grandmother. 262 00:13:51,781 --> 00:13:54,477 It was my grandmother's suffering 263 00:13:54,477 --> 00:13:56,517 that inspired my work 264 00:13:56,517 --> 00:13:59,365 to improve the health of women. 265 00:13:59,365 --> 00:14:01,821 That's her legacy. 266 00:14:01,821 --> 00:14:06,229 Our legacy can be to improve the health of women 267 00:14:06,229 --> 00:14:08,445 for this generation 268 00:14:08,445 --> 00:14:11,421 and for generations to come. 269 00:14:11,421 --> 00:14:12,893 Thank you. 270 00:14:12,893 --> 00:14:16,221 (Applause)