1 00:00:00,520 --> 00:00:04,040 Speaker 1: Already and this is the daily This is the daily 2 00:00:04,120 --> 00:00:06,840 Speaker 1: ohs oh, now it makes sense. 3 00:00:14,680 --> 00:00:17,520 Speaker 2: Good morning and welcome to the Daily OS. It's Thursday, 4 00:00:17,560 --> 00:00:18,960 Speaker 2: the sixteenth of January. 5 00:00:19,079 --> 00:00:20,480 Speaker 3: I'm emma, I'm sam. 6 00:00:20,760 --> 00:00:24,680 Speaker 2: Depression effects around one in every four young Ossie adults. 7 00:00:24,960 --> 00:00:27,840 Speaker 2: We know the mental health conditions have surged among young 8 00:00:27,880 --> 00:00:31,800 Speaker 2: people in recent years. We know depression can be triggered 9 00:00:31,840 --> 00:00:35,839 Speaker 2: by environmental factors and life events, but there's still so 10 00:00:36,000 --> 00:00:38,279 Speaker 2: much we don't know when it comes to the complex 11 00:00:38,360 --> 00:00:42,599 Speaker 2: role of genetics in mental health disorders. It's what's motivated 12 00:00:42,640 --> 00:00:45,879 Speaker 2: researchers from around the world to conduct the largest and 13 00:00:46,000 --> 00:00:49,600 Speaker 2: most diverse study of its kind aimed at understanding the 14 00:00:49,640 --> 00:00:52,680 Speaker 2: link between biological factors and depression. 15 00:00:56,160 --> 00:00:59,080 Speaker 4: Over six years, a team of researchers from around the 16 00:00:59,120 --> 00:01:03,400 Speaker 4: world and here in Australia analyze nearly seven hundred thousand 17 00:01:03,680 --> 00:01:07,880 Speaker 4: genetic samples from twenty nine countries. The global study identified 18 00:01:08,000 --> 00:01:12,600 Speaker 4: previously unknown genetic variance linked to depression. It could change 19 00:01:12,600 --> 00:01:16,400 Speaker 4: the way depression is diagnosed and treated and proves that 20 00:01:16,440 --> 00:01:20,160 Speaker 4: there is a strong biological basis to having the mental illness. 21 00:01:20,680 --> 00:01:24,360 Speaker 2: Doctor Britney Mitchell from the qim R Berghoff for Medical 22 00:01:24,400 --> 00:01:27,880 Speaker 2: Research Institute was involved in that very study and she 23 00:01:28,040 --> 00:01:31,360 Speaker 2: joins us from Queensland now to talk through these findings. 24 00:01:31,720 --> 00:01:33,680 Speaker 2: Doctor Britney, welcome to the podcast. 25 00:01:33,959 --> 00:01:34,840 Speaker 1: Thank you for having me. 26 00:01:35,360 --> 00:01:38,319 Speaker 2: We are talking today about this global study. 27 00:01:38,000 --> 00:01:39,360 Speaker 3: That you've been involved in. 28 00:01:39,640 --> 00:01:43,040 Speaker 2: It's been described as an unprecedented study into the genetics 29 00:01:43,040 --> 00:01:45,640 Speaker 2: of depression. Can you tell us a bit more about 30 00:01:45,680 --> 00:01:50,000 Speaker 2: your involvement in this research and its scope? 31 00:01:50,520 --> 00:01:53,360 Speaker 1: Yees. So this was a big research project that came 32 00:01:53,400 --> 00:01:56,520 Speaker 1: out of the consortium, and so that consortium is pretty 33 00:01:56,560 --> 00:01:59,160 Speaker 1: much the pooling of anyone in the world that's working 34 00:01:59,240 --> 00:02:03,520 Speaker 1: on of depression. We all decided or came to the 35 00:02:03,560 --> 00:02:06,880 Speaker 1: conclusion that for us to make any meaningful progress, we 36 00:02:06,920 --> 00:02:10,000 Speaker 1: needed to kind of join forces, pull our data together 37 00:02:10,080 --> 00:02:13,200 Speaker 1: and our expertise to kind of comeback what is a 38 00:02:13,240 --> 00:02:16,320 Speaker 1: really complicated condition and really difficult to understand in terms 39 00:02:16,320 --> 00:02:19,680 Speaker 1: of its ateology and its causes. And so my contribution 40 00:02:20,120 --> 00:02:24,480 Speaker 1: was leading the Australian arm of this stay and contributing 41 00:02:24,480 --> 00:02:26,320 Speaker 1: the data from the side of the world. 42 00:02:27,000 --> 00:02:30,600 Speaker 2: For those of us who are not genetics experts like you, 43 00:02:31,600 --> 00:02:35,560 Speaker 2: what do we need to understand about genes? What our 44 00:02:35,880 --> 00:02:39,639 Speaker 2: genetic variants. What are these findings actually tell us? 45 00:02:39,960 --> 00:02:43,600 Speaker 1: Great question. So we've known for quite a while that 46 00:02:43,840 --> 00:02:48,840 Speaker 1: biology plays a role in depression causing, and so we've 47 00:02:48,840 --> 00:02:52,600 Speaker 1: known that from long ago when we saw the depression 48 00:02:52,680 --> 00:02:55,239 Speaker 1: ran in families and that people that had a family 49 00:02:55,360 --> 00:02:58,840 Speaker 1: history of depression had a higher likelihood of having it 50 00:02:58,880 --> 00:03:02,959 Speaker 1: in their lifetime. But identifying the genes specifically the player 51 00:03:03,040 --> 00:03:05,600 Speaker 1: role has been a lot of a kind of slower process, 52 00:03:06,120 --> 00:03:08,640 Speaker 1: and a lot of that comes from the fact that 53 00:03:08,680 --> 00:03:12,560 Speaker 1: these genetic variants are really small in effect, and so 54 00:03:12,680 --> 00:03:15,840 Speaker 1: each gene on its own plays a very small role 55 00:03:15,880 --> 00:03:19,680 Speaker 1: in increasing our risk of depression, but then cumulatively they 56 00:03:19,720 --> 00:03:22,920 Speaker 1: all add up. And so that's where we came to 57 00:03:22,960 --> 00:03:27,080 Speaker 1: the kind of realization that our sample sizes, they weren't 58 00:03:27,080 --> 00:03:30,160 Speaker 1: big enough for us to detect these genetic variants that 59 00:03:30,200 --> 00:03:33,480 Speaker 1: have such small effect sizes. And so that's what kind 60 00:03:33,480 --> 00:03:36,360 Speaker 1: of motivated the pooling of the data that allowed us 61 00:03:36,400 --> 00:03:39,520 Speaker 1: to find out what the genes are that make up 62 00:03:39,520 --> 00:03:41,600 Speaker 1: this genetic component of depression risk. 63 00:03:42,360 --> 00:03:46,360 Speaker 2: How big was that pool that you pulled data from? 64 00:03:46,360 --> 00:03:50,440 Speaker 2: What's the right size gene pool to really comprehensively be 65 00:03:50,560 --> 00:03:54,640 Speaker 2: able to prove that relationship between biology and depression. 66 00:03:55,280 --> 00:03:58,680 Speaker 1: Yeah, so it was an incredibly large sample, so we're 67 00:03:58,760 --> 00:04:02,000 Speaker 1: very proud of everyone that's contributed and volunteered and to 68 00:04:02,080 --> 00:04:04,480 Speaker 1: the studies that have gone into it. So we ended 69 00:04:04,560 --> 00:04:06,840 Speaker 1: up analyzing the DNA of six hundred and eighty five 70 00:04:06,880 --> 00:04:10,680 Speaker 1: thousand people that had had depression in their lifetime, and 71 00:04:10,720 --> 00:04:12,800 Speaker 1: then we had to compare their DNA to people that 72 00:04:12,880 --> 00:04:15,640 Speaker 1: had never had depression, and so we had four million 73 00:04:15,680 --> 00:04:18,560 Speaker 1: people that had volunteered that had never had depression. And 74 00:04:18,600 --> 00:04:21,400 Speaker 1: it's from that comparison that we're able to find so 75 00:04:21,560 --> 00:04:22,960 Speaker 1: many of these genetic variants. 76 00:04:23,560 --> 00:04:28,000 Speaker 2: I'm interested in particular in the genetics testing of non 77 00:04:28,080 --> 00:04:32,200 Speaker 2: European populations. I was really surprised to learn that that's 78 00:04:32,240 --> 00:04:35,640 Speaker 2: not something that had really been conducted before in this space. 79 00:04:35,839 --> 00:04:37,200 Speaker 3: Can you tell us a bit more about that. 80 00:04:37,800 --> 00:04:42,520 Speaker 1: Yeah, absolutely, So this is a major shortfall of genetic research. 81 00:04:42,560 --> 00:04:45,920 Speaker 1: It's not unique to depression genetics or mental health genetics 82 00:04:45,920 --> 00:04:49,919 Speaker 1: at all. It's all genetic research into human traits and 83 00:04:50,000 --> 00:04:53,080 Speaker 1: diseases in that most of what we know has come 84 00:04:53,080 --> 00:04:57,400 Speaker 1: from people from European ancestry backgrounds, and the history as 85 00:04:57,400 --> 00:05:00,400 Speaker 1: to why that is is very complicated. And a lot 86 00:05:00,400 --> 00:05:02,400 Speaker 1: of it's got to do with who was funding genetic 87 00:05:02,440 --> 00:05:06,360 Speaker 1: research decades ago. But now we're at the point where 88 00:05:06,480 --> 00:05:11,680 Speaker 1: if we want our findings to matter and actually be 89 00:05:12,160 --> 00:05:15,000 Speaker 1: meaningful to the population, we need to make sure that 90 00:05:15,040 --> 00:05:17,279 Speaker 1: the science is representative of it. So this is the 91 00:05:17,279 --> 00:05:22,280 Speaker 1: first study looking at the genetics of depression in diverse ancestries, 92 00:05:22,320 --> 00:05:25,679 Speaker 1: and so looking across the board for as many different 93 00:05:25,760 --> 00:05:28,800 Speaker 1: cultures as we could, creating it together and then finding 94 00:05:29,000 --> 00:05:33,559 Speaker 1: genetic variants across everyone, rather than subgrouping to specific parts 95 00:05:33,600 --> 00:05:34,240 Speaker 1: of the population. 96 00:05:35,279 --> 00:05:39,400 Speaker 2: So, of these nearly seven hundred genetic variants that the 97 00:05:39,480 --> 00:05:44,000 Speaker 2: study has connected to depression, what does that mean in 98 00:05:44,040 --> 00:05:48,720 Speaker 2: real terms? If someone has one of these genes one 99 00:05:48,760 --> 00:05:53,440 Speaker 2: of those variants, does that mean that they will experience depression? 100 00:05:53,800 --> 00:05:55,120 Speaker 3: How should we interpret that? 101 00:05:55,760 --> 00:05:58,680 Speaker 1: In reality, we will all have some of these variants, 102 00:05:58,800 --> 00:06:00,920 Speaker 1: and so I like to look at it as kind 103 00:06:00,960 --> 00:06:04,719 Speaker 1: of a continuum, and we're also somewhere in how many 104 00:06:04,800 --> 00:06:07,400 Speaker 1: of these variants we carry, but in reality we'll all 105 00:06:07,440 --> 00:06:09,919 Speaker 1: have some. And then it's only in the kind of 106 00:06:10,040 --> 00:06:11,920 Speaker 1: very tail end of that where you have a lot 107 00:06:11,960 --> 00:06:14,479 Speaker 1: of these variants that that actually ends up having a 108 00:06:14,560 --> 00:06:17,919 Speaker 1: clinical effect on increasing your risk of depression. 109 00:06:18,720 --> 00:06:23,720 Speaker 2: The idea of mental health conditions being tied to biology 110 00:06:23,800 --> 00:06:28,920 Speaker 2: there being hereditary factors isn't necessarily a new discussion. But 111 00:06:29,040 --> 00:06:33,719 Speaker 2: what do these findings specifically mean for our understanding of depression? 112 00:06:33,760 --> 00:06:34,800 Speaker 3: And I'm interested in your. 113 00:06:34,680 --> 00:06:38,760 Speaker 2: Perspective, both at a clinical level but also from a 114 00:06:38,920 --> 00:06:41,160 Speaker 2: social and cultural perspective. 115 00:06:41,920 --> 00:06:45,039 Speaker 1: The thing that I hope comes across with this people 116 00:06:45,040 --> 00:06:48,240 Speaker 1: more than anything else, is that we do show that 117 00:06:48,720 --> 00:06:52,120 Speaker 1: depression has a biological basis. That doesn't mean for everyone 118 00:06:52,200 --> 00:06:54,200 Speaker 1: the cause is the same. We know that there are 119 00:06:54,240 --> 00:06:57,320 Speaker 1: many different causes full depression. We know that environmentally is 120 00:06:57,320 --> 00:07:01,479 Speaker 1: a very big role. Lifestyle factors, experiences trauma, we know 121 00:07:01,600 --> 00:07:04,400 Speaker 1: that those are very important for many people do cause 122 00:07:04,440 --> 00:07:08,600 Speaker 1: depression irrespective of your genetics, but it does also for 123 00:07:08,640 --> 00:07:12,120 Speaker 1: some people have this biological basis. And I think mental 124 00:07:12,120 --> 00:07:15,560 Speaker 1: health in general, but also depression specificity, has for a 125 00:07:15,640 --> 00:07:19,040 Speaker 1: very long time been really stigmatized and quite often seen 126 00:07:19,480 --> 00:07:22,640 Speaker 1: perhaps as a weakness or something that you shouldn't openly 127 00:07:22,680 --> 00:07:24,960 Speaker 1: talk about, or people often talk about being told to 128 00:07:25,040 --> 00:07:28,160 Speaker 1: kind of snap out of it. And I think by 129 00:07:28,200 --> 00:07:32,200 Speaker 1: showing quite concretely that there are there's genes play a 130 00:07:32,320 --> 00:07:35,760 Speaker 1: role here that that might help that stigmatism a little bit, 131 00:07:35,760 --> 00:07:39,200 Speaker 1: and it's taken seriously as a medical condition. You know, 132 00:07:39,280 --> 00:07:41,560 Speaker 1: that is as biological as a lot of other things 133 00:07:41,600 --> 00:07:45,240 Speaker 1: like diabetes, and so I hope this helps starting to 134 00:07:45,280 --> 00:07:47,600 Speaker 1: kind of open that door to taking it a little 135 00:07:47,600 --> 00:07:50,920 Speaker 1: bit more seriously and more being less stigmatized than easily 136 00:07:50,960 --> 00:07:51,480 Speaker 1: talked about. 137 00:07:52,280 --> 00:07:57,679 Speaker 2: So these findings play a role potentially in empowering more people. 138 00:07:58,160 --> 00:08:02,000 Speaker 2: What about in terms of treatments, how could this evidence 139 00:08:02,160 --> 00:08:06,600 Speaker 2: be used to change the way we diagnose or treat depression. 140 00:08:07,120 --> 00:08:11,600 Speaker 1: So in terms of treatment, we're really excited by two avenues, 141 00:08:11,640 --> 00:08:14,440 Speaker 1: and the one is, you know, by understanding the biology 142 00:08:14,440 --> 00:08:16,880 Speaker 1: and knowing what's going on in the brain, this gives 143 00:08:16,920 --> 00:08:20,280 Speaker 1: us a curra understanding of how depression is coming about, 144 00:08:21,080 --> 00:08:23,080 Speaker 1: and that gives us new targets that you can then 145 00:08:23,080 --> 00:08:27,000 Speaker 1: look for new drugs or medications that may help depression. 146 00:08:27,640 --> 00:08:30,360 Speaker 1: And along those similar lines what we've done in the study, 147 00:08:30,760 --> 00:08:33,280 Speaker 1: because we now know or have a kera idea of 148 00:08:33,320 --> 00:08:36,560 Speaker 1: these pathways, we've been able to identify drugs that are 149 00:08:36,559 --> 00:08:40,480 Speaker 1: already on the market that treat other conditions. So one 150 00:08:40,520 --> 00:08:43,319 Speaker 1: of the ones mentioned in the paper is called medath not. 151 00:08:43,480 --> 00:08:46,800 Speaker 1: Its used often to treat narcolepsy or prescribe to shift 152 00:08:46,800 --> 00:08:49,880 Speaker 1: workers that need to stay awake during the night, and 153 00:08:49,960 --> 00:08:54,200 Speaker 1: it really helps with kind of alertness and fatigue. And 154 00:08:54,280 --> 00:08:57,360 Speaker 1: we've shown that that medication targets a lot of the 155 00:08:57,360 --> 00:09:01,080 Speaker 1: same pathways that are enriched in people that have depression, 156 00:09:01,440 --> 00:09:02,959 Speaker 1: and it kind of makes sense if you start to 157 00:09:03,000 --> 00:09:05,560 Speaker 1: think about a lot of the symptoms of depression also 158 00:09:05,640 --> 00:09:09,000 Speaker 1: include difficulty sleeping or difficulty getting up in the morning 159 00:09:09,040 --> 00:09:10,040 Speaker 1: and lack of motivation. 160 00:09:10,840 --> 00:09:12,040 Speaker 2: And so if. 161 00:09:11,880 --> 00:09:15,360 Speaker 1: We're able to use those growths, it's already available, it's safe, 162 00:09:16,040 --> 00:09:19,160 Speaker 1: that would really shorten the time frame between getting it 163 00:09:19,200 --> 00:09:22,200 Speaker 1: to people that have depression and might be useful because 164 00:09:22,200 --> 00:09:25,280 Speaker 1: they're not responding to the current antidepressive medications. 165 00:09:25,920 --> 00:09:30,440 Speaker 2: So it's not necessarily about reinventing the wheel or months 166 00:09:30,480 --> 00:09:34,760 Speaker 2: or years of trials and testing. There could be drugs 167 00:09:34,800 --> 00:09:39,360 Speaker 2: on the market right now that could easily be repurposed. 168 00:09:39,120 --> 00:09:42,679 Speaker 1: Yes, potentially, So we're very excited about that. We you know, 169 00:09:43,120 --> 00:09:45,520 Speaker 1: by no means want everyone to go out and buy 170 00:09:45,559 --> 00:09:48,840 Speaker 1: a medafnel now after they suffering from depression, but it 171 00:09:48,880 --> 00:09:51,360 Speaker 1: would be a very promising aspect and that's that's really 172 00:09:51,400 --> 00:09:53,160 Speaker 1: kind of one of the next steps we want to take. 173 00:09:53,880 --> 00:09:57,960 Speaker 2: Will this changing understanding of the role of genetics in 174 00:09:58,000 --> 00:10:03,200 Speaker 2: depression be meaningful for treatment resistant depression or what we've 175 00:10:03,240 --> 00:10:06,679 Speaker 2: previously thought of as treatment resistant depression. It's something we've 176 00:10:06,720 --> 00:10:09,640 Speaker 2: spoken to our audience about before. It's something we know 177 00:10:09,960 --> 00:10:14,959 Speaker 2: a huge portion of people with depression have experienced. What 178 00:10:15,000 --> 00:10:16,200 Speaker 2: does this mean for that space? 179 00:10:16,720 --> 00:10:19,640 Speaker 1: Yeah, absolutely so. I think that's something that I also 180 00:10:19,679 --> 00:10:23,920 Speaker 1: personally am really interested in in understanding who responds to 181 00:10:23,960 --> 00:10:27,080 Speaker 1: treatment and who doesn't. And we know that a very 182 00:10:27,160 --> 00:10:29,800 Speaker 1: large portion of people don't respond to at least their 183 00:10:29,800 --> 00:10:33,360 Speaker 1: first medication, and then that goes on and as you say, 184 00:10:33,400 --> 00:10:35,200 Speaker 1: then we get people that don't seem to respond to 185 00:10:35,240 --> 00:10:39,280 Speaker 1: any types of currently available medications or other forms of treatment. 186 00:10:39,720 --> 00:10:45,000 Speaker 1: What we don't really understand is why why does an 187 00:10:45,120 --> 00:10:48,120 Speaker 1: ssri antidepressant work for one person and doesn't work for 188 00:10:48,160 --> 00:10:51,720 Speaker 1: the other, or why can some people try five ten 189 00:10:51,760 --> 00:10:55,800 Speaker 1: different types of medication and never find that helps for them. 190 00:10:56,600 --> 00:10:58,840 Speaker 1: We hypothesize that this could at least be in part 191 00:10:58,960 --> 00:11:02,240 Speaker 1: by due to biology, due to your person's genetic makeup, 192 00:11:02,600 --> 00:11:04,920 Speaker 1: and if we can understand that, we can help try 193 00:11:04,960 --> 00:11:07,720 Speaker 1: and match people with more effective medication. 194 00:11:07,440 --> 00:11:15,080 Speaker 2: Sooner could hypothetically researchers apply the same approach as they 195 00:11:15,120 --> 00:11:19,960 Speaker 2: did with this genetic variant depression study to understanding other 196 00:11:20,040 --> 00:11:21,240 Speaker 2: mental health conditions. 197 00:11:22,000 --> 00:11:25,880 Speaker 1: Absolutely, so that's ongoing part of this CONSORTI that are 198 00:11:25,920 --> 00:11:29,920 Speaker 1: mentioned in the Psychiatric Genetics Consortium, they have work groups 199 00:11:29,920 --> 00:11:32,880 Speaker 1: and each of those work groups concentrate on different mental 200 00:11:32,920 --> 00:11:35,720 Speaker 1: health conditions. So this is the outcome from the depression 201 00:11:35,720 --> 00:11:38,920 Speaker 1: work group, but there's equally a bipolar disorder work group, 202 00:11:38,920 --> 00:11:41,920 Speaker 1: and a schizophrenia work group and an anxiety disorders work groups. 203 00:11:41,920 --> 00:11:44,240 Speaker 1: So there are a lot of people working on this. 204 00:11:45,360 --> 00:11:46,920 Speaker 3: What are the next steps from here? 205 00:11:46,960 --> 00:11:49,680 Speaker 2: How might these findings and you know, the future findings 206 00:11:49,679 --> 00:11:50,400 Speaker 2: from these other. 207 00:11:50,320 --> 00:11:53,360 Speaker 3: Working groups that you've touched on be used to. 208 00:11:53,400 --> 00:11:57,480 Speaker 2: Create tangible change for the lives of people with mental 209 00:11:57,480 --> 00:11:58,360 Speaker 2: health conditions. 210 00:11:59,040 --> 00:12:02,280 Speaker 1: The ultimate goal is that we can start to incorporate 211 00:12:02,679 --> 00:12:07,160 Speaker 1: genetic profiles or genetic information in general healthcare and so 212 00:12:07,400 --> 00:12:09,400 Speaker 1: both from a preventative measure. 213 00:12:09,440 --> 00:12:11,040 Speaker 3: If you know you're able to do. 214 00:12:11,040 --> 00:12:14,319 Speaker 1: A test that profiles your genetic risk of mental health conditions, 215 00:12:14,640 --> 00:12:17,160 Speaker 1: you can then work with healthcare providers to try and 216 00:12:17,200 --> 00:12:20,040 Speaker 1: mitigate risks or potentially, you know, if you know you're 217 00:12:20,040 --> 00:12:22,640 Speaker 1: at a higher risk of having depression and you go 218 00:12:22,720 --> 00:12:26,360 Speaker 1: through a really traumatic event, you can help try mitigate 219 00:12:26,440 --> 00:12:30,800 Speaker 1: risks from that by seeking professional help earlier, potentially, And 220 00:12:30,840 --> 00:12:33,840 Speaker 1: while we're still away off that, we're hoping that that 221 00:12:34,200 --> 00:12:37,760 Speaker 1: doesn't come to fruition, at least hopefully in my lifetime. 222 00:12:39,280 --> 00:12:42,200 Speaker 1: There's also a lot to consider in terms of legal frameworks, 223 00:12:42,240 --> 00:12:45,480 Speaker 1: ethical frameworks. You know, once you've got to persons genetic information, 224 00:12:45,960 --> 00:12:48,360 Speaker 1: there's a lot of safeguards that are needed on what 225 00:12:48,520 --> 00:12:50,840 Speaker 1: happens with that information. But I think there's also a 226 00:12:50,840 --> 00:12:53,920 Speaker 1: lot of exciting prospects going forward and what we can 227 00:12:53,960 --> 00:12:56,560 Speaker 1: do with that, And then on the flip side on 228 00:12:56,679 --> 00:12:59,520 Speaker 1: better treatments and matching people to better treatments so they 229 00:12:59,559 --> 00:13:01,880 Speaker 1: don't have to go to the doctor and get prescribed 230 00:13:01,920 --> 00:13:04,600 Speaker 1: a certain medication and then told to wait six to 231 00:13:04,600 --> 00:13:07,160 Speaker 1: twelve weeks and see if that gets better, and if 232 00:13:07,160 --> 00:13:09,400 Speaker 1: it doesn't, then we just try you on a different medication. 233 00:13:09,440 --> 00:13:12,439 Speaker 1: And that's a really long time for someone that's suffering 234 00:13:12,920 --> 00:13:14,640 Speaker 1: to just be told to kind of sid and wait. 235 00:13:14,840 --> 00:13:16,080 Speaker 1: So we hope we can improve that. 236 00:13:17,120 --> 00:13:21,880 Speaker 2: The Australian Genetics of Depression Study is still recruiting new participants. 237 00:13:22,440 --> 00:13:25,800 Speaker 2: So if someone is listening and wanting to get involved, 238 00:13:26,160 --> 00:13:28,240 Speaker 2: how do they go about that? What are you guys 239 00:13:28,320 --> 00:13:30,680 Speaker 2: sort of looking for or who are you hoping to recruit? 240 00:13:31,280 --> 00:13:36,000 Speaker 1: Absolutely, so we're very proud of our contribution. We were 241 00:13:36,040 --> 00:13:37,920 Speaker 1: one of the biggest cohorts in the world that went 242 00:13:37,960 --> 00:13:41,640 Speaker 1: into the study, and that came from the Australian Genetics 243 00:13:41,679 --> 00:13:46,200 Speaker 1: of Depression Study where people volunteered and shared their experiences 244 00:13:46,240 --> 00:13:49,600 Speaker 1: of depression. So the study website's very easy to find 245 00:13:49,600 --> 00:13:51,599 Speaker 1: if you Google it or you go to Genetics of 246 00:13:51,640 --> 00:13:55,120 Speaker 1: Depression not already knew, and it explains what the study 247 00:13:55,200 --> 00:13:57,600 Speaker 1: is about and how you go about it. We're really 248 00:13:57,640 --> 00:14:01,480 Speaker 1: looking to continue to expand our sizes. As I've said, 249 00:14:01,559 --> 00:14:05,040 Speaker 1: depression is incredibly complicated. It looks very different from one 250 00:14:05,120 --> 00:14:07,840 Speaker 1: person to another, and so for us to understand why 251 00:14:07,880 --> 00:14:11,120 Speaker 1: this is, we need as representative sample as we can 252 00:14:11,280 --> 00:14:13,839 Speaker 1: of the different experiences. And so if we can get 253 00:14:13,840 --> 00:14:16,800 Speaker 1: anyone that's interested, or you know someone that has depression 254 00:14:16,800 --> 00:14:20,280 Speaker 1: that might be interested, regardless of your background or your age, 255 00:14:20,360 --> 00:14:23,240 Speaker 1: or whether medications worked for you or hasn't worked for you, 256 00:14:23,240 --> 00:14:25,280 Speaker 1: and you'd be very very happy to hear from you. 257 00:14:26,240 --> 00:14:28,600 Speaker 4: That's all I've got time for on today's episode. A 258 00:14:28,680 --> 00:14:32,760 Speaker 4: big thank you to QIMR. Berghoffer researcher doctor Britney Mitchell 259 00:14:32,800 --> 00:14:35,360 Speaker 4: for joining us to explain those findings. Now, if you 260 00:14:35,440 --> 00:14:38,560 Speaker 4: learn something from today's episode, don't forget to hit subscribe 261 00:14:38,600 --> 00:14:41,720 Speaker 4: where you listen or watch the Daily Yours if you're 262 00:14:41,720 --> 00:14:44,440 Speaker 4: watching on YouTube. Hello, we are really enjoying being here 263 00:14:44,480 --> 00:14:46,480 Speaker 4: in twenty twenty five. We're going to be back a 264 00:14:46,520 --> 00:14:49,720 Speaker 4: little later today with the latest news headlines, but until then, 265 00:14:49,840 --> 00:14:50,560 Speaker 4: have a great day. 266 00:14:54,720 --> 00:14:57,040 Speaker 3: My name is Lily Madden and I'm a proud Dunda 267 00:14:57,280 --> 00:14:59,840 Speaker 3: Bungelung Calcotten woman from Gadigal Country. 268 00:15:00,640 --> 00:15:03,800 Speaker 1: The Daily oz acknowledges that this podcast is recorded on 269 00:15:03,840 --> 00:15:06,320 Speaker 1: the lands of the Gadigal people and pays respect to 270 00:15:06,400 --> 00:15:09,720 Speaker 1: all Aboriginal and torrest Rate island and nations. We pay 271 00:15:09,720 --> 00:15:12,680 Speaker 1: our respects to the first peoples of these countries, both 272 00:15:12,720 --> 00:15:13,600 Speaker 1: past and present.