1 00:00:00,000 --> 00:00:08,880 Welcome to From the Spectrum Podcast. This is a podcast about autism. It is my 2 00:00:08,880 --> 00:00:17,640 goal to explain what is autism. I plan to use a mixture of scientific literature, 3 00:00:17,640 --> 00:00:25,320 personal experience, and opinion. With opinion, I will explain why. I feel the 4 00:00:25,320 --> 00:00:33,240 way I do and give examples. I will provide links to various references for each episode. 5 00:00:33,240 --> 00:00:42,320 For each episode, we will discuss various aspects of autism. For today's episode, 6 00:00:42,320 --> 00:00:50,520 it is my pleasure to announce the guest, Dr. Leanna Hernandez. Dr. Leanna Hernandez is an 7 00:00:50,520 --> 00:00:59,720 assistant professor in the Department of Psychiatry and Biobehavioral Sciences at UCLA and a member of 8 00:00:59,720 --> 00:01:09,560 the Center for Autism Research and Treatment, or CART, the Center of Neurobehavioral Genetics and 9 00:01:09,560 --> 00:01:16,960 the Brain Research Institute. Dr. Hernandez also serves as a co-director for the genetics, 10 00:01:16,960 --> 00:01:26,120 genomics, and informatics core for UCLA's Intellectual Developmental Disabilities Research Center. 11 00:01:26,120 --> 00:01:35,480 In addition, Dr. Hernandez directs the Hernandez lab at UCLA, where they examine genetic and 12 00:01:35,480 --> 00:01:45,600 neurobiology of autism, schizophrenia, and other related psychiatric disorders. Our discussion 13 00:01:45,600 --> 00:01:55,160 includes genetic variations and brain connectivity in autism, oxytocin and oxytocin receptor gene, 14 00:01:55,160 --> 00:02:06,200 sex and diagnosis differences in autism and brain connectivity, and the future of autism research. 15 00:02:06,200 --> 00:02:17,680 With the sex and diagnosis differences, you have autistic boys, non-autistic boys, autistic girls, 16 00:02:17,680 --> 00:02:27,520 and non-autistic girls. So, four comparison groups. As you hear, Dr. Hernandez explain this 17 00:02:27,520 --> 00:02:36,560 connectivity. Think about autism, what you know about autism. Remember the social communication 18 00:02:36,560 --> 00:02:45,120 and interaction challenges and the restricted repetitive behaviors, the preference for routines, 19 00:02:45,120 --> 00:02:55,080 sameness, and those preferences for restricted, fixated interests that are perfect in intensity 20 00:02:55,080 --> 00:03:06,440 or focus. You know the DSM uses abnormal, but to say abnormal with interest, intensity, or focus, 21 00:03:06,440 --> 00:03:16,280 is wrong by them. Now, think about how the biology that gives us autism provided those 22 00:03:16,280 --> 00:03:26,560 behaviors, those routines, the sameness, and so-called restricted behaviors. They are safe and predictable. 23 00:03:26,560 --> 00:03:37,240 The biology that gives us autism creates a chaotic outside world, and this connectivity gives us poor 24 00:03:37,240 --> 00:03:47,040 adapting skills. With the poor socialness and restricted behaviors, we have limited adaptive 25 00:03:47,040 --> 00:03:58,360 responses, and an unpredictable chaotic outside world requires adaptive responding. The biology 26 00:03:58,360 --> 00:04:07,360 that gives us autism allows us to be comfortable within ourselves, and that can be, that can be a 27 00:04:07,360 --> 00:04:17,920 path for finding and developing superpowers. And now, my discussion with Dr. Leanna Hernandez. 28 00:04:17,920 --> 00:04:25,080 Dr. Hernandez, thank you for joining. Why don't you start by taking us to the moment you realized 29 00:04:25,080 --> 00:04:31,160 autism was going to be a part of your professional life, and take us all the way up to the present day. 30 00:04:31,160 --> 00:04:38,240 Sure. So, I first started working in the field of autism after graduating from college with a degree 31 00:04:38,240 --> 00:04:45,520 in psychology, and I started working as an in-home aide for kids with autism. At that time, I got to 32 00:04:45,520 --> 00:04:50,240 know a lot of the different families and the challenges that they were facing, became familiar 33 00:04:50,240 --> 00:04:57,160 with many of the different behavioral symptoms associated with autism, and just became really 34 00:04:57,160 --> 00:05:01,880 interested in it more generally, and really fell in love with the kids and families that I was working 35 00:05:01,880 --> 00:05:08,560 with. After that, I decided that I wanted to learn more about the brain and brain development in 36 00:05:08,560 --> 00:05:15,240 general. I've always sort of been interested in development, and so I went on to work as a research 37 00:05:15,240 --> 00:05:23,480 assistant at UCLA in a lab that collected MRI scans, so magnetic resonance imaging scans of the brain, 38 00:05:23,480 --> 00:05:30,080 during childhood and adolescence, both in typically developing kids and in autistic males and females. 39 00:05:30,080 --> 00:05:36,480 And so from there, I then went on to become really interested, obviously, in brain development, 40 00:05:36,480 --> 00:05:43,800 and I learned more about the genetics of autism, and went on to do a PhD in neuroscience also at UCLA, 41 00:05:43,800 --> 00:05:50,680 where I studied the effects of different genetic variants on the oxytocin receptor gene and how 42 00:05:50,680 --> 00:05:59,200 they're related to brain function and connectivity. After that, I continued to be interested in the 43 00:05:59,200 --> 00:06:07,240 genetics of autism and did a postdoc at UCLA again, really focused on psychiatric genetics, and began 44 00:06:07,240 --> 00:06:13,440 to investigate genetic variants associated with autism through genome-wide association studies, 45 00:06:13,440 --> 00:06:15,600 which is some of the work that we continue to do today. 46 00:06:16,600 --> 00:06:21,480 Oh, wow. Okay. Tell me about the creation of the Hernandez lab. 47 00:06:22,360 --> 00:06:31,800 Yeah, it's very exciting. So we just opened up our doors in December of 2022. So I currently lead a 48 00:06:31,800 --> 00:06:38,960 small group at UCLA in the Department of Psychiatry in the Semmel Institute. And so our work really 49 00:06:38,960 --> 00:06:44,240 continues to focus on understanding brain development, not only in autism, but also in other 50 00:06:45,400 --> 00:06:52,120 related childhood neurodevelopmental disorders, including psychosis and ADHD. We're also very 51 00:06:52,120 --> 00:06:58,320 interested in some behavioral symptoms that sort of cross-diagnostic boundaries. So for example, 52 00:06:58,320 --> 00:07:03,520 issues with sleep or sensory processing. And so these are some of the things that we're continuing 53 00:07:03,520 --> 00:07:10,880 to investigate. We conduct MRI studies, and we're also interested in identifying the genes that might 54 00:07:10,880 --> 00:07:17,840 be associated with some of these different behavioral traits. Okay. So something that interests me is 55 00:07:18,400 --> 00:07:24,480 the downstream effect of that might be autism, or it might be OCD, or it might be schizophrenia, 56 00:07:24,480 --> 00:07:34,720 etc. Could you briefly explain maybe what is known about what causes the differences in the disorder? 57 00:07:35,280 --> 00:07:41,600 Sure. Yeah. So a lot of the different neurodevelopmental disorders that you just mentioned are 58 00:07:41,600 --> 00:07:47,920 highly polygenic. And so what polygenic means is that there are many genetic variants across the 59 00:07:47,920 --> 00:07:54,560 genome that are associated with those different disorders. So for example, in the case of autism, 60 00:07:54,560 --> 00:07:59,680 it's hypothesized that hundreds of genes across the genome are associated with the disorder. 61 00:07:59,680 --> 00:08:04,720 Now, the genome-wide association studies that we've performed so far haven't identified all of 62 00:08:04,720 --> 00:08:11,120 those genetic variants. The identification of those variants is really a function of the size of 63 00:08:11,120 --> 00:08:17,360 your study, the sample size. So what we know is that some of the genetic variants, as you mentioned, 64 00:08:17,360 --> 00:08:22,800 that are associated with autism might also be associated with ADHD or schizophrenia. And this 65 00:08:22,800 --> 00:08:28,080 would indicate what we might call a positive genetic correlation, meaning that the same genes 66 00:08:28,080 --> 00:08:35,280 are influencing two traits. And so there are some of those variants that will impact 67 00:08:36,800 --> 00:08:41,600 multiple traits. And then of course, there may be others that are specific to a particular 68 00:08:41,600 --> 00:08:46,240 neurodevelopmental disorder. And so that area of research is still really ongoing, identifying 69 00:08:46,240 --> 00:08:52,080 those shared and unique genetic underpinnings of the different neurodevelopmental disorders. 70 00:08:54,080 --> 00:08:58,000 It always seems like there's a lot of variability and moving parts coming 71 00:08:58,000 --> 00:09:07,680 funneling down into the individual. Let's start with one of your earlier research papers released 72 00:09:07,680 --> 00:09:18,720 in 2017, if you don't mind, in molecular psychiatry. Take us through what questions were asked or 73 00:09:19,520 --> 00:09:26,320 how was it determined. You mentioned earlier, as you're in your education development, 74 00:09:27,120 --> 00:09:34,160 studied oxytocin receptor quite early. And then was just around that time frame or 75 00:09:34,160 --> 00:09:41,280 let's just walk through that paper. Okay, sounds great. Yeah. So this is a paper 76 00:09:42,640 --> 00:09:48,480 focusing on genetic variants, common genetic variants on the oxytocin receptor gene. And so 77 00:09:48,480 --> 00:09:54,960 what we're looking at here is single nucleotide polymorphisms or SNPs. And so these are common 78 00:09:54,960 --> 00:10:00,640 genetic variants that occur across individuals in the population. They're very common. So by 79 00:10:00,640 --> 00:10:06,800 definition, they occur in at least 1% of the population. And there are variations in a single 80 00:10:08,160 --> 00:10:16,960 base. And so you can have somebody who might have an AG genotype, GG or AA. And so basically, 81 00:10:16,960 --> 00:10:21,040 we're looking at differences between people who have these different genotypes at a specific 82 00:10:21,040 --> 00:10:26,720 genetic variant. And so here we wanted to focus on variants on the oxytocin receptor gene. And 83 00:10:26,720 --> 00:10:32,480 we chose that gene for a couple of reasons. First, because there had been animal studies that 84 00:10:32,480 --> 00:10:40,800 showed that there are differences in oxytocin receptor gene expression in subcortical brain 85 00:10:40,800 --> 00:10:46,960 areas that are involved in reward and social processing. And so some of the really foundational 86 00:10:46,960 --> 00:10:55,520 work in this area has been done in animal models, where they found that, for example, in prairie 87 00:10:55,520 --> 00:11:02,640 voles, which engage in high levels of parental behavior and are monogamous, if you look at 88 00:11:02,640 --> 00:11:07,760 brain slices from prairie voles, which you'll find is really dense staining for the oxytocin 89 00:11:07,760 --> 00:11:13,920 receptor in these subcortical reward-related brain regions, including the nucleus accumbens. 90 00:11:13,920 --> 00:11:20,640 Now, you can contrast that with, for example, the meadow vol, which lives in solitary burrows, 91 00:11:20,640 --> 00:11:26,160 and is non-monogamous. And what you'll find is much reduced staining for the oxytocin receptor 92 00:11:26,160 --> 00:11:31,040 in that nucleus accumbens brain region in those meadow voles. And so that's, you know, 93 00:11:31,040 --> 00:11:35,360 sort of an interesting starting point. Some animal work showing that there might be differences in 94 00:11:35,360 --> 00:11:42,160 gene expression in this brain area in these two species that are quite different in terms of 95 00:11:42,160 --> 00:11:49,440 those their social behavior. There had also been some studies suggesting that there might be a link 96 00:11:49,440 --> 00:11:54,720 between different genetic variants on the oxytocin receptor gene and autism, so some family-based 97 00:11:54,720 --> 00:11:59,360 studies. Although I do want to point out that more recent genome-wide association studies 98 00:11:59,360 --> 00:12:03,600 haven't found a link with the oxytocin receptor gene. So a lot of the work that we were really 99 00:12:03,600 --> 00:12:09,440 doing, as you mentioned, this was back in 2017, was more grounded in this, you know, animal work, 100 00:12:09,440 --> 00:12:15,280 which had shown an association with social behavior, parental behavior, and bonding. 101 00:12:15,280 --> 00:12:22,800 And so what we did there was we looked at four different genetic variants on the oxytocin receptor 102 00:12:22,800 --> 00:12:30,720 gene, and we made an additive score across those different genetic variants. So how many oxytocin, 103 00:12:31,280 --> 00:12:38,080 how many autism-associated, you know, alleles does a person have in adding them up across those four 104 00:12:38,080 --> 00:12:45,840 different genetic variants. What we then wanted to do was to look and see how a person's sort of 105 00:12:45,840 --> 00:12:52,960 additive genetic liability for autism on the oxytocin receptor gene might be related to brain 106 00:12:52,960 --> 00:12:59,200 connectivity. And there we were really interested in, again, connectivity of reward-related brain 107 00:12:59,200 --> 00:13:05,120 regions, specifically focusing on the nucleus accumbens. And so I know you've talked in some of 108 00:13:05,120 --> 00:13:10,640 your previous podcasts about some human work that has shown that there may be differences in 109 00:13:10,640 --> 00:13:19,840 nucleus accumbens activity in autistic people when viewing, you know, smiling faces, different sorts 110 00:13:19,840 --> 00:13:26,960 of social rewards. And so that was sort of the basis for this work as well. So what we did is we 111 00:13:26,960 --> 00:13:37,200 had about 40 autistic children and non-autistic children come and do an MRI scan. And what we 112 00:13:37,200 --> 00:13:43,120 did was we looked at connectivity of the nucleus accumbens with different brain regions. And so how 113 00:13:43,120 --> 00:13:50,320 this works is that you would take a seed, a region in the nucleus accumbens, and you extract 114 00:13:50,320 --> 00:13:55,600 brain activity from that region. And then you look to see how that brain activity is 115 00:13:55,600 --> 00:14:02,800 correlated with every other region of the brain. So are there brain areas that are increasing their 116 00:14:02,800 --> 00:14:08,560 activity in synchrony with the nucleus accumbens? And also you can identify brain areas that are 117 00:14:08,560 --> 00:14:12,880 that are sort of anti-correlated, right? Where the nucleus accumbens activity is going up and the 118 00:14:12,880 --> 00:14:20,320 activity in these other brain regions is going down. It's like a seesaw. Yes. Vision it. Yes. 119 00:14:20,320 --> 00:14:28,800 And so what we did was we looked to see, you know, first, what does this connectivity of the nucleus 120 00:14:28,800 --> 00:14:36,000 accumbens look like in our autism group and in our other group? And so what we found was that, you 121 00:14:36,000 --> 00:14:41,440 know, using this seed in the nucleus accumbens, we found really robust connectivity between this hub 122 00:14:41,440 --> 00:14:47,600 of the reward network, the nucleus accumbens, and other subcortical reward-related brain regions, 123 00:14:47,600 --> 00:14:55,200 the frontal cortex. And then we also saw some negative connectivity, so anti-correlated activity, 124 00:14:55,200 --> 00:15:00,880 with subcortical brain regions like the thalamus and also visual cortex. 125 00:15:02,480 --> 00:15:08,560 In autistic groups or the typical groups? In general, in both groups. In both groups. Yes. We 126 00:15:08,560 --> 00:15:13,840 actually did look at the differences also between the autistic group and our typical group. And what 127 00:15:13,840 --> 00:15:18,080 we found was that the typical group had more connectivity between the nucleus accumbens 128 00:15:18,800 --> 00:15:27,280 and an area called the precuneus, which is thought to be really important when sort of thinking about 129 00:15:27,280 --> 00:15:32,080 the thoughts of yourself and others. It's the hub of a network that we call the default mode network, 130 00:15:32,080 --> 00:15:38,240 which I'm not sure if you've discussed yet already on your podcast. Not yet. Just briefly. Okay, great. 131 00:15:38,240 --> 00:15:46,160 So from there, what we did was we really wanted to see the impact of these oxytocin receptor 132 00:15:46,160 --> 00:15:51,360 gene variants on this brain connectivity. So we want to see how is connectivity changing as a 133 00:15:51,360 --> 00:15:59,440 function of increased dosage on this particular gene. And so what we found was that in our autism 134 00:15:59,440 --> 00:16:06,640 group, having more genetic variants associated with autism on the oxytocin receptor gene, 135 00:16:06,640 --> 00:16:13,120 was associated with reduced connectivity between the nucleus accumbens and other 136 00:16:13,120 --> 00:16:18,720 subcortical brain regions, including the cate, putamen, and also frontal brain regions in the 137 00:16:18,720 --> 00:16:29,520 anterior cingulate. So the dorsal striatum, cate and pudiman, for the listener, I've discussed 138 00:16:29,520 --> 00:16:36,640 this. That's more of like a what I know it as stimulus responses. Sure. Yeah, it's involved 139 00:16:36,640 --> 00:16:44,800 sort of in, you know, implicit learning and your right stimulus response. Correct. Okay. I've talked 140 00:16:44,800 --> 00:16:53,120 a lot about stimulus responses. So I just wanted to make mention of that. Yes, perfect. And so what 141 00:16:53,120 --> 00:16:59,360 was interesting is that we found a quite different pattern in our other non-autistic group. So 142 00:16:59,360 --> 00:17:05,600 in non-autistic individuals, what we found was that having more of these, they still have the 143 00:17:05,600 --> 00:17:12,240 autism associated alleles, right? As I said, these are quite common genetic variants. So even in the 144 00:17:12,240 --> 00:17:18,400 non-autistic group, what we found was that having more autism associated variants on the oxytocin 145 00:17:18,400 --> 00:17:25,920 receptor gene was associated with increased connectivity between the nucleus accumbens 146 00:17:25,920 --> 00:17:32,080 and regions in the frontal cortex, and particularly the frontal pole. And so we were sort of curious, 147 00:17:32,080 --> 00:17:38,080 you know, what is this difference in connectivity? What does it sort of mean? And so what we did was 148 00:17:38,080 --> 00:17:44,720 we extracted the connectivity values between that nucleus accumbens and frontal cortex, 149 00:17:44,720 --> 00:17:51,360 and we said, okay, what sort of behavioral measures might this be related to? And so we took that 150 00:17:51,360 --> 00:17:57,840 activity and we looked at its relationship with scores on the social responsiveness scale or SRS. 151 00:17:57,840 --> 00:18:06,960 And so this is a parent-report measure of autism associated behavior. It is, you know, 152 00:18:06,960 --> 00:18:12,080 adequate for use both in autistic and non-autistic groups. A very popular instrument, too, 153 00:18:12,640 --> 00:18:19,360 during the autism assessment. And so what we found was that in this non-autistic group, this increased 154 00:18:19,360 --> 00:18:23,920 connectivity between the nucleus accumbens and frontal brain region was actually related to 155 00:18:23,920 --> 00:18:31,040 lower scores on the SRS, indicating more sort of typical behavior, less autism associated symptoms. 156 00:18:31,680 --> 00:18:37,200 And so we took that to mean that that might be sort of a compensatory mechanism, this increased 157 00:18:37,200 --> 00:18:41,920 connectivity between the nucleus accumbens and frontal cortex, that, you know, when a person 158 00:18:41,920 --> 00:18:48,640 might have more autism associated variants on the oxytocin receptor gene, the extent to which you 159 00:18:48,640 --> 00:18:54,320 can sort of up-regulate this connectivity between the nucleus accumbens and frontal cortex might sort 160 00:18:54,320 --> 00:19:05,600 of buffer and, you know, result in more typical social behavior. Yeah. Kind of the prefrontal, 161 00:19:07,040 --> 00:19:13,360 my vision of it is, you know, I always say, it quiets things so that we can properly evaluate 162 00:19:13,360 --> 00:19:20,320 things. Right. Yeah, that's a big role of the prefrontal cortex is sort of top-down modulation 163 00:19:20,320 --> 00:19:25,280 of some of these subcortical brain structures that we were just talking about. So that's a big 164 00:19:25,280 --> 00:19:35,200 finding that difference. Whenever you first saw the total number of Ls, I'm gonna sort of, I got 165 00:19:35,200 --> 00:19:42,880 that right, they seemed to me like they were pretty similar. Is that the population, has that 1%, 166 00:19:42,880 --> 00:19:48,800 is that from the total, so you're saying the total number of autism associated variants 167 00:19:48,800 --> 00:19:55,440 between the two groups? Yes. Yes, they were very similar. That's right. As I said, these are very 168 00:19:55,440 --> 00:20:02,560 common, you know, everybody has these single nucleotide polymorphisms, these SNPs. And so they 169 00:20:02,560 --> 00:20:10,960 were present in both groups. Okay. So with the, with that SRS, what did that inform you or what, 170 00:20:10,960 --> 00:20:18,320 what did that lead to as far as what was the next step here? The next step. Yeah. So, 171 00:20:18,960 --> 00:20:23,520 so what we found was this relationship with specifically the social cognition sub-scale 172 00:20:23,520 --> 00:20:28,240 of the SRS, which makes a lot of sense given what we know about the role of the frontal cortex in 173 00:20:28,240 --> 00:20:34,560 cognitive functioning. And so the thing about the study that I just mentioned is that it was 174 00:20:34,560 --> 00:20:43,040 performed in two groups of largely male children. And so as you know, there's a large male bias in 175 00:20:43,040 --> 00:20:48,400 the diagnosis of autism. And so, you know, we sort of started with this group of mostly male 176 00:20:48,400 --> 00:20:53,680 individuals. But what we really wanted to do was to move on and also look at whether there might 177 00:20:53,680 --> 00:21:00,640 be sex differences in the effects of these oxytocin receptor gene SNPs on brain connectivity. 178 00:21:00,640 --> 00:21:08,640 And so in the next study that we did, we worked with the Gendar Consortium, which is a group of 179 00:21:10,560 --> 00:21:17,200 researchers at different universities across the US who worked to gather a large neuroimaging cohort 180 00:21:17,200 --> 00:21:24,560 of girls with autism and without autism. And so in our next study, what we did was a similar set 181 00:21:24,560 --> 00:21:30,080 of analyses, but this time looking at sex differences in the effects of the oxytocin receptor gene on 182 00:21:30,080 --> 00:21:37,840 reward network connectivity. Yeah, this is wonderful data. What comes after this is just 183 00:21:37,840 --> 00:21:45,600 wonderful data, I think, in the role of autism. Before we get into the data, can you explain to 184 00:21:45,600 --> 00:21:51,840 us about Gendar? Sure, yeah. So this was a collaborative effort across a couple of different 185 00:21:51,840 --> 00:21:59,200 research institutions in the US in order to recruit and collect data from a large cohort 186 00:21:59,200 --> 00:22:05,760 of autistic girls. And so the four different sites for Gendar and Gendar stands for gender 187 00:22:05,760 --> 00:22:11,120 exploration of neurogenetics and development to advance autism research, just so everyone knows 188 00:22:11,120 --> 00:22:18,000 what that stands for. But so the girls were recruited and participated in MRI scanning at four 189 00:22:18,000 --> 00:22:24,720 different sites at Harvard, Seattle Children's Hospital UCLA, and also Yale. And so the data 190 00:22:24,720 --> 00:22:30,000 came from these various sources and really gave us the opportunity to examine what was when this 191 00:22:30,000 --> 00:22:38,960 data was published, you know, the largest study of neurogenetics in girls with autism. 192 00:22:39,840 --> 00:22:43,760 There's some powerhouse universities there too involved. Yes, absolutely. 193 00:22:45,680 --> 00:22:53,520 Let's talk about some of those scannings or the scanning and the connectivity with this data. 194 00:22:53,520 --> 00:23:00,880 Sure, sounds great. So similar to the previous study, everybody came in and had an MRI scan. 195 00:23:00,880 --> 00:23:06,400 These MRI scans are done, I should have mentioned, while everybody is at rest. And so 196 00:23:07,200 --> 00:23:11,840 people come in and have an MRI scan. But what they're actually doing is just looking at 197 00:23:11,840 --> 00:23:16,880 a little black sort of crosshair plus sign on a white screen. And they're told that they can 198 00:23:16,880 --> 00:23:23,200 just let their mind wander while we take pictures of their brain. And so we use those pictures as 199 00:23:23,200 --> 00:23:30,000 I mentioned in order to look at these co fluctuating signals across different brain areas. And so here 200 00:23:30,000 --> 00:23:35,840 again, we're looking at co fluctuating symptoms between the nucleus accumbens that have the reward 201 00:23:35,840 --> 00:23:46,880 network and other brain regions. Okay. And some interesting findings, I think, is how the autistic 202 00:23:46,880 --> 00:23:54,480 girls one differs from the autistic boys, the similarities maybe between autistic girls and 203 00:23:54,480 --> 00:24:03,680 the typicals. Right, right, right. So what we found was that similar to what we found just 204 00:24:03,680 --> 00:24:09,200 generally for connectivity in the male groups that when we looked at what other brain regions the 205 00:24:09,200 --> 00:24:14,400 nucleus accumbens was connected to was really robustly connected to other reward related brain 206 00:24:14,400 --> 00:24:20,880 regions and also frontal cortex. And then again, again, we found those negative associations 207 00:24:20,880 --> 00:24:26,640 with the thalamus and visual areas. And that was both in autistic girls and non autistic girls. 208 00:24:28,000 --> 00:24:34,000 So the next thing that we wanted to do was to look to see whether there may be any differences 209 00:24:34,000 --> 00:24:38,560 between those two groups. And we actually didn't find any differences just looking at, you know, 210 00:24:38,560 --> 00:24:45,120 connectivity of the nucleus accumbens more generally. And so the next thing that we did was to look at 211 00:24:45,120 --> 00:24:52,160 how these oxytocin receptor gene variants might influence this connectivity. So what we found was 212 00:24:52,160 --> 00:25:00,240 that in the non autistic group, having more autism associated variants on the oxytocin receptor gene 213 00:25:00,240 --> 00:25:08,880 was associated with increased connectivity with frontal brain regions. While in the autistic 214 00:25:08,880 --> 00:25:15,280 female group, we actually found that more of these oxytocin receptor gene variants was associated 215 00:25:15,280 --> 00:25:21,040 with increased connectivity with other sub cortical brain regions, including the caudate and the 216 00:25:21,040 --> 00:25:25,600 thalamus. And so like we mentioned before, these are two brain regions that are very important 217 00:25:25,600 --> 00:25:30,560 in implicit learning. And so we wanted to see what this connectivity might be associated with. 218 00:25:30,560 --> 00:25:35,360 And again, we looked at associations with other behavioral measures. And what we found was that 219 00:25:35,360 --> 00:25:41,600 higher connectivity between the nucleus accumbens and the sub cortical areas was associated with 220 00:25:41,600 --> 00:25:49,680 higher scores on the ADOS repetitive behavior scale, which we thought was quite interesting. 221 00:25:49,680 --> 00:26:00,240 That is interesting. It kind of leads me to a question of, well, maybe one, what draws these 222 00:26:00,240 --> 00:26:07,120 individuals, these autistic girls into an assessment? And how, what are their assessment 223 00:26:07,120 --> 00:26:13,600 results look like to receive that diagnosis? Right, right. I mean, so overall, we did find that the 224 00:26:13,600 --> 00:26:23,920 autistic girls had higher SRS scores relative to the non autistic group. But, you know, as you know, 225 00:26:23,920 --> 00:26:31,920 there are, there's sort of ongoing research in terms of the diagnostic criteria that goes into 226 00:26:32,640 --> 00:26:39,600 identifying girls and boys with autism. And so one thing that you may have talked about already 227 00:26:39,600 --> 00:26:44,720 is the female protective effect or this hypothesis of a female protective effect in autism, 228 00:26:45,440 --> 00:26:53,680 which sort of suggests that it's possible that females may require a higher number of genetic 229 00:26:53,680 --> 00:27:02,160 variants or environmental factors to occur in order to sort of express the autism phenotype 230 00:27:02,160 --> 00:27:08,560 relative to males. So that, you know, that females would require relatively more of these 231 00:27:08,560 --> 00:27:15,440 different factors in order to actually go ahead and get a diagnosis. Okay. There, it appears 232 00:27:15,440 --> 00:27:24,080 that their social motivation is much different than autistic boys and pretty similar, if not 233 00:27:25,440 --> 00:27:33,120 equal to or greater than the non-autistics. And something else that I was wondering is 234 00:27:33,120 --> 00:27:42,960 if that social motivation is actually above the normal where they might need more affinity or 235 00:27:42,960 --> 00:27:53,680 more social interaction. And if that is a result of the biology that gives them autism or what leads 236 00:27:53,680 --> 00:27:59,600 them into the assessment. Yeah, that's really interesting. You know, I haven't done a lot of 237 00:27:59,600 --> 00:28:06,880 research myself on differences on the SRS or social motivation in girls with autism, but I think 238 00:28:06,880 --> 00:28:17,840 that's a really interesting point. Yeah, okay. It's also the question about how girls camouflage 239 00:28:17,840 --> 00:28:24,240 or mask. Right. Yeah, I think that leads in really well to actually the next finding. Maybe I should 240 00:28:24,240 --> 00:28:30,640 talk a little bit more about the next finding in the paper. Okay, great. So the next thing that we 241 00:28:30,640 --> 00:28:38,560 wanted to do was to compare autistic females and autistic males. So how might this, you know, 242 00:28:38,560 --> 00:28:42,880 differences in the oxytocin receptor gene be differentially modulating brain connectivity 243 00:28:42,880 --> 00:28:50,480 in these two groups? And so what we found was that relative to autistic males, our autistic females 244 00:28:50,480 --> 00:28:56,480 showed up regulation of connectivity between the nucleus accumbens and the frontal brain region. 245 00:28:57,040 --> 00:29:02,000 And so this was really exciting to us because there was, you know, really a lot of overlap 246 00:29:02,000 --> 00:29:08,480 between this frontal brain region that we found was upregulated in the autistic females and the 247 00:29:08,480 --> 00:29:15,200 brain region where we had previously found in the 2017 paper that higher connectivity in males was 248 00:29:15,200 --> 00:29:21,280 associated with lower SRS scores. So what we did again here was we took connectivity between the 249 00:29:21,280 --> 00:29:25,760 nucleus accumbens and this frontal brain region and we plotted them as a function of the SRS 250 00:29:27,440 --> 00:29:34,400 in our girls with autism. And so what we found was that really mirroring the results from 2017, 251 00:29:34,400 --> 00:29:38,880 again, having more connectivity between the nucleus accumbens and frontal brain regions 252 00:29:38,880 --> 00:29:44,240 was again associated with lower scores on the social responsiveness scale. 253 00:29:44,240 --> 00:29:50,880 Sort of suggesting that there might be this sort of neurobiological compensatory mechanism that 254 00:29:50,880 --> 00:29:56,880 may facilitate some of this sort of masking behavior that you were just mentioning in girls 255 00:29:56,880 --> 00:30:01,200 with autism, given that we're finding this increased connectivity between frontal brain 256 00:30:01,200 --> 00:30:05,760 regions involved in cognition and cognitive control and these subcortical brain regions 257 00:30:05,760 --> 00:30:14,160 involved in reward and social processing. Wow. That's quite the findings as far as recent 258 00:30:14,160 --> 00:30:21,760 autism research and especially the gender differences. With those findings, how do you 259 00:30:21,760 --> 00:30:32,080 anticipate that informing the assessment side or the instruments used for diagnosing autism? 260 00:30:34,320 --> 00:30:39,840 I mean, you know, I think what it really indicates is that there are probably other 261 00:30:39,840 --> 00:30:49,760 genetic and environmental factors that interact with the oxytocin receptor gene that cause these 262 00:30:49,760 --> 00:30:58,960 that are associated with these sex differences. And so what those are, I think is still an open 263 00:30:58,960 --> 00:31:10,880 question. And so I'm not sure how this might impact use of the SRS in order to and SRS is 264 00:31:10,880 --> 00:31:16,720 not a diagnostic instrument, in fact, for autism. The ADOS and the ADIR, the gold standards for 265 00:31:16,720 --> 00:31:24,160 autism diagnosis. But what it sort of suggests is one biological mechanism that might be sort of 266 00:31:24,160 --> 00:31:32,400 facilitating enhanced social behavior in girls with autism. This female protective effect, 267 00:31:33,760 --> 00:31:44,240 findings like that explains a lot. It explains a lot about just the recency of autism, 268 00:31:44,240 --> 00:31:53,760 both the increase of SS or a diagnosis as we were down to like 1 in 36 or whatever. And then 269 00:31:53,760 --> 00:32:01,520 just what we knew about that boy bias. Right. Yeah. So there's been some previous research 270 00:32:01,520 --> 00:32:08,800 showing that, you know, there are differences in gene expression in males and females. This may be 271 00:32:08,800 --> 00:32:14,160 one thing that also interacts with autism genetic risk differences in hormone levels, 272 00:32:15,040 --> 00:32:20,640 differences in, you know, environmental inputs. And so there are a lot of factors, I think that, 273 00:32:20,640 --> 00:32:26,800 you know, need to be investigated in order to better understand some of these sex differences, 274 00:32:26,800 --> 00:32:33,280 and especially potential sex differences in the influence of autism associated genetic variants 275 00:32:33,280 --> 00:32:39,440 on brain development. I do also want to mention that, you know, in this study, we were looking at 276 00:32:39,440 --> 00:32:45,840 one gene, right, the oxytocin receptor gene. But there are actually many genes, as I mentioned, 277 00:32:45,840 --> 00:32:52,080 across the genome that are associated with autism. And so more current research is taking 278 00:32:52,080 --> 00:32:58,480 more of a sort of genome wide approach in order to look at genetic variants and how they might be 279 00:32:58,480 --> 00:33:05,200 related to brain development. And so, you know, more recently, we've been doing things like 280 00:33:05,200 --> 00:33:12,080 looking at polygenic risk scores for autism, which really add up. So the idea there is that you would 281 00:33:12,080 --> 00:33:19,280 add up the sort of effects of different autism variants across the entire genome 282 00:33:19,280 --> 00:33:24,880 to generate a single score. And then you could look at that and see how it's related to brain 283 00:33:24,880 --> 00:33:31,440 structure and function across development. How easy is that to do? Is that sometimes 284 00:33:31,440 --> 00:33:37,360 complicated per individual? So, I mean, there are a couple of steps. The first thing that you really 285 00:33:37,360 --> 00:33:43,040 need is a very well-powered genome wide association study of autism. And so currently, you know, 286 00:33:43,040 --> 00:33:48,320 our current GWAS of autism are still relatively limited in their power to detect the genetic 287 00:33:48,320 --> 00:33:53,520 variants associated with autism compared to other psychiatric diagnoses, for example, 288 00:33:53,520 --> 00:34:00,320 schizophrenia, where there are very large GWAS studies. And so, you know, we really need to 289 00:34:00,320 --> 00:34:06,080 continue increasing our sample size in order to be able to detect all of these different 290 00:34:06,080 --> 00:34:11,520 genome wide genetic variants that might be associated with autism. And then from there, 291 00:34:11,520 --> 00:34:21,600 it's sort of a matter of having, as I mentioned, the well-powered GWAS, and then also having 292 00:34:21,600 --> 00:34:31,520 genetics data of your own in another cohort. So at UCLA, we often collect saliva in order to do 293 00:34:31,520 --> 00:34:37,280 genotyping from the participants that come in. And so when you have genotype data from your own 294 00:34:37,280 --> 00:34:42,560 individual group of participants, you can sort of marry those two different sources of data in 295 00:34:42,560 --> 00:34:51,680 order to make a score indicating, you know, genetic predisposition to autism in the data 296 00:34:51,680 --> 00:34:58,640 that you have from your own unique participants. Well, that's my best grade insight. I'm glad, 297 00:34:58,640 --> 00:35:05,440 I'm glad you shared that. That's something, that's information that is hard to come by for 298 00:35:06,400 --> 00:35:14,080 the lay public, just that information. Something with the oxytocin is very interesting, 299 00:35:14,080 --> 00:35:21,280 though, because of the everything it's attached to, both in the central and peripheral nervous 300 00:35:21,280 --> 00:35:28,640 system. So one, I guess it seems like that would be hard to narrow down, but two, 301 00:35:31,440 --> 00:35:36,880 the amount of roles it has seems like a great contender on that end. 302 00:35:38,000 --> 00:35:44,640 Yes, it has a lot of roles. You're so right. So the oxytocin receptor gene, when it's bound to, 303 00:35:44,640 --> 00:35:51,760 sort of through a cascade of events, ends up impacting intracellular calcium levels. And so, 304 00:35:52,560 --> 00:35:58,320 you know, that can promote the release of different neurotransmitters. Oxytocin receptors 305 00:35:58,320 --> 00:36:05,840 expressed on excitatory neurons can promote the release of glutamate, which leads to enhanced 306 00:36:05,840 --> 00:36:13,120 excitatory neurotransmission. For example, in the hippocampus, you know, oxytocin has been found to 307 00:36:13,120 --> 00:36:20,400 enhance excitatory synaptic transmission and also help with learning and memory. Oxytocin receptors 308 00:36:20,400 --> 00:36:26,080 are also expressed on inhibitory interneurons, where they can influence the release of GABA, 309 00:36:26,080 --> 00:36:33,440 which is the main inhibitory neurotransmitter in the brain. And so that is thought to be involved 310 00:36:33,440 --> 00:36:39,760 with some of the sort of anti-anxiety effects that it has by working on inhibitory control in the 311 00:36:39,760 --> 00:36:45,200 amygdala. And then in the prefrontal cortex that we were talking about recently, oxytocin can 312 00:36:45,200 --> 00:36:51,920 influence both excitation and inhibition. So it definitely has many roles and also, you know, 313 00:36:51,920 --> 00:36:59,040 the roles are sort of dependent on brain region as well. So it leads up lots of different potential 314 00:36:59,040 --> 00:37:06,400 avenues for investigation, I think. Yeah, yeah. Oxytocin is a very fascinating molecule in our 315 00:37:06,400 --> 00:37:17,120 body. After this data, what kind of information could you share about how somebody in the lay 316 00:37:17,120 --> 00:37:25,600 public can find this information and kind of develop their understanding of this spectrum 317 00:37:25,600 --> 00:37:31,920 now that this work spectrum has kind of opened up? Right. No, I mean, I think what you're doing 318 00:37:31,920 --> 00:37:37,200 here is fantastic. Bringing, you know, scientists on to talk about their work. It's definitely a 319 00:37:37,200 --> 00:37:42,640 challenge. You know, a lot of the work that we publish is in different scientific journals. It's 320 00:37:42,640 --> 00:37:47,760 not always accessible to a lot of people. I think scientists are also trying to do a better job of 321 00:37:47,760 --> 00:37:55,040 actually communicating with the public through social media and other means, right? I think also 322 00:37:55,040 --> 00:38:02,000 since COVID, we've had a huge opportunity to record lectures and talks and presentations at 323 00:38:02,000 --> 00:38:08,960 different universities and post them online. You know, going to the websites of different 324 00:38:09,600 --> 00:38:16,320 autism centers and research groups are all things you can do in order to learn more about this area 325 00:38:16,320 --> 00:38:21,280 of research. But I think what you're doing here is really fantastic. So happy to have been here. 326 00:38:21,280 --> 00:38:26,560 Yeah, it was one of my it was one of the things that motivated me. It's having, 327 00:38:26,560 --> 00:38:31,760 reviewing scientific literature, then bringing scientists on like yourself and sharing such 328 00:38:31,760 --> 00:38:39,120 wonderful data. What are some of the things that you're currently working on? Yeah, so a couple 329 00:38:39,120 --> 00:38:44,480 of things we're working on. One is again, these large scale genome wide association studies of 330 00:38:44,480 --> 00:38:52,240 autism. And I am particularly passionate about performing that research in diverse populations. 331 00:38:52,240 --> 00:38:57,680 And so a lot of the what we know about the genetics of autism and a lot of different 332 00:38:57,680 --> 00:39:04,640 psychiatric disorders right now is really focused on European populations. And we also know that 333 00:39:04,640 --> 00:39:14,880 what we find in these European populations might not always, you know, sort of be portable to other 334 00:39:14,880 --> 00:39:22,080 other populations from sort of a precision medicine perspective. So your ability to predict 335 00:39:22,080 --> 00:39:27,280 using genetics is impacted based off of the different populations you might be looking at. 336 00:39:27,280 --> 00:39:34,080 And so what we really need is larger, more diverse, genetic studies of autism, as I mentioned, 337 00:39:34,080 --> 00:39:38,160 in order to identify these different variants that might be so to see it in not just with autism, 338 00:39:38,160 --> 00:39:44,880 but also with other, you know, co occurring issues, for example, sensory processing problems, 339 00:39:45,600 --> 00:39:52,240 you know, mode motor related delays. And so there's a lot of room, I think, in order to improve in 340 00:39:52,240 --> 00:39:57,040 that area. So that's one of the one of the areas that we're currently doing some research on. 341 00:39:57,840 --> 00:40:02,720 And then another area is, you know, everything we talked about today is the impact of these 342 00:40:02,720 --> 00:40:09,280 common genetic variants or SNPs on brain connectivity. But what's the mechanism through 343 00:40:09,280 --> 00:40:14,800 which those those SNPs are actually influencing brain development, right? So we know that 344 00:40:15,440 --> 00:40:22,640 genetic variation in these different SNPs can also influence gene expression. And so what we're 345 00:40:22,640 --> 00:40:29,760 also working to understand is how these different genetic variants might impact brain gene expression. 346 00:40:29,760 --> 00:40:35,040 And then how that gene expression in turn influences developmental trajectories during 347 00:40:35,040 --> 00:40:40,720 childhood and adolescence. Wow. It seems like such a crucial time for that. 348 00:40:42,080 --> 00:40:47,280 Yeah, it's really a great time to be doing this type of research, because a lot of these really 349 00:40:47,280 --> 00:40:52,880 large scale data sets have recently become, you know, publicly available. None of this work 350 00:40:52,880 --> 00:41:01,040 could really be done without the participation of the community. But, but yeah, it's a great 351 00:41:01,040 --> 00:41:06,160 time for doing this type of work. A lot of the different genetic variants that we've been talking 352 00:41:06,160 --> 00:41:13,200 about today, and, you know, the genetic variants identified through GWAS of autism, each individual 353 00:41:13,200 --> 00:41:21,600 variant has a very, very small impact, a very small effect size. So in order to identify these 354 00:41:21,600 --> 00:41:28,880 these variants, you really need very well powered large scale studies. And so I think we're sort of, 355 00:41:28,880 --> 00:41:33,520 you know, we're in that era now where a lot of these studies are available. And I think it's 356 00:41:33,520 --> 00:41:41,360 going to be great for facilitating our understanding of autism and lots of other disorders as well. 357 00:41:41,360 --> 00:41:45,520 Yeah, it's something that makes me anxious and excited about 358 00:41:45,520 --> 00:41:53,440 what happens next. What do you think autism is in 10 years? In 10 years, I hope we're working to, 359 00:41:54,320 --> 00:42:03,600 you know, just understand the unique biology and needs of the individual, and that we're able to 360 00:42:05,120 --> 00:42:13,280 wear helpful intervene earlier on before the sort of manifestation of really difficult and what 361 00:42:13,280 --> 00:42:21,520 can be, you know, impairing symptoms and that we would know earlier on in development who is more 362 00:42:21,520 --> 00:42:30,080 likely to go on to need, you know, more targeted interventions for some of the different symptoms, 363 00:42:30,080 --> 00:42:36,240 and that our work in genetics and behavior and brain development can help to inform some of those 364 00:42:36,240 --> 00:42:42,640 some of those findings. Yeah, absolutely. That's where it's happening. I'm thinking about 365 00:42:44,560 --> 00:42:50,080 April 2024 communications biology from UCLA released a study on six week old, 366 00:42:50,960 --> 00:42:59,600 and they followed them up to 12 months. And that looked that was some revealing data about how 367 00:42:59,600 --> 00:43:07,040 the 12 month at 12 month old, they started developing autistic traits using an instrument. It wasn't an 368 00:43:07,040 --> 00:43:13,760 ADOS, I don't believe. I can't remember. But studies like that, and then the intranasal 369 00:43:14,400 --> 00:43:23,680 option of oxytocin seems like it has a lot of promise. It's very low risk, which is phenomenal. 370 00:43:23,680 --> 00:43:33,840 It's very inconsistent, but it does show that to it does help some. And so that's, that's a huge step. 371 00:43:36,000 --> 00:43:41,680 I agree. Yeah, I think this work really helps to it just inform our understanding of how variation 372 00:43:41,680 --> 00:43:47,360 in human genetics can lead to variation in brain development and behavior. Everything that we talked 373 00:43:47,360 --> 00:43:53,840 about today, all the individuals who participated were children and adolescents. And so I think your 374 00:43:54,880 --> 00:44:02,080 sort of alluding to moving to younger ages is, you know, very timely as well. At this point, 375 00:44:02,080 --> 00:44:08,560 a lot of that data, the infant data is still the sample sizes are relatively small. And so, 376 00:44:08,560 --> 00:44:12,960 you know, that's one area that I think we need to work on increasing sample size there so that we 377 00:44:12,960 --> 00:44:18,880 have lots of power in order to identify different associations. But it's definitely a really 378 00:44:19,600 --> 00:44:24,240 interesting time to be working in this in this area, all the all the data from the 379 00:44:24,880 --> 00:44:28,960 different modalities seems to be coming together, you know, the genetics, the neuroimaging and the 380 00:44:28,960 --> 00:44:33,840 behavior. And I think that's really, really interesting and can be really informative for 381 00:44:33,840 --> 00:44:40,320 our understanding of heterogeneity in autism and other and other traits. 382 00:44:40,320 --> 00:44:46,560 Yeah, yeah, I think you that was that was very well said about different disciplines are coming 383 00:44:46,560 --> 00:44:54,400 together and working on kind of a common goal. And that's going to really just accelerate information. 384 00:44:55,520 --> 00:44:56,880 So that's very promising. 385 00:45:00,400 --> 00:45:06,240 Well, I can't thank you enough for coming on and sharing this wonderful data and being so kind. 386 00:45:06,240 --> 00:45:13,360 And just letting us know what to expect from you and the autism scientific community over the next 387 00:45:13,360 --> 00:45:19,760 few years and everything looks promising. And maybe we'll just hold you up to that. 388 00:45:21,040 --> 00:45:26,240 Yes, thank you so much for having me and thank you for what you're doing here, you know, spreading 389 00:45:26,960 --> 00:45:32,800 spreading information and inviting me on it's been a great experience. And I know, you know, 390 00:45:32,800 --> 00:45:37,760 a lot of people are learning from you and what you're doing here. And so I appreciate you and 391 00:45:37,760 --> 00:45:43,120 and good luck moving forward. Wow, thank you. Thank you so much. I hope you have a wonderful day 392 00:45:43,120 --> 00:45:50,240 and good luck with everything. You too. Thank you. If you're listening and enjoy the episode 393 00:45:50,240 --> 00:45:59,360 or enjoy the podcast, please feel free to leave a review or rating. In podcasting, reviews, ratings 394 00:45:59,360 --> 00:46:18,720 and downloads are huge. And I very much appreciate your feedback. You can contact me at info.fromthespectrum.gmail.com 395 00:46:18,720 --> 00:46:30,240 and thank you for listening to From the Spectrum podcast.