This project will expand an existing longitudinal study that tracked children from infancy and recently reported that a high proportion of those who were later diagnosed with autism showed an excess volume of cerebrospinal fluid in their brains when they were 6 months old. To date, assessment of these infants stopped at a diagnosis. This student will administer additional assessments to these families to determine whether this increase in cerebrospinal fluid persists as the children age, whether it’s associated with any behavioral features including attention difficulties, executive function and ADHD, and whether it predicts differences in autism severity.
Following Up with Infants with a Unique Biomarker for ASD
Brain imaging studies of infants with autism have shown a faster rate of expansion of a layer of the brain called the cortex in those who go on to be diagnosed with autism. Some infants also exhibit macrocephaly (larger than expected overall brain size). However, little is known about these features in autism. This study will develop a new model system utilizing organoids, which are aggregates of cells obtained directly from individual study participants and then further manipulated in a dish to recreate the cortex. In this way, scientists can understand how cells divide, expand, and grow. This researcher will then compare features in the organoids with brain scans collected from the same individual. This work will provide the research community with a novel way to test therapies and interventions on those with macrocephaly.
Most of the genetic research conducted to understand rare genetic forms of autism has been focused on the coding regions of the DNA. In genetics, the coding regions are specific parts of the DNA sequence that directly encode instructions for building proteins. There is still a lack of knowledge around the non-coding regions of the genome, which do not contain instructions to make proteins but rather regulate how genes are turned on and off. Recent studies have shown that the non-coding regions play an integral role in brain development. This study will look at over 700,000 non-coding variants in autism to determine their role and importance.
Following the initial analysis, regions that are determined to play a role in the coding of a gene called SCN2A will be targeted. SCN2A is a protein that controls how cells turn on and off, and is strongly tied to both autism and epilepsy. Identifying and validating the enhancers of ASD-associated genes like SCN2A will help scientists better understand mechanisms behind genetic influence of autism and comorbid features, and will also provide novel therapeutic targets for single gene disorders.
This project is graciously co-funded by FamilieSCN2A, the patient advocacy group that supports families with this genetic variation.
Compared to people without autism, the risk of Alzheimer’s disease is 2.6 times higher in people with autism, and they are twice as likely to die prematurely – with autistic women being at even higher risk for premature death. However, very few research studies focus on or even include autistic adults who are middle aged and older. This project capitalizes on a cohort of older autistic and neurotypical adults who receive assessments of brain structure, memory function, and intellectual ability at multiple timepoints as they age. Integrating brain imaging, genomic techniques, and statistical tools, this researcher will determine if autism risk genes also lead to memory decline and how these genes affect brain structure and the cortical thinning that is typical in all older adults. In addition, they will examine sex differences in autistic adult memory and changes in the memory system across age, with the goal of identifying sex-specific biomarkers that can be used to predict who will be most vulnerable to adverse aging outcomes. This work has implications for the future development of precision medicine and other interventions that will increase the quality of life for older adults across the spectrum.
On this week’s podcast episode, more on genetics as an influence to an autism diagnosis with a twist: can genetics lead to a specific treatment for core symptoms – across the board? How do you measure such broad symptoms? Our Rett Syndrome family friends and colleagues developed a novel outcome measure to capture what was most important to them, and the FDA approved it for use in a clinical trial. Years later, a new drug was approved that led to a reduction in behaviors associated with Rett Syndrome. Autism can take a lesson from this. In addition, can the genetics of autism be explained by parents with similar phenotypes? This is called assortative mating. The answer is complex.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10450502/pdf/fped-11-1229553.pdf
Very rarely are scientists able to look at single genes within the brains of people across neuropsychiatric disorders and understand how the genes in each of these cells influence expression of proteins and interactions of different cells with each other. Recently, a collaboration called PsychENCODE released a series of papers that investigated what genes are expressed in what cells in autism in different situations, how cells that communicate interact with more support or glial cells, and what mechanisms are in place to identify ways in which the broad environment (chemicals, contextual factors, illness) may influence gene expression leading to disorders like autism, schizophrenia and bipolar disorder. This podcast summarizes these papers as they are related to autism – or at least tries to.
In recognition of Father’s Day on the 16th, today’s podcast includes the latest research on fathers. Fathers may often be the “secondary caregiver” but should hardly be dismissed as inconsequential. Father’s sensitivity and insightfulness plays an important part in development, psychiatric diagnoses (including autism) change the the chance of having a child with autism, and more understanding is being done on the heritable factors associated with chemical exposures in the father.
https://www.tandfonline.com/doi/full/10.1080/14616734.2024.2326416
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11059471/pdf/main.pdf
Scientists have spent a lot of time trying to understand the biology of autism, unfortunately in the past, scientific studies had everyone with autism lumped together in one group and there are so many differences between people with a diagnosis that any features of the diagnosis itself were hard to detect. In the past, researchers grouped those who are cognitively abled with those who have average or superior intellectual disability, those who are able to express themselves verbally with those who cannot, and those who need 24-hour care with those who can live independently. This week, researchers changed that pattern of lumping all the autisms together by using profound autism as a subgroup and as a way to determine differences across autism subgroups. Researchers at @UCSD examined the cell sizes and the brain sizes of individuals with profound autism and compared them to those with non-profound autism. They found the larger the brain cell, the larger the brain size in different areas, and the more profound the autism. There were differences between profound autism, non-profound autism and typically developing controls. This is just a first step in using different classifications of behavior to understand the neurobiology of ASD and link brain function to autism behaviors, leading to more specific support for those across the spectrum. Learn more on this week’s podcast episode.
https://molecularautism.biomedcentral.com/articles/10.1186/s13229-024-00602-8#Sec26
As health care and outcomes for very premature infants has improved, scientists are able to track their longer term behavioral development, and that includes risk of developmental disorders like autism. On this week’s #ASFpodcast, Dr. Jessica Bradshaw discusses her recent research examining biological predictors like body temperature and heart rate and how they are linked to early autism features like social communication deficits in toddlerhood. All parents of pre-meet need to be vigilant and lean into resources like @BabyNavigator to help track their infant’s development.
In honor of the last week of Autism Awareness/Acceptance Month, we review in this podcast episode two new scientific findings that call for more awareness and action, and less acceptance of the status quo. First: sex differences in autism are not well understood, and as it turns out, the influences on a diagnosis are different. Males have a higher rate of heritability compared to females. Second, those with rare genetic disorders have very few options for treatment, but a new study promises hope for more personalized approaches. The researchers use Timothy Syndrome as an example of how cells can start to function properly through a targeted approach which focuses on a small part of a gene. This is potentially life saving for individuals with this disorder.
Did you miss the ASF 2024 Day of Learning and can’t wait for the videos to be posted? This is a 17 minute brief summary of what was discussed, but unfortunately, with no visuals. Don’t just listen to the podcast, watch the videos when they are posted. Also included in this podcast is a shoutout to the Profound Autism Summit which brought together hundreds of advocates around those who need 24/7 care for their lives. The link to their advocacy page is here: https://www.votervoice.net/ProfoundAutism/campaigns/112917/respond
This podcast episode provides updates on studies that help with prediction of an autism diagnosis – which is important for preparing for the future and for intervening early. First, a study that uses environmental factors to create an equation for the probability of a diagnosis following a combination of of non-genetic factors only which does a fairly good, but not perfect, job at predicting a diagnosis. Second, a study that looks at the accuracy of a machine that predicts autism from eye gaze as early as 9 months of age and with only a 2 minute test. This one wasn’t as accurate as the one that takes longer and tests older kids, but it’s a first step. No ONE thing does a perfect job at predicting a diagnosis – it’s going to be a combination of things, tested over time and multiple times that will be most helpful at predicting a diagnosis. Both studies are open access!
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10904522/pdf/fpsyt-15-1291356.pdf