A Hunt for Early Indicators in Autism

The case of finding a cause for Autism Spectrum Disorder (ASD) has been a long and complex one. It is extremely widespread, and its diversity in the the effect can range from extremely severe to almost unnoticeable. As more research has come out about the success in early treatment on severity of symptoms for those living with autism, it has become more and more important to find and pinpoint the key causes as a way to target and identify them for future people at risk.

Dr. Maggie Guy conducted research on just one of the pieces that may contribute to the cause and help lead to early identification of ASD. In her research, she looked at three different populations: low-risk controls (LR), siblings of children with ASD (ASIBs), and infants with fragile X syndrome (FXS). ASIBs are shown to be 18-20 times more likely to receive diagnosis, and they show the broader autism phenotype. Infants with FXS are at high risk, as FXS is the most common known genetic cause of ASD, and 60-74% of those with FXS meet criterion for ASD. Dr. Guy’s research was conducted with the question of looking at the neural correlates of face-processing across these groups, but on a broader level, looking at the heterogeneous pathways to ASD emergence.

In this particular study, Dr. Guy used a series of different brief stimuli presentations (pictures of toys or faces) and looked at both Event-Related Potential (ERP) results and used cortical source analysis. The negative ERP component N290 shows a greater response or activation to faces than toys in all groups, however there were more muted responses in ASIBs to faces than the other two groups, and the strongest responses were from those participants in the FXS group. In addition to the N290, the negative central (Nc) shows responses to visual stimuli with its greatest amplitude being in response to novel stimuli. In these results, both LR and ASIB infants showed a higher amplitude Nc response to novel stimuli than to their mother’s face, while FXS infants showed a higher amplitude Nc response to familiar stimuli than the novel stimuli presented. The results of Dr. Guy’s study could help show just one way to potentially target early indicators of ASD.

Another study led by Christopher Walsh, chief of genetics at Boston Children’s Hospital, focused on the importance of de novo, non-inherited, or mosaic mutations in those with ASD. In this particular study, the researchers relied on DNA from blood and saliva to identify these potential neural correlates for ASD known as mosaic mutations. Many of these mosaic mutations happen to be highly expressed in the amygdala. Some of the genes that were targeted in this study that have mosaic mutations were SCN2A, one of the top autism risk genes, and SMARCA4, which regulates the expression of another leading autism risk gene. The results of this study indicated that mosaic mutations have milder effects on ASD than those affecting the entire body, but this is not to say that the results are not significant. Both the findings of Dr. Guy and Dr. Walsh have helped progress the identification of ASD’s key factors. Whether the results indicated a gene or factor of a key factor or as a smaller contributing factor, it helped narrow down those potential factors to hopefully help future research.

References: https://www.spectrumnews.org/news/large-study-shines-spotlight-mosaic-mutations-autism/

Autism Spectrum Disorder (ASD) Broad Range of Potential Factors: The Search Continues

Autism Spectrum Disorder (ASD) refers to serious cognitive and behavioral disorders that affect a person’s ability to communicate and socially interact. The reason behind the cause of autism is yet to be discovered while it only gets harder to narrow down the genetic factors. Individuals with ASD vary from case to case, which is why the spectrum goes from a low-end to a high-end. 

In the article, “Across the Spectrum,” Anna Mikulak recapped Bourgeron’s 2017 keynote at the International Convention of Psychological Science in Vienna. Bourgeron and his interdisciplinary team are researching autism with a number of methods, such as “genetic analyses, brain imaging, mouse models, and even stem-cell applications” (Mikulak) in order to recognize the biological pathways that interact with the phenotypic differences that display ASD. Like I mentioned earlier, ASD varies across individuals; the article states, “Some may have severe cognitive impairment, while others seem to have extraordinarily high IQs; some may have no language, while others show quite advanced verbal ability” (Mikulak). Bourgeron says that autism is not just one autistic disorder, but dozens.

In a recent study, his team studied three siblings’ genes—a child with ASD, another child with Asperger’s syndrome, and another child without any complications. The siblings with a diagnose displayed mutations to genes related with the presynaptic protein neuroligin. Interesting enough, their mother had the same mutation but was protected from any disorders thanks to her second X chromosome. Although their concluding findings did not reveal the gene which causes autism, Bourgeron and his team sure did open up a potential pathway. 

The article, “Maternal obesity, diabetes tied to increased autism risk in kids,” highlights another potential pathway for ASD rose from Dr. Xiaobin Wang, a public health and pediatrics researcher at Johns Hopkins University. Wang and his colleagues reviewed information on over 2,000 mother-child relationships from Boston Medical Center between 1998 and 2014 and came to a realization that “Mothers of children with ASD were likely to be older, obese and to have diabetes diagnosed before or during pregnancy” (Rapaport). Mothers with maternal obesity rose a high percentage of autism risks by 92%. Mothers with diabetes before pregnancy was three times higher the risk, while mothers with both conditions escalated four to five times more.  

Although the actual reason for the increase rates are not clear, Elinor Sullivan (who was not involved in Wang’s study), a biology and neuroscience researcher at the University of Portland stated in the article, “it's possible that increased inflammation, nutrients and hormones linked to diabetes and obesity may be responsible for the added autism risk” (Rapaport). The brain is affected quite easily, as it is malleable, and there’s no doubt that these factors affect the development of the brain. 

The hunt to find the cause of ASD continues each and every day from scientists to researchers in multiple fields. As you can see from mentioned studies, the difficulty arises due to the multiple potential factors in the broad spectrum. Despite this, it is always best to track ASD in early stages in order to decrease bigger problems in the individual’s future. 

Works Cited

Mikulak, Anna. “Across the Spectrum.” Association for Psychological Science, 27 Apr. 2017, 

www.psychologicalscience.org/observer/across-the-spectrum. 

Rapaport, Lisa. “Maternal Obesity, Diabetes Tied to Increased Autism Risk in Kids.” Scientific 

American, www.scientificamerican.com/article/maternal-obesity-diabetes-tied-to-

increased-autism-risk-in-kids/.

Steps towards Stopping Obesity

For the individual, obesity bears consequences on their short and long-term health, in addition to crippling their overall well-being. For the nation, it translates into incredible losses in productivity and profit, as an increasingly overwhelming majority of the population in the United States fall into the category of either overweight or obese. Bordering upon epidemic, the rising weight problem has ignited a barrage of investigating bodies of scientific studies and inquiries, all curious as to how it works and how it can be stopped.

              Using fruit flies (Drosophila melanogaster) to examine feeding pathways in the brain, Jen Beshel and colleagues studied molecular modulators and behaviors of obesity related to it in A Leptin Analog Locally Produced in the Brain Acts via a Conserved Neural Circuit to Modulate Obesity-Linked Behaviors in Drosophila. Notable mechanisms important to the study were those of the circuit involving upd1, domeless receptors, and npf (a nonmammalian neuropeoptide that regulates food odor valuation and stimulates appetite), and the circuit involving leptin, leptin receptors, and npy (a mammalian neuropeptide that is a homolog of npf). Upd1, a leptin analog, is a ligand that bears similar weight-regulating functions. Through the manipulation of neural circuits and knockout of upd1, the study found that upd1 linked to domeless receptors on npf-positive cells affected satiety, and that obesity traits are mediated by the leptin analog in the brain, rather than fat tissues. The neural circuit studied in in fruit flies is functionally conserved with that in mammals; thus, the study offers a good prediction as to what would happen in mammals undergoing similar obesogenic or anorexigenic conditions.

From Obesity alters brain structure and function.

In 2016, a story published in the Guardian went on to investigate what obesity, in turn, does to the brain. Using the results from a study in the University of Cambridge, it highlighted links between obesity and memory loss, raising flags as to whether another consequence of the lifestyle is a potential contribution to dementia. Supporting this notion is Lucy Cheke and her colleagues, who in this study found a clear relationship between BMI (Body Mass Index, a measure of weight relative to height) and memory deficits. This furthers an ever-expanding body of knowledge suggesting obesity may contribute to neurodegenerative diseases including Alzheimer's. Another study cited in the article showed a correlation between healthy, middle-aged adults with raised abdominal fat and lower brain volume, a loss especially prominent in the hippocampus. As this part of the brain is crucial in learning and memory, this finding can help explain the eating behaviors individuals struggling with obesity as well as form the basis of proposed memory damage, a growing concern. Going along with Beshel's focus on neural-hormonal correlates in the brain rather than the fat body, this illustrates the importance of the association between brain function and obesity.

              A year after the story was published, a review by Chelsea Stillman and colleagues (Body-Brain Connections: The Effects of Obesity and Behavioral Interventions on Neurocognitive Aging) provided yet another examination of obesity's effect on neurocognitive function by comparing and contrasting it with the effects physical activity and fitness have on the brain. On a cellular and molecular level, there are several emerging mechanisms that offer to explain the pathways for obesity’s negative impact on brain function and structure – areas the pathways of physical activity and energy restriction positively impact. Decrease in gray matter volume is one such negative structural change. According to the review, the areas of the brain affected by obesity and aging are shown to increase in neurocognitive health with the introduction of physical activity interventions – one such area being the hippocampus, crucial for episodic and relational memory as mentioned in the Guardian article. The review went on to say that though obesity and physical activity do not simply cause inverse effects (the review states their effects of limbic and reward-related brain networks as one example of where they diverge), there is substantial overlap between the mechanisms of the two. The existence of lifestyles that reduce obesity have always been known; however, this notion that such lifestyles can also improve neurocognitive health exponentially raises their benefit and provides key insight into effective solutions or mediators of obesity beyond the externally physical results.

              These are glimpses into only a few studies from the vast body of rising knowledge that continues to shed further light on the health crisis that is gripping the US and spreading to other westernizing countries. As we raise our understanding of its severity, hopefully we come closer towards a means of mediating the consequences of obesity and moving towards a future where it rampage is but a scientific and historical memory.

References

Beshel, J, et al. “A Leptin Analog Locally Produced in the Brain Acts via a Conserved Neural Circuit to Modulate Obesity-Linked Behaviors in Drosophila.” Cell Metabolism., U.S. National Library of Medicine, 10 Jan. 2017

www.ncbi.nlm.nih.gov/pubmed/28076762

Costandi, Mo. “Obesity alters brain structure and function.” The Guardian, 23 November 2016. https://www.theguardian.com/science/neurophilosophy/2016/nov/23/obesity-alters-brain-structure-and-function

Stillman, Chelsea M. et al. “Body–Brain Connections: The Effects of Obesity and Behavioral Interventions on Neurocognitive Aging.” Frontiers in Aging Neuroscience 9 (2017): 115. PMC. Web. 18 Oct. 2018.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5410624/

Diagnosing Autism Early

Diagnosing children at a young age for autism can be hard because you might not be able to tell until anywhere between two to four years old.  On top of that, most families are not able to see a specialist for almost a year.  This can make getting a diagnosis take even longer while they wait to get an appointment with a specialist.  The University of California identified a group of blood metabolites that is able to help detect children with the autism spectrum disorder (ASD).  The testing that is currently being used to detect autism is through an interview with the children instead of doing a brain test.
In the research that Maggie Guy conducted, she focuses on how infants react to different objects on a computer screen. While the infants were looking at the screen, they had an EEG cap on the infants head so they could record the different brain waves throughout the picture process. She did this with infant siblings of the children that are diagnosed with autism.  She also did it with infants that have fragile X syndrome.  By doing this, she was able to see how their brain waves change throughout looking at pictures of their caregiver, a random stranger, and their favorite toy.
The average age in which children get diagnosed with autism is three. Autism may be found early through, what researchers believe to be true, the metabolome. Metabolome is what remains after larger molecules have broken done. Biological markers involved in the process of determine if a child has autism. The biological markers are not able to detect all autism, but it can detect sizable subsets of those who have autism. Those who have autism have a unique concentration of amino acids in their blood compared to an individual who is showing typical development.

https://www.sciencedaily.com/releases/2018/09/180906082016.htm

The Broader Autism Phenotype

According to the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders), Autism Spectrum Disorder is a neurodevelopmental disorder categorized primarily by deficits in social communication and restrictive/repetitive behaviors that cause significant impairment. To be diagnosed with ASD, one must present with symptoms early on in their development. Typically, children are not diagnosed until after the age of 4, and though the DSM argues that a diagnosis can be made starting from 12 months depending on symptom severity, many argue that diagnosis in infants is unreliable using current methods.

In order to study Autism symptoms in younger children, Dr. Maggie Guy conducted a study utilizing EEG (electroencephalogram) imaging. In said study, Dr. Guy studied neural correlates of facial processing, as abnormal processing is a well documented aspect of ASD. Dr. Guy measured ERP’s (event related potentials) in three groups of infants. One group of 21 infants was considered to be high risk for developing Autism due to having an older sibling with the disorder, another group of 15 was considered high risk due to having Fragile X Syndrome, and the final group was considered to be low risk due to no known history of familial or personal disorders. The facial processing task in the study looked at familiar and unfamiliar faces and toys in order to focus on N290, which is a negative ERP component which shows a greater amplitude in reaction to faces versus other things. According to the results, the infants with Fragile X showed the largest response, while the low risk infants were in the middle with the high risk infants due to a sibling with Autism displayed the lowest response. These results suggest that the heightened response of infants with FXS may point towards a higher risk of developing later anxiety disorders, and the smaller response in other high risk infants may be explained by deficits in automatic face processing in those with Autism-like traits.

One may wonder what benefit studying younger siblings of children with Autism may have, as they’re not guaranteed to be diagnosed with Autism. Yet newer research points to the existence of something called the Broader Autism Phenotype within family members of someone with ASD. The Broader Autism Phenotype describes those that have subclinical traits of Autism, meaning they display social difficulties or restrictive behaviors, just not to a severity that qualifies for a diagnosis of ASD. These traits further indicate a genetic link in the disorder. Irregardless of whether or not these children with siblings with Autism themselves develop the disorder, they have a significant risk of struggling with social and emotional difficulties. According to Carolyn Shivers, whose team looked at 69 studies that include siblings that are at least age 5, these children are more likely to have social deficits. They tend to develop anxiety and depression as well, leading Shivers to state that 'typical' siblings alongside their siblings with Autism would benefit from early behavioral interventions.

Works Cited:

Rudy, Lisa Jo. “Parents of Autistic Children May Have Mild Autism Symptoms.” Verywell Health, 18 May 2018, www.verywellhealth.com/what-is-the-broad-autism-phenotype-260048.

“Siblings of Children with Autism Have Social, Emotional Problems.” Spectrum | Autism Research News, 10 Oct. 2018, www.spectrumnews.org/news/siblings-children-autism-social-emotional-problems/.

Guy, Maggie W., et al. “Neural Correlates of Face Processing in Etiologically-Distinct 12-Month-Old Infants at High-Risk of Autism Spectrum Disorder.” Developmental Cognitive Neuroscience, vol. 29, 2018, pp. 61–71., doi:10.1016/j.dcn.2017.03.002.

Diagnostic and Statistical Manual of Mental Disorders: DSM-5. American Psychiatric Association, 2013.

America and Obesity: What is the Cost?

As obesity seems to spread far and wide across America, one cannot help but wonder what the causes of obesity are and how we can start to combat it.  Obesity is now the leading cause of death in the United States as it comes along with heart disease, diabetes, stroke, and certain cancers.  It is a major problem we see that is exploding at what seems like an uncontrollable rate not only in the United States but throughout the world as well.  How can this problem be so far spread out, amongst all types of people throughout the entire world?  This question brings researchers to look a little deeper into the molecular and cellular aspects of obesity: genetics. 

Dr. Jennifer Beshel and her fellow researchers looked into the genetics aspect of obesity and tried to find a connection between the two that could possibly explain this massive increase in obesity since the 1970's.  Drosophila flies were used to look into this genetics aspect of obesity and more specifically, Dr. Beshel looked into the effects of upd1 in the brain.  People with obesity consume more food than is needed and in return store the excess energy they consumed in the form of fat.  One might say, "well why don't they just stop eating?" but this is not as simple as it may seem.  Dr. Beshel discovered with the fly models that this upd1 gene, if knocked down, in fact caused increased food attraction, increased consumption, and overall weight gain.  These behaviors are all seen with obese patients, and could be an explanation for some why this is.  

Obesity is a major problem in the United States and has lead to Diabetes among many obese patients.  It had cost more than $327 billion in 2017 for diabetes expenses, with 90% being for diabetes type 2 caused by obesity according to the New York Times article, "The Toll of America's Obesity," by David S. Ludwig and Kenneth S. Rogoff.  What is more interesting is that the obesity increase has seemed to hit lower income individuals at a higher rate in America.  This means that the economic hardships of diseases and conditions associated with obesity hit the lower income individuals a lot more.  Insulin needed for patients who develop type 2 diabetes from obesity is trending towards over $900, making a diabetes diagnosis among lower income individuals life altering in more ways than one.  But what could cause this higher rate of obesity amongst lower income communities?  The answer lies in the food manufacturing and big businesses that are forcing these people into diets that aren't healthy as grocery stores do not tend to be located in areas that are in reach of these individuals causing food deserts.  These people do not have access to fresh fruits and vegetables, which are also very expensive, and instead are forced into processed foods that are cheap and produced in mass quantities by these money hungry companies that do not care about the health of America, which is what needs to end.

Considering the effects these "big food companies" are having on America's health, this New York Times article suggest the government needs to step in and take action and I think they are absolutely right.  These money making machines will not stop until someone stops them.  Until this is done, we might not see a decline in the this country's leading cause of death for awhile.  I hope the government will soon come to see the impact obesity is having on our country and soon take action to stop it.

Works Cited
Beshel, Jennifer, et al. “A Leptin Analog Locally Produced in the Brain Acts via a Conserved Neural Circuit to 
      Modulate Obesity-Linked Behaviors in Drosophila.” Cell Metabolism, vol. 25, no. 1, 2017, pp. 208–217.,                      doi:10.1016/j.cmet.2016.12.013.
Ludwig, David S., and Kenneth S. Rogoff. “The Toll of America's Obesity.” The New York Times, The New York 

      Times, 9 Aug. 2018, www.nytimes.com/2018/08/09/opinion/cost-diabetes-obesity-budget.html

 

Central Energy Homeostasis: is it in our gut or in our brain?

Energy homeostasis plays a critical role controlling how much we should eat in order to provide sufficient energy to our bodies. Unfortunately, this system does not always work properly in any bodies in which it signals the body to intake more food even after a person just eat five grilled cheese burgers. Consequently, people with this disorder usually have heavy body weight, or obesity. It is widely believed that the neural system is responsible for regulating energy homeostasis according to Bernard and his teams.

Particularly, according to the article 'Melanocortin-4 receptor-regulated energy homeostasis”, the authors points out that the central melanocortin system accounts for body weights and overall metabolic fitness. Within that neural circuit, MC4R neural population is believed to be the diverging signal although the majority of the population remains unknown. What captured my attention in this article is that the authors also found "there is the contribution of MC4Rs in enteroendocrine L-cells of the intestine which is activated by the release of GLP1 and Peptide YY. Therefore, potentially enhancing centrally mediated MC4R signaling can improve the weight loss and the energy expenditure efficacy".

This finding reminds me the review "Gut-feelings: the emerging biology of gut-brain communication", Mayer and his collaborators claim that gut microbiota can liberate various neurotransmitters, such as peptide YY, GLP1 ghrelin, 5-HT, to elicit satiety and emotional responses. Recently, more and more studies find that microbiota in the gut can influence our behavior. If this is true, it would provide a better clinical avenue to treat energy homeostasis disorder because engineered bacteria are much more targeting than medications.

Link for "Melanocortin-4 receptor-regulated energy homeostasis" :https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5244821/

Link for "Gut-feelings: the emerging biology of gut-brain communication" : https://www.ncbi.nlm.nih.gov/pubmed/21750565

Link for " Body Energy Homeostasis" https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2605663/

The Role of Environmental Cues In Motivated Behavior

Addiction is a disease that results from a combination of behavioral, environmental and biological factors. In Dr. Stephan Steidl’s article, “Opioid-induced rewards, locomotion and dopamine activation: A proposed model for control by mesopontine and rostromedial tegmental neurons”, he and his colleagues assessed the relationship between the dopamine rewards system and environmental cues in relation to motivated behavior.

In Dr. Steidl’s experiments, he utilized optogenetic activation in rats, to observe dopamine uptake in response to glutamate and acetylcholine. In each experiment, the rodent subject was given the ability to self-administer the neurotransmitter. For example, in the glutamate studies, rats were given the ability to self-administer glutamate simply by entering one of two chambers: a light (stimulation) chamber or a non-stimulation chamber. When rats entered the light chamber, a blue light would be sent to stimulate the ventral tegmental area (VTA). Seeing as though stimulation could only be disengaged by the rat leaving the chamber, the amount of stimulation each rat received was contingent upon independent volition.

At the conclusion of the experiments, it was found that the rats in the glutamate studies spent less time in the stimulation chamber, but returned more frequently then they had in the acetylcholine experiments. Steidl explains how this finding may be attributed to acetylcholine having a slower dopamine uptake, but a longer dopamine activation period; whereas glutamate may have a faster dopamine uptake, but a shorter dopamine activation period. Thus, the rats in the glutamate experiments were motivated to return to the stimulation chamber more frequently to get the dopamine stimulation. The same may be true for those struggling with opioid addiction.

A recent study conducted by the University of Minnesota Medical School, revealed that dopamine neurons assign extrinsic values to environmental cues. It is through these values, that dopamine is able to motivate our actions and behaviors. Through the use of a Pavlovian model, researchers were able to assess whether a simple cue (such as turning on a light) before the activation of dopamine neurons would motivate behavior. Two types of dopamine neurons were observed: those found within the substantia nigra (SN) and those within the ventral tegmental area (VTA). Researchers discovered that the different responses elicited, were dependent upon the location of the neuron activated (either within the SN or the VTA). Those neurons located within the SN evoked a more rapid and energetic response, to which they described as “get up and go”. Whereas those cues that activated the neurons in the VTA produced a response analogous to “where do I go?”. Seeing as though the activation of VTA neurons has been linked to addiction, the results of the experiment demonstrate that the brain can assign a motivational value to certain environmental cues; ultimately leading to the release of dopamine. In other words, an opioid addict may be motivated to relapse (or increase their drug use) when environmental cues (such as a bar, or a needle) are presented and cause an increase in dopamine release.  

The research outlined in Dr. Steidl’s talk, as well as the research conducted by the University of Minnesota, demonstrate how important the interplay between environmental cues and the dopamine reward system is. However, if proven dysfunctional, these environmental cues can have maladaptive consequences -one of which being sensitization. In the case of opioid addiction, the constant administration (or injection) of opioids, such as heroin, results in behavioral sensitization. Steidl describes behavioral sensitization as the long-term enhancement ability of a stimulus to activate dopamine neurotransmitters and elicit appetitive behaviors (cravings). Dr. Steidl’s research on rats with pre exposure to amphetamines, demonstrates this enhanced dopamine response. In his study, the rats with a history of amphetamine use worked harder to obtain an I.V. drug, and displayed enhanced dopamine reactivity and dependence; all of which are anticipated with sensitization.

Although the future of the opioid epidemic looks bleak, by utilizing the information presented in these two studies, researchers can better understand the process of addiction. Researchers at the University of Minnesota, hope that future studies will help to decipher the difference between healthy motivation and dysfunctional motivation -giving a solution to the drawn-out crisis of addiction.

Works cited:

University of Minnesota Medical School(2018, August 3). How Cues Drive Our Behavior. NeuroscienceNews. Retrieved August 3, 2018 from http://neurosciencenews.com/behavior-cues-dopamine-9654/

Addiction as a Disease. (2017, April 14). Retrieved October 18, 2018, from https://www.centeronaddiction.org/what-addiction/addiction-disease