Autism, Power Outages and the Starving Brain?

There are certain Critical Periods in the development of the human brain and these are the most vulnerable times to any genetic or environmental insult.  Critical Periods (CPs) will be the subject of post appearing shortly.

Another power outage waiting to happen

 Have you wondered why autism secondary to mitochondrial disease (regressive autism) almost always seem to occur before five years of age, and usually much earlier?  Why does it not happen later? Why is it's onset often preceded by a viral infection?

I think you can consider much of this in terms of the brain running out of energy. Humans have evolved to require a huge amount of energy to power their developing brains, a massive 40% of the body’s energy is required by the brain in early childhood.  If your overload a power grid it will end in a blackout.

We know many people with autism have a tendency towards mitochondrial dysfunction, they lack some key enzyme complexes. This means that the process of OXPHOS (Oxidative phosphorylation), by which the body converts glucose to usable energy (ATP), is partially disabled. 

Mitochondrial Disease and Autism

We saw in earlier posts how the supply of glucose and oxygen to the brain can be impaired in autism because there is unstable blood flow.

Unstable Blood Flow in Autistic Brains

It is just like in your house, all your electrical appliances might mean you need a 25KW supply, because you do not use them all at the same time. Just to be on the safe side you might have a 40KW limit. What if the power company will only give you a 20 KW connection? If you turn on the clothes drier, the oven, the air conditioning and some other things all of a sudden you blow the main fuse and perhaps damage the hard drive of your old computer.

So, in the power-hungry brain of a three-year-old, you add a viral infection and all of a sudden you exceed the available power supply from the mitochondria, that have soldered on for 3years with impaired supply of complex 1 and imperfect cerebral blood flow. By the sixth year of life, the peak power requirement from the brain would have fallen to within the safe limit of the mitochondria and its impaired supply of complex 1.  Instead of blowing the fuse, which is easy to reset, you have blown some neuronal circuitry, which is not so easy to repair.    

Too Many Synapses?

We know that it is the synapses in the brain that are the big energy users and we also know that in most autism there are too many synapses. So, in that group of autism there is an even bigger potential energy demand.

Note that in Alzheimer’s type dementia (AD in the above chart) you see a severe loss of synapses/spines as atrophy takes place. This occurs at the same time as a loss of insulin sensitivity occurs (type 3 diabetes). Perhaps the AD brain is also starved of energy, it does seem to respond to ketosis (ketones replacing glucose as the fuel) and it responds to Agmatine (increasing blood flow via eNOS).

We also know that adolescent synaptic pruning is dysfunctional in autism and we even know why. Interestingly by modifying GABA_A function with bumetanide we may indeed allow the brain to eliminate more synapses (a good thing), so possibly an unexpected benefit from Ben Ari’s original idea.

https://www.sciencedaily.com/releases/2016/05/160502161118.htm

"Working with a mouse model we have shown that, at puberty, there is an increase in inhibitory GABA receptors, which are targets for brain chemicals that quiet down nerve cells. We now report that these GABA receptors trigger synaptic pruning at puberty in the mouse hippocampus, a brain area involved in learning and memory." The report, published by eLife, "Synaptic pruning in the female hippocampus is triggered at puberty by extrasynaptic GABAA receptors on dendritic spines."            

These findings may suggest new treatments targeting GABA receptors for "normalizing" synaptic pruning in diseases such as autism and schizophrenia, where synaptic pruning is abnormal. Research has suggested that children with autism may have an over-abundance of synapses in some parts of the brain.

Synaptic pruning in the female hippocampus is triggered at puberty by extrasynaptic GABAA receptors on dendritic spines

Adolescent synaptic pruning is thought to enable optimal cognition because it is disrupted in certain neuropathologies, yet the initiator of this process is unknown. One factor not yet considered is the α4βδ GABA_A receptor (GABAR), an extrasynaptic inhibitory receptor which first emerges on dendritic spines at puberty in female mice. Here we show that α4βδ GABARs trigger adolescent pruning. Spine density of CA1 hippocampal pyramidal cells decreased by half post-pubertally in female wild-type but not α4 KO mice. This effect was associated with decreased expression of kalirin-7 (Kal7), a spine protein which controls actin cytoskeleton remodeling. Kal7 decreased at puberty as a result of reduced NMDAR activation due to α4βδ-mediated inhibition. In the absence of this inhibition, Kal7 expression was unchanged at puberty. In the unpruned condition, spatial re-learning was impaired. These data suggest that pubertal pruning requires α4βδ GABARs. In their absence, pruning is prevented and cognition is not optimal.

Strange Patterns of Growth

Longitudinal studies are when researchers collect the same data over long period of years. Most autism research is just based on a single snapshot in time.

One observation of mine is that some people with strictly defined autism (SDA) are born at the 90+ percentile for height, but then fall back to something like the 20 percentile. Body growth has dramatically slowed. Was this because energy has been diverted to the overgrowing brain? 

A Long Childhood Feeds the Hungry Human Brain
Study of brain scans explains why children grow slowly and childhood lasts so long 

A five-year old’s brain is an energy monster. It uses twice as much glucose (the energy that fuels the brain) as that of a full-grown adult, a new study led by Northwestern University anthropologists has found.

It was previously believed that the brain’s resource burden on the body was largest at birth, when the size of the brain relative to the body is greatest. The researchers found instead that the brain maxes out its glucose use at age 5. At age 4 the brain consumes glucose at a rate comparable to 66 percent of the body’s resting metabolic rate (or more than 40 percent of the body’s total energy expenditure). 

“The mid-childhood peak in brain costs has to do with the fact that synapses, connections in the brain, max out at this age, when we learn so many of the things we need to know to be successful humans,” Kuzawa said.

“At its peak in childhood, the brain burns through two-thirds of the calories the entire body uses at rest, much more than other primate species,” said William Leonard, co-author of the study. “To compensate for these heavy energy demands of our big brains, children grow more slowly and are less physically active during this age range. Our findings strongly suggest that humans evolved to grow slowly during this time in order to free up fuel for our expensive, busy childhood brains.” 

Full paper: -

Metabolic costs and evolutionary implications of human brain development

The high energetic costs of human brain development have been hypothesized to explain distinctive human traits, including exceptionally slow and protracted preadult growth. Although widely assumed to constrain life-history evolution, the metabolic requirements of the growing human brain are unknown. We combined previously collected PET and MRI data to calculate the human brain’s glucose use from birth to adulthood, which we compare with body growth rate. We evaluate the strength of brain–body metabolic trade-offs using the ratios of brain glucose uptake to the body’s resting metabolic rate (RMR) and daily energy requirements (DER) expressed in glucose-gram equivalents (glucose_rmr% and glucose_der%). We find that glucose_rmr% and glucose_der% do not peak at birth (52.5% and 59.8% of RMR, or 35.4% and 38.7% of DER, for males and females, respectively), when relative brain size is largest, but rather in childhood (66.3% and 65.0% of RMR and 43.3% and 43.8% of DER). Body-weight growth (dw/dt) and both glucose_rmr% and glucose_der% are strongly, inversely related: soon after birth, increases in brain glucose demand are accompanied by proportionate decreases in dw/dt. Ages of peak brain glucose demand and lowest dw/dt co-occur and subsequent developmental declines in brain metabolism are matched by proportionate increases in dw/dt until puberty. The finding that human brain glucose demands peak during childhood, and evidence that brain metabolism and body growth rate covary inversely across development, support the hypothesis that the high costs of human brain development require compensatory slowing of body growth rate. 

To quantify the metabolic costs of the human brain, in this study we used a unique, previously collected age series of PET measures of brain glucose uptake spanning birth to adulthood (32), along with existing MRI volumetric data (36), to calculate the brain’s total glucose use from birth to adulthood, which we compare with body growth rate. We estimate total brain glucose uptake by age (inclusive of all oxidative and nonoxidative functions), which we compare with two measures of whole-body energy expenditure: RMR, reflecting maintenance functions only, and daily energy requirements (DER), reflecting the combination of maintenance, activity, and growth. We hypothesized that ages of peak substrate competition (i.e., competition for glucose) between brain and body would be aligned developmentally with the age of slowest childhood body growth, and more generally that growth rate and brain glucose use would covary inversely during development, as is predicted by the concept of a trade-off between brain metabolism and body growth in human life-history evolution. 

Daily glucose use by the brain peaks at 5.2 y of age at 167.0 g/d and 146.1 g/d in males and females, respectively. These values represent 1.88- and 1.82-times the daily glucose use of the brain in adulthood (Fig. 1 A and B and SI Appendix, Fig. S2), despite the fact that body size is more than three-times as large in the adult.

Glucose use of the human brain by age. (A) Grams per day in males. (B) Grams per day in females; dashed horizontal line is adult value (A and B). (C) Glucose_rmr% (solid line) and glucose_der% (dashed line) in males. (D) Glucose_rmr% (solid line) and glucose_der% (dashed line) in females.

The most relevant data is the line highlighted in yellow below, showing brain consumption of glucose peaks at 40% (of total body consumption) around 5 years old and drops to 20% in adulthood.

Our findings agree with past estimates indicating that the brain dominates the body’s metabolism during early life (31). However, our PET-based calculations reveal that the magnitude of brain glucose uptake, both in absolute terms and relative to the body’s metabolic budget, does not peak at birth but rather in childhood, when the glucose used by the brain comprises the equivalent of 66% of the body’s RMR, and roughly 43% of total expenditure. These findings are in broad agreement with past clinical work showing that the body’s mass-specific glucose production rates are highest in childhood, and tightly linked with the brain’s metabolic needs (40). Whereas past attempts to quantify the contribution of the brain to the body’s metabolic expenditure suggested that the brain accounted for a continuously decreasing fraction of RMR as the brain-to-body weight ratio declined with age (25, 31), we find a more complex pattern of substrate trade-off. Both glucose_rmr% and glucose_der% decline in the first half-year as a fast but decelerating pace of body growth established in utero initially outpaces postnatal increases in brain metabolism. Beginning around 6 mo, increases in relative glucose use are matched by proportionate decreases in weight growth, whereas ages of declining brain glucose uptake in late childhood and early adolescence are accompanied by proportionate increases in weight growth. The relationships that we document between age changes in brain glucose demands and body-weight growth rate are particularly striking in males, who maintain these inverse linear trends despite experiencing threefold changes in brain glucose demand and body growth rate between 6 mo and 13 y of age. In females, an earlier onset of pubertal weight gain leads to earlier deviations from similar linear inverse relationships.

                                     

What the researchers then did was to see how the growth rate of the brain is correlated to the growth rate of the body. In effect that what they found was that the growth of the body has to slow down to allow the energy hungry brain to develop.  One the brain has passed its peak energy requirement at about 5 years old, body growth can then gradually accelerate. 

The brain is the red line, the body is blue. The chart on the left is males and the one on the right is females. 

So, we might suspect that in 2 to 4-year olds who seem not to be growing as fast as we might expect, the reason is that their brain is over-growing, a key feature of classic autism.

Glucose_der% and body-weight growth rate. Glucose_der% and weight velocities plotted as SD scores to allow unitless comparison. (A) Glucose_der% (red dots) and dw/dt (blue dots) by age in males. (B) Glucose_der% (red dots) and dw/dt (blue dots) by age in females

Brain Overgrowth in Autism

As has been previous commented on in this blog, Eric Courchesne has pretty much figured out what goes wrong in the growth trajectory of the autistic brain; that was almost 15 years ago.

Brain development in autism: early overgrowth followed by premature arrest of growth.

Courchesne E

Author information

Abstract

Due to the relatively late age of clinical diagnosis of autism, the early brain pathology of children with autism has remained largely unstudied. The increased use of retrospective measures such as head circumference, along with a surge of MRI studies of toddlers with autism, have opened a whole new area of research and discovery. Recent studies have now shown that abnormal brain overgrowth occurs during the first 2 years of life in children with autism. By 2-4 years of age, the most deviant overgrowth is in cerebral, cerebellar, and limbic structures that underlie higher-order cognitive, social, emotional, and language functions. Excessive growth is followed by abnormally slow or arrested growth. Deviant brain growth in autism occurs at the very time when the formation of cerebral circuitry is at its most exuberant and vulnerable stage, and it may signal disruption of this process of circuit formation. The resulting aberrant connectivity and dysfunction may lead to the development of autistic behaviors. To discover the causes, neural substrates, early-warning signs and effective treatments of autism, future research should focus on elucidating the neurobiological defects that underlie brain growth abnormalities in autism that appear during these critical first years of life.

Research from 2017: -

Rapid brain growth in infancy may signal autism

Early brain development in infants at high risk for autism spectrum disorder

Conclusion

A record of children’s height and weight and even head circumference is usually collected by their doctor. In an earlier post I did ask why they bother if nobody is checking this data. If a child falls from the 90^th percentile in height to the 20^th, something clearly is going on.

When I discussed this with a pediatric endocrinologist a few years ago, we then measured bone-age and IGF-1. If you have low IGF-1 and retarded bone age you might opt for some kind of growth hormone therapy.

In what is broadly defined as autism, I think we have some distinctly different things possibly happening: -

Group AMD

Energy conversion in the brain is less efficient than it should be due to a combination of impaired vascular function and impaired mitochondrial enzyme complex production. No symptoms are apparent and developmental milestones are achieved.  As the brain creates more synapses it energy requirement grows until the day when the body has some external insult like a viral infection, and the required power is not available, triggering a “power outage” which appears as the regression into autism. In biological terms there has been death of neurons and demyelination.

Group Sliding Down the Percentiles 

This group looks like a sub-set of classic autism. The brain grows too rapidly in the first two years after birth and this causes the expected slowing of body growth to occur much earlier than in typical children. This manifests itself in the child tumbling down the percentiles for height and weight.

The brain then stops growing prematurely, reducing energy consumption and allowing body growth to accelerate and the child slowly rises back up the height/weight percentiles.

Perhaps all those excessive synapses that were not pruned correctly are wasting glucose and so delay the growth of the rest of the body?   
In the sliding down the growth percentiles group, does this overgrowing brain ever exceed maximum available power? Maybe it just grows too fast and so mal-develops, as suggested by Courchesne, or maybe it grows too fast and cannot fuel correct development?  What happens if you increase maximum available power in this group, in the way some athletes use to enhance their performance/cheat?

All I know for sure is that in Monty, aged 14 with autism, increasing eNOS (endothelial nitric oxide synthase) using agmatine seems to make him achieve much more, with the same daily glucose consumption. I wonder what would happen if Agmatine was given to very young children as soon as it was noted that they were tumbling down the height percentiles?  This is perhaps what the pediatric endocrinologists should be thinking about, rather than just whether or not to administer growth hormones/IGF-1.

If you could identify Group AMD before the “power outage” you might be able to boost maximum power production or reduce body growth slightly and hence avoid the brain ever being starved of energy. That way you would not have most regressive autism.